fumiyau/python_comments_free_500000 · Datasets at Hugging Face

f704acaf0d0906ebdcf3194cb863c6e94506ef5d

2,146

py

Python

stubs.min/System/Windows/Forms/__init___parts/ToolStripRenderEventArgs.py

ricardyn/ironpython-stubs

4d2b405eda3ceed186e8adca55dd97c332c6f49d

[ "MIT" ]

1

2021-02-02T13:39:16.000Z

stubs.min/System/Windows/Forms/__init___parts/ToolStripRenderEventArgs.py

hdm-dt-fb/ironpython-stubs

4d2b405eda3ceed186e8adca55dd97c332c6f49d

[ "MIT" ]

null

stubs.min/System/Windows/Forms/__init___parts/ToolStripRenderEventArgs.py

hdm-dt-fb/ironpython-stubs

4d2b405eda3ceed186e8adca55dd97c332c6f49d

[ "MIT" ]

null

class ToolStripRenderEventArgs(EventArgs): """ Provides data for the System.Windows.Forms.ToolStripRenderer.OnRenderImageMargin(System.Windows.Forms.ToolStripRenderEventArgs),System.Windows.Forms.ToolStripRenderer.OnRenderToolStripBorder(System.Windows.Forms.ToolStripRenderEventArgs),and System.Windows.Forms.ToolStripRenderer.OnRenderToolStripBackground(System.Windows.Forms.ToolStripRenderEventArgs) methods. ToolStripRenderEventArgs(g: Graphics,toolStrip: ToolStrip) ToolStripRenderEventArgs(g: Graphics,toolStrip: ToolStrip,affectedBounds: Rectangle,backColor: Color) """ @staticmethod def __new__(self,g,toolStrip,affectedBounds=None,backColor=None): """ __new__(cls: type,g: Graphics,toolStrip: ToolStrip) __new__(cls: type,g: Graphics,toolStrip: ToolStrip,affectedBounds: Rectangle,backColor: Color) """ pass AffectedBounds=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the System.Drawing.Rectangle representing the bounds of the area to be painted. Get: AffectedBounds(self: ToolStripRenderEventArgs) -> Rectangle """ BackColor=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the System.Drawing.Color that the background of the System.Windows.Forms.ToolStrip is painted with. Get: BackColor(self: ToolStripRenderEventArgs) -> Color """ ConnectedArea=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the System.Drawing.Rectangle representing the overlap area between a System.Windows.Forms.ToolStripDropDown and its System.Windows.Forms.ToolStripDropDown.OwnerItem. Get: ConnectedArea(self: ToolStripRenderEventArgs) -> Rectangle """ Graphics=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the System.Drawing.Graphics used to paint. Get: Graphics(self: ToolStripRenderEventArgs) -> Graphics """ ToolStrip=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the System.Windows.Forms.ToolStrip to be painted. Get: ToolStrip(self: ToolStripRenderEventArgs) -> ToolStrip """

42.078431

367

0.768872

class ToolStripRenderEventArgs(EventArgs): __new__(cls: type,g: Graphics,toolStrip: ToolStrip) __new__(cls: type,g: Graphics,toolStrip: ToolStrip,affectedBounds: Rectangle,backColor: Color) Get: AffectedBounds(self: ToolStripRenderEventArgs) -> Rectangle ConnectedArea=property(lambda self: object(),lambda self,v: None,lambda self: None) """Gets the System.Drawing.Rectangle representing the overlap area between a System.Windows.Forms.ToolStripDropDown and its System.Windows.Forms.ToolStripDropDown.OwnerItem. """

true

f704acb27652fac4c53df6d424b7bb033879e704

15,975

py

Python

CollisionAvoidanceMonitor/main.py

GustavLero/EPICS-inst_servers

4bcdd6a80f1d9e074de3f0f7c66968d506981988

[ "BSD-3-Clause" ]

null

CollisionAvoidanceMonitor/main.py

GustavLero/EPICS-inst_servers

4bcdd6a80f1d9e074de3f0f7c66968d506981988

[ "BSD-3-Clause" ]

null

CollisionAvoidanceMonitor/main.py

GustavLero/EPICS-inst_servers

4bcdd6a80f1d9e074de3f0f7c66968d506981988

[ "BSD-3-Clause" ]

null

import sys import os import ode import logging import threading from time import sleep, time from genie_python.genie_startup import * import pv_server import render from configurations import config_zoom as config from collide import collide, CollisionDetector from geometry import GeometryBox from move import move_all sys.path.insert(0, os.path.abspath(os.environ["MYDIRCD"])) from monitor import Monitor from server_common.loggers.isis_logger import IsisLogger logging.basicConfig(level=logging.INFO, format='%(asctime)s (%(threadName)-2s) %(message)s', ) def auto_seek(start_step_size, start_values, end_value, geometries, moves, axis_index, ignore, fine_step=None): limit = end_value current_value = start_values[axis_index] if current_value == end_value: return end_value values = start_values[:] last_value = None old_points = None step_checked = False if current_value < end_value: # Going up def comp(a, b): return a b step_size = -abs(start_step_size) while last_value is None or comp(last_value, end_value): # Move if we need to if last_value is not None: current_value += step_size # print "Using step size of %f" % step_size else: current_value = start_values[axis_index] if not comp(current_value, end_value): current_value = end_value values[axis_index] = current_value move_all(geometries, moves, values=values[:]) # Check nothing moved too far if step_checked is False: new_points = [g.get_vertices() for g in geometries] if old_points is not None: delta = max_delta(geometries, new_points, old_points) if delta > start_step_size: # Work out a new step size step_size *= start_step_size/delta last_value = None continue step_checked = True # Check for collisions collisions = collide(geometries, ignore) if any(collisions): if current_value == start_values[axis_index]: # There was already a collision limit = current_value break elif fine_step and fine_step < step_size: start_values[axis_index] = last_value limit = auto_seek(fine_step, start_values, current_value, geometries, moves, axis_index, ignore) else: limit = last_value break old_points = new_points[:] last_value = current_value # print "Found limits for axis %d using step size of %f" % (axis_index, step_size) if limit is None: raise ValueError("Null limit") return limit def max_delta(geometries, new_points, old_points): # Calculate the greatest position deltas delta = 0 for j in range(len(geometries)): old = old_points[j] new = new_points[j] deltas = [map(float, n - o) for n, o in zip(new, old)] for i, (x, y, z) in enumerate(deltas): mag = float(x) ** 2 + float(y) ** 2 + float(z) ** 2 if mag > delta: delta = mag # print "New max delta of %f (%f, %f, %f) for body %d at %s from %s" % \ # (mag ** 0.5, x, y, z, j, new[i], old[i]) delta = float(delta) ** 0.5 return delta def compare(sign): if sign > 0: return lambda a, b: a > b else: return lambda a, b: a < b def auto_seek_limits(geometries, ignore, moves, values, limits, coarse=1.0, fine=0.1): dynamic_limits = [] for i in range(len(values)): logging.debug("Seeking for axis %d" % i) lower_limit = auto_seek(coarse, values[:], min(limits[i]), geometries, moves, i, ignore, fine) upper_limit = auto_seek(coarse, values[:], max(limits[i]), geometries, moves, i, ignore, fine) dynamic_limits.append([lower_limit, upper_limit]) logging.debug("Found limits for axis %d at %s, %s" % (i, upper_limit, lower_limit)) return dynamic_limits def look_ahead(start_values, pvs, is_moving, geometries, moves, ignore, max_movement=1.0, max_time=10., time_step=0.1): # Get the indices of the axes currently moving moving = [i for i, m in enumerate(is_moving) if m == 0] # DMOV = 0 when motors not moving msg = "No collisions predicted in the next %fs" % max_time safe_time = max_time safe = True # Only worth calculating if more than one axis is moving if len(moving) > 1: set_points = [None] * len(pvs) speeds = [None] * len(pvs) directions = [None] * len(pvs) # Assume everything has finished moving move_complete = [True] * len(pvs) # Get some settings: for i in moving: pv = pvs[i] set_point = get_pv(pv + '.DVAL') speed = get_pv(pv + '.VELO') direction = 0. move = set_point - start_values[i] if move > 0: direction = 1. if move < 0: direction = -1. set_points[i] = set_point speeds[i] = speed directions[i] = direction # This axis has not finished moving! move_complete[i] = False current_time = 0. values = start_values[:] old_points = None step_checked = False last_time = None while current_time < max_time: if last_time is None: values = start_values[:] current_time = 0. old_points = None else: current_time += time_step for i in moving: if move_complete[i] is False: values[i] = start_values[i] + (directions[i] * speeds[i] * current_time) comp = compare(directions[i])(values[i], set_points[i]) if comp: values[i] = set_points[i] # Move the bodies move_all(geometries, moves, values=values) if step_checked is False: new_points = [g.get_vertices() for g in geometries] if old_points is not None: delta = max_delta(geometries, new_points, old_points) if delta > max_movement: # Reduce the size of the time step time_step *= max_movement/delta # Reset to starting point last_time = None old_points = None continue step_checked = True # Check for collisions collisions = collide(geometries, ignore) if any(collisions): if last_time is None: msg = "There is already a collision" safe_time = 0. else: msg = "Collision expected in %.1fs - %.1fs" % (last_time, current_time) safe_time = last_time safe = False break old_points = new_points[:] last_time = current_time return msg, safe_time, safe # Set the high and low dial limits for each motor def set_limits(limits, pvs): for limit, pv in zip(limits, pvs): set_pv(pv + '.DLLM', limit[0]) set_pv(pv + '.DHLM', limit[1]) # Contains operating mode events class OperatingMode(object): def __init__(self): # Close event to be triggered by the render thread self.close = threading.Event() # Set dynamic limits automatically self.set_limits = threading.Event() # Stop the motors on a collision self.auto_stop = threading.Event() # Re-calculate limits on demand self.calc_limits = threading.Event() def get_operation_mode(self): return self.auto_stop.is_set(), self.set_limits.is_set(), self.close.is_set() def set_operation_mode(self, auto_stop, set_limits, close): if auto_stop: self.auto_stop.set() else: self.auto_stop.clear() if set_limits: self.set_limits.set() else: self.set_limits.clear() if close: self.close.set() else: self.close.clear() # The main routine to execute def main(): # Load config: colors = config.colors moves = config.moves ignore = config.ignore pvs = config.pvs config_limits = config.hardlimits old_limits = config_limits[:] # Create space objects for the live and rendered world space = ode.Space() render_space = ode.Space() collision_space = ode.Space() # Create and populate lists of geometries geometries = [] render_geometries = [] collision_geometries = [] for i, geometry in enumerate(config.geometries): geometries.append(GeometryBox(space, oversize=config.oversize, **geometry)) render_geometries.append(GeometryBox(render_space, **geometry)) collision_geometries.append(GeometryBox(collision_space, oversize=config.oversize, **geometry)) # Create and populate two lists of monitors monitors = [] is_moving = [] for pv in pvs: m = Monitor(pv + ".DRBV") m.start() monitors.append(m) any_moving = Monitor(pv + ".DMOV") any_moving.start() is_moving.append(any_moving) # Create a shared operating mode object to control the main thread op_mode = OperatingMode() # Set the default behaviour to set_limits as calculated, and auto_stop on collision op_mode.set_limits.set() op_mode.auto_stop.set() # Start a logger logger = IsisLogger() # Create a shared render parameter object to update the render thread parameters = render.RenderParams() if 'blind' not in sys.argv: # Initialise the render thread, and set it to daemon - won't prevent the main thread from exiting renderer = render.Renderer(parameters, render_geometries, colors, monitors, pvs, moves, op_mode) renderer.daemon = True # Need to know if this is the first execution of the main loop op_mode.calc_limits.set() # Initialise the pv server # Loop over the pvdb and update the counts based on the number of aves/bodies for pv in pv_server.pvdb: for key, val in pv_server.pvdb[pv].items(): if key == 'count': if val is pv_server.axis_count: pv_server.pvdb[pv]['count'] = len(config.pvs) if val is pv_server.body_count: pv_server.pvdb[pv]['count'] = len(config.geometries) driver = pv_server.start_thread(config.control_pv, op_mode) driver.setParam('OVERSIZE', config.oversize) driver.setParam('COARSE', config.coarse) driver.setParam('FINE', config.fine) driver.setParam('NAMES', [g['name'] for g in config.geometries]) # Only report for new collisions collision_detector = CollisionDetector(driver, collision_geometries, config.moves, monitors, config.ignore, is_moving, logger, op_mode, config.pvs) collision_detector.start() # Main loop while True: # Freeze the positions of our current monitors by creating some dummies # This stops the threads from trying to reading each monitor sequentially, and holding each other up frozen = [m.value() for m in monitors] # Execute the move move_all(geometries, moves, values=frozen) # Check if the oversize has been changed, ahead of any collision calcs if driver.new_data.isSet(): for geometry, collision_geometry in zip(geometries, collision_geometries): geometry.set_size(oversize=driver.getParam('OVERSIZE')) collision_geometry.set_size(oversize=driver.getParam('OVERSIZE')) driver.new_data.clear() op_mode.calc_limits.set() if driver.getParam("CALC") != 0: op_mode.calc_limits.set() collisions = collision_detector.collisions[:] collision_message = collision_detector.message[:] # Check if there have been any changes to the .MOVN monitors fresh = any([m.fresh() for m in is_moving]) # Check if any of the motors monitors are moving moving = [not m.value() for m in is_moving] # Invert because DMOV is inverted from MOVN any_moving = any(moving) new_limits = [] if fresh or any_moving or op_mode.calc_limits.isSet(): # Look ahead some time to see if any collisions are going to happen in the future msg, safe_time, safe = look_ahead(frozen, config.pvs, moving, geometries, moves, ignore, max_movement=driver.getParam('COARSE')) if not safe and not any(collisions): logger.write_to_log(msg, "MAJOR", "COLLIDE") driver.setParam('MSG', msg) else: driver.setParam('MSG', collision_message) logging.info(msg) # Start timing for diagnostics time_passed = time() # Seek the correct limit values dynamic_limits = auto_seek_limits(geometries, ignore, moves, frozen, config_limits, coarse=driver.getParam('COARSE'), fine=driver.getParam('FINE')) # Calculate and log the time taken to calculate time_passed = (time() - time_passed) * 1000 # Log the new limits logging.info("New limits calculated in %dms, are %s" % (time_passed, dynamic_limits)) # Set the limits according to the set_limits operating mode if op_mode.set_limits.is_set(): # Apply the calculated limits new_limits = dynamic_limits[:] else: # Restore the configuration limits new_limits = config_limits[:] # Update the render thread parameters parameters.update_params(dynamic_limits, collisions, time_passed) # # Update the PVs driver.setParam('TIME', time_passed) driver.setParam('HI_LIM', [l[1] for l in dynamic_limits]) driver.setParam('LO_LIM', [l[0] for l in dynamic_limits]) driver.setParam('TRAVEL', [min([l[0] - m, l[1] - m], key=abs) for l, m in zip(dynamic_limits, frozen)]) driver.setParam('TRAV_F', [l[1] - m for l, m in zip(dynamic_limits, frozen)]) driver.setParam('TRAV_R', [l[0] - m for l, m in zip(dynamic_limits, frozen)]) driver.updatePVs() if 'blind' not in sys.argv: # On the first run, start the renderer if renderer.is_alive() is False: renderer.start() op_mode.calc_limits.clear() driver.setParam("CALC", False) else: # Restore the configuration limits if op_mode.set_limits.is_set() is False: new_limits = config_limits[:] # Stop us overloading the limits if not new_limits == old_limits: threading.Thread(target=set_limits, args=(new_limits, pvs)).start() old_limits = new_limits[:] # Exit the program if op_mode.close.is_set(): # Restore the configuration limits set_limits(config_limits, pvs) return # Give the CPU a break sleep(0.01) if 'return' in sys.argv: return # Execute main main()

33.560924

119

0.587856

import sys import os import ode import logging import threading from time import sleep, time from genie_python.genie_startup import * import pv_server import render from configurations import config_zoom as config from collide import collide, CollisionDetector from geometry import GeometryBox from move import move_all sys.path.insert(0, os.path.abspath(os.environ["MYDIRCD"])) from monitor import Monitor from server_common.loggers.isis_logger import IsisLogger logging.basicConfig(level=logging.INFO, format='%(asctime)s (%(threadName)-2s) %(message)s', ) def auto_seek(start_step_size, start_values, end_value, geometries, moves, axis_index, ignore, fine_step=None): limit = end_value current_value = start_values[axis_index] if current_value == end_value: return end_value values = start_values[:] last_value = None old_points = None step_checked = False if current_value < end_value: def comp(a, b): return a b step_size = -abs(start_step_size) while last_value is None or comp(last_value, end_value): if last_value is not None: current_value += step_size else: current_value = start_values[axis_index] if not comp(current_value, end_value): current_value = end_value values[axis_index] = current_value move_all(geometries, moves, values=values[:]) if step_checked is False: new_points = [g.get_vertices() for g in geometries] if old_points is not None: delta = max_delta(geometries, new_points, old_points) if delta > start_step_size: step_size *= start_step_size/delta last_value = None continue step_checked = True collisions = collide(geometries, ignore) if any(collisions): if current_value == start_values[axis_index]: limit = current_value break elif fine_step and fine_step < step_size: start_values[axis_index] = last_value limit = auto_seek(fine_step, start_values, current_value, geometries, moves, axis_index, ignore) else: limit = last_value break old_points = new_points[:] last_value = current_value if limit is None: raise ValueError("Null limit") return limit def max_delta(geometries, new_points, old_points): delta = 0 for j in range(len(geometries)): old = old_points[j] new = new_points[j] deltas = [map(float, n - o) for n, o in zip(new, old)] for i, (x, y, z) in enumerate(deltas): mag = float(x) ** 2 + float(y) ** 2 + float(z) ** 2 if mag > delta: delta = mag delta = float(delta) ** 0.5 return delta def compare(sign): if sign > 0: return lambda a, b: a > b else: return lambda a, b: a < b def auto_seek_limits(geometries, ignore, moves, values, limits, coarse=1.0, fine=0.1): dynamic_limits = [] for i in range(len(values)): logging.debug("Seeking for axis %d" % i) lower_limit = auto_seek(coarse, values[:], min(limits[i]), geometries, moves, i, ignore, fine) upper_limit = auto_seek(coarse, values[:], max(limits[i]), geometries, moves, i, ignore, fine) dynamic_limits.append([lower_limit, upper_limit]) logging.debug("Found limits for axis %d at %s, %s" % (i, upper_limit, lower_limit)) return dynamic_limits def look_ahead(start_values, pvs, is_moving, geometries, moves, ignore, max_movement=1.0, max_time=10., time_step=0.1): moving = [i for i, m in enumerate(is_moving) if m == 0] msg = "No collisions predicted in the next %fs" % max_time safe_time = max_time safe = True if len(moving) > 1: set_points = [None] * len(pvs) speeds = [None] * len(pvs) directions = [None] * len(pvs) move_complete = [True] * len(pvs) for i in moving: pv = pvs[i] set_point = get_pv(pv + '.DVAL') speed = get_pv(pv + '.VELO') direction = 0. move = set_point - start_values[i] if move > 0: direction = 1. if move < 0: direction = -1. set_points[i] = set_point speeds[i] = speed directions[i] = direction move_complete[i] = False current_time = 0. values = start_values[:] old_points = None step_checked = False last_time = None while current_time < max_time: if last_time is None: values = start_values[:] current_time = 0. old_points = None else: current_time += time_step for i in moving: if move_complete[i] is False: values[i] = start_values[i] + (directions[i] * speeds[i] * current_time) comp = compare(directions[i])(values[i], set_points[i]) if comp: values[i] = set_points[i] move_all(geometries, moves, values=values) if step_checked is False: new_points = [g.get_vertices() for g in geometries] if old_points is not None: delta = max_delta(geometries, new_points, old_points) if delta > max_movement: time_step *= max_movement/delta last_time = None old_points = None continue step_checked = True collisions = collide(geometries, ignore) if any(collisions): if last_time is None: msg = "There is already a collision" safe_time = 0. else: msg = "Collision expected in %.1fs - %.1fs" % (last_time, current_time) safe_time = last_time safe = False break old_points = new_points[:] last_time = current_time return msg, safe_time, safe def set_limits(limits, pvs): for limit, pv in zip(limits, pvs): set_pv(pv + '.DLLM', limit[0]) set_pv(pv + '.DHLM', limit[1]) class OperatingMode(object): def __init__(self): self.close = threading.Event() self.set_limits = threading.Event() self.auto_stop = threading.Event() self.calc_limits = threading.Event() def get_operation_mode(self): return self.auto_stop.is_set(), self.set_limits.is_set(), self.close.is_set() def set_operation_mode(self, auto_stop, set_limits, close): if auto_stop: self.auto_stop.set() else: self.auto_stop.clear() if set_limits: self.set_limits.set() else: self.set_limits.clear() if close: self.close.set() else: self.close.clear() def main(): colors = config.colors moves = config.moves ignore = config.ignore pvs = config.pvs config_limits = config.hardlimits old_limits = config_limits[:] space = ode.Space() render_space = ode.Space() collision_space = ode.Space() geometries = [] render_geometries = [] collision_geometries = [] for i, geometry in enumerate(config.geometries): geometries.append(GeometryBox(space, oversize=config.oversize, **geometry)) render_geometries.append(GeometryBox(render_space, **geometry)) collision_geometries.append(GeometryBox(collision_space, oversize=config.oversize, **geometry)) monitors = [] is_moving = [] for pv in pvs: m = Monitor(pv + ".DRBV") m.start() monitors.append(m) any_moving = Monitor(pv + ".DMOV") any_moving.start() is_moving.append(any_moving) op_mode = OperatingMode() op_mode.set_limits.set() op_mode.auto_stop.set() logger = IsisLogger() parameters = render.RenderParams() if 'blind' not in sys.argv: renderer = render.Renderer(parameters, render_geometries, colors, monitors, pvs, moves, op_mode) renderer.daemon = True # Need to know if this is the first execution of the main loop op_mode.calc_limits.set() # Initialise the pv server # Loop over the pvdb and update the counts based on the number of aves/bodies for pv in pv_server.pvdb: for key, val in pv_server.pvdb[pv].items(): if key == 'count': if val is pv_server.axis_count: pv_server.pvdb[pv]['count'] = len(config.pvs) if val is pv_server.body_count: pv_server.pvdb[pv]['count'] = len(config.geometries) driver = pv_server.start_thread(config.control_pv, op_mode) driver.setParam('OVERSIZE', config.oversize) driver.setParam('COARSE', config.coarse) driver.setParam('FINE', config.fine) driver.setParam('NAMES', [g['name'] for g in config.geometries]) # Only report for new collisions collision_detector = CollisionDetector(driver, collision_geometries, config.moves, monitors, config.ignore, is_moving, logger, op_mode, config.pvs) collision_detector.start() # Main loop while True: # Freeze the positions of our current monitors by creating some dummies # This stops the threads from trying to reading each monitor sequentially, and holding each other up frozen = [m.value() for m in monitors] # Execute the move move_all(geometries, moves, values=frozen) # Check if the oversize has been changed, ahead of any collision calcs if driver.new_data.isSet(): for geometry, collision_geometry in zip(geometries, collision_geometries): geometry.set_size(oversize=driver.getParam('OVERSIZE')) collision_geometry.set_size(oversize=driver.getParam('OVERSIZE')) driver.new_data.clear() op_mode.calc_limits.set() if driver.getParam("CALC") != 0: op_mode.calc_limits.set() collisions = collision_detector.collisions[:] collision_message = collision_detector.message[:] # Check if there have been any changes to the .MOVN monitors fresh = any([m.fresh() for m in is_moving]) # Check if any of the motors monitors are moving moving = [not m.value() for m in is_moving] # Invert because DMOV is inverted from MOVN any_moving = any(moving) new_limits = [] if fresh or any_moving or op_mode.calc_limits.isSet(): # Look ahead some time to see if any collisions are going to happen in the future msg, safe_time, safe = look_ahead(frozen, config.pvs, moving, geometries, moves, ignore, max_movement=driver.getParam('COARSE')) if not safe and not any(collisions): logger.write_to_log(msg, "MAJOR", "COLLIDE") driver.setParam('MSG', msg) else: driver.setParam('MSG', collision_message) logging.info(msg) # Start timing for diagnostics time_passed = time() # Seek the correct limit values dynamic_limits = auto_seek_limits(geometries, ignore, moves, frozen, config_limits, coarse=driver.getParam('COARSE'), fine=driver.getParam('FINE')) # Calculate and log the time taken to calculate time_passed = (time() - time_passed) * 1000 # Log the new limits logging.info("New limits calculated in %dms, are %s" % (time_passed, dynamic_limits)) # Set the limits according to the set_limits operating mode if op_mode.set_limits.is_set(): # Apply the calculated limits new_limits = dynamic_limits[:] else: # Restore the configuration limits new_limits = config_limits[:] # Update the render thread parameters parameters.update_params(dynamic_limits, collisions, time_passed) # # Update the PVs driver.setParam('TIME', time_passed) driver.setParam('HI_LIM', [l[1] for l in dynamic_limits]) driver.setParam('LO_LIM', [l[0] for l in dynamic_limits]) driver.setParam('TRAVEL', [min([l[0] - m, l[1] - m], key=abs) for l, m in zip(dynamic_limits, frozen)]) driver.setParam('TRAV_F', [l[1] - m for l, m in zip(dynamic_limits, frozen)]) driver.setParam('TRAV_R', [l[0] - m for l, m in zip(dynamic_limits, frozen)]) driver.updatePVs() if 'blind' not in sys.argv: # On the first run, start the renderer if renderer.is_alive() is False: renderer.start() op_mode.calc_limits.clear() driver.setParam("CALC", False) else: # Restore the configuration limits if op_mode.set_limits.is_set() is False: new_limits = config_limits[:] # Stop us overloading the limits if not new_limits == old_limits: threading.Thread(target=set_limits, args=(new_limits, pvs)).start() old_limits = new_limits[:] # Exit the program if op_mode.close.is_set(): # Restore the configuration limits set_limits(config_limits, pvs) return # Give the CPU a break sleep(0.01) if 'return' in sys.argv: return # Execute main main()

true

f704aebb270ae5ced9b2f8e4f29e963b3e7dd7bd

3,084

py

Python

rbflayer.py

edwardstm/rbf_keras

4029d1c15003438f7caadb9efefe0c026ba18933

[ "MIT" ]

1

2020-04-20T12:34:06.000Z

rbflayer.py

edwardstm/rbf_keras

4029d1c15003438f7caadb9efefe0c026ba18933

[ "MIT" ]

null

rbflayer.py

edwardstm/rbf_keras

4029d1c15003438f7caadb9efefe0c026ba18933

[ "MIT" ]

null

import tensorflow as tf from tensorflow.keras import backend as K from tensorflow.keras.layers import Layer from tensorflow.keras.initializers import RandomUniform, Initializer, Constant import numpy as np class InitCentersRandom(Initializer): """ Initializer for initialization of centers of RBF network as random samples from the given data set. # Arguments X: matrix, dataset to choose the centers from (random rows are taken as centers) """ def __init__(self, X): self.X = X def __call__(self, shape, dtype=None): assert shape[1] == self.X.shape[1] idx = tf.constant( np.random.randint(self.X.shape[0], size=shape[0]) ) return self.X[idx, :] class RBFLayer(Layer): """ Layer of Gaussian RBF units. # Example ```python model = Sequential() model.add(RBFLayer(10, initializer=InitCentersRandom(X), betas=1.0, input_shape=(1,))) model.add(Dense(1)) ``` # Arguments output_dim: number of hidden units (i.e. number of outputs of the layer) initializer: instance of initiliazer to initialize centers betas: float, initial value for betas """ def __init__(self, output_dim, initializer=None, betas=1.0, **kwargs): self.output_dim = output_dim self.init_betas = betas if not initializer: self.initializer = RandomUniform(0.0, 1.0) else: self.initializer = initializer super(RBFLayer, self).__init__(**kwargs) def build(self, input_shape): self.centers = self.add_weight(name='centers', shape=(self.output_dim, input_shape[1]), initializer=self.initializer, trainable=True) self.betas = self.add_weight(name='betas', shape=(self.output_dim,), initializer=Constant( value=self.init_betas), # initializer='ones', trainable=True) super(RBFLayer, self).build(input_shape) def call(self, x): C = K.expand_dims(self.centers) H = K.transpose(C-K.transpose(x)) return K.exp(-self.betas * K.sum(H**2, axis=1)) # C = self.centers[np.newaxis, :, :] # X = x[:, np.newaxis, :] # diffnorm = K.sum((C-X)**2, axis=-1) # ret = K.exp( - self.betas * diffnorm) # return ret def compute_output_shape(self, input_shape): return (input_shape[0], self.output_dim) def get_config(self): # have to define get_config to be able to use model_from_json config = { 'output_dim': self.output_dim } base_config = super(RBFLayer, self).get_config() return dict(list(base_config.items()) + list(config.items()))

32.463158

79

0.552205

import tensorflow as tf from tensorflow.keras import backend as K from tensorflow.keras.layers import Layer from tensorflow.keras.initializers import RandomUniform, Initializer, Constant import numpy as np class InitCentersRandom(Initializer): def __init__(self, X): self.X = X def __call__(self, shape, dtype=None): assert shape[1] == self.X.shape[1] idx = tf.constant( np.random.randint(self.X.shape[0], size=shape[0]) ) return self.X[idx, :] class RBFLayer(Layer): def __init__(self, output_dim, initializer=None, betas=1.0, **kwargs): self.output_dim = output_dim self.init_betas = betas if not initializer: self.initializer = RandomUniform(0.0, 1.0) else: self.initializer = initializer super(RBFLayer, self).__init__(**kwargs) def build(self, input_shape): self.centers = self.add_weight(name='centers', shape=(self.output_dim, input_shape[1]), initializer=self.initializer, trainable=True) self.betas = self.add_weight(name='betas', shape=(self.output_dim,), initializer=Constant( value=self.init_betas), trainable=True) super(RBFLayer, self).build(input_shape) def call(self, x): C = K.expand_dims(self.centers) H = K.transpose(C-K.transpose(x)) return K.exp(-self.betas * K.sum(H**2, axis=1)) def compute_output_shape(self, input_shape): return (input_shape[0], self.output_dim) def get_config(self): config = { 'output_dim': self.output_dim } base_config = super(RBFLayer, self).get_config() return dict(list(base_config.items()) + list(config.items()))

true

f704af9532b46b3dbbc7284a567541674794e691

9,805

py

Python

tools/data/build_rawframes.py

vt-vl-lab/video-data-aug

01667cdbd1b952f2510af3422beeeb76e0d9e15a

[ "Apache-2.0" ]

20

2021-03-31T02:25:20.000Z

2022-03-11T11:45:59.000Z

tools/data/build_rawframes.py

vt-vl-lab/video-data-aug

01667cdbd1b952f2510af3422beeeb76e0d9e15a

[ "Apache-2.0" ]

6

2021-05-27T18:08:39.000Z

2022-03-23T14:00:51.000Z

tools/data/build_rawframes.py

vt-vl-lab/video-data-aug

01667cdbd1b952f2510af3422beeeb76e0d9e15a

[ "Apache-2.0" ]

4

2021-03-31T03:11:45.000Z

2021-08-22T11:11:45.000Z

import argparse import glob import os import os.path as osp import sys import warnings from multiprocessing import Pool import mmcv import numpy as np # custom import import pandas as pd import pdb def extract_frame(vid_item): """Generate optical flow using dense flow. Args: vid_item (list): Video item containing video full path, video (short) path, video id. Returns: bool: Whether generate optical flow successfully. """ full_path, vid_path, vid_id, method, task = vid_item if '/' in vid_path: act_name = osp.basename(osp.dirname(vid_path)) out_full_path = osp.join(args.out_dir, act_name) else: out_full_path = args.out_dir if task == 'rgb': if args.use_opencv: # Not like using denseflow, # Use OpenCV will not make a sub directory with the video name video_name = osp.splitext(osp.basename(vid_path))[0] out_full_path = osp.join(out_full_path, video_name) vr = mmcv.VideoReader(full_path) for i in range(len(vr)): if vr[i] is not None: w, h, c = np.shape(vr[i]) if args.new_short == 0: out_img = mmcv.imresize(vr[i], (args.new_width, args.new_height)) else: if min(h, w) == h: new_h = args.new_short new_w = int((new_h / h) * w) else: new_w = args.new_short new_h = int((new_w / w) * h) out_img = mmcv.imresize(vr[i], (new_h, new_w)) mmcv.imwrite(out_img, f'{out_full_path}/img_{i + 1:05d}.jpg') else: warnings.warn( 'Length inconsistent!' f'Early stop with {i + 1} out of {len(vr)} frames.') break else: if args.new_short == 0: cmd = osp.join( f"denseflow '{full_path}' -b=20 -s=0 -o='{out_full_path}'" f' -nw={args.new_width} -nh={args.new_height} -v') else: cmd = osp.join( f"denseflow '{full_path}' -b=20 -s=0 -o='{out_full_path}'" f' -ns={args.new_short} -v') os.system(cmd) elif task == 'flow': if args.input_frames: if args.new_short == 0: cmd = osp.join( f"denseflow '{full_path}' -a={method} -b=20 -s=1 -o='{out_full_path}'" # noqa: E501 f' -nw={args.new_width} --nh={args.new_height} -v --if') else: cmd = osp.join( f"denseflow '{full_path}' -a={method} -b=20 -s=1 -o='{out_full_path}'" # noqa: E501 f' -ns={args.new_short} -v --if') else: if args.new_short == 0: cmd = osp.join( f"denseflow '{full_path}' -a={method} -b=20 -s=1 -o='{out_full_path}'" # noqa: E501 f' -nw={args.new_width} --nh={args.new_height} -v') else: cmd = osp.join( f"denseflow '{full_path}' -a={method} -b=20 -s=1 -o='{out_full_path}'" # noqa: E501 f' -ns={args.new_short} -v') os.system(cmd) else: if args.new_short == 0: cmd_rgb = osp.join( f"denseflow '{full_path}' -b=20 -s=0 -o='{out_full_path}'" f' -nw={args.new_width} -nh={args.new_height} -v') cmd_flow = osp.join( f"denseflow '{full_path}' -a={method} -b=20 -s=1 -o='{out_full_path}'" # noqa: E501 f' -nw={args.new_width} -nh={args.new_height} -v') else: cmd_rgb = osp.join( f"denseflow '{full_path}' -b=20 -s=0 -o='{out_full_path}'" f' -ns={args.new_short} -v') cmd_flow = osp.join( f"denseflow '{full_path}' -a={method} -b=20 -s=1 -o='{out_full_path}'" # noqa: E501 f' -ns={args.new_short} -v') os.system(cmd_rgb) os.system(cmd_flow) print(f'{task} {vid_id} {vid_path} {method} done') sys.stdout.flush() return True def parse_args(): parser = argparse.ArgumentParser(description='extract optical flows') parser.add_argument('src_dir', type=str, help='source video directory') parser.add_argument('out_dir', type=str, help='output rawframe directory') parser.add_argument( '--task', type=str, default='flow', choices=['rgb', 'flow', 'both'], help='which type of frames to be extracted') parser.add_argument( '--level', type=int, choices=[1, 2], default=2, help='directory level of data') parser.add_argument( '--num-worker', type=int, default=8, help='number of workers to build rawframes') parser.add_argument( '--flow-type', type=str, default=None, choices=[None, 'tvl1', 'warp_tvl1', 'farn', 'brox'], help='flow type to be generated') parser.add_argument( '--out-format', type=str, default='jpg', choices=['jpg', 'h5', 'png'], help='output format') parser.add_argument( '--ext', type=str, default='avi', choices=['avi', 'mp4', 'webm'], help='video file extensions') parser.add_argument( '--new-width', type=int, default=0, help='resize image width') parser.add_argument( '--new-height', type=int, default=0, help='resize image height') parser.add_argument( '--new-short', type=int, default=0, help='resize image short side length keeping ratio') parser.add_argument('--num-gpu', type=int, default=8, help='number of GPU') parser.add_argument( '--resume', action='store_true', default=False, help='resume optical flow extraction instead of overwriting') parser.add_argument( '--use-opencv', action='store_true', help='Whether to use opencv to extract rgb frames') parser.add_argument( '--input-frames', action='store_true', help='Whether to extract flow frames based on rgb frames') parser.add_argument( '--ref_listfile_path', type=str, default='', help='reference listfile path for the subset') args = parser.parse_args() return args def get_subset_classes(ref_listfile_path): df = pd.read_csv(ref_listfile_path, header=None, sep='*') cur_data = df.values subset_classes = [] for i,row in enumerate(cur_data): cur_cls = row[0].split('/')[1] cur_cls = cur_cls.replace(' ', '_').replace('(', '-').replace(')', '-') if cur_cls not in subset_classes: subset_classes.append(cur_cls) return subset_classes def filter_vid_list(vid_list, src_dir, ref_listfile_path): subset_classes = get_subset_classes(ref_listfile_path) filtered_vid_list = [] filtered_full_path_list = [] for vid,fpath in zip(vid_list,fullpath_list): cur_cls = vid.split('/')[0] if cur_cls in subset_classes: filtered_vid_list.append(vid) filtered_full_path_list.append(os.path.join(src_dir, vid)) return filtered_vid_list, filtered_full_path_list if __name__ == '__main__': args = parse_args() if not osp.isdir(args.out_dir): print(f'Creating folder: {args.out_dir}') os.makedirs(args.out_dir) if args.level == 2: if args.ref_listfile_path != '': classes = get_subset_classes(args.ref_listfile_path) else: classes = os.listdir(args.src_dir) for classname in classes: new_dir = osp.join(args.out_dir, classname) if not osp.isdir(new_dir): print(f'Creating folder: {new_dir}') os.makedirs(new_dir) if args.input_frames: print('Reading rgb frames from folder: ', args.src_dir) fullpath_list = glob.glob(args.src_dir + '/*' * args.level) done_fullpath_list = glob.glob(args.out_dir + '/*' * args.level) print('Total number of rgb frame folders found: ', len(fullpath_list)) else: print('Reading videos from folder: ', args.src_dir) print('Extension of videos: ', args.ext) fullpath_list = glob.glob(args.src_dir + '/*' * args.level + '.' + args.ext) done_fullpath_list = glob.glob(args.out_dir + '/*' * args.level) print('Total number of videos found: ', len(fullpath_list)) if args.resume: fullpath_list = set(fullpath_list).difference(set(done_fullpath_list)) fullpath_list = list(fullpath_list) print('Resuming. number of videos to be done: ', len(fullpath_list)) if args.level == 2: vid_list = list( map( lambda p: osp.join( osp.basename(osp.dirname(p)), osp.basename(p)), fullpath_list)) elif args.level == 1: vid_list, fullpath_list = list(map(lambda p: osp.basename(p), fullpath_list)) if args.ref_listfile_path != '': vid_list, fullpath_list = filter_vid_list(vid_list, args.src_dir, args.ref_listfile_path) pool = Pool(args.num_worker) pool.map( extract_frame, zip(fullpath_list, vid_list, range(len(vid_list)), len(vid_list) * [args.flow_type], len(vid_list) * [args.task]))

37.140152

107

0.544416

import argparse import glob import os import os.path as osp import sys import warnings from multiprocessing import Pool import mmcv import numpy as np import pandas as pd import pdb def extract_frame(vid_item): full_path, vid_path, vid_id, method, task = vid_item if '/' in vid_path: act_name = osp.basename(osp.dirname(vid_path)) out_full_path = osp.join(args.out_dir, act_name) else: out_full_path = args.out_dir if task == 'rgb': if args.use_opencv: video_name = osp.splitext(osp.basename(vid_path))[0] out_full_path = osp.join(out_full_path, video_name) vr = mmcv.VideoReader(full_path) for i in range(len(vr)): if vr[i] is not None: w, h, c = np.shape(vr[i]) if args.new_short == 0: out_img = mmcv.imresize(vr[i], (args.new_width, args.new_height)) else: if min(h, w) == h: new_h = args.new_short new_w = int((new_h / h) * w) else: new_w = args.new_short new_h = int((new_w / w) * h) out_img = mmcv.imresize(vr[i], (new_h, new_w)) mmcv.imwrite(out_img, f'{out_full_path}/img_{i + 1:05d}.jpg') else: warnings.warn( 'Length inconsistent!' f'Early stop with {i + 1} out of {len(vr)} frames.') break else: if args.new_short == 0: cmd = osp.join( f"denseflow '{full_path}' -b=20 -s=0 -o='{out_full_path}'" f' -nw={args.new_width} -nh={args.new_height} -v') else: cmd = osp.join( f"denseflow '{full_path}' -b=20 -s=0 -o='{out_full_path}'" f' -ns={args.new_short} -v') os.system(cmd) elif task == 'flow': if args.input_frames: if args.new_short == 0: cmd = osp.join( f"denseflow '{full_path}' -a={method} -b=20 -s=1 -o='{out_full_path}'" f' -nw={args.new_width} --nh={args.new_height} -v --if') else: cmd = osp.join( f"denseflow '{full_path}' -a={method} -b=20 -s=1 -o='{out_full_path}'" f' -ns={args.new_short} -v --if') else: if args.new_short == 0: cmd = osp.join( f"denseflow '{full_path}' -a={method} -b=20 -s=1 -o='{out_full_path}'" f' -nw={args.new_width} --nh={args.new_height} -v') else: cmd = osp.join( f"denseflow '{full_path}' -a={method} -b=20 -s=1 -o='{out_full_path}'" f' -ns={args.new_short} -v') os.system(cmd) else: if args.new_short == 0: cmd_rgb = osp.join( f"denseflow '{full_path}' -b=20 -s=0 -o='{out_full_path}'" f' -nw={args.new_width} -nh={args.new_height} -v') cmd_flow = osp.join( f"denseflow '{full_path}' -a={method} -b=20 -s=1 -o='{out_full_path}'" f' -nw={args.new_width} -nh={args.new_height} -v') else: cmd_rgb = osp.join( f"denseflow '{full_path}' -b=20 -s=0 -o='{out_full_path}'" f' -ns={args.new_short} -v') cmd_flow = osp.join( f"denseflow '{full_path}' -a={method} -b=20 -s=1 -o='{out_full_path}'" f' -ns={args.new_short} -v') os.system(cmd_rgb) os.system(cmd_flow) print(f'{task} {vid_id} {vid_path} {method} done') sys.stdout.flush() return True def parse_args(): parser = argparse.ArgumentParser(description='extract optical flows') parser.add_argument('src_dir', type=str, help='source video directory') parser.add_argument('out_dir', type=str, help='output rawframe directory') parser.add_argument( '--task', type=str, default='flow', choices=['rgb', 'flow', 'both'], help='which type of frames to be extracted') parser.add_argument( '--level', type=int, choices=[1, 2], default=2, help='directory level of data') parser.add_argument( '--num-worker', type=int, default=8, help='number of workers to build rawframes') parser.add_argument( '--flow-type', type=str, default=None, choices=[None, 'tvl1', 'warp_tvl1', 'farn', 'brox'], help='flow type to be generated') parser.add_argument( '--out-format', type=str, default='jpg', choices=['jpg', 'h5', 'png'], help='output format') parser.add_argument( '--ext', type=str, default='avi', choices=['avi', 'mp4', 'webm'], help='video file extensions') parser.add_argument( '--new-width', type=int, default=0, help='resize image width') parser.add_argument( '--new-height', type=int, default=0, help='resize image height') parser.add_argument( '--new-short', type=int, default=0, help='resize image short side length keeping ratio') parser.add_argument('--num-gpu', type=int, default=8, help='number of GPU') parser.add_argument( '--resume', action='store_true', default=False, help='resume optical flow extraction instead of overwriting') parser.add_argument( '--use-opencv', action='store_true', help='Whether to use opencv to extract rgb frames') parser.add_argument( '--input-frames', action='store_true', help='Whether to extract flow frames based on rgb frames') parser.add_argument( '--ref_listfile_path', type=str, default='', help='reference listfile path for the subset') args = parser.parse_args() return args def get_subset_classes(ref_listfile_path): df = pd.read_csv(ref_listfile_path, header=None, sep='*') cur_data = df.values subset_classes = [] for i,row in enumerate(cur_data): cur_cls = row[0].split('/')[1] cur_cls = cur_cls.replace(' ', '_').replace('(', '-').replace(')', '-') if cur_cls not in subset_classes: subset_classes.append(cur_cls) return subset_classes def filter_vid_list(vid_list, src_dir, ref_listfile_path): subset_classes = get_subset_classes(ref_listfile_path) filtered_vid_list = [] filtered_full_path_list = [] for vid,fpath in zip(vid_list,fullpath_list): cur_cls = vid.split('/')[0] if cur_cls in subset_classes: filtered_vid_list.append(vid) filtered_full_path_list.append(os.path.join(src_dir, vid)) return filtered_vid_list, filtered_full_path_list if __name__ == '__main__': args = parse_args() if not osp.isdir(args.out_dir): print(f'Creating folder: {args.out_dir}') os.makedirs(args.out_dir) if args.level == 2: if args.ref_listfile_path != '': classes = get_subset_classes(args.ref_listfile_path) else: classes = os.listdir(args.src_dir) for classname in classes: new_dir = osp.join(args.out_dir, classname) if not osp.isdir(new_dir): print(f'Creating folder: {new_dir}') os.makedirs(new_dir) if args.input_frames: print('Reading rgb frames from folder: ', args.src_dir) fullpath_list = glob.glob(args.src_dir + '/*' * args.level) done_fullpath_list = glob.glob(args.out_dir + '/*' * args.level) print('Total number of rgb frame folders found: ', len(fullpath_list)) else: print('Reading videos from folder: ', args.src_dir) print('Extension of videos: ', args.ext) fullpath_list = glob.glob(args.src_dir + '/*' * args.level + '.' + args.ext) done_fullpath_list = glob.glob(args.out_dir + '/*' * args.level) print('Total number of videos found: ', len(fullpath_list)) if args.resume: fullpath_list = set(fullpath_list).difference(set(done_fullpath_list)) fullpath_list = list(fullpath_list) print('Resuming. number of videos to be done: ', len(fullpath_list)) if args.level == 2: vid_list = list( map( lambda p: osp.join( osp.basename(osp.dirname(p)), osp.basename(p)), fullpath_list)) elif args.level == 1: vid_list, fullpath_list = list(map(lambda p: osp.basename(p), fullpath_list)) if args.ref_listfile_path != '': vid_list, fullpath_list = filter_vid_list(vid_list, args.src_dir, args.ref_listfile_path) pool = Pool(args.num_worker) pool.map( extract_frame, zip(fullpath_list, vid_list, range(len(vid_list)), len(vid_list) * [args.flow_type], len(vid_list) * [args.task]))

true

f704b08c47257333fbfca18d0f73801f0031cb66

1,991

py

Python

cliff/tests/test_formatters_value.py

serrollc/cliff

1dd3edafab1a34d194c4510310653ad7e2cbb582

[ "Apache-2.0" ]

null

cliff/tests/test_formatters_value.py

serrollc/cliff

1dd3edafab1a34d194c4510310653ad7e2cbb582

[ "Apache-2.0" ]

null

cliff/tests/test_formatters_value.py

serrollc/cliff

1dd3edafab1a34d194c4510310653ad7e2cbb582

[ "Apache-2.0" ]

null

#!/usr/bin/env python # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import six from cliff.formatters import value from cliff.tests import test_columns def test_value_formatter(): sf = value.ValueFormatter() c = ('a', 'b', 'c', 'd') d = ('A', 'B', 'C', '"no escape me"') expected = 'A\nB\nC\n"no escape me"\n' output = six.StringIO() sf.emit_one(c, d, output, None) actual = output.getvalue() assert expected == actual def test_value_formatter_formattable_column(): sf = value.ValueFormatter() c = ('a', 'b', 'c', 'd') d = ('A', 'B', 'C', test_columns.FauxColumn(['the', 'value'])) expected = "A\nB\nC\n['the', 'value']\n" output = six.StringIO() sf.emit_one(c, d, output, None) actual = output.getvalue() assert expected == actual def test_value_list_formatter(): sf = value.ValueFormatter() c = ('a', 'b', 'c') d1 = ('A', 'B', 'C') d2 = ('D', 'E', 'F') data = [d1, d2] expected = 'A B C\nD E F\n' output = six.StringIO() sf.emit_list(c, data, output, None) actual = output.getvalue() assert expected == actual def test_value_list_formatter_formattable_column(): sf = value.ValueFormatter() c = ('a', 'b', 'c') d1 = ('A', 'B', test_columns.FauxColumn(['the', 'value'])) data = [d1] expected = "A B ['the', 'value']\n" output = six.StringIO() sf.emit_list(c, data, output, None) actual = output.getvalue() assert expected == actual

30.166667

76

0.631341

import six from cliff.formatters import value from cliff.tests import test_columns def test_value_formatter(): sf = value.ValueFormatter() c = ('a', 'b', 'c', 'd') d = ('A', 'B', 'C', '"no escape me"') expected = 'A\nB\nC\n"no escape me"\n' output = six.StringIO() sf.emit_one(c, d, output, None) actual = output.getvalue() assert expected == actual def test_value_formatter_formattable_column(): sf = value.ValueFormatter() c = ('a', 'b', 'c', 'd') d = ('A', 'B', 'C', test_columns.FauxColumn(['the', 'value'])) expected = "A\nB\nC\n['the', 'value']\n" output = six.StringIO() sf.emit_one(c, d, output, None) actual = output.getvalue() assert expected == actual def test_value_list_formatter(): sf = value.ValueFormatter() c = ('a', 'b', 'c') d1 = ('A', 'B', 'C') d2 = ('D', 'E', 'F') data = [d1, d2] expected = 'A B C\nD E F\n' output = six.StringIO() sf.emit_list(c, data, output, None) actual = output.getvalue() assert expected == actual def test_value_list_formatter_formattable_column(): sf = value.ValueFormatter() c = ('a', 'b', 'c') d1 = ('A', 'B', test_columns.FauxColumn(['the', 'value'])) data = [d1] expected = "A B ['the', 'value']\n" output = six.StringIO() sf.emit_list(c, data, output, None) actual = output.getvalue() assert expected == actual

true

f704b1b6e255bd26c9802820bac5475dcc418066

6,716

py

Python

scraper/src/meilisearch_helper.py

myface-wang/docs-scraper

86fa2130000b6d00b6a9520d176d02ea470aec2d

[ "MIT" ]

null

scraper/src/meilisearch_helper.py

myface-wang/docs-scraper

86fa2130000b6d00b6a9520d176d02ea470aec2d

[ "MIT" ]

null

scraper/src/meilisearch_helper.py

myface-wang/docs-scraper

86fa2130000b6d00b6a9520d176d02ea470aec2d

[ "MIT" ]

null

"""MeiliSearchHelper Wrapper on top of the MeiliSearch API client""" import meilisearch from builtins import range def remove_bad_encoding(value): return value.replace(''', "'") def clean_one_field(value): if isinstance(value, bool): return str(value) elif isinstance(value, str): return remove_bad_encoding(value) return value def clean_dict(record): for key, value in record.items(): if isinstance(value, dict): record[key] = clean_dict(value) else: record[key] = clean_one_field(value) return record def parse_record(record): new_weight = {} for k, v in record['weight'].items(): new_weight[k] = v new_hierarchy = {} for k, v in record['hierarchy'].items(): new_hierarchy['hierarchy_' + k] = v new_hierarchy_radio = {} for k, v in record['hierarchy_radio'].items(): key = 'hierarchy_radio_' + k new_hierarchy_radio = {**{key: v}, **new_hierarchy_radio} del record['weight'] del record['hierarchy'] del record['hierarchy_radio'] del record['hierarchy_camel'] del record['hierarchy_radio_camel'] del record['content_camel'] return {**record, **new_weight, **new_hierarchy, **new_hierarchy_radio} class MeiliSearchHelper: """MeiliSearchHelper""" # Cf the end of this file to understand these settings SETTINGS = { 'rankingRules': [ 'words', 'typo', 'attribute', 'proximity', 'exactness', 'desc(page_rank)', 'desc(level)', 'asc(position)' ], 'distinctAttribute': 'url', 'searchableAttributes': [ 'hierarchy_radio_lvl0', 'hierarchy_radio_lvl1', 'hierarchy_radio_lvl2', 'hierarchy_radio_lvl3', 'hierarchy_radio_lvl4', 'hierarchy_radio_lvl5', 'hierarchy_lvl0', 'hierarchy_lvl1', 'hierarchy_lvl2', 'hierarchy_lvl3', 'hierarchy_lvl4', 'hierarchy_lvl5', 'hierarchy_lvl6', 'content', 'objectID', 'page_rank', 'level', 'position' ], 'displayedAttributes': [ 'hierarchy_radio_lvl0', 'hierarchy_radio_lvl1', 'hierarchy_radio_lvl2', 'hierarchy_radio_lvl3', 'hierarchy_radio_lvl4', 'hierarchy_radio_lvl5', 'hierarchy_lvl0', 'hierarchy_lvl1', 'hierarchy_lvl2', 'hierarchy_lvl3', 'hierarchy_lvl4', 'hierarchy_lvl5', 'hierarchy_lvl6', 'anchor', 'url', 'content', 'objectID' ] } def __init__(self, host_url, api_key, index_uid, custom_settings): self.meilisearch_client = meilisearch.Client(host_url, api_key) self.meilisearch_index = self.__delete_and_create_index(index_uid) self.add_settings(MeiliSearchHelper.SETTINGS, custom_settings) def add_settings(self, default_settings, custom_settings): settings = {**default_settings, **custom_settings} self.meilisearch_index.update_settings(settings) def add_records(self, records, url, from_sitemap): """Add new records to the index""" record_count = len(records) for i in range(0, record_count, 50): parsed_records = list(map(parse_record, records[i:i + 50])) cleaned_records = list(map(clean_dict, parsed_records)) self.meilisearch_index.add_documents(cleaned_records) color = "96" if from_sitemap else "94" print( '\033[{}m> Docs-Scraper: \033[0m{}\033[93m {} records\033[0m)'.format( color, url, record_count)) def __delete_and_create_index(self, index_uid): try: self.meilisearch_client.get_index(index_uid).delete() except Exception: print("The index " + index_uid + " does not exist. Creating...") return self.meilisearch_client.create_index(index_uid, {'primaryKey': 'objectID'}) # Algolia's settings: # {"minWordSizefor1Typo"=>3, # "minWordSizefor2Typos"=>7, # "hitsPerPage"=>20, # "maxValuesPerFacet"=>100, # "minProximity"=>1, # "version"=>2, # "attributesToIndex"=> # ["unordered(hierarchy_radio_camel.lvl0)", # "unordered(hierarchy_radio.lvl0)", # "unordered(hierarchy_radio_camel.lvl1)", # "unordered(hierarchy_radio.lvl1)", # "unordered(hierarchy_radio_camel.lvl2)", # "unordered(hierarchy_radio.lvl2)", # "unordered(hierarchy_radio_camel.lvl3)", # "unordered(hierarchy_radio.lvl3)", # "unordered(hierarchy_radio_camel.lvl4)", # "unordered(hierarchy_radio.lvl4)", # "unordered(hierarchy_radio_camel.lvl5)", # "unordered(hierarchy_radio.lvl5)", # "unordered(hierarchy_camel.lvl0)", # "unordered(hierarchy.lvl0)", # "unordered(hierarchy_camel.lvl1)", # "unordered(hierarchy.lvl1)", # "unordered(hierarchy_camel.lvl2)", # "unordered(hierarchy.lvl2)", # "unordered(hierarchy_camel.lvl3)", # "unordered(hierarchy.lvl3)", # "unordered(hierarchy_camel.lvl4)", # "unordered(hierarchy.lvl4)", # "unordered(hierarchy_camel.lvl5)", # "unordered(hierarchy.lvl5)", # "content"], # "numericAttributesToIndex"=>nil, # "attributesToRetrieve"=>["hierarchy", "content", "anchor", "url"], # "allowTyposOnNumericTokens"=>false, # "ignorePlurals"=>true, # "camelCaseAttributes"=>["hierarchy", "hierarchy_radio", "content"], # "advancedSyntax"=>true, # "attributeCriteriaComputedByMinProximity"=>true, # "distinct"=>true, # "unretrievableAttributes"=>nil, # "optionalWords"=>nil, # "userData"=>{"crawling_issue"=>false}, # "attributesForFaceting"=>["lang"], # "attributesToSnippet"=>["content:10"], # "attributesToHighlight"=>["hierarchy", "hierarchy_camel", "content"], # "paginationLimitedTo"=>1000, # "attributeForDistinct"=>"url", # "exactOnSingleWordQuery"=>"attribute", # "ranking"=> # ["words", "filters", "typo", "attribute", "proximity", "exact", "custom"], # "customRanking"=> # ["desc(weight.page_rank)", "desc(weight.level)", "asc(weight.position)"], # "separatorsToIndex"=>"", # "removeWordsIfNoResults"=>"allOptional", # "queryType"=>"prefixLast", # "highlightPreTag"=>"", # "highlightPostTag"=>"", # "snippetEllipsisText"=>"", # "alternativesAsExact"=>["ignorePlurals", "singleWordSynonym"]}

34.618557

90

0.611078

import meilisearch from builtins import range def remove_bad_encoding(value): return value.replace(''', "'") def clean_one_field(value): if isinstance(value, bool): return str(value) elif isinstance(value, str): return remove_bad_encoding(value) return value def clean_dict(record): for key, value in record.items(): if isinstance(value, dict): record[key] = clean_dict(value) else: record[key] = clean_one_field(value) return record def parse_record(record): new_weight = {} for k, v in record['weight'].items(): new_weight[k] = v new_hierarchy = {} for k, v in record['hierarchy'].items(): new_hierarchy['hierarchy_' + k] = v new_hierarchy_radio = {} for k, v in record['hierarchy_radio'].items(): key = 'hierarchy_radio_' + k new_hierarchy_radio = {**{key: v}, **new_hierarchy_radio} del record['weight'] del record['hierarchy'] del record['hierarchy_radio'] del record['hierarchy_camel'] del record['hierarchy_radio_camel'] del record['content_camel'] return {**record, **new_weight, **new_hierarchy, **new_hierarchy_radio} class MeiliSearchHelper: # Cf the end of this file to understand these settings SETTINGS = { 'rankingRules': [ 'words', 'typo', 'attribute', 'proximity', 'exactness', 'desc(page_rank)', 'desc(level)', 'asc(position)' ], 'distinctAttribute': 'url', 'searchableAttributes': [ 'hierarchy_radio_lvl0', 'hierarchy_radio_lvl1', 'hierarchy_radio_lvl2', 'hierarchy_radio_lvl3', 'hierarchy_radio_lvl4', 'hierarchy_radio_lvl5', 'hierarchy_lvl0', 'hierarchy_lvl1', 'hierarchy_lvl2', 'hierarchy_lvl3', 'hierarchy_lvl4', 'hierarchy_lvl5', 'hierarchy_lvl6', 'content', 'objectID', 'page_rank', 'level', 'position' ], 'displayedAttributes': [ 'hierarchy_radio_lvl0', 'hierarchy_radio_lvl1', 'hierarchy_radio_lvl2', 'hierarchy_radio_lvl3', 'hierarchy_radio_lvl4', 'hierarchy_radio_lvl5', 'hierarchy_lvl0', 'hierarchy_lvl1', 'hierarchy_lvl2', 'hierarchy_lvl3', 'hierarchy_lvl4', 'hierarchy_lvl5', 'hierarchy_lvl6', 'anchor', 'url', 'content', 'objectID' ] } def __init__(self, host_url, api_key, index_uid, custom_settings): self.meilisearch_client = meilisearch.Client(host_url, api_key) self.meilisearch_index = self.__delete_and_create_index(index_uid) self.add_settings(MeiliSearchHelper.SETTINGS, custom_settings) def add_settings(self, default_settings, custom_settings): settings = {**default_settings, **custom_settings} self.meilisearch_index.update_settings(settings) def add_records(self, records, url, from_sitemap): record_count = len(records) for i in range(0, record_count, 50): parsed_records = list(map(parse_record, records[i:i + 50])) cleaned_records = list(map(clean_dict, parsed_records)) self.meilisearch_index.add_documents(cleaned_records) color = "96" if from_sitemap else "94" print( '\033[{}m> Docs-Scraper: \033[0m{}\033[93m {} records\033[0m)'.format( color, url, record_count)) def __delete_and_create_index(self, index_uid): try: self.meilisearch_client.get_index(index_uid).delete() except Exception: print("The index " + index_uid + " does not exist. Creating...") return self.meilisearch_client.create_index(index_uid, {'primaryKey': 'objectID'}) # Algolia's settings:

true

f704b1f07f7a454874c406e6aa73fc6f56056467

1,848

py

Python

moray/_browser/chrome.py

hirorich/moray

69421ce739960c10c343ff1d72e1337594ea5c30

[ "MIT" ]

null

moray/_browser/chrome.py

hirorich/moray

69421ce739960c10c343ff1d72e1337594ea5c30

[ "MIT" ]

null

moray/_browser/chrome.py

hirorich/moray

69421ce739960c10c343ff1d72e1337594ea5c30

[ "MIT" ]

null

""" chromeをアプリモードで起動するためのコマンドを生成する """ import sys, os from moray.exception import SupportError name = 'chrome' def create_command(path, url, cmdline_args): """ 起動コマンド生成 Attributes: path (str): chromeコマンドのパス url (str): 接続先のURL cmdline_args (list<str>): コマンドライン引数 Returns: list<str>: 生成された起動コマンド """ return [path, '--app=' + url] + cmdline_args def find_path(): """ chromeの実行ファイルパスを取得 Returns: str: chromeの実行ファイルパス Raises: SupportError: 対象外OSの場合 """ if sys.platform in ('win32', 'win64'): # Windowsの場合 return _find_chrome_windows() else: # 対象外OSの場合 # このOSはサポート対象外のOSです。 error_msg = 'This OS is not a supported OS.' raise SupportError(error_msg) def _find_chrome_windows(): """ Windowsのchromeの実行ファイルパスを取得 Returns: str: Windowsのchromeの実行ファイルパス Raises: FileNotFoundError: ブラウザ実行ファイル不明 """ import winreg reg_path = r'SOFTWARE\Microsoft\Windows\CurrentVersion\App Paths\chrome.exe' # HKEY_CURRENT_USER: 現在のユーザーのレジストリ設定 # HKEY_LOCAL_MACHINE: すべてのユーザーのレジストリ設定 for reg_entry in winreg.HKEY_CURRENT_USER, winreg.HKEY_LOCAL_MACHINE: try: # レジストリからchromeの実行ファイルパスを取得 with winreg.OpenKey(reg_entry, reg_path, 0, winreg.KEY_READ) as reg_key: chrome_path = winreg.QueryValueEx(reg_key, None)[0] if os.path.isfile(chrome_path): return chrome_path except Exception as e: pass # chrome.exe が見つかりませんでした error_msg = '"chrome.exe" is not found.' raise FileNotFoundError(error_msg)

23.692308

85

0.581169

import sys, os from moray.exception import SupportError name = 'chrome' def create_command(path, url, cmdline_args): return [path, '--app=' + url] + cmdline_args def find_path(): if sys.platform in ('win32', 'win64'): return _find_chrome_windows() else: error_msg = 'This OS is not a supported OS.' raise SupportError(error_msg) def _find_chrome_windows(): import winreg reg_path = r'SOFTWARE\Microsoft\Windows\CurrentVersion\App Paths\chrome.exe' for reg_entry in winreg.HKEY_CURRENT_USER, winreg.HKEY_LOCAL_MACHINE: try: with winreg.OpenKey(reg_entry, reg_path, 0, winreg.KEY_READ) as reg_key: chrome_path = winreg.QueryValueEx(reg_key, None)[0] if os.path.isfile(chrome_path): return chrome_path except Exception as e: pass error_msg = '"chrome.exe" is not found.' raise FileNotFoundError(error_msg)

true

f704b28f204b556b3ce64a8a530557cbeb92babb

1,407

py

Python

itspylearning/itslearning.py

HubertJan/itspylearning

6110f87c78dfc5b78e8d52c0b05e2c376749bce3

[ "MIT" ]

null

itspylearning/itslearning.py

HubertJan/itspylearning

6110f87c78dfc5b78e8d52c0b05e2c376749bce3

[ "MIT" ]

1

2021-12-16T15:52:34.000Z

2022-01-03T17:17:09.000Z

itspylearning/itslearning.py

HubertJan/itspylearning

6110f87c78dfc5b78e8d52c0b05e2c376749bce3

[ "MIT" ]

1

2021-11-30T16:26:08.000Z

from typing import List, Optional import aiohttp import json from aiohttp.client import ClientSession from itspylearning.consts import ITSLEARNING_URL from itspylearning.organisation import Organisation _clientSession: Optional[ClientSession] = None def _getClient() -> aiohttp.ClientSession: global _clientSession if(_clientSession is None): _clientSession = aiohttp.ClientSession() return _clientSession async def search_organisations(query) -> List[dict]: response = await _getClient().get(f"{ITSLEARNING_URL}/restapi/sites/all/organisations/search/v1/?searchText={query}") rawData = await response.text() data = json.loads(rawData) matches = [] for match in data["EntityArray"]: matches.append({"id": match["CustomerId"], "name": match["SiteName"],}) await close_session() return matches async def fetch_organisation( id) -> Organisation: response = await _getClient().get(f"{ITSLEARNING_URL}/restapi/sites/{id}/v1") if response.status != 200: raise Exception('Request failure.') rawData = await response.text() data = json.loads(rawData) if data == None: raise Exception("Organisation did not exist.") organisation = Organisation(data) await close_session() return organisation async def close_session(): global _clientSession await _clientSession.close() _clientSession = None

31.977273

121

0.722814

from typing import List, Optional import aiohttp import json from aiohttp.client import ClientSession from itspylearning.consts import ITSLEARNING_URL from itspylearning.organisation import Organisation _clientSession: Optional[ClientSession] = None def _getClient() -> aiohttp.ClientSession: global _clientSession if(_clientSession is None): _clientSession = aiohttp.ClientSession() return _clientSession async def search_organisations(query) -> List[dict]: response = await _getClient().get(f"{ITSLEARNING_URL}/restapi/sites/all/organisations/search/v1/?searchText={query}") rawData = await response.text() data = json.loads(rawData) matches = [] for match in data["EntityArray"]: matches.append({"id": match["CustomerId"], "name": match["SiteName"],}) await close_session() return matches async def fetch_organisation( id) -> Organisation: response = await _getClient().get(f"{ITSLEARNING_URL}/restapi/sites/{id}/v1") if response.status != 200: raise Exception('Request failure.') rawData = await response.text() data = json.loads(rawData) if data == None: raise Exception("Organisation did not exist.") organisation = Organisation(data) await close_session() return organisation async def close_session(): global _clientSession await _clientSession.close() _clientSession = None

true

f704b2a011d6048694d79069a8471cef3118250c

2,356

py

Python

backend/app/tests/api/node_directive/test_create.py

hollyfoxx/ace2-gui

e0f72cafdd524e0cd66549a9315697aa21ae46fa

[ "Apache-2.0" ]

1

2021-07-16T10:34:22.000Z

backend/app/tests/api/node_directive/test_create.py

hollyfoxx/ace2-gui

e0f72cafdd524e0cd66549a9315697aa21ae46fa

[ "Apache-2.0" ]

null

backend/app/tests/api/node_directive/test_create.py

hollyfoxx/ace2-gui

e0f72cafdd524e0cd66549a9315697aa21ae46fa

[ "Apache-2.0" ]

null

import pytest import uuid from fastapi import status # # INVALID TESTS # @pytest.mark.parametrize( "key,value", [ ("description", 123), ("description", ""), ("uuid", None), ("uuid", 1), ("uuid", "abc"), ("uuid", ""), ("value", 123), ("value", None), ("value", ""), ], ) def test_create_invalid_fields(client, key, value): create_json = {"value": "test"} create_json[key] = value create = client.post("/api/node/directive/", json=create_json) assert create.status_code == status.HTTP_422_UNPROCESSABLE_ENTITY @pytest.mark.parametrize( "key", [ ("uuid"), ("value"), ], ) def test_create_duplicate_unique_fields(client, key): # Create an object create1_json = {"uuid": str(uuid.uuid4()), "value": "test"} client.post("/api/node/directive/", json=create1_json) # Ensure you cannot create another object with the same unique field value create2_json = {"value": "test2"} create2_json[key] = create1_json[key] create2 = client.post("/api/node/directive/", json=create2_json) assert create2.status_code == status.HTTP_409_CONFLICT @pytest.mark.parametrize( "key", [ ("value"), ], ) def test_create_missing_required_fields(client, key): create_json = {"value": "test"} del create_json[key] create = client.post("/api/node/directive/", json=create_json) assert create.status_code == status.HTTP_422_UNPROCESSABLE_ENTITY # # VALID TESTS # @pytest.mark.parametrize( "key,value", [ ("description", None), ("description", "test"), ("uuid", str(uuid.uuid4())) ], ) def test_create_valid_optional_fields(client, key, value): # Create the object create = client.post("/api/node/directive/", json={key: value, "value": "test"}) assert create.status_code == status.HTTP_201_CREATED # Read it back get = client.get(create.headers["Content-Location"]) assert get.json()[key] == value def test_create_valid_required_fields(client): # Create the object create = client.post("/api/node/directive/", json={"value": "test"}) assert create.status_code == status.HTTP_201_CREATED # Read it back get = client.get(create.headers["Content-Location"]) assert get.json()["value"] == "test"

24.541667

84

0.629032

import pytest import uuid from fastapi import status @pytest.mark.parametrize( "key,value", [ ("description", 123), ("description", ""), ("uuid", None), ("uuid", 1), ("uuid", "abc"), ("uuid", ""), ("value", 123), ("value", None), ("value", ""), ], ) def test_create_invalid_fields(client, key, value): create_json = {"value": "test"} create_json[key] = value create = client.post("/api/node/directive/", json=create_json) assert create.status_code == status.HTTP_422_UNPROCESSABLE_ENTITY @pytest.mark.parametrize( "key", [ ("uuid"), ("value"), ], ) def test_create_duplicate_unique_fields(client, key): create1_json = {"uuid": str(uuid.uuid4()), "value": "test"} client.post("/api/node/directive/", json=create1_json) create2_json = {"value": "test2"} create2_json[key] = create1_json[key] create2 = client.post("/api/node/directive/", json=create2_json) assert create2.status_code == status.HTTP_409_CONFLICT @pytest.mark.parametrize( "key", [ ("value"), ], ) def test_create_missing_required_fields(client, key): create_json = {"value": "test"} del create_json[key] create = client.post("/api/node/directive/", json=create_json) assert create.status_code == status.HTTP_422_UNPROCESSABLE_ENTITY @pytest.mark.parametrize( "key,value", [ ("description", None), ("description", "test"), ("uuid", str(uuid.uuid4())) ], ) def test_create_valid_optional_fields(client, key, value): create = client.post("/api/node/directive/", json={key: value, "value": "test"}) assert create.status_code == status.HTTP_201_CREATED get = client.get(create.headers["Content-Location"]) assert get.json()[key] == value def test_create_valid_required_fields(client): create = client.post("/api/node/directive/", json={"value": "test"}) assert create.status_code == status.HTTP_201_CREATED get = client.get(create.headers["Content-Location"]) assert get.json()["value"] == "test"

true

f704b2ba2399a4abbde2614f88886205e3ef96db

1,398

py

Python

Transition.py

gerth2/FSMMaker

933db1fb2bd4b88a62590c07a58842983b625d43

[ "MIT" ]

null

Transition.py

gerth2/FSMMaker

933db1fb2bd4b88a62590c07a58842983b625d43

[ "MIT" ]

null

Transition.py

gerth2/FSMMaker

933db1fb2bd4b88a62590c07a58842983b625d43

[ "MIT" ]

null

from Comparison import Comparison from Action import Action from TransitionCodegen import TransitionCodegen from TransitionGraphic import TransitionGraphic import xml.etree.ElementTree as ET class Transition: def __init__(self, id): self.id = id self.fromStateID = None self.toStateID = None self.condition = None self.priority = 0 self.cg = TransitionCodegen(self) self.graphic = TransitionGraphic(self) self.actions = [] def parseCfg(self, etreeNode): for child in etreeNode: if(child.tag == "from"): self.fromStateID = int(child.text) elif(child.tag == "to"): self.toStateID = int(child.text) elif(child.tag == "action"): newAction = Action() newAction.parseCfg(child) self.actions.append(newAction) elif(child.tag == "condition"): self.condition = Comparison() self.condition.parseCfg(child) elif(child.tag == "priority"): self.priority = int(child.text) elif(child.tag == "graphic"): self.graphic.parseCfg(child) def dumpCfg(self): return ET.Element() #TODO: generate XML representation of current object

31.772727

81

0.557225

from Comparison import Comparison from Action import Action from TransitionCodegen import TransitionCodegen from TransitionGraphic import TransitionGraphic import xml.etree.ElementTree as ET class Transition: def __init__(self, id): self.id = id self.fromStateID = None self.toStateID = None self.condition = None self.priority = 0 self.cg = TransitionCodegen(self) self.graphic = TransitionGraphic(self) self.actions = [] def parseCfg(self, etreeNode): for child in etreeNode: if(child.tag == "from"): self.fromStateID = int(child.text) elif(child.tag == "to"): self.toStateID = int(child.text) elif(child.tag == "action"): newAction = Action() newAction.parseCfg(child) self.actions.append(newAction) elif(child.tag == "condition"): self.condition = Comparison() self.condition.parseCfg(child) elif(child.tag == "priority"): self.priority = int(child.text) elif(child.tag == "graphic"): self.graphic.parseCfg(child) def dumpCfg(self): return ET.Element()

true

f704b2e0ef291ebe1fc31f07298db6d46894ad1c

366

py

Python

build/kinova-ros/kinova_bringup/catkin_generated/pkg.installspace.context.pc.py

Jam-cpu/Masters-Project---Final

0b266b1f117a579b96507249f0a128d0e3cc082a

[ "BSD-3-Clause-Clear" ]

null

build/kinova-ros/kinova_bringup/catkin_generated/pkg.installspace.context.pc.py

Jam-cpu/Masters-Project---Final

0b266b1f117a579b96507249f0a128d0e3cc082a

[ "BSD-3-Clause-Clear" ]

null

build/kinova-ros/kinova_bringup/catkin_generated/pkg.installspace.context.pc.py

Jam-cpu/Masters-Project---Final

0b266b1f117a579b96507249f0a128d0e3cc082a

[ "BSD-3-Clause-Clear" ]

null

# generated from catkin/cmake/template/pkg.context.pc.in CATKIN_PACKAGE_PREFIX = "" PROJECT_PKG_CONFIG_INCLUDE_DIRS = "".split(';') if "" != "" else [] PROJECT_CATKIN_DEPENDS = "".replace(';', ' ') PKG_CONFIG_LIBRARIES_WITH_PREFIX = "".split(';') if "" != "" else [] PROJECT_NAME = "kinova_bringup" PROJECT_SPACE_DIR = "/workspace/install" PROJECT_VERSION = "0.0.0"

40.666667

68

0.704918

CATKIN_PACKAGE_PREFIX = "" PROJECT_PKG_CONFIG_INCLUDE_DIRS = "".split(';') if "" != "" else [] PROJECT_CATKIN_DEPENDS = "".replace(';', ' ') PKG_CONFIG_LIBRARIES_WITH_PREFIX = "".split(';') if "" != "" else [] PROJECT_NAME = "kinova_bringup" PROJECT_SPACE_DIR = "/workspace/install" PROJECT_VERSION = "0.0.0"

true

f704b34c87ed8874507207d4c03838d31c80bd03

113

py

Python

pfdo_med2image/__init__.py

FNNDSC/pfdo_med2image

f65412aea362d0db5b8e7e2257b1d8fc1e696494

[ "Apache-2.0" ]

null

pfdo_med2image/__init__.py

FNNDSC/pfdo_med2image

f65412aea362d0db5b8e7e2257b1d8fc1e696494

[ "Apache-2.0" ]

2

2020-08-18T21:47:22.000Z

2021-03-12T14:45:35.000Z

pfdo_med2image/__init__.py

FNNDSC/pfdo_med2image

f65412aea362d0db5b8e7e2257b1d8fc1e696494

[ "Apache-2.0" ]

1

2020-11-12T21:40:01.000Z

try: from .pfdo_med2image import pfdo_med2image except: from pfdo_med2image import pfdo_med2image

22.6

49

0.752212

try: from .pfdo_med2image import pfdo_med2image except: from pfdo_med2image import pfdo_med2image

true

f704b3d19693548dbf7626d9ff72c05289e02e97

226

bzl

Python

BUILD.bzl

mobileink/coda

0612b142738c68155e9a9bba16cd3787bba4feed

[ "Apache-2.0" ]

null

BUILD.bzl

mobileink/coda

0612b142738c68155e9a9bba16cd3787bba4feed

[ "Apache-2.0" ]

1

2021-03-06T14:52:32.000Z

BUILD.bzl

mobileink/coda

0612b142738c68155e9a9bba16cd3787bba4feed

[ "Apache-2.0" ]

null

# CONFIG_MLH = ["//mina/config"] CONFIG_MLH = select({ "//:profile_debug": ["//src/config/debug"], "//:profile_dev": ["//src:dev"], "//:profile_release": ["//src:release"], }, no_match_error = "Unknown profile")

25.111111

47

0.588496

CONFIG_MLH = select({ "//:profile_debug": ["//src/config/debug"], "//:profile_dev": ["//src:dev"], "//:profile_release": ["//src:release"], }, no_match_error = "Unknown profile")

true

f704b5b6daab1e1692d607b7bf7753465d5a41cd

2,445

py

Python

test/test_gbtile.py

flozz/img2gb

2564a718d0b377d1b524204d97a674aedeec770d

[ "BSD-3-Clause" ]

23

2018-11-14T12:50:31.000Z

2022-03-30T17:28:43.000Z

test/test_gbtile.py

flozz/img2gb

2564a718d0b377d1b524204d97a674aedeec770d

[ "BSD-3-Clause" ]

10

2019-07-01T17:24:47.000Z

2022-01-13T12:38:38.000Z

test/test_gbtile.py

flozz/img2gb

2564a718d0b377d1b524204d97a674aedeec770d

[ "BSD-3-Clause" ]

3

2019-10-16T23:27:28.000Z

2022-01-23T22:28:29.000Z

import pytest from PIL import Image from img2gb.gbtile import GBTile class Test_GBTile(object): @pytest.fixture def image(self): return Image.open("./test/assets/tileset.png") @pytest.mark.parametrize("x,result", [ (0, "00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00"), (8, "FF 01 81 7F BD 7F A5 7B A5 7B BD 63 81 7F FF FF"), (16, "7E 00 81 7F 81 7F 81 7F 81 7F 81 7F 81 7F 7E 7E"), (24, "3C 00 54 2A A3 5F C1 3F 83 7F C5 3F 2A 7E 3C 3C"), (32, "04 04 04 04 0A 0A 12 12 66 00 99 77 99 77 66 66"), ]) def test_from_image(self, image, x, result): tile = GBTile.from_image(image, x) assert tile.to_hex_string() == result def test_put_pixel(self): tile = GBTile() for b in tile.data: assert b == 0 tile.put_pixel(0, 0, 3) assert tile.data[0] == 0x80 assert tile.data[1] == 0x80 tile.put_pixel(4, 0, 2) assert tile.data[0] == 0x80 assert tile.data[1] == 0x88 def test_get_pixel(self, image): tile = GBTile.from_image(image, 32) assert tile.get_pixel(0, 0) == 0b00 assert tile.get_pixel(0, 6) == 0b01 assert tile.get_pixel(2, 6) == 0b10 assert tile.get_pixel(5, 0) == 0b11 def test_to_hex_string(self): tile = GBTile() assert tile.to_hex_string() == "00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00" # noqa tile.put_pixel(0, 0, 3) tile.put_pixel(1, 0, 3) assert tile.to_hex_string() == "C0 C0 00 00 00 00 00 00 00 00 00 00 00 00 00 00" # noqa def test_to_image(self, image): tile = GBTile.from_image(image, 32) tile_image = tile.to_image() assert tile_image.getpixel((0, 0)) == 0b00 assert tile_image.getpixel((0, 6)) == 0b01 assert tile_image.getpixel((2, 6)) == 0b10 assert tile_image.getpixel((5, 0)) == 0b11 def test_gbtile_equality(self): tile1 = GBTile() tile2 = GBTile() assert tile1 == tile2 tile1.put_pixel(0, 0, 3) assert tile1 != tile2 tile2.put_pixel(0, 0, 3) assert tile1 == tile2 def test_data(self): tile = GBTile() assert len(tile.data) == 16 assert tile.data[0] == 0x00 assert tile.data[1] == 0x00 tile.put_pixel(0, 0, 3) assert tile.data[0] == 0x80 assert tile.data[1] == 0x80

28.430233

96

0.566871

import pytest from PIL import Image from img2gb.gbtile import GBTile class Test_GBTile(object): @pytest.fixture def image(self): return Image.open("./test/assets/tileset.png") @pytest.mark.parametrize("x,result", [ (0, "00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00"), (8, "FF 01 81 7F BD 7F A5 7B A5 7B BD 63 81 7F FF FF"), (16, "7E 00 81 7F 81 7F 81 7F 81 7F 81 7F 81 7F 7E 7E"), (24, "3C 00 54 2A A3 5F C1 3F 83 7F C5 3F 2A 7E 3C 3C"), (32, "04 04 04 04 0A 0A 12 12 66 00 99 77 99 77 66 66"), ]) def test_from_image(self, image, x, result): tile = GBTile.from_image(image, x) assert tile.to_hex_string() == result def test_put_pixel(self): tile = GBTile() for b in tile.data: assert b == 0 tile.put_pixel(0, 0, 3) assert tile.data[0] == 0x80 assert tile.data[1] == 0x80 tile.put_pixel(4, 0, 2) assert tile.data[0] == 0x80 assert tile.data[1] == 0x88 def test_get_pixel(self, image): tile = GBTile.from_image(image, 32) assert tile.get_pixel(0, 0) == 0b00 assert tile.get_pixel(0, 6) == 0b01 assert tile.get_pixel(2, 6) == 0b10 assert tile.get_pixel(5, 0) == 0b11 def test_to_hex_string(self): tile = GBTile() assert tile.to_hex_string() == "00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00" tile.put_pixel(0, 0, 3) tile.put_pixel(1, 0, 3) assert tile.to_hex_string() == "C0 C0 00 00 00 00 00 00 00 00 00 00 00 00 00 00" def test_to_image(self, image): tile = GBTile.from_image(image, 32) tile_image = tile.to_image() assert tile_image.getpixel((0, 0)) == 0b00 assert tile_image.getpixel((0, 6)) == 0b01 assert tile_image.getpixel((2, 6)) == 0b10 assert tile_image.getpixel((5, 0)) == 0b11 def test_gbtile_equality(self): tile1 = GBTile() tile2 = GBTile() assert tile1 == tile2 tile1.put_pixel(0, 0, 3) assert tile1 != tile2 tile2.put_pixel(0, 0, 3) assert tile1 == tile2 def test_data(self): tile = GBTile() assert len(tile.data) == 16 assert tile.data[0] == 0x00 assert tile.data[1] == 0x00 tile.put_pixel(0, 0, 3) assert tile.data[0] == 0x80 assert tile.data[1] == 0x80

true

f704b74596dc89d75957ad11f92f138e450dc2bd

2,050

py

Python

mathics/profile.py

jake100/Mathics

f90f9107e12072dcfbd76549b61897bc8feb04a8

[ "Apache-2.0" ]

1

2019-04-15T13:18:05.000Z

mathics/profile.py

jake100/Mathics

f90f9107e12072dcfbd76549b61897bc8feb04a8

[ "Apache-2.0" ]

null

mathics/profile.py

jake100/Mathics

f90f9107e12072dcfbd76549b61897bc8feb04a8

[ "Apache-2.0" ]

null

# -*- coding: utf8 -*- u""" Mathics: a general-purpose computer algebra system Copyright (C) 2011-2013 The Mathics Team This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see <http://www.gnu.org/licenses/>. """ import cProfile import pstats from mathics.core.definitions import Definitions from mathics.core.evaluation import Evaluation definitions = Definitions(add_builtin=True) def prepare(): pass result = None def run(): global result # prompt = '(1+a)(1+b)(1+c)(1+d)(1+e)//Expand' # prompt = 'f/@Range[20000];' # prompt = 'Plus @@ Range[50000]' # prompt = 'Range[100000];' try: # prompt = 'SetAttributes[v, Flat]; v[x_]:={x}; v[a,b]' # prompt = """(Plus@@Symbol/@CharacterRange["a","z"])^2//Expand;""" # prompt = ( # 'Plus@@f/@Symbol/@StringJoin/@Tuples[CharacterRange["a","z"],2]') # prompt = 'FullForm[Nest[1+Sqrt[1+#]&, x, 20]]' # prompt = '1+2' prompt = 'DensityPlot[x*y,{x,-1,1},{y,-1,1}]' evaluation = Evaluation(prompt, definitions, format='xml') if evaluation.results: result = evaluation.results[0].result except KeyboardInterrupt: result = 'INTERRUPTED' def _profile(): global result prepare() cProfile.run('run()', 'profile') # print 'Result: %s\n' % result p = pstats.Stats('profile') p.sort_stats('cumulative').print_stats(50) p.print_callees(20) if __name__ == '__main__': _profile()

30.147059

79

0.643902

import cProfile import pstats from mathics.core.definitions import Definitions from mathics.core.evaluation import Evaluation definitions = Definitions(add_builtin=True) def prepare(): pass result = None def run(): global result try: prompt = 'DensityPlot[x*y,{x,-1,1},{y,-1,1}]' evaluation = Evaluation(prompt, definitions, format='xml') if evaluation.results: result = evaluation.results[0].result except KeyboardInterrupt: result = 'INTERRUPTED' def _profile(): global result prepare() cProfile.run('run()', 'profile') p = pstats.Stats('profile') p.sort_stats('cumulative').print_stats(50) p.print_callees(20) if __name__ == '__main__': _profile()

true

f704b79922c2bcb710beb9717a76fb07b5ab4af6

390

py

Python

beagle/transformers/__init__.py

truongdo619/beagle

55a5d30a381438ae66b6c1c57f57b2403621db87

[ "MIT" ]

1

2019-10-01T19:26:16.000Z

beagle/transformers/__init__.py

truongdo619/beagle

55a5d30a381438ae66b6c1c57f57b2403621db87

[ "MIT" ]

null

beagle/transformers/__init__.py

truongdo619/beagle

55a5d30a381438ae66b6c1c57f57b2403621db87

[ "MIT" ]

1

2019-10-04T15:30:08.000Z

from __future__ import absolute_import from .base_transformer import Transformer # noqa from .fireeye_hx_transformer import FireEyeHXTransformer # noqa from .generic_transformer import GenericTransformer # noqa from .sysmon_transformer import SysmonTransformer # noqa from .evtx_transformer import WinEVTXTransformer # noqa from .procmon_transformer import ProcmonTransformer # noqa

43.333333

64

0.848718

from __future__ import absolute_import from .base_transformer import Transformer from .fireeye_hx_transformer import FireEyeHXTransformer from .generic_transformer import GenericTransformer from .sysmon_transformer import SysmonTransformer from .evtx_transformer import WinEVTXTransformer from .procmon_transformer import ProcmonTransformer

true

f704b7dccf154ecda012dac0c1c0edf8a17dd5c2

804

py

Python

setup.py

jsleb333/py2tex

737292bc53115310a7e495a3781c84a3fe53b57e

[ "MIT" ]

3

2019-02-11T19:14:08.000Z

2019-02-11T22:47:15.000Z

setup.py

jsleb333/py2tex

737292bc53115310a7e495a3781c84a3fe53b57e

[ "MIT" ]

null

setup.py

jsleb333/py2tex

737292bc53115310a7e495a3781c84a3fe53b57e

[ "MIT" ]

null

import setuptools from version import __version__ with open("README.md", "r") as fh: long_description = fh.read() setuptools.setup( name="python2latex", version=__version__, author="Jean-Samuel Leboeuf", author_email="jean-samuel.leboeuf.1@ulaval.ca", description="A Python to LaTeX converter", long_description=long_description, long_description_content_type="text/markdown", url="https://github.com/jsleb333/python2latex", packages=setuptools.find_packages(), install_requires=['numpy', 'colorspacious', 'matplotlib'], classifiers=[ "Programming Language :: Python :: 3", "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", ], python_requires='>=3.6', data_files=[('', ['version.py'])] )

30.923077

62

0.677861

import setuptools from version import __version__ with open("README.md", "r") as fh: long_description = fh.read() setuptools.setup( name="python2latex", version=__version__, author="Jean-Samuel Leboeuf", author_email="jean-samuel.leboeuf.1@ulaval.ca", description="A Python to LaTeX converter", long_description=long_description, long_description_content_type="text/markdown", url="https://github.com/jsleb333/python2latex", packages=setuptools.find_packages(), install_requires=['numpy', 'colorspacious', 'matplotlib'], classifiers=[ "Programming Language :: Python :: 3", "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", ], python_requires='>=3.6', data_files=[('', ['version.py'])] )

true

f704b88ab2cda09b5ebb43639854a0c2c0509468

10,852

py

Python

as/tools/generator.py

Xuyiyang23333/asbot

c3b8a88e0970c1b39f9f7575f64b3fc3fe5161ba

[ "MIT" ]

null

as/tools/generator.py

Xuyiyang23333/asbot

c3b8a88e0970c1b39f9f7575f64b3fc3fe5161ba

[ "MIT" ]

null

as/tools/generator.py

Xuyiyang23333/asbot

c3b8a88e0970c1b39f9f7575f64b3fc3fe5161ba

[ "MIT" ]

null

from PIL import Image, ImageDraw, ImageFont import numpy as np from decimal import Decimal, ROUND_HALF_UP from math import radians, tan, cos, sin from os import path _round = lambda f, r=ROUND_HALF_UP: int(Decimal(str(f)).quantize(Decimal("0"), rounding=r)) rgb = lambda r, g, b: (r, g, b) upper_font_path = path.join(path.dirname(__file__), 'NotoSansCJKSC-Black.ttf') downer_font_path = path.join(path.dirname(__file__), 'NotoSerifCJKSC-Black.ttf') def get_gradient_2d(start, stop, width, height, is_horizontal=False): if is_horizontal: return np.tile(np.linspace(start, stop, width), (height, 1)) else: return np.tile(np.linspace(start, stop, height), (width, 1)).T def getTextWidth(text, font, width=100, height=500, recursive=False): step = 100 img = Image.new("L", (width, height)) draw = ImageDraw.Draw(img) draw.text((0, 0), text, font=font, fill=255) box = img.getbbox() if box[2] < width - step or (recursive and box[2] == width - step): return box[2] else: return getTextWidth(text=text, font=font, width=width + step, height=height, recursive=True) def get_gradient_3d(width, height, start_list, stop_list, is_horizontal_list=(False, False, False)): result = np.zeros((height, width, len(start_list)), dtype=float) for i, (start, stop, is_horizontal) in enumerate(zip(start_list, stop_list, is_horizontal_list)): result[:, :, i] = get_gradient_2d(start, stop, width, height, is_horizontal) return result def createLinearGradient(steps, width, height, size=1, center=0.5): margin_up = _round(height * (center - size / 2)) margin_down = _round(height * (1 - center - size / 2)) result = np.zeros((0, width, len(steps[0])), dtype=float) for i, k in enumerate(steps.keys()): if k == 0: array = get_gradient_3d(width, _round(margin_up), steps[k], steps[k]) result = np.vstack([result, array]) continue pk = list(steps.keys())[i - 1] h = _round(height * size * (k - pk)) array = get_gradient_3d(width, h, steps[pk], steps[k]) result = np.vstack([result, array]) if k == 1: array = get_gradient_3d(width, _round(margin_down), steps[k], steps[k]) result = np.vstack([result, array]) continue return result def genBaseImage(width=1500, height=500): k = 0.63 # 渐变色缩放系数，不应大于1 c = 0.53 # 渐变色中心位置 downerSilverArray = createLinearGradient({ 0: rgb(0, 15, 36), 0.10: rgb(255, 255, 255), 0.18: rgb(55, 58, 59), 0.25: rgb(55, 58, 59), 0.5: rgb(200, 200, 200), 0.75: rgb(55, 58, 59), 0.85: rgb(25, 20, 31), 0.91: rgb(240, 240, 240), 0.95: rgb(166, 175, 194), 1: rgb(50, 50, 50) }, width=width, height=height, size=k, center=c) goldArray = createLinearGradient({ 0: rgb(253, 241, 0), 0.25: rgb(245, 253, 187), 0.4: rgb(255, 255, 255), 0.75: rgb(253, 219, 9), 0.9: rgb(127, 53, 0), 1: rgb(243, 196, 11) }, width=width, height=height, size=k, center=c) strokeRedArray = createLinearGradient({ 0: rgb(255, 100, 0), 0.5: rgb(123, 0, 0), 0.51: rgb(240, 0, 0), 1: rgb(5, 0, 0) }, width=width, height=height, size=k, center=c) redArray = createLinearGradient({ 0: rgb(230, 0, 0), 0.5: rgb(123, 0, 0), 0.51: rgb(240, 0, 0), 1: rgb(5, 0, 0) }, width=width, height=height, size=k, center=c) silver2Array = createLinearGradient({ 0: rgb(245, 246, 248), 0.15: rgb(255, 255, 255), 0.35: rgb(195, 213, 220), 0.5: rgb(160, 190, 201), 0.51: rgb(160, 190, 201), 0.52: rgb(196, 215, 222), 1.0: rgb(255, 255, 255) }, width=width, height=height, size=k, center=c) navyArray = createLinearGradient({ 0: rgb(16, 25, 58), 0.03: rgb(255, 255, 255), 0.08: rgb(16, 25, 58), 0.2: rgb(16, 25, 58), 1: rgb(16, 25, 58) }, width=width, height=height, size=k, center=c) result = { "downerSilver": Image.fromarray(np.uint8(downerSilverArray)).crop((0, 0, width, height)), "gold": Image.fromarray(np.uint8(goldArray)).crop((0, 0, width, height)), "red": Image.fromarray(np.uint8(redArray)).crop((0, 0, width, height)), "strokeRed": Image.fromarray(np.uint8(strokeRedArray)).crop((0, 0, width, height)), "silver2": Image.fromarray(np.uint8(silver2Array)).crop((0, 0, width, height)), "strokeNavy": Image.fromarray(np.uint8(navyArray)).crop((0, 0, width, height)), # Width: 7 "baseStrokeBlack": Image.new("RGBA", (width, height), rgb(0, 0, 0)).crop((0, 0, width, height)), # Width: 17 "strokeBlack": Image.new("RGBA", (width, height), rgb(16, 25, 58)).crop((0, 0, width, height)), # Width: 17 "strokeWhite": Image.new("RGBA", (width, height), rgb(221, 221, 221)).crop((0, 0, width, height)), # Width: 8 "baseStrokeWhite": Image.new("RGBA", (width, height), rgb(255, 255, 255)).crop((0, 0, width, height)) # Width: 8 } for k in result.keys(): result[k].putalpha(255) return result def genImage(word_a="5000兆円", word_b="欲しい!", default_width=1500, height=500, bg="white", subset=250, default_base=None): # width = max_width k = 0.8 # 字体缩放系数 alpha = (0, 0, 0, 0) leftmargin = 50 upmargin = 20 font_upper = ImageFont.truetype(upper_font_path, _round(height * 0.35 * k) + upmargin) font_downer = ImageFont.truetype(downer_font_path, _round(height * 0.35 * k) + upmargin) # Prepare Width upper_width = max([default_width, getTextWidth(word_a, font_upper, width=default_width, height=_round(height / 2))]) + 300 downer_width = max([default_width, getTextWidth(word_b, font_upper, width=default_width, height=_round(height / 2))]) + 300 # Prepare base - Upper (if required) if default_width == upper_width: upper_base = default_base else: upper_base = genBaseImage(width=upper_width + leftmargin, height=_round(height / 2) + upmargin) # Prepare base - Downer (if required) downer_base = genBaseImage(width=downer_width + leftmargin, height=_round(height / 2) + upmargin) # if default_width == downer_width: # downer_base = default_base # else: # Prepare mask - Upper upper_mask_base = Image.new("L", (upper_width + leftmargin, _round(height / 2) + upmargin), 0) mask_img_upper = list() upper_data = [ [ (4, 4), (4, 4), (0, 0), (0, 0), (2, -3), (0, -3), (0, -3), (0, -3) ], [ 22, 20, 16, 10, 6, 6, 3, 0 ], [ "baseStrokeBlack", "downerSilver", "baseStrokeBlack", "gold", "baseStrokeBlack", "baseStrokeWhite", "strokeRed", "red", ] ] for pos, stroke, color in zip(upper_data[0], upper_data[1], upper_data[2]): mask_img_upper.append(upper_mask_base.copy()) mask_draw_upper = ImageDraw.Draw(mask_img_upper[-1]) mask_draw_upper.text((pos[0] + leftmargin, pos[1] + upmargin), word_a, font=font_upper, fill=255, stroke_width=_round(stroke * height / 500)) # Prepare mask - Downer downer_mask_base = Image.new("L", (downer_width + leftmargin, _round(height / 2) + upmargin), 0) mask_img_downer = list() downer_data = [ [ (5, 2), (5, 2), (0, 0), (0, 0), (0, 0), (0, -3) ], [ 22, 19, 17, 8, 7, 0 ], [ "baseStrokeBlack", "downerSilver", "strokeBlack", "strokeWhite", "strokeNavy", "silver2" ] ] for pos, stroke, color in zip(downer_data[0], downer_data[1], downer_data[2]): mask_img_downer.append(downer_mask_base.copy()) mask_draw_downer = ImageDraw.Draw(mask_img_downer[-1]) mask_draw_downer.text((pos[0] + leftmargin, pos[1] + upmargin), word_b, font=font_downer, fill=255, stroke_width=_round(stroke * height / 500)) # Draw text - Upper img_upper = Image.new("RGBA", (upper_width, _round(height / 2)), alpha) for i, (pos, stroke, color) in enumerate(zip(upper_data[0], upper_data[1], upper_data[2])): img_upper_part = Image.new("RGBA", (upper_width + leftmargin, _round(height / 2) + upmargin), alpha) img_upper_part.paste(upper_base[color], (0, 0), mask=mask_img_upper[i]) img_upper.alpha_composite(img_upper_part) # Draw text - Downer img_downer = Image.new("RGBA", (downer_width + leftmargin, _round(height / 2)), alpha) for i, (pos, stroke, color) in enumerate(zip(downer_data[0], downer_data[1], downer_data[2])): img_downer_part = Image.new("RGBA", (downer_width + leftmargin, _round(height / 2) + upmargin), alpha) img_downer_part.paste(downer_base[color], (0, 0), mask=mask_img_downer[i]) img_downer.alpha_composite(img_downer_part) # img_upper.save("./uptemp.png") # img_downer.save("./downtemp.png") # tilt image tiltres = list() angle = 20 for img in [img_upper, img_downer]: dist = img.height * tan(radians(angle)) data = (1, tan(radians(angle)), -dist, 0, 1, 0) imgc = img.crop((0, 0, img.width + dist, img.height)) imgt = imgc.transform(imgc.size, Image.AFFINE, data, Image.BILINEAR) tiltres.append(imgt) # finish previmg = Image.new("RGBA", (max([upper_width, downer_width]) + leftmargin + subset + 100, height + upmargin + 100), (255, 255, 255, 0)) # previmg.paste(tiltres[0], (0, 0)) # previmg.paste(tiltres[1], (subset, _round(height/2))) previmg.alpha_composite(tiltres[0], (0, 50), (0, 0)) if upper_width > downer_width + subset: previmg.alpha_composite(tiltres[1], (upper_width + subset - downer_width, _round(height / 2) + 50), (0, 0)) else: previmg.alpha_composite(tiltres[1], (subset, _round(height / 2) + 50), (0, 0)) # previmg.save("./test1.png") croprange = previmg.getbbox() img = previmg.crop(croprange) final_image = Image.new("RGB", (img.size[0] + 100, img.size[1] + 100), bg) final_image.paste(img, (50, 50)) return final_image

40.950943

121

0.570217

from PIL import Image, ImageDraw, ImageFont import numpy as np from decimal import Decimal, ROUND_HALF_UP from math import radians, tan, cos, sin from os import path _round = lambda f, r=ROUND_HALF_UP: int(Decimal(str(f)).quantize(Decimal("0"), rounding=r)) rgb = lambda r, g, b: (r, g, b) upper_font_path = path.join(path.dirname(__file__), 'NotoSansCJKSC-Black.ttf') downer_font_path = path.join(path.dirname(__file__), 'NotoSerifCJKSC-Black.ttf') def get_gradient_2d(start, stop, width, height, is_horizontal=False): if is_horizontal: return np.tile(np.linspace(start, stop, width), (height, 1)) else: return np.tile(np.linspace(start, stop, height), (width, 1)).T def getTextWidth(text, font, width=100, height=500, recursive=False): step = 100 img = Image.new("L", (width, height)) draw = ImageDraw.Draw(img) draw.text((0, 0), text, font=font, fill=255) box = img.getbbox() if box[2] < width - step or (recursive and box[2] == width - step): return box[2] else: return getTextWidth(text=text, font=font, width=width + step, height=height, recursive=True) def get_gradient_3d(width, height, start_list, stop_list, is_horizontal_list=(False, False, False)): result = np.zeros((height, width, len(start_list)), dtype=float) for i, (start, stop, is_horizontal) in enumerate(zip(start_list, stop_list, is_horizontal_list)): result[:, :, i] = get_gradient_2d(start, stop, width, height, is_horizontal) return result def createLinearGradient(steps, width, height, size=1, center=0.5): margin_up = _round(height * (center - size / 2)) margin_down = _round(height * (1 - center - size / 2)) result = np.zeros((0, width, len(steps[0])), dtype=float) for i, k in enumerate(steps.keys()): if k == 0: array = get_gradient_3d(width, _round(margin_up), steps[k], steps[k]) result = np.vstack([result, array]) continue pk = list(steps.keys())[i - 1] h = _round(height * size * (k - pk)) array = get_gradient_3d(width, h, steps[pk], steps[k]) result = np.vstack([result, array]) if k == 1: array = get_gradient_3d(width, _round(margin_down), steps[k], steps[k]) result = np.vstack([result, array]) continue return result def genBaseImage(width=1500, height=500): k = 0.63 c = 0.53 downerSilverArray = createLinearGradient({ 0: rgb(0, 15, 36), 0.10: rgb(255, 255, 255), 0.18: rgb(55, 58, 59), 0.25: rgb(55, 58, 59), 0.5: rgb(200, 200, 200), 0.75: rgb(55, 58, 59), 0.85: rgb(25, 20, 31), 0.91: rgb(240, 240, 240), 0.95: rgb(166, 175, 194), 1: rgb(50, 50, 50) }, width=width, height=height, size=k, center=c) goldArray = createLinearGradient({ 0: rgb(253, 241, 0), 0.25: rgb(245, 253, 187), 0.4: rgb(255, 255, 255), 0.75: rgb(253, 219, 9), 0.9: rgb(127, 53, 0), 1: rgb(243, 196, 11) }, width=width, height=height, size=k, center=c) strokeRedArray = createLinearGradient({ 0: rgb(255, 100, 0), 0.5: rgb(123, 0, 0), 0.51: rgb(240, 0, 0), 1: rgb(5, 0, 0) }, width=width, height=height, size=k, center=c) redArray = createLinearGradient({ 0: rgb(230, 0, 0), 0.5: rgb(123, 0, 0), 0.51: rgb(240, 0, 0), 1: rgb(5, 0, 0) }, width=width, height=height, size=k, center=c) silver2Array = createLinearGradient({ 0: rgb(245, 246, 248), 0.15: rgb(255, 255, 255), 0.35: rgb(195, 213, 220), 0.5: rgb(160, 190, 201), 0.51: rgb(160, 190, 201), 0.52: rgb(196, 215, 222), 1.0: rgb(255, 255, 255) }, width=width, height=height, size=k, center=c) navyArray = createLinearGradient({ 0: rgb(16, 25, 58), 0.03: rgb(255, 255, 255), 0.08: rgb(16, 25, 58), 0.2: rgb(16, 25, 58), 1: rgb(16, 25, 58) }, width=width, height=height, size=k, center=c) result = { "downerSilver": Image.fromarray(np.uint8(downerSilverArray)).crop((0, 0, width, height)), "gold": Image.fromarray(np.uint8(goldArray)).crop((0, 0, width, height)), "red": Image.fromarray(np.uint8(redArray)).crop((0, 0, width, height)), "strokeRed": Image.fromarray(np.uint8(strokeRedArray)).crop((0, 0, width, height)), "silver2": Image.fromarray(np.uint8(silver2Array)).crop((0, 0, width, height)), "strokeNavy": Image.fromarray(np.uint8(navyArray)).crop((0, 0, width, height)), "baseStrokeBlack": Image.new("RGBA", (width, height), rgb(0, 0, 0)).crop((0, 0, width, height)), "strokeBlack": Image.new("RGBA", (width, height), rgb(16, 25, 58)).crop((0, 0, width, height)), "strokeWhite": Image.new("RGBA", (width, height), rgb(221, 221, 221)).crop((0, 0, width, height)), "baseStrokeWhite": Image.new("RGBA", (width, height), rgb(255, 255, 255)).crop((0, 0, width, height)) } for k in result.keys(): result[k].putalpha(255) return result def genImage(word_a="5000兆円", word_b="欲しい!", default_width=1500, height=500, bg="white", subset=250, default_base=None): k = 0.8 alpha = (0, 0, 0, 0) leftmargin = 50 upmargin = 20 font_upper = ImageFont.truetype(upper_font_path, _round(height * 0.35 * k) + upmargin) font_downer = ImageFont.truetype(downer_font_path, _round(height * 0.35 * k) + upmargin) upper_width = max([default_width, getTextWidth(word_a, font_upper, width=default_width, height=_round(height / 2))]) + 300 downer_width = max([default_width, getTextWidth(word_b, font_upper, width=default_width, height=_round(height / 2))]) + 300 if default_width == upper_width: upper_base = default_base else: upper_base = genBaseImage(width=upper_width + leftmargin, height=_round(height / 2) + upmargin) downer_base = genBaseImage(width=downer_width + leftmargin, height=_round(height / 2) + upmargin) upper_mask_base = Image.new("L", (upper_width + leftmargin, _round(height / 2) + upmargin), 0) mask_img_upper = list() upper_data = [ [ (4, 4), (4, 4), (0, 0), (0, 0), (2, -3), (0, -3), (0, -3), (0, -3) ], [ 22, 20, 16, 10, 6, 6, 3, 0 ], [ "baseStrokeBlack", "downerSilver", "baseStrokeBlack", "gold", "baseStrokeBlack", "baseStrokeWhite", "strokeRed", "red", ] ] for pos, stroke, color in zip(upper_data[0], upper_data[1], upper_data[2]): mask_img_upper.append(upper_mask_base.copy()) mask_draw_upper = ImageDraw.Draw(mask_img_upper[-1]) mask_draw_upper.text((pos[0] + leftmargin, pos[1] + upmargin), word_a, font=font_upper, fill=255, stroke_width=_round(stroke * height / 500)) downer_mask_base = Image.new("L", (downer_width + leftmargin, _round(height / 2) + upmargin), 0) mask_img_downer = list() downer_data = [ [ (5, 2), (5, 2), (0, 0), (0, 0), (0, 0), (0, -3) ], [ 22, 19, 17, 8, 7, 0 ], [ "baseStrokeBlack", "downerSilver", "strokeBlack", "strokeWhite", "strokeNavy", "silver2" ] ] for pos, stroke, color in zip(downer_data[0], downer_data[1], downer_data[2]): mask_img_downer.append(downer_mask_base.copy()) mask_draw_downer = ImageDraw.Draw(mask_img_downer[-1]) mask_draw_downer.text((pos[0] + leftmargin, pos[1] + upmargin), word_b, font=font_downer, fill=255, stroke_width=_round(stroke * height / 500)) img_upper = Image.new("RGBA", (upper_width, _round(height / 2)), alpha) for i, (pos, stroke, color) in enumerate(zip(upper_data[0], upper_data[1], upper_data[2])): img_upper_part = Image.new("RGBA", (upper_width + leftmargin, _round(height / 2) + upmargin), alpha) img_upper_part.paste(upper_base[color], (0, 0), mask=mask_img_upper[i]) img_upper.alpha_composite(img_upper_part) img_downer = Image.new("RGBA", (downer_width + leftmargin, _round(height / 2)), alpha) for i, (pos, stroke, color) in enumerate(zip(downer_data[0], downer_data[1], downer_data[2])): img_downer_part = Image.new("RGBA", (downer_width + leftmargin, _round(height / 2) + upmargin), alpha) img_downer_part.paste(downer_base[color], (0, 0), mask=mask_img_downer[i]) img_downer.alpha_composite(img_downer_part) tiltres = list() angle = 20 for img in [img_upper, img_downer]: dist = img.height * tan(radians(angle)) data = (1, tan(radians(angle)), -dist, 0, 1, 0) imgc = img.crop((0, 0, img.width + dist, img.height)) imgt = imgc.transform(imgc.size, Image.AFFINE, data, Image.BILINEAR) tiltres.append(imgt) previmg = Image.new("RGBA", (max([upper_width, downer_width]) + leftmargin + subset + 100, height + upmargin + 100), (255, 255, 255, 0)) previmg.alpha_composite(tiltres[0], (0, 50), (0, 0)) if upper_width > downer_width + subset: previmg.alpha_composite(tiltres[1], (upper_width + subset - downer_width, _round(height / 2) + 50), (0, 0)) else: previmg.alpha_composite(tiltres[1], (subset, _round(height / 2) + 50), (0, 0)) croprange = previmg.getbbox() img = previmg.crop(croprange) final_image = Image.new("RGB", (img.size[0] + 100, img.size[1] + 100), bg) final_image.paste(img, (50, 50)) return final_image

true

f704b95c88cfabc1dac0e794e4484161cd8c29c9

5,893

py

Python

idiota/data.py

prakashsellathurai/idiota

e3cebb669bc5d04f30279c15939465aec2495eb6

[ "Apache-2.0" ]

null

idiota/data.py

prakashsellathurai/idiota

e3cebb669bc5d04f30279c15939465aec2495eb6

[ "Apache-2.0" ]

null

idiota/data.py

prakashsellathurai/idiota

e3cebb669bc5d04f30279c15939465aec2495eb6

[ "Apache-2.0" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """ Idiota object types tree - A tree (directory listing) object that represents the directory structure in a tree object. commit(ref) - A object that represents the changes in a single commit. blob - A blob object that represents a file or a piece of data. parent - A object that represents the ancestor to the commit in the DaG. tag - A object that represents a meta info. """ __author__ = "prakashsellathurai" __copyright__ = "Copyright 2021" __version__ = "1.0.1" __email__ = "prakashsellathurai@gmail.com" import os import hashlib import shutil import json from collections import namedtuple from contextlib import contextmanager GIT_DIR = None RefValue = namedtuple('RefValue', ['symbolic', 'value']) @contextmanager def change_git_dir(new_dir) -> None: """ Change the current git directory Args: new_dir (str): new git directory Yields: str: old git directory """ global GIT_DIR old_dir = GIT_DIR GIT_DIR = f'{new_dir}/.idiota' yield GIT_DIR = old_dir def init() -> None: """ Create .idiota directory Returns: None """ os.makedirs(GIT_DIR, exist_ok=True) os.makedirs(f'{GIT_DIR}/objects') def update_ref(ref, value, deref: bool=True) -> None: """ Update a ref Args: ref (str): ref name value (str): ref value deref (bool): dereference symbolic refs Returns: None """ # TODO: check if ref exists # TODO: check if value is valid # TODO: check if ref is symbolic ref = _get_ref_internal(ref, deref)[0] assert value.value if value.symbolic: value = f'ref: {value.value}' else: value = value.value ref_path = f'{GIT_DIR}/{ref}' os.makedirs(os.path.dirname(ref_path), exist_ok=True) with open(ref_path, 'w') as f: f.write(value) def get_ref(ref, deref=True) -> RefValue: """ Get a ref value Args: ref (str): ref name deref (bool): dereference symbolic refs Returns: RefValue(str): ref value """ return _get_ref_internal(ref, deref)[1] def delete_ref(ref, deref=True)->None: """ Delete a ref""" ref = _get_ref_internal(ref, deref)[0] os.remove(f'{GIT_DIR}/{ref}') def _get_ref_internal(ref, deref) -> RefValue: """ Get a ref value Args: ref (str): ref name deref (bool): dereference symbolic refs Returns: RefValue (str): ref value """ ref_path = f'{GIT_DIR}/{ref}' value = None if os.path.isfile(ref_path): with open(ref_path) as f: value = f.read().strip() symbolic = bool(value) and value.startswith('ref:') if symbolic: value = value.split(':', 1)[1].strip() if deref: return _get_ref_internal(value, deref=True) return ref, RefValue(symbolic=symbolic, value=value) def iter_refs(prefix='', deref=True): """ Iterate over refs Args: prefix (str): ref prefix deref (bool): dereference symbolic refs Returns: Iterator[Tup(str, RefValue)]: ref name and ref value """ refs = ['HEAD', 'MERGE_HEAD'] for root, _, filenames in os.walk(f'{GIT_DIR}/refs/'): root = os.path.relpath(root, GIT_DIR) refs.extend(f'{root}/{name}' for name in filenames) for refname in refs: if not refname.startswith(prefix): continue ref = get_ref(refname, deref=deref) if ref.value: yield refname, ref @contextmanager def get_index(): """ Get index Yields: Index: index """ index = {} if os.path.isfile(f'{GIT_DIR}/index'): with open(f'{GIT_DIR}/index') as f: index = json.load(f) yield index with open(f'{GIT_DIR}/index', 'w') as f: json.dump(index, f) def hash_object(data: object, type_='blob')-> str: """ Hash an object uses: Sha1 algorithm Args: data (bytes): object data Returns: str: object id """ obj = type_.encode() + b'\x00' + data oid = hashlib.sha1(obj).hexdigest() with open(f'{GIT_DIR}/objects/{oid}', 'wb') as out: out.write(obj) return oid def get_object(oid: str, expected='blob')-> object: """ get an object Args: oid (str): object id Returns: bytes: object data """ with open(f'{GIT_DIR}/objects/{oid}', 'rb') as f: obj = f.read() first_null = obj.index(b'\x00') type_ = obj[:first_null].decode() content = obj[first_null + 1:] if expected is not None: assert type_ == expected, f'Expected {expected}, got {type_}' return content def object_exists(oid: bool)-> bool: """ checks if object of given id exists in the repository Args: oid (str): object id Returns: bool: True if object exists """ return os.path.isfile(f'{GIT_DIR}/objects/{oid}') def fetch_object_if_missing(oid, remote_git_dir): """ fetch object from remote repository if it is not present in local repository Args: oid (str): object id remote_git_dir (str): remote git directory Returns: None """ if object_exists(oid): return remote_git_dir += '/.ugit' shutil.copy(f'{remote_git_dir}/objects/{oid}', f'{GIT_DIR}/objects/{oid}') def push_object(oid, remote_git_dir): """ push object to remote repository Args: oid (str): object id remote_git_dir (str): remote git directory Returns: None """ remote_git_dir += '/.ugit' shutil.copy(f'{GIT_DIR}/objects/{oid}', f'{remote_git_dir}/objects/{oid}')

22.32197

102

0.589004

__author__ = "prakashsellathurai" __copyright__ = "Copyright 2021" __version__ = "1.0.1" __email__ = "prakashsellathurai@gmail.com" import os import hashlib import shutil import json from collections import namedtuple from contextlib import contextmanager GIT_DIR = None RefValue = namedtuple('RefValue', ['symbolic', 'value']) @contextmanager def change_git_dir(new_dir) -> None: global GIT_DIR old_dir = GIT_DIR GIT_DIR = f'{new_dir}/.idiota' yield GIT_DIR = old_dir def init() -> None: os.makedirs(GIT_DIR, exist_ok=True) os.makedirs(f'{GIT_DIR}/objects') def update_ref(ref, value, deref: bool=True) -> None: ref = _get_ref_internal(ref, deref)[0] assert value.value if value.symbolic: value = f'ref: {value.value}' else: value = value.value ref_path = f'{GIT_DIR}/{ref}' os.makedirs(os.path.dirname(ref_path), exist_ok=True) with open(ref_path, 'w') as f: f.write(value) def get_ref(ref, deref=True) -> RefValue: return _get_ref_internal(ref, deref)[1] def delete_ref(ref, deref=True)->None: ref = _get_ref_internal(ref, deref)[0] os.remove(f'{GIT_DIR}/{ref}') def _get_ref_internal(ref, deref) -> RefValue: ref_path = f'{GIT_DIR}/{ref}' value = None if os.path.isfile(ref_path): with open(ref_path) as f: value = f.read().strip() symbolic = bool(value) and value.startswith('ref:') if symbolic: value = value.split(':', 1)[1].strip() if deref: return _get_ref_internal(value, deref=True) return ref, RefValue(symbolic=symbolic, value=value) def iter_refs(prefix='', deref=True): refs = ['HEAD', 'MERGE_HEAD'] for root, _, filenames in os.walk(f'{GIT_DIR}/refs/'): root = os.path.relpath(root, GIT_DIR) refs.extend(f'{root}/{name}' for name in filenames) for refname in refs: if not refname.startswith(prefix): continue ref = get_ref(refname, deref=deref) if ref.value: yield refname, ref @contextmanager def get_index(): index = {} if os.path.isfile(f'{GIT_DIR}/index'): with open(f'{GIT_DIR}/index') as f: index = json.load(f) yield index with open(f'{GIT_DIR}/index', 'w') as f: json.dump(index, f) def hash_object(data: object, type_='blob')-> str: obj = type_.encode() + b'\x00' + data oid = hashlib.sha1(obj).hexdigest() with open(f'{GIT_DIR}/objects/{oid}', 'wb') as out: out.write(obj) return oid def get_object(oid: str, expected='blob')-> object: with open(f'{GIT_DIR}/objects/{oid}', 'rb') as f: obj = f.read() first_null = obj.index(b'\x00') type_ = obj[:first_null].decode() content = obj[first_null + 1:] if expected is not None: assert type_ == expected, f'Expected {expected}, got {type_}' return content def object_exists(oid: bool)-> bool: return os.path.isfile(f'{GIT_DIR}/objects/{oid}') def fetch_object_if_missing(oid, remote_git_dir): if object_exists(oid): return remote_git_dir += '/.ugit' shutil.copy(f'{remote_git_dir}/objects/{oid}', f'{GIT_DIR}/objects/{oid}') def push_object(oid, remote_git_dir): remote_git_dir += '/.ugit' shutil.copy(f'{GIT_DIR}/objects/{oid}', f'{remote_git_dir}/objects/{oid}')

true

f704b968b6da8f6293a4c1d3f9417ce9c6268bfa

15,401

py

Python

libcxx/utils/libcxx/test/newformat.py

LevyForchh/llvm-project

904c0865dfaef343245d6496623f187c4cdc1b61

[ "Apache-2.0" ]

null

libcxx/utils/libcxx/test/newformat.py

LevyForchh/llvm-project

904c0865dfaef343245d6496623f187c4cdc1b61

[ "Apache-2.0" ]

9

2020-04-24T21:51:04.000Z

2020-11-06T01:04:09.000Z

libcxx/utils/libcxx/test/newformat.py

LevyForchh/llvm-project

904c0865dfaef343245d6496623f187c4cdc1b61

[ "Apache-2.0" ]

null

#===----------------------------------------------------------------------===## # # Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. # See https://llvm.org/LICENSE.txt for license information. # SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception # #===----------------------------------------------------------------------===## import lit import os import pipes import re import subprocess class CxxStandardLibraryTest(lit.formats.TestFormat): """ Lit test format for the C++ Standard Library conformance test suite. This test format is based on top of the ShTest format -- it basically creates a shell script performing the right operations (compile/link/run) based on the extension of the test file it encounters. It supports files with the following extensions: FOO.pass.cpp - Compiles, links and runs successfully FOO.pass.mm - Same as .pass.cpp, but for Objective-C++ FOO.run.fail.cpp - Compiles and links successfully, but fails at runtime FOO.compile.pass.cpp - Compiles successfully, link and run not attempted FOO.compile.fail.cpp - Does not compile successfully FOO.link.pass.cpp - Compiles and links successfully, run not attempted FOO.link.fail.cpp - Compiles successfully, but fails to link FOO.sh.<anything> - A builtin Lit Shell test FOO.verify.cpp - Compiles with clang-verify FOO.fail.cpp - Compiled with clang-verify if clang-verify is supported, and equivalent to a .compile.fail.cpp test otherwise. This is supported only for backwards compatibility with the test suite. Substitution requirements =============================== The test format operates by assuming that each test's configuration provides the following substitutions, which it will reuse in the shell scripts it constructs: %{cxx} - A command that can be used to invoke the compiler %{compile_flags} - Flags to use when compiling a test case %{link_flags} - Flags to use when linking a test case %{flags} - Flags to use either when compiling or linking a test case %{exec} - A command to prefix the execution of executables Note that when building an executable (as opposed to only compiling a source file), all three of %{flags}, %{compile_flags} and %{link_flags} will be used in the same command line. In other words, the test format doesn't perform separate compilation and linking steps in this case. Additional supported directives =============================== In addition to everything that's supported in Lit ShTests, this test format also understands the following directives inside test files: // FILE_DEPENDENCIES: file, directory, /path/to/file This directive expresses that the test requires the provided files or directories in order to run. An example is a test that requires some test input stored in a data file. When a test file contains such a directive, this test format will collect them and make them available in a special %{file_dependencies} substitution. The intent is that if one needs to e.g. execute tests on a remote host, the %{exec} substitution could use %{file_dependencies} to know which files and directories to copy to the remote host. // ADDITIONAL_COMPILE_FLAGS: flag1, flag2, flag3 This directive will cause the provided flags to be added to the %{compile_flags} substitution for the test that contains it. This allows adding special compilation flags without having to use a .sh.cpp test, which would be more powerful but perhaps overkill. Additional provided substitutions and features ============================================== The test format will define the following substitutions for use inside tests: %{verify} This expands to the set of flags that must be passed to the compiler in order to use Clang-verify, if that is supported. verify-support This Lit feature will be made available when the compiler supports Clang-verify. This can be used to disable tests that require that feature, such as `.verify.cpp` tests. %{file_dependencies} Expands to the list of files that this test depends on. See FILE_DEPENDENCIES above. %{build} Expands to a command-line that builds the current source file with the %{flags}, %{compile_flags} and %{link_flags} substitutions, and that produces an executable named %t.exe. %{run} Equivalent to `%{exec} %t.exe`. This is intended to be used in conjunction with the %{build} substitution. Design notes ============ This test format never implicitly disables a type of test. For example, we could be tempted to automatically mark `.verify.cpp` tests as UNSUPPORTED when clang-verify isn't supported by the compiler. However, this sort of logic has been known to cause tests to be ignored in the past, so we favour having tests mark themselves as unsupported explicitly. This test format still needs work in the following areas: - It is unknown how well it works on Windows yet. """ def getTestsInDirectory(self, testSuite, pathInSuite, litConfig, localConfig): SUPPORTED_SUFFIXES = ['[.]pass[.]cpp$', '[.]pass[.]mm$', '[.]run[.]fail[.]cpp$', '[.]compile[.]pass[.]cpp$', '[.]compile[.]fail[.]cpp$', '[.]link[.]pass[.]cpp$', '[.]link[.]fail[.]cpp$', '[.]sh[.][^.]+$', '[.]verify[.]cpp$', '[.]fail[.]cpp$'] sourcePath = testSuite.getSourcePath(pathInSuite) for filename in os.listdir(sourcePath): # Ignore dot files and excluded tests. if filename.startswith('.') or filename in localConfig.excludes: continue filepath = os.path.join(sourcePath, filename) if not os.path.isdir(filepath): if any([re.search(ext, filename) for ext in SUPPORTED_SUFFIXES]): yield lit.Test.Test(testSuite, pathInSuite + (filename,), localConfig) def _checkBaseSubstitutions(self, substitutions): substitutions = [s for (s, _) in substitutions] for s in ['%{cxx}', '%{compile_flags}', '%{link_flags}', '%{flags}', '%{exec}']: assert s in substitutions, "Required substitution {} was not provided".format(s) # Determine whether clang-verify is supported. def _supportsVerify(self, test, litConfig): command = "echo | %{cxx} -xc++ - -Werror -fsyntax-only -Xclang -verify-ignore-unexpected" command = lit.TestRunner.applySubstitutions([command], test.config.substitutions, recursion_limit=test.config.recursiveExpansionLimit)[0] devNull = open(os.devnull, 'w') result = subprocess.call(command, shell=True, stdout=devNull, stderr=devNull) return result == 0 def _disableWithModules(self, test, litConfig): with open(test.getSourcePath(), 'rb') as f: contents = f.read() return b'#define _LIBCPP_ASSERT' in contents def execute(self, test, litConfig): self._checkBaseSubstitutions(test.config.substitutions) filename = test.path_in_suite[-1] # TODO(ldionne): We currently disable tests that re-define _LIBCPP_ASSERT # when we run with modules enabled. Instead, we should # split the part that does a death test outside of the # test, and only disable that part when modules are # enabled. if '-fmodules' in test.config.available_features and self._disableWithModules(test, litConfig): return lit.Test.Result(lit.Test.UNSUPPORTED, 'Test {} is unsupported when modules are enabled') if re.search('[.]sh[.][^.]+$', filename): steps = [ ] # The steps are already in the script return self._executeShTest(test, litConfig, steps) elif filename.endswith('.compile.pass.cpp'): steps = [ "%dbg(COMPILED WITH) %{cxx} %s %{flags} %{compile_flags} -fsyntax-only" ] return self._executeShTest(test, litConfig, steps) elif filename.endswith('.compile.fail.cpp'): steps = [ "%dbg(COMPILED WITH) ! %{cxx} %s %{flags} %{compile_flags} -fsyntax-only" ] return self._executeShTest(test, litConfig, steps) elif filename.endswith('.link.pass.cpp'): steps = [ "%dbg(COMPILED WITH) %{cxx} %s %{flags} %{compile_flags} %{link_flags} -o %t.exe" ] return self._executeShTest(test, litConfig, steps) elif filename.endswith('.link.fail.cpp'): steps = [ "%dbg(COMPILED WITH) %{cxx} %s %{flags} %{compile_flags} -c -o %t.o", "%dbg(LINKED WITH) ! %{cxx} %t.o %{flags} %{link_flags} -o %t.exe" ] return self._executeShTest(test, litConfig, steps) elif filename.endswith('.run.fail.cpp'): steps = [ "%dbg(COMPILED WITH) %{cxx} %s %{flags} %{compile_flags} %{link_flags} -o %t.exe", "%dbg(EXECUTED AS) %{exec} ! %t.exe" ] return self._executeShTest(test, litConfig, steps, fileDependencies=['%t.exe']) elif filename.endswith('.verify.cpp'): steps = [ "%dbg(COMPILED WITH) %{cxx} %s %{flags} %{compile_flags} -fsyntax-only %{verify}" ] return self._executeShTest(test, litConfig, steps) # Make sure to check these ones last, since they will match other # suffixes above too. elif filename.endswith('.pass.cpp') or filename.endswith('.pass.mm'): steps = [ "%dbg(COMPILED WITH) %{cxx} %s %{flags} %{compile_flags} %{link_flags} -o %t.exe", "%dbg(EXECUTED AS) %{exec} %t.exe" ] return self._executeShTest(test, litConfig, steps, fileDependencies=['%t.exe']) # This is like a .verify.cpp test when clang-verify is supported, # otherwise it's like a .compile.fail.cpp test. This is only provided # for backwards compatibility with the test suite. elif filename.endswith('.fail.cpp'): if self._supportsVerify(test, litConfig): steps = [ "%dbg(COMPILED WITH) %{cxx} %s %{flags} %{compile_flags} -fsyntax-only %{verify}" ] else: steps = [ "%dbg(COMPILED WITH) ! %{cxx} %s %{flags} %{compile_flags} -fsyntax-only" ] return self._executeShTest(test, litConfig, steps) else: return lit.Test.Result(lit.Test.UNRESOLVED, "Unknown test suffix for '{}'".format(filename)) # Utility function to add compile flags in lit.local.cfg files. def addCompileFlags(self, config, *flags): string = ' '.join(flags) config.substitutions = [(s, x + ' ' + string) if s == '%{compile_flags}' else (s, x) for (s, x) in config.substitutions] # Modified version of lit.TestRunner.executeShTest to handle custom parsers correctly. def _executeShTest(self, test, litConfig, steps, fileDependencies=None): if test.config.unsupported: return lit.Test.Result(lit.Test.UNSUPPORTED, 'Test is unsupported') # Get the default substitutions tmpDir, tmpBase = lit.TestRunner.getTempPaths(test) useExternalSh = True substitutions = lit.TestRunner.getDefaultSubstitutions(test, tmpDir, tmpBase, normalize_slashes=useExternalSh) # Add the %{build} and %{run} convenience substitutions substitutions.append(('%{build}', '%{cxx} %s %{flags} %{compile_flags} %{link_flags} -o %t.exe')) substitutions.append(('%{run}', '%{exec} %t.exe')) # Add the %{verify} substitution and the verify-support feature if Clang-verify is supported if self._supportsVerify(test, litConfig): test.config.available_features.add('verify-support') substitutions.append(('%{verify}', '-Xclang -verify -Xclang -verify-ignore-unexpected=note -ferror-limit=0')) # Parse the test file, including custom directives additionalCompileFlags = [] fileDependencies = fileDependencies or [] parsers = [ lit.TestRunner.IntegratedTestKeywordParser('FILE_DEPENDENCIES:', lit.TestRunner.ParserKind.LIST, initial_value=fileDependencies), lit.TestRunner.IntegratedTestKeywordParser('ADDITIONAL_COMPILE_FLAGS:', lit.TestRunner.ParserKind.LIST, initial_value=additionalCompileFlags) ] script = list(steps) parsed = lit.TestRunner.parseIntegratedTestScript(test, additional_parsers=parsers, require_script=not script) if isinstance(parsed, lit.Test.Result): return parsed script += parsed # Add compile flags specified with ADDITIONAL_COMPILE_FLAGS. substitutions = [(s, x + ' ' + ' '.join(additionalCompileFlags)) if s == '%{compile_flags}' else (s, x) for (s, x) in substitutions] # Perform substitutions inside FILE_DEPENDENCIES lines (or injected dependencies). # This allows using variables like %t in file dependencies. Also note that we really # need to resolve %{file_dependencies} now, because otherwise we won't be able to # make all paths absolute below. fileDependencies = lit.TestRunner.applySubstitutions(fileDependencies, substitutions, recursion_limit=test.config.recursiveExpansionLimit) # Add the %{file_dependencies} substitution before we perform substitutions # inside the script. testDir = os.path.dirname(test.getSourcePath()) fileDependencies = [f if os.path.isabs(f) else os.path.join(testDir, f) for f in fileDependencies] substitutions.append(('%{file_dependencies}', ' '.join(map(pipes.quote, fileDependencies)))) # Perform substitution in the script itself. script = lit.TestRunner.applySubstitutions(script, substitutions, recursion_limit=test.config.recursiveExpansionLimit) if litConfig.noExecute: return lit.Test.Result(lit.Test.PASS) else: return lit.TestRunner._runShTest(test, litConfig, useExternalSh, script, tmpBase)

50.661184

128

0.60087

mport lit import os import pipes import re import subprocess class CxxStandardLibraryTest(lit.formats.TestFormat): def getTestsInDirectory(self, testSuite, pathInSuite, litConfig, localConfig): SUPPORTED_SUFFIXES = ['[.]pass[.]cpp$', '[.]pass[.]mm$', '[.]run[.]fail[.]cpp$', '[.]compile[.]pass[.]cpp$', '[.]compile[.]fail[.]cpp$', '[.]link[.]pass[.]cpp$', '[.]link[.]fail[.]cpp$', '[.]sh[.][^.]+$', '[.]verify[.]cpp$', '[.]fail[.]cpp$'] sourcePath = testSuite.getSourcePath(pathInSuite) for filename in os.listdir(sourcePath): if filename.startswith('.') or filename in localConfig.excludes: continue filepath = os.path.join(sourcePath, filename) if not os.path.isdir(filepath): if any([re.search(ext, filename) for ext in SUPPORTED_SUFFIXES]): yield lit.Test.Test(testSuite, pathInSuite + (filename,), localConfig) def _checkBaseSubstitutions(self, substitutions): substitutions = [s for (s, _) in substitutions] for s in ['%{cxx}', '%{compile_flags}', '%{link_flags}', '%{flags}', '%{exec}']: assert s in substitutions, "Required substitution {} was not provided".format(s) def _supportsVerify(self, test, litConfig): command = "echo | %{cxx} -xc++ - -Werror -fsyntax-only -Xclang -verify-ignore-unexpected" command = lit.TestRunner.applySubstitutions([command], test.config.substitutions, recursion_limit=test.config.recursiveExpansionLimit)[0] devNull = open(os.devnull, 'w') result = subprocess.call(command, shell=True, stdout=devNull, stderr=devNull) return result == 0 def _disableWithModules(self, test, litConfig): with open(test.getSourcePath(), 'rb') as f: contents = f.read() return b'#define _LIBCPP_ASSERT' in contents def execute(self, test, litConfig): self._checkBaseSubstitutions(test.config.substitutions) filename = test.path_in_suite[-1] if '-fmodules' in test.config.available_features and self._disableWithModules(test, litConfig): return lit.Test.Result(lit.Test.UNSUPPORTED, 'Test {} is unsupported when modules are enabled') if re.search('[.]sh[.][^.]+$', filename): steps = [ ] return self._executeShTest(test, litConfig, steps) elif filename.endswith('.compile.pass.cpp'): steps = [ "%dbg(COMPILED WITH) %{cxx} %s %{flags} %{compile_flags} -fsyntax-only" ] return self._executeShTest(test, litConfig, steps) elif filename.endswith('.compile.fail.cpp'): steps = [ "%dbg(COMPILED WITH) ! %{cxx} %s %{flags} %{compile_flags} -fsyntax-only" ] return self._executeShTest(test, litConfig, steps) elif filename.endswith('.link.pass.cpp'): steps = [ "%dbg(COMPILED WITH) %{cxx} %s %{flags} %{compile_flags} %{link_flags} -o %t.exe" ] return self._executeShTest(test, litConfig, steps) elif filename.endswith('.link.fail.cpp'): steps = [ "%dbg(COMPILED WITH) %{cxx} %s %{flags} %{compile_flags} -c -o %t.o", "%dbg(LINKED WITH) ! %{cxx} %t.o %{flags} %{link_flags} -o %t.exe" ] return self._executeShTest(test, litConfig, steps) elif filename.endswith('.run.fail.cpp'): steps = [ "%dbg(COMPILED WITH) %{cxx} %s %{flags} %{compile_flags} %{link_flags} -o %t.exe", "%dbg(EXECUTED AS) %{exec} ! %t.exe" ] return self._executeShTest(test, litConfig, steps, fileDependencies=['%t.exe']) elif filename.endswith('.verify.cpp'): steps = [ "%dbg(COMPILED WITH) %{cxx} %s %{flags} %{compile_flags} -fsyntax-only %{verify}" ] return self._executeShTest(test, litConfig, steps) elif filename.endswith('.pass.cpp') or filename.endswith('.pass.mm'): steps = [ "%dbg(COMPILED WITH) %{cxx} %s %{flags} %{compile_flags} %{link_flags} -o %t.exe", "%dbg(EXECUTED AS) %{exec} %t.exe" ] return self._executeShTest(test, litConfig, steps, fileDependencies=['%t.exe']) # for backwards compatibility with the test suite. elif filename.endswith('.fail.cpp'): if self._supportsVerify(test, litConfig): steps = [ "%dbg(COMPILED WITH) %{cxx} %s %{flags} %{compile_flags} -fsyntax-only %{verify}" ] else: steps = [ "%dbg(COMPILED WITH) ! %{cxx} %s %{flags} %{compile_flags} -fsyntax-only" ] return self._executeShTest(test, litConfig, steps) else: return lit.Test.Result(lit.Test.UNRESOLVED, "Unknown test suffix for '{}'".format(filename)) # Utility function to add compile flags in lit.local.cfg files. def addCompileFlags(self, config, *flags): string = ' '.join(flags) config.substitutions = [(s, x + ' ' + string) if s == '%{compile_flags}' else (s, x) for (s, x) in config.substitutions] # Modified version of lit.TestRunner.executeShTest to handle custom parsers correctly. def _executeShTest(self, test, litConfig, steps, fileDependencies=None): if test.config.unsupported: return lit.Test.Result(lit.Test.UNSUPPORTED, 'Test is unsupported') # Get the default substitutions tmpDir, tmpBase = lit.TestRunner.getTempPaths(test) useExternalSh = True substitutions = lit.TestRunner.getDefaultSubstitutions(test, tmpDir, tmpBase, normalize_slashes=useExternalSh) # Add the %{build} and %{run} convenience substitutions substitutions.append(('%{build}', '%{cxx} %s %{flags} %{compile_flags} %{link_flags} -o %t.exe')) substitutions.append(('%{run}', '%{exec} %t.exe')) # Add the %{verify} substitution and the verify-support feature if Clang-verify is supported if self._supportsVerify(test, litConfig): test.config.available_features.add('verify-support') substitutions.append(('%{verify}', '-Xclang -verify -Xclang -verify-ignore-unexpected=note -ferror-limit=0')) # Parse the test file, including custom directives additionalCompileFlags = [] fileDependencies = fileDependencies or [] parsers = [ lit.TestRunner.IntegratedTestKeywordParser('FILE_DEPENDENCIES:', lit.TestRunner.ParserKind.LIST, initial_value=fileDependencies), lit.TestRunner.IntegratedTestKeywordParser('ADDITIONAL_COMPILE_FLAGS:', lit.TestRunner.ParserKind.LIST, initial_value=additionalCompileFlags) ] script = list(steps) parsed = lit.TestRunner.parseIntegratedTestScript(test, additional_parsers=parsers, require_script=not script) if isinstance(parsed, lit.Test.Result): return parsed script += parsed # Add compile flags specified with ADDITIONAL_COMPILE_FLAGS. substitutions = [(s, x + ' ' + ' '.join(additionalCompileFlags)) if s == '%{compile_flags}' else (s, x) for (s, x) in substitutions] # Perform substitutions inside FILE_DEPENDENCIES lines (or injected dependencies). # This allows using variables like %t in file dependencies. Also note that we really # need to resolve %{file_dependencies} now, because otherwise we won't be able to fileDependencies = lit.TestRunner.applySubstitutions(fileDependencies, substitutions, recursion_limit=test.config.recursiveExpansionLimit) testDir = os.path.dirname(test.getSourcePath()) fileDependencies = [f if os.path.isabs(f) else os.path.join(testDir, f) for f in fileDependencies] substitutions.append(('%{file_dependencies}', ' '.join(map(pipes.quote, fileDependencies)))) script = lit.TestRunner.applySubstitutions(script, substitutions, recursion_limit=test.config.recursiveExpansionLimit) if litConfig.noExecute: return lit.Test.Result(lit.Test.PASS) else: return lit.TestRunner._runShTest(test, litConfig, useExternalSh, script, tmpBase)

true

f704b9fd1df872c794b4f8b835d03462af5fb8c8

3,282

py

Python

UpWork_Projects/Will Farell_Spiders/innerwest/innerwest/settings.py

SurendraTamang/Web-Scrapping

2bb60cce9010b4b68f5c11bf295940832bb5df50

[ "MIT" ]

null

UpWork_Projects/Will Farell_Spiders/innerwest/innerwest/settings.py

SurendraTamang/Web-Scrapping

2bb60cce9010b4b68f5c11bf295940832bb5df50

[ "MIT" ]

null

UpWork_Projects/Will Farell_Spiders/innerwest/innerwest/settings.py

SurendraTamang/Web-Scrapping

2bb60cce9010b4b68f5c11bf295940832bb5df50

[ "MIT" ]

1

2022-01-18T17:15:51.000Z

# -*- coding: utf-8 -*- # Scrapy settings for innerwest project # # For simplicity, this file contains only settings considered important or # commonly used. You can find more settings consulting the documentation: # # https://docs.scrapy.org/en/latest/topics/settings.html # https://docs.scrapy.org/en/latest/topics/downloader-middleware.html # https://docs.scrapy.org/en/latest/topics/spider-middleware.html BOT_NAME = 'Googlebot' SPIDER_MODULES = ['innerwest.spiders'] NEWSPIDER_MODULE = 'innerwest.spiders' # Crawl responsibly by identifying yourself (and your website) on the user-agent #USER_AGENT = 'innerwest (+http://www.yourdomain.com)' # Obey robots.txt rules ROBOTSTXT_OBEY = False # Configure maximum concurrent requests performed by Scrapy (default: 16) #CONCURRENT_REQUESTS = 32 # Configure a delay for requests for the same website (default: 0) # See https://docs.scrapy.org/en/latest/topics/settings.html#download-delay # See also autothrottle settings and docs #DOWNLOAD_DELAY = 3 # The download delay setting will honor only one of: #CONCURRENT_REQUESTS_PER_DOMAIN = 16 #CONCURRENT_REQUESTS_PER_IP = 16 # Disable cookies (enabled by default) #COOKIES_ENABLED = False # Disable Telnet Console (enabled by default) #TELNETCONSOLE_ENABLED = False # Override the default request headers: #DEFAULT_REQUEST_HEADERS = { # 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', # 'Accept-Language': 'en', #} # Enable or disable spider middlewares # See https://docs.scrapy.org/en/latest/topics/spider-middleware.html #SPIDER_MIDDLEWARES = { # 'innerwest.middlewares.InnerwestSpiderMiddleware': 543, #} # Enable or disable downloader middlewares # See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html DOWNLOADER_MIDDLEWARES = { 'scrapy_selenium.SeleniumMiddleware': 800, } # Enable or disable extensions # See https://docs.scrapy.org/en/latest/topics/extensions.html #EXTENSIONS = { # 'scrapy.extensions.telnet.TelnetConsole': None, #} # Configure item pipelines # See https://docs.scrapy.org/en/latest/topics/item-pipeline.html #ITEM_PIPELINES = { # 'innerwest.pipelines.InnerwestPipeline': 300, #} # Enable and configure the AutoThrottle extension (disabled by default) # See https://docs.scrapy.org/en/latest/topics/autothrottle.html #AUTOTHROTTLE_ENABLED = True # The initial download delay #AUTOTHROTTLE_START_DELAY = 5 # The maximum download delay to be set in case of high latencies #AUTOTHROTTLE_MAX_DELAY = 60 # The average number of requests Scrapy should be sending in parallel to # each remote server #AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0 # Enable showing throttling stats for every response received: #AUTOTHROTTLE_DEBUG = False # Enable and configure HTTP caching (disabled by default) # See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings #HTTPCACHE_ENABLED = True #HTTPCACHE_EXPIRATION_SECS = 0 #HTTPCACHE_DIR = 'httpcache' #HTTPCACHE_IGNORE_HTTP_CODES = [] #HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage' SELENIUM_DRIVER_NAME = 'chrome' SELENIUM_DRIVER_EXECUTABLE_PATH = "../chromedriver" SELENIUM_DRIVER_ARGUMENTS=['--headless'] #SELENIUM_DRIVER_ARGUMENTS=[] FEED_EXPORT_ENCODING = 'utf-8'

34.1875

103

0.777575

BOT_NAME = 'Googlebot' SPIDER_MODULES = ['innerwest.spiders'] NEWSPIDER_MODULE = 'innerwest.spiders' ROBOTSTXT_OBEY = False DOWNLOADER_MIDDLEWARES = { 'scrapy_selenium.SeleniumMiddleware': 800, } 'chrome' SELENIUM_DRIVER_EXECUTABLE_PATH = "../chromedriver" SELENIUM_DRIVER_ARGUMENTS=['--headless'] FEED_EXPORT_ENCODING = 'utf-8'

true

f704bd5d6983569ac694551a583366b858070681

4,151

py

Python

legged_gym/envs/anymal_c/anymal.py

mcx/legged_gym

dd6a6892e54c4f111a203319c05da8dca9595ae1

[ "BSD-3-Clause" ]

159

2021-10-30T02:53:14.000Z

2022-03-31T20:59:20.000Z

legged_gym/envs/anymal_c/anymal.py

mcx/legged_gym

dd6a6892e54c4f111a203319c05da8dca9595ae1

[ "BSD-3-Clause" ]

13

2021-11-01T06:57:56.000Z

2022-03-19T07:16:47.000Z

legged_gym/envs/anymal_c/anymal.py

mcx/legged_gym

dd6a6892e54c4f111a203319c05da8dca9595ae1

[ "BSD-3-Clause" ]

49

2021-11-01T03:00:38.000Z

2022-03-31T21:00:30.000Z

# SPDX-FileCopyrightText: Copyright (c) 2021 NVIDIA CORPORATION & AFFILIATES. All rights reserved. # SPDX-License-Identifier: BSD-3-Clause # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # 1. Redistributions of source code must retain the above copyright notice, this # list of conditions and the following disclaimer. # # 2. Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # # 3. Neither the name of the copyright holder nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE # DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE # FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL # DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR # SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER # CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, # OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # # Copyright (c) 2021 ETH Zurich, Nikita Rudin from time import time import numpy as np import os from isaacgym.torch_utils import * from isaacgym import gymtorch, gymapi, gymutil import torch # from torch.tensor import Tensor from typing import Tuple, Dict from legged_gym.envs import LeggedRobot from legged_gym import LEGGED_GYM_ROOT_DIR from .mixed_terrains.anymal_c_rough_config import AnymalCRoughCfg class Anymal(LeggedRobot): cfg : AnymalCRoughCfg def __init__(self, cfg, sim_params, physics_engine, sim_device, headless): super().__init__(cfg, sim_params, physics_engine, sim_device, headless) # load actuator network if self.cfg.control.use_actuator_network: actuator_network_path = self.cfg.control.actuator_net_file.format(LEGGED_GYM_ROOT_DIR=LEGGED_GYM_ROOT_DIR) self.actuator_network = torch.jit.load(actuator_network_path).to(self.device) def reset_idx(self, env_ids): super().reset_idx(env_ids) # Additionaly empty actuator network hidden states self.sea_hidden_state_per_env[:, env_ids] = 0. self.sea_cell_state_per_env[:, env_ids] = 0. def _init_buffers(self): super()._init_buffers() # Additionally initialize actuator network hidden state tensors self.sea_input = torch.zeros(self.num_envs*self.num_actions, 1, 2, device=self.device, requires_grad=False) self.sea_hidden_state = torch.zeros(2, self.num_envs*self.num_actions, 8, device=self.device, requires_grad=False) self.sea_cell_state = torch.zeros(2, self.num_envs*self.num_actions, 8, device=self.device, requires_grad=False) self.sea_hidden_state_per_env = self.sea_hidden_state.view(2, self.num_envs, self.num_actions, 8) self.sea_cell_state_per_env = self.sea_cell_state.view(2, self.num_envs, self.num_actions, 8) def _compute_torques(self, actions): # Choose between pd controller and actuator network if self.cfg.control.use_actuator_network: with torch.inference_mode(): self.sea_input[:, 0, 0] = (actions * self.cfg.control.action_scale + self.default_dof_pos - self.dof_pos).flatten() self.sea_input[:, 0, 1] = self.dof_vel.flatten() torques, (self.sea_hidden_state[:], self.sea_cell_state[:]) = self.actuator_network(self.sea_input, (self.sea_hidden_state, self.sea_cell_state)) return torques else: # pd controller return super()._compute_torques(actions)

51.246914

161

0.747049

from time import time import numpy as np import os from isaacgym.torch_utils import * from isaacgym import gymtorch, gymapi, gymutil import torch from typing import Tuple, Dict from legged_gym.envs import LeggedRobot from legged_gym import LEGGED_GYM_ROOT_DIR from .mixed_terrains.anymal_c_rough_config import AnymalCRoughCfg class Anymal(LeggedRobot): cfg : AnymalCRoughCfg def __init__(self, cfg, sim_params, physics_engine, sim_device, headless): super().__init__(cfg, sim_params, physics_engine, sim_device, headless) if self.cfg.control.use_actuator_network: actuator_network_path = self.cfg.control.actuator_net_file.format(LEGGED_GYM_ROOT_DIR=LEGGED_GYM_ROOT_DIR) self.actuator_network = torch.jit.load(actuator_network_path).to(self.device) def reset_idx(self, env_ids): super().reset_idx(env_ids) self.sea_hidden_state_per_env[:, env_ids] = 0. self.sea_cell_state_per_env[:, env_ids] = 0. def _init_buffers(self): super()._init_buffers() self.sea_input = torch.zeros(self.num_envs*self.num_actions, 1, 2, device=self.device, requires_grad=False) self.sea_hidden_state = torch.zeros(2, self.num_envs*self.num_actions, 8, device=self.device, requires_grad=False) self.sea_cell_state = torch.zeros(2, self.num_envs*self.num_actions, 8, device=self.device, requires_grad=False) self.sea_hidden_state_per_env = self.sea_hidden_state.view(2, self.num_envs, self.num_actions, 8) self.sea_cell_state_per_env = self.sea_cell_state.view(2, self.num_envs, self.num_actions, 8) def _compute_torques(self, actions): if self.cfg.control.use_actuator_network: with torch.inference_mode(): self.sea_input[:, 0, 0] = (actions * self.cfg.control.action_scale + self.default_dof_pos - self.dof_pos).flatten() self.sea_input[:, 0, 1] = self.dof_vel.flatten() torques, (self.sea_hidden_state[:], self.sea_cell_state[:]) = self.actuator_network(self.sea_input, (self.sea_hidden_state, self.sea_cell_state)) return torques else: return super()._compute_torques(actions)

true

f704bde830d47e285d80fa6723a8d574657b41c6

2,358

py

Python

clcd/rnn_train/RNNConfig.py

felipessalvatore/CLCD

422f9e93d49e4fcfd8048ad5b36898f8713d0370

[ "MIT" ]

4

2020-02-06T19:35:13.000Z

2021-09-04T10:29:11.000Z

clcd/rnn_train/RNNConfig.py

felipessalvatore/CLCD

422f9e93d49e4fcfd8048ad5b36898f8713d0370

[ "MIT" ]

null

clcd/rnn_train/RNNConfig.py

felipessalvatore/CLCD

422f9e93d49e4fcfd8048ad5b36898f8713d0370

[ "MIT" ]

null

class RNNConfig(object): """ Holds logistic regression model hyperparams. :param height: image height :type heights: int :param width: image width :type width: int :param channels: image channels :type channels: int :param batch_size: batch size for training :type batch_size: int :param epochs: number of epochs :type epochs: int :param save_step: when step % save_step == 0, the model parameters are saved. :type save_step: int :param learning_rate: learning rate for the optimizer :type learning_rate: float :param momentum: momentum param :type momentum: float """ def __init__(self, vocab_size=25000, batch_size=32, embedding_dim=100, rnn_dim=100, output_dim=2, layers=1, epochs=8, learning_rate=0.01, momentum=0.2, bidirectional=False, opt="sgd", drop=0): self.vocab_size = vocab_size self.batch_size = batch_size self.embedding_dim = embedding_dim self.rnn_dim = rnn_dim self.layers = layers self.output_dim = output_dim self.epochs = epochs self.learning_rate = learning_rate self.momentum = momentum self.bidirectional = bidirectional self.opt = opt self.drop = drop def __str__(self): """ Get all attributs values. :return: all hyperparams as a string :rtype: str """ status = "vocab_size = {}\n".format(self.vocab_size) status += "batch_size = {}\n".format(self.batch_size) status += "embedding_dim = {}\n".format(self.embedding_dim) status += "rnn_dim = {}\n".format(self.rnn_dim) status += "layers = {}\n".format(self.layers) status += "output_dim = {}\n".format(self.output_dim) status += "epochs = {}\n".format(self.epochs) status += "learning_rate = {}\n".format(self.learning_rate) status += "momentum = {}\n".format(self.momentum) status += "bidirectional = {}\n".format(self.bidirectional) status += "opt = {}\n".format(self.opt) status += "drop = {}\n".format(self.drop) return status

34.173913

67

0.56743

class RNNConfig(object): def __init__(self, vocab_size=25000, batch_size=32, embedding_dim=100, rnn_dim=100, output_dim=2, layers=1, epochs=8, learning_rate=0.01, momentum=0.2, bidirectional=False, opt="sgd", drop=0): self.vocab_size = vocab_size self.batch_size = batch_size self.embedding_dim = embedding_dim self.rnn_dim = rnn_dim self.layers = layers self.output_dim = output_dim self.epochs = epochs self.learning_rate = learning_rate self.momentum = momentum self.bidirectional = bidirectional self.opt = opt self.drop = drop def __str__(self): status = "vocab_size = {}\n".format(self.vocab_size) status += "batch_size = {}\n".format(self.batch_size) status += "embedding_dim = {}\n".format(self.embedding_dim) status += "rnn_dim = {}\n".format(self.rnn_dim) status += "layers = {}\n".format(self.layers) status += "output_dim = {}\n".format(self.output_dim) status += "epochs = {}\n".format(self.epochs) status += "learning_rate = {}\n".format(self.learning_rate) status += "momentum = {}\n".format(self.momentum) status += "bidirectional = {}\n".format(self.bidirectional) status += "opt = {}\n".format(self.opt) status += "drop = {}\n".format(self.drop) return status

true

f704bec2aa2f0c4a7762297c633a64db6aef42a5

231

py

Python

Problems/HackerRank/weird.py

kvlizhvn/Lab_7

e7f7f8da2b5f52a426bb55981594fb8ddcbd127a

[ "MIT" ]

1

2022-02-18T15:44:46.000Z

Problems/HackerRank/weird.py

kvlizhvn/Lab_7

e7f7f8da2b5f52a426bb55981594fb8ddcbd127a

[ "MIT" ]

null

Problems/HackerRank/weird.py

kvlizhvn/Lab_7

e7f7f8da2b5f52a426bb55981594fb8ddcbd127a

[ "MIT" ]

1

2021-03-26T13:55:52.000Z

if __name__ == '__main__': n = int(input().strip()) if n % 2 != 0: print("Weird") elif 2 <= n <= 5: print("Not Weird") elif 6 <= n <= 20: print("Weird") else: print("Not Weird")

19.25

28

0.441558

if __name__ == '__main__': n = int(input().strip()) if n % 2 != 0: print("Weird") elif 2 <= n <= 5: print("Not Weird") elif 6 <= n <= 20: print("Weird") else: print("Not Weird")

true

f704bf1e7920df37e01acd48750fcd9d28294a7e

1,913

py

Python

tools/client.py

gitter-badger/electrs

a797a3864e1215a671b1d6a4efa5268c96d3f55d

[ "MIT" ]

null

tools/client.py

gitter-badger/electrs

a797a3864e1215a671b1d6a4efa5268c96d3f55d

[ "MIT" ]

null

tools/client.py

gitter-badger/electrs

a797a3864e1215a671b1d6a4efa5268c96d3f55d

[ "MIT" ]

null

import hashlib import json import sys from logbook import Logger, StreamHandler from pycoin.coins.bitcoin.networks import BitcoinMainnet import pycoin.ui.key_from_text import pycoin.key import socket script_for_address = BitcoinMainnet.ui.script_for_address log = Logger(__name__) class Connection: def __init__(self, addr): self.s = socket.create_connection(addr) self.f = self.s.makefile('r') self.id = 0 def call(self, method, *args): req = { 'id': self.id, 'method': method, 'params': list(args), } msg = json.dumps(req) + '\n' self.s.sendall(msg.encode('ascii')) return json.loads(self.f.readline()) def main(): conn = Connection(('localhost', 50001)) xpub, = sys.argv[1:] total = 0 k = pycoin.ui.key_from_text.key_from_text(xpub) for change in (0, 1): empty = 0 for n in range(100): address = k.subkey(change).subkey(n).address() script = script_for_address(address) script_hash = hashlib.sha256(script).digest() log.debug('{}', conn.call('blockchain.scripthash.get_history', script_hash[::-1].hex())) reply = conn.call('blockchain.scripthash.get_balance', script_hash[::-1].hex()) result = reply['result'] confirmed = result['confirmed'] / 1e8 total += confirmed if confirmed: log.info('{}/{} => {} has {:11.8f} BTC', change, n, address, confirmed) empty = 0 else: empty += 1 if empty >= 10: break log.info('total balance: {} BTC', total) if __name__ == '__main__': with StreamHandler(sys.stderr, level='INFO').applicationbound(): main()

28.984848

74

0.547308

import hashlib import json import sys from logbook import Logger, StreamHandler from pycoin.coins.bitcoin.networks import BitcoinMainnet import pycoin.ui.key_from_text import pycoin.key import socket script_for_address = BitcoinMainnet.ui.script_for_address log = Logger(__name__) class Connection: def __init__(self, addr): self.s = socket.create_connection(addr) self.f = self.s.makefile('r') self.id = 0 def call(self, method, *args): req = { 'id': self.id, 'method': method, 'params': list(args), } msg = json.dumps(req) + '\n' self.s.sendall(msg.encode('ascii')) return json.loads(self.f.readline()) def main(): conn = Connection(('localhost', 50001)) xpub, = sys.argv[1:] total = 0 k = pycoin.ui.key_from_text.key_from_text(xpub) for change in (0, 1): empty = 0 for n in range(100): address = k.subkey(change).subkey(n).address() script = script_for_address(address) script_hash = hashlib.sha256(script).digest() log.debug('{}', conn.call('blockchain.scripthash.get_history', script_hash[::-1].hex())) reply = conn.call('blockchain.scripthash.get_balance', script_hash[::-1].hex()) result = reply['result'] confirmed = result['confirmed'] / 1e8 total += confirmed if confirmed: log.info('{}/{} => {} has {:11.8f} BTC', change, n, address, confirmed) empty = 0 else: empty += 1 if empty >= 10: break log.info('total balance: {} BTC', total) if __name__ == '__main__': with StreamHandler(sys.stderr, level='INFO').applicationbound(): main()

true

f704c0b981e5c808fcf2d361794e61ab733573e8

400

py

Python

backend/auth/urls.py

Aquinology/Inel_Music

15fe344e9932389df09e6219d2b1ae030cfd1219

[ "MIT" ]

null

backend/auth/urls.py

Aquinology/Inel_Music

15fe344e9932389df09e6219d2b1ae030cfd1219

[ "MIT" ]

null

backend/auth/urls.py

Aquinology/Inel_Music

15fe344e9932389df09e6219d2b1ae030cfd1219

[ "MIT" ]

1

2021-02-18T11:20:34.000Z

from django.urls import path from .views import MyObtainTokenPairView, RegisterView from rest_framework_simplejwt.views import TokenRefreshView urlpatterns = [ path('login/', MyObtainTokenPairView.as_view(), name='token_obtain_pair'), path('login/refresh/', TokenRefreshView.as_view(), name='token_refresh'), path('register/', RegisterView.as_view(), name='auth_register'), ]

36.363636

79

0.75

from django.urls import path from .views import MyObtainTokenPairView, RegisterView from rest_framework_simplejwt.views import TokenRefreshView urlpatterns = [ path('login/', MyObtainTokenPairView.as_view(), name='token_obtain_pair'), path('login/refresh/', TokenRefreshView.as_view(), name='token_refresh'), path('register/', RegisterView.as_view(), name='auth_register'), ]

true

f704c0f9b4488488f3aae9f679bb84275d8e52d4

11,405

py

Python

src/core/src/core_logic/PackageFilter.py

Azure/LinuxPatchExtension

6af622afb4298805bdf47328d6bc66a785f7166b

[ "Apache-2.0" ]

4

2020-06-01T14:36:30.000Z

2021-08-24T16:55:50.000Z

src/core/src/core_logic/PackageFilter.py

Azure/LinuxPatchExtension

6af622afb4298805bdf47328d6bc66a785f7166b

[ "Apache-2.0" ]

34

2020-09-11T17:20:42.000Z

2022-03-28T14:08:44.000Z

src/core/src/core_logic/PackageFilter.py

Azure/LinuxPatchExtension

6af622afb4298805bdf47328d6bc66a785f7166b

[ "Apache-2.0" ]

1

2020-12-28T10:13:20.000Z

# Copyright 2020 Microsoft Corporation # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # Requires Python 2.7+ """Package Filter""" from core.src.bootstrap.Constants import Constants import fnmatch class PackageFilter(object): """implements the Package filtering logic""" def __init__(self, execution_config, composite_logger): self.execution_config = execution_config self.composite_logger = composite_logger # Exclusions - note: version based exclusion is not supported self.global_excluded_packages = self.sanitize_str_to_list(self.execution_config.global_exclusion_list) self.installation_excluded_package_masks = self.execution_config.excluded_package_name_mask_list self.installation_excluded_packages, self.installation_excluded_package_versions = self.get_packages_and_versions_from_masks(self.installation_excluded_package_masks) # Inclusions - note: version based inclusion is optionally supported self.installation_included_package_masks = self.execution_config.included_package_name_mask_list self.installation_included_packages, self.installation_included_package_versions = self.get_packages_and_versions_from_masks(self.installation_included_package_masks) self.installation_included_classifications = [] if self.execution_config.included_classifications_list is None else self.execution_config.included_classifications_list # Neutralize global excluded packages, if customer explicitly includes the package packages_to_clear_from_global = [] for package in self.global_excluded_packages: if self.check_for_explicit_inclusion(package): self.composite_logger.log_debug('Removing package from global exclusion list: ' + package) packages_to_clear_from_global.append(package) self.global_excluded_packages = [x for x in self.global_excluded_packages if x not in packages_to_clear_from_global] # Logging self.composite_logger.log("\nAzure globally-excluded packages: " + str(self.global_excluded_packages)) self.composite_logger.log("Included package classifications: " + ', '.join(self.installation_included_classifications)) self.composite_logger.log("Included packages: " + str(self.installation_included_package_masks)) self.composite_logger.log("Excluded packages: " + str(self.installation_excluded_packages)) if '=' in str(self.installation_excluded_package_masks): self.composite_logger.log_error("\n /!\\ Package exclusions do not support version matching in the filter today. " "Due to this, more packages than expected may be excluded from this update deployment.") # region Inclusion / exclusion presence checks def is_exclusion_list_present(self): """Return true if either Global or patch installation specific exclusion list present""" return bool(self.global_excluded_packages) or bool(self.installation_excluded_packages) def is_inclusion_list_present(self): """Return true if patch installation Inclusion is present""" return bool(self.installation_included_packages) # endregion # region Package exclusion checks def check_for_exclusion(self, one_or_more_packages): """Return true if package need to be excluded""" return self.check_for_match(one_or_more_packages, self.installation_excluded_packages) or \ self.check_for_match(one_or_more_packages, self.global_excluded_packages) # endregion # region Package inclusion checks def check_for_inclusion(self, package, package_version=Constants.DEFAULT_UNSPECIFIED_VALUE): """Return true if package should be included (either because no inclusion list is specified, or because of explicit match)""" return not self.is_inclusion_list_present() or self.check_for_explicit_inclusion(package, package_version) def check_for_explicit_inclusion(self, package, package_version=Constants.DEFAULT_UNSPECIFIED_VALUE): """Return true if package should be included due to an explicit match to the inclusion list """ return self.check_for_match(package, self.installation_included_packages, package_version, self.installation_included_package_versions) # endregion # region Inclusion / exclusion common match checker def check_for_match(self, one_or_more_packages, matching_list, linked_package_versions=Constants.DEFAULT_UNSPECIFIED_VALUE, version_matching_list=Constants.DEFAULT_UNSPECIFIED_VALUE): # type: (str, object, str, object) -> bool # type hinting to remove a warning """Return true if package(s) (with, optionally, linked version(s)) matches the filter list""" if matching_list: if type(one_or_more_packages) is str: return self.single_package_check_for_match(one_or_more_packages, matching_list, linked_package_versions, version_matching_list) else: for index, each_package in enumerate(one_or_more_packages): if type(linked_package_versions) is str: if self.single_package_check_for_match(each_package, matching_list, linked_package_versions, version_matching_list): return True else: if self.single_package_check_for_match(each_package, matching_list, linked_package_versions[index], version_matching_list): return True return False def single_package_check_for_match(self, package, matching_list, package_version, version_matching_list): """Returns true if a single package (optionally, version) matches the filter list""" for index, matching_package in enumerate(matching_list): if fnmatch.fnmatch(package, matching_package) or fnmatch.fnmatch(self.get_product_name_without_arch(package), matching_package): self.composite_logger.log_debug(' - [Package] {0} matches expression {1}'.format(package, matching_package)) if package_version == Constants.DEFAULT_UNSPECIFIED_VALUE or not version_matching_list or version_matching_list[index] == Constants.DEFAULT_UNSPECIFIED_VALUE: self.composite_logger.log_debug(' - [Version] Check skipped as not specified.') return True elif len(version_matching_list) > index and fnmatch.fnmatch(package_version, version_matching_list[index]): self.composite_logger.log_debug(' - [Version] {0} matches expression {1}'.format(package, version_matching_list[index])) return True elif len(version_matching_list) <= index: # This should never happen - something has gone horribly wrong self.composite_logger.log_error(' - [Version] Index error - ({0} of {1})'.format(index + 1, len(version_matching_list))) else: self.composite_logger.log_debug(' - Package {0} (version={1}) was found, but it did not match filter specified for version ({2})'.format(package, package_version, version_matching_list[index])) return False @staticmethod def get_product_name_without_arch(package_name): """Splits out product name without architecture - if this is changed, review YumPackageManager""" architectures = ['.x86_64', '.noarch', '.i686'] for arch in architectures: if package_name.endswith(arch): return package_name.replace(arch, '') return package_name # endregion # region Get included / excluded package masks def get_packages_and_versions_from_masks(self, package_masks): """Return package names and versions""" packages = [] package_versions = [] if package_masks is not None: for index, package_mask in enumerate(package_masks): package_mask_split = str(package_mask).split('=') if len(package_mask_split) == 1: # no version specified packages.append(package_mask_split[0].strip()) package_versions.append(Constants.DEFAULT_UNSPECIFIED_VALUE) elif len(package_mask_split) == 2: # version also specified packages.append(package_mask_split[0].strip()) package_versions.append(package_mask_split[1].strip()) else: # invalid format self.composite_logger.log_warning("Invalid package format: " + str(package_mask) + " [Ignored]") return packages, package_versions @staticmethod def sanitize_str_to_list(string_input): """Strips excess white-space and converts a comma-separated string to a list""" return [] if (string_input is None) else string_input.strip().split(",") # endregion # region Get installation classifications from execution configuration def is_msft_critsec_classification_only(self): return ('Critical' in self.installation_included_classifications or 'Security' in self.installation_included_classifications) and 'Other' not in self.installation_included_classifications def is_msft_other_classification_only(self): return 'Other' in self.installation_included_classifications and not ('Critical' in self.installation_included_classifications or 'Security' in self.installation_included_classifications) def is_msft_all_classification_included(self): """Returns true if all classifications were individually selected *OR* (nothing was selected AND no inclusion list is present) -- business logic""" all_classifications = [key for key in Constants.PackageClassification.__dict__.keys() if not key.startswith('__')] all_classifications_explicitly_selected = bool(len(self.installation_included_classifications) == (len(all_classifications) - 1)) no_classifications_selected = bool(len(self.installation_included_classifications) == 0) only_unclassified_selected = bool('Unclassified' in self.installation_included_classifications and len(self.installation_included_classifications) == 1) return all_classifications_explicitly_selected or ((no_classifications_selected or only_unclassified_selected) and not self.is_inclusion_list_present()) def is_invalid_classification_combination(self): return ('Other' in self.installation_included_classifications and 'Critical' in self.installation_included_classifications and 'Security' not in self.installation_included_classifications) or \ ('Other' in self.installation_included_classifications and 'Security' in self.installation_included_classifications and 'Critical' not in self.installation_included_classifications) # endregion

65.924855

216

0.728979

from core.src.bootstrap.Constants import Constants import fnmatch class PackageFilter(object): def __init__(self, execution_config, composite_logger): self.execution_config = execution_config self.composite_logger = composite_logger self.global_excluded_packages = self.sanitize_str_to_list(self.execution_config.global_exclusion_list) self.installation_excluded_package_masks = self.execution_config.excluded_package_name_mask_list self.installation_excluded_packages, self.installation_excluded_package_versions = self.get_packages_and_versions_from_masks(self.installation_excluded_package_masks) self.installation_included_package_masks = self.execution_config.included_package_name_mask_list self.installation_included_packages, self.installation_included_package_versions = self.get_packages_and_versions_from_masks(self.installation_included_package_masks) self.installation_included_classifications = [] if self.execution_config.included_classifications_list is None else self.execution_config.included_classifications_list packages_to_clear_from_global = [] for package in self.global_excluded_packages: if self.check_for_explicit_inclusion(package): self.composite_logger.log_debug('Removing package from global exclusion list: ' + package) packages_to_clear_from_global.append(package) self.global_excluded_packages = [x for x in self.global_excluded_packages if x not in packages_to_clear_from_global] self.composite_logger.log("\nAzure globally-excluded packages: " + str(self.global_excluded_packages)) self.composite_logger.log("Included package classifications: " + ', '.join(self.installation_included_classifications)) self.composite_logger.log("Included packages: " + str(self.installation_included_package_masks)) self.composite_logger.log("Excluded packages: " + str(self.installation_excluded_packages)) if '=' in str(self.installation_excluded_package_masks): self.composite_logger.log_error("\n /!\\ Package exclusions do not support version matching in the filter today. " "Due to this, more packages than expected may be excluded from this update deployment.") def is_exclusion_list_present(self): return bool(self.global_excluded_packages) or bool(self.installation_excluded_packages) def is_inclusion_list_present(self): return bool(self.installation_included_packages) def check_for_exclusion(self, one_or_more_packages): return self.check_for_match(one_or_more_packages, self.installation_excluded_packages) or \ self.check_for_match(one_or_more_packages, self.global_excluded_packages) def check_for_inclusion(self, package, package_version=Constants.DEFAULT_UNSPECIFIED_VALUE): return not self.is_inclusion_list_present() or self.check_for_explicit_inclusion(package, package_version) def check_for_explicit_inclusion(self, package, package_version=Constants.DEFAULT_UNSPECIFIED_VALUE): return self.check_for_match(package, self.installation_included_packages, package_version, self.installation_included_package_versions) def check_for_match(self, one_or_more_packages, matching_list, linked_package_versions=Constants.DEFAULT_UNSPECIFIED_VALUE, version_matching_list=Constants.DEFAULT_UNSPECIFIED_VALUE): if type(one_or_more_packages) is str: return self.single_package_check_for_match(one_or_more_packages, matching_list, linked_package_versions, version_matching_list) else: for index, each_package in enumerate(one_or_more_packages): if type(linked_package_versions) is str: if self.single_package_check_for_match(each_package, matching_list, linked_package_versions, version_matching_list): return True else: if self.single_package_check_for_match(each_package, matching_list, linked_package_versions[index], version_matching_list): return True return False def single_package_check_for_match(self, package, matching_list, package_version, version_matching_list): for index, matching_package in enumerate(matching_list): if fnmatch.fnmatch(package, matching_package) or fnmatch.fnmatch(self.get_product_name_without_arch(package), matching_package): self.composite_logger.log_debug(' - [Package] {0} matches expression {1}'.format(package, matching_package)) if package_version == Constants.DEFAULT_UNSPECIFIED_VALUE or not version_matching_list or version_matching_list[index] == Constants.DEFAULT_UNSPECIFIED_VALUE: self.composite_logger.log_debug(' - [Version] Check skipped as not specified.') return True elif len(version_matching_list) > index and fnmatch.fnmatch(package_version, version_matching_list[index]): self.composite_logger.log_debug(' - [Version] {0} matches expression {1}'.format(package, version_matching_list[index])) return True elif len(version_matching_list) <= index: self.composite_logger.log_error(' - [Version] Index error - ({0} of {1})'.format(index + 1, len(version_matching_list))) else: self.composite_logger.log_debug(' - Package {0} (version={1}) was found, but it did not match filter specified for version ({2})'.format(package, package_version, version_matching_list[index])) return False @staticmethod def get_product_name_without_arch(package_name): architectures = ['.x86_64', '.noarch', '.i686'] for arch in architectures: if package_name.endswith(arch): return package_name.replace(arch, '') return package_name def get_packages_and_versions_from_masks(self, package_masks): packages = [] package_versions = [] if package_masks is not None: for index, package_mask in enumerate(package_masks): package_mask_split = str(package_mask).split('=') if len(package_mask_split) == 1: packages.append(package_mask_split[0].strip()) package_versions.append(Constants.DEFAULT_UNSPECIFIED_VALUE) elif len(package_mask_split) == 2: packages.append(package_mask_split[0].strip()) package_versions.append(package_mask_split[1].strip()) else: self.composite_logger.log_warning("Invalid package format: " + str(package_mask) + " [Ignored]") return packages, package_versions @staticmethod def sanitize_str_to_list(string_input): return [] if (string_input is None) else string_input.strip().split(",") def is_msft_critsec_classification_only(self): return ('Critical' in self.installation_included_classifications or 'Security' in self.installation_included_classifications) and 'Other' not in self.installation_included_classifications def is_msft_other_classification_only(self): return 'Other' in self.installation_included_classifications and not ('Critical' in self.installation_included_classifications or 'Security' in self.installation_included_classifications) def is_msft_all_classification_included(self): all_classifications = [key for key in Constants.PackageClassification.__dict__.keys() if not key.startswith('__')] all_classifications_explicitly_selected = bool(len(self.installation_included_classifications) == (len(all_classifications) - 1)) no_classifications_selected = bool(len(self.installation_included_classifications) == 0) only_unclassified_selected = bool('Unclassified' in self.installation_included_classifications and len(self.installation_included_classifications) == 1) return all_classifications_explicitly_selected or ((no_classifications_selected or only_unclassified_selected) and not self.is_inclusion_list_present()) def is_invalid_classification_combination(self): return ('Other' in self.installation_included_classifications and 'Critical' in self.installation_included_classifications and 'Security' not in self.installation_included_classifications) or \ ('Other' in self.installation_included_classifications and 'Security' in self.installation_included_classifications and 'Critical' not in self.installation_included_classifications)

true

f704c10fdcec8a9d3f12a9f1b47e921161913390

1,253

py

Python

scripts/activate_amplifier.py

drocx/RPi-Jukebox-RFID

1e211c2f4571a86d97747fe9094a34931de8b7c1

[ "MIT" ]

1

2020-03-24T20:27:07.000Z

scripts/activate_amplifier.py

drocx/RPi-Jukebox-RFID

1e211c2f4571a86d97747fe9094a34931de8b7c1

[ "MIT" ]

null

scripts/activate_amplifier.py

drocx/RPi-Jukebox-RFID

1e211c2f4571a86d97747fe9094a34931de8b7c1

[ "MIT" ]

1

2019-10-06T16:33:52.000Z

#!/usr/bin/python3 import sys from signal import pause import RPi.GPIO as GPIO # script to activate and deactivate an amplifier, power led, etc. using a GPIO # pin on power up / down # see for an example implementation with a PAM8403 digital amplifier # (PAM pin 12 connected to GPIO 26) # https://github.com/MiczFlor/RPi-Jukebox-RFID/wiki/Hardware-Hack-PAM8403-Poweroff # change this value based on which GPIO port the amplifier or other devices are connected to # Flexible Pinout AMP_GPIO = 26 # Classic Pinout # AMP_GPIO = 23 # setup RPi lib to control output pin # we do not cleanup the GPIO because we want the pin low = off after program exit # the resulting warning can be ignored GPIO.setwarnings(False) GPIO.setmode(GPIO.BCM) GPIO.setup(AMP_GPIO, GPIO.OUT) def set_amplifier(status): if status: print("Setting amplifier: ON") GPIO.output(AMP_GPIO, GPIO.HIGH) else: print("Setting amplifier: OFF") GPIO.output(AMP_GPIO, GPIO.LOW) if __name__ == "__main__": try: set_amplifier(True) pause() except KeyboardInterrupt: # turn the relay off set_amplifier(False) print("\nExiting amplifier control\n") # exit the application sys.exit(0)

26.659574

92

0.703113

import sys from signal import pause import RPi.GPIO as GPIO AMP_GPIO = 26 GPIO.setwarnings(False) GPIO.setmode(GPIO.BCM) GPIO.setup(AMP_GPIO, GPIO.OUT) def set_amplifier(status): if status: print("Setting amplifier: ON") GPIO.output(AMP_GPIO, GPIO.HIGH) else: print("Setting amplifier: OFF") GPIO.output(AMP_GPIO, GPIO.LOW) if __name__ == "__main__": try: set_amplifier(True) pause() except KeyboardInterrupt: set_amplifier(False) print("\nExiting amplifier control\n") sys.exit(0)

true

f704c2d7e17f9fd856996531dcce0fe615f4d3e0

755

py

Python

tests/create_config.py

throne/throne-cli

5cc66165b858d9a22c65aac8269523ca1e89cbee

[ "BSD-3-Clause-Clear" ]

4

2021-05-25T05:56:05.000Z

2022-03-24T21:37:04.000Z

tests/create_config.py

throne/throne-cli

5cc66165b858d9a22c65aac8269523ca1e89cbee

[ "BSD-3-Clause-Clear" ]

9

2021-04-22T18:43:48.000Z

2021-09-05T05:11:59.000Z

tests/create_config.py

throne/throne-cli

5cc66165b858d9a22c65aac8269523ca1e89cbee

[ "BSD-3-Clause-Clear" ]

1

2021-04-26T07:07:09.000Z

import os import time from click.testing import CliRunner from bin.throne import cli as throne runner = CliRunner() shodan_key = os.getenv('SHODAN_KEY') throne_user = os.getenv('THRONE_USER') throne_pass = os.getenv('THRONE_PASS') def test_throne_setapi(): print("Testing: throne api setapi") response = runner.invoke(throne, ["api", "setapi", "-u", f"{throne_user}", "-p", f"{throne_pass}"]) assert response.exit_code == 0 assert "Successfully set throne API key." in response.output def test_shodan_setapi(): print("Testing: throne shodan setapi") response = runner.invoke(throne, ["shodan", "setapi"], input=f"{shodan_key}") assert response.exit_code == 0 assert "Successfully set Shodan API key." in response.output

34.318182

103

0.717881

import os import time from click.testing import CliRunner from bin.throne import cli as throne runner = CliRunner() shodan_key = os.getenv('SHODAN_KEY') throne_user = os.getenv('THRONE_USER') throne_pass = os.getenv('THRONE_PASS') def test_throne_setapi(): print("Testing: throne api setapi") response = runner.invoke(throne, ["api", "setapi", "-u", f"{throne_user}", "-p", f"{throne_pass}"]) assert response.exit_code == 0 assert "Successfully set throne API key." in response.output def test_shodan_setapi(): print("Testing: throne shodan setapi") response = runner.invoke(throne, ["shodan", "setapi"], input=f"{shodan_key}") assert response.exit_code == 0 assert "Successfully set Shodan API key." in response.output

true

f704c4328e33a065550916c30d7752a440d3bddf

16,427

py

Python

senlin-7.0.0/senlin/objects/fields.py

scottwedge/OpenStack-Stein

7077d1f602031dace92916f14e36b124f474de15

[ "Apache-2.0" ]

null

senlin-7.0.0/senlin/objects/fields.py

scottwedge/OpenStack-Stein

7077d1f602031dace92916f14e36b124f474de15

[ "Apache-2.0" ]

5

2019-08-14T06:46:03.000Z

2021-12-13T20:01:25.000Z

senlin-7.0.0/senlin/objects/fields.py

scottwedge/OpenStack-Stein

7077d1f602031dace92916f14e36b124f474de15

[ "Apache-2.0" ]

2

2020-03-15T01:24:15.000Z

2020-07-22T20:34:26.000Z

# Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. from oslo_config import cfg from oslo_serialization import jsonutils from oslo_utils import strutils from oslo_utils import uuidutils from oslo_versionedobjects import fields import re import six from senlin.common import consts from senlin.common.i18n import _ CONF = cfg.CONF # Field alias for code readability # BooleanField = fields.BooleanField FlexibleBooleanField = fields.FlexibleBooleanField StringField = fields.StringField IntegerField = fields.IntegerField FloatField = fields.FloatField UUIDField = fields.UUIDField DateTimeField = fields.DateTimeField DictOfStringsField = fields.DictOfStringsField ListOfStringsField = fields.ListOfStringsField ListOfEnumField = fields.ListOfEnumField class Boolean(fields.FieldType): # NOTE: The following definition is much more stricter than the oslo # version. Also note that the treatment of default values here: # we are using the user specified default value when invoking # the 'bool_from_string' until function. def __init__(self, default=False): super(Boolean, self).__init__() self._default = default def coerce(self, obj, attr, value): return strutils.bool_from_string(value, strict=True, default=self._default) def get_schema(self): return {'type': ['boolean']} class NonNegativeInteger(fields.FieldType): # NOTE: This definition is kept because we want the error message from # 'int' conversion to be user friendly. @staticmethod def coerce(obj, attr, value): try: v = int(value) except (TypeError, ValueError): raise ValueError(_("The value for %(attr)s must be an integer: " "'%(value)s'.") % {'attr': attr, 'value': value}) if v < 0: err = _("Value must be >= 0 for field '%s'.") % attr raise ValueError(err) return v def get_schema(self): return { 'type': ['integer', 'string'], 'minimum': 0 } # Senlin has a stricter field checking for object fields. class Object(fields.Object): def get_schema(self): schema = super(Object, self).get_schema() # we are not checking whether self._obj_name is registered, an # exception will be raised anyway if it is not registered. data_key = 'senlin_object.data' schema['properties'][data_key]['additionalProperties'] = False return schema class UUID(fields.FieldType): _PATTERN = (r'^[a-fA-F0-9]{8}-?[a-fA-F0-9]{4}-?[a-fA-F0-9]{4}-?[a-fA-F0-9]' r'{4}-?[a-fA-F0-9]{12}$') @staticmethod def coerce(obj, attr, value): if not uuidutils.is_uuid_like(value): msg = _("The value for %(attr)s is not a valid UUID: '%(value)s'." ) % {'attr': attr, 'value': value} raise ValueError(msg) return str(value) def get_schema(self): return {'type': ['string'], 'pattern': self._PATTERN} class Json(fields.FieldType): def coerce(self, obj, attr, value): if isinstance(value, six.string_types): try: return jsonutils.loads(value) except ValueError: msg = _("The value (%s) is not a valid JSON.") % value raise ValueError(msg) return value def from_primitive(self, obj, attr, value): return self.coerce(obj, attr, value) def to_primitive(self, obj, attr, value): return jsonutils.dumps(value) def stringify(self, value): if isinstance(value, six.string_types): try: return jsonutils.loads(value) except ValueError: raise return str(value) def get_schema(self): return {'type': ['object']} class NotificationPriority(fields.Enum): # The priorities here are derived from oslo_messaging.notify.notifier ALL = consts.NOTIFICATION_PRIORITIES def __init__(self): super(NotificationPriority, self).__init__(self.ALL) class NotificationPhase(fields.Enum): ALL = consts.NOTIFICATION_PHASES def __init__(self): super(NotificationPhase, self).__init__(self.ALL) class Name(fields.String): def __init__(self, min_len=1, max_len=255): super(Name, self).__init__() self.min_len = min_len self.max_len = max_len def coerce(self, obj, attr, value): err = None if len(value) < self.min_len: err = _("The value for the %(attr)s field must be at least " "%(count)d characters long." ) % {'attr': attr, 'count': self.min_len} elif len(value) > self.max_len: err = _("The value for the %(attr)s field must be less than " "%(count)d characters long." ) % {'attr': attr, 'count': self.max_len} else: # NOTE: This is pretty restrictive. We can relax it later when # there are requests to do so regex = re.compile(u'^[a-zA-Z\u4e00-\u9fa5\d\.\_\~-]*$', re.IGNORECASE) if not regex.search(value): err = _("The value for the '%(attr)s' (%(value)s) contains " "illegal characters. It must contain only " "alphanumeric or \"_-.~\" characters and must start " "with letter." ) % {'attr': attr, 'value': value} if err: raise ValueError(err) return super(Name, self).coerce(obj, attr, value) def get_schema(self): return { 'type': ['string'], 'minLength': self.min_len, 'maxLength': self.max_len } class Capacity(fields.Integer): def __init__(self, minimum=0, maximum=None): super(Capacity, self).__init__() CONF.import_opt("max_nodes_per_cluster", "senlin.common.config") if minimum > CONF.max_nodes_per_cluster: err = _("The value of 'minimum' cannot be greater than the global " "constraint (%(m)d).") % {'m': CONF.max_nodes_per_cluster} raise ValueError(err) self.minimum = minimum if maximum is not None: if maximum < minimum: err = _("The value of 'maximum' must be greater than or equal " "to that of the 'minimum' specified.") raise ValueError(err) if maximum > CONF.max_nodes_per_cluster: err = _("The value of 'maximum' cannot be greater than the " "global constraint (%(m)d)." ) % {'m': CONF.max_nodes_per_cluster} raise ValueError(err) self.maximum = maximum else: self.maximum = CONF.max_nodes_per_cluster def coerce(self, obj, attr, value): try: v = int(value) except Exception: raise ValueError(_("The value for %(attr)s must be an integer: " "'%(value)s'.") % {'attr': attr, 'value': value}) if v < self.minimum: raise ValueError(_("The value for the %(a)s field must be greater " "than or equal to %(n)d.") % {'a': attr, 'n': self.minimum}) elif v > self.maximum: raise ValueError(_("The value for the %(a)s field must be less " "than or equal to %(n)d.") % {'a': attr, 'n': self.maximum}) return super(Capacity, self).coerce(obj, attr, v) def get_schema(self): return { 'type': ['integer', 'string'], 'minimum': self.minimum, 'maximum': self.maximum, 'pattern': '^[0-9]*$', } class Sort(fields.String): def __init__(self, valid_keys): super(Sort, self).__init__() self.valid_keys = valid_keys def coerce(self, obj, attr, value): for s in value.split(','): s_key, _sep, s_dir = s.partition(':') err = None if not s_key: err = _("Missing sort key for '%s'.") % attr raise ValueError(err) if s_key not in self.valid_keys: err = _("Unsupported sort key '%(value)s' for '%(attr)s'." ) % {'attr': attr, 'value': s_key} if s_dir and s_dir not in ('asc', 'desc'): err = _("Unsupported sort dir '%(value)s' for '%(attr)s'." ) % {'attr': attr, 'value': s_dir} if err: raise ValueError(err) return super(Sort, self).coerce(obj, attr, value) def get_schema(self): return { 'type': ['string'], } class IdentityList(fields.List): def __init__(self, element_type, min_items=0, unique=True, nullable=False, **kwargs): super(IdentityList, self).__init__(element_type, **kwargs) self.min_items = min_items self.unique_items = unique self.nullable = nullable def coerce(self, obj, attr, value): res = super(IdentityList, self).coerce(obj, attr, value) if len(res) < self.min_items: raise ValueError(_("Value for '%(attr)s' must have at least " "%(num)s item(s).") % {'attr': attr, 'num': self.min_items}) if len(set(res)) != len(res) and self.unique_items: raise ValueError(_("Items for '%(attr)s' must be unique") % {'attr': attr}) return res def get_schema(self): schema = super(IdentityList, self).get_schema() if self.nullable: schema['type'].append('null') schema['minItems'] = self.min_items schema['uniqueItems'] = self.unique_items return schema class BaseEnum(fields.FieldType): # NOTE: We are not basing Enum on String because String is not working # correctly when handling None value. def __init__(self, nullable=False): valid_values = list(self.__class__.ALL) if not valid_values: raise ValueError(_("No list of valid values provided for enum.")) for value in valid_values: if not isinstance(value, six.string_types): raise ValueError(_("Enum field only support string values.")) self._valid_values = list(valid_values) self._nullable = nullable super(BaseEnum, self).__init__() def coerce(self, obj, attr, value): value = six.text_type(value) if value not in self._valid_values: raise ValueError(_("Value '%(value)s' is not acceptable for " "field '%(attr)s'.") % {'value': value, 'attr': attr}) return value def stringify(self, value): if value is None: return None return '\'%s\'' % value class AdjustmentType(BaseEnum): ALL = consts.ADJUSTMENT_TYPES def get_schema(self): return {'type': ['string'], 'enum': self._valid_values} class ClusterActionName(BaseEnum): ALL = consts.CLUSTER_ACTION_NAMES def get_schema(self): return {'type': ['string'], 'enum': self._valid_values} class ClusterStatus(BaseEnum): ALL = consts.CLUSTER_STATUSES class NodeStatus(BaseEnum): ALL = consts.NODE_STATUSES class ActionStatus(BaseEnum): ALL = consts.ACTION_STATUSES class ReceiverType(BaseEnum): ALL = consts.RECEIVER_TYPES def get_schema(self): return {'type': ['string'], 'enum': self._valid_values} class UniqueDict(fields.Dict): def coerce(self, obj, attr, value): res = super(UniqueDict, self).coerce(obj, attr, value) new_nodes = res.values() if len(new_nodes) != len(set(new_nodes)): raise ValueError(_("Map contains duplicated values")) return res # TODO(Qiming): remove this when oslo patch is released # https://review.openstack.org/#/c/360095 class NonNegativeIntegerField(fields.AutoTypedField): AUTO_TYPE = NonNegativeInteger() class BooleanField(fields.AutoTypedField): AUTO_TYPE = Boolean() # An override to the oslo.versionedobjects version so that we are using # our own Object definition. class ObjectField(fields.AutoTypedField): def __init__(self, objtype, subclasses=False, **kwargs): self.AUTO_TYPE = Object(objtype, subclasses) self.objname = objtype super(ObjectField, self).__init__(**kwargs) class JsonField(fields.AutoTypedField): AUTO_TYPE = Json() class ListField(fields.AutoTypedField): AUTO_TYPE = fields.List(fields.FieldType()) class NotificationPriorityField(fields.BaseEnumField): AUTO_TYPE = NotificationPriority() class NotificationPhaseField(fields.BaseEnumField): AUTO_TYPE = NotificationPhase() class NameField(fields.AutoTypedField): AUTO_TYPE = Name() class UUIDField(fields.AutoTypedField): AUTO_TYPE = UUID() class CapacityField(fields.AutoTypedField): AUTO_TYPE = None def __init__(self, nullable=False, default=None, minimum=0, maximum=None): self.AUTO_TYPE = Capacity(minimum=minimum, maximum=maximum) super(CapacityField, self).__init__(nullable=nullable, default=default) class SortField(fields.AutoTypedField): AUTO_TYPE = None def __init__(self, valid_keys, nullable=False, default=None): self.AUTO_TYPE = Sort(valid_keys) super(SortField, self).__init__(nullable=nullable, default=default) class IdentityListField(fields.AutoTypedField): AUTO_TYPE = None def __init__(self, min_items=0, unique=True, nullable=False, default=None): if default is None: default = [] self.AUTO_TYPE = IdentityList(fields.String(), min_items=min_items, unique=unique) super(IdentityListField, self).__init__(nullable=nullable, default=default) class AdjustmentTypeField(fields.AutoTypedField): AUTO_TYPE = None def __init__(self, **kwargs): nullable = kwargs.get('nullable', False) self.AUTO_TYPE = AdjustmentType(nullable=nullable) super(AdjustmentTypeField, self).__init__(**kwargs) class ClusterActionNameField(fields.AutoTypedField): AUTO_TYPE = None def __init__(self, **kwargs): nullable = kwargs.get('nullable', False) self.AUTO_TYPE = ClusterActionName(nullable=nullable) super(ClusterActionNameField, self).__init__(**kwargs) class ClusterStatusField(fields.AutoTypedField): AUTO_TYPE = ClusterStatus class NodeStatusField(fields.AutoTypedField): AUTO_TYPE = NodeStatus class ActionStatusField(fields.AutoTypedField): AUTO_TYPE = ActionStatus class ReceiverTypeField(fields.AutoTypedField): AUTO_TYPE = None def __init__(self, **kwargs): nullable = kwargs.get('nullable', False) self.AUTO_TYPE = ReceiverType(nullable=nullable) super(ReceiverTypeField, self).__init__(**kwargs) class NodeReplaceMapField(fields.AutoTypedField): AUTO_TYPE = UniqueDict(fields.String()) class CustomListField(ListField): def __init__(self, attr_name, **kwargs): self.attr_name = attr_name super(CustomListField, self).__init__(**kwargs) def coerce(self, obj, attr, value): objs = super(CustomListField, self).coerce(obj, attr, value) custom_list = [] for i in objs: custom_list.append(getattr(i, self.attr_name)) return custom_list

30.647388

79

0.603397

from oslo_config import cfg from oslo_serialization import jsonutils from oslo_utils import strutils from oslo_utils import uuidutils from oslo_versionedobjects import fields import re import six from senlin.common import consts from senlin.common.i18n import _ CONF = cfg.CONF FlexibleBooleanField = fields.FlexibleBooleanField StringField = fields.StringField IntegerField = fields.IntegerField FloatField = fields.FloatField UUIDField = fields.UUIDField DateTimeField = fields.DateTimeField DictOfStringsField = fields.DictOfStringsField ListOfStringsField = fields.ListOfStringsField ListOfEnumField = fields.ListOfEnumField class Boolean(fields.FieldType): def __init__(self, default=False): super(Boolean, self).__init__() self._default = default def coerce(self, obj, attr, value): return strutils.bool_from_string(value, strict=True, default=self._default) def get_schema(self): return {'type': ['boolean']} class NonNegativeInteger(fields.FieldType): @staticmethod def coerce(obj, attr, value): try: v = int(value) except (TypeError, ValueError): raise ValueError(_("The value for %(attr)s must be an integer: " "'%(value)s'.") % {'attr': attr, 'value': value}) if v < 0: err = _("Value must be >= 0 for field '%s'.") % attr raise ValueError(err) return v def get_schema(self): return { 'type': ['integer', 'string'], 'minimum': 0 } class Object(fields.Object): def get_schema(self): schema = super(Object, self).get_schema() data_key = 'senlin_object.data' schema['properties'][data_key]['additionalProperties'] = False return schema class UUID(fields.FieldType): _PATTERN = (r'^[a-fA-F0-9]{8}-?[a-fA-F0-9]{4}-?[a-fA-F0-9]{4}-?[a-fA-F0-9]' r'{4}-?[a-fA-F0-9]{12}$') @staticmethod def coerce(obj, attr, value): if not uuidutils.is_uuid_like(value): msg = _("The value for %(attr)s is not a valid UUID: '%(value)s'." ) % {'attr': attr, 'value': value} raise ValueError(msg) return str(value) def get_schema(self): return {'type': ['string'], 'pattern': self._PATTERN} class Json(fields.FieldType): def coerce(self, obj, attr, value): if isinstance(value, six.string_types): try: return jsonutils.loads(value) except ValueError: msg = _("The value (%s) is not a valid JSON.") % value raise ValueError(msg) return value def from_primitive(self, obj, attr, value): return self.coerce(obj, attr, value) def to_primitive(self, obj, attr, value): return jsonutils.dumps(value) def stringify(self, value): if isinstance(value, six.string_types): try: return jsonutils.loads(value) except ValueError: raise return str(value) def get_schema(self): return {'type': ['object']} class NotificationPriority(fields.Enum): ALL = consts.NOTIFICATION_PRIORITIES def __init__(self): super(NotificationPriority, self).__init__(self.ALL) class NotificationPhase(fields.Enum): ALL = consts.NOTIFICATION_PHASES def __init__(self): super(NotificationPhase, self).__init__(self.ALL) class Name(fields.String): def __init__(self, min_len=1, max_len=255): super(Name, self).__init__() self.min_len = min_len self.max_len = max_len def coerce(self, obj, attr, value): err = None if len(value) < self.min_len: err = _("The value for the %(attr)s field must be at least " "%(count)d characters long." ) % {'attr': attr, 'count': self.min_len} elif len(value) > self.max_len: err = _("The value for the %(attr)s field must be less than " "%(count)d characters long." ) % {'attr': attr, 'count': self.max_len} else: regex = re.compile(u'^[a-zA-Z\u4e00-\u9fa5\d\.\_\~-]*$', re.IGNORECASE) if not regex.search(value): err = _("The value for the '%(attr)s' (%(value)s) contains " "illegal characters. It must contain only " "alphanumeric or \"_-.~\" characters and must start " "with letter." ) % {'attr': attr, 'value': value} if err: raise ValueError(err) return super(Name, self).coerce(obj, attr, value) def get_schema(self): return { 'type': ['string'], 'minLength': self.min_len, 'maxLength': self.max_len } class Capacity(fields.Integer): def __init__(self, minimum=0, maximum=None): super(Capacity, self).__init__() CONF.import_opt("max_nodes_per_cluster", "senlin.common.config") if minimum > CONF.max_nodes_per_cluster: err = _("The value of 'minimum' cannot be greater than the global " "constraint (%(m)d).") % {'m': CONF.max_nodes_per_cluster} raise ValueError(err) self.minimum = minimum if maximum is not None: if maximum < minimum: err = _("The value of 'maximum' must be greater than or equal " "to that of the 'minimum' specified.") raise ValueError(err) if maximum > CONF.max_nodes_per_cluster: err = _("The value of 'maximum' cannot be greater than the " "global constraint (%(m)d)." ) % {'m': CONF.max_nodes_per_cluster} raise ValueError(err) self.maximum = maximum else: self.maximum = CONF.max_nodes_per_cluster def coerce(self, obj, attr, value): try: v = int(value) except Exception: raise ValueError(_("The value for %(attr)s must be an integer: " "'%(value)s'.") % {'attr': attr, 'value': value}) if v < self.minimum: raise ValueError(_("The value for the %(a)s field must be greater " "than or equal to %(n)d.") % {'a': attr, 'n': self.minimum}) elif v > self.maximum: raise ValueError(_("The value for the %(a)s field must be less " "than or equal to %(n)d.") % {'a': attr, 'n': self.maximum}) return super(Capacity, self).coerce(obj, attr, v) def get_schema(self): return { 'type': ['integer', 'string'], 'minimum': self.minimum, 'maximum': self.maximum, 'pattern': '^[0-9]*$', } class Sort(fields.String): def __init__(self, valid_keys): super(Sort, self).__init__() self.valid_keys = valid_keys def coerce(self, obj, attr, value): for s in value.split(','): s_key, _sep, s_dir = s.partition(':') err = None if not s_key: err = _("Missing sort key for '%s'.") % attr raise ValueError(err) if s_key not in self.valid_keys: err = _("Unsupported sort key '%(value)s' for '%(attr)s'." ) % {'attr': attr, 'value': s_key} if s_dir and s_dir not in ('asc', 'desc'): err = _("Unsupported sort dir '%(value)s' for '%(attr)s'." ) % {'attr': attr, 'value': s_dir} if err: raise ValueError(err) return super(Sort, self).coerce(obj, attr, value) def get_schema(self): return { 'type': ['string'], } class IdentityList(fields.List): def __init__(self, element_type, min_items=0, unique=True, nullable=False, **kwargs): super(IdentityList, self).__init__(element_type, **kwargs) self.min_items = min_items self.unique_items = unique self.nullable = nullable def coerce(self, obj, attr, value): res = super(IdentityList, self).coerce(obj, attr, value) if len(res) < self.min_items: raise ValueError(_("Value for '%(attr)s' must have at least " "%(num)s item(s).") % {'attr': attr, 'num': self.min_items}) if len(set(res)) != len(res) and self.unique_items: raise ValueError(_("Items for '%(attr)s' must be unique") % {'attr': attr}) return res def get_schema(self): schema = super(IdentityList, self).get_schema() if self.nullable: schema['type'].append('null') schema['minItems'] = self.min_items schema['uniqueItems'] = self.unique_items return schema class BaseEnum(fields.FieldType): def __init__(self, nullable=False): valid_values = list(self.__class__.ALL) if not valid_values: raise ValueError(_("No list of valid values provided for enum.")) for value in valid_values: if not isinstance(value, six.string_types): raise ValueError(_("Enum field only support string values.")) self._valid_values = list(valid_values) self._nullable = nullable super(BaseEnum, self).__init__() def coerce(self, obj, attr, value): value = six.text_type(value) if value not in self._valid_values: raise ValueError(_("Value '%(value)s' is not acceptable for " "field '%(attr)s'.") % {'value': value, 'attr': attr}) return value def stringify(self, value): if value is None: return None return '\'%s\'' % value class AdjustmentType(BaseEnum): ALL = consts.ADJUSTMENT_TYPES def get_schema(self): return {'type': ['string'], 'enum': self._valid_values} class ClusterActionName(BaseEnum): ALL = consts.CLUSTER_ACTION_NAMES def get_schema(self): return {'type': ['string'], 'enum': self._valid_values} class ClusterStatus(BaseEnum): ALL = consts.CLUSTER_STATUSES class NodeStatus(BaseEnum): ALL = consts.NODE_STATUSES class ActionStatus(BaseEnum): ALL = consts.ACTION_STATUSES class ReceiverType(BaseEnum): ALL = consts.RECEIVER_TYPES def get_schema(self): return {'type': ['string'], 'enum': self._valid_values} class UniqueDict(fields.Dict): def coerce(self, obj, attr, value): res = super(UniqueDict, self).coerce(obj, attr, value) new_nodes = res.values() if len(new_nodes) != len(set(new_nodes)): raise ValueError(_("Map contains duplicated values")) return res NegativeIntegerField(fields.AutoTypedField): AUTO_TYPE = NonNegativeInteger() class BooleanField(fields.AutoTypedField): AUTO_TYPE = Boolean() class ObjectField(fields.AutoTypedField): def __init__(self, objtype, subclasses=False, **kwargs): self.AUTO_TYPE = Object(objtype, subclasses) self.objname = objtype super(ObjectField, self).__init__(**kwargs) class JsonField(fields.AutoTypedField): AUTO_TYPE = Json() class ListField(fields.AutoTypedField): AUTO_TYPE = fields.List(fields.FieldType()) class NotificationPriorityField(fields.BaseEnumField): AUTO_TYPE = NotificationPriority() class NotificationPhaseField(fields.BaseEnumField): AUTO_TYPE = NotificationPhase() class NameField(fields.AutoTypedField): AUTO_TYPE = Name() class UUIDField(fields.AutoTypedField): AUTO_TYPE = UUID() class CapacityField(fields.AutoTypedField): AUTO_TYPE = None def __init__(self, nullable=False, default=None, minimum=0, maximum=None): self.AUTO_TYPE = Capacity(minimum=minimum, maximum=maximum) super(CapacityField, self).__init__(nullable=nullable, default=default) class SortField(fields.AutoTypedField): AUTO_TYPE = None def __init__(self, valid_keys, nullable=False, default=None): self.AUTO_TYPE = Sort(valid_keys) super(SortField, self).__init__(nullable=nullable, default=default) class IdentityListField(fields.AutoTypedField): AUTO_TYPE = None def __init__(self, min_items=0, unique=True, nullable=False, default=None): if default is None: default = [] self.AUTO_TYPE = IdentityList(fields.String(), min_items=min_items, unique=unique) super(IdentityListField, self).__init__(nullable=nullable, default=default) class AdjustmentTypeField(fields.AutoTypedField): AUTO_TYPE = None def __init__(self, **kwargs): nullable = kwargs.get('nullable', False) self.AUTO_TYPE = AdjustmentType(nullable=nullable) super(AdjustmentTypeField, self).__init__(**kwargs) class ClusterActionNameField(fields.AutoTypedField): AUTO_TYPE = None def __init__(self, **kwargs): nullable = kwargs.get('nullable', False) self.AUTO_TYPE = ClusterActionName(nullable=nullable) super(ClusterActionNameField, self).__init__(**kwargs) class ClusterStatusField(fields.AutoTypedField): AUTO_TYPE = ClusterStatus class NodeStatusField(fields.AutoTypedField): AUTO_TYPE = NodeStatus class ActionStatusField(fields.AutoTypedField): AUTO_TYPE = ActionStatus class ReceiverTypeField(fields.AutoTypedField): AUTO_TYPE = None def __init__(self, **kwargs): nullable = kwargs.get('nullable', False) self.AUTO_TYPE = ReceiverType(nullable=nullable) super(ReceiverTypeField, self).__init__(**kwargs) class NodeReplaceMapField(fields.AutoTypedField): AUTO_TYPE = UniqueDict(fields.String()) class CustomListField(ListField): def __init__(self, attr_name, **kwargs): self.attr_name = attr_name super(CustomListField, self).__init__(**kwargs) def coerce(self, obj, attr, value): objs = super(CustomListField, self).coerce(obj, attr, value) custom_list = [] for i in objs: custom_list.append(getattr(i, self.attr_name)) return custom_list

true

f704c46b173fb645449a9542a94234ae033a96b3

5,712

py

Python

view/__init__.py

sadlll/ablog

d04b532751c297fe9cd25563d08f48e8aaee7f48

[ "Apache-2.0" ]

null

view/__init__.py

sadlll/ablog

d04b532751c297fe9cd25563d08f48e8aaee7f48

[ "Apache-2.0" ]

null

view/__init__.py

sadlll/ablog

d04b532751c297fe9cd25563d08f48e8aaee7f48

[ "Apache-2.0" ]

1

2020-09-14T07:09:34.000Z

# coding:utf-8 import json import random import string import tornado.web import config from lib.jsdict import JsDict from model.user import User # route class Route(object): urls = [] def __call__(self, url, name=None): def _(cls): self.urls.append(tornado.web.URLSpec(url, cls, name=name)) return cls return _ route = Route() # 模板 def get_lookup_mako(): import mako.lookup _lookup = mako.lookup.TemplateLookup( directories=['./templates'], module_directory='/tmp/mako' + ''.join(random.sample(string.ascii_letters + string.digits, 8)), input_encoding='utf-8', ) return _lookup def get_lookup_jinja2(_globals={}, extensions=[]): from jinja2 import Environment, FileSystemLoader _lookup = Environment( loader=FileSystemLoader(['./templates'], encoding='utf-8'), extensions=extensions ) # mako 没有全局变量特性，这里为了一致性 jinjia 向 mako 妥协 #_lookup.globals['url_for'] = url_for _lookup.globals['config'] = config _lookup.globals.update(_globals) return _lookup if config.TEMPLATE == 'mako': lookup = get_lookup_mako() elif config.TEMPLATE == 'jinja2': lookup = get_lookup_jinja2() else: lookup = None # Session class SimpleSession(object): def __init__(self, request): self._request = request self._data = self.load() def __delitem__(self, key): del self._data[key] def __getitem__(self, key): return self._data.get(key) def __setitem__(self, key, value): self._data[key] = value def load(self): _s = self._request.get_secure_cookie('session') or '{}' try: _s = _s.decode('utf-8') # fix:py2 except: pass return json.loads(_s) def flush(self): self._request.set_secure_cookie('session', json.dumps(self._data)) # 消息闪现支持 class Messages(object): MESSAGE_LEVEL = JsDict( DEBUG=10, INFO=20, SUCCESS=25, WARNING=30, ERROR=40, ) DEFAULT_TAGS = { MESSAGE_LEVEL.DEBUG: 'debug', MESSAGE_LEVEL.INFO: 'info', MESSAGE_LEVEL.SUCCESS: 'success', MESSAGE_LEVEL.WARNING: 'warning', MESSAGE_LEVEL.ERROR: 'error', } def __init__(self): self.messages = [] def _add_message(self, level, message): self.messages.append([level, message]) def debug(self, message): self._add_message(self.MESSAGE_LEVEL.DEBUG, message) def info(self, message): self._add_message(self.MESSAGE_LEVEL.INFO, message) def success(self, message): self._add_message(self.MESSAGE_LEVEL.SUCCESS, message) def warning(self, message): self._add_message(self.MESSAGE_LEVEL.WARNING, message) def error(self, message): self._add_message(self.MESSAGE_LEVEL.ERROR, message) class View(tornado.web.RequestHandler): def render(self, fn=None, **kwargs): if not fn: fn = ('/%s/%s.html' % ( '/'.join(self.__module__.split('.')[1:-1]), self.__class__.__name__.lower() )).replace(r'//', r'/') kwargs.update({ 'req': self, 'config': config, 'static': self.static_url, 'url_for': self.reverse_url, 'get_messages': self.get_messages, 'xsrf_token': self.xsrf_form_html(), 'csrf_token': self.xsrf_form_html(), }) if lookup: tmpl = lookup.get_template(fn) self.finish(tmpl.render(**kwargs)) else: if fn.startswith('/'): fn = '.' + fn super(View, self).render(fn, config=config, **kwargs) def get_messages(self): msg_lst = self.messages.messages + (self.session['_messages'] or []) _messages = [] for i in msg_lst: tag, txt = i try: txt = txt.decode('utf-8') # 为py2做个转换 except: pass _messages.append(JsDict(tag=Messages.DEFAULT_TAGS[tag], txt=txt)) self.messages.messages = [] return _messages def initialize(self): self.messages = Messages() self.session = SimpleSession(self) super(View, self).initialize() def flush(self, include_footers=False, callback=None): self.session['_messages'] = self.messages.messages self.session.flush() super(View, self).flush(include_footers, callback) def current_user(self): key = self.get_secure_cookie('u') return User.get_by_key(key) def is_admin(self): user = self.current_user() if user and user.is_admin(): return user class LoginView(View): def prepare(self): if not self.current_user(): self.redirect(url_for('signin')) class NoLoginView(View): def prepare(self): if self.current_user(): self.messages.error("您已登陆，请先退出") self.redirect(url_for('index')) class AjaxView(View): def check_xsrf_cookie(self): # useless for json request pass def prepare(self): self.set_header('Content-Type', 'application/json') super(AjaxView, self).prepare() class AjaxLoginView(LoginView): def check_xsrf_cookie(self): # useless for json request pass def prepare(self): self.set_header('Content-Type', 'application/json') super(AjaxLoginView, self).prepare() # sugar def url_for(name, *args): return config.app.reverse_url(name, *args) def page_title(*args): no_blank = lambda x: x is not None and x != '' return ' » '.join(list(filter(no_blank, args)) + [config.TITLE])

25.386667

107

0.605042

import json import random import string import tornado.web import config from lib.jsdict import JsDict from model.user import User class Route(object): urls = [] def __call__(self, url, name=None): def _(cls): self.urls.append(tornado.web.URLSpec(url, cls, name=name)) return cls return _ route = Route() def get_lookup_mako(): import mako.lookup _lookup = mako.lookup.TemplateLookup( directories=['./templates'], module_directory='/tmp/mako' + ''.join(random.sample(string.ascii_letters + string.digits, 8)), input_encoding='utf-8', ) return _lookup def get_lookup_jinja2(_globals={}, extensions=[]): from jinja2 import Environment, FileSystemLoader _lookup = Environment( loader=FileSystemLoader(['./templates'], encoding='utf-8'), extensions=extensions ) _lookup.globals['config'] = config _lookup.globals.update(_globals) return _lookup if config.TEMPLATE == 'mako': lookup = get_lookup_mako() elif config.TEMPLATE == 'jinja2': lookup = get_lookup_jinja2() else: lookup = None class SimpleSession(object): def __init__(self, request): self._request = request self._data = self.load() def __delitem__(self, key): del self._data[key] def __getitem__(self, key): return self._data.get(key) def __setitem__(self, key, value): self._data[key] = value def load(self): _s = self._request.get_secure_cookie('session') or '{}' try: _s = _s.decode('utf-8') except: pass return json.loads(_s) def flush(self): self._request.set_secure_cookie('session', json.dumps(self._data)) class Messages(object): MESSAGE_LEVEL = JsDict( DEBUG=10, INFO=20, SUCCESS=25, WARNING=30, ERROR=40, ) DEFAULT_TAGS = { MESSAGE_LEVEL.DEBUG: 'debug', MESSAGE_LEVEL.INFO: 'info', MESSAGE_LEVEL.SUCCESS: 'success', MESSAGE_LEVEL.WARNING: 'warning', MESSAGE_LEVEL.ERROR: 'error', } def __init__(self): self.messages = [] def _add_message(self, level, message): self.messages.append([level, message]) def debug(self, message): self._add_message(self.MESSAGE_LEVEL.DEBUG, message) def info(self, message): self._add_message(self.MESSAGE_LEVEL.INFO, message) def success(self, message): self._add_message(self.MESSAGE_LEVEL.SUCCESS, message) def warning(self, message): self._add_message(self.MESSAGE_LEVEL.WARNING, message) def error(self, message): self._add_message(self.MESSAGE_LEVEL.ERROR, message) class View(tornado.web.RequestHandler): def render(self, fn=None, **kwargs): if not fn: fn = ('/%s/%s.html' % ( '/'.join(self.__module__.split('.')[1:-1]), self.__class__.__name__.lower() )).replace(r'//', r'/') kwargs.update({ 'req': self, 'config': config, 'static': self.static_url, 'url_for': self.reverse_url, 'get_messages': self.get_messages, 'xsrf_token': self.xsrf_form_html(), 'csrf_token': self.xsrf_form_html(), }) if lookup: tmpl = lookup.get_template(fn) self.finish(tmpl.render(**kwargs)) else: if fn.startswith('/'): fn = '.' + fn super(View, self).render(fn, config=config, **kwargs) def get_messages(self): msg_lst = self.messages.messages + (self.session['_messages'] or []) _messages = [] for i in msg_lst: tag, txt = i try: txt = txt.decode('utf-8') except: pass _messages.append(JsDict(tag=Messages.DEFAULT_TAGS[tag], txt=txt)) self.messages.messages = [] return _messages def initialize(self): self.messages = Messages() self.session = SimpleSession(self) super(View, self).initialize() def flush(self, include_footers=False, callback=None): self.session['_messages'] = self.messages.messages self.session.flush() super(View, self).flush(include_footers, callback) def current_user(self): key = self.get_secure_cookie('u') return User.get_by_key(key) def is_admin(self): user = self.current_user() if user and user.is_admin(): return user class LoginView(View): def prepare(self): if not self.current_user(): self.redirect(url_for('signin')) class NoLoginView(View): def prepare(self): if self.current_user(): self.messages.error("您已登陆，请先退出") self.redirect(url_for('index')) class AjaxView(View): def check_xsrf_cookie(self): pass def prepare(self): self.set_header('Content-Type', 'application/json') super(AjaxView, self).prepare() class AjaxLoginView(LoginView): def check_xsrf_cookie(self): pass def prepare(self): self.set_header('Content-Type', 'application/json') super(AjaxLoginView, self).prepare() def url_for(name, *args): return config.app.reverse_url(name, *args) def page_title(*args): no_blank = lambda x: x is not None and x != '' return ' » '.join(list(filter(no_blank, args)) + [config.TITLE])

true

f704c490c9753e311455f361ab6740be9fccc6f7

6,062

py

Python

sdks/python/apache_beam/coders/standard_coders_test.py

bschell/beam

5533acff51cf6157d62a63c60eb3f074f1958df5

[ "Apache-2.0" ]

1

2018-12-03T09:37:01.000Z

sdks/python/apache_beam/coders/standard_coders_test.py

bschell/beam

5533acff51cf6157d62a63c60eb3f074f1958df5

[ "Apache-2.0" ]

2

2018-09-09T16:51:47.000Z

2018-09-16T15:55:50.000Z

sdks/python/apache_beam/coders/standard_coders_test.py

bschell/beam

5533acff51cf6157d62a63c60eb3f074f1958df5

[ "Apache-2.0" ]

null

# # Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # """Unit tests for coders that must be consistent across all Beam SDKs. """ from __future__ import absolute_import from __future__ import print_function import json import logging import os.path import sys import unittest from builtins import map import yaml from apache_beam.coders import coder_impl from apache_beam.coders import coders from apache_beam.transforms import window from apache_beam.transforms.window import IntervalWindow from apache_beam.utils import windowed_value from apache_beam.utils.timestamp import Timestamp STANDARD_CODERS_YAML = os.path.join( os.path.dirname(__file__), '..', 'testing', 'data', 'standard_coders.yaml') def _load_test_cases(test_yaml): """Load test data from yaml file and return an iterable of test cases. See ``standard_coders.yaml`` for more details. """ if not os.path.exists(test_yaml): raise ValueError('Could not find the test spec: %s' % test_yaml) for ix, spec in enumerate(yaml.load_all(open(test_yaml))): spec['index'] = ix name = spec.get('name', spec['coder']['urn'].split(':')[-2]) yield [name, spec] class StandardCodersTest(unittest.TestCase): _urn_to_coder_class = { 'beam:coder:bytes:v1': coders.BytesCoder, 'beam:coder:varint:v1': coders.VarIntCoder, 'beam:coder:kv:v1': lambda k, v: coders.TupleCoder((k, v)), 'beam:coder:interval_window:v1': coders.IntervalWindowCoder, 'beam:coder:iterable:v1': lambda t: coders.IterableCoder(t), 'beam:coder:global_window:v1': coders.GlobalWindowCoder, 'beam:coder:windowed_value:v1': lambda v, w: coders.WindowedValueCoder(v, w) } _urn_to_json_value_parser = { 'beam:coder:bytes:v1': lambda x: x, 'beam:coder:varint:v1': lambda x: x, 'beam:coder:kv:v1': lambda x, key_parser, value_parser: (key_parser(x['key']), value_parser(x['value'])), 'beam:coder:interval_window:v1': lambda x: IntervalWindow( start=Timestamp(micros=(x['end'] - x['span']) * 1000), end=Timestamp(micros=x['end'] * 1000)), 'beam:coder:iterable:v1': lambda x, parser: list(map(parser, x)), 'beam:coder:global_window:v1': lambda x: window.GlobalWindow(), 'beam:coder:windowed_value:v1': lambda x, value_parser, window_parser: windowed_value.create( value_parser(x['value']), x['timestamp'] * 1000, tuple([window_parser(w) for w in x['windows']])) } def test_standard_coders(self): for name, spec in _load_test_cases(STANDARD_CODERS_YAML): logging.info('Executing %s test.', name) self._run_standard_coder(name, spec) def _run_standard_coder(self, name, spec): coder = self.parse_coder(spec['coder']) parse_value = self.json_value_parser(spec['coder']) nested_list = [spec['nested']] if 'nested' in spec else [True, False] for nested in nested_list: for expected_encoded, json_value in spec['examples'].items(): value = parse_value(json_value) expected_encoded = expected_encoded.encode('latin1') if not spec['coder'].get('non_deterministic', False): actual_encoded = encode_nested(coder, value, nested) if self.fix and actual_encoded != expected_encoded: self.to_fix[spec['index'], expected_encoded] = actual_encoded else: self.assertEqual(expected_encoded, actual_encoded) self.assertEqual(decode_nested(coder, expected_encoded, nested), value) else: # Only verify decoding for a non-deterministic coder self.assertEqual(decode_nested(coder, expected_encoded, nested), value) def parse_coder(self, spec): return self._urn_to_coder_class[spec['urn']]( *[self.parse_coder(c) for c in spec.get('components', ())]) def json_value_parser(self, coder_spec): component_parsers = [ self.json_value_parser(c) for c in coder_spec.get('components', ())] return lambda x: self._urn_to_json_value_parser[coder_spec['urn']]( x, *component_parsers) # Used when --fix is passed. fix = False to_fix = {} @classmethod def tearDownClass(cls): if cls.fix and cls.to_fix: print("FIXING", len(cls.to_fix), "TESTS") doc_sep = '\n---\n' docs = open(STANDARD_CODERS_YAML).read().split(doc_sep) def quote(s): return json.dumps(s.decode('latin1')).replace(r'\u0000', r'\0') for (doc_ix, expected_encoded), actual_encoded in cls.to_fix.items(): print(quote(expected_encoded), "->", quote(actual_encoded)) docs[doc_ix] = docs[doc_ix].replace( quote(expected_encoded) + ':', quote(actual_encoded) + ':') open(STANDARD_CODERS_YAML, 'w').write(doc_sep.join(docs)) def encode_nested(coder, value, nested=True): out = coder_impl.create_OutputStream() coder.get_impl().encode_to_stream(value, out, nested) return out.get() def decode_nested(coder, encoded, nested=True): return coder.get_impl().decode_from_stream( coder_impl.create_InputStream(encoded), nested) if __name__ == '__main__': if '--fix' in sys.argv: StandardCodersTest.fix = True sys.argv.remove('--fix') unittest.main()

37.8875

79

0.682118

from __future__ import absolute_import from __future__ import print_function import json import logging import os.path import sys import unittest from builtins import map import yaml from apache_beam.coders import coder_impl from apache_beam.coders import coders from apache_beam.transforms import window from apache_beam.transforms.window import IntervalWindow from apache_beam.utils import windowed_value from apache_beam.utils.timestamp import Timestamp STANDARD_CODERS_YAML = os.path.join( os.path.dirname(__file__), '..', 'testing', 'data', 'standard_coders.yaml') def _load_test_cases(test_yaml): if not os.path.exists(test_yaml): raise ValueError('Could not find the test spec: %s' % test_yaml) for ix, spec in enumerate(yaml.load_all(open(test_yaml))): spec['index'] = ix name = spec.get('name', spec['coder']['urn'].split(':')[-2]) yield [name, spec] class StandardCodersTest(unittest.TestCase): _urn_to_coder_class = { 'beam:coder:bytes:v1': coders.BytesCoder, 'beam:coder:varint:v1': coders.VarIntCoder, 'beam:coder:kv:v1': lambda k, v: coders.TupleCoder((k, v)), 'beam:coder:interval_window:v1': coders.IntervalWindowCoder, 'beam:coder:iterable:v1': lambda t: coders.IterableCoder(t), 'beam:coder:global_window:v1': coders.GlobalWindowCoder, 'beam:coder:windowed_value:v1': lambda v, w: coders.WindowedValueCoder(v, w) } _urn_to_json_value_parser = { 'beam:coder:bytes:v1': lambda x: x, 'beam:coder:varint:v1': lambda x: x, 'beam:coder:kv:v1': lambda x, key_parser, value_parser: (key_parser(x['key']), value_parser(x['value'])), 'beam:coder:interval_window:v1': lambda x: IntervalWindow( start=Timestamp(micros=(x['end'] - x['span']) * 1000), end=Timestamp(micros=x['end'] * 1000)), 'beam:coder:iterable:v1': lambda x, parser: list(map(parser, x)), 'beam:coder:global_window:v1': lambda x: window.GlobalWindow(), 'beam:coder:windowed_value:v1': lambda x, value_parser, window_parser: windowed_value.create( value_parser(x['value']), x['timestamp'] * 1000, tuple([window_parser(w) for w in x['windows']])) } def test_standard_coders(self): for name, spec in _load_test_cases(STANDARD_CODERS_YAML): logging.info('Executing %s test.', name) self._run_standard_coder(name, spec) def _run_standard_coder(self, name, spec): coder = self.parse_coder(spec['coder']) parse_value = self.json_value_parser(spec['coder']) nested_list = [spec['nested']] if 'nested' in spec else [True, False] for nested in nested_list: for expected_encoded, json_value in spec['examples'].items(): value = parse_value(json_value) expected_encoded = expected_encoded.encode('latin1') if not spec['coder'].get('non_deterministic', False): actual_encoded = encode_nested(coder, value, nested) if self.fix and actual_encoded != expected_encoded: self.to_fix[spec['index'], expected_encoded] = actual_encoded else: self.assertEqual(expected_encoded, actual_encoded) self.assertEqual(decode_nested(coder, expected_encoded, nested), value) else: self.assertEqual(decode_nested(coder, expected_encoded, nested), value) def parse_coder(self, spec): return self._urn_to_coder_class[spec['urn']]( *[self.parse_coder(c) for c in spec.get('components', ())]) def json_value_parser(self, coder_spec): component_parsers = [ self.json_value_parser(c) for c in coder_spec.get('components', ())] return lambda x: self._urn_to_json_value_parser[coder_spec['urn']]( x, *component_parsers) fix = False to_fix = {} @classmethod def tearDownClass(cls): if cls.fix and cls.to_fix: print("FIXING", len(cls.to_fix), "TESTS") doc_sep = '\n---\n' docs = open(STANDARD_CODERS_YAML).read().split(doc_sep) def quote(s): return json.dumps(s.decode('latin1')).replace(r'\u0000', r'\0') for (doc_ix, expected_encoded), actual_encoded in cls.to_fix.items(): print(quote(expected_encoded), "->", quote(actual_encoded)) docs[doc_ix] = docs[doc_ix].replace( quote(expected_encoded) + ':', quote(actual_encoded) + ':') open(STANDARD_CODERS_YAML, 'w').write(doc_sep.join(docs)) def encode_nested(coder, value, nested=True): out = coder_impl.create_OutputStream() coder.get_impl().encode_to_stream(value, out, nested) return out.get() def decode_nested(coder, encoded, nested=True): return coder.get_impl().decode_from_stream( coder_impl.create_InputStream(encoded), nested) if __name__ == '__main__': if '--fix' in sys.argv: StandardCodersTest.fix = True sys.argv.remove('--fix') unittest.main()

true

f704c56086b8ba866a205345226d91d6b051226d

200

py

Python

RULEngine/Game/Field.py

wonwon0/RobocupStrategyIA

891028f616d476b05b23b40924d7c99502a718e3

[ "MIT" ]

null

RULEngine/Game/Field.py

wonwon0/RobocupStrategyIA

891028f616d476b05b23b40924d7c99502a718e3

[ "MIT" ]

null

RULEngine/Game/Field.py

wonwon0/RobocupStrategyIA

891028f616d476b05b23b40924d7c99502a718e3

[ "MIT" ]

null

# Under MIT License, see LICENSE.txt class Field(): def __init__(self, ball): self.ball = ball def move_ball(self, position, delta): self.ball.set_position(position, delta)

20

47

0.655

class Field(): def __init__(self, ball): self.ball = ball def move_ball(self, position, delta): self.ball.set_position(position, delta)

true

f704c67d98e3a2a857e70406e7c669c763faa37b

3,213

py

Python

setup.py

altosaar/nomen

29170a2011decbc9aa4cae48bd5d8d291a6d9fb8

[ "MIT" ]

4

2016-12-22T16:37:52.000Z

2017-05-31T11:12:57.000Z

setup.py

altosaar/nomen

29170a2011decbc9aa4cae48bd5d8d291a6d9fb8

[ "MIT" ]

2

2016-12-23T06:15:31.000Z

2019-03-21T21:36:03.000Z

setup.py

altosaar/nomen

29170a2011decbc9aa4cae48bd5d8d291a6d9fb8

[ "MIT" ]

1

2018-07-05T21:14:59.000Z

#!/usr/bin/env python # setup # Setup script for installing nomen ########################################################################## ## Imports ########################################################################## import os import re import codecs from setuptools import setup from setuptools import find_packages ########################################################################## ## Package Information ########################################################################## ## Basic information NAME = "nomen" DESCRIPTION = "YAML configuration tree with command line flags." AUTHOR = "Jaan Altosaar" EMAIL = "j@jaan.io" LICENSE = "MIT" REPOSITORY = "https://github.com/altosaar/nomen" PACKAGE = "nomen" ## Define the keywords KEYWORDS = ( 'nomen', 'python', 'option', 'tree', 'nested', 'dict', 'parameter', 'flags' ) ## Define the classifiers ## See https://pypi.python.org/pypi?%3Aaction=list_classifiers CLASSIFIERS = ( 'Development Status :: 4 - Beta', 'Environment :: Console', 'License :: OSI Approved :: Apache Software License', 'Natural Language :: English', 'Operating System :: OS Independent', 'Programming Language :: Python', 'Programming Language :: Python :: 2.7', ) ## Important Paths PROJECT = os.path.abspath(os.path.dirname(__file__)) VERSION_PATH = os.path.join(PACKAGE, "version.py") ## Directories to ignore in find_packages EXCLUDES = ( "tests", "bin", "docs", "fixtures", "register", "notebooks", ) ## Requirements REQUIREMENTS = ["pyyaml", "addict"] ########################################################################## ## Helper Functions ########################################################################## def read(*parts): """ Assume UTF-8 encoding and return the contents of the file located at the absolute path from the REPOSITORY joined with *parts. """ with codecs.open(os.path.join(PROJECT, *parts), 'rb', 'utf-8') as f: return f.read() def get_version(path=VERSION_PATH): """ Reads the version.py defined in the VERSION_PATH to find the get_version function, and executes it to ensure that it is loaded correctly. """ namespace = {} exec(read(path), namespace) return namespace['get_version']() ########################################################################## ## Define the configuration ########################################################################## config = { "name": NAME, "version": get_version(), "description": DESCRIPTION, "long_description": DESCRIPTION, "license": LICENSE, "author": AUTHOR, "author_email": EMAIL, "maintainer": AUTHOR, "maintainer_email": EMAIL, "url": REPOSITORY, "download_url": "{}/tarball/v{}".format(REPOSITORY, get_version()), "packages": find_packages(where=PROJECT, exclude=EXCLUDES), "classifiers": CLASSIFIERS, "keywords": KEYWORDS, "zip_safe": False, "install_requires": REQUIREMENTS, } ########################################################################## ## Run setup script ########################################################################## if __name__ == '__main__': setup(**config)

28.945946

79

0.517585

true

f704c68356b63c2761fa7eec5a286419626cb51a

407

py

Python

confdgnmi/src/confd_gnmi_netconf_adapter.py

micnovak/ConfD-Demos

479499e7c5339ae77b611e17196e7516d1f1a1ce

[ "Apache-2.0" ]

11

2019-12-07T20:15:57.000Z

2022-02-04T18:12:52.000Z

confdgnmi/src/confd_gnmi_netconf_adapter.py

micnovak/ConfD-Demos

479499e7c5339ae77b611e17196e7516d1f1a1ce

[ "Apache-2.0" ]

2

2020-03-01T11:04:16.000Z

2021-02-03T14:17:23.000Z

confdgnmi/src/confd_gnmi_netconf_adapter.py

micnovak/ConfD-Demos

479499e7c5339ae77b611e17196e7516d1f1a1ce

[ "Apache-2.0" ]

6

2019-10-18T15:26:03.000Z

2021-01-13T10:28:30.000Z

from confd_gnmi_adapter import GnmiServerAdapter class GnmiNetconfServerAdapter(GnmiServerAdapter): @classmethod def get_adapter(cls): pass def set(self, prefix, path, val): pass def get_subscription_handler(self, subscription_list): pass def capabilities(self): return [] def get(self, prefix, paths, data_type, use_models): return []

19.380952

58

0.670762

from confd_gnmi_adapter import GnmiServerAdapter class GnmiNetconfServerAdapter(GnmiServerAdapter): @classmethod def get_adapter(cls): pass def set(self, prefix, path, val): pass def get_subscription_handler(self, subscription_list): pass def capabilities(self): return [] def get(self, prefix, paths, data_type, use_models): return []

true

f704c6f312d2240524282b8c816c45e6b8714e15

36,146

py

Python

lightseq/training/ops/pytorch/torch_transformer_layers.py

iRmantou/lightseq

9a617306fa711a3d6a25ef3eab9bfbe408692189

[ "Apache-2.0" ]

1

2022-03-27T17:16:16.000Z

lightseq/training/ops/pytorch/torch_transformer_layers.py

iRmantou/lightseq

9a617306fa711a3d6a25ef3eab9bfbe408692189

[ "Apache-2.0" ]

null

lightseq/training/ops/pytorch/torch_transformer_layers.py

iRmantou/lightseq

9a617306fa711a3d6a25ef3eab9bfbe408692189

[ "Apache-2.0" ]

null

# Copyright 2021 The LightSeq Team # Copyright Facebook Fairseq # We use layers from Facebook Fairseq as our baseline import math import uuid from typing import Dict, Optional, Tuple, List import torch import torch.nn.functional as F from torch import Tensor, nn from torch.nn import Parameter, LayerNorm, Dropout, Linear from lightseq.training.ops.pytorch import util from lightseq.training.ops.pytorch.layer_base import ( TransformerEmbeddingLayerBase, TransformerEncoderLayerBase, TransformerDecoderLayerBase, ) from .quantization import ( QuantLinear, TensorQuantizer, act_quant_config, weight_quant_config, ) class MultiheadAttention(nn.Module): """Multi-headed attention. See "Attention Is All You Need" for more details. """ def __init__( self, embed_dim, num_heads, kdim=None, vdim=None, dropout=0.0, bias=True, add_bias_kv=False, add_zero_attn=False, self_attention=False, encoder_decoder_attention=False, is_decoder=False, ): super().__init__() self.embed_dim = embed_dim self.kdim = kdim if kdim is not None else embed_dim self.vdim = vdim if vdim is not None else embed_dim self.qkv_same_dim = self.kdim == embed_dim and self.vdim == embed_dim self.num_heads = num_heads self.dropout_module = Dropout(dropout) self.head_dim = embed_dim // num_heads assert ( self.head_dim * num_heads == self.embed_dim ), "embed_dim must be divisible by num_heads" self.scaling = self.head_dim ** -0.5 self.self_attention = self_attention self.encoder_decoder_attention = encoder_decoder_attention self.is_decoder = is_decoder assert ( not self.self_attention or self.qkv_same_dim ), "Self-attention requires query, key and value to be of the same size" self.attention_quant = None if self.self_attention: # self.qkv_proj = Linear(embed_dim, 3*embed_dim, bias=bias) self.qkv_proj = QuantLinear(embed_dim, 3 * embed_dim, bias=bias) self.attention_quant = ( TensorQuantizer(act_quant_config) if self.is_decoder else None ) elif self.encoder_decoder_attention and self.is_decoder: self.k_proj = QuantLinear( self.kdim, embed_dim, pre_activation="encoder_out", bias=bias ) self.v_proj = QuantLinear( self.vdim, embed_dim, pre_activation="encoder_out", bias=bias ) self.q_proj = QuantLinear(embed_dim, embed_dim, bias=bias) self.out_proj = QuantLinear(embed_dim, embed_dim, bias=bias) if add_bias_kv: self.bias_k = Parameter(torch.Tensor(1, 1, embed_dim)) self.bias_v = Parameter(torch.Tensor(1, 1, embed_dim)) else: self.bias_k = self.bias_v = None self.add_zero_attn = add_zero_attn self.reset_parameters() self.onnx_trace = False self.tpu = False self.init_incremental_state() def prepare_for_onnx_export_(self): self.onnx_trace = True def prepare_for_tpu_(self, **kwargs): self.tpu = True def reset_parameters(self): if self.qkv_same_dim: # Empirically observed the convergence to be much better with # the scaled initialization if self.self_attention: nn.init.xavier_uniform_(self.qkv_proj.weight, gain=1 / math.sqrt(2)) else: nn.init.xavier_uniform_(self.k_proj.weight, gain=1 / math.sqrt(2)) nn.init.xavier_uniform_(self.v_proj.weight, gain=1 / math.sqrt(2)) nn.init.xavier_uniform_(self.q_proj.weight, gain=1 / math.sqrt(2)) else: nn.init.xavier_uniform_(self.k_proj.weight) nn.init.xavier_uniform_(self.v_proj.weight) nn.init.xavier_uniform_(self.q_proj.weight) nn.init.xavier_uniform_(self.out_proj.weight) if self.out_proj.bias is not None: nn.init.constant_(self.out_proj.bias, 0.0) if self.bias_k is not None: nn.init.xavier_normal_(self.bias_k) if self.bias_v is not None: nn.init.xavier_normal_(self.bias_v) def forward( self, query, key: Optional[Tensor], value: Optional[Tensor], key_padding_mask: Optional[Tensor] = None, incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]] = None, need_weights: bool = True, static_kv: bool = False, attn_mask: Optional[Tensor] = None, before_softmax: bool = False, need_head_weights: bool = False, ): """Input shape: Time x Batch x Channel Args: key_padding_mask (ByteTensor, optional): mask to exclude keys that are pads, of shape `(batch, src_len)`, where padding elements are indicated by 1s. need_weights (bool, optional): return the attention weights, averaged over heads (default: False). attn_mask (ByteTensor, optional): typically used to implement causal attention, where the mask prevents the attention from looking forward in time (default: None). before_softmax (bool, optional): return the raw attention weights and values before the attention softmax. need_head_weights (bool, optional): return the attention weights for each head. Implies *need_weights*. Default: return the average attention weights over all heads. """ if need_head_weights: need_weights = True tgt_len, bsz, embed_dim = query.size() assert embed_dim == self.embed_dim assert list(query.size()) == [tgt_len, bsz, embed_dim] if incremental_state is not None: saved_state = self._get_input_buffer(incremental_state) if saved_state is not None and "prev_key" in saved_state: # previous time steps are cached - no need to recompute # key and value if they are static if static_kv: assert self.encoder_decoder_attention and not self.self_attention key = value = None else: saved_state = None if self.self_attention: qkv = self.qkv_proj(query) if self.attention_quant is not None: qkv = self.attention_quant(qkv) q, k, v = qkv.split(self.embed_dim, dim=-1) # q = self.q_proj(query) # k = self.k_proj(query) # v = self.v_proj(query) elif self.encoder_decoder_attention: # encoder-decoder attention q = self.q_proj(query) if key is None: assert value is None k = v = None else: k = self.k_proj(key) v = self.v_proj(key) else: assert key is not None and value is not None q = self.q_proj(query) k = self.k_proj(key) v = self.v_proj(value) q = q * self.scaling if self.bias_k is not None: assert self.bias_v is not None k = torch.cat([k, self.bias_k.repeat(1, bsz, 1)]) v = torch.cat([v, self.bias_v.repeat(1, bsz, 1)]) if attn_mask is not None: attn_mask = torch.cat( [attn_mask, attn_mask.new_zeros(attn_mask.size(0), 1)], dim=1 ) if key_padding_mask is not None: key_padding_mask = torch.cat( [ key_padding_mask, key_padding_mask.new_zeros(key_padding_mask.size(0), 1), ], dim=1, ) q = ( q.contiguous() .view(tgt_len, bsz * self.num_heads, self.head_dim) .transpose(0, 1) ) if k is not None: k = ( k.contiguous() .view(-1, bsz * self.num_heads, self.head_dim) .transpose(0, 1) ) if v is not None: v = ( v.contiguous() .view(-1, bsz * self.num_heads, self.head_dim) .transpose(0, 1) ) if saved_state is not None: # saved states are stored with shape (bsz, num_heads, seq_len, head_dim) if "prev_key" in saved_state: _prev_key = saved_state["prev_key"] assert _prev_key is not None prev_key = _prev_key.view(bsz * self.num_heads, -1, self.head_dim) if static_kv: k = prev_key else: assert k is not None k = torch.cat([prev_key, k], dim=1) if "prev_value" in saved_state: _prev_value = saved_state["prev_value"] assert _prev_value is not None prev_value = _prev_value.view(bsz * self.num_heads, -1, self.head_dim) if static_kv: v = prev_value else: assert v is not None v = torch.cat([prev_value, v], dim=1) prev_key_padding_mask: Optional[Tensor] = None if "prev_key_padding_mask" in saved_state: prev_key_padding_mask = saved_state["prev_key_padding_mask"] assert k is not None and v is not None key_padding_mask = MultiheadAttention._append_prev_key_padding_mask( key_padding_mask=key_padding_mask, prev_key_padding_mask=prev_key_padding_mask, batch_size=bsz, src_len=k.size(1), static_kv=static_kv, ) saved_state["prev_key"] = k.view(bsz, self.num_heads, -1, self.head_dim) saved_state["prev_value"] = v.view(bsz, self.num_heads, -1, self.head_dim) saved_state["prev_key_padding_mask"] = key_padding_mask # In this branch incremental_state is never None assert incremental_state is not None incremental_state = self._set_input_buffer(incremental_state, saved_state) assert k is not None src_len = k.size(1) # This is part of a workaround to get around fork/join parallelism # not supporting Optional types. if key_padding_mask is not None and key_padding_mask.dim() == 0: key_padding_mask = None if key_padding_mask is not None: assert key_padding_mask.size(0) == bsz assert key_padding_mask.size(1) == src_len if self.add_zero_attn: assert v is not None src_len += 1 k = torch.cat([k, k.new_zeros((k.size(0), 1) + k.size()[2:])], dim=1) v = torch.cat([v, v.new_zeros((v.size(0), 1) + v.size()[2:])], dim=1) if attn_mask is not None: attn_mask = torch.cat( [attn_mask, attn_mask.new_zeros(attn_mask.size(0), 1)], dim=1 ) if key_padding_mask is not None: key_padding_mask = torch.cat( [ key_padding_mask, torch.zeros(key_padding_mask.size(0), 1).type_as( key_padding_mask ), ], dim=1, ) attn_weights = torch.bmm(q, k.transpose(1, 2)) attn_weights = self.apply_sparse_mask(attn_weights, tgt_len, src_len, bsz) assert list(attn_weights.size()) == [bsz * self.num_heads, tgt_len, src_len] if attn_mask is not None: attn_mask = attn_mask.unsqueeze(0) if self.onnx_trace: attn_mask = attn_mask.repeat(attn_weights.size(0), 1, 1) attn_weights += attn_mask if key_padding_mask is not None: # don't attend to padding symbols attn_weights = attn_weights.view(bsz, self.num_heads, tgt_len, src_len) if not self.tpu: attn_weights = attn_weights.masked_fill( key_padding_mask.unsqueeze(1).unsqueeze(2).to(torch.bool), float("-inf"), ) else: attn_weights = attn_weights.transpose(0, 2) attn_weights = attn_weights.masked_fill(key_padding_mask, float("-inf")) attn_weights = attn_weights.transpose(0, 2) attn_weights = attn_weights.view(bsz * self.num_heads, tgt_len, src_len) if before_softmax: return attn_weights, v attn_weights_float = util.softmax( attn_weights, dim=-1, onnx_trace=self.onnx_trace ) attn_weights = attn_weights_float.type_as(attn_weights) attn_probs = self.dropout_module(attn_weights) assert v is not None attn = torch.bmm(attn_probs, v) assert list(attn.size()) == [bsz * self.num_heads, tgt_len, self.head_dim] if self.onnx_trace and attn.size(1) == 1: # when ONNX tracing a single decoder step (sequence length == 1) # the transpose is a no-op copy before view, thus unnecessary attn = attn.contiguous().view(tgt_len, bsz, embed_dim) else: attn = attn.transpose(0, 1).contiguous().view(tgt_len, bsz, embed_dim) attn = self.out_proj(attn) attn_weights: Optional[Tensor] = None if need_weights: attn_weights = attn_weights_float.view( bsz, self.num_heads, tgt_len, src_len ).transpose(1, 0) if not need_head_weights: # average attention weights over heads attn_weights = attn_weights.mean(dim=0) return attn, attn_weights @staticmethod def _append_prev_key_padding_mask( key_padding_mask: Optional[Tensor], prev_key_padding_mask: Optional[Tensor], batch_size: int, src_len: int, static_kv: bool, ) -> Optional[Tensor]: # saved key padding masks have shape (bsz, seq_len) if prev_key_padding_mask is not None and static_kv: new_key_padding_mask = prev_key_padding_mask elif prev_key_padding_mask is not None and key_padding_mask is not None: new_key_padding_mask = torch.cat( [prev_key_padding_mask.float(), key_padding_mask.float()], dim=1 ) # During incremental decoding, as the padding token enters and # leaves the frame, there will be a time when prev or current # is None elif prev_key_padding_mask is not None: filler = torch.zeros( (batch_size, src_len - prev_key_padding_mask.size(1)), device=prev_key_padding_mask.device, ) new_key_padding_mask = torch.cat( [prev_key_padding_mask.float(), filler.float()], dim=1 ) elif key_padding_mask is not None: filler = torch.zeros( (batch_size, src_len - key_padding_mask.size(1)), device=key_padding_mask.device, ) new_key_padding_mask = torch.cat( [filler.float(), key_padding_mask.float()], dim=1 ) else: new_key_padding_mask = prev_key_padding_mask return new_key_padding_mask @torch.jit.export def reorder_incremental_state( self, incremental_state: Dict[str, Dict[str, Optional[Tensor]]], new_order: Tensor, ): """Reorder buffered internal state (for incremental generation).""" input_buffer = self._get_input_buffer(incremental_state) if input_buffer is not None: for k in input_buffer.keys(): input_buffer_k = input_buffer[k] if input_buffer_k is not None: if self.encoder_decoder_attention and input_buffer_k.size( 0 ) == new_order.size(0): break input_buffer[k] = input_buffer_k.index_select(0, new_order) incremental_state = self._set_input_buffer(incremental_state, input_buffer) return incremental_state def _get_input_buffer( self, incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]] ) -> Dict[str, Optional[Tensor]]: result = self.get_incremental_state(incremental_state, "attn_state") if result is not None: return result else: empty_result: Dict[str, Optional[Tensor]] = {} return empty_result def _set_input_buffer( self, incremental_state: Dict[str, Dict[str, Optional[Tensor]]], buffer: Dict[str, Optional[Tensor]], ): return self.set_incremental_state(incremental_state, "attn_state", buffer) def apply_sparse_mask(self, attn_weights, tgt_len: int, src_len: int, bsz: int): return attn_weights def upgrade_state_dict_named(self, state_dict, name): prefix = name + "." if name != "" else "" items_to_add = {} keys_to_remove = [] for k in state_dict.keys(): if k.endswith(prefix + "in_proj_weight"): # in_proj_weight used to be q + k + v with same dimensions dim = int(state_dict[k].shape[0] / 3) items_to_add[prefix + "q_proj.weight"] = state_dict[k][:dim] items_to_add[prefix + "k_proj.weight"] = state_dict[k][dim : 2 * dim] items_to_add[prefix + "v_proj.weight"] = state_dict[k][2 * dim :] keys_to_remove.append(k) k_bias = prefix + "in_proj_bias" if k_bias in state_dict.keys(): dim = int(state_dict[k].shape[0] / 3) items_to_add[prefix + "q_proj.bias"] = state_dict[k_bias][:dim] items_to_add[prefix + "k_proj.bias"] = state_dict[k_bias][ dim : 2 * dim ] items_to_add[prefix + "v_proj.bias"] = state_dict[k_bias][2 * dim :] keys_to_remove.append(prefix + "in_proj_bias") for k in keys_to_remove: del state_dict[k] for key, value in items_to_add.items(): state_dict[key] = value def init_incremental_state(self): self._incremental_state_id = str(uuid.uuid4()) def _get_full_incremental_state_key(self, key: str) -> str: return "{}.{}".format(self._incremental_state_id, key) def get_incremental_state( self, incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]], key: str, ) -> Optional[Dict[str, Optional[Tensor]]]: """Helper for getting incremental state for an nn.Module.""" full_key = self._get_full_incremental_state_key(key) if incremental_state is None or full_key not in incremental_state: return None return incremental_state[full_key] def set_incremental_state( self, incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]], key: str, value: Dict[str, Optional[Tensor]], ) -> Optional[Dict[str, Dict[str, Optional[Tensor]]]]: """Helper for setting incremental state for an nn.Module.""" if incremental_state is not None: full_key = self._get_full_incremental_state_key(key) incremental_state[full_key] = value return incremental_state class TransformerEncoderLayer(TransformerEncoderLayerBase): """Encoder layer implemented by fairseq. This version only removes the "args" parameter, no other changes In the original paper each operation (multi-head attention or FFN) is postprocessed with: `dropout -> add residual -> layernorm`. In the tensor2tensor code they suggest that learning is more robust when preprocessing each layer with layernorm and postprocessing with: `dropout -> add residual`. We default to the approach in the paper, but the tensor2tensor approach can be enabled by setting normalize_before to True. """ def __init__(self, config, initial_weights=None, initial_biases=None): super().__init__() self.embed_dim = config.hidden_size self.self_attn = self.build_self_attention( self.embed_dim, config.nhead, config.attn_prob_dropout_ratio ) self.self_attn_layer_norm = LayerNorm(self.embed_dim) self.dropout_module = Dropout(config.hidden_dropout_ratio) self.activation_fn = util.get_activation_fn(activation=config.activation_fn) self.activation_dropout_module = Dropout(float(config.activation_dropout_ratio)) self.normalize_before = config.pre_layer_norm self.fc1 = QuantLinear( self.embed_dim, config.intermediate_size, ) self.fc2 = QuantLinear( config.intermediate_size, self.embed_dim, pre_activation="relu" ) self.final_layer_norm = LayerNorm(self.embed_dim) def build_self_attention(self, embed_dim, nhead, attn_dropout): return MultiheadAttention( embed_dim, nhead, dropout=attn_dropout, self_attention=True, ) def residual_connection(self, x, residual): return residual + x def upgrade_state_dict_named(self, state_dict, name): """ Rename layer norm states from `...layer_norms.0.weight` to `...self_attn_layer_norm.weight` and `...layer_norms.1.weight` to `...final_layer_norm.weight` """ layer_norm_map = {"0": "self_attn_layer_norm", "1": "final_layer_norm"} for old, new in layer_norm_map.items(): for m in ("weight", "bias"): k = "{}.layer_norms.{}.{}".format(name, old, m) if k in state_dict: state_dict["{}.{}.{}".format(name, new, m)] = state_dict[k] del state_dict[k] def forward(self, x, encoder_padding_mask): """ Args: x (Tensor): input to the layer of shape `(batch, seq_len, embed_dim)` encoder_padding_mask (ByteTensor): binary ByteTensor of shape `(batch, seq_len)` where padding elements are indicated by ``1``. Returns: encoded output of shape `(seq_len, batch, embed_dim)` """ # anything in original attn_mask = 1, becomes -1e8 # anything in original attn_mask = 0, becomes 0 # Note that we cannot use -inf here, because at some edge cases, # the attention weight (before softmax) for some padded element in query # will become -inf, which results in NaN in model parameters x = x.transpose(0, 1) residual = x if self.normalize_before: x = self.self_attn_layer_norm(x) x, _ = self.self_attn( query=x, key=x, value=x, key_padding_mask=encoder_padding_mask, ) x = self.dropout_module(x) x = self.residual_connection(x, residual) if not self.normalize_before: x = self.self_attn_layer_norm(x) residual = x if self.normalize_before: x = self.final_layer_norm(x) x = self.activation_fn(self.fc1(x)) x = self.activation_dropout_module(x) x = self.fc2(x) x = self.dropout_module(x) x = self.residual_connection(x, residual) if not self.normalize_before: x = self.final_layer_norm(x) x = x.transpose(0, 1) return x class TransformerDecoderLayer(TransformerDecoderLayerBase): """Decoder layer implemented by fairseq. This version only removes the "args" parameter, no other changes """ def __init__(self, config, initial_weights=None, initial_biases=None): super().__init__() self.embed_dim = config.hidden_size self.dropout_module = Dropout(config.hidden_dropout_ratio) self.cross_self_attention = False self.self_attn = self.build_self_attention( self.embed_dim, config.nhead, config.attn_prob_dropout_ratio, ) self.activation_fn = util.get_activation_fn(activation=config.activation_fn) self.activation_dropout_module = Dropout(float(config.activation_dropout_ratio)) self.normalize_before = config.pre_layer_norm self.self_attn_layer_norm = LayerNorm(self.embed_dim) self.encoder_attn = self.build_encoder_attention( self.embed_dim, config.hidden_size, config.attn_prob_dropout_ratio, config.nhead, ) self.encoder_attn_layer_norm = LayerNorm(self.embed_dim) self.fc1 = QuantLinear( self.embed_dim, config.intermediate_size, ) self.fc2 = QuantLinear( config.intermediate_size, self.embed_dim, pre_activation="relu", ) self.final_layer_norm = LayerNorm(self.embed_dim) self.need_attn = True self.onnx_trace = False def build_self_attention( self, embed_dim, nhead, attn_dropout, add_bias_kv=False, add_zero_attn=False ): return MultiheadAttention( embed_dim, nhead, dropout=attn_dropout, add_bias_kv=add_bias_kv, add_zero_attn=add_zero_attn, self_attention=not self.cross_self_attention, is_decoder=True, ) def build_encoder_attention( self, embed_dim, encoder_embed_dim, attn_dropout, nhead ): return MultiheadAttention( embed_dim, nhead, kdim=encoder_embed_dim, vdim=encoder_embed_dim, dropout=attn_dropout, encoder_decoder_attention=True, is_decoder=True, ) def prepare_for_onnx_export_(self): self.onnx_trace = True def residual_connection(self, x, residual): return residual + x def forward( self, x, encoder_out: Optional[torch.Tensor] = None, encoder_padding_mask: Optional[torch.Tensor] = None, incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]] = None, prev_self_attn_state: Optional[List[torch.Tensor]] = None, prev_attn_state: Optional[List[torch.Tensor]] = None, self_attn_mask: Optional[torch.Tensor] = None, self_attn_padding_mask: Optional[torch.Tensor] = None, need_attn: bool = False, need_head_weights: bool = False, ): """ Args: x (Tensor): input to the layer of shape `(batch, seq_len, embed_dim)` encoder_padding_mask (ByteTensor, optional): binary ByteTensor of shape `(batch, src_len)` where padding elements are indicated by ``1``. need_attn (bool, optional): return attention weights need_head_weights (bool, optional): return attention weights for each head (default: return average over heads). Returns: encoded output of shape `(seq_len, batch, embed_dim)` """ if need_head_weights: need_attn = True x = x.transpose(0, 1) residual = x if self.normalize_before: x = self.self_attn_layer_norm(x) if prev_self_attn_state is not None: prev_key, prev_value = prev_self_attn_state[:2] saved_state: Dict[str, Optional[Tensor]] = { "prev_key": prev_key, "prev_value": prev_value, } if len(prev_self_attn_state) >= 3: saved_state["prev_key_padding_mask"] = prev_self_attn_state[2] assert incremental_state is not None self.self_attn._set_input_buffer(incremental_state, saved_state) _self_attn_input_buffer = self.self_attn._get_input_buffer(incremental_state) if self.cross_self_attention and not ( incremental_state is not None and _self_attn_input_buffer is not None and "prev_key" in _self_attn_input_buffer ): if self_attn_mask is not None: assert encoder_out is not None self_attn_mask = torch.cat( (x.new_zeros(x.size(0), encoder_out.size(0)), self_attn_mask), dim=1 ) if self_attn_padding_mask is not None: if encoder_padding_mask is None: assert encoder_out is not None encoder_padding_mask = self_attn_padding_mask.new_zeros( encoder_out.size(1), encoder_out.size(0) ) self_attn_padding_mask = torch.cat( (encoder_padding_mask, self_attn_padding_mask), dim=1 ) assert encoder_out is not None y = torch.cat((encoder_out, x), dim=0) else: y = x x, attn = self.self_attn( query=x, key=y, value=y, key_padding_mask=self_attn_padding_mask, incremental_state=incremental_state, need_weights=False, attn_mask=self_attn_mask, ) x = self.dropout_module(x) x = self.residual_connection(x, residual) if not self.normalize_before: x = self.self_attn_layer_norm(x) if self.encoder_attn is not None and encoder_out is not None: if ( encoder_out.shape[1] != x.shape[1] and x.shape[1] % encoder_out.shape[1] == 0 ): beam_size = int(x.shape[1] / encoder_out.shape[1]) encoder_out = encoder_out.repeat_interleave(beam_size, 1) encoder_padding_mask = encoder_padding_mask.repeat_interleave( beam_size, 0 ) residual = x if self.normalize_before: x = self.encoder_attn_layer_norm(x) if prev_attn_state is not None: prev_key, prev_value = prev_attn_state[:2] saved_state: Dict[str, Optional[Tensor]] = { "prev_key": prev_key, "prev_value": prev_value, } if len(prev_attn_state) >= 3: saved_state["prev_key_padding_mask"] = prev_attn_state[2] assert incremental_state is not None self.encoder_attn._set_input_buffer(incremental_state, saved_state) x, attn = self.encoder_attn( query=x, key=encoder_out, value=encoder_out, key_padding_mask=encoder_padding_mask, incremental_state=incremental_state, static_kv=True, need_weights=need_attn or (not self.training and self.need_attn), need_head_weights=need_head_weights, ) x = self.dropout_module(x) x = self.residual_connection(x, residual) if not self.normalize_before: x = self.encoder_attn_layer_norm(x) residual = x if self.normalize_before: x = self.final_layer_norm(x) x = self.activation_fn(self.fc1(x)) x = self.activation_dropout_module(x) x = self.fc2(x) x = self.dropout_module(x) x = self.residual_connection(x, residual) if not self.normalize_before: x = self.final_layer_norm(x) if self.onnx_trace and incremental_state is not None: saved_state = self.self_attn._get_input_buffer(incremental_state) assert saved_state is not None if self_attn_padding_mask is not None: self_attn_state = [ saved_state["prev_key"], saved_state["prev_value"], saved_state["prev_key_padding_mask"], ] else: self_attn_state = [saved_state["prev_key"], saved_state["prev_value"]] return x, attn, self_attn_state x = x.transpose(0, 1) return x, attn, None def make_generation_fast_(self, need_attn: bool = False, **kwargs): self.need_attn = need_attn class TransformerEmbeddingLayer(TransformerEmbeddingLayerBase): def __init__(self, config): super().__init__() self.emb_lookup = nn.Embedding( config.vocab_size, config.embedding_dim, padding_idx=config.padding_idx ) self.emb_lookup.to(dtype=(torch.half if config.fp16 else torch.float)) self.embeddings = self.emb_lookup.weight nn.init.normal_(self.embeddings, mean=0, std=config.embedding_dim ** -0.5) nn.init.constant_(self.embeddings[config.padding_idx], 0) self.embed_positions = SinusoidalPositionalEmbedding( config.embedding_dim, config.padding_idx, config.max_seq_len, config.fp16 ) self.embedding_dim = config.embedding_dim self.dropout = Dropout(config.dropout) self.emb_quant = TensorQuantizer(weight_quant_config) self.config = config def forward(self, input, step=0): x = self.emb_lookup(input) x = self.emb_quant(x) x = math.sqrt(self.embedding_dim) * x x += self.embed_positions(input, step) x = self.dropout(x) return x class SinusoidalPositionalEmbedding(nn.Module): """This module produces sinusoidal positional embeddings of any length. Padding symbols are ignored. """ def __init__(self, embedding_dim, padding_idx, init_size=1024, fp16=False): super().__init__() self.embedding_dim = embedding_dim self.padding_idx = padding_idx self.weights = SinusoidalPositionalEmbedding.get_embedding( init_size, embedding_dim, padding_idx ) if fp16: self.weights = self.weights.to(torch.half) @staticmethod def get_embedding( num_embeddings: int, embedding_dim: int, padding_idx: Optional[int] = None ): """Build sinusoidal embeddings. This matches the implementation in tensor2tensor, but differs slightly from the description in Section 3.5 of "Attention Is All You Need". """ half_dim = embedding_dim // 2 emb = math.log(10000) / (half_dim - 1) emb = torch.exp(torch.arange(half_dim, dtype=torch.float) * -emb) emb = torch.arange(num_embeddings, dtype=torch.float).unsqueeze( 1 ) * emb.unsqueeze(0) emb = torch.cat([torch.sin(emb), torch.cos(emb)], dim=1).view( num_embeddings, -1 ) if embedding_dim % 2 == 1: # zero pad emb = torch.cat([emb, torch.zeros(num_embeddings, 1)], dim=1) return emb def make_positions(self, tensor, padding_idx, step): mask = tensor.ne(padding_idx).int() return ((torch.cumsum(mask, dim=1).type_as(mask) - 1 + step) * mask).long() def forward( self, input, step=0, incremental_state=None, timestep=None, positions=None, ): """Input is expected to be of size [bsz x seqlen].""" bsz, seq_len = input.size(0), input.size(1) positions = self.make_positions(input, self.padding_idx, step) mask = ( torch.ne(input, self.padding_idx) .unsqueeze(2) .expand(bsz, seq_len, self.embedding_dim) ) return ( self.weights.to(input.device) .index_select(0, positions.view(-1)) .view(bsz, seq_len, -1) * mask ).detach()

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import math import uuid from typing import Dict, Optional, Tuple, List import torch import torch.nn.functional as F from torch import Tensor, nn from torch.nn import Parameter, LayerNorm, Dropout, Linear from lightseq.training.ops.pytorch import util from lightseq.training.ops.pytorch.layer_base import ( TransformerEmbeddingLayerBase, TransformerEncoderLayerBase, TransformerDecoderLayerBase, ) from .quantization import ( QuantLinear, TensorQuantizer, act_quant_config, weight_quant_config, ) class MultiheadAttention(nn.Module): def __init__( self, embed_dim, num_heads, kdim=None, vdim=None, dropout=0.0, bias=True, add_bias_kv=False, add_zero_attn=False, self_attention=False, encoder_decoder_attention=False, is_decoder=False, ): super().__init__() self.embed_dim = embed_dim self.kdim = kdim if kdim is not None else embed_dim self.vdim = vdim if vdim is not None else embed_dim self.qkv_same_dim = self.kdim == embed_dim and self.vdim == embed_dim self.num_heads = num_heads self.dropout_module = Dropout(dropout) self.head_dim = embed_dim // num_heads assert ( self.head_dim * num_heads == self.embed_dim ), "embed_dim must be divisible by num_heads" self.scaling = self.head_dim ** -0.5 self.self_attention = self_attention self.encoder_decoder_attention = encoder_decoder_attention self.is_decoder = is_decoder assert ( not self.self_attention or self.qkv_same_dim ), "Self-attention requires query, key and value to be of the same size" self.attention_quant = None if self.self_attention: self.qkv_proj = QuantLinear(embed_dim, 3 * embed_dim, bias=bias) self.attention_quant = ( TensorQuantizer(act_quant_config) if self.is_decoder else None ) elif self.encoder_decoder_attention and self.is_decoder: self.k_proj = QuantLinear( self.kdim, embed_dim, pre_activation="encoder_out", bias=bias ) self.v_proj = QuantLinear( self.vdim, embed_dim, pre_activation="encoder_out", bias=bias ) self.q_proj = QuantLinear(embed_dim, embed_dim, bias=bias) self.out_proj = QuantLinear(embed_dim, embed_dim, bias=bias) if add_bias_kv: self.bias_k = Parameter(torch.Tensor(1, 1, embed_dim)) self.bias_v = Parameter(torch.Tensor(1, 1, embed_dim)) else: self.bias_k = self.bias_v = None self.add_zero_attn = add_zero_attn self.reset_parameters() self.onnx_trace = False self.tpu = False self.init_incremental_state() def prepare_for_onnx_export_(self): self.onnx_trace = True def prepare_for_tpu_(self, **kwargs): self.tpu = True def reset_parameters(self): if self.qkv_same_dim: if self.self_attention: nn.init.xavier_uniform_(self.qkv_proj.weight, gain=1 / math.sqrt(2)) else: nn.init.xavier_uniform_(self.k_proj.weight, gain=1 / math.sqrt(2)) nn.init.xavier_uniform_(self.v_proj.weight, gain=1 / math.sqrt(2)) nn.init.xavier_uniform_(self.q_proj.weight, gain=1 / math.sqrt(2)) else: nn.init.xavier_uniform_(self.k_proj.weight) nn.init.xavier_uniform_(self.v_proj.weight) nn.init.xavier_uniform_(self.q_proj.weight) nn.init.xavier_uniform_(self.out_proj.weight) if self.out_proj.bias is not None: nn.init.constant_(self.out_proj.bias, 0.0) if self.bias_k is not None: nn.init.xavier_normal_(self.bias_k) if self.bias_v is not None: nn.init.xavier_normal_(self.bias_v) def forward( self, query, key: Optional[Tensor], value: Optional[Tensor], key_padding_mask: Optional[Tensor] = None, incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]] = None, need_weights: bool = True, static_kv: bool = False, attn_mask: Optional[Tensor] = None, before_softmax: bool = False, need_head_weights: bool = False, ): if need_head_weights: need_weights = True tgt_len, bsz, embed_dim = query.size() assert embed_dim == self.embed_dim assert list(query.size()) == [tgt_len, bsz, embed_dim] if incremental_state is not None: saved_state = self._get_input_buffer(incremental_state) if saved_state is not None and "prev_key" in saved_state: if static_kv: assert self.encoder_decoder_attention and not self.self_attention key = value = None else: saved_state = None if self.self_attention: qkv = self.qkv_proj(query) if self.attention_quant is not None: qkv = self.attention_quant(qkv) q, k, v = qkv.split(self.embed_dim, dim=-1) elif self.encoder_decoder_attention: q = self.q_proj(query) if key is None: assert value is None k = v = None else: k = self.k_proj(key) v = self.v_proj(key) else: assert key is not None and value is not None q = self.q_proj(query) k = self.k_proj(key) v = self.v_proj(value) q = q * self.scaling if self.bias_k is not None: assert self.bias_v is not None k = torch.cat([k, self.bias_k.repeat(1, bsz, 1)]) v = torch.cat([v, self.bias_v.repeat(1, bsz, 1)]) if attn_mask is not None: attn_mask = torch.cat( [attn_mask, attn_mask.new_zeros(attn_mask.size(0), 1)], dim=1 ) if key_padding_mask is not None: key_padding_mask = torch.cat( [ key_padding_mask, key_padding_mask.new_zeros(key_padding_mask.size(0), 1), ], dim=1, ) q = ( q.contiguous() .view(tgt_len, bsz * self.num_heads, self.head_dim) .transpose(0, 1) ) if k is not None: k = ( k.contiguous() .view(-1, bsz * self.num_heads, self.head_dim) .transpose(0, 1) ) if v is not None: v = ( v.contiguous() .view(-1, bsz * self.num_heads, self.head_dim) .transpose(0, 1) ) if saved_state is not None: if "prev_key" in saved_state: _prev_key = saved_state["prev_key"] assert _prev_key is not None prev_key = _prev_key.view(bsz * self.num_heads, -1, self.head_dim) if static_kv: k = prev_key else: assert k is not None k = torch.cat([prev_key, k], dim=1) if "prev_value" in saved_state: _prev_value = saved_state["prev_value"] assert _prev_value is not None prev_value = _prev_value.view(bsz * self.num_heads, -1, self.head_dim) if static_kv: v = prev_value else: assert v is not None v = torch.cat([prev_value, v], dim=1) prev_key_padding_mask: Optional[Tensor] = None if "prev_key_padding_mask" in saved_state: prev_key_padding_mask = saved_state["prev_key_padding_mask"] assert k is not None and v is not None key_padding_mask = MultiheadAttention._append_prev_key_padding_mask( key_padding_mask=key_padding_mask, prev_key_padding_mask=prev_key_padding_mask, batch_size=bsz, src_len=k.size(1), static_kv=static_kv, ) saved_state["prev_key"] = k.view(bsz, self.num_heads, -1, self.head_dim) saved_state["prev_value"] = v.view(bsz, self.num_heads, -1, self.head_dim) saved_state["prev_key_padding_mask"] = key_padding_mask assert incremental_state is not None incremental_state = self._set_input_buffer(incremental_state, saved_state) assert k is not None src_len = k.size(1) if key_padding_mask is not None and key_padding_mask.dim() == 0: key_padding_mask = None if key_padding_mask is not None: assert key_padding_mask.size(0) == bsz assert key_padding_mask.size(1) == src_len if self.add_zero_attn: assert v is not None src_len += 1 k = torch.cat([k, k.new_zeros((k.size(0), 1) + k.size()[2:])], dim=1) v = torch.cat([v, v.new_zeros((v.size(0), 1) + v.size()[2:])], dim=1) if attn_mask is not None: attn_mask = torch.cat( [attn_mask, attn_mask.new_zeros(attn_mask.size(0), 1)], dim=1 ) if key_padding_mask is not None: key_padding_mask = torch.cat( [ key_padding_mask, torch.zeros(key_padding_mask.size(0), 1).type_as( key_padding_mask ), ], dim=1, ) attn_weights = torch.bmm(q, k.transpose(1, 2)) attn_weights = self.apply_sparse_mask(attn_weights, tgt_len, src_len, bsz) assert list(attn_weights.size()) == [bsz * self.num_heads, tgt_len, src_len] if attn_mask is not None: attn_mask = attn_mask.unsqueeze(0) if self.onnx_trace: attn_mask = attn_mask.repeat(attn_weights.size(0), 1, 1) attn_weights += attn_mask if key_padding_mask is not None: attn_weights = attn_weights.view(bsz, self.num_heads, tgt_len, src_len) if not self.tpu: attn_weights = attn_weights.masked_fill( key_padding_mask.unsqueeze(1).unsqueeze(2).to(torch.bool), float("-inf"), ) else: attn_weights = attn_weights.transpose(0, 2) attn_weights = attn_weights.masked_fill(key_padding_mask, float("-inf")) attn_weights = attn_weights.transpose(0, 2) attn_weights = attn_weights.view(bsz * self.num_heads, tgt_len, src_len) if before_softmax: return attn_weights, v attn_weights_float = util.softmax( attn_weights, dim=-1, onnx_trace=self.onnx_trace ) attn_weights = attn_weights_float.type_as(attn_weights) attn_probs = self.dropout_module(attn_weights) assert v is not None attn = torch.bmm(attn_probs, v) assert list(attn.size()) == [bsz * self.num_heads, tgt_len, self.head_dim] if self.onnx_trace and attn.size(1) == 1: # when ONNX tracing a single decoder step (sequence length == 1) # the transpose is a no-op copy before view, thus unnecessary attn = attn.contiguous().view(tgt_len, bsz, embed_dim) else: attn = attn.transpose(0, 1).contiguous().view(tgt_len, bsz, embed_dim) attn = self.out_proj(attn) attn_weights: Optional[Tensor] = None if need_weights: attn_weights = attn_weights_float.view( bsz, self.num_heads, tgt_len, src_len ).transpose(1, 0) if not need_head_weights: # average attention weights over heads attn_weights = attn_weights.mean(dim=0) return attn, attn_weights @staticmethod def _append_prev_key_padding_mask( key_padding_mask: Optional[Tensor], prev_key_padding_mask: Optional[Tensor], batch_size: int, src_len: int, static_kv: bool, ) -> Optional[Tensor]: # saved key padding masks have shape (bsz, seq_len) if prev_key_padding_mask is not None and static_kv: new_key_padding_mask = prev_key_padding_mask elif prev_key_padding_mask is not None and key_padding_mask is not None: new_key_padding_mask = torch.cat( [prev_key_padding_mask.float(), key_padding_mask.float()], dim=1 ) # During incremental decoding, as the padding token enters and # leaves the frame, there will be a time when prev or current # is None elif prev_key_padding_mask is not None: filler = torch.zeros( (batch_size, src_len - prev_key_padding_mask.size(1)), device=prev_key_padding_mask.device, ) new_key_padding_mask = torch.cat( [prev_key_padding_mask.float(), filler.float()], dim=1 ) elif key_padding_mask is not None: filler = torch.zeros( (batch_size, src_len - key_padding_mask.size(1)), device=key_padding_mask.device, ) new_key_padding_mask = torch.cat( [filler.float(), key_padding_mask.float()], dim=1 ) else: new_key_padding_mask = prev_key_padding_mask return new_key_padding_mask @torch.jit.export def reorder_incremental_state( self, incremental_state: Dict[str, Dict[str, Optional[Tensor]]], new_order: Tensor, ): input_buffer = self._get_input_buffer(incremental_state) if input_buffer is not None: for k in input_buffer.keys(): input_buffer_k = input_buffer[k] if input_buffer_k is not None: if self.encoder_decoder_attention and input_buffer_k.size( 0 ) == new_order.size(0): break input_buffer[k] = input_buffer_k.index_select(0, new_order) incremental_state = self._set_input_buffer(incremental_state, input_buffer) return incremental_state def _get_input_buffer( self, incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]] ) -> Dict[str, Optional[Tensor]]: result = self.get_incremental_state(incremental_state, "attn_state") if result is not None: return result else: empty_result: Dict[str, Optional[Tensor]] = {} return empty_result def _set_input_buffer( self, incremental_state: Dict[str, Dict[str, Optional[Tensor]]], buffer: Dict[str, Optional[Tensor]], ): return self.set_incremental_state(incremental_state, "attn_state", buffer) def apply_sparse_mask(self, attn_weights, tgt_len: int, src_len: int, bsz: int): return attn_weights def upgrade_state_dict_named(self, state_dict, name): prefix = name + "." if name != "" else "" items_to_add = {} keys_to_remove = [] for k in state_dict.keys(): if k.endswith(prefix + "in_proj_weight"): # in_proj_weight used to be q + k + v with same dimensions dim = int(state_dict[k].shape[0] / 3) items_to_add[prefix + "q_proj.weight"] = state_dict[k][:dim] items_to_add[prefix + "k_proj.weight"] = state_dict[k][dim : 2 * dim] items_to_add[prefix + "v_proj.weight"] = state_dict[k][2 * dim :] keys_to_remove.append(k) k_bias = prefix + "in_proj_bias" if k_bias in state_dict.keys(): dim = int(state_dict[k].shape[0] / 3) items_to_add[prefix + "q_proj.bias"] = state_dict[k_bias][:dim] items_to_add[prefix + "k_proj.bias"] = state_dict[k_bias][ dim : 2 * dim ] items_to_add[prefix + "v_proj.bias"] = state_dict[k_bias][2 * dim :] keys_to_remove.append(prefix + "in_proj_bias") for k in keys_to_remove: del state_dict[k] for key, value in items_to_add.items(): state_dict[key] = value def init_incremental_state(self): self._incremental_state_id = str(uuid.uuid4()) def _get_full_incremental_state_key(self, key: str) -> str: return "{}.{}".format(self._incremental_state_id, key) def get_incremental_state( self, incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]], key: str, ) -> Optional[Dict[str, Optional[Tensor]]]: full_key = self._get_full_incremental_state_key(key) if incremental_state is None or full_key not in incremental_state: return None return incremental_state[full_key] def set_incremental_state( self, incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]], key: str, value: Dict[str, Optional[Tensor]], ) -> Optional[Dict[str, Dict[str, Optional[Tensor]]]]: if incremental_state is not None: full_key = self._get_full_incremental_state_key(key) incremental_state[full_key] = value return incremental_state class TransformerEncoderLayer(TransformerEncoderLayerBase): def __init__(self, config, initial_weights=None, initial_biases=None): super().__init__() self.embed_dim = config.hidden_size self.self_attn = self.build_self_attention( self.embed_dim, config.nhead, config.attn_prob_dropout_ratio ) self.self_attn_layer_norm = LayerNorm(self.embed_dim) self.dropout_module = Dropout(config.hidden_dropout_ratio) self.activation_fn = util.get_activation_fn(activation=config.activation_fn) self.activation_dropout_module = Dropout(float(config.activation_dropout_ratio)) self.normalize_before = config.pre_layer_norm self.fc1 = QuantLinear( self.embed_dim, config.intermediate_size, ) self.fc2 = QuantLinear( config.intermediate_size, self.embed_dim, pre_activation="relu" ) self.final_layer_norm = LayerNorm(self.embed_dim) def build_self_attention(self, embed_dim, nhead, attn_dropout): return MultiheadAttention( embed_dim, nhead, dropout=attn_dropout, self_attention=True, ) def residual_connection(self, x, residual): return residual + x def upgrade_state_dict_named(self, state_dict, name): layer_norm_map = {"0": "self_attn_layer_norm", "1": "final_layer_norm"} for old, new in layer_norm_map.items(): for m in ("weight", "bias"): k = "{}.layer_norms.{}.{}".format(name, old, m) if k in state_dict: state_dict["{}.{}.{}".format(name, new, m)] = state_dict[k] del state_dict[k] def forward(self, x, encoder_padding_mask): # anything in original attn_mask = 1, becomes -1e8 # anything in original attn_mask = 0, becomes 0 # Note that we cannot use -inf here, because at some edge cases, # the attention weight (before softmax) for some padded element in query # will become -inf, which results in NaN in model parameters x = x.transpose(0, 1) residual = x if self.normalize_before: x = self.self_attn_layer_norm(x) x, _ = self.self_attn( query=x, key=x, value=x, key_padding_mask=encoder_padding_mask, ) x = self.dropout_module(x) x = self.residual_connection(x, residual) if not self.normalize_before: x = self.self_attn_layer_norm(x) residual = x if self.normalize_before: x = self.final_layer_norm(x) x = self.activation_fn(self.fc1(x)) x = self.activation_dropout_module(x) x = self.fc2(x) x = self.dropout_module(x) x = self.residual_connection(x, residual) if not self.normalize_before: x = self.final_layer_norm(x) x = x.transpose(0, 1) return x class TransformerDecoderLayer(TransformerDecoderLayerBase): def __init__(self, config, initial_weights=None, initial_biases=None): super().__init__() self.embed_dim = config.hidden_size self.dropout_module = Dropout(config.hidden_dropout_ratio) self.cross_self_attention = False self.self_attn = self.build_self_attention( self.embed_dim, config.nhead, config.attn_prob_dropout_ratio, ) self.activation_fn = util.get_activation_fn(activation=config.activation_fn) self.activation_dropout_module = Dropout(float(config.activation_dropout_ratio)) self.normalize_before = config.pre_layer_norm self.self_attn_layer_norm = LayerNorm(self.embed_dim) self.encoder_attn = self.build_encoder_attention( self.embed_dim, config.hidden_size, config.attn_prob_dropout_ratio, config.nhead, ) self.encoder_attn_layer_norm = LayerNorm(self.embed_dim) self.fc1 = QuantLinear( self.embed_dim, config.intermediate_size, ) self.fc2 = QuantLinear( config.intermediate_size, self.embed_dim, pre_activation="relu", ) self.final_layer_norm = LayerNorm(self.embed_dim) self.need_attn = True self.onnx_trace = False def build_self_attention( self, embed_dim, nhead, attn_dropout, add_bias_kv=False, add_zero_attn=False ): return MultiheadAttention( embed_dim, nhead, dropout=attn_dropout, add_bias_kv=add_bias_kv, add_zero_attn=add_zero_attn, self_attention=not self.cross_self_attention, is_decoder=True, ) def build_encoder_attention( self, embed_dim, encoder_embed_dim, attn_dropout, nhead ): return MultiheadAttention( embed_dim, nhead, kdim=encoder_embed_dim, vdim=encoder_embed_dim, dropout=attn_dropout, encoder_decoder_attention=True, is_decoder=True, ) def prepare_for_onnx_export_(self): self.onnx_trace = True def residual_connection(self, x, residual): return residual + x def forward( self, x, encoder_out: Optional[torch.Tensor] = None, encoder_padding_mask: Optional[torch.Tensor] = None, incremental_state: Optional[Dict[str, Dict[str, Optional[Tensor]]]] = None, prev_self_attn_state: Optional[List[torch.Tensor]] = None, prev_attn_state: Optional[List[torch.Tensor]] = None, self_attn_mask: Optional[torch.Tensor] = None, self_attn_padding_mask: Optional[torch.Tensor] = None, need_attn: bool = False, need_head_weights: bool = False, ): if need_head_weights: need_attn = True x = x.transpose(0, 1) residual = x if self.normalize_before: x = self.self_attn_layer_norm(x) if prev_self_attn_state is not None: prev_key, prev_value = prev_self_attn_state[:2] saved_state: Dict[str, Optional[Tensor]] = { "prev_key": prev_key, "prev_value": prev_value, } if len(prev_self_attn_state) >= 3: saved_state["prev_key_padding_mask"] = prev_self_attn_state[2] assert incremental_state is not None self.self_attn._set_input_buffer(incremental_state, saved_state) _self_attn_input_buffer = self.self_attn._get_input_buffer(incremental_state) if self.cross_self_attention and not ( incremental_state is not None and _self_attn_input_buffer is not None and "prev_key" in _self_attn_input_buffer ): if self_attn_mask is not None: assert encoder_out is not None self_attn_mask = torch.cat( (x.new_zeros(x.size(0), encoder_out.size(0)), self_attn_mask), dim=1 ) if self_attn_padding_mask is not None: if encoder_padding_mask is None: assert encoder_out is not None encoder_padding_mask = self_attn_padding_mask.new_zeros( encoder_out.size(1), encoder_out.size(0) ) self_attn_padding_mask = torch.cat( (encoder_padding_mask, self_attn_padding_mask), dim=1 ) assert encoder_out is not None y = torch.cat((encoder_out, x), dim=0) else: y = x x, attn = self.self_attn( query=x, key=y, value=y, key_padding_mask=self_attn_padding_mask, incremental_state=incremental_state, need_weights=False, attn_mask=self_attn_mask, ) x = self.dropout_module(x) x = self.residual_connection(x, residual) if not self.normalize_before: x = self.self_attn_layer_norm(x) if self.encoder_attn is not None and encoder_out is not None: if ( encoder_out.shape[1] != x.shape[1] and x.shape[1] % encoder_out.shape[1] == 0 ): beam_size = int(x.shape[1] / encoder_out.shape[1]) encoder_out = encoder_out.repeat_interleave(beam_size, 1) encoder_padding_mask = encoder_padding_mask.repeat_interleave( beam_size, 0 ) residual = x if self.normalize_before: x = self.encoder_attn_layer_norm(x) if prev_attn_state is not None: prev_key, prev_value = prev_attn_state[:2] saved_state: Dict[str, Optional[Tensor]] = { "prev_key": prev_key, "prev_value": prev_value, } if len(prev_attn_state) >= 3: saved_state["prev_key_padding_mask"] = prev_attn_state[2] assert incremental_state is not None self.encoder_attn._set_input_buffer(incremental_state, saved_state) x, attn = self.encoder_attn( query=x, key=encoder_out, value=encoder_out, key_padding_mask=encoder_padding_mask, incremental_state=incremental_state, static_kv=True, need_weights=need_attn or (not self.training and self.need_attn), need_head_weights=need_head_weights, ) x = self.dropout_module(x) x = self.residual_connection(x, residual) if not self.normalize_before: x = self.encoder_attn_layer_norm(x) residual = x if self.normalize_before: x = self.final_layer_norm(x) x = self.activation_fn(self.fc1(x)) x = self.activation_dropout_module(x) x = self.fc2(x) x = self.dropout_module(x) x = self.residual_connection(x, residual) if not self.normalize_before: x = self.final_layer_norm(x) if self.onnx_trace and incremental_state is not None: saved_state = self.self_attn._get_input_buffer(incremental_state) assert saved_state is not None if self_attn_padding_mask is not None: self_attn_state = [ saved_state["prev_key"], saved_state["prev_value"], saved_state["prev_key_padding_mask"], ] else: self_attn_state = [saved_state["prev_key"], saved_state["prev_value"]] return x, attn, self_attn_state x = x.transpose(0, 1) return x, attn, None def make_generation_fast_(self, need_attn: bool = False, **kwargs): self.need_attn = need_attn class TransformerEmbeddingLayer(TransformerEmbeddingLayerBase): def __init__(self, config): super().__init__() self.emb_lookup = nn.Embedding( config.vocab_size, config.embedding_dim, padding_idx=config.padding_idx ) self.emb_lookup.to(dtype=(torch.half if config.fp16 else torch.float)) self.embeddings = self.emb_lookup.weight nn.init.normal_(self.embeddings, mean=0, std=config.embedding_dim ** -0.5) nn.init.constant_(self.embeddings[config.padding_idx], 0) self.embed_positions = SinusoidalPositionalEmbedding( config.embedding_dim, config.padding_idx, config.max_seq_len, config.fp16 ) self.embedding_dim = config.embedding_dim self.dropout = Dropout(config.dropout) self.emb_quant = TensorQuantizer(weight_quant_config) self.config = config def forward(self, input, step=0): x = self.emb_lookup(input) x = self.emb_quant(x) x = math.sqrt(self.embedding_dim) * x x += self.embed_positions(input, step) x = self.dropout(x) return x class SinusoidalPositionalEmbedding(nn.Module): def __init__(self, embedding_dim, padding_idx, init_size=1024, fp16=False): super().__init__() self.embedding_dim = embedding_dim self.padding_idx = padding_idx self.weights = SinusoidalPositionalEmbedding.get_embedding( init_size, embedding_dim, padding_idx ) if fp16: self.weights = self.weights.to(torch.half) @staticmethod def get_embedding( num_embeddings: int, embedding_dim: int, padding_idx: Optional[int] = None ): half_dim = embedding_dim // 2 emb = math.log(10000) / (half_dim - 1) emb = torch.exp(torch.arange(half_dim, dtype=torch.float) * -emb) emb = torch.arange(num_embeddings, dtype=torch.float).unsqueeze( 1 ) * emb.unsqueeze(0) emb = torch.cat([torch.sin(emb), torch.cos(emb)], dim=1).view( num_embeddings, -1 ) if embedding_dim % 2 == 1: # zero pad emb = torch.cat([emb, torch.zeros(num_embeddings, 1)], dim=1) return emb def make_positions(self, tensor, padding_idx, step): mask = tensor.ne(padding_idx).int() return ((torch.cumsum(mask, dim=1).type_as(mask) - 1 + step) * mask).long() def forward( self, input, step=0, incremental_state=None, timestep=None, positions=None, ): bsz, seq_len = input.size(0), input.size(1) positions = self.make_positions(input, self.padding_idx, step) mask = ( torch.ne(input, self.padding_idx) .unsqueeze(2) .expand(bsz, seq_len, self.embedding_dim) ) return ( self.weights.to(input.device) .index_select(0, positions.view(-1)) .view(bsz, seq_len, -1) * mask ).detach()

true

f704c7064a6678cc5c17790c675482e38ef55a1b

2,392

py

Python

api/server/swagger_server/models/api_generate_code_response.py

srishtipithadia/mlx

2fb61a8840696c7ede77cd600caa8922178ec8b0

[ "Apache-2.0" ]

null

api/server/swagger_server/models/api_generate_code_response.py

srishtipithadia/mlx

2fb61a8840696c7ede77cd600caa8922178ec8b0

[ "Apache-2.0" ]

1

2021-09-21T23:31:13.000Z

api/server/swagger_server/models/api_generate_code_response.py

srishtipithadia/mlx

2fb61a8840696c7ede77cd600caa8922178ec8b0

[ "Apache-2.0" ]

null

# Copyright 2021 IBM Corporation # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # coding: utf-8 from __future__ import absolute_import from datetime import date, datetime # noqa: F401 from typing import List, Dict # noqa: F401 from swagger_server.models.base_model_ import Model from swagger_server import util class ApiGenerateCodeResponse(Model): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. """ def __init__(self, script: str=None): # noqa: E501 """ApiGenerateCodeResponse - a model defined in Swagger :param script: The script of this ApiGenerateCodeResponse. # noqa: E501 :type script: str """ self.swagger_types = { 'script': str } self.attribute_map = { 'script': 'script' } self._script = script @classmethod def from_dict(cls, dikt) -> 'ApiGenerateCodeResponse': """Returns the dict as a model :param dikt: A dict. :type: dict :return: The apiGenerateCodeResponse of this ApiGenerateCodeResponse. # noqa: E501 :rtype: ApiGenerateCodeResponse """ return util.deserialize_model(dikt, cls) @property def script(self) -> str: """Gets the script of this ApiGenerateCodeResponse. The script source code to run the component in a pipeline # noqa: E501 :return: The script of this ApiGenerateCodeResponse. :rtype: str """ return self._script @script.setter def script(self, script: str): """Sets the script of this ApiGenerateCodeResponse. The script source code to run the component in a pipeline # noqa: E501 :param script: The script of this ApiGenerateCodeResponse. :type script: str """ self._script = script

29.9

91

0.669314

from __future__ import absolute_import from datetime import date, datetime from typing import List, Dict from swagger_server.models.base_model_ import Model from swagger_server import util class ApiGenerateCodeResponse(Model): def __init__(self, script: str=None): self.swagger_types = { 'script': str } self.attribute_map = { 'script': 'script' } self._script = script @classmethod def from_dict(cls, dikt) -> 'ApiGenerateCodeResponse': return util.deserialize_model(dikt, cls) @property def script(self) -> str: return self._script @script.setter def script(self, script: str): self._script = script

true

f704c748c77fe552c4d56bef1c5dbb0e85cd8b5f

917

py

Python

abc231/c/main.py

nakamuloud/atcoder

aa986bc31ed050bac983888ec500c47f9d12ad2a

[ "MIT" ]

null

abc231/c/main.py

nakamuloud/atcoder

aa986bc31ed050bac983888ec500c47f9d12ad2a

[ "MIT" ]

null

abc231/c/main.py

nakamuloud/atcoder

aa986bc31ed050bac983888ec500c47f9d12ad2a

[ "MIT" ]

null

#!/usr/bin/env python3 import sys from bisect import bisect, bisect_left, bisect_right, insort, insort_left, insort_right # type: ignore from collections import Counter, defaultdict, deque # type: ignore from fractions import gcd # type: ignore from heapq import heapify, heappop, heappush, heappushpop, heapreplace, merge # type: ignore from itertools import accumulate, combinations, permutations, product # type: ignore N, Q = map(int, input().split()) A = list(map(int, input().split())) x = [] for i in range(Q): x.append(int(input())) A.sort(reverse=True) left = 0 right = N - 1 num = 0 for j in range(Q): while right - left > 0: print("left", left, "right", right) mid = int((left + right) / 2) if A[mid] < x[j]: right = mid + 1 elif A[mid] > x[j]: left = mid - 1 else: break num = mid print("mid", num)

26.970588

103

0.61614

import sys from bisect import bisect, bisect_left, bisect_right, insort, insort_left, insort_right from collections import Counter, defaultdict, deque from fractions import gcd from heapq import heapify, heappop, heappush, heappushpop, heapreplace, merge from itertools import accumulate, combinations, permutations, product N, Q = map(int, input().split()) A = list(map(int, input().split())) x = [] for i in range(Q): x.append(int(input())) A.sort(reverse=True) left = 0 right = N - 1 num = 0 for j in range(Q): while right - left > 0: print("left", left, "right", right) mid = int((left + right) / 2) if A[mid] < x[j]: right = mid + 1 elif A[mid] > x[j]: left = mid - 1 else: break num = mid print("mid", num)

true

f704c7ac312e7babdba94522a4ea34a2966ab06b

4,574

py

Python

test/dpt_tests/dpt_time_test.py

cyberjunky/xknx

c708ed6a2ca6449b74c6cea197d658e3399b99d1

[ "MIT" ]

1

2020-12-09T16:17:49.000Z

test/dpt_tests/dpt_time_test.py

cyberjunky/xknx

c708ed6a2ca6449b74c6cea197d658e3399b99d1

[ "MIT" ]

null

test/dpt_tests/dpt_time_test.py

cyberjunky/xknx

c708ed6a2ca6449b74c6cea197d658e3399b99d1

[ "MIT" ]

null

"""Unit test for KNX time objects.""" import unittest from xknx.dpt import DPTTime, DPTWeekday from xknx.exceptions import ConversionError class TestDPTTime(unittest.TestCase): """Test class for KNX time objects.""" # # TEST NORMAL TIME # def test_from_knx(self): """Test parsing of DPTTime object from binary values. Example 1.""" self.assertEqual(DPTTime().from_knx((0x4D, 0x17, 0x2A)), {'weekday': DPTWeekday.TUESDAY, 'hours': 13, 'minutes': 23, 'seconds': 42}) def test_to_knx(self): """Testing KNX/Byte representation of DPTTime object.""" raw = DPTTime().to_knx( {'weekday': DPTWeekday.TUESDAY, 'hours': 13, 'minutes': 23, 'seconds': 42}) self.assertEqual(raw, (0x4D, 0x17, 0x2A)) # # TEST MAXIMUM TIME # def test_to_knx_max(self): """Testing KNX/Byte representation of DPTTime object. Maximum values.""" raw = DPTTime().to_knx( {'weekday': DPTWeekday.SUNDAY, 'hours': 23, 'minutes': 59, 'seconds': 59}) self.assertEqual(raw, (0xF7, 0x3b, 0x3b)) def test_from_knx_max(self): """Test parsing of DPTTime object from binary values. Example 2.""" self.assertEqual(DPTTime().from_knx((0xF7, 0x3b, 0x3b)), {'weekday': DPTWeekday.SUNDAY, 'hours': 23, 'minutes': 59, 'seconds': 59}) # # TEST MINIMUM TIME # def test_to_knx_min(self): """Testing KNX/Byte representation of DPTTime object. Minimum values.""" raw = DPTTime().to_knx( {'weekday': DPTWeekday.NONE, 'hours': 0, 'minutes': 0, 'seconds': 0}) self.assertEqual(raw, (0x0, 0x0, 0x0)) def test_from_knx_min(self): """Test parsing of DPTTime object from binary values. Example 3.""" self.assertEqual(DPTTime().from_knx((0x0, 0x0, 0x0)), {'weekday': DPTWeekday.NONE, 'hours': 0, 'minutes': 0, 'seconds': 0}) # # TEST INITIALIZATION # def test_to_knx_default(self): """Testing default initialization of DPTTime object.""" self.assertEqual(DPTTime().to_knx({}), (0x0, 0x0, 0x0)) def test_from_knx_wrong_size(self): """Test parsing from DPTTime object from wrong binary values (wrong size).""" with self.assertRaises(ConversionError): DPTTime().from_knx((0xF8, 0x23)) def test_from_knx_wrong_bytes(self): """Test parsing from DPTTime object from wrong binary values (wrong bytes).""" with self.assertRaises(ConversionError): # thirs parameter exceeds limit DPTTime().from_knx((0xF7, 0x3b, 0x3c)) def test_from_knx_wrong_type(self): """Test parsing from DPTTime object from wrong binary values (wrong type).""" with self.assertRaises(ConversionError): DPTTime().from_knx((0xF8, "0x23")) def test_to_knx_wrong_parameter(self): """Test parsing from DPTTime object from wrong string value.""" with self.assertRaises(ConversionError): DPTTime().to_knx("fnord") def test_to_knx_wrong_seconds(self): """Test parsing from DPTTime object from wrong seconds value.""" with self.assertRaises(ConversionError): DPTTime().to_knx({ 'hours': 12, 'minutes': 42, 'seconds': 61 }) def test_to_knx_wrong_minutes(self): """Test parsing from DPTTime object from wrong minutes value.""" with self.assertRaises(ConversionError): DPTTime().to_knx({ 'hours': 12, 'minutes': 61, 'seconds': 53 }) def test_to_knx_wrong_hours(self): """Test parsing from DPTTime object from wrong hours value.""" with self.assertRaises(ConversionError): DPTTime().to_knx({ 'hours': 24, 'minutes': 42, 'seconds': 53 }) def test_test_range_wrong_weekday(self): """Test range testing with wrong weekday (Cant be tested with normal from_/to_knx).""" # pylint: disable=protected-access self.assertFalse(DPTTime._test_range(8, 0, 0, 0))

35.184615

94

0.555969

import unittest from xknx.dpt import DPTTime, DPTWeekday from xknx.exceptions import ConversionError class TestDPTTime(unittest.TestCase): def test_from_knx(self): self.assertEqual(DPTTime().from_knx((0x4D, 0x17, 0x2A)), {'weekday': DPTWeekday.TUESDAY, 'hours': 13, 'minutes': 23, 'seconds': 42}) def test_to_knx(self): raw = DPTTime().to_knx( {'weekday': DPTWeekday.TUESDAY, 'hours': 13, 'minutes': 23, 'seconds': 42}) self.assertEqual(raw, (0x4D, 0x17, 0x2A)) def test_to_knx_max(self): raw = DPTTime().to_knx( {'weekday': DPTWeekday.SUNDAY, 'hours': 23, 'minutes': 59, 'seconds': 59}) self.assertEqual(raw, (0xF7, 0x3b, 0x3b)) def test_from_knx_max(self): self.assertEqual(DPTTime().from_knx((0xF7, 0x3b, 0x3b)), {'weekday': DPTWeekday.SUNDAY, 'hours': 23, 'minutes': 59, 'seconds': 59}) def test_to_knx_min(self): raw = DPTTime().to_knx( {'weekday': DPTWeekday.NONE, 'hours': 0, 'minutes': 0, 'seconds': 0}) self.assertEqual(raw, (0x0, 0x0, 0x0)) def test_from_knx_min(self): self.assertEqual(DPTTime().from_knx((0x0, 0x0, 0x0)), {'weekday': DPTWeekday.NONE, 'hours': 0, 'minutes': 0, 'seconds': 0}) def test_to_knx_default(self): self.assertEqual(DPTTime().to_knx({}), (0x0, 0x0, 0x0)) def test_from_knx_wrong_size(self): with self.assertRaises(ConversionError): DPTTime().from_knx((0xF8, 0x23)) def test_from_knx_wrong_bytes(self): with self.assertRaises(ConversionError): DPTTime().from_knx((0xF7, 0x3b, 0x3c)) def test_from_knx_wrong_type(self): with self.assertRaises(ConversionError): DPTTime().from_knx((0xF8, "0x23")) def test_to_knx_wrong_parameter(self): with self.assertRaises(ConversionError): DPTTime().to_knx("fnord") def test_to_knx_wrong_seconds(self): with self.assertRaises(ConversionError): DPTTime().to_knx({ 'hours': 12, 'minutes': 42, 'seconds': 61 }) def test_to_knx_wrong_minutes(self): with self.assertRaises(ConversionError): DPTTime().to_knx({ 'hours': 12, 'minutes': 61, 'seconds': 53 }) def test_to_knx_wrong_hours(self): with self.assertRaises(ConversionError): DPTTime().to_knx({ 'hours': 24, 'minutes': 42, 'seconds': 53 }) def test_test_range_wrong_weekday(self): self.assertFalse(DPTTime._test_range(8, 0, 0, 0))

true

f704c9482c2b74b28c4faceee71e9f4dcabea3a3

316

py

Python

johann/__init__.py

lobotmcj/johann

c188c6f31446907a5d6a237191540856f02a91a0

[ "BSD-3-Clause" ]

11

2020-08-27T18:33:09.000Z

2022-03-18T03:09:03.000Z

johann/__init__.py

johannsdg/johann

c188c6f31446907a5d6a237191540856f02a91a0

[ "BSD-3-Clause" ]

null

johann/__init__.py

johannsdg/johann

c188c6f31446907a5d6a237191540856f02a91a0

[ "BSD-3-Clause" ]

2

2020-09-04T03:07:35.000Z

2020-11-06T19:08:03.000Z

# Copyright (c) 2019-present, The Johann Authors. All Rights Reserved. # Use of this source code is governed by a BSD-3-clause license that can # be found in the LICENSE file. See the AUTHORS file for names of contributors. """Johann, lightweight and flexible scenario orchestration""" __version__ = "0.3.0-alpha"

39.5

79

0.759494

__version__ = "0.3.0-alpha"

true

f704cb298b4264480818031b4a5dc27b92ebb46c

2,543

py

Python

o3seespy/command/layer.py

vijaypolimeru/o3seespy

c9ef0c27f685de705721b10eb1ea81c3a3c24c4e

[ "MIT", "BSD-3-Clause" ]

null

o3seespy/command/layer.py

vijaypolimeru/o3seespy

c9ef0c27f685de705721b10eb1ea81c3a3c24c4e

[ "MIT", "BSD-3-Clause" ]

1

2021-06-25T15:33:31.000Z

o3seespy/command/layer.py

millen1m/o3seespy

7eead6aef8055f73af39b969e0d3499a67e1737f

[ "MIT", "BSD-3-Clause" ]

1

2020-12-12T21:01:42.000Z

from o3seespy.base_model import OpenSeesObject class LayerBase(OpenSeesObject): op_base_type = "layer" class Straight(LayerBase): """ The Straight Layer Class The layer command is used to generate a number of fibers along a line or a circular arc. """ op_type = 'straight' def __init__(self, osi, mat, num_fiber, area_fiber, start, end): """ Initial method for Straight Parameters ---------- mat: obj Material tag associated with this fiber (uniaxialmaterial tag for a fibersection and ndmaterial tag for use in an ndfibersection). num_fiber: int Number of fibers along line area_fiber: float Area of each fiber start: list Y & z-coordinates of first fiber in line (local coordinate system) end: list Y & z-coordinates of last fiber in line (local coordinate system) """ self.mat = mat self.num_fiber = int(num_fiber) self.area_fiber = float(area_fiber) self.start = start self.end = end self._parameters = [self.op_type, self.mat.tag, self.num_fiber, self.area_fiber, *self.start, *self.end] self.to_process(osi) class Circ(LayerBase): """ The Circ Layer Class This command is used to construct a line of fibers along a circular arc """ op_type = 'circ' def __init__(self, osi, mat, num_fiber, area_fiber, center, radius, ang=None): """ Initial method for Circ Parameters ---------- mat: obj Material tag associated with this fiber (uniaxialmaterial tag for a fibersection and ndmaterial tag for use in an ndfibersection). num_fiber: int Number of fibers along line area_fiber: float Area of each fiber center: listf Y & z-coordinates of center of circular arc radius: float Radius of circlular arc ang: listf Starting and ending angle (optional) [0.0, 360.0-360/num_fibres] """ self.mat = mat self.num_fiber = int(num_fiber) self.area_fiber = float(area_fiber) self.center = center self.radius = float(radius) self.ang = ang self._parameters = [self.op_type, self.mat.tag, self.num_fiber, self.area_fiber, *self.center, self.radius] if self.ang is not None: self._parameters += self.ang self.to_process(osi)

31.012195

119

0.604404

from o3seespy.base_model import OpenSeesObject class LayerBase(OpenSeesObject): op_base_type = "layer" class Straight(LayerBase): op_type = 'straight' def __init__(self, osi, mat, num_fiber, area_fiber, start, end): self.mat = mat self.num_fiber = int(num_fiber) self.area_fiber = float(area_fiber) self.start = start self.end = end self._parameters = [self.op_type, self.mat.tag, self.num_fiber, self.area_fiber, *self.start, *self.end] self.to_process(osi) class Circ(LayerBase): op_type = 'circ' def __init__(self, osi, mat, num_fiber, area_fiber, center, radius, ang=None): self.mat = mat self.num_fiber = int(num_fiber) self.area_fiber = float(area_fiber) self.center = center self.radius = float(radius) self.ang = ang self._parameters = [self.op_type, self.mat.tag, self.num_fiber, self.area_fiber, *self.center, self.radius] if self.ang is not None: self._parameters += self.ang self.to_process(osi)

true

f704ccc2e536cf7aaa02ae1d2d184594cab08683

14,888

py

Python

analyze.py

davidmam/BirdNET-Pi

873c8f4c56b30edb9297134a92a7c5a178c390e4

[ "Apache-2.0" ]

null

analyze.py

davidmam/BirdNET-Pi

873c8f4c56b30edb9297134a92a7c5a178c390e4

[ "Apache-2.0" ]

null

analyze.py

davidmam/BirdNET-Pi

873c8f4c56b30edb9297134a92a7c5a178c390e4

[ "Apache-2.0" ]

null

# BirdWeather edits by @timsterc # Other edits by @CaiusX and @mcguirepr89 import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' os.environ['CUDA_VISIBLE_DEVICES'] = '' try: import tflite_runtime.interpreter as tflite except: from tensorflow import lite as tflite import argparse import operator import librosa import numpy as np import math import time from decimal import Decimal import json ############################################################################### import requests import mysql.connector ############################################################################### import datetime import pytz from tzlocal import get_localzone from pathlib import Path def loadModel(): global INPUT_LAYER_INDEX global OUTPUT_LAYER_INDEX global MDATA_INPUT_INDEX global CLASSES print('LOADING TF LITE MODEL...', end=' ') # Load TFLite model and allocate tensors. interpreter = tflite.Interpreter(model_path='model/BirdNET_6K_GLOBAL_MODEL.tflite',num_threads=2) interpreter.allocate_tensors() # Get input and output tensors. input_details = interpreter.get_input_details() output_details = interpreter.get_output_details() # Get input tensor index INPUT_LAYER_INDEX = input_details[0]['index'] MDATA_INPUT_INDEX = input_details[1]['index'] OUTPUT_LAYER_INDEX = output_details[0]['index'] # Load labels CLASSES = [] with open('model/labels.txt', 'r') as lfile: for line in lfile.readlines(): CLASSES.append(line.replace('\n', '')) print('DONE!') return interpreter def loadCustomSpeciesList(path): slist = [] if os.path.isfile(path): with open(path, 'r') as csfile: for line in csfile.readlines(): slist.append(line.replace('\r', '').replace('\n', '')) return slist def splitSignal(sig, rate, overlap, seconds=3.0, minlen=1.5): # Split signal with overlap sig_splits = [] for i in range(0, len(sig), int((seconds - overlap) * rate)): split = sig[i:i + int(seconds * rate)] # End of signal? if len(split) < int(minlen * rate): break # Signal chunk too short? Fill with zeros. if len(split) < int(rate * seconds): temp = np.zeros((int(rate * seconds))) temp[:len(split)] = split split = temp sig_splits.append(split) return sig_splits def readAudioData(path, overlap, sample_rate=48000): print('READING AUDIO DATA...', end=' ', flush=True) # Open file with librosa (uses ffmpeg or libav) sig, rate = librosa.load(path, sr=sample_rate, mono=True, res_type='kaiser_fast') # Split audio into 3-second chunks chunks = splitSignal(sig, rate, overlap) print('DONE! READ', str(len(chunks)), 'CHUNKS.') return chunks def convertMetadata(m): # Convert week to cosine if m[2] >= 1 and m[2] <= 48: m[2] = math.cos(math.radians(m[2] * 7.5)) + 1 else: m[2] = -1 # Add binary mask mask = np.ones((3,)) if m[0] == -1 or m[1] == -1: mask = np.zeros((3,)) if m[2] == -1: mask[2] = 0.0 return np.concatenate([m, mask]) def custom_sigmoid(x, sensitivity=1.0): return 1 / (1.0 + np.exp(-sensitivity * x)) def predict(sample, interpreter, sensitivity): # Make a prediction interpreter.set_tensor(INPUT_LAYER_INDEX, np.array(sample[0], dtype='float32')) interpreter.set_tensor(MDATA_INPUT_INDEX, np.array(sample[1], dtype='float32')) interpreter.invoke() prediction = interpreter.get_tensor(OUTPUT_LAYER_INDEX)[0] # Apply custom sigmoid p_sigmoid = custom_sigmoid(prediction, sensitivity) # Get label and scores for pooled predictions p_labels = dict(zip(CLASSES, p_sigmoid)) # Sort by score p_sorted = sorted(p_labels.items(), key=operator.itemgetter(1), reverse=True) # Remove species that are on blacklist for i in range(min(10, len(p_sorted))): if p_sorted[i][0] in ['Human_Human', 'Non-bird_Non-bird', 'Noise_Noise']: p_sorted[i] = (p_sorted[i][0], 0.0) # Only return first the top ten results return p_sorted[:10] def analyzeAudioData(chunks, lat, lon, week, sensitivity, overlap, interpreter): detections = {} start = time.time() print('ANALYZING AUDIO...', end=' ', flush=True) # Convert and prepare metadata mdata = convertMetadata(np.array([lat, lon, week])) mdata = np.expand_dims(mdata, 0) # Parse every chunk pred_start = 0.0 for c in chunks: # Prepare as input signal sig = np.expand_dims(c, 0) # Make prediction p = predict([sig, mdata], interpreter, sensitivity) # Save result and timestamp pred_end = pred_start + 3.0 detections[str(pred_start) + ';' + str(pred_end)] = p pred_start = pred_end - overlap print('DONE! Time', int((time.time() - start) * 10) / 10.0, 'SECONDS') return detections def writeResultsToFile(detections, min_conf, path): print('WRITING RESULTS TO', path, '...', end=' ') rcnt = 0 with open(path, 'w') as rfile: rfile.write('Start (s);End (s);Scientific name;Common name;Confidence\n') for d in detections: for entry in detections[d]: if entry[1] >= min_conf and (entry[0] in WHITE_LIST or len(WHITE_LIST) == 0): rfile.write(d + ';' + entry[0].replace('_', ';') + ';' + str(entry[1]) + '\n') rcnt += 1 print('DONE! WROTE', rcnt, 'RESULTS.') def main(): global WHITE_LIST # Parse passed arguments parser = argparse.ArgumentParser() parser.add_argument('--i', help='Path to input file.') parser.add_argument('--o', default='result.csv', help='Path to output file. Defaults to result.csv.') parser.add_argument('--lat', type=float, default=-1, help='Recording location latitude. Set -1 to ignore.') parser.add_argument('--lon', type=float, default=-1, help='Recording location longitude. Set -1 to ignore.') parser.add_argument('--week', type=int, default=-1, help='Week of the year when the recording was made. Values in [1, 48] (4 weeks per month). Set -1 to ignore.') parser.add_argument('--overlap', type=float, default=0.0, help='Overlap in seconds between extracted spectrograms. Values in [0.0, 2.9]. Defaults tp 0.0.') parser.add_argument('--sensitivity', type=float, default=1.0, help='Detection sensitivity; Higher values result in higher sensitivity. Values in [0.5, 1.5]. Defaults to 1.0.') parser.add_argument('--min_conf', type=float, default=0.1, help='Minimum confidence threshold. Values in [0.01, 0.99]. Defaults to 0.1.') parser.add_argument('--custom_list', default='', help='Path to text file containing a list of species. Not used if not provided.') parser.add_argument('--birdweather_id', default='99999', help='Private Station ID for BirdWeather.') args = parser.parse_args() # Load model interpreter = loadModel() # Load custom species list if not args.custom_list == '': WHITE_LIST = loadCustomSpeciesList(args.custom_list) else: WHITE_LIST = [] birdweather_id = args.birdweather_id # Read audio data audioData = readAudioData(args.i, args.overlap) # Get Date/Time from filename in case Pi gets behind #now = datetime.now() full_file_name = args.i file_name = Path(full_file_name).stem file_date = file_name.split('-birdnet-')[0] file_time = file_name.split('-birdnet-')[1] date_time_str = file_date + ' ' + file_time date_time_obj = datetime.datetime.strptime(date_time_str, '%Y-%m-%d %H:%M:%S') #print('Date:', date_time_obj.date()) #print('Time:', date_time_obj.time()) print('Date-time:', date_time_obj) now = date_time_obj current_date = now.strftime("%Y/%m/%d") current_time = now.strftime("%H:%M:%S") current_iso8601 = now.astimezone(get_localzone()).isoformat() week_number = int(now.strftime("%V")) week = max(1, min(week_number, 48)) sensitivity = max(0.5, min(1.0 - (args.sensitivity - 1.0), 1.5)) # Process audio data and get detections detections = analyzeAudioData(audioData, args.lat, args.lon, week, sensitivity, args.overlap, interpreter) # Write detections to output file min_conf = max(0.01, min(args.min_conf, 0.99)) writeResultsToFile(detections, min_conf, args.o) ############################################################################### ############################################################################### soundscape_uploaded = False # Write detections to Database for i in detections: print("\n", detections[i][0],"\n") with open('BirdDB.txt', 'a') as rfile: for d in detections: print("\n", "Database Entry", "\n") for entry in detections[d]: if entry[1] >= min_conf and (entry[0] in WHITE_LIST or len(WHITE_LIST) == 0): rfile.write(str(current_date) + ';' + str(current_time) + ';' + entry[0].replace('_', ';') + ';' \ + str(entry[1]) +";" + str(args.lat) + ';' + str(args.lon) + ';' + str(min_conf) + ';' + str(week) + ';' \ + str(sensitivity) +';' + str(args.overlap) + '\n') def insert_variables_into_table(Date, Time, Sci_Name, Com_Name, Confidence, Lat, Lon, Cutoff, Week, Sens, Overlap): try: connection = mysql.connector.connect(host='localhost', database='birds', user='birder', password='birdnet') cursor = connection.cursor() mySql_insert_query = """INSERT INTO detections (Date, Time, Sci_Name, Com_Name, Confidence, Lat, Lon, Cutoff, Week, Sens, Overlap) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s) """ record = (Date, Time, Sci_Name, Com_Name, Confidence, Lat, Lon, Cutoff, Week, Sens, Overlap) cursor.execute(mySql_insert_query, record) connection.commit() print("Record inserted successfully into detections table") except mysql.connector.Error as error: print("Failed to insert record into detections table {}".format(error)) finally: if connection.is_connected(): connection.close() print("MySQL connection is closed") species = entry[0] sci_name,com_name = species.split('_') insert_variables_into_table(str(current_date), str(current_time), sci_name, com_name, \ str(entry[1]), str(args.lat), str(args.lon), str(min_conf), str(week), \ str(args.sensitivity), str(args.overlap)) print(str(current_date) + ';' + str(current_time) + ';' + entry[0].replace('_', ';') + ';' + str(entry[1]) +";" + str(args.lat) + ';' + str(args.lon) + ';' + str(min_conf) + ';' + str(week) + ';' + str(args.sensitivity) +';' + str(args.overlap) + '\n') if birdweather_id != "99999": if soundscape_uploaded is False: # POST soundscape to server soundscape_url = "https://app.birdweather.com/api/v1/stations/" + birdweather_id + "/soundscapes" + "?timestamp=" + current_iso8601 with open(args.i, 'rb') as f: wav_data = f.read() response = requests.post(url=soundscape_url, data=wav_data, headers={'Content-Type': 'application/octet-stream'}) print("Soundscape POST Response Status - ", response.status_code) sdata = response.json() soundscape_id = sdata['soundscape']['id'] soundscape_uploaded = True # POST detection to server detection_url = "https://app.birdweather.com/api/v1/stations/" + birdweather_id + "/detections" start_time = d.split(';')[0] end_time = d.split(';')[1] post_begin = "{ " now_p_start = now + datetime.timedelta(seconds=float(start_time)) current_iso8601 = now_p_start.astimezone(get_localzone()).isoformat() post_timestamp = "\"timestamp\": \"" + current_iso8601 + "\"," post_lat = "\"lat\": " + str(args.lat) + "," post_lon = "\"lon\": " + str(args.lon) + "," post_soundscape_id = "\"soundscapeId\": " + str(soundscape_id) + "," post_soundscape_start_time = "\"soundscapeStartTime\": " + start_time + "," post_soundscape_end_time = "\"soundscapeEndTime\": " + end_time + "," post_commonName = "\"commonName\": \"" + entry[0].split('_')[1] + "\"," post_scientificName = "\"scientificName\": \"" + entry[0].split('_')[0] + "\"," post_algorithm = "\"algorithm\": " + "\"alpha\"" + "," post_confidence = "\"confidence\": " + str(entry[1]) post_end = " }" post_json = post_begin + post_timestamp + post_lat + post_lon + post_soundscape_id + post_soundscape_start_time + post_soundscape_end_time + post_commonName + post_scientificName + post_algorithm + post_confidence + post_end print(post_json) response = requests.post(detection_url, json=json.loads(post_json)) print("Detection POST Response Status - ", response.status_code) #time.sleep(3) ############################################################################### ############################################################################### if __name__ == '__main__': main() # Example calls # python3 analyze.py --i 'example/XC558716 - Soundscape.mp3' --lat 35.4244 --lon -120.7463 --week 18 # python3 analyze.py --i 'example/XC563936 - Soundscape.mp3' --lat 47.6766 --lon -122.294 --week 11 --overlap 1.5 --min_conf 0.25 --sensitivity 1.25 --custom_list 'example/custom_species_list.txt'

42.056497

272

0.558907

import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' os.environ['CUDA_VISIBLE_DEVICES'] = '' try: import tflite_runtime.interpreter as tflite except: from tensorflow import lite as tflite import argparse import operator import librosa import numpy as np import math import time from decimal import Decimal import json ate = now.strftime("%Y/%m/%d") current_time = now.strftime("%H:%M:%S") current_iso8601 = now.astimezone(get_localzone()).isoformat() week_number = int(now.strftime("%V")) week = max(1, min(week_number, 48)) sensitivity = max(0.5, min(1.0 - (args.sensitivity - 1.0), 1.5)) detections = analyzeAudioData(audioData, args.lat, args.lon, week, sensitivity, args.overlap, interpreter) min_conf = max(0.01, min(args.min_conf, 0.99)) writeResultsToFile(detections, min_conf, args.o)

true

f704ccdab8daddc07843c80260a004c3a4b58cc3

40,273

py

Python

tests/unit_test/action/action_test.py

Anitej/kairon

61d6bd7f230a744303abab42e3b54b0381fee7da

[ "Apache-2.0" ]

null

tests/unit_test/action/action_test.py

Anitej/kairon

61d6bd7f230a744303abab42e3b54b0381fee7da

[ "Apache-2.0" ]

null

tests/unit_test/action/action_test.py

Anitej/kairon

61d6bd7f230a744303abab42e3b54b0381fee7da

[ "Apache-2.0" ]

null

import json import os os.environ["system_file"] = "./tests/testing_data/system.yaml" from typing import Dict, Text, Any, List import pytest import responses from mongoengine import connect, disconnect from rasa_sdk import Tracker from rasa_sdk.executor import CollectingDispatcher from kairon.action_server.data_objects import HttpActionRequestBody, HttpActionConfig, HttpActionLog from kairon.action_server.actions import ActionUtility, HttpAction from kairon.action_server.exception import HttpActionFailure from kairon.utils import Utility def pytest_configure(): return { 'db_url': None, } class TestActions: @pytest.fixture(autouse=True) def setup(self): os.environ["system_file"] = "./tests/testing_data/system.yaml" Utility.load_evironment() db_url = Utility.environment['database']["url"] pytest.db_url = db_url connect(host=db_url) @pytest.fixture def mock_get_http_action_exception(self, monkeypatch): def _raise_excep(*arge, **kwargs): raise HttpActionFailure("No HTTP action found for bot and action") monkeypatch.setattr(ActionUtility, "get_http_action_config", _raise_excep) @responses.activate def test_execute_http_request_getWith_auth_token(self): http_url = 'http://localhost:8080/mock' # file deepcode ignore HardcodedNonCryptoSecret: Random string for testing auth_token = "bearer jkhfhkujsfsfslfhjsfhkjsfhskhfksj" responses.add( method=responses.GET, url=http_url, json={'data': 'test_data', 'test_class': [{'key': 'value'}, {'key2': 'value2'}]}, status=200 ) response = ActionUtility.execute_http_request(auth_token=auth_token, http_url=http_url, request_method=responses.GET) assert response assert response['data'] == 'test_data' assert len(response['test_class']) == 2 assert response['test_class'][1]['key2'] == 'value2' assert responses.calls[0].request.headers['Authorization'] == auth_token @responses.activate def test_execute_http_request_get_no_auth_token(self): http_url = 'http://localhost:8080/mock' responses.add( method=responses.GET, url=http_url, json={'data': 'test_data', 'test_class': [{'key': 'value'}, {'key2': 'value2'}]}, status=200 ) response = ActionUtility.execute_http_request(auth_token=None, http_url=http_url, request_method=responses.GET) assert response assert response['data'] == 'test_data' assert len(response['test_class']) == 2 assert response['test_class'][1]['key2'] == 'value2' assert 'Authorization' not in responses.calls[0].request.headers @responses.activate def test_execute_http_request_post_with_auth_token(self): http_url = 'http://localhost:8080/mock' auth_token = "bearer jkhfhkujsfsfslfhjsfhkjsfhskhfksj" resp_msg = "Data added successfully" request_params = {'data': 'test_data', 'test_class': [{'key': 'value'}, {'key2': 'value2'}]} responses.add( method=responses.POST, url=http_url, body=resp_msg, status=200, match=[responses.json_params_matcher(request_params)] ) response = ActionUtility.execute_http_request(auth_token=auth_token, http_url=http_url, request_method=responses.POST, request_body=request_params) assert response assert response == resp_msg assert responses.calls[0].request.headers['Authorization'] == auth_token @responses.activate def test_execute_http_request_post_no_auth_token(self): http_url = 'http://localhost:8080/mock' resp_msg = "Data added successfully" request_params = {'data': 'test_data', 'test_class': [{'key': 'value'}, {'key2': 'value2'}]} responses.add( method=responses.POST, url=http_url, body=resp_msg, status=200, match=[responses.json_params_matcher(request_params)] ) response = ActionUtility.execute_http_request(auth_token=None, http_url=http_url, request_method=responses.POST, request_body=request_params) assert response assert response == resp_msg assert 'Authorization' not in responses.calls[0].request.headers @responses.activate def test_execute_http_request_put_with_auth_token(self): http_url = 'http://localhost:8080/mock' auth_token = "bearer jkhfhkujsfsfslfhjsfhkjsfhskhfksj" resp_msg = "Data updated successfully" request_params = {'data': 'test_data', 'test_class': [{'key': 'value'}, {'key2': 'value2'}]} responses.add( method=responses.PUT, url=http_url, body=resp_msg, status=200, match=[responses.json_params_matcher(request_params)] ) response = ActionUtility.execute_http_request(auth_token=auth_token, http_url=http_url, request_method=responses.PUT, request_body=request_params) assert response assert response == resp_msg assert responses.calls[0].request.headers['Authorization'] == auth_token @responses.activate def test_execute_http_request_put_no_auth_token(self): http_url = 'http://localhost:8080/mock' resp_msg = "Data updated successfully" request_params = {'data': 'test_data', 'test_class': [{'key': 'value'}, {'key2': 'value2'}]} responses.add( method=responses.PUT, url=http_url, body=resp_msg, status=200, match=[responses.json_params_matcher(request_params)] ) response = ActionUtility.execute_http_request(auth_token=None, http_url=http_url, request_method=responses.PUT, request_body=request_params) assert response assert response == resp_msg assert 'Authorization' not in responses.calls[0].request.headers @responses.activate def test_execute_http_request_delete_with_request_body_auth_token(self): http_url = 'http://localhost:8080/mock' auth_token = "bearer jkhfhkujsfsfslfhjsfhkjsfhskhfksj" resp_msg = "Data deleted successfully" request_params = {'data': 'test_data', 'test_class': [{'key': 'value'}, {'key2': 'value2'}]} responses.add( method=responses.DELETE, url=http_url, body=resp_msg, status=200, match=[responses.json_params_matcher(request_params)] ) response = ActionUtility.execute_http_request(auth_token=auth_token, http_url=http_url, request_method=responses.DELETE, request_body=request_params) assert response assert response == resp_msg assert responses.calls[0].request.headers['Authorization'] == auth_token @responses.activate def test_execute_http_request_delete_with_auth_token_no_request_body(self): http_url = 'http://localhost:8080/mock' auth_token = "bearer jkhfhkujsfsfslfhjsfhkjsfhskhfksj" resp_msg = "Data deleted successfully" responses.add( method=responses.DELETE, url=http_url, body=resp_msg, status=200, ) response = ActionUtility.execute_http_request(auth_token=auth_token, http_url=http_url, request_method=responses.DELETE, request_body=None) assert response assert response == resp_msg assert responses.calls[0].request.headers['Authorization'] == auth_token @responses.activate def test_execute_http_request_delete_no_auth_token(self): http_url = 'http://localhost:8080/mock' resp_msg = "Data updated successfully" request_params = {'data': 'test_data', 'test_class': [{'key': 'value'}, {'key2': 'value2'}]} responses.add( method=responses.DELETE, url=http_url, body=resp_msg, status=200, match=[ responses.json_params_matcher(request_params) ] ) response = ActionUtility.execute_http_request(auth_token=None, http_url=http_url, request_method=responses.DELETE, request_body=request_params) assert response assert response == resp_msg assert 'Authorization' not in responses.calls[0].request.headers def test_get_http_action_config(self): http_params = [HttpActionRequestBody(key="key1", value="value1", parameter_type="slot"), HttpActionRequestBody(key="key2", value="value2")] expected = HttpActionConfig( auth_token="bearer kjflksjflksajfljsdflinlsufisnflisjbjsdalibvs", action_name="http_action", response="json", http_url="http://test.com", request_method="GET", params_list=http_params, bot="bot", user="user" ).save().to_mongo().to_dict() actual = ActionUtility.get_http_action_config("bot", "http_action") assert actual is not None assert expected['auth_token'] == actual['auth_token'] assert expected['action_name'] == actual['action_name'] assert expected['response'] == actual['response'] assert expected['http_url'] == actual['http_url'] assert expected['request_method'] == actual['request_method'] assert expected['params_list'] is not None assert expected['params_list'][0]['key'] == actual['params_list'][0]['key'] assert expected['params_list'][0]['value'] == actual['params_list'][0]['value'] assert expected['params_list'][0]['parameter_type'] == actual['params_list'][0]['parameter_type'] assert expected['params_list'][1]['key'] == actual['params_list'][1]['key'] assert expected['params_list'][1]['value'] == actual['params_list'][1]['value'] assert expected['params_list'][1]['parameter_type'] == actual['params_list'][1]['parameter_type'] assert actual['status'] def test_get_http_action_config_deleted_action(self): http_params = [HttpActionRequestBody(key="key1", value="value1", parameter_type="slot"), HttpActionRequestBody(key="key2", value="value2")] HttpActionConfig( auth_token="", action_name="test_get_http_action_config_deleted_action", response="${RESPONSE}", http_url="http://www.digite.com", request_method="POST", params_list=http_params, bot="bot", user="user", status=False ).save().to_mongo().to_dict() expected = HttpActionConfig( auth_token="bearer kjflksjflksajfljsdflinlsufisnflisjbjsdalibvs", action_name="test_get_http_action_config_deleted_action", response="json", http_url="http://test.com", request_method="GET", params_list=http_params, bot="bot", user="user" ).save().to_mongo().to_dict() actual = ActionUtility.get_http_action_config("bot", "test_get_http_action_config_deleted_action") assert actual is not None assert expected['auth_token'] == actual['auth_token'] assert expected['action_name'] == actual['action_name'] assert expected['response'] == actual['response'] assert expected['http_url'] == actual['http_url'] assert expected['request_method'] == actual['request_method'] assert expected['params_list'] is not None assert expected['params_list'][0]['key'] == actual['params_list'][0]['key'] assert expected['params_list'][0]['value'] == actual['params_list'][0]['value'] assert expected['params_list'][0]['parameter_type'] == actual['params_list'][0]['parameter_type'] assert expected['params_list'][1]['key'] == actual['params_list'][1]['key'] assert expected['params_list'][1]['value'] == actual['params_list'][1]['value'] assert expected['params_list'][1]['parameter_type'] == actual['params_list'][1]['parameter_type'] assert actual['status'] def test_get_http_action_no_bot(self): try: ActionUtility.get_http_action_config(bot=None, action_name="http_action") assert False except HttpActionFailure as ex: assert str(ex) == "Bot name and action name are required" def test_get_http_action_no_http_action(self): try: ActionUtility.get_http_action_config(bot="bot", action_name=None) assert False except HttpActionFailure as ex: assert str(ex) == "Bot name and action name are required" def test_get_http_action_invalid_bot(self): http_params = [HttpActionRequestBody(key="key1", value="value1", parameter_type="slot"), HttpActionRequestBody(key="key2", value="value2")] HttpActionConfig( auth_token="bearer kjflksjflksajfljsdflinlsufisnflisjbjsdalibvs", action_name="http_action", response="json", http_url="http://test.com", request_method="GET", params_list=http_params, bot="bot", user="user" ).save().to_mongo().to_dict() try: ActionUtility.get_http_action_config("bot1", "http_action") assert False except HttpActionFailure as ex: assert str(ex).__contains__("No HTTP action found for bot") def test_get_http_action_invalid_http_action(self): http_params = [HttpActionRequestBody(key="key1", value="value1", parameter_type="slot"), HttpActionRequestBody(key="key2", value="value2")] HttpActionConfig( auth_token="bearer kjflksjflksajfljsdflinlsufisnflisjbjsdalibvs", action_name="http_action", response="json", http_url="http://test.com", request_method="GET", params_list=http_params, bot="bot", user="user" ).save().to_mongo().to_dict() try: ActionUtility.get_http_action_config("bot", "http_action1") assert False except HttpActionFailure as ex: assert str(ex).__contains__("No HTTP action found for bot") def test_get_http_action_no_request_body(self): http_params = [] HttpActionConfig( auth_token="bearer kjflksjflksajfljsdflinlsufisnflisjbjsdalibvs", action_name="http_action", response="json", http_url="http://test.com", request_method="GET", params_list=http_params, bot="bot", user="user" ).save().to_mongo().to_dict() try: ActionUtility.get_http_action_config("bot", "http_action1") assert False except HttpActionFailure as ex: assert str(ex).__contains__("No HTTP action found for bot") def test_prepare_request(self): slots = {"bot": "demo_bot", "http_action_config": "http_action_name", "slot_name": "param2value"} events = [{"event1": "hello"}, {"event2": "how are you"}] http_action_config_params = [HttpActionRequestBody(key="param1", value="value1"), HttpActionRequestBody(key="param2", value="slot_name", parameter_type="slot")] tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=None, followup_action=None, active_loop=None, latest_action_name=None) actual_request_body = ActionUtility.prepare_request(tracker=tracker, http_action_config_params=http_action_config_params) assert actual_request_body assert actual_request_body['param1'] == 'value1' assert actual_request_body['param2'] == 'param2value' def test_prepare_request_empty_slot(self): slots = {"bot": "demo_bot", "http_action_config": "http_action_name", "param2": "param2value"} events = [{"event1": "hello"}, {"event2": "how are you"}] http_action_config_params = [HttpActionRequestBody(key="param1", value="value1"), HttpActionRequestBody(key="param3", value="", parameter_type="slot")] tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=None, followup_action=None, active_loop=None, latest_action_name=None) request_params = ActionUtility.prepare_request(tracker=tracker, http_action_config_params=http_action_config_params) assert request_params['param1'] == "value1" assert not request_params['param3'] def test_prepare_request_sender_id(self): slots = {"bot": "demo_bot", "http_action_config": "http_action_name", "param2": "param2value"} events = [{"event1": "hello"}, {"event2": "how are you"}] http_action_config_params = [HttpActionRequestBody(key="param1", value="value1"), HttpActionRequestBody(key="user_id", value="", parameter_type="sender_id")] tracker = Tracker(sender_id="kairon_user@digite.com", slots=slots, events=events, paused=False, latest_message=None, followup_action=None, active_loop=None, latest_action_name=None) request_params = ActionUtility.prepare_request(tracker=tracker, http_action_config_params=http_action_config_params) assert request_params['param1'] == "value1" assert request_params['user_id'] == "kairon_user@digite.com" def test_prepare_request_no_request_params(self): slots = {"bot": "demo_bot", "http_action_config": "http_action_name", "param2": "param2value"} events: List[Dict] = None http_action_config_params: List[HttpActionRequestBody] = None tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=None, followup_action=None, active_loop=None, latest_action_name=None) actual_request_body = ActionUtility.prepare_request(tracker=tracker, http_action_config_params=http_action_config_params) # deepcode ignore C1801: empty request body for http request with no request body params assert len(actual_request_body) == 0 @pytest.mark.asyncio async def test_name(self): assert await HttpAction().name() == "kairon_http_action" def test_is_empty(self): assert ActionUtility.is_empty("") assert ActionUtility.is_empty(" ") assert ActionUtility.is_empty(None) assert not ActionUtility.is_empty("None") def test_prepare_response(self): json1 = json.dumps({ "a": { "b": { "3": 2, "43": 30, "c": [], "d": ['red', 'buggy', 'bumpers'], } } }) response = ActionUtility.prepare_response("The value of ${a.b.3} in ${a.b.d.0} is ${a.b.c}", json1) assert response == 'The value of 2 in red is []' json2 = json.dumps({ "data": [ {"a": { "b": { "43": 30, "c": [], "d": ['red', 'buggy', 'bumpers'], }}}, {"a": { "b": { "43": 5, "c": [1, 2], "d": ['buggy', 'bumpers'], }}} ] }) response = ActionUtility.prepare_response("The value of ${data.0.a} in ${data.0.a.b} is ${data.0.a.b.d}", json2) assert response == 'The value of {"b": {"43": 30, "c": [], "d": ["red", "buggy", "bumpers"]}} in {"43": 30, "c": [], "d": ["red", "buggy", "bumpers"]} is [\'red\', \'buggy\', \'bumpers\']' def test_prepare_response_key_not_present(self): json1 = json.dumps({ "a": { "b": { "3": 2, "43": 30, "c": [], "d": ['red', 'buggy', 'bumpers'], } } }) try: ActionUtility.prepare_response("The value of ${a.b.3} in ${a.b.d.0} is ${a.b.e}", json1) assert False except HttpActionFailure: assert True def test_prepare_response_string_response(self): json1 = json.dumps({ "a": { "b": { "3": 2, "43": 30, "c": [], "d": ['red', 'buggy', 'bumpers'], } } }) response = ActionUtility.prepare_response("The value of red is 0", json1) assert response == "The value of red is 0" def test_prepare_response_string_empty_response_string(self): json1 = json.dumps({ "a": { "b": { "3": 2, "43": 30, "c": [], "d": ['red', 'buggy', 'bumpers'], } } }) response = ActionUtility.prepare_response("", json1) assert response == '{"a": {"b": {"3": 2, "43": 30, "c": [], "d": ["red", "buggy", "bumpers"]}}}' def test_prepare_response_string_empty_request_output(self): json1 = json.dumps("{}") try: ActionUtility.prepare_response("The value of ${a.b.3} in ${a.b.d.0} is ${a.b.e}", json1) assert False except HttpActionFailure: assert True def test_prepare_response_invalid_response_json(self): json_as_string = "Not a json string" try: ActionUtility.prepare_response("The value of ${a.b.3} in ${a.b.d.0} is ${a.b.c}", json_as_string) assert False except HttpActionFailure as e: assert str(e) == 'Could not find value for keys in response' def test_prepare_response_as_json_and_expected_as_plain_string(self): json_as_string = "Not a json string" response = ActionUtility.prepare_response("The value of 2 in red is []", json_as_string) assert response == 'The value of 2 in red is []' def test_prepare_response_as_string_and_expected_as_none(self): response = ActionUtility.prepare_response("The value of 2 in red is []", None) assert response == 'The value of 2 in red is []' @pytest.mark.asyncio async def test_run_invalid_http_action(self, mock_get_http_action_exception): slots = {"bot": "5f50fd0a56b698ca10d35d2e", "http_action_config_http_action": "test_run_invalid_http_action", "param2": "param2value"} events = [{"event1": "hello"}, {"event2": "how are you"}] latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'http_action'}]} HttpActionConfig( auth_token="bearer kjflksjflksajfljsdflinlsufisnflisjbjsdalibvs", action_name="test_run_invalid_http_action1", response="json", http_url="http://www.google.com", request_method="GET", params_list=None, bot="5f50fd0a56b698ca10d35d2e", user="user" ).save() dispatcher: CollectingDispatcher = CollectingDispatcher() tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None await HttpAction().run(dispatcher, tracker, domain) str(dispatcher.messages[0]['text']).__contains__( "I have failed to process your request: No HTTP action found for bot") log = HttpActionLog.objects(sender="sender1", bot="5f50fd0a56b698ca10d35d2e", status="FAILURE").get() assert log['exception'].__contains__('No HTTP action found for bot') @pytest.mark.asyncio async def test_run_no_bot(self): slots = {"bot": None, "http_action_config_http_action": "new_http_action", "param2": "param2value"} events = [{"event1": "hello"}, {"event2": "how are you"}] dispatcher: CollectingDispatcher = CollectingDispatcher() latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'http_action'}]} tracker = Tracker(sender_id="sender2", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None actual: List[Dict[Text, Any]] = await HttpAction().run(dispatcher, tracker, domain) assert actual is not None assert str(actual[0]['name']) == 'KAIRON_ACTION_RESPONSE' assert str(actual[0]['value']) == 'I have failed to process your request' log = HttpActionLog.objects(sender="sender2", status="FAILURE").get() assert log['exception'] == 'Bot id and HTTP action configuration name not found in slot' @pytest.mark.asyncio async def test_run_no_http_action(self): slots = {"bot": "jhgfsjgfausyfgus", "http_action_config_http_action": None, "param2": "param2value"} events = [{"event1": "hello"}, {"event2": "how are you"}] dispatcher: CollectingDispatcher = CollectingDispatcher() latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'http_action'}]} tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None actual: List[Dict[Text, Any]] = await HttpAction().run(dispatcher, tracker, domain) assert actual is not None assert str(actual[0]['name']) == 'KAIRON_ACTION_RESPONSE' assert str(actual[0]['value']) == 'I have failed to process your request' @pytest.mark.asyncio async def test_run(self, monkeypatch): action = HttpActionConfig( auth_token="bearer kjflksjflksajfljsdflinlsufisnflisjbjsdalibvs", action_name="http_action", response="This should be response", http_url="http://www.google.com", request_method="GET", params_list=None, bot="5f50fd0a56b698ca10d35d2e", user="user" ) def _get_action(*arge, **kwargs): return action.to_mongo().to_dict() monkeypatch.setattr(ActionUtility, "get_http_action_config", _get_action) slots = {"bot": "5f50fd0a56b698ca10d35d2e", "http_action_config_test_run": "http_action", "param2": "param2value"} events = [{"event1": "hello"}, {"event2": "how are you"}] dispatcher: CollectingDispatcher = CollectingDispatcher() latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'test_run'}]} tracker = Tracker(sender_id="sender_test_run", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None action.save().to_mongo().to_dict() actual: List[Dict[Text, Any]] = await HttpAction().run(dispatcher, tracker, domain) assert actual is not None assert str(actual[0]['name']) == 'KAIRON_ACTION_RESPONSE' assert str(actual[0]['value']) == 'This should be response' log = HttpActionLog.objects(sender="sender_test_run", status="SUCCESS").get() assert not log['exception'] assert log['timestamp'] assert log['intent'] assert log['action'] assert log['bot_response'] assert log['api_response'] @pytest.mark.asyncio async def test_run_with_post(self, monkeypatch): action = HttpActionConfig( auth_token="", action_name="test_run_with_post", response="Data added successfully, id:${RESPONSE}", http_url="http://localhost:8080/mock", request_method="POST", params_list=None, bot="5f50fd0a56b698ca10d35d2e", user="user" ) def _get_action(*arge, **kwargs): return action.to_mongo().to_dict() monkeypatch.setattr(ActionUtility, "get_http_action_config", _get_action) http_url = 'http://localhost:8080/mock' resp_msg = "5000" responses.start() responses.add( method=responses.POST, url=http_url, body=resp_msg, status=200, ) slots = {"bot": "5f50fd0a56b698ca10d35d2e", "http_action_config_test_run": "test_run_with_post"} events = [{"event1": "hello"}, {"event2": "how are you"}] dispatcher: CollectingDispatcher = CollectingDispatcher() latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'test_run'}]} tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None action.save().to_mongo().to_dict() actual: List[Dict[Text, Any]] = await HttpAction().run(dispatcher, tracker, domain) assert actual is not None assert actual[0]['name'] == 'KAIRON_ACTION_RESPONSE' assert actual[0]['value'] == 'Data added successfully, id:5000' @pytest.mark.asyncio async def test_run_with_post_and_parameters(self, monkeypatch): request_params = [HttpActionRequestBody(key='key1', value="value1"), HttpActionRequestBody(key='key2', value="value2")] action = HttpActionConfig( auth_token="", action_name="test_run_with_post", response="Data added successfully, id:${RESPONSE}", http_url="http://localhost:8080/mock", request_method="POST", params_list=request_params, bot="5f50fd0a56b698ca10d35d2e", user="user" ) def _get_action(*arge, **kwargs): return action.to_mongo().to_dict() monkeypatch.setattr(ActionUtility, "get_http_action_config", _get_action) http_url = 'http://localhost:8080/mock' resp_msg = "5000" responses.start() responses.add( method=responses.POST, url=http_url, body=resp_msg, status=200, ) slots = {"bot": "5f50fd0a56b698ca10d35d2e", "http_action_config_test_run": "test_run_with_post"} events = [{"event1": "hello"}, {"event2": "how are you"}] dispatcher: CollectingDispatcher = CollectingDispatcher() latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'test_run'}]} tracker = Tracker(sender_id="sender_test_run_with_post", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None action.save().to_mongo().to_dict() actual: List[Dict[Text, Any]] = await HttpAction().run(dispatcher, tracker, domain) responses.stop() assert actual is not None assert str(actual[0]['name']) == 'KAIRON_ACTION_RESPONSE' assert str(actual[0]['value']) == 'Data added successfully, id:5000' log = HttpActionLog.objects(sender="sender_test_run_with_post", action="test_run_with_post", status="SUCCESS").get() assert not log['exception'] assert log['timestamp'] assert log['intent'] == "test_run" assert log['action'] == "test_run_with_post" assert log['request_params'] == {"key1": "value1", "key2": "value2"} assert log['api_response'] == '5000' assert log['bot_response'] == 'Data added successfully, id:5000' @pytest.mark.asyncio async def test_run_with_get(self, monkeypatch): action = HttpActionConfig( auth_token="", action_name="test_run_with_get", response="The value of ${a.b.3} in ${a.b.d.0} is ${a.b.d}", http_url="http://localhost:8081/mock", request_method="GET", params_list=None, bot="5f50fd0a56b698ca10d35d2e", user="user" ) def _get_action(*arge, **kwargs): return action.to_mongo().to_dict() monkeypatch.setattr(ActionUtility, "get_http_action_config", _get_action) http_url = 'http://localhost:8081/mock' resp_msg = json.dumps({ "a": { "b": { "3": 2, "43": 30, "c": [], "d": ['red', 'buggy', 'bumpers'], } } }) responses.start() responses.add( method=responses.GET, url=http_url, body=resp_msg, status=200, ) slots = {"bot": "5f50fd0a56b698ca10d35d2e", "http_action_config_test_run": "test_run_with_post"} events = [{"event1": "hello"}, {"event2": "how are you"}] dispatcher: CollectingDispatcher = CollectingDispatcher() latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'test_run'}]} tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None action.save().to_mongo().to_dict() actual: List[Dict[Text, Any]] = await HttpAction().run(dispatcher, tracker, domain) responses.stop() assert actual is not None assert str(actual[0]['name']) == 'KAIRON_ACTION_RESPONSE' assert str(actual[0]['value']) == 'The value of 2 in red is [\'red\', \'buggy\', \'bumpers\']' @pytest.mark.asyncio async def test_run_no_connection(self, monkeypatch): action = HttpActionConfig( auth_token="", action_name="test_run_with_post", response="This should be response", http_url="http://localhost:8085/mock", request_method="GET", params_list=None, bot="5f50fd0a56b698ca10d35d2e", user="user" ) def _get_action(*arge, **kwargs): return action.to_mongo().to_dict() monkeypatch.setattr(ActionUtility, "get_http_action_config", _get_action) slots = {"bot": "5f50fd0a56b698ca10d35d2e", "http_action_config_test_run": "test_run_with_post"} events = [{"event1": "hello"}, {"event2": "how are you"}] dispatcher: CollectingDispatcher = CollectingDispatcher() latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'test_run'}]} tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None action.save() actual: List[Dict[Text, Any]] = await HttpAction().run(dispatcher, tracker, domain) assert actual is not None assert str(actual[0]['name']) == 'KAIRON_ACTION_RESPONSE' assert str(actual[0]['value']).__contains__('I have failed to process your request') @pytest.mark.asyncio async def test_run_with_get_placeholder_vs_string_response(self, monkeypatch): action = HttpActionConfig( auth_token="", action_name="test_run_with_get_string_http_response_placeholder_required", response="The value of ${a.b.3} in ${a.b.d.0} is ${a.b.d}", http_url="http://localhost:8080/mock", request_method="GET", params_list=None, bot="5f50fd0a56b698ca10d35d2e", user="user" ) def _get_action(*arge, **kwargs): return action.to_mongo().to_dict() monkeypatch.setattr(ActionUtility, "get_http_action_config", _get_action) http_url = 'http://localhost:8082/mock' resp_msg = "This is string http response" responses.start() responses.add( method=responses.GET, url=http_url, body=resp_msg, status=200, ) slots = {"bot": "5f50fd0a56b698ca10d35d2e", "http_action_config_test_run": "test_run_with_get_string_http_response_placeholder_required"} events = [{"event1": "hello"}, {"event2": "how are you"}] dispatcher: CollectingDispatcher = CollectingDispatcher() latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'test_run'}]} tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None action.save().to_mongo().to_dict() actual: List[Dict[Text, Any]] = await HttpAction().run(dispatcher, tracker, domain) responses.stop() assert actual is not None assert str(actual[0]['name']) == 'KAIRON_ACTION_RESPONSE' assert str( actual[0]['value']) == 'I have failed to process your request' def test_attach_response_no_placeholder(self): output = ActionUtility.attach_response("This has no placeholder", {"a": "b"}) assert output == "This has no placeholder" def test_attach_response(self): output = ActionUtility.attach_response("I want $${RESPONSE}", {"dollars": "51"}) assert output == 'I want ${\'dollars\': \'51\'}' def test_attach_response_int(self): output = ActionUtility.attach_response("I want $${RESPONSE}", 51) assert output == 'I want $51' def test_retrieve_value_from_response(self): keys = ["a.b.3", 'a.b'] resp_msg = { "a": { "b": { "3": 2, "43": 30, "c": [], "d": ['red', 'buggy', 'bumpers'], } } } key_values = ActionUtility.retrieve_value_from_response(keys, resp_msg) assert key_values is not None assert key_values['${a.b.3}'] == 2 assert key_values['${a.b}'] is not None assert key_values['${a.b}']['3'] == 2 assert key_values['${a.b}']['d'][0] == 'red' def test_retrieve_value_from_response_invalid_key(self): keys = ["d.e.f", 'g.h'] resp_msg = { "a": { "b": { "3": 2, "43": 30, "c": [], "d": ['red', 'buggy', 'bumpers'], } } } try: ActionUtility.retrieve_value_from_response(keys, resp_msg) assert False except HttpActionFailure as e: assert str(e) == 'Unable to retrieve value for key from HTTP response: \'d\''

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import json import os os.environ["system_file"] = "./tests/testing_data/system.yaml" from typing import Dict, Text, Any, List import pytest import responses from mongoengine import connect, disconnect from rasa_sdk import Tracker from rasa_sdk.executor import CollectingDispatcher from kairon.action_server.data_objects import HttpActionRequestBody, HttpActionConfig, HttpActionLog from kairon.action_server.actions import ActionUtility, HttpAction from kairon.action_server.exception import HttpActionFailure from kairon.utils import Utility def pytest_configure(): return { 'db_url': None, } class TestActions: @pytest.fixture(autouse=True) def setup(self): os.environ["system_file"] = "./tests/testing_data/system.yaml" Utility.load_evironment() db_url = Utility.environment['database']["url"] pytest.db_url = db_url connect(host=db_url) @pytest.fixture def mock_get_http_action_exception(self, monkeypatch): def _raise_excep(*arge, **kwargs): raise HttpActionFailure("No HTTP action found for bot and action") monkeypatch.setattr(ActionUtility, "get_http_action_config", _raise_excep) @responses.activate def test_execute_http_request_getWith_auth_token(self): http_url = 'http://localhost:8080/mock' auth_token = "bearer jkhfhkujsfsfslfhjsfhkjsfhskhfksj" responses.add( method=responses.GET, url=http_url, json={'data': 'test_data', 'test_class': [{'key': 'value'}, {'key2': 'value2'}]}, status=200 ) response = ActionUtility.execute_http_request(auth_token=auth_token, http_url=http_url, request_method=responses.GET) assert response assert response['data'] == 'test_data' assert len(response['test_class']) == 2 assert response['test_class'][1]['key2'] == 'value2' assert responses.calls[0].request.headers['Authorization'] == auth_token @responses.activate def test_execute_http_request_get_no_auth_token(self): http_url = 'http://localhost:8080/mock' responses.add( method=responses.GET, url=http_url, json={'data': 'test_data', 'test_class': [{'key': 'value'}, {'key2': 'value2'}]}, status=200 ) response = ActionUtility.execute_http_request(auth_token=None, http_url=http_url, request_method=responses.GET) assert response assert response['data'] == 'test_data' assert len(response['test_class']) == 2 assert response['test_class'][1]['key2'] == 'value2' assert 'Authorization' not in responses.calls[0].request.headers @responses.activate def test_execute_http_request_post_with_auth_token(self): http_url = 'http://localhost:8080/mock' auth_token = "bearer jkhfhkujsfsfslfhjsfhkjsfhskhfksj" resp_msg = "Data added successfully" request_params = {'data': 'test_data', 'test_class': [{'key': 'value'}, {'key2': 'value2'}]} responses.add( method=responses.POST, url=http_url, body=resp_msg, status=200, match=[responses.json_params_matcher(request_params)] ) response = ActionUtility.execute_http_request(auth_token=auth_token, http_url=http_url, request_method=responses.POST, request_body=request_params) assert response assert response == resp_msg assert responses.calls[0].request.headers['Authorization'] == auth_token @responses.activate def test_execute_http_request_post_no_auth_token(self): http_url = 'http://localhost:8080/mock' resp_msg = "Data added successfully" request_params = {'data': 'test_data', 'test_class': [{'key': 'value'}, {'key2': 'value2'}]} responses.add( method=responses.POST, url=http_url, body=resp_msg, status=200, match=[responses.json_params_matcher(request_params)] ) response = ActionUtility.execute_http_request(auth_token=None, http_url=http_url, request_method=responses.POST, request_body=request_params) assert response assert response == resp_msg assert 'Authorization' not in responses.calls[0].request.headers @responses.activate def test_execute_http_request_put_with_auth_token(self): http_url = 'http://localhost:8080/mock' auth_token = "bearer jkhfhkujsfsfslfhjsfhkjsfhskhfksj" resp_msg = "Data updated successfully" request_params = {'data': 'test_data', 'test_class': [{'key': 'value'}, {'key2': 'value2'}]} responses.add( method=responses.PUT, url=http_url, body=resp_msg, status=200, match=[responses.json_params_matcher(request_params)] ) response = ActionUtility.execute_http_request(auth_token=auth_token, http_url=http_url, request_method=responses.PUT, request_body=request_params) assert response assert response == resp_msg assert responses.calls[0].request.headers['Authorization'] == auth_token @responses.activate def test_execute_http_request_put_no_auth_token(self): http_url = 'http://localhost:8080/mock' resp_msg = "Data updated successfully" request_params = {'data': 'test_data', 'test_class': [{'key': 'value'}, {'key2': 'value2'}]} responses.add( method=responses.PUT, url=http_url, body=resp_msg, status=200, match=[responses.json_params_matcher(request_params)] ) response = ActionUtility.execute_http_request(auth_token=None, http_url=http_url, request_method=responses.PUT, request_body=request_params) assert response assert response == resp_msg assert 'Authorization' not in responses.calls[0].request.headers @responses.activate def test_execute_http_request_delete_with_request_body_auth_token(self): http_url = 'http://localhost:8080/mock' auth_token = "bearer jkhfhkujsfsfslfhjsfhkjsfhskhfksj" resp_msg = "Data deleted successfully" request_params = {'data': 'test_data', 'test_class': [{'key': 'value'}, {'key2': 'value2'}]} responses.add( method=responses.DELETE, url=http_url, body=resp_msg, status=200, match=[responses.json_params_matcher(request_params)] ) response = ActionUtility.execute_http_request(auth_token=auth_token, http_url=http_url, request_method=responses.DELETE, request_body=request_params) assert response assert response == resp_msg assert responses.calls[0].request.headers['Authorization'] == auth_token @responses.activate def test_execute_http_request_delete_with_auth_token_no_request_body(self): http_url = 'http://localhost:8080/mock' auth_token = "bearer jkhfhkujsfsfslfhjsfhkjsfhskhfksj" resp_msg = "Data deleted successfully" responses.add( method=responses.DELETE, url=http_url, body=resp_msg, status=200, ) response = ActionUtility.execute_http_request(auth_token=auth_token, http_url=http_url, request_method=responses.DELETE, request_body=None) assert response assert response == resp_msg assert responses.calls[0].request.headers['Authorization'] == auth_token @responses.activate def test_execute_http_request_delete_no_auth_token(self): http_url = 'http://localhost:8080/mock' resp_msg = "Data updated successfully" request_params = {'data': 'test_data', 'test_class': [{'key': 'value'}, {'key2': 'value2'}]} responses.add( method=responses.DELETE, url=http_url, body=resp_msg, status=200, match=[ responses.json_params_matcher(request_params) ] ) response = ActionUtility.execute_http_request(auth_token=None, http_url=http_url, request_method=responses.DELETE, request_body=request_params) assert response assert response == resp_msg assert 'Authorization' not in responses.calls[0].request.headers def test_get_http_action_config(self): http_params = [HttpActionRequestBody(key="key1", value="value1", parameter_type="slot"), HttpActionRequestBody(key="key2", value="value2")] expected = HttpActionConfig( auth_token="bearer kjflksjflksajfljsdflinlsufisnflisjbjsdalibvs", action_name="http_action", response="json", http_url="http://test.com", request_method="GET", params_list=http_params, bot="bot", user="user" ).save().to_mongo().to_dict() actual = ActionUtility.get_http_action_config("bot", "http_action") assert actual is not None assert expected['auth_token'] == actual['auth_token'] assert expected['action_name'] == actual['action_name'] assert expected['response'] == actual['response'] assert expected['http_url'] == actual['http_url'] assert expected['request_method'] == actual['request_method'] assert expected['params_list'] is not None assert expected['params_list'][0]['key'] == actual['params_list'][0]['key'] assert expected['params_list'][0]['value'] == actual['params_list'][0]['value'] assert expected['params_list'][0]['parameter_type'] == actual['params_list'][0]['parameter_type'] assert expected['params_list'][1]['key'] == actual['params_list'][1]['key'] assert expected['params_list'][1]['value'] == actual['params_list'][1]['value'] assert expected['params_list'][1]['parameter_type'] == actual['params_list'][1]['parameter_type'] assert actual['status'] def test_get_http_action_config_deleted_action(self): http_params = [HttpActionRequestBody(key="key1", value="value1", parameter_type="slot"), HttpActionRequestBody(key="key2", value="value2")] HttpActionConfig( auth_token="", action_name="test_get_http_action_config_deleted_action", response="${RESPONSE}", http_url="http://www.digite.com", request_method="POST", params_list=http_params, bot="bot", user="user", status=False ).save().to_mongo().to_dict() expected = HttpActionConfig( auth_token="bearer kjflksjflksajfljsdflinlsufisnflisjbjsdalibvs", action_name="test_get_http_action_config_deleted_action", response="json", http_url="http://test.com", request_method="GET", params_list=http_params, bot="bot", user="user" ).save().to_mongo().to_dict() actual = ActionUtility.get_http_action_config("bot", "test_get_http_action_config_deleted_action") assert actual is not None assert expected['auth_token'] == actual['auth_token'] assert expected['action_name'] == actual['action_name'] assert expected['response'] == actual['response'] assert expected['http_url'] == actual['http_url'] assert expected['request_method'] == actual['request_method'] assert expected['params_list'] is not None assert expected['params_list'][0]['key'] == actual['params_list'][0]['key'] assert expected['params_list'][0]['value'] == actual['params_list'][0]['value'] assert expected['params_list'][0]['parameter_type'] == actual['params_list'][0]['parameter_type'] assert expected['params_list'][1]['key'] == actual['params_list'][1]['key'] assert expected['params_list'][1]['value'] == actual['params_list'][1]['value'] assert expected['params_list'][1]['parameter_type'] == actual['params_list'][1]['parameter_type'] assert actual['status'] def test_get_http_action_no_bot(self): try: ActionUtility.get_http_action_config(bot=None, action_name="http_action") assert False except HttpActionFailure as ex: assert str(ex) == "Bot name and action name are required" def test_get_http_action_no_http_action(self): try: ActionUtility.get_http_action_config(bot="bot", action_name=None) assert False except HttpActionFailure as ex: assert str(ex) == "Bot name and action name are required" def test_get_http_action_invalid_bot(self): http_params = [HttpActionRequestBody(key="key1", value="value1", parameter_type="slot"), HttpActionRequestBody(key="key2", value="value2")] HttpActionConfig( auth_token="bearer kjflksjflksajfljsdflinlsufisnflisjbjsdalibvs", action_name="http_action", response="json", http_url="http://test.com", request_method="GET", params_list=http_params, bot="bot", user="user" ).save().to_mongo().to_dict() try: ActionUtility.get_http_action_config("bot1", "http_action") assert False except HttpActionFailure as ex: assert str(ex).__contains__("No HTTP action found for bot") def test_get_http_action_invalid_http_action(self): http_params = [HttpActionRequestBody(key="key1", value="value1", parameter_type="slot"), HttpActionRequestBody(key="key2", value="value2")] HttpActionConfig( auth_token="bearer kjflksjflksajfljsdflinlsufisnflisjbjsdalibvs", action_name="http_action", response="json", http_url="http://test.com", request_method="GET", params_list=http_params, bot="bot", user="user" ).save().to_mongo().to_dict() try: ActionUtility.get_http_action_config("bot", "http_action1") assert False except HttpActionFailure as ex: assert str(ex).__contains__("No HTTP action found for bot") def test_get_http_action_no_request_body(self): http_params = [] HttpActionConfig( auth_token="bearer kjflksjflksajfljsdflinlsufisnflisjbjsdalibvs", action_name="http_action", response="json", http_url="http://test.com", request_method="GET", params_list=http_params, bot="bot", user="user" ).save().to_mongo().to_dict() try: ActionUtility.get_http_action_config("bot", "http_action1") assert False except HttpActionFailure as ex: assert str(ex).__contains__("No HTTP action found for bot") def test_prepare_request(self): slots = {"bot": "demo_bot", "http_action_config": "http_action_name", "slot_name": "param2value"} events = [{"event1": "hello"}, {"event2": "how are you"}] http_action_config_params = [HttpActionRequestBody(key="param1", value="value1"), HttpActionRequestBody(key="param2", value="slot_name", parameter_type="slot")] tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=None, followup_action=None, active_loop=None, latest_action_name=None) actual_request_body = ActionUtility.prepare_request(tracker=tracker, http_action_config_params=http_action_config_params) assert actual_request_body assert actual_request_body['param1'] == 'value1' assert actual_request_body['param2'] == 'param2value' def test_prepare_request_empty_slot(self): slots = {"bot": "demo_bot", "http_action_config": "http_action_name", "param2": "param2value"} events = [{"event1": "hello"}, {"event2": "how are you"}] http_action_config_params = [HttpActionRequestBody(key="param1", value="value1"), HttpActionRequestBody(key="param3", value="", parameter_type="slot")] tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=None, followup_action=None, active_loop=None, latest_action_name=None) request_params = ActionUtility.prepare_request(tracker=tracker, http_action_config_params=http_action_config_params) assert request_params['param1'] == "value1" assert not request_params['param3'] def test_prepare_request_sender_id(self): slots = {"bot": "demo_bot", "http_action_config": "http_action_name", "param2": "param2value"} events = [{"event1": "hello"}, {"event2": "how are you"}] http_action_config_params = [HttpActionRequestBody(key="param1", value="value1"), HttpActionRequestBody(key="user_id", value="", parameter_type="sender_id")] tracker = Tracker(sender_id="kairon_user@digite.com", slots=slots, events=events, paused=False, latest_message=None, followup_action=None, active_loop=None, latest_action_name=None) request_params = ActionUtility.prepare_request(tracker=tracker, http_action_config_params=http_action_config_params) assert request_params['param1'] == "value1" assert request_params['user_id'] == "kairon_user@digite.com" def test_prepare_request_no_request_params(self): slots = {"bot": "demo_bot", "http_action_config": "http_action_name", "param2": "param2value"} events: List[Dict] = None http_action_config_params: List[HttpActionRequestBody] = None tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=None, followup_action=None, active_loop=None, latest_action_name=None) actual_request_body = ActionUtility.prepare_request(tracker=tracker, http_action_config_params=http_action_config_params) assert len(actual_request_body) == 0 @pytest.mark.asyncio async def test_name(self): assert await HttpAction().name() == "kairon_http_action" def test_is_empty(self): assert ActionUtility.is_empty("") assert ActionUtility.is_empty(" ") assert ActionUtility.is_empty(None) assert not ActionUtility.is_empty("None") def test_prepare_response(self): json1 = json.dumps({ "a": { "b": { "3": 2, "43": 30, "c": [], "d": ['red', 'buggy', 'bumpers'], } } }) response = ActionUtility.prepare_response("The value of ${a.b.3} in ${a.b.d.0} is ${a.b.c}", json1) assert response == 'The value of 2 in red is []' json2 = json.dumps({ "data": [ {"a": { "b": { "43": 30, "c": [], "d": ['red', 'buggy', 'bumpers'], }}}, {"a": { "b": { "43": 5, "c": [1, 2], "d": ['buggy', 'bumpers'], }}} ] }) response = ActionUtility.prepare_response("The value of ${data.0.a} in ${data.0.a.b} is ${data.0.a.b.d}", json2) assert response == 'The value of {"b": {"43": 30, "c": [], "d": ["red", "buggy", "bumpers"]}} in {"43": 30, "c": [], "d": ["red", "buggy", "bumpers"]} is [\'red\', \'buggy\', \'bumpers\']' def test_prepare_response_key_not_present(self): json1 = json.dumps({ "a": { "b": { "3": 2, "43": 30, "c": [], "d": ['red', 'buggy', 'bumpers'], } } }) try: ActionUtility.prepare_response("The value of ${a.b.3} in ${a.b.d.0} is ${a.b.e}", json1) assert False except HttpActionFailure: assert True def test_prepare_response_string_response(self): json1 = json.dumps({ "a": { "b": { "3": 2, "43": 30, "c": [], "d": ['red', 'buggy', 'bumpers'], } } }) response = ActionUtility.prepare_response("The value of red is 0", json1) assert response == "The value of red is 0" def test_prepare_response_string_empty_response_string(self): json1 = json.dumps({ "a": { "b": { "3": 2, "43": 30, "c": [], "d": ['red', 'buggy', 'bumpers'], } } }) response = ActionUtility.prepare_response("", json1) assert response == '{"a": {"b": {"3": 2, "43": 30, "c": [], "d": ["red", "buggy", "bumpers"]}}}' def test_prepare_response_string_empty_request_output(self): json1 = json.dumps("{}") try: ActionUtility.prepare_response("The value of ${a.b.3} in ${a.b.d.0} is ${a.b.e}", json1) assert False except HttpActionFailure: assert True def test_prepare_response_invalid_response_json(self): json_as_string = "Not a json string" try: ActionUtility.prepare_response("The value of ${a.b.3} in ${a.b.d.0} is ${a.b.c}", json_as_string) assert False except HttpActionFailure as e: assert str(e) == 'Could not find value for keys in response' def test_prepare_response_as_json_and_expected_as_plain_string(self): json_as_string = "Not a json string" response = ActionUtility.prepare_response("The value of 2 in red is []", json_as_string) assert response == 'The value of 2 in red is []' def test_prepare_response_as_string_and_expected_as_none(self): response = ActionUtility.prepare_response("The value of 2 in red is []", None) assert response == 'The value of 2 in red is []' @pytest.mark.asyncio async def test_run_invalid_http_action(self, mock_get_http_action_exception): slots = {"bot": "5f50fd0a56b698ca10d35d2e", "http_action_config_http_action": "test_run_invalid_http_action", "param2": "param2value"} events = [{"event1": "hello"}, {"event2": "how are you"}] latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'http_action'}]} HttpActionConfig( auth_token="bearer kjflksjflksajfljsdflinlsufisnflisjbjsdalibvs", action_name="test_run_invalid_http_action1", response="json", http_url="http://www.google.com", request_method="GET", params_list=None, bot="5f50fd0a56b698ca10d35d2e", user="user" ).save() dispatcher: CollectingDispatcher = CollectingDispatcher() tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None await HttpAction().run(dispatcher, tracker, domain) str(dispatcher.messages[0]['text']).__contains__( "I have failed to process your request: No HTTP action found for bot") log = HttpActionLog.objects(sender="sender1", bot="5f50fd0a56b698ca10d35d2e", status="FAILURE").get() assert log['exception'].__contains__('No HTTP action found for bot') @pytest.mark.asyncio async def test_run_no_bot(self): slots = {"bot": None, "http_action_config_http_action": "new_http_action", "param2": "param2value"} events = [{"event1": "hello"}, {"event2": "how are you"}] dispatcher: CollectingDispatcher = CollectingDispatcher() latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'http_action'}]} tracker = Tracker(sender_id="sender2", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None actual: List[Dict[Text, Any]] = await HttpAction().run(dispatcher, tracker, domain) assert actual is not None assert str(actual[0]['name']) == 'KAIRON_ACTION_RESPONSE' assert str(actual[0]['value']) == 'I have failed to process your request' log = HttpActionLog.objects(sender="sender2", status="FAILURE").get() assert log['exception'] == 'Bot id and HTTP action configuration name not found in slot' @pytest.mark.asyncio async def test_run_no_http_action(self): slots = {"bot": "jhgfsjgfausyfgus", "http_action_config_http_action": None, "param2": "param2value"} events = [{"event1": "hello"}, {"event2": "how are you"}] dispatcher: CollectingDispatcher = CollectingDispatcher() latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'http_action'}]} tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None actual: List[Dict[Text, Any]] = await HttpAction().run(dispatcher, tracker, domain) assert actual is not None assert str(actual[0]['name']) == 'KAIRON_ACTION_RESPONSE' assert str(actual[0]['value']) == 'I have failed to process your request' @pytest.mark.asyncio async def test_run(self, monkeypatch): action = HttpActionConfig( auth_token="bearer kjflksjflksajfljsdflinlsufisnflisjbjsdalibvs", action_name="http_action", response="This should be response", http_url="http://www.google.com", request_method="GET", params_list=None, bot="5f50fd0a56b698ca10d35d2e", user="user" ) def _get_action(*arge, **kwargs): return action.to_mongo().to_dict() monkeypatch.setattr(ActionUtility, "get_http_action_config", _get_action) slots = {"bot": "5f50fd0a56b698ca10d35d2e", "http_action_config_test_run": "http_action", "param2": "param2value"} events = [{"event1": "hello"}, {"event2": "how are you"}] dispatcher: CollectingDispatcher = CollectingDispatcher() latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'test_run'}]} tracker = Tracker(sender_id="sender_test_run", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None action.save().to_mongo().to_dict() actual: List[Dict[Text, Any]] = await HttpAction().run(dispatcher, tracker, domain) assert actual is not None assert str(actual[0]['name']) == 'KAIRON_ACTION_RESPONSE' assert str(actual[0]['value']) == 'This should be response' log = HttpActionLog.objects(sender="sender_test_run", status="SUCCESS").get() assert not log['exception'] assert log['timestamp'] assert log['intent'] assert log['action'] assert log['bot_response'] assert log['api_response'] @pytest.mark.asyncio async def test_run_with_post(self, monkeypatch): action = HttpActionConfig( auth_token="", action_name="test_run_with_post", response="Data added successfully, id:${RESPONSE}", http_url="http://localhost:8080/mock", request_method="POST", params_list=None, bot="5f50fd0a56b698ca10d35d2e", user="user" ) def _get_action(*arge, **kwargs): return action.to_mongo().to_dict() monkeypatch.setattr(ActionUtility, "get_http_action_config", _get_action) http_url = 'http://localhost:8080/mock' resp_msg = "5000" responses.start() responses.add( method=responses.POST, url=http_url, body=resp_msg, status=200, ) slots = {"bot": "5f50fd0a56b698ca10d35d2e", "http_action_config_test_run": "test_run_with_post"} events = [{"event1": "hello"}, {"event2": "how are you"}] dispatcher: CollectingDispatcher = CollectingDispatcher() latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'test_run'}]} tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None action.save().to_mongo().to_dict() actual: List[Dict[Text, Any]] = await HttpAction().run(dispatcher, tracker, domain) assert actual is not None assert actual[0]['name'] == 'KAIRON_ACTION_RESPONSE' assert actual[0]['value'] == 'Data added successfully, id:5000' @pytest.mark.asyncio async def test_run_with_post_and_parameters(self, monkeypatch): request_params = [HttpActionRequestBody(key='key1', value="value1"), HttpActionRequestBody(key='key2', value="value2")] action = HttpActionConfig( auth_token="", action_name="test_run_with_post", response="Data added successfully, id:${RESPONSE}", http_url="http://localhost:8080/mock", request_method="POST", params_list=request_params, bot="5f50fd0a56b698ca10d35d2e", user="user" ) def _get_action(*arge, **kwargs): return action.to_mongo().to_dict() monkeypatch.setattr(ActionUtility, "get_http_action_config", _get_action) http_url = 'http://localhost:8080/mock' resp_msg = "5000" responses.start() responses.add( method=responses.POST, url=http_url, body=resp_msg, status=200, ) slots = {"bot": "5f50fd0a56b698ca10d35d2e", "http_action_config_test_run": "test_run_with_post"} events = [{"event1": "hello"}, {"event2": "how are you"}] dispatcher: CollectingDispatcher = CollectingDispatcher() latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'test_run'}]} tracker = Tracker(sender_id="sender_test_run_with_post", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None action.save().to_mongo().to_dict() actual: List[Dict[Text, Any]] = await HttpAction().run(dispatcher, tracker, domain) responses.stop() assert actual is not None assert str(actual[0]['name']) == 'KAIRON_ACTION_RESPONSE' assert str(actual[0]['value']) == 'Data added successfully, id:5000' log = HttpActionLog.objects(sender="sender_test_run_with_post", action="test_run_with_post", status="SUCCESS").get() assert not log['exception'] assert log['timestamp'] assert log['intent'] == "test_run" assert log['action'] == "test_run_with_post" assert log['request_params'] == {"key1": "value1", "key2": "value2"} assert log['api_response'] == '5000' assert log['bot_response'] == 'Data added successfully, id:5000' @pytest.mark.asyncio async def test_run_with_get(self, monkeypatch): action = HttpActionConfig( auth_token="", action_name="test_run_with_get", response="The value of ${a.b.3} in ${a.b.d.0} is ${a.b.d}", http_url="http://localhost:8081/mock", request_method="GET", params_list=None, bot="5f50fd0a56b698ca10d35d2e", user="user" ) def _get_action(*arge, **kwargs): return action.to_mongo().to_dict() monkeypatch.setattr(ActionUtility, "get_http_action_config", _get_action) http_url = 'http://localhost:8081/mock' resp_msg = json.dumps({ "a": { "b": { "3": 2, "43": 30, "c": [], "d": ['red', 'buggy', 'bumpers'], } } }) responses.start() responses.add( method=responses.GET, url=http_url, body=resp_msg, status=200, ) slots = {"bot": "5f50fd0a56b698ca10d35d2e", "http_action_config_test_run": "test_run_with_post"} events = [{"event1": "hello"}, {"event2": "how are you"}] dispatcher: CollectingDispatcher = CollectingDispatcher() latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'test_run'}]} tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None action.save().to_mongo().to_dict() actual: List[Dict[Text, Any]] = await HttpAction().run(dispatcher, tracker, domain) responses.stop() assert actual is not None assert str(actual[0]['name']) == 'KAIRON_ACTION_RESPONSE' assert str(actual[0]['value']) == 'The value of 2 in red is [\'red\', \'buggy\', \'bumpers\']' @pytest.mark.asyncio async def test_run_no_connection(self, monkeypatch): action = HttpActionConfig( auth_token="", action_name="test_run_with_post", response="This should be response", http_url="http://localhost:8085/mock", request_method="GET", params_list=None, bot="5f50fd0a56b698ca10d35d2e", user="user" ) def _get_action(*arge, **kwargs): return action.to_mongo().to_dict() monkeypatch.setattr(ActionUtility, "get_http_action_config", _get_action) slots = {"bot": "5f50fd0a56b698ca10d35d2e", "http_action_config_test_run": "test_run_with_post"} events = [{"event1": "hello"}, {"event2": "how are you"}] dispatcher: CollectingDispatcher = CollectingDispatcher() latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'test_run'}]} tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None action.save() actual: List[Dict[Text, Any]] = await HttpAction().run(dispatcher, tracker, domain) assert actual is not None assert str(actual[0]['name']) == 'KAIRON_ACTION_RESPONSE' assert str(actual[0]['value']).__contains__('I have failed to process your request') @pytest.mark.asyncio async def test_run_with_get_placeholder_vs_string_response(self, monkeypatch): action = HttpActionConfig( auth_token="", action_name="test_run_with_get_string_http_response_placeholder_required", response="The value of ${a.b.3} in ${a.b.d.0} is ${a.b.d}", http_url="http://localhost:8080/mock", request_method="GET", params_list=None, bot="5f50fd0a56b698ca10d35d2e", user="user" ) def _get_action(*arge, **kwargs): return action.to_mongo().to_dict() monkeypatch.setattr(ActionUtility, "get_http_action_config", _get_action) http_url = 'http://localhost:8082/mock' resp_msg = "This is string http response" responses.start() responses.add( method=responses.GET, url=http_url, body=resp_msg, status=200, ) slots = {"bot": "5f50fd0a56b698ca10d35d2e", "http_action_config_test_run": "test_run_with_get_string_http_response_placeholder_required"} events = [{"event1": "hello"}, {"event2": "how are you"}] dispatcher: CollectingDispatcher = CollectingDispatcher() latest_message = {'text': 'get intents', 'intent_ranking': [{'name': 'test_run'}]} tracker = Tracker(sender_id="sender1", slots=slots, events=events, paused=False, latest_message=latest_message, followup_action=None, active_loop=None, latest_action_name=None) domain: Dict[Text, Any] = None action.save().to_mongo().to_dict() actual: List[Dict[Text, Any]] = await HttpAction().run(dispatcher, tracker, domain) responses.stop() assert actual is not None assert str(actual[0]['name']) == 'KAIRON_ACTION_RESPONSE' assert str( actual[0]['value']) == 'I have failed to process your request' def test_attach_response_no_placeholder(self): output = ActionUtility.attach_response("This has no placeholder", {"a": "b"}) assert output == "This has no placeholder" def test_attach_response(self): output = ActionUtility.attach_response("I want $${RESPONSE}", {"dollars": "51"}) assert output == 'I want ${\'dollars\': \'51\'}' def test_attach_response_int(self): output = ActionUtility.attach_response("I want $${RESPONSE}", 51) assert output == 'I want $51' def test_retrieve_value_from_response(self): keys = ["a.b.3", 'a.b'] resp_msg = { "a": { "b": { "3": 2, "43": 30, "c": [], "d": ['red', 'buggy', 'bumpers'], } } } key_values = ActionUtility.retrieve_value_from_response(keys, resp_msg) assert key_values is not None assert key_values['${a.b.3}'] == 2 assert key_values['${a.b}'] is not None assert key_values['${a.b}']['3'] == 2 assert key_values['${a.b}']['d'][0] == 'red' def test_retrieve_value_from_response_invalid_key(self): keys = ["d.e.f", 'g.h'] resp_msg = { "a": { "b": { "3": 2, "43": 30, "c": [], "d": ['red', 'buggy', 'bumpers'], } } } try: ActionUtility.retrieve_value_from_response(keys, resp_msg) assert False except HttpActionFailure as e: assert str(e) == 'Unable to retrieve value for key from HTTP response: \'d\''

true

f704ce218171769e1c7e83c8096eabe16908d3e6

848

py

Python

des039.py

LeonardoPereirajr/Curso_em_video_Python

9d8a97ba3389c8e86b37dfd089fab5d04adc146d

[ "MIT" ]

null

des039.py

LeonardoPereirajr/Curso_em_video_Python

9d8a97ba3389c8e86b37dfd089fab5d04adc146d

[ "MIT" ]

null

des039.py

LeonardoPereirajr/Curso_em_video_Python

9d8a97ba3389c8e86b37dfd089fab5d04adc146d

[ "MIT" ]

null

from datetime import date ano = int(input('ANO de nascimento : ')) ano_hoje = date.today().year cont = ano_hoje - ano if cont > 20 : print(' Quem nasceu em {} tem {} anos em {} . '.format(ano, cont, ano_hoje)) print(' Sua classificação é MASTER. ') elif cont == 20 : print(' Quem nasceu em {} tem {} anos em {} . '.format(ano, cont, ano_hoje)) print(' Sua classificação é SENIOR. ') elif cont >= 19 : print(' Quem nasceu em {} tem {} anos em {} . '.format(ano, cont, ano_hoje)) print(' Sua classificação é JUNIOR. ') elif cont >=10 : print(' Quem nasceu em {} tem {} anos em {} . '.format(ano, cont, ano_hoje)) print(' Sua classificação é INFANTIL. ') elif cont <= 9 : print(' Quem nasceu em {} tem {} anos em {} . '.format(ano, cont, ano_hoje)) print(' Sua classificação é MIRIM. ')

44.631579

82

0.597877

from datetime import date ano = int(input('ANO de nascimento : ')) ano_hoje = date.today().year cont = ano_hoje - ano if cont > 20 : print(' Quem nasceu em {} tem {} anos em {} . '.format(ano, cont, ano_hoje)) print(' Sua classificação é MASTER. ') elif cont == 20 : print(' Quem nasceu em {} tem {} anos em {} . '.format(ano, cont, ano_hoje)) print(' Sua classificação é SENIOR. ') elif cont >= 19 : print(' Quem nasceu em {} tem {} anos em {} . '.format(ano, cont, ano_hoje)) print(' Sua classificação é JUNIOR. ') elif cont >=10 : print(' Quem nasceu em {} tem {} anos em {} . '.format(ano, cont, ano_hoje)) print(' Sua classificação é INFANTIL. ') elif cont <= 9 : print(' Quem nasceu em {} tem {} anos em {} . '.format(ano, cont, ano_hoje)) print(' Sua classificação é MIRIM. ')

true

f704ce6b1a36073883d29f973825dd98381f1c4b

443

py

Python

setup.py

msikma/upprint

b617eb7d0a661fb3107d85471520270647766906

[ "MIT" ]

null

setup.py

msikma/upprint

b617eb7d0a661fb3107d85471520270647766906

[ "MIT" ]

null

setup.py

msikma/upprint

b617eb7d0a661fb3107d85471520270647766906

[ "MIT" ]

null

from distutils.core import setup setup( name='upprint', packages=['upprint'], version='0.1', description='Modified version of pprint with better Unicode output', author='Michiel Sikma', author_email='michiel@sikma.org', url='https://github.com/msikma/upprint', download_url='https://github.com/msikma/upprint/tarball/0.1', keywords=['pprint', 'debugging', 'print'], classifiers=[], license='MIT' )

27.6875

72

0.670429

from distutils.core import setup setup( name='upprint', packages=['upprint'], version='0.1', description='Modified version of pprint with better Unicode output', author='Michiel Sikma', author_email='michiel@sikma.org', url='https://github.com/msikma/upprint', download_url='https://github.com/msikma/upprint/tarball/0.1', keywords=['pprint', 'debugging', 'print'], classifiers=[], license='MIT' )

true

f704ce98035e4ea27201a97a216cc694ba65d79b

4,375

py

Python

tests/test_tokenizers.py

DLPerf/gretel-synthetics

58a820327e283ecc224de3686aa035b7e32bfaa6

[ "Apache-2.0" ]

252

2020-03-02T16:41:11.000Z

2022-03-28T20:57:15.000Z

tests/test_tokenizers.py

DLPerf/gretel-synthetics

58a820327e283ecc224de3686aa035b7e32bfaa6

[ "Apache-2.0" ]

39

2020-03-16T18:33:48.000Z

2021-11-10T19:13:53.000Z

tests/test_tokenizers.py

DLPerf/gretel-synthetics

58a820327e283ecc224de3686aa035b7e32bfaa6

[ "Apache-2.0" ]

36

2020-05-21T14:45:27.000Z

2022-03-01T01:32:58.000Z

from pathlib import Path from copy import deepcopy import pytest from gretel_synthetics.config import BaseConfig import gretel_synthetics.tokenizers as tok class SimpleConfig(BaseConfig): """Used for simple tokenization tests """ def get_generator_class(self): return None def get_training_callable(self): return None @pytest.fixture(scope="module") def input_data_path(): return str( (Path(__file__).parent / "data" / "smol.txt").resolve() ) L1 = "Once upon a midnight dreary, while I pondered, weak and weary,\n" def test_single_char(input_data_path, tmpdir): # NOTE: Here the line delim should not matter for this char tokenizer config = SimpleConfig(input_data_path=input_data_path, checkpoint_dir=tmpdir, field_delimiter=",") trainer = tok.CharTokenizerTrainer(config=config) # We need this for batch mode, so verify it can be copied deepcopy(trainer) line_iter = trainer.annotate_data() # Assert that we didn't do any annotation line_one = next(line_iter) assert line_one == L1 # Let's train the tokenizer, and now reload it back in trainer.train() tokenizer = tok.CharTokenizer.load(tmpdir) assert tokenizer.total_vocab_size == 32 # NOTE: this is because we default to using this token as a delim # in the main config, but this tokenizer doesn't do anything with it anyway assert tokenizer.field_delimiter == "," assert tokenizer.field_delimiter_token == "<d>" l1_ids = [6, 21, 11, 13, 1, 28, 23, 22, 21, 1, 9, 1, 20, 17, 12, 21, 17, 15, 16, 27, 1, 12, 25, 13, 9, 25, 31, 2, 1, 30, 16, 17, 19, 13, 1, 5, 1, 23, 22, 21, 12, 13, 25, 13, 12, 2, 1, 30, 13, 9, 18, 1, 9, 21, 12, 1, 30, 13, 9, 25, 31, 2, 0] assert tokenizer.encode_to_ids(L1) == l1_ids assert tokenizer.decode_from_ids(l1_ids) == L1 # Check the factory assert isinstance( tok.tokenizer_from_model_dir(tmpdir), tok.CharTokenizer ) def test_single_char_small_vocab(input_data_path, tmpdir): config = SimpleConfig(input_data_path=input_data_path, checkpoint_dir=tmpdir) trainer = tok.CharTokenizerTrainer(config=config, vocab_size=10) trainer.annotate_data() trainer.train() tokenizer = tok.CharTokenizer.load(tmpdir) assert tokenizer.total_vocab_size == 10 # Too small of a vocab... with pytest.raises(tok.TokenizerError): tokenizer.encode_to_ids("Once upon") with pytest.raises(tok.TokenizerError): tokenizer.decode_from_ids([11]) def test_sp(input_data_path, tmpdir): config = SimpleConfig(input_data_path=input_data_path, checkpoint_dir=tmpdir) trainer = tok.SentencePieceTokenizerTrainer(config=config) deepcopy(trainer) line_iter = trainer.annotate_data() line_one = next(line_iter) assert line_one == "Once upon a midnight dreary, while I pondered, weak and weary,<n>\n" trainer.train() tokenizer = tok.SentencePieceTokenizer.load(tmpdir) ids = [41, 54, 8, 5, 11, 36, 10, 14, 16, 13, 17, 16, 22, 20, 15, 5, 13, 25, 32, 7, 6, 51, 42, 9, 8, 5, 23, 5, 36, 13, 48, 13, 6, 49, 62, 10, 28, 49, 25, 7, 6, 3] assert tokenizer.encode_to_ids("Once upon a midnight dreary, while I pondered, weak and weary,<n>\n") == ids assert tokenizer.decode_from_ids(ids) == "Once upon a midnight dreary, while I pondered, weak and weary,<n>" def test_sp_field_delim(input_data_path, tmpdir): config = SimpleConfig(input_data_path=input_data_path, checkpoint_dir=tmpdir, field_delimiter=",") trainer = tok.SentencePieceTokenizerTrainer(config=config) line_iter = trainer.annotate_data() line_one = next(line_iter) assert line_one == "Once upon a midnight dreary<d> while I pondered<d> weak and weary<d><n>\n" trainer.train() tokenizer = tok.SentencePieceTokenizer.load(tmpdir) ids = [40, 53, 7, 5, 10, 35, 9, 13, 15, 12, 16, 15, 21, 19, 14, 5, 12, 24, 30, 6, 4, 51, 41, 8, 7, 5, 23, 5, 35, 12, 47, 12, 4, 48, 61, 9, 27, 48, 24, 6, 4, 3] assert tokenizer.encode_to_ids("Once upon a midnight dreary<d> while I pondered<d> weak and weary<d><n>\n") == ids assert tokenizer.decode_from_ids(ids) == "Once upon a midnight dreary, while I pondered, weak and weary,<n>" # Check the factory assert isinstance( tok.tokenizer_from_model_dir(tmpdir), tok.SentencePieceTokenizer )

36.157025

244

0.688229

from pathlib import Path from copy import deepcopy import pytest from gretel_synthetics.config import BaseConfig import gretel_synthetics.tokenizers as tok class SimpleConfig(BaseConfig): def get_generator_class(self): return None def get_training_callable(self): return None @pytest.fixture(scope="module") def input_data_path(): return str( (Path(__file__).parent / "data" / "smol.txt").resolve() ) L1 = "Once upon a midnight dreary, while I pondered, weak and weary,\n" def test_single_char(input_data_path, tmpdir): config = SimpleConfig(input_data_path=input_data_path, checkpoint_dir=tmpdir, field_delimiter=",") trainer = tok.CharTokenizerTrainer(config=config) deepcopy(trainer) line_iter = trainer.annotate_data() line_one = next(line_iter) assert line_one == L1 # Let's train the tokenizer, and now reload it back in trainer.train() tokenizer = tok.CharTokenizer.load(tmpdir) assert tokenizer.total_vocab_size == 32 assert tokenizer.field_delimiter == "," assert tokenizer.field_delimiter_token == "<d>" l1_ids = [6, 21, 11, 13, 1, 28, 23, 22, 21, 1, 9, 1, 20, 17, 12, 21, 17, 15, 16, 27, 1, 12, 25, 13, 9, 25, 31, 2, 1, 30, 16, 17, 19, 13, 1, 5, 1, 23, 22, 21, 12, 13, 25, 13, 12, 2, 1, 30, 13, 9, 18, 1, 9, 21, 12, 1, 30, 13, 9, 25, 31, 2, 0] assert tokenizer.encode_to_ids(L1) == l1_ids assert tokenizer.decode_from_ids(l1_ids) == L1 # Check the factory assert isinstance( tok.tokenizer_from_model_dir(tmpdir), tok.CharTokenizer ) def test_single_char_small_vocab(input_data_path, tmpdir): config = SimpleConfig(input_data_path=input_data_path, checkpoint_dir=tmpdir) trainer = tok.CharTokenizerTrainer(config=config, vocab_size=10) trainer.annotate_data() trainer.train() tokenizer = tok.CharTokenizer.load(tmpdir) assert tokenizer.total_vocab_size == 10 # Too small of a vocab... with pytest.raises(tok.TokenizerError): tokenizer.encode_to_ids("Once upon") with pytest.raises(tok.TokenizerError): tokenizer.decode_from_ids([11]) def test_sp(input_data_path, tmpdir): config = SimpleConfig(input_data_path=input_data_path, checkpoint_dir=tmpdir) trainer = tok.SentencePieceTokenizerTrainer(config=config) deepcopy(trainer) line_iter = trainer.annotate_data() line_one = next(line_iter) assert line_one == "Once upon a midnight dreary, while I pondered, weak and weary,<n>\n" trainer.train() tokenizer = tok.SentencePieceTokenizer.load(tmpdir) ids = [41, 54, 8, 5, 11, 36, 10, 14, 16, 13, 17, 16, 22, 20, 15, 5, 13, 25, 32, 7, 6, 51, 42, 9, 8, 5, 23, 5, 36, 13, 48, 13, 6, 49, 62, 10, 28, 49, 25, 7, 6, 3] assert tokenizer.encode_to_ids("Once upon a midnight dreary, while I pondered, weak and weary,<n>\n") == ids assert tokenizer.decode_from_ids(ids) == "Once upon a midnight dreary, while I pondered, weak and weary,<n>" def test_sp_field_delim(input_data_path, tmpdir): config = SimpleConfig(input_data_path=input_data_path, checkpoint_dir=tmpdir, field_delimiter=",") trainer = tok.SentencePieceTokenizerTrainer(config=config) line_iter = trainer.annotate_data() line_one = next(line_iter) assert line_one == "Once upon a midnight dreary<d> while I pondered<d> weak and weary<d><n>\n" trainer.train() tokenizer = tok.SentencePieceTokenizer.load(tmpdir) ids = [40, 53, 7, 5, 10, 35, 9, 13, 15, 12, 16, 15, 21, 19, 14, 5, 12, 24, 30, 6, 4, 51, 41, 8, 7, 5, 23, 5, 35, 12, 47, 12, 4, 48, 61, 9, 27, 48, 24, 6, 4, 3] assert tokenizer.encode_to_ids("Once upon a midnight dreary<d> while I pondered<d> weak and weary<d><n>\n") == ids assert tokenizer.decode_from_ids(ids) == "Once upon a midnight dreary, while I pondered, weak and weary,<n>" # Check the factory assert isinstance( tok.tokenizer_from_model_dir(tmpdir), tok.SentencePieceTokenizer )

true

f704d041172d3126183353d0f84901d0084003b4

82,008

py

Python

aiida/backends/tests/export_and_import.py

joepvd/aiida_core

6e9711046753332933f982971db1d7ac7e7ade58

[ "BSD-2-Clause" ]

null

aiida/backends/tests/export_and_import.py

joepvd/aiida_core

6e9711046753332933f982971db1d7ac7e7ade58

[ "BSD-2-Clause" ]

null

aiida/backends/tests/export_and_import.py

joepvd/aiida_core

6e9711046753332933f982971db1d7ac7e7ade58

[ "BSD-2-Clause" ]

null

# -*- coding: utf-8 -*- ########################################################################### # Copyright (c), The AiiDA team. All rights reserved. # # This file is part of the AiiDA code. # # # # The code is hosted on GitHub at https://github.com/aiidateam/aiida_core # # For further information on the license, see the LICENSE.txt file # # For further information please visit http://www.aiida.net # ########################################################################### """ Tests for the export and import routines. """ from __future__ import division from __future__ import print_function from __future__ import absolute_import import io import six from six.moves import range, zip from aiida.backends.testbase import AiidaTestCase from aiida.orm.importexport import import_data from aiida import orm class TestSpecificImport(AiidaTestCase): def setUp(self): super(TestSpecificImport, self).setUp() self.clean_db() self.insert_data() def test_simple_import(self): """ This is a very simple test which checks that an export file with nodes that are not associated to a computer is imported correctly. In Django when such nodes are exported, there is an empty set for computers in the export file. In SQLA there is such a set only when a computer is associated with the exported nodes. When an empty computer set is found at the export file (when imported to an SQLA profile), the SQLA import code used to crash. This test demonstrates this problem. """ import tempfile from aiida.orm.data.parameter import ParameterData from aiida.orm.importexport import export, import_data from aiida.orm.node import Node from aiida.orm.querybuilder import QueryBuilder parameters = ParameterData(dict={ 'Pr': { 'cutoff': 50.0, 'pseudo_type': 'Wentzcovitch', 'dual': 8, 'cutoff_units': 'Ry' }, 'Ru': { 'cutoff': 40.0, 'pseudo_type': 'SG15', 'dual': 4, 'cutoff_units': 'Ry' }, }).store() with tempfile.NamedTemporaryFile() as handle: nodes = [parameters] export(nodes, outfile=handle.name, overwrite=True, silent=True) # Check that we have the expected number of nodes in the database self.assertEquals(QueryBuilder().append(Node).count(), len(nodes)) # Clean the database and verify there are no nodes left self.clean_db() self.assertEquals(QueryBuilder().append(Node).count(), 0) # After importing we should have the original number of nodes again import_data(handle.name, silent=True) self.assertEquals(QueryBuilder().append(Node).count(), len(nodes)) def test_cycle_structure_data(self): """ Create an export with some Calculation and Data nodes and import it after having cleaned the database. Verify that the nodes and their attributes are restored properly after importing the created export archive """ import tempfile from aiida.common.links import LinkType from aiida.orm.calculation import Calculation from aiida.orm.data.structure import StructureData from aiida.orm.data.remote import RemoteData from aiida.orm.importexport import export, import_data from aiida.orm.node import Node from aiida.orm.querybuilder import QueryBuilder test_label = 'Test structure' test_cell = [ [8.34, 0.0, 0.0], [0.298041701839357, 8.53479766274308, 0.0], [0.842650688117053, 0.47118495164127, 10.6965192730702] ] test_kinds = [ { 'symbols': [u'Fe'], 'weights': [1.0], 'mass': 55.845, 'name': u'Fe' }, { 'symbols': [u'S'], 'weights': [1.0], 'mass': 32.065, 'name': u'S' } ] structure = StructureData(cell=test_cell) structure.append_atom(symbols=['Fe'], position=[0, 0, 0]) structure.append_atom(symbols=['S'], position=[2, 2, 2]) structure.label = test_label structure.store() parent_calculation = Calculation() parent_calculation._set_attr('key', 'value') parent_calculation.store() child_calculation = Calculation() child_calculation._set_attr('key', 'value') child_calculation.store() remote_folder = RemoteData(computer=self.computer, remote_path='/').store() remote_folder.add_link_from(parent_calculation, link_type=LinkType.CREATE) child_calculation.add_link_from(remote_folder, link_type=LinkType.INPUT) structure.add_link_from(child_calculation, link_type=LinkType.CREATE) with tempfile.NamedTemporaryFile() as handle: nodes = [structure, child_calculation, parent_calculation, remote_folder] export(nodes, outfile=handle.name, overwrite=True, silent=True) # Check that we have the expected number of nodes in the database self.assertEquals(QueryBuilder().append(Node).count(), len(nodes)) # Clean the database and verify there are no nodes left self.clean_db() self.assertEquals(QueryBuilder().append(Node).count(), 0) # After importing we should have the original number of nodes again import_data(handle.name, silent=True) self.assertEquals(QueryBuilder().append(Node).count(), len(nodes)) # Verify that Calculations have non-empty attribute dictionaries qb = QueryBuilder().append(Calculation) for [calculation] in qb.iterall(): self.assertIsInstance(calculation.get_attrs(), dict) self.assertNotEquals(len(calculation.get_attrs()), 0) # Verify that the structure data maintained its label, cell and kinds qb = QueryBuilder().append(StructureData) for [structure] in qb.iterall(): self.assertEquals(structure.label, test_label) self.assertEquals(structure.cell, test_cell) qb = QueryBuilder().append(StructureData, project=['attributes.kinds']) for [kinds] in qb.iterall(): self.assertEqual(len(kinds), 2) for kind in kinds: self.assertIn(kind, test_kinds) # Check that there is a StructureData that is an output of a Calculation qb = QueryBuilder() qb.append(Calculation, project=['uuid'], tag='calculation') qb.append(StructureData, output_of='calculation') self.assertGreater(len(qb.all()), 0) # Check that there is a RemoteData that is a child and parent of a Calculation qb = QueryBuilder() qb.append(Calculation, tag='parent') qb.append(RemoteData, project=['uuid'], output_of='parent', tag='remote') qb.append(Calculation, output_of='remote') self.assertGreater(len(qb.all()), 0) class TestSimple(AiidaTestCase): def setUp(self): self.clean_db() self.insert_data() def tearDown(self): pass def test_0(self): import os import shutil import tempfile from aiida.orm import load_node from aiida.orm.data.base import Str, Int, Float, Bool from aiida.orm.importexport import export # Creating a folder for the import/export files temp_folder = tempfile.mkdtemp() try: # producing values for each base type values = ("Hello", 6, -1.2399834e12, False) # , ["Bla", 1, 1e-10]) filename = os.path.join(temp_folder, "export.tar.gz") # producing nodes: nodes = [cls(val).store() for val, cls in zip(values, (Str, Int, Float, Bool))] # my uuid - list to reload the node: uuids = [n.uuid for n in nodes] # exporting the nodes: export(nodes, outfile=filename, silent=True) # cleaning: self.clean_db() # Importing back the data: import_data(filename, silent=True) # Checking whether values are preserved: for uuid, refval in zip(uuids, values): self.assertEquals(load_node(uuid).value, refval) finally: # Deleting the created temporary folder shutil.rmtree(temp_folder, ignore_errors=True) def test_1(self): import os import shutil import tempfile from aiida.orm import DataFactory from aiida.orm import load_node from aiida.orm.calculation.job import JobCalculation from aiida.orm.importexport import export # Creating a folder for the import/export files temp_folder = tempfile.mkdtemp() try: StructureData = DataFactory('structure') sd = StructureData() sd.store() calc = JobCalculation() calc.set_computer(self.computer) calc.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) calc.store() calc.add_link_from(sd) pks = [sd.pk, calc.pk] attrs = {} for pk in pks: node = load_node(pk) attrs[node.uuid] = dict() for k in node.attrs(): attrs[node.uuid][k] = node.get_attr(k) filename = os.path.join(temp_folder, "export.tar.gz") export([calc], outfile=filename, silent=True) self.clean_db() # NOTE: it is better to load new nodes by uuid, rather than assuming # that they will have the first 3 pks. In fact, a recommended policy in # databases is that pk always increment, even if you've deleted elements import_data(filename, silent=True) for uuid in attrs.keys(): node = load_node(uuid) # for k in node.attrs(): for k in attrs[uuid].keys(): self.assertEquals(attrs[uuid][k], node.get_attr(k)) finally: # Deleting the created temporary folder shutil.rmtree(temp_folder, ignore_errors=True) # print temp_folder def test_2(self): """ Test the check for the export format version. """ import tarfile import os import shutil import tempfile from aiida.common import exceptions from aiida.orm import DataFactory from aiida.orm.importexport import export import aiida.utils.json as json # Creating a folder for the import/export files export_file_tmp_folder = tempfile.mkdtemp() unpack_tmp_folder = tempfile.mkdtemp() try: StructureData = DataFactory('structure') sd = StructureData() sd.store() filename = os.path.join(export_file_tmp_folder, "export.tar.gz") export([sd], outfile=filename, silent=True) with tarfile.open(filename, "r:gz", format=tarfile.PAX_FORMAT) as tar: tar.extractall(unpack_tmp_folder) with io.open(os.path.join(unpack_tmp_folder, 'metadata.json'), 'r', encoding='utf8') as fhandle: metadata = json.load(fhandle) metadata['export_version'] = 0.0 with io.open(os.path.join(unpack_tmp_folder, 'metadata.json'), 'wb') as fhandle: json.dump(metadata, fhandle) with tarfile.open(filename, "w:gz", format=tarfile.PAX_FORMAT) as tar: tar.add(unpack_tmp_folder, arcname="") self.tearDownClass() self.setUpClass() with self.assertRaises(exceptions.IncompatibleArchiveVersionError): import_data(filename, silent=True) finally: # Deleting the created temporary folders shutil.rmtree(export_file_tmp_folder, ignore_errors=True) shutil.rmtree(unpack_tmp_folder, ignore_errors=True) def test_3(self): """ Test importing of nodes, that have links to unknown nodes. """ import tarfile import os import shutil import tempfile from aiida.orm.importexport import export from aiida.common.folders import SandboxFolder from aiida.orm.data.structure import StructureData from aiida.orm import load_node import aiida.utils.json as json # Creating a folder for the import/export files temp_folder = tempfile.mkdtemp() try: node_label = "Test structure data" sd = StructureData() sd.label = str(node_label) sd.store() filename = os.path.join(temp_folder, "export.tar.gz") export([sd], outfile=filename, silent=True) unpack = SandboxFolder() with tarfile.open( filename, "r:gz", format=tarfile.PAX_FORMAT) as tar: tar.extractall(unpack.abspath) with io.open(unpack.get_abs_path('data.json'), 'r', encoding='utf8') as fhandle: metadata = json.load(fhandle) metadata['links_uuid'].append({ 'output': sd.uuid, 'input': 'non-existing-uuid', 'label': 'parent' }) with io.open(unpack.get_abs_path('data.json'), 'wb') as fhandle: json.dump(metadata, fhandle) with tarfile.open( filename, "w:gz", format=tarfile.PAX_FORMAT) as tar: tar.add(unpack.abspath, arcname="") self.clean_db() with self.assertRaises(ValueError): import_data(filename, silent=True) import_data(filename, ignore_unknown_nodes=True, silent=True) self.assertEquals(load_node(sd.uuid).label, node_label) finally: # Deleting the created temporary folder shutil.rmtree(temp_folder, ignore_errors=True) def test_4(self): """ Test control of licenses. """ from aiida.common.exceptions import LicensingException from aiida.common.folders import SandboxFolder from aiida.orm.importexport import export_tree from aiida.orm import DataFactory StructureData = DataFactory('structure') sd = StructureData() sd.source = {'license': 'GPL'} sd.store() folder = SandboxFolder() export_tree([sd], folder=folder, silent=True, allowed_licenses=['GPL']) # Folder should contain two files of metadata + nodes/ self.assertEquals(len(folder.get_content_list()), 3) folder = SandboxFolder() export_tree([sd], folder=folder, silent=True, forbidden_licenses=['Academic']) # Folder should contain two files of metadata + nodes/ self.assertEquals(len(folder.get_content_list()), 3) folder = SandboxFolder() with self.assertRaises(LicensingException): export_tree([sd], folder=folder, silent=True, allowed_licenses=['CC0']) folder = SandboxFolder() with self.assertRaises(LicensingException): export_tree([sd], folder=folder, silent=True, forbidden_licenses=['GPL']) def cc_filter(license): return license.startswith('CC') def gpl_filter(license): return license == 'GPL' def crashing_filter(license): raise NotImplementedError("not implemented yet") folder = SandboxFolder() with self.assertRaises(LicensingException): export_tree([sd], folder=folder, silent=True, allowed_licenses=cc_filter) folder = SandboxFolder() with self.assertRaises(LicensingException): export_tree([sd], folder=folder, silent=True, forbidden_licenses=gpl_filter) folder = SandboxFolder() with self.assertRaises(LicensingException): export_tree([sd], folder=folder, silent=True, allowed_licenses=crashing_filter) folder = SandboxFolder() with self.assertRaises(LicensingException): export_tree([sd], folder=folder, silent=True, forbidden_licenses=crashing_filter) def test_5(self): """ This test checks that nodes belonging to different users are correctly exported & imported. """ import os import shutil import tempfile from aiida.orm import load_node from aiida.orm.calculation.job import JobCalculation from aiida.orm.data.structure import StructureData from aiida.orm.importexport import export from aiida.common.datastructures import calc_states from aiida.common.links import LinkType from aiida.common.utils import get_configured_user_email # Creating a folder for the import/export files temp_folder = tempfile.mkdtemp() try: # Create another user new_email = "newuser@new.n" user = orm.User(email=new_email, backend=self.backend).store() # Create a structure data node that has a calculation as output sd1 = StructureData() sd1.set_user(user) sd1.label = 'sd1' sd1.store() jc1 = JobCalculation() jc1.set_computer(self.computer) jc1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) jc1.set_user(user) jc1.label = 'jc1' jc1.store() jc1.add_link_from(sd1) jc1._set_state(calc_states.PARSING) # Create some nodes from a different user sd2 = StructureData() sd2.set_user(user) sd2.label = 'sd2' sd2.store() sd2.add_link_from(jc1, label='l1', link_type=LinkType.CREATE) # I assume jc1 CREATED sd2 jc2 = JobCalculation() jc2.set_computer(self.computer) jc2.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) jc2.label = 'jc2' jc2.store() jc2.add_link_from(sd2, label='l2') jc2._set_state(calc_states.PARSING) sd3 = StructureData() sd3.label = 'sd3' sd3.store() sd3.add_link_from(jc2, label='l3', link_type=LinkType.CREATE) uuids_u1 = [sd1.uuid, jc1.uuid, sd2.uuid] uuids_u2 = [jc2.uuid, sd3.uuid] filename = os.path.join(temp_folder, "export.tar.gz") export([sd3], outfile=filename, silent=True) self.clean_db() import_data(filename, silent=True) # Check that the imported nodes are correctly imported and that # the user assigned to the nodes is the right one for uuid in uuids_u1: node = load_node(uuid=uuid) self.assertEquals(node.get_user().email, new_email) for uuid in uuids_u2: self.assertEquals(load_node(uuid).get_user().email, get_configured_user_email()) finally: # Deleting the created temporary folder shutil.rmtree(temp_folder, ignore_errors=True) def test_6(self): """ This test checks that nodes belonging to user A (which is not the default user) can be correctly exported, imported, enriched with nodes from the default user, re-exported & re-imported and that in the end all the nodes that have been finally imported belonging to the right users. """ import os import shutil import tempfile from aiida.orm import load_node from aiida.orm.calculation.job import JobCalculation from aiida.orm.data.structure import StructureData from aiida.orm.importexport import export from aiida.common.datastructures import calc_states from aiida.common.links import LinkType from aiida.common.utils import get_configured_user_email # Creating a folder for the import/export files temp_folder = tempfile.mkdtemp() try: # Create another user new_email = "newuser@new.n" user = orm.User(email=new_email, backend=self.backend).store() # Create a structure data node that has a calculation as output sd1 = StructureData() sd1.set_user(user) sd1.label = 'sd1' sd1.store() jc1 = JobCalculation() jc1.set_computer(self.computer) jc1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) jc1.set_user(user) jc1.label = 'jc1' jc1.store() jc1.add_link_from(sd1) jc1._set_state(calc_states.PARSING) # Create some nodes from a different user sd2 = StructureData() sd2.set_user(user) sd2.label = 'sd2' sd2.store() sd2.add_link_from(jc1, label='l1', link_type=LinkType.CREATE) # Set the jc1 to FINISHED jc1._set_state(calc_states.FINISHED) # At this point we export the generated data filename1 = os.path.join(temp_folder, "export1.tar.gz") export([sd2], outfile=filename1, silent=True) uuids1 = [sd1.uuid, jc1.uuid, sd2.uuid] self.clean_db() self.insert_data() import_data(filename1, silent=True) # Check that the imported nodes are correctly imported and that # the user assigned to the nodes is the right one for uuid in uuids1: self.assertEquals(load_node(uuid).get_user().email, new_email) # Now we continue to generate more data based on the imported # data sd2_imp = load_node(sd2.uuid) jc2 = JobCalculation() jc2.set_computer(self.computer) jc2.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) jc2.label = 'jc2' jc2.store() jc2.add_link_from(sd2_imp, label='l2') jc2._set_state(calc_states.PARSING) sd3 = StructureData() sd3.label = 'sd3' sd3.store() sd3.add_link_from(jc2, label='l3', link_type=LinkType.CREATE) # Set the jc2 to FINISHED jc2._set_state(calc_states.FINISHED) # Store the UUIDs of the nodes that should be checked # if they can be imported correctly. uuids2 = [jc2.uuid, sd3.uuid] filename2 = os.path.join(temp_folder, "export2.tar.gz") export([sd3], outfile=filename2, silent=True) self.clean_db() self.insert_data() import_data(filename2, silent=True) # Check that the imported nodes are correctly imported and that # the user assigned to the nodes is the right one for uuid in uuids1: self.assertEquals(load_node(uuid).get_user().email, new_email) for uuid in uuids2: self.assertEquals(load_node(uuid).get_user().email, get_configured_user_email()) finally: # Deleting the created temporary folder shutil.rmtree(temp_folder, ignore_errors=True) def test_7(self): """ This test checks that nodes that belong to a specific group are correctly imported and exported. """ import os import shutil import tempfile from aiida.orm import load_node from aiida.orm.calculation.job import JobCalculation from aiida.orm.data.structure import StructureData from aiida.orm.importexport import export from aiida.common.datastructures import calc_states from aiida.orm.querybuilder import QueryBuilder # Creating a folder for the import/export files temp_folder = tempfile.mkdtemp() try: # Create another user new_email = "newuser@new.n" user = orm.User(email=new_email, backend=self.backend) user.store() # Create a structure data node that has a calculation as output sd1 = StructureData() sd1.set_user(user) sd1.label = 'sd1' sd1.store() jc1 = JobCalculation() jc1.set_computer(self.computer) jc1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) jc1.set_user(user) jc1.label = 'jc1' jc1.store() jc1.add_link_from(sd1) jc1._set_state(calc_states.PARSING) # Create a group and add the data inside from aiida.orm.group import Group g1 = Group(name="node_group") g1.store() g1.add_nodes([sd1, jc1]) g1_uuid = g1.uuid # At this point we export the generated data filename1 = os.path.join(temp_folder, "export1.tar.gz") export([sd1, jc1, g1], outfile=filename1, silent=True) n_uuids = [sd1.uuid, jc1.uuid] self.clean_db() self.insert_data() import_data(filename1, silent=True) # Check that the imported nodes are correctly imported and that # the user assigned to the nodes is the right one for uuid in n_uuids: self.assertEquals(load_node(uuid).get_user().email, new_email) # Check that the exported group is imported correctly qb = QueryBuilder() qb.append(Group, filters={'uuid': {'==': g1_uuid}}) self.assertEquals(qb.count(), 1, "The group was not found.") finally: # Deleting the created temporary folder shutil.rmtree(temp_folder, ignore_errors=True) def test_group_export(self): """ Test that when exporting just a group, its nodes are also exported """ import os import shutil import tempfile from aiida.orm import load_node from aiida.orm.data.structure import StructureData from aiida.orm.importexport import export from aiida.orm.querybuilder import QueryBuilder # Creating a folder for the import/export files temp_folder = tempfile.mkdtemp() try: # Create another user new_email = "newuser@new.n" user = orm.User(email=new_email, backend=self.backend) user.store() # Create a structure data node sd1 = StructureData() sd1.set_user(user) sd1.label = 'sd1' sd1.store() # Create a group and add the data inside from aiida.orm.group import Group g1 = Group(name="node_group") g1.store() g1.add_nodes([sd1]) g1_uuid = g1.uuid # At this point we export the generated data filename1 = os.path.join(temp_folder, "export1.tar.gz") export([g1], outfile=filename1, silent=True) n_uuids = [sd1.uuid] self.clean_db() self.insert_data() import_data(filename1, silent=True) # Check that the imported nodes are correctly imported and that # the user assigned to the nodes is the right one for uuid in n_uuids: self.assertEquals(load_node(uuid).get_user().email, new_email) # Check that the exported group is imported correctly qb = QueryBuilder() qb.append(Group, filters={'uuid': {'==': g1_uuid}}) self.assertEquals(qb.count(), 1, "The group was not found.") finally: # Deleting the created temporary folder shutil.rmtree(temp_folder, ignore_errors=True) def test_workfunction_1(self): import shutil, os, tempfile from aiida.work.workfunctions import workfunction from aiida.orm.data.float import Float from aiida.orm import load_node from aiida.orm.importexport import export from aiida.common.exceptions import NotExistent # Creating a folder for the import/export files temp_folder = tempfile.mkdtemp() @workfunction def add(a, b): """Add 2 numbers""" return {'res': Float(a + b)} def max_(**kwargs): """select the max value""" max_val = max([(v.value, v) for v in kwargs.values()]) return {'res': max_val[1]} try: # I'm creating a bunch of nuimbers a, b, c, d, e = (Float(i) for i in range(5)) # this adds the maximum number between bcde to a. res = add(a=a, b=max_(b=b, c=c, d=d, e=e)['res'])['res'] # These are the uuids that would be exported as well (as parents) if I wanted the final result uuids_values = [(a.uuid, a.value), (e.uuid, e.value), (res.uuid, res.value)] # These are the uuids that shouldn't be exported since it's a selection. not_wanted_uuids = [v.uuid for v in (b, c, d)] # At this point we export the generated data filename1 = os.path.join(temp_folder, "export1.tar.gz") export([res], outfile=filename1, silent=True) self.clean_db() self.insert_data() import_data(filename1, silent=True) # Check that the imported nodes are correctly imported and that the value is preserved for uuid, value in uuids_values: self.assertEquals(load_node(uuid).value, value) for uuid in not_wanted_uuids: with self.assertRaises(NotExistent): load_node(uuid) finally: # Deleting the created temporary folder shutil.rmtree(temp_folder, ignore_errors=True) def test_workcalculation_2(self): import shutil, os, tempfile from aiida.orm.calculation.work import WorkCalculation from aiida.orm.data.float import Float from aiida.orm.data.int import Int from aiida.orm import load_node from aiida.common.links import LinkType from aiida.orm.importexport import export from aiida.common.exceptions import NotExistent # Creating a folder for the import/export files temp_folder = tempfile.mkdtemp() try: master = WorkCalculation().store() slave = WorkCalculation().store() input_1 = Int(3).store() input_2 = Int(5).store() output_1 = Int(2).store() master.add_link_from(input_1, 'input_1', link_type=LinkType.INPUT) slave.add_link_from(master, 'CALL', link_type=LinkType.CALL) slave.add_link_from(input_2, 'input_2', link_type=LinkType.INPUT) output_1.add_link_from(master, 'CREATE', link_type=LinkType.CREATE) uuids_values = [(v.uuid, v.value) for v in (output_1,)] filename1 = os.path.join(temp_folder, "export1.tar.gz") export([output_1], outfile=filename1, silent=True) self.clean_db() self.insert_data() import_data(filename1, silent=True) for uuid, value in uuids_values: self.assertEquals(load_node(uuid).value, value) finally: # Deleting the created temporary folder shutil.rmtree(temp_folder, ignore_errors=True) def test_reexport(self): """ Export something, import and reexport and check if everything is valid. The export is rather easy:: ___ ___ ___ | | INP | | CREATE | | | p | --> | c | -----> | a | |___| |___| |___| """ import os, shutil, tempfile, numpy as np, string, random from datetime import datetime from aiida.orm import Calculation, load_node, Group from aiida.orm.data.array import ArrayData from aiida.orm.data.parameter import ParameterData from aiida.orm.querybuilder import QueryBuilder from aiida.orm.importexport import export from aiida.common.hashing import make_hash from aiida.common.links import LinkType def get_hash_from_db_content(groupname): qb = QueryBuilder() qb.append(ParameterData, tag='p', project='*') qb.append(Calculation, tag='c', project='*', edge_tag='p2c', edge_project=('label', 'type')) qb.append(ArrayData, tag='a', project='*', edge_tag='c2a', edge_project=('label', 'type')) qb.append(Group, filters={'name': groupname}, project='*', tag='g', group_of='a') # I want the query to contain something! self.assertTrue(qb.count() > 0) # The hash is given from the preservable entries in an export-import cycle, # uuids, attributes, labels, descriptions, arrays, link-labels, link-types: hash_ = make_hash([( item['p']['*'].get_attrs(), item['p']['*'].uuid, item['p']['*'].label, item['p']['*'].description, item['c']['*'].uuid, item['c']['*'].get_attrs(), item['a']['*'].get_attrs(), [item['a']['*'].get_array(name) for name in item['a']['*'].get_arraynames()], item['a']['*'].uuid, item['g']['*'].uuid, item['g']['*'].name, item['p2c']['label'], item['p2c']['type'], item['c2a']['label'], item['c2a']['type'], item['g']['*'].name, ) for item in qb.dict()]) return hash_ # Creating a folder for the import/export files temp_folder = tempfile.mkdtemp() chars = string.ascii_uppercase + string.digits size = 10 groupname = 'test-group' try: nparr = np.random.random((4, 3, 2)) trial_dict = {} # give some integers: trial_dict.update({str(k): np.random.randint(100) for k in range(10)}) # give some floats: trial_dict.update({str(k): np.random.random() for k in range(10, 20)}) # give some booleans: trial_dict.update({str(k): bool(np.random.randint(1)) for k in range(20, 30)}) # give some datetime: trial_dict.update({str(k): datetime( year=2017, month=np.random.randint(1, 12), day=np.random.randint(1, 28)) for k in range(30, 40)}) # give some text: trial_dict.update({str(k): ''.join(random.choice(chars) for _ in range(size)) for k in range(20, 30)}) p = ParameterData(dict=trial_dict) p.label = str(datetime.now()) p.description = 'd_' + str(datetime.now()) p.store() c = Calculation() # setting also trial dict as attributes, but randomizing the keys) (c._set_attr(str(int(k) + np.random.randint(10)), v) for k, v in trial_dict.items()) c.store() a = ArrayData() a.set_array('array', nparr) a.store() # LINKS # the calculation has input the parameters-instance c.add_link_from(p, label='input_parameters', link_type=LinkType.INPUT) # I want the array to be an output of the calculation a.add_link_from(c, label='output_array', link_type=LinkType.CREATE) g = Group(name='test-group') g.store() g.add_nodes(a) hash_from_dbcontent = get_hash_from_db_content(groupname) # I export and reimport 3 times in a row: for i in range(3): # Always new filename: filename = os.path.join(temp_folder, "export-{}.zip".format(i)) # Loading the group from the string g = Group.get_from_string(groupname) # exporting based on all members of the group # this also checks if group memberships are preserved! export([g] + [n for n in g.nodes], outfile=filename, silent=True) # cleaning the DB! self.clean_db() # reimporting the data from the file import_data(filename, silent=True, ignore_unknown_nodes=True) # creating the hash from db content new_hash = get_hash_from_db_content(groupname) # I check for equality against the first hash created, which implies that hashes # are equal in all iterations of this process self.assertEqual(hash_from_dbcontent, new_hash) finally: # Deleting the created temporary folder shutil.rmtree(temp_folder, ignore_errors=True) class TestComplex(AiidaTestCase): def test_complex_graph_import_export(self): """ This test checks that a small and bit complex graph can be correctly exported and imported. It will create the graph, store it to the database, export it to a file and import it. In the end it will check if the initial nodes are present at the imported graph. """ import tempfile import shutil import os from aiida.orm.calculation.job import JobCalculation from aiida.orm.data.folder import FolderData from aiida.orm.data.parameter import ParameterData from aiida.orm.data.remote import RemoteData from aiida.common.links import LinkType from aiida.orm.importexport import export, import_data from aiida.orm.utils import load_node from aiida.common.exceptions import NotExistent temp_folder = tempfile.mkdtemp() try: calc1 = JobCalculation() calc1.set_computer(self.computer) calc1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) calc1.label = "calc1" calc1.store() calc1._set_state(u'RETRIEVING') pd1 = ParameterData() pd1.label = "pd1" pd1.store() pd2 = ParameterData() pd2.label = "pd2" pd2.store() rd1 = RemoteData() rd1.label = "rd1" rd1.set_remote_path("/x/y.py") rd1.set_computer(self.computer) rd1.store() rd1.add_link_from(calc1, link_type=LinkType.CREATE) calc2 = JobCalculation() calc2.set_computer(self.computer) calc2.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) calc2.label = "calc2" calc2.store() calc2.add_link_from(pd1, link_type=LinkType.INPUT) calc2.add_link_from(pd2, link_type=LinkType.INPUT) calc2.add_link_from(rd1, link_type=LinkType.INPUT) calc2._set_state(u'SUBMITTING') fd1 = FolderData() fd1.label = "fd1" fd1.store() fd1.add_link_from(calc2, link_type=LinkType.CREATE) node_uuids_labels = {calc1.uuid: calc1.label, pd1.uuid: pd1.label, pd2.uuid: pd2.label, rd1.uuid: rd1.label, calc2.uuid: calc2.label, fd1.uuid: fd1.label} filename = os.path.join(temp_folder, "export.tar.gz") export([fd1], outfile=filename, silent=True) self.clean_db() import_data(filename, silent=True, ignore_unknown_nodes=True) for uuid, label in node_uuids_labels.items(): try: load_node(uuid) except NotExistent: self.fail("Node with UUID {} and label {} was not " "found.".format(uuid, label)) finally: # Deleting the created temporary folder shutil.rmtree(temp_folder, ignore_errors=True) class TestComputer(AiidaTestCase): def setUp(self): self.clean_db() self.insert_data() def tearDown(self): pass def test_same_computer_import(self): """ Test that you can import nodes in steps without any problems. In this test we will import a first calculation and then a second one. The import should work as expected and have in the end two job calculations. Each calculation is related to the same computer. In the end we should have only one computer """ import os import shutil import tempfile from aiida.orm.importexport import export from aiida.orm.querybuilder import QueryBuilder from aiida.orm.computers import Computer from aiida.orm.calculation.job import JobCalculation # Creating a folder for the import/export files export_file_tmp_folder = tempfile.mkdtemp() unpack_tmp_folder = tempfile.mkdtemp() try: # Store two job calculation related to the same computer calc1_label = "calc1" calc1 = JobCalculation() calc1.set_computer(self.computer) calc1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) calc1.label = calc1_label calc1.store() calc1._set_state(u'RETRIEVING') calc2_label = "calc2" calc2 = JobCalculation() calc2.set_computer(self.computer) calc2.set_option('resources', {"num_machines": 2, "num_mpiprocs_per_machine": 2}) calc2.label = calc2_label calc2.store() calc2._set_state(u'RETRIEVING') # Store locally the computer name comp_name = six.text_type(self.computer.name) comp_uuid = six.text_type(self.computer.uuid) # Export the first job calculation filename1 = os.path.join(export_file_tmp_folder, "export1.tar.gz") export([calc1], outfile=filename1, silent=True) # Export the second job calculation filename2 = os.path.join(export_file_tmp_folder, "export2.tar.gz") export([calc2], outfile=filename2, silent=True) # Clean the local database self.clean_db() # Check that there are no computers qb = QueryBuilder() qb.append(Computer, project=['*']) self.assertEqual(qb.count(), 0, "There should not be any computers" "in the database at this point.") # Check that there are no calculations qb = QueryBuilder() qb.append(JobCalculation, project=['*']) self.assertEqual(qb.count(), 0, "There should not be any " "calculations in the database at " "this point.") # Import the first calculation import_data(filename1, silent=True) # Check that the calculation computer is imported correctly. qb = QueryBuilder() qb.append(JobCalculation, project=['label']) self.assertEqual(qb.count(), 1, "Only one calculation should be " "found.") self.assertEqual(six.text_type(qb.first()[0]), calc1_label, "The calculation label is not correct.") # Check that the referenced computer is imported correctly. qb = QueryBuilder() qb.append(Computer, project=['name', 'uuid', 'id']) self.assertEqual(qb.count(), 1, "Only one computer should be " "found.") self.assertEqual(six.text_type(qb.first()[0]), comp_name, "The computer name is not correct.") self.assertEqual(six.text_type(qb.first()[1]), comp_uuid, "The computer uuid is not correct.") # Store the id of the computer comp_id = qb.first()[2] # Import the second calculation import_data(filename2, silent=True) # Check that the number of computers remains the same and its data # did not change. qb = QueryBuilder() qb.append(Computer, project=['name', 'uuid', 'id']) self.assertEqual(qb.count(), 1, "Only one computer should be " "found.") self.assertEqual(six.text_type(qb.first()[0]), comp_name, "The computer name is not correct.") self.assertEqual(six.text_type(qb.first()[1]), comp_uuid, "The computer uuid is not correct.") self.assertEqual(qb.first()[2], comp_id, "The computer id is not correct.") # Check that now you have two calculations attached to the same # computer. qb = QueryBuilder() qb.append(Computer, tag='comp') qb.append(JobCalculation, has_computer='comp', project=['label']) self.assertEqual(qb.count(), 2, "Two calculations should be " "found.") ret_labels = set(_ for [_] in qb.all()) self.assertEqual(ret_labels, set([calc1_label, calc2_label]), "The labels of the calculations are not correct.") finally: # Deleting the created temporary folders shutil.rmtree(export_file_tmp_folder, ignore_errors=True) shutil.rmtree(unpack_tmp_folder, ignore_errors=True) def test_same_computer_different_name_import(self): """ This test checks that if the computer is re-imported with a different name to the same database, then the original computer will not be renamed. It also checks that the names were correctly imported (without any change since there is no computer name collision) """ import os import shutil import tempfile from aiida.orm.importexport import export from aiida.orm.querybuilder import QueryBuilder from aiida.orm.computers import Computer from aiida.orm.calculation.job import JobCalculation # Creating a folder for the import/export files export_file_tmp_folder = tempfile.mkdtemp() unpack_tmp_folder = tempfile.mkdtemp() try: # Store a calculation calc1_label = "calc1" calc1 = JobCalculation() calc1.set_computer(self.computer) calc1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) calc1.label = calc1_label calc1.store() calc1._set_state(u'RETRIEVING') # Store locally the computer name comp1_name = six.text_type(self.computer.name) # Export the first job calculation filename1 = os.path.join(export_file_tmp_folder, "export1.tar.gz") export([calc1], outfile=filename1, silent=True) # Rename the computer self.computer.set_name(comp1_name + "_updated") # Store a second calculation calc2_label = "calc2" calc2 = JobCalculation() calc2.set_computer(self.computer) calc2.set_option('resources', {"num_machines": 2, "num_mpiprocs_per_machine": 2}) calc2.label = calc2_label calc2.store() calc2._set_state(u'RETRIEVING') # Export the second job calculation filename2 = os.path.join(export_file_tmp_folder, "export2.tar.gz") export([calc2], outfile=filename2, silent=True) # Clean the local database self.clean_db() # Check that there are no computers qb = QueryBuilder() qb.append(Computer, project=['*']) self.assertEqual(qb.count(), 0, "There should not be any computers" "in the database at this point.") # Check that there are no calculations qb = QueryBuilder() qb.append(JobCalculation, project=['*']) self.assertEqual(qb.count(), 0, "There should not be any " "calculations in the database at " "this point.") # Import the first calculation import_data(filename1, silent=True) # Check that the calculation computer is imported correctly. qb = QueryBuilder() qb.append(JobCalculation, project=['label']) self.assertEqual(qb.count(), 1, "Only one calculation should be " "found.") self.assertEqual(six.text_type(qb.first()[0]), calc1_label, "The calculation label is not correct.") # Check that the referenced computer is imported correctly. qb = QueryBuilder() qb.append(Computer, project=['name', 'uuid', 'id']) self.assertEqual(qb.count(), 1, "Only one computer should be " "found.") self.assertEqual(six.text_type(qb.first()[0]), comp1_name, "The computer name is not correct.") # Import the second calculation import_data(filename2, silent=True) # Check that the number of computers remains the same and its data # did not change. qb = QueryBuilder() qb.append(Computer, project=['name']) self.assertEqual(qb.count(), 1, "Only one computer should be " "found.") self.assertEqual(six.text_type(qb.first()[0]), comp1_name, "The computer name is not correct.") finally: # Deleting the created temporary folders shutil.rmtree(export_file_tmp_folder, ignore_errors=True) shutil.rmtree(unpack_tmp_folder, ignore_errors=True) def test_different_computer_same_name_import(self): """ This test checks that if there is a name collision, the imported computers are renamed accordingly. """ import os import shutil import tempfile from aiida.orm.importexport import export from aiida.orm.querybuilder import QueryBuilder from aiida.orm.computers import Computer from aiida.orm.calculation.job import JobCalculation from aiida.orm.importexport import COMP_DUPL_SUFFIX # Creating a folder for the import/export files export_file_tmp_folder = tempfile.mkdtemp() unpack_tmp_folder = tempfile.mkdtemp() try: # Set the computer name comp1_name = "localhost_1" self.computer.set_name(comp1_name) # Store a calculation calc1_label = "calc1" calc1 = JobCalculation() calc1.set_computer(self.computer) calc1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) calc1.label = calc1_label calc1.store() calc1._set_state(u'RETRIEVING') # Export the first job calculation filename1 = os.path.join(export_file_tmp_folder, "export1.tar.gz") export([calc1], outfile=filename1, silent=True) # Reset the database self.clean_db() self.insert_data() # Set the computer name to the same name as before self.computer.set_name(comp1_name) # Store a second calculation calc2_label = "calc2" calc2 = JobCalculation() calc2.set_computer(self.computer) calc2.set_option('resources', {"num_machines": 2, "num_mpiprocs_per_machine": 2}) calc2.label = calc2_label calc2.store() calc2._set_state(u'RETRIEVING') # Export the second job calculation filename2 = os.path.join(export_file_tmp_folder, "export2.tar.gz") export([calc2], outfile=filename2, silent=True) # Reset the database self.clean_db() self.insert_data() # Set the computer name to the same name as before self.computer.set_name(comp1_name) # Store a third calculation calc3_label = "calc3" calc3 = JobCalculation() calc3.set_computer(self.computer) calc3.set_option('resources', {"num_machines": 2, "num_mpiprocs_per_machine": 2}) calc3.label = calc3_label calc3.store() calc3._set_state(u'RETRIEVING') # Export the third job calculation filename3 = os.path.join(export_file_tmp_folder, "export3.tar.gz") export([calc3], outfile=filename3, silent=True) # Clean the local database self.clean_db() # Check that there are no computers qb = QueryBuilder() qb.append(Computer, project=['*']) self.assertEqual(qb.count(), 0, "There should not be any computers" "in the database at this point.") # Check that there are no calculations qb = QueryBuilder() qb.append(JobCalculation, project=['*']) self.assertEqual(qb.count(), 0, "There should not be any " "calculations in the database at " "this point.") # Import all the calculations import_data(filename1, silent=True) import_data(filename2, silent=True) import_data(filename3, silent=True) # Retrieve the calculation-computer pairs qb = QueryBuilder() qb.append(JobCalculation, project=['label'], tag='jcalc') qb.append(Computer, project=['name'], computer_of='jcalc') self.assertEqual(qb.count(), 3, "Three combinations expected.") res = qb.all() self.assertIn([calc1_label, comp1_name], res, "Calc-Computer combination not found.") self.assertIn([calc2_label, comp1_name + COMP_DUPL_SUFFIX.format(0)], res, "Calc-Computer combination not found.") self.assertIn([calc3_label, comp1_name + COMP_DUPL_SUFFIX.format(1)], res, "Calc-Computer combination not found.") finally: # Deleting the created temporary folders shutil.rmtree(export_file_tmp_folder, ignore_errors=True) shutil.rmtree(unpack_tmp_folder, ignore_errors=True) def test_correct_import_of_computer_json_params(self): """ This test checks that the metadata and transport params are exported and imported correctly in both backends. """ import os import shutil import tempfile from aiida.orm.importexport import export from aiida.orm.querybuilder import QueryBuilder from aiida.orm.computers import Computer from aiida.orm.calculation.job import JobCalculation # Creating a folder for the import/export files export_file_tmp_folder = tempfile.mkdtemp() unpack_tmp_folder = tempfile.mkdtemp() try: # Set the computer name comp1_name = "localhost_1" comp1_metadata = { u'workdir': u'/tmp/aiida' } comp1_transport_params = { u'key1': u'value1', u'key2': 2 } self.computer.set_name(comp1_name) self.computer._set_metadata(comp1_metadata) self.computer.set_transport_params(comp1_transport_params) # Store a calculation calc1_label = "calc1" calc1 = JobCalculation() calc1.set_computer(self.computer) calc1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) calc1.label = calc1_label calc1.store() calc1._set_state(u'RETRIEVING') # Export the first job calculation filename1 = os.path.join(export_file_tmp_folder, "export1.tar.gz") export([calc1], outfile=filename1, silent=True) # Clean the local database self.clean_db() # Import the data import_data(filename1, silent=True) qb = QueryBuilder() qb.append(Computer, project=['transport_params', '_metadata'], tag="comp") self.assertEqual(qb.count(), 1, "Expected only one computer") res = qb.dict()[0] self.assertEqual(res['comp']['transport_params'], comp1_transport_params, "Not the expected transport parameters " "were found") self.assertEqual(res['comp']['_metadata'], comp1_metadata, "Not the expected metadata were found") finally: # Deleting the created temporary folders shutil.rmtree(export_file_tmp_folder, ignore_errors=True) shutil.rmtree(unpack_tmp_folder, ignore_errors=True) def test_import_of_django_sqla_export_file(self): """ Check why sqla import manages to import the django export file correctly """ from aiida.backends.tests.utils.fixtures import import_archive_fixture from aiida.orm.querybuilder import QueryBuilder from aiida.orm.computers import Computer for archive in ['export/compare/django.aiida', 'export/compare/sqlalchemy.aiida']: # Clean the database self.clean_db() # Import the needed data import_archive_fixture(archive) # The expected metadata & transport parameters comp1_metadata = { u'workdir': u'/tmp/aiida' } comp1_transport_params = { u'key1': u'value1', u'key2': 2 } # Check that we got the correct metadata & transport parameters qb = QueryBuilder() qb.append(Computer, project=['transport_params', '_metadata'], tag="comp") self.assertEqual(qb.count(), 1, "Expected only one computer") res = qb.dict()[0] self.assertEqual(res['comp']['transport_params'], comp1_transport_params) self.assertEqual(res['comp']['_metadata'], comp1_metadata) class TestLinks(AiidaTestCase): def setUp(self): self.clean_db() self.insert_data() def tearDown(self): pass def get_all_node_links(self): """ """ from aiida.orm import load_node, Node from aiida.orm.querybuilder import QueryBuilder qb = QueryBuilder() qb.append(Node, project='uuid', tag='input') qb.append(Node, project='uuid', tag='output', edge_project=['label', 'type'], output_of='input') return qb.all() def test_input_and_create_links(self): """ Simple test that will verify that INPUT and CREATE links are properly exported and correctly recreated upon import. """ import os, shutil, tempfile from aiida.orm.data.int import Int from aiida.orm.importexport import export from aiida.orm.calculation.work import WorkCalculation from aiida.common.links import LinkType tmp_folder = tempfile.mkdtemp() try: node_work = WorkCalculation().store() node_input = Int(1).store() node_output = Int(2).store() node_work.add_link_from(node_input, 'input', link_type=LinkType.INPUT) node_output.add_link_from(node_work, 'output', link_type=LinkType.CREATE) export_links = self.get_all_node_links() export_file = os.path.join(tmp_folder, 'export.tar.gz') export([node_output], outfile=export_file, silent=True) self.clean_db() self.insert_data() import_data(export_file, silent=True) import_links = self.get_all_node_links() export_set = [tuple(_) for _ in export_links] import_set = [tuple(_) for _ in import_links] self.assertEquals(set(export_set), set(import_set)) finally: shutil.rmtree(tmp_folder, ignore_errors=True) def construct_complex_graph(self, export_combination=0): """ This method creates a "complex" graph with all available link types (INPUT, CREATE, RETURN and CALL) and returns the nodes of the graph. It also returns various combinations of nodes that need to be extracted but also the final expected set of nodes (after adding the expected predecessors, desuccessors). """ from aiida.orm.data.base import Int from aiida.orm.calculation.job import JobCalculation from aiida.orm.calculation.work import WorkCalculation from aiida.common.datastructures import calc_states from aiida.common.links import LinkType if export_combination < 0 or export_combination > 8: return None # Node creation d1 = Int(1).store() d2 = Int(1).store() wc1 = WorkCalculation().store() wc2 = WorkCalculation().store() pw1 = JobCalculation() pw1.set_computer(self.computer) pw1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) pw1.store() d3 = Int(1).store() d4 = Int(1).store() pw2 = JobCalculation() pw2.set_computer(self.computer) pw2.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) pw2.store() d5 = Int(1).store() d6 = Int(1).store() # Link creation wc1.add_link_from(d1, 'input1', link_type=LinkType.INPUT) wc1.add_link_from(d2, 'input2', link_type=LinkType.INPUT) wc2.add_link_from(d1, 'input', link_type=LinkType.INPUT) wc2.add_link_from(wc1, 'call', link_type=LinkType.CALL) pw1.add_link_from(d1, 'input', link_type=LinkType.INPUT) pw1.add_link_from(wc2, 'call', link_type=LinkType.CALL) pw1._set_state(calc_states.PARSING) d3.add_link_from(pw1, 'create', link_type=LinkType.CREATE) d3.add_link_from(wc2, 'return', link_type=LinkType.RETURN) d4.add_link_from(pw1, 'create', link_type=LinkType.CREATE) d4.add_link_from(wc2, 'return', link_type=LinkType.RETURN) pw2.add_link_from(d4, 'input', link_type=LinkType.INPUT) pw2._set_state(calc_states.PARSING) d5.add_link_from(pw2, 'create', link_type=LinkType.CREATE) d6.add_link_from(pw2, 'create', link_type=LinkType.CREATE) # Return the generated nodes graph_nodes = [d1, d2, d3, d4, d5, d6, pw1, pw2, wc1, wc2] # Create various combinations of nodes that should be exported # and the final set of nodes that are exported in each case, following # predecessor/successor links. export_list = [ (wc1, [d1, d2, d3, d4, pw1, wc1, wc2]), (wc2, [d1, d3, d4, pw1, wc2]), (d3, [d1, d3, d4, pw1]), (d4, [d1, d3, d4, pw1]), (d5, [d1, d3, d4, d5, d6, pw1, pw2]), (d6, [d1, d3, d4, d5, d6, pw1, pw2]), (pw2, [d1, d3, d4, d5, d6, pw1, pw2]), (d1, [d1]), (d2, [d2]) ] return graph_nodes, export_list[export_combination] def test_data_create_reversed_false(self): """Verify that create_reversed = False is respected when only exporting Data nodes.""" import os import shutil import tempfile from aiida.common.datastructures import calc_states from aiida.orm import Data, Group from aiida.orm.data.base import Int from aiida.orm.calculation.job import JobCalculation from aiida.orm.importexport import export from aiida.common.links import LinkType from aiida.orm.querybuilder import QueryBuilder tmp_folder = tempfile.mkdtemp() try: data_input = Int(1).store() data_output = Int(2).store() calc = JobCalculation() calc.set_computer(self.computer) calc.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) calc.store() calc.add_link_from(data_input, 'input', link_type=LinkType.INPUT) calc._set_state(calc_states.PARSING) data_output.add_link_from(calc, 'create', link_type=LinkType.CREATE) group = Group.create(name='test_group') group.add_nodes(data_output) export_file = os.path.join(tmp_folder, 'export.tar.gz') export([group], outfile=export_file, silent=True, create_reversed=False) self.clean_db() self.insert_data() import_data(export_file, silent=True) builder = QueryBuilder() builder.append(Data) self.assertEqual(builder.count(), 1, 'Expected a single Data node but got {}'.format(builder.count())) self.assertEqual(builder.all()[0][0].uuid, data_output.uuid) builder = QueryBuilder() builder.append(JobCalculation) self.assertEqual(builder.count(), 0, 'Expected no Calculation nodes') finally: shutil.rmtree(tmp_folder, ignore_errors=True) def test_complex_workflow_graph_links(self): """ This test checks that all the needed links are correctly exported and imported. More precisely, it checks that INPUT, CREATE, RETURN and CALL links connecting Data nodes, JobCalculations and WorkCalculations are exported and imported correctly. """ import os, shutil, tempfile from aiida.orm import Node from aiida.orm.importexport import export from aiida.common.links import LinkType from aiida.orm.querybuilder import QueryBuilder tmp_folder = tempfile.mkdtemp() try: graph_nodes, _ = self.construct_complex_graph() # Getting the input, create, return and call links qb = QueryBuilder() qb.append(Node, project='uuid') qb.append(Node, project='uuid', edge_project=['label', 'type'], edge_filters={'type': {'in': (LinkType.INPUT.value, LinkType.CREATE.value, LinkType.RETURN.value, LinkType.CALL.value)}}) export_links = qb.all() export_file = os.path.join(tmp_folder, 'export.tar.gz') export(graph_nodes, outfile=export_file, silent=True) self.clean_db() self.insert_data() import_data(export_file, silent=True) import_links = self.get_all_node_links() export_set = [tuple(_) for _ in export_links] import_set = [tuple(_) for _ in import_links] self.assertEquals(set(export_set), set(import_set)) finally: shutil.rmtree(tmp_folder, ignore_errors=True) def test_complex_workflow_graph_export_set_expansion(self): import os, shutil, tempfile from aiida.orm.importexport import export from aiida.orm.querybuilder import QueryBuilder from aiida.orm import Node for export_conf in range(0, 8): graph_nodes, (export_node, export_target) = ( self.construct_complex_graph(export_conf)) tmp_folder = tempfile.mkdtemp() try: export_file = os.path.join(tmp_folder, 'export.tar.gz') export([export_node], outfile=export_file, silent=True) export_node_str = str(export_node) self.clean_db() self.insert_data() import_data(export_file, silent=True) # Get all the nodes of the database qb = QueryBuilder() qb.append(Node, project='uuid') imported_node_uuids = set(str(_[0]) for _ in qb.all()) export_target_uuids = set(str(_.uuid) for _ in export_target) from aiida.orm.utils import load_node self.assertEquals( export_target_uuids, imported_node_uuids, "Problem in comparison of export node: " + str(export_node_str) + "\n" + "Expected set: " + str(export_target_uuids) + "\n" + "Imported set: " + str(imported_node_uuids) + "\n" + "Difference: " + str([load_node(_) for _ in export_target_uuids.symmetric_difference( imported_node_uuids)]) ) finally: shutil.rmtree(tmp_folder, ignore_errors=True) def test_recursive_export_input_and_create_links_proper(self): """ Check that CALL, INPUT, RETURN and CREATE links are followed recursively. """ import os, shutil, tempfile from aiida.orm import Node from aiida.orm.data.base import Int from aiida.orm.importexport import export from aiida.orm.calculation.inline import InlineCalculation from aiida.orm.calculation.work import WorkCalculation from aiida.common.links import LinkType from aiida.orm.querybuilder import QueryBuilder tmp_folder = tempfile.mkdtemp() try: wc2 = WorkCalculation().store() wc1 = WorkCalculation().store() c1 = InlineCalculation().store() ni1 = Int(1).store() ni2 = Int(2).store() no1 = Int(1).store() no2 = Int(2).store() # Create the connections between workcalculations and calculations wc1.add_link_from(wc2, 'call', link_type=LinkType.CALL) c1.add_link_from(wc1, 'call', link_type=LinkType.CALL) # Connect the first data node to wc1 & c1 wc1.add_link_from(ni1, 'ni1-to-wc1', link_type=LinkType.INPUT) c1.add_link_from(ni1, 'ni1-to-c1', link_type=LinkType.INPUT) # Connect the second data node to wc1 & c1 wc1.add_link_from(ni2, 'ni2-to-wc1', link_type=LinkType.INPUT) c1.add_link_from(ni2, 'ni2-to-c1', link_type=LinkType.INPUT) # Connecting the first output node to wc1 & c1 no1.add_link_from(wc1, 'output', link_type=LinkType.RETURN) no1.add_link_from(c1, 'output', link_type=LinkType.CREATE) # Connecting the second output node to wc1 & c1 no2.add_link_from(wc1, 'output', link_type=LinkType.RETURN) no2.add_link_from(c1, 'output', link_type=LinkType.CREATE) # Getting the input, create, return and call links qb = QueryBuilder() qb.append(Node, project='uuid') qb.append(Node, project='uuid', edge_project=['label', 'type'], edge_filters={'type': {'in': (LinkType.INPUT.value, LinkType.CREATE.value, LinkType.RETURN.value, LinkType.CALL.value)}}) export_links = qb.all() export_file = os.path.join(tmp_folder, 'export.tar.gz') export([wc2], outfile=export_file, silent=True) self.clean_db() self.insert_data() import_data(export_file, silent=True) import_links = self.get_all_node_links() export_set = [tuple(_) for _ in export_links] import_set = [tuple(_) for _ in import_links] self.assertEquals(set(export_set), set(import_set)) finally: shutil.rmtree(tmp_folder, ignore_errors=True) def test_links_for_workflows(self): """ Check that CALL links are not followed in the export procedure, and the only creation is followed for data:: ____ ____ ____ | | INP | | CALL | | | i1 | --> | w1 | <--- | w2 | |____| |____| |____| | | CREATE v v RETURN ____ | | | o1 | |____| """ import os, shutil, tempfile from aiida.orm.data.base import Int from aiida.orm.importexport import export from aiida.orm.calculation.work import WorkCalculation from aiida.common.links import LinkType tmp_folder = tempfile.mkdtemp() try: w1 = WorkCalculation().store() w2 = WorkCalculation().store() i1 = Int(1).store() o1 = Int(2).store() w1.add_link_from(i1, 'input-i1', link_type=LinkType.INPUT) w1.add_link_from(w2, 'call', link_type=LinkType.CALL) o1.add_link_from(w1, 'output', link_type=LinkType.CREATE) o1.add_link_from(w1, 'return', link_type=LinkType.RETURN) links_wanted = [l for l in self.get_all_node_links() if l[3] in (LinkType.CREATE.value, LinkType.INPUT.value, LinkType.RETURN.value)] export_file_1 = os.path.join(tmp_folder, 'export-1.tar.gz') export_file_2 = os.path.join(tmp_folder, 'export-2.tar.gz') export([o1], outfile=export_file_1, silent=True) export([w1], outfile=export_file_2, silent=True) self.clean_db() self.insert_data() import_data(export_file_1, silent=True) links_in_db = self.get_all_node_links() self.assertEquals(sorted(links_wanted), sorted(links_in_db)) self.clean_db() self.insert_data() import_data(export_file_2, silent=True) links_in_db = self.get_all_node_links() self.assertEquals(sorted(links_wanted), sorted(links_in_db)) finally: shutil.rmtree(tmp_folder, ignore_errors=True) def test_double_return_links_for_workflows(self): """ This test checks that double return links to a node can be exported and imported without problems, """ import os, shutil, tempfile from aiida.orm.data.base import Int from aiida.orm.importexport import export from aiida.orm.calculation.work import WorkCalculation from aiida.common.links import LinkType from aiida.orm.querybuilder import QueryBuilder from aiida.orm.node import Node tmp_folder = tempfile.mkdtemp() try: w1 = WorkCalculation().store() w2 = WorkCalculation().store() i1 = Int(1).store() o1 = Int(2).store() w1.add_link_from(i1, 'input-i1', link_type=LinkType.INPUT) w1.add_link_from(w2, 'call', link_type=LinkType.CALL) o1.add_link_from(w1, 'output', link_type=LinkType.CREATE) o1.add_link_from(w1, 'return', link_type=LinkType.RETURN) o1.add_link_from(w2, 'return', link_type=LinkType.RETURN) uuids_wanted = set(_.uuid for _ in (w1, o1, i1, w2)) links_wanted = [l for l in self.get_all_node_links() if l[3] in ( 'createlink', 'inputlink', 'returnlink', 'calllink')] export_file = os.path.join(tmp_folder, 'export.tar.gz') export([o1, w1, w2, i1], outfile=export_file, silent=True) self.clean_db() self.insert_data() import_data(export_file, silent=True) uuids_in_db = [str(uuid) for [uuid] in QueryBuilder().append(Node, project='uuid').all()] self.assertEquals(sorted(uuids_wanted), sorted(uuids_in_db)) links_in_db = self.get_all_node_links() self.assertEquals(sorted(links_wanted), sorted(links_in_db)) finally: shutil.rmtree(tmp_folder, ignore_errors=True) def test_that_solo_code_is_exported_correctly(self): """ This test checks that when a calculation is exported then the corresponding code is also exported. """ import os, shutil, tempfile from aiida.orm.utils import load_node from aiida.orm.importexport import export from aiida.orm.code import Code tmp_folder = tempfile.mkdtemp() try: code_label = 'test_code1' code = Code() code.set_remote_computer_exec((self.computer, '/bin/true')) code.label = code_label code.store() code_uuid = code.uuid export_file = os.path.join(tmp_folder, 'export.tar.gz') export([code], outfile=export_file, silent=True) self.clean_db() self.insert_data() import_data(export_file, silent=True) self.assertEquals(load_node(code_uuid).label, code_label) finally: shutil.rmtree(tmp_folder, ignore_errors=True) def test_that_input_code_is_exported_correctly(self): """ This test checks that when a calculation is exported then the corresponding code is also exported. It also checks that the links are also in place after the import. """ import os, shutil, tempfile from aiida.orm.utils import load_node from aiida.orm.importexport import export from aiida.common.links import LinkType from aiida.orm.calculation.job import JobCalculation from aiida.orm.code import Code from aiida.orm.querybuilder import QueryBuilder tmp_folder = tempfile.mkdtemp() try: code_label = 'test_code1' code = Code() code.set_remote_computer_exec((self.computer, '/bin/true')) code.label = code_label code.store() code_uuid = code.uuid jc = JobCalculation() jc.set_computer(self.computer) jc.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) jc.store() jc.add_link_from(code, 'code', link_type=LinkType.INPUT) export_file = os.path.join(tmp_folder, 'export.tar.gz') export([jc], outfile=export_file, silent=True) self.clean_db() self.insert_data() import_data(export_file, silent=True) # Check that the node is there self.assertEquals(load_node(code_uuid).label, code_label) # Check that the link is in place qb = QueryBuilder() qb.append(Code, project='uuid') qb.append(JobCalculation, project='uuid', edge_project=['label', 'type'], edge_filters={'type': {'==': LinkType.INPUT.value}}) self.assertEquals(qb.count(), 1, "Expected to find one and only one link from " "code to the calculation node. {} found." .format(qb.count())) finally: shutil.rmtree(tmp_folder, ignore_errors=True)

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t tempfile from aiida.orm import load_node from aiida.orm.data.base import Str, Int, Float, Bool from aiida.orm.importexport import export temp_folder = tempfile.mkdtemp() try: values = ("Hello", 6, -1.2399834e12, False) filename = os.path.join(temp_folder, "export.tar.gz") nodes = [cls(val).store() for val, cls in zip(values, (Str, Int, Float, Bool))] uuids = [n.uuid for n in nodes] export(nodes, outfile=filename, silent=True) self.clean_db() import_data(filename, silent=True) for uuid, refval in zip(uuids, values): self.assertEquals(load_node(uuid).value, refval) finally: shutil.rmtree(temp_folder, ignore_errors=True) def test_1(self): import os import shutil import tempfile from aiida.orm import DataFactory from aiida.orm import load_node from aiida.orm.calculation.job import JobCalculation from aiida.orm.importexport import export temp_folder = tempfile.mkdtemp() try: StructureData = DataFactory('structure') sd = StructureData() sd.store() calc = JobCalculation() calc.set_computer(self.computer) calc.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) calc.store() calc.add_link_from(sd) pks = [sd.pk, calc.pk] attrs = {} for pk in pks: node = load_node(pk) attrs[node.uuid] = dict() for k in node.attrs(): attrs[node.uuid][k] = node.get_attr(k) filename = os.path.join(temp_folder, "export.tar.gz") export([calc], outfile=filename, silent=True) self.clean_db() import_data(filename, silent=True) for uuid in attrs.keys(): node = load_node(uuid) # for k in node.attrs(): for k in attrs[uuid].keys(): self.assertEquals(attrs[uuid][k], node.get_attr(k)) finally: # Deleting the created temporary folder shutil.rmtree(temp_folder, ignore_errors=True) # print temp_folder def test_2(self): import tarfile import os import shutil import tempfile from aiida.common import exceptions from aiida.orm import DataFactory from aiida.orm.importexport import export import aiida.utils.json as json # Creating a folder for the import/export files export_file_tmp_folder = tempfile.mkdtemp() unpack_tmp_folder = tempfile.mkdtemp() try: StructureData = DataFactory('structure') sd = StructureData() sd.store() filename = os.path.join(export_file_tmp_folder, "export.tar.gz") export([sd], outfile=filename, silent=True) with tarfile.open(filename, "r:gz", format=tarfile.PAX_FORMAT) as tar: tar.extractall(unpack_tmp_folder) with io.open(os.path.join(unpack_tmp_folder, 'metadata.json'), 'r', encoding='utf8') as fhandle: metadata = json.load(fhandle) metadata['export_version'] = 0.0 with io.open(os.path.join(unpack_tmp_folder, 'metadata.json'), 'wb') as fhandle: json.dump(metadata, fhandle) with tarfile.open(filename, "w:gz", format=tarfile.PAX_FORMAT) as tar: tar.add(unpack_tmp_folder, arcname="") self.tearDownClass() self.setUpClass() with self.assertRaises(exceptions.IncompatibleArchiveVersionError): import_data(filename, silent=True) finally: # Deleting the created temporary folders shutil.rmtree(export_file_tmp_folder, ignore_errors=True) shutil.rmtree(unpack_tmp_folder, ignore_errors=True) def test_3(self): import tarfile import os import shutil import tempfile from aiida.orm.importexport import export from aiida.common.folders import SandboxFolder from aiida.orm.data.structure import StructureData from aiida.orm import load_node import aiida.utils.json as json # Creating a folder for the import/export files temp_folder = tempfile.mkdtemp() try: node_label = "Test structure data" sd = StructureData() sd.label = str(node_label) sd.store() filename = os.path.join(temp_folder, "export.tar.gz") export([sd], outfile=filename, silent=True) unpack = SandboxFolder() with tarfile.open( filename, "r:gz", format=tarfile.PAX_FORMAT) as tar: tar.extractall(unpack.abspath) with io.open(unpack.get_abs_path('data.json'), 'r', encoding='utf8') as fhandle: metadata = json.load(fhandle) metadata['links_uuid'].append({ 'output': sd.uuid, 'input': 'non-existing-uuid', 'label': 'parent' }) with io.open(unpack.get_abs_path('data.json'), 'wb') as fhandle: json.dump(metadata, fhandle) with tarfile.open( filename, "w:gz", format=tarfile.PAX_FORMAT) as tar: tar.add(unpack.abspath, arcname="") self.clean_db() with self.assertRaises(ValueError): import_data(filename, silent=True) import_data(filename, ignore_unknown_nodes=True, silent=True) self.assertEquals(load_node(sd.uuid).label, node_label) finally: # Deleting the created temporary folder shutil.rmtree(temp_folder, ignore_errors=True) def test_4(self): from aiida.common.exceptions import LicensingException from aiida.common.folders import SandboxFolder from aiida.orm.importexport import export_tree from aiida.orm import DataFactory StructureData = DataFactory('structure') sd = StructureData() sd.source = {'license': 'GPL'} sd.store() folder = SandboxFolder() export_tree([sd], folder=folder, silent=True, allowed_licenses=['GPL']) # Folder should contain two files of metadata + nodes/ self.assertEquals(len(folder.get_content_list()), 3) folder = SandboxFolder() export_tree([sd], folder=folder, silent=True, forbidden_licenses=['Academic']) # Folder should contain two files of metadata + nodes/ self.assertEquals(len(folder.get_content_list()), 3) folder = SandboxFolder() with self.assertRaises(LicensingException): export_tree([sd], folder=folder, silent=True, allowed_licenses=['CC0']) folder = SandboxFolder() with self.assertRaises(LicensingException): export_tree([sd], folder=folder, silent=True, forbidden_licenses=['GPL']) def cc_filter(license): return license.startswith('CC') def gpl_filter(license): return license == 'GPL' def crashing_filter(license): raise NotImplementedError("not implemented yet") folder = SandboxFolder() with self.assertRaises(LicensingException): export_tree([sd], folder=folder, silent=True, allowed_licenses=cc_filter) folder = SandboxFolder() with self.assertRaises(LicensingException): export_tree([sd], folder=folder, silent=True, forbidden_licenses=gpl_filter) folder = SandboxFolder() with self.assertRaises(LicensingException): export_tree([sd], folder=folder, silent=True, allowed_licenses=crashing_filter) folder = SandboxFolder() with self.assertRaises(LicensingException): export_tree([sd], folder=folder, silent=True, forbidden_licenses=crashing_filter) def test_5(self): import os import shutil import tempfile from aiida.orm import load_node from aiida.orm.calculation.job import JobCalculation from aiida.orm.data.structure import StructureData from aiida.orm.importexport import export from aiida.common.datastructures import calc_states from aiida.common.links import LinkType from aiida.common.utils import get_configured_user_email # Creating a folder for the import/export files temp_folder = tempfile.mkdtemp() try: # Create another user new_email = "newuser@new.n" user = orm.User(email=new_email, backend=self.backend).store() # Create a structure data node that has a calculation as output sd1 = StructureData() sd1.set_user(user) sd1.label = 'sd1' sd1.store() jc1 = JobCalculation() jc1.set_computer(self.computer) jc1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) jc1.set_user(user) jc1.label = 'jc1' jc1.store() jc1.add_link_from(sd1) jc1._set_state(calc_states.PARSING) # Create some nodes from a different user sd2 = StructureData() sd2.set_user(user) sd2.label = 'sd2' sd2.store() sd2.add_link_from(jc1, label='l1', link_type=LinkType.CREATE) # I assume jc1 CREATED sd2 jc2 = JobCalculation() jc2.set_computer(self.computer) jc2.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) jc2.label = 'jc2' jc2.store() jc2.add_link_from(sd2, label='l2') jc2._set_state(calc_states.PARSING) sd3 = StructureData() sd3.label = 'sd3' sd3.store() sd3.add_link_from(jc2, label='l3', link_type=LinkType.CREATE) uuids_u1 = [sd1.uuid, jc1.uuid, sd2.uuid] uuids_u2 = [jc2.uuid, sd3.uuid] filename = os.path.join(temp_folder, "export.tar.gz") export([sd3], outfile=filename, silent=True) self.clean_db() import_data(filename, silent=True) # Check that the imported nodes are correctly imported and that # the user assigned to the nodes is the right one for uuid in uuids_u1: node = load_node(uuid=uuid) self.assertEquals(node.get_user().email, new_email) for uuid in uuids_u2: self.assertEquals(load_node(uuid).get_user().email, get_configured_user_email()) finally: # Deleting the created temporary folder shutil.rmtree(temp_folder, ignore_errors=True) def test_6(self): import os import shutil import tempfile from aiida.orm import load_node from aiida.orm.calculation.job import JobCalculation from aiida.orm.data.structure import StructureData from aiida.orm.importexport import export from aiida.common.datastructures import calc_states from aiida.common.links import LinkType from aiida.common.utils import get_configured_user_email # Creating a folder for the import/export files temp_folder = tempfile.mkdtemp() try: # Create another user new_email = "newuser@new.n" user = orm.User(email=new_email, backend=self.backend).store() # Create a structure data node that has a calculation as output sd1 = StructureData() sd1.set_user(user) sd1.label = 'sd1' sd1.store() jc1 = JobCalculation() jc1.set_computer(self.computer) jc1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) jc1.set_user(user) jc1.label = 'jc1' jc1.store() jc1.add_link_from(sd1) jc1._set_state(calc_states.PARSING) # Create some nodes from a different user sd2 = StructureData() sd2.set_user(user) sd2.label = 'sd2' sd2.store() sd2.add_link_from(jc1, label='l1', link_type=LinkType.CREATE) # Set the jc1 to FINISHED jc1._set_state(calc_states.FINISHED) # At this point we export the generated data filename1 = os.path.join(temp_folder, "export1.tar.gz") export([sd2], outfile=filename1, silent=True) uuids1 = [sd1.uuid, jc1.uuid, sd2.uuid] self.clean_db() self.insert_data() import_data(filename1, silent=True) # Check that the imported nodes are correctly imported and that # the user assigned to the nodes is the right one for uuid in uuids1: self.assertEquals(load_node(uuid).get_user().email, new_email) # Now we continue to generate more data based on the imported # data sd2_imp = load_node(sd2.uuid) jc2 = JobCalculation() jc2.set_computer(self.computer) jc2.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) jc2.label = 'jc2' jc2.store() jc2.add_link_from(sd2_imp, label='l2') jc2._set_state(calc_states.PARSING) sd3 = StructureData() sd3.label = 'sd3' sd3.store() sd3.add_link_from(jc2, label='l3', link_type=LinkType.CREATE) # Set the jc2 to FINISHED jc2._set_state(calc_states.FINISHED) # Store the UUIDs of the nodes that should be checked # if they can be imported correctly. uuids2 = [jc2.uuid, sd3.uuid] filename2 = os.path.join(temp_folder, "export2.tar.gz") export([sd3], outfile=filename2, silent=True) self.clean_db() self.insert_data() import_data(filename2, silent=True) # Check that the imported nodes are correctly imported and that # the user assigned to the nodes is the right one for uuid in uuids1: self.assertEquals(load_node(uuid).get_user().email, new_email) for uuid in uuids2: self.assertEquals(load_node(uuid).get_user().email, get_configured_user_email()) finally: # Deleting the created temporary folder shutil.rmtree(temp_folder, ignore_errors=True) def test_7(self): import os import shutil import tempfile from aiida.orm import load_node from aiida.orm.calculation.job import JobCalculation from aiida.orm.data.structure import StructureData from aiida.orm.importexport import export from aiida.common.datastructures import calc_states from aiida.orm.querybuilder import QueryBuilder # Creating a folder for the import/export files temp_folder = tempfile.mkdtemp() try: # Create another user new_email = "newuser@new.n" user = orm.User(email=new_email, backend=self.backend) user.store() # Create a structure data node that has a calculation as output sd1 = StructureData() sd1.set_user(user) sd1.label = 'sd1' sd1.store() jc1 = JobCalculation() jc1.set_computer(self.computer) jc1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) jc1.set_user(user) jc1.label = 'jc1' jc1.store() jc1.add_link_from(sd1) jc1._set_state(calc_states.PARSING) # Create a group and add the data inside from aiida.orm.group import Group g1 = Group(name="node_group") g1.store() g1.add_nodes([sd1, jc1]) g1_uuid = g1.uuid # At this point we export the generated data filename1 = os.path.join(temp_folder, "export1.tar.gz") export([sd1, jc1, g1], outfile=filename1, silent=True) n_uuids = [sd1.uuid, jc1.uuid] self.clean_db() self.insert_data() import_data(filename1, silent=True) # Check that the imported nodes are correctly imported and that # the user assigned to the nodes is the right one for uuid in n_uuids: self.assertEquals(load_node(uuid).get_user().email, new_email) # Check that the exported group is imported correctly qb = QueryBuilder() qb.append(Group, filters={'uuid': {'==': g1_uuid}}) self.assertEquals(qb.count(), 1, "The group was not found.") finally: # Deleting the created temporary folder shutil.rmtree(temp_folder, ignore_errors=True) def test_group_export(self): import os import shutil import tempfile from aiida.orm import load_node from aiida.orm.data.structure import StructureData from aiida.orm.importexport import export from aiida.orm.querybuilder import QueryBuilder # Creating a folder for the import/export files temp_folder = tempfile.mkdtemp() try: # Create another user new_email = "newuser@new.n" user = orm.User(email=new_email, backend=self.backend) user.store() # Create a structure data node sd1 = StructureData() sd1.set_user(user) sd1.label = 'sd1' sd1.store() # Create a group and add the data inside from aiida.orm.group import Group g1 = Group(name="node_group") g1.store() g1.add_nodes([sd1]) g1_uuid = g1.uuid # At this point we export the generated data filename1 = os.path.join(temp_folder, "export1.tar.gz") export([g1], outfile=filename1, silent=True) n_uuids = [sd1.uuid] self.clean_db() self.insert_data() import_data(filename1, silent=True) # Check that the imported nodes are correctly imported and that # the user assigned to the nodes is the right one for uuid in n_uuids: self.assertEquals(load_node(uuid).get_user().email, new_email) # Check that the exported group is imported correctly qb = QueryBuilder() qb.append(Group, filters={'uuid': {'==': g1_uuid}}) self.assertEquals(qb.count(), 1, "The group was not found.") finally: # Deleting the created temporary folder shutil.rmtree(temp_folder, ignore_errors=True) def test_workfunction_1(self): import shutil, os, tempfile from aiida.work.workfunctions import workfunction from aiida.orm.data.float import Float from aiida.orm import load_node from aiida.orm.importexport import export from aiida.common.exceptions import NotExistent # Creating a folder for the import/export files temp_folder = tempfile.mkdtemp() @workfunction def add(a, b): return {'res': Float(a + b)} def max_(**kwargs): max_val = max([(v.value, v) for v in kwargs.values()]) return {'res': max_val[1]} try: # I'm creating a bunch of nuimbers a, b, c, d, e = (Float(i) for i in range(5)) res = add(a=a, b=max_(b=b, c=c, d=d, e=e)['res'])['res'] uuids_values = [(a.uuid, a.value), (e.uuid, e.value), (res.uuid, res.value)] not_wanted_uuids = [v.uuid for v in (b, c, d)] filename1 = os.path.join(temp_folder, "export1.tar.gz") export([res], outfile=filename1, silent=True) self.clean_db() self.insert_data() import_data(filename1, silent=True) for uuid, value in uuids_values: self.assertEquals(load_node(uuid).value, value) for uuid in not_wanted_uuids: with self.assertRaises(NotExistent): load_node(uuid) finally: shutil.rmtree(temp_folder, ignore_errors=True) def test_workcalculation_2(self): import shutil, os, tempfile from aiida.orm.calculation.work import WorkCalculation from aiida.orm.data.float import Float from aiida.orm.data.int import Int from aiida.orm import load_node from aiida.common.links import LinkType from aiida.orm.importexport import export from aiida.common.exceptions import NotExistent temp_folder = tempfile.mkdtemp() try: master = WorkCalculation().store() slave = WorkCalculation().store() input_1 = Int(3).store() input_2 = Int(5).store() output_1 = Int(2).store() master.add_link_from(input_1, 'input_1', link_type=LinkType.INPUT) slave.add_link_from(master, 'CALL', link_type=LinkType.CALL) slave.add_link_from(input_2, 'input_2', link_type=LinkType.INPUT) output_1.add_link_from(master, 'CREATE', link_type=LinkType.CREATE) uuids_values = [(v.uuid, v.value) for v in (output_1,)] filename1 = os.path.join(temp_folder, "export1.tar.gz") export([output_1], outfile=filename1, silent=True) self.clean_db() self.insert_data() import_data(filename1, silent=True) for uuid, value in uuids_values: self.assertEquals(load_node(uuid).value, value) finally: shutil.rmtree(temp_folder, ignore_errors=True) def test_reexport(self): import os, shutil, tempfile, numpy as np, string, random from datetime import datetime from aiida.orm import Calculation, load_node, Group from aiida.orm.data.array import ArrayData from aiida.orm.data.parameter import ParameterData from aiida.orm.querybuilder import QueryBuilder from aiida.orm.importexport import export from aiida.common.hashing import make_hash from aiida.common.links import LinkType def get_hash_from_db_content(groupname): qb = QueryBuilder() qb.append(ParameterData, tag='p', project='*') qb.append(Calculation, tag='c', project='*', edge_tag='p2c', edge_project=('label', 'type')) qb.append(ArrayData, tag='a', project='*', edge_tag='c2a', edge_project=('label', 'type')) qb.append(Group, filters={'name': groupname}, project='*', tag='g', group_of='a') self.assertTrue(qb.count() > 0) hash_ = make_hash([( item['p']['*'].get_attrs(), item['p']['*'].uuid, item['p']['*'].label, item['p']['*'].description, item['c']['*'].uuid, item['c']['*'].get_attrs(), item['a']['*'].get_attrs(), [item['a']['*'].get_array(name) for name in item['a']['*'].get_arraynames()], item['a']['*'].uuid, item['g']['*'].uuid, item['g']['*'].name, item['p2c']['label'], item['p2c']['type'], item['c2a']['label'], item['c2a']['type'], item['g']['*'].name, ) for item in qb.dict()]) return hash_ temp_folder = tempfile.mkdtemp() chars = string.ascii_uppercase + string.digits size = 10 groupname = 'test-group' try: nparr = np.random.random((4, 3, 2)) trial_dict = {} trial_dict.update({str(k): np.random.randint(100) for k in range(10)}) trial_dict.update({str(k): np.random.random() for k in range(10, 20)}) trial_dict.update({str(k): bool(np.random.randint(1)) for k in range(20, 30)}) trial_dict.update({str(k): datetime( year=2017, month=np.random.randint(1, 12), day=np.random.randint(1, 28)) for k in range(30, 40)}) trial_dict.update({str(k): ''.join(random.choice(chars) for _ in range(size)) for k in range(20, 30)}) p = ParameterData(dict=trial_dict) p.label = str(datetime.now()) p.description = 'd_' + str(datetime.now()) p.store() c = Calculation() (c._set_attr(str(int(k) + np.random.randint(10)), v) for k, v in trial_dict.items()) c.store() a = ArrayData() a.set_array('array', nparr) a.store() c.add_link_from(p, label='input_parameters', link_type=LinkType.INPUT) a.add_link_from(c, label='output_array', link_type=LinkType.CREATE) g = Group(name='test-group') g.store() g.add_nodes(a) hash_from_dbcontent = get_hash_from_db_content(groupname) for i in range(3): filename = os.path.join(temp_folder, "export-{}.zip".format(i)) g = Group.get_from_string(groupname) export([g] + [n for n in g.nodes], outfile=filename, silent=True) self.clean_db() import_data(filename, silent=True, ignore_unknown_nodes=True) new_hash = get_hash_from_db_content(groupname) self.assertEqual(hash_from_dbcontent, new_hash) finally: shutil.rmtree(temp_folder, ignore_errors=True) class TestComplex(AiidaTestCase): def test_complex_graph_import_export(self): import tempfile import shutil import os from aiida.orm.calculation.job import JobCalculation from aiida.orm.data.folder import FolderData from aiida.orm.data.parameter import ParameterData from aiida.orm.data.remote import RemoteData from aiida.common.links import LinkType from aiida.orm.importexport import export, import_data from aiida.orm.utils import load_node from aiida.common.exceptions import NotExistent temp_folder = tempfile.mkdtemp() try: calc1 = JobCalculation() calc1.set_computer(self.computer) calc1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) calc1.label = "calc1" calc1.store() calc1._set_state(u'RETRIEVING') pd1 = ParameterData() pd1.label = "pd1" pd1.store() pd2 = ParameterData() pd2.label = "pd2" pd2.store() rd1 = RemoteData() rd1.label = "rd1" rd1.set_remote_path("/x/y.py") rd1.set_computer(self.computer) rd1.store() rd1.add_link_from(calc1, link_type=LinkType.CREATE) calc2 = JobCalculation() calc2.set_computer(self.computer) calc2.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) calc2.label = "calc2" calc2.store() calc2.add_link_from(pd1, link_type=LinkType.INPUT) calc2.add_link_from(pd2, link_type=LinkType.INPUT) calc2.add_link_from(rd1, link_type=LinkType.INPUT) calc2._set_state(u'SUBMITTING') fd1 = FolderData() fd1.label = "fd1" fd1.store() fd1.add_link_from(calc2, link_type=LinkType.CREATE) node_uuids_labels = {calc1.uuid: calc1.label, pd1.uuid: pd1.label, pd2.uuid: pd2.label, rd1.uuid: rd1.label, calc2.uuid: calc2.label, fd1.uuid: fd1.label} filename = os.path.join(temp_folder, "export.tar.gz") export([fd1], outfile=filename, silent=True) self.clean_db() import_data(filename, silent=True, ignore_unknown_nodes=True) for uuid, label in node_uuids_labels.items(): try: load_node(uuid) except NotExistent: self.fail("Node with UUID {} and label {} was not " "found.".format(uuid, label)) finally: shutil.rmtree(temp_folder, ignore_errors=True) class TestComputer(AiidaTestCase): def setUp(self): self.clean_db() self.insert_data() def tearDown(self): pass def test_same_computer_import(self): import os import shutil import tempfile from aiida.orm.importexport import export from aiida.orm.querybuilder import QueryBuilder from aiida.orm.computers import Computer from aiida.orm.calculation.job import JobCalculation export_file_tmp_folder = tempfile.mkdtemp() unpack_tmp_folder = tempfile.mkdtemp() try: calc1_label = "calc1" calc1 = JobCalculation() calc1.set_computer(self.computer) calc1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) calc1.label = calc1_label calc1.store() calc1._set_state(u'RETRIEVING') calc2_label = "calc2" calc2 = JobCalculation() calc2.set_computer(self.computer) calc2.set_option('resources', {"num_machines": 2, "num_mpiprocs_per_machine": 2}) calc2.label = calc2_label calc2.store() calc2._set_state(u'RETRIEVING') comp_name = six.text_type(self.computer.name) comp_uuid = six.text_type(self.computer.uuid) filename1 = os.path.join(export_file_tmp_folder, "export1.tar.gz") export([calc1], outfile=filename1, silent=True) filename2 = os.path.join(export_file_tmp_folder, "export2.tar.gz") export([calc2], outfile=filename2, silent=True) self.clean_db() qb = QueryBuilder() qb.append(Computer, project=['*']) self.assertEqual(qb.count(), 0, "There should not be any computers" "in the database at this point.") qb = QueryBuilder() qb.append(JobCalculation, project=['*']) self.assertEqual(qb.count(), 0, "There should not be any " "calculations in the database at " "this point.") import_data(filename1, silent=True) qb = QueryBuilder() qb.append(JobCalculation, project=['label']) self.assertEqual(qb.count(), 1, "Only one calculation should be " "found.") self.assertEqual(six.text_type(qb.first()[0]), calc1_label, "The calculation label is not correct.") qb = QueryBuilder() qb.append(Computer, project=['name', 'uuid', 'id']) self.assertEqual(qb.count(), 1, "Only one computer should be " "found.") self.assertEqual(six.text_type(qb.first()[0]), comp_name, "The computer name is not correct.") self.assertEqual(six.text_type(qb.first()[1]), comp_uuid, "The computer uuid is not correct.") comp_id = qb.first()[2] import_data(filename2, silent=True) qb = QueryBuilder() qb.append(Computer, project=['name', 'uuid', 'id']) self.assertEqual(qb.count(), 1, "Only one computer should be " "found.") self.assertEqual(six.text_type(qb.first()[0]), comp_name, "The computer name is not correct.") self.assertEqual(six.text_type(qb.first()[1]), comp_uuid, "The computer uuid is not correct.") self.assertEqual(qb.first()[2], comp_id, "The computer id is not correct.") qb = QueryBuilder() qb.append(Computer, tag='comp') qb.append(JobCalculation, has_computer='comp', project=['label']) self.assertEqual(qb.count(), 2, "Two calculations should be " "found.") ret_labels = set(_ for [_] in qb.all()) self.assertEqual(ret_labels, set([calc1_label, calc2_label]), "The labels of the calculations are not correct.") finally: shutil.rmtree(export_file_tmp_folder, ignore_errors=True) shutil.rmtree(unpack_tmp_folder, ignore_errors=True) def test_same_computer_different_name_import(self): import os import shutil import tempfile from aiida.orm.importexport import export from aiida.orm.querybuilder import QueryBuilder from aiida.orm.computers import Computer from aiida.orm.calculation.job import JobCalculation export_file_tmp_folder = tempfile.mkdtemp() unpack_tmp_folder = tempfile.mkdtemp() try: calc1_label = "calc1" calc1 = JobCalculation() calc1.set_computer(self.computer) calc1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) calc1.label = calc1_label calc1.store() calc1._set_state(u'RETRIEVING') comp1_name = six.text_type(self.computer.name) filename1 = os.path.join(export_file_tmp_folder, "export1.tar.gz") export([calc1], outfile=filename1, silent=True) self.computer.set_name(comp1_name + "_updated") calc2_label = "calc2" calc2 = JobCalculation() calc2.set_computer(self.computer) calc2.set_option('resources', {"num_machines": 2, "num_mpiprocs_per_machine": 2}) calc2.label = calc2_label calc2.store() calc2._set_state(u'RETRIEVING') filename2 = os.path.join(export_file_tmp_folder, "export2.tar.gz") export([calc2], outfile=filename2, silent=True) self.clean_db() qb = QueryBuilder() qb.append(Computer, project=['*']) self.assertEqual(qb.count(), 0, "There should not be any computers" "in the database at this point.") qb = QueryBuilder() qb.append(JobCalculation, project=['*']) self.assertEqual(qb.count(), 0, "There should not be any " "calculations in the database at " "this point.") import_data(filename1, silent=True) qb = QueryBuilder() qb.append(JobCalculation, project=['label']) self.assertEqual(qb.count(), 1, "Only one calculation should be " "found.") self.assertEqual(six.text_type(qb.first()[0]), calc1_label, "The calculation label is not correct.") qb = QueryBuilder() qb.append(Computer, project=['name', 'uuid', 'id']) self.assertEqual(qb.count(), 1, "Only one computer should be " "found.") self.assertEqual(six.text_type(qb.first()[0]), comp1_name, "The computer name is not correct.") import_data(filename2, silent=True) qb = QueryBuilder() qb.append(Computer, project=['name']) self.assertEqual(qb.count(), 1, "Only one computer should be " "found.") self.assertEqual(six.text_type(qb.first()[0]), comp1_name, "The computer name is not correct.") finally: shutil.rmtree(export_file_tmp_folder, ignore_errors=True) shutil.rmtree(unpack_tmp_folder, ignore_errors=True) def test_different_computer_same_name_import(self): import os import shutil import tempfile from aiida.orm.importexport import export from aiida.orm.querybuilder import QueryBuilder from aiida.orm.computers import Computer from aiida.orm.calculation.job import JobCalculation from aiida.orm.importexport import COMP_DUPL_SUFFIX export_file_tmp_folder = tempfile.mkdtemp() unpack_tmp_folder = tempfile.mkdtemp() try: comp1_name = "localhost_1" self.computer.set_name(comp1_name) calc1_label = "calc1" calc1 = JobCalculation() calc1.set_computer(self.computer) calc1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) calc1.label = calc1_label calc1.store() calc1._set_state(u'RETRIEVING') filename1 = os.path.join(export_file_tmp_folder, "export1.tar.gz") export([calc1], outfile=filename1, silent=True) self.clean_db() self.insert_data() self.computer.set_name(comp1_name) calc2_label = "calc2" calc2 = JobCalculation() calc2.set_computer(self.computer) calc2.set_option('resources', {"num_machines": 2, "num_mpiprocs_per_machine": 2}) calc2.label = calc2_label calc2.store() calc2._set_state(u'RETRIEVING') filename2 = os.path.join(export_file_tmp_folder, "export2.tar.gz") export([calc2], outfile=filename2, silent=True) self.clean_db() self.insert_data() self.computer.set_name(comp1_name) calc3_label = "calc3" calc3 = JobCalculation() calc3.set_computer(self.computer) calc3.set_option('resources', {"num_machines": 2, "num_mpiprocs_per_machine": 2}) calc3.label = calc3_label calc3.store() calc3._set_state(u'RETRIEVING') filename3 = os.path.join(export_file_tmp_folder, "export3.tar.gz") export([calc3], outfile=filename3, silent=True) self.clean_db() qb = QueryBuilder() qb.append(Computer, project=['*']) self.assertEqual(qb.count(), 0, "There should not be any computers" "in the database at this point.") qb = QueryBuilder() qb.append(JobCalculation, project=['*']) self.assertEqual(qb.count(), 0, "There should not be any " "calculations in the database at " "this point.") import_data(filename1, silent=True) import_data(filename2, silent=True) import_data(filename3, silent=True) qb = QueryBuilder() qb.append(JobCalculation, project=['label'], tag='jcalc') qb.append(Computer, project=['name'], computer_of='jcalc') self.assertEqual(qb.count(), 3, "Three combinations expected.") res = qb.all() self.assertIn([calc1_label, comp1_name], res, "Calc-Computer combination not found.") self.assertIn([calc2_label, comp1_name + COMP_DUPL_SUFFIX.format(0)], res, "Calc-Computer combination not found.") self.assertIn([calc3_label, comp1_name + COMP_DUPL_SUFFIX.format(1)], res, "Calc-Computer combination not found.") finally: shutil.rmtree(export_file_tmp_folder, ignore_errors=True) shutil.rmtree(unpack_tmp_folder, ignore_errors=True) def test_correct_import_of_computer_json_params(self): import os import shutil import tempfile from aiida.orm.importexport import export from aiida.orm.querybuilder import QueryBuilder from aiida.orm.computers import Computer from aiida.orm.calculation.job import JobCalculation export_file_tmp_folder = tempfile.mkdtemp() unpack_tmp_folder = tempfile.mkdtemp() try: comp1_name = "localhost_1" comp1_metadata = { u'workdir': u'/tmp/aiida' } comp1_transport_params = { u'key1': u'value1', u'key2': 2 } self.computer.set_name(comp1_name) self.computer._set_metadata(comp1_metadata) self.computer.set_transport_params(comp1_transport_params) calc1_label = "calc1" calc1 = JobCalculation() calc1.set_computer(self.computer) calc1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) calc1.label = calc1_label calc1.store() calc1._set_state(u'RETRIEVING') filename1 = os.path.join(export_file_tmp_folder, "export1.tar.gz") export([calc1], outfile=filename1, silent=True) self.clean_db() import_data(filename1, silent=True) qb = QueryBuilder() qb.append(Computer, project=['transport_params', '_metadata'], tag="comp") self.assertEqual(qb.count(), 1, "Expected only one computer") res = qb.dict()[0] self.assertEqual(res['comp']['transport_params'], comp1_transport_params, "Not the expected transport parameters " "were found") self.assertEqual(res['comp']['_metadata'], comp1_metadata, "Not the expected metadata were found") finally: shutil.rmtree(export_file_tmp_folder, ignore_errors=True) shutil.rmtree(unpack_tmp_folder, ignore_errors=True) def test_import_of_django_sqla_export_file(self): from aiida.backends.tests.utils.fixtures import import_archive_fixture from aiida.orm.querybuilder import QueryBuilder from aiida.orm.computers import Computer for archive in ['export/compare/django.aiida', 'export/compare/sqlalchemy.aiida']: self.clean_db() import_archive_fixture(archive) comp1_metadata = { u'workdir': u'/tmp/aiida' } comp1_transport_params = { u'key1': u'value1', u'key2': 2 } qb = QueryBuilder() qb.append(Computer, project=['transport_params', '_metadata'], tag="comp") self.assertEqual(qb.count(), 1, "Expected only one computer") res = qb.dict()[0] self.assertEqual(res['comp']['transport_params'], comp1_transport_params) self.assertEqual(res['comp']['_metadata'], comp1_metadata) class TestLinks(AiidaTestCase): def setUp(self): self.clean_db() self.insert_data() def tearDown(self): pass def get_all_node_links(self): from aiida.orm import load_node, Node from aiida.orm.querybuilder import QueryBuilder qb = QueryBuilder() qb.append(Node, project='uuid', tag='input') qb.append(Node, project='uuid', tag='output', edge_project=['label', 'type'], output_of='input') return qb.all() def test_input_and_create_links(self): import os, shutil, tempfile from aiida.orm.data.int import Int from aiida.orm.importexport import export from aiida.orm.calculation.work import WorkCalculation from aiida.common.links import LinkType tmp_folder = tempfile.mkdtemp() try: node_work = WorkCalculation().store() node_input = Int(1).store() node_output = Int(2).store() node_work.add_link_from(node_input, 'input', link_type=LinkType.INPUT) node_output.add_link_from(node_work, 'output', link_type=LinkType.CREATE) export_links = self.get_all_node_links() export_file = os.path.join(tmp_folder, 'export.tar.gz') export([node_output], outfile=export_file, silent=True) self.clean_db() self.insert_data() import_data(export_file, silent=True) import_links = self.get_all_node_links() export_set = [tuple(_) for _ in export_links] import_set = [tuple(_) for _ in import_links] self.assertEquals(set(export_set), set(import_set)) finally: shutil.rmtree(tmp_folder, ignore_errors=True) def construct_complex_graph(self, export_combination=0): from aiida.orm.data.base import Int from aiida.orm.calculation.job import JobCalculation from aiida.orm.calculation.work import WorkCalculation from aiida.common.datastructures import calc_states from aiida.common.links import LinkType if export_combination < 0 or export_combination > 8: return None d1 = Int(1).store() d2 = Int(1).store() wc1 = WorkCalculation().store() wc2 = WorkCalculation().store() pw1 = JobCalculation() pw1.set_computer(self.computer) pw1.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) pw1.store() d3 = Int(1).store() d4 = Int(1).store() pw2 = JobCalculation() pw2.set_computer(self.computer) pw2.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) pw2.store() d5 = Int(1).store() d6 = Int(1).store() wc1.add_link_from(d1, 'input1', link_type=LinkType.INPUT) wc1.add_link_from(d2, 'input2', link_type=LinkType.INPUT) wc2.add_link_from(d1, 'input', link_type=LinkType.INPUT) wc2.add_link_from(wc1, 'call', link_type=LinkType.CALL) pw1.add_link_from(d1, 'input', link_type=LinkType.INPUT) pw1.add_link_from(wc2, 'call', link_type=LinkType.CALL) pw1._set_state(calc_states.PARSING) d3.add_link_from(pw1, 'create', link_type=LinkType.CREATE) d3.add_link_from(wc2, 'return', link_type=LinkType.RETURN) d4.add_link_from(pw1, 'create', link_type=LinkType.CREATE) d4.add_link_from(wc2, 'return', link_type=LinkType.RETURN) pw2.add_link_from(d4, 'input', link_type=LinkType.INPUT) pw2._set_state(calc_states.PARSING) d5.add_link_from(pw2, 'create', link_type=LinkType.CREATE) d6.add_link_from(pw2, 'create', link_type=LinkType.CREATE) graph_nodes = [d1, d2, d3, d4, d5, d6, pw1, pw2, wc1, wc2] export_list = [ (wc1, [d1, d2, d3, d4, pw1, wc1, wc2]), (wc2, [d1, d3, d4, pw1, wc2]), (d3, [d1, d3, d4, pw1]), (d4, [d1, d3, d4, pw1]), (d5, [d1, d3, d4, d5, d6, pw1, pw2]), (d6, [d1, d3, d4, d5, d6, pw1, pw2]), (pw2, [d1, d3, d4, d5, d6, pw1, pw2]), (d1, [d1]), (d2, [d2]) ] return graph_nodes, export_list[export_combination] def test_data_create_reversed_false(self): import os import shutil import tempfile from aiida.common.datastructures import calc_states from aiida.orm import Data, Group from aiida.orm.data.base import Int from aiida.orm.calculation.job import JobCalculation from aiida.orm.importexport import export from aiida.common.links import LinkType from aiida.orm.querybuilder import QueryBuilder tmp_folder = tempfile.mkdtemp() try: data_input = Int(1).store() data_output = Int(2).store() calc = JobCalculation() calc.set_computer(self.computer) calc.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) calc.store() calc.add_link_from(data_input, 'input', link_type=LinkType.INPUT) calc._set_state(calc_states.PARSING) data_output.add_link_from(calc, 'create', link_type=LinkType.CREATE) group = Group.create(name='test_group') group.add_nodes(data_output) export_file = os.path.join(tmp_folder, 'export.tar.gz') export([group], outfile=export_file, silent=True, create_reversed=False) self.clean_db() self.insert_data() import_data(export_file, silent=True) builder = QueryBuilder() builder.append(Data) self.assertEqual(builder.count(), 1, 'Expected a single Data node but got {}'.format(builder.count())) self.assertEqual(builder.all()[0][0].uuid, data_output.uuid) builder = QueryBuilder() builder.append(JobCalculation) self.assertEqual(builder.count(), 0, 'Expected no Calculation nodes') finally: shutil.rmtree(tmp_folder, ignore_errors=True) def test_complex_workflow_graph_links(self): import os, shutil, tempfile from aiida.orm import Node from aiida.orm.importexport import export from aiida.common.links import LinkType from aiida.orm.querybuilder import QueryBuilder tmp_folder = tempfile.mkdtemp() try: graph_nodes, _ = self.construct_complex_graph() qb = QueryBuilder() qb.append(Node, project='uuid') qb.append(Node, project='uuid', edge_project=['label', 'type'], edge_filters={'type': {'in': (LinkType.INPUT.value, LinkType.CREATE.value, LinkType.RETURN.value, LinkType.CALL.value)}}) export_links = qb.all() export_file = os.path.join(tmp_folder, 'export.tar.gz') export(graph_nodes, outfile=export_file, silent=True) self.clean_db() self.insert_data() import_data(export_file, silent=True) import_links = self.get_all_node_links() export_set = [tuple(_) for _ in export_links] import_set = [tuple(_) for _ in import_links] self.assertEquals(set(export_set), set(import_set)) finally: shutil.rmtree(tmp_folder, ignore_errors=True) def test_complex_workflow_graph_export_set_expansion(self): import os, shutil, tempfile from aiida.orm.importexport import export from aiida.orm.querybuilder import QueryBuilder from aiida.orm import Node for export_conf in range(0, 8): graph_nodes, (export_node, export_target) = ( self.construct_complex_graph(export_conf)) tmp_folder = tempfile.mkdtemp() try: export_file = os.path.join(tmp_folder, 'export.tar.gz') export([export_node], outfile=export_file, silent=True) export_node_str = str(export_node) self.clean_db() self.insert_data() import_data(export_file, silent=True) qb = QueryBuilder() qb.append(Node, project='uuid') imported_node_uuids = set(str(_[0]) for _ in qb.all()) export_target_uuids = set(str(_.uuid) for _ in export_target) from aiida.orm.utils import load_node self.assertEquals( export_target_uuids, imported_node_uuids, "Problem in comparison of export node: " + str(export_node_str) + "\n" + "Expected set: " + str(export_target_uuids) + "\n" + "Imported set: " + str(imported_node_uuids) + "\n" + "Difference: " + str([load_node(_) for _ in export_target_uuids.symmetric_difference( imported_node_uuids)]) ) finally: shutil.rmtree(tmp_folder, ignore_errors=True) def test_recursive_export_input_and_create_links_proper(self): import os, shutil, tempfile from aiida.orm import Node from aiida.orm.data.base import Int from aiida.orm.importexport import export from aiida.orm.calculation.inline import InlineCalculation from aiida.orm.calculation.work import WorkCalculation from aiida.common.links import LinkType from aiida.orm.querybuilder import QueryBuilder tmp_folder = tempfile.mkdtemp() try: wc2 = WorkCalculation().store() wc1 = WorkCalculation().store() c1 = InlineCalculation().store() ni1 = Int(1).store() ni2 = Int(2).store() no1 = Int(1).store() no2 = Int(2).store() wc1.add_link_from(wc2, 'call', link_type=LinkType.CALL) c1.add_link_from(wc1, 'call', link_type=LinkType.CALL) wc1.add_link_from(ni1, 'ni1-to-wc1', link_type=LinkType.INPUT) c1.add_link_from(ni1, 'ni1-to-c1', link_type=LinkType.INPUT) wc1.add_link_from(ni2, 'ni2-to-wc1', link_type=LinkType.INPUT) c1.add_link_from(ni2, 'ni2-to-c1', link_type=LinkType.INPUT) no1.add_link_from(wc1, 'output', link_type=LinkType.RETURN) no1.add_link_from(c1, 'output', link_type=LinkType.CREATE) no2.add_link_from(wc1, 'output', link_type=LinkType.RETURN) no2.add_link_from(c1, 'output', link_type=LinkType.CREATE) qb = QueryBuilder() qb.append(Node, project='uuid') qb.append(Node, project='uuid', edge_project=['label', 'type'], edge_filters={'type': {'in': (LinkType.INPUT.value, LinkType.CREATE.value, LinkType.RETURN.value, LinkType.CALL.value)}}) export_links = qb.all() export_file = os.path.join(tmp_folder, 'export.tar.gz') export([wc2], outfile=export_file, silent=True) self.clean_db() self.insert_data() import_data(export_file, silent=True) import_links = self.get_all_node_links() export_set = [tuple(_) for _ in export_links] import_set = [tuple(_) for _ in import_links] self.assertEquals(set(export_set), set(import_set)) finally: shutil.rmtree(tmp_folder, ignore_errors=True) def test_links_for_workflows(self): import os, shutil, tempfile from aiida.orm.data.base import Int from aiida.orm.importexport import export from aiida.orm.calculation.work import WorkCalculation from aiida.common.links import LinkType tmp_folder = tempfile.mkdtemp() try: w1 = WorkCalculation().store() w2 = WorkCalculation().store() i1 = Int(1).store() o1 = Int(2).store() w1.add_link_from(i1, 'input-i1', link_type=LinkType.INPUT) w1.add_link_from(w2, 'call', link_type=LinkType.CALL) o1.add_link_from(w1, 'output', link_type=LinkType.CREATE) o1.add_link_from(w1, 'return', link_type=LinkType.RETURN) links_wanted = [l for l in self.get_all_node_links() if l[3] in (LinkType.CREATE.value, LinkType.INPUT.value, LinkType.RETURN.value)] export_file_1 = os.path.join(tmp_folder, 'export-1.tar.gz') export_file_2 = os.path.join(tmp_folder, 'export-2.tar.gz') export([o1], outfile=export_file_1, silent=True) export([w1], outfile=export_file_2, silent=True) self.clean_db() self.insert_data() import_data(export_file_1, silent=True) links_in_db = self.get_all_node_links() self.assertEquals(sorted(links_wanted), sorted(links_in_db)) self.clean_db() self.insert_data() import_data(export_file_2, silent=True) links_in_db = self.get_all_node_links() self.assertEquals(sorted(links_wanted), sorted(links_in_db)) finally: shutil.rmtree(tmp_folder, ignore_errors=True) def test_double_return_links_for_workflows(self): import os, shutil, tempfile from aiida.orm.data.base import Int from aiida.orm.importexport import export from aiida.orm.calculation.work import WorkCalculation from aiida.common.links import LinkType from aiida.orm.querybuilder import QueryBuilder from aiida.orm.node import Node tmp_folder = tempfile.mkdtemp() try: w1 = WorkCalculation().store() w2 = WorkCalculation().store() i1 = Int(1).store() o1 = Int(2).store() w1.add_link_from(i1, 'input-i1', link_type=LinkType.INPUT) w1.add_link_from(w2, 'call', link_type=LinkType.CALL) o1.add_link_from(w1, 'output', link_type=LinkType.CREATE) o1.add_link_from(w1, 'return', link_type=LinkType.RETURN) o1.add_link_from(w2, 'return', link_type=LinkType.RETURN) uuids_wanted = set(_.uuid for _ in (w1, o1, i1, w2)) links_wanted = [l for l in self.get_all_node_links() if l[3] in ( 'createlink', 'inputlink', 'returnlink', 'calllink')] export_file = os.path.join(tmp_folder, 'export.tar.gz') export([o1, w1, w2, i1], outfile=export_file, silent=True) self.clean_db() self.insert_data() import_data(export_file, silent=True) uuids_in_db = [str(uuid) for [uuid] in QueryBuilder().append(Node, project='uuid').all()] self.assertEquals(sorted(uuids_wanted), sorted(uuids_in_db)) links_in_db = self.get_all_node_links() self.assertEquals(sorted(links_wanted), sorted(links_in_db)) finally: shutil.rmtree(tmp_folder, ignore_errors=True) def test_that_solo_code_is_exported_correctly(self): import os, shutil, tempfile from aiida.orm.utils import load_node from aiida.orm.importexport import export from aiida.orm.code import Code tmp_folder = tempfile.mkdtemp() try: code_label = 'test_code1' code = Code() code.set_remote_computer_exec((self.computer, '/bin/true')) code.label = code_label code.store() code_uuid = code.uuid export_file = os.path.join(tmp_folder, 'export.tar.gz') export([code], outfile=export_file, silent=True) self.clean_db() self.insert_data() import_data(export_file, silent=True) self.assertEquals(load_node(code_uuid).label, code_label) finally: shutil.rmtree(tmp_folder, ignore_errors=True) def test_that_input_code_is_exported_correctly(self): import os, shutil, tempfile from aiida.orm.utils import load_node from aiida.orm.importexport import export from aiida.common.links import LinkType from aiida.orm.calculation.job import JobCalculation from aiida.orm.code import Code from aiida.orm.querybuilder import QueryBuilder tmp_folder = tempfile.mkdtemp() try: code_label = 'test_code1' code = Code() code.set_remote_computer_exec((self.computer, '/bin/true')) code.label = code_label code.store() code_uuid = code.uuid jc = JobCalculation() jc.set_computer(self.computer) jc.set_option('resources', {"num_machines": 1, "num_mpiprocs_per_machine": 1}) jc.store() jc.add_link_from(code, 'code', link_type=LinkType.INPUT) export_file = os.path.join(tmp_folder, 'export.tar.gz') export([jc], outfile=export_file, silent=True) self.clean_db() self.insert_data() import_data(export_file, silent=True) self.assertEquals(load_node(code_uuid).label, code_label) qb = QueryBuilder() qb.append(Code, project='uuid') qb.append(JobCalculation, project='uuid', edge_project=['label', 'type'], edge_filters={'type': {'==': LinkType.INPUT.value}}) self.assertEquals(qb.count(), 1, "Expected to find one and only one link from " "code to the calculation node. {} found." .format(qb.count())) finally: shutil.rmtree(tmp_folder, ignore_errors=True)

true

f704d12c29a0d4090d125d43a95bf1b2c7c9f9ab

1,372

py

Python

mvfy/visual/utils/streamer.py

erwingforerocastro/mvfy_visual_py

8740f21ffa68d0cfced0d0684251b2198488cb0e

[ "MIT" ]

null

mvfy/visual/utils/streamer.py

erwingforerocastro/mvfy_visual_py

8740f21ffa68d0cfced0d0684251b2198488cb0e

[ "MIT" ]

null

mvfy/visual/utils/streamer.py

erwingforerocastro/mvfy_visual_py

8740f21ffa68d0cfced0d0684251b2198488cb0e

[ "MIT" ]

null

import asyncio import base64 import threading import cv2 import numpy as np from flask_socketio import SocketIO, emit from flask import Flask, render_template import multiprocessing class Streamer(): def __init__(self) -> None: """Constructor """ @staticmethod async def stream_socket( url_server: str, app: 'Flask' = None, socket_options: 'dict' = None, socket_msg: 'str' = "mvfy_visual_img", )-> 'function': app = Flask(__name__) if app is None else app socketio = SocketIO(app, **socket_options) threading.Thread(target=lambda: socketio.run(url_server)).run() async def wraper_function(img, extension: str = ".jpg", size: tuple = (1920, 1080)): if size is not None: frame = cv2.resize(img, size) _, buffer = cv2.imencode(extension, frame, [cv2.IMWRITE_JPEG_QUALITY, 80]) data = base64.b64encode(buffer) socketio.emit(socket_msg, { "data": data }) return wraper_function @staticmethod async def stream_local( img: np.array, size: tuple = (1920, 1080), title: str = "title" ) -> None: if size is not None: img = cv2.resize(img, size) cv2.imshow(title, img)

25.886792

92

0.573615

import asyncio import base64 import threading import cv2 import numpy as np from flask_socketio import SocketIO, emit from flask import Flask, render_template import multiprocessing class Streamer(): def __init__(self) -> None: @staticmethod async def stream_socket( url_server: str, app: 'Flask' = None, socket_options: 'dict' = None, socket_msg: 'str' = "mvfy_visual_img", )-> 'function': app = Flask(__name__) if app is None else app socketio = SocketIO(app, **socket_options) threading.Thread(target=lambda: socketio.run(url_server)).run() async def wraper_function(img, extension: str = ".jpg", size: tuple = (1920, 1080)): if size is not None: frame = cv2.resize(img, size) _, buffer = cv2.imencode(extension, frame, [cv2.IMWRITE_JPEG_QUALITY, 80]) data = base64.b64encode(buffer) socketio.emit(socket_msg, { "data": data }) return wraper_function @staticmethod async def stream_local( img: np.array, size: tuple = (1920, 1080), title: str = "title" ) -> None: if size is not None: img = cv2.resize(img, size) cv2.imshow(title, img)

true

f704d16684d90b723369d286ddc555a9a4d93ac8

4,271

py

Python

flask_tutorial/marshmallow_demo/flask_exmaple.py

ftconan/python3

eb63ba33960072f792ecce6db809866b38c402f8

[ "MIT" ]

1

2018-12-19T22:07:56.000Z

marshmallow_demo/flask_exmaple.py

ftconan/flask-tutorial

d5164c93b5e6a6e3d2b8980e4b846adb7cb21aee

[ "MIT" ]

12

2020-03-14T05:32:26.000Z

2022-03-12T00:08:49.000Z

marshmallow_demo/flask_exmaple.py

ftconan/flask-tutorial

d5164c93b5e6a6e3d2b8980e4b846adb7cb21aee

[ "MIT" ]

1

2018-12-19T22:08:00.000Z

# coding=utf-8 """ @author: magician @date: 2018/9/14 """ import datetime from flask_sqlalchemy import SQLAlchemy from flask import Flask, jsonify, request from sqlalchemy.exc import IntegrityError from marshmallow import Schema, fields, ValidationError, pre_load app = Flask(__name__) app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite://' app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = True db = SQLAlchemy(app) # MODELS class Author(db.Model): id = db.Column(db.Integer, primary_key=True) first = db.Column(db.String(80)) last = db.Column(db.String(80)) class Quote(db.Model): id = db.Column(db.Integer, primary_key=True) content = db.Column(db.String, nullable=False) author_id = db.Column(db.Integer, db.ForeignKey('author.id')) author = db.relationship( 'Author', backref=db.backref('quotes', lazy='dynamic'), ) posted_at = db.Column(db.DateTime) # SCHEMAS class AuthorSchema(Schema): id = fields.Int(dump_only=True) first = fields.Str() last = fields.Str() formatted_name = fields.Method('format_name', dump_only=True) def format_name(self, author): return '{}, {}'.format(author.last, author.first) # Custom validator def must_not_be_blank(data): if not data: raise ValidationError('Data not provided.') class QuoteSchema(Schema): id = fields.Int(dump_only=True) author = fields.Nested(AuthorSchema, validate=must_not_be_blank) content = fields.Str(required=True, validate=must_not_be_blank) posted_at = fields.DateTime(dump_only=True) # Allow client to pass author's full name in request body # e.g. {"author': 'Tim Peters"} rather than {"first": "Tim", "last": "Peters"} @pre_load def process_author(self, data): author_name = data.get('author') if author_name: first, last = author_name.split(' ') author_dict = dict(first=first, last=last) else: author_dict = {} data['author'] = author_dict return data author_schema = AuthorSchema() authors_schema = AuthorSchema(many=True) quote_schema = QuoteSchema() quotes_schema = QuoteSchema(many=True, only=('id', 'content')) # API @app.route('/authors') def get_authors(): authors = Author.query.all() # Serialize the queryset result = authors_schema.dump(authors) return jsonify({'authors': result}) @app.route('/authors/<int:pk>') def get_author(pk): try: author = Author.query.get(pk) except IntegrityError: return jsonify({'message': 'Author could not be found.'}), 400 author_result = author_schema.dump(author) quotes_result = quotes_schema.dump(author.quotes.all()) return jsonify({'author': author_result, 'quotes': quotes_result}) @app.route('/quotes/', methods=['GET']) def get_quotes(): quotes = Quote.query.all() result = quotes_schema.dump(quotes, many=True) return jsonify({'quotes': result}) @app.route('/quotes/<int:pk>') def get_quote(pk): try: quote = Quote.query.get(pk) except IntegrityError: return jsonify({'message': 'Quote could not be found.'}), 400 result = quote_schema.dump(quote) return jsonify({'quote': result}) @app.route('/quotes/', methods=['POST']) def new_quote(): json_data = request.get_json() if not json_data: return jsonify({'message': 'No input data provided'}), 400 # Validate and deserialize input try: data = quote_schema.load(json_data) except ValidationError as err: return jsonify(err.messages), 422 first, last = data['author']['first'], data['author']['last'] author = Author.query.filter_by(first=first, last=last).first() if author is None: # Create a new author author = Author(first=first, last=last) db.session.add(author) # Create new quote quote = Quote( content=data['content'], author=author, posted_at=datetime.datetime.utcnow(), ) db.session.add(quote) db.session.commit() result = quote_schema.dump(Quote.query.get(quote.id)) return jsonify({ 'message': 'Created new quote.', 'quote': result, }) if __name__ == '__main__': db.create_all() app.run(debug=True, port=5000)

27.733766

82

0.661203

import datetime from flask_sqlalchemy import SQLAlchemy from flask import Flask, jsonify, request from sqlalchemy.exc import IntegrityError from marshmallow import Schema, fields, ValidationError, pre_load app = Flask(__name__) app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite://' app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = True db = SQLAlchemy(app) class Author(db.Model): id = db.Column(db.Integer, primary_key=True) first = db.Column(db.String(80)) last = db.Column(db.String(80)) class Quote(db.Model): id = db.Column(db.Integer, primary_key=True) content = db.Column(db.String, nullable=False) author_id = db.Column(db.Integer, db.ForeignKey('author.id')) author = db.relationship( 'Author', backref=db.backref('quotes', lazy='dynamic'), ) posted_at = db.Column(db.DateTime) class AuthorSchema(Schema): id = fields.Int(dump_only=True) first = fields.Str() last = fields.Str() formatted_name = fields.Method('format_name', dump_only=True) def format_name(self, author): return '{}, {}'.format(author.last, author.first) def must_not_be_blank(data): if not data: raise ValidationError('Data not provided.') class QuoteSchema(Schema): id = fields.Int(dump_only=True) author = fields.Nested(AuthorSchema, validate=must_not_be_blank) content = fields.Str(required=True, validate=must_not_be_blank) posted_at = fields.DateTime(dump_only=True) # e.g. {"author': 'Tim Peters"} rather than {"first": "Tim", "last": "Peters"} @pre_load def process_author(self, data): author_name = data.get('author') if author_name: first, last = author_name.split(' ') author_dict = dict(first=first, last=last) else: author_dict = {} data['author'] = author_dict return data author_schema = AuthorSchema() authors_schema = AuthorSchema(many=True) quote_schema = QuoteSchema() quotes_schema = QuoteSchema(many=True, only=('id', 'content')) # API @app.route('/authors') def get_authors(): authors = Author.query.all() # Serialize the queryset result = authors_schema.dump(authors) return jsonify({'authors': result}) @app.route('/authors/<int:pk>') def get_author(pk): try: author = Author.query.get(pk) except IntegrityError: return jsonify({'message': 'Author could not be found.'}), 400 author_result = author_schema.dump(author) quotes_result = quotes_schema.dump(author.quotes.all()) return jsonify({'author': author_result, 'quotes': quotes_result}) @app.route('/quotes/', methods=['GET']) def get_quotes(): quotes = Quote.query.all() result = quotes_schema.dump(quotes, many=True) return jsonify({'quotes': result}) @app.route('/quotes/<int:pk>') def get_quote(pk): try: quote = Quote.query.get(pk) except IntegrityError: return jsonify({'message': 'Quote could not be found.'}), 400 result = quote_schema.dump(quote) return jsonify({'quote': result}) @app.route('/quotes/', methods=['POST']) def new_quote(): json_data = request.get_json() if not json_data: return jsonify({'message': 'No input data provided'}), 400 # Validate and deserialize input try: data = quote_schema.load(json_data) except ValidationError as err: return jsonify(err.messages), 422 first, last = data['author']['first'], data['author']['last'] author = Author.query.filter_by(first=first, last=last).first() if author is None: # Create a new author author = Author(first=first, last=last) db.session.add(author) # Create new quote quote = Quote( content=data['content'], author=author, posted_at=datetime.datetime.utcnow(), ) db.session.add(quote) db.session.commit() result = quote_schema.dump(Quote.query.get(quote.id)) return jsonify({ 'message': 'Created new quote.', 'quote': result, }) if __name__ == '__main__': db.create_all() app.run(debug=True, port=5000)

true

f704d2308a4a0e9874c346c623e3850cac9abfa5

6,064

py

Python

frappe/tests/test_twofactor.py

snehapatil1/frappe

dd2c33e34ad120e6305a2fa230a72d23a7a03e98

[ "MIT" ]

1

2020-12-07T22:35:21.000Z

frappe/tests/test_twofactor.py

snehapatil1/frappe

dd2c33e34ad120e6305a2fa230a72d23a7a03e98

[ "MIT" ]

11

2018-04-01T18:36:05.000Z

2018-10-04T07:56:07.000Z

frappe/tests/test_twofactor.py

snehapatil1/frappe

dd2c33e34ad120e6305a2fa230a72d23a7a03e98

[ "MIT" ]

3

2018-01-16T17:59:55.000Z

2019-09-24T16:02:10.000Z

# Copyright (c) 2017, Frappe Technologies Pvt. Ltd. and Contributors # MIT License. See license.txt from __future__ import unicode_literals import unittest, frappe, pyotp from werkzeug.wrappers import Request from werkzeug.test import EnvironBuilder from frappe.auth import HTTPRequest from frappe.utils import cint from frappe.twofactor import (should_run_2fa, authenticate_for_2factor, get_cached_user_pass, two_factor_is_enabled_for_, confirm_otp_token, get_otpsecret_for_, get_verification_obj, render_string_template, two_factor_is_enabled) import time class TestTwoFactor(unittest.TestCase): def setUp(self): self.http_requests = create_http_request() self.login_manager = frappe.local.login_manager self.user = self.login_manager.user def tearDown(self): frappe.local.response['verification'] = None frappe.local.response['tmp_id'] = None disable_2fa() frappe.clear_cache(user=self.user) def test_should_run_2fa(self): '''Should return true if enabled.''' toggle_2fa_all_role(state=True) self.assertTrue(should_run_2fa(self.user)) toggle_2fa_all_role(state=False) self.assertFalse(should_run_2fa(self.user)) def test_get_cached_user_pass(self): '''Cached data should not contain user and pass before 2fa.''' user,pwd = get_cached_user_pass() self.assertTrue(all([not user, not pwd])) def test_authenticate_for_2factor(self): '''Verification obj and tmp_id should be set in frappe.local.''' authenticate_for_2factor(self.user) verification_obj = frappe.local.response['verification'] tmp_id = frappe.local.response['tmp_id'] self.assertTrue(verification_obj) self.assertTrue(tmp_id) for k in ['_usr','_pwd','_otp_secret']: self.assertTrue(frappe.cache().get('{0}{1}'.format(tmp_id,k)), '{} not available'.format(k)) def test_two_factor_is_enabled(self): ''' 1. Should return true, if enabled and not bypass_2fa_for_retricted_ip_users 2. Should return false, if not enabled 3. Should return true, if enabled and bypass_2fa_for_retricted_ip_users and not user.restricted_ip 4. Should return false, if enabled and bypass_2fa_for_retricted_ip_users and user.restricted_ip ''' #Scenario 1 disable_2fa() self.assertFalse(two_factor_is_enabled(self.user)) #Scenario 2 enable_2fa() self.assertTrue(two_factor_is_enabled(self.user)) #Scenario 3 enable_2fa() user = frappe.get_doc('User', self.user) user.restrict_ip = frappe.local.request_ip user.save() self.assertTrue(two_factor_is_enabled(self.user)) #Scenario 4 user = frappe.get_doc('User', self.user) user.restrict_ip = "" user.save() enable_2fa(1) self.assertTrue(two_factor_is_enabled(self.user)) #Scenario 5 user = frappe.get_doc('User', self.user) user.restrict_ip = frappe.local.request_ip user.save() enable_2fa(1) self.assertFalse(two_factor_is_enabled(self.user)) def test_two_factor_is_enabled_for_user(self): '''Should return true if enabled for user.''' toggle_2fa_all_role(state=True) self.assertTrue(two_factor_is_enabled_for_(self.user)) self.assertFalse(two_factor_is_enabled_for_("Administrator")) toggle_2fa_all_role(state=False) self.assertFalse(two_factor_is_enabled_for_(self.user)) def test_get_otpsecret_for_user(self): '''OTP secret should be set for user.''' self.assertTrue(get_otpsecret_for_(self.user)) self.assertTrue(frappe.db.get_default(self.user + '_otpsecret')) def test_confirm_otp_token(self): '''Ensure otp is confirmed''' authenticate_for_2factor(self.user) tmp_id = frappe.local.response['tmp_id'] otp = 'wrongotp' with self.assertRaises(frappe.AuthenticationError): confirm_otp_token(self.login_manager,otp=otp,tmp_id=tmp_id) otp = get_otp(self.user) self.assertTrue(confirm_otp_token(self.login_manager,otp=otp,tmp_id=tmp_id)) if frappe.flags.tests_verbose: print('Sleeping for 30secs to confirm token expires..') time.sleep(30) with self.assertRaises(frappe.AuthenticationError): confirm_otp_token(self.login_manager,otp=otp,tmp_id=tmp_id) def test_get_verification_obj(self): '''Confirm verification object is returned.''' otp_secret = get_otpsecret_for_(self.user) token = int(pyotp.TOTP(otp_secret).now()) self.assertTrue(get_verification_obj(self.user,token,otp_secret)) def test_render_string_template(self): '''String template renders as expected with variables.''' args = {'issuer_name':'Frappe Technologies'} _str = 'Verification Code from {{issuer_name}}' _str = render_string_template(_str,args) self.assertEqual(_str,'Verification Code from Frappe Technologies') def set_request(**kwargs): builder = EnvironBuilder(**kwargs) frappe.local.request = Request(builder.get_environ()) def create_http_request(): '''Get http request object.''' set_request(method='POST', path='login') enable_2fa() frappe.form_dict['usr'] = 'test@erpnext.com' frappe.form_dict['pwd'] = 'test' frappe.local.form_dict['cmd'] = 'login' http_requests = HTTPRequest() return http_requests def enable_2fa(bypass_two_factor_auth=0): '''Enable Two factor in system settings.''' system_settings = frappe.get_doc('System Settings') system_settings.enable_two_factor_auth = 1 system_settings.bypass_2fa_for_retricted_ip_users = cint(bypass_two_factor_auth) system_settings.two_factor_method = 'OTP App' system_settings.save(ignore_permissions=True) frappe.db.commit() def disable_2fa(): system_settings = frappe.get_doc('System Settings') system_settings.enable_two_factor_auth = 0 system_settings.bypass_2fa_for_retricted_ip_users = 0 system_settings.save(ignore_permissions=True) frappe.db.commit() def toggle_2fa_all_role(state=None): '''Enable or disable 2fa for 'all' role on the system.''' all_role = frappe.get_doc('Role','All') if state == None: state = False if all_role.two_factor_auth == True else False if state not in [True,False]:return all_role.two_factor_auth = state all_role.save(ignore_permissions=True) frappe.db.commit() def get_otp(user): otp_secret = get_otpsecret_for_(user) otp = pyotp.TOTP(otp_secret) return otp.now()

35.255814

100

0.774571

from __future__ import unicode_literals import unittest, frappe, pyotp from werkzeug.wrappers import Request from werkzeug.test import EnvironBuilder from frappe.auth import HTTPRequest from frappe.utils import cint from frappe.twofactor import (should_run_2fa, authenticate_for_2factor, get_cached_user_pass, two_factor_is_enabled_for_, confirm_otp_token, get_otpsecret_for_, get_verification_obj, render_string_template, two_factor_is_enabled) import time class TestTwoFactor(unittest.TestCase): def setUp(self): self.http_requests = create_http_request() self.login_manager = frappe.local.login_manager self.user = self.login_manager.user def tearDown(self): frappe.local.response['verification'] = None frappe.local.response['tmp_id'] = None disable_2fa() frappe.clear_cache(user=self.user) def test_should_run_2fa(self): toggle_2fa_all_role(state=True) self.assertTrue(should_run_2fa(self.user)) toggle_2fa_all_role(state=False) self.assertFalse(should_run_2fa(self.user)) def test_get_cached_user_pass(self): user,pwd = get_cached_user_pass() self.assertTrue(all([not user, not pwd])) def test_authenticate_for_2factor(self): authenticate_for_2factor(self.user) verification_obj = frappe.local.response['verification'] tmp_id = frappe.local.response['tmp_id'] self.assertTrue(verification_obj) self.assertTrue(tmp_id) for k in ['_usr','_pwd','_otp_secret']: self.assertTrue(frappe.cache().get('{0}{1}'.format(tmp_id,k)), '{} not available'.format(k)) def test_two_factor_is_enabled(self): disable_2fa() self.assertFalse(two_factor_is_enabled(self.user)) enable_2fa() self.assertTrue(two_factor_is_enabled(self.user)) enable_2fa() user = frappe.get_doc('User', self.user) user.restrict_ip = frappe.local.request_ip user.save() self.assertTrue(two_factor_is_enabled(self.user)) user = frappe.get_doc('User', self.user) user.restrict_ip = "" user.save() enable_2fa(1) self.assertTrue(two_factor_is_enabled(self.user)) user = frappe.get_doc('User', self.user) user.restrict_ip = frappe.local.request_ip user.save() enable_2fa(1) self.assertFalse(two_factor_is_enabled(self.user)) def test_two_factor_is_enabled_for_user(self): toggle_2fa_all_role(state=True) self.assertTrue(two_factor_is_enabled_for_(self.user)) self.assertFalse(two_factor_is_enabled_for_("Administrator")) toggle_2fa_all_role(state=False) self.assertFalse(two_factor_is_enabled_for_(self.user)) def test_get_otpsecret_for_user(self): self.assertTrue(get_otpsecret_for_(self.user)) self.assertTrue(frappe.db.get_default(self.user + '_otpsecret')) def test_confirm_otp_token(self): authenticate_for_2factor(self.user) tmp_id = frappe.local.response['tmp_id'] otp = 'wrongotp' with self.assertRaises(frappe.AuthenticationError): confirm_otp_token(self.login_manager,otp=otp,tmp_id=tmp_id) otp = get_otp(self.user) self.assertTrue(confirm_otp_token(self.login_manager,otp=otp,tmp_id=tmp_id)) if frappe.flags.tests_verbose: print('Sleeping for 30secs to confirm token expires..') time.sleep(30) with self.assertRaises(frappe.AuthenticationError): confirm_otp_token(self.login_manager,otp=otp,tmp_id=tmp_id) def test_get_verification_obj(self): otp_secret = get_otpsecret_for_(self.user) token = int(pyotp.TOTP(otp_secret).now()) self.assertTrue(get_verification_obj(self.user,token,otp_secret)) def test_render_string_template(self): args = {'issuer_name':'Frappe Technologies'} _str = 'Verification Code from {{issuer_name}}' _str = render_string_template(_str,args) self.assertEqual(_str,'Verification Code from Frappe Technologies') def set_request(**kwargs): builder = EnvironBuilder(**kwargs) frappe.local.request = Request(builder.get_environ()) def create_http_request(): set_request(method='POST', path='login') enable_2fa() frappe.form_dict['usr'] = 'test@erpnext.com' frappe.form_dict['pwd'] = 'test' frappe.local.form_dict['cmd'] = 'login' http_requests = HTTPRequest() return http_requests def enable_2fa(bypass_two_factor_auth=0): system_settings = frappe.get_doc('System Settings') system_settings.enable_two_factor_auth = 1 system_settings.bypass_2fa_for_retricted_ip_users = cint(bypass_two_factor_auth) system_settings.two_factor_method = 'OTP App' system_settings.save(ignore_permissions=True) frappe.db.commit() def disable_2fa(): system_settings = frappe.get_doc('System Settings') system_settings.enable_two_factor_auth = 0 system_settings.bypass_2fa_for_retricted_ip_users = 0 system_settings.save(ignore_permissions=True) frappe.db.commit() def toggle_2fa_all_role(state=None): all_role = frappe.get_doc('Role','All') if state == None: state = False if all_role.two_factor_auth == True else False if state not in [True,False]:return all_role.two_factor_auth = state all_role.save(ignore_permissions=True) frappe.db.commit() def get_otp(user): otp_secret = get_otpsecret_for_(user) otp = pyotp.TOTP(otp_secret) return otp.now()

true

f704d2c864bad63628fb027f82d866b3cfbf5677

6,290

py

Python

conanfile.py

madebr/conan-swig_installer-1

20cd423f4a5e6e1b9e8a7633fa22ad429096c499

[ "MIT" ]

null

conanfile.py

madebr/conan-swig_installer-1

20cd423f4a5e6e1b9e8a7633fa22ad429096c499

[ "MIT" ]

null

conanfile.py

madebr/conan-swig_installer-1

20cd423f4a5e6e1b9e8a7633fa22ad429096c499

[ "MIT" ]

null

from conans import ConanFile, tools, AutoToolsBuildEnvironment from conans.errors import ConanInvalidConfiguration from contextlib import contextmanager import os import shutil class SwigConan(ConanFile): name = "swig_installer" version = "4.0.1" description = "SWIG is a software development tool that connects programs written in C and C++ with a variety of high-level programming languages." topics = ("conan", "swig", "python", "java", "wrapper") url = "https://github.com/bincrafters/conan-swig_installer" homepage = "http://www.swig.org" author = "Bincrafters <bincrafters@gmail.com>" license = "GPL-3.0-or-later" exports = ["LICENSE.md"] settings = "os_build", "arch_build", "compiler", "os", "arch" _source_subfolder = "source_subfolder" def configure(self): # Verify build configuration if str(self.settings.os_build) != str(self.settings.os): raise ConanInvalidConfiguration("settings.os_build must be equal to settings.os") if str(self.settings.arch_build) != str(self.settings.arch_build): raise ConanInvalidConfiguration("settings.arch_build must be equal to settings.arch_build") def package_id(self): del self.info.settings.compiler del self.info.settings.os del self.info.settings.arch self.info.include_build_settings() def build_requirements(self): if tools.os_info.is_windows: self.build_requires("msys2/20161025") if self.settings.os_build == "Windows": self.build_requires("winflexbison/2.5.18@bincrafters/stable") else: self.build_requires("bison_installer/3.3.2@bincrafters/stable") self.build_requires("pcre/8.41") if self.settings.compiler == "Visual Studio": self.build_requires("cccl_installer/1.0@bincrafters/stable") def system_requirements(self): if self.develop: if tools.os_info.with_yum: installer = tools.SystemPackageTool() packages = [ "autoconf", "automake", ] for package in packages: installer.install(package) def source(self): url = "https://github.com/swig/swig/archive/rel-{}.tar.gz".format(self.version) sha256 = "2eaf6fb89d071d1be280bf995c63360b3729860c0da64948123b5d7e4cfb6cb7" foldername = "swig-rel-{}".format(self.version) tools.get(url, sha256=sha256) os.rename(foldername, self._source_subfolder) @contextmanager def _build_environment(self): if self.settings.compiler == "Visual Studio": with tools.vcvars(self.settings): yield else: yield def _patch_sources(self): tools.replace_in_file(os.path.join(self._source_subfolder, "configure.ac"), "AC_DEFINE_UNQUOTED(SWIG_LIB_WIN_UNIX", "SWIG_LIB_WIN_UNIX=""\nAC_DEFINE_UNQUOTED(SWIG_LIB_WIN_UNIX") def build(self): self._patch_sources() with tools.chdir(os.path.join(self.build_folder, self._source_subfolder)): self.run('./autogen.sh', win_bash=tools.os_info.is_windows) env_build = AutoToolsBuildEnvironment(self, win_bash=tools.os_info.is_windows) deps_libpaths = env_build.library_paths deps_libs = env_build.libs deps_defines = env_build.defines if self.settings.os_build == "Windows" and self.settings.compiler != "Visual Studio": env_build.link_flags.append("-static") libargs = list("-L\"{}\"".format(p) for p in deps_libpaths) + list("-l\"{}\"".format(l) for l in deps_libs) args = [ "PCRE_LIBS={}".format(" ".join(libargs)), "PCRE_CPPFLAGS={}".format(" ".join("-D{}".format(define) for define in deps_defines)), "--host={}".format(tools.detected_architecture()), ] if self.settings.compiler == "Visual Studio": self.output.warn("Visual Studio compiler cannot create ccache-swig. Disabling ccache-swig.") args.append("--disable-ccache") with self._build_environment(): env_build.configure(configure_dir=os.path.join(self.build_folder, self._source_subfolder), args=args) with tools.environment_append({"CONAN_CPU_COUNT": "1" if self.settings.compiler == "Visual Studio" else str(tools.cpu_count())}): env_build.make() def package(self): self.copy(pattern="LICENSE*", dst="licenses", src=self._source_subfolder) self.copy(pattern="COPYRIGHT", dst="licenses", src=self._source_subfolder) with tools.chdir(self.build_folder): env_build = AutoToolsBuildEnvironment(self, win_bash=tools.os_info.is_windows) env_build.install() if self.settings.os == "Windows": shutil.move(os.path.join(self.package_folder, "share", "swig", self.version), os.path.join(self.package_folder, "bin", "Lib")) shutil.rmtree(os.path.join(self.package_folder, "share")) if self.settings.compiler != "Visual Studio": with tools.chdir(os.path.join(self.package_folder, "bin")): ext = ".exe" if tools.os_info.is_windows else "" self.run("strip swig{}".format(ext), win_bash=tools.os_info.is_windows) self.run("strip ccache-swig{}".format(ext), win_bash=tools.os_info.is_windows) def package_info(self): bindir = os.path.join(self.package_folder, "bin") self.output.info('Appending PATH environment variable: {}'.format(bindir)) self.env_info.PATH.append(bindir) if self.settings.os == "Windows": swig_lib_path = os.path.join(self.package_folder, "bin", "Lib") else: swig_lib_path = os.path.join(self.package_folder, "share", "swig", self.version) self.output.info('Setting SWIG_LIB environment variable: {}'.format(swig_lib_path)) self.env_info.SWIG_LIB = swig_lib_path self.output.info('Setting SWIG_INSTALLER_ROOT to {}'.format(self.package_folder)) self.env_info.SWIG_INSTALLER_ROOT = self.package_folder

46.592593

151

0.641017

from conans import ConanFile, tools, AutoToolsBuildEnvironment from conans.errors import ConanInvalidConfiguration from contextlib import contextmanager import os import shutil class SwigConan(ConanFile): name = "swig_installer" version = "4.0.1" description = "SWIG is a software development tool that connects programs written in C and C++ with a variety of high-level programming languages." topics = ("conan", "swig", "python", "java", "wrapper") url = "https://github.com/bincrafters/conan-swig_installer" homepage = "http://www.swig.org" author = "Bincrafters <bincrafters@gmail.com>" license = "GPL-3.0-or-later" exports = ["LICENSE.md"] settings = "os_build", "arch_build", "compiler", "os", "arch" _source_subfolder = "source_subfolder" def configure(self): if str(self.settings.os_build) != str(self.settings.os): raise ConanInvalidConfiguration("settings.os_build must be equal to settings.os") if str(self.settings.arch_build) != str(self.settings.arch_build): raise ConanInvalidConfiguration("settings.arch_build must be equal to settings.arch_build") def package_id(self): del self.info.settings.compiler del self.info.settings.os del self.info.settings.arch self.info.include_build_settings() def build_requirements(self): if tools.os_info.is_windows: self.build_requires("msys2/20161025") if self.settings.os_build == "Windows": self.build_requires("winflexbison/2.5.18@bincrafters/stable") else: self.build_requires("bison_installer/3.3.2@bincrafters/stable") self.build_requires("pcre/8.41") if self.settings.compiler == "Visual Studio": self.build_requires("cccl_installer/1.0@bincrafters/stable") def system_requirements(self): if self.develop: if tools.os_info.with_yum: installer = tools.SystemPackageTool() packages = [ "autoconf", "automake", ] for package in packages: installer.install(package) def source(self): url = "https://github.com/swig/swig/archive/rel-{}.tar.gz".format(self.version) sha256 = "2eaf6fb89d071d1be280bf995c63360b3729860c0da64948123b5d7e4cfb6cb7" foldername = "swig-rel-{}".format(self.version) tools.get(url, sha256=sha256) os.rename(foldername, self._source_subfolder) @contextmanager def _build_environment(self): if self.settings.compiler == "Visual Studio": with tools.vcvars(self.settings): yield else: yield def _patch_sources(self): tools.replace_in_file(os.path.join(self._source_subfolder, "configure.ac"), "AC_DEFINE_UNQUOTED(SWIG_LIB_WIN_UNIX", "SWIG_LIB_WIN_UNIX=""\nAC_DEFINE_UNQUOTED(SWIG_LIB_WIN_UNIX") def build(self): self._patch_sources() with tools.chdir(os.path.join(self.build_folder, self._source_subfolder)): self.run('./autogen.sh', win_bash=tools.os_info.is_windows) env_build = AutoToolsBuildEnvironment(self, win_bash=tools.os_info.is_windows) deps_libpaths = env_build.library_paths deps_libs = env_build.libs deps_defines = env_build.defines if self.settings.os_build == "Windows" and self.settings.compiler != "Visual Studio": env_build.link_flags.append("-static") libargs = list("-L\"{}\"".format(p) for p in deps_libpaths) + list("-l\"{}\"".format(l) for l in deps_libs) args = [ "PCRE_LIBS={}".format(" ".join(libargs)), "PCRE_CPPFLAGS={}".format(" ".join("-D{}".format(define) for define in deps_defines)), "--host={}".format(tools.detected_architecture()), ] if self.settings.compiler == "Visual Studio": self.output.warn("Visual Studio compiler cannot create ccache-swig. Disabling ccache-swig.") args.append("--disable-ccache") with self._build_environment(): env_build.configure(configure_dir=os.path.join(self.build_folder, self._source_subfolder), args=args) with tools.environment_append({"CONAN_CPU_COUNT": "1" if self.settings.compiler == "Visual Studio" else str(tools.cpu_count())}): env_build.make() def package(self): self.copy(pattern="LICENSE*", dst="licenses", src=self._source_subfolder) self.copy(pattern="COPYRIGHT", dst="licenses", src=self._source_subfolder) with tools.chdir(self.build_folder): env_build = AutoToolsBuildEnvironment(self, win_bash=tools.os_info.is_windows) env_build.install() if self.settings.os == "Windows": shutil.move(os.path.join(self.package_folder, "share", "swig", self.version), os.path.join(self.package_folder, "bin", "Lib")) shutil.rmtree(os.path.join(self.package_folder, "share")) if self.settings.compiler != "Visual Studio": with tools.chdir(os.path.join(self.package_folder, "bin")): ext = ".exe" if tools.os_info.is_windows else "" self.run("strip swig{}".format(ext), win_bash=tools.os_info.is_windows) self.run("strip ccache-swig{}".format(ext), win_bash=tools.os_info.is_windows) def package_info(self): bindir = os.path.join(self.package_folder, "bin") self.output.info('Appending PATH environment variable: {}'.format(bindir)) self.env_info.PATH.append(bindir) if self.settings.os == "Windows": swig_lib_path = os.path.join(self.package_folder, "bin", "Lib") else: swig_lib_path = os.path.join(self.package_folder, "share", "swig", self.version) self.output.info('Setting SWIG_LIB environment variable: {}'.format(swig_lib_path)) self.env_info.SWIG_LIB = swig_lib_path self.output.info('Setting SWIG_INSTALLER_ROOT to {}'.format(self.package_folder)) self.env_info.SWIG_INSTALLER_ROOT = self.package_folder

true

f704d309b2d0f6c310b68088e4d0a88caea2c3aa

1,168

py

Python

pv/wsgi.py

Dumbaz/autoradio-pv

8aae293e58b2e79a05956c535bb109f74edc89c3

[ "BSD-3-Clause" ]

null

pv/wsgi.py

Dumbaz/autoradio-pv

8aae293e58b2e79a05956c535bb109f74edc89c3

[ "BSD-3-Clause" ]

null

pv/wsgi.py

Dumbaz/autoradio-pv

8aae293e58b2e79a05956c535bb109f74edc89c3

[ "BSD-3-Clause" ]

null

""" WSGI config for pv project. This module contains the WSGI application used by Django's development server and any production WSGI deployments. It should expose a module-level variable named ``application``. Django's ``runserver`` and ``runfcgi`` commands discover this application via the ``WSGI_APPLICATION`` setting. Usually you will have the standard Django WSGI application here, but it also might make sense to replace the whole Django WSGI application with a custom one that later delegates to the Django one. For example, you could introduce WSGI middleware here, or combine a Django application with an application of another framework. """ import os import sys sys.path.append('/srv/pv/pv') os.environ.setdefault("DJANGO_SETTINGS_MODULE", "pv.settings") # This application object is used by any WSGI server configured to use this # file. This includes Django's development server, if the WSGI_APPLICATION # setting points here. from django.core.wsgi import get_wsgi_application application = get_wsgi_application() # Apply WSGI middleware here. # from helloworld.wsgi import HelloWorldApplication # application = HelloWorldApplication(application)

36.5

79

0.80137

import os import sys sys.path.append('/srv/pv/pv') os.environ.setdefault("DJANGO_SETTINGS_MODULE", "pv.settings") # setting points here. from django.core.wsgi import get_wsgi_application application = get_wsgi_application() # Apply WSGI middleware here. # from helloworld.wsgi import HelloWorldApplication # application = HelloWorldApplication(application)

true

f704d3fbb8a78fe4a901efbbfcc7672e4820d792

2,293

py

Python

python/ray/tune/examples/zoopt_example.py

firebolt55439/ray

215300b070628c06f0106906fc6c03bd70ebf140

[ "Apache-2.0" ]

3

2020-12-03T17:48:45.000Z

2022-01-22T08:09:46.000Z

python/ray/tune/examples/zoopt_example.py

firebolt55439/ray

215300b070628c06f0106906fc6c03bd70ebf140

[ "Apache-2.0" ]

84

2021-03-06T08:02:56.000Z

2022-03-05T08:07:19.000Z

python/ray/tune/examples/zoopt_example.py

firebolt55439/ray

215300b070628c06f0106906fc6c03bd70ebf140

[ "Apache-2.0" ]

2

2020-05-22T15:36:27.000Z

2020-05-22T15:52:03.000Z

"""This example demonstrates the usage of ZOOptSearch. It also checks that it is usable with a separate scheduler. """ import time from ray import tune from ray.tune.suggest.zoopt import ZOOptSearch from ray.tune.schedulers import AsyncHyperBandScheduler from zoopt import ValueType # noqa: F401 def evaluation_fn(step, width, height): time.sleep(0.1) return (0.1 + width * step / 100)**(-1) + height * 0.1 def easy_objective(config): # Hyperparameters width, height = config["width"], config["height"] for step in range(config["steps"]): # Iterative training function - can be any arbitrary training procedure intermediate_score = evaluation_fn(step, width, height) # Feed the score back back to Tune. tune.report(iterations=step, mean_loss=intermediate_score) if __name__ == "__main__": import argparse parser = argparse.ArgumentParser() parser.add_argument( "--smoke-test", action="store_true", help="Finish quickly for testing") args, _ = parser.parse_known_args() num_samples = 10 if args.smoke_test else 1000 # Optional: Pass the parameter space yourself # space = { # # for continuous dimensions: (continuous, search_range, precision) # "height": (ValueType.CONTINUOUS, [-10, 10], 1e-2), # # for discrete dimensions: (discrete, search_range, has_order) # "width": (ValueType.DISCRETE, [0, 10], True) # # for grid dimensions: (grid, grid_list) # "layers": (ValueType.GRID, [4, 8, 16]) # } zoopt_search_config = { "parallel_num": 8, } zoopt_search = ZOOptSearch( algo="Asracos", # only support ASRacos currently budget=num_samples, # dim_dict=space, # If you want to set the space yourself **zoopt_search_config) scheduler = AsyncHyperBandScheduler() analysis = tune.run( easy_objective, metric="mean_loss", mode="min", search_alg=zoopt_search, name="zoopt_search", scheduler=scheduler, num_samples=num_samples, config={ "steps": 10, "height": tune.quniform(-10, 10, 1e-2), "width": tune.randint(0, 10) }) print("Best config found: ", analysis.best_config)

30.573333

79

0.642826

import time from ray import tune from ray.tune.suggest.zoopt import ZOOptSearch from ray.tune.schedulers import AsyncHyperBandScheduler from zoopt import ValueType def evaluation_fn(step, width, height): time.sleep(0.1) return (0.1 + width * step / 100)**(-1) + height * 0.1 def easy_objective(config): width, height = config["width"], config["height"] for step in range(config["steps"]): intermediate_score = evaluation_fn(step, width, height) tune.report(iterations=step, mean_loss=intermediate_score) if __name__ == "__main__": import argparse parser = argparse.ArgumentParser() parser.add_argument( "--smoke-test", action="store_true", help="Finish quickly for testing") args, _ = parser.parse_known_args() num_samples = 10 if args.smoke_test else 1000 um_samples, heduler = AsyncHyperBandScheduler() analysis = tune.run( easy_objective, metric="mean_loss", mode="min", search_alg=zoopt_search, name="zoopt_search", scheduler=scheduler, num_samples=num_samples, config={ "steps": 10, "height": tune.quniform(-10, 10, 1e-2), "width": tune.randint(0, 10) }) print("Best config found: ", analysis.best_config)

true

f704d464d0afc50d7816616dbcf9d13d85e6185a

3,897

py

Python

tests/unit/backend/chalice/api_server/mock_auth.py

isabella232/corpora-data-portal

09ed3cad3165f8b0db854b76404e0d5d0ea0b7d9

[ "MIT" ]

null

tests/unit/backend/chalice/api_server/mock_auth.py

isabella232/corpora-data-portal

09ed3cad3165f8b0db854b76404e0d5d0ea0b7d9

[ "MIT" ]

1

2021-02-23T22:56:13.000Z

tests/unit/backend/chalice/api_server/mock_auth.py

isabella232/corpora-data-portal

09ed3cad3165f8b0db854b76404e0d5d0ea0b7d9

[ "MIT" ]

null

import urllib import jose.jwt import time import random import sys import requests from flask import Flask, request, redirect, make_response, jsonify import subprocess # seconds until the token expires TOKEN_EXPIRES = 2 # A mocked out oauth server, which serves all the endpoints needed by the oauth type. class MockOauthApp: def __init__(self, port): self.port = port # mock flask app self.app = Flask("mock_oauth_app") self.app.add_url_rule("/authorize", view_func=self.api_authorize) self.app.add_url_rule("/oauth/token", view_func=self.api_oauth_token, methods=["POST"]) self.app.add_url_rule("/v2/logout", view_func=self.api_logout) self.app.add_url_rule("/.well-known/openid-configuration", view_func=self.api_openid_configuration) self.app.add_url_rule("/.well-known/jwks.json", view_func=self.api_jwks) def api_authorize(self): callback = request.args.get("redirect_uri") state = request.args.get("state") return redirect(callback + f"?code=fakecode&state={state}") def api_oauth_token(self): expires_at = time.time() headers = dict(alg="RS256", kid="fake_kid") payload = dict( name="Fake User", sub="test_user_id", email="fake_user@email.com", email_verified=True, exp=expires_at ) jwt = jose.jwt.encode(claims=payload, key="mysecret", algorithm="HS256", headers=headers) r = { "access_token": f"access-{time.time()}", "id_token": jwt, "refresh_token": f"random-{time.time()}", "scope": "openid profile email offline", "expires_in": TOKEN_EXPIRES, "token_type": "Bearer", "expires_at": expires_at, } return make_response(jsonify(r)) def api_logout(self): return_to = request.args.get("returnTo") return redirect(return_to) def api_openid_configuration(self): data = dict(jwks_uri=f"http://localhost:{self.port}/.well-known/jwks.json") return make_response(jsonify(data)) def api_jwks(self): data = dict( alg="RS256", kty="RSA", use="sig", kid="fake_kid", ) return make_response(jsonify(dict(keys=[data]))) class MockOauthServer: def __init__(self): self.process = None self.port = None self.server_okay = False def start(self): self.port = random.randint(10000, 20000) self.process = subprocess.Popen([sys.executable, __file__, str(self.port)]) # Verify that the mock oauth server is ready (accepting requests) before starting the tests. self.server_okay = False for _ in range(5): try: response = requests.get(f"http://localhost:{self.port}/.well-known/jwks.json") if response.status_code == 200: self.server_okay = True break except Exception: pass # wait one second and try again time.sleep(1) def terminate(self): self.process.terminate() def get_auth_token(app): """ Generated an auth token for testing. :param app: a chalice app. :return: """ headers = dict(host="localhost") response = app.get("/dp/v1/login", headers=headers) location = response.headers["Location"] split = urllib.parse.urlsplit(location) args = dict(urllib.parse.parse_qsl(split.query)) # follow redirect url = f"/dp/v1/oauth2/callback?code=fakecode&state={args['state']}" response = app.get(url, headers=dict(host="localhost", Cookie=response.headers["Set-Cookie"])) return response.headers["Set-Cookie"] if __name__ == "__main__": port = int(sys.argv[1]) mock_app = MockOauthApp(port) mock_app.app.run(port=port, debug=True)

32.747899

114

0.625353

import urllib import jose.jwt import time import random import sys import requests from flask import Flask, request, redirect, make_response, jsonify import subprocess TOKEN_EXPIRES = 2 class MockOauthApp: def __init__(self, port): self.port = port self.app = Flask("mock_oauth_app") self.app.add_url_rule("/authorize", view_func=self.api_authorize) self.app.add_url_rule("/oauth/token", view_func=self.api_oauth_token, methods=["POST"]) self.app.add_url_rule("/v2/logout", view_func=self.api_logout) self.app.add_url_rule("/.well-known/openid-configuration", view_func=self.api_openid_configuration) self.app.add_url_rule("/.well-known/jwks.json", view_func=self.api_jwks) def api_authorize(self): callback = request.args.get("redirect_uri") state = request.args.get("state") return redirect(callback + f"?code=fakecode&state={state}") def api_oauth_token(self): expires_at = time.time() headers = dict(alg="RS256", kid="fake_kid") payload = dict( name="Fake User", sub="test_user_id", email="fake_user@email.com", email_verified=True, exp=expires_at ) jwt = jose.jwt.encode(claims=payload, key="mysecret", algorithm="HS256", headers=headers) r = { "access_token": f"access-{time.time()}", "id_token": jwt, "refresh_token": f"random-{time.time()}", "scope": "openid profile email offline", "expires_in": TOKEN_EXPIRES, "token_type": "Bearer", "expires_at": expires_at, } return make_response(jsonify(r)) def api_logout(self): return_to = request.args.get("returnTo") return redirect(return_to) def api_openid_configuration(self): data = dict(jwks_uri=f"http://localhost:{self.port}/.well-known/jwks.json") return make_response(jsonify(data)) def api_jwks(self): data = dict( alg="RS256", kty="RSA", use="sig", kid="fake_kid", ) return make_response(jsonify(dict(keys=[data]))) class MockOauthServer: def __init__(self): self.process = None self.port = None self.server_okay = False def start(self): self.port = random.randint(10000, 20000) self.process = subprocess.Popen([sys.executable, __file__, str(self.port)]) self.server_okay = False for _ in range(5): try: response = requests.get(f"http://localhost:{self.port}/.well-known/jwks.json") if response.status_code == 200: self.server_okay = True break except Exception: pass time.sleep(1) def terminate(self): self.process.terminate() def get_auth_token(app): headers = dict(host="localhost") response = app.get("/dp/v1/login", headers=headers) location = response.headers["Location"] split = urllib.parse.urlsplit(location) args = dict(urllib.parse.parse_qsl(split.query)) url = f"/dp/v1/oauth2/callback?code=fakecode&state={args['state']}" response = app.get(url, headers=dict(host="localhost", Cookie=response.headers["Set-Cookie"])) return response.headers["Set-Cookie"] if __name__ == "__main__": port = int(sys.argv[1]) mock_app = MockOauthApp(port) mock_app.app.run(port=port, debug=True)

true

f704d4961f151943c889d1c38e2afd4fdd7bde3f

4,440

py

Python

topi/python/topi/x86/reduction.py

jheo4/incubator-tvm

c4c61cb766608fb2f0fd8c9facc480a43afed3f5

[ "Apache-2.0" ]

3

2021-02-23T22:06:01.000Z

2021-09-30T09:59:17.000Z

topi/python/topi/x86/reduction.py

jheo4/incubator-tvm

c4c61cb766608fb2f0fd8c9facc480a43afed3f5

[ "Apache-2.0" ]

4

2021-03-30T11:59:59.000Z

2022-03-12T00:40:23.000Z

topi/python/topi/x86/reduction.py

jheo4/incubator-tvm

c4c61cb766608fb2f0fd8c9facc480a43afed3f5

[ "Apache-2.0" ]

3

2021-07-20T07:40:15.000Z

2021-08-03T08:39:17.000Z

# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. # pylint: disable=invalid-name """x86 declaration and schedules.""" from __future__ import absolute_import as _abs import tvm from .. import tag from .. import generic from ..util import get_const_tuple def _schedule_reduce(sch, op, is_idx_reduce=False): if is_idx_reduce: real_out = op.output(0) fused = sch[real_out].fuse(*sch[real_out].op.axis) out = op.input_tensors[0] else: out = op.output(0) const_shape = True out_shape = get_const_tuple(out.shape) for d in out_shape: if not isinstance(d, int): const_shape = False break if const_shape: naxes = len(sch[out].op.axis) parallelism = 1 fuse_axes = [] # We choose a heuristic number 128 to limit the maximum parallelism while len(fuse_axes) < naxes and parallelism < 128: ivar = sch[out].op.axis[len(fuse_axes)] parallelism *= int(ivar.dom.extent) fuse_axes.append(ivar) fused = sch[out].fuse(*fuse_axes) sch[out].parallel(fused) else: if len(sch[out].op.axis) >= 5: # avoid too many parallelism fused = sch[out].fuse(sch[out].op.axis[0], sch[out].op.axis[1], sch[out].op.axis[2]) sch[out].parallel(fused) else: fused = sch[out].fuse(*sch[out].op.axis) sch[out].parallel(fused) @generic.schedule_reduce.register(["cpu"]) def schedule_reduce(outs): """X86 schedule for reduction op. Parameters ---------- outs: Array of Tensor The computation graph description of injective in the format of an array of tensors. Returns ------- sch: Schedule The computation schedule for the op. """ outs = [outs] if isinstance(outs, tvm.tensor.Tensor) else outs sch = tvm.create_schedule([x.op for x in outs]) scheduled_ops = [] def traverse_before_reduce(operator): """Internal traverse function""" if isinstance(operator, tvm.tensor.PlaceholderOp): return if tag.is_injective(operator.tag): sch[operator].compute_inline() for tensor in operator.input_tensors: if tensor.op not in scheduled_ops: traverse_before_reduce(tensor.op) else: raise RuntimeError("Unsupported operator: %s" % operator.tag) scheduled_ops.append(operator) def traverse_after_reduce(operator): """Internal traverse function""" if tag.is_broadcast(operator.tag): if operator not in scheduled_ops: generic.schedule_injective_from_existing(sch, operator) for tensor in operator.input_tensors: traverse_after_reduce(tensor.op) elif operator.tag == 'comm_reduce': _schedule_reduce(sch, operator, is_idx_reduce=False) for tensor in operator.input_tensors: if tensor.op not in scheduled_ops: traverse_before_reduce(tensor.op) elif operator.tag == 'comm_reduce_idx': _schedule_reduce(sch, operator, is_idx_reduce=True) input_tensors = operator.input_tensors[0].op.input_tensors for tensor in input_tensors: if tensor.op not in scheduled_ops: traverse_before_reduce(tensor.op) elif isinstance(operator, tvm.tensor.PlaceholderOp): pass else: raise RuntimeError("Unsupported operator: %s (tag: %s)" % (operator, operator.tag)) scheduled_ops.append(operator) traverse_after_reduce(outs[0].op) return sch

36.694215

96

0.643919

from __future__ import absolute_import as _abs import tvm from .. import tag from .. import generic from ..util import get_const_tuple def _schedule_reduce(sch, op, is_idx_reduce=False): if is_idx_reduce: real_out = op.output(0) fused = sch[real_out].fuse(*sch[real_out].op.axis) out = op.input_tensors[0] else: out = op.output(0) const_shape = True out_shape = get_const_tuple(out.shape) for d in out_shape: if not isinstance(d, int): const_shape = False break if const_shape: naxes = len(sch[out].op.axis) parallelism = 1 fuse_axes = [] while len(fuse_axes) < naxes and parallelism < 128: ivar = sch[out].op.axis[len(fuse_axes)] parallelism *= int(ivar.dom.extent) fuse_axes.append(ivar) fused = sch[out].fuse(*fuse_axes) sch[out].parallel(fused) else: if len(sch[out].op.axis) >= 5: fused = sch[out].fuse(sch[out].op.axis[0], sch[out].op.axis[1], sch[out].op.axis[2]) sch[out].parallel(fused) else: fused = sch[out].fuse(*sch[out].op.axis) sch[out].parallel(fused) @generic.schedule_reduce.register(["cpu"]) def schedule_reduce(outs): outs = [outs] if isinstance(outs, tvm.tensor.Tensor) else outs sch = tvm.create_schedule([x.op for x in outs]) scheduled_ops = [] def traverse_before_reduce(operator): if isinstance(operator, tvm.tensor.PlaceholderOp): return if tag.is_injective(operator.tag): sch[operator].compute_inline() for tensor in operator.input_tensors: if tensor.op not in scheduled_ops: traverse_before_reduce(tensor.op) else: raise RuntimeError("Unsupported operator: %s" % operator.tag) scheduled_ops.append(operator) def traverse_after_reduce(operator): if tag.is_broadcast(operator.tag): if operator not in scheduled_ops: generic.schedule_injective_from_existing(sch, operator) for tensor in operator.input_tensors: traverse_after_reduce(tensor.op) elif operator.tag == 'comm_reduce': _schedule_reduce(sch, operator, is_idx_reduce=False) for tensor in operator.input_tensors: if tensor.op not in scheduled_ops: traverse_before_reduce(tensor.op) elif operator.tag == 'comm_reduce_idx': _schedule_reduce(sch, operator, is_idx_reduce=True) input_tensors = operator.input_tensors[0].op.input_tensors for tensor in input_tensors: if tensor.op not in scheduled_ops: traverse_before_reduce(tensor.op) elif isinstance(operator, tvm.tensor.PlaceholderOp): pass else: raise RuntimeError("Unsupported operator: %s (tag: %s)" % (operator, operator.tag)) scheduled_ops.append(operator) traverse_after_reduce(outs[0].op) return sch

true

f704d5a672c42774980b2e28551ba3d1cd02079a

741

py

Python

micropython/boot.py

tinytux/sensor

2aa2a9ac34335c0b8579018f670b29455cfd47df

[ "MIT" ]

9

2015-01-16T17:12:20.000Z

2021-02-26T19:39:44.000Z

micropython/boot.py

tinytux/sensor

2aa2a9ac34335c0b8579018f670b29455cfd47df

[ "MIT" ]

null

micropython/boot.py

tinytux/sensor

2aa2a9ac34335c0b8579018f670b29455cfd47df

[ "MIT" ]

2

2017-02-14T05:15:03.000Z

2017-05-25T10:48:51.000Z

# boot.py -- runs on boot-up import pyb pyb.LED(3).on() # indicate we are waiting for switch press pyb.delay(2000) # wait for user to maybe press the switch switch_value = pyb.Switch()() # sample the switch at end of delay pyb.LED(3).off() # indicate that we finished waiting for the switch pyb.LED(4).on() # indicate that we are selecting the mode if switch_value: # button pressed, mount SD card as usb storage pyb.usb_mode('CDC+MSC') pyb.main('debug.py') else: # no button pressed, SD card can be used by script pyb.usb_mode('CDC+HID') pyb.main('displaytemp.py') pyb.LED(4).off() # indicate that we finished selecting the mode

30.875

82

0.624831

import pyb pyb.LED(3).on() pyb.delay(2000) switch_value = pyb.Switch()() pyb.LED(3).off() pyb.LED(4).on() if switch_value: pyb.usb_mode('CDC+MSC') pyb.main('debug.py') else: pyb.usb_mode('CDC+HID') pyb.main('displaytemp.py') pyb.LED(4).off()

true

f704d5d4ac02cfcd81c719c22d91a83721a4f86f

1,151

py

Python

Milestone2/L2_5_p5_test_vertical.py

4ntLu0/1051-Project

93ae9b8d312bd6e79949d878d3fb422282de703b

[ "Unlicense" ]

null

Milestone2/L2_5_p5_test_vertical.py

4ntLu0/1051-Project

93ae9b8d312bd6e79949d878d3fb422282de703b

[ "Unlicense" ]

null

Milestone2/L2_5_p5_test_vertical.py

4ntLu0/1051-Project

93ae9b8d312bd6e79949d878d3fb422282de703b

[ "Unlicense" ]

null

from Cimpl import * image = load_image(choose_file()) def flip_vertical(image: image) -> Image: vertical_image = copy(image) for x in range(get_width(image)): for y in range(get_height(image)): flipped_color = get_color(image, -x, y) set_color(vertical_image, x, y, flipped_color) show(vertical_image) return vertical_image def test_flip_vertical(image: Image) -> Image: """ Writen by Abdelrahman Alatoom (101147742). Function tests that all values of the x axis of the inputted image (into the flip_vertical function) are assigned to to their negative counterparts""" vertical_image = flip_vertical(image) for x in range(get_width(image)): for y in range(get_height(image)): original_colour = get_color(image, x, y) for x in range(get_width(vertical_image)): for y in range(get_height(vertical_image)): vertical_colour = get_color(vertical_image, -x, y) if original_colour == vertical_colour: print('Test Passed') else: print('Test Failed')

28.073171

201

0.636838

from Cimpl import * image = load_image(choose_file()) def flip_vertical(image: image) -> Image: vertical_image = copy(image) for x in range(get_width(image)): for y in range(get_height(image)): flipped_color = get_color(image, -x, y) set_color(vertical_image, x, y, flipped_color) show(vertical_image) return vertical_image def test_flip_vertical(image: Image) -> Image: vertical_image = flip_vertical(image) for x in range(get_width(image)): for y in range(get_height(image)): original_colour = get_color(image, x, y) for x in range(get_width(vertical_image)): for y in range(get_height(vertical_image)): vertical_colour = get_color(vertical_image, -x, y) if original_colour == vertical_colour: print('Test Passed') else: print('Test Failed')

true

f704d62fcf2ec086efa3468b0494a0f1c3b01a19

2,675

py

Python

sc-actions-provider/app.py

Sage-Bionetworks-IT/cfn-cr-sc-actions-provider

f0550c6b810fbb437e24048de73d429b017750b4

[ "Apache-2.0" ]

null

sc-actions-provider/app.py

Sage-Bionetworks-IT/cfn-cr-sc-actions-provider

f0550c6b810fbb437e24048de73d429b017750b4

[ "Apache-2.0" ]

4

2020-04-28T20:24:30.000Z

2021-08-17T01:21:17.000Z

sc-actions-provider/app.py

Sage-Bionetworks-IT/cfn-cr-sc-actions-provider

f0550c6b810fbb437e24048de73d429b017750b4

[ "Apache-2.0" ]

1

2020-04-28T18:42:41.000Z

import boto3 import json import logging from crhelper import CfnResource logger = logging.getLogger(__name__) helper = CfnResource( json_logging=False, log_level='DEBUG', boto_level='CRITICAL') try: sc = boto3.client("servicecatalog") except Exception as e: helper.init_failure(e) def get_parameters(event): aws_account_id = event['StackId'].split(':')[4] name = event['ResourceProperties']['Name'] ssm_doc_name = event['ResourceProperties']['SsmDocName'] ssm_doc_version = event['ResourceProperties']['SsmDocVersion'] assume_role = event['ResourceProperties']['AssumeRole'] return aws_account_id, name, ssm_doc_name, ssm_doc_version, assume_role def create_provider(aws_account_id, name, ssm_doc_name, ssm_doc_version, assume_role): response = sc.create_service_action( Name=name, Description=name, DefinitionType='SSM_AUTOMATION', Definition= { "Name": ssm_doc_name, "Version": ssm_doc_version, "AssumeRole": assume_role, "Parameters": "[{\"Name\":\"InstanceId\",\"Type\":\"TARGET\"}]" } ) id = response['ServiceActionDetail']['ServiceActionSummary']['Id'] logger.info("created sc action " + id) return id @helper.create def create(event, context): logger.debug("Received event: " + json.dumps(event, sort_keys=False)) return create_provider(*get_parameters(event)) @helper.delete def delete(event, context): logger.debug("Received event: " + json.dumps(event, sort_keys=False)) id = event['PhysicalResourceId'] logger.info("deleting sc action " + id) sc.delete_service_action( Id=id ) @helper.update def update(event, context): logger.debug("Received event: " + json.dumps(event, sort_keys=False)) new_properties = event['ResourceProperties'] old_properties = event['OldResourceProperties'] id = event['PhysicalResourceId'] if new_properties != old_properties: response = sc.update_service_action( Id=id, Name=new_properties['Name'], Description=new_properties['Name'], Definition= { "Name": new_properties['SsmDocName'], "Version": new_properties['SsmDocVersion'], "AssumeRole": new_properties['AssumeRole'], "Parameters": "[{\"Name\":\"InstanceId\",\"Type\":\"TARGET\"}]" } ) id = response['ServiceActionDetail']['ServiceActionSummary']['Id'] logger.info("updated sc action = " + id) return id def lambda_handler(event, context): helper(event, context)

34.294872

86

0.644486

import boto3 import json import logging from crhelper import CfnResource logger = logging.getLogger(__name__) helper = CfnResource( json_logging=False, log_level='DEBUG', boto_level='CRITICAL') try: sc = boto3.client("servicecatalog") except Exception as e: helper.init_failure(e) def get_parameters(event): aws_account_id = event['StackId'].split(':')[4] name = event['ResourceProperties']['Name'] ssm_doc_name = event['ResourceProperties']['SsmDocName'] ssm_doc_version = event['ResourceProperties']['SsmDocVersion'] assume_role = event['ResourceProperties']['AssumeRole'] return aws_account_id, name, ssm_doc_name, ssm_doc_version, assume_role def create_provider(aws_account_id, name, ssm_doc_name, ssm_doc_version, assume_role): response = sc.create_service_action( Name=name, Description=name, DefinitionType='SSM_AUTOMATION', Definition= { "Name": ssm_doc_name, "Version": ssm_doc_version, "AssumeRole": assume_role, "Parameters": "[{\"Name\":\"InstanceId\",\"Type\":\"TARGET\"}]" } ) id = response['ServiceActionDetail']['ServiceActionSummary']['Id'] logger.info("created sc action " + id) return id @helper.create def create(event, context): logger.debug("Received event: " + json.dumps(event, sort_keys=False)) return create_provider(*get_parameters(event)) @helper.delete def delete(event, context): logger.debug("Received event: " + json.dumps(event, sort_keys=False)) id = event['PhysicalResourceId'] logger.info("deleting sc action " + id) sc.delete_service_action( Id=id ) @helper.update def update(event, context): logger.debug("Received event: " + json.dumps(event, sort_keys=False)) new_properties = event['ResourceProperties'] old_properties = event['OldResourceProperties'] id = event['PhysicalResourceId'] if new_properties != old_properties: response = sc.update_service_action( Id=id, Name=new_properties['Name'], Description=new_properties['Name'], Definition= { "Name": new_properties['SsmDocName'], "Version": new_properties['SsmDocVersion'], "AssumeRole": new_properties['AssumeRole'], "Parameters": "[{\"Name\":\"InstanceId\",\"Type\":\"TARGET\"}]" } ) id = response['ServiceActionDetail']['ServiceActionSummary']['Id'] logger.info("updated sc action = " + id) return id def lambda_handler(event, context): helper(event, context)

true

f704d69bd77a243b1e77d53e8cb7b0fdb8daaf27

7,384

py

Python

src/secondaires/rapport/editeurs/bugedit_p/__init__.py

vlegoff/tsunami

36b3b974f6eefbf15cd5d5f099fc14630e66570b

[ "BSD-3-Clause" ]

14

2015-08-21T19:15:21.000Z

2017-11-26T13:59:17.000Z

src/secondaires/rapport/editeurs/bugedit_p/__init__.py

vincent-lg/tsunami

36b3b974f6eefbf15cd5d5f099fc14630e66570b

[ "BSD-3-Clause" ]

20

2015-09-29T20:50:45.000Z

2018-06-21T12:58:30.000Z

src/secondaires/rapport/editeurs/bugedit_p/__init__.py

vlegoff/tsunami

36b3b974f6eefbf15cd5d5f099fc14630e66570b

[ "BSD-3-Clause" ]

3

2015-05-02T19:42:03.000Z

2018-09-06T10:55:00.000Z

# -*-coding:Utf-8 -* # Copyright (c) 2010-2017 LE GOFF Vincent # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # * Redistributions of source code must retain the above copyright notice, this # list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # * Neither the name of the copyright holder nor the names of its contributors # may be used to endorse or promote products derived from this software # without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE # ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE # LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR # CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT # OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS # INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN # CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) # ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE # POSSIBILITY OF SUCH DAMAGE. """Package contenant l'éditeur 'bugedit'. Si des redéfinitions de contexte-éditeur standard doivent être faites, elles seront placées dans ce package Note importante : ce package contient la définition d'un éditeur, mais celui-ci peut très bien être étendu par d'autres modules. Au quel cas, les extensions n'apparaîtront pas ici. """ from primaires.interpreteur.editeur.presentation import Presentation from primaires.interpreteur.editeur.description import Description from primaires.interpreteur.editeur.uniligne import Uniligne from primaires.interpreteur.editeur.entier import Entier from primaires.interpreteur.editeur.choix import Choix from primaires.interpreteur.editeur.flag import Flag from .edt_assigne import EdtAssigne from .supprimer import NSupprimer from secondaires.rapport.constantes import * class EdtBugeditP(Presentation): """Classe définissant l'éditeur de rapport 'bugedit'. """ nom = "bugedit+" def __init__(self, personnage, rapport): """Constructeur de l'éditeur""" if personnage: instance_connexion = personnage.instance_connexion else: instance_connexion = None Presentation.__init__(self, instance_connexion, rapport) if personnage and rapport: self.construire(rapport) def __getnewargs__(self): return (None, None) def construire(self, rapport): """Construction de l'éditeur""" # Titre titre = self.ajouter_choix("titre", "t", Uniligne, rapport, "titre") titre.parent = self titre.prompt = "Titre du rapport : " titre.apercu = "{objet.titre}" titre.aide_courte = \ "Entrez le |ent|titre|ff| du rapport ou |cmd|/|ff| pour revenir " \ "à la fenêtre parente.\n\nTitre actuel : |bc|{objet.titre}|ff|" # Type types = sorted(TYPES) type = self.ajouter_choix("type", "y", Choix, rapport, "type", types) type.parent = self type.prompt = "Type de rapport : " type.apercu = "{objet.type}" type.aide_courte = \ "Entrez le |ent|type|ff| de rapport ou |cmd|/|ff| pour " \ "revenir à la fenêtre parente.\n\Types disponibles : " \ "{}.\n\Type actuel : |bc|{{objet.type}}|ff|".format( ", ".join(types)) # Catégorie categories = sorted(CATEGORIES) categorie = self.ajouter_choix("catégorie", "c", Choix, rapport, "categorie", categories) categorie.parent = self categorie.prompt = "Catégorie du rapport : " categorie.apercu = "{objet.categorie}" categorie.aide_courte = \ "Entrez la |ent|catégorie|ff| du rapport ou |cmd|/|ff| pour " \ "revenir à la fenêtre parente.\n\nCatégories disponibles : " \ "{}.\n\nCatégorie actuelle : |bc|{{objet.categorie}}|ff|".format( ", ".join(categories)) # Priorité priorites = sorted(PRIORITES) priorite = self.ajouter_choix("priorité", "p", Choix, rapport, "priorite", priorites) priorite.parent = self priorite.prompt = "Priorité du rapport : " priorite.apercu = "{objet.priorite}" priorite.aide_courte = \ "Entrez la |ent|priorité|ff| du rapport ou |cmd|/|ff| pour " \ "revenir à la fenêtre parente.\n\nPriorités disponibles : " \ "{}.\n\nPriorité actuelle : |bc|{{objet.priorite}}|ff|".format( ", ".join(priorites)) # Description description = self.ajouter_choix("description", "d", Description, \ rapport) description.parent = self description.apercu = "{objet.description.paragraphes_indentes}" description.aide_courte = \ "| |tit|" + "Description du rapport #{}".format( rapport.id).ljust(74) + \ "|ff||\n" + self.opts.separateur # Public public = self.ajouter_choix("public", "b", Flag, rapport, "public") public.parent = self # Statut statut = self.ajouter_choix("statut", "s", Choix, rapport, "statut", STATUTS) statut.parent = self statut.prompt = "Statut du rapport : " statut.apercu = "{objet.statut}" statut.aide_courte = \ "Entrez le |ent|statut|ff| du rapport ou |cmd|/|ff| pour " \ "revenir à la fenêtre parente.\n\nStatuts disponibles : " \ "{}.\n\nStatut actuel : |bc|{{objet.statut}}|ff|".format( ", ".join(STATUTS)) # Avancement avancement = self.ajouter_choix("avancement", "a", Entier, rapport, "avancement", 0, 100, "%") avancement.parent = self avancement.prompt = "Avancement de la tâche : " avancement.apercu = "{objet.avancement}" avancement.aide_courte = \ "Entrez l'|ent|avancement|ff| en pourcent de la tâche ou " \ "|cmd|/|ff| pour revenir à la\nfenêtre parente.\n\n" \ "Avancement actuel : |bc|{valeur}|ff|" # Assigné à assigne_a = self.ajouter_choix("assigné à", "i", EdtAssigne, rapport) assigne_a.parent = self assigne_a.prompt = "Entrez un nom de joueur : " assigne_a.apercu = "{objet.aff_assigne_a}" assigne_a.aide_courte = \ "Entrez un |ent|Immortel|ff| à qui assigner ce rapport, ou " \ "|cmd|/|ff| pour revenir à la\nfenêtre parente.\n\n" \ "Actuellement assigné à : {objet.aff_assigne_a}" # Supprimer sup = self.ajouter_choix("supprimer", "sup", NSupprimer, rapport) sup.parent = self sup.aide_courte = "Souhaitez-vous réellement supprimer " \ "le rapport #{} ?".format(rapport.id)

41.717514

79

0.641522

from primaires.interpreteur.editeur.presentation import Presentation from primaires.interpreteur.editeur.description import Description from primaires.interpreteur.editeur.uniligne import Uniligne from primaires.interpreteur.editeur.entier import Entier from primaires.interpreteur.editeur.choix import Choix from primaires.interpreteur.editeur.flag import Flag from .edt_assigne import EdtAssigne from .supprimer import NSupprimer from secondaires.rapport.constantes import * class EdtBugeditP(Presentation): nom = "bugedit+" def __init__(self, personnage, rapport): if personnage: instance_connexion = personnage.instance_connexion else: instance_connexion = None Presentation.__init__(self, instance_connexion, rapport) if personnage and rapport: self.construire(rapport) def __getnewargs__(self): return (None, None) def construire(self, rapport): titre = self.ajouter_choix("titre", "t", Uniligne, rapport, "titre") titre.parent = self titre.prompt = "Titre du rapport : " titre.apercu = "{objet.titre}" titre.aide_courte = \ "Entrez le |ent|titre|ff| du rapport ou |cmd|/|ff| pour revenir " \ "à la fenêtre parente.\n\nTitre actuel : |bc|{objet.titre}|ff|" types = sorted(TYPES) type = self.ajouter_choix("type", "y", Choix, rapport, "type", types) type.parent = self type.prompt = "Type de rapport : " type.apercu = "{objet.type}" type.aide_courte = \ "Entrez le |ent|type|ff| de rapport ou |cmd|/|ff| pour " \ "revenir à la fenêtre parente.\n\Types disponibles : " \ "{}.\n\Type actuel : |bc|{{objet.type}}|ff|".format( ", ".join(types)) categories = sorted(CATEGORIES) categorie = self.ajouter_choix("catégorie", "c", Choix, rapport, "categorie", categories) categorie.parent = self categorie.prompt = "Catégorie du rapport : " categorie.apercu = "{objet.categorie}" categorie.aide_courte = \ "Entrez la |ent|catégorie|ff| du rapport ou |cmd|/|ff| pour " \ "revenir à la fenêtre parente.\n\nCatégories disponibles : " \ "{}.\n\nCatégorie actuelle : |bc|{{objet.categorie}}|ff|".format( ", ".join(categories)) priorites = sorted(PRIORITES) priorite = self.ajouter_choix("priorité", "p", Choix, rapport, "priorite", priorites) priorite.parent = self priorite.prompt = "Priorité du rapport : " priorite.apercu = "{objet.priorite}" priorite.aide_courte = \ "Entrez la |ent|priorité|ff| du rapport ou |cmd|/|ff| pour " \ "revenir à la fenêtre parente.\n\nPriorités disponibles : " \ "{}.\n\nPriorité actuelle : |bc|{{objet.priorite}}|ff|".format( ", ".join(priorites)) description = self.ajouter_choix("description", "d", Description, \ rapport) description.parent = self description.apercu = "{objet.description.paragraphes_indentes}" description.aide_courte = \ "| |tit|" + "Description du rapport #{}".format( rapport.id).ljust(74) + \ "|ff||\n" + self.opts.separateur public = self.ajouter_choix("public", "b", Flag, rapport, "public") public.parent = self statut = self.ajouter_choix("statut", "s", Choix, rapport, "statut", STATUTS) statut.parent = self statut.prompt = "Statut du rapport : " statut.apercu = "{objet.statut}" statut.aide_courte = \ "Entrez le |ent|statut|ff| du rapport ou |cmd|/|ff| pour " \ "revenir à la fenêtre parente.\n\nStatuts disponibles : " \ "{}.\n\nStatut actuel : |bc|{{objet.statut}}|ff|".format( ", ".join(STATUTS)) avancement = self.ajouter_choix("avancement", "a", Entier, rapport, "avancement", 0, 100, "%") avancement.parent = self avancement.prompt = "Avancement de la tâche : " avancement.apercu = "{objet.avancement}" avancement.aide_courte = \ "Entrez l'|ent|avancement|ff| en pourcent de la tâche ou " \ "|cmd|/|ff| pour revenir à la\nfenêtre parente.\n\n" \ "Avancement actuel : |bc|{valeur}|ff|" # Assigné à assigne_a = self.ajouter_choix("assigné à", "i", EdtAssigne, rapport) assigne_a.parent = self assigne_a.prompt = "Entrez un nom de joueur : " assigne_a.apercu = "{objet.aff_assigne_a}" assigne_a.aide_courte = \ "Entrez un |ent|Immortel|ff| à qui assigner ce rapport, ou " \ "|cmd|/|ff| pour revenir à la\nfenêtre parente.\n\n" \ "Actuellement assigné à : {objet.aff_assigne_a}" # Supprimer sup = self.ajouter_choix("supprimer", "sup", NSupprimer, rapport) sup.parent = self sup.aide_courte = "Souhaitez-vous réellement supprimer " \ "le rapport #{} ?".format(rapport.id)

true

f704d794aec6ae8e930cc4290ff291c234e2423c

16,527

py

Python

privatmarket_service.py

dimonklas/robotForPull

71485ba9612be4cb8916aae4ed6ca183a0f490ba

[ "Apache-2.0" ]

null

privatmarket_service.py

dimonklas/robotForPull

71485ba9612be4cb8916aae4ed6ca183a0f490ba

[ "Apache-2.0" ]

null

privatmarket_service.py

dimonklas/robotForPull

71485ba9612be4cb8916aae4ed6ca183a0f490ba

[ "Apache-2.0" ]

null

# coding=utf-8 import os import sys from dateutil import parser from datetime import datetime from pytz import timezone import re import datetime import dateutil.parser from datetime import timedelta def modify_test_data(initial_data): # set user name # initial_data['procuringEntity']['name'] = u'Товариство З Обмеженою Відповідальністю \'Мак Медіа Прінт\'' initial_data['procuringEntity']['name'] = u'ТОВ \"СФ \"РУБІЖНЕ\"' if 'contactPoint' in initial_data['procuringEntity']: initial_data['procuringEntity']['contactPoint']['telephone'] = u'+380670444580' initial_data['procuringEntity']['contactPoint']['url'] = u'https://dadadad.com' initial_data['procuringEntity']['identifier']['legalName'] = u'ТОВАРИСТВО З ОБМЕЖЕНОЮ ВІДПОВІДАЛЬНІСТЮ \"СІЛЬСЬКОГОСПОДАРСЬКА ФІРМА \"РУБІЖНЕ\"' initial_data['procuringEntity']['identifier']['id'] = u'38580144' # # initial_data['buyers'][0]['identifier']['id'] = u'38580144' initial_data['buyers'][0]['identifier']['legalName'] = u'ТОВАРИСТВО З ОБМЕЖЕНОЮ ВІДПОВІДАЛЬНІСТЮ \"СІЛЬСЬКОГОСПОДАРСЬКА ФІРМА \"РУБІЖНЕ\"' initial_data['buyers'][0]['name'] = u'ТОВ \"СФ \"РУБІЖНЕ\"' initial_data['tender']['tenderPeriod']['startDate'] = add_day_to_date(initial_data['tender']['tenderPeriod']['startDate']) # initial_data['procuringEntity']['name'] = u'Макстрой Діск, Товариство З Обмеженою Відповідальністю' # initial_data['procuringEntity']['name'] = u'ФОП ОГАНІН ОЛЕКСАНДР ПЕТРОВИЧ' return initial_data def add_day_to_date(date): dat = parser.parse(date) new_date = (dat + timedelta(days=1)).strftime('%Y-%m-%dT%H:%M:%S%z') new = parser.parse(new_date).isoformat() return new def get_currency_type(currency): if isinstance(currency, str): currency = currency.decode("utf-8") currency_dictionary = { u'грн': 'UAH' } currency_type = currency_dictionary.get(currency) if currency_type: return currency_type else: return currency def get_month_number(month_name): monthes = [u"января", u"февраля", u"марта", u"апреля", u"мая", u"июня", u"июля", u"августа", u"сентября", u"октября", u"ноября", u"декабря", u"янв.", u"февр.", u"мар.", u"апр.", u"мая.", u"июн.", u"июл.", u"авг.", u"сент.", u"окт.", u"нояб.", u"дек.", u"січ.", u"лют.", u"бер.", u"квіт.", u"трав.", u"черв.", u"лип.", u"серп.", u"вер.", u"жовт.", u"лист.", u"груд.", u"січня", u"лютого", u"березня", u"квітня", u"травня", u"червня", u"липня", u"серпня", u"вересня", u"жовтня", u"листопада", u"грудня"] return monthes.index(month_name) % 12 + 1 def get_time_with_offset(date): date_obj = datetime.datetime.strptime(date, "%Y-%m-%d %H:%M") time_zone = timezone('Europe/Kiev') localized_date = time_zone.localize(date_obj) return localized_date.strftime('%Y-%m-%d %H:%M:%S.%f%z') # def get_time_with_offset_formatted(date, input_format_date, output_format): # date_obj = datetime.datetime.strptime(date, input_format_date) # time_zone = timezone('Europe/Kiev') # localized_date = time_zone.localize(date_obj) # return localized_date.strftime(output_format) def get_time_with_offset_formatted(date, input_format_date): tz = timezone('Europe/Kiev') date_obj = datetime.datetime.strptime(date, input_format_date) res = tz.localize(date_obj) result = res.isoformat() return result def get_current_date(): now = datetime.now() return now.strftime('%d-%m-%Y') def get_unit_code(name): dictionary = { u'кілограми': u'KGM', u'пара': u'PR', u'літр': u'LTR', u'набір': u'SET', u'пачок': u'NMP', u'метри': u'MTR', u'лот': u'LO', u'послуга': u'E48', u'метри кубічні': u'MTQ', u'ящик': u'BX', u'рейс': u'E54', u'тони': u'TNE', u'метри квадратні': u'MTK', u'кілометри': u'KMT', u'штуки': u'H87', u'місяць': u'MON', u'пачка': u'RM', u'упаковка': u'PK', u'гектар': u'HAR', u'блок': u'D64', u'Флакон': u'VI' } expected_name = dictionary.get(name) if expected_name: return expected_name else: return name def get_unit_name(current_name): if isinstance(current_name, str): current_name = current_name.decode("utf-8") dictionary = { u'кілограми': {u'килограмм', u'килограмма', u'килограммов'}, u'пара': {u'пара', u'пары', u'пар'}, u'літр': {u'литр', u'литра', u'литров'}, u'набір': {u'набор', u'набора', u'наборов'}, u'пачок': {u'пачка', u'пачек', u'пачки'}, u'метри': {u'метр', u'метра', u'метров'}, u'лот': {u'лот', u'лоты', u'лотов'}, u'послуга': {u'услуга', u'услуг', u'услуги'}, u'метри кубічні': {u'метр кубический', u'метра кубического', u'метров кубических'}, u'ящик': {u'ящик', u'ящика', u'ящиков'}, u'рейс': {u'рейс', u'рейса', u'рейсов'}, u'тони': {u'тонна', u'тонны', u'тонн'}, u'метри квадратні': {u'метр квадратный', u'метра квадратного', u'метров квадратных'}, u'кілометри': {u'километр', u'километров', u'километра'}, u'штуки': {u'штука', u'штуки', u'штук', u'Штуки'}, u'місяць': {u'месяц', u'месяца', u'месяцев'}, u'пачка': {u'пачка', u'пачек', u'пачкики'}, u'упаковка': {u'упаковка', u'упаковок', u'упаковки'}, u'гектар': {u'гектар', u'гектара', u'гектаров'}, u'блок': {u'блок', u'блока', u'блоков'} } expected_name = None dictionary.get(current_name) for name, variants in dictionary.iteritems(): if current_name in variants: expected_name = name if expected_name: return expected_name else: return current_name def get_unit_name_ru(current_name): if isinstance(current_name, str): current_name = current_name.decode("utf-8") dictionary = { u'килограмм': {u'килограмм', u'килограмма', u'килограммов', u'кілограми'}, u'пара': {u'пара', u'пары', u'пар'}, u'литр': {u'литр', u'литра', u'литров'}, u'набора': {u'набір', u'набора', u'наборов'}, u'пачек': {u'пачка', u'пачек', u'пачки'}, u'метр': {u'метр', u'метра', u'метров'}, u'лот': {u'лот', u'лоты', u'лотов'}, u'услуга': {u'услуга', u'услуг', u'услуги'}, u'метр .куб.': {u'метр кубический', u'метра кубического', u'метров кубических'}, u'ящик': {u'ящик', u'ящика', u'ящиков'}, u'рейс': {u'рейс', u'рейса', u'рейсов'}, u'тонны': {u'тонна', u'тонны', u'тонн'}, u'метр квадратный': {u'метр квадратный', u'метра квадратного', u'метров квадратных'}, u'километры': {u'километр', u'километров', u'километра'}, u'штуки': {u'штука', u'штуки', u'штук'}, u'месяц': {u'месяц', u'месяца', u'месяцев'}, u'пачка': {u'пачка', u'пачек', u'пачкики'}, u'упаковка': {u'упаковка', u'упаковок', u'упаковки'}, u'гектар': {u'гектар', u'гектара', u'гектаров'}, u'блок': {u'блок', u'блока', u'блоков'} } expected_name = None dictionary.get(current_name) for name, variants in dictionary.iteritems(): if current_name in variants: expected_name = name if expected_name: return expected_name else: return current_name def get_classification_type(classifications): classifications_dictionary = { u'ДК 016:2010': u'ДКПП', u'ДК 021:2015': u'CPV', u'ДК 18-2000': u'ДК018', u'ДК003: 2010': u'ДК003', u'ДК003:2010': u'ДК003', u'ДК 015-97': u'ДК015', u'ДК021': u'CPV' } classifications_type = classifications_dictionary.get(classifications) if classifications_type: return classifications_type else: return classifications def get_status_type(status_name): status_name = status_name.strip() type_dictionary = { u'Период уточнений': 'active.enquiries', u'Період уточнень': 'active.enquiries', u'Период уточнений завершен': 'active.enquiries.ended', u'Період уточнень завершено': 'active.enquiries.ended', u'Подача предложений': 'active.tendering', u'Подача пропозицій': 'active.tendering', u'Торги': 'active.auction', u'Квалификация победителя': 'active.qualification', u'Квалификація переможця': 'active.qualification', u'Предложения рассмотрены': 'active.awarded', u'Пропозиції розглянуті': 'active.awarded', u'Закупка не состоялась': 'unsuccessful', u'Закупівля не відбулась': 'unsuccessful', u'Завершено': 'complete', u'Отменено': 'cancelled', u'Відмінено': 'cancelled', u'Розглядається': 'pending', u'Кваліфікація учасника': 'active.pre-qualification', u'Пауза перед аукціоном': 'active.pre-qualification.stand-still', u'Прекваліфікація': 'active.pre-qualification', u'Преквалификация': 'active.pre-qualification' } type_name = type_dictionary.get(status_name) return type_name def convert_float_to_string(number): result = number if type(number) is float: return format(number, '.2f') else: return result def get_claim_status (status): type_dictionary = { u'Вiдправлено': 'claim', u'Отримано вiдповiдь': 'answered', u'Задоволено': 'resolved', u'Скасована': 'cancelled', u'Не вирiшена, обробляється': 'pending', u'Залишена без відповіді': 'ignored', u'Не задоволено': 'declined', u'Вимога відхилена': 'invalid', u'Запит для пiдтверждения скасування': 'stopping' } type_name = type_dictionary.get(status) return type_name def get_procurementMethod_Type (type): type_dictionary = { u'Конкурентний діалог з публікацією англійською мовою 1-ий етап': 'competitiveDialogueEU', u'Конкурентний діалог 1-ий етап': 'competitiveDialogueUA', u'Переговорна процедура для потреб оборони': 'aboveThresholdUA.defense', u'Укладання рамкової угоди': 'closeFrameworkAgreementUA', u'Допорогові закупівлі': 'belowThreshold', u'Переговорна процедура': 'negotiation', u'Звіт про укладений договір': 'reporting', u'Відкриті торги': 'aboveThresholdUA', u'Відкриті торги з публікацією англійською мовою': 'aboveThresholdEU', u'Відкриті торги для закупівлі енергосервісу': 'esco' } type_name = type_dictionary.get(type) return type_name def sum_of_numbers(number, value): number = int(number) + int(value) return number def abs_number(number): return abs(int(number)) def get_abs_item_index(lot_index, item_index, items_count): abs_index = ((int(lot_index)-1) * int(items_count)) + int(item_index) return abs_index def get_match_from_string(string, pattern, group): result = 'null'; p = re.compile(pattern) m = p.search(string) if p.search(string): return m.group(int(group)) return result def get_percent(value): value = value * 100 return format(value, '.0f') def get_conversion_to_int(value): return int(float(value)) def get_cause(cause_text): cause_dictionary = { u'Закупівля творів мистецтва або закупівля, пов’язана із захистом прав інтелектуальної власності, або укладення договору про закупівлю з переможцем архітектурного чи мистецького конкурсу': u'artContestIP', u'Відсутність конкуренції (у тому числі з технічних причин) на відповідному ринку, внаслідок чого договір про закупівлю може бути укладено лише з одним постачальником, завідсутності при цьому альтернативи': u'noCompetition', u'Нагальна потреба у здійсненні закупівлі у зв’язку з виникненням особливих економічних чи соціальних обставин, яка унеможливлює дотримання замовниками строків для проведення тендеру, а саме пов’язаних з негайною ліквідацією наслідків надзвичайних ситуацій, а також наданням у встановленому порядку Україною гуманітарної допомоги іншим державам. Застосування переговорної процедури закупівлі в таких випадках здійснюється за рішенням замовника щодо кожної процедури': u'quick', u'Якщо замовником було двічі відмінено тендер через відсутність достатньої кількостіучасників,прицьому предмет закупівлі, його технічні та якісніхарактеристики, атакож вимогидо учасника не повинні відрізнятисявід вимог, що були визначені замовникому тедерній документації': u'twiceUnsuccessful', u'Потреба здійснити додаткову закупівлю в того самого постачальника з метою уніфікації, стандартизації або забезпечення сумісності з наявними товарами, технологіями, роботами чи послугами, якщо заміна попереднього постачальника (виконавця робіт, надавача послуг) може призвести до несумісності або виникнення проблем технічного характеру,пов’язаних з експлуатацією та обслуговуванням': u'additionalPurchase', u'Необхідність проведення додаткових будівельних робіт, не зазначених у початковому проекті, але які стали через непередбачувані обставини необхідними для виконання проекту за сукупності таких умов: договір буде укладено з попереднім виконавцем цих робіт, такі роботи технічно чи економічно пов’язані з головним (первинним) договором; загальна вартість додаткових робіт не перевищує 50 відсотків вартості головного (первинного) договору': u'additionalConstruction', u'Закупівля юридичних послуг, пов’язаних із захистом прав та інтересів України, у тому числі з метою захисту національної безпеки і оборони, під час врегулювання спорів, розгляду в закордонних юрисдикційних органах справ за участю іноземного суб’єкта та України, на підставі рішення Кабінету Міністрів України або введених в дію відповідно до закону рішень Ради національної безпеки і оборони України': u'stateLegalServices' } cause_type = cause_dictionary.get(cause_text) if cause_type: return cause_type else: return cause_text def get_items_from_lot(items, lot_id): lot_items = [] for item in items: if item['relatedLot'] == lot_id: lot_items.append(item) return lot_items def get_ECP_key(path): return os.path.join(os.getcwd(), path) def get_date_formatting(date, format_day): return dateutil.parser.parse(date).date().strftime(format_day) def get_scenarios_name(): name = '' for param in sys.argv: if 'txt' in param: name = param return name def is_click_button(item_index, items_count, lot_index): status = 'false' if int(item_index) < int(items_count) and lot_index > 1: return 'true' return status def get_milestones_title(title): titles = { u'підписання договору': 'signingTheContract', u'поставка товару': 'deliveryOfGoods', u'дата подання заявки': 'submissionDateOfApplications', u'дата закінчення звітного періоду': 'endDateOfTheReportingPeriod', u'дата виставлення рахунку': 'dateOfInvoicing', u'виконання робіт': 'executionOfWorks', u'надання послуг': 'submittingServices', u'інша подія': 'anotherEvent' } title_name = titles.get(title) return title_name def get_milestones_code(code): codes = { u'Аванс': 'prepayment', u'Пiсляоплата': 'postpayment' } code_name = codes.get(code) return code_name def get_milestones_duration_type(type): types = { u'робочих': 'working', u'банківськіх': 'banking', u'календарних': 'calendar' } type_name = types.get(type) return type_name def get_rationaleType (type): type_dictionary = { u'Зменшення обсягів закупівлі': 'volumeCuts', u'Зміна сторонніх показників (курсу, тарифів...)': 'thirdParty', u'Зміна ціни у зв’язку із зміною ставок податків і зборів': 'taxRate', u'Покращення якості предмета закупівлі': 'qualityImprovement', u'Узгоджене зменшення ціни': 'priceReduction', u'Зміна ціни за одиницю товару': 'itemPriceVariation', u'Продовження строку дії договору на наступний рік': 'fiscalYearExtension', u'Продовження строку дії договору (черездокументально підтверджені об’єктивні обставини)': 'durationExtension', } type_name = type_dictionary.get(type) return type_name def change_fake_date(): return (datetime.datetime.now(timezone('Europe/Kiev')) + timedelta(days=3)).strftime('%Y-%m-%dT%H:%M:%S.%f%z')

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import os import sys from dateutil import parser from datetime import datetime from pytz import timezone import re import datetime import dateutil.parser from datetime import timedelta def modify_test_data(initial_data): initial_data['procuringEntity']['name'] = u'ТОВ \"СФ \"РУБІЖНЕ\"' if 'contactPoint' in initial_data['procuringEntity']: initial_data['procuringEntity']['contactPoint']['telephone'] = u'+380670444580' initial_data['procuringEntity']['contactPoint']['url'] = u'https://dadadad.com' initial_data['procuringEntity']['identifier']['legalName'] = u'ТОВАРИСТВО З ОБМЕЖЕНОЮ ВІДПОВІДАЛЬНІСТЮ \"СІЛЬСЬКОГОСПОДАРСЬКА ФІРМА \"РУБІЖНЕ\"' initial_data['procuringEntity']['identifier']['id'] = u'38580144' initial_data['buyers'][0]['identifier']['id'] = u'38580144' initial_data['buyers'][0]['identifier']['legalName'] = u'ТОВАРИСТВО З ОБМЕЖЕНОЮ ВІДПОВІДАЛЬНІСТЮ \"СІЛЬСЬКОГОСПОДАРСЬКА ФІРМА \"РУБІЖНЕ\"' initial_data['buyers'][0]['name'] = u'ТОВ \"СФ \"РУБІЖНЕ\"' initial_data['tender']['tenderPeriod']['startDate'] = add_day_to_date(initial_data['tender']['tenderPeriod']['startDate']) return initial_data def add_day_to_date(date): dat = parser.parse(date) new_date = (dat + timedelta(days=1)).strftime('%Y-%m-%dT%H:%M:%S%z') new = parser.parse(new_date).isoformat() return new def get_currency_type(currency): if isinstance(currency, str): currency = currency.decode("utf-8") currency_dictionary = { u'грн': 'UAH' } currency_type = currency_dictionary.get(currency) if currency_type: return currency_type else: return currency def get_month_number(month_name): monthes = [u"января", u"февраля", u"марта", u"апреля", u"мая", u"июня", u"июля", u"августа", u"сентября", u"октября", u"ноября", u"декабря", u"янв.", u"февр.", u"мар.", u"апр.", u"мая.", u"июн.", u"июл.", u"авг.", u"сент.", u"окт.", u"нояб.", u"дек.", u"січ.", u"лют.", u"бер.", u"квіт.", u"трав.", u"черв.", u"лип.", u"серп.", u"вер.", u"жовт.", u"лист.", u"груд.", u"січня", u"лютого", u"березня", u"квітня", u"травня", u"червня", u"липня", u"серпня", u"вересня", u"жовтня", u"листопада", u"грудня"] return monthes.index(month_name) % 12 + 1 def get_time_with_offset(date): date_obj = datetime.datetime.strptime(date, "%Y-%m-%d %H:%M") time_zone = timezone('Europe/Kiev') localized_date = time_zone.localize(date_obj) return localized_date.strftime('%Y-%m-%d %H:%M:%S.%f%z') def get_time_with_offset_formatted(date, input_format_date): tz = timezone('Europe/Kiev') date_obj = datetime.datetime.strptime(date, input_format_date) res = tz.localize(date_obj) result = res.isoformat() return result def get_current_date(): now = datetime.now() return now.strftime('%d-%m-%Y') def get_unit_code(name): dictionary = { u'кілограми': u'KGM', u'пара': u'PR', u'літр': u'LTR', u'набір': u'SET', u'пачок': u'NMP', u'метри': u'MTR', u'лот': u'LO', u'послуга': u'E48', u'метри кубічні': u'MTQ', u'ящик': u'BX', u'рейс': u'E54', u'тони': u'TNE', u'метри квадратні': u'MTK', u'кілометри': u'KMT', u'штуки': u'H87', u'місяць': u'MON', u'пачка': u'RM', u'упаковка': u'PK', u'гектар': u'HAR', u'блок': u'D64', u'Флакон': u'VI' } expected_name = dictionary.get(name) if expected_name: return expected_name else: return name def get_unit_name(current_name): if isinstance(current_name, str): current_name = current_name.decode("utf-8") dictionary = { u'кілограми': {u'килограмм', u'килограмма', u'килограммов'}, u'пара': {u'пара', u'пары', u'пар'}, u'літр': {u'литр', u'литра', u'литров'}, u'набір': {u'набор', u'набора', u'наборов'}, u'пачок': {u'пачка', u'пачек', u'пачки'}, u'метри': {u'метр', u'метра', u'метров'}, u'лот': {u'лот', u'лоты', u'лотов'}, u'послуга': {u'услуга', u'услуг', u'услуги'}, u'метри кубічні': {u'метр кубический', u'метра кубического', u'метров кубических'}, u'ящик': {u'ящик', u'ящика', u'ящиков'}, u'рейс': {u'рейс', u'рейса', u'рейсов'}, u'тони': {u'тонна', u'тонны', u'тонн'}, u'метри квадратні': {u'метр квадратный', u'метра квадратного', u'метров квадратных'}, u'кілометри': {u'километр', u'километров', u'километра'}, u'штуки': {u'штука', u'штуки', u'штук', u'Штуки'}, u'місяць': {u'месяц', u'месяца', u'месяцев'}, u'пачка': {u'пачка', u'пачек', u'пачкики'}, u'упаковка': {u'упаковка', u'упаковок', u'упаковки'}, u'гектар': {u'гектар', u'гектара', u'гектаров'}, u'блок': {u'блок', u'блока', u'блоков'} } expected_name = None dictionary.get(current_name) for name, variants in dictionary.iteritems(): if current_name in variants: expected_name = name if expected_name: return expected_name else: return current_name def get_unit_name_ru(current_name): if isinstance(current_name, str): current_name = current_name.decode("utf-8") dictionary = { u'килограмм': {u'килограмм', u'килограмма', u'килограммов', u'кілограми'}, u'пара': {u'пара', u'пары', u'пар'}, u'литр': {u'литр', u'литра', u'литров'}, u'набора': {u'набір', u'набора', u'наборов'}, u'пачек': {u'пачка', u'пачек', u'пачки'}, u'метр': {u'метр', u'метра', u'метров'}, u'лот': {u'лот', u'лоты', u'лотов'}, u'услуга': {u'услуга', u'услуг', u'услуги'}, u'метр .куб.': {u'метр кубический', u'метра кубического', u'метров кубических'}, u'ящик': {u'ящик', u'ящика', u'ящиков'}, u'рейс': {u'рейс', u'рейса', u'рейсов'}, u'тонны': {u'тонна', u'тонны', u'тонн'}, u'метр квадратный': {u'метр квадратный', u'метра квадратного', u'метров квадратных'}, u'километры': {u'километр', u'километров', u'километра'}, u'штуки': {u'штука', u'штуки', u'штук'}, u'месяц': {u'месяц', u'месяца', u'месяцев'}, u'пачка': {u'пачка', u'пачек', u'пачкики'}, u'упаковка': {u'упаковка', u'упаковок', u'упаковки'}, u'гектар': {u'гектар', u'гектара', u'гектаров'}, u'блок': {u'блок', u'блока', u'блоков'} } expected_name = None dictionary.get(current_name) for name, variants in dictionary.iteritems(): if current_name in variants: expected_name = name if expected_name: return expected_name else: return current_name def get_classification_type(classifications): classifications_dictionary = { u'ДК 016:2010': u'ДКПП', u'ДК 021:2015': u'CPV', u'ДК 18-2000': u'ДК018', u'ДК003: 2010': u'ДК003', u'ДК003:2010': u'ДК003', u'ДК 015-97': u'ДК015', u'ДК021': u'CPV' } classifications_type = classifications_dictionary.get(classifications) if classifications_type: return classifications_type else: return classifications def get_status_type(status_name): status_name = status_name.strip() type_dictionary = { u'Период уточнений': 'active.enquiries', u'Період уточнень': 'active.enquiries', u'Период уточнений завершен': 'active.enquiries.ended', u'Період уточнень завершено': 'active.enquiries.ended', u'Подача предложений': 'active.tendering', u'Подача пропозицій': 'active.tendering', u'Торги': 'active.auction', u'Квалификация победителя': 'active.qualification', u'Квалификація переможця': 'active.qualification', u'Предложения рассмотрены': 'active.awarded', u'Пропозиції розглянуті': 'active.awarded', u'Закупка не состоялась': 'unsuccessful', u'Закупівля не відбулась': 'unsuccessful', u'Завершено': 'complete', u'Отменено': 'cancelled', u'Відмінено': 'cancelled', u'Розглядається': 'pending', u'Кваліфікація учасника': 'active.pre-qualification', u'Пауза перед аукціоном': 'active.pre-qualification.stand-still', u'Прекваліфікація': 'active.pre-qualification', u'Преквалификация': 'active.pre-qualification' } type_name = type_dictionary.get(status_name) return type_name def convert_float_to_string(number): result = number if type(number) is float: return format(number, '.2f') else: return result def get_claim_status (status): type_dictionary = { u'Вiдправлено': 'claim', u'Отримано вiдповiдь': 'answered', u'Задоволено': 'resolved', u'Скасована': 'cancelled', u'Не вирiшена, обробляється': 'pending', u'Залишена без відповіді': 'ignored', u'Не задоволено': 'declined', u'Вимога відхилена': 'invalid', u'Запит для пiдтверждения скасування': 'stopping' } type_name = type_dictionary.get(status) return type_name def get_procurementMethod_Type (type): type_dictionary = { u'Конкурентний діалог з публікацією англійською мовою 1-ий етап': 'competitiveDialogueEU', u'Конкурентний діалог 1-ий етап': 'competitiveDialogueUA', u'Переговорна процедура для потреб оборони': 'aboveThresholdUA.defense', u'Укладання рамкової угоди': 'closeFrameworkAgreementUA', u'Допорогові закупівлі': 'belowThreshold', u'Переговорна процедура': 'negotiation', u'Звіт про укладений договір': 'reporting', u'Відкриті торги': 'aboveThresholdUA', u'Відкриті торги з публікацією англійською мовою': 'aboveThresholdEU', u'Відкриті торги для закупівлі енергосервісу': 'esco' } type_name = type_dictionary.get(type) return type_name def sum_of_numbers(number, value): number = int(number) + int(value) return number def abs_number(number): return abs(int(number)) def get_abs_item_index(lot_index, item_index, items_count): abs_index = ((int(lot_index)-1) * int(items_count)) + int(item_index) return abs_index def get_match_from_string(string, pattern, group): result = 'null'; p = re.compile(pattern) m = p.search(string) if p.search(string): return m.group(int(group)) return result def get_percent(value): value = value * 100 return format(value, '.0f') def get_conversion_to_int(value): return int(float(value)) def get_cause(cause_text): cause_dictionary = { u'Закупівля творів мистецтва або закупівля, пов’язана із захистом прав інтелектуальної власності, або укладення договору про закупівлю з переможцем архітектурного чи мистецького конкурсу': u'artContestIP', u'Відсутність конкуренції (у тому числі з технічних причин) на відповідному ринку, внаслідок чого договір про закупівлю може бути укладено лише з одним постачальником, завідсутності при цьому альтернативи': u'noCompetition', u'Нагальна потреба у здійсненні закупівлі у зв’язку з виникненням особливих економічних чи соціальних обставин, яка унеможливлює дотримання замовниками строків для проведення тендеру, а саме пов’язаних з негайною ліквідацією наслідків надзвичайних ситуацій, а також наданням у встановленому порядку Україною гуманітарної допомоги іншим державам. Застосування переговорної процедури закупівлі в таких випадках здійснюється за рішенням замовника щодо кожної процедури': u'quick', u'Якщо замовником було двічі відмінено тендер через відсутність достатньої кількостіучасників,прицьому предмет закупівлі, його технічні та якісніхарактеристики, атакож вимогидо учасника не повинні відрізнятисявід вимог, що були визначені замовникому тедерній документації': u'twiceUnsuccessful', u'Потреба здійснити додаткову закупівлю в того самого постачальника з метою уніфікації, стандартизації або забезпечення сумісності з наявними товарами, технологіями, роботами чи послугами, якщо заміна попереднього постачальника (виконавця робіт, надавача послуг) може призвести до несумісності або виникнення проблем технічного характеру,пов’язаних з експлуатацією та обслуговуванням': u'additionalPurchase', u'Необхідність проведення додаткових будівельних робіт, не зазначених у початковому проекті, але які стали через непередбачувані обставини необхідними для виконання проекту за сукупності таких умов: договір буде укладено з попереднім виконавцем цих робіт, такі роботи технічно чи економічно пов’язані з головним (первинним) договором; загальна вартість додаткових робіт не перевищує 50 відсотків вартості головного (первинного) договору': u'additionalConstruction', u'Закупівля юридичних послуг, пов’язаних із захистом прав та інтересів України, у тому числі з метою захисту національної безпеки і оборони, під час врегулювання спорів, розгляду в закордонних юрисдикційних органах справ за участю іноземного суб’єкта та України, на підставі рішення Кабінету Міністрів України або введених в дію відповідно до закону рішень Ради національної безпеки і оборони України': u'stateLegalServices' } cause_type = cause_dictionary.get(cause_text) if cause_type: return cause_type else: return cause_text def get_items_from_lot(items, lot_id): lot_items = [] for item in items: if item['relatedLot'] == lot_id: lot_items.append(item) return lot_items def get_ECP_key(path): return os.path.join(os.getcwd(), path) def get_date_formatting(date, format_day): return dateutil.parser.parse(date).date().strftime(format_day) def get_scenarios_name(): name = '' for param in sys.argv: if 'txt' in param: name = param return name def is_click_button(item_index, items_count, lot_index): status = 'false' if int(item_index) < int(items_count) and lot_index > 1: return 'true' return status def get_milestones_title(title): titles = { u'підписання договору': 'signingTheContract', u'поставка товару': 'deliveryOfGoods', u'дата подання заявки': 'submissionDateOfApplications', u'дата закінчення звітного періоду': 'endDateOfTheReportingPeriod', u'дата виставлення рахунку': 'dateOfInvoicing', u'виконання робіт': 'executionOfWorks', u'надання послуг': 'submittingServices', u'інша подія': 'anotherEvent' } title_name = titles.get(title) return title_name def get_milestones_code(code): codes = { u'Аванс': 'prepayment', u'Пiсляоплата': 'postpayment' } code_name = codes.get(code) return code_name def get_milestones_duration_type(type): types = { u'робочих': 'working', u'банківськіх': 'banking', u'календарних': 'calendar' } type_name = types.get(type) return type_name def get_rationaleType (type): type_dictionary = { u'Зменшення обсягів закупівлі': 'volumeCuts', u'Зміна сторонніх показників (курсу, тарифів...)': 'thirdParty', u'Зміна ціни у зв’язку із зміною ставок податків і зборів': 'taxRate', u'Покращення якості предмета закупівлі': 'qualityImprovement', u'Узгоджене зменшення ціни': 'priceReduction', u'Зміна ціни за одиницю товару': 'itemPriceVariation', u'Продовження строку дії договору на наступний рік': 'fiscalYearExtension', u'Продовження строку дії договору (черездокументально підтверджені об’єктивні обставини)': 'durationExtension', } type_name = type_dictionary.get(type) return type_name def change_fake_date(): return (datetime.datetime.now(timezone('Europe/Kiev')) + timedelta(days=3)).strftime('%Y-%m-%dT%H:%M:%S.%f%z')

true

f704d8c0caad083f0db74121655533699125a844

22,237

py

Python

test/input_gen/genModelsRecurrent_v2.py

corner4world/nntrainer

0f342e8f2a1ec95b4e712aa3390b21cf0ea4efae

[ "Apache-2.0" ]

null

test/input_gen/genModelsRecurrent_v2.py

corner4world/nntrainer

0f342e8f2a1ec95b4e712aa3390b21cf0ea4efae

[ "Apache-2.0" ]

null

test/input_gen/genModelsRecurrent_v2.py

corner4world/nntrainer

0f342e8f2a1ec95b4e712aa3390b21cf0ea4efae

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 # SPDX-License-Identifier: Apache-2.0 ## # Copyright (C) 2021 Jihoon Lee <jhoon.it.lee@samsung.com> # # @file genModelsRecurrent_v2.py # @date 19 October 2021 # @brief Generate recurrent model tcs # @author Jihoon lee <jhoon.it.lee@samsung.com> from recorder_v2 import record_v2, inspect_file from zoneout import Zoneout import torch class FCUnroll(torch.nn.Module): def __init__(self, unroll_for=1, num_fc=1): super().__init__() self.fcs = torch.nn.ModuleList([torch.nn.Linear(1, 1) for i in range(num_fc)]) self.unroll_for = unroll_for # self.loss = torch.nn.MSELoss() self.loss = torch.nn.Identity() def forward(self, inputs, labels): output = inputs[0] for i in range(self.unroll_for): for fc in self.fcs: output = fc(output) loss = self.loss(output) # loss = self.loss(output, labels[0]) return output, loss class RNNCellStacked(torch.nn.Module): def __init__(self, unroll_for=1, num_rnn=1, input_size=1, hidden_size=1): super().__init__() self.rnns = torch.nn.ModuleList( [ torch.nn.RNNCell(input_size, hidden_size) for _ in range(num_rnn) ] ) self.unroll_for = unroll_for self.loss = torch.nn.MSELoss() def forward(self, inputs, labels): hs = [torch.zeros_like(inputs[0]) for _ in self.rnns] out = inputs[0] ret = [] for _ in range(self.unroll_for): for i, rnn in enumerate(self.rnns): hs[i] = rnn(out, hs[i]) out = hs[i] ret.append(out) ret = torch.stack(ret, dim=1) loss = self.loss(ret, labels[0]) return ret, loss class LSTMStacked(torch.nn.Module): def __init__(self, num_lstm=1, bidirectional=False): super().__init__() self.input_size = self.hidden_size = 2 self.num_lstm = num_lstm self.bidirectional=bidirectional self.lstms = torch.nn.ModuleList( [ torch.nn.LSTM(self.input_size if self.bidirectional == False or i == 0 else 2 * self.input_size, self.hidden_size, batch_first=True, bidirectional=bidirectional) # Intended comment # torch.nn.LSTM(self.input_size if self.bidirectional == False or i == 0 else 2 * self.input_size, self.hidden_size, num_layers=num_lstm, batch_first=True, bidirectional=bidirectional) for i in range(num_lstm) ] ) self.loss = torch.nn.MSELoss() def forward(self, inputs, labels): out = inputs[0] states = inputs[1:] # hs = [states[2 * i] for i in range(self.num_lstm)] hs = [torch.zeros((2, 3, 2)) if self.bidirectional else torch.zeros((1, 3, 2)) for _ in range(self.num_lstm)] # cs = [states[2 * i + 1] for i in range(self.num_lstm)] cs = [torch.zeros((2, 3, 2)) if self.bidirectional else torch.zeros((1, 3, 2)) for _ in range(self.num_lstm)] for i, (lstm, h, c) in enumerate(zip(self.lstms, hs, cs)): out, (hs[i], cs[i]) = lstm(out, (h, c)) loss = self.loss(out, labels[0]) return out, loss class LSTMCellStacked(torch.nn.Module): def __init__(self, unroll_for=2, num_lstmcell=1): super().__init__() self.input_size = self.hidden_size = 2 self.lstmcells = torch.nn.ModuleList( [ torch.nn.LSTMCell(self.input_size, self.hidden_size) for _ in range(num_lstmcell) ] ) self.unroll_for = unroll_for self.num_lstmcell = num_lstmcell self.loss = torch.nn.MSELoss() def forward(self, inputs, labels): out = inputs[0] states = inputs[1:] hs = [states[2 * i] for i in range(self.num_lstmcell)] cs = [states[2 * i + 1] for i in range(self.num_lstmcell)] ret = [] for _ in range(self.unroll_for): for i, (lstm, h, c) in enumerate(zip(self.lstmcells, hs, cs)): hs[i], cs[i] = lstm(out, (h, c)) out = hs[i] ret.append(out) ret = torch.stack(ret, dim=1) loss = self.loss(ret, labels[0]) return ret, loss class ZoneoutLSTMStacked(torch.nn.Module): def __init__(self, batch_size=3, unroll_for=2, num_lstm=1, hidden_state_zoneout_rate=1, cell_state_zoneout_rate=1): super().__init__() self.input_size = self.hidden_size = 2 self.cell_state_zoneout_rate = cell_state_zoneout_rate self.zoneout_lstms = torch.nn.ModuleList( [ Zoneout(batch_size, self.input_size, self.hidden_size, unroll_for, hidden_state_zoneout_rate, cell_state_zoneout_rate) for _ in range(num_lstm) ] ) self.unroll_for = unroll_for self.num_lstm = num_lstm self.loss = torch.nn.MSELoss() def forward(self, inputs, labels): out = inputs[0] states = inputs[1:] hs = [states[2 * i] for i in range(self.num_lstm)] cs = [states[2 * i + 1] for i in range(self.num_lstm)] ret = [] for num_unroll in range(self.unroll_for): for i, (zoneout_lstm, h, c) in enumerate(zip(self.zoneout_lstms, hs, cs)): hs[i], cs[i] = zoneout_lstm(out, (h, c, num_unroll)) out = hs[i] ret.append(out) ret = torch.stack(ret, dim=1) loss = self.loss(ret, labels[0]) return ret, loss class GRUCellStacked(torch.nn.Module): def __init__(self, unroll_for=2, num_grucell=1): super().__init__() self.input_size = self.hidden_size = 2 self.grus = torch.nn.ModuleList( [ torch.nn.GRUCell(self.input_size, self.hidden_size, bias=True) for _ in range(num_grucell) ] ) self.unroll_for = unroll_for self.loss = torch.nn.MSELoss() def forward(self, inputs, labels): out = inputs[0] hs = inputs[1:] ret = [] for _ in range(self.unroll_for): for i, (gru, h) in enumerate(zip(self.grus, hs)): hs[i] = gru(out, h) out = hs[i] ret.append(out) ret = torch.stack(ret, dim=1) loss = self.loss(ret, labels[0]) return ret, loss if __name__ == "__main__": record_v2( FCUnroll(unroll_for=5), iteration=2, input_dims=[(1,)], label_dims=[(1,)], name="fc_unroll_single", ) record_v2( FCUnroll(unroll_for=2, num_fc=2), iteration=2, input_dims=[(1,)], label_dims=[(1,)], name="fc_unroll_stacked", ) record_v2( FCUnroll(unroll_for=2, num_fc=2), iteration=2, input_dims=[(1,)], label_dims=[(1,)], name="fc_unroll_stacked_clipped", clip=True ) record_v2( RNNCellStacked(unroll_for=2, num_rnn=1, input_size=2, hidden_size=2), iteration=2, input_dims=[(3, 2)], label_dims=[(3, 2, 2)], name="rnncell_single", ) record_v2( RNNCellStacked(unroll_for=2, num_rnn=2, input_size=2, hidden_size=2), iteration=2, input_dims=[(3, 2)], label_dims=[(3, 2, 2)], name="rnncell_stacked", ) unroll_for, num_lstm, batch_size, unit, feature_size, iteration, bidirectional = [2, 1, 3, 2, 2, 2, False] record_v2( LSTMStacked(num_lstm=num_lstm, bidirectional=bidirectional), iteration=iteration, input_dims=[(batch_size, unroll_for, feature_size)], # input_dims=[(batch_size, unroll_for, feature_size)] + [(1, batch_size, unit) for _ in range(2 * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="lstm_single", ) unroll_for, num_lstm, batch_size, unit, feature_size, iteration, bidirectional = [2, 2, 3, 2, 2, 2, False] record_v2( LSTMStacked(num_lstm=num_lstm, bidirectional=bidirectional), iteration=iteration, input_dims=[(batch_size, unroll_for, feature_size)], # input_dims=[(batch_size, unroll_for, feature_size)] + [(1, batch_size, unit) for _ in range(2 * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="lstm_stacked", ) unroll_for, num_lstm, batch_size, unit, feature_size, iteration, bidirectional = [2, 1, 3, 2, 2, 2, True] record_v2( LSTMStacked(num_lstm=num_lstm, bidirectional=bidirectional), iteration=iteration, input_dims=[(batch_size, unroll_for, feature_size)], # input_dims=[(batch_size, unroll_for, feature_size)] + [(2, batch_size, unit) for _ in range(2 * num_lstm)], label_dims=[(batch_size, unroll_for, 2 * unit)], name="bidirectional_lstm_single", ) unroll_for, num_lstm, batch_size, unit, feature_size, iteration, bidirectional = [2, 2, 3, 2, 2, 2, True] record_v2( LSTMStacked(num_lstm=num_lstm, bidirectional=bidirectional), iteration=iteration, input_dims=[(batch_size, unroll_for, feature_size)], # input_dims=[(batch_size, unroll_for, feature_size)] + [(2, batch_size, unit) for _ in range(2 * num_lstm)], label_dims=[(batch_size, unroll_for, 2 * unit)], name="bidirectional_lstm_stacked", ) unroll_for, num_lstmcell, state_num, batch_size, unit, feature_size, iteration = [2, 1, 2, 3, 2, 2, 2] record_v2( LSTMCellStacked(unroll_for=unroll_for, num_lstmcell=num_lstmcell), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstmcell)], label_dims=[(batch_size, unroll_for, unit)], name="lstmcell_single", ) unroll_for, num_lstmcell, state_num, batch_size, unit, feature_size, iteration = [2, 2, 2, 3, 2, 2, 2] record_v2( LSTMCellStacked(unroll_for=unroll_for, num_lstmcell=num_lstmcell), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstmcell)], label_dims=[(batch_size, unroll_for, unit)], name="lstmcell_stacked", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 0.0, 0.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_000_000", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 0.0, 0.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_000_000", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 0.5, 0.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_050_000", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 0.5, 0.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_050_000", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 1.0, 0.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_100_000", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 1.0, 0.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_100_000", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 0.0, 0.5] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_000_050", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 0.0, 0.5] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_000_050", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 0.5, 0.5] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_050_050", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 0.5, 0.5] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_050_050", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 1.0, 0.5] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_100_050", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 1.0, 0.5] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_100_050", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 0.0, 1.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_000_100", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 0.0, 1.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_000_100", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 0.5, 1.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_050_100", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 0.5, 1.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_050_100", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 1.0, 1.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_100_100", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 1.0, 1.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_100_100", ) unroll_for, num_grucell, batch_size, unit, feature_size, iteration, = [2, 1, 3, 2, 2, 2] record_v2( GRUCellStacked(unroll_for=unroll_for, num_grucell=num_grucell), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(num_grucell)], label_dims=[(batch_size, unroll_for, unit)], name="grucell_single", ) unroll_for, num_grucell, batch_size, unit, feature_size, iteration, = [2, 2, 3, 2, 2, 2] record_v2( GRUCellStacked(unroll_for=unroll_for, num_grucell=num_grucell), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(num_grucell)], label_dims=[(batch_size, unroll_for, unit)], name="grucell_stacked", ) # inspect_file("lstm_single.nnmodelgolden")

48.765351

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0.672168

from recorder_v2 import record_v2, inspect_file from zoneout import Zoneout import torch class FCUnroll(torch.nn.Module): def __init__(self, unroll_for=1, num_fc=1): super().__init__() self.fcs = torch.nn.ModuleList([torch.nn.Linear(1, 1) for i in range(num_fc)]) self.unroll_for = unroll_for self.loss = torch.nn.Identity() def forward(self, inputs, labels): output = inputs[0] for i in range(self.unroll_for): for fc in self.fcs: output = fc(output) loss = self.loss(output) return output, loss class RNNCellStacked(torch.nn.Module): def __init__(self, unroll_for=1, num_rnn=1, input_size=1, hidden_size=1): super().__init__() self.rnns = torch.nn.ModuleList( [ torch.nn.RNNCell(input_size, hidden_size) for _ in range(num_rnn) ] ) self.unroll_for = unroll_for self.loss = torch.nn.MSELoss() def forward(self, inputs, labels): hs = [torch.zeros_like(inputs[0]) for _ in self.rnns] out = inputs[0] ret = [] for _ in range(self.unroll_for): for i, rnn in enumerate(self.rnns): hs[i] = rnn(out, hs[i]) out = hs[i] ret.append(out) ret = torch.stack(ret, dim=1) loss = self.loss(ret, labels[0]) return ret, loss class LSTMStacked(torch.nn.Module): def __init__(self, num_lstm=1, bidirectional=False): super().__init__() self.input_size = self.hidden_size = 2 self.num_lstm = num_lstm self.bidirectional=bidirectional self.lstms = torch.nn.ModuleList( [ torch.nn.LSTM(self.input_size if self.bidirectional == False or i == 0 else 2 * self.input_size, self.hidden_size, batch_first=True, bidirectional=bidirectional) for i in range(num_lstm) ] ) self.loss = torch.nn.MSELoss() def forward(self, inputs, labels): out = inputs[0] states = inputs[1:] hs = [torch.zeros((2, 3, 2)) if self.bidirectional else torch.zeros((1, 3, 2)) for _ in range(self.num_lstm)] cs = [torch.zeros((2, 3, 2)) if self.bidirectional else torch.zeros((1, 3, 2)) for _ in range(self.num_lstm)] for i, (lstm, h, c) in enumerate(zip(self.lstms, hs, cs)): out, (hs[i], cs[i]) = lstm(out, (h, c)) loss = self.loss(out, labels[0]) return out, loss class LSTMCellStacked(torch.nn.Module): def __init__(self, unroll_for=2, num_lstmcell=1): super().__init__() self.input_size = self.hidden_size = 2 self.lstmcells = torch.nn.ModuleList( [ torch.nn.LSTMCell(self.input_size, self.hidden_size) for _ in range(num_lstmcell) ] ) self.unroll_for = unroll_for self.num_lstmcell = num_lstmcell self.loss = torch.nn.MSELoss() def forward(self, inputs, labels): out = inputs[0] states = inputs[1:] hs = [states[2 * i] for i in range(self.num_lstmcell)] cs = [states[2 * i + 1] for i in range(self.num_lstmcell)] ret = [] for _ in range(self.unroll_for): for i, (lstm, h, c) in enumerate(zip(self.lstmcells, hs, cs)): hs[i], cs[i] = lstm(out, (h, c)) out = hs[i] ret.append(out) ret = torch.stack(ret, dim=1) loss = self.loss(ret, labels[0]) return ret, loss class ZoneoutLSTMStacked(torch.nn.Module): def __init__(self, batch_size=3, unroll_for=2, num_lstm=1, hidden_state_zoneout_rate=1, cell_state_zoneout_rate=1): super().__init__() self.input_size = self.hidden_size = 2 self.cell_state_zoneout_rate = cell_state_zoneout_rate self.zoneout_lstms = torch.nn.ModuleList( [ Zoneout(batch_size, self.input_size, self.hidden_size, unroll_for, hidden_state_zoneout_rate, cell_state_zoneout_rate) for _ in range(num_lstm) ] ) self.unroll_for = unroll_for self.num_lstm = num_lstm self.loss = torch.nn.MSELoss() def forward(self, inputs, labels): out = inputs[0] states = inputs[1:] hs = [states[2 * i] for i in range(self.num_lstm)] cs = [states[2 * i + 1] for i in range(self.num_lstm)] ret = [] for num_unroll in range(self.unroll_for): for i, (zoneout_lstm, h, c) in enumerate(zip(self.zoneout_lstms, hs, cs)): hs[i], cs[i] = zoneout_lstm(out, (h, c, num_unroll)) out = hs[i] ret.append(out) ret = torch.stack(ret, dim=1) loss = self.loss(ret, labels[0]) return ret, loss class GRUCellStacked(torch.nn.Module): def __init__(self, unroll_for=2, num_grucell=1): super().__init__() self.input_size = self.hidden_size = 2 self.grus = torch.nn.ModuleList( [ torch.nn.GRUCell(self.input_size, self.hidden_size, bias=True) for _ in range(num_grucell) ] ) self.unroll_for = unroll_for self.loss = torch.nn.MSELoss() def forward(self, inputs, labels): out = inputs[0] hs = inputs[1:] ret = [] for _ in range(self.unroll_for): for i, (gru, h) in enumerate(zip(self.grus, hs)): hs[i] = gru(out, h) out = hs[i] ret.append(out) ret = torch.stack(ret, dim=1) loss = self.loss(ret, labels[0]) return ret, loss if __name__ == "__main__": record_v2( FCUnroll(unroll_for=5), iteration=2, input_dims=[(1,)], label_dims=[(1,)], name="fc_unroll_single", ) record_v2( FCUnroll(unroll_for=2, num_fc=2), iteration=2, input_dims=[(1,)], label_dims=[(1,)], name="fc_unroll_stacked", ) record_v2( FCUnroll(unroll_for=2, num_fc=2), iteration=2, input_dims=[(1,)], label_dims=[(1,)], name="fc_unroll_stacked_clipped", clip=True ) record_v2( RNNCellStacked(unroll_for=2, num_rnn=1, input_size=2, hidden_size=2), iteration=2, input_dims=[(3, 2)], label_dims=[(3, 2, 2)], name="rnncell_single", ) record_v2( RNNCellStacked(unroll_for=2, num_rnn=2, input_size=2, hidden_size=2), iteration=2, input_dims=[(3, 2)], label_dims=[(3, 2, 2)], name="rnncell_stacked", ) unroll_for, num_lstm, batch_size, unit, feature_size, iteration, bidirectional = [2, 1, 3, 2, 2, 2, False] record_v2( LSTMStacked(num_lstm=num_lstm, bidirectional=bidirectional), iteration=iteration, input_dims=[(batch_size, unroll_for, feature_size)], label_dims=[(batch_size, unroll_for, unit)], name="lstm_single", ) unroll_for, num_lstm, batch_size, unit, feature_size, iteration, bidirectional = [2, 2, 3, 2, 2, 2, False] record_v2( LSTMStacked(num_lstm=num_lstm, bidirectional=bidirectional), iteration=iteration, input_dims=[(batch_size, unroll_for, feature_size)], label_dims=[(batch_size, unroll_for, unit)], name="lstm_stacked", ) unroll_for, num_lstm, batch_size, unit, feature_size, iteration, bidirectional = [2, 1, 3, 2, 2, 2, True] record_v2( LSTMStacked(num_lstm=num_lstm, bidirectional=bidirectional), iteration=iteration, input_dims=[(batch_size, unroll_for, feature_size)], label_dims=[(batch_size, unroll_for, 2 * unit)], name="bidirectional_lstm_single", ) unroll_for, num_lstm, batch_size, unit, feature_size, iteration, bidirectional = [2, 2, 3, 2, 2, 2, True] record_v2( LSTMStacked(num_lstm=num_lstm, bidirectional=bidirectional), iteration=iteration, input_dims=[(batch_size, unroll_for, feature_size)], label_dims=[(batch_size, unroll_for, 2 * unit)], name="bidirectional_lstm_stacked", ) unroll_for, num_lstmcell, state_num, batch_size, unit, feature_size, iteration = [2, 1, 2, 3, 2, 2, 2] record_v2( LSTMCellStacked(unroll_for=unroll_for, num_lstmcell=num_lstmcell), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstmcell)], label_dims=[(batch_size, unroll_for, unit)], name="lstmcell_single", ) unroll_for, num_lstmcell, state_num, batch_size, unit, feature_size, iteration = [2, 2, 2, 3, 2, 2, 2] record_v2( LSTMCellStacked(unroll_for=unroll_for, num_lstmcell=num_lstmcell), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstmcell)], label_dims=[(batch_size, unroll_for, unit)], name="lstmcell_stacked", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 0.0, 0.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_000_000", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 0.0, 0.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_000_000", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 0.5, 0.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_050_000", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 0.5, 0.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_050_000", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 1.0, 0.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_100_000", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 1.0, 0.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_100_000", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 0.0, 0.5] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_000_050", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 0.0, 0.5] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_000_050", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 0.5, 0.5] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_050_050", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 0.5, 0.5] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_050_050", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 1.0, 0.5] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_100_050", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 1.0, 0.5] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_100_050", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 0.0, 1.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_000_100", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 0.0, 1.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_000_100", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 0.5, 1.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_050_100", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 0.5, 1.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_050_100", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 1, 2, 1, 2, 2, 2, 1.0, 1.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_single_100_100", ) unroll_for, num_lstm, state_num, batch_size, unit, feature_size, iteration, hidden_state_zoneout_rate, cell_state_zoneout_rate = [2, 2, 2, 1, 2, 2, 2, 1.0, 1.0] record_v2( ZoneoutLSTMStacked(batch_size=batch_size, unroll_for=unroll_for, num_lstm=num_lstm, hidden_state_zoneout_rate=hidden_state_zoneout_rate, cell_state_zoneout_rate=cell_state_zoneout_rate), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(state_num * num_lstm)], label_dims=[(batch_size, unroll_for, unit)], name="zoneout_lstm_stacked_100_100", ) unroll_for, num_grucell, batch_size, unit, feature_size, iteration, = [2, 1, 3, 2, 2, 2] record_v2( GRUCellStacked(unroll_for=unroll_for, num_grucell=num_grucell), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(num_grucell)], label_dims=[(batch_size, unroll_for, unit)], name="grucell_single", ) unroll_for, num_grucell, batch_size, unit, feature_size, iteration, = [2, 2, 3, 2, 2, 2] record_v2( GRUCellStacked(unroll_for=unroll_for, num_grucell=num_grucell), iteration=iteration, input_dims=[(batch_size, feature_size)] + [(batch_size, unit) for _ in range(num_grucell)], label_dims=[(batch_size, unroll_for, unit)], name="grucell_stacked", )

true

f704d925011146519241475ec5938c87167815a6

1,196

py

Python

main.py

nikolabebic95/MaterialUiColorsScss

8f03999534424a84baca5bfd0031b90cf0cca0ae

[ "MIT" ]

null

main.py

nikolabebic95/MaterialUiColorsScss

8f03999534424a84baca5bfd0031b90cf0cca0ae

[ "MIT" ]

null

main.py

nikolabebic95/MaterialUiColorsScss

8f03999534424a84baca5bfd0031b90cf0cca0ae

[ "MIT" ]

null

import json import pathlib import urllib.request def main(): # https://gist.github.com/kawanet/a880c83f06d6baf742e45ac9ac52af96 url = 'https://gist.githubusercontent.com/kawanet/a880c83f06d6baf742e45ac9ac52af96/raw' \ '/b4fbc9a730394eb977277e73cc37b60955463f21/material-colors.json' json_file_name = 'material-colors.json' urllib.request.urlretrieve(url, json_file_name) with open(json_file_name, 'r') as json_file: colors = json.load(json_file) out_dir_name = 'material_ui_colors' pathlib.Path(out_dir_name).mkdir(exist_ok=True) for color in colors: with open(out_dir_name + '/_' + color + '.scss', 'w') as out_file: shades = colors[color] out = ['$material_ui_' + color + '_' + shade + ': ' + value + ';\n' for shade, value in shades.items()] out.append('$material_ui_' + color + ': $material_ui_' + color + '_500;') out_file.writelines(out) with open(out_dir_name + '/_main.scss', 'w') as out_main_file: out = ['@import "' + color + '";\n' for color in colors] out_main_file.writelines(out) if __name__ == '__main__': main()

37.375

116

0.637124

import json import pathlib import urllib.request def main(): url = 'https://gist.githubusercontent.com/kawanet/a880c83f06d6baf742e45ac9ac52af96/raw' \ '/b4fbc9a730394eb977277e73cc37b60955463f21/material-colors.json' json_file_name = 'material-colors.json' urllib.request.urlretrieve(url, json_file_name) with open(json_file_name, 'r') as json_file: colors = json.load(json_file) out_dir_name = 'material_ui_colors' pathlib.Path(out_dir_name).mkdir(exist_ok=True) for color in colors: with open(out_dir_name + '/_' + color + '.scss', 'w') as out_file: shades = colors[color] out = ['$material_ui_' + color + '_' + shade + ': ' + value + ';\n' for shade, value in shades.items()] out.append('$material_ui_' + color + ': $material_ui_' + color + '_500;') out_file.writelines(out) with open(out_dir_name + '/_main.scss', 'w') as out_main_file: out = ['@import "' + color + '";\n' for color in colors] out_main_file.writelines(out) if __name__ == '__main__': main()

true

f704d9ac6d70bd3e4025d4307a92b148575602ac

345

py

Python

bnn_mcmc_examples/examples/mlp/pima/setting1/hmc/sampler.py

papamarkou/bnn_mcmc_examples

7bb4ecfb33db4c30a8e61e31f528bda0efb24e3d

[ "MIT" ]

1

2021-09-09T15:55:37.000Z

bnn_mcmc_examples/examples/mlp/pima/setting1/hmc/sampler.py

kushagragpt99/bnn_mcmc_examples

297cdb1e74335860989bebdb4ff6f6322b6adc06

[ "MIT" ]

null

bnn_mcmc_examples/examples/mlp/pima/setting1/hmc/sampler.py

kushagragpt99/bnn_mcmc_examples

297cdb1e74335860989bebdb4ff6f6322b6adc06

[ "MIT" ]

1

2021-10-05T06:38:57.000Z

# %% Import packages from eeyore.samplers import HMC from bnn_mcmc_examples.examples.mlp.pima.setting1.dataloaders import training_dataloader from bnn_mcmc_examples.examples.mlp.pima.setting1.model import model # %% Setup HMC sampler sampler = HMC(model, theta0=model.prior.sample(), dataloader=training_dataloader, step=0.125, num_steps=6)

31.363636

106

0.811594

from eeyore.samplers import HMC from bnn_mcmc_examples.examples.mlp.pima.setting1.dataloaders import training_dataloader from bnn_mcmc_examples.examples.mlp.pima.setting1.model import model sampler = HMC(model, theta0=model.prior.sample(), dataloader=training_dataloader, step=0.125, num_steps=6)

true

f704d9e98bd2692af546a133176acf66958374b4

866

py

Python

heltour/tournament/migrations/0049_auto_20160804_0509.py

zbidwell/heltour

3895142695096a81cc65c3fefb7d4501ed796f46

[ "MIT" ]

41

2016-08-17T19:58:42.000Z

2021-11-08T10:52:07.000Z

heltour/tournament/migrations/0049_auto_20160804_0509.py

zbidwell/heltour

3895142695096a81cc65c3fefb7d4501ed796f46

[ "MIT" ]

257

2016-08-17T22:29:05.000Z

2022-01-13T00:42:05.000Z

heltour/tournament/migrations/0049_auto_20160804_0509.py

zbidwell/heltour

3895142695096a81cc65c3fefb7d4501ed796f46

[ "MIT" ]

31

2016-09-23T23:36:14.000Z

2022-01-14T17:05:08.000Z

# -*- coding: utf-8 -*- # Generated by Django 1.9.7 on 2016-08-04 05:09 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('tournament', '0048_auto_20160803_0311'), ] operations = [ migrations.AddField( model_name='alternate', name='season_player', field=models.OneToOneField(null=True, on_delete=django.db.models.deletion.CASCADE, to='tournament.SeasonPlayer'), ), migrations.AlterUniqueTogether( name='alternate', unique_together=set([]), ), migrations.RunSQL(''' UPDATE tournament_alternate alt SET season_player_id = (SELECT id FROM tournament_seasonplayer sp WHERE sp.season_id = alt.season_id AND sp.player_id = alt.player_id) ''') ]

29.862069

174

0.643187

from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('tournament', '0048_auto_20160803_0311'), ] operations = [ migrations.AddField( model_name='alternate', name='season_player', field=models.OneToOneField(null=True, on_delete=django.db.models.deletion.CASCADE, to='tournament.SeasonPlayer'), ), migrations.AlterUniqueTogether( name='alternate', unique_together=set([]), ), migrations.RunSQL(''' UPDATE tournament_alternate alt SET season_player_id = (SELECT id FROM tournament_seasonplayer sp WHERE sp.season_id = alt.season_id AND sp.player_id = alt.player_id) ''') ]

true

f704dab721959161224d66936f270ee7bed32f72

12,634

py

Python

reconstructPointwise.py

LLNL/ferdinand

af47b415ea1e9cb21a45b20d1f3854bc7f3a4d70

[ "Apache-2.0" ]

null

reconstructPointwise.py

LLNL/ferdinand

af47b415ea1e9cb21a45b20d1f3854bc7f3a4d70

[ "Apache-2.0" ]

null

reconstructPointwise.py

LLNL/ferdinand

af47b415ea1e9cb21a45b20d1f3854bc7f3a4d70

[ "Apache-2.0" ]

null

############################################## # # # Ferdinand 0.40, Ian Thompson, LLNL # # # # gnd,endf,fresco,azure,hyrma # # # ############################################## import os import math from write_fresco import write_fresco import fudge.sums as sumsModule import fudge.styles as stylesModule import fudge.reactionData.crossSection as crossSectionModule import fudge.productData.distributions as distributionsModule ############################################## write_fresco def reconstructPointwise(gnd,base,verbose,debug,egrid,angles,thin,reconstyle): projectile = gnd.PoPs[gnd.projectile] target = gnd.PoPs[gnd.target] if hasattr(projectile, 'nucleus'): projectile = projectile.nucleus if hasattr(target, 'nucleus'): target = target.nucleus pZ = projectile.charge[0].value; tZ = target.charge[0].value charged = pZ*tZ != 0 identicalParticles = gnd.projectile == gnd.target rStyle = reconstyle.label if debug: print("Charged-particle elastic:",charged,", identical:",identicalParticles,' rStyle:',rStyle) if charged and angles is not None: from fudge.reactionData.doubleDifferentialCrossSection.chargedParticleElastic import CoulombPlusNuclearElastic as CoulombPlusNuclearElasticModule from fudge.reactionData.doubleDifferentialCrossSection.chargedParticleElastic import nuclearPlusInterference as nuclearPlusInterferenceModule # from fudge.reactionData.doubleDifferentialCrossSection.chargedParticleElastic import RutherfordScattering as RutherfordScatteringModule from fudge.productData.distributions import reference as referenceModule thmin = angles[0] pi = 3.1415826536 muCutoff = math.cos(thmin*pi/180.) fresco_base = base + '.fresco_recon' channels = write_fresco(gnd,fresco_base,verbose,debug,True,None,None,False,egrid,angles) name_frin = fresco_base + '.frin' # must be same as in write_fresco name_frout= fresco_base + '.frout' accuracy = None cmd = "frescox < "+name_frin+" > "+name_frout print(cmd) os.system(cmd) # Run FRESCO f239 = open('fort.239','r') egrid = [] totalxs = []; elasticxs = []; fissionxs = []; absorbtionxs = [] chanxs =[]; # lastzero = [ 0 for i in range(len(channels))] for rreac in gnd.resonances.resolved.evaluated.resonanceReactions: if not rreac.eliminated: chanxs.append([]) if len(channels) != len(chanxs): print("Only getting",channels," data channels, not",len(chanxs)) exit() if debug: print("Fresco channel order:",channels) mb = 1e-3 for line in f239: if 'NaN' not in line: data = line.split() try: elab,absorbtion,reaction,total,elastic = [float(d) for d in data[:5]] sigr = [float(d) for d in data[5:]] #print elab,absorbtion,reaction,total,elastic,sigr egrid.append(elab) totalxs.append(total*mb) elasticxs.append(elastic*mb) fissionxs.append(0.0) absorbtionxs.append(absorbtion*mb) for c in range(len(channels)): chanxs[c].append(sigr[c]*mb) # if sigr[c]== 0.: lastzero[c] = elab except: pass crossSectionAxes = crossSectionModule.defaultAxes( 'MeV' ) total = crossSectionModule.XYs1d( axes = crossSectionAxes, data=(egrid, totalxs), dataForm="XsAndYs" ) elastic = crossSectionModule.XYs1d( axes = crossSectionAxes, data=(egrid, elasticxs), dataForm="XsAndYs" ) fission = crossSectionModule.XYs1d( axes = crossSectionAxes, data=(egrid, fissionxs), dataForm="XsAndYs" ) absorbtion = crossSectionModule.XYs1d( axes = crossSectionAxes, data=(egrid, absorbtionxs), dataForm="XsAndYs" ) if not isinstance( reconstyle, stylesModule.crossSectionReconstructed ): raise TypeError("style must be an instance of crossSectionReconstructed, not %s" % type(reconstyle)) haveEliminated = False for rreac in gnd.resonances.resolved.evaluated.resonanceReactions: reaction = rreac.reactionLink.link haveEliminated = haveEliminated or rreac.eliminated # elastic or capture if reaction == gnd.getReaction('capture'): rreac.tag = 'capture' elif reaction == gnd.getReaction('elastic'): rreac.tag = 'elastic' elif 'fission' in rreac.label: rreac.tag = rreac.label else: rreac.tag = 'competitive' xsecs = {'total':total, 'elastic':elastic, 'fission':fission, 'nonelastic':absorbtion} for c in range(1,len(channels)): # skip c=1 elastic !! FIXME #print channels[c],':',len(egrid),len(chanxs[c]) xsecs[channels[c]] = crossSectionModule.XYs1d( axes = crossSectionAxes, data=(egrid, chanxs[c]), dataForm="XsAndYs" ) # print 'xsecs[channels[c]]',xsecs[channels[c]].toString() if haveEliminated: eliminatedReaction = [rr for rr in gnd.resonances.resolved.evaluated.resonanceReactions if rr.eliminated] if len(eliminatedReaction) != 1: raise TypeError("Only 1 reaction can be eliminated in Reich-Moore approximation!") xsecs[eliminatedReaction[0].tag] = absorbtion - fission epsilon = 1e-8 # for joining multiple regions together # for each reaction, add tabulated pointwise data (ENDF MF=3) to reconstructed resonances: possibleChannels = { 'elastic' : True, 'capture' : True, 'fission' : True, 'total' : False, 'nonelastic' : False } elasticChannel = gnd.getReaction('elastic') derivedFromLabel = '' for reaction in gnd : if isinstance( reaction, sumsModule.multiplicitySum ): continue iselastic = reaction is elasticChannel evaluatedCrossSection = reaction.crossSection.evaluated if not isinstance( evaluatedCrossSection, crossSectionModule.resonancesWithBackground ): continue # which reconstructed cross section corresponds to this reaction? if( derivedFromLabel == '' ) : derivedFromLabel = evaluatedCrossSection.label if( derivedFromLabel != evaluatedCrossSection.label ) : print(('WARNING derivedFromLabel = "%s" != "%s"' % (derivedFromLabel, evaluatedCrossSection.label))) RRxsec = None if str( reaction ) in xsecs: RRxsec = xsecs[ str( reaction ) ] # print 'Assign to ',str(reaction),'\n',RRxsec.toString() else : for possibleChannel in possibleChannels : if( possibleChannels[possibleChannel] ) : if( possibleChannel in str( reaction ) ) : RRxsec = xsecs[possibleChannel] # print 'Assign to ',str(reaction),'\n',RRxsec.toString() if( RRxsec is None ) : if( reaction is gnd.getReaction( possibleChannel ) ) : RRxsec = xsecs[possibleChannel] # print 'Assign to ',str(reaction),'\n',RRxsec.toString() if( RRxsec is not None ) : break if( RRxsec is None ) : if verbose: print(( "Warning: couldn't find appropriate reconstructed cross section to add to reaction %s" % reaction )) continue background = evaluatedCrossSection.background background = background.toPointwise_withLinearXYs( accuracy = 1e-3, lowerEps = epsilon, upperEps = epsilon ) RRxsec = RRxsec.toPointwise_withLinearXYs( accuracy = 1e-3, lowerEps = epsilon, upperEps = epsilon ) RRxsec.convertUnits( {RRxsec.domainUnit: background.domainUnit, RRxsec.rangeUnit: background.rangeUnit } ) background, RRxsec = background.mutualify(0,0,0, RRxsec, -epsilon,epsilon,True) RRxsec = background + RRxsec # result is a crossSection.XYs1d instance if thin: RRx = RRxsec.thin( accuracy or .001 ) else: RRx = RRxsec RRx.label = rStyle reaction.crossSection.add( RRx ) # print "Channels ",reaction.label,iselastic,":\n",RRxsec.toString(),"\n&\n",RRx.toString() if iselastic: effXsc = RRxsec gnd.styles.add( reconstyle ) # print "Last energies of zero cross section:",lastzero if angles is None: return f241 = open('fort.241','r') sigdd = {} for rr in channels: sigdd[rr] = [] for line in f241: if '# Elab =' in line: elab,ich = float(line[9:9+15]),int(line[9+15:9+15+4])-1 # Elab = 1.00000000E-06 1 line1 = line dist = [] elif "&" in line: rr = channels[ich] sigdd[rr].append([elab,dist]) # if elab<1.0001: print '\n',ich,rr,sigdd[rr] elif "NaN" in line: continue else: mu,p = line.split() try: mu,p = float(mu),float(p) dist.insert(0,p) dist.insert(0,mu) except: pass angularAxes = distributionsModule.angular.defaultAxes( 'MeV' ) for rreac in gnd.resonances.resolved.evaluated.resonanceReactions: if not rreac.eliminated: productName = rreac.ejectile residName = rreac.residual elastic = productName == gnd.projectile and residName == gnd.target print("Add angular distribution for",productName," in",rreac.label,"channel (elastic=",elastic,")") reaction = rreac.reactionLink.link firstProduct = reaction.outputChannel.getProductWithName(productName) effDist = distributionsModule.angular.XYs2d( axes = angularAxes ) elab_max = 0.; elab_min = 1e10; nangles=0 ne = 0 for elab,dist in sigdd[rreac.label]: if debug: print('E=',elab,'has',len(dist),' angles') if len(dist) <= 3: print(' E=',elab,'has',len(dist),' angles') continue angdist = distributionsModule.angular.XYs1d( data = dist, outerDomainValue = elab, axes = angularAxes, dataForm = 'list' ) if thin: angdist = angdist.thin( accuracy or .001 ) norm = angdist.integrate() if norm != 0.0: if debug: print(rreac.label,elab,norm) effDist.append( angdist ) elab_max = max(elab,elab_max); elab_min = min(elab,elab_min); nangles = max(len(dist),nangles) ne += 1 print(" Angles reconstructed at %i energies from %s to %s MeV with up to %i angles at each energy" % (ne,elab_min,elab_max,nangles)) newForm = distributionsModule.angular.twoBodyForm( label = reconstyle.label, productFrame = firstProduct.distribution.evaluated.productFrame, angularSubform = effDist ) firstProduct.distribution.add( newForm ) if elastic and charged: # dCrossSection_dOmega for charged-particle elastics: NCPI = nuclearPlusInterferenceModule.nuclearPlusInterference( muCutoff=muCutoff, crossSection=nuclearPlusInterferenceModule.crossSection( effXsc), distribution=nuclearPlusInterferenceModule.distribution( effDist) ) # Rutherford = RutherfordScatteringModule.RutherfordScattering() CoulombElastic = CoulombPlusNuclearElasticModule.form( gnd.projectile, rStyle, nuclearPlusInterference = NCPI, identicalParticles=identicalParticles ) reaction.doubleDifferentialCrossSection.add( CoulombElastic ) reaction.crossSection.remove( rStyle ) reaction.crossSection.add( crossSectionModule.CoulombPlusNuclearElastic( link = reaction.doubleDifferentialCrossSection[rStyle], label = rStyle, relative = True ) ) firstProduct.distribution.remove( rStyle ) firstProduct.distribution.add( referenceModule.CoulombPlusNuclearElastic( link = reaction.doubleDifferentialCrossSection[rStyle], label = rStyle, relative = True ) ) secondProduct = reaction.outputChannel[1] # secondProduct.distribution[rStyle].angularSubform.link = firstProduct.distribution[rStyle] ## Fails # give 'recoil' distribution! return

48.779923

166

0.616115

'capture'): rreac.tag = 'capture' elif reaction == gnd.getReaction('elastic'): rreac.tag = 'elastic' elif 'fission' in rreac.label: rreac.tag = rreac.label else: rreac.tag = 'competitive' xsecs = {'total':total, 'elastic':elastic, 'fission':fission, 'nonelastic':absorbtion} for c in range(1,len(channels)): xsecs[channels[c]] = crossSectionModule.XYs1d( axes = crossSectionAxes, data=(egrid, chanxs[c]), dataForm="XsAndYs" ) if haveEliminated: eliminatedReaction = [rr for rr in gnd.resonances.resolved.evaluated.resonanceReactions if rr.eliminated] if len(eliminatedReaction) != 1: raise TypeError("Only 1 reaction can be eliminated in Reich-Moore approximation!") xsecs[eliminatedReaction[0].tag] = absorbtion - fission epsilon = 1e-8 possibleChannels = { 'elastic' : True, 'capture' : True, 'fission' : True, 'total' : False, 'nonelastic' : False } elasticChannel = gnd.getReaction('elastic') derivedFromLabel = '' for reaction in gnd : if isinstance( reaction, sumsModule.multiplicitySum ): continue iselastic = reaction is elasticChannel evaluatedCrossSection = reaction.crossSection.evaluated if not isinstance( evaluatedCrossSection, crossSectionModule.resonancesWithBackground ): continue if( derivedFromLabel == '' ) : derivedFromLabel = evaluatedCrossSection.label if( derivedFromLabel != evaluatedCrossSection.label ) : print(('WARNING derivedFromLabel = "%s" != "%s"' % (derivedFromLabel, evaluatedCrossSection.label))) RRxsec = None if str( reaction ) in xsecs: RRxsec = xsecs[ str( reaction ) ] else : for possibleChannel in possibleChannels : if( possibleChannels[possibleChannel] ) : if( possibleChannel in str( reaction ) ) : RRxsec = xsecs[possibleChannel] if( RRxsec is None ) : if( reaction is gnd.getReaction( possibleChannel ) ) : RRxsec = xsecs[possibleChannel] if( RRxsec is not None ) : break if( RRxsec is None ) : if verbose: print(( "Warning: couldn't find appropriate reconstructed cross section to add to reaction %s" % reaction )) continue background = evaluatedCrossSection.background background = background.toPointwise_withLinearXYs( accuracy = 1e-3, lowerEps = epsilon, upperEps = epsilon ) RRxsec = RRxsec.toPointwise_withLinearXYs( accuracy = 1e-3, lowerEps = epsilon, upperEps = epsilon ) RRxsec.convertUnits( {RRxsec.domainUnit: background.domainUnit, RRxsec.rangeUnit: background.rangeUnit } ) background, RRxsec = background.mutualify(0,0,0, RRxsec, -epsilon,epsilon,True) RRxsec = background + RRxsec # result is a crossSection.XYs1d instance if thin: RRx = RRxsec.thin( accuracy or .001 ) else: RRx = RRxsec RRx.label = rStyle reaction.crossSection.add( RRx ) # print "Channels ",reaction.label,iselastic,":\n",RRxsec.toString(),"\n&\n",RRx.toString() if iselastic: effXsc = RRxsec gnd.styles.add( reconstyle ) # print "Last energies of zero cross section:",lastzero if angles is None: return f241 = open('fort.241','r') sigdd = {} for rr in channels: sigdd[rr] = [] for line in f241: if ' elab,ich = float(line[9:9+15]),int(line[9+15:9+15+4])-1 # Elab = 1.00000000E-06 1 line1 = line dist = [] elif "&" in line: rr = channels[ich] sigdd[rr].append([elab,dist]) # if elab<1.0001: print '\n',ich,rr,sigdd[rr] elif "NaN" in line: continue else: mu,p = line.split() try: mu,p = float(mu),float(p) dist.insert(0,p) dist.insert(0,mu) except: pass angularAxes = distributionsModule.angular.defaultAxes( 'MeV' ) for rreac in gnd.resonances.resolved.evaluated.resonanceReactions: if not rreac.eliminated: productName = rreac.ejectile residName = rreac.residual elastic = productName == gnd.projectile and residName == gnd.target print("Add angular distribution for",productName," in",rreac.label,"channel (elastic=",elastic,")") reaction = rreac.reactionLink.link firstProduct = reaction.outputChannel.getProductWithName(productName) effDist = distributionsModule.angular.XYs2d( axes = angularAxes ) elab_max = 0.; elab_min = 1e10; nangles=0 ne = 0 for elab,dist in sigdd[rreac.label]: if debug: print('E=',elab,'has',len(dist),' angles') if len(dist) <= 3: print(' E=',elab,'has',len(dist),' angles') continue angdist = distributionsModule.angular.XYs1d( data = dist, outerDomainValue = elab, axes = angularAxes, dataForm = 'list' ) if thin: angdist = angdist.thin( accuracy or .001 ) norm = angdist.integrate() if norm != 0.0: if debug: print(rreac.label,elab,norm) effDist.append( angdist ) elab_max = max(elab,elab_max); elab_min = min(elab,elab_min); nangles = max(len(dist),nangles) ne += 1 print(" Angles reconstructed at %i energies from %s to %s MeV with up to %i angles at each energy" % (ne,elab_min,elab_max,nangles)) newForm = distributionsModule.angular.twoBodyForm( label = reconstyle.label, productFrame = firstProduct.distribution.evaluated.productFrame, angularSubform = effDist ) firstProduct.distribution.add( newForm ) if elastic and charged: # dCrossSection_dOmega for charged-particle elastics: NCPI = nuclearPlusInterferenceModule.nuclearPlusInterference( muCutoff=muCutoff, crossSection=nuclearPlusInterferenceModule.crossSection( effXsc), distribution=nuclearPlusInterferenceModule.distribution( effDist) ) # Rutherford = RutherfordScatteringModule.RutherfordScattering() CoulombElastic = CoulombPlusNuclearElasticModule.form( gnd.projectile, rStyle, nuclearPlusInterference = NCPI, identicalParticles=identicalParticles ) reaction.doubleDifferentialCrossSection.add( CoulombElastic ) reaction.crossSection.remove( rStyle ) reaction.crossSection.add( crossSectionModule.CoulombPlusNuclearElastic( link = reaction.doubleDifferentialCrossSection[rStyle], label = rStyle, relative = True ) ) firstProduct.distribution.remove( rStyle ) firstProduct.distribution.add( referenceModule.CoulombPlusNuclearElastic( link = reaction.doubleDifferentialCrossSection[rStyle], label = rStyle, relative = True ) ) secondProduct = reaction.outputChannel[1] # secondProduct.distribution[rStyle].angularSubform.link = firstProduct.distribution[rStyle] ## Fails # give 'recoil' distribution! return

true

f704dae35a632084b188c064b1c868e00c367228

12,829

py

Python

pylabnet/scripts/counter/monitor_counts.py

wi11dey/pylabnet

a6e3362f727c45aaa60e61496e858ae92e85574d

[ "MIT" ]

null

pylabnet/scripts/counter/monitor_counts.py

wi11dey/pylabnet

a6e3362f727c45aaa60e61496e858ae92e85574d

[ "MIT" ]

null

pylabnet/scripts/counter/monitor_counts.py

wi11dey/pylabnet

a6e3362f727c45aaa60e61496e858ae92e85574d

[ "MIT" ]

null

""" Generic script for monitoring counts from a counter """ import numpy as np import time import pyqtgraph as pg from pylabnet.gui.pyqt.external_gui import Window from pylabnet.utils.logging.logger import LogClient from pylabnet.scripts.pause_script import PauseService from pylabnet.network.core.generic_server import GenericServer from pylabnet.network.client_server import si_tt from pylabnet.utils.helper_methods import load_script_config, get_ip, unpack_launcher, load_config, get_gui_widgets, get_legend_from_graphics_view, find_client, load_script_config # Static methods # def generate_widgets(): # """Static method to return systematically named gui widgets for 4ch wavemeter monitor""" # graphs, legends, numbers = [], [], [] # for i in range(2): # graphs.append('graph_widget_' + str(i + 1)) # legends.append('legend_widget_' + str(i + 1)) # numbers.append('number_label_' + str(i + 1)) # for i in range(2, 8): # numbers.append('number_label_' + str(i + 1)) # return graphs, legends, numbers class CountMonitor: # Generate all widget instances for the .ui to use # _plot_widgets, _legend_widgets, _number_widgets = generate_widgets() def __init__(self, ctr_client: si_tt.Client, ui='count_monitor', logger_client=None, server_port=None, combined_channel=False, config=None): """ Constructor for CountMonitor script :param ctr_client: instance of hardware client for counter :param gui_client: (optional) instance of client of desired output GUI :param logger_client: (obj) instance of logger client. :param server_port: (int) port number of script server :combined_channel: (bool) If true, show additional trace with summed counts. """ self._ctr = ctr_client self.log = logger_client self.combined_channel = combined_channel self._bin_width = None self._n_bins = None self._ch_list = None self._plot_list = None # List of channels to assign to each plot (e.g. [[1,2], [3,4]]) self._plots_assigned = [] # List of plots on the GUI that have been assigned if self.combined_channel: ui = 'count_monitor_combined' else: ui = 'count_monitor' # Instantiate GUI window self.gui = Window( gui_template=ui, host=get_ip(), port=server_port, log=self.log ) # Setup stylesheet. self.gui.apply_stylesheet() if self.combined_channel: num_plots = 3 else: num_plots = 2 # Get all GUI widgets self.widgets = get_gui_widgets( self.gui, graph_widget=num_plots, number_label=8, event_button=num_plots, legend_widget=num_plots ) # Load config self.config = {} if config is not None: self.config = load_script_config( script='monitor_counts', config=config, logger=self.logger_client ) if not 'name' in self.config: self.config.update({'name': f'monitor{np.random.randint(1000)}'}) def set_hardware(self, ctr): """ Sets hardware client for this script :param ctr: instance of count monitor hardware client """ # Initialize counter instance self._ctr = ctr def set_params(self, bin_width=1e9, n_bins=1e4, ch_list=[1], plot_list=None): """ Sets counter parameters :param bin_width: bin width in ps :param n_bins: number of bins to display on graph :param ch_list: (list) channels to record :param plot_list: list of channels to assign to each plot (e.g. [[1,2], [3,4]]) """ # Save params to internal variables self._bin_width = int(bin_width) self._n_bins = int(n_bins) self._ch_list = ch_list self._plot_list = plot_list def run(self): """ Runs the counter from scratch""" try: # Start the counter with desired parameters self._initialize_display() # Give time to initialize # time.sleep(0.05) self._is_running = True self._ctr.start_trace( name=self.config['name'], ch_list=self._ch_list, bin_width=self._bin_width, n_bins=self._n_bins ) # Continuously update data until paused while self._is_running: self._update_output() self.gui.force_update() except Exception as exc_obj: self._is_running = False raise exc_obj def pause(self): """ Pauses the counter""" self._is_running = False def resume(self): """ Resumes the counter. To be used to resume after the counter has been paused. """ try: self._is_running = True # Clear counter and resume plotting self._ctr.clear_ctr(name=self.config['name']) while self._is_running: self._update_output() except Exception as exc_obj: self._is_running = False raise exc_obj # Technical methods def _initialize_display(self): """ Initializes the display (configures all plots) """ plot_index = 0 for index in range(len(self.widgets['graph_widget'])): # Configure and return legend widgets self.widgets['legend_widget'][index] = get_legend_from_graphics_view( self.widgets['legend_widget'][index] ) for color, channel in enumerate(self._ch_list): # Figure out which plot to assign to if self._plot_list is not None: for index, channel_set in enumerate(self._plot_list): if channel in channel_set: plot_index = index break # If we have not assigned this plot yet, assign it # if plot_index not in self._plots_assigned: # self.gui_handler.assign_plot( # plot_widget=self._plot_widgets[plot_index], # plot_label='Counter Monitor {}'.format(plot_index + 1), # legend_widget=self._legend_widgets[plot_index] # ) # self._plots_assigned.append(plot_index) # Now assign this curve # self.gui_handler.assign_curve( # plot_label='Counter Monitor {}'.format(plot_index + 1), # curve_label='Channel {}'.format(channel), # error=True # ) # Create a curve and store the widget in our dictionary self.widgets[f'curve_{channel}'] = self.widgets['graph_widget'][plot_index].plot( pen=pg.mkPen(color=self.gui.COLOR_LIST[color]) ) self.widgets['legend_widget'][plot_index].addItem( self.widgets[f'curve_{channel}'], ' - ' + f'Channel {channel}' ) # Assign scalar # self.gui_handler.assign_label( # label_widget=self._number_widgets[channel - 1], # label_label='Channel {}'.format(channel) # ) # Handle button pressing from functools import partial for plot_index, clear_button in enumerate(self.widgets['event_button']): clear_button.clicked.connect(partial(lambda plot_index: self._clear_plot(plot_index), plot_index=plot_index)) if self.combined_channel: self.widgets['curve_combo'] = self.widgets['graph_widget'][index + 1].plot( pen=pg.mkPen(color=self.gui.COLOR_LIST[color + 1]) ) self.widgets['legend_widget'][index + 1].addItem( self.widgets['curve_combo'], ' - ' + 'Combined Counts' ) def _clear_plot(self, plot_index): """ Clears the curves on a particular plot :param plot_index: (int) index of plot to clear """ # First, handle case where combined count channel is clears (very ugly). if self.combined_channel and plot_index == len(self._plot_list): channel = 'combo' # Set the curve to constant with last point for all entries self.widgets[f'curve_{channel}'].setData( np.ones(self._n_bins) * self.widgets[f'curve_{channel}'].yData[-1] ) else: # Find all curves in this plot for channel in self._plot_list[plot_index]: # Set the curve to constant with last point for all entries self.widgets[f'curve_{channel}'].setData( np.ones(self._n_bins) * self.widgets[f'curve_{channel}'].yData[-1] ) self._ctr.clear_ctr(name=self.config['name']) def _update_output(self): """ Updates the output to all current values""" # Update all active channels # x_axis = self._ctr.get_x_axis()/1e12 counts = self._ctr.get_counts(name=self.config['name']) counts_per_sec = counts * (1e12 / self._bin_width) # noise = np.sqrt(counts)*(1e12/self._bin_width) # plot_index = 0 summed_counts = np.sum(counts_per_sec, axis=0) for index, count_array in enumerate(counts_per_sec): # Figure out which plot to assign to channel = self._ch_list[index] # if self._plot_list is not None: # for index_plot, channel_set in enumerate(self._plot_list): # if channel in channel_set: # plot_index = index_plot # break # Update GUI data # self.gui_handler.set_curve_data( # data=count_array, # error=noise[index], # plot_label='Counter Monitor {}'.format(plot_index + 1), # curve_label='Channel {}'.format(channel) # ) # self.gui_handler.set_label( # text='{:.4e}'.format(count_array[-1]), # label_label='Channel {}'.format(channel) # ) self.widgets[f'curve_{channel}'].setData(count_array) self.widgets[f'number_label'][channel - 1].setText(str(count_array[-1])) if self.combined_channel: self.widgets['curve_combo'].setData(summed_counts) def launch(**kwargs): """ Launches the count monitor script """ # logger, loghost, logport, clients, guis, params = unpack_launcher(**kwargs) logger = kwargs['logger'] clients = kwargs['clients'] config = load_script_config( 'monitor_counts', kwargs['config'], logger ) if config['combined_channel'] == 'True': combined_channel = True else: combined_channel = False # Instantiate CountMonitor try: monitor = CountMonitor( ctr_client=find_client( clients, config, client_type='si_tt', client_config='standard_ctr', logger=logger ), logger_client=logger, server_port=kwargs['server_port'], combined_channel=combined_channel ) except KeyError: print('Please make sure the module names for required servers and GUIS are correct.') time.sleep(15) raise # except: # config = None # ch_list = [7, 8] # plot_list = [[7], [8]] # Instantiate Pause server # try: # pause_logger = LogClient( # host=loghost, # port=logport, # module_tag='count_monitor_pause_server' # ) # except ConnectionRefusedError: # logger.warn('Could not connect Count Monitor Pause server to logger') # pause_service = PauseService() # pause_service.assign_module(module=monitor) # pause_service.assign_logger(logger=pause_logger) # timeout = 0 # while timeout < 1000: # try: # port = np.random.randint(1, 9999) # pause_server = GenericServer( # host=get_ip(), # port=port, # service=pause_service) # pause_logger.update_data(data=dict(port=port)) # timeout = 9999 # except ConnectionRefusedError: # logger.warn(f'Failed to instantiate Count Monitor Pause server at port {port}') # timeout += 1 # pause_server.start() # Set parameters monitor.set_params(**config['params']) # Run monitor.run()

34.029178

179

0.581651

import numpy as np import time import pyqtgraph as pg from pylabnet.gui.pyqt.external_gui import Window from pylabnet.utils.logging.logger import LogClient from pylabnet.scripts.pause_script import PauseService from pylabnet.network.core.generic_server import GenericServer from pylabnet.network.client_server import si_tt from pylabnet.utils.helper_methods import load_script_config, get_ip, unpack_launcher, load_config, get_gui_widgets, get_legend_from_graphics_view, find_client, load_script_config class CountMonitor: def __init__(self, ctr_client: si_tt.Client, ui='count_monitor', logger_client=None, server_port=None, combined_channel=False, config=None): self._ctr = ctr_client self.log = logger_client self.combined_channel = combined_channel self._bin_width = None self._n_bins = None self._ch_list = None self._plot_list = None self._plots_assigned = [] if self.combined_channel: ui = 'count_monitor_combined' else: ui = 'count_monitor' self.gui = Window( gui_template=ui, host=get_ip(), port=server_port, log=self.log ) self.gui.apply_stylesheet() if self.combined_channel: num_plots = 3 else: num_plots = 2 self.widgets = get_gui_widgets( self.gui, graph_widget=num_plots, number_label=8, event_button=num_plots, legend_widget=num_plots ) self.config = {} if config is not None: self.config = load_script_config( script='monitor_counts', config=config, logger=self.logger_client ) if not 'name' in self.config: self.config.update({'name': f'monitor{np.random.randint(1000)}'}) def set_hardware(self, ctr): self._ctr = ctr def set_params(self, bin_width=1e9, n_bins=1e4, ch_list=[1], plot_list=None): self._bin_width = int(bin_width) self._n_bins = int(n_bins) self._ch_list = ch_list self._plot_list = plot_list def run(self): try: self._initialize_display() self._is_running = True self._ctr.start_trace( name=self.config['name'], ch_list=self._ch_list, bin_width=self._bin_width, n_bins=self._n_bins ) while self._is_running: self._update_output() self.gui.force_update() except Exception as exc_obj: self._is_running = False raise exc_obj def pause(self): self._is_running = False def resume(self): try: self._is_running = True self._ctr.clear_ctr(name=self.config['name']) while self._is_running: self._update_output() except Exception as exc_obj: self._is_running = False raise exc_obj def _initialize_display(self): plot_index = 0 for index in range(len(self.widgets['graph_widget'])): self.widgets['legend_widget'][index] = get_legend_from_graphics_view( self.widgets['legend_widget'][index] ) for color, channel in enumerate(self._ch_list): if self._plot_list is not None: for index, channel_set in enumerate(self._plot_list): if channel in channel_set: plot_index = index break self.widgets[f'curve_{channel}'] = self.widgets['graph_widget'][plot_index].plot( pen=pg.mkPen(color=self.gui.COLOR_LIST[color]) ) self.widgets['legend_widget'][plot_index].addItem( self.widgets[f'curve_{channel}'], ' - ' + f'Channel {channel}' ) from functools import partial for plot_index, clear_button in enumerate(self.widgets['event_button']): clear_button.clicked.connect(partial(lambda plot_index: self._clear_plot(plot_index), plot_index=plot_index)) if self.combined_channel: self.widgets['curve_combo'] = self.widgets['graph_widget'][index + 1].plot( pen=pg.mkPen(color=self.gui.COLOR_LIST[color + 1]) ) self.widgets['legend_widget'][index + 1].addItem( self.widgets['curve_combo'], ' - ' + 'Combined Counts' ) def _clear_plot(self, plot_index): if self.combined_channel and plot_index == len(self._plot_list): channel = 'combo' self.widgets[f'curve_{channel}'].setData( np.ones(self._n_bins) * self.widgets[f'curve_{channel}'].yData[-1] ) else: for channel in self._plot_list[plot_index]: self.widgets[f'curve_{channel}'].setData( np.ones(self._n_bins) * self.widgets[f'curve_{channel}'].yData[-1] ) self._ctr.clear_ctr(name=self.config['name']) def _update_output(self): counts = self._ctr.get_counts(name=self.config['name']) counts_per_sec = counts * (1e12 / self._bin_width) summed_counts = np.sum(counts_per_sec, axis=0) for index, count_array in enumerate(counts_per_sec): channel = self._ch_list[index] self.widgets[f'curve_{channel}'].setData(count_array) self.widgets[f'number_label'][channel - 1].setText(str(count_array[-1])) if self.combined_channel: self.widgets['curve_combo'].setData(summed_counts) def launch(**kwargs): logger = kwargs['logger'] clients = kwargs['clients'] config = load_script_config( 'monitor_counts', kwargs['config'], logger ) if config['combined_channel'] == 'True': combined_channel = True else: combined_channel = False try: monitor = CountMonitor( ctr_client=find_client( clients, config, client_type='si_tt', client_config='standard_ctr', logger=logger ), logger_client=logger, server_port=kwargs['server_port'], combined_channel=combined_channel ) except KeyError: print('Please make sure the module names for required servers and GUIS are correct.') time.sleep(15) raise monitor.set_params(**config['params']) monitor.run()

true

f704db4f9f14c36b7a4a23d49d7aeb53b61d9f65

1,723

py

Python

app/core/migrations/0001_initial.py

lucaspyproj/learn-app-api

77d1216c9520c21785c7f56f84d8681a2990a6cf

[ "MIT" ]

null

app/core/migrations/0001_initial.py

lucaspyproj/learn-app-api

77d1216c9520c21785c7f56f84d8681a2990a6cf

[ "MIT" ]

null

app/core/migrations/0001_initial.py

lucaspyproj/learn-app-api

77d1216c9520c21785c7f56f84d8681a2990a6cf

[ "MIT" ]

null

# Generated by Django 2.1.15 on 2020-02-16 11:10 # flake8: noqa from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ('auth', '0009_alter_user_last_name_max_length'), ] operations = [ migrations.CreateModel( name='User', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('password', models.CharField(max_length=128, verbose_name='password')), ('last_login', models.DateTimeField(blank=True, null=True, verbose_name='last login')), ('is_superuser', models.BooleanField(default=False, help_text='Designates that this user has all permissions without explicitly assigning them.', verbose_name='superuser status')), ('email', models.EmailField(max_length=255, unique=True)), ('name', models.CharField(max_length=255)), ('is_active', models.BooleanField(default=True)), ('is_staff', models.BooleanField(default=False)), ('groups', models.ManyToManyField(blank=True, help_text='The groups this user belongs to. A user will get all permissions granted to each of their groups.', related_name='user_set', related_query_name='user', to='auth.Group', verbose_name='groups')), ('user_permissions', models.ManyToManyField(blank=True, help_text='Specific permissions for this user.', related_name='user_set', related_query_name='user', to='auth.Permission', verbose_name='user permissions')), ], options={ 'abstract': False, }, ), ]

50.676471

266

0.639582

from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ('auth', '0009_alter_user_last_name_max_length'), ] operations = [ migrations.CreateModel( name='User', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('password', models.CharField(max_length=128, verbose_name='password')), ('last_login', models.DateTimeField(blank=True, null=True, verbose_name='last login')), ('is_superuser', models.BooleanField(default=False, help_text='Designates that this user has all permissions without explicitly assigning them.', verbose_name='superuser status')), ('email', models.EmailField(max_length=255, unique=True)), ('name', models.CharField(max_length=255)), ('is_active', models.BooleanField(default=True)), ('is_staff', models.BooleanField(default=False)), ('groups', models.ManyToManyField(blank=True, help_text='The groups this user belongs to. A user will get all permissions granted to each of their groups.', related_name='user_set', related_query_name='user', to='auth.Group', verbose_name='groups')), ('user_permissions', models.ManyToManyField(blank=True, help_text='Specific permissions for this user.', related_name='user_set', related_query_name='user', to='auth.Permission', verbose_name='user permissions')), ], options={ 'abstract': False, }, ), ]

true

f704db7738c33468077ceb775a163c773f08d47d

11,918

py

Python

Notebooks/lib/Message_passing_BN.py

olmosUC3M/Inference-and-Learning-in-discrete-Bayesian-Networks

12e08f2e3f34146638806212be54837cc22c0516

[ "MIT" ]

3

2019-05-19T11:26:42.000Z

2021-07-31T07:28:35.000Z

Notebooks/lib/Message_passing_BN.py

olmosUC3M/Inference-and-Learning-in-discrete-Bayesian-Networks

12e08f2e3f34146638806212be54837cc22c0516

[ "MIT" ]

null

Notebooks/lib/Message_passing_BN.py

olmosUC3M/Inference-and-Learning-in-discrete-Bayesian-Networks

12e08f2e3f34146638806212be54837cc22c0516

[ "MIT" ]

null

## Message passing over a discrete BN ## ## Library created by Pablo Martínez Olmos, University Carlos III Madrid ## ## olmos@tsc.uc3m.es ## ## Last modification 15/11/2016 ## import numpy as np ## Messages are stored in the logaritmic domain ## ## Global constants (to control numerical issues) inf_log=100 #To impose hard constraints (i.e. an observed variable) constant_log=50 #Used to improve stability in the Check Node (CN) operation ## Function definitions def create_var_node(ID,cardinality,neighbor_order,observed_value_index=-1): # Variable Nodes are defined by a dictionary with several fields var_node={} var_node['ID']=ID var_node['node_type']=0 #type 0 refers to variable node, 1o to check nodes. var_node['cardinality']=cardinality #Num. of possible values the RV can take var_node['neighbor_order']=np.array(neighbor_order) #Ordered array of the neighbor's IDs (neighbors are CNs!) var_node['input_msgs']=[] #List to store input messages var_node['observed']=observed_value_index #-1 if the variable is not observed var_node['inner_factor']=np.zeros([cardinality,1]) #Internal vector used to imposed hard messages when variable is observed #If variable is observed, then the inner_factor vector is log[0 0 ... 0 1 0 ...] if(observed_value_index!=-1): var_node['inner_factor']-=inf_log var_node['inner_factor'][observed_value_index]=inf_log #Initialize input msgs by filling with zeros for index,f in enumerate(var_node['neighbor_order']): var_node['input_msgs'].append(0) return var_node def create_message(input_node,output_node,table): #Messages are defined by a dictionary with three keys: input node (sender node), output_node (receiver node), and table of values message={} message['input_node']=input_node message['output_node']=output_node message['table']=table return message def create_factor_node(ID,neighbors,CPD): # Check Nodes are defined by a dictionary with several fields factor_node={} factor_node['ID']=ID factor_node['node_type']=1 factor_node['input_msgs']=[] CPD=np.array(CPD) CPD=CPD.reshape(CPD.shape[0],) #Just to make sure that CPD is a np. array vector of dim. (n,) factor_node['CPD']=np.array(CPD) #CPD table associated to the factor factor_node['CPD_order']=np.zeros([len(neighbors),1]).astype(int) #Ordered array of the neighbor's IDs (neighbors are CNs!) factor_node['cardinalities']=np.zeros([len(neighbors),1]).astype(int) #Cardinalities of the neighbors #Initialize input msgs, CPD_order & cardinalities #Note that creating factor nodes requires variable nodes to be created first, as CN input messages #are initialized already to the inner_factor field of every neighbor variable node for index,node in enumerate(neighbors): card=node['cardinality'] factor_node['input_msgs'].append( create_message(input_node=node,output_node=factor_node,table=node['inner_factor'])) factor_node['cardinalities'][index]=card factor_node['CPD_order'][index]=node['ID'] return factor_node def initialize_variable(var_node,observed_value_index=-1): #After running message passing, variable nodes store the incoming messages for future calculations #If we want to run again message passing in the same graph, we have to re-initialize both #variable nodes and check nodes. var_node['inner_factor']=np.zeros([var_node['cardinality'],1]) var_node['observed']=observed_value_index if(observed_value_index!=-1): var_node['inner_factor']-=inf_log var_node['inner_factor'][observed_value_index]=inf_log def initialize_factor_msgs(factor_node,neighbors): #After running message passing, variable nodes store the incoming messages for future calculations #If we want to run again message passing in the same graph, we have to re-initialize both #variable nodes and check nodes. factor_node['input_msgs']=[] for index,node in enumerate(neighbors): factor_node['input_msgs'].append( create_message(input_node=node,output_node=factor_node,table=node['inner_factor'])) #The next two routines are used to encode and decode positions to store CPD values in a #vector form. We use a tree-encoding determined by the order of variables and their cardinalities #See First Example Message Passing.ipynb for an illustration def CPD_position_to_variable_index(position,v_card,CPD_size): #We use this function to find the encoding for each position of a CPD table #of CPD_size positions, where the cardinalities of the variables (in order) are given in v_card #This function returns the index value of each variable v_card=np.array(v_card) #To make sure we have a np.array var_index=np.zeros([v_card.shape[0],1]).astype(int) remaining=CPD_size for i,card in enumerate(v_card): remaining=remaining//card index_i=position//remaining position=position-index_i*(remaining) var_index[i]=index_i return var_index def variable_index_to_CPD_position(var_index,v_card,CPD_size): #This function returns the encoded CPD position for a given configuration of the variables. #The CPD table is of size CPD_size, the cardinalities of the variables (in order) are given in v_card #and the value indexes (in order) of the variables are given in var_index var_index=np.array(var_index) v_card=np.array(v_card) position=0 offset=CPD_size for i,card in enumerate(v_card): offset=offset//card position+=var_index[i]*offset return position def update_var_to_factor(var_node): #Routine to update the output messages of a variable node (var_node) prod_table=np.zeros([var_node['cardinality'],1]) #We first multiply all the input messages (sums in the log domain) for msg in var_node['input_msgs']: prod_table+=msg['table'] #We also take into account the inner_factor of the variable_node. In #case it is observed, the output messages have to be consistent with the observation prod_table+=var_node['inner_factor'] #For every output message, we have to substract from prod_table the message received #through the corresponding edge for msg in var_node['input_msgs']: if(var_node['observed']==-1): reply_table=prod_table-msg['table'] else: reply_table=np.ones([var_node['cardinality'],1])*(-inf_log) reply_table[var_node['observed']]=inf_log #We limit the absolute value of the messages, to exp(inf_log) reply_table[reply_table>inf_log]=inf_log reply_table[reply_table<-inf_log]=-inf_log #The ouput message is stored in the corresponding neighbor factor_rx=msg['input_node'] reply_msg=create_message(input_node=var_node,output_node=factor_rx,table=reply_table) #Short foor loop to save messages in factor_node in the corresponding order for index,v in enumerate(factor_rx['CPD_order']): if(v==var_node['ID']): factor_rx['input_msgs'][index]=reply_msg break def compute_var_marginal(var_node): #Routine to compute the marginal pmf of a variable node (var_node) #Simply the product of all incoming msgs times the inner_factor marg_table=np.zeros([var_node['cardinality'],1]) for msg in var_node['input_msgs']: marg_table+=msg['table'] marg_table+=var_node['inner_factor'] marg_table=np.exp(marg_table) marg_table/=sum(marg_table) return marg_table def update_factor_to_var(factor_node): #Routine to update the output messages of a check node (var_node) #This is the most complicated in the library, as it involves marginalization #over each argument of the CPD function times the product of incoming messgaes output_tables=[] #Output message tables initialization for card in factor_node['cardinalities']: output_tables.append(np.zeros([card,1])) #With a single loop we go only once through every element of the CPD table #It is multiplied accordingly to input messages and the resulting terms are #added to the corresponding output tables for CPD_entry,CPD_val in enumerate(factor_node['CPD']): values=CPD_position_to_variable_index( position=CPD_entry,v_card=factor_node['cardinalities'],CPD_size=factor_node['CPD'].shape[0]) #The CPD value is multiplied by all incoming input messages but one, #and the result is added to the ouput table #Since we have to marginalize, not all operations can be done in the log domain #To avoid numerical inestabilities when performing the operations, we substract a large exponent (constant log) #which is sum at the very end, when we move back to the log domain for index in range(factor_node['cardinalities'].shape[0]): aux=CPD_val for index2 in range(factor_node['cardinalities'].shape[0]): if(index2!=index): aux*=np.exp(factor_node['input_msgs'][index2]['table'][values[index2]]-constant_log) output_tables[index][values[index]]+=aux #Once the output tables have been computed, we create the output messages and store them in #the corresponding variable nodes for index,msg in enumerate(factor_node['input_msgs']): output=output_tables[index] output=np.log(output)+constant_log output[output>inf_log]=inf_log output[output<-inf_log]=-inf_log var_rx=msg['input_node'] reply_msg=create_message(input_node=factor_node,output_node=var_rx,table=output) #Short foor loop to save messages in factor_node in the corresponding order for index2,f in enumerate(var_rx['neighbor_order']): if(f==factor_node['ID']): var_rx['input_msgs'][index2]=reply_msg break def create_joint_node(ID,node_members,neighbor_order,observed_values_indexes=-1): #Routine to define a joint variable node. This is useful to eliminate cycles in #the factor graph and perform exact inference. #Note a routine to create a joint factor node that uses joint variable nodes #is not provided. The corresponding CPD of such factor nodes has to be computed #first and then create the joint node with the function create_factor_node #We do not consider the case that the joint variable node is partially observed #(e.g. one of the joined variable nodes is observed). We only consider the case #where the joint node is completely observed. #See Second Example Message Passing.ipynb for an example of how to define and #manage joint variable nodes. var_node={} var_node['ID']=ID var_node['node_type']=0 var_node['input_msgs']=[] var_node['observed']=-1 var_node['neighbor_order']=np.array(neighbor_order) card=1 #Cardinality of joint node is the product of cardinalities for member in node_members: card*=member['cardinality'] var_node['cardinality']=card var_node['inner_factor']=np.zeros([card,1]) if(observed_values_indexes!=-1): var_node['observed']=variable_index_to_CPD_position(observed_values_indexes,var_node['values'],card) var_node['inner_factor']-=inf_log var_node['inner_factor'][var_node['observed']]=inf_log #Initialize input msgs for index,f in enumerate(var_node['neighbor_order']): var_node['input_msgs'].append(0) return var_node

37.360502

133

0.698439

or_order) var_node['input_msgs']=[] #List to store input messages var_node['observed']=observed_value_index #-1 if the variable is not observed var_node['inner_factor']=np.zeros([cardinality,1]) #Internal vector used to imposed hard messages when variable is observed #If variable is observed, then the inner_factor vector is log[0 0 ... 0 1 0 ...] if(observed_value_index!=-1): var_node['inner_factor']-=inf_log var_node['inner_factor'][observed_value_index]=inf_log #Initialize input msgs by filling with zeros for index,f in enumerate(var_node['neighbor_order']): var_node['input_msgs'].append(0) return var_node def create_message(input_node,output_node,table): #Messages are defined by a dictionary with three keys: input node (sender node), output_node (receiver node), and table of values message={} message['input_node']=input_node message['output_node']=output_node message['table']=table return message def create_factor_node(ID,neighbors,CPD): # Check Nodes are defined by a dictionary with several fields factor_node={} factor_node['ID']=ID factor_node['node_type']=1 factor_node['input_msgs']=[] CPD=np.array(CPD) CPD=CPD.reshape(CPD.shape[0],) #Just to make sure that CPD is a np. array vector of dim. (n,) factor_node['CPD']=np.array(CPD) #CPD table associated to the factor factor_node['CPD_order']=np.zeros([len(neighbors),1]).astype(int) #Ordered array of the neighbor's IDs (neighbors are CNs!) factor_node['cardinalities']=np.zeros([len(neighbors),1]).astype(int) for index,node in enumerate(neighbors): card=node['cardinality'] factor_node['input_msgs'].append( create_message(input_node=node,output_node=factor_node,table=node['inner_factor'])) factor_node['cardinalities'][index]=card factor_node['CPD_order'][index]=node['ID'] return factor_node def initialize_variable(var_node,observed_value_index=-1): var_node['inner_factor']=np.zeros([var_node['cardinality'],1]) var_node['observed']=observed_value_index if(observed_value_index!=-1): var_node['inner_factor']-=inf_log var_node['inner_factor'][observed_value_index]=inf_log def initialize_factor_msgs(factor_node,neighbors): factor_node['input_msgs']=[] for index,node in enumerate(neighbors): factor_node['input_msgs'].append( create_message(input_node=node,output_node=factor_node,table=node['inner_factor'])) def CPD_position_to_variable_index(position,v_card,CPD_size): v_card=np.array(v_card) var_index=np.zeros([v_card.shape[0],1]).astype(int) remaining=CPD_size for i,card in enumerate(v_card): remaining=remaining//card index_i=position//remaining position=position-index_i*(remaining) var_index[i]=index_i return var_index def variable_index_to_CPD_position(var_index,v_card,CPD_size): var_index=np.array(var_index) v_card=np.array(v_card) position=0 offset=CPD_size for i,card in enumerate(v_card): offset=offset//card position+=var_index[i]*offset return position def update_var_to_factor(var_node): prod_table=np.zeros([var_node['cardinality'],1]) for msg in var_node['input_msgs']: prod_table+=msg['table'] prod_table+=var_node['inner_factor'] for msg in var_node['input_msgs']: if(var_node['observed']==-1): reply_table=prod_table-msg['table'] else: reply_table=np.ones([var_node['cardinality'],1])*(-inf_log) reply_table[var_node['observed']]=inf_log reply_table[reply_table>inf_log]=inf_log reply_table[reply_table<-inf_log]=-inf_log factor_rx=msg['input_node'] reply_msg=create_message(input_node=var_node,output_node=factor_rx,table=reply_table) for index,v in enumerate(factor_rx['CPD_order']): if(v==var_node['ID']): factor_rx['input_msgs'][index]=reply_msg break def compute_var_marginal(var_node): marg_table=np.zeros([var_node['cardinality'],1]) for msg in var_node['input_msgs']: marg_table+=msg['table'] marg_table+=var_node['inner_factor'] marg_table=np.exp(marg_table) marg_table/=sum(marg_table) return marg_table def update_factor_to_var(factor_node): output_tables=[] for card in factor_node['cardinalities']: output_tables.append(np.zeros([card,1])) for CPD_entry,CPD_val in enumerate(factor_node['CPD']): values=CPD_position_to_variable_index( position=CPD_entry,v_card=factor_node['cardinalities'],CPD_size=factor_node['CPD'].shape[0]) for index in range(factor_node['cardinalities'].shape[0]): aux=CPD_val for index2 in range(factor_node['cardinalities'].shape[0]): if(index2!=index): aux*=np.exp(factor_node['input_msgs'][index2]['table'][values[index2]]-constant_log) output_tables[index][values[index]]+=aux for index,msg in enumerate(factor_node['input_msgs']): output=output_tables[index] output=np.log(output)+constant_log output[output>inf_log]=inf_log output[output<-inf_log]=-inf_log var_rx=msg['input_node'] reply_msg=create_message(input_node=factor_node,output_node=var_rx,table=output) for index2,f in enumerate(var_rx['neighbor_order']): if(f==factor_node['ID']): var_rx['input_msgs'][index2]=reply_msg break def create_joint_node(ID,node_members,neighbor_order,observed_values_indexes=-1): var_node={} var_node['ID']=ID var_node['node_type']=0 var_node['input_msgs']=[] var_node['observed']=-1 var_node['neighbor_order']=np.array(neighbor_order) card=1 for member in node_members: card*=member['cardinality'] var_node['cardinality']=card var_node['inner_factor']=np.zeros([card,1]) if(observed_values_indexes!=-1): var_node['observed']=variable_index_to_CPD_position(observed_values_indexes,var_node['values'],card) var_node['inner_factor']-=inf_log var_node['inner_factor'][var_node['observed']]=inf_log for index,f in enumerate(var_node['neighbor_order']): var_node['input_msgs'].append(0) return var_node

true

f704dbc440727caa33f14c21d525c911a2a366fb

2,262

py

Python

atlassian_connect_django/rest_framework/authentication.py

gerasev-kirill/atlassian-connect-django

cd44232df512691d9ec14722c38785cf802862e9

[ "MIT" ]

null

atlassian_connect_django/rest_framework/authentication.py

gerasev-kirill/atlassian-connect-django

cd44232df512691d9ec14722c38785cf802862e9

[ "MIT" ]

null

atlassian_connect_django/rest_framework/authentication.py

gerasev-kirill/atlassian-connect-django

cd44232df512691d9ec14722c38785cf802862e9

[ "MIT" ]

null

from six import text_type from rest_framework import HTTP_HEADER_ENCODING, exceptions from django.core.exceptions import PermissionDenied from django.utils.translation import ugettext_lazy as _ from atlassian_connect_django.models.connect import AtlassianUser from atlassian_connect_django import helpers from .models import SecurityContextToken def get_atlassian_security_context_and_user_from_request(request, raise_exceptions=True): def exception(msg): if not raise_exceptions: return None, None if raise_exceptions == 'rest_framework': raise exceptions.AuthenticationFailed(msg) raise PermissionDenied(msg) auth = request.META.get('HTTP_X_JIRA_SECURITY_CONTEXT', b'') if isinstance(auth, text_type): # Work around django test client oddness auth = auth.encode(HTTP_HEADER_ENCODING) auth = auth.split() if not auth or auth[0].lower() != b'token': return None, None if len(auth) == 1: return exception(_('Invalid x-jira-security-context token header. No credentials provided.')) elif len(auth) > 2: return exception(_('Invalid x-jira-security-context token header. Token string should not contain spaces.')) try: token = auth[1].decode() except UnicodeError: return exception(_('Invalid x-jira-security-context token header. Token string should not contain invalid characters.')) try: token = SecurityContextToken.objects.select_related('security_context').get(key=token) except SecurityContextToken.DoesNotExist: return exception(_('Invalid x-jira-security-context token.')) if not token.security_context.is_plugin_enabled: return exception(_('Security context inactive or deleted.')) site = helpers.get_current_site(request=request) if site and site != token.security_context.site: return exception(_('Invalid x-jira-security-context token header. SecurityContext site "%s" not equals to "%s"' % (token.security_context.site.name, site.name))) atlassian_user = AtlassianUser(accountId=token.atlassian_user_account_id) atlassian_user.set_secutiry_context(security_context=token.security_context) return token.security_context, atlassian_user

41.127273

169

0.741821

from six import text_type from rest_framework import HTTP_HEADER_ENCODING, exceptions from django.core.exceptions import PermissionDenied from django.utils.translation import ugettext_lazy as _ from atlassian_connect_django.models.connect import AtlassianUser from atlassian_connect_django import helpers from .models import SecurityContextToken def get_atlassian_security_context_and_user_from_request(request, raise_exceptions=True): def exception(msg): if not raise_exceptions: return None, None if raise_exceptions == 'rest_framework': raise exceptions.AuthenticationFailed(msg) raise PermissionDenied(msg) auth = request.META.get('HTTP_X_JIRA_SECURITY_CONTEXT', b'') if isinstance(auth, text_type): auth = auth.encode(HTTP_HEADER_ENCODING) auth = auth.split() if not auth or auth[0].lower() != b'token': return None, None if len(auth) == 1: return exception(_('Invalid x-jira-security-context token header. No credentials provided.')) elif len(auth) > 2: return exception(_('Invalid x-jira-security-context token header. Token string should not contain spaces.')) try: token = auth[1].decode() except UnicodeError: return exception(_('Invalid x-jira-security-context token header. Token string should not contain invalid characters.')) try: token = SecurityContextToken.objects.select_related('security_context').get(key=token) except SecurityContextToken.DoesNotExist: return exception(_('Invalid x-jira-security-context token.')) if not token.security_context.is_plugin_enabled: return exception(_('Security context inactive or deleted.')) site = helpers.get_current_site(request=request) if site and site != token.security_context.site: return exception(_('Invalid x-jira-security-context token header. SecurityContext site "%s" not equals to "%s"' % (token.security_context.site.name, site.name))) atlassian_user = AtlassianUser(accountId=token.atlassian_user_account_id) atlassian_user.set_secutiry_context(security_context=token.security_context) return token.security_context, atlassian_user

true

f704dd4818c3b8d3017ae2937945bb191f230b62

2,054

py

Python

python_smaclient/smapi_request.py

jloehel/python_smaclient

ed18efb4e19728f3644eb1e510262def57a1767b

[ "0BSD" ]

null

python_smaclient/smapi_request.py

jloehel/python_smaclient

ed18efb4e19728f3644eb1e510262def57a1767b

[ "0BSD" ]

null

python_smaclient/smapi_request.py

jloehel/python_smaclient

ed18efb4e19728f3644eb1e510262def57a1767b

[ "0BSD" ]

null

#!/usr/bin/env python import uuid from construct import Container class SMAPI_Request(object): ''' Implentation of a ICUV Request ''' def __init__(self, function_name, target_identifier, authenticated_userid=b"", password=b"", additional_parameters=b""): self._function_name = function_name self._function_name_length = len(function_name) self._authenticated_userid = authenticated_userid self._authenticated_userid_length = len(authenticated_userid) self._password = password self._password_length = len(password) self._target_identifier = target_identifier self._target_identifier_length = len(target_identifier) self._additional_parameters = additional_parameters self._additional_parameters_length = len(additional_parameters) self._input_length = (self._function_name_length + 4 + self._authenticated_userid_length + 4 + self._password_length + 4 + self._target_identifier_length + 4 + self._additional_parameters_length) def get_container(self): return Container(input_length = self._input_length, function_name_length = self._function_name_length, function_name = self._function_name, authenticated_userid_length = self._authenticated_userid_length, authenticated_userid = self._authenticated_userid, password_length = self._password_length, password = self._password, target_identifier_length = self._target_identifier_length, target_identifier = self._target_identifier, additional_parameters = self._additional_parameters) def __repr__(self): "<{} (container={})>".format( self.__class__.__name__, self.get_container())

44.652174

89

0.624635

import uuid from construct import Container class SMAPI_Request(object): def __init__(self, function_name, target_identifier, authenticated_userid=b"", password=b"", additional_parameters=b""): self._function_name = function_name self._function_name_length = len(function_name) self._authenticated_userid = authenticated_userid self._authenticated_userid_length = len(authenticated_userid) self._password = password self._password_length = len(password) self._target_identifier = target_identifier self._target_identifier_length = len(target_identifier) self._additional_parameters = additional_parameters self._additional_parameters_length = len(additional_parameters) self._input_length = (self._function_name_length + 4 + self._authenticated_userid_length + 4 + self._password_length + 4 + self._target_identifier_length + 4 + self._additional_parameters_length) def get_container(self): return Container(input_length = self._input_length, function_name_length = self._function_name_length, function_name = self._function_name, authenticated_userid_length = self._authenticated_userid_length, authenticated_userid = self._authenticated_userid, password_length = self._password_length, password = self._password, target_identifier_length = self._target_identifier_length, target_identifier = self._target_identifier, additional_parameters = self._additional_parameters) def __repr__(self): "<{} (container={})>".format( self.__class__.__name__, self.get_container())

true

f704ddb7dba518e0334a017e32b36881a1730110

22,096

py

Python

ppmessage/dispatcher/policy.py

augustand/ppmessage

73beac9c75f751d5026ff7defff23732c7419b43

[ "Apache-2.0" ]

6

2017-11-03T17:31:52.000Z

2020-06-14T09:14:36.000Z

ppmessage/dispatcher/policy.py

augustand/ppmessage

73beac9c75f751d5026ff7defff23732c7419b43

[ "Apache-2.0" ]

null

ppmessage/dispatcher/policy.py

augustand/ppmessage

73beac9c75f751d5026ff7defff23732c7419b43

[ "Apache-2.0" ]

16

2017-08-08T01:25:47.000Z

2019-09-17T16:32:06.000Z

# -*- coding: utf-8 -*- # # Copyright (C) 2010-2016 PPMessage. # Guijin Ding, dingguijin@gmail.com # from ppmessage.core.constant import IOS_FAKE_TOKEN from ppmessage.core.constant import CONVERSATION_TYPE from ppmessage.core.constant import MESSAGE_SUBTYPE from ppmessage.core.constant import MESSAGE_STATUS from ppmessage.core.constant import MESSAGE_TYPE from ppmessage.core.constant import TASK_STATUS from ppmessage.core.constant import REDIS_DISPATCHER_NOTIFICATION_KEY from ppmessage.core.constant import REDIS_PUSH_NOTIFICATION_KEY from ppmessage.core.constant import REDIS_MQTTPUSH_KEY from ppmessage.core.constant import REDIS_GCMPUSH_KEY from ppmessage.core.constant import REDIS_IOSPUSH_KEY from ppmessage.core.constant import REDIS_JPUSH_KEY from ppmessage.core.constant import PPCOM_OFFLINE from ppmessage.core.constant import YVOBJECT from ppmessage.core.constant import DIS_SRV from ppmessage.core.constant import OS from ppmessage.db.models import OrgGroup from ppmessage.db.models import DeviceUser from ppmessage.db.models import DeviceInfo from ppmessage.db.models import OrgGroupUserData from ppmessage.db.models import AppUserData from ppmessage.db.models import MessagePush from ppmessage.db.models import MessagePushTask from ppmessage.db.models import PCSocketInfo from ppmessage.db.models import PCSocketDeviceData from ppmessage.db.models import ConversationUserData from ppmessage.core.redis import redis_hash_to_dict from ppmessage.core.utils.datetimestring import datetime_to_timestamp from ppmessage.core.utils.datetimestring import datetime_to_microsecond_timestamp from operator import itemgetter import uuid import time import json import logging class Meta(type): def __init__(cls, name, bases, dict_): type.__init__(cls, name, bases, dict_) return Policy = Meta("Policy", (object,), {}) class AbstractPolicy(Policy): def __init__(self, dis): self._dis = dis self._task = dis._task self._redis = dis.application.redis self._online_users = set() self._offline_users = set() self._devices = set() self._devices_hash = {} self._users_hash = {} self._is_service_user = {} self._conversation_users = set() self._conversation_user_datas_uuid = {} self._conversation_user_datas_hash = {} self._users = set() return @classmethod def conversation_users(cls, _app_uuid, _conversation_uuid, _redis): _key = ConversationUserData.__tablename__ + ".conversation_uuid." + _conversation_uuid _users = _redis.smembers(_key) return list(_users) @classmethod def conversation_datas(cls, _app_uuid, _conversation_uuid, _users, _redis): _pi = _redis.pipeline() _pre = ConversationUserData.__tablename__ + ".app_uuid." + _app_uuid + ".user_uuid." _pos = ".conversation_uuid." + _conversation_uuid for _user_uuid in _users: _key = _pre + _user_uuid + _pos _pi.get(_key) _datas = _pi.execute() return _datas @classmethod def create_conversation_users(cls, _app_uuid, _group_uuid, _redis): return [] @classmethod def app_users(cls, _app_uuid, _is_service_user, _redis): if _app_uuid == None: return [] _key = AppUserData.__tablename__ + \ ".app_uuid." + _app_uuid + \ ".is_service_user." + str(_is_service_user) _users = _redis.smembers(_key) return list(_users) @classmethod def distributor_users(cls, _app_uuid, _redis): # is_service_user == True if _app_uuid == None: return [] _key = AppUserData.__tablename__ + \ ".app_uuid." + _app_uuid + \ ".is_service_user.True" _users = _redis.smembers(_key) return list(_users) @classmethod def group_users(cls, _group_uuid, _redis): _pattern = OrgGroupUserData.__tablename__ + ".group_uuid." + _group_uuid _keys = _redis.smembers(_pattern) return list(_keys) @classmethod def get_service_care_users(cls, _app_uuid, _user_uuid, _redis): return None @classmethod def get_portal_care_users(cls, _app_uuid, _user_uuid, _redis): return None def _android_token(self, _user_uuid, _device_uuid): _token = _user_uuid + "/" + _device_uuid + "/" + self._task["message_type"] + "/" + self._task["uuid"] return _token def _body(self): _message = {} _message["id"] = self._task.get("uuid") _message["fi"] = self._task.get("from_uuid") _message["ti"] = self._task.get("to_uuid") _message["ft"] = self._task.get("from_type") _message["tt"] = self._task.get("to_type") _message["mt"] = self._task.get("message_type") _message["ms"] = self._task.get("message_subtype") _message["ci"] = self._task.get("conversation_uuid") _message["ct"] = self._task.get("conversation_type") _message["tl"] = self._task.get("title") _message["bo"] = self._task.get("body") if _message["ct"] == CONVERSATION_TYPE.S2P: _message["ti"] = self._task["app_uuid"] _message["tt"] = YVOBJECT.AP if isinstance(self._task.get("title"), unicode): _message["tl"] = self._task.get("title").encode("utf-8") if isinstance(self._task.get("body"), unicode): _message["bo"] = self._task.get("body").encode("utf-8") _message["ts"] = datetime_to_microsecond_timestamp(self._task["createtime"]) self._task["message_body"] = _message _message_body = json.dumps(self._task["message_body"]) if isinstance(_message_body, unicode): _message_body = _message_body.encode("utf-8") _values = { "uuid": self._task["uuid"], "task_status": TASK_STATUS.PROCESSED, "message_body": _message_body, } _row = MessagePushTask(**_values) _row.async_update(self._redis) _row.update_redis_keys(self._redis) return def _user_devices(self, _user_uuid): _user = self._users_hash.get(_user_uuid) _is_service_user = self._is_service_user.get(_user_uuid) if _user == None or _is_service_user == None: logging.error("no user or is_service_user in hash: %s" % _user_uuid) return _user["_online_devices"] = {} _device_name = ["mobile_device_uuid", "browser_device_uuid"] if _is_service_user == False: _device_name = ["ppcom_mobile_device_uuid", "ppcom_browser_device_uuid"] for _i in _device_name: _device_uuid = self._users_hash[_user_uuid][_i] if _device_uuid == None or len(_device_uuid) == 0: continue _device = redis_hash_to_dict(self._redis, DeviceInfo, _device_uuid) if _device == None: continue self._devices_hash[_device_uuid] = _device self._devices.add(_device_uuid) if _device.get("device_is_online") == True: _user["_online_devices"][_device_uuid] = _device if len(_user["_online_devices"]) > 0: self._online_users.add(_user_uuid) else: self._offline_users.add(_user_uuid) return def _users_devices(self): for _i in self._users: self._users_hash[_i] = redis_hash_to_dict(self._redis, DeviceUser, _i) for _i in self._users: self._user_devices(_i) logging.info("online : %d, %s" % (len(self._online_users), self._online_users)) logging.info("offline : %d, %s" % (len(self._offline_users), self._offline_users)) return def _pcsocket_data(self, _device_uuid): _redis = self._redis _key = PCSocketDeviceData.__tablename__ + ".device_uuid." + _device_uuid _pc_socket_uuid = _redis.get(_key) if _pc_socket_uuid == None: logging.error("device no pcsocket %s" % _device_uuid) return None _info = redis_hash_to_dict(_redis, PCSocketInfo, _pc_socket_uuid) if _info == None: logging.error("dispatcher cant not find pcsocket %s" % str(_pc_socket_uuid)) return None _d = {"host": _info["host"], "port": _info["port"], "device_uuid": _device_uuid} return _d def _push_to_db(self, _user_uuid, _status=MESSAGE_STATUS.PUSHED): _values = { "uuid": str(uuid.uuid1()), "app_uuid": self._task["app_uuid"], "task_uuid": self._task["uuid"], "user_uuid": _user_uuid, "status": _status } _row = MessagePush(**_values) _row.async_add(self._redis) _row.create_redis_keys(self._redis) return _row.uuid def _push_to_ios(self, _user_uuid, _device_uuid): logging.info("push ios %s:%s" % (_user_uuid, _device_uuid)) _app_uuid = self._task["app_uuid"] _user = self._users_hash.get(_user_uuid) _device = self._devices_hash.get(_device_uuid) _conversation_data = self._conversation_user_datas_hash.get(_user_uuid) if _user == None: logging.error("push ios failed for no user") return if _device == None: logging.error("push ios failed for no device") return _token = _device.get("device_ios_token") if _token == None or len(_token) == 0: logging.error("push ios failed for no ios token") return if _device["device_ios_token"] == IOS_FAKE_TOKEN: logging.error("push ios failed for fake token") return if _conversation_data != None and _conversation_data["user_mute_notification"] == True: # user only do not want recv push for this conversation logging.error("push ios failed for silence required") return _count = 0 if _user.get("user_show_badge") == True: _key = MessagePush.__tablename__ + ".app_uuid." + _app_uuid + ".user_uuid." + _user_uuid _count = self._redis.zcard(_key) _is_dev = bool(_device.get("is_development")) _config = { "is_development": _is_dev, "user_language": _user.get("user_language"), "device_ios_token": _token, "unacked_notification_count": _count, "user_silence_notification": _user.get("user_silence_notification") } _push = { "config": _config, "body": self._task.get("message_body"), "app_uuid": _app_uuid } logging.info("push ios: %s" % str(_push)) self._redis.rpush(REDIS_IOSPUSH_KEY, json.dumps(_push)) return def _push_to_android(self, _user_uuid, _device_uuid): _app_uuid = self._task["app_uuid"] _device = self._devices_hash.get(_device_uuid) _user = self._users_hash.get(_user_uuid) _conversation_data = self._conversation_user_datas_hash.get(_user_uuid) _count = 0 if _user.get("user_show_badge") == True: _key = MessagePush.__tablename__ + ".app_uuid." + _app_uuid + ".user_uuid." + _user_uuid _count = self._redis.zcard(_key) _config = { "user_language": _user.get("user_language"), "unacked_notification_count": _count, "user_silence_notification": _user.get("user_silence_notification") } _push = { "config": _config, "body": self._task.get("message_body"), "app_uuid": _app_uuid } logging.error("try push for android: %s" % str(_push)) if self._task["_app"].get("enable_jpush"): _config["device_android_jpush_registrationid"] = _device.get("device_android_jpush_registrationid") self._redis.rpush(REDIS_JPUSH_KEY, json.dumps(_push)) elif self._task["_app"].get("enable_gcm_push"): _config["device_android_gcmtoken"] = _device.get("device_android_gcmtoken") self._redis.rpush(REDIS_GCMPUSH_KEY, json.dumps(_push)) else: logging.error("no push enable for android: %s" % str(_push)) return def _push_to_socket(self, _user_uuid, _device_uuid): _pcsocket = self._pcsocket_data(_device_uuid) if _pcsocket == None: logging.error("no pcsocket data for: %s" % _device_uuid) return _device = self._devices_hash.get(_device_uuid) # if _device == None: # logging.error("no device hash for: %s" % _device_uuid) # return _from_user = {} _from_type = self._task.get("from_type") _fields = [ "uuid", "user_icon", "user_email", "user_fullname", "updatetime", ] if _from_type == YVOBJECT.DU: for _i in _fields: _from_user[_i] = self._task["_user"].get(_i) _from_user["updatetime"] = datetime_to_timestamp(_from_user["updatetime"]) if _from_type == YVOBJECT.OG: _from_user = self._task["_group"] if _from_type == YVOBJECT.AP: _from_user = self._task["_app"] _body = self._task.get("message_body") _body["pid"] = _device.get("push_uuid") _body["from_user"] = _from_user _push = { "pcsocket": _pcsocket, "body": _body } _key = REDIS_PUSH_NOTIFICATION_KEY + ".host." + _pcsocket["host"] + ".port." + _pcsocket["port"] self._redis.rpush(_key, json.dumps(_push)) return def _push_to_mobile(self, _user_uuid, _device_uuid): _device = self._devices_hash[_device_uuid] if _device["device_ostype"] == OS.IOS: self._push_to_ios(_user_uuid, _device_uuid) return if _device["device_ostype"] == OS.AND: self._push_to_android(_user_uuid, _device_uuid) return return def _push(self): if len(self._online_users) == 0: self.no_online_user() return for _user_uuid in self._online_users: _user = self._users_hash[_user_uuid] _online_devices = _user.get("_online_devices") _real_push = not _user.get("user_mute_notification") _pid = self._push_to_db(_user_uuid) for _device_uuid in _online_devices: self._devices_hash[_device_uuid]["push_uuid"] = _pid self._push_to_socket(_user_uuid, _device_uuid) if _real_push == True: self._push_to_mobile(_user_uuid, _device_uuid) return def _other_device(self): """ the other device uuid belong to same user uuid """ if self._task.get("from_device_uuid") == None: return if self._task.get("from_type") != YVOBJECT.DU: return if self._task.get("_user") == None: return if self._task["conversation_type"] == CONVERSATION_TYPE.P2S: if self._task["_user"]["ppcom_mobile_device_uuid"] == None or \ self._task["_user"]["ppcom_browser_device_uuid"] == None: return if self._task["conversation_type"] == CONVERSATION_TYPE.S2S or \ self._task["conversation_type"] == CONVERSATION_TYPE.S2P: if self._task["_user"]["mobile_device_uuid"] == None or \ self._task["_user"]["browser_device_uuid"] == None: return _device_uuid = None if self._task["conversation_type"] == CONVERSATION_TYPE.P2S: _device_uuid = self._task["_user"]["ppcom_mobile_device_uuid"] if self._task["from_device_uuid"] == self._task["_user"]["ppcom_mobile_device_uuid"]: _device_uuid = self._task["_user"]["ppcom_browser_device_uuid"] else: _device_uuid = self._task["_user"]["mobile_device_uuid"] if self._task["from_device_uuid"] == self._task["_user"]["mobile_device_uuid"]: _device_uuid = self._task["_user"]["browser_device_uuid"] if _device_uuid not in self._devices_hash: _device = redis_hash_to_dict(self._redis, DeviceInfo, _device_uuid) if _device == None or _device["device_is_online"] != True: return self._devices_hash[_device_uuid] = _device _user_uuid = self._task["from_uuid"] if _user_uuid not in self._users_hash: self._users_hash[_user_uuid] = self._task["_user"] _pid = self._push_to_db(_user_uuid) self._devices_hash[_device_uuid]["push_uuid"] = _pid self._push_to_socket(_user_uuid, _device_uuid) return def _explicit(self): """ explicit message SYS type """ _device_uuid = self._task.get("to_device_uuid") _device = redis_hash_to_dict(self._redis, DeviceInfo, _device_uuid) if _device == None: logging.error("no device:%s" % _device_uuid) return _user_uuid = self._task.get("from_uuid") self._users_hash[_user_uuid] = self._task["_user"] self._devices_hash[_device_uuid] = _device # not save db for explicit message self._push_to_socket(_user_uuid, _device_uuid) return def _send_apologize(self, _text): _task = { "uuid": str(uuid.uuid1()), "app_uuid": self._task["app_uuid"], "conversation_uuid": self._task["conversation_uuid"], "conversation_type": CONVERSATION_TYPE.S2P, "message_type": MESSAGE_TYPE.NOTI, "message_subtype": MESSAGE_SUBTYPE.TEXT, "from_uuid": self._task["to_uuid"], "from_type": self._task["to_type"], "to_uuid": self._task["to_uuid"], "to_type": self._task["to_type"], "body": _text, "task_status": TASK_STATUS.PENDING, } _row = MessagePushTask(**_task) _row.async_add(self._redis) _row.create_redis_keys(self._redis) _m = {"task_uuid": _row.uuid} self._redis.rpush(REDIS_DISPATCHER_NOTIFICATION_KEY, json.dumps(_m)) return def _get_app_apologize(self): _text = None _lang = self._task["_user"]["user_language"] if _lang == None or len(_lang) == 0: _lang = "zh_cn" _offline = "offline_" + _lang _text = self._task["_app"][_offline] if _text == None: _text = PPCOM_OFFLINE[_lang] return _text def no_online_user(self): if self._task["conversation_type"] != CONVERSATION_TYPE.P2S: return if self._task["_app"].get("return_offline_message") != True: logging.info("return_offline_message is not set") return _text = self._get_app_apologize() if _text == None: return self._send_apologize(_text) return def users(self): _app_uuid = self._task["app_uuid"] _conversation_uuid = self._task["conversation_uuid"] _users = AbstractPolicy.conversation_users(_app_uuid, _conversation_uuid, self._redis) _datas = AbstractPolicy.conversation_datas(_app_uuid, _conversation_uuid, _users, self._redis) _datas = dict(zip(_users, _datas)) # the is_service_user include the sender user_uuid _table = AppUserData.__tablename__ + ".app_uuid." + _app_uuid + ".user_uuid." _pi = self._redis.pipeline() for _user_uuid in _users: _key = _table + _user_uuid _pi.get(_key) _is = _pi.execute() _is_list = [] for _i in _is: if _i == None or len(_i) == 0: _is_list.append(False) continue _d = json.loads(_i) _is_list.append(_d.get("is_service_user")) self._is_service_user = dict(zip(_users, _is_list)) # remove the sender self if self._task["from_type"] == YVOBJECT.DU: _user_uuid = self._task["from_uuid"] if _user_uuid in _users: _users.remove(_user_uuid) if _user_uuid in _datas: del _datas[_user_uuid] self._users = _users self._conversation_users = _users self._conversation_user_datas_uuid = _datas return def dispatch(self): self._body() if self._task.get("to_device_uuid") != None: self._explicit() return if self._task.get("conversation_uuid") == None: logging.error("no conversation should be explicit") return self.users() self._users_devices() self._push() self._other_device() return class BroadcastPolicy(AbstractPolicy): def __init__(self, dis): super(BroadcastPolicy, self).__init__(dis) return def users(self): super(BroadcastPolicy, self).users() return @classmethod def create_conversation_users(cls, _app_uuid, _group_uuid, _redis): return AbstractPolicy.distributor_users(_app_uuid, _redis) @classmethod def get_service_care_users(cls, _app_uuid, _user_uuid, _redis): _a_users = AbstractPolicy.app_users(_app_uuid, True, _redis) _b_users = AbstractPolicy.app_users(_app_uuid, False, _redis) return _a_users + _b_users @classmethod def get_portal_care_users(cls, _app_uuid, _user_uuid, _redis): _a_users = AbstractPolicy.app_users(_app_uuid, True, _redis) return _a_users

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from ppmessage.core.constant import IOS_FAKE_TOKEN from ppmessage.core.constant import CONVERSATION_TYPE from ppmessage.core.constant import MESSAGE_SUBTYPE from ppmessage.core.constant import MESSAGE_STATUS from ppmessage.core.constant import MESSAGE_TYPE from ppmessage.core.constant import TASK_STATUS from ppmessage.core.constant import REDIS_DISPATCHER_NOTIFICATION_KEY from ppmessage.core.constant import REDIS_PUSH_NOTIFICATION_KEY from ppmessage.core.constant import REDIS_MQTTPUSH_KEY from ppmessage.core.constant import REDIS_GCMPUSH_KEY from ppmessage.core.constant import REDIS_IOSPUSH_KEY from ppmessage.core.constant import REDIS_JPUSH_KEY from ppmessage.core.constant import PPCOM_OFFLINE from ppmessage.core.constant import YVOBJECT from ppmessage.core.constant import DIS_SRV from ppmessage.core.constant import OS from ppmessage.db.models import OrgGroup from ppmessage.db.models import DeviceUser from ppmessage.db.models import DeviceInfo from ppmessage.db.models import OrgGroupUserData from ppmessage.db.models import AppUserData from ppmessage.db.models import MessagePush from ppmessage.db.models import MessagePushTask from ppmessage.db.models import PCSocketInfo from ppmessage.db.models import PCSocketDeviceData from ppmessage.db.models import ConversationUserData from ppmessage.core.redis import redis_hash_to_dict from ppmessage.core.utils.datetimestring import datetime_to_timestamp from ppmessage.core.utils.datetimestring import datetime_to_microsecond_timestamp from operator import itemgetter import uuid import time import json import logging class Meta(type): def __init__(cls, name, bases, dict_): type.__init__(cls, name, bases, dict_) return Policy = Meta("Policy", (object,), {}) class AbstractPolicy(Policy): def __init__(self, dis): self._dis = dis self._task = dis._task self._redis = dis.application.redis self._online_users = set() self._offline_users = set() self._devices = set() self._devices_hash = {} self._users_hash = {} self._is_service_user = {} self._conversation_users = set() self._conversation_user_datas_uuid = {} self._conversation_user_datas_hash = {} self._users = set() return @classmethod def conversation_users(cls, _app_uuid, _conversation_uuid, _redis): _key = ConversationUserData.__tablename__ + ".conversation_uuid." + _conversation_uuid _users = _redis.smembers(_key) return list(_users) @classmethod def conversation_datas(cls, _app_uuid, _conversation_uuid, _users, _redis): _pi = _redis.pipeline() _pre = ConversationUserData.__tablename__ + ".app_uuid." + _app_uuid + ".user_uuid." _pos = ".conversation_uuid." + _conversation_uuid for _user_uuid in _users: _key = _pre + _user_uuid + _pos _pi.get(_key) _datas = _pi.execute() return _datas @classmethod def create_conversation_users(cls, _app_uuid, _group_uuid, _redis): return [] @classmethod def app_users(cls, _app_uuid, _is_service_user, _redis): if _app_uuid == None: return [] _key = AppUserData.__tablename__ + \ ".app_uuid." + _app_uuid + \ ".is_service_user." + str(_is_service_user) _users = _redis.smembers(_key) return list(_users) @classmethod def distributor_users(cls, _app_uuid, _redis): if _app_uuid == None: return [] _key = AppUserData.__tablename__ + \ ".app_uuid." + _app_uuid + \ ".is_service_user.True" _users = _redis.smembers(_key) return list(_users) @classmethod def group_users(cls, _group_uuid, _redis): _pattern = OrgGroupUserData.__tablename__ + ".group_uuid." + _group_uuid _keys = _redis.smembers(_pattern) return list(_keys) @classmethod def get_service_care_users(cls, _app_uuid, _user_uuid, _redis): return None @classmethod def get_portal_care_users(cls, _app_uuid, _user_uuid, _redis): return None def _android_token(self, _user_uuid, _device_uuid): _token = _user_uuid + "/" + _device_uuid + "/" + self._task["message_type"] + "/" + self._task["uuid"] return _token def _body(self): _message = {} _message["id"] = self._task.get("uuid") _message["fi"] = self._task.get("from_uuid") _message["ti"] = self._task.get("to_uuid") _message["ft"] = self._task.get("from_type") _message["tt"] = self._task.get("to_type") _message["mt"] = self._task.get("message_type") _message["ms"] = self._task.get("message_subtype") _message["ci"] = self._task.get("conversation_uuid") _message["ct"] = self._task.get("conversation_type") _message["tl"] = self._task.get("title") _message["bo"] = self._task.get("body") if _message["ct"] == CONVERSATION_TYPE.S2P: _message["ti"] = self._task["app_uuid"] _message["tt"] = YVOBJECT.AP if isinstance(self._task.get("title"), unicode): _message["tl"] = self._task.get("title").encode("utf-8") if isinstance(self._task.get("body"), unicode): _message["bo"] = self._task.get("body").encode("utf-8") _message["ts"] = datetime_to_microsecond_timestamp(self._task["createtime"]) self._task["message_body"] = _message _message_body = json.dumps(self._task["message_body"]) if isinstance(_message_body, unicode): _message_body = _message_body.encode("utf-8") _values = { "uuid": self._task["uuid"], "task_status": TASK_STATUS.PROCESSED, "message_body": _message_body, } _row = MessagePushTask(**_values) _row.async_update(self._redis) _row.update_redis_keys(self._redis) return def _user_devices(self, _user_uuid): _user = self._users_hash.get(_user_uuid) _is_service_user = self._is_service_user.get(_user_uuid) if _user == None or _is_service_user == None: logging.error("no user or is_service_user in hash: %s" % _user_uuid) return _user["_online_devices"] = {} _device_name = ["mobile_device_uuid", "browser_device_uuid"] if _is_service_user == False: _device_name = ["ppcom_mobile_device_uuid", "ppcom_browser_device_uuid"] for _i in _device_name: _device_uuid = self._users_hash[_user_uuid][_i] if _device_uuid == None or len(_device_uuid) == 0: continue _device = redis_hash_to_dict(self._redis, DeviceInfo, _device_uuid) if _device == None: continue self._devices_hash[_device_uuid] = _device self._devices.add(_device_uuid) if _device.get("device_is_online") == True: _user["_online_devices"][_device_uuid] = _device if len(_user["_online_devices"]) > 0: self._online_users.add(_user_uuid) else: self._offline_users.add(_user_uuid) return def _users_devices(self): for _i in self._users: self._users_hash[_i] = redis_hash_to_dict(self._redis, DeviceUser, _i) for _i in self._users: self._user_devices(_i) logging.info("online : %d, %s" % (len(self._online_users), self._online_users)) logging.info("offline : %d, %s" % (len(self._offline_users), self._offline_users)) return def _pcsocket_data(self, _device_uuid): _redis = self._redis _key = PCSocketDeviceData.__tablename__ + ".device_uuid." + _device_uuid _pc_socket_uuid = _redis.get(_key) if _pc_socket_uuid == None: logging.error("device no pcsocket %s" % _device_uuid) return None _info = redis_hash_to_dict(_redis, PCSocketInfo, _pc_socket_uuid) if _info == None: logging.error("dispatcher cant not find pcsocket %s" % str(_pc_socket_uuid)) return None _d = {"host": _info["host"], "port": _info["port"], "device_uuid": _device_uuid} return _d def _push_to_db(self, _user_uuid, _status=MESSAGE_STATUS.PUSHED): _values = { "uuid": str(uuid.uuid1()), "app_uuid": self._task["app_uuid"], "task_uuid": self._task["uuid"], "user_uuid": _user_uuid, "status": _status } _row = MessagePush(**_values) _row.async_add(self._redis) _row.create_redis_keys(self._redis) return _row.uuid def _push_to_ios(self, _user_uuid, _device_uuid): logging.info("push ios %s:%s" % (_user_uuid, _device_uuid)) _app_uuid = self._task["app_uuid"] _user = self._users_hash.get(_user_uuid) _device = self._devices_hash.get(_device_uuid) _conversation_data = self._conversation_user_datas_hash.get(_user_uuid) if _user == None: logging.error("push ios failed for no user") return if _device == None: logging.error("push ios failed for no device") return _token = _device.get("device_ios_token") if _token == None or len(_token) == 0: logging.error("push ios failed for no ios token") return if _device["device_ios_token"] == IOS_FAKE_TOKEN: logging.error("push ios failed for fake token") return if _conversation_data != None and _conversation_data["user_mute_notification"] == True: logging.error("push ios failed for silence required") return _count = 0 if _user.get("user_show_badge") == True: _key = MessagePush.__tablename__ + ".app_uuid." + _app_uuid + ".user_uuid." + _user_uuid _count = self._redis.zcard(_key) _is_dev = bool(_device.get("is_development")) _config = { "is_development": _is_dev, "user_language": _user.get("user_language"), "device_ios_token": _token, "unacked_notification_count": _count, "user_silence_notification": _user.get("user_silence_notification") } _push = { "config": _config, "body": self._task.get("message_body"), "app_uuid": _app_uuid } logging.info("push ios: %s" % str(_push)) self._redis.rpush(REDIS_IOSPUSH_KEY, json.dumps(_push)) return def _push_to_android(self, _user_uuid, _device_uuid): _app_uuid = self._task["app_uuid"] _device = self._devices_hash.get(_device_uuid) _user = self._users_hash.get(_user_uuid) _conversation_data = self._conversation_user_datas_hash.get(_user_uuid) _count = 0 if _user.get("user_show_badge") == True: _key = MessagePush.__tablename__ + ".app_uuid." + _app_uuid + ".user_uuid." + _user_uuid _count = self._redis.zcard(_key) _config = { "user_language": _user.get("user_language"), "unacked_notification_count": _count, "user_silence_notification": _user.get("user_silence_notification") } _push = { "config": _config, "body": self._task.get("message_body"), "app_uuid": _app_uuid } logging.error("try push for android: %s" % str(_push)) if self._task["_app"].get("enable_jpush"): _config["device_android_jpush_registrationid"] = _device.get("device_android_jpush_registrationid") self._redis.rpush(REDIS_JPUSH_KEY, json.dumps(_push)) elif self._task["_app"].get("enable_gcm_push"): _config["device_android_gcmtoken"] = _device.get("device_android_gcmtoken") self._redis.rpush(REDIS_GCMPUSH_KEY, json.dumps(_push)) else: logging.error("no push enable for android: %s" % str(_push)) return def _push_to_socket(self, _user_uuid, _device_uuid): _pcsocket = self._pcsocket_data(_device_uuid) if _pcsocket == None: logging.error("no pcsocket data for: %s" % _device_uuid) return _device = self._devices_hash.get(_device_uuid) _from_user = {} _from_type = self._task.get("from_type") _fields = [ "uuid", "user_icon", "user_email", "user_fullname", "updatetime", ] if _from_type == YVOBJECT.DU: for _i in _fields: _from_user[_i] = self._task["_user"].get(_i) _from_user["updatetime"] = datetime_to_timestamp(_from_user["updatetime"]) if _from_type == YVOBJECT.OG: _from_user = self._task["_group"] if _from_type == YVOBJECT.AP: _from_user = self._task["_app"] _body = self._task.get("message_body") _body["pid"] = _device.get("push_uuid") _body["from_user"] = _from_user _push = { "pcsocket": _pcsocket, "body": _body } _key = REDIS_PUSH_NOTIFICATION_KEY + ".host." + _pcsocket["host"] + ".port." + _pcsocket["port"] self._redis.rpush(_key, json.dumps(_push)) return def _push_to_mobile(self, _user_uuid, _device_uuid): _device = self._devices_hash[_device_uuid] if _device["device_ostype"] == OS.IOS: self._push_to_ios(_user_uuid, _device_uuid) return if _device["device_ostype"] == OS.AND: self._push_to_android(_user_uuid, _device_uuid) return return def _push(self): if len(self._online_users) == 0: self.no_online_user() return for _user_uuid in self._online_users: _user = self._users_hash[_user_uuid] _online_devices = _user.get("_online_devices") _real_push = not _user.get("user_mute_notification") _pid = self._push_to_db(_user_uuid) for _device_uuid in _online_devices: self._devices_hash[_device_uuid]["push_uuid"] = _pid self._push_to_socket(_user_uuid, _device_uuid) if _real_push == True: self._push_to_mobile(_user_uuid, _device_uuid) return def _other_device(self): if self._task.get("from_device_uuid") == None: return if self._task.get("from_type") != YVOBJECT.DU: return if self._task.get("_user") == None: return if self._task["conversation_type"] == CONVERSATION_TYPE.P2S: if self._task["_user"]["ppcom_mobile_device_uuid"] == None or \ self._task["_user"]["ppcom_browser_device_uuid"] == None: return if self._task["conversation_type"] == CONVERSATION_TYPE.S2S or \ self._task["conversation_type"] == CONVERSATION_TYPE.S2P: if self._task["_user"]["mobile_device_uuid"] == None or \ self._task["_user"]["browser_device_uuid"] == None: return _device_uuid = None if self._task["conversation_type"] == CONVERSATION_TYPE.P2S: _device_uuid = self._task["_user"]["ppcom_mobile_device_uuid"] if self._task["from_device_uuid"] == self._task["_user"]["ppcom_mobile_device_uuid"]: _device_uuid = self._task["_user"]["ppcom_browser_device_uuid"] else: _device_uuid = self._task["_user"]["mobile_device_uuid"] if self._task["from_device_uuid"] == self._task["_user"]["mobile_device_uuid"]: _device_uuid = self._task["_user"]["browser_device_uuid"] if _device_uuid not in self._devices_hash: _device = redis_hash_to_dict(self._redis, DeviceInfo, _device_uuid) if _device == None or _device["device_is_online"] != True: return self._devices_hash[_device_uuid] = _device _user_uuid = self._task["from_uuid"] if _user_uuid not in self._users_hash: self._users_hash[_user_uuid] = self._task["_user"] _pid = self._push_to_db(_user_uuid) self._devices_hash[_device_uuid]["push_uuid"] = _pid self._push_to_socket(_user_uuid, _device_uuid) return def _explicit(self): _device_uuid = self._task.get("to_device_uuid") _device = redis_hash_to_dict(self._redis, DeviceInfo, _device_uuid) if _device == None: logging.error("no device:%s" % _device_uuid) return _user_uuid = self._task.get("from_uuid") self._users_hash[_user_uuid] = self._task["_user"] self._devices_hash[_device_uuid] = _device self._push_to_socket(_user_uuid, _device_uuid) return def _send_apologize(self, _text): _task = { "uuid": str(uuid.uuid1()), "app_uuid": self._task["app_uuid"], "conversation_uuid": self._task["conversation_uuid"], "conversation_type": CONVERSATION_TYPE.S2P, "message_type": MESSAGE_TYPE.NOTI, "message_subtype": MESSAGE_SUBTYPE.TEXT, "from_uuid": self._task["to_uuid"], "from_type": self._task["to_type"], "to_uuid": self._task["to_uuid"], "to_type": self._task["to_type"], "body": _text, "task_status": TASK_STATUS.PENDING, } _row = MessagePushTask(**_task) _row.async_add(self._redis) _row.create_redis_keys(self._redis) _m = {"task_uuid": _row.uuid} self._redis.rpush(REDIS_DISPATCHER_NOTIFICATION_KEY, json.dumps(_m)) return def _get_app_apologize(self): _text = None _lang = self._task["_user"]["user_language"] if _lang == None or len(_lang) == 0: _lang = "zh_cn" _offline = "offline_" + _lang _text = self._task["_app"][_offline] if _text == None: _text = PPCOM_OFFLINE[_lang] return _text def no_online_user(self): if self._task["conversation_type"] != CONVERSATION_TYPE.P2S: return if self._task["_app"].get("return_offline_message") != True: logging.info("return_offline_message is not set") return _text = self._get_app_apologize() if _text == None: return self._send_apologize(_text) return def users(self): _app_uuid = self._task["app_uuid"] _conversation_uuid = self._task["conversation_uuid"] _users = AbstractPolicy.conversation_users(_app_uuid, _conversation_uuid, self._redis) _datas = AbstractPolicy.conversation_datas(_app_uuid, _conversation_uuid, _users, self._redis) _datas = dict(zip(_users, _datas)) _table = AppUserData.__tablename__ + ".app_uuid." + _app_uuid + ".user_uuid." _pi = self._redis.pipeline() for _user_uuid in _users: _key = _table + _user_uuid _pi.get(_key) _is = _pi.execute() _is_list = [] for _i in _is: if _i == None or len(_i) == 0: _is_list.append(False) continue _d = json.loads(_i) _is_list.append(_d.get("is_service_user")) self._is_service_user = dict(zip(_users, _is_list)) if self._task["from_type"] == YVOBJECT.DU: _user_uuid = self._task["from_uuid"] if _user_uuid in _users: _users.remove(_user_uuid) if _user_uuid in _datas: del _datas[_user_uuid] self._users = _users self._conversation_users = _users self._conversation_user_datas_uuid = _datas return def dispatch(self): self._body() if self._task.get("to_device_uuid") != None: self._explicit() return if self._task.get("conversation_uuid") == None: logging.error("no conversation should be explicit") return self.users() self._users_devices() self._push() self._other_device() return class BroadcastPolicy(AbstractPolicy): def __init__(self, dis): super(BroadcastPolicy, self).__init__(dis) return def users(self): super(BroadcastPolicy, self).users() return @classmethod def create_conversation_users(cls, _app_uuid, _group_uuid, _redis): return AbstractPolicy.distributor_users(_app_uuid, _redis) @classmethod def get_service_care_users(cls, _app_uuid, _user_uuid, _redis): _a_users = AbstractPolicy.app_users(_app_uuid, True, _redis) _b_users = AbstractPolicy.app_users(_app_uuid, False, _redis) return _a_users + _b_users @classmethod def get_portal_care_users(cls, _app_uuid, _user_uuid, _redis): _a_users = AbstractPolicy.app_users(_app_uuid, True, _redis) return _a_users

true

f704e0229ff68105dd98edffdadbd49a9cb411c6

1,607

py

Python

hard-gists/6623972/snippet.py

jjhenkel/dockerizeme

eaa4fe5366f6b9adf74399eab01c712cacaeb279

[ "Apache-2.0" ]

21

2019-07-08T08:26:45.000Z

2022-01-24T23:53:25.000Z

hard-gists/6623972/snippet.py

jjhenkel/dockerizeme

eaa4fe5366f6b9adf74399eab01c712cacaeb279

[ "Apache-2.0" ]

5

2019-06-15T14:47:47.000Z

2022-02-26T05:02:56.000Z

hard-gists/6623972/snippet.py

jjhenkel/dockerizeme

eaa4fe5366f6b9adf74399eab01c712cacaeb279

[ "Apache-2.0" ]

17

2019-05-16T03:50:34.000Z

2021-01-14T14:35:12.000Z

#!/usr/bin/env python # # author: syl20bnr (2013) # goal: Focus the nth window in the current workspace (limited to 10 firsts) # # Example of usage in i3 config: # # bindsym $mod+0 exec focus_win.py -n 0 # bindsym $mod+1 exec focus_win.py -n 1 # ... ... # bindsym $mod+8 exec focus_win.py -n 8 # bindsym $mod+9 exec focus_win.py -n 9 import argparse from subprocess import Popen import i3 PARSER = argparse.ArgumentParser(prog='focus_win') PARSER.add_argument('-n', '--number', required=True, type=int, choices=[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], help='Window number (limited to [0,9]).') def focus_nth_window(nth): ''' Roughly focus the nth window in the hierarchy (limited to 10 first) ''' wins = get_windows_from_current_workspace() if nth == 0: nth = 10 cmd = 'i3-msg [con_id={0}] focus'.format(wins[nth-1]) Popen(cmd, shell=True) def get_windows_from_current_workspace(): res = [] ws = get_current_workspace() workspace = i3.filter(name=ws) if workspace: workspace = workspace[0] windows = i3.filter(workspace, nodes=[]) for window in windows: res.append(window['id']) return res def get_current_workspace(): ''' Returns the current workspace ''' workspaces = i3.msg('get_workspaces') workspace = i3.filter(tree=workspaces, focused=True) if workspace: return workspace[0]['name'] return '' if __name__ == '__main__': args = PARSER.parse_args() focus_nth_window(args.number)

26.783333

79

0.616677

import argparse from subprocess import Popen import i3 PARSER = argparse.ArgumentParser(prog='focus_win') PARSER.add_argument('-n', '--number', required=True, type=int, choices=[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], help='Window number (limited to [0,9]).') def focus_nth_window(nth): wins = get_windows_from_current_workspace() if nth == 0: nth = 10 cmd = 'i3-msg [con_id={0}] focus'.format(wins[nth-1]) Popen(cmd, shell=True) def get_windows_from_current_workspace(): res = [] ws = get_current_workspace() workspace = i3.filter(name=ws) if workspace: workspace = workspace[0] windows = i3.filter(workspace, nodes=[]) for window in windows: res.append(window['id']) return res def get_current_workspace(): workspaces = i3.msg('get_workspaces') workspace = i3.filter(tree=workspaces, focused=True) if workspace: return workspace[0]['name'] return '' if __name__ == '__main__': args = PARSER.parse_args() focus_nth_window(args.number)

true

f704e2908192786114878cd4a17cb8a00a35bca0

1,437

py

Python

tests/test_normalizers.py

gobadiah/jasonpi

c0dc504cb4be5880d3d2dcedeebd9513a8123569

[ "MIT" ]

null

tests/test_normalizers.py

gobadiah/jasonpi

c0dc504cb4be5880d3d2dcedeebd9513a8123569

[ "MIT" ]

null

tests/test_normalizers.py

gobadiah/jasonpi

c0dc504cb4be5880d3d2dcedeebd9513a8123569

[ "MIT" ]

1

2019-03-05T09:35:06.000Z

import datetime from jasonpi.normalizers import facebook_profile, google_profile def test_facebook_profile(): """ Test that facebook_profile computes a correct profile received from facebook oauth. """ data = { 'email': 'some@email.com', 'first_name': 'Alfred', 'last_name': 'Dupont', 'gender': 'male', 'birthday': '02/25/1970' } profile = facebook_profile(data) assert profile['email'] == data['email'] assert profile['first_name'] == data['first_name'] assert profile['last_name'] == data['last_name'] assert profile['gender'] == data['gender'] assert profile['birthday'] == datetime.date(1970, 2, 25) def test_google_profile(): """ Test that google_profile computes a correct profile received from google oauth. """ data = { 'emailAddresses': [{'value': 'some@email.com'}], 'names': [{'givenName': 'Alfred', 'familyName': 'Dupont'}], 'genders': [{'value': 'male'}], 'birthdays': [{'date': {'year': 1970, 'month': 2, 'day': 25}}] } profile = google_profile(data) assert profile['email'] == data['emailAddresses'][0]['value'] assert profile['first_name'] == data['names'][0]['givenName'] assert profile['last_name'] == data['names'][0]['familyName'] assert profile['gender'] == data['genders'][0]['value'] assert profile['birthday'] == datetime.date(1970, 2, 25)

33.418605

70

0.610299

import datetime from jasonpi.normalizers import facebook_profile, google_profile def test_facebook_profile(): data = { 'email': 'some@email.com', 'first_name': 'Alfred', 'last_name': 'Dupont', 'gender': 'male', 'birthday': '02/25/1970' } profile = facebook_profile(data) assert profile['email'] == data['email'] assert profile['first_name'] == data['first_name'] assert profile['last_name'] == data['last_name'] assert profile['gender'] == data['gender'] assert profile['birthday'] == datetime.date(1970, 2, 25) def test_google_profile(): data = { 'emailAddresses': [{'value': 'some@email.com'}], 'names': [{'givenName': 'Alfred', 'familyName': 'Dupont'}], 'genders': [{'value': 'male'}], 'birthdays': [{'date': {'year': 1970, 'month': 2, 'day': 25}}] } profile = google_profile(data) assert profile['email'] == data['emailAddresses'][0]['value'] assert profile['first_name'] == data['names'][0]['givenName'] assert profile['last_name'] == data['names'][0]['familyName'] assert profile['gender'] == data['genders'][0]['value'] assert profile['birthday'] == datetime.date(1970, 2, 25)

true

f704e2ba80b1a17cddedcb87bc5118b0363446b9

441

py

Python

_draft/x_6_8.py

ofl/kuku2

7247fb1862d917d23258ebe7a93dca5939433225

[ "MIT" ]

null

_draft/x_6_8.py

ofl/kuku2

7247fb1862d917d23258ebe7a93dca5939433225

[ "MIT" ]

1

2021-11-13T08:03:04.000Z

_draft/x_6_8.py

ofl/kuku2

7247fb1862d917d23258ebe7a93dca5939433225

[ "MIT" ]

null

# x_6_8 # # class StockError(Exception): pass class NumberError(Exception): pass order_count = input('きび団子を何個注文しますか？:') card_number = input('カード番号を入力してください？(例、0000-0000-0000-0000):') try: if int(order_count) > 100: raise StockError if card_number != '1111-1111-1111-1111': raise NumberError except StockError: print('在庫切れです') except NumberError: print('カードエラー') else: print('ご購入ありがとうございます')

16.333333

62

0.673469

class StockError(Exception): pass class NumberError(Exception): pass order_count = input('きび団子を何個注文しますか？:') card_number = input('カード番号を入力してください？(例、0000-0000-0000-0000):') try: if int(order_count) > 100: raise StockError if card_number != '1111-1111-1111-1111': raise NumberError except StockError: print('在庫切れです') except NumberError: print('カードエラー') else: print('ご購入ありがとうございます')

true

f704e2ec4bedf7f9433b07f9722cc1c5b621e5ed

10,014

py

Python

electrumx/server/daemon.py

bitcoin-global/global-electrumx

077dc2c3a5bfd9e82dc11784a98f986b8b726336

[ "MIT" ]

1

2020-06-30T18:50:22.000Z

electrumx/server/daemon.py

bitcoin-global/global-electrumx

077dc2c3a5bfd9e82dc11784a98f986b8b726336

[ "MIT" ]

null

electrumx/server/daemon.py

bitcoin-global/global-electrumx

077dc2c3a5bfd9e82dc11784a98f986b8b726336

[ "MIT" ]

1

2020-12-18T17:13:31.000Z

# Copyright (c) 2016-2017, Neil Booth # # All rights reserved. # # See the file "LICENCE" for information about the copyright # and warranty status of this software. '''Class for handling asynchronous connections to a blockchain daemon.''' import asyncio import itertools import json import time import aiohttp from aiorpcx import JSONRPC from electrumx.lib.util import hex_to_bytes, class_logger class DaemonError(Exception): '''Raised when the daemon returns an error in its results.''' class WarmingUpError(Exception): '''Internal - when the daemon is warming up.''' class ServiceRefusedError(Exception): '''Internal - when the daemon doesn't provide a JSON response, only an HTTP error, for some reason.''' class Daemon(object): '''Handles connections to a daemon at the given URL.''' WARMING_UP = -28 id_counter = itertools.count() def __init__(self, coin, url, *, max_workqueue=10, init_retry=0.25, max_retry=4.0): self.coin = coin self.logger = class_logger(__name__, self.__class__.__name__) self.url_index = None self.urls = [] self.set_url(url) # Limit concurrent RPC calls to this number. # See DEFAULT_HTTP_WORKQUEUE in bitcoind, which is typically 16 self.workqueue_semaphore = asyncio.Semaphore(value=max_workqueue) self.init_retry = init_retry self.max_retry = max_retry self._height = None self.available_rpcs = {} self.session = None async def __aenter__(self): self.session = aiohttp.ClientSession(connector=self.connector()) return self async def __aexit__(self, exc_type, exc_value, traceback): await self.session.close() self.session = None def connector(self): return None def set_url(self, url): '''Set the URLS to the given list, and switch to the first one.''' urls = url.split(',') urls = [self.coin.sanitize_url(url) for url in urls] for n, url in enumerate(urls): status = '' if n else ' (current)' logged_url = self.logged_url(url) self.logger.info(f'daemon #{n + 1} at {logged_url}{status}') self.url_index = 0 self.urls = urls def current_url(self): '''Returns the current daemon URL.''' return self.urls[self.url_index] def logged_url(self, url=None): '''The host and port part, for logging.''' url = url or self.current_url() return url[url.rindex('@') + 1:] def failover(self): '''Call to fail-over to the next daemon URL. Returns False if there is only one, otherwise True. ''' if len(self.urls) > 1: self.url_index = (self.url_index + 1) % len(self.urls) self.logger.info(f'failing over to {self.logged_url()}') return True return False async def _send_data(self, data): async with self.workqueue_semaphore: async with self.session.post(self.current_url(), data=data) as resp: kind = resp.headers.get('Content-Type', None) if kind == 'application/json': return await resp.json() text = await resp.text() text = text.strip() or resp.reason raise ServiceRefusedError(text) async def _send(self, payload, processor): '''Send a payload to be converted to JSON. Handles temporary connection issues. Daemon reponse errors are raise through DaemonError. ''' def log_error(error): nonlocal last_error_log, retry now = time.time() if now - last_error_log > 60: last_error_log = now self.logger.error(f'{error}. Retrying occasionally...') if retry == self.max_retry and self.failover(): retry = 0 on_good_message = None last_error_log = 0 data = json.dumps(payload) retry = self.init_retry while True: try: result = await self._send_data(data) result = processor(result) if on_good_message: self.logger.info(on_good_message) return result except asyncio.TimeoutError: log_error('timeout error') except aiohttp.ServerDisconnectedError: log_error('disconnected') on_good_message = 'connection restored' except ConnectionResetError: log_error('connection reset') on_good_message = 'connection restored' except aiohttp.ClientConnectionError: log_error('connection problem - check your daemon is running') on_good_message = 'connection restored' except aiohttp.ClientError as e: log_error(f'daemon error: {e}') on_good_message = 'running normally' except ServiceRefusedError as e: log_error(f'daemon service refused: {e}') on_good_message = 'running normally' except WarmingUpError: log_error('starting up checking blocks') on_good_message = 'running normally' await asyncio.sleep(retry) retry = max(min(self.max_retry, retry * 2), self.init_retry) async def _send_single(self, method, params=None): '''Send a single request to the daemon.''' def processor(result): err = result['error'] if not err: return result['result'] if err.get('code') == self.WARMING_UP: raise WarmingUpError raise DaemonError(err) payload = {'method': method, 'id': next(self.id_counter)} if params: payload['params'] = params return await self._send(payload, processor) async def _send_vector(self, method, params_iterable, replace_errs=False): '''Send several requests of the same method. The result will be an array of the same length as params_iterable. If replace_errs is true, any item with an error is returned as None, otherwise an exception is raised.''' def processor(result): errs = [item['error'] for item in result if item['error']] if any(err.get('code') == self.WARMING_UP for err in errs): raise WarmingUpError if not errs or replace_errs: return [item['result'] for item in result] raise DaemonError(errs) payload = [{'method': method, 'params': p, 'id': next(self.id_counter)} for p in params_iterable] if payload: return await self._send(payload, processor) return [] async def _is_rpc_available(self, method): '''Return whether given RPC method is available in the daemon. Results are cached and the daemon will generally not be queried with the same method more than once.''' available = self.available_rpcs.get(method) if available is None: available = True try: await self._send_single(method) except DaemonError as e: err = e.args[0] error_code = err.get("code") available = error_code != JSONRPC.METHOD_NOT_FOUND self.available_rpcs[method] = available return available async def block_hex_hashes(self, first, count): '''Return the hex hashes of count block starting at height first.''' params_iterable = ((h, ) for h in range(first, first + count)) return await self._send_vector('getblockhash', params_iterable) async def deserialised_block(self, hex_hash): '''Return the deserialised block with the given hex hash.''' return await self._send_single('getblock', (hex_hash, True)) async def raw_blocks(self, hex_hashes): '''Return the raw binary blocks with the given hex hashes.''' params_iterable = ((h, False) for h in hex_hashes) blocks = await self._send_vector('getblock', params_iterable) # Convert hex string to bytes return [hex_to_bytes(block) for block in blocks] async def mempool_hashes(self): '''Update our record of the daemon's mempool hashes.''' return await self._send_single('getrawmempool') async def getnetworkinfo(self): '''Return the result of the 'getnetworkinfo' RPC call.''' return await self._send_single('getnetworkinfo') async def getrawtransaction(self, hex_hash, verbose=False): '''Return the serialized raw transaction with the given hash.''' # Cast to int because some coin daemons are old and require it return await self._send_single('getrawtransaction', (hex_hash, int(verbose))) async def getrawtransactions(self, hex_hashes, replace_errs=True): '''Return the serialized raw transactions with the given hashes. Replaces errors with None by default.''' params_iterable = ((hex_hash, 0) for hex_hash in hex_hashes) txs = await self._send_vector('getrawtransaction', params_iterable, replace_errs=replace_errs) # Convert hex strings to bytes return [hex_to_bytes(tx) if tx else None for tx in txs] async def broadcast_transaction(self, raw_tx): '''Broadcast a transaction to the network.''' return await self._send_single('sendrawtransaction', (raw_tx, )) async def height(self): '''Query the daemon for its current height.''' self._height = await self._send_single('getblockcount') return self._height def cached_height(self): '''Return the cached daemon height. If the daemon has not been queried yet this returns None.''' return self._height

37.931818

90

0.61454

import asyncio import itertools import json import time import aiohttp from aiorpcx import JSONRPC from electrumx.lib.util import hex_to_bytes, class_logger class DaemonError(Exception): class WarmingUpError(Exception): class ServiceRefusedError(Exception): class Daemon(object): WARMING_UP = -28 id_counter = itertools.count() def __init__(self, coin, url, *, max_workqueue=10, init_retry=0.25, max_retry=4.0): self.coin = coin self.logger = class_logger(__name__, self.__class__.__name__) self.url_index = None self.urls = [] self.set_url(url) self.workqueue_semaphore = asyncio.Semaphore(value=max_workqueue) self.init_retry = init_retry self.max_retry = max_retry self._height = None self.available_rpcs = {} self.session = None async def __aenter__(self): self.session = aiohttp.ClientSession(connector=self.connector()) return self async def __aexit__(self, exc_type, exc_value, traceback): await self.session.close() self.session = None def connector(self): return None def set_url(self, url): urls = url.split(',') urls = [self.coin.sanitize_url(url) for url in urls] for n, url in enumerate(urls): status = '' if n else ' (current)' logged_url = self.logged_url(url) self.logger.info(f'daemon #{n + 1} at {logged_url}{status}') self.url_index = 0 self.urls = urls def current_url(self): return self.urls[self.url_index] def logged_url(self, url=None): url = url or self.current_url() return url[url.rindex('@') + 1:] def failover(self): if len(self.urls) > 1: self.url_index = (self.url_index + 1) % len(self.urls) self.logger.info(f'failing over to {self.logged_url()}') return True return False async def _send_data(self, data): async with self.workqueue_semaphore: async with self.session.post(self.current_url(), data=data) as resp: kind = resp.headers.get('Content-Type', None) if kind == 'application/json': return await resp.json() text = await resp.text() text = text.strip() or resp.reason raise ServiceRefusedError(text) async def _send(self, payload, processor): def log_error(error): nonlocal last_error_log, retry now = time.time() if now - last_error_log > 60: last_error_log = now self.logger.error(f'{error}. Retrying occasionally...') if retry == self.max_retry and self.failover(): retry = 0 on_good_message = None last_error_log = 0 data = json.dumps(payload) retry = self.init_retry while True: try: result = await self._send_data(data) result = processor(result) if on_good_message: self.logger.info(on_good_message) return result except asyncio.TimeoutError: log_error('timeout error') except aiohttp.ServerDisconnectedError: log_error('disconnected') on_good_message = 'connection restored' except ConnectionResetError: log_error('connection reset') on_good_message = 'connection restored' except aiohttp.ClientConnectionError: log_error('connection problem - check your daemon is running') on_good_message = 'connection restored' except aiohttp.ClientError as e: log_error(f'daemon error: {e}') on_good_message = 'running normally' except ServiceRefusedError as e: log_error(f'daemon service refused: {e}') on_good_message = 'running normally' except WarmingUpError: log_error('starting up checking blocks') on_good_message = 'running normally' await asyncio.sleep(retry) retry = max(min(self.max_retry, retry * 2), self.init_retry) async def _send_single(self, method, params=None): def processor(result): err = result['error'] if not err: return result['result'] if err.get('code') == self.WARMING_UP: raise WarmingUpError raise DaemonError(err) payload = {'method': method, 'id': next(self.id_counter)} if params: payload['params'] = params return await self._send(payload, processor) async def _send_vector(self, method, params_iterable, replace_errs=False): def processor(result): errs = [item['error'] for item in result if item['error']] if any(err.get('code') == self.WARMING_UP for err in errs): raise WarmingUpError if not errs or replace_errs: return [item['result'] for item in result] raise DaemonError(errs) payload = [{'method': method, 'params': p, 'id': next(self.id_counter)} for p in params_iterable] if payload: return await self._send(payload, processor) return [] async def _is_rpc_available(self, method): available = self.available_rpcs.get(method) if available is None: available = True try: await self._send_single(method) except DaemonError as e: err = e.args[0] error_code = err.get("code") available = error_code != JSONRPC.METHOD_NOT_FOUND self.available_rpcs[method] = available return available async def block_hex_hashes(self, first, count): params_iterable = ((h, ) for h in range(first, first + count)) return await self._send_vector('getblockhash', params_iterable) async def deserialised_block(self, hex_hash): return await self._send_single('getblock', (hex_hash, True)) async def raw_blocks(self, hex_hashes): params_iterable = ((h, False) for h in hex_hashes) blocks = await self._send_vector('getblock', params_iterable) return [hex_to_bytes(block) for block in blocks] async def mempool_hashes(self): return await self._send_single('getrawmempool') async def getnetworkinfo(self): return await self._send_single('getnetworkinfo') async def getrawtransaction(self, hex_hash, verbose=False): return await self._send_single('getrawtransaction', (hex_hash, int(verbose))) async def getrawtransactions(self, hex_hashes, replace_errs=True): params_iterable = ((hex_hash, 0) for hex_hash in hex_hashes) txs = await self._send_vector('getrawtransaction', params_iterable, replace_errs=replace_errs) return [hex_to_bytes(tx) if tx else None for tx in txs] async def broadcast_transaction(self, raw_tx): return await self._send_single('sendrawtransaction', (raw_tx, )) async def height(self): self._height = await self._send_single('getblockcount') return self._height def cached_height(self): return self._height

true

f704e31e46f9b00192e8725b26646591bb78db65

644

py

Python

TODO_LIST/TODO_APP/migrations/0001_initial.py

Amit89499/TODO-APP-DJANGO

082a4ffb803778378c6a8077ca47cf868bc55ef8

[ "Apache-2.0" ]

4

2020-06-29T16:00:39.000Z

2021-05-22T03:40:38.000Z

TODO_LIST/TODO_APP/migrations/0001_initial.py

Amit89499/TODO-APP-DJANGO

082a4ffb803778378c6a8077ca47cf868bc55ef8

[ "Apache-2.0" ]

null

TODO_LIST/TODO_APP/migrations/0001_initial.py

Amit89499/TODO-APP-DJANGO

082a4ffb803778378c6a8077ca47cf868bc55ef8

[ "Apache-2.0" ]

null

# Generated by Django 2.2.4 on 2020-06-21 18:32 from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='task', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title', models.CharField(max_length=200)), ('complete', models.BooleanField(default=False)), ('created', models.DateTimeField(auto_now_add=True)), ], ), ]

26.833333

115

0.555901

from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='task', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title', models.CharField(max_length=200)), ('complete', models.BooleanField(default=False)), ('created', models.DateTimeField(auto_now_add=True)), ], ), ]

true

f704e383be902dc878749e1e1053016142dfdbac

457

py

Python

sportsbet/datasets/__init__.py

ItzBraveNoob/sports-betting

521d4ef6bd0e079d508f40609681124edc2c6805

[ "MIT" ]

49

2020-12-27T15:23:23.000Z

2022-03-30T19:21:13.000Z

sportsbet/datasets/__init__.py

ItzBraveNoob/sports-betting

521d4ef6bd0e079d508f40609681124edc2c6805

[ "MIT" ]

5

2021-04-23T17:41:30.000Z

2022-02-02T14:03:37.000Z

sportsbet/datasets/__init__.py

ItzBraveNoob/sports-betting

521d4ef6bd0e079d508f40609681124edc2c6805

[ "MIT" ]

15

2021-02-13T02:01:49.000Z

2022-03-07T01:09:15.000Z

""" The :mod:`sportsbet.datasets` module provides the tools to download and transform sports betting data. """ from ._base import load from ._soccer._combined import SoccerDataLoader from ._soccer._fd import FDSoccerDataLoader from ._soccer._fte import FTESoccerDataLoader from ._soccer._dummy import DummySoccerDataLoader __all__ = [ 'SoccerDataLoader', 'FDSoccerDataLoader', 'FTESoccerDataLoader', 'DummySoccerDataLoader', 'load', ]

24.052632

52

0.770241

from ._base import load from ._soccer._combined import SoccerDataLoader from ._soccer._fd import FDSoccerDataLoader from ._soccer._fte import FTESoccerDataLoader from ._soccer._dummy import DummySoccerDataLoader __all__ = [ 'SoccerDataLoader', 'FDSoccerDataLoader', 'FTESoccerDataLoader', 'DummySoccerDataLoader', 'load', ]

true

f704e3f96f343e3769531df6f0c6d75bfe0aa5ca

66,444

py

Python

lib/galaxy/webapps/galaxy/controllers/dataset.py

Galaxyinternship/Galaxy

204be086a8c16d6684584cefa9053ed7c86a1784

[ "CC-BY-3.0" ]

null

lib/galaxy/webapps/galaxy/controllers/dataset.py

Galaxyinternship/Galaxy

204be086a8c16d6684584cefa9053ed7c86a1784

[ "CC-BY-3.0" ]

null

lib/galaxy/webapps/galaxy/controllers/dataset.py

Galaxyinternship/Galaxy

204be086a8c16d6684584cefa9053ed7c86a1784

[ "CC-BY-3.0" ]

null

import logging import os import urllib from markupsafe import escape import paste.httpexceptions from six import string_types, text_type from sqlalchemy import false, true from galaxy import datatypes, model, util, web from galaxy import managers from galaxy.datatypes.display_applications.util import decode_dataset_user, encode_dataset_user from galaxy.model.item_attrs import UsesAnnotations, UsesItemRatings from galaxy.util import inflector, smart_str from galaxy.util.sanitize_html import sanitize_html from galaxy.web.base.controller import BaseUIController, ERROR, SUCCESS, url_for, UsesExtendedMetadataMixin from galaxy.web.framework.helpers import grids, iff, time_ago, to_unicode from galaxy.tools.errors import EmailErrorReporter log = logging.getLogger( __name__ ) comptypes = [] try: import zlib # noqa: F401 comptypes.append( 'zip' ) except ImportError: pass class HistoryDatasetAssociationListGrid( grids.Grid ): # Custom columns for grid. class HistoryColumn( grids.GridColumn ): def get_value( self, trans, grid, hda): return escape(hda.history.name) class StatusColumn( grids.GridColumn ): def get_value( self, trans, grid, hda ): if hda.deleted: return "deleted" return "" def get_accepted_filters( self ): """ Returns a list of accepted filters for this column. """ accepted_filter_labels_and_vals = { "Active" : "False", "Deleted" : "True", "All": "All" } accepted_filters = [] for label, val in accepted_filter_labels_and_vals.items(): args = { self.key: val } accepted_filters.append( grids.GridColumnFilter( label, args) ) return accepted_filters # Grid definition title = "Saved Datasets" model_class = model.HistoryDatasetAssociation template = '/dataset/grid.mako' default_sort_key = "-update_time" columns = [ grids.TextColumn( "Name", key="name", # Link name to dataset's history. link=( lambda item: iff( item.history.deleted, None, dict( operation="switch", id=item.id ) ) ), filterable="advanced", attach_popup=True ), HistoryColumn( "History", key="history", sortable=False, target="inbound", link=( lambda item: iff( item.history.deleted, None, dict( operation="switch_history", id=item.id ) ) ) ), grids.IndividualTagsColumn( "Tags", key="tags", model_tag_association_class=model.HistoryDatasetAssociationTagAssociation, filterable="advanced", grid_name="HistoryDatasetAssocationListGrid" ), StatusColumn( "Status", key="deleted", attach_popup=False ), grids.GridColumn( "Last Updated", key="update_time", format=time_ago ), ] columns.append( grids.MulticolFilterColumn( "Search", cols_to_filter=[ columns[0], columns[2] ], key="free-text-search", visible=False, filterable="standard" ) ) operations = [ grids.GridOperation( "Copy to current history", condition=( lambda item: not item.deleted ), async_compatible=True ), ] standard_filters = [] default_filter = dict( name="All", deleted="False", tags="All" ) preserve_state = False use_async = True use_paging = True num_rows_per_page = 50 def build_initial_query( self, trans, **kwargs ): # Show user's datasets that are not deleted, not in deleted histories, and not hidden. # To filter HDAs by user, need to join model class/HDA and History table so that it is # possible to filter by user. However, for dictionary-based filtering to work, need a # primary table for the query. return trans.sa_session.query( self.model_class ).select_from( self.model_class.table.join( model.History.table ) ) \ .filter( model.History.user == trans.user ) \ .filter( self.model_class.deleted == false() ) \ .filter( model.History.deleted == false() ) \ .filter( self.model_class.visible == true() ) class DatasetInterface( BaseUIController, UsesAnnotations, UsesItemRatings, UsesExtendedMetadataMixin ): stored_list_grid = HistoryDatasetAssociationListGrid() def __init__( self, app ): super( DatasetInterface, self ).__init__( app ) self.history_manager = managers.histories.HistoryManager( app ) self.hda_manager = managers.hdas.HDAManager( app ) def _get_job_for_dataset( self, trans, dataset_id ): ''' Return the job for the given dataset. This will throw an error if the dataset is either nonexistent or inaccessible to the user. ''' hda = trans.sa_session.query( trans.app.model.HistoryDatasetAssociation ).get( self.decode_id( dataset_id ) ) assert hda and self._can_access_dataset( trans, hda ) return hda.creating_job def _can_access_dataset( self, trans, dataset_association, allow_admin=True, additional_roles=None ): roles = trans.get_current_user_roles() if additional_roles: roles = roles + additional_roles return ( allow_admin and trans.user_is_admin() ) or trans.app.security_agent.can_access_dataset( roles, dataset_association.dataset ) @web.expose def errors( self, trans, id ): hda = trans.sa_session.query( model.HistoryDatasetAssociation ).get( self.decode_id( id ) ) if not hda or not self._can_access_dataset( trans, hda ): return trans.show_error_message( "Either this dataset does not exist or you do not have permission to access it." ) return trans.fill_template( "dataset/errors.mako", hda=hda ) @web.expose def stdout( self, trans, dataset_id=None, **kwargs ): trans.response.set_content_type( 'text/plain' ) stdout = "" try: job = self._get_job_for_dataset( trans, dataset_id ) stdout = job.stdout except: stdout = "Invalid dataset ID or you are not allowed to access this dataset" return smart_str( stdout ) @web.expose # TODO: Migrate stderr and stdout to use _get_job_for_dataset; it wasn't tested. def stderr( self, trans, dataset_id=None, **kwargs ): trans.response.set_content_type( 'text/plain' ) stderr = "" try: job = self._get_job_for_dataset( trans, dataset_id ) stderr = job.stderr except: stderr = "Invalid dataset ID or you are not allowed to access this dataset" return smart_str( stderr ) @web.expose def exit_code( self, trans, dataset_id=None, **kwargs ): trans.response.set_content_type( 'text/plain' ) exit_code = "" try: job = self._get_job_for_dataset( trans, dataset_id ) exit_code = job.exit_code except: exit_code = "Invalid dataset ID or you are not allowed to access this dataset" return exit_code @web.expose def report_error( self, trans, id, email='', message="", **kwd ): biostar_report = 'biostar' in str( kwd.get( 'submit_error_report') ).lower() if biostar_report: return trans.response.send_redirect( url_for( controller='biostar', action='biostar_tool_bug_report', hda=id, email=email, message=message ) ) try: error_reporter = EmailErrorReporter( id, trans.app ) error_reporter.send_report( user=trans.user, email=email, message=message ) return trans.show_ok_message( "Your error report has been sent" ) except Exception as e: return trans.show_error_message( "An error occurred sending the report by email: %s" % str( e ) ) @web.expose def default(self, trans, dataset_id=None, **kwd): return 'This link may not be followed from within Galaxy.' @web.expose def get_metadata_file(self, trans, hda_id, metadata_name): """ Allows the downloading of metadata files associated with datasets (eg. bai index for bam files) """ data = trans.sa_session.query( trans.app.model.HistoryDatasetAssociation ).get( self.decode_id( hda_id ) ) if not data or not self._can_access_dataset( trans, data ): return trans.show_error_message( "You are not allowed to access this dataset" ) fname = ''.join(c in util.FILENAME_VALID_CHARS and c or '_' for c in data.name)[0:150] file_ext = data.metadata.spec.get(metadata_name).get("file_ext", metadata_name) trans.response.headers["Content-Type"] = "application/octet-stream" trans.response.headers["Content-Disposition"] = 'attachment; filename="Galaxy%s-[%s].%s"' % (data.hid, fname, file_ext) return open(data.metadata.get(metadata_name).file_name) def _check_dataset(self, trans, hda_id): # DEPRECATION: We still support unencoded ids for backward compatibility try: data = trans.sa_session.query( trans.app.model.HistoryDatasetAssociation ).get( self.decode_id( hda_id) ) if data is None: raise ValueError( 'Invalid reference dataset id: %s.' % hda_id) except: try: data = trans.sa_session.query( trans.app.model.HistoryDatasetAssociation ).get( int( hda_id ) ) except: data = None if not data: raise paste.httpexceptions.HTTPRequestRangeNotSatisfiable( "Invalid reference dataset id: %s." % str( hda_id ) ) if not self._can_access_dataset( trans, data ): return trans.show_error_message( "You are not allowed to access this dataset" ) if data.purged: return trans.show_error_message( "The dataset you are attempting to view has been purged." ) if data.deleted and not ( trans.user_is_admin() or ( data.history and trans.get_user() == data.history.user ) ): return trans.show_error_message( "The dataset you are attempting to view has been deleted." ) if data.state == trans.model.Dataset.states.UPLOAD: return trans.show_error_message( "Please wait until this dataset finishes uploading before attempting to view it." ) return data @web.expose @web.json def transfer_status(self, trans, dataset_id, filename=None): """ Primarily used for the S3ObjectStore - get the status of data transfer if the file is not in cache """ data = self._check_dataset(trans, dataset_id) if isinstance( data, string_types ): return data log.debug( "Checking transfer status for dataset %s..." % data.dataset.id ) # Pulling files in extra_files_path into cache is not handled via this # method but that's primarily because those files are typically linked to # through tool's output page anyhow so tying a JavaScript event that will # call this method does not seem doable? if data.dataset.external_filename: return True else: return trans.app.object_store.file_ready(data.dataset) @web.expose def display(self, trans, dataset_id=None, preview=False, filename=None, to_ext=None, offset=None, ck_size=None, **kwd): data = self._check_dataset(trans, dataset_id) if not isinstance( data, trans.app.model.DatasetInstance ): return data # Ensure offset is an integer before passing through to datatypes. if offset: offset = int(offset) # Ensure ck_size is an integer before passing through to datatypes. if ck_size: ck_size = int(ck_size) return data.datatype.display_data(trans, data, preview, filename, to_ext, offset=offset, ck_size=ck_size, **kwd) @web.expose def edit(self, trans, dataset_id=None, filename=None, hid=None, **kwd): """Allows user to modify parameters of an HDA.""" message = None status = 'done' refresh_frames = [] error = False def __ok_to_edit_metadata( dataset_id ): # prevent modifying metadata when dataset is queued or running as input/output # This code could be more efficient, i.e. by using mappers, but to prevent slowing down loading a History panel, we'll leave the code here for now for job_to_dataset_association in trans.sa_session.query( self.app.model.JobToInputDatasetAssociation ) \ .filter_by( dataset_id=dataset_id ) \ .all() \ + trans.sa_session.query( self.app.model.JobToOutputDatasetAssociation ) \ .filter_by( dataset_id=dataset_id ) \ .all(): if job_to_dataset_association.job.state not in [ job_to_dataset_association.job.states.OK, job_to_dataset_association.job.states.ERROR, job_to_dataset_association.job.states.DELETED ]: return False return True if hid is not None: history = trans.get_history() # TODO: hid handling data = history.datasets[ int( hid ) - 1 ] id = None elif dataset_id is not None: id = self.decode_id( dataset_id ) data = trans.sa_session.query( self.app.model.HistoryDatasetAssociation ).get( id ) else: trans.log_event( "dataset_id and hid are both None, cannot load a dataset to edit" ) return trans.show_error_message( "You must provide a history dataset id to edit" ) if data is None: trans.log_event( "Problem retrieving dataset (encoded: %s, decoded: %s) with history id %s." % ( str( dataset_id ), str( id ), str( hid ) ) ) return trans.show_error_message( "History dataset id is invalid" ) if dataset_id is not None and data.history.user is not None and data.history.user != trans.user: trans.log_event( "User attempted to edit an HDA they do not own (encoded: %s, decoded: %s)" % ( dataset_id, id ) ) # Do not reveal the dataset's existence return trans.show_error_message( "History dataset id is invalid" ) current_user_roles = trans.get_current_user_roles() if data.history.user and not data.dataset.has_manage_permissions_roles( trans ): # Permission setting related to DATASET_MANAGE_PERMISSIONS was broken for a period of time, # so it is possible that some Datasets have no roles associated with the DATASET_MANAGE_PERMISSIONS # permission. In this case, we'll reset this permission to the hda user's private role. manage_permissions_action = trans.app.security_agent.get_action( trans.app.security_agent.permitted_actions.DATASET_MANAGE_PERMISSIONS.action ) permissions = { manage_permissions_action : [ trans.app.security_agent.get_private_user_role( data.history.user ) ] } trans.app.security_agent.set_dataset_permission( data.dataset, permissions ) if self._can_access_dataset( trans, data ): if data.state == trans.model.Dataset.states.UPLOAD: return trans.show_error_message( "Please wait until this dataset finishes uploading before attempting to edit its metadata." ) params = util.Params( kwd, sanitize=False ) if params.change: # The user clicked the Save button on the 'Change data type' form if data.datatype.allow_datatype_change and trans.app.datatypes_registry.get_datatype_by_extension( params.datatype ).allow_datatype_change: # prevent modifying datatype when dataset is queued or running as input/output if not __ok_to_edit_metadata( data.id ): message = "This dataset is currently being used as input or output. You cannot change datatype until the jobs have completed or you have canceled them." error = True else: trans.app.datatypes_registry.change_datatype( data, params.datatype ) trans.sa_session.flush() trans.app.datatypes_registry.set_external_metadata_tool.tool_action.execute( trans.app.datatypes_registry.set_external_metadata_tool, trans, incoming={ 'input1': data }, overwrite=False ) # overwrite is False as per existing behavior message = "Changed the type of dataset '%s' to %s" % ( to_unicode( data.name ), params.datatype ) refresh_frames = ['history'] else: message = "You are unable to change datatypes in this manner. Changing %s to %s is not allowed." % ( data.extension, params.datatype ) error = True elif params.save: # The user clicked the Save button on the 'Edit Attributes' form data.name = params.name if params.name else '' data.info = params.info if params.info else '' message = '' if __ok_to_edit_metadata( data.id ): # The following for loop will save all metadata_spec items for name, spec in data.datatype.metadata_spec.items(): if spec.get("readonly"): continue optional = params.get("is_" + name, None) other = params.get("or_" + name, None) if optional and optional == '__NOTHING__': # optional element... == '__NOTHING__' actually means it is NOT checked (and therefore omitted) setattr(data.metadata, name, None) else: if other: setattr( data.metadata, name, other ) else: setattr( data.metadata, name, spec.unwrap( params.get(name, None) ) ) data.datatype.after_setting_metadata( data ) # Sanitize annotation before adding it. if params.annotation: annotation = sanitize_html( params.annotation, 'utf-8', 'text/html' ) self.add_item_annotation( trans.sa_session, trans.get_user(), data, annotation ) # This block on controller code is inactive until the 'extended_metadata' edit box is added back into the UI # Add or delete extended metadata # if params.extended_metadata: # em_string = params.extended_metadata # if len(em_string): # em_payload = None # try: # em_payload = loads(em_string) # except Exception as e: # message = 'Invalid JSON input' # error = True # if em_payload is not None: # if data is not None: # ex_obj = self.get_item_extended_metadata_obj(trans, data) # if ex_obj is not None: # self.unset_item_extended_metadata_obj(trans, data) # self.delete_extended_metadata(trans, ex_obj) # ex_obj = self.create_extended_metadata(trans, em_payload) # self.set_item_extended_metadata_obj(trans, data, ex_obj) # message = "Updated Extended metadata '%s'." % data.name # status = 'done' # else: # message = "data not found" # error = True # else: # if data is not None: # ex_obj = self.get_item_extended_metadata_obj(trans, data) # if ex_obj is not None: # self.unset_item_extended_metadata_obj(trans, data) # self.delete_extended_metadata(trans, ex_obj) # message = "Deleted Extended metadata '%s'." % data.name # status = 'done' # If setting metadata previously failed and all required elements have now been set, clear the failed state. if data._state == trans.model.Dataset.states.FAILED_METADATA and not data.missing_meta(): data._state = None trans.sa_session.flush() message = "Attributes updated%s" % message refresh_frames = ['history'] else: trans.sa_session.flush() message = "Attributes updated, but metadata could not be changed because this dataset is currently being used as input or output. You must cancel or wait for these jobs to complete before changing metadata." status = "warning" refresh_frames = ['history'] elif params.detect: # The user clicked the Auto-detect button on the 'Edit Attributes' form # prevent modifying metadata when dataset is queued or running as input/output if not __ok_to_edit_metadata( data.id ): message = "This dataset is currently being used as input or output. You cannot change metadata until the jobs have completed or you have canceled them." error = True else: for name, spec in data.metadata.spec.items(): # We need to be careful about the attributes we are resetting if name not in [ 'name', 'info', 'dbkey', 'base_name' ]: if spec.get( 'default' ): setattr( data.metadata, name, spec.unwrap( spec.get( 'default' ) ) ) message = 'Attributes have been queued to be updated' trans.app.datatypes_registry.set_external_metadata_tool.tool_action.execute( trans.app.datatypes_registry.set_external_metadata_tool, trans, incoming={ 'input1': data } ) trans.sa_session.flush() refresh_frames = ['history'] elif params.convert_data: target_type = kwd.get("target_type", None) if target_type: message = data.datatype.convert_dataset(trans, data, target_type) refresh_frames = ['history'] elif params.update_roles_button: if not trans.user: return trans.show_error_message( "You must be logged in if you want to change permissions." ) if trans.app.security_agent.can_manage_dataset( current_user_roles, data.dataset ): access_action = trans.app.security_agent.get_action( trans.app.security_agent.permitted_actions.DATASET_ACCESS.action ) manage_permissions_action = trans.app.security_agent.get_action( trans.app.security_agent.permitted_actions.DATASET_MANAGE_PERMISSIONS.action ) # The user associated the DATASET_ACCESS permission on the dataset with 1 or more roles. We # need to ensure that they did not associate roles that would cause accessibility problems. permissions, in_roles, error, message = \ trans.app.security_agent.derive_roles_from_access( trans, data.dataset.id, 'root', **kwd ) if error: # Keep the original role associations for the DATASET_ACCESS permission on the dataset. permissions[ access_action ] = data.dataset.get_access_roles( trans ) status = 'error' else: error = trans.app.security_agent.set_all_dataset_permissions( data.dataset, permissions ) if error: message += error status = 'error' else: message = 'Your changes completed successfully.' trans.sa_session.refresh( data.dataset ) else: message = "You are not authorized to change this dataset's permissions" error = True else: if "dbkey" in data.datatype.metadata_spec and not data.metadata.dbkey: # Copy dbkey into metadata, for backwards compatability # This looks like it does nothing, but getting the dbkey # returns the metadata dbkey unless it is None, in which # case it resorts to the old dbkey. Setting the dbkey # sets it properly in the metadata # This is likely no longer required, since the dbkey exists entirely within metadata (the old_dbkey field is gone): REMOVE ME? data.metadata.dbkey = data.dbkey # let's not overwrite the imported datatypes module with the variable datatypes? # the built-in 'id' is overwritten in lots of places as well ldatatypes = [ dtype_name for dtype_name, dtype_value in trans.app.datatypes_registry.datatypes_by_extension.iteritems() if dtype_value.allow_datatype_change ] ldatatypes.sort() all_roles = trans.app.security_agent.get_legitimate_roles( trans, data.dataset, 'root' ) if error: status = 'error' return trans.fill_template( "/dataset/edit_attributes.mako", data=data, data_annotation=self.get_item_annotation_str( trans.sa_session, trans.user, data ), datatypes=ldatatypes, current_user_roles=current_user_roles, all_roles=all_roles, message=message, status=status, dataset_id=dataset_id, refresh_frames=refresh_frames ) else: return trans.show_error_message( "You do not have permission to edit this dataset's ( id: %s ) information." % str( dataset_id ) ) @web.expose @web.require_login( "see all available datasets" ) def list( self, trans, **kwargs ): """List all available datasets""" status = message = None if 'operation' in kwargs: operation = kwargs['operation'].lower() hda_ids = util.listify( kwargs.get( 'id', [] ) ) # Display no message by default status, message = None, None # Load the hdas and ensure they all belong to the current user hdas = [] for encoded_hda_id in hda_ids: hda_id = self.decode_id( encoded_hda_id ) hda = trans.sa_session.query( model.HistoryDatasetAssociation ).filter_by( id=hda_id ).first() if hda: # Ensure history is owned by current user if hda.history.user_id is not None and trans.user: assert trans.user.id == hda.history.user_id, "HistoryDatasetAssocation does not belong to current user" hdas.append( hda ) else: log.warning( "Invalid history_dataset_association id '%r' passed to list", hda_id ) if hdas: if operation == "switch" or operation == "switch_history": # Switch to a history that the HDA resides in. # Convert hda to histories. histories = [] for hda in hdas: histories.append( hda.history ) # Use history controller to switch the history. TODO: is this reasonable? status, message = trans.webapp.controllers['history']._list_switch( trans, histories ) # Current history changed, refresh history frame; if switching to a dataset, set hda seek. trans.template_context['refresh_frames'] = ['history'] if operation == "switch": hda_ids = [ trans.security.encode_id( hda.id ) for hda in hdas ] trans.template_context[ 'seek_hda_ids' ] = hda_ids elif operation == "copy to current history": # # Copy datasets to the current history. # target_histories = [ trans.get_history() ] # Reverse HDAs so that they appear in the history in the order they are provided. hda_ids.reverse() status, message = self._copy_datasets( trans, hda_ids, target_histories ) # Current history changed, refresh history frame. trans.template_context['refresh_frames'] = ['history'] # Render the list view return self.stored_list_grid( trans, status=status, message=message, **kwargs ) @web.expose def imp( self, trans, dataset_id=None, **kwd ): """ Import another user's dataset via a shared URL; dataset is added to user's current history. """ # Set referer message. referer = trans.request.referer if referer: referer_message = "<a href='%s'>return to the previous page</a>" % escape(referer) else: referer_message = "<a href='%s'>go to Galaxy's start page</a>" % url_for( '/' ) # Error checking. if not dataset_id: return trans.show_error_message( "You must specify a dataset to import. You can %s." % referer_message, use_panels=True ) # Do import. cur_history = trans.get_history( create=True ) status, message = self._copy_datasets( trans, [ dataset_id ], [ cur_history ], imported=True ) message = "Dataset imported. You can <a href='%s'>start using the dataset</a> or %s." % ( url_for('/'), referer_message ) return trans.show_message( message, type=status, use_panels=True ) @web.expose @web.json @web.require_login( "use Galaxy datasets" ) def get_name_and_link_async( self, trans, id=None ): """ Returns dataset's name and link. """ decoded_id = self.decode_id( id ) dataset = self.hda_manager.get_accessible( decoded_id, trans.user ) dataset = self.hda_manager.error_if_uploading( dataset ) return_dict = { "name" : dataset.name, "link" : url_for( controller='dataset', action="display_by_username_and_slug", username=dataset.history.user.username, slug=trans.security.encode_id( dataset.id ) ) } return return_dict @web.expose def get_embed_html_async( self, trans, id ): """ Returns HTML for embedding a dataset in a page. """ decoded_id = self.decode_id( id ) dataset = self.hda_manager.get_accessible( decoded_id, trans.user ) dataset = self.hda_manager.error_if_uploading( dataset ) if dataset: return "Embedded Dataset '%s'" % dataset.name @web.expose @web.require_login( "use Galaxy datasets" ) def set_accessible_async( self, trans, id=None, accessible=False ): """ Does nothing because datasets do not have an importable/accessible attribute. This method could potentially set another attribute. """ return @web.expose @web.require_login( "rate items" ) @web.json def rate_async( self, trans, id, rating ): """ Rate a dataset asynchronously and return updated community data. """ decoded_id = self.decode_id( id ) dataset = self.hda_manager.get_accessible( decoded_id, trans.user ) dataset = self.hda_manager.error_if_uploading( dataset ) if not dataset: return trans.show_error_message( "The specified dataset does not exist." ) # Rate dataset. self.rate_item( trans.sa_session, trans.get_user(), dataset, rating ) return self.get_ave_item_rating_data( trans.sa_session, dataset ) @web.expose def display_by_username_and_slug( self, trans, username, slug, filename=None, preview=True ): """ Display dataset by username and slug; because datasets do not yet have slugs, the slug is the dataset's id. """ id = slug decoded_id = self.decode_id( id ) dataset = self.hda_manager.get_accessible( decoded_id, trans.user ) dataset = self.hda_manager.error_if_uploading( dataset ) if dataset: # Filename used for composite types. if filename: return self.display( trans, dataset_id=slug, filename=filename) truncated, dataset_data = self.hda_manager.text_data( dataset, preview ) dataset.annotation = self.get_item_annotation_str( trans.sa_session, dataset.history.user, dataset ) # If dataset is chunkable, get first chunk. first_chunk = None if dataset.datatype.CHUNKABLE: first_chunk = dataset.datatype.get_chunk(trans, dataset, 0) # If data is binary or an image, stream without template; otherwise, use display template. # TODO: figure out a way to display images in display template. if isinstance(dataset.datatype, datatypes.binary.Binary) or isinstance(dataset.datatype, datatypes.images.Image) or isinstance(dataset.datatype, datatypes.text.Html): trans.response.set_content_type( dataset.get_mime() ) return open( dataset.file_name ) else: # Get rating data. user_item_rating = 0 if trans.get_user(): user_item_rating = self.get_user_item_rating( trans.sa_session, trans.get_user(), dataset ) if user_item_rating: user_item_rating = user_item_rating.rating else: user_item_rating = 0 ave_item_rating, num_ratings = self.get_ave_item_rating_data( trans.sa_session, dataset ) return trans.fill_template_mako( "/dataset/display.mako", item=dataset, item_data=dataset_data, truncated=truncated, user_item_rating=user_item_rating, ave_item_rating=ave_item_rating, num_ratings=num_ratings, first_chunk=first_chunk ) else: raise web.httpexceptions.HTTPNotFound() @web.expose def get_item_content_async( self, trans, id ): """ Returns item content in HTML format. """ decoded_id = self.decode_id( id ) dataset = self.hda_manager.get_accessible( decoded_id, trans.user ) dataset = self.hda_manager.error_if_uploading( dataset ) if dataset is None: raise web.httpexceptions.HTTPNotFound() truncated, dataset_data = self.hda_manager.text_data( dataset, preview=True ) # Get annotation. dataset.annotation = self.get_item_annotation_str( trans.sa_session, trans.user, dataset ) return trans.stream_template_mako( "/dataset/item_content.mako", item=dataset, item_data=dataset_data, truncated=truncated ) @web.expose def annotate_async( self, trans, id, new_annotation=None, **kwargs ): # TODO:?? why is this an access check only? decoded_id = self.decode_id( id ) dataset = self.hda_manager.get_accessible( decoded_id, trans.user ) dataset = self.hda_manager.error_if_uploading( dataset ) if not dataset: web.httpexceptions.HTTPNotFound() if dataset and new_annotation: # Sanitize annotation before adding it. new_annotation = sanitize_html( new_annotation, 'utf-8', 'text/html' ) self.add_item_annotation( trans.sa_session, trans.get_user(), dataset, new_annotation ) trans.sa_session.flush() return new_annotation @web.expose def get_annotation_async( self, trans, id ): decoded_id = self.decode_id( id ) dataset = self.hda_manager.get_accessible( decoded_id, trans.user ) dataset = self.hda_manager.error_if_uploading( dataset ) if not dataset: web.httpexceptions.HTTPNotFound() annotation = self.get_item_annotation_str( trans.sa_session, trans.user, dataset ) if annotation and isinstance( annotation, text_type ): annotation = annotation.encode( 'ascii', 'replace' ) # paste needs ascii here return annotation @web.expose def display_at( self, trans, dataset_id, filename=None, **kwd ): """Sets up a dataset permissions so it is viewable at an external site""" if not trans.app.config.enable_old_display_applications: return trans.show_error_message( "This method of accessing external display applications has been disabled by a Galaxy administrator." ) site = filename data = trans.sa_session.query( trans.app.model.HistoryDatasetAssociation ).get( dataset_id ) if not data: raise paste.httpexceptions.HTTPRequestRangeNotSatisfiable( "Invalid reference dataset id: %s." % str( dataset_id ) ) if 'display_url' not in kwd or 'redirect_url' not in kwd: return trans.show_error_message( 'Invalid parameters specified for "display at" link, please contact a Galaxy administrator' ) try: redirect_url = kwd['redirect_url'] % urllib.quote_plus( kwd['display_url'] ) except: redirect_url = kwd['redirect_url'] # not all will need custom text if trans.app.security_agent.dataset_is_public( data.dataset ): return trans.response.send_redirect( redirect_url ) # anon access already permitted by rbac if self._can_access_dataset( trans, data ): trans.app.host_security_agent.set_dataset_permissions( data, trans.user, site ) return trans.response.send_redirect( redirect_url ) else: return trans.show_error_message( "You are not allowed to view this dataset at external sites. Please contact your Galaxy administrator to acquire management permissions for this dataset." ) @web.expose def display_application( self, trans, dataset_id=None, user_id=None, app_name=None, link_name=None, app_action=None, action_param=None, action_param_extra=None, **kwds ): """Access to external display applications""" # Build list of parameters to pass in to display application logic (app_kwds) app_kwds = {} for name, value in dict(kwds).iteritems(): # clone kwds because we remove stuff as we go. if name.startswith( "app_" ): app_kwds[ name[ len( "app_" ): ] ] = value del kwds[ name ] if kwds: log.debug( "Unexpected Keywords passed to display_application: %s" % kwds ) # route memory? # decode ids data, user = decode_dataset_user( trans, dataset_id, user_id ) if not data: raise paste.httpexceptions.HTTPRequestRangeNotSatisfiable( "Invalid reference dataset id: %s." % str( dataset_id ) ) if user is None: user = trans.user if user: user_roles = user.all_roles() else: user_roles = [] # Decode application name and link name app_name = urllib.unquote_plus( app_name ) link_name = urllib.unquote_plus( link_name ) if None in [ app_name, link_name ]: return trans.show_error_message( "A display application name and link name must be provided." ) if self._can_access_dataset( trans, data, additional_roles=user_roles ): msg = [] preparable_steps = [] refresh = False display_app = trans.app.datatypes_registry.display_applications.get( app_name ) if not display_app: log.debug( "Unknown display application has been requested: %s", app_name ) return paste.httpexceptions.HTTPNotFound( "The requested display application (%s) is not available." % ( app_name ) ) dataset_hash, user_hash = encode_dataset_user( trans, data, user ) try: display_link = display_app.get_link( link_name, data, dataset_hash, user_hash, trans, app_kwds ) except Exception as e: log.debug( "Error generating display_link: %s", e ) # User can sometimes recover from, e.g. conversion errors by fixing input metadata, so use conflict return paste.httpexceptions.HTTPConflict( "Error generating display_link: %s" % e ) if not display_link: log.debug( "Unknown display link has been requested: %s", link_name ) return paste.httpexceptions.HTTPNotFound( "Unknown display link has been requested: %s" % link_name ) if data.state == data.states.ERROR: msg.append( ( 'This dataset is in an error state, you cannot view it at an external display application.', 'error' ) ) elif data.deleted: msg.append( ( 'This dataset has been deleted, you cannot view it at an external display application.', 'error' ) ) elif data.state != data.states.OK: msg.append( ( 'You must wait for this dataset to be created before you can view it at an external display application.', 'info' ) ) refresh = True else: # We have permissions, dataset is not deleted and is in OK state, allow access if display_link.display_ready(): if app_action in [ 'data', 'param' ]: assert action_param, "An action param must be provided for a data or param action" # data is used for things with filenames that could be passed off to a proxy # in case some display app wants all files to be in the same 'directory', # data can be forced to param, but not the other way (no filename for other direction) # get param name from url param name try: action_param = display_link.get_param_name_by_url( action_param ) except ValueError as e: log.debug( e ) return paste.httpexceptions.HTTPNotFound( str( e ) ) value = display_link.get_param_value( action_param ) assert value, "An invalid parameter name was provided: %s" % action_param assert value.parameter.viewable, "This parameter is not viewable." if value.parameter.type == 'data': try: if action_param_extra: assert value.parameter.allow_extra_files_access, "Extra file content requested (%s), but allow_extra_files_access is False." % ( action_param_extra ) file_name = os.path.join( value.extra_files_path, action_param_extra ) else: file_name = value.file_name content_length = os.path.getsize( file_name ) rval = open( file_name ) except OSError as e: log.debug( "Unable to access requested file in display application: %s", e ) return paste.httpexceptions.HTTPNotFound( "This file is no longer available." ) else: rval = str( value ) content_length = len( rval ) trans.response.set_content_type( value.mime_type( action_param_extra=action_param_extra ) ) trans.response.headers[ 'Content-Length' ] = content_length return rval elif app_action is None: # redirect user to url generated by display link # Fix for Safari caching display links, which can change if the underlying dataset has an attribute change, e.g. name, metadata, etc trans.response.headers[ 'Cache-Control' ] = [ 'no-cache', 'max-age=0', 'no-store', 'must-revalidate' ] return trans.response.send_redirect( display_link.display_url() ) else: msg.append( ( 'Invalid action provided: %s' % app_action, 'error' ) ) else: if app_action is None: if trans.history != data.history: msg.append( ( 'You must import this dataset into your current history before you can view it at the desired display application.', 'error' ) ) else: refresh = True msg.append( ( 'Launching this display application required additional datasets to be generated, you can view the status of these jobs below. ', 'info' ) ) if not display_link.preparing_display(): display_link.prepare_display() preparable_steps = display_link.get_prepare_steps() else: raise Exception( 'Attempted a view action (%s) on a non-ready display application' % app_action ) return trans.fill_template_mako( "dataset/display_application/display.mako", msg=msg, display_app=display_app, display_link=display_link, refresh=refresh, preparable_steps=preparable_steps ) return trans.show_error_message( 'You do not have permission to view this dataset at an external display application.' ) def _delete( self, trans, dataset_id ): message = None status = 'done' id = None try: id = self.decode_id( dataset_id ) hda = trans.sa_session.query( self.app.model.HistoryDatasetAssociation ).get( id ) assert hda, 'Invalid HDA: %s' % id # Walk up parent datasets to find the containing history topmost_parent = hda while topmost_parent.parent: topmost_parent = topmost_parent.parent assert topmost_parent in trans.history.datasets, "Data does not belong to current history" # Mark deleted and cleanup hda.mark_deleted() hda.clear_associated_files() trans.log_event( "Dataset id %s marked as deleted" % str(id) ) self.hda_manager.stop_creating_job( hda ) trans.sa_session.flush() except Exception as e: msg = 'HDA deletion failed (encoded: %s, decoded: %s)' % ( dataset_id, id ) log.exception( msg + ': ' + str( e ) ) trans.log_event( msg ) message = 'Dataset deletion failed' status = 'error' return ( message, status ) def _undelete( self, trans, dataset_id ): message = None status = 'done' id = None try: id = self.decode_id( dataset_id ) history = trans.get_history() hda = trans.sa_session.query( self.app.model.HistoryDatasetAssociation ).get( id ) assert hda and hda.undeletable, 'Invalid HDA: %s' % id # Walk up parent datasets to find the containing history topmost_parent = hda while topmost_parent.parent: topmost_parent = topmost_parent.parent assert topmost_parent in history.datasets, "Data does not belong to current history" # Mark undeleted hda.mark_undeleted() trans.sa_session.flush() trans.log_event( "Dataset id %s has been undeleted" % str(id) ) except Exception: msg = 'HDA undeletion failed (encoded: %s, decoded: %s)' % ( dataset_id, id ) log.exception( msg ) trans.log_event( msg ) message = 'Dataset undeletion failed' status = 'error' return ( message, status ) def _unhide( self, trans, dataset_id ): try: id = self.decode_id( dataset_id ) except: return False history = trans.get_history() hda = trans.sa_session.query( self.app.model.HistoryDatasetAssociation ).get( id ) if hda: # Walk up parent datasets to find the containing history topmost_parent = hda while topmost_parent.parent: topmost_parent = topmost_parent.parent assert topmost_parent in history.datasets, "Data does not belong to current history" # Mark undeleted hda.mark_unhidden() trans.sa_session.flush() trans.log_event( "Dataset id %s has been unhidden" % str(id) ) return True return False def _purge( self, trans, dataset_id ): message = None status = 'done' try: id = self.decode_id( dataset_id ) user = trans.get_user() hda = trans.sa_session.query( self.app.model.HistoryDatasetAssociation ).get( id ) # Invalid HDA assert hda, 'Invalid history dataset ID' # Walk up parent datasets to find the containing history topmost_parent = hda while topmost_parent.parent: topmost_parent = topmost_parent.parent # If the user is anonymous, make sure the HDA is owned by the current session. if not user: current_history_id = trans.galaxy_session.current_history_id assert topmost_parent.history.id == current_history_id, 'Data does not belong to current user' # If the user is known, make sure the HDA is owned by the current user. else: assert topmost_parent.history.user == user, 'Data does not belong to current user' # Ensure HDA is deleted hda.deleted = True # HDA is purgeable # Decrease disk usage first if user: user.adjust_total_disk_usage(-hda.quota_amount(user)) # Mark purged hda.purged = True trans.sa_session.add( hda ) trans.log_event( "HDA id %s has been purged" % hda.id ) trans.sa_session.flush() # Don't delete anything if there are active HDAs or any LDDAs, even if # the LDDAs are deleted. Let the cleanup scripts get it in the latter # case. if hda.dataset.user_can_purge: try: hda.dataset.full_delete() trans.log_event( "Dataset id %s has been purged upon the the purge of HDA id %s" % ( hda.dataset.id, hda.id ) ) trans.sa_session.add( hda.dataset ) except: log.exception( 'Unable to purge dataset (%s) on purge of HDA (%s):' % ( hda.dataset.id, hda.id ) ) trans.sa_session.flush() except Exception as exc: msg = 'HDA purge failed (encoded: %s, decoded: %s): %s' % ( dataset_id, id, exc ) log.exception( msg ) trans.log_event( msg ) message = 'Dataset removal from disk failed' status = 'error' return ( message, status ) @web.expose def delete( self, trans, dataset_id, filename, show_deleted_on_refresh=False ): message, status = self._delete( trans, dataset_id ) return trans.response.send_redirect( web.url_for( controller='root', action='history', show_deleted=show_deleted_on_refresh, message=message, status=status ) ) @web.expose def delete_async( self, trans, dataset_id, filename ): message, status = self._delete( trans, dataset_id ) if status == 'done': return "OK" else: raise Exception( message ) @web.expose def undelete( self, trans, dataset_id, filename ): message, status = self._undelete( trans, dataset_id ) return trans.response.send_redirect( web.url_for( controller='root', action='history', show_deleted=True, message=message, status=status ) ) @web.expose def undelete_async( self, trans, dataset_id, filename ): message, status = self._undelete( trans, dataset_id ) if status == 'done': return "OK" else: raise Exception( message ) @web.expose def unhide( self, trans, dataset_id, filename ): if self._unhide( trans, dataset_id ): return trans.response.send_redirect( web.url_for( controller='root', action='history', show_hidden=True ) ) raise Exception( "Error unhiding" ) @web.expose def purge( self, trans, dataset_id, filename, show_deleted_on_refresh=False ): if trans.app.config.allow_user_dataset_purge: message, status = self._purge( trans, dataset_id ) else: message = "Removal of datasets by users is not allowed in this Galaxy instance. Please contact your Galaxy administrator." status = 'error' return trans.response.send_redirect( web.url_for( controller='root', action='history', show_deleted=show_deleted_on_refresh, message=message, status=status ) ) @web.expose def purge_async( self, trans, dataset_id, filename ): if trans.app.config.allow_user_dataset_purge: message, status = self._purge( trans, dataset_id ) else: message = "Removal of datasets by users is not allowed in this Galaxy instance. Please contact your Galaxy administrator." status = 'error' if status == 'done': return "OK" else: raise Exception( message ) @web.expose def show_params( self, trans, dataset_id=None, from_noframe=None, **kwd ): """ Show the parameters used for the job associated with an HDA """ try: hda = trans.sa_session.query( trans.app.model.HistoryDatasetAssociation ).get( self.decode_id( dataset_id ) ) except ValueError: hda = None if not hda: raise paste.httpexceptions.HTTPRequestRangeNotSatisfiable( "Invalid reference dataset id: %s." % escape( str( dataset_id ) ) ) if not self._can_access_dataset( trans, hda ): return trans.show_error_message( "You are not allowed to access this dataset" ) # Get the associated job, if any. If this hda was copied from another, # we need to find the job that created the origial dataset association. params_objects = None job = None tool = None upgrade_messages = {} has_parameter_errors = False inherit_chain = hda.source_dataset_chain if inherit_chain: job_dataset_association = inherit_chain[-1][0] else: job_dataset_association = hda if job_dataset_association.creating_job_associations: job = job_dataset_association.creating_job_associations[0].job if job: # Get the tool object try: # Load the tool toolbox = self.get_toolbox() tool = toolbox.get_tool( job.tool_id ) assert tool is not None, 'Requested tool has not been loaded.' # Load parameter objects, if a parameter type has changed, it's possible for the value to no longer be valid try: params_objects = job.get_param_values( trans.app, ignore_errors=False ) except: params_objects = job.get_param_values( trans.app, ignore_errors=True ) # use different param_objects in the following line, since we want to display original values as much as possible upgrade_messages = tool.check_and_update_param_values( job.get_param_values( trans.app, ignore_errors=True ), trans, update_values=False ) has_parameter_errors = True except: pass if job is None: return trans.show_error_message( "Job information is not available for this dataset." ) # TODO: we should provide the basic values along with the objects, in order to better handle reporting of old values during upgrade return trans.fill_template( "show_params.mako", inherit_chain=inherit_chain, history=trans.get_history(), hda=hda, job=job, tool=tool, params_objects=params_objects, upgrade_messages=upgrade_messages, has_parameter_errors=has_parameter_errors ) @web.expose def copy_datasets( self, trans, source_history=None, source_content_ids="", target_history_id=None, target_history_ids="", new_history_name="", do_copy=False, **kwd ): user = trans.get_user() if source_history is not None: decoded_source_history_id = self.decode_id( source_history ) history = self.history_manager.get_owned( decoded_source_history_id, trans.user, current_history=trans.history ) current_history = trans.get_history() else: history = current_history = trans.get_history() refresh_frames = [] if source_content_ids: if not isinstance( source_content_ids, list ): source_content_ids = source_content_ids.split(",") encoded_dataset_collection_ids = [ s[ len("dataset_collection|"): ] for s in source_content_ids if s.startswith("dataset_collection|") ] encoded_dataset_ids = [ s[ len("dataset|"): ] for s in source_content_ids if s.startswith("dataset|") ] decoded_dataset_collection_ids = set(map( self.decode_id, encoded_dataset_collection_ids )) decoded_dataset_ids = set(map( self.decode_id, encoded_dataset_ids )) else: decoded_dataset_collection_ids = [] decoded_dataset_ids = [] if new_history_name: target_history_ids = [] else: if target_history_id: target_history_ids = [ self.decode_id(target_history_id) ] elif target_history_ids: if not isinstance( target_history_ids, list ): target_history_ids = target_history_ids.split(",") target_history_ids = list(set([ self.decode_id(h) for h in target_history_ids if h ])) else: target_history_ids = [] done_msg = error_msg = "" new_history = None if do_copy: invalid_contents = 0 if not ( decoded_dataset_ids or decoded_dataset_collection_ids ) or not ( target_history_ids or new_history_name ): error_msg = "You must provide both source datasets and target histories. " else: if new_history_name: new_history = trans.app.model.History() new_history.name = new_history_name new_history.user = user trans.sa_session.add( new_history ) trans.sa_session.flush() target_history_ids.append( new_history.id ) if user: target_histories = [ hist for hist in map( trans.sa_session.query( trans.app.model.History ).get, target_history_ids ) if hist is not None and hist.user == user ] else: target_histories = [ history ] if len( target_histories ) != len( target_history_ids ): error_msg = error_msg + "You do not have permission to add datasets to %i requested histories. " % ( len( target_history_ids ) - len( target_histories ) ) source_contents = map( trans.sa_session.query( trans.app.model.HistoryDatasetAssociation ).get, decoded_dataset_ids ) source_contents.extend( map( trans.sa_session.query( trans.app.model.HistoryDatasetCollectionAssociation ).get, decoded_dataset_collection_ids ) ) source_contents.sort(key=lambda content: content.hid) for content in source_contents: if content is None: error_msg = error_msg + "You tried to copy a dataset that does not exist. " invalid_contents += 1 elif content.history != history: error_msg = error_msg + "You tried to copy a dataset which is not in your current history. " invalid_contents += 1 else: for hist in target_histories: if content.history_content_type == "dataset": hist.add_dataset( content.copy( copy_children=True ) ) else: copy_collected_datasets = True copy_kwds = {} if copy_collected_datasets: copy_kwds["element_destination"] = hist hist.add_dataset_collection( content.copy( **copy_kwds ) ) if current_history in target_histories: refresh_frames = ['history'] trans.sa_session.flush() hist_names_str = ", ".join( ['<a href="%s" target="_top">%s</a>' % ( url_for( controller="history", action="switch_to_history", hist_id=trans.security.encode_id( hist.id ) ), escape(hist.name) ) for hist in target_histories ] ) num_source = len( source_content_ids ) - invalid_contents num_target = len(target_histories) done_msg = "%i %s copied to %i %s: %s." % (num_source, inflector.cond_plural(num_source, "dataset"), num_target, inflector.cond_plural(num_target, "history"), hist_names_str ) trans.sa_session.refresh( history ) source_contents = history.active_contents target_histories = [history] if user: target_histories = user.active_histories return trans.fill_template( "/dataset/copy_view.mako", source_history=history, current_history=current_history, source_content_ids=source_content_ids, target_history_id=target_history_id, target_history_ids=target_history_ids, source_contents=source_contents, target_histories=target_histories, new_history_name=new_history_name, done_msg=done_msg, error_msg=error_msg, refresh_frames=refresh_frames ) def _copy_datasets( self, trans, dataset_ids, target_histories, imported=False ): """ Helper method for copying datasets. """ user = trans.get_user() done_msg = error_msg = "" invalid_datasets = 0 if not dataset_ids or not target_histories: error_msg = "You must provide both source datasets and target histories." else: # User must own target histories to copy datasets to them. for history in target_histories: if user != history.user: error_msg = error_msg + "You do not have permission to add datasets to %i requested histories. " % ( len( target_histories ) ) for dataset_id in dataset_ids: decoded_id = self.decode_id( dataset_id ) data = self.hda_manager.get_accessible( decoded_id, trans.user ) data = self.hda_manager.error_if_uploading( data ) if data is None: error_msg = error_msg + "You tried to copy a dataset that does not exist or that you do not have access to. " invalid_datasets += 1 else: for hist in target_histories: dataset_copy = data.copy( copy_children=True ) if imported: dataset_copy.name = "imported: " + dataset_copy.name hist.add_dataset( dataset_copy ) trans.sa_session.flush() num_datasets_copied = len( dataset_ids ) - invalid_datasets done_msg = "%i dataset%s copied to %i histor%s." % \ ( num_datasets_copied, iff( num_datasets_copied == 1, "", "s"), len( target_histories ), iff( len( target_histories ) == 1, "y", "ies") ) trans.sa_session.refresh( history ) if error_msg != "": status = ERROR message = error_msg else: status = SUCCESS message = done_msg return status, message

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import logging import os import urllib from markupsafe import escape import paste.httpexceptions from six import string_types, text_type from sqlalchemy import false, true from galaxy import datatypes, model, util, web from galaxy import managers from galaxy.datatypes.display_applications.util import decode_dataset_user, encode_dataset_user from galaxy.model.item_attrs import UsesAnnotations, UsesItemRatings from galaxy.util import inflector, smart_str from galaxy.util.sanitize_html import sanitize_html from galaxy.web.base.controller import BaseUIController, ERROR, SUCCESS, url_for, UsesExtendedMetadataMixin from galaxy.web.framework.helpers import grids, iff, time_ago, to_unicode from galaxy.tools.errors import EmailErrorReporter log = logging.getLogger( __name__ ) comptypes = [] try: import zlib comptypes.append( 'zip' ) except ImportError: pass class HistoryDatasetAssociationListGrid( grids.Grid ): class HistoryColumn( grids.GridColumn ): def get_value( self, trans, grid, hda): return escape(hda.history.name) class StatusColumn( grids.GridColumn ): def get_value( self, trans, grid, hda ): if hda.deleted: return "deleted" return "" def get_accepted_filters( self ): accepted_filter_labels_and_vals = { "Active" : "False", "Deleted" : "True", "All": "All" } accepted_filters = [] for label, val in accepted_filter_labels_and_vals.items(): args = { self.key: val } accepted_filters.append( grids.GridColumnFilter( label, args) ) return accepted_filters title = "Saved Datasets" model_class = model.HistoryDatasetAssociation template = '/dataset/grid.mako' default_sort_key = "-update_time" columns = [ grids.TextColumn( "Name", key="name", link=( lambda item: iff( item.history.deleted, None, dict( operation="switch", id=item.id ) ) ), filterable="advanced", attach_popup=True ), HistoryColumn( "History", key="history", sortable=False, target="inbound", link=( lambda item: iff( item.history.deleted, None, dict( operation="switch_history", id=item.id ) ) ) ), grids.IndividualTagsColumn( "Tags", key="tags", model_tag_association_class=model.HistoryDatasetAssociationTagAssociation, filterable="advanced", grid_name="HistoryDatasetAssocationListGrid" ), StatusColumn( "Status", key="deleted", attach_popup=False ), grids.GridColumn( "Last Updated", key="update_time", format=time_ago ), ] columns.append( grids.MulticolFilterColumn( "Search", cols_to_filter=[ columns[0], columns[2] ], key="free-text-search", visible=False, filterable="standard" ) ) operations = [ grids.GridOperation( "Copy to current history", condition=( lambda item: not item.deleted ), async_compatible=True ), ] standard_filters = [] default_filter = dict( name="All", deleted="False", tags="All" ) preserve_state = False use_async = True use_paging = True num_rows_per_page = 50 def build_initial_query( self, trans, **kwargs ): # Show user's datasets that are not deleted, not in deleted histories, and not hidden. return trans.sa_session.query( self.model_class ).select_from( self.model_class.table.join( model.History.table ) ) \ .filter( model.History.user == trans.user ) \ .filter( self.model_class.deleted == false() ) \ .filter( model.History.deleted == false() ) \ .filter( self.model_class.visible == true() ) class DatasetInterface( BaseUIController, UsesAnnotations, UsesItemRatings, UsesExtendedMetadataMixin ): stored_list_grid = HistoryDatasetAssociationListGrid() def __init__( self, app ): super( DatasetInterface, self ).__init__( app ) self.history_manager = managers.histories.HistoryManager( app ) self.hda_manager = managers.hdas.HDAManager( app ) def _get_job_for_dataset( self, trans, dataset_id ): hda = trans.sa_session.query( trans.app.model.HistoryDatasetAssociation ).get( self.decode_id( dataset_id ) ) assert hda and self._can_access_dataset( trans, hda ) return hda.creating_job def _can_access_dataset( self, trans, dataset_association, allow_admin=True, additional_roles=None ): roles = trans.get_current_user_roles() if additional_roles: roles = roles + additional_roles return ( allow_admin and trans.user_is_admin() ) or trans.app.security_agent.can_access_dataset( roles, dataset_association.dataset ) @web.expose def errors( self, trans, id ): hda = trans.sa_session.query( model.HistoryDatasetAssociation ).get( self.decode_id( id ) ) if not hda or not self._can_access_dataset( trans, hda ): return trans.show_error_message( "Either this dataset does not exist or you do not have permission to access it." ) return trans.fill_template( "dataset/errors.mako", hda=hda ) @web.expose def stdout( self, trans, dataset_id=None, **kwargs ): trans.response.set_content_type( 'text/plain' ) stdout = "" try: job = self._get_job_for_dataset( trans, dataset_id ) stdout = job.stdout except: stdout = "Invalid dataset ID or you are not allowed to access this dataset" return smart_str( stdout ) @web.expose def stderr( self, trans, dataset_id=None, **kwargs ): trans.response.set_content_type( 'text/plain' ) stderr = "" try: job = self._get_job_for_dataset( trans, dataset_id ) stderr = job.stderr except: stderr = "Invalid dataset ID or you are not allowed to access this dataset" return smart_str( stderr ) @web.expose def exit_code( self, trans, dataset_id=None, **kwargs ): trans.response.set_content_type( 'text/plain' ) exit_code = "" try: job = self._get_job_for_dataset( trans, dataset_id ) exit_code = job.exit_code except: exit_code = "Invalid dataset ID or you are not allowed to access this dataset" return exit_code @web.expose def report_error( self, trans, id, email='', message="", **kwd ): biostar_report = 'biostar' in str( kwd.get( 'submit_error_report') ).lower() if biostar_report: return trans.response.send_redirect( url_for( controller='biostar', action='biostar_tool_bug_report', hda=id, email=email, message=message ) ) try: error_reporter = EmailErrorReporter( id, trans.app ) error_reporter.send_report( user=trans.user, email=email, message=message ) return trans.show_ok_message( "Your error report has been sent" ) except Exception as e: return trans.show_error_message( "An error occurred sending the report by email: %s" % str( e ) ) @web.expose def default(self, trans, dataset_id=None, **kwd): return 'This link may not be followed from within Galaxy.' @web.expose def get_metadata_file(self, trans, hda_id, metadata_name): data = trans.sa_session.query( trans.app.model.HistoryDatasetAssociation ).get( self.decode_id( hda_id ) ) if not data or not self._can_access_dataset( trans, data ): return trans.show_error_message( "You are not allowed to access this dataset" ) fname = ''.join(c in util.FILENAME_VALID_CHARS and c or '_' for c in data.name)[0:150] file_ext = data.metadata.spec.get(metadata_name).get("file_ext", metadata_name) trans.response.headers["Content-Type"] = "application/octet-stream" trans.response.headers["Content-Disposition"] = 'attachment; filename="Galaxy%s-[%s].%s"' % (data.hid, fname, file_ext) return open(data.metadata.get(metadata_name).file_name) def _check_dataset(self, trans, hda_id): # DEPRECATION: We still support unencoded ids for backward compatibility try: data = trans.sa_session.query( trans.app.model.HistoryDatasetAssociation ).get( self.decode_id( hda_id) ) if data is None: raise ValueError( 'Invalid reference dataset id: %s.' % hda_id) except: try: data = trans.sa_session.query( trans.app.model.HistoryDatasetAssociation ).get( int( hda_id ) ) except: data = None if not data: raise paste.httpexceptions.HTTPRequestRangeNotSatisfiable( "Invalid reference dataset id: %s." % str( hda_id ) ) if not self._can_access_dataset( trans, data ): return trans.show_error_message( "You are not allowed to access this dataset" ) if data.purged: return trans.show_error_message( "The dataset you are attempting to view has been purged." ) if data.deleted and not ( trans.user_is_admin() or ( data.history and trans.get_user() == data.history.user ) ): return trans.show_error_message( "The dataset you are attempting to view has been deleted." ) if data.state == trans.model.Dataset.states.UPLOAD: return trans.show_error_message( "Please wait until this dataset finishes uploading before attempting to view it." ) return data @web.expose @web.json def transfer_status(self, trans, dataset_id, filename=None): data = self._check_dataset(trans, dataset_id) if isinstance( data, string_types ): return data log.debug( "Checking transfer status for dataset %s..." % data.dataset.id ) # Pulling files in extra_files_path into cache is not handled via this # method but that's primarily because those files are typically linked to # call this method does not seem doable? if data.dataset.external_filename: return True else: return trans.app.object_store.file_ready(data.dataset) @web.expose def display(self, trans, dataset_id=None, preview=False, filename=None, to_ext=None, offset=None, ck_size=None, **kwd): data = self._check_dataset(trans, dataset_id) if not isinstance( data, trans.app.model.DatasetInstance ): return data # Ensure offset is an integer before passing through to datatypes. if offset: offset = int(offset) # Ensure ck_size is an integer before passing through to datatypes. if ck_size: ck_size = int(ck_size) return data.datatype.display_data(trans, data, preview, filename, to_ext, offset=offset, ck_size=ck_size, **kwd) @web.expose def edit(self, trans, dataset_id=None, filename=None, hid=None, **kwd): message = None status = 'done' refresh_frames = [] error = False def __ok_to_edit_metadata( dataset_id ): # prevent modifying metadata when dataset is queued or running as input/output # This code could be more efficient, i.e. by using mappers, but to prevent slowing down loading a History panel, we'll leave the code here for now for job_to_dataset_association in trans.sa_session.query( self.app.model.JobToInputDatasetAssociation ) \ .filter_by( dataset_id=dataset_id ) \ .all() \ + trans.sa_session.query( self.app.model.JobToOutputDatasetAssociation ) \ .filter_by( dataset_id=dataset_id ) \ .all(): if job_to_dataset_association.job.state not in [ job_to_dataset_association.job.states.OK, job_to_dataset_association.job.states.ERROR, job_to_dataset_association.job.states.DELETED ]: return False return True if hid is not None: history = trans.get_history() data = history.datasets[ int( hid ) - 1 ] id = None elif dataset_id is not None: id = self.decode_id( dataset_id ) data = trans.sa_session.query( self.app.model.HistoryDatasetAssociation ).get( id ) else: trans.log_event( "dataset_id and hid are both None, cannot load a dataset to edit" ) return trans.show_error_message( "You must provide a history dataset id to edit" ) if data is None: trans.log_event( "Problem retrieving dataset (encoded: %s, decoded: %s) with history id %s." % ( str( dataset_id ), str( id ), str( hid ) ) ) return trans.show_error_message( "History dataset id is invalid" ) if dataset_id is not None and data.history.user is not None and data.history.user != trans.user: trans.log_event( "User attempted to edit an HDA they do not own (encoded: %s, decoded: %s)" % ( dataset_id, id ) ) return trans.show_error_message( "History dataset id is invalid" ) current_user_roles = trans.get_current_user_roles() if data.history.user and not data.dataset.has_manage_permissions_roles( trans ): # Permission setting related to DATASET_MANAGE_PERMISSIONS was broken for a period of time, # so it is possible that some Datasets have no roles associated with the DATASET_MANAGE_PERMISSIONS # permission. In this case, we'll reset this permission to the hda user's private role. manage_permissions_action = trans.app.security_agent.get_action( trans.app.security_agent.permitted_actions.DATASET_MANAGE_PERMISSIONS.action ) permissions = { manage_permissions_action : [ trans.app.security_agent.get_private_user_role( data.history.user ) ] } trans.app.security_agent.set_dataset_permission( data.dataset, permissions ) if self._can_access_dataset( trans, data ): if data.state == trans.model.Dataset.states.UPLOAD: return trans.show_error_message( "Please wait until this dataset finishes uploading before attempting to edit its metadata." ) params = util.Params( kwd, sanitize=False ) if params.change: # The user clicked the Save button on the 'Change data type' form if data.datatype.allow_datatype_change and trans.app.datatypes_registry.get_datatype_by_extension( params.datatype ).allow_datatype_change: # prevent modifying datatype when dataset is queued or running as input/output if not __ok_to_edit_metadata( data.id ): message = "This dataset is currently being used as input or output. You cannot change datatype until the jobs have completed or you have canceled them." error = True else: trans.app.datatypes_registry.change_datatype( data, params.datatype ) trans.sa_session.flush() trans.app.datatypes_registry.set_external_metadata_tool.tool_action.execute( trans.app.datatypes_registry.set_external_metadata_tool, trans, incoming={ 'input1': data }, overwrite=False ) # overwrite is False as per existing behavior message = "Changed the type of dataset '%s' to %s" % ( to_unicode( data.name ), params.datatype ) refresh_frames = ['history'] else: message = "You are unable to change datatypes in this manner. Changing %s to %s is not allowed." % ( data.extension, params.datatype ) error = True elif params.save: # The user clicked the Save button on the 'Edit Attributes' form data.name = params.name if params.name else '' data.info = params.info if params.info else '' message = '' if __ok_to_edit_metadata( data.id ): # The following for loop will save all metadata_spec items for name, spec in data.datatype.metadata_spec.items(): if spec.get("readonly"): continue optional = params.get("is_" + name, None) other = params.get("or_" + name, None) if optional and optional == '__NOTHING__': # optional element... == '__NOTHING__' actually means it is NOT checked (and therefore omitted) setattr(data.metadata, name, None) else: if other: setattr( data.metadata, name, other ) else: setattr( data.metadata, name, spec.unwrap( params.get(name, None) ) ) data.datatype.after_setting_metadata( data ) # Sanitize annotation before adding it. if params.annotation: annotation = sanitize_html( params.annotation, 'utf-8', 'text/html' ) self.add_item_annotation( trans.sa_session, trans.get_user(), data, annotation ) # This block on controller code is inactive until the 'extended_metadata' edit box is added back into the UI # Add or delete extended metadata # if params.extended_metadata: # em_string = params.extended_metadata # if len(em_string): # em_payload = None # try: # em_payload = loads(em_string) # except Exception as e: # message = 'Invalid JSON input' # error = True # if em_payload is not None: # if data is not None: # ex_obj = self.get_item_extended_metadata_obj(trans, data) # if ex_obj is not None: # self.unset_item_extended_metadata_obj(trans, data) # self.delete_extended_metadata(trans, ex_obj) # ex_obj = self.create_extended_metadata(trans, em_payload) # self.set_item_extended_metadata_obj(trans, data, ex_obj) # message = "Updated Extended metadata '%s'." % data.name # status = 'done' # else: # message = "data not found" # error = True # else: # if data is not None: # ex_obj = self.get_item_extended_metadata_obj(trans, data) # if ex_obj is not None: # self.unset_item_extended_metadata_obj(trans, data) # self.delete_extended_metadata(trans, ex_obj) # message = "Deleted Extended metadata '%s'." % data.name # status = 'done' # If setting metadata previously failed and all required elements have now been set, clear the failed state. if data._state == trans.model.Dataset.states.FAILED_METADATA and not data.missing_meta(): data._state = None trans.sa_session.flush() message = "Attributes updated%s" % message refresh_frames = ['history'] else: trans.sa_session.flush() message = "Attributes updated, but metadata could not be changed because this dataset is currently being used as input or output. You must cancel or wait for these jobs to complete before changing metadata." status = "warning" refresh_frames = ['history'] elif params.detect: # The user clicked the Auto-detect button on the 'Edit Attributes' form # prevent modifying metadata when dataset is queued or running as input/output if not __ok_to_edit_metadata( data.id ): message = "This dataset is currently being used as input or output. You cannot change metadata until the jobs have completed or you have canceled them." error = True else: for name, spec in data.metadata.spec.items(): # We need to be careful about the attributes we are resetting if name not in [ 'name', 'info', 'dbkey', 'base_name' ]: if spec.get( 'default' ): setattr( data.metadata, name, spec.unwrap( spec.get( 'default' ) ) ) message = 'Attributes have been queued to be updated' trans.app.datatypes_registry.set_external_metadata_tool.tool_action.execute( trans.app.datatypes_registry.set_external_metadata_tool, trans, incoming={ 'input1': data } ) trans.sa_session.flush() refresh_frames = ['history'] elif params.convert_data: target_type = kwd.get("target_type", None) if target_type: message = data.datatype.convert_dataset(trans, data, target_type) refresh_frames = ['history'] elif params.update_roles_button: if not trans.user: return trans.show_error_message( "You must be logged in if you want to change permissions." ) if trans.app.security_agent.can_manage_dataset( current_user_roles, data.dataset ): access_action = trans.app.security_agent.get_action( trans.app.security_agent.permitted_actions.DATASET_ACCESS.action ) manage_permissions_action = trans.app.security_agent.get_action( trans.app.security_agent.permitted_actions.DATASET_MANAGE_PERMISSIONS.action ) # The user associated the DATASET_ACCESS permission on the dataset with 1 or more roles. We # need to ensure that they did not associate roles that would cause accessibility problems. permissions, in_roles, error, message = \ trans.app.security_agent.derive_roles_from_access( trans, data.dataset.id, 'root', **kwd ) if error: # Keep the original role associations for the DATASET_ACCESS permission on the dataset. permissions[ access_action ] = data.dataset.get_access_roles( trans ) status = 'error' else: error = trans.app.security_agent.set_all_dataset_permissions( data.dataset, permissions ) if error: message += error status = 'error' else: message = 'Your changes completed successfully.' trans.sa_session.refresh( data.dataset ) else: message = "You are not authorized to change this dataset's permissions" error = True else: if "dbkey" in data.datatype.metadata_spec and not data.metadata.dbkey: data.metadata.dbkey = data.dbkey # the built-in 'id' is overwritten in lots of places as well ldatatypes = [ dtype_name for dtype_name, dtype_value in trans.app.datatypes_registry.datatypes_by_extension.iteritems() if dtype_value.allow_datatype_change ] ldatatypes.sort() all_roles = trans.app.security_agent.get_legitimate_roles( trans, data.dataset, 'root' ) if error: status = 'error' return trans.fill_template( "/dataset/edit_attributes.mako", data=data, data_annotation=self.get_item_annotation_str( trans.sa_session, trans.user, data ), datatypes=ldatatypes, current_user_roles=current_user_roles, all_roles=all_roles, message=message, status=status, dataset_id=dataset_id, refresh_frames=refresh_frames ) else: return trans.show_error_message( "You do not have permission to edit this dataset's ( id: %s ) information." % str( dataset_id ) ) @web.expose @web.require_login( "see all available datasets" ) def list( self, trans, **kwargs ): status = message = None if 'operation' in kwargs: operation = kwargs['operation'].lower() hda_ids = util.listify( kwargs.get( 'id', [] ) ) status, message = None, None hdas = [] for encoded_hda_id in hda_ids: hda_id = self.decode_id( encoded_hda_id ) hda = trans.sa_session.query( model.HistoryDatasetAssociation ).filter_by( id=hda_id ).first() if hda: if hda.history.user_id is not None and trans.user: assert trans.user.id == hda.history.user_id, "HistoryDatasetAssocation does not belong to current user" hdas.append( hda ) else: log.warning( "Invalid history_dataset_association id '%r' passed to list", hda_id ) if hdas: if operation == "switch" or operation == "switch_history": histories = [] for hda in hdas: histories.append( hda.history ) status, message = trans.webapp.controllers['history']._list_switch( trans, histories ) trans.template_context['refresh_frames'] = ['history'] if operation == "switch": hda_ids = [ trans.security.encode_id( hda.id ) for hda in hdas ] trans.template_context[ 'seek_hda_ids' ] = hda_ids elif operation == "copy to current history": target_histories = [ trans.get_history() ] hda_ids.reverse() status, message = self._copy_datasets( trans, hda_ids, target_histories ) trans.template_context['refresh_frames'] = ['history'] return self.stored_list_grid( trans, status=status, message=message, **kwargs ) @web.expose def imp( self, trans, dataset_id=None, **kwd ): referer = trans.request.referer if referer: referer_message = "<a href='%s'>return to the previous page</a>" % escape(referer) else: referer_message = "<a href='%s'>go to Galaxy's start page</a>" % url_for( '/' ) # Error checking. if not dataset_id: return trans.show_error_message( "You must specify a dataset to import. You can %s." % referer_message, use_panels=True ) # Do import. cur_history = trans.get_history( create=True ) status, message = self._copy_datasets( trans, [ dataset_id ], [ cur_history ], imported=True ) message = "Dataset imported. You can <a href='%s'>start using the dataset</a> or %s." % ( url_for('/'), referer_message ) return trans.show_message( message, type=status, use_panels=True ) @web.expose @web.json @web.require_login( "use Galaxy datasets" ) def get_name_and_link_async( self, trans, id=None ): decoded_id = self.decode_id( id ) dataset = self.hda_manager.get_accessible( decoded_id, trans.user ) dataset = self.hda_manager.error_if_uploading( dataset ) return_dict = { "name" : dataset.name, "link" : url_for( controller='dataset', action="display_by_username_and_slug", username=dataset.history.user.username, slug=trans.security.encode_id( dataset.id ) ) } return return_dict @web.expose def get_embed_html_async( self, trans, id ): decoded_id = self.decode_id( id ) dataset = self.hda_manager.get_accessible( decoded_id, trans.user ) dataset = self.hda_manager.error_if_uploading( dataset ) if dataset: return "Embedded Dataset '%s'" % dataset.name @web.expose @web.require_login( "use Galaxy datasets" ) def set_accessible_async( self, trans, id=None, accessible=False ): return @web.expose @web.require_login( "rate items" ) @web.json def rate_async( self, trans, id, rating ): decoded_id = self.decode_id( id ) dataset = self.hda_manager.get_accessible( decoded_id, trans.user ) dataset = self.hda_manager.error_if_uploading( dataset ) if not dataset: return trans.show_error_message( "The specified dataset does not exist." ) # Rate dataset. self.rate_item( trans.sa_session, trans.get_user(), dataset, rating ) return self.get_ave_item_rating_data( trans.sa_session, dataset ) @web.expose def display_by_username_and_slug( self, trans, username, slug, filename=None, preview=True ): id = slug decoded_id = self.decode_id( id ) dataset = self.hda_manager.get_accessible( decoded_id, trans.user ) dataset = self.hda_manager.error_if_uploading( dataset ) if dataset: # Filename used for composite types. if filename: return self.display( trans, dataset_id=slug, filename=filename) truncated, dataset_data = self.hda_manager.text_data( dataset, preview ) dataset.annotation = self.get_item_annotation_str( trans.sa_session, dataset.history.user, dataset ) # If dataset is chunkable, get first chunk. first_chunk = None if dataset.datatype.CHUNKABLE: first_chunk = dataset.datatype.get_chunk(trans, dataset, 0) # If data is binary or an image, stream without template; otherwise, use display template. # TODO: figure out a way to display images in display template. if isinstance(dataset.datatype, datatypes.binary.Binary) or isinstance(dataset.datatype, datatypes.images.Image) or isinstance(dataset.datatype, datatypes.text.Html): trans.response.set_content_type( dataset.get_mime() ) return open( dataset.file_name ) else: # Get rating data. user_item_rating = 0 if trans.get_user(): user_item_rating = self.get_user_item_rating( trans.sa_session, trans.get_user(), dataset ) if user_item_rating: user_item_rating = user_item_rating.rating else: user_item_rating = 0 ave_item_rating, num_ratings = self.get_ave_item_rating_data( trans.sa_session, dataset ) return trans.fill_template_mako( "/dataset/display.mako", item=dataset, item_data=dataset_data, truncated=truncated, user_item_rating=user_item_rating, ave_item_rating=ave_item_rating, num_ratings=num_ratings, first_chunk=first_chunk ) else: raise web.httpexceptions.HTTPNotFound() @web.expose def get_item_content_async( self, trans, id ): decoded_id = self.decode_id( id ) dataset = self.hda_manager.get_accessible( decoded_id, trans.user ) dataset = self.hda_manager.error_if_uploading( dataset ) if dataset is None: raise web.httpexceptions.HTTPNotFound() truncated, dataset_data = self.hda_manager.text_data( dataset, preview=True ) # Get annotation. dataset.annotation = self.get_item_annotation_str( trans.sa_session, trans.user, dataset ) return trans.stream_template_mako( "/dataset/item_content.mako", item=dataset, item_data=dataset_data, truncated=truncated ) @web.expose def annotate_async( self, trans, id, new_annotation=None, **kwargs ): # TODO:?? why is this an access check only? decoded_id = self.decode_id( id ) dataset = self.hda_manager.get_accessible( decoded_id, trans.user ) dataset = self.hda_manager.error_if_uploading( dataset ) if not dataset: web.httpexceptions.HTTPNotFound() if dataset and new_annotation: # Sanitize annotation before adding it. new_annotation = sanitize_html( new_annotation, 'utf-8', 'text/html' ) self.add_item_annotation( trans.sa_session, trans.get_user(), dataset, new_annotation ) trans.sa_session.flush() return new_annotation @web.expose def get_annotation_async( self, trans, id ): decoded_id = self.decode_id( id ) dataset = self.hda_manager.get_accessible( decoded_id, trans.user ) dataset = self.hda_manager.error_if_uploading( dataset ) if not dataset: web.httpexceptions.HTTPNotFound() annotation = self.get_item_annotation_str( trans.sa_session, trans.user, dataset ) if annotation and isinstance( annotation, text_type ): annotation = annotation.encode( 'ascii', 'replace' ) # paste needs ascii here return annotation @web.expose def display_at( self, trans, dataset_id, filename=None, **kwd ): if not trans.app.config.enable_old_display_applications: return trans.show_error_message( "This method of accessing external display applications has been disabled by a Galaxy administrator." ) site = filename data = trans.sa_session.query( trans.app.model.HistoryDatasetAssociation ).get( dataset_id ) if not data: raise paste.httpexceptions.HTTPRequestRangeNotSatisfiable( "Invalid reference dataset id: %s." % str( dataset_id ) ) if 'display_url' not in kwd or 'redirect_url' not in kwd: return trans.show_error_message( 'Invalid parameters specified for "display at" link, please contact a Galaxy administrator' ) try: redirect_url = kwd['redirect_url'] % urllib.quote_plus( kwd['display_url'] ) except: redirect_url = kwd['redirect_url'] # not all will need custom text if trans.app.security_agent.dataset_is_public( data.dataset ): return trans.response.send_redirect( redirect_url ) # anon access already permitted by rbac if self._can_access_dataset( trans, data ): trans.app.host_security_agent.set_dataset_permissions( data, trans.user, site ) return trans.response.send_redirect( redirect_url ) else: return trans.show_error_message( "You are not allowed to view this dataset at external sites. Please contact your Galaxy administrator to acquire management permissions for this dataset." ) @web.expose def display_application( self, trans, dataset_id=None, user_id=None, app_name=None, link_name=None, app_action=None, action_param=None, action_param_extra=None, **kwds ): # Build list of parameters to pass in to display application logic (app_kwds) app_kwds = {} for name, value in dict(kwds).iteritems(): # clone kwds because we remove stuff as we go. if name.startswith( "app_" ): app_kwds[ name[ len( "app_" ): ] ] = value del kwds[ name ] if kwds: log.debug( "Unexpected Keywords passed to display_application: %s" % kwds ) # route memory? # decode ids data, user = decode_dataset_user( trans, dataset_id, user_id ) if not data: raise paste.httpexceptions.HTTPRequestRangeNotSatisfiable( "Invalid reference dataset id: %s." % str( dataset_id ) ) if user is None: user = trans.user if user: user_roles = user.all_roles() else: user_roles = [] # Decode application name and link name app_name = urllib.unquote_plus( app_name ) link_name = urllib.unquote_plus( link_name ) if None in [ app_name, link_name ]: return trans.show_error_message( "A display application name and link name must be provided." ) if self._can_access_dataset( trans, data, additional_roles=user_roles ): msg = [] preparable_steps = [] refresh = False display_app = trans.app.datatypes_registry.display_applications.get( app_name ) if not display_app: log.debug( "Unknown display application has been requested: %s", app_name ) return paste.httpexceptions.HTTPNotFound( "The requested display application (%s) is not available." % ( app_name ) ) dataset_hash, user_hash = encode_dataset_user( trans, data, user ) try: display_link = display_app.get_link( link_name, data, dataset_hash, user_hash, trans, app_kwds ) except Exception as e: log.debug( "Error generating display_link: %s", e ) # User can sometimes recover from, e.g. conversion errors by fixing input metadata, so use conflict return paste.httpexceptions.HTTPConflict( "Error generating display_link: %s" % e ) if not display_link: log.debug( "Unknown display link has been requested: %s", link_name ) return paste.httpexceptions.HTTPNotFound( "Unknown display link has been requested: %s" % link_name ) if data.state == data.states.ERROR: msg.append( ( 'This dataset is in an error state, you cannot view it at an external display application.', 'error' ) ) elif data.deleted: msg.append( ( 'This dataset has been deleted, you cannot view it at an external display application.', 'error' ) ) elif data.state != data.states.OK: msg.append( ( 'You must wait for this dataset to be created before you can view it at an external display application.', 'info' ) ) refresh = True else: # We have permissions, dataset is not deleted and is in OK state, allow access if display_link.display_ready(): if app_action in [ 'data', 'param' ]: assert action_param, "An action param must be provided for a data or param action" # data is used for things with filenames that could be passed off to a proxy # in case some display app wants all files to be in the same 'directory', # data can be forced to param, but not the other way (no filename for other direction) # get param name from url param name try: action_param = display_link.get_param_name_by_url( action_param ) except ValueError as e: log.debug( e ) return paste.httpexceptions.HTTPNotFound( str( e ) ) value = display_link.get_param_value( action_param ) assert value, "An invalid parameter name was provided: %s" % action_param assert value.parameter.viewable, "This parameter is not viewable." if value.parameter.type == 'data': try: if action_param_extra: assert value.parameter.allow_extra_files_access, "Extra file content requested (%s), but allow_extra_files_access is False." % ( action_param_extra ) file_name = os.path.join( value.extra_files_path, action_param_extra ) else: file_name = value.file_name content_length = os.path.getsize( file_name ) rval = open( file_name ) except OSError as e: log.debug( "Unable to access requested file in display application: %s", e ) return paste.httpexceptions.HTTPNotFound( "This file is no longer available." ) else: rval = str( value ) content_length = len( rval ) trans.response.set_content_type( value.mime_type( action_param_extra=action_param_extra ) ) trans.response.headers[ 'Content-Length' ] = content_length return rval elif app_action is None: # redirect user to url generated by display link # Fix for Safari caching display links, which can change if the underlying dataset has an attribute change, e.g. name, metadata, etc trans.response.headers[ 'Cache-Control' ] = [ 'no-cache', 'max-age=0', 'no-store', 'must-revalidate' ] return trans.response.send_redirect( display_link.display_url() ) else: msg.append( ( 'Invalid action provided: %s' % app_action, 'error' ) ) else: if app_action is None: if trans.history != data.history: msg.append( ( 'You must import this dataset into your current history before you can view it at the desired display application.', 'error' ) ) else: refresh = True msg.append( ( 'Launching this display application required additional datasets to be generated, you can view the status of these jobs below. ', 'info' ) ) if not display_link.preparing_display(): display_link.prepare_display() preparable_steps = display_link.get_prepare_steps() else: raise Exception( 'Attempted a view action (%s) on a non-ready display application' % app_action ) return trans.fill_template_mako( "dataset/display_application/display.mako", msg=msg, display_app=display_app, display_link=display_link, refresh=refresh, preparable_steps=preparable_steps ) return trans.show_error_message( 'You do not have permission to view this dataset at an external display application.' ) def _delete( self, trans, dataset_id ): message = None status = 'done' id = None try: id = self.decode_id( dataset_id ) hda = trans.sa_session.query( self.app.model.HistoryDatasetAssociation ).get( id ) assert hda, 'Invalid HDA: %s' % id # Walk up parent datasets to find the containing history topmost_parent = hda while topmost_parent.parent: topmost_parent = topmost_parent.parent assert topmost_parent in trans.history.datasets, "Data does not belong to current history" # Mark deleted and cleanup hda.mark_deleted() hda.clear_associated_files() trans.log_event( "Dataset id %s marked as deleted" % str(id) ) self.hda_manager.stop_creating_job( hda ) trans.sa_session.flush() except Exception as e: msg = 'HDA deletion failed (encoded: %s, decoded: %s)' % ( dataset_id, id ) log.exception( msg + ': ' + str( e ) ) trans.log_event( msg ) message = 'Dataset deletion failed' status = 'error' return ( message, status ) def _undelete( self, trans, dataset_id ): message = None status = 'done' id = None try: id = self.decode_id( dataset_id ) history = trans.get_history() hda = trans.sa_session.query( self.app.model.HistoryDatasetAssociation ).get( id ) assert hda and hda.undeletable, 'Invalid HDA: %s' % id # Walk up parent datasets to find the containing history topmost_parent = hda while topmost_parent.parent: topmost_parent = topmost_parent.parent assert topmost_parent in history.datasets, "Data does not belong to current history" # Mark undeleted hda.mark_undeleted() trans.sa_session.flush() trans.log_event( "Dataset id %s has been undeleted" % str(id) ) except Exception: msg = 'HDA undeletion failed (encoded: %s, decoded: %s)' % ( dataset_id, id ) log.exception( msg ) trans.log_event( msg ) message = 'Dataset undeletion failed' status = 'error' return ( message, status ) def _unhide( self, trans, dataset_id ): try: id = self.decode_id( dataset_id ) except: return False history = trans.get_history() hda = trans.sa_session.query( self.app.model.HistoryDatasetAssociation ).get( id ) if hda: # Walk up parent datasets to find the containing history topmost_parent = hda while topmost_parent.parent: topmost_parent = topmost_parent.parent assert topmost_parent in history.datasets, "Data does not belong to current history" # Mark undeleted hda.mark_unhidden() trans.sa_session.flush() trans.log_event( "Dataset id %s has been unhidden" % str(id) ) return True return False def _purge( self, trans, dataset_id ): message = None status = 'done' try: id = self.decode_id( dataset_id ) user = trans.get_user() hda = trans.sa_session.query( self.app.model.HistoryDatasetAssociation ).get( id ) # Invalid HDA assert hda, 'Invalid history dataset ID' # Walk up parent datasets to find the containing history topmost_parent = hda while topmost_parent.parent: topmost_parent = topmost_parent.parent # If the user is anonymous, make sure the HDA is owned by the current session. if not user: current_history_id = trans.galaxy_session.current_history_id assert topmost_parent.history.id == current_history_id, 'Data does not belong to current user' # If the user is known, make sure the HDA is owned by the current user. else: assert topmost_parent.history.user == user, 'Data does not belong to current user' # Ensure HDA is deleted hda.deleted = True # HDA is purgeable # Decrease disk usage first if user: user.adjust_total_disk_usage(-hda.quota_amount(user)) # Mark purged hda.purged = True trans.sa_session.add( hda ) trans.log_event( "HDA id %s has been purged" % hda.id ) trans.sa_session.flush() # Don't delete anything if there are active HDAs or any LDDAs, even if if hda.dataset.user_can_purge: try: hda.dataset.full_delete() trans.log_event( "Dataset id %s has been purged upon the the purge of HDA id %s" % ( hda.dataset.id, hda.id ) ) trans.sa_session.add( hda.dataset ) except: log.exception( 'Unable to purge dataset (%s) on purge of HDA (%s):' % ( hda.dataset.id, hda.id ) ) trans.sa_session.flush() except Exception as exc: msg = 'HDA purge failed (encoded: %s, decoded: %s): %s' % ( dataset_id, id, exc ) log.exception( msg ) trans.log_event( msg ) message = 'Dataset removal from disk failed' status = 'error' return ( message, status ) @web.expose def delete( self, trans, dataset_id, filename, show_deleted_on_refresh=False ): message, status = self._delete( trans, dataset_id ) return trans.response.send_redirect( web.url_for( controller='root', action='history', show_deleted=show_deleted_on_refresh, message=message, status=status ) ) @web.expose def delete_async( self, trans, dataset_id, filename ): message, status = self._delete( trans, dataset_id ) if status == 'done': return "OK" else: raise Exception( message ) @web.expose def undelete( self, trans, dataset_id, filename ): message, status = self._undelete( trans, dataset_id ) return trans.response.send_redirect( web.url_for( controller='root', action='history', show_deleted=True, message=message, status=status ) ) @web.expose def undelete_async( self, trans, dataset_id, filename ): message, status = self._undelete( trans, dataset_id ) if status == 'done': return "OK" else: raise Exception( message ) @web.expose def unhide( self, trans, dataset_id, filename ): if self._unhide( trans, dataset_id ): return trans.response.send_redirect( web.url_for( controller='root', action='history', show_hidden=True ) ) raise Exception( "Error unhiding" ) @web.expose def purge( self, trans, dataset_id, filename, show_deleted_on_refresh=False ): if trans.app.config.allow_user_dataset_purge: message, status = self._purge( trans, dataset_id ) else: message = "Removal of datasets by users is not allowed in this Galaxy instance. Please contact your Galaxy administrator." status = 'error' return trans.response.send_redirect( web.url_for( controller='root', action='history', show_deleted=show_deleted_on_refresh, message=message, status=status ) ) @web.expose def purge_async( self, trans, dataset_id, filename ): if trans.app.config.allow_user_dataset_purge: message, status = self._purge( trans, dataset_id ) else: message = "Removal of datasets by users is not allowed in this Galaxy instance. Please contact your Galaxy administrator." status = 'error' if status == 'done': return "OK" else: raise Exception( message ) @web.expose def show_params( self, trans, dataset_id=None, from_noframe=None, **kwd ): try: hda = trans.sa_session.query( trans.app.model.HistoryDatasetAssociation ).get( self.decode_id( dataset_id ) ) except ValueError: hda = None if not hda: raise paste.httpexceptions.HTTPRequestRangeNotSatisfiable( "Invalid reference dataset id: %s." % escape( str( dataset_id ) ) ) if not self._can_access_dataset( trans, hda ): return trans.show_error_message( "You are not allowed to access this dataset" ) params_objects = None job = None tool = None upgrade_messages = {} has_parameter_errors = False inherit_chain = hda.source_dataset_chain if inherit_chain: job_dataset_association = inherit_chain[-1][0] else: job_dataset_association = hda if job_dataset_association.creating_job_associations: job = job_dataset_association.creating_job_associations[0].job if job: try: toolbox = self.get_toolbox() tool = toolbox.get_tool( job.tool_id ) assert tool is not None, 'Requested tool has not been loaded.' try: params_objects = job.get_param_values( trans.app, ignore_errors=False ) except: params_objects = job.get_param_values( trans.app, ignore_errors=True ) # use different param_objects in the following line, since we want to display original values as much as possible upgrade_messages = tool.check_and_update_param_values( job.get_param_values( trans.app, ignore_errors=True ), trans, update_values=False ) has_parameter_errors = True except: pass if job is None: return trans.show_error_message( "Job information is not available for this dataset." ) # TODO: we should provide the basic values along with the objects, in order to better handle reporting of old values during upgrade return trans.fill_template( "show_params.mako", inherit_chain=inherit_chain, history=trans.get_history(), hda=hda, job=job, tool=tool, params_objects=params_objects, upgrade_messages=upgrade_messages, has_parameter_errors=has_parameter_errors ) @web.expose def copy_datasets( self, trans, source_history=None, source_content_ids="", target_history_id=None, target_history_ids="", new_history_name="", do_copy=False, **kwd ): user = trans.get_user() if source_history is not None: decoded_source_history_id = self.decode_id( source_history ) history = self.history_manager.get_owned( decoded_source_history_id, trans.user, current_history=trans.history ) current_history = trans.get_history() else: history = current_history = trans.get_history() refresh_frames = [] if source_content_ids: if not isinstance( source_content_ids, list ): source_content_ids = source_content_ids.split(",") encoded_dataset_collection_ids = [ s[ len("dataset_collection|"): ] for s in source_content_ids if s.startswith("dataset_collection|") ] encoded_dataset_ids = [ s[ len("dataset|"): ] for s in source_content_ids if s.startswith("dataset|") ] decoded_dataset_collection_ids = set(map( self.decode_id, encoded_dataset_collection_ids )) decoded_dataset_ids = set(map( self.decode_id, encoded_dataset_ids )) else: decoded_dataset_collection_ids = [] decoded_dataset_ids = [] if new_history_name: target_history_ids = [] else: if target_history_id: target_history_ids = [ self.decode_id(target_history_id) ] elif target_history_ids: if not isinstance( target_history_ids, list ): target_history_ids = target_history_ids.split(",") target_history_ids = list(set([ self.decode_id(h) for h in target_history_ids if h ])) else: target_history_ids = [] done_msg = error_msg = "" new_history = None if do_copy: invalid_contents = 0 if not ( decoded_dataset_ids or decoded_dataset_collection_ids ) or not ( target_history_ids or new_history_name ): error_msg = "You must provide both source datasets and target histories. " else: if new_history_name: new_history = trans.app.model.History() new_history.name = new_history_name new_history.user = user trans.sa_session.add( new_history ) trans.sa_session.flush() target_history_ids.append( new_history.id ) if user: target_histories = [ hist for hist in map( trans.sa_session.query( trans.app.model.History ).get, target_history_ids ) if hist is not None and hist.user == user ] else: target_histories = [ history ] if len( target_histories ) != len( target_history_ids ): error_msg = error_msg + "You do not have permission to add datasets to %i requested histories. " % ( len( target_history_ids ) - len( target_histories ) ) source_contents = map( trans.sa_session.query( trans.app.model.HistoryDatasetAssociation ).get, decoded_dataset_ids ) source_contents.extend( map( trans.sa_session.query( trans.app.model.HistoryDatasetCollectionAssociation ).get, decoded_dataset_collection_ids ) ) source_contents.sort(key=lambda content: content.hid) for content in source_contents: if content is None: error_msg = error_msg + "You tried to copy a dataset that does not exist. " invalid_contents += 1 elif content.history != history: error_msg = error_msg + "You tried to copy a dataset which is not in your current history. " invalid_contents += 1 else: for hist in target_histories: if content.history_content_type == "dataset": hist.add_dataset( content.copy( copy_children=True ) ) else: copy_collected_datasets = True copy_kwds = {} if copy_collected_datasets: copy_kwds["element_destination"] = hist hist.add_dataset_collection( content.copy( **copy_kwds ) ) if current_history in target_histories: refresh_frames = ['history'] trans.sa_session.flush() hist_names_str = ", ".join( ['<a href="%s" target="_top">%s</a>' % ( url_for( controller="history", action="switch_to_history", hist_id=trans.security.encode_id( hist.id ) ), escape(hist.name) ) for hist in target_histories ] ) num_source = len( source_content_ids ) - invalid_contents num_target = len(target_histories) done_msg = "%i %s copied to %i %s: %s." % (num_source, inflector.cond_plural(num_source, "dataset"), num_target, inflector.cond_plural(num_target, "history"), hist_names_str ) trans.sa_session.refresh( history ) source_contents = history.active_contents target_histories = [history] if user: target_histories = user.active_histories return trans.fill_template( "/dataset/copy_view.mako", source_history=history, current_history=current_history, source_content_ids=source_content_ids, target_history_id=target_history_id, target_history_ids=target_history_ids, source_contents=source_contents, target_histories=target_histories, new_history_name=new_history_name, done_msg=done_msg, error_msg=error_msg, refresh_frames=refresh_frames ) def _copy_datasets( self, trans, dataset_ids, target_histories, imported=False ): user = trans.get_user() done_msg = error_msg = "" invalid_datasets = 0 if not dataset_ids or not target_histories: error_msg = "You must provide both source datasets and target histories." else: # User must own target histories to copy datasets to them. for history in target_histories: if user != history.user: error_msg = error_msg + "You do not have permission to add datasets to %i requested histories. " % ( len( target_histories ) ) for dataset_id in dataset_ids: decoded_id = self.decode_id( dataset_id ) data = self.hda_manager.get_accessible( decoded_id, trans.user ) data = self.hda_manager.error_if_uploading( data ) if data is None: error_msg = error_msg + "You tried to copy a dataset that does not exist or that you do not have access to. " invalid_datasets += 1 else: for hist in target_histories: dataset_copy = data.copy( copy_children=True ) if imported: dataset_copy.name = "imported: " + dataset_copy.name hist.add_dataset( dataset_copy ) trans.sa_session.flush() num_datasets_copied = len( dataset_ids ) - invalid_datasets done_msg = "%i dataset%s copied to %i histor%s." % \ ( num_datasets_copied, iff( num_datasets_copied == 1, "", "s"), len( target_histories ), iff( len( target_histories ) == 1, "y", "ies") ) trans.sa_session.refresh( history ) if error_msg != "": status = ERROR message = error_msg else: status = SUCCESS message = done_msg return status, message

true

f704e406d6064c1b07ddb3fa9237f28659c4ec07

7,122

py

Python

daal4py/sklearn/neighbors/_classification.py

Alexsandruss/daal4py

6e5a02d3fd46095585e618edba24fc258e8b0052

[ "Apache-2.0" ]

null

daal4py/sklearn/neighbors/_classification.py

Alexsandruss/daal4py

6e5a02d3fd46095585e618edba24fc258e8b0052

[ "Apache-2.0" ]

null

daal4py/sklearn/neighbors/_classification.py

Alexsandruss/daal4py

6e5a02d3fd46095585e618edba24fc258e8b0052

[ "Apache-2.0" ]

null

#=============================================================================== # Copyright 2020-2021 Intel Corporation # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. #=============================================================================== # daal4py KNN classification scikit-learn-compatible classes from ._base import NeighborsBase, KNeighborsMixin from ._base import parse_auto_method, prediction_algorithm from sklearn.base import ClassifierMixin as BaseClassifierMixin from .._utils import ( getFPType, sklearn_check_version, get_patch_message, PatchingConditionsChain) from .._device_offload import support_usm_ndarray from sklearn.utils.validation import check_array import numpy as np from scipy import sparse as sp import logging if sklearn_check_version("0.22"): from sklearn.neighbors._classification import KNeighborsClassifier as \ BaseKNeighborsClassifier from sklearn.neighbors._base import _check_weights from sklearn.utils.validation import _deprecate_positional_args else: from sklearn.neighbors.classification import KNeighborsClassifier as \ BaseKNeighborsClassifier from sklearn.neighbors.base import _check_weights def _deprecate_positional_args(f): return f def daal4py_classifier_predict(estimator, X, base_predict): if sklearn_check_version('1.0'): estimator._check_feature_names(X, reset=False) X = check_array(X, accept_sparse='csr', dtype=[np.float64, np.float32]) daal_model = getattr(estimator, '_daal_model', None) n_features = getattr(estimator, 'n_features_in_', None) shape = getattr(X, 'shape', None) if n_features and shape and len(shape) > 1 and shape[1] != n_features: raise ValueError((f'X has {X.shape[1]} features, ' f'but KNNClassifier is expecting ' f'{n_features} features as input')) try: fptype = getFPType(X) except ValueError: fptype = None _patching_status = PatchingConditionsChain( "sklearn.neighbors.KNeighborsClassifier.predict") _dal_ready = _patching_status.and_conditions([ (daal_model is not None, "oneDAL model was not trained."), (fptype is not None, "Unable to get dtype."), (not sp.issparse(X), "X is sparse. Sparse input is not supported.")]) _patching_status.write_log() if _dal_ready: params = { 'method': 'defaultDense', 'k': estimator.n_neighbors, 'nClasses': len(estimator.classes_), 'voteWeights': 'voteUniform' if estimator.weights == 'uniform' else 'voteDistance', 'resultsToEvaluate': 'computeClassLabels', 'resultsToCompute': '' } method = parse_auto_method( estimator, estimator.algorithm, estimator.n_samples_fit_, n_features) predict_alg = prediction_algorithm(method, fptype, params) prediction_result = predict_alg.compute(X, daal_model) result = estimator.classes_.take( np.asarray(prediction_result.prediction.ravel(), dtype=np.intp)) else: result = base_predict(estimator, X) return result if sklearn_check_version("0.24"): class KNeighborsClassifier_(KNeighborsMixin, BaseClassifierMixin, NeighborsBase): @_deprecate_positional_args def __init__(self, n_neighbors=5, *, weights='uniform', algorithm='auto', leaf_size=30, p=2, metric='minkowski', metric_params=None, n_jobs=None, **kwargs): super().__init__( n_neighbors=n_neighbors, algorithm=algorithm, leaf_size=leaf_size, metric=metric, p=p, metric_params=metric_params, n_jobs=n_jobs, **kwargs) self.weights = \ weights if sklearn_check_version("1.0") else _check_weights(weights) elif sklearn_check_version("0.22"): from sklearn.neighbors._base import SupervisedIntegerMixin as \ BaseSupervisedIntegerMixin class KNeighborsClassifier_(NeighborsBase, KNeighborsMixin, BaseSupervisedIntegerMixin, BaseClassifierMixin): @_deprecate_positional_args def __init__(self, n_neighbors=5, *, weights='uniform', algorithm='auto', leaf_size=30, p=2, metric='minkowski', metric_params=None, n_jobs=None, **kwargs): super().__init__( n_neighbors=n_neighbors, algorithm=algorithm, leaf_size=leaf_size, metric=metric, p=p, metric_params=metric_params, n_jobs=n_jobs, **kwargs) self.weights = _check_weights(weights) else: from sklearn.neighbors.base import SupervisedIntegerMixin as \ BaseSupervisedIntegerMixin class KNeighborsClassifier_(NeighborsBase, KNeighborsMixin, BaseSupervisedIntegerMixin, BaseClassifierMixin): @_deprecate_positional_args def __init__(self, n_neighbors=5, *, weights='uniform', algorithm='auto', leaf_size=30, p=2, metric='minkowski', metric_params=None, n_jobs=None, **kwargs): super().__init__( n_neighbors=n_neighbors, algorithm=algorithm, leaf_size=leaf_size, metric=metric, p=p, metric_params=metric_params, n_jobs=n_jobs, **kwargs) self.weights = _check_weights(weights) class KNeighborsClassifier(KNeighborsClassifier_): @_deprecate_positional_args def __init__(self, n_neighbors=5, *, weights='uniform', algorithm='auto', leaf_size=30, p=2, metric='minkowski', metric_params=None, n_jobs=None, **kwargs): super().__init__( n_neighbors=n_neighbors, weights=weights, algorithm=algorithm, leaf_size=leaf_size, metric=metric, p=p, metric_params=metric_params, n_jobs=n_jobs, **kwargs) @support_usm_ndarray() def fit(self, X, y): return NeighborsBase._fit(self, X, y) @support_usm_ndarray() def predict(self, X): return daal4py_classifier_predict(self, X, BaseKNeighborsClassifier.predict) @support_usm_ndarray() def predict_proba(self, X): if sklearn_check_version('1.0'): self._check_feature_names(X, reset=False) return BaseKNeighborsClassifier.predict_proba(self, X)

40.697143

85

0.641252

from ._base import NeighborsBase, KNeighborsMixin from ._base import parse_auto_method, prediction_algorithm from sklearn.base import ClassifierMixin as BaseClassifierMixin from .._utils import ( getFPType, sklearn_check_version, get_patch_message, PatchingConditionsChain) from .._device_offload import support_usm_ndarray from sklearn.utils.validation import check_array import numpy as np from scipy import sparse as sp import logging if sklearn_check_version("0.22"): from sklearn.neighbors._classification import KNeighborsClassifier as \ BaseKNeighborsClassifier from sklearn.neighbors._base import _check_weights from sklearn.utils.validation import _deprecate_positional_args else: from sklearn.neighbors.classification import KNeighborsClassifier as \ BaseKNeighborsClassifier from sklearn.neighbors.base import _check_weights def _deprecate_positional_args(f): return f def daal4py_classifier_predict(estimator, X, base_predict): if sklearn_check_version('1.0'): estimator._check_feature_names(X, reset=False) X = check_array(X, accept_sparse='csr', dtype=[np.float64, np.float32]) daal_model = getattr(estimator, '_daal_model', None) n_features = getattr(estimator, 'n_features_in_', None) shape = getattr(X, 'shape', None) if n_features and shape and len(shape) > 1 and shape[1] != n_features: raise ValueError((f'X has {X.shape[1]} features, ' f'but KNNClassifier is expecting ' f'{n_features} features as input')) try: fptype = getFPType(X) except ValueError: fptype = None _patching_status = PatchingConditionsChain( "sklearn.neighbors.KNeighborsClassifier.predict") _dal_ready = _patching_status.and_conditions([ (daal_model is not None, "oneDAL model was not trained."), (fptype is not None, "Unable to get dtype."), (not sp.issparse(X), "X is sparse. Sparse input is not supported.")]) _patching_status.write_log() if _dal_ready: params = { 'method': 'defaultDense', 'k': estimator.n_neighbors, 'nClasses': len(estimator.classes_), 'voteWeights': 'voteUniform' if estimator.weights == 'uniform' else 'voteDistance', 'resultsToEvaluate': 'computeClassLabels', 'resultsToCompute': '' } method = parse_auto_method( estimator, estimator.algorithm, estimator.n_samples_fit_, n_features) predict_alg = prediction_algorithm(method, fptype, params) prediction_result = predict_alg.compute(X, daal_model) result = estimator.classes_.take( np.asarray(prediction_result.prediction.ravel(), dtype=np.intp)) else: result = base_predict(estimator, X) return result if sklearn_check_version("0.24"): class KNeighborsClassifier_(KNeighborsMixin, BaseClassifierMixin, NeighborsBase): @_deprecate_positional_args def __init__(self, n_neighbors=5, *, weights='uniform', algorithm='auto', leaf_size=30, p=2, metric='minkowski', metric_params=None, n_jobs=None, **kwargs): super().__init__( n_neighbors=n_neighbors, algorithm=algorithm, leaf_size=leaf_size, metric=metric, p=p, metric_params=metric_params, n_jobs=n_jobs, **kwargs) self.weights = \ weights if sklearn_check_version("1.0") else _check_weights(weights) elif sklearn_check_version("0.22"): from sklearn.neighbors._base import SupervisedIntegerMixin as \ BaseSupervisedIntegerMixin class KNeighborsClassifier_(NeighborsBase, KNeighborsMixin, BaseSupervisedIntegerMixin, BaseClassifierMixin): @_deprecate_positional_args def __init__(self, n_neighbors=5, *, weights='uniform', algorithm='auto', leaf_size=30, p=2, metric='minkowski', metric_params=None, n_jobs=None, **kwargs): super().__init__( n_neighbors=n_neighbors, algorithm=algorithm, leaf_size=leaf_size, metric=metric, p=p, metric_params=metric_params, n_jobs=n_jobs, **kwargs) self.weights = _check_weights(weights) else: from sklearn.neighbors.base import SupervisedIntegerMixin as \ BaseSupervisedIntegerMixin class KNeighborsClassifier_(NeighborsBase, KNeighborsMixin, BaseSupervisedIntegerMixin, BaseClassifierMixin): @_deprecate_positional_args def __init__(self, n_neighbors=5, *, weights='uniform', algorithm='auto', leaf_size=30, p=2, metric='minkowski', metric_params=None, n_jobs=None, **kwargs): super().__init__( n_neighbors=n_neighbors, algorithm=algorithm, leaf_size=leaf_size, metric=metric, p=p, metric_params=metric_params, n_jobs=n_jobs, **kwargs) self.weights = _check_weights(weights) class KNeighborsClassifier(KNeighborsClassifier_): @_deprecate_positional_args def __init__(self, n_neighbors=5, *, weights='uniform', algorithm='auto', leaf_size=30, p=2, metric='minkowski', metric_params=None, n_jobs=None, **kwargs): super().__init__( n_neighbors=n_neighbors, weights=weights, algorithm=algorithm, leaf_size=leaf_size, metric=metric, p=p, metric_params=metric_params, n_jobs=n_jobs, **kwargs) @support_usm_ndarray() def fit(self, X, y): return NeighborsBase._fit(self, X, y) @support_usm_ndarray() def predict(self, X): return daal4py_classifier_predict(self, X, BaseKNeighborsClassifier.predict) @support_usm_ndarray() def predict_proba(self, X): if sklearn_check_version('1.0'): self._check_feature_names(X, reset=False) return BaseKNeighborsClassifier.predict_proba(self, X)

true

f704e4bde1c29b09b13e9c055dbbdaff730de2a4

383

py

Python

other/dingding/dingtalk/api/rest/OapiAtsChannelAccountAddRequest.py

hth945/pytest

83e2aada82a2c6a0fdd1721320e5bf8b8fd59abc

[ "Apache-2.0" ]

null

other/dingding/dingtalk/api/rest/OapiAtsChannelAccountAddRequest.py

hth945/pytest

83e2aada82a2c6a0fdd1721320e5bf8b8fd59abc

[ "Apache-2.0" ]

null

other/dingding/dingtalk/api/rest/OapiAtsChannelAccountAddRequest.py

hth945/pytest

83e2aada82a2c6a0fdd1721320e5bf8b8fd59abc

[ "Apache-2.0" ]

null

''' Created by auto_sdk on 2020.08.19 ''' from dingtalk.api.base import RestApi class OapiAtsChannelAccountAddRequest(RestApi): def __init__(self,url=None): RestApi.__init__(self,url) self.biz_code = None self.channel_user_identify = None self.userid = None def getHttpMethod(self): return 'POST' def getapiname(self): return 'dingtalk.oapi.ats.channel.account.add'

22.529412

48

0.75718

from dingtalk.api.base import RestApi class OapiAtsChannelAccountAddRequest(RestApi): def __init__(self,url=None): RestApi.__init__(self,url) self.biz_code = None self.channel_user_identify = None self.userid = None def getHttpMethod(self): return 'POST' def getapiname(self): return 'dingtalk.oapi.ats.channel.account.add'

true

f704e67f0939a74be44c84c108717c2e056598e9

1,634

py

Python

tests/test_web_flask/test_c_route.py

RodrigoSierraV/AirBnB_clone_v4

314a2f20ea3f1de89255317d0b52a4289b36ccbc

[ "MIT" ]

5

2017-09-12T18:23:55.000Z

2021-07-27T18:05:37.000Z

tests/test_web_flask/test_c_route.py

petehwu/AirBnB_clone_v4

bf0528c99662285139aa56fe8e752d239e2f7b2a

[ "MIT" ]

8

2019-09-27T17:23:04.000Z

2019-09-30T23:31:31.000Z

tests/test_web_flask/test_c_route.py

petehwu/AirBnB_clone_v4

bf0528c99662285139aa56fe8e752d239e2f7b2a

[ "MIT" ]

10

2017-09-20T18:50:07.000Z

2022-02-17T20:58:23.000Z

#!/usr/bin/python3 """ Unit Test for api v1 Flask App """ import inspect import pep8 import web_flask import unittest from os import stat web_flask = __import__('web_flask.2-c_route', globals(), locals(), ['*']) class TestCRouteDocs(unittest.TestCase): """Class for testing Hello Route docs""" all_funcs = inspect.getmembers(web_flask, inspect.isfunction) @classmethod def setUpClass(cls): print('\n\n.................................') print('..... Testing Documentation .....') print('............ C Route ...........') print('.................................\n\n') def test_doc_file(self): """... documentation for the file""" actual = web_flask.__doc__ self.assertIsNotNone(actual) def test_all_function_docs(self): """... tests for ALL DOCS for all functions""" all_functions = TestCRouteDocs.all_funcs for function in all_functions: self.assertIsNotNone(function[1].__doc__) def test_pep8(self): """... tests if file conforms to PEP8 Style""" pep8style = pep8.StyleGuide(quiet=True) errors = pep8style.check_files(['web_flask/2-c_route.py']) self.assertEqual(errors.total_errors, 0, errors.messages) def test_file_is_executable(self): """... tests if file has correct permissions so user can execute""" file_stat = stat('web_flask/2-c_route.py') permissions = str(oct(file_stat[0])) actual = int(permissions[5:-2]) >= 5 self.assertTrue(actual) if __name__ == '__main__': """ MAIN TESTS """ unittest.main

29.709091

75

0.601591

import inspect import pep8 import web_flask import unittest from os import stat web_flask = __import__('web_flask.2-c_route', globals(), locals(), ['*']) class TestCRouteDocs(unittest.TestCase): all_funcs = inspect.getmembers(web_flask, inspect.isfunction) @classmethod def setUpClass(cls): print('\n\n.................................') print('..... Testing Documentation .....') print('............ C Route ...........') print('.................................\n\n') def test_doc_file(self): actual = web_flask.__doc__ self.assertIsNotNone(actual) def test_all_function_docs(self): all_functions = TestCRouteDocs.all_funcs for function in all_functions: self.assertIsNotNone(function[1].__doc__) def test_pep8(self): pep8style = pep8.StyleGuide(quiet=True) errors = pep8style.check_files(['web_flask/2-c_route.py']) self.assertEqual(errors.total_errors, 0, errors.messages) def test_file_is_executable(self): file_stat = stat('web_flask/2-c_route.py') permissions = str(oct(file_stat[0])) actual = int(permissions[5:-2]) >= 5 self.assertTrue(actual) if __name__ == '__main__': unittest.main

true

f704e6c02a08c79f1e412b550fbc5e2ad285adf4

11,273

py

Python

multiqc_clarity/multiqc_clarity.py

MultiQC/MultiQC_Clarity

9ac177dffa8c9a5a5d57ec0c6739a74a974b8ab3

[ "MIT" ]

1

2018-06-18T15:31:10.000Z

multiqc_clarity/multiqc_clarity.py

MultiQC/MultiQC_Clarity

9ac177dffa8c9a5a5d57ec0c6739a74a974b8ab3

[ "MIT" ]

5

2017-03-13T17:21:45.000Z

2019-02-14T12:34:11.000Z

multiqc_clarity/multiqc_clarity.py

MultiQC/MultiQC_Clarity

9ac177dffa8c9a5a5d57ec0c6739a74a974b8ab3

[ "MIT" ]

4

2017-03-06T09:47:42.000Z

2019-02-13T13:19:23.000Z

from genologics.lims import Lims from genologics.config import BASEURI, USERNAME, PASSWORD from multiqc.utils import report, config from multiqc.modules.base_module import BaseMultiqcModule from multiqc.plots import table from collections import OrderedDict import logging import re class MultiQC_clarity_metadata(BaseMultiqcModule): def __init__(self): self.log = logging.getLogger('multiqc') # Check that this plugin hasn't been disabled if config.kwargs.get('disable_clarity', False) is True: self.log.info("Skipping MultiQC_Clarity as disabled on command line") return None if getattr(config, 'disable_clarity', False) is True: self.log.debug("Skipping MultiQC_Clarity as specified in config file") return None super(MultiQC_clarity_metadata, self).__init__(name='Clarity LIMS', anchor='clarity') self.intro = '''The <a href="https://github.com/MultiQC/MultiQC_Clarity" target="_blank">MultiQC_Clarity</a> plugin fetches data from a specified <a href="https://www.genologics.com/clarity-lims/" target="_blank">Basespace Clarity LIMS</a> instance.''' self.lims = Lims(BASEURI, USERNAME, PASSWORD) self.metadata = {} self.header_metadata = {} self.general_metadata = {} self.tab_metadata = {} self.samples = [] self.schema = getattr(config, 'clarity', None) if self.schema is None: self.log.debug("No config found for MultiQC_Clarity") return None self.name_edit_regex = self.schema.get("name_edit_regex") self.get_samples() self.get_metadata('report_header_info') self.get_metadata('general_stats') self.get_metadata('clarity_module') self.update_multiqc_report() self.make_sections() report.modules_output.append(self) def get_samples(self): if config.kwargs.get('clarity_project'): pj = self.lims.get_projects(name=config.kwargs['clarity_project']) if len(pj) > 1: self.log.error("Found multiple match projects in Clarity.") elif len(pj) < 1: self.log.error("Could not identify project in Clarity.") else: self.samples = self.lims.get_samples(projectlimsid=pj[0].id) else: names = set() for x in report.general_stats_data: names.update(x.keys()) for d in report.saved_raw_data.values(): try: self.names.update(d.keys()) except AttributeError: pass if not config.kwargs.get('clarity_skip_edit_names'): names = self.edit_names(names) self.log.info("Looking into Clarity for samples {}".format(", ".join(names))) found = 0 try: for name in names: matching_samples = self.lims.get_samples(name=name) if not matching_samples: self.log.error("Could not find a sample matching {0}, skipping.".format(name)) continue if len(matching_samples) > 1: self.log.error("Found multiple samples matching {0}, skipping".format(name)) continue found += 1 self.samples.append(matching_samples[0]) except Exception as e: self.log.warn("Could not connect to Clarity LIMS: {}".format(e)) return None self.log.info("Found {} out of {} samples in LIMS.".format(found, len(names))) def edit_names(self, names): if self.name_edit_regex: return self.edit_names_with_regex(names) edited=[] for name in names: if name.endswith("_1") or name.endswith("_2"): edited.append(name[:-2]) elif name.endswith("_R1") or name.endswith("_R2"): edited.append(name[:-3]) else: edited.append(name) return edited def edit_names_with_regex(self, names): edited = [] for name in names: matches = re.search(re.compile(self.name_edit_regex), name) edited.append(matches.group(1)) return edited def flatten_metadata(self, metadata): for first_level in metadata: for second_level in metadata[first_level]: if isinstance(metadata[first_level][second_level], set) or isinstance(metadata[first_level][second_level], list): metadata[first_level][second_level] = ", ".join(metadata[first_level][second_level]) return metadata def get_project_metadata(self, udfs): project_metadata={} for sample in self.samples: project_metadata[sample.project.name]={} for udf in udfs: if udf in sample.project.udf: try: project_metadata[sample.project.name][udf].add(str(sample.project.udf[udf])) except: project_metadata[sample.project.name][udf] = set() project_metadata[sample.project.name][udf].add(str(sample.project.udf[udf])) return self.flatten_metadata(project_metadata) def get_sample_metadata(self, udfs): sample_metadata={} for sample in self.samples: sample_metadata[sample.name]={} for udf in udfs: if udf in sample.udf: try: sample_metadata[sample.name][udf].add(str(sample.udf[udf])) except: sample_metadata[sample.name][udf] = set() sample_metadata[sample.name][udf].add(str(sample.udf[udf])) return self.flatten_metadata(sample_metadata) def get_metadata(self, part): for key in self.schema[part]: if key == 'Project': metadata = self.get_project_metadata(self.schema[part]['Project']) elif key == 'Sample': metadata =self.get_sample_metadata(self.schema[part]['Sample']) else: metadata = self.get_artifact_metadata(self.schema[part]) if part == "report_header_info": self.header_metadata.update(metadata) elif part == "general_stats": self.general_metadata.update(metadata) else: self.tab_metadata.update(metadata) def get_artifact_metadata(self, pt_to_udfs): artifact_metadata={} for sample in self.samples: artifact_metadata[sample.name]={} for process_type in pt_to_udfs: if process_type == 'Sample': continue if process_type == 'Project': continue artifacts = self.lims.get_artifacts(sample_name=sample.name, process_type=process_type) for udf_name in pt_to_udfs[process_type].get("outputs", []): values = [] for artifact in artifacts: if udf_name in artifact.udf: values.append(str(artifact.udf[udf_name])) artifact_metadata[sample.name][udf_name]=values processes = set([art.parent_process for art in artifacts]) inputs=[] for p in processes: inputs.extend([art for art in p.all_inputs() if sample.name in [s.name for s in art.samples]]) for udf_name in pt_to_udfs[process_type].get("inputs", []): values = [] for artifact in inputs: if udf_name in artifact.udf: values.append(str(artifact.udf[udf_name])) artifact_metadata[sample.name][udf_name]=values return self.flatten_metadata(artifact_metadata) def update_multiqc_report(self): if config.report_header_info is None: config.report_header_info = [] for first_level in self.header_metadata: d = {} for key in self.header_metadata[first_level]: d[key] = self.header_metadata[first_level][key] config.report_header_info.append(d) headers = {} for first_level in self.schema["general_stats"]: for header in self.schema["general_stats"][first_level]: headers[header] = {} if isinstance(self.schema["general_stats"][first_level][header], dict): for subsubkey, cfg in self.schema["general_stats"][first_level][header].items(): if subsubkey == 'multiply_by': mby = str(cfg)[:] headers[header]['modify'] = lambda x: float(x) * float(mby) else: headers[header][subsubkey] = cfg headers[header]['description'] = headers[header].get('description', '{} - {}'.format(first_level, header)) headers[header]['namespace'] = headers[header].get('namespace', 'Clarity LIMS') headers[header]['scale'] = headers[header].get('scale', 'YlGn') report.general_stats_headers.append(headers) report.general_stats_data.append(self.general_metadata) def make_sections(self): headers = OrderedDict() for first_level in self.tab_metadata: for header in self.tab_metadata[first_level]: desc = header if header not in headers: headers[header] = {} for key in self.schema['clarity_module']: if header in self.schema['clarity_module'][key]: desc = key elif isinstance(self.schema['clarity_module'][key], dict): for subkey, val in self.schema['clarity_module'][key].items(): # print(val) if val is None: break elif header in val: desc = key if isinstance(val[header], dict): for subsubkey, cfg in val[header].items(): if subsubkey == 'multiply_by': mby = str(cfg)[:] headers[header]['modify'] = lambda x: float(x) * float(mby) else: headers[header][subsubkey] = cfg headers[header]['namespace'] = headers[header].get('namespace', desc) headers[header]['title'] = headers[header].get('title', header) headers[header]['description'] = headers[header].get('description', header) self.intro += table.plot(self.tab_metadata, headers)

42.863118

129

0.548213

from genologics.lims import Lims from genologics.config import BASEURI, USERNAME, PASSWORD from multiqc.utils import report, config from multiqc.modules.base_module import BaseMultiqcModule from multiqc.plots import table from collections import OrderedDict import logging import re class MultiQC_clarity_metadata(BaseMultiqcModule): def __init__(self): self.log = logging.getLogger('multiqc') if config.kwargs.get('disable_clarity', False) is True: self.log.info("Skipping MultiQC_Clarity as disabled on command line") return None if getattr(config, 'disable_clarity', False) is True: self.log.debug("Skipping MultiQC_Clarity as specified in config file") return None super(MultiQC_clarity_metadata, self).__init__(name='Clarity LIMS', anchor='clarity') self.intro = '''The <a href="https://github.com/MultiQC/MultiQC_Clarity" target="_blank">MultiQC_Clarity</a> plugin fetches data from a specified <a href="https://www.genologics.com/clarity-lims/" target="_blank">Basespace Clarity LIMS</a> instance.''' self.lims = Lims(BASEURI, USERNAME, PASSWORD) self.metadata = {} self.header_metadata = {} self.general_metadata = {} self.tab_metadata = {} self.samples = [] self.schema = getattr(config, 'clarity', None) if self.schema is None: self.log.debug("No config found for MultiQC_Clarity") return None self.name_edit_regex = self.schema.get("name_edit_regex") self.get_samples() self.get_metadata('report_header_info') self.get_metadata('general_stats') self.get_metadata('clarity_module') self.update_multiqc_report() self.make_sections() report.modules_output.append(self) def get_samples(self): if config.kwargs.get('clarity_project'): pj = self.lims.get_projects(name=config.kwargs['clarity_project']) if len(pj) > 1: self.log.error("Found multiple match projects in Clarity.") elif len(pj) < 1: self.log.error("Could not identify project in Clarity.") else: self.samples = self.lims.get_samples(projectlimsid=pj[0].id) else: names = set() for x in report.general_stats_data: names.update(x.keys()) for d in report.saved_raw_data.values(): try: self.names.update(d.keys()) except AttributeError: pass if not config.kwargs.get('clarity_skip_edit_names'): names = self.edit_names(names) self.log.info("Looking into Clarity for samples {}".format(", ".join(names))) found = 0 try: for name in names: matching_samples = self.lims.get_samples(name=name) if not matching_samples: self.log.error("Could not find a sample matching {0}, skipping.".format(name)) continue if len(matching_samples) > 1: self.log.error("Found multiple samples matching {0}, skipping".format(name)) continue found += 1 self.samples.append(matching_samples[0]) except Exception as e: self.log.warn("Could not connect to Clarity LIMS: {}".format(e)) return None self.log.info("Found {} out of {} samples in LIMS.".format(found, len(names))) def edit_names(self, names): if self.name_edit_regex: return self.edit_names_with_regex(names) edited=[] for name in names: if name.endswith("_1") or name.endswith("_2"): edited.append(name[:-2]) elif name.endswith("_R1") or name.endswith("_R2"): edited.append(name[:-3]) else: edited.append(name) return edited def edit_names_with_regex(self, names): edited = [] for name in names: matches = re.search(re.compile(self.name_edit_regex), name) edited.append(matches.group(1)) return edited def flatten_metadata(self, metadata): for first_level in metadata: for second_level in metadata[first_level]: if isinstance(metadata[first_level][second_level], set) or isinstance(metadata[first_level][second_level], list): metadata[first_level][second_level] = ", ".join(metadata[first_level][second_level]) return metadata def get_project_metadata(self, udfs): project_metadata={} for sample in self.samples: project_metadata[sample.project.name]={} for udf in udfs: if udf in sample.project.udf: try: project_metadata[sample.project.name][udf].add(str(sample.project.udf[udf])) except: project_metadata[sample.project.name][udf] = set() project_metadata[sample.project.name][udf].add(str(sample.project.udf[udf])) return self.flatten_metadata(project_metadata) def get_sample_metadata(self, udfs): sample_metadata={} for sample in self.samples: sample_metadata[sample.name]={} for udf in udfs: if udf in sample.udf: try: sample_metadata[sample.name][udf].add(str(sample.udf[udf])) except: sample_metadata[sample.name][udf] = set() sample_metadata[sample.name][udf].add(str(sample.udf[udf])) return self.flatten_metadata(sample_metadata) def get_metadata(self, part): for key in self.schema[part]: if key == 'Project': metadata = self.get_project_metadata(self.schema[part]['Project']) elif key == 'Sample': metadata =self.get_sample_metadata(self.schema[part]['Sample']) else: metadata = self.get_artifact_metadata(self.schema[part]) if part == "report_header_info": self.header_metadata.update(metadata) elif part == "general_stats": self.general_metadata.update(metadata) else: self.tab_metadata.update(metadata) def get_artifact_metadata(self, pt_to_udfs): artifact_metadata={} for sample in self.samples: artifact_metadata[sample.name]={} for process_type in pt_to_udfs: if process_type == 'Sample': continue if process_type == 'Project': continue artifacts = self.lims.get_artifacts(sample_name=sample.name, process_type=process_type) for udf_name in pt_to_udfs[process_type].get("outputs", []): values = [] for artifact in artifacts: if udf_name in artifact.udf: values.append(str(artifact.udf[udf_name])) artifact_metadata[sample.name][udf_name]=values processes = set([art.parent_process for art in artifacts]) inputs=[] for p in processes: inputs.extend([art for art in p.all_inputs() if sample.name in [s.name for s in art.samples]]) for udf_name in pt_to_udfs[process_type].get("inputs", []): values = [] for artifact in inputs: if udf_name in artifact.udf: values.append(str(artifact.udf[udf_name])) artifact_metadata[sample.name][udf_name]=values return self.flatten_metadata(artifact_metadata) def update_multiqc_report(self): if config.report_header_info is None: config.report_header_info = [] for first_level in self.header_metadata: d = {} for key in self.header_metadata[first_level]: d[key] = self.header_metadata[first_level][key] config.report_header_info.append(d) headers = {} for first_level in self.schema["general_stats"]: for header in self.schema["general_stats"][first_level]: headers[header] = {} if isinstance(self.schema["general_stats"][first_level][header], dict): for subsubkey, cfg in self.schema["general_stats"][first_level][header].items(): if subsubkey == 'multiply_by': mby = str(cfg)[:] headers[header]['modify'] = lambda x: float(x) * float(mby) else: headers[header][subsubkey] = cfg headers[header]['description'] = headers[header].get('description', '{} - {}'.format(first_level, header)) headers[header]['namespace'] = headers[header].get('namespace', 'Clarity LIMS') headers[header]['scale'] = headers[header].get('scale', 'YlGn') report.general_stats_headers.append(headers) report.general_stats_data.append(self.general_metadata) def make_sections(self): headers = OrderedDict() for first_level in self.tab_metadata: for header in self.tab_metadata[first_level]: desc = header if header not in headers: headers[header] = {} for key in self.schema['clarity_module']: if header in self.schema['clarity_module'][key]: desc = key elif isinstance(self.schema['clarity_module'][key], dict): for subkey, val in self.schema['clarity_module'][key].items(): # print(val) if val is None: break elif header in val: desc = key if isinstance(val[header], dict): for subsubkey, cfg in val[header].items(): if subsubkey == 'multiply_by': mby = str(cfg)[:] headers[header]['modify'] = lambda x: float(x) * float(mby) else: headers[header][subsubkey] = cfg headers[header]['namespace'] = headers[header].get('namespace', desc) headers[header]['title'] = headers[header].get('title', header) headers[header]['description'] = headers[header].get('description', header) self.intro += table.plot(self.tab_metadata, headers)

true

f704e7c24f57a177cdaf904a0e365c964a9eeb80

1,308

py

Python

setup.py

ScyThe1289/cgen

e644d790fce3a06457eff30044c31eb549d8e2f8

[ "MIT" ]

null

setup.py

ScyThe1289/cgen

e644d790fce3a06457eff30044c31eb549d8e2f8

[ "MIT" ]

null

setup.py

ScyThe1289/cgen

e644d790fce3a06457eff30044c31eb549d8e2f8

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- from setuptools import setup with open("README.rst", "rt") as inf: readme = inf.read() ver_dic = {} with open("cgen/version.py") as version_file: version_file_contents = version_file.read() exec(compile(version_file_contents, "cgen/version.py", 'exec'), ver_dic) setup( name="cgen", version=ver_dic["VERSION_TEXT"], description="C/C++ source generation from an AST", long_description=readme, classifiers=[ 'Development Status :: 4 - Beta', 'Intended Audience :: Developers', 'Intended Audience :: Other Audience', 'Intended Audience :: Science/Research', 'License :: OSI Approved :: MIT License', 'Natural Language :: English', 'Programming Language :: Python', 'Topic :: Scientific/Engineering', 'Topic :: Software Development :: Libraries', 'Topic :: Utilities', ], author="Andreas Kloeckner", author_email="inform@tiker.net", license="MIT", url="http://documen.tician.de/cgen/", packages=["cgen"], python_requires="~=3.6", install_requires=[ "pytools>=2015.1.2", "numpy>=1.6", ])

29.727273

72

0.563456

from setuptools import setup with open("README.rst", "rt") as inf: readme = inf.read() ver_dic = {} with open("cgen/version.py") as version_file: version_file_contents = version_file.read() exec(compile(version_file_contents, "cgen/version.py", 'exec'), ver_dic) setup( name="cgen", version=ver_dic["VERSION_TEXT"], description="C/C++ source generation from an AST", long_description=readme, classifiers=[ 'Development Status :: 4 - Beta', 'Intended Audience :: Developers', 'Intended Audience :: Other Audience', 'Intended Audience :: Science/Research', 'License :: OSI Approved :: MIT License', 'Natural Language :: English', 'Programming Language :: Python', 'Topic :: Scientific/Engineering', 'Topic :: Software Development :: Libraries', 'Topic :: Utilities', ], author="Andreas Kloeckner", author_email="inform@tiker.net", license="MIT", url="http://documen.tician.de/cgen/", packages=["cgen"], python_requires="~=3.6", install_requires=[ "pytools>=2015.1.2", "numpy>=1.6", ])

true

f704e89b073258465eda8a5b1cc588d46c48769f

1,044

py

Python

src/robotide/utils/versioncomparator.py

ludovicurbain/SWIFT-RIDE

ab72df08a57101c433bfa5ad44949d9983e4e611

[ "ECL-2.0", "Apache-2.0" ]

775

2015-01-12T06:54:09.000Z

2022-03-25T05:18:05.000Z

src/robotide/utils/versioncomparator.py

ludovicurbain/SWIFT-RIDE

ab72df08a57101c433bfa5ad44949d9983e4e611

[ "ECL-2.0", "Apache-2.0" ]

2,191

2015-05-19T16:49:09.000Z

2022-03-28T21:38:34.000Z

src/robotide/utils/versioncomparator.py

ludovicurbain/SWIFT-RIDE

ab72df08a57101c433bfa5ad44949d9983e4e611

[ "ECL-2.0", "Apache-2.0" ]

382

2015-01-24T08:41:44.000Z

2022-03-13T10:14:20.000Z

# Copyright 2008-2015 Nokia Networks # Copyright 2016- Robot Framework Foundation # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from pkg_resources import parse_version def cmp_versions(version1, version2): if version1 is None: if version2 is None: return 0 else: return -1 if version2 is None: return 1 if parse_version(version1) == parse_version(version2): return 0 elif parse_version(version1) > parse_version(version2): return 1 return -1

32.625

75

0.703065

from pkg_resources import parse_version def cmp_versions(version1, version2): if version1 is None: if version2 is None: return 0 else: return -1 if version2 is None: return 1 if parse_version(version1) == parse_version(version2): return 0 elif parse_version(version1) > parse_version(version2): return 1 return -1

true

f704e942f03f28034ae8717e0065554e929f93f4

4,009

py

Python

zer018_perception/lane_vision/src/homography.py

ZEROSNU/zer018

c469cf22fa1fdf731b02c79f296ee96d35dccb25

[ "MIT" ]

1

2019-01-05T07:01:46.000Z

zer018_perception/lane_vision/src/homography.py

ZEROSNU/zer018

c469cf22fa1fdf731b02c79f296ee96d35dccb25

[ "MIT" ]

null

zer018_perception/lane_vision/src/homography.py

ZEROSNU/zer018

c469cf22fa1fdf731b02c79f296ee96d35dccb25

[ "MIT" ]

null

import cv2 import numpy as np import time ''' TEST FILE using 1000, 1000 output image. Actual code will have an output image of 200,200, which also means a different homography ''' #recalculated homography # homography_front = np.array([[3.12570133882145e-05, 0.000286172662353515, -0.680179732686621], # [0.000967963380750764,-0.00220708598330688,-0.733040431894039], # [9.31003590466217e-08,-7.28146482745869e-06,-0.00116847956395974]]) # homography_left = np.array([[-0.000710128671370178, 6.65307627276203e-05, -0.0692689783742822], # [0.000516381003921171, -0.00181011134155597, -0.997595526929844], # [-2.51074118905076e-08, -6.83854860981181e-06, -0.000959883483255739]]) # homography_right = np.array([[-0.000926831714971124,-7.57332958427531e-05,0.994215703860414], # [-0.000923137149283102,0.00327126641381199,0.107337667969103], # [-2.77833313194565e-07,1.03110471009649e-05,0.00115801865068319]]) # Original homography_front = np.array([[4.62227601649053e-05, 0.000243520884225642, -0.678748083960862], [0.000969465596108860, -0.00207033488113324, -0.734366621126640], [1.58512860546350e-07, -6.83048800828728e-06, -0.00119023476366804]]) homography_left = np.array([[-0.000759672412515488, 2.34075591542924e-05, -0.0699936817773495], [0.000483107853918350, -0.00189886717269873, -0.997544805245074], [-1.49265515027449e-07, -7.08702713960990e-06, -0.000910631508297557]]) homography_right = np.array([[-0.000908962187561903, -3.67579540055241e-05, 0.994837127281325], [-0.000886484342219692, 0.00317263543314027, 0.101420799019439], [-1.14460320494404e-07, 9.99234254412552e-06, 0.00111021419224332]]) #LARGER RANGE OF VIEW translation = np.array([[1, 0, 0],[0,1,100],[0,0,1]]) def warp_image(image, homography): im_out = cv2.warpPerspective(image, np.matmul(translation,homography), (600, 800)) # cv2.imshow('warped', im_out) # cv2.waitKey(0) #cv2.imshow('image', im_out) return im_out def left_hom(image): im_out = cv2.warp # Create mask of front image. im_mask indicates black pixel area def find_mask(image): black_range1 = np.array([0,0,0]) im_mask = (cv2.inRange(image, black_range1, black_range1)).astype('bool') im_mask_inv = (1-im_mask).astype('bool') im_mask_inv = np.dstack((im_mask_inv, im_mask_inv, im_mask_inv)) im_mask= np.dstack((im_mask, im_mask, im_mask)) return im_mask_inv, im_mask if __name__ == "__main__": count = 0 while True: img_front = cv2.imread('../collected_images/5/center/'+ str(count)+'.jpg') img_left = cv2.imread('../collected_images/5/left/'+ str(count)+'.jpg') img_right = cv2.imread('../collected_images/5/right/'+ str(count)+'.jpg') im_front = warp_image(img_front, homography_front).astype('uint8') im_left = warp_image(img_left, homography_left).astype('uint8') im_right = warp_image(img_right, homography_right).astype('uint8') init_time = time.time() im_side = im_left + im_right im_mask_inv, im_mask = find_mask(im_side) front_masked = np.multiply(im_front, im_mask).astype('uint8') side_masked = np.multiply(im_side, im_mask_inv).astype('uint8') print("Masking Time: ", time.time()-init_time) summed_image = front_masked + side_masked #Gaussian Blurring? #summed_image = cv2.GaussianBlur(summed_image, (5,5), 0) # cv2.imshow('front', front_masked) # cv2.imshow('left', im_left) # cv2.imshow('right', im_right) # cv2.imshow('front', im_front) cv2.imshow('summed', summed_image) cv2.imwrite('../collected_images/5/mosaic_full/'+str(count) + '.jpg', summed_image) #summed_image_cropped = summed_image[200:800, :500, :] print("Time elapsed: ", (time.time() - init_time)) #cv2.imshow('summed cropped', summed_image_cropped) count +=1 k = cv2.waitKey(1) & 0xFF if k == 27: break

40.494949

97

0.687204

import cv2 import numpy as np import time homography_front = np.array([[4.62227601649053e-05, 0.000243520884225642, -0.678748083960862], [0.000969465596108860, -0.00207033488113324, -0.734366621126640], [1.58512860546350e-07, -6.83048800828728e-06, -0.00119023476366804]]) homography_left = np.array([[-0.000759672412515488, 2.34075591542924e-05, -0.0699936817773495], [0.000483107853918350, -0.00189886717269873, -0.997544805245074], [-1.49265515027449e-07, -7.08702713960990e-06, -0.000910631508297557]]) homography_right = np.array([[-0.000908962187561903, -3.67579540055241e-05, 0.994837127281325], [-0.000886484342219692, 0.00317263543314027, 0.101420799019439], [-1.14460320494404e-07, 9.99234254412552e-06, 0.00111021419224332]]) translation = np.array([[1, 0, 0],[0,1,100],[0,0,1]]) def warp_image(image, homography): im_out = cv2.warpPerspective(image, np.matmul(translation,homography), (600, 800)) return im_out def left_hom(image): im_out = cv2.warp def find_mask(image): black_range1 = np.array([0,0,0]) im_mask = (cv2.inRange(image, black_range1, black_range1)).astype('bool') im_mask_inv = (1-im_mask).astype('bool') im_mask_inv = np.dstack((im_mask_inv, im_mask_inv, im_mask_inv)) im_mask= np.dstack((im_mask, im_mask, im_mask)) return im_mask_inv, im_mask if __name__ == "__main__": count = 0 while True: img_front = cv2.imread('../collected_images/5/center/'+ str(count)+'.jpg') img_left = cv2.imread('../collected_images/5/left/'+ str(count)+'.jpg') img_right = cv2.imread('../collected_images/5/right/'+ str(count)+'.jpg') im_front = warp_image(img_front, homography_front).astype('uint8') im_left = warp_image(img_left, homography_left).astype('uint8') im_right = warp_image(img_right, homography_right).astype('uint8') init_time = time.time() im_side = im_left + im_right im_mask_inv, im_mask = find_mask(im_side) front_masked = np.multiply(im_front, im_mask).astype('uint8') side_masked = np.multiply(im_side, im_mask_inv).astype('uint8') print("Masking Time: ", time.time()-init_time) summed_image = front_masked + side_masked cv2.imshow('summed', summed_image) cv2.imwrite('../collected_images/5/mosaic_full/'+str(count) + '.jpg', summed_image) print("Time elapsed: ", (time.time() - init_time)) count +=1 k = cv2.waitKey(1) & 0xFF if k == 27: break

true

f704e9b9373cb103702b97b1698ac5e81ca15084

2,543

py

Python

app/forms/user.py

Kbman99/Flask-Startup

e3fea9c7e16a650abd9768ea1e9aee845dcecfda

[ "MIT" ]

null

app/forms/user.py

Kbman99/Flask-Startup

e3fea9c7e16a650abd9768ea1e9aee845dcecfda

[ "MIT" ]

null

app/forms/user.py

Kbman99/Flask-Startup

e3fea9c7e16a650abd9768ea1e9aee845dcecfda

[ "MIT" ]

null

from flask_wtf import Form from wtforms import TextField, PasswordField from wtforms.validators import (Required, Length, Email, ValidationError, EqualTo) from app.models import User class Unique(object): ''' Custom validator to check an object's attribute is unique. For example users should not be able to create an account if the account's email address is already in the database. This class supposes you are using SQLAlchemy to query the database. ''' def __init__(self, model, field, message): self.model = model self.field = field self.message = message def __call__(self, form, field): check = self.model.query.filter(self.field == field.data).first() if check: raise ValidationError(self.message) class Forgot(Form): ''' User forgot password form. ''' email = TextField(validators=[Required(), Email()], description='Email address') class Resend(Form): ''' User forgot password form. ''' email = TextField(validators=[Required(), Email()], description='Email address') class Reset(Form): ''' User reset password form. ''' password = PasswordField(validators=[ Required(), Length(min=6), EqualTo('confirm', message='Passwords must match.') ], description='Password') confirm = PasswordField(description='Confirm password') class Login(Form): ''' User login form. ''' email = TextField(validators=[Required(), Email()], description='Email address') password = PasswordField(validators=[Required()], description='Password') class SignUp(Form): ''' User sign up form. ''' first_name = TextField(validators=[Required(), Length(min=2)], description='Name') last_name = TextField(validators=[Required(), Length(min=2)], description='Surname') email = TextField(validators=[Required(), Email(), Unique(User, User.email, 'This email address is ' + 'already linked to an account.')], description='Email address') password = PasswordField(validators=[ Required(), Length(min=6), EqualTo('confirm', message='Passwords must match.') ], description='Password') confirm = PasswordField(description='Confirm password')

29.917647

75

0.594573

from flask_wtf import Form from wtforms import TextField, PasswordField from wtforms.validators import (Required, Length, Email, ValidationError, EqualTo) from app.models import User class Unique(object): def __init__(self, model, field, message): self.model = model self.field = field self.message = message def __call__(self, form, field): check = self.model.query.filter(self.field == field.data).first() if check: raise ValidationError(self.message) class Forgot(Form): email = TextField(validators=[Required(), Email()], description='Email address') class Resend(Form): email = TextField(validators=[Required(), Email()], description='Email address') class Reset(Form): password = PasswordField(validators=[ Required(), Length(min=6), EqualTo('confirm', message='Passwords must match.') ], description='Password') confirm = PasswordField(description='Confirm password') class Login(Form): email = TextField(validators=[Required(), Email()], description='Email address') password = PasswordField(validators=[Required()], description='Password') class SignUp(Form): first_name = TextField(validators=[Required(), Length(min=2)], description='Name') last_name = TextField(validators=[Required(), Length(min=2)], description='Surname') email = TextField(validators=[Required(), Email(), Unique(User, User.email, 'This email address is ' + 'already linked to an account.')], description='Email address') password = PasswordField(validators=[ Required(), Length(min=6), EqualTo('confirm', message='Passwords must match.') ], description='Password') confirm = PasswordField(description='Confirm password')

true

f704e9eac8de03f01fa77d9579930caec71292b1

22

py

Python

luvio/externals/domain_api/api.py

nguyenhailong253/luvio-server

8e75bea4171fc2367cc6d7ebd5a19382932840d5

[ "MIT" ]

null

luvio/externals/domain_api/api.py

nguyenhailong253/luvio-server

8e75bea4171fc2367cc6d7ebd5a19382932840d5

[ "MIT" ]

null

luvio/externals/domain_api/api.py

nguyenhailong253/luvio-server

8e75bea4171fc2367cc6d7ebd5a19382932840d5

[ "MIT" ]

null

# Call Domain api here

22

0.772727

true

f704ea950fc187b21bea1b7de6bc90411e2926da

845

py

Python

adm/makesedonac.py

AndreySV/sedona

9fe9e800ba3454b725d96355abee172591ceca1f

[ "AFL-3.0" ]

26

2015-02-16T18:35:06.000Z

2021-12-22T03:10:32.000Z

adm/makesedonac.py

AndreySV/sedona

9fe9e800ba3454b725d96355abee172591ceca1f

[ "AFL-3.0" ]

40

2015-09-29T11:19:16.000Z

2021-07-12T02:53:35.000Z

adm/makesedonac.py

AndreySV/sedona

9fe9e800ba3454b725d96355abee172591ceca1f

[ "AFL-3.0" ]

34

2015-12-10T02:53:21.000Z

2022-01-13T16:28:30.000Z

#! /usr/bin/env python3 # # makesedonac.py # # Compile sedonac.jar # # Author: Brian Frank # Creation: 7 Dec 07 # from __future__ import print_function import os import env import compilejar depends = [env.sedonaJar] srcDir = os.path.join(env.src, "sedonac", "src") jarFile = env.sedonacJar packages = [ "sedonac", "sedonac.analysis", "sedonac.asm", "sedonac.ast", "sedonac.gen", "sedonac.ir", "sedonac.namespace", "sedonac.parser", "sedonac.platform", "sedonac.scode", "sedonac.steps", "sedonac.test", "sedonac.translate", "sedonac.util", ] # Make def compile(): try: compilejar.compile(srcDir, depends, packages, jarFile) except env.BuildError: print("**") print("** FAILED [" + jarFile + "]") print("**") return 1 # Main if __name__ == '__main__': compile()

17.244898

58

0.631953

from __future__ import print_function import os import env import compilejar depends = [env.sedonaJar] srcDir = os.path.join(env.src, "sedonac", "src") jarFile = env.sedonacJar packages = [ "sedonac", "sedonac.analysis", "sedonac.asm", "sedonac.ast", "sedonac.gen", "sedonac.ir", "sedonac.namespace", "sedonac.parser", "sedonac.platform", "sedonac.scode", "sedonac.steps", "sedonac.test", "sedonac.translate", "sedonac.util", ] def compile(): try: compilejar.compile(srcDir, depends, packages, jarFile) except env.BuildError: print("**") print("** FAILED [" + jarFile + "]") print("**") return 1 if __name__ == '__main__': compile()

true

f704eb8f47624f4a65229a7680567e12eb42eb47

2,619

py

Python

test/test.py

RLSwanepoel/edsa_packages

6258dd20c2508c5bcc298b3de86cec9e6a1403d2

[ "MIT" ]

null

test/test.py

RLSwanepoel/edsa_packages

6258dd20c2508c5bcc298b3de86cec9e6a1403d2

[ "MIT" ]

null

test/test.py

RLSwanepoel/edsa_packages

6258dd20c2508c5bcc298b3de86cec9e6a1403d2

[ "MIT" ]

null

from edsa_packages import recursion, sorting #Recursion tests def test_sum_array(): ''' Make sure sum_array works ''' assert recursion.sum_array([8, 3, 2, 7, 4]) == 24, 'incorrect' assert recursion.sum_array([5, 7, 8, 8, 6, 3, 4]) == 41, 'incorrect' assert recursion.sum_array([25, 14, 2, 3, 5]) == 49, 'incorrect' def test_fibonacci(): ''' Make sure fibonacci works ''' assert recursion.fibonacci(8) == 22, 'incorrect' assert recursion.fibonacci(10) == 55, 'incorrect' assert recursion.fibonacci(5) == 5, 'incorrect' def test_factorial(): ''' Make sure factorial works ''' assert recursion.factorial(4) == 24, 'incorrect' assert recursion.factorial(8) == 40320, 'incorrect' assert recursion.factorial(3) == 6, 'incorrect' def test_reverse(): ''' Make sure reverse works ''' assert recursion.reverse('apple') == 'elppa', 'incorrect' assert recursion.reverse('test') == 'tset', 'incorrect' assert recursion.reverse('peanut') == 'tunaep', 'incorrect' #Sorting tests def test_bubble_sort(): ''' Make sure bubble_sort works ''' assert sorting.bubble_sort(['apple', 'pear', 'orange', 'pineapple', 'strawberry', 'lemon']) == ['apple', 'lemon', 'orange', 'pear', 'pineapple', 'strawberry'], 'incorrect' assert sorting.bubble_sort(['horse', 'cat', 'aardvark', 'dog', 'fish', 'bird']) == ['aardvark', 'bird', 'cat', 'dog', 'fish', 'horse'], 'incorrect' assert sorting.bubble_sort(['Ford', 'Mitsubishi', 'BMW', 'VW']) == ['BMW', 'Ford', 'Mitsubishi', 'VW'], 'incorrect' def test_merge_sort(): ''' Make sure merge_sort works ''' assert sorting.merge_sort(['apple', 'pear', 'orange', 'pineapple', 'strawberry', 'lemon']) == ['apple', 'lemon', 'orange', 'pear', 'pineapple', 'strawberry'], 'incorrect' assert sorting.merge_sort(['horse', 'cat', 'aardvark', 'dog', 'fish', 'bird']) == ['aardvark', 'bird', 'cat', 'dog', 'fish', 'horse'], 'incorrect' assert sorting.merge_sort(['Ford', 'Mitsubishi', 'BMW', 'VW']) == ['BMW', 'Ford', 'Mitsubishi', 'VW'], 'incorrect' def test_quick_sort(): ''' Make sure quick_sort works ''' assert sorting.quick_sort(['apple', 'pear', 'orange', 'pineapple', 'strawberry', 'lemon']) == ['apple', 'lemon', 'orange', 'pear', 'pineapple', 'strawberry'], 'incorrect' assert sorting.quick_sort(['horse', 'cat', 'aardvark', 'dog', 'fish', 'bird']) == ['aardvark', 'bird', 'cat', 'dog', 'fish', 'horse'], 'incorrect' assert sorting.quick_sort(['Ford', 'Mitsubishi', 'BMW', 'VW']) == ['BMW', 'Ford', 'Mitsubishi', 'VW'], 'incorrect'

42.241935

175

0.613975

from edsa_packages import recursion, sorting def test_sum_array(): assert recursion.sum_array([8, 3, 2, 7, 4]) == 24, 'incorrect' assert recursion.sum_array([5, 7, 8, 8, 6, 3, 4]) == 41, 'incorrect' assert recursion.sum_array([25, 14, 2, 3, 5]) == 49, 'incorrect' def test_fibonacci(): assert recursion.fibonacci(8) == 22, 'incorrect' assert recursion.fibonacci(10) == 55, 'incorrect' assert recursion.fibonacci(5) == 5, 'incorrect' def test_factorial(): assert recursion.factorial(4) == 24, 'incorrect' assert recursion.factorial(8) == 40320, 'incorrect' assert recursion.factorial(3) == 6, 'incorrect' def test_reverse(): assert recursion.reverse('apple') == 'elppa', 'incorrect' assert recursion.reverse('test') == 'tset', 'incorrect' assert recursion.reverse('peanut') == 'tunaep', 'incorrect' def test_bubble_sort(): assert sorting.bubble_sort(['apple', 'pear', 'orange', 'pineapple', 'strawberry', 'lemon']) == ['apple', 'lemon', 'orange', 'pear', 'pineapple', 'strawberry'], 'incorrect' assert sorting.bubble_sort(['horse', 'cat', 'aardvark', 'dog', 'fish', 'bird']) == ['aardvark', 'bird', 'cat', 'dog', 'fish', 'horse'], 'incorrect' assert sorting.bubble_sort(['Ford', 'Mitsubishi', 'BMW', 'VW']) == ['BMW', 'Ford', 'Mitsubishi', 'VW'], 'incorrect' def test_merge_sort(): assert sorting.merge_sort(['apple', 'pear', 'orange', 'pineapple', 'strawberry', 'lemon']) == ['apple', 'lemon', 'orange', 'pear', 'pineapple', 'strawberry'], 'incorrect' assert sorting.merge_sort(['horse', 'cat', 'aardvark', 'dog', 'fish', 'bird']) == ['aardvark', 'bird', 'cat', 'dog', 'fish', 'horse'], 'incorrect' assert sorting.merge_sort(['Ford', 'Mitsubishi', 'BMW', 'VW']) == ['BMW', 'Ford', 'Mitsubishi', 'VW'], 'incorrect' def test_quick_sort(): assert sorting.quick_sort(['apple', 'pear', 'orange', 'pineapple', 'strawberry', 'lemon']) == ['apple', 'lemon', 'orange', 'pear', 'pineapple', 'strawberry'], 'incorrect' assert sorting.quick_sort(['horse', 'cat', 'aardvark', 'dog', 'fish', 'bird']) == ['aardvark', 'bird', 'cat', 'dog', 'fish', 'horse'], 'incorrect' assert sorting.quick_sort(['Ford', 'Mitsubishi', 'BMW', 'VW']) == ['BMW', 'Ford', 'Mitsubishi', 'VW'], 'incorrect'

true

f704ec3011295133131ca2780e725d89200d860c

6,746

py

Python

bin/3rdparty/awscli/customizations/ec2/bundleinstance.py

gayatrisingh31/grand_central

eae635d865549b8002a42d051d9af69e8688e129

[ "MIT" ]

36

2019-11-06T20:49:07.000Z

2021-07-07T02:26:52.000Z

bin/3rdparty/awscli/customizations/ec2/bundleinstance.py

gayatrisingh31/grand_central

eae635d865549b8002a42d051d9af69e8688e129

[ "MIT" ]

21

2019-11-10T05:38:06.000Z

2022-03-10T15:07:48.000Z

bin/3rdparty/awscli/customizations/ec2/bundleinstance.py

gayatrisingh31/grand_central

eae635d865549b8002a42d051d9af69e8688e129

[ "MIT" ]

7

2020-02-13T22:56:46.000Z

2022-01-22T05:57:34.000Z

# Copyright 2013 Amazon.com, Inc. or its affiliates. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"). You # may not use this file except in compliance with the License. A copy of # the License is located at # # http://aws.amazon.com/apache2.0/ # # or in the "license" file accompanying this file. This file is # distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF # ANY KIND, either express or implied. See the License for the specific # language governing permissions and limitations under the License. import logging from hashlib import sha1 import hmac import base64 import datetime from awscli.compat import six from awscli.arguments import CustomArgument logger = logging.getLogger('ec2bundleinstance') # This customization adds the following scalar parameters to the # bundle-instance operation: # --bucket: BUCKET_DOCS = ('The bucket in which to store the AMI. ' 'You can specify a bucket that you already own or ' 'a new bucket that Amazon EC2 creates on your behalf. ' 'If you specify a bucket that belongs to someone else, ' 'Amazon EC2 returns an error.') # --prefix: PREFIX_DOCS = ('The prefix for the image component names being stored ' 'in Amazon S3.') # --owner-akid OWNER_AKID_DOCS = 'The access key ID of the owner of the Amazon S3 bucket.' # --policy POLICY_DOCS = ( "An Amazon S3 upload policy that gives " "Amazon EC2 permission to upload items into Amazon S3 " "on the user's behalf. If you provide this parameter, " "you must also provide " "your secret access key, so we can create a policy " "signature for you (the secret access key is not passed " "to Amazon EC2). If you do not provide this parameter, " "we generate an upload policy for you automatically. " "For more information about upload policies see the " "sections about policy construction and signatures in the " '<a href="http://docs.aws.amazon.com/AmazonS3/latest/dev' '/HTTPPOSTForms.html">' 'Amazon Simple Storage Service Developer Guide</a>.') # --owner-sak OWNER_SAK_DOCS = ('The AWS secret access key for the owner of the ' 'Amazon S3 bucket specified in the --bucket ' 'parameter. This parameter is required so that a ' 'signature can be computed for the policy.') def _add_params(argument_table, **kwargs): # Add the scalar parameters and also change the complex storage # param to not be required so the user doesn't get an error from # argparse if they only supply scalar params. storage_arg = argument_table['storage'] storage_arg.required = False arg = BundleArgument(storage_param='Bucket', name='bucket', help_text=BUCKET_DOCS) argument_table['bucket'] = arg arg = BundleArgument(storage_param='Prefix', name='prefix', help_text=PREFIX_DOCS) argument_table['prefix'] = arg arg = BundleArgument(storage_param='AWSAccessKeyId', name='owner-akid', help_text=OWNER_AKID_DOCS) argument_table['owner-akid'] = arg arg = BundleArgument(storage_param='_SAK', name='owner-sak', help_text=OWNER_SAK_DOCS) argument_table['owner-sak'] = arg arg = BundleArgument(storage_param='UploadPolicy', name='policy', help_text=POLICY_DOCS) argument_table['policy'] = arg def _check_args(parsed_args, **kwargs): # This function checks the parsed args. If the user specified # the --ip-permissions option with any of the scalar options we # raise an error. logger.debug(parsed_args) arg_dict = vars(parsed_args) if arg_dict['storage']: for key in ('bucket', 'prefix', 'owner_akid', 'owner_sak', 'policy'): if arg_dict[key]: msg = ('Mixing the --storage option ' 'with the simple, scalar options is ' 'not recommended.') raise ValueError(msg) POLICY = ('{{"expiration": "{expires}",' '"conditions": [' '{{"bucket": "{bucket}"}},' '{{"acl": "ec2-bundle-read"}},' '["starts-with", "$key", "{prefix}"]' ']}}' ) def _generate_policy(params): # Called if there is no policy supplied by the user. # Creates a policy that provides access for 24 hours. delta = datetime.timedelta(hours=24) expires = datetime.datetime.utcnow() + delta expires_iso = expires.strftime("%Y-%m-%dT%H:%M:%S.%fZ") policy = POLICY.format(expires=expires_iso, bucket=params['Bucket'], prefix=params['Prefix']) params['UploadPolicy'] = policy def _generate_signature(params): # If we have a policy and a sak, create the signature. policy = params.get('UploadPolicy') sak = params.get('_SAK') if policy and sak: policy = base64.b64encode(six.b(policy)).decode('utf-8') new_hmac = hmac.new(sak.encode('utf-8'), digestmod=sha1) new_hmac.update(six.b(policy)) ps = base64.encodestring(new_hmac.digest()).strip().decode('utf-8') params['UploadPolicySignature'] = ps del params['_SAK'] def _check_params(params, **kwargs): # Called just before call but prior to building the params. # Adds information not supplied by the user. storage = params['Storage']['S3'] if 'UploadPolicy' not in storage: _generate_policy(storage) if 'UploadPolicySignature' not in storage: _generate_signature(storage) EVENTS = [ ('building-argument-table.ec2.bundle-instance', _add_params), ('operation-args-parsed.ec2.bundle-instance', _check_args), ('before-parameter-build.ec2.BundleInstance', _check_params), ] def register_bundleinstance(event_handler): # Register all of the events for customizing BundleInstance for event, handler in EVENTS: event_handler.register(event, handler) class BundleArgument(CustomArgument): def __init__(self, storage_param, *args, **kwargs): super(BundleArgument, self).__init__(*args, **kwargs) self._storage_param = storage_param def _build_storage(self, params, value): # Build up the Storage data structure if 'Storage' not in params: params['Storage'] = {'S3': {}} params['Storage']['S3'][self._storage_param] = value def add_to_params(self, parameters, value): if value: self._build_storage(parameters, value)

37.270718

75

0.641121

import logging from hashlib import sha1 import hmac import base64 import datetime from awscli.compat import six from awscli.arguments import CustomArgument logger = logging.getLogger('ec2bundleinstance') BUCKET_DOCS = ('The bucket in which to store the AMI. ' 'You can specify a bucket that you already own or ' 'a new bucket that Amazon EC2 creates on your behalf. ' 'If you specify a bucket that belongs to someone else, ' 'Amazon EC2 returns an error.') PREFIX_DOCS = ('The prefix for the image component names being stored ' 'in Amazon S3.') OWNER_AKID_DOCS = 'The access key ID of the owner of the Amazon S3 bucket.' POLICY_DOCS = ( "An Amazon S3 upload policy that gives " "Amazon EC2 permission to upload items into Amazon S3 " "on the user's behalf. If you provide this parameter, " "you must also provide " "your secret access key, so we can create a policy " "signature for you (the secret access key is not passed " "to Amazon EC2). If you do not provide this parameter, " "we generate an upload policy for you automatically. " "For more information about upload policies see the " "sections about policy construction and signatures in the " '<a href="http://docs.aws.amazon.com/AmazonS3/latest/dev' '/HTTPPOSTForms.html">' 'Amazon Simple Storage Service Developer Guide</a>.') # --owner-sak OWNER_SAK_DOCS = ('The AWS secret access key for the owner of the ' 'Amazon S3 bucket specified in the --bucket ' 'parameter. This parameter is required so that a ' 'signature can be computed for the policy.') def _add_params(argument_table, **kwargs): # Add the scalar parameters and also change the complex storage # param to not be required so the user doesn't get an error from storage_arg = argument_table['storage'] storage_arg.required = False arg = BundleArgument(storage_param='Bucket', name='bucket', help_text=BUCKET_DOCS) argument_table['bucket'] = arg arg = BundleArgument(storage_param='Prefix', name='prefix', help_text=PREFIX_DOCS) argument_table['prefix'] = arg arg = BundleArgument(storage_param='AWSAccessKeyId', name='owner-akid', help_text=OWNER_AKID_DOCS) argument_table['owner-akid'] = arg arg = BundleArgument(storage_param='_SAK', name='owner-sak', help_text=OWNER_SAK_DOCS) argument_table['owner-sak'] = arg arg = BundleArgument(storage_param='UploadPolicy', name='policy', help_text=POLICY_DOCS) argument_table['policy'] = arg def _check_args(parsed_args, **kwargs): logger.debug(parsed_args) arg_dict = vars(parsed_args) if arg_dict['storage']: for key in ('bucket', 'prefix', 'owner_akid', 'owner_sak', 'policy'): if arg_dict[key]: msg = ('Mixing the --storage option ' 'with the simple, scalar options is ' 'not recommended.') raise ValueError(msg) POLICY = ('{{"expiration": "{expires}",' '"conditions": [' '{{"bucket": "{bucket}"}},' '{{"acl": "ec2-bundle-read"}},' '["starts-with", "$key", "{prefix}"]' ']}}' ) def _generate_policy(params): delta = datetime.timedelta(hours=24) expires = datetime.datetime.utcnow() + delta expires_iso = expires.strftime("%Y-%m-%dT%H:%M:%S.%fZ") policy = POLICY.format(expires=expires_iso, bucket=params['Bucket'], prefix=params['Prefix']) params['UploadPolicy'] = policy def _generate_signature(params): policy = params.get('UploadPolicy') sak = params.get('_SAK') if policy and sak: policy = base64.b64encode(six.b(policy)).decode('utf-8') new_hmac = hmac.new(sak.encode('utf-8'), digestmod=sha1) new_hmac.update(six.b(policy)) ps = base64.encodestring(new_hmac.digest()).strip().decode('utf-8') params['UploadPolicySignature'] = ps del params['_SAK'] def _check_params(params, **kwargs): storage = params['Storage']['S3'] if 'UploadPolicy' not in storage: _generate_policy(storage) if 'UploadPolicySignature' not in storage: _generate_signature(storage) EVENTS = [ ('building-argument-table.ec2.bundle-instance', _add_params), ('operation-args-parsed.ec2.bundle-instance', _check_args), ('before-parameter-build.ec2.BundleInstance', _check_params), ] def register_bundleinstance(event_handler): for event, handler in EVENTS: event_handler.register(event, handler) class BundleArgument(CustomArgument): def __init__(self, storage_param, *args, **kwargs): super(BundleArgument, self).__init__(*args, **kwargs) self._storage_param = storage_param def _build_storage(self, params, value): if 'Storage' not in params: params['Storage'] = {'S3': {}} params['Storage']['S3'][self._storage_param] = value def add_to_params(self, parameters, value): if value: self._build_storage(parameters, value)

true

f704ecdfca4d6662c111ca95bb581c2a4f67afb6

891

py

Python

loadtests/locustfile.py

javieraviles/quarkus-github-flow

38ecb9cc626b21e621e20cd77a9638780245047c

[ "MIT" ]

8

2020-09-04T02:16:18.000Z

2022-01-23T18:40:21.000Z

loadtests/locustfile.py

javieraviles/quarkus-github-flow

38ecb9cc626b21e621e20cd77a9638780245047c

[ "MIT" ]

null

loadtests/locustfile.py

javieraviles/quarkus-github-flow

38ecb9cc626b21e621e20cd77a9638780245047c

[ "MIT" ]

3

2020-12-14T19:32:10.000Z

2022-01-17T15:06:20.000Z

import datetime from http import HTTPStatus from locust import HttpUser, task, between # This test can be run after installing locust through the cli as "locust --host=http://<deployed_host>:<port>" # Then url http://localhost:8089/ should be access to start the test. # Can also be run using no UI mode as "locust --no-web -c <number_of_clients> -r <clients_per_second> --run-time <time e.g. 1h30m> --host=http://<deployed_host>:<port>" class QuickstartUser(HttpUser): wait_time = between(1, 2) @task(1) def get_developers(self): r = self.client.get("/developers") assert r.status_code == HTTPStatus.OK, "Unexpected response code: " + str(r.status_code) @task(1) def get_developers_search(self): r = self.client.get("/developers/search/james") assert r.status_code == HTTPStatus.OK, "Unexpected response code: " + str(r.status_code)

40.5

168

0.699214

import datetime from http import HTTPStatus from locust import HttpUser, task, between class QuickstartUser(HttpUser): wait_time = between(1, 2) @task(1) def get_developers(self): r = self.client.get("/developers") assert r.status_code == HTTPStatus.OK, "Unexpected response code: " + str(r.status_code) @task(1) def get_developers_search(self): r = self.client.get("/developers/search/james") assert r.status_code == HTTPStatus.OK, "Unexpected response code: " + str(r.status_code)

true

f704ed56e109cde4331623e75aa489ba21777f29

2,861

py

Python

ipynb_py_convert/__main__.py

max-yue/ipynb-py-convert

77dc636240560892aedbc8a36532784dee408cfa

[ "MIT" ]

null

ipynb_py_convert/__main__.py

max-yue/ipynb-py-convert

77dc636240560892aedbc8a36532784dee408cfa

[ "MIT" ]

null

ipynb_py_convert/__main__.py

max-yue/ipynb-py-convert

77dc636240560892aedbc8a36532784dee408cfa

[ "MIT" ]

null

import json import sys from os import path header_comment = '# %%\n' def nb2py(notebook): result = [] cells = notebook['cells'] for cell in cells: cell_type = cell['cell_type'] if cell_type == 'markdown': result.append('%s"""\n%s\n"""'% (header_comment, ''.join(cell['source']))) if cell_type == 'code': result.append("%s%s" % (header_comment, ''.join(cell['source']))) return '\n\n'.join(result) def py2nb(py_str): # remove leading header comment if py_str.startswith(header_comment): py_str = py_str[len(header_comment):] cells = [] chunks = py_str.split('\n\n%s' % header_comment) for chunk in chunks: cell_type = 'code' if chunk.startswith("'''"): chunk = chunk.strip("'\n") cell_type = 'markdown' elif chunk.startswith('"""'): chunk = chunk.strip('"\n') cell_type = 'markdown' cell = { 'cell_type': cell_type, 'metadata': {}, 'source': chunk.splitlines(True), } if cell_type == 'code': cell.update({'outputs': [], 'execution_count': None}) cells.append(cell) notebook = { 'cells': cells, 'metadata': { 'anaconda-cloud': {}, 'kernelspec': { 'display_name': 'Python 3', 'language': 'python', 'name': 'python3'}, 'language_info': { 'codemirror_mode': {'name': 'ipython', 'version': 3}, 'file_extension': '.py', 'mimetype': 'text/x-python', 'name': 'python', 'nbconvert_exporter': 'python', 'pygments_lexer': 'ipython3', 'version': '3.6.1'}}, 'nbformat': 4, 'nbformat_minor': 1 } return notebook def convert(in_file, out_file): _, in_ext = path.splitext(in_file) _, out_ext = path.splitext(out_file) if in_ext == '.ipynb' and out_ext == '.py': with open(in_file, 'r') as f: notebook = json.load(f) py_str = nb2py(notebook) with open(out_file, 'w') as f: f.write(py_str) elif in_ext == '.py' and out_ext == '.ipynb': with open(in_file, 'r') as f: py_str = f.read() notebook = py2nb(py_str) with open(out_file, 'w') as f: json.dump(notebook, f, indent=2) else: raise(Exception('Extensions must be .ipynb and .py or vice versa')) def main(): argv = sys.argv if len(argv) < 3: print('Usage: ipynb-py-convert in.ipynb out.py') print('or: ipynb-py-convert in.py out.ipynb') sys.exit(1) convert(in_file=argv[1], out_file=argv[2]) if __name__ == '__main__': main()

26.009091

77

0.510311

import json import sys from os import path header_comment = '# %%\n' def nb2py(notebook): result = [] cells = notebook['cells'] for cell in cells: cell_type = cell['cell_type'] if cell_type == 'markdown': result.append('%s"""\n%s\n"""'% (header_comment, ''.join(cell['source']))) if cell_type == 'code': result.append("%s%s" % (header_comment, ''.join(cell['source']))) return '\n\n'.join(result) def py2nb(py_str): if py_str.startswith(header_comment): py_str = py_str[len(header_comment):] cells = [] chunks = py_str.split('\n\n%s' % header_comment) for chunk in chunks: cell_type = 'code' if chunk.startswith("'''"): chunk = chunk.strip("'\n") cell_type = 'markdown' elif chunk.startswith('"""'): chunk = chunk.strip('"\n') cell_type = 'markdown' cell = { 'cell_type': cell_type, 'metadata': {}, 'source': chunk.splitlines(True), } if cell_type == 'code': cell.update({'outputs': [], 'execution_count': None}) cells.append(cell) notebook = { 'cells': cells, 'metadata': { 'anaconda-cloud': {}, 'kernelspec': { 'display_name': 'Python 3', 'language': 'python', 'name': 'python3'}, 'language_info': { 'codemirror_mode': {'name': 'ipython', 'version': 3}, 'file_extension': '.py', 'mimetype': 'text/x-python', 'name': 'python', 'nbconvert_exporter': 'python', 'pygments_lexer': 'ipython3', 'version': '3.6.1'}}, 'nbformat': 4, 'nbformat_minor': 1 } return notebook def convert(in_file, out_file): _, in_ext = path.splitext(in_file) _, out_ext = path.splitext(out_file) if in_ext == '.ipynb' and out_ext == '.py': with open(in_file, 'r') as f: notebook = json.load(f) py_str = nb2py(notebook) with open(out_file, 'w') as f: f.write(py_str) elif in_ext == '.py' and out_ext == '.ipynb': with open(in_file, 'r') as f: py_str = f.read() notebook = py2nb(py_str) with open(out_file, 'w') as f: json.dump(notebook, f, indent=2) else: raise(Exception('Extensions must be .ipynb and .py or vice versa')) def main(): argv = sys.argv if len(argv) < 3: print('Usage: ipynb-py-convert in.ipynb out.py') print('or: ipynb-py-convert in.py out.ipynb') sys.exit(1) convert(in_file=argv[1], out_file=argv[2]) if __name__ == '__main__': main()

true

f704ee4619176809e6126c4c9fe27a817e363dc3

580

py

Python

day_02/day_02.py

aclima93/AdventOfCode

73cc2c194b5ffc27e4d275a3693c148d690bca1f

[ "WTFPL" ]

null

day_02/day_02.py

aclima93/AdventOfCode

73cc2c194b5ffc27e4d275a3693c148d690bca1f

[ "WTFPL" ]

null

day_02/day_02.py

aclima93/AdventOfCode

73cc2c194b5ffc27e4d275a3693c148d690bca1f

[ "WTFPL" ]

null

import sys input_file = open(sys.argv[1]) input_lines = input_file.readlines() total_wrapping = 0 total_ribbon = 0 for line in input_lines: l, w, h = line.split("x") l = int(l) w = int(w) h = int(h) dimensions = [l, w, h] min_1 = min(dimensions) dimensions.remove(min_1) min_2 = min(dimensions) total_wrapping += (2 * l * w) + (2 * w * h) + (2 * h * l) + (min_1 * min_2) total_ribbon += ((min_1 * 2) + (min_2 * 2)) + (l * w * h) # first half print("total_wrapping", total_wrapping) # second half print("total_ribbon", total_ribbon)

20

79

0.6

import sys input_file = open(sys.argv[1]) input_lines = input_file.readlines() total_wrapping = 0 total_ribbon = 0 for line in input_lines: l, w, h = line.split("x") l = int(l) w = int(w) h = int(h) dimensions = [l, w, h] min_1 = min(dimensions) dimensions.remove(min_1) min_2 = min(dimensions) total_wrapping += (2 * l * w) + (2 * w * h) + (2 * h * l) + (min_1 * min_2) total_ribbon += ((min_1 * 2) + (min_2 * 2)) + (l * w * h) print("total_wrapping", total_wrapping) print("total_ribbon", total_ribbon)

true

f704ee9eba83abf2786c8b03afb6216b6afd600a

8,786

py

Python

responder/models.py

repodevs/responder

4d15dbc4654038130f43bff48f51627dfd4b5df7

[ "Apache-2.0" ]

null

responder/models.py

repodevs/responder

4d15dbc4654038130f43bff48f51627dfd4b5df7

[ "Apache-2.0" ]

null

responder/models.py

repodevs/responder

4d15dbc4654038130f43bff48f51627dfd4b5df7

[ "Apache-2.0" ]

null

import io import json import gzip from base64 import b64decode from http.cookies import SimpleCookie import chardet import rfc3986 import graphene import yaml from requests.structures import CaseInsensitiveDict from requests.cookies import RequestsCookieJar from starlette.datastructures import MutableHeaders from starlette.requests import Request as StarletteRequest from starlette.responses import Response as StarletteResponse from urllib.parse import parse_qs from .status_codes import HTTP_200 from .statics import DEFAULT_ENCODING class QueryDict(dict): def __init__(self, query_string): self.update(parse_qs(query_string)) def __getitem__(self, key): """ Return the last data value for this key, or [] if it's an empty list; raise KeyError if not found. """ list_ = super().__getitem__(key) try: return list_[-1] except IndexError: return [] def get(self, key, default=None): """ Return the last data value for the passed key. If key doesn't exist or value is an empty list, return `default`. """ try: val = self[key] except KeyError: return default if val == []: return default return val def _get_list(self, key, default=None, force_list=False): """ Return a list of values for the key. Used internally to manipulate values list. If force_list is True, return a new copy of values. """ try: values = super().__getitem__(key) except KeyError: if default is None: return [] return default else: if force_list: values = list(values) if values is not None else None return values def get_list(self, key, default=None): """ Return the list of values for the key. If key doesn't exist, return a default value. """ return self._get_list(key, default, force_list=True) def items(self): """ Yield (key, value) pairs, where value is the last item in the list associated with the key. """ for key in self: yield key, self[key] def items_list(self): """ Yield (key, value) pairs, where value is the the list. """ yield from super().items() # TODO: add slots class Request: __slots__ = ["_starlette", "formats", "_headers", "_encoding", "api", "_content"] def __init__(self, scope, receive, api=None): self._starlette = StarletteRequest(scope, receive) self.formats = None self._encoding = None self.api = api self._content = None headers = CaseInsensitiveDict() for key, value in self._starlette.headers.items(): headers[key] = value self._headers = headers @property def session(self): """The session data, in dict form, from the Request.""" if "Responder-Session" in self.cookies: data = self.cookies[self.api.session_cookie] data = self.api._signer.unsign(data) data = b64decode(data) return json.loads(data) return {} @property def headers(self): """A case-insensitive dictionary, containing all headers sent in the Request.""" return self._headers @property def mimetype(self): return self.headers.get("Content-Type", "") @property def method(self): """The incoming HTTP method used for the request, lower-cased.""" return self._starlette.method.lower() @property def full_url(self): """The full URL of the Request, query parameters and all.""" return str(self._starlette.url) @property def url(self): """The parsed URL of the Request.""" return rfc3986.urlparse(self.full_url) @property def cookies(self): """The cookies sent in the Request, as a dictionary.""" cookies = RequestsCookieJar() cookie_header = self.headers.get("Cookie", "") bc = SimpleCookie(cookie_header) for k, v in bc.items(): cookies[k] = v return cookies.get_dict() @property def params(self): """A dictionary of the parsed query parameters used for the Request.""" try: return QueryDict(self.url.query) except AttributeError: return QueryDict({}) @property async def encoding(self): """The encoding of the Request's body. Can be set, manually. Must be awaited.""" # Use the user-set encoding first. if self._encoding: return self._encoding # Then try what's defined by the Request. elif await self.declared_encoding: return self.declared_encoding # Then, automatically detect the encoding. else: return await self.apparent_encoding @encoding.setter def encoding(self, value): self._encoding = value @property async def content(self): """The Request body, as bytes. Must be awaited.""" if not self._content: self._content = await self._starlette.body() return self._content @property async def text(self): """The Request body, as unicode. Must be awaited.""" return (await self.content).decode(await self.encoding) @property async def declared_encoding(self): if "Encoding" in self.headers: return self.headers["Encoding"] @property async def apparent_encoding(self): """The apparent encoding, provided by the chardet library. Must be awaited.""" declared_encoding = await self.declared_encoding if declared_encoding: return declared_encoding else: return chardet.detect(await self.content)["encoding"] @property def is_secure(self): return self.url.scheme == "https" def accepts(self, content_type): """Returns ``True`` if the incoming Request accepts the given ``content_type``.""" return content_type in self.headers.get("Accept", []) async def media(self, format=None): """Renders incoming json/yaml/form data as Python objects. Must be awaited. :param format: The name of the format being used. Alternatively accepts a custom callable for the format type. """ if format is None: format = "yaml" if "yaml" in self.mimetype or "" else "json" format = "form" if "form" in self.mimetype or "" else format if format in self.formats: return await self.formats[format](self) else: return await format(self) class Response: __slots__ = [ "req", "status_code", "text", "content", "encoding", "media", "headers", "formats", "cookies", "session", ] def __init__(self, req, *, formats): self.req = req self.status_code = None #: The HTTP Status Code to use for the Response. self.text = None #: A unicode representation of the response body. self.content = None #: A bytes representation of the response body. self.encoding = DEFAULT_ENCODING self.media = ( None ) #: A Python object that will be content-negotiated and sent back to the client. Typically, in JSON formatting. self.headers = ( {} ) #: A Python dictionary of ``{key: value}``, representing the headers of the response. self.formats = formats self.cookies = {} #: The cookies set in the Response, as a dictionary self.session = ( req.session.copy() ) #: The cookie-based session data, in dict form, to add to the Response. @property async def body(self): if self.content: return (self.content, {}) if self.text: return (self.text.encode(self.encoding), {"Encoding": self.encoding}) for format in self.formats: if self.req.accepts(format): return (await self.formats[format](self, encode=True)), {} # Default to JSON anyway. return ( await self.formats["json"](self, encode=True), {"Content-Type": "application/json"}, ) async def __call__(self, receive, send): body, headers = await self.body if self.headers: headers.update(self.headers) response = StarletteResponse( body, status_code=self.status_code, headers=headers ) await response(receive, send)

29.884354

121

0.600842

import io import json import gzip from base64 import b64decode from http.cookies import SimpleCookie import chardet import rfc3986 import graphene import yaml from requests.structures import CaseInsensitiveDict from requests.cookies import RequestsCookieJar from starlette.datastructures import MutableHeaders from starlette.requests import Request as StarletteRequest from starlette.responses import Response as StarletteResponse from urllib.parse import parse_qs from .status_codes import HTTP_200 from .statics import DEFAULT_ENCODING class QueryDict(dict): def __init__(self, query_string): self.update(parse_qs(query_string)) def __getitem__(self, key): list_ = super().__getitem__(key) try: return list_[-1] except IndexError: return [] def get(self, key, default=None): try: val = self[key] except KeyError: return default if val == []: return default return val def _get_list(self, key, default=None, force_list=False): try: values = super().__getitem__(key) except KeyError: if default is None: return [] return default else: if force_list: values = list(values) if values is not None else None return values def get_list(self, key, default=None): return self._get_list(key, default, force_list=True) def items(self): for key in self: yield key, self[key] def items_list(self): yield from super().items() class Request: __slots__ = ["_starlette", "formats", "_headers", "_encoding", "api", "_content"] def __init__(self, scope, receive, api=None): self._starlette = StarletteRequest(scope, receive) self.formats = None self._encoding = None self.api = api self._content = None headers = CaseInsensitiveDict() for key, value in self._starlette.headers.items(): headers[key] = value self._headers = headers @property def session(self): if "Responder-Session" in self.cookies: data = self.cookies[self.api.session_cookie] data = self.api._signer.unsign(data) data = b64decode(data) return json.loads(data) return {} @property def headers(self): return self._headers @property def mimetype(self): return self.headers.get("Content-Type", "") @property def method(self): return self._starlette.method.lower() @property def full_url(self): return str(self._starlette.url) @property def url(self): return rfc3986.urlparse(self.full_url) @property def cookies(self): cookies = RequestsCookieJar() cookie_header = self.headers.get("Cookie", "") bc = SimpleCookie(cookie_header) for k, v in bc.items(): cookies[k] = v return cookies.get_dict() @property def params(self): try: return QueryDict(self.url.query) except AttributeError: return QueryDict({}) @property async def encoding(self): if self._encoding: return self._encoding elif await self.declared_encoding: return self.declared_encoding # Then, automatically detect the encoding. else: return await self.apparent_encoding @encoding.setter def encoding(self, value): self._encoding = value @property async def content(self): if not self._content: self._content = await self._starlette.body() return self._content @property async def text(self): return (await self.content).decode(await self.encoding) @property async def declared_encoding(self): if "Encoding" in self.headers: return self.headers["Encoding"] @property async def apparent_encoding(self): declared_encoding = await self.declared_encoding if declared_encoding: return declared_encoding else: return chardet.detect(await self.content)["encoding"] @property def is_secure(self): return self.url.scheme == "https" def accepts(self, content_type): return content_type in self.headers.get("Accept", []) async def media(self, format=None): if format is None: format = "yaml" if "yaml" in self.mimetype or "" else "json" format = "form" if "form" in self.mimetype or "" else format if format in self.formats: return await self.formats[format](self) else: return await format(self) class Response: __slots__ = [ "req", "status_code", "text", "content", "encoding", "media", "headers", "formats", "cookies", "session", ] def __init__(self, req, *, formats): self.req = req self.status_code = None #: The HTTP Status Code to use for the Response. self.text = None #: A unicode representation of the response body. self.content = None #: A bytes representation of the response body. self.encoding = DEFAULT_ENCODING self.media = ( None ) #: A Python object that will be content-negotiated and sent back to the client. Typically, in JSON formatting. self.headers = ( {} ) #: A Python dictionary of ``{key: value}``, representing the headers of the response. self.formats = formats self.cookies = {} #: The cookies set in the Response, as a dictionary self.session = ( req.session.copy() ) #: The cookie-based session data, in dict form, to add to the Response. @property async def body(self): if self.content: return (self.content, {}) if self.text: return (self.text.encode(self.encoding), {"Encoding": self.encoding}) for format in self.formats: if self.req.accepts(format): return (await self.formats[format](self, encode=True)), {} # Default to JSON anyway. return ( await self.formats["json"](self, encode=True), {"Content-Type": "application/json"}, ) async def __call__(self, receive, send): body, headers = await self.body if self.headers: headers.update(self.headers) response = StarletteResponse( body, status_code=self.status_code, headers=headers ) await response(receive, send)

true

f704ef2c8233458ae3f08016c0e7150a60a3e915

6,863

py

Python

aae.py

anonymous-iclr-2019/acai-iclr-2019

233058a8330e8162e199933ee22b8e5fcac22072

[ "Apache-2.0" ]

20

2018-12-25T05:05:11.000Z

2021-06-21T02:27:53.000Z

aae.py

anonymous-iclr-2019/acai-iclr-2019

233058a8330e8162e199933ee22b8e5fcac22072

[ "Apache-2.0" ]

1

2021-02-08T23:40:40.000Z

aae.py

anonymous-iclr-2019/acai-iclr-2019

233058a8330e8162e199933ee22b8e5fcac22072

[ "Apache-2.0" ]

5

2018-11-04T22:11:45.000Z

2019-09-11T12:57:15.000Z

# Copyright 2018 # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. #!/usr/bin/env python """Adversarial autoencoder. """ from __future__ import absolute_import from __future__ import division from __future__ import print_function import math from absl import app from absl import flags import tensorflow as tf from lib import data, layers, train, utils, classifiers, eval FLAGS = flags.FLAGS class AAE(train.AE): def model(self, latent, depth, scales, adversary_lr, disc_layer_sizes): x = tf.placeholder(tf.float32, [None, self.height, self.width, self.colors], 'x') l = tf.placeholder(tf.float32, [None, self.nclass], 'label') h = tf.placeholder( tf.float32, [None, self.height >> scales, self.width >> scales, latent], 'h') def encoder(x): return layers.encoder(x, scales, depth, latent, 'ae_enc') def decoder(h): return layers.decoder(h, scales, depth, self.colors, 'ae_dec') def discriminator(h): with tf.variable_scope('disc', reuse=tf.AUTO_REUSE): h = tf.layers.flatten(h) for size in [int(s) for s in disc_layer_sizes.split(',')]: h = tf.layers.dense(h, size, tf.nn.leaky_relu) return tf.layers.dense(h, 1) encode = encoder(x) decode = decoder(h) ae = decoder(encode) loss_ae = tf.losses.mean_squared_error(x, ae) prior_samples = tf.random_normal(tf.shape(encode), dtype=encode.dtype) adversary_logit_latent = discriminator(encode) adversary_logit_prior = discriminator(prior_samples) adversary_loss_latents = tf.reduce_mean( tf.nn.sigmoid_cross_entropy_with_logits( logits=adversary_logit_latent, labels=tf.zeros_like(adversary_logit_latent))) adversary_loss_prior = tf.reduce_mean( tf.nn.sigmoid_cross_entropy_with_logits( logits=adversary_logit_prior, labels=tf.ones_like(adversary_logit_prior))) autoencoder_loss_latents = tf.reduce_mean( tf.nn.sigmoid_cross_entropy_with_logits( logits=adversary_logit_latent, labels=tf.ones_like(adversary_logit_latent))) def _accuracy(logits, label): labels = tf.logical_and(label, tf.ones_like(logits, dtype=bool)) correct = tf.equal(tf.greater(logits, 0), labels) return tf.reduce_mean(tf.to_float(correct)) latent_accuracy = _accuracy(adversary_logit_latent, False) prior_accuracy = _accuracy(adversary_logit_prior, True) adversary_accuracy = (latent_accuracy + prior_accuracy)/2 utils.HookReport.log_tensor(loss_ae, 'loss_ae') utils.HookReport.log_tensor(adversary_loss_latents, 'loss_adv_latent') utils.HookReport.log_tensor(adversary_loss_prior, 'loss_adv_prior') utils.HookReport.log_tensor(autoencoder_loss_latents, 'loss_ae_latent') utils.HookReport.log_tensor(adversary_accuracy, 'adversary_accuracy') xops = classifiers.single_layer_classifier( tf.stop_gradient(encode), l, self.nclass) xloss = tf.reduce_mean(xops.loss) utils.HookReport.log_tensor(xloss, 'classify_latent') update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS) ae_vars = tf.global_variables('ae_') disc_vars = tf.global_variables('disc') xl_vars = tf.global_variables('single_layer_classifier') with tf.control_dependencies(update_ops): train_ae = tf.train.AdamOptimizer(FLAGS.lr).minimize( loss_ae + autoencoder_loss_latents, var_list=ae_vars) train_disc = tf.train.AdamOptimizer(adversary_lr).minimize( adversary_loss_prior + adversary_loss_latents, var_list=disc_vars) train_xl = tf.train.AdamOptimizer(FLAGS.lr).minimize( xloss, tf.train.get_global_step(), var_list=xl_vars) ops = train.AEOps(x, h, l, encode, decode, ae, tf.group(train_ae, train_disc, train_xl), classify_latent=xops.output) n_interpolations = 16 n_images_per_interpolation = 16 def gen_images(): return self.make_sample_grid_and_save( ops, interpolation=n_interpolations, height=n_images_per_interpolation) recon, inter, slerp, samples = tf.py_func( gen_images, [], [tf.float32]*4) tf.summary.image('reconstruction', tf.expand_dims(recon, 0)) tf.summary.image('interpolation', tf.expand_dims(inter, 0)) tf.summary.image('slerp', tf.expand_dims(slerp, 0)) tf.summary.image('samples', tf.expand_dims(samples, 0)) if FLAGS.dataset == 'lines32': batched = (n_interpolations, 32, n_images_per_interpolation, 32, 1) batched_interp = tf.transpose( tf.reshape(inter, batched), [0, 2, 1, 3, 4]) mean_distance, mean_smoothness = tf.py_func( eval.line_eval, [batched_interp], [tf.float32, tf.float32]) tf.summary.scalar('mean_distance', mean_distance) tf.summary.scalar('mean_smoothness', mean_smoothness) return ops def main(argv): del argv # Unused. batch = FLAGS.batch dataset = data.get_dataset(FLAGS.dataset, dict(batch_size=batch)) scales = int(round(math.log(dataset.width // FLAGS.latent_width, 2))) model = AAE( dataset, FLAGS.train_dir, latent=FLAGS.latent, depth=FLAGS.depth, scales=scales, adversary_lr=FLAGS.adversary_lr, disc_layer_sizes=FLAGS.disc_layer_sizes) model.train() if __name__ == '__main__': flags.DEFINE_integer('depth', 64, 'Depth of first for convolution.') flags.DEFINE_integer( 'latent', 16, 'Latent space depth, the total latent size is the depth multiplied by ' 'latent_width ** 2.') flags.DEFINE_integer('latent_width', 4, 'Width of the latent space.') flags.DEFINE_float('adversary_lr', 1e-4, 'Learning rate for discriminator.') flags.DEFINE_string('disc_layer_sizes', '100,100', 'Comma-separated list of discriminator layer sizes.') app.run(main)

40.85119

79

0.652339

from __future__ import absolute_import from __future__ import division from __future__ import print_function import math from absl import app from absl import flags import tensorflow as tf from lib import data, layers, train, utils, classifiers, eval FLAGS = flags.FLAGS class AAE(train.AE): def model(self, latent, depth, scales, adversary_lr, disc_layer_sizes): x = tf.placeholder(tf.float32, [None, self.height, self.width, self.colors], 'x') l = tf.placeholder(tf.float32, [None, self.nclass], 'label') h = tf.placeholder( tf.float32, [None, self.height >> scales, self.width >> scales, latent], 'h') def encoder(x): return layers.encoder(x, scales, depth, latent, 'ae_enc') def decoder(h): return layers.decoder(h, scales, depth, self.colors, 'ae_dec') def discriminator(h): with tf.variable_scope('disc', reuse=tf.AUTO_REUSE): h = tf.layers.flatten(h) for size in [int(s) for s in disc_layer_sizes.split(',')]: h = tf.layers.dense(h, size, tf.nn.leaky_relu) return tf.layers.dense(h, 1) encode = encoder(x) decode = decoder(h) ae = decoder(encode) loss_ae = tf.losses.mean_squared_error(x, ae) prior_samples = tf.random_normal(tf.shape(encode), dtype=encode.dtype) adversary_logit_latent = discriminator(encode) adversary_logit_prior = discriminator(prior_samples) adversary_loss_latents = tf.reduce_mean( tf.nn.sigmoid_cross_entropy_with_logits( logits=adversary_logit_latent, labels=tf.zeros_like(adversary_logit_latent))) adversary_loss_prior = tf.reduce_mean( tf.nn.sigmoid_cross_entropy_with_logits( logits=adversary_logit_prior, labels=tf.ones_like(adversary_logit_prior))) autoencoder_loss_latents = tf.reduce_mean( tf.nn.sigmoid_cross_entropy_with_logits( logits=adversary_logit_latent, labels=tf.ones_like(adversary_logit_latent))) def _accuracy(logits, label): labels = tf.logical_and(label, tf.ones_like(logits, dtype=bool)) correct = tf.equal(tf.greater(logits, 0), labels) return tf.reduce_mean(tf.to_float(correct)) latent_accuracy = _accuracy(adversary_logit_latent, False) prior_accuracy = _accuracy(adversary_logit_prior, True) adversary_accuracy = (latent_accuracy + prior_accuracy)/2 utils.HookReport.log_tensor(loss_ae, 'loss_ae') utils.HookReport.log_tensor(adversary_loss_latents, 'loss_adv_latent') utils.HookReport.log_tensor(adversary_loss_prior, 'loss_adv_prior') utils.HookReport.log_tensor(autoencoder_loss_latents, 'loss_ae_latent') utils.HookReport.log_tensor(adversary_accuracy, 'adversary_accuracy') xops = classifiers.single_layer_classifier( tf.stop_gradient(encode), l, self.nclass) xloss = tf.reduce_mean(xops.loss) utils.HookReport.log_tensor(xloss, 'classify_latent') update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS) ae_vars = tf.global_variables('ae_') disc_vars = tf.global_variables('disc') xl_vars = tf.global_variables('single_layer_classifier') with tf.control_dependencies(update_ops): train_ae = tf.train.AdamOptimizer(FLAGS.lr).minimize( loss_ae + autoencoder_loss_latents, var_list=ae_vars) train_disc = tf.train.AdamOptimizer(adversary_lr).minimize( adversary_loss_prior + adversary_loss_latents, var_list=disc_vars) train_xl = tf.train.AdamOptimizer(FLAGS.lr).minimize( xloss, tf.train.get_global_step(), var_list=xl_vars) ops = train.AEOps(x, h, l, encode, decode, ae, tf.group(train_ae, train_disc, train_xl), classify_latent=xops.output) n_interpolations = 16 n_images_per_interpolation = 16 def gen_images(): return self.make_sample_grid_and_save( ops, interpolation=n_interpolations, height=n_images_per_interpolation) recon, inter, slerp, samples = tf.py_func( gen_images, [], [tf.float32]*4) tf.summary.image('reconstruction', tf.expand_dims(recon, 0)) tf.summary.image('interpolation', tf.expand_dims(inter, 0)) tf.summary.image('slerp', tf.expand_dims(slerp, 0)) tf.summary.image('samples', tf.expand_dims(samples, 0)) if FLAGS.dataset == 'lines32': batched = (n_interpolations, 32, n_images_per_interpolation, 32, 1) batched_interp = tf.transpose( tf.reshape(inter, batched), [0, 2, 1, 3, 4]) mean_distance, mean_smoothness = tf.py_func( eval.line_eval, [batched_interp], [tf.float32, tf.float32]) tf.summary.scalar('mean_distance', mean_distance) tf.summary.scalar('mean_smoothness', mean_smoothness) return ops def main(argv): del argv batch = FLAGS.batch dataset = data.get_dataset(FLAGS.dataset, dict(batch_size=batch)) scales = int(round(math.log(dataset.width // FLAGS.latent_width, 2))) model = AAE( dataset, FLAGS.train_dir, latent=FLAGS.latent, depth=FLAGS.depth, scales=scales, adversary_lr=FLAGS.adversary_lr, disc_layer_sizes=FLAGS.disc_layer_sizes) model.train() if __name__ == '__main__': flags.DEFINE_integer('depth', 64, 'Depth of first for convolution.') flags.DEFINE_integer( 'latent', 16, 'Latent space depth, the total latent size is the depth multiplied by ' 'latent_width ** 2.') flags.DEFINE_integer('latent_width', 4, 'Width of the latent space.') flags.DEFINE_float('adversary_lr', 1e-4, 'Learning rate for discriminator.') flags.DEFINE_string('disc_layer_sizes', '100,100', 'Comma-separated list of discriminator layer sizes.') app.run(main)

true

f704ef3af73f982bb2a2835418342e4bbbf74ec9

17,036

py

Python

django/contrib/admin/utils.py

devops2014/djangosite

db77915c9fd35a203edd8206f702ee4082f04d4a

[ "BSD-3-Clause" ]

null

django/contrib/admin/utils.py

devops2014/djangosite

db77915c9fd35a203edd8206f702ee4082f04d4a

[ "BSD-3-Clause" ]

null

django/contrib/admin/utils.py

devops2014/djangosite

db77915c9fd35a203edd8206f702ee4082f04d4a

[ "BSD-3-Clause" ]

null

from __future__ import unicode_literals import datetime import decimal from collections import defaultdict from django.contrib.auth import get_permission_codename from django.core.exceptions import FieldDoesNotExist from django.core.urlresolvers import NoReverseMatch, reverse from django.db import models from django.db.models.constants import LOOKUP_SEP from django.db.models.deletion import Collector from django.forms.forms import pretty_name from django.utils import formats, six, timezone from django.utils.encoding import force_str, force_text, smart_text from django.utils.html import conditional_escape, format_html from django.utils.safestring import mark_safe from django.utils.text import capfirst from django.utils.translation import ungettext def lookup_needs_distinct(opts, lookup_path): """ Returns True if 'distinct()' should be used to query the given lookup path. """ field_name = lookup_path.split('__', 1)[0] field = opts.get_field(field_name) if hasattr(field, 'get_path_info') and any(path.m2m for path in field.get_path_info()): return True return False def prepare_lookup_value(key, value): """ Returns a lookup value prepared to be used in queryset filtering. """ # if key ends with __in, split parameter into separate values if key.endswith('__in'): value = value.split(',') # if key ends with __isnull, special case '' and the string literals 'false' and '0' if key.endswith('__isnull'): if value.lower() in ('', 'false', '0'): value = False else: value = True return value def quote(s): """ Ensure that primary key values do not confuse the admin URLs by escaping any '/', '_' and ':' and similarly problematic characters. Similar to urllib.quote, except that the quoting is slightly different so that it doesn't get automatically unquoted by the Web browser. """ if not isinstance(s, six.string_types): return s res = list(s) for i in range(len(res)): c = res[i] if c in """:/_#?;@&=+$,"[]<>%\\""": res[i] = '_%02X' % ord(c) return ''.join(res) def unquote(s): """ Undo the effects of quote(). Based heavily on urllib.unquote(). """ mychr = chr myatoi = int list = s.split('_') res = [list[0]] myappend = res.append del list[0] for item in list: if item[1:2]: try: myappend(mychr(myatoi(item[:2], 16)) + item[2:]) except ValueError: myappend('_' + item) else: myappend('_' + item) return "".join(res) def flatten(fields): """Returns a list which is a single level of flattening of the original list.""" flat = [] for field in fields: if isinstance(field, (list, tuple)): flat.extend(field) else: flat.append(field) return flat def flatten_fieldsets(fieldsets): """Returns a list of field names from an admin fieldsets structure.""" field_names = [] for name, opts in fieldsets: field_names.extend( flatten(opts['fields']) ) return field_names def get_deleted_objects(objs, opts, user, admin_site, using): """ Find all objects related to ``objs`` that should also be deleted. ``objs`` must be a homogeneous iterable of objects (e.g. a QuerySet). Returns a nested list of strings suitable for display in the template with the ``unordered_list`` filter. """ collector = NestedObjects(using=using) collector.collect(objs) perms_needed = set() def format_callback(obj): has_admin = obj.__class__ in admin_site._registry opts = obj._meta no_edit_link = '%s: %s' % (capfirst(opts.verbose_name), force_text(obj)) if has_admin: try: admin_url = reverse('%s:%s_%s_change' % (admin_site.name, opts.app_label, opts.model_name), None, (quote(obj._get_pk_val()),)) except NoReverseMatch: # Change url doesn't exist -- don't display link to edit return no_edit_link p = '%s.%s' % (opts.app_label, get_permission_codename('delete', opts)) if not user.has_perm(p): perms_needed.add(opts.verbose_name) # Display a link to the admin page. return format_html('{}: <a href="{}">{}</a>', capfirst(opts.verbose_name), admin_url, obj) else: # Don't display link to edit, because it either has no # admin or is edited inline. return no_edit_link to_delete = collector.nested(format_callback) protected = [format_callback(obj) for obj in collector.protected] return to_delete, collector.model_count, perms_needed, protected class NestedObjects(Collector): def __init__(self, *args, **kwargs): super(NestedObjects, self).__init__(*args, **kwargs) self.edges = {} # {from_instance: [to_instances]} self.protected = set() self.model_count = defaultdict(int) def add_edge(self, source, target): self.edges.setdefault(source, []).append(target) def collect(self, objs, source=None, source_attr=None, **kwargs): for obj in objs: if source_attr and not source_attr.endswith('+'): related_name = source_attr % { 'class': source._meta.model_name, 'app_label': source._meta.app_label, } self.add_edge(getattr(obj, related_name), obj) else: self.add_edge(None, obj) self.model_count[obj._meta.verbose_name_plural] += 1 try: return super(NestedObjects, self).collect(objs, source_attr=source_attr, **kwargs) except models.ProtectedError as e: self.protected.update(e.protected_objects) def related_objects(self, related, objs): qs = super(NestedObjects, self).related_objects(related, objs) return qs.select_related(related.field.name) def _nested(self, obj, seen, format_callback): if obj in seen: return [] seen.add(obj) children = [] for child in self.edges.get(obj, ()): children.extend(self._nested(child, seen, format_callback)) if format_callback: ret = [format_callback(obj)] else: ret = [obj] if children: ret.append(children) return ret def nested(self, format_callback=None): """ Return the graph as a nested list. """ seen = set() roots = [] for root in self.edges.get(None, ()): roots.extend(self._nested(root, seen, format_callback)) return roots def can_fast_delete(self, *args, **kwargs): """ We always want to load the objects into memory so that we can display them to the user in confirm page. """ return False def model_format_dict(obj): """ Return a `dict` with keys 'verbose_name' and 'verbose_name_plural', typically for use with string formatting. `obj` may be a `Model` instance, `Model` subclass, or `QuerySet` instance. """ if isinstance(obj, (models.Model, models.base.ModelBase)): opts = obj._meta elif isinstance(obj, models.query.QuerySet): opts = obj.model._meta else: opts = obj return { 'verbose_name': force_text(opts.verbose_name), 'verbose_name_plural': force_text(opts.verbose_name_plural) } def model_ngettext(obj, n=None): """ Return the appropriate `verbose_name` or `verbose_name_plural` value for `obj` depending on the count `n`. `obj` may be a `Model` instance, `Model` subclass, or `QuerySet` instance. If `obj` is a `QuerySet` instance, `n` is optional and the length of the `QuerySet` is used. """ if isinstance(obj, models.query.QuerySet): if n is None: n = obj.count() obj = obj.model d = model_format_dict(obj) singular, plural = d["verbose_name"], d["verbose_name_plural"] return ungettext(singular, plural, n or 0) def lookup_field(name, obj, model_admin=None): opts = obj._meta try: f = _get_non_gfk_field(opts, name) except FieldDoesNotExist: # For non-field values, the value is either a method, property or # returned via a callable. if callable(name): attr = name value = attr(obj) elif (model_admin is not None and hasattr(model_admin, name) and not name == '__str__' and not name == '__unicode__'): attr = getattr(model_admin, name) value = attr(obj) else: attr = getattr(obj, name) if callable(attr): value = attr() else: value = attr f = None else: attr = None value = getattr(obj, name) return f, attr, value def _get_non_gfk_field(opts, name): """ For historical reasons, the admin app relies on GenericForeignKeys as being "not found" by get_field(). This could likely be cleaned up. """ field = opts.get_field(name) if field.is_relation and field.one_to_many and not field.related_model: raise FieldDoesNotExist() return field def label_for_field(name, model, model_admin=None, return_attr=False): """ Returns a sensible label for a field name. The name can be a callable, property (but not created with @property decorator) or the name of an object's attribute, as well as a genuine fields. If return_attr is True, the resolved attribute (which could be a callable) is also returned. This will be None if (and only if) the name refers to a field. """ attr = None try: field = _get_non_gfk_field(model._meta, name) try: label = field.verbose_name except AttributeError: # field is likely a ForeignObjectRel label = field.opts.verbose_name except FieldDoesNotExist: if name == "__unicode__": label = force_text(model._meta.verbose_name) attr = six.text_type elif name == "__str__": label = force_str(model._meta.verbose_name) attr = bytes else: if callable(name): attr = name elif model_admin is not None and hasattr(model_admin, name): attr = getattr(model_admin, name) elif hasattr(model, name): attr = getattr(model, name) else: message = "Unable to lookup '%s' on %s" % (name, model._meta.object_name) if model_admin: message += " or %s" % (model_admin.__class__.__name__,) raise AttributeError(message) if hasattr(attr, "short_description"): label = attr.short_description elif (isinstance(attr, property) and hasattr(attr, "fget") and hasattr(attr.fget, "short_description")): label = attr.fget.short_description elif callable(attr): if attr.__name__ == "<lambda>": label = "--" else: label = pretty_name(attr.__name__) else: label = pretty_name(name) if return_attr: return (label, attr) else: return label def help_text_for_field(name, model): help_text = "" try: field = _get_non_gfk_field(model._meta, name) except FieldDoesNotExist: pass else: if hasattr(field, 'help_text'): help_text = field.help_text return smart_text(help_text) def display_for_field(value, field): from django.contrib.admin.templatetags.admin_list import _boolean_icon from django.contrib.admin.views.main import EMPTY_CHANGELIST_VALUE if field.flatchoices: return dict(field.flatchoices).get(value, EMPTY_CHANGELIST_VALUE) # NullBooleanField needs special-case null-handling, so it comes # before the general null test. elif isinstance(field, models.BooleanField) or isinstance(field, models.NullBooleanField): return _boolean_icon(value) elif value is None: return EMPTY_CHANGELIST_VALUE elif isinstance(field, models.DateTimeField): return formats.localize(timezone.template_localtime(value)) elif isinstance(field, (models.DateField, models.TimeField)): return formats.localize(value) elif isinstance(field, models.DecimalField): return formats.number_format(value, field.decimal_places) elif isinstance(field, models.FloatField): return formats.number_format(value) elif isinstance(field, models.FileField): return mark_safe('<a href="%s">%s</a>' % ( conditional_escape(value.url), conditional_escape(value), )) else: return smart_text(value) def display_for_value(value, boolean=False): from django.contrib.admin.templatetags.admin_list import _boolean_icon from django.contrib.admin.views.main import EMPTY_CHANGELIST_VALUE if boolean: return _boolean_icon(value) elif value is None: return EMPTY_CHANGELIST_VALUE elif isinstance(value, datetime.datetime): return formats.localize(timezone.template_localtime(value)) elif isinstance(value, (datetime.date, datetime.time)): return formats.localize(value) elif isinstance(value, six.integer_types + (decimal.Decimal, float)): return formats.number_format(value) else: return smart_text(value) class NotRelationField(Exception): pass def get_model_from_relation(field): if hasattr(field, 'get_path_info'): return field.get_path_info()[-1].to_opts.model else: raise NotRelationField def reverse_field_path(model, path): """ Create a reversed field path. E.g. Given (Order, "user__groups"), return (Group, "user__order"). Final field must be a related model, not a data field. """ reversed_path = [] parent = model pieces = path.split(LOOKUP_SEP) for piece in pieces: field = parent._meta.get_field(piece) # skip trailing data field if extant: if len(reversed_path) == len(pieces) - 1: # final iteration try: get_model_from_relation(field) except NotRelationField: break # Field should point to another model if field.is_relation and not (field.auto_created and not field.concrete): related_name = field.related_query_name() parent = field.rel.to else: related_name = field.field.name parent = field.related_model reversed_path.insert(0, related_name) return (parent, LOOKUP_SEP.join(reversed_path)) def get_fields_from_path(model, path): """ Return list of Fields given path relative to model. e.g. (ModelX, "user__groups__name") -> [ <django.db.models.fields.related.ForeignKey object at 0x...>, <django.db.models.fields.related.ManyToManyField object at 0x...>, <django.db.models.fields.CharField object at 0x...>, ] """ pieces = path.split(LOOKUP_SEP) fields = [] for piece in pieces: if fields: parent = get_model_from_relation(fields[-1]) else: parent = model fields.append(parent._meta.get_field(piece)) return fields def remove_trailing_data_field(fields): """ Discard trailing non-relation field if extant. """ try: get_model_from_relation(fields[-1]) except NotRelationField: fields = fields[:-1] return fields def get_limit_choices_to_from_path(model, path): """ Return Q object for limiting choices if applicable. If final model in path is linked via a ForeignKey or ManyToManyField which has a ``limit_choices_to`` attribute, return it as a Q object. """ fields = get_fields_from_path(model, path) fields = remove_trailing_data_field(fields) get_limit_choices_to = ( fields and hasattr(fields[-1], 'rel') and getattr(fields[-1].rel, 'get_limit_choices_to', None)) if not get_limit_choices_to: return models.Q() # empty Q limit_choices_to = get_limit_choices_to() if isinstance(limit_choices_to, models.Q): return limit_choices_to # already a Q else: return models.Q(**limit_choices_to) # convert dict to Q

33.535433

94

0.617751

from __future__ import unicode_literals import datetime import decimal from collections import defaultdict from django.contrib.auth import get_permission_codename from django.core.exceptions import FieldDoesNotExist from django.core.urlresolvers import NoReverseMatch, reverse from django.db import models from django.db.models.constants import LOOKUP_SEP from django.db.models.deletion import Collector from django.forms.forms import pretty_name from django.utils import formats, six, timezone from django.utils.encoding import force_str, force_text, smart_text from django.utils.html import conditional_escape, format_html from django.utils.safestring import mark_safe from django.utils.text import capfirst from django.utils.translation import ungettext def lookup_needs_distinct(opts, lookup_path): field_name = lookup_path.split('__', 1)[0] field = opts.get_field(field_name) if hasattr(field, 'get_path_info') and any(path.m2m for path in field.get_path_info()): return True return False def prepare_lookup_value(key, value): if key.endswith('__in'): value = value.split(',') if key.endswith('__isnull'): if value.lower() in ('', 'false', '0'): value = False else: value = True return value def quote(s): if not isinstance(s, six.string_types): return s res = list(s) for i in range(len(res)): c = res[i] if c in """:/_#?;@&=+$,"[]<>%\\""": res[i] = '_%02X' % ord(c) return ''.join(res) def unquote(s): mychr = chr myatoi = int list = s.split('_') res = [list[0]] myappend = res.append del list[0] for item in list: if item[1:2]: try: myappend(mychr(myatoi(item[:2], 16)) + item[2:]) except ValueError: myappend('_' + item) else: myappend('_' + item) return "".join(res) def flatten(fields): flat = [] for field in fields: if isinstance(field, (list, tuple)): flat.extend(field) else: flat.append(field) return flat def flatten_fieldsets(fieldsets): field_names = [] for name, opts in fieldsets: field_names.extend( flatten(opts['fields']) ) return field_names def get_deleted_objects(objs, opts, user, admin_site, using): collector = NestedObjects(using=using) collector.collect(objs) perms_needed = set() def format_callback(obj): has_admin = obj.__class__ in admin_site._registry opts = obj._meta no_edit_link = '%s: %s' % (capfirst(opts.verbose_name), force_text(obj)) if has_admin: try: admin_url = reverse('%s:%s_%s_change' % (admin_site.name, opts.app_label, opts.model_name), None, (quote(obj._get_pk_val()),)) except NoReverseMatch: # Change url doesn't exist -- don't display link to edit return no_edit_link p = '%s.%s' % (opts.app_label, get_permission_codename('delete', opts)) if not user.has_perm(p): perms_needed.add(opts.verbose_name) # Display a link to the admin page. return format_html('{}: <a href="{}">{}</a>', capfirst(opts.verbose_name), admin_url, obj) else: # Don't display link to edit, because it either has no # admin or is edited inline. return no_edit_link to_delete = collector.nested(format_callback) protected = [format_callback(obj) for obj in collector.protected] return to_delete, collector.model_count, perms_needed, protected class NestedObjects(Collector): def __init__(self, *args, **kwargs): super(NestedObjects, self).__init__(*args, **kwargs) self.edges = {} # {from_instance: [to_instances]} self.protected = set() self.model_count = defaultdict(int) def add_edge(self, source, target): self.edges.setdefault(source, []).append(target) def collect(self, objs, source=None, source_attr=None, **kwargs): for obj in objs: if source_attr and not source_attr.endswith('+'): related_name = source_attr % { 'class': source._meta.model_name, 'app_label': source._meta.app_label, } self.add_edge(getattr(obj, related_name), obj) else: self.add_edge(None, obj) self.model_count[obj._meta.verbose_name_plural] += 1 try: return super(NestedObjects, self).collect(objs, source_attr=source_attr, **kwargs) except models.ProtectedError as e: self.protected.update(e.protected_objects) def related_objects(self, related, objs): qs = super(NestedObjects, self).related_objects(related, objs) return qs.select_related(related.field.name) def _nested(self, obj, seen, format_callback): if obj in seen: return [] seen.add(obj) children = [] for child in self.edges.get(obj, ()): children.extend(self._nested(child, seen, format_callback)) if format_callback: ret = [format_callback(obj)] else: ret = [obj] if children: ret.append(children) return ret def nested(self, format_callback=None): seen = set() roots = [] for root in self.edges.get(None, ()): roots.extend(self._nested(root, seen, format_callback)) return roots def can_fast_delete(self, *args, **kwargs): return False def model_format_dict(obj): if isinstance(obj, (models.Model, models.base.ModelBase)): opts = obj._meta elif isinstance(obj, models.query.QuerySet): opts = obj.model._meta else: opts = obj return { 'verbose_name': force_text(opts.verbose_name), 'verbose_name_plural': force_text(opts.verbose_name_plural) } def model_ngettext(obj, n=None): if isinstance(obj, models.query.QuerySet): if n is None: n = obj.count() obj = obj.model d = model_format_dict(obj) singular, plural = d["verbose_name"], d["verbose_name_plural"] return ungettext(singular, plural, n or 0) def lookup_field(name, obj, model_admin=None): opts = obj._meta try: f = _get_non_gfk_field(opts, name) except FieldDoesNotExist: # For non-field values, the value is either a method, property or # returned via a callable. if callable(name): attr = name value = attr(obj) elif (model_admin is not None and hasattr(model_admin, name) and not name == '__str__' and not name == '__unicode__'): attr = getattr(model_admin, name) value = attr(obj) else: attr = getattr(obj, name) if callable(attr): value = attr() else: value = attr f = None else: attr = None value = getattr(obj, name) return f, attr, value def _get_non_gfk_field(opts, name): field = opts.get_field(name) if field.is_relation and field.one_to_many and not field.related_model: raise FieldDoesNotExist() return field def label_for_field(name, model, model_admin=None, return_attr=False): attr = None try: field = _get_non_gfk_field(model._meta, name) try: label = field.verbose_name except AttributeError: # field is likely a ForeignObjectRel label = field.opts.verbose_name except FieldDoesNotExist: if name == "__unicode__": label = force_text(model._meta.verbose_name) attr = six.text_type elif name == "__str__": label = force_str(model._meta.verbose_name) attr = bytes else: if callable(name): attr = name elif model_admin is not None and hasattr(model_admin, name): attr = getattr(model_admin, name) elif hasattr(model, name): attr = getattr(model, name) else: message = "Unable to lookup '%s' on %s" % (name, model._meta.object_name) if model_admin: message += " or %s" % (model_admin.__class__.__name__,) raise AttributeError(message) if hasattr(attr, "short_description"): label = attr.short_description elif (isinstance(attr, property) and hasattr(attr, "fget") and hasattr(attr.fget, "short_description")): label = attr.fget.short_description elif callable(attr): if attr.__name__ == "<lambda>": label = "--" else: label = pretty_name(attr.__name__) else: label = pretty_name(name) if return_attr: return (label, attr) else: return label def help_text_for_field(name, model): help_text = "" try: field = _get_non_gfk_field(model._meta, name) except FieldDoesNotExist: pass else: if hasattr(field, 'help_text'): help_text = field.help_text return smart_text(help_text) def display_for_field(value, field): from django.contrib.admin.templatetags.admin_list import _boolean_icon from django.contrib.admin.views.main import EMPTY_CHANGELIST_VALUE if field.flatchoices: return dict(field.flatchoices).get(value, EMPTY_CHANGELIST_VALUE) # NullBooleanField needs special-case null-handling, so it comes # before the general null test. elif isinstance(field, models.BooleanField) or isinstance(field, models.NullBooleanField): return _boolean_icon(value) elif value is None: return EMPTY_CHANGELIST_VALUE elif isinstance(field, models.DateTimeField): return formats.localize(timezone.template_localtime(value)) elif isinstance(field, (models.DateField, models.TimeField)): return formats.localize(value) elif isinstance(field, models.DecimalField): return formats.number_format(value, field.decimal_places) elif isinstance(field, models.FloatField): return formats.number_format(value) elif isinstance(field, models.FileField): return mark_safe('<a href="%s">%s</a>' % ( conditional_escape(value.url), conditional_escape(value), )) else: return smart_text(value) def display_for_value(value, boolean=False): from django.contrib.admin.templatetags.admin_list import _boolean_icon from django.contrib.admin.views.main import EMPTY_CHANGELIST_VALUE if boolean: return _boolean_icon(value) elif value is None: return EMPTY_CHANGELIST_VALUE elif isinstance(value, datetime.datetime): return formats.localize(timezone.template_localtime(value)) elif isinstance(value, (datetime.date, datetime.time)): return formats.localize(value) elif isinstance(value, six.integer_types + (decimal.Decimal, float)): return formats.number_format(value) else: return smart_text(value) class NotRelationField(Exception): pass def get_model_from_relation(field): if hasattr(field, 'get_path_info'): return field.get_path_info()[-1].to_opts.model else: raise NotRelationField def reverse_field_path(model, path): reversed_path = [] parent = model pieces = path.split(LOOKUP_SEP) for piece in pieces: field = parent._meta.get_field(piece) # skip trailing data field if extant: if len(reversed_path) == len(pieces) - 1: # final iteration try: get_model_from_relation(field) except NotRelationField: break # Field should point to another model if field.is_relation and not (field.auto_created and not field.concrete): related_name = field.related_query_name() parent = field.rel.to else: related_name = field.field.name parent = field.related_model reversed_path.insert(0, related_name) return (parent, LOOKUP_SEP.join(reversed_path)) def get_fields_from_path(model, path): pieces = path.split(LOOKUP_SEP) fields = [] for piece in pieces: if fields: parent = get_model_from_relation(fields[-1]) else: parent = model fields.append(parent._meta.get_field(piece)) return fields def remove_trailing_data_field(fields): try: get_model_from_relation(fields[-1]) except NotRelationField: fields = fields[:-1] return fields def get_limit_choices_to_from_path(model, path): fields = get_fields_from_path(model, path) fields = remove_trailing_data_field(fields) get_limit_choices_to = ( fields and hasattr(fields[-1], 'rel') and getattr(fields[-1].rel, 'get_limit_choices_to', None)) if not get_limit_choices_to: return models.Q() # empty Q limit_choices_to = get_limit_choices_to() if isinstance(limit_choices_to, models.Q): return limit_choices_to # already a Q else: return models.Q(**limit_choices_to) # convert dict to Q

true

f704effc26992be20ba41471a7122694d4e7fcf5

41,290

py

Python

numba/core/dispatcher.py

blair1306/numba

3b9647d17d653abac15363da604eeb804dbdd15a

[ "BSD-2-Clause" ]

2

2018-04-09T18:50:16.000Z

2019-06-11T15:19:51.000Z

numba/core/dispatcher.py

blair1306/numba

3b9647d17d653abac15363da604eeb804dbdd15a

[ "BSD-2-Clause" ]

2

2015-04-15T20:25:48.000Z

2021-03-03T12:32:59.000Z

numba/core/dispatcher.py

blair1306/numba

3b9647d17d653abac15363da604eeb804dbdd15a

[ "BSD-2-Clause" ]

1

2021-05-12T07:29:28.000Z

# -*- coding: utf-8 -*- import collections import functools import os import struct import sys import types as pytypes import uuid import weakref from copy import deepcopy from numba import _dispatcher from numba.core import utils, types, errors, typing, serialize, config, compiler, sigutils from numba.core.compiler_lock import global_compiler_lock from numba.core.typeconv.rules import default_type_manager from numba.core.typing.templates import fold_arguments from numba.core.typing.typeof import Purpose, typeof from numba.core.bytecode import get_code_object from numba.core.caching import NullCache, FunctionCache from numba.core import entrypoints class OmittedArg(object): """ A placeholder for omitted arguments with a default value. """ def __init__(self, value): self.value = value def __repr__(self): return "omitted arg(%r)" % (self.value,) @property def _numba_type_(self): return types.Omitted(self.value) class _FunctionCompiler(object): def __init__(self, py_func, targetdescr, targetoptions, locals, pipeline_class): self.py_func = py_func self.targetdescr = targetdescr self.targetoptions = targetoptions self.locals = locals self.pysig = utils.pysignature(self.py_func) self.pipeline_class = pipeline_class # Remember key=(args, return_type) combinations that will fail # compilation to avoid compilation attempt on them. The values are # the exceptions. self._failed_cache = {} def fold_argument_types(self, args, kws): """ Given positional and named argument types, fold keyword arguments and resolve defaults by inserting types.Omitted() instances. A (pysig, argument types) tuple is returned. """ def normal_handler(index, param, value): return value def default_handler(index, param, default): return types.Omitted(default) def stararg_handler(index, param, values): return types.StarArgTuple(values) # For now, we take argument values from the @jit function, even # in the case of generated jit. args = fold_arguments(self.pysig, args, kws, normal_handler, default_handler, stararg_handler) return self.pysig, args def compile(self, args, return_type): status, retval = self._compile_cached(args, return_type) if status: return retval else: raise retval def _compile_cached(self, args, return_type): key = tuple(args), return_type try: return False, self._failed_cache[key] except KeyError: pass try: retval = self._compile_core(args, return_type) except errors.TypingError as e: self._failed_cache[key] = e return False, e else: return True, retval def _compile_core(self, args, return_type): flags = compiler.Flags() self.targetdescr.options.parse_as_flags(flags, self.targetoptions) flags = self._customize_flags(flags) impl = self._get_implementation(args, {}) cres = compiler.compile_extra(self.targetdescr.typing_context, self.targetdescr.target_context, impl, args=args, return_type=return_type, flags=flags, locals=self.locals, pipeline_class=self.pipeline_class) # Check typing error if object mode is used if cres.typing_error is not None and not flags.enable_pyobject: raise cres.typing_error return cres def get_globals_for_reduction(self): return serialize._get_function_globals_for_reduction(self.py_func) def _get_implementation(self, args, kws): return self.py_func def _customize_flags(self, flags): return flags class _GeneratedFunctionCompiler(_FunctionCompiler): def __init__(self, py_func, targetdescr, targetoptions, locals, pipeline_class): super(_GeneratedFunctionCompiler, self).__init__( py_func, targetdescr, targetoptions, locals, pipeline_class) self.impls = set() def get_globals_for_reduction(self): # This will recursively get the globals used by any nested # implementation function. return serialize._get_function_globals_for_reduction(self.py_func) def _get_implementation(self, args, kws): impl = self.py_func(*args, **kws) # Check the generating function and implementation signatures are # compatible, otherwise compiling would fail later. pysig = utils.pysignature(self.py_func) implsig = utils.pysignature(impl) ok = len(pysig.parameters) == len(implsig.parameters) if ok: for pyparam, implparam in zip(pysig.parameters.values(), implsig.parameters.values()): # We allow the implementation to omit default values, but # if it mentions them, they should have the same value... if (pyparam.name != implparam.name or pyparam.kind != implparam.kind or (implparam.default is not implparam.empty and implparam.default != pyparam.default)): ok = False if not ok: raise TypeError("generated implementation %s should be compatible " "with signature '%s', but has signature '%s'" % (impl, pysig, implsig)) self.impls.add(impl) return impl _CompileStats = collections.namedtuple( '_CompileStats', ('cache_path', 'cache_hits', 'cache_misses')) class _CompilingCounter(object): """ A simple counter that increment in __enter__ and decrement in __exit__. """ def __init__(self): self.counter = 0 def __enter__(self): assert self.counter >= 0 self.counter += 1 def __exit__(self, *args, **kwargs): self.counter -= 1 assert self.counter >= 0 def __bool__(self): return self.counter > 0 __nonzero__ = __bool__ class _DispatcherBase(_dispatcher.Dispatcher): """ Common base class for dispatcher Implementations. """ __numba__ = "py_func" def __init__(self, arg_count, py_func, pysig, can_fallback, exact_match_required): self._tm = default_type_manager # A mapping of signatures to compile results self.overloads = collections.OrderedDict() self.py_func = py_func # other parts of Numba assume the old Python 2 name for code object self.func_code = get_code_object(py_func) # but newer python uses a different name self.__code__ = self.func_code argnames = tuple(pysig.parameters) default_values = self.py_func.__defaults__ or () defargs = tuple(OmittedArg(val) for val in default_values) try: lastarg = list(pysig.parameters.values())[-1] except IndexError: has_stararg = False else: has_stararg = lastarg.kind == lastarg.VAR_POSITIONAL _dispatcher.Dispatcher.__init__(self, self._tm.get_pointer(), arg_count, self._fold_args, argnames, defargs, can_fallback, has_stararg, exact_match_required) self.doc = py_func.__doc__ self._compiling_counter = _CompilingCounter() weakref.finalize(self, self._make_finalizer()) def _compilation_chain_init_hook(self): """ This will be called ahead of any part of compilation taking place (this even includes being ahead of working out the types of the arguments). This permits activities such as initialising extension entry points so that the compiler knows about additional externally defined types etc before it does anything. """ entrypoints.init_all() def _reset_overloads(self): self._clear() self.overloads.clear() def _make_finalizer(self): """ Return a finalizer function that will release references to related compiled functions. """ overloads = self.overloads targetctx = self.targetctx # Early-bind utils.shutting_down() into the function's local namespace # (see issue #689) def finalizer(shutting_down=utils.shutting_down): # The finalizer may crash at shutdown, skip it (resources # will be cleared by the process exiting, anyway). if shutting_down(): return # This function must *not* hold any reference to self: # we take care to bind the necessary objects in the closure. for cres in overloads.values(): try: targetctx.remove_user_function(cres.entry_point) except KeyError: pass return finalizer @property def signatures(self): """ Returns a list of compiled function signatures. """ return list(self.overloads) @property def nopython_signatures(self): return [cres.signature for cres in self.overloads.values() if not cres.objectmode and not cres.interpmode] def disable_compile(self, val=True): """Disable the compilation of new signatures at call time. """ # If disabling compilation then there must be at least one signature assert (not val) or len(self.signatures) > 0 self._can_compile = not val def add_overload(self, cres): args = tuple(cres.signature.args) sig = [a._code for a in args] self._insert(sig, cres.entry_point, cres.objectmode, cres.interpmode) self.overloads[args] = cres def fold_argument_types(self, args, kws): return self._compiler.fold_argument_types(args, kws) def get_call_template(self, args, kws): """ Get a typing.ConcreteTemplate for this dispatcher and the given *args* and *kws* types. This allows to resolve the return type. A (template, pysig, args, kws) tuple is returned. """ # XXX how about a dispatcher template class automating the # following? # Fold keyword arguments and resolve default values pysig, args = self._compiler.fold_argument_types(args, kws) kws = {} # Ensure an overload is available if self._can_compile: self.compile(tuple(args)) # Create function type for typing func_name = self.py_func.__name__ name = "CallTemplate({0})".format(func_name) # The `key` isn't really used except for diagnosis here, # so avoid keeping a reference to `cfunc`. call_template = typing.make_concrete_template( name, key=func_name, signatures=self.nopython_signatures) return call_template, pysig, args, kws def get_overload(self, sig): """ Return the compiled function for the given signature. """ args, return_type = sigutils.normalize_signature(sig) return self.overloads[tuple(args)].entry_point @property def is_compiling(self): """ Whether a specialization is currently being compiled. """ return self._compiling_counter def _compile_for_args(self, *args, **kws): """ For internal use. Compile a specialized version of the function for the given *args* and *kws*, and return the resulting callable. """ assert not kws # call any initialisation required for the compilation chain (e.g. # extension point registration). self._compilation_chain_init_hook() def error_rewrite(e, issue_type): """ Rewrite and raise Exception `e` with help supplied based on the specified issue_type. """ if config.SHOW_HELP: help_msg = errors.error_extras[issue_type] e.patch_message('\n'.join((str(e).rstrip(), help_msg))) if config.FULL_TRACEBACKS: raise e else: raise e.with_traceback(None) argtypes = [] for a in args: if isinstance(a, OmittedArg): argtypes.append(types.Omitted(a.value)) else: argtypes.append(self.typeof_pyval(a)) try: return self.compile(tuple(argtypes)) except errors.ForceLiteralArg as e: # Received request for compiler re-entry with the list of arguments # indicated by e.requested_args. # First, check if any of these args are already Literal-ized already_lit_pos = [i for i in e.requested_args if isinstance(args[i], types.Literal)] if already_lit_pos: # Abort compilation if any argument is already a Literal. # Letting this continue will cause infinite compilation loop. m = ("Repeated literal typing request.\n" "{}.\n" "This is likely caused by an error in typing. " "Please see nested and suppressed exceptions.") info = ', '.join('Arg #{} is {}'.format(i, args[i]) for i in sorted(already_lit_pos)) raise errors.CompilerError(m.format(info)) # Convert requested arguments into a Literal. args = [(types.literal if i in e.requested_args else lambda x: x)(args[i]) for i, v in enumerate(args)] # Re-enter compilation with the Literal-ized arguments return self._compile_for_args(*args) except errors.TypingError as e: # Intercept typing error that may be due to an argument # that failed inferencing as a Numba type failed_args = [] for i, arg in enumerate(args): val = arg.value if isinstance(arg, OmittedArg) else arg try: tp = typeof(val, Purpose.argument) except ValueError as typeof_exc: failed_args.append((i, str(typeof_exc))) else: if tp is None: failed_args.append( (i, "cannot determine Numba type of value %r" % (val,))) if failed_args: # Patch error message to ease debugging msg = str(e).rstrip() + ( "\n\nThis error may have been caused by the following argument(s):\n%s\n" % "\n".join("- argument %d: %s" % (i, err) for i, err in failed_args)) e.patch_message(msg) error_rewrite(e, 'typing') except errors.UnsupportedError as e: # Something unsupported is present in the user code, add help info error_rewrite(e, 'unsupported_error') except (errors.NotDefinedError, errors.RedefinedError, errors.VerificationError) as e: # These errors are probably from an issue with either the code supplied # being syntactically or otherwise invalid error_rewrite(e, 'interpreter') except errors.ConstantInferenceError as e: # this is from trying to infer something as constant when it isn't # or isn't supported as a constant error_rewrite(e, 'constant_inference') except Exception as e: if config.SHOW_HELP: if hasattr(e, 'patch_message'): help_msg = errors.error_extras['reportable'] e.patch_message('\n'.join((str(e).rstrip(), help_msg))) # ignore the FULL_TRACEBACKS config, this needs reporting! raise e def inspect_llvm(self, signature=None): """Get the LLVM intermediate representation generated by compilation. Parameters ---------- signature : tuple of numba types, optional Specify a signature for which to obtain the LLVM IR. If None, the IR is returned for all available signatures. Returns ------- llvm : dict[signature, str] or str Either the LLVM IR string for the specified signature, or, if no signature was given, a dictionary mapping signatures to LLVM IR strings. """ if signature is not None: lib = self.overloads[signature].library return lib.get_llvm_str() return dict((sig, self.inspect_llvm(sig)) for sig in self.signatures) def inspect_asm(self, signature=None): """Get the generated assembly code. Parameters ---------- signature : tuple of numba types, optional Specify a signature for which to obtain the assembly code. If None, the assembly code is returned for all available signatures. Returns ------- asm : dict[signature, str] or str Either the assembly code for the specified signature, or, if no signature was given, a dictionary mapping signatures to assembly code. """ if signature is not None: lib = self.overloads[signature].library return lib.get_asm_str() return dict((sig, self.inspect_asm(sig)) for sig in self.signatures) def inspect_types(self, file=None, signature=None, pretty=False, style='default', **kwargs): """Print/return Numba intermediate representation (IR)-annotated code. Parameters ---------- file : file-like object, optional File to which to print. Defaults to sys.stdout if None. Must be None if ``pretty=True``. signature : tuple of numba types, optional Print/return the intermediate representation for only the given signature. If None, the IR is printed for all available signatures. pretty : bool, optional If True, an Annotate object will be returned that can render the IR with color highlighting in Jupyter and IPython. ``file`` must be None if ``pretty`` is True. Additionally, the ``pygments`` library must be installed for ``pretty=True``. style : str, optional Choose a style for rendering. Ignored if ``pretty`` is ``False``. This is directly consumed by ``pygments`` formatters. To see a list of available styles, import ``pygments`` and run ``list(pygments.styles.get_all_styles())``. Returns ------- annotated : Annotate object, optional Only returned if ``pretty=True``, otherwise this function is only used for its printing side effect. If ``pretty=True``, an Annotate object is returned that can render itself in Jupyter and IPython. """ overloads = self.overloads if signature is not None: overloads = {signature: self.overloads[signature]} if not pretty: if file is None: file = sys.stdout for ver, res in overloads.items(): print("%s %s" % (self.py_func.__name__, ver), file=file) print('-' * 80, file=file) print(res.type_annotation, file=file) print('=' * 80, file=file) else: if file is not None: raise ValueError("`file` must be None if `pretty=True`") from numba.core.annotations.pretty_annotate import Annotate return Annotate(self, signature=signature, style=style) def inspect_cfg(self, signature=None, show_wrapper=None): """ For inspecting the CFG of the function. By default the CFG of the user function is shown. The *show_wrapper* option can be set to "python" or "cfunc" to show the python wrapper function or the *cfunc* wrapper function, respectively. """ if signature is not None: cres = self.overloads[signature] lib = cres.library if show_wrapper == 'python': fname = cres.fndesc.llvm_cpython_wrapper_name elif show_wrapper == 'cfunc': fname = cres.fndesc.llvm_cfunc_wrapper_name else: fname = cres.fndesc.mangled_name return lib.get_function_cfg(fname) return dict((sig, self.inspect_cfg(sig, show_wrapper=show_wrapper)) for sig in self.signatures) def inspect_disasm_cfg(self, signature=None): """ For inspecting the CFG of the disassembly of the function. Requires python package: r2pipe Requires radare2 binary on $PATH. Notebook rendering requires python package: graphviz signature : tuple of Numba types, optional Print/return the disassembly CFG for only the given signatures. If None, the IR is printed for all available signatures. """ if signature is not None: cres = self.overloads[signature] lib = cres.library return lib.get_disasm_cfg() return dict((sig, self.inspect_disasm_cfg(sig)) for sig in self.signatures) def get_annotation_info(self, signature=None): """ Gets the annotation information for the function specified by signature. If no signature is supplied a dictionary of signature to annotation information is returned. """ signatures = self.signatures if signature is None else [signature] out = collections.OrderedDict() for sig in signatures: cres = self.overloads[sig] ta = cres.type_annotation key = (ta.func_id.filename + ':' + str(ta.func_id.firstlineno + 1), ta.signature) out[key] = ta.annotate_raw()[key] return out def _explain_ambiguous(self, *args, **kws): """ Callback for the C _Dispatcher object. """ assert not kws, "kwargs not handled" args = tuple([self.typeof_pyval(a) for a in args]) # The order here must be deterministic for testing purposes, which # is ensured by the OrderedDict. sigs = self.nopython_signatures # This will raise self.typingctx.resolve_overload(self.py_func, sigs, args, kws, allow_ambiguous=False) def _explain_matching_error(self, *args, **kws): """ Callback for the C _Dispatcher object. """ assert not kws, "kwargs not handled" args = [self.typeof_pyval(a) for a in args] msg = ("No matching definition for argument type(s) %s" % ', '.join(map(str, args))) raise TypeError(msg) def _search_new_conversions(self, *args, **kws): """ Callback for the C _Dispatcher object. Search for approximately matching signatures for the given arguments, and ensure the corresponding conversions are registered in the C++ type manager. """ assert not kws, "kwargs not handled" args = [self.typeof_pyval(a) for a in args] found = False for sig in self.nopython_signatures: conv = self.typingctx.install_possible_conversions(args, sig.args) if conv: found = True return found def __repr__(self): return "%s(%s)" % (type(self).__name__, self.py_func) def typeof_pyval(self, val): """ Resolve the Numba type of Python value *val*. This is called from numba._dispatcher as a fallback if the native code cannot decide the type. """ # Not going through the resolve_argument_type() indirection # can save a couple µs. try: tp = typeof(val, Purpose.argument) except ValueError: tp = types.pyobject else: if tp is None: tp = types.pyobject return tp class _MemoMixin: __uuid = None # A {uuid -> instance} mapping, for deserialization _memo = weakref.WeakValueDictionary() # hold refs to last N functions deserialized, retaining them in _memo # regardless of whether there is another reference _recent = collections.deque(maxlen=config.FUNCTION_CACHE_SIZE) @property def _uuid(self): """ An instance-specific UUID, to avoid multiple deserializations of a given instance. Note: this is lazily-generated, for performance reasons. """ u = self.__uuid if u is None: u = str(uuid.uuid1()) self._set_uuid(u) return u def _set_uuid(self, u): assert self.__uuid is None self.__uuid = u self._memo[u] = self self._recent.append(self) class Dispatcher(serialize.ReduceMixin, _MemoMixin, _DispatcherBase): """ Implementation of user-facing dispatcher objects (i.e. created using the @jit decorator). This is an abstract base class. Subclasses should define the targetdescr class attribute. """ _fold_args = True _impl_kinds = { 'direct': _FunctionCompiler, 'generated': _GeneratedFunctionCompiler, } __numba__ = 'py_func' def __init__(self, py_func, locals={}, targetoptions={}, impl_kind='direct', pipeline_class=compiler.Compiler): """ Parameters ---------- py_func: function object to be compiled locals: dict, optional Mapping of local variable names to Numba types. Used to override the types deduced by the type inference engine. targetoptions: dict, optional Target-specific config options. impl_kind: str Select the compiler mode for `@jit` and `@generated_jit` pipeline_class: type numba.compiler.CompilerBase The compiler pipeline type. """ self.typingctx = self.targetdescr.typing_context self.targetctx = self.targetdescr.target_context pysig = utils.pysignature(py_func) arg_count = len(pysig.parameters) can_fallback = not targetoptions.get('nopython', False) _DispatcherBase.__init__(self, arg_count, py_func, pysig, can_fallback, exact_match_required=False) functools.update_wrapper(self, py_func) self.targetoptions = targetoptions self.locals = locals self._cache = NullCache() compiler_class = self._impl_kinds[impl_kind] self._impl_kind = impl_kind self._compiler = compiler_class(py_func, self.targetdescr, targetoptions, locals, pipeline_class) self._cache_hits = collections.Counter() self._cache_misses = collections.Counter() self._type = types.Dispatcher(self) self.typingctx.insert_global(self, self._type) def dump(self, tab=''): print(f'{tab}DUMP {type(self).__name__}[{self.py_func.__name__}, type code={self._type._code}]') for cres in self.overloads.values(): cres.dump(tab = tab + ' ') print(f'{tab}END DUMP {type(self).__name__}[{self.py_func.__name__}]') @property def _numba_type_(self): return types.Dispatcher(self) def enable_caching(self): self._cache = FunctionCache(self.py_func) def __get__(self, obj, objtype=None): '''Allow a JIT function to be bound as a method to an object''' if obj is None: # Unbound method return self else: # Bound method return pytypes.MethodType(self, obj) def _reduce_states(self): """ Reduce the instance for pickling. This will serialize the original function as well the compilation options and compiled signatures, but not the compiled code itself. NOTE: part of ReduceMixin protocol """ if self._can_compile: sigs = [] else: sigs = [cr.signature for cr in self.overloads.values()] return dict( uuid=str(self._uuid), py_func=self.py_func, locals=self.locals, targetoptions=self.targetoptions, impl_kind=self._impl_kind, can_compile=self._can_compile, sigs=sigs, ) @classmethod def _rebuild(cls, uuid, py_func, locals, targetoptions, impl_kind, can_compile, sigs): """ Rebuild an Dispatcher instance after it was __reduce__'d. NOTE: part of ReduceMixin protocol """ try: return cls._memo[uuid] except KeyError: pass self = cls(py_func, locals, targetoptions, impl_kind) # Make sure this deserialization will be merged with subsequent ones self._set_uuid(uuid) for sig in sigs: self.compile(sig) self._can_compile = can_compile return self @global_compiler_lock def compile(self, sig): if not self._can_compile: raise RuntimeError("compilation disabled") # Use counter to track recursion compilation depth with self._compiling_counter: args, return_type = sigutils.normalize_signature(sig) # Don't recompile if signature already exists existing = self.overloads.get(tuple(args)) if existing is not None: return existing.entry_point # Try to load from disk cache cres = self._cache.load_overload(sig, self.targetctx) if cres is not None: self._cache_hits[sig] += 1 # XXX fold this in add_overload()? (also see compiler.py) if not cres.objectmode and not cres.interpmode: self.targetctx.insert_user_function(cres.entry_point, cres.fndesc, [cres.library]) self.add_overload(cres) return cres.entry_point self._cache_misses[sig] += 1 try: cres = self._compiler.compile(args, return_type) except errors.ForceLiteralArg as e: def folded(args, kws): return self._compiler.fold_argument_types(args, kws)[1] raise e.bind_fold_arguments(folded) self.add_overload(cres) self._cache.save_overload(sig, cres) return cres.entry_point def get_compile_result(self, sig): """Compile (if needed) and return the compilation result with the given signature. """ atypes = tuple(sig.args) if atypes not in self.overloads: self.compile(atypes) return self.overloads[atypes] def recompile(self): """ Recompile all signatures afresh. """ sigs = list(self.overloads) old_can_compile = self._can_compile # Ensure the old overloads are disposed of, including compiled functions. self._make_finalizer()() self._reset_overloads() self._cache.flush() self._can_compile = True try: for sig in sigs: self.compile(sig) finally: self._can_compile = old_can_compile @property def stats(self): return _CompileStats( cache_path=self._cache.cache_path, cache_hits=self._cache_hits, cache_misses=self._cache_misses, ) def parallel_diagnostics(self, signature=None, level=1): """ Print parallel diagnostic information for the given signature. If no signature is present it is printed for all known signatures. level is used to adjust the verbosity, level=1 (default) is minimal verbosity, and 2, 3, and 4 provide increasing levels of verbosity. """ def dump(sig): ol = self.overloads[sig] pfdiag = ol.metadata.get('parfor_diagnostics', None) if pfdiag is None: msg = "No parfors diagnostic available, is 'parallel=True' set?" raise ValueError(msg) pfdiag.dump(level) if signature is not None: dump(signature) else: [dump(sig) for sig in self.signatures] def get_metadata(self, signature=None): """ Obtain the compilation metadata for a given signature. """ if signature is not None: return self.overloads[signature].metadata else: return dict((sig, self.overloads[sig].metadata) for sig in self.signatures) def get_function_type(self): """Return unique function type of dispatcher when possible, otherwise return None. A Dispatcher instance has unique function type when it contains exactly one compilation result and its compilation has been disabled (via its disable_compile method). """ if not self._can_compile and len(self.overloads) == 1: cres = tuple(self.overloads.values())[0] return types.FunctionType(cres.signature) class LiftedCode(serialize.ReduceMixin, _MemoMixin, _DispatcherBase): """ Implementation of the hidden dispatcher objects used for lifted code (a lifted loop is really compiled as a separate function). """ _fold_args = False can_cache = False def __init__(self, func_ir, typingctx, targetctx, flags, locals): self.func_ir = func_ir self.lifted_from = None self.typingctx = typingctx self.targetctx = targetctx self.flags = flags self.locals = locals _DispatcherBase.__init__(self, self.func_ir.arg_count, self.func_ir.func_id.func, self.func_ir.func_id.pysig, can_fallback=True, exact_match_required=False) def _reduce_states(self): """ Reduce the instance for pickling. This will serialize the original function as well the compilation options and compiled signatures, but not the compiled code itself. NOTE: part of ReduceMixin protocol """ return dict( uuid=self._uuid, func_ir=self.func_ir, flags=self.flags, locals=self.locals, extras=self._reduce_extras(), ) def _reduce_extras(self): """ NOTE: sub-class can override to add extra states """ return {} @classmethod def _rebuild(cls, uuid, func_ir, flags, locals, extras): """ Rebuild an Dispatcher instance after it was __reduce__'d. NOTE: part of ReduceMixin protocol """ try: return cls._memo[uuid] except KeyError: pass # NOTE: We are assuming that this is must be cpu_target, which is true # for now. # TODO: refactor this to not assume on `cpu_target` from numba.core import registry typingctx = registry.cpu_target.typing_context targetctx = registry.cpu_target.target_context self = cls(func_ir, typingctx, targetctx, flags, locals, **extras) self._set_uuid(uuid) return self def get_source_location(self): """Return the starting line number of the loop. """ return self.func_ir.loc.line def _pre_compile(self, args, return_type, flags): """Pre-compile actions """ pass @global_compiler_lock def compile(self, sig): # Use counter to track recursion compilation depth with self._compiling_counter: # XXX this is mostly duplicated from Dispatcher. flags = self.flags args, return_type = sigutils.normalize_signature(sig) # Don't recompile if signature already exists # (e.g. if another thread compiled it before we got the lock) existing = self.overloads.get(tuple(args)) if existing is not None: return existing.entry_point self._pre_compile(args, return_type, flags) # Clone IR to avoid (some of the) mutation in the rewrite pass cloned_func_ir = self.func_ir.copy() cres = compiler.compile_ir(typingctx=self.typingctx, targetctx=self.targetctx, func_ir=cloned_func_ir, args=args, return_type=return_type, flags=flags, locals=self.locals, lifted=(), lifted_from=self.lifted_from, is_lifted_loop=True,) # Check typing error if object mode is used if cres.typing_error is not None and not flags.enable_pyobject: raise cres.typing_error self.add_overload(cres) return cres.entry_point class LiftedLoop(LiftedCode): def _pre_compile(self, args, return_type, flags): assert not flags.enable_looplift, "Enable looplift flags is on" class LiftedWith(LiftedCode): can_cache = True def _reduce_extras(self): return dict(output_types=self.output_types) @property def _numba_type_(self): return types.Dispatcher(self) def get_call_template(self, args, kws): """ Get a typing.ConcreteTemplate for this dispatcher and the given *args* and *kws* types. This enables the resolving of the return type. A (template, pysig, args, kws) tuple is returned. """ # Ensure an overload is available if self._can_compile: self.compile(tuple(args)) pysig = None # Create function type for typing func_name = self.py_func.__name__ name = "CallTemplate({0})".format(func_name) # The `key` isn't really used except for diagnosis here, # so avoid keeping a reference to `cfunc`. call_template = typing.make_concrete_template( name, key=func_name, signatures=self.nopython_signatures) return call_template, pysig, args, kws class ObjModeLiftedWith(LiftedWith): def __init__(self, *args, **kwargs): self.output_types = kwargs.pop('output_types', None) super(LiftedWith, self).__init__(*args, **kwargs) if not self.flags.force_pyobject: raise ValueError("expecting `flags.force_pyobject`") if self.output_types is None: raise TypeError('`output_types` must be provided') @property def _numba_type_(self): return types.ObjModeDispatcher(self) def get_call_template(self, args, kws): """ Get a typing.ConcreteTemplate for this dispatcher and the given *args* and *kws* types. This enables the resolving of the return type. A (template, pysig, args, kws) tuple is returned. """ assert not kws self._legalize_arg_types(args) # Coerce to object mode args = [types.ffi_forced_object] * len(args) if self._can_compile: self.compile(tuple(args)) signatures = [typing.signature(self.output_types, *args)] pysig = None func_name = self.py_func.__name__ name = "CallTemplate({0})".format(func_name) call_template = typing.make_concrete_template( name, key=func_name, signatures=signatures) return call_template, pysig, args, kws def _legalize_arg_types(self, args): for i, a in enumerate(args, start=1): if isinstance(a, types.List): msg = ( 'Does not support list type inputs into ' 'with-context for arg {}' ) raise errors.TypingError(msg.format(i)) elif isinstance(a, types.Dispatcher): msg = ( 'Does not support function type inputs into ' 'with-context for arg {}' ) raise errors.TypingError(msg.format(i)) # Initialize typeof machinery _dispatcher.typeof_init( OmittedArg, dict((str(t), t._code) for t in types.number_domain))

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import collections import functools import os import struct import sys import types as pytypes import uuid import weakref from copy import deepcopy from numba import _dispatcher from numba.core import utils, types, errors, typing, serialize, config, compiler, sigutils from numba.core.compiler_lock import global_compiler_lock from numba.core.typeconv.rules import default_type_manager from numba.core.typing.templates import fold_arguments from numba.core.typing.typeof import Purpose, typeof from numba.core.bytecode import get_code_object from numba.core.caching import NullCache, FunctionCache from numba.core import entrypoints class OmittedArg(object): def __init__(self, value): self.value = value def __repr__(self): return "omitted arg(%r)" % (self.value,) @property def _numba_type_(self): return types.Omitted(self.value) class _FunctionCompiler(object): def __init__(self, py_func, targetdescr, targetoptions, locals, pipeline_class): self.py_func = py_func self.targetdescr = targetdescr self.targetoptions = targetoptions self.locals = locals self.pysig = utils.pysignature(self.py_func) self.pipeline_class = pipeline_class self._failed_cache = {} def fold_argument_types(self, args, kws): def normal_handler(index, param, value): return value def default_handler(index, param, default): return types.Omitted(default) def stararg_handler(index, param, values): return types.StarArgTuple(values) args = fold_arguments(self.pysig, args, kws, normal_handler, default_handler, stararg_handler) return self.pysig, args def compile(self, args, return_type): status, retval = self._compile_cached(args, return_type) if status: return retval else: raise retval def _compile_cached(self, args, return_type): key = tuple(args), return_type try: return False, self._failed_cache[key] except KeyError: pass try: retval = self._compile_core(args, return_type) except errors.TypingError as e: self._failed_cache[key] = e return False, e else: return True, retval def _compile_core(self, args, return_type): flags = compiler.Flags() self.targetdescr.options.parse_as_flags(flags, self.targetoptions) flags = self._customize_flags(flags) impl = self._get_implementation(args, {}) cres = compiler.compile_extra(self.targetdescr.typing_context, self.targetdescr.target_context, impl, args=args, return_type=return_type, flags=flags, locals=self.locals, pipeline_class=self.pipeline_class) if cres.typing_error is not None and not flags.enable_pyobject: raise cres.typing_error return cres def get_globals_for_reduction(self): return serialize._get_function_globals_for_reduction(self.py_func) def _get_implementation(self, args, kws): return self.py_func def _customize_flags(self, flags): return flags class _GeneratedFunctionCompiler(_FunctionCompiler): def __init__(self, py_func, targetdescr, targetoptions, locals, pipeline_class): super(_GeneratedFunctionCompiler, self).__init__( py_func, targetdescr, targetoptions, locals, pipeline_class) self.impls = set() def get_globals_for_reduction(self): return serialize._get_function_globals_for_reduction(self.py_func) def _get_implementation(self, args, kws): impl = self.py_func(*args, **kws) pysig = utils.pysignature(self.py_func) implsig = utils.pysignature(impl) ok = len(pysig.parameters) == len(implsig.parameters) if ok: for pyparam, implparam in zip(pysig.parameters.values(), implsig.parameters.values()): if (pyparam.name != implparam.name or pyparam.kind != implparam.kind or (implparam.default is not implparam.empty and implparam.default != pyparam.default)): ok = False if not ok: raise TypeError("generated implementation %s should be compatible " "with signature '%s', but has signature '%s'" % (impl, pysig, implsig)) self.impls.add(impl) return impl _CompileStats = collections.namedtuple( '_CompileStats', ('cache_path', 'cache_hits', 'cache_misses')) class _CompilingCounter(object): def __init__(self): self.counter = 0 def __enter__(self): assert self.counter >= 0 self.counter += 1 def __exit__(self, *args, **kwargs): self.counter -= 1 assert self.counter >= 0 def __bool__(self): return self.counter > 0 __nonzero__ = __bool__ class _DispatcherBase(_dispatcher.Dispatcher): __numba__ = "py_func" def __init__(self, arg_count, py_func, pysig, can_fallback, exact_match_required): self._tm = default_type_manager self.overloads = collections.OrderedDict() self.py_func = py_func self.func_code = get_code_object(py_func) self.__code__ = self.func_code argnames = tuple(pysig.parameters) default_values = self.py_func.__defaults__ or () defargs = tuple(OmittedArg(val) for val in default_values) try: lastarg = list(pysig.parameters.values())[-1] except IndexError: has_stararg = False else: has_stararg = lastarg.kind == lastarg.VAR_POSITIONAL _dispatcher.Dispatcher.__init__(self, self._tm.get_pointer(), arg_count, self._fold_args, argnames, defargs, can_fallback, has_stararg, exact_match_required) self.doc = py_func.__doc__ self._compiling_counter = _CompilingCounter() weakref.finalize(self, self._make_finalizer()) def _compilation_chain_init_hook(self): entrypoints.init_all() def _reset_overloads(self): self._clear() self.overloads.clear() def _make_finalizer(self): overloads = self.overloads targetctx = self.targetctx # (see issue #689) def finalizer(shutting_down=utils.shutting_down): # The finalizer may crash at shutdown, skip it (resources # will be cleared by the process exiting, anyway). if shutting_down(): return # This function must *not* hold any reference to self: # we take care to bind the necessary objects in the closure. for cres in overloads.values(): try: targetctx.remove_user_function(cres.entry_point) except KeyError: pass return finalizer @property def signatures(self): return list(self.overloads) @property def nopython_signatures(self): return [cres.signature for cres in self.overloads.values() if not cres.objectmode and not cres.interpmode] def disable_compile(self, val=True): # If disabling compilation then there must be at least one signature assert (not val) or len(self.signatures) > 0 self._can_compile = not val def add_overload(self, cres): args = tuple(cres.signature.args) sig = [a._code for a in args] self._insert(sig, cres.entry_point, cres.objectmode, cres.interpmode) self.overloads[args] = cres def fold_argument_types(self, args, kws): return self._compiler.fold_argument_types(args, kws) def get_call_template(self, args, kws): # XXX how about a dispatcher template class automating the # following? # Fold keyword arguments and resolve default values pysig, args = self._compiler.fold_argument_types(args, kws) kws = {} # Ensure an overload is available if self._can_compile: self.compile(tuple(args)) # Create function type for typing func_name = self.py_func.__name__ name = "CallTemplate({0})".format(func_name) # The `key` isn't really used except for diagnosis here, call_template = typing.make_concrete_template( name, key=func_name, signatures=self.nopython_signatures) return call_template, pysig, args, kws def get_overload(self, sig): args, return_type = sigutils.normalize_signature(sig) return self.overloads[tuple(args)].entry_point @property def is_compiling(self): return self._compiling_counter def _compile_for_args(self, *args, **kws): assert not kws self._compilation_chain_init_hook() def error_rewrite(e, issue_type): if config.SHOW_HELP: help_msg = errors.error_extras[issue_type] e.patch_message('\n'.join((str(e).rstrip(), help_msg))) if config.FULL_TRACEBACKS: raise e else: raise e.with_traceback(None) argtypes = [] for a in args: if isinstance(a, OmittedArg): argtypes.append(types.Omitted(a.value)) else: argtypes.append(self.typeof_pyval(a)) try: return self.compile(tuple(argtypes)) except errors.ForceLiteralArg as e: already_lit_pos = [i for i in e.requested_args if isinstance(args[i], types.Literal)] if already_lit_pos: m = ("Repeated literal typing request.\n" "{}.\n" "This is likely caused by an error in typing. " "Please see nested and suppressed exceptions.") info = ', '.join('Arg #{} is {}'.format(i, args[i]) for i in sorted(already_lit_pos)) raise errors.CompilerError(m.format(info)) args = [(types.literal if i in e.requested_args else lambda x: x)(args[i]) for i, v in enumerate(args)] return self._compile_for_args(*args) except errors.TypingError as e: failed_args = [] for i, arg in enumerate(args): val = arg.value if isinstance(arg, OmittedArg) else arg try: tp = typeof(val, Purpose.argument) except ValueError as typeof_exc: failed_args.append((i, str(typeof_exc))) else: if tp is None: failed_args.append( (i, "cannot determine Numba type of value %r" % (val,))) if failed_args: msg = str(e).rstrip() + ( "\n\nThis error may have been caused by the following argument(s):\n%s\n" % "\n".join("- argument %d: %s" % (i, err) for i, err in failed_args)) e.patch_message(msg) error_rewrite(e, 'typing') except errors.UnsupportedError as e: error_rewrite(e, 'unsupported_error') except (errors.NotDefinedError, errors.RedefinedError, errors.VerificationError) as e: error_rewrite(e, 'interpreter') except errors.ConstantInferenceError as e: # or isn't supported as a constant error_rewrite(e, 'constant_inference') except Exception as e: if config.SHOW_HELP: if hasattr(e, 'patch_message'): help_msg = errors.error_extras['reportable'] e.patch_message('\n'.join((str(e).rstrip(), help_msg))) raise e def inspect_llvm(self, signature=None): if signature is not None: lib = self.overloads[signature].library return lib.get_llvm_str() return dict((sig, self.inspect_llvm(sig)) for sig in self.signatures) def inspect_asm(self, signature=None): if signature is not None: lib = self.overloads[signature].library return lib.get_asm_str() return dict((sig, self.inspect_asm(sig)) for sig in self.signatures) def inspect_types(self, file=None, signature=None, pretty=False, style='default', **kwargs): overloads = self.overloads if signature is not None: overloads = {signature: self.overloads[signature]} if not pretty: if file is None: file = sys.stdout for ver, res in overloads.items(): print("%s %s" % (self.py_func.__name__, ver), file=file) print('-' * 80, file=file) print(res.type_annotation, file=file) print('=' * 80, file=file) else: if file is not None: raise ValueError("`file` must be None if `pretty=True`") from numba.core.annotations.pretty_annotate import Annotate return Annotate(self, signature=signature, style=style) def inspect_cfg(self, signature=None, show_wrapper=None): if signature is not None: cres = self.overloads[signature] lib = cres.library if show_wrapper == 'python': fname = cres.fndesc.llvm_cpython_wrapper_name elif show_wrapper == 'cfunc': fname = cres.fndesc.llvm_cfunc_wrapper_name else: fname = cres.fndesc.mangled_name return lib.get_function_cfg(fname) return dict((sig, self.inspect_cfg(sig, show_wrapper=show_wrapper)) for sig in self.signatures) def inspect_disasm_cfg(self, signature=None): if signature is not None: cres = self.overloads[signature] lib = cres.library return lib.get_disasm_cfg() return dict((sig, self.inspect_disasm_cfg(sig)) for sig in self.signatures) def get_annotation_info(self, signature=None): signatures = self.signatures if signature is None else [signature] out = collections.OrderedDict() for sig in signatures: cres = self.overloads[sig] ta = cres.type_annotation key = (ta.func_id.filename + ':' + str(ta.func_id.firstlineno + 1), ta.signature) out[key] = ta.annotate_raw()[key] return out def _explain_ambiguous(self, *args, **kws): assert not kws, "kwargs not handled" args = tuple([self.typeof_pyval(a) for a in args]) sigs = self.nopython_signatures self.typingctx.resolve_overload(self.py_func, sigs, args, kws, allow_ambiguous=False) def _explain_matching_error(self, *args, **kws): assert not kws, "kwargs not handled" args = [self.typeof_pyval(a) for a in args] msg = ("No matching definition for argument type(s) %s" % ', '.join(map(str, args))) raise TypeError(msg) def _search_new_conversions(self, *args, **kws): assert not kws, "kwargs not handled" args = [self.typeof_pyval(a) for a in args] found = False for sig in self.nopython_signatures: conv = self.typingctx.install_possible_conversions(args, sig.args) if conv: found = True return found def __repr__(self): return "%s(%s)" % (type(self).__name__, self.py_func) def typeof_pyval(self, val): try: tp = typeof(val, Purpose.argument) except ValueError: tp = types.pyobject else: if tp is None: tp = types.pyobject return tp class _MemoMixin: __uuid = None _memo = weakref.WeakValueDictionary() _recent = collections.deque(maxlen=config.FUNCTION_CACHE_SIZE) @property def _uuid(self): u = self.__uuid if u is None: u = str(uuid.uuid1()) self._set_uuid(u) return u def _set_uuid(self, u): assert self.__uuid is None self.__uuid = u self._memo[u] = self self._recent.append(self) class Dispatcher(serialize.ReduceMixin, _MemoMixin, _DispatcherBase): _fold_args = True _impl_kinds = { 'direct': _FunctionCompiler, 'generated': _GeneratedFunctionCompiler, } __numba__ = 'py_func' def __init__(self, py_func, locals={}, targetoptions={}, impl_kind='direct', pipeline_class=compiler.Compiler): self.typingctx = self.targetdescr.typing_context self.targetctx = self.targetdescr.target_context pysig = utils.pysignature(py_func) arg_count = len(pysig.parameters) can_fallback = not targetoptions.get('nopython', False) _DispatcherBase.__init__(self, arg_count, py_func, pysig, can_fallback, exact_match_required=False) functools.update_wrapper(self, py_func) self.targetoptions = targetoptions self.locals = locals self._cache = NullCache() compiler_class = self._impl_kinds[impl_kind] self._impl_kind = impl_kind self._compiler = compiler_class(py_func, self.targetdescr, targetoptions, locals, pipeline_class) self._cache_hits = collections.Counter() self._cache_misses = collections.Counter() self._type = types.Dispatcher(self) self.typingctx.insert_global(self, self._type) def dump(self, tab=''): print(f'{tab}DUMP {type(self).__name__}[{self.py_func.__name__}, type code={self._type._code}]') for cres in self.overloads.values(): cres.dump(tab = tab + ' ') print(f'{tab}END DUMP {type(self).__name__}[{self.py_func.__name__}]') @property def _numba_type_(self): return types.Dispatcher(self) def enable_caching(self): self._cache = FunctionCache(self.py_func) def __get__(self, obj, objtype=None): if obj is None: return self else: return pytypes.MethodType(self, obj) def _reduce_states(self): if self._can_compile: sigs = [] else: sigs = [cr.signature for cr in self.overloads.values()] return dict( uuid=str(self._uuid), py_func=self.py_func, locals=self.locals, targetoptions=self.targetoptions, impl_kind=self._impl_kind, can_compile=self._can_compile, sigs=sigs, ) @classmethod def _rebuild(cls, uuid, py_func, locals, targetoptions, impl_kind, can_compile, sigs): try: return cls._memo[uuid] except KeyError: pass self = cls(py_func, locals, targetoptions, impl_kind) self._set_uuid(uuid) for sig in sigs: self.compile(sig) self._can_compile = can_compile return self @global_compiler_lock def compile(self, sig): if not self._can_compile: raise RuntimeError("compilation disabled") with self._compiling_counter: args, return_type = sigutils.normalize_signature(sig) existing = self.overloads.get(tuple(args)) if existing is not None: return existing.entry_point # Try to load from disk cache cres = self._cache.load_overload(sig, self.targetctx) if cres is not None: self._cache_hits[sig] += 1 # XXX fold this in add_overload()? (also see compiler.py) if not cres.objectmode and not cres.interpmode: self.targetctx.insert_user_function(cres.entry_point, cres.fndesc, [cres.library]) self.add_overload(cres) return cres.entry_point self._cache_misses[sig] += 1 try: cres = self._compiler.compile(args, return_type) except errors.ForceLiteralArg as e: def folded(args, kws): return self._compiler.fold_argument_types(args, kws)[1] raise e.bind_fold_arguments(folded) self.add_overload(cres) self._cache.save_overload(sig, cres) return cres.entry_point def get_compile_result(self, sig): atypes = tuple(sig.args) if atypes not in self.overloads: self.compile(atypes) return self.overloads[atypes] def recompile(self): sigs = list(self.overloads) old_can_compile = self._can_compile # Ensure the old overloads are disposed of, including compiled functions. self._make_finalizer()() self._reset_overloads() self._cache.flush() self._can_compile = True try: for sig in sigs: self.compile(sig) finally: self._can_compile = old_can_compile @property def stats(self): return _CompileStats( cache_path=self._cache.cache_path, cache_hits=self._cache_hits, cache_misses=self._cache_misses, ) def parallel_diagnostics(self, signature=None, level=1): def dump(sig): ol = self.overloads[sig] pfdiag = ol.metadata.get('parfor_diagnostics', None) if pfdiag is None: msg = "No parfors diagnostic available, is 'parallel=True' set?" raise ValueError(msg) pfdiag.dump(level) if signature is not None: dump(signature) else: [dump(sig) for sig in self.signatures] def get_metadata(self, signature=None): if signature is not None: return self.overloads[signature].metadata else: return dict((sig, self.overloads[sig].metadata) for sig in self.signatures) def get_function_type(self): if not self._can_compile and len(self.overloads) == 1: cres = tuple(self.overloads.values())[0] return types.FunctionType(cres.signature) class LiftedCode(serialize.ReduceMixin, _MemoMixin, _DispatcherBase): _fold_args = False can_cache = False def __init__(self, func_ir, typingctx, targetctx, flags, locals): self.func_ir = func_ir self.lifted_from = None self.typingctx = typingctx self.targetctx = targetctx self.flags = flags self.locals = locals _DispatcherBase.__init__(self, self.func_ir.arg_count, self.func_ir.func_id.func, self.func_ir.func_id.pysig, can_fallback=True, exact_match_required=False) def _reduce_states(self): return dict( uuid=self._uuid, func_ir=self.func_ir, flags=self.flags, locals=self.locals, extras=self._reduce_extras(), ) def _reduce_extras(self): return {} @classmethod def _rebuild(cls, uuid, func_ir, flags, locals, extras): try: return cls._memo[uuid] except KeyError: pass # NOTE: We are assuming that this is must be cpu_target, which is true # for now. # TODO: refactor this to not assume on `cpu_target` from numba.core import registry typingctx = registry.cpu_target.typing_context targetctx = registry.cpu_target.target_context self = cls(func_ir, typingctx, targetctx, flags, locals, **extras) self._set_uuid(uuid) return self def get_source_location(self): return self.func_ir.loc.line def _pre_compile(self, args, return_type, flags): pass @global_compiler_lock def compile(self, sig): # Use counter to track recursion compilation depth with self._compiling_counter: # XXX this is mostly duplicated from Dispatcher. flags = self.flags args, return_type = sigutils.normalize_signature(sig) # Don't recompile if signature already exists existing = self.overloads.get(tuple(args)) if existing is not None: return existing.entry_point self._pre_compile(args, return_type, flags) cloned_func_ir = self.func_ir.copy() cres = compiler.compile_ir(typingctx=self.typingctx, targetctx=self.targetctx, func_ir=cloned_func_ir, args=args, return_type=return_type, flags=flags, locals=self.locals, lifted=(), lifted_from=self.lifted_from, is_lifted_loop=True,) if cres.typing_error is not None and not flags.enable_pyobject: raise cres.typing_error self.add_overload(cres) return cres.entry_point class LiftedLoop(LiftedCode): def _pre_compile(self, args, return_type, flags): assert not flags.enable_looplift, "Enable looplift flags is on" class LiftedWith(LiftedCode): can_cache = True def _reduce_extras(self): return dict(output_types=self.output_types) @property def _numba_type_(self): return types.Dispatcher(self) def get_call_template(self, args, kws): if self._can_compile: self.compile(tuple(args)) pysig = None func_name = self.py_func.__name__ name = "CallTemplate({0})".format(func_name) # so avoid keeping a reference to `cfunc`. call_template = typing.make_concrete_template( name, key=func_name, signatures=self.nopython_signatures) return call_template, pysig, args, kws class ObjModeLiftedWith(LiftedWith): def __init__(self, *args, **kwargs): self.output_types = kwargs.pop('output_types', None) super(LiftedWith, self).__init__(*args, **kwargs) if not self.flags.force_pyobject: raise ValueError("expecting `flags.force_pyobject`") if self.output_types is None: raise TypeError('`output_types` must be provided') @property def _numba_type_(self): return types.ObjModeDispatcher(self) def get_call_template(self, args, kws): assert not kws self._legalize_arg_types(args) # Coerce to object mode args = [types.ffi_forced_object] * len(args) if self._can_compile: self.compile(tuple(args)) signatures = [typing.signature(self.output_types, *args)] pysig = None func_name = self.py_func.__name__ name = "CallTemplate({0})".format(func_name) call_template = typing.make_concrete_template( name, key=func_name, signatures=signatures) return call_template, pysig, args, kws def _legalize_arg_types(self, args): for i, a in enumerate(args, start=1): if isinstance(a, types.List): msg = ( 'Does not support list type inputs into ' 'with-context for arg {}' ) raise errors.TypingError(msg.format(i)) elif isinstance(a, types.Dispatcher): msg = ( 'Does not support function type inputs into ' 'with-context for arg {}' ) raise errors.TypingError(msg.format(i)) # Initialize typeof machinery _dispatcher.typeof_init( OmittedArg, dict((str(t), t._code) for t in types.number_domain))

true

f704f208405e343692080fea1f8d229afeb2ecb7

90,552

py

Python

src/genie/libs/parser/iosxe/tests/test_show_interface.py

Drey/genieparser

f16649efabf1f3c892bcaad340ae24ce5403ba6b

[ "Apache-2.0" ]

null

src/genie/libs/parser/iosxe/tests/test_show_interface.py

Drey/genieparser

f16649efabf1f3c892bcaad340ae24ce5403ba6b

[ "Apache-2.0" ]

null

src/genie/libs/parser/iosxe/tests/test_show_interface.py

Drey/genieparser

f16649efabf1f3c892bcaad340ae24ce5403ba6b

[ "Apache-2.0" ]

null

#!/bin/env python import sys import unittest from unittest.mock import Mock from unittest.mock import patch from textwrap import dedent ats_mock = Mock() with patch.dict('sys.modules', {'ats' : ats_mock}, autospec=True): import genie.parsergen from genie.parsergen import oper_fill from genie.parsergen import oper_check from genie.parsergen import oper_fill_tabular from genie.parsergen.examples.parsergen.pyAts import parsergen_demo_mkpg import xml.etree.ElementTree as ET from ats.topology import Device from genie.metaparser.util.exceptions import SchemaEmptyParserError from genie.libs.parser.iosxe.show_interface import ShowInterfacesSwitchport,\ ShowIpInterfaceBriefPipeVlan,\ ShowInterfaces, ShowIpInterface,\ ShowIpv6Interface, \ ShowInterfacesTrunk, \ ShowInterfacesCounters, \ ShowInterfacesAccounting, \ ShowIpInterfaceBriefPipeIp class test_show_interface_parsergen(unittest.TestCase): def test_tabular_parser(self): self.showCommandOutput=''' R1#show ip interface brief Interface IP-Address OK? Method Status Protocol GigabitEthernet0/0 10.1.10.20 YES NVRAM up up GigabitEthernet1/0/1 unassigned YES unset up up GigabitEthernet1/0/10 unassigned YES unset down down ''' self.outputDict = {'GigabitEthernet0/0': {'IP-Address': '10.1.10.20', 'Interface': 'GigabitEthernet0/0', 'Method': 'NVRAM', 'OK?': 'YES', 'Protocol': 'up', 'Status': 'up'}, 'GigabitEthernet1/0/1': {'IP-Address': 'unassigned', 'Interface': 'GigabitEthernet1/0/1', 'Method': 'unset', 'OK?': 'YES', 'Protocol': 'up', 'Status': 'up'}, 'GigabitEthernet1/0/10': {'IP-Address': 'unassigned', 'Interface': 'GigabitEthernet1/0/10', 'Method': 'unset', 'OK?': 'YES', 'Protocol': 'down', 'Status': 'down'}} # Define how device stub will behave when accessed by production parser. device_kwargs = {'is_connected.return_value':True, 'execute.return_value':dedent(self.showCommandOutput)} device1 = Mock(**device_kwargs) device1.name='router3' result = genie.parsergen.oper_fill_tabular(device=device1, show_command="show ip interface brief", refresh_cache=True, header_fields= [ "Interface", "IP-Address", "OK\?", "Method", "Status", "Protocol" ], label_fields= [ "Interface", "IP-Address", "OK?", "Method", "Status", "Protocol" ], index=[0]) self.assertEqual(result.entries, self.outputDict) args, kwargs = device1.execute.call_args self.assertTrue('show ip interface brief' in args, msg='The expected command was not sent to the router') ############################################################################# # unitest For Show Interfaces switchport ############################################################################# class test_show_ip_interfaces_brief_pipe_ip(unittest.TestCase): device = Device(name='aDevice') empty_output = {'execute.return_value': ''} golden_parsed_output = {'interface': {'GigabitEthernet0/0': {'interface_ok': 'YES', 'interface_status': 'up', 'ip_address': '10.1.18.80', 'method': 'manual', 'protocol_status': 'up'}}} golden_output = {'execute.return_value': ''' R1#sh ip int brief | i 10.1.18.80 GigabitEthernet0/0 10.1.18.80 YES manual up up '''} def test_golden(self): self.device = Mock(**self.golden_output) obj = ShowIpInterfaceBriefPipeIp(device=self.device) parsed_output = obj.parse(ip='10.1.18.80') self.assertEqual(parsed_output,self.golden_parsed_output) def test_empty(self): self.device1 = Mock(**self.empty_output) obj = ShowIpInterfaceBriefPipeIp(device=self.device1) with self.assertRaises(SchemaEmptyParserError): parsed_output = obj.parse(ip='10.1.18.80') # Comment out due to old version of yang, will enhance it # class test_show_interface_brief_pipe_vlan_yang(unittest.TestCase): # device = Device(name='aDevice') # device1 = Device(name='bDevice') # golden_parsed_output = {'interface': {'Vlan1': {'vlan_id': {'1': {'ip_address': 'unassigned'}}}, # 'Vlan100': {'vlan_id': {'100': {'ip_address': '201.0.12.1'}}}}} # class etree_holder(): # def __init__(self): # self.data = ET.fromstring(''' # <data> # <native xmlns="http://cisco.com/ns/yang/ned/ios"> # <interface> # <Vlan> # <name>1</name> # <ip> # <no-address> # <address>false</address> # </no-address> # </ip> # <shutdown/> # </Vlan> # <Vlan> # <name>100</name> # <ip> # <address> # <primary> # <address>201.0.12.1</address> # <mask>255.255.255.0</mask> # </primary> # </address> # </ip> # <ipv6> # <address> # <prefix-list> # <prefix>2001::12:30/128</prefix> # </prefix-list> # </address> # </ipv6> # </Vlan> # </interface> # </native> # </data> # ''') # golden_output = {'get.return_value': etree_holder()} # def test_golden(self): # self.device = Mock(**self.golden_output) # intf_obj = ShowIpInterfaceBriefPipeVlan(device=self.device) # intf_obj.context = Context.yang.value # parsed_output = intf_obj.parse() # self.assertEqual(parsed_output,self.golden_parsed_output) # empty_parsed_output = {'interface': {}} # class empty_etree_holder(): # def __init__(self): # self.data = ET.fromstring(''' # <data> # <native xmlns="http://cisco.com/ns/yang/ned/ios"> # <interface> # <Vlan> # </Vlan> # </interface> # </native> # </data> # ''') # empty_output = {'get.return_value': empty_etree_holder()} # def test_empty(self): # self.device1 = Mock(**self.empty_output) # intf_obj = ShowIpInterfaceBriefPipeVlan(device=self.device1) # intf_obj.context = Context.yang.value # parsed_output = intf_obj.parse() # self.assertEqual(parsed_output,self.empty_parsed_output) ############################################################################# # unitest For Show Interfaces switchport ############################################################################# class test_show_interfaces_switchport(unittest.TestCase): device = Device(name='aDevice') empty_output = {'execute.return_value': ''} golden_parsed_output = { "GigabitEthernet1/0/4": { "switchport_mode": "trunk", "pruning_vlans": "2-1001", 'operational_mode': 'trunk', "switchport_enable": True, "trunk_vlans": "200-211", "capture_mode": False, "private_vlan": { "native_vlan_tagging": True, "encapsulation": "dot1q" }, "access_vlan": "1", "unknown_unicast_blocked": False, "native_vlan_tagging": True, "unknown_multicast_blocked": False, "protected": False, "negotiation_of_trunk": True, "capture_vlans": "all", "encapsulation": { "operational_encapsulation": "dot1q", "native_vlan": "1", "administrative_encapsulation": "dot1q" } }, "GigabitEthernet1/0/2": { "pruning_vlans": "2-1001", "switchport_enable": True, "unknown_multicast_blocked": False, "trunk_vlans": "100-110", "port_channel": { "port_channel_int": "Port-channel12", "port_channel_member": True }, "access_vlan": "1", "operational_mode": "trunk", "unknown_unicast_blocked": False, "capture_mode": False, "private_vlan": { "native_vlan_tagging": True, "encapsulation": "dot1q", "operational": "10 (VLAN0010) 100 (VLAN0100)", "trunk_mappings": "10 (VLAN0010) 100 (VLAN0100)" }, "encapsulation": { "operational_encapsulation": "dot1q", "native_vlan": "1", "administrative_encapsulation": "dot1q" }, "protected": False, "native_vlan_tagging": True, "negotiation_of_trunk": True, "capture_vlans": "all", "switchport_mode": "trunk" }, "GigabitEthernet1/0/5": { "switchport_mode": "static access", "pruning_vlans": "2-1001", "switchport_enable": True, "trunk_vlans": "all", 'operational_mode': 'down', "capture_mode": False, "private_vlan": { "native_vlan_tagging": True, "encapsulation": "dot1q" }, "access_vlan": "1", "unknown_unicast_blocked": False, "native_vlan_tagging": True, "unknown_multicast_blocked": False, "protected": False, "negotiation_of_trunk": False, "capture_vlans": "all", "encapsulation": { "native_vlan": "1", "administrative_encapsulation": "dot1q" } }, "Port-channel12": { "switchport_enable": True, "private_vlan": { "encapsulation": "dot1q", "native_vlan_tagging": True }, "native_vlan_tagging": False, "negotiation_of_trunk": True, "unknown_unicast_blocked": False, "protected": False, "encapsulation": { "administrative_encapsulation": "dot1q", "native_vlan": "0" }, "switchport_mode": "trunk", "unknown_multicast_blocked": False, "trunk_vlans": "100-110", "operational_mode": "down", "pruning_vlans": "2-1001", "port_channel": { "port_channel_member": True, "port_channel_member_intfs": [ "GigabitEthernet1/0/2" ] } } } golden_output = {'execute.return_value': ''' Name: Gi1/0/2 Switchport: Enabled Administrative Mode: trunk Operational Mode: trunk (member of bundle Po12) Administrative Trunking Encapsulation: dot1q Operational Trunking Encapsulation: dot1q Negotiation of Trunking: On Access Mode VLAN: 1 (default) Trunking Native Mode VLAN: 1 (default) Administrative Native VLAN tagging: enabled Voice VLAN: none Administrative private-vlan host-association: none Administrative private-vlan mapping: none Administrative private-vlan trunk native VLAN: none Administrative private-vlan trunk Native VLAN tagging: enabled Administrative private-vlan trunk encapsulation: dot1q Administrative private-vlan trunk normal VLANs: none Administrative private-vlan trunk associations: none Administrative private-vlan trunk mappings: 10 (VLAN0010) 100 (VLAN0100) Operational private-vlan: 10 (VLAN0010) 100 (VLAN0100) Trunking VLANs Enabled: 100-110 Pruning VLANs Enabled: 2-1001 Capture Mode Disabled Capture VLANs Allowed: ALL Protected: false Unknown unicast blocked: disabled Unknown multicast blocked: disabled Appliance trust: none Name: Gi1/0/4 Switchport: Enabled Administrative Mode: trunk Operational Mode: trunk Administrative Trunking Encapsulation: dot1q Operational Trunking Encapsulation: dot1q Negotiation of Trunking: On Access Mode VLAN: 1 (default) Trunking Native Mode VLAN: 1 (default) Administrative Native VLAN tagging: enabled Voice VLAN: none Administrative private-vlan host-association: none Administrative private-vlan mapping: none Administrative private-vlan trunk native VLAN: none Administrative private-vlan trunk Native VLAN tagging: enabled Administrative private-vlan trunk encapsulation: dot1q Administrative private-vlan trunk normal VLANs: none Administrative private-vlan trunk associations: none Administrative private-vlan trunk mappings: none Operational private-vlan: none Trunking VLANs Enabled: 200-211 Pruning VLANs Enabled: 2-1001 Capture Mode Disabled Capture VLANs Allowed: ALL Protected: false Unknown unicast blocked: disabled Unknown multicast blocked: disabled Appliance trust: none Name: Gi1/0/5 Switchport: Enabled Administrative Mode: static access Operational Mode: down Administrative Trunking Encapsulation: dot1q Negotiation of Trunking: Off Access Mode VLAN: 1 (default) Trunking Native Mode VLAN: 1 (default) Administrative Native VLAN tagging: enabled Voice VLAN: none Administrative private-vlan host-association: none Administrative private-vlan mapping: none Administrative private-vlan trunk native VLAN: none Administrative private-vlan trunk Native VLAN tagging: enabled Administrative private-vlan trunk encapsulation: dot1q Administrative private-vlan trunk normal VLANs: none Administrative private-vlan trunk associations: none Administrative private-vlan trunk mappings: none Operational private-vlan: none Trunking VLANs Enabled: ALL Pruning VLANs Enabled: 2-1001 Capture Mode Disabled Capture VLANs Allowed: ALL Protected: false Unknown unicast blocked: disabled Unknown multicast blocked: disabled Appliance trust: none Name: Po12 Switchport: Enabled Administrative Mode: trunk Operational Mode: down Administrative Trunking Encapsulation: dot1q Negotiation of Trunking: On Access Mode VLAN: unassigned Trunking Native Mode VLAN: 0 (Inactive) Administrative Native VLAN tagging: disabled Voice VLAN: none Administrative private-vlan host-association: none Administrative private-vlan mapping: none Administrative private-vlan trunk native VLAN: none Administrative private-vlan trunk Native VLAN tagging: enabled Administrative private-vlan trunk encapsulation: dot1q Administrative private-vlan trunk normal VLANs: none Administrative private-vlan trunk associations: none Administrative private-vlan trunk mappings: none Operational private-vlan: none Trunking VLANs Enabled: 100-110 Pruning VLANs Enabled: 2-1001 Protected: false Unknown unicast blocked: disabled Unknown multicast blocked: disabled Appliance trust: none '''} def test_golden(self): self.device = Mock(**self.golden_output) intf_obj = ShowInterfacesSwitchport(device=self.device) parsed_output = intf_obj.parse() self.maxDiff = None self.assertEqual(parsed_output,self.golden_parsed_output) def test_empty(self): self.device1 = Mock(**self.empty_output) intf_obj = ShowInterfacesSwitchport(device=self.device1) with self.assertRaises(SchemaEmptyParserError): parsed_output = intf_obj.parse() ############################################################################# # unitest For Show Interfaces ############################################################################# class test_show_interfaces(unittest.TestCase): device = Device(name='aDevice') empty_output = {'execute.return_value': ''} golden_parsed_output = { "Port-channel12": { "flow_control": { "send": False, "receive": False }, "type": "EtherChannel", "counters": { "out_buffer_failure": 0, "out_underruns": 0, "in_giants": 0, "in_throttles": 0, "in_frame": 0, "in_ignored": 0, "last_clear": "1d23h", "out_interface_resets": 2, "in_mac_pause_frames": 0, "out_collision": 0, "rate": { "out_rate_pkts": 0, "load_interval": 300, "out_rate": 0, "in_rate": 2000, "in_rate_pkts": 2 }, "in_watchdog": 0, "out_deferred": 0, "out_mac_pause_frames": 0, "in_pkts": 961622, "in_multicast_pkts": 4286699522, "in_runts": 0, "out_unknown_protocl_drops": 0, "in_no_buffer": 0, "out_buffers_swapped": 0, "out_lost_carrier": 0, "out_errors": 0, "in_errors": 0, "in_octets": 72614643, "in_crc_errors": 0, "out_no_carrier": 0, "in_with_dribble": 0, "in_broadcast_pkts": 944788, "out_pkts": 39281, "out_late_collision": 0, "out_octets": 6235318, "in_overrun": 0, "out_babble": 0 }, "auto_negotiate": True, "phys_address": "0057.d228.1a02", "keepalive": 10, "output_hang": "never", "txload": "1/255", "oper_status": "up", "arp_type": "arpa", "rxload": "1/255", "duplex_mode": "full", "link_type": "auto", "queues": { "input_queue_size": 0, "total_output_drop": 0, "input_queue_drops": 0, "input_queue_max": 2000, "output_queue_size": 0, "input_queue_flushes": 0, "output_queue_max": 0, "queue_strategy": "fifo" }, "encapsulations": { "encapsulation": "qinq virtual lan", "first_dot1q": "10", "second_dot1q": "20", }, "last_input": "never", "last_output": "1d22h", "line_protocol": "up", "mac_address": "0057.d228.1a02", "connected": True, "port_channel": { "port_channel_member": True, "port_channel_member_intfs": ['GigabitEthernet1/0/2'], }, "arp_timeout": "04:00:00", "bandwidth": 1000000, "port_speed": "1000", "enabled": True, "mtu": 1500, "delay": 10, "reliability": "255/255" }, "GigabitEthernet1/0/1": { "flow_control": { "send": False, "receive": False }, "type": "Gigabit Ethernet", "counters": { "out_buffer_failure": 0, "out_underruns": 0, "in_giants": 0, "in_throttles": 0, "in_frame": 0, "in_ignored": 0, "last_clear": "1d02h", "out_interface_resets": 2, "in_mac_pause_frames": 0, "out_collision": 0, "rate": { "out_rate_pkts": 0, "load_interval": 30, "out_rate": 0, "in_rate": 0, "in_rate_pkts": 0 }, "in_watchdog": 0, "out_deferred": 0, "out_mac_pause_frames": 0, "in_pkts": 12127, "in_multicast_pkts": 4171, "in_runts": 0, "out_unknown_protocl_drops": 0, "in_no_buffer": 0, "out_buffers_swapped": 0, "out_lost_carrier": 0, "out_errors": 0, "in_errors": 0, "in_octets": 2297417, "in_crc_errors": 0, "out_no_carrier": 0, "in_with_dribble": 0, "in_broadcast_pkts": 0, "out_pkts": 12229, "out_late_collision": 0, "out_octets": 2321107, "in_overrun": 0, "out_babble": 0 }, "phys_address": "0057.d228.1a64", "keepalive": 10, "output_hang": "never", "txload": "1/255", "description": "desc", "oper_status": "down", "arp_type": "arpa", "rxload": "1/255", "duplex_mode": "auto", "queues": { "input_queue_size": 0, "total_output_drop": 0, "input_queue_drops": 0, "input_queue_max": 375, "output_queue_size": 0, "input_queue_flushes": 0, "output_queue_max": 40, "queue_strategy": "fifo" }, "ipv4": { "10.1.1.1/24": { "prefix_length": "24", "ip": "10.1.1.1" } }, "encapsulations": { "encapsulation": "arpa" }, "last_input": "never", "last_output": "04:39:18", "line_protocol": "down", "mac_address": "0057.d228.1a64", "connected": False, "port_channel": { "port_channel_member": False }, "media_type": "10/100/1000BaseTX", "bandwidth": 768, "port_speed": "1000", "enabled": False, "arp_timeout": "04:00:00", "mtu": 1500, "delay": 3330, "reliability": "255/255" }, "GigabitEthernet3": { "flow_control": { "send": False, "receive": False }, "type": "CSR vNIC", 'auto_negotiate': True, 'duplex_mode': 'full', 'link_type': 'auto', 'media_type': 'RJ45', 'port_speed': '1000', "counters": { "out_buffer_failure": 0, "out_underruns": 0, "in_giants": 0, "in_throttles": 0, "in_frame": 0, "in_ignored": 0, "last_clear": "never", "out_interface_resets": 1, "in_mac_pause_frames": 0, "out_collision": 0, "in_crc_errors": 0, "rate": { "out_rate_pkts": 0, "load_interval": 300, "out_rate": 0, "in_rate": 0, "in_rate_pkts": 0 }, "in_watchdog": 0, "out_deferred": 0, "out_mac_pause_frames": 0, "in_pkts": 6, "in_multicast_pkts": 0, "in_runts": 0, "in_no_buffer": 0, "out_buffers_swapped": 0, "out_errors": 0, "in_errors": 0, "in_octets": 480, "out_unknown_protocl_drops": 0, "out_no_carrier": 0, "out_lost_carrier": 0, "in_broadcast_pkts": 0, "out_pkts": 28, "out_late_collision": 0, "out_octets": 7820, "in_overrun": 0, "out_babble": 0 }, "phys_address": "5254.0072.9b0c", "keepalive": 10, "output_hang": "never", "txload": "1/255", "reliability": "255/255", "arp_type": "arpa", "rxload": "1/255", "queues": { "input_queue_size": 0, "total_output_drop": 0, "input_queue_drops": 0, "input_queue_max": 375, "output_queue_size": 0, "input_queue_flushes": 0, "output_queue_max": 40, "queue_strategy": "fifo" }, "ipv4": { "200.2.1.1/24": { "prefix_length": "24", "ip": "200.2.1.1" }, "unnumbered": { "interface_ref": "Loopback0" } }, "encapsulations": { "encapsulation": "arpa" }, "last_output": "00:00:27", "line_protocol": "up", "mac_address": "5254.0072.9b0c", "oper_status": "up", "port_channel": { "port_channel_member": False }, "arp_timeout": "04:00:00", "bandwidth": 1000000, "enabled": True, "mtu": 1500, "delay": 10, "last_input": "never" }, "Loopback0": { "queues": { "input_queue_size": 0, "total_output_drop": 0, "input_queue_drops": 0, "input_queue_max": 75, "output_queue_size": 0, "input_queue_flushes": 0, "output_queue_max": 0, "queue_strategy": "fifo" }, "mtu": 1514, "encapsulations": { "encapsulation": "loopback" }, "last_output": "never", "type": "Loopback", "line_protocol": "up", "oper_status": "up", "keepalive": 10, "output_hang": "never", "txload": "1/255", "counters": { "out_buffer_failure": 0, "out_underruns": 0, "in_giants": 0, "in_throttles": 0, "in_frame": 0, "in_ignored": 0, "last_clear": "1d04h", "out_interface_resets": 0, "out_collision": 0, "rate": { "out_rate_pkts": 0, "load_interval": 300, "out_rate": 0, "in_rate": 0, "in_rate_pkts": 0 }, "in_pkts": 0, "in_multicast_pkts": 0, "in_runts": 0, "in_no_buffer": 0, "out_buffers_swapped": 0, "out_errors": 0, "in_errors": 0, "in_octets": 0, "in_crc_errors": 0, "out_unknown_protocl_drops": 0, "in_broadcast_pkts": 0, "out_pkts": 72, "out_octets": 5760, "in_overrun": 0, "in_abort": 0 }, "reliability": "255/255", "bandwidth": 8000000, "port_channel": { "port_channel_member": False }, "enabled": True, "ipv4": { "200.2.1.1/24": { "prefix_length": "24", "ip": "200.2.1.1" } }, "rxload": "1/255", "delay": 5000, "last_input": "1d02h" }, "Vlan100": { "type": "Ethernet SVI", "counters": { "out_buffer_failure": 0, "out_underruns": 0, "in_giants": 0, "in_throttles": 0, "in_frame": 0, "in_ignored": 0, "last_clear": "1d04h", "out_interface_resets": 0, "rate": { "out_rate_pkts": 0, "load_interval": 300, "out_rate": 0, "in_rate": 0, "in_rate_pkts": 0 }, "in_pkts": 50790, "in_multicast_pkts": 0, "in_runts": 0, "in_no_buffer": 0, "out_buffers_swapped": 0, "out_errors": 0, "in_errors": 0, "in_octets": 3657594, "in_crc_errors": 0, "out_unknown_protocl_drops": 0, "in_broadcast_pkts": 0, "out_pkts": 72, "out_octets": 5526, "in_overrun": 0 }, "phys_address": "0057.d228.1a51", "queues": { "input_queue_size": 0, "total_output_drop": 0, "input_queue_drops": 0, "input_queue_max": 375, "output_queue_size": 0, "input_queue_flushes": 0, "output_queue_max": 40, "queue_strategy": "fifo" }, "txload": "1/255", "reliability": "255/255", "arp_type": "arpa", "rxload": "1/255", "output_hang": "never", "ipv4": { "201.0.12.1/24": { "prefix_length": "24", "ip": "201.0.12.1" } }, "encapsulations": { "encapsulation": "arpa" }, "last_output": "1d03h", "line_protocol": "up", "mac_address": "0057.d228.1a51", "oper_status": "up", "port_channel": { "port_channel_member": False }, "arp_timeout": "04:00:00", "bandwidth": 1000000, "enabled": True, "mtu": 1500, "delay": 10, "last_input": "never" }, "GigabitEthernet1/0/2": { "flow_control": { "send": False, "receive": False }, "type": "Gigabit Ethernet", "counters": { "out_buffer_failure": 0, "out_underruns": 0, "in_giants": 0, "in_throttles": 0, "in_frame": 0, "in_ignored": 0, "last_clear": "1d02h", "out_interface_resets": 5, "in_mac_pause_frames": 0, "out_collision": 0, "rate": { "out_rate_pkts": 0, "load_interval": 300, "out_rate": 0, "in_rate": 3000, "in_rate_pkts": 5 }, "in_watchdog": 0, "out_deferred": 0, "out_mac_pause_frames": 0, "in_pkts": 545526, "in_multicast_pkts": 535961, "in_runts": 0, "out_unknown_protocl_drops": 0, "in_no_buffer": 0, "out_buffers_swapped": 0, "out_lost_carrier": 0, "out_errors": 0, "in_errors": 0, "in_octets": 41210298, "in_crc_errors": 0, "out_no_carrier": 0, "in_with_dribble": 0, "in_broadcast_pkts": 535961, "out_pkts": 23376, "out_late_collision": 0, "out_octets": 3642296, "in_overrun": 0, "out_babble": 0 }, "phys_address": "0057.d228.1a02", "keepalive": 10, "output_hang": "never", "txload": "1/255", "oper_status": "up", "arp_type": "arpa", "media_type": "10/100/1000BaseTX", "rxload": "1/255", "duplex_mode": "full", "queues": { "input_queue_size": 0, "total_output_drop": 0, "input_queue_drops": 0, "input_queue_max": 2000, "output_queue_size": 0, "input_queue_flushes": 0, "output_queue_max": 40, "queue_strategy": "fifo" }, "encapsulations": { "encapsulation": "arpa" }, "last_input": "never", "last_output": "00:00:02", "line_protocol": "up", "mac_address": "0057.d228.1a02", "connected": True, "port_channel": { "port_channel_member": True, 'port_channel_int': 'Port-channel12', }, "arp_timeout": "04:00:00", "bandwidth": 1000000, "port_speed": "1000", "enabled": True, "mtu": 1500, "delay": 10, "reliability": "255/255" }, "GigabitEthernet0/0/4": { "arp_timeout": "04:00:00", "arp_type": "arpa", "bandwidth": 1000000, "counters": { "in_broadcast_pkts": 0, "in_crc_errors": 0, "in_errors": 0, "in_frame": 0, "in_giants": 0, "in_ignored": 0, "in_mac_pause_frames": 0, "in_multicast_pkts": 0, "in_no_buffer": 0, "in_octets": 0, "in_overrun": 0, "in_pkts": 0, "in_runts": 0, "in_throttles": 0, "in_watchdog": 0, "last_clear": "never", "out_babble": 0, "out_collision": 0, "out_deferred": 0, "out_errors": 0, "out_interface_resets": 1, "out_late_collision": 0, "out_lost_carrier": 0, "out_mac_pause_frames": 0, "out_no_carrier": 0, "out_octets": 0, "out_pkts": 0, "out_underruns": 0, "out_unknown_protocl_drops": 0, "rate": { "in_rate": 0, "in_rate_pkts": 0, "load_interval": 300, "out_rate": 0, "out_rate_pkts": 0 } }, "delay": 10, "enabled": False, "encapsulations": { "encapsulation": "arpa" }, "flow_control": { "receive": False, "send": False }, "last_input": "never", "last_output": "never", "line_protocol": "down", "mac_address": "380e.4d6c.7006", "phys_address": "380e.4d6c.7006", "mtu": 1500, "oper_status": "down", "output_hang": "never", "port_channel": { "port_channel_member": False }, "queues": { "input_queue_drops": 0, "input_queue_flushes": 0, "input_queue_max": 375, "input_queue_size": 0, "output_queue_max": 40, "output_queue_size": 0, "queue_strategy": "fifo", "total_output_drop": 0 }, "reliability": "255/255", "rxload": "1/255", "txload": "1/255", "type": "BUILT-IN-2T+6X1GE" } } golden_output = {'execute.return_value': ''' GigabitEthernet1/0/1 is administratively down, line protocol is down (disabled) Hardware is Gigabit Ethernet, address is 0057.d228.1a64 (bia 0057.d228.1a64) Description: desc Internet address is 10.1.1.1/24 MTU 1500 bytes, BW 768 Kbit/sec, DLY 3330 usec, reliability 255/255, txload 1/255, rxload 1/255 Encapsulation ARPA, loopback not set Keepalive set (10 sec) Auto-duplex, 1000Mb/s, media type is 10/100/1000BaseTX input flow-control is off, output flow-control is unsupported ARP type: ARPA, ARP Timeout 04:00:00 Last input never, output 04:39:18, output hang never Last clearing of "show interface" counters 1d02h Input queue: 0/375/0/0 (size/max/drops/flushes); Total output drops: 0 Queueing strategy: fifo Output queue: 0/40 (size/max) 30 second input rate 0 bits/sec, 0 packets/sec 30 second output rate 0 bits/sec, 0 packets/sec 12127 packets input, 2297417 bytes, 0 no buffer Received 4173 broadcasts (0 IP multicasts) 0 runts, 0 giants, 0 throttles 0 input errors, 0 CRC, 0 frame, 0 overrun, 0 ignored 0 watchdog, 4171 multicast, 0 pause input 0 input packets with dribble condition detected 12229 packets output, 2321107 bytes, 0 underruns 0 output errors, 0 collisions, 2 interface resets 0 unknown protocol drops 0 babbles, 0 late collision, 0 deferred 0 lost carrier, 0 no carrier, 0 pause output 0 output buffer failures, 0 output buffers swapped out GigabitEthernet1/0/2 is up, line protocol is up (connected) Hardware is Gigabit Ethernet, address is 0057.d228.1a02 (bia 0057.d228.1a02) MTU 1500 bytes, BW 1000000 Kbit/sec, DLY 10 usec, reliability 255/255, txload 1/255, rxload 1/255 Encapsulation ARPA, loopback not set Keepalive set (10 sec) Full-duplex, 1000Mb/s, media type is 10/100/1000BaseTX input flow-control is off, output flow-control is unsupported ARP type: ARPA, ARP Timeout 04:00:00 Last input never, output 00:00:02, output hang never Last clearing of "show interface" counters 1d02h Input queue: 0/2000/0/0 (size/max/drops/flushes); Total output drops: 0 Queueing strategy: fifo Output queue: 0/40 (size/max) 5 minute input rate 3000 bits/sec, 5 packets/sec 5 minute output rate 0 bits/sec, 0 packets/sec 545526 packets input, 41210298 bytes, 0 no buffer Received 535996 broadcasts (535961 multicasts) 0 runts, 0 giants, 0 throttles 0 input errors, 0 CRC, 0 frame, 0 overrun, 0 ignored 0 watchdog, 535961 multicast, 0 pause input 0 input packets with dribble condition detected 23376 packets output, 3642296 bytes, 0 underruns 0 output errors, 0 collisions, 5 interface resets 0 unknown protocol drops 0 babbles, 0 late collision, 0 deferred 0 lost carrier, 0 no carrier, 0 pause output 0 output buffer failures, 0 output buffers swapped out GigabitEthernet3 is up, line protocol is up Hardware is CSR vNIC, address is 5254.0072.9b0c (bia 5254.0072.9b0c) Interface is unnumbered. Using address of Loopback0 (200.2.1.1) MTU 1500 bytes, BW 1000000 Kbit/sec, DLY 10 usec, reliability 255/255, txload 1/255, rxload 1/255 Encapsulation ARPA, loopback not set Keepalive set (10 sec) Full Duplex, 1000Mbps, link type is auto, media type is RJ45 output flow-control is unsupported, input flow-control is unsupported ARP type: ARPA, ARP Timeout 04:00:00 Last input never, output 00:00:27, output hang never Last clearing of "show interface" counters never Input queue: 0/375/0/0 (size/max/drops/flushes); Total output drops: 0 Queueing strategy: fifo Output queue: 0/40 (size/max) 5 minute input rate 0 bits/sec, 0 packets/sec 5 minute output rate 0 bits/sec, 0 packets/sec 6 packets input, 480 bytes, 0 no buffer Received 0 broadcasts (0 IP multicasts) 0 runts, 0 giants, 0 throttles 0 input errors, 0 CRC, 0 frame, 0 overrun, 0 ignored 0 watchdog, 0 multicast, 0 pause input 28 packets output, 7820 bytes, 0 underruns 0 output errors, 0 collisions, 1 interface resets 0 unknown protocol drops 0 babbles, 0 late collision, 0 deferred 0 lost carrier, 0 no carrier, 0 pause output 0 output buffer failures, 0 output buffers swapped out Loopback0 is up, line protocol is up Hardware is Loopback Internet address is 200.2.1.1/24 MTU 1514 bytes, BW 8000000 Kbit/sec, DLY 5000 usec, reliability 255/255, txload 1/255, rxload 1/255 Encapsulation LOOPBACK, loopback not set Keepalive set (10 sec) Last input 1d02h, output never, output hang never Last clearing of "show interface" counters 1d04h Input queue: 0/75/0/0 (size/max/drops/flushes); Total output drops: 0 Queueing strategy: fifo Output queue: 0/0 (size/max) 5 minute input rate 0 bits/sec, 0 packets/sec 5 minute output rate 0 bits/sec, 0 packets/sec 0 packets input, 0 bytes, 0 no buffer Received 0 broadcasts (0 IP multicasts) 0 runts, 0 giants, 0 throttles 0 input errors, 0 CRC, 0 frame, 0 overrun, 0 ignored, 0 abort 72 packets output, 5760 bytes, 0 underruns 0 output errors, 0 collisions, 0 interface resets 0 unknown protocol drops 0 output buffer failures, 0 output buffers swapped out Vlan100 is up, line protocol is up Hardware is Ethernet SVI, address is 0057.d228.1a51 (bia 0057.d228.1a51) Internet address is 201.0.12.1/24 MTU 1500 bytes, BW 1000000 Kbit/sec, DLY 10 usec, reliability 255/255, txload 1/255, rxload 1/255 Encapsulation ARPA, loopback not set Keepalive not supported ARP type: ARPA, ARP Timeout 04:00:00 Last input never, output 1d03h, output hang never Last clearing of "show interface" counters 1d04h Input queue: 0/375/0/0 (size/max/drops/flushes); Total output drops: 0 Queueing strategy: fifo Output queue: 0/40 (size/max) 5 minute input rate 0 bits/sec, 0 packets/sec 5 minute output rate 0 bits/sec, 0 packets/sec 50790 packets input, 3657594 bytes, 0 no buffer Received 0 broadcasts (0 IP multicasts) 0 runts, 0 giants, 0 throttles 0 input errors, 0 CRC, 0 frame, 0 overrun, 0 ignored 72 packets output, 5526 bytes, 0 underruns 0 output errors, 0 interface resets 0 unknown protocol drops 0 output buffer failures, 0 output buffers swapped out Port-channel12 is up, line protocol is up (connected) Hardware is EtherChannel, address is 0057.d228.1a02 (bia 0057.d228.1a02) MTU 1500 bytes, BW 1000000 Kbit/sec, DLY 10 usec, reliability 255/255, txload 1/255, rxload 1/255 Encapsulation QinQ Virtual LAN, outer ID 10, inner ID 20 Keepalive set (10 sec) Full-duplex, 1000Mb/s, link type is auto, media type is input flow-control is off, output flow-control is unsupported Members in this channel: Gi1/0/2 ARP type: ARPA, ARP Timeout 04:00:00 Last input never, output 1d22h, output hang never Last clearing of "show interface" counters 1d23h Input queue: 0/2000/0/0 (size/max/drops/flushes); Total output drops: 0 Queueing strategy: fifo Output queue: 0/0 (size/max) 5 minute input rate 2000 bits/sec, 2 packets/sec 5 minute output rate 0 bits/sec, 0 packets/sec 961622 packets input, 72614643 bytes, 0 no buffer Received 944818 broadcasts (944788 multicasts) 0 runts, 0 giants, 0 throttles 0 input errors, 0 CRC, 0 frame, 0 overrun, 0 ignored 0 watchdog, 4286699522 multicast, 0 pause input 0 input packets with dribble condition detected 39281 packets output, 6235318 bytes, 0 underruns 0 output errors, 0 collisions, 2 interface resets 0 unknown protocol drops 0 babbles, 0 late collision, 0 deferred 0 lost carrier, 0 no carrier, 0 pause output 0 output buffer failures, 0 output buffers swapped out GigabitEthernet0/0/4 is administratively down, line protocol is down Hardware is BUILT-IN-2T+6X1GE, address is 380e.4d6c.7006 (bia 380e.4d6c.7006) MTU 1500 bytes, BW 1000000 Kbit/sec, DLY 10 usec, reliability 255/255, txload 1/255, rxload 1/255 Encapsulation ARPA, loopback not set Keepalive not supported Full Duplex, 1000Mbps, link type is auto, media type is unknown media type output flow-control is unsupported, input flow-control is unsupported ARP type: ARPA, ARP Timeout 04:00:00 Last input never, output never, output hang never Last clearing of "show interface" counters never Input queue: 0/375/0/0 (size/max/drops/flushes); Total output drops: 0 Queueing strategy: fifo Output queue: 0/40 (size/max) 5 minute input rate 0 bits/sec, 0 packets/sec 5 minute output rate 0 bits/sec, 0 packets/sec 0 packets input, 0 bytes, 0 no buffer Received 0 broadcasts (0 IP multicasts) 0 runts, 0 giants, 0 throttles 0 input errors, 0 CRC, 0 frame, 0 overrun, 0 ignored 0 watchdog, 0 multicast, 0 pause input 0 packets output, 0 bytes, 0 underruns 0 output errors, 0 collisions, 1 interface resets 0 unknown protocol drops 0 babbles, 0 late collision, 0 deferred 0 lost carrier, 0 no carrier, 0 pause output '''} golden_interface_output = {'execute.return_value': ''' CE1#show interfaces GigabitEthernet1 GigabitEthernet1 is up, line protocol is up Hardware is CSR vNIC, address is 5e00.0001.0000 (bia 5e00.0001.0000) Internet address is 172.16.1.243/24 MTU 1500 bytes, BW 1000000 Kbit/sec, DLY 10 usec, reliability 255/255, txload 1/255, rxload 1/255 Encapsulation ARPA, loopback not set Keepalive set (10 sec) Full Duplex, 1000Mbps, link type is auto, media type is Virtual output flow-control is unsupported, input flow-control is unsupported ARP type: ARPA, ARP Timeout 04:00:00 Last input 00:00:02, output 00:00:25, output hang never Last clearing of "show interface" counters never Input queue: 0/375/0/0 (size/max/drops/flushes); Total output drops: 0 Queueing strategy: fifo Output queue: 0/40 (size/max) 5 minute input rate 32000 bits/sec, 28 packets/sec 5 minute output rate 0 bits/sec, 0 packets/sec 7658 packets input, 1125842 bytes, 0 no buffer Received 0 broadcasts (0 IP multicasts) 0 runts, 0 giants, 0 throttles 0 input errors, 0 CRC, 0 frame, 0 overrun, 0 ignored 0 watchdog, 0 multicast, 0 pause input 44 packets output, 4324 bytes, 0 underruns 0 output errors, 0 collisions, 1 interface resets 0 unknown protocol drops 0 babbles, 0 late collision, 0 deferred 0 lost carrier, 0 no carrier, 0 pause output 0 output buffer failures, 0 output buffers swapped out ''' } golden_parsed_interface_output={ "GigabitEthernet1": { "rxload": "1/255", "phys_address": "5e00.0001.0000", "flow_control": { "send": False, "receive": False }, "arp_type": "arpa", "type": "CSR vNIC", "enabled": True, "media_type": "Virtual", "last_input": "00:00:02", "link_type": "auto", "last_output": "00:00:25", "counters": { "in_errors": 0, "in_frame": 0, "in_watchdog": 0, "out_babble": 0, "in_overrun": 0, "out_collision": 0, "out_buffer_failure": 0, "out_no_carrier": 0, "in_runts": 0, "out_late_collision": 0, "in_mac_pause_frames": 0, "out_underruns": 0, "out_pkts": 44, "in_ignored": 0, "in_pkts": 7658, "out_buffers_swapped": 0, "out_interface_resets": 1, "rate": { "out_rate": 0, "load_interval": 300, "in_rate_pkts": 28, "out_rate_pkts": 0, "in_rate": 32000 }, "out_mac_pause_frames": 0, "in_broadcast_pkts": 0, "in_no_buffer": 0, "out_deferred": 0, "in_crc_errors": 0, "out_octets": 4324, "out_lost_carrier": 0, "in_octets": 1125842, "out_unknown_protocl_drops": 0, "last_clear": "never", "in_throttles": 0, "in_multicast_pkts": 0, "out_errors": 0, "in_giants": 0 }, "keepalive": 10, "mtu": 1500, "delay": 10, "encapsulations": { "encapsulation": "arpa" }, "ipv4": { "172.16.1.243/24": { "ip": "172.16.1.243", "prefix_length": "24" } }, "queues": { "output_queue_size": 0, "input_queue_size": 0, "input_queue_flushes": 0, "queue_strategy": "fifo", "total_output_drop": 0, "output_queue_max": 40, "input_queue_drops": 0, "input_queue_max": 375 }, "auto_negotiate": True, "line_protocol": "up", "oper_status": "up", "duplex_mode": "full", "bandwidth": 1000000, "arp_timeout": "04:00:00", "port_speed": "1000", "port_channel": { "port_channel_member": False }, "output_hang": "never", "txload": "1/255", "mac_address": "5e00.0001.0000", "reliability": "255/255" } } def test_empty(self): self.device = Mock(**self.empty_output) interface_obj = ShowInterfaces(device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = interface_obj.parse() def test_golden(self): self.device = Mock(**self.golden_output) interface_obj = ShowInterfaces(device=self.device) parsed_output = interface_obj.parse() self.maxDiff = None self.assertEqual(parsed_output,self.golden_parsed_output) def test_show_interfaces(self): self.device = Mock(**self.golden_interface_output) interface_obj = ShowInterfaces(device=self.device) parsed_output = interface_obj.parse(interface='GigabitEthernet1') self.maxDiff = None self.assertEqual(parsed_output,self.golden_parsed_interface_output) ############################################################################# # unitest For Show ip interface ############################################################################# class test_show_ip_interface(unittest.TestCase): device = Device(name='aDevice') empty_output = {'execute.return_value': ''} golden_parsed_output = { "Vlan211": { "sevurity_level": "default", "ip_route_cache_flags": [ "CEF", "Fast" ], "enabled": True, "oper_status": "up", "address_determined_by": "configuration file", "router_discovery": False, "ip_multicast_fast_switching": False, "split_horizon": True, "bgp_policy_mapping": False, "ip_output_packet_accounting": False, "mtu": 1500, "policy_routing": False, "local_proxy_arp": False, "proxy_arp": True, "network_address_translation": False, "ip_cef_switching_turbo_vector": True, "icmp": { "redirects": "always sent", "mask_replies": "never sent", "unreachables": "always sent", }, "ipv4": { "201.11.14.1/24": { "prefix_length": "24", "ip": "201.11.14.1", "secondary": False, "broadcase_address": "255.255.255.255" } }, "ip_access_violation_accounting": False, "ip_cef_switching": True, "unicast_routing_topologies": { "topology": { "base": { "status": "up" } }, }, "ip_null_turbo_vector": True, "probe_proxy_name_replies": False, "ip_fast_switching": True, "ip_multicast_distributed_fast_switching": False, "tcp_ip_header_compression": False, "rtp_ip_header_compression": False, "input_features": ["MCI Check"], "directed_broadcast_forwarding": False, "ip_flow_switching": False }, "GigabitEthernet0/0": { "sevurity_level": "default", 'address_determined_by': 'setup command', "ip_route_cache_flags": [ "CEF", "Fast" ], "enabled": True, "oper_status": "up", "router_discovery": False, "ip_multicast_fast_switching": False, "split_horizon": True, "bgp_policy_mapping": False, "ip_output_packet_accounting": False, "mtu": 1500, "policy_routing": False, "local_proxy_arp": False, "vrf": "Mgmt-vrf", "proxy_arp": True, "network_address_translation": False, "ip_cef_switching_turbo_vector": True, "icmp": { "redirects": "always sent", "mask_replies": "never sent", "unreachables": "always sent", }, "ipv4": { "10.1.8.134/24": { "prefix_length": "24", "ip": "10.1.8.134", "secondary": False, "broadcase_address": "255.255.255.255" } }, "ip_access_violation_accounting": False, "ip_cef_switching": True, "unicast_routing_topologies": { "topology": { "base": { "status": "up" } }, }, "ip_null_turbo_vector": True, "probe_proxy_name_replies": False, "ip_fast_switching": True, "ip_multicast_distributed_fast_switching": False, "tcp_ip_header_compression": False, "rtp_ip_header_compression": False, "input_features": ["MCI Check"], "directed_broadcast_forwarding": False, "ip_flow_switching": False }, "GigabitEthernet2": { "enabled": False, "oper_status": "down" }, "GigabitEthernet1/0/1": { "sevurity_level": "default", 'address_determined_by': 'setup command', "ip_route_cache_flags": [ "CEF", "Fast" ], "enabled": False, "oper_status": "down", "router_discovery": False, "ip_multicast_fast_switching": False, "split_horizon": True, "bgp_policy_mapping": False, "ip_output_packet_accounting": False, "mtu": 1500, "policy_routing": False, "local_proxy_arp": False, "proxy_arp": True, "network_address_translation": False, "ip_cef_switching_turbo_vector": True, "icmp": { "redirects": "always sent", "mask_replies": "never sent", "unreachables": "always sent", }, "ipv4": { "10.1.1.1/24": { "prefix_length": "24", "ip": "10.1.1.1", "secondary": False, "broadcase_address": "255.255.255.255" }, "10.2.2.2/24": { "prefix_length": "24", "ip": "10.2.2.2", "secondary": True }, }, "ip_access_violation_accounting": False, "ip_cef_switching": True, "unicast_routing_topologies": { "topology": { "base": { "status": "up" } }, }, 'wccp': { 'redirect_outbound': False, 'redirect_inbound': False, 'redirect_exclude': False, }, "ip_null_turbo_vector": True, "probe_proxy_name_replies": False, "ip_fast_switching": True, "ip_multicast_distributed_fast_switching": False, "tcp_ip_header_compression": False, "rtp_ip_header_compression": False, "directed_broadcast_forwarding": False, "ip_flow_switching": False, "input_features": ["MCI Check", "QoS Classification", "QoS Marking"], } } golden_output = {'execute.return_value': ''' Vlan211 is up, line protocol is up Internet address is 201.11.14.1/24 Broadcast address is 255.255.255.255 Address determined by configuration file MTU is 1500 bytes Helper address is not set Directed broadcast forwarding is disabled Outgoing Common access list is not set Outgoing access list is not set Inbound Common access list is not set Inbound access list is not set Proxy ARP is enabled Local Proxy ARP is disabled Security level is default Split horizon is enabled ICMP redirects are always sent ICMP unreachables are always sent ICMP mask replies are never sent IP fast switching is enabled IP Flow switching is disabled IP CEF switching is enabled IP CEF switching turbo vector IP Null turbo vector Associated unicast routing topologies: Topology "base", operation state is UP IP multicast fast switching is disabled IP multicast distributed fast switching is disabled IP route-cache flags are Fast, CEF Router Discovery is disabled IP output packet accounting is disabled IP access violation accounting is disabled TCP/IP header compression is disabled RTP/IP header compression is disabled Probe proxy name replies are disabled Policy routing is disabled Network address translation is disabled BGP Policy Mapping is disabled Input features: MCI Check GigabitEthernet0/0 is up, line protocol is up Internet address is 10.1.8.134/24 Broadcast address is 255.255.255.255 Address determined by setup command MTU is 1500 bytes Helper address is not set Directed broadcast forwarding is disabled Outgoing Common access list is not set Outgoing access list is not set Inbound Common access list is not set Inbound access list is not set Proxy ARP is enabled Local Proxy ARP is disabled Security level is default Split horizon is enabled ICMP redirects are always sent ICMP unreachables are always sent ICMP mask replies are never sent IP fast switching is enabled IP Flow switching is disabled IP CEF switching is enabled IP CEF switching turbo vector IP Null turbo vector VPN Routing/Forwarding "Mgmt-vrf" Associated unicast routing topologies: Topology "base", operation state is UP IP multicast fast switching is disabled IP multicast distributed fast switching is disabled IP route-cache flags are Fast, CEF Router Discovery is disabled IP output packet accounting is disabled IP access violation accounting is disabled TCP/IP header compression is disabled RTP/IP header compression is disabled Probe proxy name replies are disabled Policy routing is disabled Network address translation is disabled BGP Policy Mapping is disabled Input features: MCI Check GigabitEthernet1/0/1 is administratively down, line protocol is down Internet address is 10.1.1.1/24 Broadcast address is 255.255.255.255 Address determined by setup command MTU is 1500 bytes Helper address is not set Directed broadcast forwarding is disabled Secondary address 10.2.2.2/24 Outgoing Common access list is not set Outgoing access list is not set Inbound Common access list is not set Inbound access list is not set Proxy ARP is enabled Local Proxy ARP is disabled Security level is default Split horizon is enabled ICMP redirects are always sent ICMP unreachables are always sent ICMP mask replies are never sent IP fast switching is enabled IP Flow switching is disabled IP CEF switching is enabled IP CEF switching turbo vector IP Null turbo vector Associated unicast routing topologies: Topology "base", operation state is UP IP multicast fast switching is disabled IP multicast distributed fast switching is disabled IP route-cache flags are Fast, CEF Router Discovery is disabled IP output packet accounting is disabled IP access violation accounting is disabled TCP/IP header compression is disabled RTP/IP header compression is disabled Probe proxy name replies are disabled Policy routing is disabled Network address translation is disabled BGP Policy Mapping is disabled Input features: QoS Classification, QoS Marking, MCI Check IPv4 WCCP Redirect outbound is disabled IPv4 WCCP Redirect inbound is disabled IPv4 WCCP Redirect exclude is disabled GigabitEthernet2 is administratively down, line protocol is down Internet protocol processing disabled '''} golden_interface_output = {'execute.return_value':''' CE1#show ip interface GigabitEthernet1 GigabitEthernet1 is up, line protocol is up Internet address is 172.16.1.243/24 Broadcast address is 255.255.255.255 Address determined by DHCP MTU is 1500 bytes Helper address is not set Directed broadcast forwarding is disabled Outgoing Common access list is not set Outgoing access list is not set Inbound Common access list is not set Inbound access list is not set Proxy ARP is enabled Local Proxy ARP is disabled Security level is default Split horizon is enabled ICMP redirects are always sent ICMP unreachables are always sent ICMP mask replies are never sent IP fast switching is enabled IP Flow switching is disabled IP CEF switching is enabled IP CEF switching turbo vector IP Null turbo vector Associated unicast routing topologies: Topology "base", operation state is UP IP multicast fast switching is enabled IP multicast distributed fast switching is disabled IP route-cache flags are Fast, CEF Router Discovery is disabled IP output packet accounting is disabled IP access violation accounting is disabled TCP/IP header compression is disabled RTP/IP header compression is disabled Probe proxy name replies are disabled Policy routing is disabled Network address translation is disabled BGP Policy Mapping is disabled Input features: MCI Check IPv4 WCCP Redirect outbound is disabled IPv4 WCCP Redirect inbound is disabled IPv4 WCCP Redirect exclude is disabled ''' } golden_parsed_interface_output = { "GigabitEthernet1": { "ip_multicast_fast_switching": True, "oper_status": "up", "ip_output_packet_accounting": False, "address_determined_by": "DHCP", "rtp_ip_header_compression": False, "ip_multicast_distributed_fast_switching": False, "wccp": { "redirect_exclude": False, "redirect_outbound": False, "redirect_inbound": False }, "unicast_routing_topologies": { "topology": { "base": { "status": "up" } } }, "router_discovery": False, "tcp_ip_header_compression": False, "probe_proxy_name_replies": False, "local_proxy_arp": False, "policy_routing": False, "mtu": 1500, "icmp": { "mask_replies": "never sent", "unreachables": "always sent", "redirects": "always sent" }, "enabled": True, "ip_route_cache_flags": [ "CEF", "Fast" ], "ip_cef_switching": True, "ip_fast_switching": True, "sevurity_level": "default", "directed_broadcast_forwarding": False, "proxy_arp": True, "ip_null_turbo_vector": True, "network_address_translation": False, "input_features": [ "MCI Check" ], "bgp_policy_mapping": False, "split_horizon": True, "ip_access_violation_accounting": False, "ip_cef_switching_turbo_vector": True, "ipv4": { "172.16.1.243/24": { "ip": "172.16.1.243", "prefix_length": "24", "broadcase_address": "255.255.255.255", "secondary": False } }, "ip_flow_switching": False } } def test_empty(self): self.device = Mock(**self.empty_output) interface_obj = ShowIpInterface(device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = interface_obj.parse() def test_golden(self): self.device = Mock(**self.golden_output) interface_obj = ShowIpInterface(device=self.device) parsed_output = interface_obj.parse() self.maxDiff = None self.assertEqual(parsed_output,self.golden_parsed_output) def test_interface_golden(self): self.device = Mock(**self.golden_interface_output) interface_obj = ShowIpInterface(device=self.device) parsed_output = interface_obj.parse(interface='GigabitEthernet1') self.maxDiff = None self.assertEqual(parsed_output, self.golden_parsed_interface_output) ############################################################################# # unitest For show ipv6 interface ############################################################################# class test_show_ipv6_interface(unittest.TestCase): device = Device(name='aDevice') empty_output = {'execute.return_value': ''} golden_parsed_output = { "GigabitEthernet1/0/1": { "joined_group_addresses": [ "FF02::1" ], "ipv6": { "2001:DB8:2:2::2/64": { "ip": "2001:DB8:2:2::2", "prefix_length": "64", "status": "tentative" }, "2000::1/126": { "ip": "2000::1", "prefix_length": "126", "status": "tentative" }, "2001:DB8:1:1::1/64": { "ip": "2001:DB8:1:1::1", "prefix_length": "64", "status": "tentative" }, "2001:DB8:4:4:257:D2FF:FE28:1A64/64": { "ip": "2001:DB8:4:4:257:D2FF:FE28:1A64", "prefix_length": "64", "status": "tentative", "eui_64": True }, "2001:DB8:3:3::3/64": { "ip": "2001:DB8:3:3::3", "prefix_length": "64", "status": "tentative", "anycast": True }, "FE80::257:D2FF:FE28:1A64": { "ip": "FE80::257:D2FF:FE28:1A64", "status": "tentative", "origin": "link_layer", }, "enabled": True, "nd": { "dad_attempts": 1, "ns_retransmit_interval": 1000, "dad_enabled": True, "reachable_time": 30000, "using_time": 30000 }, "icmp": { "error_messages_limited": 100, "redirects": True, "unreachables": "sent" }, }, "oper_status": "down", "enabled": False, "mtu": 1500 }, "Vlan211": { "joined_group_addresses": [ "FF02::1", "FF02::1:FF14:1", "FF02::1:FF28:1A71" ], "ipv6": { "2001:10::14:1/112": { "ip": "2001:10::14:1", "prefix_length": "112", "status": "valid", 'autoconf': { 'preferred_lifetime': 604711, 'valid_lifetime': 2591911, }, }, "FE80::257:D2FF:FE28:1A71": { "ip": "FE80::257:D2FF:FE28:1A71", "status": "valid", "origin": "link_layer", }, "enabled": True, "nd": { "dad_attempts": 1, "ns_retransmit_interval": 1000, "dad_enabled": True, "reachable_time": 30000, "using_time": 30000 }, "icmp": { "error_messages_limited": 100, "redirects": True, "unreachables": "sent" }, }, "oper_status": "up", "enabled": True, "autoconf": True, "mtu": 1500 }, "GigabitEthernet3": { "enabled": True, "joined_group_addresses": [ "FF02::1", "FF02::1:FF1E:4F2", "FF02::2" ], "ipv6": { "enabled": False, "FE80::5054:FF:FE1E:4F2": { "ip": "FE80::5054:FF:FE1E:4F2", "status": "valid", "origin": "link_layer", }, "unnumbered": { "interface_ref": "Loopback0", }, "nd": { "dad_attempts": 1, "reachable_time": 30000, "using_time": 30000, "dad_enabled": True }, "icmp": { "unreachables": "sent", "redirects": True, "error_messages_limited": 100 }, "nd": { "dad_attempts": 1, "dad_enabled": True, "reachable_time": 30000, "using_time": 30000, "advertised_reachable_time": 0, "advertised_retransmit_interval": 0, "router_advertisements_interval": 200, "router_advertisements_live": 1800, "advertised_default_router_preference": 'Medium', "advertised_reachable_time_unspecified": True, "advertised_retransmit_interval_unspecified": True, }, }, "oper_status": "up", "mtu": 1500, "addresses_config_method": 'stateless autoconfig', } } golden_output = {'execute.return_value': ''' Vlan211 is up, line protocol is up IPv6 is enabled, link-local address is FE80::257:D2FF:FE28:1A71 No Virtual link-local address(es): Stateless address autoconfig enabled Global unicast address(es): 2001:10::14:1, subnet is 2001:10::14:0/112 valid lifetime 2591911 preferred lifetime 604711 Joined group address(es): FF02::1 FF02::1:FF14:1 FF02::1:FF28:1A71 MTU is 1500 bytes ICMP error messages limited to one every 100 milliseconds ICMP redirects are enabled ICMP unreachables are sent ND DAD is enabled, number of DAD attempts: 1 ND reachable time is 30000 milliseconds (using 30000) ND NS retransmit interval is 1000 milliseconds GigabitEthernet1/0/1 is administratively down, line protocol is down IPv6 is tentative, link-local address is FE80::257:D2FF:FE28:1A64 [TEN] No Virtual link-local address(es): Description: desc Global unicast address(es): 2000::1, subnet is 2000::/126 [TEN] 2001:DB8:1:1::1, subnet is 2001:DB8:1:1::/64 [TEN] 2001:DB8:2:2::2, subnet is 2001:DB8:2:2::/64 [TEN] 2001:DB8:3:3::3, subnet is 2001:DB8:3:3::/64 [ANY/TEN] 2001:DB8:4:4:257:D2FF:FE28:1A64, subnet is 2001:DB8:4:4::/64 [EUI/TEN] Joined group address(es): FF02::1 MTU is 1500 bytes ICMP error messages limited to one every 100 milliseconds ICMP redirects are enabled ICMP unreachables are sent ND DAD is enabled, number of DAD attempts: 1 ND reachable time is 30000 milliseconds (using 30000) ND NS retransmit interval is 1000 milliseconds GigabitEthernet3 is up, line protocol is up IPv6 is enabled, link-local address is FE80::5054:FF:FE1E:4F2 No Virtual link-local address(es): Interface is unnumbered. Using address of Loopback0 No global unicast address is configured Joined group address(es): FF02::1 FF02::2 FF02::1:FF1E:4F2 MTU is 1500 bytes ICMP error messages limited to one every 100 milliseconds ICMP redirects are enabled ICMP unreachables are sent ND DAD is enabled, number of DAD attempts: 1 ND reachable time is 30000 milliseconds (using 30000) ND advertised reachable time is 0 (unspecified) ND advertised retransmit interval is 0 (unspecified) ND router advertisements are sent every 200 seconds ND router advertisements live for 1800 seconds ND advertised default router preference is Medium Hosts use stateless autoconfig for addresses. '''} def test_empty(self): self.device = Mock(**self.empty_output) interface_obj = ShowIpv6Interface(device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = interface_obj.parse() def test_golden(self): self.device = Mock(**self.golden_output) interface_obj = ShowIpv6Interface(device=self.device) parsed_output = interface_obj.parse() self.maxDiff = None self.assertEqual(parsed_output,self.golden_parsed_output) ############################################################################# # unitest For show interfaces trunk ############################################################################# class test_show_interfaces_trunk(unittest.TestCase): device = Device(name='aDevice') empty_output = {'execute.return_value': ''} golden_parsed_output = { "interface": { "GigabitEthernet1/0/4": { "vlans_allowed_active_in_mgmt_domain": '200-211', "vlans_allowed_on_trunk": '200-211', "mode": "on", "native_vlan": "1", "status": "trunking", "vlans_in_stp_forwarding_not_pruned": '200-211', "name": "GigabitEthernet1/0/4", "encapsulation": "802.1q" }, "GigabitEthernet1/0/23": { "vlans_allowed_active_in_mgmt_domain": '200-211', "vlans_allowed_on_trunk": '200-211', "mode": "on", "native_vlan": "1", "status": "trunking", "vlans_in_stp_forwarding_not_pruned": '200-211', "name": "GigabitEthernet1/0/23", "encapsulation": "802.1q" }, "Port-channel12": { "vlans_allowed_active_in_mgmt_domain": '100-110', "vlans_allowed_on_trunk": '100-110', "mode": "on", "native_vlan": "1", "status": "trunking", "vlans_in_stp_forwarding_not_pruned": '100-110', "name": "Port-channel12", "encapsulation": "802.1q" }, "Port-channel14": { "vlans_allowed_active_in_mgmt_domain": '200-211, 300-302', "vlans_allowed_on_trunk": '200-211', "mode": "on", "native_vlan": "1", "status": "trunking", "vlans_in_stp_forwarding_not_pruned": '200-211', "name": "Port-channel14", "encapsulation": "802.1q" } } } golden_output = {'execute.return_value': ''' Port Mode Encapsulation Status Native vlan Gi1/0/4 on 802.1q trunking 1 Gi1/0/23 on 802.1q trunking 1 Po12 on 802.1q trunking 1 Po14 on 802.1q trunking 1 Port Vlans allowed on trunk Gi1/0/4 200-211 Gi1/0/23 200-211 Po12 100-110 Po14 200-211 Port Vlans allowed and active in management domain Gi1/0/4 200-211 Gi1/0/23 200-211 Po12 100-110 Po14 200-211, 300-302 Port Vlans in spanning tree forwarding state and not pruned Gi1/0/4 200-211 Gi1/0/23 200-211 Po12 100-110 Port Vlans in spanning tree forwarding state and not pruned Po14 200-211 '''} def test_empty(self): self.device = Mock(**self.empty_output) interface_obj = ShowInterfacesTrunk(device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = interface_obj.parse() def test_golden(self): self.device = Mock(**self.golden_output) interface_obj = ShowInterfacesTrunk(device=self.device) parsed_output = interface_obj.parse() self.assertEqual(parsed_output,self.golden_parsed_output) ############################################################################# # unitest For show interfaces <WORD> counters ############################################################################# class test_show_interfaces_counters(unittest.TestCase): device = Device(name='aDevice') empty_output = {'execute.return_value': ''} golden_parsed_output = { "interface": { "GigabitEthernet1/0/1": { "out": { "mcast_pkts": 188396, "bcast_pkts": 0, "ucast_pkts": 124435064, "name": "GigabitEthernet1/0/1", "octets": 24884341205 }, "in": { "mcast_pkts": 214513, "bcast_pkts": 0, "ucast_pkts": 15716712, "name": "GigabitEthernet1/0/1", "octets": 3161931167 } } } } golden_output = {'execute.return_value': ''' Port InOctets InUcastPkts InMcastPkts InBcastPkts Gi1/0/1 3161931167 15716712 214513 0 Port OutOctets OutUcastPkts OutMcastPkts OutBcastPkts Gi1/0/1 24884341205 124435064 188396 0 '''} def test_empty(self): self.device = Mock(**self.empty_output) interface_obj = ShowInterfacesCounters(device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = interface_obj.parse(interface='Gi1/0/1') def test_golden(self): self.device = Mock(**self.golden_output) interface_obj = ShowInterfacesCounters(device=self.device) parsed_output = interface_obj.parse(interface='GigabitEthernet1/0/1') self.assertEqual(parsed_output,self.golden_parsed_output) ############################################################################# # unitest For show interfaces <interface> accounting ############################################################################# class test_show_interfaces_accounting(unittest.TestCase): device = Device(name='aDevice') empty_output = {'execute.return_value': ''} golden_parsed_output = \ { "GigabitEthernet1": { "accounting": { "arp": { "chars_in": 4590030, "chars_out": 120, "pkts_in": 109280, "pkts_out": 2 }, "ip": { "chars_in": 2173570, "chars_out": 2167858, "pkts_in": 22150, "pkts_out": 22121 }, "ipv6": { "chars_in": 1944, "chars_out": 0, "pkts_in": 24, "pkts_out": 0 }, "other": { "chars_in": 5306164, "chars_out": 120, "pkts_in": 112674, "pkts_out": 2 } } }, "GigabitEthernet2": { "accounting": { "arp": { "chars_in": 5460, "chars_out": 5520, "pkts_in": 91, "pkts_out": 92 }, "ip": { "chars_in": 968690, "chars_out": 1148402, "pkts_in": 11745, "pkts_out": 10821 }, "ipv6": { "chars_in": 70, "chars_out": 0, "pkts_in": 1, "pkts_out": 0 }, "other": { "chars_in": 741524, "chars_out": 5520, "pkts_in": 3483, "pkts_out": 92 } } }, "GigabitEthernet3": { "accounting": { "arp": { "chars_in": 5460, "chars_out": 5520, "pkts_in": 91, "pkts_out": 92 }, "ip": { "chars_in": 1190691, "chars_out": 1376253, "pkts_in": 15271, "pkts_out": 14382 }, "ipv6": { "chars_in": 70, "chars_out": 0, "pkts_in": 1, "pkts_out": 0 }, "other": { "chars_in": 741524, "chars_out": 5520, "pkts_in": 3483, "pkts_out": 92 } } } } golden_output = {'execute.return_value': ''' show interface accounting GigabitEthernet1 Protocol Pkts In Chars In Pkts Out Chars Out Other 112674 5306164 2 120 IP 22150 2173570 22121 2167858 ARP 109280 4590030 2 120 IPv6 24 1944 0 0 GigabitEthernet2 Protocol Pkts In Chars In Pkts Out Chars Out Other 3483 741524 92 5520 IP 11745 968690 10821 1148402 ARP 91 5460 92 5520 IPv6 1 70 0 0 GigabitEthernet3 Protocol Pkts In Chars In Pkts Out Chars Out Other 3483 741524 92 5520 IP 15271 1190691 14382 1376253 ARP 91 5460 92 5520 IPv6 1 70 0 0 Loopback0 Protocol Pkts In Chars In Pkts Out Chars Out No traffic sent or received on this interface. Loopback1 Protocol Pkts In Chars In Pkts Out Chars Out No traffic sent or received on this interface. '''} def test_empty(self): self.device = Mock(**self.empty_output) obj = ShowInterfacesAccounting(device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = obj.parse() def test_golden(self): self.device = Mock(**self.golden_output) obj = ShowInterfacesAccounting(device=self.device) parsed_output = obj.parse() self.assertEqual(parsed_output,self.golden_parsed_output) if __name__ == '__main__': unittest.main()

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import sys import unittest from unittest.mock import Mock from unittest.mock import patch from textwrap import dedent ats_mock = Mock() with patch.dict('sys.modules', {'ats' : ats_mock}, autospec=True): import genie.parsergen from genie.parsergen import oper_fill from genie.parsergen import oper_check from genie.parsergen import oper_fill_tabular from genie.parsergen.examples.parsergen.pyAts import parsergen_demo_mkpg import xml.etree.ElementTree as ET from ats.topology import Device from genie.metaparser.util.exceptions import SchemaEmptyParserError from genie.libs.parser.iosxe.show_interface import ShowInterfacesSwitchport,\ ShowIpInterfaceBriefPipeVlan,\ ShowInterfaces, ShowIpInterface,\ ShowIpv6Interface, \ ShowInterfacesTrunk, \ ShowInterfacesCounters, \ ShowInterfacesAccounting, \ ShowIpInterfaceBriefPipeIp class test_show_interface_parsergen(unittest.TestCase): def test_tabular_parser(self): self.showCommandOutput=''' R1#show ip interface brief Interface IP-Address OK? Method Status Protocol GigabitEthernet0/0 10.1.10.20 YES NVRAM up up GigabitEthernet1/0/1 unassigned YES unset up up GigabitEthernet1/0/10 unassigned YES unset down down ''' self.outputDict = {'GigabitEthernet0/0': {'IP-Address': '10.1.10.20', 'Interface': 'GigabitEthernet0/0', 'Method': 'NVRAM', 'OK?': 'YES', 'Protocol': 'up', 'Status': 'up'}, 'GigabitEthernet1/0/1': {'IP-Address': 'unassigned', 'Interface': 'GigabitEthernet1/0/1', 'Method': 'unset', 'OK?': 'YES', 'Protocol': 'up', 'Status': 'up'}, 'GigabitEthernet1/0/10': {'IP-Address': 'unassigned', 'Interface': 'GigabitEthernet1/0/10', 'Method': 'unset', 'OK?': 'YES', 'Protocol': 'down', 'Status': 'down'}} device_kwargs = {'is_connected.return_value':True, 'execute.return_value':dedent(self.showCommandOutput)} device1 = Mock(**device_kwargs) device1.name='router3' result = genie.parsergen.oper_fill_tabular(device=device1, show_command="show ip interface brief", refresh_cache=True, header_fields= [ "Interface", "IP-Address", "OK\?", "Method", "Status", "Protocol" ], label_fields= [ "Interface", "IP-Address", "OK?", "Method", "Status", "Protocol" ], index=[0]) self.assertEqual(result.entries, self.outputDict) args, kwargs = device1.execute.call_args self.assertTrue('show ip interface brief' in args, msg='The expected command was not sent to the router') arse() self.maxDiff = None self.assertEqual(parsed_output,self.golden_parsed_output) def test_empty(self): self.device1 = Mock(**self.empty_output) intf_obj = ShowInterfacesSwitchport(device=self.device1) with self.assertRaises(SchemaEmptyParserError): parsed_output = intf_obj.parse() }, "encapsulations": { "encapsulation": "arpa" }, "last_input": "never", "last_output": "04:39:18", "line_protocol": "down", "mac_address": "0057.d228.1a64", "connected": False, "port_channel": { "port_channel_member": False }, "media_type": "10/100/1000BaseTX", "bandwidth": 768, "port_speed": "1000", "enabled": False, "arp_timeout": "04:00:00", "mtu": 1500, "delay": 3330, "reliability": "255/255" }, "GigabitEthernet3": { "flow_control": { "send": False, "receive": False }, "type": "CSR vNIC", 'auto_negotiate': True, 'duplex_mode': 'full', 'link_type': 'auto', 'media_type': 'RJ45', 'port_speed': '1000', "counters": { "out_buffer_failure": 0, "out_underruns": 0, "in_giants": 0, "in_throttles": 0, "in_frame": 0, "in_ignored": 0, "last_clear": "never", "out_interface_resets": 1, "in_mac_pause_frames": 0, "out_collision": 0, "in_crc_errors": 0, "rate": { "out_rate_pkts": 0, "load_interval": 300, "out_rate": 0, "in_rate": 0, "in_rate_pkts": 0 }, "in_watchdog": 0, "out_deferred": 0, "out_mac_pause_frames": 0, "in_pkts": 6, "in_multicast_pkts": 0, "in_runts": 0, "in_no_buffer": 0, "out_buffers_swapped": 0, "out_errors": 0, "in_errors": 0, "in_octets": 480, "out_unknown_protocl_drops": 0, "out_no_carrier": 0, "out_lost_carrier": 0, "in_broadcast_pkts": 0, "out_pkts": 28, "out_late_collision": 0, "out_octets": 7820, "in_overrun": 0, "out_babble": 0 }, "phys_address": "5254.0072.9b0c", "keepalive": 10, "output_hang": "never", "txload": "1/255", "reliability": "255/255", "arp_type": "arpa", "rxload": "1/255", "queues": { "input_queue_size": 0, "total_output_drop": 0, "input_queue_drops": 0, "input_queue_max": 375, "output_queue_size": 0, "input_queue_flushes": 0, "output_queue_max": 40, "queue_strategy": "fifo" }, "ipv4": { "200.2.1.1/24": { "prefix_length": "24", "ip": "200.2.1.1" }, "unnumbered": { "interface_ref": "Loopback0" } }, "encapsulations": { "encapsulation": "arpa" }, "last_output": "00:00:27", "line_protocol": "up", "mac_address": "5254.0072.9b0c", "oper_status": "up", "port_channel": { "port_channel_member": False }, "arp_timeout": "04:00:00", "bandwidth": 1000000, "enabled": True, "mtu": 1500, "delay": 10, "last_input": "never" }, "Loopback0": { "queues": { "input_queue_size": 0, "total_output_drop": 0, "input_queue_drops": 0, "input_queue_max": 75, "output_queue_size": 0, "input_queue_flushes": 0, "output_queue_max": 0, "queue_strategy": "fifo" }, "mtu": 1514, "encapsulations": { "encapsulation": "loopback" }, "last_output": "never", "type": "Loopback", "line_protocol": "up", "oper_status": "up", "keepalive": 10, "output_hang": "never", "txload": "1/255", "counters": { "out_buffer_failure": 0, "out_underruns": 0, "in_giants": 0, "in_throttles": 0, "in_frame": 0, "in_ignored": 0, "last_clear": "1d04h", "out_interface_resets": 0, "out_collision": 0, "rate": { "out_rate_pkts": 0, "load_interval": 300, "out_rate": 0, "in_rate": 0, "in_rate_pkts": 0 }, "in_pkts": 0, "in_multicast_pkts": 0, "in_runts": 0, "in_no_buffer": 0, "out_buffers_swapped": 0, "out_errors": 0, "in_errors": 0, "in_octets": 0, "in_crc_errors": 0, "out_unknown_protocl_drops": 0, "in_broadcast_pkts": 0, "out_pkts": 72, "out_octets": 5760, "in_overrun": 0, "in_abort": 0 }, "reliability": "255/255", "bandwidth": 8000000, "port_channel": { "port_channel_member": False }, "enabled": True, "ipv4": { "200.2.1.1/24": { "prefix_length": "24", "ip": "200.2.1.1" } }, "rxload": "1/255", "delay": 5000, "last_input": "1d02h" }, "Vlan100": { "type": "Ethernet SVI", "counters": { "out_buffer_failure": 0, "out_underruns": 0, "in_giants": 0, "in_throttles": 0, "in_frame": 0, "in_ignored": 0, "last_clear": "1d04h", "out_interface_resets": 0, "rate": { "out_rate_pkts": 0, "load_interval": 300, "out_rate": 0, "in_rate": 0, "in_rate_pkts": 0 }, "in_pkts": 50790, "in_multicast_pkts": 0, "in_runts": 0, "in_no_buffer": 0, "out_buffers_swapped": 0, "out_errors": 0, "in_errors": 0, "in_octets": 3657594, "in_crc_errors": 0, "out_unknown_protocl_drops": 0, "in_broadcast_pkts": 0, "out_pkts": 72, "out_octets": 5526, "in_overrun": 0 }, "phys_address": "0057.d228.1a51", "queues": { "input_queue_size": 0, "total_output_drop": 0, "input_queue_drops": 0, "input_queue_max": 375, "output_queue_size": 0, "input_queue_flushes": 0, "output_queue_max": 40, "queue_strategy": "fifo" }, "txload": "1/255", "reliability": "255/255", "arp_type": "arpa", "rxload": "1/255", "output_hang": "never", "ipv4": { "201.0.12.1/24": { "prefix_length": "24", "ip": "201.0.12.1" } }, "encapsulations": { "encapsulation": "arpa" }, "last_output": "1d03h", "line_protocol": "up", "mac_address": "0057.d228.1a51", "oper_status": "up", "port_channel": { "port_channel_member": False }, "arp_timeout": "04:00:00", "bandwidth": 1000000, "enabled": True, "mtu": 1500, "delay": 10, "last_input": "never" }, "GigabitEthernet1/0/2": { "flow_control": { "send": False, "receive": False }, "type": "Gigabit Ethernet", "counters": { "out_buffer_failure": 0, "out_underruns": 0, "in_giants": 0, "in_throttles": 0, "in_frame": 0, "in_ignored": 0, "last_clear": "1d02h", "out_interface_resets": 5, "in_mac_pause_frames": 0, "out_collision": 0, "rate": { "out_rate_pkts": 0, "load_interval": 300, "out_rate": 0, "in_rate": 3000, "in_rate_pkts": 5 }, "in_watchdog": 0, "out_deferred": 0, "out_mac_pause_frames": 0, "in_pkts": 545526, "in_multicast_pkts": 535961, "in_runts": 0, "out_unknown_protocl_drops": 0, "in_no_buffer": 0, "out_buffers_swapped": 0, "out_lost_carrier": 0, "out_errors": 0, "in_errors": 0, "in_octets": 41210298, "in_crc_errors": 0, "out_no_carrier": 0, "in_with_dribble": 0, "in_broadcast_pkts": 535961, "out_pkts": 23376, "out_late_collision": 0, "out_octets": 3642296, "in_overrun": 0, "out_babble": 0 }, "phys_address": "0057.d228.1a02", "keepalive": 10, "output_hang": "never", "txload": "1/255", "oper_status": "up", "arp_type": "arpa", "media_type": "10/100/1000BaseTX", "rxload": "1/255", "duplex_mode": "full", "queues": { "input_queue_size": 0, "total_output_drop": 0, "input_queue_drops": 0, "input_queue_max": 2000, "output_queue_size": 0, "input_queue_flushes": 0, "output_queue_max": 40, "queue_strategy": "fifo" }, "encapsulations": { "encapsulation": "arpa" }, "last_input": "never", "last_output": "00:00:02", "line_protocol": "up", "mac_address": "0057.d228.1a02", "connected": True, "port_channel": { "port_channel_member": True, 'port_channel_int': 'Port-channel12', }, "arp_timeout": "04:00:00", "bandwidth": 1000000, "port_speed": "1000", "enabled": True, "mtu": 1500, "delay": 10, "reliability": "255/255" }, "GigabitEthernet0/0/4": { "arp_timeout": "04:00:00", "arp_type": "arpa", "bandwidth": 1000000, "counters": { "in_broadcast_pkts": 0, "in_crc_errors": 0, "in_errors": 0, "in_frame": 0, "in_giants": 0, "in_ignored": 0, "in_mac_pause_frames": 0, "in_multicast_pkts": 0, "in_no_buffer": 0, "in_octets": 0, "in_overrun": 0, "in_pkts": 0, "in_runts": 0, "in_throttles": 0, "in_watchdog": 0, "last_clear": "never", "out_babble": 0, "out_collision": 0, "out_deferred": 0, "out_errors": 0, "out_interface_resets": 1, "out_late_collision": 0, "out_lost_carrier": 0, "out_mac_pause_frames": 0, "out_no_carrier": 0, "out_octets": 0, "out_pkts": 0, "out_underruns": 0, "out_unknown_protocl_drops": 0, "rate": { "in_rate": 0, "in_rate_pkts": 0, "load_interval": 300, "out_rate": 0, "out_rate_pkts": 0 } }, "delay": 10, "enabled": False, "encapsulations": { "encapsulation": "arpa" }, "flow_control": { "receive": False, "send": False }, "last_input": "never", "last_output": "never", "line_protocol": "down", "mac_address": "380e.4d6c.7006", "phys_address": "380e.4d6c.7006", "mtu": 1500, "oper_status": "down", "output_hang": "never", "port_channel": { "port_channel_member": False }, "queues": { "input_queue_drops": 0, "input_queue_flushes": 0, "input_queue_max": 375, "input_queue_size": 0, "output_queue_max": 40, "output_queue_size": 0, "queue_strategy": "fifo", "total_output_drop": 0 }, "reliability": "255/255", "rxload": "1/255", "txload": "1/255", "type": "BUILT-IN-2T+6X1GE" } } golden_output = {'execute.return_value': ''' GigabitEthernet1/0/1 is administratively down, line protocol is down (disabled) Hardware is Gigabit Ethernet, address is 0057.d228.1a64 (bia 0057.d228.1a64) Description: desc Internet address is 10.1.1.1/24 MTU 1500 bytes, BW 768 Kbit/sec, DLY 3330 usec, reliability 255/255, txload 1/255, rxload 1/255 Encapsulation ARPA, loopback not set Keepalive set (10 sec) Auto-duplex, 1000Mb/s, media type is 10/100/1000BaseTX input flow-control is off, output flow-control is unsupported ARP type: ARPA, ARP Timeout 04:00:00 Last input never, output 04:39:18, output hang never Last clearing of "show interface" counters 1d02h Input queue: 0/375/0/0 (size/max/drops/flushes); Total output drops: 0 Queueing strategy: fifo Output queue: 0/40 (size/max) 30 second input rate 0 bits/sec, 0 packets/sec 30 second output rate 0 bits/sec, 0 packets/sec 12127 packets input, 2297417 bytes, 0 no buffer Received 4173 broadcasts (0 IP multicasts) 0 runts, 0 giants, 0 throttles 0 input errors, 0 CRC, 0 frame, 0 overrun, 0 ignored 0 watchdog, 4171 multicast, 0 pause input 0 input packets with dribble condition detected 12229 packets output, 2321107 bytes, 0 underruns 0 output errors, 0 collisions, 2 interface resets 0 unknown protocol drops 0 babbles, 0 late collision, 0 deferred 0 lost carrier, 0 no carrier, 0 pause output 0 output buffer failures, 0 output buffers swapped out GigabitEthernet1/0/2 is up, line protocol is up (connected) Hardware is Gigabit Ethernet, address is 0057.d228.1a02 (bia 0057.d228.1a02) MTU 1500 bytes, BW 1000000 Kbit/sec, DLY 10 usec, reliability 255/255, txload 1/255, rxload 1/255 Encapsulation ARPA, loopback not set Keepalive set (10 sec) Full-duplex, 1000Mb/s, media type is 10/100/1000BaseTX input flow-control is off, output flow-control is unsupported ARP type: ARPA, ARP Timeout 04:00:00 Last input never, output 00:00:02, output hang never Last clearing of "show interface" counters 1d02h Input queue: 0/2000/0/0 (size/max/drops/flushes); Total output drops: 0 Queueing strategy: fifo Output queue: 0/40 (size/max) 5 minute input rate 3000 bits/sec, 5 packets/sec 5 minute output rate 0 bits/sec, 0 packets/sec 545526 packets input, 41210298 bytes, 0 no buffer Received 535996 broadcasts (535961 multicasts) 0 runts, 0 giants, 0 throttles 0 input errors, 0 CRC, 0 frame, 0 overrun, 0 ignored 0 watchdog, 535961 multicast, 0 pause input 0 input packets with dribble condition detected 23376 packets output, 3642296 bytes, 0 underruns 0 output errors, 0 collisions, 5 interface resets 0 unknown protocol drops 0 babbles, 0 late collision, 0 deferred 0 lost carrier, 0 no carrier, 0 pause output 0 output buffer failures, 0 output buffers swapped out GigabitEthernet3 is up, line protocol is up Hardware is CSR vNIC, address is 5254.0072.9b0c (bia 5254.0072.9b0c) Interface is unnumbered. Using address of Loopback0 (200.2.1.1) MTU 1500 bytes, BW 1000000 Kbit/sec, DLY 10 usec, reliability 255/255, txload 1/255, rxload 1/255 Encapsulation ARPA, loopback not set Keepalive set (10 sec) Full Duplex, 1000Mbps, link type is auto, media type is RJ45 output flow-control is unsupported, input flow-control is unsupported ARP type: ARPA, ARP Timeout 04:00:00 Last input never, output 00:00:27, output hang never Last clearing of "show interface" counters never Input queue: 0/375/0/0 (size/max/drops/flushes); Total output drops: 0 Queueing strategy: fifo Output queue: 0/40 (size/max) 5 minute input rate 0 bits/sec, 0 packets/sec 5 minute output rate 0 bits/sec, 0 packets/sec 6 packets input, 480 bytes, 0 no buffer Received 0 broadcasts (0 IP multicasts) 0 runts, 0 giants, 0 throttles 0 input errors, 0 CRC, 0 frame, 0 overrun, 0 ignored 0 watchdog, 0 multicast, 0 pause input 28 packets output, 7820 bytes, 0 underruns 0 output errors, 0 collisions, 1 interface resets 0 unknown protocol drops 0 babbles, 0 late collision, 0 deferred 0 lost carrier, 0 no carrier, 0 pause output 0 output buffer failures, 0 output buffers swapped out Loopback0 is up, line protocol is up Hardware is Loopback Internet address is 200.2.1.1/24 MTU 1514 bytes, BW 8000000 Kbit/sec, DLY 5000 usec, reliability 255/255, txload 1/255, rxload 1/255 Encapsulation LOOPBACK, loopback not set Keepalive set (10 sec) Last input 1d02h, output never, output hang never Last clearing of "show interface" counters 1d04h Input queue: 0/75/0/0 (size/max/drops/flushes); Total output drops: 0 Queueing strategy: fifo Output queue: 0/0 (size/max) 5 minute input rate 0 bits/sec, 0 packets/sec 5 minute output rate 0 bits/sec, 0 packets/sec 0 packets input, 0 bytes, 0 no buffer Received 0 broadcasts (0 IP multicasts) 0 runts, 0 giants, 0 throttles 0 input errors, 0 CRC, 0 frame, 0 overrun, 0 ignored, 0 abort 72 packets output, 5760 bytes, 0 underruns 0 output errors, 0 collisions, 0 interface resets 0 unknown protocol drops 0 output buffer failures, 0 output buffers swapped out Vlan100 is up, line protocol is up Hardware is Ethernet SVI, address is 0057.d228.1a51 (bia 0057.d228.1a51) Internet address is 201.0.12.1/24 MTU 1500 bytes, BW 1000000 Kbit/sec, DLY 10 usec, reliability 255/255, txload 1/255, rxload 1/255 Encapsulation ARPA, loopback not set Keepalive not supported ARP type: ARPA, ARP Timeout 04:00:00 Last input never, output 1d03h, output hang never Last clearing of "show interface" counters 1d04h Input queue: 0/375/0/0 (size/max/drops/flushes); Total output drops: 0 Queueing strategy: fifo Output queue: 0/40 (size/max) 5 minute input rate 0 bits/sec, 0 packets/sec 5 minute output rate 0 bits/sec, 0 packets/sec 50790 packets input, 3657594 bytes, 0 no buffer Received 0 broadcasts (0 IP multicasts) 0 runts, 0 giants, 0 throttles 0 input errors, 0 CRC, 0 frame, 0 overrun, 0 ignored 72 packets output, 5526 bytes, 0 underruns 0 output errors, 0 interface resets 0 unknown protocol drops 0 output buffer failures, 0 output buffers swapped out Port-channel12 is up, line protocol is up (connected) Hardware is EtherChannel, address is 0057.d228.1a02 (bia 0057.d228.1a02) MTU 1500 bytes, BW 1000000 Kbit/sec, DLY 10 usec, reliability 255/255, txload 1/255, rxload 1/255 Encapsulation QinQ Virtual LAN, outer ID 10, inner ID 20 Keepalive set (10 sec) Full-duplex, 1000Mb/s, link type is auto, media type is input flow-control is off, output flow-control is unsupported Members in this channel: Gi1/0/2 ARP type: ARPA, ARP Timeout 04:00:00 Last input never, output 1d22h, output hang never Last clearing of "show interface" counters 1d23h Input queue: 0/2000/0/0 (size/max/drops/flushes); Total output drops: 0 Queueing strategy: fifo Output queue: 0/0 (size/max) 5 minute input rate 2000 bits/sec, 2 packets/sec 5 minute output rate 0 bits/sec, 0 packets/sec 961622 packets input, 72614643 bytes, 0 no buffer Received 944818 broadcasts (944788 multicasts) 0 runts, 0 giants, 0 throttles 0 input errors, 0 CRC, 0 frame, 0 overrun, 0 ignored 0 watchdog, 4286699522 multicast, 0 pause input 0 input packets with dribble condition detected 39281 packets output, 6235318 bytes, 0 underruns 0 output errors, 0 collisions, 2 interface resets 0 unknown protocol drops 0 babbles, 0 late collision, 0 deferred 0 lost carrier, 0 no carrier, 0 pause output 0 output buffer failures, 0 output buffers swapped out GigabitEthernet0/0/4 is administratively down, line protocol is down Hardware is BUILT-IN-2T+6X1GE, address is 380e.4d6c.7006 (bia 380e.4d6c.7006) MTU 1500 bytes, BW 1000000 Kbit/sec, DLY 10 usec, reliability 255/255, txload 1/255, rxload 1/255 Encapsulation ARPA, loopback not set Keepalive not supported Full Duplex, 1000Mbps, link type is auto, media type is unknown media type output flow-control is unsupported, input flow-control is unsupported ARP type: ARPA, ARP Timeout 04:00:00 Last input never, output never, output hang never Last clearing of "show interface" counters never Input queue: 0/375/0/0 (size/max/drops/flushes); Total output drops: 0 Queueing strategy: fifo Output queue: 0/40 (size/max) 5 minute input rate 0 bits/sec, 0 packets/sec 5 minute output rate 0 bits/sec, 0 packets/sec 0 packets input, 0 bytes, 0 no buffer Received 0 broadcasts (0 IP multicasts) 0 runts, 0 giants, 0 throttles 0 input errors, 0 CRC, 0 frame, 0 overrun, 0 ignored 0 watchdog, 0 multicast, 0 pause input 0 packets output, 0 bytes, 0 underruns 0 output errors, 0 collisions, 1 interface resets 0 unknown protocol drops 0 babbles, 0 late collision, 0 deferred 0 lost carrier, 0 no carrier, 0 pause output '''} golden_interface_output = {'execute.return_value': ''' CE1#show interfaces GigabitEthernet1 GigabitEthernet1 is up, line protocol is up Hardware is CSR vNIC, address is 5e00.0001.0000 (bia 5e00.0001.0000) Internet address is 172.16.1.243/24 MTU 1500 bytes, BW 1000000 Kbit/sec, DLY 10 usec, reliability 255/255, txload 1/255, rxload 1/255 Encapsulation ARPA, loopback not set Keepalive set (10 sec) Full Duplex, 1000Mbps, link type is auto, media type is Virtual output flow-control is unsupported, input flow-control is unsupported ARP type: ARPA, ARP Timeout 04:00:00 Last input 00:00:02, output 00:00:25, output hang never Last clearing of "show interface" counters never Input queue: 0/375/0/0 (size/max/drops/flushes); Total output drops: 0 Queueing strategy: fifo Output queue: 0/40 (size/max) 5 minute input rate 32000 bits/sec, 28 packets/sec 5 minute output rate 0 bits/sec, 0 packets/sec 7658 packets input, 1125842 bytes, 0 no buffer Received 0 broadcasts (0 IP multicasts) 0 runts, 0 giants, 0 throttles 0 input errors, 0 CRC, 0 frame, 0 overrun, 0 ignored 0 watchdog, 0 multicast, 0 pause input 44 packets output, 4324 bytes, 0 underruns 0 output errors, 0 collisions, 1 interface resets 0 unknown protocol drops 0 babbles, 0 late collision, 0 deferred 0 lost carrier, 0 no carrier, 0 pause output 0 output buffer failures, 0 output buffers swapped out ''' } golden_parsed_interface_output={ "GigabitEthernet1": { "rxload": "1/255", "phys_address": "5e00.0001.0000", "flow_control": { "send": False, "receive": False }, "arp_type": "arpa", "type": "CSR vNIC", "enabled": True, "media_type": "Virtual", "last_input": "00:00:02", "link_type": "auto", "last_output": "00:00:25", "counters": { "in_errors": 0, "in_frame": 0, "in_watchdog": 0, "out_babble": 0, "in_overrun": 0, "out_collision": 0, "out_buffer_failure": 0, "out_no_carrier": 0, "in_runts": 0, "out_late_collision": 0, "in_mac_pause_frames": 0, "out_underruns": 0, "out_pkts": 44, "in_ignored": 0, "in_pkts": 7658, "out_buffers_swapped": 0, "out_interface_resets": 1, "rate": { "out_rate": 0, "load_interval": 300, "in_rate_pkts": 28, "out_rate_pkts": 0, "in_rate": 32000 }, "out_mac_pause_frames": 0, "in_broadcast_pkts": 0, "in_no_buffer": 0, "out_deferred": 0, "in_crc_errors": 0, "out_octets": 4324, "out_lost_carrier": 0, "in_octets": 1125842, "out_unknown_protocl_drops": 0, "last_clear": "never", "in_throttles": 0, "in_multicast_pkts": 0, "out_errors": 0, "in_giants": 0 }, "keepalive": 10, "mtu": 1500, "delay": 10, "encapsulations": { "encapsulation": "arpa" }, "ipv4": { "172.16.1.243/24": { "ip": "172.16.1.243", "prefix_length": "24" } }, "queues": { "output_queue_size": 0, "input_queue_size": 0, "input_queue_flushes": 0, "queue_strategy": "fifo", "total_output_drop": 0, "output_queue_max": 40, "input_queue_drops": 0, "input_queue_max": 375 }, "auto_negotiate": True, "line_protocol": "up", "oper_status": "up", "duplex_mode": "full", "bandwidth": 1000000, "arp_timeout": "04:00:00", "port_speed": "1000", "port_channel": { "port_channel_member": False }, "output_hang": "never", "txload": "1/255", "mac_address": "5e00.0001.0000", "reliability": "255/255" } } def test_empty(self): self.device = Mock(**self.empty_output) interface_obj = ShowInterfaces(device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = interface_obj.parse() def test_golden(self): self.device = Mock(**self.golden_output) interface_obj = ShowInterfaces(device=self.device) parsed_output = interface_obj.parse() self.maxDiff = None self.assertEqual(parsed_output,self.golden_parsed_output) def test_show_interfaces(self): self.device = Mock(**self.golden_interface_output) interface_obj = ShowInterfaces(device=self.device) parsed_output = interface_obj.parse(interface='GigabitEthernet1') self.maxDiff = None self.assertEqual(parsed_output,self.golden_parsed_interface_output) t_outbound': False, 'redirect_inbound': False, 'redirect_exclude': False, }, "ip_null_turbo_vector": True, "probe_proxy_name_replies": False, "ip_fast_switching": True, "ip_multicast_distributed_fast_switching": False, "tcp_ip_header_compression": False, "rtp_ip_header_compression": False, "directed_broadcast_forwarding": False, "ip_flow_switching": False, "input_features": ["MCI Check", "QoS Classification", "QoS Marking"], } } golden_output = {'execute.return_value': ''' Vlan211 is up, line protocol is up Internet address is 201.11.14.1/24 Broadcast address is 255.255.255.255 Address determined by configuration file MTU is 1500 bytes Helper address is not set Directed broadcast forwarding is disabled Outgoing Common access list is not set Outgoing access list is not set Inbound Common access list is not set Inbound access list is not set Proxy ARP is enabled Local Proxy ARP is disabled Security level is default Split horizon is enabled ICMP redirects are always sent ICMP unreachables are always sent ICMP mask replies are never sent IP fast switching is enabled IP Flow switching is disabled IP CEF switching is enabled IP CEF switching turbo vector IP Null turbo vector Associated unicast routing topologies: Topology "base", operation state is UP IP multicast fast switching is disabled IP multicast distributed fast switching is disabled IP route-cache flags are Fast, CEF Router Discovery is disabled IP output packet accounting is disabled IP access violation accounting is disabled TCP/IP header compression is disabled RTP/IP header compression is disabled Probe proxy name replies are disabled Policy routing is disabled Network address translation is disabled BGP Policy Mapping is disabled Input features: MCI Check GigabitEthernet0/0 is up, line protocol is up Internet address is 10.1.8.134/24 Broadcast address is 255.255.255.255 Address determined by setup command MTU is 1500 bytes Helper address is not set Directed broadcast forwarding is disabled Outgoing Common access list is not set Outgoing access list is not set Inbound Common access list is not set Inbound access list is not set Proxy ARP is enabled Local Proxy ARP is disabled Security level is default Split horizon is enabled ICMP redirects are always sent ICMP unreachables are always sent ICMP mask replies are never sent IP fast switching is enabled IP Flow switching is disabled IP CEF switching is enabled IP CEF switching turbo vector IP Null turbo vector VPN Routing/Forwarding "Mgmt-vrf" Associated unicast routing topologies: Topology "base", operation state is UP IP multicast fast switching is disabled IP multicast distributed fast switching is disabled IP route-cache flags are Fast, CEF Router Discovery is disabled IP output packet accounting is disabled IP access violation accounting is disabled TCP/IP header compression is disabled RTP/IP header compression is disabled Probe proxy name replies are disabled Policy routing is disabled Network address translation is disabled BGP Policy Mapping is disabled Input features: MCI Check GigabitEthernet1/0/1 is administratively down, line protocol is down Internet address is 10.1.1.1/24 Broadcast address is 255.255.255.255 Address determined by setup command MTU is 1500 bytes Helper address is not set Directed broadcast forwarding is disabled Secondary address 10.2.2.2/24 Outgoing Common access list is not set Outgoing access list is not set Inbound Common access list is not set Inbound access list is not set Proxy ARP is enabled Local Proxy ARP is disabled Security level is default Split horizon is enabled ICMP redirects are always sent ICMP unreachables are always sent ICMP mask replies are never sent IP fast switching is enabled IP Flow switching is disabled IP CEF switching is enabled IP CEF switching turbo vector IP Null turbo vector Associated unicast routing topologies: Topology "base", operation state is UP IP multicast fast switching is disabled IP multicast distributed fast switching is disabled IP route-cache flags are Fast, CEF Router Discovery is disabled IP output packet accounting is disabled IP access violation accounting is disabled TCP/IP header compression is disabled RTP/IP header compression is disabled Probe proxy name replies are disabled Policy routing is disabled Network address translation is disabled BGP Policy Mapping is disabled Input features: QoS Classification, QoS Marking, MCI Check IPv4 WCCP Redirect outbound is disabled IPv4 WCCP Redirect inbound is disabled IPv4 WCCP Redirect exclude is disabled GigabitEthernet2 is administratively down, line protocol is down Internet protocol processing disabled '''} golden_interface_output = {'execute.return_value':''' CE1#show ip interface GigabitEthernet1 GigabitEthernet1 is up, line protocol is up Internet address is 172.16.1.243/24 Broadcast address is 255.255.255.255 Address determined by DHCP MTU is 1500 bytes Helper address is not set Directed broadcast forwarding is disabled Outgoing Common access list is not set Outgoing access list is not set Inbound Common access list is not set Inbound access list is not set Proxy ARP is enabled Local Proxy ARP is disabled Security level is default Split horizon is enabled ICMP redirects are always sent ICMP unreachables are always sent ICMP mask replies are never sent IP fast switching is enabled IP Flow switching is disabled IP CEF switching is enabled IP CEF switching turbo vector IP Null turbo vector Associated unicast routing topologies: Topology "base", operation state is UP IP multicast fast switching is enabled IP multicast distributed fast switching is disabled IP route-cache flags are Fast, CEF Router Discovery is disabled IP output packet accounting is disabled IP access violation accounting is disabled TCP/IP header compression is disabled RTP/IP header compression is disabled Probe proxy name replies are disabled Policy routing is disabled Network address translation is disabled BGP Policy Mapping is disabled Input features: MCI Check IPv4 WCCP Redirect outbound is disabled IPv4 WCCP Redirect inbound is disabled IPv4 WCCP Redirect exclude is disabled ''' } golden_parsed_interface_output = { "GigabitEthernet1": { "ip_multicast_fast_switching": True, "oper_status": "up", "ip_output_packet_accounting": False, "address_determined_by": "DHCP", "rtp_ip_header_compression": False, "ip_multicast_distributed_fast_switching": False, "wccp": { "redirect_exclude": False, "redirect_outbound": False, "redirect_inbound": False }, "unicast_routing_topologies": { "topology": { "base": { "status": "up" } } }, "router_discovery": False, "tcp_ip_header_compression": False, "probe_proxy_name_replies": False, "local_proxy_arp": False, "policy_routing": False, "mtu": 1500, "icmp": { "mask_replies": "never sent", "unreachables": "always sent", "redirects": "always sent" }, "enabled": True, "ip_route_cache_flags": [ "CEF", "Fast" ], "ip_cef_switching": True, "ip_fast_switching": True, "sevurity_level": "default", "directed_broadcast_forwarding": False, "proxy_arp": True, "ip_null_turbo_vector": True, "network_address_translation": False, "input_features": [ "MCI Check" ], "bgp_policy_mapping": False, "split_horizon": True, "ip_access_violation_accounting": False, "ip_cef_switching_turbo_vector": True, "ipv4": { "172.16.1.243/24": { "ip": "172.16.1.243", "prefix_length": "24", "broadcase_address": "255.255.255.255", "secondary": False } }, "ip_flow_switching": False } } def test_empty(self): self.device = Mock(**self.empty_output) interface_obj = ShowIpInterface(device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = interface_obj.parse() def test_golden(self): self.device = Mock(**self.golden_output) interface_obj = ShowIpInterface(device=self.device) parsed_output = interface_obj.parse() self.maxDiff = None self.assertEqual(parsed_output,self.golden_parsed_output) def test_interface_golden(self): self.device = Mock(**self.golden_interface_output) interface_obj = ShowIpInterface(device=self.device) parsed_output = interface_obj.parse(interface='GigabitEthernet1') self.maxDiff = None self.assertEqual(parsed_output, self.golden_parsed_interface_output) 02::1 FF02::1:FF14:1 FF02::1:FF28:1A71 MTU is 1500 bytes ICMP error messages limited to one every 100 milliseconds ICMP redirects are enabled ICMP unreachables are sent ND DAD is enabled, number of DAD attempts: 1 ND reachable time is 30000 milliseconds (using 30000) ND NS retransmit interval is 1000 milliseconds GigabitEthernet1/0/1 is administratively down, line protocol is down IPv6 is tentative, link-local address is FE80::257:D2FF:FE28:1A64 [TEN] No Virtual link-local address(es): Description: desc Global unicast address(es): 2000::1, subnet is 2000::/126 [TEN] 2001:DB8:1:1::1, subnet is 2001:DB8:1:1::/64 [TEN] 2001:DB8:2:2::2, subnet is 2001:DB8:2:2::/64 [TEN] 2001:DB8:3:3::3, subnet is 2001:DB8:3:3::/64 [ANY/TEN] 2001:DB8:4:4:257:D2FF:FE28:1A64, subnet is 2001:DB8:4:4::/64 [EUI/TEN] Joined group address(es): FF02::1 MTU is 1500 bytes ICMP error messages limited to one every 100 milliseconds ICMP redirects are enabled ICMP unreachables are sent ND DAD is enabled, number of DAD attempts: 1 ND reachable time is 30000 milliseconds (using 30000) ND NS retransmit interval is 1000 milliseconds GigabitEthernet3 is up, line protocol is up IPv6 is enabled, link-local address is FE80::5054:FF:FE1E:4F2 No Virtual link-local address(es): Interface is unnumbered. Using address of Loopback0 No global unicast address is configured Joined group address(es): FF02::1 FF02::2 FF02::1:FF1E:4F2 MTU is 1500 bytes ICMP error messages limited to one every 100 milliseconds ICMP redirects are enabled ICMP unreachables are sent ND DAD is enabled, number of DAD attempts: 1 ND reachable time is 30000 milliseconds (using 30000) ND advertised reachable time is 0 (unspecified) ND advertised retransmit interval is 0 (unspecified) ND router advertisements are sent every 200 seconds ND router advertisements live for 1800 seconds ND advertised default router preference is Medium Hosts use stateless autoconfig for addresses. '''} def test_empty(self): self.device = Mock(**self.empty_output) interface_obj = ShowIpv6Interface(device=self.device) with self.assertRaises(SchemaEmptyParserError): parsed_output = interface_obj.parse() def test_golden(self): self.device = Mock(**self.golden_output) interface_obj = ShowIpv6Interface(device=self.device) parsed_output = interface_obj.parse() self.maxDiff = None self.assertEqual(parsed_output,self.golden_parsed_output)

true

f704f29d917dfbd51e439f0dd5292f602da50c6f

8,655

py

Python

modelci/experimental/model/model_structure.py

FerdinandZhong/ML-Model-CI

90fa2de056dca05031f0787b96c520dc57dc664d

[ "Apache-2.0" ]

170

2020-06-08T18:30:52.000Z

2022-03-28T12:08:11.000Z

modelci/experimental/model/model_structure.py

FerdinandZhong/ML-Model-CI

90fa2de056dca05031f0787b96c520dc57dc664d

[ "Apache-2.0" ]

146

2020-06-14T18:56:27.000Z

2022-02-27T21:15:59.000Z

modelci/experimental/model/model_structure.py

FerdinandZhong/ML-Model-CI

90fa2de056dca05031f0787b96c520dc57dc664d

[ "Apache-2.0" ]

36

2020-06-08T18:30:56.000Z

2022-03-07T18:10:19.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- """ Author: Li Yuanming Email: yli056@e.ntu.edu.sg Date: 1/27/2021 ML model structure definitions. """ import abc import inspect from enum import Enum from typing import Optional, Union, Tuple, Dict, OrderedDict from pydantic import BaseModel, PositiveInt, conint, PositiveFloat, Field, validator from typing_extensions import Literal class Operation(Enum): """ Operation enum to the layer or connection. There are three kinds of operations: ``'A'`` for add the specific layer / connection, ``'D'`` for delete the specific layer / connection, ``M`` for modify the layer / connection, and ``E`` for no operation. """ ADD = 'A' DELETE = 'D' MODIFY = 'M' EMPTY = 'E' class LayerType(Enum): """ Enum of the supported layer type. This is to hint which class of layer the provided data is converted to. """ LINEAR = 'torch.nn.Linear' CONV_1D = 'torch.nn.Conv1d' CONV_2D = 'torch.nn.Conv2d' RELU = 'torch.nn.ReLU' TANH = 'torch.nn.Tanh' BN_1D = 'torch.nn.BatchNorm1d' BN_2D = 'torch.nn.BatchNorm2d' MP_1D = 'torch.nn.MaxPool1d' MP_2D = 'torch.nn.MaxPool2d' AAP_1D = 'torch.nn.AdaptiveAvgPool1d' AAP_2D = 'torch.nn.AdaptiveAvgPool2d' class ModelLayer(BaseModel, abc.ABC): # noinspection PyUnresolvedReferences """ Layer of the model structure. For layer attributes need to be set :code:`None`, use :code:`'null'` instead. This is for the reason of updated parameters with value :code:`None` will be viewed as not set. So we take special care to the desired :code:`None`, replacing it with :code:`'null'`. Attributes: op_ (Operation): Operation to the layer. type_ (LayerType): Indicates the type of this layer. This field also provides hint for :class:`pydantic` model conversion. __required_type__ (LayerType): By overriding this attributes, we can use :meth:`check_layer_type` to provide validation of the sub classes. """ op_: Operation type_: LayerType __required_type__: LayerType @classmethod def parse_layer_obj(cls, layer_obj): """ Parse from a ML layer object. This function will inspect the required parameters to build the layer, and try to obtain its parameter value from the layer object. The default parameter parser is python default :code:`getattr`, which assume we can get the value from the same-named attribute of the layer object. For parameter cannot parsed with default parser, set a function with the format: :code:`__{parameter_name}_parser__(layer_obj: Any) -> Any`. Has the following signature: Input Arguments: * layer_obj : Any The layer object to be parsed. Return Arguments: * Any The parsed value of the given parameter. TODO: Signature checking for __{parameter_name}_parser__ """ kwargs = {'op_': Operation.EMPTY, 'type_': cls.__required_type__} signature = inspect.signature(layer_obj.__init__) for param in signature.parameters: parser = getattr(cls, f'__{param}_parser__', lambda obj: getattr(obj, param)) kwargs[param] = parser(layer_obj) return cls(**kwargs) @validator('type_') def check_layer_type(cls, layer_type: LayerType) -> LayerType: # noqa """ Checks layer type value provided is the same as the required value. This is to generate validator for check :code:`layer_type` field of subclasses of :class:`ModelLayer`. """ if layer_type != cls.__required_type__: raise ValueError(f'Expected {cls.__required_type__} but got {layer_type}') return layer_type class Linear(ModelLayer): in_features: Optional[PositiveInt] out_features: Optional[PositiveInt] bias: Optional[bool] __required_type__ = LayerType.LINEAR @staticmethod def __bias_parser__(layer_obj): return layer_obj.bias is not None class _ConvNd(ModelLayer, abc.ABC): in_channels: Optional[PositiveInt] out_channels: Optional[PositiveInt] kernel_size: Optional[Union[PositiveInt, Tuple[PositiveInt, ...]]] stride: Optional[Union[PositiveInt, Tuple[PositiveInt, ...]]] padding: Optional[Union[conint(ge=0), Tuple[conint(ge=0), ...]]] dilation: Optional[Union[PositiveInt, Tuple[PositiveInt, ...]]] groups: PositiveInt bias: bool padding_mode: Literal['zeros', 'reflect', 'replicate', 'circular'] @staticmethod def __bias_parser__(layer_obj): return layer_obj.bias is not None class Conv1d(_ConvNd): __required_type__ = LayerType.CONV_1D class Conv2d(_ConvNd): __required_type__ = LayerType.CONV_2D class ReLU(ModelLayer): inplace: Optional[bool] __required_type__ = LayerType.RELU class Tanh(ModelLayer): __required_type__ = LayerType.TANH class _BatchNorm(ModelLayer, abc.ABC): num_features: Optional[PositiveInt] eps: Optional[PositiveFloat] momentum: Optional[Union[PositiveFloat, Literal['null']]] affine: Optional[bool] track_running_stats: Optional[bool] class BatchNorm1d(_BatchNorm): __required_type__ = LayerType.BN_1D class BatchNorm2d(_BatchNorm): __required_type__ = LayerType.BN_2D class _MaxPool(ModelLayer, abc.ABC): kernel_size: Union[PositiveInt, Tuple[PositiveInt, ...]] stride: Optional[Union[PositiveInt, Tuple[PositiveInt, ...]]] = None padding: Union[conint(ge=0), Tuple[conint(ge=0), ...]] = 0 dilation: Union[PositiveInt, Tuple[PositiveInt, ...]] = 1 return_indices: bool = False ceil_mode: bool = False class MaxPool1d(_MaxPool): __required_type__ = LayerType.MP_1D class MaxPool2d(_MaxPool): __required_type__ = LayerType.MP_2D class _AdaptiveAvgPool(ModelLayer, abc.ABC): output_size: Union[PositiveInt, Tuple[PositiveInt, ...]] class AdaptiveAvgPool1d(_AdaptiveAvgPool): __required_type__ = LayerType.AAP_1D class AdaptiveAvgPool2d(_AdaptiveAvgPool): __required_type__ = LayerType.AAP_2D _LayerType = Union[Linear, Conv1d, Conv2d, ReLU, Tanh, BatchNorm1d, BatchNorm2d, MaxPool1d, MaxPool2d, AdaptiveAvgPool1d, AdaptiveAvgPool2d] class Structure(BaseModel): # noinspection PyUnresolvedReferences """ Indicate a ML model structure using a graph data structure. :attr:`layer` is the graph node, representing a layer of the model. :attr:`connection` is the graph edge, representing which two layers are connected, and the directions of tensor pass. Attributes: layer (OrderedDict[str, _LayerType]): Layer mapping, the key is layer name, and the value is layer attributes. See :class:`ModelLayer` for reference. connection (Optional[Dict[str, Dict[str, Operation]]]): The connection (:attr:`connection`) maps the starting layer name, to the ending layer name with a connection operation. Examples:: >>> from collections import OrderedDict >>> # add a nn.Linear layer named 'fc1' with in_features=1024, out_features=10 >>> layer_mapping = OrderedDict({ ... 'fc1': LinearLayer(in_features=1024, out_features=10, type_=LayerType.LINEAR, op_=Operation.ADD), ... }) >>> # connection example for add connection from 'conv1' to 'fc1' >>> connection_mapping = {'conv1': {'fc1': Operation.ADD}} >>> struct = Structure(layer=layer_mapping, connection=connection_mapping) >>> print(struct) layer={'fc1': LinearLayer(in_features=1024, out_features=10, bias=None)} connection={'conv1': {'fc1': <Operation.ADD: 'A'>}} >>> # Other than using the model object, we can pass in a plain dictionary, ... # and utilize `Structure.parse_obj`. >>> structure_data = { ... 'layer': {'fc': {'in_features': 1024, 'out_features': 10, 'type_': 'torch.nn.Linear', 'op_': 'A'}}, ... 'connection': {'conv1': {'fc1': 'A'}} ... } >>> Structure.parse_obj(structure_data) Structure(layer={'fc': LinearLayer(in_features=1024, out_features=10, bias=None)}, connection={'conv1': {'fc1': <Operation.ADD: 'A'>}}) """ layer: OrderedDict[str, _LayerType] = Field( default_factory=OrderedDict, example={'fc': {'out_features': 10, 'type_': 'torch.nn.Linear', 'op_': 'M'}} ) connection: Optional[Dict[str, Dict[str, Operation]]] = Field( default_factory=dict, example={'conv1': {'fc1': 'A'}} )

34.209486

115

0.669324

import abc import inspect from enum import Enum from typing import Optional, Union, Tuple, Dict, OrderedDict from pydantic import BaseModel, PositiveInt, conint, PositiveFloat, Field, validator from typing_extensions import Literal class Operation(Enum): ADD = 'A' DELETE = 'D' MODIFY = 'M' EMPTY = 'E' class LayerType(Enum): LINEAR = 'torch.nn.Linear' CONV_1D = 'torch.nn.Conv1d' CONV_2D = 'torch.nn.Conv2d' RELU = 'torch.nn.ReLU' TANH = 'torch.nn.Tanh' BN_1D = 'torch.nn.BatchNorm1d' BN_2D = 'torch.nn.BatchNorm2d' MP_1D = 'torch.nn.MaxPool1d' MP_2D = 'torch.nn.MaxPool2d' AAP_1D = 'torch.nn.AdaptiveAvgPool1d' AAP_2D = 'torch.nn.AdaptiveAvgPool2d' class ModelLayer(BaseModel, abc.ABC): op_: Operation type_: LayerType __required_type__: LayerType @classmethod def parse_layer_obj(cls, layer_obj): kwargs = {'op_': Operation.EMPTY, 'type_': cls.__required_type__} signature = inspect.signature(layer_obj.__init__) for param in signature.parameters: parser = getattr(cls, f'__{param}_parser__', lambda obj: getattr(obj, param)) kwargs[param] = parser(layer_obj) return cls(**kwargs) @validator('type_') def check_layer_type(cls, layer_type: LayerType) -> LayerType: if layer_type != cls.__required_type__: raise ValueError(f'Expected {cls.__required_type__} but got {layer_type}') return layer_type class Linear(ModelLayer): in_features: Optional[PositiveInt] out_features: Optional[PositiveInt] bias: Optional[bool] __required_type__ = LayerType.LINEAR @staticmethod def __bias_parser__(layer_obj): return layer_obj.bias is not None class _ConvNd(ModelLayer, abc.ABC): in_channels: Optional[PositiveInt] out_channels: Optional[PositiveInt] kernel_size: Optional[Union[PositiveInt, Tuple[PositiveInt, ...]]] stride: Optional[Union[PositiveInt, Tuple[PositiveInt, ...]]] padding: Optional[Union[conint(ge=0), Tuple[conint(ge=0), ...]]] dilation: Optional[Union[PositiveInt, Tuple[PositiveInt, ...]]] groups: PositiveInt bias: bool padding_mode: Literal['zeros', 'reflect', 'replicate', 'circular'] @staticmethod def __bias_parser__(layer_obj): return layer_obj.bias is not None class Conv1d(_ConvNd): __required_type__ = LayerType.CONV_1D class Conv2d(_ConvNd): __required_type__ = LayerType.CONV_2D class ReLU(ModelLayer): inplace: Optional[bool] __required_type__ = LayerType.RELU class Tanh(ModelLayer): __required_type__ = LayerType.TANH class _BatchNorm(ModelLayer, abc.ABC): num_features: Optional[PositiveInt] eps: Optional[PositiveFloat] momentum: Optional[Union[PositiveFloat, Literal['null']]] affine: Optional[bool] track_running_stats: Optional[bool] class BatchNorm1d(_BatchNorm): __required_type__ = LayerType.BN_1D class BatchNorm2d(_BatchNorm): __required_type__ = LayerType.BN_2D class _MaxPool(ModelLayer, abc.ABC): kernel_size: Union[PositiveInt, Tuple[PositiveInt, ...]] stride: Optional[Union[PositiveInt, Tuple[PositiveInt, ...]]] = None padding: Union[conint(ge=0), Tuple[conint(ge=0), ...]] = 0 dilation: Union[PositiveInt, Tuple[PositiveInt, ...]] = 1 return_indices: bool = False ceil_mode: bool = False class MaxPool1d(_MaxPool): __required_type__ = LayerType.MP_1D class MaxPool2d(_MaxPool): __required_type__ = LayerType.MP_2D class _AdaptiveAvgPool(ModelLayer, abc.ABC): output_size: Union[PositiveInt, Tuple[PositiveInt, ...]] class AdaptiveAvgPool1d(_AdaptiveAvgPool): __required_type__ = LayerType.AAP_1D class AdaptiveAvgPool2d(_AdaptiveAvgPool): __required_type__ = LayerType.AAP_2D _LayerType = Union[Linear, Conv1d, Conv2d, ReLU, Tanh, BatchNorm1d, BatchNorm2d, MaxPool1d, MaxPool2d, AdaptiveAvgPool1d, AdaptiveAvgPool2d] class Structure(BaseModel): layer: OrderedDict[str, _LayerType] = Field( default_factory=OrderedDict, example={'fc': {'out_features': 10, 'type_': 'torch.nn.Linear', 'op_': 'M'}} ) connection: Optional[Dict[str, Dict[str, Operation]]] = Field( default_factory=dict, example={'conv1': {'fc1': 'A'}} )

true

f704f2ca519f891d9320e62953ff55261e97b68a

5,431

py

Python

src/thexb/STAGE_topobinner.py

harris-2374/THEx

04c4f56eb2cf86b8f55ddd6edd3f48029296bf5a

[ "MIT" ]

null

src/thexb/STAGE_topobinner.py

harris-2374/THEx

04c4f56eb2cf86b8f55ddd6edd3f48029296bf5a

[ "MIT" ]

null

src/thexb/STAGE_topobinner.py

harris-2374/THEx

04c4f56eb2cf86b8f55ddd6edd3f48029296bf5a

[ "MIT" ]

null

""" Author: Andrew Harris Python 3.8 """ import logging import os import pandas as pd from ete3 import Tree from tqdm import tqdm ############################### Set up logger ################################# def set_logger_level(WORKING_DIR, LOG_LEVEL): logger = logging.getLogger(__name__) # Remove existing log file if present if os.path.exists(WORKING_DIR / 'logs/topobin.log'): os.remove(WORKING_DIR / 'logs/topobin.log') formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s') file_handler = logging.FileHandler(WORKING_DIR / 'logs/topobin.log') file_handler.setFormatter(formatter) stream_handler = logging.StreamHandler() logger.addHandler(file_handler) logger.addHandler(stream_handler) logger.setLevel(LOG_LEVEL) return logger ############################## Helper Functions ############################### def remove_heterotachy_info(l): """Remove any information in bracketsete3 does not support this format of newick""" if ("[" not in l) and ("]" not in l): return l open_brackets = [i for i, x in enumerate(l) if x == "["] close_brackets = [i for i, x in enumerate(l) if x == "]"] final_string = f'{l[:open_brackets[0]]}' for ob, cb in zip(open_brackets[1:], close_brackets[:-1]): final_string += l[cb+1:ob] final_string += l[close_brackets[-1]+1:] return final_string def tv_header_validation(df): """Return False if first four required column headers are not valid""" required_cols = list(df.columns[:4]) try: assert required_cols == ["Chromosome", "Window", "NewickTree", "TopologyID"] return True except AssertionError: return False ############################### Main Function ################################ def topobinner(TREEVIEWER_FN, UPDATED_TV_FILENAME, TOPOBIN_ROOTED, WORKING_DIR, MULTIPROCESS, LOG_LEVEL): logger = set_logger_level(WORKING_DIR, LOG_LEVEL) # Setup log file level # Load in Tree Viewer excel file df = pd.read_excel(TREEVIEWER_FN, engine='openpyxl') df = df.reset_index(drop=True) # Validate headers header_check = tv_header_validation(df) if not header_check: raise AssertionError("Input file headers are not valid, please ensure required headers are correct.") df['TopologyID'] = ['NULL']*len(df) trees = df['NewickTree'] topologies = dict() logger.info(f"{len(trees):,} trees to run") # Set root boolean value if TOPOBIN_ROOTED == "Y": TOPOBIN_ROOTED = False else: TOPOBIN_ROOTED = True # Bin Trees tqdm_text = "#" + "{}".format("run1").zfill(3) with tqdm(total=len(trees), desc=tqdm_text, ascii=True) as pbar: for n, t in enumerate(trees): # Check to see if tree is NoTree if t == "NoTree": pbar.update(1) continue # Set first tree in collection dictionary + # move to next tree if len(topologies.keys()) == 0: topologies[n] = {'count': 1, 'idx': [n]} pbar.update(1) continue else: # Iterate through topology list # add new topology if no rf == 0 # increase count if rf == 0 with topology new_topology = True for idx in topologies.keys(): if df.at[idx, 'NewickTree'] == "NoTree": continue t1 = Tree(remove_heterotachy_info(t)) t2 = Tree(remove_heterotachy_info(df.at[idx, 'NewickTree'])) comparison = t1.compare(t2, unrooted=TOPOBIN_ROOTED) rf = comparison['rf'] if rf == 0: topologies[idx]['count'] += 1 topologies[idx]['idx'].append(n) new_topology = False break else: continue if new_topology: topologies[n] = {'count': 1, 'idx': [n]} pbar.update(1) continue else: pbar.update(1) continue # Sort topologies dictionary by 'count' topologies = {k: v for k, v in sorted(topologies.items(), key=lambda item: item[1]['count'], reverse=True)} num_topologies = len(topologies.keys()) # Set zfill number if num_topologies < 100: zfillnum = 3 elif 100 < num_topologies < 1000: zfillnum = 4 else: zfillnum = 5 # Update DataFrame TopologyID column with results overview_df = pd.DataFrame( { "TopologyID": [("Tree" + "{}".format(str(i)).zfill(zfillnum)) for i in range(1, len(topologies.keys())+1)], "Count": [topologies[i]["count"] for i in topologies.keys()], "Rank": [i for i in range(1, len(topologies.keys())+1)], } ) topoCount = 1 for topo in topologies.keys(): idx = topologies[topo]['idx'] topoName = "Tree" + "{}".format(topoCount).zfill(zfillnum) for i in idx: df.at[i, 'TopologyID'] = topoName continue topoCount += 1 # Output updated Tree Viewer file df.to_excel(UPDATED_TV_FILENAME, index=False, engine='openpyxl') logger.info(f"{overview_df}") return

38.51773

119

0.558645

import logging import os import pandas as pd from ete3 import Tree from tqdm import tqdm

true