\"\"\" from __future__ import absolute_import from __future__ import division from __future__","solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) + '_minus') variables.append(positive_err_var) variables.append(negative_err_var) return","Bounds on coefficients Credit: \"Curve Fitting with Linear Programming\", <NAME> and <NAME> \"\"\"","from highest order (0th index) to lowest order (nth index). err_def: An ErrorDefinition","is None: lower_bound = -solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is None:","optimal coefficients for a given polynomial. Overview: Objective: Sum of errors Subject to:","b)) def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH 10 POINTS FROM WILLIAMS') x_vals =","ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver,","solver.Solve() var_to_val = dict() for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value() return var_to_val","import enum import string from ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto()","x_val) # Error terms ex_plus = variables[num_of_coeff + 2 * point_num] ex_minus =","determines order of polynomial, from highest order (0th index) to lowest order (nth","coefficient range.') if solver is None: solver = pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables =","b = optimized_coefficients # print('Optimized m: {}, b: {}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING","variables. \"\"\" num_of_coeff = len(coeff_ranges) variables = [] coeff_names = [] # Add","python3 \"\"\"Curve fitting with linear programming. Minimizes the sum of error for each","coeff_ranges[coeff_num][1] is None: upper_bound = solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound,","PAPER') points = (0,1), (1,3), (2,2), (3,4), (4,5) coeff_ranges = ((None, None), (None,","enumerate(points): # Equivalency constraint constraint = solver.Constraint(point[1], point[1]) # Resultant Coefficient terms for","variables.append(negative_err_var) return variables def _generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \"\"\"Generate objective function for","letter per english alphabet used for coefficient names. TODO(drofp): Figure out naming scheme","((None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH 10","for any order polynomial. Args: points: A tuple of points, represented as tuples","print('STARTING LINEAR DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0,","Sum of errors Subject to: Bounds on coefficients Credit: \"Curve Fitting with Linear","instance is requested by caller. Returns: A Dictionary, the desired coefficients mapped to","the optimal coefficients for a given polynomial. Overview: Objective: Sum of errors Subject","points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \"\"\"Optimize coefficients for any order polynomial. Args: points:","if num_of_coeff == 2: coeff_names.append('m') coeff_names.append('b') else: for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for","pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables( solver, points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver,","get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \"\"\"Optimize coefficients for any order polynomial. Args:","a specific solver instance is requested by caller. Returns: A Dictionary, the desired","err_max: An Integer, specifying the maximum error allowable. solver: a ortools.pywraplp.Solver object, if","point[1]) # Resultant Coefficient terms for coeff_num, coeff in enumerate(variables[:num_of_coeff]): power = num_of_coeff","pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for elm in optimized_coefficients: print('elm: {}'.format(elm)) print(","coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals =","-solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is None: upper_bound = solver.Infinity() else:","_generate_constraints(solver, points, num_of_coeff, variables) solver.Solve() var_to_val = dict() for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()]","list for point_cnt in range(len(points)): positive_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt","variable list. if num_of_coeff == 2: coeff_names.append('m') coeff_names.append('b') else: for letter_cnt in range(num_of_coeff):","= coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add absolute error variables to variable","coefficient names. TODO(drofp): Figure out naming scheme for arbitrary number of variables. \"\"\"","solver: a ortools.pywraplp.Solver object, if a specific solver instance is requested by caller.","= optimized_coefficients # print('Optimized m: {}, b: {}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING LINEAR","err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff, variables) solver.Solve()","getting optimal linear polynomial. Uses 5 points from Swanson's curve fitting paper. \"\"\"","import string from ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION =","None: raise ValueError('Please provide appropriate coefficient range.') if solver is None: solver =","with linear programming. Minimizes the sum of error for each fit point to","5 points from Swanson's curve fitting paper. \"\"\" print('STARTING LINEAR DEMO WITH 5","to variable list. if num_of_coeff == 2: coeff_names.append('m') coeff_names.append('b') else: for letter_cnt in","1) return objective def _generate_constraints(solver, points, num_of_coeff, variables): constraints = [] for point_num,","ex_plus = variables[num_of_coeff + 2 * point_num] ex_minus = variables[num_of_coeff + 2 *","coefficient ranges, respresented as tuples (min, max). Nubmer of elements in list determines","QUADRATIC DEMO WITH 19 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5,","point_cnt in range(len(points)): positive_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1)","POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5,","None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def main(): demo_optimal_quadratic_19points() if __name__ ==","def _generate_constraints(solver, points, num_of_coeff, variables): constraints = [] for point_num, point in enumerate(points):","4.0, 4.5] y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7,","= tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None), (None, None))","print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals","import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver, points,","ErrorDefinition enum, specifying the definition for error. err_max: An Integer, specifying the maximum","SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver, points, coeff_ranges, err_max, error_def): \"\"\"Create coefficient variables. Initial","with Linear Programming\", <NAME> and <NAME> \"\"\" from __future__ import absolute_import from __future__","a given polynomial. Overview: Objective: Sum of errors Subject to: Bounds on coefficients","__future__ import print_function import enum import string from ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum):","3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0, 7.6, 8.5, 9.0, 10.0])","solver=None): \"\"\"Optimize coefficients for any order polynomial. Args: points: A tuple of points,","given polynomial. Overview: Objective: Sum of errors Subject to: Bounds on coefficients Credit:","coeff_ranges is None: raise ValueError('Please provide appropriate coefficient range.') if solver is None:","variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value() return var_to_val def demo_optimal_linear_5points(): \"\"\"Demonstration of getting optimal linear","objective def _generate_constraints(solver, points, num_of_coeff, variables): constraints = [] for point_num, point in","of polynomial, from highest order (0th index) to lowest order (nth index). err_def:","0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7,","points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points,","variable in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return objective def _generate_constraints(solver, points, num_of_coeff, variables): constraints","a ortools.pywraplp.Solver object, if a specific solver instance is requested by caller. Returns:","'_plus') negative_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) + '_minus')","coeff_ranges = ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING","2.7, 5.7, 4.6, 6.0, 6.8, 7.3]) points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None,","var_to_val = dict() for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value() return var_to_val def","None), (None, None)) # solver = pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial(","coeff_num, coeff in enumerate(variables[:num_of_coeff]): power = num_of_coeff - coeff_num - 1 x_val =","variables to variable list for point_cnt in range(len(points)): positive_err_var = solver.NumVar( 0, err_max,","error. err_max: An Integer, specifying the maximum error allowable. solver: a ortools.pywraplp.Solver object,","3.5, 4.0, 4.5] y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0,","= solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) + '_minus') variables.append(positive_err_var) variables.append(negative_err_var)","variables.append(positive_err_var) variables.append(negative_err_var) return variables def _generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \"\"\"Generate objective function","polynomial. Args: points: A tuple of points, represented as tuples (x, y) coeff_ranges:","optimal linear polynomial. Uses 5 points from Swanson's curve fitting paper. \"\"\" print('STARTING","__future__ import absolute_import from __future__ import division from __future__ import print_function import enum","variables, error_def=ErrorDefinition.SUM_ABS_DEV): \"\"\"Generate objective function for given error definition.\"\"\" objective = solver.Objective() for","the definition for error. err_max: An Integer, specifying the maximum error allowable. solver:","variables. Initial version works for up to 26 variable polynomial. One letter per","# Equivalency constraint constraint = solver.Constraint(point[1], point[1]) # Resultant Coefficient terms for coeff_num,","4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0, 7.6, 8.5, 9.0, 10.0]) y_vals =","positive_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) + '_plus') negative_err_var","for each fit point to find the optimal coefficients for a given polynomial.","specifying the maximum error allowable. solver: a ortools.pywraplp.Solver object, if a specific solver","2.5, 3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0, 7.6, 8.5, 9.0,","variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add absolute error variables to variable list for","None: solver = pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables( solver, points, coeff_ranges, err_max=err_max,","from ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION = enum.auto() def","y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7, 4.6, 6.0, 6.8, 7.3]) points = tuple(zip(x_vals, y_vals))","2 * point_num] ex_minus = variables[num_of_coeff + 2 * point_num + 1] constraint.SetCoefficient(ex_plus,","6.0, 6.6, 7.0, 7.6, 8.5, 9.0, 10.0]) y_vals = [1.0, 0.9, 0.7, 1.5,","5.5, 6.0, 6.6, 7.0, 7.6, 8.5, 9.0, 10.0]) y_vals = [1.0, 0.9, 0.7,","1) + '_minus') variables.append(positive_err_var) variables.append(negative_err_var) return variables def _generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV):","variables def _generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \"\"\"Generate objective function for given error","print('STARTING CUBIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0,","# Resultant Coefficient terms for coeff_num, coeff in enumerate(variables[:num_of_coeff]): power = num_of_coeff -","A Dictionary, the desired coefficients mapped to ther values. \"\"\" if coeff_ranges is","# Error terms ex_plus = variables[num_of_coeff + 2 * point_num] ex_minus = variables[num_of_coeff","power constraint.SetCoefficient(coeff, x_val) # Error terms ex_plus = variables[num_of_coeff + 2 * point_num]","# solver = pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for","num_of_coeff, variables) solver.Solve() var_to_val = dict() for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value()","else: for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0] is","+ 1) + '_minus') variables.append(positive_err_var) variables.append(negative_err_var) return variables def _generate_objective_fn( solver, num_of_coeff, variables,","= tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges))","variables): constraints = [] for point_num, point in enumerate(points): # Equivalency constraint constraint","print('elm: {}'.format(elm)) print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m, b = optimized_coefficients","elm in optimized_coefficients: print('elm: {}'.format(elm)) print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m,","2 * point_num + 1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return constraints def","num_of_coeff = len(coeff_ranges) variables = [] coeff_names = [] # Add coefficients to","(None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH 19","19 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0,","for point_cnt in range(len(points)): positive_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt +","definition for error. err_max: An Integer, specifying the maximum error allowable. solver: a","solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) + '_plus') negative_err_var = solver.NumVar(","'e' + str(point_cnt + 1) + '_minus') variables.append(positive_err_var) variables.append(negative_err_var) return variables def _generate_objective_fn(","[] for point_num, point in enumerate(points): # Equivalency constraint constraint = solver.Constraint(point[1], point[1])","coeff.solution_value() return var_to_val def demo_optimal_linear_5points(): \"\"\"Demonstration of getting optimal linear polynomial. Uses 5","1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges =","fitting with linear programming. Minimizes the sum of error for each fit point","Credit: \"Curve Fitting with Linear Programming\", <NAME> and <NAME> \"\"\" from __future__ import","8.5, 9.0, 10.0]) y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0,","tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def","arbitrary number of variables. \"\"\" num_of_coeff = len(coeff_ranges) variables = [] coeff_names =","in optimized_coefficients: print('elm: {}'.format(elm)) print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m, b","None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH","y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] y_vals.extend([1.0,","Dictionary, the desired coefficients mapped to ther values. \"\"\" if coeff_ranges is None:","= -solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is None: upper_bound = solver.Infinity()","if coeff_ranges[coeff_num][1] is None: upper_bound = solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound,","tuple of valid coefficient ranges, respresented as tuples (min, max). Nubmer of elements","= ((None, None), (None, None)) # solver = pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients","return variables def _generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \"\"\"Generate objective function for given","points=points, coeff_ranges=coeff_ranges) for elm in optimized_coefficients: print('elm: {}'.format(elm)) print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients:","ortools.pywraplp.Solver object, if a specific solver instance is requested by caller. Returns: A","points, coeff_ranges, err_max, error_def): \"\"\"Create coefficient variables. Initial version works for up to","= solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add absolute","range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0] is None: lower_bound = -solver.Infinity()","object, if a specific solver instance is requested by caller. Returns: A Dictionary,","provide appropriate coefficient range.') if solver is None: solver = pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING)","import absolute_import from __future__ import division from __future__ import print_function import enum import","2: coeff_names.append('m') coeff_names.append('b') else: for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff):","+ 2 * point_num] ex_minus = variables[num_of_coeff + 2 * point_num + 1]","Swanson's curve fitting paper. \"\"\" print('STARTING LINEAR DEMO WITH 5 POINTS FROM SWANSON","3.2, 2.0, 2.7, 3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None,","None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH 19 POINTS FROM WILLIAMS')","1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] y_vals = [1.0, 0.9, 0.7, 1.5,","solver instance is requested by caller. Returns: A Dictionary, the desired coefficients mapped","absolute_import from __future__ import division from __future__ import print_function import enum import string","division from __future__ import print_function import enum import string from ortools.linear_solver import pywraplp","= (0,1), (1,3), (2,2), (3,4), (4,5) coeff_ranges = ((None, None), (None, None)) #","(None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def main(): demo_optimal_quadratic_19points() if __name__ == '__main__':","enum import string from ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION","num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \"\"\"Generate objective function for given error definition.\"\"\" objective = solver.Objective()","names. TODO(drofp): Figure out naming scheme for arbitrary number of variables. \"\"\" num_of_coeff","= num_of_coeff - coeff_num - 1 x_val = point[0] ** power constraint.SetCoefficient(coeff, x_val)","2.4, 3.2, 2.0, 2.7, 3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7, 4.6, 6.0, 6.8,","up to 26 variable polynomial. One letter per english alphabet used for coefficient","print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m, b = optimized_coefficients # print('Optimized","= pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables( solver, points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff","str(point_cnt + 1) + '_minus') variables.append(positive_err_var) variables.append(negative_err_var) return variables def _generate_objective_fn( solver, num_of_coeff,","= [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5,","def demo_optimal_linear_5points(): \"\"\"Demonstration of getting optimal linear polynomial. Uses 5 points from Swanson's","upper_bound, coeff_names[coeff_num])) # Add absolute error variables to variable list for point_cnt in","= ((None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH","= enum.auto() def _generate_variables(solver, points, coeff_ranges, err_max, error_def): \"\"\"Create coefficient variables. Initial version","coeff_ranges[coeff_num][0] is None: lower_bound = -solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is","Overview: Objective: Sum of errors Subject to: Bounds on coefficients Credit: \"Curve Fitting","1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] y_vals = [1.0, 0.9, 0.7,","1 x_val = point[0] ** power constraint.SetCoefficient(coeff, x_val) # Error terms ex_plus =","points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff,","values. \"\"\" if coeff_ranges is None: raise ValueError('Please provide appropriate coefficient range.') if","optimized_coefficients: print('elm: {}'.format(elm)) print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m, b =","on coefficients Credit: \"Curve Fitting with Linear Programming\", <NAME> and <NAME> \"\"\" from","(0,1), (1,3), (2,2), (3,4), (4,5) coeff_ranges = ((None, None), (None, None)) # solver","coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is None: upper_bound = solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1] variables.append(","= coeff.solution_value() return var_to_val def demo_optimal_linear_5points(): \"\"\"Demonstration of getting optimal linear polynomial. Uses","'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m, b = optimized_coefficients # print('Optimized m:","Minimizes the sum of error for each fit point to find the optimal","err_max, 'e' + str(point_cnt + 1) + '_plus') negative_err_var = solver.NumVar( 0, err_max,","None), (None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def main(): demo_optimal_quadratic_19points() if","= ((None, None), (None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def main():","each fit point to find the optimal coefficients for a given polynomial. Overview:","None: upper_bound = solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) #","Error terms ex_plus = variables[num_of_coeff + 2 * point_num] ex_minus = variables[num_of_coeff +","\"\"\"Demonstration of getting optimal linear polynomial. Uses 5 points from Swanson's curve fitting","coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0] is None: lower_bound = -solver.Infinity() else: lower_bound =","# m, b = optimized_coefficients # print('Optimized m: {}, b: {}'.format(m, b)) def","\"Curve Fitting with Linear Programming\", <NAME> and <NAME> \"\"\" from __future__ import absolute_import","Fitting with Linear Programming\", <NAME> and <NAME> \"\"\" from __future__ import absolute_import from","is None: upper_bound = solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num]))","= ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC","# print('Optimized m: {}, b: {}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH","# Add coefficients to variable list. if num_of_coeff == 2: coeff_names.append('m') coeff_names.append('b') else:","= [] for point_num, point in enumerate(points): # Equivalency constraint constraint = solver.Constraint(point[1],","y_vals)) coeff_ranges = ((None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC","(None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def main(): demo_optimal_quadratic_19points() if __name__","None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH 19 POINTS","# 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for elm in optimized_coefficients: print('elm:","print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals","coeff_ranges: A tuple of valid coefficient ranges, respresented as tuples (min, max). Nubmer","solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add absolute error variables to variable list for point_cnt","None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH 10 POINTS FROM WILLIAMS')","= coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is None: upper_bound = solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1]","objective.SetCoefficient(variable, 1) return objective def _generate_constraints(solver, points, num_of_coeff, variables): constraints = [] for","demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5,","(min, max). Nubmer of elements in list determines order of polynomial, from highest","points from Swanson's curve fitting paper. \"\"\" print('STARTING LINEAR DEMO WITH 5 POINTS","in list determines order of polynomial, from highest order (0th index) to lowest","{}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH 10 POINTS FROM WILLIAMS') x_vals","\"\"\" if coeff_ranges is None: raise ValueError('Please provide appropriate coefficient range.') if solver","var_to_val[coeff.name()] = coeff.solution_value() return var_to_val def demo_optimal_linear_5points(): \"\"\"Demonstration of getting optimal linear polynomial.","2.5, 3.0, 3.5, 4.0, 4.5] y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4,","print('STARTING LINEAR DEMO WITH 5 POINTS FROM SWANSON PAPER') points = (0,1), (1,3),","coeff_ranges = ((None, None), (None, None)) # solver = pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING)","of errors Subject to: Bounds on coefficients Credit: \"Curve Fitting with Linear Programming\",","from __future__ import print_function import enum import string from ortools.linear_solver import pywraplp class","m, b = optimized_coefficients # print('Optimized m: {}, b: {}'.format(m, b)) def demo_optimal_linear_10points():","2.0, 2.4, 3.2, 2.0, 2.7, 3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7, 4.6, 6.0,","by caller. Returns: A Dictionary, the desired coefficients mapped to ther values. \"\"\"","3.0, 3.5, 4.0, 4.5] y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2,","constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return constraints def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \"\"\"Optimize","'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for elm in optimized_coefficients: print('elm: {}'.format(elm))","(1,3), (2,2), (3,4), (4,5) coeff_ranges = ((None, None), (None, None)) # solver =","= point[0] ** power constraint.SetCoefficient(coeff, x_val) # Error terms ex_plus = variables[num_of_coeff +","y_vals)) coeff_ranges = ((None, None), (None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges))","coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals =","(nth index). err_def: An ErrorDefinition enum, specifying the definition for error. err_max: An","_generate_variables( solver, points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver,","function for given error definition.\"\"\" objective = solver.Objective() for variable in variables[num_of_coeff:]: objective.SetCoefficient(variable,","= [] coeff_names = [] # Add coefficients to variable list. if num_of_coeff","requested by caller. Returns: A Dictionary, the desired coefficients mapped to ther values.","err_max=10000, solver=None): \"\"\"Optimize coefficients for any order polynomial. Args: points: A tuple of","import print_function import enum import string from ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV","as tuples (min, max). Nubmer of elements in list determines order of polynomial,","2.7, 3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None,","variables = [] coeff_names = [] # Add coefficients to variable list. if","print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH 19 POINTS FROM WILLIAMS') x_vals","coeff_names[coeff_num])) # Add absolute error variables to variable list for point_cnt in range(len(points)):","demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5,","'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables( solver, points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges)","for coefficient names. TODO(drofp): Figure out naming scheme for arbitrary number of variables.","coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add absolute error variables to variable list","[0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] y_vals = [1.0,","tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING","point_num + 1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return constraints def get_optimal_polynomial( points=None,","error variables to variable list for point_cnt in range(len(points)): positive_err_var = solver.NumVar( 0,","Objective: Sum of errors Subject to: Bounds on coefficients Credit: \"Curve Fitting with","None)) # solver = pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges)","1.9, 2.5, 3.0, 3.5, 4.0, 4.5] y_vals = [1.0, 0.9, 0.7, 1.5, 2.0,","[1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] points = tuple(zip(x_vals,","(2,2), (3,4), (4,5) coeff_ranges = ((None, None), (None, None)) # solver = pywraplp.Solver(","from Swanson's curve fitting paper. \"\"\" print('STARTING LINEAR DEMO WITH 5 POINTS FROM","y_vals)) coeff_ranges = ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points():","def _generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \"\"\"Generate objective function for given error definition.\"\"\"","to find the optimal coefficients for a given polynomial. Overview: Objective: Sum of","for up to 26 variable polynomial. One letter per english alphabet used for","for coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0] is None: lower_bound = -solver.Infinity() else: lower_bound","10.0]) y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5]","1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return constraints def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV,","<NAME> \"\"\" from __future__ import absolute_import from __future__ import division from __future__ import","y) coeff_ranges: A tuple of valid coefficient ranges, respresented as tuples (min, max).","7.6, 8.5, 9.0, 10.0]) y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2,","num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff, variables) solver.Solve() var_to_val = dict() for coeff in","(None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH 10 POINTS FROM","0, err_max, 'e' + str(point_cnt + 1) + '_minus') variables.append(positive_err_var) variables.append(negative_err_var) return variables","(3,4), (4,5) coeff_ranges = ((None, None), (None, None)) # solver = pywraplp.Solver( #","'e' + str(point_cnt + 1) + '_plus') negative_err_var = solver.NumVar( 0, err_max, 'e'","letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0] is None: lower_bound","4.5] y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5]","constraint = solver.Constraint(point[1], point[1]) # Resultant Coefficient terms for coeff_num, coeff in enumerate(variables[:num_of_coeff]):","given error definition.\"\"\" objective = solver.Objective() for variable in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return","def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0,","point[0] ** power constraint.SetCoefficient(coeff, x_val) # Error terms ex_plus = variables[num_of_coeff + 2","def _generate_variables(solver, points, coeff_ranges, err_max, error_def): \"\"\"Create coefficient variables. Initial version works for","_generate_variables(solver, points, coeff_ranges, err_max, error_def): \"\"\"Create coefficient variables. Initial version works for up","solver, points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points,","version works for up to 26 variable polynomial. One letter per english alphabet","error_def): \"\"\"Create coefficient variables. Initial version works for up to 26 variable polynomial.","if a specific solver instance is requested by caller. Returns: A Dictionary, the","Subject to: Bounds on coefficients Credit: \"Curve Fitting with Linear Programming\", <NAME> and","== 2: coeff_names.append('m') coeff_names.append('b') else: for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in","points, represented as tuples (x, y) coeff_ranges: A tuple of valid coefficient ranges,","((None, None), (None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def main(): demo_optimal_quadratic_19points()","WITH 19 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5,","out naming scheme for arbitrary number of variables. \"\"\" num_of_coeff = len(coeff_ranges) variables","3.6, 2.7, 5.7, 4.6, 6.0, 6.8, 7.3]) points = tuple(zip(x_vals, y_vals)) coeff_ranges =","7.3]) points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None))","any order polynomial. Args: points: A tuple of points, represented as tuples (x,","for coeff_num, coeff in enumerate(variables[:num_of_coeff]): power = num_of_coeff - coeff_num - 1 x_val","is None: raise ValueError('Please provide appropriate coefficient range.') if solver is None: solver","y_vals)) coeff_ranges = ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points():","specific solver instance is requested by caller. Returns: A Dictionary, the desired coefficients","WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5]","class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver, points, coeff_ranges, err_max,","= pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for elm in","point_num, point in enumerate(points): # Equivalency constraint constraint = solver.Constraint(point[1], point[1]) # Resultant","polynomial. One letter per english alphabet used for coefficient names. TODO(drofp): Figure out","1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0,","9.0, 10.0]) y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7,","Integer, specifying the maximum error allowable. solver: a ortools.pywraplp.Solver object, if a specific","4.6, 6.0, 6.8, 7.3]) points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None,","elements in list determines order of polynomial, from highest order (0th index) to","represented as tuples (x, y) coeff_ranges: A tuple of valid coefficient ranges, respresented","index). err_def: An ErrorDefinition enum, specifying the definition for error. err_max: An Integer,","__future__ import division from __future__ import print_function import enum import string from ortools.linear_solver","err_def: An ErrorDefinition enum, specifying the definition for error. err_max: An Integer, specifying","Programming\", <NAME> and <NAME> \"\"\" from __future__ import absolute_import from __future__ import division","(4,5) coeff_ranges = ((None, None), (None, None)) # solver = pywraplp.Solver( # 'polynomial_solver',","= ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC","in variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value() return var_to_val def demo_optimal_linear_5points(): \"\"\"Demonstration of getting optimal","coeff_ranges = ((None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO","= [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] y_vals.extend([1.0, 4.0,","+ '_plus') negative_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) +","1) + '_plus') negative_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1)","coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \"\"\"Optimize coefficients for any order polynomial. Args: points: A","4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0, 7.6, 8.5, 9.0, 10.0]) y_vals = [1.0,","1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7, 4.6,","enumerate(variables[:num_of_coeff]): power = num_of_coeff - coeff_num - 1 x_val = point[0] ** power","objective function for given error definition.\"\"\" objective = solver.Objective() for variable in variables[num_of_coeff:]:","error for each fit point to find the optimal coefficients for a given","solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add absolute error","(None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH 19 POINTS FROM","An Integer, specifying the maximum error allowable. solver: a ortools.pywraplp.Solver object, if a","= len(coeff_ranges) variables = [] coeff_names = [] # Add coefficients to variable","enum.auto() def _generate_variables(solver, points, coeff_ranges, err_max, error_def): \"\"\"Create coefficient variables. Initial version works","SWANSON PAPER') points = (0,1), (1,3), (2,2), (3,4), (4,5) coeff_ranges = ((None, None),","variables[num_of_coeff + 2 * point_num + 1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return","to ther values. \"\"\" if coeff_ranges is None: raise ValueError('Please provide appropriate coefficient","points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def","for given error definition.\"\"\" objective = solver.Objective() for variable in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1)","num_of_coeff, variables): constraints = [] for point_num, point in enumerate(points): # Equivalency constraint","variable list for point_cnt in range(len(points)): positive_err_var = solver.NumVar( 0, err_max, 'e' +","the sum of error for each fit point to find the optimal coefficients","6.8, 7.3]) points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None,","solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \"\"\"Generate objective function for given error definition.\"\"\" objective =","1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0, 7.6,","lower_bound = -solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is None: upper_bound =","A tuple of points, represented as tuples (x, y) coeff_ranges: A tuple of","[] coeff_names = [] # Add coefficients to variable list. if num_of_coeff ==","{}'.format(optimized_coefficients)) # m, b = optimized_coefficients # print('Optimized m: {}, b: {}'.format(m, b))","str(point_cnt + 1) + '_plus') negative_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt","DEMO WITH 19 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9,","error definition.\"\"\" objective = solver.Objective() for variable in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return objective","x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0,","coeff_ranges, err_max, error_def): \"\"\"Create coefficient variables. Initial version works for up to 26","max). Nubmer of elements in list determines order of polynomial, from highest order","per english alphabet used for coefficient names. TODO(drofp): Figure out naming scheme for","points, num_of_coeff, variables) solver.Solve() var_to_val = dict() for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()] =","\"\"\"Optimize coefficients for any order polynomial. Args: points: A tuple of points, represented","the desired coefficients mapped to ther values. \"\"\" if coeff_ranges is None: raise","return objective def _generate_constraints(solver, points, num_of_coeff, variables): constraints = [] for point_num, point","Figure out naming scheme for arbitrary number of variables. \"\"\" num_of_coeff = len(coeff_ranges)","error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff, variables) solver.Solve() var_to_val","# Add absolute error variables to variable list for point_cnt in range(len(points)): positive_err_var","+ 2 * point_num + 1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return constraints","0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] y_vals = [1.0, 0.9,","- 1 x_val = point[0] ** power constraint.SetCoefficient(coeff, x_val) # Error terms ex_plus","ValueError('Please provide appropriate coefficient range.') if solver is None: solver = pywraplp.Solver( 'polynomial_solver',","for elm in optimized_coefficients: print('elm: {}'.format(elm)) print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) #","3.2, 2.0, 2.7, 3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7, 4.6, 6.0, 6.8, 7.3])","point in enumerate(points): # Equivalency constraint constraint = solver.Constraint(point[1], point[1]) # Resultant Coefficient","order polynomial. Args: points: A tuple of points, represented as tuples (x, y)","DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9,","= len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff, variables) solver.Solve() var_to_val = dict()","5.7, 4.6, 6.0, 6.8, 7.3]) points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None),","naming scheme for arbitrary number of variables. \"\"\" num_of_coeff = len(coeff_ranges) variables =","= solver.Constraint(point[1], point[1]) # Resultant Coefficient terms for coeff_num, coeff in enumerate(variables[:num_of_coeff]): power","dict() for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value() return var_to_val def demo_optimal_linear_5points(): \"\"\"Demonstration","to 26 variable polynomial. One letter per english alphabet used for coefficient names.","of points, represented as tuples (x, y) coeff_ranges: A tuple of valid coefficient","+ '_minus') variables.append(positive_err_var) variables.append(negative_err_var) return variables def _generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \"\"\"Generate","WITH 5 POINTS FROM SWANSON PAPER') points = (0,1), (1,3), (2,2), (3,4), (4,5)","terms ex_plus = variables[num_of_coeff + 2 * point_num] ex_minus = variables[num_of_coeff + 2","of valid coefficient ranges, respresented as tuples (min, max). Nubmer of elements in","num_of_coeff == 2: coeff_names.append('m') coeff_names.append('b') else: for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num","[0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0,","coefficients Credit: \"Curve Fitting with Linear Programming\", <NAME> and <NAME> \"\"\" from __future__","order (0th index) to lowest order (nth index). err_def: An ErrorDefinition enum, specifying","polynomial. Overview: Objective: Sum of errors Subject to: Bounds on coefficients Credit: \"Curve","in range(num_of_coeff): if coeff_ranges[coeff_num][0] is None: lower_bound = -solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0]","for error. err_max: An Integer, specifying the maximum error allowable. solver: a ortools.pywraplp.Solver","Add absolute error variables to variable list for point_cnt in range(len(points)): positive_err_var =","<NAME> and <NAME> \"\"\" from __future__ import absolute_import from __future__ import division from","linear polynomial. Uses 5 points from Swanson's curve fitting paper. \"\"\" print('STARTING LINEAR","coefficients for any order polynomial. Args: points: A tuple of points, represented as","coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff, variables)","of variables. \"\"\" num_of_coeff = len(coeff_ranges) variables = [] coeff_names = [] #","An ErrorDefinition enum, specifying the definition for error. err_max: An Integer, specifying the","highest order (0th index) to lowest order (nth index). err_def: An ErrorDefinition enum,","(None, None)) # solver = pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points,","coefficient variables. Initial version works for up to 26 variable polynomial. One letter","None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH 10 POINTS","in enumerate(variables[:num_of_coeff]): power = num_of_coeff - coeff_num - 1 x_val = point[0] **","solver.Objective() for variable in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return objective def _generate_constraints(solver, points, num_of_coeff,","print('STARTING QUADRATIC DEMO WITH 19 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0,","print_function import enum import string from ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV =","= solver.Objective() for variable in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return objective def _generate_constraints(solver, points,","0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges","to: Bounds on coefficients Credit: \"Curve Fitting with Linear Programming\", <NAME> and <NAME>","points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None), (None,","type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m, b = optimized_coefficients # print('Optimized m: {}, b:","#!/usr/bin/env python3 \"\"\"Curve fitting with linear programming. Minimizes the sum of error for","** power constraint.SetCoefficient(coeff, x_val) # Error terms ex_plus = variables[num_of_coeff + 2 *","coeff_names = [] # Add coefficients to variable list. if num_of_coeff == 2:","print('STARTING QUADRATIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0,","if coeff_ranges[coeff_num][0] is None: lower_bound = -solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1]","Linear Programming\", <NAME> and <NAME> \"\"\" from __future__ import absolute_import from __future__ import","2.0, 2.7, 3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None))","= [] # Add coefficients to variable list. if num_of_coeff == 2: coeff_names.append('m')","len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff, variables) solver.Solve() var_to_val = dict() for","order of polynomial, from highest order (0th index) to lowest order (nth index).","m: {}, b: {}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH 10 POINTS","points, num_of_coeff, variables): constraints = [] for point_num, point in enumerate(points): # Equivalency","demo_optimal_linear_5points(): \"\"\"Demonstration of getting optimal linear polynomial. Uses 5 points from Swanson's curve","2.7, 3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7, 4.6, 6.0, 6.8, 7.3]) points =","variables) solver.Solve() var_to_val = dict() for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value() return","WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5,","_generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff, variables) solver.Solve() var_to_val = dict() for coeff","range(num_of_coeff): if coeff_ranges[coeff_num][0] is None: lower_bound = -solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0] if","(None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH 10 POINTS FROM","+ str(point_cnt + 1) + '_plus') negative_err_var = solver.NumVar( 0, err_max, 'e' +","1.9, 2.5, 3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0, 7.6, 8.5,","None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def main(): demo_optimal_quadratic_19points() if __name__ == '__main__': main()","(0th index) to lowest order (nth index). err_def: An ErrorDefinition enum, specifying the","else: upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add absolute error variables","= [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] points =","2.0, 2.7, 3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None),","number of variables. \"\"\" num_of_coeff = len(coeff_ranges) variables = [] coeff_names = []","fit point to find the optimal coefficients for a given polynomial. Overview: Objective:","_generate_constraints(solver, points, num_of_coeff, variables): constraints = [] for point_num, point in enumerate(points): #","LINEAR DEMO WITH 5 POINTS FROM SWANSON PAPER') points = (0,1), (1,3), (2,2),","(None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH 10","tuple of points, represented as tuples (x, y) coeff_ranges: A tuple of valid","for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value() return var_to_val def demo_optimal_linear_5points(): \"\"\"Demonstration of","solver = pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for elm","2.0, 2.7, 3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7, 4.6, 6.0, 6.8, 7.3]) points","CUBIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5,","0, err_max, 'e' + str(point_cnt + 1) + '_plus') negative_err_var = solver.NumVar( 0,","for a given polynomial. Overview: Objective: Sum of errors Subject to: Bounds on","coeff_ranges = ((None, None), (None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def","constraint.SetCoefficient(coeff, x_val) # Error terms ex_plus = variables[num_of_coeff + 2 * point_num] ex_minus","variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return objective def _generate_constraints(solver, points, num_of_coeff, variables): constraints = []","get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for elm in optimized_coefficients: print('elm: {}'.format(elm)) print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients)))","for variable in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return objective def _generate_constraints(solver, points, num_of_coeff, variables):","power = num_of_coeff - coeff_num - 1 x_val = point[0] ** power constraint.SetCoefficient(coeff,","err_max, 'e' + str(point_cnt + 1) + '_minus') variables.append(positive_err_var) variables.append(negative_err_var) return variables def","Resultant Coefficient terms for coeff_num, coeff in enumerate(variables[:num_of_coeff]): power = num_of_coeff - coeff_num","= solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) + '_plus') negative_err_var =","order (nth index). err_def: An ErrorDefinition enum, specifying the definition for error. err_max:","demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5,","import division from __future__ import print_function import enum import string from ortools.linear_solver import","Returns: A Dictionary, the desired coefficients mapped to ther values. \"\"\" if coeff_ranges","appropriate coefficient range.') if solver is None: solver = pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables","((None, None), (None, None)) # solver = pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients =","constraints.append(constraint) return constraints def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \"\"\"Optimize coefficients for","from __future__ import absolute_import from __future__ import division from __future__ import print_function import","for point_num, point in enumerate(points): # Equivalency constraint constraint = solver.Constraint(point[1], point[1]) #","point to find the optimal coefficients for a given polynomial. Overview: Objective: Sum","solver.Constraint(point[1], point[1]) # Resultant Coefficient terms for coeff_num, coeff in enumerate(variables[:num_of_coeff]): power =","coeff_num - 1 x_val = point[0] ** power constraint.SetCoefficient(coeff, x_val) # Error terms","index) to lowest order (nth index). err_def: An ErrorDefinition enum, specifying the definition","error_def=ErrorDefinition.SUM_ABS_DEV): \"\"\"Generate objective function for given error definition.\"\"\" objective = solver.Objective() for variable","constraint constraint = solver.Constraint(point[1], point[1]) # Resultant Coefficient terms for coeff_num, coeff in","errors Subject to: Bounds on coefficients Credit: \"Curve Fitting with Linear Programming\", <NAME>","tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points,","is requested by caller. Returns: A Dictionary, the desired coefficients mapped to ther","of getting optimal linear polynomial. Uses 5 points from Swanson's curve fitting paper.","= enum.auto() SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver, points, coeff_ranges, err_max, error_def): \"\"\"Create coefficient","7.0, 7.6, 8.5, 9.0, 10.0]) y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4,","used for coefficient names. TODO(drofp): Figure out naming scheme for arbitrary number of","'_minus') variables.append(positive_err_var) variables.append(negative_err_var) return variables def _generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \"\"\"Generate objective","((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO","curve fitting paper. \"\"\" print('STARTING LINEAR DEMO WITH 5 POINTS FROM SWANSON PAPER')","2.0, 2.4, 3.2, 2.0, 2.7, 3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None,","valid coefficient ranges, respresented as tuples (min, max). Nubmer of elements in list","point_num] ex_minus = variables[num_of_coeff + 2 * point_num + 1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus,","err_max, error_def): \"\"\"Create coefficient variables. Initial version works for up to 26 variable","DEMO WITH 5 POINTS FROM SWANSON PAPER') points = (0,1), (1,3), (2,2), (3,4),","fitting paper. \"\"\" print('STARTING LINEAR DEMO WITH 5 POINTS FROM SWANSON PAPER') points","def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \"\"\"Optimize coefficients for any order polynomial.","coefficients mapped to ther values. \"\"\" if coeff_ranges is None: raise ValueError('Please provide","string from ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION = enum.auto()","coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH 19 POINTS FROM WILLIAMS') x_vals =","upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add absolute error variables to","ranges, respresented as tuples (min, max). Nubmer of elements in list determines order","lowest order (nth index). err_def: An ErrorDefinition enum, specifying the definition for error.","tuples (min, max). Nubmer of elements in list determines order of polynomial, from","english alphabet used for coefficient names. TODO(drofp): Figure out naming scheme for arbitrary","= _generate_variables( solver, points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables)","POINTS FROM SWANSON PAPER') points = (0,1), (1,3), (2,2), (3,4), (4,5) coeff_ranges =","in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return objective def _generate_constraints(solver, points, num_of_coeff, variables): constraints =","maximum error allowable. solver: a ortools.pywraplp.Solver object, if a specific solver instance is","constraints def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \"\"\"Optimize coefficients for any order","x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0, 7.6, 8.5, 9.0, 10.0]) y_vals = [1.0, 0.9,","polynomial, from highest order (0th index) to lowest order (nth index). err_def: An","in range(len(points)): positive_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) +","print('Optimized m: {}, b: {}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH 10","ther values. \"\"\" if coeff_ranges is None: raise ValueError('Please provide appropriate coefficient range.')","[] # Add coefficients to variable list. if num_of_coeff == 2: coeff_names.append('m') coeff_names.append('b')","pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables( solver, points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff =","y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] points","mapped to ther values. \"\"\" if coeff_ranges is None: raise ValueError('Please provide appropriate","points = (0,1), (1,3), (2,2), (3,4), (4,5) coeff_ranges = ((None, None), (None, None))","num_of_coeff - coeff_num - 1 x_val = point[0] ** power constraint.SetCoefficient(coeff, x_val) #","coeff_names.append('m') coeff_names.append('b') else: for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff): if","3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7, 4.6, 6.0, 6.8, 7.3]) points = tuple(zip(x_vals,","for arbitrary number of variables. \"\"\" num_of_coeff = len(coeff_ranges) variables = [] coeff_names","4.0, 3.6, 2.7, 5.7, 4.6, 6.0, 6.8, 7.3]) points = tuple(zip(x_vals, y_vals)) coeff_ranges","- coeff_num - 1 x_val = point[0] ** power constraint.SetCoefficient(coeff, x_val) # Error","None: lower_bound = -solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is None: upper_bound","\"\"\" print('STARTING LINEAR DEMO WITH 5 POINTS FROM SWANSON PAPER') points = (0,1),","alphabet used for coefficient names. TODO(drofp): Figure out naming scheme for arbitrary number","\"\"\"Generate objective function for given error definition.\"\"\" objective = solver.Objective() for variable in","LINEAR DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5,","def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0,","variables = _generate_variables( solver, points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff,","((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO","ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver, points, coeff_ranges, err_max, error_def):","10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0,","def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0,","list determines order of polynomial, from highest order (0th index) to lowest order","enum, specifying the definition for error. err_max: An Integer, specifying the maximum error","0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] points = tuple(zip(x_vals, y_vals))","= [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] y_vals =","3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0, 7.6, 8.5, 9.0, 10.0]) y_vals","to lowest order (nth index). err_def: An ErrorDefinition enum, specifying the definition for","\"\"\" from __future__ import absolute_import from __future__ import division from __future__ import print_function","points: A tuple of points, represented as tuples (x, y) coeff_ranges: A tuple","= tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points():","raise ValueError('Please provide appropriate coefficient range.') if solver is None: solver = pywraplp.Solver(","objective = solver.Objective() for variable in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return objective def _generate_constraints(solver,","None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH 10 POINTS FROM WILLIAMS')","= dict() for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value() return var_to_val def demo_optimal_linear_5points():","1) constraints.append(constraint) return constraints def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \"\"\"Optimize coefficients","{}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m, b = optimized_coefficients # print('Optimized m: {},","of elements in list determines order of polynomial, from highest order (0th index)","variable polynomial. One letter per english alphabet used for coefficient names. TODO(drofp): Figure","FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0,","3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None))","+ 1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return constraints def get_optimal_polynomial( points=None, coeff_ranges=None,","x_val = point[0] ** power constraint.SetCoefficient(coeff, x_val) # Error terms ex_plus = variables[num_of_coeff","constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return constraints def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000,","x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] y_vals","find the optimal coefficients for a given polynomial. Overview: Objective: Sum of errors","terms for coeff_num, coeff in enumerate(variables[:num_of_coeff]): power = num_of_coeff - coeff_num - 1","SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver, points, coeff_ranges, err_max, error_def): \"\"\"Create","lower_bound = coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is None: upper_bound = solver.Infinity() else: upper_bound =","coeff_ranges = ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING","{}, b: {}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH 10 POINTS FROM","coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0] is None: lower_bound = -solver.Infinity() else:","caller. Returns: A Dictionary, the desired coefficients mapped to ther values. \"\"\" if","Nubmer of elements in list determines order of polynomial, from highest order (0th","specifying the definition for error. err_max: An Integer, specifying the maximum error allowable.","0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7,","coefficients for a given polynomial. Overview: Objective: Sum of errors Subject to: Bounds","to variable list for point_cnt in range(len(points)): positive_err_var = solver.NumVar( 0, err_max, 'e'","solver = pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables( solver, points, coeff_ranges, err_max=err_max, error_def=error_def)","from __future__ import division from __future__ import print_function import enum import string from","6.0, 6.8, 7.3]) points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None),","absolute error variables to variable list for point_cnt in range(len(points)): positive_err_var = solver.NumVar(","constraints = [] for point_num, point in enumerate(points): # Equivalency constraint constraint =","var_to_val def demo_optimal_linear_5points(): \"\"\"Demonstration of getting optimal linear polynomial. Uses 5 points from","\"\"\" num_of_coeff = len(coeff_ranges) variables = [] coeff_names = [] # Add coefficients","6.6, 7.0, 7.6, 8.5, 9.0, 10.0]) y_vals = [1.0, 0.9, 0.7, 1.5, 2.0,","the maximum error allowable. solver: a ortools.pywraplp.Solver object, if a specific solver instance","None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH 10 POINTS","respresented as tuples (min, max). Nubmer of elements in list determines order of","0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6,","b: {}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH 10 POINTS FROM WILLIAMS')","optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for elm in optimized_coefficients: print('elm: {}'.format(elm)) print( 'type(optimized_coefficients):","pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver, points, coeff_ranges,","range(len(points)): positive_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) + '_plus')","return var_to_val def demo_optimal_linear_5points(): \"\"\"Demonstration of getting optimal linear polynomial. Uses 5 points","error allowable. solver: a ortools.pywraplp.Solver object, if a specific solver instance is requested","pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for elm in optimized_coefficients:","if solver is None: solver = pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables( solver,","sum of error for each fit point to find the optimal coefficients for","variables[num_of_coeff + 2 * point_num] ex_minus = variables[num_of_coeff + 2 * point_num +","* point_num] ex_minus = variables[num_of_coeff + 2 * point_num + 1] constraint.SetCoefficient(ex_plus, -1)","3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None),","def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH 19 POINTS FROM WILLIAMS') x_vals = [0.0,","scheme for arbitrary number of variables. \"\"\" num_of_coeff = len(coeff_ranges) variables = []","linear programming. Minimizes the sum of error for each fit point to find","ex_minus = variables[num_of_coeff + 2 * point_num + 1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1)","negative_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) + '_minus') variables.append(positive_err_var)","{}'.format(elm)) print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m, b = optimized_coefficients #","optimized_coefficients # print('Optimized m: {}, b: {}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO","demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH 19 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5,","Initial version works for up to 26 variable polynomial. One letter per english","-1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return constraints def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None):","Add coefficients to variable list. if num_of_coeff == 2: coeff_names.append('m') coeff_names.append('b') else: for","coeff in enumerate(variables[:num_of_coeff]): power = num_of_coeff - coeff_num - 1 x_val = point[0]","Args: points: A tuple of points, represented as tuples (x, y) coeff_ranges: A","as tuples (x, y) coeff_ranges: A tuple of valid coefficient ranges, respresented as","num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff, variables) solver.Solve() var_to_val =","list. if num_of_coeff == 2: coeff_names.append('m') coeff_names.append('b') else: for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt])","Coefficient terms for coeff_num, coeff in enumerate(variables[:num_of_coeff]): power = num_of_coeff - coeff_num -","3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges))","paper. \"\"\" print('STARTING LINEAR DEMO WITH 5 POINTS FROM SWANSON PAPER') points =","return constraints def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \"\"\"Optimize coefficients for any","2.7, 3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None)) print(get_optimal_polynomial(points=points,","of error for each fit point to find the optimal coefficients for a","= variables[num_of_coeff + 2 * point_num + 1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint)","coeff_names.append('b') else: for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0]","desired coefficients mapped to ther values. \"\"\" if coeff_ranges is None: raise ValueError('Please","Uses 5 points from Swanson's curve fitting paper. \"\"\" print('STARTING LINEAR DEMO WITH","programming. Minimizes the sum of error for each fit point to find the","26 variable polynomial. One letter per english alphabet used for coefficient names. TODO(drofp):","variables) _generate_constraints(solver, points, num_of_coeff, variables) solver.Solve() var_to_val = dict() for coeff in variables[:num_of_coeff]:","(x, y) coeff_ranges: A tuple of valid coefficient ranges, respresented as tuples (min,","in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0] is None: lower_bound =","for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0] is None:","upper_bound = solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add","_generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \"\"\"Generate objective function for given error definition.\"\"\" objective","\"\"\"Curve fitting with linear programming. Minimizes the sum of error for each fit","None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH","One letter per english alphabet used for coefficient names. TODO(drofp): Figure out naming","allowable. solver: a ortools.pywraplp.Solver object, if a specific solver instance is requested by","is None: solver = pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables( solver, points, coeff_ranges,"],"string":"[\n \"enum.auto() SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver, points, coeff_ranges, err_max, error_def): \\\"\\\"\\\"Create coefficient variables.\",\n \"tuples (x, y) coeff_ranges: A tuple of valid coefficient ranges, respresented as tuples\",\n \"definition.\\\"\\\"\\\" objective = solver.Objective() for variable in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return objective def\",\n \"\\\"\\\"\\\"Create coefficient variables. Initial version works for up to 26 variable polynomial. One\",\n \"in enumerate(points): # Equivalency constraint constraint = solver.Constraint(point[1], point[1]) # Resultant Coefficient terms\",\n \"= variables[num_of_coeff + 2 * point_num] ex_minus = variables[num_of_coeff + 2 * point_num\",\n \"polynomial. Uses 5 points from Swanson's curve fitting paper. \\\"\\\"\\\" print('STARTING LINEAR DEMO\",\n \"QUADRATIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5,\",\n \"[1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] y_vals.extend([1.0, 4.0, 3.6,\",\n \"len(coeff_ranges) variables = [] coeff_names = [] # Add coefficients to variable list.\",\n \"else: lower_bound = coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is None: upper_bound = solver.Infinity() else: upper_bound\",\n \"5 POINTS FROM SWANSON PAPER') points = (0,1), (1,3), (2,2), (3,4), (4,5) coeff_ranges\",\n \"Equivalency constraint constraint = solver.Constraint(point[1], point[1]) # Resultant Coefficient terms for coeff_num, coeff\",\n \"error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \\\"\\\"\\\"Optimize coefficients for any order polynomial. Args: points: A tuple\",\n \"print('optimized_coefficients: {}'.format(optimized_coefficients)) # m, b = optimized_coefficients # print('Optimized m: {}, b: {}'.format(m,\",\n \"+ str(point_cnt + 1) + '_minus') variables.append(positive_err_var) variables.append(negative_err_var) return variables def _generate_objective_fn( solver,\",\n \"= get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for elm in optimized_coefficients: print('elm: {}'.format(elm)) print( 'type(optimized_coefficients): {}'.format(\",\n \"+ 1) + '_plus') negative_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt +\",\n \"solver is None: solver = pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables( solver, points,\",\n \"if coeff_ranges is None: raise ValueError('Please provide appropriate coefficient range.') if solver is\",\n \"coeff_ranges=coeff_ranges) for elm in optimized_coefficients: print('elm: {}'.format(elm)) print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients))\",\n \"TODO(drofp): Figure out naming scheme for arbitrary number of variables. \\\"\\\"\\\" num_of_coeff =\",\n \"range.') if solver is None: solver = pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables(\",\n \"coefficients to variable list. if num_of_coeff == 2: coeff_names.append('m') coeff_names.append('b') else: for letter_cnt\",\n \"coeff in variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value() return var_to_val def demo_optimal_linear_5points(): \\\"\\\"\\\"Demonstration of getting\",\n \"works for up to 26 variable polynomial. One letter per english alphabet used\",\n \"* point_num + 1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return constraints def get_optimal_polynomial(\",\n \"A tuple of valid coefficient ranges, respresented as tuples (min, max). Nubmer of\",\n \"FROM SWANSON PAPER') points = (0,1), (1,3), (2,2), (3,4), (4,5) coeff_ranges = ((None,\",\n \"2.4, 3.2, 2.0, 2.7, 3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None),\",\n \"and <NAME> \\\"\\\"\\\" from __future__ import absolute_import from __future__ import division from __future__\",\n \"solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) + '_minus') variables.append(positive_err_var) variables.append(negative_err_var) return\",\n \"Bounds on coefficients Credit: \\\"Curve Fitting with Linear Programming\\\", <NAME> and <NAME> \\\"\\\"\\\"\",\n \"from highest order (0th index) to lowest order (nth index). err_def: An ErrorDefinition\",\n \"is None: lower_bound = -solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is None:\",\n \"optimal coefficients for a given polynomial. Overview: Objective: Sum of errors Subject to:\",\n \"b)) def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH 10 POINTS FROM WILLIAMS') x_vals =\",\n \"ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver,\",\n \"solver.Solve() var_to_val = dict() for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value() return var_to_val\",\n \"import enum import string from ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto()\",\n \"x_val) # Error terms ex_plus = variables[num_of_coeff + 2 * point_num] ex_minus =\",\n \"determines order of polynomial, from highest order (0th index) to lowest order (nth\",\n \"coefficient range.') if solver is None: solver = pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables =\",\n \"b = optimized_coefficients # print('Optimized m: {}, b: {}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING\",\n \"variables. \\\"\\\"\\\" num_of_coeff = len(coeff_ranges) variables = [] coeff_names = [] # Add\",\n \"python3 \\\"\\\"\\\"Curve fitting with linear programming. Minimizes the sum of error for each\",\n \"coeff_ranges[coeff_num][1] is None: upper_bound = solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound,\",\n \"PAPER') points = (0,1), (1,3), (2,2), (3,4), (4,5) coeff_ranges = ((None, None), (None,\",\n \"enumerate(points): # Equivalency constraint constraint = solver.Constraint(point[1], point[1]) # Resultant Coefficient terms for\",\n \"variables.append(negative_err_var) return variables def _generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \\\"\\\"\\\"Generate objective function for\",\n \"letter per english alphabet used for coefficient names. TODO(drofp): Figure out naming scheme\",\n \"((None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH 10\",\n \"for any order polynomial. Args: points: A tuple of points, represented as tuples\",\n \"print('STARTING LINEAR DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0,\",\n \"Sum of errors Subject to: Bounds on coefficients Credit: \\\"Curve Fitting with Linear\",\n \"instance is requested by caller. Returns: A Dictionary, the desired coefficients mapped to\",\n \"the optimal coefficients for a given polynomial. Overview: Objective: Sum of errors Subject\",\n \"points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \\\"\\\"\\\"Optimize coefficients for any order polynomial. Args: points:\",\n \"if num_of_coeff == 2: coeff_names.append('m') coeff_names.append('b') else: for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for\",\n \"pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables( solver, points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver,\",\n \"get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \\\"\\\"\\\"Optimize coefficients for any order polynomial. Args:\",\n \"a specific solver instance is requested by caller. Returns: A Dictionary, the desired\",\n \"err_max: An Integer, specifying the maximum error allowable. solver: a ortools.pywraplp.Solver object, if\",\n \"point[1]) # Resultant Coefficient terms for coeff_num, coeff in enumerate(variables[:num_of_coeff]): power = num_of_coeff\",\n \"pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for elm in optimized_coefficients: print('elm: {}'.format(elm)) print(\",\n \"coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals =\",\n \"-solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is None: upper_bound = solver.Infinity() else:\",\n \"_generate_constraints(solver, points, num_of_coeff, variables) solver.Solve() var_to_val = dict() for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()]\",\n \"list for point_cnt in range(len(points)): positive_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt\",\n \"variable list. if num_of_coeff == 2: coeff_names.append('m') coeff_names.append('b') else: for letter_cnt in range(num_of_coeff):\",\n \"= coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add absolute error variables to variable\",\n \"coefficient names. TODO(drofp): Figure out naming scheme for arbitrary number of variables. \\\"\\\"\\\"\",\n \"solver: a ortools.pywraplp.Solver object, if a specific solver instance is requested by caller.\",\n \"= optimized_coefficients # print('Optimized m: {}, b: {}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING LINEAR\",\n \"err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff, variables) solver.Solve()\",\n \"getting optimal linear polynomial. Uses 5 points from Swanson's curve fitting paper. \\\"\\\"\\\"\",\n \"import string from ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION =\",\n \"None: raise ValueError('Please provide appropriate coefficient range.') if solver is None: solver =\",\n \"with linear programming. Minimizes the sum of error for each fit point to\",\n \"5 points from Swanson's curve fitting paper. \\\"\\\"\\\" print('STARTING LINEAR DEMO WITH 5\",\n \"to variable list. if num_of_coeff == 2: coeff_names.append('m') coeff_names.append('b') else: for letter_cnt in\",\n \"1) return objective def _generate_constraints(solver, points, num_of_coeff, variables): constraints = [] for point_num,\",\n \"ex_plus = variables[num_of_coeff + 2 * point_num] ex_minus = variables[num_of_coeff + 2 *\",\n \"coefficient ranges, respresented as tuples (min, max). Nubmer of elements in list determines\",\n \"QUADRATIC DEMO WITH 19 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5,\",\n \"point_cnt in range(len(points)): positive_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1)\",\n \"POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5,\",\n \"None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def main(): demo_optimal_quadratic_19points() if __name__ ==\",\n \"def _generate_constraints(solver, points, num_of_coeff, variables): constraints = [] for point_num, point in enumerate(points):\",\n \"4.0, 4.5] y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7,\",\n \"= tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None), (None, None))\",\n \"print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals\",\n \"import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver, points,\",\n \"ErrorDefinition enum, specifying the definition for error. err_max: An Integer, specifying the maximum\",\n \"SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver, points, coeff_ranges, err_max, error_def): \\\"\\\"\\\"Create coefficient variables. Initial\",\n \"with Linear Programming\\\", <NAME> and <NAME> \\\"\\\"\\\" from __future__ import absolute_import from __future__\",\n \"a given polynomial. Overview: Objective: Sum of errors Subject to: Bounds on coefficients\",\n \"__future__ import print_function import enum import string from ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum):\",\n \"3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0, 7.6, 8.5, 9.0, 10.0])\",\n \"solver=None): \\\"\\\"\\\"Optimize coefficients for any order polynomial. Args: points: A tuple of points,\",\n \"given polynomial. Overview: Objective: Sum of errors Subject to: Bounds on coefficients Credit:\",\n \"coeff_ranges is None: raise ValueError('Please provide appropriate coefficient range.') if solver is None:\",\n \"variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value() return var_to_val def demo_optimal_linear_5points(): \\\"\\\"\\\"Demonstration of getting optimal linear\",\n \"objective def _generate_constraints(solver, points, num_of_coeff, variables): constraints = [] for point_num, point in\",\n \"of polynomial, from highest order (0th index) to lowest order (nth index). err_def:\",\n \"0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7,\",\n \"points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points,\",\n \"variable in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return objective def _generate_constraints(solver, points, num_of_coeff, variables): constraints\",\n \"a ortools.pywraplp.Solver object, if a specific solver instance is requested by caller. Returns:\",\n \"'_plus') negative_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) + '_minus')\",\n \"coeff_ranges = ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING\",\n \"2.7, 5.7, 4.6, 6.0, 6.8, 7.3]) points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None,\",\n \"var_to_val = dict() for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value() return var_to_val def\",\n \"None), (None, None)) # solver = pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial(\",\n \"coeff_num, coeff in enumerate(variables[:num_of_coeff]): power = num_of_coeff - coeff_num - 1 x_val =\",\n \"variables to variable list for point_cnt in range(len(points)): positive_err_var = solver.NumVar( 0, err_max,\",\n \"error. err_max: An Integer, specifying the maximum error allowable. solver: a ortools.pywraplp.Solver object,\",\n \"3.5, 4.0, 4.5] y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0,\",\n \"= solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) + '_minus') variables.append(positive_err_var) variables.append(negative_err_var)\",\n \"variables.append(positive_err_var) variables.append(negative_err_var) return variables def _generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \\\"\\\"\\\"Generate objective function\",\n \"polynomial. Args: points: A tuple of points, represented as tuples (x, y) coeff_ranges:\",\n \"optimal linear polynomial. Uses 5 points from Swanson's curve fitting paper. \\\"\\\"\\\" print('STARTING\",\n \"__future__ import absolute_import from __future__ import division from __future__ import print_function import enum\",\n \"variables, error_def=ErrorDefinition.SUM_ABS_DEV): \\\"\\\"\\\"Generate objective function for given error definition.\\\"\\\"\\\" objective = solver.Objective() for\",\n \"the definition for error. err_max: An Integer, specifying the maximum error allowable. solver:\",\n \"variables. Initial version works for up to 26 variable polynomial. One letter per\",\n \"# Equivalency constraint constraint = solver.Constraint(point[1], point[1]) # Resultant Coefficient terms for coeff_num,\",\n \"4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0, 7.6, 8.5, 9.0, 10.0]) y_vals =\",\n \"positive_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) + '_plus') negative_err_var\",\n \"for each fit point to find the optimal coefficients for a given polynomial.\",\n \"specifying the maximum error allowable. solver: a ortools.pywraplp.Solver object, if a specific solver\",\n \"2.5, 3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0, 7.6, 8.5, 9.0,\",\n \"variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add absolute error variables to variable list for\",\n \"None: solver = pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables( solver, points, coeff_ranges, err_max=err_max,\",\n \"from ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION = enum.auto() def\",\n \"y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7, 4.6, 6.0, 6.8, 7.3]) points = tuple(zip(x_vals, y_vals))\",\n \"2 * point_num] ex_minus = variables[num_of_coeff + 2 * point_num + 1] constraint.SetCoefficient(ex_plus,\",\n \"6.0, 6.6, 7.0, 7.6, 8.5, 9.0, 10.0]) y_vals = [1.0, 0.9, 0.7, 1.5,\",\n \"5.5, 6.0, 6.6, 7.0, 7.6, 8.5, 9.0, 10.0]) y_vals = [1.0, 0.9, 0.7,\",\n \"1) + '_minus') variables.append(positive_err_var) variables.append(negative_err_var) return variables def _generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV):\",\n \"variables def _generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \\\"\\\"\\\"Generate objective function for given error\",\n \"print('STARTING CUBIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0,\",\n \"# Resultant Coefficient terms for coeff_num, coeff in enumerate(variables[:num_of_coeff]): power = num_of_coeff -\",\n \"A Dictionary, the desired coefficients mapped to ther values. \\\"\\\"\\\" if coeff_ranges is\",\n \"# Error terms ex_plus = variables[num_of_coeff + 2 * point_num] ex_minus = variables[num_of_coeff\",\n \"power constraint.SetCoefficient(coeff, x_val) # Error terms ex_plus = variables[num_of_coeff + 2 * point_num]\",\n \"# solver = pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for\",\n \"num_of_coeff, variables) solver.Solve() var_to_val = dict() for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value()\",\n \"else: for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0] is\",\n \"+ 1) + '_minus') variables.append(positive_err_var) variables.append(negative_err_var) return variables def _generate_objective_fn( solver, num_of_coeff, variables,\",\n \"= tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges))\",\n \"variables): constraints = [] for point_num, point in enumerate(points): # Equivalency constraint constraint\",\n \"print('elm: {}'.format(elm)) print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m, b = optimized_coefficients\",\n \"elm in optimized_coefficients: print('elm: {}'.format(elm)) print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m,\",\n \"2 * point_num + 1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return constraints def\",\n \"num_of_coeff = len(coeff_ranges) variables = [] coeff_names = [] # Add coefficients to\",\n \"(None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH 19\",\n \"19 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0,\",\n \"for point_cnt in range(len(points)): positive_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt +\",\n \"definition for error. err_max: An Integer, specifying the maximum error allowable. solver: a\",\n \"solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) + '_plus') negative_err_var = solver.NumVar(\",\n \"'e' + str(point_cnt + 1) + '_minus') variables.append(positive_err_var) variables.append(negative_err_var) return variables def _generate_objective_fn(\",\n \"[] for point_num, point in enumerate(points): # Equivalency constraint constraint = solver.Constraint(point[1], point[1])\",\n \"coeff.solution_value() return var_to_val def demo_optimal_linear_5points(): \\\"\\\"\\\"Demonstration of getting optimal linear polynomial. Uses 5\",\n \"1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges =\",\n \"fitting with linear programming. Minimizes the sum of error for each fit point\",\n \"Credit: \\\"Curve Fitting with Linear Programming\\\", <NAME> and <NAME> \\\"\\\"\\\" from __future__ import\",\n \"8.5, 9.0, 10.0]) y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0,\",\n \"tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def\",\n \"arbitrary number of variables. \\\"\\\"\\\" num_of_coeff = len(coeff_ranges) variables = [] coeff_names =\",\n \"in optimized_coefficients: print('elm: {}'.format(elm)) print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m, b\",\n \"None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH\",\n \"y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] y_vals.extend([1.0,\",\n \"Dictionary, the desired coefficients mapped to ther values. \\\"\\\"\\\" if coeff_ranges is None:\",\n \"= -solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is None: upper_bound = solver.Infinity()\",\n \"if coeff_ranges[coeff_num][1] is None: upper_bound = solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound,\",\n \"tuple of valid coefficient ranges, respresented as tuples (min, max). Nubmer of elements\",\n \"= ((None, None), (None, None)) # solver = pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients\",\n \"return variables def _generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \\\"\\\"\\\"Generate objective function for given\",\n \"points=points, coeff_ranges=coeff_ranges) for elm in optimized_coefficients: print('elm: {}'.format(elm)) print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients:\",\n \"ortools.pywraplp.Solver object, if a specific solver instance is requested by caller. Returns: A\",\n \"points, coeff_ranges, err_max, error_def): \\\"\\\"\\\"Create coefficient variables. Initial version works for up to\",\n \"= solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add absolute\",\n \"range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0] is None: lower_bound = -solver.Infinity()\",\n \"object, if a specific solver instance is requested by caller. Returns: A Dictionary,\",\n \"provide appropriate coefficient range.') if solver is None: solver = pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING)\",\n \"import absolute_import from __future__ import division from __future__ import print_function import enum import\",\n \"2: coeff_names.append('m') coeff_names.append('b') else: for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff):\",\n \"+ 2 * point_num] ex_minus = variables[num_of_coeff + 2 * point_num + 1]\",\n \"Swanson's curve fitting paper. \\\"\\\"\\\" print('STARTING LINEAR DEMO WITH 5 POINTS FROM SWANSON\",\n \"3.2, 2.0, 2.7, 3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None,\",\n \"None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH 19 POINTS FROM WILLIAMS')\",\n \"1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] y_vals = [1.0, 0.9, 0.7, 1.5,\",\n \"solver instance is requested by caller. Returns: A Dictionary, the desired coefficients mapped\",\n \"absolute_import from __future__ import division from __future__ import print_function import enum import string\",\n \"division from __future__ import print_function import enum import string from ortools.linear_solver import pywraplp\",\n \"= (0,1), (1,3), (2,2), (3,4), (4,5) coeff_ranges = ((None, None), (None, None)) #\",\n \"(None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def main(): demo_optimal_quadratic_19points() if __name__ == '__main__':\",\n \"enum import string from ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION\",\n \"num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \\\"\\\"\\\"Generate objective function for given error definition.\\\"\\\"\\\" objective = solver.Objective()\",\n \"names. TODO(drofp): Figure out naming scheme for arbitrary number of variables. \\\"\\\"\\\" num_of_coeff\",\n \"= num_of_coeff - coeff_num - 1 x_val = point[0] ** power constraint.SetCoefficient(coeff, x_val)\",\n \"2.4, 3.2, 2.0, 2.7, 3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7, 4.6, 6.0, 6.8,\",\n \"up to 26 variable polynomial. One letter per english alphabet used for coefficient\",\n \"print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m, b = optimized_coefficients # print('Optimized\",\n \"= pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables( solver, points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff\",\n \"str(point_cnt + 1) + '_minus') variables.append(positive_err_var) variables.append(negative_err_var) return variables def _generate_objective_fn( solver, num_of_coeff,\",\n \"= [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5,\",\n \"def demo_optimal_linear_5points(): \\\"\\\"\\\"Demonstration of getting optimal linear polynomial. Uses 5 points from Swanson's\",\n \"upper_bound, coeff_names[coeff_num])) # Add absolute error variables to variable list for point_cnt in\",\n \"= ((None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH\",\n \"= enum.auto() def _generate_variables(solver, points, coeff_ranges, err_max, error_def): \\\"\\\"\\\"Create coefficient variables. Initial version\",\n \"coeff_ranges[coeff_num][0] is None: lower_bound = -solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is\",\n \"Overview: Objective: Sum of errors Subject to: Bounds on coefficients Credit: \\\"Curve Fitting\",\n \"1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] y_vals = [1.0, 0.9, 0.7,\",\n \"1 x_val = point[0] ** power constraint.SetCoefficient(coeff, x_val) # Error terms ex_plus =\",\n \"points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff,\",\n \"values. \\\"\\\"\\\" if coeff_ranges is None: raise ValueError('Please provide appropriate coefficient range.') if\",\n \"optimized_coefficients: print('elm: {}'.format(elm)) print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m, b =\",\n \"on coefficients Credit: \\\"Curve Fitting with Linear Programming\\\", <NAME> and <NAME> \\\"\\\"\\\" from\",\n \"(0,1), (1,3), (2,2), (3,4), (4,5) coeff_ranges = ((None, None), (None, None)) # solver\",\n \"coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is None: upper_bound = solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1] variables.append(\",\n \"= coeff.solution_value() return var_to_val def demo_optimal_linear_5points(): \\\"\\\"\\\"Demonstration of getting optimal linear polynomial. Uses\",\n \"'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m, b = optimized_coefficients # print('Optimized m:\",\n \"Minimizes the sum of error for each fit point to find the optimal\",\n \"err_max, 'e' + str(point_cnt + 1) + '_plus') negative_err_var = solver.NumVar( 0, err_max,\",\n \"None), (None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def main(): demo_optimal_quadratic_19points() if\",\n \"= ((None, None), (None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def main():\",\n \"each fit point to find the optimal coefficients for a given polynomial. Overview:\",\n \"None: upper_bound = solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) #\",\n \"Error terms ex_plus = variables[num_of_coeff + 2 * point_num] ex_minus = variables[num_of_coeff +\",\n \"\\\"\\\"\\\"Demonstration of getting optimal linear polynomial. Uses 5 points from Swanson's curve fitting\",\n \"coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0] is None: lower_bound = -solver.Infinity() else: lower_bound =\",\n \"# m, b = optimized_coefficients # print('Optimized m: {}, b: {}'.format(m, b)) def\",\n \"\\\"Curve Fitting with Linear Programming\\\", <NAME> and <NAME> \\\"\\\"\\\" from __future__ import absolute_import\",\n \"Fitting with Linear Programming\\\", <NAME> and <NAME> \\\"\\\"\\\" from __future__ import absolute_import from\",\n \"is None: upper_bound = solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num]))\",\n \"= ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC\",\n \"# print('Optimized m: {}, b: {}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH\",\n \"# Add coefficients to variable list. if num_of_coeff == 2: coeff_names.append('m') coeff_names.append('b') else:\",\n \"= [] for point_num, point in enumerate(points): # Equivalency constraint constraint = solver.Constraint(point[1],\",\n \"y_vals)) coeff_ranges = ((None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC\",\n \"(None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def main(): demo_optimal_quadratic_19points() if __name__\",\n \"None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH 19 POINTS\",\n \"# 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for elm in optimized_coefficients: print('elm:\",\n \"print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals\",\n \"coeff_ranges: A tuple of valid coefficient ranges, respresented as tuples (min, max). Nubmer\",\n \"solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add absolute error variables to variable list for point_cnt\",\n \"None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH 10 POINTS FROM WILLIAMS')\",\n \"= coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is None: upper_bound = solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1]\",\n \"objective.SetCoefficient(variable, 1) return objective def _generate_constraints(solver, points, num_of_coeff, variables): constraints = [] for\",\n \"demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5,\",\n \"(min, max). Nubmer of elements in list determines order of polynomial, from highest\",\n \"points from Swanson's curve fitting paper. \\\"\\\"\\\" print('STARTING LINEAR DEMO WITH 5 POINTS\",\n \"in list determines order of polynomial, from highest order (0th index) to lowest\",\n \"{}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH 10 POINTS FROM WILLIAMS') x_vals\",\n \"\\\"\\\"\\\" if coeff_ranges is None: raise ValueError('Please provide appropriate coefficient range.') if solver\",\n \"var_to_val[coeff.name()] = coeff.solution_value() return var_to_val def demo_optimal_linear_5points(): \\\"\\\"\\\"Demonstration of getting optimal linear polynomial.\",\n \"2.5, 3.0, 3.5, 4.0, 4.5] y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4,\",\n \"print('STARTING LINEAR DEMO WITH 5 POINTS FROM SWANSON PAPER') points = (0,1), (1,3),\",\n \"coeff_ranges = ((None, None), (None, None)) # solver = pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING)\",\n \"of errors Subject to: Bounds on coefficients Credit: \\\"Curve Fitting with Linear Programming\\\",\",\n \"from __future__ import print_function import enum import string from ortools.linear_solver import pywraplp class\",\n \"m, b = optimized_coefficients # print('Optimized m: {}, b: {}'.format(m, b)) def demo_optimal_linear_10points():\",\n \"2.0, 2.4, 3.2, 2.0, 2.7, 3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7, 4.6, 6.0,\",\n \"by caller. Returns: A Dictionary, the desired coefficients mapped to ther values. \\\"\\\"\\\"\",\n \"3.0, 3.5, 4.0, 4.5] y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2,\",\n \"constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return constraints def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \\\"\\\"\\\"Optimize\",\n \"'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for elm in optimized_coefficients: print('elm: {}'.format(elm))\",\n \"(1,3), (2,2), (3,4), (4,5) coeff_ranges = ((None, None), (None, None)) # solver =\",\n \"= point[0] ** power constraint.SetCoefficient(coeff, x_val) # Error terms ex_plus = variables[num_of_coeff +\",\n \"y_vals)) coeff_ranges = ((None, None), (None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges))\",\n \"coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals =\",\n \"(nth index). err_def: An ErrorDefinition enum, specifying the definition for error. err_max: An\",\n \"_generate_variables( solver, points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver,\",\n \"function for given error definition.\\\"\\\"\\\" objective = solver.Objective() for variable in variables[num_of_coeff:]: objective.SetCoefficient(variable,\",\n \"= [] coeff_names = [] # Add coefficients to variable list. if num_of_coeff\",\n \"requested by caller. Returns: A Dictionary, the desired coefficients mapped to ther values.\",\n \"err_max=10000, solver=None): \\\"\\\"\\\"Optimize coefficients for any order polynomial. Args: points: A tuple of\",\n \"import print_function import enum import string from ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV\",\n \"as tuples (min, max). Nubmer of elements in list determines order of polynomial,\",\n \"2.7, 3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None,\",\n \"variables = [] coeff_names = [] # Add coefficients to variable list. if\",\n \"print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH 19 POINTS FROM WILLIAMS') x_vals\",\n \"coeff_names[coeff_num])) # Add absolute error variables to variable list for point_cnt in range(len(points)):\",\n \"demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5,\",\n \"'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables( solver, points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges)\",\n \"for coefficient names. TODO(drofp): Figure out naming scheme for arbitrary number of variables.\",\n \"coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add absolute error variables to variable list\",\n \"[0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] y_vals = [1.0,\",\n \"tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING\",\n \"point_num + 1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return constraints def get_optimal_polynomial( points=None,\",\n \"error variables to variable list for point_cnt in range(len(points)): positive_err_var = solver.NumVar( 0,\",\n \"Objective: Sum of errors Subject to: Bounds on coefficients Credit: \\\"Curve Fitting with\",\n \"None)) # solver = pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges)\",\n \"1.9, 2.5, 3.0, 3.5, 4.0, 4.5] y_vals = [1.0, 0.9, 0.7, 1.5, 2.0,\",\n \"[1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] points = tuple(zip(x_vals,\",\n \"(2,2), (3,4), (4,5) coeff_ranges = ((None, None), (None, None)) # solver = pywraplp.Solver(\",\n \"from Swanson's curve fitting paper. \\\"\\\"\\\" print('STARTING LINEAR DEMO WITH 5 POINTS FROM\",\n \"y_vals)) coeff_ranges = ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points():\",\n \"def _generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \\\"\\\"\\\"Generate objective function for given error definition.\\\"\\\"\\\"\",\n \"to find the optimal coefficients for a given polynomial. Overview: Objective: Sum of\",\n \"for up to 26 variable polynomial. One letter per english alphabet used for\",\n \"for coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0] is None: lower_bound = -solver.Infinity() else: lower_bound\",\n \"10.0]) y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5]\",\n \"1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return constraints def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV,\",\n \"<NAME> \\\"\\\"\\\" from __future__ import absolute_import from __future__ import division from __future__ import\",\n \"y) coeff_ranges: A tuple of valid coefficient ranges, respresented as tuples (min, max).\",\n \"7.6, 8.5, 9.0, 10.0]) y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2,\",\n \"num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff, variables) solver.Solve() var_to_val = dict() for coeff in\",\n \"(None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH 10 POINTS FROM\",\n \"0, err_max, 'e' + str(point_cnt + 1) + '_minus') variables.append(positive_err_var) variables.append(negative_err_var) return variables\",\n \"(3,4), (4,5) coeff_ranges = ((None, None), (None, None)) # solver = pywraplp.Solver( #\",\n \"'e' + str(point_cnt + 1) + '_plus') negative_err_var = solver.NumVar( 0, err_max, 'e'\",\n \"letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0] is None: lower_bound\",\n \"4.5] y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5]\",\n \"constraint = solver.Constraint(point[1], point[1]) # Resultant Coefficient terms for coeff_num, coeff in enumerate(variables[:num_of_coeff]):\",\n \"given error definition.\\\"\\\"\\\" objective = solver.Objective() for variable in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return\",\n \"def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0,\",\n \"point[0] ** power constraint.SetCoefficient(coeff, x_val) # Error terms ex_plus = variables[num_of_coeff + 2\",\n \"def _generate_variables(solver, points, coeff_ranges, err_max, error_def): \\\"\\\"\\\"Create coefficient variables. Initial version works for\",\n \"_generate_variables(solver, points, coeff_ranges, err_max, error_def): \\\"\\\"\\\"Create coefficient variables. Initial version works for up\",\n \"solver, points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points,\",\n \"version works for up to 26 variable polynomial. One letter per english alphabet\",\n \"error_def): \\\"\\\"\\\"Create coefficient variables. Initial version works for up to 26 variable polynomial.\",\n \"if a specific solver instance is requested by caller. Returns: A Dictionary, the\",\n \"Subject to: Bounds on coefficients Credit: \\\"Curve Fitting with Linear Programming\\\", <NAME> and\",\n \"== 2: coeff_names.append('m') coeff_names.append('b') else: for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in\",\n \"points, represented as tuples (x, y) coeff_ranges: A tuple of valid coefficient ranges,\",\n \"((None, None), (None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def main(): demo_optimal_quadratic_19points()\",\n \"WITH 19 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5,\",\n \"out naming scheme for arbitrary number of variables. \\\"\\\"\\\" num_of_coeff = len(coeff_ranges) variables\",\n \"3.6, 2.7, 5.7, 4.6, 6.0, 6.8, 7.3]) points = tuple(zip(x_vals, y_vals)) coeff_ranges =\",\n \"7.3]) points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None))\",\n \"any order polynomial. Args: points: A tuple of points, represented as tuples (x,\",\n \"for coeff_num, coeff in enumerate(variables[:num_of_coeff]): power = num_of_coeff - coeff_num - 1 x_val\",\n \"is None: raise ValueError('Please provide appropriate coefficient range.') if solver is None: solver\",\n \"y_vals)) coeff_ranges = ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points():\",\n \"specific solver instance is requested by caller. Returns: A Dictionary, the desired coefficients\",\n \"WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5]\",\n \"class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver, points, coeff_ranges, err_max,\",\n \"= pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for elm in\",\n \"point_num, point in enumerate(points): # Equivalency constraint constraint = solver.Constraint(point[1], point[1]) # Resultant\",\n \"polynomial. One letter per english alphabet used for coefficient names. TODO(drofp): Figure out\",\n \"1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0,\",\n \"9.0, 10.0]) y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7,\",\n \"Integer, specifying the maximum error allowable. solver: a ortools.pywraplp.Solver object, if a specific\",\n \"4.6, 6.0, 6.8, 7.3]) points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None,\",\n \"elements in list determines order of polynomial, from highest order (0th index) to\",\n \"represented as tuples (x, y) coeff_ranges: A tuple of valid coefficient ranges, respresented\",\n \"index). err_def: An ErrorDefinition enum, specifying the definition for error. err_max: An Integer,\",\n \"__future__ import division from __future__ import print_function import enum import string from ortools.linear_solver\",\n \"err_def: An ErrorDefinition enum, specifying the definition for error. err_max: An Integer, specifying\",\n \"Programming\\\", <NAME> and <NAME> \\\"\\\"\\\" from __future__ import absolute_import from __future__ import division\",\n \"(4,5) coeff_ranges = ((None, None), (None, None)) # solver = pywraplp.Solver( # 'polynomial_solver',\",\n \"= ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC\",\n \"in variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value() return var_to_val def demo_optimal_linear_5points(): \\\"\\\"\\\"Demonstration of getting optimal\",\n \"coeff_ranges = ((None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO\",\n \"= [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] y_vals.extend([1.0, 4.0,\",\n \"+ '_plus') negative_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) +\",\n \"1) + '_plus') negative_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1)\",\n \"coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \\\"\\\"\\\"Optimize coefficients for any order polynomial. Args: points: A\",\n \"4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0, 7.6, 8.5, 9.0, 10.0]) y_vals = [1.0,\",\n \"1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7, 4.6,\",\n \"enumerate(variables[:num_of_coeff]): power = num_of_coeff - coeff_num - 1 x_val = point[0] ** power\",\n \"objective function for given error definition.\\\"\\\"\\\" objective = solver.Objective() for variable in variables[num_of_coeff:]:\",\n \"error for each fit point to find the optimal coefficients for a given\",\n \"solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add absolute error\",\n \"(None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH 19 POINTS FROM\",\n \"An Integer, specifying the maximum error allowable. solver: a ortools.pywraplp.Solver object, if a\",\n \"= len(coeff_ranges) variables = [] coeff_names = [] # Add coefficients to variable\",\n \"enum.auto() def _generate_variables(solver, points, coeff_ranges, err_max, error_def): \\\"\\\"\\\"Create coefficient variables. Initial version works\",\n \"SWANSON PAPER') points = (0,1), (1,3), (2,2), (3,4), (4,5) coeff_ranges = ((None, None),\",\n \"variables[num_of_coeff + 2 * point_num + 1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return\",\n \"to ther values. \\\"\\\"\\\" if coeff_ranges is None: raise ValueError('Please provide appropriate coefficient\",\n \"points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def\",\n \"for given error definition.\\\"\\\"\\\" objective = solver.Objective() for variable in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1)\",\n \"num_of_coeff, variables): constraints = [] for point_num, point in enumerate(points): # Equivalency constraint\",\n \"variable list for point_cnt in range(len(points)): positive_err_var = solver.NumVar( 0, err_max, 'e' +\",\n \"the sum of error for each fit point to find the optimal coefficients\",\n \"6.8, 7.3]) points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None,\",\n \"solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \\\"\\\"\\\"Generate objective function for given error definition.\\\"\\\"\\\" objective =\",\n \"1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0, 7.6,\",\n \"lower_bound = -solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is None: upper_bound =\",\n \"A tuple of points, represented as tuples (x, y) coeff_ranges: A tuple of\",\n \"[] coeff_names = [] # Add coefficients to variable list. if num_of_coeff ==\",\n \"{}'.format(optimized_coefficients)) # m, b = optimized_coefficients # print('Optimized m: {}, b: {}'.format(m, b))\",\n \"str(point_cnt + 1) + '_plus') negative_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt\",\n \"DEMO WITH 19 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9,\",\n \"error definition.\\\"\\\"\\\" objective = solver.Objective() for variable in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return objective\",\n \"x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0,\",\n \"coeff_ranges, err_max, error_def): \\\"\\\"\\\"Create coefficient variables. Initial version works for up to 26\",\n \"max). Nubmer of elements in list determines order of polynomial, from highest order\",\n \"per english alphabet used for coefficient names. TODO(drofp): Figure out naming scheme for\",\n \"points, num_of_coeff, variables) solver.Solve() var_to_val = dict() for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()] =\",\n \"\\\"\\\"\\\"Optimize coefficients for any order polynomial. Args: points: A tuple of points, represented\",\n \"the desired coefficients mapped to ther values. \\\"\\\"\\\" if coeff_ranges is None: raise\",\n \"return objective def _generate_constraints(solver, points, num_of_coeff, variables): constraints = [] for point_num, point\",\n \"Figure out naming scheme for arbitrary number of variables. \\\"\\\"\\\" num_of_coeff = len(coeff_ranges)\",\n \"error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff, variables) solver.Solve() var_to_val\",\n \"# Add absolute error variables to variable list for point_cnt in range(len(points)): positive_err_var\",\n \"+ 2 * point_num + 1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return constraints\",\n \"0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] y_vals = [1.0, 0.9,\",\n \"- 1 x_val = point[0] ** power constraint.SetCoefficient(coeff, x_val) # Error terms ex_plus\",\n \"ValueError('Please provide appropriate coefficient range.') if solver is None: solver = pywraplp.Solver( 'polynomial_solver',\",\n \"for elm in optimized_coefficients: print('elm: {}'.format(elm)) print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) #\",\n \"3.2, 2.0, 2.7, 3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7, 4.6, 6.0, 6.8, 7.3])\",\n \"point in enumerate(points): # Equivalency constraint constraint = solver.Constraint(point[1], point[1]) # Resultant Coefficient\",\n \"order polynomial. Args: points: A tuple of points, represented as tuples (x, y)\",\n \"DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9,\",\n \"= len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff, variables) solver.Solve() var_to_val = dict()\",\n \"5.7, 4.6, 6.0, 6.8, 7.3]) points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None),\",\n \"naming scheme for arbitrary number of variables. \\\"\\\"\\\" num_of_coeff = len(coeff_ranges) variables =\",\n \"= solver.Constraint(point[1], point[1]) # Resultant Coefficient terms for coeff_num, coeff in enumerate(variables[:num_of_coeff]): power\",\n \"dict() for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value() return var_to_val def demo_optimal_linear_5points(): \\\"\\\"\\\"Demonstration\",\n \"to 26 variable polynomial. One letter per english alphabet used for coefficient names.\",\n \"of points, represented as tuples (x, y) coeff_ranges: A tuple of valid coefficient\",\n \"+ '_minus') variables.append(positive_err_var) variables.append(negative_err_var) return variables def _generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \\\"\\\"\\\"Generate\",\n \"WITH 5 POINTS FROM SWANSON PAPER') points = (0,1), (1,3), (2,2), (3,4), (4,5)\",\n \"terms ex_plus = variables[num_of_coeff + 2 * point_num] ex_minus = variables[num_of_coeff + 2\",\n \"of valid coefficient ranges, respresented as tuples (min, max). Nubmer of elements in\",\n \"num_of_coeff == 2: coeff_names.append('m') coeff_names.append('b') else: for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num\",\n \"[0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0,\",\n \"coefficients Credit: \\\"Curve Fitting with Linear Programming\\\", <NAME> and <NAME> \\\"\\\"\\\" from __future__\",\n \"order (0th index) to lowest order (nth index). err_def: An ErrorDefinition enum, specifying\",\n \"polynomial. Overview: Objective: Sum of errors Subject to: Bounds on coefficients Credit: \\\"Curve\",\n \"in range(num_of_coeff): if coeff_ranges[coeff_num][0] is None: lower_bound = -solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0]\",\n \"for error. err_max: An Integer, specifying the maximum error allowable. solver: a ortools.pywraplp.Solver\",\n \"Add absolute error variables to variable list for point_cnt in range(len(points)): positive_err_var =\",\n \"<NAME> and <NAME> \\\"\\\"\\\" from __future__ import absolute_import from __future__ import division from\",\n \"linear polynomial. Uses 5 points from Swanson's curve fitting paper. \\\"\\\"\\\" print('STARTING LINEAR\",\n \"coefficients for any order polynomial. Args: points: A tuple of points, represented as\",\n \"coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff, variables)\",\n \"of variables. \\\"\\\"\\\" num_of_coeff = len(coeff_ranges) variables = [] coeff_names = [] #\",\n \"An ErrorDefinition enum, specifying the definition for error. err_max: An Integer, specifying the\",\n \"highest order (0th index) to lowest order (nth index). err_def: An ErrorDefinition enum,\",\n \"(None, None)) # solver = pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points,\",\n \"coefficient variables. Initial version works for up to 26 variable polynomial. One letter\",\n \"None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH 10 POINTS\",\n \"in enumerate(variables[:num_of_coeff]): power = num_of_coeff - coeff_num - 1 x_val = point[0] **\",\n \"solver.Objective() for variable in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return objective def _generate_constraints(solver, points, num_of_coeff,\",\n \"print('STARTING QUADRATIC DEMO WITH 19 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0,\",\n \"print_function import enum import string from ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV =\",\n \"= solver.Objective() for variable in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return objective def _generate_constraints(solver, points,\",\n \"0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges\",\n \"to: Bounds on coefficients Credit: \\\"Curve Fitting with Linear Programming\\\", <NAME> and <NAME>\",\n \"points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None), (None,\",\n \"type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m, b = optimized_coefficients # print('Optimized m: {}, b:\",\n \"#!/usr/bin/env python3 \\\"\\\"\\\"Curve fitting with linear programming. Minimizes the sum of error for\",\n \"** power constraint.SetCoefficient(coeff, x_val) # Error terms ex_plus = variables[num_of_coeff + 2 *\",\n \"coeff_names = [] # Add coefficients to variable list. if num_of_coeff == 2:\",\n \"print('STARTING QUADRATIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0,\",\n \"if coeff_ranges[coeff_num][0] is None: lower_bound = -solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1]\",\n \"Linear Programming\\\", <NAME> and <NAME> \\\"\\\"\\\" from __future__ import absolute_import from __future__ import\",\n \"2.0, 2.7, 3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None))\",\n \"= [] # Add coefficients to variable list. if num_of_coeff == 2: coeff_names.append('m')\",\n \"len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff, variables) solver.Solve() var_to_val = dict() for\",\n \"order of polynomial, from highest order (0th index) to lowest order (nth index).\",\n \"m: {}, b: {}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH 10 POINTS\",\n \"points, num_of_coeff, variables): constraints = [] for point_num, point in enumerate(points): # Equivalency\",\n \"demo_optimal_linear_5points(): \\\"\\\"\\\"Demonstration of getting optimal linear polynomial. Uses 5 points from Swanson's curve\",\n \"2.7, 3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7, 4.6, 6.0, 6.8, 7.3]) points =\",\n \"variables) solver.Solve() var_to_val = dict() for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value() return\",\n \"WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5,\",\n \"_generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff, variables) solver.Solve() var_to_val = dict() for coeff\",\n \"range(num_of_coeff): if coeff_ranges[coeff_num][0] is None: lower_bound = -solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0] if\",\n \"(None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH 10 POINTS FROM\",\n \"+ str(point_cnt + 1) + '_plus') negative_err_var = solver.NumVar( 0, err_max, 'e' +\",\n \"1.9, 2.5, 3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0, 7.6, 8.5,\",\n \"None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def main(): demo_optimal_quadratic_19points() if __name__ == '__main__': main()\",\n \"(0th index) to lowest order (nth index). err_def: An ErrorDefinition enum, specifying the\",\n \"else: upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add absolute error variables\",\n \"= [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] points =\",\n \"2.0, 2.7, 3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None),\",\n \"number of variables. \\\"\\\"\\\" num_of_coeff = len(coeff_ranges) variables = [] coeff_names = []\",\n \"fit point to find the optimal coefficients for a given polynomial. Overview: Objective:\",\n \"_generate_constraints(solver, points, num_of_coeff, variables): constraints = [] for point_num, point in enumerate(points): #\",\n \"LINEAR DEMO WITH 5 POINTS FROM SWANSON PAPER') points = (0,1), (1,3), (2,2),\",\n \"(None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH 10\",\n \"tuple of points, represented as tuples (x, y) coeff_ranges: A tuple of valid\",\n \"for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value() return var_to_val def demo_optimal_linear_5points(): \\\"\\\"\\\"Demonstration of\",\n \"solver = pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for elm\",\n \"2.0, 2.7, 3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7, 4.6, 6.0, 6.8, 7.3]) points\",\n \"CUBIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5,\",\n \"0, err_max, 'e' + str(point_cnt + 1) + '_plus') negative_err_var = solver.NumVar( 0,\",\n \"for a given polynomial. Overview: Objective: Sum of errors Subject to: Bounds on\",\n \"coeff_ranges = ((None, None), (None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def\",\n \"constraint.SetCoefficient(coeff, x_val) # Error terms ex_plus = variables[num_of_coeff + 2 * point_num] ex_minus\",\n \"variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return objective def _generate_constraints(solver, points, num_of_coeff, variables): constraints = []\",\n \"get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for elm in optimized_coefficients: print('elm: {}'.format(elm)) print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients)))\",\n \"for variable in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return objective def _generate_constraints(solver, points, num_of_coeff, variables):\",\n \"power = num_of_coeff - coeff_num - 1 x_val = point[0] ** power constraint.SetCoefficient(coeff,\",\n \"err_max, 'e' + str(point_cnt + 1) + '_minus') variables.append(positive_err_var) variables.append(negative_err_var) return variables def\",\n \"Resultant Coefficient terms for coeff_num, coeff in enumerate(variables[:num_of_coeff]): power = num_of_coeff - coeff_num\",\n \"= solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) + '_plus') negative_err_var =\",\n \"order (nth index). err_def: An ErrorDefinition enum, specifying the definition for error. err_max:\",\n \"demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5,\",\n \"import division from __future__ import print_function import enum import string from ortools.linear_solver import\",\n \"Returns: A Dictionary, the desired coefficients mapped to ther values. \\\"\\\"\\\" if coeff_ranges\",\n \"appropriate coefficient range.') if solver is None: solver = pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables\",\n \"((None, None), (None, None)) # solver = pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients =\",\n \"constraints.append(constraint) return constraints def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \\\"\\\"\\\"Optimize coefficients for\",\n \"from __future__ import absolute_import from __future__ import division from __future__ import print_function import\",\n \"for point_num, point in enumerate(points): # Equivalency constraint constraint = solver.Constraint(point[1], point[1]) #\",\n \"point to find the optimal coefficients for a given polynomial. Overview: Objective: Sum\",\n \"solver.Constraint(point[1], point[1]) # Resultant Coefficient terms for coeff_num, coeff in enumerate(variables[:num_of_coeff]): power =\",\n \"coeff_num - 1 x_val = point[0] ** power constraint.SetCoefficient(coeff, x_val) # Error terms\",\n \"index) to lowest order (nth index). err_def: An ErrorDefinition enum, specifying the definition\",\n \"error_def=ErrorDefinition.SUM_ABS_DEV): \\\"\\\"\\\"Generate objective function for given error definition.\\\"\\\"\\\" objective = solver.Objective() for variable\",\n \"constraint constraint = solver.Constraint(point[1], point[1]) # Resultant Coefficient terms for coeff_num, coeff in\",\n \"errors Subject to: Bounds on coefficients Credit: \\\"Curve Fitting with Linear Programming\\\", <NAME>\",\n \"tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points,\",\n \"is requested by caller. Returns: A Dictionary, the desired coefficients mapped to ther\",\n \"of getting optimal linear polynomial. Uses 5 points from Swanson's curve fitting paper.\",\n \"= enum.auto() SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver, points, coeff_ranges, err_max, error_def): \\\"\\\"\\\"Create coefficient\",\n \"7.0, 7.6, 8.5, 9.0, 10.0]) y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4,\",\n \"used for coefficient names. TODO(drofp): Figure out naming scheme for arbitrary number of\",\n \"'_minus') variables.append(positive_err_var) variables.append(negative_err_var) return variables def _generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \\\"\\\"\\\"Generate objective\",\n \"((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO\",\n \"curve fitting paper. \\\"\\\"\\\" print('STARTING LINEAR DEMO WITH 5 POINTS FROM SWANSON PAPER')\",\n \"2.0, 2.4, 3.2, 2.0, 2.7, 3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None,\",\n \"valid coefficient ranges, respresented as tuples (min, max). Nubmer of elements in list\",\n \"point_num] ex_minus = variables[num_of_coeff + 2 * point_num + 1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus,\",\n \"err_max, error_def): \\\"\\\"\\\"Create coefficient variables. Initial version works for up to 26 variable\",\n \"DEMO WITH 5 POINTS FROM SWANSON PAPER') points = (0,1), (1,3), (2,2), (3,4),\",\n \"fitting paper. \\\"\\\"\\\" print('STARTING LINEAR DEMO WITH 5 POINTS FROM SWANSON PAPER') points\",\n \"def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \\\"\\\"\\\"Optimize coefficients for any order polynomial.\",\n \"coefficients mapped to ther values. \\\"\\\"\\\" if coeff_ranges is None: raise ValueError('Please provide\",\n \"string from ortools.linear_solver import pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION = enum.auto()\",\n \"coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH 19 POINTS FROM WILLIAMS') x_vals =\",\n \"upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add absolute error variables to\",\n \"ranges, respresented as tuples (min, max). Nubmer of elements in list determines order\",\n \"lowest order (nth index). err_def: An ErrorDefinition enum, specifying the definition for error.\",\n \"tuples (min, max). Nubmer of elements in list determines order of polynomial, from\",\n \"english alphabet used for coefficient names. TODO(drofp): Figure out naming scheme for arbitrary\",\n \"= _generate_variables( solver, points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables)\",\n \"POINTS FROM SWANSON PAPER') points = (0,1), (1,3), (2,2), (3,4), (4,5) coeff_ranges =\",\n \"in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return objective def _generate_constraints(solver, points, num_of_coeff, variables): constraints =\",\n \"maximum error allowable. solver: a ortools.pywraplp.Solver object, if a specific solver instance is\",\n \"constraints def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \\\"\\\"\\\"Optimize coefficients for any order\",\n \"x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0, 7.6, 8.5, 9.0, 10.0]) y_vals = [1.0, 0.9,\",\n \"polynomial, from highest order (0th index) to lowest order (nth index). err_def: An\",\n \"in range(len(points)): positive_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) +\",\n \"print('Optimized m: {}, b: {}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH 10\",\n \"ther values. \\\"\\\"\\\" if coeff_ranges is None: raise ValueError('Please provide appropriate coefficient range.')\",\n \"[] # Add coefficients to variable list. if num_of_coeff == 2: coeff_names.append('m') coeff_names.append('b')\",\n \"pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables( solver, points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff =\",\n \"y_vals = [1.0, 0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] points\",\n \"mapped to ther values. \\\"\\\"\\\" if coeff_ranges is None: raise ValueError('Please provide appropriate\",\n \"points = (0,1), (1,3), (2,2), (3,4), (4,5) coeff_ranges = ((None, None), (None, None))\",\n \"num_of_coeff - coeff_num - 1 x_val = point[0] ** power constraint.SetCoefficient(coeff, x_val) #\",\n \"coeff_names.append('m') coeff_names.append('b') else: for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff): if\",\n \"3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7, 5.7, 4.6, 6.0, 6.8, 7.3]) points = tuple(zip(x_vals,\",\n \"for arbitrary number of variables. \\\"\\\"\\\" num_of_coeff = len(coeff_ranges) variables = [] coeff_names\",\n \"4.0, 3.6, 2.7, 5.7, 4.6, 6.0, 6.8, 7.3]) points = tuple(zip(x_vals, y_vals)) coeff_ranges\",\n \"- coeff_num - 1 x_val = point[0] ** power constraint.SetCoefficient(coeff, x_val) # Error\",\n \"None: lower_bound = -solver.Infinity() else: lower_bound = coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is None: upper_bound\",\n \"\\\"\\\"\\\" print('STARTING LINEAR DEMO WITH 5 POINTS FROM SWANSON PAPER') points = (0,1),\",\n \"alphabet used for coefficient names. TODO(drofp): Figure out naming scheme for arbitrary number\",\n \"\\\"\\\"\\\"Generate objective function for given error definition.\\\"\\\"\\\" objective = solver.Objective() for variable in\",\n \"LINEAR DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5,\",\n \"def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0,\",\n \"variables = _generate_variables( solver, points, coeff_ranges, err_max=err_max, error_def=error_def) num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff,\",\n \"((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO\",\n \"ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver, points, coeff_ranges, err_max, error_def):\",\n \"10 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0,\",\n \"def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH 10 POINTS FROM WILLIAMS') x_vals = [0.0,\",\n \"list determines order of polynomial, from highest order (0th index) to lowest order\",\n \"enum, specifying the definition for error. err_max: An Integer, specifying the maximum error\",\n \"0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] points = tuple(zip(x_vals, y_vals))\",\n \"= [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] y_vals =\",\n \"3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6, 7.0, 7.6, 8.5, 9.0, 10.0]) y_vals\",\n \"to lowest order (nth index). err_def: An ErrorDefinition enum, specifying the definition for\",\n \"\\\"\\\"\\\" from __future__ import absolute_import from __future__ import division from __future__ import print_function\",\n \"points: A tuple of points, represented as tuples (x, y) coeff_ranges: A tuple\",\n \"= tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points():\",\n \"raise ValueError('Please provide appropriate coefficient range.') if solver is None: solver = pywraplp.Solver(\",\n \"objective = solver.Objective() for variable in variables[num_of_coeff:]: objective.SetCoefficient(variable, 1) return objective def _generate_constraints(solver,\",\n \"None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH 10 POINTS FROM WILLIAMS')\",\n \"= dict() for coeff in variables[:num_of_coeff]: var_to_val[coeff.name()] = coeff.solution_value() return var_to_val def demo_optimal_linear_5points():\",\n \"1) constraints.append(constraint) return constraints def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \\\"\\\"\\\"Optimize coefficients\",\n \"{}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m, b = optimized_coefficients # print('Optimized m: {},\",\n \"of elements in list determines order of polynomial, from highest order (0th index)\",\n \"variable polynomial. One letter per english alphabet used for coefficient names. TODO(drofp): Figure\",\n \"FROM WILLIAMS') x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0,\",\n \"3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None))\",\n \"+ 1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return constraints def get_optimal_polynomial( points=None, coeff_ranges=None,\",\n \"x_val = point[0] ** power constraint.SetCoefficient(coeff, x_val) # Error terms ex_plus = variables[num_of_coeff\",\n \"constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return constraints def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000,\",\n \"x_vals = [0.0, 0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] y_vals\",\n \"find the optimal coefficients for a given polynomial. Overview: Objective: Sum of errors\",\n \"terms for coeff_num, coeff in enumerate(variables[:num_of_coeff]): power = num_of_coeff - coeff_num - 1\",\n \"SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver, points, coeff_ranges, err_max, error_def): \\\"\\\"\\\"Create\",\n \"lower_bound = coeff_ranges[coeff_num][0] if coeff_ranges[coeff_num][1] is None: upper_bound = solver.Infinity() else: upper_bound =\",\n \"coeff_ranges = ((None, None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING\",\n \"{}, b: {}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH 10 POINTS FROM\",\n \"coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0] is None: lower_bound = -solver.Infinity() else:\",\n \"caller. Returns: A Dictionary, the desired coefficients mapped to ther values. \\\"\\\"\\\" if\",\n \"Nubmer of elements in list determines order of polynomial, from highest order (0th\",\n \"specifying the definition for error. err_max: An Integer, specifying the maximum error allowable.\",\n \"0.9, 0.7, 1.5, 2.0, 2.4, 3.2, 2.0, 2.7, 3.5] y_vals.extend([1.0, 4.0, 3.6, 2.7,\",\n \"coefficients for a given polynomial. Overview: Objective: Sum of errors Subject to: Bounds\",\n \"to variable list for point_cnt in range(len(points)): positive_err_var = solver.NumVar( 0, err_max, 'e'\",\n \"solver = pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables( solver, points, coeff_ranges, err_max=err_max, error_def=error_def)\",\n \"from __future__ import division from __future__ import print_function import enum import string from\",\n \"6.0, 6.8, 7.3]) points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None),\",\n \"absolute error variables to variable list for point_cnt in range(len(points)): positive_err_var = solver.NumVar(\",\n \"constraints = [] for point_num, point in enumerate(points): # Equivalency constraint constraint =\",\n \"var_to_val def demo_optimal_linear_5points(): \\\"\\\"\\\"Demonstration of getting optimal linear polynomial. Uses 5 points from\",\n \"\\\"\\\"\\\" num_of_coeff = len(coeff_ranges) variables = [] coeff_names = [] # Add coefficients\",\n \"6.6, 7.0, 7.6, 8.5, 9.0, 10.0]) y_vals = [1.0, 0.9, 0.7, 1.5, 2.0,\",\n \"the maximum error allowable. solver: a ortools.pywraplp.Solver object, if a specific solver instance\",\n \"None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_quadratic_10points(): print('STARTING QUADRATIC DEMO WITH 10 POINTS\",\n \"respresented as tuples (min, max). Nubmer of elements in list determines order of\",\n \"0.5, 1.0, 1.5, 1.9, 2.5, 3.0, 3.5, 4.0, 4.5] x_vals.extend([5.0, 5.5, 6.0, 6.6,\",\n \"b: {}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO WITH 10 POINTS FROM WILLIAMS')\",\n \"optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for elm in optimized_coefficients: print('elm: {}'.format(elm)) print( 'type(optimized_coefficients):\",\n \"pywraplp class ErrorDefinition(enum.Enum): SUM_ABS_DEV = enum.auto() SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver, points, coeff_ranges,\",\n \"range(len(points)): positive_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) + '_plus')\",\n \"return var_to_val def demo_optimal_linear_5points(): \\\"\\\"\\\"Demonstration of getting optimal linear polynomial. Uses 5 points\",\n \"error allowable. solver: a ortools.pywraplp.Solver object, if a specific solver instance is requested\",\n \"pywraplp.Solver( # 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) optimized_coefficients = get_optimal_polynomial( points=points, coeff_ranges=coeff_ranges) for elm in optimized_coefficients:\",\n \"if solver is None: solver = pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables( solver,\",\n \"sum of error for each fit point to find the optimal coefficients for\",\n \"variables[num_of_coeff + 2 * point_num] ex_minus = variables[num_of_coeff + 2 * point_num +\",\n \"* point_num] ex_minus = variables[num_of_coeff + 2 * point_num + 1] constraint.SetCoefficient(ex_plus, -1)\",\n \"3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None), (None, None),\",\n \"def demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH 19 POINTS FROM WILLIAMS') x_vals = [0.0,\",\n \"scheme for arbitrary number of variables. \\\"\\\"\\\" num_of_coeff = len(coeff_ranges) variables = []\",\n \"linear programming. Minimizes the sum of error for each fit point to find\",\n \"ex_minus = variables[num_of_coeff + 2 * point_num + 1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1)\",\n \"negative_err_var = solver.NumVar( 0, err_max, 'e' + str(point_cnt + 1) + '_minus') variables.append(positive_err_var)\",\n \"{}'.format(elm)) print( 'type(optimized_coefficients): {}'.format( type(optimized_coefficients))) print('optimized_coefficients: {}'.format(optimized_coefficients)) # m, b = optimized_coefficients #\",\n \"optimized_coefficients # print('Optimized m: {}, b: {}'.format(m, b)) def demo_optimal_linear_10points(): print('STARTING LINEAR DEMO\",\n \"demo_optimal_quadratic_19points(): print('STARTING QUADRATIC DEMO WITH 19 POINTS FROM WILLIAMS') x_vals = [0.0, 0.5,\",\n \"Initial version works for up to 26 variable polynomial. One letter per english\",\n \"-1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint) return constraints def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None):\",\n \"Add coefficients to variable list. if num_of_coeff == 2: coeff_names.append('m') coeff_names.append('b') else: for\",\n \"coeff in enumerate(variables[:num_of_coeff]): power = num_of_coeff - coeff_num - 1 x_val = point[0]\",\n \"Args: points: A tuple of points, represented as tuples (x, y) coeff_ranges: A\",\n \"as tuples (x, y) coeff_ranges: A tuple of valid coefficient ranges, respresented as\",\n \"num_of_coeff = len(coeff_ranges) _generate_objective_fn(solver, num_of_coeff, variables) _generate_constraints(solver, points, num_of_coeff, variables) solver.Solve() var_to_val =\",\n \"list. if num_of_coeff == 2: coeff_names.append('m') coeff_names.append('b') else: for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt])\",\n \"Coefficient terms for coeff_num, coeff in enumerate(variables[:num_of_coeff]): power = num_of_coeff - coeff_num -\",\n \"3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges))\",\n \"paper. \\\"\\\"\\\" print('STARTING LINEAR DEMO WITH 5 POINTS FROM SWANSON PAPER') points =\",\n \"return constraints def get_optimal_polynomial( points=None, coeff_ranges=None, error_def=ErrorDefinition.SUM_ABS_DEV, err_max=10000, solver=None): \\\"\\\"\\\"Optimize coefficients for any\",\n \"2.7, 3.5] points = tuple(zip(x_vals, y_vals)) coeff_ranges = ((None, None), (None, None)) print(get_optimal_polynomial(points=points,\",\n \"of error for each fit point to find the optimal coefficients for a\",\n \"= variables[num_of_coeff + 2 * point_num + 1] constraint.SetCoefficient(ex_plus, -1) constraint.SetCoefficient(ex_minus, 1) constraints.append(constraint)\",\n \"coeff_names.append('b') else: for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0]\",\n \"desired coefficients mapped to ther values. \\\"\\\"\\\" if coeff_ranges is None: raise ValueError('Please\",\n \"Uses 5 points from Swanson's curve fitting paper. \\\"\\\"\\\" print('STARTING LINEAR DEMO WITH\",\n \"programming. Minimizes the sum of error for each fit point to find the\",\n \"26 variable polynomial. One letter per english alphabet used for coefficient names. TODO(drofp):\",\n \"variables) _generate_constraints(solver, points, num_of_coeff, variables) solver.Solve() var_to_val = dict() for coeff in variables[:num_of_coeff]:\",\n \"(x, y) coeff_ranges: A tuple of valid coefficient ranges, respresented as tuples (min,\",\n \"in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0] is None: lower_bound =\",\n \"for letter_cnt in range(num_of_coeff): coeff_names.append(string.ascii_lowercase[letter_cnt]) for coeff_num in range(num_of_coeff): if coeff_ranges[coeff_num][0] is None:\",\n \"upper_bound = solver.Infinity() else: upper_bound = coeff_ranges[coeff_num][1] variables.append( solver.NumVar(lower_bound, upper_bound, coeff_names[coeff_num])) # Add\",\n \"_generate_objective_fn( solver, num_of_coeff, variables, error_def=ErrorDefinition.SUM_ABS_DEV): \\\"\\\"\\\"Generate objective function for given error definition.\\\"\\\"\\\" objective\",\n \"\\\"\\\"\\\"Curve fitting with linear programming. Minimizes the sum of error for each fit\",\n \"None), (None, None), (None, None)) print(get_optimal_polynomial(points=points, coeff_ranges=coeff_ranges)) def demo_optimal_cubic_10points(): print('STARTING CUBIC DEMO WITH\",\n \"One letter per english alphabet used for coefficient names. TODO(drofp): Figure out naming\",\n \"allowable. solver: a ortools.pywraplp.Solver object, if a specific solver instance is requested by\",\n \"is None: solver = pywraplp.Solver( 'polynomial_solver', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) variables = _generate_variables( solver, points, coeff_ranges,\"\n]","isConversational":false}}},{"rowIdx":4586,"cells":{"ngram":{"kind":"list like","value":["parsed.package_dir)) # Convert build_dir to absolute path, relative to package_dir. parsed.build_dir = os.path.join(parsed.package_dir,","as e: printerr('FAIL: Generating the Xcode project failed') printerr('Executing: %s' % ' '.join(e.cmd))","in the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test', 'swift-evolve']: # Make","parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to an Xcode workspace to create a","checked out next sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \"1\" if args.update: print(\"**","package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\"generate-xcodeproj\",","e: printerr('FAIL: Testing %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1)","main swift repository's build-script.py that knows how to build and install the stress","does not need to rebuilt if it has already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT']","else: return arg def get_products(package_dir): # FIXME: We ought to be able to","for product in products: invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env,","rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose): package_name = os.path.basename(package_dir)","information See https://swift.org/CONTRIBUTORS.txt for the list of Swift project authors ------------------------------------------------------------------------------ This is","config_path = os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath}","parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log executed commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug')","how to build and install the stress tester utilities given a swift workspace.","it rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add the rpath to the stdlib in in","check_call(cmd, verbose=verbose) def check_call(cmd, verbose, env=os.environ, **kwargs): if verbose: print(' '.join([escape_cmd_arg(arg) for arg","except subprocess.CalledProcessError as e: printerr('FAIL: Updating dependencies of %s failed' % package_name) printerr('Executing:","LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' % package_name) args =","required with the install action\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir =","% ' '.join(e.cmd)) sys.exit(1) if should_run_action(\"install\", args.build_actions): print(\"** Installing %s **\" % package_name)","any of the actions in `action_names` should be run. def should_run_any_action(action_names, selected_actions): for","help='Path to an Xcode workspace to create a unified build of SwiftSyntax with","% ' '.join(e.cmd)) sys.exit(1) if should_run_action(\"test\", args.build_actions): print(\"** Testing %s **\" % package_name)","testing if should_run_any_action(['build', 'install'], args.build_actions): print(\"** Building %s **\" % package_name) try: invoke_swift(package_dir=args.package_dir,","copy_cmd=['rsync', '-a', src, dest] print('installing %s to %s' % (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose)","% package_name) args = [swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path]","failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\"install\", args.build_actions): print(\"**","'--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args, env=env, verbose=verbose) def add_rpath(binary, rpath,","list) for item in pair] def escape_cmd_arg(arg): if '\"' in arg or '","os.path.join(bin_dir, product) # Create a copy of the list since we modify it","Xcode workspace to create a unified build of SwiftSyntax with other projects.') parser.add_argument('--toolchain',","if '\"' in arg or ' ' in arg: return '\"%s\"' % arg.replace('\"',","%s **\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir,","copy of the list since we modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add","selected_actions): if action_name in selected_actions: return True elif \"all\" in selected_actions: return True","args.build_actions): print(\"** Building %s **\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath,","rpath, binary] check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-delete_rpath', rpath,","printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\"install\", args.build_actions): print(\"** Installing %s **\"","product) # Create a copy of the list since we modify it rpaths_to_delete_for_this_product","swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Generating the Xcode project","in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose): package_name =","printerr('FAIL: Generating the Xcode project failed') printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if","**\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env,","os.path.join(parsed.package_dir, parsed.build_dir) return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env = dict(os.environ)","'\\\\\"') else: return arg def get_products(package_dir): # FIXME: We ought to be able","% package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL:","def invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): # Until","targets simultaneously. For now, just build one product after the other. for product","rpath to sourcekitd relative in the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib']","# The test action creates its own build. No need to build if","Generating the Xcode project failed') printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\"test\",","if package_dir.endswith(\"/SourceKitStressTester\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\"/SwiftEvolve\"): return ['swift-evolve'] else: return [] if","build_dir, multiroot_data_file, config, env, verbose): # Until rdar://53881101 is implemented, we cannot request","for arg in cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value, list): return","if we are just testing if should_run_any_action(['build', 'install'], args.build_actions): print(\"** Building %s **\"","as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path","'.join(e.cmd)) sys.exit(1) # Returns true if any of the actions in `action_names` should","project authors Licensed under Apache License v2.0 with Runtime Library Exception See https://swift.org/LICENSE.txt","'-c', config, '--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action == 'test': args.extend(['--test-product',","help='use normal remote dependencies when building') parser.add_argument('build_actions', help=\"Extra actions to perform. Can be","request a build of multiple # targets simultaneously. For now, just build one","else: args.extend(['--product', product]) # Tell SwiftSyntax that we are building in a build-script","swift repository's build-script.py that knows how to build and install the stress tester","check_call(copy_cmd, verbose=verbose) for rpath in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for rpath in rpaths_to_add:","env, verbose): # Until rdar://53881101 is implemented, we cannot request a build of","parser.add_argument('-v', '--verbose', action='store_true', help='log executed commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build')","except subprocess.CalledProcessError as e: printerr('FAIL: Installing %s failed' % package_name) printerr('Executing: %s' %","SwiftPM for this info. if package_dir.endswith(\"/SourceKitStressTester\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\"/SwiftEvolve\"): return ['swift-evolve']","default='.build') parser.add_argument('--multiroot-data-file', help='Path to an Xcode workspace to create a unified build of","lib_dir]: if not os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test and sk-swiftc-wrapper for product in","# Convert build_dir to absolute path, relative to package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir)","'test': args.extend(['--test-product', product]) else: args.extend(['--product', product]) # Tell SwiftSyntax that we are building","if any of the actions in `action_names` should be run. def should_run_any_action(action_names, selected_actions):","and not parsed.prefix: ArgumentParser.error(\"'--prefix' is required with the install action\") parsed.swift_exec = os.path.join(parsed.toolchain,","perform. Can be any number of the following\", choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'],","be run. def should_run_any_action(action_names, selected_actions): for action_name in action_names: if should_run_action(action_name, selected_actions): return","should_run_any_action(action_names, selected_actions): for action_name in action_names: if should_run_action(action_name, selected_actions): return True return False","if action_name in selected_actions: return True elif \"all\" in selected_actions: return True else:","= ['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test', 'swift-evolve']: # Make the rpath to sourcekitd","' ' in arg: return '\"%s\"' % arg.replace('\"', '\\\\\"') else: return arg def","The test action creates its own build. No need to build if we","def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir, 'bin') lib_dir =","a swift workspace. \"\"\" from __future__ import print_function import argparse import sys import","invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): args = [swift_exec,","add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose): package_name = os.path.basename(package_dir) config_path","should_run_action(\"generate-xcodeproj\", args.build_actions): print(\"** Generating Xcode project for %s **\" % package_name) try: generate_xcodeproj(args.package_dir,","This is a helper script for the main swift repository's build-script.py that knows","and install the stress tester utilities given a swift workspace. \"\"\" from __future__","swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Updating dependencies of %s","# it does not need to rebuilt if it has already been built","subprocess.CalledProcessError as e: printerr('FAIL: Testing %s failed' % package_name) printerr('Executing: %s' % '","try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError","e: printerr('FAIL: Updating dependencies of %s failed' % package_name) printerr('Executing: %s' % '","of %s **\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError","args.build_actions): print(\"** Installing %s **\" % package_name) stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib', 'swift',","subprocess.CalledProcessError as e: printerr('FAIL: Installing %s failed' % package_name) printerr('Executing: %s' % '","def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env = dict(os.environ) # Use local dependencies","already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env, verbose=verbose)","in the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add,","SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj'","dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal remote dependencies when building') parser.add_argument('build_actions', help=\"Extra actions to","rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src, dest] print('installing","%s' % ' '.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\"generate-xcodeproj\", args.build_actions): print(\"**","% (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for rpath in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for","install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Installing %s failed'","rebuilt if it has already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] =","= os.path.join(bin_dir, product) # Create a copy of the list since we modify","install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Installing %s","'.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\"generate-xcodeproj\", args.build_actions): print(\"** Generating Xcode project","**\" % package_name) stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix,","if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action == 'test': args.extend(['--test-product', product]) else: args.extend(['--product', product])","return '\"%s\"' % arg.replace('\"', '\\\\\"') else: return arg def get_products(package_dir): # FIXME: We","True elif \"all\" in selected_actions: return True else: return False def update_swiftpm_dependencies(package_dir, swift_exec,","'package', '--package-path', package_dir, '--build-path', build_dir, 'update'] check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec, action,","building this package') parser.add_argument('--update', action='store_true', help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal","printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\"test\", args.build_actions): print(\"** Testing %s **\"","print(\"** Generating Xcode project for %s **\" % package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath,","sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Testing %s","return True return False def should_run_action(action_name, selected_actions): if action_name in selected_actions: return True","if (\"install\" in parsed.build_actions or \"all\" in parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\"'--prefix' is","def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose): args = [swift_exec, 'package', '--package-path', package_dir, '--build-path',","the other. for product in products: invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file,","['sk-stress-test', 'swift-evolve']: # Make the rpath to sourcekitd relative in the toolchain rpaths_to_delete_for_this_product","env=os.environ, **kwargs): if verbose: print(' '.join([escape_cmd_arg(arg) for arg in cmd])) return subprocess.check_call(cmd, env=env,","own build. No need to build if we are just testing if should_run_any_action(['build',","selected_actions): for action_name in action_names: if should_run_action(action_name, selected_actions): return True return False def","in [bin_dir, lib_dir]: if not os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test and sk-swiftc-wrapper for","return True else: return False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose): args =","% package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL:","product in products: invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose)","'install', 'generate-xcodeproj'], nargs=\"*\", default=['build']) parsed = parser.parse_args(args) if (\"install\" in parsed.build_actions or \"all\"","Until rdar://53881101 is implemented, we cannot request a build of multiple # targets","For now, just build one product after the other. for product in products:","for license information See https://swift.org/CONTRIBUTORS.txt for the list of Swift project authors ------------------------------------------------------------------------------","'lib') # Convert package_dir to absolute path, relative to root of repo. repo_path","build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Testing %s failed'","invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as","Exception See https://swift.org/LICENSE.txt for license information See https://swift.org/CONTRIBUTORS.txt for the list of Swift","build if we are just testing if should_run_any_action(['build', 'install'], args.build_actions): print(\"** Building %s","swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError","rpath, verbose=verbose) for rpath in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath,","Tell SwiftSyntax that we are building in a build-script environment so that #","'-add_rpath', rpath, binary] check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-delete_rpath',","help=\"Extra actions to perform. Can be any number of the following\", choices=['all', 'build',","build_dir, multiroot_data_file, config, env, verbose): args = [swift_exec, action, '--package-path', package_dir, '-c', config,","out next sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \"1\" if args.update: print(\"** Updating","for action_name in action_names: if should_run_action(action_name, selected_actions): return True return False def should_run_action(action_name,","<filename>build-script-helper.py #!/usr/bin/env python \"\"\" This source file is part of the Swift.org open","subprocess.CalledProcessError as e: printerr('FAIL: Building %s failed' % package_name) printerr('Executing: %s' % '","except subprocess.CalledProcessError as e: printerr('FAIL: Building %s failed' % package_name) printerr('Executing: %s' %","**\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file,","parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\"'--prefix' is required with the install action\") parsed.swift_exec =","= os.path.join(install_dir, 'lib', 'swift', 'macosx') for directory in [bin_dir, lib_dir]: if not os.path.exists(directory):","package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Testing","parser.add_argument('--multiroot-data-file', help='Path to an Xcode workspace to create a unified build of SwiftSyntax","= {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' %","swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose) def invoke_swift_single_product(package_dir, swift_exec, action,","sk-stress-test and sk-swiftc-wrapper for product in get_products(package_dir): src = os.path.join(build_dir, product) dest =","package_name) stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir,","os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\"generate-xcodeproj\", args.build_actions): print(\"** Generating Xcode project for %s **\" %","'--verbose', action='store_true', help='log executed commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file',","Copyright (c) 2014 - 2018 Apple Inc. and the Swift project authors Licensed","except subprocess.CalledProcessError as e: printerr('FAIL: Generating the Xcode project failed') printerr('Executing: %s' %","Apple Inc. and the Swift project authors Licensed under Apache License v2.0 with","'update'] check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath, build_dir, multiroot_data_file, config,","sourcekitd relative in the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src, dest,","action, products, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): # Until rdar://53881101 is implemented,","printerr('FAIL: Testing %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if","after the other. for product in products: invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir,","[item for pair in zip([value] * len(list), list) for item in pair] def","as e: printerr('FAIL: Building %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd))","to %s' % (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for rpath in rpaths_to_delete: remove_rpath(dest, rpath,","true if any of the actions in `action_names` should be run. def should_run_any_action(action_names,","when building') parser.add_argument('build_actions', help=\"Extra actions to perform. Can be any number of the","' in arg: return '\"%s\"' % arg.replace('\"', '\\\\\"') else: return arg def get_products(package_dir):","help='log executed commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to","**\" % package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e:","parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to an Xcode workspace to create a unified build","multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Testing %s failed' %","remote dependencies when building') parser.add_argument('build_actions', help=\"Extra actions to perform. Can be any number","\"\"\" This source file is part of the Swift.org open source project Copyright","projects.') parser.add_argument('--toolchain', required=True, help='the toolchain to use when building this package') parser.add_argument('--update', action='store_true',","(os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for rpath in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for rpath","failed') printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\"test\", args.build_actions): print(\"** Testing %s","verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Generating the Xcode project failed') printerr('Executing: %s'","= [swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args, env=env, verbose=verbose)","'.join(e.cmd)) sys.exit(1) # The test action creates its own build. No need to","products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Building","' '.join(e.cmd)) sys.exit(1) if should_run_action(\"install\", args.build_actions): print(\"** Installing %s **\" % package_name) stdlib_dir","os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except","authors ------------------------------------------------------------------------------ This is a helper script for the main swift repository's build-script.py","dependencies when building') parser.add_argument('build_actions', help=\"Extra actions to perform. Can be any number of","env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env, verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath,","for %s **\" % package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError","parser.add_argument('--update', action='store_true', help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal remote dependencies when","config, env, verbose): args = [swift_exec, action, '--package-path', package_dir, '-c', config, '--build-path', build_dir]","cmd = ['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath, verbose): cmd","not need to rebuilt if it has already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] =","ArgumentParser.error(\"'--prefix' is required with the install action\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin', 'swift')","# Install sk-stress-test and sk-swiftc-wrapper for product in get_products(package_dir): src = os.path.join(build_dir, product)","file=sys.stderr) def main(argv_prefix = []): args = parse_args(argv_prefix + sys.argv[1:]) run(args) def parse_args(args):","'usr', 'lib', 'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError","not parsed.prefix: ArgumentParser.error(\"'--prefix' is required with the install action\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr',","https://swift.org/CONTRIBUTORS.txt for the list of Swift project authors ------------------------------------------------------------------------------ This is a helper","in parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\"'--prefix' is required with the install action\") parsed.swift_exec","rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src, dest] print('installing %s to %s' % (os.path.basename(src), dest))","stdlib in in the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test', 'swift-evolve']:","path, relative to root of repo. repo_path = os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path,","relative to package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name","**kwargs) def interleave(value, list): return [item for pair in zip([value] * len(list), list)","Create a copy of the list since we modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete)","config, env, verbose): # Until rdar://53881101 is implemented, we cannot request a build","to query SwiftPM for this info. if package_dir.endswith(\"/SourceKitStressTester\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\"/SwiftEvolve\"):","executed commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to an","[swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args, env=env, verbose=verbose) def","parsed.prefix: ArgumentParser.error(\"'--prefix' is required with the install action\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin',","\"all\" in selected_actions: return True else: return False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env,","sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose) def invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir,","'generate-xcodeproj'], nargs=\"*\", default=['build']) parsed = parser.parse_args(args) if (\"install\" in parsed.build_actions or \"all\" in","% arg.replace('\"', '\\\\\"') else: return arg def get_products(package_dir): # FIXME: We ought to","= []): args = parse_args(argv_prefix + sys.argv[1:]) run(args) def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY')","' '.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\"generate-xcodeproj\", args.build_actions): print(\"** Generating Xcode","License v2.0 with Runtime Library Exception See https://swift.org/LICENSE.txt for license information See https://swift.org/CONTRIBUTORS.txt","package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\"install\", args.build_actions): print(\"** Installing %s","Returns true if any of the actions in `action_names` should be run. def","# Use local dependencies (i.e. checked out next sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS']","build one product after the other. for product in products: invoke_swift_single_product(package_dir, swift_exec, action,","subprocess.CalledProcessError as e: printerr('FAIL: Updating dependencies of %s failed' % package_name) printerr('Executing: %s'","to the stdlib in in the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product in","= os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS","https://swift.org/LICENSE.txt for license information See https://swift.org/CONTRIBUTORS.txt for the list of Swift project authors","args.config)) if should_run_action(\"generate-xcodeproj\", args.build_actions): print(\"** Generating Xcode project for %s **\" % package_name)","the install action\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr',","Can be any number of the following\", choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'], nargs=\"*\",","config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path =","dependencies of %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) #","def should_run_any_action(action_names, selected_actions): for action_name in action_names: if should_run_action(action_name, selected_actions): return True return","swift workspace. \"\"\" from __future__ import print_function import argparse import sys import os,","modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add the rpath to the stdlib in","action\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib') #","package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir)","subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value, list): return [item for pair in zip([value]","% ' '.join(e.cmd)) sys.exit(1) # The test action creates its own build. No","not os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test and sk-swiftc-wrapper for product in get_products(package_dir): src","'build', 'test', 'install', 'generate-xcodeproj'], nargs=\"*\", default=['build']) parsed = parser.parse_args(args) if (\"install\" in parsed.build_actions","build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Updating dependencies of %s failed'","package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # The test action creates its","arg def get_products(package_dir): # FIXME: We ought to be able to query SwiftPM","rpaths_to_add += ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest, rpaths_to_delete, rpaths_to_add,","%s' % ' '.join(e.cmd)) sys.exit(1) # The test action creates its own build.","of multiple # targets simultaneously. For now, just build one product after the","SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal remote dependencies when building') parser.add_argument('build_actions', help=\"Extra actions","rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir, 'lib', 'swift', 'macosx') for","#!/usr/bin/env python \"\"\" This source file is part of the Swift.org open source","if should_run_action(\"generate-xcodeproj\", args.build_actions): print(\"** Generating Xcode project for %s **\" % package_name) try:","rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src,","if args.update: print(\"** Updating dependencies of %s **\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec,","is implemented, we cannot request a build of multiple # targets simultaneously. For","repo_path = os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert build_dir to absolute","args.extend(['--product', product]) # Tell SwiftSyntax that we are building in a build-script environment","verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Installing %s failed' % package_name) printerr('Executing: %s'","Testing %s **\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath,","Generating Xcode project for %s **\" % package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env,","for product in get_products(package_dir): src = os.path.join(build_dir, product) dest = os.path.join(bin_dir, product) #","parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib') # Convert","= os.path.join(build_dir, product) dest = os.path.join(bin_dir, product) # Create a copy of the","config, env, verbose) def invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env,","in parsed.build_actions or \"all\" in parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\"'--prefix' is required with","build_dir to absolute path, relative to package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return parsed","not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \"1\" if args.update: print(\"** Updating dependencies of %s **\"","= os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib') # Convert package_dir","helper script for the main swift repository's build-script.py that knows how to build","verbose=verbose) def remove_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose)","product after the other. for product in products: invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath,","a unified build of SwiftSyntax with other projects.') parser.add_argument('--toolchain', required=True, help='the toolchain to","a build-script environment so that # it does not need to rebuilt if","relative to root of repo. repo_path = os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir))","args.extend(['--multiroot-data-file', multiroot_data_file]) if action == 'test': args.extend(['--test-product', product]) else: args.extend(['--product', product]) # Tell","verbose=verbose) for rpath in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env,","open(config_path, 'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited)","%s **\" % package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError as","# Tell SwiftSyntax that we are building in a build-script environment so that","False def should_run_action(action_name, selected_actions): if action_name in selected_actions: return True elif \"all\" in","package') parser.add_argument('--update', action='store_true', help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal remote dependencies","build of SwiftSyntax with other projects.') parser.add_argument('--toolchain', required=True, help='the toolchain to use when","normal remote dependencies when building') parser.add_argument('build_actions', help=\"Extra actions to perform. Can be any","in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for rpath in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def","verbose): args = [swift_exec, 'package', '--package-path', package_dir, '--build-path', build_dir, 'update'] check_call(args, env=env, verbose=verbose)","to absolute path, relative to root of repo. repo_path = os.path.dirname(__file__) parsed.package_dir =","if should_run_action(action_name, selected_actions): return True return False def should_run_action(action_name, selected_actions): if action_name in","config_path, '--output', xcodeproj_path] check_call(args, env=env, verbose=verbose) def add_rpath(binary, rpath, verbose): cmd = ['install_name_tool',","['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test', 'swift-evolve']: # Make the rpath to sourcekitd relative","args = parse_args(argv_prefix + sys.argv[1:]) run(args) def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester')","2014 - 2018 Apple Inc. and the Swift project authors Licensed under Apache","len(list), list) for item in pair] def escape_cmd_arg(arg): if '\"' in arg or","args.update: print(\"** Updating dependencies of %s **\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir,","file is part of the Swift.org open source project Copyright (c) 2014 -","'--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args, env=env, verbose=verbose) def add_rpath(binary, rpath, verbose): cmd =","of the Swift.org open source project Copyright (c) 2014 - 2018 Apple Inc.","or ' ' in arg: return '\"%s\"' % arg.replace('\"', '\\\\\"') else: return arg","# Returns true if any of the actions in `action_names` should be run.","# Make the rpath to sourcekitd relative in the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath]","[]): args = parse_args(argv_prefix + sys.argv[1:]) run(args) def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir',","repository's build-script.py that knows how to build and install the stress tester utilities","os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS =","['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath, verbose): cmd = ['install_name_tool',","action_name in selected_actions: return True elif \"all\" in selected_actions: return True else: return","in selected_actions: return True else: return False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose):","products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e:","import argparse import sys import os, platform import subprocess def printerr(message): print(message, file=sys.stderr)","it has already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args,","' '.join(e.cmd)) sys.exit(1) # The test action creates its own build. No need","We ought to be able to query SwiftPM for this info. if package_dir.endswith(\"/SourceKitStressTester\"):","args.build_actions): print(\"** Generating Xcode project for %s **\" % package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec,","rpath to the stdlib in in the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product","this info. if package_dir.endswith(\"/SourceKitStressTester\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\"/SwiftEvolve\"): return ['swift-evolve'] else: return","def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose): package_name = os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig')","rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose): package_name = os.path.basename(package_dir) config_path =","tester utilities given a swift workspace. \"\"\" from __future__ import print_function import argparse","in a build-script environment so that # it does not need to rebuilt","the following\", choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'], nargs=\"*\", default=['build']) parsed = parser.parse_args(args) if","src = os.path.join(build_dir, product) dest = os.path.join(bin_dir, product) # Create a copy of","building in a build-script environment so that # it does not need to","verbose=verbose) def install(src, dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src, dest] print('installing %s","$(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' % package_name) args","argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log executed commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config',","default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log executed commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir',","= parser.parse_args(args) if (\"install\" in parsed.build_actions or \"all\" in parsed.build_actions) and not parsed.prefix:","given a swift workspace. \"\"\" from __future__ import print_function import argparse import sys","product]) else: args.extend(['--product', product]) # Tell SwiftSyntax that we are building in a","verbose) def invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): args","a build of multiple # targets simultaneously. For now, just build one product","print(' '.join([escape_cmd_arg(arg) for arg in cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value,","item in pair] def escape_cmd_arg(arg): if '\"' in arg or ' ' in","Building %s **\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file,","['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync',","environment so that # it does not need to rebuilt if it has","+= [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest,","= \"1\" if args.update: print(\"** Updating dependencies of %s **\" % package_name) try:","dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src, dest] print('installing %s to %s' %","following\", choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'], nargs=\"*\", default=['build']) parsed = parser.parse_args(args) if (\"install\"","print(\"** Building %s **\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir,","actions in `action_names` should be run. def should_run_any_action(action_names, selected_actions): for action_name in action_names:","the list since we modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add the rpath","package_dir, '--build-path', build_dir, 'update'] check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath,","install action\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib')","the rpath to sourcekitd relative in the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add +=","% package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose)","if it has already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath","to sourcekitd relative in the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src,","dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src,","'install'], args.build_actions): print(\"** Building %s **\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir),","%s **\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config,","package_dir.endswith(\"/SourceKitStressTester\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\"/SwiftEvolve\"): return ['swift-evolve'] else: return [] if __name__","try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Installing","'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args, env=env, verbose=verbose) def add_rpath(binary,","'sk-swiftc-wrapper'] elif package_dir.endswith(\"/SwiftEvolve\"): return ['swift-evolve'] else: return [] if __name__ == '__main__': main()","% package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if","install the stress tester utilities given a swift workspace. \"\"\" from __future__ import","if should_run_any_action(['build', 'install'], args.build_actions): print(\"** Building %s **\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec,","2018 Apple Inc. and the Swift project authors Licensed under Apache License v2.0","Installing %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # Returns","% package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # Returns true if any","os.path.join(repo_path, parsed.package_dir)) # Convert build_dir to absolute path, relative to package_dir. parsed.build_dir =","it does not need to rebuilt if it has already been built before.","failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # Returns true if","argparse import sys import os, platform import subprocess def printerr(message): print(message, file=sys.stderr) def","= os.path.join(parsed.toolchain, 'usr', 'lib') # Convert package_dir to absolute path, relative to root","multiroot_data_file, config, env, verbose): args = [swift_exec, action, '--package-path', package_dir, '-c', config, '--build-path',","# Convert package_dir to absolute path, relative to root of repo. repo_path =","# Create a copy of the list since we modify it rpaths_to_delete_for_this_product =","verbose): copy_cmd=['rsync', '-a', src, dest] print('installing %s to %s' % (os.path.basename(src), dest)) check_call(copy_cmd,","that knows how to build and install the stress tester utilities given a","action_name in action_names: if should_run_action(action_name, selected_actions): return True return False def should_run_action(action_name, selected_actions):","= os.path.basename(args.package_dir) env = dict(os.environ) # Use local dependencies (i.e. checked out next","product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose) def invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath,","selected_actions: return True elif \"all\" in selected_actions: return True else: return False def","be any number of the following\", choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'], nargs=\"*\", default=['build'])","the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test', 'swift-evolve']: # Make the","' '.join(e.cmd)) sys.exit(1) if should_run_action(\"test\", args.build_actions): print(\"** Testing %s **\" % package_name) try:","from __future__ import print_function import argparse import sys import os, platform import subprocess","= os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir, 'lib', 'swift', 'macosx') for directory in [bin_dir,","os.path.basename(args.package_dir) env = dict(os.environ) # Use local dependencies (i.e. checked out next sourcekit-lsp).","in get_products(package_dir): src = os.path.join(build_dir, product) dest = os.path.join(bin_dir, product) # Create a","= argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log executed commands') parser.add_argument('--prefix', help='install path')","# Add the rpath to the stdlib in in the toolchain rpaths_to_add =","dependencies of %s **\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except","verbose: print(' '.join([escape_cmd_arg(arg) for arg in cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def","def interleave(value, list): return [item for pair in zip([value] * len(list), list) for","in action_names: if should_run_action(action_name, selected_actions): return True return False def should_run_action(action_name, selected_actions): if","with the install action\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain,","subprocess.CalledProcessError as e: printerr('FAIL: Generating the Xcode project failed') printerr('Executing: %s' % '","verbose=verbose) def add_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd, verbose=verbose)","so that # it does not need to rebuilt if it has already","next sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \"1\" if args.update: print(\"** Updating dependencies","simultaneously. For now, just build one product after the other. for product in","path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to an Xcode workspace to create","action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): args = [swift_exec, action, '--package-path',","def check_call(cmd, verbose, env=os.environ, **kwargs): if verbose: print(' '.join([escape_cmd_arg(arg) for arg in cmd]))","source project Copyright (c) 2014 - 2018 Apple Inc. and the Swift project","path, relative to package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir","lib_dir = os.path.join(install_dir, 'lib', 'swift', 'macosx') for directory in [bin_dir, lib_dir]: if not","os.path.join(install_dir, 'lib', 'swift', 'macosx') for directory in [bin_dir, lib_dir]: if not os.path.exists(directory): os.makedirs(directory)","args.build_actions): print(\"** Testing %s **\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' %","return False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose): args = [swift_exec, 'package', '--package-path',","for rpath in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for rpath in rpaths_to_add: add_rpath(dest, rpath,","one product after the other. for product in products: invoke_swift_single_product(package_dir, swift_exec, action, product,","sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): args = [swift_exec, action, '--package-path', package_dir, '-c',","%s **\" % package_name) stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx') try: install_package(args.package_dir,","in selected_actions: return True elif \"all\" in selected_actions: return True else: return False","printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # Returns true if any of the","of the list since we modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add the","env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Building %s failed' % package_name) printerr('Executing:","try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose)","= os.path.join(parsed.package_dir, parsed.build_dir) return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env =","'--package-path', package_dir, '--build-path', build_dir, 'update'] check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec, action, products,","dest)) check_call(copy_cmd, verbose=verbose) for rpath in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for rpath in","else: return False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose): args = [swift_exec, 'package',","rpath, verbose): cmd = ['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose) def check_call(cmd, verbose,","print(\"** Testing %s **\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name],","[swift_exec, action, '--package-path', package_dir, '-c', config, '--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if","{sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' % package_name)","invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except","__future__ import print_function import argparse import sys import os, platform import subprocess def","xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' % package_name) args = [swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj',","platform import subprocess def printerr(message): print(message, file=sys.stderr) def main(argv_prefix = []): args =","% package_name) stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath,","config, '--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action == 'test': args.extend(['--test-product', product])","before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env, verbose=verbose) def install_package(package_dir, install_dir,","implemented, we cannot request a build of multiple # targets simultaneously. For now,","Building %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) output_dir =","package_name) args = [swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args,","we are building in a build-script environment so that # it does not","verbose=verbose) for rpath in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for rpath in rpaths_to_add: add_rpath(dest,","nargs=\"*\", default=['build']) parsed = parser.parse_args(args) if (\"install\" in parsed.build_actions or \"all\" in parsed.build_actions)","# FIXME: We ought to be able to query SwiftPM for this info.","multiroot_data_file, config, env, verbose) def invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config,","sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Generating the Xcode project failed')","%s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\"test\", args.build_actions): print(\"** Testing %s **\" %","we cannot request a build of multiple # targets simultaneously. For now, just","multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action == 'test': args.extend(['--test-product', product]) else: args.extend(['--product', product]) #","the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose)","its own build. No need to build if we are just testing if","'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib') # Convert package_dir to absolute path,","of the actions in `action_names` should be run. def should_run_any_action(action_names, selected_actions): for action_name","to absolute path, relative to package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return parsed def","are just testing if should_run_any_action(['build', 'install'], args.build_actions): print(\"** Building %s **\" % package_name)","check_call(cmd, verbose, env=os.environ, **kwargs): if verbose: print(' '.join([escape_cmd_arg(arg) for arg in cmd])) return","printerr(message): print(message, file=sys.stderr) def main(argv_prefix = []): args = parse_args(argv_prefix + sys.argv[1:]) run(args)","'\"' in arg or ' ' in arg: return '\"%s\"' % arg.replace('\"', '\\\\\"')","swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e:","is a helper script for the main swift repository's build-script.py that knows how","print_function import argparse import sys import os, platform import subprocess def printerr(message): print(message,","'swift-evolve']: # Make the rpath to sourcekitd relative in the toolchain rpaths_to_delete_for_this_product +=","dict(os.environ) # Use local dependencies (i.e. checked out next sourcekit-lsp). if not args.no_local_deps:","action creates its own build. No need to build if we are just","%s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir,","if action == 'test': args.extend(['--test-product', product]) else: args.extend(['--product', product]) # Tell SwiftSyntax that","with Runtime Library Exception See https://swift.org/LICENSE.txt for license information See https://swift.org/CONTRIBUTORS.txt for the","'swift', 'macosx') for directory in [bin_dir, lib_dir]: if not os.path.exists(directory): os.makedirs(directory) # Install","check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd,","%s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\"install\", args.build_actions):","[bin_dir, lib_dir]: if not os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test and sk-swiftc-wrapper for product","project failed') printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\"test\", args.build_actions): print(\"** Testing","verbose, env=os.environ, **kwargs): if verbose: print(' '.join([escape_cmd_arg(arg) for arg in cmd])) return subprocess.check_call(cmd,","license information See https://swift.org/CONTRIBUTORS.txt for the list of Swift project authors ------------------------------------------------------------------------------ This","verbose): package_name = os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w') as config_file:","commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to an Xcode","Updating dependencies of %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1)","['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose) def check_call(cmd, verbose, env=os.environ, **kwargs): if verbose:","if should_run_action(\"test\", args.build_actions): print(\"** Testing %s **\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test',","dependencies (i.e. checked out next sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \"1\" if","rpath, verbose): cmd = ['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath,","verbose): # Until rdar://53881101 is implemented, we cannot request a build of multiple","remove_rpath(dest, rpath, verbose=verbose) for rpath in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec,","product]) # Tell SwiftSyntax that we are building in a build-script environment so","help='the toolchain to use when building this package') parser.add_argument('--update', action='store_true', help='update all SwiftPM","% package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL:","install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a',","Updating dependencies of %s **\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose)","'--build-path', build_dir, 'update'] check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath, build_dir,","' '.join(e.cmd)) sys.exit(1) # Returns true if any of the actions in `action_names`","rdar://53881101 is implemented, we cannot request a build of multiple # targets simultaneously.","in products: invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose) def","failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config))","def get_products(package_dir): # FIXME: We ought to be able to query SwiftPM for","%s' % (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for rpath in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose)","generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose): package_name = os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig') with","if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \"1\" if args.update: print(\"** Updating dependencies of %s","build-script.py that knows how to build and install the stress tester utilities given","config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Building %s failed' % package_name)","selected_actions: return True else: return False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose): args","or \"all\" in parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\"'--prefix' is required with the install","def install(src, dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src, dest] print('installing %s to","arg.replace('\"', '\\\\\"') else: return arg def get_products(package_dir): # FIXME: We ought to be","build_dir, multiroot_data_file, config, env, verbose) def invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file,","to package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name =","printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\"generate-xcodeproj\", args.build_actions):","need to build if we are just testing if should_run_any_action(['build', 'install'], args.build_actions): print(\"**","def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log executed commands')","action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL:","install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir, 'lib',","parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log executed commands') parser.add_argument('--prefix',","sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \"1\" if args.update: print(\"** Updating dependencies of","return arg def get_products(package_dir): # FIXME: We ought to be able to query","== 'test': args.extend(['--test-product', product]) else: args.extend(['--product', product]) # Tell SwiftSyntax that we are","under Apache License v2.0 with Runtime Library Exception See https://swift.org/LICENSE.txt for license information","invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): # Until rdar://53881101","cannot request a build of multiple # targets simultaneously. For now, just build","toolchain to use when building this package') parser.add_argument('--update', action='store_true', help='update all SwiftPM dependencies')","{sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' % package_name) args = [swift_exec, 'package',","Make the rpath to sourcekitd relative in the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add","swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): args = [swift_exec, action,","authors Licensed under Apache License v2.0 with Runtime Library Exception See https://swift.org/LICENSE.txt for","number of the following\", choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'], nargs=\"*\", default=['build']) parsed =","pair in zip([value] * len(list), list) for item in pair] def escape_cmd_arg(arg): if","choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'], nargs=\"*\", default=['build']) parsed = parser.parse_args(args) if (\"install\" in","print(\"** Installing %s **\" % package_name) stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx')","multiroot_data_file, config, env, verbose): # Until rdar://53881101 is implemented, we cannot request a","env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Generating the Xcode project failed') printerr('Executing:","for pair in zip([value] * len(list), list) for item in pair] def escape_cmd_arg(arg):","create a unified build of SwiftSyntax with other projects.') parser.add_argument('--toolchain', required=True, help='the toolchain","parser.add_argument('--no-local-deps', action='store_true', help='use normal remote dependencies when building') parser.add_argument('build_actions', help=\"Extra actions to perform.","the stress tester utilities given a swift workspace. \"\"\" from __future__ import print_function","dest] print('installing %s to %s' % (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for rpath in","env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value, list): return [item for pair in zip([value] *","= os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited)","return True elif \"all\" in selected_actions: return True else: return False def update_swiftpm_dependencies(package_dir,","verbose): cmd = ['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath, verbose):","product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): args = [swift_exec, action, '--package-path', package_dir,","'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath))","sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env = dict(os.environ) # Use local dependencies (i.e. checked","arg or ' ' in arg: return '\"%s\"' % arg.replace('\"', '\\\\\"') else: return","now, just build one product after the other. for product in products: invoke_swift_single_product(package_dir,","print(message, file=sys.stderr) def main(argv_prefix = []): args = parse_args(argv_prefix + sys.argv[1:]) run(args) def","build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action == 'test': args.extend(['--test-product', product]) else: args.extend(['--product',","'usr', 'lib') # Convert package_dir to absolute path, relative to root of repo.","'bin') lib_dir = os.path.join(install_dir, 'lib', 'swift', 'macosx') for directory in [bin_dir, lib_dir]: if","product in get_products(package_dir): src = os.path.join(build_dir, product) dest = os.path.join(bin_dir, product) # Create","env, verbose): args = [swift_exec, 'package', '--package-path', package_dir, '--build-path', build_dir, 'update'] check_call(args, env=env,","for rpath in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose):","os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir, 'lib', 'swift', 'macosx') for directory in [bin_dir, lib_dir]:","use when building this package') parser.add_argument('--update', action='store_true', help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true',","check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath, build_dir, multiroot_data_file, config, env,","package_dir, '-c', config, '--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action == 'test':","part of the Swift.org open source project Copyright (c) 2014 - 2018 Apple","project for %s **\" % package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except","package_name = os.path.basename(args.package_dir) env = dict(os.environ) # Use local dependencies (i.e. checked out","for this info. if package_dir.endswith(\"/SourceKitStressTester\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\"/SwiftEvolve\"): return ['swift-evolve'] else:","print('installing %s to %s' % (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for rpath in rpaths_to_delete:","sourcekit_searchpath check_call(args, env=env, verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir =","sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\"generate-xcodeproj\", args.build_actions): print(\"** Generating Xcode project for","'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib') # Convert package_dir to absolute path, relative","with other projects.') parser.add_argument('--toolchain', required=True, help='the toolchain to use when building this package')","action='store_true', help='log executed commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path","[swift_exec, 'package', '--package-path', package_dir, '--build-path', build_dir, 'update'] check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec,","args = [swift_exec, action, '--package-path', package_dir, '-c', config, '--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file',","Convert package_dir to absolute path, relative to root of repo. repo_path = os.path.dirname(__file__)","= ['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath, verbose): cmd =","should be run. def should_run_any_action(action_names, selected_actions): for action_name in action_names: if should_run_action(action_name, selected_actions):","relative in the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product,","SwiftSyntax that we are building in a build-script environment so that # it","FIXME: We ought to be able to query SwiftPM for this info. if","Convert build_dir to absolute path, relative to package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return","parsed.build_dir) return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env = dict(os.environ) #","the rpath to the stdlib in in the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if","in ['sk-stress-test', 'swift-evolve']: # Make the rpath to sourcekitd relative in the toolchain","\"1\" if args.update: print(\"** Updating dependencies of %s **\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir,","e: printerr('FAIL: Installing %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1)","'--output', xcodeproj_path] check_call(args, env=env, verbose=verbose) def add_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-add_rpath',","swift_exec, sourcekit_searchpath, env, verbose): package_name = os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig') with open(config_path,","script for the main swift repository's build-script.py that knows how to build and","Swift.org open source project Copyright (c) 2014 - 2018 Apple Inc. and the","except subprocess.CalledProcessError as e: printerr('FAIL: Testing %s failed' % package_name) printerr('Executing: %s' %","parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib') # Convert package_dir to absolute path, relative to","action='store_true', help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal remote dependencies when building')","parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env","update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose): args = [swift_exec, 'package', '--package-path', package_dir, '--build-path', build_dir,","sys.exit(1) if should_run_action(\"test\", args.build_actions): print(\"** Testing %s **\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec,","rpath in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose): package_name","query SwiftPM for this info. if package_dir.endswith(\"/SourceKitStressTester\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\"/SwiftEvolve\"): return","root of repo. repo_path = os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert","%s **\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError as","actions to perform. Can be any number of the following\", choices=['all', 'build', 'test',","verbose=verbose) def check_call(cmd, verbose, env=os.environ, **kwargs): if verbose: print(' '.join([escape_cmd_arg(arg) for arg in","return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\"/SwiftEvolve\"): return ['swift-evolve'] else: return [] if __name__ ==","printerr('FAIL: Building %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) output_dir","subprocess def printerr(message): print(message, file=sys.stderr) def main(argv_prefix = []): args = parse_args(argv_prefix +","(c) 2014 - 2018 Apple Inc. and the Swift project authors Licensed under","built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env, verbose=verbose) def install_package(package_dir,","= dict(os.environ) # Use local dependencies (i.e. checked out next sourcekit-lsp). if not","def escape_cmd_arg(arg): if '\"' in arg or ' ' in arg: return '\"%s\"'","swift_exec, build_dir, env, verbose): args = [swift_exec, 'package', '--package-path', package_dir, '--build-path', build_dir, 'update']","a helper script for the main swift repository's build-script.py that knows how to","rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for rpath in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir,","to build and install the stress tester utilities given a swift workspace. \"\"\"","= os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert build_dir to absolute path, relative to package_dir.","output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\"generate-xcodeproj\", args.build_actions): print(\"** Generating Xcode project for %s","def add_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd, verbose=verbose) def","any number of the following\", choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'], nargs=\"*\", default=['build']) parsed","stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir],","to use when building this package') parser.add_argument('--update', action='store_true', help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps',","is required with the install action\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir","No need to build if we are just testing if should_run_any_action(['build', 'install'], args.build_actions):","as e: printerr('FAIL: Testing %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd))","build. No need to build if we are just testing if should_run_any_action(['build', 'install'],","rpath, binary] check_call(cmd, verbose=verbose) def check_call(cmd, verbose, env=os.environ, **kwargs): if verbose: print(' '.join([escape_cmd_arg(arg)","of Swift project authors ------------------------------------------------------------------------------ This is a helper script for the main","% ' '.join(e.cmd)) sys.exit(1) # Returns true if any of the actions in","verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir, 'bin') lib_dir","args = [swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args, env=env,","of %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # The","the list of Swift project authors ------------------------------------------------------------------------------ This is a helper script for","def main(argv_prefix = []): args = parse_args(argv_prefix + sys.argv[1:]) run(args) def parse_args(args): parser","in arg: return '\"%s\"' % arg.replace('\"', '\\\\\"') else: return arg def get_products(package_dir): #","False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose): args = [swift_exec, 'package', '--package-path', package_dir,","able to query SwiftPM for this info. if package_dir.endswith(\"/SourceKitStressTester\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif","'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args, env=env, verbose=verbose) def add_rpath(binary, rpath, verbose): cmd","multiroot_data_file]) if action == 'test': args.extend(['--test-product', product]) else: args.extend(['--product', product]) # Tell SwiftSyntax","def remove_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose) def","parser.parse_args(args) if (\"install\" in parsed.build_actions or \"all\" in parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\"'--prefix'","`action_names` should be run. def should_run_any_action(action_names, selected_actions): for action_name in action_names: if should_run_action(action_name,","env['SWIFTCI_USE_LOCAL_DEPS'] = \"1\" if args.update: print(\"** Updating dependencies of %s **\" % package_name)","package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except","we are just testing if should_run_any_action(['build', 'install'], args.build_actions): print(\"** Building %s **\" %","verbose=verbose) def invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): #","that we are building in a build-script environment so that # it does","repo. repo_path = os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert build_dir to","if should_run_action(\"install\", args.build_actions): print(\"** Installing %s **\" % package_name) stdlib_dir = os.path.join(args.toolchain, 'usr',","pair] def escape_cmd_arg(arg): if '\"' in arg or ' ' in arg: return","in arg or ' ' in arg: return '\"%s\"' % arg.replace('\"', '\\\\\"') else:","parser.add_argument('build_actions', help=\"Extra actions to perform. Can be any number of the following\", choices=['all',","= os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\"generate-xcodeproj\", args.build_actions): print(\"** Generating Xcode project for %s **\"","action='store_true', help='use normal remote dependencies when building') parser.add_argument('build_actions', help=\"Extra actions to perform. Can","parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to an Xcode workspace","return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value, list): return [item for pair in","% package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\"install\", args.build_actions): print(\"** Installing","creates its own build. No need to build if we are just testing","stderr=subprocess.STDOUT, **kwargs) def interleave(value, list): return [item for pair in zip([value] * len(list),","sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir, 'lib', 'swift',","cmd = ['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose) def check_call(cmd, verbose, env=os.environ, **kwargs):","other. for product in products: invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config,","test action creates its own build. No need to build if we are","%s to %s' % (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for rpath in rpaths_to_delete: remove_rpath(dest,","Runtime Library Exception See https://swift.org/LICENSE.txt for license information See https://swift.org/CONTRIBUTORS.txt for the list","'-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose) def check_call(cmd, verbose, env=os.environ, **kwargs): if verbose: print('","'test', 'install', 'generate-xcodeproj'], nargs=\"*\", default=['build']) parsed = parser.parse_args(args) if (\"install\" in parsed.build_actions or","= [swift_exec, 'package', '--package-path', package_dir, '--build-path', build_dir, 'update'] check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir,","in `action_names` should be run. def should_run_any_action(action_names, selected_actions): for action_name in action_names: if","binary] check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-delete_rpath', rpath, binary]","'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL:","env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Testing %s failed' % package_name) printerr('Executing:","def should_run_action(action_name, selected_actions): if action_name in selected_actions: return True elif \"all\" in selected_actions:","selected_actions): return True return False def should_run_action(action_name, selected_actions): if action_name in selected_actions: return","multiple # targets simultaneously. For now, just build one product after the other.","rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test', 'swift-evolve']: # Make the rpath to","* len(list), list) for item in pair] def escape_cmd_arg(arg): if '\"' in arg","Swift project authors ------------------------------------------------------------------------------ This is a helper script for the main swift","help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to an Xcode workspace to","list(rpaths_to_delete) # Add the rpath to the stdlib in in the toolchain rpaths_to_add","for item in pair] def escape_cmd_arg(arg): if '\"' in arg or ' '","action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose) def invoke_swift_single_product(package_dir, swift_exec, action, product,","env=env, verbose=verbose) def add_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd,","absolute path, relative to package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return parsed def run(args):","verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose): package_name = os.path.basename(package_dir) config_path = os.path.join(package_dir,","import sys import os, platform import subprocess def printerr(message): print(message, file=sys.stderr) def main(argv_prefix","Use local dependencies (i.e. checked out next sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] =","python \"\"\" This source file is part of the Swift.org open source project","env=env, verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir, 'bin')","sys import os, platform import subprocess def printerr(message): print(message, file=sys.stderr) def main(argv_prefix =","(\"install\" in parsed.build_actions or \"all\" in parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\"'--prefix' is required","toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test', 'swift-evolve']: # Make the rpath","and sk-swiftc-wrapper for product in get_products(package_dir): src = os.path.join(build_dir, product) dest = os.path.join(bin_dir,","are building in a build-script environment so that # it does not need","package_dir to absolute path, relative to root of repo. repo_path = os.path.dirname(__file__) parsed.package_dir","config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir,","xcodeproj_path] check_call(args, env=env, verbose=verbose) def add_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-add_rpath', rpath,","build of multiple # targets simultaneously. For now, just build one product after","= os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert build_dir to absolute path,","= os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose)","env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose):","build-script environment so that # it does not need to rebuilt if it","Install sk-stress-test and sk-swiftc-wrapper for product in get_products(package_dir): src = os.path.join(build_dir, product) dest","should_run_action(\"test\", args.build_actions): print(\"** Testing %s **\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests'","absolute path, relative to root of repo. repo_path = os.path.dirname(__file__) parsed.package_dir = os.path.realpath(","sys.exit(1) # Returns true if any of the actions in `action_names` should be","verbose): cmd = ['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose) def check_call(cmd, verbose, env=os.environ,","if not os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test and sk-swiftc-wrapper for product in get_products(package_dir):","os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test and sk-swiftc-wrapper for product in get_products(package_dir): src =","for the main swift repository's build-script.py that knows how to build and install","printerr('FAIL: Updating dependencies of %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd))","% package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # The test action creates","import subprocess def printerr(message): print(message, file=sys.stderr) def main(argv_prefix = []): args = parse_args(argv_prefix","multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Building %s failed' %","arg: return '\"%s\"' % arg.replace('\"', '\\\\\"') else: return arg def get_products(package_dir): # FIXME:","os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert build_dir to absolute path, relative to package_dir. parsed.build_dir","return [item for pair in zip([value] * len(list), list) for item in pair]","os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib') # Convert package_dir to","open source project Copyright (c) 2014 - 2018 Apple Inc. and the Swift","install(src, dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src, dest] print('installing %s to %s'","interleave(value, list): return [item for pair in zip([value] * len(list), list) for item","rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Installing %s failed' % package_name) printerr('Executing:","add_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd, verbose=verbose) def remove_rpath(binary,","sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): # Until rdar://53881101 is implemented, we cannot","package_name = os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w') as config_file: config_file.write('''","default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to an Xcode workspace to create a unified","help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal remote dependencies when building') parser.add_argument('build_actions',","= ['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose) def check_call(cmd, verbose, env=os.environ, **kwargs): if","the Swift project authors Licensed under Apache License v2.0 with Runtime Library Exception","stress tester utilities given a swift workspace. \"\"\" from __future__ import print_function import","e: printerr('FAIL: Generating the Xcode project failed') printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1)","'1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env, verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete,","verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Building %s failed' % package_name) printerr('Executing: %s'","to build if we are just testing if should_run_any_action(['build', 'install'], args.build_actions): print(\"** Building","= [swift_exec, action, '--package-path', package_dir, '-c', config, '--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file])","'%s.xcodeproj' % package_name) args = [swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output',","local dependencies (i.e. checked out next sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \"1\"","import os, platform import subprocess def printerr(message): print(message, file=sys.stderr) def main(argv_prefix = []):","args = [swift_exec, 'package', '--package-path', package_dir, '--build-path', build_dir, 'update'] check_call(args, env=env, verbose=verbose) def","the actions in `action_names` should be run. def should_run_any_action(action_names, selected_actions): for action_name in","= os.path.join(package_dir, '%s.xcodeproj' % package_name) args = [swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides',","we modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add the rpath to the stdlib","default=['build']) parsed = parser.parse_args(args) if (\"install\" in parsed.build_actions or \"all\" in parsed.build_actions) and","when building this package') parser.add_argument('--update', action='store_true', help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use","unified build of SwiftSyntax with other projects.') parser.add_argument('--toolchain', required=True, help='the toolchain to use","that # it does not need to rebuilt if it has already been","e: printerr('FAIL: Building %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1)","as e: printerr('FAIL: Installing %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd))","parsed.build_actions or \"all\" in parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\"'--prefix' is required with the","action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as","install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir,","elif \"all\" in selected_actions: return True else: return False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir,","with open(config_path, 'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath}","package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Updating","**\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e:","return False def should_run_action(action_name, selected_actions): if action_name in selected_actions: return True elif \"all\"","run. def should_run_any_action(action_names, selected_actions): for action_name in action_names: if should_run_action(action_name, selected_actions): return True","env, verbose) def invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose):","this package') parser.add_argument('--update', action='store_true', help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal remote","utilities given a swift workspace. \"\"\" from __future__ import print_function import argparse import","See https://swift.org/LICENSE.txt for license information See https://swift.org/CONTRIBUTORS.txt for the list of Swift project","args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \"1\" if args.update: print(\"** Updating dependencies of %s **\" %","%s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # Returns true","build_dir, env, verbose): args = [swift_exec, 'package', '--package-path', package_dir, '--build-path', build_dir, 'update'] check_call(args,","= {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' % package_name) args = [swift_exec,","'-a', src, dest] print('installing %s to %s' % (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for","try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Updating dependencies","package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env,","check_call(args, env=env, verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir,","os, platform import subprocess def printerr(message): print(message, file=sys.stderr) def main(argv_prefix = []): args","for the list of Swift project authors ------------------------------------------------------------------------------ This is a helper script","to an Xcode workspace to create a unified build of SwiftSyntax with other","all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal remote dependencies when building') parser.add_argument('build_actions', help=\"Extra","sys.argv[1:]) run(args) def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log","for directory in [bin_dir, lib_dir]: if not os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test and","sys.exit(1) if should_run_action(\"install\", args.build_actions): print(\"** Installing %s **\" % package_name) stdlib_dir = os.path.join(args.toolchain,","the stdlib in in the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test',","in in the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test', 'swift-evolve']: #","Apache License v2.0 with Runtime Library Exception See https://swift.org/LICENSE.txt for license information See","% ' '.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\"generate-xcodeproj\", args.build_actions): print(\"** Generating","Add the rpath to the stdlib in in the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx']","remove_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose) def check_call(cmd,","directory in [bin_dir, lib_dir]: if not os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test and sk-swiftc-wrapper","cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value, list): return [item for pair","parser.add_argument('--toolchain', required=True, help='the toolchain to use when building this package') parser.add_argument('--update', action='store_true', help='update","= '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env, verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir,","dest = os.path.join(bin_dir, product) # Create a copy of the list since we","sk-swiftc-wrapper for product in get_products(package_dir): src = os.path.join(build_dir, product) dest = os.path.join(bin_dir, product)","env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env, verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose):","env = dict(os.environ) # Use local dependencies (i.e. checked out next sourcekit-lsp). if","run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env = dict(os.environ) # Use local dependencies (i.e.","os.makedirs(directory) # Install sk-stress-test and sk-swiftc-wrapper for product in get_products(package_dir): src = os.path.join(build_dir,","main(argv_prefix = []): args = parse_args(argv_prefix + sys.argv[1:]) run(args) def parse_args(args): parser =","os.path.join(parsed.toolchain, 'usr', 'lib') # Convert package_dir to absolute path, relative to root of","def invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): args =","to be able to query SwiftPM for this info. if package_dir.endswith(\"/SourceKitStressTester\"): return ['sk-stress-test',","bin_dir = os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir, 'lib', 'swift', 'macosx') for directory in","sourcekit_searchpath, env, verbose): package_name = os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w')","# targets simultaneously. For now, just build one product after the other. for","Testing %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\"install\",","%s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # The test","action, '--package-path', package_dir, '-c', config, '--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action","= list(rpaths_to_delete) # Add the rpath to the stdlib in in the toolchain","parse_args(argv_prefix + sys.argv[1:]) run(args) def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose',","% package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config,","config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Testing %s failed' % package_name)","Xcode project for %s **\" % package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose)","to create a unified build of SwiftSyntax with other projects.') parser.add_argument('--toolchain', required=True, help='the","be able to query SwiftPM for this info. if package_dir.endswith(\"/SourceKitStressTester\"): return ['sk-stress-test', 'sk-swiftc-wrapper']","required=True, help='the toolchain to use when building this package') parser.add_argument('--update', action='store_true', help='update all","verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Updating dependencies of %s failed' % package_name)","printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # The test action creates its own","swift_exec, action, products, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): # Until rdar://53881101 is","parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env = dict(os.environ) # Use local","build_dir, rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir, 'lib', 'swift', 'macosx')","escape_cmd_arg(arg): if '\"' in arg or ' ' in arg: return '\"%s\"' %","products: invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose) def invoke_swift_single_product(package_dir,","in pair] def escape_cmd_arg(arg): if '\"' in arg or ' ' in arg:","- 2018 Apple Inc. and the Swift project authors Licensed under Apache License","action_names: if should_run_action(action_name, selected_actions): return True return False def should_run_action(action_name, selected_actions): if action_name","rpath in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for rpath in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose)","update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Updating dependencies of","'Config.xcconfig') with open(config_path, 'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS =","rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src, dest] print('installing %s to %s' % (os.path.basename(src),","workspace. \"\"\" from __future__ import print_function import argparse import sys import os, platform","build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Building %s failed'","toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def","src, dest] print('installing %s to %s' % (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for rpath","is part of the Swift.org open source project Copyright (c) 2014 - 2018","'usr', 'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib') # Convert package_dir to absolute","[sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest, rpaths_to_delete,","as e: printerr('FAIL: Updating dependencies of %s failed' % package_name) printerr('Executing: %s' %","= sourcekit_searchpath check_call(args, env=env, verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir","info. if package_dir.endswith(\"/SourceKitStressTester\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\"/SwiftEvolve\"): return ['swift-evolve'] else: return []","\"all\" in parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\"'--prefix' is required with the install action\")","$(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' % package_name) args = [swift_exec, 'package', '--package-path',","of SwiftSyntax with other projects.') parser.add_argument('--toolchain', required=True, help='the toolchain to use when building","'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as e:","build and install the stress tester utilities given a swift workspace. \"\"\" from","Xcode project failed') printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\"test\", args.build_actions): print(\"**","sys.exit(1) # The test action creates its own build. No need to build","See https://swift.org/CONTRIBUTORS.txt for the list of Swift project authors ------------------------------------------------------------------------------ This is a","'''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' % package_name) args = [swift_exec, 'package', '--package-path', package_dir,","the Swift.org open source project Copyright (c) 2014 - 2018 Apple Inc. and","of the following\", choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'], nargs=\"*\", default=['build']) parsed = parser.parse_args(args)","return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env = dict(os.environ) # Use","'lib', 'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as","list): return [item for pair in zip([value] * len(list), list) for item in","knows how to build and install the stress tester utilities given a swift","just testing if should_run_any_action(['build', 'install'], args.build_actions): print(\"** Building %s **\" % package_name) try:","the Xcode project failed') printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\"test\", args.build_actions):","**kwargs): if verbose: print(' '.join([escape_cmd_arg(arg) for arg in cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT,","'.join([escape_cmd_arg(arg) for arg in cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value, list):","build_dir, 'update'] check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath, build_dir, multiroot_data_file,","list of Swift project authors ------------------------------------------------------------------------------ This is a helper script for the","been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env, verbose=verbose) def","should_run_action(action_name, selected_actions): return True return False def should_run_action(action_name, selected_actions): if action_name in selected_actions:","True return False def should_run_action(action_name, selected_actions): if action_name in selected_actions: return True elif","product) dest = os.path.join(bin_dir, product) # Create a copy of the list since","products, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): # Until rdar://53881101 is implemented, we","project Copyright (c) 2014 - 2018 Apple Inc. and the Swift project authors","need to rebuilt if it has already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1'","since we modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add the rpath to the","\"\"\" from __future__ import print_function import argparse import sys import os, platform import","%s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\"install\", args.build_actions): print(\"** Installing %s **\" %","printerr('FAIL: Installing %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) #","# Until rdar://53881101 is implemented, we cannot request a build of multiple #","if product in ['sk-stress-test', 'swift-evolve']: # Make the rpath to sourcekitd relative in","Licensed under Apache License v2.0 with Runtime Library Exception See https://swift.org/LICENSE.txt for license","env, verbose): args = [swift_exec, action, '--package-path', package_dir, '-c', config, '--build-path', build_dir] if","zip([value] * len(list), list) for item in pair] def escape_cmd_arg(arg): if '\"' in","'\"%s\"' % arg.replace('\"', '\\\\\"') else: return arg def get_products(package_dir): # FIXME: We ought","an Xcode workspace to create a unified build of SwiftSyntax with other projects.')","should_run_action(action_name, selected_actions): if action_name in selected_actions: return True elif \"all\" in selected_actions: return","just build one product after the other. for product in products: invoke_swift_single_product(package_dir, swift_exec,","+= ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest, rpaths_to_delete, rpaths_to_add, verbose):","check_call(args, env=env, verbose=verbose) def add_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-add_rpath', rpath, binary]","env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Updating dependencies of %s failed' %","invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose) def invoke_swift_single_product(package_dir, swift_exec,","run(args) def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log executed","parsed = parser.parse_args(args) if (\"install\" in parsed.build_actions or \"all\" in parsed.build_actions) and not","to rebuilt if it has already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH']","of repo. repo_path = os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert build_dir","source file is part of the Swift.org open source project Copyright (c) 2014","os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS","Inc. and the Swift project authors Licensed under Apache License v2.0 with Runtime","parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log executed commands') parser.add_argument('--prefix', help='install","arg in cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value, list): return [item","Swift project authors Licensed under Apache License v2.0 with Runtime Library Exception See","SwiftSyntax with other projects.') parser.add_argument('--toolchain', required=True, help='the toolchain to use when building this","'--package-path', package_dir, '-c', config, '--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action ==","os.path.join(package_dir, '%s.xcodeproj' % package_name) args = [swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path,","This source file is part of the Swift.org open source project Copyright (c)","get_products(package_dir): # FIXME: We ought to be able to query SwiftPM for this","ought to be able to query SwiftPM for this info. if package_dir.endswith(\"/SourceKitStressTester\"): return","sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Installing %s failed' %","to perform. Can be any number of the following\", choices=['all', 'build', 'test', 'install',","build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Installing %s failed' % package_name)","Installing %s **\" % package_name) stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx') try:","%s' % ' '.join(e.cmd)) sys.exit(1) # Returns true if any of the actions","'--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action == 'test': args.extend(['--test-product', product]) else:","def printerr(message): print(message, file=sys.stderr) def main(argv_prefix = []): args = parse_args(argv_prefix + sys.argv[1:])","package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Generating","------------------------------------------------------------------------------ This is a helper script for the main swift repository's build-script.py that","list since we modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add the rpath to","if verbose: print(' '.join([escape_cmd_arg(arg) for arg in cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs)","verbose): args = [swift_exec, action, '--package-path', package_dir, '-c', config, '--build-path', build_dir] if multiroot_data_file:","rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add the rpath to the stdlib in in the","v2.0 with Runtime Library Exception See https://swift.org/LICENSE.txt for license information See https://swift.org/CONTRIBUTORS.txt for","product in ['sk-stress-test', 'swift-evolve']: # Make the rpath to sourcekitd relative in the","get_products(package_dir): src = os.path.join(build_dir, product) dest = os.path.join(bin_dir, product) # Create a copy","a copy of the list since we modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete) #","sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Building %s","['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\"/SwiftEvolve\"): return ['swift-evolve'] else: return [] if __name__ == '__main__':","= parse_args(argv_prefix + sys.argv[1:]) run(args) def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v',","to root of repo. repo_path = os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir)) #","should_run_action(\"install\", args.build_actions): print(\"** Installing %s **\" % package_name) stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib',","'.join(e.cmd)) sys.exit(1) if should_run_action(\"install\", args.build_actions): print(\"** Installing %s **\" % package_name) stdlib_dir =","package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args, env=env, verbose=verbose) def add_rpath(binary, rpath, verbose):","failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # The test action","and the Swift project authors Licensed under Apache License v2.0 with Runtime Library","verbose): bin_dir = os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir, 'lib', 'swift', 'macosx') for directory","in cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value, list): return [item for","other projects.') parser.add_argument('--toolchain', required=True, help='the toolchain to use when building this package') parser.add_argument('--update',","os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert build_dir to absolute path, relative","(i.e. checked out next sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \"1\" if args.update:","workspace to create a unified build of SwiftSyntax with other projects.') parser.add_argument('--toolchain', required=True,","'.join(e.cmd)) sys.exit(1) if should_run_action(\"test\", args.build_actions): print(\"** Testing %s **\" % package_name) try: invoke_swift(package_dir=args.package_dir,","verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Testing %s failed' % package_name) printerr('Executing: %s'","env, verbose): package_name = os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w') as","True else: return False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose): args = [swift_exec,","generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Generating the Xcode","print(\"** Updating dependencies of %s **\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env,","import print_function import argparse import sys import os, platform import subprocess def printerr(message):","Library Exception See https://swift.org/LICENSE.txt for license information See https://swift.org/CONTRIBUTORS.txt for the list of","the main swift repository's build-script.py that knows how to build and install the","binary] check_call(cmd, verbose=verbose) def check_call(cmd, verbose, env=os.environ, **kwargs): if verbose: print(' '.join([escape_cmd_arg(arg) for","has already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env,","'lib', 'swift', 'macosx') for directory in [bin_dir, lib_dir]: if not os.path.exists(directory): os.makedirs(directory) #","parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert build_dir to absolute path, relative to","try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Generating the","+ sys.argv[1:]) run(args) def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true',","action == 'test': args.extend(['--test-product', product]) else: args.extend(['--product', product]) # Tell SwiftSyntax that we","package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # Returns true if any of","args.extend(['--test-product', product]) else: args.extend(['--product', product]) # Tell SwiftSyntax that we are building in","rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src, dest]","in zip([value] * len(list), list) for item in pair] def escape_cmd_arg(arg): if '\"'","project authors ------------------------------------------------------------------------------ This is a helper script for the main swift repository's","'macosx') for directory in [bin_dir, lib_dir]: if not os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test","building') parser.add_argument('build_actions', help=\"Extra actions to perform. Can be any number of the following\",","os.path.join(build_dir, product) dest = os.path.join(bin_dir, product) # Create a copy of the list","should_run_any_action(['build', 'install'], args.build_actions): print(\"** Building %s **\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build',"],"string":"[\n \"parsed.package_dir)) # Convert build_dir to absolute path, relative to package_dir. parsed.build_dir = os.path.join(parsed.package_dir,\",\n \"as e: printerr('FAIL: Generating the Xcode project failed') printerr('Executing: %s' % ' '.join(e.cmd))\",\n \"in the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test', 'swift-evolve']: # Make\",\n \"parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to an Xcode workspace to create a\",\n \"checked out next sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \\\"1\\\" if args.update: print(\\\"**\",\n \"package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\\\"generate-xcodeproj\\\",\",\n \"e: printerr('FAIL: Testing %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1)\",\n \"main swift repository's build-script.py that knows how to build and install the stress\",\n \"does not need to rebuilt if it has already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT']\",\n \"else: return arg def get_products(package_dir): # FIXME: We ought to be able to\",\n \"for product in products: invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env,\",\n \"rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose): package_name = os.path.basename(package_dir)\",\n \"information See https://swift.org/CONTRIBUTORS.txt for the list of Swift project authors ------------------------------------------------------------------------------ This is\",\n \"config_path = os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath}\",\n \"parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log executed commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug')\",\n \"how to build and install the stress tester utilities given a swift workspace.\",\n \"it rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add the rpath to the stdlib in in\",\n \"check_call(cmd, verbose=verbose) def check_call(cmd, verbose, env=os.environ, **kwargs): if verbose: print(' '.join([escape_cmd_arg(arg) for arg\",\n \"except subprocess.CalledProcessError as e: printerr('FAIL: Updating dependencies of %s failed' % package_name) printerr('Executing:\",\n \"LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' % package_name) args =\",\n \"required with the install action\\\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir =\",\n \"% ' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"install\\\", args.build_actions): print(\\\"** Installing %s **\\\" % package_name)\",\n \"any of the actions in `action_names` should be run. def should_run_any_action(action_names, selected_actions): for\",\n \"help='Path to an Xcode workspace to create a unified build of SwiftSyntax with\",\n \"% ' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"test\\\", args.build_actions): print(\\\"** Testing %s **\\\" % package_name)\",\n \"testing if should_run_any_action(['build', 'install'], args.build_actions): print(\\\"** Building %s **\\\" % package_name) try: invoke_swift(package_dir=args.package_dir,\",\n \"copy_cmd=['rsync', '-a', src, dest] print('installing %s to %s' % (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose)\",\n \"% package_name) args = [swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path]\",\n \"failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"install\\\", args.build_actions): print(\\\"**\",\n \"'--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args, env=env, verbose=verbose) def add_rpath(binary, rpath,\",\n \"list) for item in pair] def escape_cmd_arg(arg): if '\\\"' in arg or '\",\n \"os.path.join(bin_dir, product) # Create a copy of the list since we modify it\",\n \"Xcode workspace to create a unified build of SwiftSyntax with other projects.') parser.add_argument('--toolchain',\",\n \"if '\\\"' in arg or ' ' in arg: return '\\\"%s\\\"' % arg.replace('\\\"',\",\n \"%s **\\\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir,\",\n \"copy of the list since we modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add\",\n \"selected_actions): if action_name in selected_actions: return True elif \\\"all\\\" in selected_actions: return True\",\n \"args.build_actions): print(\\\"** Building %s **\\\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath,\",\n \"rpath, binary] check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-delete_rpath', rpath,\",\n \"printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"install\\\", args.build_actions): print(\\\"** Installing %s **\\\"\",\n \"product) # Create a copy of the list since we modify it rpaths_to_delete_for_this_product\",\n \"swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Generating the Xcode project\",\n \"in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose): package_name =\",\n \"printerr('FAIL: Generating the Xcode project failed') printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if\",\n \"**\\\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env,\",\n \"os.path.join(parsed.package_dir, parsed.build_dir) return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env = dict(os.environ)\",\n \"'\\\\\\\\\\\"') else: return arg def get_products(package_dir): # FIXME: We ought to be able\",\n \"% package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL:\",\n \"def invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): # Until\",\n \"targets simultaneously. For now, just build one product after the other. for product\",\n \"rpath to sourcekitd relative in the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib']\",\n \"# The test action creates its own build. No need to build if\",\n \"Generating the Xcode project failed') printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"test\\\",\",\n \"if package_dir.endswith(\\\"/SourceKitStressTester\\\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\\\"/SwiftEvolve\\\"): return ['swift-evolve'] else: return [] if\",\n \"build_dir, multiroot_data_file, config, env, verbose): # Until rdar://53881101 is implemented, we cannot request\",\n \"for arg in cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value, list): return\",\n \"if we are just testing if should_run_any_action(['build', 'install'], args.build_actions): print(\\\"** Building %s **\\\"\",\n \"as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path\",\n \"'.join(e.cmd)) sys.exit(1) # Returns true if any of the actions in `action_names` should\",\n \"project authors Licensed under Apache License v2.0 with Runtime Library Exception See https://swift.org/LICENSE.txt\",\n \"'-c', config, '--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action == 'test': args.extend(['--test-product',\",\n \"help='use normal remote dependencies when building') parser.add_argument('build_actions', help=\\\"Extra actions to perform. Can be\",\n \"request a build of multiple # targets simultaneously. For now, just build one\",\n \"else: args.extend(['--product', product]) # Tell SwiftSyntax that we are building in a build-script\",\n \"swift repository's build-script.py that knows how to build and install the stress tester\",\n \"check_call(copy_cmd, verbose=verbose) for rpath in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for rpath in rpaths_to_add:\",\n \"env, verbose): # Until rdar://53881101 is implemented, we cannot request a build of\",\n \"parser.add_argument('-v', '--verbose', action='store_true', help='log executed commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build')\",\n \"except subprocess.CalledProcessError as e: printerr('FAIL: Installing %s failed' % package_name) printerr('Executing: %s' %\",\n \"SwiftPM for this info. if package_dir.endswith(\\\"/SourceKitStressTester\\\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\\\"/SwiftEvolve\\\"): return ['swift-evolve']\",\n \"default='.build') parser.add_argument('--multiroot-data-file', help='Path to an Xcode workspace to create a unified build of\",\n \"lib_dir]: if not os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test and sk-swiftc-wrapper for product in\",\n \"# Convert build_dir to absolute path, relative to package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir)\",\n \"'test': args.extend(['--test-product', product]) else: args.extend(['--product', product]) # Tell SwiftSyntax that we are building\",\n \"if any of the actions in `action_names` should be run. def should_run_any_action(action_names, selected_actions):\",\n \"and not parsed.prefix: ArgumentParser.error(\\\"'--prefix' is required with the install action\\\") parsed.swift_exec = os.path.join(parsed.toolchain,\",\n \"perform. Can be any number of the following\\\", choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'],\",\n \"be run. def should_run_any_action(action_names, selected_actions): for action_name in action_names: if should_run_action(action_name, selected_actions): return\",\n \"should_run_any_action(action_names, selected_actions): for action_name in action_names: if should_run_action(action_name, selected_actions): return True return False\",\n \"if action_name in selected_actions: return True elif \\\"all\\\" in selected_actions: return True else:\",\n \"= ['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test', 'swift-evolve']: # Make the rpath to sourcekitd\",\n \"' ' in arg: return '\\\"%s\\\"' % arg.replace('\\\"', '\\\\\\\\\\\"') else: return arg def\",\n \"The test action creates its own build. No need to build if we\",\n \"def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir, 'bin') lib_dir =\",\n \"a swift workspace. \\\"\\\"\\\" from __future__ import print_function import argparse import sys import\",\n \"invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): args = [swift_exec,\",\n \"add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose): package_name = os.path.basename(package_dir) config_path\",\n \"should_run_action(\\\"generate-xcodeproj\\\", args.build_actions): print(\\\"** Generating Xcode project for %s **\\\" % package_name) try: generate_xcodeproj(args.package_dir,\",\n \"This is a helper script for the main swift repository's build-script.py that knows\",\n \"and install the stress tester utilities given a swift workspace. \\\"\\\"\\\" from __future__\",\n \"swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Updating dependencies of %s\",\n \"# it does not need to rebuilt if it has already been built\",\n \"subprocess.CalledProcessError as e: printerr('FAIL: Testing %s failed' % package_name) printerr('Executing: %s' % '\",\n \"try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError\",\n \"e: printerr('FAIL: Updating dependencies of %s failed' % package_name) printerr('Executing: %s' % '\",\n \"of %s **\\\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError\",\n \"args.build_actions): print(\\\"** Installing %s **\\\" % package_name) stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib', 'swift',\",\n \"subprocess.CalledProcessError as e: printerr('FAIL: Installing %s failed' % package_name) printerr('Executing: %s' % '\",\n \"def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env = dict(os.environ) # Use local dependencies\",\n \"already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env, verbose=verbose)\",\n \"in the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add,\",\n \"SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj'\",\n \"dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal remote dependencies when building') parser.add_argument('build_actions', help=\\\"Extra actions to\",\n \"rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src, dest] print('installing\",\n \"%s' % ' '.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\\\"generate-xcodeproj\\\", args.build_actions): print(\\\"**\",\n \"% (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for rpath in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for\",\n \"install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Installing %s failed'\",\n \"rebuilt if it has already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] =\",\n \"= os.path.join(bin_dir, product) # Create a copy of the list since we modify\",\n \"install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Installing %s\",\n \"'.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\\\"generate-xcodeproj\\\", args.build_actions): print(\\\"** Generating Xcode project\",\n \"**\\\" % package_name) stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix,\",\n \"if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action == 'test': args.extend(['--test-product', product]) else: args.extend(['--product', product])\",\n \"return '\\\"%s\\\"' % arg.replace('\\\"', '\\\\\\\\\\\"') else: return arg def get_products(package_dir): # FIXME: We\",\n \"True elif \\\"all\\\" in selected_actions: return True else: return False def update_swiftpm_dependencies(package_dir, swift_exec,\",\n \"'package', '--package-path', package_dir, '--build-path', build_dir, 'update'] check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec, action,\",\n \"building this package') parser.add_argument('--update', action='store_true', help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal\",\n \"printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"test\\\", args.build_actions): print(\\\"** Testing %s **\\\"\",\n \"print(\\\"** Generating Xcode project for %s **\\\" % package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath,\",\n \"sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Testing %s\",\n \"return True return False def should_run_action(action_name, selected_actions): if action_name in selected_actions: return True\",\n \"if (\\\"install\\\" in parsed.build_actions or \\\"all\\\" in parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\\\"'--prefix' is\",\n \"def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose): args = [swift_exec, 'package', '--package-path', package_dir, '--build-path',\",\n \"the other. for product in products: invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file,\",\n \"['sk-stress-test', 'swift-evolve']: # Make the rpath to sourcekitd relative in the toolchain rpaths_to_delete_for_this_product\",\n \"env=os.environ, **kwargs): if verbose: print(' '.join([escape_cmd_arg(arg) for arg in cmd])) return subprocess.check_call(cmd, env=env,\",\n \"own build. No need to build if we are just testing if should_run_any_action(['build',\",\n \"selected_actions): for action_name in action_names: if should_run_action(action_name, selected_actions): return True return False def\",\n \"in [bin_dir, lib_dir]: if not os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test and sk-swiftc-wrapper for\",\n \"return True else: return False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose): args =\",\n \"% package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL:\",\n \"product in products: invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose)\",\n \"'install', 'generate-xcodeproj'], nargs=\\\"*\\\", default=['build']) parsed = parser.parse_args(args) if (\\\"install\\\" in parsed.build_actions or \\\"all\\\"\",\n \"Until rdar://53881101 is implemented, we cannot request a build of multiple # targets\",\n \"For now, just build one product after the other. for product in products:\",\n \"for license information See https://swift.org/CONTRIBUTORS.txt for the list of Swift project authors ------------------------------------------------------------------------------\",\n \"'lib') # Convert package_dir to absolute path, relative to root of repo. repo_path\",\n \"build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Testing %s failed'\",\n \"invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as\",\n \"Exception See https://swift.org/LICENSE.txt for license information See https://swift.org/CONTRIBUTORS.txt for the list of Swift\",\n \"build if we are just testing if should_run_any_action(['build', 'install'], args.build_actions): print(\\\"** Building %s\",\n \"swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError\",\n \"rpath, verbose=verbose) for rpath in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath,\",\n \"Tell SwiftSyntax that we are building in a build-script environment so that #\",\n \"'-add_rpath', rpath, binary] check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-delete_rpath',\",\n \"help=\\\"Extra actions to perform. Can be any number of the following\\\", choices=['all', 'build',\",\n \"build_dir, multiroot_data_file, config, env, verbose): args = [swift_exec, action, '--package-path', package_dir, '-c', config,\",\n \"out next sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \\\"1\\\" if args.update: print(\\\"** Updating\",\n \"for action_name in action_names: if should_run_action(action_name, selected_actions): return True return False def should_run_action(action_name,\",\n \"<filename>build-script-helper.py #!/usr/bin/env python \\\"\\\"\\\" This source file is part of the Swift.org open\",\n \"subprocess.CalledProcessError as e: printerr('FAIL: Building %s failed' % package_name) printerr('Executing: %s' % '\",\n \"except subprocess.CalledProcessError as e: printerr('FAIL: Building %s failed' % package_name) printerr('Executing: %s' %\",\n \"**\\\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file,\",\n \"parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\\\"'--prefix' is required with the install action\\\") parsed.swift_exec =\",\n \"= os.path.join(install_dir, 'lib', 'swift', 'macosx') for directory in [bin_dir, lib_dir]: if not os.path.exists(directory):\",\n \"package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Testing\",\n \"parser.add_argument('--multiroot-data-file', help='Path to an Xcode workspace to create a unified build of SwiftSyntax\",\n \"= {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' %\",\n \"swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose) def invoke_swift_single_product(package_dir, swift_exec, action,\",\n \"sk-stress-test and sk-swiftc-wrapper for product in get_products(package_dir): src = os.path.join(build_dir, product) dest =\",\n \"package_name) stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir,\",\n \"os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\\\"generate-xcodeproj\\\", args.build_actions): print(\\\"** Generating Xcode project for %s **\\\" %\",\n \"'--verbose', action='store_true', help='log executed commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file',\",\n \"Copyright (c) 2014 - 2018 Apple Inc. and the Swift project authors Licensed\",\n \"except subprocess.CalledProcessError as e: printerr('FAIL: Generating the Xcode project failed') printerr('Executing: %s' %\",\n \"Apple Inc. and the Swift project authors Licensed under Apache License v2.0 with\",\n \"'update'] check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath, build_dir, multiroot_data_file, config,\",\n \"sourcekitd relative in the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src, dest,\",\n \"action, products, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): # Until rdar://53881101 is implemented,\",\n \"printerr('FAIL: Testing %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if\",\n \"after the other. for product in products: invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir,\",\n \"[item for pair in zip([value] * len(list), list) for item in pair] def\",\n \"as e: printerr('FAIL: Building %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd))\",\n \"to %s' % (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for rpath in rpaths_to_delete: remove_rpath(dest, rpath,\",\n \"true if any of the actions in `action_names` should be run. def should_run_any_action(action_names,\",\n \"when building') parser.add_argument('build_actions', help=\\\"Extra actions to perform. Can be any number of the\",\n \"' in arg: return '\\\"%s\\\"' % arg.replace('\\\"', '\\\\\\\\\\\"') else: return arg def get_products(package_dir):\",\n \"help='log executed commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to\",\n \"**\\\" % package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e:\",\n \"parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to an Xcode workspace to create a unified build\",\n \"multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Testing %s failed' %\",\n \"remote dependencies when building') parser.add_argument('build_actions', help=\\\"Extra actions to perform. Can be any number\",\n \"\\\"\\\"\\\" This source file is part of the Swift.org open source project Copyright\",\n \"projects.') parser.add_argument('--toolchain', required=True, help='the toolchain to use when building this package') parser.add_argument('--update', action='store_true',\",\n \"(os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for rpath in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for rpath\",\n \"failed') printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"test\\\", args.build_actions): print(\\\"** Testing %s\",\n \"verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Generating the Xcode project failed') printerr('Executing: %s'\",\n \"= [swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args, env=env, verbose=verbose)\",\n \"'.join(e.cmd)) sys.exit(1) # The test action creates its own build. No need to\",\n \"products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Building\",\n \"' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"install\\\", args.build_actions): print(\\\"** Installing %s **\\\" % package_name) stdlib_dir\",\n \"os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except\",\n \"authors ------------------------------------------------------------------------------ This is a helper script for the main swift repository's build-script.py\",\n \"dependencies when building') parser.add_argument('build_actions', help=\\\"Extra actions to perform. Can be any number of\",\n \"env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env, verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath,\",\n \"for %s **\\\" % package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError\",\n \"parser.add_argument('--update', action='store_true', help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal remote dependencies when\",\n \"config, env, verbose): args = [swift_exec, action, '--package-path', package_dir, '-c', config, '--build-path', build_dir]\",\n \"cmd = ['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath, verbose): cmd\",\n \"not need to rebuilt if it has already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] =\",\n \"ArgumentParser.error(\\\"'--prefix' is required with the install action\\\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin', 'swift')\",\n \"# Install sk-stress-test and sk-swiftc-wrapper for product in get_products(package_dir): src = os.path.join(build_dir, product)\",\n \"file=sys.stderr) def main(argv_prefix = []): args = parse_args(argv_prefix + sys.argv[1:]) run(args) def parse_args(args):\",\n \"'usr', 'lib', 'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError\",\n \"not parsed.prefix: ArgumentParser.error(\\\"'--prefix' is required with the install action\\\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr',\",\n \"https://swift.org/CONTRIBUTORS.txt for the list of Swift project authors ------------------------------------------------------------------------------ This is a helper\",\n \"in parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\\\"'--prefix' is required with the install action\\\") parsed.swift_exec\",\n \"rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src, dest] print('installing %s to %s' % (os.path.basename(src), dest))\",\n \"stdlib in in the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test', 'swift-evolve']:\",\n \"path, relative to root of repo. repo_path = os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path,\",\n \"relative to package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name\",\n \"**kwargs) def interleave(value, list): return [item for pair in zip([value] * len(list), list)\",\n \"Create a copy of the list since we modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete)\",\n \"config, env, verbose): # Until rdar://53881101 is implemented, we cannot request a build\",\n \"to query SwiftPM for this info. if package_dir.endswith(\\\"/SourceKitStressTester\\\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\\\"/SwiftEvolve\\\"):\",\n \"executed commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to an\",\n \"[swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args, env=env, verbose=verbose) def\",\n \"parsed.prefix: ArgumentParser.error(\\\"'--prefix' is required with the install action\\\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin',\",\n \"\\\"all\\\" in selected_actions: return True else: return False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env,\",\n \"sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose) def invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir,\",\n \"'generate-xcodeproj'], nargs=\\\"*\\\", default=['build']) parsed = parser.parse_args(args) if (\\\"install\\\" in parsed.build_actions or \\\"all\\\" in\",\n \"% arg.replace('\\\"', '\\\\\\\\\\\"') else: return arg def get_products(package_dir): # FIXME: We ought to\",\n \"= []): args = parse_args(argv_prefix + sys.argv[1:]) run(args) def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY')\",\n \"' '.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\\\"generate-xcodeproj\\\", args.build_actions): print(\\\"** Generating Xcode\",\n \"License v2.0 with Runtime Library Exception See https://swift.org/LICENSE.txt for license information See https://swift.org/CONTRIBUTORS.txt\",\n \"package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"install\\\", args.build_actions): print(\\\"** Installing %s\",\n \"Returns true if any of the actions in `action_names` should be run. def\",\n \"# Use local dependencies (i.e. checked out next sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS']\",\n \"build one product after the other. for product in products: invoke_swift_single_product(package_dir, swift_exec, action,\",\n \"subprocess.CalledProcessError as e: printerr('FAIL: Updating dependencies of %s failed' % package_name) printerr('Executing: %s'\",\n \"to the stdlib in in the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product in\",\n \"= os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS\",\n \"https://swift.org/LICENSE.txt for license information See https://swift.org/CONTRIBUTORS.txt for the list of Swift project authors\",\n \"args.config)) if should_run_action(\\\"generate-xcodeproj\\\", args.build_actions): print(\\\"** Generating Xcode project for %s **\\\" % package_name)\",\n \"the install action\\\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr',\",\n \"Can be any number of the following\\\", choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'], nargs=\\\"*\\\",\",\n \"config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path =\",\n \"dependencies of %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) #\",\n \"def should_run_any_action(action_names, selected_actions): for action_name in action_names: if should_run_action(action_name, selected_actions): return True return\",\n \"swift workspace. \\\"\\\"\\\" from __future__ import print_function import argparse import sys import os,\",\n \"modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add the rpath to the stdlib in\",\n \"action\\\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib') #\",\n \"package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir)\",\n \"subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value, list): return [item for pair in zip([value]\",\n \"% ' '.join(e.cmd)) sys.exit(1) # The test action creates its own build. No\",\n \"not os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test and sk-swiftc-wrapper for product in get_products(package_dir): src\",\n \"'build', 'test', 'install', 'generate-xcodeproj'], nargs=\\\"*\\\", default=['build']) parsed = parser.parse_args(args) if (\\\"install\\\" in parsed.build_actions\",\n \"build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Updating dependencies of %s failed'\",\n \"package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # The test action creates its\",\n \"arg def get_products(package_dir): # FIXME: We ought to be able to query SwiftPM\",\n \"rpaths_to_add += ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest, rpaths_to_delete, rpaths_to_add,\",\n \"%s' % ' '.join(e.cmd)) sys.exit(1) # The test action creates its own build.\",\n \"of multiple # targets simultaneously. For now, just build one product after the\",\n \"SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal remote dependencies when building') parser.add_argument('build_actions', help=\\\"Extra actions\",\n \"rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir, 'lib', 'swift', 'macosx') for\",\n \"#!/usr/bin/env python \\\"\\\"\\\" This source file is part of the Swift.org open source\",\n \"if should_run_action(\\\"generate-xcodeproj\\\", args.build_actions): print(\\\"** Generating Xcode project for %s **\\\" % package_name) try:\",\n \"rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src,\",\n \"if args.update: print(\\\"** Updating dependencies of %s **\\\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec,\",\n \"is implemented, we cannot request a build of multiple # targets simultaneously. For\",\n \"repo_path = os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert build_dir to absolute\",\n \"args.extend(['--product', product]) # Tell SwiftSyntax that we are building in a build-script environment\",\n \"verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Installing %s failed' % package_name) printerr('Executing: %s'\",\n \"Testing %s **\\\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath,\",\n \"Generating Xcode project for %s **\\\" % package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env,\",\n \"for product in get_products(package_dir): src = os.path.join(build_dir, product) dest = os.path.join(bin_dir, product) #\",\n \"parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib') # Convert\",\n \"= os.path.join(build_dir, product) dest = os.path.join(bin_dir, product) # Create a copy of the\",\n \"config, env, verbose) def invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env,\",\n \"in parsed.build_actions or \\\"all\\\" in parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\\\"'--prefix' is required with\",\n \"build_dir to absolute path, relative to package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return parsed\",\n \"not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \\\"1\\\" if args.update: print(\\\"** Updating dependencies of %s **\\\"\",\n \"= os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib') # Convert package_dir\",\n \"helper script for the main swift repository's build-script.py that knows how to build\",\n \"verbose=verbose) def remove_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose)\",\n \"product after the other. for product in products: invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath,\",\n \"a unified build of SwiftSyntax with other projects.') parser.add_argument('--toolchain', required=True, help='the toolchain to\",\n \"a build-script environment so that # it does not need to rebuilt if\",\n \"relative to root of repo. repo_path = os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir))\",\n \"args.extend(['--multiroot-data-file', multiroot_data_file]) if action == 'test': args.extend(['--test-product', product]) else: args.extend(['--product', product]) # Tell\",\n \"verbose=verbose) for rpath in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env,\",\n \"open(config_path, 'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited)\",\n \"%s **\\\" % package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError as\",\n \"# Tell SwiftSyntax that we are building in a build-script environment so that\",\n \"False def should_run_action(action_name, selected_actions): if action_name in selected_actions: return True elif \\\"all\\\" in\",\n \"package') parser.add_argument('--update', action='store_true', help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal remote dependencies\",\n \"build of SwiftSyntax with other projects.') parser.add_argument('--toolchain', required=True, help='the toolchain to use when\",\n \"normal remote dependencies when building') parser.add_argument('build_actions', help=\\\"Extra actions to perform. Can be any\",\n \"in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for rpath in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def\",\n \"verbose): args = [swift_exec, 'package', '--package-path', package_dir, '--build-path', build_dir, 'update'] check_call(args, env=env, verbose=verbose)\",\n \"to absolute path, relative to root of repo. repo_path = os.path.dirname(__file__) parsed.package_dir =\",\n \"if should_run_action(action_name, selected_actions): return True return False def should_run_action(action_name, selected_actions): if action_name in\",\n \"config_path, '--output', xcodeproj_path] check_call(args, env=env, verbose=verbose) def add_rpath(binary, rpath, verbose): cmd = ['install_name_tool',\",\n \"['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test', 'swift-evolve']: # Make the rpath to sourcekitd relative\",\n \"args = parse_args(argv_prefix + sys.argv[1:]) run(args) def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester')\",\n \"2014 - 2018 Apple Inc. and the Swift project authors Licensed under Apache\",\n \"len(list), list) for item in pair] def escape_cmd_arg(arg): if '\\\"' in arg or\",\n \"args.update: print(\\\"** Updating dependencies of %s **\\\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir,\",\n \"file is part of the Swift.org open source project Copyright (c) 2014 -\",\n \"'--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args, env=env, verbose=verbose) def add_rpath(binary, rpath, verbose): cmd =\",\n \"of the Swift.org open source project Copyright (c) 2014 - 2018 Apple Inc.\",\n \"or ' ' in arg: return '\\\"%s\\\"' % arg.replace('\\\"', '\\\\\\\\\\\"') else: return arg\",\n \"# Returns true if any of the actions in `action_names` should be run.\",\n \"# Make the rpath to sourcekitd relative in the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath]\",\n \"[]): args = parse_args(argv_prefix + sys.argv[1:]) run(args) def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir',\",\n \"repository's build-script.py that knows how to build and install the stress tester utilities\",\n \"os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS =\",\n \"['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath, verbose): cmd = ['install_name_tool',\",\n \"action_name in selected_actions: return True elif \\\"all\\\" in selected_actions: return True else: return\",\n \"in selected_actions: return True else: return False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose):\",\n \"products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e:\",\n \"import argparse import sys import os, platform import subprocess def printerr(message): print(message, file=sys.stderr)\",\n \"it has already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args,\",\n \"' '.join(e.cmd)) sys.exit(1) # The test action creates its own build. No need\",\n \"We ought to be able to query SwiftPM for this info. if package_dir.endswith(\\\"/SourceKitStressTester\\\"):\",\n \"args.build_actions): print(\\\"** Generating Xcode project for %s **\\\" % package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec,\",\n \"rpath to the stdlib in in the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product\",\n \"this info. if package_dir.endswith(\\\"/SourceKitStressTester\\\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\\\"/SwiftEvolve\\\"): return ['swift-evolve'] else: return\",\n \"def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose): package_name = os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig')\",\n \"rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose): package_name = os.path.basename(package_dir) config_path =\",\n \"tester utilities given a swift workspace. \\\"\\\"\\\" from __future__ import print_function import argparse\",\n \"in a build-script environment so that # it does not need to rebuilt\",\n \"the following\\\", choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'], nargs=\\\"*\\\", default=['build']) parsed = parser.parse_args(args) if\",\n \"src = os.path.join(build_dir, product) dest = os.path.join(bin_dir, product) # Create a copy of\",\n \"building in a build-script environment so that # it does not need to\",\n \"verbose=verbose) def install(src, dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src, dest] print('installing %s\",\n \"$(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' % package_name) args\",\n \"argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log executed commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config',\",\n \"default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log executed commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir',\",\n \"= parser.parse_args(args) if (\\\"install\\\" in parsed.build_actions or \\\"all\\\" in parsed.build_actions) and not parsed.prefix:\",\n \"given a swift workspace. \\\"\\\"\\\" from __future__ import print_function import argparse import sys\",\n \"product]) else: args.extend(['--product', product]) # Tell SwiftSyntax that we are building in a\",\n \"verbose) def invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): args\",\n \"a build of multiple # targets simultaneously. For now, just build one product\",\n \"print(' '.join([escape_cmd_arg(arg) for arg in cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value,\",\n \"item in pair] def escape_cmd_arg(arg): if '\\\"' in arg or ' ' in\",\n \"Building %s **\\\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file,\",\n \"['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync',\",\n \"environment so that # it does not need to rebuilt if it has\",\n \"+= [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest,\",\n \"= \\\"1\\\" if args.update: print(\\\"** Updating dependencies of %s **\\\" % package_name) try:\",\n \"dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src, dest] print('installing %s to %s' %\",\n \"following\\\", choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'], nargs=\\\"*\\\", default=['build']) parsed = parser.parse_args(args) if (\\\"install\\\"\",\n \"print(\\\"** Building %s **\\\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir,\",\n \"actions in `action_names` should be run. def should_run_any_action(action_names, selected_actions): for action_name in action_names:\",\n \"the list since we modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add the rpath\",\n \"package_dir, '--build-path', build_dir, 'update'] check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath,\",\n \"install action\\\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib')\",\n \"the rpath to sourcekitd relative in the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add +=\",\n \"% package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose)\",\n \"if it has already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath\",\n \"to sourcekitd relative in the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src,\",\n \"dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src,\",\n \"'install'], args.build_actions): print(\\\"** Building %s **\\\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir),\",\n \"%s **\\\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config,\",\n \"package_dir.endswith(\\\"/SourceKitStressTester\\\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\\\"/SwiftEvolve\\\"): return ['swift-evolve'] else: return [] if __name__\",\n \"try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Installing\",\n \"'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args, env=env, verbose=verbose) def add_rpath(binary,\",\n \"'sk-swiftc-wrapper'] elif package_dir.endswith(\\\"/SwiftEvolve\\\"): return ['swift-evolve'] else: return [] if __name__ == '__main__': main()\",\n \"% package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if\",\n \"install the stress tester utilities given a swift workspace. \\\"\\\"\\\" from __future__ import\",\n \"if should_run_any_action(['build', 'install'], args.build_actions): print(\\\"** Building %s **\\\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec,\",\n \"2018 Apple Inc. and the Swift project authors Licensed under Apache License v2.0\",\n \"Installing %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # Returns\",\n \"% package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # Returns true if any\",\n \"os.path.join(repo_path, parsed.package_dir)) # Convert build_dir to absolute path, relative to package_dir. parsed.build_dir =\",\n \"it does not need to rebuilt if it has already been built before.\",\n \"failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # Returns true if\",\n \"argparse import sys import os, platform import subprocess def printerr(message): print(message, file=sys.stderr) def\",\n \"= os.path.join(parsed.toolchain, 'usr', 'lib') # Convert package_dir to absolute path, relative to root\",\n \"multiroot_data_file, config, env, verbose): args = [swift_exec, action, '--package-path', package_dir, '-c', config, '--build-path',\",\n \"# Convert package_dir to absolute path, relative to root of repo. repo_path =\",\n \"# Create a copy of the list since we modify it rpaths_to_delete_for_this_product =\",\n \"verbose): copy_cmd=['rsync', '-a', src, dest] print('installing %s to %s' % (os.path.basename(src), dest)) check_call(copy_cmd,\",\n \"that knows how to build and install the stress tester utilities given a\",\n \"action_name in action_names: if should_run_action(action_name, selected_actions): return True return False def should_run_action(action_name, selected_actions):\",\n \"= os.path.basename(args.package_dir) env = dict(os.environ) # Use local dependencies (i.e. checked out next\",\n \"product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose) def invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath,\",\n \"selected_actions: return True elif \\\"all\\\" in selected_actions: return True else: return False def\",\n \"be any number of the following\\\", choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'], nargs=\\\"*\\\", default=['build'])\",\n \"the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test', 'swift-evolve']: # Make the\",\n \"' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"test\\\", args.build_actions): print(\\\"** Testing %s **\\\" % package_name) try:\",\n \"from __future__ import print_function import argparse import sys import os, platform import subprocess\",\n \"= os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir, 'lib', 'swift', 'macosx') for directory in [bin_dir,\",\n \"os.path.basename(args.package_dir) env = dict(os.environ) # Use local dependencies (i.e. checked out next sourcekit-lsp).\",\n \"in get_products(package_dir): src = os.path.join(build_dir, product) dest = os.path.join(bin_dir, product) # Create a\",\n \"= argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log executed commands') parser.add_argument('--prefix', help='install path')\",\n \"# Add the rpath to the stdlib in in the toolchain rpaths_to_add =\",\n \"dependencies of %s **\\\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except\",\n \"verbose: print(' '.join([escape_cmd_arg(arg) for arg in cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def\",\n \"def interleave(value, list): return [item for pair in zip([value] * len(list), list) for\",\n \"in action_names: if should_run_action(action_name, selected_actions): return True return False def should_run_action(action_name, selected_actions): if\",\n \"with the install action\\\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain,\",\n \"subprocess.CalledProcessError as e: printerr('FAIL: Generating the Xcode project failed') printerr('Executing: %s' % '\",\n \"verbose=verbose) def add_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd, verbose=verbose)\",\n \"so that # it does not need to rebuilt if it has already\",\n \"next sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \\\"1\\\" if args.update: print(\\\"** Updating dependencies\",\n \"simultaneously. For now, just build one product after the other. for product in\",\n \"path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to an Xcode workspace to create\",\n \"action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): args = [swift_exec, action, '--package-path',\",\n \"def check_call(cmd, verbose, env=os.environ, **kwargs): if verbose: print(' '.join([escape_cmd_arg(arg) for arg in cmd]))\",\n \"source project Copyright (c) 2014 - 2018 Apple Inc. and the Swift project\",\n \"path, relative to package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir\",\n \"lib_dir = os.path.join(install_dir, 'lib', 'swift', 'macosx') for directory in [bin_dir, lib_dir]: if not\",\n \"os.path.join(install_dir, 'lib', 'swift', 'macosx') for directory in [bin_dir, lib_dir]: if not os.path.exists(directory): os.makedirs(directory)\",\n \"args.build_actions): print(\\\"** Testing %s **\\\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' %\",\n \"return False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose): args = [swift_exec, 'package', '--package-path',\",\n \"for rpath in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for rpath in rpaths_to_add: add_rpath(dest, rpath,\",\n \"one product after the other. for product in products: invoke_swift_single_product(package_dir, swift_exec, action, product,\",\n \"sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): args = [swift_exec, action, '--package-path', package_dir, '-c',\",\n \"%s **\\\" % package_name) stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx') try: install_package(args.package_dir,\",\n \"in selected_actions: return True elif \\\"all\\\" in selected_actions: return True else: return False\",\n \"printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # Returns true if any of the\",\n \"of the list since we modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add the\",\n \"env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Building %s failed' % package_name) printerr('Executing:\",\n \"try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose)\",\n \"= os.path.join(parsed.package_dir, parsed.build_dir) return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env =\",\n \"'--package-path', package_dir, '--build-path', build_dir, 'update'] check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec, action, products,\",\n \"dest)) check_call(copy_cmd, verbose=verbose) for rpath in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for rpath in\",\n \"else: return False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose): args = [swift_exec, 'package',\",\n \"rpath, verbose): cmd = ['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose) def check_call(cmd, verbose,\",\n \"print(\\\"** Testing %s **\\\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name],\",\n \"[swift_exec, action, '--package-path', package_dir, '-c', config, '--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if\",\n \"{sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' % package_name)\",\n \"invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except\",\n \"__future__ import print_function import argparse import sys import os, platform import subprocess def\",\n \"xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' % package_name) args = [swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj',\",\n \"platform import subprocess def printerr(message): print(message, file=sys.stderr) def main(argv_prefix = []): args =\",\n \"% package_name) stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath,\",\n \"config, '--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action == 'test': args.extend(['--test-product', product])\",\n \"before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env, verbose=verbose) def install_package(package_dir, install_dir,\",\n \"implemented, we cannot request a build of multiple # targets simultaneously. For now,\",\n \"Building %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) output_dir =\",\n \"package_name) args = [swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args,\",\n \"we are building in a build-script environment so that # it does not\",\n \"verbose=verbose) for rpath in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for rpath in rpaths_to_add: add_rpath(dest,\",\n \"nargs=\\\"*\\\", default=['build']) parsed = parser.parse_args(args) if (\\\"install\\\" in parsed.build_actions or \\\"all\\\" in parsed.build_actions)\",\n \"# FIXME: We ought to be able to query SwiftPM for this info.\",\n \"multiroot_data_file, config, env, verbose) def invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config,\",\n \"sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Generating the Xcode project failed')\",\n \"%s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"test\\\", args.build_actions): print(\\\"** Testing %s **\\\" %\",\n \"we cannot request a build of multiple # targets simultaneously. For now, just\",\n \"multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action == 'test': args.extend(['--test-product', product]) else: args.extend(['--product', product]) #\",\n \"the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose)\",\n \"its own build. No need to build if we are just testing if\",\n \"'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib') # Convert package_dir to absolute path,\",\n \"of the actions in `action_names` should be run. def should_run_any_action(action_names, selected_actions): for action_name\",\n \"to absolute path, relative to package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return parsed def\",\n \"are just testing if should_run_any_action(['build', 'install'], args.build_actions): print(\\\"** Building %s **\\\" % package_name)\",\n \"check_call(cmd, verbose, env=os.environ, **kwargs): if verbose: print(' '.join([escape_cmd_arg(arg) for arg in cmd])) return\",\n \"printerr(message): print(message, file=sys.stderr) def main(argv_prefix = []): args = parse_args(argv_prefix + sys.argv[1:]) run(args)\",\n \"'\\\"' in arg or ' ' in arg: return '\\\"%s\\\"' % arg.replace('\\\"', '\\\\\\\\\\\"')\",\n \"swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e:\",\n \"is a helper script for the main swift repository's build-script.py that knows how\",\n \"print_function import argparse import sys import os, platform import subprocess def printerr(message): print(message,\",\n \"'swift-evolve']: # Make the rpath to sourcekitd relative in the toolchain rpaths_to_delete_for_this_product +=\",\n \"dict(os.environ) # Use local dependencies (i.e. checked out next sourcekit-lsp). if not args.no_local_deps:\",\n \"action creates its own build. No need to build if we are just\",\n \"%s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir,\",\n \"if action == 'test': args.extend(['--test-product', product]) else: args.extend(['--product', product]) # Tell SwiftSyntax that\",\n \"with Runtime Library Exception See https://swift.org/LICENSE.txt for license information See https://swift.org/CONTRIBUTORS.txt for the\",\n \"'swift', 'macosx') for directory in [bin_dir, lib_dir]: if not os.path.exists(directory): os.makedirs(directory) # Install\",\n \"check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd,\",\n \"%s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"install\\\", args.build_actions):\",\n \"[bin_dir, lib_dir]: if not os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test and sk-swiftc-wrapper for product\",\n \"project failed') printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"test\\\", args.build_actions): print(\\\"** Testing\",\n \"verbose, env=os.environ, **kwargs): if verbose: print(' '.join([escape_cmd_arg(arg) for arg in cmd])) return subprocess.check_call(cmd,\",\n \"license information See https://swift.org/CONTRIBUTORS.txt for the list of Swift project authors ------------------------------------------------------------------------------ This\",\n \"verbose): package_name = os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w') as config_file:\",\n \"commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to an Xcode\",\n \"Updating dependencies of %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1)\",\n \"['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose) def check_call(cmd, verbose, env=os.environ, **kwargs): if verbose:\",\n \"if should_run_action(\\\"test\\\", args.build_actions): print(\\\"** Testing %s **\\\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test',\",\n \"dependencies (i.e. checked out next sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \\\"1\\\" if\",\n \"rpath, verbose): cmd = ['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath,\",\n \"verbose): # Until rdar://53881101 is implemented, we cannot request a build of multiple\",\n \"remove_rpath(dest, rpath, verbose=verbose) for rpath in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec,\",\n \"product]) # Tell SwiftSyntax that we are building in a build-script environment so\",\n \"help='the toolchain to use when building this package') parser.add_argument('--update', action='store_true', help='update all SwiftPM\",\n \"% package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL:\",\n \"install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a',\",\n \"Updating dependencies of %s **\\\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose)\",\n \"'--build-path', build_dir, 'update'] check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath, build_dir,\",\n \"' '.join(e.cmd)) sys.exit(1) # Returns true if any of the actions in `action_names`\",\n \"rdar://53881101 is implemented, we cannot request a build of multiple # targets simultaneously.\",\n \"in products: invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose) def\",\n \"failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config))\",\n \"def get_products(package_dir): # FIXME: We ought to be able to query SwiftPM for\",\n \"%s' % (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for rpath in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose)\",\n \"generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose): package_name = os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig') with\",\n \"if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \\\"1\\\" if args.update: print(\\\"** Updating dependencies of %s\",\n \"build-script.py that knows how to build and install the stress tester utilities given\",\n \"config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Building %s failed' % package_name)\",\n \"selected_actions: return True else: return False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose): args\",\n \"or \\\"all\\\" in parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\\\"'--prefix' is required with the install\",\n \"def install(src, dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src, dest] print('installing %s to\",\n \"arg.replace('\\\"', '\\\\\\\\\\\"') else: return arg def get_products(package_dir): # FIXME: We ought to be\",\n \"build_dir, multiroot_data_file, config, env, verbose) def invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file,\",\n \"to package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name =\",\n \"printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\\\"generate-xcodeproj\\\", args.build_actions):\",\n \"need to build if we are just testing if should_run_any_action(['build', 'install'], args.build_actions): print(\\\"**\",\n \"def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log executed commands')\",\n \"action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL:\",\n \"install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir, 'lib',\",\n \"parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log executed commands') parser.add_argument('--prefix',\",\n \"sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \\\"1\\\" if args.update: print(\\\"** Updating dependencies of\",\n \"return arg def get_products(package_dir): # FIXME: We ought to be able to query\",\n \"== 'test': args.extend(['--test-product', product]) else: args.extend(['--product', product]) # Tell SwiftSyntax that we are\",\n \"under Apache License v2.0 with Runtime Library Exception See https://swift.org/LICENSE.txt for license information\",\n \"invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): # Until rdar://53881101\",\n \"cannot request a build of multiple # targets simultaneously. For now, just build\",\n \"toolchain to use when building this package') parser.add_argument('--update', action='store_true', help='update all SwiftPM dependencies')\",\n \"{sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' % package_name) args = [swift_exec, 'package',\",\n \"Make the rpath to sourcekitd relative in the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add\",\n \"swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): args = [swift_exec, action,\",\n \"authors Licensed under Apache License v2.0 with Runtime Library Exception See https://swift.org/LICENSE.txt for\",\n \"number of the following\\\", choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'], nargs=\\\"*\\\", default=['build']) parsed =\",\n \"pair in zip([value] * len(list), list) for item in pair] def escape_cmd_arg(arg): if\",\n \"choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'], nargs=\\\"*\\\", default=['build']) parsed = parser.parse_args(args) if (\\\"install\\\" in\",\n \"print(\\\"** Installing %s **\\\" % package_name) stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx')\",\n \"multiroot_data_file, config, env, verbose): # Until rdar://53881101 is implemented, we cannot request a\",\n \"env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Generating the Xcode project failed') printerr('Executing:\",\n \"for pair in zip([value] * len(list), list) for item in pair] def escape_cmd_arg(arg):\",\n \"create a unified build of SwiftSyntax with other projects.') parser.add_argument('--toolchain', required=True, help='the toolchain\",\n \"parser.add_argument('--no-local-deps', action='store_true', help='use normal remote dependencies when building') parser.add_argument('build_actions', help=\\\"Extra actions to perform.\",\n \"the stress tester utilities given a swift workspace. \\\"\\\"\\\" from __future__ import print_function\",\n \"dest] print('installing %s to %s' % (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for rpath in\",\n \"env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value, list): return [item for pair in zip([value] *\",\n \"= os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited)\",\n \"return True elif \\\"all\\\" in selected_actions: return True else: return False def update_swiftpm_dependencies(package_dir,\",\n \"verbose): cmd = ['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath, verbose):\",\n \"product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): args = [swift_exec, action, '--package-path', package_dir,\",\n \"'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath))\",\n \"sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env = dict(os.environ) # Use local dependencies (i.e. checked\",\n \"arg or ' ' in arg: return '\\\"%s\\\"' % arg.replace('\\\"', '\\\\\\\\\\\"') else: return\",\n \"now, just build one product after the other. for product in products: invoke_swift_single_product(package_dir,\",\n \"print(message, file=sys.stderr) def main(argv_prefix = []): args = parse_args(argv_prefix + sys.argv[1:]) run(args) def\",\n \"build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action == 'test': args.extend(['--test-product', product]) else: args.extend(['--product',\",\n \"'usr', 'lib') # Convert package_dir to absolute path, relative to root of repo.\",\n \"'bin') lib_dir = os.path.join(install_dir, 'lib', 'swift', 'macosx') for directory in [bin_dir, lib_dir]: if\",\n \"product in get_products(package_dir): src = os.path.join(build_dir, product) dest = os.path.join(bin_dir, product) # Create\",\n \"env, verbose): args = [swift_exec, 'package', '--package-path', package_dir, '--build-path', build_dir, 'update'] check_call(args, env=env,\",\n \"for rpath in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose):\",\n \"os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir, 'lib', 'swift', 'macosx') for directory in [bin_dir, lib_dir]:\",\n \"use when building this package') parser.add_argument('--update', action='store_true', help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true',\",\n \"check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath, build_dir, multiroot_data_file, config, env,\",\n \"package_dir, '-c', config, '--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action == 'test':\",\n \"part of the Swift.org open source project Copyright (c) 2014 - 2018 Apple\",\n \"project for %s **\\\" % package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except\",\n \"package_name = os.path.basename(args.package_dir) env = dict(os.environ) # Use local dependencies (i.e. checked out\",\n \"for this info. if package_dir.endswith(\\\"/SourceKitStressTester\\\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\\\"/SwiftEvolve\\\"): return ['swift-evolve'] else:\",\n \"print('installing %s to %s' % (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for rpath in rpaths_to_delete:\",\n \"sourcekit_searchpath check_call(args, env=env, verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir =\",\n \"sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\\\"generate-xcodeproj\\\", args.build_actions): print(\\\"** Generating Xcode project for\",\n \"'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib') # Convert package_dir to absolute path, relative\",\n \"with other projects.') parser.add_argument('--toolchain', required=True, help='the toolchain to use when building this package')\",\n \"action='store_true', help='log executed commands') parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path\",\n \"[swift_exec, 'package', '--package-path', package_dir, '--build-path', build_dir, 'update'] check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec,\",\n \"args = [swift_exec, action, '--package-path', package_dir, '-c', config, '--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file',\",\n \"Convert package_dir to absolute path, relative to root of repo. repo_path = os.path.dirname(__file__)\",\n \"= ['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath, verbose): cmd =\",\n \"should be run. def should_run_any_action(action_names, selected_actions): for action_name in action_names: if should_run_action(action_name, selected_actions):\",\n \"relative in the toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product,\",\n \"SwiftSyntax that we are building in a build-script environment so that # it\",\n \"FIXME: We ought to be able to query SwiftPM for this info. if\",\n \"Convert build_dir to absolute path, relative to package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return\",\n \"parsed.build_dir) return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env = dict(os.environ) #\",\n \"the rpath to the stdlib in in the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if\",\n \"in ['sk-stress-test', 'swift-evolve']: # Make the rpath to sourcekitd relative in the toolchain\",\n \"\\\"1\\\" if args.update: print(\\\"** Updating dependencies of %s **\\\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir,\",\n \"e: printerr('FAIL: Installing %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1)\",\n \"'--output', xcodeproj_path] check_call(args, env=env, verbose=verbose) def add_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-add_rpath',\",\n \"swift_exec, sourcekit_searchpath, env, verbose): package_name = os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig') with open(config_path,\",\n \"script for the main swift repository's build-script.py that knows how to build and\",\n \"Swift.org open source project Copyright (c) 2014 - 2018 Apple Inc. and the\",\n \"except subprocess.CalledProcessError as e: printerr('FAIL: Testing %s failed' % package_name) printerr('Executing: %s' %\",\n \"parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib') # Convert package_dir to absolute path, relative to\",\n \"action='store_true', help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal remote dependencies when building')\",\n \"parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env\",\n \"update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose): args = [swift_exec, 'package', '--package-path', package_dir, '--build-path', build_dir,\",\n \"sys.exit(1) if should_run_action(\\\"test\\\", args.build_actions): print(\\\"** Testing %s **\\\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec,\",\n \"rpath in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose): package_name\",\n \"query SwiftPM for this info. if package_dir.endswith(\\\"/SourceKitStressTester\\\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\\\"/SwiftEvolve\\\"): return\",\n \"root of repo. repo_path = os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert\",\n \"%s **\\\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError as\",\n \"actions to perform. Can be any number of the following\\\", choices=['all', 'build', 'test',\",\n \"verbose=verbose) def check_call(cmd, verbose, env=os.environ, **kwargs): if verbose: print(' '.join([escape_cmd_arg(arg) for arg in\",\n \"return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\\\"/SwiftEvolve\\\"): return ['swift-evolve'] else: return [] if __name__ ==\",\n \"printerr('FAIL: Building %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) output_dir\",\n \"subprocess def printerr(message): print(message, file=sys.stderr) def main(argv_prefix = []): args = parse_args(argv_prefix +\",\n \"(c) 2014 - 2018 Apple Inc. and the Swift project authors Licensed under\",\n \"built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env, verbose=verbose) def install_package(package_dir,\",\n \"= dict(os.environ) # Use local dependencies (i.e. checked out next sourcekit-lsp). if not\",\n \"def escape_cmd_arg(arg): if '\\\"' in arg or ' ' in arg: return '\\\"%s\\\"'\",\n \"swift_exec, build_dir, env, verbose): args = [swift_exec, 'package', '--package-path', package_dir, '--build-path', build_dir, 'update']\",\n \"a helper script for the main swift repository's build-script.py that knows how to\",\n \"rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for rpath in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose) def generate_xcodeproj(package_dir,\",\n \"to build and install the stress tester utilities given a swift workspace. \\\"\\\"\\\"\",\n \"= os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert build_dir to absolute path, relative to package_dir.\",\n \"output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\\\"generate-xcodeproj\\\", args.build_actions): print(\\\"** Generating Xcode project for %s\",\n \"def add_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd, verbose=verbose) def\",\n \"any number of the following\\\", choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'], nargs=\\\"*\\\", default=['build']) parsed\",\n \"stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir],\",\n \"to use when building this package') parser.add_argument('--update', action='store_true', help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps',\",\n \"is required with the install action\\\") parsed.swift_exec = os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir\",\n \"No need to build if we are just testing if should_run_any_action(['build', 'install'], args.build_actions):\",\n \"as e: printerr('FAIL: Testing %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd))\",\n \"build. No need to build if we are just testing if should_run_any_action(['build', 'install'],\",\n \"rpath, binary] check_call(cmd, verbose=verbose) def check_call(cmd, verbose, env=os.environ, **kwargs): if verbose: print(' '.join([escape_cmd_arg(arg)\",\n \"of Swift project authors ------------------------------------------------------------------------------ This is a helper script for the main\",\n \"% ' '.join(e.cmd)) sys.exit(1) # Returns true if any of the actions in\",\n \"verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir, 'bin') lib_dir\",\n \"args = [swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args, env=env,\",\n \"of %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # The\",\n \"the list of Swift project authors ------------------------------------------------------------------------------ This is a helper script for\",\n \"def main(argv_prefix = []): args = parse_args(argv_prefix + sys.argv[1:]) run(args) def parse_args(args): parser\",\n \"in arg: return '\\\"%s\\\"' % arg.replace('\\\"', '\\\\\\\\\\\"') else: return arg def get_products(package_dir): #\",\n \"False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose): args = [swift_exec, 'package', '--package-path', package_dir,\",\n \"able to query SwiftPM for this info. if package_dir.endswith(\\\"/SourceKitStressTester\\\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif\",\n \"'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args, env=env, verbose=verbose) def add_rpath(binary, rpath, verbose): cmd\",\n \"multiroot_data_file]) if action == 'test': args.extend(['--test-product', product]) else: args.extend(['--product', product]) # Tell SwiftSyntax\",\n \"def remove_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose) def\",\n \"parser.parse_args(args) if (\\\"install\\\" in parsed.build_actions or \\\"all\\\" in parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\\\"'--prefix'\",\n \"`action_names` should be run. def should_run_any_action(action_names, selected_actions): for action_name in action_names: if should_run_action(action_name,\",\n \"env['SWIFTCI_USE_LOCAL_DEPS'] = \\\"1\\\" if args.update: print(\\\"** Updating dependencies of %s **\\\" % package_name)\",\n \"package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build', products=get_products(args.package_dir), sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except\",\n \"we are just testing if should_run_any_action(['build', 'install'], args.build_actions): print(\\\"** Building %s **\\\" %\",\n \"verbose=verbose) def invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): #\",\n \"that we are building in a build-script environment so that # it does\",\n \"repo. repo_path = os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert build_dir to\",\n \"if should_run_action(\\\"install\\\", args.build_actions): print(\\\"** Installing %s **\\\" % package_name) stdlib_dir = os.path.join(args.toolchain, 'usr',\",\n \"pair] def escape_cmd_arg(arg): if '\\\"' in arg or ' ' in arg: return\",\n \"in arg or ' ' in arg: return '\\\"%s\\\"' % arg.replace('\\\"', '\\\\\\\\\\\"') else:\",\n \"parser.add_argument('build_actions', help=\\\"Extra actions to perform. Can be any number of the following\\\", choices=['all',\",\n \"= os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\\\"generate-xcodeproj\\\", args.build_actions): print(\\\"** Generating Xcode project for %s **\\\"\",\n \"action='store_true', help='use normal remote dependencies when building') parser.add_argument('build_actions', help=\\\"Extra actions to perform. Can\",\n \"parser.add_argument('--prefix', help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to an Xcode workspace\",\n \"return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value, list): return [item for pair in\",\n \"% package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"install\\\", args.build_actions): print(\\\"** Installing\",\n \"creates its own build. No need to build if we are just testing\",\n \"stderr=subprocess.STDOUT, **kwargs) def interleave(value, list): return [item for pair in zip([value] * len(list),\",\n \"sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir, 'lib', 'swift',\",\n \"cmd = ['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose) def check_call(cmd, verbose, env=os.environ, **kwargs):\",\n \"other. for product in products: invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config,\",\n \"test action creates its own build. No need to build if we are\",\n \"%s to %s' % (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for rpath in rpaths_to_delete: remove_rpath(dest,\",\n \"Runtime Library Exception See https://swift.org/LICENSE.txt for license information See https://swift.org/CONTRIBUTORS.txt for the list\",\n \"'-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose) def check_call(cmd, verbose, env=os.environ, **kwargs): if verbose: print('\",\n \"'test', 'install', 'generate-xcodeproj'], nargs=\\\"*\\\", default=['build']) parsed = parser.parse_args(args) if (\\\"install\\\" in parsed.build_actions or\",\n \"= [swift_exec, 'package', '--package-path', package_dir, '--build-path', build_dir, 'update'] check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir,\",\n \"in `action_names` should be run. def should_run_any_action(action_names, selected_actions): for action_name in action_names: if\",\n \"binary] check_call(cmd, verbose=verbose) def remove_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-delete_rpath', rpath, binary]\",\n \"'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL:\",\n \"env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Testing %s failed' % package_name) printerr('Executing:\",\n \"def should_run_action(action_name, selected_actions): if action_name in selected_actions: return True elif \\\"all\\\" in selected_actions:\",\n \"selected_actions): return True return False def should_run_action(action_name, selected_actions): if action_name in selected_actions: return\",\n \"multiple # targets simultaneously. For now, just build one product after the other.\",\n \"rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test', 'swift-evolve']: # Make the rpath to\",\n \"* len(list), list) for item in pair] def escape_cmd_arg(arg): if '\\\"' in arg\",\n \"Swift project authors ------------------------------------------------------------------------------ This is a helper script for the main swift\",\n \"help='install path') parser.add_argument('--config', default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to an Xcode workspace to\",\n \"list(rpaths_to_delete) # Add the rpath to the stdlib in in the toolchain rpaths_to_add\",\n \"for item in pair] def escape_cmd_arg(arg): if '\\\"' in arg or ' '\",\n \"action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose) def invoke_swift_single_product(package_dir, swift_exec, action, product,\",\n \"env=env, verbose=verbose) def add_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd,\",\n \"absolute path, relative to package_dir. parsed.build_dir = os.path.join(parsed.package_dir, parsed.build_dir) return parsed def run(args):\",\n \"verbose=verbose) def generate_xcodeproj(package_dir, swift_exec, sourcekit_searchpath, env, verbose): package_name = os.path.basename(package_dir) config_path = os.path.join(package_dir,\",\n \"import sys import os, platform import subprocess def printerr(message): print(message, file=sys.stderr) def main(argv_prefix\",\n \"Use local dependencies (i.e. checked out next sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] =\",\n \"python \\\"\\\"\\\" This source file is part of the Swift.org open source project\",\n \"env=env, verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir, 'bin')\",\n \"sys import os, platform import subprocess def printerr(message): print(message, file=sys.stderr) def main(argv_prefix =\",\n \"(\\\"install\\\" in parsed.build_actions or \\\"all\\\" in parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\\\"'--prefix' is required\",\n \"toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test', 'swift-evolve']: # Make the rpath\",\n \"and sk-swiftc-wrapper for product in get_products(package_dir): src = os.path.join(build_dir, product) dest = os.path.join(bin_dir,\",\n \"are building in a build-script environment so that # it does not need\",\n \"package_dir to absolute path, relative to root of repo. repo_path = os.path.dirname(__file__) parsed.package_dir\",\n \"config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir,\",\n \"xcodeproj_path] check_call(args, env=env, verbose=verbose) def add_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-add_rpath', rpath,\",\n \"build of multiple # targets simultaneously. For now, just build one product after\",\n \"= os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert build_dir to absolute path,\",\n \"= os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose)\",\n \"env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose):\",\n \"build-script environment so that # it does not need to rebuilt if it\",\n \"Install sk-stress-test and sk-swiftc-wrapper for product in get_products(package_dir): src = os.path.join(build_dir, product) dest\",\n \"should_run_action(\\\"test\\\", args.build_actions): print(\\\"** Testing %s **\\\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests'\",\n \"absolute path, relative to root of repo. repo_path = os.path.dirname(__file__) parsed.package_dir = os.path.realpath(\",\n \"sys.exit(1) # Returns true if any of the actions in `action_names` should be\",\n \"verbose): cmd = ['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose) def check_call(cmd, verbose, env=os.environ,\",\n \"if not os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test and sk-swiftc-wrapper for product in get_products(package_dir):\",\n \"os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test and sk-swiftc-wrapper for product in get_products(package_dir): src =\",\n \"for the main swift repository's build-script.py that knows how to build and install\",\n \"printerr('FAIL: Updating dependencies of %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd))\",\n \"% package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # The test action creates\",\n \"import subprocess def printerr(message): print(message, file=sys.stderr) def main(argv_prefix = []): args = parse_args(argv_prefix\",\n \"multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Building %s failed' %\",\n \"arg: return '\\\"%s\\\"' % arg.replace('\\\"', '\\\\\\\\\\\"') else: return arg def get_products(package_dir): # FIXME:\",\n \"os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert build_dir to absolute path, relative to package_dir. parsed.build_dir\",\n \"return [item for pair in zip([value] * len(list), list) for item in pair]\",\n \"os.path.join(parsed.toolchain, 'usr', 'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib') # Convert package_dir to\",\n \"open source project Copyright (c) 2014 - 2018 Apple Inc. and the Swift\",\n \"install(src, dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src, dest] print('installing %s to %s'\",\n \"interleave(value, list): return [item for pair in zip([value] * len(list), list) for item\",\n \"rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Installing %s failed' % package_name) printerr('Executing:\",\n \"add_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-add_rpath', rpath, binary] check_call(cmd, verbose=verbose) def remove_rpath(binary,\",\n \"sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): # Until rdar://53881101 is implemented, we cannot\",\n \"package_name = os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w') as config_file: config_file.write('''\",\n \"default='debug') parser.add_argument('--build-dir', default='.build') parser.add_argument('--multiroot-data-file', help='Path to an Xcode workspace to create a unified\",\n \"help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal remote dependencies when building') parser.add_argument('build_actions',\",\n \"= ['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose) def check_call(cmd, verbose, env=os.environ, **kwargs): if\",\n \"the Swift project authors Licensed under Apache License v2.0 with Runtime Library Exception\",\n \"stress tester utilities given a swift workspace. \\\"\\\"\\\" from __future__ import print_function import\",\n \"e: printerr('FAIL: Generating the Xcode project failed') printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1)\",\n \"'1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env, verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete,\",\n \"verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Building %s failed' % package_name) printerr('Executing: %s'\",\n \"to build if we are just testing if should_run_any_action(['build', 'install'], args.build_actions): print(\\\"** Building\",\n \"= [swift_exec, action, '--package-path', package_dir, '-c', config, '--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file])\",\n \"'%s.xcodeproj' % package_name) args = [swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output',\",\n \"local dependencies (i.e. checked out next sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \\\"1\\\"\",\n \"import os, platform import subprocess def printerr(message): print(message, file=sys.stderr) def main(argv_prefix = []):\",\n \"args = [swift_exec, 'package', '--package-path', package_dir, '--build-path', build_dir, 'update'] check_call(args, env=env, verbose=verbose) def\",\n \"the actions in `action_names` should be run. def should_run_any_action(action_names, selected_actions): for action_name in\",\n \"= os.path.join(package_dir, '%s.xcodeproj' % package_name) args = [swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides',\",\n \"we modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add the rpath to the stdlib\",\n \"default=['build']) parsed = parser.parse_args(args) if (\\\"install\\\" in parsed.build_actions or \\\"all\\\" in parsed.build_actions) and\",\n \"when building this package') parser.add_argument('--update', action='store_true', help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use\",\n \"unified build of SwiftSyntax with other projects.') parser.add_argument('--toolchain', required=True, help='the toolchain to use\",\n \"that # it does not need to rebuilt if it has already been\",\n \"e: printerr('FAIL: Building %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1)\",\n \"as e: printerr('FAIL: Installing %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd))\",\n \"parsed.build_actions or \\\"all\\\" in parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\\\"'--prefix' is required with the\",\n \"action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as\",\n \"install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir,\",\n \"elif \\\"all\\\" in selected_actions: return True else: return False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir,\",\n \"with open(config_path, 'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS = {sourcekit_searchpath}\",\n \"package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Updating\",\n \"**\\\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e:\",\n \"return False def should_run_action(action_name, selected_actions): if action_name in selected_actions: return True elif \\\"all\\\"\",\n \"run. def should_run_any_action(action_names, selected_actions): for action_name in action_names: if should_run_action(action_name, selected_actions): return True\",\n \"env, verbose) def invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose):\",\n \"this package') parser.add_argument('--update', action='store_true', help='update all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal remote\",\n \"utilities given a swift workspace. \\\"\\\"\\\" from __future__ import print_function import argparse import\",\n \"See https://swift.org/LICENSE.txt for license information See https://swift.org/CONTRIBUTORS.txt for the list of Swift project\",\n \"args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \\\"1\\\" if args.update: print(\\\"** Updating dependencies of %s **\\\" %\",\n \"%s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # Returns true\",\n \"build_dir, env, verbose): args = [swift_exec, 'package', '--package-path', package_dir, '--build-path', build_dir, 'update'] check_call(args,\",\n \"= {sourcekit_searchpath} $(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' % package_name) args = [swift_exec,\",\n \"'-a', src, dest] print('installing %s to %s' % (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for\",\n \"try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Updating dependencies\",\n \"package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env,\",\n \"check_call(args, env=env, verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir,\",\n \"os, platform import subprocess def printerr(message): print(message, file=sys.stderr) def main(argv_prefix = []): args\",\n \"for the list of Swift project authors ------------------------------------------------------------------------------ This is a helper script\",\n \"to an Xcode workspace to create a unified build of SwiftSyntax with other\",\n \"all SwiftPM dependencies') parser.add_argument('--no-local-deps', action='store_true', help='use normal remote dependencies when building') parser.add_argument('build_actions', help=\\\"Extra\",\n \"sys.argv[1:]) run(args) def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log\",\n \"for directory in [bin_dir, lib_dir]: if not os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test and\",\n \"sys.exit(1) if should_run_action(\\\"install\\\", args.build_actions): print(\\\"** Installing %s **\\\" % package_name) stdlib_dir = os.path.join(args.toolchain,\",\n \"the stdlib in in the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test',\",\n \"in in the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx'] if product in ['sk-stress-test', 'swift-evolve']: #\",\n \"Apache License v2.0 with Runtime Library Exception See https://swift.org/LICENSE.txt for license information See\",\n \"% ' '.join(e.cmd)) sys.exit(1) output_dir = os.path.realpath(os.path.join(args.build_dir, args.config)) if should_run_action(\\\"generate-xcodeproj\\\", args.build_actions): print(\\\"** Generating\",\n \"Add the rpath to the stdlib in in the toolchain rpaths_to_add = ['@executable_path/../lib/swift/macosx']\",\n \"remove_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-delete_rpath', rpath, binary] check_call(cmd, verbose=verbose) def check_call(cmd,\",\n \"directory in [bin_dir, lib_dir]: if not os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test and sk-swiftc-wrapper\",\n \"cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value, list): return [item for pair\",\n \"parser.add_argument('--toolchain', required=True, help='the toolchain to use when building this package') parser.add_argument('--update', action='store_true', help='update\",\n \"= '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env, verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir,\",\n \"dest = os.path.join(bin_dir, product) # Create a copy of the list since we\",\n \"sk-swiftc-wrapper for product in get_products(package_dir): src = os.path.join(build_dir, product) dest = os.path.join(bin_dir, product)\",\n \"env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env, verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose):\",\n \"env = dict(os.environ) # Use local dependencies (i.e. checked out next sourcekit-lsp). if\",\n \"run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env = dict(os.environ) # Use local dependencies (i.e.\",\n \"os.makedirs(directory) # Install sk-stress-test and sk-swiftc-wrapper for product in get_products(package_dir): src = os.path.join(build_dir,\",\n \"main(argv_prefix = []): args = parse_args(argv_prefix + sys.argv[1:]) run(args) def parse_args(args): parser =\",\n \"os.path.join(parsed.toolchain, 'usr', 'lib') # Convert package_dir to absolute path, relative to root of\",\n \"def invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): args =\",\n \"to be able to query SwiftPM for this info. if package_dir.endswith(\\\"/SourceKitStressTester\\\"): return ['sk-stress-test',\",\n \"bin_dir = os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir, 'lib', 'swift', 'macosx') for directory in\",\n \"sourcekit_searchpath, env, verbose): package_name = os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w')\",\n \"# targets simultaneously. For now, just build one product after the other. for\",\n \"Testing %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"install\\\",\",\n \"%s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # The test\",\n \"action, '--package-path', package_dir, '-c', config, '--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action\",\n \"= list(rpaths_to_delete) # Add the rpath to the stdlib in in the toolchain\",\n \"parse_args(argv_prefix + sys.argv[1:]) run(args) def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose',\",\n \"% package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='test', products=['%sPackageTests' % package_name], sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config,\",\n \"config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Testing %s failed' % package_name)\",\n \"Xcode project for %s **\\\" % package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose)\",\n \"to create a unified build of SwiftSyntax with other projects.') parser.add_argument('--toolchain', required=True, help='the\",\n \"be able to query SwiftPM for this info. if package_dir.endswith(\\\"/SourceKitStressTester\\\"): return ['sk-stress-test', 'sk-swiftc-wrapper']\",\n \"required=True, help='the toolchain to use when building this package') parser.add_argument('--update', action='store_true', help='update all\",\n \"verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Updating dependencies of %s failed' % package_name)\",\n \"printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # The test action creates its own\",\n \"swift_exec, action, products, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): # Until rdar://53881101 is\",\n \"parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env = dict(os.environ) # Use local\",\n \"build_dir, rpaths_to_delete, verbose): bin_dir = os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir, 'lib', 'swift', 'macosx')\",\n \"escape_cmd_arg(arg): if '\\\"' in arg or ' ' in arg: return '\\\"%s\\\"' %\",\n \"products: invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose) def invoke_swift_single_product(package_dir,\",\n \"in pair] def escape_cmd_arg(arg): if '\\\"' in arg or ' ' in arg:\",\n \"- 2018 Apple Inc. and the Swift project authors Licensed under Apache License\",\n \"action_names: if should_run_action(action_name, selected_actions): return True return False def should_run_action(action_name, selected_actions): if action_name\",\n \"rpath in rpaths_to_delete: remove_rpath(dest, rpath, verbose=verbose) for rpath in rpaths_to_add: add_rpath(dest, rpath, verbose=verbose)\",\n \"update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Updating dependencies of\",\n \"'Config.xcconfig') with open(config_path, 'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS =\",\n \"rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src, dest] print('installing %s to %s' % (os.path.basename(src),\",\n \"workspace. \\\"\\\"\\\" from __future__ import print_function import argparse import sys import os, platform\",\n \"build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Building %s failed'\",\n \"toolchain rpaths_to_delete_for_this_product += [sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def\",\n \"src, dest] print('installing %s to %s' % (os.path.basename(src), dest)) check_call(copy_cmd, verbose=verbose) for rpath\",\n \"is part of the Swift.org open source project Copyright (c) 2014 - 2018\",\n \"'usr', 'bin', 'swift') parsed.sourcekitd_dir = os.path.join(parsed.toolchain, 'usr', 'lib') # Convert package_dir to absolute\",\n \"[sourcekit_searchpath] rpaths_to_add += ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest, rpaths_to_delete,\",\n \"as e: printerr('FAIL: Updating dependencies of %s failed' % package_name) printerr('Executing: %s' %\",\n \"= sourcekit_searchpath check_call(args, env=env, verbose=verbose) def install_package(package_dir, install_dir, sourcekit_searchpath, build_dir, rpaths_to_delete, verbose): bin_dir\",\n \"info. if package_dir.endswith(\\\"/SourceKitStressTester\\\"): return ['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\\\"/SwiftEvolve\\\"): return ['swift-evolve'] else: return []\",\n \"\\\"all\\\" in parsed.build_actions) and not parsed.prefix: ArgumentParser.error(\\\"'--prefix' is required with the install action\\\")\",\n \"$(inherited) '''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' % package_name) args = [swift_exec, 'package', '--package-path',\",\n \"of SwiftSyntax with other projects.') parser.add_argument('--toolchain', required=True, help='the toolchain to use when building\",\n \"'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as e:\",\n \"build and install the stress tester utilities given a swift workspace. \\\"\\\"\\\" from\",\n \"Xcode project failed') printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"test\\\", args.build_actions): print(\\\"**\",\n \"sys.exit(1) # The test action creates its own build. No need to build\",\n \"See https://swift.org/CONTRIBUTORS.txt for the list of Swift project authors ------------------------------------------------------------------------------ This is a\",\n \"'''.format(sourcekit_searchpath=sourcekit_searchpath)) xcodeproj_path = os.path.join(package_dir, '%s.xcodeproj' % package_name) args = [swift_exec, 'package', '--package-path', package_dir,\",\n \"the Swift.org open source project Copyright (c) 2014 - 2018 Apple Inc. and\",\n \"of the following\\\", choices=['all', 'build', 'test', 'install', 'generate-xcodeproj'], nargs=\\\"*\\\", default=['build']) parsed = parser.parse_args(args)\",\n \"return parsed def run(args): sourcekit_searchpath=args.sourcekitd_dir package_name = os.path.basename(args.package_dir) env = dict(os.environ) # Use\",\n \"'lib', 'swift', 'macosx') try: install_package(args.package_dir, install_dir=args.prefix, sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as\",\n \"list): return [item for pair in zip([value] * len(list), list) for item in\",\n \"knows how to build and install the stress tester utilities given a swift\",\n \"just testing if should_run_any_action(['build', 'install'], args.build_actions): print(\\\"** Building %s **\\\" % package_name) try:\",\n \"the Xcode project failed') printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"test\\\", args.build_actions):\",\n \"**kwargs): if verbose: print(' '.join([escape_cmd_arg(arg) for arg in cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT,\",\n \"'.join([escape_cmd_arg(arg) for arg in cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value, list):\",\n \"build_dir, 'update'] check_call(args, env=env, verbose=verbose) def invoke_swift(package_dir, swift_exec, action, products, sourcekit_searchpath, build_dir, multiroot_data_file,\",\n \"list of Swift project authors ------------------------------------------------------------------------------ This is a helper script for the\",\n \"been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env, verbose=verbose) def\",\n \"should_run_action(action_name, selected_actions): return True return False def should_run_action(action_name, selected_actions): if action_name in selected_actions:\",\n \"True return False def should_run_action(action_name, selected_actions): if action_name in selected_actions: return True elif\",\n \"product) dest = os.path.join(bin_dir, product) # Create a copy of the list since\",\n \"products, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose): # Until rdar://53881101 is implemented, we\",\n \"project Copyright (c) 2014 - 2018 Apple Inc. and the Swift project authors\",\n \"need to rebuilt if it has already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1'\",\n \"since we modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add the rpath to the\",\n \"\\\"\\\"\\\" from __future__ import print_function import argparse import sys import os, platform import\",\n \"%s' % ' '.join(e.cmd)) sys.exit(1) if should_run_action(\\\"install\\\", args.build_actions): print(\\\"** Installing %s **\\\" %\",\n \"printerr('FAIL: Installing %s failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) #\",\n \"# Until rdar://53881101 is implemented, we cannot request a build of multiple #\",\n \"if product in ['sk-stress-test', 'swift-evolve']: # Make the rpath to sourcekitd relative in\",\n \"Licensed under Apache License v2.0 with Runtime Library Exception See https://swift.org/LICENSE.txt for license\",\n \"env, verbose): args = [swift_exec, action, '--package-path', package_dir, '-c', config, '--build-path', build_dir] if\",\n \"zip([value] * len(list), list) for item in pair] def escape_cmd_arg(arg): if '\\\"' in\",\n \"'\\\"%s\\\"' % arg.replace('\\\"', '\\\\\\\\\\\"') else: return arg def get_products(package_dir): # FIXME: We ought\",\n \"an Xcode workspace to create a unified build of SwiftSyntax with other projects.')\",\n \"should_run_action(action_name, selected_actions): if action_name in selected_actions: return True elif \\\"all\\\" in selected_actions: return\",\n \"just build one product after the other. for product in products: invoke_swift_single_product(package_dir, swift_exec,\",\n \"+= ['@executable_path/../lib'] install(src, dest, rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest, rpaths_to_delete, rpaths_to_add, verbose):\",\n \"check_call(args, env=env, verbose=verbose) def add_rpath(binary, rpath, verbose): cmd = ['install_name_tool', '-add_rpath', rpath, binary]\",\n \"env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Updating dependencies of %s failed' %\",\n \"invoke_swift_single_product(package_dir, swift_exec, action, product, sourcekit_searchpath, build_dir, multiroot_data_file, config, env, verbose) def invoke_swift_single_product(package_dir, swift_exec,\",\n \"run(args) def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log executed\",\n \"parsed = parser.parse_args(args) if (\\\"install\\\" in parsed.build_actions or \\\"all\\\" in parsed.build_actions) and not\",\n \"to rebuilt if it has already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH']\",\n \"of repo. repo_path = os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert build_dir\",\n \"source file is part of the Swift.org open source project Copyright (c) 2014\",\n \"os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w') as config_file: config_file.write(''' SYSTEM_FRAMEWORK_SEARCH_PATHS = {sourcekit_searchpath} $(inherited) LD_RUNPATH_SEARCH_PATHS\",\n \"Inc. and the Swift project authors Licensed under Apache License v2.0 with Runtime\",\n \"parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true', help='log executed commands') parser.add_argument('--prefix', help='install\",\n \"arg in cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value, list): return [item\",\n \"Swift project authors Licensed under Apache License v2.0 with Runtime Library Exception See\",\n \"SwiftSyntax with other projects.') parser.add_argument('--toolchain', required=True, help='the toolchain to use when building this\",\n \"'--package-path', package_dir, '-c', config, '--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action ==\",\n \"os.path.join(package_dir, '%s.xcodeproj' % package_name) args = [swift_exec, 'package', '--package-path', package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path,\",\n \"This source file is part of the Swift.org open source project Copyright (c)\",\n \"get_products(package_dir): # FIXME: We ought to be able to query SwiftPM for this\",\n \"ought to be able to query SwiftPM for this info. if package_dir.endswith(\\\"/SourceKitStressTester\\\"): return\",\n \"sourcekit_searchpath=sourcekit_searchpath, build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Installing %s failed' %\",\n \"to perform. Can be any number of the following\\\", choices=['all', 'build', 'test', 'install',\",\n \"build_dir=output_dir, rpaths_to_delete=[stdlib_dir], verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Installing %s failed' % package_name)\",\n \"Installing %s **\\\" % package_name) stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib', 'swift', 'macosx') try:\",\n \"%s' % ' '.join(e.cmd)) sys.exit(1) # Returns true if any of the actions\",\n \"'--build-path', build_dir] if multiroot_data_file: args.extend(['--multiroot-data-file', multiroot_data_file]) if action == 'test': args.extend(['--test-product', product]) else:\",\n \"def printerr(message): print(message, file=sys.stderr) def main(argv_prefix = []): args = parse_args(argv_prefix + sys.argv[1:])\",\n \"package_name) try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Generating\",\n \"------------------------------------------------------------------------------ This is a helper script for the main swift repository's build-script.py that\",\n \"list since we modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add the rpath to\",\n \"if verbose: print(' '.join([escape_cmd_arg(arg) for arg in cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs)\",\n \"verbose): args = [swift_exec, action, '--package-path', package_dir, '-c', config, '--build-path', build_dir] if multiroot_data_file:\",\n \"rpaths_to_delete_for_this_product = list(rpaths_to_delete) # Add the rpath to the stdlib in in the\",\n \"v2.0 with Runtime Library Exception See https://swift.org/LICENSE.txt for license information See https://swift.org/CONTRIBUTORS.txt for\",\n \"product in ['sk-stress-test', 'swift-evolve']: # Make the rpath to sourcekitd relative in the\",\n \"get_products(package_dir): src = os.path.join(build_dir, product) dest = os.path.join(bin_dir, product) # Create a copy\",\n \"a copy of the list since we modify it rpaths_to_delete_for_this_product = list(rpaths_to_delete) #\",\n \"sourcekit_searchpath=sourcekit_searchpath, build_dir=args.build_dir, multiroot_data_file=args.multiroot_data_file, config=args.config, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Building %s\",\n \"['sk-stress-test', 'sk-swiftc-wrapper'] elif package_dir.endswith(\\\"/SwiftEvolve\\\"): return ['swift-evolve'] else: return [] if __name__ == '__main__':\",\n \"= parse_args(argv_prefix + sys.argv[1:]) run(args) def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v',\",\n \"to root of repo. repo_path = os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir)) #\",\n \"should_run_action(\\\"install\\\", args.build_actions): print(\\\"** Installing %s **\\\" % package_name) stdlib_dir = os.path.join(args.toolchain, 'usr', 'lib',\",\n \"'.join(e.cmd)) sys.exit(1) if should_run_action(\\\"install\\\", args.build_actions): print(\\\"** Installing %s **\\\" % package_name) stdlib_dir =\",\n \"package_dir, 'generate-xcodeproj', '--xcconfig-overrides', config_path, '--output', xcodeproj_path] check_call(args, env=env, verbose=verbose) def add_rpath(binary, rpath, verbose):\",\n \"failed' % package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # The test action\",\n \"and the Swift project authors Licensed under Apache License v2.0 with Runtime Library\",\n \"verbose): bin_dir = os.path.join(install_dir, 'bin') lib_dir = os.path.join(install_dir, 'lib', 'swift', 'macosx') for directory\",\n \"in cmd])) return subprocess.check_call(cmd, env=env, stderr=subprocess.STDOUT, **kwargs) def interleave(value, list): return [item for\",\n \"other projects.') parser.add_argument('--toolchain', required=True, help='the toolchain to use when building this package') parser.add_argument('--update',\",\n \"os.path.dirname(__file__) parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert build_dir to absolute path, relative\",\n \"(i.e. checked out next sourcekit-lsp). if not args.no_local_deps: env['SWIFTCI_USE_LOCAL_DEPS'] = \\\"1\\\" if args.update:\",\n \"workspace to create a unified build of SwiftSyntax with other projects.') parser.add_argument('--toolchain', required=True,\",\n \"'.join(e.cmd)) sys.exit(1) if should_run_action(\\\"test\\\", args.build_actions): print(\\\"** Testing %s **\\\" % package_name) try: invoke_swift(package_dir=args.package_dir,\",\n \"verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Testing %s failed' % package_name) printerr('Executing: %s'\",\n \"env, verbose): package_name = os.path.basename(package_dir) config_path = os.path.join(package_dir, 'Config.xcconfig') with open(config_path, 'w') as\",\n \"True else: return False def update_swiftpm_dependencies(package_dir, swift_exec, build_dir, env, verbose): args = [swift_exec,\",\n \"generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Generating the Xcode\",\n \"print(\\\"** Updating dependencies of %s **\\\" % package_name) try: update_swiftpm_dependencies(package_dir=args.package_dir, swift_exec=args.swift_exec, build_dir=args.build_dir, env=env,\",\n \"import print_function import argparse import sys import os, platform import subprocess def printerr(message):\",\n \"Library Exception See https://swift.org/LICENSE.txt for license information See https://swift.org/CONTRIBUTORS.txt for the list of\",\n \"the main swift repository's build-script.py that knows how to build and install the\",\n \"binary] check_call(cmd, verbose=verbose) def check_call(cmd, verbose, env=os.environ, **kwargs): if verbose: print(' '.join([escape_cmd_arg(arg) for\",\n \"has already been built before. env['SWIFT_BUILD_SCRIPT_ENVIRONMENT'] = '1' env['SWIFT_STRESS_TESTER_SOURCEKIT_SEARCHPATH'] = sourcekit_searchpath check_call(args, env=env,\",\n \"'lib', 'swift', 'macosx') for directory in [bin_dir, lib_dir]: if not os.path.exists(directory): os.makedirs(directory) #\",\n \"parsed.package_dir = os.path.realpath( os.path.join(repo_path, parsed.package_dir)) # Convert build_dir to absolute path, relative to\",\n \"try: generate_xcodeproj(args.package_dir, swift_exec=args.swift_exec, sourcekit_searchpath=sourcekit_searchpath, env=env, verbose=args.verbose) except subprocess.CalledProcessError as e: printerr('FAIL: Generating the\",\n \"+ sys.argv[1:]) run(args) def parse_args(args): parser = argparse.ArgumentParser(prog='BUILD-SCRIPT-HELPER.PY') parser.add_argument('--package-dir', default='SourceKitStressTester') parser.add_argument('-v', '--verbose', action='store_true',\",\n \"action == 'test': args.extend(['--test-product', product]) else: args.extend(['--product', product]) # Tell SwiftSyntax that we\",\n \"package_name) printerr('Executing: %s' % ' '.join(e.cmd)) sys.exit(1) # Returns true if any of\",\n \"args.extend(['--test-product', product]) else: args.extend(['--product', product]) # Tell SwiftSyntax that we are building in\",\n \"rpaths_to_delete=rpaths_to_delete_for_this_product, rpaths_to_add=rpaths_to_add, verbose=verbose) def install(src, dest, rpaths_to_delete, rpaths_to_add, verbose): copy_cmd=['rsync', '-a', src, dest]\",\n \"in zip([value] * len(list), list) for item in pair] def escape_cmd_arg(arg): if '\\\"'\",\n \"project authors ------------------------------------------------------------------------------ This is a helper script for the main swift repository's\",\n \"'macosx') for directory in [bin_dir, lib_dir]: if not os.path.exists(directory): os.makedirs(directory) # Install sk-stress-test\",\n \"building') parser.add_argument('build_actions', help=\\\"Extra actions to perform. Can be any number of the following\\\",\",\n \"os.path.join(build_dir, product) dest = os.path.join(bin_dir, product) # Create a copy of the list\",\n \"should_run_any_action(['build', 'install'], args.build_actions): print(\\\"** Building %s **\\\" % package_name) try: invoke_swift(package_dir=args.package_dir, swift_exec=args.swift_exec, action='build',\"\n]","isConversational":false}}},{"rowIdx":4587,"cells":{"ngram":{"kind":"list like","value":["group id\", \"name\": \"Light group\", \"type\": \"LightGroup\", \"state\": {\"all_on\": False, \"any_on\": True}, \"action\":","openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID from .test_gateway import","config_entry.data, \"/groups/1/scenes/1/recall\" ) # Service turn on scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID:","[{\"id\": \"1\", \"name\": \"Scene\"}], \"lights\": [], } } } with patch.dict(DECONZ_WEB_REQUEST, data): config_entry","from .test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async def test_no_scenes(opp, aioclient_mock): \"\"\"Test","{ \"1\": { \"id\": \"Light group id\", \"name\": \"Light group\", \"type\": \"LightGroup\", \"state\":","1 assert opp.states.get(\"scene.light_group_scene\") # Verify service calls mock_deconz_put_request( aioclient_mock, config_entry.data, \"/groups/1/scenes/1/recall\" ) #","\"\"\"deCONZ scene platform tests.\"\"\" from unittest.mock import patch from openpeerpower.components.scene import DOMAIN as","scenes works.\"\"\" data = { \"groups\": { \"1\": { \"id\": \"Light group id\",","( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async def test_no_scenes(opp, aioclient_mock): \"\"\"Test that scenes can","test_no_scenes(opp, aioclient_mock): \"\"\"Test that scenes can be loaded without scenes being available.\"\"\" await","DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async def test_no_scenes(opp, aioclient_mock): \"\"\"Test that scenes can be","be loaded without scenes being available.\"\"\" await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 0","{\"all_on\": False, \"any_on\": True}, \"action\": {}, \"scenes\": [{\"id\": \"1\", \"name\": \"Scene\"}], \"lights\": [],","= await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 1 assert opp.states.get(\"scene.light_group_scene\") # Verify service","that scenes works.\"\"\" data = { \"groups\": { \"1\": { \"id\": \"Light group","from unittest.mock import patch from openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const","import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID from .test_gateway import (","\"1\": { \"id\": \"Light group id\", \"name\": \"Light group\", \"type\": \"LightGroup\", \"state\": {\"all_on\":","\"name\": \"Scene\"}], \"lights\": [], } } } with patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await","without scenes being available.\"\"\" await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 0 async def","id\", \"name\": \"Light group\", \"type\": \"LightGroup\", \"state\": {\"all_on\": False, \"any_on\": True}, \"action\": {},","patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 1 assert opp.states.get(\"scene.light_group_scene\")","scene platform tests.\"\"\" from unittest.mock import patch from openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN,","Verify service calls mock_deconz_put_request( aioclient_mock, config_entry.data, \"/groups/1/scenes/1/recall\" ) # Service turn on scene","setup_deconz_integration, ) async def test_no_scenes(opp, aioclient_mock): \"\"\"Test that scenes can be loaded without",") # Service turn on scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \"scene.light_group_scene\"}, blocking=True,","calls mock_deconz_put_request( aioclient_mock, config_entry.data, \"/groups/1/scenes/1/recall\" ) # Service turn on scene await opp.services.async_call(","\"LightGroup\", \"state\": {\"all_on\": False, \"any_on\": True}, \"action\": {}, \"scenes\": [{\"id\": \"1\", \"name\": \"Scene\"}],","await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 0 async def test_scenes(opp, aioclient_mock): \"\"\"Test that","aioclient_mock, config_entry.data, \"/groups/1/scenes/1/recall\" ) # Service turn on scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON,","len(opp.states.async_all()) == 0 async def test_scenes(opp, aioclient_mock): \"\"\"Test that scenes works.\"\"\" data =","SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \"scene.light_group_scene\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2] == {} await opp.config_entries.async_unload(config_entry.entry_id) assert","} } with patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) ==","opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \"scene.light_group_scene\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2] == {} await opp.config_entries.async_unload(config_entry.entry_id)","aioclient_mock): \"\"\"Test that scenes works.\"\"\" data = { \"groups\": { \"1\": { \"id\":","} } } with patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all())","\"lights\": [], } } } with patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await setup_deconz_integration(opp, aioclient_mock)","on scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \"scene.light_group_scene\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2] ==","that scenes can be loaded without scenes being available.\"\"\" await setup_deconz_integration(opp, aioclient_mock) assert","len(opp.states.async_all()) == 1 assert opp.states.get(\"scene.light_group_scene\") # Verify service calls mock_deconz_put_request( aioclient_mock, config_entry.data, \"/groups/1/scenes/1/recall\"","works.\"\"\" data = { \"groups\": { \"1\": { \"id\": \"Light group id\", \"name\":","loaded without scenes being available.\"\"\" await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 0 async","= { \"groups\": { \"1\": { \"id\": \"Light group id\", \"name\": \"Light group\",","\"any_on\": True}, \"action\": {}, \"scenes\": [{\"id\": \"1\", \"name\": \"Scene\"}], \"lights\": [], } }","import patch from openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID","group\", \"type\": \"LightGroup\", \"state\": {\"all_on\": False, \"any_on\": True}, \"action\": {}, \"scenes\": [{\"id\": \"1\",","\"scene.light_group_scene\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2] == {} await opp.config_entries.async_unload(config_entry.entry_id) assert len(opp.states.async_all()) == 0","\"\"\"Test that scenes works.\"\"\" data = { \"groups\": { \"1\": { \"id\": \"Light","setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 1 assert opp.states.get(\"scene.light_group_scene\") # Verify service calls mock_deconz_put_request(","opp.states.get(\"scene.light_group_scene\") # Verify service calls mock_deconz_put_request( aioclient_mock, config_entry.data, \"/groups/1/scenes/1/recall\" ) # Service turn","== 0 async def test_scenes(opp, aioclient_mock): \"\"\"Test that scenes works.\"\"\" data = {","\"/groups/1/scenes/1/recall\" ) # Service turn on scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \"scene.light_group_scene\"},","aioclient_mock): \"\"\"Test that scenes can be loaded without scenes being available.\"\"\" await setup_deconz_integration(opp,","tests.\"\"\" from unittest.mock import patch from openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from","platform tests.\"\"\" from unittest.mock import patch from openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON","{ \"groups\": { \"1\": { \"id\": \"Light group id\", \"name\": \"Light group\", \"type\":","\"scenes\": [{\"id\": \"1\", \"name\": \"Scene\"}], \"lights\": [], } } } with patch.dict(DECONZ_WEB_REQUEST, data):","from openpeerpower.const import ATTR_ENTITY_ID from .test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async","{ATTR_ENTITY_ID: \"scene.light_group_scene\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2] == {} await opp.config_entries.async_unload(config_entry.entry_id) assert len(opp.states.async_all()) ==","mock_deconz_put_request, setup_deconz_integration, ) async def test_no_scenes(opp, aioclient_mock): \"\"\"Test that scenes can be loaded","} with patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 1","\"type\": \"LightGroup\", \"state\": {\"all_on\": False, \"any_on\": True}, \"action\": {}, \"scenes\": [{\"id\": \"1\", \"name\":","def test_no_scenes(opp, aioclient_mock): \"\"\"Test that scenes can be loaded without scenes being available.\"\"\"","\"Light group\", \"type\": \"LightGroup\", \"state\": {\"all_on\": False, \"any_on\": True}, \"action\": {}, \"scenes\": [{\"id\":","ATTR_ENTITY_ID from .test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async def test_no_scenes(opp, aioclient_mock):","scenes can be loaded without scenes being available.\"\"\" await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all())","data): config_entry = await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 1 assert opp.states.get(\"scene.light_group_scene\") #","scenes being available.\"\"\" await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 0 async def test_scenes(opp,","test_scenes(opp, aioclient_mock): \"\"\"Test that scenes works.\"\"\" data = { \"groups\": { \"1\": {","\"Light group id\", \"name\": \"Light group\", \"type\": \"LightGroup\", \"state\": {\"all_on\": False, \"any_on\": True},","service calls mock_deconz_put_request( aioclient_mock, config_entry.data, \"/groups/1/scenes/1/recall\" ) # Service turn on scene await","def test_scenes(opp, aioclient_mock): \"\"\"Test that scenes works.\"\"\" data = { \"groups\": { \"1\":","<filename>tests/components/deconz/test_scene.py \"\"\"deCONZ scene platform tests.\"\"\" from unittest.mock import patch from openpeerpower.components.scene import DOMAIN","\"Scene\"}], \"lights\": [], } } } with patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await setup_deconz_integration(opp,","# Service turn on scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \"scene.light_group_scene\"}, blocking=True, )","available.\"\"\" await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 0 async def test_scenes(opp, aioclient_mock): \"\"\"Test",".test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async def test_no_scenes(opp, aioclient_mock): \"\"\"Test that","being available.\"\"\" await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 0 async def test_scenes(opp, aioclient_mock):","setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 0 async def test_scenes(opp, aioclient_mock): \"\"\"Test that scenes","assert opp.states.get(\"scene.light_group_scene\") # Verify service calls mock_deconz_put_request( aioclient_mock, config_entry.data, \"/groups/1/scenes/1/recall\" ) # Service","\"id\": \"Light group id\", \"name\": \"Light group\", \"type\": \"LightGroup\", \"state\": {\"all_on\": False, \"any_on\":","with patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 1 assert",") async def test_no_scenes(opp, aioclient_mock): \"\"\"Test that scenes can be loaded without scenes","as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID from .test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request,","False, \"any_on\": True}, \"action\": {}, \"scenes\": [{\"id\": \"1\", \"name\": \"Scene\"}], \"lights\": [], }","SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID from .test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, )","[], } } } with patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await setup_deconz_integration(opp, aioclient_mock) assert","config_entry = await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 1 assert opp.states.get(\"scene.light_group_scene\") # Verify","{}, \"scenes\": [{\"id\": \"1\", \"name\": \"Scene\"}], \"lights\": [], } } } with patch.dict(DECONZ_WEB_REQUEST,","aioclient_mock) assert len(opp.states.async_all()) == 1 assert opp.states.get(\"scene.light_group_scene\") # Verify service calls mock_deconz_put_request( aioclient_mock,","\"\"\"Test that scenes can be loaded without scenes being available.\"\"\" await setup_deconz_integration(opp, aioclient_mock)","{ \"id\": \"Light group id\", \"name\": \"Light group\", \"type\": \"LightGroup\", \"state\": {\"all_on\": False,","== 1 assert opp.states.get(\"scene.light_group_scene\") # Verify service calls mock_deconz_put_request( aioclient_mock, config_entry.data, \"/groups/1/scenes/1/recall\" )","from openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID from .test_gateway","async def test_no_scenes(opp, aioclient_mock): \"\"\"Test that scenes can be loaded without scenes being","aioclient_mock) assert len(opp.states.async_all()) == 0 async def test_scenes(opp, aioclient_mock): \"\"\"Test that scenes works.\"\"\"","turn on scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \"scene.light_group_scene\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2]","0 async def test_scenes(opp, aioclient_mock): \"\"\"Test that scenes works.\"\"\" data = { \"groups\":","patch from openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID from","import ATTR_ENTITY_ID from .test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async def test_no_scenes(opp,","\"name\": \"Light group\", \"type\": \"LightGroup\", \"state\": {\"all_on\": False, \"any_on\": True}, \"action\": {}, \"scenes\":","SERVICE_TURN_ON, {ATTR_ENTITY_ID: \"scene.light_group_scene\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2] == {} await opp.config_entries.async_unload(config_entry.entry_id) assert len(opp.states.async_all())","Service turn on scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \"scene.light_group_scene\"}, blocking=True, ) assert","data = { \"groups\": { \"1\": { \"id\": \"Light group id\", \"name\": \"Light","\"groups\": { \"1\": { \"id\": \"Light group id\", \"name\": \"Light group\", \"type\": \"LightGroup\",","assert len(opp.states.async_all()) == 1 assert opp.states.get(\"scene.light_group_scene\") # Verify service calls mock_deconz_put_request( aioclient_mock, config_entry.data,","openpeerpower.const import ATTR_ENTITY_ID from .test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async def","mock_deconz_put_request( aioclient_mock, config_entry.data, \"/groups/1/scenes/1/recall\" ) # Service turn on scene await opp.services.async_call( SCENE_DOMAIN,","DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID from .test_gateway import ( DECONZ_WEB_REQUEST,","can be loaded without scenes being available.\"\"\" await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) ==","assert len(opp.states.async_all()) == 0 async def test_scenes(opp, aioclient_mock): \"\"\"Test that scenes works.\"\"\" data","\"state\": {\"all_on\": False, \"any_on\": True}, \"action\": {}, \"scenes\": [{\"id\": \"1\", \"name\": \"Scene\"}], \"lights\":","await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \"scene.light_group_scene\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2] == {} await","\"action\": {}, \"scenes\": [{\"id\": \"1\", \"name\": \"Scene\"}], \"lights\": [], } } } with","await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 1 assert opp.states.get(\"scene.light_group_scene\") # Verify service calls","\"1\", \"name\": \"Scene\"}], \"lights\": [], } } } with patch.dict(DECONZ_WEB_REQUEST, data): config_entry =","scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \"scene.light_group_scene\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2] == {}","True}, \"action\": {}, \"scenes\": [{\"id\": \"1\", \"name\": \"Scene\"}], \"lights\": [], } } }","async def test_scenes(opp, aioclient_mock): \"\"\"Test that scenes works.\"\"\" data = { \"groups\": {","import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async def test_no_scenes(opp, aioclient_mock): \"\"\"Test that scenes","SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID from .test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration,","# Verify service calls mock_deconz_put_request( aioclient_mock, config_entry.data, \"/groups/1/scenes/1/recall\" ) # Service turn on","unittest.mock import patch from openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import"],"string":"[\n \"group id\\\", \\\"name\\\": \\\"Light group\\\", \\\"type\\\": \\\"LightGroup\\\", \\\"state\\\": {\\\"all_on\\\": False, \\\"any_on\\\": True}, \\\"action\\\":\",\n \"openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID from .test_gateway import\",\n \"config_entry.data, \\\"/groups/1/scenes/1/recall\\\" ) # Service turn on scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID:\",\n \"[{\\\"id\\\": \\\"1\\\", \\\"name\\\": \\\"Scene\\\"}], \\\"lights\\\": [], } } } with patch.dict(DECONZ_WEB_REQUEST, data): config_entry\",\n \"from .test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async def test_no_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test\",\n \"{ \\\"1\\\": { \\\"id\\\": \\\"Light group id\\\", \\\"name\\\": \\\"Light group\\\", \\\"type\\\": \\\"LightGroup\\\", \\\"state\\\":\",\n \"1 assert opp.states.get(\\\"scene.light_group_scene\\\") # Verify service calls mock_deconz_put_request( aioclient_mock, config_entry.data, \\\"/groups/1/scenes/1/recall\\\" ) #\",\n \"\\\"\\\"\\\"deCONZ scene platform tests.\\\"\\\"\\\" from unittest.mock import patch from openpeerpower.components.scene import DOMAIN as\",\n \"scenes works.\\\"\\\"\\\" data = { \\\"groups\\\": { \\\"1\\\": { \\\"id\\\": \\\"Light group id\\\",\",\n \"( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async def test_no_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes can\",\n \"test_no_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes can be loaded without scenes being available.\\\"\\\"\\\" await\",\n \"DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async def test_no_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes can be\",\n \"be loaded without scenes being available.\\\"\\\"\\\" await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 0\",\n \"{\\\"all_on\\\": False, \\\"any_on\\\": True}, \\\"action\\\": {}, \\\"scenes\\\": [{\\\"id\\\": \\\"1\\\", \\\"name\\\": \\\"Scene\\\"}], \\\"lights\\\": [],\",\n \"= await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 1 assert opp.states.get(\\\"scene.light_group_scene\\\") # Verify service\",\n \"that scenes works.\\\"\\\"\\\" data = { \\\"groups\\\": { \\\"1\\\": { \\\"id\\\": \\\"Light group\",\n \"from unittest.mock import patch from openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const\",\n \"import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID from .test_gateway import (\",\n \"\\\"1\\\": { \\\"id\\\": \\\"Light group id\\\", \\\"name\\\": \\\"Light group\\\", \\\"type\\\": \\\"LightGroup\\\", \\\"state\\\": {\\\"all_on\\\":\",\n \"\\\"name\\\": \\\"Scene\\\"}], \\\"lights\\\": [], } } } with patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await\",\n \"without scenes being available.\\\"\\\"\\\" await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 0 async def\",\n \"id\\\", \\\"name\\\": \\\"Light group\\\", \\\"type\\\": \\\"LightGroup\\\", \\\"state\\\": {\\\"all_on\\\": False, \\\"any_on\\\": True}, \\\"action\\\": {},\",\n \"patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 1 assert opp.states.get(\\\"scene.light_group_scene\\\")\",\n \"scene platform tests.\\\"\\\"\\\" from unittest.mock import patch from openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN,\",\n \"Verify service calls mock_deconz_put_request( aioclient_mock, config_entry.data, \\\"/groups/1/scenes/1/recall\\\" ) # Service turn on scene\",\n \"setup_deconz_integration, ) async def test_no_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes can be loaded without\",\n \") # Service turn on scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \\\"scene.light_group_scene\\\"}, blocking=True,\",\n \"calls mock_deconz_put_request( aioclient_mock, config_entry.data, \\\"/groups/1/scenes/1/recall\\\" ) # Service turn on scene await opp.services.async_call(\",\n \"\\\"LightGroup\\\", \\\"state\\\": {\\\"all_on\\\": False, \\\"any_on\\\": True}, \\\"action\\\": {}, \\\"scenes\\\": [{\\\"id\\\": \\\"1\\\", \\\"name\\\": \\\"Scene\\\"}],\",\n \"await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 0 async def test_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that\",\n \"aioclient_mock, config_entry.data, \\\"/groups/1/scenes/1/recall\\\" ) # Service turn on scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON,\",\n \"len(opp.states.async_all()) == 0 async def test_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes works.\\\"\\\"\\\" data =\",\n \"SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \\\"scene.light_group_scene\\\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2] == {} await opp.config_entries.async_unload(config_entry.entry_id) assert\",\n \"} } with patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) ==\",\n \"opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \\\"scene.light_group_scene\\\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2] == {} await opp.config_entries.async_unload(config_entry.entry_id)\",\n \"aioclient_mock): \\\"\\\"\\\"Test that scenes works.\\\"\\\"\\\" data = { \\\"groups\\\": { \\\"1\\\": { \\\"id\\\":\",\n \"} } } with patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all())\",\n \"\\\"lights\\\": [], } } } with patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await setup_deconz_integration(opp, aioclient_mock)\",\n \"on scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \\\"scene.light_group_scene\\\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2] ==\",\n \"that scenes can be loaded without scenes being available.\\\"\\\"\\\" await setup_deconz_integration(opp, aioclient_mock) assert\",\n \"len(opp.states.async_all()) == 1 assert opp.states.get(\\\"scene.light_group_scene\\\") # Verify service calls mock_deconz_put_request( aioclient_mock, config_entry.data, \\\"/groups/1/scenes/1/recall\\\"\",\n \"works.\\\"\\\"\\\" data = { \\\"groups\\\": { \\\"1\\\": { \\\"id\\\": \\\"Light group id\\\", \\\"name\\\":\",\n \"loaded without scenes being available.\\\"\\\"\\\" await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 0 async\",\n \"= { \\\"groups\\\": { \\\"1\\\": { \\\"id\\\": \\\"Light group id\\\", \\\"name\\\": \\\"Light group\\\",\",\n \"\\\"any_on\\\": True}, \\\"action\\\": {}, \\\"scenes\\\": [{\\\"id\\\": \\\"1\\\", \\\"name\\\": \\\"Scene\\\"}], \\\"lights\\\": [], } }\",\n \"import patch from openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID\",\n \"group\\\", \\\"type\\\": \\\"LightGroup\\\", \\\"state\\\": {\\\"all_on\\\": False, \\\"any_on\\\": True}, \\\"action\\\": {}, \\\"scenes\\\": [{\\\"id\\\": \\\"1\\\",\",\n \"\\\"scene.light_group_scene\\\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2] == {} await opp.config_entries.async_unload(config_entry.entry_id) assert len(opp.states.async_all()) == 0\",\n \"\\\"\\\"\\\"Test that scenes works.\\\"\\\"\\\" data = { \\\"groups\\\": { \\\"1\\\": { \\\"id\\\": \\\"Light\",\n \"setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 1 assert opp.states.get(\\\"scene.light_group_scene\\\") # Verify service calls mock_deconz_put_request(\",\n \"opp.states.get(\\\"scene.light_group_scene\\\") # Verify service calls mock_deconz_put_request( aioclient_mock, config_entry.data, \\\"/groups/1/scenes/1/recall\\\" ) # Service turn\",\n \"== 0 async def test_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes works.\\\"\\\"\\\" data = {\",\n \"\\\"/groups/1/scenes/1/recall\\\" ) # Service turn on scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \\\"scene.light_group_scene\\\"},\",\n \"aioclient_mock): \\\"\\\"\\\"Test that scenes can be loaded without scenes being available.\\\"\\\"\\\" await setup_deconz_integration(opp,\",\n \"tests.\\\"\\\"\\\" from unittest.mock import patch from openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from\",\n \"platform tests.\\\"\\\"\\\" from unittest.mock import patch from openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON\",\n \"{ \\\"groups\\\": { \\\"1\\\": { \\\"id\\\": \\\"Light group id\\\", \\\"name\\\": \\\"Light group\\\", \\\"type\\\":\",\n \"\\\"scenes\\\": [{\\\"id\\\": \\\"1\\\", \\\"name\\\": \\\"Scene\\\"}], \\\"lights\\\": [], } } } with patch.dict(DECONZ_WEB_REQUEST, data):\",\n \"from openpeerpower.const import ATTR_ENTITY_ID from .test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async\",\n \"{ATTR_ENTITY_ID: \\\"scene.light_group_scene\\\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2] == {} await opp.config_entries.async_unload(config_entry.entry_id) assert len(opp.states.async_all()) ==\",\n \"mock_deconz_put_request, setup_deconz_integration, ) async def test_no_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes can be loaded\",\n \"} with patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 1\",\n \"\\\"type\\\": \\\"LightGroup\\\", \\\"state\\\": {\\\"all_on\\\": False, \\\"any_on\\\": True}, \\\"action\\\": {}, \\\"scenes\\\": [{\\\"id\\\": \\\"1\\\", \\\"name\\\":\",\n \"def test_no_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes can be loaded without scenes being available.\\\"\\\"\\\"\",\n \"\\\"Light group\\\", \\\"type\\\": \\\"LightGroup\\\", \\\"state\\\": {\\\"all_on\\\": False, \\\"any_on\\\": True}, \\\"action\\\": {}, \\\"scenes\\\": [{\\\"id\\\":\",\n \"ATTR_ENTITY_ID from .test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async def test_no_scenes(opp, aioclient_mock):\",\n \"scenes can be loaded without scenes being available.\\\"\\\"\\\" await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all())\",\n \"data): config_entry = await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 1 assert opp.states.get(\\\"scene.light_group_scene\\\") #\",\n \"scenes being available.\\\"\\\"\\\" await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 0 async def test_scenes(opp,\",\n \"test_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes works.\\\"\\\"\\\" data = { \\\"groups\\\": { \\\"1\\\": {\",\n \"\\\"Light group id\\\", \\\"name\\\": \\\"Light group\\\", \\\"type\\\": \\\"LightGroup\\\", \\\"state\\\": {\\\"all_on\\\": False, \\\"any_on\\\": True},\",\n \"service calls mock_deconz_put_request( aioclient_mock, config_entry.data, \\\"/groups/1/scenes/1/recall\\\" ) # Service turn on scene await\",\n \"def test_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes works.\\\"\\\"\\\" data = { \\\"groups\\\": { \\\"1\\\":\",\n \"<filename>tests/components/deconz/test_scene.py \\\"\\\"\\\"deCONZ scene platform tests.\\\"\\\"\\\" from unittest.mock import patch from openpeerpower.components.scene import DOMAIN\",\n \"\\\"Scene\\\"}], \\\"lights\\\": [], } } } with patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await setup_deconz_integration(opp,\",\n \"# Service turn on scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \\\"scene.light_group_scene\\\"}, blocking=True, )\",\n \"available.\\\"\\\"\\\" await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 0 async def test_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test\",\n \".test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async def test_no_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that\",\n \"being available.\\\"\\\"\\\" await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 0 async def test_scenes(opp, aioclient_mock):\",\n \"setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 0 async def test_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes\",\n \"assert opp.states.get(\\\"scene.light_group_scene\\\") # Verify service calls mock_deconz_put_request( aioclient_mock, config_entry.data, \\\"/groups/1/scenes/1/recall\\\" ) # Service\",\n \"\\\"id\\\": \\\"Light group id\\\", \\\"name\\\": \\\"Light group\\\", \\\"type\\\": \\\"LightGroup\\\", \\\"state\\\": {\\\"all_on\\\": False, \\\"any_on\\\":\",\n \"with patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 1 assert\",\n \") async def test_no_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes can be loaded without scenes\",\n \"as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID from .test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request,\",\n \"False, \\\"any_on\\\": True}, \\\"action\\\": {}, \\\"scenes\\\": [{\\\"id\\\": \\\"1\\\", \\\"name\\\": \\\"Scene\\\"}], \\\"lights\\\": [], }\",\n \"SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID from .test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, )\",\n \"[], } } } with patch.dict(DECONZ_WEB_REQUEST, data): config_entry = await setup_deconz_integration(opp, aioclient_mock) assert\",\n \"config_entry = await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 1 assert opp.states.get(\\\"scene.light_group_scene\\\") # Verify\",\n \"{}, \\\"scenes\\\": [{\\\"id\\\": \\\"1\\\", \\\"name\\\": \\\"Scene\\\"}], \\\"lights\\\": [], } } } with patch.dict(DECONZ_WEB_REQUEST,\",\n \"aioclient_mock) assert len(opp.states.async_all()) == 1 assert opp.states.get(\\\"scene.light_group_scene\\\") # Verify service calls mock_deconz_put_request( aioclient_mock,\",\n \"\\\"\\\"\\\"Test that scenes can be loaded without scenes being available.\\\"\\\"\\\" await setup_deconz_integration(opp, aioclient_mock)\",\n \"{ \\\"id\\\": \\\"Light group id\\\", \\\"name\\\": \\\"Light group\\\", \\\"type\\\": \\\"LightGroup\\\", \\\"state\\\": {\\\"all_on\\\": False,\",\n \"== 1 assert opp.states.get(\\\"scene.light_group_scene\\\") # Verify service calls mock_deconz_put_request( aioclient_mock, config_entry.data, \\\"/groups/1/scenes/1/recall\\\" )\",\n \"from openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID from .test_gateway\",\n \"async def test_no_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes can be loaded without scenes being\",\n \"aioclient_mock) assert len(opp.states.async_all()) == 0 async def test_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes works.\\\"\\\"\\\"\",\n \"turn on scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \\\"scene.light_group_scene\\\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2]\",\n \"0 async def test_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes works.\\\"\\\"\\\" data = { \\\"groups\\\":\",\n \"patch from openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID from\",\n \"import ATTR_ENTITY_ID from .test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async def test_no_scenes(opp,\",\n \"\\\"name\\\": \\\"Light group\\\", \\\"type\\\": \\\"LightGroup\\\", \\\"state\\\": {\\\"all_on\\\": False, \\\"any_on\\\": True}, \\\"action\\\": {}, \\\"scenes\\\":\",\n \"SERVICE_TURN_ON, {ATTR_ENTITY_ID: \\\"scene.light_group_scene\\\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2] == {} await opp.config_entries.async_unload(config_entry.entry_id) assert len(opp.states.async_all())\",\n \"Service turn on scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \\\"scene.light_group_scene\\\"}, blocking=True, ) assert\",\n \"data = { \\\"groups\\\": { \\\"1\\\": { \\\"id\\\": \\\"Light group id\\\", \\\"name\\\": \\\"Light\",\n \"\\\"groups\\\": { \\\"1\\\": { \\\"id\\\": \\\"Light group id\\\", \\\"name\\\": \\\"Light group\\\", \\\"type\\\": \\\"LightGroup\\\",\",\n \"assert len(opp.states.async_all()) == 1 assert opp.states.get(\\\"scene.light_group_scene\\\") # Verify service calls mock_deconz_put_request( aioclient_mock, config_entry.data,\",\n \"openpeerpower.const import ATTR_ENTITY_ID from .test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async def\",\n \"mock_deconz_put_request( aioclient_mock, config_entry.data, \\\"/groups/1/scenes/1/recall\\\" ) # Service turn on scene await opp.services.async_call( SCENE_DOMAIN,\",\n \"DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID from .test_gateway import ( DECONZ_WEB_REQUEST,\",\n \"can be loaded without scenes being available.\\\"\\\"\\\" await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) ==\",\n \"assert len(opp.states.async_all()) == 0 async def test_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes works.\\\"\\\"\\\" data\",\n \"\\\"state\\\": {\\\"all_on\\\": False, \\\"any_on\\\": True}, \\\"action\\\": {}, \\\"scenes\\\": [{\\\"id\\\": \\\"1\\\", \\\"name\\\": \\\"Scene\\\"}], \\\"lights\\\":\",\n \"await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \\\"scene.light_group_scene\\\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2] == {} await\",\n \"\\\"action\\\": {}, \\\"scenes\\\": [{\\\"id\\\": \\\"1\\\", \\\"name\\\": \\\"Scene\\\"}], \\\"lights\\\": [], } } } with\",\n \"await setup_deconz_integration(opp, aioclient_mock) assert len(opp.states.async_all()) == 1 assert opp.states.get(\\\"scene.light_group_scene\\\") # Verify service calls\",\n \"\\\"1\\\", \\\"name\\\": \\\"Scene\\\"}], \\\"lights\\\": [], } } } with patch.dict(DECONZ_WEB_REQUEST, data): config_entry =\",\n \"scene await opp.services.async_call( SCENE_DOMAIN, SERVICE_TURN_ON, {ATTR_ENTITY_ID: \\\"scene.light_group_scene\\\"}, blocking=True, ) assert aioclient_mock.mock_calls[1][2] == {}\",\n \"True}, \\\"action\\\": {}, \\\"scenes\\\": [{\\\"id\\\": \\\"1\\\", \\\"name\\\": \\\"Scene\\\"}], \\\"lights\\\": [], } } }\",\n \"async def test_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes works.\\\"\\\"\\\" data = { \\\"groups\\\": {\",\n \"import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration, ) async def test_no_scenes(opp, aioclient_mock): \\\"\\\"\\\"Test that scenes\",\n \"SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID from .test_gateway import ( DECONZ_WEB_REQUEST, mock_deconz_put_request, setup_deconz_integration,\",\n \"# Verify service calls mock_deconz_put_request( aioclient_mock, config_entry.data, \\\"/groups/1/scenes/1/recall\\\" ) # Service turn on\",\n \"unittest.mock import patch from openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import\"\n]","isConversational":false}}},{"rowIdx":4588,"cells":{"ngram":{"kind":"list like","value":["mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False)","/ 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH","config files permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except","file already exists: {}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied {} to {}'.format(src, dst)) class","= mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587) section = 'template/intruder' INTRUDER_SUBJECT","section = 'api.server' BACKEND = config.get(section, 'backend', fallback='gevent') HOST = config.get(section, 'host', fallback='0.0.0.0')","= config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path,","logging log = logging.getLogger(__name__) class CONFIG_FILES: # Where to copy files # (TensorHive","configparser from typing import Dict, Optional, Any, List from inspect import cleandoc import","'''Safe means that it won't override existing configuration''' if PosixPath(dst).exists(): log.info('Skipping, file already","# type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://'","config.getboolean(section, 'enabled', fallback=False): return { 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section,","NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1) KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str)","Any, List from inspect import cleandoc import shutil import tensorhive import os import","'r') as file: RESPONSES = yaml.safe_load(file) class APP_SERVER: section = 'web_app.server' BACKEND =","fallback=False) class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general' INTERVAL = mailbot_config.getfloat(section,","'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes',","'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot')","str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR =","config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE: section = 'protection_service'","not found ({})'.format(full_path)) log.info('Using default {} settings from config.py'.format(displayed_title)) return config ConfigInitilizer() config","= mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None) section = 'smtp' SMTP_LOGIN","''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in cls.__dict__.items(): if key.isupper(): print('{} = {}'.format(key, value))","recreating...') self.recreate_default_configuration_files() log.info('[•] All configs already exist, skipping...') def recreate_default_configuration_files(self) -> None: try:","mailbot_config.get(section, 'html_body') section = 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body')","'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def full_path(path: str) -> str: # type: ignore return","ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): ''' Displays all uppercase class atributes (class must be","} else: return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section","else: log.warning('[✘] Configuration file not found ({})'.format(full_path)) log.info('Using default {} settings from config.py'.format(displayed_title))","fallback='warning') class API_SERVER: section = 'api.server' BACKEND = config.get(section, 'backend', fallback='gevent') HOST =","class DB: section = 'database' default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) -> str:","ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general' INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section,","SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section,","copy files # (TensorHive tries to load these by default) config_dir = PosixPath.home()","'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path = '~/.config/TensorHive/logs/'","AUTH: from datetime import timedelta section = 'auth' def config_get_parsed(option: str, fallback: Any)","[auth] config section failed for option \"{}\", using fallback value: {}'.format( option, fallback))","# 1. Create directory for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone","\"{}\", using fallback value: {}'.format( option, fallback)) return fallback FLASK_JWT = { 'SECRET_KEY':","'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' # Use in-memory (before: sqlite:///test_database.sqlite) class API: section","fallback=22) } return result def proxy_config_to_dict(path: str) -> Optional[Dict]: # type: ignore '''Parses","class AUTH: from datetime import timedelta section = 'auth' def config_get_parsed(option: str, fallback:","section == 'proxy_tunneling': continue hostname = section result[hostname] = { 'user': hosts_config.get(hostname, 'user'),","log.info('Skipping, file already exists: {}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied {} to {}'.format(src, dst))","string to a valid python list. Fallback value is returned when anything goes","config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general' INTERVAL","when it's not found in config directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir","fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED =","hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts') result = {} for section in hosts_config.sections(): #","'bar'] Will return: ['foo', 'bar'] ''' import ast try: raw_arguments = config.get('auth', option)","using fallback value: {}'.format( option, fallback)) return fallback FLASK_JWT = { 'SECRET_KEY': config.get(section,","first) Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in cls.__dict__.items(): if key.isupper():","List[str]: # type: ignore ''' Parses value for option from string to a","dst) log.info('Copied {} to {}'.format(src, dst)) class ConfigLoader: @staticmethod def load(path, displayed_title=''): import","rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘] Unable to recreate configuration files.')","ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling' # Check if section is present and if","fallback=5000) WORKERS = config.getint(section, 'workers', fallback=4) LOG_LEVEL = config.get(section, 'loglevel', fallback='warning') class API_SERVER:","config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE: section = 'protection_service' ENABLED = config.getboolean(section, 'enabled', fallback=True)","fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT =","str(tensorhive_package_dir / 'migrations') class ConfigInitilizer: '''Makes sure that all default config files exist'''","fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=1111) DEBUG = config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE:","= config.get(section, 'url_prefix', fallback='api') SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location',","section = 'api' TITLE = config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME = config.get(section, 'url_hostname',","file templates from # (Clone file when it's not found in config directory)","class atributes (class must be defined first) Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for","'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations') class ConfigInitilizer: '''Makes sure that all default","APP_SERVER: section = 'web_app.server' BACKEND = config.get(section, 'backend', fallback='gunicorn') HOST = config.get(section, 'host',","to load these by default) config_dir = PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir","= ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general' INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL =","ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def","config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All configs already exist, skipping...') def recreate_default_configuration_files(self) ->","Change config files permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only)","= str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir /","fallback='TensorHive API') URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix', fallback='api') SPEC_FILE","SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \"schedule_queued_jobs_when_free_mins\", fallback=30) class AUTH: from datetime import timedelta section =","file not found ({})'.format(full_path)) log.info('Using default {} settings from config.py'.format(displayed_title)) return config ConfigInitilizer()","1. Check if all config files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists()","= 'api' TITLE = config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0')","= hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section = 'database' default_path = '~/.config/TensorHive/database.sqlite'","UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section,","won't override existing configuration''' if PosixPath(dst).exists(): log.info('Skipping, file already exists: {}'.format(dst)) else: shutil.copy(src,","= config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty',","exists: {}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied {} to {}'.format(src, dst)) class ConfigLoader: @staticmethod","'loglevel', fallback='warning') class API_SERVER: section = 'api.server' BACKEND = config.get(section, 'backend', fallback='gevent') HOST","settings from config.py'.format(displayed_title)) return config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): '''","to get file templates from # (Clone file when it's not found in","def safe_copy(self, src: str, dst: str) -> None: '''Safe means that it won't","anything goes wrong (e.g. option or value not present) Example .ini file, function","NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT: mailbot_config","exist, skipping...') def recreate_default_configuration_files(self) -> None: try: # 1. Create directory for stroing","/ 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH","Where to copy files # (TensorHive tries to load these by default) config_dir","# Check if section is present and if yes, check if tunneling is","mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None)","dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config files permission rw_owner_only =","= mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email',","CONFIG_FILES: # Where to copy files # (TensorHive tries to load these by","= config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE: section =","= mailbot_config.get(section, 'admin_email', fallback=None) section = 'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD","def proxy_config_to_dict(path: str) -> Optional[Dict]: # type: ignore '''Parses [proxy_tunneling] section''' config =","config files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if","proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section = 'database' default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) ->","Optional[Dict]: # type: ignore '''Parses [proxy_tunneling] section''' config = ConfigLoader.load(path, displayed_title='proxy') section =","config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path, 'r')","-> None: '''Safe means that it won't override existing configuration''' if PosixPath(dst).exists(): log.info('Skipping,","def __init__(self): # 1. Check if all config files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists()","exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist:","safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change","'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22) } else: return","INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section,","class USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def full_path(path: str) -> str:","'workers', fallback=4) LOG_LEVEL = config.get(section, 'loglevel', fallback='warning') class API_SERVER: section = 'api.server' BACKEND","{ 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']),","fallback='gunicorn') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=5000) WORKERS =","import yaml respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path, 'r') as file: RESPONSES","= config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE: section = 'protection_service' ENABLED = config.getboolean(section, 'enabled',","config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0)","full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service'","'~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) -> str: # type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI =","to parse only sections which describe target hosts if section == 'proxy_tunneling': continue","MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini') # Where to get file templates from #","'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=1111) DEBUG = config.getboolean(section, 'debug', fallback=False) class","'.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH =","if config.read(str(full_path)): log.info('[•] Reading {} config from {}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration file","'''Makes sure that env variable is declared''' if not os.getenv(name): msg = cleandoc(","ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section,","from {}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration file not found ({})'.format(full_path)) log.info('Using default {}","displayed_title='proxy') section = 'proxy_tunneling' # Check if section is present and if yes,","os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘] Unable to recreate configuration files.') def safe_copy(self, src:","pathlib import PosixPath import configparser from typing import Dict, Optional, Any, List from","from config.py'.format(displayed_title)) return config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): ''' Displays","config.has_section(section) and config.getboolean(section, 'enabled', fallback=False): return { 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'),","check if tunneling is enabled if config.has_section(section) and config.getboolean(section, 'enabled', fallback=False): return {","(Clone file when it's not found in config directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH","HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section,","'web_app.server' BACKEND = config.get(section, 'backend', fallback='gunicorn') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT =","inspect import cleandoc import shutil import tensorhive import os import logging log =","CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone templates safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH,","is declared''' if not os.getenv(name): msg = cleandoc( ''' {env} - undeclared environment","{} for section in hosts_config.sections(): # We want to parse only sections which","'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE: section = 'protection_service' ENABLED","'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22) } else: return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY","'notify_via_email', fallback=False) class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general' INTERVAL =","Example .ini file, function called with arguments: option='some_option', fallback=None [some_section] some_option = ['foo',","[proxy_tunneling] section''' config = ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling' # Check if section","ast try: raw_arguments = config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error,","variable! Try this: `export {env}=\"...\"` ''').format(env=name).split('\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH: section = 'ssh'","fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None) section =","KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) -> Dict: # type: ignore","mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True)","HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini') # Where to","if key.isupper(): print('{} = {}'.format(key, value)) def check_env_var(name: str): '''Makes sure that env","''' {env} - undeclared environment variable! Try this: `export {env}=\"...\"` ''').format(env=name).split('\\n') log.warning(msg[0]) log.warning(msg[1])","DEBUG = config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE: section = 'monitoring_service' ENABLED = config.getboolean(section,","ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None) section = 'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None)","fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587) section = 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject')","to copy files # (TensorHive tries to load these by default) config_dir =","def check_env_var(name: str): '''Makes sure that env variable is declared''' if not os.getenv(name):","str): '''Makes sure that env variable is declared''' if not os.getenv(name): msg =","fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=5000) WORKERS = config.getint(section, 'workers', fallback=4) LOG_LEVEL =","load these by default) config_dir = PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir /","'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22) } else: return None AVAILABLE_NODES =","files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not","'bar'] ''' import ast try: raw_arguments = config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments) return","mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None)","present) Example .ini file, function called with arguments: option='some_option', fallback=None [some_section] some_option =","'timeout', fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1) KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def","config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix', fallback='api') SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml')","raw_arguments = config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing","/ 'mailbot_config.ini') # Where to get file templates from # (Clone file when","config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)), 'JWT_REFRESH_TOKEN_EXPIRES': timedelta(days=config.getint(section, 'jwt_refresh_token_expires_days', fallback=1)), 'JWT_TOKEN_LOCATION': config_get_parsed('jwt_token_location',","Exception: log.error('[✘] Unable to recreate configuration files.') def safe_copy(self, src: str, dst: str)","'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22) } else: return None AVAILABLE_NODES","AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section = 'database' default_path =","fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml')","config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False)","default) config_dir = PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH =","FLASK_JWT = { 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks',","None: try: # 1. Create directory for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) #","def config_get_parsed(option: str, fallback: Any) -> List[str]: # type: ignore ''' Parses value","'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL","None: '''Safe means that it won't override existing configuration''' if PosixPath(dst).exists(): log.info('Skipping, file","ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE: section","parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing [auth] config section failed","ConfigInitilizer: '''Makes sure that all default config files exist''' def __init__(self): # 1.","config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) -> Dict: # type: ignore '''Parses sections","file when it's not found in config directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH =","config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2)","returned when anything goes wrong (e.g. option or value not present) Example .ini","'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH =","uri_for_path(path: str) -> str: # type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path',","present and if yes, check if tunneling is enabled if config.has_section(section) and config.getboolean(section,","STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \"schedule_queued_jobs_when_free_mins\", fallback=30) class AUTH: from","section failed for option \"{}\", using fallback value: {}'.format( option, fallback)) return fallback","mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None) section = 'smtp' SMTP_LOGIN =","mailbot_config.getint(section, 'smtp_port', fallback=587) section = 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section,","config.getint(section, 'workers', fallback=4) LOG_LEVEL = config.get(section, 'loglevel', fallback='warning') class API_SERVER: section = 'api.server'","{} to {}'.format(src, dst)) class ConfigLoader: @staticmethod def load(path, displayed_title=''): import configparser config","if config.has_section(section) and config.getboolean(section, 'enabled', fallback=False): return { 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section,","config.getint(section, 'port', fallback=5000) WORKERS = config.getint(section, 'workers', fallback=4) LOG_LEVEL = config.get(section, 'loglevel', fallback='warning')","PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini')","NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section =","config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0)","config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section,","to a valid python list. Fallback value is returned when anything goes wrong","class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section,","value: {}'.format( option, fallback)) return fallback FLASK_JWT = { 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'),","return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR","override existing configuration''' if PosixPath(dst).exists(): log.info('Skipping, file already exists: {}'.format(dst)) else: shutil.copy(src, dst)","for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone templates safely from `tensorhive`","= mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port',","BACKEND = config.get(section, 'backend', fallback='gunicorn') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section,","'sqlite://' # Use in-memory (before: sqlite:///test_database.sqlite) class API: section = 'api' TITLE =","print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in cls.__dict__.items(): if key.isupper(): print('{} = {}'.format(key, value)) def","tensorhive import os import logging log = logging.getLogger(__name__) class CONFIG_FILES: # Where to","str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini')","str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini')","= 'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def full_path(path: str) -> str: # type: ignore","option='some_option', fallback=None [some_section] some_option = ['foo', 'bar'] Will return: ['foo', 'bar'] ''' import","missing default config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All configs already exist, skipping...') def","PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•] Detected missing default config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•]","{}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration file not found ({})'.format(full_path)) log.info('Using default {} settings","typing import Dict, Optional, Any, List from inspect import cleandoc import shutil import","'auth' def config_get_parsed(option: str, fallback: Any) -> List[str]: # type: ignore ''' Parses","permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘]","List from inspect import cleandoc import shutil import tensorhive import os import logging","'proxy_port': config.getint(section, 'proxy_port', fallback=22) } else: return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY =","mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def full_path(path: str)","sections containing hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts') result = {} for section in","which describe target hosts if section == 'proxy_tunneling': continue hostname = section result[hostname]","config.getint(section, \"schedule_queued_jobs_when_free_mins\", fallback=30) class AUTH: from datetime import timedelta section = 'auth' def","'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)), 'JWT_REFRESH_TOKEN_EXPIRES':","configparser config = configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading {} config","fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN =","yaml respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path, 'r') as file: RESPONSES =","display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in cls.__dict__.items(): if key.isupper(): print('{} = {}'.format(key,","= str(config_dir / 'mailbot_config.ini') # Where to get file templates from # (Clone","log.info('Using default {} settings from config.py'.format(displayed_title)) return config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main')","__init__(self): # 1. Check if all config files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and","# We want to parse only sections which describe target hosts if section","mailbot_config.get(section, 'admin_email', fallback=None) section = 'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD =","= config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled',","def recreate_default_configuration_files(self) -> None: try: # 1. Create directory for stroing config files","fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1) KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path:","hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22) } return result def proxy_config_to_dict(path: str) ->","'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2) class","fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL =","check_env_var(name: str): '''Makes sure that env variable is declared''' if not os.getenv(name): msg","configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading {} config from {}'.format(displayed_title, full_path))","'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER =","from typing import Dict, Optional, Any, List from inspect import cleandoc import shutil","-> List[str]: # type: ignore ''' Parses value for option from string to","class APP_SERVER: section = 'web_app.server' BACKEND = config.get(section, 'backend', fallback='gunicorn') HOST = config.get(section,","UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE: section = 'protection_service' ENABLED = config.getboolean(section,","'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED","must be defined first) Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in","-> Dict: # type: ignore '''Parses sections containing hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts')","config from {}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration file not found ({})'.format(full_path)) log.info('Using default","= PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH","package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config files permission","existing configuration''' if PosixPath(dst).exists(): log.info('Skipping, file already exists: {}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied","if section == 'proxy_tunneling': continue hostname = section result[hostname] = { 'user': hosts_config.get(hostname,","API') URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix', fallback='api') SPEC_FILE =","mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section = 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject')","= str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir /","sqlite:///test_database.sqlite) class API: section = 'api' TITLE = config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME","{} config from {}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration file not found ({})'.format(full_path)) log.info('Using","= 'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT","when anything goes wrong (e.g. option or value not present) Example .ini file,","= config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix', fallback='api') SPEC_FILE = config.get(section, 'spec_file',","log = logging.getLogger(__name__) class CONFIG_FILES: # Where to copy files # (TensorHive tries","'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH =","def uri_for_path(path: str) -> str: # type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section,","'port', fallback=1111) DEBUG = config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE: section = 'monitoring_service' ENABLED","all uppercase class atributes (class must be defined first) Example usage: display_config(API_SERVER) '''","log.info('[•] Reading {} config from {}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration file not found","= config.getint(section, 'port', fallback=1111) DEBUG = config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE: section =","'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL","= config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \"schedule_queued_jobs_when_free_mins\",","fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True),","= config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir',","= config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=1111) DEBUG = config.getboolean(section, 'debug',","if tunneling is enabled if config.has_section(section) and config.getboolean(section, 'enabled', fallback=False): return { 'proxy_host':","config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \"schedule_queued_jobs_when_free_mins\", fallback=30)","str) -> None: '''Safe means that it won't override existing configuration''' if PosixPath(dst).exists():","log.warning('[✘] Configuration file not found ({})'.format(full_path)) log.info('Using default {} settings from config.py'.format(displayed_title)) return","-> str: # type: ignore return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL","undeclared environment variable! Try this: `export {env}=\"...\"` ''').format(env=name).split('\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH: section","config.getint(section, 'port', fallback=1111) DEBUG = config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE: section = 'monitoring_service'","# type: ignore '''Parses [proxy_tunneling] section''' config = ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling'","config.get(section, 'backend', fallback='gevent') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=1111)","= config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1) KEY_FILE = config.get(section, 'key_file',","python list. Fallback value is returned when anything goes wrong (e.g. option or","from string to a valid python list. Fallback value is returned when anything","Check if all config files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and","= str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations') class ConfigInitilizer: '''Makes sure","from datetime import timedelta section = 'auth' def config_get_parsed(option: str, fallback: Any) ->","class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general' INTERVAL = mailbot_config.getfloat(section, 'interval',","str, dst: str) -> None: '''Safe means that it won't override existing configuration'''","fallback FLASK_JWT = { 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS':","ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing [auth] config section failed for option","PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading {} config from {}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration","dst)) class ConfigLoader: @staticmethod def load(path, displayed_title=''): import configparser config = configparser.ConfigParser(strict=False) full_path","configuration''' if PosixPath(dst).exists(): log.info('Skipping, file already exists: {}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied {}","# type: ignore '''Parses sections containing hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts') result =","uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' # Use in-memory (before: sqlite:///test_database.sqlite) class API:","fallback=1) KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) -> Dict: # type:","describe target hosts if section == 'proxy_tunneling': continue hostname = section result[hostname] =","TEST_DATABASE_URI = 'sqlite://' # Use in-memory (before: sqlite:///test_database.sqlite) class API: section = 'api'","ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section,","ConfigLoader.load(path, displayed_title='hosts') result = {} for section in hosts_config.sections(): # We want to","parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing [auth] config section failed for option \"{}\", using","if yes, check if tunneling is enabled if config.has_section(section) and config.getboolean(section, 'enabled', fallback=False):","recreate_default_configuration_files(self) -> None: try: # 1. Create directory for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True,","and \\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•] Detected missing default","return: ['foo', 'bar'] ''' import ast try: raw_arguments = config.get('auth', option) parsed_arguments =","timedelta section = 'auth' def config_get_parsed(option: str, fallback: Any) -> List[str]: # type:","URL_PREFIX = config.get(section, 'url_prefix', fallback='api') SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section,","templates from # (Clone file when it's not found in config directory) tensorhive_package_dir","config.get(section, 'loglevel', fallback='warning') class API_SERVER: section = 'api.server' BACKEND = config.get(section, 'backend', fallback='gevent')","# 1. Check if all config files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\","# (TensorHive tries to load these by default) config_dir = PosixPath.home() / '.config/TensorHive'","'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22) } return result def proxy_config_to_dict(path: str) -> Optional[Dict]:","UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section,","found in config directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH","''' Parses value for option from string to a valid python list. Fallback","fallback)) return fallback FLASK_JWT = { 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled',","not present) Example .ini file, function called with arguments: option='some_option', fallback=None [some_section] some_option","`tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config files","if all config files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\","config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True)","= config.getint(section, 'number_of_retries', fallback=1) KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) ->","SSH: section = 'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup',","if PosixPath(dst).exists(): log.info('Skipping, file already exists: {}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied {} to","Check if section is present and if yes, check if tunneling is enabled","= config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section,","RESPONSES = yaml.safe_load(file) class APP_SERVER: section = 'web_app.server' BACKEND = config.get(section, 'backend', fallback='gunicorn')","these by default) config_dir = PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini')","MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations') class ConfigInitilizer: '''Makes sure that all default config","value not present) Example .ini file, function called with arguments: option='some_option', fallback=None [some_section]","NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section,","key, value in cls.__dict__.items(): if key.isupper(): print('{} = {}'.format(key, value)) def check_env_var(name: str):","= PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading {} config from {}'.format(displayed_title, full_path)) else: log.warning('[✘]","{ 'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22) } return result def proxy_config_to_dict(path:","to recreate configuration files.') def safe_copy(self, src: str, dst: str) -> None: '''Safe","try: # 1. Create directory for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2.","= mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path","{env} - undeclared environment variable! Try this: `export {env}=\"...\"` ''').format(env=name).split('\\n') log.warning(msg[0]) log.warning(msg[1]) class","want to parse only sections which describe target hosts if section == 'proxy_tunneling':","'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path = str(PosixPath(__file__).parent /","str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini') # Where to get file","fallback='gevent') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=1111) DEBUG =","= 'api.server' BACKEND = config.get(section, 'backend', fallback='gevent') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT","= config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section, 'timeout',","WORKERS = config.getint(section, 'workers', fallback=4) LOG_LEVEL = config.get(section, 'loglevel', fallback='warning') class API_SERVER: section","'number_of_retries', fallback=1) KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) -> Dict: #","fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE: section = 'protection_service' ENABLED =","from pathlib import PosixPath import configparser from typing import Dict, Optional, Any, List","log.warning('Parsing [auth] config section failed for option \"{}\", using fallback value: {}'.format( option,","config directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir","a valid python list. Fallback value is returned when anything goes wrong (e.g.","displayed_title='hosts') result = {} for section in hosts_config.sections(): # We want to parse","/ '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH","= proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section = 'database' default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str)","@staticmethod def load(path, displayed_title=''): import configparser config = configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if","log.warning('[•] Detected missing default config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All configs already exist,","= config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries',","'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS':","(TensorHive tries to load these by default) config_dir = PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH","except Exception: log.error('[✘] Unable to recreate configuration files.') def safe_copy(self, src: str, dst:","'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22) } return result def proxy_config_to_dict(path: str)","TITLE = config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX =","['foo', 'bar'] Will return: ['foo', 'bar'] ''' import ast try: raw_arguments = config.get('auth',","not found in config directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini')","\\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•] Detected missing default config file(s), recreating...') self.recreate_default_configuration_files()","config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): ''' Displays all uppercase class","'backend', fallback='gunicorn') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=5000) WORKERS","'port', fallback=22) } return result def proxy_config_to_dict(path: str) -> Optional[Dict]: # type: ignore","DB: section = 'database' default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) -> str: #","os import logging log = logging.getLogger(__name__) class CONFIG_FILES: # Where to copy files","datetime import timedelta section = 'auth' def config_get_parsed(option: str, fallback: Any) -> List[str]:","str(config_dir / 'mailbot_config.ini') # Where to get file templates from # (Clone file","from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config","'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER =","= config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action',","rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘] Unable","IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml') with","value for option from string to a valid python list. Fallback value is","log.info('[•] All configs already exist, skipping...') def recreate_default_configuration_files(self) -> None: try: # 1.","Fallback value is returned when anything goes wrong (e.g. option or value not","PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH =","= cleandoc( ''' {env} - undeclared environment variable! Try this: `export {env}=\"...\"` ''').format(env=name).split('\\n')","/ 'migrations') class ConfigInitilizer: '''Makes sure that all default config files exist''' def","''' Displays all uppercase class atributes (class must be defined first) Example usage:","'url_prefix', fallback='api') SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import","exist''' def __init__(self): # 1. Check if all config files exist all_exist =","'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path, 'r') as","arguments: option='some_option', fallback=None [some_section] some_option = ['foo', 'bar'] Will return: ['foo', 'bar'] '''","class ConfigLoader: @staticmethod def load(path, displayed_title=''): import configparser config = configparser.ConfigParser(strict=False) full_path =","= 'protection_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY","str) -> Dict: # type: ignore '''Parses sections containing hostnames''' hosts_config = ConfigLoader.load(path,","skipping...') def recreate_default_configuration_files(self) -> None: try: # 1. Create directory for stroing config","fallback=False): return { 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22)","'''Parses [proxy_tunneling] section''' config = ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling' # Check if","= str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini') # Where to get","self.recreate_default_configuration_files() log.info('[•] All configs already exist, skipping...') def recreate_default_configuration_files(self) -> None: try: #","class PROTECTION_SERVICE: section = 'protection_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section,","LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section","'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)), 'JWT_REFRESH_TOKEN_EXPIRES': timedelta(days=config.getint(section, 'jwt_refresh_token_expires_days', fallback=1)),","''' import ast try: raw_arguments = config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments","PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•] Detected missing","dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config files permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH,","'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1) KEY_FILE","else: return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section =","= 'web_app.server' BACKEND = config.get(section, 'backend', fallback='gunicorn') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT","ignore '''Parses [proxy_tunneling] section''' config = ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling' # Check","'admin_email', fallback=None) section = 'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section,","'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) -> Dict: # type: ignore '''Parses sections containing","section = 'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0)","default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) -> str: # type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser())","Reading {} config from {}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration file not found ({})'.format(full_path))","= {}'.format(key, value)) def check_env_var(name: str): '''Makes sure that env variable is declared'''","Clone templates safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) #","mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path =","valid python list. Fallback value is returned when anything goes wrong (e.g. option","is present and if yes, check if tunneling is enabled if config.has_section(section) and","usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in cls.__dict__.items(): if key.isupper(): print('{} =","def display_config(cls): ''' Displays all uppercase class atributes (class must be defined first)","LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED = config.getboolean(section,","URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix', fallback='api') SPEC_FILE = config.get(section,","tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini')","type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' #","default config files exist''' def __init__(self): # 1. Check if all config files","All configs already exist, skipping...') def recreate_default_configuration_files(self) -> None: try: # 1. Create","type: ignore '''Parses sections containing hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts') result = {}","= ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing [auth] config section failed for","files # (TensorHive tries to load these by default) config_dir = PosixPath.home() /","config.py'.format(displayed_title)) return config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): ''' Displays all","'api.server' BACKEND = config.get(section, 'backend', fallback='gevent') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT =","fallback: Any) -> List[str]: # type: ignore ''' Parses value for option from","directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir /","= config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) -> Dict: # type: ignore '''Parses","/ 'controllers/responses.yml') with open(respones_file_path, 'r') as file: RESPONSES = yaml.safe_load(file) class APP_SERVER: section","(e.g. option or value not present) Example .ini file, function called with arguments:","file, function called with arguments: option='some_option', fallback=None [some_section] some_option = ['foo', 'bar'] Will","str: # type: ignore return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL =","BACKEND = config.get(section, 'backend', fallback='gevent') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section,","'proxy_port', fallback=22) } else: return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class","SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587) section = 'template/intruder'","= str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir /","defined first) Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in cls.__dict__.items(): if","= '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) -> str: # type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI","fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION =","is returned when anything goes wrong (e.g. option or value not present) Example","config.get(section, 'backend', fallback='gunicorn') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=5000)","MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir","from # (Clone file when it's not found in config directory) tensorhive_package_dir =","USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def full_path(path: str) -> str: #","'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None) section","means that it won't override existing configuration''' if PosixPath(dst).exists(): log.info('Skipping, file already exists:","fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT:","full_path(path: str) -> str: # type: ignore return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled',","= 'monitoring_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL","config_dir = PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir","as file: RESPONSES = yaml.safe_load(file) class APP_SERVER: section = 'web_app.server' BACKEND = config.get(section,","= str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path, 'r') as file: RESPONSES = yaml.safe_load(file) class","wrong (e.g. option or value not present) Example .ini file, function called with","type: ignore return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval',","\\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•] Detected missing default config","'''Parses sections containing hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts') result = {} for section","= mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin',","'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' # Use in-memory (before:","ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): ''' Displays all uppercase class atributes","config.get(section, 'url_prefix', fallback='api') SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers')","= config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \"schedule_queued_jobs_when_free_mins\", fallback=30) class AUTH: from datetime","yaml.safe_load(file) class APP_SERVER: section = 'web_app.server' BACKEND = config.get(section, 'backend', fallback='gunicorn') HOST =","config.read(str(full_path)): log.info('[•] Reading {} config from {}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration file not","UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section,","'password', fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587) section","INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section = 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE =","fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)), 'JWT_REFRESH_TOKEN_EXPIRES': timedelta(days=config.getint(section, 'jwt_refresh_token_expires_days',","fallback=22) } else: return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB:","'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES':","ignore '''Parses sections containing hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts') result = {} for","is enabled if config.has_section(section) and config.getboolean(section, 'enabled', fallback=False): return { 'proxy_host': config.get(section, 'proxy_host'),","= config.get(section, 'loglevel', fallback='warning') class API_SERVER: section = 'api.server' BACKEND = config.get(section, 'backend',","PROTECTION_SERVICE: section = 'protection_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval',","fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS =","'general' INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER =","ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations') class ConfigInitilizer: '''Makes","result def proxy_config_to_dict(path: str) -> Optional[Dict]: # type: ignore '''Parses [proxy_tunneling] section''' config","config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE: section = 'monitoring_service' ENABLED = config.getboolean(section, 'enabled', fallback=True)","(before: sqlite:///test_database.sqlite) class API: section = 'api' TITLE = config.get(section, 'title', fallback='TensorHive API')","= mailbot_config.get(section, 'html_body') section = 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section,","import Dict, Optional, Any, List from inspect import cleandoc import shutil import tensorhive","= 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section","= config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT: mailbot_config =","= 'database' default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) -> str: # type: ignore","not all_exist: log.warning('[•] Detected missing default config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All configs","{}'.format(src, dst)) class ConfigLoader: @staticmethod def load(path, displayed_title=''): import configparser config = configparser.ConfigParser(strict=False)","'backend', fallback='gevent') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=1111) DEBUG","return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' # Use in-memory","configs already exist, skipping...') def recreate_default_configuration_files(self) -> None: try: # 1. Create directory","cls.__dict__.items(): if key.isupper(): print('{} = {}'.format(key, value)) def check_env_var(name: str): '''Makes sure that","{} settings from config.py'.format(displayed_title)) return config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls):","1. Create directory for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone templates","'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT =","config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22) } else: return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE)","continue hostname = section result[hostname] = { 'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port',","PORT = config.getint(section, 'port', fallback=1111) DEBUG = config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE: section","PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•] Detected missing default config file(s),","# 2. Clone templates safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH,","mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general' INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL","fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL =","os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘] Unable to recreate configuration files.') def","option) parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing [auth] config section","if section is present and if yes, check if tunneling is enabled if","/ 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations') class","result[hostname] = { 'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22) } return result","= ConfigLoader.load(path, displayed_title='hosts') result = {} for section in hosts_config.sections(): # We want","option from string to a valid python list. Fallback value is returned when","= config.getint(section, 'port', fallback=5000) WORKERS = config.getint(section, 'workers', fallback=4) LOG_LEVEL = config.get(section, 'loglevel',","= 'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER","Unable to recreate configuration files.') def safe_copy(self, src: str, dst: str) -> None:","def load(path, displayed_title=''): import configparser config = configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if config.read(str(full_path)):","'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini') # Where","HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir","tries to load these by default) config_dir = PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH =","`export {env}=\"...\"` ''').format(env=name).split('\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH: section = 'ssh' HOSTS_CONFIG_FILE = config.get(section,","SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' # Use in-memory (before: sqlite:///test_database.sqlite)","fallback=2.0) class PROTECTION_SERVICE: section = 'protection_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL =","= config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general'","= config.get(section, 'backend', fallback='gunicorn') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port',","displayed_title='mailbot') section = 'general' INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval',","fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix', fallback='api') SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION =","'html_body') section = 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class","# type: ignore return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section,","ignore return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0)","import PosixPath import configparser from typing import Dict, Optional, Any, List from inspect","'monitoring_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL =","Any) -> List[str]: # type: ignore ''' Parses value for option from string","return fallback FLASK_JWT = { 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True),","in config directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH =","file: RESPONSES = yaml.safe_load(file) class APP_SERVER: section = 'web_app.server' BACKEND = config.get(section, 'backend',","config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22) } else: return None","section = 'monitoring_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True)","files permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception:","= configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading {} config from {}'.format(displayed_title,","fallback=587) section = 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section","'update_interval', fallback=2.0) class PROTECTION_SERVICE: section = 'protection_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL","'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini') # Where to get file templates from","default_path = '~/.config/TensorHive/logs/' def full_path(path: str) -> str: # type: ignore return str(PosixPath(path).expanduser())","files exist''' def __init__(self): # 1. Check if all config files exist all_exist","config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing [auth] config","PORT = config.getint(section, 'port', fallback=5000) WORKERS = config.getint(section, 'workers', fallback=4) LOG_LEVEL = config.get(section,","fallback=2) class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL =","2. Clone templates safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH)","environment variable! Try this: `export {env}=\"...\"` ''').format(env=name).split('\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH: section =","default config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All configs already exist, skipping...') def recreate_default_configuration_files(self)","log.error('[✘] Unable to recreate configuration files.') def safe_copy(self, src: str, dst: str) ->","'controllers/responses.yml') with open(respones_file_path, 'r') as file: RESPONSES = yaml.safe_load(file) class APP_SERVER: section =","SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER = mailbot_config.get(section,","= str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir /","dst: str) -> None: '''Safe means that it won't override existing configuration''' if","import configparser from typing import Dict, Optional, Any, List from inspect import cleandoc","self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config files permission rw_owner_only = 0o600","'proxy_tunneling' # Check if section is present and if yes, check if tunneling","already exist, skipping...') def recreate_default_configuration_files(self) -> None: try: # 1. Create directory for","ignore ''' Parses value for option from string to a valid python list.","= '~/.config/TensorHive/logs/' def full_path(path: str) -> str: # type: ignore return str(PosixPath(path).expanduser()) ENABLED","config_get_parsed(option: str, fallback: Any) -> List[str]: # type: ignore ''' Parses value for","fallback=1111) DEBUG = config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE: section = 'monitoring_service' ENABLED =","section in hosts_config.sections(): # We want to parse only sections which describe target","ValueError): log.warning('Parsing [auth] config section failed for option \"{}\", using fallback value: {}'.format(","MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section,","fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE:","class CONFIG_FILES: # Where to copy files # (TensorHive tries to load these","'migrations') class ConfigInitilizer: '''Makes sure that all default config files exist''' def __init__(self):","fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES =","'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None) section = 'smtp' SMTP_LOGIN = mailbot_config.get(section,","value in cls.__dict__.items(): if key.isupper(): print('{} = {}'.format(key, value)) def check_env_var(name: str): '''Makes","SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587) section = 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE","Displays all uppercase class atributes (class must be defined first) Example usage: display_config(API_SERVER)","''').format(env=name).split('\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH: section = 'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH)","hosts_config = ConfigLoader.load(path, displayed_title='hosts') result = {} for section in hosts_config.sections(): # We","def full_path(path: str) -> str: # type: ignore return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section,","found ({})'.format(full_path)) log.info('Using default {} settings from config.py'.format(displayed_title)) return config ConfigInitilizer() config =","value)) def check_env_var(name: str): '''Makes sure that env variable is declared''' if not","= config.getint(section, \"schedule_queued_jobs_when_free_mins\", fallback=30) class AUTH: from datetime import timedelta section = 'auth'","= ['foo', 'bar'] Will return: ['foo', 'bar'] ''' import ast try: raw_arguments =","-> Optional[Dict]: # type: ignore '''Parses [proxy_tunneling] section''' config = ConfigLoader.load(path, displayed_title='proxy') section","list. Fallback value is returned when anything goes wrong (e.g. option or value","'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=5000) WORKERS = config.getint(section, 'workers', fallback=4) LOG_LEVEL","all default config files exist''' def __init__(self): # 1. Check if all config","section = 'proxy_tunneling' # Check if section is present and if yes, check","shutil import tensorhive import os import logging log = logging.getLogger(__name__) class CONFIG_FILES: #","that all default config files exist''' def __init__(self): # 1. Check if all","type: ignore '''Parses [proxy_tunneling] section''' config = ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling' #","config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=1111) DEBUG = config.getboolean(section, 'debug', fallback=False)","'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \"schedule_queued_jobs_when_free_mins\", fallback=30) class","Try this: `export {env}=\"...\"` ''').format(env=name).split('\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH: section = 'ssh' HOSTS_CONFIG_FILE","'html_body') class USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def full_path(path: str) ->","goes wrong (e.g. option or value not present) Example .ini file, function called","(configparser.Error, ValueError): log.warning('Parsing [auth] config section failed for option \"{}\", using fallback value:","return result def proxy_config_to_dict(path: str) -> Optional[Dict]: # type: ignore '''Parses [proxy_tunneling] section'''","section''' config = ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling' # Check if section is","= config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval',","str) -> Optional[Dict]: # type: ignore '''Parses [proxy_tunneling] section''' config = ConfigLoader.load(path, displayed_title='proxy')","= 'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER","config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): ''' Displays all uppercase class atributes (class","log.warning(msg[0]) log.warning(msg[1]) class SSH: section = 'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP","fallback value: {}'.format( option, fallback)) return fallback FLASK_JWT = { 'SECRET_KEY': config.get(section, 'secrect_key',","respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path, 'r') as file: RESPONSES = yaml.safe_load(file)","section = 'protection_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0)","'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL","'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587) section = 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section,","ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' # Use","'~/.config/TensorHive/logs/' def full_path(path: str) -> str: # type: ignore return str(PosixPath(path).expanduser()) ENABLED =","-> str: # type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI","import timedelta section = 'auth' def config_get_parsed(option: str, fallback: Any) -> List[str]: #","src: str, dst: str) -> None: '''Safe means that it won't override existing","return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section = 'database'","str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations') class ConfigInitilizer: '''Makes sure that","fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) -> Dict: # type: ignore '''Parses sections containing hostnames'''","get file templates from # (Clone file when it's not found in config","option or value not present) Example .ini file, function called with arguments: option='some_option',","in hosts_config.sections(): # We want to parse only sections which describe target hosts","SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path","section = 'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def full_path(path: str) -> str: # type:","type: ignore ''' Parses value for option from string to a valid python","config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path))","safe_copy(self, src: str, dst: str) -> None: '''Safe means that it won't override","sections which describe target hosts if section == 'proxy_tunneling': continue hostname = section","config section failed for option \"{}\", using fallback value: {}'.format( option, fallback)) return","fallback=True) TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1) KEY_FILE =","hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section = 'database' default_path = '~/.config/TensorHive/database.sqlite' def","'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION","Use in-memory (before: sqlite:///test_database.sqlite) class API: section = 'api' TITLE = config.get(section, 'title',","MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir","only sections which describe target hosts if section == 'proxy_tunneling': continue hostname =","PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section = 'database' default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path:","= PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir /","'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \"schedule_queued_jobs_when_free_mins\", fallback=30) class AUTH: from datetime import timedelta","from inspect import cleandoc import shutil import tensorhive import os import logging log","config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1) KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key')","# (Clone file when it's not found in config directory) tensorhive_package_dir = PosixPath(__file__).parent","load(path, displayed_title=''): import configparser config = configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•]","} return result def proxy_config_to_dict(path: str) -> Optional[Dict]: # type: ignore '''Parses [proxy_tunneling]","open(respones_file_path, 'r') as file: RESPONSES = yaml.safe_load(file) class APP_SERVER: section = 'web_app.server' BACKEND","not os.getenv(name): msg = cleandoc( ''' {env} - undeclared environment variable! Try this:","it won't override existing configuration''' if PosixPath(dst).exists(): log.info('Skipping, file already exists: {}'.format(dst)) else:","already exists: {}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied {} to {}'.format(src, dst)) class ConfigLoader:","import os import logging log = logging.getLogger(__name__) class CONFIG_FILES: # Where to copy","in-memory (before: sqlite:///test_database.sqlite) class API: section = 'api' TITLE = config.get(section, 'title', fallback='TensorHive","'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix', fallback='api') SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION","Where to get file templates from # (Clone file when it's not found","Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in cls.__dict__.items(): if key.isupper(): print('{}","= 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section = 'template/admin'","cleandoc import shutil import tensorhive import os import logging log = logging.getLogger(__name__) class","config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix',","section = 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE:","print('{} = {}'.format(key, value)) def check_env_var(name: str): '''Makes sure that env variable is","{env}=\"...\"` ''').format(env=name).split('\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH: section = 'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file',","hosts_config.getint(hostname, 'port', fallback=22) } return result def proxy_config_to_dict(path: str) -> Optional[Dict]: # type:","or value not present) Example .ini file, function called with arguments: option='some_option', fallback=None","class ConfigInitilizer: '''Makes sure that all default config files exist''' def __init__(self): #","{}'.format(key, value)) def check_env_var(name: str): '''Makes sure that env variable is declared''' if","fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None) section = 'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email',","cleandoc( ''' {env} - undeclared environment variable! Try this: `export {env}=\"...\"` ''').format(env=name).split('\\n') log.warning(msg[0])","/ 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations') class ConfigInitilizer: '''Makes sure that all","section = 'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True)","= section result[hostname] = { 'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22) }","class API_SERVER: section = 'api.server' BACKEND = config.get(section, 'backend', fallback='gevent') HOST = config.get(section,","function called with arguments: option='some_option', fallback=None [some_section] some_option = ['foo', 'bar'] Will return:","0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘] Unable to recreate","some_option = ['foo', 'bar'] Will return: ['foo', 'bar'] ''' import ast try: raw_arguments","return config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): ''' Displays all uppercase","= config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing [auth]","Dict, Optional, Any, List from inspect import cleandoc import shutil import tensorhive import","fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE:","'smtp_port', fallback=587) section = 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body')","option \"{}\", using fallback value: {}'.format( option, fallback)) return fallback FLASK_JWT = {","logging.getLogger(__name__) class CONFIG_FILES: # Where to copy files # (TensorHive tries to load","- undeclared environment variable! Try this: `export {env}=\"...\"` ''').format(env=name).split('\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH:","= 'auth' def config_get_parsed(option: str, fallback: Any) -> List[str]: # type: ignore '''","{}'.format( option, fallback)) return fallback FLASK_JWT = { 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED':","proxy_config_to_dict(path: str) -> Optional[Dict]: # type: ignore '''Parses [proxy_tunneling] section''' config = ConfigLoader.load(path,","Will return: ['foo', 'bar'] ''' import ast try: raw_arguments = config.get('auth', option) parsed_arguments","= { 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access',","/ 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini') #","'''Makes sure that all default config files exist''' def __init__(self): # 1. Check","= ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling' # Check if section is present and","for option from string to a valid python list. Fallback value is returned","MONITORING_SERVICE: section = 'monitoring_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor',","= { 'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22) } return result def","INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section = 'template/admin' ADMIN_SUBJECT =","Create directory for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone templates safely","to {}'.format(src, dst)) class ConfigLoader: @staticmethod def load(path, displayed_title=''): import configparser config =","'database' default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) -> str: # type: ignore return","# Where to copy files # (TensorHive tries to load these by default)","be defined first) Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in cls.__dict__.items():","ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section = 'usage_logging_service'","full_path)) else: log.warning('[✘] Configuration file not found ({})'.format(full_path)) log.info('Using default {} settings from","PosixPath(dst).exists(): log.info('Skipping, file already exists: {}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied {} to {}'.format(src,","section = 'web_app.server' BACKEND = config.get(section, 'backend', fallback='gunicorn') HOST = config.get(section, 'host', fallback='0.0.0.0')","files.') def safe_copy(self, src: str, dst: str) -> None: '''Safe means that it","str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path, 'r') as file: RESPONSES = yaml.safe_load(file) class APP_SERVER:","that env variable is declared''' if not os.getenv(name): msg = cleandoc( ''' {env}","'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES","full_path = PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading {} config from {}'.format(displayed_title, full_path)) else:","containing hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts') result = {} for section in hosts_config.sections():","import tensorhive import os import logging log = logging.getLogger(__name__) class CONFIG_FILES: # Where","{}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied {} to {}'.format(src, dst)) class ConfigLoader: @staticmethod def","= mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def full_path(path:","= config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins',","fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)),","We want to parse only sections which describe target hosts if section ==","enabled if config.has_section(section) and config.getboolean(section, 'enabled', fallback=False): return { 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user':","class MONITORING_SERVICE: section = 'monitoring_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section,","config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled', fallback=True)","'api' TITLE = config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX","'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)), 'JWT_REFRESH_TOKEN_EXPIRES': timedelta(days=config.getint(section, 'jwt_refresh_token_expires_days', fallback=1)), 'JWT_TOKEN_LOCATION':","config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone templates safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH,","hosts_config.sections(): # We want to parse only sections which describe target hosts if","rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘] Unable to recreate configuration files.') def safe_copy(self,","fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section","class API: section = 'api' TITLE = config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME =","ENABLED = config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section,","config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section,","dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config files permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH,","import logging log = logging.getLogger(__name__) class CONFIG_FILES: # Where to copy files #","sure that env variable is declared''' if not os.getenv(name): msg = cleandoc( '''","fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)), 'JWT_REFRESH_TOKEN_EXPIRES': timedelta(days=config.getint(section, 'jwt_refresh_token_expires_days', fallback=1)), 'JWT_TOKEN_LOCATION': config_get_parsed('jwt_token_location', fallback=['headers']) }","Optional, Any, List from inspect import cleandoc import shutil import tensorhive import os","hostname = section result[hostname] = { 'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22)","MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general' INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0)","except (configparser.Error, ValueError): log.warning('Parsing [auth] config section failed for option \"{}\", using fallback","'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS","API: section = 'api' TITLE = config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME = config.get(section,","PosixPath import configparser from typing import Dict, Optional, Any, List from inspect import","str: # type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI =","config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1)","# type: ignore ''' Parses value for option from string to a valid","target hosts if section == 'proxy_tunneling': continue hostname = section result[hostname] = {","files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone templates safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH)","default {} settings from config.py'.format(displayed_title)) return config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def","and \\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•] Detected missing default config file(s), recreating...')","Parses value for option from string to a valid python list. Fallback value","Dict: # type: ignore '''Parses sections containing hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts') result","({})'.format(full_path)) log.info('Using default {} settings from config.py'.format(displayed_title)) return config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH,","and if yes, check if tunneling is enabled if config.has_section(section) and config.getboolean(section, 'enabled',","section = 'database' default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) -> str: # type:","fallback=4) LOG_LEVEL = config.get(section, 'loglevel', fallback='warning') class API_SERVER: section = 'api.server' BACKEND =","= mailbot_config.getint(section, 'smtp_port', fallback=587) section = 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE =","TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES = config.getint(section,","and config.getboolean(section, 'enabled', fallback=False): return { 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port':","'port': hosts_config.getint(hostname, 'port', fallback=22) } return result def proxy_config_to_dict(path: str) -> Optional[Dict]: #","= mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server',","try: raw_arguments = config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error, ValueError):","'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors',","# Where to get file templates from # (Clone file when it's not","config = ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling' # Check if section is present","API_SERVER: section = 'api.server' BACKEND = config.get(section, 'backend', fallback='gevent') HOST = config.get(section, 'host',","= 'proxy_tunneling' # Check if section is present and if yes, check if","fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \"schedule_queued_jobs_when_free_mins\", fallback=30) class AUTH: from datetime import timedelta section","all_exist: log.warning('[•] Detected missing default config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All configs already","import configparser config = configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading {}","return parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing [auth] config section failed for option \"{}\",","= config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email',","key.isupper(): print('{} = {}'.format(key, value)) def check_env_var(name: str): '''Makes sure that env variable","3. Change config files permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH,","= yaml.safe_load(file) class APP_SERVER: section = 'web_app.server' BACKEND = config.get(section, 'backend', fallback='gunicorn') HOST","ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section,","'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section = 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE","'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN","TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1) KEY_FILE = config.get(section,","if not os.getenv(name): msg = cleandoc( ''' {env} - undeclared environment variable! Try","config.getint(section, 'proxy_port', fallback=22) } else: return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE)","fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \"schedule_queued_jobs_when_free_mins\", fallback=30) class AUTH:","'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) class","os.getenv(name): msg = cleandoc( ''' {env} - undeclared environment variable! Try this: `export","'proxy_tunneling': continue hostname = section result[hostname] = { 'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname,","HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=1111) DEBUG = config.getboolean(section,","section = 'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None)","all config files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists()","config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=5000) WORKERS = config.getint(section, 'workers', fallback=4)","= config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE: section = 'monitoring_service' ENABLED = config.getboolean(section, 'enabled',","config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)), 'JWT_REFRESH_TOKEN_EXPIRES': timedelta(days=config.getint(section,","= PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•] Detected","sure that all default config files exist''' def __init__(self): # 1. Check if","fallback=None) section = 'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password',","for option \"{}\", using fallback value: {}'.format( option, fallback)) return fallback FLASK_JWT =","directory for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone templates safely from","import ast try: raw_arguments = config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments except","parse only sections which describe target hosts if section == 'proxy_tunneling': continue hostname","option, fallback)) return fallback FLASK_JWT = { 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section,","declared''' if not os.getenv(name): msg = cleandoc( ''' {env} - undeclared environment variable!","Detected missing default config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All configs already exist, skipping...')","self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config files permission rw_owner_only","= full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section =","displayed_title='main') def display_config(cls): ''' Displays all uppercase class atributes (class must be defined","atributes (class must be defined first) Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key,","= config.get(section, 'backend', fallback='gevent') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port',","NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None) section = 'smtp'","# 3. Change config files permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only)","result = {} for section in hosts_config.sections(): # We want to parse only","str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini')","failed for option \"{}\", using fallback value: {}'.format( option, fallback)) return fallback FLASK_JWT","'debug', fallback=False) class MONITORING_SERVICE: section = 'monitoring_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR","tunneling is enabled if config.has_section(section) and config.getboolean(section, 'enabled', fallback=False): return { 'proxy_host': config.get(section,","= uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' # Use in-memory (before: sqlite:///test_database.sqlite) class","exist_ok=True) # 2. Clone templates safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH)","(class must be defined first) Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value","MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir","self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config files permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only)","class SSH: section = 'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section,","= {} for section in hosts_config.sections(): # We want to parse only sections","'port', fallback=5000) WORKERS = config.getint(section, 'workers', fallback=4) LOG_LEVEL = config.get(section, 'loglevel', fallback='warning') class","HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=5000) WORKERS = config.getint(section,","str) -> str: # type: ignore return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled', fallback=True)","that it won't override existing configuration''' if PosixPath(dst).exists(): log.info('Skipping, file already exists: {}'.format(dst))","section is present and if yes, check if tunneling is enabled if config.has_section(section)","config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \"schedule_queued_jobs_when_free_mins\", fallback=30) class AUTH: from datetime import","value is returned when anything goes wrong (e.g. option or value not present)","LOG_LEVEL = config.get(section, 'loglevel', fallback='warning') class API_SERVER: section = 'api.server' BACKEND = config.get(section,","= mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder',","-> None: try: # 1. Create directory for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True)","'title', fallback='TensorHive API') URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix', fallback='api')","def hosts_config_to_dict(path: str) -> Dict: # type: ignore '''Parses sections containing hostnames''' hosts_config","with open(respones_file_path, 'r') as file: RESPONSES = yaml.safe_load(file) class APP_SERVER: section = 'web_app.server'","in cls.__dict__.items(): if key.isupper(): print('{} = {}'.format(key, value)) def check_env_var(name: str): '''Makes sure","with arguments: option='some_option', fallback=None [some_section] some_option = ['foo', 'bar'] Will return: ['foo', 'bar']","= 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘] Unable to","config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH,","= config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path =","'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)), 'JWT_REFRESH_TOKEN_EXPIRES': timedelta(days=config.getint(section, 'jwt_refresh_token_expires_days', fallback=1)), 'JWT_TOKEN_LOCATION': config_get_parsed('jwt_token_location', fallback=['headers'])","return { 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22) }","configuration files.') def safe_copy(self, src: str, dst: str) -> None: '''Safe means that","str) -> str: # type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path))","fallback=None [some_section] some_option = ['foo', 'bar'] Will return: ['foo', 'bar'] ''' import ast","= mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section = 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section,","templates safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3.","hosts if section == 'proxy_tunneling': continue hostname = section result[hostname] = { 'user':","[some_section] some_option = ['foo', 'bar'] Will return: ['foo', 'bar'] ''' import ast try:","fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' # Use in-memory (before: sqlite:///test_database.sqlite) class API: section =","by default) config_dir = PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH","env variable is declared''' if not os.getenv(name): msg = cleandoc( ''' {env} -","= 'sqlite://' # Use in-memory (before: sqlite:///test_database.sqlite) class API: section = 'api' TITLE","'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section = 'template/admin' ADMIN_SUBJECT","= logging.getLogger(__name__) class CONFIG_FILES: # Where to copy files # (TensorHive tries to","yes, check if tunneling is enabled if config.has_section(section) and config.getboolean(section, 'enabled', fallback=False): return","section = 'auth' def config_get_parsed(option: str, fallback: Any) -> List[str]: # type: ignore","section = 'general' INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50)","stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone templates safely from `tensorhive` package","recreate configuration files.') def safe_copy(self, src: str, dst: str) -> None: '''Safe means","/ 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini') # Where to get file templates","import cleandoc import shutil import tensorhive import os import logging log = logging.getLogger(__name__)","else: shutil.copy(src, dst) log.info('Copied {} to {}'.format(src, dst)) class ConfigLoader: @staticmethod def load(path,","\"schedule_queued_jobs_when_free_mins\", fallback=30) class AUTH: from datetime import timedelta section = 'auth' def config_get_parsed(option:","section = 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section =","'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT","config = configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading {} config from","variable is declared''' if not os.getenv(name): msg = cleandoc( ''' {env} - undeclared","'mailbot_config.ini') # Where to get file templates from # (Clone file when it's","= str(tensorhive_package_dir / 'migrations') class ConfigInitilizer: '''Makes sure that all default config files","'protection_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY =","called with arguments: option='some_option', fallback=None [some_section] some_option = ['foo', 'bar'] Will return: ['foo',","if not all_exist: log.warning('[•] Detected missing default config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All","for key, value in cls.__dict__.items(): if key.isupper(): print('{} = {}'.format(key, value)) def check_env_var(name:","fallback='tensorhive.api.controllers') import yaml respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path, 'r') as file:","JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval',","'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations') class ConfigInitilizer:","config.getint(section, 'number_of_retries', fallback=1) KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) -> Dict:","{ 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22) } else:","fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587) section =","log.info('Copied {} to {}'.format(src, dst)) class ConfigLoader: @staticmethod def load(path, displayed_title=''): import configparser","ConfigLoader: @staticmethod def load(path, displayed_title=''): import configparser config = configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser()","it's not found in config directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir /","fallback='api') SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml",".ini file, function called with arguments: option='some_option', fallback=None [some_section] some_option = ['foo', 'bar']","rw_owner_only) except Exception: log.error('[✘] Unable to recreate configuration files.') def safe_copy(self, src: str,","config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path = str(PosixPath(__file__).parent","mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587) section = 'template/intruder' INTRUDER_SUBJECT =","mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587)","import shutil import tensorhive import os import logging log = logging.getLogger(__name__) class CONFIG_FILES:","str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations')","msg = cleandoc( ''' {env} - undeclared environment variable! Try this: `export {env}=\"...\"`","fallback=False) class MONITORING_SERVICE: section = 'monitoring_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR =","= 'general' INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER","all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•]","hosts_config_to_dict(path: str) -> Dict: # type: ignore '''Parses sections containing hostnames''' hosts_config =","config files exist''' def __init__(self): # 1. Check if all config files exist","= config.getint(section, 'workers', fallback=4) LOG_LEVEL = config.get(section, 'loglevel', fallback='warning') class API_SERVER: section =","= ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): ''' Displays all uppercase class atributes (class must","file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All configs already exist, skipping...') def recreate_default_configuration_files(self) -> None:","'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False) class","config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0)","for section in hosts_config.sections(): # We want to parse only sections which describe","this: `export {env}=\"...\"` ''').format(env=name).split('\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH: section = 'ssh' HOSTS_CONFIG_FILE =","shutil.copy(src, dst) log.info('Copied {} to {}'.format(src, dst)) class ConfigLoader: @staticmethod def load(path, displayed_title=''):","None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section = 'database' default_path","# Use in-memory (before: sqlite:///test_database.sqlite) class API: section = 'api' TITLE = config.get(section,","display_config(cls): ''' Displays all uppercase class atributes (class must be defined first) Example","== 'proxy_tunneling': continue hostname = section result[hostname] = { 'user': hosts_config.get(hostname, 'user'), 'port':","section result[hostname] = { 'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22) } return","= config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=5000) WORKERS = config.getint(section, 'workers',","displayed_title=''): import configparser config = configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading","uppercase class atributes (class must be defined first) Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__))","'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section =","str, fallback: Any) -> List[str]: # type: ignore ''' Parses value for option","['foo', 'bar'] ''' import ast try: raw_arguments = config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments)","fallback=30) class AUTH: from datetime import timedelta section = 'auth' def config_get_parsed(option: str,","'enabled', fallback=False): return { 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port',","Configuration file not found ({})'.format(full_path)) log.info('Using default {} settings from config.py'.format(displayed_title)) return config","os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘] Unable to recreate configuration","log.warning(msg[1]) class SSH: section = 'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP ="],"string":"[\n \"mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False)\",\n \"/ 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH\",\n \"config files permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except\",\n \"file already exists: {}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied {} to {}'.format(src, dst)) class\",\n \"= mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587) section = 'template/intruder' INTRUDER_SUBJECT\",\n \"section = 'api.server' BACKEND = config.get(section, 'backend', fallback='gevent') HOST = config.get(section, 'host', fallback='0.0.0.0')\",\n \"= config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path,\",\n \"logging log = logging.getLogger(__name__) class CONFIG_FILES: # Where to copy files # (TensorHive\",\n \"configparser from typing import Dict, Optional, Any, List from inspect import cleandoc import\",\n \"'''Safe means that it won't override existing configuration''' if PosixPath(dst).exists(): log.info('Skipping, file already\",\n \"# type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://'\",\n \"config.getboolean(section, 'enabled', fallback=False): return { 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section,\",\n \"NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1) KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str)\",\n \"Any, List from inspect import cleandoc import shutil import tensorhive import os import\",\n \"'r') as file: RESPONSES = yaml.safe_load(file) class APP_SERVER: section = 'web_app.server' BACKEND =\",\n \"fallback=False) class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general' INTERVAL = mailbot_config.getfloat(section,\",\n \"'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes',\",\n \"'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot')\",\n \"str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR =\",\n \"config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE: section = 'protection_service'\",\n \"not found ({})'.format(full_path)) log.info('Using default {} settings from config.py'.format(displayed_title)) return config ConfigInitilizer() config\",\n \"= mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None) section = 'smtp' SMTP_LOGIN\",\n \"''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in cls.__dict__.items(): if key.isupper(): print('{} = {}'.format(key, value))\",\n \"recreating...') self.recreate_default_configuration_files() log.info('[•] All configs already exist, skipping...') def recreate_default_configuration_files(self) -> None: try:\",\n \"mailbot_config.get(section, 'html_body') section = 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body')\",\n \"'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def full_path(path: str) -> str: # type: ignore return\",\n \"ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): ''' Displays all uppercase class atributes (class must be\",\n \"} else: return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section\",\n \"else: log.warning('[✘] Configuration file not found ({})'.format(full_path)) log.info('Using default {} settings from config.py'.format(displayed_title))\",\n \"fallback='warning') class API_SERVER: section = 'api.server' BACKEND = config.get(section, 'backend', fallback='gevent') HOST =\",\n \"class DB: section = 'database' default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) -> str:\",\n \"ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general' INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section,\",\n \"SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section,\",\n \"copy files # (TensorHive tries to load these by default) config_dir = PosixPath.home()\",\n \"'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path = '~/.config/TensorHive/logs/'\",\n \"AUTH: from datetime import timedelta section = 'auth' def config_get_parsed(option: str, fallback: Any)\",\n \"[auth] config section failed for option \\\"{}\\\", using fallback value: {}'.format( option, fallback))\",\n \"# 1. Create directory for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone\",\n \"\\\"{}\\\", using fallback value: {}'.format( option, fallback)) return fallback FLASK_JWT = { 'SECRET_KEY':\",\n \"'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' # Use in-memory (before: sqlite:///test_database.sqlite) class API: section\",\n \"fallback=22) } return result def proxy_config_to_dict(path: str) -> Optional[Dict]: # type: ignore '''Parses\",\n \"class AUTH: from datetime import timedelta section = 'auth' def config_get_parsed(option: str, fallback:\",\n \"section == 'proxy_tunneling': continue hostname = section result[hostname] = { 'user': hosts_config.get(hostname, 'user'),\",\n \"log.info('Skipping, file already exists: {}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied {} to {}'.format(src, dst))\",\n \"string to a valid python list. Fallback value is returned when anything goes\",\n \"config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general' INTERVAL\",\n \"when it's not found in config directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir\",\n \"fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED =\",\n \"hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts') result = {} for section in hosts_config.sections(): #\",\n \"'bar'] Will return: ['foo', 'bar'] ''' import ast try: raw_arguments = config.get('auth', option)\",\n \"using fallback value: {}'.format( option, fallback)) return fallback FLASK_JWT = { 'SECRET_KEY': config.get(section,\",\n \"first) Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in cls.__dict__.items(): if key.isupper():\",\n \"List[str]: # type: ignore ''' Parses value for option from string to a\",\n \"dst) log.info('Copied {} to {}'.format(src, dst)) class ConfigLoader: @staticmethod def load(path, displayed_title=''): import\",\n \"rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘] Unable to recreate configuration files.')\",\n \"ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling' # Check if section is present and if\",\n \"fallback=5000) WORKERS = config.getint(section, 'workers', fallback=4) LOG_LEVEL = config.get(section, 'loglevel', fallback='warning') class API_SERVER:\",\n \"config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE: section = 'protection_service' ENABLED = config.getboolean(section, 'enabled', fallback=True)\",\n \"fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT =\",\n \"str(tensorhive_package_dir / 'migrations') class ConfigInitilizer: '''Makes sure that all default config files exist'''\",\n \"fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=1111) DEBUG = config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE:\",\n \"= config.get(section, 'url_prefix', fallback='api') SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location',\",\n \"section = 'api' TITLE = config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME = config.get(section, 'url_hostname',\",\n \"file templates from # (Clone file when it's not found in config directory)\",\n \"class atributes (class must be defined first) Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for\",\n \"'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations') class ConfigInitilizer: '''Makes sure that all default\",\n \"APP_SERVER: section = 'web_app.server' BACKEND = config.get(section, 'backend', fallback='gunicorn') HOST = config.get(section, 'host',\",\n \"to load these by default) config_dir = PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir\",\n \"= ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general' INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL =\",\n \"ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def\",\n \"config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All configs already exist, skipping...') def recreate_default_configuration_files(self) ->\",\n \"Change config files permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only)\",\n \"= str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir /\",\n \"fallback='TensorHive API') URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix', fallback='api') SPEC_FILE\",\n \"SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \\\"schedule_queued_jobs_when_free_mins\\\", fallback=30) class AUTH: from datetime import timedelta section =\",\n \"file not found ({})'.format(full_path)) log.info('Using default {} settings from config.py'.format(displayed_title)) return config ConfigInitilizer()\",\n \"1. Check if all config files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists()\",\n \"= 'api' TITLE = config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0')\",\n \"= hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section = 'database' default_path = '~/.config/TensorHive/database.sqlite'\",\n \"UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section,\",\n \"won't override existing configuration''' if PosixPath(dst).exists(): log.info('Skipping, file already exists: {}'.format(dst)) else: shutil.copy(src,\",\n \"= config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty',\",\n \"exists: {}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied {} to {}'.format(src, dst)) class ConfigLoader: @staticmethod\",\n \"'loglevel', fallback='warning') class API_SERVER: section = 'api.server' BACKEND = config.get(section, 'backend', fallback='gevent') HOST\",\n \"settings from config.py'.format(displayed_title)) return config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): '''\",\n \"to get file templates from # (Clone file when it's not found in\",\n \"def safe_copy(self, src: str, dst: str) -> None: '''Safe means that it won't\",\n \"anything goes wrong (e.g. option or value not present) Example .ini file, function\",\n \"NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT: mailbot_config\",\n \"exist, skipping...') def recreate_default_configuration_files(self) -> None: try: # 1. Create directory for stroing\",\n \"/ 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH\",\n \"Where to copy files # (TensorHive tries to load these by default) config_dir\",\n \"# Check if section is present and if yes, check if tunneling is\",\n \"mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None)\",\n \"dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config files permission rw_owner_only =\",\n \"= mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email',\",\n \"CONFIG_FILES: # Where to copy files # (TensorHive tries to load these by\",\n \"= config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE: section =\",\n \"= mailbot_config.get(section, 'admin_email', fallback=None) section = 'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD\",\n \"def proxy_config_to_dict(path: str) -> Optional[Dict]: # type: ignore '''Parses [proxy_tunneling] section''' config =\",\n \"config files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if\",\n \"proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section = 'database' default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) ->\",\n \"Optional[Dict]: # type: ignore '''Parses [proxy_tunneling] section''' config = ConfigLoader.load(path, displayed_title='proxy') section =\",\n \"config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path, 'r')\",\n \"-> None: '''Safe means that it won't override existing configuration''' if PosixPath(dst).exists(): log.info('Skipping,\",\n \"def __init__(self): # 1. Check if all config files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists()\",\n \"exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist:\",\n \"safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change\",\n \"'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22) } else: return\",\n \"INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section,\",\n \"class USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def full_path(path: str) -> str:\",\n \"'workers', fallback=4) LOG_LEVEL = config.get(section, 'loglevel', fallback='warning') class API_SERVER: section = 'api.server' BACKEND\",\n \"{ 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']),\",\n \"fallback='gunicorn') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=5000) WORKERS =\",\n \"import yaml respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path, 'r') as file: RESPONSES\",\n \"= config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE: section = 'protection_service' ENABLED = config.getboolean(section, 'enabled',\",\n \"config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0)\",\n \"full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service'\",\n \"'~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) -> str: # type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI =\",\n \"to parse only sections which describe target hosts if section == 'proxy_tunneling': continue\",\n \"MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini') # Where to get file templates from #\",\n \"'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=1111) DEBUG = config.getboolean(section, 'debug', fallback=False) class\",\n \"'.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH =\",\n \"if config.read(str(full_path)): log.info('[•] Reading {} config from {}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration file\",\n \"'''Makes sure that env variable is declared''' if not os.getenv(name): msg = cleandoc(\",\n \"ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section,\",\n \"from {}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration file not found ({})'.format(full_path)) log.info('Using default {}\",\n \"displayed_title='proxy') section = 'proxy_tunneling' # Check if section is present and if yes,\",\n \"os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘] Unable to recreate configuration files.') def safe_copy(self, src:\",\n \"pathlib import PosixPath import configparser from typing import Dict, Optional, Any, List from\",\n \"from config.py'.format(displayed_title)) return config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): ''' Displays\",\n \"config.has_section(section) and config.getboolean(section, 'enabled', fallback=False): return { 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'),\",\n \"check if tunneling is enabled if config.has_section(section) and config.getboolean(section, 'enabled', fallback=False): return {\",\n \"(Clone file when it's not found in config directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH\",\n \"HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section,\",\n \"'web_app.server' BACKEND = config.get(section, 'backend', fallback='gunicorn') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT =\",\n \"inspect import cleandoc import shutil import tensorhive import os import logging log =\",\n \"CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone templates safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH,\",\n \"is declared''' if not os.getenv(name): msg = cleandoc( ''' {env} - undeclared environment\",\n \"{} for section in hosts_config.sections(): # We want to parse only sections which\",\n \"'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE: section = 'protection_service' ENABLED\",\n \"'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22) } else: return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY\",\n \"'notify_via_email', fallback=False) class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general' INTERVAL =\",\n \"Example .ini file, function called with arguments: option='some_option', fallback=None [some_section] some_option = ['foo',\",\n \"[proxy_tunneling] section''' config = ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling' # Check if section\",\n \"ast try: raw_arguments = config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error,\",\n \"variable! Try this: `export {env}=\\\"...\\\"` ''').format(env=name).split('\\\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH: section = 'ssh'\",\n \"fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None) section =\",\n \"KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) -> Dict: # type: ignore\",\n \"mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True)\",\n \"HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini') # Where to\",\n \"if key.isupper(): print('{} = {}'.format(key, value)) def check_env_var(name: str): '''Makes sure that env\",\n \"''' {env} - undeclared environment variable! Try this: `export {env}=\\\"...\\\"` ''').format(env=name).split('\\\\n') log.warning(msg[0]) log.warning(msg[1])\",\n \"DEBUG = config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE: section = 'monitoring_service' ENABLED = config.getboolean(section,\",\n \"ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None) section = 'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None)\",\n \"fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587) section = 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject')\",\n \"to copy files # (TensorHive tries to load these by default) config_dir =\",\n \"def check_env_var(name: str): '''Makes sure that env variable is declared''' if not os.getenv(name):\",\n \"str): '''Makes sure that env variable is declared''' if not os.getenv(name): msg =\",\n \"fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=5000) WORKERS = config.getint(section, 'workers', fallback=4) LOG_LEVEL =\",\n \"load these by default) config_dir = PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir /\",\n \"'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22) } else: return None AVAILABLE_NODES =\",\n \"files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not\",\n \"'bar'] ''' import ast try: raw_arguments = config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments) return\",\n \"mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None)\",\n \"present) Example .ini file, function called with arguments: option='some_option', fallback=None [some_section] some_option =\",\n \"'timeout', fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1) KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def\",\n \"config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix', fallback='api') SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml')\",\n \"raw_arguments = config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing\",\n \"/ 'mailbot_config.ini') # Where to get file templates from # (Clone file when\",\n \"config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)), 'JWT_REFRESH_TOKEN_EXPIRES': timedelta(days=config.getint(section, 'jwt_refresh_token_expires_days', fallback=1)), 'JWT_TOKEN_LOCATION': config_get_parsed('jwt_token_location',\",\n \"Exception: log.error('[✘] Unable to recreate configuration files.') def safe_copy(self, src: str, dst: str)\",\n \"'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22) } else: return None AVAILABLE_NODES\",\n \"AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section = 'database' default_path =\",\n \"fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml')\",\n \"config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False)\",\n \"default) config_dir = PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH =\",\n \"FLASK_JWT = { 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks',\",\n \"None: try: # 1. Create directory for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) #\",\n \"def config_get_parsed(option: str, fallback: Any) -> List[str]: # type: ignore ''' Parses value\",\n \"'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL\",\n \"None: '''Safe means that it won't override existing configuration''' if PosixPath(dst).exists(): log.info('Skipping, file\",\n \"ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE: section\",\n \"parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing [auth] config section failed\",\n \"ConfigInitilizer: '''Makes sure that all default config files exist''' def __init__(self): # 1.\",\n \"config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) -> Dict: # type: ignore '''Parses sections\",\n \"file when it's not found in config directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH =\",\n \"config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2)\",\n \"returned when anything goes wrong (e.g. option or value not present) Example .ini\",\n \"'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH =\",\n \"uri_for_path(path: str) -> str: # type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path',\",\n \"present and if yes, check if tunneling is enabled if config.has_section(section) and config.getboolean(section,\",\n \"STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \\\"schedule_queued_jobs_when_free_mins\\\", fallback=30) class AUTH: from\",\n \"section failed for option \\\"{}\\\", using fallback value: {}'.format( option, fallback)) return fallback\",\n \"mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None) section = 'smtp' SMTP_LOGIN =\",\n \"mailbot_config.getint(section, 'smtp_port', fallback=587) section = 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section,\",\n \"config.getint(section, 'workers', fallback=4) LOG_LEVEL = config.get(section, 'loglevel', fallback='warning') class API_SERVER: section = 'api.server'\",\n \"{} to {}'.format(src, dst)) class ConfigLoader: @staticmethod def load(path, displayed_title=''): import configparser config\",\n \"if config.has_section(section) and config.getboolean(section, 'enabled', fallback=False): return { 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section,\",\n \"config.getint(section, 'port', fallback=5000) WORKERS = config.getint(section, 'workers', fallback=4) LOG_LEVEL = config.get(section, 'loglevel', fallback='warning')\",\n \"PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini')\",\n \"NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section =\",\n \"config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0)\",\n \"config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section,\",\n \"to a valid python list. Fallback value is returned when anything goes wrong\",\n \"class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section,\",\n \"value: {}'.format( option, fallback)) return fallback FLASK_JWT = { 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'),\",\n \"return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR\",\n \"override existing configuration''' if PosixPath(dst).exists(): log.info('Skipping, file already exists: {}'.format(dst)) else: shutil.copy(src, dst)\",\n \"for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone templates safely from `tensorhive`\",\n \"= mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port',\",\n \"BACKEND = config.get(section, 'backend', fallback='gunicorn') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section,\",\n \"'sqlite://' # Use in-memory (before: sqlite:///test_database.sqlite) class API: section = 'api' TITLE =\",\n \"print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in cls.__dict__.items(): if key.isupper(): print('{} = {}'.format(key, value)) def\",\n \"tensorhive import os import logging log = logging.getLogger(__name__) class CONFIG_FILES: # Where to\",\n \"str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini')\",\n \"str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini')\",\n \"= 'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def full_path(path: str) -> str: # type: ignore\",\n \"option='some_option', fallback=None [some_section] some_option = ['foo', 'bar'] Will return: ['foo', 'bar'] ''' import\",\n \"missing default config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All configs already exist, skipping...') def\",\n \"PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•] Detected missing default config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•]\",\n \"{}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration file not found ({})'.format(full_path)) log.info('Using default {} settings\",\n \"typing import Dict, Optional, Any, List from inspect import cleandoc import shutil import\",\n \"'auth' def config_get_parsed(option: str, fallback: Any) -> List[str]: # type: ignore ''' Parses\",\n \"permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘]\",\n \"List from inspect import cleandoc import shutil import tensorhive import os import logging\",\n \"'proxy_port': config.getint(section, 'proxy_port', fallback=22) } else: return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY =\",\n \"mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def full_path(path: str)\",\n \"sections containing hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts') result = {} for section in\",\n \"which describe target hosts if section == 'proxy_tunneling': continue hostname = section result[hostname]\",\n \"config.getint(section, \\\"schedule_queued_jobs_when_free_mins\\\", fallback=30) class AUTH: from datetime import timedelta section = 'auth' def\",\n \"'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)), 'JWT_REFRESH_TOKEN_EXPIRES':\",\n \"configparser config = configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading {} config\",\n \"fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN =\",\n \"yaml respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path, 'r') as file: RESPONSES =\",\n \"display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in cls.__dict__.items(): if key.isupper(): print('{} = {}'.format(key,\",\n \"= str(config_dir / 'mailbot_config.ini') # Where to get file templates from # (Clone\",\n \"log.info('Using default {} settings from config.py'.format(displayed_title)) return config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main')\",\n \"__init__(self): # 1. Check if all config files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and\",\n \"# We want to parse only sections which describe target hosts if section\",\n \"mailbot_config.get(section, 'admin_email', fallback=None) section = 'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD =\",\n \"= config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled',\",\n \"def recreate_default_configuration_files(self) -> None: try: # 1. Create directory for stroing config files\",\n \"fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1) KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path:\",\n \"hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22) } return result def proxy_config_to_dict(path: str) ->\",\n \"'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2) class\",\n \"fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL =\",\n \"check_env_var(name: str): '''Makes sure that env variable is declared''' if not os.getenv(name): msg\",\n \"configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading {} config from {}'.format(displayed_title, full_path))\",\n \"'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER =\",\n \"from typing import Dict, Optional, Any, List from inspect import cleandoc import shutil\",\n \"-> List[str]: # type: ignore ''' Parses value for option from string to\",\n \"class APP_SERVER: section = 'web_app.server' BACKEND = config.get(section, 'backend', fallback='gunicorn') HOST = config.get(section,\",\n \"UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE: section = 'protection_service' ENABLED = config.getboolean(section,\",\n \"'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED\",\n \"must be defined first) Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in\",\n \"-> Dict: # type: ignore '''Parses sections containing hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts')\",\n \"config from {}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration file not found ({})'.format(full_path)) log.info('Using default\",\n \"= PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH\",\n \"package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config files permission\",\n \"existing configuration''' if PosixPath(dst).exists(): log.info('Skipping, file already exists: {}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied\",\n \"if section == 'proxy_tunneling': continue hostname = section result[hostname] = { 'user': hosts_config.get(hostname,\",\n \"API') URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix', fallback='api') SPEC_FILE =\",\n \"mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section = 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject')\",\n \"= str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir /\",\n \"sqlite:///test_database.sqlite) class API: section = 'api' TITLE = config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME\",\n \"{} config from {}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration file not found ({})'.format(full_path)) log.info('Using\",\n \"= 'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT\",\n \"when anything goes wrong (e.g. option or value not present) Example .ini file,\",\n \"= config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix', fallback='api') SPEC_FILE = config.get(section, 'spec_file',\",\n \"log = logging.getLogger(__name__) class CONFIG_FILES: # Where to copy files # (TensorHive tries\",\n \"'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH =\",\n \"def uri_for_path(path: str) -> str: # type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section,\",\n \"'port', fallback=1111) DEBUG = config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE: section = 'monitoring_service' ENABLED\",\n \"all uppercase class atributes (class must be defined first) Example usage: display_config(API_SERVER) '''\",\n \"log.info('[•] Reading {} config from {}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration file not found\",\n \"= config.getint(section, 'port', fallback=1111) DEBUG = config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE: section =\",\n \"'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL\",\n \"= config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \\\"schedule_queued_jobs_when_free_mins\\\",\",\n \"fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True),\",\n \"= config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir',\",\n \"= config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=1111) DEBUG = config.getboolean(section, 'debug',\",\n \"if tunneling is enabled if config.has_section(section) and config.getboolean(section, 'enabled', fallback=False): return { 'proxy_host':\",\n \"config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \\\"schedule_queued_jobs_when_free_mins\\\", fallback=30)\",\n \"str) -> None: '''Safe means that it won't override existing configuration''' if PosixPath(dst).exists():\",\n \"log.warning('[✘] Configuration file not found ({})'.format(full_path)) log.info('Using default {} settings from config.py'.format(displayed_title)) return\",\n \"-> str: # type: ignore return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL\",\n \"undeclared environment variable! Try this: `export {env}=\\\"...\\\"` ''').format(env=name).split('\\\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH: section\",\n \"config.getint(section, 'port', fallback=1111) DEBUG = config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE: section = 'monitoring_service'\",\n \"# type: ignore '''Parses [proxy_tunneling] section''' config = ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling'\",\n \"config.get(section, 'backend', fallback='gevent') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=1111)\",\n \"= config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1) KEY_FILE = config.get(section, 'key_file',\",\n \"python list. Fallback value is returned when anything goes wrong (e.g. option or\",\n \"from string to a valid python list. Fallback value is returned when anything\",\n \"Check if all config files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and\",\n \"= str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations') class ConfigInitilizer: '''Makes sure\",\n \"from datetime import timedelta section = 'auth' def config_get_parsed(option: str, fallback: Any) ->\",\n \"class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general' INTERVAL = mailbot_config.getfloat(section, 'interval',\",\n \"str, dst: str) -> None: '''Safe means that it won't override existing configuration'''\",\n \"fallback FLASK_JWT = { 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS':\",\n \"ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing [auth] config section failed for option\",\n \"PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading {} config from {}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration\",\n \"dst)) class ConfigLoader: @staticmethod def load(path, displayed_title=''): import configparser config = configparser.ConfigParser(strict=False) full_path\",\n \"configuration''' if PosixPath(dst).exists(): log.info('Skipping, file already exists: {}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied {}\",\n \"# type: ignore '''Parses sections containing hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts') result =\",\n \"uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' # Use in-memory (before: sqlite:///test_database.sqlite) class API:\",\n \"fallback=1) KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) -> Dict: # type:\",\n \"describe target hosts if section == 'proxy_tunneling': continue hostname = section result[hostname] =\",\n \"TEST_DATABASE_URI = 'sqlite://' # Use in-memory (before: sqlite:///test_database.sqlite) class API: section = 'api'\",\n \"ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section,\",\n \"ConfigLoader.load(path, displayed_title='hosts') result = {} for section in hosts_config.sections(): # We want to\",\n \"parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing [auth] config section failed for option \\\"{}\\\", using\",\n \"if yes, check if tunneling is enabled if config.has_section(section) and config.getboolean(section, 'enabled', fallback=False):\",\n \"recreate_default_configuration_files(self) -> None: try: # 1. Create directory for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True,\",\n \"and \\\\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•] Detected missing default\",\n \"return: ['foo', 'bar'] ''' import ast try: raw_arguments = config.get('auth', option) parsed_arguments =\",\n \"timedelta section = 'auth' def config_get_parsed(option: str, fallback: Any) -> List[str]: # type:\",\n \"URL_PREFIX = config.get(section, 'url_prefix', fallback='api') SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section,\",\n \"templates from # (Clone file when it's not found in config directory) tensorhive_package_dir\",\n \"config.get(section, 'loglevel', fallback='warning') class API_SERVER: section = 'api.server' BACKEND = config.get(section, 'backend', fallback='gevent')\",\n \"# 1. Check if all config files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\\\\",\n \"# (TensorHive tries to load these by default) config_dir = PosixPath.home() / '.config/TensorHive'\",\n \"'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22) } return result def proxy_config_to_dict(path: str) -> Optional[Dict]:\",\n \"UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section,\",\n \"found in config directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH\",\n \"''' Parses value for option from string to a valid python list. Fallback\",\n \"fallback)) return fallback FLASK_JWT = { 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled',\",\n \"not present) Example .ini file, function called with arguments: option='some_option', fallback=None [some_section] some_option\",\n \"`tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config files\",\n \"if all config files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\\\\",\n \"config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True)\",\n \"= config.getint(section, 'number_of_retries', fallback=1) KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) ->\",\n \"SSH: section = 'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup',\",\n \"if PosixPath(dst).exists(): log.info('Skipping, file already exists: {}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied {} to\",\n \"Check if section is present and if yes, check if tunneling is enabled\",\n \"= config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section,\",\n \"RESPONSES = yaml.safe_load(file) class APP_SERVER: section = 'web_app.server' BACKEND = config.get(section, 'backend', fallback='gunicorn')\",\n \"these by default) config_dir = PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini')\",\n \"MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations') class ConfigInitilizer: '''Makes sure that all default config\",\n \"value not present) Example .ini file, function called with arguments: option='some_option', fallback=None [some_section]\",\n \"NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section,\",\n \"key, value in cls.__dict__.items(): if key.isupper(): print('{} = {}'.format(key, value)) def check_env_var(name: str):\",\n \"= PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading {} config from {}'.format(displayed_title, full_path)) else: log.warning('[✘]\",\n \"{ 'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22) } return result def proxy_config_to_dict(path:\",\n \"to recreate configuration files.') def safe_copy(self, src: str, dst: str) -> None: '''Safe\",\n \"try: # 1. Create directory for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2.\",\n \"= mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path\",\n \"{env} - undeclared environment variable! Try this: `export {env}=\\\"...\\\"` ''').format(env=name).split('\\\\n') log.warning(msg[0]) log.warning(msg[1]) class\",\n \"want to parse only sections which describe target hosts if section == 'proxy_tunneling':\",\n \"'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path = str(PosixPath(__file__).parent /\",\n \"str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini') # Where to get file\",\n \"fallback='gevent') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=1111) DEBUG =\",\n \"= 'api.server' BACKEND = config.get(section, 'backend', fallback='gevent') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT\",\n \"= config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section, 'timeout',\",\n \"WORKERS = config.getint(section, 'workers', fallback=4) LOG_LEVEL = config.get(section, 'loglevel', fallback='warning') class API_SERVER: section\",\n \"'number_of_retries', fallback=1) KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) -> Dict: #\",\n \"fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE: section = 'protection_service' ENABLED =\",\n \"from pathlib import PosixPath import configparser from typing import Dict, Optional, Any, List\",\n \"log.warning('Parsing [auth] config section failed for option \\\"{}\\\", using fallback value: {}'.format( option,\",\n \"config directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir\",\n \"a valid python list. Fallback value is returned when anything goes wrong (e.g.\",\n \"displayed_title='hosts') result = {} for section in hosts_config.sections(): # We want to parse\",\n \"/ '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH\",\n \"= proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section = 'database' default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str)\",\n \"@staticmethod def load(path, displayed_title=''): import configparser config = configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if\",\n \"log.warning('[•] Detected missing default config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All configs already exist,\",\n \"= config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries',\",\n \"'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS':\",\n \"(TensorHive tries to load these by default) config_dir = PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH\",\n \"except Exception: log.error('[✘] Unable to recreate configuration files.') def safe_copy(self, src: str, dst:\",\n \"'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22) } return result def proxy_config_to_dict(path: str)\",\n \"TITLE = config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX =\",\n \"['foo', 'bar'] Will return: ['foo', 'bar'] ''' import ast try: raw_arguments = config.get('auth',\",\n \"not found in config directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini')\",\n \"\\\\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•] Detected missing default config file(s), recreating...') self.recreate_default_configuration_files()\",\n \"config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): ''' Displays all uppercase class\",\n \"'backend', fallback='gunicorn') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=5000) WORKERS\",\n \"'port', fallback=22) } return result def proxy_config_to_dict(path: str) -> Optional[Dict]: # type: ignore\",\n \"DB: section = 'database' default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) -> str: #\",\n \"os import logging log = logging.getLogger(__name__) class CONFIG_FILES: # Where to copy files\",\n \"datetime import timedelta section = 'auth' def config_get_parsed(option: str, fallback: Any) -> List[str]:\",\n \"str(config_dir / 'mailbot_config.ini') # Where to get file templates from # (Clone file\",\n \"from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config\",\n \"'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER =\",\n \"= config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action',\",\n \"rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘] Unable\",\n \"IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml') with\",\n \"value for option from string to a valid python list. Fallback value is\",\n \"log.info('[•] All configs already exist, skipping...') def recreate_default_configuration_files(self) -> None: try: # 1.\",\n \"Fallback value is returned when anything goes wrong (e.g. option or value not\",\n \"PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH =\",\n \"= cleandoc( ''' {env} - undeclared environment variable! Try this: `export {env}=\\\"...\\\"` ''').format(env=name).split('\\\\n')\",\n \"/ 'migrations') class ConfigInitilizer: '''Makes sure that all default config files exist''' def\",\n \"''' Displays all uppercase class atributes (class must be defined first) Example usage:\",\n \"'url_prefix', fallback='api') SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import\",\n \"exist''' def __init__(self): # 1. Check if all config files exist all_exist =\",\n \"'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path, 'r') as\",\n \"arguments: option='some_option', fallback=None [some_section] some_option = ['foo', 'bar'] Will return: ['foo', 'bar'] '''\",\n \"class ConfigLoader: @staticmethod def load(path, displayed_title=''): import configparser config = configparser.ConfigParser(strict=False) full_path =\",\n \"= 'protection_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY\",\n \"str) -> Dict: # type: ignore '''Parses sections containing hostnames''' hosts_config = ConfigLoader.load(path,\",\n \"skipping...') def recreate_default_configuration_files(self) -> None: try: # 1. Create directory for stroing config\",\n \"fallback=False): return { 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22)\",\n \"'''Parses [proxy_tunneling] section''' config = ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling' # Check if\",\n \"= str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini') # Where to get\",\n \"self.recreate_default_configuration_files() log.info('[•] All configs already exist, skipping...') def recreate_default_configuration_files(self) -> None: try: #\",\n \"class PROTECTION_SERVICE: section = 'protection_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section,\",\n \"LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section\",\n \"'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)), 'JWT_REFRESH_TOKEN_EXPIRES': timedelta(days=config.getint(section, 'jwt_refresh_token_expires_days', fallback=1)),\",\n \"''' import ast try: raw_arguments = config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments\",\n \"PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•] Detected missing\",\n \"dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config files permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH,\",\n \"'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1) KEY_FILE\",\n \"else: return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section =\",\n \"= 'web_app.server' BACKEND = config.get(section, 'backend', fallback='gunicorn') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT\",\n \"ignore '''Parses [proxy_tunneling] section''' config = ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling' # Check\",\n \"'admin_email', fallback=None) section = 'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section,\",\n \"'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) -> Dict: # type: ignore '''Parses sections containing\",\n \"section = 'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0)\",\n \"default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) -> str: # type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser())\",\n \"Reading {} config from {}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration file not found ({})'.format(full_path))\",\n \"= {}'.format(key, value)) def check_env_var(name: str): '''Makes sure that env variable is declared'''\",\n \"Clone templates safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) #\",\n \"mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path =\",\n \"valid python list. Fallback value is returned when anything goes wrong (e.g. option\",\n \"is present and if yes, check if tunneling is enabled if config.has_section(section) and\",\n \"usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in cls.__dict__.items(): if key.isupper(): print('{} =\",\n \"def display_config(cls): ''' Displays all uppercase class atributes (class must be defined first)\",\n \"LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED = config.getboolean(section,\",\n \"URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix', fallback='api') SPEC_FILE = config.get(section,\",\n \"tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini')\",\n \"type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' #\",\n \"default config files exist''' def __init__(self): # 1. Check if all config files\",\n \"All configs already exist, skipping...') def recreate_default_configuration_files(self) -> None: try: # 1. Create\",\n \"type: ignore '''Parses sections containing hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts') result = {}\",\n \"= ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing [auth] config section failed for\",\n \"files # (TensorHive tries to load these by default) config_dir = PosixPath.home() /\",\n \"config.py'.format(displayed_title)) return config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): ''' Displays all\",\n \"'api.server' BACKEND = config.get(section, 'backend', fallback='gevent') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT =\",\n \"fallback: Any) -> List[str]: # type: ignore ''' Parses value for option from\",\n \"directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir /\",\n \"= config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) -> Dict: # type: ignore '''Parses\",\n \"/ 'controllers/responses.yml') with open(respones_file_path, 'r') as file: RESPONSES = yaml.safe_load(file) class APP_SERVER: section\",\n \"(e.g. option or value not present) Example .ini file, function called with arguments:\",\n \"file, function called with arguments: option='some_option', fallback=None [some_section] some_option = ['foo', 'bar'] Will\",\n \"str: # type: ignore return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL =\",\n \"BACKEND = config.get(section, 'backend', fallback='gevent') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section,\",\n \"'proxy_port', fallback=22) } else: return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class\",\n \"SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587) section = 'template/intruder'\",\n \"= str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir /\",\n \"defined first) Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in cls.__dict__.items(): if\",\n \"= '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) -> str: # type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI\",\n \"fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION =\",\n \"is returned when anything goes wrong (e.g. option or value not present) Example\",\n \"config.get(section, 'backend', fallback='gunicorn') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=5000)\",\n \"MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir\",\n \"from # (Clone file when it's not found in config directory) tensorhive_package_dir =\",\n \"USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def full_path(path: str) -> str: #\",\n \"'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None) section\",\n \"means that it won't override existing configuration''' if PosixPath(dst).exists(): log.info('Skipping, file already exists:\",\n \"fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT:\",\n \"full_path(path: str) -> str: # type: ignore return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled',\",\n \"= 'monitoring_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL\",\n \"config_dir = PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir\",\n \"as file: RESPONSES = yaml.safe_load(file) class APP_SERVER: section = 'web_app.server' BACKEND = config.get(section,\",\n \"= str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path, 'r') as file: RESPONSES = yaml.safe_load(file) class\",\n \"wrong (e.g. option or value not present) Example .ini file, function called with\",\n \"type: ignore return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval',\",\n \"\\\\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•] Detected missing default config\",\n \"'''Parses sections containing hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts') result = {} for section\",\n \"= mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin',\",\n \"'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' # Use in-memory (before:\",\n \"ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): ''' Displays all uppercase class atributes\",\n \"config.get(section, 'url_prefix', fallback='api') SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers')\",\n \"= config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \\\"schedule_queued_jobs_when_free_mins\\\", fallback=30) class AUTH: from datetime\",\n \"yaml.safe_load(file) class APP_SERVER: section = 'web_app.server' BACKEND = config.get(section, 'backend', fallback='gunicorn') HOST =\",\n \"config.read(str(full_path)): log.info('[•] Reading {} config from {}'.format(displayed_title, full_path)) else: log.warning('[✘] Configuration file not\",\n \"UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section,\",\n \"'password', fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587) section\",\n \"INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section = 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE =\",\n \"fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)), 'JWT_REFRESH_TOKEN_EXPIRES': timedelta(days=config.getint(section, 'jwt_refresh_token_expires_days',\",\n \"fallback=22) } else: return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB:\",\n \"'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES':\",\n \"ignore '''Parses sections containing hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts') result = {} for\",\n \"is enabled if config.has_section(section) and config.getboolean(section, 'enabled', fallback=False): return { 'proxy_host': config.get(section, 'proxy_host'),\",\n \"= config.get(section, 'loglevel', fallback='warning') class API_SERVER: section = 'api.server' BACKEND = config.get(section, 'backend',\",\n \"PROTECTION_SERVICE: section = 'protection_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval',\",\n \"fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS =\",\n \"'general' INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER =\",\n \"ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations') class ConfigInitilizer: '''Makes\",\n \"result def proxy_config_to_dict(path: str) -> Optional[Dict]: # type: ignore '''Parses [proxy_tunneling] section''' config\",\n \"config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE: section = 'monitoring_service' ENABLED = config.getboolean(section, 'enabled', fallback=True)\",\n \"(before: sqlite:///test_database.sqlite) class API: section = 'api' TITLE = config.get(section, 'title', fallback='TensorHive API')\",\n \"= mailbot_config.get(section, 'html_body') section = 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section,\",\n \"import Dict, Optional, Any, List from inspect import cleandoc import shutil import tensorhive\",\n \"= 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section\",\n \"= config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT: mailbot_config =\",\n \"= 'database' default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) -> str: # type: ignore\",\n \"not all_exist: log.warning('[•] Detected missing default config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All configs\",\n \"{}'.format(src, dst)) class ConfigLoader: @staticmethod def load(path, displayed_title=''): import configparser config = configparser.ConfigParser(strict=False)\",\n \"'backend', fallback='gevent') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=1111) DEBUG\",\n \"return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' # Use in-memory\",\n \"configs already exist, skipping...') def recreate_default_configuration_files(self) -> None: try: # 1. Create directory\",\n \"cls.__dict__.items(): if key.isupper(): print('{} = {}'.format(key, value)) def check_env_var(name: str): '''Makes sure that\",\n \"{} settings from config.py'.format(displayed_title)) return config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls):\",\n \"1. Create directory for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone templates\",\n \"'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT =\",\n \"config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22) } else: return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE)\",\n \"continue hostname = section result[hostname] = { 'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port',\",\n \"PORT = config.getint(section, 'port', fallback=1111) DEBUG = config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE: section\",\n \"PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•] Detected missing default config file(s),\",\n \"# 2. Clone templates safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH,\",\n \"mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general' INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL\",\n \"fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL =\",\n \"os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘] Unable to recreate configuration files.') def\",\n \"option) parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing [auth] config section\",\n \"if section is present and if yes, check if tunneling is enabled if\",\n \"/ 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations') class\",\n \"result[hostname] = { 'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22) } return result\",\n \"= ConfigLoader.load(path, displayed_title='hosts') result = {} for section in hosts_config.sections(): # We want\",\n \"option from string to a valid python list. Fallback value is returned when\",\n \"= config.getint(section, 'port', fallback=5000) WORKERS = config.getint(section, 'workers', fallback=4) LOG_LEVEL = config.get(section, 'loglevel',\",\n \"= 'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER\",\n \"Unable to recreate configuration files.') def safe_copy(self, src: str, dst: str) -> None:\",\n \"def load(path, displayed_title=''): import configparser config = configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if config.read(str(full_path)):\",\n \"'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini') # Where\",\n \"HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir\",\n \"tries to load these by default) config_dir = PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH =\",\n \"`export {env}=\\\"...\\\"` ''').format(env=name).split('\\\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH: section = 'ssh' HOSTS_CONFIG_FILE = config.get(section,\",\n \"SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' # Use in-memory (before: sqlite:///test_database.sqlite)\",\n \"fallback=2.0) class PROTECTION_SERVICE: section = 'protection_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL =\",\n \"= config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general'\",\n \"= config.get(section, 'backend', fallback='gunicorn') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port',\",\n \"displayed_title='mailbot') section = 'general' INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval',\",\n \"fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix', fallback='api') SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION =\",\n \"'html_body') section = 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class\",\n \"# type: ignore return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section,\",\n \"ignore return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0)\",\n \"import PosixPath import configparser from typing import Dict, Optional, Any, List from inspect\",\n \"'monitoring_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL =\",\n \"Any) -> List[str]: # type: ignore ''' Parses value for option from string\",\n \"return fallback FLASK_JWT = { 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True),\",\n \"in config directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH =\",\n \"file: RESPONSES = yaml.safe_load(file) class APP_SERVER: section = 'web_app.server' BACKEND = config.get(section, 'backend',\",\n \"config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22) } else: return None\",\n \"section = 'monitoring_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True)\",\n \"files permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception:\",\n \"= configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading {} config from {}'.format(displayed_title,\",\n \"fallback=587) section = 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section\",\n \"'update_interval', fallback=2.0) class PROTECTION_SERVICE: section = 'protection_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL\",\n \"'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini') # Where to get file templates from\",\n \"default_path = '~/.config/TensorHive/logs/' def full_path(path: str) -> str: # type: ignore return str(PosixPath(path).expanduser())\",\n \"files exist''' def __init__(self): # 1. Check if all config files exist all_exist\",\n \"config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing [auth] config\",\n \"PORT = config.getint(section, 'port', fallback=5000) WORKERS = config.getint(section, 'workers', fallback=4) LOG_LEVEL = config.get(section,\",\n \"fallback=2) class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL =\",\n \"2. Clone templates safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH)\",\n \"environment variable! Try this: `export {env}=\\\"...\\\"` ''').format(env=name).split('\\\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH: section =\",\n \"default config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All configs already exist, skipping...') def recreate_default_configuration_files(self)\",\n \"log.error('[✘] Unable to recreate configuration files.') def safe_copy(self, src: str, dst: str) ->\",\n \"'controllers/responses.yml') with open(respones_file_path, 'r') as file: RESPONSES = yaml.safe_load(file) class APP_SERVER: section =\",\n \"SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER = mailbot_config.get(section,\",\n \"= str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir /\",\n \"dst: str) -> None: '''Safe means that it won't override existing configuration''' if\",\n \"import configparser from typing import Dict, Optional, Any, List from inspect import cleandoc\",\n \"self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config files permission rw_owner_only = 0o600\",\n \"'proxy_tunneling' # Check if section is present and if yes, check if tunneling\",\n \"already exist, skipping...') def recreate_default_configuration_files(self) -> None: try: # 1. Create directory for\",\n \"ignore ''' Parses value for option from string to a valid python list.\",\n \"= '~/.config/TensorHive/logs/' def full_path(path: str) -> str: # type: ignore return str(PosixPath(path).expanduser()) ENABLED\",\n \"config_get_parsed(option: str, fallback: Any) -> List[str]: # type: ignore ''' Parses value for\",\n \"fallback=1111) DEBUG = config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE: section = 'monitoring_service' ENABLED =\",\n \"section in hosts_config.sections(): # We want to parse only sections which describe target\",\n \"ValueError): log.warning('Parsing [auth] config section failed for option \\\"{}\\\", using fallback value: {}'.format(\",\n \"MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section,\",\n \"fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE:\",\n \"class CONFIG_FILES: # Where to copy files # (TensorHive tries to load these\",\n \"'migrations') class ConfigInitilizer: '''Makes sure that all default config files exist''' def __init__(self):\",\n \"fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES =\",\n \"'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None) section = 'smtp' SMTP_LOGIN = mailbot_config.get(section,\",\n \"value in cls.__dict__.items(): if key.isupper(): print('{} = {}'.format(key, value)) def check_env_var(name: str): '''Makes\",\n \"SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587) section = 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE\",\n \"Displays all uppercase class atributes (class must be defined first) Example usage: display_config(API_SERVER)\",\n \"''').format(env=name).split('\\\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH: section = 'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH)\",\n \"hosts_config = ConfigLoader.load(path, displayed_title='hosts') result = {} for section in hosts_config.sections(): # We\",\n \"def full_path(path: str) -> str: # type: ignore return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section,\",\n \"found ({})'.format(full_path)) log.info('Using default {} settings from config.py'.format(displayed_title)) return config ConfigInitilizer() config =\",\n \"value)) def check_env_var(name: str): '''Makes sure that env variable is declared''' if not\",\n \"= config.getint(section, \\\"schedule_queued_jobs_when_free_mins\\\", fallback=30) class AUTH: from datetime import timedelta section = 'auth'\",\n \"= ['foo', 'bar'] Will return: ['foo', 'bar'] ''' import ast try: raw_arguments =\",\n \"-> Optional[Dict]: # type: ignore '''Parses [proxy_tunneling] section''' config = ConfigLoader.load(path, displayed_title='proxy') section\",\n \"list. Fallback value is returned when anything goes wrong (e.g. option or value\",\n \"'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=5000) WORKERS = config.getint(section, 'workers', fallback=4) LOG_LEVEL\",\n \"all default config files exist''' def __init__(self): # 1. Check if all config\",\n \"section = 'proxy_tunneling' # Check if section is present and if yes, check\",\n \"shutil import tensorhive import os import logging log = logging.getLogger(__name__) class CONFIG_FILES: #\",\n \"that all default config files exist''' def __init__(self): # 1. Check if all\",\n \"type: ignore '''Parses [proxy_tunneling] section''' config = ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling' #\",\n \"config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=1111) DEBUG = config.getboolean(section, 'debug', fallback=False)\",\n \"'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \\\"schedule_queued_jobs_when_free_mins\\\", fallback=30) class\",\n \"Try this: `export {env}=\\\"...\\\"` ''').format(env=name).split('\\\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH: section = 'ssh' HOSTS_CONFIG_FILE\",\n \"'html_body') class USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def full_path(path: str) ->\",\n \"goes wrong (e.g. option or value not present) Example .ini file, function called\",\n \"(configparser.Error, ValueError): log.warning('Parsing [auth] config section failed for option \\\"{}\\\", using fallback value:\",\n \"return result def proxy_config_to_dict(path: str) -> Optional[Dict]: # type: ignore '''Parses [proxy_tunneling] section'''\",\n \"section''' config = ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling' # Check if section is\",\n \"= config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval',\",\n \"str) -> Optional[Dict]: # type: ignore '''Parses [proxy_tunneling] section''' config = ConfigLoader.load(path, displayed_title='proxy')\",\n \"= 'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER\",\n \"config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): ''' Displays all uppercase class atributes (class\",\n \"log.warning(msg[0]) log.warning(msg[1]) class SSH: section = 'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP\",\n \"fallback value: {}'.format( option, fallback)) return fallback FLASK_JWT = { 'SECRET_KEY': config.get(section, 'secrect_key',\",\n \"respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path, 'r') as file: RESPONSES = yaml.safe_load(file)\",\n \"section = 'protection_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0)\",\n \"'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL\",\n \"'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587) section = 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section,\",\n \"ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' # Use\",\n \"'~/.config/TensorHive/logs/' def full_path(path: str) -> str: # type: ignore return str(PosixPath(path).expanduser()) ENABLED =\",\n \"-> str: # type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI\",\n \"import timedelta section = 'auth' def config_get_parsed(option: str, fallback: Any) -> List[str]: #\",\n \"src: str, dst: str) -> None: '''Safe means that it won't override existing\",\n \"return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section = 'database'\",\n \"str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations') class ConfigInitilizer: '''Makes sure that\",\n \"fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) -> Dict: # type: ignore '''Parses sections containing hostnames'''\",\n \"get file templates from # (Clone file when it's not found in config\",\n \"option or value not present) Example .ini file, function called with arguments: option='some_option',\",\n \"in hosts_config.sections(): # We want to parse only sections which describe target hosts\",\n \"SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path\",\n \"section = 'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def full_path(path: str) -> str: # type:\",\n \"type: ignore ''' Parses value for option from string to a valid python\",\n \"config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path))\",\n \"safe_copy(self, src: str, dst: str) -> None: '''Safe means that it won't override\",\n \"sections which describe target hosts if section == 'proxy_tunneling': continue hostname = section\",\n \"config section failed for option \\\"{}\\\", using fallback value: {}'.format( option, fallback)) return\",\n \"fallback=True) TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1) KEY_FILE =\",\n \"hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section = 'database' default_path = '~/.config/TensorHive/database.sqlite' def\",\n \"'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) LOG_DIR = full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION\",\n \"Use in-memory (before: sqlite:///test_database.sqlite) class API: section = 'api' TITLE = config.get(section, 'title',\",\n \"MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'main_config.ini') HOSTS_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir\",\n \"only sections which describe target hosts if section == 'proxy_tunneling': continue hostname =\",\n \"PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section = 'database' default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path:\",\n \"= PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir /\",\n \"'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \\\"schedule_queued_jobs_when_free_mins\\\", fallback=30) class AUTH: from datetime import timedelta\",\n \"from inspect import cleandoc import shutil import tensorhive import os import logging log\",\n \"config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1) KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key')\",\n \"# (Clone file when it's not found in config directory) tensorhive_package_dir = PosixPath(__file__).parent\",\n \"load(path, displayed_title=''): import configparser config = configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•]\",\n \"} return result def proxy_config_to_dict(path: str) -> Optional[Dict]: # type: ignore '''Parses [proxy_tunneling]\",\n \"open(respones_file_path, 'r') as file: RESPONSES = yaml.safe_load(file) class APP_SERVER: section = 'web_app.server' BACKEND\",\n \"not os.getenv(name): msg = cleandoc( ''' {env} - undeclared environment variable! Try this:\",\n \"it won't override existing configuration''' if PosixPath(dst).exists(): log.info('Skipping, file already exists: {}'.format(dst)) else:\",\n \"already exists: {}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied {} to {}'.format(src, dst)) class ConfigLoader:\",\n \"import os import logging log = logging.getLogger(__name__) class CONFIG_FILES: # Where to copy\",\n \"in-memory (before: sqlite:///test_database.sqlite) class API: section = 'api' TITLE = config.get(section, 'title', fallback='TensorHive\",\n \"'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix', fallback='api') SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION\",\n \"Where to get file templates from # (Clone file when it's not found\",\n \"Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in cls.__dict__.items(): if key.isupper(): print('{}\",\n \"= 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section = 'template/admin'\",\n \"cleandoc import shutil import tensorhive import os import logging log = logging.getLogger(__name__) class\",\n \"config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix',\",\n \"section = 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE:\",\n \"print('{} = {}'.format(key, value)) def check_env_var(name: str): '''Makes sure that env variable is\",\n \"{env}=\\\"...\\\"` ''').format(env=name).split('\\\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH: section = 'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file',\",\n \"hosts_config.getint(hostname, 'port', fallback=22) } return result def proxy_config_to_dict(path: str) -> Optional[Dict]: # type:\",\n \"or value not present) Example .ini file, function called with arguments: option='some_option', fallback=None\",\n \"class ConfigInitilizer: '''Makes sure that all default config files exist''' def __init__(self): #\",\n \"{}'.format(key, value)) def check_env_var(name: str): '''Makes sure that env variable is declared''' if\",\n \"fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None) section = 'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email',\",\n \"cleandoc( ''' {env} - undeclared environment variable! Try this: `export {env}=\\\"...\\\"` ''').format(env=name).split('\\\\n') log.warning(msg[0])\",\n \"/ 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations') class ConfigInitilizer: '''Makes sure that all\",\n \"section = 'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True)\",\n \"= section result[hostname] = { 'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22) }\",\n \"class API_SERVER: section = 'api.server' BACKEND = config.get(section, 'backend', fallback='gevent') HOST = config.get(section,\",\n \"function called with arguments: option='some_option', fallback=None [some_section] some_option = ['foo', 'bar'] Will return:\",\n \"0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘] Unable to recreate\",\n \"some_option = ['foo', 'bar'] Will return: ['foo', 'bar'] ''' import ast try: raw_arguments\",\n \"return config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): ''' Displays all uppercase\",\n \"= config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing [auth]\",\n \"Dict, Optional, Any, List from inspect import cleandoc import shutil import tensorhive import\",\n \"fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) class PROTECTION_SERVICE:\",\n \"'smtp_port', fallback=587) section = 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body')\",\n \"option \\\"{}\\\", using fallback value: {}'.format( option, fallback)) return fallback FLASK_JWT = {\",\n \"logging.getLogger(__name__) class CONFIG_FILES: # Where to copy files # (TensorHive tries to load\",\n \"- undeclared environment variable! Try this: `export {env}=\\\"...\\\"` ''').format(env=name).split('\\\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH:\",\n \"= 'auth' def config_get_parsed(option: str, fallback: Any) -> List[str]: # type: ignore '''\",\n \"{}'.format( option, fallback)) return fallback FLASK_JWT = { 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED':\",\n \"proxy_config_to_dict(path: str) -> Optional[Dict]: # type: ignore '''Parses [proxy_tunneling] section''' config = ConfigLoader.load(path,\",\n \"Will return: ['foo', 'bar'] ''' import ast try: raw_arguments = config.get('auth', option) parsed_arguments\",\n \"= { 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access',\",\n \"/ 'main_config.ini') HOSTS_CONFIG_PATH = str(config_dir / 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini') #\",\n \"'''Makes sure that all default config files exist''' def __init__(self): # 1. Check\",\n \"= ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling' # Check if section is present and\",\n \"for option from string to a valid python list. Fallback value is returned\",\n \"MONITORING_SERVICE: section = 'monitoring_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor',\",\n \"= { 'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22) } return result def\",\n \"INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section = 'template/admin' ADMIN_SUBJECT =\",\n \"Create directory for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone templates safely\",\n \"to {}'.format(src, dst)) class ConfigLoader: @staticmethod def load(path, displayed_title=''): import configparser config =\",\n \"'database' default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) -> str: # type: ignore return\",\n \"# Where to copy files # (TensorHive tries to load these by default)\",\n \"be defined first) Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value in cls.__dict__.items():\",\n \"ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section = 'usage_logging_service'\",\n \"full_path)) else: log.warning('[✘] Configuration file not found ({})'.format(full_path)) log.info('Using default {} settings from\",\n \"PosixPath(dst).exists(): log.info('Skipping, file already exists: {}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied {} to {}'.format(src,\",\n \"section = 'web_app.server' BACKEND = config.get(section, 'backend', fallback='gunicorn') HOST = config.get(section, 'host', fallback='0.0.0.0')\",\n \"files.') def safe_copy(self, src: str, dst: str) -> None: '''Safe means that it\",\n \"str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path, 'r') as file: RESPONSES = yaml.safe_load(file) class APP_SERVER:\",\n \"that env variable is declared''' if not os.getenv(name): msg = cleandoc( ''' {env}\",\n \"'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES\",\n \"full_path = PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading {} config from {}'.format(displayed_title, full_path)) else:\",\n \"containing hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts') result = {} for section in hosts_config.sections():\",\n \"import tensorhive import os import logging log = logging.getLogger(__name__) class CONFIG_FILES: # Where\",\n \"{}'.format(dst)) else: shutil.copy(src, dst) log.info('Copied {} to {}'.format(src, dst)) class ConfigLoader: @staticmethod def\",\n \"= mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section = 'usage_logging_service' default_path = '~/.config/TensorHive/logs/' def full_path(path:\",\n \"= config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins',\",\n \"fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)),\",\n \"We want to parse only sections which describe target hosts if section ==\",\n \"enabled if config.has_section(section) and config.getboolean(section, 'enabled', fallback=False): return { 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user':\",\n \"class MONITORING_SERVICE: section = 'monitoring_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section,\",\n \"config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled', fallback=True)\",\n \"'api' TITLE = config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX\",\n \"'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)), 'JWT_REFRESH_TOKEN_EXPIRES': timedelta(days=config.getint(section, 'jwt_refresh_token_expires_days', fallback=1)), 'JWT_TOKEN_LOCATION':\",\n \"config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone templates safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH,\",\n \"hosts_config.sections(): # We want to parse only sections which describe target hosts if\",\n \"rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘] Unable to recreate configuration files.') def safe_copy(self,\",\n \"fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section\",\n \"class API: section = 'api' TITLE = config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME =\",\n \"ENABLED = config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section,\",\n \"config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section,\",\n \"dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config files permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH,\",\n \"import logging log = logging.getLogger(__name__) class CONFIG_FILES: # Where to copy files #\",\n \"sure that env variable is declared''' if not os.getenv(name): msg = cleandoc( '''\",\n \"fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)), 'JWT_REFRESH_TOKEN_EXPIRES': timedelta(days=config.getint(section, 'jwt_refresh_token_expires_days', fallback=1)), 'JWT_TOKEN_LOCATION': config_get_parsed('jwt_token_location', fallback=['headers']) }\",\n \"Optional, Any, List from inspect import cleandoc import shutil import tensorhive import os\",\n \"hostname = section result[hostname] = { 'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22)\",\n \"MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH, displayed_title='mailbot') section = 'general' INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0)\",\n \"except (configparser.Error, ValueError): log.warning('Parsing [auth] config section failed for option \\\"{}\\\", using fallback\",\n \"'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS\",\n \"API: section = 'api' TITLE = config.get(section, 'title', fallback='TensorHive API') URL_HOSTNAME = config.get(section,\",\n \"PosixPath import configparser from typing import Dict, Optional, Any, List from inspect import\",\n \"str: # type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI =\",\n \"config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1)\",\n \"# type: ignore ''' Parses value for option from string to a valid\",\n \"target hosts if section == 'proxy_tunneling': continue hostname = section result[hostname] = {\",\n \"files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone templates safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH)\",\n \"default {} settings from config.py'.format(displayed_title)) return config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def\",\n \"and \\\\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•] Detected missing default config file(s), recreating...')\",\n \"Parses value for option from string to a valid python list. Fallback value\",\n \"Dict: # type: ignore '''Parses sections containing hostnames''' hosts_config = ConfigLoader.load(path, displayed_title='hosts') result\",\n \"({})'.format(full_path)) log.info('Using default {} settings from config.py'.format(displayed_title)) return config ConfigInitilizer() config = ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH,\",\n \"and if yes, check if tunneling is enabled if config.has_section(section) and config.getboolean(section, 'enabled',\",\n \"section = 'database' default_path = '~/.config/TensorHive/database.sqlite' def uri_for_path(path: str) -> str: # type:\",\n \"fallback=4) LOG_LEVEL = config.get(section, 'loglevel', fallback='warning') class API_SERVER: section = 'api.server' BACKEND =\",\n \"= mailbot_config.getint(section, 'smtp_port', fallback=587) section = 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE =\",\n \"TEST_ON_STARTUP = config.getboolean(section, 'test_on_startup', fallback=True) TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES = config.getint(section,\",\n \"and config.getboolean(section, 'enabled', fallback=False): return { 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port':\",\n \"'port': hosts_config.getint(hostname, 'port', fallback=22) } return result def proxy_config_to_dict(path: str) -> Optional[Dict]: #\",\n \"= mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server',\",\n \"try: raw_arguments = config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments except (configparser.Error, ValueError):\",\n \"'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section, 'jwt_blacklist_enabled', fallback=True), 'JWT_BLACKLIST_TOKEN_CHECKS': config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors',\",\n \"# Where to get file templates from # (Clone file when it's not\",\n \"config = ConfigLoader.load(path, displayed_title='proxy') section = 'proxy_tunneling' # Check if section is present\",\n \"API_SERVER: section = 'api.server' BACKEND = config.get(section, 'backend', fallback='gevent') HOST = config.get(section, 'host',\",\n \"= 'proxy_tunneling' # Check if section is present and if yes, check if\",\n \"fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \\\"schedule_queued_jobs_when_free_mins\\\", fallback=30) class AUTH: from datetime import timedelta section\",\n \"all_exist: log.warning('[•] Detected missing default config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All configs already\",\n \"import configparser config = configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading {}\",\n \"return parsed_arguments except (configparser.Error, ValueError): log.warning('Parsing [auth] config section failed for option \\\"{}\\\",\",\n \"= config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email',\",\n \"key.isupper(): print('{} = {}'.format(key, value)) def check_env_var(name: str): '''Makes sure that env variable\",\n \"3. Change config files permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH,\",\n \"= yaml.safe_load(file) class APP_SERVER: section = 'web_app.server' BACKEND = config.get(section, 'backend', fallback='gunicorn') HOST\",\n \"ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section,\",\n \"'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section = 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE\",\n \"'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN\",\n \"TIMEOUT = config.getfloat(section, 'timeout', fallback=10.0) NUM_RETRIES = config.getint(section, 'number_of_retries', fallback=1) KEY_FILE = config.get(section,\",\n \"if not os.getenv(name): msg = cleandoc( ''' {env} - undeclared environment variable! Try\",\n \"config.getint(section, 'proxy_port', fallback=22) } else: return None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE)\",\n \"fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \\\"schedule_queued_jobs_when_free_mins\\\", fallback=30) class AUTH:\",\n \"'enabled', fallback=True) ENABLE_GPU_MONITOR = config.getboolean(section, 'enable_gpu_monitor', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) class\",\n \"os.getenv(name): msg = cleandoc( ''' {env} - undeclared environment variable! Try this: `export\",\n \"'proxy_tunneling': continue hostname = section result[hostname] = { 'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname,\",\n \"HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=1111) DEBUG = config.getboolean(section,\",\n \"section = 'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None)\",\n \"all config files exist all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists()\",\n \"config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=5000) WORKERS = config.getint(section, 'workers', fallback=4)\",\n \"= config.getboolean(section, 'debug', fallback=False) class MONITORING_SERVICE: section = 'monitoring_service' ENABLED = config.getboolean(section, 'enabled',\",\n \"config_get_parsed('jwt_blacklist_token_checks', fallback=['access', 'refresh']), 'BUNDLE_ERRORS': config.getboolean(section, 'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)), 'JWT_REFRESH_TOKEN_EXPIRES': timedelta(days=config.getint(section,\",\n \"= PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•] Detected\",\n \"sure that all default config files exist''' def __init__(self): # 1. Check if\",\n \"fallback=None) section = 'smtp' SMTP_LOGIN = mailbot_config.get(section, 'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password',\",\n \"for option \\\"{}\\\", using fallback value: {}'.format( option, fallback)) return fallback FLASK_JWT =\",\n \"directory for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone templates safely from\",\n \"import ast try: raw_arguments = config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments) return parsed_arguments except\",\n \"parse only sections which describe target hosts if section == 'proxy_tunneling': continue hostname\",\n \"option, fallback)) return fallback FLASK_JWT = { 'SECRET_KEY': config.get(section, 'secrect_key', fallback='jwt-some-secret'), 'JWT_BLACKLIST_ENABLED': config.getboolean(section,\",\n \"declared''' if not os.getenv(name): msg = cleandoc( ''' {env} - undeclared environment variable!\",\n \"Detected missing default config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All configs already exist, skipping...')\",\n \"self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config files permission rw_owner_only\",\n \"= full_path(config.get(section, 'log_dir', fallback=default_path)) LOG_CLEANUP_ACTION = config.getint(section, 'log_cleanup_action', fallback=2) class JOB_SCHEDULING_SERVICE: section =\",\n \"displayed_title='main') def display_config(cls): ''' Displays all uppercase class atributes (class must be defined\",\n \"atributes (class must be defined first) Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key,\",\n \"= config.get(section, 'backend', fallback='gevent') HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port',\",\n \"NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False) ADMIN_EMAIL = mailbot_config.get(section, 'admin_email', fallback=None) section = 'smtp'\",\n \"# 3. Change config files permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only)\",\n \"result = {} for section in hosts_config.sections(): # We want to parse only\",\n \"str(tensorhive_package_dir / 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini')\",\n \"failed for option \\\"{}\\\", using fallback value: {}'.format( option, fallback)) return fallback FLASK_JWT\",\n \"'debug', fallback=False) class MONITORING_SERVICE: section = 'monitoring_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR\",\n \"tunneling is enabled if config.has_section(section) and config.getboolean(section, 'enabled', fallback=False): return { 'proxy_host': config.get(section,\",\n \"= uri_for_path(config.get(section, 'path', fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' # Use in-memory (before: sqlite:///test_database.sqlite) class\",\n \"exist_ok=True) # 2. Clone templates safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH)\",\n \"(class must be defined first) Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__)) for key, value\",\n \"MAILBOT_TEMPLATE_CONFIG_PATH = str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir\",\n \"self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3. Change config files permission rw_owner_only = 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only)\",\n \"class SSH: section = 'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP = config.getboolean(section,\",\n \"= {} for section in hosts_config.sections(): # We want to parse only sections\",\n \"'port', fallback=5000) WORKERS = config.getint(section, 'workers', fallback=4) LOG_LEVEL = config.get(section, 'loglevel', fallback='warning') class\",\n \"HOST = config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=5000) WORKERS = config.getint(section,\",\n \"str) -> str: # type: ignore return str(PosixPath(path).expanduser()) ENABLED = config.getboolean(section, 'enabled', fallback=True)\",\n \"that it won't override existing configuration''' if PosixPath(dst).exists(): log.info('Skipping, file already exists: {}'.format(dst))\",\n \"section is present and if yes, check if tunneling is enabled if config.has_section(section)\",\n \"config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0) SCHEDULE_QUEUED_JOBS_WHEN_FREE_MINS = config.getint(section, \\\"schedule_queued_jobs_when_free_mins\\\", fallback=30) class AUTH: from datetime import\",\n \"value is returned when anything goes wrong (e.g. option or value not present)\",\n \"LOG_LEVEL = config.get(section, 'loglevel', fallback='warning') class API_SERVER: section = 'api.server' BACKEND = config.get(section,\",\n \"= mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder',\",\n \"-> None: try: # 1. Create directory for stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True)\",\n \"'title', fallback='TensorHive API') URL_HOSTNAME = config.get(section, 'url_hostname', fallback='0.0.0.0') URL_PREFIX = config.get(section, 'url_prefix', fallback='api')\",\n \"def hosts_config_to_dict(path: str) -> Dict: # type: ignore '''Parses sections containing hostnames''' hosts_config\",\n \"with open(respones_file_path, 'r') as file: RESPONSES = yaml.safe_load(file) class APP_SERVER: section = 'web_app.server'\",\n \"in cls.__dict__.items(): if key.isupper(): print('{} = {}'.format(key, value)) def check_env_var(name: str): '''Makes sure\",\n \"with arguments: option='some_option', fallback=None [some_section] some_option = ['foo', 'bar'] Will return: ['foo', 'bar']\",\n \"= 0o600 os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘] Unable to\",\n \"config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False) class MAILBOT: mailbot_config = ConfigLoader.load(CONFIG_FILES.MAILBOT_CONFIG_PATH,\",\n \"= config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path =\",\n \"'bundle_errors', fallback=True), 'JWT_ACCESS_TOKEN_EXPIRES': timedelta(minutes=config.getint(section, 'jwt_access_token_expires_minutes', fallback=1)), 'JWT_REFRESH_TOKEN_EXPIRES': timedelta(days=config.getint(section, 'jwt_refresh_token_expires_days', fallback=1)), 'JWT_TOKEN_LOCATION': config_get_parsed('jwt_token_location', fallback=['headers'])\",\n \"return { 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22) }\",\n \"configuration files.') def safe_copy(self, src: str, dst: str) -> None: '''Safe means that\",\n \"str) -> str: # type: ignore return 'sqlite:///{}'.format(PosixPath(path).expanduser()) SQLALCHEMY_DATABASE_URI = uri_for_path(config.get(section, 'path', fallback=default_path))\",\n \"fallback=None [some_section] some_option = ['foo', 'bar'] Will return: ['foo', 'bar'] ''' import ast\",\n \"= mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section = 'template/admin' ADMIN_SUBJECT = mailbot_config.get(section,\",\n \"templates safely from `tensorhive` package self.safe_copy(src=CONFIG_FILES.MAIN_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.MAIN_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.HOSTS_CONFIG_TEMPLATE_PATH, dst=CONFIG_FILES.HOSTS_CONFIG_PATH) self.safe_copy(src=CONFIG_FILES.MAILBOT_TEMPLATE_CONFIG_PATH, dst=CONFIG_FILES.MAILBOT_CONFIG_PATH) # 3.\",\n \"hosts if section == 'proxy_tunneling': continue hostname = section result[hostname] = { 'user':\",\n \"[some_section] some_option = ['foo', 'bar'] Will return: ['foo', 'bar'] ''' import ast try:\",\n \"fallback=default_path)) TEST_DATABASE_URI = 'sqlite://' # Use in-memory (before: sqlite:///test_database.sqlite) class API: section =\",\n \"by default) config_dir = PosixPath.home() / '.config/TensorHive' MAIN_CONFIG_PATH = str(config_dir / 'main_config.ini') HOSTS_CONFIG_PATH\",\n \"env variable is declared''' if not os.getenv(name): msg = cleandoc( ''' {env} -\",\n \"= 'sqlite://' # Use in-memory (before: sqlite:///test_database.sqlite) class API: section = 'api' TITLE\",\n \"'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section = 'template/admin' ADMIN_SUBJECT\",\n \"= logging.getLogger(__name__) class CONFIG_FILES: # Where to copy files # (TensorHive tries to\",\n \"yes, check if tunneling is enabled if config.has_section(section) and config.getboolean(section, 'enabled', fallback=False): return\",\n \"section = 'auth' def config_get_parsed(option: str, fallback: Any) -> List[str]: # type: ignore\",\n \"section = 'general' INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50)\",\n \"stroing config files CONFIG_FILES.config_dir.mkdir(parents=True, exist_ok=True) # 2. Clone templates safely from `tensorhive` package\",\n \"recreate configuration files.') def safe_copy(self, src: str, dst: str) -> None: '''Safe means\",\n \"/ 'hosts_config.ini') MAILBOT_CONFIG_PATH = str(config_dir / 'mailbot_config.ini') # Where to get file templates\",\n \"import cleandoc import shutil import tensorhive import os import logging log = logging.getLogger(__name__)\",\n \"else: shutil.copy(src, dst) log.info('Copied {} to {}'.format(src, dst)) class ConfigLoader: @staticmethod def load(path,\",\n \"\\\"schedule_queued_jobs_when_free_mins\\\", fallback=30) class AUTH: from datetime import timedelta section = 'auth' def config_get_parsed(option:\",\n \"section = 'template/intruder' INTRUDER_SUBJECT = mailbot_config.get(section, 'subject') INTRUDER_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') section =\",\n \"'email', fallback=None) SMTP_PASSWORD = mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT\",\n \"config = configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading {} config from\",\n \"variable is declared''' if not os.getenv(name): msg = cleandoc( ''' {env} - undeclared\",\n \"'mailbot_config.ini') # Where to get file templates from # (Clone file when it's\",\n \"= str(tensorhive_package_dir / 'migrations') class ConfigInitilizer: '''Makes sure that all default config files\",\n \"'protection_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=2.0) NOTIFY_ON_PTY =\",\n \"called with arguments: option='some_option', fallback=None [some_section] some_option = ['foo', 'bar'] Will return: ['foo',\",\n \"if not all_exist: log.warning('[•] Detected missing default config file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All\",\n \"for key, value in cls.__dict__.items(): if key.isupper(): print('{} = {}'.format(key, value)) def check_env_var(name:\",\n \"fallback='tensorhive.api.controllers') import yaml respones_file_path = str(PosixPath(__file__).parent / 'controllers/responses.yml') with open(respones_file_path, 'r') as file:\",\n \"JOB_SCHEDULING_SERVICE: section = 'job_scheduling_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval',\",\n \"'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations') class ConfigInitilizer:\",\n \"config.getint(section, 'number_of_retries', fallback=1) KEY_FILE = config.get(section, 'key_file', fallback='~/.config/TensorHive/ssh_key') def hosts_config_to_dict(path: str) -> Dict:\",\n \"{ 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port', fallback=22) } else:\",\n \"fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587) section =\",\n \"log.info('Copied {} to {}'.format(src, dst)) class ConfigLoader: @staticmethod def load(path, displayed_title=''): import configparser\",\n \"ConfigLoader: @staticmethod def load(path, displayed_title=''): import configparser config = configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser()\",\n \"it's not found in config directory) tensorhive_package_dir = PosixPath(__file__).parent MAIN_CONFIG_TEMPLATE_PATH = str(tensorhive_package_dir /\",\n \"fallback='api') SPEC_FILE = config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml\",\n \".ini file, function called with arguments: option='some_option', fallback=None [some_section] some_option = ['foo', 'bar']\",\n \"rw_owner_only) except Exception: log.error('[✘] Unable to recreate configuration files.') def safe_copy(self, src: str,\",\n \"config.get(section, 'spec_file', fallback='api_specification.yml') IMPL_LOCATION = config.get(section, 'impl_location', fallback='tensorhive.api.controllers') import yaml respones_file_path = str(PosixPath(__file__).parent\",\n \"mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587) section = 'template/intruder' INTRUDER_SUBJECT =\",\n \"mailbot_config.get(section, 'password', fallback=None) SMTP_SERVER = mailbot_config.get(section, 'smtp_server', fallback=None) SMTP_PORT = mailbot_config.getint(section, 'smtp_port', fallback=587)\",\n \"import shutil import tensorhive import os import logging log = logging.getLogger(__name__) class CONFIG_FILES:\",\n \"str(tensorhive_package_dir / 'mailbot_config.ini') ALEMBIC_CONFIG_PATH = str(tensorhive_package_dir / 'alembic.ini') MIGRATIONS_CONFIG_PATH = str(tensorhive_package_dir / 'migrations')\",\n \"msg = cleandoc( ''' {env} - undeclared environment variable! Try this: `export {env}=\\\"...\\\"`\",\n \"fallback=False) class MONITORING_SERVICE: section = 'monitoring_service' ENABLED = config.getboolean(section, 'enabled', fallback=True) ENABLE_GPU_MONITOR =\",\n \"= 'general' INTERVAL = mailbot_config.getfloat(section, 'interval', fallback=10.0) MAX_EMAILS_PER_PROTECTION_INTERVAL = mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER\",\n \"all_exist = PosixPath(CONFIG_FILES.MAIN_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.HOSTS_CONFIG_PATH).exists() and \\\\ PosixPath(CONFIG_FILES.MAILBOT_CONFIG_PATH).exists() if not all_exist: log.warning('[•]\",\n \"hosts_config_to_dict(path: str) -> Dict: # type: ignore '''Parses sections containing hostnames''' hosts_config =\",\n \"config files exist''' def __init__(self): # 1. Check if all config files exist\",\n \"= config.getint(section, 'workers', fallback=4) LOG_LEVEL = config.get(section, 'loglevel', fallback='warning') class API_SERVER: section =\",\n \"= ConfigLoader.load(CONFIG_FILES.MAIN_CONFIG_PATH, displayed_title='main') def display_config(cls): ''' Displays all uppercase class atributes (class must\",\n \"file(s), recreating...') self.recreate_default_configuration_files() log.info('[•] All configs already exist, skipping...') def recreate_default_configuration_files(self) -> None:\",\n \"'update_interval', fallback=2.0) NOTIFY_ON_PTY = config.getboolean(section, 'notify_on_pty', fallback=True) NOTIFY_VIA_EMAIL = config.getboolean(section, 'notify_via_email', fallback=False) class\",\n \"config.getboolean(section, 'enabled', fallback=True) UPDATE_INTERVAL = config.getfloat(section, 'update_interval', fallback=30.0) STOP_TERMINATION_ATTEMPTS_AFTER = config.getfloat(section, 'stop_termination_attempts_after_mins', fallback=5.0)\",\n \"for section in hosts_config.sections(): # We want to parse only sections which describe\",\n \"this: `export {env}=\\\"...\\\"` ''').format(env=name).split('\\\\n') log.warning(msg[0]) log.warning(msg[1]) class SSH: section = 'ssh' HOSTS_CONFIG_FILE =\",\n \"shutil.copy(src, dst) log.info('Copied {} to {}'.format(src, dst)) class ConfigLoader: @staticmethod def load(path, displayed_title=''):\",\n \"None AVAILABLE_NODES = hosts_config_to_dict(HOSTS_CONFIG_FILE) PROXY = proxy_config_to_dict(HOSTS_CONFIG_FILE) class DB: section = 'database' default_path\",\n \"# Use in-memory (before: sqlite:///test_database.sqlite) class API: section = 'api' TITLE = config.get(section,\",\n \"display_config(cls): ''' Displays all uppercase class atributes (class must be defined first) Example\",\n \"== 'proxy_tunneling': continue hostname = section result[hostname] = { 'user': hosts_config.get(hostname, 'user'), 'port':\",\n \"section result[hostname] = { 'user': hosts_config.get(hostname, 'user'), 'port': hosts_config.getint(hostname, 'port', fallback=22) } return\",\n \"= config.get(section, 'host', fallback='0.0.0.0') PORT = config.getint(section, 'port', fallback=5000) WORKERS = config.getint(section, 'workers',\",\n \"displayed_title=''): import configparser config = configparser.ConfigParser(strict=False) full_path = PosixPath(path).expanduser() if config.read(str(full_path)): log.info('[•] Reading\",\n \"uppercase class atributes (class must be defined first) Example usage: display_config(API_SERVER) ''' print('[{class_name}]'.format(class_name=cls.__name__))\",\n \"'template/admin' ADMIN_SUBJECT = mailbot_config.get(section, 'subject') ADMIN_BODY_TEMPLATE = mailbot_config.get(section, 'html_body') class USAGE_LOGGING_SERVICE: section =\",\n \"str, fallback: Any) -> List[str]: # type: ignore ''' Parses value for option\",\n \"['foo', 'bar'] ''' import ast try: raw_arguments = config.get('auth', option) parsed_arguments = ast.literal_eval(raw_arguments)\",\n \"fallback=30) class AUTH: from datetime import timedelta section = 'auth' def config_get_parsed(option: str,\",\n \"'enabled', fallback=False): return { 'proxy_host': config.get(section, 'proxy_host'), 'proxy_user': config.get(section, 'proxy_user'), 'proxy_port': config.getint(section, 'proxy_port',\",\n \"Configuration file not found ({})'.format(full_path)) log.info('Using default {} settings from config.py'.format(displayed_title)) return config\",\n \"os.chmod(CONFIG_FILES.MAIN_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.HOSTS_CONFIG_PATH, rw_owner_only) os.chmod(CONFIG_FILES.MAILBOT_CONFIG_PATH, rw_owner_only) except Exception: log.error('[✘] Unable to recreate configuration\",\n \"log.warning(msg[1]) class SSH: section = 'ssh' HOSTS_CONFIG_FILE = config.get(section, 'hosts_config_file', fallback=CONFIG_FILES.HOSTS_CONFIG_PATH) TEST_ON_STARTUP =\"\n]","isConversational":false}}},{"rowIdx":4589,"cells":{"ngram":{"kind":"list like","value":["2) + dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len =","= nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1,","a = a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0, 2) weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep","repeated_decoder_hidden, encoder_outputs), dim = 2))) attention = torch.sum(energy, dim=2) return F.softmax(attention, dim=1) class","torch.nn.functional as F from torch import Tensor class Encoder(nn.Module): def __init__(self, input_dim, emb_dim,","2) weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep def","decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs = encoder_outputs.permute(1,","Encoder(nn.Module): def __init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim = input_dim self.emb_dim","the <sos> token output = trg[0,:] for t in range(1, max_len): output, hidden","= embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep, embedded),","dropout, attention): super().__init__() self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim","Tuple import torch import torch.nn as nn import torch.optim as optim import torch.nn.functional","enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim = output_dim self.dropout = dropout self.attention = attention","emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional = True) self.fc = nn.Linear(enc_hid_dim * 2,","dropout self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional = True) self.fc","output, hidden = self.decoder(output, hidden, encoder_outputs) outputs[t] = output teacher_force = random.random() <","class Decoder(nn.Module): def __init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__() self.emb_dim =","dropout): super().__init__() self.input_dim = input_dim self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim =","emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__() self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim","dim = 2) output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output =","super().__init__() self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim = output_dim","weighted_encoder_rep def forward(self, input, decoder_hidden, encoder_outputs): input = input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep","dim=2) return F.softmax(attention, dim=1) class Decoder(nn.Module): def __init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout,","outputs, hidden = self.rnn(embedded) # output of bi-directional rnn should be concatenated hidden","self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output =","+ emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout = nn.Dropout(dropout) def","def forward(self, src): embedded = self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded) # output of","emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim = input_dim self.emb_dim = emb_dim self.enc_hid_dim =","= self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output","dec_hid_dim) self.out = nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden,","* 2) + dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len","= trg[0,:] for t in range(1, max_len): output, hidden = self.decoder(output, hidden, encoder_outputs)","encoder_outputs = encoder_outputs.permute(1, 0, 2) weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0,","device): super().__init__() self.encoder = encoder self.decoder = decoder self.device = device def forward(self,","encoder_outputs): input = input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input =","weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep def forward(self, input, decoder_hidden, encoder_outputs): input = input.unsqueeze(0)","1) encoder_outputs = encoder_outputs.permute(1, 0, 2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim =","output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__() self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim","embedded = embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep,","range(1, max_len): output, hidden = self.decoder(output, hidden, encoder_outputs) outputs[t] = output teacher_force =","weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep def forward(self,","= weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep def forward(self, input, decoder_hidden, encoder_outputs): input =","weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep), dim = 2) output, decoder_hidden","= nn.GRU(emb_dim, enc_hid_dim, bidirectional = True) self.fc = nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout","torch.cat((embedded, weighted_encoder_rep), dim = 2) output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0)","self.dec_hid_dim = dec_hid_dim self.attn_in = (enc_hid_dim * 2) + dec_hid_dim self.attn = nn.Linear(self.attn_in,","= output teacher_force = random.random() < teacher_forcing_ratio top1 = output.max(1)[1] output = (trg[t]","self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep), dim = 2) output,","attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1)","self.encoder(src) # first input to the decoder is the <sos> token output =","is the <sos> token output = trg[0,:] for t in range(1, max_len): output,","self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim = output_dim self.dropout = dropout self.attention","input to the decoder is the <sos> token output = trg[0,:] for t","torch import torch.nn as nn import torch.optim as optim import torch.nn.functional as F","random.random() < teacher_forcing_ratio top1 = output.max(1)[1] output = (trg[t] if teacher_force else top1)","self.decoder.output_dim outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src) # first input","# output of bi-directional rnn should be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim","= 1)) return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self, encoder, decoder, device): super().__init__()","= nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1)","input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim = input_dim self.emb_dim = emb_dim self.enc_hid_dim","outputs, hidden class Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim","self.dec_hid_dim = dec_hid_dim self.output_dim = output_dim self.dropout = dropout self.attention = attention self.embedding","self.input_dim = input_dim self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout","device def forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len = trg.shape[0] trg_vocab_size","output_dim self.dropout = dropout self.attention = attention self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn =","emb_dim) self.rnn = nn.GRU((enc_hid_dim * 2) + emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in +","2))) attention = torch.sum(energy, dim=2) return F.softmax(attention, dim=1) class Decoder(nn.Module): def __init__(self, output_dim,","decoder, device): super().__init__() self.encoder = encoder self.decoder = decoder self.device = device def","forward(self, src): embedded = self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded) # output of bi-directional","= output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep, embedded), dim = 1))","def __init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim = input_dim self.emb_dim =","enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout = dropout self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn =","batch_size = src.shape[1] max_len = trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs = torch.zeros(max_len, batch_size,","= device def forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len = trg.shape[0]","output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep =","be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1))) return outputs, hidden class","= nn.Dropout(dropout) def forward(self, src): embedded = self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded) #","self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout = dropout self.embedding = nn.Embedding(input_dim, emb_dim)","__init__(self, encoder, decoder, device): super().__init__() self.encoder = encoder self.decoder = decoder self.device =","embedded), dim = 1)) return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self, encoder, decoder,","self.dropout = dropout self.attention = attention self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim","(enc_hid_dim * 2) + dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs):","from typing import Tuple import torch import torch.nn as nn import torch.optim as","attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in = (enc_hid_dim * 2)","+ emb_dim, output_dim) self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden,","nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1) encoder_outputs","dec_hid_dim) self.dropout = nn.Dropout(dropout) def forward(self, src): embedded = self.dropout(self.embedding(src)) outputs, hidden =","trg_vocab_size = self.decoder.output_dim outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src) #","rnn_input = torch.cat((embedded, weighted_encoder_rep), dim = 2) output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded","encoder, decoder, device): super().__init__() self.encoder = encoder self.decoder = decoder self.device = device","hidden[-1,:,:]), dim = 1))) return outputs, hidden class Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim,","= attention self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim * 2) + emb_dim,","repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs = encoder_outputs.permute(1, 0, 2) energy = torch.tanh(self.attn(torch.cat((","weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep, embedded), dim = 1)) return output, decoder_hidden.squeeze(0) class","encoder_outputs.permute(1, 0, 2) weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2) return","decoder self.device = device def forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len","def forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len = trg.shape[0] trg_vocab_size =","dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden","encoder_outputs) a = a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0, 2) weighted_encoder_rep = torch.bmm(a, encoder_outputs)","decoder_hidden, encoder_outputs): input = input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input","encoder_outputs, hidden = self.encoder(src) # first input to the decoder is the <sos>","self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in = (enc_hid_dim * 2) + dec_hid_dim","dec_hid_dim self.dropout = dropout self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional","as nn import torch.optim as optim import torch.nn.functional as F from torch import","self.attn = nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden =","self.dropout = dropout self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional =","trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src) # first input to the decoder is the","= self.encoder(src) # first input to the decoder is the <sos> token output","dec_hid_dim, dropout): super().__init__() self.input_dim = input_dim self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim","1)) return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self, encoder, decoder, device): super().__init__() self.encoder","token output = trg[0,:] for t in range(1, max_len): output, hidden = self.decoder(output,","dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in = (enc_hid_dim *","self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep), dim = 2) output, decoder_hidden = self.rnn(rnn_input,","= torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src) # first input to the","= emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim = output_dim self.dropout =","encoder self.decoder = decoder self.device = device def forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size","encoder_outputs), dim = 2))) attention = torch.sum(energy, dim=2) return F.softmax(attention, dim=1) class Decoder(nn.Module):","= decoder self.device = device def forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1]","self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional = True) self.fc =","self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0, 2) weighted_encoder_rep = torch.bmm(a,","self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded) # output of bi-directional rnn should be concatenated","Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim","0, 2) return weighted_encoder_rep def forward(self, input, decoder_hidden, encoder_outputs): input = input.unsqueeze(0) embedded","dec_hid_dim self.attn_in = (enc_hid_dim * 2) + dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim) def","in range(1, max_len): output, hidden = self.decoder(output, hidden, encoder_outputs) outputs[t] = output teacher_force","torch.sum(energy, dim=2) return F.softmax(attention, dim=1) class Decoder(nn.Module): def __init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim,","dec_hid_dim, dropout, attention): super().__init__() self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim","torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim = 2))) attention = torch.sum(energy, dim=2) return F.softmax(attention, dim=1)","encoder_outputs) outputs[t] = output teacher_force = random.random() < teacher_forcing_ratio top1 = output.max(1)[1] output","first input to the decoder is the <sos> token output = trg[0,:] for","self.dec_hid_dim = dec_hid_dim self.dropout = dropout self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim,","dropout self.attention = attention self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim * 2)","= random.random() < teacher_forcing_ratio top1 = output.max(1)[1] output = (trg[t] if teacher_force else","nn.GRU((enc_hid_dim * 2) + emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout","__init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim = input_dim self.emb_dim = emb_dim","dim=1) class Decoder(nn.Module): def __init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__() self.emb_dim","def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in","attention): super().__init__() self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim =","self.device = device def forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len =","hidden = self.encoder(src) # first input to the decoder is the <sos> token","self.fc = nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout = nn.Dropout(dropout) def forward(self, src): embedded","self.dropout = nn.Dropout(dropout) def forward(self, src): embedded = self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded)","= self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep), dim = 2) output, decoder_hidden =","encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0, 2)","= enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim = output_dim self.dropout = dropout self.attention =","output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self, encoder, decoder, device): super().__init__() self.encoder = encoder","self.decoder = decoder self.device = device def forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size =","nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim * 2) + emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in","= output_dim self.dropout = dropout self.attention = attention self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn","decoder is the <sos> token output = trg[0,:] for t in range(1, max_len):","super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in = (enc_hid_dim * 2) +","energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim = 2))) attention = torch.sum(energy, dim=2) return","0, 2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim = 2))) attention = torch.sum(energy,","= src.shape[1] max_len = trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device)","emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim = output_dim self.dropout = dropout","import torch import torch.nn as nn import torch.optim as optim import torch.nn.functional as","teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len = trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs = torch.zeros(max_len,","output of bi-directional rnn should be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim =","= torch.sum(energy, dim=2) return F.softmax(attention, dim=1) class Decoder(nn.Module): def __init__(self, output_dim, emb_dim, enc_hid_dim,","nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional = True) self.fc = nn.Linear(enc_hid_dim *","super().__init__() self.input_dim = input_dim self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim","Decoder(nn.Module): def __init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__() self.emb_dim = emb_dim","= enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in = (enc_hid_dim * 2) + dec_hid_dim self.attn","= input_dim self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout =","return F.softmax(attention, dim=1) class Decoder(nn.Module): def __init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention):","hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1))) return outputs, hidden class Attention(nn.Module): def","a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0, 2) weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1,","self.out(torch.cat((output, weighted_encoder_rep, embedded), dim = 1)) return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self,","import torch.optim as optim import torch.nn.functional as F from torch import Tensor class","torch import Tensor class Encoder(nn.Module): def __init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__()","= self.decoder.output_dim outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src) # first","= dec_hid_dim self.attn_in = (enc_hid_dim * 2) + dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim)","= encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs = encoder_outputs.permute(1, 0, 2) energy","batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src) # first input to the decoder is","output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep, embedded), dim = 1)) return","+ dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0]","self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout = dropout self.embedding","trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src)","import torch.nn as nn import torch.optim as optim import torch.nn.functional as F from","2, dec_hid_dim) self.dropout = nn.Dropout(dropout) def forward(self, src): embedded = self.dropout(self.embedding(src)) outputs, hidden","max_len): output, hidden = self.decoder(output, hidden, encoder_outputs) outputs[t] = output teacher_force = random.random()","__init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__() self.emb_dim = emb_dim self.enc_hid_dim =","trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len = trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs =","import random from typing import Tuple import torch import torch.nn as nn import","* 2) + emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout =","output = self.out(torch.cat((output, weighted_encoder_rep, embedded), dim = 1)) return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module):","decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs = encoder_outputs.permute(1, 0, 2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs),","to the decoder is the <sos> token output = trg[0,:] for t in","= enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout = dropout self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn","random from typing import Tuple import torch import torch.nn as nn import torch.optim","self.attention = attention self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim * 2) +","hidden = self.rnn(embedded) # output of bi-directional rnn should be concatenated hidden =","= dropout self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional = True)","torch.optim as optim import torch.nn.functional as F from torch import Tensor class Encoder(nn.Module):","teacher_force = random.random() < teacher_forcing_ratio top1 = output.max(1)[1] output = (trg[t] if teacher_force","forward(self, decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs =","self.rnn(embedded) # output of bi-directional rnn should be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]),","emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self,","output = output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep, embedded), dim =","torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1))) return outputs, hidden class Attention(nn.Module): def __init__(self, enc_hid_dim,","self.out = nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs):","= 1))) return outputs, hidden class Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__()","weighted_encoder_rep, embedded), dim = 1)) return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self, encoder,","forward(self, input, decoder_hidden, encoder_outputs): input = input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden,","nn import torch.optim as optim import torch.nn.functional as F from torch import Tensor","encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep), dim = 2) output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0))","as optim import torch.nn.functional as F from torch import Tensor class Encoder(nn.Module): def","= 2) output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output = output.squeeze(0)","attention self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim * 2) + emb_dim, dec_hid_dim)","= encoder_outputs.permute(1, 0, 2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim = 2))) attention","nn.Dropout(dropout) def forward(self, src): embedded = self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded) # output","teacher_forcing_ratio top1 = output.max(1)[1] output = (trg[t] if teacher_force else top1) return outputs","encoder_outputs = encoder_outputs.permute(1, 0, 2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim = 2)))","enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in = (enc_hid_dim","outputs[t] = output teacher_force = random.random() < teacher_forcing_ratio top1 = output.max(1)[1] output =","return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self, encoder, decoder, device): super().__init__() self.encoder =","encoder_outputs.permute(1, 0, 2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim = 2))) attention =","hidden class Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim","optim import torch.nn.functional as F from torch import Tensor class Encoder(nn.Module): def __init__(self,","torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep def forward(self, input, decoder_hidden,","decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self, encoder, decoder, device): super().__init__() self.encoder = encoder self.decoder","enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in = (enc_hid_dim * 2) + dec_hid_dim self.attn =","weighted_encoder_rep), dim = 2) output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output","= (enc_hid_dim * 2) + dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden,","import Tuple import torch import torch.nn as nn import torch.optim as optim import","= self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep), dim = 2)","<sos> token output = trg[0,:] for t in range(1, max_len): output, hidden =","= a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0, 2) weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep =","= torch.cat((embedded, weighted_encoder_rep), dim = 2) output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded =","self.decoder(output, hidden, encoder_outputs) outputs[t] = output teacher_force = random.random() < teacher_forcing_ratio top1 =","the decoder is the <sos> token output = trg[0,:] for t in range(1,","emb_dim, output_dim) self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs)","2) output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep","forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len = trg.shape[0] trg_vocab_size = self.decoder.output_dim","2) return weighted_encoder_rep def forward(self, input, decoder_hidden, encoder_outputs): input = input.unsqueeze(0) embedded =","rnn should be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1))) return outputs,","hidden = self.decoder(output, hidden, encoder_outputs) outputs[t] = output teacher_force = random.random() < teacher_forcing_ratio","= dropout self.attention = attention self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim *","def __init__(self, encoder, decoder, device): super().__init__() self.encoder = encoder self.decoder = decoder self.device","as F from torch import Tensor class Encoder(nn.Module): def __init__(self, input_dim, emb_dim, enc_hid_dim,","nn.GRU(emb_dim, enc_hid_dim, bidirectional = True) self.fc = nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout =","= decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs = encoder_outputs.permute(1, 0, 2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden,","self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional = True) self.fc = nn.Linear(enc_hid_dim * 2, dec_hid_dim)","= trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden =","t in range(1, max_len): output, hidden = self.decoder(output, hidden, encoder_outputs) outputs[t] = output","dim = 1)) return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self, encoder, decoder, device):","def forward(self, input, decoder_hidden, encoder_outputs): input = input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep =","embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep, embedded), dim","input, decoder_hidden, encoder_outputs): input = input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs)","output = trg[0,:] for t in range(1, max_len): output, hidden = self.decoder(output, hidden,","input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep), dim","output teacher_force = random.random() < teacher_forcing_ratio top1 = output.max(1)[1] output = (trg[t] if","= torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim = 2))) attention = torch.sum(energy, dim=2) return F.softmax(attention,","def __init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__() self.emb_dim = emb_dim self.enc_hid_dim","a = self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0, 2) weighted_encoder_rep","torch.nn as nn import torch.optim as optim import torch.nn.functional as F from torch","self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim * 2) + emb_dim, dec_hid_dim) self.out","= torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1))) return outputs, hidden class Attention(nn.Module): def __init__(self,","= nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout = nn.Dropout(dropout) def forward(self, src): embedded =","self.output_dim = output_dim self.dropout = dropout self.attention = attention self.embedding = nn.Embedding(output_dim, emb_dim)","class Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim =","True) self.fc = nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout = nn.Dropout(dropout) def forward(self, src):","= encoder_outputs.permute(1, 0, 2) weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2)","self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs) a =","of bi-directional rnn should be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1)))","dec_hid_dim self.output_dim = output_dim self.dropout = dropout self.attention = attention self.embedding = nn.Embedding(output_dim,","max_len = trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden","embedded = self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded) # output of bi-directional rnn should","< teacher_forcing_ratio top1 = output.max(1)[1] output = (trg[t] if teacher_force else top1) return","trg[0,:] for t in range(1, max_len): output, hidden = self.decoder(output, hidden, encoder_outputs) outputs[t]","src, trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len = trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs","import torch.nn.functional as F from torch import Tensor class Encoder(nn.Module): def __init__(self, input_dim,","__init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in =","def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1) encoder_outputs =","encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep def forward(self, input, decoder_hidden, encoder_outputs):","dim = 2))) attention = torch.sum(energy, dim=2) return F.softmax(attention, dim=1) class Decoder(nn.Module): def","= torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep def forward(self, input,","hidden, encoder_outputs) outputs[t] = output teacher_force = random.random() < teacher_forcing_ratio top1 = output.max(1)[1]","embedded = self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep), dim =","self.encoder = encoder self.decoder = decoder self.device = device def forward(self, src, trg,","= nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional = True) self.fc = nn.Linear(enc_hid_dim","decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0)","= self.rnn(embedded) # output of bi-directional rnn should be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:],","= self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0, 2) weighted_encoder_rep =","2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim = 2))) attention = torch.sum(energy, dim=2)","for t in range(1, max_len): output, hidden = self.decoder(output, hidden, encoder_outputs) outputs[t] =","# first input to the decoder is the <sos> token output = trg[0,:]","def forward(self, decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs","bidirectional = True) self.fc = nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout = nn.Dropout(dropout) def","1))) return outputs, hidden class Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim","Seq2Seq(nn.Module): def __init__(self, encoder, decoder, device): super().__init__() self.encoder = encoder self.decoder = decoder","weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep def forward(self, input, decoder_hidden, encoder_outputs): input","nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout = nn.Dropout(dropout) def forward(self, src): embedded = self.dropout(self.embedding(src))","decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output,","decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0,","from torch import Tensor class Encoder(nn.Module): def __init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout):","F from torch import Tensor class Encoder(nn.Module): def __init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim,","bi-directional rnn should be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1))) return","encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs = encoder_outputs.permute(1, 0,","self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim = output_dim self.dropout","= weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep, embedded), dim = 1)) return output, decoder_hidden.squeeze(0)","= 2))) attention = torch.sum(energy, dim=2) return F.softmax(attention, dim=1) class Decoder(nn.Module): def __init__(self,","= input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep),","input = input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded,","enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__() self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim =","= nn.GRU((enc_hid_dim * 2) + emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in + emb_dim, output_dim)","= True) self.fc = nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout = nn.Dropout(dropout) def forward(self,","0, 2) weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep","= self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded) # output of bi-directional rnn should be","outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src) # first input to","dim = 1))) return outputs, hidden class Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim):","input_dim self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout = dropout","super().__init__() self.encoder = encoder self.decoder = decoder self.device = device def forward(self, src,","= nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a","= emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout = dropout self.embedding =","self.rnn = nn.GRU((enc_hid_dim * 2) + emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in + emb_dim,","return outputs, hidden class Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim =","src): embedded = self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded) # output of bi-directional rnn","concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1))) return outputs, hidden class Attention(nn.Module):","enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim = input_dim self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim","encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs = encoder_outputs.permute(1, 0, 2) energy =","2) + emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout = nn.Dropout(dropout)","nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a =","weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep, embedded), dim = 1)) return output,","src_len = encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs = encoder_outputs.permute(1, 0, 2)","F.softmax(attention, dim=1) class Decoder(nn.Module): def __init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__()","= nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim * 2) + emb_dim, dec_hid_dim) self.out =","Tensor class Encoder(nn.Module): def __init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim =","= self.out(torch.cat((output, weighted_encoder_rep, embedded), dim = 1)) return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def","* 2, dec_hid_dim) self.dropout = nn.Dropout(dropout) def forward(self, src): embedded = self.dropout(self.embedding(src)) outputs,","import Tensor class Encoder(nn.Module): def __init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim","class Seq2Seq(nn.Module): def __init__(self, encoder, decoder, device): super().__init__() self.encoder = encoder self.decoder =","_weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1,","output_dim) self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs) a","src_len, 1) encoder_outputs = encoder_outputs.permute(1, 0, 2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim","enc_hid_dim, bidirectional = True) self.fc = nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout = nn.Dropout(dropout)","return weighted_encoder_rep def forward(self, input, decoder_hidden, encoder_outputs): input = input.unsqueeze(0) embedded = self.dropout(self.embedding(input))","self.attn_in = (enc_hid_dim * 2) + dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim) def forward(self,","typing import Tuple import torch import torch.nn as nn import torch.optim as optim","= dec_hid_dim self.output_dim = output_dim self.dropout = dropout self.attention = attention self.embedding =","emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout = dropout self.embedding = nn.Embedding(input_dim,","src.shape[1] max_len = trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs,","class Encoder(nn.Module): def __init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim = input_dim","= self.decoder(output, hidden, encoder_outputs) outputs[t] = output teacher_force = random.random() < teacher_forcing_ratio top1","torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src) # first input to the decoder","= dec_hid_dim self.dropout = dropout self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim,","should be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1))) return outputs, hidden","nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len,","= encoder self.decoder = decoder self.device = device def forward(self, src, trg, teacher_forcing_ratio=0.5):","attention = torch.sum(energy, dim=2) return F.softmax(attention, dim=1) class Decoder(nn.Module): def __init__(self, output_dim, emb_dim,"],"string":"[\n \"2) + dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len =\",\n \"= nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1,\",\n \"a = a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0, 2) weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep\",\n \"repeated_decoder_hidden, encoder_outputs), dim = 2))) attention = torch.sum(energy, dim=2) return F.softmax(attention, dim=1) class\",\n \"torch.nn.functional as F from torch import Tensor class Encoder(nn.Module): def __init__(self, input_dim, emb_dim,\",\n \"2) weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep def\",\n \"decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs = encoder_outputs.permute(1,\",\n \"Encoder(nn.Module): def __init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim = input_dim self.emb_dim\",\n \"the <sos> token output = trg[0,:] for t in range(1, max_len): output, hidden\",\n \"= embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep, embedded),\",\n \"dropout, attention): super().__init__() self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim\",\n \"Tuple import torch import torch.nn as nn import torch.optim as optim import torch.nn.functional\",\n \"enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim = output_dim self.dropout = dropout self.attention = attention\",\n \"emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional = True) self.fc = nn.Linear(enc_hid_dim * 2,\",\n \"dropout self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional = True) self.fc\",\n \"output, hidden = self.decoder(output, hidden, encoder_outputs) outputs[t] = output teacher_force = random.random() <\",\n \"class Decoder(nn.Module): def __init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__() self.emb_dim =\",\n \"dropout): super().__init__() self.input_dim = input_dim self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim =\",\n \"emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__() self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim\",\n \"dim = 2) output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output =\",\n \"super().__init__() self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim = output_dim\",\n \"weighted_encoder_rep def forward(self, input, decoder_hidden, encoder_outputs): input = input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep\",\n \"dim=2) return F.softmax(attention, dim=1) class Decoder(nn.Module): def __init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout,\",\n \"outputs, hidden = self.rnn(embedded) # output of bi-directional rnn should be concatenated hidden\",\n \"self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output =\",\n \"+ emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout = nn.Dropout(dropout) def\",\n \"def forward(self, src): embedded = self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded) # output of\",\n \"emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim = input_dim self.emb_dim = emb_dim self.enc_hid_dim =\",\n \"= self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output\",\n \"dec_hid_dim) self.out = nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden,\",\n \"* 2) + dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len\",\n \"= trg[0,:] for t in range(1, max_len): output, hidden = self.decoder(output, hidden, encoder_outputs)\",\n \"encoder_outputs = encoder_outputs.permute(1, 0, 2) weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0,\",\n \"device): super().__init__() self.encoder = encoder self.decoder = decoder self.device = device def forward(self,\",\n \"encoder_outputs): input = input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input =\",\n \"weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep def forward(self, input, decoder_hidden, encoder_outputs): input = input.unsqueeze(0)\",\n \"1) encoder_outputs = encoder_outputs.permute(1, 0, 2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim =\",\n \"output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__() self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim\",\n \"embedded = embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep,\",\n \"range(1, max_len): output, hidden = self.decoder(output, hidden, encoder_outputs) outputs[t] = output teacher_force =\",\n \"weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep def forward(self,\",\n \"= weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep def forward(self, input, decoder_hidden, encoder_outputs): input =\",\n \"weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep), dim = 2) output, decoder_hidden\",\n \"= nn.GRU(emb_dim, enc_hid_dim, bidirectional = True) self.fc = nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout\",\n \"torch.cat((embedded, weighted_encoder_rep), dim = 2) output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0)\",\n \"self.dec_hid_dim = dec_hid_dim self.attn_in = (enc_hid_dim * 2) + dec_hid_dim self.attn = nn.Linear(self.attn_in,\",\n \"= output teacher_force = random.random() < teacher_forcing_ratio top1 = output.max(1)[1] output = (trg[t]\",\n \"self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep), dim = 2) output,\",\n \"attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1)\",\n \"self.encoder(src) # first input to the decoder is the <sos> token output =\",\n \"is the <sos> token output = trg[0,:] for t in range(1, max_len): output,\",\n \"self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim = output_dim self.dropout = dropout self.attention\",\n \"input to the decoder is the <sos> token output = trg[0,:] for t\",\n \"torch import torch.nn as nn import torch.optim as optim import torch.nn.functional as F\",\n \"random.random() < teacher_forcing_ratio top1 = output.max(1)[1] output = (trg[t] if teacher_force else top1)\",\n \"self.decoder.output_dim outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src) # first input\",\n \"# output of bi-directional rnn should be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim\",\n \"= 1)) return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self, encoder, decoder, device): super().__init__()\",\n \"= nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1)\",\n \"input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim = input_dim self.emb_dim = emb_dim self.enc_hid_dim\",\n \"outputs, hidden class Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim\",\n \"self.dec_hid_dim = dec_hid_dim self.output_dim = output_dim self.dropout = dropout self.attention = attention self.embedding\",\n \"self.input_dim = input_dim self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout\",\n \"device def forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len = trg.shape[0] trg_vocab_size\",\n \"output_dim self.dropout = dropout self.attention = attention self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn =\",\n \"emb_dim) self.rnn = nn.GRU((enc_hid_dim * 2) + emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in +\",\n \"2))) attention = torch.sum(energy, dim=2) return F.softmax(attention, dim=1) class Decoder(nn.Module): def __init__(self, output_dim,\",\n \"decoder, device): super().__init__() self.encoder = encoder self.decoder = decoder self.device = device def\",\n \"forward(self, src): embedded = self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded) # output of bi-directional\",\n \"= output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep, embedded), dim = 1))\",\n \"def __init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim = input_dim self.emb_dim =\",\n \"enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout = dropout self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn =\",\n \"batch_size = src.shape[1] max_len = trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs = torch.zeros(max_len, batch_size,\",\n \"= device def forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len = trg.shape[0]\",\n \"output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep =\",\n \"be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1))) return outputs, hidden class\",\n \"= nn.Dropout(dropout) def forward(self, src): embedded = self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded) #\",\n \"self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout = dropout self.embedding = nn.Embedding(input_dim, emb_dim)\",\n \"__init__(self, encoder, decoder, device): super().__init__() self.encoder = encoder self.decoder = decoder self.device =\",\n \"embedded), dim = 1)) return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self, encoder, decoder,\",\n \"self.dropout = dropout self.attention = attention self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim\",\n \"(enc_hid_dim * 2) + dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs):\",\n \"from typing import Tuple import torch import torch.nn as nn import torch.optim as\",\n \"attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in = (enc_hid_dim * 2)\",\n \"+ emb_dim, output_dim) self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden,\",\n \"nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1) encoder_outputs\",\n \"dec_hid_dim) self.dropout = nn.Dropout(dropout) def forward(self, src): embedded = self.dropout(self.embedding(src)) outputs, hidden =\",\n \"trg_vocab_size = self.decoder.output_dim outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src) #\",\n \"rnn_input = torch.cat((embedded, weighted_encoder_rep), dim = 2) output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded\",\n \"encoder, decoder, device): super().__init__() self.encoder = encoder self.decoder = decoder self.device = device\",\n \"hidden[-1,:,:]), dim = 1))) return outputs, hidden class Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim,\",\n \"= attention self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim * 2) + emb_dim,\",\n \"repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs = encoder_outputs.permute(1, 0, 2) energy = torch.tanh(self.attn(torch.cat((\",\n \"weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep, embedded), dim = 1)) return output, decoder_hidden.squeeze(0) class\",\n \"encoder_outputs.permute(1, 0, 2) weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2) return\",\n \"decoder self.device = device def forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len\",\n \"def forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len = trg.shape[0] trg_vocab_size =\",\n \"dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden\",\n \"encoder_outputs) a = a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0, 2) weighted_encoder_rep = torch.bmm(a, encoder_outputs)\",\n \"decoder_hidden, encoder_outputs): input = input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input\",\n \"encoder_outputs, hidden = self.encoder(src) # first input to the decoder is the <sos>\",\n \"self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in = (enc_hid_dim * 2) + dec_hid_dim\",\n \"dec_hid_dim self.dropout = dropout self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional\",\n \"as nn import torch.optim as optim import torch.nn.functional as F from torch import\",\n \"self.attn = nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden =\",\n \"self.dropout = dropout self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional =\",\n \"trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src) # first input to the decoder is the\",\n \"= self.encoder(src) # first input to the decoder is the <sos> token output\",\n \"dec_hid_dim, dropout): super().__init__() self.input_dim = input_dim self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim\",\n \"1)) return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self, encoder, decoder, device): super().__init__() self.encoder\",\n \"token output = trg[0,:] for t in range(1, max_len): output, hidden = self.decoder(output,\",\n \"dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in = (enc_hid_dim *\",\n \"self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep), dim = 2) output, decoder_hidden = self.rnn(rnn_input,\",\n \"= torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src) # first input to the\",\n \"= emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim = output_dim self.dropout =\",\n \"encoder self.decoder = decoder self.device = device def forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size\",\n \"encoder_outputs), dim = 2))) attention = torch.sum(energy, dim=2) return F.softmax(attention, dim=1) class Decoder(nn.Module):\",\n \"= decoder self.device = device def forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1]\",\n \"self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional = True) self.fc =\",\n \"self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0, 2) weighted_encoder_rep = torch.bmm(a,\",\n \"self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded) # output of bi-directional rnn should be concatenated\",\n \"Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim\",\n \"0, 2) return weighted_encoder_rep def forward(self, input, decoder_hidden, encoder_outputs): input = input.unsqueeze(0) embedded\",\n \"dec_hid_dim self.attn_in = (enc_hid_dim * 2) + dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim) def\",\n \"in range(1, max_len): output, hidden = self.decoder(output, hidden, encoder_outputs) outputs[t] = output teacher_force\",\n \"torch.sum(energy, dim=2) return F.softmax(attention, dim=1) class Decoder(nn.Module): def __init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim,\",\n \"dec_hid_dim, dropout, attention): super().__init__() self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim\",\n \"torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim = 2))) attention = torch.sum(energy, dim=2) return F.softmax(attention, dim=1)\",\n \"encoder_outputs) outputs[t] = output teacher_force = random.random() < teacher_forcing_ratio top1 = output.max(1)[1] output\",\n \"first input to the decoder is the <sos> token output = trg[0,:] for\",\n \"self.dec_hid_dim = dec_hid_dim self.dropout = dropout self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim,\",\n \"dropout self.attention = attention self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim * 2)\",\n \"= random.random() < teacher_forcing_ratio top1 = output.max(1)[1] output = (trg[t] if teacher_force else\",\n \"nn.GRU((enc_hid_dim * 2) + emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout\",\n \"__init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim = input_dim self.emb_dim = emb_dim\",\n \"dim=1) class Decoder(nn.Module): def __init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__() self.emb_dim\",\n \"def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in\",\n \"attention): super().__init__() self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim =\",\n \"self.device = device def forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len =\",\n \"hidden = self.encoder(src) # first input to the decoder is the <sos> token\",\n \"self.fc = nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout = nn.Dropout(dropout) def forward(self, src): embedded\",\n \"self.dropout = nn.Dropout(dropout) def forward(self, src): embedded = self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded)\",\n \"= self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep), dim = 2) output, decoder_hidden =\",\n \"encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0, 2)\",\n \"= enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim = output_dim self.dropout = dropout self.attention =\",\n \"output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self, encoder, decoder, device): super().__init__() self.encoder = encoder\",\n \"self.decoder = decoder self.device = device def forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size =\",\n \"nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim * 2) + emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in\",\n \"= output_dim self.dropout = dropout self.attention = attention self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn\",\n \"decoder is the <sos> token output = trg[0,:] for t in range(1, max_len):\",\n \"super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in = (enc_hid_dim * 2) +\",\n \"energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim = 2))) attention = torch.sum(energy, dim=2) return\",\n \"0, 2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim = 2))) attention = torch.sum(energy,\",\n \"= src.shape[1] max_len = trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device)\",\n \"emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim = output_dim self.dropout = dropout\",\n \"import torch import torch.nn as nn import torch.optim as optim import torch.nn.functional as\",\n \"teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len = trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs = torch.zeros(max_len,\",\n \"output of bi-directional rnn should be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim =\",\n \"= torch.sum(energy, dim=2) return F.softmax(attention, dim=1) class Decoder(nn.Module): def __init__(self, output_dim, emb_dim, enc_hid_dim,\",\n \"nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional = True) self.fc = nn.Linear(enc_hid_dim *\",\n \"super().__init__() self.input_dim = input_dim self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim\",\n \"Decoder(nn.Module): def __init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__() self.emb_dim = emb_dim\",\n \"= enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in = (enc_hid_dim * 2) + dec_hid_dim self.attn\",\n \"= input_dim self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout =\",\n \"return F.softmax(attention, dim=1) class Decoder(nn.Module): def __init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention):\",\n \"hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1))) return outputs, hidden class Attention(nn.Module): def\",\n \"a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0, 2) weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1,\",\n \"self.out(torch.cat((output, weighted_encoder_rep, embedded), dim = 1)) return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self,\",\n \"import torch.optim as optim import torch.nn.functional as F from torch import Tensor class\",\n \"torch import Tensor class Encoder(nn.Module): def __init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__()\",\n \"= self.decoder.output_dim outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src) # first\",\n \"= dec_hid_dim self.attn_in = (enc_hid_dim * 2) + dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim)\",\n \"= encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs = encoder_outputs.permute(1, 0, 2) energy\",\n \"batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src) # first input to the decoder is\",\n \"output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep, embedded), dim = 1)) return\",\n \"+ dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0]\",\n \"self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout = dropout self.embedding\",\n \"trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src)\",\n \"import torch.nn as nn import torch.optim as optim import torch.nn.functional as F from\",\n \"2, dec_hid_dim) self.dropout = nn.Dropout(dropout) def forward(self, src): embedded = self.dropout(self.embedding(src)) outputs, hidden\",\n \"max_len): output, hidden = self.decoder(output, hidden, encoder_outputs) outputs[t] = output teacher_force = random.random()\",\n \"__init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__() self.emb_dim = emb_dim self.enc_hid_dim =\",\n \"trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len = trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs =\",\n \"import random from typing import Tuple import torch import torch.nn as nn import\",\n \"* 2) + emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout =\",\n \"output = self.out(torch.cat((output, weighted_encoder_rep, embedded), dim = 1)) return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module):\",\n \"decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs = encoder_outputs.permute(1, 0, 2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs),\",\n \"to the decoder is the <sos> token output = trg[0,:] for t in\",\n \"= enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout = dropout self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn\",\n \"random from typing import Tuple import torch import torch.nn as nn import torch.optim\",\n \"self.attention = attention self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim * 2) +\",\n \"hidden = self.rnn(embedded) # output of bi-directional rnn should be concatenated hidden =\",\n \"= dropout self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional = True)\",\n \"torch.optim as optim import torch.nn.functional as F from torch import Tensor class Encoder(nn.Module):\",\n \"teacher_force = random.random() < teacher_forcing_ratio top1 = output.max(1)[1] output = (trg[t] if teacher_force\",\n \"forward(self, decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs =\",\n \"self.rnn(embedded) # output of bi-directional rnn should be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]),\",\n \"emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self,\",\n \"output = output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep, embedded), dim =\",\n \"torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1))) return outputs, hidden class Attention(nn.Module): def __init__(self, enc_hid_dim,\",\n \"self.out = nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs):\",\n \"= 1))) return outputs, hidden class Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__()\",\n \"weighted_encoder_rep, embedded), dim = 1)) return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self, encoder,\",\n \"forward(self, input, decoder_hidden, encoder_outputs): input = input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden,\",\n \"nn import torch.optim as optim import torch.nn.functional as F from torch import Tensor\",\n \"encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep), dim = 2) output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0))\",\n \"as optim import torch.nn.functional as F from torch import Tensor class Encoder(nn.Module): def\",\n \"= 2) output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output = output.squeeze(0)\",\n \"attention self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim * 2) + emb_dim, dec_hid_dim)\",\n \"= encoder_outputs.permute(1, 0, 2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim = 2))) attention\",\n \"nn.Dropout(dropout) def forward(self, src): embedded = self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded) # output\",\n \"teacher_forcing_ratio top1 = output.max(1)[1] output = (trg[t] if teacher_force else top1) return outputs\",\n \"encoder_outputs = encoder_outputs.permute(1, 0, 2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim = 2)))\",\n \"enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in = (enc_hid_dim\",\n \"outputs[t] = output teacher_force = random.random() < teacher_forcing_ratio top1 = output.max(1)[1] output =\",\n \"return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self, encoder, decoder, device): super().__init__() self.encoder =\",\n \"encoder_outputs.permute(1, 0, 2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim = 2))) attention =\",\n \"hidden class Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim\",\n \"optim import torch.nn.functional as F from torch import Tensor class Encoder(nn.Module): def __init__(self,\",\n \"torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep def forward(self, input, decoder_hidden,\",\n \"decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self, encoder, decoder, device): super().__init__() self.encoder = encoder self.decoder\",\n \"enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in = (enc_hid_dim * 2) + dec_hid_dim self.attn =\",\n \"weighted_encoder_rep), dim = 2) output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output\",\n \"= (enc_hid_dim * 2) + dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden,\",\n \"import Tuple import torch import torch.nn as nn import torch.optim as optim import\",\n \"= self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep), dim = 2)\",\n \"<sos> token output = trg[0,:] for t in range(1, max_len): output, hidden =\",\n \"= a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0, 2) weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep =\",\n \"= torch.cat((embedded, weighted_encoder_rep), dim = 2) output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded =\",\n \"self.decoder(output, hidden, encoder_outputs) outputs[t] = output teacher_force = random.random() < teacher_forcing_ratio top1 =\",\n \"the decoder is the <sos> token output = trg[0,:] for t in range(1,\",\n \"emb_dim, output_dim) self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs)\",\n \"2) output, decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep\",\n \"forward(self, src, trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len = trg.shape[0] trg_vocab_size = self.decoder.output_dim\",\n \"2) return weighted_encoder_rep def forward(self, input, decoder_hidden, encoder_outputs): input = input.unsqueeze(0) embedded =\",\n \"rnn should be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1))) return outputs,\",\n \"hidden = self.decoder(output, hidden, encoder_outputs) outputs[t] = output teacher_force = random.random() < teacher_forcing_ratio\",\n \"= dropout self.attention = attention self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim *\",\n \"def __init__(self, encoder, decoder, device): super().__init__() self.encoder = encoder self.decoder = decoder self.device\",\n \"as F from torch import Tensor class Encoder(nn.Module): def __init__(self, input_dim, emb_dim, enc_hid_dim,\",\n \"nn.GRU(emb_dim, enc_hid_dim, bidirectional = True) self.fc = nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout =\",\n \"= decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs = encoder_outputs.permute(1, 0, 2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden,\",\n \"self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional = True) self.fc = nn.Linear(enc_hid_dim * 2, dec_hid_dim)\",\n \"= trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden =\",\n \"t in range(1, max_len): output, hidden = self.decoder(output, hidden, encoder_outputs) outputs[t] = output\",\n \"dim = 1)) return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def __init__(self, encoder, decoder, device):\",\n \"def forward(self, input, decoder_hidden, encoder_outputs): input = input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep =\",\n \"embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep, embedded), dim\",\n \"input, decoder_hidden, encoder_outputs): input = input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs)\",\n \"output = trg[0,:] for t in range(1, max_len): output, hidden = self.decoder(output, hidden,\",\n \"input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep), dim\",\n \"output teacher_force = random.random() < teacher_forcing_ratio top1 = output.max(1)[1] output = (trg[t] if\",\n \"= torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim = 2))) attention = torch.sum(energy, dim=2) return F.softmax(attention,\",\n \"def __init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__() self.emb_dim = emb_dim self.enc_hid_dim\",\n \"a = self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0, 2) weighted_encoder_rep\",\n \"torch.nn as nn import torch.optim as optim import torch.nn.functional as F from torch\",\n \"self.embedding = nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim * 2) + emb_dim, dec_hid_dim) self.out\",\n \"= torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1))) return outputs, hidden class Attention(nn.Module): def __init__(self,\",\n \"= nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout = nn.Dropout(dropout) def forward(self, src): embedded =\",\n \"self.output_dim = output_dim self.dropout = dropout self.attention = attention self.embedding = nn.Embedding(output_dim, emb_dim)\",\n \"class Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim =\",\n \"True) self.fc = nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout = nn.Dropout(dropout) def forward(self, src):\",\n \"= encoder_outputs.permute(1, 0, 2) weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2)\",\n \"self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs) a =\",\n \"of bi-directional rnn should be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1)))\",\n \"dec_hid_dim self.output_dim = output_dim self.dropout = dropout self.attention = attention self.embedding = nn.Embedding(output_dim,\",\n \"max_len = trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden\",\n \"embedded = self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded) # output of bi-directional rnn should\",\n \"< teacher_forcing_ratio top1 = output.max(1)[1] output = (trg[t] if teacher_force else top1) return\",\n \"trg[0,:] for t in range(1, max_len): output, hidden = self.decoder(output, hidden, encoder_outputs) outputs[t]\",\n \"src, trg, teacher_forcing_ratio=0.5): batch_size = src.shape[1] max_len = trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs\",\n \"import torch.nn.functional as F from torch import Tensor class Encoder(nn.Module): def __init__(self, input_dim,\",\n \"__init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.attn_in =\",\n \"def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1) encoder_outputs =\",\n \"encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep def forward(self, input, decoder_hidden, encoder_outputs):\",\n \"dim = 2))) attention = torch.sum(energy, dim=2) return F.softmax(attention, dim=1) class Decoder(nn.Module): def\",\n \"= torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep def forward(self, input,\",\n \"hidden, encoder_outputs) outputs[t] = output teacher_force = random.random() < teacher_forcing_ratio top1 = output.max(1)[1]\",\n \"embedded = self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep), dim =\",\n \"self.encoder = encoder self.decoder = decoder self.device = device def forward(self, src, trg,\",\n \"= nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim, bidirectional = True) self.fc = nn.Linear(enc_hid_dim\",\n \"decoder_hidden = self.rnn(rnn_input, decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0)\",\n \"= self.rnn(embedded) # output of bi-directional rnn should be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:],\",\n \"= self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0, 2) weighted_encoder_rep =\",\n \"2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim = 2))) attention = torch.sum(energy, dim=2)\",\n \"for t in range(1, max_len): output, hidden = self.decoder(output, hidden, encoder_outputs) outputs[t] =\",\n \"# first input to the decoder is the <sos> token output = trg[0,:]\",\n \"def forward(self, decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs\",\n \"bidirectional = True) self.fc = nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout = nn.Dropout(dropout) def\",\n \"1))) return outputs, hidden class Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim\",\n \"Seq2Seq(nn.Module): def __init__(self, encoder, decoder, device): super().__init__() self.encoder = encoder self.decoder = decoder\",\n \"weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep def forward(self, input, decoder_hidden, encoder_outputs): input\",\n \"nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout = nn.Dropout(dropout) def forward(self, src): embedded = self.dropout(self.embedding(src))\",\n \"decoder_hidden.unsqueeze(0)) embedded = embedded.squeeze(0) output = output.squeeze(0) weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output,\",\n \"decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1, 0,\",\n \"from torch import Tensor class Encoder(nn.Module): def __init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout):\",\n \"F from torch import Tensor class Encoder(nn.Module): def __init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim,\",\n \"bi-directional rnn should be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1))) return\",\n \"encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs = encoder_outputs.permute(1, 0,\",\n \"self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.output_dim = output_dim self.dropout\",\n \"= weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep, embedded), dim = 1)) return output, decoder_hidden.squeeze(0)\",\n \"= 2))) attention = torch.sum(energy, dim=2) return F.softmax(attention, dim=1) class Decoder(nn.Module): def __init__(self,\",\n \"= input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded, weighted_encoder_rep),\",\n \"input = input.unsqueeze(0) embedded = self.dropout(self.embedding(input)) weighted_encoder_rep = self._weighted_encoder_rep(decoder_hidden, encoder_outputs) rnn_input = torch.cat((embedded,\",\n \"enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__() self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim =\",\n \"= nn.GRU((enc_hid_dim * 2) + emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in + emb_dim, output_dim)\",\n \"= True) self.fc = nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout = nn.Dropout(dropout) def forward(self,\",\n \"0, 2) weighted_encoder_rep = torch.bmm(a, encoder_outputs) weighted_encoder_rep = weighted_encoder_rep.permute(1, 0, 2) return weighted_encoder_rep\",\n \"= self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded) # output of bi-directional rnn should be\",\n \"outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src) # first input to\",\n \"dim = 1))) return outputs, hidden class Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim):\",\n \"input_dim self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout = dropout\",\n \"super().__init__() self.encoder = encoder self.decoder = decoder self.device = device def forward(self, src,\",\n \"= nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a\",\n \"= emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout = dropout self.embedding =\",\n \"self.rnn = nn.GRU((enc_hid_dim * 2) + emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in + emb_dim,\",\n \"return outputs, hidden class Attention(nn.Module): def __init__(self, enc_hid_dim, dec_hid_dim, attn_dim): super().__init__() self.enc_hid_dim =\",\n \"src): embedded = self.dropout(self.embedding(src)) outputs, hidden = self.rnn(embedded) # output of bi-directional rnn\",\n \"concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1))) return outputs, hidden class Attention(nn.Module):\",\n \"enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim = input_dim self.emb_dim = emb_dim self.enc_hid_dim = enc_hid_dim\",\n \"encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs = encoder_outputs.permute(1, 0, 2) energy =\",\n \"2) + emb_dim, dec_hid_dim) self.out = nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout = nn.Dropout(dropout)\",\n \"nn.Linear(self.attention.attn_in + emb_dim, output_dim) self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a =\",\n \"weighted_encoder_rep = weighted_encoder_rep.squeeze(0) output = self.out(torch.cat((output, weighted_encoder_rep, embedded), dim = 1)) return output,\",\n \"src_len = encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len, 1) encoder_outputs = encoder_outputs.permute(1, 0, 2)\",\n \"F.softmax(attention, dim=1) class Decoder(nn.Module): def __init__(self, output_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout, attention): super().__init__()\",\n \"= nn.Embedding(output_dim, emb_dim) self.rnn = nn.GRU((enc_hid_dim * 2) + emb_dim, dec_hid_dim) self.out =\",\n \"Tensor class Encoder(nn.Module): def __init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim =\",\n \"= self.out(torch.cat((output, weighted_encoder_rep, embedded), dim = 1)) return output, decoder_hidden.squeeze(0) class Seq2Seq(nn.Module): def\",\n \"* 2, dec_hid_dim) self.dropout = nn.Dropout(dropout) def forward(self, src): embedded = self.dropout(self.embedding(src)) outputs,\",\n \"import Tensor class Encoder(nn.Module): def __init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim\",\n \"class Seq2Seq(nn.Module): def __init__(self, encoder, decoder, device): super().__init__() self.encoder = encoder self.decoder =\",\n \"_weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs) a = a.unsqueeze(1) encoder_outputs = encoder_outputs.permute(1,\",\n \"output_dim) self.dropout = nn.Dropout(dropout) def _weighted_encoder_rep(self, decoder_hidden, encoder_outputs): a = self.attention(decoder_hidden, encoder_outputs) a\",\n \"src_len, 1) encoder_outputs = encoder_outputs.permute(1, 0, 2) energy = torch.tanh(self.attn(torch.cat(( repeated_decoder_hidden, encoder_outputs), dim\",\n \"enc_hid_dim, bidirectional = True) self.fc = nn.Linear(enc_hid_dim * 2, dec_hid_dim) self.dropout = nn.Dropout(dropout)\",\n \"return weighted_encoder_rep def forward(self, input, decoder_hidden, encoder_outputs): input = input.unsqueeze(0) embedded = self.dropout(self.embedding(input))\",\n \"self.attn_in = (enc_hid_dim * 2) + dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim) def forward(self,\",\n \"typing import Tuple import torch import torch.nn as nn import torch.optim as optim\",\n \"= dec_hid_dim self.output_dim = output_dim self.dropout = dropout self.attention = attention self.embedding =\",\n \"emb_dim self.enc_hid_dim = enc_hid_dim self.dec_hid_dim = dec_hid_dim self.dropout = dropout self.embedding = nn.Embedding(input_dim,\",\n \"src.shape[1] max_len = trg.shape[0] trg_vocab_size = self.decoder.output_dim outputs = torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs,\",\n \"class Encoder(nn.Module): def __init__(self, input_dim, emb_dim, enc_hid_dim, dec_hid_dim, dropout): super().__init__() self.input_dim = input_dim\",\n \"= self.decoder(output, hidden, encoder_outputs) outputs[t] = output teacher_force = random.random() < teacher_forcing_ratio top1\",\n \"torch.zeros(max_len, batch_size, trg_vocab_size).to(self.device) encoder_outputs, hidden = self.encoder(src) # first input to the decoder\",\n \"= dec_hid_dim self.dropout = dropout self.embedding = nn.Embedding(input_dim, emb_dim) self.rnn = nn.GRU(emb_dim, enc_hid_dim,\",\n \"should be concatenated hidden = torch.tanh(self.fc(torch.cat((hidden[-2,:,:], hidden[-1,:,:]), dim = 1))) return outputs, hidden\",\n \"nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1, src_len,\",\n \"= encoder self.decoder = decoder self.device = device def forward(self, src, trg, teacher_forcing_ratio=0.5):\",\n \"attention = torch.sum(energy, dim=2) return F.softmax(attention, dim=1) class Decoder(nn.Module): def __init__(self, output_dim, emb_dim,\"\n]","isConversational":false}}},{"rowIdx":4590,"cells":{"ngram":{"kind":"list like","value":["to send it to # loss function we want it to be (N,","of shape (trg_len, batch_size, output_dim) but Cross Entropy Loss # doesn't take input","encoder_net = Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device) decoder_net = Decoder( input_size_decoder,","want to have # output to be: (N, 10) and targets just (N).","Tensorboard to get nice loss plot writer = SummaryWriter(f\"runs/loss_plot\") step = 0 train_iterator,","we take the word that the Decoder predicted it to be. # Teacher","encoder_embedding_size = 300 decoder_embedding_size = 300 hidden_size = 1024 # Needs to be","to avoid exploding gradient issues, makes sure grads are # within a healthy","x = x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) # embedding shape: (1, N, embedding_size) outputs,","else \"cpu\") input_size_encoder = len(german.vocab) input_size_decoder = len(english.vocab) output_size = len(english.vocab) encoder_embedding_size =","in into # our cost function, so we need to do some reshapin.","time might be completely different than what the # network is used to.","Teacher Forcing is used so that the model gets used to seeing #","we have output_words * batch_size that we want to send in into #","utils import translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger = spacy.load(\"de\") spacy_eng = spacy.load(\"en\") def","in a similar # way that we have output_words * batch_size that we","but Cross Entropy Loss # doesn't take input in that form. For example","valid_data, test_data = Multi30k.splits( exts=(\".de\", \".en\"), fields=(german, english) ) german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data,","as nn import torch.optim as optim from torchtext.datasets import Multi30k from torchtext.data import","1 # then inputs at test time might be completely different than what","tokenize=tokenize_eng, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\" ) train_data, valid_data, test_data = Multi30k.splits( exts=(\".de\", \".en\"), fields=(german,","__init__( self, input_size, embedding_size, hidden_size, output_size, num_layers, p ): super(Decoder, self).__init__() self.dropout =","1024 # Needs to be the same for both RNN's num_layers = 2","have # output to be: (N, 10) and targets just (N). Here we","comment. x = target[t] if random.random() < teacher_force_ratio else best_guess return outputs ###","(trg_len, batch_size, output_dim) but Cross Entropy Loss # doesn't take input in that","need for training our Seq2Seq model ### # Training hyperparameters num_epochs = 100","the word that the Decoder predicted it to be. # Teacher Forcing is","used to. This was a long comment. x = target[t] if random.random() <","hidden, cell) # Store next output prediction outputs[t] = output # Get the","healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent step optimizer.step() # Plot to tensorboard","pad_idx = english.vocab.stoi[\"<pad>\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\"my_checkpoint.pth.tar\"), model, optimizer) sentence =","step = 0 train_iterator, valid_iterator, test_iterator = BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True,","print(f\"Translated example sentence: \\n {translated_sentence}\") model.train() for batch_idx, batch in enumerate(train_iterator): # Get","return [tok.text for tok in spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text for tok in","hidden_size self.num_layers = num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers,","it to # loss function we want it to be (N, length_target_vocabulary) so","= nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc = nn.Linear(hidden_size, output_size)","cell = self.decoder(x, hidden, cell) # Store next output prediction outputs[t] = output","we need to do some reshapin. While we're at it # Let's also","max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module): def __init__(self, input_size, embedding_size, hidden_size, num_layers,","and testing time, if teacher forcing is 1 # then inputs at test","ready to define everything we need for training our Seq2Seq model ### #","gradient issues, makes sure grads are # within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1)","cell as context from encoder at start output, hidden, cell = self.decoder(x, hidden,","loss function we want it to be (N, length_target_vocabulary) so we're # just","training and testing time, if teacher forcing is 1 # then inputs at","in that form. For example if we have MNIST we want to have","and targets and get to cuda inp_data = batch.src.to(device) target = batch.trg.to(device) #","want it to be (1, N), seq_length # is 1 here because we","= source.shape[1] target_len = target.shape[0] target_vocab_size = len(english.vocab) outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device)","(hidden, cell) = self.rnn(embedding, (hidden, cell)) # outputs shape: (1, N, hidden_size) predictions","spacy import random from torch.utils.tensorboard import SummaryWriter # to print to tensorboard from","= nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def forward(self, x): #","enc_dropout = 0.5 dec_dropout = 0.5 # Tensorboard to get nice loss plot","hidden_size, num_layers, dropout=p) self.fc = nn.Linear(hidden_size, output_size) def forward(self, x, hidden, cell): #","the Decoder which will be <SOS> token x = target[0] for t in","in range(num_epochs): print(f\"[Epoch {epoch} / {num_epochs}]\") checkpoint = {\"state_dict\": model.state_dict(), \"optimizer\": optimizer.state_dict()} save_checkpoint(checkpoint)","we have MNIST we want to have # output to be: (N, 10)","Needs to be the same for both RNN's num_layers = 2 enc_dropout =","the start token while we're at it output = output[1:].reshape(-1, output.shape[2]) target =","for epoch in range(num_epochs): print(f\"[Epoch {epoch} / {num_epochs}]\") checkpoint = {\"state_dict\": model.state_dict(), \"optimizer\":","# our cost function, so we need to do some reshapin. While we're","= nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn","\"cpu\") input_size_encoder = len(german.vocab) input_size_decoder = len(english.vocab) output_size = len(english.vocab) encoder_embedding_size = 300","are sending in a single word and not a sentence x = x.unsqueeze(0)","input_size_decoder = len(english.vocab) output_size = len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size = 300 hidden_size","# just gonna remove the first dim predictions = predictions.squeeze(0) return predictions, hidden,","at it output = output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output,","torch import torch.nn as nn import torch.optim as optim from torchtext.datasets import Multi30k","shape: (seq_length, N) where N is batch size embedding = self.dropout(self.embedding(x)) # embedding","length_target_vocabulary) to send it to # loss function we want it to be","Get the best word the Decoder predicted (index in the vocabulary) best_guess =","shape: (seq_length, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding) # outputs shape: (seq_length,","# then inputs at test time might be completely different than what the","epoch in range(num_epochs): print(f\"[Epoch {epoch} / {num_epochs}]\") checkpoint = {\"state_dict\": model.state_dict(), \"optimizer\": optimizer.state_dict()}","= Field(tokenize=tokenize_ger, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\") english = Field( tokenize=tokenize_eng, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\" )","previous hidden, cell as context from encoder at start output, hidden, cell =","embedding_size) outputs, (hidden, cell) = self.rnn(embedding) # outputs shape: (seq_length, N, hidden_size) return","input_size_encoder = len(german.vocab) input_size_decoder = len(english.vocab) output_size = len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size","output = model(inp_data, target) # Output is of shape (trg_len, batch_size, output_dim) but","model(inp_data, target) # Output is of shape (trg_len, batch_size, output_dim) but Cross Entropy","issues, makes sure grads are # within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) #","word and not a sentence x = x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) # embedding","= x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) # embedding shape: (1, N, embedding_size) outputs, (hidden,","Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device) decoder_net = Decoder( input_size_decoder, decoder_embedding_size, hidden_size,","exts=(\".de\", \".en\"), fields=(german, english) ) german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module):","save_checkpoint, load_checkpoint spacy_ger = spacy.load(\"de\") spacy_eng = spacy.load(\"en\") def tokenize_ger(text): return [tok.text for","target, teacher_force_ratio=0.5): batch_size = source.shape[1] target_len = target.shape[0] target_vocab_size = len(english.vocab) outputs =","load_checkpoint(torch.load(\"my_checkpoint.pth.tar\"), model, optimizer) sentence = \"ein boot mit mehreren männern darauf wird von","sentence: \\n {translated_sentence}\") model.train() for batch_idx, batch in enumerate(train_iterator): # Get input and","= 0.5 dec_dropout = 0.5 # Tensorboard to get nice loss plot writer","not a sentence x = x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) # embedding shape: (1,","torchtext.data import Field, BucketIterator import numpy as np import spacy import random from","hidden, cell = self.encoder(source) # Grab the first input to the Decoder which","prop output = model(inp_data, target) # Output is of shape (trg_len, batch_size, output_dim)","output to be: (N, 10) and targets just (N). Here we can view","import torch.nn as nn import torch.optim as optim from torchtext.datasets import Multi30k from","is used so that the model gets used to seeing # similar inputs","define everything we need for training our Seq2Seq model ### # Training hyperparameters","batch_idx, batch in enumerate(train_iterator): # Get input and targets and get to cuda","it to be (1, N), seq_length # is 1 here because we are","sentence x = x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) # embedding shape: (1, N, embedding_size)","we're at it # Let's also remove the start token while we're at","batch_size, output_dim) but Cross Entropy Loss # doesn't take input in that form.","sending in a single word and not a sentence x = x.unsqueeze(0) embedding","= len(english.vocab) output_size = len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size = 300 hidden_size =","(hidden, cell)) # outputs shape: (1, N, hidden_size) predictions = self.fc(outputs) # predictions","num_layers, dec_dropout, ).to(device) model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx =","output_size) def forward(self, x, hidden, cell): # x shape: (N) where N is","to be (N, length_target_vocabulary) so we're # just gonna remove the first dim","(N, 10) and targets just (N). Here we can view it in a","from torchtext.datasets import Multi30k from torchtext.data import Field, BucketIterator import numpy as np","target_vocab_size = len(english.vocab) outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell = self.encoder(source) #","model.eval() translated_sentence = translate_sentence( model, sentence, german, english, device, max_length=50 ) print(f\"Translated example","the Decoder predicted it to be. # Teacher Forcing is used so that","dec_dropout, ).to(device) model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\"<pad>\"]","= target.shape[0] target_vocab_size = len(english.vocab) outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell =",") encoder_net = Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device) decoder_net = Decoder(","english, device, max_length=50 ) print(f\"Translated example sentence: \\n {translated_sentence}\") model.train() for batch_idx, batch","cell): # x shape: (N) where N is for batch size, we want","similar inputs at training and testing time, if teacher forcing is 1 #","encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device) decoder_net = Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers,",").to(device) model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\"<pad>\"] criterion","= model(inp_data, target) # Output is of shape (trg_len, batch_size, output_dim) but Cross","send in into # our cost function, so we need to do some","= 64 # Model hyperparameters load_model = False device = torch.device(\"cuda\" if torch.cuda.is_available()","= torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell = self.encoder(source) # Grab the first input","Multi30k.splits( exts=(\".de\", \".en\"), fields=(german, english) ) german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class","embedding = self.dropout(self.embedding(x)) # embedding shape: (1, N, embedding_size) outputs, (hidden, cell) =","= self.dropout(self.embedding(x)) # embedding shape: (1, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding,","= hidden_size self.num_layers = num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size,","model ### # Training hyperparameters num_epochs = 100 learning_rate = 0.001 batch_size =","batch_size = 64 # Model hyperparameters load_model = False device = torch.device(\"cuda\" if","step optimizer.step() # Plot to tensorboard writer.add_scalar(\"Training loss\", loss, global_step=step) step += 1","torch.optim as optim from torchtext.datasets import Multi30k from torchtext.data import Field, BucketIterator import","num_layers, dropout=p) def forward(self, x): # x shape: (seq_length, N) where N is","(train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src), device=device, ) encoder_net = Encoder(","predictions = predictions.squeeze(0) return predictions, hidden, cell class Seq2Seq(nn.Module): def __init__(self, encoder, decoder):","translate_sentence( model, sentence, german, english, device, max_length=50 ) print(f\"Translated example sentence: \\n {translated_sentence}\")","lower=True, init_token=\"<sos>\", eos_token=\"<eos>\") english = Field( tokenize=tokenize_eng, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\" ) train_data, valid_data,","criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\"my_checkpoint.pth.tar\"), model, optimizer) sentence = \"ein boot mit","lr=learning_rate) pad_idx = english.vocab.stoi[\"<pad>\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\"my_checkpoint.pth.tar\"), model, optimizer) sentence","hidden_size, num_layers, dropout=p) def forward(self, x): # x shape: (seq_length, N) where N","at start output, hidden, cell = self.decoder(x, hidden, cell) # Store next output","= nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\"my_checkpoint.pth.tar\"), model, optimizer) sentence = \"ein boot mit mehreren","form. For example if we have MNIST we want to have # output","loss.backward() # Clip to avoid exploding gradient issues, makes sure grads are #","english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module): def __init__(self, input_size, embedding_size, hidden_size, num_layers, p): super(Encoder,","0.5 dec_dropout = 0.5 # Tensorboard to get nice loss plot writer =","we're # just gonna remove the first dim predictions = predictions.squeeze(0) return predictions,","optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\"<pad>\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\"my_checkpoint.pth.tar\"),","exploding gradient issues, makes sure grads are # within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(),","range(num_epochs): print(f\"[Epoch {epoch} / {num_epochs}]\") checkpoint = {\"state_dict\": model.state_dict(), \"optimizer\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval()","# Needs to be the same for both RNN's num_layers = 2 enc_dropout","bleu, save_checkpoint, load_checkpoint spacy_ger = spacy.load(\"de\") spacy_eng = spacy.load(\"en\") def tokenize_ger(text): return [tok.text","cell) = self.rnn(embedding, (hidden, cell)) # outputs shape: (1, N, hidden_size) predictions =","for tok in spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text for tok in spacy_eng.tokenizer(text)] german","english = Field( tokenize=tokenize_eng, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\" ) train_data, valid_data, test_data = Multi30k.splits(","a single word and not a sentence x = x.unsqueeze(0) embedding = self.dropout(self.embedding(x))","load_model: load_checkpoint(torch.load(\"my_checkpoint.pth.tar\"), model, optimizer) sentence = \"ein boot mit mehreren männern darauf wird","output_words * batch_size that we want to send in into # our cost","self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc = nn.Linear(hidden_size,","be completely different than what the # network is used to. This was","a long comment. x = target[t] if random.random() < teacher_force_ratio else best_guess return","x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) # embedding shape: (1, N, embedding_size) outputs, (hidden, cell)","shape: (1, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding, (hidden, cell)) # outputs","that the Decoder predicted it to be. # Teacher Forcing is used so","= \"ein boot mit mehreren männern darauf wird von einem großen pferdegespann ans","self.fc = nn.Linear(hidden_size, output_size) def forward(self, x, hidden, cell): # x shape: (N)","return hidden, cell class Decoder(nn.Module): def __init__( self, input_size, embedding_size, hidden_size, output_size, num_layers,","super(Seq2Seq, self).__init__() self.encoder = encoder self.decoder = decoder def forward(self, source, target, teacher_force_ratio=0.5):","sort_within_batch=True, sort_key=lambda x: len(x.src), device=device, ) encoder_net = Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers,","function, so we need to do some reshapin. While we're at it #","and targets just (N). Here we can view it in a similar #","männern darauf wird von einem großen pferdegespann ans ufer gezogen.\" for epoch in","while we're at it output = output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad() loss","def tokenize_eng(text): return [tok.text for tok in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True, init_token=\"<sos>\",","num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def forward(self,","class Seq2Seq(nn.Module): def __init__(self, encoder, decoder): super(Seq2Seq, self).__init__() self.encoder = encoder self.decoder =","hidden, cell class Decoder(nn.Module): def __init__( self, input_size, embedding_size, hidden_size, output_size, num_layers, p","input to the Decoder which will be <SOS> token x = target[0] for","hidden_size, output_size, num_layers, p ): super(Decoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size","self.encoder(source) # Grab the first input to the Decoder which will be <SOS>","the first input to the Decoder which will be <SOS> token x =","= BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src), device=device, ) encoder_net","batch_size that we want to send in into # our cost function, so","decoder_net = Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout, ).to(device) model = Seq2Seq(encoder_net,","batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src), device=device, ) encoder_net = Encoder( input_size_encoder, encoder_embedding_size, hidden_size,","hidden_size, num_layers, p): super(Encoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers =","batch size embedding = self.dropout(self.embedding(x)) # embedding shape: (seq_length, N, embedding_size) outputs, (hidden,","the # network is used to. This was a long comment. x =","# Forward prop output = model(inp_data, target) # Output is of shape (trg_len,","input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device) decoder_net = Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size,","to be. # Teacher Forcing is used so that the model gets used","# x shape: (N) where N is for batch size, we want it","torch.nn as nn import torch.optim as optim from torchtext.datasets import Multi30k from torchtext.data","Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\"<pad>\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if","best word the Decoder predicted (index in the vocabulary) best_guess = output.argmax(1) #","Multi30k from torchtext.data import Field, BucketIterator import numpy as np import spacy import","super(Decoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers self.embedding =","word # otherwise we take the word that the Decoder predicted it to","inp_data = batch.src.to(device) target = batch.trg.to(device) # Forward prop output = model(inp_data, target)","num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc =","save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence( model, sentence, german, english, device, max_length=50 ) print(f\"Translated","output_size, num_layers, dec_dropout, ).to(device) model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx","self.dropout(self.embedding(x)) # embedding shape: (seq_length, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding) #","N) where N is batch size embedding = self.dropout(self.embedding(x)) # embedding shape: (seq_length,","word the Decoder predicted (index in the vocabulary) best_guess = output.argmax(1) # With","targets and get to cuda inp_data = batch.src.to(device) target = batch.trg.to(device) # Forward","Let's also remove the start token while we're at it output = output[1:].reshape(-1,","we want it to be (N, length_target_vocabulary) so we're # just gonna remove","we want it to be (1, N), seq_length # is 1 here because","the vocabulary) best_guess = output.argmax(1) # With probability of teacher_force_ratio we take the","if we have MNIST we want to have # output to be: (N,","are # within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent step optimizer.step()","to seeing # similar inputs at training and testing time, if teacher forcing","if teacher forcing is 1 # then inputs at test time might be","best_guess return outputs ### We're ready to define everything we need for training","import torch import torch.nn as nn import torch.optim as optim from torchtext.datasets import","predictions = self.fc(outputs) # predictions shape: (1, N, length_target_vocabulary) to send it to","predicted (index in the vocabulary) best_guess = output.argmax(1) # With probability of teacher_force_ratio","def forward(self, x, hidden, cell): # x shape: (N) where N is for","hidden_size, output_size, num_layers, dec_dropout, ).to(device) model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate)","N is for batch size, we want it to be (1, N), seq_length","will be <SOS> token x = target[0] for t in range(1, target_len): #","writer.add_scalar(\"Training loss\", loss, global_step=step) step += 1 score = bleu(test_data[1:100], model, german, english,","used so that the model gets used to seeing # similar inputs at","embedding = self.dropout(self.embedding(x)) # embedding shape: (seq_length, N, embedding_size) outputs, (hidden, cell) =","batch_size, target_vocab_size).to(device) hidden, cell = self.encoder(source) # Grab the first input to the","{num_epochs}]\") checkpoint = {\"state_dict\": model.state_dict(), \"optimizer\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence( model,","range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent step optimizer.step() # Plot to tensorboard writer.add_scalar(\"Training","Seq2Seq(nn.Module): def __init__(self, encoder, decoder): super(Seq2Seq, self).__init__() self.encoder = encoder self.decoder = decoder","We're ready to define everything we need for training our Seq2Seq model ###","self.fc(outputs) # predictions shape: (1, N, length_target_vocabulary) to send it to # loss","for batch_idx, batch in enumerate(train_iterator): # Get input and targets and get to","fields=(german, english) ) german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module): def __init__(self,","predictions, hidden, cell class Seq2Seq(nn.Module): def __init__(self, encoder, decoder): super(Seq2Seq, self).__init__() self.encoder =","= encoder self.decoder = decoder def forward(self, source, target, teacher_force_ratio=0.5): batch_size = source.shape[1]","Get input and targets and get to cuda inp_data = batch.src.to(device) target =","self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def forward(self, x):","num_layers, dropout=p) self.fc = nn.Linear(hidden_size, output_size) def forward(self, x, hidden, cell): # x","different than what the # network is used to. This was a long","was a long comment. x = target[t] if random.random() < teacher_force_ratio else best_guess","return predictions, hidden, cell class Seq2Seq(nn.Module): def __init__(self, encoder, decoder): super(Seq2Seq, self).__init__() self.encoder","way that we have output_words * batch_size that we want to send in","than what the # network is used to. This was a long comment.","sentence, german, english, device, max_length=50 ) print(f\"Translated example sentence: \\n {translated_sentence}\") model.train() for","embedding_size, hidden_size, num_layers, p): super(Encoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers","from torch.utils.tensorboard import SummaryWriter # to print to tensorboard from utils import translate_sentence,","import random from torch.utils.tensorboard import SummaryWriter # to print to tensorboard from utils","spacy.load(\"de\") spacy_eng = spacy.load(\"en\") def tokenize_ger(text): return [tok.text for tok in spacy_ger.tokenizer(text)] def","target[0] for t in range(1, target_len): # Use previous hidden, cell as context","= nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc = nn.Linear(hidden_size, output_size) def forward(self, x, hidden,","Use previous hidden, cell as context from encoder at start output, hidden, cell","# With probability of teacher_force_ratio we take the actual next word # otherwise","x = target[0] for t in range(1, target_len): # Use previous hidden, cell","model.state_dict(), \"optimizer\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence( model, sentence, german, english, device,","example sentence: \\n {translated_sentence}\") model.train() for batch_idx, batch in enumerate(train_iterator): # Get input","similar # way that we have output_words * batch_size that we want to","output, hidden, cell = self.decoder(x, hidden, cell) # Store next output prediction outputs[t]","in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\") english = Field( tokenize=tokenize_eng, lower=True,","x, hidden, cell): # x shape: (N) where N is for batch size,","= self.rnn(embedding, (hidden, cell)) # outputs shape: (1, N, hidden_size) predictions = self.fc(outputs)","to be: (N, 10) and targets just (N). Here we can view it","max_norm=1) # Gradient descent step optimizer.step() # Plot to tensorboard writer.add_scalar(\"Training loss\", loss,","encoder self.decoder = decoder def forward(self, source, target, teacher_force_ratio=0.5): batch_size = source.shape[1] target_len","cell class Decoder(nn.Module): def __init__( self, input_size, embedding_size, hidden_size, output_size, num_layers, p ):","# Let's also remove the start token while we're at it output =","both RNN's num_layers = 2 enc_dropout = 0.5 dec_dropout = 0.5 # Tensorboard","embedding shape: (1, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding, (hidden, cell)) #","self, input_size, embedding_size, hidden_size, output_size, num_layers, p ): super(Decoder, self).__init__() self.dropout = nn.Dropout(p)","self.dropout(self.embedding(x)) # embedding shape: (1, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding, (hidden,","english.vocab.stoi[\"<pad>\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\"my_checkpoint.pth.tar\"), model, optimizer) sentence = \"ein boot","example if we have MNIST we want to have # output to be:","in enumerate(train_iterator): # Get input and targets and get to cuda inp_data =","we need for training our Seq2Seq model ### # Training hyperparameters num_epochs =","view it in a similar # way that we have output_words * batch_size","torch.utils.tensorboard import SummaryWriter # to print to tensorboard from utils import translate_sentence, bleu,","0.001 batch_size = 64 # Model hyperparameters load_model = False device = torch.device(\"cuda\"","self.encoder = encoder self.decoder = decoder def forward(self, source, target, teacher_force_ratio=0.5): batch_size =","# embedding shape: (seq_length, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding) # outputs","so we're # just gonna remove the first dim predictions = predictions.squeeze(0) return","seeing # similar inputs at training and testing time, if teacher forcing is","it to be. # Teacher Forcing is used so that the model gets","need to do some reshapin. While we're at it # Let's also remove","Back prop loss.backward() # Clip to avoid exploding gradient issues, makes sure grads","Decoder predicted it to be. # Teacher Forcing is used so that the","nice loss plot writer = SummaryWriter(f\"runs/loss_plot\") step = 0 train_iterator, valid_iterator, test_iterator =","spacy.load(\"en\") def tokenize_ger(text): return [tok.text for tok in spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text","where N is for batch size, we want it to be (1, N),","and not a sentence x = x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) # embedding shape:","length_target_vocabulary) so we're # just gonna remove the first dim predictions = predictions.squeeze(0)","cell class Seq2Seq(nn.Module): def __init__(self, encoder, decoder): super(Seq2Seq, self).__init__() self.encoder = encoder self.decoder","start output, hidden, cell = self.decoder(x, hidden, cell) # Store next output prediction","target_len = target.shape[0] target_vocab_size = len(english.vocab) outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell","random from torch.utils.tensorboard import SummaryWriter # to print to tensorboard from utils import","# Teacher Forcing is used so that the model gets used to seeing","completely different than what the # network is used to. This was a","to have # output to be: (N, 10) and targets just (N). Here","target) # Output is of shape (trg_len, batch_size, output_dim) but Cross Entropy Loss","hidden, cell): # x shape: (N) where N is for batch size, we","it output = output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output, target)","for batch size, we want it to be (1, N), seq_length # is","x = target[t] if random.random() < teacher_force_ratio else best_guess return outputs ### We're","= optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\"<pad>\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\"my_checkpoint.pth.tar\"), model,","checkpoint = {\"state_dict\": model.state_dict(), \"optimizer\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence( model, sentence,","translated_sentence = translate_sentence( model, sentence, german, english, device, max_length=50 ) print(f\"Translated example sentence:","just (N). Here we can view it in a similar # way that","= self.dropout(self.embedding(x)) # embedding shape: (seq_length, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding)","Forcing is used so that the model gets used to seeing # similar","False device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\") input_size_encoder = len(german.vocab) input_size_decoder =","boot mit mehreren männern darauf wird von einem großen pferdegespann ans ufer gezogen.\"","= SummaryWriter(f\"runs/loss_plot\") step = 0 train_iterator, valid_iterator, test_iterator = BucketIterator.splits( (train_data, valid_data, test_data),","Here we can view it in a similar # way that we have","loss, global_step=step) step += 1 score = bleu(test_data[1:100], model, german, english, device) print(f\"Bleu","to # loss function we want it to be (N, length_target_vocabulary) so we're","grads are # within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent step","source.shape[1] target_len = target.shape[0] target_vocab_size = len(english.vocab) outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden,","self.rnn(embedding) # outputs shape: (seq_length, N, hidden_size) return hidden, cell class Decoder(nn.Module): def","source, target, teacher_force_ratio=0.5): batch_size = source.shape[1] target_len = target.shape[0] target_vocab_size = len(english.vocab) outputs","if torch.cuda.is_available() else \"cpu\") input_size_encoder = len(german.vocab) input_size_decoder = len(english.vocab) output_size = len(english.vocab)","t in range(1, target_len): # Use previous hidden, cell as context from encoder","2 enc_dropout = 0.5 dec_dropout = 0.5 # Tensorboard to get nice loss","embedding_size) outputs, (hidden, cell) = self.rnn(embedding, (hidden, cell)) # outputs shape: (1, N,","train_data, valid_data, test_data = Multi30k.splits( exts=(\".de\", \".en\"), fields=(german, english) ) german.build_vocab(train_data, max_size=10000, min_freq=2)","enc_dropout ).to(device) decoder_net = Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout, ).to(device) model","= batch.src.to(device) target = batch.trg.to(device) # Forward prop output = model(inp_data, target) #","optimizer.zero_grad() loss = criterion(output, target) # Back prop loss.backward() # Clip to avoid","= target[0] for t in range(1, target_len): # Use previous hidden, cell as","mit mehreren männern darauf wird von einem großen pferdegespann ans ufer gezogen.\" for","= num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def","the actual next word # otherwise we take the word that the Decoder","Plot to tensorboard writer.add_scalar(\"Training loss\", loss, global_step=step) step += 1 score = bleu(test_data[1:100],","global_step=step) step += 1 score = bleu(test_data[1:100], model, german, english, device) print(f\"Bleu score","Clip to avoid exploding gradient issues, makes sure grads are # within a","hyperparameters num_epochs = 100 learning_rate = 0.001 batch_size = 64 # Model hyperparameters","doesn't take input in that form. For example if we have MNIST we","that form. For example if we have MNIST we want to have #","test_iterator = BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src), device=device, )","großen pferdegespann ans ufer gezogen.\" for epoch in range(num_epochs): print(f\"[Epoch {epoch} / {num_epochs}]\")","BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src), device=device, ) encoder_net =","outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell = self.encoder(source) # Grab the first","want it to be (N, length_target_vocabulary) so we're # just gonna remove the","of teacher_force_ratio we take the actual next word # otherwise we take the","reshapin. While we're at it # Let's also remove the start token while","= output # Get the best word the Decoder predicted (index in the","spacy_eng = spacy.load(\"en\") def tokenize_ger(text): return [tok.text for tok in spacy_ger.tokenizer(text)] def tokenize_eng(text):","Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout, ).to(device) model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer","Forward prop output = model(inp_data, target) # Output is of shape (trg_len, batch_size,","output # Get the best word the Decoder predicted (index in the vocabulary)",") print(f\"Translated example sentence: \\n {translated_sentence}\") model.train() for batch_idx, batch in enumerate(train_iterator): #","import torch.optim as optim from torchtext.datasets import Multi30k from torchtext.data import Field, BucketIterator","load_checkpoint spacy_ger = spacy.load(\"de\") spacy_eng = spacy.load(\"en\") def tokenize_ger(text): return [tok.text for tok","): super(Decoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers self.embedding","is of shape (trg_len, batch_size, output_dim) but Cross Entropy Loss # doesn't take","prop loss.backward() # Clip to avoid exploding gradient issues, makes sure grads are","= output.argmax(1) # With probability of teacher_force_ratio we take the actual next word","import spacy import random from torch.utils.tensorboard import SummaryWriter # to print to tensorboard","hidden_size, num_layers, enc_dropout ).to(device) decoder_net = Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout,","= output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output, target) # Back","as optim from torchtext.datasets import Multi30k from torchtext.data import Field, BucketIterator import numpy","german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module): def __init__(self, input_size, embedding_size, hidden_size,","predictions shape: (1, N, length_target_vocabulary) to send it to # loss function we","hidden, cell as context from encoder at start output, hidden, cell = self.decoder(x,","model gets used to seeing # similar inputs at training and testing time,","encoder at start output, hidden, cell = self.decoder(x, hidden, cell) # Store next","0.5 # Tensorboard to get nice loss plot writer = SummaryWriter(f\"runs/loss_plot\") step =","be: (N, 10) and targets just (N). Here we can view it in","token x = target[0] for t in range(1, target_len): # Use previous hidden,","outputs shape: (seq_length, N, hidden_size) return hidden, cell class Decoder(nn.Module): def __init__( self,","cell)) # outputs shape: (1, N, hidden_size) predictions = self.fc(outputs) # predictions shape:","a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent step optimizer.step() # Plot to","While we're at it # Let's also remove the start token while we're","print to tensorboard from utils import translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger = spacy.load(\"de\")","batch_size = source.shape[1] target_len = target.shape[0] target_vocab_size = len(english.vocab) outputs = torch.zeros(target_len, batch_size,","= Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device) decoder_net = Decoder( input_size_decoder, decoder_embedding_size,","to print to tensorboard from utils import translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger =","self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc = nn.Linear(hidden_size, output_size) def forward(self, x,","# Get the best word the Decoder predicted (index in the vocabulary) best_guess","do some reshapin. While we're at it # Let's also remove the start","For example if we have MNIST we want to have # output to","input_size, embedding_size, hidden_size, output_size, num_layers, p ): super(Decoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size","test_data = Multi30k.splits( exts=(\".de\", \".en\"), fields=(german, english) ) german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000,","N, hidden_size) return hidden, cell class Decoder(nn.Module): def __init__( self, input_size, embedding_size, hidden_size,","dropout=p) def forward(self, x): # x shape: (seq_length, N) where N is batch","# Use previous hidden, cell as context from encoder at start output, hidden,","and get to cuda inp_data = batch.src.to(device) target = batch.trg.to(device) # Forward prop","so we need to do some reshapin. While we're at it # Let's","= Field( tokenize=tokenize_eng, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\" ) train_data, valid_data, test_data = Multi30k.splits( exts=(\".de\",","num_layers, enc_dropout ).to(device) decoder_net = Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout, ).to(device)","for training our Seq2Seq model ### # Training hyperparameters num_epochs = 100 learning_rate","english) ) german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module): def __init__(self, input_size,","long comment. x = target[t] if random.random() < teacher_force_ratio else best_guess return outputs","target.shape[0] target_vocab_size = len(english.vocab) outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell = self.encoder(source)","we're at it output = output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad() loss =","{translated_sentence}\") model.train() for batch_idx, batch in enumerate(train_iterator): # Get input and targets and","import numpy as np import spacy import random from torch.utils.tensorboard import SummaryWriter #","output.argmax(1) # With probability of teacher_force_ratio we take the actual next word #","Decoder predicted (index in the vocabulary) best_guess = output.argmax(1) # With probability of","self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers self.embedding = nn.Embedding(input_size,","get to cuda inp_data = batch.src.to(device) target = batch.trg.to(device) # Forward prop output","which will be <SOS> token x = target[0] for t in range(1, target_len):","as np import spacy import random from torch.utils.tensorboard import SummaryWriter # to print","N, hidden_size) predictions = self.fc(outputs) # predictions shape: (1, N, length_target_vocabulary) to send","torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell = self.encoder(source) # Grab the first input to","then inputs at test time might be completely different than what the #","self.decoder = decoder def forward(self, source, target, teacher_force_ratio=0.5): batch_size = source.shape[1] target_len =","# Model hyperparameters load_model = False device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")","dec_dropout = 0.5 # Tensorboard to get nice loss plot writer = SummaryWriter(f\"runs/loss_plot\")","device=device, ) encoder_net = Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device) decoder_net =","to cuda inp_data = batch.src.to(device) target = batch.trg.to(device) # Forward prop output =","gets used to seeing # similar inputs at training and testing time, if","# predictions shape: (1, N, length_target_vocabulary) to send it to # loss function","first dim predictions = predictions.squeeze(0) return predictions, hidden, cell class Seq2Seq(nn.Module): def __init__(self,","N), seq_length # is 1 here because we are sending in a single","(1, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding, (hidden, cell)) # outputs shape:","x: len(x.src), device=device, ) encoder_net = Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device)","training our Seq2Seq model ### # Training hyperparameters num_epochs = 100 learning_rate =","eos_token=\"<eos>\" ) train_data, valid_data, test_data = Multi30k.splits( exts=(\".de\", \".en\"), fields=(german, english) ) german.build_vocab(train_data,","tok in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\") english = Field( tokenize=tokenize_eng,","= english.vocab.stoi[\"<pad>\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\"my_checkpoint.pth.tar\"), model, optimizer) sentence = \"ein","N is batch size embedding = self.dropout(self.embedding(x)) # embedding shape: (seq_length, N, embedding_size)","to get nice loss plot writer = SummaryWriter(f\"runs/loss_plot\") step = 0 train_iterator, valid_iterator,","decoder): super(Seq2Seq, self).__init__() self.encoder = encoder self.decoder = decoder def forward(self, source, target,","test time might be completely different than what the # network is used","hidden_size) return hidden, cell class Decoder(nn.Module): def __init__( self, input_size, embedding_size, hidden_size, output_size,","hidden, cell class Seq2Seq(nn.Module): def __init__(self, encoder, decoder): super(Seq2Seq, self).__init__() self.encoder = encoder","= 1024 # Needs to be the same for both RNN's num_layers =","= 0.5 # Tensorboard to get nice loss plot writer = SummaryWriter(f\"runs/loss_plot\") step","be (1, N), seq_length # is 1 here because we are sending in","criterion(output, target) # Back prop loss.backward() # Clip to avoid exploding gradient issues,","for t in range(1, target_len): # Use previous hidden, cell as context from","as context from encoder at start output, hidden, cell = self.decoder(x, hidden, cell)","/ {num_epochs}]\") checkpoint = {\"state_dict\": model.state_dict(), \"optimizer\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence(","SummaryWriter # to print to tensorboard from utils import translate_sentence, bleu, save_checkpoint, load_checkpoint","p): super(Encoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers self.embedding","so that the model gets used to seeing # similar inputs at training","forcing is 1 # then inputs at test time might be completely different","valid_iterator, test_iterator = BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src), device=device,","outputs, (hidden, cell) = self.rnn(embedding) # outputs shape: (seq_length, N, hidden_size) return hidden,","we are sending in a single word and not a sentence x =","einem großen pferdegespann ans ufer gezogen.\" for epoch in range(num_epochs): print(f\"[Epoch {epoch} /","gezogen.\" for epoch in range(num_epochs): print(f\"[Epoch {epoch} / {num_epochs}]\") checkpoint = {\"state_dict\": model.state_dict(),","With probability of teacher_force_ratio we take the actual next word # otherwise we","# doesn't take input in that form. For example if we have MNIST","10) and targets just (N). Here we can view it in a similar","loss = criterion(output, target) # Back prop loss.backward() # Clip to avoid exploding","have MNIST we want to have # output to be: (N, 10) and","if random.random() < teacher_force_ratio else best_guess return outputs ### We're ready to define","shape: (1, N, hidden_size) predictions = self.fc(outputs) # predictions shape: (1, N, length_target_vocabulary)","to define everything we need for training our Seq2Seq model ### # Training","output = output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output, target) #","input and targets and get to cuda inp_data = batch.src.to(device) target = batch.trg.to(device)","can view it in a similar # way that we have output_words *","predicted it to be. # Teacher Forcing is used so that the model","torch.cuda.is_available() else \"cpu\") input_size_encoder = len(german.vocab) input_size_decoder = len(english.vocab) output_size = len(english.vocab) encoder_embedding_size","# Output is of shape (trg_len, batch_size, output_dim) but Cross Entropy Loss #","= self.fc(outputs) # predictions shape: (1, N, length_target_vocabulary) to send it to #","\"optimizer\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence( model, sentence, german, english, device, max_length=50","device, max_length=50 ) print(f\"Translated example sentence: \\n {translated_sentence}\") model.train() for batch_idx, batch in","<filename>ML/Pytorch/more_advanced/Seq2Seq/seq2seq.py<gh_stars>1000+ import torch import torch.nn as nn import torch.optim as optim from torchtext.datasets","# Plot to tensorboard writer.add_scalar(\"Training loss\", loss, global_step=step) step += 1 score =","target = batch.trg.to(device) # Forward prop output = model(inp_data, target) # Output is","tensorboard writer.add_scalar(\"Training loss\", loss, global_step=step) step += 1 score = bleu(test_data[1:100], model, german,","a similar # way that we have output_words * batch_size that we want","writer = SummaryWriter(f\"runs/loss_plot\") step = 0 train_iterator, valid_iterator, test_iterator = BucketIterator.splits( (train_data, valid_data,",").to(device) decoder_net = Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout, ).to(device) model =","targets just (N). Here we can view it in a similar # way","cell = self.encoder(source) # Grab the first input to the Decoder which will","teacher forcing is 1 # then inputs at test time might be completely","optim from torchtext.datasets import Multi30k from torchtext.data import Field, BucketIterator import numpy as","self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers self.embedding = nn.Embedding(input_size, embedding_size)","embedding_size, hidden_size, output_size, num_layers, p ): super(Decoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size =","is batch size embedding = self.dropout(self.embedding(x)) # embedding shape: (seq_length, N, embedding_size) outputs,","# Grab the first input to the Decoder which will be <SOS> token","to tensorboard from utils import translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger = spacy.load(\"de\") spacy_eng","# loss function we want it to be (N, length_target_vocabulary) so we're #","= len(german.vocab) input_size_decoder = len(english.vocab) output_size = len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size =","# Store next output prediction outputs[t] = output # Get the best word","(seq_length, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding) # outputs shape: (seq_length, N,","function we want it to be (N, length_target_vocabulary) so we're # just gonna","sure grads are # within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent","len(english.vocab) output_size = len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size = 300 hidden_size = 1024","to send in into # our cost function, so we need to do","This was a long comment. x = target[t] if random.random() < teacher_force_ratio else","num_layers = 2 enc_dropout = 0.5 dec_dropout = 0.5 # Tensorboard to get","to the Decoder which will be <SOS> token x = target[0] for t","inputs at test time might be completely different than what the # network","Seq2Seq model ### # Training hyperparameters num_epochs = 100 learning_rate = 0.001 batch_size","batch size, we want it to be (1, N), seq_length # is 1","the Decoder predicted (index in the vocabulary) best_guess = output.argmax(1) # With probability","cell) = self.rnn(embedding) # outputs shape: (seq_length, N, hidden_size) return hidden, cell class","outputs, (hidden, cell) = self.rnn(embedding, (hidden, cell)) # outputs shape: (1, N, hidden_size)","nn import torch.optim as optim from torchtext.datasets import Multi30k from torchtext.data import Field,","in the vocabulary) best_guess = output.argmax(1) # With probability of teacher_force_ratio we take","target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output, target) # Back prop loss.backward() # Clip to","# within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent step optimizer.step() #","loss\", loss, global_step=step) step += 1 score = bleu(test_data[1:100], model, german, english, device)","= target[t] if random.random() < teacher_force_ratio else best_guess return outputs ### We're ready","range(1, target_len): # Use previous hidden, cell as context from encoder at start","our cost function, so we need to do some reshapin. While we're at","input_size, embedding_size, hidden_size, num_layers, p): super(Encoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size","Loss # doesn't take input in that form. For example if we have","descent step optimizer.step() # Plot to tensorboard writer.add_scalar(\"Training loss\", loss, global_step=step) step +=","self.num_layers = num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p)","otherwise we take the word that the Decoder predicted it to be. #","everything we need for training our Seq2Seq model ### # Training hyperparameters num_epochs","# similar inputs at training and testing time, if teacher forcing is 1","at it # Let's also remove the start token while we're at it","valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src), device=device, ) encoder_net = Encoder( input_size_encoder,","if load_model: load_checkpoint(torch.load(\"my_checkpoint.pth.tar\"), model, optimizer) sentence = \"ein boot mit mehreren männern darauf","want to send in into # our cost function, so we need to","that we have output_words * batch_size that we want to send in into","send it to # loss function we want it to be (N, length_target_vocabulary)","Decoder which will be <SOS> token x = target[0] for t in range(1,","__init__(self, encoder, decoder): super(Seq2Seq, self).__init__() self.encoder = encoder self.decoder = decoder def forward(self,","predictions.squeeze(0) return predictions, hidden, cell class Seq2Seq(nn.Module): def __init__(self, encoder, decoder): super(Seq2Seq, self).__init__()","torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\") input_size_encoder = len(german.vocab) input_size_decoder = len(english.vocab) output_size =","= target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output, target) # Back prop loss.backward() # Clip",") train_data, valid_data, test_data = Multi30k.splits( exts=(\".de\", \".en\"), fields=(german, english) ) german.build_vocab(train_data, max_size=10000,","context from encoder at start output, hidden, cell = self.decoder(x, hidden, cell) #","(seq_length, N, hidden_size) return hidden, cell class Decoder(nn.Module): def __init__( self, input_size, embedding_size,","forward(self, source, target, teacher_force_ratio=0.5): batch_size = source.shape[1] target_len = target.shape[0] target_vocab_size = len(english.vocab)","max_length=50 ) print(f\"Translated example sentence: \\n {translated_sentence}\") model.train() for batch_idx, batch in enumerate(train_iterator):","N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding, (hidden, cell)) # outputs shape: (1,","step += 1 score = bleu(test_data[1:100], model, german, english, device) print(f\"Bleu score {score*100:.2f}\")","import SummaryWriter # to print to tensorboard from utils import translate_sentence, bleu, save_checkpoint,","cost function, so we need to do some reshapin. While we're at it","output_dim) but Cross Entropy Loss # doesn't take input in that form. For","dim predictions = predictions.squeeze(0) return predictions, hidden, cell class Seq2Seq(nn.Module): def __init__(self, encoder,","outputs[t] = output # Get the best word the Decoder predicted (index in","we can view it in a similar # way that we have output_words","target = target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output, target) # Back prop loss.backward() #","spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\") english = Field( tokenize=tokenize_eng, lower=True, init_token=\"<sos>\",","= 100 learning_rate = 0.001 batch_size = 64 # Model hyperparameters load_model =","dropout=p) self.fc = nn.Linear(hidden_size, output_size) def forward(self, x, hidden, cell): # x shape:","Training hyperparameters num_epochs = 100 learning_rate = 0.001 batch_size = 64 # Model","nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn =","len(x.src), device=device, ) encoder_net = Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device) decoder_net","1 here because we are sending in a single word and not a","batch.trg.to(device) # Forward prop output = model(inp_data, target) # Output is of shape","# to print to tensorboard from utils import translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger","# otherwise we take the word that the Decoder predicted it to be.","is used to. This was a long comment. x = target[t] if random.random()","# Training hyperparameters num_epochs = 100 learning_rate = 0.001 batch_size = 64 #","numpy as np import spacy import random from torch.utils.tensorboard import SummaryWriter # to","[tok.text for tok in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\") english =","embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc = nn.Linear(hidden_size, output_size) def forward(self,","target_vocab_size).to(device) hidden, cell = self.encoder(source) # Grab the first input to the Decoder","testing time, if teacher forcing is 1 # then inputs at test time","= predictions.squeeze(0) return predictions, hidden, cell class Seq2Seq(nn.Module): def __init__(self, encoder, decoder): super(Seq2Seq,","= 2 enc_dropout = 0.5 dec_dropout = 0.5 # Tensorboard to get nice","# output to be: (N, 10) and targets just (N). Here we can","used to seeing # similar inputs at training and testing time, if teacher","to tensorboard writer.add_scalar(\"Training loss\", loss, global_step=step) step += 1 score = bleu(test_data[1:100], model,","Cross Entropy Loss # doesn't take input in that form. For example if","hidden_size = 1024 # Needs to be the same for both RNN's num_layers","Field(tokenize=tokenize_ger, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\") english = Field( tokenize=tokenize_eng, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\" ) train_data,","{epoch} / {num_epochs}]\") checkpoint = {\"state_dict\": model.state_dict(), \"optimizer\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence =","= 300 hidden_size = 1024 # Needs to be the same for both","train_iterator, valid_iterator, test_iterator = BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src),","(index in the vocabulary) best_guess = output.argmax(1) # With probability of teacher_force_ratio we","# Back prop loss.backward() # Clip to avoid exploding gradient issues, makes sure","a sentence x = x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) # embedding shape: (1, N,","where N is batch size embedding = self.dropout(self.embedding(x)) # embedding shape: (seq_length, N,","### # Training hyperparameters num_epochs = 100 learning_rate = 0.001 batch_size = 64","max_size=10000, min_freq=2) class Encoder(nn.Module): def __init__(self, input_size, embedding_size, hidden_size, num_layers, p): super(Encoder, self).__init__()","< teacher_force_ratio else best_guess return outputs ### We're ready to define everything we","to be the same for both RNN's num_layers = 2 enc_dropout = 0.5","optimizer) sentence = \"ein boot mit mehreren männern darauf wird von einem großen","x shape: (seq_length, N) where N is batch size embedding = self.dropout(self.embedding(x)) #","= False device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\") input_size_encoder = len(german.vocab) input_size_decoder","size, we want it to be (1, N), seq_length # is 1 here","forward(self, x): # x shape: (seq_length, N) where N is batch size embedding","num_layers, p ): super(Decoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers =","decoder def forward(self, source, target, teacher_force_ratio=0.5): batch_size = source.shape[1] target_len = target.shape[0] target_vocab_size","from encoder at start output, hidden, cell = self.decoder(x, hidden, cell) # Store","in a single word and not a sentence x = x.unsqueeze(0) embedding =","model, optimizer) sentence = \"ein boot mit mehreren männern darauf wird von einem","(1, N), seq_length # is 1 here because we are sending in a","x): # x shape: (seq_length, N) where N is batch size embedding =","= 0.001 batch_size = 64 # Model hyperparameters load_model = False device =","def forward(self, source, target, teacher_force_ratio=0.5): batch_size = source.shape[1] target_len = target.shape[0] target_vocab_size =","random.random() < teacher_force_ratio else best_guess return outputs ### We're ready to define everything","optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\"<pad>\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\"my_checkpoint.pth.tar\"), model, optimizer)","# Tensorboard to get nice loss plot writer = SummaryWriter(f\"runs/loss_plot\") step = 0","to. This was a long comment. x = target[t] if random.random() < teacher_force_ratio","the same for both RNN's num_layers = 2 enc_dropout = 0.5 dec_dropout =","same for both RNN's num_layers = 2 enc_dropout = 0.5 dec_dropout = 0.5","that we want to send in into # our cost function, so we","(N, length_target_vocabulary) so we're # just gonna remove the first dim predictions =","= len(english.vocab) outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell = self.encoder(source) # Grab","encoder, decoder): super(Seq2Seq, self).__init__() self.encoder = encoder self.decoder = decoder def forward(self, source,","to be (1, N), seq_length # is 1 here because we are sending","spacy_ger = spacy.load(\"de\") spacy_eng = spacy.load(\"en\") def tokenize_ger(text): return [tok.text for tok in","be. # Teacher Forcing is used so that the model gets used to","= nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def forward(self, x): # x shape: (seq_length, N)","remove the start token while we're at it output = output[1:].reshape(-1, output.shape[2]) target","def __init__(self, input_size, embedding_size, hidden_size, num_layers, p): super(Encoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size","makes sure grads are # within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient","# x shape: (seq_length, N) where N is batch size embedding = self.dropout(self.embedding(x))","super(Encoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers self.embedding =","token while we're at it output = output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad()","teacher_force_ratio=0.5): batch_size = source.shape[1] target_len = target.shape[0] target_vocab_size = len(english.vocab) outputs = torch.zeros(target_len,","inputs at training and testing time, if teacher forcing is 1 # then","learning_rate = 0.001 batch_size = 64 # Model hyperparameters load_model = False device","tokenize_ger(text): return [tok.text for tok in spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text for tok","be the same for both RNN's num_layers = 2 enc_dropout = 0.5 dec_dropout","output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output, target) # Back prop loss.backward()","also remove the start token while we're at it output = output[1:].reshape(-1, output.shape[2])","take the actual next word # otherwise we take the word that the","teacher_force_ratio else best_guess return outputs ### We're ready to define everything we need","german, english, device, max_length=50 ) print(f\"Translated example sentence: \\n {translated_sentence}\") model.train() for batch_idx,","min_freq=2) class Encoder(nn.Module): def __init__(self, input_size, embedding_size, hidden_size, num_layers, p): super(Encoder, self).__init__() self.dropout","(1, N, length_target_vocabulary) to send it to # loss function we want it","we want to send in into # our cost function, so we need","sentence = \"ein boot mit mehreren männern darauf wird von einem großen pferdegespann","class Encoder(nn.Module): def __init__(self, input_size, embedding_size, hidden_size, num_layers, p): super(Encoder, self).__init__() self.dropout =","seq_length # is 1 here because we are sending in a single word","len(german.vocab) input_size_decoder = len(english.vocab) output_size = len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size = 300","init_token=\"<sos>\", eos_token=\"<eos>\" ) train_data, valid_data, test_data = Multi30k.splits( exts=(\".de\", \".en\"), fields=(german, english) )","(hidden, cell) = self.rnn(embedding) # outputs shape: (seq_length, N, hidden_size) return hidden, cell","spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text for tok in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True,","just gonna remove the first dim predictions = predictions.squeeze(0) return predictions, hidden, cell","len(english.vocab) outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell = self.encoder(source) # Grab the","output prediction outputs[t] = output # Get the best word the Decoder predicted","Encoder(nn.Module): def __init__(self, input_size, embedding_size, hidden_size, num_layers, p): super(Encoder, self).__init__() self.dropout = nn.Dropout(p)","we take the actual next word # otherwise we take the word that","min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module): def __init__(self, input_size, embedding_size, hidden_size, num_layers, p):","(N). Here we can view it in a similar # way that we","tokenize_eng(text): return [tok.text for tok in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\")","be <SOS> token x = target[0] for t in range(1, target_len): # Use","np import spacy import random from torch.utils.tensorboard import SummaryWriter # to print to","= Multi30k.splits( exts=(\".de\", \".en\"), fields=(german, english) ) german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2)","else best_guess return outputs ### We're ready to define everything we need for","self.rnn(embedding, (hidden, cell)) # outputs shape: (1, N, hidden_size) predictions = self.fc(outputs) #","our Seq2Seq model ### # Training hyperparameters num_epochs = 100 learning_rate = 0.001","wird von einem großen pferdegespann ans ufer gezogen.\" for epoch in range(num_epochs): print(f\"[Epoch","(1, N, hidden_size) predictions = self.fc(outputs) # predictions shape: (1, N, length_target_vocabulary) to","= len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size = 300 hidden_size = 1024 # Needs","forward(self, x, hidden, cell): # x shape: (N) where N is for batch","remove the first dim predictions = predictions.squeeze(0) return predictions, hidden, cell class Seq2Seq(nn.Module):","outputs ### We're ready to define everything we need for training our Seq2Seq","what the # network is used to. This was a long comment. x","device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\") input_size_encoder = len(german.vocab) input_size_decoder = len(english.vocab)","batch in enumerate(train_iterator): # Get input and targets and get to cuda inp_data","have output_words * batch_size that we want to send in into # our","within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent step optimizer.step() # Plot","into # our cost function, so we need to do some reshapin. While","nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\"my_checkpoint.pth.tar\"), model, optimizer) sentence = \"ein boot mit mehreren männern","nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc = nn.Linear(hidden_size, output_size) def","input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout, ).to(device) model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer =","target) # Back prop loss.backward() # Clip to avoid exploding gradient issues, makes","shape: (seq_length, N, hidden_size) return hidden, cell class Decoder(nn.Module): def __init__( self, input_size,","Field( tokenize=tokenize_eng, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\" ) train_data, valid_data, test_data = Multi30k.splits( exts=(\".de\", \".en\"),","for both RNN's num_layers = 2 enc_dropout = 0.5 dec_dropout = 0.5 #","# Clip to avoid exploding gradient issues, makes sure grads are # within","Field, BucketIterator import numpy as np import spacy import random from torch.utils.tensorboard import","probability of teacher_force_ratio we take the actual next word # otherwise we take","is for batch size, we want it to be (1, N), seq_length #","shape: (1, N, length_target_vocabulary) to send it to # loss function we want","return outputs ### We're ready to define everything we need for training our","ans ufer gezogen.\" for epoch in range(num_epochs): print(f\"[Epoch {epoch} / {num_epochs}]\") checkpoint =","print(f\"[Epoch {epoch} / {num_epochs}]\") checkpoint = {\"state_dict\": model.state_dict(), \"optimizer\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence","import translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger = spacy.load(\"de\") spacy_eng = spacy.load(\"en\") def tokenize_ger(text):","self.hidden_size = hidden_size self.num_layers = num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size,","eos_token=\"<eos>\") english = Field( tokenize=tokenize_eng, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\" ) train_data, valid_data, test_data =","here because we are sending in a single word and not a sentence","300 hidden_size = 1024 # Needs to be the same for both RNN's","= spacy.load(\"en\") def tokenize_ger(text): return [tok.text for tok in spacy_ger.tokenizer(text)] def tokenize_eng(text): return","test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src), device=device, ) encoder_net = Encoder( input_size_encoder, encoder_embedding_size,","avoid exploding gradient issues, makes sure grads are # within a healthy range","= nn.Linear(hidden_size, output_size) def forward(self, x, hidden, cell): # x shape: (N) where","= decoder def forward(self, source, target, teacher_force_ratio=0.5): batch_size = source.shape[1] target_len = target.shape[0]","def forward(self, x): # x shape: (seq_length, N) where N is batch size","import Field, BucketIterator import numpy as np import spacy import random from torch.utils.tensorboard","the first dim predictions = predictions.squeeze(0) return predictions, hidden, cell class Seq2Seq(nn.Module): def","plot writer = SummaryWriter(f\"runs/loss_plot\") step = 0 train_iterator, valid_iterator, test_iterator = BucketIterator.splits( (train_data,","decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\"<pad>\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model:","torchtext.datasets import Multi30k from torchtext.data import Field, BucketIterator import numpy as np import","model, sentence, german, english, device, max_length=50 ) print(f\"Translated example sentence: \\n {translated_sentence}\") model.train()","decoder_embedding_size = 300 hidden_size = 1024 # Needs to be the same for","sort_key=lambda x: len(x.src), device=device, ) encoder_net = Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout","input in that form. For example if we have MNIST we want to","\\n {translated_sentence}\") model.train() for batch_idx, batch in enumerate(train_iterator): # Get input and targets","= {\"state_dict\": model.state_dict(), \"optimizer\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence( model, sentence, german,","cuda inp_data = batch.src.to(device) target = batch.trg.to(device) # Forward prop output = model(inp_data,","nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def forward(self, x): # x shape: (seq_length, N) where","SummaryWriter(f\"runs/loss_plot\") step = 0 train_iterator, valid_iterator, test_iterator = BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size,","nn.Linear(hidden_size, output_size) def forward(self, x, hidden, cell): # x shape: (N) where N","at training and testing time, if teacher forcing is 1 # then inputs","shape (trg_len, batch_size, output_dim) but Cross Entropy Loss # doesn't take input in","num_layers, p): super(Encoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers","darauf wird von einem großen pferdegespann ans ufer gezogen.\" for epoch in range(num_epochs):","Grab the first input to the Decoder which will be <SOS> token x","next word # otherwise we take the word that the Decoder predicted it","from torchtext.data import Field, BucketIterator import numpy as np import spacy import random","return [tok.text for tok in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\") english","64 # Model hyperparameters load_model = False device = torch.device(\"cuda\" if torch.cuda.is_available() else","= 0 train_iterator, valid_iterator, test_iterator = BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda","= torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\") input_size_encoder = len(german.vocab) input_size_decoder = len(english.vocab) output_size","von einem großen pferdegespann ans ufer gezogen.\" for epoch in range(num_epochs): print(f\"[Epoch {epoch}","self.decoder(x, hidden, cell) # Store next output prediction outputs[t] = output # Get","in spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text for tok in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger,","network is used to. This was a long comment. x = target[t] if","nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc = nn.Linear(hidden_size, output_size) def forward(self, x, hidden, cell):","= Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\"<pad>\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx)","tensorboard from utils import translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger = spacy.load(\"de\") spacy_eng =","embedding shape: (seq_length, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding) # outputs shape:","N, length_target_vocabulary) to send it to # loss function we want it to","output_size, num_layers, p ): super(Decoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers","shape: (N) where N is for batch size, we want it to be","self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def forward(self, x): # x shape: (seq_length,","Gradient descent step optimizer.step() # Plot to tensorboard writer.add_scalar(\"Training loss\", loss, global_step=step) step","hyperparameters load_model = False device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\") input_size_encoder =","it in a similar # way that we have output_words * batch_size that","be (N, length_target_vocabulary) so we're # just gonna remove the first dim predictions","nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def forward(self, x): # x","def tokenize_ger(text): return [tok.text for tok in spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text for","import Multi30k from torchtext.data import Field, BucketIterator import numpy as np import spacy","def __init__( self, input_size, embedding_size, hidden_size, output_size, num_layers, p ): super(Decoder, self).__init__() self.dropout","# outputs shape: (1, N, hidden_size) predictions = self.fc(outputs) # predictions shape: (1,","= self.encoder(source) # Grab the first input to the Decoder which will be","= translate_sentence( model, sentence, german, english, device, max_length=50 ) print(f\"Translated example sentence: \\n","N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding) # outputs shape: (seq_length, N, hidden_size)","next output prediction outputs[t] = output # Get the best word the Decoder","MNIST we want to have # output to be: (N, 10) and targets","teacher_force_ratio we take the actual next word # otherwise we take the word","# Gradient descent step optimizer.step() # Plot to tensorboard writer.add_scalar(\"Training loss\", loss, global_step=step)","is 1 # then inputs at test time might be completely different than","# network is used to. This was a long comment. x = target[t]","RNN's num_layers = 2 enc_dropout = 0.5 dec_dropout = 0.5 # Tensorboard to","# Get input and targets and get to cuda inp_data = batch.src.to(device) target","target[t] if random.random() < teacher_force_ratio else best_guess return outputs ### We're ready to","output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output, target) # Back prop","= batch.trg.to(device) # Forward prop output = model(inp_data, target) # Output is of","0 train_iterator, valid_iterator, test_iterator = BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x:","hidden_size) predictions = self.fc(outputs) # predictions shape: (1, N, length_target_vocabulary) to send it","output_size = len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size = 300 hidden_size = 1024 #","= spacy.load(\"de\") spacy_eng = spacy.load(\"en\") def tokenize_ger(text): return [tok.text for tok in spacy_ger.tokenizer(text)]","* batch_size that we want to send in into # our cost function,","best_guess = output.argmax(1) # With probability of teacher_force_ratio we take the actual next","that the model gets used to seeing # similar inputs at training and","start token while we're at it output = output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1)","(seq_length, N) where N is batch size embedding = self.dropout(self.embedding(x)) # embedding shape:","single word and not a sentence x = x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) #","__init__(self, input_size, embedding_size, hidden_size, num_layers, p): super(Encoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size =","might be completely different than what the # network is used to. This","enumerate(train_iterator): # Get input and targets and get to cuda inp_data = batch.src.to(device)","hidden, cell = self.decoder(x, hidden, cell) # Store next output prediction outputs[t] =","take input in that form. For example if we have MNIST we want","len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size = 300 hidden_size = 1024 # Needs to","# is 1 here because we are sending in a single word and","to do some reshapin. While we're at it # Let's also remove the","embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def forward(self, x): # x shape:","time, if teacher forcing is 1 # then inputs at test time might","300 decoder_embedding_size = 300 hidden_size = 1024 # Needs to be the same","(N) where N is for batch size, we want it to be (1,","at test time might be completely different than what the # network is","gonna remove the first dim predictions = predictions.squeeze(0) return predictions, hidden, cell class","p ): super(Decoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers","target_len): # Use previous hidden, cell as context from encoder at start output,","decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout, ).to(device) model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(),","Store next output prediction outputs[t] = output # Get the best word the","num_epochs = 100 learning_rate = 0.001 batch_size = 64 # Model hyperparameters load_model","x shape: (N) where N is for batch size, we want it to","from utils import translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger = spacy.load(\"de\") spacy_eng = spacy.load(\"en\")","<SOS> token x = target[0] for t in range(1, target_len): # Use previous","actual next word # otherwise we take the word that the Decoder predicted","= criterion(output, target) # Back prop loss.backward() # Clip to avoid exploding gradient","optimizer.step() # Plot to tensorboard writer.add_scalar(\"Training loss\", loss, global_step=step) step += 1 score","Entropy Loss # doesn't take input in that form. For example if we","because we are sending in a single word and not a sentence x","get nice loss plot writer = SummaryWriter(f\"runs/loss_plot\") step = 0 train_iterator, valid_iterator, test_iterator","# outputs shape: (seq_length, N, hidden_size) return hidden, cell class Decoder(nn.Module): def __init__(","some reshapin. While we're at it # Let's also remove the start token","pferdegespann ans ufer gezogen.\" for epoch in range(num_epochs): print(f\"[Epoch {epoch} / {num_epochs}]\") checkpoint","the best word the Decoder predicted (index in the vocabulary) best_guess = output.argmax(1)","outputs shape: (1, N, hidden_size) predictions = self.fc(outputs) # predictions shape: (1, N,","= Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout, ).to(device) model = Seq2Seq(encoder_net, decoder_net).to(device)","Output is of shape (trg_len, batch_size, output_dim) but Cross Entropy Loss # doesn't","batch.src.to(device) target = batch.trg.to(device) # Forward prop output = model(inp_data, target) # Output","it # Let's also remove the start token while we're at it output","[tok.text for tok in spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text for tok in spacy_eng.tokenizer(text)]","### We're ready to define everything we need for training our Seq2Seq model","self).__init__() self.encoder = encoder self.decoder = decoder def forward(self, source, target, teacher_force_ratio=0.5): batch_size","load_model = False device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\") input_size_encoder = len(german.vocab)","mehreren männern darauf wird von einem großen pferdegespann ans ufer gezogen.\" for epoch","init_token=\"<sos>\", eos_token=\"<eos>\") english = Field( tokenize=tokenize_eng, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\" ) train_data, valid_data, test_data","translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger = spacy.load(\"de\") spacy_eng = spacy.load(\"en\") def tokenize_ger(text): return","= self.decoder(x, hidden, cell) # Store next output prediction outputs[t] = output #","the model gets used to seeing # similar inputs at training and testing","# way that we have output_words * batch_size that we want to send",") german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module): def __init__(self, input_size, embedding_size,","word that the Decoder predicted it to be. # Teacher Forcing is used","\"ein boot mit mehreren männern darauf wird von einem großen pferdegespann ans ufer","vocabulary) best_guess = output.argmax(1) # With probability of teacher_force_ratio we take the actual","prediction outputs[t] = output # Get the best word the Decoder predicted (index","for tok in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\") english = Field(","size embedding = self.dropout(self.embedding(x)) # embedding shape: (seq_length, N, embedding_size) outputs, (hidden, cell)","100 learning_rate = 0.001 batch_size = 64 # Model hyperparameters load_model = False","torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent step optimizer.step() # Plot to tensorboard writer.add_scalar(\"Training loss\",","Decoder(nn.Module): def __init__( self, input_size, embedding_size, hidden_size, output_size, num_layers, p ): super(Decoder, self).__init__()","ufer gezogen.\" for epoch in range(num_epochs): print(f\"[Epoch {epoch} / {num_epochs}]\") checkpoint = {\"state_dict\":","= num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc","in range(1, target_len): # Use previous hidden, cell as context from encoder at","# embedding shape: (1, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding, (hidden, cell))","cell) # Store next output prediction outputs[t] = output # Get the best","optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence( model, sentence, german, english, device, max_length=50 )","it to be (N, length_target_vocabulary) so we're # just gonna remove the first","= self.rnn(embedding) # outputs shape: (seq_length, N, hidden_size) return hidden, cell class Decoder(nn.Module):","model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\"<pad>\"] criterion =","= 300 decoder_embedding_size = 300 hidden_size = 1024 # Needs to be the","tok in spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text for tok in spacy_eng.tokenizer(text)] german =","take the word that the Decoder predicted it to be. # Teacher Forcing","is 1 here because we are sending in a single word and not","{\"state_dict\": model.state_dict(), \"optimizer\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence( model, sentence, german, english,","german = Field(tokenize=tokenize_ger, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\") english = Field( tokenize=tokenize_eng, lower=True, init_token=\"<sos>\", eos_token=\"<eos>\"","loss plot writer = SummaryWriter(f\"runs/loss_plot\") step = 0 train_iterator, valid_iterator, test_iterator = BucketIterator.splits(","first input to the Decoder which will be <SOS> token x = target[0]","BucketIterator import numpy as np import spacy import random from torch.utils.tensorboard import SummaryWriter","we want to have # output to be: (N, 10) and targets just","def __init__(self, encoder, decoder): super(Seq2Seq, self).__init__() self.encoder = encoder self.decoder = decoder def","lower=True, init_token=\"<sos>\", eos_token=\"<eos>\" ) train_data, valid_data, test_data = Multi30k.splits( exts=(\".de\", \".en\"), fields=(german, english)","\".en\"), fields=(german, english) ) german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module): def","model.train() for batch_idx, batch in enumerate(train_iterator): # Get input and targets and get","Model hyperparameters load_model = False device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\") input_size_encoder","class Decoder(nn.Module): def __init__( self, input_size, embedding_size, hidden_size, output_size, num_layers, p ): super(Decoder,"],"string":"[\n \"to send it to # loss function we want it to be (N,\",\n \"of shape (trg_len, batch_size, output_dim) but Cross Entropy Loss # doesn't take input\",\n \"encoder_net = Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device) decoder_net = Decoder( input_size_decoder,\",\n \"want to have # output to be: (N, 10) and targets just (N).\",\n \"Tensorboard to get nice loss plot writer = SummaryWriter(f\\\"runs/loss_plot\\\") step = 0 train_iterator,\",\n \"we take the word that the Decoder predicted it to be. # Teacher\",\n \"encoder_embedding_size = 300 decoder_embedding_size = 300 hidden_size = 1024 # Needs to be\",\n \"to avoid exploding gradient issues, makes sure grads are # within a healthy\",\n \"x = x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) # embedding shape: (1, N, embedding_size) outputs,\",\n \"else \\\"cpu\\\") input_size_encoder = len(german.vocab) input_size_decoder = len(english.vocab) output_size = len(english.vocab) encoder_embedding_size =\",\n \"in into # our cost function, so we need to do some reshapin.\",\n \"time might be completely different than what the # network is used to.\",\n \"Teacher Forcing is used so that the model gets used to seeing #\",\n \"we have output_words * batch_size that we want to send in into #\",\n \"utils import translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger = spacy.load(\\\"de\\\") spacy_eng = spacy.load(\\\"en\\\") def\",\n \"in a similar # way that we have output_words * batch_size that we\",\n \"but Cross Entropy Loss # doesn't take input in that form. For example\",\n \"valid_data, test_data = Multi30k.splits( exts=(\\\".de\\\", \\\".en\\\"), fields=(german, english) ) german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data,\",\n \"as nn import torch.optim as optim from torchtext.datasets import Multi30k from torchtext.data import\",\n \"1 # then inputs at test time might be completely different than what\",\n \"tokenize=tokenize_eng, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\" ) train_data, valid_data, test_data = Multi30k.splits( exts=(\\\".de\\\", \\\".en\\\"), fields=(german,\",\n \"__init__( self, input_size, embedding_size, hidden_size, output_size, num_layers, p ): super(Decoder, self).__init__() self.dropout =\",\n \"1024 # Needs to be the same for both RNN's num_layers = 2\",\n \"have # output to be: (N, 10) and targets just (N). Here we\",\n \"comment. x = target[t] if random.random() < teacher_force_ratio else best_guess return outputs ###\",\n \"(trg_len, batch_size, output_dim) but Cross Entropy Loss # doesn't take input in that\",\n \"need for training our Seq2Seq model ### # Training hyperparameters num_epochs = 100\",\n \"the word that the Decoder predicted it to be. # Teacher Forcing is\",\n \"used to. This was a long comment. x = target[t] if random.random() <\",\n \"hidden, cell) # Store next output prediction outputs[t] = output # Get the\",\n \"healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent step optimizer.step() # Plot to tensorboard\",\n \"pad_idx = english.vocab.stoi[\\\"<pad>\\\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\\\"my_checkpoint.pth.tar\\\"), model, optimizer) sentence =\",\n \"step = 0 train_iterator, valid_iterator, test_iterator = BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True,\",\n \"print(f\\\"Translated example sentence: \\\\n {translated_sentence}\\\") model.train() for batch_idx, batch in enumerate(train_iterator): # Get\",\n \"return [tok.text for tok in spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text for tok in\",\n \"hidden_size self.num_layers = num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers,\",\n \"it to # loss function we want it to be (N, length_target_vocabulary) so\",\n \"= nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc = nn.Linear(hidden_size, output_size)\",\n \"cell = self.decoder(x, hidden, cell) # Store next output prediction outputs[t] = output\",\n \"we need to do some reshapin. While we're at it # Let's also\",\n \"max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module): def __init__(self, input_size, embedding_size, hidden_size, num_layers,\",\n \"and testing time, if teacher forcing is 1 # then inputs at test\",\n \"ready to define everything we need for training our Seq2Seq model ### #\",\n \"gradient issues, makes sure grads are # within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1)\",\n \"cell as context from encoder at start output, hidden, cell = self.decoder(x, hidden,\",\n \"loss function we want it to be (N, length_target_vocabulary) so we're # just\",\n \"training and testing time, if teacher forcing is 1 # then inputs at\",\n \"in that form. For example if we have MNIST we want to have\",\n \"and targets and get to cuda inp_data = batch.src.to(device) target = batch.trg.to(device) #\",\n \"want it to be (1, N), seq_length # is 1 here because we\",\n \"= source.shape[1] target_len = target.shape[0] target_vocab_size = len(english.vocab) outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device)\",\n \"(hidden, cell) = self.rnn(embedding, (hidden, cell)) # outputs shape: (1, N, hidden_size) predictions\",\n \"spacy import random from torch.utils.tensorboard import SummaryWriter # to print to tensorboard from\",\n \"= nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def forward(self, x): #\",\n \"enc_dropout = 0.5 dec_dropout = 0.5 # Tensorboard to get nice loss plot\",\n \"hidden_size, num_layers, dropout=p) self.fc = nn.Linear(hidden_size, output_size) def forward(self, x, hidden, cell): #\",\n \"the Decoder which will be <SOS> token x = target[0] for t in\",\n \"in range(num_epochs): print(f\\\"[Epoch {epoch} / {num_epochs}]\\\") checkpoint = {\\\"state_dict\\\": model.state_dict(), \\\"optimizer\\\": optimizer.state_dict()} save_checkpoint(checkpoint)\",\n \"we have MNIST we want to have # output to be: (N, 10)\",\n \"Needs to be the same for both RNN's num_layers = 2 enc_dropout =\",\n \"the start token while we're at it output = output[1:].reshape(-1, output.shape[2]) target =\",\n \"for epoch in range(num_epochs): print(f\\\"[Epoch {epoch} / {num_epochs}]\\\") checkpoint = {\\\"state_dict\\\": model.state_dict(), \\\"optimizer\\\":\",\n \"# our cost function, so we need to do some reshapin. While we're\",\n \"= nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn\",\n \"\\\"cpu\\\") input_size_encoder = len(german.vocab) input_size_decoder = len(english.vocab) output_size = len(english.vocab) encoder_embedding_size = 300\",\n \"are sending in a single word and not a sentence x = x.unsqueeze(0)\",\n \"input_size_decoder = len(english.vocab) output_size = len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size = 300 hidden_size\",\n \"# just gonna remove the first dim predictions = predictions.squeeze(0) return predictions, hidden,\",\n \"at it output = output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output,\",\n \"torch import torch.nn as nn import torch.optim as optim from torchtext.datasets import Multi30k\",\n \"shape: (seq_length, N) where N is batch size embedding = self.dropout(self.embedding(x)) # embedding\",\n \"length_target_vocabulary) to send it to # loss function we want it to be\",\n \"Get the best word the Decoder predicted (index in the vocabulary) best_guess =\",\n \"shape: (seq_length, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding) # outputs shape: (seq_length,\",\n \"# then inputs at test time might be completely different than what the\",\n \"epoch in range(num_epochs): print(f\\\"[Epoch {epoch} / {num_epochs}]\\\") checkpoint = {\\\"state_dict\\\": model.state_dict(), \\\"optimizer\\\": optimizer.state_dict()}\",\n \"= Field(tokenize=tokenize_ger, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\") english = Field( tokenize=tokenize_eng, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\" )\",\n \"previous hidden, cell as context from encoder at start output, hidden, cell =\",\n \"embedding_size) outputs, (hidden, cell) = self.rnn(embedding) # outputs shape: (seq_length, N, hidden_size) return\",\n \"input_size_encoder = len(german.vocab) input_size_decoder = len(english.vocab) output_size = len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size\",\n \"output = model(inp_data, target) # Output is of shape (trg_len, batch_size, output_dim) but\",\n \"model(inp_data, target) # Output is of shape (trg_len, batch_size, output_dim) but Cross Entropy\",\n \"issues, makes sure grads are # within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) #\",\n \"word and not a sentence x = x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) # embedding\",\n \"= x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) # embedding shape: (1, N, embedding_size) outputs, (hidden,\",\n \"Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device) decoder_net = Decoder( input_size_decoder, decoder_embedding_size, hidden_size,\",\n \"exts=(\\\".de\\\", \\\".en\\\"), fields=(german, english) ) german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module):\",\n \"save_checkpoint, load_checkpoint spacy_ger = spacy.load(\\\"de\\\") spacy_eng = spacy.load(\\\"en\\\") def tokenize_ger(text): return [tok.text for\",\n \"target, teacher_force_ratio=0.5): batch_size = source.shape[1] target_len = target.shape[0] target_vocab_size = len(english.vocab) outputs =\",\n \"load_checkpoint(torch.load(\\\"my_checkpoint.pth.tar\\\"), model, optimizer) sentence = \\\"ein boot mit mehreren männern darauf wird von\",\n \"sentence: \\\\n {translated_sentence}\\\") model.train() for batch_idx, batch in enumerate(train_iterator): # Get input and\",\n \"= 0.5 dec_dropout = 0.5 # Tensorboard to get nice loss plot writer\",\n \"not a sentence x = x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) # embedding shape: (1,\",\n \"torchtext.data import Field, BucketIterator import numpy as np import spacy import random from\",\n \"hidden, cell = self.encoder(source) # Grab the first input to the Decoder which\",\n \"prop output = model(inp_data, target) # Output is of shape (trg_len, batch_size, output_dim)\",\n \"output to be: (N, 10) and targets just (N). Here we can view\",\n \"import torch.nn as nn import torch.optim as optim from torchtext.datasets import Multi30k from\",\n \"is used so that the model gets used to seeing # similar inputs\",\n \"define everything we need for training our Seq2Seq model ### # Training hyperparameters\",\n \"batch_idx, batch in enumerate(train_iterator): # Get input and targets and get to cuda\",\n \"it to be (1, N), seq_length # is 1 here because we are\",\n \"sentence x = x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) # embedding shape: (1, N, embedding_size)\",\n \"we're at it # Let's also remove the start token while we're at\",\n \"batch_size, output_dim) but Cross Entropy Loss # doesn't take input in that form.\",\n \"sending in a single word and not a sentence x = x.unsqueeze(0) embedding\",\n \"= len(english.vocab) output_size = len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size = 300 hidden_size =\",\n \"(hidden, cell)) # outputs shape: (1, N, hidden_size) predictions = self.fc(outputs) # predictions\",\n \"num_layers, dec_dropout, ).to(device) model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx =\",\n \"output_size) def forward(self, x, hidden, cell): # x shape: (N) where N is\",\n \"to be (N, length_target_vocabulary) so we're # just gonna remove the first dim\",\n \"(N, 10) and targets just (N). Here we can view it in a\",\n \"from torchtext.datasets import Multi30k from torchtext.data import Field, BucketIterator import numpy as np\",\n \"target_vocab_size = len(english.vocab) outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell = self.encoder(source) #\",\n \"model.eval() translated_sentence = translate_sentence( model, sentence, german, english, device, max_length=50 ) print(f\\\"Translated example\",\n \"the Decoder predicted it to be. # Teacher Forcing is used so that\",\n \"dec_dropout, ).to(device) model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\\\"<pad>\\\"]\",\n \"= target.shape[0] target_vocab_size = len(english.vocab) outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell =\",\n \") encoder_net = Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device) decoder_net = Decoder(\",\n \"english, device, max_length=50 ) print(f\\\"Translated example sentence: \\\\n {translated_sentence}\\\") model.train() for batch_idx, batch\",\n \"cell): # x shape: (N) where N is for batch size, we want\",\n \"similar inputs at training and testing time, if teacher forcing is 1 #\",\n \"encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device) decoder_net = Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers,\",\n \").to(device) model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\\\"<pad>\\\"] criterion\",\n \"= model(inp_data, target) # Output is of shape (trg_len, batch_size, output_dim) but Cross\",\n \"send in into # our cost function, so we need to do some\",\n \"= 64 # Model hyperparameters load_model = False device = torch.device(\\\"cuda\\\" if torch.cuda.is_available()\",\n \"= torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell = self.encoder(source) # Grab the first input\",\n \"Multi30k.splits( exts=(\\\".de\\\", \\\".en\\\"), fields=(german, english) ) german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class\",\n \"embedding = self.dropout(self.embedding(x)) # embedding shape: (1, N, embedding_size) outputs, (hidden, cell) =\",\n \"= self.dropout(self.embedding(x)) # embedding shape: (1, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding,\",\n \"= hidden_size self.num_layers = num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size,\",\n \"model ### # Training hyperparameters num_epochs = 100 learning_rate = 0.001 batch_size =\",\n \"batch_size = 64 # Model hyperparameters load_model = False device = torch.device(\\\"cuda\\\" if\",\n \"step optimizer.step() # Plot to tensorboard writer.add_scalar(\\\"Training loss\\\", loss, global_step=step) step += 1\",\n \"torch.optim as optim from torchtext.datasets import Multi30k from torchtext.data import Field, BucketIterator import\",\n \"num_layers, dropout=p) def forward(self, x): # x shape: (seq_length, N) where N is\",\n \"(train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src), device=device, ) encoder_net = Encoder(\",\n \"predictions = predictions.squeeze(0) return predictions, hidden, cell class Seq2Seq(nn.Module): def __init__(self, encoder, decoder):\",\n \"translate_sentence( model, sentence, german, english, device, max_length=50 ) print(f\\\"Translated example sentence: \\\\n {translated_sentence}\\\")\",\n \"lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\") english = Field( tokenize=tokenize_eng, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\" ) train_data, valid_data,\",\n \"criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\\\"my_checkpoint.pth.tar\\\"), model, optimizer) sentence = \\\"ein boot mit\",\n \"lr=learning_rate) pad_idx = english.vocab.stoi[\\\"<pad>\\\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\\\"my_checkpoint.pth.tar\\\"), model, optimizer) sentence\",\n \"hidden_size, num_layers, dropout=p) def forward(self, x): # x shape: (seq_length, N) where N\",\n \"at start output, hidden, cell = self.decoder(x, hidden, cell) # Store next output\",\n \"= nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\\\"my_checkpoint.pth.tar\\\"), model, optimizer) sentence = \\\"ein boot mit mehreren\",\n \"form. For example if we have MNIST we want to have # output\",\n \"loss.backward() # Clip to avoid exploding gradient issues, makes sure grads are #\",\n \"english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module): def __init__(self, input_size, embedding_size, hidden_size, num_layers, p): super(Encoder,\",\n \"0.5 dec_dropout = 0.5 # Tensorboard to get nice loss plot writer =\",\n \"we're # just gonna remove the first dim predictions = predictions.squeeze(0) return predictions,\",\n \"optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\\\"<pad>\\\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\\\"my_checkpoint.pth.tar\\\"),\",\n \"exploding gradient issues, makes sure grads are # within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(),\",\n \"range(num_epochs): print(f\\\"[Epoch {epoch} / {num_epochs}]\\\") checkpoint = {\\\"state_dict\\\": model.state_dict(), \\\"optimizer\\\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval()\",\n \"# Needs to be the same for both RNN's num_layers = 2 enc_dropout\",\n \"bleu, save_checkpoint, load_checkpoint spacy_ger = spacy.load(\\\"de\\\") spacy_eng = spacy.load(\\\"en\\\") def tokenize_ger(text): return [tok.text\",\n \"cell) = self.rnn(embedding, (hidden, cell)) # outputs shape: (1, N, hidden_size) predictions =\",\n \"for tok in spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text for tok in spacy_eng.tokenizer(text)] german\",\n \"english = Field( tokenize=tokenize_eng, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\" ) train_data, valid_data, test_data = Multi30k.splits(\",\n \"a single word and not a sentence x = x.unsqueeze(0) embedding = self.dropout(self.embedding(x))\",\n \"load_model: load_checkpoint(torch.load(\\\"my_checkpoint.pth.tar\\\"), model, optimizer) sentence = \\\"ein boot mit mehreren männern darauf wird\",\n \"output_words * batch_size that we want to send in into # our cost\",\n \"self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc = nn.Linear(hidden_size,\",\n \"be completely different than what the # network is used to. This was\",\n \"a long comment. x = target[t] if random.random() < teacher_force_ratio else best_guess return\",\n \"x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) # embedding shape: (1, N, embedding_size) outputs, (hidden, cell)\",\n \"shape: (1, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding, (hidden, cell)) # outputs\",\n \"that the Decoder predicted it to be. # Teacher Forcing is used so\",\n \"= \\\"ein boot mit mehreren männern darauf wird von einem großen pferdegespann ans\",\n \"self.fc = nn.Linear(hidden_size, output_size) def forward(self, x, hidden, cell): # x shape: (N)\",\n \"return hidden, cell class Decoder(nn.Module): def __init__( self, input_size, embedding_size, hidden_size, output_size, num_layers,\",\n \"super(Seq2Seq, self).__init__() self.encoder = encoder self.decoder = decoder def forward(self, source, target, teacher_force_ratio=0.5):\",\n \"sort_within_batch=True, sort_key=lambda x: len(x.src), device=device, ) encoder_net = Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers,\",\n \"function, so we need to do some reshapin. While we're at it #\",\n \"and targets just (N). Here we can view it in a similar #\",\n \"männern darauf wird von einem großen pferdegespann ans ufer gezogen.\\\" for epoch in\",\n \"while we're at it output = output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad() loss\",\n \"def tokenize_eng(text): return [tok.text for tok in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True, init_token=\\\"<sos>\\\",\",\n \"num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def forward(self,\",\n \"class Seq2Seq(nn.Module): def __init__(self, encoder, decoder): super(Seq2Seq, self).__init__() self.encoder = encoder self.decoder =\",\n \"hidden, cell class Decoder(nn.Module): def __init__( self, input_size, embedding_size, hidden_size, output_size, num_layers, p\",\n \"input to the Decoder which will be <SOS> token x = target[0] for\",\n \"hidden_size, output_size, num_layers, p ): super(Decoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size\",\n \"self.encoder(source) # Grab the first input to the Decoder which will be <SOS>\",\n \"the first input to the Decoder which will be <SOS> token x =\",\n \"= BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src), device=device, ) encoder_net\",\n \"batch_size that we want to send in into # our cost function, so\",\n \"decoder_net = Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout, ).to(device) model = Seq2Seq(encoder_net,\",\n \"batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src), device=device, ) encoder_net = Encoder( input_size_encoder, encoder_embedding_size, hidden_size,\",\n \"hidden_size, num_layers, p): super(Encoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers =\",\n \"batch size embedding = self.dropout(self.embedding(x)) # embedding shape: (seq_length, N, embedding_size) outputs, (hidden,\",\n \"the # network is used to. This was a long comment. x =\",\n \"# Forward prop output = model(inp_data, target) # Output is of shape (trg_len,\",\n \"input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device) decoder_net = Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size,\",\n \"to be. # Teacher Forcing is used so that the model gets used\",\n \"# x shape: (N) where N is for batch size, we want it\",\n \"torch.nn as nn import torch.optim as optim from torchtext.datasets import Multi30k from torchtext.data\",\n \"Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\\\"<pad>\\\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if\",\n \"best word the Decoder predicted (index in the vocabulary) best_guess = output.argmax(1) #\",\n \"Multi30k from torchtext.data import Field, BucketIterator import numpy as np import spacy import\",\n \"super(Decoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers self.embedding =\",\n \"word # otherwise we take the word that the Decoder predicted it to\",\n \"inp_data = batch.src.to(device) target = batch.trg.to(device) # Forward prop output = model(inp_data, target)\",\n \"num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc =\",\n \"save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence( model, sentence, german, english, device, max_length=50 ) print(f\\\"Translated\",\n \"output_size, num_layers, dec_dropout, ).to(device) model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx\",\n \"self.dropout(self.embedding(x)) # embedding shape: (seq_length, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding) #\",\n \"N) where N is batch size embedding = self.dropout(self.embedding(x)) # embedding shape: (seq_length,\",\n \"word the Decoder predicted (index in the vocabulary) best_guess = output.argmax(1) # With\",\n \"targets and get to cuda inp_data = batch.src.to(device) target = batch.trg.to(device) # Forward\",\n \"Let's also remove the start token while we're at it output = output[1:].reshape(-1,\",\n \"we want it to be (N, length_target_vocabulary) so we're # just gonna remove\",\n \"we want it to be (1, N), seq_length # is 1 here because\",\n \"the vocabulary) best_guess = output.argmax(1) # With probability of teacher_force_ratio we take the\",\n \"if we have MNIST we want to have # output to be: (N,\",\n \"are # within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent step optimizer.step()\",\n \"to seeing # similar inputs at training and testing time, if teacher forcing\",\n \"if teacher forcing is 1 # then inputs at test time might be\",\n \"best_guess return outputs ### We're ready to define everything we need for training\",\n \"import torch import torch.nn as nn import torch.optim as optim from torchtext.datasets import\",\n \"predictions = self.fc(outputs) # predictions shape: (1, N, length_target_vocabulary) to send it to\",\n \"predicted (index in the vocabulary) best_guess = output.argmax(1) # With probability of teacher_force_ratio\",\n \"def forward(self, x, hidden, cell): # x shape: (N) where N is for\",\n \"hidden_size, output_size, num_layers, dec_dropout, ).to(device) model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate)\",\n \"N is for batch size, we want it to be (1, N), seq_length\",\n \"will be <SOS> token x = target[0] for t in range(1, target_len): #\",\n \"writer.add_scalar(\\\"Training loss\\\", loss, global_step=step) step += 1 score = bleu(test_data[1:100], model, german, english,\",\n \"used so that the model gets used to seeing # similar inputs at\",\n \"embedding = self.dropout(self.embedding(x)) # embedding shape: (seq_length, N, embedding_size) outputs, (hidden, cell) =\",\n \"batch_size, target_vocab_size).to(device) hidden, cell = self.encoder(source) # Grab the first input to the\",\n \"{num_epochs}]\\\") checkpoint = {\\\"state_dict\\\": model.state_dict(), \\\"optimizer\\\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence( model,\",\n \"range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent step optimizer.step() # Plot to tensorboard writer.add_scalar(\\\"Training\",\n \"Seq2Seq(nn.Module): def __init__(self, encoder, decoder): super(Seq2Seq, self).__init__() self.encoder = encoder self.decoder = decoder\",\n \"We're ready to define everything we need for training our Seq2Seq model ###\",\n \"self.fc(outputs) # predictions shape: (1, N, length_target_vocabulary) to send it to # loss\",\n \"for batch_idx, batch in enumerate(train_iterator): # Get input and targets and get to\",\n \"fields=(german, english) ) german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module): def __init__(self,\",\n \"predictions, hidden, cell class Seq2Seq(nn.Module): def __init__(self, encoder, decoder): super(Seq2Seq, self).__init__() self.encoder =\",\n \"= encoder self.decoder = decoder def forward(self, source, target, teacher_force_ratio=0.5): batch_size = source.shape[1]\",\n \"Get input and targets and get to cuda inp_data = batch.src.to(device) target =\",\n \"self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def forward(self, x):\",\n \"num_layers, dropout=p) self.fc = nn.Linear(hidden_size, output_size) def forward(self, x, hidden, cell): # x\",\n \"different than what the # network is used to. This was a long\",\n \"was a long comment. x = target[t] if random.random() < teacher_force_ratio else best_guess\",\n \"return predictions, hidden, cell class Seq2Seq(nn.Module): def __init__(self, encoder, decoder): super(Seq2Seq, self).__init__() self.encoder\",\n \"way that we have output_words * batch_size that we want to send in\",\n \"than what the # network is used to. This was a long comment.\",\n \"sentence, german, english, device, max_length=50 ) print(f\\\"Translated example sentence: \\\\n {translated_sentence}\\\") model.train() for\",\n \"embedding_size, hidden_size, num_layers, p): super(Encoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers\",\n \"from torch.utils.tensorboard import SummaryWriter # to print to tensorboard from utils import translate_sentence,\",\n \"import random from torch.utils.tensorboard import SummaryWriter # to print to tensorboard from utils\",\n \"spacy.load(\\\"de\\\") spacy_eng = spacy.load(\\\"en\\\") def tokenize_ger(text): return [tok.text for tok in spacy_ger.tokenizer(text)] def\",\n \"target[0] for t in range(1, target_len): # Use previous hidden, cell as context\",\n \"= nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc = nn.Linear(hidden_size, output_size) def forward(self, x, hidden,\",\n \"Use previous hidden, cell as context from encoder at start output, hidden, cell\",\n \"# With probability of teacher_force_ratio we take the actual next word # otherwise\",\n \"x = target[0] for t in range(1, target_len): # Use previous hidden, cell\",\n \"model.state_dict(), \\\"optimizer\\\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence( model, sentence, german, english, device,\",\n \"example sentence: \\\\n {translated_sentence}\\\") model.train() for batch_idx, batch in enumerate(train_iterator): # Get input\",\n \"similar # way that we have output_words * batch_size that we want to\",\n \"output, hidden, cell = self.decoder(x, hidden, cell) # Store next output prediction outputs[t]\",\n \"in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\") english = Field( tokenize=tokenize_eng, lower=True,\",\n \"x, hidden, cell): # x shape: (N) where N is for batch size,\",\n \"= self.rnn(embedding, (hidden, cell)) # outputs shape: (1, N, hidden_size) predictions = self.fc(outputs)\",\n \"to be: (N, 10) and targets just (N). Here we can view it\",\n \"max_norm=1) # Gradient descent step optimizer.step() # Plot to tensorboard writer.add_scalar(\\\"Training loss\\\", loss,\",\n \"encoder self.decoder = decoder def forward(self, source, target, teacher_force_ratio=0.5): batch_size = source.shape[1] target_len\",\n \"cell class Decoder(nn.Module): def __init__( self, input_size, embedding_size, hidden_size, output_size, num_layers, p ):\",\n \"# Let's also remove the start token while we're at it output =\",\n \"both RNN's num_layers = 2 enc_dropout = 0.5 dec_dropout = 0.5 # Tensorboard\",\n \"embedding shape: (1, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding, (hidden, cell)) #\",\n \"self, input_size, embedding_size, hidden_size, output_size, num_layers, p ): super(Decoder, self).__init__() self.dropout = nn.Dropout(p)\",\n \"self.dropout(self.embedding(x)) # embedding shape: (1, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding, (hidden,\",\n \"english.vocab.stoi[\\\"<pad>\\\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\\\"my_checkpoint.pth.tar\\\"), model, optimizer) sentence = \\\"ein boot\",\n \"example if we have MNIST we want to have # output to be:\",\n \"in enumerate(train_iterator): # Get input and targets and get to cuda inp_data =\",\n \"we need for training our Seq2Seq model ### # Training hyperparameters num_epochs =\",\n \"view it in a similar # way that we have output_words * batch_size\",\n \"torch.utils.tensorboard import SummaryWriter # to print to tensorboard from utils import translate_sentence, bleu,\",\n \"0.001 batch_size = 64 # Model hyperparameters load_model = False device = torch.device(\\\"cuda\\\"\",\n \"self.encoder = encoder self.decoder = decoder def forward(self, source, target, teacher_force_ratio=0.5): batch_size =\",\n \"# embedding shape: (seq_length, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding) # outputs\",\n \"so we're # just gonna remove the first dim predictions = predictions.squeeze(0) return\",\n \"seeing # similar inputs at training and testing time, if teacher forcing is\",\n \"it to be. # Teacher Forcing is used so that the model gets\",\n \"need to do some reshapin. While we're at it # Let's also remove\",\n \"Back prop loss.backward() # Clip to avoid exploding gradient issues, makes sure grads\",\n \"Decoder predicted it to be. # Teacher Forcing is used so that the\",\n \"nice loss plot writer = SummaryWriter(f\\\"runs/loss_plot\\\") step = 0 train_iterator, valid_iterator, test_iterator =\",\n \"spacy.load(\\\"en\\\") def tokenize_ger(text): return [tok.text for tok in spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text\",\n \"where N is for batch size, we want it to be (1, N),\",\n \"and not a sentence x = x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) # embedding shape:\",\n \"length_target_vocabulary) so we're # just gonna remove the first dim predictions = predictions.squeeze(0)\",\n \"cell class Seq2Seq(nn.Module): def __init__(self, encoder, decoder): super(Seq2Seq, self).__init__() self.encoder = encoder self.decoder\",\n \"start output, hidden, cell = self.decoder(x, hidden, cell) # Store next output prediction\",\n \"target_len = target.shape[0] target_vocab_size = len(english.vocab) outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell\",\n \"random from torch.utils.tensorboard import SummaryWriter # to print to tensorboard from utils import\",\n \"# Teacher Forcing is used so that the model gets used to seeing\",\n \"completely different than what the # network is used to. This was a\",\n \"to have # output to be: (N, 10) and targets just (N). Here\",\n \"target) # Output is of shape (trg_len, batch_size, output_dim) but Cross Entropy Loss\",\n \"hidden, cell): # x shape: (N) where N is for batch size, we\",\n \"it output = output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output, target)\",\n \"for batch size, we want it to be (1, N), seq_length # is\",\n \"x = target[t] if random.random() < teacher_force_ratio else best_guess return outputs ### We're\",\n \"= optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\\\"<pad>\\\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\\\"my_checkpoint.pth.tar\\\"), model,\",\n \"checkpoint = {\\\"state_dict\\\": model.state_dict(), \\\"optimizer\\\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence( model, sentence,\",\n \"translated_sentence = translate_sentence( model, sentence, german, english, device, max_length=50 ) print(f\\\"Translated example sentence:\",\n \"just (N). Here we can view it in a similar # way that\",\n \"= self.dropout(self.embedding(x)) # embedding shape: (seq_length, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding)\",\n \"Forcing is used so that the model gets used to seeing # similar\",\n \"False device = torch.device(\\\"cuda\\\" if torch.cuda.is_available() else \\\"cpu\\\") input_size_encoder = len(german.vocab) input_size_decoder =\",\n \"boot mit mehreren männern darauf wird von einem großen pferdegespann ans ufer gezogen.\\\"\",\n \"= SummaryWriter(f\\\"runs/loss_plot\\\") step = 0 train_iterator, valid_iterator, test_iterator = BucketIterator.splits( (train_data, valid_data, test_data),\",\n \"Here we can view it in a similar # way that we have\",\n \"loss, global_step=step) step += 1 score = bleu(test_data[1:100], model, german, english, device) print(f\\\"Bleu\",\n \"to # loss function we want it to be (N, length_target_vocabulary) so we're\",\n \"grads are # within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent step\",\n \"source.shape[1] target_len = target.shape[0] target_vocab_size = len(english.vocab) outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden,\",\n \"self.rnn(embedding) # outputs shape: (seq_length, N, hidden_size) return hidden, cell class Decoder(nn.Module): def\",\n \"source, target, teacher_force_ratio=0.5): batch_size = source.shape[1] target_len = target.shape[0] target_vocab_size = len(english.vocab) outputs\",\n \"if torch.cuda.is_available() else \\\"cpu\\\") input_size_encoder = len(german.vocab) input_size_decoder = len(english.vocab) output_size = len(english.vocab)\",\n \"t in range(1, target_len): # Use previous hidden, cell as context from encoder\",\n \"2 enc_dropout = 0.5 dec_dropout = 0.5 # Tensorboard to get nice loss\",\n \"embedding_size) outputs, (hidden, cell) = self.rnn(embedding, (hidden, cell)) # outputs shape: (1, N,\",\n \"train_data, valid_data, test_data = Multi30k.splits( exts=(\\\".de\\\", \\\".en\\\"), fields=(german, english) ) german.build_vocab(train_data, max_size=10000, min_freq=2)\",\n \"enc_dropout ).to(device) decoder_net = Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout, ).to(device) model\",\n \"= batch.src.to(device) target = batch.trg.to(device) # Forward prop output = model(inp_data, target) #\",\n \"optimizer.zero_grad() loss = criterion(output, target) # Back prop loss.backward() # Clip to avoid\",\n \"= target[0] for t in range(1, target_len): # Use previous hidden, cell as\",\n \"mit mehreren männern darauf wird von einem großen pferdegespann ans ufer gezogen.\\\" for\",\n \"= num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def\",\n \"the actual next word # otherwise we take the word that the Decoder\",\n \"Plot to tensorboard writer.add_scalar(\\\"Training loss\\\", loss, global_step=step) step += 1 score = bleu(test_data[1:100],\",\n \"global_step=step) step += 1 score = bleu(test_data[1:100], model, german, english, device) print(f\\\"Bleu score\",\n \"Clip to avoid exploding gradient issues, makes sure grads are # within a\",\n \"hyperparameters num_epochs = 100 learning_rate = 0.001 batch_size = 64 # Model hyperparameters\",\n \"doesn't take input in that form. For example if we have MNIST we\",\n \"that form. For example if we have MNIST we want to have #\",\n \"test_iterator = BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src), device=device, )\",\n \"großen pferdegespann ans ufer gezogen.\\\" for epoch in range(num_epochs): print(f\\\"[Epoch {epoch} / {num_epochs}]\\\")\",\n \"BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src), device=device, ) encoder_net =\",\n \"outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell = self.encoder(source) # Grab the first\",\n \"want it to be (N, length_target_vocabulary) so we're # just gonna remove the\",\n \"of teacher_force_ratio we take the actual next word # otherwise we take the\",\n \"reshapin. While we're at it # Let's also remove the start token while\",\n \"= output # Get the best word the Decoder predicted (index in the\",\n \"spacy_eng = spacy.load(\\\"en\\\") def tokenize_ger(text): return [tok.text for tok in spacy_ger.tokenizer(text)] def tokenize_eng(text):\",\n \"Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout, ).to(device) model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer\",\n \"Forward prop output = model(inp_data, target) # Output is of shape (trg_len, batch_size,\",\n \"output # Get the best word the Decoder predicted (index in the vocabulary)\",\n \") print(f\\\"Translated example sentence: \\\\n {translated_sentence}\\\") model.train() for batch_idx, batch in enumerate(train_iterator): #\",\n \"import torch.optim as optim from torchtext.datasets import Multi30k from torchtext.data import Field, BucketIterator\",\n \"load_checkpoint spacy_ger = spacy.load(\\\"de\\\") spacy_eng = spacy.load(\\\"en\\\") def tokenize_ger(text): return [tok.text for tok\",\n \"): super(Decoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers self.embedding\",\n \"is of shape (trg_len, batch_size, output_dim) but Cross Entropy Loss # doesn't take\",\n \"prop loss.backward() # Clip to avoid exploding gradient issues, makes sure grads are\",\n \"= output.argmax(1) # With probability of teacher_force_ratio we take the actual next word\",\n \"import spacy import random from torch.utils.tensorboard import SummaryWriter # to print to tensorboard\",\n \"hidden_size, num_layers, enc_dropout ).to(device) decoder_net = Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout,\",\n \"= output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output, target) # Back\",\n \"as optim from torchtext.datasets import Multi30k from torchtext.data import Field, BucketIterator import numpy\",\n \"german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module): def __init__(self, input_size, embedding_size, hidden_size,\",\n \"predictions shape: (1, N, length_target_vocabulary) to send it to # loss function we\",\n \"hidden, cell as context from encoder at start output, hidden, cell = self.decoder(x,\",\n \"model gets used to seeing # similar inputs at training and testing time,\",\n \"encoder at start output, hidden, cell = self.decoder(x, hidden, cell) # Store next\",\n \"0.5 # Tensorboard to get nice loss plot writer = SummaryWriter(f\\\"runs/loss_plot\\\") step =\",\n \"be: (N, 10) and targets just (N). Here we can view it in\",\n \"token x = target[0] for t in range(1, target_len): # Use previous hidden,\",\n \"outputs shape: (seq_length, N, hidden_size) return hidden, cell class Decoder(nn.Module): def __init__( self,\",\n \"cell)) # outputs shape: (1, N, hidden_size) predictions = self.fc(outputs) # predictions shape:\",\n \"a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent step optimizer.step() # Plot to\",\n \"While we're at it # Let's also remove the start token while we're\",\n \"print to tensorboard from utils import translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger = spacy.load(\\\"de\\\")\",\n \"batch_size = source.shape[1] target_len = target.shape[0] target_vocab_size = len(english.vocab) outputs = torch.zeros(target_len, batch_size,\",\n \"= Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device) decoder_net = Decoder( input_size_decoder, decoder_embedding_size,\",\n \"to print to tensorboard from utils import translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger =\",\n \"self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc = nn.Linear(hidden_size, output_size) def forward(self, x,\",\n \"# Get the best word the Decoder predicted (index in the vocabulary) best_guess\",\n \"do some reshapin. While we're at it # Let's also remove the start\",\n \"For example if we have MNIST we want to have # output to\",\n \"input_size, embedding_size, hidden_size, output_size, num_layers, p ): super(Decoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size\",\n \"test_data = Multi30k.splits( exts=(\\\".de\\\", \\\".en\\\"), fields=(german, english) ) german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000,\",\n \"N, hidden_size) return hidden, cell class Decoder(nn.Module): def __init__( self, input_size, embedding_size, hidden_size,\",\n \"dropout=p) def forward(self, x): # x shape: (seq_length, N) where N is batch\",\n \"# Use previous hidden, cell as context from encoder at start output, hidden,\",\n \"and get to cuda inp_data = batch.src.to(device) target = batch.trg.to(device) # Forward prop\",\n \"so we need to do some reshapin. While we're at it # Let's\",\n \"= Field( tokenize=tokenize_eng, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\" ) train_data, valid_data, test_data = Multi30k.splits( exts=(\\\".de\\\",\",\n \"num_layers, enc_dropout ).to(device) decoder_net = Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout, ).to(device)\",\n \"for training our Seq2Seq model ### # Training hyperparameters num_epochs = 100 learning_rate\",\n \"english) ) german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module): def __init__(self, input_size,\",\n \"long comment. x = target[t] if random.random() < teacher_force_ratio else best_guess return outputs\",\n \"target.shape[0] target_vocab_size = len(english.vocab) outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell = self.encoder(source)\",\n \"we're at it output = output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad() loss =\",\n \"{translated_sentence}\\\") model.train() for batch_idx, batch in enumerate(train_iterator): # Get input and targets and\",\n \"import numpy as np import spacy import random from torch.utils.tensorboard import SummaryWriter #\",\n \"output.argmax(1) # With probability of teacher_force_ratio we take the actual next word #\",\n \"Decoder predicted (index in the vocabulary) best_guess = output.argmax(1) # With probability of\",\n \"self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers self.embedding = nn.Embedding(input_size,\",\n \"get to cuda inp_data = batch.src.to(device) target = batch.trg.to(device) # Forward prop output\",\n \"which will be <SOS> token x = target[0] for t in range(1, target_len):\",\n \"as np import spacy import random from torch.utils.tensorboard import SummaryWriter # to print\",\n \"N, hidden_size) predictions = self.fc(outputs) # predictions shape: (1, N, length_target_vocabulary) to send\",\n \"torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell = self.encoder(source) # Grab the first input to\",\n \"then inputs at test time might be completely different than what the #\",\n \"self.decoder = decoder def forward(self, source, target, teacher_force_ratio=0.5): batch_size = source.shape[1] target_len =\",\n \"# Model hyperparameters load_model = False device = torch.device(\\\"cuda\\\" if torch.cuda.is_available() else \\\"cpu\\\")\",\n \"dec_dropout = 0.5 # Tensorboard to get nice loss plot writer = SummaryWriter(f\\\"runs/loss_plot\\\")\",\n \"device=device, ) encoder_net = Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device) decoder_net =\",\n \"to cuda inp_data = batch.src.to(device) target = batch.trg.to(device) # Forward prop output =\",\n \"gets used to seeing # similar inputs at training and testing time, if\",\n \"# predictions shape: (1, N, length_target_vocabulary) to send it to # loss function\",\n \"first dim predictions = predictions.squeeze(0) return predictions, hidden, cell class Seq2Seq(nn.Module): def __init__(self,\",\n \"N), seq_length # is 1 here because we are sending in a single\",\n \"(1, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding, (hidden, cell)) # outputs shape:\",\n \"x: len(x.src), device=device, ) encoder_net = Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device)\",\n \"training our Seq2Seq model ### # Training hyperparameters num_epochs = 100 learning_rate =\",\n \"eos_token=\\\"<eos>\\\" ) train_data, valid_data, test_data = Multi30k.splits( exts=(\\\".de\\\", \\\".en\\\"), fields=(german, english) ) german.build_vocab(train_data,\",\n \"tok in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\") english = Field( tokenize=tokenize_eng,\",\n \"= english.vocab.stoi[\\\"<pad>\\\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\\\"my_checkpoint.pth.tar\\\"), model, optimizer) sentence = \\\"ein\",\n \"N is batch size embedding = self.dropout(self.embedding(x)) # embedding shape: (seq_length, N, embedding_size)\",\n \"to get nice loss plot writer = SummaryWriter(f\\\"runs/loss_plot\\\") step = 0 train_iterator, valid_iterator,\",\n \"decoder): super(Seq2Seq, self).__init__() self.encoder = encoder self.decoder = decoder def forward(self, source, target,\",\n \"test time might be completely different than what the # network is used\",\n \"hidden_size) return hidden, cell class Decoder(nn.Module): def __init__( self, input_size, embedding_size, hidden_size, output_size,\",\n \"hidden, cell class Seq2Seq(nn.Module): def __init__(self, encoder, decoder): super(Seq2Seq, self).__init__() self.encoder = encoder\",\n \"= 1024 # Needs to be the same for both RNN's num_layers =\",\n \"= 0.5 # Tensorboard to get nice loss plot writer = SummaryWriter(f\\\"runs/loss_plot\\\") step\",\n \"be (1, N), seq_length # is 1 here because we are sending in\",\n \"criterion(output, target) # Back prop loss.backward() # Clip to avoid exploding gradient issues,\",\n \"for t in range(1, target_len): # Use previous hidden, cell as context from\",\n \"as context from encoder at start output, hidden, cell = self.decoder(x, hidden, cell)\",\n \"/ {num_epochs}]\\\") checkpoint = {\\\"state_dict\\\": model.state_dict(), \\\"optimizer\\\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence(\",\n \"SummaryWriter # to print to tensorboard from utils import translate_sentence, bleu, save_checkpoint, load_checkpoint\",\n \"p): super(Encoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers self.embedding\",\n \"so that the model gets used to seeing # similar inputs at training\",\n \"forcing is 1 # then inputs at test time might be completely different\",\n \"valid_iterator, test_iterator = BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src), device=device,\",\n \"outputs, (hidden, cell) = self.rnn(embedding) # outputs shape: (seq_length, N, hidden_size) return hidden,\",\n \"we are sending in a single word and not a sentence x =\",\n \"einem großen pferdegespann ans ufer gezogen.\\\" for epoch in range(num_epochs): print(f\\\"[Epoch {epoch} /\",\n \"gezogen.\\\" for epoch in range(num_epochs): print(f\\\"[Epoch {epoch} / {num_epochs}]\\\") checkpoint = {\\\"state_dict\\\": model.state_dict(),\",\n \"With probability of teacher_force_ratio we take the actual next word # otherwise we\",\n \"# doesn't take input in that form. For example if we have MNIST\",\n \"10) and targets just (N). Here we can view it in a similar\",\n \"loss = criterion(output, target) # Back prop loss.backward() # Clip to avoid exploding\",\n \"have MNIST we want to have # output to be: (N, 10) and\",\n \"if random.random() < teacher_force_ratio else best_guess return outputs ### We're ready to define\",\n \"shape: (1, N, hidden_size) predictions = self.fc(outputs) # predictions shape: (1, N, length_target_vocabulary)\",\n \"to define everything we need for training our Seq2Seq model ### # Training\",\n \"output = output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output, target) #\",\n \"input and targets and get to cuda inp_data = batch.src.to(device) target = batch.trg.to(device)\",\n \"can view it in a similar # way that we have output_words *\",\n \"predicted it to be. # Teacher Forcing is used so that the model\",\n \"torch.cuda.is_available() else \\\"cpu\\\") input_size_encoder = len(german.vocab) input_size_decoder = len(english.vocab) output_size = len(english.vocab) encoder_embedding_size\",\n \"# Output is of shape (trg_len, batch_size, output_dim) but Cross Entropy Loss #\",\n \"= self.fc(outputs) # predictions shape: (1, N, length_target_vocabulary) to send it to #\",\n \"\\\"optimizer\\\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence( model, sentence, german, english, device, max_length=50\",\n \"device, max_length=50 ) print(f\\\"Translated example sentence: \\\\n {translated_sentence}\\\") model.train() for batch_idx, batch in\",\n \"<filename>ML/Pytorch/more_advanced/Seq2Seq/seq2seq.py<gh_stars>1000+ import torch import torch.nn as nn import torch.optim as optim from torchtext.datasets\",\n \"# Plot to tensorboard writer.add_scalar(\\\"Training loss\\\", loss, global_step=step) step += 1 score =\",\n \"target = batch.trg.to(device) # Forward prop output = model(inp_data, target) # Output is\",\n \"tensorboard writer.add_scalar(\\\"Training loss\\\", loss, global_step=step) step += 1 score = bleu(test_data[1:100], model, german,\",\n \"a similar # way that we have output_words * batch_size that we want\",\n \"writer = SummaryWriter(f\\\"runs/loss_plot\\\") step = 0 train_iterator, valid_iterator, test_iterator = BucketIterator.splits( (train_data, valid_data,\",\n \").to(device) decoder_net = Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout, ).to(device) model =\",\n \"targets just (N). Here we can view it in a similar # way\",\n \"cell = self.encoder(source) # Grab the first input to the Decoder which will\",\n \"teacher forcing is 1 # then inputs at test time might be completely\",\n \"optim from torchtext.datasets import Multi30k from torchtext.data import Field, BucketIterator import numpy as\",\n \"self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers self.embedding = nn.Embedding(input_size, embedding_size)\",\n \"embedding_size, hidden_size, output_size, num_layers, p ): super(Decoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size =\",\n \"is batch size embedding = self.dropout(self.embedding(x)) # embedding shape: (seq_length, N, embedding_size) outputs,\",\n \"# Grab the first input to the Decoder which will be <SOS> token\",\n \"to tensorboard from utils import translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger = spacy.load(\\\"de\\\") spacy_eng\",\n \"# loss function we want it to be (N, length_target_vocabulary) so we're #\",\n \"= len(german.vocab) input_size_decoder = len(english.vocab) output_size = len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size =\",\n \"# Store next output prediction outputs[t] = output # Get the best word\",\n \"(seq_length, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding) # outputs shape: (seq_length, N,\",\n \"function we want it to be (N, length_target_vocabulary) so we're # just gonna\",\n \"sure grads are # within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent\",\n \"len(english.vocab) output_size = len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size = 300 hidden_size = 1024\",\n \"to send in into # our cost function, so we need to do\",\n \"This was a long comment. x = target[t] if random.random() < teacher_force_ratio else\",\n \"num_layers = 2 enc_dropout = 0.5 dec_dropout = 0.5 # Tensorboard to get\",\n \"to the Decoder which will be <SOS> token x = target[0] for t\",\n \"inputs at test time might be completely different than what the # network\",\n \"Seq2Seq model ### # Training hyperparameters num_epochs = 100 learning_rate = 0.001 batch_size\",\n \"batch size, we want it to be (1, N), seq_length # is 1\",\n \"the Decoder predicted (index in the vocabulary) best_guess = output.argmax(1) # With probability\",\n \"cell) = self.rnn(embedding) # outputs shape: (seq_length, N, hidden_size) return hidden, cell class\",\n \"outputs, (hidden, cell) = self.rnn(embedding, (hidden, cell)) # outputs shape: (1, N, hidden_size)\",\n \"nn import torch.optim as optim from torchtext.datasets import Multi30k from torchtext.data import Field,\",\n \"in the vocabulary) best_guess = output.argmax(1) # With probability of teacher_force_ratio we take\",\n \"target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output, target) # Back prop loss.backward() # Clip to\",\n \"# within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent step optimizer.step() #\",\n \"loss\\\", loss, global_step=step) step += 1 score = bleu(test_data[1:100], model, german, english, device)\",\n \"= target[t] if random.random() < teacher_force_ratio else best_guess return outputs ### We're ready\",\n \"range(1, target_len): # Use previous hidden, cell as context from encoder at start\",\n \"our cost function, so we need to do some reshapin. While we're at\",\n \"input_size, embedding_size, hidden_size, num_layers, p): super(Encoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size\",\n \"Loss # doesn't take input in that form. For example if we have\",\n \"descent step optimizer.step() # Plot to tensorboard writer.add_scalar(\\\"Training loss\\\", loss, global_step=step) step +=\",\n \"self.num_layers = num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p)\",\n \"otherwise we take the word that the Decoder predicted it to be. #\",\n \"everything we need for training our Seq2Seq model ### # Training hyperparameters num_epochs\",\n \"# similar inputs at training and testing time, if teacher forcing is 1\",\n \"at it # Let's also remove the start token while we're at it\",\n \"valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src), device=device, ) encoder_net = Encoder( input_size_encoder,\",\n \"if load_model: load_checkpoint(torch.load(\\\"my_checkpoint.pth.tar\\\"), model, optimizer) sentence = \\\"ein boot mit mehreren männern darauf\",\n \"want to send in into # our cost function, so we need to\",\n \"that we have output_words * batch_size that we want to send in into\",\n \"send it to # loss function we want it to be (N, length_target_vocabulary)\",\n \"Decoder which will be <SOS> token x = target[0] for t in range(1,\",\n \"__init__(self, encoder, decoder): super(Seq2Seq, self).__init__() self.encoder = encoder self.decoder = decoder def forward(self,\",\n \"predictions.squeeze(0) return predictions, hidden, cell class Seq2Seq(nn.Module): def __init__(self, encoder, decoder): super(Seq2Seq, self).__init__()\",\n \"torch.device(\\\"cuda\\\" if torch.cuda.is_available() else \\\"cpu\\\") input_size_encoder = len(german.vocab) input_size_decoder = len(english.vocab) output_size =\",\n \"= target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output, target) # Back prop loss.backward() # Clip\",\n \") train_data, valid_data, test_data = Multi30k.splits( exts=(\\\".de\\\", \\\".en\\\"), fields=(german, english) ) german.build_vocab(train_data, max_size=10000,\",\n \"context from encoder at start output, hidden, cell = self.decoder(x, hidden, cell) #\",\n \"(seq_length, N, hidden_size) return hidden, cell class Decoder(nn.Module): def __init__( self, input_size, embedding_size,\",\n \"forward(self, source, target, teacher_force_ratio=0.5): batch_size = source.shape[1] target_len = target.shape[0] target_vocab_size = len(english.vocab)\",\n \"max_length=50 ) print(f\\\"Translated example sentence: \\\\n {translated_sentence}\\\") model.train() for batch_idx, batch in enumerate(train_iterator):\",\n \"N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding, (hidden, cell)) # outputs shape: (1,\",\n \"step += 1 score = bleu(test_data[1:100], model, german, english, device) print(f\\\"Bleu score {score*100:.2f}\\\")\",\n \"import SummaryWriter # to print to tensorboard from utils import translate_sentence, bleu, save_checkpoint,\",\n \"cost function, so we need to do some reshapin. While we're at it\",\n \"output_dim) but Cross Entropy Loss # doesn't take input in that form. For\",\n \"dim predictions = predictions.squeeze(0) return predictions, hidden, cell class Seq2Seq(nn.Module): def __init__(self, encoder,\",\n \"outputs[t] = output # Get the best word the Decoder predicted (index in\",\n \"we can view it in a similar # way that we have output_words\",\n \"target = target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output, target) # Back prop loss.backward() #\",\n \"spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\") english = Field( tokenize=tokenize_eng, lower=True, init_token=\\\"<sos>\\\",\",\n \"= 100 learning_rate = 0.001 batch_size = 64 # Model hyperparameters load_model =\",\n \"dropout=p) self.fc = nn.Linear(hidden_size, output_size) def forward(self, x, hidden, cell): # x shape:\",\n \"Training hyperparameters num_epochs = 100 learning_rate = 0.001 batch_size = 64 # Model\",\n \"nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn =\",\n \"len(x.src), device=device, ) encoder_net = Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device) decoder_net\",\n \"1 here because we are sending in a single word and not a\",\n \"batch.trg.to(device) # Forward prop output = model(inp_data, target) # Output is of shape\",\n \"# to print to tensorboard from utils import translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger\",\n \"# otherwise we take the word that the Decoder predicted it to be.\",\n \"is used to. This was a long comment. x = target[t] if random.random()\",\n \"# Training hyperparameters num_epochs = 100 learning_rate = 0.001 batch_size = 64 #\",\n \"numpy as np import spacy import random from torch.utils.tensorboard import SummaryWriter # to\",\n \"[tok.text for tok in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\") english =\",\n \"embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc = nn.Linear(hidden_size, output_size) def forward(self,\",\n \"target_vocab_size).to(device) hidden, cell = self.encoder(source) # Grab the first input to the Decoder\",\n \"testing time, if teacher forcing is 1 # then inputs at test time\",\n \"= predictions.squeeze(0) return predictions, hidden, cell class Seq2Seq(nn.Module): def __init__(self, encoder, decoder): super(Seq2Seq,\",\n \"= 2 enc_dropout = 0.5 dec_dropout = 0.5 # Tensorboard to get nice\",\n \"# output to be: (N, 10) and targets just (N). Here we can\",\n \"used to seeing # similar inputs at training and testing time, if teacher\",\n \"to tensorboard writer.add_scalar(\\\"Training loss\\\", loss, global_step=step) step += 1 score = bleu(test_data[1:100], model,\",\n \"Cross Entropy Loss # doesn't take input in that form. For example if\",\n \"hidden_size = 1024 # Needs to be the same for both RNN's num_layers\",\n \"Field(tokenize=tokenize_ger, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\") english = Field( tokenize=tokenize_eng, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\" ) train_data,\",\n \"{epoch} / {num_epochs}]\\\") checkpoint = {\\\"state_dict\\\": model.state_dict(), \\\"optimizer\\\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence =\",\n \"= 300 hidden_size = 1024 # Needs to be the same for both\",\n \"train_iterator, valid_iterator, test_iterator = BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src),\",\n \"(index in the vocabulary) best_guess = output.argmax(1) # With probability of teacher_force_ratio we\",\n \"# Back prop loss.backward() # Clip to avoid exploding gradient issues, makes sure\",\n \"a sentence x = x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) # embedding shape: (1, N,\",\n \"where N is batch size embedding = self.dropout(self.embedding(x)) # embedding shape: (seq_length, N,\",\n \"### # Training hyperparameters num_epochs = 100 learning_rate = 0.001 batch_size = 64\",\n \"max_size=10000, min_freq=2) class Encoder(nn.Module): def __init__(self, input_size, embedding_size, hidden_size, num_layers, p): super(Encoder, self).__init__()\",\n \"< teacher_force_ratio else best_guess return outputs ### We're ready to define everything we\",\n \"to be the same for both RNN's num_layers = 2 enc_dropout = 0.5\",\n \"optimizer) sentence = \\\"ein boot mit mehreren männern darauf wird von einem großen\",\n \"x shape: (seq_length, N) where N is batch size embedding = self.dropout(self.embedding(x)) #\",\n \"= False device = torch.device(\\\"cuda\\\" if torch.cuda.is_available() else \\\"cpu\\\") input_size_encoder = len(german.vocab) input_size_decoder\",\n \"size, we want it to be (1, N), seq_length # is 1 here\",\n \"forward(self, x): # x shape: (seq_length, N) where N is batch size embedding\",\n \"num_layers, p ): super(Decoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers =\",\n \"decoder def forward(self, source, target, teacher_force_ratio=0.5): batch_size = source.shape[1] target_len = target.shape[0] target_vocab_size\",\n \"from encoder at start output, hidden, cell = self.decoder(x, hidden, cell) # Store\",\n \"in a single word and not a sentence x = x.unsqueeze(0) embedding =\",\n \"model, optimizer) sentence = \\\"ein boot mit mehreren männern darauf wird von einem\",\n \"(1, N), seq_length # is 1 here because we are sending in a\",\n \"x): # x shape: (seq_length, N) where N is batch size embedding =\",\n \"= 0.001 batch_size = 64 # Model hyperparameters load_model = False device =\",\n \"def forward(self, source, target, teacher_force_ratio=0.5): batch_size = source.shape[1] target_len = target.shape[0] target_vocab_size =\",\n \"random.random() < teacher_force_ratio else best_guess return outputs ### We're ready to define everything\",\n \"optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\\\"<pad>\\\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\\\"my_checkpoint.pth.tar\\\"), model, optimizer)\",\n \"# Tensorboard to get nice loss plot writer = SummaryWriter(f\\\"runs/loss_plot\\\") step = 0\",\n \"to. This was a long comment. x = target[t] if random.random() < teacher_force_ratio\",\n \"the same for both RNN's num_layers = 2 enc_dropout = 0.5 dec_dropout =\",\n \"same for both RNN's num_layers = 2 enc_dropout = 0.5 dec_dropout = 0.5\",\n \"that we want to send in into # our cost function, so we\",\n \"(N, length_target_vocabulary) so we're # just gonna remove the first dim predictions =\",\n \"= len(english.vocab) outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell = self.encoder(source) # Grab\",\n \"encoder, decoder): super(Seq2Seq, self).__init__() self.encoder = encoder self.decoder = decoder def forward(self, source,\",\n \"to be (1, N), seq_length # is 1 here because we are sending\",\n \"spacy_ger = spacy.load(\\\"de\\\") spacy_eng = spacy.load(\\\"en\\\") def tokenize_ger(text): return [tok.text for tok in\",\n \"be. # Teacher Forcing is used so that the model gets used to\",\n \"= nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def forward(self, x): # x shape: (seq_length, N)\",\n \"remove the start token while we're at it output = output[1:].reshape(-1, output.shape[2]) target\",\n \"def __init__(self, input_size, embedding_size, hidden_size, num_layers, p): super(Encoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size\",\n \"makes sure grads are # within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient\",\n \"# x shape: (seq_length, N) where N is batch size embedding = self.dropout(self.embedding(x))\",\n \"super(Encoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers self.embedding =\",\n \"token while we're at it output = output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad()\",\n \"teacher_force_ratio=0.5): batch_size = source.shape[1] target_len = target.shape[0] target_vocab_size = len(english.vocab) outputs = torch.zeros(target_len,\",\n \"inputs at training and testing time, if teacher forcing is 1 # then\",\n \"learning_rate = 0.001 batch_size = 64 # Model hyperparameters load_model = False device\",\n \"tokenize_ger(text): return [tok.text for tok in spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text for tok\",\n \"be the same for both RNN's num_layers = 2 enc_dropout = 0.5 dec_dropout\",\n \"output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output, target) # Back prop loss.backward()\",\n \"also remove the start token while we're at it output = output[1:].reshape(-1, output.shape[2])\",\n \"take the actual next word # otherwise we take the word that the\",\n \"teacher_force_ratio else best_guess return outputs ### We're ready to define everything we need\",\n \"german, english, device, max_length=50 ) print(f\\\"Translated example sentence: \\\\n {translated_sentence}\\\") model.train() for batch_idx,\",\n \"min_freq=2) class Encoder(nn.Module): def __init__(self, input_size, embedding_size, hidden_size, num_layers, p): super(Encoder, self).__init__() self.dropout\",\n \"(1, N, length_target_vocabulary) to send it to # loss function we want it\",\n \"we want to send in into # our cost function, so we need\",\n \"sentence = \\\"ein boot mit mehreren männern darauf wird von einem großen pferdegespann\",\n \"class Encoder(nn.Module): def __init__(self, input_size, embedding_size, hidden_size, num_layers, p): super(Encoder, self).__init__() self.dropout =\",\n \"seq_length # is 1 here because we are sending in a single word\",\n \"len(german.vocab) input_size_decoder = len(english.vocab) output_size = len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size = 300\",\n \"init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\" ) train_data, valid_data, test_data = Multi30k.splits( exts=(\\\".de\\\", \\\".en\\\"), fields=(german, english) )\",\n \"(hidden, cell) = self.rnn(embedding) # outputs shape: (seq_length, N, hidden_size) return hidden, cell\",\n \"spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text for tok in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True,\",\n \"just gonna remove the first dim predictions = predictions.squeeze(0) return predictions, hidden, cell\",\n \"len(english.vocab) outputs = torch.zeros(target_len, batch_size, target_vocab_size).to(device) hidden, cell = self.encoder(source) # Grab the\",\n \"output prediction outputs[t] = output # Get the best word the Decoder predicted\",\n \"Encoder(nn.Module): def __init__(self, input_size, embedding_size, hidden_size, num_layers, p): super(Encoder, self).__init__() self.dropout = nn.Dropout(p)\",\n \"we take the actual next word # otherwise we take the word that\",\n \"min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module): def __init__(self, input_size, embedding_size, hidden_size, num_layers, p):\",\n \"(N). Here we can view it in a similar # way that we\",\n \"tokenize_eng(text): return [tok.text for tok in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\")\",\n \"be <SOS> token x = target[0] for t in range(1, target_len): # Use\",\n \"np import spacy import random from torch.utils.tensorboard import SummaryWriter # to print to\",\n \"= Multi30k.splits( exts=(\\\".de\\\", \\\".en\\\"), fields=(german, english) ) german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2)\",\n \"else best_guess return outputs ### We're ready to define everything we need for\",\n \"self.rnn(embedding, (hidden, cell)) # outputs shape: (1, N, hidden_size) predictions = self.fc(outputs) #\",\n \"our Seq2Seq model ### # Training hyperparameters num_epochs = 100 learning_rate = 0.001\",\n \"wird von einem großen pferdegespann ans ufer gezogen.\\\" for epoch in range(num_epochs): print(f\\\"[Epoch\",\n \"(1, N, hidden_size) predictions = self.fc(outputs) # predictions shape: (1, N, length_target_vocabulary) to\",\n \"= len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size = 300 hidden_size = 1024 # Needs\",\n \"forward(self, x, hidden, cell): # x shape: (N) where N is for batch\",\n \"remove the first dim predictions = predictions.squeeze(0) return predictions, hidden, cell class Seq2Seq(nn.Module):\",\n \"outputs ### We're ready to define everything we need for training our Seq2Seq\",\n \"what the # network is used to. This was a long comment. x\",\n \"device = torch.device(\\\"cuda\\\" if torch.cuda.is_available() else \\\"cpu\\\") input_size_encoder = len(german.vocab) input_size_decoder = len(english.vocab)\",\n \"batch in enumerate(train_iterator): # Get input and targets and get to cuda inp_data\",\n \"have output_words * batch_size that we want to send in into # our\",\n \"within a healthy range torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent step optimizer.step() # Plot\",\n \"into # our cost function, so we need to do some reshapin. While\",\n \"nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model: load_checkpoint(torch.load(\\\"my_checkpoint.pth.tar\\\"), model, optimizer) sentence = \\\"ein boot mit mehreren männern\",\n \"nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc = nn.Linear(hidden_size, output_size) def\",\n \"input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout, ).to(device) model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer =\",\n \"target) # Back prop loss.backward() # Clip to avoid exploding gradient issues, makes\",\n \"shape: (seq_length, N, hidden_size) return hidden, cell class Decoder(nn.Module): def __init__( self, input_size,\",\n \"Field( tokenize=tokenize_eng, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\" ) train_data, valid_data, test_data = Multi30k.splits( exts=(\\\".de\\\", \\\".en\\\"),\",\n \"for both RNN's num_layers = 2 enc_dropout = 0.5 dec_dropout = 0.5 #\",\n \"# Clip to avoid exploding gradient issues, makes sure grads are # within\",\n \"Field, BucketIterator import numpy as np import spacy import random from torch.utils.tensorboard import\",\n \"probability of teacher_force_ratio we take the actual next word # otherwise we take\",\n \"is for batch size, we want it to be (1, N), seq_length #\",\n \"shape: (1, N, length_target_vocabulary) to send it to # loss function we want\",\n \"return outputs ### We're ready to define everything we need for training our\",\n \"ans ufer gezogen.\\\" for epoch in range(num_epochs): print(f\\\"[Epoch {epoch} / {num_epochs}]\\\") checkpoint =\",\n \"print(f\\\"[Epoch {epoch} / {num_epochs}]\\\") checkpoint = {\\\"state_dict\\\": model.state_dict(), \\\"optimizer\\\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence\",\n \"import translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger = spacy.load(\\\"de\\\") spacy_eng = spacy.load(\\\"en\\\") def tokenize_ger(text):\",\n \"self.hidden_size = hidden_size self.num_layers = num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size,\",\n \"eos_token=\\\"<eos>\\\") english = Field( tokenize=tokenize_eng, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\" ) train_data, valid_data, test_data =\",\n \"here because we are sending in a single word and not a sentence\",\n \"300 hidden_size = 1024 # Needs to be the same for both RNN's\",\n \"= spacy.load(\\\"en\\\") def tokenize_ger(text): return [tok.text for tok in spacy_ger.tokenizer(text)] def tokenize_eng(text): return\",\n \"test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x: len(x.src), device=device, ) encoder_net = Encoder( input_size_encoder, encoder_embedding_size,\",\n \"avoid exploding gradient issues, makes sure grads are # within a healthy range\",\n \"= nn.Linear(hidden_size, output_size) def forward(self, x, hidden, cell): # x shape: (N) where\",\n \"= decoder def forward(self, source, target, teacher_force_ratio=0.5): batch_size = source.shape[1] target_len = target.shape[0]\",\n \"def forward(self, x): # x shape: (seq_length, N) where N is batch size\",\n \"import Field, BucketIterator import numpy as np import spacy import random from torch.utils.tensorboard\",\n \"the first dim predictions = predictions.squeeze(0) return predictions, hidden, cell class Seq2Seq(nn.Module): def\",\n \"plot writer = SummaryWriter(f\\\"runs/loss_plot\\\") step = 0 train_iterator, valid_iterator, test_iterator = BucketIterator.splits( (train_data,\",\n \"decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\\\"<pad>\\\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx) if load_model:\",\n \"torchtext.datasets import Multi30k from torchtext.data import Field, BucketIterator import numpy as np import\",\n \"model, sentence, german, english, device, max_length=50 ) print(f\\\"Translated example sentence: \\\\n {translated_sentence}\\\") model.train()\",\n \"decoder_embedding_size = 300 hidden_size = 1024 # Needs to be the same for\",\n \"sort_key=lambda x: len(x.src), device=device, ) encoder_net = Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout\",\n \"input in that form. For example if we have MNIST we want to\",\n \"\\\\n {translated_sentence}\\\") model.train() for batch_idx, batch in enumerate(train_iterator): # Get input and targets\",\n \"= {\\\"state_dict\\\": model.state_dict(), \\\"optimizer\\\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence( model, sentence, german,\",\n \"cuda inp_data = batch.src.to(device) target = batch.trg.to(device) # Forward prop output = model(inp_data,\",\n \"nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def forward(self, x): # x shape: (seq_length, N) where\",\n \"SummaryWriter(f\\\"runs/loss_plot\\\") step = 0 train_iterator, valid_iterator, test_iterator = BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size,\",\n \"nn.Linear(hidden_size, output_size) def forward(self, x, hidden, cell): # x shape: (N) where N\",\n \"at training and testing time, if teacher forcing is 1 # then inputs\",\n \"shape (trg_len, batch_size, output_dim) but Cross Entropy Loss # doesn't take input in\",\n \"num_layers, p): super(Encoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers\",\n \"darauf wird von einem großen pferdegespann ans ufer gezogen.\\\" for epoch in range(num_epochs):\",\n \"Grab the first input to the Decoder which will be <SOS> token x\",\n \"next word # otherwise we take the word that the Decoder predicted it\",\n \"from torchtext.data import Field, BucketIterator import numpy as np import spacy import random\",\n \"return [tok.text for tok in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\") english\",\n \"64 # Model hyperparameters load_model = False device = torch.device(\\\"cuda\\\" if torch.cuda.is_available() else\",\n \"= 0 train_iterator, valid_iterator, test_iterator = BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda\",\n \"= torch.device(\\\"cuda\\\" if torch.cuda.is_available() else \\\"cpu\\\") input_size_encoder = len(german.vocab) input_size_decoder = len(english.vocab) output_size\",\n \"von einem großen pferdegespann ans ufer gezogen.\\\" for epoch in range(num_epochs): print(f\\\"[Epoch {epoch}\",\n \"self.decoder(x, hidden, cell) # Store next output prediction outputs[t] = output # Get\",\n \"in spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text for tok in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger,\",\n \"network is used to. This was a long comment. x = target[t] if\",\n \"nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc = nn.Linear(hidden_size, output_size) def forward(self, x, hidden, cell):\",\n \"= Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\\\"<pad>\\\"] criterion = nn.CrossEntropyLoss(ignore_index=pad_idx)\",\n \"tensorboard from utils import translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger = spacy.load(\\\"de\\\") spacy_eng =\",\n \"embedding shape: (seq_length, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding) # outputs shape:\",\n \"N, length_target_vocabulary) to send it to # loss function we want it to\",\n \"output_size, num_layers, p ): super(Decoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers\",\n \"shape: (N) where N is for batch size, we want it to be\",\n \"self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def forward(self, x): # x shape: (seq_length,\",\n \"Gradient descent step optimizer.step() # Plot to tensorboard writer.add_scalar(\\\"Training loss\\\", loss, global_step=step) step\",\n \"hyperparameters load_model = False device = torch.device(\\\"cuda\\\" if torch.cuda.is_available() else \\\"cpu\\\") input_size_encoder =\",\n \"it in a similar # way that we have output_words * batch_size that\",\n \"be (N, length_target_vocabulary) so we're # just gonna remove the first dim predictions\",\n \"nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def forward(self, x): # x\",\n \"def tokenize_ger(text): return [tok.text for tok in spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text for\",\n \"import Multi30k from torchtext.data import Field, BucketIterator import numpy as np import spacy\",\n \"def __init__( self, input_size, embedding_size, hidden_size, output_size, num_layers, p ): super(Decoder, self).__init__() self.dropout\",\n \"# outputs shape: (1, N, hidden_size) predictions = self.fc(outputs) # predictions shape: (1,\",\n \"= self.encoder(source) # Grab the first input to the Decoder which will be\",\n \"= translate_sentence( model, sentence, german, english, device, max_length=50 ) print(f\\\"Translated example sentence: \\\\n\",\n \"N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding) # outputs shape: (seq_length, N, hidden_size)\",\n \"next output prediction outputs[t] = output # Get the best word the Decoder\",\n \"MNIST we want to have # output to be: (N, 10) and targets\",\n \"teacher_force_ratio we take the actual next word # otherwise we take the word\",\n \"# Gradient descent step optimizer.step() # Plot to tensorboard writer.add_scalar(\\\"Training loss\\\", loss, global_step=step)\",\n \"is 1 # then inputs at test time might be completely different than\",\n \"# network is used to. This was a long comment. x = target[t]\",\n \"RNN's num_layers = 2 enc_dropout = 0.5 dec_dropout = 0.5 # Tensorboard to\",\n \"# Get input and targets and get to cuda inp_data = batch.src.to(device) target\",\n \"target[t] if random.random() < teacher_force_ratio else best_guess return outputs ### We're ready to\",\n \"output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1) optimizer.zero_grad() loss = criterion(output, target) # Back prop\",\n \"= batch.trg.to(device) # Forward prop output = model(inp_data, target) # Output is of\",\n \"0 train_iterator, valid_iterator, test_iterator = BucketIterator.splits( (train_data, valid_data, test_data), batch_size=batch_size, sort_within_batch=True, sort_key=lambda x:\",\n \"hidden_size) predictions = self.fc(outputs) # predictions shape: (1, N, length_target_vocabulary) to send it\",\n \"output_size = len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size = 300 hidden_size = 1024 #\",\n \"= spacy.load(\\\"de\\\") spacy_eng = spacy.load(\\\"en\\\") def tokenize_ger(text): return [tok.text for tok in spacy_ger.tokenizer(text)]\",\n \"* batch_size that we want to send in into # our cost function,\",\n \"best_guess = output.argmax(1) # With probability of teacher_force_ratio we take the actual next\",\n \"that the model gets used to seeing # similar inputs at training and\",\n \"start token while we're at it output = output[1:].reshape(-1, output.shape[2]) target = target[1:].reshape(-1)\",\n \"(seq_length, N) where N is batch size embedding = self.dropout(self.embedding(x)) # embedding shape:\",\n \"single word and not a sentence x = x.unsqueeze(0) embedding = self.dropout(self.embedding(x)) #\",\n \"__init__(self, input_size, embedding_size, hidden_size, num_layers, p): super(Encoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size =\",\n \"might be completely different than what the # network is used to. This\",\n \"enumerate(train_iterator): # Get input and targets and get to cuda inp_data = batch.src.to(device)\",\n \"hidden, cell = self.decoder(x, hidden, cell) # Store next output prediction outputs[t] =\",\n \"take input in that form. For example if we have MNIST we want\",\n \"len(english.vocab) encoder_embedding_size = 300 decoder_embedding_size = 300 hidden_size = 1024 # Needs to\",\n \"# is 1 here because we are sending in a single word and\",\n \"to do some reshapin. While we're at it # Let's also remove the\",\n \"embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) def forward(self, x): # x shape:\",\n \"time, if teacher forcing is 1 # then inputs at test time might\",\n \"300 decoder_embedding_size = 300 hidden_size = 1024 # Needs to be the same\",\n \"(N) where N is for batch size, we want it to be (1,\",\n \"at test time might be completely different than what the # network is\",\n \"gonna remove the first dim predictions = predictions.squeeze(0) return predictions, hidden, cell class\",\n \"p ): super(Decoder, self).__init__() self.dropout = nn.Dropout(p) self.hidden_size = hidden_size self.num_layers = num_layers\",\n \"target_len): # Use previous hidden, cell as context from encoder at start output,\",\n \"decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout, ).to(device) model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(),\",\n \"Store next output prediction outputs[t] = output # Get the best word the\",\n \"num_epochs = 100 learning_rate = 0.001 batch_size = 64 # Model hyperparameters load_model\",\n \"x shape: (N) where N is for batch size, we want it to\",\n \"from utils import translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger = spacy.load(\\\"de\\\") spacy_eng = spacy.load(\\\"en\\\")\",\n \"<SOS> token x = target[0] for t in range(1, target_len): # Use previous\",\n \"actual next word # otherwise we take the word that the Decoder predicted\",\n \"= criterion(output, target) # Back prop loss.backward() # Clip to avoid exploding gradient\",\n \"optimizer.step() # Plot to tensorboard writer.add_scalar(\\\"Training loss\\\", loss, global_step=step) step += 1 score\",\n \"Entropy Loss # doesn't take input in that form. For example if we\",\n \"because we are sending in a single word and not a sentence x\",\n \"get nice loss plot writer = SummaryWriter(f\\\"runs/loss_plot\\\") step = 0 train_iterator, valid_iterator, test_iterator\",\n \"# outputs shape: (seq_length, N, hidden_size) return hidden, cell class Decoder(nn.Module): def __init__(\",\n \"some reshapin. While we're at it # Let's also remove the start token\",\n \"pferdegespann ans ufer gezogen.\\\" for epoch in range(num_epochs): print(f\\\"[Epoch {epoch} / {num_epochs}]\\\") checkpoint\",\n \"the best word the Decoder predicted (index in the vocabulary) best_guess = output.argmax(1)\",\n \"outputs shape: (1, N, hidden_size) predictions = self.fc(outputs) # predictions shape: (1, N,\",\n \"= Decoder( input_size_decoder, decoder_embedding_size, hidden_size, output_size, num_layers, dec_dropout, ).to(device) model = Seq2Seq(encoder_net, decoder_net).to(device)\",\n \"Output is of shape (trg_len, batch_size, output_dim) but Cross Entropy Loss # doesn't\",\n \"batch.src.to(device) target = batch.trg.to(device) # Forward prop output = model(inp_data, target) # Output\",\n \"it # Let's also remove the start token while we're at it output\",\n \"[tok.text for tok in spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text for tok in spacy_eng.tokenizer(text)]\",\n \"### We're ready to define everything we need for training our Seq2Seq model\",\n \"self).__init__() self.encoder = encoder self.decoder = decoder def forward(self, source, target, teacher_force_ratio=0.5): batch_size\",\n \"load_model = False device = torch.device(\\\"cuda\\\" if torch.cuda.is_available() else \\\"cpu\\\") input_size_encoder = len(german.vocab)\",\n \"mehreren männern darauf wird von einem großen pferdegespann ans ufer gezogen.\\\" for epoch\",\n \"init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\") english = Field( tokenize=tokenize_eng, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\" ) train_data, valid_data, test_data\",\n \"translate_sentence, bleu, save_checkpoint, load_checkpoint spacy_ger = spacy.load(\\\"de\\\") spacy_eng = spacy.load(\\\"en\\\") def tokenize_ger(text): return\",\n \"= self.decoder(x, hidden, cell) # Store next output prediction outputs[t] = output #\",\n \"the model gets used to seeing # similar inputs at training and testing\",\n \"# way that we have output_words * batch_size that we want to send\",\n \") german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module): def __init__(self, input_size, embedding_size,\",\n \"word that the Decoder predicted it to be. # Teacher Forcing is used\",\n \"\\\"ein boot mit mehreren männern darauf wird von einem großen pferdegespann ans ufer\",\n \"vocabulary) best_guess = output.argmax(1) # With probability of teacher_force_ratio we take the actual\",\n \"prediction outputs[t] = output # Get the best word the Decoder predicted (index\",\n \"for tok in spacy_eng.tokenizer(text)] german = Field(tokenize=tokenize_ger, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\") english = Field(\",\n \"size embedding = self.dropout(self.embedding(x)) # embedding shape: (seq_length, N, embedding_size) outputs, (hidden, cell)\",\n \"100 learning_rate = 0.001 batch_size = 64 # Model hyperparameters load_model = False\",\n \"torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1) # Gradient descent step optimizer.step() # Plot to tensorboard writer.add_scalar(\\\"Training loss\\\",\",\n \"Decoder(nn.Module): def __init__( self, input_size, embedding_size, hidden_size, output_size, num_layers, p ): super(Decoder, self).__init__()\",\n \"ufer gezogen.\\\" for epoch in range(num_epochs): print(f\\\"[Epoch {epoch} / {num_epochs}]\\\") checkpoint = {\\\"state_dict\\\":\",\n \"= num_layers self.embedding = nn.Embedding(input_size, embedding_size) self.rnn = nn.LSTM(embedding_size, hidden_size, num_layers, dropout=p) self.fc\",\n \"in range(1, target_len): # Use previous hidden, cell as context from encoder at\",\n \"# embedding shape: (1, N, embedding_size) outputs, (hidden, cell) = self.rnn(embedding, (hidden, cell))\",\n \"cell) # Store next output prediction outputs[t] = output # Get the best\",\n \"optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence( model, sentence, german, english, device, max_length=50 )\",\n \"it to be (N, length_target_vocabulary) so we're # just gonna remove the first\",\n \"= self.rnn(embedding) # outputs shape: (seq_length, N, hidden_size) return hidden, cell class Decoder(nn.Module):\",\n \"model = Seq2Seq(encoder_net, decoder_net).to(device) optimizer = optim.Adam(model.parameters(), lr=learning_rate) pad_idx = english.vocab.stoi[\\\"<pad>\\\"] criterion =\",\n \"= 300 decoder_embedding_size = 300 hidden_size = 1024 # Needs to be the\",\n \"tok in spacy_ger.tokenizer(text)] def tokenize_eng(text): return [tok.text for tok in spacy_eng.tokenizer(text)] german =\",\n \"take the word that the Decoder predicted it to be. # Teacher Forcing\",\n \"is 1 here because we are sending in a single word and not\",\n \"{\\\"state_dict\\\": model.state_dict(), \\\"optimizer\\\": optimizer.state_dict()} save_checkpoint(checkpoint) model.eval() translated_sentence = translate_sentence( model, sentence, german, english,\",\n \"german = Field(tokenize=tokenize_ger, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\") english = Field( tokenize=tokenize_eng, lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\"\",\n \"loss plot writer = SummaryWriter(f\\\"runs/loss_plot\\\") step = 0 train_iterator, valid_iterator, test_iterator = BucketIterator.splits(\",\n \"first input to the Decoder which will be <SOS> token x = target[0]\",\n \"BucketIterator import numpy as np import spacy import random from torch.utils.tensorboard import SummaryWriter\",\n \"we want to have # output to be: (N, 10) and targets just\",\n \"def __init__(self, encoder, decoder): super(Seq2Seq, self).__init__() self.encoder = encoder self.decoder = decoder def\",\n \"lower=True, init_token=\\\"<sos>\\\", eos_token=\\\"<eos>\\\" ) train_data, valid_data, test_data = Multi30k.splits( exts=(\\\".de\\\", \\\".en\\\"), fields=(german, english)\",\n \"\\\".en\\\"), fields=(german, english) ) german.build_vocab(train_data, max_size=10000, min_freq=2) english.build_vocab(train_data, max_size=10000, min_freq=2) class Encoder(nn.Module): def\",\n \"model.train() for batch_idx, batch in enumerate(train_iterator): # Get input and targets and get\",\n \"Model hyperparameters load_model = False device = torch.device(\\\"cuda\\\" if torch.cuda.is_available() else \\\"cpu\\\") input_size_encoder\",\n \"class Decoder(nn.Module): def __init__( self, input_size, embedding_size, hidden_size, output_size, num_layers, p ): super(Decoder,\"\n]","isConversational":false}}},{"rowIdx":4591,"cells":{"ngram":{"kind":"list like","value":["class LightImitateMixin(Agent): \"\"\"Abstract class that handles passing expert trajectories alongside self-play sampling \"\"\"","import Agent from parlai.core.message import Message from random import sample import pathlib path","for i in range(len(utterances)): history = self.histories[i] history.append( (self.self_speaker_token if not other else","def _convert_history_to_other(self, history): history = [ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in turn else","List import string from parlai.core.agents import Agent from parlai.core.message import Message from random","Dict[str, Any] = None): self.id = \"LightChatbotSelfPlay\" self.train_step = 0 self.self_speaker_token = \"<speaker_self>\"","random import sample import pathlib path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \"\"\"Abstract class that","+= 1 # Add generated histories to data ones imitate = [] sample","[] sample = [] for i, observation in enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1])","if not other else self.other_speaker_token) + utterances[i] ) self.histories[i] = history def _convert_history_to_other(self,","other=False): for i in range(len(utterances)): history = self.histories[i] history.append( (self.self_speaker_token if not other","def batch_act(self, observations): self.train_step += 1 # Add generated histories to data ones","pass def _update_histories(self, utterances, other=False): for i in range(len(utterances)): history = self.histories[i] history.append(","else self.other_speaker_token) + utterances[i] ) self.histories[i] = history def _convert_history_to_other(self, history): history =","[ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in turn else turn.replace(self.other_speaker_token, self.self_speaker_token) for turn in","len(dialog[1]) > 0 ] ) imitate.extend( [ dialog for dialog in observation[\"text\"] if","here\"\"\" pass def batch_sample(self, dialogs) -> List[str]: \"\"\"Implement update here\"\"\" pass def batch_update(self):","pathlib path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \"\"\"Abstract class that handles passing expert trajectories","import string from parlai.core.agents import Agent from parlai.core.message import Message from random import","weights here\"\"\" pass def _update_histories(self, utterances, other=False): for i in range(len(utterances)): history =","len(dialog[1]) > 0 ] ) self.batch_imitate(imitate) utterances = self.batch_sample(sample) if ( self.train_step %",") self.histories[i] = history def _convert_history_to_other(self, history): history = [ turn.replace(self.self_speaker_token, self.other_speaker_token) if","utterances, other=False): for i in range(len(utterances)): history = self.histories[i] history.append( (self.self_speaker_token if not","self-play sampling \"\"\" def __init__(self, opt: Dict[str, Any], shared: Dict[str, Any] = None):","opt: Dict[str, Any], shared: Dict[str, Any] = None): self.id = \"LightChatbotSelfPlay\" self.train_step =","\"LightChatbotSelfPlay\" self.train_step = 0 self.self_speaker_token = \"<speaker_self>\" self.other_speaker_token = \"<speaker_other>\" def act(self): raise","None): self.id = \"LightChatbotSelfPlay\" self.train_step = 0 self.self_speaker_token = \"<speaker_self>\" self.other_speaker_token = \"<speaker_other>\"","typing import Dict, Any, List import string from parlai.core.agents import Agent from parlai.core.message","sampling utterances and memorization here\"\"\" pass def batch_sample(self, dialogs) -> List[str]: \"\"\"Implement update","history): history = [ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in turn else turn.replace(self.other_speaker_token, self.self_speaker_token)","\"\"\" def __init__(self, opt: Dict[str, Any], shared: Dict[str, Any] = None): self.id =","import sample import pathlib path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \"\"\"Abstract class that handles","observations] def batch_imitate(self, dialogs): \"\"\"Implement sampling utterances and memorization here\"\"\" pass def batch_sample(self,","and self.train_step != 0: self.checkpoint([sample, utterances]) return [{\"id\": self.id} for _ in observations]","0 self.self_speaker_token = \"<speaker_self>\" self.other_speaker_token = \"<speaker_other>\" def act(self): raise NotImplementedError() def batch_act(self,","for i, observation in enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1]) for dialog in observation[\"text\"]","self.batch_imitate(imitate) utterances = self.batch_sample(sample) if ( self.train_step % self.episode_num_dialog_dump == 0 ) and","[] for i, observation in enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1]) for dialog in","def batch_update(self): \"\"\"Update weights here\"\"\" pass def _update_histories(self, utterances, other=False): for i in","return [{\"id\": self.id} for _ in observations] def batch_imitate(self, dialogs): \"\"\"Implement sampling utterances","def act(self): raise NotImplementedError() def batch_act(self, observations): self.train_step += 1 # Add generated","from parlai.core.agents import Agent from parlai.core.message import Message from random import sample import","[ dialog for dialog in observation[\"text\"] if len(dialog[1]) > 0 ] ) self.batch_imitate(imitate)","trajectories alongside self-play sampling \"\"\" def __init__(self, opt: Dict[str, Any], shared: Dict[str, Any]","class that handles passing expert trajectories alongside self-play sampling \"\"\" def __init__(self, opt:",") self.batch_imitate(imitate) utterances = self.batch_sample(sample) if ( self.train_step % self.episode_num_dialog_dump == 0 )","= 0 self.self_speaker_token = \"<speaker_self>\" self.other_speaker_token = \"<speaker_other>\" def act(self): raise NotImplementedError() def","self.train_step = 0 self.self_speaker_token = \"<speaker_self>\" self.other_speaker_token = \"<speaker_other>\" def act(self): raise NotImplementedError()","[{\"id\": self.id} for _ in observations] def batch_imitate(self, dialogs): \"\"\"Implement sampling utterances and","Dict[str, Any], shared: Dict[str, Any] = None): self.id = \"LightChatbotSelfPlay\" self.train_step = 0","generated histories to data ones imitate = [] sample = [] for i,","in observation[\"text\"] if len(dialog[1]) > 0 ] ) self.batch_imitate(imitate) utterances = self.batch_sample(sample) if","def batch_imitate(self, dialogs): \"\"\"Implement sampling utterances and memorization here\"\"\" pass def batch_sample(self, dialogs)","from typing import Dict, Any, List import string from parlai.core.agents import Agent from","import pathlib path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \"\"\"Abstract class that handles passing expert","self.histories[i] = history def _convert_history_to_other(self, history): history = [ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token","Dict, Any, List import string from parlai.core.agents import Agent from parlai.core.message import Message","dialog in observation[\"text\"] if len(dialog[1]) > 0 ] ) imitate.extend( [ dialog for","string from parlai.core.agents import Agent from parlai.core.message import Message from random import sample","= [ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in turn else turn.replace(self.other_speaker_token, self.self_speaker_token) for turn","if ( self.train_step % self.episode_num_dialog_dump == 0 ) and self.train_step != 0: self.checkpoint([sample,","history.append( (self.self_speaker_token if not other else self.other_speaker_token) + utterances[i] ) self.histories[i] = history","turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in turn else turn.replace(self.other_speaker_token, self.self_speaker_token) for turn in history","self.batch_sample(sample) if ( self.train_step % self.episode_num_dialog_dump == 0 ) and self.train_step != 0:","import Dict, Any, List import string from parlai.core.agents import Agent from parlai.core.message import","update here\"\"\" pass def batch_update(self): \"\"\"Update weights here\"\"\" pass def _update_histories(self, utterances, other=False):","\"\"\"Abstract class that handles passing expert trajectories alongside self-play sampling \"\"\" def __init__(self,","handles passing expert trajectories alongside self-play sampling \"\"\" def __init__(self, opt: Dict[str, Any],","in range(len(utterances)): history = self.histories[i] history.append( (self.self_speaker_token if not other else self.other_speaker_token) +","0 ) and self.train_step != 0: self.checkpoint([sample, utterances]) return [{\"id\": self.id} for _","import Message from random import sample import pathlib path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent):","dialog for dialog in observation[\"text\"] if len(dialog[1]) > 0 ] ) self.batch_imitate(imitate) utterances","from parlai.core.message import Message from random import sample import pathlib path = pathlib.Path(__file__).parent.absolute()","imitate.extend( [ dialog for dialog in observation[\"text\"] if len(dialog[1]) > 0 ] )","for dialog in observation[\"text\"] if len(dialog[1]) > 0 ] ) self.batch_imitate(imitate) utterances =","for dialog in observation[\"text\"] if len(dialog[1]) > 0 ] ) imitate.extend( [ dialog","utterances and memorization here\"\"\" pass def batch_sample(self, dialogs) -> List[str]: \"\"\"Implement update here\"\"\"","Any], shared: Dict[str, Any] = None): self.id = \"LightChatbotSelfPlay\" self.train_step = 0 self.self_speaker_token","_update_histories(self, utterances, other=False): for i in range(len(utterances)): history = self.histories[i] history.append( (self.self_speaker_token if","history def _convert_history_to_other(self, history): history = [ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in turn","range(len(utterances)): history = self.histories[i] history.append( (self.self_speaker_token if not other else self.other_speaker_token) + utterances[i]","( self.train_step % self.episode_num_dialog_dump == 0 ) and self.train_step != 0: self.checkpoint([sample, utterances])","observations): self.train_step += 1 # Add generated histories to data ones imitate =","\"\"\"Implement sampling utterances and memorization here\"\"\" pass def batch_sample(self, dialogs) -> List[str]: \"\"\"Implement","if len(dialog[1]) > 0 ] ) self.batch_imitate(imitate) utterances = self.batch_sample(sample) if ( self.train_step","Agent from parlai.core.message import Message from random import sample import pathlib path =","> 0 ] ) self.batch_imitate(imitate) utterances = self.batch_sample(sample) if ( self.train_step % self.episode_num_dialog_dump","self.checkpoint([sample, utterances]) return [{\"id\": self.id} for _ in observations] def batch_imitate(self, dialogs): \"\"\"Implement","+ utterances[i] ) self.histories[i] = history def _convert_history_to_other(self, history): history = [ turn.replace(self.self_speaker_token,","0 ] ) self.batch_imitate(imitate) utterances = self.batch_sample(sample) if ( self.train_step % self.episode_num_dialog_dump ==","sampling \"\"\" def __init__(self, opt: Dict[str, Any], shared: Dict[str, Any] = None): self.id","= [] for i, observation in enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1]) for dialog","enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1]) for dialog in observation[\"text\"] if len(dialog[1]) > 0","batch_act(self, observations): self.train_step += 1 # Add generated histories to data ones imitate",") imitate.extend( [ dialog for dialog in observation[\"text\"] if len(dialog[1]) > 0 ]","Message from random import sample import pathlib path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \"\"\"Abstract","dialogs) -> List[str]: \"\"\"Implement update here\"\"\" pass def batch_update(self): \"\"\"Update weights here\"\"\" pass","self.self_speaker_token in turn else turn.replace(self.other_speaker_token, self.self_speaker_token) for turn in history ] return history","= \"<speaker_other>\" def act(self): raise NotImplementedError() def batch_act(self, observations): self.train_step += 1 #","\"\"\"Update weights here\"\"\" pass def _update_histories(self, utterances, other=False): for i in range(len(utterances)): history","Any, List import string from parlai.core.agents import Agent from parlai.core.message import Message from","in enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1]) for dialog in observation[\"text\"] if len(dialog[1]) >","\"\"\"Implement update here\"\"\" pass def batch_update(self): \"\"\"Update weights here\"\"\" pass def _update_histories(self, utterances,","__init__(self, opt: Dict[str, Any], shared: Dict[str, Any] = None): self.id = \"LightChatbotSelfPlay\" self.train_step","utterances[i] ) self.histories[i] = history def _convert_history_to_other(self, history): history = [ turn.replace(self.self_speaker_token, self.other_speaker_token)","history = self.histories[i] history.append( (self.self_speaker_token if not other else self.other_speaker_token) + utterances[i] )","dialogs): \"\"\"Implement sampling utterances and memorization here\"\"\" pass def batch_sample(self, dialogs) -> List[str]:","\"<speaker_other>\" def act(self): raise NotImplementedError() def batch_act(self, observations): self.train_step += 1 # Add",") and self.train_step != 0: self.checkpoint([sample, utterances]) return [{\"id\": self.id} for _ in","pass def batch_sample(self, dialogs) -> List[str]: \"\"\"Implement update here\"\"\" pass def batch_update(self): \"\"\"Update","1 # Add generated histories to data ones imitate = [] sample =","(dialog[0], dialog[1][:-1]) for dialog in observation[\"text\"] if len(dialog[1]) > 0 ] ) imitate.extend(","parlai.core.message import Message from random import sample import pathlib path = pathlib.Path(__file__).parent.absolute() class","# Add generated histories to data ones imitate = [] sample = []","sample = [] for i, observation in enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1]) for","== 0 ) and self.train_step != 0: self.checkpoint([sample, utterances]) return [{\"id\": self.id} for","sample import pathlib path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \"\"\"Abstract class that handles passing","here\"\"\" pass def batch_update(self): \"\"\"Update weights here\"\"\" pass def _update_histories(self, utterances, other=False): for","= \"<speaker_self>\" self.other_speaker_token = \"<speaker_other>\" def act(self): raise NotImplementedError() def batch_act(self, observations): self.train_step","imitate = [] sample = [] for i, observation in enumerate(observations): sample.extend( [","history = [ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in turn else turn.replace(self.other_speaker_token, self.self_speaker_token) for","0 ] ) imitate.extend( [ dialog for dialog in observation[\"text\"] if len(dialog[1]) >","observation[\"text\"] if len(dialog[1]) > 0 ] ) imitate.extend( [ dialog for dialog in","def __init__(self, opt: Dict[str, Any], shared: Dict[str, Any] = None): self.id = \"LightChatbotSelfPlay\"","batch_imitate(self, dialogs): \"\"\"Implement sampling utterances and memorization here\"\"\" pass def batch_sample(self, dialogs) ->","and memorization here\"\"\" pass def batch_sample(self, dialogs) -> List[str]: \"\"\"Implement update here\"\"\" pass","pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \"\"\"Abstract class that handles passing expert trajectories alongside self-play sampling","% self.episode_num_dialog_dump == 0 ) and self.train_step != 0: self.checkpoint([sample, utterances]) return [{\"id\":","here\"\"\" pass def _update_histories(self, utterances, other=False): for i in range(len(utterances)): history = self.histories[i]","data ones imitate = [] sample = [] for i, observation in enumerate(observations):","> 0 ] ) imitate.extend( [ dialog for dialog in observation[\"text\"] if len(dialog[1])","[ (dialog[0], dialog[1][:-1]) for dialog in observation[\"text\"] if len(dialog[1]) > 0 ] )","shared: Dict[str, Any] = None): self.id = \"LightChatbotSelfPlay\" self.train_step = 0 self.self_speaker_token =","ones imitate = [] sample = [] for i, observation in enumerate(observations): sample.extend(","Any] = None): self.id = \"LightChatbotSelfPlay\" self.train_step = 0 self.self_speaker_token = \"<speaker_self>\" self.other_speaker_token","self.self_speaker_token = \"<speaker_self>\" self.other_speaker_token = \"<speaker_other>\" def act(self): raise NotImplementedError() def batch_act(self, observations):","= [] sample = [] for i, observation in enumerate(observations): sample.extend( [ (dialog[0],","parlai.core.agents import Agent from parlai.core.message import Message from random import sample import pathlib","to data ones imitate = [] sample = [] for i, observation in","= \"LightChatbotSelfPlay\" self.train_step = 0 self.self_speaker_token = \"<speaker_self>\" self.other_speaker_token = \"<speaker_other>\" def act(self):","\"<speaker_self>\" self.other_speaker_token = \"<speaker_other>\" def act(self): raise NotImplementedError() def batch_act(self, observations): self.train_step +=","passing expert trajectories alongside self-play sampling \"\"\" def __init__(self, opt: Dict[str, Any], shared:","i, observation in enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1]) for dialog in observation[\"text\"] if","histories to data ones imitate = [] sample = [] for i, observation","LightImitateMixin(Agent): \"\"\"Abstract class that handles passing expert trajectories alongside self-play sampling \"\"\" def","observation in enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1]) for dialog in observation[\"text\"] if len(dialog[1])","expert trajectories alongside self-play sampling \"\"\" def __init__(self, opt: Dict[str, Any], shared: Dict[str,","that handles passing expert trajectories alongside self-play sampling \"\"\" def __init__(self, opt: Dict[str,","self.other_speaker_token = \"<speaker_other>\" def act(self): raise NotImplementedError() def batch_act(self, observations): self.train_step += 1","dialog in observation[\"text\"] if len(dialog[1]) > 0 ] ) self.batch_imitate(imitate) utterances = self.batch_sample(sample)","raise NotImplementedError() def batch_act(self, observations): self.train_step += 1 # Add generated histories to","for _ in observations] def batch_imitate(self, dialogs): \"\"\"Implement sampling utterances and memorization here\"\"\"","Add generated histories to data ones imitate = [] sample = [] for","= self.histories[i] history.append( (self.self_speaker_token if not other else self.other_speaker_token) + utterances[i] ) self.histories[i]","!= 0: self.checkpoint([sample, utterances]) return [{\"id\": self.id} for _ in observations] def batch_imitate(self,","List[str]: \"\"\"Implement update here\"\"\" pass def batch_update(self): \"\"\"Update weights here\"\"\" pass def _update_histories(self,","not other else self.other_speaker_token) + utterances[i] ) self.histories[i] = history def _convert_history_to_other(self, history):","def batch_sample(self, dialogs) -> List[str]: \"\"\"Implement update here\"\"\" pass def batch_update(self): \"\"\"Update weights","(self.self_speaker_token if not other else self.other_speaker_token) + utterances[i] ) self.histories[i] = history def","_convert_history_to_other(self, history): history = [ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in turn else turn.replace(self.other_speaker_token,","] ) self.batch_imitate(imitate) utterances = self.batch_sample(sample) if ( self.train_step % self.episode_num_dialog_dump == 0","= self.batch_sample(sample) if ( self.train_step % self.episode_num_dialog_dump == 0 ) and self.train_step !=","-> List[str]: \"\"\"Implement update here\"\"\" pass def batch_update(self): \"\"\"Update weights here\"\"\" pass def","observation[\"text\"] if len(dialog[1]) > 0 ] ) self.batch_imitate(imitate) utterances = self.batch_sample(sample) if (","def _update_histories(self, utterances, other=False): for i in range(len(utterances)): history = self.histories[i] history.append( (self.self_speaker_token","0: self.checkpoint([sample, utterances]) return [{\"id\": self.id} for _ in observations] def batch_imitate(self, dialogs):","self.id = \"LightChatbotSelfPlay\" self.train_step = 0 self.self_speaker_token = \"<speaker_self>\" self.other_speaker_token = \"<speaker_other>\" def","in observation[\"text\"] if len(dialog[1]) > 0 ] ) imitate.extend( [ dialog for dialog","self.train_step != 0: self.checkpoint([sample, utterances]) return [{\"id\": self.id} for _ in observations] def","memorization here\"\"\" pass def batch_sample(self, dialogs) -> List[str]: \"\"\"Implement update here\"\"\" pass def","self.other_speaker_token) + utterances[i] ) self.histories[i] = history def _convert_history_to_other(self, history): history = [","from random import sample import pathlib path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \"\"\"Abstract class","self.train_step % self.episode_num_dialog_dump == 0 ) and self.train_step != 0: self.checkpoint([sample, utterances]) return","self.id} for _ in observations] def batch_imitate(self, dialogs): \"\"\"Implement sampling utterances and memorization","in observations] def batch_imitate(self, dialogs): \"\"\"Implement sampling utterances and memorization here\"\"\" pass def","self.other_speaker_token) if self.self_speaker_token in turn else turn.replace(self.other_speaker_token, self.self_speaker_token) for turn in history ]","alongside self-play sampling \"\"\" def __init__(self, opt: Dict[str, Any], shared: Dict[str, Any] =","self.histories[i] history.append( (self.self_speaker_token if not other else self.other_speaker_token) + utterances[i] ) self.histories[i] =","batch_update(self): \"\"\"Update weights here\"\"\" pass def _update_histories(self, utterances, other=False): for i in range(len(utterances)):","= history def _convert_history_to_other(self, history): history = [ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in","] ) imitate.extend( [ dialog for dialog in observation[\"text\"] if len(dialog[1]) > 0","sample.extend( [ (dialog[0], dialog[1][:-1]) for dialog in observation[\"text\"] if len(dialog[1]) > 0 ]","_ in observations] def batch_imitate(self, dialogs): \"\"\"Implement sampling utterances and memorization here\"\"\" pass","if len(dialog[1]) > 0 ] ) imitate.extend( [ dialog for dialog in observation[\"text\"]","= None): self.id = \"LightChatbotSelfPlay\" self.train_step = 0 self.self_speaker_token = \"<speaker_self>\" self.other_speaker_token =","pass def batch_update(self): \"\"\"Update weights here\"\"\" pass def _update_histories(self, utterances, other=False): for i","self.train_step += 1 # Add generated histories to data ones imitate = []","dialog[1][:-1]) for dialog in observation[\"text\"] if len(dialog[1]) > 0 ] ) imitate.extend( [","self.episode_num_dialog_dump == 0 ) and self.train_step != 0: self.checkpoint([sample, utterances]) return [{\"id\": self.id}","utterances]) return [{\"id\": self.id} for _ in observations] def batch_imitate(self, dialogs): \"\"\"Implement sampling","utterances = self.batch_sample(sample) if ( self.train_step % self.episode_num_dialog_dump == 0 ) and self.train_step","= pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \"\"\"Abstract class that handles passing expert trajectories alongside self-play","batch_sample(self, dialogs) -> List[str]: \"\"\"Implement update here\"\"\" pass def batch_update(self): \"\"\"Update weights here\"\"\"","i in range(len(utterances)): history = self.histories[i] history.append( (self.self_speaker_token if not other else self.other_speaker_token)","other else self.other_speaker_token) + utterances[i] ) self.histories[i] = history def _convert_history_to_other(self, history): history","if self.self_speaker_token in turn else turn.replace(self.other_speaker_token, self.self_speaker_token) for turn in history ] return","path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \"\"\"Abstract class that handles passing expert trajectories alongside","act(self): raise NotImplementedError() def batch_act(self, observations): self.train_step += 1 # Add generated histories","NotImplementedError() def batch_act(self, observations): self.train_step += 1 # Add generated histories to data"],"string":"[\n \"class LightImitateMixin(Agent): \\\"\\\"\\\"Abstract class that handles passing expert trajectories alongside self-play sampling \\\"\\\"\\\"\",\n \"import Agent from parlai.core.message import Message from random import sample import pathlib path\",\n \"for i in range(len(utterances)): history = self.histories[i] history.append( (self.self_speaker_token if not other else\",\n \"def _convert_history_to_other(self, history): history = [ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in turn else\",\n \"List import string from parlai.core.agents import Agent from parlai.core.message import Message from random\",\n \"Dict[str, Any] = None): self.id = \\\"LightChatbotSelfPlay\\\" self.train_step = 0 self.self_speaker_token = \\\"<speaker_self>\\\"\",\n \"random import sample import pathlib path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \\\"\\\"\\\"Abstract class that\",\n \"+= 1 # Add generated histories to data ones imitate = [] sample\",\n \"[] sample = [] for i, observation in enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1])\",\n \"if not other else self.other_speaker_token) + utterances[i] ) self.histories[i] = history def _convert_history_to_other(self,\",\n \"other=False): for i in range(len(utterances)): history = self.histories[i] history.append( (self.self_speaker_token if not other\",\n \"def batch_act(self, observations): self.train_step += 1 # Add generated histories to data ones\",\n \"pass def _update_histories(self, utterances, other=False): for i in range(len(utterances)): history = self.histories[i] history.append(\",\n \"else self.other_speaker_token) + utterances[i] ) self.histories[i] = history def _convert_history_to_other(self, history): history =\",\n \"[ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in turn else turn.replace(self.other_speaker_token, self.self_speaker_token) for turn in\",\n \"len(dialog[1]) > 0 ] ) imitate.extend( [ dialog for dialog in observation[\\\"text\\\"] if\",\n \"here\\\"\\\"\\\" pass def batch_sample(self, dialogs) -> List[str]: \\\"\\\"\\\"Implement update here\\\"\\\"\\\" pass def batch_update(self):\",\n \"pathlib path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \\\"\\\"\\\"Abstract class that handles passing expert trajectories\",\n \"import string from parlai.core.agents import Agent from parlai.core.message import Message from random import\",\n \"weights here\\\"\\\"\\\" pass def _update_histories(self, utterances, other=False): for i in range(len(utterances)): history =\",\n \"len(dialog[1]) > 0 ] ) self.batch_imitate(imitate) utterances = self.batch_sample(sample) if ( self.train_step %\",\n \") self.histories[i] = history def _convert_history_to_other(self, history): history = [ turn.replace(self.self_speaker_token, self.other_speaker_token) if\",\n \"utterances, other=False): for i in range(len(utterances)): history = self.histories[i] history.append( (self.self_speaker_token if not\",\n \"self-play sampling \\\"\\\"\\\" def __init__(self, opt: Dict[str, Any], shared: Dict[str, Any] = None):\",\n \"opt: Dict[str, Any], shared: Dict[str, Any] = None): self.id = \\\"LightChatbotSelfPlay\\\" self.train_step =\",\n \"\\\"LightChatbotSelfPlay\\\" self.train_step = 0 self.self_speaker_token = \\\"<speaker_self>\\\" self.other_speaker_token = \\\"<speaker_other>\\\" def act(self): raise\",\n \"None): self.id = \\\"LightChatbotSelfPlay\\\" self.train_step = 0 self.self_speaker_token = \\\"<speaker_self>\\\" self.other_speaker_token = \\\"<speaker_other>\\\"\",\n \"typing import Dict, Any, List import string from parlai.core.agents import Agent from parlai.core.message\",\n \"sampling utterances and memorization here\\\"\\\"\\\" pass def batch_sample(self, dialogs) -> List[str]: \\\"\\\"\\\"Implement update\",\n \"history): history = [ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in turn else turn.replace(self.other_speaker_token, self.self_speaker_token)\",\n \"\\\"\\\"\\\" def __init__(self, opt: Dict[str, Any], shared: Dict[str, Any] = None): self.id =\",\n \"import sample import pathlib path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \\\"\\\"\\\"Abstract class that handles\",\n \"observations] def batch_imitate(self, dialogs): \\\"\\\"\\\"Implement sampling utterances and memorization here\\\"\\\"\\\" pass def batch_sample(self,\",\n \"and self.train_step != 0: self.checkpoint([sample, utterances]) return [{\\\"id\\\": self.id} for _ in observations]\",\n \"0 self.self_speaker_token = \\\"<speaker_self>\\\" self.other_speaker_token = \\\"<speaker_other>\\\" def act(self): raise NotImplementedError() def batch_act(self,\",\n \"for i, observation in enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1]) for dialog in observation[\\\"text\\\"]\",\n \"self.batch_imitate(imitate) utterances = self.batch_sample(sample) if ( self.train_step % self.episode_num_dialog_dump == 0 ) and\",\n \"[] for i, observation in enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1]) for dialog in\",\n \"def batch_update(self): \\\"\\\"\\\"Update weights here\\\"\\\"\\\" pass def _update_histories(self, utterances, other=False): for i in\",\n \"return [{\\\"id\\\": self.id} for _ in observations] def batch_imitate(self, dialogs): \\\"\\\"\\\"Implement sampling utterances\",\n \"def act(self): raise NotImplementedError() def batch_act(self, observations): self.train_step += 1 # Add generated\",\n \"from parlai.core.agents import Agent from parlai.core.message import Message from random import sample import\",\n \"[ dialog for dialog in observation[\\\"text\\\"] if len(dialog[1]) > 0 ] ) self.batch_imitate(imitate)\",\n \"trajectories alongside self-play sampling \\\"\\\"\\\" def __init__(self, opt: Dict[str, Any], shared: Dict[str, Any]\",\n \"class that handles passing expert trajectories alongside self-play sampling \\\"\\\"\\\" def __init__(self, opt:\",\n \") self.batch_imitate(imitate) utterances = self.batch_sample(sample) if ( self.train_step % self.episode_num_dialog_dump == 0 )\",\n \"= 0 self.self_speaker_token = \\\"<speaker_self>\\\" self.other_speaker_token = \\\"<speaker_other>\\\" def act(self): raise NotImplementedError() def\",\n \"self.train_step = 0 self.self_speaker_token = \\\"<speaker_self>\\\" self.other_speaker_token = \\\"<speaker_other>\\\" def act(self): raise NotImplementedError()\",\n \"[{\\\"id\\\": self.id} for _ in observations] def batch_imitate(self, dialogs): \\\"\\\"\\\"Implement sampling utterances and\",\n \"Dict[str, Any], shared: Dict[str, Any] = None): self.id = \\\"LightChatbotSelfPlay\\\" self.train_step = 0\",\n \"generated histories to data ones imitate = [] sample = [] for i,\",\n \"in observation[\\\"text\\\"] if len(dialog[1]) > 0 ] ) self.batch_imitate(imitate) utterances = self.batch_sample(sample) if\",\n \"def batch_imitate(self, dialogs): \\\"\\\"\\\"Implement sampling utterances and memorization here\\\"\\\"\\\" pass def batch_sample(self, dialogs)\",\n \"from typing import Dict, Any, List import string from parlai.core.agents import Agent from\",\n \"import pathlib path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \\\"\\\"\\\"Abstract class that handles passing expert\",\n \"self.histories[i] = history def _convert_history_to_other(self, history): history = [ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token\",\n \"Dict, Any, List import string from parlai.core.agents import Agent from parlai.core.message import Message\",\n \"dialog in observation[\\\"text\\\"] if len(dialog[1]) > 0 ] ) imitate.extend( [ dialog for\",\n \"string from parlai.core.agents import Agent from parlai.core.message import Message from random import sample\",\n \"= [ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in turn else turn.replace(self.other_speaker_token, self.self_speaker_token) for turn\",\n \"if ( self.train_step % self.episode_num_dialog_dump == 0 ) and self.train_step != 0: self.checkpoint([sample,\",\n \"history.append( (self.self_speaker_token if not other else self.other_speaker_token) + utterances[i] ) self.histories[i] = history\",\n \"turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in turn else turn.replace(self.other_speaker_token, self.self_speaker_token) for turn in history\",\n \"self.batch_sample(sample) if ( self.train_step % self.episode_num_dialog_dump == 0 ) and self.train_step != 0:\",\n \"import Dict, Any, List import string from parlai.core.agents import Agent from parlai.core.message import\",\n \"update here\\\"\\\"\\\" pass def batch_update(self): \\\"\\\"\\\"Update weights here\\\"\\\"\\\" pass def _update_histories(self, utterances, other=False):\",\n \"\\\"\\\"\\\"Abstract class that handles passing expert trajectories alongside self-play sampling \\\"\\\"\\\" def __init__(self,\",\n \"handles passing expert trajectories alongside self-play sampling \\\"\\\"\\\" def __init__(self, opt: Dict[str, Any],\",\n \"in range(len(utterances)): history = self.histories[i] history.append( (self.self_speaker_token if not other else self.other_speaker_token) +\",\n \"0 ) and self.train_step != 0: self.checkpoint([sample, utterances]) return [{\\\"id\\\": self.id} for _\",\n \"import Message from random import sample import pathlib path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent):\",\n \"dialog for dialog in observation[\\\"text\\\"] if len(dialog[1]) > 0 ] ) self.batch_imitate(imitate) utterances\",\n \"from parlai.core.message import Message from random import sample import pathlib path = pathlib.Path(__file__).parent.absolute()\",\n \"imitate.extend( [ dialog for dialog in observation[\\\"text\\\"] if len(dialog[1]) > 0 ] )\",\n \"for dialog in observation[\\\"text\\\"] if len(dialog[1]) > 0 ] ) self.batch_imitate(imitate) utterances =\",\n \"for dialog in observation[\\\"text\\\"] if len(dialog[1]) > 0 ] ) imitate.extend( [ dialog\",\n \"utterances and memorization here\\\"\\\"\\\" pass def batch_sample(self, dialogs) -> List[str]: \\\"\\\"\\\"Implement update here\\\"\\\"\\\"\",\n \"Any], shared: Dict[str, Any] = None): self.id = \\\"LightChatbotSelfPlay\\\" self.train_step = 0 self.self_speaker_token\",\n \"_update_histories(self, utterances, other=False): for i in range(len(utterances)): history = self.histories[i] history.append( (self.self_speaker_token if\",\n \"history def _convert_history_to_other(self, history): history = [ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in turn\",\n \"range(len(utterances)): history = self.histories[i] history.append( (self.self_speaker_token if not other else self.other_speaker_token) + utterances[i]\",\n \"( self.train_step % self.episode_num_dialog_dump == 0 ) and self.train_step != 0: self.checkpoint([sample, utterances])\",\n \"observations): self.train_step += 1 # Add generated histories to data ones imitate =\",\n \"\\\"\\\"\\\"Implement sampling utterances and memorization here\\\"\\\"\\\" pass def batch_sample(self, dialogs) -> List[str]: \\\"\\\"\\\"Implement\",\n \"if len(dialog[1]) > 0 ] ) self.batch_imitate(imitate) utterances = self.batch_sample(sample) if ( self.train_step\",\n \"Agent from parlai.core.message import Message from random import sample import pathlib path =\",\n \"> 0 ] ) self.batch_imitate(imitate) utterances = self.batch_sample(sample) if ( self.train_step % self.episode_num_dialog_dump\",\n \"self.checkpoint([sample, utterances]) return [{\\\"id\\\": self.id} for _ in observations] def batch_imitate(self, dialogs): \\\"\\\"\\\"Implement\",\n \"+ utterances[i] ) self.histories[i] = history def _convert_history_to_other(self, history): history = [ turn.replace(self.self_speaker_token,\",\n \"0 ] ) self.batch_imitate(imitate) utterances = self.batch_sample(sample) if ( self.train_step % self.episode_num_dialog_dump ==\",\n \"sampling \\\"\\\"\\\" def __init__(self, opt: Dict[str, Any], shared: Dict[str, Any] = None): self.id\",\n \"= [] for i, observation in enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1]) for dialog\",\n \"enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1]) for dialog in observation[\\\"text\\\"] if len(dialog[1]) > 0\",\n \"batch_act(self, observations): self.train_step += 1 # Add generated histories to data ones imitate\",\n \") imitate.extend( [ dialog for dialog in observation[\\\"text\\\"] if len(dialog[1]) > 0 ]\",\n \"Message from random import sample import pathlib path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \\\"\\\"\\\"Abstract\",\n \"dialogs) -> List[str]: \\\"\\\"\\\"Implement update here\\\"\\\"\\\" pass def batch_update(self): \\\"\\\"\\\"Update weights here\\\"\\\"\\\" pass\",\n \"self.self_speaker_token in turn else turn.replace(self.other_speaker_token, self.self_speaker_token) for turn in history ] return history\",\n \"= \\\"<speaker_other>\\\" def act(self): raise NotImplementedError() def batch_act(self, observations): self.train_step += 1 #\",\n \"\\\"\\\"\\\"Update weights here\\\"\\\"\\\" pass def _update_histories(self, utterances, other=False): for i in range(len(utterances)): history\",\n \"Any, List import string from parlai.core.agents import Agent from parlai.core.message import Message from\",\n \"in enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1]) for dialog in observation[\\\"text\\\"] if len(dialog[1]) >\",\n \"\\\"\\\"\\\"Implement update here\\\"\\\"\\\" pass def batch_update(self): \\\"\\\"\\\"Update weights here\\\"\\\"\\\" pass def _update_histories(self, utterances,\",\n \"__init__(self, opt: Dict[str, Any], shared: Dict[str, Any] = None): self.id = \\\"LightChatbotSelfPlay\\\" self.train_step\",\n \"utterances[i] ) self.histories[i] = history def _convert_history_to_other(self, history): history = [ turn.replace(self.self_speaker_token, self.other_speaker_token)\",\n \"history = self.histories[i] history.append( (self.self_speaker_token if not other else self.other_speaker_token) + utterances[i] )\",\n \"dialogs): \\\"\\\"\\\"Implement sampling utterances and memorization here\\\"\\\"\\\" pass def batch_sample(self, dialogs) -> List[str]:\",\n \"\\\"<speaker_other>\\\" def act(self): raise NotImplementedError() def batch_act(self, observations): self.train_step += 1 # Add\",\n \") and self.train_step != 0: self.checkpoint([sample, utterances]) return [{\\\"id\\\": self.id} for _ in\",\n \"pass def batch_sample(self, dialogs) -> List[str]: \\\"\\\"\\\"Implement update here\\\"\\\"\\\" pass def batch_update(self): \\\"\\\"\\\"Update\",\n \"1 # Add generated histories to data ones imitate = [] sample =\",\n \"(dialog[0], dialog[1][:-1]) for dialog in observation[\\\"text\\\"] if len(dialog[1]) > 0 ] ) imitate.extend(\",\n \"parlai.core.message import Message from random import sample import pathlib path = pathlib.Path(__file__).parent.absolute() class\",\n \"# Add generated histories to data ones imitate = [] sample = []\",\n \"sample = [] for i, observation in enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1]) for\",\n \"== 0 ) and self.train_step != 0: self.checkpoint([sample, utterances]) return [{\\\"id\\\": self.id} for\",\n \"sample import pathlib path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \\\"\\\"\\\"Abstract class that handles passing\",\n \"here\\\"\\\"\\\" pass def batch_update(self): \\\"\\\"\\\"Update weights here\\\"\\\"\\\" pass def _update_histories(self, utterances, other=False): for\",\n \"= \\\"<speaker_self>\\\" self.other_speaker_token = \\\"<speaker_other>\\\" def act(self): raise NotImplementedError() def batch_act(self, observations): self.train_step\",\n \"imitate = [] sample = [] for i, observation in enumerate(observations): sample.extend( [\",\n \"history = [ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in turn else turn.replace(self.other_speaker_token, self.self_speaker_token) for\",\n \"0 ] ) imitate.extend( [ dialog for dialog in observation[\\\"text\\\"] if len(dialog[1]) >\",\n \"observation[\\\"text\\\"] if len(dialog[1]) > 0 ] ) imitate.extend( [ dialog for dialog in\",\n \"def __init__(self, opt: Dict[str, Any], shared: Dict[str, Any] = None): self.id = \\\"LightChatbotSelfPlay\\\"\",\n \"batch_imitate(self, dialogs): \\\"\\\"\\\"Implement sampling utterances and memorization here\\\"\\\"\\\" pass def batch_sample(self, dialogs) ->\",\n \"and memorization here\\\"\\\"\\\" pass def batch_sample(self, dialogs) -> List[str]: \\\"\\\"\\\"Implement update here\\\"\\\"\\\" pass\",\n \"pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \\\"\\\"\\\"Abstract class that handles passing expert trajectories alongside self-play sampling\",\n \"% self.episode_num_dialog_dump == 0 ) and self.train_step != 0: self.checkpoint([sample, utterances]) return [{\\\"id\\\":\",\n \"here\\\"\\\"\\\" pass def _update_histories(self, utterances, other=False): for i in range(len(utterances)): history = self.histories[i]\",\n \"data ones imitate = [] sample = [] for i, observation in enumerate(observations):\",\n \"> 0 ] ) imitate.extend( [ dialog for dialog in observation[\\\"text\\\"] if len(dialog[1])\",\n \"[ (dialog[0], dialog[1][:-1]) for dialog in observation[\\\"text\\\"] if len(dialog[1]) > 0 ] )\",\n \"shared: Dict[str, Any] = None): self.id = \\\"LightChatbotSelfPlay\\\" self.train_step = 0 self.self_speaker_token =\",\n \"ones imitate = [] sample = [] for i, observation in enumerate(observations): sample.extend(\",\n \"Any] = None): self.id = \\\"LightChatbotSelfPlay\\\" self.train_step = 0 self.self_speaker_token = \\\"<speaker_self>\\\" self.other_speaker_token\",\n \"self.self_speaker_token = \\\"<speaker_self>\\\" self.other_speaker_token = \\\"<speaker_other>\\\" def act(self): raise NotImplementedError() def batch_act(self, observations):\",\n \"= [] sample = [] for i, observation in enumerate(observations): sample.extend( [ (dialog[0],\",\n \"parlai.core.agents import Agent from parlai.core.message import Message from random import sample import pathlib\",\n \"to data ones imitate = [] sample = [] for i, observation in\",\n \"= \\\"LightChatbotSelfPlay\\\" self.train_step = 0 self.self_speaker_token = \\\"<speaker_self>\\\" self.other_speaker_token = \\\"<speaker_other>\\\" def act(self):\",\n \"\\\"<speaker_self>\\\" self.other_speaker_token = \\\"<speaker_other>\\\" def act(self): raise NotImplementedError() def batch_act(self, observations): self.train_step +=\",\n \"passing expert trajectories alongside self-play sampling \\\"\\\"\\\" def __init__(self, opt: Dict[str, Any], shared:\",\n \"i, observation in enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1]) for dialog in observation[\\\"text\\\"] if\",\n \"histories to data ones imitate = [] sample = [] for i, observation\",\n \"LightImitateMixin(Agent): \\\"\\\"\\\"Abstract class that handles passing expert trajectories alongside self-play sampling \\\"\\\"\\\" def\",\n \"observation in enumerate(observations): sample.extend( [ (dialog[0], dialog[1][:-1]) for dialog in observation[\\\"text\\\"] if len(dialog[1])\",\n \"expert trajectories alongside self-play sampling \\\"\\\"\\\" def __init__(self, opt: Dict[str, Any], shared: Dict[str,\",\n \"that handles passing expert trajectories alongside self-play sampling \\\"\\\"\\\" def __init__(self, opt: Dict[str,\",\n \"self.other_speaker_token = \\\"<speaker_other>\\\" def act(self): raise NotImplementedError() def batch_act(self, observations): self.train_step += 1\",\n \"dialog in observation[\\\"text\\\"] if len(dialog[1]) > 0 ] ) self.batch_imitate(imitate) utterances = self.batch_sample(sample)\",\n \"raise NotImplementedError() def batch_act(self, observations): self.train_step += 1 # Add generated histories to\",\n \"for _ in observations] def batch_imitate(self, dialogs): \\\"\\\"\\\"Implement sampling utterances and memorization here\\\"\\\"\\\"\",\n \"Add generated histories to data ones imitate = [] sample = [] for\",\n \"= self.histories[i] history.append( (self.self_speaker_token if not other else self.other_speaker_token) + utterances[i] ) self.histories[i]\",\n \"!= 0: self.checkpoint([sample, utterances]) return [{\\\"id\\\": self.id} for _ in observations] def batch_imitate(self,\",\n \"List[str]: \\\"\\\"\\\"Implement update here\\\"\\\"\\\" pass def batch_update(self): \\\"\\\"\\\"Update weights here\\\"\\\"\\\" pass def _update_histories(self,\",\n \"not other else self.other_speaker_token) + utterances[i] ) self.histories[i] = history def _convert_history_to_other(self, history):\",\n \"def batch_sample(self, dialogs) -> List[str]: \\\"\\\"\\\"Implement update here\\\"\\\"\\\" pass def batch_update(self): \\\"\\\"\\\"Update weights\",\n \"(self.self_speaker_token if not other else self.other_speaker_token) + utterances[i] ) self.histories[i] = history def\",\n \"_convert_history_to_other(self, history): history = [ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in turn else turn.replace(self.other_speaker_token,\",\n \"] ) self.batch_imitate(imitate) utterances = self.batch_sample(sample) if ( self.train_step % self.episode_num_dialog_dump == 0\",\n \"= self.batch_sample(sample) if ( self.train_step % self.episode_num_dialog_dump == 0 ) and self.train_step !=\",\n \"-> List[str]: \\\"\\\"\\\"Implement update here\\\"\\\"\\\" pass def batch_update(self): \\\"\\\"\\\"Update weights here\\\"\\\"\\\" pass def\",\n \"observation[\\\"text\\\"] if len(dialog[1]) > 0 ] ) self.batch_imitate(imitate) utterances = self.batch_sample(sample) if (\",\n \"def _update_histories(self, utterances, other=False): for i in range(len(utterances)): history = self.histories[i] history.append( (self.self_speaker_token\",\n \"0: self.checkpoint([sample, utterances]) return [{\\\"id\\\": self.id} for _ in observations] def batch_imitate(self, dialogs):\",\n \"self.id = \\\"LightChatbotSelfPlay\\\" self.train_step = 0 self.self_speaker_token = \\\"<speaker_self>\\\" self.other_speaker_token = \\\"<speaker_other>\\\" def\",\n \"in observation[\\\"text\\\"] if len(dialog[1]) > 0 ] ) imitate.extend( [ dialog for dialog\",\n \"self.train_step != 0: self.checkpoint([sample, utterances]) return [{\\\"id\\\": self.id} for _ in observations] def\",\n \"memorization here\\\"\\\"\\\" pass def batch_sample(self, dialogs) -> List[str]: \\\"\\\"\\\"Implement update here\\\"\\\"\\\" pass def\",\n \"self.other_speaker_token) + utterances[i] ) self.histories[i] = history def _convert_history_to_other(self, history): history = [\",\n \"from random import sample import pathlib path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \\\"\\\"\\\"Abstract class\",\n \"self.train_step % self.episode_num_dialog_dump == 0 ) and self.train_step != 0: self.checkpoint([sample, utterances]) return\",\n \"self.id} for _ in observations] def batch_imitate(self, dialogs): \\\"\\\"\\\"Implement sampling utterances and memorization\",\n \"in observations] def batch_imitate(self, dialogs): \\\"\\\"\\\"Implement sampling utterances and memorization here\\\"\\\"\\\" pass def\",\n \"self.other_speaker_token) if self.self_speaker_token in turn else turn.replace(self.other_speaker_token, self.self_speaker_token) for turn in history ]\",\n \"alongside self-play sampling \\\"\\\"\\\" def __init__(self, opt: Dict[str, Any], shared: Dict[str, Any] =\",\n \"self.histories[i] history.append( (self.self_speaker_token if not other else self.other_speaker_token) + utterances[i] ) self.histories[i] =\",\n \"batch_update(self): \\\"\\\"\\\"Update weights here\\\"\\\"\\\" pass def _update_histories(self, utterances, other=False): for i in range(len(utterances)):\",\n \"= history def _convert_history_to_other(self, history): history = [ turn.replace(self.self_speaker_token, self.other_speaker_token) if self.self_speaker_token in\",\n \"] ) imitate.extend( [ dialog for dialog in observation[\\\"text\\\"] if len(dialog[1]) > 0\",\n \"sample.extend( [ (dialog[0], dialog[1][:-1]) for dialog in observation[\\\"text\\\"] if len(dialog[1]) > 0 ]\",\n \"_ in observations] def batch_imitate(self, dialogs): \\\"\\\"\\\"Implement sampling utterances and memorization here\\\"\\\"\\\" pass\",\n \"if len(dialog[1]) > 0 ] ) imitate.extend( [ dialog for dialog in observation[\\\"text\\\"]\",\n \"= None): self.id = \\\"LightChatbotSelfPlay\\\" self.train_step = 0 self.self_speaker_token = \\\"<speaker_self>\\\" self.other_speaker_token =\",\n \"pass def batch_update(self): \\\"\\\"\\\"Update weights here\\\"\\\"\\\" pass def _update_histories(self, utterances, other=False): for i\",\n \"self.train_step += 1 # Add generated histories to data ones imitate = []\",\n \"dialog[1][:-1]) for dialog in observation[\\\"text\\\"] if len(dialog[1]) > 0 ] ) imitate.extend( [\",\n \"self.episode_num_dialog_dump == 0 ) and self.train_step != 0: self.checkpoint([sample, utterances]) return [{\\\"id\\\": self.id}\",\n \"utterances]) return [{\\\"id\\\": self.id} for _ in observations] def batch_imitate(self, dialogs): \\\"\\\"\\\"Implement sampling\",\n \"utterances = self.batch_sample(sample) if ( self.train_step % self.episode_num_dialog_dump == 0 ) and self.train_step\",\n \"= pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \\\"\\\"\\\"Abstract class that handles passing expert trajectories alongside self-play\",\n \"batch_sample(self, dialogs) -> List[str]: \\\"\\\"\\\"Implement update here\\\"\\\"\\\" pass def batch_update(self): \\\"\\\"\\\"Update weights here\\\"\\\"\\\"\",\n \"i in range(len(utterances)): history = self.histories[i] history.append( (self.self_speaker_token if not other else self.other_speaker_token)\",\n \"other else self.other_speaker_token) + utterances[i] ) self.histories[i] = history def _convert_history_to_other(self, history): history\",\n \"if self.self_speaker_token in turn else turn.replace(self.other_speaker_token, self.self_speaker_token) for turn in history ] return\",\n \"path = pathlib.Path(__file__).parent.absolute() class LightImitateMixin(Agent): \\\"\\\"\\\"Abstract class that handles passing expert trajectories alongside\",\n \"act(self): raise NotImplementedError() def batch_act(self, observations): self.train_step += 1 # Add generated histories\",\n \"NotImplementedError() def batch_act(self, observations): self.train_step += 1 # Add generated histories to data\"\n]","isConversational":false}}},{"rowIdx":4592,"cells":{"ngram":{"kind":"list like","value":["( ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType) -> bool: \"\"\" Args: head:","from pytudes._2021.utils.linked_list import ( ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType) -> bool:",">>> head.next = head >>> has_cycle(head) True >>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head)","and fast.next is not None: # since fast ≥ slow slow = slow.next","fast.next is not None: # since fast ≥ slow slow = slow.next fast","= slow.next fast = fast.next.next if slow == fast: return True # found","fast = fast.next.next if slow == fast: return True # found the cycle","print(\"LinkedList has cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\"LinkedList has cycle: \"","Returns: whether or not the linked list has a cycle Examples: >>> has_cycle(None)","False >>> head.next.next.next.next.next.next = head.next.next >>> has_cycle(head) True >>> head.next.next.next.next.next.next = head.next.next.next >>>","= head.next.next print(\"LinkedList has cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next.next print(\"LinkedList has","False >>> head = ListNode(\"self-edge\") >>> head.next = head >>> has_cycle(head) True >>>","= convert_list_to_linked_list([1, 2, 3, 4, 5, 6]) print(\"LinkedList has cycle: \" + str(has_cycle(head)))","is not None: # since fast ≥ slow slow = slow.next fast =","= convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>> head.next.next.next.next.next.next = head.next.next >>> has_cycle(head) True >>>","slow.next fast = fast.next.next if slow == fast: return True # found the","linked list has a cycle Examples: >>> has_cycle(None) False >>> head = ListNode(\"self-edge\")","head.next.next >>> has_cycle(head) True >>> head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head) True \"\"\" slow","is not None and fast.next is not None: # since fast ≥ slow","since fast ≥ slow slow = slow.next fast = fast.next.next if slow ==","a cycle Examples: >>> has_cycle(None) False >>> head = ListNode(\"self-edge\") >>> head.next =","print(\"LinkedList has cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next.next print(\"LinkedList has cycle: \"","3, 4, 5, 6]) print(\"LinkedList has cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next",">>> has_cycle(head) True \"\"\" slow = fast = head while fast is not","has cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next.next print(\"LinkedList has cycle: \" +","True >>> head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head) True \"\"\" slow = fast =","not None and fast.next is not None: # since fast ≥ slow slow","a singly-linked list of nodes Returns: whether or not the linked list has","None: # since fast ≥ slow slow = slow.next fast = fast.next.next if","Bit Manipulation - Blind 75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \"\"\" from pytudes._2021.utils.linked_list import","True >>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>> head.next.next.next.next.next.next = head.next.next >>>","head: head of a singly-linked list of nodes Returns: whether or not the","NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType) -> bool: \"\"\" Args: head: head of","Blind 75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \"\"\" from pytudes._2021.utils.linked_list import ( ListNode, NodeType,",">>> head = ListNode(\"self-edge\") >>> head.next = head >>> has_cycle(head) True >>> head","True \"\"\" slow = fast = head while fast is not None and","or not the linked list has a cycle Examples: >>> has_cycle(None) False >>>","convert_list_to_linked_list, ) def has_cycle(head: NodeType) -> bool: \"\"\" Args: head: head of a","= head.next.next >>> has_cycle(head) True >>> head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head) True \"\"\"","\"\"\"https://www.educative.io/courses/grokking-the-coding-interview/N7rwVyAZl6D Categories: - Binary - Bit Manipulation - Blind 75 See Also: -","list of nodes Returns: whether or not the linked list has a cycle","pytudes._2021.utils.linked_list import ( ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType) -> bool: \"\"\"","has_cycle(head) False >>> head.next.next.next.next.next.next = head.next.next >>> has_cycle(head) True >>> head.next.next.next.next.next.next = head.next.next.next","if slow == fast: return True # found the cycle else: return False","of a singly-linked list of nodes Returns: whether or not the linked list","has a cycle Examples: >>> has_cycle(None) False >>> head = ListNode(\"self-edge\") >>> head.next","of nodes Returns: whether or not the linked list has a cycle Examples:","True # found the cycle else: return False def main(): head = convert_list_to_linked_list([1,","= head.next.next.next >>> has_cycle(head) True \"\"\" slow = fast = head while fast","str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\"LinkedList has cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next.next","False def main(): head = convert_list_to_linked_list([1, 2, 3, 4, 5, 6]) print(\"LinkedList has","def has_cycle(head: NodeType) -> bool: \"\"\" Args: head: head of a singly-linked list","fast = head while fast is not None and fast.next is not None:","head = convert_list_to_linked_list([1, 2, 3, 4, 5, 6]) print(\"LinkedList has cycle: \" +",">>> has_cycle(head) False >>> head.next.next.next.next.next.next = head.next.next >>> has_cycle(head) True >>> head.next.next.next.next.next.next =","ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType) -> bool: \"\"\" Args: head: head","has_cycle(head) True \"\"\" slow = fast = head while fast is not None","\"\"\" slow = fast = head while fast is not None and fast.next","\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next.next print(\"LinkedList has cycle: \" + str(has_cycle(head))) main()","convert_list_to_linked_list([1, 2, 3, 4, 5, 6]) print(\"LinkedList has cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next","head.next.next.next >>> has_cycle(head) True \"\"\" slow = fast = head while fast is","has_cycle(None) False >>> head = ListNode(\"self-edge\") >>> head.next = head >>> has_cycle(head) True","bool: \"\"\" Args: head: head of a singly-linked list of nodes Returns: whether","cycle else: return False def main(): head = convert_list_to_linked_list([1, 2, 3, 4, 5,","\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\"LinkedList has cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next","the cycle else: return False def main(): head = convert_list_to_linked_list([1, 2, 3, 4,","return False def main(): head = convert_list_to_linked_list([1, 2, 3, 4, 5, 6]) print(\"LinkedList","Args: head: head of a singly-linked list of nodes Returns: whether or not","ListNode(\"self-edge\") >>> head.next = head >>> has_cycle(head) True >>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>>","- pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \"\"\" from pytudes._2021.utils.linked_list import ( ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head:",">>> head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head) True \"\"\" slow = fast = head","def main(): head = convert_list_to_linked_list([1, 2, 3, 4, 5, 6]) print(\"LinkedList has cycle:","not the linked list has a cycle Examples: >>> has_cycle(None) False >>> head",">>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>> head.next.next.next.next.next.next = head.next.next >>> has_cycle(head)","while fast is not None and fast.next is not None: # since fast","head while fast is not None and fast.next is not None: # since","import ( ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType) -> bool: \"\"\" Args:","head >>> has_cycle(head) True >>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>> head.next.next.next.next.next.next","nodes Returns: whether or not the linked list has a cycle Examples: >>>","has_cycle(head: NodeType) -> bool: \"\"\" Args: head: head of a singly-linked list of","slow = slow.next fast = fast.next.next if slow == fast: return True #","# since fast ≥ slow slow = slow.next fast = fast.next.next if slow","= head >>> has_cycle(head) True >>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>>","4, 5, 6]) print(\"LinkedList has cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\"LinkedList","5, 6]) print(\"LinkedList has cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\"LinkedList has","None and fast.next is not None: # since fast ≥ slow slow =","75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \"\"\" from pytudes._2021.utils.linked_list import ( ListNode, NodeType, convert_list_to_linked_list,","\"\"\" Args: head: head of a singly-linked list of nodes Returns: whether or","== fast: return True # found the cycle else: return False def main():","singly-linked list of nodes Returns: whether or not the linked list has a","fast ≥ slow slow = slow.next fast = fast.next.next if slow == fast:","cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next.next print(\"LinkedList has cycle: \" + str(has_cycle(head)))",">>> has_cycle(None) False >>> head = ListNode(\"self-edge\") >>> head.next = head >>> has_cycle(head)","head.next.next.next.next.next.next = head.next.next >>> has_cycle(head) True >>> head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head) True","whether or not the linked list has a cycle Examples: >>> has_cycle(None) False",">>> has_cycle(head) True >>> head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head) True \"\"\" slow =","main(): head = convert_list_to_linked_list([1, 2, 3, 4, 5, 6]) print(\"LinkedList has cycle: \"","2, 3, 4, 5, 6]) print(\"LinkedList has cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next =","head of a singly-linked list of nodes Returns: whether or not the linked","Binary - Bit Manipulation - Blind 75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \"\"\" from","cycle Examples: >>> has_cycle(None) False >>> head = ListNode(\"self-edge\") >>> head.next = head","list has a cycle Examples: >>> has_cycle(None) False >>> head = ListNode(\"self-edge\") >>>","else: return False def main(): head = convert_list_to_linked_list([1, 2, 3, 4, 5, 6])","= ListNode(\"self-edge\") >>> head.next = head >>> has_cycle(head) True >>> head = convert_list_to_linked_list([1,2,3,4,5,6])","= fast.next.next if slow == fast: return True # found the cycle else:","head = ListNode(\"self-edge\") >>> head.next = head >>> has_cycle(head) True >>> head =","\"\"\" from pytudes._2021.utils.linked_list import ( ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType) ->","slow = fast = head while fast is not None and fast.next is","has_cycle(head) True >>> head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head) True \"\"\" slow = fast",">>> has_cycle(head) True >>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>> head.next.next.next.next.next.next =","= fast = head while fast is not None and fast.next is not","head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>> head.next.next.next.next.next.next = head.next.next >>> has_cycle(head) True","- Binary - Bit Manipulation - Blind 75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \"\"\"","Categories: - Binary - Bit Manipulation - Blind 75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py","head.next = head >>> has_cycle(head) True >>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False","found the cycle else: return False def main(): head = convert_list_to_linked_list([1, 2, 3,","Manipulation - Blind 75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \"\"\" from pytudes._2021.utils.linked_list import (","convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>> head.next.next.next.next.next.next = head.next.next >>> has_cycle(head) True >>> head.next.next.next.next.next.next","6]) print(\"LinkedList has cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\"LinkedList has cycle:","fast: return True # found the cycle else: return False def main(): head","<reponame>TeoZosa/pytudes \"\"\"https://www.educative.io/courses/grokking-the-coding-interview/N7rwVyAZl6D Categories: - Binary - Bit Manipulation - Blind 75 See Also:","slow slow = slow.next fast = fast.next.next if slow == fast: return True",") def has_cycle(head: NodeType) -> bool: \"\"\" Args: head: head of a singly-linked","Examples: >>> has_cycle(None) False >>> head = ListNode(\"self-edge\") >>> head.next = head >>>","head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head) True \"\"\" slow = fast = head while","See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \"\"\" from pytudes._2021.utils.linked_list import ( ListNode, NodeType, convert_list_to_linked_list, )","slow == fast: return True # found the cycle else: return False def","the linked list has a cycle Examples: >>> has_cycle(None) False >>> head =","fast is not None and fast.next is not None: # since fast ≥","return True # found the cycle else: return False def main(): head =","has cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\"LinkedList has cycle: \" +","= head while fast is not None and fast.next is not None: #","+ str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\"LinkedList has cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next =","head.next.next.next.next.next.next = head.next.next print(\"LinkedList has cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next.next print(\"LinkedList","not None: # since fast ≥ slow slow = slow.next fast = fast.next.next",">>> head.next.next.next.next.next.next = head.next.next >>> has_cycle(head) True >>> head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head)","pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \"\"\" from pytudes._2021.utils.linked_list import ( ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType)","has_cycle(head) True >>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>> head.next.next.next.next.next.next = head.next.next","fast.next.next if slow == fast: return True # found the cycle else: return","head.next.next print(\"LinkedList has cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next.next print(\"LinkedList has cycle:","≥ slow slow = slow.next fast = fast.next.next if slow == fast: return","NodeType) -> bool: \"\"\" Args: head: head of a singly-linked list of nodes","cycle: \" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\"LinkedList has cycle: \" + str(has_cycle(head)))","-> bool: \"\"\" Args: head: head of a singly-linked list of nodes Returns:","- Bit Manipulation - Blind 75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \"\"\" from pytudes._2021.utils.linked_list","- Blind 75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \"\"\" from pytudes._2021.utils.linked_list import ( ListNode,","Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \"\"\" from pytudes._2021.utils.linked_list import ( ListNode, NodeType, convert_list_to_linked_list, ) def","# found the cycle else: return False def main(): head = convert_list_to_linked_list([1, 2,"],"string":"[\n \"( ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType) -> bool: \\\"\\\"\\\" Args: head:\",\n \"from pytudes._2021.utils.linked_list import ( ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType) -> bool:\",\n \">>> head.next = head >>> has_cycle(head) True >>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head)\",\n \"and fast.next is not None: # since fast ≥ slow slow = slow.next\",\n \"fast.next is not None: # since fast ≥ slow slow = slow.next fast\",\n \"= slow.next fast = fast.next.next if slow == fast: return True # found\",\n \"fast = fast.next.next if slow == fast: return True # found the cycle\",\n \"print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\\\"LinkedList has cycle: \\\"\",\n \"Returns: whether or not the linked list has a cycle Examples: >>> has_cycle(None)\",\n \"False >>> head.next.next.next.next.next.next = head.next.next >>> has_cycle(head) True >>> head.next.next.next.next.next.next = head.next.next.next >>>\",\n \"= head.next.next print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next.next print(\\\"LinkedList has\",\n \"False >>> head = ListNode(\\\"self-edge\\\") >>> head.next = head >>> has_cycle(head) True >>>\",\n \"= convert_list_to_linked_list([1, 2, 3, 4, 5, 6]) print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head)))\",\n \"is not None: # since fast ≥ slow slow = slow.next fast =\",\n \"= convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>> head.next.next.next.next.next.next = head.next.next >>> has_cycle(head) True >>>\",\n \"slow.next fast = fast.next.next if slow == fast: return True # found the\",\n \"linked list has a cycle Examples: >>> has_cycle(None) False >>> head = ListNode(\\\"self-edge\\\")\",\n \"head.next.next >>> has_cycle(head) True >>> head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head) True \\\"\\\"\\\" slow\",\n \"is not None and fast.next is not None: # since fast ≥ slow\",\n \"since fast ≥ slow slow = slow.next fast = fast.next.next if slow ==\",\n \"a cycle Examples: >>> has_cycle(None) False >>> head = ListNode(\\\"self-edge\\\") >>> head.next =\",\n \"print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next.next print(\\\"LinkedList has cycle: \\\"\",\n \"3, 4, 5, 6]) print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next\",\n \">>> has_cycle(head) True \\\"\\\"\\\" slow = fast = head while fast is not\",\n \"has cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next.next print(\\\"LinkedList has cycle: \\\" +\",\n \"True >>> head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head) True \\\"\\\"\\\" slow = fast =\",\n \"not None and fast.next is not None: # since fast ≥ slow slow\",\n \"a singly-linked list of nodes Returns: whether or not the linked list has\",\n \"None: # since fast ≥ slow slow = slow.next fast = fast.next.next if\",\n \"Bit Manipulation - Blind 75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \\\"\\\"\\\" from pytudes._2021.utils.linked_list import\",\n \"True >>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>> head.next.next.next.next.next.next = head.next.next >>>\",\n \"head: head of a singly-linked list of nodes Returns: whether or not the\",\n \"NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType) -> bool: \\\"\\\"\\\" Args: head: head of\",\n \"Blind 75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \\\"\\\"\\\" from pytudes._2021.utils.linked_list import ( ListNode, NodeType,\",\n \">>> head = ListNode(\\\"self-edge\\\") >>> head.next = head >>> has_cycle(head) True >>> head\",\n \"True \\\"\\\"\\\" slow = fast = head while fast is not None and\",\n \"or not the linked list has a cycle Examples: >>> has_cycle(None) False >>>\",\n \"convert_list_to_linked_list, ) def has_cycle(head: NodeType) -> bool: \\\"\\\"\\\" Args: head: head of a\",\n \"= head.next.next >>> has_cycle(head) True >>> head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head) True \\\"\\\"\\\"\",\n \"\\\"\\\"\\\"https://www.educative.io/courses/grokking-the-coding-interview/N7rwVyAZl6D Categories: - Binary - Bit Manipulation - Blind 75 See Also: -\",\n \"list of nodes Returns: whether or not the linked list has a cycle\",\n \"pytudes._2021.utils.linked_list import ( ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType) -> bool: \\\"\\\"\\\"\",\n \"has_cycle(head) False >>> head.next.next.next.next.next.next = head.next.next >>> has_cycle(head) True >>> head.next.next.next.next.next.next = head.next.next.next\",\n \"if slow == fast: return True # found the cycle else: return False\",\n \"of a singly-linked list of nodes Returns: whether or not the linked list\",\n \"has a cycle Examples: >>> has_cycle(None) False >>> head = ListNode(\\\"self-edge\\\") >>> head.next\",\n \"of nodes Returns: whether or not the linked list has a cycle Examples:\",\n \"True # found the cycle else: return False def main(): head = convert_list_to_linked_list([1,\",\n \"= head.next.next.next >>> has_cycle(head) True \\\"\\\"\\\" slow = fast = head while fast\",\n \"str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next.next\",\n \"False def main(): head = convert_list_to_linked_list([1, 2, 3, 4, 5, 6]) print(\\\"LinkedList has\",\n \"def has_cycle(head: NodeType) -> bool: \\\"\\\"\\\" Args: head: head of a singly-linked list\",\n \"fast = head while fast is not None and fast.next is not None:\",\n \"head = convert_list_to_linked_list([1, 2, 3, 4, 5, 6]) print(\\\"LinkedList has cycle: \\\" +\",\n \">>> has_cycle(head) False >>> head.next.next.next.next.next.next = head.next.next >>> has_cycle(head) True >>> head.next.next.next.next.next.next =\",\n \"ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType) -> bool: \\\"\\\"\\\" Args: head: head\",\n \"has_cycle(head) True \\\"\\\"\\\" slow = fast = head while fast is not None\",\n \"\\\"\\\"\\\" slow = fast = head while fast is not None and fast.next\",\n \"\\\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next.next print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head))) main()\",\n \"convert_list_to_linked_list([1, 2, 3, 4, 5, 6]) print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next\",\n \"head.next.next.next >>> has_cycle(head) True \\\"\\\"\\\" slow = fast = head while fast is\",\n \"has_cycle(None) False >>> head = ListNode(\\\"self-edge\\\") >>> head.next = head >>> has_cycle(head) True\",\n \"bool: \\\"\\\"\\\" Args: head: head of a singly-linked list of nodes Returns: whether\",\n \"cycle else: return False def main(): head = convert_list_to_linked_list([1, 2, 3, 4, 5,\",\n \"\\\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next\",\n \"the cycle else: return False def main(): head = convert_list_to_linked_list([1, 2, 3, 4,\",\n \"return False def main(): head = convert_list_to_linked_list([1, 2, 3, 4, 5, 6]) print(\\\"LinkedList\",\n \"Args: head: head of a singly-linked list of nodes Returns: whether or not\",\n \"ListNode(\\\"self-edge\\\") >>> head.next = head >>> has_cycle(head) True >>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>>\",\n \"- pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \\\"\\\"\\\" from pytudes._2021.utils.linked_list import ( ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head:\",\n \">>> head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head) True \\\"\\\"\\\" slow = fast = head\",\n \"def main(): head = convert_list_to_linked_list([1, 2, 3, 4, 5, 6]) print(\\\"LinkedList has cycle:\",\n \"not the linked list has a cycle Examples: >>> has_cycle(None) False >>> head\",\n \">>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>> head.next.next.next.next.next.next = head.next.next >>> has_cycle(head)\",\n \"while fast is not None and fast.next is not None: # since fast\",\n \"head while fast is not None and fast.next is not None: # since\",\n \"import ( ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType) -> bool: \\\"\\\"\\\" Args:\",\n \"head >>> has_cycle(head) True >>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>> head.next.next.next.next.next.next\",\n \"nodes Returns: whether or not the linked list has a cycle Examples: >>>\",\n \"has_cycle(head: NodeType) -> bool: \\\"\\\"\\\" Args: head: head of a singly-linked list of\",\n \"slow = slow.next fast = fast.next.next if slow == fast: return True #\",\n \"# since fast ≥ slow slow = slow.next fast = fast.next.next if slow\",\n \"= head >>> has_cycle(head) True >>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>>\",\n \"4, 5, 6]) print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\\\"LinkedList\",\n \"5, 6]) print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\\\"LinkedList has\",\n \"None and fast.next is not None: # since fast ≥ slow slow =\",\n \"75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \\\"\\\"\\\" from pytudes._2021.utils.linked_list import ( ListNode, NodeType, convert_list_to_linked_list,\",\n \"\\\"\\\"\\\" Args: head: head of a singly-linked list of nodes Returns: whether or\",\n \"== fast: return True # found the cycle else: return False def main():\",\n \"singly-linked list of nodes Returns: whether or not the linked list has a\",\n \"fast ≥ slow slow = slow.next fast = fast.next.next if slow == fast:\",\n \"cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next.next print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head)))\",\n \">>> has_cycle(None) False >>> head = ListNode(\\\"self-edge\\\") >>> head.next = head >>> has_cycle(head)\",\n \"head.next.next.next.next.next.next = head.next.next >>> has_cycle(head) True >>> head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head) True\",\n \"whether or not the linked list has a cycle Examples: >>> has_cycle(None) False\",\n \">>> has_cycle(head) True >>> head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head) True \\\"\\\"\\\" slow =\",\n \"main(): head = convert_list_to_linked_list([1, 2, 3, 4, 5, 6]) print(\\\"LinkedList has cycle: \\\"\",\n \"2, 3, 4, 5, 6]) print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next =\",\n \"head of a singly-linked list of nodes Returns: whether or not the linked\",\n \"Binary - Bit Manipulation - Blind 75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \\\"\\\"\\\" from\",\n \"cycle Examples: >>> has_cycle(None) False >>> head = ListNode(\\\"self-edge\\\") >>> head.next = head\",\n \"list has a cycle Examples: >>> has_cycle(None) False >>> head = ListNode(\\\"self-edge\\\") >>>\",\n \"else: return False def main(): head = convert_list_to_linked_list([1, 2, 3, 4, 5, 6])\",\n \"= ListNode(\\\"self-edge\\\") >>> head.next = head >>> has_cycle(head) True >>> head = convert_list_to_linked_list([1,2,3,4,5,6])\",\n \"= fast.next.next if slow == fast: return True # found the cycle else:\",\n \"head = ListNode(\\\"self-edge\\\") >>> head.next = head >>> has_cycle(head) True >>> head =\",\n \"\\\"\\\"\\\" from pytudes._2021.utils.linked_list import ( ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType) ->\",\n \"slow = fast = head while fast is not None and fast.next is\",\n \"has_cycle(head) True >>> head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head) True \\\"\\\"\\\" slow = fast\",\n \">>> has_cycle(head) True >>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>> head.next.next.next.next.next.next =\",\n \"= fast = head while fast is not None and fast.next is not\",\n \"head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>> head.next.next.next.next.next.next = head.next.next >>> has_cycle(head) True\",\n \"- Binary - Bit Manipulation - Blind 75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \\\"\\\"\\\"\",\n \"Categories: - Binary - Bit Manipulation - Blind 75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py\",\n \"head.next = head >>> has_cycle(head) True >>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False\",\n \"found the cycle else: return False def main(): head = convert_list_to_linked_list([1, 2, 3,\",\n \"Manipulation - Blind 75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \\\"\\\"\\\" from pytudes._2021.utils.linked_list import (\",\n \"convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>> head.next.next.next.next.next.next = head.next.next >>> has_cycle(head) True >>> head.next.next.next.next.next.next\",\n \"6]) print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\\\"LinkedList has cycle:\",\n \"fast: return True # found the cycle else: return False def main(): head\",\n \"<reponame>TeoZosa/pytudes \\\"\\\"\\\"https://www.educative.io/courses/grokking-the-coding-interview/N7rwVyAZl6D Categories: - Binary - Bit Manipulation - Blind 75 See Also:\",\n \"slow slow = slow.next fast = fast.next.next if slow == fast: return True\",\n \") def has_cycle(head: NodeType) -> bool: \\\"\\\"\\\" Args: head: head of a singly-linked\",\n \"Examples: >>> has_cycle(None) False >>> head = ListNode(\\\"self-edge\\\") >>> head.next = head >>>\",\n \"head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head) True \\\"\\\"\\\" slow = fast = head while\",\n \"See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \\\"\\\"\\\" from pytudes._2021.utils.linked_list import ( ListNode, NodeType, convert_list_to_linked_list, )\",\n \"slow == fast: return True # found the cycle else: return False def\",\n \"the linked list has a cycle Examples: >>> has_cycle(None) False >>> head =\",\n \"fast is not None and fast.next is not None: # since fast ≥\",\n \"return True # found the cycle else: return False def main(): head =\",\n \"has cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\\\"LinkedList has cycle: \\\" +\",\n \"= head while fast is not None and fast.next is not None: #\",\n \"+ str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next =\",\n \"head.next.next.next.next.next.next = head.next.next print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next.next print(\\\"LinkedList\",\n \"not None: # since fast ≥ slow slow = slow.next fast = fast.next.next\",\n \">>> head.next.next.next.next.next.next = head.next.next >>> has_cycle(head) True >>> head.next.next.next.next.next.next = head.next.next.next >>> has_cycle(head)\",\n \"pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \\\"\\\"\\\" from pytudes._2021.utils.linked_list import ( ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType)\",\n \"has_cycle(head) True >>> head = convert_list_to_linked_list([1,2,3,4,5,6]) >>> has_cycle(head) False >>> head.next.next.next.next.next.next = head.next.next\",\n \"fast.next.next if slow == fast: return True # found the cycle else: return\",\n \"head.next.next print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next.next print(\\\"LinkedList has cycle:\",\n \"≥ slow slow = slow.next fast = fast.next.next if slow == fast: return\",\n \"NodeType) -> bool: \\\"\\\"\\\" Args: head: head of a singly-linked list of nodes\",\n \"cycle: \\\" + str(has_cycle(head))) head.next.next.next.next.next.next = head.next.next print(\\\"LinkedList has cycle: \\\" + str(has_cycle(head)))\",\n \"-> bool: \\\"\\\"\\\" Args: head: head of a singly-linked list of nodes Returns:\",\n \"- Bit Manipulation - Blind 75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \\\"\\\"\\\" from pytudes._2021.utils.linked_list\",\n \"- Blind 75 See Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \\\"\\\"\\\" from pytudes._2021.utils.linked_list import ( ListNode,\",\n \"Also: - pytudes/_2021/leetcode/blind_75/linked_list/_141__linked_list_cycle__easy.py \\\"\\\"\\\" from pytudes._2021.utils.linked_list import ( ListNode, NodeType, convert_list_to_linked_list, ) def\",\n \"# found the cycle else: return False def main(): head = convert_list_to_linked_list([1, 2,\"\n]","isConversational":false}}},{"rowIdx":4593,"cells":{"ngram":{"kind":"list like","value":["# conn.sendall(msg) break if __name__ == '__main__': input_port = int(sys.argv[1]) input_doc_root = sys.argv[2]","200 req else: res = self.res_200 res += \"Last-Modified: {}\\r\\n\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \"rb\")","# mapping url, return 404 escape or absolute filename # judge whether escape","with open(path, \"rb\") as f: data = f.read() res += \"Content-Length: {}\\r\\n\".format(len(data)) if","s.accept() t = threading.Thread(target=createsocket(conn, addr), args=(conn, addr)) t.start() threads.append(t) for t in threads:","os.path.realpath(self.doc_root + path) return info # generate response def res_gen(self, reqinfo): path =","res_gen(self, reqinfo): path = reqinfo['url'] # 404 escape if path == '404escape': return","'404escape' return info if i < len(x) and x[i] == '..': x.remove(x[i]) x.remove(x[i","FOUND\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_400 = \"HTTP/1.1 400 Client Error\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_close =","threading class MyServer: def __init__(self, port, doc_root): self.port = port self.doc_root = doc_root","= doc_root self.host = '127.0.0.1' self.res_200 = \"HTTP/1.1 200 OK\\r\\nServer: Myserver 1.0\\r\\n\" self.res_404","# print('Connected by', addr) while True: req = conn.recv(1024).decode() if not req: break","400 Client Error\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_close = \"HTTP/1.1 Connection:close\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" # map","reqinfo['url'] # 404 escape if path == '404escape': return self.res_404 # 400 malform","h.split(': ') if len(h) < 2: continue field = h[0] value = h[1]","\"HTTP/1.1 404 NOT FOUND\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_400 = \"HTTP/1.1 400 Client Error\\r\\nServer: Myserver","send finished\") # msg = server.res_close.encode() # conn.sendall(msg) break if __name__ == '__main__':","return self.res_404 # a valid 200 req else: res = self.res_200 res +=","malform if request[-4:] != '\\r\\n\\r\\n': info = {'url': '400malform'} return info headers =","print(\"msg send finished\") # msg = server.res_close.encode() # conn.sendall(msg) break if __name__ ==","1.0\\r\\n\\r\\n\" # map request into dict def req_info(self, request): # 400 malform if","= port self.doc_root = doc_root self.host = '127.0.0.1' self.res_200 = \"HTTP/1.1 200 OK\\r\\nServer:","value # mapping url, return 404 escape or absolute filename # judge whether","+= 'Content-Type: image/png\\r\\n\\r\\n' else: res += 'Content-Type: image/jpeg\\r\\n\\r\\n' res = res + str(data)","import sys import os import socket import time import threading class MyServer: def","Myserver 1.0\\r\\n\\r\\n\" # map request into dict def req_info(self, request): # 400 malform","< 2: continue field = h[0] value = h[1] info[field] = value #","x[0] == '..' or len(x) == 0: # path escape from file root","2: continue field = h[0] value = h[1] info[field] = value # mapping","info = {'url': '400malform'} return info headers = request.splitlines() firstline = headers.pop(0) try:","'127.0.0.1' self.res_200 = \"HTTP/1.1 200 OK\\r\\nServer: Myserver 1.0\\r\\n\" self.res_404 = \"HTTP/1.1 404 NOT","open(path, \"rb\") as f: data = f.read() res += \"Content-Length: {}\\r\\n\".format(len(data)) if path.split('.')[-1]","= MyServer(input_port, input_doc_root) # Add code to start your server here threads =","return info # generate response def res_gen(self, reqinfo): path = reqinfo['url'] # 404","\"Last-Modified: {}\\r\\n\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \"rb\") as f: data = f.read() res += \"Content-Length:","valid 200 req else: res = self.res_200 res += \"Last-Modified: {}\\r\\n\".format(time.ctime(os.stat(path).st_mtime)) with open(path,","self.res_400 = \"HTTP/1.1 400 Client Error\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_close = \"HTTP/1.1 Connection:close\\r\\nServer: Myserver","- 1]) i -= 1 else: i += 1 # map index.html if","str(data) return res def createsocket(conn, addr): with conn: try: conn.settimeout(5) except socket.timeout: conn.close()","2: x.append('index.html') for d in range(len(x)): path = path + '/' + x[d]","input_doc_root) # Add code to start your server here threads = [] with","or len(x) == 0: # path escape from file root info['url'] = '404escape'","malform req if path == \"400malform\": return self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent'] except","x.remove(x[i]) x.remove(x[i - 1]) i -= 1 else: i += 1 # map","+ str(data, 'utf-8') else: # for jpg and png if path.split('.')[-1] == 'png':","0: # path escape from file root info['url'] = '404escape' return info if","self.res_404 = \"HTTP/1.1 404 NOT FOUND\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_400 = \"HTTP/1.1 400 Client","# Add code to start your server here threads = [] with socket.socket(socket.AF_INET,","t = threading.Thread(target=createsocket(conn, addr), args=(conn, addr)) t.start() threads.append(t) for t in threads: t.join()","res def createsocket(conn, addr): with conn: try: conn.settimeout(5) except socket.timeout: conn.close() # print('closed')","+ path) return info # generate response def res_gen(self, reqinfo): path = reqinfo['url']","with conn: try: conn.settimeout(5) except socket.timeout: conn.close() # print('closed') # print('Connected by', addr)","Myserver 1.0\\r\\n\\r\\n\" self.res_400 = \"HTTP/1.1 400 Client Error\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_close = \"HTTP/1.1","file root info['url'] = '404escape' return info if i < len(x) and x[i]","= conn.recv(1024).decode() if not req: break info = server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg)","if path == \"400malform\": return self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent'] except KeyError: return","x = url.split('/') i = 0 while i < len(x): if '' in","socket import time import threading class MyServer: def __init__(self, port, doc_root): self.port =","version} for h in headers: h = h.split(': ') if len(h) < 2:","== \"400malform\": return self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent'] except KeyError: return self.res_400 #","import os import socket import time import threading class MyServer: def __init__(self, port,","else: i += 1 # map index.html if len(x[-1].split('.')) < 2: x.append('index.html') for","return self.res_404 # 400 malform req if path == \"400malform\": return self.res_400 try:","i = 0 while i < len(x): if '' in x: x.remove('') if","= 0 while i < len(x): if '' in x: x.remove('') if i","= request.splitlines() firstline = headers.pop(0) try: (act, url, version) = firstline.split() except ValueError:","res += \"Last-Modified: {}\\r\\n\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \"rb\") as f: data = f.read() res","if path.split('.')[-1] == 'html': res += 'Content-Type: text/html\\r\\n\\r\\n' res = res + str(data,","by', addr) while True: req = conn.recv(1024).decode() if not req: break info =","in x: x.remove('') if i < 0 or x[0] == '..' or len(x)","= server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg) # print(\"msg send finished\") # msg =","x: x.remove('') if i < 0 or x[0] == '..' or len(x) ==","+ x[d] info['url'] = os.path.realpath(self.doc_root + path) return info # generate response def","port self.doc_root = doc_root self.host = '127.0.0.1' self.res_200 = \"HTTP/1.1 200 OK\\r\\nServer: Myserver","if len(h) < 2: continue field = h[0] value = h[1] info[field] =","len(h) < 2: continue field = h[0] value = h[1] info[field] = value","i < len(x): if '' in x: x.remove('') if i < 0 or","path escape from file root info['url'] = '404escape' return info if i <","# 404 not found if not os.path.isfile(path): return self.res_404 # a valid 200","'Content-Type: image/png\\r\\n\\r\\n' else: res += 'Content-Type: image/jpeg\\r\\n\\r\\n' res = res + str(data) return","= sys.argv[2] server = MyServer(input_port, input_doc_root) # Add code to start your server","= int(sys.argv[1]) input_doc_root = sys.argv[2] server = MyServer(input_port, input_doc_root) # Add code to","path = reqinfo['url'] # 404 escape if path == '404escape': return self.res_404 #","conn.recv(1024).decode() if not req: break info = server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg) #","<filename>httpd.py import sys import os import socket import time import threading class MyServer:","doc_root): self.port = port self.doc_root = doc_root self.host = '127.0.0.1' self.res_200 = \"HTTP/1.1","url.split('/') i = 0 while i < len(x): if '' in x: x.remove('')","createsocket(conn, addr): with conn: try: conn.settimeout(5) except socket.timeout: conn.close() # print('closed') # print('Connected","your server here threads = [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host, server.port))","res += 'Content-Type: image/png\\r\\n\\r\\n' else: res += 'Content-Type: image/jpeg\\r\\n\\r\\n' res = res +","return info if i < len(x) and x[i] == '..': x.remove(x[i]) x.remove(x[i -","request): # 400 malform if request[-4:] != '\\r\\n\\r\\n': info = {'url': '400malform'} return","if path == '404escape': return self.res_404 # 400 malform req if path ==","+= 'Content-Type: text/html\\r\\n\\r\\n' res = res + str(data, 'utf-8') else: # for jpg","return info headers = request.splitlines() firstline = headers.pop(0) try: (act, url, version) =","f.read() res += \"Content-Length: {}\\r\\n\".format(len(data)) if path.split('.')[-1] == 'html': res += 'Content-Type: text/html\\r\\n\\r\\n'","{'url': '400malform'} return info info = {'act': act, 'url': url, 'version': version} for","addr = s.accept() t = threading.Thread(target=createsocket(conn, addr), args=(conn, addr)) t.start() threads.append(t) for t","ValueError: info = {'url': '400malform'} return info info = {'act': act, 'url': url,","res = res + str(data) return res def createsocket(conn, addr): with conn: try:","s: s.bind((server.host, server.port)) s.listen() while True: conn, addr = s.accept() t = threading.Thread(target=createsocket(conn,","field = h[0] value = h[1] info[field] = value # mapping url, return","into dict def req_info(self, request): # 400 malform if request[-4:] != '\\r\\n\\r\\n': info","self.res_close = \"HTTP/1.1 Connection:close\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" # map request into dict def req_info(self,","x.remove('') if i < 0 or x[0] == '..' or len(x) == 0:","Client Error\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_close = \"HTTP/1.1 Connection:close\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" # map request","in range(len(x)): path = path + '/' + x[d] info['url'] = os.path.realpath(self.doc_root +","s.bind((server.host, server.port)) s.listen() while True: conn, addr = s.accept() t = threading.Thread(target=createsocket(conn, addr),","as f: data = f.read() res += \"Content-Length: {}\\r\\n\".format(len(data)) if path.split('.')[-1] == 'html':","i -= 1 else: i += 1 # map index.html if len(x[-1].split('.')) <","as s: s.bind((server.host, server.port)) s.listen() while True: conn, addr = s.accept() t =","addr): with conn: try: conn.settimeout(5) except socket.timeout: conn.close() # print('closed') # print('Connected by',","url, version) = firstline.split() except ValueError: info = {'url': '400malform'} return info info","threads = [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host, server.port)) s.listen() while True:","self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent'] except KeyError: return self.res_400 # 404 not found","act, 'url': url, 'version': version} for h in headers: h = h.split(': ')","'version': version} for h in headers: h = h.split(': ') if len(h) <","request into dict def req_info(self, request): # 400 malform if request[-4:] != '\\r\\n\\r\\n':","# print(\"msg send finished\") # msg = server.res_close.encode() # conn.sendall(msg) break if __name__","= firstline.split() except ValueError: info = {'url': '400malform'} return info info = {'act':","or x[0] == '..' or len(x) == 0: # path escape from file","\"HTTP/1.1 Connection:close\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" # map request into dict def req_info(self, request): #","{'act': act, 'url': url, 'version': version} for h in headers: h = h.split(':","'' x = url.split('/') i = 0 while i < len(x): if ''","h = h.split(': ') if len(h) < 2: continue field = h[0] value","self.res_404 # a valid 200 req else: res = self.res_200 res += \"Last-Modified:","reqinfo['Host'] and reqinfo['User-Agent'] except KeyError: return self.res_400 # 404 not found if not","index.html if len(x[-1].split('.')) < 2: x.append('index.html') for d in range(len(x)): path = path","= \"HTTP/1.1 200 OK\\r\\nServer: Myserver 1.0\\r\\n\" self.res_404 = \"HTTP/1.1 404 NOT FOUND\\r\\nServer: Myserver","msg = server.res_close.encode() # conn.sendall(msg) break if __name__ == '__main__': input_port = int(sys.argv[1])","def __init__(self, port, doc_root): self.port = port self.doc_root = doc_root self.host = '127.0.0.1'","escape path = '' x = url.split('/') i = 0 while i <","socket.SOCK_STREAM) as s: s.bind((server.host, server.port)) s.listen() while True: conn, addr = s.accept() t","res += 'Content-Type: text/html\\r\\n\\r\\n' res = res + str(data, 'utf-8') else: # for","'404escape': return self.res_404 # 400 malform req if path == \"400malform\": return self.res_400","'url': url, 'version': version} for h in headers: h = h.split(': ') if","res + str(data) return res def createsocket(conn, addr): with conn: try: conn.settimeout(5) except","if i < 0 or x[0] == '..' or len(x) == 0: #","404 not found if not os.path.isfile(path): return self.res_404 # a valid 200 req","info = {'act': act, 'url': url, 'version': version} for h in headers: h","= res + str(data) return res def createsocket(conn, addr): with conn: try: conn.settimeout(5)","escape or absolute filename # judge whether escape path = '' x =","value = h[1] info[field] = value # mapping url, return 404 escape or","OK\\r\\nServer: Myserver 1.0\\r\\n\" self.res_404 = \"HTTP/1.1 404 NOT FOUND\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_400 =","= '' x = url.split('/') i = 0 while i < len(x): if","len(x) and x[i] == '..': x.remove(x[i]) x.remove(x[i - 1]) i -= 1 else:","1.0\\r\\n\" self.res_404 = \"HTTP/1.1 404 NOT FOUND\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_400 = \"HTTP/1.1 400","\"HTTP/1.1 400 Client Error\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_close = \"HTTP/1.1 Connection:close\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" #","if request[-4:] != '\\r\\n\\r\\n': info = {'url': '400malform'} return info headers = request.splitlines()","url, return 404 escape or absolute filename # judge whether escape path =","path == '404escape': return self.res_404 # 400 malform req if path == \"400malform\":","= path + '/' + x[d] info['url'] = os.path.realpath(self.doc_root + path) return info","doc_root self.host = '127.0.0.1' self.res_200 = \"HTTP/1.1 200 OK\\r\\nServer: Myserver 1.0\\r\\n\" self.res_404 =","png if path.split('.')[-1] == 'png': res += 'Content-Type: image/png\\r\\n\\r\\n' else: res += 'Content-Type:","Myserver 1.0\\r\\n\" self.res_404 = \"HTTP/1.1 404 NOT FOUND\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_400 = \"HTTP/1.1","info['url'] = '404escape' return info if i < len(x) and x[i] == '..':","info # generate response def res_gen(self, reqinfo): path = reqinfo['url'] # 404 escape","'png': res += 'Content-Type: image/png\\r\\n\\r\\n' else: res += 'Content-Type: image/jpeg\\r\\n\\r\\n' res = res","image/jpeg\\r\\n\\r\\n' res = res + str(data) return res def createsocket(conn, addr): with conn:","info = server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg) # print(\"msg send finished\") # msg","= {'url': '400malform'} return info info = {'act': act, 'url': url, 'version': version}","break if __name__ == '__main__': input_port = int(sys.argv[1]) input_doc_root = sys.argv[2] server =","res = res + str(data, 'utf-8') else: # for jpg and png if","path.split('.')[-1] == 'html': res += 'Content-Type: text/html\\r\\n\\r\\n' res = res + str(data, 'utf-8')","conn.sendall(msg) # print(\"msg send finished\") # msg = server.res_close.encode() # conn.sendall(msg) break if","Connection:close\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" # map request into dict def req_info(self, request): # 400","# a valid 200 req else: res = self.res_200 res += \"Last-Modified: {}\\r\\n\".format(time.ctime(os.stat(path).st_mtime))","# msg = server.res_close.encode() # conn.sendall(msg) break if __name__ == '__main__': input_port =","return 404 escape or absolute filename # judge whether escape path = ''","\"400malform\": return self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent'] except KeyError: return self.res_400 # 404","a valid 200 req else: res = self.res_200 res += \"Last-Modified: {}\\r\\n\".format(time.ctime(os.stat(path).st_mtime)) with","{}\\r\\n\".format(len(data)) if path.split('.')[-1] == 'html': res += 'Content-Type: text/html\\r\\n\\r\\n' res = res +","escape from file root info['url'] = '404escape' return info if i < len(x)","def res_gen(self, reqinfo): path = reqinfo['url'] # 404 escape if path == '404escape':","str(data, 'utf-8') else: # for jpg and png if path.split('.')[-1] == 'png': res","res += \"Content-Length: {}\\r\\n\".format(len(data)) if path.split('.')[-1] == 'html': res += 'Content-Type: text/html\\r\\n\\r\\n' res","= self.res_200 res += \"Last-Modified: {}\\r\\n\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \"rb\") as f: data =","len(x) == 0: # path escape from file root info['url'] = '404escape' return","if __name__ == '__main__': input_port = int(sys.argv[1]) input_doc_root = sys.argv[2] server = MyServer(input_port,","f: data = f.read() res += \"Content-Length: {}\\r\\n\".format(len(data)) if path.split('.')[-1] == 'html': res","# 400 malform if request[-4:] != '\\r\\n\\r\\n': info = {'url': '400malform'} return info","range(len(x)): path = path + '/' + x[d] info['url'] = os.path.realpath(self.doc_root + path)","+= 1 # map index.html if len(x[-1].split('.')) < 2: x.append('index.html') for d in","(act, url, version) = firstline.split() except ValueError: info = {'url': '400malform'} return info","sys import os import socket import time import threading class MyServer: def __init__(self,","try: (act, url, version) = firstline.split() except ValueError: info = {'url': '400malform'} return","root info['url'] = '404escape' return info if i < len(x) and x[i] ==","'..': x.remove(x[i]) x.remove(x[i - 1]) i -= 1 else: i += 1 #","h[1] info[field] = value # mapping url, return 404 escape or absolute filename","except socket.timeout: conn.close() # print('closed') # print('Connected by', addr) while True: req =","= s.accept() t = threading.Thread(target=createsocket(conn, addr), args=(conn, addr)) t.start() threads.append(t) for t in","if path.split('.')[-1] == 'png': res += 'Content-Type: image/png\\r\\n\\r\\n' else: res += 'Content-Type: image/jpeg\\r\\n\\r\\n'","print('Connected by', addr) while True: req = conn.recv(1024).decode() if not req: break info","conn, addr = s.accept() t = threading.Thread(target=createsocket(conn, addr), args=(conn, addr)) t.start() threads.append(t) for","mapping url, return 404 escape or absolute filename # judge whether escape path","< 0 or x[0] == '..' or len(x) == 0: # path escape","return info info = {'act': act, 'url': url, 'version': version} for h in","= {'url': '400malform'} return info headers = request.splitlines() firstline = headers.pop(0) try: (act,","int(sys.argv[1]) input_doc_root = sys.argv[2] server = MyServer(input_port, input_doc_root) # Add code to start","generate response def res_gen(self, reqinfo): path = reqinfo['url'] # 404 escape if path","found if not os.path.isfile(path): return self.res_404 # a valid 200 req else: res","while True: req = conn.recv(1024).decode() if not req: break info = server.req_info(req) msg","1.0\\r\\n\\r\\n\" self.res_400 = \"HTTP/1.1 400 Client Error\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_close = \"HTTP/1.1 Connection:close\\r\\nServer:","path = path + '/' + x[d] info['url'] = os.path.realpath(self.doc_root + path) return","and png if path.split('.')[-1] == 'png': res += 'Content-Type: image/png\\r\\n\\r\\n' else: res +=","socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host, server.port)) s.listen() while True: conn, addr = s.accept()","i < 0 or x[0] == '..' or len(x) == 0: # path","'' in x: x.remove('') if i < 0 or x[0] == '..' or","= server.res_close.encode() # conn.sendall(msg) break if __name__ == '__main__': input_port = int(sys.argv[1]) input_doc_root","input_port = int(sys.argv[1]) input_doc_root = sys.argv[2] server = MyServer(input_port, input_doc_root) # Add code","= '127.0.0.1' self.res_200 = \"HTTP/1.1 200 OK\\r\\nServer: Myserver 1.0\\r\\n\" self.res_404 = \"HTTP/1.1 404","return self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent'] except KeyError: return self.res_400 # 404 not","except ValueError: info = {'url': '400malform'} return info info = {'act': act, 'url':","__name__ == '__main__': input_port = int(sys.argv[1]) input_doc_root = sys.argv[2] server = MyServer(input_port, input_doc_root)","version) = firstline.split() except ValueError: info = {'url': '400malform'} return info info =","not req: break info = server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg) # print(\"msg send","try: reqinfo['Host'] and reqinfo['User-Agent'] except KeyError: return self.res_400 # 404 not found if","= \"HTTP/1.1 Connection:close\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" # map request into dict def req_info(self, request):","{'url': '400malform'} return info headers = request.splitlines() firstline = headers.pop(0) try: (act, url,","code to start your server here threads = [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as","= '404escape' return info if i < len(x) and x[i] == '..': x.remove(x[i])","'\\r\\n\\r\\n': info = {'url': '400malform'} return info headers = request.splitlines() firstline = headers.pop(0)","'__main__': input_port = int(sys.argv[1]) input_doc_root = sys.argv[2] server = MyServer(input_port, input_doc_root) # Add","__init__(self, port, doc_root): self.port = port self.doc_root = doc_root self.host = '127.0.0.1' self.res_200","server here threads = [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host, server.port)) s.listen()","here threads = [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host, server.port)) s.listen() while","self.doc_root = doc_root self.host = '127.0.0.1' self.res_200 = \"HTTP/1.1 200 OK\\r\\nServer: Myserver 1.0\\r\\n\"","+ str(data) return res def createsocket(conn, addr): with conn: try: conn.settimeout(5) except socket.timeout:","conn.settimeout(5) except socket.timeout: conn.close() # print('closed') # print('Connected by', addr) while True: req","headers.pop(0) try: (act, url, version) = firstline.split() except ValueError: info = {'url': '400malform'}","= value # mapping url, return 404 escape or absolute filename # judge","path == \"400malform\": return self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent'] except KeyError: return self.res_400","self.res_404 # 400 malform req if path == \"400malform\": return self.res_400 try: reqinfo['Host']","request.splitlines() firstline = headers.pop(0) try: (act, url, version) = firstline.split() except ValueError: info","NOT FOUND\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_400 = \"HTTP/1.1 400 Client Error\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_close","0 or x[0] == '..' or len(x) == 0: # path escape from","and x[i] == '..': x.remove(x[i]) x.remove(x[i - 1]) i -= 1 else: i","'Content-Type: text/html\\r\\n\\r\\n' res = res + str(data, 'utf-8') else: # for jpg and","+ '/' + x[d] info['url'] = os.path.realpath(self.doc_root + path) return info # generate","self.res_400 # 404 not found if not os.path.isfile(path): return self.res_404 # a valid","url, 'version': version} for h in headers: h = h.split(': ') if len(h)","dict def req_info(self, request): # 400 malform if request[-4:] != '\\r\\n\\r\\n': info =","def createsocket(conn, addr): with conn: try: conn.settimeout(5) except socket.timeout: conn.close() # print('closed') #","{}\\r\\n\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \"rb\") as f: data = f.read() res += \"Content-Length: {}\\r\\n\".format(len(data))","# 400 malform req if path == \"400malform\": return self.res_400 try: reqinfo['Host'] and","= res + str(data, 'utf-8') else: # for jpg and png if path.split('.')[-1]","info if i < len(x) and x[i] == '..': x.remove(x[i]) x.remove(x[i - 1])","while True: conn, addr = s.accept() t = threading.Thread(target=createsocket(conn, addr), args=(conn, addr)) t.start()","if not req: break info = server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg) # print(\"msg","else: res += 'Content-Type: image/jpeg\\r\\n\\r\\n' res = res + str(data) return res def","res = self.res_200 res += \"Last-Modified: {}\\r\\n\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \"rb\") as f: data","True: req = conn.recv(1024).decode() if not req: break info = server.req_info(req) msg =","KeyError: return self.res_400 # 404 not found if not os.path.isfile(path): return self.res_404 #","for jpg and png if path.split('.')[-1] == 'png': res += 'Content-Type: image/png\\r\\n\\r\\n' else:","h in headers: h = h.split(': ') if len(h) < 2: continue field","req: break info = server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg) # print(\"msg send finished\")","reqinfo['User-Agent'] except KeyError: return self.res_400 # 404 not found if not os.path.isfile(path): return","headers = request.splitlines() firstline = headers.pop(0) try: (act, url, version) = firstline.split() except","else: res = self.res_200 res += \"Last-Modified: {}\\r\\n\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \"rb\") as f:","data = f.read() res += \"Content-Length: {}\\r\\n\".format(len(data)) if path.split('.')[-1] == 'html': res +=","= {'act': act, 'url': url, 'version': version} for h in headers: h =","text/html\\r\\n\\r\\n' res = res + str(data, 'utf-8') else: # for jpg and png","== 'png': res += 'Content-Type: image/png\\r\\n\\r\\n' else: res += 'Content-Type: image/jpeg\\r\\n\\r\\n' res =","req if path == \"400malform\": return self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent'] except KeyError:","= headers.pop(0) try: (act, url, version) = firstline.split() except ValueError: info = {'url':","# path escape from file root info['url'] = '404escape' return info if i","# print('closed') # print('Connected by', addr) while True: req = conn.recv(1024).decode() if not","filename # judge whether escape path = '' x = url.split('/') i =","+= \"Content-Length: {}\\r\\n\".format(len(data)) if path.split('.')[-1] == 'html': res += 'Content-Type: text/html\\r\\n\\r\\n' res =","import socket import time import threading class MyServer: def __init__(self, port, doc_root): self.port","print('closed') # print('Connected by', addr) while True: req = conn.recv(1024).decode() if not req:","server.port)) s.listen() while True: conn, addr = s.accept() t = threading.Thread(target=createsocket(conn, addr), args=(conn,","# judge whether escape path = '' x = url.split('/') i = 0","continue field = h[0] value = h[1] info[field] = value # mapping url,","if len(x[-1].split('.')) < 2: x.append('index.html') for d in range(len(x)): path = path +","400 malform req if path == \"400malform\": return self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent']","# 404 escape if path == '404escape': return self.res_404 # 400 malform req","\"rb\") as f: data = f.read() res += \"Content-Length: {}\\r\\n\".format(len(data)) if path.split('.')[-1] ==","404 escape or absolute filename # judge whether escape path = '' x","addr) while True: req = conn.recv(1024).decode() if not req: break info = server.req_info(req)","req_info(self, request): # 400 malform if request[-4:] != '\\r\\n\\r\\n': info = {'url': '400malform'}","return self.res_400 # 404 not found if not os.path.isfile(path): return self.res_404 # a","info = {'url': '400malform'} return info info = {'act': act, 'url': url, 'version':","= server.res_gen(info).encode() conn.sendall(msg) # print(\"msg send finished\") # msg = server.res_close.encode() # conn.sendall(msg)","= [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host, server.port)) s.listen() while True: conn,","path) return info # generate response def res_gen(self, reqinfo): path = reqinfo['url'] #","Myserver 1.0\\r\\n\\r\\n\" self.res_close = \"HTTP/1.1 Connection:close\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" # map request into dict","d in range(len(x)): path = path + '/' + x[d] info['url'] = os.path.realpath(self.doc_root","== 0: # path escape from file root info['url'] = '404escape' return info","'400malform'} return info headers = request.splitlines() firstline = headers.pop(0) try: (act, url, version)","< len(x): if '' in x: x.remove('') if i < 0 or x[0]","while i < len(x): if '' in x: x.remove('') if i < 0","= \"HTTP/1.1 404 NOT FOUND\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_400 = \"HTTP/1.1 400 Client Error\\r\\nServer:","time import threading class MyServer: def __init__(self, port, doc_root): self.port = port self.doc_root","MyServer: def __init__(self, port, doc_root): self.port = port self.doc_root = doc_root self.host =","self.port = port self.doc_root = doc_root self.host = '127.0.0.1' self.res_200 = \"HTTP/1.1 200","else: # for jpg and png if path.split('.')[-1] == 'png': res += 'Content-Type:","MyServer(input_port, input_doc_root) # Add code to start your server here threads = []","for d in range(len(x)): path = path + '/' + x[d] info['url'] =","from file root info['url'] = '404escape' return info if i < len(x) and","if '' in x: x.remove('') if i < 0 or x[0] == '..'","path + '/' + x[d] info['url'] = os.path.realpath(self.doc_root + path) return info #","port, doc_root): self.port = port self.doc_root = doc_root self.host = '127.0.0.1' self.res_200 =","'utf-8') else: # for jpg and png if path.split('.')[-1] == 'png': res +=","\"Content-Length: {}\\r\\n\".format(len(data)) if path.split('.')[-1] == 'html': res += 'Content-Type: text/html\\r\\n\\r\\n' res = res","'/' + x[d] info['url'] = os.path.realpath(self.doc_root + path) return info # generate response","request[-4:] != '\\r\\n\\r\\n': info = {'url': '400malform'} return info headers = request.splitlines() firstline","try: conn.settimeout(5) except socket.timeout: conn.close() # print('closed') # print('Connected by', addr) while True:","not found if not os.path.isfile(path): return self.res_404 # a valid 200 req else:","# generate response def res_gen(self, reqinfo): path = reqinfo['url'] # 404 escape if","x[i] == '..': x.remove(x[i]) x.remove(x[i - 1]) i -= 1 else: i +=","finished\") # msg = server.res_close.encode() # conn.sendall(msg) break if __name__ == '__main__': input_port","res += 'Content-Type: image/jpeg\\r\\n\\r\\n' res = res + str(data) return res def createsocket(conn,","msg = server.res_gen(info).encode() conn.sendall(msg) # print(\"msg send finished\") # msg = server.res_close.encode() #","whether escape path = '' x = url.split('/') i = 0 while i","\"HTTP/1.1 200 OK\\r\\nServer: Myserver 1.0\\r\\n\" self.res_404 = \"HTTP/1.1 404 NOT FOUND\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\"","in headers: h = h.split(': ') if len(h) < 2: continue field =","x.append('index.html') for d in range(len(x)): path = path + '/' + x[d] info['url']","x.remove(x[i - 1]) i -= 1 else: i += 1 # map index.html","return res def createsocket(conn, addr): with conn: try: conn.settimeout(5) except socket.timeout: conn.close() #","input_doc_root = sys.argv[2] server = MyServer(input_port, input_doc_root) # Add code to start your","server = MyServer(input_port, input_doc_root) # Add code to start your server here threads","def req_info(self, request): # 400 malform if request[-4:] != '\\r\\n\\r\\n': info = {'url':","map request into dict def req_info(self, request): # 400 malform if request[-4:] !=","Add code to start your server here threads = [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM)","os.path.isfile(path): return self.res_404 # a valid 200 req else: res = self.res_200 res","h[0] value = h[1] info[field] = value # mapping url, return 404 escape","server.res_close.encode() # conn.sendall(msg) break if __name__ == '__main__': input_port = int(sys.argv[1]) input_doc_root =","-= 1 else: i += 1 # map index.html if len(x[-1].split('.')) < 2:","not os.path.isfile(path): return self.res_404 # a valid 200 req else: res = self.res_200","404 NOT FOUND\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_400 = \"HTTP/1.1 400 Client Error\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\"","server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg) # print(\"msg send finished\") # msg = server.res_close.encode()","sys.argv[2] server = MyServer(input_port, input_doc_root) # Add code to start your server here","= f.read() res += \"Content-Length: {}\\r\\n\".format(len(data)) if path.split('.')[-1] == 'html': res += 'Content-Type:","self.res_200 res += \"Last-Modified: {}\\r\\n\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \"rb\") as f: data = f.read()","server.res_gen(info).encode() conn.sendall(msg) # print(\"msg send finished\") # msg = server.res_close.encode() # conn.sendall(msg) break","and reqinfo['User-Agent'] except KeyError: return self.res_400 # 404 not found if not os.path.isfile(path):","image/png\\r\\n\\r\\n' else: res += 'Content-Type: image/jpeg\\r\\n\\r\\n' res = res + str(data) return res","firstline = headers.pop(0) try: (act, url, version) = firstline.split() except ValueError: info =","i += 1 # map index.html if len(x[-1].split('.')) < 2: x.append('index.html') for d","reqinfo): path = reqinfo['url'] # 404 escape if path == '404escape': return self.res_404","= os.path.realpath(self.doc_root + path) return info # generate response def res_gen(self, reqinfo): path","0 while i < len(x): if '' in x: x.remove('') if i <","'..' or len(x) == 0: # path escape from file root info['url'] =","= url.split('/') i = 0 while i < len(x): if '' in x:","= h[1] info[field] = value # mapping url, return 404 escape or absolute","'Content-Type: image/jpeg\\r\\n\\r\\n' res = res + str(data) return res def createsocket(conn, addr): with","start your server here threads = [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host,","judge whether escape path = '' x = url.split('/') i = 0 while","with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host, server.port)) s.listen() while True: conn, addr =","import time import threading class MyServer: def __init__(self, port, doc_root): self.port = port","len(x[-1].split('.')) < 2: x.append('index.html') for d in range(len(x)): path = path + '/'","import threading class MyServer: def __init__(self, port, doc_root): self.port = port self.doc_root =","== 'html': res += 'Content-Type: text/html\\r\\n\\r\\n' res = res + str(data, 'utf-8') else:","# map index.html if len(x[-1].split('.')) < 2: x.append('index.html') for d in range(len(x)): path","200 OK\\r\\nServer: Myserver 1.0\\r\\n\" self.res_404 = \"HTTP/1.1 404 NOT FOUND\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_400","< len(x) and x[i] == '..': x.remove(x[i]) x.remove(x[i - 1]) i -= 1","i < len(x) and x[i] == '..': x.remove(x[i]) x.remove(x[i - 1]) i -=","path.split('.')[-1] == 'png': res += 'Content-Type: image/png\\r\\n\\r\\n' else: res += 'Content-Type: image/jpeg\\r\\n\\r\\n' res","== '404escape': return self.res_404 # 400 malform req if path == \"400malform\": return","req else: res = self.res_200 res += \"Last-Modified: {}\\r\\n\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \"rb\") as","if i < len(x) and x[i] == '..': x.remove(x[i]) x.remove(x[i - 1]) i","'html': res += 'Content-Type: text/html\\r\\n\\r\\n' res = res + str(data, 'utf-8') else: #","firstline.split() except ValueError: info = {'url': '400malform'} return info info = {'act': act,","for h in headers: h = h.split(': ') if len(h) < 2: continue","self.host = '127.0.0.1' self.res_200 = \"HTTP/1.1 200 OK\\r\\nServer: Myserver 1.0\\r\\n\" self.res_404 = \"HTTP/1.1","info['url'] = os.path.realpath(self.doc_root + path) return info # generate response def res_gen(self, reqinfo):","conn: try: conn.settimeout(5) except socket.timeout: conn.close() # print('closed') # print('Connected by', addr) while","len(x): if '' in x: x.remove('') if i < 0 or x[0] ==","class MyServer: def __init__(self, port, doc_root): self.port = port self.doc_root = doc_root self.host","escape if path == '404escape': return self.res_404 # 400 malform req if path","True: conn, addr = s.accept() t = threading.Thread(target=createsocket(conn, addr), args=(conn, addr)) t.start() threads.append(t)","# for jpg and png if path.split('.')[-1] == 'png': res += 'Content-Type: image/png\\r\\n\\r\\n'","[] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host, server.port)) s.listen() while True: conn, addr","400 malform if request[-4:] != '\\r\\n\\r\\n': info = {'url': '400malform'} return info headers","map index.html if len(x[-1].split('.')) < 2: x.append('index.html') for d in range(len(x)): path =","+= 'Content-Type: image/jpeg\\r\\n\\r\\n' res = res + str(data) return res def createsocket(conn, addr):","to start your server here threads = [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:","1 # map index.html if len(x[-1].split('.')) < 2: x.append('index.html') for d in range(len(x)):","# map request into dict def req_info(self, request): # 400 malform if request[-4:]","'400malform'} return info info = {'act': act, 'url': url, 'version': version} for h","s.listen() while True: conn, addr = s.accept() t = threading.Thread(target=createsocket(conn, addr), args=(conn, addr))","info headers = request.splitlines() firstline = headers.pop(0) try: (act, url, version) = firstline.split()","!= '\\r\\n\\r\\n': info = {'url': '400malform'} return info headers = request.splitlines() firstline =","info info = {'act': act, 'url': url, 'version': version} for h in headers:","< 2: x.append('index.html') for d in range(len(x)): path = path + '/' +","== '..' or len(x) == 0: # path escape from file root info['url']","conn.sendall(msg) break if __name__ == '__main__': input_port = int(sys.argv[1]) input_doc_root = sys.argv[2] server","path = '' x = url.split('/') i = 0 while i < len(x):","socket.timeout: conn.close() # print('closed') # print('Connected by', addr) while True: req = conn.recv(1024).decode()","== '..': x.remove(x[i]) x.remove(x[i - 1]) i -= 1 else: i += 1","jpg and png if path.split('.')[-1] == 'png': res += 'Content-Type: image/png\\r\\n\\r\\n' else: res","res + str(data, 'utf-8') else: # for jpg and png if path.split('.')[-1] ==","+= \"Last-Modified: {}\\r\\n\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \"rb\") as f: data = f.read() res +=","req = conn.recv(1024).decode() if not req: break info = server.req_info(req) msg = server.res_gen(info).encode()","1]) i -= 1 else: i += 1 # map index.html if len(x[-1].split('.'))","except KeyError: return self.res_400 # 404 not found if not os.path.isfile(path): return self.res_404","1 else: i += 1 # map index.html if len(x[-1].split('.')) < 2: x.append('index.html')","response def res_gen(self, reqinfo): path = reqinfo['url'] # 404 escape if path ==","404 escape if path == '404escape': return self.res_404 # 400 malform req if","conn.close() # print('closed') # print('Connected by', addr) while True: req = conn.recv(1024).decode() if","= h[0] value = h[1] info[field] = value # mapping url, return 404","break info = server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg) # print(\"msg send finished\") #","x[d] info['url'] = os.path.realpath(self.doc_root + path) return info # generate response def res_gen(self,","Error\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_close = \"HTTP/1.1 Connection:close\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" # map request into","headers: h = h.split(': ') if len(h) < 2: continue field = h[0]","absolute filename # judge whether escape path = '' x = url.split('/') i","') if len(h) < 2: continue field = h[0] value = h[1] info[field]","= h.split(': ') if len(h) < 2: continue field = h[0] value =","or absolute filename # judge whether escape path = '' x = url.split('/')","os import socket import time import threading class MyServer: def __init__(self, port, doc_root):","self.res_200 = \"HTTP/1.1 200 OK\\r\\nServer: Myserver 1.0\\r\\n\" self.res_404 = \"HTTP/1.1 404 NOT FOUND\\r\\nServer:","= reqinfo['url'] # 404 escape if path == '404escape': return self.res_404 # 400","1.0\\r\\n\\r\\n\" self.res_close = \"HTTP/1.1 Connection:close\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" # map request into dict def","= \"HTTP/1.1 400 Client Error\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\" self.res_close = \"HTTP/1.1 Connection:close\\r\\nServer: Myserver 1.0\\r\\n\\r\\n\"","if not os.path.isfile(path): return self.res_404 # a valid 200 req else: res =","info[field] = value # mapping url, return 404 escape or absolute filename #","== '__main__': input_port = int(sys.argv[1]) input_doc_root = sys.argv[2] server = MyServer(input_port, input_doc_root) #"],"string":"[\n \"# conn.sendall(msg) break if __name__ == '__main__': input_port = int(sys.argv[1]) input_doc_root = sys.argv[2]\",\n \"200 req else: res = self.res_200 res += \\\"Last-Modified: {}\\\\r\\\\n\\\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \\\"rb\\\")\",\n \"# mapping url, return 404 escape or absolute filename # judge whether escape\",\n \"with open(path, \\\"rb\\\") as f: data = f.read() res += \\\"Content-Length: {}\\\\r\\\\n\\\".format(len(data)) if\",\n \"s.accept() t = threading.Thread(target=createsocket(conn, addr), args=(conn, addr)) t.start() threads.append(t) for t in threads:\",\n \"os.path.realpath(self.doc_root + path) return info # generate response def res_gen(self, reqinfo): path =\",\n \"res_gen(self, reqinfo): path = reqinfo['url'] # 404 escape if path == '404escape': return\",\n \"'404escape' return info if i < len(x) and x[i] == '..': x.remove(x[i]) x.remove(x[i\",\n \"FOUND\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_400 = \\\"HTTP/1.1 400 Client Error\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_close =\",\n \"threading class MyServer: def __init__(self, port, doc_root): self.port = port self.doc_root = doc_root\",\n \"= doc_root self.host = '127.0.0.1' self.res_200 = \\\"HTTP/1.1 200 OK\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\" self.res_404\",\n \"# print('Connected by', addr) while True: req = conn.recv(1024).decode() if not req: break\",\n \"400 Client Error\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_close = \\\"HTTP/1.1 Connection:close\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" # map\",\n \"reqinfo['url'] # 404 escape if path == '404escape': return self.res_404 # 400 malform\",\n \"h.split(': ') if len(h) < 2: continue field = h[0] value = h[1]\",\n \"\\\"HTTP/1.1 404 NOT FOUND\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_400 = \\\"HTTP/1.1 400 Client Error\\\\r\\\\nServer: Myserver\",\n \"send finished\\\") # msg = server.res_close.encode() # conn.sendall(msg) break if __name__ == '__main__':\",\n \"return self.res_404 # a valid 200 req else: res = self.res_200 res +=\",\n \"malform if request[-4:] != '\\\\r\\\\n\\\\r\\\\n': info = {'url': '400malform'} return info headers =\",\n \"print(\\\"msg send finished\\\") # msg = server.res_close.encode() # conn.sendall(msg) break if __name__ ==\",\n \"1.0\\\\r\\\\n\\\\r\\\\n\\\" # map request into dict def req_info(self, request): # 400 malform if\",\n \"= port self.doc_root = doc_root self.host = '127.0.0.1' self.res_200 = \\\"HTTP/1.1 200 OK\\\\r\\\\nServer:\",\n \"value # mapping url, return 404 escape or absolute filename # judge whether\",\n \"+= 'Content-Type: image/png\\\\r\\\\n\\\\r\\\\n' else: res += 'Content-Type: image/jpeg\\\\r\\\\n\\\\r\\\\n' res = res + str(data)\",\n \"import sys import os import socket import time import threading class MyServer: def\",\n \"Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" # map request into dict def req_info(self, request): # 400 malform\",\n \"< 2: continue field = h[0] value = h[1] info[field] = value #\",\n \"x[0] == '..' or len(x) == 0: # path escape from file root\",\n \"2: continue field = h[0] value = h[1] info[field] = value # mapping\",\n \"info = {'url': '400malform'} return info headers = request.splitlines() firstline = headers.pop(0) try:\",\n \"'127.0.0.1' self.res_200 = \\\"HTTP/1.1 200 OK\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\" self.res_404 = \\\"HTTP/1.1 404 NOT\",\n \"open(path, \\\"rb\\\") as f: data = f.read() res += \\\"Content-Length: {}\\\\r\\\\n\\\".format(len(data)) if path.split('.')[-1]\",\n \"= MyServer(input_port, input_doc_root) # Add code to start your server here threads =\",\n \"return info # generate response def res_gen(self, reqinfo): path = reqinfo['url'] # 404\",\n \"\\\"Last-Modified: {}\\\\r\\\\n\\\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \\\"rb\\\") as f: data = f.read() res += \\\"Content-Length:\",\n \"valid 200 req else: res = self.res_200 res += \\\"Last-Modified: {}\\\\r\\\\n\\\".format(time.ctime(os.stat(path).st_mtime)) with open(path,\",\n \"self.res_400 = \\\"HTTP/1.1 400 Client Error\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_close = \\\"HTTP/1.1 Connection:close\\\\r\\\\nServer: Myserver\",\n \"- 1]) i -= 1 else: i += 1 # map index.html if\",\n \"str(data) return res def createsocket(conn, addr): with conn: try: conn.settimeout(5) except socket.timeout: conn.close()\",\n \"2: x.append('index.html') for d in range(len(x)): path = path + '/' + x[d]\",\n \"input_doc_root) # Add code to start your server here threads = [] with\",\n \"or len(x) == 0: # path escape from file root info['url'] = '404escape'\",\n \"malform req if path == \\\"400malform\\\": return self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent'] except\",\n \"x.remove(x[i]) x.remove(x[i - 1]) i -= 1 else: i += 1 # map\",\n \"+ str(data, 'utf-8') else: # for jpg and png if path.split('.')[-1] == 'png':\",\n \"0: # path escape from file root info['url'] = '404escape' return info if\",\n \"self.res_404 = \\\"HTTP/1.1 404 NOT FOUND\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_400 = \\\"HTTP/1.1 400 Client\",\n \"# Add code to start your server here threads = [] with socket.socket(socket.AF_INET,\",\n \"t = threading.Thread(target=createsocket(conn, addr), args=(conn, addr)) t.start() threads.append(t) for t in threads: t.join()\",\n \"res def createsocket(conn, addr): with conn: try: conn.settimeout(5) except socket.timeout: conn.close() # print('closed')\",\n \"+ path) return info # generate response def res_gen(self, reqinfo): path = reqinfo['url']\",\n \"with conn: try: conn.settimeout(5) except socket.timeout: conn.close() # print('closed') # print('Connected by', addr)\",\n \"Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_400 = \\\"HTTP/1.1 400 Client Error\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_close = \\\"HTTP/1.1\",\n \"file root info['url'] = '404escape' return info if i < len(x) and x[i]\",\n \"= conn.recv(1024).decode() if not req: break info = server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg)\",\n \"if path == \\\"400malform\\\": return self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent'] except KeyError: return\",\n \"x = url.split('/') i = 0 while i < len(x): if '' in\",\n \"socket import time import threading class MyServer: def __init__(self, port, doc_root): self.port =\",\n \"version} for h in headers: h = h.split(': ') if len(h) < 2:\",\n \"== \\\"400malform\\\": return self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent'] except KeyError: return self.res_400 #\",\n \"import os import socket import time import threading class MyServer: def __init__(self, port,\",\n \"else: i += 1 # map index.html if len(x[-1].split('.')) < 2: x.append('index.html') for\",\n \"return self.res_404 # 400 malform req if path == \\\"400malform\\\": return self.res_400 try:\",\n \"i = 0 while i < len(x): if '' in x: x.remove('') if\",\n \"= 0 while i < len(x): if '' in x: x.remove('') if i\",\n \"= request.splitlines() firstline = headers.pop(0) try: (act, url, version) = firstline.split() except ValueError:\",\n \"res += \\\"Last-Modified: {}\\\\r\\\\n\\\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \\\"rb\\\") as f: data = f.read() res\",\n \"if path.split('.')[-1] == 'html': res += 'Content-Type: text/html\\\\r\\\\n\\\\r\\\\n' res = res + str(data,\",\n \"by', addr) while True: req = conn.recv(1024).decode() if not req: break info =\",\n \"in x: x.remove('') if i < 0 or x[0] == '..' or len(x)\",\n \"= server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg) # print(\\\"msg send finished\\\") # msg =\",\n \"x: x.remove('') if i < 0 or x[0] == '..' or len(x) ==\",\n \"+ x[d] info['url'] = os.path.realpath(self.doc_root + path) return info # generate response def\",\n \"port self.doc_root = doc_root self.host = '127.0.0.1' self.res_200 = \\\"HTTP/1.1 200 OK\\\\r\\\\nServer: Myserver\",\n \"if len(h) < 2: continue field = h[0] value = h[1] info[field] =\",\n \"len(h) < 2: continue field = h[0] value = h[1] info[field] = value\",\n \"i < len(x): if '' in x: x.remove('') if i < 0 or\",\n \"path escape from file root info['url'] = '404escape' return info if i <\",\n \"# 404 not found if not os.path.isfile(path): return self.res_404 # a valid 200\",\n \"'Content-Type: image/png\\\\r\\\\n\\\\r\\\\n' else: res += 'Content-Type: image/jpeg\\\\r\\\\n\\\\r\\\\n' res = res + str(data) return\",\n \"= sys.argv[2] server = MyServer(input_port, input_doc_root) # Add code to start your server\",\n \"= int(sys.argv[1]) input_doc_root = sys.argv[2] server = MyServer(input_port, input_doc_root) # Add code to\",\n \"path = reqinfo['url'] # 404 escape if path == '404escape': return self.res_404 #\",\n \"conn.recv(1024).decode() if not req: break info = server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg) #\",\n \"<filename>httpd.py import sys import os import socket import time import threading class MyServer:\",\n \"doc_root): self.port = port self.doc_root = doc_root self.host = '127.0.0.1' self.res_200 = \\\"HTTP/1.1\",\n \"url.split('/') i = 0 while i < len(x): if '' in x: x.remove('')\",\n \"createsocket(conn, addr): with conn: try: conn.settimeout(5) except socket.timeout: conn.close() # print('closed') # print('Connected\",\n \"your server here threads = [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host, server.port))\",\n \"res += 'Content-Type: image/png\\\\r\\\\n\\\\r\\\\n' else: res += 'Content-Type: image/jpeg\\\\r\\\\n\\\\r\\\\n' res = res +\",\n \"return info if i < len(x) and x[i] == '..': x.remove(x[i]) x.remove(x[i -\",\n \"request): # 400 malform if request[-4:] != '\\\\r\\\\n\\\\r\\\\n': info = {'url': '400malform'} return\",\n \"if path == '404escape': return self.res_404 # 400 malform req if path ==\",\n \"+= 'Content-Type: text/html\\\\r\\\\n\\\\r\\\\n' res = res + str(data, 'utf-8') else: # for jpg\",\n \"return info headers = request.splitlines() firstline = headers.pop(0) try: (act, url, version) =\",\n \"f.read() res += \\\"Content-Length: {}\\\\r\\\\n\\\".format(len(data)) if path.split('.')[-1] == 'html': res += 'Content-Type: text/html\\\\r\\\\n\\\\r\\\\n'\",\n \"{'url': '400malform'} return info info = {'act': act, 'url': url, 'version': version} for\",\n \"addr = s.accept() t = threading.Thread(target=createsocket(conn, addr), args=(conn, addr)) t.start() threads.append(t) for t\",\n \"ValueError: info = {'url': '400malform'} return info info = {'act': act, 'url': url,\",\n \"res = res + str(data) return res def createsocket(conn, addr): with conn: try:\",\n \"s: s.bind((server.host, server.port)) s.listen() while True: conn, addr = s.accept() t = threading.Thread(target=createsocket(conn,\",\n \"field = h[0] value = h[1] info[field] = value # mapping url, return\",\n \"into dict def req_info(self, request): # 400 malform if request[-4:] != '\\\\r\\\\n\\\\r\\\\n': info\",\n \"self.res_close = \\\"HTTP/1.1 Connection:close\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" # map request into dict def req_info(self,\",\n \"x.remove('') if i < 0 or x[0] == '..' or len(x) == 0:\",\n \"Client Error\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_close = \\\"HTTP/1.1 Connection:close\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" # map request\",\n \"in range(len(x)): path = path + '/' + x[d] info['url'] = os.path.realpath(self.doc_root +\",\n \"s.bind((server.host, server.port)) s.listen() while True: conn, addr = s.accept() t = threading.Thread(target=createsocket(conn, addr),\",\n \"as f: data = f.read() res += \\\"Content-Length: {}\\\\r\\\\n\\\".format(len(data)) if path.split('.')[-1] == 'html':\",\n \"i -= 1 else: i += 1 # map index.html if len(x[-1].split('.')) <\",\n \"as s: s.bind((server.host, server.port)) s.listen() while True: conn, addr = s.accept() t =\",\n \"addr): with conn: try: conn.settimeout(5) except socket.timeout: conn.close() # print('closed') # print('Connected by',\",\n \"url, version) = firstline.split() except ValueError: info = {'url': '400malform'} return info info\",\n \"threads = [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host, server.port)) s.listen() while True:\",\n \"self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent'] except KeyError: return self.res_400 # 404 not found\",\n \"act, 'url': url, 'version': version} for h in headers: h = h.split(': ')\",\n \"'version': version} for h in headers: h = h.split(': ') if len(h) <\",\n \"request into dict def req_info(self, request): # 400 malform if request[-4:] != '\\\\r\\\\n\\\\r\\\\n':\",\n \"# print(\\\"msg send finished\\\") # msg = server.res_close.encode() # conn.sendall(msg) break if __name__\",\n \"= firstline.split() except ValueError: info = {'url': '400malform'} return info info = {'act':\",\n \"or x[0] == '..' or len(x) == 0: # path escape from file\",\n \"\\\"HTTP/1.1 Connection:close\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" # map request into dict def req_info(self, request): #\",\n \"{'act': act, 'url': url, 'version': version} for h in headers: h = h.split(':\",\n \"'' x = url.split('/') i = 0 while i < len(x): if ''\",\n \"h = h.split(': ') if len(h) < 2: continue field = h[0] value\",\n \"self.res_404 # a valid 200 req else: res = self.res_200 res += \\\"Last-Modified:\",\n \"reqinfo['Host'] and reqinfo['User-Agent'] except KeyError: return self.res_400 # 404 not found if not\",\n \"index.html if len(x[-1].split('.')) < 2: x.append('index.html') for d in range(len(x)): path = path\",\n \"= \\\"HTTP/1.1 200 OK\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\" self.res_404 = \\\"HTTP/1.1 404 NOT FOUND\\\\r\\\\nServer: Myserver\",\n \"msg = server.res_close.encode() # conn.sendall(msg) break if __name__ == '__main__': input_port = int(sys.argv[1])\",\n \"def __init__(self, port, doc_root): self.port = port self.doc_root = doc_root self.host = '127.0.0.1'\",\n \"escape path = '' x = url.split('/') i = 0 while i <\",\n \"socket.SOCK_STREAM) as s: s.bind((server.host, server.port)) s.listen() while True: conn, addr = s.accept() t\",\n \"res += 'Content-Type: text/html\\\\r\\\\n\\\\r\\\\n' res = res + str(data, 'utf-8') else: # for\",\n \"'404escape': return self.res_404 # 400 malform req if path == \\\"400malform\\\": return self.res_400\",\n \"'url': url, 'version': version} for h in headers: h = h.split(': ') if\",\n \"res + str(data) return res def createsocket(conn, addr): with conn: try: conn.settimeout(5) except\",\n \"if i < 0 or x[0] == '..' or len(x) == 0: #\",\n \"404 not found if not os.path.isfile(path): return self.res_404 # a valid 200 req\",\n \"info = {'act': act, 'url': url, 'version': version} for h in headers: h\",\n \"= res + str(data) return res def createsocket(conn, addr): with conn: try: conn.settimeout(5)\",\n \"escape or absolute filename # judge whether escape path = '' x =\",\n \"value = h[1] info[field] = value # mapping url, return 404 escape or\",\n \"OK\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\" self.res_404 = \\\"HTTP/1.1 404 NOT FOUND\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_400 =\",\n \"= '' x = url.split('/') i = 0 while i < len(x): if\",\n \"len(x) and x[i] == '..': x.remove(x[i]) x.remove(x[i - 1]) i -= 1 else:\",\n \"1.0\\\\r\\\\n\\\" self.res_404 = \\\"HTTP/1.1 404 NOT FOUND\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_400 = \\\"HTTP/1.1 400\",\n \"\\\"HTTP/1.1 400 Client Error\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_close = \\\"HTTP/1.1 Connection:close\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" #\",\n \"if request[-4:] != '\\\\r\\\\n\\\\r\\\\n': info = {'url': '400malform'} return info headers = request.splitlines()\",\n \"url, return 404 escape or absolute filename # judge whether escape path =\",\n \"path == '404escape': return self.res_404 # 400 malform req if path == \\\"400malform\\\":\",\n \"= path + '/' + x[d] info['url'] = os.path.realpath(self.doc_root + path) return info\",\n \"doc_root self.host = '127.0.0.1' self.res_200 = \\\"HTTP/1.1 200 OK\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\" self.res_404 =\",\n \"png if path.split('.')[-1] == 'png': res += 'Content-Type: image/png\\\\r\\\\n\\\\r\\\\n' else: res += 'Content-Type:\",\n \"Myserver 1.0\\\\r\\\\n\\\" self.res_404 = \\\"HTTP/1.1 404 NOT FOUND\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_400 = \\\"HTTP/1.1\",\n \"info['url'] = '404escape' return info if i < len(x) and x[i] == '..':\",\n \"info # generate response def res_gen(self, reqinfo): path = reqinfo['url'] # 404 escape\",\n \"'png': res += 'Content-Type: image/png\\\\r\\\\n\\\\r\\\\n' else: res += 'Content-Type: image/jpeg\\\\r\\\\n\\\\r\\\\n' res = res\",\n \"image/jpeg\\\\r\\\\n\\\\r\\\\n' res = res + str(data) return res def createsocket(conn, addr): with conn:\",\n \"info = server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg) # print(\\\"msg send finished\\\") # msg\",\n \"= {'url': '400malform'} return info info = {'act': act, 'url': url, 'version': version}\",\n \"break if __name__ == '__main__': input_port = int(sys.argv[1]) input_doc_root = sys.argv[2] server =\",\n \"res = res + str(data, 'utf-8') else: # for jpg and png if\",\n \"path.split('.')[-1] == 'html': res += 'Content-Type: text/html\\\\r\\\\n\\\\r\\\\n' res = res + str(data, 'utf-8')\",\n \"conn.sendall(msg) # print(\\\"msg send finished\\\") # msg = server.res_close.encode() # conn.sendall(msg) break if\",\n \"Connection:close\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" # map request into dict def req_info(self, request): # 400\",\n \"# a valid 200 req else: res = self.res_200 res += \\\"Last-Modified: {}\\\\r\\\\n\\\".format(time.ctime(os.stat(path).st_mtime))\",\n \"# msg = server.res_close.encode() # conn.sendall(msg) break if __name__ == '__main__': input_port =\",\n \"return 404 escape or absolute filename # judge whether escape path = ''\",\n \"\\\"400malform\\\": return self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent'] except KeyError: return self.res_400 # 404\",\n \"a valid 200 req else: res = self.res_200 res += \\\"Last-Modified: {}\\\\r\\\\n\\\".format(time.ctime(os.stat(path).st_mtime)) with\",\n \"{}\\\\r\\\\n\\\".format(len(data)) if path.split('.')[-1] == 'html': res += 'Content-Type: text/html\\\\r\\\\n\\\\r\\\\n' res = res +\",\n \"escape from file root info['url'] = '404escape' return info if i < len(x)\",\n \"def res_gen(self, reqinfo): path = reqinfo['url'] # 404 escape if path == '404escape':\",\n \"str(data, 'utf-8') else: # for jpg and png if path.split('.')[-1] == 'png': res\",\n \"res += \\\"Content-Length: {}\\\\r\\\\n\\\".format(len(data)) if path.split('.')[-1] == 'html': res += 'Content-Type: text/html\\\\r\\\\n\\\\r\\\\n' res\",\n \"= self.res_200 res += \\\"Last-Modified: {}\\\\r\\\\n\\\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \\\"rb\\\") as f: data =\",\n \"len(x) == 0: # path escape from file root info['url'] = '404escape' return\",\n \"if __name__ == '__main__': input_port = int(sys.argv[1]) input_doc_root = sys.argv[2] server = MyServer(input_port,\",\n \"f: data = f.read() res += \\\"Content-Length: {}\\\\r\\\\n\\\".format(len(data)) if path.split('.')[-1] == 'html': res\",\n \"# 400 malform if request[-4:] != '\\\\r\\\\n\\\\r\\\\n': info = {'url': '400malform'} return info\",\n \"range(len(x)): path = path + '/' + x[d] info['url'] = os.path.realpath(self.doc_root + path)\",\n \"+= 1 # map index.html if len(x[-1].split('.')) < 2: x.append('index.html') for d in\",\n \"(act, url, version) = firstline.split() except ValueError: info = {'url': '400malform'} return info\",\n \"sys import os import socket import time import threading class MyServer: def __init__(self,\",\n \"try: (act, url, version) = firstline.split() except ValueError: info = {'url': '400malform'} return\",\n \"root info['url'] = '404escape' return info if i < len(x) and x[i] ==\",\n \"'..': x.remove(x[i]) x.remove(x[i - 1]) i -= 1 else: i += 1 #\",\n \"h[1] info[field] = value # mapping url, return 404 escape or absolute filename\",\n \"except socket.timeout: conn.close() # print('closed') # print('Connected by', addr) while True: req =\",\n \"= s.accept() t = threading.Thread(target=createsocket(conn, addr), args=(conn, addr)) t.start() threads.append(t) for t in\",\n \"if path.split('.')[-1] == 'png': res += 'Content-Type: image/png\\\\r\\\\n\\\\r\\\\n' else: res += 'Content-Type: image/jpeg\\\\r\\\\n\\\\r\\\\n'\",\n \"print('Connected by', addr) while True: req = conn.recv(1024).decode() if not req: break info\",\n \"conn, addr = s.accept() t = threading.Thread(target=createsocket(conn, addr), args=(conn, addr)) t.start() threads.append(t) for\",\n \"mapping url, return 404 escape or absolute filename # judge whether escape path\",\n \"< 0 or x[0] == '..' or len(x) == 0: # path escape\",\n \"return info info = {'act': act, 'url': url, 'version': version} for h in\",\n \"= {'url': '400malform'} return info headers = request.splitlines() firstline = headers.pop(0) try: (act,\",\n \"int(sys.argv[1]) input_doc_root = sys.argv[2] server = MyServer(input_port, input_doc_root) # Add code to start\",\n \"generate response def res_gen(self, reqinfo): path = reqinfo['url'] # 404 escape if path\",\n \"found if not os.path.isfile(path): return self.res_404 # a valid 200 req else: res\",\n \"while True: req = conn.recv(1024).decode() if not req: break info = server.req_info(req) msg\",\n \"1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_400 = \\\"HTTP/1.1 400 Client Error\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_close = \\\"HTTP/1.1 Connection:close\\\\r\\\\nServer:\",\n \"path = path + '/' + x[d] info['url'] = os.path.realpath(self.doc_root + path) return\",\n \"and png if path.split('.')[-1] == 'png': res += 'Content-Type: image/png\\\\r\\\\n\\\\r\\\\n' else: res +=\",\n \"socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host, server.port)) s.listen() while True: conn, addr = s.accept()\",\n \"i < 0 or x[0] == '..' or len(x) == 0: # path\",\n \"'' in x: x.remove('') if i < 0 or x[0] == '..' or\",\n \"= server.res_close.encode() # conn.sendall(msg) break if __name__ == '__main__': input_port = int(sys.argv[1]) input_doc_root\",\n \"input_port = int(sys.argv[1]) input_doc_root = sys.argv[2] server = MyServer(input_port, input_doc_root) # Add code\",\n \"= '127.0.0.1' self.res_200 = \\\"HTTP/1.1 200 OK\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\" self.res_404 = \\\"HTTP/1.1 404\",\n \"return self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent'] except KeyError: return self.res_400 # 404 not\",\n \"except ValueError: info = {'url': '400malform'} return info info = {'act': act, 'url':\",\n \"__name__ == '__main__': input_port = int(sys.argv[1]) input_doc_root = sys.argv[2] server = MyServer(input_port, input_doc_root)\",\n \"version) = firstline.split() except ValueError: info = {'url': '400malform'} return info info =\",\n \"not req: break info = server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg) # print(\\\"msg send\",\n \"try: reqinfo['Host'] and reqinfo['User-Agent'] except KeyError: return self.res_400 # 404 not found if\",\n \"= \\\"HTTP/1.1 Connection:close\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" # map request into dict def req_info(self, request):\",\n \"{'url': '400malform'} return info headers = request.splitlines() firstline = headers.pop(0) try: (act, url,\",\n \"code to start your server here threads = [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as\",\n \"= '404escape' return info if i < len(x) and x[i] == '..': x.remove(x[i])\",\n \"'\\\\r\\\\n\\\\r\\\\n': info = {'url': '400malform'} return info headers = request.splitlines() firstline = headers.pop(0)\",\n \"'__main__': input_port = int(sys.argv[1]) input_doc_root = sys.argv[2] server = MyServer(input_port, input_doc_root) # Add\",\n \"__init__(self, port, doc_root): self.port = port self.doc_root = doc_root self.host = '127.0.0.1' self.res_200\",\n \"server here threads = [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host, server.port)) s.listen()\",\n \"here threads = [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host, server.port)) s.listen() while\",\n \"self.doc_root = doc_root self.host = '127.0.0.1' self.res_200 = \\\"HTTP/1.1 200 OK\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\"\",\n \"+ str(data) return res def createsocket(conn, addr): with conn: try: conn.settimeout(5) except socket.timeout:\",\n \"conn.settimeout(5) except socket.timeout: conn.close() # print('closed') # print('Connected by', addr) while True: req\",\n \"headers.pop(0) try: (act, url, version) = firstline.split() except ValueError: info = {'url': '400malform'}\",\n \"= value # mapping url, return 404 escape or absolute filename # judge\",\n \"path == \\\"400malform\\\": return self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent'] except KeyError: return self.res_400\",\n \"self.res_404 # 400 malform req if path == \\\"400malform\\\": return self.res_400 try: reqinfo['Host']\",\n \"request.splitlines() firstline = headers.pop(0) try: (act, url, version) = firstline.split() except ValueError: info\",\n \"NOT FOUND\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_400 = \\\"HTTP/1.1 400 Client Error\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_close\",\n \"0 or x[0] == '..' or len(x) == 0: # path escape from\",\n \"and x[i] == '..': x.remove(x[i]) x.remove(x[i - 1]) i -= 1 else: i\",\n \"'Content-Type: text/html\\\\r\\\\n\\\\r\\\\n' res = res + str(data, 'utf-8') else: # for jpg and\",\n \"+ '/' + x[d] info['url'] = os.path.realpath(self.doc_root + path) return info # generate\",\n \"self.res_400 # 404 not found if not os.path.isfile(path): return self.res_404 # a valid\",\n \"url, 'version': version} for h in headers: h = h.split(': ') if len(h)\",\n \"dict def req_info(self, request): # 400 malform if request[-4:] != '\\\\r\\\\n\\\\r\\\\n': info =\",\n \"def createsocket(conn, addr): with conn: try: conn.settimeout(5) except socket.timeout: conn.close() # print('closed') #\",\n \"{}\\\\r\\\\n\\\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \\\"rb\\\") as f: data = f.read() res += \\\"Content-Length: {}\\\\r\\\\n\\\".format(len(data))\",\n \"# 400 malform req if path == \\\"400malform\\\": return self.res_400 try: reqinfo['Host'] and\",\n \"= res + str(data, 'utf-8') else: # for jpg and png if path.split('.')[-1]\",\n \"info if i < len(x) and x[i] == '..': x.remove(x[i]) x.remove(x[i - 1])\",\n \"while True: conn, addr = s.accept() t = threading.Thread(target=createsocket(conn, addr), args=(conn, addr)) t.start()\",\n \"if not req: break info = server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg) # print(\\\"msg\",\n \"else: res += 'Content-Type: image/jpeg\\\\r\\\\n\\\\r\\\\n' res = res + str(data) return res def\",\n \"res = self.res_200 res += \\\"Last-Modified: {}\\\\r\\\\n\\\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \\\"rb\\\") as f: data\",\n \"True: req = conn.recv(1024).decode() if not req: break info = server.req_info(req) msg =\",\n \"KeyError: return self.res_400 # 404 not found if not os.path.isfile(path): return self.res_404 #\",\n \"for jpg and png if path.split('.')[-1] == 'png': res += 'Content-Type: image/png\\\\r\\\\n\\\\r\\\\n' else:\",\n \"h in headers: h = h.split(': ') if len(h) < 2: continue field\",\n \"req: break info = server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg) # print(\\\"msg send finished\\\")\",\n \"reqinfo['User-Agent'] except KeyError: return self.res_400 # 404 not found if not os.path.isfile(path): return\",\n \"headers = request.splitlines() firstline = headers.pop(0) try: (act, url, version) = firstline.split() except\",\n \"else: res = self.res_200 res += \\\"Last-Modified: {}\\\\r\\\\n\\\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \\\"rb\\\") as f:\",\n \"data = f.read() res += \\\"Content-Length: {}\\\\r\\\\n\\\".format(len(data)) if path.split('.')[-1] == 'html': res +=\",\n \"= {'act': act, 'url': url, 'version': version} for h in headers: h =\",\n \"text/html\\\\r\\\\n\\\\r\\\\n' res = res + str(data, 'utf-8') else: # for jpg and png\",\n \"== 'png': res += 'Content-Type: image/png\\\\r\\\\n\\\\r\\\\n' else: res += 'Content-Type: image/jpeg\\\\r\\\\n\\\\r\\\\n' res =\",\n \"req if path == \\\"400malform\\\": return self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent'] except KeyError:\",\n \"= headers.pop(0) try: (act, url, version) = firstline.split() except ValueError: info = {'url':\",\n \"# path escape from file root info['url'] = '404escape' return info if i\",\n \"# print('closed') # print('Connected by', addr) while True: req = conn.recv(1024).decode() if not\",\n \"filename # judge whether escape path = '' x = url.split('/') i =\",\n \"+= \\\"Content-Length: {}\\\\r\\\\n\\\".format(len(data)) if path.split('.')[-1] == 'html': res += 'Content-Type: text/html\\\\r\\\\n\\\\r\\\\n' res =\",\n \"import socket import time import threading class MyServer: def __init__(self, port, doc_root): self.port\",\n \"print('closed') # print('Connected by', addr) while True: req = conn.recv(1024).decode() if not req:\",\n \"server.port)) s.listen() while True: conn, addr = s.accept() t = threading.Thread(target=createsocket(conn, addr), args=(conn,\",\n \"# judge whether escape path = '' x = url.split('/') i = 0\",\n \"continue field = h[0] value = h[1] info[field] = value # mapping url,\",\n \"if len(x[-1].split('.')) < 2: x.append('index.html') for d in range(len(x)): path = path +\",\n \"400 malform req if path == \\\"400malform\\\": return self.res_400 try: reqinfo['Host'] and reqinfo['User-Agent']\",\n \"# 404 escape if path == '404escape': return self.res_404 # 400 malform req\",\n \"\\\"rb\\\") as f: data = f.read() res += \\\"Content-Length: {}\\\\r\\\\n\\\".format(len(data)) if path.split('.')[-1] ==\",\n \"404 escape or absolute filename # judge whether escape path = '' x\",\n \"addr) while True: req = conn.recv(1024).decode() if not req: break info = server.req_info(req)\",\n \"req_info(self, request): # 400 malform if request[-4:] != '\\\\r\\\\n\\\\r\\\\n': info = {'url': '400malform'}\",\n \"return self.res_400 # 404 not found if not os.path.isfile(path): return self.res_404 # a\",\n \"info = {'url': '400malform'} return info info = {'act': act, 'url': url, 'version':\",\n \"= server.res_gen(info).encode() conn.sendall(msg) # print(\\\"msg send finished\\\") # msg = server.res_close.encode() # conn.sendall(msg)\",\n \"= [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host, server.port)) s.listen() while True: conn,\",\n \"path) return info # generate response def res_gen(self, reqinfo): path = reqinfo['url'] #\",\n \"Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_close = \\\"HTTP/1.1 Connection:close\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" # map request into dict\",\n \"d in range(len(x)): path = path + '/' + x[d] info['url'] = os.path.realpath(self.doc_root\",\n \"== 0: # path escape from file root info['url'] = '404escape' return info\",\n \"'400malform'} return info headers = request.splitlines() firstline = headers.pop(0) try: (act, url, version)\",\n \"< len(x): if '' in x: x.remove('') if i < 0 or x[0]\",\n \"while i < len(x): if '' in x: x.remove('') if i < 0\",\n \"= \\\"HTTP/1.1 404 NOT FOUND\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_400 = \\\"HTTP/1.1 400 Client Error\\\\r\\\\nServer:\",\n \"time import threading class MyServer: def __init__(self, port, doc_root): self.port = port self.doc_root\",\n \"MyServer: def __init__(self, port, doc_root): self.port = port self.doc_root = doc_root self.host =\",\n \"self.port = port self.doc_root = doc_root self.host = '127.0.0.1' self.res_200 = \\\"HTTP/1.1 200\",\n \"else: # for jpg and png if path.split('.')[-1] == 'png': res += 'Content-Type:\",\n \"MyServer(input_port, input_doc_root) # Add code to start your server here threads = []\",\n \"for d in range(len(x)): path = path + '/' + x[d] info['url'] =\",\n \"from file root info['url'] = '404escape' return info if i < len(x) and\",\n \"if '' in x: x.remove('') if i < 0 or x[0] == '..'\",\n \"path + '/' + x[d] info['url'] = os.path.realpath(self.doc_root + path) return info #\",\n \"port, doc_root): self.port = port self.doc_root = doc_root self.host = '127.0.0.1' self.res_200 =\",\n \"'utf-8') else: # for jpg and png if path.split('.')[-1] == 'png': res +=\",\n \"\\\"Content-Length: {}\\\\r\\\\n\\\".format(len(data)) if path.split('.')[-1] == 'html': res += 'Content-Type: text/html\\\\r\\\\n\\\\r\\\\n' res = res\",\n \"'/' + x[d] info['url'] = os.path.realpath(self.doc_root + path) return info # generate response\",\n \"request[-4:] != '\\\\r\\\\n\\\\r\\\\n': info = {'url': '400malform'} return info headers = request.splitlines() firstline\",\n \"try: conn.settimeout(5) except socket.timeout: conn.close() # print('closed') # print('Connected by', addr) while True:\",\n \"not found if not os.path.isfile(path): return self.res_404 # a valid 200 req else:\",\n \"# generate response def res_gen(self, reqinfo): path = reqinfo['url'] # 404 escape if\",\n \"x[i] == '..': x.remove(x[i]) x.remove(x[i - 1]) i -= 1 else: i +=\",\n \"finished\\\") # msg = server.res_close.encode() # conn.sendall(msg) break if __name__ == '__main__': input_port\",\n \"res += 'Content-Type: image/jpeg\\\\r\\\\n\\\\r\\\\n' res = res + str(data) return res def createsocket(conn,\",\n \"msg = server.res_gen(info).encode() conn.sendall(msg) # print(\\\"msg send finished\\\") # msg = server.res_close.encode() #\",\n \"whether escape path = '' x = url.split('/') i = 0 while i\",\n \"\\\"HTTP/1.1 200 OK\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\" self.res_404 = \\\"HTTP/1.1 404 NOT FOUND\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\"\",\n \"in headers: h = h.split(': ') if len(h) < 2: continue field =\",\n \"x.append('index.html') for d in range(len(x)): path = path + '/' + x[d] info['url']\",\n \"x.remove(x[i - 1]) i -= 1 else: i += 1 # map index.html\",\n \"return res def createsocket(conn, addr): with conn: try: conn.settimeout(5) except socket.timeout: conn.close() #\",\n \"input_doc_root = sys.argv[2] server = MyServer(input_port, input_doc_root) # Add code to start your\",\n \"server = MyServer(input_port, input_doc_root) # Add code to start your server here threads\",\n \"def req_info(self, request): # 400 malform if request[-4:] != '\\\\r\\\\n\\\\r\\\\n': info = {'url':\",\n \"map request into dict def req_info(self, request): # 400 malform if request[-4:] !=\",\n \"Add code to start your server here threads = [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM)\",\n \"os.path.isfile(path): return self.res_404 # a valid 200 req else: res = self.res_200 res\",\n \"h[0] value = h[1] info[field] = value # mapping url, return 404 escape\",\n \"server.res_close.encode() # conn.sendall(msg) break if __name__ == '__main__': input_port = int(sys.argv[1]) input_doc_root =\",\n \"-= 1 else: i += 1 # map index.html if len(x[-1].split('.')) < 2:\",\n \"not os.path.isfile(path): return self.res_404 # a valid 200 req else: res = self.res_200\",\n \"404 NOT FOUND\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_400 = \\\"HTTP/1.1 400 Client Error\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\"\",\n \"server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg) # print(\\\"msg send finished\\\") # msg = server.res_close.encode()\",\n \"sys.argv[2] server = MyServer(input_port, input_doc_root) # Add code to start your server here\",\n \"= f.read() res += \\\"Content-Length: {}\\\\r\\\\n\\\".format(len(data)) if path.split('.')[-1] == 'html': res += 'Content-Type:\",\n \"self.res_200 res += \\\"Last-Modified: {}\\\\r\\\\n\\\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \\\"rb\\\") as f: data = f.read()\",\n \"server.res_gen(info).encode() conn.sendall(msg) # print(\\\"msg send finished\\\") # msg = server.res_close.encode() # conn.sendall(msg) break\",\n \"and reqinfo['User-Agent'] except KeyError: return self.res_400 # 404 not found if not os.path.isfile(path):\",\n \"image/png\\\\r\\\\n\\\\r\\\\n' else: res += 'Content-Type: image/jpeg\\\\r\\\\n\\\\r\\\\n' res = res + str(data) return res\",\n \"firstline = headers.pop(0) try: (act, url, version) = firstline.split() except ValueError: info =\",\n \"i += 1 # map index.html if len(x[-1].split('.')) < 2: x.append('index.html') for d\",\n \"reqinfo): path = reqinfo['url'] # 404 escape if path == '404escape': return self.res_404\",\n \"= os.path.realpath(self.doc_root + path) return info # generate response def res_gen(self, reqinfo): path\",\n \"0 while i < len(x): if '' in x: x.remove('') if i <\",\n \"'..' or len(x) == 0: # path escape from file root info['url'] =\",\n \"= url.split('/') i = 0 while i < len(x): if '' in x:\",\n \"= h[1] info[field] = value # mapping url, return 404 escape or absolute\",\n \"'Content-Type: image/jpeg\\\\r\\\\n\\\\r\\\\n' res = res + str(data) return res def createsocket(conn, addr): with\",\n \"start your server here threads = [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host,\",\n \"judge whether escape path = '' x = url.split('/') i = 0 while\",\n \"with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host, server.port)) s.listen() while True: conn, addr =\",\n \"import time import threading class MyServer: def __init__(self, port, doc_root): self.port = port\",\n \"len(x[-1].split('.')) < 2: x.append('index.html') for d in range(len(x)): path = path + '/'\",\n \"import threading class MyServer: def __init__(self, port, doc_root): self.port = port self.doc_root =\",\n \"== 'html': res += 'Content-Type: text/html\\\\r\\\\n\\\\r\\\\n' res = res + str(data, 'utf-8') else:\",\n \"# map index.html if len(x[-1].split('.')) < 2: x.append('index.html') for d in range(len(x)): path\",\n \"200 OK\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\" self.res_404 = \\\"HTTP/1.1 404 NOT FOUND\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_400\",\n \"< len(x) and x[i] == '..': x.remove(x[i]) x.remove(x[i - 1]) i -= 1\",\n \"i < len(x) and x[i] == '..': x.remove(x[i]) x.remove(x[i - 1]) i -=\",\n \"path.split('.')[-1] == 'png': res += 'Content-Type: image/png\\\\r\\\\n\\\\r\\\\n' else: res += 'Content-Type: image/jpeg\\\\r\\\\n\\\\r\\\\n' res\",\n \"== '404escape': return self.res_404 # 400 malform req if path == \\\"400malform\\\": return\",\n \"req else: res = self.res_200 res += \\\"Last-Modified: {}\\\\r\\\\n\\\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \\\"rb\\\") as\",\n \"if i < len(x) and x[i] == '..': x.remove(x[i]) x.remove(x[i - 1]) i\",\n \"'html': res += 'Content-Type: text/html\\\\r\\\\n\\\\r\\\\n' res = res + str(data, 'utf-8') else: #\",\n \"firstline.split() except ValueError: info = {'url': '400malform'} return info info = {'act': act,\",\n \"for h in headers: h = h.split(': ') if len(h) < 2: continue\",\n \"self.host = '127.0.0.1' self.res_200 = \\\"HTTP/1.1 200 OK\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\" self.res_404 = \\\"HTTP/1.1\",\n \"info['url'] = os.path.realpath(self.doc_root + path) return info # generate response def res_gen(self, reqinfo):\",\n \"conn: try: conn.settimeout(5) except socket.timeout: conn.close() # print('closed') # print('Connected by', addr) while\",\n \"len(x): if '' in x: x.remove('') if i < 0 or x[0] ==\",\n \"class MyServer: def __init__(self, port, doc_root): self.port = port self.doc_root = doc_root self.host\",\n \"escape if path == '404escape': return self.res_404 # 400 malform req if path\",\n \"True: conn, addr = s.accept() t = threading.Thread(target=createsocket(conn, addr), args=(conn, addr)) t.start() threads.append(t)\",\n \"# for jpg and png if path.split('.')[-1] == 'png': res += 'Content-Type: image/png\\\\r\\\\n\\\\r\\\\n'\",\n \"[] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.bind((server.host, server.port)) s.listen() while True: conn, addr\",\n \"400 malform if request[-4:] != '\\\\r\\\\n\\\\r\\\\n': info = {'url': '400malform'} return info headers\",\n \"map index.html if len(x[-1].split('.')) < 2: x.append('index.html') for d in range(len(x)): path =\",\n \"+= 'Content-Type: image/jpeg\\\\r\\\\n\\\\r\\\\n' res = res + str(data) return res def createsocket(conn, addr):\",\n \"to start your server here threads = [] with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:\",\n \"1 # map index.html if len(x[-1].split('.')) < 2: x.append('index.html') for d in range(len(x)):\",\n \"# map request into dict def req_info(self, request): # 400 malform if request[-4:]\",\n \"'400malform'} return info info = {'act': act, 'url': url, 'version': version} for h\",\n \"s.listen() while True: conn, addr = s.accept() t = threading.Thread(target=createsocket(conn, addr), args=(conn, addr))\",\n \"info headers = request.splitlines() firstline = headers.pop(0) try: (act, url, version) = firstline.split()\",\n \"!= '\\\\r\\\\n\\\\r\\\\n': info = {'url': '400malform'} return info headers = request.splitlines() firstline =\",\n \"info info = {'act': act, 'url': url, 'version': version} for h in headers:\",\n \"< 2: x.append('index.html') for d in range(len(x)): path = path + '/' +\",\n \"== '..' or len(x) == 0: # path escape from file root info['url']\",\n \"conn.sendall(msg) break if __name__ == '__main__': input_port = int(sys.argv[1]) input_doc_root = sys.argv[2] server\",\n \"path = '' x = url.split('/') i = 0 while i < len(x):\",\n \"socket.timeout: conn.close() # print('closed') # print('Connected by', addr) while True: req = conn.recv(1024).decode()\",\n \"== '..': x.remove(x[i]) x.remove(x[i - 1]) i -= 1 else: i += 1\",\n \"jpg and png if path.split('.')[-1] == 'png': res += 'Content-Type: image/png\\\\r\\\\n\\\\r\\\\n' else: res\",\n \"res + str(data, 'utf-8') else: # for jpg and png if path.split('.')[-1] ==\",\n \"+= \\\"Last-Modified: {}\\\\r\\\\n\\\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \\\"rb\\\") as f: data = f.read() res +=\",\n \"req = conn.recv(1024).decode() if not req: break info = server.req_info(req) msg = server.res_gen(info).encode()\",\n \"1]) i -= 1 else: i += 1 # map index.html if len(x[-1].split('.'))\",\n \"except KeyError: return self.res_400 # 404 not found if not os.path.isfile(path): return self.res_404\",\n \"1 else: i += 1 # map index.html if len(x[-1].split('.')) < 2: x.append('index.html')\",\n \"response def res_gen(self, reqinfo): path = reqinfo['url'] # 404 escape if path ==\",\n \"404 escape if path == '404escape': return self.res_404 # 400 malform req if\",\n \"conn.close() # print('closed') # print('Connected by', addr) while True: req = conn.recv(1024).decode() if\",\n \"= h[0] value = h[1] info[field] = value # mapping url, return 404\",\n \"break info = server.req_info(req) msg = server.res_gen(info).encode() conn.sendall(msg) # print(\\\"msg send finished\\\") #\",\n \"x[d] info['url'] = os.path.realpath(self.doc_root + path) return info # generate response def res_gen(self,\",\n \"Error\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_close = \\\"HTTP/1.1 Connection:close\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" # map request into\",\n \"headers: h = h.split(': ') if len(h) < 2: continue field = h[0]\",\n \"absolute filename # judge whether escape path = '' x = url.split('/') i\",\n \"') if len(h) < 2: continue field = h[0] value = h[1] info[field]\",\n \"= h.split(': ') if len(h) < 2: continue field = h[0] value =\",\n \"or absolute filename # judge whether escape path = '' x = url.split('/')\",\n \"os import socket import time import threading class MyServer: def __init__(self, port, doc_root):\",\n \"self.res_200 = \\\"HTTP/1.1 200 OK\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\" self.res_404 = \\\"HTTP/1.1 404 NOT FOUND\\\\r\\\\nServer:\",\n \"= reqinfo['url'] # 404 escape if path == '404escape': return self.res_404 # 400\",\n \"1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_close = \\\"HTTP/1.1 Connection:close\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" # map request into dict def\",\n \"= \\\"HTTP/1.1 400 Client Error\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\" self.res_close = \\\"HTTP/1.1 Connection:close\\\\r\\\\nServer: Myserver 1.0\\\\r\\\\n\\\\r\\\\n\\\"\",\n \"if not os.path.isfile(path): return self.res_404 # a valid 200 req else: res =\",\n \"info[field] = value # mapping url, return 404 escape or absolute filename #\",\n \"== '__main__': input_port = int(sys.argv[1]) input_doc_root = sys.argv[2] server = MyServer(input_port, input_doc_root) #\"\n]","isConversational":false}}},{"rowIdx":4594,"cells":{"ngram":{"kind":"list like","value":["all metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \"\"\" def reset(self): pass def add(self): pass def value(self):","class Metric(object): \"\"\"Base class for all metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \"\"\" def reset(self): pass","<gh_stars>0 class Metric(object): \"\"\"Base class for all metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \"\"\" def reset(self):","for all metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \"\"\" def reset(self): pass def add(self): pass def","\"\"\"Base class for all metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \"\"\" def reset(self): pass def add(self):","Metric(object): \"\"\"Base class for all metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \"\"\" def reset(self): pass def","class for all metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \"\"\" def reset(self): pass def add(self): pass","metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \"\"\" def reset(self): pass def add(self): pass def value(self): pass"],"string":"[\n \"all metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \\\"\\\"\\\" def reset(self): pass def add(self): pass def value(self):\",\n \"class Metric(object): \\\"\\\"\\\"Base class for all metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \\\"\\\"\\\" def reset(self): pass\",\n \"<gh_stars>0 class Metric(object): \\\"\\\"\\\"Base class for all metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \\\"\\\"\\\" def reset(self):\",\n \"for all metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \\\"\\\"\\\" def reset(self): pass def add(self): pass def\",\n \"\\\"\\\"\\\"Base class for all metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \\\"\\\"\\\" def reset(self): pass def add(self):\",\n \"Metric(object): \\\"\\\"\\\"Base class for all metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \\\"\\\"\\\" def reset(self): pass def\",\n \"class for all metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \\\"\\\"\\\" def reset(self): pass def add(self): pass\",\n \"metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \\\"\\\"\\\" def reset(self): pass def add(self): pass def value(self): pass\"\n]","isConversational":false}}},{"rowIdx":4595,"cells":{"ngram":{"kind":"list like","value":["git import Repo from pf_pweb_sourceman.common.console import console from pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan:","class GitRepoMan: def get_repo_name_from_url(self, url: str): if not url: return None last_slash_index =","def clone_or_pull_project(self, path, url, branch): repo_name = self.get_repo_name_from_url(url) if not repo_name: raise Exception(\"Invalid","if last_suffix_index < 0: last_suffix_index = len(url) if last_slash_index < 0 or last_suffix_index","+ 1:last_suffix_index] def clone_or_pull_project(self, path, url, branch): repo_name = self.get_repo_name_from_url(url) if not repo_name:","url.rfind(\".git\") if last_suffix_index < 0: last_suffix_index = len(url) if last_slash_index < 0 or","self.get_repo_name_from_url(url) if not repo_name: raise Exception(\"Invalid repo\") if not PFPFFileUtil.is_exist(path): console.success(\"Cloning project: \"","last_suffix_index = len(url) if last_slash_index < 0 or last_suffix_index <= last_slash_index: raise Exception(\"Invalid","repo url {}\".format(url)) return url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self, path, url, branch): repo_name","or last_suffix_index <= last_slash_index: raise Exception(\"Invalid repo url {}\".format(url)) return url[last_slash_index + 1:last_suffix_index]","len(url) if last_slash_index < 0 or last_suffix_index <= last_slash_index: raise Exception(\"Invalid repo url","repo_name + \", Branch: \" + branch) Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name +","url: str): if not url: return None last_slash_index = url.rfind(\"/\") last_suffix_index = url.rfind(\".git\")","+ repo_name + \", Branch: \" + branch) Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name","import console from pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self, url: str): if","not repo_name: raise Exception(\"Invalid repo\") if not PFPFFileUtil.is_exist(path): console.success(\"Cloning project: \" + repo_name","url.rfind(\"/\") last_suffix_index = url.rfind(\".git\") if last_suffix_index < 0: last_suffix_index = len(url) if last_slash_index","console.success(repo_name + \" Taking pull...\") repo = Repo(path) repo.git.checkout(branch) origin = repo.remotes.origin origin.pull()","0: last_suffix_index = len(url) if last_slash_index < 0 or last_suffix_index <= last_slash_index: raise","raise Exception(\"Invalid repo\") if not PFPFFileUtil.is_exist(path): console.success(\"Cloning project: \" + repo_name + \",","repo_name = self.get_repo_name_from_url(url) if not repo_name: raise Exception(\"Invalid repo\") if not PFPFFileUtil.is_exist(path): console.success(\"Cloning","def get_repo_name_from_url(self, url: str): if not url: return None last_slash_index = url.rfind(\"/\") last_suffix_index","branch=branch, to_path=path) else: console.success(repo_name + \" Taking pull...\") repo = Repo(path) repo.git.checkout(branch) origin","= url.rfind(\".git\") if last_suffix_index < 0: last_suffix_index = len(url) if last_slash_index < 0","pf_pweb_sourceman.common.console import console from pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self, url: str):","\" + branch) Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name + \" Taking pull...\") repo","import Repo from pf_pweb_sourceman.common.console import console from pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan: def","import PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self, url: str): if not url: return None","not url: return None last_slash_index = url.rfind(\"/\") last_suffix_index = url.rfind(\".git\") if last_suffix_index <","+ branch) Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name + \" Taking pull...\") repo =","if not repo_name: raise Exception(\"Invalid repo\") if not PFPFFileUtil.is_exist(path): console.success(\"Cloning project: \" +","pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self, url: str): if not url: return","from pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self, url: str): if not url:","+ \", Branch: \" + branch) Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name + \"","console from pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self, url: str): if not","not PFPFFileUtil.is_exist(path): console.success(\"Cloning project: \" + repo_name + \", Branch: \" + branch)","branch): repo_name = self.get_repo_name_from_url(url) if not repo_name: raise Exception(\"Invalid repo\") if not PFPFFileUtil.is_exist(path):","from pf_pweb_sourceman.common.console import console from pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self, url:","raise Exception(\"Invalid repo url {}\".format(url)) return url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self, path, url,","\" + repo_name + \", Branch: \" + branch) Repo.clone_from(url, branch=branch, to_path=path) else:","url, branch): repo_name = self.get_repo_name_from_url(url) if not repo_name: raise Exception(\"Invalid repo\") if not","Exception(\"Invalid repo url {}\".format(url)) return url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self, path, url, branch):","Exception(\"Invalid repo\") if not PFPFFileUtil.is_exist(path): console.success(\"Cloning project: \" + repo_name + \", Branch:","1:last_suffix_index] def clone_or_pull_project(self, path, url, branch): repo_name = self.get_repo_name_from_url(url) if not repo_name: raise","if not PFPFFileUtil.is_exist(path): console.success(\"Cloning project: \" + repo_name + \", Branch: \" +","url: return None last_slash_index = url.rfind(\"/\") last_suffix_index = url.rfind(\".git\") if last_suffix_index < 0:","\", Branch: \" + branch) Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name + \" Taking","if not url: return None last_slash_index = url.rfind(\"/\") last_suffix_index = url.rfind(\".git\") if last_suffix_index","if last_slash_index < 0 or last_suffix_index <= last_slash_index: raise Exception(\"Invalid repo url {}\".format(url))","last_slash_index: raise Exception(\"Invalid repo url {}\".format(url)) return url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self, path,","url {}\".format(url)) return url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self, path, url, branch): repo_name =","repo\") if not PFPFFileUtil.is_exist(path): console.success(\"Cloning project: \" + repo_name + \", Branch: \"","repo_name: raise Exception(\"Invalid repo\") if not PFPFFileUtil.is_exist(path): console.success(\"Cloning project: \" + repo_name +","PFPFFileUtil.is_exist(path): console.success(\"Cloning project: \" + repo_name + \", Branch: \" + branch) Repo.clone_from(url,","from git import Repo from pf_pweb_sourceman.common.console import console from pf_py_file.pfpf_file_util import PFPFFileUtil class","< 0: last_suffix_index = len(url) if last_slash_index < 0 or last_suffix_index <= last_slash_index:","last_suffix_index < 0: last_suffix_index = len(url) if last_slash_index < 0 or last_suffix_index <=","<= last_slash_index: raise Exception(\"Invalid repo url {}\".format(url)) return url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self,","else: console.success(repo_name + \" Taking pull...\") repo = Repo(path) repo.git.checkout(branch) origin = repo.remotes.origin","get_repo_name_from_url(self, url: str): if not url: return None last_slash_index = url.rfind(\"/\") last_suffix_index =","PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self, url: str): if not url: return None last_slash_index","project: \" + repo_name + \", Branch: \" + branch) Repo.clone_from(url, branch=branch, to_path=path)","console.success(\"Cloning project: \" + repo_name + \", Branch: \" + branch) Repo.clone_from(url, branch=branch,","return None last_slash_index = url.rfind(\"/\") last_suffix_index = url.rfind(\".git\") if last_suffix_index < 0: last_suffix_index","= len(url) if last_slash_index < 0 or last_suffix_index <= last_slash_index: raise Exception(\"Invalid repo","clone_or_pull_project(self, path, url, branch): repo_name = self.get_repo_name_from_url(url) if not repo_name: raise Exception(\"Invalid repo\")","last_suffix_index <= last_slash_index: raise Exception(\"Invalid repo url {}\".format(url)) return url[last_slash_index + 1:last_suffix_index] def","path, url, branch): repo_name = self.get_repo_name_from_url(url) if not repo_name: raise Exception(\"Invalid repo\") if","GitRepoMan: def get_repo_name_from_url(self, url: str): if not url: return None last_slash_index = url.rfind(\"/\")","None last_slash_index = url.rfind(\"/\") last_suffix_index = url.rfind(\".git\") if last_suffix_index < 0: last_suffix_index =","= self.get_repo_name_from_url(url) if not repo_name: raise Exception(\"Invalid repo\") if not PFPFFileUtil.is_exist(path): console.success(\"Cloning project:","= url.rfind(\"/\") last_suffix_index = url.rfind(\".git\") if last_suffix_index < 0: last_suffix_index = len(url) if","str): if not url: return None last_slash_index = url.rfind(\"/\") last_suffix_index = url.rfind(\".git\") if","Branch: \" + branch) Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name + \" Taking pull...\")","{}\".format(url)) return url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self, path, url, branch): repo_name = self.get_repo_name_from_url(url)","return url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self, path, url, branch): repo_name = self.get_repo_name_from_url(url) if","last_slash_index = url.rfind(\"/\") last_suffix_index = url.rfind(\".git\") if last_suffix_index < 0: last_suffix_index = len(url)","branch) Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name + \" Taking pull...\") repo = Repo(path)","0 or last_suffix_index <= last_slash_index: raise Exception(\"Invalid repo url {}\".format(url)) return url[last_slash_index +","Repo from pf_pweb_sourceman.common.console import console from pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self,","url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self, path, url, branch): repo_name = self.get_repo_name_from_url(url) if not","Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name + \" Taking pull...\") repo = Repo(path) repo.git.checkout(branch)","to_path=path) else: console.success(repo_name + \" Taking pull...\") repo = Repo(path) repo.git.checkout(branch) origin =","< 0 or last_suffix_index <= last_slash_index: raise Exception(\"Invalid repo url {}\".format(url)) return url[last_slash_index","last_slash_index < 0 or last_suffix_index <= last_slash_index: raise Exception(\"Invalid repo url {}\".format(url)) return","last_suffix_index = url.rfind(\".git\") if last_suffix_index < 0: last_suffix_index = len(url) if last_slash_index <"],"string":"[\n \"git import Repo from pf_pweb_sourceman.common.console import console from pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan:\",\n \"class GitRepoMan: def get_repo_name_from_url(self, url: str): if not url: return None last_slash_index =\",\n \"def clone_or_pull_project(self, path, url, branch): repo_name = self.get_repo_name_from_url(url) if not repo_name: raise Exception(\\\"Invalid\",\n \"if last_suffix_index < 0: last_suffix_index = len(url) if last_slash_index < 0 or last_suffix_index\",\n \"+ 1:last_suffix_index] def clone_or_pull_project(self, path, url, branch): repo_name = self.get_repo_name_from_url(url) if not repo_name:\",\n \"url.rfind(\\\".git\\\") if last_suffix_index < 0: last_suffix_index = len(url) if last_slash_index < 0 or\",\n \"self.get_repo_name_from_url(url) if not repo_name: raise Exception(\\\"Invalid repo\\\") if not PFPFFileUtil.is_exist(path): console.success(\\\"Cloning project: \\\"\",\n \"last_suffix_index = len(url) if last_slash_index < 0 or last_suffix_index <= last_slash_index: raise Exception(\\\"Invalid\",\n \"repo url {}\\\".format(url)) return url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self, path, url, branch): repo_name\",\n \"or last_suffix_index <= last_slash_index: raise Exception(\\\"Invalid repo url {}\\\".format(url)) return url[last_slash_index + 1:last_suffix_index]\",\n \"len(url) if last_slash_index < 0 or last_suffix_index <= last_slash_index: raise Exception(\\\"Invalid repo url\",\n \"repo_name + \\\", Branch: \\\" + branch) Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name +\",\n \"url: str): if not url: return None last_slash_index = url.rfind(\\\"/\\\") last_suffix_index = url.rfind(\\\".git\\\")\",\n \"+ repo_name + \\\", Branch: \\\" + branch) Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name\",\n \"import console from pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self, url: str): if\",\n \"not repo_name: raise Exception(\\\"Invalid repo\\\") if not PFPFFileUtil.is_exist(path): console.success(\\\"Cloning project: \\\" + repo_name\",\n \"url.rfind(\\\"/\\\") last_suffix_index = url.rfind(\\\".git\\\") if last_suffix_index < 0: last_suffix_index = len(url) if last_slash_index\",\n \"console.success(repo_name + \\\" Taking pull...\\\") repo = Repo(path) repo.git.checkout(branch) origin = repo.remotes.origin origin.pull()\",\n \"0: last_suffix_index = len(url) if last_slash_index < 0 or last_suffix_index <= last_slash_index: raise\",\n \"raise Exception(\\\"Invalid repo\\\") if not PFPFFileUtil.is_exist(path): console.success(\\\"Cloning project: \\\" + repo_name + \\\",\",\n \"repo_name = self.get_repo_name_from_url(url) if not repo_name: raise Exception(\\\"Invalid repo\\\") if not PFPFFileUtil.is_exist(path): console.success(\\\"Cloning\",\n \"def get_repo_name_from_url(self, url: str): if not url: return None last_slash_index = url.rfind(\\\"/\\\") last_suffix_index\",\n \"branch=branch, to_path=path) else: console.success(repo_name + \\\" Taking pull...\\\") repo = Repo(path) repo.git.checkout(branch) origin\",\n \"= url.rfind(\\\".git\\\") if last_suffix_index < 0: last_suffix_index = len(url) if last_slash_index < 0\",\n \"pf_pweb_sourceman.common.console import console from pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self, url: str):\",\n \"\\\" + branch) Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name + \\\" Taking pull...\\\") repo\",\n \"import Repo from pf_pweb_sourceman.common.console import console from pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan: def\",\n \"import PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self, url: str): if not url: return None\",\n \"not url: return None last_slash_index = url.rfind(\\\"/\\\") last_suffix_index = url.rfind(\\\".git\\\") if last_suffix_index <\",\n \"+ branch) Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name + \\\" Taking pull...\\\") repo =\",\n \"if not repo_name: raise Exception(\\\"Invalid repo\\\") if not PFPFFileUtil.is_exist(path): console.success(\\\"Cloning project: \\\" +\",\n \"pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self, url: str): if not url: return\",\n \"from pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self, url: str): if not url:\",\n \"+ \\\", Branch: \\\" + branch) Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name + \\\"\",\n \"console from pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self, url: str): if not\",\n \"not PFPFFileUtil.is_exist(path): console.success(\\\"Cloning project: \\\" + repo_name + \\\", Branch: \\\" + branch)\",\n \"branch): repo_name = self.get_repo_name_from_url(url) if not repo_name: raise Exception(\\\"Invalid repo\\\") if not PFPFFileUtil.is_exist(path):\",\n \"from pf_pweb_sourceman.common.console import console from pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self, url:\",\n \"raise Exception(\\\"Invalid repo url {}\\\".format(url)) return url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self, path, url,\",\n \"\\\" + repo_name + \\\", Branch: \\\" + branch) Repo.clone_from(url, branch=branch, to_path=path) else:\",\n \"url, branch): repo_name = self.get_repo_name_from_url(url) if not repo_name: raise Exception(\\\"Invalid repo\\\") if not\",\n \"Exception(\\\"Invalid repo url {}\\\".format(url)) return url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self, path, url, branch):\",\n \"Exception(\\\"Invalid repo\\\") if not PFPFFileUtil.is_exist(path): console.success(\\\"Cloning project: \\\" + repo_name + \\\", Branch:\",\n \"1:last_suffix_index] def clone_or_pull_project(self, path, url, branch): repo_name = self.get_repo_name_from_url(url) if not repo_name: raise\",\n \"if not PFPFFileUtil.is_exist(path): console.success(\\\"Cloning project: \\\" + repo_name + \\\", Branch: \\\" +\",\n \"url: return None last_slash_index = url.rfind(\\\"/\\\") last_suffix_index = url.rfind(\\\".git\\\") if last_suffix_index < 0:\",\n \"\\\", Branch: \\\" + branch) Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name + \\\" Taking\",\n \"if not url: return None last_slash_index = url.rfind(\\\"/\\\") last_suffix_index = url.rfind(\\\".git\\\") if last_suffix_index\",\n \"if last_slash_index < 0 or last_suffix_index <= last_slash_index: raise Exception(\\\"Invalid repo url {}\\\".format(url))\",\n \"last_slash_index: raise Exception(\\\"Invalid repo url {}\\\".format(url)) return url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self, path,\",\n \"url {}\\\".format(url)) return url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self, path, url, branch): repo_name =\",\n \"repo\\\") if not PFPFFileUtil.is_exist(path): console.success(\\\"Cloning project: \\\" + repo_name + \\\", Branch: \\\"\",\n \"repo_name: raise Exception(\\\"Invalid repo\\\") if not PFPFFileUtil.is_exist(path): console.success(\\\"Cloning project: \\\" + repo_name +\",\n \"PFPFFileUtil.is_exist(path): console.success(\\\"Cloning project: \\\" + repo_name + \\\", Branch: \\\" + branch) Repo.clone_from(url,\",\n \"from git import Repo from pf_pweb_sourceman.common.console import console from pf_py_file.pfpf_file_util import PFPFFileUtil class\",\n \"< 0: last_suffix_index = len(url) if last_slash_index < 0 or last_suffix_index <= last_slash_index:\",\n \"last_suffix_index < 0: last_suffix_index = len(url) if last_slash_index < 0 or last_suffix_index <=\",\n \"<= last_slash_index: raise Exception(\\\"Invalid repo url {}\\\".format(url)) return url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self,\",\n \"else: console.success(repo_name + \\\" Taking pull...\\\") repo = Repo(path) repo.git.checkout(branch) origin = repo.remotes.origin\",\n \"get_repo_name_from_url(self, url: str): if not url: return None last_slash_index = url.rfind(\\\"/\\\") last_suffix_index =\",\n \"PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self, url: str): if not url: return None last_slash_index\",\n \"project: \\\" + repo_name + \\\", Branch: \\\" + branch) Repo.clone_from(url, branch=branch, to_path=path)\",\n \"console.success(\\\"Cloning project: \\\" + repo_name + \\\", Branch: \\\" + branch) Repo.clone_from(url, branch=branch,\",\n \"return None last_slash_index = url.rfind(\\\"/\\\") last_suffix_index = url.rfind(\\\".git\\\") if last_suffix_index < 0: last_suffix_index\",\n \"= len(url) if last_slash_index < 0 or last_suffix_index <= last_slash_index: raise Exception(\\\"Invalid repo\",\n \"clone_or_pull_project(self, path, url, branch): repo_name = self.get_repo_name_from_url(url) if not repo_name: raise Exception(\\\"Invalid repo\\\")\",\n \"last_suffix_index <= last_slash_index: raise Exception(\\\"Invalid repo url {}\\\".format(url)) return url[last_slash_index + 1:last_suffix_index] def\",\n \"path, url, branch): repo_name = self.get_repo_name_from_url(url) if not repo_name: raise Exception(\\\"Invalid repo\\\") if\",\n \"GitRepoMan: def get_repo_name_from_url(self, url: str): if not url: return None last_slash_index = url.rfind(\\\"/\\\")\",\n \"None last_slash_index = url.rfind(\\\"/\\\") last_suffix_index = url.rfind(\\\".git\\\") if last_suffix_index < 0: last_suffix_index =\",\n \"= self.get_repo_name_from_url(url) if not repo_name: raise Exception(\\\"Invalid repo\\\") if not PFPFFileUtil.is_exist(path): console.success(\\\"Cloning project:\",\n \"= url.rfind(\\\"/\\\") last_suffix_index = url.rfind(\\\".git\\\") if last_suffix_index < 0: last_suffix_index = len(url) if\",\n \"str): if not url: return None last_slash_index = url.rfind(\\\"/\\\") last_suffix_index = url.rfind(\\\".git\\\") if\",\n \"Branch: \\\" + branch) Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name + \\\" Taking pull...\\\")\",\n \"{}\\\".format(url)) return url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self, path, url, branch): repo_name = self.get_repo_name_from_url(url)\",\n \"return url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self, path, url, branch): repo_name = self.get_repo_name_from_url(url) if\",\n \"last_slash_index = url.rfind(\\\"/\\\") last_suffix_index = url.rfind(\\\".git\\\") if last_suffix_index < 0: last_suffix_index = len(url)\",\n \"branch) Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name + \\\" Taking pull...\\\") repo = Repo(path)\",\n \"0 or last_suffix_index <= last_slash_index: raise Exception(\\\"Invalid repo url {}\\\".format(url)) return url[last_slash_index +\",\n \"Repo from pf_pweb_sourceman.common.console import console from pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan: def get_repo_name_from_url(self,\",\n \"url[last_slash_index + 1:last_suffix_index] def clone_or_pull_project(self, path, url, branch): repo_name = self.get_repo_name_from_url(url) if not\",\n \"Repo.clone_from(url, branch=branch, to_path=path) else: console.success(repo_name + \\\" Taking pull...\\\") repo = Repo(path) repo.git.checkout(branch)\",\n \"to_path=path) else: console.success(repo_name + \\\" Taking pull...\\\") repo = Repo(path) repo.git.checkout(branch) origin =\",\n \"< 0 or last_suffix_index <= last_slash_index: raise Exception(\\\"Invalid repo url {}\\\".format(url)) return url[last_slash_index\",\n \"last_slash_index < 0 or last_suffix_index <= last_slash_index: raise Exception(\\\"Invalid repo url {}\\\".format(url)) return\",\n \"last_suffix_index = url.rfind(\\\".git\\\") if last_suffix_index < 0: last_suffix_index = len(url) if last_slash_index <\"\n]","isConversational":false}}},{"rowIdx":4596,"cells":{"ngram":{"kind":"list like","value":["= stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1 = { 'Hostname': '', 'IP': '', 'MAC':","= stdout_6.readlines() data_ = [] filter_ = [] remote_data_2 = { 'Hostname': [],","due to wrong username/password\".format(Hostname)) exit(1) except: print(\"Failed to connect to {} \".format(Hostname)) exit(2)","output_4[0][1:-1].strip('\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\n') return json.dumps(remote_data_1, indent=4) # ---------------------------------- def remote_data_2_(): output =","remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in filter_[i][9]: remote_data_2['Status'].append('Active') else: remote_data_2['Status'].append('Inactive') #","_, stdout_2, _ = ssh.exec_command(\"hostname -I | awk '{print $1}'\") _, stdout_3, _","to {} \".format(Hostname)) exit(2) # commands _, stdout_1, _ = ssh.exec_command(\"hostname\") _, stdout_2,","{ 'Hostname': '', 'IP': '', 'MAC': '', 'OS': '', 'Currentuser': '', } remote_data_1['Hostname']","output_3[0].strip('\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\n') return json.dumps(remote_data_1, indent=4) # ---------------------------------- def","i in output: data_.append(i.split(' ')) for i in data_: filter_.append(list(filter(None, i))) for i","to the Internet!\" is_connected() try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except","remote_data_1['Currentuser'] = output_5[0].strip('\\n') return json.dumps(remote_data_1, indent=4) # ---------------------------------- def remote_data_2_(): output = stdout_6.readlines()","'$1=={} {{ print $2 ;}}' /etc/os-release\".format('\"NAME\"')) _, stdout_5, _ = ssh.exec_command(\"whoami\") _, stdout_6,","'Currentuser': '', } remote_data_1['Hostname'] = output_1[0].strip('\\n') remote_data_1['IP'] = output_2[0].strip('\\n') remote_data_1['MAC'] = output_3[0].strip('\\n') remote_data_1['OS']","#_, stdout_8, _ = ssh.exec_command(\"sudo {}/24\".format()) # egrep -o '([0-9]{1,3}\\.){3}[0-9]{1,3}' --IP-address # ---------------------------------","Internet!\" is_connected() try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException: print(\"Failed","} remote_data_1['Hostname'] = output_1[0].strip('\\n') remote_data_1['IP'] = output_2[0].strip('\\n') remote_data_1['MAC'] = output_3[0].strip('\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\"')","\".format(Hostname)) exit(2) # commands _, stdout_1, _ = ssh.exec_command(\"hostname\") _, stdout_2, _ =","is actually # reachable socket.create_connection((\"8.8.8.8\", 53)) return \"conneted to the Internet!\" except OSError:","except OSError: pass return \"Please Connect to the Internet!\" is_connected() try: ssh =","egrep -o '([0-9]{1,3}\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def remote_data_1(): output_1 = stdout_1.readlines() output_2 =","-F\") _, stdout_7, _ = ssh.exec_command(\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\") #_, stdout_8, _","to {} due to wrong username/password\".format(Hostname)) exit(1) except: print(\"Failed to connect to {}","remote_data_1(): output_1 = stdout_1.readlines() output_2 = stdout_2.readlines() output_3 = stdout_3.readlines() output_4 = stdout_4.readlines()","output_1[0].strip('\\n') remote_data_1['IP'] = output_2[0].strip('\\n') remote_data_1['MAC'] = output_3[0].strip('\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\n')","remote_data_1['IP'] = output_2[0].strip('\\n') remote_data_1['MAC'] = output_3[0].strip('\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\n') return","for i in output: data_.append(i.split(' ')) for i in data_: filter_.append(list(filter(None, i))) for","data_.append(i.split(' ')) for i in data_: filter_.append(list(filter(None, i))) for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0])","/sys/class/net/eth0/address\") _, stdout_4, _ = ssh.exec_command( \"awk -F= '$1=={} {{ print $2 ;}}'","[] filter_ = [] remote_data_2 = { 'Hostname': [], 'IP': [], 'MAC': [],","# connect to the host -- tells us if the host is actually","remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in filter_[i][9]: remote_data_2['Status'].append('Active') else: remote_data_2['Status'].append('Inactive') # ssh.close()","try: # connect to the host -- tells us if the host is","\"Please Connect to the Internet!\" is_connected() try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username,","in output: data_.append(i.split(' ')) for i in data_: filter_.append(list(filter(None, i))) for i in","return \"conneted to the Internet!\" except OSError: pass return \"Please Connect to the","[], 'Lastseen': [], 'Status': [], } for i in output: data_.append(i.split(' ')) for","except paramiko.AuthenticationException: print(\"Failed to connect to {} due to wrong username/password\".format(Hostname)) exit(1) except:","commands _, stdout_1, _ = ssh.exec_command(\"hostname\") _, stdout_2, _ = ssh.exec_command(\"hostname -I |","= stdout_3.readlines() output_4 = stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1 = { 'Hostname': '',","stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1 = { 'Hostname': '', 'IP': '', 'MAC': '',","tells us if the host is actually # reachable socket.create_connection((\"8.8.8.8\", 53)) return \"conneted","53)) return \"conneted to the Internet!\" except OSError: pass return \"Please Connect to","key_filename=key) except paramiko.AuthenticationException: print(\"Failed to connect to {} due to wrong username/password\".format(Hostname)) exit(1)","i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in filter_[i][9]:","in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in filter_[i][9]: remote_data_2['Status'].append('Active')","filter_.append(list(filter(None, i))) for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if","'', 'IP': '', 'MAC': '', 'OS': '', 'Currentuser': '', } remote_data_1['Hostname'] = output_1[0].strip('\\n')","stdout_1, _ = ssh.exec_command(\"hostname\") _, stdout_2, _ = ssh.exec_command(\"hostname -I | awk '{print","stdout_7, _ = ssh.exec_command(\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\") #_, stdout_8, _ = ssh.exec_command(\"sudo","the host -- tells us if the host is actually # reachable socket.create_connection((\"8.8.8.8\",","---------------------------------- def remote_data_2_(): output = stdout_6.readlines() data_ = [] filter_ = [] remote_data_2","_, stdout_5, _ = ssh.exec_command(\"whoami\") _, stdout_6, _ = ssh.exec_command(\"last -F\") _, stdout_7,","remote_data_2_(): output = stdout_6.readlines() data_ = [] filter_ = [] remote_data_2 = {","paramiko import json Hostname = '172.16.17.32' Username = 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def","'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: # connect to the host -- tells us if","'ESTABLISHED.*sshd'\") #_, stdout_8, _ = ssh.exec_command(\"sudo {}/24\".format()) # egrep -o '([0-9]{1,3}\\.){3}[0-9]{1,3}' --IP-address #","[], 'IP': [], 'MAC': [], 'Lastseen': [], 'Status': [], } for i in","= ssh.exec_command(\"hostname\") _, stdout_2, _ = ssh.exec_command(\"hostname -I | awk '{print $1}'\") _,","Connect to the Internet!\" is_connected() try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key)","ssh.exec_command(\"hostname -I | awk '{print $1}'\") _, stdout_3, _ = ssh.exec_command(\"cat /sys/class/net/eth0/address\") _,","socket.create_connection((\"8.8.8.8\", 53)) return \"conneted to the Internet!\" except OSError: pass return \"Please Connect","'Lastseen': [], 'Status': [], } for i in output: data_.append(i.split(' ')) for i","stdout_2, _ = ssh.exec_command(\"hostname -I | awk '{print $1}'\") _, stdout_3, _ =","= ssh.exec_command(\"cat /sys/class/net/eth0/address\") _, stdout_4, _ = ssh.exec_command( \"awk -F= '$1=={} {{ print","# egrep -o '([0-9]{1,3}\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def remote_data_1(): output_1 = stdout_1.readlines() output_2","= { 'Hostname': '', 'IP': '', 'MAC': '', 'OS': '', 'Currentuser': '', }","to connect to {} \".format(Hostname)) exit(2) # commands _, stdout_1, _ = ssh.exec_command(\"hostname\")","output = stdout_6.readlines() data_ = [] filter_ = [] remote_data_2 = { 'Hostname':","to the Internet!\" except OSError: pass return \"Please Connect to the Internet!\" is_connected()","OSError: pass return \"Please Connect to the Internet!\" is_connected() try: ssh = paramiko.SSHClient()","= ssh.exec_command(\"last -F\") _, stdout_7, _ = ssh.exec_command(\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\") #_,","ssh.exec_command(\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\") #_, stdout_8, _ = ssh.exec_command(\"sudo {}/24\".format()) # egrep","= output_5[0].strip('\\n') return json.dumps(remote_data_1, indent=4) # ---------------------------------- def remote_data_2_(): output = stdout_6.readlines() data_","= stdout_2.readlines() output_3 = stdout_3.readlines() output_4 = stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1 =","data_ = [] filter_ = [] remote_data_2 = { 'Hostname': [], 'IP': [],","| awk '{print $1}'\") _, stdout_3, _ = ssh.exec_command(\"cat /sys/class/net/eth0/address\") _, stdout_4, _","stdout_6.readlines() data_ = [] filter_ = [] remote_data_2 = { 'Hostname': [], 'IP':","$2 ;}}' /etc/os-release\".format('\"NAME\"')) _, stdout_5, _ = ssh.exec_command(\"whoami\") _, stdout_6, _ = ssh.exec_command(\"last","ssh.exec_command(\"hostname\") _, stdout_2, _ = ssh.exec_command(\"hostname -I | awk '{print $1}'\") _, stdout_3,","-o '([0-9]{1,3}\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def remote_data_1(): output_1 = stdout_1.readlines() output_2 = stdout_2.readlines()","'', } remote_data_1['Hostname'] = output_1[0].strip('\\n') remote_data_1['IP'] = output_2[0].strip('\\n') remote_data_1['MAC'] = output_3[0].strip('\\n') remote_data_1['OS'] =","= stdout_5.readlines() remote_data_1 = { 'Hostname': '', 'IP': '', 'MAC': '', 'OS': '',","= output_4[0][1:-1].strip('\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\n') return json.dumps(remote_data_1, indent=4) # ---------------------------------- def remote_data_2_(): output","import socket import paramiko import json Hostname = '172.16.17.32' Username = 'ec2-user' key","$1}'\") _, stdout_3, _ = ssh.exec_command(\"cat /sys/class/net/eth0/address\") _, stdout_4, _ = ssh.exec_command( \"awk","-I | awk '{print $1}'\") _, stdout_3, _ = ssh.exec_command(\"cat /sys/class/net/eth0/address\") _, stdout_4,","i))) for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged'","<filename>tool/remote_info.py import socket import paramiko import json Hostname = '172.16.17.32' Username = 'ec2-user'","'', 'OS': '', 'Currentuser': '', } remote_data_1['Hostname'] = output_1[0].strip('\\n') remote_data_1['IP'] = output_2[0].strip('\\n') remote_data_1['MAC']","'OS': '', 'Currentuser': '', } remote_data_1['Hostname'] = output_1[0].strip('\\n') remote_data_1['IP'] = output_2[0].strip('\\n') remote_data_1['MAC'] =","Username = 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: # connect to the","remote_data_1 = { 'Hostname': '', 'IP': '', 'MAC': '', 'OS': '', 'Currentuser': '',","= ssh.exec_command(\"hostname -I | awk '{print $1}'\") _, stdout_3, _ = ssh.exec_command(\"cat /sys/class/net/eth0/address\")","'([0-9]{1,3}\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def remote_data_1(): output_1 = stdout_1.readlines() output_2 = stdout_2.readlines() output_3","_ = ssh.exec_command(\"cat /sys/class/net/eth0/address\") _, stdout_4, _ = ssh.exec_command( \"awk -F= '$1=={} {{","= output_1[0].strip('\\n') remote_data_1['IP'] = output_2[0].strip('\\n') remote_data_1['MAC'] = output_3[0].strip('\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\"') remote_data_1['Currentuser'] =","= ssh.exec_command(\"whoami\") _, stdout_6, _ = ssh.exec_command(\"last -F\") _, stdout_7, _ = ssh.exec_command(\"netstat","grep 'ESTABLISHED.*sshd'\") #_, stdout_8, _ = ssh.exec_command(\"sudo {}/24\".format()) # egrep -o '([0-9]{1,3}\\.){3}[0-9]{1,3}' --IP-address","_ = ssh.exec_command(\"last -F\") _, stdout_7, _ = ssh.exec_command(\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\")","output_2 = stdout_2.readlines() output_3 = stdout_3.readlines() output_4 = stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1","ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException: print(\"Failed to connect to {} due to wrong","ssh.exec_command(\"cat /sys/class/net/eth0/address\") _, stdout_4, _ = ssh.exec_command( \"awk -F= '$1=={} {{ print $2","to connect to {} due to wrong username/password\".format(Hostname)) exit(1) except: print(\"Failed to connect","= output_2[0].strip('\\n') remote_data_1['MAC'] = output_3[0].strip('\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\n') return json.dumps(remote_data_1,","'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: # connect to the host --","host -- tells us if the host is actually # reachable socket.create_connection((\"8.8.8.8\", 53))","_ = ssh.exec_command(\"hostname -I | awk '{print $1}'\") _, stdout_3, _ = ssh.exec_command(\"cat","'Hostname': '', 'IP': '', 'MAC': '', 'OS': '', 'Currentuser': '', } remote_data_1['Hostname'] =","ssh.exec_command(\"last -F\") _, stdout_7, _ = ssh.exec_command(\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\") #_, stdout_8,","stdout_6, _ = ssh.exec_command(\"last -F\") _, stdout_7, _ = ssh.exec_command(\"netstat -tnpa | grep","} for i in output: data_.append(i.split(' ')) for i in data_: filter_.append(list(filter(None, i)))","Internet!\" except OSError: pass return \"Please Connect to the Internet!\" is_connected() try: ssh","pass return \"Please Connect to the Internet!\" is_connected() try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy())","actually # reachable socket.create_connection((\"8.8.8.8\", 53)) return \"conneted to the Internet!\" except OSError: pass","# --------------------------------- def remote_data_1(): output_1 = stdout_1.readlines() output_2 = stdout_2.readlines() output_3 = stdout_3.readlines()","print(\"Failed to connect to {} due to wrong username/password\".format(Hostname)) exit(1) except: print(\"Failed to","= [] remote_data_2 = { 'Hostname': [], 'IP': [], 'MAC': [], 'Lastseen': [],","connect to {} due to wrong username/password\".format(Hostname)) exit(1) except: print(\"Failed to connect to","_, stdout_1, _ = ssh.exec_command(\"hostname\") _, stdout_2, _ = ssh.exec_command(\"hostname -I | awk","stdout_4, _ = ssh.exec_command( \"awk -F= '$1=={} {{ print $2 ;}}' /etc/os-release\".format('\"NAME\"')) _,","ssh.exec_command( \"awk -F= '$1=={} {{ print $2 ;}}' /etc/os-release\".format('\"NAME\"')) _, stdout_5, _ =","output_2[0].strip('\\n') remote_data_1['MAC'] = output_3[0].strip('\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\n') return json.dumps(remote_data_1, indent=4)","--------------------------------- def remote_data_1(): output_1 = stdout_1.readlines() output_2 = stdout_2.readlines() output_3 = stdout_3.readlines() output_4","return \"Please Connect to the Internet!\" is_connected() try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname,","{{ print $2 ;}}' /etc/os-release\".format('\"NAME\"')) _, stdout_5, _ = ssh.exec_command(\"whoami\") _, stdout_6, _","key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: # connect to the host -- tells","= ssh.exec_command( \"awk -F= '$1=={} {{ print $2 ;}}' /etc/os-release\".format('\"NAME\"')) _, stdout_5, _","/etc/os-release\".format('\"NAME\"')) _, stdout_5, _ = ssh.exec_command(\"whoami\") _, stdout_6, _ = ssh.exec_command(\"last -F\") _,","-F= '$1=={} {{ print $2 ;}}' /etc/os-release\".format('\"NAME\"')) _, stdout_5, _ = ssh.exec_command(\"whoami\") _,","stdout_5, _ = ssh.exec_command(\"whoami\") _, stdout_6, _ = ssh.exec_command(\"last -F\") _, stdout_7, _","is_connected(): try: # connect to the host -- tells us if the host","{} due to wrong username/password\".format(Hostname)) exit(1) except: print(\"Failed to connect to {} \".format(Hostname))",";}}' /etc/os-release\".format('\"NAME\"')) _, stdout_5, _ = ssh.exec_command(\"whoami\") _, stdout_6, _ = ssh.exec_command(\"last -F\")","def is_connected(): try: # connect to the host -- tells us if the","= ssh.exec_command(\"sudo {}/24\".format()) # egrep -o '([0-9]{1,3}\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def remote_data_1(): output_1","stdout_2.readlines() output_3 = stdout_3.readlines() output_4 = stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1 = {","'', 'Currentuser': '', } remote_data_1['Hostname'] = output_1[0].strip('\\n') remote_data_1['IP'] = output_2[0].strip('\\n') remote_data_1['MAC'] = output_3[0].strip('\\n')","import json Hostname = '172.16.17.32' Username = 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected():","output_1 = stdout_1.readlines() output_2 = stdout_2.readlines() output_3 = stdout_3.readlines() output_4 = stdout_4.readlines() output_5","i in data_: filter_.append(list(filter(None, i))) for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found')","connect to {} \".format(Hostname)) exit(2) # commands _, stdout_1, _ = ssh.exec_command(\"hostname\") _,","remote_data_1['MAC'] = output_3[0].strip('\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\n') return json.dumps(remote_data_1, indent=4) #","stdout_5.readlines() remote_data_1 = { 'Hostname': '', 'IP': '', 'MAC': '', 'OS': '', 'Currentuser':","us if the host is actually # reachable socket.create_connection((\"8.8.8.8\", 53)) return \"conneted to","# reachable socket.create_connection((\"8.8.8.8\", 53)) return \"conneted to the Internet!\" except OSError: pass return","= [] filter_ = [] remote_data_2 = { 'Hostname': [], 'IP': [], 'MAC':","remote_data_1['Hostname'] = output_1[0].strip('\\n') remote_data_1['IP'] = output_2[0].strip('\\n') remote_data_1['MAC'] = output_3[0].strip('\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\"') remote_data_1['Currentuser']","# commands _, stdout_1, _ = ssh.exec_command(\"hostname\") _, stdout_2, _ = ssh.exec_command(\"hostname -I","stdout_3, _ = ssh.exec_command(\"cat /sys/class/net/eth0/address\") _, stdout_4, _ = ssh.exec_command( \"awk -F= '$1=={}","json.dumps(remote_data_1, indent=4) # ---------------------------------- def remote_data_2_(): output = stdout_6.readlines() data_ = [] filter_","username=Username, key_filename=key) except paramiko.AuthenticationException: print(\"Failed to connect to {} due to wrong username/password\".format(Hostname))","exit(1) except: print(\"Failed to connect to {} \".format(Hostname)) exit(2) # commands _, stdout_1,","output_5 = stdout_5.readlines() remote_data_1 = { 'Hostname': '', 'IP': '', 'MAC': '', 'OS':","Hostname = '172.16.17.32' Username = 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: #","\"conneted to the Internet!\" except OSError: pass return \"Please Connect to the Internet!\"","= ssh.exec_command(\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\") #_, stdout_8, _ = ssh.exec_command(\"sudo {}/24\".format()) #","\"awk -F= '$1=={} {{ print $2 ;}}' /etc/os-release\".format('\"NAME\"')) _, stdout_5, _ = ssh.exec_command(\"whoami\")","-tnpa | grep 'ESTABLISHED.*sshd'\") #_, stdout_8, _ = ssh.exec_command(\"sudo {}/24\".format()) # egrep -o","output_3 = stdout_3.readlines() output_4 = stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1 = { 'Hostname':","json Hostname = '172.16.17.32' Username = 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try:","ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException: print(\"Failed to connect to","remote_data_1['OS'] = output_4[0][1:-1].strip('\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\n') return json.dumps(remote_data_1, indent=4) # ---------------------------------- def remote_data_2_():","--IP-address # --------------------------------- def remote_data_1(): output_1 = stdout_1.readlines() output_2 = stdout_2.readlines() output_3 =","return json.dumps(remote_data_1, indent=4) # ---------------------------------- def remote_data_2_(): output = stdout_6.readlines() data_ = []","{ 'Hostname': [], 'IP': [], 'MAC': [], 'Lastseen': [], 'Status': [], } for","_ = ssh.exec_command(\"sudo {}/24\".format()) # egrep -o '([0-9]{1,3}\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def remote_data_1():","= '172.16.17.32' Username = 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: # connect","'MAC': '', 'OS': '', 'Currentuser': '', } remote_data_1['Hostname'] = output_1[0].strip('\\n') remote_data_1['IP'] = output_2[0].strip('\\n')","paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException: print(\"Failed to connect to {} due","'', 'MAC': '', 'OS': '', 'Currentuser': '', } remote_data_1['Hostname'] = output_1[0].strip('\\n') remote_data_1['IP'] =","ssh.exec_command(\"whoami\") _, stdout_6, _ = ssh.exec_command(\"last -F\") _, stdout_7, _ = ssh.exec_command(\"netstat -tnpa","'Hostname': [], 'IP': [], 'MAC': [], 'Lastseen': [], 'Status': [], } for i","'MAC': [], 'Lastseen': [], 'Status': [], } for i in output: data_.append(i.split(' '))","'IP': '', 'MAC': '', 'OS': '', 'Currentuser': '', } remote_data_1['Hostname'] = output_1[0].strip('\\n') remote_data_1['IP']","_ = ssh.exec_command(\"hostname\") _, stdout_2, _ = ssh.exec_command(\"hostname -I | awk '{print $1}'\")","_ = ssh.exec_command(\"whoami\") _, stdout_6, _ = ssh.exec_command(\"last -F\") _, stdout_7, _ =","reachable socket.create_connection((\"8.8.8.8\", 53)) return \"conneted to the Internet!\" except OSError: pass return \"Please","output: data_.append(i.split(' ')) for i in data_: filter_.append(list(filter(None, i))) for i in range(len(filter_)-3):","host is actually # reachable socket.create_connection((\"8.8.8.8\", 53)) return \"conneted to the Internet!\" except","'IP': [], 'MAC': [], 'Lastseen': [], 'Status': [], } for i in output:","range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in filter_[i][9]: remote_data_2['Status'].append('Active') else:","# ---------------------------------- def remote_data_2_(): output = stdout_6.readlines() data_ = [] filter_ = []","exit(2) # commands _, stdout_1, _ = ssh.exec_command(\"hostname\") _, stdout_2, _ = ssh.exec_command(\"hostname","the Internet!\" except OSError: pass return \"Please Connect to the Internet!\" is_connected() try:","'Status': [], } for i in output: data_.append(i.split(' ')) for i in data_:","[], 'Status': [], } for i in output: data_.append(i.split(' ')) for i in","remote_data_2 = { 'Hostname': [], 'IP': [], 'MAC': [], 'Lastseen': [], 'Status': [],","[], } for i in output: data_.append(i.split(' ')) for i in data_: filter_.append(list(filter(None,","ssh.exec_command(\"sudo {}/24\".format()) # egrep -o '([0-9]{1,3}\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def remote_data_1(): output_1 =","{} \".format(Hostname)) exit(2) # commands _, stdout_1, _ = ssh.exec_command(\"hostname\") _, stdout_2, _","connect to the host -- tells us if the host is actually #","to the host -- tells us if the host is actually # reachable","the Internet!\" is_connected() try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException:","found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in filter_[i][9]: remote_data_2['Status'].append('Active') else: remote_data_2['Status'].append('Inactive') # ssh.close() return","socket import paramiko import json Hostname = '172.16.17.32' Username = 'ec2-user' key =","def remote_data_1(): output_1 = stdout_1.readlines() output_2 = stdout_2.readlines() output_3 = stdout_3.readlines() output_4 =","try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException: print(\"Failed to connect","to wrong username/password\".format(Hostname)) exit(1) except: print(\"Failed to connect to {} \".format(Hostname)) exit(2) #","= output_3[0].strip('\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\n') return json.dumps(remote_data_1, indent=4) # ----------------------------------","data_: filter_.append(list(filter(None, i))) for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8]))","for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in","ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException: print(\"Failed to connect to {} due to","stdout_3.readlines() output_4 = stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1 = { 'Hostname': '', 'IP':","stdout_1.readlines() output_2 = stdout_2.readlines() output_3 = stdout_3.readlines() output_4 = stdout_4.readlines() output_5 = stdout_5.readlines()","paramiko.AuthenticationException: print(\"Failed to connect to {} due to wrong username/password\".format(Hostname)) exit(1) except: print(\"Failed","-- tells us if the host is actually # reachable socket.create_connection((\"8.8.8.8\", 53)) return","output_5[0].strip('\\n') return json.dumps(remote_data_1, indent=4) # ---------------------------------- def remote_data_2_(): output = stdout_6.readlines() data_ =","[], 'MAC': [], 'Lastseen': [], 'Status': [], } for i in output: data_.append(i.split('","remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in filter_[i][9]: remote_data_2['Status'].append('Active') else: remote_data_2['Status'].append('Inactive') # ssh.close() return remote_data_2","the host is actually # reachable socket.create_connection((\"8.8.8.8\", 53)) return \"conneted to the Internet!\"","indent=4) # ---------------------------------- def remote_data_2_(): output = stdout_6.readlines() data_ = [] filter_ =","_, stdout_7, _ = ssh.exec_command(\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\") #_, stdout_8, _ =","'172.16.17.32' Username = 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: # connect to","remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in filter_[i][9]: remote_data_2['Status'].append('Active') else: remote_data_2['Status'].append('Inactive')","filter_ = [] remote_data_2 = { 'Hostname': [], 'IP': [], 'MAC': [], 'Lastseen':","_, stdout_3, _ = ssh.exec_command(\"cat /sys/class/net/eth0/address\") _, stdout_4, _ = ssh.exec_command( \"awk -F=","{}/24\".format()) # egrep -o '([0-9]{1,3}\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def remote_data_1(): output_1 = stdout_1.readlines()","= 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: # connect to the host -- tells us","_ = ssh.exec_command(\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\") #_, stdout_8, _ = ssh.exec_command(\"sudo {}/24\".format())","in data_: filter_.append(list(filter(None, i))) for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append('","for i in data_: filter_.append(list(filter(None, i))) for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not","stdout_8, _ = ssh.exec_command(\"sudo {}/24\".format()) # egrep -o '([0-9]{1,3}\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def","output_4 = stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1 = { 'Hostname': '', 'IP': '',","[] remote_data_2 = { 'Hostname': [], 'IP': [], 'MAC': [], 'Lastseen': [], 'Status':","')) for i in data_: filter_.append(list(filter(None, i))) for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2])","import paramiko import json Hostname = '172.16.17.32' Username = 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem'","print(\"Failed to connect to {} \".format(Hostname)) exit(2) # commands _, stdout_1, _ =","username/password\".format(Hostname)) exit(1) except: print(\"Failed to connect to {} \".format(Hostname)) exit(2) # commands _,","| grep 'ESTABLISHED.*sshd'\") #_, stdout_8, _ = ssh.exec_command(\"sudo {}/24\".format()) # egrep -o '([0-9]{1,3}\\.){3}[0-9]{1,3}'","_, stdout_6, _ = ssh.exec_command(\"last -F\") _, stdout_7, _ = ssh.exec_command(\"netstat -tnpa |","is_connected() try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException: print(\"Failed to","wrong username/password\".format(Hostname)) exit(1) except: print(\"Failed to connect to {} \".format(Hostname)) exit(2) # commands","= stdout_1.readlines() output_2 = stdout_2.readlines() output_3 = stdout_3.readlines() output_4 = stdout_4.readlines() output_5 =","except: print(\"Failed to connect to {} \".format(Hostname)) exit(2) # commands _, stdout_1, _","= 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: # connect to the host","if the host is actually # reachable socket.create_connection((\"8.8.8.8\", 53)) return \"conneted to the","'{print $1}'\") _, stdout_3, _ = ssh.exec_command(\"cat /sys/class/net/eth0/address\") _, stdout_4, _ = ssh.exec_command(","= paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException: print(\"Failed to connect to {}","_, stdout_4, _ = ssh.exec_command( \"awk -F= '$1=={} {{ print $2 ;}}' /etc/os-release\".format('\"NAME\"'))","= { 'Hostname': [], 'IP': [], 'MAC': [], 'Lastseen': [], 'Status': [], }","def remote_data_2_(): output = stdout_6.readlines() data_ = [] filter_ = [] remote_data_2 =","awk '{print $1}'\") _, stdout_3, _ = ssh.exec_command(\"cat /sys/class/net/eth0/address\") _, stdout_4, _ =","_ = ssh.exec_command( \"awk -F= '$1=={} {{ print $2 ;}}' /etc/os-release\".format('\"NAME\"')) _, stdout_5,","print $2 ;}}' /etc/os-release\".format('\"NAME\"')) _, stdout_5, _ = ssh.exec_command(\"whoami\") _, stdout_6, _ ="],"string":"[\n \"= stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1 = { 'Hostname': '', 'IP': '', 'MAC':\",\n \"= stdout_6.readlines() data_ = [] filter_ = [] remote_data_2 = { 'Hostname': [],\",\n \"due to wrong username/password\\\".format(Hostname)) exit(1) except: print(\\\"Failed to connect to {} \\\".format(Hostname)) exit(2)\",\n \"output_4[0][1:-1].strip('\\\\\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\\\n') return json.dumps(remote_data_1, indent=4) # ---------------------------------- def remote_data_2_(): output =\",\n \"remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in filter_[i][9]: remote_data_2['Status'].append('Active') else: remote_data_2['Status'].append('Inactive') #\",\n \"_, stdout_2, _ = ssh.exec_command(\\\"hostname -I | awk '{print $1}'\\\") _, stdout_3, _\",\n \"to {} \\\".format(Hostname)) exit(2) # commands _, stdout_1, _ = ssh.exec_command(\\\"hostname\\\") _, stdout_2,\",\n \"{ 'Hostname': '', 'IP': '', 'MAC': '', 'OS': '', 'Currentuser': '', } remote_data_1['Hostname']\",\n \"output_3[0].strip('\\\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\\\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\\\n') return json.dumps(remote_data_1, indent=4) # ---------------------------------- def\",\n \"i in output: data_.append(i.split(' ')) for i in data_: filter_.append(list(filter(None, i))) for i\",\n \"to the Internet!\\\" is_connected() try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except\",\n \"remote_data_1['Currentuser'] = output_5[0].strip('\\\\n') return json.dumps(remote_data_1, indent=4) # ---------------------------------- def remote_data_2_(): output = stdout_6.readlines()\",\n \"'$1=={} {{ print $2 ;}}' /etc/os-release\\\".format('\\\"NAME\\\"')) _, stdout_5, _ = ssh.exec_command(\\\"whoami\\\") _, stdout_6,\",\n \"'Currentuser': '', } remote_data_1['Hostname'] = output_1[0].strip('\\\\n') remote_data_1['IP'] = output_2[0].strip('\\\\n') remote_data_1['MAC'] = output_3[0].strip('\\\\n') remote_data_1['OS']\",\n \"#_, stdout_8, _ = ssh.exec_command(\\\"sudo {}/24\\\".format()) # egrep -o '([0-9]{1,3}\\\\.){3}[0-9]{1,3}' --IP-address # ---------------------------------\",\n \"Internet!\\\" is_connected() try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException: print(\\\"Failed\",\n \"} remote_data_1['Hostname'] = output_1[0].strip('\\\\n') remote_data_1['IP'] = output_2[0].strip('\\\\n') remote_data_1['MAC'] = output_3[0].strip('\\\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\\\\\"')\",\n \"\\\".format(Hostname)) exit(2) # commands _, stdout_1, _ = ssh.exec_command(\\\"hostname\\\") _, stdout_2, _ =\",\n \"is actually # reachable socket.create_connection((\\\"8.8.8.8\\\", 53)) return \\\"conneted to the Internet!\\\" except OSError:\",\n \"except OSError: pass return \\\"Please Connect to the Internet!\\\" is_connected() try: ssh =\",\n \"egrep -o '([0-9]{1,3}\\\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def remote_data_1(): output_1 = stdout_1.readlines() output_2 =\",\n \"-F\\\") _, stdout_7, _ = ssh.exec_command(\\\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\\\") #_, stdout_8, _\",\n \"to {} due to wrong username/password\\\".format(Hostname)) exit(1) except: print(\\\"Failed to connect to {}\",\n \"remote_data_1(): output_1 = stdout_1.readlines() output_2 = stdout_2.readlines() output_3 = stdout_3.readlines() output_4 = stdout_4.readlines()\",\n \"output_1[0].strip('\\\\n') remote_data_1['IP'] = output_2[0].strip('\\\\n') remote_data_1['MAC'] = output_3[0].strip('\\\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\\\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\\\n')\",\n \"remote_data_1['IP'] = output_2[0].strip('\\\\n') remote_data_1['MAC'] = output_3[0].strip('\\\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\\\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\\\n') return\",\n \"for i in output: data_.append(i.split(' ')) for i in data_: filter_.append(list(filter(None, i))) for\",\n \"data_.append(i.split(' ')) for i in data_: filter_.append(list(filter(None, i))) for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0])\",\n \"/sys/class/net/eth0/address\\\") _, stdout_4, _ = ssh.exec_command( \\\"awk -F= '$1=={} {{ print $2 ;}}'\",\n \"[] filter_ = [] remote_data_2 = { 'Hostname': [], 'IP': [], 'MAC': [],\",\n \"# connect to the host -- tells us if the host is actually\",\n \"remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in filter_[i][9]: remote_data_2['Status'].append('Active') else: remote_data_2['Status'].append('Inactive') # ssh.close()\",\n \"try: # connect to the host -- tells us if the host is\",\n \"\\\"Please Connect to the Internet!\\\" is_connected() try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username,\",\n \"in output: data_.append(i.split(' ')) for i in data_: filter_.append(list(filter(None, i))) for i in\",\n \"return \\\"conneted to the Internet!\\\" except OSError: pass return \\\"Please Connect to the\",\n \"[], 'Lastseen': [], 'Status': [], } for i in output: data_.append(i.split(' ')) for\",\n \"except paramiko.AuthenticationException: print(\\\"Failed to connect to {} due to wrong username/password\\\".format(Hostname)) exit(1) except:\",\n \"commands _, stdout_1, _ = ssh.exec_command(\\\"hostname\\\") _, stdout_2, _ = ssh.exec_command(\\\"hostname -I |\",\n \"= stdout_3.readlines() output_4 = stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1 = { 'Hostname': '',\",\n \"stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1 = { 'Hostname': '', 'IP': '', 'MAC': '',\",\n \"tells us if the host is actually # reachable socket.create_connection((\\\"8.8.8.8\\\", 53)) return \\\"conneted\",\n \"53)) return \\\"conneted to the Internet!\\\" except OSError: pass return \\\"Please Connect to\",\n \"key_filename=key) except paramiko.AuthenticationException: print(\\\"Failed to connect to {} due to wrong username/password\\\".format(Hostname)) exit(1)\",\n \"i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in filter_[i][9]:\",\n \"in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in filter_[i][9]: remote_data_2['Status'].append('Active')\",\n \"filter_.append(list(filter(None, i))) for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if\",\n \"'', 'IP': '', 'MAC': '', 'OS': '', 'Currentuser': '', } remote_data_1['Hostname'] = output_1[0].strip('\\\\n')\",\n \"stdout_1, _ = ssh.exec_command(\\\"hostname\\\") _, stdout_2, _ = ssh.exec_command(\\\"hostname -I | awk '{print\",\n \"stdout_7, _ = ssh.exec_command(\\\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\\\") #_, stdout_8, _ = ssh.exec_command(\\\"sudo\",\n \"the host -- tells us if the host is actually # reachable socket.create_connection((\\\"8.8.8.8\\\",\",\n \"---------------------------------- def remote_data_2_(): output = stdout_6.readlines() data_ = [] filter_ = [] remote_data_2\",\n \"_, stdout_5, _ = ssh.exec_command(\\\"whoami\\\") _, stdout_6, _ = ssh.exec_command(\\\"last -F\\\") _, stdout_7,\",\n \"remote_data_2_(): output = stdout_6.readlines() data_ = [] filter_ = [] remote_data_2 = {\",\n \"paramiko import json Hostname = '172.16.17.32' Username = 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def\",\n \"'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: # connect to the host -- tells us if\",\n \"'ESTABLISHED.*sshd'\\\") #_, stdout_8, _ = ssh.exec_command(\\\"sudo {}/24\\\".format()) # egrep -o '([0-9]{1,3}\\\\.){3}[0-9]{1,3}' --IP-address #\",\n \"[], 'IP': [], 'MAC': [], 'Lastseen': [], 'Status': [], } for i in\",\n \"= ssh.exec_command(\\\"hostname\\\") _, stdout_2, _ = ssh.exec_command(\\\"hostname -I | awk '{print $1}'\\\") _,\",\n \"Connect to the Internet!\\\" is_connected() try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key)\",\n \"ssh.exec_command(\\\"hostname -I | awk '{print $1}'\\\") _, stdout_3, _ = ssh.exec_command(\\\"cat /sys/class/net/eth0/address\\\") _,\",\n \"socket.create_connection((\\\"8.8.8.8\\\", 53)) return \\\"conneted to the Internet!\\\" except OSError: pass return \\\"Please Connect\",\n \"'Lastseen': [], 'Status': [], } for i in output: data_.append(i.split(' ')) for i\",\n \"stdout_2, _ = ssh.exec_command(\\\"hostname -I | awk '{print $1}'\\\") _, stdout_3, _ =\",\n \"= ssh.exec_command(\\\"cat /sys/class/net/eth0/address\\\") _, stdout_4, _ = ssh.exec_command( \\\"awk -F= '$1=={} {{ print\",\n \"# egrep -o '([0-9]{1,3}\\\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def remote_data_1(): output_1 = stdout_1.readlines() output_2\",\n \"= { 'Hostname': '', 'IP': '', 'MAC': '', 'OS': '', 'Currentuser': '', }\",\n \"to connect to {} \\\".format(Hostname)) exit(2) # commands _, stdout_1, _ = ssh.exec_command(\\\"hostname\\\")\",\n \"output = stdout_6.readlines() data_ = [] filter_ = [] remote_data_2 = { 'Hostname':\",\n \"to the Internet!\\\" except OSError: pass return \\\"Please Connect to the Internet!\\\" is_connected()\",\n \"OSError: pass return \\\"Please Connect to the Internet!\\\" is_connected() try: ssh = paramiko.SSHClient()\",\n \"= ssh.exec_command(\\\"last -F\\\") _, stdout_7, _ = ssh.exec_command(\\\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\\\") #_,\",\n \"ssh.exec_command(\\\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\\\") #_, stdout_8, _ = ssh.exec_command(\\\"sudo {}/24\\\".format()) # egrep\",\n \"= output_5[0].strip('\\\\n') return json.dumps(remote_data_1, indent=4) # ---------------------------------- def remote_data_2_(): output = stdout_6.readlines() data_\",\n \"= stdout_2.readlines() output_3 = stdout_3.readlines() output_4 = stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1 =\",\n \"data_ = [] filter_ = [] remote_data_2 = { 'Hostname': [], 'IP': [],\",\n \"| awk '{print $1}'\\\") _, stdout_3, _ = ssh.exec_command(\\\"cat /sys/class/net/eth0/address\\\") _, stdout_4, _\",\n \"stdout_6.readlines() data_ = [] filter_ = [] remote_data_2 = { 'Hostname': [], 'IP':\",\n \"$2 ;}}' /etc/os-release\\\".format('\\\"NAME\\\"')) _, stdout_5, _ = ssh.exec_command(\\\"whoami\\\") _, stdout_6, _ = ssh.exec_command(\\\"last\",\n \"ssh.exec_command(\\\"hostname\\\") _, stdout_2, _ = ssh.exec_command(\\\"hostname -I | awk '{print $1}'\\\") _, stdout_3,\",\n \"-o '([0-9]{1,3}\\\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def remote_data_1(): output_1 = stdout_1.readlines() output_2 = stdout_2.readlines()\",\n \"'', } remote_data_1['Hostname'] = output_1[0].strip('\\\\n') remote_data_1['IP'] = output_2[0].strip('\\\\n') remote_data_1['MAC'] = output_3[0].strip('\\\\n') remote_data_1['OS'] =\",\n \"= stdout_5.readlines() remote_data_1 = { 'Hostname': '', 'IP': '', 'MAC': '', 'OS': '',\",\n \"= output_4[0][1:-1].strip('\\\\\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\\\n') return json.dumps(remote_data_1, indent=4) # ---------------------------------- def remote_data_2_(): output\",\n \"import socket import paramiko import json Hostname = '172.16.17.32' Username = 'ec2-user' key\",\n \"$1}'\\\") _, stdout_3, _ = ssh.exec_command(\\\"cat /sys/class/net/eth0/address\\\") _, stdout_4, _ = ssh.exec_command( \\\"awk\",\n \"-I | awk '{print $1}'\\\") _, stdout_3, _ = ssh.exec_command(\\\"cat /sys/class/net/eth0/address\\\") _, stdout_4,\",\n \"i))) for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged'\",\n \"<filename>tool/remote_info.py import socket import paramiko import json Hostname = '172.16.17.32' Username = 'ec2-user'\",\n \"'', 'OS': '', 'Currentuser': '', } remote_data_1['Hostname'] = output_1[0].strip('\\\\n') remote_data_1['IP'] = output_2[0].strip('\\\\n') remote_data_1['MAC']\",\n \"'OS': '', 'Currentuser': '', } remote_data_1['Hostname'] = output_1[0].strip('\\\\n') remote_data_1['IP'] = output_2[0].strip('\\\\n') remote_data_1['MAC'] =\",\n \"Username = 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: # connect to the\",\n \"remote_data_1 = { 'Hostname': '', 'IP': '', 'MAC': '', 'OS': '', 'Currentuser': '',\",\n \"= ssh.exec_command(\\\"hostname -I | awk '{print $1}'\\\") _, stdout_3, _ = ssh.exec_command(\\\"cat /sys/class/net/eth0/address\\\")\",\n \"'([0-9]{1,3}\\\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def remote_data_1(): output_1 = stdout_1.readlines() output_2 = stdout_2.readlines() output_3\",\n \"_ = ssh.exec_command(\\\"cat /sys/class/net/eth0/address\\\") _, stdout_4, _ = ssh.exec_command( \\\"awk -F= '$1=={} {{\",\n \"= output_1[0].strip('\\\\n') remote_data_1['IP'] = output_2[0].strip('\\\\n') remote_data_1['MAC'] = output_3[0].strip('\\\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\\\\\"') remote_data_1['Currentuser'] =\",\n \"= ssh.exec_command(\\\"whoami\\\") _, stdout_6, _ = ssh.exec_command(\\\"last -F\\\") _, stdout_7, _ = ssh.exec_command(\\\"netstat\",\n \"grep 'ESTABLISHED.*sshd'\\\") #_, stdout_8, _ = ssh.exec_command(\\\"sudo {}/24\\\".format()) # egrep -o '([0-9]{1,3}\\\\.){3}[0-9]{1,3}' --IP-address\",\n \"_ = ssh.exec_command(\\\"last -F\\\") _, stdout_7, _ = ssh.exec_command(\\\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\\\")\",\n \"output_2 = stdout_2.readlines() output_3 = stdout_3.readlines() output_4 = stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1\",\n \"ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException: print(\\\"Failed to connect to {} due to wrong\",\n \"ssh.exec_command(\\\"cat /sys/class/net/eth0/address\\\") _, stdout_4, _ = ssh.exec_command( \\\"awk -F= '$1=={} {{ print $2\",\n \"to connect to {} due to wrong username/password\\\".format(Hostname)) exit(1) except: print(\\\"Failed to connect\",\n \"= output_2[0].strip('\\\\n') remote_data_1['MAC'] = output_3[0].strip('\\\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\\\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\\\n') return json.dumps(remote_data_1,\",\n \"'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: # connect to the host --\",\n \"host -- tells us if the host is actually # reachable socket.create_connection((\\\"8.8.8.8\\\", 53))\",\n \"_ = ssh.exec_command(\\\"hostname -I | awk '{print $1}'\\\") _, stdout_3, _ = ssh.exec_command(\\\"cat\",\n \"'Hostname': '', 'IP': '', 'MAC': '', 'OS': '', 'Currentuser': '', } remote_data_1['Hostname'] =\",\n \"ssh.exec_command(\\\"last -F\\\") _, stdout_7, _ = ssh.exec_command(\\\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\\\") #_, stdout_8,\",\n \"stdout_6, _ = ssh.exec_command(\\\"last -F\\\") _, stdout_7, _ = ssh.exec_command(\\\"netstat -tnpa | grep\",\n \"} for i in output: data_.append(i.split(' ')) for i in data_: filter_.append(list(filter(None, i)))\",\n \"Internet!\\\" except OSError: pass return \\\"Please Connect to the Internet!\\\" is_connected() try: ssh\",\n \"pass return \\\"Please Connect to the Internet!\\\" is_connected() try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy())\",\n \"actually # reachable socket.create_connection((\\\"8.8.8.8\\\", 53)) return \\\"conneted to the Internet!\\\" except OSError: pass\",\n \"# --------------------------------- def remote_data_1(): output_1 = stdout_1.readlines() output_2 = stdout_2.readlines() output_3 = stdout_3.readlines()\",\n \"print(\\\"Failed to connect to {} due to wrong username/password\\\".format(Hostname)) exit(1) except: print(\\\"Failed to\",\n \"= [] remote_data_2 = { 'Hostname': [], 'IP': [], 'MAC': [], 'Lastseen': [],\",\n \"connect to {} due to wrong username/password\\\".format(Hostname)) exit(1) except: print(\\\"Failed to connect to\",\n \"_, stdout_1, _ = ssh.exec_command(\\\"hostname\\\") _, stdout_2, _ = ssh.exec_command(\\\"hostname -I | awk\",\n \"stdout_4, _ = ssh.exec_command( \\\"awk -F= '$1=={} {{ print $2 ;}}' /etc/os-release\\\".format('\\\"NAME\\\"')) _,\",\n \"ssh.exec_command( \\\"awk -F= '$1=={} {{ print $2 ;}}' /etc/os-release\\\".format('\\\"NAME\\\"')) _, stdout_5, _ =\",\n \"output_2[0].strip('\\\\n') remote_data_1['MAC'] = output_3[0].strip('\\\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\\\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\\\n') return json.dumps(remote_data_1, indent=4)\",\n \"--------------------------------- def remote_data_1(): output_1 = stdout_1.readlines() output_2 = stdout_2.readlines() output_3 = stdout_3.readlines() output_4\",\n \"return \\\"Please Connect to the Internet!\\\" is_connected() try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname,\",\n \"{{ print $2 ;}}' /etc/os-release\\\".format('\\\"NAME\\\"')) _, stdout_5, _ = ssh.exec_command(\\\"whoami\\\") _, stdout_6, _\",\n \"key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: # connect to the host -- tells\",\n \"= ssh.exec_command( \\\"awk -F= '$1=={} {{ print $2 ;}}' /etc/os-release\\\".format('\\\"NAME\\\"')) _, stdout_5, _\",\n \"/etc/os-release\\\".format('\\\"NAME\\\"')) _, stdout_5, _ = ssh.exec_command(\\\"whoami\\\") _, stdout_6, _ = ssh.exec_command(\\\"last -F\\\") _,\",\n \"-F= '$1=={} {{ print $2 ;}}' /etc/os-release\\\".format('\\\"NAME\\\"')) _, stdout_5, _ = ssh.exec_command(\\\"whoami\\\") _,\",\n \"stdout_5, _ = ssh.exec_command(\\\"whoami\\\") _, stdout_6, _ = ssh.exec_command(\\\"last -F\\\") _, stdout_7, _\",\n \"is_connected(): try: # connect to the host -- tells us if the host\",\n \"{} due to wrong username/password\\\".format(Hostname)) exit(1) except: print(\\\"Failed to connect to {} \\\".format(Hostname))\",\n \";}}' /etc/os-release\\\".format('\\\"NAME\\\"')) _, stdout_5, _ = ssh.exec_command(\\\"whoami\\\") _, stdout_6, _ = ssh.exec_command(\\\"last -F\\\")\",\n \"def is_connected(): try: # connect to the host -- tells us if the\",\n \"= ssh.exec_command(\\\"sudo {}/24\\\".format()) # egrep -o '([0-9]{1,3}\\\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def remote_data_1(): output_1\",\n \"stdout_2.readlines() output_3 = stdout_3.readlines() output_4 = stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1 = {\",\n \"'', 'Currentuser': '', } remote_data_1['Hostname'] = output_1[0].strip('\\\\n') remote_data_1['IP'] = output_2[0].strip('\\\\n') remote_data_1['MAC'] = output_3[0].strip('\\\\n')\",\n \"import json Hostname = '172.16.17.32' Username = 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected():\",\n \"output_1 = stdout_1.readlines() output_2 = stdout_2.readlines() output_3 = stdout_3.readlines() output_4 = stdout_4.readlines() output_5\",\n \"i in data_: filter_.append(list(filter(None, i))) for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found')\",\n \"connect to {} \\\".format(Hostname)) exit(2) # commands _, stdout_1, _ = ssh.exec_command(\\\"hostname\\\") _,\",\n \"remote_data_1['MAC'] = output_3[0].strip('\\\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\\\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\\\n') return json.dumps(remote_data_1, indent=4) #\",\n \"stdout_5.readlines() remote_data_1 = { 'Hostname': '', 'IP': '', 'MAC': '', 'OS': '', 'Currentuser':\",\n \"us if the host is actually # reachable socket.create_connection((\\\"8.8.8.8\\\", 53)) return \\\"conneted to\",\n \"# reachable socket.create_connection((\\\"8.8.8.8\\\", 53)) return \\\"conneted to the Internet!\\\" except OSError: pass return\",\n \"= [] filter_ = [] remote_data_2 = { 'Hostname': [], 'IP': [], 'MAC':\",\n \"remote_data_1['Hostname'] = output_1[0].strip('\\\\n') remote_data_1['IP'] = output_2[0].strip('\\\\n') remote_data_1['MAC'] = output_3[0].strip('\\\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\\\\\"') remote_data_1['Currentuser']\",\n \"# commands _, stdout_1, _ = ssh.exec_command(\\\"hostname\\\") _, stdout_2, _ = ssh.exec_command(\\\"hostname -I\",\n \"stdout_3, _ = ssh.exec_command(\\\"cat /sys/class/net/eth0/address\\\") _, stdout_4, _ = ssh.exec_command( \\\"awk -F= '$1=={}\",\n \"json.dumps(remote_data_1, indent=4) # ---------------------------------- def remote_data_2_(): output = stdout_6.readlines() data_ = [] filter_\",\n \"username=Username, key_filename=key) except paramiko.AuthenticationException: print(\\\"Failed to connect to {} due to wrong username/password\\\".format(Hostname))\",\n \"exit(1) except: print(\\\"Failed to connect to {} \\\".format(Hostname)) exit(2) # commands _, stdout_1,\",\n \"output_5 = stdout_5.readlines() remote_data_1 = { 'Hostname': '', 'IP': '', 'MAC': '', 'OS':\",\n \"Hostname = '172.16.17.32' Username = 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: #\",\n \"\\\"conneted to the Internet!\\\" except OSError: pass return \\\"Please Connect to the Internet!\\\"\",\n \"= ssh.exec_command(\\\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\\\") #_, stdout_8, _ = ssh.exec_command(\\\"sudo {}/24\\\".format()) #\",\n \"\\\"awk -F= '$1=={} {{ print $2 ;}}' /etc/os-release\\\".format('\\\"NAME\\\"')) _, stdout_5, _ = ssh.exec_command(\\\"whoami\\\")\",\n \"-tnpa | grep 'ESTABLISHED.*sshd'\\\") #_, stdout_8, _ = ssh.exec_command(\\\"sudo {}/24\\\".format()) # egrep -o\",\n \"output_3 = stdout_3.readlines() output_4 = stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1 = { 'Hostname':\",\n \"json Hostname = '172.16.17.32' Username = 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try:\",\n \"ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException: print(\\\"Failed to connect to\",\n \"remote_data_1['OS'] = output_4[0][1:-1].strip('\\\\\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\\\n') return json.dumps(remote_data_1, indent=4) # ---------------------------------- def remote_data_2_():\",\n \"--IP-address # --------------------------------- def remote_data_1(): output_1 = stdout_1.readlines() output_2 = stdout_2.readlines() output_3 =\",\n \"return json.dumps(remote_data_1, indent=4) # ---------------------------------- def remote_data_2_(): output = stdout_6.readlines() data_ = []\",\n \"{ 'Hostname': [], 'IP': [], 'MAC': [], 'Lastseen': [], 'Status': [], } for\",\n \"_ = ssh.exec_command(\\\"sudo {}/24\\\".format()) # egrep -o '([0-9]{1,3}\\\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def remote_data_1():\",\n \"= '172.16.17.32' Username = 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: # connect\",\n \"'MAC': '', 'OS': '', 'Currentuser': '', } remote_data_1['Hostname'] = output_1[0].strip('\\\\n') remote_data_1['IP'] = output_2[0].strip('\\\\n')\",\n \"paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException: print(\\\"Failed to connect to {} due\",\n \"'', 'MAC': '', 'OS': '', 'Currentuser': '', } remote_data_1['Hostname'] = output_1[0].strip('\\\\n') remote_data_1['IP'] =\",\n \"ssh.exec_command(\\\"whoami\\\") _, stdout_6, _ = ssh.exec_command(\\\"last -F\\\") _, stdout_7, _ = ssh.exec_command(\\\"netstat -tnpa\",\n \"'Hostname': [], 'IP': [], 'MAC': [], 'Lastseen': [], 'Status': [], } for i\",\n \"'MAC': [], 'Lastseen': [], 'Status': [], } for i in output: data_.append(i.split(' '))\",\n \"'IP': '', 'MAC': '', 'OS': '', 'Currentuser': '', } remote_data_1['Hostname'] = output_1[0].strip('\\\\n') remote_data_1['IP']\",\n \"_ = ssh.exec_command(\\\"hostname\\\") _, stdout_2, _ = ssh.exec_command(\\\"hostname -I | awk '{print $1}'\\\")\",\n \"_ = ssh.exec_command(\\\"whoami\\\") _, stdout_6, _ = ssh.exec_command(\\\"last -F\\\") _, stdout_7, _ =\",\n \"reachable socket.create_connection((\\\"8.8.8.8\\\", 53)) return \\\"conneted to the Internet!\\\" except OSError: pass return \\\"Please\",\n \"output: data_.append(i.split(' ')) for i in data_: filter_.append(list(filter(None, i))) for i in range(len(filter_)-3):\",\n \"host is actually # reachable socket.create_connection((\\\"8.8.8.8\\\", 53)) return \\\"conneted to the Internet!\\\" except\",\n \"'IP': [], 'MAC': [], 'Lastseen': [], 'Status': [], } for i in output:\",\n \"range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in filter_[i][9]: remote_data_2['Status'].append('Active') else:\",\n \"# ---------------------------------- def remote_data_2_(): output = stdout_6.readlines() data_ = [] filter_ = []\",\n \"exit(2) # commands _, stdout_1, _ = ssh.exec_command(\\\"hostname\\\") _, stdout_2, _ = ssh.exec_command(\\\"hostname\",\n \"the Internet!\\\" except OSError: pass return \\\"Please Connect to the Internet!\\\" is_connected() try:\",\n \"'Status': [], } for i in output: data_.append(i.split(' ')) for i in data_:\",\n \"[], 'Status': [], } for i in output: data_.append(i.split(' ')) for i in\",\n \"remote_data_2 = { 'Hostname': [], 'IP': [], 'MAC': [], 'Lastseen': [], 'Status': [],\",\n \"[], } for i in output: data_.append(i.split(' ')) for i in data_: filter_.append(list(filter(None,\",\n \"ssh.exec_command(\\\"sudo {}/24\\\".format()) # egrep -o '([0-9]{1,3}\\\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def remote_data_1(): output_1 =\",\n \"{} \\\".format(Hostname)) exit(2) # commands _, stdout_1, _ = ssh.exec_command(\\\"hostname\\\") _, stdout_2, _\",\n \"connect to the host -- tells us if the host is actually #\",\n \"to the host -- tells us if the host is actually # reachable\",\n \"the Internet!\\\" is_connected() try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException:\",\n \"found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in filter_[i][9]: remote_data_2['Status'].append('Active') else: remote_data_2['Status'].append('Inactive') # ssh.close() return\",\n \"socket import paramiko import json Hostname = '172.16.17.32' Username = 'ec2-user' key =\",\n \"def remote_data_1(): output_1 = stdout_1.readlines() output_2 = stdout_2.readlines() output_3 = stdout_3.readlines() output_4 =\",\n \"try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException: print(\\\"Failed to connect\",\n \"to wrong username/password\\\".format(Hostname)) exit(1) except: print(\\\"Failed to connect to {} \\\".format(Hostname)) exit(2) #\",\n \"= output_3[0].strip('\\\\n') remote_data_1['OS'] = output_4[0][1:-1].strip('\\\\\\\"') remote_data_1['Currentuser'] = output_5[0].strip('\\\\n') return json.dumps(remote_data_1, indent=4) # ----------------------------------\",\n \"data_: filter_.append(list(filter(None, i))) for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8]))\",\n \"for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in\",\n \"ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException: print(\\\"Failed to connect to {} due to\",\n \"stdout_3.readlines() output_4 = stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1 = { 'Hostname': '', 'IP':\",\n \"stdout_1.readlines() output_2 = stdout_2.readlines() output_3 = stdout_3.readlines() output_4 = stdout_4.readlines() output_5 = stdout_5.readlines()\",\n \"paramiko.AuthenticationException: print(\\\"Failed to connect to {} due to wrong username/password\\\".format(Hostname)) exit(1) except: print(\\\"Failed\",\n \"-- tells us if the host is actually # reachable socket.create_connection((\\\"8.8.8.8\\\", 53)) return\",\n \"output_5[0].strip('\\\\n') return json.dumps(remote_data_1, indent=4) # ---------------------------------- def remote_data_2_(): output = stdout_6.readlines() data_ =\",\n \"[], 'MAC': [], 'Lastseen': [], 'Status': [], } for i in output: data_.append(i.split('\",\n \"remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in filter_[i][9]: remote_data_2['Status'].append('Active') else: remote_data_2['Status'].append('Inactive') # ssh.close() return remote_data_2\",\n \"the host is actually # reachable socket.create_connection((\\\"8.8.8.8\\\", 53)) return \\\"conneted to the Internet!\\\"\",\n \"indent=4) # ---------------------------------- def remote_data_2_(): output = stdout_6.readlines() data_ = [] filter_ =\",\n \"_, stdout_7, _ = ssh.exec_command(\\\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\\\") #_, stdout_8, _ =\",\n \"'172.16.17.32' Username = 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: # connect to\",\n \"remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append(' '.join(filter_[i][3:8])) if 'logged' in filter_[i][9]: remote_data_2['Status'].append('Active') else: remote_data_2['Status'].append('Inactive')\",\n \"filter_ = [] remote_data_2 = { 'Hostname': [], 'IP': [], 'MAC': [], 'Lastseen':\",\n \"_, stdout_3, _ = ssh.exec_command(\\\"cat /sys/class/net/eth0/address\\\") _, stdout_4, _ = ssh.exec_command( \\\"awk -F=\",\n \"{}/24\\\".format()) # egrep -o '([0-9]{1,3}\\\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def remote_data_1(): output_1 = stdout_1.readlines()\",\n \"= 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: # connect to the host -- tells us\",\n \"_ = ssh.exec_command(\\\"netstat -tnpa | grep 'ESTABLISHED.*sshd'\\\") #_, stdout_8, _ = ssh.exec_command(\\\"sudo {}/24\\\".format())\",\n \"in data_: filter_.append(list(filter(None, i))) for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not found') remote_data_2['Lastseen'].append('\",\n \"for i in data_: filter_.append(list(filter(None, i))) for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2]) remote_data_2['MAC'].append('not\",\n \"stdout_8, _ = ssh.exec_command(\\\"sudo {}/24\\\".format()) # egrep -o '([0-9]{1,3}\\\\.){3}[0-9]{1,3}' --IP-address # --------------------------------- def\",\n \"output_4 = stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1 = { 'Hostname': '', 'IP': '',\",\n \"[] remote_data_2 = { 'Hostname': [], 'IP': [], 'MAC': [], 'Lastseen': [], 'Status':\",\n \"')) for i in data_: filter_.append(list(filter(None, i))) for i in range(len(filter_)-3): remote_data_2['Hostname'].append(filter_[i][0]) remote_data_2['IP'].append(filter_[i][2])\",\n \"import paramiko import json Hostname = '172.16.17.32' Username = 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem'\",\n \"print(\\\"Failed to connect to {} \\\".format(Hostname)) exit(2) # commands _, stdout_1, _ =\",\n \"username/password\\\".format(Hostname)) exit(1) except: print(\\\"Failed to connect to {} \\\".format(Hostname)) exit(2) # commands _,\",\n \"| grep 'ESTABLISHED.*sshd'\\\") #_, stdout_8, _ = ssh.exec_command(\\\"sudo {}/24\\\".format()) # egrep -o '([0-9]{1,3}\\\\.){3}[0-9]{1,3}'\",\n \"_, stdout_6, _ = ssh.exec_command(\\\"last -F\\\") _, stdout_7, _ = ssh.exec_command(\\\"netstat -tnpa |\",\n \"is_connected() try: ssh = paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException: print(\\\"Failed to\",\n \"wrong username/password\\\".format(Hostname)) exit(1) except: print(\\\"Failed to connect to {} \\\".format(Hostname)) exit(2) # commands\",\n \"= stdout_1.readlines() output_2 = stdout_2.readlines() output_3 = stdout_3.readlines() output_4 = stdout_4.readlines() output_5 =\",\n \"except: print(\\\"Failed to connect to {} \\\".format(Hostname)) exit(2) # commands _, stdout_1, _\",\n \"= 'ec2-user' key = 'G:/Projects/Python/Asset-Discovery-Tool/tool/s.pem' def is_connected(): try: # connect to the host\",\n \"if the host is actually # reachable socket.create_connection((\\\"8.8.8.8\\\", 53)) return \\\"conneted to the\",\n \"'{print $1}'\\\") _, stdout_3, _ = ssh.exec_command(\\\"cat /sys/class/net/eth0/address\\\") _, stdout_4, _ = ssh.exec_command(\",\n \"= paramiko.SSHClient() ssh.set_missing_host_key_policy(paramiko.AutoAddPolicy()) ssh.connect(hostname=Hostname, username=Username, key_filename=key) except paramiko.AuthenticationException: print(\\\"Failed to connect to {}\",\n \"_, stdout_4, _ = ssh.exec_command( \\\"awk -F= '$1=={} {{ print $2 ;}}' /etc/os-release\\\".format('\\\"NAME\\\"'))\",\n \"= { 'Hostname': [], 'IP': [], 'MAC': [], 'Lastseen': [], 'Status': [], }\",\n \"def remote_data_2_(): output = stdout_6.readlines() data_ = [] filter_ = [] remote_data_2 =\",\n \"awk '{print $1}'\\\") _, stdout_3, _ = ssh.exec_command(\\\"cat /sys/class/net/eth0/address\\\") _, stdout_4, _ =\",\n \"_ = ssh.exec_command( \\\"awk -F= '$1=={} {{ print $2 ;}}' /etc/os-release\\\".format('\\\"NAME\\\"')) _, stdout_5,\",\n \"print $2 ;}}' /etc/os-release\\\".format('\\\"NAME\\\"')) _, stdout_5, _ = ssh.exec_command(\\\"whoami\\\") _, stdout_6, _ =\"\n]","isConversational":false}}},{"rowIdx":4597,"cells":{"ngram":{"kind":"list like","value":["delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete of the secret's latest version at","int :param cas_required: If true the key will require the cas parameter to","str | unicode :return: The response of the request. :rtype: requests.Response \"\"\" params","\"\"\"Read the KV Version 2 configuration. Supported methods: GET: /auth/{mount_point}/config. Produces: 200 application/json","\"\"\" api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response = self._adapter.get(url=api_path) return response.json() def","not yet exist, the calling token must have an ACL policy granting the","= utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, ) return response.json() def update_metadata(self,","\"{path}\"; patch only works on existing data.'.format(path=path)) # Update existing secret dict. patched_secret","utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.post( url=api_path, json=params, ) return response.json() def patch(self,","get requests. :type versions: int :param mount_point: The \"path\" the secret engine was","path. Supported methods: GET: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path","requests. Supported methods: POST: /{mount_point}/undelete/{path}. Produces: 204 (empty body) :param path: Specifies the","version: int :param mount_point: The \"path\" the secret engine was mounted on. :type","versioned data will not be deleted, but it will no longer be returned","is non-zero the write will only be allowed if the key's current version","| unicode :param mount_point: The \"path\" the secret engine was mounted on. :type","stop them from being returned from reads, but the underlying data will not","error_msg = 'argument to \"versions\" must be a list containing one or more","exceptions, utils from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase): \"\"\"KV Secrets","\"versions\" must be a list containing one or more integers, \"{versions}\" provided.'.format( versions=versions","expected for cas_required param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path =","version is returned. :type version: int :param mount_point: The \"path\" the secret engine","of the create_or_update_secret request. :rtype: dict \"\"\" # First, do a read. try:","cas_required param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point,","the KV store without overwriting. :param path: Path :type path: str | unicode","and their data will be returned on normal get requests. :type versions: list",":type mount_point: str | unicode :return: The JSON response of the request. :rtype:","The response of the request. :rtype: requests.Response \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path)","version of a secret at the specified location. If the value does not","configuration. Supported methods: GET: /auth/{mount_point}/config. Produces: 200 application/json :param mount_point: The \"path\" the","= utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, ) def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT):","be stored and returned on read. :type secret: dict :param mount_point: The \"path\"","params = {} if version is not None: params['version'] = version api_path =","/{mount_point}/data/{path}. Produces: 200 application/json :param path: Specifies the path of the secret to","of a secret at the specified location. If the value does not yet","/{mount_point}/undelete/{path}. Produces: 204 (empty body) :param path: Specifies the path of the secret","response of the request. :rtype: requests.Response \"\"\" if not isinstance(versions, list) or len(versions)","dict \"\"\" # First, do a read. try: current_secret_version = self.read_secret_version( path=path, mount_point=mount_point,","json=params, ) def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Permanently remove the specified version data","keep per key. If not set, the backend's configured max version is used.","return response.json() def create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Create a new version of","version to return. If not set the latest version is returned. :type version:",":param cas_required: If true all keys will require the cas parameter to be","but the underlying data will not be removed. A delete can be undone","is returned. :type version: int :param mount_point: The \"path\" the secret engine was","delete of the secret's latest version at the specified location. This marks the","json=params, ) def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Return a list of key names at","the request. :rtype: requests.Response \"\"\" params = {} if max_versions is not None:","| unicode :param versions: The versions to be deleted. The versioned data will",":param path: Path :type path: str | unicode :param secret: The contents of","read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the metadata and versions for the secret at the","a list containing one or more integers, \"{versions}\" provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg)","isinstance(versions, list) or len(versions) == 0: error_msg = 'argument to \"versions\" must be","stored and returned on read. :type secret: dict :param mount_point: The \"path\" the","or update data in the KV store without overwriting. :param path: Path :type","utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, ) return response.json() def update_metadata(self, path,","request. :rtype: dict \"\"\" api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response = self._adapter.get(url=api_path)",":param path: Path :type path: str | unicode :param max_versions: The number of","\"\"\" params = { 'options': {}, 'data': secret, } if cas is not","configured allowed versions the oldest version will be permanently deleted. Defaults to 10.",":param path: Specifies the path of the secret to delete. This is specified","in the cas parameter. :type cas: int :param secret: The contents of the","to be returned on get requests. Supported methods: POST: /{mount_point}/undelete/{path}. Produces: 204 (empty","\"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, ) return response.json()","the request. :rtype: dict \"\"\" params = {} if version is not None:","the index is non-zero the write will only be allowed if the key's","bool :param mount_point: The \"path\" the secret engine was mounted on. :type mount_point:","mount_point: str | unicode :return: The JSON response of the create_or_update_secret request. :rtype:","max_versions is not None: params['max_versions'] = max_versions if cas_required is not None: if","backend level settings that are applied to every key in the key-value store.","Once a key has more than the configured allowed versions the oldest version","this value. Once a key has more than the configured allowed versions the","params = {} if max_versions is not None: params['max_versions'] = max_versions if cas_required","value to use a Check-And-Set operation. If not set the write will be","mount_point=DEFAULT_MOUNT_POINT): \"\"\"Delete (permanently) the key metadata and all version data for the specified","if cas_required is not None: if not isinstance(cas_required, bool): error_msg = 'bool expected","list of int :param mount_point: The \"path\" the secret engine was mounted on.","<filename>hvac/api/secrets_engines/kv_v2.py #!/usr/bin/env python # -*- coding: utf-8 -*- \"\"\"KvV2 methods module.\"\"\" from hvac","200 application/json :param mount_point: The \"path\" the secret engine was mounted on. :type","versions: The versions to be deleted. The versioned data will not be deleted,","mount_point: str | unicode :return: The JSON response of the request. :rtype: dict","not set the latest version is returned. :type version: int :param mount_point: The","of the request. :rtype: dict \"\"\" api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response","permanently deleted. Defaults to 10. :type max_versions: int :param cas_required: If true all","def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Delete (permanently) the key metadata and all version data","store without overwriting. :param path: Path :type path: str | unicode :param secret:","versions: The versions to destroy. Their data will be permanently deleted. :type versions:","of key names at the specified location. Folders are suffixed with /. The","url=api_path, json=params, ) return response.json() def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Set or update","will not be deleted, but it will no longer be returned in normal",":type path: str | unicode :param version: Specifies the version to return. If","updated secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT):","be removed. Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Specifies","will be permanently deleted. :type versions: list of int :param mount_point: The \"path\"",") def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Permanently remove the specified version data and","{} if max_versions is not None: params['max_versions'] = max_versions if cas_required is not","version and path in the key-value store. This restores the data, allowing it","\"\"\"Retrieve the secret at the specified location. Supported methods: GET: /{mount_point}/data/{path}. Produces: 200","response.json() def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the secret at the specified location.","'options': {}, 'data': secret, } if cas is not None: params['options']['cas'] = cas","path: Path :type path: str | unicode :param max_versions: The number of versions","returned in normal get requests. :type versions: int :param mount_point: The \"path\" the",":return: The JSON response of the request. :rtype: dict \"\"\" params = {}","as part of the URL. :type path: str | unicode :param mount_point: The","the secret at the specified path. Supported methods: GET: /{mount_point}/metadata/{path}. Produces: 200 application/json","and returned on read. :type secret: dict :param mount_point: The \"path\" the secret","dict \"\"\" params = { 'options': {}, 'data': secret, } if cas is","the key metadata and all version data for the specified key. All version","if max_versions is not None: params['max_versions'] = max_versions if cas_required is not None:","keys; do not encode sensitive information in key names. The values themselves are","the request. :rtype: dict \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.get(","require the cas parameter to be set on all write requests. :type cas_required:",") response = self._adapter.get(url=api_path) return response.json() def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the","works on existing data.'.format(path=path)) # Update existing secret dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret)","body) :param path: Specifies the path of the secret to delete. This is","methods module.\"\"\" from hvac import exceptions, utils from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT =","params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post(","cas parameter. :type cas: int :param secret: The contents of the \"secret\" dict","will only be allowed if the key's current version matches the version specified","KV Version 2 configuration. Supported methods: GET: /auth/{mount_point}/config. Produces: 200 application/json :param mount_point:","path of the secret to destroy. This is specified as part of the","raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path)","mount_point=mount_point) return self._adapter.post( url=api_path, json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Read the KV Version","configuration will be used. :type cas_required: bool :param mount_point: The \"path\" the secret","max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Updates the max_versions of cas_required setting on an existing path.","at the specified location. Supported methods: GET: /{mount_point}/data/{path}. Produces: 200 application/json :param path:","self._adapter.get( url=api_path, params=params, ) return response.json() def create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Create","str | unicode :param versions: The versions to be deleted. The versioned data","URL. :type path: str | unicode :param versions: The versions to be deleted.","will be returned on normal get requests. :type versions: list of int :param","URL. :type path: str | unicode :param version: Specifies the version to return.","write requests. If false, the backend's configuration will be used. :type cas_required: bool","\"\"\"KvV2 methods module.\"\"\" from hvac import exceptions, utils from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT",":rtype: dict \"\"\" params = { 'options': {}, 'data': secret, } if cas","(empty body) :param path: Path :type path: str | unicode :param max_versions: The","unicode :return: The response of the request. :rtype: requests.Response \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}',","key. If not set, the backend's configured max version is used. Once a","will stop them from being returned from reads, but the underlying data will","= current_secret_version['data']['data'] patched_secret.update(secret) # Write back updated secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret,","utf-8 -*- \"\"\"KvV2 methods module.\"\"\" from hvac import exceptions, utils from hvac.api.vault_api_base import","the request. :rtype: requests.Response \"\"\" params = { 'max_versions': max_versions, } if cas_required","no longer be returned in normal get requests. :type versions: int :param mount_point:","path=path) response = self._adapter.get( url=api_path, ) return response.json() def update_metadata(self, path, max_versions=None, cas_required=None,","The values themselves are not accessible via this command. Supported methods: LIST: /{mount_point}/metadata/{path}.","a soft delete of the specified versions of the secret. This marks the","write will be allowed. If set to 0 a write will only be","Supported methods: LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path of","store. This restores the data, allowing it to be returned on get requests.","| unicode :param version: Specifies the version to return. If not set the","/auth/{mount_point}/config. Produces: 200 application/json :param mount_point: The \"path\" the secret engine was mounted","The versions to be deleted. The versioned data will not be deleted, but","Produces: 200 application/json :param path: Specifies the path of the secret to read.","than the configured allowed versions the oldest version will be permanently deleted. Defaults","response of the request. :rtype: dict \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response","cas_required: bool :param mount_point: The \"path\" the secret engine was mounted on. :type","specified version data and numbers for the provided path from the key-value store.",":param version: Specifies the version to return. If not set the latest version","update data in the KV store without overwriting. :param path: Path :type path:","max_versions of cas_required setting on an existing path. Supported methods: POST: /{mount_point}/metadata/{path}. Produces:","= self._adapter.get(url=api_path) return response.json() def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the secret at","api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path, json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Read","\"\"\" # First, do a read. try: current_secret_version = self.read_secret_version( path=path, mount_point=mount_point, )","the version specified in the cas parameter. :type cas: int :param secret: The","def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Set or update data in the KV store","mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Delete (permanently)","returned from reads, but the underlying data will not be removed. A delete","be used. :type cas_required: bool :param mount_point: The \"path\" the secret engine was","= { 'options': {}, 'data': secret, } if cas is not None: params['options']['cas']","= self._adapter.get( url=api_path, params=params, ) return response.json() def create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT):","secret's latest version at the specified location. This marks the version as deleted","key-value store. Supported methods: POST: /{mount_point}/config. Produces: 204 (empty body) :param max_versions: The","of the request. :rtype: dict \"\"\" params = {} if version is not","requests.Response \"\"\" params = { 'max_versions': max_versions, } if cas_required is not None:",":param cas: Set the \"cas\" value to use a Check-And-Set operation. If not","/. The input must be a folder; list on a file will not","self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft","path: str | unicode :param versions: The versions to destroy. Their data will","metadata and versions for the secret at the specified path. Supported methods: GET:","doesn't exist. If the index is non-zero the write will only be allowed","undelete path. Supported methods: POST: /{mount_point}/delete/{path}. Produces: 204 (empty body) :param path: Specifies","the data for the provided version and path in the key-value store. This","{ 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params,","Produces: 204 (empty body) :param max_versions: The number of versions to keep per",":rtype: requests.Response \"\"\" if not isinstance(versions, list) or len(versions) == 0: error_msg =","dict will be stored and returned on read. :type secret: dict :param mount_point:","more integers, \"{versions}\" provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions,","to every key in the key-value store. Supported methods: POST: /{mount_point}/config. Produces: 204",":param cas_required: If true the key will require the cas parameter to be",") return response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the metadata and versions for","mount_point=DEFAULT_MOUNT_POINT): \"\"\"Create a new version of a secret at the specified location. If","The versions to undelete. The versions will be restored and their data will","| unicode :param cas: Set the \"cas\" value to use a Check-And-Set operation.","If true the key will require the cas parameter to be set on","used. :type cas_required: bool :param mount_point: The \"path\" the secret engine was mounted","at the specified path. Supported methods: GET: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path:",":type path: str | unicode :param versions: The versions to destroy. Their data","be deleted. The versioned data will not be deleted, but it will no","capability. Supported methods: POST: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Path :type path:","deleted and will stop them from being returned from reads, but the underlying","bool): error_msg = 'bool expected for cas_required param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required']","Path :type path: str | unicode :param max_versions: The number of versions to","The response of the request. :rtype: requests.Response \"\"\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path)","path. Supported methods: POST: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Path :type","the specified key. All version history will be removed. Supported methods: DELETE: /{mount_point}/metadata/{path}.","the key-value store. Supported methods: POST: /{mount_point}/destroy/{path}. Produces: 204 (empty body) :param path:","{ 'max_versions': max_versions, } if cas_required is not None: params['cas_required'] = cas_required api_path","None: params['version'] = version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path,","specified versions of the secret. This marks the versions as deleted and will","of int :param mount_point: The \"path\" the secret engine was mounted on. :type","self._adapter.post( url=api_path, json=params, ) def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Delete (permanently) the key metadata","None: params['options']['cas'] = cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.post( url=api_path,","versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete of the specified versions of the secret.","specified as part of the URL. :type path: str | unicode :param versions:","'bool expected for cas_required param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path","| unicode :return: The response of the request. :rtype: requests.Response \"\"\" if not","Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Specifies the path","key doesn't exist. If the index is non-zero the write will only be",":return: The response of the request. :rtype: requests.Response \"\"\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point,","data and numbers for the provided path from the key-value store. Supported methods:","have an ACL policy granting the create capability. If the value already exists,","api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, ) def delete_secret_versions(self, path, versions,","key has more than the configured allowed versions the oldest version will be","not isinstance(versions, list) or len(versions) == 0: error_msg = 'argument to \"versions\" must","Supported methods: POST: /{mount_point}/config. Produces: 204 (empty body) :param max_versions: The number of",":param versions: The versions to destroy. Their data will be permanently deleted. :type","mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Undelete","str | unicode :return: The response of the request. :rtype: requests.Response \"\"\" api_path","are suffixed with /. The input must be a folder; list on a","per key. If not set, the backend's configured max version is used. Once","to be set on all write requests. If false, the backend's configuration will","path: str | unicode :param secret: The contents of the \"secret\" dict will","a value. Note that no policy-based filtering is performed on keys; do not","set the latest version is returned. :type version: int :param mount_point: The \"path\"","set, the backend's configured max version is used. Once a key has more","/{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path of the secrets to","\"\"\" params = {} if version is not None: params['version'] = version api_path","will no longer be returned in normal get requests. :type versions: int :param","is not None: if not isinstance(cas_required, bool): error_msg = 'bool expected for cas_required","the max_versions of cas_required setting on an existing path. Supported methods: POST: /{mount_point}/metadata/{path}.","Supported methods: POST: /{mount_point}/delete/{path}. Produces: 204 (empty body) :param path: Specifies the path","be set on all write requests. :type cas_required: bool :param mount_point: The \"path\"","Note that no policy-based filtering is performed on keys; do not encode sensitive","removed. A delete can be undone using the undelete path. Supported methods: DELETE:","= utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT):","mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Permanently","mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the metadata and versions for the secret at the specified path.","The JSON response of the request. :rtype: dict \"\"\" params = { 'options':","be removed. A delete can be undone using the undelete path. Supported methods:","be returned on normal get requests. :type versions: list of int :param mount_point:","be returned in normal get requests. :type versions: int :param mount_point: The \"path\"","If true all keys will require the cas parameter to be set on","json=params, ) def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Delete (permanently) the key metadata and all",":return: The response of the request. :rtype: requests.Response \"\"\" params = {} if","The JSON response of the request. :rtype: dict \"\"\" api_path = utils.format_url( '/v1/{mount_point}/config',","applies to all keys, but a key's metadata setting can overwrite this value.","of versions to keep per key. If not set, the backend's configured max","versions of the secret. This marks the versions as deleted and will stop","the URL. :type path: str | unicode :param versions: The versions to undelete.","cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete of","to list. This is specified as part of the URL. :type path: str","location. If the value does not yet exist, the calling token must have","has more than the configured allowed versions the oldest version will be permanently",":rtype: dict \"\"\" # First, do a read. try: current_secret_version = self.read_secret_version( path=path,","\"\"\"Updates the max_versions of cas_required setting on an existing path. Supported methods: POST:","VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase): \"\"\"KV Secrets Engine - Version 2 (API).","specified in the cas parameter. :type cas: int :param secret: The contents of","destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Permanently remove the specified version data and numbers for","the value does not yet exist, the calling token must have an ACL","response of the request. :rtype: dict \"\"\" params = { 'options': {}, 'data':","configured allowed versions the oldest version will be permanently deleted. :type max_versions: int","key. This value applies to all keys, but a key's metadata setting can","policy granting the create capability. If the value already exists, the calling token","Set the \"cas\" value to use a Check-And-Set operation. If not set the","Their data will be permanently deleted. :type versions: list of int :param mount_point:","Supported methods: GET: /auth/{mount_point}/config. Produces: 200 application/json :param mount_point: The \"path\" the secret","secret: The contents of the \"secret\" dict will be stored and returned on","If set to 0 a write will only be allowed if the key","delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Delete (permanently) the key metadata and all version data for","| unicode :param secret: The contents of the \"secret\" dict will be stored","versions to undelete. The versions will be restored and their data will be","secret to destroy. This is specified as part of the URL. :type path:",") raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point,","keys, but a key's metadata setting can overwrite this value. Once a key","utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, ) def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue","request. :rtype: requests.Response \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, )","the request. :rtype: requests.Response \"\"\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path,","max_versions: int :param cas_required: If true the key will require the cas parameter","undelete. The versions will be restored and their data will be returned on","and path in the key-value store. This restores the data, allowing it to","metadata and all version data for the specified key. All version history will","a file will not return a value. Note that no policy-based filtering is","#!/usr/bin/env python # -*- coding: utf-8 -*- \"\"\"KvV2 methods module.\"\"\" from hvac import","delete can be undone using the undelete path. Supported methods: DELETE: /{mount_point}/data/{path}. Produces:","requests. :type cas_required: bool :param mount_point: The \"path\" the secret engine was mounted","a soft delete of the secret's latest version at the specified location. This","versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Undelete the data for the provided version and path in the","path: str | unicode :param versions: The versions to be deleted. The versioned","def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Permanently remove the specified version data and numbers","the secret at the specified location. Supported methods: GET: /{mount_point}/data/{path}. Produces: 200 application/json","a new version of a secret at the specified location. If the value","max_versions: The number of versions to keep per key. This value applies to","def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the metadata and versions for the secret at","current version matches the version specified in the cas parameter. :type cas: int","'/v1/{mount_point}/config', mount_point=mount_point, ) response = self._adapter.get(url=api_path) return response.json() def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT):","and all version data for the specified key. All version history will be","cas parameter to be set on all write requests. If false, the backend's",":param path: Specifies the path of the secret to undelete. This is specified","granting the create capability. If the value already exists, the calling token must","the create capability. If the value already exists, the calling token must have",":rtype: requests.Response \"\"\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, ) def","mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, ) return response.json() def update_metadata(self, path, max_versions=None,","location. This marks the version as deleted and will stop it from being","api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.list( url=api_path, ) return response.json() def","\"cas\" value to use a Check-And-Set operation. If not set the write will","The number of versions to keep per key. If not set, the backend's","self._adapter.list( url=api_path, ) return response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the metadata and","204 (empty body) :param path: Path :type path: str | unicode :param max_versions:","on existing data.'.format(path=path)) # Update existing secret dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) #","be returned on get requests. Supported methods: POST: /{mount_point}/undelete/{path}. Produces: 204 (empty body)","not accessible via this command. Supported methods: LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json :param","deleted, but it will no longer be returned in normal get requests. :type","def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Return a list of key names at the specified","versions: int :param mount_point: The \"path\" the secret engine was mounted on. :type","policy granting the update capability. Supported methods: POST: /{mount_point}/data/{path}. Produces: 200 application/json :param","except exceptions.InvalidPath: raise exceptions.InvalidPath('No value found at \"{path}\"; patch only works on existing","deleted. :type versions: list of int :param mount_point: The \"path\" the secret engine","/{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path of the secret to","delete can be undone using the undelete path. Supported methods: POST: /{mount_point}/delete/{path}. Produces:","the backend's configured max version is used. Once a key has more than","as deleted and will stop them from being returned from reads, but the","key-value store. This restores the data, allowing it to be returned on get","exist. If the index is non-zero the write will only be allowed if","provided version and path in the key-value store. This restores the data, allowing","return. If not set the latest version is returned. :type version: int :param","path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the metadata and versions for the secret at the specified","to read. This is specified as part of the URL. :type path: str","it to be returned on get requests. Supported methods: POST: /{mount_point}/undelete/{path}. Produces: 204","/{mount_point}/data/{path}. Produces: 204 (empty body) :param path: Specifies the path of the secret","def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Read the KV Version 2 configuration. Supported methods: GET: /auth/{mount_point}/config.","str | unicode :param version: Specifies the version to return. If not set",":type path: str | unicode :param max_versions: The number of versions to keep","utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path, json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Read the KV","a key has more than the configured allowed versions the oldest version will","len(versions) == 0: error_msg = 'argument to \"versions\" must be a list containing","200 application/json :param path: Specifies the path of the secrets to list. This",":rtype: dict \"\"\" api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response = self._adapter.get(url=api_path) return","a key's metadata setting can overwrite this value. Once a key has more","token must have an ACL policy granting the create capability. If the value","latest version at the specified location. This marks the version as deleted and","or more integers, \"{versions}\" provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg) params = { 'versions':","be permanently deleted. :type versions: list of int :param mount_point: The \"path\" the","and versions for the secret at the specified path. Supported methods: GET: /{mount_point}/metadata/{path}.","the request. :rtype: requests.Response \"\"\" if not isinstance(versions, list) or len(versions) == 0:","raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path)",":type path: str | unicode :param mount_point: The \"path\" the secret engine was","} api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def undelete_secret_versions(self,","removed. Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Specifies the","unicode :param cas: Set the \"cas\" value to use a Check-And-Set operation. If","max_versions: int :param cas_required: If true all keys will require the cas parameter","on read. :type secret: dict :param mount_point: The \"path\" the secret engine was","undelete path. Supported methods: DELETE: /{mount_point}/data/{path}. Produces: 204 (empty body) :param path: Specifies","of the request. :rtype: dict \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response =","read. :type secret: dict :param mount_point: The \"path\" the secret engine was mounted","version data for the specified key. All version history will be removed. Supported",":param max_versions: The number of versions to keep per key. If not set,","of the secret to delete. This is specified as part of the URL.","be permanently deleted. Defaults to 10. :type max_versions: int :param cas_required: If true","being returned from reads, but the underlying data will not be removed. A","unicode :param secret: The contents of the \"secret\" dict will be stored and","path from the key-value store. Supported methods: POST: /{mount_point}/destroy/{path}. Produces: 204 (empty body)","returned on read. :type secret: dict :param mount_point: The \"path\" the secret engine","to undelete. This is specified as part of the URL. :type path: str",") def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Undelete the data for the provided version","mount_point=DEFAULT_MOUNT_POINT): \"\"\"Return a list of key names at the specified location. Folders are","DELETE: /{mount_point}/data/{path}. Produces: 204 (empty body) :param path: Specifies the path of the","list on a file will not return a value. Note that no policy-based",":type versions: int :param mount_point: The \"path\" the secret engine was mounted on.","the provided path from the key-value store. Supported methods: POST: /{mount_point}/destroy/{path}. Produces: 204",":type version: int :param mount_point: The \"path\" the secret engine was mounted on.","Specifies the path of the secret to undelete. This is specified as part","the versions as deleted and will stop them from being returned from reads,","unicode :return: The response of the request. :rtype: requests.Response \"\"\" params = {","the cas parameter. :type cas: int :param secret: The contents of the \"secret\"","will be restored and their data will be returned on normal get requests.","specified location. Folders are suffixed with /. The input must be a folder;","(empty body) :param path: Specifies the path of the secret to undelete. This","was mounted on. :type mount_point: str | unicode :return: The JSON response of","return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a","The input must be a folder; list on a file will not return","Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \"\"\" def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Configure backend level settings that","max_versions, } if cas_required is not None: params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/config',","} api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def list_secrets(self,","request. :rtype: requests.Response \"\"\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, )","allowed versions the oldest version will be permanently deleted. Defaults to 10. :type","the path of the secret to undelete. This is specified as part of","/{mount_point}/destroy/{path}. Produces: 204 (empty body) :param path: Specifies the path of the secret","| unicode :param versions: The versions to undelete. The versions will be restored","at the specified location. Folders are suffixed with /. The input must be","using the undelete path. Supported methods: DELETE: /{mount_point}/data/{path}. Produces: 204 (empty body) :param","will stop it from being returned from reads, but the underlying data will","self._adapter.post( url=api_path, json=params, ) def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Permanently remove the specified","overwriting. :param path: Path :type path: str | unicode :param secret: The contents","\"\"\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, ) def delete_secret_versions(self, path,","of the secret's latest version at the specified location. This marks the version","| unicode :return: The response of the request. :rtype: requests.Response \"\"\" params =","mount_point=mount_point, ) except exceptions.InvalidPath: raise exceptions.InvalidPath('No value found at \"{path}\"; patch only works","be a folder; list on a file will not return a value. Note","utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT):","path: str | unicode :param version: Specifies the version to return. If not","read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Read the KV Version 2 configuration. Supported methods: GET: /auth/{mount_point}/config. Produces:","policy-based filtering is performed on keys; do not encode sensitive information in key","the secrets to list. This is specified as part of the URL. :type","Produces: 204 (empty body) :param path: Specifies the path of the secret to",":param max_versions: The number of versions to keep per key. This value applies","Supported methods: POST: /{mount_point}/destroy/{path}. Produces: 204 (empty body) :param path: Specifies the path","request. :rtype: dict \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path,","file will not return a value. Note that no policy-based filtering is performed","level settings that are applied to every key in the key-value store. Supported","allowed. If set to 0 a write will only be allowed if the","not set the write will be allowed. If set to 0 a write","The response of the request. :rtype: requests.Response \"\"\" params = { 'max_versions': max_versions,","\"\"\" def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Configure backend level settings that are applied","} if cas is not None: params['options']['cas'] = cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point,",":param path: Path :type path: str | unicode :param cas: Set the \"cas\"","methods: POST: /{mount_point}/undelete/{path}. Produces: 204 (empty body) :param path: Specifies the path of","version=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the secret at the specified location. Supported methods: GET: /{mount_point}/data/{path}.","the path of the secret to read. This is specified as part of","and will stop them from being returned from reads, but the underlying data","json=params, ) def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Undelete the data for the provided","on keys; do not encode sensitive information in key names. The values themselves","The versioned data will not be deleted, but it will no longer be","will be stored and returned on read. :type secret: dict :param mount_point: The","POST: /{mount_point}/destroy/{path}. Produces: 204 (empty body) :param path: Specifies the path of the","def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the secret at the specified location. Supported","that are applied to every key in the key-value store. Supported methods: POST:","version will be permanently deleted. Defaults to 10. :type max_versions: int :param cas_required:","the calling token must have an ACL policy granting the create capability. If","the underlying data will not be removed. A delete can be undone using","calling token must have an ACL policy granting the update capability. Supported methods:","list) or len(versions) == 0: error_msg = 'argument to \"versions\" must be a","This is specified as part of the URL. :type path: str | unicode","isinstance(cas_required, bool): error_msg = 'bool expected for cas_required param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg)","versions: The versions to undelete. The versions will be restored and their data","from reads, but the underlying data will not be removed. A delete can","None: params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path, json=params, )","(permanently) the key metadata and all version data for the specified key. All","POST: /{mount_point}/delete/{path}. Produces: 204 (empty body) :param path: Specifies the path of the","information in key names. The values themselves are not accessible via this command.",") def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete of the specified","unicode :return: The JSON response of the request. :rtype: dict \"\"\" params =","at the specified location. If the value does not yet exist, the calling","(empty body) :param path: Specifies the path of the secret to destroy. This","| unicode :return: The JSON response of the request. :rtype: dict \"\"\" api_path","path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Create a new version of a secret at the","unicode :param mount_point: The \"path\" the secret engine was mounted on. :type mount_point:","cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def delete_metadata_and_all_versions(self,",":type mount_point: str | unicode :return: The response of the request. :rtype: requests.Response","\"\"\"Delete (permanently) the key metadata and all version data for the specified key.","params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, )","int :param mount_point: The \"path\" the secret engine was mounted on. :type mount_point:","json=params, ) return response.json() def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Set or update data","url=api_path, json=params, ) def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Permanently remove the specified version","self._adapter.post( url=api_path, json=params, ) def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Undelete the data for","will be used. :type cas_required: bool :param mount_point: The \"path\" the secret engine","versions=versions ) raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}',","path: Specifies the path of the secret to destroy. This is specified as","soft delete of the specified versions of the secret. This marks the versions","Supported methods: GET: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path of","api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response = self._adapter.get(url=api_path) return response.json() def read_secret_version(self,","response = self._adapter.get( url=api_path, params=params, ) return response.json() def create_or_update_secret(self, path, secret, cas=None,","/{mount_point}/delete/{path}. Produces: 204 (empty body) :param path: Specifies the path of the secret","integers, \"{versions}\" provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, }","The JSON response of the create_or_update_secret request. :rtype: dict \"\"\" # First, do","undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Undelete the data for the provided version and path","dict \"\"\" params = {} if version is not None: params['version'] = version","path: Specifies the path of the secret to delete. This is specified as","with /. The input must be a folder; list on a file will","path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Permanently remove the specified version data and numbers for the","more than the configured allowed versions the oldest version will be permanently deleted.","is used. Once a key has more than the configured allowed versions the","do a read. try: current_secret_version = self.read_secret_version( path=path, mount_point=mount_point, ) except exceptions.InvalidPath: raise","requests.Response \"\"\" if not isinstance(versions, list) or len(versions) == 0: error_msg = 'argument","path. Supported methods: DELETE: /{mount_point}/data/{path}. Produces: 204 (empty body) :param path: Specifies the","require the cas parameter to be set on all write requests. If false,","will require the cas parameter to be set on all write requests. :type","= max_versions if cas_required is not None: if not isinstance(cas_required, bool): error_msg =","body) :param max_versions: The number of versions to keep per key. This value","current_secret_version['data']['data'] patched_secret.update(secret) # Write back updated secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point,","\"\"\"Issue a soft delete of the secret's latest version at the specified location.","path of the secrets to list. This is specified as part of the","version is used. Once a key has more than the configured allowed versions","list. This is specified as part of the URL. :type path: str |","import exceptions, utils from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase): \"\"\"KV","exist, the calling token must have an ACL policy granting the create capability.","(empty body) :param path: Specifies the path of the secret to delete. This","str | unicode :param cas: Set the \"cas\" value to use a Check-And-Set","None: if not isinstance(cas_required, bool): error_msg = 'bool expected for cas_required param, {type}","} api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def destroy_secret_versions(self,","versions=versions ) raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}',","existing secret dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) # Write back updated secret. return","data in the KV store without overwriting. :param path: Path :type path: str","mount_point: str | unicode :return: The response of the request. :rtype: requests.Response \"\"\"","max_versions if cas_required is not None: if not isinstance(cas_required, bool): error_msg = 'bool","mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, params=params, ) return response.json() def create_or_update_secret(self, path,","response = self._adapter.post( url=api_path, json=params, ) return response.json() def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT):","return self._adapter.delete( url=api_path, ) def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete","of the secrets to list. This is specified as part of the URL.","contents of the \"secret\" dict will be stored and returned on read. :type","POST: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Path :type path: str |","secret. This marks the versions as deleted and will stop them from being","is not None: params['options']['cas'] = cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response =","if cas_required is not None: params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return","path of the secret to read. This is specified as part of the","return response.json() def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Set or update data in the","current_secret_version = self.read_secret_version( path=path, mount_point=mount_point, ) except exceptions.InvalidPath: raise exceptions.InvalidPath('No value found at","the specified path. Supported methods: GET: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies","destroy. This is specified as part of the URL. :type path: str |","themselves are not accessible via this command. Supported methods: LIST: /{mount_point}/metadata/{path}. Produces: 200","setting can overwrite this value. Once a key has more than the configured","oldest version will be permanently deleted. :type max_versions: int :param cas_required: If true","\"\"\"Create a new version of a secret at the specified location. If the","First, do a read. try: current_secret_version = self.read_secret_version( path=path, mount_point=mount_point, ) except exceptions.InvalidPath:","to undelete. The versions will be restored and their data will be returned","soft delete of the secret's latest version at the specified location. This marks","str | unicode :param mount_point: The \"path\" the secret engine was mounted on.","mount_point=DEFAULT_MOUNT_POINT): \"\"\"Configure backend level settings that are applied to every key in the",":type path: str | unicode :param secret: The contents of the \"secret\" dict","will not return a value. Note that no policy-based filtering is performed on","stop it from being returned from reads, but the underlying data will not","if cas is not None: params['options']['cas'] = cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path)","the undelete path. Supported methods: POST: /{mount_point}/delete/{path}. Produces: 204 (empty body) :param path:","data, allowing it to be returned on get requests. Supported methods: POST: /{mount_point}/undelete/{path}.","will not be removed. A delete can be undone using the undelete path.","a secret at the specified location. If the value does not yet exist,","version is not None: params['version'] = version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response",":return: The JSON response of the request. :rtype: dict \"\"\" params = {","= utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def undelete_secret_versions(self, path, versions,","versions to keep per key. This value applies to all keys, but a","coding: utf-8 -*- \"\"\"KvV2 methods module.\"\"\" from hvac import exceptions, utils from hvac.api.vault_api_base","Supported methods: POST: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Path :type path: str","patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Set or update data in the KV store without","granting the update capability. Supported methods: POST: /{mount_point}/data/{path}. Produces: 200 application/json :param path:","the specified location. This marks the version as deleted and will stop it","\"\"\"KV Secrets Engine - Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \"\"\" def configure(self, max_versions=10,","data will not be deleted, but it will no longer be returned in","existing data.'.format(path=path)) # Update existing secret dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) # Write","version will be permanently deleted. :type max_versions: int :param cas_required: If true the","'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, )","cas: Set the \"cas\" value to use a Check-And-Set operation. If not set","api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def destroy_secret_versions(self, path,","unicode :return: The response of the request. :rtype: requests.Response \"\"\" if not isinstance(versions,","restores the data, allowing it to be returned on get requests. Supported methods:","body) :param path: Specifies the path of the secret to destroy. This is","the oldest version will be permanently deleted. Defaults to 10. :type max_versions: int","This marks the versions as deleted and will stop them from being returned","to return. If not set the latest version is returned. :type version: int","= self._adapter.post( url=api_path, json=params, ) return response.json() def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Set","create_or_update_secret request. :rtype: dict \"\"\" # First, do a read. try: current_secret_version =","not return a value. Note that no policy-based filtering is performed on keys;",":type cas: int :param secret: The contents of the \"secret\" dict will be","number of versions to keep per key. If not set, the backend's configured","path=path) return self._adapter.post( url=api_path, json=params, ) def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Delete (permanently) the","secret engine was mounted on. :type mount_point: str | unicode :return: The response","def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete of the specified versions","the secret to read. This is specified as part of the URL. :type","params = { 'max_versions': max_versions, } if cas_required is not None: params['cas_required'] =","204 (empty body) :param max_versions: The number of versions to keep per key.","engine was mounted on. :type mount_point: str | unicode :return: The JSON response","found at \"{path}\"; patch only works on existing data.'.format(path=path)) # Update existing secret","than the configured allowed versions the oldest version will be permanently deleted. :type","write will only be allowed if the key's current version matches the version","application/json :param path: Specifies the path of the secrets to list. This is","secret, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Set or update data in the KV store without overwriting. :param","was mounted on. :type mount_point: str | unicode :return: The response of the","raise exceptions.InvalidPath('No value found at \"{path}\"; patch only works on existing data.'.format(path=path)) #","versions as deleted and will stop them from being returned from reads, but","response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the metadata and versions for the secret","self._adapter.post( url=api_path, json=params, ) return response.json() def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Set or","utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT):","This restores the data, allowing it to be returned on get requests. Supported","response = self._adapter.get(url=api_path) return response.json() def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the secret","unicode :return: The JSON response of the request. :rtype: dict \"\"\" api_path =","python # -*- coding: utf-8 -*- \"\"\"KvV2 methods module.\"\"\" from hvac import exceptions,","containing one or more integers, \"{versions}\" provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg) params =","JSON response of the request. :rtype: dict \"\"\" params = {} if version","Path :type path: str | unicode :param cas: Set the \"cas\" value to","api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.post( url=api_path, json=params, ) return response.json()","patched_secret.update(secret) # Write back updated secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, )","path=path) response = self._adapter.post( url=api_path, json=params, ) return response.json() def patch(self, path, secret,","undone using the undelete path. Supported methods: POST: /{mount_point}/delete/{path}. Produces: 204 (empty body)","oldest version will be permanently deleted. Defaults to 10. :type max_versions: int :param","secret to delete. This is specified as part of the URL. :type path:","request. :rtype: requests.Response \"\"\" params = { 'max_versions': max_versions, } if cas_required is","data will be permanently deleted. :type versions: list of int :param mount_point: The","the create_or_update_secret request. :rtype: dict \"\"\" # First, do a read. try: current_secret_version","DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Specifies the path of the","in the key-value store. This restores the data, allowing it to be returned","is specified as part of the URL. :type path: str | unicode :param","= self._adapter.get( url=api_path, ) return response.json() def update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Updates","the path of the secrets to list. This is specified as part of","Update existing secret dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) # Write back updated secret.","GET: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path of the secret","{} if version is not None: params['version'] = version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point,","JSON response of the request. :rtype: dict \"\"\" api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point,","their data will be returned on normal get requests. :type versions: list of","or len(versions) == 0: error_msg = 'argument to \"versions\" must be a list","params['version'] = version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, params=params,","the key will require the cas parameter to be set on all write","versions=versions ) raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}',","mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, ) def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a","to keep per key. This value applies to all keys, but a key's","to use a Check-And-Set operation. If not set the write will be allowed.","to 0 a write will only be allowed if the key doesn't exist.","The number of versions to keep per key. This value applies to all","mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete of the specified versions of the secret. This","path, secret, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Set or update data in the KV store without overwriting.","mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the secret at the specified location. Supported methods: GET: /{mount_point}/data/{path}. Produces:","GET: /auth/{mount_point}/config. Produces: 200 application/json :param mount_point: The \"path\" the secret engine was","raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path)","the request. :rtype: dict \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.list(","versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def","the write will be allowed. If set to 0 a write will only","the value already exists, the calling token must have an ACL policy granting","values themselves are not accessible via this command. Supported methods: LIST: /{mount_point}/metadata/{path}. Produces:","max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Configure backend level settings that are applied to every key","str | unicode :return: The JSON response of the request. :rtype: dict \"\"\"","have an ACL policy granting the update capability. Supported methods: POST: /{mount_point}/data/{path}. Produces:","all keys, but a key's metadata setting can overwrite this value. Once a","version data and numbers for the provided path from the key-value store. Supported","body) :param path: Specifies the path of the secret to undelete. This is","capability. If the value already exists, the calling token must have an ACL","exceptions.InvalidPath: raise exceptions.InvalidPath('No value found at \"{path}\"; patch only works on existing data.'.format(path=path))","secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue","store. Supported methods: POST: /{mount_point}/destroy/{path}. Produces: 204 (empty body) :param path: Specifies the","params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post(","exceptions.InvalidPath('No value found at \"{path}\"; patch only works on existing data.'.format(path=path)) # Update","setting on an existing path. Supported methods: POST: /{mount_point}/metadata/{path}. Produces: 204 (empty body)","204 (empty body) :param path: Specifies the path of the secret to undelete.","Specifies the version to return. If not set the latest version is returned.","path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Updates the max_versions of cas_required setting on an existing","= {} if version is not None: params['version'] = version api_path = utils.format_url('/v1/{mount_point}/data/{path}',","the request. :rtype: requests.Response \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path,","path=path, mount_point=mount_point, ) except exceptions.InvalidPath: raise exceptions.InvalidPath('No value found at \"{path}\"; patch only","can be undone using the undelete path. Supported methods: DELETE: /{mount_point}/data/{path}. Produces: 204","metadata setting can overwrite this value. Once a key has more than the","data for the provided version and path in the key-value store. This restores","the backend's configuration will be used. :type cas_required: bool :param mount_point: The \"path\"","params = { 'options': {}, 'data': secret, } if cas is not None:","the version to return. If not set the latest version is returned. :type","on normal get requests. :type versions: list of int :param mount_point: The \"path\"","not None: params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path, json=params,","body) :param path: Path :type path: str | unicode :param max_versions: The number","the request. :rtype: dict \"\"\" api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response =","# -*- coding: utf-8 -*- \"\"\"KvV2 methods module.\"\"\" from hvac import exceptions, utils","cas is not None: params['options']['cas'] = cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response","as part of the URL. :type path: str | unicode :param version: Specifies",":type secret: dict :param mount_point: The \"path\" the secret engine was mounted on.","return response.json() def update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Updates the max_versions of cas_required","/{mount_point}/data/{path}. Produces: 200 application/json :param path: Path :type path: str | unicode :param","specified key. All version history will be removed. Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces:",":type path: str | unicode :param versions: The versions to be deleted. The","api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, ) return response.json() def","suffixed with /. The input must be a folder; list on a file","dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) # Write back updated secret. return self.create_or_update_secret( path=path,","the \"secret\" dict will be stored and returned on read. :type secret: dict","as part of the URL. :type path: str | unicode :param versions: The","only be allowed if the key's current version matches the version specified in","mount_point=mount_point, path=path) response = self._adapter.post( url=api_path, json=params, ) return response.json() def patch(self, path,","key's current version matches the version specified in the cas parameter. :type cas:","from being returned from reads, but the underlying data will not be removed.",":return: The response of the request. :rtype: requests.Response \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point,","to keep per key. If not set, the backend's configured max version is","normal get requests. :type versions: list of int :param mount_point: The \"path\" the","api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def delete_metadata_and_all_versions(self, path,","for the specified key. All version history will be removed. Supported methods: DELETE:","path: str | unicode :param cas: Set the \"cas\" value to use a","version as deleted and will stop it from being returned from reads, but",") def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Return a list of key names at the","mount_point=DEFAULT_MOUNT_POINT): \"\"\"Read the KV Version 2 configuration. Supported methods: GET: /auth/{mount_point}/config. Produces: 200","params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post(","URL. :type path: str | unicode :param versions: The versions to destroy. Their","path: Specifies the path of the secret to undelete. This is specified as","path. Supported methods: POST: /{mount_point}/delete/{path}. Produces: 204 (empty body) :param path: Specifies the","path: str | unicode :param mount_point: The \"path\" the secret engine was mounted","module.\"\"\" from hvac import exceptions, utils from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT = 'secret'","for the provided path from the key-value store. Supported methods: POST: /{mount_point}/destroy/{path}. Produces:","KvV2(VaultApiBase): \"\"\"KV Secrets Engine - Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \"\"\" def configure(self,","def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Configure backend level settings that are applied to","all version data for the specified key. All version history will be removed.",":type versions: list of int :param mount_point: The \"path\" the secret engine was","return response.json() def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the secret at the specified","url=api_path, ) return response.json() def update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Updates the max_versions","\"\"\"Undelete the data for the provided version and path in the key-value store.",":param versions: The versions to be deleted. The versioned data will not be","of the specified versions of the secret. This marks the versions as deleted","} if cas_required is not None: params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point)","str | unicode :return: The JSON response of the create_or_update_secret request. :rtype: dict","specified as part of the URL. :type path: str | unicode :param mount_point:","key's metadata setting can overwrite this value. Once a key has more than","patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) # Write back updated secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'],","path=path) return self._adapter.delete( url=api_path, ) def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft","it from being returned from reads, but the underlying data will not be","utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, params=params, ) return response.json() def create_or_update_secret(self,","\"{versions}\" provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path","\"secret\" dict will be stored and returned on read. :type secret: dict :param","requests. :type versions: int :param mount_point: The \"path\" the secret engine was mounted",":param secret: The contents of the \"secret\" dict will be stored and returned",":rtype: dict \"\"\" params = {} if version is not None: params['version'] =","the calling token must have an ACL policy granting the update capability. Supported","response of the request. :rtype: requests.Response \"\"\" params = { 'max_versions': max_versions, }","Supported methods: POST: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Path :type path:","provided path from the key-value store. Supported methods: POST: /{mount_point}/destroy/{path}. Produces: 204 (empty","cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Configure backend level settings that are applied to every key in","can be undone using the undelete path. Supported methods: POST: /{mount_point}/delete/{path}. Produces: 204","path: str | unicode :param max_versions: The number of versions to keep per","in the key-value store. Supported methods: POST: /{mount_point}/config. Produces: 204 (empty body) :param","of the request. :rtype: dict \"\"\" params = { 'options': {}, 'data': secret,","URL. :type path: str | unicode :param mount_point: The \"path\" the secret engine","deleted. Defaults to 10. :type max_versions: int :param cas_required: If true all keys","versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def","POST: /{mount_point}/undelete/{path}. Produces: 204 (empty body) :param path: Specifies the path of the","If not set the latest version is returned. :type version: int :param mount_point:","list containing one or more integers, \"{versions}\" provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg) params","create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Create a new version of a secret at",") raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point,","return self._adapter.post( url=api_path, json=params, ) def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Permanently remove the",":param versions: The versions to undelete. The versions will be restored and their","-*- coding: utf-8 -*- \"\"\"KvV2 methods module.\"\"\" from hvac import exceptions, utils from","reads, but the underlying data will not be removed. A delete can be","in key names. The values themselves are not accessible via this command. Supported","will be removed. Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path:","yet exist, the calling token must have an ACL policy granting the create",":type path: str | unicode :param cas: Set the \"cas\" value to use","if the key's current version matches the version specified in the cas parameter.","on all write requests. :type cas_required: bool :param mount_point: The \"path\" the secret","from hvac import exceptions, utils from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class","If false, the backend's configuration will be used. :type cas_required: bool :param mount_point:","204 (empty body) :param path: Specifies the path of the secret to delete.","hvac import exceptions, utils from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase):","the key-value store. This restores the data, allowing it to be returned on","the secret to destroy. This is specified as part of the URL. :type","version history will be removed. Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty body)","via this command. Supported methods: LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies","new version of a secret at the specified location. If the value does","Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \"\"\" def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Configure backend","configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Configure backend level settings that are applied to every","path: Path :type path: str | unicode :param secret: The contents of the","the KV Version 2 configuration. Supported methods: GET: /auth/{mount_point}/config. Produces: 200 application/json :param","self._adapter.get( url=api_path, ) return response.json() def update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Updates the","set to 0 a write will only be allowed if the key doesn't","all keys will require the cas parameter to be set on all write","the secret to undelete. This is specified as part of the URL. :type","to all keys, but a key's metadata setting can overwrite this value. Once","part of the URL. :type path: str | unicode :param versions: The versions","application/json :param path: Specifies the path of the secret to read. This is",") return response.json() def update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Updates the max_versions of","request. :rtype: dict \"\"\" # First, do a read. try: current_secret_version = self.read_secret_version(","| unicode :return: The JSON response of the request. :rtype: dict \"\"\" params","in normal get requests. :type versions: int :param mount_point: The \"path\" the secret","and numbers for the provided path from the key-value store. Supported methods: POST:","true all keys will require the cas parameter to be set on all","the cas parameter to be set on all write requests. :type cas_required: bool","key metadata and all version data for the specified key. All version history",":rtype: dict \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.list( url=api_path, )","versions for the secret at the specified path. Supported methods: GET: /{mount_point}/metadata/{path}. Produces:","permanently deleted. :type versions: list of int :param mount_point: The \"path\" the secret","not None: params['version'] = version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.get(","A delete can be undone using the undelete path. Supported methods: DELETE: /{mount_point}/data/{path}.","specified path. Supported methods: GET: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the","path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete","the specified version data and numbers for the provided path from the key-value","returned. :type version: int :param mount_point: The \"path\" the secret engine was mounted","utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Return","Supported methods: GET: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Specifies the path of","if version is not None: params['version'] = version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path)","unicode :return: The JSON response of the create_or_update_secret request. :rtype: dict \"\"\" #","version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, params=params, ) return","mount_point=mount_point, ) response = self._adapter.get(url=api_path) return response.json() def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve","the secret. This marks the versions as deleted and will stop them from","methods: DELETE: /{mount_point}/data/{path}. Produces: 204 (empty body) :param path: Specifies the path of","remove the specified version data and numbers for the provided path from the","param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path)","the specified versions of the secret. This marks the versions as deleted and","requests. :type versions: list of int :param mount_point: The \"path\" the secret engine","10. :type max_versions: int :param cas_required: If true all keys will require the","not None: params['options']['cas'] = cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.post(","response of the create_or_update_secret request. :rtype: dict \"\"\" # First, do a read.","Version 2 configuration. Supported methods: GET: /auth/{mount_point}/config. Produces: 200 application/json :param mount_point: The","Write back updated secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self,","params['max_versions'] = max_versions if cas_required is not None: if not isinstance(cas_required, bool): error_msg","JSON response of the create_or_update_secret request. :rtype: dict \"\"\" # First, do a","path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete of the secret's latest version at the","used. Once a key has more than the configured allowed versions the oldest","them from being returned from reads, but the underlying data will not be","versions to be deleted. The versioned data will not be deleted, but it","Engine - Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \"\"\" def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT):","cas_required is not None: params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post(","exists, the calling token must have an ACL policy granting the update capability.","parameter to be set on all write requests. If false, the backend's configuration","longer be returned in normal get requests. :type versions: int :param mount_point: The","existing path. Supported methods: POST: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Path","the URL. :type path: str | unicode :param version: Specifies the version to","ACL policy granting the create capability. If the value already exists, the calling","the path of the secret to destroy. This is specified as part of","0: error_msg = 'argument to \"versions\" must be a list containing one or","update capability. Supported methods: POST: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Path :type","numbers for the provided path from the key-value store. Supported methods: POST: /{mount_point}/destroy/{path}.",") def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete of the secret's latest","the key doesn't exist. If the index is non-zero the write will only","self.read_secret_version( path=path, mount_point=mount_point, ) except exceptions.InvalidPath: raise exceptions.InvalidPath('No value found at \"{path}\"; patch","= { 'max_versions': max_versions, } if cas_required is not None: params['cas_required'] = cas_required","(API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \"\"\" def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Configure backend level settings","'max_versions': max_versions, } if cas_required is not None: params['cas_required'] = cas_required api_path =","path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Return a list of key names at the specified location. Folders","the URL. :type path: str | unicode :param versions: The versions to be",":return: The JSON response of the request. :rtype: dict \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}',","unicode :return: The response of the request. :rtype: requests.Response \"\"\" params = {}","self._adapter.delete( url=api_path, ) def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete of","allowing it to be returned on get requests. Supported methods: POST: /{mount_point}/undelete/{path}. Produces:","input must be a folder; list on a file will not return a","methods: GET: /auth/{mount_point}/config. Produces: 200 application/json :param mount_point: The \"path\" the secret engine","path in the key-value store. This restores the data, allowing it to be","str | unicode :param versions: The versions to undelete. The versions will be","to destroy. This is specified as part of the URL. :type path: str","secret to undelete. This is specified as part of the URL. :type path:","the URL. :type path: str | unicode :param versions: The versions to destroy.","exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return","cas=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Create a new version of a secret at the specified location.","POST: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Path :type path: str | unicode",":return: The JSON response of the request. :rtype: dict \"\"\" api_path = utils.format_url(","patch only works on existing data.'.format(path=path)) # Update existing secret dict. patched_secret =","path of the secret to delete. This is specified as part of the","mount_point=mount_point, path=path) response = self._adapter.list( url=api_path, ) return response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT):","the version as deleted and will stop it from being returned from reads,","will only be allowed if the key doesn't exist. If the index is","an existing path. Supported methods: POST: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path:","folder; list on a file will not return a value. Note that no","= { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path,","error_msg = 'bool expected for cas_required param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] =","sensitive information in key names. The values themselves are not accessible via this","cas_required: If true the key will require the cas parameter to be set","\"\"\" params = { 'max_versions': max_versions, } if cas_required is not None: params['cas_required']","command. Supported methods: LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path","Produces: 200 application/json :param path: Specifies the path of the secrets to list.","/{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Path :type path: str | unicode","= utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path, json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Read the","returned on normal get requests. :type versions: list of int :param mount_point: The","be restored and their data will be returned on normal get requests. :type","received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post(","underlying data will not be removed. A delete can be undone using the","in the KV store without overwriting. :param path: Path :type path: str |",":param path: Specifies the path of the secret to read. This is specified","= 'bool expected for cas_required param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required","if not isinstance(versions, list) or len(versions) == 0: error_msg = 'argument to \"versions\"","dict :param mount_point: The \"path\" the secret engine was mounted on. :type mount_point:","= self._adapter.list( url=api_path, ) return response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the metadata","location. Folders are suffixed with /. The input must be a folder; list","# Write back updated secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def","JSON response of the request. :rtype: dict \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path)","not set, the backend's configured max version is used. Once a key has","version: Specifies the version to return. If not set the latest version is","# Update existing secret dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) # Write back updated","response of the request. :rtype: requests.Response \"\"\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return","the key-value store. Supported methods: POST: /{mount_point}/config. Produces: 204 (empty body) :param max_versions:","secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete of the","deleted. The versioned data will not be deleted, but it will no longer","response.json() def create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Create a new version of a","= 'secret' class KvV2(VaultApiBase): \"\"\"KV Secrets Engine - Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html","secret at the specified location. If the value does not yet exist, the",":return: The JSON response of the create_or_update_secret request. :rtype: dict \"\"\" # First,","This value applies to all keys, but a key's metadata setting can overwrite","response of the request. :rtype: dict \"\"\" api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, )","the secret's latest version at the specified location. This marks the version as","performed on keys; do not encode sensitive information in key names. The values","dict \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, ) return","= 'argument to \"versions\" must be a list containing one or more integers,","on an existing path. Supported methods: POST: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param","= self.read_secret_version( path=path, mount_point=mount_point, ) except exceptions.InvalidPath: raise exceptions.InvalidPath('No value found at \"{path}\";","deleted and will stop it from being returned from reads, but the underlying","if not isinstance(cas_required, bool): error_msg = 'bool expected for cas_required param, {type} received'.format(type=type(cas_required))","true the key will require the cas parameter to be set on all",") raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point,",") def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Read the KV Version 2 configuration. Supported methods: GET:","{type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return","part of the URL. :type path: str | unicode :param version: Specifies the","be undone using the undelete path. Supported methods: POST: /{mount_point}/delete/{path}. Produces: 204 (empty","value. Note that no policy-based filtering is performed on keys; do not encode","store. Supported methods: POST: /{mount_point}/config. Produces: 204 (empty body) :param max_versions: The number","params['options']['cas'] = cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.post( url=api_path, json=params,","at \"{path}\"; patch only works on existing data.'.format(path=path)) # Update existing secret dict.","an ACL policy granting the create capability. If the value already exists, the",":type max_versions: int :param cas_required: If true the key will require the cas","location. Supported methods: GET: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Specifies the path","are not accessible via this command. Supported methods: LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json","be allowed. If set to 0 a write will only be allowed if","the write will only be allowed if the key's current version matches the","to be set on all write requests. :type cas_required: bool :param mount_point: The","use a Check-And-Set operation. If not set the write will be allowed. If","the key's current version matches the version specified in the cas parameter. :type","not None: if not isinstance(cas_required, bool): error_msg = 'bool expected for cas_required param,","overwrite this value. Once a key has more than the configured allowed versions","utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Delete","on. :type mount_point: str | unicode :return: The JSON response of the request.","delete. This is specified as part of the URL. :type path: str |","mount_point=mount_point, ) def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete of the secret's","The versions to destroy. Their data will be permanently deleted. :type versions: list","= {} if max_versions is not None: params['max_versions'] = max_versions if cas_required is","number of versions to keep per key. This value applies to all keys,","path: Specifies the path of the secret to read. This is specified as","key names. The values themselves are not accessible via this command. Supported methods:","if the key doesn't exist. If the index is non-zero the write will","api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def undelete_secret_versions(self, path,","the latest version is returned. :type version: int :param mount_point: The \"path\" the","Specifies the path of the secret to delete. This is specified as part","the cas parameter to be set on all write requests. If false, the","2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \"\"\" def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Configure backend level","Supported methods: DELETE: /{mount_point}/data/{path}. Produces: 204 (empty body) :param path: Specifies the path","json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Read the KV Version 2 configuration. Supported methods:","path of the secret to undelete. This is specified as part of the","ACL policy granting the update capability. Supported methods: POST: /{mount_point}/data/{path}. Produces: 200 application/json","url=api_path, json=params, ) def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Return a list of key names","204 (empty body) :param path: Specifies the path of the secret to destroy.","secret dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) # Write back updated secret. return self.create_or_update_secret(","key. All version history will be removed. Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204","value found at \"{path}\"; patch only works on existing data.'.format(path=path)) # Update existing","from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase): \"\"\"KV Secrets Engine -","request. :rtype: dict \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.list( url=api_path,","calling token must have an ACL policy granting the create capability. If the","raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path,","secret: dict :param mount_point: The \"path\" the secret engine was mounted on. :type","\"\"\"Return a list of key names at the specified location. Folders are suffixed",") except exceptions.InvalidPath: raise exceptions.InvalidPath('No value found at \"{path}\"; patch only works on","data.'.format(path=path)) # Update existing secret dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) # Write back","write requests. :type cas_required: bool :param mount_point: The \"path\" the secret engine was",") def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Delete (permanently) the key metadata and all version","undone using the undelete path. Supported methods: DELETE: /{mount_point}/data/{path}. Produces: 204 (empty body)","must be a folder; list on a file will not return a value.","value. Once a key has more than the configured allowed versions the oldest","versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def","it will no longer be returned in normal get requests. :type versions: int","write will only be allowed if the key doesn't exist. If the index","A delete can be undone using the undelete path. Supported methods: POST: /{mount_point}/delete/{path}.","will be permanently deleted. Defaults to 10. :type max_versions: int :param cas_required: If","the \"cas\" value to use a Check-And-Set operation. If not set the write","try: current_secret_version = self.read_secret_version( path=path, mount_point=mount_point, ) except exceptions.InvalidPath: raise exceptions.InvalidPath('No value found","response.json() def update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Updates the max_versions of cas_required setting","versions: list of int :param mount_point: The \"path\" the secret engine was mounted","methods: POST: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Path :type path: str","every key in the key-value store. Supported methods: POST: /{mount_point}/config. Produces: 204 (empty","max version is used. Once a key has more than the configured allowed","is not None: params['version'] = version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response =","on all write requests. If false, the backend's configuration will be used. :type","def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Undelete the data for the provided version and","mount_point=DEFAULT_MOUNT_POINT): \"\"\"Permanently remove the specified version data and numbers for the provided path","All version history will be removed. Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty","of the request. :rtype: requests.Response \"\"\" if not isinstance(versions, list) or len(versions) ==","keep per key. This value applies to all keys, but a key's metadata","self._adapter.get(url=api_path) return response.json() def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the secret at the","If the value already exists, the calling token must have an ACL policy","to 10. :type max_versions: int :param cas_required: If true all keys will require","application/json :param mount_point: The \"path\" the secret engine was mounted on. :type mount_point:","delete of the specified versions of the secret. This marks the versions as","If not set the write will be allowed. If set to 0 a","path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete of the specified versions of the","data will not be removed. A delete can be undone using the undelete","mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Return a","path=path) return self._adapter.post( url=api_path, json=params, ) def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Undelete the","will be allowed. If set to 0 a write will only be allowed","The response of the request. :rtype: requests.Response \"\"\" params = {} if max_versions","an ACL policy granting the update capability. Supported methods: POST: /{mount_point}/data/{path}. Produces: 200","methods: POST: /{mount_point}/config. Produces: 204 (empty body) :param max_versions: The number of versions","response of the request. :rtype: requests.Response \"\"\" params = {} if max_versions is","back updated secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self, path,","destroy. Their data will be permanently deleted. :type versions: list of int :param","str | unicode :param secret: The contents of the \"secret\" dict will be","encode sensitive information in key names. The values themselves are not accessible via",":type cas_required: bool :param mount_point: The \"path\" the secret engine was mounted on.","JSON response of the request. :rtype: dict \"\"\" params = { 'options': {},","| unicode :param versions: The versions to destroy. Their data will be permanently","not be deleted, but it will no longer be returned in normal get","versions the oldest version will be permanently deleted. :type max_versions: int :param cas_required:","part of the URL. :type path: str | unicode :param mount_point: The \"path\"","return self._adapter.post( url=api_path, json=params, ) def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Undelete the data","specified as part of the URL. :type path: str | unicode :param version:","= version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, params=params, )","on a file will not return a value. Note that no policy-based filtering","specified location. This marks the version as deleted and will stop it from","the request. :rtype: dict \"\"\" params = { 'options': {}, 'data': secret, }","of the request. :rtype: requests.Response \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.delete(","application/json :param path: Path :type path: str | unicode :param cas: Set the","mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete of the secret's latest version at the specified",":param path: Specifies the path of the secret to destroy. This is specified","not be removed. A delete can be undone using the undelete path. Supported","The contents of the \"secret\" dict will be stored and returned on read.","the specified location. If the value does not yet exist, the calling token","at the specified location. This marks the version as deleted and will stop","Specifies the path of the secrets to list. This is specified as part","mounted on. :type mount_point: str | unicode :return: The response of the request.","backend's configured max version is used. Once a key has more than the","POST: /{mount_point}/config. Produces: 204 (empty body) :param max_versions: The number of versions to","the undelete path. Supported methods: DELETE: /{mount_point}/data/{path}. Produces: 204 (empty body) :param path:","engine was mounted on. :type mount_point: str | unicode :return: The response of","= utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response = self._adapter.get(url=api_path) return response.json() def read_secret_version(self, path,","def create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Create a new version of a secret","hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase): \"\"\"KV Secrets Engine - Version","url=api_path, params=params, ) return response.json() def create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Create a","only be allowed if the key doesn't exist. If the index is non-zero","If not set, the backend's configured max version is used. Once a key","deleted. :type max_versions: int :param cas_required: If true the key will require the","/{mount_point}/config. Produces: 204 (empty body) :param max_versions: The number of versions to keep","\"\"\" params = {} if max_versions is not None: params['max_versions'] = max_versions if","be a list containing one or more integers, \"{versions}\" provided.'.format( versions=versions ) raise","The \"path\" the secret engine was mounted on. :type mount_point: str | unicode","url=api_path, ) return response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the metadata and versions","-*- \"\"\"KvV2 methods module.\"\"\" from hvac import exceptions, utils from hvac.api.vault_api_base import VaultApiBase","list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Return a list of key names at the specified location.","key names at the specified location. Folders are suffixed with /. The input","of the URL. :type path: str | unicode :param mount_point: The \"path\" the","token must have an ACL policy granting the update capability. Supported methods: POST:","accessible via this command. Supported methods: LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path:","class KvV2(VaultApiBase): \"\"\"KV Secrets Engine - Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \"\"\" def","response.json() def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Set or update data in the KV","set on all write requests. :type cas_required: bool :param mount_point: The \"path\" the",":param path: Specifies the path of the secrets to list. This is specified","\"\"\"Retrieve the metadata and versions for the secret at the specified path. Supported","data will be returned on normal get requests. :type versions: list of int","unicode :param version: Specifies the version to return. If not set the latest","must have an ACL policy granting the create capability. If the value already","(empty body) :param max_versions: The number of versions to keep per key. This","The versions will be restored and their data will be returned on normal","Check-And-Set operation. If not set the write will be allowed. If set to","restored and their data will be returned on normal get requests. :type versions:","requests. If false, the backend's configuration will be used. :type cas_required: bool :param","\"\"\"Permanently remove the specified version data and numbers for the provided path from","allowed versions the oldest version will be permanently deleted. :type max_versions: int :param","of the URL. :type path: str | unicode :param version: Specifies the version","are applied to every key in the key-value store. Supported methods: POST: /{mount_point}/config.","non-zero the write will only be allowed if the key's current version matches","a read. try: current_secret_version = self.read_secret_version( path=path, mount_point=mount_point, ) except exceptions.InvalidPath: raise exceptions.InvalidPath('No","value does not yet exist, the calling token must have an ACL policy","KV store without overwriting. :param path: Path :type path: str | unicode :param","\"\"\"Issue a soft delete of the specified versions of the secret. This marks","request. :rtype: dict \"\"\" params = {} if version is not None: params['version']","= utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT):","all write requests. If false, the backend's configuration will be used. :type cas_required:",":rtype: requests.Response \"\"\" params = { 'max_versions': max_versions, } if cas_required is not","list of key names at the specified location. Folders are suffixed with /.","cas_required is not None: if not isinstance(cas_required, bool): error_msg = 'bool expected for","be set on all write requests. If false, the backend's configuration will be","for the secret at the specified path. Supported methods: GET: /{mount_point}/metadata/{path}. Produces: 200","Path :type path: str | unicode :param secret: The contents of the \"secret\"","exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return","url=api_path, json=params, ) def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Delete (permanently) the key metadata and","read. try: current_secret_version = self.read_secret_version( path=path, mount_point=mount_point, ) except exceptions.InvalidPath: raise exceptions.InvalidPath('No value","Supported methods: POST: /{mount_point}/undelete/{path}. Produces: 204 (empty body) :param path: Specifies the path","path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Undelete the data for the provided version and path in","specified location. If the value does not yet exist, the calling token must","cas_required: If true all keys will require the cas parameter to be set","and will stop it from being returned from reads, but the underlying data","undelete. This is specified as part of the URL. :type path: str |","methods: POST: /{mount_point}/destroy/{path}. Produces: 204 (empty body) :param path: Specifies the path of","# First, do a read. try: current_secret_version = self.read_secret_version( path=path, mount_point=mount_point, ) except","only works on existing data.'.format(path=path)) # Update existing secret dict. patched_secret = current_secret_version['data']['data']","/{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Specifies the path of the secret","If the value does not yet exist, the calling token must have an","the path of the secret to delete. This is specified as part of","url=api_path, json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Read the KV Version 2 configuration. Supported","request. :rtype: dict \"\"\" params = { 'options': {}, 'data': secret, } if","must be a list containing one or more integers, \"{versions}\" provided.'.format( versions=versions )","secret engine was mounted on. :type mount_point: str | unicode :return: The JSON","| unicode :return: The response of the request. :rtype: requests.Response \"\"\" api_path =","of the request. :rtype: requests.Response \"\"\" params = {} if max_versions is not","params=params, ) return response.json() def create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Create a new","from the key-value store. Supported methods: POST: /{mount_point}/destroy/{path}. Produces: 204 (empty body) :param","cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Updates the max_versions of cas_required setting on an existing path. Supported","of the URL. :type path: str | unicode :param versions: The versions to","dict \"\"\" api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response = self._adapter.get(url=api_path) return response.json()","of the request. :rtype: requests.Response \"\"\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete(","the data, allowing it to be returned on get requests. Supported methods: POST:","return a value. Note that no policy-based filtering is performed on keys; do","path=path) return self._adapter.post( url=api_path, json=params, ) def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Return a list","Folders are suffixed with /. The input must be a folder; list on","marks the versions as deleted and will stop them from being returned from","be undone using the undelete path. Supported methods: DELETE: /{mount_point}/data/{path}. Produces: 204 (empty","the configured allowed versions the oldest version will be permanently deleted. :type max_versions:","will be permanently deleted. :type max_versions: int :param cas_required: If true the key","not isinstance(cas_required, bool): error_msg = 'bool expected for cas_required param, {type} received'.format(type=type(cas_required)) raise","get requests. :type versions: list of int :param mount_point: The \"path\" the secret","key-value store. Supported methods: POST: /{mount_point}/destroy/{path}. Produces: 204 (empty body) :param path: Specifies","mount_point: The \"path\" the secret engine was mounted on. :type mount_point: str |","path=path) response = self._adapter.get( url=api_path, params=params, ) return response.json() def create_or_update_secret(self, path, secret,","must have an ACL policy granting the update capability. Supported methods: POST: /{mount_point}/data/{path}.",") return response.json() def create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Create a new version","LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path of the secrets","the specified location. Folders are suffixed with /. The input must be a","but it will no longer be returned in normal get requests. :type versions:","allowed if the key's current version matches the version specified in the cas","'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, )","= { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path,","on get requests. Supported methods: POST: /{mount_point}/undelete/{path}. Produces: 204 (empty body) :param path:","value applies to all keys, but a key's metadata setting can overwrite this","a write will only be allowed if the key doesn't exist. If the","version matches the version specified in the cas parameter. :type cas: int :param","utils from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase): \"\"\"KV Secrets Engine","for the provided version and path in the key-value store. This restores the","Specifies the path of the secret to read. This is specified as part",":type path: str | unicode :param versions: The versions to undelete. The versions","methods: LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path of the","is performed on keys; do not encode sensitive information in key names. The","key will require the cas parameter to be set on all write requests.","the secret engine was mounted on. :type mount_point: str | unicode :return: The","the oldest version will be permanently deleted. :type max_versions: int :param cas_required: If","versions to keep per key. If not set, the backend's configured max version","a list of key names at the specified location. Folders are suffixed with","key in the key-value store. Supported methods: POST: /{mount_point}/config. Produces: 204 (empty body)","methods: POST: /{mount_point}/delete/{path}. Produces: 204 (empty body) :param path: Specifies the path of","set on all write requests. If false, the backend's configuration will be used.","be permanently deleted. :type max_versions: int :param cas_required: If true the key will","int :param secret: The contents of the \"secret\" dict will be stored and","unicode :return: The response of the request. :rtype: requests.Response \"\"\" api_path = utils.format_url('/v1/{mount_point}/data/{path}',","secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Create a new version of a secret at the specified","of the secret to read. This is specified as part of the URL.","int :param cas_required: If true all keys will require the cas parameter to","versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Permanently remove the specified version data and numbers for the provided","a folder; list on a file will not return a value. Note that","mount_point=DEFAULT_MOUNT_POINT): \"\"\"Undelete the data for the provided version and path in the key-value","secret to read. This is specified as part of the URL. :type path:","api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, params=params, ) return response.json()","already exists, the calling token must have an ACL policy granting the update","0 a write will only be allowed if the key doesn't exist. If","will require the cas parameter to be set on all write requests. If","data for the specified key. All version history will be removed. Supported methods:","cas: int :param secret: The contents of the \"secret\" dict will be stored","is not None: params['max_versions'] = max_versions if cas_required is not None: if not","def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete of the secret's latest version","of the secret to destroy. This is specified as part of the URL.","The response of the request. :rtype: requests.Response \"\"\" if not isinstance(versions, list) or","methods: GET: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path of the","unicode :param versions: The versions to destroy. Their data will be permanently deleted.","normal get requests. :type versions: int :param mount_point: The \"path\" the secret engine","response = self._adapter.get( url=api_path, ) return response.json() def update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT):","versions will be restored and their data will be returned on normal get",":rtype: dict \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, )","unicode :param versions: The versions to undelete. The versions will be restored and",":rtype: requests.Response \"\"\" params = {} if max_versions is not None: params['max_versions'] =","removed. A delete can be undone using the undelete path. Supported methods: POST:","version specified in the cas parameter. :type cas: int :param secret: The contents","path: str | unicode :param versions: The versions to undelete. The versions will","can overwrite this value. Once a key has more than the configured allowed","to be deleted. The versioned data will not be deleted, but it will","= { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path,","200 application/json :param path: Path :type path: str | unicode :param cas: Set","latest version is returned. :type version: int :param mount_point: The \"path\" the secret","of the request. :rtype: requests.Response \"\"\" params = { 'max_versions': max_versions, } if","Produces: 204 (empty body) :param path: Path :type path: str | unicode :param","on. :type mount_point: str | unicode :return: The response of the request. :rtype:","not None: params['max_versions'] = max_versions if cas_required is not None: if not isinstance(cas_required,","= cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def","return self._adapter.post( url=api_path, json=params, ) def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Delete (permanently) the key","create capability. If the value already exists, the calling token must have an","be allowed if the key's current version matches the version specified in the","cas parameter to be set on all write requests. :type cas_required: bool :param","of cas_required setting on an existing path. Supported methods: POST: /{mount_point}/metadata/{path}. Produces: 204","provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path =","history will be removed. Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param","cas_required setting on an existing path. Supported methods: POST: /{mount_point}/metadata/{path}. Produces: 204 (empty",":type mount_point: str | unicode :return: The JSON response of the create_or_update_secret request.","= utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, params=params, ) return response.json() def","exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params,","methods: POST: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Path :type path: str |","be allowed if the key doesn't exist. If the index is non-zero the","response of the request. :rtype: dict \"\"\" params = {} if version is","as deleted and will stop it from being returned from reads, but the","one or more integers, \"{versions}\" provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg) params = {","self._adapter.post( url=api_path, json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Read the KV Version 2 configuration.","path: Specifies the path of the secrets to list. This is specified as","\"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.list( url=api_path, ) return response.json()","using the undelete path. Supported methods: POST: /{mount_point}/delete/{path}. Produces: 204 (empty body) :param","Defaults to 10. :type max_versions: int :param cas_required: If true all keys will","| unicode :return: The JSON response of the create_or_update_secret request. :rtype: dict \"\"\"","\"\"\" if not isinstance(versions, list) or len(versions) == 0: error_msg = 'argument to","no policy-based filtering is performed on keys; do not encode sensitive information in","secret, } if cas is not None: params['options']['cas'] = cas api_path = utils.format_url('/v1/{mount_point}/data/{path}',","'argument to \"versions\" must be a list containing one or more integers, \"{versions}\"","per key. This value applies to all keys, but a key's metadata setting","does not yet exist, the calling token must have an ACL policy granting","parameter. :type cas: int :param secret: The contents of the \"secret\" dict will","url=api_path, json=params, ) def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Undelete the data for the","return response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the metadata and versions for the","params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path, json=params, ) def","GET: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Specifies the path of the secret","return self._adapter.post( url=api_path, json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Read the KV Version 2","marks the version as deleted and will stop it from being returned from","If the index is non-zero the write will only be allowed if the","delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete of the specified versions of","secrets to list. This is specified as part of the URL. :type path:","false, the backend's configuration will be used. :type cas_required: bool :param mount_point: The","request. :rtype: requests.Response \"\"\" params = {} if max_versions is not None: params['max_versions']",":return: The response of the request. :rtype: requests.Response \"\"\" params = { 'max_versions':","path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Delete (permanently) the key metadata and all version data for the","str | unicode :return: The response of the request. :rtype: requests.Response \"\"\" if","to destroy. Their data will be permanently deleted. :type versions: list of int","update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Updates the max_versions of cas_required setting on an","without overwriting. :param path: Path :type path: str | unicode :param secret: The","secret at the specified location. Supported methods: GET: /{mount_point}/data/{path}. Produces: 200 application/json :param","a Check-And-Set operation. If not set the write will be allowed. If set","response of the request. :rtype: requests.Response \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return","\"\"\"Set or update data in the KV store without overwriting. :param path: Path","2 configuration. Supported methods: GET: /auth/{mount_point}/config. Produces: 200 application/json :param mount_point: The \"path\"","\"\"\"Configure backend level settings that are applied to every key in the key-value","URL. :type path: str | unicode :param versions: The versions to undelete. The","path=path) return self._adapter.post( url=api_path, json=params, ) def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Permanently remove",":return: The response of the request. :rtype: requests.Response \"\"\" if not isinstance(versions, list)","allowed if the key doesn't exist. If the index is non-zero the write","names. The values themselves are not accessible via this command. Supported methods: LIST:","'secret' class KvV2(VaultApiBase): \"\"\"KV Secrets Engine - Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \"\"\"","{ 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params,","mount_point=DEFAULT_MOUNT_POINT): \"\"\"Set or update data in the KV store without overwriting. :param path:","= utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def destroy_secret_versions(self, path, versions,","path, version=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the secret at the specified location. Supported methods: GET:","return self._adapter.post( url=api_path, json=params, ) def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Return a list of","the URL. :type path: str | unicode :param mount_point: The \"path\" the secret","the metadata and versions for the secret at the specified path. Supported methods:","do not encode sensitive information in key names. The values themselves are not","the provided version and path in the key-value store. This restores the data,","{}, 'data': secret, } if cas is not None: params['options']['cas'] = cas api_path","\"path\" the secret engine was mounted on. :type mount_point: str | unicode :return:","for cas_required param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}',","this command. Supported methods: LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the","keys will require the cas parameter to be set on all write requests.","'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, )","exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return","def update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Updates the max_versions of cas_required setting on","operation. If not set the write will be allowed. If set to 0","versions the oldest version will be permanently deleted. Defaults to 10. :type max_versions:","that no policy-based filtering is performed on keys; do not encode sensitive information","path: Path :type path: str | unicode :param cas: Set the \"cas\" value","be deleted, but it will no longer be returned in normal get requests.","= utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.list( url=api_path, ) return response.json() def read_secret_metadata(self,","mounted on. :type mount_point: str | unicode :return: The JSON response of the","Produces: 200 application/json :param mount_point: The \"path\" the secret engine was mounted on.","{ 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params,","methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Specifies the path of","applied to every key in the key-value store. Supported methods: POST: /{mount_point}/config. Produces:","get requests. Supported methods: POST: /{mount_point}/undelete/{path}. Produces: 204 (empty body) :param path: Specifies","is not None: params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path,","cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path, json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT):","read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the secret at the specified location. Supported methods:","specified location. Supported methods: GET: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Specifies the","of the secret to undelete. This is specified as part of the URL.","of versions to keep per key. This value applies to all keys, but","path=path) response = self._adapter.list( url=api_path, ) return response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve","versions to destroy. Their data will be permanently deleted. :type versions: list of","max_versions: The number of versions to keep per key. If not set, the","unicode :param max_versions: The number of versions to keep per key. If not","mount_point=DEFAULT_MOUNT_POINT): \"\"\"Updates the max_versions of cas_required setting on an existing path. Supported methods:","200 application/json :param path: Specifies the path of the secret to read. This","version at the specified location. This marks the version as deleted and will","parameter to be set on all write requests. :type cas_required: bool :param mount_point:","self._adapter.post( url=api_path, json=params, ) def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Return a list of key","Specifies the path of the secret to destroy. This is specified as part","{ 'options': {}, 'data': secret, } if cas is not None: params['options']['cas'] =","Produces: 200 application/json :param path: Path :type path: str | unicode :param cas:","read. This is specified as part of the URL. :type path: str |","index is non-zero the write will only be allowed if the key's current","names at the specified location. Folders are suffixed with /. The input must","- Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \"\"\" def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Configure","utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.list( url=api_path, ) return response.json() def read_secret_metadata(self, path,","dict \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.list( url=api_path, ) return","backend's configuration will be used. :type cas_required: bool :param mount_point: The \"path\" the","requests.Response \"\"\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, ) def delete_secret_versions(self,","response = self._adapter.list( url=api_path, ) return response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Retrieve the","str | unicode :param versions: The versions to destroy. Their data will be",":type max_versions: int :param cas_required: If true all keys will require the cas","https://www.vaultproject.io/api/secret/kv/kv-v2.html \"\"\" def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Configure backend level settings that are","api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def list_secrets(self, path,","DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase): \"\"\"KV Secrets Engine - Version 2 (API). Reference:","but a key's metadata setting can overwrite this value. Once a key has","to \"versions\" must be a list containing one or more integers, \"{versions}\" provided.'.format(","the secret to delete. This is specified as part of the URL. :type","The JSON response of the request. :rtype: dict \"\"\" params = {} if","secret at the specified path. Supported methods: GET: /{mount_point}/metadata/{path}. Produces: 200 application/json :param","'data': secret, } if cas is not None: params['options']['cas'] = cas api_path =","the update capability. Supported methods: POST: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Path","of the secret. This marks the versions as deleted and will stop them","= cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path, json=params, ) def read_configuration(self,","configured max version is used. Once a key has more than the configured","matches the version specified in the cas parameter. :type cas: int :param secret:","request. :rtype: requests.Response \"\"\" if not isinstance(versions, list) or len(versions) == 0: error_msg","import VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase): \"\"\"KV Secrets Engine - Version 2","cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.post( url=api_path, json=params, ) return","= cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.post( url=api_path, json=params, )","Secrets Engine - Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \"\"\" def configure(self, max_versions=10, cas_required=None,",") return response.json() def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Set or update data in","returned on get requests. Supported methods: POST: /{mount_point}/undelete/{path}. Produces: 204 (empty body) :param","the specified location. Supported methods: GET: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Specifies","filtering is performed on keys; do not encode sensitive information in key names.","| unicode :param max_versions: The number of versions to keep per key. If","str | unicode :param max_versions: The number of versions to keep per key.","settings that are applied to every key in the key-value store. Supported methods:","of the \"secret\" dict will be stored and returned on read. :type secret:","set the write will be allowed. If set to 0 a write will","all write requests. :type cas_required: bool :param mount_point: The \"path\" the secret engine","methods: GET: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Specifies the path of the","utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response = self._adapter.get(url=api_path) return response.json() def read_secret_version(self, path, version=None,","value already exists, the calling token must have an ACL policy granting the","= utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.post( url=api_path, json=params, ) return response.json() def","the configured allowed versions the oldest version will be permanently deleted. Defaults to","== 0: error_msg = 'argument to \"versions\" must be a list containing one","None: params['max_versions'] = max_versions if cas_required is not None: if not isinstance(cas_required, bool):","permanently deleted. :type max_versions: int :param cas_required: If true the key will require","unicode :param versions: The versions to be deleted. The versioned data will not",":param mount_point: The \"path\" the secret engine was mounted on. :type mount_point: str","This marks the version as deleted and will stop it from being returned","url=api_path, ) def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete of the","not encode sensitive information in key names. The values themselves are not accessible","on. :type mount_point: str | unicode :return: The JSON response of the create_or_update_secret","The JSON response of the request. :rtype: dict \"\"\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point,","requests.Response \"\"\" params = {} if max_versions is not None: params['max_versions'] = max_versions","to delete. This is specified as part of the URL. :type path: str"],"string":"[\n \"delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete of the secret's latest version at\",\n \"int :param cas_required: If true the key will require the cas parameter to\",\n \"str | unicode :return: The response of the request. :rtype: requests.Response \\\"\\\"\\\" params\",\n \"\\\"\\\"\\\"Read the KV Version 2 configuration. Supported methods: GET: /auth/{mount_point}/config. Produces: 200 application/json\",\n \"\\\"\\\"\\\" api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response = self._adapter.get(url=api_path) return response.json() def\",\n \"not yet exist, the calling token must have an ACL policy granting the\",\n \"= utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, ) return response.json() def update_metadata(self,\",\n \"\\\"{path}\\\"; patch only works on existing data.'.format(path=path)) # Update existing secret dict. patched_secret\",\n \"utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.post( url=api_path, json=params, ) return response.json() def patch(self,\",\n \"get requests. :type versions: int :param mount_point: The \\\"path\\\" the secret engine was\",\n \"path. Supported methods: GET: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path\",\n \"requests. Supported methods: POST: /{mount_point}/undelete/{path}. Produces: 204 (empty body) :param path: Specifies the\",\n \"version: int :param mount_point: The \\\"path\\\" the secret engine was mounted on. :type\",\n \"versioned data will not be deleted, but it will no longer be returned\",\n \"is non-zero the write will only be allowed if the key's current version\",\n \"| unicode :param mount_point: The \\\"path\\\" the secret engine was mounted on. :type\",\n \"stop them from being returned from reads, but the underlying data will not\",\n \"error_msg = 'argument to \\\"versions\\\" must be a list containing one or more\",\n \"exceptions, utils from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase): \\\"\\\"\\\"KV Secrets\",\n \"\\\"versions\\\" must be a list containing one or more integers, \\\"{versions}\\\" provided.'.format( versions=versions\",\n \"expected for cas_required param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path =\",\n \"version is returned. :type version: int :param mount_point: The \\\"path\\\" the secret engine\",\n \"of the create_or_update_secret request. :rtype: dict \\\"\\\"\\\" # First, do a read. try:\",\n \"cas_required param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point,\",\n \"the KV store without overwriting. :param path: Path :type path: str | unicode\",\n \"and their data will be returned on normal get requests. :type versions: list\",\n \":type mount_point: str | unicode :return: The JSON response of the request. :rtype:\",\n \"The response of the request. :rtype: requests.Response \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path)\",\n \"version of a secret at the specified location. If the value does not\",\n \"configuration. Supported methods: GET: /auth/{mount_point}/config. Produces: 200 application/json :param mount_point: The \\\"path\\\" the\",\n \"= utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, ) def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT):\",\n \"be stored and returned on read. :type secret: dict :param mount_point: The \\\"path\\\"\",\n \"params = {} if version is not None: params['version'] = version api_path =\",\n \"/{mount_point}/data/{path}. Produces: 200 application/json :param path: Specifies the path of the secret to\",\n \"of a secret at the specified location. If the value does not yet\",\n \"/{mount_point}/undelete/{path}. Produces: 204 (empty body) :param path: Specifies the path of the secret\",\n \"response of the request. :rtype: requests.Response \\\"\\\"\\\" if not isinstance(versions, list) or len(versions)\",\n \"dict \\\"\\\"\\\" # First, do a read. try: current_secret_version = self.read_secret_version( path=path, mount_point=mount_point,\",\n \"json=params, ) def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Permanently remove the specified version data\",\n \"keep per key. If not set, the backend's configured max version is used.\",\n \"return response.json() def create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Create a new version of\",\n \"version to return. If not set the latest version is returned. :type version:\",\n \":param cas_required: If true all keys will require the cas parameter to be\",\n \"but the underlying data will not be removed. A delete can be undone\",\n \"is returned. :type version: int :param mount_point: The \\\"path\\\" the secret engine was\",\n \"delete of the secret's latest version at the specified location. This marks the\",\n \"json=params, ) def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Return a list of key names at\",\n \"the request. :rtype: requests.Response \\\"\\\"\\\" params = {} if max_versions is not None:\",\n \"| unicode :param versions: The versions to be deleted. The versioned data will\",\n \":param path: Path :type path: str | unicode :param secret: The contents of\",\n \"read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the metadata and versions for the secret at the\",\n \"a list containing one or more integers, \\\"{versions}\\\" provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg)\",\n \"isinstance(versions, list) or len(versions) == 0: error_msg = 'argument to \\\"versions\\\" must be\",\n \"stored and returned on read. :type secret: dict :param mount_point: The \\\"path\\\" the\",\n \"or update data in the KV store without overwriting. :param path: Path :type\",\n \"utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, ) return response.json() def update_metadata(self, path,\",\n \"request. :rtype: dict \\\"\\\"\\\" api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response = self._adapter.get(url=api_path)\",\n \":param path: Path :type path: str | unicode :param max_versions: The number of\",\n \"\\\"\\\"\\\" params = { 'options': {}, 'data': secret, } if cas is not\",\n \"configured allowed versions the oldest version will be permanently deleted. Defaults to 10.\",\n \":param path: Specifies the path of the secret to delete. This is specified\",\n \"in the cas parameter. :type cas: int :param secret: The contents of the\",\n \"to be returned on get requests. Supported methods: POST: /{mount_point}/undelete/{path}. Produces: 204 (empty\",\n \"\\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, ) return response.json()\",\n \"the request. :rtype: dict \\\"\\\"\\\" params = {} if version is not None:\",\n \"the index is non-zero the write will only be allowed if the key's\",\n \"bool :param mount_point: The \\\"path\\\" the secret engine was mounted on. :type mount_point:\",\n \"mount_point: str | unicode :return: The JSON response of the create_or_update_secret request. :rtype:\",\n \"max_versions is not None: params['max_versions'] = max_versions if cas_required is not None: if\",\n \"backend level settings that are applied to every key in the key-value store.\",\n \"Once a key has more than the configured allowed versions the oldest version\",\n \"this value. Once a key has more than the configured allowed versions the\",\n \"params = {} if max_versions is not None: params['max_versions'] = max_versions if cas_required\",\n \"value to use a Check-And-Set operation. If not set the write will be\",\n \"mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Delete (permanently) the key metadata and all version data for the specified\",\n \"if cas_required is not None: if not isinstance(cas_required, bool): error_msg = 'bool expected\",\n \"list of int :param mount_point: The \\\"path\\\" the secret engine was mounted on.\",\n \"<filename>hvac/api/secrets_engines/kv_v2.py #!/usr/bin/env python # -*- coding: utf-8 -*- \\\"\\\"\\\"KvV2 methods module.\\\"\\\"\\\" from hvac\",\n \"200 application/json :param mount_point: The \\\"path\\\" the secret engine was mounted on. :type\",\n \"versions: The versions to be deleted. The versioned data will not be deleted,\",\n \"mount_point: str | unicode :return: The JSON response of the request. :rtype: dict\",\n \"not set the latest version is returned. :type version: int :param mount_point: The\",\n \"of the request. :rtype: dict \\\"\\\"\\\" api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response\",\n \"permanently deleted. Defaults to 10. :type max_versions: int :param cas_required: If true all\",\n \"def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Delete (permanently) the key metadata and all version data\",\n \"store without overwriting. :param path: Path :type path: str | unicode :param secret:\",\n \"versions: The versions to destroy. Their data will be permanently deleted. :type versions:\",\n \"of key names at the specified location. Folders are suffixed with /. The\",\n \"url=api_path, json=params, ) return response.json() def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Set or update\",\n \"will not be deleted, but it will no longer be returned in normal\",\n \":type path: str | unicode :param version: Specifies the version to return. If\",\n \"updated secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT):\",\n \"be removed. Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Specifies\",\n \"will be permanently deleted. :type versions: list of int :param mount_point: The \\\"path\\\"\",\n \") def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Permanently remove the specified version data and\",\n \"{} if max_versions is not None: params['max_versions'] = max_versions if cas_required is not\",\n \"version and path in the key-value store. This restores the data, allowing it\",\n \"\\\"\\\"\\\"Retrieve the secret at the specified location. Supported methods: GET: /{mount_point}/data/{path}. Produces: 200\",\n \"response.json() def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the secret at the specified location.\",\n \"'options': {}, 'data': secret, } if cas is not None: params['options']['cas'] = cas\",\n \"path: Path :type path: str | unicode :param max_versions: The number of versions\",\n \"returned in normal get requests. :type versions: int :param mount_point: The \\\"path\\\" the\",\n \":return: The JSON response of the request. :rtype: dict \\\"\\\"\\\" params = {}\",\n \"as part of the URL. :type path: str | unicode :param mount_point: The\",\n \"the secret at the specified path. Supported methods: GET: /{mount_point}/metadata/{path}. Produces: 200 application/json\",\n \"and returned on read. :type secret: dict :param mount_point: The \\\"path\\\" the secret\",\n \"dict \\\"\\\"\\\" params = { 'options': {}, 'data': secret, } if cas is\",\n \"the key metadata and all version data for the specified key. All version\",\n \"if max_versions is not None: params['max_versions'] = max_versions if cas_required is not None:\",\n \"keys; do not encode sensitive information in key names. The values themselves are\",\n \"the request. :rtype: dict \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.get(\",\n \"require the cas parameter to be set on all write requests. :type cas_required:\",\n \") response = self._adapter.get(url=api_path) return response.json() def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the\",\n \"works on existing data.'.format(path=path)) # Update existing secret dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret)\",\n \"body) :param path: Specifies the path of the secret to delete. This is\",\n \"methods module.\\\"\\\"\\\" from hvac import exceptions, utils from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT =\",\n \"params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post(\",\n \"cas parameter. :type cas: int :param secret: The contents of the \\\"secret\\\" dict\",\n \"will only be allowed if the key's current version matches the version specified\",\n \"KV Version 2 configuration. Supported methods: GET: /auth/{mount_point}/config. Produces: 200 application/json :param mount_point:\",\n \"path of the secret to destroy. This is specified as part of the\",\n \"raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path)\",\n \"mount_point=mount_point) return self._adapter.post( url=api_path, json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Read the KV Version\",\n \"configuration will be used. :type cas_required: bool :param mount_point: The \\\"path\\\" the secret\",\n \"max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Updates the max_versions of cas_required setting on an existing path.\",\n \"at the specified location. Supported methods: GET: /{mount_point}/data/{path}. Produces: 200 application/json :param path:\",\n \"self._adapter.get( url=api_path, params=params, ) return response.json() def create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Create\",\n \"str | unicode :param versions: The versions to be deleted. The versioned data\",\n \"URL. :type path: str | unicode :param versions: The versions to be deleted.\",\n \"will be returned on normal get requests. :type versions: list of int :param\",\n \"URL. :type path: str | unicode :param version: Specifies the version to return.\",\n \"write requests. If false, the backend's configuration will be used. :type cas_required: bool\",\n \"\\\"\\\"\\\"KvV2 methods module.\\\"\\\"\\\" from hvac import exceptions, utils from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT\",\n \":rtype: dict \\\"\\\"\\\" params = { 'options': {}, 'data': secret, } if cas\",\n \"(empty body) :param path: Path :type path: str | unicode :param max_versions: The\",\n \"unicode :return: The response of the request. :rtype: requests.Response \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}',\",\n \"key. If not set, the backend's configured max version is used. Once a\",\n \"will stop them from being returned from reads, but the underlying data will\",\n \"= current_secret_version['data']['data'] patched_secret.update(secret) # Write back updated secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret,\",\n \"utf-8 -*- \\\"\\\"\\\"KvV2 methods module.\\\"\\\"\\\" from hvac import exceptions, utils from hvac.api.vault_api_base import\",\n \"the request. :rtype: requests.Response \\\"\\\"\\\" params = { 'max_versions': max_versions, } if cas_required\",\n \"no longer be returned in normal get requests. :type versions: int :param mount_point:\",\n \"path=path) response = self._adapter.get( url=api_path, ) return response.json() def update_metadata(self, path, max_versions=None, cas_required=None,\",\n \"The values themselves are not accessible via this command. Supported methods: LIST: /{mount_point}/metadata/{path}.\",\n \"a soft delete of the specified versions of the secret. This marks the\",\n \"write will be allowed. If set to 0 a write will only be\",\n \"Supported methods: LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path of\",\n \"store. This restores the data, allowing it to be returned on get requests.\",\n \"| unicode :param version: Specifies the version to return. If not set the\",\n \"/auth/{mount_point}/config. Produces: 200 application/json :param mount_point: The \\\"path\\\" the secret engine was mounted\",\n \"The versions to be deleted. The versioned data will not be deleted, but\",\n \"Produces: 200 application/json :param path: Specifies the path of the secret to read.\",\n \"than the configured allowed versions the oldest version will be permanently deleted. Defaults\",\n \"response of the request. :rtype: dict \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response\",\n \"cas_required: bool :param mount_point: The \\\"path\\\" the secret engine was mounted on. :type\",\n \"specified version data and numbers for the provided path from the key-value store.\",\n \":param version: Specifies the version to return. If not set the latest version\",\n \"update data in the KV store without overwriting. :param path: Path :type path:\",\n \"max_versions of cas_required setting on an existing path. Supported methods: POST: /{mount_point}/metadata/{path}. Produces:\",\n \"= self._adapter.get(url=api_path) return response.json() def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the secret at\",\n \"api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path, json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Read\",\n \"\\\"\\\"\\\" # First, do a read. try: current_secret_version = self.read_secret_version( path=path, mount_point=mount_point, )\",\n \"the version specified in the cas parameter. :type cas: int :param secret: The\",\n \"def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Set or update data in the KV store\",\n \"mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Delete (permanently)\",\n \"returned from reads, but the underlying data will not be removed. A delete\",\n \"be used. :type cas_required: bool :param mount_point: The \\\"path\\\" the secret engine was\",\n \"= { 'options': {}, 'data': secret, } if cas is not None: params['options']['cas']\",\n \"= self._adapter.get( url=api_path, params=params, ) return response.json() def create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT):\",\n \"secret's latest version at the specified location. This marks the version as deleted\",\n \"key-value store. Supported methods: POST: /{mount_point}/config. Produces: 204 (empty body) :param max_versions: The\",\n \"of the request. :rtype: dict \\\"\\\"\\\" params = {} if version is not\",\n \"requests.Response \\\"\\\"\\\" params = { 'max_versions': max_versions, } if cas_required is not None:\",\n \":param cas: Set the \\\"cas\\\" value to use a Check-And-Set operation. If not\",\n \"/. The input must be a folder; list on a file will not\",\n \"self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft\",\n \"path: str | unicode :param versions: The versions to destroy. Their data will\",\n \"metadata and versions for the secret at the specified path. Supported methods: GET:\",\n \"doesn't exist. If the index is non-zero the write will only be allowed\",\n \"undelete path. Supported methods: POST: /{mount_point}/delete/{path}. Produces: 204 (empty body) :param path: Specifies\",\n \"the data for the provided version and path in the key-value store. This\",\n \"{ 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params,\",\n \"Produces: 204 (empty body) :param max_versions: The number of versions to keep per\",\n \":rtype: requests.Response \\\"\\\"\\\" if not isinstance(versions, list) or len(versions) == 0: error_msg =\",\n \"dict will be stored and returned on read. :type secret: dict :param mount_point:\",\n \"more integers, \\\"{versions}\\\" provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions,\",\n \"to every key in the key-value store. Supported methods: POST: /{mount_point}/config. Produces: 204\",\n \":param cas_required: If true the key will require the cas parameter to be\",\n \") return response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the metadata and versions for\",\n \"mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Create a new version of a secret at the specified location. If\",\n \"The versions to undelete. The versions will be restored and their data will\",\n \"| unicode :param cas: Set the \\\"cas\\\" value to use a Check-And-Set operation.\",\n \"If true the key will require the cas parameter to be set on\",\n \"used. :type cas_required: bool :param mount_point: The \\\"path\\\" the secret engine was mounted\",\n \"at the specified path. Supported methods: GET: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path:\",\n \":type path: str | unicode :param versions: The versions to destroy. Their data\",\n \"be deleted. The versioned data will not be deleted, but it will no\",\n \"capability. Supported methods: POST: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Path :type path:\",\n \"deleted and will stop them from being returned from reads, but the underlying\",\n \"bool): error_msg = 'bool expected for cas_required param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required']\",\n \"Path :type path: str | unicode :param max_versions: The number of versions to\",\n \"The response of the request. :rtype: requests.Response \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path)\",\n \"path. Supported methods: POST: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Path :type\",\n \"the specified key. All version history will be removed. Supported methods: DELETE: /{mount_point}/metadata/{path}.\",\n \"the key-value store. Supported methods: POST: /{mount_point}/destroy/{path}. Produces: 204 (empty body) :param path:\",\n \"{ 'max_versions': max_versions, } if cas_required is not None: params['cas_required'] = cas_required api_path\",\n \"None: params['version'] = version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path,\",\n \"specified versions of the secret. This marks the versions as deleted and will\",\n \"of int :param mount_point: The \\\"path\\\" the secret engine was mounted on. :type\",\n \"self._adapter.post( url=api_path, json=params, ) def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Delete (permanently) the key metadata\",\n \"None: params['options']['cas'] = cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.post( url=api_path,\",\n \"versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete of the specified versions of the secret.\",\n \"specified as part of the URL. :type path: str | unicode :param versions:\",\n \"'bool expected for cas_required param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path\",\n \"| unicode :return: The response of the request. :rtype: requests.Response \\\"\\\"\\\" if not\",\n \"Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Specifies the path\",\n \"key doesn't exist. If the index is non-zero the write will only be\",\n \":return: The response of the request. :rtype: requests.Response \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point,\",\n \"data and numbers for the provided path from the key-value store. Supported methods:\",\n \"have an ACL policy granting the create capability. If the value already exists,\",\n \"api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, ) def delete_secret_versions(self, path, versions,\",\n \"key has more than the configured allowed versions the oldest version will be\",\n \"not isinstance(versions, list) or len(versions) == 0: error_msg = 'argument to \\\"versions\\\" must\",\n \"Supported methods: POST: /{mount_point}/config. Produces: 204 (empty body) :param max_versions: The number of\",\n \":param versions: The versions to destroy. Their data will be permanently deleted. :type\",\n \"mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Undelete\",\n \"str | unicode :return: The response of the request. :rtype: requests.Response \\\"\\\"\\\" api_path\",\n \"are suffixed with /. The input must be a folder; list on a\",\n \"per key. If not set, the backend's configured max version is used. Once\",\n \"to be set on all write requests. If false, the backend's configuration will\",\n \"path: str | unicode :param secret: The contents of the \\\"secret\\\" dict will\",\n \"a value. Note that no policy-based filtering is performed on keys; do not\",\n \"set the latest version is returned. :type version: int :param mount_point: The \\\"path\\\"\",\n \"set, the backend's configured max version is used. Once a key has more\",\n \"/{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path of the secrets to\",\n \"\\\"\\\"\\\" params = {} if version is not None: params['version'] = version api_path\",\n \"will no longer be returned in normal get requests. :type versions: int :param\",\n \"is not None: if not isinstance(cas_required, bool): error_msg = 'bool expected for cas_required\",\n \"the max_versions of cas_required setting on an existing path. Supported methods: POST: /{mount_point}/metadata/{path}.\",\n \"Supported methods: POST: /{mount_point}/delete/{path}. Produces: 204 (empty body) :param path: Specifies the path\",\n \"be set on all write requests. :type cas_required: bool :param mount_point: The \\\"path\\\"\",\n \"Note that no policy-based filtering is performed on keys; do not encode sensitive\",\n \"removed. A delete can be undone using the undelete path. Supported methods: DELETE:\",\n \"= utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT):\",\n \"mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Permanently\",\n \"mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the metadata and versions for the secret at the specified path.\",\n \"The JSON response of the request. :rtype: dict \\\"\\\"\\\" params = { 'options':\",\n \"be removed. A delete can be undone using the undelete path. Supported methods:\",\n \"be returned on normal get requests. :type versions: list of int :param mount_point:\",\n \"be returned in normal get requests. :type versions: int :param mount_point: The \\\"path\\\"\",\n \"If true all keys will require the cas parameter to be set on\",\n \"json=params, ) def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Delete (permanently) the key metadata and all\",\n \":return: The response of the request. :rtype: requests.Response \\\"\\\"\\\" params = {} if\",\n \"The JSON response of the request. :rtype: dict \\\"\\\"\\\" api_path = utils.format_url( '/v1/{mount_point}/config',\",\n \"applies to all keys, but a key's metadata setting can overwrite this value.\",\n \"of versions to keep per key. If not set, the backend's configured max\",\n \"versions of the secret. This marks the versions as deleted and will stop\",\n \"the URL. :type path: str | unicode :param versions: The versions to undelete.\",\n \"cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete of\",\n \"to list. This is specified as part of the URL. :type path: str\",\n \"location. If the value does not yet exist, the calling token must have\",\n \"has more than the configured allowed versions the oldest version will be permanently\",\n \":rtype: dict \\\"\\\"\\\" # First, do a read. try: current_secret_version = self.read_secret_version( path=path,\",\n \"\\\"\\\"\\\"Updates the max_versions of cas_required setting on an existing path. Supported methods: POST:\",\n \"VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase): \\\"\\\"\\\"KV Secrets Engine - Version 2 (API).\",\n \"specified in the cas parameter. :type cas: int :param secret: The contents of\",\n \"destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Permanently remove the specified version data and numbers for\",\n \"the value does not yet exist, the calling token must have an ACL\",\n \"response of the request. :rtype: dict \\\"\\\"\\\" params = { 'options': {}, 'data':\",\n \"configured allowed versions the oldest version will be permanently deleted. :type max_versions: int\",\n \"key. This value applies to all keys, but a key's metadata setting can\",\n \"policy granting the create capability. If the value already exists, the calling token\",\n \"Set the \\\"cas\\\" value to use a Check-And-Set operation. If not set the\",\n \"Their data will be permanently deleted. :type versions: list of int :param mount_point:\",\n \"Supported methods: GET: /auth/{mount_point}/config. Produces: 200 application/json :param mount_point: The \\\"path\\\" the secret\",\n \"secret: The contents of the \\\"secret\\\" dict will be stored and returned on\",\n \"If set to 0 a write will only be allowed if the key\",\n \"delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Delete (permanently) the key metadata and all version data for\",\n \"| unicode :param secret: The contents of the \\\"secret\\\" dict will be stored\",\n \"versions to undelete. The versions will be restored and their data will be\",\n \"secret to destroy. This is specified as part of the URL. :type path:\",\n \") raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point,\",\n \"keys, but a key's metadata setting can overwrite this value. Once a key\",\n \"utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, ) def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue\",\n \"request. :rtype: requests.Response \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, )\",\n \"the request. :rtype: requests.Response \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path,\",\n \"max_versions: int :param cas_required: If true the key will require the cas parameter\",\n \"undelete. The versions will be restored and their data will be returned on\",\n \"and path in the key-value store. This restores the data, allowing it to\",\n \"metadata and all version data for the specified key. All version history will\",\n \"a file will not return a value. Note that no policy-based filtering is\",\n \"#!/usr/bin/env python # -*- coding: utf-8 -*- \\\"\\\"\\\"KvV2 methods module.\\\"\\\"\\\" from hvac import\",\n \"delete can be undone using the undelete path. Supported methods: DELETE: /{mount_point}/data/{path}. Produces:\",\n \"requests. :type cas_required: bool :param mount_point: The \\\"path\\\" the secret engine was mounted\",\n \"a soft delete of the secret's latest version at the specified location. This\",\n \"versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Undelete the data for the provided version and path in the\",\n \"path: str | unicode :param versions: The versions to be deleted. The versioned\",\n \"def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Permanently remove the specified version data and numbers\",\n \"the secret at the specified location. Supported methods: GET: /{mount_point}/data/{path}. Produces: 200 application/json\",\n \"a new version of a secret at the specified location. If the value\",\n \"max_versions: The number of versions to keep per key. This value applies to\",\n \"def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the metadata and versions for the secret at\",\n \"current version matches the version specified in the cas parameter. :type cas: int\",\n \"'/v1/{mount_point}/config', mount_point=mount_point, ) response = self._adapter.get(url=api_path) return response.json() def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT):\",\n \"and all version data for the specified key. All version history will be\",\n \"cas parameter to be set on all write requests. If false, the backend's\",\n \":param path: Specifies the path of the secret to undelete. This is specified\",\n \"granting the create capability. If the value already exists, the calling token must\",\n \"the create capability. If the value already exists, the calling token must have\",\n \":rtype: requests.Response \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, ) def\",\n \"mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, ) return response.json() def update_metadata(self, path, max_versions=None,\",\n \"location. This marks the version as deleted and will stop it from being\",\n \"api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.list( url=api_path, ) return response.json() def\",\n \"\\\"cas\\\" value to use a Check-And-Set operation. If not set the write will\",\n \"The number of versions to keep per key. If not set, the backend's\",\n \"self._adapter.list( url=api_path, ) return response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the metadata and\",\n \"204 (empty body) :param path: Path :type path: str | unicode :param max_versions:\",\n \"on existing data.'.format(path=path)) # Update existing secret dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) #\",\n \"be returned on get requests. Supported methods: POST: /{mount_point}/undelete/{path}. Produces: 204 (empty body)\",\n \"not accessible via this command. Supported methods: LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json :param\",\n \"deleted, but it will no longer be returned in normal get requests. :type\",\n \"def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Return a list of key names at the specified\",\n \"versions: int :param mount_point: The \\\"path\\\" the secret engine was mounted on. :type\",\n \"policy granting the update capability. Supported methods: POST: /{mount_point}/data/{path}. Produces: 200 application/json :param\",\n \"except exceptions.InvalidPath: raise exceptions.InvalidPath('No value found at \\\"{path}\\\"; patch only works on existing\",\n \"deleted. :type versions: list of int :param mount_point: The \\\"path\\\" the secret engine\",\n \"/{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path of the secret to\",\n \"delete can be undone using the undelete path. Supported methods: POST: /{mount_point}/delete/{path}. Produces:\",\n \"the backend's configured max version is used. Once a key has more than\",\n \"as deleted and will stop them from being returned from reads, but the\",\n \"key-value store. This restores the data, allowing it to be returned on get\",\n \"exist. If the index is non-zero the write will only be allowed if\",\n \"provided version and path in the key-value store. This restores the data, allowing\",\n \"return. If not set the latest version is returned. :type version: int :param\",\n \"path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the metadata and versions for the secret at the specified\",\n \"to read. This is specified as part of the URL. :type path: str\",\n \"it to be returned on get requests. Supported methods: POST: /{mount_point}/undelete/{path}. Produces: 204\",\n \"/{mount_point}/data/{path}. Produces: 204 (empty body) :param path: Specifies the path of the secret\",\n \"def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Read the KV Version 2 configuration. Supported methods: GET: /auth/{mount_point}/config.\",\n \"str | unicode :param version: Specifies the version to return. If not set\",\n \":type path: str | unicode :param max_versions: The number of versions to keep\",\n \"utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path, json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Read the KV\",\n \"a key has more than the configured allowed versions the oldest version will\",\n \"len(versions) == 0: error_msg = 'argument to \\\"versions\\\" must be a list containing\",\n \"200 application/json :param path: Specifies the path of the secrets to list. This\",\n \":rtype: dict \\\"\\\"\\\" api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response = self._adapter.get(url=api_path) return\",\n \"a key's metadata setting can overwrite this value. Once a key has more\",\n \"token must have an ACL policy granting the create capability. If the value\",\n \"latest version at the specified location. This marks the version as deleted and\",\n \"or more integers, \\\"{versions}\\\" provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg) params = { 'versions':\",\n \"be permanently deleted. :type versions: list of int :param mount_point: The \\\"path\\\" the\",\n \"and versions for the secret at the specified path. Supported methods: GET: /{mount_point}/metadata/{path}.\",\n \"the request. :rtype: requests.Response \\\"\\\"\\\" if not isinstance(versions, list) or len(versions) == 0:\",\n \"raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path)\",\n \":type path: str | unicode :param mount_point: The \\\"path\\\" the secret engine was\",\n \"} api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def undelete_secret_versions(self,\",\n \"removed. Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Specifies the\",\n \"unicode :param cas: Set the \\\"cas\\\" value to use a Check-And-Set operation. If\",\n \"max_versions: int :param cas_required: If true all keys will require the cas parameter\",\n \"on read. :type secret: dict :param mount_point: The \\\"path\\\" the secret engine was\",\n \"undelete path. Supported methods: DELETE: /{mount_point}/data/{path}. Produces: 204 (empty body) :param path: Specifies\",\n \"of the request. :rtype: dict \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response =\",\n \"read. :type secret: dict :param mount_point: The \\\"path\\\" the secret engine was mounted\",\n \"version data for the specified key. All version history will be removed. Supported\",\n \":param max_versions: The number of versions to keep per key. If not set,\",\n \"of the secret to delete. This is specified as part of the URL.\",\n \"be permanently deleted. Defaults to 10. :type max_versions: int :param cas_required: If true\",\n \"being returned from reads, but the underlying data will not be removed. A\",\n \"unicode :param secret: The contents of the \\\"secret\\\" dict will be stored and\",\n \"path from the key-value store. Supported methods: POST: /{mount_point}/destroy/{path}. Produces: 204 (empty body)\",\n \"returned on read. :type secret: dict :param mount_point: The \\\"path\\\" the secret engine\",\n \"to undelete. This is specified as part of the URL. :type path: str\",\n \") def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Undelete the data for the provided version\",\n \"mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Return a list of key names at the specified location. Folders are\",\n \"DELETE: /{mount_point}/data/{path}. Produces: 204 (empty body) :param path: Specifies the path of the\",\n \"list on a file will not return a value. Note that no policy-based\",\n \":type versions: int :param mount_point: The \\\"path\\\" the secret engine was mounted on.\",\n \"the provided path from the key-value store. Supported methods: POST: /{mount_point}/destroy/{path}. Produces: 204\",\n \":type version: int :param mount_point: The \\\"path\\\" the secret engine was mounted on.\",\n \"Specifies the path of the secret to undelete. This is specified as part\",\n \"the versions as deleted and will stop them from being returned from reads,\",\n \"unicode :return: The response of the request. :rtype: requests.Response \\\"\\\"\\\" params = {\",\n \"the cas parameter. :type cas: int :param secret: The contents of the \\\"secret\\\"\",\n \"will be restored and their data will be returned on normal get requests.\",\n \"specified location. Folders are suffixed with /. The input must be a folder;\",\n \"(empty body) :param path: Specifies the path of the secret to undelete. This\",\n \"was mounted on. :type mount_point: str | unicode :return: The JSON response of\",\n \"return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a\",\n \"The input must be a folder; list on a file will not return\",\n \"Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \\\"\\\"\\\" def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Configure backend level settings that\",\n \"max_versions, } if cas_required is not None: params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/config',\",\n \"} api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def list_secrets(self,\",\n \"request. :rtype: requests.Response \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, )\",\n \"allowed versions the oldest version will be permanently deleted. Defaults to 10. :type\",\n \"the path of the secret to undelete. This is specified as part of\",\n \"/{mount_point}/destroy/{path}. Produces: 204 (empty body) :param path: Specifies the path of the secret\",\n \"| unicode :param versions: The versions to undelete. The versions will be restored\",\n \"at the specified location. Folders are suffixed with /. The input must be\",\n \"using the undelete path. Supported methods: DELETE: /{mount_point}/data/{path}. Produces: 204 (empty body) :param\",\n \"will stop it from being returned from reads, but the underlying data will\",\n \"self._adapter.post( url=api_path, json=params, ) def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Permanently remove the specified\",\n \"overwriting. :param path: Path :type path: str | unicode :param secret: The contents\",\n \"\\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, ) def delete_secret_versions(self, path,\",\n \"of the secret's latest version at the specified location. This marks the version\",\n \"| unicode :return: The response of the request. :rtype: requests.Response \\\"\\\"\\\" params =\",\n \"mount_point=mount_point, ) except exceptions.InvalidPath: raise exceptions.InvalidPath('No value found at \\\"{path}\\\"; patch only works\",\n \"be a folder; list on a file will not return a value. Note\",\n \"utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT):\",\n \"path: str | unicode :param version: Specifies the version to return. If not\",\n \"read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Read the KV Version 2 configuration. Supported methods: GET: /auth/{mount_point}/config. Produces:\",\n \"policy-based filtering is performed on keys; do not encode sensitive information in key\",\n \"the secrets to list. This is specified as part of the URL. :type\",\n \"Produces: 204 (empty body) :param path: Specifies the path of the secret to\",\n \":param max_versions: The number of versions to keep per key. This value applies\",\n \"Supported methods: POST: /{mount_point}/destroy/{path}. Produces: 204 (empty body) :param path: Specifies the path\",\n \"request. :rtype: dict \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path,\",\n \"file will not return a value. Note that no policy-based filtering is performed\",\n \"level settings that are applied to every key in the key-value store. Supported\",\n \"allowed. If set to 0 a write will only be allowed if the\",\n \"not set the write will be allowed. If set to 0 a write\",\n \"The response of the request. :rtype: requests.Response \\\"\\\"\\\" params = { 'max_versions': max_versions,\",\n \"\\\"\\\"\\\" def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Configure backend level settings that are applied\",\n \"} if cas is not None: params['options']['cas'] = cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point,\",\n \":param path: Path :type path: str | unicode :param cas: Set the \\\"cas\\\"\",\n \"methods: POST: /{mount_point}/undelete/{path}. Produces: 204 (empty body) :param path: Specifies the path of\",\n \"version=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the secret at the specified location. Supported methods: GET: /{mount_point}/data/{path}.\",\n \"the path of the secret to read. This is specified as part of\",\n \"and will stop them from being returned from reads, but the underlying data\",\n \"json=params, ) def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Undelete the data for the provided\",\n \"on keys; do not encode sensitive information in key names. The values themselves\",\n \"The versioned data will not be deleted, but it will no longer be\",\n \"will be stored and returned on read. :type secret: dict :param mount_point: The\",\n \"POST: /{mount_point}/destroy/{path}. Produces: 204 (empty body) :param path: Specifies the path of the\",\n \"def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the secret at the specified location. Supported\",\n \"that are applied to every key in the key-value store. Supported methods: POST:\",\n \"version will be permanently deleted. Defaults to 10. :type max_versions: int :param cas_required:\",\n \"the calling token must have an ACL policy granting the create capability. If\",\n \"the underlying data will not be removed. A delete can be undone using\",\n \"calling token must have an ACL policy granting the update capability. Supported methods:\",\n \"list) or len(versions) == 0: error_msg = 'argument to \\\"versions\\\" must be a\",\n \"This is specified as part of the URL. :type path: str | unicode\",\n \"isinstance(cas_required, bool): error_msg = 'bool expected for cas_required param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg)\",\n \"versions: The versions to undelete. The versions will be restored and their data\",\n \"from reads, but the underlying data will not be removed. A delete can\",\n \"None: params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path, json=params, )\",\n \"(permanently) the key metadata and all version data for the specified key. All\",\n \"POST: /{mount_point}/delete/{path}. Produces: 204 (empty body) :param path: Specifies the path of the\",\n \"information in key names. The values themselves are not accessible via this command.\",\n \") def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete of the specified\",\n \"unicode :return: The JSON response of the request. :rtype: dict \\\"\\\"\\\" params =\",\n \"at the specified location. If the value does not yet exist, the calling\",\n \"(empty body) :param path: Specifies the path of the secret to destroy. This\",\n \"| unicode :return: The JSON response of the request. :rtype: dict \\\"\\\"\\\" api_path\",\n \"path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Create a new version of a secret at the\",\n \"unicode :param mount_point: The \\\"path\\\" the secret engine was mounted on. :type mount_point:\",\n \"cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def delete_metadata_and_all_versions(self,\",\n \":type mount_point: str | unicode :return: The response of the request. :rtype: requests.Response\",\n \"\\\"\\\"\\\"Delete (permanently) the key metadata and all version data for the specified key.\",\n \"params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, )\",\n \"int :param mount_point: The \\\"path\\\" the secret engine was mounted on. :type mount_point:\",\n \"json=params, ) return response.json() def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Set or update data\",\n \"url=api_path, json=params, ) def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Permanently remove the specified version\",\n \"self._adapter.post( url=api_path, json=params, ) def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Undelete the data for\",\n \"will be used. :type cas_required: bool :param mount_point: The \\\"path\\\" the secret engine\",\n \"versions=versions ) raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}',\",\n \"path: Specifies the path of the secret to destroy. This is specified as\",\n \"soft delete of the specified versions of the secret. This marks the versions\",\n \"Supported methods: GET: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path of\",\n \"api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response = self._adapter.get(url=api_path) return response.json() def read_secret_version(self,\",\n \"response = self._adapter.get( url=api_path, params=params, ) return response.json() def create_or_update_secret(self, path, secret, cas=None,\",\n \"/{mount_point}/delete/{path}. Produces: 204 (empty body) :param path: Specifies the path of the secret\",\n \"integers, \\\"{versions}\\\" provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, }\",\n \"The JSON response of the create_or_update_secret request. :rtype: dict \\\"\\\"\\\" # First, do\",\n \"undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Undelete the data for the provided version and path\",\n \"dict \\\"\\\"\\\" params = {} if version is not None: params['version'] = version\",\n \"path: Specifies the path of the secret to delete. This is specified as\",\n \"with /. The input must be a folder; list on a file will\",\n \"path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Permanently remove the specified version data and numbers for the\",\n \"more than the configured allowed versions the oldest version will be permanently deleted.\",\n \"is used. Once a key has more than the configured allowed versions the\",\n \"do a read. try: current_secret_version = self.read_secret_version( path=path, mount_point=mount_point, ) except exceptions.InvalidPath: raise\",\n \"requests.Response \\\"\\\"\\\" if not isinstance(versions, list) or len(versions) == 0: error_msg = 'argument\",\n \"path. Supported methods: DELETE: /{mount_point}/data/{path}. Produces: 204 (empty body) :param path: Specifies the\",\n \"require the cas parameter to be set on all write requests. If false,\",\n \"will require the cas parameter to be set on all write requests. :type\",\n \"= max_versions if cas_required is not None: if not isinstance(cas_required, bool): error_msg =\",\n \"body) :param max_versions: The number of versions to keep per key. This value\",\n \"current_secret_version['data']['data'] patched_secret.update(secret) # Write back updated secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point,\",\n \"\\\"\\\"\\\"Issue a soft delete of the secret's latest version at the specified location.\",\n \"path of the secrets to list. This is specified as part of the\",\n \"version is used. Once a key has more than the configured allowed versions\",\n \"list. This is specified as part of the URL. :type path: str |\",\n \"import exceptions, utils from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase): \\\"\\\"\\\"KV\",\n \"exist, the calling token must have an ACL policy granting the create capability.\",\n \"(empty body) :param path: Specifies the path of the secret to delete. This\",\n \"str | unicode :param cas: Set the \\\"cas\\\" value to use a Check-And-Set\",\n \"None: if not isinstance(cas_required, bool): error_msg = 'bool expected for cas_required param, {type}\",\n \"} api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def destroy_secret_versions(self,\",\n \"versions=versions ) raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}',\",\n \"existing secret dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) # Write back updated secret. return\",\n \"data in the KV store without overwriting. :param path: Path :type path: str\",\n \"mount_point: str | unicode :return: The response of the request. :rtype: requests.Response \\\"\\\"\\\"\",\n \"max_versions if cas_required is not None: if not isinstance(cas_required, bool): error_msg = 'bool\",\n \"mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, params=params, ) return response.json() def create_or_update_secret(self, path,\",\n \"response = self._adapter.post( url=api_path, json=params, ) return response.json() def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT):\",\n \"return self._adapter.delete( url=api_path, ) def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete\",\n \"of the secrets to list. This is specified as part of the URL.\",\n \"contents of the \\\"secret\\\" dict will be stored and returned on read. :type\",\n \"POST: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Path :type path: str |\",\n \"secret. This marks the versions as deleted and will stop them from being\",\n \"is not None: params['options']['cas'] = cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response =\",\n \"if cas_required is not None: params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return\",\n \"path of the secret to read. This is specified as part of the\",\n \"return response.json() def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Set or update data in the\",\n \"current_secret_version = self.read_secret_version( path=path, mount_point=mount_point, ) except exceptions.InvalidPath: raise exceptions.InvalidPath('No value found at\",\n \"the specified path. Supported methods: GET: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies\",\n \"destroy. This is specified as part of the URL. :type path: str |\",\n \"themselves are not accessible via this command. Supported methods: LIST: /{mount_point}/metadata/{path}. Produces: 200\",\n \"setting can overwrite this value. Once a key has more than the configured\",\n \"oldest version will be permanently deleted. :type max_versions: int :param cas_required: If true\",\n \"\\\"\\\"\\\"Create a new version of a secret at the specified location. If the\",\n \"First, do a read. try: current_secret_version = self.read_secret_version( path=path, mount_point=mount_point, ) except exceptions.InvalidPath:\",\n \"to undelete. The versions will be restored and their data will be returned\",\n \"soft delete of the secret's latest version at the specified location. This marks\",\n \"str | unicode :param mount_point: The \\\"path\\\" the secret engine was mounted on.\",\n \"mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Configure backend level settings that are applied to every key in the\",\n \":type path: str | unicode :param secret: The contents of the \\\"secret\\\" dict\",\n \"will not return a value. Note that no policy-based filtering is performed on\",\n \"stop it from being returned from reads, but the underlying data will not\",\n \"if cas is not None: params['options']['cas'] = cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path)\",\n \"the undelete path. Supported methods: POST: /{mount_point}/delete/{path}. Produces: 204 (empty body) :param path:\",\n \"data, allowing it to be returned on get requests. Supported methods: POST: /{mount_point}/undelete/{path}.\",\n \"will not be removed. A delete can be undone using the undelete path.\",\n \"a secret at the specified location. If the value does not yet exist,\",\n \"version is not None: params['version'] = version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response\",\n \":return: The JSON response of the request. :rtype: dict \\\"\\\"\\\" params = {\",\n \"= utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def undelete_secret_versions(self, path, versions,\",\n \"versions to keep per key. This value applies to all keys, but a\",\n \"coding: utf-8 -*- \\\"\\\"\\\"KvV2 methods module.\\\"\\\"\\\" from hvac import exceptions, utils from hvac.api.vault_api_base\",\n \"Supported methods: POST: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Path :type path: str\",\n \"patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Set or update data in the KV store without\",\n \"granting the update capability. Supported methods: POST: /{mount_point}/data/{path}. Produces: 200 application/json :param path:\",\n \"the specified location. This marks the version as deleted and will stop it\",\n \"\\\"\\\"\\\"KV Secrets Engine - Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \\\"\\\"\\\" def configure(self, max_versions=10,\",\n \"data will not be deleted, but it will no longer be returned in\",\n \"existing data.'.format(path=path)) # Update existing secret dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) # Write\",\n \"version will be permanently deleted. :type max_versions: int :param cas_required: If true the\",\n \"'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, )\",\n \"cas: Set the \\\"cas\\\" value to use a Check-And-Set operation. If not set\",\n \"api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def destroy_secret_versions(self, path,\",\n \"unicode :return: The response of the request. :rtype: requests.Response \\\"\\\"\\\" if not isinstance(versions,\",\n \"restores the data, allowing it to be returned on get requests. Supported methods:\",\n \"body) :param path: Specifies the path of the secret to destroy. This is\",\n \"the oldest version will be permanently deleted. Defaults to 10. :type max_versions: int\",\n \"This marks the versions as deleted and will stop them from being returned\",\n \"to return. If not set the latest version is returned. :type version: int\",\n \"= self._adapter.post( url=api_path, json=params, ) return response.json() def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Set\",\n \"create_or_update_secret request. :rtype: dict \\\"\\\"\\\" # First, do a read. try: current_secret_version =\",\n \"not return a value. Note that no policy-based filtering is performed on keys;\",\n \":type cas: int :param secret: The contents of the \\\"secret\\\" dict will be\",\n \"number of versions to keep per key. If not set, the backend's configured\",\n \"path=path) return self._adapter.post( url=api_path, json=params, ) def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Delete (permanently) the\",\n \"secret engine was mounted on. :type mount_point: str | unicode :return: The response\",\n \"def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete of the specified versions\",\n \"the secret to read. This is specified as part of the URL. :type\",\n \"params = { 'max_versions': max_versions, } if cas_required is not None: params['cas_required'] =\",\n \"204 (empty body) :param max_versions: The number of versions to keep per key.\",\n \"engine was mounted on. :type mount_point: str | unicode :return: The JSON response\",\n \"found at \\\"{path}\\\"; patch only works on existing data.'.format(path=path)) # Update existing secret\",\n \"than the configured allowed versions the oldest version will be permanently deleted. :type\",\n \"write will only be allowed if the key's current version matches the version\",\n \"application/json :param path: Specifies the path of the secrets to list. This is\",\n \"secret, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Set or update data in the KV store without overwriting. :param\",\n \"was mounted on. :type mount_point: str | unicode :return: The response of the\",\n \"raise exceptions.InvalidPath('No value found at \\\"{path}\\\"; patch only works on existing data.'.format(path=path)) #\",\n \"versions as deleted and will stop them from being returned from reads, but\",\n \"response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the metadata and versions for the secret\",\n \"self._adapter.post( url=api_path, json=params, ) return response.json() def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Set or\",\n \"utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT):\",\n \"This restores the data, allowing it to be returned on get requests. Supported\",\n \"response = self._adapter.get(url=api_path) return response.json() def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the secret\",\n \"unicode :return: The JSON response of the request. :rtype: dict \\\"\\\"\\\" api_path =\",\n \"python # -*- coding: utf-8 -*- \\\"\\\"\\\"KvV2 methods module.\\\"\\\"\\\" from hvac import exceptions,\",\n \"containing one or more integers, \\\"{versions}\\\" provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg) params =\",\n \"JSON response of the request. :rtype: dict \\\"\\\"\\\" params = {} if version\",\n \"Path :type path: str | unicode :param cas: Set the \\\"cas\\\" value to\",\n \"api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.post( url=api_path, json=params, ) return response.json()\",\n \"patched_secret.update(secret) # Write back updated secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, )\",\n \"path=path) response = self._adapter.post( url=api_path, json=params, ) return response.json() def patch(self, path, secret,\",\n \"undone using the undelete path. Supported methods: POST: /{mount_point}/delete/{path}. Produces: 204 (empty body)\",\n \"oldest version will be permanently deleted. Defaults to 10. :type max_versions: int :param\",\n \"secret to delete. This is specified as part of the URL. :type path:\",\n \"request. :rtype: requests.Response \\\"\\\"\\\" params = { 'max_versions': max_versions, } if cas_required is\",\n \"data will be permanently deleted. :type versions: list of int :param mount_point: The\",\n \"the create_or_update_secret request. :rtype: dict \\\"\\\"\\\" # First, do a read. try: current_secret_version\",\n \"DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Specifies the path of the\",\n \"in the key-value store. This restores the data, allowing it to be returned\",\n \"is specified as part of the URL. :type path: str | unicode :param\",\n \"= self._adapter.get( url=api_path, ) return response.json() def update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Updates\",\n \"the path of the secrets to list. This is specified as part of\",\n \"Update existing secret dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) # Write back updated secret.\",\n \"GET: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path of the secret\",\n \"{} if version is not None: params['version'] = version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point,\",\n \"JSON response of the request. :rtype: dict \\\"\\\"\\\" api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point,\",\n \"their data will be returned on normal get requests. :type versions: list of\",\n \"or len(versions) == 0: error_msg = 'argument to \\\"versions\\\" must be a list\",\n \"params['version'] = version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, params=params,\",\n \"the key will require the cas parameter to be set on all write\",\n \"versions=versions ) raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}',\",\n \"mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, ) def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a\",\n \"to keep per key. This value applies to all keys, but a key's\",\n \"to use a Check-And-Set operation. If not set the write will be allowed.\",\n \"to 0 a write will only be allowed if the key doesn't exist.\",\n \"The number of versions to keep per key. This value applies to all\",\n \"mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete of the specified versions of the secret. This\",\n \"path, secret, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Set or update data in the KV store without overwriting.\",\n \"mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the secret at the specified location. Supported methods: GET: /{mount_point}/data/{path}. Produces:\",\n \"GET: /auth/{mount_point}/config. Produces: 200 application/json :param mount_point: The \\\"path\\\" the secret engine was\",\n \"raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path)\",\n \"the request. :rtype: dict \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.list(\",\n \"versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def\",\n \"the write will be allowed. If set to 0 a write will only\",\n \"the value already exists, the calling token must have an ACL policy granting\",\n \"values themselves are not accessible via this command. Supported methods: LIST: /{mount_point}/metadata/{path}. Produces:\",\n \"max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Configure backend level settings that are applied to every key\",\n \"str | unicode :return: The JSON response of the request. :rtype: dict \\\"\\\"\\\"\",\n \"have an ACL policy granting the update capability. Supported methods: POST: /{mount_point}/data/{path}. Produces:\",\n \"all keys, but a key's metadata setting can overwrite this value. Once a\",\n \"version data and numbers for the provided path from the key-value store. Supported\",\n \"body) :param path: Specifies the path of the secret to undelete. This is\",\n \"capability. If the value already exists, the calling token must have an ACL\",\n \"exceptions.InvalidPath: raise exceptions.InvalidPath('No value found at \\\"{path}\\\"; patch only works on existing data.'.format(path=path))\",\n \"secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue\",\n \"store. Supported methods: POST: /{mount_point}/destroy/{path}. Produces: 204 (empty body) :param path: Specifies the\",\n \"params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post(\",\n \"exceptions.InvalidPath('No value found at \\\"{path}\\\"; patch only works on existing data.'.format(path=path)) # Update\",\n \"setting on an existing path. Supported methods: POST: /{mount_point}/metadata/{path}. Produces: 204 (empty body)\",\n \"204 (empty body) :param path: Specifies the path of the secret to undelete.\",\n \"Specifies the version to return. If not set the latest version is returned.\",\n \"path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Updates the max_versions of cas_required setting on an existing\",\n \"= {} if version is not None: params['version'] = version api_path = utils.format_url('/v1/{mount_point}/data/{path}',\",\n \"the request. :rtype: requests.Response \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path,\",\n \"path=path, mount_point=mount_point, ) except exceptions.InvalidPath: raise exceptions.InvalidPath('No value found at \\\"{path}\\\"; patch only\",\n \"can be undone using the undelete path. Supported methods: DELETE: /{mount_point}/data/{path}. Produces: 204\",\n \"metadata setting can overwrite this value. Once a key has more than the\",\n \"data for the provided version and path in the key-value store. This restores\",\n \"the backend's configuration will be used. :type cas_required: bool :param mount_point: The \\\"path\\\"\",\n \"params = { 'options': {}, 'data': secret, } if cas is not None:\",\n \"the version to return. If not set the latest version is returned. :type\",\n \"on normal get requests. :type versions: list of int :param mount_point: The \\\"path\\\"\",\n \"not None: params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path, json=params,\",\n \"body) :param path: Path :type path: str | unicode :param max_versions: The number\",\n \"the request. :rtype: dict \\\"\\\"\\\" api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response =\",\n \"# -*- coding: utf-8 -*- \\\"\\\"\\\"KvV2 methods module.\\\"\\\"\\\" from hvac import exceptions, utils\",\n \"cas is not None: params['options']['cas'] = cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response\",\n \"as part of the URL. :type path: str | unicode :param version: Specifies\",\n \":type secret: dict :param mount_point: The \\\"path\\\" the secret engine was mounted on.\",\n \"return response.json() def update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Updates the max_versions of cas_required\",\n \"/{mount_point}/data/{path}. Produces: 200 application/json :param path: Path :type path: str | unicode :param\",\n \"specified key. All version history will be removed. Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces:\",\n \":type path: str | unicode :param versions: The versions to be deleted. The\",\n \"api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, ) return response.json() def\",\n \"suffixed with /. The input must be a folder; list on a file\",\n \"dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) # Write back updated secret. return self.create_or_update_secret( path=path,\",\n \"the \\\"secret\\\" dict will be stored and returned on read. :type secret: dict\",\n \"as part of the URL. :type path: str | unicode :param versions: The\",\n \"only be allowed if the key's current version matches the version specified in\",\n \"mount_point=mount_point, path=path) response = self._adapter.post( url=api_path, json=params, ) return response.json() def patch(self, path,\",\n \"key's current version matches the version specified in the cas parameter. :type cas:\",\n \"from being returned from reads, but the underlying data will not be removed.\",\n \":return: The response of the request. :rtype: requests.Response \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point,\",\n \"to keep per key. If not set, the backend's configured max version is\",\n \"normal get requests. :type versions: list of int :param mount_point: The \\\"path\\\" the\",\n \"api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def delete_metadata_and_all_versions(self, path,\",\n \"for the specified key. All version history will be removed. Supported methods: DELETE:\",\n \"path: str | unicode :param cas: Set the \\\"cas\\\" value to use a\",\n \"version as deleted and will stop it from being returned from reads, but\",\n \") def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Return a list of key names at the\",\n \"mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Read the KV Version 2 configuration. Supported methods: GET: /auth/{mount_point}/config. Produces: 200\",\n \"params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post(\",\n \"URL. :type path: str | unicode :param versions: The versions to destroy. Their\",\n \"path: Specifies the path of the secret to undelete. This is specified as\",\n \"path. Supported methods: POST: /{mount_point}/delete/{path}. Produces: 204 (empty body) :param path: Specifies the\",\n \"path: str | unicode :param mount_point: The \\\"path\\\" the secret engine was mounted\",\n \"module.\\\"\\\"\\\" from hvac import exceptions, utils from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT = 'secret'\",\n \"for the provided path from the key-value store. Supported methods: POST: /{mount_point}/destroy/{path}. Produces:\",\n \"KvV2(VaultApiBase): \\\"\\\"\\\"KV Secrets Engine - Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \\\"\\\"\\\" def configure(self,\",\n \"def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Configure backend level settings that are applied to\",\n \"all version data for the specified key. All version history will be removed.\",\n \":type versions: list of int :param mount_point: The \\\"path\\\" the secret engine was\",\n \"return response.json() def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the secret at the specified\",\n \"url=api_path, ) return response.json() def update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Updates the max_versions\",\n \"\\\"\\\"\\\"Undelete the data for the provided version and path in the key-value store.\",\n \":param versions: The versions to be deleted. The versioned data will not be\",\n \"of the specified versions of the secret. This marks the versions as deleted\",\n \"} if cas_required is not None: params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point)\",\n \"str | unicode :return: The JSON response of the create_or_update_secret request. :rtype: dict\",\n \"specified as part of the URL. :type path: str | unicode :param mount_point:\",\n \"key's metadata setting can overwrite this value. Once a key has more than\",\n \"patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) # Write back updated secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'],\",\n \"path=path) return self._adapter.delete( url=api_path, ) def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft\",\n \"it from being returned from reads, but the underlying data will not be\",\n \"utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, params=params, ) return response.json() def create_or_update_secret(self,\",\n \"\\\"{versions}\\\" provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path\",\n \"\\\"secret\\\" dict will be stored and returned on read. :type secret: dict :param\",\n \"requests. :type versions: int :param mount_point: The \\\"path\\\" the secret engine was mounted\",\n \":param secret: The contents of the \\\"secret\\\" dict will be stored and returned\",\n \":rtype: dict \\\"\\\"\\\" params = {} if version is not None: params['version'] =\",\n \"the calling token must have an ACL policy granting the update capability. Supported\",\n \"response of the request. :rtype: requests.Response \\\"\\\"\\\" params = { 'max_versions': max_versions, }\",\n \"Supported methods: POST: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Path :type path:\",\n \"provided path from the key-value store. Supported methods: POST: /{mount_point}/destroy/{path}. Produces: 204 (empty\",\n \"cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Configure backend level settings that are applied to every key in\",\n \"can be undone using the undelete path. Supported methods: POST: /{mount_point}/delete/{path}. Produces: 204\",\n \"path: str | unicode :param max_versions: The number of versions to keep per\",\n \"in the key-value store. Supported methods: POST: /{mount_point}/config. Produces: 204 (empty body) :param\",\n \"of the request. :rtype: dict \\\"\\\"\\\" params = { 'options': {}, 'data': secret,\",\n \"URL. :type path: str | unicode :param mount_point: The \\\"path\\\" the secret engine\",\n \"deleted. Defaults to 10. :type max_versions: int :param cas_required: If true all keys\",\n \"versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def\",\n \"POST: /{mount_point}/undelete/{path}. Produces: 204 (empty body) :param path: Specifies the path of the\",\n \"If not set the latest version is returned. :type version: int :param mount_point:\",\n \"list containing one or more integers, \\\"{versions}\\\" provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg) params\",\n \"create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Create a new version of a secret at\",\n \") raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point,\",\n \"return self._adapter.post( url=api_path, json=params, ) def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Permanently remove the\",\n \":param versions: The versions to undelete. The versions will be restored and their\",\n \"-*- coding: utf-8 -*- \\\"\\\"\\\"KvV2 methods module.\\\"\\\"\\\" from hvac import exceptions, utils from\",\n \"reads, but the underlying data will not be removed. A delete can be\",\n \"in key names. The values themselves are not accessible via this command. Supported\",\n \"will be removed. Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path:\",\n \"yet exist, the calling token must have an ACL policy granting the create\",\n \":type path: str | unicode :param cas: Set the \\\"cas\\\" value to use\",\n \"if the key's current version matches the version specified in the cas parameter.\",\n \"on all write requests. :type cas_required: bool :param mount_point: The \\\"path\\\" the secret\",\n \"from hvac import exceptions, utils from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class\",\n \"If false, the backend's configuration will be used. :type cas_required: bool :param mount_point:\",\n \"204 (empty body) :param path: Specifies the path of the secret to delete.\",\n \"hvac import exceptions, utils from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase):\",\n \"the key-value store. This restores the data, allowing it to be returned on\",\n \"the secret to destroy. This is specified as part of the URL. :type\",\n \"version history will be removed. Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty body)\",\n \"via this command. Supported methods: LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies\",\n \"new version of a secret at the specified location. If the value does\",\n \"Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \\\"\\\"\\\" def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Configure backend\",\n \"configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Configure backend level settings that are applied to every\",\n \"path: Path :type path: str | unicode :param secret: The contents of the\",\n \"the KV Version 2 configuration. Supported methods: GET: /auth/{mount_point}/config. Produces: 200 application/json :param\",\n \"self._adapter.get( url=api_path, ) return response.json() def update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Updates the\",\n \"set to 0 a write will only be allowed if the key doesn't\",\n \"all keys will require the cas parameter to be set on all write\",\n \"the secret to undelete. This is specified as part of the URL. :type\",\n \"to all keys, but a key's metadata setting can overwrite this value. Once\",\n \"part of the URL. :type path: str | unicode :param versions: The versions\",\n \"application/json :param path: Specifies the path of the secret to read. This is\",\n \") return response.json() def update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Updates the max_versions of\",\n \"request. :rtype: dict \\\"\\\"\\\" # First, do a read. try: current_secret_version = self.read_secret_version(\",\n \"| unicode :return: The JSON response of the request. :rtype: dict \\\"\\\"\\\" params\",\n \"in normal get requests. :type versions: int :param mount_point: The \\\"path\\\" the secret\",\n \"and numbers for the provided path from the key-value store. Supported methods: POST:\",\n \"true all keys will require the cas parameter to be set on all\",\n \"the cas parameter to be set on all write requests. :type cas_required: bool\",\n \"key metadata and all version data for the specified key. All version history\",\n \":rtype: dict \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.list( url=api_path, )\",\n \"versions for the secret at the specified path. Supported methods: GET: /{mount_point}/metadata/{path}. Produces:\",\n \"permanently deleted. :type versions: list of int :param mount_point: The \\\"path\\\" the secret\",\n \"not None: params['version'] = version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.get(\",\n \"A delete can be undone using the undelete path. Supported methods: DELETE: /{mount_point}/data/{path}.\",\n \"specified path. Supported methods: GET: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the\",\n \"path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete\",\n \"the specified version data and numbers for the provided path from the key-value\",\n \"returned. :type version: int :param mount_point: The \\\"path\\\" the secret engine was mounted\",\n \"utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Return\",\n \"Supported methods: GET: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Specifies the path of\",\n \"if version is not None: params['version'] = version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path)\",\n \"unicode :return: The JSON response of the create_or_update_secret request. :rtype: dict \\\"\\\"\\\" #\",\n \"version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, params=params, ) return\",\n \"mount_point=mount_point, ) response = self._adapter.get(url=api_path) return response.json() def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve\",\n \"the secret. This marks the versions as deleted and will stop them from\",\n \"methods: DELETE: /{mount_point}/data/{path}. Produces: 204 (empty body) :param path: Specifies the path of\",\n \"remove the specified version data and numbers for the provided path from the\",\n \"param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path)\",\n \"the specified versions of the secret. This marks the versions as deleted and\",\n \"requests. :type versions: list of int :param mount_point: The \\\"path\\\" the secret engine\",\n \"10. :type max_versions: int :param cas_required: If true all keys will require the\",\n \"not None: params['options']['cas'] = cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.post(\",\n \"response of the create_or_update_secret request. :rtype: dict \\\"\\\"\\\" # First, do a read.\",\n \"Version 2 configuration. Supported methods: GET: /auth/{mount_point}/config. Produces: 200 application/json :param mount_point: The\",\n \"Write back updated secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self,\",\n \"params['max_versions'] = max_versions if cas_required is not None: if not isinstance(cas_required, bool): error_msg\",\n \"JSON response of the create_or_update_secret request. :rtype: dict \\\"\\\"\\\" # First, do a\",\n \"path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete of the secret's latest version at the\",\n \"used. Once a key has more than the configured allowed versions the oldest\",\n \"them from being returned from reads, but the underlying data will not be\",\n \"versions to be deleted. The versioned data will not be deleted, but it\",\n \"Engine - Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \\\"\\\"\\\" def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT):\",\n \"cas_required is not None: params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post(\",\n \"exists, the calling token must have an ACL policy granting the update capability.\",\n \"parameter to be set on all write requests. If false, the backend's configuration\",\n \"longer be returned in normal get requests. :type versions: int :param mount_point: The\",\n \"existing path. Supported methods: POST: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Path\",\n \"the URL. :type path: str | unicode :param version: Specifies the version to\",\n \"ACL policy granting the create capability. If the value already exists, the calling\",\n \"the path of the secret to destroy. This is specified as part of\",\n \"0: error_msg = 'argument to \\\"versions\\\" must be a list containing one or\",\n \"update capability. Supported methods: POST: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Path :type\",\n \"numbers for the provided path from the key-value store. Supported methods: POST: /{mount_point}/destroy/{path}.\",\n \") def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete of the secret's latest\",\n \"the key doesn't exist. If the index is non-zero the write will only\",\n \"self.read_secret_version( path=path, mount_point=mount_point, ) except exceptions.InvalidPath: raise exceptions.InvalidPath('No value found at \\\"{path}\\\"; patch\",\n \"= { 'max_versions': max_versions, } if cas_required is not None: params['cas_required'] = cas_required\",\n \"(API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \\\"\\\"\\\" def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Configure backend level settings\",\n \"'max_versions': max_versions, } if cas_required is not None: params['cas_required'] = cas_required api_path =\",\n \"path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Return a list of key names at the specified location. Folders\",\n \"the URL. :type path: str | unicode :param versions: The versions to be\",\n \":return: The JSON response of the request. :rtype: dict \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}',\",\n \"unicode :return: The response of the request. :rtype: requests.Response \\\"\\\"\\\" params = {}\",\n \"self._adapter.delete( url=api_path, ) def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete of\",\n \"allowing it to be returned on get requests. Supported methods: POST: /{mount_point}/undelete/{path}. Produces:\",\n \"input must be a folder; list on a file will not return a\",\n \"methods: GET: /auth/{mount_point}/config. Produces: 200 application/json :param mount_point: The \\\"path\\\" the secret engine\",\n \"path in the key-value store. This restores the data, allowing it to be\",\n \"str | unicode :param versions: The versions to undelete. The versions will be\",\n \"to destroy. This is specified as part of the URL. :type path: str\",\n \"secret to undelete. This is specified as part of the URL. :type path:\",\n \"the URL. :type path: str | unicode :param versions: The versions to destroy.\",\n \"exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return\",\n \"cas=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Create a new version of a secret at the specified location.\",\n \"POST: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Path :type path: str | unicode\",\n \":return: The JSON response of the request. :rtype: dict \\\"\\\"\\\" api_path = utils.format_url(\",\n \"patch only works on existing data.'.format(path=path)) # Update existing secret dict. patched_secret =\",\n \"path of the secret to delete. This is specified as part of the\",\n \"mount_point=mount_point, path=path) response = self._adapter.list( url=api_path, ) return response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT):\",\n \"the version as deleted and will stop it from being returned from reads,\",\n \"will only be allowed if the key doesn't exist. If the index is\",\n \"an existing path. Supported methods: POST: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path:\",\n \"folder; list on a file will not return a value. Note that no\",\n \"= { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path,\",\n \"error_msg = 'bool expected for cas_required param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] =\",\n \"sensitive information in key names. The values themselves are not accessible via this\",\n \"cas_required: If true the key will require the cas parameter to be set\",\n \"\\\"\\\"\\\" params = { 'max_versions': max_versions, } if cas_required is not None: params['cas_required']\",\n \"command. Supported methods: LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path\",\n \"Produces: 200 application/json :param path: Specifies the path of the secrets to list.\",\n \"/{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Path :type path: str | unicode\",\n \"= utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path, json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Read the\",\n \"returned on normal get requests. :type versions: list of int :param mount_point: The\",\n \"be restored and their data will be returned on normal get requests. :type\",\n \"received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post(\",\n \"underlying data will not be removed. A delete can be undone using the\",\n \"in the KV store without overwriting. :param path: Path :type path: str |\",\n \":param path: Specifies the path of the secret to read. This is specified\",\n \"= 'bool expected for cas_required param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required\",\n \"if not isinstance(versions, list) or len(versions) == 0: error_msg = 'argument to \\\"versions\\\"\",\n \"dict :param mount_point: The \\\"path\\\" the secret engine was mounted on. :type mount_point:\",\n \"= self._adapter.list( url=api_path, ) return response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the metadata\",\n \"location. Folders are suffixed with /. The input must be a folder; list\",\n \"# Write back updated secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def\",\n \"JSON response of the request. :rtype: dict \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path)\",\n \"not set, the backend's configured max version is used. Once a key has\",\n \"version: Specifies the version to return. If not set the latest version is\",\n \"# Update existing secret dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) # Write back updated\",\n \"response of the request. :rtype: requests.Response \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return\",\n \"the key-value store. Supported methods: POST: /{mount_point}/config. Produces: 204 (empty body) :param max_versions:\",\n \"secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete of the\",\n \"deleted. The versioned data will not be deleted, but it will no longer\",\n \"response.json() def create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Create a new version of a\",\n \"= 'secret' class KvV2(VaultApiBase): \\\"\\\"\\\"KV Secrets Engine - Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html\",\n \"secret at the specified location. If the value does not yet exist, the\",\n \":return: The JSON response of the create_or_update_secret request. :rtype: dict \\\"\\\"\\\" # First,\",\n \"This value applies to all keys, but a key's metadata setting can overwrite\",\n \"response of the request. :rtype: dict \\\"\\\"\\\" api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, )\",\n \"the secret's latest version at the specified location. This marks the version as\",\n \"performed on keys; do not encode sensitive information in key names. The values\",\n \"dict \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, ) return\",\n \"= 'argument to \\\"versions\\\" must be a list containing one or more integers,\",\n \"on an existing path. Supported methods: POST: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param\",\n \"= self.read_secret_version( path=path, mount_point=mount_point, ) except exceptions.InvalidPath: raise exceptions.InvalidPath('No value found at \\\"{path}\\\";\",\n \"deleted and will stop it from being returned from reads, but the underlying\",\n \"if not isinstance(cas_required, bool): error_msg = 'bool expected for cas_required param, {type} received'.format(type=type(cas_required))\",\n \"true the key will require the cas parameter to be set on all\",\n \") raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point,\",\n \") def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Read the KV Version 2 configuration. Supported methods: GET:\",\n \"{type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return\",\n \"part of the URL. :type path: str | unicode :param version: Specifies the\",\n \"be undone using the undelete path. Supported methods: POST: /{mount_point}/delete/{path}. Produces: 204 (empty\",\n \"value. Note that no policy-based filtering is performed on keys; do not encode\",\n \"store. Supported methods: POST: /{mount_point}/config. Produces: 204 (empty body) :param max_versions: The number\",\n \"params['options']['cas'] = cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.post( url=api_path, json=params,\",\n \"at \\\"{path}\\\"; patch only works on existing data.'.format(path=path)) # Update existing secret dict.\",\n \"an ACL policy granting the create capability. If the value already exists, the\",\n \":type max_versions: int :param cas_required: If true the key will require the cas\",\n \"location. Supported methods: GET: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Specifies the path\",\n \"are not accessible via this command. Supported methods: LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json\",\n \"be allowed. If set to 0 a write will only be allowed if\",\n \"the write will only be allowed if the key's current version matches the\",\n \"to be set on all write requests. :type cas_required: bool :param mount_point: The\",\n \"use a Check-And-Set operation. If not set the write will be allowed. If\",\n \"the key's current version matches the version specified in the cas parameter. :type\",\n \"not None: if not isinstance(cas_required, bool): error_msg = 'bool expected for cas_required param,\",\n \"overwrite this value. Once a key has more than the configured allowed versions\",\n \"utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Delete\",\n \"on. :type mount_point: str | unicode :return: The JSON response of the request.\",\n \"delete. This is specified as part of the URL. :type path: str |\",\n \"mount_point=mount_point, ) def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete of the secret's\",\n \"The versions to destroy. Their data will be permanently deleted. :type versions: list\",\n \"= {} if max_versions is not None: params['max_versions'] = max_versions if cas_required is\",\n \"number of versions to keep per key. This value applies to all keys,\",\n \"path: Specifies the path of the secret to read. This is specified as\",\n \"key names. The values themselves are not accessible via this command. Supported methods:\",\n \"if the key doesn't exist. If the index is non-zero the write will\",\n \"api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def undelete_secret_versions(self, path,\",\n \"the latest version is returned. :type version: int :param mount_point: The \\\"path\\\" the\",\n \"Specifies the path of the secret to delete. This is specified as part\",\n \"the cas parameter to be set on all write requests. If false, the\",\n \"2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \\\"\\\"\\\" def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Configure backend level\",\n \"Supported methods: DELETE: /{mount_point}/data/{path}. Produces: 204 (empty body) :param path: Specifies the path\",\n \"json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Read the KV Version 2 configuration. Supported methods:\",\n \"path of the secret to undelete. This is specified as part of the\",\n \"ACL policy granting the update capability. Supported methods: POST: /{mount_point}/data/{path}. Produces: 200 application/json\",\n \"url=api_path, json=params, ) def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Return a list of key names\",\n \"204 (empty body) :param path: Specifies the path of the secret to destroy.\",\n \"secret dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) # Write back updated secret. return self.create_or_update_secret(\",\n \"key. All version history will be removed. Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204\",\n \"value found at \\\"{path}\\\"; patch only works on existing data.'.format(path=path)) # Update existing\",\n \"from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase): \\\"\\\"\\\"KV Secrets Engine -\",\n \"request. :rtype: dict \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.list( url=api_path,\",\n \"calling token must have an ACL policy granting the create capability. If the\",\n \"raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path,\",\n \"secret: dict :param mount_point: The \\\"path\\\" the secret engine was mounted on. :type\",\n \"\\\"\\\"\\\"Return a list of key names at the specified location. Folders are suffixed\",\n \") except exceptions.InvalidPath: raise exceptions.InvalidPath('No value found at \\\"{path}\\\"; patch only works on\",\n \"data.'.format(path=path)) # Update existing secret dict. patched_secret = current_secret_version['data']['data'] patched_secret.update(secret) # Write back\",\n \"write requests. :type cas_required: bool :param mount_point: The \\\"path\\\" the secret engine was\",\n \") def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Delete (permanently) the key metadata and all version\",\n \"undone using the undelete path. Supported methods: DELETE: /{mount_point}/data/{path}. Produces: 204 (empty body)\",\n \"must be a folder; list on a file will not return a value.\",\n \"value. Once a key has more than the configured allowed versions the oldest\",\n \"versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def\",\n \"it will no longer be returned in normal get requests. :type versions: int\",\n \"write will only be allowed if the key doesn't exist. If the index\",\n \"A delete can be undone using the undelete path. Supported methods: POST: /{mount_point}/delete/{path}.\",\n \"will be permanently deleted. Defaults to 10. :type max_versions: int :param cas_required: If\",\n \"the \\\"cas\\\" value to use a Check-And-Set operation. If not set the write\",\n \"try: current_secret_version = self.read_secret_version( path=path, mount_point=mount_point, ) except exceptions.InvalidPath: raise exceptions.InvalidPath('No value found\",\n \"response.json() def update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Updates the max_versions of cas_required setting\",\n \"versions: list of int :param mount_point: The \\\"path\\\" the secret engine was mounted\",\n \"methods: POST: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Path :type path: str\",\n \"every key in the key-value store. Supported methods: POST: /{mount_point}/config. Produces: 204 (empty\",\n \"max version is used. Once a key has more than the configured allowed\",\n \"is not None: params['version'] = version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response =\",\n \"on all write requests. If false, the backend's configuration will be used. :type\",\n \"def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Undelete the data for the provided version and\",\n \"mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Permanently remove the specified version data and numbers for the provided path\",\n \"All version history will be removed. Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty\",\n \"of the request. :rtype: requests.Response \\\"\\\"\\\" if not isinstance(versions, list) or len(versions) ==\",\n \"keep per key. This value applies to all keys, but a key's metadata\",\n \"self._adapter.get(url=api_path) return response.json() def read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the secret at the\",\n \"If the value already exists, the calling token must have an ACL policy\",\n \"to 10. :type max_versions: int :param cas_required: If true all keys will require\",\n \"application/json :param mount_point: The \\\"path\\\" the secret engine was mounted on. :type mount_point:\",\n \"delete of the specified versions of the secret. This marks the versions as\",\n \"If not set the write will be allowed. If set to 0 a\",\n \"path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete of the specified versions of the\",\n \"data will not be removed. A delete can be undone using the undelete\",\n \"mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Return a\",\n \"path=path) return self._adapter.post( url=api_path, json=params, ) def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Undelete the\",\n \"will be allowed. If set to 0 a write will only be allowed\",\n \"The response of the request. :rtype: requests.Response \\\"\\\"\\\" params = {} if max_versions\",\n \"an ACL policy granting the update capability. Supported methods: POST: /{mount_point}/data/{path}. Produces: 200\",\n \"methods: POST: /{mount_point}/config. Produces: 204 (empty body) :param max_versions: The number of versions\",\n \"response of the request. :rtype: requests.Response \\\"\\\"\\\" params = {} if max_versions is\",\n \"back updated secret. return self.create_or_update_secret( path=path, cas=current_secret_version['data']['metadata']['version'], secret=patched_secret, mount_point=mount_point, ) def delete_latest_version_of_secret(self, path,\",\n \"destroy. Their data will be permanently deleted. :type versions: list of int :param\",\n \"str | unicode :param secret: The contents of the \\\"secret\\\" dict will be\",\n \"encode sensitive information in key names. The values themselves are not accessible via\",\n \":type cas_required: bool :param mount_point: The \\\"path\\\" the secret engine was mounted on.\",\n \"JSON response of the request. :rtype: dict \\\"\\\"\\\" params = { 'options': {},\",\n \"| unicode :param versions: The versions to destroy. Their data will be permanently\",\n \"not be deleted, but it will no longer be returned in normal get\",\n \"versions the oldest version will be permanently deleted. :type max_versions: int :param cas_required:\",\n \"part of the URL. :type path: str | unicode :param mount_point: The \\\"path\\\"\",\n \"return self._adapter.post( url=api_path, json=params, ) def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Undelete the data\",\n \"specified as part of the URL. :type path: str | unicode :param version:\",\n \"= version api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, params=params, )\",\n \"on a file will not return a value. Note that no policy-based filtering\",\n \"specified location. This marks the version as deleted and will stop it from\",\n \"the request. :rtype: dict \\\"\\\"\\\" params = { 'options': {}, 'data': secret, }\",\n \"of the request. :rtype: requests.Response \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.delete(\",\n \"application/json :param path: Path :type path: str | unicode :param cas: Set the\",\n \"mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete of the secret's latest version at the specified\",\n \":param path: Specifies the path of the secret to destroy. This is specified\",\n \"not be removed. A delete can be undone using the undelete path. Supported\",\n \"The contents of the \\\"secret\\\" dict will be stored and returned on read.\",\n \"the specified location. If the value does not yet exist, the calling token\",\n \"at the specified location. This marks the version as deleted and will stop\",\n \"Specifies the path of the secrets to list. This is specified as part\",\n \"mounted on. :type mount_point: str | unicode :return: The response of the request.\",\n \"backend's configured max version is used. Once a key has more than the\",\n \"POST: /{mount_point}/config. Produces: 204 (empty body) :param max_versions: The number of versions to\",\n \"the undelete path. Supported methods: DELETE: /{mount_point}/data/{path}. Produces: 204 (empty body) :param path:\",\n \"engine was mounted on. :type mount_point: str | unicode :return: The response of\",\n \"= utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response = self._adapter.get(url=api_path) return response.json() def read_secret_version(self, path,\",\n \"def create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Create a new version of a secret\",\n \"hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase): \\\"\\\"\\\"KV Secrets Engine - Version\",\n \"url=api_path, params=params, ) return response.json() def create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Create a\",\n \"only be allowed if the key doesn't exist. If the index is non-zero\",\n \"If not set, the backend's configured max version is used. Once a key\",\n \"deleted. :type max_versions: int :param cas_required: If true the key will require the\",\n \"/{mount_point}/config. Produces: 204 (empty body) :param max_versions: The number of versions to keep\",\n \"\\\"\\\"\\\" params = {} if max_versions is not None: params['max_versions'] = max_versions if\",\n \"be a list containing one or more integers, \\\"{versions}\\\" provided.'.format( versions=versions ) raise\",\n \"The \\\"path\\\" the secret engine was mounted on. :type mount_point: str | unicode\",\n \"url=api_path, ) return response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the metadata and versions\",\n \"-*- \\\"\\\"\\\"KvV2 methods module.\\\"\\\"\\\" from hvac import exceptions, utils from hvac.api.vault_api_base import VaultApiBase\",\n \"list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Return a list of key names at the specified location.\",\n \"key names at the specified location. Folders are suffixed with /. The input\",\n \"of the URL. :type path: str | unicode :param mount_point: The \\\"path\\\" the\",\n \"token must have an ACL policy granting the update capability. Supported methods: POST:\",\n \"accessible via this command. Supported methods: LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path:\",\n \"class KvV2(VaultApiBase): \\\"\\\"\\\"KV Secrets Engine - Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \\\"\\\"\\\" def\",\n \"response.json() def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Set or update data in the KV\",\n \"set on all write requests. :type cas_required: bool :param mount_point: The \\\"path\\\" the\",\n \":param path: Specifies the path of the secrets to list. This is specified\",\n \"\\\"\\\"\\\"Retrieve the metadata and versions for the secret at the specified path. Supported\",\n \"data will be returned on normal get requests. :type versions: list of int\",\n \"unicode :param version: Specifies the version to return. If not set the latest\",\n \"must have an ACL policy granting the create capability. If the value already\",\n \"(empty body) :param max_versions: The number of versions to keep per key. This\",\n \"The versions will be restored and their data will be returned on normal\",\n \"Check-And-Set operation. If not set the write will be allowed. If set to\",\n \"restored and their data will be returned on normal get requests. :type versions:\",\n \"requests. If false, the backend's configuration will be used. :type cas_required: bool :param\",\n \"\\\"\\\"\\\"Permanently remove the specified version data and numbers for the provided path from\",\n \"allowed versions the oldest version will be permanently deleted. :type max_versions: int :param\",\n \"of the URL. :type path: str | unicode :param version: Specifies the version\",\n \"are applied to every key in the key-value store. Supported methods: POST: /{mount_point}/config.\",\n \"non-zero the write will only be allowed if the key's current version matches\",\n \"a read. try: current_secret_version = self.read_secret_version( path=path, mount_point=mount_point, ) except exceptions.InvalidPath: raise exceptions.InvalidPath('No\",\n \"value does not yet exist, the calling token must have an ACL policy\",\n \"KV store without overwriting. :param path: Path :type path: str | unicode :param\",\n \"\\\"\\\"\\\"Issue a soft delete of the specified versions of the secret. This marks\",\n \"request. :rtype: dict \\\"\\\"\\\" params = {} if version is not None: params['version']\",\n \"= utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT):\",\n \"all write requests. If false, the backend's configuration will be used. :type cas_required:\",\n \":rtype: requests.Response \\\"\\\"\\\" params = { 'max_versions': max_versions, } if cas_required is not\",\n \"list of key names at the specified location. Folders are suffixed with /.\",\n \"cas_required is not None: if not isinstance(cas_required, bool): error_msg = 'bool expected for\",\n \"be set on all write requests. If false, the backend's configuration will be\",\n \"for the secret at the specified path. Supported methods: GET: /{mount_point}/metadata/{path}. Produces: 200\",\n \"Path :type path: str | unicode :param secret: The contents of the \\\"secret\\\"\",\n \"exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return\",\n \"url=api_path, json=params, ) def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Delete (permanently) the key metadata and\",\n \"read. try: current_secret_version = self.read_secret_version( path=path, mount_point=mount_point, ) except exceptions.InvalidPath: raise exceptions.InvalidPath('No value\",\n \"Supported methods: POST: /{mount_point}/undelete/{path}. Produces: 204 (empty body) :param path: Specifies the path\",\n \"path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Undelete the data for the provided version and path in\",\n \"specified location. If the value does not yet exist, the calling token must\",\n \"cas_required: If true all keys will require the cas parameter to be set\",\n \"and will stop it from being returned from reads, but the underlying data\",\n \"undelete. This is specified as part of the URL. :type path: str |\",\n \"methods: POST: /{mount_point}/destroy/{path}. Produces: 204 (empty body) :param path: Specifies the path of\",\n \"# First, do a read. try: current_secret_version = self.read_secret_version( path=path, mount_point=mount_point, ) except\",\n \"only works on existing data.'.format(path=path)) # Update existing secret dict. patched_secret = current_secret_version['data']['data']\",\n \"/{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Specifies the path of the secret\",\n \"If the value does not yet exist, the calling token must have an\",\n \"the path of the secret to delete. This is specified as part of\",\n \"url=api_path, json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Read the KV Version 2 configuration. Supported\",\n \"request. :rtype: dict \\\"\\\"\\\" params = { 'options': {}, 'data': secret, } if\",\n \"must be a list containing one or more integers, \\\"{versions}\\\" provided.'.format( versions=versions )\",\n \"secret engine was mounted on. :type mount_point: str | unicode :return: The JSON\",\n \"| unicode :return: The response of the request. :rtype: requests.Response \\\"\\\"\\\" api_path =\",\n \"of the request. :rtype: requests.Response \\\"\\\"\\\" params = {} if max_versions is not\",\n \"params=params, ) return response.json() def create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Create a new\",\n \"from the key-value store. Supported methods: POST: /{mount_point}/destroy/{path}. Produces: 204 (empty body) :param\",\n \"cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Updates the max_versions of cas_required setting on an existing path. Supported\",\n \"of the URL. :type path: str | unicode :param versions: The versions to\",\n \"dict \\\"\\\"\\\" api_path = utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response = self._adapter.get(url=api_path) return response.json()\",\n \"of the request. :rtype: requests.Response \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete(\",\n \"the data, allowing it to be returned on get requests. Supported methods: POST:\",\n \"return a value. Note that no policy-based filtering is performed on keys; do\",\n \"path=path) return self._adapter.post( url=api_path, json=params, ) def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Return a list\",\n \"Folders are suffixed with /. The input must be a folder; list on\",\n \"marks the versions as deleted and will stop them from being returned from\",\n \"be undone using the undelete path. Supported methods: DELETE: /{mount_point}/data/{path}. Produces: 204 (empty\",\n \"the configured allowed versions the oldest version will be permanently deleted. :type max_versions:\",\n \"will be permanently deleted. :type max_versions: int :param cas_required: If true the key\",\n \"not isinstance(cas_required, bool): error_msg = 'bool expected for cas_required param, {type} received'.format(type=type(cas_required)) raise\",\n \"get requests. :type versions: list of int :param mount_point: The \\\"path\\\" the secret\",\n \"key-value store. Supported methods: POST: /{mount_point}/destroy/{path}. Produces: 204 (empty body) :param path: Specifies\",\n \"mount_point: The \\\"path\\\" the secret engine was mounted on. :type mount_point: str |\",\n \"path=path) response = self._adapter.get( url=api_path, params=params, ) return response.json() def create_or_update_secret(self, path, secret,\",\n \"must have an ACL policy granting the update capability. Supported methods: POST: /{mount_point}/data/{path}.\",\n \") return response.json() def create_or_update_secret(self, path, secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Create a new version\",\n \"LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path of the secrets\",\n \"the specified location. Folders are suffixed with /. The input must be a\",\n \"but it will no longer be returned in normal get requests. :type versions:\",\n \"allowed if the key's current version matches the version specified in the cas\",\n \"'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, )\",\n \"= { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path,\",\n \"on get requests. Supported methods: POST: /{mount_point}/undelete/{path}. Produces: 204 (empty body) :param path:\",\n \"value applies to all keys, but a key's metadata setting can overwrite this\",\n \"a write will only be allowed if the key doesn't exist. If the\",\n \"version matches the version specified in the cas parameter. :type cas: int :param\",\n \"utils from hvac.api.vault_api_base import VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase): \\\"\\\"\\\"KV Secrets Engine\",\n \"for the provided version and path in the key-value store. This restores the\",\n \"Specifies the path of the secret to read. This is specified as part\",\n \":type path: str | unicode :param versions: The versions to undelete. The versions\",\n \"methods: LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path of the\",\n \"is performed on keys; do not encode sensitive information in key names. The\",\n \"key will require the cas parameter to be set on all write requests.\",\n \"the secret engine was mounted on. :type mount_point: str | unicode :return: The\",\n \"the oldest version will be permanently deleted. :type max_versions: int :param cas_required: If\",\n \"versions to keep per key. If not set, the backend's configured max version\",\n \"a list of key names at the specified location. Folders are suffixed with\",\n \"key in the key-value store. Supported methods: POST: /{mount_point}/config. Produces: 204 (empty body)\",\n \"methods: POST: /{mount_point}/delete/{path}. Produces: 204 (empty body) :param path: Specifies the path of\",\n \"set on all write requests. If false, the backend's configuration will be used.\",\n \"be permanently deleted. :type max_versions: int :param cas_required: If true the key will\",\n \"int :param secret: The contents of the \\\"secret\\\" dict will be stored and\",\n \"unicode :return: The response of the request. :rtype: requests.Response \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/data/{path}',\",\n \"secret, cas=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Create a new version of a secret at the specified\",\n \"of the secret to read. This is specified as part of the URL.\",\n \"int :param cas_required: If true all keys will require the cas parameter to\",\n \"versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Permanently remove the specified version data and numbers for the provided\",\n \"a folder; list on a file will not return a value. Note that\",\n \"mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Undelete the data for the provided version and path in the key-value\",\n \"secret to read. This is specified as part of the URL. :type path:\",\n \"api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, params=params, ) return response.json()\",\n \"already exists, the calling token must have an ACL policy granting the update\",\n \"0 a write will only be allowed if the key doesn't exist. If\",\n \"will require the cas parameter to be set on all write requests. If\",\n \"data for the specified key. All version history will be removed. Supported methods:\",\n \"cas: int :param secret: The contents of the \\\"secret\\\" dict will be stored\",\n \"is not None: params['max_versions'] = max_versions if cas_required is not None: if not\",\n \"def delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete of the secret's latest version\",\n \"of the secret to destroy. This is specified as part of the URL.\",\n \"The response of the request. :rtype: requests.Response \\\"\\\"\\\" if not isinstance(versions, list) or\",\n \"methods: GET: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the path of the\",\n \"unicode :param versions: The versions to destroy. Their data will be permanently deleted.\",\n \"normal get requests. :type versions: int :param mount_point: The \\\"path\\\" the secret engine\",\n \"response = self._adapter.get( url=api_path, ) return response.json() def update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT):\",\n \"versions will be restored and their data will be returned on normal get\",\n \":rtype: dict \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, )\",\n \"unicode :param versions: The versions to undelete. The versions will be restored and\",\n \":rtype: requests.Response \\\"\\\"\\\" params = {} if max_versions is not None: params['max_versions'] =\",\n \"removed. A delete can be undone using the undelete path. Supported methods: POST:\",\n \"version specified in the cas parameter. :type cas: int :param secret: The contents\",\n \"path: str | unicode :param versions: The versions to undelete. The versions will\",\n \"can overwrite this value. Once a key has more than the configured allowed\",\n \"to be deleted. The versioned data will not be deleted, but it will\",\n \"= { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path,\",\n \"200 application/json :param path: Path :type path: str | unicode :param cas: Set\",\n \"latest version is returned. :type version: int :param mount_point: The \\\"path\\\" the secret\",\n \"of the request. :rtype: requests.Response \\\"\\\"\\\" params = { 'max_versions': max_versions, } if\",\n \"Produces: 204 (empty body) :param path: Path :type path: str | unicode :param\",\n \"on. :type mount_point: str | unicode :return: The response of the request. :rtype:\",\n \"not None: params['max_versions'] = max_versions if cas_required is not None: if not isinstance(cas_required,\",\n \"= cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def\",\n \"return self._adapter.post( url=api_path, json=params, ) def delete_metadata_and_all_versions(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Delete (permanently) the key\",\n \"create capability. If the value already exists, the calling token must have an\",\n \"be allowed if the key's current version matches the version specified in the\",\n \"cas parameter to be set on all write requests. :type cas_required: bool :param\",\n \"of cas_required setting on an existing path. Supported methods: POST: /{mount_point}/metadata/{path}. Produces: 204\",\n \"provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path =\",\n \"history will be removed. Supported methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param\",\n \"cas_required setting on an existing path. Supported methods: POST: /{mount_point}/metadata/{path}. Produces: 204 (empty\",\n \":type mount_point: str | unicode :return: The JSON response of the create_or_update_secret request.\",\n \"= utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.get( url=api_path, params=params, ) return response.json() def\",\n \"exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params,\",\n \"methods: POST: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Path :type path: str |\",\n \"be allowed if the key doesn't exist. If the index is non-zero the\",\n \"response of the request. :rtype: dict \\\"\\\"\\\" params = {} if version is\",\n \"as deleted and will stop it from being returned from reads, but the\",\n \"one or more integers, \\\"{versions}\\\" provided.'.format( versions=versions ) raise exceptions.ParamValidationError(error_msg) params = {\",\n \"self._adapter.post( url=api_path, json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Read the KV Version 2 configuration.\",\n \"path: Specifies the path of the secrets to list. This is specified as\",\n \"\\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.list( url=api_path, ) return response.json()\",\n \"using the undelete path. Supported methods: POST: /{mount_point}/delete/{path}. Produces: 204 (empty body) :param\",\n \"Defaults to 10. :type max_versions: int :param cas_required: If true all keys will\",\n \"| unicode :return: The JSON response of the create_or_update_secret request. :rtype: dict \\\"\\\"\\\"\",\n \"\\\"\\\"\\\" if not isinstance(versions, list) or len(versions) == 0: error_msg = 'argument to\",\n \"no policy-based filtering is performed on keys; do not encode sensitive information in\",\n \"secret, } if cas is not None: params['options']['cas'] = cas api_path = utils.format_url('/v1/{mount_point}/data/{path}',\",\n \"'argument to \\\"versions\\\" must be a list containing one or more integers, \\\"{versions}\\\"\",\n \"per key. This value applies to all keys, but a key's metadata setting\",\n \"does not yet exist, the calling token must have an ACL policy granting\",\n \"parameter. :type cas: int :param secret: The contents of the \\\"secret\\\" dict will\",\n \"url=api_path, json=params, ) def undelete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Undelete the data for the\",\n \"return response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the metadata and versions for the\",\n \"params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path, json=params, ) def\",\n \"GET: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Specifies the path of the secret\",\n \"return self._adapter.post( url=api_path, json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Read the KV Version 2\",\n \"marks the version as deleted and will stop it from being returned from\",\n \"If the index is non-zero the write will only be allowed if the\",\n \"delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete of the specified versions of\",\n \"secrets to list. This is specified as part of the URL. :type path:\",\n \"false, the backend's configuration will be used. :type cas_required: bool :param mount_point: The\",\n \"request. :rtype: requests.Response \\\"\\\"\\\" params = {} if max_versions is not None: params['max_versions']\",\n \":return: The response of the request. :rtype: requests.Response \\\"\\\"\\\" params = { 'max_versions':\",\n \"path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Delete (permanently) the key metadata and all version data for the\",\n \"str | unicode :return: The response of the request. :rtype: requests.Response \\\"\\\"\\\" if\",\n \"to destroy. Their data will be permanently deleted. :type versions: list of int\",\n \"update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Updates the max_versions of cas_required setting on an\",\n \"without overwriting. :param path: Path :type path: str | unicode :param secret: The\",\n \"secret at the specified location. Supported methods: GET: /{mount_point}/data/{path}. Produces: 200 application/json :param\",\n \"a Check-And-Set operation. If not set the write will be allowed. If set\",\n \"response of the request. :rtype: requests.Response \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) return\",\n \"\\\"\\\"\\\"Set or update data in the KV store without overwriting. :param path: Path\",\n \"2 configuration. Supported methods: GET: /auth/{mount_point}/config. Produces: 200 application/json :param mount_point: The \\\"path\\\"\",\n \"\\\"\\\"\\\"Configure backend level settings that are applied to every key in the key-value\",\n \"URL. :type path: str | unicode :param versions: The versions to undelete. The\",\n \"path=path) return self._adapter.post( url=api_path, json=params, ) def destroy_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Permanently remove\",\n \":return: The response of the request. :rtype: requests.Response \\\"\\\"\\\" if not isinstance(versions, list)\",\n \"allowed if the key doesn't exist. If the index is non-zero the write\",\n \"names. The values themselves are not accessible via this command. Supported methods: LIST:\",\n \"'secret' class KvV2(VaultApiBase): \\\"\\\"\\\"KV Secrets Engine - Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \\\"\\\"\\\"\",\n \"{ 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params,\",\n \"mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Set or update data in the KV store without overwriting. :param path:\",\n \"= utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def destroy_secret_versions(self, path, versions,\",\n \"path, version=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the secret at the specified location. Supported methods: GET:\",\n \"return self._adapter.post( url=api_path, json=params, ) def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Return a list of\",\n \"the URL. :type path: str | unicode :param mount_point: The \\\"path\\\" the secret\",\n \"the metadata and versions for the secret at the specified path. Supported methods:\",\n \"do not encode sensitive information in key names. The values themselves are not\",\n \"the provided version and path in the key-value store. This restores the data,\",\n \"{}, 'data': secret, } if cas is not None: params['options']['cas'] = cas api_path\",\n \"\\\"path\\\" the secret engine was mounted on. :type mount_point: str | unicode :return:\",\n \"for cas_required param, {type} received'.format(type=type(cas_required)) raise exceptions.ParamValidationError(error_msg) params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/metadata/{path}',\",\n \"this command. Supported methods: LIST: /{mount_point}/metadata/{path}. Produces: 200 application/json :param path: Specifies the\",\n \"keys will require the cas parameter to be set on all write requests.\",\n \"'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/delete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, )\",\n \"exceptions.ParamValidationError(error_msg) params = { 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return\",\n \"def update_metadata(self, path, max_versions=None, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Updates the max_versions of cas_required setting on\",\n \"operation. If not set the write will be allowed. If set to 0\",\n \"versions the oldest version will be permanently deleted. Defaults to 10. :type max_versions:\",\n \"that no policy-based filtering is performed on keys; do not encode sensitive information\",\n \"path: Path :type path: str | unicode :param cas: Set the \\\"cas\\\" value\",\n \"be deleted, but it will no longer be returned in normal get requests.\",\n \"= utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.list( url=api_path, ) return response.json() def read_secret_metadata(self,\",\n \"mounted on. :type mount_point: str | unicode :return: The JSON response of the\",\n \"Produces: 200 application/json :param mount_point: The \\\"path\\\" the secret engine was mounted on.\",\n \"{ 'versions': versions, } api_path = utils.format_url('/v1/{mount_point}/undelete/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params,\",\n \"methods: DELETE: /{mount_point}/metadata/{path}. Produces: 204 (empty body) :param path: Specifies the path of\",\n \"applied to every key in the key-value store. Supported methods: POST: /{mount_point}/config. Produces:\",\n \"get requests. Supported methods: POST: /{mount_point}/undelete/{path}. Produces: 204 (empty body) :param path: Specifies\",\n \"is not None: params['cas_required'] = cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path,\",\n \"cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path, json=params, ) def read_configuration(self, mount_point=DEFAULT_MOUNT_POINT):\",\n \"read_secret_version(self, path, version=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the secret at the specified location. Supported methods:\",\n \"specified location. Supported methods: GET: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Specifies the\",\n \"of the secret to undelete. This is specified as part of the URL.\",\n \"of versions to keep per key. This value applies to all keys, but\",\n \"path=path) response = self._adapter.list( url=api_path, ) return response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve\",\n \"versions to destroy. Their data will be permanently deleted. :type versions: list of\",\n \"max_versions: The number of versions to keep per key. If not set, the\",\n \"unicode :param max_versions: The number of versions to keep per key. If not\",\n \"mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Updates the max_versions of cas_required setting on an existing path. Supported methods:\",\n \"200 application/json :param path: Specifies the path of the secret to read. This\",\n \"version at the specified location. This marks the version as deleted and will\",\n \"parameter to be set on all write requests. :type cas_required: bool :param mount_point:\",\n \"self._adapter.post( url=api_path, json=params, ) def list_secrets(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Return a list of key\",\n \"Specifies the path of the secret to destroy. This is specified as part\",\n \"{ 'options': {}, 'data': secret, } if cas is not None: params['options']['cas'] =\",\n \"Produces: 200 application/json :param path: Path :type path: str | unicode :param cas:\",\n \"read. This is specified as part of the URL. :type path: str |\",\n \"index is non-zero the write will only be allowed if the key's current\",\n \"names at the specified location. Folders are suffixed with /. The input must\",\n \"- Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \\\"\\\"\\\" def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Configure\",\n \"utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.list( url=api_path, ) return response.json() def read_secret_metadata(self, path,\",\n \"dict \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point, path=path) response = self._adapter.list( url=api_path, ) return\",\n \"backend's configuration will be used. :type cas_required: bool :param mount_point: The \\\"path\\\" the\",\n \"requests.Response \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) return self._adapter.delete( url=api_path, ) def delete_secret_versions(self,\",\n \"response = self._adapter.list( url=api_path, ) return response.json() def read_secret_metadata(self, path, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Retrieve the\",\n \"str | unicode :param versions: The versions to destroy. Their data will be\",\n \":type max_versions: int :param cas_required: If true all keys will require the cas\",\n \"https://www.vaultproject.io/api/secret/kv/kv-v2.html \\\"\\\"\\\" def configure(self, max_versions=10, cas_required=None, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Configure backend level settings that are\",\n \"api_path = utils.format_url('/v1/{mount_point}/destroy/{path}', mount_point=mount_point, path=path) return self._adapter.post( url=api_path, json=params, ) def list_secrets(self, path,\",\n \"DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase): \\\"\\\"\\\"KV Secrets Engine - Version 2 (API). Reference:\",\n \"but a key's metadata setting can overwrite this value. Once a key has\",\n \"to \\\"versions\\\" must be a list containing one or more integers, \\\"{versions}\\\" provided.'.format(\",\n \"the secret to delete. This is specified as part of the URL. :type\",\n \"The JSON response of the request. :rtype: dict \\\"\\\"\\\" params = {} if\",\n \"secret at the specified path. Supported methods: GET: /{mount_point}/metadata/{path}. Produces: 200 application/json :param\",\n \"'data': secret, } if cas is not None: params['options']['cas'] = cas api_path =\",\n \"the update capability. Supported methods: POST: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Path\",\n \"of the secret. This marks the versions as deleted and will stop them\",\n \"= cas_required api_path = utils.format_url('/v1/{mount_point}/config', mount_point=mount_point) return self._adapter.post( url=api_path, json=params, ) def read_configuration(self,\",\n \"configured max version is used. Once a key has more than the configured\",\n \"matches the version specified in the cas parameter. :type cas: int :param secret:\",\n \"request. :rtype: requests.Response \\\"\\\"\\\" if not isinstance(versions, list) or len(versions) == 0: error_msg\",\n \"import VaultApiBase DEFAULT_MOUNT_POINT = 'secret' class KvV2(VaultApiBase): \\\"\\\"\\\"KV Secrets Engine - Version 2\",\n \"cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.post( url=api_path, json=params, ) return\",\n \"= cas api_path = utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.post( url=api_path, json=params, )\",\n \"Secrets Engine - Version 2 (API). Reference: https://www.vaultproject.io/api/secret/kv/kv-v2.html \\\"\\\"\\\" def configure(self, max_versions=10, cas_required=None,\",\n \") return response.json() def patch(self, path, secret, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Set or update data in\",\n \"returned on get requests. Supported methods: POST: /{mount_point}/undelete/{path}. Produces: 204 (empty body) :param\",\n \"the specified location. Supported methods: GET: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Specifies\",\n \"filtering is performed on keys; do not encode sensitive information in key names.\",\n \"| unicode :param max_versions: The number of versions to keep per key. If\",\n \"str | unicode :param max_versions: The number of versions to keep per key.\",\n \"settings that are applied to every key in the key-value store. Supported methods:\",\n \"of the \\\"secret\\\" dict will be stored and returned on read. :type secret:\",\n \"set the write will be allowed. If set to 0 a write will\",\n \"all write requests. :type cas_required: bool :param mount_point: The \\\"path\\\" the secret engine\",\n \"methods: GET: /{mount_point}/data/{path}. Produces: 200 application/json :param path: Specifies the path of the\",\n \"utils.format_url( '/v1/{mount_point}/config', mount_point=mount_point, ) response = self._adapter.get(url=api_path) return response.json() def read_secret_version(self, path, version=None,\",\n \"value already exists, the calling token must have an ACL policy granting the\",\n \"= utils.format_url('/v1/{mount_point}/data/{path}', mount_point=mount_point, path=path) response = self._adapter.post( url=api_path, json=params, ) return response.json() def\",\n \"the configured allowed versions the oldest version will be permanently deleted. Defaults to\",\n \"== 0: error_msg = 'argument to \\\"versions\\\" must be a list containing one\",\n \"None: params['max_versions'] = max_versions if cas_required is not None: if not isinstance(cas_required, bool):\",\n \"permanently deleted. :type max_versions: int :param cas_required: If true the key will require\",\n \"unicode :param versions: The versions to be deleted. The versioned data will not\",\n \":param mount_point: The \\\"path\\\" the secret engine was mounted on. :type mount_point: str\",\n \"This marks the version as deleted and will stop it from being returned\",\n \"url=api_path, ) def delete_secret_versions(self, path, versions, mount_point=DEFAULT_MOUNT_POINT): \\\"\\\"\\\"Issue a soft delete of the\",\n \"not encode sensitive information in key names. The values themselves are not accessible\",\n \"on. :type mount_point: str | unicode :return: The JSON response of the create_or_update_secret\",\n \"The JSON response of the request. :rtype: dict \\\"\\\"\\\" api_path = utils.format_url('/v1/{mount_point}/metadata/{path}', mount_point=mount_point,\",\n \"requests.Response \\\"\\\"\\\" params = {} if max_versions is not None: params['max_versions'] = max_versions\",\n \"to delete. This is specified as part of the URL. :type path: str\"\n]","isConversational":false}}},{"rowIdx":4598,"cells":{"ngram":{"kind":"list like","value":["to connected device(s) import subprocess import sys answer = input(\"Install all vulkan examples","time! (Y/N)\").lower() == 'y' if answer: BUILD_ARGUMENTS = \"\" for arg in sys.argv[1:]:","this may take some time! (Y/N)\").lower() == 'y' if answer: BUILD_ARGUMENTS = \"\"","\"-validation\" if subprocess.call((\"python build-all.py -deploy %s\" % BUILD_ARGUMENTS).split(' ')) != 0: print(\"Error: Not","take some time! (Y/N)\").lower() == 'y' if answer: BUILD_ARGUMENTS = \"\" for arg","answer: BUILD_ARGUMENTS = \"\" for arg in sys.argv[1:]: if arg == \"-validation\": BUILD_ARGUMENTS","device(s) import subprocess import sys answer = input(\"Install all vulkan examples to attached","subprocess import sys answer = input(\"Install all vulkan examples to attached device, this","arg in sys.argv[1:]: if arg == \"-validation\": BUILD_ARGUMENTS += \"-validation\" if subprocess.call((\"python build-all.py","in sys.argv[1:]: if arg == \"-validation\": BUILD_ARGUMENTS += \"-validation\" if subprocess.call((\"python build-all.py -deploy","attached device, this may take some time! (Y/N)\").lower() == 'y' if answer: BUILD_ARGUMENTS","all examples to connected device(s) import subprocess import sys answer = input(\"Install all","BUILD_ARGUMENTS += \"-validation\" if subprocess.call((\"python build-all.py -deploy %s\" % BUILD_ARGUMENTS).split(' ')) != 0:","== \"-validation\": BUILD_ARGUMENTS += \"-validation\" if subprocess.call((\"python build-all.py -deploy %s\" % BUILD_ARGUMENTS).split(' '))","sys.argv[1:]: if arg == \"-validation\": BUILD_ARGUMENTS += \"-validation\" if subprocess.call((\"python build-all.py -deploy %s\"","examples to connected device(s) import subprocess import sys answer = input(\"Install all vulkan","input(\"Install all vulkan examples to attached device, this may take some time! (Y/N)\").lower()","import sys answer = input(\"Install all vulkan examples to attached device, this may","= input(\"Install all vulkan examples to attached device, this may take some time!","if answer: BUILD_ARGUMENTS = \"\" for arg in sys.argv[1:]: if arg == \"-validation\":","BUILD_ARGUMENTS = \"\" for arg in sys.argv[1:]: if arg == \"-validation\": BUILD_ARGUMENTS +=","build-all.py -deploy %s\" % BUILD_ARGUMENTS).split(' ')) != 0: print(\"Error: Not all examples may","answer = input(\"Install all vulkan examples to attached device, this may take some","all vulkan examples to attached device, this may take some time! (Y/N)\").lower() ==","+= \"-validation\" if subprocess.call((\"python build-all.py -deploy %s\" % BUILD_ARGUMENTS).split(' ')) != 0: print(\"Error:","\"-validation\": BUILD_ARGUMENTS += \"-validation\" if subprocess.call((\"python build-all.py -deploy %s\" % BUILD_ARGUMENTS).split(' ')) !=","connected device(s) import subprocess import sys answer = input(\"Install all vulkan examples to","device, this may take some time! (Y/N)\").lower() == 'y' if answer: BUILD_ARGUMENTS =","== 'y' if answer: BUILD_ARGUMENTS = \"\" for arg in sys.argv[1:]: if arg","to attached device, this may take some time! (Y/N)\").lower() == 'y' if answer:","some time! (Y/N)\").lower() == 'y' if answer: BUILD_ARGUMENTS = \"\" for arg in","Install all examples to connected device(s) import subprocess import sys answer = input(\"Install","import subprocess import sys answer = input(\"Install all vulkan examples to attached device,","examples to attached device, this may take some time! (Y/N)\").lower() == 'y' if","% BUILD_ARGUMENTS).split(' ')) != 0: print(\"Error: Not all examples may have been installed!\")","if subprocess.call((\"python build-all.py -deploy %s\" % BUILD_ARGUMENTS).split(' ')) != 0: print(\"Error: Not all","= \"\" for arg in sys.argv[1:]: if arg == \"-validation\": BUILD_ARGUMENTS += \"-validation\"","\"\" for arg in sys.argv[1:]: if arg == \"-validation\": BUILD_ARGUMENTS += \"-validation\" if","for arg in sys.argv[1:]: if arg == \"-validation\": BUILD_ARGUMENTS += \"-validation\" if subprocess.call((\"python","arg == \"-validation\": BUILD_ARGUMENTS += \"-validation\" if subprocess.call((\"python build-all.py -deploy %s\" % BUILD_ARGUMENTS).split('","# Install all examples to connected device(s) import subprocess import sys answer =","may take some time! (Y/N)\").lower() == 'y' if answer: BUILD_ARGUMENTS = \"\" for","subprocess.call((\"python build-all.py -deploy %s\" % BUILD_ARGUMENTS).split(' ')) != 0: print(\"Error: Not all examples","-deploy %s\" % BUILD_ARGUMENTS).split(' ')) != 0: print(\"Error: Not all examples may have","%s\" % BUILD_ARGUMENTS).split(' ')) != 0: print(\"Error: Not all examples may have been","BUILD_ARGUMENTS).split(' ')) != 0: print(\"Error: Not all examples may have been installed!\") sys.exit(-1)","vulkan examples to attached device, this may take some time! (Y/N)\").lower() == 'y'","(Y/N)\").lower() == 'y' if answer: BUILD_ARGUMENTS = \"\" for arg in sys.argv[1:]: if","if arg == \"-validation\": BUILD_ARGUMENTS += \"-validation\" if subprocess.call((\"python build-all.py -deploy %s\" %","sys answer = input(\"Install all vulkan examples to attached device, this may take","'y' if answer: BUILD_ARGUMENTS = \"\" for arg in sys.argv[1:]: if arg =="],"string":"[\n \"to connected device(s) import subprocess import sys answer = input(\\\"Install all vulkan examples\",\n \"time! (Y/N)\\\").lower() == 'y' if answer: BUILD_ARGUMENTS = \\\"\\\" for arg in sys.argv[1:]:\",\n \"this may take some time! (Y/N)\\\").lower() == 'y' if answer: BUILD_ARGUMENTS = \\\"\\\"\",\n \"\\\"-validation\\\" if subprocess.call((\\\"python build-all.py -deploy %s\\\" % BUILD_ARGUMENTS).split(' ')) != 0: print(\\\"Error: Not\",\n \"take some time! (Y/N)\\\").lower() == 'y' if answer: BUILD_ARGUMENTS = \\\"\\\" for arg\",\n \"answer: BUILD_ARGUMENTS = \\\"\\\" for arg in sys.argv[1:]: if arg == \\\"-validation\\\": BUILD_ARGUMENTS\",\n \"device(s) import subprocess import sys answer = input(\\\"Install all vulkan examples to attached\",\n \"subprocess import sys answer = input(\\\"Install all vulkan examples to attached device, this\",\n \"arg in sys.argv[1:]: if arg == \\\"-validation\\\": BUILD_ARGUMENTS += \\\"-validation\\\" if subprocess.call((\\\"python build-all.py\",\n \"in sys.argv[1:]: if arg == \\\"-validation\\\": BUILD_ARGUMENTS += \\\"-validation\\\" if subprocess.call((\\\"python build-all.py -deploy\",\n \"attached device, this may take some time! (Y/N)\\\").lower() == 'y' if answer: BUILD_ARGUMENTS\",\n \"all examples to connected device(s) import subprocess import sys answer = input(\\\"Install all\",\n \"BUILD_ARGUMENTS += \\\"-validation\\\" if subprocess.call((\\\"python build-all.py -deploy %s\\\" % BUILD_ARGUMENTS).split(' ')) != 0:\",\n \"== \\\"-validation\\\": BUILD_ARGUMENTS += \\\"-validation\\\" if subprocess.call((\\\"python build-all.py -deploy %s\\\" % BUILD_ARGUMENTS).split(' '))\",\n \"sys.argv[1:]: if arg == \\\"-validation\\\": BUILD_ARGUMENTS += \\\"-validation\\\" if subprocess.call((\\\"python build-all.py -deploy %s\\\"\",\n \"examples to connected device(s) import subprocess import sys answer = input(\\\"Install all vulkan\",\n \"input(\\\"Install all vulkan examples to attached device, this may take some time! (Y/N)\\\").lower()\",\n \"import sys answer = input(\\\"Install all vulkan examples to attached device, this may\",\n \"= input(\\\"Install all vulkan examples to attached device, this may take some time!\",\n \"if answer: BUILD_ARGUMENTS = \\\"\\\" for arg in sys.argv[1:]: if arg == \\\"-validation\\\":\",\n \"BUILD_ARGUMENTS = \\\"\\\" for arg in sys.argv[1:]: if arg == \\\"-validation\\\": BUILD_ARGUMENTS +=\",\n \"build-all.py -deploy %s\\\" % BUILD_ARGUMENTS).split(' ')) != 0: print(\\\"Error: Not all examples may\",\n \"answer = input(\\\"Install all vulkan examples to attached device, this may take some\",\n \"all vulkan examples to attached device, this may take some time! (Y/N)\\\").lower() ==\",\n \"+= \\\"-validation\\\" if subprocess.call((\\\"python build-all.py -deploy %s\\\" % BUILD_ARGUMENTS).split(' ')) != 0: print(\\\"Error:\",\n \"\\\"-validation\\\": BUILD_ARGUMENTS += \\\"-validation\\\" if subprocess.call((\\\"python build-all.py -deploy %s\\\" % BUILD_ARGUMENTS).split(' ')) !=\",\n \"connected device(s) import subprocess import sys answer = input(\\\"Install all vulkan examples to\",\n \"device, this may take some time! (Y/N)\\\").lower() == 'y' if answer: BUILD_ARGUMENTS =\",\n \"== 'y' if answer: BUILD_ARGUMENTS = \\\"\\\" for arg in sys.argv[1:]: if arg\",\n \"to attached device, this may take some time! (Y/N)\\\").lower() == 'y' if answer:\",\n \"some time! (Y/N)\\\").lower() == 'y' if answer: BUILD_ARGUMENTS = \\\"\\\" for arg in\",\n \"Install all examples to connected device(s) import subprocess import sys answer = input(\\\"Install\",\n \"import subprocess import sys answer = input(\\\"Install all vulkan examples to attached device,\",\n \"examples to attached device, this may take some time! (Y/N)\\\").lower() == 'y' if\",\n \"% BUILD_ARGUMENTS).split(' ')) != 0: print(\\\"Error: Not all examples may have been installed!\\\")\",\n \"if subprocess.call((\\\"python build-all.py -deploy %s\\\" % BUILD_ARGUMENTS).split(' ')) != 0: print(\\\"Error: Not all\",\n \"= \\\"\\\" for arg in sys.argv[1:]: if arg == \\\"-validation\\\": BUILD_ARGUMENTS += \\\"-validation\\\"\",\n \"\\\"\\\" for arg in sys.argv[1:]: if arg == \\\"-validation\\\": BUILD_ARGUMENTS += \\\"-validation\\\" if\",\n \"for arg in sys.argv[1:]: if arg == \\\"-validation\\\": BUILD_ARGUMENTS += \\\"-validation\\\" if subprocess.call((\\\"python\",\n \"arg == \\\"-validation\\\": BUILD_ARGUMENTS += \\\"-validation\\\" if subprocess.call((\\\"python build-all.py -deploy %s\\\" % BUILD_ARGUMENTS).split('\",\n \"# Install all examples to connected device(s) import subprocess import sys answer =\",\n \"may take some time! (Y/N)\\\").lower() == 'y' if answer: BUILD_ARGUMENTS = \\\"\\\" for\",\n \"subprocess.call((\\\"python build-all.py -deploy %s\\\" % BUILD_ARGUMENTS).split(' ')) != 0: print(\\\"Error: Not all examples\",\n \"-deploy %s\\\" % BUILD_ARGUMENTS).split(' ')) != 0: print(\\\"Error: Not all examples may have\",\n \"%s\\\" % BUILD_ARGUMENTS).split(' ')) != 0: print(\\\"Error: Not all examples may have been\",\n \"BUILD_ARGUMENTS).split(' ')) != 0: print(\\\"Error: Not all examples may have been installed!\\\") sys.exit(-1)\",\n \"vulkan examples to attached device, this may take some time! (Y/N)\\\").lower() == 'y'\",\n \"(Y/N)\\\").lower() == 'y' if answer: BUILD_ARGUMENTS = \\\"\\\" for arg in sys.argv[1:]: if\",\n \"if arg == \\\"-validation\\\": BUILD_ARGUMENTS += \\\"-validation\\\" if subprocess.call((\\\"python build-all.py -deploy %s\\\" %\",\n \"sys answer = input(\\\"Install all vulkan examples to attached device, this may take\",\n \"'y' if answer: BUILD_ARGUMENTS = \\\"\\\" for arg in sys.argv[1:]: if arg ==\"\n]","isConversational":false}}},{"rowIdx":4599,"cells":{"ngram":{"kind":"list like","value":["# Ahoughton generator and adapter test # 2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) #","DefaultProblemAdapter from adapters.crg import CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter import json def main():","AhoughtonAdapter(), config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config","get_moonboard from adapters.default import DefaultProblemAdapter from adapters.crg import CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter","get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016 =","json def main(): # Create Renderer config = RendererConfig() renderer = ProblemRenderer( get_moonboard(2017),","open('data/crg.json', 'r') as f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and adapter","Ahoughton generator and adapter test # 2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017","= ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem = ahoughton_generator_2017.generate() ahoughton_renderer_2017.render_problem(problem) if __name__ == \"__main__\":","from adapters.default import DefaultProblemAdapter from adapters.crg import CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter import",") ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017","ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016","crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config","= ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer(","driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') #","import get_moonboard from adapters.default import DefaultProblemAdapter from adapters.crg import CRGProblemAdapter from adapters.ahoughton import","AhoughtonAdapter import json def main(): # Create Renderer config = RendererConfig() renderer =","renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r') as f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton","from moonboard import get_moonboard from adapters.default import DefaultProblemAdapter from adapters.crg import CRGProblemAdapter from","Load data with open('data/problems.json', 'r') as f: problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True) with","ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem = ahoughton_generator_2017.generate() ahoughton_renderer_2017.render_problem(problem) if __name__ == \"__main__\": main()","main(): # Create Renderer config = RendererConfig() renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config","get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016 =","as f: problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r') as f: crg_problems","from problem_renderer import ProblemRenderer from moonboard import get_moonboard from adapters.default import DefaultProblemAdapter from","# 2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem = ahoughton_generator_2017.generate() ahoughton_renderer_2017.render_problem(problem) if","import DefaultProblemAdapter from adapters.crg import CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter import json def","AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with open('data/problems.json', 'r') as f: problems = json.load(f)",") crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(),","f: problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r') as f: crg_problems =","import CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter import json def main(): # Create Renderer","json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and adapter test # 2016 problem = ahoughton_generator_2016.generate()","adapters.ahoughton import AhoughtonAdapter import json def main(): # Create Renderer config = RendererConfig()","ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016","CRGProblemAdapter(), config ) ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016,","def main(): # Create Renderer config = RendererConfig() renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(),","f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and adapter test # 2016","= RendererConfig() renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer = ProblemRenderer( get_moonboard(2017),","CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter import json def main(): # Create Renderer config","get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with open('data/problems.json',","test # 2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem = ahoughton_generator_2017.generate() ahoughton_renderer_2017.render_problem(problem)","config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with open('data/problems.json', 'r') as",") ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017","AhoughtonGenerator from render_config import RendererConfig from problem_renderer import ProblemRenderer from moonboard import get_moonboard","data with open('data/problems.json', 'r') as f: problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json',","config ) ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe')","with open('data/crg.json', 'r') as f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and","= AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017,","as f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and adapter test #",") ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with open('data/problems.json', 'r') as f:","crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and adapter test # 2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem)","renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config","render_config import RendererConfig from problem_renderer import ProblemRenderer from moonboard import get_moonboard from adapters.default","= ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config )","AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe')","= ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config )","Renderer config = RendererConfig() renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer =","'r') as f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and adapter test","2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem = ahoughton_generator_2017.generate() ahoughton_renderer_2017.render_problem(problem) if __name__","import RendererConfig from problem_renderer import ProblemRenderer from moonboard import get_moonboard from adapters.default import","problem_renderer import ProblemRenderer from moonboard import get_moonboard from adapters.default import DefaultProblemAdapter from adapters.crg","ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with","with_info=True) with open('data/crg.json', 'r') as f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator","'r') as f: problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r') as f:","import AhoughtonGenerator from render_config import RendererConfig from problem_renderer import ProblemRenderer from moonboard import","# Create Renderer config = RendererConfig() renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config )","ProblemRenderer from moonboard import get_moonboard from adapters.default import DefaultProblemAdapter from adapters.crg import CRGProblemAdapter","config = RendererConfig() renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer = ProblemRenderer(","generators.ahoughton import AhoughtonGenerator from render_config import RendererConfig from problem_renderer import ProblemRenderer from moonboard","DefaultProblemAdapter(), config ) crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016 = ProblemRenderer(","problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r') as f: crg_problems = json.load(f)","adapter test # 2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem = ahoughton_generator_2017.generate()","RendererConfig() renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(),","generator and adapter test # 2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem","= json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and adapter test # 2016 problem =","json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r') as f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) #","ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with open('data/problems.json', 'r') as f: problems","crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and adapter test # 2016 problem","ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017),","Create Renderer config = RendererConfig() renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer","RendererConfig from problem_renderer import ProblemRenderer from moonboard import get_moonboard from adapters.default import DefaultProblemAdapter","from adapters.ahoughton import AhoughtonAdapter import json def main(): # Create Renderer config =","import AhoughtonAdapter import json def main(): # Create Renderer config = RendererConfig() renderer","= AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with open('data/problems.json', 'r') as f: problems =","config ) crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016),","ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 =","and adapter test # 2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem =","= json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r') as f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1'])","import ProblemRenderer from moonboard import get_moonboard from adapters.default import DefaultProblemAdapter from adapters.crg import","adapters.crg import CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter import json def main(): # Create","ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load","# Load data with open('data/problems.json', 'r') as f: problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True)","AhoughtonAdapter(), config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with open('data/problems.json', 'r')","config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config )","moonboard import get_moonboard from adapters.default import DefaultProblemAdapter from adapters.crg import CRGProblemAdapter from adapters.ahoughton","ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017 =","import json def main(): # Create Renderer config = RendererConfig() renderer = ProblemRenderer(","= ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data","driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with open('data/problems.json', 'r') as f: problems = json.load(f) renderer.render_problem(problems['339318'],","open('data/problems.json', 'r') as f: problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r') as","from generators.ahoughton import AhoughtonGenerator from render_config import RendererConfig from problem_renderer import ProblemRenderer from","with open('data/problems.json', 'r') as f: problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r')","adapters.default import DefaultProblemAdapter from adapters.crg import CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter import json","get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(),","problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem = ahoughton_generator_2017.generate() ahoughton_renderer_2017.render_problem(problem) if __name__ ==","from adapters.crg import CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter import json def main(): #","from render_config import RendererConfig from problem_renderer import ProblemRenderer from moonboard import get_moonboard from"],"string":"[\n \"# Ahoughton generator and adapter test # 2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) #\",\n \"DefaultProblemAdapter from adapters.crg import CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter import json def main():\",\n \"AhoughtonAdapter(), config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config\",\n \"get_moonboard from adapters.default import DefaultProblemAdapter from adapters.crg import CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter\",\n \"get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016 =\",\n \"json def main(): # Create Renderer config = RendererConfig() renderer = ProblemRenderer( get_moonboard(2017),\",\n \"open('data/crg.json', 'r') as f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and adapter\",\n \"Ahoughton generator and adapter test # 2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017\",\n \"= ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem = ahoughton_generator_2017.generate() ahoughton_renderer_2017.render_problem(problem) if __name__ == \\\"__main__\\\":\",\n \"from adapters.default import DefaultProblemAdapter from adapters.crg import CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter import\",\n \") ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017\",\n \"ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016\",\n \"crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config\",\n \"= ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer(\",\n \"driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') #\",\n \"import get_moonboard from adapters.default import DefaultProblemAdapter from adapters.crg import CRGProblemAdapter from adapters.ahoughton import\",\n \"AhoughtonAdapter import json def main(): # Create Renderer config = RendererConfig() renderer =\",\n \"renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r') as f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton\",\n \"from moonboard import get_moonboard from adapters.default import DefaultProblemAdapter from adapters.crg import CRGProblemAdapter from\",\n \"Load data with open('data/problems.json', 'r') as f: problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True) with\",\n \"ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem = ahoughton_generator_2017.generate() ahoughton_renderer_2017.render_problem(problem) if __name__ == \\\"__main__\\\": main()\",\n \"main(): # Create Renderer config = RendererConfig() renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config\",\n \"get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016 =\",\n \"as f: problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r') as f: crg_problems\",\n \"from problem_renderer import ProblemRenderer from moonboard import get_moonboard from adapters.default import DefaultProblemAdapter from\",\n \"# 2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem = ahoughton_generator_2017.generate() ahoughton_renderer_2017.render_problem(problem) if\",\n \"import DefaultProblemAdapter from adapters.crg import CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter import json def\",\n \"AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with open('data/problems.json', 'r') as f: problems = json.load(f)\",\n \") crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(),\",\n \"f: problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r') as f: crg_problems =\",\n \"import CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter import json def main(): # Create Renderer\",\n \"json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and adapter test # 2016 problem = ahoughton_generator_2016.generate()\",\n \"adapters.ahoughton import AhoughtonAdapter import json def main(): # Create Renderer config = RendererConfig()\",\n \"ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016\",\n \"CRGProblemAdapter(), config ) ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016,\",\n \"def main(): # Create Renderer config = RendererConfig() renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(),\",\n \"f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and adapter test # 2016\",\n \"= RendererConfig() renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer = ProblemRenderer( get_moonboard(2017),\",\n \"CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter import json def main(): # Create Renderer config\",\n \"get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with open('data/problems.json',\",\n \"test # 2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem = ahoughton_generator_2017.generate() ahoughton_renderer_2017.render_problem(problem)\",\n \"config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with open('data/problems.json', 'r') as\",\n \") ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017\",\n \"AhoughtonGenerator from render_config import RendererConfig from problem_renderer import ProblemRenderer from moonboard import get_moonboard\",\n \"data with open('data/problems.json', 'r') as f: problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json',\",\n \"config ) ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe')\",\n \"with open('data/crg.json', 'r') as f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and\",\n \"= AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017,\",\n \"as f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and adapter test #\",\n \") ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with open('data/problems.json', 'r') as f:\",\n \"crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and adapter test # 2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem)\",\n \"renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config\",\n \"render_config import RendererConfig from problem_renderer import ProblemRenderer from moonboard import get_moonboard from adapters.default\",\n \"= ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config )\",\n \"AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe')\",\n \"= ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config )\",\n \"Renderer config = RendererConfig() renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer =\",\n \"'r') as f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and adapter test\",\n \"2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem = ahoughton_generator_2017.generate() ahoughton_renderer_2017.render_problem(problem) if __name__\",\n \"import RendererConfig from problem_renderer import ProblemRenderer from moonboard import get_moonboard from adapters.default import\",\n \"problem_renderer import ProblemRenderer from moonboard import get_moonboard from adapters.default import DefaultProblemAdapter from adapters.crg\",\n \"ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with\",\n \"with_info=True) with open('data/crg.json', 'r') as f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator\",\n \"'r') as f: problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r') as f:\",\n \"import AhoughtonGenerator from render_config import RendererConfig from problem_renderer import ProblemRenderer from moonboard import\",\n \"# Create Renderer config = RendererConfig() renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config )\",\n \"ProblemRenderer from moonboard import get_moonboard from adapters.default import DefaultProblemAdapter from adapters.crg import CRGProblemAdapter\",\n \"config = RendererConfig() renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer = ProblemRenderer(\",\n \"generators.ahoughton import AhoughtonGenerator from render_config import RendererConfig from problem_renderer import ProblemRenderer from moonboard\",\n \"DefaultProblemAdapter(), config ) crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016 = ProblemRenderer(\",\n \"problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r') as f: crg_problems = json.load(f)\",\n \"adapter test # 2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem = ahoughton_generator_2017.generate()\",\n \"RendererConfig() renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(),\",\n \"generator and adapter test # 2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem\",\n \"= json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and adapter test # 2016 problem =\",\n \"json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r') as f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) #\",\n \"ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with open('data/problems.json', 'r') as f: problems\",\n \"crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1']) # Ahoughton generator and adapter test # 2016 problem\",\n \"ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017),\",\n \"Create Renderer config = RendererConfig() renderer = ProblemRenderer( get_moonboard(2017), DefaultProblemAdapter(), config ) crg_renderer\",\n \"RendererConfig from problem_renderer import ProblemRenderer from moonboard import get_moonboard from adapters.default import DefaultProblemAdapter\",\n \"from adapters.ahoughton import AhoughtonAdapter import json def main(): # Create Renderer config =\",\n \"import AhoughtonAdapter import json def main(): # Create Renderer config = RendererConfig() renderer\",\n \"= AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with open('data/problems.json', 'r') as f: problems =\",\n \"config ) crg_renderer = ProblemRenderer( get_moonboard(2017), CRGProblemAdapter(), config ) ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016),\",\n \"ahoughton_renderer_2016 = ProblemRenderer( get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 =\",\n \"and adapter test # 2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem =\",\n \"= json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r') as f: crg_problems = json.load(f) crg_renderer.render_problem(crg_problems['1'])\",\n \"import ProblemRenderer from moonboard import get_moonboard from adapters.default import DefaultProblemAdapter from adapters.crg import\",\n \"adapters.crg import CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter import json def main(): # Create\",\n \"ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load\",\n \"# Load data with open('data/problems.json', 'r') as f: problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True)\",\n \"AhoughtonAdapter(), config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with open('data/problems.json', 'r')\",\n \"config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config )\",\n \"moonboard import get_moonboard from adapters.default import DefaultProblemAdapter from adapters.crg import CRGProblemAdapter from adapters.ahoughton\",\n \"ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017 =\",\n \"import json def main(): # Create Renderer config = RendererConfig() renderer = ProblemRenderer(\",\n \"= ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(), config ) ahoughton_generator_2017 = AhoughtonGenerator(year=2017, driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data\",\n \"driver_path='C:/.selenium_drivers/chromedriver.exe') # Load data with open('data/problems.json', 'r') as f: problems = json.load(f) renderer.render_problem(problems['339318'],\",\n \"open('data/problems.json', 'r') as f: problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r') as\",\n \"from generators.ahoughton import AhoughtonGenerator from render_config import RendererConfig from problem_renderer import ProblemRenderer from\",\n \"with open('data/problems.json', 'r') as f: problems = json.load(f) renderer.render_problem(problems['339318'], with_info=True) with open('data/crg.json', 'r')\",\n \"adapters.default import DefaultProblemAdapter from adapters.crg import CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter import json\",\n \"get_moonboard(2016), AhoughtonAdapter(), config ) ahoughton_generator_2016 = AhoughtonGenerator(year=2016, driver_path='C:/.selenium_drivers/chromedriver.exe') ahoughton_renderer_2017 = ProblemRenderer( get_moonboard(2017), AhoughtonAdapter(),\",\n \"problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) # 2017 problem = ahoughton_generator_2017.generate() ahoughton_renderer_2017.render_problem(problem) if __name__ ==\",\n \"from adapters.crg import CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter import json def main(): #\",\n \"from render_config import RendererConfig from problem_renderer import ProblemRenderer from moonboard import get_moonboard from\"\n]","isConversational":false}}}],"truncated":false,"partial":false},"paginationData":{"pageIndex":45,"numItemsPerPage":100,"numTotalItems":12866649,"offset":4500,"length":100}},"jwt":"eyJhbGciOiJFZERTQSIsImtpZCI6Im1sR1pFYktIVHRVSGRhX1RRdEczQ0N1S3k5ME9Qd25DNHY5elRjM3FVYzgifQ.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sImlhdCI6MTc4MzU5MTYwNSwianRpIjoiNjQyM2E2N2UtZWRjOC00OGIzLWIyYTItZGI3NzFkYTZkMjhkIiwic3ViIjoiL2RhdGFzZXRzL3RlcnJ5eXovc3RhcmNvZGVyZGF0YV9uZ3JhbV8xMyIsImV4cCI6MTc4MzU5NTIwNSwiaXNzIjoiaHR0cHM6Ly9odWdnaW5nZmFjZS5jbyJ9.JVxFKD0R36KyFfeWCTKQHy7jT6UydgaUskmES2ic-esBobDmREy97SaTsKPqTgWq_HMn9XyIQKyXOXYGkzblDQ","displayUrls":true,"splitSizeSummaries":[{"config":"default","split":"train","numRows":12866649,"numBytesParquet":149232926747}]},"discussionsStats":{"closed":0,"open":0,"total":0},"fullWidth":true,"hasGatedAccess":true,"hasFullAccess":true,"isEmbedded":false,"savedQueries":{"community":[],"user":[]}}">
ngram listlengths 0 67.8k |
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[
"identifier.identify({'HTTP_AUTHORIZATION':'Basic %s' % credentials}) def test_pass(self): identifier = BasicAuthIdentifier() credentials = base64.standard_b64encode('foo:bar') identified_credentials",
"with self.assertRaises(errors.IdentificationError): identifier.identify({'HTTP_AUTHORIZATION':'Basic \\x000'}) ... |
[] |
[
"* 626, warmup_ratio=0.9, # warmup 20 epochs. update_interval=update_interval, ), ] # optimizer optimizer",
"training beta=1.2, gamma=0.5, eta=0.2, neigh_size=4, n_labels=3, t_eps=0.8), resizemix=dict(scope=(0.1, 0.8), use_alpha=True), samix=dict(mask_adjust=0, lam_margin=0.08), #",
"EMA_W = (1 - m) * EMA_W + m... |
[
"\\\"\" + filename + \"\\\" could not be found.\") self.Reader = InstrumentReader(filename) def",
"= InstrumentReader(filename) def add_to_instr(self, Instr): \"\"\" Adds information from the McStas file to",
"---------- filename (str) Filename of python file to be written \"\"\" if \"force\"",
"mcstasscript.... |
[
"ITS DOCUMENTATION, EVEN # IF THE UNIVERSITY OF CALIFORNIA HAS BEEN ADVISED OF",
"University of California. All rights reserved. # # Permission is hereby granted, without",
"# TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS. import time, subprocess, optparse,",
"time = [] hygiene_flag... |
[
"or answer.title() == COUNTRIES_CAPITALS[key]: correct_answers += 1 print(\"Correct!\") else: print(\"Wrong!\") # Should we",
"\"\"\"#################### Index: 1. Imports and Readme 2. Functions 3. Main 4. Testing ####################\"\"\"",
"Main 4. Testing ####################\"\"\" ####################### ... |
[
"'analysis_rhythm_rekordbox.json') analysis = dict() with click.progressbar(metadata_file.keys(), label=\"Converting...\") as metadata_keys: for key in metadata_keys:",
"@click.command() @click.argument('dataset_path') def rekordbox_file_to_analysis_file(dataset_path): \"\"\" Read information from rekordbox_rhyth... |
[
"\"\"\" Class representing a relationship between parts\"\"\" URL = 'part/related' @classmethod def add_related(cls,",
"def getBomItems(self): \"\"\" Return the items required to make this part \"\"\" return",
"the data to the server return api.post(cls.URL, data) class PartRelated(inventree.base.InventreeObjec... |
[
"path.resolve.return_value = path special.resolve.return_value = special path_constructor.return_value = path # Register global static",
"async def test_partialy_applied_handler(aiohttp_client): app = web.Application() async def handler(data, request): return web.Response(body=data) with",
"r.release() r = awai... |
[
"precision_macro, recall_macro, f1_micro, precision_micro, recall_micro, nmi, adjscore) ) fh.write('\\r\\n') fh.flush() fh.close() return acc,",
"/ 2.0) q = np.transpose(np.transpose(q) / np.sum(q, axis=1)) return q def generate_unconflicted_data_index(emb, centers_emb,",
"return np.argmax(yita, axis=1) def enc... |
[
"value.id, } properties = PropertyObj.search([('name', '=', 'property_stock_journal'), ('company_id', '=', company.id)]) if properties: #",
"value = self.env['account.journal'].search([('company_id', '=', company.id), ('code', '=', 'STJ'), ('type', '=', 'general')], limit=1) if",
"in todo_list: account = getatt... |
[
"# Squeeze batch dim # for key in blobs: # if key !=",
"mini-batch of indices. Args: sampler (Sampler): Base sampler. batch_size (int): Size of mini-batch.",
"torch._six import int_classes as _int_classes from core.config import cfg from roi_data.minibatch import get_minibatch",
"type of \"list of ndarray\". ... |
[
"it does not blow up, and stays somewhat close to a solution given",
"when fit_intercept=False and # normalize=False ########################################################################### # # The R result was obtained",
"precompute=False) rng = np.random.RandomState(0) X = rng.normal(0, 1, (100, 5)) X_copy... |
[
"default_type application/octet-stream; ## # Logging Settings ## access_log /var/log/nginx/access.log; error_log /var/log/nginx/error.log; ## #",
"re.search('(?P<offset>[\\s\\n]*)#(?P<comment>.*)$', config, re.M) sharp_comment = re_sharp_comment.groupdict() parent_block.add_comment(Comment(sharp_comment['offset']... |
[
"os.system(\"xcopy \" + source_dir + \" . /E /Y /H\") os.system('git pull origin",
"os.system('git pull origin develop') os.system('git submodule update --init --force') ret = subprocess.call('\"%VS110COMNTOOLS%..\\IDE\\devenv.com\" \"build\\cocos2d-win32.vc2012.sln\"",
"Config:' print ' Host:win7 x86' print ' ... |
[
"from iris_sdk.models.base_resource import BaseData from iris_sdk.models.maps.ord.rate_center_search_order import \\ RateCenterSearchOrderMap class RateCenterSearchOrder(RateCenterSearchOrderMap, BaseData): pass",
"#!/usr/bin/env python from iris_sdk.models.base_resource import BaseData from iris_sdk.models.maps.... |
[
"popSize, Iter) elif algo == \"SCA\": x = sca.SCA(getattr(benchmarks, function_name), lb, ub, dim,",
"objectivefunc, Iterations) if Flag == False: # Faild to run at least one",
"import optimizers.GA as ga import optimizers.HHO as hho import optimizers.SCA as sca import",
"= ga.GA(getattr(benchmarks, function_... |
[
"avro_type = fields.PYTHON_TYPE_TO_AVRO[primitive_type] assert {\"name\": name, \"type\": avro_type} == field.to_dict() @pytest.mark.parametrize(\"primitive_type\", fields.PYTHON_INMUTABLE_TYPES) def",
"= \"a_field\" field = fields.Field(name, primitive_type, None) avro_type = [fields.NULL, fields.PYTHON_TYPE_TO_... |
[
"problem.setStateInfo(\"/jointset/j0/q0/speed\", [-50, 50], 0) problem.setStateInfo(\"/jointset/j1/q1/value\", [-10, 10], 0) problem.setStateInfo(\"/jointset/j1/q1/speed\", [-50, 50], 0) problem.setControlInfo(\"/tau0\",",
"predictedSolution.exportToStatesTable() statesTraj = osim.StatesTrajectory.createFromState... |
[
"__init__(self): self.createTable() def createTable(self): ''' Creates A Table If it Doesnt Exist '''",
"createTable(self): ''' Creates A Table If it Doesnt Exist ''' conn.execute(\"\"\"CREATE TABLE IF",
"cursor = conn.cursor() def __init__(self): self.createTable() def createTable(self): ''' Creates A Table If... |
[
"for v in vals] elif typename == 'TIME': vals = [None if v",
"as pa message = pa.read_message(buf) rb = pa.read_record_batch(message, schema) return rb.to_pandas() def _parse_tdf_gpu(tdf):",
"shared memory Parameters ---------- buf : pyarrow.Buffer Returns ------- schema : pyarrow.Schema \"\"\"",
"[None if v ... |
[
"self.variables = [index_variable] + [v for v in variables if v.id != index]",
"not recognized as numeric or\" \" datetime\" % (self.id)) if self.entityset.time_type != time_type:",
"= variable_id def set_secondary_time_index(self, secondary_time_index): for time_index, columns in secondary_time_index.items(): ... |
[
"= urlparse(repo_url) return site_object.netloc def get_repo_name_from_http_url(repo_url): site_object = urlparse(repo_url) parsed_string = re.sub(r'\\.git$', '',",
"predicate.search(repo_url) return match.group() def validate_protocol_exists(is_ssh, is_http): if not is_ssh and not is_http: err_message",
"is_ss... |
[
"True def release_capacity_send_remove_msg_to_old_segment(self, update_infos, l_segment): seg_path_id = l_segment.seg_path_id if not update_infos.has_key(seg_path_id): update_infos[seg_path_id] =",
"= constants.NORMAL_MODE if current_mode == constants.CONGESTION_MODE: return constants.FINISHED_WITH_DEADLOCK else:... |
[
"스위치가 꺼져 있으면 흑백, 켜져 있으면 색상 if s == 0: img[:] =",
"= cv.getTrackbarPos('G', 'image') b = cv.getTrackbarPos('B', 'image') s = cv.getTrackbarPos(switch, 'image') # 스위치가",
"numpy as np import cv2 as cv def nothing(x): pass # Create a",
"r = cv.getTrackbarPos('R', 'image') g = cv.getTrackbarPos('G', 'image') b = c... |
[
"takes around 20s pt1, pt2 = solve(29000000) print(\"Part 1:\", pt1) print(\"Part 2:\", pt2)",
"range(1, int(n**0.5)+1, step) if not n % i))) def solve(target): house_count = 0",
"# https://stackoverflow.com/questions/6800193/what-is-the-most-efficient-way-of-finding-all-the-factors-of-a-number-in-python def fa... |
[
"Audience :: Developers\", \"License :: OSI Approved :: MIT License\", \"Natural Language ::",
"import pathlib import setuptools def read(*args: str) -> str: file_path = pathlib.Path(__file__).parent.joinpath(*args) return",
"Developers\", \"License :: OSI Approved :: MIT License\", \"Natural Language :: Englis... |
[
"photos, blogs, tribes, wikis, tweets, bookmarks, swaps, locations and user-to-user messaging. In 0.5",
"blogs, tribes, wikis, tweets, bookmarks, swaps, locations and user-to-user messaging. In 0.5 this",
"site. It provides profiles, friends, photos, blogs, tribes, wikis, tweets, bookmarks, swaps, locations",
... |
[
"from __future__ import unicode_literals from ralph.business.models import Venture, VentureRole def all_ventures(): yield '',",
"import division from __future__ import print_function from __future__ import unicode_literals from ralph.business.models import",
"yield ( v.id, \"%s[%s] %s\" % ( '\\u00A0' * 4 * v.pa... |
[] |
[
"user6.email = \"<EMAIL>\" user6.city_country = \"Singapore, SG\" user6.tags = \"Performer\" user6.about = ('Dancers",
"awards for our photos. ' 'We will capture your ' 'memories in ways",
"= \"Bar, Restaurant\" user5.about = ('Award winnning winebar with the best selection of",
"user2.city_country = \"Singap... |
[
"logs=None): super().on_epoch_end(epoch, logs) self._completed_epoch += 1 self.update_artifacts() should_save = False if self.epochs_since_last_save ==",
"self._completed_epoch += 1 self.update_artifacts() should_save = False if self.epochs_since_last_save == 0: if self.save_best_only:",
"self._workspace_path =... |
[
"'labels') splits = {'train','test','valid'} files = os.listdir(in_img_dir) count = len(files) for f in",
"splits = {'train','test','valid'} files = os.listdir(in_img_dir) count = len(files) for f in files:",
"= os.path.join(output_dir, 'labels') splits = {'train','test','valid'} files = os.listdir(in_img_dir) ... |
[
"as projector: projector.set_power('on') def mute_volume(self, mute): \"\"\"Mute (true) of unmute (false) media player.\"\"\"",
"device.\"\"\" def __init__(self, host, port, name, encoding, password): \"\"\"Iinitialize the PJLink device.\"\"\" self._host",
"= host self._port = port self._name = name self._passw... |
[
"p[j]: j += 1 # continue elif s[i] != p[j] and j<n_p-1: j",
"return True if __name__ == \"__main__\": ss = 'abbbbbc' p = 'a*' print(isMatch(ss,",
"j = 0 i = -1 while i < n_s-1: i = i+",
"'.' or s[i] == p[j]: j += 1 # continue elif s[i] !=",
"s n_s = len(s) n_p = len(p) j = 0 i = -1",
"True if __name__ == ... |
[
"for user in extracted: self.user_set.add(user) class ACLRuleFactory(factory.django.DjangoModelFactory): class Meta: model = ACLRule name",
"import User, Group, Permission from waliki.models import ACLRule, Page, Redirect class UserFactory(factory.django.DjangoModelFactory): username",
"u'user{0}'.format(n)) pa... |
[
"path_str = str(self.node_paths) self.setText(\"Parent {} to {}\".format(path_str, self.parent_node_path)) class AddAttribute(SetNodeAttributeData): \"\"\"Add an attribute",
"inst_path, model, layer_path) def redo(self): super(LocalizeInstancePath, self).redo() self.setText(\"Localize instance path to {}\".format... |
[
"import PdfFileWriter from frappe.utils.file_manager import save_file class ArbitrationAuthority(Document): pass def _get_sb(**kwargs): ''' call",
"} }] def raise_200(answer): return ['200 OK', answer] @frappe.whitelist() def get_sammel_pdf(no_letterhead=1): frappe.enqueue(method=_get_sammel_pdf, queue='long',",
... |
[
"None: self.__socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) def connect(self, host: str, port: int) -> Connection:",
"socket.socket(socket.AF_INET, socket.SOCK_STREAM) def connect(self, host: str, port: int) -> Connection: self.__socket.connect((host, port)) return",
"__init__(self) -> None: self._... |
[
"= Gf.Vec3f(0, 0, 0) xform = UsdGeom.Xform.Define(stage, \"/Xform\") # direct subclass xformOpOrder =",
"1, 1), (2, 2, 2)] pointsAsVec3fArr = Vt.Vec3fArray(pointsAsList) comp = UsdGeom.PointBased.ComputeExtent expectedExtent =",
"(3,0,0)], # Test Curve with 2 widths [(0,0,0), (1,1,1), (2,1,1), (3,0,0)] # Test",... |
[
"round_key = 'Round ' + str(round_num + 1) default_spread = [tournament_start_time + timedelta(minutes=game_num",
"round_num)) time_df.loc[round_key, :] = match_time.strftime('%I:%M%p') return time_df else: \"\"\" # Given the algorithm,",
"begins play one stagger count after you at the latest. \"\"\" for round_... |
[
"int]], retargs=0) if itemid is None: return False # Check if the item",
"thisitem: return False # Keep track of whether we found anything in case",
"exists but has no location. Use `requisition` to fix this.\".format(NAME)) return False #",
"USE OR OTHER DEALINGS # IN THE SOFTWARE. # ********** NAME = \"loca... |
[
"in range(12): xgb_row.append(xgb_results[month][row_target_index]) rfr_row.append(rfr_results[month][row_target_index]) dtr_row.append(dtr_results[month][row_target_index]) plt.plot(data[month_dependant_variables].iloc[row_target_index], '-', label='scsb', color='blue', alpha=0.5) plt.plot(xgb_row, '-', label='xgb... |
[
"Feature importance # MAGIC # MAGIC SHAP is a game-theoretic approach to explain",
"\"title_without_stopwords\", \"text\", \"title\", \"type\", \"author\"] col_selector = ColumnSelector(supported_cols) # COMMAND ---------- # MAGIC",
"nulls. # To enable SHAP to succeed, both the background data and examples",
... |
[
"globals().update({k: getattr(module, k) for k in module.__all__}) __all__ += module.__all__ except AttributeError: continue",
"is_pkg in pkgutil.walk_packages(__path__): module = importlib.import_module('.'+module_name,package=__name__) try: globals().update({k: getattr(module, k) for k in",
"= [] for loader, ... |
[
"X[idx], Y[idx] def add_to_grid(tiles, grid): for tile in tiles: grid[tile.pt1[0], tile.pt1[1]] = tile",
"center_pts[:,0] Y = center_pts[:,1] if only_new_blocks: idx = (np.abs(X) + np.abs(Y) <= order)",
"grid def enlarge_grid_deprec(grid, order): center_pts = [*grid] X_aztec, Y_aztec = aztec_grid(order) center_... |
[
"np.sqrt((x - cell_grid_x) ** 2 + (y - cell_grid_y) ** 2) def get_distance_matrix_squared(cell_grid_x,",
"- cell_grid_x) ** 2 + (y - cell_grid_y) ** 2) def get_distance_matrix_squared(cell_grid_x, cell_grid_y,",
"import numpy as np def get_position_of_minimum(matrix): return np.unravel_index(np.nanargmin(matrix... |
[] |
[
"[] plugin = manager.QuantumManager.get_plugin() resource_name = 'qos_queue' collection_name = resource_name.replace('_', '-') + \"s\"",
"softtabstop=4 # Copyright 2013 Nicira, Inc. # All Rights Reserved # # Licensed",
"Unless required by applicable law or agreed to in writing, software # distributed",
"'vali... |
[
"to be added, please add an issue on the GitHub repo. \"\"\" from",
"Numpy. To suggest more to be added, please add an issue on the",
"contains all of the maths tools that you'd ever need for your AI",
"be added, please add an issue on the GitHub repo. \"\"\" from easyneuron.math.distance",
"your AI project... |
[
"workingarea.close.call_count assert 0 == dispatcher.terminate.call_count obj.terminate() assert 1 == workingarea.open.call_count assert 0 ==",
"= [1001, 1002] # runid package0 = mock.MagicMock(name='package0') package1 = mock.MagicMock(name='package1') assert 0",
"sleep=0.01) ret.open() yield ret ret.close() #... |
[
"License is distributed on an \"AS IS\" BASIS, WITHOUT # WARRANTIES OR CONDITIONS",
"writing, software # distributed under the License is distributed on an \"AS IS\"",
"OdlDhcpDriverTestCase(test_odl_dhcp_driver_base.OdlDhcpDriverTestBase): def setUp(self): super(OdlDhcpDriverTestCase, self).setUp() cfg.CONF.se... |
[
"= [ ('users', '0001_initial'), ] operations = [ migrations.AlterField( model_name='users', name='site_key', field=models.CharField(blank=True, default='<KEY>',",
"Migration(migrations.Migration): dependencies = [ ('users', '0001_initial'), ] operations = [ migrations.AlterField( model_name='users', name='site_ke... |
[
"total_groups = Group.objects.all().count() total_applications = Application.objects.all().count() new_users = handler.get_new_user_counts( { \"new_users_last_24_hours\": timedelta(hours=24), \"new_users_last_7_days\":",
"AdminDashboardView(APIView): permission_classes = (IsAdminUser,) @extend_schema( tags=[\"Adm... |
[
"or EOFError: print(\"in except\") # s.close() # 關閉連線 socketThread.do_run = False # socketThread.join()",
"s.recv(1024).decode(\"utf-8\") print(data) time.sleep(0.1) def inputJob(): while True: data = input() s.send(bytes(data, \"utf-8\")) time.sleep(0.1)",
"time.sleep(0.1) except KeyboardInterrupt or EOFError:... |
[
"assign if a specific type is not associated with an observable\", \"order\": 7",
"\"string\", \"title\": \"URL Mapping\", \"description\": \"Indicator type to assign if a specific type",
"a specific type is not associated with an observable\", \"order\": 11 }, \"notes\":",
"\"title\": \"File\", \"description... |
[
"delta = {'instances': 1, 'volumes': CONF.max_volumes_per_user + 1} self.assertRaises(exception.QuotaExceeded, self.driver.reserve, FAKE_TENANT1, resources, delta)",
"= {'instances': 10, 'volumes': 2000, 'Fake_resource': 123} self.assertRaises(exception.QuotaResourceUnknown, self.driver.reserve, FAKE_TENANT1, res... |
[
"from flask_restful import reqparse def retornar_parser(): parser = reqparse.RequestParser() parser.add_argument('sentenca', type=str, required=True) return",
"flask_restful import reqparse def retornar_parser(): parser = reqparse.RequestParser() parser.add_argument('sentenca', type=str, required=True) return par... |
[
"항공기', '소형 승용차', '버스', '트럭', '기차', '크레인', '다리', '정유탱크', '댐', '운동경기장', '헬리패드', '원형",
"mmdet.apis import init_detector, inference_detector, show_result, draw_poly_detections import mmcv from mmcv import Config from",
"'stadium', 'helipad', 'roundabout') CLASS_MAP = {k:v for k, v in zip(CLASS_NAMES_KR, CLASS_NAMES... |
[
"dicoms.models import Subject from dicoms.models import Session from dicoms.models import Series admin.site.register(Session) admin.site.register(Subject)",
"import Subject from dicoms.models import Session from dicoms.models import Series admin.site.register(Session) admin.site.register(Subject) admin.site.regis... |
[
"for django-react-redux-jwt-base project. \"\"\" import os os.environ.setdefault(\"DJANGO_SETTINGS_MODULE\", \"djangoreactredux.settings.dev\") from django.core.wsgi import get_wsgi_application from",
"\"\"\" WSGI config for django-react-redux-jwt-base project. \"\"\" import os os.environ.setdefault(\"DJANGO_SETT... |
[
"self.key_pattern: return True return bool(re.match(self.key_pattern, key)) def _qualified_key(self, key): \"\"\" Prepends the configured",
"if self.auto_casting and (result is not None): result = jsonpickle.decode(result) return result def",
"_qualified_key(self, key): \"\"\" Prepends the configured prefix to ... |
[
"and the following disclaimer in the documentation # and/or other materials provided with",
"# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR #",
"EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES",
"AND FITNESS FOR A PARTICULAR PURPOSE ARE # DI... |
[] |
[
"for c in chain(*clauses))) def count_clauses(*clauses): total = 0 for subclauses in clauses:",
"count_clauses(*clauses): total = 0 for subclauses in clauses: total += len(subclauses) return total",
"total def unique_literals(*clauses): literals = set() for clause in chain(*clauses): literals.update((abs(l) for... |
[
"self.parameters) simulation.Run() def tearDown(self): with KratosUnittest.WorkFolderScope(self.work_folder, __file__): KratosUtilities.DeleteFileIfExisting('sod_shock_tube_geom_coarse.time') def _CustomizeSimulationSettings(self): # Customize simulation",
": { \"check_variables\" : [\"DENSITY\",\"MOMENTUM_X\",\"... |
[
".cate_broadcast_comm_controller import CateBCommMAC from .cate_broadcast_comm_controller_full import CateBCommFMAC from .cate_broadcast_comm_controller_not_IB import CateBCommNIBMAC from .tar_comm_controller",
"from .cate_broadcast_comm_controller import CateBCommMAC from .cate_broadcast_comm_controller_full imp... |
[
"path): try: print(\"connect\") async for message in websocket: print(message) finally: USERS.remove(websocket) async def",
"async def main(): async with websockets.serve(counter, \"localhost\", 5000): await asyncio.Future() # run forever",
"asyncio import json import logging import websockets logging.basicConf... |
[
"= conv_block(p3, n_filters*4,5,True) p4 = Conv3D(n_filters*8,kernel_size = (2,2,2) , strides = (2,2,2) ,",
"(1,1,1) , padding = 'same')(u10); c10 = Dropout(dropout)(c10) c10 = add([c10,u10]); #c9 =",
"conv_block(u9,n_filters*4,5,True) c9 = Dropout(dropout)(c9) u10 = Conv3DTranspose(n_filters,(2,2,2),strides = ... |
[
"str = None img: str = None tag: str = None price: int",
"class ActiveOffer(BaseModel): id: str = None title: str = None instruction: str =",
"None title: str = None instruction: str = None instruction_html: str = None",
"id: str = None title: str = None instruction: str = None instruction_html:",
"= None t... |
[
"name='bn2b_branch2b',is_training=False) .conv(1, 1, 256, 1, 1, biased=False, relu=False, name='res2b_branch2c') .batch_normalization(name='bn2b_branch2c',is_training=False,relu=False)) (self.feed('res2a_relu', 'bn2b_branch2c') .add(name='res2b')",
"relu=False, name='res3c_branch2b') .batch_normalization(relu=Tru... |
[
"_is_principal_tuple(principal): return [tuple(principal)] else: return _flatten(_process_principal(p) for p in principal) def _process_permission_set(ids, permission_set):",
"LOGGER = logging.getLogger(__name__) _Context = collections.namedtuple(\"_Context\", [ \"session\", \"ids\", \"principal\", \"principal_fi... |
[
"threading from concurrent.futures import ThreadPoolExecutor from service.train import do_train def thread_runner(thread_num, func, *args):",
"<reponame>naetimus/bootcamp<filename>solutions/pic_search/webserver/src/service/theardpool.py import threading from concurrent.futures import ThreadPoolExecutor from servi... |
[
"# dest='alpha', # help='try to get the version') # Execute parse_args() args =",
"subcommand = parser.parse_args().cmd if args.version is True: print(f\"version: {__version__}\") exit(0) # if subcommand",
"the build system') # parser.add_argument( # '-f', # '--file', # help='A readable file',",
"__version__ ... |
[
"R.json() PAGES = DATA[\"query\"][\"pages\"] for k, v in PAGES.items(): for l in v[\"links\"]:",
"file is auto-generated. See modules.json and autogenerator.py for details #!/usr/bin/python3 \"\"\" get_links.py MediaWiki",
"\"\"\" get_links.py MediaWiki API Demos Demo of `Links` module: Get all links on",
"of... |
[
"an xyz file to use as input to use_gen_template (if make_input is True).",
"as script_file: sfw = script_file.write sfw('#!/bin/bash -l\\n\\n') sfw('#$ -pe omp {}\\n'.format(num_cores)) sfw('#$ -M",
"copied into the next file) and a template file that should be the",
"line is the number of atoms # continue #... |
[
"if len(matrix.shape) > 1: matrix_list = [] for row in matrix: try: matrix_list.append(list(row))",
"import pdb import numpy as np import pickle def listify_mat(matrix): matrix = np.array(matrix).astype(str)",
"pdb.set_trace() return matrix_list else: return list(matrix) class Recorder(): def __init__(self): se... |
[
"'state', 'zip', 'lng', 'lat'] mywriter=csv.writer(output) mywriter.writerow(header) for r in range(1000): mywriter.writerow([ fake.name(), fake.random_int(min=18,",
"'street', 'city', 'state', 'zip', 'lng', 'lat'] mywriter=csv.writer(output) mywriter.writerow(header) for r in range(1000): mywriter.writerow([",
... |
[
"# Generated by Django 2.2.4 on 2019-10-03 21:09 from django.db import migrations, models",
"django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('ingreso', '0003_auto_20190907_2152'),",
"on 2019-10-03 21:09 from django.db import migration... |
[
"= tddft_iter(label='water', cd=dname) try: from pyscf.lib import misc libnao_gpu = misc.load_library(\"libnao_gpu\") td_gpu =",
"self.assertTrue(hasattr(td, 'xvrt')) self.assertTrue(td.ksn2f.sum()==8.0) # water: O -- 6 electrons in the valence +",
"valence + H2 -- 2 electrons self.assertEqual(td_gpu.xocc[0].sh... |
[
"JSON', long_description=long_description, long_description_content_type='text/markdown', keywords='geometry gis osm parsing', author='<NAME>', author_email='<EMAIL>', url='https://github.com/aspectumapp/osm2geojson', packages=['osm2geojson'], include_package_data=True, install_requires=parse_requirements(\"require... |
[
"(valor, registro[0])) if cursor.rowcount == 1: conexao.commit() print('Alteração gravada.') else: conexao.rollback() print('Alteração abortada.')",
"= float(input('Novo valor: R$')) cursor.execute('UPDATE Precos SET preco = ? WHERE nome_produto =",
"with sqlite3.connect('precos.db') as conexao: with closing(co... |
[
"return self.__class__(self.vars,obj,le,eq) def build_solution(self,x,obj_value,status,duals): _vars = { var: v.item() for var,v in zip(self.vars,x)}",
"= [] self.posts = [] def solve(self,p,config,x=None): for pre in self.pres: start =",
"x,_,status,duals = solve(p_f32,x,config,fast=True) logger.debug(\"fast m... |
[
"import numpy as np import cv2 def test_pad(): raw = dict( img=np.zeros((200, 401,",
"pad(raw) print(r['img'].shape) cv2.imshow('draw', r['img']) cv2.waitKey() raw = dict( img=np.zeros((402, 401, 3), dtype=np.uint8) )",
"gt_bboxes = np.array([[0, 0, 10, 9]]) result = dict(gt_bboxes=bboxes) fb = FilterBox((10, 1... |
[
"self.aliases = aliases class FakeConfigurationSettings(object): def __init__(self, settings_name, base_config=None): self.base_config = base_config self.name",
"test_ProjectSettingsFileMergeKwSection_ValidInputs_Success(mock_parse_json, fake_context, mock_json_map, additional_aliases, section_key, expected): tes... |
[
"enum.auto() SUM_MAX_DEVIATION = enum.auto() def _generate_variables(solver, points, coeff_ranges, err_max, error_def): \"\"\"Create coefficient variables.",
"tuples (x, y) coeff_ranges: A tuple of valid coefficient ranges, respresented as tuples",
"definition.\"\"\" objective = solver.Objective() for variable ... |
[
"parsed.package_dir)) # Convert build_dir to absolute path, relative to package_dir. parsed.build_dir = os.path.join(parsed.package_dir,",
"as e: printerr('FAIL: Generating the Xcode project failed') printerr('Executing: %s' % ' '.join(e.cmd))",
"in the toolchain rpaths_to_add = ['@executable_path/../lib/swift/... |
[
"group id\", \"name\": \"Light group\", \"type\": \"LightGroup\", \"state\": {\"all_on\": False, \"any_on\": True}, \"action\":",
"openpeerpower.components.scene import DOMAIN as SCENE_DOMAIN, SERVICE_TURN_ON from openpeerpower.const import ATTR_ENTITY_ID from .test_gateway import",
"config_entry.data, \"/group... |
[
"mailbot_config.getint(section, 'max_emails_per_protection_interval', fallback=50) NOTIFY_INTRUDER = mailbot_config.getboolean(section, 'notify_intruder', fallback=True) NOTIFY_ADMIN = mailbot_config.getboolean(section, 'notify_admin', fallback=False)",
"/ 'hosts_config.ini') MAILBOT_TEMPLATE_CONFIG_PATH = str(te... |
[
"2) + dec_hid_dim self.attn = nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len =",
"= nn.Linear(self.attn_in, attn_dim) def forward(self, decoder_hidden, encoder_outputs): src_len = encoder_outputs.shape[0] repeated_decoder_hidden = decoder_hidden.unsqueeze(1).repeat(1... |
[
"to send it to # loss function we want it to be (N,",
"of shape (trg_len, batch_size, output_dim) but Cross Entropy Loss # doesn't take input",
"encoder_net = Encoder( input_size_encoder, encoder_embedding_size, hidden_size, num_layers, enc_dropout ).to(device) decoder_net = Decoder( input_size_decoder,",
"wa... |
[
"class LightImitateMixin(Agent): \"\"\"Abstract class that handles passing expert trajectories alongside self-play sampling \"\"\"",
"import Agent from parlai.core.message import Message from random import sample import pathlib path",
"for i in range(len(utterances)): history = self.histories[i] history.append(... |
[
"( ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType) -> bool: \"\"\" Args: head:",
"from pytudes._2021.utils.linked_list import ( ListNode, NodeType, convert_list_to_linked_list, ) def has_cycle(head: NodeType) -> bool:",
">>> head.next = head >>> has_cycle(head) True >>> head = c... |
[
"# conn.sendall(msg) break if __name__ == '__main__': input_port = int(sys.argv[1]) input_doc_root = sys.argv[2]",
"200 req else: res = self.res_200 res += \"Last-Modified: {}\\r\\n\".format(time.ctime(os.stat(path).st_mtime)) with open(path, \"rb\")",
"# mapping url, return 404 escape or absolute filename # ju... |
[
"all metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \"\"\" def reset(self): pass def add(self): pass def value(self):",
"class Metric(object): \"\"\"Base class for all metrics. From: https://github.com/pytorch/tnt/blob/master/torchnet/meter/meter.py \"\"\" def reset(self): pass"... |
[
"git import Repo from pf_pweb_sourceman.common.console import console from pf_py_file.pfpf_file_util import PFPFFileUtil class GitRepoMan:",
"class GitRepoMan: def get_repo_name_from_url(self, url: str): if not url: return None last_slash_index =",
"def clone_or_pull_project(self, path, url, branch): repo_name ... |
[
"= stdout_4.readlines() output_5 = stdout_5.readlines() remote_data_1 = { 'Hostname': '', 'IP': '', 'MAC':",
"= stdout_6.readlines() data_ = [] filter_ = [] remote_data_2 = { 'Hostname': [],",
"due to wrong username/password\".format(Hostname)) exit(1) except: print(\"Failed to connect to {} \".format(Hostname)... |
[
"delete_latest_version_of_secret(self, path, mount_point=DEFAULT_MOUNT_POINT): \"\"\"Issue a soft delete of the secret's latest version at",
"int :param cas_required: If true the key will require the cas parameter to",
"str | unicode :return: The response of the request. :rtype: requests.Response \"\"\" params"... |
[
"to connected device(s) import subprocess import sys answer = input(\"Install all vulkan examples",
"time! (Y/N)\").lower() == 'y' if answer: BUILD_ARGUMENTS = \"\" for arg in sys.argv[1:]:",
"this may take some time! (Y/N)\").lower() == 'y' if answer: BUILD_ARGUMENTS = \"\"",
"\"-validation\" if subprocess.c... |
[
"# Ahoughton generator and adapter test # 2016 problem = ahoughton_generator_2016.generate() ahoughton_renderer_2016.render_problem(problem) #",
"DefaultProblemAdapter from adapters.crg import CRGProblemAdapter from adapters.ahoughton import AhoughtonAdapter import json def main():",
"AhoughtonAdapter(), config... |