xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

a2adf5688c4900d441d7a83bf0b2ddb04d8e66b1

80

py

Python

flasky/main/forms/__init__.py

by46/fasky

c6941972b57284c2167dfacf022f981939249256

[ "MIT" ]

null

flasky/main/forms/__init__.py

by46/fasky

c6941972b57284c2167dfacf022f981939249256

[ "MIT" ]

null

flasky/main/forms/__init__.py

by46/fasky

c6941972b57284c2167dfacf022f981939249256

[ "MIT" ]

null

from .profile import EditProfileAdminForm from .profile import EdtProfileForm

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a2d483c1e9b75dc55073e8b235cad453d5fdc0b0

2,267

py

Python

mab/tests/test_algs.py

rsoaresp/mabalgs

82de4148269c3838256600d5e85d849244b14de1

[ "Apache-2.0" ]

95

2019-01-25T14:54:09.000Z

2022-02-27T11:48:49.000Z

mab/tests/test_algs.py

rsoaresp/mabalgs

82de4148269c3838256600d5e85d849244b14de1

[ "Apache-2.0" ]

6

2019-01-28T12:36:38.000Z

2019-12-11T22:26:40.000Z

mab/tests/test_algs.py

rsoaresp/mabalgs

82de4148269c3838256600d5e85d849244b14de1

[ "Apache-2.0" ]

20

2019-02-10T01:17:54.000Z

2022-02-01T02:14:20.000Z

from mab import algs import numpy as np def test_ucb_init_return_first_arm(): ucb_with_two_arms = algs.UCB1(2) assert ucb_with_two_arms.select()[0] == 0 def test_ucb_use_all_arm_dont_usage(): ucb_with_two_arms = algs.UCB1(2) assert ucb_with_two_arms.select()[0] == 0 assert ucb_with_two_arms.select()[0] == 1 def test_ucb_use_all_arm_dont_usage_after_priorize(): ucb_with_two_arms = algs.UCB1(2) assert ucb_with_two_arms.select()[0] == 0 assert ucb_with_two_arms.select()[0] == 1 assert ucb_with_two_arms.select()[0] == 1 def test_ucb_select_two_arms_and_success_return_second(): ucb_with_two_arms = algs.UCB1(2) ucb_with_two_arms.select() ucb_with_two_arms.select() ucb_with_two_arms.reward(1) assert ucb_with_two_arms.select()[0] == 1 def test_ucb_select_two_arms_and_success_one_return_first(): ucb_with_two_arms = algs.UCB1(2) ucb_with_two_arms.select() ucb_with_two_arms.select() ucb_with_two_arms.reward(0) assert ucb_with_two_arms.select()[0] == 0 def test_ucb_select_two_arms_and_have_two_reward_priorize_first(): ucb_with_two_arms = algs.UCB1(2) ucb_with_two_arms.select() ucb_with_two_arms.reward(0) ucb_with_two_arms.select() ucb_with_two_arms.reward(1) ucb_with_two_arms.select() ucb_with_two_arms.reward(0) ucb_with_two_arms.select() ucb_with_two_arms.reward(1) assert ucb_with_two_arms.select()[0] == 1 def test_ucb_exploration_first(): ucb_with_two_arms = algs.UCB1(2) ucb_with_two_arms.select() ucb_with_two_arms.reward(0) ucb_with_two_arms.select() ucb_with_two_arms.reward(1) ucb_with_two_arms.select() ucb_with_two_arms.reward(0) ucb_with_two_arms.select() ucb_with_two_arms.reward(1) last_arm = ucb_with_two_arms.select()[0] assert last_arm == 1 def test_ucb_exploration_second(): ucb_with_two_arms = algs.UCB1(2) ucb_with_two_arms.select() ucb_with_two_arms.reward(0) ucb_with_two_arms.select() ucb_with_two_arms.reward(1) ucb_with_two_arms.select() ucb_with_two_arms.reward(0) ucb_with_two_arms.select() ucb_with_two_arms.reward(1) ucb_with_two_arms.select() last_arm = ucb_with_two_arms.select()[0] assert last_arm == 0

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a2f0765912c790f675eb1bde603c47a77ca771b0

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py

Python

bottleneck/slow/move.py

stroxler/bottleneck

6e91bcb8a21170588ee9a3f2c425a4e307ae05de

[ "BSD-2-Clause" ]

2

2015-05-26T09:06:32.000Z

2015-05-26T09:06:46.000Z

bottleneck/slow/move.py

stroxler/bottleneck

6e91bcb8a21170588ee9a3f2c425a4e307ae05de

[ "BSD-2-Clause" ]

null

bottleneck/slow/move.py

stroxler/bottleneck

6e91bcb8a21170588ee9a3f2c425a4e307ae05de

[ "BSD-2-Clause" ]

null

""" Alternative methods (non-Cython) of calculating moving window statistics. These function are slow but useful for unit testing. """ import numpy as np import bottleneck as bn convolve1d = None minimum_filter1d = None maximum_filter1d = None __all__ = ['move_sum', 'move_nansum', 'move_mean', 'move_nanmean', 'move_std', 'move_nanstd', 'move_min', 'move_nanmin', 'move_max', 'move_nanmax', 'move_median'] # SUM ----------------------------------------------------------------------- def move_sum(arr, window, axis=-1, method='loop'): """ Slow move_sum for unaccelerated ndim/dtype combinations. Parameters ---------- arr : array_like Input array. window : int The number of elements in the moving window. axis : int, optional The axis over which to perform the moving sum. By default the moving sum is taken over the last axis (-1). method : str, optional The following moving window methods are available: ========== ===================================== 'filter' scipy.ndimage.convolve1d 'strides' strides tricks 'loop' brute force python loop (default) ========== ===================================== Returns ------- y : array_like The moving sum of the input array along the specified axis. The output has the same shape as the input. Examples -------- >>> arr = np.array([1, 2, 3, 4]) >>> bn.slow.move_sum(arr, window=2, axis=0) array([ NaN, 3., 5., 7.]) """ arr = np.array(arr, copy=False) if method == 'filter': y = move_sum_filter(arr, window, axis=axis) elif method == 'strides': y = move_func_strides(np.sum, arr, window, axis=axis) elif method == 'loop': y = move_func_loop(np.sum, arr, window, axis=axis) else: msg = "`method` must be 'filter', 'strides', or 'loop'." raise ValueError(msg) if y.dtype != arr.dtype: if issubclass(arr.dtype.type, np.inexact): y = y.astype(arr.dtype) return y def move_nansum(arr, window, axis=-1, method='loop'): """ Slow move_nansum for unaccelerated ndim/dtype combinations. Parameters ---------- arr : array_like Input array. window : int The number of elements in the moving window. axis : int, optional The axis over which to perform the moving sum. By default the moving sum is taken over the last axis (-1). method : str, optional The following moving window methods are available: ========== ===================================== 'filter' scipy.ndimage.convolve1d 'strides' strides tricks 'loop' brute force python loop (default) ========== ===================================== Returns ------- y : ndarray The moving sum of the input array along the specified axis, ignoring NaNs. (A window with all NaNs returns NaN for the window sum.) The output has the same shape as the input. Examples -------- >>> arr = np.array([1, 2, np.nan, 4]) >>> bn.slow.move_nansum(arr, window=2, axis=0) array([ NaN, 3., 2., 4.]) """ arr = np.array(arr, copy=False) if method == 'filter': y = move_nansum_filter(arr, window, axis=axis) elif method == 'strides': y = move_func_strides(np.nansum, arr, window, axis=axis) elif method == 'loop': y = move_func_loop(np.nansum, arr, window, axis=axis) else: msg = "`method` must be 'filter', 'strides', or 'loop'." raise ValueError(msg) if y.dtype != arr.dtype: if issubclass(arr.dtype.type, np.inexact): y = y.astype(arr.dtype) return y def move_sum_filter(arr, window, axis=-1): """ Moving window sum along the specified axis using the filter method. Parameters ---------- arr : array_like Input array. window : int The number of elements in the moving window. axis : int, optional The axis over which to perform the moving sum. By default the moving sum is taken over the last axis (-1). Returns ------- y : ndarray The moving sum of the input array along the specified axis. The output has the same shape as the input. Notes ----- The calculation of the sums uses scipy.ndimage.convolve1d. Examples -------- >>> from bottleneck.slow.move import move_sum_filter >>> arr = np.array([1, 2, 3, 4]) >>> move_sum_filter(arr, window=2, axis=0) array([ NaN, 3., 5., 7.]) """ arr = np.array(arr, copy=False) global convolve1d if convolve1d is None: try: from scipy.ndimage import convolve1d except ImportError: raise ValueError("'filter' method requires SciPy.") if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") arr = arr.astype(float) w = np.ones(window, dtype=int) x0 = (1 - window) // 2 convolve1d(arr, w, axis=axis, mode='constant', cval=np.nan, origin=x0, output=arr) return arr def move_nansum_filter(arr, window, axis=-1): """ Moving sum (ignoring NaNs) along specified axis using the filter method. Parameters ---------- arr : array_like Input array. window : int The number of elements in the moving window. axis : int, optional The axis over which to perform the moving sum. By default the moving sum is taken over the last axis (-1). Returns ------- y : ndarray The moving sum (ignoring NaNs) of the input array along the specified axis.(A window with all NaNs returns NaN for the window sum.) The output has the same shape as the input. Notes ----- The calculation of the sums uses scipy.ndimage.convolve1d. Examples -------- >>> from bottleneck.slow.move import move_nansum_filter >>> arr = np.array([1, 2, np.nan, 4, 5, 6, 7]) >>> move_nansum_filter(arr, window=2, axis=0) array([ NaN, 3., 2., 4., 9., 11., 13.]) """ arr = np.array(arr, copy=False) global convolve1d if convolve1d is None: try: from scipy.ndimage import convolve1d except ImportError: raise ValueError("'filter' method requires SciPy.") if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") arr = arr.astype(float) nrr = np.isnan(arr) arr[nrr] = 0 nrr = nrr.astype(int) w = np.ones(window, dtype=int) x0 = (1 - window) // 2 convolve1d(arr, w, axis=axis, mode='constant', cval=np.nan, origin=x0, output=arr) convolve1d(nrr, w, axis=axis, mode='constant', cval=0, origin=x0, output=nrr) arr[nrr == window] = np.nan return arr # MEAN ------------------------------------------------------------------- def move_mean(arr, window, axis=-1, method='loop'): """ Slow move_mean for unaccelerated ndim/dtype combinations. Parameters ---------- arr : array_like Input array. window : int The number of elements in the moving window. axis : int, optional The axis over which to perform the moving mean. By default the moving mean is taken over the last axis (-1). method : str, optional The following moving window methods are available: ========== ===================================== 'filter' scipy.ndimage.convolve1d 'strides' strides tricks 'loop' brute force python loop (default) ========== ===================================== Returns ------- y : ndarray The moving mean of the input array along the specified axis. The output has the same shape as the input. Examples -------- >>> arr = np.array([1, 2, 3, 4]) >>> bn.slow.move_mean(arr, window=2, axis=0) array([ NaN, 1.5, 2.5, 3.5]) """ arr = np.array(arr, copy=False) if method == 'filter': y = move_mean_filter(arr, window, axis=axis) elif method == 'strides': y = move_func_strides(np.mean, arr, window, axis=axis) elif method == 'loop': y = move_func_loop(np.mean, arr, window, axis=axis) else: msg = "`method` must be 'filter', 'strides', or 'loop'." raise ValueError(msg) if y.dtype != arr.dtype: if issubclass(arr.dtype.type, np.inexact): y = y.astype(arr.dtype) return y def move_nanmean(arr, window, axis=-1, method='loop'): """ Slow move_nanmean for unaccelerated ndim/dtype combinations. Parameters ---------- arr : array_like Input array. window : int The number of elements in the moving window. axis : int, optional The axis over which to perform the moving mean. By default the moving mean is taken over the last axis (-1). method : str, optional The following moving window methods are available: ========== ===================================== 'filter' scipy.ndimage.convolve1d 'strides' strides tricks 'loop' brute force python loop (default) ========== ===================================== Returns ------- y : ndarray The moving mean of the input array along the specified axis, ignoring NaNs. (A window with all NaNs returns NaN for the window mean.) The output has the same shape as the input. Examples -------- >>> arr = np.array([1, 2, np.nan, 4]) >>> bn.slow.move_nanmean(arr, window=2, axis=0) array([ NaN, 1.5, 2. , 4. ]) """ arr = np.array(arr, copy=False) if method == 'filter': y = move_nanmean_filter(arr, window, axis=axis) elif method == 'strides': y = move_func_strides(bn.slow.nanmean, arr, window, axis=axis) elif method == 'loop': y = move_func_loop(bn.slow.nanmean, arr, window, axis=axis) else: msg = "`method` must be 'filter', 'strides', or 'loop'." raise ValueError(msg) if y.dtype != arr.dtype: if issubclass(arr.dtype.type, np.inexact): y = y.astype(arr.dtype) return y def move_mean_filter(arr, window, axis=-1): "Moving window mean implemented with a filter." arr = np.array(arr, copy=False) global convolve1d if convolve1d is None: try: from scipy.ndimage import convolve1d except ImportError: raise ValueError("'filter' method requires SciPy.") if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") arr = arr.astype(float) w = np.empty(window) w.fill(1.0 / window) x0 = (1 - window) // 2 convolve1d(arr, w, axis=axis, mode='constant', cval=np.nan, origin=x0, output=arr) return arr def move_nanmean_filter(arr, window, axis=-1): "Moving window nanmean implemented with a filter." arr = np.array(arr, copy=False) global convolve1d if convolve1d is None: try: from scipy.ndimage import convolve1d except ImportError: raise ValueError("'filter' method requires SciPy.") if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") arr = arr.astype(float) nrr = np.isnan(arr) arr[nrr] = 0 nrr = nrr.astype(int) w = np.ones(window, dtype=int) x0 = (1 - window) // 2 convolve1d(arr, w, axis=axis, mode='constant', cval=np.nan, origin=x0, output=arr) convolve1d(nrr, w, axis=axis, mode='constant', cval=0, origin=x0, output=nrr) arr /= (window - nrr) arr[nrr == window] = np.nan return arr # VAR ----------------------------------------------------------------------- def move_var(arr, window, axis=-1, method='loop', ddof=0): """ Slow move_var for unaccelerated ndim/dtype combinations. Parameters ---------- arr : array_like Input array. window : int The number of elements in the moving window. axis : int, optional The axis over which to perform the moving variance. By default the moving variance is taken over the last axis (-1). method : str, optional The following moving window methods are available: ========== ===================================== 'filter' scipy.ndimage.convolve1d 'strides' strides tricks 'loop' brute force python loop (default) ========== ===================================== Returns ------- y : ndarray The moving variance of the input array along the specified axis. The output has the same shape as the input. Examples -------- >>> arr = np.array([1, 2, 3, 4]) >>> bn.slow.move_var(arr, window=2, axis=0) array([ NaN, 0.25, 0.25, 0.25]) """ arr = np.array(arr, copy=False) if ddof != 0: raise ValueError("`ddof` must be zero for unaccelerated input.") if method == 'filter': y = move_var_filter(arr, window, axis=axis) elif method == 'strides': y = move_func_strides(np.var, arr, window, axis=axis) elif method == 'loop': y = move_func_loop(np.var, arr, window, axis=axis) else: msg = "`method` must be 'filter', 'strides', or 'loop'." raise ValueError(msg) if y.dtype != arr.dtype: if issubclass(arr.dtype.type, np.inexact): y = y.astype(arr.dtype) return y def move_nanvar(arr, window, axis=-1, method='loop', ddof=0): """ Slow move_nanvar for unaccelerated ndim/dtype combinations. Parameters ---------- arr : array_like Input array. window : int The number of elements in the moving window. axis : int, optional The axis over which to perform the moving variance. By default the moving variance is taken over the last axis (-1). method : str, optional The following moving window methods are available: ========== ===================================== 'filter' scipy.ndimage.convolve1d 'strides' strides tricks 'loop' brute force python loop (default) ========== ===================================== Returns ------- y : ndarray The moving variance of the input array along the specified axis, ignoring NaNs. (A window with all NaNs returns NaN for the window variance.) The output has the same shape as the input. Examples -------- >>> arr = np.array([1, 2, np.nan, 4, 5]) >>> bn.slow.move_nanvar(arr, window=3, axis=0) array([ NaN, NaN, 0.25, 1. , 0.25]) """ arr = np.array(arr, copy=False) if ddof != 0: raise ValueError("`ddof` must be zero for unaccelerated input.") if method == 'filter': y = move_nanvar_filter(arr, window, axis=axis) elif method == 'strides': y = move_func_strides(bn.slow.nanvar, arr, window, axis=axis) elif method == 'loop': y = move_func_loop(bn.slow.nanvar, arr, window, axis=axis) else: msg = "`method` must be 'filter', 'strides', or 'loop'." raise ValueError(msg) if y.dtype != arr.dtype: if issubclass(arr.dtype.type, np.inexact): y = y.astype(arr.dtype) return y def move_var_filter(arr, window, axis=-1): "Moving window variance implemented with a filter." arr = np.array(arr, copy=False) global convolve1d if convolve1d is None: try: from scipy.ndimage import convolve1d except ImportError: raise ValueError("'filter' method requires SciPy.") if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") arr = arr.astype(float) w = np.empty(window) w.fill(1.0 / window) x0 = (1 - window) // 2 y = convolve1d(arr, w, axis=axis, mode='constant', cval=np.nan, origin=x0) y *= y arr *= arr convolve1d(arr, w, axis=axis, mode='constant', cval=np.nan, origin=x0, output=arr) arr -= y return arr def move_nanvar_filter(arr, window, axis=-1): "Moving window variance ignoring NaNs, implemented with a filter." arr = np.array(arr, copy=False) global convolve1d if convolve1d is None: try: from scipy.ndimage import convolve1d except ImportError: raise ValueError("'filter' method requires SciPy.") if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") arr = arr.astype(float) nrr = np.isnan(arr) arr[nrr] = 0 nrr = nrr.astype(int) w = np.ones(window, dtype=int) x0 = (1 - window) // 2 convolve1d(nrr, w, axis=axis, mode='constant', cval=0, origin=x0, output=nrr) y = convolve1d(arr, w, axis=axis, mode='constant', cval=np.nan, origin=x0) y /= (window - nrr) y *= y arr *= arr convolve1d(arr, w, axis=axis, mode='constant', cval=np.nan, origin=x0, output=arr) arr /= (window - nrr) arr -= y arr[nrr == window] = np.nan return arr # STD ----------------------------------------------------------------------- def move_std(arr, window, axis=-1, method='loop', ddof=0): """ Moving window standard deviation along the specified axis. Parameters ---------- arr : array_like Input array. window : int The number of elements in the moving window. axis : int, optional The axis over which to perform the moving standard deviation. By default the moving standard deviation is taken over the last axis (-1). method : str, optional The following moving window methods are available: ========== ===================================== 'filter' scipy.ndimage.convolve1d 'strides' strides tricks 'loop' brute force python loop (default) ========== ===================================== Returns ------- y : ndarray The moving standard deviation of the input array along the specified axis. The output has the same shape as the input. Examples -------- >>> arr = np.array([1, 2, 3, 4]) >>> bn.slow.move_std(arr, window=2) array([ NaN, 0.5, 0.5, 0.5]) """ arr = np.array(arr, copy=False) if ddof != 0: raise ValueError("`ddof` must be zero for unaccelerated input.") if method == 'filter': y = move_std_filter(arr, window, axis=axis) elif method == 'strides': y = move_func_strides(np.std, arr, window, axis=axis) elif method == 'loop': y = move_func_loop(np.std, arr, window, axis=axis) else: msg = "`method` must be 'filter', 'strides', or 'loop'." raise ValueError(msg) if y.dtype != arr.dtype: if issubclass(arr.dtype.type, np.inexact): y = y.astype(arr.dtype) return y def move_nanstd(arr, window, axis=-1, method='loop', ddof=0): """ Moving window standard deviation along the specified axis, ignoring NaNs. Parameters ---------- arr : array_like Input array. window : int The number of elements in the moving window. axis : int, optional The axis over which to perform the moving standard deviation. By default the moving standard deviation is taken over the last axis (-1). method : str, optional The following moving window methods are available: ========== ===================================== 'filter' scipy.ndimage.convolve1d 'strides' strides tricks 'loop' brute force python loop (default) ========== ===================================== Returns ------- y : ndarray The moving standard deviation of the input array along the specified axis, ignoring NaNs. (A window with all NaNs returns NaN for the window standard deviation.) The output has the same shape as the input. Examples -------- >>> arr = np.array([1, 2, np.nan, 4, 5]) >>> bn.slow.move_nanstd(arr, window=3) array([ NaN, NaN, 0.5, 1. , 0.5]) """ arr = np.array(arr, copy=False) if ddof != 0: raise ValueError("`ddof` must be zero for unaccelerated input.") if method == 'filter': y = move_nanstd_filter(arr, window, axis=axis) elif method == 'strides': y = move_func_strides(bn.slow.nanstd, arr, window, axis=axis) elif method == 'loop': y = move_func_loop(bn.slow.nanstd, arr, window, axis=axis) else: msg = "`method` must be 'filter', 'strides', or 'loop'." raise ValueError(msg) if y.dtype != arr.dtype: if issubclass(arr.dtype.type, np.inexact): y = y.astype(arr.dtype) return y def move_std_filter(arr, window, axis=-1): "Moving window standard deviation implemented with a filter." arr = np.array(arr, copy=False) if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") y = move_var_filter(arr, window, axis=axis) np.sqrt(y, y) return y def move_nanstd_filter(arr, window, axis=-1): "Moving window standard deviation ignoring NaNs, implemented with filter." arr = np.array(arr, copy=False) if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") y = move_nanvar_filter(arr, window, axis=axis) np.sqrt(y, y) return y # MIN ----------------------------------------------------------------------- def move_min(arr, window, axis=-1, method='loop'): """ Slow move_min for unaccelerated ndim/dtype combinations. Parameters ---------- arr : array_like Input array. window : int The number of elements in the moving window. axis : int, optional The axis over which to perform the moving minimum. By default the moving minimum is taken over the last axis (-1). method : str, optional The following moving window methods are available: ========== ========================================= 'filter' scipy.ndimage.minimum_filter1d 'strides' strides tricks 'loop' brute force python loop (default) ========== ========================================= Returns ------- y : ndarray The moving minimum of the input array along the specified axis. The output has the same shape as the input. Examples -------- >>> arr = np.array([1, 2, 3, 4]) >>> bn.slow.move_min(arr, window=2) array([ NaN, 1., 2., 3.]) """ if method == 'filter': y = move_min_filter(arr, window, axis=axis) elif method == 'strides': y = move_func_strides(np.min, arr, window, axis=axis) elif method == 'loop': y = move_func_loop(np.min, arr, window, axis=axis) else: raise ValueError("`method` must be 'filter', 'strides', or 'loop'.") return y def move_nanmin(arr, window, axis=-1, method='loop'): """ Slow move_nanmin for unaccelerated ndim/dtype combinations. Parameters ---------- arr : array_like Input array. window : int The number of elements in the moving window. axis : int, optional The axis over which to perform the moving minimum. By default the moving minimum is taken over the last axis (-1). method : str, optional The following moving window methods are available: ========== ========================================= 'filter' scipy.ndimage.minimum_filter1d 'strides' strides tricks 'loop' brute force python loop (default) ========== ========================================= Returns ------- y : ndarray The moving minimum of the input array along the specified axis, ignoring NaNs. (A window with all NaNs returns NaN for the window minimum.) The output has the same shape as the input. Examples -------- >>> arr = np.array([1, 2, np.nan, 4, 5]) >>> bn.slow.move_nanmin(arr, window=2) array([ NaN, 1., 2., 4., 4.]) """ if method == 'filter': y = move_nanmin_filter(arr, window, axis=axis) elif method == 'strides': y = move_nanmin_strides(arr, window, axis=axis) elif method == 'loop': y = move_nanmin_loop(arr, window, axis=axis) else: raise ValueError("`method` must be 'filter', 'strides', or 'loop'.") return y def move_min_filter(arr, window, axis=-1): "Moving window minimium implemented with a filter." arr = np.array(arr, copy=False) global minimum_filter1d if minimum_filter1d is None: try: from scipy.ndimage import minimum_filter1d except ImportError: raise ValueError("'filter' method requires SciPy.") if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") y = arr.astype(float) x0 = (window - 1) // 2 minimum_filter1d(y, window, axis=axis, mode='constant', cval=np.nan, origin=x0, output=y) return y def move_nanmin_filter(arr, window, axis=-1): "Moving window minimium ignoring NaNs, implemented with a filter." global minimum_filter1d, convolve1d arr = np.array(arr, copy=False) if minimum_filter1d is None: try: from scipy.ndimage import minimum_filter1d except ImportError: raise ValueError("'filter' method requires SciPy.") if convolve1d is None: try: from scipy.ndimage import convolve1d except ImportError: raise ValueError("'filter' method requires SciPy.") if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") arr = arr.astype(float) nrr = np.isnan(arr) arr[nrr] = np.inf x0 = (window - 1) // 2 minimum_filter1d(arr, window, axis=axis, mode='constant', cval=np.nan, origin=x0, output=arr) w = np.ones(window, dtype=int) nrr = nrr.astype(int) x0 = (1 - window) // 2 convolve1d(nrr, w, axis=axis, mode='constant', cval=0, origin=x0, output=nrr) arr[nrr == window] = np.nan return arr def move_nanmin_loop(arr, window, axis=-1): "Moving window minimium ignoring NaNs, implemented with a python loop." arr = np.array(arr, copy=False) if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") arr = arr.astype(float) nrr = np.isnan(arr) arr[nrr] = np.inf y = move_func_loop(np.min, arr, window, axis=axis) m = move_func_loop(np.sum, nrr.astype(int), window, axis=axis) y[m == window] = np.nan return y def move_nanmin_strides(arr, window, axis=-1): "Moving window minimium ignoring NaNs, implemented with stides tricks." arr = np.array(arr, copy=False) if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") arr = arr.astype(float) nrr = np.isnan(arr) arr[nrr] = np.inf y = move_func_strides(np.min, arr, window, axis=axis) m = move_func_strides(np.sum, nrr.astype(int), window, axis=axis) y[m == window] = np.nan return y # MAX ----------------------------------------------------------------------- def move_max(arr, window, axis=-1, method='loop'): """ Slow move_max for unaccelerated ndim/dtype combinations. Parameters ---------- arr : array_like Input array. window : int The number of elements in the moving window. axis : int, optional The axis over which to perform the moving maximum. By default the moving maximum is taken over the last axis (-1). method : str, optional The following moving window methods are available: ========== ========================================= 'filter' scipy.ndimage.minimum_filter1d 'strides' strides tricks 'loop' brute force python loop (default) ========== ========================================= Returns ------- y : ndarray The moving maximum of the input array along the specified axis. The output has the same shape as the input. Examples -------- >>> arr = np.array([1, 2, 3, 4]) >>> bn.slow.move_max(arr, window=2) array([ NaN, 2., 3., 4.]) """ if method == 'filter': y = move_max_filter(arr, window, axis=axis) elif method == 'strides': y = move_func_strides(np.max, arr, window, axis=axis) elif method == 'loop': y = move_func_loop(np.max, arr, window, axis=axis) else: raise ValueError("`method` must be 'filter', 'strides', or 'loop'.") return y def move_nanmax(arr, window, axis=-1, method='loop'): """ Slow move_nanmax for unaccelerated ndim/dtype combinations, ignoring NaNs. Parameters ---------- arr : array_like Input array. window : int The number of elements in the moving window. axis : int, optional The axis over which to perform the moving maximum. By default the moving maximum is taken over the last axis (-1). method : str, optional The following moving window methods are available: ========== ========================================= 'filter' scipy.ndimage.maximum_filter1d 'strides' strides tricks 'loop' brute force python loop (default) ========== ========================================= Returns ------- y : ndarray The moving maximum of the input array along the specified axis, ignoring NaNs. (A window with all NaNs returns NaN for the window maximum.) The output has the same shape as the input. Examples -------- >>> arr = np.array([1, 2, np.nan, 4, 5]) >>> bn.slow.move_nanmax(arr, window=2) array([ NaN, 2., 2., 4., 5.]) """ if method == 'filter': y = move_nanmax_filter(arr, window, axis=axis) elif method == 'strides': y = move_nanmax_strides(arr, window, axis=axis) elif method == 'loop': y = move_nanmax_loop(arr, window, axis=axis) else: raise ValueError("`method` must be 'filter', 'strides', or 'loop'.") return y def move_max_filter(arr, window, axis=-1): "Moving window maximium implemented with a filter." arr = np.array(arr, copy=False) global maximum_filter1d if maximum_filter1d is None: try: from scipy.ndimage import maximum_filter1d except ImportError: raise ValueError("'filter' method requires SciPy.") if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") y = arr.astype(float) x0 = (window - 1) // 2 maximum_filter1d(y, window, axis=axis, mode='constant', cval=np.nan, origin=x0, output=y) return y def move_nanmax_filter(arr, window, axis=-1): "Moving window maximium ignoring NaNs, implemented with a filter." arr = np.array(arr, copy=False) global maximum_filter1d, convolve1d if maximum_filter1d is None: try: from scipy.ndimage import maximum_filter1d except ImportError: raise ValueError("'filter' method requires SciPy.") if convolve1d is None: try: from scipy.ndimage import convolve1d except ImportError: raise ValueError("'filter' method requires SciPy.") if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") arr = arr.astype(float) nrr = np.isnan(arr) arr[nrr] = -np.inf x0 = (window - 1) // 2 maximum_filter1d(arr, window, axis=axis, mode='constant', cval=np.nan, origin=x0, output=arr) w = np.ones(window, dtype=int) nrr = nrr.astype(int) x0 = (1 - window) // 2 convolve1d(nrr, w, axis=axis, mode='constant', cval=0, origin=x0, output=nrr) arr[nrr == window] = np.nan return arr def move_nanmax_loop(arr, window, axis=-1): "Moving window maximium ignoring NaNs, implemented with a python loop." arr = np.array(arr, copy=False) if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") arr = arr.astype(float) nrr = np.isnan(arr) arr[nrr] = -np.inf y = move_func_loop(np.max, arr, window, axis=axis) m = move_func_loop(np.sum, nrr.astype(int), window, axis=axis) y[m == window] = np.nan return y def move_nanmax_strides(arr, window, axis=-1): "Moving window maximium ignoring NaNs, implemented with stides tricks." arr = np.array(arr, copy=False) if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") arr = arr.astype(float) nrr = np.isnan(arr) arr[nrr] = -np.inf y = move_func_strides(np.max, arr, window, axis=axis) m = move_func_strides(np.sum, nrr.astype(int), window, axis=axis) y[m == window] = np.nan return y # MEDIAN -------------------------------------------------------------------- def move_median(arr, window, axis=-1, method='loop'): """ Slow moving window median along the specified axis. Parameters ---------- arr : array_like Input array. window : int The number of elements in the moving window. axis : int, optional The axis over which to perform the moving median. By default the moving median is taken over the last axis (-1). method : str, optional The following moving window methods are available: ========== ===================================== 'loop' brute force python loop (default) 'strides' strides tricks ========== ===================================== Returns ------- y : ndarray The moving median of the input array along the specified axis. The output has the same shape as the input. Examples -------- >>> arr = np.array([1, 2, 3, 4, 5]) >>> bn.move_median(arr, window=2) array([ NaN, 1.5, 2.5, 3.5, 4.5]) """ arr = np.array(arr, copy=False) if method == 'strides': y = move_func_strides(np.median, arr, window, axis=axis) elif method == 'loop': y = move_func_loop(np.median, arr, window, axis=axis) else: msg = "`method` must be 'strides' or 'loop'." raise ValueError(msg) if y.dtype != arr.dtype: if issubclass(arr.dtype.type, np.inexact): y = y.astype(arr.dtype) return y # GENERAL -------------------------------------------------------------------- def move_func(func, arr, window, axis=-1, method='loop', **kwargs): """ Generic moving window function along the specified axis. Parameters ---------- func : function A reducing function such as np.sum, np.max, or np.median that takes a Numpy array and axis and, optionally, key word arguments as input. arr : array_like Input array. window : int The number of elements in the moving window. axis : int, optional The axis over which to evaluate `func`. By default the window moves along the last axis (-1). method : str, optional The following moving window methods are available: ========== ===================================== 'loop' brute force python loop (default) 'strides' strides tricks ========== ===================================== Returns ------- y : ndarray A moving window evaluation of `func` along the specified axis of the input array. The output has the same shape as the input. Examples -------- >>> arr = np.arange(4) >>> bn.slow.move_func(np.sum, arr, window=2) array([ NaN, 1., 3., 5.]) which give the same result as: >>> bn.slow.move_sum(arr, window=2) array([ NaN, 1., 3., 5.]) """ if method == 'strides': y = move_func_strides(func, arr, window, axis=axis, **kwargs) elif method == 'loop': y = move_func_loop(func, arr, window, axis=axis) else: msg = "`method` must be 'strides' or 'loop'." raise ValueError(msg) return y def move_func_loop(func, arr, window, axis=-1, **kwargs): "Generic moving window function implemented with a python loop." arr = np.array(arr, copy=False) if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") y = np.empty(arr.shape) y.fill(np.nan) idx1 = [slice(None)] * arr.ndim idx2 = list(idx1) for i in range(window - 1, arr.shape[axis]): idx1[axis] = slice(i + 1 - window, i + 1) idx2[axis] = i y[idx2] = func(arr[idx1], axis=axis, **kwargs) return y def move_func_strides(func, arr, window, axis=-1, **kwargs): "Generic moving window function implemented with strides." arr = np.array(arr, copy=False) if axis is None: raise ValueError("An `axis` value of None is not supported.") if window < 1: raise ValueError("`window` must be at least 1.") if window > arr.shape[axis]: raise ValueError("`window` is too long.") ndim = arr.ndim idx = range(ndim) axis = idx[axis] arrshape0 = tuple(arr.shape) if axis >= ndim: raise IndexError("`axis` is out of range.") strides = arr.strides num_windows = arr.shape[axis] - window + 1 shape = arr.shape[:axis] + (num_windows, window) + arr.shape[axis + 1:] strides = (strides[:axis] + (strides[axis], strides[axis]) + strides[axis + 1:]) z = np.lib.stride_tricks.as_strided(arr, shape=shape, strides=strides) y = func(z, axis=(axis + 1), **kwargs) ynan = np.empty(arrshape0) ynan.fill(np.nan) index = [slice(None)] * ndim index[axis] = slice(window - 1, None) ynan[index] = y return ynan

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null

0

7

0c08e01c3ccb1e8541e31133bfa2c64c0f8a1605

10,144

py

Python

seqgra/learner/bayes/bayeslearner.py

gifford-lab/seqgra

3c7547878ecda4c00572746b8a07e0d614c9dbef

[ "MIT" ]

null

seqgra/learner/bayes/bayeslearner.py

gifford-lab/seqgra

3c7547878ecda4c00572746b8a07e0d614c9dbef

[ "MIT" ]

null

seqgra/learner/bayes/bayeslearner.py

gifford-lab/seqgra

3c7547878ecda4c00572746b8a07e0d614c9dbef

[ "MIT" ]

2

2021-06-14T20:27:40.000Z

2021-06-14T20:29:29.000Z

"""MIT - CSAIL - Gifford Lab - seqgra TensorFlow Keras learners @author: Konstantin Krismer """ from typing import Any, List, Optional from seqgra import ModelSize from seqgra.learner import DNAMultiClassClassificationLearner from seqgra.learner import DNAMultiLabelClassificationLearner from seqgra.learner import ProteinMultiClassClassificationLearner from seqgra.learner import ProteinMultiLabelClassificationLearner from seqgra.learner.bayes import BayesOptimalHelper from seqgra.model import ModelDefinition class BayesOptimalDNAMultiClassClassificationLearner( DNAMultiClassClassificationLearner): def __init__(self, model_definition: ModelDefinition, data_dir: str, output_dir: str, validate_data: bool = True, silent: bool = False) -> None: super().__init__(model_definition, data_dir, output_dir, validate_data, silent=silent) def create_model(self) -> None: BayesOptimalHelper.create_model(self) def print_model_summary(self): BayesOptimalHelper.print_model_summary(self) def set_seed(self) -> None: BayesOptimalHelper.set_seed(self) def _train_model(self, file_name_train: Optional[str] = None, file_name_val: Optional[str] = None, x_train: Optional[List[str]] = None, y_train: Optional[List[str]] = None, x_val: Optional[List[str]] = None, y_val: Optional[List[str]] = None) -> None: BayesOptimalHelper.train_model(self) def evaluate_model(self, file_name: Optional[str] = None, x: Optional[List[str]] = None, y: Optional[List[str]] = None): if x is not None and y is not None: pass elif file_name is not None: x, y = self.parse_examples_data(file_name) else: raise Exception("specify either file_name or x, y") x = self.encode_x(x) y = self.encode_y(y) return BayesOptimalHelper.evaluate_model(self, x, y) def predict(self, file_name: Optional[str] = None, x: Optional[Any] = None, encode: bool = True): if x is not None: if encode: x = self.encode_x(x) elif file_name is not None: x, _ = self.parse_examples_data(file_name) x = self.encode_x(x) else: raise Exception("specify either file_name or x") return BayesOptimalHelper.predict(self, x, self.silent) def save_model(self, file_name: Optional[str] = None): pass def write_session_info(self) -> None: BayesOptimalHelper.write_session_info(self) def load_model(self, file_name: Optional[str] = None): self.create_model() def get_num_params(self) -> ModelSize: return 0 class BayesOptimalDNAMultiLabelClassificationLearner( DNAMultiLabelClassificationLearner): def __init__(self, model_definition: ModelDefinition, data_dir: str, output_dir: str, validate_data: bool = True, silent: bool = False) -> None: super().__init__(model_definition, data_dir, output_dir, validate_data, silent=silent) def create_model(self) -> None: BayesOptimalHelper.create_model(self) def print_model_summary(self): BayesOptimalHelper.print_model_summary(self) def set_seed(self) -> None: BayesOptimalHelper.set_seed(self) def _train_model(self, file_name_train: Optional[str] = None, file_name_val: Optional[str] = None, x_train: Optional[List[str]] = None, y_train: Optional[List[str]] = None, x_val: Optional[List[str]] = None, y_val: Optional[List[str]] = None) -> None: BayesOptimalHelper.train_model(self) def evaluate_model(self, file_name: Optional[str] = None, x: Optional[List[str]] = None, y: Optional[List[str]] = None): if x is not None and y is not None: pass elif file_name is not None: x, y = self.parse_examples_data(file_name) else: raise Exception("specify either file_name or x, y") x = self.encode_x(x) y = self.encode_y(y) return BayesOptimalHelper.evaluate_model(self, x, y) def predict(self, file_name: Optional[str] = None, x: Optional[Any] = None, encode: bool = True): if x is not None: if encode: x = self.encode_x(x) elif file_name is not None: x, _ = self.parse_examples_data(file_name) x = self.encode_x(x) else: raise Exception("specify either file_name or x") return BayesOptimalHelper.predict(self, x, self.silent) def save_model(self, file_name: Optional[str] = None): pass def write_session_info(self) -> None: BayesOptimalHelper.write_session_info(self) def load_model(self, file_name: Optional[str] = None): self.create_model() def get_num_params(self) -> ModelSize: return 0 class BayesOptimalProteinMultiClassClassificationLearner( ProteinMultiClassClassificationLearner): def __init__(self, model_definition: ModelDefinition, data_dir: str, output_dir: str, validate_data: bool = True, silent: bool = False) -> None: super().__init__(model_definition, data_dir, output_dir, validate_data, silent=silent) def create_model(self) -> None: BayesOptimalHelper.create_model(self) def print_model_summary(self): BayesOptimalHelper.print_model_summary(self) def set_seed(self) -> None: BayesOptimalHelper.set_seed(self) def _train_model(self, file_name_train: Optional[str] = None, file_name_val: Optional[str] = None, x_train: Optional[List[str]] = None, y_train: Optional[List[str]] = None, x_val: Optional[List[str]] = None, y_val: Optional[List[str]] = None) -> None: BayesOptimalHelper.train_model(self) def evaluate_model(self, file_name: Optional[str] = None, x: Optional[List[str]] = None, y: Optional[List[str]] = None): if x is not None and y is not None: pass elif file_name is not None: x, y = self.parse_examples_data(file_name) else: raise Exception("specify either file_name or x, y") x = self.encode_x(x) y = self.encode_y(y) return BayesOptimalHelper.evaluate_model(self, x, y) def predict(self, file_name: Optional[str] = None, x: Optional[Any] = None, encode: bool = True): if x is not None: if encode: x = self.encode_x(x) elif file_name is not None: x, _ = self.parse_examples_data(file_name) x = self.encode_x(x) else: raise Exception("specify either file_name or x") return BayesOptimalHelper.predict(self, x, self.silent) def save_model(self, file_name: Optional[str] = None): pass def write_session_info(self) -> None: BayesOptimalHelper.write_session_info(self) def load_model(self, file_name: Optional[str] = None): self.create_model() def get_num_params(self) -> ModelSize: return 0 class BayesOptimalProteinMultiLabelClassificationLearner( ProteinMultiLabelClassificationLearner): def __init__(self, model_definition: ModelDefinition, data_dir: str, output_dir: str, validate_data: bool = True, silent: bool = False) -> None: super().__init__(model_definition, data_dir, output_dir, validate_data, silent=silent) def create_model(self) -> None: BayesOptimalHelper.create_model(self) def print_model_summary(self): BayesOptimalHelper.print_model_summary(self) def set_seed(self) -> None: BayesOptimalHelper.set_seed(self) def _train_model(self, file_name_train: Optional[str] = None, file_name_val: Optional[str] = None, x_train: Optional[List[str]] = None, y_train: Optional[List[str]] = None, x_val: Optional[List[str]] = None, y_val: Optional[List[str]] = None) -> None: BayesOptimalHelper.train_model(self) def evaluate_model(self, file_name: Optional[str] = None, x: Optional[List[str]] = None, y: Optional[List[str]] = None): if x is not None and y is not None: pass elif file_name is not None: x, y = self.parse_examples_data(file_name) else: raise Exception("specify either file_name or x, y") x = self.encode_x(x) y = self.encode_y(y) return BayesOptimalHelper.evaluate_model(self, x, y) def predict(self, file_name: Optional[str] = None, x: Optional[Any] = None, encode: bool = True): if x is not None: if encode: x = self.encode_x(x) elif file_name is not None: x, _ = self.parse_examples_data(file_name) x = self.encode_x(x) else: raise Exception("specify either file_name or x") return BayesOptimalHelper.predict(self, x, self.silent) def save_model(self, file_name: Optional[str] = None): pass def write_session_info(self) -> None: BayesOptimalHelper.write_session_info(self) def load_model(self, file_name: Optional[str] = None): self.create_model() def get_num_params(self) -> ModelSize: return 0

35.71831

79

0.600946

1,176

10,144

4.962585

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0

0.000571

0.309937

10,144

283

80

35.844523

0.833143

0.008872

0

0.927273

0

0.024286

0

1

0.2

false

0.036364

0.018182

0.309091

0.036364

0

null

0

1

0

1

0

null

0

7

0c146bca4f6cdebf19d5624ca3ea24ba563e4507

3,634

py

Python

tests/core/test_jwt.py

bossjones/ultron8

45db73d32542a844570d44bc83defa935e15803f

[ "Apache-2.0", "MIT" ]

null

tests/core/test_jwt.py

bossjones/ultron8

45db73d32542a844570d44bc83defa935e15803f

[ "Apache-2.0", "MIT" ]

43

2019-06-01T23:08:32.000Z

2022-02-07T22:24:53.000Z

tests/core/test_jwt.py

bossjones/ultron8

45db73d32542a844570d44bc83defa935e15803f

[ "Apache-2.0", "MIT" ]

null

import datetime from datetime import timedelta import logging from typing import Tuple # import jwt as pyjwt from freezegun import freeze_time from jose import jwt as josejwt import pytest from sqlalchemy.orm import Session import ultron8 from ultron8.api import crud, settings from ultron8.api.core import jwt from tests.conftest import fixtures_path logger = logging.getLogger(__name__) @freeze_time("2012-01-14 03:21:34", tz_offset=-4) @pytest.mark.jwtonly @pytest.mark.unittest class TestCreateAccessToken(object): # def test_create_access_token( # self, first_superuser_username_and_password_fixtures, db # ): # username, password = first_superuser_username_and_password_fixtures # access_token_expires = timedelta(minutes=settings.ACCESS_TOKEN_EXPIRE_MINUTES) # user = crud.user.authenticate(db, email=username, password=password) # a_token = jwt.create_access_token( # data={"user_id": user.id}, expires_delta=access_token_expires # ) # expire_expected = datetime.datetime.utcnow() + access_token_expires # test_data = {"user_id": user.id, "exp": expire_expected, "sub": "access"} # expected_token = pyjwt.encode(test_data, settings.SECRET_KEY, algorithm="HS256") # assert a_token == expected_token # def test_create_access_token_without_timedelta( # self, first_superuser_username_and_password_fixtures, db # ): # username, password = first_superuser_username_and_password_fixtures # user = crud.user.authenticate(db, email=username, password=password) # a_token = jwt.create_access_token(data={"user_id": user.id}) # expire_expected = datetime.datetime.utcnow() + timedelta(minutes=15) # test_data = {"user_id": user.id, "exp": expire_expected, "sub": "access"} # expected_token = pyjwt.encode(test_data, settings.SECRET_KEY, algorithm="HS256") # assert a_token == expected_token def test_create_access_token2( self, first_superuser_username_and_password_fixtures: Tuple[str, str], db: Session, ) -> None: username, password = first_superuser_username_and_password_fixtures FIXTURE_ACCESS_TOKEN_EXPIRE_MINUTES = ( 60 * 24 * 2 ) # 60 minutes * 24 hours * 2 days = 2 days access_token_expires = timedelta(minutes=FIXTURE_ACCESS_TOKEN_EXPIRE_MINUTES) user = crud.user.authenticate(db, email=username, password=password) a_token = jwt.create_access_token(user.id, expires_delta=access_token_expires) expire_expected = datetime.datetime.utcnow() + access_token_expires test_data = {"exp": expire_expected, "sub": str(user.id)} expected_token = josejwt.encode( test_data, settings.SECRET_KEY, algorithm="HS256" ) assert a_token == expected_token def test_create_access_token_without_timedelta2( self, first_superuser_username_and_password_fixtures: Tuple[str, str], db: Session, ) -> None: username, password = first_superuser_username_and_password_fixtures user = crud.user.authenticate(db, email=username, password=password) a_token = jwt.create_access_token(user.id) expire_expected = datetime.datetime.utcnow() + timedelta( minutes=settings.ACCESS_TOKEN_EXPIRE_MINUTES ) test_data = {"exp": expire_expected, "sub": str(user.id)} expected_token = josejwt.encode( test_data, settings.SECRET_KEY, algorithm="HS256" ) assert a_token == expected_token

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0.698954

436

3,634

5.504587

0.206422

0.077917

0.073333

0.083333

0.800417

0.752917

0.729583

0.68625

0

0.01569

0.210787

3,634

110

91

33.036364

0.82113

0.375069

0

0.392157

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1

0.039216

false

0.117647

0.235294

0

0.294118

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null

0

1

0

null

0

1

0

7

0c1c4aec3a8c53cda2f66cb238eab93fcd4abf54

1,331

py

Python

src/numpy_change.py

benchoi93/DeepMapMatching

ac87934d909de8fb5a635001f92b4e93cb69fdd3

[ "MIT" ]

1

2021-12-10T08:52:15.000Z

src/numpy_change.py

safarzadeh-reza/DeepMapMatching

ac87934d909de8fb5a635001f92b4e93cb69fdd3

[ "MIT" ]

null

src/numpy_change.py

safarzadeh-reza/DeepMapMatching

ac87934d909de8fb5a635001f92b4e93cb69fdd3

[ "MIT" ]

1

2022-01-10T17:39:02.000Z

# %% import numpy as np raw_target = np.load("../data/Label_0.npy") raw_target = raw_target.reshape(raw_target.shape[0], raw_target.shape[1]) padding = -1 temp_input = np.array([]) length_batch = raw_target.shape[0] length_len = raw_target.shape[1] for i in range(length_batch): temp_data = raw_target[i] _, idx = np.unique(temp_data, return_index=True) temp = temp_data[np.sort(idx)] if sum(temp == -1) == 0: temp = np.insert(temp, len(temp), padding) temp_input = np.append(temp_input, temp) temp_input = temp_input.reshape(length_batch, len(temp), 1) temp_input = temp_input.astype(int) np.save("../data/Label_1.npy", temp_input) # %% def shortencode(raw_target): raw_target = raw_target.reshape(raw_target.shape[0], raw_target.shape[1]) padding = -1 temp_input = np.array([]) length_batch = raw_target.shape[0] length_len = raw_target.shape[1] for i in range(length_batch): temp_data = raw_target[i] _, idx = np.unique(temp_data, return_index=True) temp = temp_data[np.sort(idx)] if sum(temp == -1) == 0: temp = np.insert(temp, len(temp), padding) temp_input = np.append(temp_input, temp) temp_input = temp_input.reshape(length_batch, len(temp), 1) temp_input = temp_input.astype(int) return temp_input

30.25

77

0.670924

209

1,331

4.023923

0.191388

0.171225

0.133175

0.071344

0.870392

0

0.016636

0.187077

1,331

43

78

30.953488

0.760628

0.003757

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0.848485

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0

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0.090909

0

null

0

1

0

1

0

null

0

7

0c4d0e44bd526aad9a6e99bf21fc1549a6d0699d

56

py

Python

sheslcrypto/__init__.py

shesl-meow/shesl-crypto

d6caf4fe13a15fa6700c1fef5667816f9d9a03d6

[ "Apache-2.0" ]

2

2019-11-30T17:29:11.000Z

2019-12-12T15:42:01.000Z

sheslcrypto/__init__.py

shesl-meow/shesl-crypto

d6caf4fe13a15fa6700c1fef5667816f9d9a03d6

[ "Apache-2.0" ]

null

sheslcrypto/__init__.py

shesl-meow/shesl-crypto

d6caf4fe13a15fa6700c1fef5667816f9d9a03d6

[ "Apache-2.0" ]

null

from sheslcrypto import RSA from sheslcrypto import LFSR

28

0.875

8

56

6.125

0.625

0.612245

0.857143

0

0.125

56

2

28

1

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

a7986a41f7c262597114965da868ec1392d74e78

138

py

Python

Python3/Exercises/SingleLetterCount/single_letter_count.py

norbertosanchezdichi/TIL

2e9719ddd288022f53b094a42679e849bdbcc625

[ "MIT" ]

null

Python3/Exercises/SingleLetterCount/single_letter_count.py

norbertosanchezdichi/TIL

2e9719ddd288022f53b094a42679e849bdbcc625

[ "MIT" ]

null

Python3/Exercises/SingleLetterCount/single_letter_count.py

norbertosanchezdichi/TIL

2e9719ddd288022f53b094a42679e849bdbcc625

[ "MIT" ]

null

def single_letter_count(string, letter): return string.lower().count(letter.lower()) print (single_letter_count('Norberto', 'O'))

34.5

47

0.724638

18

138

5.333333

0.555556

0.25

0.354167

0

0.115942

138

4

48

34.5

0.786885

0

0.064748

0

1

0.333333

false

0

0.333333

0.666667

0.333333

1

0

null

1

0

1

0

null

0

1

0

1

0

7

a7a0078032602ad60b28d541d4adad1cc1ee4c08

140

py

Python

app/errors.py

averycrespi/statice

bd6158595106df90fcabd8ac16e899bf58db1a3b

[ "MIT" ]

null

app/errors.py

averycrespi/statice

bd6158595106df90fcabd8ac16e899bf58db1a3b

[ "MIT" ]

40

2020-01-23T01:45:20.000Z

2020-03-24T18:48:25.000Z

app/errors.py

averycrespi/statice

bd6158595106df90fcabd8ac16e899bf58db1a3b

[ "MIT" ]

null

from flask import render_template def page_not_found(e): """Handle Page Not Found error.""" return render_template("404.j2"), 404

20

41

0.714286

21

140

4.571429

0.714286

0.291667

0.25

0

0.060345

0.171429

140

6

42

23.333333

0.767241

0.2

0

0.056604

0

1

0.333333

false

0

0.333333

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

a7acce645853ca6c083b2cff0fbd528a675c874c

6,575

py

Python

pyjuque/Engine/Database.py

Physicworld/pyjuque

ad52d0409558c04583a143398d9df01d2909fda3

[ "MIT" ]

1

2021-02-25T12:48:27.000Z

pyjuque/Engine/Database.py

Physicworld/pyjuque

ad52d0409558c04583a143398d9df01d2909fda3

[ "MIT" ]

null

pyjuque/Engine/Database.py

Physicworld/pyjuque

ad52d0409558c04583a143398d9df01d2909fda3

[ "MIT" ]

null

from pyjuque.Engine.Models import TABotModel as Bot, PairModel as Pair, \ EntrySettingsModel as EntrySettings, ExitSettingsModel as ExitSettings, getSession def InitializeDatabaseTaBot(session, params={}): """ Function that initializes the database by creating a bot with two pairs. """ name = 'My Bot' symbols = [] quote_asset = 'BTC' starting_balance = 0.001 test_run = False initial_entry_allocation = 25 signal_distance = 0.3 profit_target = 2 stop_loss_value = 0 exit_on_signal = False if params.__contains__('name'): assert type(params['name']) == str name = params['name'] if params.__contains__('symbols'): assert type(params['symbols']) == list symbols = params['symbols'] if params.__contains__('quote_asset'): assert type(params['quote_asset']) == str quote_asset = params['quote_asset'] if params.__contains__('starting_balance'): assert type(params['starting_balance']) in [int, float] starting_balance = params['starting_balance'] if params.__contains__('test_run'): assert type(params['test_run']) == bool test_run = params['test_run'] if params.__contains__('entry_settings'): assert type(params['entry_settings']) == dict entry_settings = params['entry_settings'] if entry_settings.__contains__('initial_entry_allocation'): assert type(entry_settings['initial_entry_allocation']) in [int, float] initial_entry_allocation = entry_settings['initial_entry_allocation'] if entry_settings.__contains__('signal_distance'): assert type(entry_settings['signal_distance']) in [int, float] signal_distance = entry_settings['signal_distance'] if params.__contains__('exit_settings'): assert type(params['exit_settings']) == dict exit_settings = params['exit_settings'] if exit_settings.__contains__('take_profit'): assert type(exit_settings['take_profit']) in [int, float] profit_target = exit_settings['take_profit'] if exit_settings.__contains__('stop_loss_value'): assert type(exit_settings['stop_loss_value']) in [int, float] stop_loss_value = exit_settings['stop_loss_value'] if exit_settings.__contains__('exit_on_signal'): assert type(exit_settings['exit_on_signal']) == bool exit_on_signal = exit_settings['exit_on_signal'] myobject = Bot( name = name, quote_asset = quote_asset, starting_balance = starting_balance, current_balance = starting_balance, test_run = test_run ) session.add(myobject) entrysets = EntrySettings( initial_entry_allocation = initial_entry_allocation, signal_distance = signal_distance ) exitsets = ExitSettings( profit_target = profit_target, # in % stop_loss_value = stop_loss_value, # in % exit_on_signal = exit_on_signal ) myobject.entry_settings = entrysets myobject.exit_settings = exitsets session.commit() for symbol in symbols: pair = Pair( bot_id = myobject.id, symbol = symbol, current_order_id = None ) session.add(pair) session.commit() def InitializeDatabaseGridBot(session, params={}): """ Function that initializes the database by creating a bot with two pairs. """ name = 'My Bot' symbols = [] quote_asset = 'BTC' starting_balance = 0.001 test_run = False initial_entry_allocation = 25 signal_distance = 0.3 profit_target = 2 stop_loss_value = 0 exit_on_signal = False if params.__contains__('name'): assert type(params['name']) == str name = params['name'] if params.__contains__('symbols'): assert type(params['symbols']) == list symbols = params['symbols'] if params.__contains__('quote_asset'): assert type(params['quote_asset']) == str quote_asset = params['quote_asset'] if params.__contains__('starting_balance'): assert type(params['starting_balance']) in [int, float] starting_balance = params['starting_balance'] if params.__contains__('test_run'): assert type(params['test_run']) == bool test_run = params['test_run'] if params.__contains__('entry_settings'): assert type(params['entry_settings']) == dict entry_settings = params['entry_settings'] if entry_settings.__contains__('initial_entry_allocation'): assert type(entry_settings['initial_entry_allocation']) in [int, float] initial_entry_allocation = entry_settings['initial_entry_allocation'] if entry_settings.__contains__('signal_distance'): assert type(entry_settings['signal_distance']) in [int, float] signal_distance = entry_settings['signal_distance'] if params.__contains__('exit_settings'): assert type(params['exit_settings']) == dict exit_settings = params['exit_settings'] if exit_settings.__contains__('take_profit'): assert type(exit_settings['take_profit']) in [int, float] profit_target = exit_settings['take_profit'] if exit_settings.__contains__('stop_loss_value'): assert type(exit_settings['stop_loss_value']) in [int, float] stop_loss_value = exit_settings['stop_loss_value'] if exit_settings.__contains__('exit_on_signal'): assert type(exit_settings['exit_on_signal']) == bool exit_on_signal = exit_settings['exit_on_signal'] myobject = Bot( name = name, quote_asset = quote_asset, starting_balance = starting_balance, current_balance = starting_balance, test_run = test_run ) session.add(myobject) entrysets = EntrySettings( initial_entry_allocation = initial_entry_allocation, signal_distance = signal_distance ) exitsets = ExitSettings( profit_target = profit_target, # in % stop_loss_value = stop_loss_value, # in % exit_on_signal = exit_on_signal ) myobject.entry_settings = entrysets myobject.exit_settings = exitsets session.commit() for symbol in symbols: pair = Pair( bot_id = myobject.id, symbol = symbol, current_order_id = None ) session.add(pair) session.commit()

33.717949

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6,575

5.445205

0.113699

0.084528

0.077484

0.033208

0.952956

0

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0.249582

6,575

194

87

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0.801581

0.025551

0

0.921053

0

0.145722

0.022563

0

0.157895

1

0.013158

false

0

0.006579

0

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0

null

0

1

0

1

0

null

0

7

a7dcae754e511a38316f1c528bf6e653b9514829

12,900

py

Python

tests/integrationv2/test_session_resumption.py

bryce-shang/s2n-tls

b0725af8e9900da37c2ec32bb40bf5a92e6bc896

[ "Apache-2.0" ]

4,256

2015-06-30T11:37:38.000Z

2021-02-17T10:46:30.000Z

tests/integrationv2/test_session_resumption.py

bryce-shang/s2n-tls

b0725af8e9900da37c2ec32bb40bf5a92e6bc896

[ "Apache-2.0" ]

2,088

2015-06-30T12:12:51.000Z

2021-02-17T22:27:43.000Z

tests/integrationv2/test_session_resumption.py

bryce-shang/s2n-tls

b0725af8e9900da37c2ec32bb40bf5a92e6bc896

[ "Apache-2.0" ]

676

2015-06-30T11:11:51.000Z

2021-02-15T20:07:16.000Z

import copy import os import pytest import time from configuration import available_ports, ALL_TEST_CIPHERS, ALL_TEST_CURVES, ALL_TEST_CERTS, PROTOCOLS, TLS13_CIPHERS from common import ProviderOptions, Protocols, data_bytes from fixtures import managed_process from providers import Provider, S2N, OpenSSL from utils import invalid_test_parameters, get_parameter_name, get_expected_s2n_version, to_bytes @pytest.mark.uncollect_if(func=invalid_test_parameters) @pytest.mark.parametrize("cipher", ALL_TEST_CIPHERS, ids=get_parameter_name) @pytest.mark.parametrize("curve", ALL_TEST_CURVES, ids=get_parameter_name) @pytest.mark.parametrize("certificate", ALL_TEST_CERTS, ids=get_parameter_name) @pytest.mark.parametrize("protocol", [p for p in PROTOCOLS if p != Protocols.TLS13], ids=get_parameter_name) @pytest.mark.parametrize("provider", [OpenSSL], ids=get_parameter_name) @pytest.mark.parametrize("use_ticket", [True, False]) def test_session_resumption_s2n_server(managed_process, cipher, curve, protocol, provider, certificate, use_ticket): port = next(available_ports) client_options = ProviderOptions( mode=Provider.ClientMode, port=port, cipher=cipher, curve=curve, insecure=True, reconnect=True, protocol=protocol) server_options = copy.copy(client_options) server_options.reconnects_before_exit = 6 server_options.mode = Provider.ServerMode server_options.use_session_ticket=use_ticket, server_options.key = certificate.key server_options.cert = certificate.cert # Passing the type of client and server as a parameter will # allow us to use a fixture to enumerate all possibilities. server = managed_process(S2N, server_options, timeout=5) client = managed_process(provider, client_options, timeout=5) # The client should connect and return without error for results in client.get_results(): results.assert_success() assert results.stdout.count(to_bytes("Session-ID:")) == 6 expected_version = get_expected_s2n_version(protocol, OpenSSL) # S2N should indicate the procotol version in a successful connection. for results in server.get_results(): results.assert_success() assert results.stdout.count(to_bytes("Actual protocol version: {}".format(expected_version))) == 6 @pytest.mark.uncollect_if(func=invalid_test_parameters) @pytest.mark.parametrize("cipher", ALL_TEST_CIPHERS, ids=get_parameter_name) @pytest.mark.parametrize("curve", ALL_TEST_CURVES, ids=get_parameter_name) @pytest.mark.parametrize("certificate", ALL_TEST_CERTS, ids=get_parameter_name) @pytest.mark.parametrize("protocol", [p for p in PROTOCOLS if p != Protocols.TLS13], ids=get_parameter_name) @pytest.mark.parametrize("provider", [OpenSSL], ids=get_parameter_name) @pytest.mark.parametrize("use_ticket", [True, False]) def test_session_resumption_s2n_client(managed_process, cipher, curve, protocol, provider, certificate, use_ticket): port = next(available_ports) client_options = ProviderOptions( mode=Provider.ClientMode, port=port, cipher=cipher, curve=curve, insecure=True, reconnect=True, use_session_ticket=use_ticket, protocol=protocol) server_options = copy.copy(client_options) server_options.reconnects_before_exit = 6 server_options.mode = Provider.ServerMode server_options.key = certificate.key server_options.cert = certificate.cert server_options.use_session_ticket = False # Passing the type of client and server as a parameter will # allow us to use a fixture to enumerate all possibilities. server = managed_process(provider, server_options, timeout=5) client = managed_process(S2N, client_options, timeout=5) expected_version = get_expected_s2n_version(protocol, OpenSSL) for results in client.get_results(): results.assert_success() assert results.stdout.count(to_bytes("Actual protocol version: {}".format(expected_version))) == 6 for results in server.get_results(): results.assert_success() assert results.stdout.count(to_bytes("6 server accepts that finished")) @pytest.mark.uncollect_if(func=invalid_test_parameters) @pytest.mark.parametrize("cipher", TLS13_CIPHERS, ids=get_parameter_name) @pytest.mark.parametrize("curve", ALL_TEST_CURVES, ids=get_parameter_name) @pytest.mark.parametrize("certificate", ALL_TEST_CERTS, ids=get_parameter_name) @pytest.mark.parametrize("protocol", [Protocols.TLS13], ids=get_parameter_name) @pytest.mark.parametrize("provider", [OpenSSL], ids=get_parameter_name) def test_tls13_session_resumption_s2n_server(managed_process, tmp_path, cipher, curve, protocol, provider, certificate): port = str(next(available_ports)) # Use temp directory to store session tickets p = tmp_path / 'ticket.pem' path_to_ticket = str(p) close_marker_bytes = data_bytes(10) client_options = ProviderOptions( mode=Provider.ClientMode, port=port, cipher=cipher, curve=curve, insecure=True, reconnect=False, extra_flags = ['-sess_out', path_to_ticket], protocol=protocol) server_options = copy.copy(client_options) server_options.mode = Provider.ServerMode server_options.key = certificate.key server_options.cert = certificate.cert server_options.use_session_ticket = True server_options.extra_flags = None server_options.data_to_send = close_marker_bytes server = managed_process(S2N, server_options, timeout=5, send_marker=S2N.get_send_marker()) client = managed_process(provider, client_options, timeout=5, close_marker=str(close_marker_bytes)) # The client should have received a session ticket for results in client.get_results(): results.assert_success() assert b'Post-Handshake New Session Ticket arrived:' in results.stdout for results in server.get_results(): results.assert_success() # The first connection is a full handshake assert b'Resumed session' not in results.stdout # Client inputs received session ticket to resume a session assert os.path.exists(path_to_ticket) client_options.extra_flags = ['-sess_in', path_to_ticket] port = str(next(available_ports)) client_options.port = port server_options.port = port server = managed_process(S2N, server_options, timeout=5, send_marker=S2N.get_send_marker()) client = managed_process(provider, client_options, timeout=5, close_marker=str(close_marker_bytes)) s2n_version = get_expected_s2n_version(protocol, provider) # Client has not read server certificate message as this is a resumed session for results in client.get_results(): results.assert_success() assert to_bytes("SSL_connect:SSLv3/TLS read server certificate") not in results.stderr # The server should indicate a session has been resumed for results in server.get_results(): results.assert_success() assert b'Resumed session' in results.stdout assert to_bytes("Actual protocol version: {}".format(s2n_version)) in results.stdout @pytest.mark.uncollect_if(func=invalid_test_parameters) @pytest.mark.parametrize("cipher", TLS13_CIPHERS, ids=get_parameter_name) @pytest.mark.parametrize("curve", ALL_TEST_CURVES, ids=get_parameter_name) @pytest.mark.parametrize("certificate", ALL_TEST_CERTS, ids=get_parameter_name) @pytest.mark.parametrize("protocol", [Protocols.TLS13], ids=get_parameter_name) @pytest.mark.parametrize("provider", [OpenSSL, S2N], ids=get_parameter_name) def test_tls13_session_resumption_s2n_client(managed_process, cipher, curve, protocol, provider, certificate): port = str(next(available_ports)) # The reconnect option for s2nc allows the client to reconnect automatically # five times. In this test we expect one full connection and five resumption # connections. num_full_connections = 1 num_resumed_connections = 5 client_options = ProviderOptions( mode=Provider.ClientMode, port=port, cipher=cipher, curve=curve, insecure=True, use_session_ticket=True, reconnect=True, protocol=protocol) server_options = copy.copy(client_options) server_options.mode = Provider.ServerMode server_options.key = certificate.key server_options.cert = certificate.cert server_options.reconnects_before_exit = num_resumed_connections + num_full_connections server = managed_process(provider, server_options, timeout=5) client = managed_process(S2N, client_options, timeout=5) s2n_version = get_expected_s2n_version(protocol, provider) # s2nc indicates the number of resumed connections in its output for results in client.get_results(): results.assert_success() assert results.stdout.count(b'Resumed session') == num_resumed_connections assert to_bytes("Actual protocol version: {}".format(s2n_version)) in results.stdout server_accepts_str = str(num_resumed_connections + num_full_connections) + " server accepts that finished" for results in server.get_results(): results.assert_success() if provider is S2N: assert results.stdout.count(b'Resumed session') == num_resumed_connections assert to_bytes("Actual protocol version: {}".format(s2n_version)) in results.stdout else: assert to_bytes(server_accepts_str) in results.stdout # s_server only writes one certificate message in all of the connections assert results.stderr.count(b'SSL_accept:SSLv3/TLS write certificate') == num_full_connections @pytest.mark.uncollect_if(func=invalid_test_parameters) @pytest.mark.parametrize("cipher", TLS13_CIPHERS, ids=get_parameter_name) @pytest.mark.parametrize("curve", ALL_TEST_CURVES, ids=get_parameter_name) @pytest.mark.parametrize("certificate", ALL_TEST_CERTS, ids=get_parameter_name) @pytest.mark.parametrize("protocol", [Protocols.TLS13], ids=get_parameter_name) @pytest.mark.parametrize("provider", [OpenSSL], ids=get_parameter_name) def test_s2nd_falls_back_to_full_connection(managed_process, tmp_path, cipher, curve, protocol, provider, certificate): port = str(next(available_ports)) # Use temp directory to store session tickets p = tmp_path / 'ticket.pem' path_to_ticket = str(p) """ This test will set up a full connection with an Openssl client and server to obtain a valid Openssl session ticket. Then, the Openssl client attempts to send the received session ticket to an s2n server to resume a session. s2nd will fallback to a full connection as it does not recognize the session ticket. """ client_options = ProviderOptions( mode=Provider.ClientMode, port=port, cipher=cipher, curve=curve, insecure=True, reconnect=False, extra_flags = ['-sess_out', path_to_ticket], data_to_send = data_bytes(4069), protocol=protocol) server_options = copy.copy(client_options) server_options.mode = Provider.ServerMode server_options.key = certificate.key server_options.cert = certificate.cert server_options.extra_flags = None server = managed_process(provider, server_options, timeout=5) client = managed_process(provider, client_options, timeout=5) # The client should have received a session ticket for results in client.get_results(): results.assert_success() assert b'Post-Handshake New Session Ticket arrived:' in results.stdout for results in server.get_results(): results.assert_success() # Server should have sent certificate message as this is a full connection assert b'SSL_accept:SSLv3/TLS write certificate' in results.stderr # Client inputs received session ticket to resume a session assert os.path.exists(path_to_ticket) client_options.extra_flags = ['-sess_in', path_to_ticket] port = str(next(available_ports)) client_options.port = port server_options.port = port # Switch providers so now s2n is the server server = managed_process(S2N, server_options, timeout=5) client = managed_process(provider, client_options, timeout=5) s2n_version = get_expected_s2n_version(protocol, provider) # Client has read server certificate because this is a full connection for results in client.get_results(): results.assert_success() assert to_bytes("SSL_connect:SSLv3/TLS read server certificate") in results.stderr # The server should indicate a session has not been resumed for results in server.get_results(): results.assert_success() assert b'Resumed session' not in results.stdout assert to_bytes("Actual protocol version: {}".format(s2n_version)) in results.stdout

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0.169612

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null

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1

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null

0

7

ac0b700668b0e2af70d36f1f54959b2481bb90f0

301

py

Python

product/product_manufacturing_places.py

saiihamza/open_data_parsing

6757c6c6823a0523ca1d2af79e99b761b57a794d

[ "Apache-2.0" ]

null

product/product_manufacturing_places.py

saiihamza/open_data_parsing

6757c6c6823a0523ca1d2af79e99b761b57a794d

[ "Apache-2.0" ]

null

product/product_manufacturing_places.py

saiihamza/open_data_parsing

6757c6c6823a0523ca1d2af79e99b761b57a794d

[ "Apache-2.0" ]

null

class ProductManufacturingPlaces(object): def __init__(self, manufacturing_places, manufacturing_places_tags): self.ManufacturingPlaces = manufacturing_places self.ManufacturingPlacesTags = manufacturing_places_tags def __str__(self): return self.ManufacturingPlaces

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1

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7

ac0d965b0834a4bfafbb52af90f17da0b16d45bf

26,566

py

Python

analysis/c_utils/utils_hour.py

chrelli/3DDD_social_mouse_tracker

291d2ed90029628dd65db0ce3e8972b721159a15

[ "Apache-2.0" ]

1

2022-02-10T07:26:09.000Z

analysis/c_utils/utils_hour.py

chrelli/3DDD_social_mouse_tracker

291d2ed90029628dd65db0ce3e8972b721159a15

[ "Apache-2.0" ]

1

2022-02-11T06:55:29.000Z

2022-02-12T22:26:44.000Z

analysis/c_utils/utils_hour.py

chrelli/3DDD_social_mouse_tracker

291d2ed90029628dd65db0ce3e8972b721159a15

[ "Apache-2.0" ]

null

# FROM TIRAMISU # %matplotlib inline # %load_ext autoreload # %autoreload 2 import time from pathlib import Path import numpy as np import matplotlib.pyplot as plt import torch import torch.nn as nn import torch.optim as optim import torchvision import torchvision.transforms as transforms # import the tiramisu models #from pytorch_tiramisu.models import tiramisu # from pose.models import hourglass #import deepfly.pose2d.models as flymodels # from datasets import camvid #from pytorch_tiramisu.datasets import joint_transforms #import pytorch_tiramisu.utils.imgs #import pytorch_tiramisu.utils.training as train_utils import sys, os, pickle import h5py import cv2 from colour import Color #%% # for making the target maps! def gaussian(img, pt, sigma): # Draw a 2D gaussian, unless the point is in the upper corner # Check that any part of the gaussian is in-bounds ul = [int(pt[0] - 3 * sigma), int(pt[1] - 3 * sigma)] br = [int(pt[0] + 3 * sigma + 1), int(pt[1] + 3 * sigma + 1)] if (ul[0] > img.shape[1] or ul[1] >= img.shape[0] or br[0] < 0 or br[1] < 0) : # If not, just return the image as is return img # Generate gaussian size = 6 * sigma + 1 x = np.arange(0, size, 1, float) y = x[:, np.newaxis] x0 = y0 = size // 2 # The gaussian is not normalized, we want the center value to equal 1 g = np.exp(- ((x - x0) ** 2 + (y - y0) ** 2) / (2 * sigma ** 2)) # Usable gaussian range g_x = max(0, -ul[0]), min(br[0], img.shape[1]) - ul[0] g_y = max(0, -ul[1]), min(br[1], img.shape[0]) - ul[1] # Image range img_x = max(0, ul[0]), min(br[0], img.shape[1]) img_y = max(0, ul[1]), min(br[1], img.shape[0]) img[img_y[0]:img_y[1], img_x[0]:img_x[1]] = g[g_y[0]:g_y[1], g_x[0]:g_x[1]] return img #%% def check_h5(h5_path): # plots a random file from the h5py with h5py.File(h5_path, mode='r') as h5file: print(h5file.keys()) ji = np.random.choice(len(h5file['c_images'])) c_image = h5file['c_images'][ji] points = h5file['annotations'][ji] plt.figure(figsize=(10,10)) plt.imshow(c_image[..., [2,1,0]]) plt.plot(points[:,0],points[:,1],'or') plt.title("raw width: {} height: {}".format(c_image.shape[0],c_image.shape[1])) plt.show() h5file.close() #%% def check_h5_ir(h5_path, ji = None): # plots a random file from the h5py with h5py.File(h5_path, mode='r') as h5file: print(h5file.keys()) if ji is None: ji = np.random.choice(len(h5file['c_images'])) c_image = h5file['c_images'][ji] points = h5file['annotations'][ji] plt.figure(figsize=(10,10)) plt.imshow(c_image) plt.plot(points[:,0],points[:,1],'or') plt.title("raw width: {} height: {}".format(c_image.shape[0],c_image.shape[1])) plt.show() h5file.close() return c_image #%% def check_h5_ir_bw(h5_path, ji = None,savepath=None): # plots a random file from the h5py with h5py.File(h5_path, mode='r') as h5file: print(h5file.keys()) if ji is None: ji = np.random.choice(len(h5file['c_images'])) c_image = h5file['c_images'][ji] points = h5file['annotations'][ji] annotated = h5file['annotated'][ji] skel = h5file['skeleton'][:] print(h5file.keys()) print(skel) # housekeeping for plotting body_colors =['dodgerblue','red','lime','orange'] label_names = ['impl','ear','ear','nose','tail','ear','ear','nose','tail'] body_names = ['mouse0','mouse0','mouse0','mouse0','mouse0','mouse1','mouse1','mouse1','mouse1'] label_index = [0,1,1,2,3,1,1,2,3] body_index = [0,0,0,0,0,1,1,1,1] plt.figure(figsize=(10,10)) plt.imshow(c_image,cmap = 'gray') for jj in range(points.shape[0]): if points[jj,0] <10: continue cc =body_colors[label_index[jj]] plt.scatter(points[jj,0],points[jj,1],marker='o',s=200,edgecolor=cc,facecolor='none',linewidth=3) # plt.title("raw width: {} height: {}".format(c_image.shape[0],c_image.shape[1])) plt.axis('off') if savepath is not None: plt.savefig(savepath) plt.show() h5file.close() return c_image,points #%% SOME PLOTTING def plot_im_target(im,target,size = 5): im_np = im.numpy() target_np = target.numpy()[0,:,:] c = im_np[0,[2,1,0],:,:] # dac = im_np[0,3,:,:] c = np.moveaxis(c,[0],[2]) # dac = im_c[] point_map = np.max( target_np[:4,:,:] , axis = 0) posture_map = np.max( target_np[4:,:,:] , axis = 0) full_map = np.max( target_np[:,:,:] , axis = 0) # plt.imshow(posture_map) plt.figure(figsize=(1.3*size,size)) plt.subplot(2,2,1) plt.imshow( c ) plt.title("RGB") plt.subplot(2,2,2) plt.imshow( full_map ) # plt.imshow( dac ) plt.title("all") plt.subplot(2,2,3) plt.imshow( point_map ) plt.title("Point targets") plt.subplot(2,2,4) plt.imshow( posture_map ) plt.title("Affinity map") plt.show() def plot_im_target_ir(im,target,size = 5): im_np = im.numpy() target_np = target.numpy()[0,:,:] c = im_np[0,0,:,:] # dac = im_np[0,3,:,:] # c = np.moveaxis(c,[0],[2]) # dac = im_c[] point_map = np.max( target_np[:4,:,:] , axis = 0) posture_map = np.max( target_np[4:,:,:] , axis = 0) full_map = np.max( target_np[:,:,:] , axis = 0) # plt.imshow(posture_map) plt.figure(figsize=(1.3*size,size)) plt.subplot(2,2,1) plt.imshow( c ) plt.title("RGB") plt.subplot(2,2,2) plt.imshow( full_map ) # plt.imshow( dac ) plt.title("all") plt.subplot(2,2,3) plt.imshow( point_map ) plt.title("Point targets") plt.subplot(2,2,4) plt.imshow( posture_map ) plt.title("Affinity map") plt.show() def random_from(MouseValidLoader): N = MouseValidLoader.__len__() k = np.random.randint(0,N) for i, data in enumerate(MouseValidLoader): if i == k: print(i) return data[0],data[1] def specific_from(MouseValidLoader,k): N = MouseValidLoader.__len__() for i, data in enumerate(MouseValidLoader): if i == k: print(i) return data[0],data[1] def plot_im_target_pseudo(input_var,target_var,size = 10,save_fig = False): # def show_frame(input_var,target_var): # plt.imshow(input_var.data.cpu()[0,:,:,:].numpy()) input_image = input_var.data.cpu()[0,:3,:,:].numpy() input_image = np.moveaxis(input_image,0,2) target_stack = target_var.data.cpu()[0,:,:,:].numpy() target_image = target_stack[:4,...] target_pose = target_stack[4:,...] # = np.moveaxis(target[0,:,:,:].numpy() ,0,2) # test.shape # score_map = output.data.cpu() tt = ["implant","ears","noses",'tails'] # show the tracking belief map Fig1 = plt.figure(figsize=(1.5*size,size)) plt.subplot(2,3,1) plt.imshow(input_image[:,:,[2,1,0]]) plt.title("image space, h: {} w: {}".format(input_image.shape[0],input_image.shape[1]) ) plt.subplot(2,3,2) # from matplotlib.pyplot import cm pseudo = np.zeros((target_image.shape[1],target_image.shape[2],3)) body_colors =['dodgerblue','red','lime','orange'] for i,col in enumerate(body_colors): bright = target_image[i,:,:] rgb = Color(col).rgb color_im = bright[:,:,np.newaxis] * np.asarray(rgb)[np.newaxis,np.newaxis,:] pseudo += color_im pseudo = np.clip(pseudo,0,1) # # Write some Text # font = cv2.FONT_HERSHEY_SIMPLEX # fontScale = .4 # lineType = 0 t_h,t_w = pseudo.shape[:2] pad = 10 # for i,(type,col,x,y) in enumerate(zip(tt,body_colors,[pad,pad,t_h-pad,t_h-pad],[pad,2*pad,pad,2*pad])): # # do as in-place? # rgb = Color(col).rgb # fontColor = rgb # bottomLeftCornerOfText = (10,i*10+20) # bottomLeftCornerOfText = (x,y) # cv2.putText(pseudo,type,bottomLeftCornerOfText,font,fontScale,fontColor,lineType) plt.imshow(pseudo) for i,(type,col,x,y) in enumerate(zip(tt,body_colors,[pad,pad,t_h-pad,t_h-pad],[pad,2*pad,pad,2*pad])): x = 6 y = i*6+6 plt.text(x, y, type, fontsize=12,color = col) pseudo_net = np.zeros((target_image.shape[1],target_image.shape[2],3)) affinity_colors = ['dodgerblue','yellow','purple','red','lime','orange','hotpink'] for i,col in enumerate(affinity_colors): bright = target_pose[i,:,:] rgb = Color(col).rgb color_im = bright[:,:,np.newaxis] * np.asarray(rgb)[np.newaxis,np.newaxis,:] pseudo_net += color_im plt.subplot(2,3,3) plt.imshow(pseudo_net.clip(0,1)) plt.title("affinity field") plt.subplot(2,3,2) plt.title("pixel targets, h: {} w: {}".format(pseudo_net.shape[0],pseudo_net.shape[1])) for i,(t,col) in enumerate(zip(["I --> E","I --> N","I --> T","E --> E","E --> T","E --> N","N --> T"],affinity_colors)): plt.subplot(4,4,9+i) bright = target_pose[i,:,:] rgb = Color(col).rgb color_im = bright[:,:,np.newaxis] * np.asarray(rgb)[np.newaxis,np.newaxis,:] plt.imshow( color_im/np.max(color_im) ) # plt.imshow( color_im) # plt.imshow(bright) plt.axis('off') plt.title(t) # ADD FINAL TOUCH plt.subplot(4,4,16) show = np.copy(pseudo_net.clip(0,1)) add_me = pseudo.clip(0,1) mask_me = np.any(add_me > .3,2) show[mask_me,:] = add_me[mask_me,:] plt.imshow(show) if save_fig: plt.savefig('cinema_training/trainframe_{}_.png'.format(np.random.uniform())) plt.show() #%% def plot_im_target_pseudo_ir(input_var,target_var,size = 10,save_fig = False): # def show_frame(input_var,target_var): # plt.imshow(input_var.data.cpu()[0,:,:,:].numpy()) input_image = input_var.data.cpu()[0,0,:,:].numpy() target_stack = target_var.data.cpu()[0,:,:,:].numpy() target_image = target_stack[:4,...] target_pose = target_stack[4:,...] # = np.moveaxis(target[0,:,:,:].numpy() ,0,2) # test.shape # score_map = output.data.cpu() tt = ["implant","ears","noses",'tails'] # show the tracking belief map Fig1 = plt.figure(figsize=(1.5*size,size)) plt.subplot(2,3,1) plt.imshow(input_image,cmap='gray') plt.title("image space, h: {} w: {}".format(input_image.shape[0],input_image.shape[1]) ) plt.subplot(2,3,2) # from matplotlib.pyplot import cm pseudo = np.zeros((target_image.shape[1],target_image.shape[2],3)) body_colors =['dodgerblue','red','lime','orange'] for i,col in enumerate(body_colors): bright = target_image[i,:,:] rgb = Color(col).rgb color_im = bright[:,:,np.newaxis] * np.asarray(rgb)[np.newaxis,np.newaxis,:] pseudo += color_im pseudo = np.clip(pseudo,0,1) # # Write some Text # font = cv2.FONT_HERSHEY_SIMPLEX # fontScale = .4 # lineType = 0 t_h,t_w = pseudo.shape[:2] pad = 10 # for i,(type,col,x,y) in enumerate(zip(tt,body_colors,[pad,pad,t_h-pad,t_h-pad],[pad,2*pad,pad,2*pad])): # # do as in-place? # rgb = Color(col).rgb # fontColor = rgb # bottomLeftCornerOfText = (10,i*10+20) # bottomLeftCornerOfText = (x,y) # cv2.putText(pseudo,type,bottomLeftCornerOfText,font,fontScale,fontColor,lineType) plt.imshow(pseudo) for i,(type,col,x,y) in enumerate(zip(tt,body_colors,[pad,pad,t_h-pad,t_h-pad],[pad,2*pad,pad,2*pad])): x = 6 y = i*6+6 plt.text(x, y, type, fontsize=12,color = col) pseudo_net = np.zeros((target_image.shape[1],target_image.shape[2],3)) affinity_colors = ['dodgerblue','yellow','purple','red','lime','orange','hotpink'] for i,col in enumerate(affinity_colors): bright = target_pose[i,:,:] rgb = Color(col).rgb color_im = bright[:,:,np.newaxis] * np.asarray(rgb)[np.newaxis,np.newaxis,:] pseudo_net += color_im plt.subplot(2,3,3) plt.imshow(pseudo_net.clip(0,1)) plt.title("affinity field") plt.subplot(2,3,2) plt.title("pixel targets, h: {} w: {}".format(pseudo_net.shape[0],pseudo_net.shape[1])) for i,(t,col) in enumerate(zip(["I --> E","I --> N","I --> T","E --> E","E --> T","E --> N","N --> T"],affinity_colors)): plt.subplot(4,4,9+i) bright = target_pose[i,:,:] rgb = Color(col).rgb color_im = bright[:,:,np.newaxis] * np.asarray(rgb)[np.newaxis,np.newaxis,:] plt.imshow( color_im/np.max(color_im) ) # plt.imshow( color_im) # plt.imshow(bright) plt.axis('off') plt.title(t) # ADD FINAL TOUCH plt.subplot(4,4,16) show = np.copy(pseudo_net.clip(0,1)) add_me = pseudo.clip(0,1) mask_me = np.any(add_me > .3,2) show[mask_me,:] = add_me[mask_me,:] plt.imshow(show) if save_fig: plt.savefig('cinema_training/trainframe_{}_.png'.format(np.random.uniform())) plt.show() #%% def convet_to_pseudo(target_var): # def show_frame(input_var,target_var): # plt.imshow(input_var.data.cpu()[0,:,:,:].numpy()) target_stack = target_var.data.cpu()[0,:,:,:].numpy() target_image = target_stack[:4,...] target_pose = target_stack[4:,...] # = np.moveaxis(target[0,:,:,:].numpy() ,0,2) # test.shape # score_map = output.data.cpu() tt = ["implant","ears","noses",'tails'] pseudo = np.zeros((target_image.shape[1],target_image.shape[2],3)) body_colors =['dodgerblue','red','lime','orange'] for i,col in enumerate(body_colors): bright = target_image[i,:,:] rgb = Color(col).rgb color_im = bright[:,:,np.newaxis] * np.asarray(rgb)[np.newaxis,np.newaxis,:] pseudo += color_im pseudo = np.clip(pseudo,0,1) pseudo_net = np.zeros((target_image.shape[1],target_image.shape[2],3)) affinity_colors = ['dodgerblue','yellow','purple','red','lime','orange','hotpink'] for i,col in enumerate(affinity_colors): bright = target_pose[i,:,:] rgb = Color(col).rgb color_im = bright[:,:,np.newaxis] * np.asarray(rgb)[np.newaxis,np.newaxis,:] pseudo_net += color_im pseudo_net = np.clip(pseudo_net,0,1) show = np.copy(pseudo_net.clip(0,1)) add_me = pseudo.clip(0,1) mask_me = np.any(add_me > .3,2) show[mask_me,:] = add_me[mask_me,:] return pseudo, pseudo_net,show def plot_and_dump_im_target_pseudo(input_var,target_var,size = 10,save_fig = False): # def show_frame(input_var,target_var): # plt.imshow(input_var.data.cpu()[0,:,:,:].numpy()) input_image = input_var.data.cpu()[0,:3,:,:].numpy() input_image = np.moveaxis(input_image,0,2) target_stack = target_var.data.cpu()[0,:,:,:].numpy() target_image = target_stack[:4,...] target_pose = target_stack[4:,...] # = np.moveaxis(target[0,:,:,:].numpy() ,0,2) # test.shape # score_map = output.data.cpu() tt = ["implant","ears","noses",'tails'] # show the tracking belief map Fig1 = plt.figure(figsize=(1.5*size,size)) plt.subplot(2,3,1) plt.imshow(input_image[:,:,[2,1,0]]) figure_dump_folder = '/home/chrelli/git/3d_sandbox/mouseposev0p2/figure_raw_pics/figure_3' cv2.imwrite(figure_dump_folder+'/train/dump_im'+'.png',input_image*255) plt.title("image space, h: {} w: {}".format(input_image.shape[0],input_image.shape[1]) ) plt.subplot(2,3,2) # from matplotlib.pyplot import cm pseudo = np.zeros((target_image.shape[1],target_image.shape[2],3)) body_colors =['dodgerblue','red','lime','orange'] for i,col in enumerate(body_colors): bright = target_image[i,:,:] rgb = Color(col).rgb color_im = bright[:,:,np.newaxis] * np.asarray(rgb)[np.newaxis,np.newaxis,:] pseudo += color_im pseudo = np.clip(pseudo,0,1) # # Write some Text # font = cv2.FONT_HERSHEY_SIMPLEX # fontScale = .4 # lineType = 0 t_h,t_w = pseudo.shape[:2] pad = 10 # for i,(type,col,x,y) in enumerate(zip(tt,body_colors,[pad,pad,t_h-pad,t_h-pad],[pad,2*pad,pad,2*pad])): # # do as in-place? # rgb = Color(col).rgb # fontColor = rgb # bottomLeftCornerOfText = (10,i*10+20) # bottomLeftCornerOfText = (x,y) # cv2.putText(pseudo,type,bottomLeftCornerOfText,font,fontScale,fontColor,lineType) plt.imshow(pseudo) cv2.imwrite(figure_dump_folder+'/train/dump_pseudo_targets'+'.png',pseudo[:,:,[2,1,0]]*255) for i,(type,col,x,y) in enumerate(zip(tt,body_colors,[pad,pad,t_h-pad,t_h-pad],[pad,2*pad,pad,2*pad])): x = 6 y = i*6+6 plt.text(x, y, type, fontsize=12,color = col) pseudo_net = np.zeros((target_image.shape[1],target_image.shape[2],3)) affinity_colors = ['dodgerblue','yellow','purple','red','lime','orange','hotpink'] for i,col in enumerate(affinity_colors): bright = target_pose[i,:,:] rgb = Color(col).rgb color_im = bright[:,:,np.newaxis] * np.asarray(rgb)[np.newaxis,np.newaxis,:] pseudo_net += color_im plt.subplot(2,3,3) plt.imshow(pseudo_net.clip(0,1)) dddump = pseudo_net[:,:,[2,1,0]].clip(0,1) cv2.imwrite(figure_dump_folder+'/train/dump_pseudo_pafs'+'.png',dddump/np.max(dddump)*255) plt.title("affinity field") plt.subplot(2,3,2) plt.title("pixel targets, h: {} w: {}".format(pseudo_net.shape[0],pseudo_net.shape[1])) for i,(t,col) in enumerate(zip(["I --> E","I --> N","I --> T","E --> E","E --> T","E --> N","N --> T"],affinity_colors)): plt.subplot(4,4,9+i) bright = target_pose[i,:,:] rgb = Color(col).rgb color_im = bright[:,:,np.newaxis] * np.asarray(rgb)[np.newaxis,np.newaxis,:] plt.imshow( color_im/np.max(color_im) ) # plt.imshow( color_im) cv2.imwrite(figure_dump_folder+'/train/dump_pafs'+t+'.png',color_im[:,:,[2,1,0]]/np.max(color_im)*255) # plt.imshow(bright) plt.axis('off') plt.title(t) if save_fig: plt.savefig('cinema_training/trainframe_{}_.png'.format(np.random.uniform())) plt.show() #%% def plot_ito_pseudo(input_var,target_var,output,size = 10): # def show_frame(input_var,target_var): # plt.imshow(input_var.data.cpu()[0,:,:,:].numpy()) input_image = input_var.data.cpu()[0,:3,:,:].numpy() input_image = np.moveaxis(input_image,0,2) target_stack = target_var.data.cpu()[0,:,:,:].numpy() # clip the target to 1! target_stack = np.clip(target_stack,0,1) target_image = target_stack[:4,...] target_pose = target_stack[4:,...] # = np.moveaxis(target[0,:,:,:].numpy() ,0,2) # test.shape score_map = output[-1].data.cpu().numpy() tt = ["implant","ears","noses",'tails'] # show the tracking belief map Fig1 = plt.figure(figsize=(1.5*size,size)) plt.subplot(3,3,1) plt.title('image space') plt.imshow(input_image[:,:,[2,1,0]]) plt.subplot(3,3,2) # from matplotlib.pyplot import cm body_colors =['dodgerblue','red','lime','orange'] def color_target_points(target_image,body_colors): pseudo = np.zeros((target_image.shape[1],target_image.shape[2],3)) for i,col in enumerate(body_colors): bright = target_image[i,:,:] rgb = Color(col).rgb color_im = bright[:,:,np.newaxis] * np.asarray(rgb)[np.newaxis,np.newaxis,:] pseudo += color_im pseudo = np.clip(pseudo,0,1) return pseudo pseudo = color_target_points(target_image,body_colors) t_h,t_w = pseudo.shape[:2] pad = 10 plt.imshow(pseudo) for i,(type,col,x,y) in enumerate(zip(tt,body_colors,[pad,pad,t_h-pad,t_h-pad],[pad,2*pad,pad,2*pad])): x = 10 y = i*10+10 plt.text(x, y, type, fontsize=18,color = col) plt.title("pixel targets") affinity_colors = ['dodgerblue','yellow','purple','red','lime','orange','hotpink'] def color_target_lines(target_pose,affinity_colors): pseudo_net = np.zeros((target_pose.shape[1],target_pose.shape[2],3)) for i,col in enumerate(affinity_colors): bright = target_pose[i,:,:] rgb = Color(col).rgb color_im = bright[:,:,np.newaxis] * np.asarray(rgb)[np.newaxis,np.newaxis,:] pseudo_net += color_im pseudo_net = pseudo_net.clip(0,1) return pseudo_net plt.subplot(3,3,3) pseudo_net = color_target_lines(target_pose,affinity_colors) plt.imshow(pseudo_net) plt.title("affinity field") plt.subplot(3,3,5) pseudo_belief = color_target_points(score_map[0,:4,:,:],body_colors) plt.imshow(pseudo_belief) plt.title("network belief") plt.subplot(3,3,6) pseudo_belief = color_target_lines(score_map[0,4:,:,:],affinity_colors) plt.imshow(pseudo_belief) plt.title("network belief") pseudo = np.zeros((target_image.shape[1],target_image.shape[2],3)) for i,col in enumerate(body_colors): plt.subplot(3,4,9+i) bright = score_map[0,i,:,:] rgb = Color(col).rgb color_im = bright[:,:,np.newaxis] * np.asarray(rgb)[np.newaxis,np.newaxis,:] color_im = color_im.clip(0,1) plt.imshow(color_im) return Fig1 def plot_ito_pseudo_ir(input_var,target_var,output,size = 10): # def show_frame(input_var,target_var): # plt.imshow(input_var.data.cpu()[0,:,:,:].numpy()) input_image = input_var.data.cpu()[0,0,:,:].numpy() target_stack = target_var.data.cpu()[0,:,:,:].numpy() # clip the target to 1! target_stack = np.clip(target_stack,0,1) target_image = target_stack[:4,...] target_pose = target_stack[4:,...] # = np.moveaxis(target[0,:,:,:].numpy() ,0,2) # test.shape score_map = output[-1].data.cpu().numpy() tt = ["implant","ears","noses",'tails'] # show the tracking belief map Fig1 = plt.figure(figsize=(1.5*size,size)) plt.subplot(3,3,1) plt.title('image space') plt.imshow(input_image) plt.subplot(3,3,2) # from matplotlib.pyplot import cm body_colors =['dodgerblue','red','lime','orange'] def color_target_points(target_image,body_colors): pseudo = np.zeros((target_image.shape[1],target_image.shape[2],3)) for i,col in enumerate(body_colors): bright = target_image[i,:,:] rgb = Color(col).rgb color_im = bright[:,:,np.newaxis] * np.asarray(rgb)[np.newaxis,np.newaxis,:] pseudo += color_im pseudo = np.clip(pseudo,0,1) return pseudo pseudo = color_target_points(target_image,body_colors) t_h,t_w = pseudo.shape[:2] pad = 10 plt.imshow(pseudo) for i,(type,col,x,y) in enumerate(zip(tt,body_colors,[pad,pad,t_h-pad,t_h-pad],[pad,2*pad,pad,2*pad])): x = 10 y = i*10+10 plt.text(x, y, type, fontsize=18,color = col) plt.title("pixel targets") affinity_colors = ['dodgerblue','yellow','purple','red','lime','orange','hotpink'] def color_target_lines(target_pose,affinity_colors): pseudo_net = np.zeros((target_pose.shape[1],target_pose.shape[2],3)) for i,col in enumerate(affinity_colors): bright = target_pose[i,:,:] rgb = Color(col).rgb color_im = bright[:,:,np.newaxis] * np.asarray(rgb)[np.newaxis,np.newaxis,:] pseudo_net += color_im pseudo_net = pseudo_net.clip(0,1) return pseudo_net plt.subplot(3,3,3) pseudo_net = color_target_lines(target_pose,affinity_colors) plt.imshow(pseudo_net) plt.title("affinity field") plt.subplot(3,3,5) pseudo_belief = color_target_points(score_map[0,:4,:,:],body_colors) plt.imshow(pseudo_belief) plt.title("network belief") plt.subplot(3,3,6) pseudo_belief = color_target_lines(score_map[0,4:,:,:],affinity_colors) plt.imshow(pseudo_belief) plt.title("network belief") pseudo = np.zeros((target_image.shape[1],target_image.shape[2],3)) for i,col in enumerate(body_colors): plt.subplot(3,4,9+i) bright = score_map[0,i,:,:] rgb = Color(col).rgb color_im = bright[:,:,np.newaxis] * np.asarray(rgb)[np.newaxis,np.newaxis,:] color_im = color_im.clip(0,1) plt.imshow(color_im) return Fig1 # # EXAMPLE OF AUGMENTATION # index = 5 # geometry = pickle.load( open( tracking_folder+'/geometry.pkl', "rb" ) ) # depth_scale = geometry['d_cam_params'][3][4] # xy = h5_file['annotations'][index] # c_image = h5_file['c_images'][index] # dac_image = h5_file['dac_images'][index] # # images = im[:3,:,:].astype('float32') # # images = np.moveaxis(images,0,2)[np.newaxis,:,:,:] # images = c_image[np.newaxis,:,:,[2,1,0]] # import imgaug.augmenters as iaa # seq = iaa.Sequential([ # # iaa.Crop(px=(0, 100)), # crop images from each side by 0 to 16px (randomly chosen) # iaa.CropAndPad(percent=(-0.05, 0.15), sample_independently=False), # iaa.Fliplr(0.5), # horizontally flip 50% of the images # iaa.Sometimes(.2, iaa.GaussianBlur(sigma=(0, 1.5)) ), # blur images with a sigma of 0 to 3.0 # iaa.Sometimes( 1, iaa.Dropout(p = (0,0.2)) ), # iaa.Affine(rotate=(-30, 30)), # iaa.Affine(translate_percent={"x": (-0.2, 0.2), "y": (-0.2, 0.2)}) # ]) # for _ in range(5): # images_aug, xy_aug_list = seq(images = images, keypoints=[xy]) # xy_aug = xy_aug_list[0] # plt.figure(figsize=(15,15)) # plt.subplot(2,2,1) # plt.imshow(images[0,...]) # plt.plot(xy[:,0],xy[:,1],'or') # plt.subplot(2,2,2) # plt.imshow(images_aug[0,...]) # plt.plot(xy_aug[:,0],xy_aug[:,1],'or') # plt.show() # plt.figure(figsize = (20,20)) # st = 620 # for i,index in enumerate(range(st,st+100)): # plt.subplot(10,10,1+i) # c_image = h5_file['c_images'][index] # # blank_image = np.zeros_like(c_image) # plt.imshow(c_image[:,:,[2,1,0]]) # plt.title(index) # plt.show() # # cv2.imshow('hm',c_image[:,:,:]) # # cv2.waitKey(500) # index = 10 # xy = h5_file['annotations'][index] # c_image = h5_file['c_images'][index] # dac_image = h5_file['dac_images'][index] # for index in range(10): # c_image = h5_file['c_images'][index] # # blank_image = np.zeros_like(c_image) # cv2.imshow('hm',c_image[:,:,:]) # cv2.waitKey(500) # cv2.destroyAllWindows()

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Python

photutils/psf/tests/test_groupstars.py

Onoddil/photutils

433f3e54d3f53282ae04eadde9e1ddf657944590

[ "BSD-3-Clause" ]

null

photutils/psf/tests/test_groupstars.py

Onoddil/photutils

433f3e54d3f53282ae04eadde9e1ddf657944590

[ "BSD-3-Clause" ]

null

photutils/psf/tests/test_groupstars.py

Onoddil/photutils

433f3e54d3f53282ae04eadde9e1ddf657944590

[ "BSD-3-Clause" ]

null

# Licensed under a 3-clause BSD style license - see LICENSE.rst """ Tests for the groupstars module. """ from astropy.table import Table, vstack import numpy as np from numpy.testing import assert_almost_equal import pytest from ..groupstars import DAOGroup, DBSCANGroup try: import sklearn.cluster # noqa HAS_SKLEARN = True except ImportError: HAS_SKLEARN = False def assert_table_almost_equal(table1, table2): assert table1.colnames == table2.colnames assert table1.meta == table2.meta for colname in table1.colnames: assert_almost_equal(table1[colname], table2[colname]) class TestDAOGROUP: def test_daogroup_one(self): """ +---------+--------+---------+---------+--------+---------+ | * * * * | | | 0.2 + + | | | | | | 0 + * * + | | | | | | -0.2 + + | | | * * * * | +---------+--------+---------+---------+--------+---------+ 0 0.5 1 1.5 2 x and y axis are in pixel coordinates. Each asterisk represents the centroid of a star. """ x_0 = np.array([0, np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4, -np.sqrt(2)/4]) y_0 = np.array([0, np.sqrt(2)/4, -np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4]) x_1 = x_0 + 2.0 first_group = Table([x_0, y_0, np.arange(len(x_0)) + 1, np.ones(len(x_0), dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) second_group = Table([x_1, y_0, len(x_0) + np.arange(len(x_0)) + 1, 2*np.ones(len(x_0), dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) starlist = vstack([first_group, second_group]) daogroup = DAOGroup(crit_separation=0.6) test_starlist = daogroup(starlist['x_0', 'y_0', 'id']) assert_table_almost_equal(starlist, test_starlist) def test_daogroup_two(self): """ +--------------+--------------+-------------+--------------+ 3 + * + | * | 2.5 + * + | * | 2 + * + | | 1.5 + + | | 1 + * + | * | 0.5 + * + | * | 0 + * + +--------------+--------------+-------------+--------------+ -1 -0.5 0 0.5 1 """ first_group = Table([np.zeros(5), np.linspace(0, 1, 5), np.arange(5) + 1, np.ones(5, dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) second_group = Table([np.zeros(5), np.linspace(2, 3, 5), 6 + np.arange(5), 2*np.ones(5, dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) starlist = vstack([first_group, second_group]) daogroup = DAOGroup(crit_separation=0.3) test_starlist = daogroup(starlist['x_0', 'y_0', 'id']) assert_table_almost_equal(starlist, test_starlist) def test_daogroup_three(self): """ 1 +--+-------+--------+--------+--------+-------+--------+--+ | | | | | | 0.5 + + | | | | 0 + * * * * * * * * * * + | | | | -0.5 + + | | | | | | -1 +--+-------+--------+--------+--------+-------+--------+--+ 0 0.5 1 1.5 2 2.5 3 """ first_group = Table([np.linspace(0, 1, 5), np.zeros(5), np.arange(5) + 1, np.ones(5, dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) second_group = Table([np.linspace(2, 3, 5), np.zeros(5), 6 + np.arange(5), 2*np.ones(5, dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) starlist = vstack([first_group, second_group]) daogroup = DAOGroup(crit_separation=0.3) test_starlist = daogroup(starlist['x_0', 'y_0', 'id']) assert_table_almost_equal(starlist, test_starlist) def test_daogroup_four(self): """ +-+---------+---------+---------+---------+-+ 1 + * + | * * | | | | | 0.5 + + | | | | | | 0 + * * + | | | | -0.5 + + | | | | | * * | -1 + * + +-+---------+---------+---------+---------+-+ -1 -0.5 0 0.5 1 """ x = np.linspace(-1., 1., 5) y = np.sqrt(1. - x**2) xx = np.hstack((x, x)) yy = np.hstack((y, -y)) starlist = Table([xx, yy, np.arange(10) + 1, np.ones(10, dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) daogroup = DAOGroup(crit_separation=2.5) test_starlist = daogroup(starlist['x_0', 'y_0', 'id']) assert_table_almost_equal(starlist, test_starlist) def test_daogroup_five(self): """ +--+--------+--------+-------+--------+--------+--------+--+ 3 + * + | * | 2.5 + * + | * | 2 + * + | | 1.5 + * * * * * * * * * * + | | 1 + * + | * | 0.5 + * + | * | 0 + * + +--+--------+--------+-------+--------+--------+--------+--+ 0 0.5 1 1.5 2 2.5 3 """ first_group = Table([1.5*np.ones(5), np.linspace(0, 1, 5), np.arange(5) + 1, np.ones(5, dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) second_group = Table([1.5*np.ones(5), np.linspace(2, 3, 5), 6 + np.arange(5), 2*np.ones(5, dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) third_group = Table([np.linspace(0, 1, 5), 1.5*np.ones(5), 11 + np.arange(5), 3*np.ones(5, dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) fourth_group = Table([np.linspace(2, 3, 5), 1.5*np.ones(5), 16 + np.arange(5), 4*np.ones(5, dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) starlist = vstack([first_group, second_group, third_group, fourth_group]) daogroup = DAOGroup(crit_separation=0.3) test_starlist = daogroup(starlist['x_0', 'y_0', 'id']) assert_table_almost_equal(starlist, test_starlist) def test_daogroup_six(self): """ +------+----------+----------+----------+----------+------+ | * * * * * * | | | 0.2 + + | | | | | | 0 + * * * + | | | | | | -0.2 + + | | | * * * * * * | +------+----------+----------+----------+----------+------+ 0 1 2 3 4 """ x_0 = np.array([0, np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4, -np.sqrt(2)/4]) y_0 = np.array([0, np.sqrt(2)/4, -np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4]) x_1 = x_0 + 2.0 x_2 = x_0 + 4.0 first_group = Table([x_0, y_0, np.arange(5) + 1, np.ones(5, dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) second_group = Table([x_1, y_0, 6 + np.arange(5), 2*np.ones(5, dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) third_group = Table([x_2, y_0, 11 + np.arange(5), 3*np.ones(5, dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) starlist = vstack([first_group, second_group, third_group]) daogroup = DAOGroup(crit_separation=0.6) test_starlist = daogroup(starlist['x_0', 'y_0', 'id']) assert_table_almost_equal(starlist, test_starlist) def test_isolated_sources(self): """ Test case when all sources are isolated. """ x_0 = np.array([0, np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4, -np.sqrt(2)/4]) y_0 = np.array([0, np.sqrt(2)/4, -np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4]) starlist = Table([x_0, y_0, np.arange(len(x_0)) + 1, np.arange(len(x_0)) + 1], names=('x_0', 'y_0', 'id', 'group_id')) daogroup = DAOGroup(crit_separation=0.01) test_starlist = daogroup(starlist['x_0', 'y_0', 'id']) assert_table_almost_equal(starlist, test_starlist) def test_id_column(self): x_0 = np.array([0, np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4, -np.sqrt(2)/4]) y_0 = np.array([0, np.sqrt(2)/4, -np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4]) starlist = Table([x_0, y_0, np.arange(len(x_0)) + 1, np.arange(len(x_0)) + 1], names=('x_0', 'y_0', 'id', 'group_id')) daogroup = DAOGroup(crit_separation=0.01) test_starlist = daogroup(starlist['x_0', 'y_0']) assert_table_almost_equal(starlist, test_starlist) def test_id_column_raise_error(self): x_0 = np.array([0, np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4, -np.sqrt(2)/4]) y_0 = np.array([0, np.sqrt(2)/4, -np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4]) starlist = Table([x_0, y_0, np.arange(len(x_0)), np.arange(len(x_0)) + 1], names=('x_0', 'y_0', 'id', 'group_id')) daogroup = DAOGroup(crit_separation=0.01) with pytest.raises(ValueError): daogroup(starlist['x_0', 'y_0', 'id']) @pytest.mark.skipif('not HAS_SKLEARN') class TestDBSCANGroup: def test_group_stars_one(object): x_0 = np.array([0, np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4, -np.sqrt(2)/4]) y_0 = np.array([0, np.sqrt(2)/4, -np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4]) x_1 = x_0 + 2.0 first_group = Table([x_0, y_0, np.arange(len(x_0)) + 1, np.ones(len(x_0), dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) second_group = Table([x_1, y_0, len(x_0) + np.arange(len(x_0)) + 1, 2*np.ones(len(x_0), dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) starlist = vstack([first_group, second_group]) dbscan = DBSCANGroup(crit_separation=0.6) test_starlist = dbscan(starlist['x_0', 'y_0', 'id']) assert_table_almost_equal(starlist, test_starlist) def test_group_stars_two(object): first_group = Table([1.5*np.ones(5), np.linspace(0, 1, 5), np.arange(5) + 1, np.ones(5, dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) second_group = Table([1.5*np.ones(5), np.linspace(2, 3, 5), 6 + np.arange(5), 2*np.ones(5, dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) third_group = Table([np.linspace(0, 1, 5), 1.5*np.ones(5), 11 + np.arange(5), 3*np.ones(5, dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) fourth_group = Table([np.linspace(2, 3, 5), 1.5*np.ones(5), 16 + np.arange(5), 4*np.ones(5, dtype=int)], names=('x_0', 'y_0', 'id', 'group_id')) starlist = vstack([first_group, second_group, third_group, fourth_group]) dbscan = DBSCANGroup(crit_separation=0.3) test_starlist = dbscan(starlist['x_0', 'y_0', 'id']) assert_table_almost_equal(starlist, test_starlist) def test_isolated_sources(self): """ Test case when all sources are isolated. """ x_0 = np.array([0, np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4, -np.sqrt(2)/4]) y_0 = np.array([0, np.sqrt(2)/4, -np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4]) starlist = Table([x_0, y_0, np.arange(len(x_0)) + 1, np.arange(len(x_0)) + 1], names=('x_0', 'y_0', 'id', 'group_id')) dbscan = DBSCANGroup(crit_separation=0.01) test_starlist = dbscan(starlist['x_0', 'y_0', 'id']) assert_table_almost_equal(starlist, test_starlist) def test_id_column(self): x_0 = np.array([0, np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4, -np.sqrt(2)/4]) y_0 = np.array([0, np.sqrt(2)/4, -np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4]) starlist = Table([x_0, y_0, np.arange(len(x_0)) + 1, np.arange(len(x_0)) + 1], names=('x_0', 'y_0', 'id', 'group_id')) dbscan = DBSCANGroup(crit_separation=0.01) test_starlist = dbscan(starlist['x_0', 'y_0']) assert_table_almost_equal(starlist, test_starlist) def test_id_column_raise_error(self): x_0 = np.array([0, np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4, -np.sqrt(2)/4]) y_0 = np.array([0, np.sqrt(2)/4, -np.sqrt(2)/4, np.sqrt(2)/4, -np.sqrt(2)/4]) starlist = Table([x_0, y_0, np.arange(len(x_0)), np.arange(len(x_0)) + 1], names=('x_0', 'y_0', 'id', 'group_id')) dbscan = DBSCANGroup(crit_separation=0.01) with pytest.raises(ValueError): dbscan(starlist['x_0', 'y_0', 'id'])

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ac2caa6da07958c426fbea7ac8132740efedf17a

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Python

tests/test_opts.py

loriab/pylibefp

f8d934fd1b25de4eccfd2915a7306ac766a0b0a1

[ "BSD-3-Clause" ]

2

2019-01-27T13:37:08.000Z

2021-11-04T16:44:29.000Z

tests/test_opts.py

loriab/pylibefp

f8d934fd1b25de4eccfd2915a7306ac766a0b0a1

[ "BSD-3-Clause" ]

7

2018-10-06T23:17:20.000Z

2019-09-03T06:45:31.000Z

tests/test_opts.py

loriab/pylibefp

f8d934fd1b25de4eccfd2915a7306ac766a0b0a1

[ "BSD-3-Clause" ]

1

2019-05-26T23:10:52.000Z

import sys import pytest import pprint import pylibefp from systems import * from qcelemental.testing import compare_recursive def test_opts_libefp(): asdf = system_1() ref1 = { 'ai_elec': False, 'elec_damp': 'screen', 'ai_disp': False, 'chtr': False, 'swf_cutoff': 0.0, 'enable_cutoff': False, 'disp': False, 'ai_pol': False, 'pol': False, 'xr': False, 'pol_driver': 'iterative', 'ai_xr': False, 'elec': False, 'pol_damp': 'tt', 'disp_damp': 'overlap', 'enable_pbc': False, 'ai_chtr': False } ans1 = asdf.set_opts({}) assert compare_recursive(ref1, ans1, sys._getframe().f_code.co_name + ': blank', atol=1.e-6) ref2 = { 'ai_elec': True, 'elec_damp': 'off', 'ai_disp': False, 'chtr': False, 'swf_cutoff': 1.0, 'enable_cutoff': False, 'disp': False, 'ai_pol': False, 'pol': False, 'xr': False, 'pol_driver': 'iterative', 'ai_xr': False, 'elec': True, 'pol_damp': 'tt', 'disp_damp': 'overlap', 'enable_pbc': False, 'ai_chtr': False } ans2 = asdf.set_opts({ 'elec_damp': 'OFF', 'swf_cutoff': 1.0, 'elec': True, 'ai_elec': True, 'enable_cutoff': False }) assert compare_recursive(ref2, ans2, sys._getframe().f_code.co_name + ': setting', atol=1.e-6) ref3 = { 'ai_elec': True, 'elec_damp': 'off', 'ai_disp': False, 'chtr': False, 'swf_cutoff': 2.0, 'enable_cutoff': False, 'disp': False, 'ai_pol': False, 'pol': False, 'xr': False, 'pol_driver': 'iterative', 'ai_xr': False, 'elec': False, 'pol_damp': 'tt', 'disp_damp': 'tt', 'enable_pbc': False, 'ai_chtr': False } ans3 = asdf.set_opts({'swf_cutoff': 2, 'elec': False, 'ai_elec': True, 'disp_damp': 'TT'}, append='append') assert compare_recursive(ref3, ans3, sys._getframe().f_code.co_name + ': append setting', atol=1.e-6) ref4 = { 'ai_elec': False, 'elec_damp': 'off', 'ai_disp': False, 'chtr': False, 'swf_cutoff': 0.0, 'enable_cutoff': False, 'disp': False, 'ai_pol': False, 'pol': False, 'xr': False, 'pol_driver': 'iterative', 'ai_xr': False, 'elec': True, 'pol_damp': 'tt', 'disp_damp': 'overlap', 'enable_pbc': False, 'ai_chtr': False } ans4 = asdf.set_opts({ 'elec_damp': 'OFF', 'swf_cutoff': 0.0, 'elec': True, 'enable_cutoff': False }, append='libefp') assert compare_recursive(ref4, ans4, sys._getframe().f_code.co_name + ': reset setting', atol=1.e-6) def test_opts_fail_1(): asdf = system_1() ans = asdf.set_opts({'nonsense_key': 'harmless'}) with pytest.raises(pylibefp.EFPSyntaxError) as e_info: ans = asdf.set_opts({'elec_damp': 'nonsense'}) def test_opts_fail_2(): asdf = system_1() with pytest.raises(pylibefp.EFPSyntaxError) as e_info: ans = asdf.set_opts({'elec': 'yEs'}) def test_opts_psi(): asdf = system_1() ref = { 'qm_elst': False, 'elst_damping': 'screen', 'qm_disp': False, 'chtr': False, 'swf_cutoff': 0.0, 'enable_cutoff': False, 'disp': False, 'qm_ind': False, 'ind': False, 'exch': False, 'ind_driver': 'iterative', 'qm_exch': False, 'elst': False, 'ind_damping': 'tt', 'disp_damping': 'overlap', 'enable_pbc': False, 'qm_chtr': False } ans = asdf.set_opts({}, label='psi') assert compare_recursive(ref, ans, sys._getframe().f_code.co_name + ': psi blank', atol=1.e-6) ref = { 'qm_elst': True, 'elst_damping': 'off', 'qm_disp': False, 'chtr': False, 'swf_cutoff': 1.0, 'enable_cutoff': False, 'disp': False, 'qm_ind': False, 'ind': False, 'exch': False, 'ind_driver': 'iterative', 'qm_exch': False, 'elst': True, 'ind_damping': 'tt', 'disp_damping': 'overlap', 'enable_pbc': False, 'qm_chtr': False } ans = asdf.set_opts( { 'elst_damping': 'OFF', 'swf_cutoff': 1.0, 'elst': True, 'qm_elst': True, 'enable_cutoff': False }, label='psi') assert compare_recursive(ref, ans, sys._getframe().f_code.co_name + ': psi setting', atol=1.e-6) ref = { 'qm_elst': True, 'elst_damping': 'off', 'qm_disp': False, 'chtr': False, 'swf_cutoff': 2.0, 'enable_cutoff': False, 'disp': False, 'qm_ind': False, 'ind': False, 'exch': False, 'ind_driver': 'iterative', 'qm_exch': False, 'elst': False, 'ind_damping': 'tt', 'disp_damping': 'tt', 'enable_pbc': False, 'qm_chtr': False } ans = asdf.set_opts({ 'swf_cutoff': 2, 'elst': False, 'qm_elst': True, 'disp_damping': 'TT' }, append='append', label='psi') assert compare_recursive(ref, ans, sys._getframe().f_code.co_name + ': psi append setting', atol=1.e-6) ref = { 'qm_elst': False, 'elst_damping': 'off', 'qm_disp': False, 'chtr': False, 'swf_cutoff': 0.0, 'enable_cutoff': False, 'disp': False, 'qm_ind': False, 'ind': False, 'exch': False, 'ind_driver': 'iterative', 'qm_exch': False, 'elst': True, 'ind_damping': 'tt', 'disp_damping': 'overlap', 'enable_pbc': False, 'qm_chtr': False } ans = asdf.set_opts({ 'elst_damping': 'OFF', 'swf_cutoff': 0.0, 'elst': True, 'enable_cutoff': False }, append='libefp', label='psi') assert compare_recursive(ref, ans, sys._getframe().f_code.co_name + ': psi reset setting', atol=1.e-6) def test_opts_psi_dflt(): asdf = system_1() ref = { 'qm_elst': True, 'elst_damping': 'screen', 'qm_disp': False, 'chtr': False, 'swf_cutoff': 0.0, 'enable_cutoff': False, 'disp': True, 'qm_ind': True, 'ind': True, 'exch': True, 'ind_driver': 'iterative', 'qm_exch': False, 'elst': True, 'ind_damping': 'tt', 'disp_damping': 'overlap', 'enable_pbc': False, 'qm_chtr': False } ans = asdf.set_opts({}, label='psi', append='psi') assert compare_recursive(ref, ans, sys._getframe().f_code.co_name + ': psi default blank', atol=1.e-6) ref = { 'qm_elst': False, 'elst_damping': 'off', 'qm_disp': False, 'chtr': False, 'swf_cutoff': 1.0, 'enable_cutoff': False, 'disp': True, 'qm_ind': True, 'ind': True, 'exch': True, 'ind_driver': 'iterative', 'qm_exch': False, 'elst': True, 'ind_damping': 'tt', 'disp_damping': 'overlap', 'enable_pbc': False, 'qm_chtr': False } ans = asdf.set_opts( { 'elst_damping': 'OFF', 'swf_cutoff': 1.0, 'elst': True, 'qm_elst': False, 'enable_cutoff': False }, label='psi', append='append') assert compare_recursive(ref, ans, sys._getframe().f_code.co_name + ': psi default append setting', atol=1.e-6) ref = { 'qm_elst': True, 'elst_damping': 'overlap', 'qm_disp': False, 'chtr': False, 'swf_cutoff': 2.0, 'enable_cutoff': True, 'disp': True, 'qm_ind': True, 'ind': True, 'exch': True, 'ind_driver': 'iterative', 'qm_exch': False, 'elst': False, 'ind_damping': 'tt', 'disp_damping': 'overlap', 'enable_pbc': False, 'qm_chtr': False } ans = asdf.set_opts({ 'elst_damping': 'OVERlap', 'swf_cutoff': 2.0, 'elst': False, 'enable_cutoff': True }, append='psi', label='psi') assert compare_recursive(ref, ans, sys._getframe().f_code.co_name + ': psi default reset setting', atol=1.e-6)

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7

ac51c75f24fba3b78d60603284f8add62c6e4703

8,494

py

Python

tests/functional_tests/test_fjs_instances.py

mcfadd/Job_Shop_Schedule_Problem

94696af80911c80174682f97fc6f607e4c73ae54

[ "0BSD" ]

45

2019-08-27T21:42:42.000Z

2022-02-17T12:35:18.000Z

tests/functional_tests/test_fjs_instances.py

aisha-farooq/Job_Shop_Schedule_Problem

94696af80911c80174682f97fc6f607e4c73ae54

[ "0BSD" ]

9

2019-07-20T19:45:01.000Z

2022-03-30T19:36:26.000Z

tests/functional_tests/test_fjs_instances.py

aisha-farooq/Job_Shop_Schedule_Problem

94696af80911c80174682f97fc6f607e4c73ae54

[ "0BSD" ]

17

2020-05-05T07:38:12.000Z

2022-03-23T02:36:44.000Z

import random import unittest from JSSP import data from JSSP.solver import Solver from tests.util import project_root, tmp_dir, get_files_with_suffix, rm_tree fjs_data = get_files_with_suffix(project_root / 'data/fjs_data', '.fjs') fjs_data = random.choices(fjs_data, k=20) class TestFJSOptimization(unittest.TestCase): def setUp(self) -> None: if not tmp_dir.exists(): tmp_dir.mkdir() def tearDown(self) -> None: rm_tree(tmp_dir) def test_ts_iter(self): # parameters iterations = 50 # keep this value small num_processes = 1 tabu_list_size = 10 neighborhood_size = 25 neighborhood_wait = 0.1 probability_change_machine = 0.8 for i, fjs_instance in enumerate(fjs_data): print(f"testing fjs instance {fjs_instance} ({i + 1} of {len(fjs_data)})") try: data_instance = data.FJSData(fjs_instance) solver = Solver(data_instance) solver.tabu_search_iter(iterations, num_solutions_per_process=1, num_processes=num_processes, tabu_list_size=tabu_list_size, neighborhood_size=neighborhood_size, neighborhood_wait=neighborhood_wait, probability_change_machine=probability_change_machine) except Exception as e: self.fail(f'Unexpected exception raised while running TS for {fjs_instance}:' + str(e)) self.assertIsNotNone(solver.solution, "TS should have produced a best solution") # output results output_file = tmp_dir / 'fjs_ts_schedule.xlsx' solver.solution.create_schedule_xlsx_file(output_file) self.assertTrue(output_file.exists(), "fjs_ts_schedule.xlsx was not produced") def test_ts_iter_benchmark(self): # parameters iterations = 50 # keep this value small num_processes = 1 tabu_list_size = 10 neighborhood_size = 25 neighborhood_wait = 0.1 probability_change_machine = 0.8 for i, fjs_instance in enumerate(fjs_data): print(f"testing fjs instance {fjs_instance} ({i + 1} of {len(fjs_data)})") try: data_instance = data.FJSData(fjs_instance) solver = Solver(data_instance) solver.tabu_search_iter(iterations, num_solutions_per_process=1, num_processes=num_processes, tabu_list_size=tabu_list_size, neighborhood_size=neighborhood_size, neighborhood_wait=neighborhood_wait, probability_change_machine=probability_change_machine, benchmark=True) except Exception as e: self.fail(f'Unexpected exception raised while running TS for {fjs_instance}:' + str(e)) self.assertIsNotNone(solver.solution, "TS should have produced a best solution") # output results output_file = tmp_dir / 'fjs_ts_benchmark' solver.output_benchmark_results(output_file, auto_open=False) self.assertTrue(output_file.exists(), "fjs_ts_benchmark was not produced") def test_ga_iter(self): # parameters iterations = 10 # keep this value small population_size = 50 # keep this value small mutation_probability = 0.8 selection_size = 5 for i, fjs_instance in enumerate(fjs_data): print(f"testing fjs instance {fjs_instance} ({i + 1} of {len(fjs_data)})") try: data_instance = data.FJSData(fjs_instance) # run GA solver = Solver(data_instance) solver.genetic_algorithm_iter(iterations=iterations, population_size=population_size, mutation_probability=mutation_probability, selection_size=selection_size) except Exception as e: self.fail(f'Unexpected exception raised while running GA for {fjs_instance}:' + str(e)) self.assertIsNotNone(solver.solution) self.assertIsNotNone(solver.ga_agent) # test parameters were set self.assertEqual(iterations, solver.ga_agent.iterations) self.assertFalse(solver.ga_agent.time_condition) self.assertFalse(solver.ga_agent.benchmark) self.assertEqual(population_size, solver.ga_agent.population_size) self.assertEqual(mutation_probability, solver.ga_agent.mutation_probability) self.assertEqual(selection_size, solver.ga_agent.selection_size) self.assertEqual(population_size, len(solver.ga_agent.initial_population)) self.assertEqual(population_size, len(solver.ga_agent.result_population)) # test that the result solution is better than all the solutions in the initial population for initial_sol in solver.ga_agent.initial_population: self.assertLessEqual(solver.solution, initial_sol) # test that the result population does not have duplicate solutions seen = [] self.assertTrue(not any(sol in seen or seen.append(sol) for sol in solver.ga_agent.result_population)) # output results output_file = tmp_dir / 'fjs_ga_schedule.xlsx' solver.solution.create_schedule_xlsx_file(output_file) self.assertTrue(output_file.exists(), "fjs_ga_schedule.xlsx was not produced") def test_ga_iter_benchmark(self): # parameters iterations = 10 # keep this value small population_size = 50 # keep this value small mutation_probability = 0.8 selection_size = 5 for i, fjs_instance in enumerate(fjs_data): print(f"testing fjs instance {fjs_instance} ({i + 1} of {len(fjs_data)})") try: data_instance = data.FJSData(fjs_instance) # run GA solver = Solver(data_instance) solver.genetic_algorithm_iter(iterations=iterations, population_size=population_size, mutation_probability=mutation_probability, selection_size=selection_size, benchmark=True) except Exception as e: self.fail(f'Unexpected exception raised while running GA for {fjs_instance}:' + str(e)) self.assertIsNotNone(solver.solution) self.assertIsNotNone(solver.ga_agent) # test parameters were set self.assertEqual(iterations, solver.ga_agent.iterations) self.assertFalse(solver.ga_agent.time_condition) self.assertTrue(solver.ga_agent.benchmark) self.assertEqual(population_size, solver.ga_agent.population_size) self.assertEqual(mutation_probability, solver.ga_agent.mutation_probability) self.assertEqual(selection_size, solver.ga_agent.selection_size) self.assertEqual(population_size, len(solver.ga_agent.initial_population)) self.assertEqual(population_size, len(solver.ga_agent.result_population)) # test that the result solution is better than all the solutions in the initial population for initial_sol in solver.ga_agent.initial_population: self.assertLessEqual(solver.solution, initial_sol) # test that the result population does not have duplicate solutions seen = [] self.assertTrue(not any(sol in seen or seen.append(sol) for sol in solver.ga_agent.result_population)) # output results output_file = tmp_dir / 'fjs_ga_benchmark' solver.output_benchmark_results(output_file, auto_open=False) self.assertTrue(output_file.exists(), "fjs_ga_benchmark was not produced") if __name__ == '__main__': unittest.main()

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7

ac52775c1669f559a7a1f49c89b1fd4d81bf1c45

7,633

py

Python

wendigo/device/event_dispatcher.py

medmsyk/wendigopy

36e0759bf8b065548fd638063768522704506236

[ "Apache-2.0" ]

null

wendigo/device/event_dispatcher.py

medmsyk/wendigopy

36e0759bf8b065548fd638063768522704506236

[ "Apache-2.0" ]

1

2022-01-05T10:28:49.000Z

2022-03-20T09:17:04.000Z

wendigo/device/event_dispatcher.py

medmsyk/wendigopy

36e0759bf8b065548fd638063768522704506236

[ "Apache-2.0" ]

null

from typing import Callable, List from wendigo import Keys from wendigo.device import DeviceState from wendigo.device.dll import EventDispatcher as DllEventDispatcher, \ DeviceEventArgs, DeviceEventHandler from wendigo.logger import Logger class EventDispatcher: """ Event dispatcher. """ @classmethod def get_event_handler(cls, event_handler: Callable[[DeviceState], None]) -> DeviceEventHandler: """ Get an event handler. Parameters ---------- event_handler: Event Handler. Returns ------- device_event_handler: Device event handler. """ def wrapper(e: DeviceEventArgs): try: event_handler(DeviceState(e)) except: Logger.exception("An exception raised in event hadler") return DeviceEventHandler(wrapper) @classmethod def get_event_handler_once(cls, name: str, event_handler: Callable[[DeviceState], None]) -> DeviceEventHandler: """ Get an event handler which is called only once. Parameters ---------- name: Name. event_handler: Event handler. Returns ------- device_event_handler: Device event handler. """ def wrapper(e: DeviceEventArgs): try: cls.unlisten(name) event_handler(DeviceState(e)) except: Logger.exception("An exception raised in event hadler") return DeviceEventHandler(wrapper) @classmethod def key_down(cls, name: str, keys: List[Keys], event_handler: Callable[[DeviceState], None], for_system: bool=False): """ Listen for key down. Parameters ---------- name: Name. keys: Keys. event_handler: Event handler. for_system: The event is for system or not. """ DllEventDispatcher.KeyDown(name, keys, cls.get_event_handler(event_handler), for_system) @classmethod def key_down_once(cls, name: str, keys: List[Keys], event_handler: Callable[[DeviceState], None], for_system: bool=False): """ Listen for key down which is called only once. Parameters ---------- name: Name. keys: Keys. event_handler: Event handler. for_system: The event is for system or not. """ DllEventDispatcher.KeyDown(name, keys, cls.get_event_handler_once(name, event_handler), for_system) @classmethod def key_up(cls, name: str, keys: List[Keys], event_handler: Callable[[DeviceState], None], for_system: bool=False): """ Listen for key up. Parameters ---------- name: Name. keys: Keys. event_handler: Event handler. for_system: The event is for system or not. """ DllEventDispatcher.KeyUp(name, keys, cls.get_event_handler(event_handler), for_system) @classmethod def key_up_once(cls, name: str, keys: List[Keys], event_handler: Callable[[DeviceState], None], for_system: bool=False): """ Listen for key up which is called only once. Parameters ---------- name: Name. keys: Keys. event_handler: Event handler. for_system: The event is for system or not. """ DllEventDispatcher.KeyUp(name, keys, cls.get_event_handler_once(name, event_handler), for_system) @classmethod def key_press(cls, name: str, keys: List[Keys], event_handler: Callable[[DeviceState], None], for_system: bool=False): """ Listen for key press. Parameters ---------- name: Name. keys: Keys. event_handler: Event handler. for_system: The event is for system or not. """ DllEventDispatcher.KeyPress(name, keys, cls.get_event_handler(event_handler), for_system) @classmethod def key_press_once(cls, name: str, keys: List[Keys], event_handler: Callable[[DeviceState], None], for_system: bool=False): """ Listen for key press which is called only once. Parameters ---------- name: Name. keys: Keys. event_handler: Event handler. for_system: The event is for system or not. """ DllEventDispatcher.KeyPress(name, keys, cls.get_event_handler_once(name, event_handler), for_system) @classmethod def mouse_move(cls, name: str, event_handler: Callable[[DeviceState], None], for_system: bool=False): """ Listen for mouse move. Parameters ---------- name: Name. event_handler: Event handler. for_system: The event is for system or not. """ DllEventDispatcher.MouseMove(name, cls.get_event_handler(event_handler), for_system) @classmethod def mouse_move_once(cls, name: str, event_handler: Callable[[DeviceState], None], for_system: bool=False): """ Listen for mouse move which is called only once. Parameters ---------- name: Name. event_handler: Event handler. for_system: The event is for system or not. """ DllEventDispatcher.MouseMove(name, cls.get_event_handler_once(name, event_handler), for_system) @classmethod def mouse_wheel(cls, name: str, event_handler: Callable[[DeviceState], None], for_system: bool=False): """ Listen for mouse wheel. Parameters ---------- name: Name. event_handler: Event handler. for_system: The event is for system or not. """ DllEventDispatcher.MouseWheel(name, cls.get_event_handler(event_handler), for_system) @classmethod def mouse_wheel_once(cls, name: str, event_handler: Callable[[DeviceState], None], for_system: bool=False): """ Listen for mouse wheel which is called only once. Parameters ---------- name: Name. event_handler: Event handler. for_system: The event is for system or not. """ DllEventDispatcher.MouseWheel(name, cls.get_event_handler_once(name, event_handler), for_system) @classmethod def mouse_tilt(cls, name: str, event_handler: Callable[[DeviceState], None], for_system: bool=False): """ Listen for mouse tilt. Parameters ---------- name: Name. event_handler: Event handler. for_system: The event is for system or not. """ DllEventDispatcher.MouseTilt(name, cls.get_event_handler(event_handler), for_system) @classmethod def mouse_tilt_once(cls, name: str, event_handler: Callable[[DeviceState], None], for_system: bool=False): """ Listen for mouse tilt which is called only once. Parameters ---------- name: Name. event_handler: Event handler. for_system: The event is for system or not. """ DllEventDispatcher.MouseTilt(name, cls.get_event_handler_once(name, event_handler), for_system) @classmethod def unlisten(cls, name: str, for_system: bool=False): """ Unlisten for device event. Parameters ---------- name: Name. for_system: The event is for system or not. """ DllEventDispatcher.Unlisten(name, for_system)

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0

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7,633

226

129

33.774336

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null

1

0

1

0

null

0

1

0

8

3bbdb27afd0611a4fc0107178eda65cbab9a0ae7

21,424

py

Python

src/models.py

ottokart/punctuator

99550ed8260a8438dbeceece79f2d9743b2c6a3b

[ "MIT" ]

92

2015-03-19T09:55:04.000Z

2021-10-22T02:46:32.000Z

src/models.py

ottokart/punctuator

99550ed8260a8438dbeceece79f2d9743b2c6a3b

[ "MIT" ]

13

2015-04-30T10:43:49.000Z

2021-05-14T03:30:28.000Z

src/models.py

ottokart/punctuator

99550ed8260a8438dbeceece79f2d9743b2c6a3b

[ "MIT" ]

26

2015-07-23T13:51:36.000Z

2021-10-31T04:32:27.000Z

# coding: utf-8 import numpy as np import cPickle import activation_functions from itertools import izip from activation_functions import Softmax, Sigmoid, Tanh from utils import get_vocabulary_size, load_model FLOATX = np.float64 class Model(object): def __init__(self): super(Model, self).__init__() self.initialized = False def output_word_probability(self, output_word_index): assert self.initialized, "initialize or load before using" assert hasattr(self, "y"), "predict before trying to use output" return self.y[range(len(output_word_index)), output_word_index] def train(self, input_word_index, output_word_index, pause=None, learning_rate=0.1): assert self.initialized, "initialize or load before using" self.predict(input_word_index, pause) self.update(input_word_index, output_word_index, learning_rate) return -np.log(self.output_word_probability(output_word_index)) def neg_log_prob(self, input_word_index, output_word_index, pause=None): assert self.initialized, "initialize or load before using" self.predict(input_word_index, pause) return -np.log(self.output_word_probability(output_word_index)) def predict_punctuation(self, input_word_index, pause=None): assert self.initialized, "initialize or load before using" self.predict(input_word_index, pause) return np.argmax(self.y, axis=1) def load(self, model): for attr in model: setattr(self, attr, model[attr]) self.hidden_activation = getattr(activation_functions, self.hidden_activation_name) self.reset_state() self.initialized = True def weights(self, i, o): s = 0.005#np.sqrt(6./(i+o)) return np.random.uniform(low=-s, high=s, size=(i, o)).astype(FLOATX) def slice(self, matrix, size, i): return matrix[:, i*size:(i+1)*size] class T_LSTM(Model): def __init__(self): super(T_LSTM, self).__init__() self.params = ["We", "Wp", # Word embeddings, pauses "W", "Wr", "Wy", # inputs-to-LSTM, recurrency, outputs "Wip", "Wfp", "Wop"] # peepholes self.initialized = False def initialize(self, hidden_size, projection_size, in_vocabulary, out_vocabulary, batch_size, hidden_activation="Tanh", bptt_steps=5, use_pauses=False): self.hidden_size = hidden_size self.projection_size = projection_size self.bptt_steps = bptt_steps self.batch_size = batch_size self.use_pauses = use_pauses self.in_vocabulary = in_vocabulary self.out_vocabulary = out_vocabulary self.hidden_activation_name = hidden_activation self.hidden_activation = getattr(activation_functions, hidden_activation) self.We = self.weights(get_vocabulary_size(self.in_vocabulary), self.projection_size) self.Wp = self.weights(1, self.projection_size) self.W = self.weights(self.projection_size, self.hidden_size*4) self.Wip = self.weights(1, self.hidden_size) self.Wfp = self.weights(1, self.hidden_size) self.Wop = self.weights(1, self.hidden_size) self.Wr = self.weights(self.hidden_size, self.hidden_size*4) self.Wy = self.weights(self.hidden_size, get_vocabulary_size(self.out_vocabulary)) # AdaGread sum of squares of per feature historical gradients for p in self.params: setattr(self, p+"_hg", np.zeros_like(getattr(self, p))) self.reset_state() self.initialized = True def reset_state(self): self.m = np.zeros(shape=(self.batch_size, self.hidden_size)) self.h = np.zeros(shape=(self.batch_size, self.hidden_size)) self.word_history = [] if self.use_pauses: self.pause_history = [] self.m_tm1_history = [] self.h_tm1_history = [] self.z_history = [] self.x_history = [] self.i_history = [] self.ig_history = [] self.fg_history = [] self.og_history = [] self.W_history = [] self.Wr_history = [] self.Wip_history = [] self.Wfp_history = [] self.Wop_history = [] def _remember_state(self, input_word_index, pause=None): self.word_history.append(input_word_index) if self.use_pauses: self.pause_history.append(pause) self.m_tm1_history.append(self.m_tm1) self.h_tm1_history.append(self.h_tm1) self.z_history.append(self.z) self.x_history.append(self.x) self.i_history.append(self.i) self.ig_history.append(self.ig) self.fg_history.append(self.fg) self.og_history.append(self.og) self.W_history.append(self.W.copy()) self.Wr_history.append(self.Wr.copy()) self.Wip_history.append(self.Wip.copy()) self.Wfp_history.append(self.Wfp.copy()) self.Wop_history.append(self.Wop.copy()) if len(self.word_history) > self.bptt_steps: del self.word_history[0] if self.use_pauses: del self.pause_history[0] del self.m_tm1_history[0] del self.h_tm1_history[0] del self.z_history[0] del self.x_history[0] del self.i_history[0] del self.ig_history[0] del self.fg_history[0] del self.og_history[0] del self.W_history[0] del self.Wr_history[0] del self.Wip_history[0] del self.Wfp_history[0] del self.Wop_history[0] def predict(self, input_word_index, pause_duration=None, compute_only_features=False): assert self.initialized, "initialize or load before using" self.m_tm1 = self.m self.h_tm1 = self.h r = np.dot(self.h_tm1, self.Wr) z = self.We[input_word_index] if self.use_pauses: z += np.dot(pause_duration[:,np.newaxis], self.Wp) self.x = self.hidden_activation.y(z) z1 = np.dot(self.x, self.W) z = self.slice(r, self.hidden_size, 0) + self.slice(z1, self.hidden_size, 0) self.i = self.hidden_activation.y(z) z = self.slice(r, self.hidden_size, 1) + self.slice(z1, self.hidden_size, 1) + self.m_tm1 * self.Wip self.ig = Sigmoid.y(z) z = self.slice(r, self.hidden_size, 2) + self.slice(z1, self.hidden_size, 2) + self.m_tm1 * self.Wfp self.fg = Sigmoid.y(z) self.m = self.i * self.ig + self.m_tm1 * self.fg z = self.slice(r, self.hidden_size, 3) + self.slice(z1, self.hidden_size, 3) + self.m * self.Wop self.og = Sigmoid.y(z) self.z = self.hidden_activation.y(self.m) self.h = self.z * self.og if not compute_only_features: z_y = np.dot(self.h, self.Wy) self.y = Softmax.y(z=z_y) if self.use_pauses: self._remember_state(input_word_index, pause_duration[:,np.newaxis]) else: self._remember_state(input_word_index) def _backpropagate(self, output_word_index): dE_dz_y = self.y.copy() # don't remove the copy() part dE_dz_y[range(len(output_word_index)), output_word_index] -= 1. self.dE_dWy = np.dot(self.h.T, dE_dz_y) dE_dh = np.dot(dE_dz_y, self.Wy.T) self.dE_dWe = {} self.dE_dW = np.zeros_like(self.W) self.dE_dWr = np.zeros_like(self.Wr) self.dE_dWip = np.zeros_like(self.Wip) self.dE_dWfp = np.zeros_like(self.Wfp) self.dE_dWop = np.zeros_like(self.Wop) self.dE_dWp = np.zeros_like(self.Wp) dE_dm_tm1 = 0. dE_dh_tm1 = 0. m = self.m pause_history = self.pause_history if self.use_pauses else [None]*len(self.word_history) for pauses, words, W, Wr, Wip, Wfp, Wop, x, m_tm1, h_tm1, z, i, ig, fg, og in reversed(zip( pause_history, self.word_history, self.W_history, self.Wr_history, self.Wip_history, self.Wfp_history, self.Wop_history, self.x_history, self.m_tm1_history, self.h_tm1_history, self.z_history, self.i_history, self.ig_history, self.fg_history, self.og_history)): dE_dh = dE_dh + dE_dh_tm1 dE_dog = dE_dh * z * Sigmoid.dy_dz(y=og) dE_dz = dE_dh * og * self.hidden_activation.dy_dz(y=z) dE_dm = dE_dz + dE_dm_tm1 + dE_dog * Wop dE_dfg = dE_dm * m_tm1 * Sigmoid.dy_dz(y=fg) dE_di = dE_dm * ig * self.hidden_activation.dy_dz(y=i) dE_dig = dE_dm * i * Sigmoid.dy_dz(y=ig) dE_dm_tm1 = dE_dm * fg + dE_dig * Wip + dE_dfg * Wfp self.dE_dWip += (dE_dig * m_tm1).sum(0) self.dE_dWfp += (dE_dfg * m_tm1).sum(0) self.dE_dWop += (dE_dog * m).sum(0) d = np.hstack((dE_di, dE_dig, dE_dfg, dE_dog)) dE_dx = np.dot(d, W.T) * self.hidden_activation.dy_dz(y=x) dE_dh_tm1 = np.dot(d, Wr.T) self.dE_dW += np.dot(x.T, d) self.dE_dWr += np.dot(h_tm1.T, d) for word, dE_dx_word in izip(words, dE_dx): self.dE_dWe[word] = self.dE_dWe.get(word, 0.) + dE_dx_word if self.use_pauses: self.dE_dWp += np.dot(pauses.T, dE_dx) dE_dh = 0. m = m_tm1 def update(self, _, output_word_index, learning_rate): """Uses AdaGrad: Duchi, John, Elad Hazan, and Yoram Singer. "Adaptive subgradient methods for online learning and stochastic optimization." The Journal of Machine Learning Research 12 (2011): 2121-2159.""" assert self.initialized, "initialize or load before using" self._backpropagate(output_word_index) self.Wy_hg += self.dE_dWy**2 self.Wy -= learning_rate * self.dE_dWy / (1e-6 + np.sqrt(self.Wy_hg)) self.Wr_hg += self.dE_dWr**2 self.Wr -= learning_rate * self.dE_dWr / (1e-6 + np.sqrt(self.Wr_hg)) self.Wip_hg += self.dE_dWip**2 self.Wip -= learning_rate * self.dE_dWip / (1e-6 + np.sqrt(self.Wip_hg)) self.Wfp_hg += self.dE_dWfp**2 self.Wfp -= learning_rate * self.dE_dWfp / (1e-6 + np.sqrt(self.Wfp_hg)) self.Wop_hg += self.dE_dWop**2 self.Wop -= learning_rate * self.dE_dWop / (1e-6 + np.sqrt(self.Wop_hg)) self.W_hg += self.dE_dW**2 self.W -= learning_rate * self.dE_dW / (1e-6 + np.sqrt(self.W_hg)) if self.use_pauses: self.Wp_hg += self.dE_dWp**2 self.Wp -= learning_rate * self.dE_dWp / (1e-6 + np.sqrt(self.Wp_hg)) for i in self.dE_dWe: self.We_hg[i] += self.dE_dWe[i]**2 self.We[i] -= learning_rate * self.dE_dWe[i] / (1e-6 + np.sqrt(self.We_hg[i])) def save(self, file_name, final): assert self.initialized, "initialize or load before using" model = { "type": self.__class__.__name__, "hidden_size": self.hidden_size, "projection_size": self.projection_size, "bptt_steps": self.bptt_steps, "batch_size": self.batch_size, "use_pauses": self.use_pauses, "in_vocabulary": self.in_vocabulary, "out_vocabulary": self.out_vocabulary, "hidden_activation_name": self.hidden_activation_name, } for p in self.params: model[p] = getattr(self, p) if not final: model[p+"_hg"] = getattr(self, p+"_hg") cPickle.dump(model, file(file_name, 'wb')) class TA_LSTM(Model): def __init__(self): super(TA_LSTM, self).__init__() self.params = ["Wp", #pauses "W", "Wr", "Wy", # inputs-to-LSTM, recurrency, outputs "Wip", "Wfp", "Wop"] # peepholes self.initialized = False def initialize(self, hidden_size, t_lstm, out_vocabulary, batch_size, hidden_activation="Tanh", bptt_steps=5, use_pauses=False): assert isinstance(t_lstm, T_LSTM) self.hidden_size = hidden_size self.t_lstm = t_lstm self.bptt_steps = bptt_steps self.batch_size = batch_size self.use_pauses = use_pauses self.in_vocabulary = self.t_lstm.in_vocabulary self.out_vocabulary = out_vocabulary self.hidden_activation_name = hidden_activation self.hidden_activation = getattr(activation_functions, hidden_activation) self.W = self.weights(self.t_lstm.hidden_size, self.hidden_size*4) self.Wp = self.weights(1, self.hidden_size*4) self.Wy = self.weights(self.hidden_size, get_vocabulary_size(self.out_vocabulary)) self.Wip = self.weights(1, self.hidden_size) self.Wfp = self.weights(1, self.hidden_size) self.Wop = self.weights(1, self.hidden_size) self.Wr = self.weights(self.hidden_size, self.hidden_size*4) # AdaGread sum of squares of per feature historical gradients for p in self.params: setattr(self, p+"_hg", np.zeros_like(getattr(self, p))) self.reset_state() self.initialized = True def reset_state(self): self.t_lstm.reset_state() self.m = np.zeros(shape=(self.batch_size, self.hidden_size)) self.h = np.zeros(shape=(self.batch_size, self.hidden_size)) if self.use_pauses: self.pause_history = [] self.t_lstm_h_history = [] self.m_tm1_history = [] self.h_tm1_history = [] self.z_history = [] self.i_history = [] self.ig_history = [] self.fg_history = [] self.og_history = [] self.Wr_history = [] self.Wip_history = [] self.Wfp_history = [] self.Wop_history = [] def _remember_state(self, pause): if self.use_pauses: self.pause_history.append(pause) self.t_lstm_h_history.append(self.t_lstm.h) self.m_tm1_history.append(self.m_tm1) self.h_tm1_history.append(self.h_tm1) self.z_history.append(self.z) self.i_history.append(self.i) self.ig_history.append(self.ig) self.fg_history.append(self.fg) self.og_history.append(self.og) self.Wr_history.append(self.Wr.copy()) self.Wip_history.append(self.Wip.copy()) self.Wfp_history.append(self.Wfp.copy()) self.Wop_history.append(self.Wop.copy()) if len(self.h_tm1_history) > self.bptt_steps: if self.use_pauses: del self.pause_history[0] del self.t_lstm_h_history[0] del self.m_tm1_history[0] del self.h_tm1_history[0] del self.z_history[0] del self.i_history[0] del self.ig_history[0] del self.fg_history[0] del self.og_history[0] del self.Wr_history[0] del self.Wip_history[0] del self.Wfp_history[0] del self.Wop_history[0] def predict(self, input_word_index, pause_duration=None): assert self.initialized, "initialize or load before using" self.t_lstm.predict(input_word_index, pause_duration, compute_only_features=True) self.m_tm1 = self.m self.h_tm1 = self.h r = np.dot(self.h_tm1, self.Wr) z1 = np.dot(self.t_lstm.h, self.W) if self.use_pauses: z1 += np.dot(pause_duration[:,np.newaxis], self.Wp) z = self.slice(r, self.hidden_size, 0) + self.slice(z1, self.hidden_size, 0) self.i = self.hidden_activation.y(z) z = self.slice(r, self.hidden_size, 1) + self.slice(z1, self.hidden_size, 1) + self.m_tm1 * self.Wip self.ig = Sigmoid.y(z) z = self.slice(r, self.hidden_size, 2) + self.slice(z1, self.hidden_size, 2) + self.m_tm1 * self.Wfp self.fg = Sigmoid.y(z) self.m = self.i * self.ig + self.m_tm1 * self.fg z = self.slice(r, self.hidden_size, 3) + self.slice(z1, self.hidden_size, 3) + self.m * self.Wop self.og = Sigmoid.y(z) self.z = self.hidden_activation.y(self.m) self.h = self.z * self.og z_y = np.dot(self.h, self.Wy) self.y = Softmax.y(z=z_y) self._remember_state(pause_duration) def _backpropagate(self, output_word_index): dE_dz_y = self.y.copy() # don't remove the copy() part dE_dz_y[range(len(output_word_index)), output_word_index] -= 1. self.dE_dWy = np.dot(self.h.T, dE_dz_y) dE_dh = np.dot(dE_dz_y, self.Wy.T) * self.hidden_activation.dy_dz(y=self.h) self.dE_dWr = np.zeros_like(self.Wr) self.dE_dW = np.zeros_like(self.W) self.dE_dWip = np.zeros_like(self.Wip) self.dE_dWfp = np.zeros_like(self.Wfp) self.dE_dWop = np.zeros_like(self.Wop) self.dE_dWp = np.zeros_like(self.Wp) dE_dm_tm1 = 0. dE_dh_tm1 = 0. m = self.m pause_history = self.pause_history if self.use_pauses else [None]*len(self.h_tm1_history) for pauses, Wr, Wip, Wfp, Wop, t_lstm_h, m_tm1, h_tm1, z, i, ig, fg, og in reversed(zip( pause_history, self.Wr_history, self.Wip_history, self.Wfp_history, self.Wop_history, self.t_lstm_h_history, self.m_tm1_history, self.h_tm1_history, self.z_history, self.i_history, self.ig_history, self.fg_history, self.og_history)): dE_dh = dE_dh + dE_dh_tm1 dE_dog = dE_dh * z * Sigmoid.dy_dz(y=og) dE_dz = dE_dh * og * self.hidden_activation.dy_dz(y=z) dE_dm = dE_dz + dE_dm_tm1 + dE_dog * Wop dE_dfg = dE_dm * m_tm1 * Sigmoid.dy_dz(y=fg) dE_di = dE_dm * ig * self.hidden_activation.dy_dz(y=i) dE_dig = dE_dm * i * Sigmoid.dy_dz(y=ig) dE_dm_tm1 = dE_dm * fg + dE_dig * Wip + dE_dfg * Wfp self.dE_dWip += (dE_dig * m_tm1).sum(0) self.dE_dWfp += (dE_dfg * m_tm1).sum(0) self.dE_dWop += (dE_dog * m).sum(0) d = np.hstack((dE_di, dE_dig, dE_dfg, dE_dog)) dE_dh_tm1 = np.dot(d, Wr.T) if self.use_pauses: self.dE_dWp += np.dot(pauses.T, d) self.dE_dW += np.dot(t_lstm_h.T, d) self.dE_dWr += np.dot(h_tm1.T, d) dE_dh = 0. m = m_tm1 def update(self, _, output_word_index, learning_rate): """Uses AdaGrad: Duchi, John, Elad Hazan, and Yoram Singer. "Adaptive subgradient methods for online learning and stochastic optimization." The Journal of Machine Learning Research 12 (2011): 2121-2159.""" assert self.initialized, "initialize or load before using" self._backpropagate(output_word_index) self.Wy_hg += self.dE_dWy**2 self.Wy -= learning_rate * self.dE_dWy / (1e-6 + np.sqrt(self.Wy_hg)) self.W_hg += self.dE_dW**2 self.W -= learning_rate * self.dE_dW / (1e-6 + np.sqrt(self.W_hg)) self.Wr_hg += self.dE_dWr**2 self.Wr -= learning_rate * self.dE_dWr / (1e-6 + np.sqrt(self.Wr_hg)) self.Wip_hg += self.dE_dWip**2 self.Wip -= learning_rate * self.dE_dWip / (1e-6 + np.sqrt(self.Wip_hg)) self.Wfp_hg += self.dE_dWfp**2 self.Wfp -= learning_rate * self.dE_dWfp / (1e-6 + np.sqrt(self.Wfp_hg)) self.Wop_hg += self.dE_dWop**2 self.Wop -= learning_rate * self.dE_dWop / (1e-6 + np.sqrt(self.Wop_hg)) if self.use_pauses: self.Wp_hg += self.dE_dWp**2 self.Wp -= learning_rate * self.dE_dWp / (1e-6 + np.sqrt(self.Wp_hg)) def save(self, file_name, final): assert self.initialized, "initialize or load before using" model = { "type": self.__class__.__name__, "hidden_size": self.hidden_size, "bptt_steps": self.bptt_steps, "batch_size": self.batch_size, "use_pauses": self.use_pauses, "out_vocabulary": self.out_vocabulary, "hidden_activation_name": self.hidden_activation_name, } for p in self.params: model[p] = getattr(self, p) if not final: model[p+"_hg"] = getattr(self, p+"_hg") t_lstm_file_name = file_name + "_t_lstm" self.t_lstm.save(t_lstm_file_name, True) model["t_lstm_file_name"] = t_lstm_file_name cPickle.dump(model, file(file_name, 'wb')) def load(self, model): self.t_lstm = load_model(model["t_lstm_file_name"]) self.in_vocabulary = self.t_lstm.in_vocabulary super(TA_LSTM, self).load(model)

39.600739

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3,085

21,424

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0.068395

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0.048632

0.031772

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0.809032

0.790816

0.770652

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21,424

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null

0

1

0

1

0

null

0

7

3bdf6f3e641db6e23d166d7a48c692564554f68c

68

py

Python

nameSurvey/__init__.py

chriswilly/demoCode

654603012157613afa0b4a6b4cc2fa0e50d1b807

[ "MIT" ]

null

nameSurvey/__init__.py

chriswilly/demoCode

654603012157613afa0b4a6b4cc2fa0e50d1b807

[ "MIT" ]

null

nameSurvey/__init__.py

chriswilly/demoCode

654603012157613afa0b4a6b4cc2fa0e50d1b807

[ "MIT" ]

null

from .nameSurvey import nameView # from .nameSurvey import nameFind

68

0.823529

8

68

7

0.625

0.5

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0.132353

68

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0.949153

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null

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0

1

0

1

0

7

cbe9e33acc09c6645384f8d9c7e9463561838769

4,823

py

Python

dispatcher/dispatcher_test.py

Gleamo/gleamo-device

6b7c24ad1683e931cacf2ce9c5aa8d3b16616503

[ "BSD-2-Clause" ]

1

2017-05-02T15:15:03.000Z

dispatcher/dispatcher_test.py

Gleamo/gleamo-python

6b7c24ad1683e931cacf2ce9c5aa8d3b16616503

[ "BSD-2-Clause" ]

4

2017-05-02T13:50:15.000Z

2017-05-02T16:12:38.000Z

dispatcher/dispatcher_test.py

Gleamo/gleamo-python

6b7c24ad1683e931cacf2ce9c5aa8d3b16616503

[ "BSD-2-Clause" ]

null

import unittest from .dispatcher import Dispatcher from hardware.mock_hardware import MockHardware from colors.color import Color from buzzer.buzzer_pattern import BuzzerPattern from commands.command import Command from state.state import State class TestDispatcher(unittest.TestCase): def test_dispatches_to_hardware(self): with MockHardware() as hardware_service: dispatcher = Dispatcher(hardware_service) current_state = State( color=Color(100, 100, 100), buzzer_pattern=BuzzerPattern.NONE ) command = Command( color=Color(110, 110, 110), duration=100, buzzer_pattern=BuzzerPattern.NONE ) now = 0 next_state = dispatcher.dispatch(current_state, command, now) self.assertEqual(next_state.color.r, 100) self.assertEqual(next_state.color.g, 100) self.assertEqual(next_state.color.b, 100) self.assertEqual(hardware_service.color_last_called_with.r, 100) self.assertEqual(hardware_service.color_last_called_with.g, 100) self.assertEqual(hardware_service.color_last_called_with.b, 100) self.assertEqual(hardware_service.color_called_count, 1) now = 10 next_state = dispatcher.dispatch(next_state, command, now) self.assertEqual(next_state.color.r, 101) self.assertEqual(next_state.color.g, 101) self.assertEqual(next_state.color.b, 101) self.assertEqual(hardware_service.color_last_called_with.r, 101) self.assertEqual(hardware_service.color_last_called_with.g, 101) self.assertEqual(hardware_service.color_last_called_with.b, 101) self.assertEqual(hardware_service.color_called_count, 2) now = 90 next_state = dispatcher.dispatch(next_state, command, now) self.assertEqual(next_state.color.r, 109) self.assertEqual(next_state.color.g, 109) self.assertEqual(next_state.color.b, 109) self.assertEqual(hardware_service.color_last_called_with.r, 109) self.assertEqual(hardware_service.color_last_called_with.g, 109) self.assertEqual(hardware_service.color_last_called_with.b, 109) self.assertEqual(hardware_service.color_called_count, 3) now = 100 next_state = dispatcher.dispatch(next_state, command, now) self.assertEqual(next_state.color.r, 110) self.assertEqual(next_state.color.g, 110) self.assertEqual(next_state.color.b, 110) self.assertEqual(hardware_service.color_last_called_with.r, 110) self.assertEqual(hardware_service.color_last_called_with.g, 110) self.assertEqual(hardware_service.color_last_called_with.b, 110) self.assertEqual(hardware_service.color_called_count, 4) def test_dispatches_to_hardware_with_buzzer(self): with MockHardware() as hardware_service: dispatcher = Dispatcher(hardware_service) current_state = State( color=Color(100, 100, 100), buzzer_pattern=BuzzerPattern.NONE ) command = Command( color=Color.no_change(), duration=100, buzzer_pattern=BuzzerPattern(duration=10, strength=1) ) now = 0 next_state = dispatcher.dispatch(current_state, command, now) self.assertEqual(next_state.color.r, 100) self.assertEqual(next_state.color.g, 100) self.assertEqual(next_state.color.b, 100) self.assertEqual(next_state.buzzer_pattern.strength, 1) self.assertEqual(hardware_service.motor_called_count, 1) self.assertEqual(hardware_service.motor_state, 1) now = 10 next_state = dispatcher.dispatch(next_state, command, now) self.assertEqual(next_state.color.r, 100) self.assertEqual(next_state.color.g, 100) self.assertEqual(next_state.color.b, 100) self.assertEqual(next_state.buzzer_pattern.strength, 1) self.assertEqual(hardware_service.motor_called_count, 2) self.assertEqual(hardware_service.motor_state, 1) now = 90 next_state = dispatcher.dispatch(next_state, command, now) self.assertEqual(next_state.color.r, 100) self.assertEqual(next_state.color.g, 100) self.assertEqual(next_state.color.b, 100) self.assertEqual(next_state.buzzer_pattern.strength, 0) self.assertEqual(hardware_service.motor_stop_called_count, 1) self.assertEqual(hardware_service.motor_state, 0)

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76

0.657475

560

4,823

5.416071

0.098214

0.227498

0.150346

0.189911

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0

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4,823

119

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null

1

0

1

0

null

0

1

0

7

cbf7ba7bab387a817f43b4bf627f069c4c8f3dfa

39,307

py

Python

generate-grammars/python-awk/python3_actions.py

mbaak/histogrammar-python

6311f5b0eec9c75f12018f22604535c64675fdf6

[ "Apache-2.0" ]

30

2016-09-25T16:36:06.000Z

2021-07-20T09:09:09.000Z

generate-grammars/python-awk/python3_actions.py

mbaak/histogrammar-python

6311f5b0eec9c75f12018f22604535c64675fdf6

[ "Apache-2.0" ]

15

2016-07-26T19:41:31.000Z

2021-02-07T16:30:11.000Z

generate-grammars/python-awk/python3_actions.py

mbaak/histogrammar-python

6311f5b0eec9c75f12018f22604535c64675fdf6

[ "Apache-2.0" ]

8

2016-09-19T20:48:37.000Z

2021-02-07T15:00:24.000Z

#!/usr/bin/env python actions = {} actions['''file_input : ENDMARKER'''] = ''' p[0] = ast.Module([], rule=inspect.currentframe().f_code.co_name, lineno=0, col_offset=0)''' actions['''file_input : file_input_star ENDMARKER'''] = ''' p[0] = ast.Module(p[1], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1][0])''' actions['''file_input_star : NEWLINE'''] = ''' p[0] = ast.Module([], rule=inspect.currentframe().f_code.co_name, lineno=0, col_offset=0)''' actions['''file_input_star : stmt'''] = ''' p[0] = p[1]''' actions['''file_input_star : file_input_star NEWLINE'''] = ''' p[0] = ast.Module(p[1], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1][0])''' actions['''file_input_star : file_input_star stmt'''] = ''' p[0] = p[1] + p[2]''' actions['''decorator : AT dotted_name NEWLINE'''] = ''' p[0] = p[2] p[0].alt = p[1][1]''' actions['''decorator : AT dotted_name LPAR RPAR NEWLINE'''] = ''' p[0] = ast.Call(p[2], [], [], None, None, rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1][1])''' actions['''decorator : AT dotted_name LPAR arglist RPAR NEWLINE'''] = ''' p[4].func = p[2] p[0] = p[4] inherit_lineno(p[0], p[2]) p[0].alt = p[1][1]''' actions['''decorators : decorators_plus'''] = ''' p[0] = p[1]''' actions['''decorators_plus : decorator'''] = ''' p[0] = [p[1]]''' actions['''decorators_plus : decorators_plus decorator'''] = ''' p[0] = p[1] + [p[2]]''' actions['''decorated : decorators classdef'''] = ''' p[2].decorator_list = p[1] p[0] = p[2] inherit_lineno(p[0], p[1][0])''' actions['''decorated : decorators funcdef'''] = ''' p[2].decorator_list = p[1] p[0] = p[2] inherit_lineno(p[0], p[1][0])''' actions['''funcdef : DEF NAME parameters COLON suite'''] = ''' p[0] = ast.FunctionDef(p[2][0], p[3], p[5], [], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''parameters : LPAR RPAR'''] = ''' p[0] = ast.arguments([], None, None, [], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''stmt : simple_stmt'''] = ''' p[0] = p[1]''' actions['''stmt : compound_stmt'''] = ''' p[0] = p[1]''' actions['''simple_stmt : small_stmt NEWLINE'''] = ''' p[0] = [p[1]]''' actions['''simple_stmt : small_stmt SEMI NEWLINE'''] = ''' p[0] = [p[1]]''' actions['''simple_stmt : small_stmt simple_stmt_star NEWLINE'''] = ''' p[0] = [p[1]] + p[2]''' actions['''simple_stmt : small_stmt simple_stmt_star SEMI NEWLINE'''] = ''' p[0] = [p[1]] + p[2]''' actions['''simple_stmt_star : SEMI small_stmt'''] = ''' p[0] = [p[2]]''' actions['''simple_stmt_star : simple_stmt_star SEMI small_stmt'''] = ''' p[0] = p[1] + [p[3]]''' actions['''small_stmt : expr_stmt'''] = ''' p[0] = p[1]''' actions['''small_stmt : del_stmt'''] = ''' p[0] = p[1]''' actions['''small_stmt : pass_stmt'''] = ''' p[0] = p[1]''' actions['''small_stmt : flow_stmt'''] = ''' p[0] = p[1]''' actions['''small_stmt : import_stmt'''] = ''' p[0] = p[1]''' actions['''small_stmt : global_stmt'''] = ''' p[0] = p[1]''' actions['''small_stmt : assert_stmt'''] = ''' p[0] = p[1]''' actions['''expr_stmt : testlist_star_expr'''] = ''' p[0] = ast.Expr(p[1], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''expr_stmt_star : EQUAL yield_expr'''] = ''' p[0] = [p[2]]''' actions['''expr_stmt_star : expr_stmt_star EQUAL yield_expr'''] = ''' p[0] = p[1] + [p[3]]''' actions['''testlist_star_expr : test'''] = ''' p[0] = p[1]''' actions['''augassign : PLUSEQUAL'''] = ''' p[0] = ast.Add(rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''augassign : MINEQUAL'''] = ''' p[0] = ast.Sub(rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''augassign : STAREQUAL'''] = ''' p[0] = ast.Mult(rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''augassign : SLASHEQUAL'''] = ''' p[0] = ast.Div(rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''augassign : PERCENTEQUAL'''] = ''' p[0] = ast.Mod(rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''augassign : AMPEREQUAL'''] = ''' p[0] = ast.BitAnd(rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''augassign : VBAREQUAL'''] = ''' p[0] = ast.BitOr(rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''augassign : CIRCUMFLEXEQUAL'''] = ''' p[0] = ast.BitXor(rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''augassign : LEFTSHIFTEQUAL'''] = ''' p[0] = ast.LShift(rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''augassign : RIGHTSHIFTEQUAL'''] = ''' p[0] = ast.RShift(rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''augassign : DOUBLESTAREQUAL'''] = ''' p[0] = ast.Pow(rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''augassign : DOUBLESLASHEQUAL'''] = ''' p[0] = ast.FloorDiv(rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''del_stmt : DEL exprlist'''] = ''' ctx_to_store(p[2], ast.Del) if isinstance(p[2], ast.Tuple) and not p[2].paren: p[0] = ast.Delete(p[2].elts, rule=inspect.currentframe().f_code.co_name, **p[1][1]) else: p[0] = ast.Delete([p[2]], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''pass_stmt : PASS'''] = ''' p[0] = ast.Pass(rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''flow_stmt : break_stmt'''] = ''' p[0] = p[1]''' actions['''flow_stmt : continue_stmt'''] = ''' p[0] = p[1]''' actions['''flow_stmt : return_stmt'''] = ''' p[0] = p[1]''' actions['''flow_stmt : raise_stmt'''] = ''' p[0] = p[1]''' actions['''flow_stmt : yield_stmt'''] = ''' p[0] = ast.Expr(p[1], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''break_stmt : BREAK'''] = ''' p[0] = ast.Break(rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''continue_stmt : CONTINUE'''] = ''' p[0] = ast.Continue(rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''return_stmt : RETURN'''] = ''' p[0] = ast.Return(None, rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''return_stmt : RETURN testlist'''] = ''' p[0] = ast.Return(p[2], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''yield_stmt : yield_expr'''] = ''' p[0] = p[1]''' actions['''raise_stmt : RAISE'''] = ''' p[0] = ast.Raise(None, None, None, rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''raise_stmt : RAISE test'''] = ''' p[0] = ast.Raise(p[2], None, None, rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''import_stmt : import_name'''] = ''' p[0] = p[1]''' actions['''import_stmt : import_from'''] = ''' p[0] = p[1]''' actions['''import_name : IMPORT dotted_as_names'''] = ''' p[0] = ast.Import(p[2], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''import_from : FROM dotted_name IMPORT STAR'''] = ''' dotted = [] last = p[2] while isinstance(last, ast.Attribute): dotted.insert(0, last.attr) last = last.value dotted.insert(0, last.id) p[0] = ast.ImportFrom(".".join(dotted), [ast.alias("*", None, rule=inspect.currentframe().f_code.co_name, **p[3][1])], 0, rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''import_from : FROM dotted_name IMPORT LPAR import_as_names RPAR'''] = ''' dotted = [] last = p[2] while isinstance(last, ast.Attribute): dotted.insert(0, last.attr) last = last.value dotted.insert(0, last.id) p[0] = ast.ImportFrom(".".join(dotted), p[5], 0, rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''import_from : FROM dotted_name IMPORT import_as_names'''] = ''' dotted = [] last = p[2] while isinstance(last, ast.Attribute): dotted.insert(0, last.attr) last = last.value dotted.insert(0, last.id) p[0] = ast.ImportFrom(".".join(dotted), p[4], 0, rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''import_from : FROM import_from_plus dotted_name IMPORT STAR'''] = ''' dotted = [] last = p[3] while isinstance(last, ast.Attribute): dotted.insert(0, last.attr) last = last.value dotted.insert(0, last.id) p[0] = ast.ImportFrom(".".join(dotted), [ast.alias("*", None, rule=inspect.currentframe().f_code.co_name, **p[4][1])], p[2], **p[1][1])''' actions['''import_from : FROM import_from_plus dotted_name IMPORT LPAR import_as_names RPAR'''] = ''' dotted = [] last = p[3] while isinstance(last, ast.Attribute): dotted.insert(0, last.attr) last = last.value dotted.insert(0, last.id) p[0] = ast.ImportFrom(".".join(dotted), p[6], p[2], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''import_from : FROM import_from_plus dotted_name IMPORT import_as_names'''] = ''' dotted = [] last = p[3] while isinstance(last, ast.Attribute): dotted.insert(0, last.attr) last = last.value dotted.insert(0, last.id) p[0] = ast.ImportFrom(".".join(dotted), p[5], p[2], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''import_from : FROM import_from_plus IMPORT STAR'''] = ''' p[0] = ast.ImportFrom(None, [ast.alias("*", None, rule=inspect.currentframe().f_code.co_name, **p[3][1])], p[2], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''import_from : FROM import_from_plus IMPORT LPAR import_as_names RPAR'''] = ''' p[0] = ast.ImportFrom(None, p[5], p[2], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''import_from : FROM import_from_plus IMPORT import_as_names'''] = ''' p[0] = ast.ImportFrom(None, p[4], p[2], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''import_from_plus : DOT'''] = ''' p[0] = 1''' actions['''import_from_plus : import_from_plus DOT'''] = ''' p[0] = p[1] + 1''' actions['''import_as_name : NAME'''] = ''' p[0] = ast.alias(p[1][0], None, rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''import_as_name : NAME AS NAME'''] = ''' p[0] = ast.alias(p[1][0], p[3][0], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''dotted_as_name : dotted_name'''] = ''' dotted = [] last = p[1] while isinstance(last, ast.Attribute): dotted.insert(0, last.attr) last = last.value dotted.insert(0, last.id) p[0] = ast.alias(".".join(dotted), None, rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''dotted_as_name : dotted_name AS NAME'''] = ''' dotted = [] last = p[1] while isinstance(last, ast.Attribute): dotted.insert(0, last.attr) last = last.value dotted.insert(0, last.id) p[0] = ast.alias(".".join(dotted), p[3][0], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''import_as_names : import_as_name'''] = ''' p[0] = [p[1]]''' actions['''import_as_names : import_as_name COMMA'''] = ''' p[0] = [p[1]]''' actions['''import_as_names : import_as_name import_as_names_star'''] = ''' p[0] = [p[1]] + p[2]''' actions['''import_as_names : import_as_name import_as_names_star COMMA'''] = ''' p[0] = [p[1]] + p[2]''' actions['''import_as_names_star : COMMA import_as_name'''] = ''' p[0] = [p[2]]''' actions['''import_as_names_star : import_as_names_star COMMA import_as_name'''] = ''' p[0] = p[1] + [p[3]]''' actions['''dotted_as_names : dotted_as_name'''] = ''' p[0] = [p[1]]''' actions['''dotted_as_names : dotted_as_name dotted_as_names_star'''] = ''' p[0] = [p[1]] + p[2]''' actions['''dotted_as_names_star : COMMA dotted_as_name'''] = ''' p[0] = [p[2]]''' actions['''dotted_as_names_star : dotted_as_names_star COMMA dotted_as_name'''] = ''' p[0] = p[1] + [p[3]]''' actions['''dotted_name : NAME'''] = ''' p[0] = ast.Name(p[1][0], ast.Load(), rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''dotted_name : NAME dotted_name_star'''] = ''' last = p[2] if isinstance(last, ast.Attribute): inherit_lineno(last, p[1][1]) while isinstance(last.value, ast.Attribute): last = last.value inherit_lineno(last, p[1][1]) last.value = ast.Attribute(ast.Name(p[1][0], ast.Load(), rule=inspect.currentframe().f_code.co_name, **p[1][1]), last.value, ast.Load(), rule=inspect.currentframe().f_code.co_name, **p[1][1]) p[0] = p[2] else: p[0] = ast.Attribute(ast.Name(p[1][0], ast.Load(), rule=inspect.currentframe().f_code.co_name, **p[1][1]), p[2], ast.Load(), rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''dotted_name_star : DOT NAME'''] = ''' p[0] = p[2][0]''' actions['''dotted_name_star : dotted_name_star DOT NAME'''] = ''' p[0] = ast.Attribute(p[1], p[3][0], ast.Load(), rule=inspect.currentframe().f_code.co_name)''' actions['''global_stmt : GLOBAL NAME'''] = ''' p[0] = ast.Global([p[2][0]], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''global_stmt : GLOBAL NAME global_stmt_star'''] = ''' p[0] = ast.Global([p[2][0]] + p[3], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''global_stmt_star : COMMA NAME'''] = ''' p[0] = [p[2][0]]''' actions['''global_stmt_star : global_stmt_star COMMA NAME'''] = ''' p[0] = p[1] + [p[3][0]]''' actions['''assert_stmt : ASSERT test'''] = ''' p[0] = ast.Assert(p[2], None, rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''assert_stmt : ASSERT test COMMA test'''] = ''' p[0] = ast.Assert(p[2], p[4], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''compound_stmt : if_stmt'''] = ''' p[0] = [p[1]]''' actions['''compound_stmt : while_stmt'''] = ''' p[0] = [p[1]]''' actions['''compound_stmt : for_stmt'''] = ''' p[0] = [p[1]]''' actions['''compound_stmt : try_stmt'''] = ''' p[0] = [p[1]]''' actions['''compound_stmt : with_stmt'''] = ''' p[0] = [p[1]]''' actions['''compound_stmt : funcdef'''] = ''' p[0] = [p[1]]''' actions['''compound_stmt : classdef'''] = ''' p[0] = [p[1]]''' actions['''compound_stmt : decorated'''] = ''' p[0] = [p[1]]''' actions['''if_stmt : IF test COLON suite'''] = ''' p[0] = ast.If(p[2], p[4], [], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''if_stmt : IF test COLON suite ELSE COLON suite'''] = ''' p[0] = ast.If(p[2], p[4], p[7], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''if_stmt : IF test COLON suite if_stmt_star'''] = ''' p[0] = ast.If(p[2], p[4], [p[5]], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''if_stmt : IF test COLON suite if_stmt_star ELSE COLON suite'''] = ''' last = p[5] while len(last.orelse) > 0: last = last.orelse[0] last.orelse.extend(p[8]) p[0] = ast.If(p[2], p[4], [p[5]], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''if_stmt_star : ELIF test COLON suite'''] = ''' p[0] = ast.If(p[2], p[4], [], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[2])''' actions['''if_stmt_star : if_stmt_star ELIF test COLON suite'''] = ''' last = p[1] while len(last.orelse) > 0: last = last.orelse[0] last.orelse.append(ast.If(p[3], p[5], [], rule=inspect.currentframe().f_code.co_name)) inherit_lineno(last.orelse[-1], p[3]) p[0] = p[1]''' actions['''while_stmt : WHILE test COLON suite'''] = ''' p[0] = ast.While(p[2], p[4], [], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''while_stmt : WHILE test COLON suite ELSE COLON suite'''] = ''' p[0] = ast.While(p[2], p[4], p[7], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''for_stmt : FOR exprlist IN testlist COLON suite'''] = ''' ctx_to_store(p[2]) p[0] = ast.For(p[2], p[4], p[6], [], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''for_stmt : FOR exprlist IN testlist COLON suite ELSE COLON suite'''] = ''' ctx_to_store(p[2]) p[0] = ast.For(p[2], p[4], p[6], p[9], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''try_stmt : TRY COLON suite try_stmt_plus'''] = ''' p[0] = ast.TryExcept(p[3], p[4], [], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''try_stmt : TRY COLON suite try_stmt_plus FINALLY COLON suite'''] = ''' p[0] = ast.TryFinally([ast.TryExcept(p[3], p[4], [], rule=inspect.currentframe().f_code.co_name, **p[1][1])], p[7], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''try_stmt : TRY COLON suite try_stmt_plus ELSE COLON suite'''] = ''' p[0] = ast.TryExcept(p[3], p[4], p[7], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''try_stmt : TRY COLON suite try_stmt_plus ELSE COLON suite FINALLY COLON suite'''] = ''' p[0] = ast.TryFinally([ast.TryExcept(p[3], p[4], p[7], rule=inspect.currentframe().f_code.co_name, **p[1][1])], p[10], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''try_stmt : TRY COLON suite FINALLY COLON suite'''] = ''' p[0] = ast.TryFinally(p[3], p[6], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''try_stmt_plus : except_clause COLON suite'''] = ''' p[1].body = p[3] p[0] = [p[1]]''' actions['''try_stmt_plus : try_stmt_plus except_clause COLON suite'''] = ''' p[2].body = p[4] p[0] = p[1] + [p[2]]''' actions['''with_stmt : WITH with_item COLON suite'''] = ''' p[2].body = p[4] p[0] = p[2]''' actions['''with_stmt : WITH with_item with_stmt_star COLON suite'''] = ''' p[2].body.append(p[3]) last = p[2] while len(last.body) > 0: last = last.body[0] last.body = p[5] p[0] = p[2]''' actions['''with_stmt_star : COMMA with_item'''] = ''' p[0] = p[2]''' actions['''with_stmt_star : with_stmt_star COMMA with_item'''] = ''' last = p[1] while len(last.body) > 0: last = last.body[0] last.body.append(p[3]) p[0] = p[1]''' actions['''with_item : test'''] = ''' p[0] = ast.With(p[1], None, [], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''with_item : test AS expr'''] = ''' ctx_to_store(p[3]) p[0] = ast.With(p[1], p[3], [], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''except_clause : EXCEPT'''] = ''' p[0] = ast.ExceptHandler(None, None, [], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''except_clause : EXCEPT test'''] = ''' p[0] = ast.ExceptHandler(p[2], None, [], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''suite : simple_stmt'''] = ''' p[0] = p[1]''' actions['''suite : NEWLINE INDENT suite_plus DEDENT'''] = ''' p[0] = p[3]''' actions['''suite_plus : stmt'''] = ''' p[0] = p[1]''' actions['''suite_plus : suite_plus stmt'''] = ''' p[0] = p[1] + p[2]''' actions['''test : or_test'''] = ''' p[0] = p[1]''' actions['''test : or_test IF or_test ELSE test'''] = ''' p[0] = ast.IfExp(p[3], p[1], p[5], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''test : lambdef'''] = ''' p[0] = p[1]''' actions['''lambdef : LAMBDA COLON test'''] = ''' p[0] = ast.Lambda(ast.arguments([], None, None, [], rule=inspect.currentframe().f_code.co_name, **p[2][1]), p[3], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''lambdef : LAMBDA varargslist COLON test'''] = ''' p[0] = ast.Lambda(p[2], p[4], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''or_test : and_test'''] = ''' p[0] = p[1]''' actions['''or_test : and_test or_test_star'''] = ''' theor = ast.Or(rule=inspect.currentframe().f_code.co_name) inherit_lineno(theor, p[2][0]) p[0] = ast.BoolOp(theor, [p[1]] + p[2], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''or_test_star : OR and_test'''] = ''' p[0] = [p[2]]''' actions['''or_test_star : or_test_star OR and_test'''] = ''' p[0] = p[1] + [p[3]]''' actions['''and_test : not_test'''] = ''' p[0] = p[1]''' actions['''and_test : not_test and_test_star'''] = ''' theand = ast.And(rule=inspect.currentframe().f_code.co_name) inherit_lineno(theand, p[2][0]) p[0] = ast.BoolOp(theand, [p[1]] + p[2], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''and_test_star : AND not_test'''] = ''' p[0] = [p[2]]''' actions['''and_test_star : and_test_star AND not_test'''] = ''' p[0] = p[1] + [p[3]]''' actions['''not_test : NOT not_test'''] = ''' thenot = ast.Not(rule=inspect.currentframe().f_code.co_name) inherit_lineno(thenot, p[2]) p[0] = ast.UnaryOp(thenot, p[2], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''not_test : comparison'''] = ''' p[0] = p[1]''' actions['''comparison : expr'''] = ''' p[0] = p[1]''' actions['''comparison : expr comparison_star'''] = ''' ops, exprs = p[2] p[0] = ast.Compare(p[1], ops, exprs, rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''comparison_star : comp_op expr'''] = ''' inherit_lineno(p[1], p[2]) p[0] = ([p[1]], [p[2]])''' actions['''comparison_star : comparison_star comp_op expr'''] = ''' ops, exprs = p[1] inherit_lineno(p[2], p[3]) p[0] = (ops + [p[2]], exprs + [p[3]])''' actions['''comp_op : LESS'''] = ''' p[0] = ast.Lt(rule=inspect.currentframe().f_code.co_name)''' actions['''comp_op : GREATER'''] = ''' p[0] = ast.Gt(rule=inspect.currentframe().f_code.co_name)''' actions['''comp_op : EQEQUAL'''] = ''' p[0] = ast.Eq(rule=inspect.currentframe().f_code.co_name)''' actions['''comp_op : GREATEREQUAL'''] = ''' p[0] = ast.GtE(rule=inspect.currentframe().f_code.co_name)''' actions['''comp_op : LESSEQUAL'''] = ''' p[0] = ast.LtE(rule=inspect.currentframe().f_code.co_name)''' actions['''comp_op : NOTEQUAL'''] = ''' p[0] = ast.NotEq(rule=inspect.currentframe().f_code.co_name)''' actions['''comp_op : IN'''] = ''' p[0] = ast.In(rule=inspect.currentframe().f_code.co_name)''' actions['''comp_op : NOT IN'''] = ''' p[0] = ast.NotIn(rule=inspect.currentframe().f_code.co_name)''' actions['''comp_op : IS'''] = ''' p[0] = ast.Is(rule=inspect.currentframe().f_code.co_name)''' actions['''comp_op : IS NOT'''] = ''' p[0] = ast.IsNot(rule=inspect.currentframe().f_code.co_name)''' actions['''expr : xor_expr'''] = ''' p[0] = p[1]''' actions['''expr : xor_expr expr_star'''] = ''' p[0] = unwrap_left_associative([p[1]] + p[2], rule=inspect.currentframe().f_code.co_name, alt=len(p[2]) > 2)''' actions['''expr_star : VBAR xor_expr'''] = ''' p[0] = [ast.BitOr(rule=inspect.currentframe().f_code.co_name, **p[1][1]), p[2]]''' actions['''expr_star : expr_star VBAR xor_expr'''] = ''' p[0] = p[1] + [ast.BitOr(rule=inspect.currentframe().f_code.co_name, **p[2][1]), p[3]]''' actions['''xor_expr : and_expr'''] = ''' p[0] = p[1]''' actions['''xor_expr : and_expr xor_expr_star'''] = ''' p[0] = unwrap_left_associative([p[1]] + p[2], rule=inspect.currentframe().f_code.co_name, alt=len(p[2]) > 2)''' actions['''xor_expr_star : CIRCUMFLEX and_expr'''] = ''' p[0] = [ast.BitXor(rule=inspect.currentframe().f_code.co_name, **p[1][1]), p[2]]''' actions['''xor_expr_star : xor_expr_star CIRCUMFLEX and_expr'''] = ''' p[0] = p[1] + [ast.BitXor(rule=inspect.currentframe().f_code.co_name, **p[2][1]), p[3]]''' actions['''and_expr : shift_expr'''] = ''' p[0] = p[1]''' actions['''and_expr : shift_expr and_expr_star'''] = ''' p[0] = unwrap_left_associative([p[1]] + p[2], rule=inspect.currentframe().f_code.co_name, alt=len(p[2]) > 0)''' actions['''and_expr_star : AMPER shift_expr'''] = ''' p[0] = [ast.BitAnd(rule=inspect.currentframe().f_code.co_name, **p[1][1]), p[2]]''' actions['''and_expr_star : and_expr_star AMPER shift_expr'''] = ''' p[0] = p[1] + [ast.BitAnd(rule=inspect.currentframe().f_code.co_name, **p[2][1]), p[3]]''' actions['''shift_expr : arith_expr'''] = ''' p[0] = p[1]''' actions['''shift_expr : arith_expr shift_expr_star'''] = ''' p[0] = unwrap_left_associative([p[1]] + p[2], rule=inspect.currentframe().f_code.co_name, alt=len(p[2]) > 2)''' actions['''shift_expr_star : LEFTSHIFT arith_expr'''] = ''' p[0] = [ast.LShift(rule=inspect.currentframe().f_code.co_name, **p[1][1]), p[2]]''' actions['''shift_expr_star : RIGHTSHIFT arith_expr'''] = ''' p[0] = [ast.RShift(rule=inspect.currentframe().f_code.co_name, **p[1][1]), p[2]]''' actions['''shift_expr_star : shift_expr_star LEFTSHIFT arith_expr'''] = ''' p[0] = p[1] + [ast.LShift(rule=inspect.currentframe().f_code.co_name, **p[2][1]), p[3]]''' actions['''shift_expr_star : shift_expr_star RIGHTSHIFT arith_expr'''] = ''' p[0] = p[1] + [ast.RShift(rule=inspect.currentframe().f_code.co_name, **p[2][1]), p[3]]''' actions['''arith_expr : term'''] = ''' p[0] = p[1]''' actions['''arith_expr : term arith_expr_star'''] = ''' p[0] = unwrap_left_associative([p[1]] + p[2], rule=inspect.currentframe().f_code.co_name, alt=len(p[2]) > 2)''' actions['''arith_expr_star : PLUS term'''] = ''' p[0] = [ast.Add(rule=inspect.currentframe().f_code.co_name, **p[1][1]), p[2]]''' actions['''arith_expr_star : MINUS term'''] = ''' p[0] = [ast.Sub(rule=inspect.currentframe().f_code.co_name, **p[1][1]), p[2]]''' actions['''arith_expr_star : arith_expr_star PLUS term'''] = ''' p[0] = p[1] + [ast.Add(rule=inspect.currentframe().f_code.co_name, **p[2][1]), p[3]]''' actions['''arith_expr_star : arith_expr_star MINUS term'''] = ''' p[0] = p[1] + [ast.Sub(rule=inspect.currentframe().f_code.co_name, **p[2][1]), p[3]]''' actions['''term : factor'''] = ''' p[0] = p[1]''' actions['''term : factor term_star'''] = ''' p[0] = unwrap_left_associative([p[1]] + p[2], rule=inspect.currentframe().f_code.co_name, alt=len(p[2]) > 2)''' actions['''term_star : STAR factor'''] = ''' p[0] = [ast.Mult(rule=inspect.currentframe().f_code.co_name, **p[1][1]), p[2]]''' actions['''term_star : SLASH factor'''] = ''' p[0] = [ast.Div(rule=inspect.currentframe().f_code.co_name, **p[1][1]), p[2]]''' actions['''term_star : PERCENT factor'''] = ''' p[0] = [ast.Mod(rule=inspect.currentframe().f_code.co_name, **p[1][1]), p[2]]''' actions['''term_star : DOUBLESLASH factor'''] = ''' p[0] = [ast.FloorDiv(rule=inspect.currentframe().f_code.co_name, **p[1][1]), p[2]]''' actions['''term_star : term_star STAR factor'''] = ''' p[0] = p[1] + [ast.Mult(rule=inspect.currentframe().f_code.co_name, **p[2][1]), p[3]]''' actions['''term_star : term_star SLASH factor'''] = ''' p[0] = p[1] + [ast.Div(rule=inspect.currentframe().f_code.co_name, **p[2][1]), p[3]]''' actions['''term_star : term_star PERCENT factor'''] = ''' p[0] = p[1] + [ast.Mod(rule=inspect.currentframe().f_code.co_name, **p[2][1]), p[3]]''' actions['''term_star : term_star DOUBLESLASH factor'''] = ''' p[0] = p[1] + [ast.FloorDiv(rule=inspect.currentframe().f_code.co_name, **p[2][1]), p[3]]''' actions['''factor : PLUS factor'''] = ''' op = ast.UAdd(rule=inspect.currentframe().f_code.co_name, **p[1][1]) p[0] = ast.UnaryOp(op, p[2], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], op)''' actions['''factor : MINUS factor'''] = ''' op = ast.USub(rule=inspect.currentframe().f_code.co_name, **p[1][1]) p[0] = ast.UnaryOp(op, p[2], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], op)''' actions['''factor : TILDE factor'''] = ''' op = ast.Invert(rule=inspect.currentframe().f_code.co_name, **p[1][1]) p[0] = ast.UnaryOp(op, p[2], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], op)''' actions['''factor : power'''] = ''' p[0] = p[1]''' actions['''power : atom_expr'''] = ''' p[0] = p[1]''' actions['''atom_expr : atom'''] = ''' p[0] = p[1]''' actions['''atom : LPAR RPAR'''] = ''' p[0] = ast.Tuple([], ast.Load(), rule=inspect.currentframe().f_code.co_name, paren=True, **p[1][1])''' actions['''atom : LPAR yield_expr RPAR'''] = ''' p[0] = p[2] if isinstance(p[0], ast.Tuple): p[0].paren = True p[0].alt = p[1][1]''' actions['''atom : LPAR testlist_comp RPAR'''] = ''' p[0] = p[2] if isinstance(p[0], ast.Tuple): p[0].paren = True p[0].alt = p[1][1]''' actions['''atom : LSQB RSQB'''] = ''' p[0] = ast.List([], ast.Load(), rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''atom : LBRACE RBRACE'''] = ''' p[0] = ast.Dict([], [], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''atom : LBRACE dictorsetmaker RBRACE'''] = ''' if isinstance(p[2], (ast.SetComp, ast.DictComp)): p[0] = p[2] p[0].alt = p[1][1] else: keys, values = p[2] if keys is None: p[0] = ast.Set(values, rule=inspect.currentframe().f_code.co_name, **p[1][1]) else: p[0] = ast.Dict(keys, values, rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''atom : NAME'''] = ''' p[0] = ast.Name(p[1][0], ast.Load(), rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''atom : NUMBER'''] = ''' p[0] = ast.Num(p[1][0], rule=inspect.currentframe().f_code.co_name, **p[1][2])''' actions['''atom : atom_plus'''] = ''' p[0] = p[1]''' actions['''atom_plus : STRING'''] = ''' p[0] = ast.Str(p[1][0], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''atom_plus : atom_plus STRING'''] = ''' p[1].s = p[1].s + p[2][0] p[0] = p[1]''' actions['''testlist_comp : test comp_for'''] = ''' p[0] = ast.GeneratorExp(p[1], p[2], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''testlist_comp : test'''] = ''' p[0] = p[1]''' actions['''testlist_comp : test COMMA'''] = ''' p[0] = ast.Tuple([p[1]], ast.Load(), rule=inspect.currentframe().f_code.co_name, paren=False) inherit_lineno(p[0], p[1])''' actions['''testlist_comp : test testlist_comp_star'''] = ''' p[0] = ast.Tuple([p[1]] + p[2], ast.Load(), rule=inspect.currentframe().f_code.co_name, paren=False) inherit_lineno(p[0], p[1])''' actions['''testlist_comp : test testlist_comp_star COMMA'''] = ''' p[0] = ast.Tuple([p[1]] + p[2], ast.Load(), rule=inspect.currentframe().f_code.co_name, paren=False) inherit_lineno(p[0], p[1])''' actions['''testlist_comp_star : COMMA test'''] = ''' p[0] = [p[2]]''' actions['''testlist_comp_star : testlist_comp_star COMMA test'''] = ''' p[0] = p[1] + [p[3]]''' actions['''trailer : LPAR RPAR'''] = ''' p[0] = ast.Call(None, [], [], None, None, rule=inspect.currentframe().f_code.co_name)''' actions['''trailer : LPAR arglist RPAR'''] = ''' p[0] = p[2]''' actions['''trailer : LSQB subscriptlist RSQB'''] = ''' p[0] = ast.Subscript(None, p[2], ast.Load(), rule=inspect.currentframe().f_code.co_name)''' actions['''trailer : DOT NAME'''] = ''' p[0] = ast.Attribute(None, p[2][0], ast.Load(), rule=inspect.currentframe().f_code.co_name)''' actions['''subscriptlist : subscript'''] = ''' p[0] = p[1]''' actions['''subscriptlist : subscript COMMA'''] = ''' if isinstance(p[1], ast.Index): tup = ast.Tuple([p[1].value], ast.Load(), rule=inspect.currentframe().f_code.co_name, paren=False) inherit_lineno(tup, p[1].value) p[0] = ast.Index(tup, rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], tup) else: p[0] = ast.ExtSlice([p[1]], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''subscriptlist : subscript subscriptlist_star'''] = ''' args = [p[1]] + p[2] if all(isinstance(x, ast.Index) for x in args): tup = ast.Tuple([x.value for x in args], ast.Load(), rule=inspect.currentframe().f_code.co_name, paren=False) inherit_lineno(tup, args[0].value) p[0] = ast.Index(tup, rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], tup) else: p[0] = ast.ExtSlice(args, rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''subscriptlist : subscript subscriptlist_star COMMA'''] = ''' args = [p[1]] + p[2] if all(isinstance(x, ast.Index) for x in args): tup = ast.Tuple([x.value for x in args], ast.Load(), rule=inspect.currentframe().f_code.co_name, paren=False) inherit_lineno(tup, args[0].value) p[0] = ast.Index(tup, rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], tup) else: p[0] = ast.ExtSlice(args, rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''subscriptlist_star : COMMA subscript'''] = ''' p[0] = [p[2]]''' actions['''subscriptlist_star : subscriptlist_star COMMA subscript'''] = ''' p[0] = p[1] + [p[3]]''' actions['''subscript : test'''] = ''' p[0] = ast.Index(p[1], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''subscript : COLON'''] = ''' p[0] = ast.Slice(None, None, None, rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''subscript : COLON sliceop'''] = ''' p[0] = ast.Slice(None, None, p[2], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''subscript : COLON test'''] = ''' p[0] = ast.Slice(None, p[2], None, rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''subscript : COLON test sliceop'''] = ''' p[0] = ast.Slice(None, p[2], p[3], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''subscript : test COLON'''] = ''' p[0] = ast.Slice(p[1], None, None, rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''subscript : test COLON sliceop'''] = ''' p[0] = ast.Slice(p[1], None, p[3], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''subscript : test COLON test'''] = ''' p[0] = ast.Slice(p[1], p[3], None, rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''subscript : test COLON test sliceop'''] = ''' p[0] = ast.Slice(p[1], p[3], p[4], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''sliceop : COLON'''] = ''' p[0] = ast.Name("None", ast.Load(), rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''sliceop : COLON test'''] = ''' p[0] = p[2]''' actions['''exprlist : expr'''] = ''' p[0] = p[1]''' actions['''exprlist : expr COMMA'''] = ''' p[0] = ast.Tuple([p[1]], ast.Load(), rule=inspect.currentframe().f_code.co_name, paren=False) inherit_lineno(p[0], p[1])''' actions['''exprlist : expr exprlist_star'''] = ''' p[0] = ast.Tuple([p[1]] + p[2], ast.Load(), rule=inspect.currentframe().f_code.co_name, paren=False) inherit_lineno(p[0], p[1])''' actions['''exprlist : expr exprlist_star COMMA'''] = ''' p[0] = ast.Tuple([p[1]] + p[2], ast.Load(), rule=inspect.currentframe().f_code.co_name, paren=False) inherit_lineno(p[0], p[1])''' actions['''exprlist_star : COMMA expr'''] = ''' p[0] = [p[2]]''' actions['''exprlist_star : exprlist_star COMMA expr'''] = ''' p[0] = p[1] + [p[3]]''' actions['''testlist : test'''] = ''' p[0] = p[1]''' actions['''testlist : test COMMA'''] = ''' p[0] = ast.Tuple([p[1]], ast.Load(), rule=inspect.currentframe().f_code.co_name, paren=False) inherit_lineno(p[0], p[1])''' actions['''testlist : test testlist_star'''] = ''' p[0] = ast.Tuple([p[1]] + p[2], ast.Load(), rule=inspect.currentframe().f_code.co_name, paren=False) inherit_lineno(p[0], p[1])''' actions['''testlist : test testlist_star COMMA'''] = ''' p[0] = ast.Tuple([p[1]] + p[2], ast.Load(), rule=inspect.currentframe().f_code.co_name, paren=False) inherit_lineno(p[0], p[1])''' actions['''testlist_star : COMMA test'''] = ''' p[0] = [p[2]]''' actions['''testlist_star : testlist_star COMMA test'''] = ''' p[0] = p[1] + [p[3]]''' actions['''dictorsetmaker : test COLON test comp_for'''] = ''' p[0] = ast.DictComp(p[1], p[3], p[4], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''dictorsetmaker : test COLON test'''] = ''' p[0] = ([p[1]], [p[3]])''' actions['''dictorsetmaker : test COLON test COMMA'''] = ''' p[0] = ([p[1]], [p[3]])''' actions['''dictorsetmaker : test COLON test dictorsetmaker_star'''] = ''' keys, values = p[4] p[0] = ([p[1]] + keys, [p[3]] + values)''' actions['''dictorsetmaker : test COLON test dictorsetmaker_star COMMA'''] = ''' keys, values = p[4] p[0] = ([p[1]] + keys, [p[3]] + values)''' actions['''dictorsetmaker : test comp_for'''] = ''' p[0] = ast.SetComp(p[1], p[2], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''dictorsetmaker : test'''] = ''' p[0] = (None, [p[1]])''' actions['''dictorsetmaker : test COMMA'''] = ''' p[0] = (None, [p[1]])''' actions['''dictorsetmaker_star : COMMA test COLON test'''] = ''' p[0] = ([p[2]], [p[4]])''' actions['''dictorsetmaker_star : dictorsetmaker_star COMMA test COLON test'''] = ''' keys, values = p[1] p[0] = (keys + [p[3]], values + [p[5]])''' actions['''classdef : CLASS NAME COLON suite'''] = ''' p[0] = ast.ClassDef(p[2][0], [], p[4], [], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''classdef : CLASS NAME LPAR RPAR COLON suite'''] = ''' p[0] = ast.ClassDef(p[2][0], [], p[6], [], rule=inspect.currentframe().f_code.co_name, **p[1][1])''' actions['''arglist : argument'''] = ''' if notkeyword(p[1]): p[0] = ast.Call(None, [p[1]], [], None, None, rule=inspect.currentframe().f_code.co_name) else: p[0] = ast.Call(None, [], [p[1]], None, None, rule=inspect.currentframe().f_code.co_name)''' actions['''arglist : argument COMMA'''] = ''' if notkeyword(p[1]): p[0] = ast.Call(None, [p[1]], [], None, None, rule=inspect.currentframe().f_code.co_name) else: p[0] = ast.Call(None, [], [p[1]], None, None, rule=inspect.currentframe().f_code.co_name)''' actions['''arglist_star : COMMA argument'''] = ''' p[0] = [p[2]]''' actions['''arglist_star : arglist_star COMMA argument'''] = ''' p[0] = p[1] + [p[3]]''' actions['''argument : test'''] = ''' p[0] = p[1]''' actions['''argument : test comp_for'''] = ''' p[0] = ast.GeneratorExp(p[1], p[2], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''argument : test EQUAL test'''] = ''' p[0] = ast.keyword(p[1].id, p[3], rule=inspect.currentframe().f_code.co_name) inherit_lineno(p[0], p[1])''' actions['''comp_iter : comp_for'''] = ''' p[0] = ([], p[1])''' actions['''comp_iter : comp_if'''] = ''' p[0] = p[1]''' actions['''comp_for : FOR exprlist IN or_test'''] = ''' ctx_to_store(p[2]) p[0] = [ast.comprehension(p[2], p[4], [], rule=inspect.currentframe().f_code.co_name, **p[1][1])]''' actions['''comp_for : FOR exprlist IN or_test comp_iter'''] = ''' ctx_to_store(p[2]) ifs, iters = p[5] p[0] = [ast.comprehension(p[2], p[4], ifs, rule=inspect.currentframe().f_code.co_name, **p[1][1])] + iters''' actions['''encoding_decl : NAME'''] = ''' p[0] = p[1]''' actions['''yield_expr : YIELD'''] = ''' p[0] = ast.Yield(None, rule=inspect.currentframe().f_code.co_name, **p[1][1])'''

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1

0

1

0

1

0

null

0

9

022e6d868c484ea0939194676e5e96b394a879b4

187

py

Python

python/tHome/util/process/__init__.py

ZigmundRat/T-Home

5dc8689f52d87dac890051e540b338b009293ced

[ "BSD-2-Clause" ]

18

2016-04-17T19:39:28.000Z

2020-11-19T06:55:20.000Z

python/tHome/util/process/__init__.py

ZigmundRat/T-Home

5dc8689f52d87dac890051e540b338b009293ced

[ "BSD-2-Clause" ]

11

2018-09-07T18:34:41.000Z

2021-05-02T04:44:54.000Z

python/tHome/util/process/__init__.py

ZigmundRat/T-Home

5dc8689f52d87dac890051e540b338b009293ced

[ "BSD-2-Clause" ]

12

2016-10-31T12:29:08.000Z

2021-12-28T12:18:28.000Z

#============================================================================= from .simple import simple #=============================================================================

31.166667

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0.117647

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187

5.5

0.75

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0.042781

187

5

79

37.4

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1

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1

0

1

0

8

0230f7d9bb5344b5b927a608f2e8627efdfc04c0

132

py

Python

test/fixtures/python/corpus/future_import_statement.A.py

matsubara0507/semantic

67899f701abc0f1f0cb4374d8d3c249afc33a272

[ "MIT" ]

8,844

2019-05-31T15:47:12.000Z

2022-03-31T18:33:51.000Z

test/fixtures/python/corpus/future_import_statement.A.py

matsubara0507/semantic

67899f701abc0f1f0cb4374d8d3c249afc33a272

[ "MIT" ]

401

2019-05-31T18:30:26.000Z

2022-03-31T16:32:29.000Z

test/fixtures/python/corpus/future_import_statement.A.py

matsubara0507/semantic

67899f701abc0f1f0cb4374d8d3c249afc33a272

[ "MIT" ]

504

2019-05-31T17:55:03.000Z

2022-03-30T04:15:04.000Z

from __future__ import print_function from __future__ import unicode_literals, division from __future__ import print_function as pf

33

49

0.878788

18

132

5.611111

0.555556

0.29703

0.475248

0.415842

0.574257

0

0.113636

132

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50

44

0.863248

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null

0

1

0

1

0

1

0

9

5a09ba4563846e0bd24f76bdcefc47f2b88476de

252

py

Python

dining_visualizer/views.py

NotDachun/hows-twitter

6f56507d9f62e7fc9e538d69215b2f0df6d334bf

[ "MIT" ]

null

dining_visualizer/views.py

NotDachun/hows-twitter

6f56507d9f62e7fc9e538d69215b2f0df6d334bf

[ "MIT" ]

3

2020-02-11T23:22:09.000Z

2021-06-10T20:55:34.000Z

dining_visualizer/views.py

NotDachun/hows-twitter

6f56507d9f62e7fc9e538d69215b2f0df6d334bf

[ "MIT" ]

null

from django.shortcuts import render from django.http import HttpResponse def home(request): return render(request, 'dining_visualizer/firstPage.html') def visualization(request): return render(request, 'dining_visualizer/visualization.html')

28

66

0.801587

30

252

6.666667

0.533333

0.1

0.19

0.26

0.42

0

0.111111

252

8

67

31.5

0.892857

0

0.269841

0

1

0.333333

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0

0.333333

1

0

null

0

1

0

1

0

null

0

1

0

1

0

7

5a560bcbc71b563b3e915a22d7a803f5e3957fbc

209

py

Python

sources/exceptions.py

plasticruler/newshound

c97ef09165eabb27ac65682e4893cf72dae7f3fb

[ "Apache-2.0" ]

null

sources/exceptions.py

plasticruler/newshound

c97ef09165eabb27ac65682e4893cf72dae7f3fb

[ "Apache-2.0" ]

null

sources/exceptions.py

plasticruler/newshound

c97ef09165eabb27ac65682e4893cf72dae7f3fb

[ "Apache-2.0" ]

null

class InvalidAPIKey(Exception): def __init__(self, provider): self.provider = provider class APIKeyMissing(Exception): def __init__(self, provider): self.provider = provider

20.9

33

0.669856

20

209

6.6

0.4

0.363636

0.242424

0.30303

0.727273

0

0.244019

209

9

34

23.222222

0.835443

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0.666667

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0.333333

false

0

0.666667

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null

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0

1

0

1

0

null

0

1

0

9

5a76358bc991a0e095a3168899b98d1d4edd8b09

4,950

py

Python

django_sso_app/core/apps/status/tests/test_backend.py

paiuolo/django-sso-app

75b96c669dc0b176dc77e08f018a3e97d259f636

[ "MIT" ]

1

2021-11-16T15:16:08.000Z

django_sso_app/core/apps/status/tests/test_backend.py

paiuolo/django-sso-app

75b96c669dc0b176dc77e08f018a3e97d259f636

[ "MIT" ]

null

django_sso_app/core/apps/status/tests/test_backend.py

paiuolo/django-sso-app

75b96c669dc0b176dc77e08f018a3e97d259f636

[ "MIT" ]

null

from django.contrib.auth import get_user_model from django.urls import reverse from django.core import mail from rest_framework import status from allauth.account.models import EmailConfirmationHMAC, EmailAddress from django_sso_app.core.tests.factories import UserTestCase from django_sso_app.core.apps.profiles.models import Profile User = get_user_model() class TestBackend(UserTestCase): def test_can_login_by_apigateway_header(self): with self.settings(DJANGO_SSO_APP_SHAPE='backend_only_apigateway'): new_pass = self._get_random_pass() new_user = self._get_new_user(password=new_pass) profile_url = reverse('django_sso_app_profile:rest-detail', args=(new_user.sso_id,)) user_device = self._get_user_device(new_user) client = self._get_client() client.cookies = self._get_jwt_cookie(user_device) response = client.get( profile_url, content_type='application/json', HTTP_X_CONSUMER_CUSTOM_ID=new_user.sso_app_profile.sso_id ) self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertEqual(response.data.get('sso_id'), new_user.sso_id, 'sso_id differs from header') self.assertEqual(Profile.objects.filter(sso_id=new_user.sso_id).count(), 1, 'no new user created') def test_redirect_to_profile_complete_if_profile_is_incomplete(self): BACKEND_URL = 'http://accounts.example.com' with self.settings(DJANGO_SSO_APP_SHAPE='backend_only', APP_URL=BACKEND_URL): new_pass = self._get_random_pass() new_user = self._get_new_incomplete_user(password=new_pass) user_device = self._get_user_device(new_user) client = self._get_client() client.cookies = self._get_jwt_cookie(user_device) response = client.get( '/profile/', content_type='application/json', HTTP_X_CONSUMER_CUSTOM_ID=new_user.sso_app_profile.sso_id ) self.assertEqual(response.status_code, status.HTTP_302_FOUND) self.assertEqual(response.url, '/profile/complete/') def test_redirect_to_profile_complete_if_profile_is_incomplete_apigateway(self): with self.settings(DJANGO_SSO_APP_SHAPE='backend_app_apigateway'): new_pass = self._get_random_pass() new_user = self._get_new_incomplete_user(password=new_pass) user_device = self._get_user_device(new_user) client = self._get_client() client.cookies = self._get_jwt_cookie(user_device) response = client.get( '/profile/', content_type='application/json', HTTP_X_CONSUMER_CUSTOM_ID=new_user.sso_app_profile.sso_id ) self.assertEqual(response.status_code, status.HTTP_302_FOUND) self.assertEqual(response.url, '/profile/complete/') def test_email_verification_redirects_to_profile_completion(self): with self.settings(DJANGO_SSO_APP_SHAPE='backend_app'): signup_obj = self._get_signup_object() client = self._get_client() response = client.post( reverse('account_signup'), data=signup_obj ) self.assertEqual(response.status_code, status.HTTP_302_FOUND) self.assertEqual(len(mail.outbox), 1) email_address = EmailAddress.objects.get(email=signup_obj['email']) email_confirmation = EmailConfirmationHMAC(email_address) response2 = client.get(reverse('account_confirm_email', args=[email_confirmation.key]), follow=True) self.assertEqual(response2.redirect_chain[-1][0], '/profile/complete/') def test_email_verification_redirects_to_profile_completion_apigateway(self): with self.settings(DJANGO_SSO_APP_SHAPE='backend_app'): signup_obj = self._get_signup_object() client = self._get_client() response = client.post( reverse('account_signup'), data=signup_obj, ) self.assertEqual(response.status_code, status.HTTP_302_FOUND) self.assertEqual(len(mail.outbox), 1) email_address = EmailAddress.objects.get(email=signup_obj['email']) email_confirmation = EmailConfirmationHMAC(email_address) new_user = User.objects.get(email=signup_obj['email']) response2 = client.get(reverse('account_confirm_email', args=[email_confirmation.key]), HTTP_X_CONSUMER_CUSTOM_ID=new_user.sso_app_profile.sso_id, follow=True) self.assertEqual(response2.redirect_chain[-1][0], '/profile/complete/')

38.076923

110

0.654949

578

4,950

5.212803

0.185121

0.044142

0.031862

0.023896

0.806505

0.793229

0.77232

0.741786

0

0.007067

0.256768

4,950

129

111

38.372093

0.811905

0

0.586207

0

0.083636

0.024444

0

0.149425

1

0.057471

false

0.068966

0.08046

0

0.149425

0

null

0

1

0

null

0

1

0

7

ce6dd5efc96f3dedb79889a834f0e618573a7f82

37

py

Python

classes/etl/spa_ncdf/__init__.py

rhyswhitley/rooting_depth

204da2e2e1fac8c8ff9f81ae096d6b1e851a71d0

[ "CC0-1.0" ]

null

classes/etl/spa_ncdf/__init__.py

rhyswhitley/rooting_depth

204da2e2e1fac8c8ff9f81ae096d6b1e851a71d0

[ "CC0-1.0" ]

null

classes/etl/spa_ncdf/__init__.py

rhyswhitley/rooting_depth

204da2e2e1fac8c8ff9f81ae096d6b1e851a71d0

[ "CC0-1.0" ]

1

2019-09-01T04:15:21.000Z

from spa_netCDF4 import spa_netCDF4

12.333333

35

0.864865

6

37

5

0.666667

0

0.0625

0.135135

37

2

36

18.5

0.875

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

ced0d441476cd6d9c5012f0a5f706820949af69f

1,228

py

Python

tests/test_paths.py

RBrearton/nexusformat

229eb8105113a8660461c7b9150bfc769959455a

[ "BSD-3-Clause-Clear" ]

null

tests/test_paths.py

RBrearton/nexusformat

229eb8105113a8660461c7b9150bfc769959455a

[ "BSD-3-Clause-Clear" ]

null

tests/test_paths.py

RBrearton/nexusformat

229eb8105113a8660461c7b9150bfc769959455a

[ "BSD-3-Clause-Clear" ]

null

import pytest from nexusformat.nexus import * field1 = NXfield((1,2), name="f1") def test_attribute_paths(): root = NXroot(NXentry()) root.entry.g1 = NXgroup(field1) assert root.entry.g1.nxpath == "/entry/g1" assert root["entry/g1"] is root.entry.g1 assert root["entry/g1/f1"] is root.entry.g1.f1 assert "g1" in root.entry assert "f1" in root.entry.g1 assert "entry/g1/f1" in root assert root.entry.g1.f1.nxroot is root def test_dictionary_paths(): root = NXroot(NXentry()) root["entry/g1"] = NXgroup(field1) assert root.entry.g1.nxpath == "/entry/g1" assert root["entry/g1"] is root.entry.g1 assert root["entry/g1/f1"] is root.entry.g1.f1 assert "g1" in root["/entry"] assert "f1" in root["/entry/g1"] assert "/entry/g1/f1" in root assert root["/entry/g1/f1"].nxroot is root def test_relative_paths(): root = NXroot(NXentry()) root["entry/g1"] = NXgroup() root["entry/g1/g2"] = NXgroup() root["entry/g1/g2/f1"] = field1 assert "f1" in root["entry/g1/g2"] assert "g2/f1" in root["entry/g1"] assert "g1/g2/f1" in root["entry"] assert root["entry/g1/g2/f1"].nxpath == "/entry/g1/g2/f1" assert "entry" in root

26.12766

61

0.636808

194

1,228

4

0.14433

0.243557

0.311856

0.197165

0.80799

0.721649

0.667526

0.615979

0

0.060545

0.192997

1,228

46

62

26.695652

0.722503

0

0.272727

0

0.187296

0

0.575758

1

0.090909

false

0

0.060606

0

0.151515

0

null

1

0

1

0

null

0

1

0

7

0c74fa2e30a7e71564c45064dad682e4e7ace7d5

4,763

py

Python

visual.py

WhiteDOU/DNN_Pruning

bb84c9161ae8e2602ae00b0e6a4907a55f74a01f

[ "MIT" ]

null

visual.py

WhiteDOU/DNN_Pruning

bb84c9161ae8e2602ae00b0e6a4907a55f74a01f

[ "MIT" ]

null

visual.py

WhiteDOU/DNN_Pruning

bb84c9161ae8e2602ae00b0e6a4907a55f74a01f

[ "MIT" ]

null

import glob import matplotlib.pyplot as plt import numpy as np from mpl_toolkits.mplot3d import Axes3D root = sorted(glob.glob('./all_fc/*')) def fc(): i = 0 name = 'fc' + str(i / 3) acc = root[i] run_time = root[i + 1] x = root[i + 2] with open(acc, 'r') as f: acc = f.readline() acc = acc.replace(' ', '').replace('[', '').replace(']', '').split(',') for i, item in enumerate(acc): acc[i] = float(acc[i]) with open(x, 'r') as f: x = f.readline() x = x.replace(' ', '').replace('[', '').replace(']', '').split(',') for i, item in enumerate(x): x[i] = float(x[i]) with open(run_time, 'r') as f: run_time = f.readline() run_time = run_time.replace(' ', '').replace('[', '').replace(']', '').split(',') for i, item in enumerate(run_time): run_time[i] = float(run_time[i]) plt.figure() plt.title(name + 'ACC & RUN_TIME') plt.plot(x, acc, color='green', label='ACC') plt.plot(x, run_time, color='red', label='RUN_TIME') plt.xlabel('weights remain(%)') plt.ylabel('ACC & RUN_TIME(s) ') plt.legend() plt.show() i = 3 name = 'fc' + str(i / 3) acc = root[i] run_time = root[i + 1] x = root[i + 2] with open(acc, 'r') as f: acc = f.readline() acc = acc.replace(' ', '').replace('[', '').replace(']', '').split(',') for i, item in enumerate(acc): acc[i] = float(acc[i]) with open(x, 'r') as f: x = f.readline() x = x.replace(' ', '').replace('[', '').replace(']', '').split(',') for i, item in enumerate(x): x[i] = float(x[i]) with open(run_time, 'r') as f: run_time = f.readline() run_time = run_time.replace(' ', '').replace('[', '').replace(']', '').split(',') for i, item in enumerate(run_time): run_time[i] = float(run_time[i]) plt.figure() plt.title(name + 'ACC & RUN_TIME') plt.plot(x, acc, color='green', label='ACC') plt.plot(x, run_time, color='red', label='RUN_TIME') plt.xlabel('weights remain(%)') plt.ylabel('ACC & RUN_TIME(s) ') plt.legend() plt.show() print(root) def feature(): for i in range(0, 15, 3): name = 'feature:' + str(i / 3) acc = root[i] x = root[i + 1] run_time = root[i + 2] with open(acc, 'r') as f: acc = f.readline() acc = acc.replace(' ', '').replace('[', '').replace(']', '').split(',') for i, item in enumerate(acc): acc[i] = float(acc[i]) with open(x, 'r') as f: x = f.readline() x = x.replace(' ', '').replace('[', '').replace(']', '').split(',') for i, item in enumerate(x): x[i] = float(x[i]) with open(run_time, 'r') as f: run_time = f.readline() run_time = run_time.replace(' ', '').replace('[', '').replace(']', '').split(',') for i, item in enumerate(run_time): run_time[i] = float(run_time[i]) plt.figure() plt.title(name + 'ACC & RUN_TIME') plt.plot(x, acc, color='green', label='ACC') plt.plot(x, run_time, color='red', label='RUN_TIME') plt.xlabel('weights remain(%)') plt.ylabel('ACC & RUN_TIME(s) ') plt.legend() plt.show() def fc_all(): acc = root[0] coord = root[1] run_time = root[2] with open(acc, 'r') as f: acc = f.readline() acc = acc.replace(' ', '').replace('[', '').replace(']', '').split(',') for i, item in enumerate(acc): acc[i] = float(acc[i]) with open(coord, 'r') as f: coord = f.readline() coord = coord.replace(' ', '').replace('[', '').replace(']', '').split(',') for i, item in enumerate(coord): coord[i] = float(coord[i]) x = coord[0::2] y = coord[1::2] with open(run_time, 'r') as f: run_time = f.readline() run_time = run_time.replace(' ', '').replace('[', '').replace(']', '').split(',') for i, item in enumerate(run_time): run_time[i] = float(run_time[i]) x = np.linspace(14, 0.0025, num=100) y = np.linspace(5, 0.0025, num=100) acc = np.array(acc).reshape(x.shape[0],y.shape[0]) run_time = np.array(run_time).reshape(x.shape[0],y.shape[0]) print(run_time) fig = plt.figure() ax = Axes3D(fig) x,y = np.meshgrid(x,y) ax.plot_surface(x,y,acc,rstride=1, cstride=1, cmap='rainbow') plt.xlabel('fc0') plt.ylabel('fc1') plt.show() plt.xlabel('fc0') plt.ylabel('fc1') ax.plot_surface(x,y,run_time,rstride=1, cstride=1, cmap='rainbow') plt.show() fc_all()

32.848276

93

0.500945

670

4,763

3.480597

0.119403

0.144082

0.020583

0.133791

0.810892

0.798027

0.773156

0.729417

0.71012

0

0.016369

0.281755

4,763

144

94

33.076389

0.665303

0

0.723077

0

0.065519

0

1

0.023077

false

0

0.030769

0

0.053846

0.015385

0

null

0

1

0

1

0

null

0

7

0c88e8beee792e5169c40d63a655beaa2545b827

605

py

Python

hostman/utils.py

jonhadfield/hostman

c1643f5dd95833715b26032821bf631a4e2c4a7e

[ "MIT" ]

20

2018-09-11T16:27:04.000Z

2021-08-16T17:21:10.000Z

hostman/utils.py

TeamAleph/hostman

8ba27903a6dc58464ee4cb8e1a48a2b1a5559696

[ "MIT" ]

2

2019-09-17T11:01:17.000Z

2020-02-13T15:53:24.000Z

hostman/utils.py

TeamAleph/hostman

8ba27903a6dc58464ee4cb8e1a48a2b1a5559696

[ "MIT" ]

4

2018-09-11T16:30:25.000Z

2021-02-24T19:52:43.000Z

import os def is_readable(path=None): """Test if the supplied filesystem path can be read :param path: A filesystem path :return: True if the path is a file that can be read. Otherwise, False. """ if os.path.isfile(path) and os.access(path, os.R_OK): return True return False def is_writeable(path=None): """Test if the supplied filesystem path can be written to :param path: A filesystem path :return: True if the path is a file that can be written. Otherwise, False. """ if os.path.isfile(path) and os.access(path, os.W_OK): return True

26.304348

78

0.667769

99

605

4.040404

0.323232

0.05

0.06

0.07

0.76

0

0.242975

605

22

79

27.5

0.873362

0.519008

0

0.25

0

1

0.25

false

0

0.125

0

0.75

0

null

0

1

0

null

0

1

0

1

0

7

0c8abae002d63dd11e69e680b8d593f8881ae6bf

13,840

py

Python

Week7/final-exam-q4/validate.py

italoag/M101P

708bdd793735228f820f3f50f57c44ce8fc637ef

[ "MIT" ]

null

Week7/final-exam-q4/validate.py

italoag/M101P

708bdd793735228f820f3f50f57c44ce8fc637ef

[ "MIT" ]

null

Week7/final-exam-q4/validate.py

italoag/M101P

708bdd793735228f820f3f50f57c44ce8fc637ef

[ "MIT" ]

null

import base64 code="
import pymongo
import urllib2
import urllib
import cookielib
import random
import re
import string
import sys
import getopt

# init the global cookie jar
cj = cookielib.CookieJar()
# declare the variables to connect to db
connection = None
db = None
webhost = "localhost:8082"
mongostr = "mongodb://localhost:27017"
db_name = "blog"

# this script will check that homework 3.2 is correct

# makes a little salt
def make_salt(n):
    salt = ""
    for i in range(n):
        salt = salt + random.choice(string.ascii_letters)
    return salt


# this is a validation script to make sure the blog works correctly.

def create_user(username, password):
    
    global cj

    try:
        print "Trying to create a test user ", username
        url = "http://{0}/signup".format(webhost)

        data = urllib.urlencode([("email",""),("username",username), ("password",password), ("verify",password)])
        request = urllib2.Request(url=url, data=data)
        opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
        f = opener.open(request)

        users = db.users
        # check that the user is in users collection
        user = users.find_one({'_id':username})
        if (user == None):
            print "Could not find the test user ", username, "in the users collection."
            return False
        print "Found the test user ", username, " in the users collection"

        # check that the user has been built
        result = f.read()
        expr = re.compile("Welcome\s+"+ username)
        if expr.search(result):
            return True
        
        print "When we tried to create a user, here is the output we got\n"
        print result
        
        return False
    except:
        print "the request to ", url, " failed, so your blog may not be running."
        raise
        return False


def try_to_login(username, password):

    try:
        print "Trying to login for test user ", username
        url = "http://{0}/login".format(webhost)

        data = urllib.urlencode([("username",username), ("password",password)])
        request = urllib2.Request(url=url, data=data)
        opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
        f = opener.open(request)

        # check for successful login
        result = f.read()
        expr = re.compile("Welcome\s+"+ username)
        if expr.search(result):
            return True

        print "When we tried to login, here is the output we got\n"
        print result
        return False
    except:
        print "the request to ", url, " failed, so your blog may not be running."
        return False


def add_blog_post(title,post,tags):

    try:
        print "Trying to submit a post with title ", title
        data = urllib.urlencode([("body",post), ("subject",title), ("tags",tags)])
        url = "http://{0}/newpost".format(webhost)
        request = urllib2.Request(url=url, data=data)
        cj.add_cookie_header(request)
        opener = urllib2.build_opener()
        f = opener.open(request)

        # check for successful login
        result = f.read()
        expr = re.compile(title + ".+" + post, re.DOTALL)

        if expr.search(result):
            return True

        print "When we tried to post, here is the output we got\n"
        print result
        return False

    except:
        print "the request to ", url, " failed, so your blog may not be running."
        raise

        return False

def add_blog_comment(title,post):

    try:
        print "+Trying to submit a blog comment for post with title", title
        url = "http://{0}/newcomment".format(webhost)
        
        doc = {}
        check_mongo_for_post(title, post, doc)

        permalink = doc['doc']['permalink']

        comment_name = make_salt(12)
        comment_body = make_salt(12)

        data = urllib.urlencode([("commentName",comment_name), ("commentBody",comment_body), ("permalink",permalink)])
        request = urllib2.Request(url=url, data=data)
        cj.add_cookie_header(request)
        opener = urllib2.build_opener()
        f = opener.open(request)

        # check for successful addition of comment on page
        result = f.read()
        expr = re.compile(title + ".+" + post, re.DOTALL)

        if not expr.search(result):
            print "When we tried to find the comment we posted at the  ", url, " here is what we got"
            print result
            return False


        # check for successful addition of comment..retrieve the doc again
        if(not check_mongo_for_post(title, post, doc)):
            print "Could not find comment in database"
            return False
        
        found = False
        if ('comments' in doc['doc']):
            for comment in doc['doc']['comments']:
                if (comment['body'] == comment_body and comment['author'] == comment_name):
                    found = True

        return found

    except:
        print "the request to ", url, " failed, so your blog may not be running."
        raise

        return False


# fetch the blog home page and return the link of the first post
def fetch_blog_home_page(posts):

    try:
        url = "http://{0}/".format(webhost)
        print "Trying to grab the blog home page at url and find the first post.", url
        request = urllib2.Request(url=url)
        cj.add_cookie_header(request)
        opener = urllib2.build_opener()
        f = opener.open(request)

        # Look for a post
        result = f.read()
        expr = re.compile("<a href=\"([^\"]+)\"\w*?>", re.DOTALL)


        match = expr.search(result)

        if match is not None:
            print "Fount a post url: ", match.group(1)
            posts.append(match.group(1))
            return True

        
        print "Hmm, can't seem to find a post. Is the blog populated with posts?"
        print "When we tried to read the blog index at ", url, " here is what we got"
        print result
        return False

    except:
        print "the request to ", url, " failed, so your blog may not be running."
        raise

        return False

# gets the likes value off the first commment or returns None
def fetch_likes(url):

    try:
        url = "http://{0}{1}".format(webhost, url)
        print "Trying to grab the number of likes for url ", url
        request = urllib2.Request(url=url)
        cj.add_cookie_header(request)
        opener = urllib2.build_opener()
        f = opener.open(request)


        # let's get the first form element
        result = f.read()
        expr = re.compile("<form[^>]*>.*?Likes:\s*(\d+)\s*<.*?</form>", re.DOTALL)

        match = expr.search(result)

        if match is not None:
            print "Likes value ", match.group(1)
            return int(match.group(1))

        print "Can't fetch the like value for the first comment. Perhaps the blog entry has no comments?"
        print "When we tried to read the blog permalink at ", url, " here is what we got"
        return None

    except:
        print "the request to ", url, " failed, so your blog may not be running."
        raise

        return None


# gets the likes value off the first commment or returns None
def click_on_like(permalink):

    print "Clicking on Like link for post: ", permalink
    try:
        expr =  re.compile("[^/]+/([^/]+)")
        match = expr.search(permalink)
        if match is None:
            return False

        permalink = match.group(1)
        url = "http://{0}/like".format(webhost)
        # print "Like POST url", url

        data = urllib.urlencode([("permalink",permalink), ("comment_ordinal","0")])
        request = urllib2.Request(url=url, data=data)
        cj.add_cookie_header(request)
        opener = urllib2.build_opener()
        f = opener.open(request)

        return True

    except:
        print "the request to ", url, " failed, so your blog may not be running."
        raise




# command line arg parsing to make folks happy who want to run at mongolabs or mongohq
# this functions uses global vars to communicate. forgive me.
def arg_parsing(argv):

    global webhost
    global mongostr
    global db_name

    try:
        opts, args = getopt.getopt(argv, "-p:-m:-d:")
    except getopt.GetoptError:
        print "usage validate.py -p webhost -m mongoConnectString -d databaseName"
        print "\twebhost defaults to {0}".format(webhost)
        print "\tmongoConnectionString default to {0}".format(mongostr)
        print "\tdatabaseName defaults to {0}".format(db_name)
        sys.exit(2)
    for opt, arg in opts:
        if (opt == '-h'):
            print "usage validate.py -p webhost -m mongoConnectString -d databaseName"
            sys.exit(2)
        elif opt in ("-p"):
            webhost = arg
            print "Overriding HTTP host to be ", webhost
        elif opt in ("-m"):
            mongostr = arg
            print "Overriding MongoDB connection string to be ", mongostr
        elif opt in ("-d"):
            db_name = arg
            print "Overriding MongoDB database to be ", db_name
            


# main section of the code
def main(argv):
            
    arg_parsing(argv)
    global connection
    global db

    print "Welcome to the M101 Final Exam, Question 4 Validation Checker"

    # connect to the db (mongostr was set in arg_parsing)
    connection = pymongo.Connection(mongostr, safe=True)
    db = connection[db_name]


    # grab the blog home page and find the first post
    posts = []
    if (not fetch_blog_home_page(posts)):
        print "I can't grab the home page of the blog"
        sys.exit(1)

    # now go to the permalink page for that post
    likes_value = fetch_likes(posts[0])

    if (likes_value is  None):
        print "Can't fetch the like value"
        sys.exit(1)

    click_on_like(posts[0])

    new_likes_value = fetch_likes(posts[0])

    if (new_likes_value != (likes_value + 1)):
        print "I was not able to increment the likes on a comment"
        print "old likes value was ", likes_value
        print "likes value after I clicked was ", new_likes_value
        print "Sorry, you have not solved it yet."
        sys.exit(1)


    print "Tests Passed for Final 4. Your validation code is 3f837hhg673ghd93hgf8"


if __name__ == "__main__":
    main(sys.argv[1:])







" eval(compile(base64.b64decode(code), "<string>", 'exec'))

3,460

13,767

0.998121

11

13,840

1,255.818182

0.818182

0

0.095056

0.000434

13,840

3

13,768

4,613.333333

0.903499

0

0.995087

0.99422

0

1

0

1

0

false

0

0.333333

0

0.333333

0

1

0

1

null

0

1

0

1

null

1

0

1

0

9

0ce345f3435ce519223a781685bbe50964f41097

17,219

py

Python

src/modules/testVTK/testDB3D.py

sankhaMukherjee/vtk

fc6ae8b4e56d62796a1a0d28e0c7dce598114103

[ "MIT" ]

null

src/modules/testVTK/testDB3D.py

sankhaMukherjee/vtk

fc6ae8b4e56d62796a1a0d28e0c7dce598114103

[ "MIT" ]

5

2020-03-24T18:03:04.000Z

2021-08-23T20:34:23.000Z

src/modules/testVTK/testDB3D.py

sankhaMukherjee/vtk

fc6ae8b4e56d62796a1a0d28e0c7dce598114103

[ "MIT" ]

null

import vtk import numpy as np from lib.simpleFunctions import simpleObjects as sO import matplotlib.pyplot as plt from matplotlib import colors as cl import os, json from datetime import datetime as dt # --------------------------------------------------------- # Global variables are always bad. However, there # appears to be no good way in which the renderer # and the window objects can be passed along to # other functions while the windoow is being rendered # --------------------------------------------------------- renWin = vtk.vtkRenderWindow() # for the screen capture ren = vtk.vtkRenderer() # for the camera def restoreCammeraSpecs(fileName): try: camera = ren.GetActiveCamera() data = json.load(open(fileName)) camera.SetFocalPoint(data['focalPoint']) camera.SetPosition(data['position']) camera.SetViewUp(data['viewUp']) camera.SetViewAngle(data['viewAngle']) camera.SetClippingRange(data['clippingRange']) except Exception as e: print(f'Unable to restore the session from [{fileName}]: {e}') return def saveCameraSpecs(): camera = ren.GetActiveCamera() folder = '../results/cameraPos' os.makedirs(folder, exist_ok=True) fileName = dt.now().strftime('3D_%Y-%m-%d--%H-%M-%S.json') fileName = os.path.join( folder, fileName ) focalPoint = [n for n in camera.GetFocalPoint()] position = [n for n in camera.GetPosition()] viewUp = [n for n in camera.GetViewUp()] viewAngle = camera.GetViewAngle() clippingRange = [n for n in camera.GetClippingRange()] data = { 'focalPoint' : focalPoint, 'position' : position, 'viewUp' : viewUp, 'viewAngle' : viewAngle, 'clippingRange' : clippingRange, } with open(fileName, 'w') as f: f.write( json.dumps(data) ) with open(os.path.join(folder, 'latest3D.json'), 'w') as f: f.write( json.dumps(data) ) print(f'+------------------------------------------') print(f'| focalPoint = {focalPoint}') print(f'| position = {position}') print(f'| viewUp = {viewUp}') print(f'| viewAngle = {viewAngle}') print(f'| clippingRange = {clippingRange}') print(f'+------------------------------------------') return def screenShot(): folder = '../results/screenShots' os.makedirs(folder, exist_ok=True) fileName = dt.now().strftime('%Y-%m-%d--%H-%M-%S.png') fileName = os.path.join( folder, fileName ) # screenshot code: w2if = vtk.vtkWindowToImageFilter() w2if.SetInput(renWin) w2if.SetInputBufferTypeToRGB() w2if.ReadFrontBufferOff() w2if.Update() writer = vtk.vtkPNGWriter() writer.SetFileName(fileName) writer.SetInputConnection(w2if.GetOutputPort()) writer.Write() return fileName def Keypress(obj, event): key = obj.GetKeySym() if (key == 's') or (key == 'S'): fileName = screenShot() print(f'Screenshot saved at [{fileName}]') if (key == 'c') or (key == 'C'): saveCameraSpecs() def getData(): data = [ ["Something","27574","M","Hispanic"], ["ArapahoeHouse","11636","M","White"], ["Other","32608","M","American Indian"], ["ArapahoeHouse","44460","F","White"], ["Something","18899","F","White"], ["ArapahoeHouse","26025","M","White"], ["ArapahoeHouse","7971","M","Hispanic"], ["ArapahoeHouse","19373","M","Black"], ["ArapahoeHouse","41578","M","White"], ["ArapahoeHouse","42446","M","Native American"], ["ArapahoeHouse","23182","F","White"], ] nPatients = len(data) nDaysList = [206, 589, 278, 348, 274, 32, 317, 73, 184, 641, 468] allCGI = [ [4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6], [4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6], [4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,1,1,1,1,1,1,1], [4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6], 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allCGI[p] data[p].append( np.random.randint(1,7,nDays) ) return data def colorMapper(forMap): uniques = sorted(list(set(forMap))) N = len(uniques)-1 mapper = { m:plt.cm.tab20b(i/N) for i, m in enumerate(uniques)} result = [ mapper[f][:3] for f in forMap ] return result def colorMapper3D_smooth(forMap): minVal = min(map(min, forMap)) maxVal = max(map(max, forMap)) forMap1 = [ (0.2+(np.array(f) - minVal)*0.8/(maxVal - minVal)) for f in forMap] forMap2 = [plt.cm.Blues(f)[:,:-1] for f in forMap1] return forMap2 def sizeMapper3D_smooth(forMap): minVal = min(map(min, forMap)) maxVal = max(map(max, forMap)) forMap1 = [ (0.2+(np.array(f) - minVal)*0.8/(maxVal - minVal)) for f in forMap] return forMap1 def get1Dobjects(colors, xPos, xText = 'x', yPosDelta=0.5, size=0.3, highlight=None): allObj = [] for i, color in enumerate(colors): if (highlight is not None) and (highlight != i): color = cl.rgb_to_hsv(color) # color[0] = 0 color[1] = 0 color = cl.hsv_to_rgb(color) obj = sO.Cube() obj.source.SetCenter(xPos, i*yPosDelta, 0) obj.setSize(size) obj.setColor( color ) if (highlight is not None) and (highlight != i): obj.actor.GetProperty().SetOpacity(0.2) allObj.append( obj ) xLabel = sO.Text(f'{xText}') xLabel.actor.SetScale( 0.1, 0.1, 0.1 ) xLabel.actor.SetPosition( xPos-0.2, -1, 0 ) xLabel.actor.GetProperty().SetColor( 0, 0, 0 ) allObj.append( xLabel ) ax1 = sO.Line((xPos,-0.4,0),(xPos,-0.6,0)) allObj.append( ax1 ) return allObj def get1DobjectsSmooth( vals, xPos, xText='x', yPosDelta=0.5, size=0.3, vMax = None, vMin=None, highlight=None ): if vMin is None: minVal = min(vals) else: minVal = vMin if vMax is None: maxVal = max(vals) else: maxVal = vMax size1 = 0.2 + 0.8*(np.array(vals) - minVal)/(maxVal-minVal) colors = plt.cm.Blues(size1)[:,:-1] allObj = [] for i, color in enumerate(colors): if (highlight is not None) and (highlight != i): color = cl.rgb_to_hsv(color) # color[0] = 0 color[1] = 0 color = cl.hsv_to_rgb(color) obj = sO.Cube() obj.source.SetCenter(xPos, i*yPosDelta, 0) obj.setSize(size*size1[i]) obj.setColor( color ) if (highlight is not None) and (highlight != i): obj.actor.GetProperty().SetOpacity(0.2) allObj.append( obj ) xLabel = sO.Text(f'{xText}') xLabel.actor.SetScale( 0.1, 0.1, 0.1 ) xLabel.actor.SetPosition( xPos-0.2, -1, 0 ) xLabel.actor.GetProperty().SetColor( 0, 0, 0 ) allObj.append( xLabel ) ax1 = sO.Line((xPos,-0.4,0),(xPos,-0.6,0)) allObj.append( ax1 ) return allObj def get2DObjects(colors2D, sizes2D, xPos, xText='x', yPosDelta=0.5, zPosDelta=0.5, size=0.3, maxNz=10, highlight=None): allObj = [] for i, (colors, sizes) in enumerate(zip(colors2D, sizes2D)): for j, (c, s) in enumerate(zip(colors, sizes)): if j > maxNz: break if (highlight is not None) and (highlight != i): c = cl.rgb_to_hsv(c) # color[0] = 0 c[1] = 0 c = cl.hsv_to_rgb(c) obj = sO.Cube() obj.source.SetCenter(xPos, i*yPosDelta, -j*zPosDelta) obj.setSize(size*s) obj.setColor( c ) if (highlight is not None) and (highlight != i): obj.actor.GetProperty().SetOpacity(0.1) allObj.append( obj ) xLabel = sO.Text(f'{xText}') xLabel.actor.SetScale( 0.1, 0.1, 0.1 ) xLabel.actor.SetPosition( xPos-0.2, -1, 0 ) xLabel.actor.GetProperty().SetColor( 0, 0, 0 ) allObj.append( xLabel ) ax1 = sO.Line((xPos,-0.4,0),(xPos,-0.6,0)) allObj.append( ax1 ) return allObj def getPatients(nPatients, xPos, yPosDelta): allObj = [] for p in range(nPatients): patientText = sO.Text(f'p_{p:03d}') patientText.actor.SetScale( 0.1, 0.1, 0.1 ) patientText.actor.SetPosition( xPos, p*yPosDelta, 0 ) patientText.actor.GetProperty().SetColor( 0, 0, 0 ) allObj.append( patientText ) ax = sO.Line((xPos-0.3 -0.1, p*yPosDelta, 0), (xPos-0.3 +0.1, p*yPosDelta, 0)) allObj.append( ax ) ax = sO.Line((xPos-0.3, 0, 0), (xPos-0.3, (nPatients-1)*yPosDelta, 0)) allObj.append( ax ) return allObj def plot3D(config): bgColor = [217/255, 211/255, 232/255] data = getData() site, patient, sex, race, cgi = zip(*data) meanCGI = [np.mean(m[:10]) for m in cgi] sexColors = colorMapper( sex ) raceColors = colorMapper( race ) siteColors = colorMapper( site ) cgiColors = colorMapper3D_smooth( cgi ) cgiSizes = sizeMapper3D_smooth( cgi ) ren.SetBackground(bgColor) renWin.AddRenderer(ren) iren = vtk.vtkRenderWindowInteractor() iren.SetRenderWindow(renWin) if config['meanCGI']: for obj in get1DobjectsSmooth( meanCGI, xPos=0, xText='meanCGI', vMax = 7, vMin=1, highlight=config['highlight'] ): ren.AddActor( obj.actor ) if config['cgi']: for obj in get2DObjects(cgiColors, cgiSizes, 1, 'cgi', highlight=config['highlight']): ren.AddActor( obj.actor ) if config['race']: for obj in get1Dobjects(raceColors, 3, 'race', highlight=config['highlight']): ren.AddActor( obj.actor ) if config['sex']: for obj in get1Dobjects(sexColors, 2, 'sex', highlight=config['highlight']): ren.AddActor( obj.actor ) for obj in getPatients(11, 4, 0.5): ren.AddActor( obj.actor ) # day4 = sO.MeshXY(0,0, 4, 5, -2, 60) # ren.AddActor( day4.actor ) if config['highlight']: user4 = sO.MeshXZ(-0.3, 0, 3.3, -5, 2, 20) ren.AddActor( user4.actor ) renWin.SetSize(900, 900) renWin.SetWindowName('3d stuff') iren.AddObserver("KeyPressEvent", Keypress) iren.Initialize() ren.ResetCamera() restoreCammeraSpecs('../results/cameraPos/latest3D.json') renWin.Render() iren.Start() return

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Python

magni/tests/cs_reconstruction.py

SIP-AAU/Magni

6328dc98a273506f433af52e6bd394754a844550

[ "BSD-2-Clause" ]

42

2015-02-09T10:17:26.000Z

2021-12-21T09:38:04.000Z

magni/tests/cs_reconstruction.py

SIP-AAU/Magni

6328dc98a273506f433af52e6bd394754a844550

[ "BSD-2-Clause" ]

3

2015-03-20T12:00:40.000Z

2015-03-20T12:01:16.000Z

magni/tests/cs_reconstruction.py

SIP-AAU/Magni

6328dc98a273506f433af52e6bd394754a844550

[ "BSD-2-Clause" ]

14

2015-04-28T03:08:32.000Z

2021-07-24T13:29:24.000Z

""" .. Copyright (c) 2015-2017, Magni developers. All rights reserved. See LICENSE.rst for further information. Module providing unittests for `magni.cs.reconstruction`. **Testing Strategy** The usage of FastOps is tested along with reconstructions in various points in the phase space. **Phase Space Tests Overview** A set of :math:`(\delta, \rho)` points in the phase space is selected. For each algorithm, the reconstruction capabilities in each point has been determined for a given problem suite. The tests are based on a comparison with these reference results. Specifically, a comparison based on `np.allclose` is done. Also some border cases (extremes) like :math:`k = 0` are tested. Points where it is likely to have positive results +-----+------+------+------+------+------+------+------+ | no.| 1 | 2 | 3 | 4 | 5 | 6 | 7 | +-----+------+------+------+------+------+------+------+ |delta| 0.08 | 0.24 | 0.38 | 0.62 | 0.78 | 0.84 | 0.96 | +-----+------+------+------+------+------+------+------+ | rho| 0.05 | 0.01 | 0.12 | 0.38 | 0.22 | 0.08 | 0.91 | +-----+------+------+------+------+------+------+------+ Points where it is unlikely to have positive results +-----+------+------+------+ | no.| A | B | C | +-----+------+------+------+ |delta| 0.06 | 0.19 | 0.29 | +-----+------+------+------+ | rho| 0.92 | 0.84 | 0.94 | +-----+------+------+------+ **Functions Tested** See the docstrings of the below listed classes. Routine listings ---------------- ComparisonGAMPTests(unittest.TestCase) Comparison of magni.cs.reconstruction.gamp to a reference implementation. FastOpsTests(unittest.TestCase) Tests of FastOp input, i.e. function based measurements and FFT dictionary. FeatureTest(object) Reconstruction algorithm feature test base class. FeaturePrecisionFloatTest(FeatureTest, unittest.TestCase) Test of the precision float feature in reconstruction algorithms. FeatureReportHistoryTest(FeatureTest, unittest.TestCase) Test the report history feature in reconstruction algorithms. FeatureStopCriterionTest(FeatureTest, unittest.TestCase) Test of the stop criterion feature in reconstruction algorithms. FeatureWarmStartTest(FeatureTest, unittest.TestCase) Test of the warm_start feature in reconstruction algorithms. PhaseSpaceExtremesTest(unittest.TestCase): Tests of border case (extreme) phase space values. PhaseSpaceTest(object) Phase space test base class. PhaseSpaceTest1(PhaseSpaceTest, unittest.TestCase) Test of reconstruction capabilities at Phase Space point (0.08, 0.05) PhaseSpaceTest2(PhaseSpaceTest, unittest.TestCase) Test of reconstruction capabilities at Phase Space point (0.24, 0.01) PhaseSpaceTest3(PhaseSpaceTest, unittest.TestCase) Test of reconstruction capabilities at Phase Space point (0.38, 0.12) PhaseSpaceTest4(PhaseSpaceTest, unittest.TestCase) Test of reconstruction capabilities at Phase Space point (0.62, 0.38) PhaseSpaceTest5(PhaseSpaceTest, unittest.TestCase) Test of reconstruction capabilities at Phase Space point (0.78, 0.22) PhaseSpaceTest6(PhaseSpaceTest, unittest.TestCase) Test of reconstruction capabilities at Phase Space point (0.84, 0.08) PhaseSpaceTest7(PhaseSpaceTest, unittest.TestCase) Test of reconstruction capabilities at Phase Space point (0.96, 0.91) PhaseSpaceTestA(PhaseSpaceTest, unittest.TestCase) Test of reconstruction capabilities at Phase Space point (0.06, 0.92) PhaseSpaceTestB(PhaseSpaceTest, unittest.TestCase) Test of reconstruction capabilities at Phase Space point (0.19, 0.84) PhaseSpaceTestC(PhaseSpaceTest, unittest.TestCase) Test of reconstruction capabilities at Phase Space point (0.29, 0.94) TestUSERademacher(unittest.TestCase) Test of the use_rademacher test fixture function. use_rademacher(n, m, k, seed) Prepare an instance of the USE/Rademacher problem suite """ from __future__ import division import os import unittest import warnings import numpy as np import magni from magni.utils.validation import decorate_validation as _decorate_validation from magni.utils.validation import validate_numeric as _numeric class ComparisonGAMPTests(unittest.TestCase): """ Comparison of magni.cs.reconstruction.gamp to a reference implementation. **Reference implementation** "run_amp" from https://github.com/eric-tramel/SwAMP-Demo/blob/master/python/amp.py commit b32755caa8d6b59929174e2a06cc685bae5849b6 """ def setUp(self): self.ns = [1024, 2048, 2048, 2000, 1000] self.ms = [770, 780, 1024, 800, 500] self.ks = [440, 440, 1024, 126, 88] self.sigma_sqs = [0.0, 0.0, 0.0, 1e-3, 1e-2] self.sigma_sqs_init = [1e-6, 1e-6, 1e-6, 1, 1] self.theta_bars = [0.0, 0.0, 0.0, 0.2, 0.0] self.theta_tildes = [1.0, 1.0, 1.0, 0.3, 1.0] self.taus = [float(k) / n for (k, n) in zip(self.ks, self.ns)] self.tolerance = 1e-16 self.iterations = 500 np.random.seed(6021) self.seeds = np.random.randint(1000, 80000, size=len(self.ns)) file_path = os.path.dirname(os.path.abspath(__file__)) + os.sep fixed_sigma_sq_sol_file = np.load( file_path + 'gamp_fixed_sigma_sq_sols.npz') em_sigma_sq_sol_file = np.load( file_path + 'gamp_em_sigma_sq_sols.npz') self.comparison_solutions_fixed_sigma_sq = [ fixed_sigma_sq_sol_file[arr] for arr in sorted( fixed_sigma_sq_sol_file.files)] self.comparison_solutions_em_sigma_sq = [ em_sigma_sq_sol_file[arr] for arr in sorted( em_sigma_sq_sol_file.files)] def tearDown(self): magni.cs.reconstruction.gamp.config.reset() def testFixedGAMPComparison(self): for ix in range(len(self.ns)): # Setup GAMP solver input_channel_params = {'tau': self.taus[ix], 'theta_bar': self.theta_bars[ix], 'theta_tilde': self.theta_tildes[ix], 'use_em': False} output_channel_params = { 'sigma_sq': self.sigma_sqs_init[ix], 'noise_level_estimation': 'fixed'} gamp_config = {'tolerance': self.tolerance, 'iterations': self.iterations, 'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params} magni.cs.reconstruction.gamp.config.update(gamp_config) # Generate problem instance z, A, alpha = use_gaussian( self.ns[ix], self.ms[ix], self.ks[ix], self.seeds[ix]) A_asq = np.abs(A)**2 if self.sigma_sqs[ix] > 0: y = z + np.random.normal( size=z.shape, loc=0.0, scale=np.sqrt(self.sigma_sqs[ix])) else: y = z # Run solver alpha_hat = magni.cs.reconstruction.gamp.run(y, A, A_asq) # Compare result self.assertTrue( np.allclose( self.comparison_solutions_fixed_sigma_sq[ix], alpha_hat.flatten())) def testEMGAMPComparison(self): for ix in range(len(self.ns)): # Setup GAMP solver input_channel_params = {'tau': self.taus[ix], 'theta_bar': self.theta_bars[ix], 'theta_tilde': self.theta_tildes[ix], 'use_em': False} output_channel_params = { 'sigma_sq': self.sigma_sqs_init[ix], 'noise_level_estimation': 'em'} gamp_config = {'tolerance': self.tolerance, 'iterations': self.iterations, 'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params} magni.cs.reconstruction.gamp.config.update(gamp_config) # Generate problem instance z, A, alpha = use_gaussian( self.ns[ix], self.ms[ix], self.ks[ix], self.seeds[ix]) A_asq = np.abs(A)**2 if self.sigma_sqs[ix] > 0: y = z + np.random.normal( size=z.shape, loc=0.0, scale=np.sqrt(self.sigma_sqs[ix])) else: y = z # Run solver alpha_hat = magni.cs.reconstruction.gamp.run(y, A, A_asq) # Compare result # The difference in EM learning for AMP vs Symmetric GAMP with AWGN # output channel makes it difficult to compare the results. # Thus, we only compare the non-zeros up to atol=1e-7. self.assertTrue( np.allclose( self.comparison_solutions_em_sigma_sq[ix][:self.ks[ix]], alpha_hat.flatten()[:self.ks[ix]], atol=1e-7)) class FastOpsTests(unittest.TestCase): """ Tests of FastOp input, i.e. function based measurements and FFT dictionary. The following tests are implemented: - *test_AMP_with_DCT_FFT_vs_Separable_2D* - *test_GAMP_with_DCT_FFT_vs_Separable_2D_rangan_sum_approx* - *test_GAMP_with_DCT_FFT_vs_Separable_2D_krzakala_sum_approx* - *test_GAMP_with_DCT_Separable_full_transform_and_precision* - *test_IT_with_DCT* - *test_IT_with_DFT* - *test_IT_with_DCT_and_precision* """ def setUp(self): h = 25 w = 25 n = h * w k = 15 self.problem_dim = (h, w) # Spiral scan pattern scan_length = 0.30 * 2 * h * w num_points = 10 * int(scan_length) img_coords = magni.imaging.measurements.spiral_sample_image( h, w, scan_length, num_points, rect_area=True) self.Phi = magni.imaging.measurements.construct_measurement_matrix( img_coords, h, w) np.random.seed(6021) self.alpha_real = np.zeros((n, 1)) self.alpha_real[:k, 0] = np.random.normal(size=k, loc=2, scale=2.0) self.alpha_complex = np.zeros((n, 1), dtype=np.complex128) self.alpha_complex[:k, 0] = (np.random.randn(k) + 1j * np.random.randn(k)) self.noise = np.random.normal(size=(self.Phi.shape[0], 1), scale=0.01) magni.cs.reconstruction.it.config.update( {'iterations': 200, 'threshold': 'fixed', 'threshold_fixed': k}) magni.cs.reconstruction.gamp.config.update( {'iterations': 500, 'tolerance': 1e-6, 'input_channel_parameters': {'tau': k/n, 'theta_bar': 2.0, 'theta_tilde': 4.0, 'use_em': False}, 'output_channel_parameters': {'sigma_sq': 1.0, 'noise_level_estimation': 'median'}} ) def tearDown(self): magni.cs.reconstruction.it.config.reset() magni.cs.reconstruction.amp.config.reset() magni.cs.reconstruction.gamp.config.reset() def test_AMP_with_DCT_FFT_vs_Separable_2D(self): Psi_fft = magni.imaging.dictionaries.get_DCT(self.problem_dim) A_fft = magni.utils.matrices.MatrixCollection((self.Phi, Psi_fft)) y_fft = A_fft.dot(self.alpha_real) + self.noise iDCT_mtx = magni.imaging.dictionaries.get_DCT_transform_matrix( self.problem_dim[0]).T Psi_sep = magni.utils.matrices.Separable2DTransform(iDCT_mtx, iDCT_mtx) A_sep = magni.utils.matrices.MatrixCollection((self.Phi, Psi_sep)) y_sep = A_sep.dot(self.alpha_real) + self.noise self.assertTrue(np.allclose(y_fft, y_sep)) alpha_hat_fft = self._amp_run(y_fft, A_fft, self.alpha_real, success=True) alpha_hat_sep = self._amp_run(y_sep, A_sep, self.alpha_real, success=True) self.assertTrue(np.allclose(alpha_hat_fft, alpha_hat_sep)) def test_GAMP_with_DCT_FFT_vs_Separable_2D_rangan_sum_approx(self): Psi_fft = magni.imaging.dictionaries.get_DCT(self.problem_dim) A_fft = magni.utils.matrices.MatrixCollection((self.Phi, Psi_fft)) y_fft = A_fft.dot(self.alpha_real) + self.noise iDCT_mtx = magni.imaging.dictionaries.get_DCT_transform_matrix( self.problem_dim[0]).T Psi_sep = magni.utils.matrices.Separable2DTransform(iDCT_mtx, iDCT_mtx) A_sep = magni.utils.matrices.MatrixCollection((self.Phi, Psi_sep)) y_sep = A_sep.dot(self.alpha_real) + self.noise self.assertEqual( magni.cs.reconstruction.gamp.config['sum_approximation_constant'], {'rangan': 1.0}) self.assertTrue(np.allclose(y_fft, y_sep)) alpha_hat_fft = self._gamp_run( y_fft, A_fft, None, self.alpha_real, success=True) alpha_hat_sep = self._gamp_run( y_sep, A_sep, None, self.alpha_real, success=True) self.assertTrue(np.allclose(alpha_hat_fft, alpha_hat_sep)) def test_GAMP_with_DCT_FFT_vs_Separable_2D_krzakala_sum_approx(self): magni.cs.reconstruction.gamp.config['sum_approximation_constant'] = { 'krzakala': 1.0 / (self.problem_dim[0] * self.problem_dim[1])} Psi_fft = magni.imaging.dictionaries.get_DCT(self.problem_dim) A_fft = magni.utils.matrices.MatrixCollection((self.Phi, Psi_fft)) y_fft = A_fft.dot(self.alpha_real) + self.noise iDCT_mtx = magni.imaging.dictionaries.get_DCT_transform_matrix( self.problem_dim[0]).T Psi_sep = magni.utils.matrices.Separable2DTransform(iDCT_mtx, iDCT_mtx) A_sep = magni.utils.matrices.MatrixCollection((self.Phi, Psi_sep)) y_sep = A_sep.dot(self.alpha_real) + self.noise self.assertEqual( magni.cs.reconstruction.gamp.config['sum_approximation_constant'], {'krzakala': 1.0 / (self.problem_dim[0] * self.problem_dim[1])}) self.assertTrue(np.allclose(y_fft, y_sep)) alpha_hat_fft = self._gamp_run( y_fft, A_fft, None, self.alpha_real, success=True) alpha_hat_sep = self._gamp_run( y_sep, A_sep, None, self.alpha_real, success=True) self.assertTrue(np.allclose(alpha_hat_fft, alpha_hat_sep)) def test_GAMP_with_DCT_Separable_full_transform_and_precision(self): # Float 32 magni.cs.reconstruction.gamp.config['precision_float'] = np.float32 self.assertEqual( magni.cs.reconstruction.gamp.config['precision_float'], np.float32) iDCT_mtx = np.float32( magni.imaging.dictionaries.get_DCT_transform_matrix( self.problem_dim[0]).T) iDCT_mtx_asq = np.abs(iDCT_mtx) ** 2 Psi = magni.utils.matrices.Separable2DTransform(iDCT_mtx, iDCT_mtx) Psi_asq = magni.utils.matrices.Separable2DTransform(iDCT_mtx_asq, iDCT_mtx_asq) A = magni.utils.matrices.MatrixCollection((self.Phi, Psi)) A_asq = magni.utils.matrices.MatrixCollection((self.Phi, Psi_asq)) y = A.dot(np.float32(self.alpha_real)) + np.float32(self.noise) self.assertEqual(y.dtype, np.float32) self.assertEqual(A.T.dot(y).dtype, np.float32) self.assertEqual(A_asq.T.dot(y).dtype, np.float32) self.assertEqual(A_asq.A.dtype, (A.A**2).dtype) self.assertTrue(np.allclose(A_asq.A, A.A**2)) alpha_hat = self._gamp_run(y, A, A_asq, self.alpha_real) self.assertEqual(alpha_hat.dtype, np.float32) # Float64 magni.cs.reconstruction.gamp.config['precision_float'] = np.float64 self.assertEqual( magni.cs.reconstruction.gamp.config['precision_float'], np.float64) iDCT_mtx = np.float64( magni.imaging.dictionaries.get_DCT_transform_matrix( self.problem_dim[0]).T) iDCT_mtx_asq = np.abs(iDCT_mtx) ** 2 Psi = magni.utils.matrices.Separable2DTransform(iDCT_mtx, iDCT_mtx) Psi_asq = magni.utils.matrices.Separable2DTransform(iDCT_mtx_asq, iDCT_mtx_asq) A = magni.utils.matrices.MatrixCollection((self.Phi, Psi)) A_asq = magni.utils.matrices.MatrixCollection((self.Phi, Psi_asq)) y = A.dot(np.float64(self.alpha_real)) + np.float64(self.noise) self.assertEqual(y.dtype, np.float64) self.assertEqual(A.T.dot(y).dtype, np.float64) self.assertEqual(A_asq.T.dot(y).dtype, np.float64) self.assertEqual(A_asq.A.dtype, (A.A**2).dtype) self.assertTrue(np.allclose(A_asq.A, A.A**2)) alpha_hat = self._gamp_run(y, A, A_asq, self.alpha_real) self.assertEqual(alpha_hat.dtype, np.float64) # Float128 if not hasattr(np, 'float128'): return magni.cs.reconstruction.gamp.config['precision_float'] = np.float128 self.assertEqual( magni.cs.reconstruction.gamp.config['precision_float'], np.float128) iDCT_mtx = np.float128( magni.imaging.dictionaries.get_DCT_transform_matrix( self.problem_dim[0]).T) iDCT_mtx_asq = np.abs(iDCT_mtx) ** 2 Psi = magni.utils.matrices.Separable2DTransform(iDCT_mtx, iDCT_mtx) Psi_asq = magni.utils.matrices.Separable2DTransform(iDCT_mtx_asq, iDCT_mtx_asq) A = magni.utils.matrices.MatrixCollection((self.Phi, Psi)) A_asq = magni.utils.matrices.MatrixCollection((self.Phi, Psi_asq)) y = A.dot(np.float128(self.alpha_real)) + np.float64(self.noise) self.assertEqual(y.dtype, np.float128) self.assertEqual(A.T.dot(y).dtype, np.float128) self.assertEqual(A_asq.T.dot(y).dtype, np.float128) self.assertEqual(A_asq.A.dtype, (A.A**2).dtype) self.assertTrue(np.allclose(A_asq.A, A.A**2)) alpha_hat = self._gamp_run(y, A, A_asq, self.alpha_real) self.assertEqual(alpha_hat.dtype, np.float128) def test_IT_with_DCT_and_precision(self): Psi = magni.imaging.dictionaries.get_DCT(self.problem_dim) A = magni.utils.matrices.MatrixCollection((self.Phi, Psi)) # Float 32 magni.cs.reconstruction.it.config.update( {'precision_float': np.float32}) self.assertEqual( magni.cs.reconstruction.it.config['precision_float'], np.float32) y = A.dot(np.float32(self.alpha_real)) self.assertEqual(y.dtype, np.float32) self.assertEqual(A.T.dot(y).dtype, np.float32) alpha_hat = self._iht_run(y, A, self.alpha_real) self.assertEqual(alpha_hat.dtype, np.float32) alpha_hat = self._ist_run(y, A, self.alpha_real) self.assertEqual(alpha_hat.dtype, np.float32) # Float 64 magni.cs.reconstruction.it.config.update( {'precision_float': np.float64}) self.assertEqual( magni.cs.reconstruction.it.config['precision_float'], np.float64) y = A.dot(np.float64(self.alpha_real)) self.assertEqual(y.dtype, np.float64) self.assertEqual(A.T.dot(y).dtype, np.float64) alpha_hat = self._iht_run(y, A, self.alpha_real) self.assertEqual(alpha_hat.dtype, np.float64) alpha_hat = self._ist_run(y, A, self.alpha_real) self.assertEqual(alpha_hat.dtype, np.float64) # Scipy DCT does not support float128 def test_IT_with_DCT(self): Psi = magni.imaging.dictionaries.get_DCT(self.problem_dim) A = magni.utils.matrices.MatrixCollection((self.Phi, Psi)) y = A.dot(self.alpha_real) self._iht_run(y, A, self.alpha_real) self._ist_run(y, A, self.alpha_real) def test_IT_with_DFT(self): Psi = magni.imaging.dictionaries.get_DFT(self.problem_dim) A = magni.utils.matrices.MatrixCollection((self.Phi, Psi)) y_real = A.dot(self.alpha_real) y_complex = A.dot(self.alpha_complex) self._iht_run(y_real, A, self.alpha_real) self._ist_run(y_real, A, self.alpha_real) self._iht_run(y_complex, A, self.alpha_complex) self._ist_run(y_complex, A, self.alpha_complex) def _amp_run(self, y, A, a, success=True): threshold_params = { 'theta': magni.cs.reconstruction.amp.util.theta_mm( float(A.shape[0]) / A.shape[1]), 'tau_hat_sq': 1.0, 'threshold_level_update_method': 'residual'} magni.cs.reconstruction.amp.config['threshold_parameters'].update( threshold_params) a_hat = magni.cs.reconstruction.amp.run(y, A) if success: self.assertTrue(np.allclose(a_hat, a, atol=1e-1)) else: self.assertFalse(np.allclose(a_hat, a, atol=1e-1)) return a_hat def _gamp_run(self, y, F, F_sq, a, success=True): a_hat = magni.cs.reconstruction.gamp.run(y, F, F_sq) if success: self.assertTrue(np.allclose(a_hat, a, atol=1e-1)) else: self.assertFalse(np.allclose(a_hat, a, atol=1e-1)) return a_hat def _iht_run(self, y, A, alpha, success=True): iht_config = {'threshold_operator': 'hard'} magni.cs.reconstruction.it.config.update(iht_config) self.assertEqual( magni.cs.reconstruction.it.config['threshold_operator'], 'hard') alpha_hat = magni.cs.reconstruction.it.run(y, A) if success: self.assertTrue(np.allclose(alpha_hat, alpha, atol=1e-2)) else: self.assertFalse(np.allclose(alpha_hat, alpha, atol=1e-2)) return alpha_hat def _ist_run(self, y, A, alpha, success=True): ist_config = {'threshold_operator': 'soft'} magni.cs.reconstruction.it.config.update(ist_config) self.assertEqual( magni.cs.reconstruction.it.config['threshold_operator'], 'soft') alpha_hat = magni.cs.reconstruction.it.run(y, A) if success: self.assertTrue(np.allclose(alpha_hat, alpha, atol=1e-2)) else: self.assertFalse(np.allclose(alpha_hat, alpha, atol=1e-2)) return alpha_hat class FeatureTest(object): """ Reconstruction algorithm feature test base class. This class defines a reconstruction problem which may be used as the base for testing features of reconstruction algorithms such as warm start or different stop criteria. See the individual feature test classes for further information. """ def setUp(self): seed = 6021 n = 500 delta = 0.78 rho = 0.17 m = int(delta * n) self.k = int(rho * m) self.tau = delta * rho self.y, self.A, self.alpha = use_rademacher(n, m, self.k, seed=seed) self.oracle_support = self.alpha != 0 self.z, self.F, self.a = use_gaussian(n, m, self.k, seed=seed) self.F_sq = self.F**2 magni.cs.reconstruction.it.config.update(iterations=200) magni.cs.reconstruction.gamp.config.update(iterations=200) def tearDown(self): magni.cs.reconstruction.it.config.reset() magni.cs.reconstruction.amp.config.reset() magni.cs.reconstruction.gamp.config.reset() def _amp_run(self, y, A, a, success=True): threshold_params = { 'theta': magni.cs.reconstruction.amp.util.theta_mm( float(A.shape[0]) / A.shape[1]), 'tau_hat_sq': 1.0, 'threshold_level_update_method': 'residual'} magni.cs.reconstruction.amp.config['threshold_parameters'].update( threshold_params) a_hat = magni.cs.reconstruction.amp.run(y, A) if success: self.assertTrue(np.allclose(a_hat, a, atol=1e-2)) else: self.assertFalse(np.allclose(a_hat, a, atol=1e-2)) return a_hat def _amp_history_run(self, y, A, a, success=True): threshold_params = { 'theta': magni.cs.reconstruction.amp.util.theta_mm( float(A.shape[0]) / A.shape[1]), 'tau_hat_sq': 1.0, 'threshold_level_update_method': 'residual'} magni.cs.reconstruction.amp.config['threshold_parameters'].update( threshold_params) a_hat, history = magni.cs.reconstruction.amp.run(y, A) if success: self.assertTrue(np.allclose(a_hat, a, atol=1e-2)) else: self.assertFalse(np.allclose(a_hat, a, atol=1e-2)) return history def _gamp_run(self, z, F, F_sq, a, success=True): a_hat = magni.cs.reconstruction.gamp.run(z, F, F_sq) if success: self.assertTrue(np.allclose(a_hat, a, atol=1e-2)) else: self.assertFalse(np.allclose(a_hat, a, atol=1e-2)) return a_hat def _gamp_history_run(self, z, F, F_sq, a, success=True): a_hat, history = magni.cs.reconstruction.gamp.run(z, F, F_sq) if success: self.assertTrue(np.allclose(a_hat, a, atol=1e-2)) else: self.assertFalse(np.allclose(a_hat, a, atol=1e-2)) return history def _iht_run(self, y, A, alpha, success=True): iht_config = {'threshold_operator': 'hard'} magni.cs.reconstruction.it.config.update(iht_config) self.assertEqual( magni.cs.reconstruction.it.config['threshold_operator'], 'hard') alpha_hat = magni.cs.reconstruction.it.run(y, A) if success: self.assertTrue(np.allclose(alpha_hat, alpha, atol=1e-2)) else: self.assertFalse(np.allclose(alpha_hat, alpha, atol=1e-2)) return alpha_hat def _ist_run(self, y, A, alpha, success=True): ist_config = {'threshold_operator': 'soft'} magni.cs.reconstruction.it.config.update(ist_config) self.assertEqual( magni.cs.reconstruction.it.config['threshold_operator'], 'soft') alpha_hat = magni.cs.reconstruction.it.run(y, A) if success: self.assertTrue(np.allclose(alpha_hat, alpha, atol=1e-2)) else: self.assertFalse(np.allclose(alpha_hat, alpha, atol=1e-2)) return alpha_hat def _ist_history_run(self, y, A, alpha, success=True): ist_config = {'threshold_operator': 'soft'} magni.cs.reconstruction.it.config.update(ist_config) self.assertEqual( magni.cs.reconstruction.it.config['threshold_operator'], 'soft') alpha_hat, history = magni.cs.reconstruction.it.run(y, A) if success: self.assertTrue(np.allclose(alpha_hat, alpha, atol=1e-2)) else: self.assertFalse(np.allclose(alpha_hat, alpha, atol=1e-2)) return history class FeaturePrecisionFloatTest(FeatureTest, unittest.TestCase): """ Test of the precision float feature in reconstruction algorithms. The following tests are implemented: - *test_float32_AMP* - *test_float32_GAMP* - *test_float32_GAMP_EM* - *test_float32_GAMP_EM_BL* - *test_float64_AMP* - *test_float64_GAMP* - *test_float64_GAMP_EM* - *test_float64_GAMP_EM_BL* - *test_float128_AMP* - *test_float128_GAMP* - *test_float128_GAMP_EM* - *test_float128_GAMP_EM_BL* - *test_float32_IST* - *test_float64_IST* - *test_float128_IST* """ def test_float32_AMP(self, success=True): magni.cs.reconstruction.amp.config['precision_float'] = np.float32 self.y = np.float32(self.y) self.A = np.float32(self.A) self.assertEqual( magni.cs.reconstruction.amp.config['precision_float'], np.float32) a_hat = self._amp_run(self.y, self.A, self.alpha, success=success) self.assertEqual(a_hat.dtype, np.float32) def test_float32_GAMP(self, success=True): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'sample_variance'} sc = magni.cs.reconstruction.gamp.stop_criterion magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'stop_criterion': sc.Residual, 'precision_float': np.float32}) self.z = np.float32(self.z) self.F = np.float32(self.F) self.F_sq = np.float32(self.F_sq) self.assertEqual( magni.cs.reconstruction.gamp.config['precision_float'], np.float32) a_hat = self._gamp_run( self.z, self.F, self.F_sq, self.a, success=success) self.assertEqual(a_hat.dtype, np.float32) def test_float32_GAMP_EM(self, success=True): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': True} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'em'} sc = magni.cs.reconstruction.gamp.stop_criterion magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'stop_criterion': sc.Residual, 'precision_float': np.float32}) self.z = np.float32(self.z) self.F = np.float32(self.F) self.F_sq = np.float32(self.F_sq) self.assertEqual( magni.cs.reconstruction.gamp.config['precision_float'], np.float32) a_hat = self._gamp_run( self.z, self.F, self.F_sq, self.a, success=success) self.assertEqual(a_hat.dtype, np.float32) def test_float32_GAMP_EM_BL(self, success=True): input_channel_params = { 'tau': self.tau, 'weights': np.ones_like(self.alpha), 'phi_channel': magni.cs.reconstruction.gamp.input_channel.IIDL, 'phi_channel_parameters': {'mu': 0, 'b': 1, 'use_em': True}, 'use_em': True} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'em'} sc = magni.cs.reconstruction.gamp.stop_criterion magni.cs.reconstruction.gamp.config.update( {'input_channel': magni.cs.reconstruction.gamp.input_channel.GWS, 'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'stop_criterion': sc.Residual, 'precision_float': np.float32}) self.z = np.float32(self.z) self.F = np.float32(self.F) self.F_sq = np.float32(self.F_sq) self.assertEqual( magni.cs.reconstruction.gamp.config['precision_float'], np.float32) a_hat = self._gamp_run( self.z, self.F, self.F_sq, self.a, success=success) self.assertEqual(a_hat.dtype, np.float32) def test_float64_AMP(self, success=True): magni.cs.reconstruction.amp.config['precision_float'] = np.float64 self.y = np.float64(self.y) self.A = np.float64(self.A) self.assertEqual( magni.cs.reconstruction.amp.config['precision_float'], np.float64) a_hat = self._amp_run(self.y, self.A, self.alpha, success=success) self.assertEqual(a_hat.dtype, np.float64) def test_float64_GAMP(self, success=True): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'sample_variance'} sc = magni.cs.reconstruction.gamp.stop_criterion magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'stop_criterion': sc.Residual, 'precision_float': np.float64}) self.z = np.float64(self.z) self.F = np.float64(self.F) self.F_sq = np.float64(self.F_sq) self.assertEqual( magni.cs.reconstruction.gamp.config['precision_float'], np.float64) a_hat = self._gamp_run( self.z, self.F, self.F_sq, self.a, success=success) self.assertEqual(a_hat.dtype, np.float64) def test_float64_GAMP_EM(self, success=True): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': True} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'em'} sc = magni.cs.reconstruction.gamp.stop_criterion magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'stop_criterion': sc.Residual, 'precision_float': np.float64}) self.z = np.float64(self.z) self.F = np.float64(self.F) self.F_sq = np.float64(self.F_sq) self.assertEqual( magni.cs.reconstruction.gamp.config['precision_float'], np.float64) a_hat = self._gamp_run( self.z, self.F, self.F_sq, self.a, success=success) self.assertEqual(a_hat.dtype, np.float64) def test_float64_GAMP_EM_BL(self, success=True): input_channel_params = { 'tau': self.tau, 'weights': np.ones_like(self.alpha), 'phi_channel': magni.cs.reconstruction.gamp.input_channel.IIDL, 'phi_channel_parameters': {'mu': 0, 'b': 1, 'use_em': True}, 'use_em': True} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'em'} sc = magni.cs.reconstruction.gamp.stop_criterion magni.cs.reconstruction.gamp.config.update( {'input_channel': magni.cs.reconstruction.gamp.input_channel.GWS, 'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'stop_criterion': sc.Residual, 'precision_float': np.float64}) self.z = np.float64(self.z) self.F = np.float64(self.F) self.F_sq = np.float64(self.F_sq) self.assertEqual( magni.cs.reconstruction.gamp.config['precision_float'], np.float64) a_hat = self._gamp_run( self.z, self.F, self.F_sq, self.a, success=success) self.assertEqual(a_hat.dtype, np.float64) @unittest.skipIf(not hasattr(np, 'float128'), 'precision is not available') def test_float128_AMP(self, success=True): magni.cs.reconstruction.amp.config['precision_float'] = np.float128 self.y = np.float128(self.y) self.A = np.float128(self.A) self.assertEqual( magni.cs.reconstruction.amp.config['precision_float'], np.float128) a_hat = self._amp_run(self.y, self.A, self.alpha, success=success) self.assertEqual(a_hat.dtype, np.float128) @unittest.skipIf(not hasattr(np, 'float128'), 'precision is not available') def test_float128_GAMP(self, success=True): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'sample_variance'} sc = magni.cs.reconstruction.gamp.stop_criterion magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'stop_criterion': sc.Residual, 'precision_float': np.float128}) self.z = np.float128(self.z) self.F = np.float128(self.F) self.F_sq = np.float128(self.F_sq) self.assertEqual( magni.cs.reconstruction.gamp.config['precision_float'], np.float128) a_hat = self._gamp_run( self.z, self.F, self.F_sq, self.a, success=success) self.assertEqual(a_hat.dtype, np.float128) @unittest.skipIf(not hasattr(np, 'float128'), 'precision is not available') def test_float128_GAMP_EM(self, success=True): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': True} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'em'} sc = magni.cs.reconstruction.gamp.stop_criterion magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'stop_criterion': sc.Residual, 'precision_float': np.float128}) self.z = np.float128(self.z) self.F = np.float128(self.F) self.F_sq = np.float128(self.F_sq) self.assertEqual( magni.cs.reconstruction.gamp.config['precision_float'], np.float128) a_hat = self._gamp_run( self.z, self.F, self.F_sq, self.a, success=success) self.assertEqual(a_hat.dtype, np.float128) @unittest.skipIf(not hasattr(np, 'float128'), 'precision is not available') def test_float128_GAMP_EM_BL(self, success=True): input_channel_params = { 'tau': self.tau, 'weights': np.ones_like(self.alpha), 'phi_channel': magni.cs.reconstruction.gamp.input_channel.IIDL, 'phi_channel_parameters': {'mu': 0, 'b': 1, 'use_em': True}, 'use_em': True} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'em'} sc = magni.cs.reconstruction.gamp.stop_criterion magni.cs.reconstruction.gamp.config.update( {'input_channel': magni.cs.reconstruction.gamp.input_channel.GWS, 'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'stop_criterion': sc.Residual, 'precision_float': np.float128}) self.z = np.float128(self.z) self.F = np.float128(self.F) self.F_sq = np.float128(self.F_sq) self.assertEqual( magni.cs.reconstruction.gamp.config['precision_float'], np.float128) a_hat = self._gamp_run( self.z, self.F, self.F_sq, self.a, success=success) self.assertEqual(a_hat.dtype, np.float128) def test_float32_IST(self, success=True): magni.cs.reconstruction.it.config.update( {'precision_float': np.float32}) self.A = np.float32(self.A) self.y = np.float32(self.y) self.assertEqual( magni.cs.reconstruction.it.config['precision_float'], np.float32) alpha_hat = self._ist_run(self.y, self.A, self.alpha, success=success) self.assertEqual(alpha_hat.dtype, np.float32) def test_float64_IST(self, success=True): magni.cs.reconstruction.it.config.update( {'precision_float': np.float64}) self.A = np.float64(self.A) self.y = np.float64(self.y) self.assertEqual( magni.cs.reconstruction.it.config['precision_float'], np.float64) alpha_hat = self._ist_run(self.y, self.A, self.alpha, success=success) self.assertEqual(alpha_hat.dtype, np.float64) @unittest.skipIf(not hasattr(np, 'float128'), 'precision is not available') def test_float128_IST(self, success=True): magni.cs.reconstruction.it.config.update( {'precision_float': np.float128}) self.A = np.float128(self.A) self.y = np.float128(self.y) self.assertEqual( magni.cs.reconstruction.it.config['precision_float'], np.float128) alpha_hat = self._ist_run(self.y, self.A, self.alpha, success=success) self.assertEqual(alpha_hat.dtype, np.float128) class FeatureReportHistoryTest(FeatureTest, unittest.TestCase): """ Test the report history feature in reconstruction algorithms. The following tests are implemented: - *test_MSE_CONVERGENCE_AMP* (stop based on MSE) - *test_MAX_INTERATIONS_AMP* (stop based on max iterations) - *test_MSE_CONVERGENCE_GAMP* (stop based on MSE) - *test_MAX_INTERATIONS_GAMP* (stop based on max iterations) - *test_MSE_CONVERGENCE_IST* (stop based on MSE) - *test_MAX_INTERATIONS_IST* (stop based on max iterations) """ def test_MSE_CONVERGENCE_AMP(self, success=True): magni.cs.reconstruction.amp.config.update( {'report_history': True, 'true_solution': self.alpha}) history = self._amp_history_run(self.y, self.A, self.alpha, success=success) self.assertEqual(history['stop_criterion'], 'MSECONVERGENCE') self.assertEqual(history['stop_reason'], 'MSECONVERGENCE') self.assertEqual(history['stop_iteration'], 31) self.assertEqual(len(history['MSE']), 33) self.assertEqual(len(history['threshold_parameters']), 33) self.assertEqual(len(history['alpha_bar']), 33) self.assertEqual(len(history['stop_criterion_value']), 33) def test_MAX_ITERATION_AMP(self, success=False): magni.cs.reconstruction.amp.config.update( {'report_history': True, 'iterations': 8}) history = self._amp_history_run(self.y, self.A, self.alpha, success=success) self.assertEqual(history['stop_criterion'], 'MSECONVERGENCE') self.assertEqual(history['stop_reason'], 'MAX_ITERATIONS') self.assertEqual(history['stop_iteration'], 7) self.assertEqual(len(history['MSE']), 1) self.assertEqual(len(history['threshold_parameters']), 9) self.assertEqual(len(history['alpha_bar']), 9) self.assertEqual(len(history['stop_criterion_value']), 9) def test_MSE_CONVERGENCE_GAMP(self, success=True): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'sample_variance'} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'report_history': True, 'true_solution': self.a}) history = self._gamp_history_run( self.z, self.F, self.F_sq, self.a, success=success) self.assertEqual(history['stop_criterion'], 'MSECONVERGENCE') self.assertEqual(history['stop_reason'], 'MSECONVERGENCE') self.assertEqual(history['stop_iteration'], 10) self.assertEqual(len(history['MSE']), 12) self.assertEqual(len(history['input_channel_parameters']), 12) self.assertEqual(len(history['output_channel_parameters']), 12) self.assertEqual(len(history['alpha_bar']), 12) self.assertEqual(len(history['alpha_tilde']), 12) self.assertEqual(len(history['stop_criterion_value']), 12) def test_MAX_ITERATIONS_GAMP(self, success=False): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'sample_variance'} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'report_history': True, 'iterations': 8}) history = self._gamp_history_run( self.z, self.F, self.F_sq, self.a, success=success) self.assertEqual(history['stop_criterion'], 'MSECONVERGENCE') self.assertEqual(history['stop_reason'], 'MAX_ITERATIONS') self.assertEqual(history['stop_iteration'], 7) self.assertEqual(len(history['MSE']), 1) self.assertEqual(len(history['output_channel_parameters']), 9) self.assertEqual(len(history['output_channel_parameters']), 9) self.assertEqual(len(history['alpha_bar']), 9) self.assertEqual(len(history['alpha_tilde']), 9) self.assertEqual(len(history['stop_criterion_value']), 9) def test_MSE_CONVERGENCE_IST(self, success=True): magni.cs.reconstruction.it.config.update( {'report_history': True, 'stop_criterion': 'mse_convergence', 'true_solution': self.alpha}) history = self._ist_history_run( self.y, self.A, self.alpha, success=False) self.assertEqual(history['stop_criterion'], 'MSE_CONVERGENCE') self.assertEqual(history['stop_reason'], 'MSE_CONVERGENCE') self.assertEqual(history['stop_iteration'], 5) self.assertEqual(len(history['MSE']), 7) self.assertEqual(len(history['alpha']), 7) self.assertEqual(len(history['stop_criterion_value']), 7) def test_MAX_ITERATIONS_IST(self, success=False): magni.cs.reconstruction.it.config.update( {'report_history': True, 'stop_criterion': 'mse_convergence', 'iterations': 2}) history = self._ist_history_run( self.y, self.A, self.alpha, success=False) self.assertEqual(history['stop_criterion'], 'MSE_CONVERGENCE') self.assertEqual(history['stop_reason'], 'MAX_ITERATIONS') self.assertEqual(history['stop_iteration'], 1) self.assertEqual(len(history['MSE']), 1) self.assertEqual(len(history['alpha']), 3) self.assertEqual(len(history['stop_criterion_value']), 3) class FeatureStopCriterionTest(FeatureTest, unittest.TestCase): """ Test of the stop criterion feature in reconstruction algorithms. The following tests are implemented: - *test_AMP_stop_criterion_error_handling - *test_residual_AMP* (stop based on residual) - *test_residual_measurements_ratio_AMP* (stop based on ratio of measurements to residual) - *test_normalised_MSE_convergence_AMP* (stop based on NMSE) - *test_GAMP_stop_criterion_error_handling - *test_residual_GAMP* (stop based on residual) - *test_residual_measurements_ratio_GAMP* (stop based on ratio of measurements to residual) - *test_normalised_MSE_convergence_GAMP* (stop based on NMSE) - *test_residual_IST* (stop based on residual) - *test_residual_measurements_ratio_IST* (stop based on ratio of measurements to residual) - *test_normalised_mse_IST* stop based on NMSE) """ def test_AMP_stop_criterion_error_handling(self): sc = magni.cs.reconstruction.amp.stop_criterion with self.assertRaises(TypeError): sc.ValidatedStopCriterion('fail') with self.assertRaises(TypeError): sc.ValidatedStopCriterion({})('fail') with self.assertRaises(TypeError): sc.NormalisedMSEConvergence('fail') with self.assertRaises(TypeError): sc.NormalisedMSEConvergence({'tolerance': 1e-3})('fail') def test_residual_AMP(self, success=True): sc = magni.cs.reconstruction.amp.stop_criterion magni.cs.reconstruction.amp.config.update( {'stop_criterion': sc.Residual}) self._amp_run(self.y, self.A, self.alpha, success=success) def test_residual_measurements_ratio_AMP(self, success=True): sc = magni.cs.reconstruction.amp.stop_criterion magni.cs.reconstruction.amp.config.update( {'stop_criterion': sc.ResidualMeasurementsRatio}) self._amp_run(self.y, self.A, self.alpha, success=success) def test_normalised_MSE_convergence_AMP(self, success=True): sc = magni.cs.reconstruction.amp.stop_criterion magni.cs.reconstruction.amp.config.update( {'stop_criterion': sc.NormalisedMSEConvergence}) self._amp_run(self.y, self.A, self.alpha, success=success) def test_GAMP_stop_criterion_error_handling(self): sc = magni.cs.reconstruction.gamp.stop_criterion with self.assertRaises(TypeError): sc.ValidatedStopCriterion('fail') with self.assertRaises(TypeError): sc.ValidatedStopCriterion({})('fail') with self.assertRaises(TypeError): sc.NormalisedMSEConvergence('fail') with self.assertRaises(TypeError): sc.NormalisedMSEConvergence({'tolerance': 1e-3})('fail') def test_residual_GAMP(self, success=True): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'sample_variance'} sc = magni.cs.reconstruction.gamp.stop_criterion magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'stop_criterion': sc.Residual}) self._gamp_run(self.z, self.F, self.F_sq, self.a, success=success) def test_residual_measurements_ratio_GAMP(self, success=True): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'sample_variance'} sc = magni.cs.reconstruction.gamp.stop_criterion magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'stop_criterion': sc.ResidualMeasurementsRatio}) self._gamp_run(self.z, self.F, self.F_sq, self.a, success=success) def test_normalised_MSE_convergence_GAMP(self, success=True): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'sample_variance'} sc = magni.cs.reconstruction.gamp.stop_criterion magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'stop_criterion': sc.NormalisedMSEConvergence}) self._gamp_run(self.z, self.F, self.F_sq, self.a, success=success) def test_residual_IST(self, success=True): magni.cs.reconstruction.it.config.update( {'stop_criterion': 'residual', 'tolerance': 1e-6}) self._ist_run(self.y, self.A, self.alpha, success=success) def test_residual_measurements_ratio_IST(self, success=True): magni.cs.reconstruction.it.config.update( {'stop_criterion': 'residual_measurements_ratio', 'tolerance': 1e-6}) self._ist_run(self.y, self.A, self.alpha, success=success) def test_normalised_mse_IST(self, success=True): magni.cs.reconstruction.it.config.update( {'stop_criterion': 'normalised_mse_convergence', 'tolerance': 1e-6, 'iterations': 500}) self._ist_run(self.y, self.A, self.alpha, success=success) class FeatureWarmStartTest(FeatureTest, unittest.TestCase): """ Test of the warm_start feature in reconstruction algorithms. The following tests are implemented: - *test_warm_start_IT* (Iterative thresholding) - *test_warm_start_AMP* (Approximate Message Passing) - *test_warm_start_GAMP* (Generalised Approximate Message Passing) """ def test_warm_start_IT(self, success_iht=True, success_ist=True): it_config = {'warm_start': 0.1 * np.ones(self.alpha.shape)} magni.cs.reconstruction.it.config.update(it_config) self._iht_run(self.y, self.A, self.alpha, success=success_iht) self._ist_run(self.y, self.A, self.alpha, success=success_ist) self.assertIsNotNone( magni.cs.reconstruction.it.config['warm_start']) def test_warm_start_AMP(self, success=True): magni.cs.reconstruction.amp.config.update( {'warm_start': 0.1 * np.ones(self.a.shape)}) self._amp_run(self.y, self.A, self.alpha, success=success) def test_warm_start_GAMP(self, success=True): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'sample_variance'} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'warm_start': (0.1 * np.ones(self.a.shape), 2 * np.ones(self.a.shape))}) self._gamp_run(self.z, self.F, self.F_sq, self.a, success=success) class FeatureGAMPChannelEMTest(FeatureTest, unittest.TestCase): """ Test of GAMP Channel EM updates The following tests are implemented: - *test_IIDG_channel_EM* (EM update of pure Gauss channel) - *test_IIDL_channel_EM* (EM update of pure Laplace channel) """ def test_IIDG_channel_EM(self, success=False): IIDG = magni.cs.reconstruction.gamp.input_channel.IIDG input_channel_params = { 'theta_bar': 0, 'theta_tilde': 1, 'use_em': True} output_channel_params = { 'sigma_sq': 1, 'noise_level_estimation': 'sample_variance'} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'input_channel': IIDG}) alpha_hat_pure_G = self._gamp_run( self.z, self.F, self.F_sq, self.a, success=success) GWS = magni.cs.reconstruction.gamp.input_channel.GWS input_channel_params = { 'tau': 1, 'weights': None, 'phi_channel': IIDG, 'phi_channel_parameters': { 'theta_bar': 0, 'theta_tilde': 1, 'use_em': True}, 'use_em': True} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'input_channel': GWS}) alpha_hat_GWS_G = self._gamp_run( self.z, self.F, self.F_sq, self.a, success=success) self.assertTrue(np.allclose(alpha_hat_pure_G, alpha_hat_GWS_G)) def test_IIDL_channel_EM(self, success=False): IIDL = magni.cs.reconstruction.gamp.input_channel.IIDL input_channel_params = { 'mu': 0, 'b': 1 / np.sqrt(2), 'use_em': True} output_channel_params = { 'sigma_sq': 1, 'noise_level_estimation': 'sample_variance'} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'input_channel': IIDL}) with warnings.catch_warnings(): warnings.simplefilter('ignore') alpha_hat_pure_L = self._gamp_run( self.z, self.F, self.F_sq, self.a, success=success) GWS = magni.cs.reconstruction.gamp.input_channel.GWS input_channel_params = { 'tau': 1, 'weights': None, 'phi_channel': IIDL, 'phi_channel_parameters': { 'mu': 0, 'b': 1 / np.sqrt(2), 'use_em': True}, 'use_em': True} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'input_channel': GWS}) with warnings.catch_warnings(): warnings.simplefilter('ignore') alpha_hat_GWS_L = self._gamp_run( self.z, self.F, self.F_sq, self.a, success=success) self.assertTrue( np.allclose(alpha_hat_pure_L, alpha_hat_GWS_L, atol=1e-4)) class PhaseSpaceExtremesTest(unittest.TestCase): """ Tests of border case (extreme) phase space values. The following tests are implemented: - *test_basic_setup* (not extremum) - *test_invalid_A_and_y* (empty A and y) - *test_k_equals_zero* - *test_k_equals_m* - *test_m_equals_one* - *test_m_equals_n* - *test_m_and_n_equals_one* - *test_n_equals_one* """ def setUp(self): self.n = 500 self.m = 200 self.k = 10 self.seed = 6021 magni.cs.reconstruction.it.config.update(iterations=200) magni.cs.reconstruction.gamp.config.update(iterations=200) # GAMP setup input_channel_params = {'tau': self.k/self.n, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False} output_channel_params = {'sigma_sq': 0.5, 'noise_level_estimation': 'sample_variance'} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params}) def tearDown(self): magni.cs.reconstruction.it.config.reset() magni.cs.reconstruction.amp.config.reset() magni.cs.reconstruction.gamp.config.reset() def test_basic_setup(self): y, A, alpha = use_rademacher(self.n, self.m, self.k, seed=self.seed) A_asq = A**2 self._iht_run(y, A, alpha) self._ist_run(y, A, alpha) self._gamp_run(y, A, A_asq, alpha) def test_invalid_A_and_y(self): A = np.array([]) A_asq = np.array([]) y = np.array([]) alpha = np.array([]) with self.assertRaises(ValueError): self._iht_run(y, A, alpha) with self.assertRaises(ValueError): self._ist_run(y, A, alpha) with self.assertRaises(ValueError): self._gamp_run(y, A, A_asq, alpha) def test_k_equals_zero(self): k = 0 y, A, alpha = use_rademacher(self.n, self.m, k, seed=self.seed) A_asq = A**2 self._iht_run(y, A, alpha) self._ist_run(y, A, alpha) self._gamp_run(y, A, A_asq, alpha) def test_k_equals_m(self): k = self.m y, A, alpha = use_rademacher(self.n, self.m, k, seed=self.seed) A_asq = A**2 self._iht_run(y, A, alpha, success=False) self._ist_run(y, A, alpha, success=False) self._gamp_run(y, A, A_asq, alpha, success=False) def test_m_equals_one(self): with warnings.catch_warnings(): warnings.simplefilter('ignore') m = 1 y, A, alpha = use_rademacher(self.n, m, self.k, seed=self.seed) A_asq = A**2 self._iht_run(y, A, alpha, success=False) self._ist_run(y, A, alpha, success=False) self._gamp_run(y, A, A_asq, alpha, success=False) def test_m_equals_n(self): m = self.n y, A, alpha = use_rademacher(self.n, m, self.k, seed=self.seed) A_asq = A**2 self._iht_run(y, A, alpha) self._ist_run(y, A, alpha) self._gamp_run(y, A, A_asq, alpha) def test_m_and_n_equals_one(self): n = 1 m = 1 k = 1 y, A, alpha = use_rademacher(n, m, k, seed=self.seed) A_asq = A**2 self._iht_run(y, A, alpha, success=False) self._ist_run(y, A, alpha, success=False) self._gamp_run(y, A, A_asq, alpha, success=False) def test_n_equals_one(self): n = 1 k = 1 y, A, alpha = use_rademacher(n, self.m, k, seed=self.seed) A_asq = A**2 self._iht_run(y, A, alpha) with warnings.catch_warnings(): warnings.simplefilter('ignore') self._ist_run(y, A, alpha, success=False) self._gamp_run(y, A, A_asq, alpha) def _gamp_run(self, z, F, F_sq, a, success=True): a_hat = magni.cs.reconstruction.gamp.run(z, F, F_sq) if success: self.assertTrue(np.allclose(a_hat, a, atol=1e-2)) else: self.assertFalse(np.allclose(a_hat, a, atol=1e-2)) def _iht_run(self, y, A, alpha, success=True): self.assertEqual( magni.cs.reconstruction.it.config['threshold_operator'], 'hard') alpha_hat = magni.cs.reconstruction.it.run(y, A) if success: self.assertTrue(np.allclose(alpha_hat, alpha, atol=1e-2)) else: self.assertFalse(np.allclose(alpha_hat, alpha, atol=1e-2)) def _ist_run(self, y, A, alpha, success=True): ist_config = {'threshold_operator': 'soft'} magni.cs.reconstruction.it.config.update(ist_config) self.assertEqual( magni.cs.reconstruction.it.config['threshold_operator'], 'soft') alpha_hat = magni.cs.reconstruction.it.run(y, A) if success: self.assertTrue(np.allclose(alpha_hat, alpha, atol=1e-2)) else: self.assertFalse(np.allclose(alpha_hat, alpha, atol=1e-2)) class PhaseSpaceTest(object): """ Phase space test base class. The following tests are implemented: - *test_default_IT* (default configuration) - *test_fixed_IT* (fixed threshold) - *test_adaptive_fixed_IT* (adaptive step-size, fixed threshold) - *test_weighted_fixed_IT* (weighted, fixed threshold) - *test_residual_soft_threshold_AMP* (soft threshold, residual level) - *test_median_soft_threshold_AMP* (soft threshold, median level) - *test_iidsGB_AWGN_GAMP* (s-GB) - *test_iidsGB_AWGN_EM_GAMP* (s-GB with EM learning) - *test_iidBL_AWGN_GAMP* (BL) - *test_iidBL_AWGN_EM_GAMP* (BL with EM learning) - *test_iidBG_AWGN_GAMP* (MMSE GAMP) - *test_iidBG_AWGN_EM_GAMP* (MMSE GAMP with EM learning) - *test_iidBG_AWGN_GAMP_rangan_sum_approx* (rangan sum approx GAMP) - *test_iidBG_AWGN_GAMP_krzakala_sum_approx* (krzakala sum approx GAMP) """ def setUp(self, n=None, delta=None, rho=None, seed=6021): m = int(delta * n) self.k = int(rho * m) self.tau = delta * rho self.y, self.A, self.alpha = use_rademacher(n, m, self.k, seed=seed) self.oracle_support = self.alpha != 0 self.z, self.F, self.a = use_gaussian(n, m, self.k, seed=seed) self.F_sq = self.F**2 magni.cs.reconstruction.it.config.update(iterations=200) magni.cs.reconstruction.gamp.config.update(iterations=200) def tearDown(self): magni.cs.reconstruction.it.config.reset() magni.cs.reconstruction.amp.config.reset() magni.cs.reconstruction.gamp.config.reset() def test_residual_soft_threshold_AMP(self, success=True): magni.cs.reconstruction.amp.config['threshold_parameters'] = { 'threshold_level_update_method': 'residual'} self._amp_run(self.y, self.A, self.alpha, success=success) def test_median_soft_threshold_AMP(self, success=True): magni.cs.reconstruction.amp.config['threshold_parameters'] = { 'threshold_level_update_method': 'median'} self._amp_run(self.y, self.A, self.alpha, success=success) def test_iidsGB_AWGN_GAMP(self, success=True): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'sample_variance'} IIDsGB = magni.cs.reconstruction.gamp.input_channel.IIDsGB magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'input_channel': IIDsGB}) self._gamp_run(self.z, self.F, self.F_sq, self.a, success=success) def test_iidsGB_AWGN_EM_GAMP(self, success=True): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': True, 'em_damping': 0.5} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'em'} IIDsGB = magni.cs.reconstruction.gamp.input_channel.IIDsGB magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'input_channel': IIDsGB}) with warnings.catch_warnings(): warnings.simplefilter('ignore') self._gamp_run(self.z, self.F, self.F_sq, self.a, success=success) def test_iidBL_AWGN_GAMP(self, success=True): GWS = magni.cs.reconstruction.gamp.input_channel.GWS IIDL = magni.cs.reconstruction.gamp.input_channel.IIDL input_channel_params = { 'tau': self.tau, 'weights': None, 'phi_channel': IIDL, 'phi_channel_parameters': { 'mu': 0, 'b': 1 / np.sqrt(2), 'use_em': False}, 'use_em': False} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'sample_variance'} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'input_channel': GWS}) with warnings.catch_warnings(): warnings.simplefilter('ignore') self._gamp_run(self.z, self.F, self.F_sq, self.a, success=success) def test_iidBL_AWGN_EM_GAMP(self, success=True): GWS = magni.cs.reconstruction.gamp.input_channel.GWS IIDL = magni.cs.reconstruction.gamp.input_channel.IIDL input_channel_params = { 'tau': self.tau, 'weights': None, 'phi_channel': IIDL, 'phi_channel_parameters': { 'mu': 0, 'b': 1 / np.sqrt(2), 'use_em': True}, 'use_em': True} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'em'} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'input_channel': GWS}) with warnings.catch_warnings(): warnings.simplefilter('ignore') self._gamp_run(self.z, self.F, self.F_sq, self.a, success=success) def test_iidBG_AWGN_GAMP(self, success=True): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'sample_variance'} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params}) self._gamp_run(self.z, self.F, self.F_sq, self.a, success=success) def test_iidBG_AWGN_EM_GAMP(self, success=True): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': True} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'em'} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params}) self._gamp_run(self.z, self.F, self.F_sq, self.a, success=success) def test_iidBG_AWGN_GAMP_rangan_sum_approx(self, success=True): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'sample_variance'} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params}) self.assertEqual( magni.cs.reconstruction.gamp.config['sum_approximation_constant'], {'rangan': 1.0}) self._gamp_run(self.z, self.F, None, self.a, success=success) def test_iidBG_AWGN_GAMP_krzakala_sum_approx(self, success=True): input_channel_params = {'tau': self.tau, 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'sample_variance'} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'sum_approximation_constant': {'krzakala': 1.0 / self.F.shape[0]}} ) self.assertEqual( magni.cs.reconstruction.gamp.config['sum_approximation_constant'], {'krzakala': 1.0 / self.F.shape[0]}) self._gamp_run(self.z, self.F, None, self.a, success=success) def test_iidwBG_ones_AWGN_GAMP(self, success=True): GWS = magni.cs.reconstruction.gamp.input_channel.GWS IIDG = magni.cs.reconstruction.gamp.input_channel.IIDG input_channel_params = { 'tau': self.tau, 'weights': np.ones_like(self.a), 'phi_channel': IIDG, 'phi_channel_parameters': { 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False}, 'use_em': False} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'em'} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'input_channel': GWS}) self._gamp_run(self.z, self.F, self.F_sq, self.a, success=success) def test_iidwBG_ones_AWGN_EM_GAMP(self, success=True): GWS = magni.cs.reconstruction.gamp.input_channel.GWS IIDG = magni.cs.reconstruction.gamp.input_channel.IIDG input_channel_params = { 'tau': self.tau, 'weights': np.ones_like(self.a), 'phi_channel': IIDG, 'phi_channel_parameters': { 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False}, 'use_em': True} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'em'} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'input_channel': GWS}) self._gamp_run(self.z, self.F, self.F_sq, self.a, success=success) def test_iidwBG_linspace_AWGN_GAMP(self, success=True): GWS = magni.cs.reconstruction.gamp.input_channel.GWS IIDG = magni.cs.reconstruction.gamp.input_channel.IIDG input_channel_params = { 'tau': self.tau, 'weights': np.linspace(0.1, 0.9, len(self.a)).reshape(-1, 1), 'phi_channel': IIDG, 'phi_channel_parameters': { 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False}, 'use_em': False} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'em'} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'input_channel': GWS}) self._gamp_run(self.z, self.F, self.F_sq, self.a, success=success) def test_iidwBG_linspace_AWGN_EM_truncate_GAMP(self, success=True): GWS = magni.cs.reconstruction.gamp.input_channel.GWS IIDG = magni.cs.reconstruction.gamp.input_channel.IIDG input_channel_params = { 'tau': self.tau, 'weights': np.linspace(0.1, 0.9, len(self.a)).reshape(-1, 1), 'phi_channel': IIDG, 'phi_channel_parameters': { 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False}, 'use_em': True, 'adjust_tau_method': 'truncate'} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'em'} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'input_channel': GWS}) self._gamp_run(self.z, self.F, self.F_sq, self.a, success=success) def test_iidwBG_linspace_AWGN_EM_reweight_GAMP(self, success=True): GWS = magni.cs.reconstruction.gamp.input_channel.GWS IIDG = magni.cs.reconstruction.gamp.input_channel.IIDG input_channel_params = { 'tau': self.tau, 'weights': np.linspace(0.1, 0.9, len(self.a)).reshape(-1, 1), 'phi_channel': IIDG, 'phi_channel_parameters': { 'theta_bar': 0, 'theta_tilde': 1, 'use_em': False}, 'use_em': True, 'adjust_tau_method': 'reweight'} output_channel_params = {'sigma_sq': 1, 'noise_level_estimation': 'em'} magni.cs.reconstruction.gamp.config.update( {'input_channel_parameters': input_channel_params, 'output_channel_parameters': output_channel_params, 'input_channel': GWS}) self._gamp_run(self.z, self.F, self.F_sq, self.a, success=success) def test_default_IT(self, success_iht=True, success_ist=True): self._iht_run(self.y, self.A, self.alpha, success=success_iht) self._ist_run(self.y, self.A, self.alpha, success=success_ist) def test_fixed_IT(self, success_iht=True, success_ist=True): it_config = {'threshold': 'fixed', 'threshold_fixed': self.k} magni.cs.reconstruction.it.config.update(it_config) self._iht_run(self.y, self.A, self.alpha, success=success_iht) self._ist_run(self.y, self.A, self.alpha, success=success_ist) self.assertEqual(magni.cs.reconstruction.it.config['threshold'], 'fixed') self.assertEqual(magni.cs.reconstruction.it.config['threshold_fixed'], self.k) def test_adaptive_fixed_IT(self, success_iht=True, success_ist=True): it_config = {'threshold': 'fixed', 'threshold_fixed': self.k, 'kappa': 'adaptive'} magni.cs.reconstruction.it.config.update(it_config) self._iht_run(self.y, self.A, self.alpha, success=success_iht) self._ist_run(self.y, self.A, self.alpha, success=success_ist) self.assertEqual(magni.cs.reconstruction.it.config['threshold'], 'fixed') self.assertEqual(magni.cs.reconstruction.it.config['threshold_fixed'], self.k) self.assertEqual(magni.cs.reconstruction.it.config['kappa'], 'adaptive') def test_weighted_fixed_IT(self, success_iht=True, success_ist=True): threshold_weights = np.linspace( 1, 0.5, self.alpha.shape[0]).reshape(-1, 1) it_config = {'threshold': 'fixed', 'threshold_fixed': self.k, 'threshold_weights': threshold_weights} magni.cs.reconstruction.it.config.update(it_config) self._wiht_run(self.y, self.A, self.alpha, success=success_iht) self._wist_run(self.y, self.A, self.alpha, success=success_ist) self.assertEqual(magni.cs.reconstruction.it.config['threshold'], 'fixed') self.assertEqual(magni.cs.reconstruction.it.config['threshold_fixed'], self.k) self.assertTrue(np.allclose( magni.cs.reconstruction.it.config['threshold_weights'], threshold_weights)) def _amp_run(self, y, A, a, success=True): threshold_params = { 'theta': magni.cs.reconstruction.amp.util.theta_mm( float(A.shape[0]) / A.shape[1]), 'tau_hat_sq': 1.0} magni.cs.reconstruction.amp.config['threshold_parameters'].update( threshold_params) a_hat = magni.cs.reconstruction.amp.run(y, A) if success: self.assertTrue(np.allclose(a_hat, a, atol=1e-2)) else: self.assertFalse(np.allclose(a_hat, a, atol=1e-2)) def _gamp_run(self, z, F, F_sq, a, success=True): a_hat = magni.cs.reconstruction.gamp.run(z, F, F_sq) if success: self.assertTrue(np.allclose(a_hat, a, atol=1e-2)) else: self.assertFalse(np.allclose(a_hat, a, atol=1e-2)) def _iht_run(self, y, A, alpha, success=True): iht_config = {'threshold_operator': 'hard'} magni.cs.reconstruction.it.config.update(iht_config) self.assertEqual( magni.cs.reconstruction.it.config['threshold_operator'], 'hard') alpha_hat = magni.cs.reconstruction.it.run(y, A) if success: self.assertTrue(np.allclose(alpha_hat, alpha, atol=1e-2)) else: self.assertFalse(np.allclose(alpha_hat, alpha, atol=1e-2)) def _ist_run(self, y, A, alpha, success=True): ist_config = {'threshold_operator': 'soft'} magni.cs.reconstruction.it.config.update(ist_config) self.assertEqual( magni.cs.reconstruction.it.config['threshold_operator'], 'soft') alpha_hat = magni.cs.reconstruction.it.run(y, A) if success: self.assertTrue(np.allclose(alpha_hat, alpha, atol=1e-2)) else: self.assertFalse(np.allclose(alpha_hat, alpha, atol=1e-2)) def _wiht_run(self, y, A, alpha, success=True): iht_config = {'threshold_operator': 'weighted_hard'} magni.cs.reconstruction.it.config.update(iht_config) self.assertEqual( magni.cs.reconstruction.it.config['threshold_operator'], 'weighted_hard') alpha_hat = magni.cs.reconstruction.it.run(y, A) if success: self.assertTrue(np.allclose(alpha_hat, alpha, atol=1e-2)) else: self.assertFalse(np.allclose(alpha_hat, alpha, atol=1e-2)) def _wist_run(self, y, A, alpha, success=True): ist_config = {'threshold_operator': 'weighted_soft'} magni.cs.reconstruction.it.config.update(ist_config) self.assertEqual( magni.cs.reconstruction.it.config['threshold_operator'], 'weighted_soft') alpha_hat = magni.cs.reconstruction.it.run(y, A) if success: self.assertTrue(np.allclose(alpha_hat, alpha, atol=1e-2)) else: self.assertFalse(np.allclose(alpha_hat, alpha, atol=1e-2)) class PhaseSpaceTest1(PhaseSpaceTest, unittest.TestCase): """ Test of reconstruction capabilities at Phase Space point: (delta, rho) = (0.08, 0.05) """ def setUp(self): n = 500 delta = 0.08 rho = 0.05 PhaseSpaceTest.setUp(self, n=n, delta=delta, rho=rho) def test_residual_soft_threshold_AMP(self): PhaseSpaceTest.test_residual_soft_threshold_AMP(self, success=False) def test_median_soft_threshold_AMP(self, success=True): PhaseSpaceTest.test_median_soft_threshold_AMP(self, success=False) def test_iidsGB_AWGN_GAMP(self): PhaseSpaceTest.test_iidsGB_AWGN_GAMP(self, success=False) def test_iidsGB_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidsGB_AWGN_EM_GAMP(self, success=False) def test_iidBL_AWGN_GAMP(self): PhaseSpaceTest.test_iidBL_AWGN_GAMP(self, success=False) def test_iidBL_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidBL_AWGN_EM_GAMP(self, success=False) def test_iidBG_AWGN_GAMP(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP(self, success=False) def test_iidBG_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidBG_AWGN_EM_GAMP(self, success=False) def test_iidBG_AWGN_GAMP_rangan_sum_approx(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP_rangan_sum_approx( self, success=False) def test_iidBG_AWGN_GAMP_krzakala_sum_approx(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP_krzakala_sum_approx( self, success=False) def test_iidwBG_ones_AWGN_GAMP(self): PhaseSpaceTest.test_iidwBG_ones_AWGN_GAMP(self, success=False) def test_iidwBG_ones_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidwBG_ones_AWGN_EM_GAMP(self, success=False) def test_iidwBG_linspace_AWGN_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_GAMP(self, success=False) def test_iidwBG_linspace_AWGN_EM_truncate_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_EM_truncate_GAMP( self, success=False) def test_iidwBG_linspace_AWGN_EM_reweight_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_EM_reweight_GAMP( self, success=False) class PhaseSpaceTest2(PhaseSpaceTest, unittest.TestCase): """ Test of reconstruction capabilities at Phase Space point: (delta, rho) = (0.24, 0.01) """ def setUp(self): n = 500 delta = 0.24 rho = 0.01 PhaseSpaceTest.setUp(self, n=n, delta=delta, rho=rho) def test_residual_soft_threshold_AMP(self): PhaseSpaceTest.test_residual_soft_threshold_AMP(self, success=False) def test_median_soft_threshold_AMP(self, success=True): PhaseSpaceTest.test_median_soft_threshold_AMP(self, success=False) def test_iidsGB_AWGN_GAMP(self): PhaseSpaceTest.test_iidsGB_AWGN_GAMP(self, success=False) def test_iidsGB_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidsGB_AWGN_EM_GAMP(self, success=False) def test_iidBL_AWGN_GAMP(self): PhaseSpaceTest.test_iidBL_AWGN_GAMP(self, success=False) def test_iidBL_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidBL_AWGN_EM_GAMP(self, success=False) def test_iidBG_AWGN_GAMP(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP(self, success=False) def test_iidBG_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidBG_AWGN_EM_GAMP(self, success=False) def test_iidBG_AWGN_GAMP_rangan_sum_approx(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP_rangan_sum_approx( self, success=False) def test_iidBG_AWGN_GAMP_krzakala_sum_approx(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP_krzakala_sum_approx( self, success=False) def test_iidwBG_ones_AWGN_GAMP(self): PhaseSpaceTest.test_iidwBG_ones_AWGN_GAMP(self, success=False) def test_iidwBG_ones_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidwBG_ones_AWGN_EM_GAMP(self, success=False) def test_iidwBG_linspace_AWGN_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_GAMP(self, success=False) def test_iidwBG_linspace_AWGN_EM_truncate_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_EM_truncate_GAMP( self, success=False) def test_iidwBG_linspace_AWGN_EM_reweight_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_EM_reweight_GAMP( self, success=False) class PhaseSpaceTest3(PhaseSpaceTest, unittest.TestCase): """ Test of reconstruction capabilities at Phase Space point: (delta, rho) = (0.38, 0.12) """ def setUp(self): n = 500 delta = 0.38 rho = 0.12 PhaseSpaceTest.setUp(self, n=n, delta=delta, rho=rho) def test_fixed_IT(self): PhaseSpaceTest.test_fixed_IT(self, success_ist=False) def test_adaptive_fixed_IT(self): PhaseSpaceTest.test_adaptive_fixed_IT(self, success_ist=False) class PhaseSpaceTest4(PhaseSpaceTest, unittest.TestCase): """ Test of reconstruction capabilities at Phase Space point: (delta, rho) = (0.62, 0.38) """ def setUp(self): n = 500 delta = 0.62 rho = 0.38 PhaseSpaceTest.setUp(self, n=n, delta=delta, rho=rho) def test_residual_soft_threshold_AMP(self): PhaseSpaceTest.test_residual_soft_threshold_AMP(self, success=False) def test_median_soft_threshold_AMP(self, success=True): PhaseSpaceTest.test_median_soft_threshold_AMP(self, success=False) def test_default_IT(self): PhaseSpaceTest.test_default_IT(self, success_iht=False, success_ist=False) def test_fixed_IT(self): PhaseSpaceTest.test_fixed_IT(self, success_iht=False, success_ist=False) def test_adaptive_fixed_IT(self): PhaseSpaceTest.test_adaptive_fixed_IT(self, success_iht=False, success_ist=False) def test_weighted_fixed_IT(self): PhaseSpaceTest.test_weighted_fixed_IT(self, success_iht=False, success_ist=False) class PhaseSpaceTest5(PhaseSpaceTest, unittest.TestCase): """ Test of reconstruction capabilities at Phase Space point: (delta, rho) = (0.78, 0.22) """ def setUp(self): n = 500 delta = 0.78 rho = 0.22 PhaseSpaceTest.setUp(self, n=n, delta=delta, rho=rho) def test_fixed_IT(self): PhaseSpaceTest.test_fixed_IT(self, success_ist=False) def test_adaptive_fixed_IT(self): PhaseSpaceTest.test_adaptive_fixed_IT(self, success_ist=False) def test_weighted_fixed_IT(self): PhaseSpaceTest.test_weighted_fixed_IT(self, success_ist=False) class PhaseSpaceTest6(PhaseSpaceTest, unittest.TestCase): """ Test of reconstruction capabilities at Phase Space point: (delta, rho) = (0.84, 0.08) """ def setUp(self): n = 500 delta = 0.84 rho = 0.08 PhaseSpaceTest.setUp(self, n=n, delta=delta, rho=rho) def test_fixed_IT(self): PhaseSpaceTest.test_fixed_IT(self, success_ist=False) def test_adaptive_fixed_IT(self): PhaseSpaceTest.test_adaptive_fixed_IT(self, success_ist=False) def test_weighted_fixed_IT(self): PhaseSpaceTest.test_weighted_fixed_IT(self, success_ist=False) class PhaseSpaceTest7(PhaseSpaceTest, unittest.TestCase): """ Test of reconstruction capabilities at Phase Space point: (delta, rho) = (0.96, 0.91) """ def setUp(self): n = 500 delta = 0.96 rho = 0.91 PhaseSpaceTest.setUp(self, n=n, delta=delta, rho=rho) def test_residual_soft_threshold_AMP(self): PhaseSpaceTest.test_residual_soft_threshold_AMP(self, success=False) def test_median_soft_threshold_AMP(self, success=True): PhaseSpaceTest.test_median_soft_threshold_AMP(self, success=False) def test_iidsGB_AWGN_GAMP(self): PhaseSpaceTest.test_iidsGB_AWGN_GAMP(self, success=False) def test_iidsGB_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidsGB_AWGN_EM_GAMP(self, success=False) def test_iidBL_AWGN_GAMP(self): PhaseSpaceTest.test_iidBL_AWGN_GAMP(self, success=False) def test_iidBL_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidBL_AWGN_EM_GAMP(self, success=False) def test_iidBG_AWGN_GAMP(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP(self, success=False) def test_iidBG_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidBG_AWGN_EM_GAMP(self, success=False) def test_iidBG_AWGN_GAMP_rangan_sum_approx(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP_rangan_sum_approx( self, success=False) def test_iidBG_AWGN_GAMP_krzakala_sum_approx(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP_krzakala_sum_approx( self, success=False) def test_iidwBG_ones_AWGN_GAMP(self): PhaseSpaceTest.test_iidwBG_ones_AWGN_GAMP(self, success=False) def test_iidwBG_ones_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidwBG_ones_AWGN_EM_GAMP(self, success=False) def test_iidwBG_linspace_AWGN_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_GAMP(self, success=False) def test_iidwBG_linspace_AWGN_EM_truncate_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_EM_truncate_GAMP( self, success=False) def test_iidwBG_linspace_AWGN_EM_reweight_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_EM_reweight_GAMP( self, success=False) def test_default_IT(self): PhaseSpaceTest.test_default_IT(self, success_iht=False, success_ist=False) def test_fixed_IT(self): PhaseSpaceTest.test_fixed_IT(self, success_iht=False, success_ist=False) def test_adaptive_fixed_IT(self): PhaseSpaceTest.test_adaptive_fixed_IT(self, success_iht=False, success_ist=False) def test_weighted_fixed_IT(self): PhaseSpaceTest.test_weighted_fixed_IT(self, success_iht=False, success_ist=False) class PhaseSpaceTestA(PhaseSpaceTest, unittest.TestCase): """ Test of reconstruction capabilities at Phase Space point: (delta, rho) = (0.06, 0.92) """ def setUp(self): n = 500 delta = 0.06 rho = 0.92 PhaseSpaceTest.setUp(self, n=n, delta=delta, rho=rho) def test_residual_soft_threshold_AMP(self): PhaseSpaceTest.test_residual_soft_threshold_AMP(self, success=False) def test_median_soft_threshold_AMP(self, success=True): PhaseSpaceTest.test_median_soft_threshold_AMP(self, success=False) def test_iidsGB_AWGN_GAMP(self): PhaseSpaceTest.test_iidsGB_AWGN_GAMP(self, success=False) def test_iidsGB_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidsGB_AWGN_EM_GAMP(self, success=False) def test_iidBL_AWGN_GAMP(self): PhaseSpaceTest.test_iidBL_AWGN_GAMP(self, success=False) def test_iidBL_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidBL_AWGN_EM_GAMP(self, success=False) def test_iidBG_AWGN_GAMP(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP(self, success=False) def test_iidBG_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidBG_AWGN_EM_GAMP(self, success=False) def test_iidBG_AWGN_GAMP_rangan_sum_approx(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP_rangan_sum_approx( self, success=False) def test_iidBG_AWGN_GAMP_krzakala_sum_approx(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP_krzakala_sum_approx( self, success=False) def test_iidwBG_ones_AWGN_GAMP(self): PhaseSpaceTest.test_iidwBG_ones_AWGN_GAMP(self, success=False) def test_iidwBG_ones_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidwBG_ones_AWGN_EM_GAMP(self, success=False) def test_iidwBG_linspace_AWGN_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_GAMP(self, success=False) def test_iidwBG_linspace_AWGN_EM_truncate_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_EM_truncate_GAMP( self, success=False) def test_iidwBG_linspace_AWGN_EM_reweight_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_EM_reweight_GAMP( self, success=False) def test_default_IT(self): PhaseSpaceTest.test_default_IT(self, success_iht=False, success_ist=False) def test_fixed_IT(self): PhaseSpaceTest.test_fixed_IT(self, success_iht=False, success_ist=False) def test_adaptive_fixed_IT(self): PhaseSpaceTest.test_adaptive_fixed_IT(self, success_iht=False, success_ist=False) def test_weighted_fixed_IT(self): PhaseSpaceTest.test_weighted_fixed_IT(self, success_iht=False, success_ist=False) class PhaseSpaceTestB(PhaseSpaceTest, unittest.TestCase): """ Test of reconstruction capabilities at Phase Space point: (delta, rho) = (0.19, 0.84) """ def setUp(self): n = 500 delta = 0.19 rho = 0.84 PhaseSpaceTest.setUp(self, n=n, delta=delta, rho=rho) def test_residual_soft_threshold_AMP(self): PhaseSpaceTest.test_residual_soft_threshold_AMP(self, success=False) def test_median_soft_threshold_AMP(self, success=True): PhaseSpaceTest.test_median_soft_threshold_AMP(self, success=False) def test_iidsGB_AWGN_GAMP(self): PhaseSpaceTest.test_iidsGB_AWGN_GAMP(self, success=False) def test_iidsGB_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidsGB_AWGN_EM_GAMP(self, success=False) def test_iidBL_AWGN_GAMP(self): PhaseSpaceTest.test_iidBL_AWGN_GAMP(self, success=False) def test_iidBL_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidBL_AWGN_EM_GAMP(self, success=False) def test_iidBG_AWGN_GAMP(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP(self, success=False) def test_iidBG_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidBG_AWGN_EM_GAMP(self, success=False) def test_iidBG_AWGN_GAMP_rangan_sum_approx(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP_rangan_sum_approx( self, success=False) def test_iidBG_AWGN_GAMP_krzakala_sum_approx(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP_krzakala_sum_approx( self, success=False) def test_iidwBG_ones_AWGN_GAMP(self): PhaseSpaceTest.test_iidwBG_ones_AWGN_GAMP(self, success=False) def test_iidwBG_ones_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidwBG_ones_AWGN_EM_GAMP(self, success=False) def test_iidwBG_linspace_AWGN_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_GAMP(self, success=False) def test_iidwBG_linspace_AWGN_EM_truncate_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_EM_truncate_GAMP( self, success=False) def test_iidwBG_linspace_AWGN_EM_reweight_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_EM_reweight_GAMP( self, success=False) def test_default_IT(self): PhaseSpaceTest.test_default_IT(self, success_iht=False, success_ist=False) def test_fixed_IT(self): PhaseSpaceTest.test_fixed_IT(self, success_iht=False, success_ist=False) def test_adaptive_fixed_IT(self): PhaseSpaceTest.test_adaptive_fixed_IT(self, success_iht=False, success_ist=False) def test_weighted_fixed_IT(self): PhaseSpaceTest.test_weighted_fixed_IT(self, success_iht=False, success_ist=False) class PhaseSpaceTestC(PhaseSpaceTest, unittest.TestCase): """ Test of reconstruction capabilities at Phase Space point: (delta, rho) = (0.29, 0.94) """ def setUp(self): n = 500 delta = 0.29 rho = 0.94 PhaseSpaceTest.setUp(self, n=n, delta=delta, rho=rho) def test_residual_soft_threshold_AMP(self): PhaseSpaceTest.test_residual_soft_threshold_AMP(self, success=False) def test_median_soft_threshold_AMP(self, success=True): PhaseSpaceTest.test_median_soft_threshold_AMP(self, success=False) def test_iidsGB_AWGN_GAMP(self): PhaseSpaceTest.test_iidsGB_AWGN_GAMP(self, success=False) def test_iidsGB_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidsGB_AWGN_EM_GAMP(self, success=False) def test_iidBL_AWGN_GAMP(self): PhaseSpaceTest.test_iidBL_AWGN_GAMP(self, success=False) def test_iidBL_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidBL_AWGN_EM_GAMP(self, success=False) def test_iidBG_AWGN_GAMP(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP(self, success=False) def test_iidBG_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidBG_AWGN_EM_GAMP(self, success=False) def test_iidBG_AWGN_GAMP_rangan_sum_approx(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP_rangan_sum_approx( self, success=False) def test_iidBG_AWGN_GAMP_krzakala_sum_approx(self): PhaseSpaceTest.test_iidBG_AWGN_GAMP_krzakala_sum_approx( self, success=False) def test_iidwBG_ones_AWGN_GAMP(self): PhaseSpaceTest.test_iidwBG_ones_AWGN_GAMP(self, success=False) def test_iidwBG_ones_AWGN_EM_GAMP(self): PhaseSpaceTest.test_iidwBG_ones_AWGN_EM_GAMP(self, success=False) def test_iidwBG_linspace_AWGN_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_GAMP(self, success=False) def test_iidwBG_linspace_AWGN_EM_truncate_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_EM_truncate_GAMP( self, success=False) def test_iidwBG_linspace_AWGN_EM_reweight_GAMP(self): PhaseSpaceTest.test_iidwBG_linspace_AWGN_EM_reweight_GAMP( self, success=False) def test_default_IT(self): PhaseSpaceTest.test_default_IT(self, success_iht=False, success_ist=False) def test_fixed_IT(self): PhaseSpaceTest.test_fixed_IT(self, success_iht=False, success_ist=False) def test_adaptive_fixed_IT(self): PhaseSpaceTest.test_adaptive_fixed_IT(self, success_iht=False, success_ist=False) def test_weighted_fixed_IT(self): PhaseSpaceTest.test_weighted_fixed_IT(self, success_iht=False, success_ist=False) class TestUSERademacher(unittest.TestCase): """ Test of the use_rademacher test fixture function. """ def test_seed_6021(self): n = 10 m = 6 k = 3 seed = 6021 alpha_true = np.array([ [-1], [1], [1], [0], [0], [0], [0], [0], [0], [0]]) A_true = np.array([ [0.3970924, 0.39094998, -0.51535881, -0.29376165, 0.80329912, 0.2343297, 0.20381475, -0.4006275, 0.97687495, -0.02913711], [-0.21781685, -0.46838027, -0.39565219, -0.29879357, -0.1528902, -0.09484526, -0.24859693, 0.42678941, -0.17170236, -0.09260817], [-0.08024309, -0.24175707, -0.1299679, -0.15608146, -0.51588714, -0.48385891, 0.15647558, -0.54407042, 0.16007046, -0.39455782], [-0.11461544, -0.09242993, 0.10134369, 0.03684144, 0.24202215, 0.22913925, -0.16115897, 0.07449874, 0.24777711, -0.20584097], [-0.49012155, 0.30646838, 0.27297925, -0.03009987, 0.21501576, -0.16483217, 0.49937075, 0.04385046, 0.26298357, 0.33893551], [-0.06364924, 0.68731702, -0.21930248, -0.20445363, 0.38122107, -0.05793133, 0.12713844, -1.14521796, -0.62776378, -0.1934683]]) y_true = A_true.dot(alpha_true) y, A, alpha = use_rademacher(n, m, k, seed) self.assertTrue(np.alltrue(alpha_true == alpha)) self.assertTrue(np.allclose(A_true, A)) self.assertTrue(np.allclose(y_true, y)) class TestUSEGaussian(unittest.TestCase): """ Test of the use_gaussian test fixture function. """ def test_seed_6021(self): n = 10 m = 6 k = 3 seed = 6021 alpha_true = np.array([ 2.5616611, -0.30927792, -0.56096039, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]).reshape(-1, 1) A_true = np.array([ [0.3970924, 0.39094998, -0.51535881, -0.29376165, 0.80329912, 0.2343297, 0.20381475, -0.4006275, 0.97687495, -0.02913711], [-0.21781685, -0.46838027, -0.39565219, -0.29879357, -0.1528902, -0.09484526, -0.24859693, 0.42678941, -0.17170236, -0.09260817], [-0.08024309, -0.24175707, -0.1299679, -0.15608146, -0.51588714, -0.48385891, 0.15647558, -0.54407042, 0.16007046, -0.39455782], [-0.11461544, -0.09242993, 0.10134369, 0.03684144, 0.24202215, 0.22913925, -0.16115897, 0.07449874, 0.24777711, -0.20584097], [-0.49012155, 0.30646838, 0.27297925, -0.03009987, 0.21501576, -0.16483217, 0.49937075, 0.04385046, 0.26298357, 0.33893551], [-0.06364924, 0.68731702, -0.21930248, -0.20445363, 0.38122107, -0.05793133, 0.12713844, -1.14521796, -0.62776378, -0.1934683]]) y_true = A_true.dot(alpha_true) y, A, alpha = use_gaussian(n, m, k, seed) self.assertTrue(np.allclose(alpha_true, alpha)) self.assertTrue(np.allclose(A_true, A)) self.assertTrue(np.allclose(y_true, y)) def use_gaussian(n, m, k, seed): """ Prepare an instance of the USE/Gaussian problem suite Prepares: * :math:`\mathbf{A} \in \mathbb{R}^{m \times n}` from Uniform Spherical Ensemble (USE). * :math:`\mathbf{alpha} \in \mathbb{R}^{n}` with :math:`k` non-zero entries drawn from the standard normal distribution. * :math:`\mathbf{y} = \mathbf{A}\mathbf{\alpha}` Parameters ---------- n : int The problem size. m : int The number of measurements. k : int The number of non-zero coefficients. seed : int The seed used in the random number generator. Returns ------- (y, A, alpha) : tuple The measurements, measurement matrix, and coefficients. """ @_decorate_validation def validate_input(): _numeric('n', 'integer', range_='[1;inf)') _numeric('m', 'integer', range_='[1;inf)') _numeric('k', 'integer', range_='[0;inf)') _numeric('seed', 'integer', range_='[0;inf)') @_decorate_validation def validate_output(): _numeric('y', ('integer', 'floating', 'complex'), shape=(m, 1)) _numeric('A', ('integer', 'floating', 'complex'), shape=(m, n)) _numeric('alpha', ('integer', 'floating', 'complex'), shape=(n, 1)) validate_input() np.random.seed(seed=seed) A = 1/np.sqrt(m) * np.random.randn(m, n) alpha = np.zeros((n, 1)) alpha[:k, 0] = np.random.randn(k) y = A.dot(alpha) validate_output() return y, A, alpha def use_rademacher(n, m, k, seed): """ Prepare an instance of the USE/Rademacher problem suite Prepares: * :math:`\mathbf{A} \in \mathbb{R}^{m \times n}` from Uniform Spherical Ensemble (USE). * :math:`\mathbf{alpha} \in \mathbb{R}^{n}` with :math:`k` non-zero entries drawn from the Rademacher distribution {1, -1}. * :math:`\mathbf{y} = \mathbf{A}\mathbf{\alpha}` Parameters ---------- n : int The problem size. m : int The number of measurements. k : int The number of non-zero coefficients. seed : int The seed used in the random number generator. Returns ------- (y, A, alpha) : tuple The measurements, measurement matrix, and coefficients. """ @_decorate_validation def validate_input(): _numeric('n', 'integer', range_='[1;inf)') _numeric('m', 'integer', range_='[1;inf)') _numeric('k', 'integer', range_='[0;inf)') _numeric('seed', 'integer', range_='[0;inf)') @_decorate_validation def validate_output(): _numeric('y', ('integer', 'floating', 'complex'), shape=(m, 1)) _numeric('A', ('integer', 'floating', 'complex'), shape=(m, n)) _numeric('alpha', ('integer', 'floating', 'complex'), shape=(n, 1)) validate_input() np.random.seed(seed=seed) A = 1/np.sqrt(m) * np.random.randn(m, n) alpha = np.zeros((n, 1)) alpha[:k, 0] = np.random.randint(0, 2, k) * 2 - 1 y = A.dot(alpha) validate_output() return y, A, alpha

40.19561

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0.636108

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104,388

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0.893082

0.867436

0.855597

0.838631

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0.031268

0.247548

104,388

2,596

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40.211094

0.77094

0.102847

0

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null

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0

1

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null

0

7

0b56e0093724b8ce683484a5eb75886e640287b0

11,251

py

Python

src/se_data_process.py

RuihongQiu/GAG

819e33eee2e3d7d56e635361aff53faea2bfad3a

[ "Apache-2.0" ]

16

2020-09-26T07:42:49.000Z

2022-03-06T07:26:05.000Z

src/se_data_process.py

UQMM/GAG

819e33eee2e3d7d56e635361aff53faea2bfad3a

[ "Apache-2.0" ]

2

2020-11-03T12:48:42.000Z

2021-07-30T01:00:35.000Z

src/se_data_process.py

UQMM/GAG

819e33eee2e3d7d56e635361aff53faea2bfad3a

[ "Apache-2.0" ]

4

2021-01-10T12:21:18.000Z

2022-01-16T14:31:39.000Z

# -*- coding: utf-8 -*- """ Created on 17/9/2019 @author: LeiGuo, RuihongQiu """ import pickle import numpy def prepare_data(seqs, labels): """Create the matrices from the datasets. This pad each sequence to the same lenght: the lenght of the longuest sequence or maxlen. if maxlen is set, we will cut all sequence to this maximum lenght. This swap the axis! """ lengths = [len(s) for s in seqs] n_samples = len(seqs) maxlen = numpy.max(lengths) x = numpy.zeros((maxlen, n_samples)).astype('int64') x_mask = numpy.ones((maxlen, n_samples)).astype(theano.config.floatX) for idx, s in enumerate(seqs): x[:lengths[idx], idx] = s x_mask *= (1 - (x == 0)) return x, x_mask, labels def load_data(path, valid_portion=0.1, maxlen=19, sort_by_len=False): """Loads the dataset :type path: String :param path: The path to the dataset (here RSC2015) :type n_items: int :param n_items: The number of items. :type valid_portion: float :param valid_portion: The proportion of the full train set used for the validation set. :type maxlen: None or positive int :param maxlen: the max sequence length we use in the train/valid set. :type sort_by_len: bool :name sort_by_len: Sort by the sequence lenght for the train, valid and test set. This allow faster execution as it cause less padding per minibatch. Another mechanism must be used to shuffle the train set at each epoch. """ path_train_data = path+'train_final.csv' path_test_data = path+'test_final.csv' f1 = open(path_train_data, 'rb') train_set = pickle.load(f1) f1.close() f2 = open(path_test_data, 'rb') test_set = pickle.load(f2) f2.close() if maxlen: new_train_set_x = [] new_train_set_y = [] new_train_set_u = [] for x, y, u in list(zip(train_set[0], train_set[1],train_set[2])): if len(x) < maxlen: new_train_set_x.append(x) new_train_set_y.append(y) new_train_set_u.append(u) else: new_train_set_x.append(x[:maxlen]) new_train_set_y.append(y) new_train_set_u.append(u) train_set = (new_train_set_x, new_train_set_y, new_train_set_u) del new_train_set_x, new_train_set_y, new_train_set_u new_test_set_x = [] new_test_set_y = [] new_test_set_u = [] for xx, yy, uu in zip(test_set[0], test_set[1], test_set[2]): if len(xx) < maxlen: new_test_set_x.append(xx) new_test_set_y.append(yy) new_test_set_u.append(uu) else: new_test_set_x.append(xx[:maxlen]) new_test_set_y.append(yy) new_test_set_u.append(uu) test_set = (new_test_set_x, new_test_set_y, new_test_set_u) del new_test_set_x, new_test_set_y, new_test_set_u # split training set into validation set train_set_x, train_set_y, train_set_u = train_set n_samples = len(train_set_x) sidx = numpy.arange(n_samples, dtype='int32') numpy.random.shuffle(sidx) n_train = int(numpy.round(n_samples * (1. - valid_portion))) valid_set_x = [train_set_x[s] for s in sidx[n_train:]] valid_set_y = [train_set_y[s] for s in sidx[n_train:]] valid_set_u = [train_set_u[s] for s in sidx[n_train:]] train_set_x = [train_set_x[s] for s in sidx[:n_train]] train_set_y = [train_set_y[s] for s in sidx[:n_train]] train_set_u = [train_set_u[s] for s in sidx[:n_train]] train_set = (train_set_x, train_set_y, train_set_u) valid_set = (valid_set_x, valid_set_y, valid_set_u) test_set_x, test_set_y, test_set_u = test_set valid_set_x, valid_set_y, valid_set_u = valid_set train_set_x, train_set_y, train_set_u = train_set def len_argsort(seq): return sorted(range(len(seq)), key=lambda x: len(seq[x])) if sort_by_len: sorted_index = len_argsort(test_set_x) test_set_x = [test_set_x[i] for i in sorted_index] test_set_y = [test_set_y[i] for i in sorted_index] sorted_index = len_argsort(valid_set_x) valid_set_x = [valid_set_x[i] for i in sorted_index] valid_set_y = [valid_set_y[i] for i in sorted_index] train = (train_set_x, train_set_y, train_set_u) valid = (valid_set_x, valid_set_y, valid_set_u) test = (test_set_x, test_set_y, test_set_u) return train, valid, test def load_traindata(trainFile, validFile, valid_portion=0.1, maxlen=19, sort_by_len=False): """Loads the dataset :type path: String :param path: The path to the dataset (here RSC2015) :type n_items: int :param n_items: The number of items. :type valid_portion: float :param valid_portion: The proportion of the full train set used for the validation set. :type maxlen: None or positive int :param maxlen: the max sequence length we use in the train/valid set. :type sort_by_len: bool :name sort_by_len: Sort by the sequence lenght for the train, valid and test set. This allow faster execution as it cause less padding per minibatch. Another mechanism must be used to shuffle the train set at each epoch. """ path_train_data = trainFile path_test_data = validFile f1 = open(path_train_data, 'rb') train_set = pickle.load(f1) f1.close() f2 = open(path_test_data, 'rb') test_set = pickle.load(f2) f2.close() if maxlen: new_train_set_x = [] new_train_set_y = [] new_train_set_u = [] for x, y, u in list(zip(train_set[0], train_set[1], train_set[2])): if len(x) < maxlen: new_train_set_x.append(x) new_train_set_y.append(y) new_train_set_u.append(u) else: new_train_set_x.append(x[:maxlen]) new_train_set_y.append(y) new_train_set_u.append(u) train_set = (new_train_set_x, new_train_set_y, new_train_set_u) del new_train_set_x, new_train_set_y, new_train_set_u new_test_set_x = [] new_test_set_y = [] new_test_set_u = [] for xx, yy, uu in zip(test_set[0], test_set[1], test_set[2]): if len(xx) < maxlen: new_test_set_x.append(xx) new_test_set_y.append(yy) new_test_set_u.append(uu) else: new_test_set_x.append(xx[:maxlen]) new_test_set_y.append(yy) new_test_set_u.append(uu) test_set = (new_test_set_x, new_test_set_y, new_test_set_u) del new_test_set_x, new_test_set_y, new_test_set_u test_set_x, test_set_y, test_set_u = test_set train_set_x, train_set_y, train_set_u = train_set def len_argsort(seq): return sorted(range(len(seq)), key=lambda x: len(seq[x])) if sort_by_len: sorted_index = len_argsort(test_set_x) test_set_x = [test_set_x[i] for i in sorted_index] test_set_y = [test_set_y[i] for i in sorted_index] train = (train_set_x, train_set_y, train_set_u) test = (test_set_x, test_set_y, test_set_u) return train, test def load_testdata(testFile, maxlen=19, sort_by_len=False): """Loads the dataset :type path: String :param path: The path to the dataset (here RSC2015) :type n_items: int :param n_items: The number of items. :type valid_portion: float :param valid_portion: The proportion of the full train set used for the validation set. :type maxlen: None or positive int :param maxlen: the max sequence length we use in the train/valid set. :type sort_by_len: bool :name sort_by_len: Sort by the sequence lenght for the train, valid and test set. This allow faster execution as it cause less padding per minibatch. Another mechanism must be used to shuffle the train set at each epoch. """ path_test_data = testFile f2 = open(path_test_data, 'rb') test_set = pickle.load(f2) f2.close() if maxlen: new_test_set_x = [] new_test_set_y = [] new_test_set_u = [] for xx, yy, uu in zip(test_set[0], test_set[1], test_set[2]): if len(xx) < maxlen: new_test_set_x.append(xx) new_test_set_y.append(yy) new_test_set_u.append(uu) else: new_test_set_x.append(xx[:maxlen]) new_test_set_y.append(yy) new_test_set_u.append(uu) test_set = (new_test_set_x, new_test_set_y, new_test_set_u) del new_test_set_x, new_test_set_y, new_test_set_u test_set_x, test_set_y, test_set_u = test_set def len_argsort(seq): return sorted(range(len(seq)), key=lambda x: len(seq[x])) if sort_by_len: sorted_index = len_argsort(test_set_x) test_set_x = [test_set_x[i] for i in sorted_index] test_set_y = [test_set_y[i] for i in sorted_index] test = (test_set_x, test_set_y, test_set_u) return test def load_data_valid(train_file, valid_portion=0.1, maxlen=19, sort_by_len=False): path_train_data = train_file f1 = open(path_train_data, 'rb') train_set = pickle.load(f1) f1.close() if maxlen: new_train_set_x = [] new_train_set_y = [] new_train_set_u = [] for x, y, u in list(zip(train_set[0], train_set[1],train_set[2])): if len(x) < maxlen: new_train_set_x.append(x) new_train_set_y.append(y) new_train_set_u.append(u) else: new_train_set_x.append(x[:maxlen]) new_train_set_y.append(y) new_train_set_u.append(u) train_set = (new_train_set_x, new_train_set_y, new_train_set_u) del new_train_set_x, new_train_set_y, new_train_set_u # split training set into validation set train_set_x, train_set_y, train_set_u = train_set n_samples = len(train_set_x) sidx = numpy.arange(n_samples, dtype='int32') numpy.random.shuffle(sidx) n_train = int(numpy.round(n_samples * (1. - valid_portion))) valid_set_x = [train_set_x[s] for s in sidx[n_train:]] valid_set_y = [train_set_y[s] for s in sidx[n_train:]] valid_set_u = [train_set_u[s] for s in sidx[n_train:]] train_set_x = [train_set_x[s] for s in sidx[:n_train]] train_set_y = [train_set_y[s] for s in sidx[:n_train]] train_set_u = [train_set_u[s] for s in sidx[:n_train]] train_set = (train_set_x, train_set_y, train_set_u) valid_set = (valid_set_x, valid_set_y, valid_set_u) valid_set_x, valid_set_y, valid_set_u = valid_set train_set_x, train_set_y, train_set_u = train_set def len_argsort(seq): return sorted(range(len(seq)), key=lambda x: len(seq[x])) if sort_by_len: sorted_index = len_argsort(valid_set_x) valid_set_x = [valid_set_x[i] for i in sorted_index] valid_set_y = [valid_set_y[i] for i in sorted_index] train = (train_set_x, train_set_y, train_set_u) valid = (valid_set_x, valid_set_y, valid_set_u) return train, valid

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7

0b667665d3aaf90a2decbcfc87fb082c7674c212

254

py

Python

7.0-threads/model.py

zehemz/clases-python-101

633cb5f0cbc85e64e242514f0394754a5bed0513

[ "Apache-2.0" ]

null

7.0-threads/model.py

zehemz/clases-python-101

633cb5f0cbc85e64e242514f0394754a5bed0513

[ "Apache-2.0" ]

null

7.0-threads/model.py

zehemz/clases-python-101

633cb5f0cbc85e64e242514f0394754a5bed0513

[ "Apache-2.0" ]

null

#!/usr/bin/python class UserModel: def __init__(self, username, email): self.username = username self.email = email self.groups = [] def getUserDictionary(self): return {"username" : self.username, "email": self.email, "groups": self.groups}

25.4

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0b9192cccc41dad4003bef43bef38b542d91dd2e

982

py

Python

src/visions/backends/python/types/__init__.py

bhumikapahariapuresoftware/visions

8838d89b4f02e401112378b4662a779227ead9f8

[ "BSD-4-Clause" ]

142

2020-01-07T21:17:10.000Z

2022-03-30T13:10:14.000Z

src/visions/backends/python/types/__init__.py

bhumikapahariapuresoftware/visions

8838d89b4f02e401112378b4662a779227ead9f8

[ "BSD-4-Clause" ]

121

2020-01-07T02:26:38.000Z

2022-03-29T17:18:19.000Z

src/visions/backends/python/types/__init__.py

bhumikapahariapuresoftware/visions

8838d89b4f02e401112378b4662a779227ead9f8

[ "BSD-4-Clause" ]

18

2020-02-17T03:17:37.000Z

2022-02-20T14:01:11.000Z

import visions.backends.python.types.boolean import visions.backends.python.types.categorical import visions.backends.python.types.complex import visions.backends.python.types.count import visions.backends.python.types.date import visions.backends.python.types.date_time import visions.backends.python.types.email_address import visions.backends.python.types.file import visions.backends.python.types.float import visions.backends.python.types.geometry import visions.backends.python.types.image import visions.backends.python.types.integer import visions.backends.python.types.ip_address import visions.backends.python.types.numeric import visions.backends.python.types.object import visions.backends.python.types.ordinal import visions.backends.python.types.path import visions.backends.python.types.string import visions.backends.python.types.time import visions.backends.python.types.time_delta import visions.backends.python.types.url import visions.backends.python.types.uuid

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7

0bb493e6adea4c87eaaa091c90eb86af14e9db2b

7,496

py

Python

decompress_gnu.py

oppressionslayer/maxentropy

0f00d2ee6733dd4038821abb86490ffb1dd4dac0

[ "MIT" ]

1

2019-09-24T01:09:12.000Z

decompress_gnu.py

oppressionslayer/maxentropy

0f00d2ee6733dd4038821abb86490ffb1dd4dac0

[ "MIT" ]

1

2020-01-17T16:32:09.000Z

decompress_gnu.py

oppressionslayer/maxentropy

0f00d2ee6733dd4038821abb86490ffb1dd4dac0

[ "MIT" ]

null

# Use python3 not python2 # The original is 30533 bytes. # It's the GNU Header repeated 4 times. # The gzip version compressed file is 2872 bytes # the lzma version of our compreesed codes # is 2840 bytes # We use lzma to compress our math operations # to uncompress the GNU Header with better # results than gzip in this case by using # an lzma header to compress our codes. # We are not compressing the file, instead # we are compressing the pattern used for # XOR operations to rebuild the original file # In no way can you uncompress the code # to reproduce the original without using our # math XOR operations. # This is to prove that XOR operations have # repetition on par with the original file # just by compressing the maths logic. # I used gzip as an example as it doesn't # compress repetition as well as other compressors. import lzma # This code uncompresses the math required to rebuild a GNU licence that is repeated 4 times. code='fd377a585a000004e6d6b4460200210116000000742fe5a3e077450ad55d0000953185805d1e19050eb115bdd0f560d3516fc2a4d1f9603d38f615e4012ce3d463f56b72f09dcfe8746a3c95e5d95ba427f711d2e70cebbdda888a340eb8acb2dfcff6381b49d185051e595a1aec163eaf70cab9b67d9f953d62d5f99b4757434dbf72dbf14e5ca7c1f786a2e245f7b8969bd8232b9f5c48b3a6ef37c33ab46d89c67ddc793c8b1c9bd62219ce9f0fe529d33776e714c707db01084a93a26d14bdd331f8e46000d7356c29ca8214691a605586a6e24d53488d4de3de87f0487ff372d0f3a8c292547d1337ae8d133072f855deb17d9534c1d1fa20e5d6f3eeb4a5bdae17f898f3c2669cbe564f0e21f94c063e88edfaa21a6c4552350771b789d7fea56c9d100f8feb513e578aabc70a813870eb17c3da76c8420480fdcd8fd1025cfb090629e1f455bd99c906c97b5dc40f9ce3d5b9fd6752f4090106ff64d24be55338ff33c7af686981b0cf8b29a9db092016d8f971feb8f4c7a28ecb7413c6dee182b76b85b9a2e2574fedce00fdb9f5795934cd0f12c9194c20b6181cbe56764dac2ebaa184f738dd4c640546bbcef1288119d105ff29d1caf90144b82b8d13430b0f7bc02b934b24edc0d1b9d39e6e68e9c4727787f713eeebf73bf7c14cc91ce3279e80fcb5d97869201f89bd689f32644f1ecc437126e741e0d255e0236b0ff044b8c8f19eaab2f8931e057e61253d781c8a895f19d3e4bfdca1480eb25ecf5fe0b9226ef5a9ec3bbc5daa2a632f8ec36e66b1fad219adb2b7e4fb3f94ae725b36c4a1d3df3dcccc3cda58c1d428b10d6db6e94dbb5925a5cb5f8684a4b8754f6995f379f4fb0e5bd85aab83c66dea1fe8fb8ae69fc275b06e1f5d325a0d6f8b910cb50fbb0cdfec39111f8d48a2bcb218f4c1831e12ef0ec2e436c63555b6ce710cd4fb9598bb2d66eb733456187394c97462be70e7dc48a94df8f0e61b84f6ca558034ef2ac021bef029f27b3ed75b1514fb9ca5072a02e759ff7a1ba4d916b6e77d72e5cb0a49fb9bf856f4a6df9e2f7ec16e92a4442e60a9838be2757bc54fc4ee7dc687cf11f7a3c410cf536fb20474bba282c74622a27d49013ed387f0e59fb1b9699d73a279bdb5d4716be8fbe062aa5bc330f901bb474836632bc3f8370f3c754578d4d107be8b31870c5914701300e7d62bb243ad46dc7786b9ded96e3e8a36aa2aaaf77f79683b9b1179d2e9e623eda2657563fab531b523dc54d74de6a27a90cc6c87aaab1c03ed9bb69586d198be4080a6ad88d485b33cfc3b203e853fcbe000265681efafe50262f1685ecbad4c0f9e8fca72f92a826a033623af98fa6b9fc4007b2f3b2ee1b2f608d95039b6e0608839c957569ba6120dcc5110c79e7f3fb474f70f9a92d505fdede096333a9c3173884b8488ac1b0c12f57a2db90ecb1639c90004e5d59e3f5e0b45d6a29606f06622047e56b40ee8c959766fbd633b4d8549b75cb287af9515facebb6f4a57a1d6cebcb2ffbe7ae999e5d109096c0777034f5b7ea96b92e75e03457c0618785f2e0091d1e44be7ed7142e988e9694fbf81892c3cc1c7670900396d3a8bdef2494fcef9afe623b94a0d067354da3a4377fadd1e72480a55184bb182b2569b9dfa7c5d59c1d72c93b4e39d2e3055d3670a74669f02b2814d9608ae888dfe9707b1461f195d1e85a87a1eb4b5228a37ec1990ffa54f310f9732cfb789582304654d2f97c596d77d812cd42797992b6d87f395f8bb23235e1af668e72bb1a5d4668e7e59672aba817446379a3cabe3797ac1abcc7dad53b22d4ea4a3c71a491d88bd49e7c472b5e20f149c5ab69708bee8149c2583f93334e54132e18711fb3f59f8df1f4f5671ce0dcb54b8b45d9ef5097dd8630115b4f44352aefd73ca8a051536bdb4fcfdfaf1062e16d6c92266a056951d7799bea9b46d79a0c602fb3136450ba9e1a2a4a09490f388d3ffab52a22e66f82d106a91412f10a283a697eac2a7c3c0bb31ace9d1202c3d716d7ab666669d4880b72c7724faff0ccdf6908e48914f4642dfb6f9732cc2cf5331333e59e8f60d861dc531f846e4ae2f6944d523f5d06ab444d45b55f3d9771a1f395b9ba0edb93f868cdb2f15c3e7cb662fe6e62c76843afb329c517676a82b3d5e644df8671f5aa0478372125b6cb8648c34393186582eba5fd62984144d35ba074046fd52a187ef17a5915c2a5cbf90816678bfaff5bf21d2398c72e8183b4ed5c327010adbe0a6ef20f2938f5ac118b5f0f65ea32c40e73384d7dae11b816bbcfbacbb1db75cbef17c43333917067245232a9efa6984c612c7e415c71a5aa7109b5674eec99f07164ceba3b8cbf8fdfadf324b5acf89811aef310308588447442a083a8eea2bb7060e89ab438c4f76178947d9ede21fd2ab327d56c2d6705d41162d8795c1d55146f0bdc9e901981a04cbd8dce76037d9ec27318fe087b73bd0b4b8995513d950ee5cf1691b1c921fcbe69ef951d465bfc91fbd403b4ddb8b228507abdd09fb68cb0d9d1f327dfd3cbcab9e6a72b913d1c49c53f26c09fedd64e86c7c5715cd6820c034690cce9a96a96711556e7573439acd3361c40ebba90d98ebb7286ba1d58fa7bd9eaad3b1b670dd3369ddc719a1b39ef292ccd94fb46e4c674d88e262c597b4bbe201741f334130ba00cd4993c75bf3db75e8e3c703d8d1116f389f1152798ea49eabb3b12b808a238f2722968f28b779d9e5cde734425023c7bdb6d8eb8fc530261da60129bde2fb8c162831648e4ac169a845eec29d3610a5c5f2a62c088e84bb205b484326cc7cd0b0be5de6d4a0587ac00722aafcfe40b16c5f6a062cdd9fe23ec1d413c94fabd3894b5b9dac0e21ca12f25bc767b22724e9cd6499d8fde8aaa20ef6a15af813b3a713df3ee4d8c7f447e625a8af9950a3e8ebcc1139f8ef03c5fe003e5d7ed89096527771033ef945822cf625f703a7f25bb42f492eae542ebd1ec779854189df226d254fd93ee71183cbc3c0e9fc0676e3c6df363a783f3f3eff3d34586728d663334d4347180436c201daf2dfa307dd94a3b66d650c215341a590e77489c8e61439e6d9932b64fbe8292e57ef859204caa4ea5cc477fddefa4eed652c2f587b2909be2d306c176f0a263865b7ded7dcc3e0029f3f990df4e81bd06a189855970886a203fb9c7396eeaf44478ec26c19e7b0592f772d46636422135a7f9df24c5199c1e92a525b90a7666aeed46c59dfb7680d3f0e49c9c1457a322d2d459399810b8de1b6c40c12e64fd679bb58ad99b4329e5a5f45ce69fca80b9105cf857a1403952fbaf32daeb9750c88be3b749efe61b186f35170e72688a478b695319267452cdc4c4e668b53af2c23d5b5b29f3d7260b5a4524f3a9b6baa71c8f4cf7c95eb29050c3916c59d5686ff5919726402f06523674c3b8d1893d98a44154d0d240dd357e0bfd11c724ea9e02abf781230929e440084b94852e9db4fad27f4b8b6ddd5c92933d39470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def decompressmaplzma(code): return bin(int(lzma.decompress(bytes.fromhex(code)).hex(),16))[2:] def decodethebetterstuff(themap): j=0 y=1 for c in range(1,len(themap)): if j < 0: if themap[c] == '0': j^=y else: j^=-y else: if themap[c] == '0': j^=-y else: j^=y y<<=1 answer=((y>>1)-1)-(abs(j)>>1) return answer themap = decompressmaplzma(code) origint = decodethebetterstuff(themap) #print(bytes.fromhex(hex(origint)[2:]).decode()) zzwrite = open('gnu_repeat4.bin', 'wb') zzbytes = bytes.fromhex(code) zzwrite.write(zzbytes) zzwrite.close() zzwrite = open('gnu_repeat4.txt', 'wb') zzbytes = bytes.fromhex(hex(origint)[2:]) zzwrite.write(zzbytes) zzwrite.close() print("") print("gnu_repeat4.txt and gnu_repeat4.bin has been created.")

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8

e7f797f35f57a5e11ff23730a05715efcef45845

1,108

py

Python

alex/resources/asr/voip_cs/kaldi/download_models.py

beka-evature/alex

e8fdc6f2d908d7a1911b18f29c218ae58d19ed6f

[ "Apache-2.0" ]

1

2015-10-19T17:36:27.000Z

alex/resources/asr/voip_cs/kaldi/download_models.py

beka-evature/alex

e8fdc6f2d908d7a1911b18f29c218ae58d19ed6f

[ "Apache-2.0" ]

null

alex/resources/asr/voip_cs/kaldi/download_models.py

beka-evature/alex

e8fdc6f2d908d7a1911b18f29c218ae58d19ed6f

[ "Apache-2.0" ]

null

#!/usr/bin/env python # encoding: utf-8 from alex.utils.config import online_update if __name__ == '__main__': import autopath # Description files online_update('resources/asr/voip_cs/kaldi/results.log') online_update('resources/asr/voip_cs/kaldi/experiment_bash_vars.log') online_update('resources/asr/voip_cs/kaldi/alex_gitlog.log') online_update('resources/asr/voip_cs/kaldi/alex_gitdiff.log') # Models online_update('resources/asr/voip_cs/kaldi/mfcc.conf') online_update('resources/asr/voip_cs/kaldi/phones.txt') online_update('resources/asr/voip_cs/kaldi/silence.csl') online_update('resources/asr/voip_cs/kaldi/tri2a.mdl') online_update('resources/asr/voip_cs/kaldi/tri2a.tree') online_update('resources/asr/voip_cs/kaldi/tri2b.mdl') online_update('resources/asr/voip_cs/kaldi/tri2b.tree') online_update('resources/asr/voip_cs/kaldi/tri2b.mat') online_update('resources/asr/voip_cs/kaldi/tri2b_bmmi.mdl') online_update('resources/asr/voip_cs/kaldi/tri2b_bmmi.tree') online_update('resources/asr/voip_cs/kaldi/tri2b_bmmi.mat')

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Python

CodeWars/7 Kyu/Moves in squared strings (I).py

anubhab-code/Competitive-Programming

de28cb7d44044b9e7d8bdb475da61e37c018ac35

[ "MIT" ]

null

CodeWars/7 Kyu/Moves in squared strings (I).py

anubhab-code/Competitive-Programming

de28cb7d44044b9e7d8bdb475da61e37c018ac35

[ "MIT" ]

null

CodeWars/7 Kyu/Moves in squared strings (I).py

anubhab-code/Competitive-Programming

de28cb7d44044b9e7d8bdb475da61e37c018ac35

[ "MIT" ]

null

def vert_mirror(strng): return "\n".join(w[::-1] for w in strng.split("\n")) def hor_mirror(strng): return "\n".join(strng.split("\n")[::-1]) def oper(fct, strng): return fct(strng)

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py

Python

GUI/PyQt/utils/Training_Test_Split.py

thomaskuestner/CNNArt

c2fc639dd2ce035f6ca90113290682a0ccd26fb8

[ "Apache-2.0" ]

22

2018-04-27T21:28:46.000Z

2021-12-24T06:44:55.000Z

GUI/PyQt/utils/Training_Test_Split.py

thomaskuestner/CNNArt

c2fc639dd2ce035f6ca90113290682a0ccd26fb8

[ "Apache-2.0" ]

81

2017-11-09T17:23:15.000Z

2020-01-28T22:54:13.000Z

GUI/PyQt/utils/Training_Test_Split.py

thomaskuestner/CNNArt

c2fc639dd2ce035f6ca90113290682a0ccd26fb8

[ "Apache-2.0" ]

18

2017-11-13T16:12:17.000Z

2020-08-27T10:17:34.000Z

# -*- coding: utf-8 -*- """ Created on Thu Mar 02 15:59:36 2017 @author: Sebastian Milde, Thomas Kuestner """ import dis import inspect import math import numpy as np from sklearn.model_selection import KFold from DLart.Constants_DLart import * def expecting(): """Return how many values the caller is expecting""" f = inspect.currentframe() f = f.f_back.f_back c = f.f_code i = f.f_lasti bytecode = c.co_code instruction = bytecode[i + 3] if instruction == dis.opmap['UNPACK_SEQUENCE']: howmany = bytecode[i + 4] return howmany elif instruction == dis.opmap['POP_TOP']: return 0 return 1 def fSplitDataset(allPatches, allY, allPats, sSplitting, patchSize, patchOverlap, testTrainingDatasetRatio=0, validationTrainRatio=0, outPutPath=None, nfolds=0, isRandomShuffle=True): # TODO: adapt path iReturn = expecting() # iReturn = 1000 # 2D or 3D patching? if len(patchSize) == 2: # 2D patches are used if allPatches.shape[0] == patchSize[0] and allPatches.shape[1] == patchSize[1]: allPatches = np.transpose(allPatches, (2, 0, 1)) elif len(patchSize) == 3: # 3D patches are used if allPatches.shape[0] == patchSize[0] and allPatches.shape[1] == patchSize[1] and allPatches.shape[2] == \ patchSize[2]: allPatches = np.transpose(allPatches, (3, 0, 1, 2)) if sSplitting == SIMPLE_RANDOM_SAMPLE_SPLITTING: # splitting indexSlices = range(allPatches.shape[0]) if isRandomShuffle: indexSlices = np.random.permutation(indexSlices) if len(patchSize) == 2: # 2D patching allPatches = allPatches[indexSlices, :, :] elif len(patchSize) == 3: # 3D patching allPatches = allPatches[indexSlices, :, :, :] shapeAllY = allY.shape if len(shapeAllY) > 1: if allY.shape[0] == patchSize[0] and allY.shape[1] == patchSize[1]: allY = np.transpose(allY, (2, 0, 1)) allY = allY[indexSlices] # num of samples in test set and validation set numAllPatches = allPatches.shape[0] numSamplesTest = math.floor(testTrainingDatasetRatio * numAllPatches) numSamplesValidation = math.floor(validationTrainRatio * (numAllPatches - numSamplesTest)) if len(patchSize) == 2: # 2D patching # subarrays as no-copy views (array slices) X_test = allPatches[:numSamplesTest, :, :] X_valid = allPatches[numSamplesTest:(numSamplesTest + numSamplesValidation), :, :] X_train = allPatches[(numSamplesTest + numSamplesValidation):, :, :] elif len(patchSize) == 3: # 3D patching # subarrays as no-copy views (array slices) X_test = allPatches[:numSamplesTest, :, :, :] X_valid = allPatches[numSamplesTest:(numSamplesTest + numSamplesValidation), :, :, :] X_train = allPatches[(numSamplesTest + numSamplesValidation):, :, :, :] y_test = allY[:numSamplesTest] y_valid = allY[numSamplesTest:(numSamplesTest + numSamplesValidation)] y_train = allY[(numSamplesTest + numSamplesValidation):] return [X_train], [y_train], [X_valid], [y_valid], [X_test], [y_test] # embed in a 1-fold list elif sSplitting == CROSS_VALIDATION_SPLITTING: # split into test/train sets # shuffle indexSlices = range(allPatches.shape[0]) indexSlices = np.random.permutation(indexSlices) allPatches = allPatches[indexSlices, :, :] allY = allY[indexSlices] # num of samples in test set numAllPatches = allPatches.shape[0] numSamplesTest = math.floor(testTrainingDatasetRatio * numAllPatches) # subarrays as no-copy views (array slices) xTest = allPatches[:numSamplesTest, :, :] yTest = allY[:numSamplesTest] xTrain = allPatches[numSamplesTest:, :, :] yTrain = allY[numSamplesTest:] # split training dataset into n folds if nfolds == 0: kf = KFold(n_splits=len(allPats)) else: kf = KFold(n_splits=nfolds) ind_split = 0 X_trainFold = [] X_testFold = [] y_trainFold = [] y_testFold = [] for train_index, test_index in kf.split(xTrain): X_train, X_test = xTrain[train_index], xTrain[test_index] y_train, y_test = yTrain[train_index], yTrain[test_index] X_trainFold.append(X_train) X_testFold.append(X_test) y_trainFold.append(y_train) y_testFold.append(y_test) ind_split += 1 X_trainFold = np.asarray(X_trainFold) X_testFold = np.asarray(X_testFold) y_trainFold = np.asarray(y_trainFold) y_testFold = np.asarray(y_testFold) return [X_trainFold], [y_trainFold], [X_testFold], [y_testFold], [xTest], [yTest] elif sSplitting == PATIENT_CROSS_VALIDATION_SPLITTING: unique_pats = len(allPats) X_trainFold = [] X_testFold = [] y_trainFold = [] y_testFold = [] for ind_split in range(unique_pats): train_index = np.where(allPats != ind_split)[0] test_index = np.where(allPats == ind_split)[0] X_train, X_test = allPatches[train_index], allPatches[test_index] y_train, y_test = allY[train_index], allY[test_index] X_trainFold.append(X_train) X_testFold.append(X_test) y_trainFold.append(y_train) y_testFold.append(y_test) X_trainFold = np.asarray(X_trainFold, dtype='f') X_testFold = np.asarray(X_testFold, dtype='f') y_trainFold = np.asarray(y_trainFold, dtype='f') y_testFold = np.asarray(y_testFold, dtype='f') X_valFold = np.asarray([]) y_valFold = np.asarray([]) if iReturn > 0: return [X_trainFold], [y_trainFold], [X_valFold], [y_valFold], [X_testFold], [y_testFold] def fSplitSegmentationDataset(allPatches, allY, allSegmentationMasks, allPats, sSplitting, patchSize, patchOverlap, testTrainingDatasetRatio=0, validationTrainRatio=0, outPutPath=None, nfolds=0, isRandomShuffle=True): # TODO: adapt path iReturn = expecting() # iReturn = 1000 # 2D or 3D patching? if len(patchSize) == 2: # 2D patches are used if allPatches.shape[0] == patchSize[0] and allPatches.shape[1] == patchSize[1]: allPatches = np.transpose(allPatches, (2, 0, 1)) allSegmentationMasks = np.transpose(allSegmentationMasks, (2, 0, 1)) elif len(patchSize) == 3: # 3D patches are used if allPatches.shape[0] == patchSize[0] and allPatches.shape[1] == patchSize[1] and allPatches.shape[2] == \ patchSize[2]: allPatches = np.transpose(allPatches, (3, 0, 1, 2)) allSegmentationMasks = np.transpose(allSegmentationMasks, (3, 0, 1, 2)) if sSplitting == SIMPLE_RANDOM_SAMPLE_SPLITTING: # splitting indexSlices = range(allPatches.shape[0]) if isRandomShuffle: indexSlices = np.random.permutation(indexSlices) if len(patchSize) == 2: # 2D patching allPatches = allPatches[indexSlices, :, :] allSegmentationMasks = allSegmentationMasks[indexSlices, :, :] elif len(patchSize) == 3: # 3D patching allPatches = allPatches[indexSlices, :, :, :] allSegmentationMasks = allSegmentationMasks[indexSlices, :, :, :] shapeAllY = allY.shape if len(shapeAllY) > 1: if allY.shape[0] == patchSize[0] and allY.shape[1] == patchSize[1]: allY = np.transpose(allY, (2, 0, 1)) allY = allY[indexSlices] # num of samples in test set and validation set numAllPatches = allPatches.shape[0] numSamplesTest = math.floor(testTrainingDatasetRatio * numAllPatches) numSamplesValidation = math.floor(validationTrainRatio * (numAllPatches - numSamplesTest)) if len(patchSize) == 2: # 2D patching # subarrays as no-copy views (array slices) X_test = allPatches[:numSamplesTest, :, :] Y_segMasks_test = allSegmentationMasks[:numSamplesTest, :, :] X_valid = allPatches[numSamplesTest:(numSamplesTest + numSamplesValidation), :, :] Y_segMasks_valid = allSegmentationMasks[numSamplesTest:(numSamplesTest + numSamplesValidation), :, :] X_train = allPatches[(numSamplesTest + numSamplesValidation):, :, :] Y_segMasks_train = allSegmentationMasks[(numSamplesTest + numSamplesValidation):, :, :] elif len(patchSize) == 3: # 3D patching # subarrays as no-copy views (array slices) X_test = allPatches[:numSamplesTest, :, :, :] Y_segMasks_test = allSegmentationMasks[:numSamplesTest, :, :, :] X_valid = allPatches[numSamplesTest:(numSamplesTest + numSamplesValidation), :, :, :] Y_segMasks_valid = allSegmentationMasks[numSamplesTest:(numSamplesTest + numSamplesValidation), :, :, :] X_train = allPatches[(numSamplesTest + numSamplesValidation):, :, :, :] Y_segMasks_train = allSegmentationMasks[(numSamplesTest + numSamplesValidation):, :, :, :] y_test = allY[:numSamplesTest] y_valid = allY[numSamplesTest:(numSamplesTest + numSamplesValidation)] y_train = allY[(numSamplesTest + numSamplesValidation):] return [X_train], [y_train], [Y_segMasks_train], [X_valid], [y_valid], [Y_segMasks_valid], [X_test], [ y_test], [Y_segMasks_test] # embed in a 1-fold list elif sSplitting == CROSS_VALIDATION_SPLITTING: # split into test/train sets # shuffle indexSlices = range(allPatches.shape[0]) indexSlices = np.random.permutation(indexSlices) allPatches = allPatches[indexSlices, :, :] allY = allY[indexSlices] # num of samples in test set numAllPatches = allPatches.shape[0] numSamplesTest = math.floor(testTrainingDatasetRatio * numAllPatches) # subarrays as no-copy views (array slices) xTest = allPatches[:numSamplesTest, :, :] yTest = allY[:numSamplesTest] xTrain = allPatches[numSamplesTest:, :, :] yTrain = allY[numSamplesTest:] # split training dataset into n folds if nfolds == 0: kf = KFold(n_splits=len(allPats)) else: kf = KFold(n_splits=nfolds) ind_split = 0 X_trainFold = [] X_testFold = [] y_trainFold = [] y_testFold = [] for train_index, test_index in kf.split(xTrain): X_train, X_test = xTrain[train_index], xTrain[test_index] y_train, y_test = yTrain[train_index], yTrain[test_index] X_trainFold.append(X_train) X_testFold.append(X_test) y_trainFold.append(y_train) y_testFold.append(y_test) ind_split += 1 X_trainFold = np.asarray(X_trainFold) X_testFold = np.asarray(X_testFold) y_trainFold = np.asarray(y_trainFold) y_testFold = np.asarray(y_testFold) return [X_trainFold], [y_trainFold], [X_testFold], [y_testFold], [xTest], [yTest] elif sSplitting == PATIENT_CROSS_VALIDATION_SPLITTING: unique_pats = len(allPats) X_trainFold = [] X_testFold = [] y_trainFold = [] y_testFold = [] for ind_split in range(unique_pats): train_index = np.where(allPats != ind_split)[0] test_index = np.where(allPats == ind_split)[0] X_train, X_test = allPatches[train_index], allPatches[test_index] y_train, y_test = allY[train_index], allY[test_index] X_trainFold.append(X_train) X_testFold.append(X_test) y_trainFold.append(y_train) y_testFold.append(y_test) X_trainFold = np.asarray(X_trainFold, dtype='f') X_testFold = np.asarray(X_testFold, dtype='f') y_trainFold = np.asarray(y_trainFold, dtype='f') y_testFold = np.asarray(y_testFold, dtype='f') X_valFold = np.asarray([]) y_valFold = np.asarray([]) if iReturn > 0: return [X_trainFold], [y_trainFold], [X_valFold], [y_valFold], [X_testFold], [y_testFold] def TransformDataset(allPatches, allY, patchSize, patchOverlap, isRandomShuffle=True, isUsingSegmentation=False, allSegmentationMasks=None): if len(patchSize) == 2: # 2D patches are used if allPatches.shape[0] == patchSize[0] and allPatches.shape[1] == patchSize[1]: allPatches = np.transpose(allPatches, (2, 0, 1)) if isUsingSegmentation: allSegmentationMasks = np.transpose(allSegmentationMasks, (2, 0, 1)) elif len(patchSize) == 3: # 3D patches are used if allPatches.shape[0] == patchSize[0] and allPatches.shape[1] == patchSize[1] and allPatches.shape[2] == \ patchSize[2]: allPatches = np.transpose(allPatches, (3, 0, 1, 2)) if isUsingSegmentation: allSegmentationMasks = np.transpose(allSegmentationMasks, (3, 0, 1, 2)) indexSlices = range(allPatches.shape[0]) if isRandomShuffle: indexSlices = np.random.permutation(indexSlices) if len(patchSize) == 2: # 2D patching allPatches = allPatches[indexSlices, :, :] if isUsingSegmentation: allSegmentationMasks = allSegmentationMasks[indexSlices, :, :] elif len(patchSize) == 3: # 3D patching allPatches = allPatches[indexSlices, :, :, :] if isUsingSegmentation: allSegmentationMasks = allSegmentationMasks[indexSlices, :, :, :] shapeAllY = allY.shape if len(shapeAllY) > 1: if allY.shape[0] == patchSize[0] and allY.shape[1] == patchSize[1]: allY = np.transpose(allY, (2, 0, 1)) allY = allY[indexSlices] X_data = allPatches if isUsingSegmentation: Y_segMasks_data = allSegmentationMasks y_data = allY if isUsingSegmentation: return [X_data], [y_data], [Y_segMasks_data] else: return [X_data], [y_data]

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f07cf14135a8d2bdbfaf33a33a53dc4f17a3d911

37,155

py

Python

ingenico/connect/sdk/merchant/payments/payments_client.py

festicket/connect-sdk-python3

c399c6443789dd978f319c89e1ebd387c812a77b

[ "MIT" ]

12

2016-09-26T21:46:31.000Z

2020-12-23T18:44:54.000Z

ingenico/connect/sdk/merchant/payments/payments_client.py

festicket/connect-sdk-python3

c399c6443789dd978f319c89e1ebd387c812a77b

[ "MIT" ]

3

2020-05-02T16:53:02.000Z

2020-06-02T12:49:51.000Z

ingenico/connect/sdk/merchant/payments/payments_client.py

festicket/connect-sdk-python3

c399c6443789dd978f319c89e1ebd387c812a77b

[ "MIT" ]

11

2017-07-16T00:55:28.000Z

2021-09-24T17:00:49.000Z

# # This class was auto-generated from the API references found at # https://epayments-api.developer-ingenico.com/s2sapi/v1/ # from ingenico.connect.sdk.api_resource import ApiResource from ingenico.connect.sdk.response_exception import ResponseException from ingenico.connect.sdk.domain.capture.capture_response import CaptureResponse from ingenico.connect.sdk.domain.capture.captures_response import CapturesResponse from ingenico.connect.sdk.domain.dispute.dispute_response import DisputeResponse from ingenico.connect.sdk.domain.dispute.disputes_response import DisputesResponse from ingenico.connect.sdk.domain.errors.error_response import ErrorResponse from ingenico.connect.sdk.domain.payment.cancel_approval_payment_response import CancelApprovalPaymentResponse from ingenico.connect.sdk.domain.payment.cancel_payment_response import CancelPaymentResponse from ingenico.connect.sdk.domain.payment.complete_payment_response import CompletePaymentResponse from ingenico.connect.sdk.domain.payment.create_payment_response import CreatePaymentResponse from ingenico.connect.sdk.domain.payment.device_fingerprint_details import DeviceFingerprintDetails from ingenico.connect.sdk.domain.payment.find_payments_response import FindPaymentsResponse from ingenico.connect.sdk.domain.payment.payment_approval_response import PaymentApprovalResponse from ingenico.connect.sdk.domain.payment.payment_error_response import PaymentErrorResponse from ingenico.connect.sdk.domain.payment.payment_response import PaymentResponse from ingenico.connect.sdk.domain.payment.third_party_status_response import ThirdPartyStatusResponse from ingenico.connect.sdk.domain.refund.refund_error_response import RefundErrorResponse from ingenico.connect.sdk.domain.refund.refund_response import RefundResponse from ingenico.connect.sdk.domain.refund.refunds_response import RefundsResponse from ingenico.connect.sdk.domain.token.create_token_response import CreateTokenResponse class PaymentsClient(ApiResource): """ Payments client. Thread-safe. """ def __init__(self, parent, path_context): """ :param parent: :class:`ingenico.connect.sdk.api_resource.ApiResource` :param path_context: dict[str, str] """ super(PaymentsClient, self).__init__(parent, path_context) def create(self, body, context=None): """ Resource /{merchantId}/payments - Create payment See also https://epayments-api.developer-ingenico.com/s2sapi/v1/en_US/python/payments/create.html :param body: :class:`ingenico.connect.sdk.domain.payment.create_payment_request.CreatePaymentRequest` :param context: :class:`ingenico.connect.sdk.call_context.CallContext` :return: :class:`ingenico.connect.sdk.domain.payment.create_payment_response.CreatePaymentResponse` :raise: DeclinedPaymentException if the Ingenico ePayments platform declined / rejected the payment. The payment result will be available from the exception. :raise: ValidationException if the request was not correct and couldn't be processed (HTTP status code 400) :raise: AuthorizationException if the request was not allowed (HTTP status code 403) :raise: ReferenceException if an object was attempted to be referenced that doesn't exist or has been removed, or there was a conflict (HTTP status code 404, 409 or 410) :raise: GlobalCollectException if something went wrong at the Ingenico ePayments platform, the Ingenico ePayments platform was unable to process a message from a downstream partner/acquirer, or the service that you're trying to reach is temporary unavailable (HTTP status code 500, 502 or 503) :raise: ApiException if the Ingenico ePayments platform returned any other error """ uri = self._instantiate_uri("/v1/{merchantId}/payments", None) try: return self._communicator.post( uri, self._client_headers, None, body, CreatePaymentResponse, context) except ResponseException as e: error_type = PaymentErrorResponse error_object = self._communicator.marshaller.unmarshal(e.body, error_type) raise self._create_exception(e.status_code, e.body, error_object, context) def find(self, query, context=None): """ Resource /{merchantId}/payments - Find payments See also https://epayments-api.developer-ingenico.com/s2sapi/v1/en_US/python/payments/find.html :param query: :class:`ingenico.connect.sdk.merchant.payments.find_payments_params.FindPaymentsParams` :param context: :class:`ingenico.connect.sdk.call_context.CallContext` :return: :class:`ingenico.connect.sdk.domain.payment.find_payments_response.FindPaymentsResponse` :raise: ValidationException if the request was not correct and couldn't be processed (HTTP status code 400) :raise: AuthorizationException if the request was not allowed (HTTP status code 403) :raise: ReferenceException if an object was attempted to be referenced that doesn't exist or has been removed, or there was a conflict (HTTP status code 404, 409 or 410) :raise: GlobalCollectException if something went wrong at the Ingenico ePayments platform, the Ingenico ePayments platform was unable to process a message from a downstream partner/acquirer, or the service that you're trying to reach is temporary unavailable (HTTP status code 500, 502 or 503) :raise: ApiException if the Ingenico ePayments platform returned any other error """ uri = self._instantiate_uri("/v1/{merchantId}/payments", None) try: return self._communicator.get( uri, self._client_headers, query, FindPaymentsResponse, context) except ResponseException as e: error_type = ErrorResponse error_object = self._communicator.marshaller.unmarshal(e.body, error_type) raise self._create_exception(e.status_code, e.body, error_object, context) def get(self, payment_id, context=None): """ Resource /{merchantId}/payments/{paymentId} - Get payment See also https://epayments-api.developer-ingenico.com/s2sapi/v1/en_US/python/payments/get.html :param payment_id: str :param context: :class:`ingenico.connect.sdk.call_context.CallContext` :return: :class:`ingenico.connect.sdk.domain.payment.payment_response.PaymentResponse` :raise: ValidationException if the request was not correct and couldn't be processed (HTTP status code 400) :raise: AuthorizationException if the request was not allowed (HTTP status code 403) :raise: ReferenceException if an object was attempted to be referenced that doesn't exist or has been removed, or there was a conflict (HTTP status code 404, 409 or 410) :raise: GlobalCollectException if something went wrong at the Ingenico ePayments platform, the Ingenico ePayments platform was unable to process a message from a downstream partner/acquirer, or the service that you're trying to reach is temporary unavailable (HTTP status code 500, 502 or 503) :raise: ApiException if the Ingenico ePayments platform returned any other error """ path_context = { "paymentId": payment_id, } uri = self._instantiate_uri("/v1/{merchantId}/payments/{paymentId}", path_context) try: return self._communicator.get( uri, self._client_headers, None, PaymentResponse, context) except ResponseException as e: error_type = ErrorResponse error_object = self._communicator.marshaller.unmarshal(e.body, error_type) raise self._create_exception(e.status_code, e.body, error_object, context) def complete(self, payment_id, body, context=None): """ Resource /{merchantId}/payments/{paymentId}/complete - Complete payment See also https://epayments-api.developer-ingenico.com/s2sapi/v1/en_US/python/payments/complete.html :param payment_id: str :param body: :class:`ingenico.connect.sdk.domain.payment.complete_payment_request.CompletePaymentRequest` :param context: :class:`ingenico.connect.sdk.call_context.CallContext` :return: :class:`ingenico.connect.sdk.domain.payment.complete_payment_response.CompletePaymentResponse` :raise: ValidationException if the request was not correct and couldn't be processed (HTTP status code 400) :raise: AuthorizationException if the request was not allowed (HTTP status code 403) :raise: ReferenceException if an object was attempted to be referenced that doesn't exist or has been removed, or there was a conflict (HTTP status code 404, 409 or 410) :raise: GlobalCollectException if something went wrong at the Ingenico ePayments platform, the Ingenico ePayments platform was unable to process a message from a downstream partner/acquirer, or the service that you're trying to reach is temporary unavailable (HTTP status code 500, 502 or 503) :raise: ApiException if the Ingenico ePayments platform returned any other error """ path_context = { "paymentId": payment_id, } uri = self._instantiate_uri("/v1/{merchantId}/payments/{paymentId}/complete", path_context) try: return self._communicator.post( uri, self._client_headers, None, body, CompletePaymentResponse, context) except ResponseException as e: error_type = ErrorResponse error_object = self._communicator.marshaller.unmarshal(e.body, error_type) raise self._create_exception(e.status_code, e.body, error_object, context) def third_party_status(self, payment_id, context=None): """ Resource /{merchantId}/payments/{paymentId}/thirdpartystatus - Third party status poll See also https://epayments-api.developer-ingenico.com/s2sapi/v1/en_US/python/payments/thirdPartyStatus.html :param payment_id: str :param context: :class:`ingenico.connect.sdk.call_context.CallContext` :return: :class:`ingenico.connect.sdk.domain.payment.third_party_status_response.ThirdPartyStatusResponse` :raise: ValidationException if the request was not correct and couldn't be processed (HTTP status code 400) :raise: AuthorizationException if the request was not allowed (HTTP status code 403) :raise: ReferenceException if an object was attempted to be referenced that doesn't exist or has been removed, or there was a conflict (HTTP status code 404, 409 or 410) :raise: GlobalCollectException if something went wrong at the Ingenico ePayments platform, the Ingenico ePayments platform was unable to process a message from a downstream partner/acquirer, or the service that you're trying to reach is temporary unavailable (HTTP status code 500, 502 or 503) :raise: ApiException if the Ingenico ePayments platform returned any other error """ path_context = { "paymentId": payment_id, } uri = self._instantiate_uri("/v1/{merchantId}/payments/{paymentId}/thirdpartystatus", path_context) try: return self._communicator.get( uri, self._client_headers, None, ThirdPartyStatusResponse, context) except ResponseException as e: error_type = ErrorResponse error_object = self._communicator.marshaller.unmarshal(e.body, error_type) raise self._create_exception(e.status_code, e.body, error_object, context) def tokenize(self, payment_id, body, context=None): """ Resource /{merchantId}/payments/{paymentId}/tokenize - Create a token from payment See also https://epayments-api.developer-ingenico.com/s2sapi/v1/en_US/python/payments/tokenize.html :param payment_id: str :param body: :class:`ingenico.connect.sdk.domain.payment.tokenize_payment_request.TokenizePaymentRequest` :param context: :class:`ingenico.connect.sdk.call_context.CallContext` :return: :class:`ingenico.connect.sdk.domain.token.create_token_response.CreateTokenResponse` :raise: ValidationException if the request was not correct and couldn't be processed (HTTP status code 400) :raise: AuthorizationException if the request was not allowed (HTTP status code 403) :raise: ReferenceException if an object was attempted to be referenced that doesn't exist or has been removed, or there was a conflict (HTTP status code 404, 409 or 410) :raise: GlobalCollectException if something went wrong at the Ingenico ePayments platform, the Ingenico ePayments platform was unable to process a message from a downstream partner/acquirer, or the service that you're trying to reach is temporary unavailable (HTTP status code 500, 502 or 503) :raise: ApiException if the Ingenico ePayments platform returned any other error """ path_context = { "paymentId": payment_id, } uri = self._instantiate_uri("/v1/{merchantId}/payments/{paymentId}/tokenize", path_context) try: return self._communicator.post( uri, self._client_headers, None, body, CreateTokenResponse, context) except ResponseException as e: error_type = ErrorResponse error_object = self._communicator.marshaller.unmarshal(e.body, error_type) raise self._create_exception(e.status_code, e.body, error_object, context) def processchallenged(self, payment_id, context=None): """ Resource /{merchantId}/payments/{paymentId}/processchallenged - Approves challenged payment See also https://epayments-api.developer-ingenico.com/s2sapi/v1/en_US/python/payments/processchallenged.html :param payment_id: str :param context: :class:`ingenico.connect.sdk.call_context.CallContext` :return: :class:`ingenico.connect.sdk.domain.payment.payment_response.PaymentResponse` :raise: ValidationException if the request was not correct and couldn't be processed (HTTP status code 400) :raise: AuthorizationException if the request was not allowed (HTTP status code 403) :raise: ReferenceException if an object was attempted to be referenced that doesn't exist or has been removed, or there was a conflict (HTTP status code 404, 409 or 410) :raise: GlobalCollectException if something went wrong at the Ingenico ePayments platform, the Ingenico ePayments platform was unable to process a message from a downstream partner/acquirer, or the service that you're trying to reach is temporary unavailable (HTTP status code 500, 502 or 503) :raise: ApiException if the Ingenico ePayments platform returned any other error """ path_context = { "paymentId": payment_id, } uri = self._instantiate_uri("/v1/{merchantId}/payments/{paymentId}/processchallenged", path_context) try: return self._communicator.post( uri, self._client_headers, None, None, PaymentResponse, context) except ResponseException as e: error_type = ErrorResponse error_object = self._communicator.marshaller.unmarshal(e.body, error_type) raise self._create_exception(e.status_code, e.body, error_object, context) def approve(self, payment_id, body, context=None): """ Resource /{merchantId}/payments/{paymentId}/approve - Approve payment See also https://epayments-api.developer-ingenico.com/s2sapi/v1/en_US/python/payments/approve.html :param payment_id: str :param body: :class:`ingenico.connect.sdk.domain.payment.approve_payment_request.ApprovePaymentRequest` :param context: :class:`ingenico.connect.sdk.call_context.CallContext` :return: :class:`ingenico.connect.sdk.domain.payment.payment_approval_response.PaymentApprovalResponse` :raise: ValidationException if the request was not correct and couldn't be processed (HTTP status code 400) :raise: AuthorizationException if the request was not allowed (HTTP status code 403) :raise: ReferenceException if an object was attempted to be referenced that doesn't exist or has been removed, or there was a conflict (HTTP status code 404, 409 or 410) :raise: GlobalCollectException if something went wrong at the Ingenico ePayments platform, the Ingenico ePayments platform was unable to process a message from a downstream partner/acquirer, or the service that you're trying to reach is temporary unavailable (HTTP status code 500, 502 or 503) :raise: ApiException if the Ingenico ePayments platform returned any other error """ path_context = { "paymentId": payment_id, } uri = self._instantiate_uri("/v1/{merchantId}/payments/{paymentId}/approve", path_context) try: return self._communicator.post( uri, self._client_headers, None, body, PaymentApprovalResponse, context) except ResponseException as e: error_type = ErrorResponse error_object = self._communicator.marshaller.unmarshal(e.body, error_type) raise self._create_exception(e.status_code, e.body, error_object, context) def capture(self, payment_id, body, context=None): """ Resource /{merchantId}/payments/{paymentId}/capture - Capture payment See also https://epayments-api.developer-ingenico.com/s2sapi/v1/en_US/python/payments/capture.html :param payment_id: str :param body: :class:`ingenico.connect.sdk.domain.payment.capture_payment_request.CapturePaymentRequest` :param context: :class:`ingenico.connect.sdk.call_context.CallContext` :return: :class:`ingenico.connect.sdk.domain.capture.capture_response.CaptureResponse` :raise: ValidationException if the request was not correct and couldn't be processed (HTTP status code 400) :raise: AuthorizationException if the request was not allowed (HTTP status code 403) :raise: ReferenceException if an object was attempted to be referenced that doesn't exist or has been removed, or there was a conflict (HTTP status code 404, 409 or 410) :raise: GlobalCollectException if something went wrong at the Ingenico ePayments platform, the Ingenico ePayments platform was unable to process a message from a downstream partner/acquirer, or the service that you're trying to reach is temporary unavailable (HTTP status code 500, 502 or 503) :raise: ApiException if the Ingenico ePayments platform returned any other error """ path_context = { "paymentId": payment_id, } uri = self._instantiate_uri("/v1/{merchantId}/payments/{paymentId}/capture", path_context) try: return self._communicator.post( uri, self._client_headers, None, body, CaptureResponse, context) except ResponseException as e: error_type = ErrorResponse error_object = self._communicator.marshaller.unmarshal(e.body, error_type) raise self._create_exception(e.status_code, e.body, error_object, context) def cancelapproval(self, payment_id, context=None): """ Resource /{merchantId}/payments/{paymentId}/cancelapproval - Undo capture payment See also https://epayments-api.developer-ingenico.com/s2sapi/v1/en_US/python/payments/cancelapproval.html :param payment_id: str :param context: :class:`ingenico.connect.sdk.call_context.CallContext` :return: :class:`ingenico.connect.sdk.domain.payment.cancel_approval_payment_response.CancelApprovalPaymentResponse` :raise: ValidationException if the request was not correct and couldn't be processed (HTTP status code 400) :raise: AuthorizationException if the request was not allowed (HTTP status code 403) :raise: ReferenceException if an object was attempted to be referenced that doesn't exist or has been removed, or there was a conflict (HTTP status code 404, 409 or 410) :raise: GlobalCollectException if something went wrong at the Ingenico ePayments platform, the Ingenico ePayments platform was unable to process a message from a downstream partner/acquirer, or the service that you're trying to reach is temporary unavailable (HTTP status code 500, 502 or 503) :raise: ApiException if the Ingenico ePayments platform returned any other error """ path_context = { "paymentId": payment_id, } uri = self._instantiate_uri("/v1/{merchantId}/payments/{paymentId}/cancelapproval", path_context) try: return self._communicator.post( uri, self._client_headers, None, None, CancelApprovalPaymentResponse, context) except ResponseException as e: error_type = ErrorResponse error_object = self._communicator.marshaller.unmarshal(e.body, error_type) raise self._create_exception(e.status_code, e.body, error_object, context) def captures(self, payment_id, context=None): """ Resource /{merchantId}/payments/{paymentId}/captures - Get captures of payment See also https://epayments-api.developer-ingenico.com/s2sapi/v1/en_US/python/payments/captures.html :param payment_id: str :param context: :class:`ingenico.connect.sdk.call_context.CallContext` :return: :class:`ingenico.connect.sdk.domain.capture.captures_response.CapturesResponse` :raise: ValidationException if the request was not correct and couldn't be processed (HTTP status code 400) :raise: AuthorizationException if the request was not allowed (HTTP status code 403) :raise: ReferenceException if an object was attempted to be referenced that doesn't exist or has been removed, or there was a conflict (HTTP status code 404, 409 or 410) :raise: GlobalCollectException if something went wrong at the Ingenico ePayments platform, the Ingenico ePayments platform was unable to process a message from a downstream partner/acquirer, or the service that you're trying to reach is temporary unavailable (HTTP status code 500, 502 or 503) :raise: ApiException if the Ingenico ePayments platform returned any other error """ path_context = { "paymentId": payment_id, } uri = self._instantiate_uri("/v1/{merchantId}/payments/{paymentId}/captures", path_context) try: return self._communicator.get( uri, self._client_headers, None, CapturesResponse, context) except ResponseException as e: error_type = ErrorResponse error_object = self._communicator.marshaller.unmarshal(e.body, error_type) raise self._create_exception(e.status_code, e.body, error_object, context) def refund(self, payment_id, body, context=None): """ Resource /{merchantId}/payments/{paymentId}/refund - Create refund See also https://epayments-api.developer-ingenico.com/s2sapi/v1/en_US/python/payments/refund.html :param payment_id: str :param body: :class:`ingenico.connect.sdk.domain.refund.refund_request.RefundRequest` :param context: :class:`ingenico.connect.sdk.call_context.CallContext` :return: :class:`ingenico.connect.sdk.domain.refund.refund_response.RefundResponse` :raise: DeclinedRefundException if the Ingenico ePayments platform declined / rejected the refund. The refund result will be available from the exception. :raise: ValidationException if the request was not correct and couldn't be processed (HTTP status code 400) :raise: AuthorizationException if the request was not allowed (HTTP status code 403) :raise: ReferenceException if an object was attempted to be referenced that doesn't exist or has been removed, or there was a conflict (HTTP status code 404, 409 or 410) :raise: GlobalCollectException if something went wrong at the Ingenico ePayments platform, the Ingenico ePayments platform was unable to process a message from a downstream partner/acquirer, or the service that you're trying to reach is temporary unavailable (HTTP status code 500, 502 or 503) :raise: ApiException if the Ingenico ePayments platform returned any other error """ path_context = { "paymentId": payment_id, } uri = self._instantiate_uri("/v1/{merchantId}/payments/{paymentId}/refund", path_context) try: return self._communicator.post( uri, self._client_headers, None, body, RefundResponse, context) except ResponseException as e: error_type = RefundErrorResponse error_object = self._communicator.marshaller.unmarshal(e.body, error_type) raise self._create_exception(e.status_code, e.body, error_object, context) def refunds(self, payment_id, context=None): """ Resource /{merchantId}/payments/{paymentId}/refunds - Get refunds of payment See also https://epayments-api.developer-ingenico.com/s2sapi/v1/en_US/python/payments/refunds.html :param payment_id: str :param context: :class:`ingenico.connect.sdk.call_context.CallContext` :return: :class:`ingenico.connect.sdk.domain.refund.refunds_response.RefundsResponse` :raise: ValidationException if the request was not correct and couldn't be processed (HTTP status code 400) :raise: AuthorizationException if the request was not allowed (HTTP status code 403) :raise: ReferenceException if an object was attempted to be referenced that doesn't exist or has been removed, or there was a conflict (HTTP status code 404, 409 or 410) :raise: GlobalCollectException if something went wrong at the Ingenico ePayments platform, the Ingenico ePayments platform was unable to process a message from a downstream partner/acquirer, or the service that you're trying to reach is temporary unavailable (HTTP status code 500, 502 or 503) :raise: ApiException if the Ingenico ePayments platform returned any other error """ path_context = { "paymentId": payment_id, } uri = self._instantiate_uri("/v1/{merchantId}/payments/{paymentId}/refunds", path_context) try: return self._communicator.get( uri, self._client_headers, None, RefundsResponse, context) except ResponseException as e: error_type = ErrorResponse error_object = self._communicator.marshaller.unmarshal(e.body, error_type) raise self._create_exception(e.status_code, e.body, error_object, context) def cancel(self, payment_id, context=None): """ Resource /{merchantId}/payments/{paymentId}/cancel - Cancel payment See also https://epayments-api.developer-ingenico.com/s2sapi/v1/en_US/python/payments/cancel.html :param payment_id: str :param context: :class:`ingenico.connect.sdk.call_context.CallContext` :return: :class:`ingenico.connect.sdk.domain.payment.cancel_payment_response.CancelPaymentResponse` :raise: ValidationException if the request was not correct and couldn't be processed (HTTP status code 400) :raise: AuthorizationException if the request was not allowed (HTTP status code 403) :raise: ReferenceException if an object was attempted to be referenced that doesn't exist or has been removed, or there was a conflict (HTTP status code 404, 409 or 410) :raise: GlobalCollectException if something went wrong at the Ingenico ePayments platform, the Ingenico ePayments platform was unable to process a message from a downstream partner/acquirer, or the service that you're trying to reach is temporary unavailable (HTTP status code 500, 502 or 503) :raise: ApiException if the Ingenico ePayments platform returned any other error """ path_context = { "paymentId": payment_id, } uri = self._instantiate_uri("/v1/{merchantId}/payments/{paymentId}/cancel", path_context) try: return self._communicator.post( uri, self._client_headers, None, None, CancelPaymentResponse, context) except ResponseException as e: error_type = ErrorResponse error_object = self._communicator.marshaller.unmarshal(e.body, error_type) raise self._create_exception(e.status_code, e.body, error_object, context) def dispute(self, payment_id, body, context=None): """ Resource /{merchantId}/payments/{paymentId}/dispute - Create dispute See also https://epayments-api.developer-ingenico.com/s2sapi/v1/en_US/python/payments/dispute.html :param payment_id: str :param body: :class:`ingenico.connect.sdk.domain.dispute.create_dispute_request.CreateDisputeRequest` :param context: :class:`ingenico.connect.sdk.call_context.CallContext` :return: :class:`ingenico.connect.sdk.domain.dispute.dispute_response.DisputeResponse` :raise: ValidationException if the request was not correct and couldn't be processed (HTTP status code 400) :raise: AuthorizationException if the request was not allowed (HTTP status code 403) :raise: ReferenceException if an object was attempted to be referenced that doesn't exist or has been removed, or there was a conflict (HTTP status code 404, 409 or 410) :raise: GlobalCollectException if something went wrong at the Ingenico ePayments platform, the Ingenico ePayments platform was unable to process a message from a downstream partner/acquirer, or the service that you're trying to reach is temporary unavailable (HTTP status code 500, 502 or 503) :raise: ApiException if the Ingenico ePayments platform returned any other error """ path_context = { "paymentId": payment_id, } uri = self._instantiate_uri("/v1/{merchantId}/payments/{paymentId}/dispute", path_context) try: return self._communicator.post( uri, self._client_headers, None, body, DisputeResponse, context) except ResponseException as e: error_type = ErrorResponse error_object = self._communicator.marshaller.unmarshal(e.body, error_type) raise self._create_exception(e.status_code, e.body, error_object, context) def disputes(self, payment_id, context=None): """ Resource /{merchantId}/payments/{paymentId}/disputes - Get disputes See also https://epayments-api.developer-ingenico.com/s2sapi/v1/en_US/python/payments/disputes.html :param payment_id: str :param context: :class:`ingenico.connect.sdk.call_context.CallContext` :return: :class:`ingenico.connect.sdk.domain.dispute.disputes_response.DisputesResponse` :raise: ValidationException if the request was not correct and couldn't be processed (HTTP status code 400) :raise: AuthorizationException if the request was not allowed (HTTP status code 403) :raise: ReferenceException if an object was attempted to be referenced that doesn't exist or has been removed, or there was a conflict (HTTP status code 404, 409 or 410) :raise: GlobalCollectException if something went wrong at the Ingenico ePayments platform, the Ingenico ePayments platform was unable to process a message from a downstream partner/acquirer, or the service that you're trying to reach is temporary unavailable (HTTP status code 500, 502 or 503) :raise: ApiException if the Ingenico ePayments platform returned any other error """ path_context = { "paymentId": payment_id, } uri = self._instantiate_uri("/v1/{merchantId}/payments/{paymentId}/disputes", path_context) try: return self._communicator.get( uri, self._client_headers, None, DisputesResponse, context) except ResponseException as e: error_type = ErrorResponse error_object = self._communicator.marshaller.unmarshal(e.body, error_type) raise self._create_exception(e.status_code, e.body, error_object, context) def devicefingerprint(self, payment_id, context=None): """ Resource /{merchantId}/payments/{paymentId}/devicefingerprint - Get Device Fingerprint details See also https://epayments-api.developer-ingenico.com/s2sapi/v1/en_US/python/payments/devicefingerprint.html :param payment_id: str :param context: :class:`ingenico.connect.sdk.call_context.CallContext` :return: :class:`ingenico.connect.sdk.domain.payment.device_fingerprint_details.DeviceFingerprintDetails` :raise: ValidationException if the request was not correct and couldn't be processed (HTTP status code 400) :raise: AuthorizationException if the request was not allowed (HTTP status code 403) :raise: ReferenceException if an object was attempted to be referenced that doesn't exist or has been removed, or there was a conflict (HTTP status code 404, 409 or 410) :raise: GlobalCollectException if something went wrong at the Ingenico ePayments platform, the Ingenico ePayments platform was unable to process a message from a downstream partner/acquirer, or the service that you're trying to reach is temporary unavailable (HTTP status code 500, 502 or 503) :raise: ApiException if the Ingenico ePayments platform returned any other error """ path_context = { "paymentId": payment_id, } uri = self._instantiate_uri("/v1/{merchantId}/payments/{paymentId}/devicefingerprint", path_context) try: return self._communicator.get( uri, self._client_headers, None, DeviceFingerprintDetails, context) except ResponseException as e: error_type = ErrorResponse error_object = self._communicator.marshaller.unmarshal(e.body, error_type) raise self._create_exception(e.status_code, e.body, error_object, context)

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b2b83c08d3799492f8cd7c057700451af6ef58fb

21,161

py

Python

optax/_src/control_variates_test.py

asmith26/optax

46849fdbfb50667cf9a7c0443f514d575a910654

[ "Apache-2.0" ]

null

optax/_src/control_variates_test.py

asmith26/optax

46849fdbfb50667cf9a7c0443f514d575a910654

[ "Apache-2.0" ]

null

optax/_src/control_variates_test.py

asmith26/optax

46849fdbfb50667cf9a7c0443f514d575a910654

[ "Apache-2.0" ]

null

# Lint as: python3 # Copyright 2019 DeepMind Technologies Limited. 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. # 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 itertools from absl.testing import absltest from absl.testing import parameterized import chex import jax import jax.numpy as jnp import numpy as np from optax._src import control_variates from optax._src import stochastic_gradient_estimators from optax._src import utils # Set seed for deterministic sampling. np.random.seed(42) def _assert_equal(actual, expected, rtol=1e-2, atol=1e-2): # Note: assert_allclose does not check shapes assert actual.shape == expected.shape # Scalar. if not actual.shape: return np.testing.assert_allclose( np.asarray(actual), np.asarray(expected), rtol, atol) # We get around the bug https://github.com/numpy/numpy/issues/13801 zero_indices = np.argwhere(expected == 0) if not np.all(np.abs(actual[zero_indices]) <= atol): raise AssertionError('Larger than {} diff in {}'.format( atol, actual[zero_indices])) non_zero_indices = np.argwhere(expected != 0) np.testing.assert_allclose( np.asarray(actual)[non_zero_indices], expected[non_zero_indices], rtol, atol) def _cross_prod(items1, items2): prod = itertools.product(items1, items2) return [i1 + (i2,) for i1, i2 in prod] def _map(cv, params, samples, state=None): return jax.vmap(lambda x: cv(params, x, state))(samples) def _map_variant(variant): return variant(_map, static_argnums=0) def _cv_jac_variant(variant): return variant( control_variates.control_variates_jacobians, static_argnums=(0, 1, 2, 4, 5, 6, 7, 8)) class DeltaControlVariateTest(chex.TestCase): @chex.all_variants @parameterized.parameters([(1.0, 0.5)]) def testQuadraticFunction(self, effective_mean, effective_log_scale): data_dims = 20 num_samples = 10**6 rng = jax.random.PRNGKey(1) mean = effective_mean * jnp.ones(shape=(data_dims), dtype=jnp.float32) log_scale = effective_log_scale * jnp.ones( shape=(data_dims), dtype=jnp.float32) params = [mean, log_scale] dist = utils.multi_normal(*params) dist_samples = dist.sample((num_samples,), rng) function = lambda x: jnp.sum(x**2) cv, expected_cv, _ = control_variates.control_delta_method(function) avg_cv = jnp.mean(_map_variant(self.variant)(cv, params, dist_samples)) expected_cv_value = jnp.sum(dist_samples** 2) / num_samples # This should be an analytical computation, the result needs to be # accurate. _assert_equal(avg_cv, expected_cv_value, rtol=1e-1, atol=1e-3) _assert_equal(expected_cv(params, None), expected_cv_value, atol=1e-1) @chex.all_variants @parameterized.parameters([(1.0, 1.0)]) def testPolinomialFunction(self, effective_mean, effective_log_scale): data_dims = 10 num_samples = 10**3 mean = effective_mean * jnp.ones(shape=(data_dims), dtype=jnp.float32) log_scale = effective_log_scale * jnp.ones( shape=(data_dims), dtype=jnp.float32) params = [mean, log_scale] dist = utils.multi_normal(*params) rng = jax.random.PRNGKey(1) dist_samples = dist.sample((num_samples,), rng) function = lambda x: jnp.sum(x**5) cv, expected_cv, _ = control_variates.control_delta_method(function) avg_cv = jnp.mean(_map_variant(self.variant)(cv, params, dist_samples)) # Check that the average value of the control variate is close to the # expected value. _assert_equal(avg_cv, expected_cv(params, None), rtol=1e-1, atol=1e-3) @chex.all_variants def testNonPolynomialFunction(self): data_dims = 10 num_samples = 10**3 mean = jnp.ones(shape=(data_dims), dtype=jnp.float32) log_scale = jnp.ones(shape=(data_dims), dtype=jnp.float32) params = [mean, log_scale] rng = jax.random.PRNGKey(1) dist = utils.multi_normal(*params) dist_samples = dist.sample((num_samples,), rng) function = lambda x: jnp.sum(jnp.log(x**2)) cv, expected_cv, _ = control_variates.control_delta_method(function) avg_cv = jnp.mean(_map_variant(self.variant)(cv, params, dist_samples)) # Check that the average value of the control variate is close to the # expected value. _assert_equal(avg_cv, expected_cv(params, None), rtol=1e-1, atol=1e-3) # Second order expansion is log(\mu**2) + 1/2 * \sigma**2 (-2 / \mu**2) expected_cv_val = - np.exp(1.) ** 2 * data_dims _assert_equal( expected_cv(params, None), expected_cv_val, rtol=1e-1, atol=1e-3) class MovingAverageBaselineTest(chex.TestCase): @chex.all_variants @parameterized.parameters( [(1.0, 0.5, 0.9), (1.0, 0.5, 0.99)]) def testLinearFunction( self, effective_mean, effective_log_scale, decay): weights = jnp.array([1., 2., 3.], dtype=jnp.float32) num_samples = 10**4 data_dims = len(weights) mean = effective_mean * jnp.ones(shape=(data_dims), dtype=jnp.float32) log_scale = effective_log_scale * jnp.ones( shape=(data_dims), dtype=jnp.float32) params = [mean, log_scale] function = lambda x: jnp.sum(weights * x) rng = jax.random.PRNGKey(1) dist = utils.multi_normal(*params) dist_samples = dist.sample((num_samples,), rng) cv, expected_cv, update_state = control_variates.moving_avg_baseline( function, decay=decay, zero_debias=False, use_decay_early_training_heuristic=False) state_1 = jnp.array(1.) avg_cv = jnp.mean(_map_variant(self.variant)( cv, params, dist_samples, (state_1, 0))) _assert_equal(avg_cv, state_1) _assert_equal(expected_cv(params, (state_1, 0)), state_1) state_2 = jnp.array(2.) avg_cv = jnp.mean( _map_variant(self.variant)(cv, params, dist_samples, (state_2, 0))) _assert_equal(avg_cv, state_2) _assert_equal(expected_cv(params, (state_2, 0)), state_2) update_state_1 = update_state(params, dist_samples, (state_1, 0))[0] _assert_equal( update_state_1, decay * state_1 + (1 - decay) * function(mean)) update_state_2 = update_state(params, dist_samples, (state_2, 0))[0] _assert_equal( update_state_2, decay * state_2 + (1 - decay) * function(mean)) @chex.all_variants @parameterized.parameters( [(1.0, 0.5, 0.9), (1.0, 0.5, 0.99)]) def testLinearFunctionWithHeuristic( self, effective_mean, effective_log_scale, decay): weights = jnp.array([1., 2., 3.], dtype=jnp.float32) num_samples = 10**5 data_dims = len(weights) mean = effective_mean * jnp.ones(shape=(data_dims), dtype=jnp.float32) log_scale = effective_log_scale * jnp.ones( shape=(data_dims), dtype=jnp.float32) params = [mean, log_scale] function = lambda x: jnp.sum(weights * x) rng = jax.random.PRNGKey(1) dist = utils.multi_normal(*params) dist_samples = dist.sample((num_samples,), rng) cv, expected_cv, update_state = control_variates.moving_avg_baseline( function, decay=decay, zero_debias=False, use_decay_early_training_heuristic=True) state_1 = jnp.array(1.) avg_cv = jnp.mean(_map_variant(self.variant)( cv, params, dist_samples, (state_1, 0))) _assert_equal(avg_cv, state_1) _assert_equal(expected_cv(params, (state_1, 0)), state_1) state_2 = jnp.array(2.) avg_cv = jnp.mean( _map_variant(self.variant)(cv, params, dist_samples, (state_2, 0))) _assert_equal(avg_cv, state_2) _assert_equal(expected_cv(params, (state_2, 0)), state_2) first_step_decay = 0.1 update_state_1 = update_state(params, dist_samples, (state_1, 0))[0] _assert_equal( update_state_1, first_step_decay * state_1 + (1 - first_step_decay) * function(mean)) second_step_decay = 2. / 11 update_state_2 = update_state(params, dist_samples, (state_2, 1))[0] _assert_equal( update_state_2, second_step_decay * state_2 + (1 - second_step_decay) * function(mean)) @parameterized.parameters( [(1.0, 0.5, 0.9), (1.0, 0.5, 0.99)]) def testLinearFunctionZeroDebias( self, effective_mean, effective_log_scale, decay): weights = jnp.array([1., 2., 3.], dtype=jnp.float32) num_samples = 10**5 data_dims = len(weights) mean = effective_mean * jnp.ones(shape=(data_dims), dtype=jnp.float32) log_scale = effective_log_scale * jnp.ones( shape=(data_dims), dtype=jnp.float32) params = [mean, log_scale] function = lambda x: jnp.sum(weights * x) rng = jax.random.PRNGKey(1) dist = utils.multi_normal(*params) dist_samples = dist.sample((num_samples,), rng) update_state = control_variates.moving_avg_baseline( function, decay=decay, zero_debias=False, use_decay_early_training_heuristic=False)[-1] update_state_zero_debias = control_variates.moving_avg_baseline( function, decay=decay, zero_debias=True, use_decay_early_training_heuristic=False)[-1] updated_state = update_state(params, dist_samples, (jnp.array(0.), 0))[0] _assert_equal(updated_state, (1 - decay) * function(mean)) updated_state_zero_debias = update_state_zero_debias( params, dist_samples, (jnp.array(0.), 0))[0] _assert_equal( updated_state_zero_debias, function(mean)) class DeltaMethodAnalyticalExpectedGrads(chex.TestCase): @chex.all_variants @parameterized.parameters(_cross_prod([ (1.0, 1.0, stochastic_gradient_estimators.score_function_jacobians), (1.0, 1.0, stochastic_gradient_estimators.pathwise_jacobians), (1.0, 1.0, stochastic_gradient_estimators.measure_valued_jacobians)], [True, False])) def testQuadraticFunction( self, effective_mean, effective_log_scale, grad_estimator, estimate_cv_coeffs): data_dims = 3 num_samples = 10**3 mean = effective_mean * jnp.ones(shape=(data_dims), dtype=jnp.float32) log_scale = effective_log_scale * jnp.ones( shape=(data_dims), dtype=jnp.float32) params = [mean, log_scale] function = lambda x: jnp.sum(x**2) rng = jax.random.PRNGKey(1) jacobians = _cv_jac_variant(self.variant)( function, control_variates.control_delta_method, grad_estimator, params, utils.multi_normal, # dist_builder rng, num_samples, None, # No cv state. estimate_cv_coeffs)[0] expected_mean_grads = 2 * effective_mean * np.ones( data_dims, dtype=np.float32) expected_log_scale_grads = 2 * np.exp(2 * effective_log_scale) * np.ones( data_dims, dtype=np.float32) mean_jacobians = jacobians[0] chex.assert_shape(mean_jacobians, (num_samples, data_dims)) mean_grads_from_jacobian = jnp.mean(mean_jacobians, axis=0) log_scale_jacobians = jacobians[1] chex.assert_shape(log_scale_jacobians, (num_samples, data_dims)) log_scale_grads_from_jacobian = jnp.mean(log_scale_jacobians, axis=0) _assert_equal(mean_grads_from_jacobian, expected_mean_grads, rtol=1e-1, atol=1e-3) _assert_equal(log_scale_grads_from_jacobian, expected_log_scale_grads, rtol=1e-1, atol=1e-3) @chex.all_variants @parameterized.parameters(_cross_prod([ (1.0, 1.0, stochastic_gradient_estimators.score_function_jacobians), (1.0, 1.0, stochastic_gradient_estimators.pathwise_jacobians), (1.0, 1.0, stochastic_gradient_estimators.measure_valued_jacobians)], [True, False])) def testCubicFunction( self, effective_mean, effective_log_scale, grad_estimator, estimate_cv_coeffs): data_dims = 1 num_samples = 10**5 mean = effective_mean * jnp.ones(shape=(data_dims), dtype=jnp.float32) log_scale = effective_log_scale * jnp.ones( shape=(data_dims), dtype=jnp.float32) params = [mean, log_scale] function = lambda x: jnp.sum(x**3) rng = jax.random.PRNGKey(1) jacobians = _cv_jac_variant(self.variant)( function, control_variates.control_delta_method, grad_estimator, params, utils.multi_normal, rng, num_samples, None, # No cv state. estimate_cv_coeffs)[0] # The third order uncentered moment of the Gaussian distribution is # mu**3 + 2 mu * sigma **2. We use that to compute the expected value # of the gradients. Note: for the log scale we need use the chain rule. expected_mean_grads = ( 3 * effective_mean**2 + 3 * np.exp(effective_log_scale)**2) expected_mean_grads *= np.ones(data_dims, dtype=np.float32) expected_log_scale_grads = ( 6 * effective_mean * np.exp(effective_log_scale) ** 2) expected_log_scale_grads *= np.ones(data_dims, dtype=np.float32) mean_jacobians = jacobians[0] chex.assert_shape(mean_jacobians, (num_samples, data_dims)) mean_grads_from_jacobian = jnp.mean(mean_jacobians, axis=0) log_scale_jacobians = jacobians[1] chex.assert_shape(log_scale_jacobians, (num_samples, data_dims)) log_scale_grads_from_jacobian = jnp.mean(log_scale_jacobians, axis=0) _assert_equal(mean_grads_from_jacobian, expected_mean_grads, rtol=1e-1, atol=1e-3) _assert_equal(log_scale_grads_from_jacobian, expected_log_scale_grads, rtol=1e-1, atol=1e-3) @chex.all_variants @parameterized.parameters(_cross_prod([ (1.0, 1.0, stochastic_gradient_estimators.score_function_jacobians), (1.0, 1.0, stochastic_gradient_estimators.pathwise_jacobians), (1.0, 1.0, stochastic_gradient_estimators.measure_valued_jacobians)], [True, False])) def testForthPowerFunction( self, effective_mean, effective_log_scale, grad_estimator, estimate_cv_coeffs): data_dims = 1 num_samples = 10**5 mean = effective_mean * jnp.ones(shape=(data_dims), dtype=jnp.float32) log_scale = effective_log_scale * jnp.ones( shape=(data_dims), dtype=jnp.float32) params = [mean, log_scale] function = lambda x: jnp.sum(x**4) rng = jax.random.PRNGKey(1) jacobians = _cv_jac_variant(self.variant)( function, control_variates.control_delta_method, grad_estimator, params, utils.multi_normal, rng, num_samples, None, # No cv state estimate_cv_coeffs)[0] # The third order uncentered moment of the Gaussian distribution is # mu**4 + 6 mu **2 sigma **2 + 3 sigma**4. We use that to compute the # expected value of the gradients. # Note: for the log scale we need use the chain rule. expected_mean_grads = ( 3 * effective_mean**3 + 12 * effective_mean * np.exp(effective_log_scale)**2) expected_mean_grads *= np.ones(data_dims, dtype=np.float32) expected_log_scale_grads = 12 * ( effective_mean**2 * np.exp(effective_log_scale) + np.exp(effective_log_scale) ** 3) * np.exp(effective_log_scale) expected_log_scale_grads *= np.ones(data_dims, dtype=np.float32) mean_jacobians = jacobians[0] chex.assert_shape(mean_jacobians, (num_samples, data_dims)) mean_grads_from_jacobian = jnp.mean(mean_jacobians, axis=0) log_scale_jacobians = jacobians[1] chex.assert_shape(log_scale_jacobians, (num_samples, data_dims)) log_scale_grads_from_jacobian = jnp.mean(log_scale_jacobians, axis=0) _assert_equal(mean_grads_from_jacobian, expected_mean_grads, rtol=1e-1, atol=1e-3) _assert_equal(log_scale_grads_from_jacobian, expected_log_scale_grads, rtol=1e-1, atol=1e-3) class ConsistencyWithStandardEstimators(chex.TestCase): @chex.all_variants @parameterized.parameters(_cross_prod([ (1, 1, stochastic_gradient_estimators.score_function_jacobians, 10 **6), (1, 1, stochastic_gradient_estimators.pathwise_jacobians, 10 **5), (1, 1, stochastic_gradient_estimators.measure_valued_jacobians, 10 **5)], [control_variates.control_delta_method, control_variates.moving_avg_baseline])) def testWeightedLinearFunction( self, effective_mean, effective_log_scale, grad_estimator, num_samples, control_variate_from_function): """Check that the gradients are consistent between estimators.""" weights = jnp.array([1., 2., 3.], dtype=jnp.float32) data_dims = len(weights) mean = effective_mean * jnp.ones(shape=(data_dims), dtype=jnp.float32) log_scale = effective_log_scale * jnp.ones( shape=(data_dims), dtype=jnp.float32) params = [mean, log_scale] function = lambda x: jnp.sum(weights * x) rng = jax.random.PRNGKey(1) cv_rng, ge_rng = jax.random.split(rng) jacobians = _cv_jac_variant(self.variant)( function, control_variate_from_function, grad_estimator, params, utils.multi_normal, # dist_builder cv_rng, # rng num_samples, (0., 0), # control_variate_state False)[0] mean_jacobians = jacobians[0] chex.assert_shape(mean_jacobians, (num_samples, data_dims)) mean_grads = jnp.mean(mean_jacobians, axis=0) log_scale_jacobians = jacobians[1] chex.assert_shape(log_scale_jacobians, (num_samples, data_dims)) log_scale_grads = jnp.mean(log_scale_jacobians, axis=0) # We use a different random number generator for the gradient estimator # without the control variate. no_cv_jacobians = grad_estimator( function, [mean, log_scale], utils.multi_normal, ge_rng, num_samples=num_samples) no_cv_mean_jacobians = no_cv_jacobians[0] chex.assert_shape(no_cv_mean_jacobians, (num_samples, data_dims)) no_cv_mean_grads = jnp.mean(no_cv_mean_jacobians, axis=0) no_cv_log_scale_jacobians = no_cv_jacobians[1] chex.assert_shape(no_cv_log_scale_jacobians, (num_samples, data_dims)) no_cv_log_scale_grads = jnp.mean(no_cv_log_scale_jacobians, axis=0) _assert_equal(mean_grads, no_cv_mean_grads, rtol=1e-1, atol=5e-2) _assert_equal(log_scale_grads, no_cv_log_scale_grads, rtol=1, atol=5e-2) @chex.all_variants @parameterized.parameters(_cross_prod([ (1, 1, stochastic_gradient_estimators.score_function_jacobians, 10 **5), (1, 1, stochastic_gradient_estimators.pathwise_jacobians, 10 **5), (1, 1, stochastic_gradient_estimators.measure_valued_jacobians, 10 **5)], [control_variates.control_delta_method, control_variates.moving_avg_baseline])) def testNonPolynomialFunction( self, effective_mean, effective_log_scale, grad_estimator, num_samples, control_variate_from_function): """Check that the gradients are consistent between estimators.""" data_dims = 3 mean = effective_mean * jnp.ones(shape=(data_dims), dtype=jnp.float32) log_scale = effective_log_scale * jnp.ones( shape=(data_dims), dtype=jnp.float32) params = [mean, log_scale] function = lambda x: jnp.log(jnp.sum(x**2)) rng = jax.random.PRNGKey(1) cv_rng, ge_rng = jax.random.split(rng) jacobians = _cv_jac_variant(self.variant)( function, control_variate_from_function, grad_estimator, params, utils.multi_normal, cv_rng, num_samples, (0., 0), # control_variate_state False)[0] mean_jacobians = jacobians[0] chex.assert_shape(mean_jacobians, (num_samples, data_dims)) mean_grads = jnp.mean(mean_jacobians, axis=0) log_scale_jacobians = jacobians[1] chex.assert_shape(log_scale_jacobians, (num_samples, data_dims)) log_scale_grads = jnp.mean(log_scale_jacobians, axis=0) # We use a different random number generator for the gradient estimator # without the control variate. no_cv_jacobians = grad_estimator( function, [mean, log_scale], utils.multi_normal, ge_rng, num_samples=num_samples) no_cv_mean_jacobians = no_cv_jacobians[0] chex.assert_shape(no_cv_mean_jacobians, (num_samples, data_dims)) no_cv_mean_grads = jnp.mean(no_cv_mean_jacobians, axis=0) no_cv_log_scale_jacobians = no_cv_jacobians[1] chex.assert_shape(no_cv_log_scale_jacobians, (num_samples, data_dims)) no_cv_log_scale_grads = jnp.mean(no_cv_log_scale_jacobians, axis=0) _assert_equal(mean_grads, no_cv_mean_grads, rtol=1e-1, atol=5e-2) _assert_equal(log_scale_grads, no_cv_log_scale_grads, rtol=1e-1, atol=5e-2) if __name__ == '__main__': absltest.main()

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b2d2169b9e42d8d759a47793cf34031da4dc110e

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Python

yolo3/models/yolo3_shufflenetv2.py

rootadminWalker/keras-YOLOv3-model-set

196ec711975e1821a260a9f6523008bf47ff8c84

[ "MIT" ]

null

yolo3/models/yolo3_shufflenetv2.py

rootadminWalker/keras-YOLOv3-model-set

196ec711975e1821a260a9f6523008bf47ff8c84

[ "MIT" ]

null

yolo3/models/yolo3_shufflenetv2.py

rootadminWalker/keras-YOLOv3-model-set

196ec711975e1821a260a9f6523008bf47ff8c84

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """YOLO_v3 ShuffleNetV2 Model Defined in Keras.""" from tensorflow.keras.layers import UpSampling2D, Concatenate from tensorflow.keras.models import Model from ...common.backbones.shufflenet_v2 import ShuffleNetV2 #from yolo3.models.layers import compose, DarknetConv2D, DarknetConv2D_BN_Leaky, Depthwise_Separable_Conv2D_BN_Leaky, make_last_layers, make_depthwise_separable_last_layers, make_spp_depthwise_separable_last_layers from .layers import yolo3_predictions, yolo3lite_predictions, tiny_yolo3_predictions, tiny_yolo3lite_predictions def yolo3_shufflenetv2_body(inputs, num_anchors, num_classes): """Create YOLO_V3 ShuffleNetV2 model CNN body in Keras.""" shufflenetv2 = ShuffleNetV2(input_tensor=inputs, weights=None, include_top=False) print('backbone layers number: {}'.format(len(shufflenetv2.layers))) # input: 416 x 416 x 3 # 1x1conv5_out: 13 x 13 x 1024 # stage4/block1/relu_1x1conv_1: 26 x 26 x 464 # stage3/block1/relu_1x1conv_1: 52 x 52 x 232 # f1: 13 x 13 x 1024 f1 = shufflenetv2.get_layer('1x1conv5_out').output # f2: 26 x 26 x 464 f2 = shufflenetv2.get_layer('stage4/block1/relu_1x1conv_1').output # f3: 52 x 52 x 232 f3 = shufflenetv2.get_layer('stage3/block1/relu_1x1conv_1').output f1_channel_num = 1024 f2_channel_num = 464 f3_channel_num = 232 #f1_channel_num = 1024 #f2_channel_num = 512 #f3_channel_num = 256 y1, y2, y3 = yolo3_predictions((f1, f2, f3), (f1_channel_num, f2_channel_num, f3_channel_num), num_anchors, num_classes) return Model(inputs = inputs, outputs=[y1,y2,y3]) def yolo3lite_shufflenetv2_body(inputs, num_anchors, num_classes): '''Create YOLO_v3 Lite ShuffleNetV2 model CNN body in keras.''' shufflenetv2 = ShuffleNetV2(input_tensor=inputs, weights=None, include_top=False) print('backbone layers number: {}'.format(len(shufflenetv2.layers))) # input: 416 x 416 x 3 # 1x1conv5_out: 13 x 13 x 1024 # stage4/block1/relu_1x1conv_1: 26 x 26 x 464 # stage3/block1/relu_1x1conv_1: 52 x 52 x 232 # f1: 13 x 13 x 1024 f1 = shufflenetv2.get_layer('1x1conv5_out').output # f2: 26 x 26 x 464 f2 = shufflenetv2.get_layer('stage4/block1/relu_1x1conv_1').output # f3: 52 x 52 x 232 f3 = shufflenetv2.get_layer('stage3/block1/relu_1x1conv_1').output f1_channel_num = 1024 f2_channel_num = 464 f3_channel_num = 232 #f1_channel_num = 1024 #f2_channel_num = 512 #f3_channel_num = 256 y1, y2, y3 = yolo3lite_predictions((f1, f2, f3), (f1_channel_num, f2_channel_num, f3_channel_num), num_anchors, num_classes) return Model(inputs = inputs, outputs=[y1,y2,y3]) def yolo3lite_spp_shufflenetv2_body(inputs, num_anchors, num_classes): '''Create YOLO_v3 Lite SPP ShuffleNetV2 model CNN body in keras.''' shufflenetv2 = ShuffleNetV2(input_tensor=inputs, weights=None, include_top=False) print('backbone layers number: {}'.format(len(shufflenetv2.layers))) # input: 416 x 416 x 3 # 1x1conv5_out: 13 x 13 x 1024 # stage4/block1/relu_1x1conv_1: 26 x 26 x 464 # stage3/block1/relu_1x1conv_1: 52 x 52 x 232 # f1: 13 x 13 x 1024 f1 = shufflenetv2.get_layer('1x1conv5_out').output # f2: 26 x 26 x 464 f2 = shufflenetv2.get_layer('stage4/block1/relu_1x1conv_1').output # f3: 52 x 52 x 232 f3 = shufflenetv2.get_layer('stage3/block1/relu_1x1conv_1').output f1_channel_num = 1024 f2_channel_num = 464 f3_channel_num = 232 #f1_channel_num = 1024 #f2_channel_num = 512 #f3_channel_num = 256 y1, y2, y3 = yolo3lite_predictions((f1, f2, f3), (f1_channel_num, f2_channel_num, f3_channel_num), num_anchors, num_classes, use_spp=True) return Model(inputs = inputs, outputs=[y1,y2,y3]) def tiny_yolo3_shufflenetv2_body(inputs, num_anchors, num_classes): '''Create Tiny YOLO_v3 ShuffleNetV2 model CNN body in keras.''' shufflenetv2 = ShuffleNetV2(input_tensor=inputs, weights=None, include_top=False) print('backbone layers number: {}'.format(len(shufflenetv2.layers))) # input: 416 x 416 x 3 # 1x1conv5_out: 13 x 13 x 1024 # stage4/block1/relu_1x1conv_1: 26 x 26 x 464 # stage3/block1/relu_1x1conv_1: 52 x 52 x 232 # f1: 13 x 13 x 1024 f1 = shufflenetv2.get_layer('1x1conv5_out').output # f2: 26 x 26 x 464 f2 = shufflenetv2.get_layer('stage4/block1/relu_1x1conv_1').output f1_channel_num = 1024 f2_channel_num = 464 #f1_channel_num = 1024 #f2_channel_num = 512 y1, y2 = tiny_yolo3_predictions((f1, f2), (f1_channel_num, f2_channel_num), num_anchors, num_classes) return Model(inputs, [y1,y2]) def tiny_yolo3lite_shufflenetv2_body(inputs, num_anchors, num_classes): '''Create Tiny YOLO_v3 Lite ShuffleNetV2 model CNN body in keras.''' shufflenetv2 = ShuffleNetV2(input_tensor=inputs, weights=None, include_top=False) print('backbone layers number: {}'.format(len(shufflenetv2.layers))) # input: 416 x 416 x 3 # 1x1conv5_out: 13 x 13 x 1024 # stage4/block1/relu_1x1conv_1: 26 x 26 x 464 # stage3/block1/relu_1x1conv_1: 52 x 52 x 232 # f1: 13 x 13 x 1024 f1 = shufflenetv2.get_layer('1x1conv5_out').output # f2: 26 x 26 x 464 f2 = shufflenetv2.get_layer('stage4/block1/relu_1x1conv_1').output f1_channel_num = 1024 f2_channel_num = 464 #f1_channel_num = 1024 #f2_channel_num = 512 y1, y2 = tiny_yolo3lite_predictions((f1, f2), (f1_channel_num, f2_channel_num), num_anchors, num_classes) return Model(inputs, [y1,y2])

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650b9d8870752bc3b0826615663d65b1e87b2796

1,779

py

Python

imagersite/imager_images/models.py

allanliebold/django-imager

1e89652ee344172b1a36a21fae1a7baf8cc28df1

[ "MIT" ]

null

imagersite/imager_images/models.py

allanliebold/django-imager

1e89652ee344172b1a36a21fae1a7baf8cc28df1

[ "MIT" ]

null

imagersite/imager_images/models.py

allanliebold/django-imager

1e89652ee344172b1a36a21fae1a7baf8cc28df1

[ "MIT" ]

null

"""Models.""" from django.db import models from django.contrib.auth.models import User class Photo(models.Model): """Photo Model that creates a photo.""" user = models.ForeignKey(User, on_delete=models.CASCADE, related_name='photo') image = models.ImageField(upload_to='images') title = models.CharField(max_length=30, blank=False) description = models.TextField(blank=True) date_uploaded = models.DateTimeField(auto_now_add=True) date_modified = models.DateTimeField(auto_now=True) date_published = models.DateTimeField(auto_now=True) PUBLISHED = [ ('PRIVATE', 'Private'), ('SHARED', 'Shared'), ('PUBLIC', 'Public') ] published = models.CharField( max_length=10, choices=PUBLISHED, blank=True ) def __str__(self): """.""" return self.title class Album(models.Model): """Album Model for pictures.""" user = models.ForeignKey(User, on_delete=models.CASCADE, related_name='album') photo = models.ManyToManyField(Photo, related_name='album') title = models.CharField(max_length=30, blank=False) description = models.TextField(blank=True) date_uploaded = models.DateTimeField(auto_now_add=True) date_modified = models.DateTimeField(auto_now=True) date_published = models.DateTimeField(auto_now=True) PUBLISHED = [ ('PRIVATE', 'Private'), ('SHARED', 'Shared'), ('PUBLIC', 'Public') ] published = models.CharField( max_length=10, choices=PUBLISHED, blank=True ) def __str__(self): """Return Album title.""" return self.title

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3303be2c8afd3c8a06638659c37bc04822397703

89

py

Python

server/handler/__init__.py

10000ms/aiohttp_mongodb_unit

5163b3e34b1648ea3a2d6135fb367debd6ed87a7

[ "MIT" ]

null

server/handler/__init__.py

10000ms/aiohttp_mongodb_unit

5163b3e34b1648ea3a2d6135fb367debd6ed87a7

[ "MIT" ]

null

server/handler/__init__.py

10000ms/aiohttp_mongodb_unit

5163b3e34b1648ea3a2d6135fb367debd6ed87a7

[ "MIT" ]

null

# -*- coding: utf-8 -*- from server.handler import user from server.handler import error

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8

3311adbf8db38ae4b31584b1382497ba77c4d46b

4,903

py

Python

pytorch_bcnn/links/connection/pixel_shuffle_upsampler.py

psadda/pytorch_bayesian_unet

bb22b44c64f5d83d78aa93880da97e0e6168dc1c

[ "MIT" ]

34

2020-03-30T16:48:45.000Z

2022-03-25T15:53:08.000Z

pytorch_bcnn/links/connection/pixel_shuffle_upsampler.py

IhabBendidi/pytorch_bayesian_unet

cc09653a051072790760447c711887e289ed11dc

[ "MIT" ]

2

2021-01-24T04:21:16.000Z

2021-04-25T19:22:14.000Z

pytorch_bcnn/links/connection/pixel_shuffle_upsampler.py

IhabBendidi/pytorch_bayesian_unet

cc09653a051072790760447c711887e289ed11dc

[ "MIT" ]

15

2020-04-10T05:29:31.000Z

2022-01-03T08:45:02.000Z

from __future__ import absolute_import import torch import torch.nn as nn import torch.nn.functional as F class PixelShuffleUpsampler2D(nn.Conv2d): """Pixel Shuffler for the super resolution. This upsampler is effective upsampling method compared with the deconvolution. The deconvolution has a problem of the checkerboard artifact. A detail of this problem shows the following. http://distill.pub/2016/deconv-checkerboard/ See also: https://arxiv.org/abs/1609.05158 """ ndim = 2 def __init__(self, in_channels, out_channels, resolution, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=True, padding_mode='zeros'): m = resolution ** self.ndim super(PixelShuffleUpsampler2D, self).__init__( in_channels, out_channels * m, kernel_size, stride, padding, dilation, groups, bias, padding_mode) self.resolution = resolution self.out_channels = out_channels def extra_repr(self): s = ('{in_channels}, {out_channels}, resolution={resolution}' ', kernel_size={kernel_size}, stride={stride}') if self.padding != (0,) * len(self.padding): s += ', padding={padding}' if self.dilation != (1,) * len(self.dilation): s += ', dilation={dilation}' if self.output_padding != (0,) * len(self.output_padding): s += ', output_padding={output_padding}' if self.groups != 1: s += ', groups={groups}' if self.bias is None: s += ', bias=False' if self.padding_mode != 'zeros': s += ', padding_mode={padding_mode}' return s.format(**self.__dict__) def forward(self, x): r = self.resolution out = super().forward(x) batchsize = out.shape[0] in_channels = out.shape[1] out_channels = self.out_channels in_shape = out.shape[2:] out_shape = tuple(s * r for s in in_shape) r_tuple = tuple(self.resolution for _ in range(self.ndim)) out = out.view((batchsize, out_channels,) + r_tuple + in_shape) out = out.permute(self.make_transpose_indices()).contiguous() out = out.view((batchsize, out_channels, ) + out_shape) return out def make_transpose_indices(self): si = [0, 1] si.extend([2 * (i + 1) + 1 for i in range(self.ndim)]) si.extend([2 * (i + 1) for i in range(self.ndim)]) return si class PixelShuffleUpsampler3D(nn.Conv3d): """Pixel Shuffler for the super resolution. This upsampler is effective upsampling method compared with the deconvolution. The deconvolution has a problem of the checkerboard artifact. A detail of this problem shows the following. http://distill.pub/2016/deconv-checkerboard/ See also: https://arxiv.org/abs/1609.05158 """ ndim = 3 def __init__(self, in_channels, out_channels, resolution, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=True, padding_mode='zeros'): m = resolution ** self.ndim super(PixelShuffleUpsampler3D, self).__init__( in_channels, out_channels * m, kernel_size, stride, padding, dilation, groups, bias, padding_mode) self.resolution = resolution self.out_channels = out_channels def extra_repr(self): s = ('{in_channels}, {out_channels}, resolution={resolution}' ', kernel_size={kernel_size}, stride={stride}') if self.padding != (0,) * len(self.padding): s += ', padding={padding}' if self.dilation != (1,) * len(self.dilation): s += ', dilation={dilation}' if self.output_padding != (0,) * len(self.output_padding): s += ', output_padding={output_padding}' if self.groups != 1: s += ', groups={groups}' if self.bias is None: s += ', bias=False' if self.padding_mode != 'zeros': s += ', padding_mode={padding_mode}' return s.format(**self.__dict__) def forward(self, x): r = self.resolution out = super().forward(x) batchsize = out.shape[0] in_channels = out.shape[1] out_channels = self.out_channels in_shape = out.shape[2:] out_shape = tuple(s * r for s in in_shape) r_tuple = tuple(self.resolution for _ in range(self.ndim)) out = out.view((batchsize, out_channels,) + r_tuple + in_shape) out = out.permute(self.make_transpose_indices()).contiguous() out = out.view((batchsize, out_channels, ) + out_shape) return out def make_transpose_indices(self): si = [0, 1] si.extend([2 * (i + 1) + 1 for i in range(self.ndim)]) si.extend([2 * (i + 1) for i in range(self.ndim)]) return si

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332362264777945740f0f0020b4a1ca93c01e76c

15,868

py

Python

tests/test_modules/test_biggan_deep_archs.py

plutoyuxie/mmgeneration

0a7f5d16c970de1766ebf049d7a0264fe506504b

[ "Apache-2.0" ]

718

2021-04-15T11:26:20.000Z

2022-03-31T03:11:56.000Z

tests/test_modules/test_biggan_deep_archs.py

plutoyuxie/mmgeneration

0a7f5d16c970de1766ebf049d7a0264fe506504b

[ "Apache-2.0" ]

191

2021-04-15T12:13:34.000Z

2022-03-31T16:04:36.000Z

tests/test_modules/test_biggan_deep_archs.py

plutoyuxie/mmgeneration

0a7f5d16c970de1766ebf049d7a0264fe506504b

[ "Apache-2.0" ]

107

2021-04-15T12:38:41.000Z

2022-03-27T02:47:16.000Z

from copy import deepcopy from functools import partial import pytest import torch from mmgen.models import build_module # yapf:disable from mmgen.models.architectures.biggan import (BigGANDeepDiscResBlock, BigGANDeepDiscriminator, BigGANDeepGenerator, BigGANDeepGenResBlock) # yapf:enable class TestBigGANDeepGenResBlock: @classmethod def setup_class(cls): cls.default_cfg = dict( type='BigGANDeepGenResBlock', in_channels=32, out_channels=16, dim_after_concat=100, act_cfg=dict(type='ReLU'), upsample_cfg=dict(type='nearest', scale_factor=2), sn_eps=1e-6, bn_eps=1e-5, with_spectral_norm=True, input_is_label=False, auto_sync_bn=True, channel_ratio=4) cls.x = torch.randn(2, 32, 8, 8) cls.y = torch.randn(2, 100) cls.label = torch.randint(0, 100, (2, )) def test_biggan_deep_gen_res_block(self): # test default setting module = build_module(self.default_cfg) assert isinstance(module, BigGANDeepGenResBlock) out = module(self.x, self.y) assert out.shape == (2, 16, 16, 16) # test without upsample cfg = deepcopy(self.default_cfg) cfg.update(dict(upsample_cfg=None)) module = build_module(cfg) out = module(self.x, self.y) assert out.shape == (2, 16, 8, 8) # test input_is_label cfg = deepcopy(self.default_cfg) cfg.update(dict(input_is_label=True)) module = build_module(cfg) out = module(self.x, self.label) assert out.shape == (2, 16, 16, 16) # test torch-sn cfg = deepcopy(self.default_cfg) cfg.update(dict(sn_style='torch')) module = build_module(cfg) out = module(self.x, self.y) assert out.shape == (2, 16, 16, 16) @pytest.mark.skipif(not torch.cuda.is_available(), reason='requires cuda') def test_biggan_deep_gen_res_block_cuda(self): # test default setting module = build_module(self.default_cfg).cuda() assert isinstance(module, BigGANDeepGenResBlock) out = module(self.x.cuda(), self.y.cuda()) assert out.shape == (2, 16, 16, 16) # test without upsample cfg = deepcopy(self.default_cfg) cfg.update(dict(upsample_cfg=None)) module = build_module(cfg).cuda() out = module(self.x.cuda(), self.y.cuda()) assert out.shape == (2, 16, 8, 8) # test input_is_label cfg = deepcopy(self.default_cfg) cfg.update(dict(input_is_label=True)) module = build_module(cfg).cuda() out = module(self.x.cuda(), self.label.cuda()) assert out.shape == (2, 16, 16, 16) # test torch-sn cfg = deepcopy(self.default_cfg) cfg.update(dict(sn_style='torch')) module = build_module(cfg).cuda() out = module(self.x.cuda(), self.y.cuda()) assert out.shape == (2, 16, 16, 16) class TestBigGANDeepDiscResBlock: @classmethod def setup_class(cls): cls.default_cfg = dict( type='BigGANDeepDiscResBlock', in_channels=32, out_channels=64, channel_ratio=4, act_cfg=dict(type='ReLU', inplace=False), sn_eps=1e-6, with_downsample=True, with_spectral_norm=True) cls.x = torch.randn(2, 32, 16, 16) def test_biggan_deep_disc_res_block(self): # test default setting module = build_module(self.default_cfg) assert isinstance(module, BigGANDeepDiscResBlock) out = module(self.x) assert out.shape == (2, 64, 8, 8) # test with_downsample cfg = deepcopy(self.default_cfg) cfg.update(dict(with_downsample=False)) module = build_module(cfg) out = module(self.x) assert out.shape == (2, 64, 16, 16) # test different channel_ratio cfg = deepcopy(self.default_cfg) cfg.update(dict(channel_ratio=8)) module = build_module(cfg) out = module(self.x) assert out.shape == (2, 64, 8, 8) # test torch-sn cfg = deepcopy(self.default_cfg) cfg.update(dict(sn_style='torch')) module = build_module(cfg) out = module(self.x) assert out.shape == (2, 64, 8, 8) @pytest.mark.skipif(not torch.cuda.is_available(), reason='requires cuda') def test_biggan_deep_disc_res_block_cuda(self): # test default setting module = build_module(self.default_cfg).cuda() assert isinstance(module, BigGANDeepDiscResBlock) out = module(self.x.cuda()) assert out.shape == (2, 64, 8, 8) # test with_downsample cfg = deepcopy(self.default_cfg) cfg.update(dict(with_downsample=False)) module = build_module(cfg).cuda() out = module(self.x.cuda()) assert out.shape == (2, 64, 16, 16) # test different channel_ratio cfg = deepcopy(self.default_cfg) cfg.update(dict(channel_ratio=8)) module = build_module(cfg) out = module(self.x) assert out.shape == (2, 64, 8, 8) # test torch-sn cfg = deepcopy(self.default_cfg) cfg.update(dict(sn_style='torch')) module = build_module(cfg).cuda() out = module(self.x.cuda()) assert out.shape == (2, 64, 8, 8) class TestBigGANDeepGenerator(object): @classmethod def setup_class(cls): cls.noise = torch.randn((3, 120)) num_classes = 1000 cls.label = torch.randint(0, num_classes, (3, )) cls.default_config = dict( type='BigGANDeepGenerator', output_scale=128, num_classes=num_classes, base_channels=4) def test_biggan_deep_generator(self): # test default setting with builder g = build_module(self.default_config) assert isinstance(g, BigGANDeepGenerator) res = g(self.noise, self.label) assert res.shape == (3, 3, 128, 128) # test 'return_noise' res = g(self.noise, self.label, return_noise=True) assert res['fake_img'].shape == (3, 3, 128, 128) assert res['noise_batch'].shape == (3, 120) assert res['label'].shape == (3, ) res = g(None, None, num_batches=3, return_noise=True) assert res['fake_img'].shape == (3, 3, 128, 128) assert res['noise_batch'].shape == (3, 120) assert res['label'].shape == (3, ) # test callable noise = torch.randn label = partial(torch.randint, 0, 1000) res = g(noise, label, num_batches=2) assert res.shape == (2, 3, 128, 128) # test different output scale cfg = deepcopy(self.default_config) cfg.update(dict(output_scale=256)) g = build_module(cfg) noise = torch.randn((3, 120)) res = g(noise, self.label) assert res.shape == (3, 3, 256, 256) res = g(None, None, num_batches=3) assert res.shape == (3, 3, 256, 256) cfg = deepcopy(self.default_config) cfg.update(dict(output_scale=512)) g = build_module(cfg) res = g(None, None, num_batches=3) assert res.shape == (3, 3, 512, 512) cfg = deepcopy(self.default_config) cfg.update(dict(output_scale=64)) g = build_module(cfg) res = g(None, None, num_batches=3) assert res.shape == (3, 3, 64, 64) cfg = deepcopy(self.default_config) cfg.update(dict(output_scale=32)) g = build_module(cfg) res = g(None, None, num_batches=3) assert res.shape == (3, 3, 32, 32) # test with `concat_noise=False` cfg = deepcopy(self.default_config) cfg.update(dict(concat_noise=False)) g = build_module(cfg) res = g(None, None, num_batches=3) assert res.shape == (3, 3, 128, 128) # test with `with_spectral_norm=False` cfg = deepcopy(self.default_config) cfg.update(dict(with_spectral_norm=False)) g = build_module(cfg) res = g(None, None, num_batches=3) assert res.shape == (3, 3, 128, 128) # test different num_classes cfg = deepcopy(self.default_config) cfg.update( dict( num_classes=0, with_shared_embedding=False, concat_noise=False)) g = build_module(cfg) res = g(None, None, num_batches=3) assert res.shape == (3, 3, 128, 128) # test no shared embedding cfg = deepcopy(self.default_config) cfg.update(dict(with_shared_embedding=False, concat_noise=False)) g = build_module(cfg) res = g(None, None, num_batches=3) assert res.shape == (3, 3, 128, 128) # test torch-sn cfg = deepcopy(self.default_config) cfg.update(dict(sn_style='torch')) g = build_module(cfg) res = g(self.noise, self.label) assert res.shape == (3, 3, 128, 128) @pytest.mark.skipif(not torch.cuda.is_available(), reason='requires cuda') def test_biggan_deep_generator_cuda(self): # test default setting with builder g = build_module(self.default_config).cuda() assert isinstance(g, BigGANDeepGenerator) res = g(self.noise.cuda(), self.label.cuda()) assert res.shape == (3, 3, 128, 128) # test 'return_noise' res = g(self.noise.cuda(), self.label.cuda(), return_noise=True) assert res['fake_img'].shape == (3, 3, 128, 128) assert res['noise_batch'].shape == (3, 120) assert res['label'].shape == (3, ) res = g(None, None, num_batches=3, return_noise=True) assert res['fake_img'].shape == (3, 3, 128, 128) assert res['noise_batch'].shape == (3, 120) assert res['label'].shape == (3, ) # test callable noise = torch.randn label = partial(torch.randint, 0, 1000) res = g(noise, label, num_batches=2) assert res.shape == (2, 3, 128, 128) # test different output scale cfg = deepcopy(self.default_config) cfg.update(dict(output_scale=256)) g = build_module(cfg).cuda() noise = torch.randn((3, 120)) res = g(noise.cuda(), self.label.cuda()) assert res.shape == (3, 3, 256, 256) res = g(None, None, num_batches=3) assert res.shape == (3, 3, 256, 256) cfg = deepcopy(self.default_config) cfg.update(dict(output_scale=512)) g = build_module(cfg).cuda() res = g(None, None, num_batches=3) assert res.shape == (3, 3, 512, 512) cfg = deepcopy(self.default_config) cfg.update(dict(output_scale=64)) g = build_module(cfg).cuda() res = g(None, None, num_batches=3) assert res.shape == (3, 3, 64, 64) cfg = deepcopy(self.default_config) cfg.update(dict(output_scale=32)) g = build_module(cfg).cuda() res = g(None, None, num_batches=3) assert res.shape == (3, 3, 32, 32) # test with `concat_noise=False` cfg = deepcopy(self.default_config) cfg.update(dict(concat_noise=False)) g = build_module(cfg).cuda() res = g(None, None, num_batches=3) assert res.shape == (3, 3, 128, 128) # test with `with_spectral_norm=False` cfg = deepcopy(self.default_config) cfg.update(dict(with_spectral_norm=False)) g = build_module(cfg).cuda() res = g(None, None, num_batches=3) assert res.shape == (3, 3, 128, 128) # test different num_classes cfg = deepcopy(self.default_config) cfg.update( dict( num_classes=0, with_shared_embedding=False, concat_noise=False)) g = build_module(cfg).cuda() res = g(None, None, num_batches=3) assert res.shape == (3, 3, 128, 128) # test no shared embedding cfg = deepcopy(self.default_config) cfg.update(dict(with_shared_embedding=False, concat_noise=False)) g = build_module(cfg).cuda() res = g(None, None, num_batches=3) assert res.shape == (3, 3, 128, 128) # test torch-sn cfg = deepcopy(self.default_config) cfg.update(dict(sn_style='torch')) g = build_module(cfg).cuda() res = g(None, None, num_batches=3) assert res.shape == (3, 3, 128, 128) class TestBigGANDeepDiscriminator(object): @classmethod def setup_class(cls): num_classes = 1000 cls.default_config = dict( type='BigGANDeepDiscriminator', input_scale=128, num_classes=num_classes, base_channels=8) cls.x = torch.randn((2, 3, 128, 128)) cls.label = torch.randint(0, num_classes, (2, )) def test_biggan_deep_discriminator(self): # test default settings d = build_module(self.default_config) assert isinstance(d, BigGANDeepDiscriminator) y = d(self.x, self.label) assert y.shape == (2, 1) # test different init types cfg = deepcopy(self.default_config) cfg.update(dict(init_type='N02')) d = build_module(cfg) y = d(self.x, self.label) assert y.shape == (2, 1) cfg = deepcopy(self.default_config) cfg.update(dict(init_type='xavier')) d = build_module(cfg) y = d(self.x, self.label) assert y.shape == (2, 1) # test different num_classes cfg = deepcopy(self.default_config) cfg.update(dict(num_classes=0)) d = build_module(cfg) y = d(self.x, None) assert y.shape == (2, 1) # test with `with_spectral_norm=False` cfg = deepcopy(self.default_config) cfg.update(dict(with_spectral_norm=False)) d = build_module(cfg) y = d(self.x, self.label) assert y.shape == (2, 1) # test torch-sn cfg = deepcopy(self.default_config) cfg.update(dict(sn_style='torch')) d = build_module(cfg) y = d(self.x, self.label) assert y.shape == (2, 1) @pytest.mark.skipif(not torch.cuda.is_available(), reason='requires cuda') def test_biggan_deep_discriminator_cuda(self): # test default settings d = build_module(self.default_config).cuda() assert isinstance(d, BigGANDeepDiscriminator) y = d(self.x.cuda(), self.label.cuda()) assert y.shape == (2, 1) # test different init types cfg = deepcopy(self.default_config) cfg.update(dict(init_type='N02')) d = build_module(cfg).cuda() y = d(self.x.cuda(), self.label.cuda()) assert y.shape == (2, 1) cfg = deepcopy(self.default_config) cfg.update(dict(init_type='xavier')) d = build_module(cfg).cuda() y = d(self.x.cuda(), self.label.cuda()) assert y.shape == (2, 1) # test different num_classes cfg = deepcopy(self.default_config) cfg.update(dict(num_classes=0)) d = build_module(cfg).cuda() y = d(self.x.cuda(), None) assert y.shape == (2, 1) # test with `with_spectral_norm=False` cfg = deepcopy(self.default_config) cfg.update(dict(with_spectral_norm=False)) d = build_module(cfg).cuda() y = d(self.x.cuda(), self.label.cuda()) assert y.shape == (2, 1) # test torch-sn cfg = deepcopy(self.default_config) cfg.update(dict(sn_style='torch')) d = build_module(cfg).cuda() y = d(self.x.cuda(), self.label.cuda()) assert y.shape == (2, 1)

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683e092f89710072f596285139a1b4cad0294c46

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bzl

Python

dnn/scripts/cutlass_generator/list.bzl

nero19960329/MegEngine

4462953fba45bdfb9aaf47b406688206fa5796c3

[ "Apache-2.0" ]

1

2022-03-21T03:13:45.000Z

dnn/scripts/cutlass_generator/list.bzl

Viktor-Paul/MegEngine

4462953fba45bdfb9aaf47b406688206fa5796c3

[ "Apache-2.0" ]

null

dnn/scripts/cutlass_generator/list.bzl

Viktor-Paul/MegEngine

4462953fba45bdfb9aaf47b406688206fa5796c3

[ "Apache-2.0" ]

null

# Generated by dnn/scripts/cutlass_generator/gen_list.py cutlass_gen_list = [ "cutlass_simt_sgemm_8x32_8x2_nn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_8x32_8x2_nn_align1.cu", "cutlass_simt_sgemm_16x32_8x2_nn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_16x32_8x2_nn_align1.cu", "cutlass_simt_sgemm_16x64_8x2_nn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_16x64_8x2_nn_align1.cu", "cutlass_simt_sgemm_32x32_8x2_nn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_32x32_8x2_nn_align1.cu", "cutlass_simt_sgemm_32x64_8x2_nn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_32x64_8x2_nn_align1.cu", "cutlass_simt_sgemm_64x32_8x2_nn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_64x32_8x2_nn_align1.cu", "cutlass_simt_sgemm_16x128_8x2_nn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_16x128_8x2_nn_align1.cu", "cutlass_simt_sgemm_32x128_8x2_nn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_32x128_8x2_nn_align1.cu", "cutlass_simt_sgemm_64x64_8x2_nn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_64x64_8x2_nn_align1.cu", "cutlass_simt_sgemm_128x32_8x2_nn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_128x32_8x2_nn_align1.cu", "cutlass_simt_sgemm_64x128_8x2_nn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_64x128_8x2_nn_align1.cu", "cutlass_simt_sgemm_128x64_8x2_nn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_128x64_8x2_nn_align1.cu", "cutlass_simt_sgemm_32x256_8x2_nn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_32x256_8x2_nn_align1.cu", "cutlass_simt_sgemm_64x256_8x2_nn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_64x256_8x2_nn_align1.cu", "cutlass_simt_sgemm_128x128_8x2_nn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_128x128_8x2_nn_align1.cu", "cutlass_simt_sgemm_256x32_8x2_nn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_256x32_8x2_nn_align1.cu", "cutlass_simt_sgemm_256x64_8x2_nn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_256x64_8x2_nn_align1.cu", "cutlass_simt_sgemm_8x32_8x2_nt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_8x32_8x2_nt_align1.cu", "cutlass_simt_sgemm_16x32_8x2_nt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_16x32_8x2_nt_align1.cu", "cutlass_simt_sgemm_16x64_8x2_nt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_16x64_8x2_nt_align1.cu", "cutlass_simt_sgemm_32x32_8x2_nt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_32x32_8x2_nt_align1.cu", "cutlass_simt_sgemm_32x64_8x2_nt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_32x64_8x2_nt_align1.cu", "cutlass_simt_sgemm_64x32_8x2_nt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_64x32_8x2_nt_align1.cu", "cutlass_simt_sgemm_16x128_8x2_nt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_16x128_8x2_nt_align1.cu", "cutlass_simt_sgemm_32x128_8x2_nt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_32x128_8x2_nt_align1.cu", "cutlass_simt_sgemm_64x64_8x2_nt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_64x64_8x2_nt_align1.cu", "cutlass_simt_sgemm_128x32_8x2_nt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_128x32_8x2_nt_align1.cu", "cutlass_simt_sgemm_64x128_8x2_nt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_64x128_8x2_nt_align1.cu", "cutlass_simt_sgemm_128x64_8x2_nt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_128x64_8x2_nt_align1.cu", "cutlass_simt_sgemm_32x256_8x2_nt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_32x256_8x2_nt_align1.cu", "cutlass_simt_sgemm_64x256_8x2_nt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_64x256_8x2_nt_align1.cu", "cutlass_simt_sgemm_128x128_8x2_nt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_128x128_8x2_nt_align1.cu", "cutlass_simt_sgemm_256x32_8x2_nt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_256x32_8x2_nt_align1.cu", "cutlass_simt_sgemm_256x64_8x2_nt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_256x64_8x2_nt_align1.cu", "cutlass_simt_sgemm_8x32_8x2_tn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_8x32_8x2_tn_align1.cu", "cutlass_simt_sgemm_16x32_8x2_tn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_16x32_8x2_tn_align1.cu", "cutlass_simt_sgemm_16x64_8x2_tn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_16x64_8x2_tn_align1.cu", "cutlass_simt_sgemm_32x32_8x2_tn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_32x32_8x2_tn_align1.cu", "cutlass_simt_sgemm_32x64_8x2_tn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_32x64_8x2_tn_align1.cu", "cutlass_simt_sgemm_64x32_8x2_tn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_64x32_8x2_tn_align1.cu", "cutlass_simt_sgemm_16x128_8x2_tn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_16x128_8x2_tn_align1.cu", "cutlass_simt_sgemm_32x128_8x2_tn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_32x128_8x2_tn_align1.cu", "cutlass_simt_sgemm_64x64_8x2_tn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_64x64_8x2_tn_align1.cu", "cutlass_simt_sgemm_128x32_8x2_tn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_128x32_8x2_tn_align1.cu", "cutlass_simt_sgemm_64x128_8x2_tn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_64x128_8x2_tn_align1.cu", "cutlass_simt_sgemm_128x64_8x2_tn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_128x64_8x2_tn_align1.cu", "cutlass_simt_sgemm_32x256_8x2_tn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_32x256_8x2_tn_align1.cu", "cutlass_simt_sgemm_64x256_8x2_tn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_64x256_8x2_tn_align1.cu", "cutlass_simt_sgemm_128x128_8x2_tn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_128x128_8x2_tn_align1.cu", "cutlass_simt_sgemm_256x32_8x2_tn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_256x32_8x2_tn_align1.cu", "cutlass_simt_sgemm_256x64_8x2_tn_align1.cu", "cutlass_simt_sgemm_split_k_parallel_256x64_8x2_tn_align1.cu", "cutlass_simt_sgemm_8x32_8x2_tt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_8x32_8x2_tt_align1.cu", "cutlass_simt_sgemm_16x32_8x2_tt_align1.cu", "cutlass_simt_sgemm_split_k_parallel_16x32_8x2_tt_align1.cu", "cutlass_simt_sgemm_16x64_8x2_tt_align1.cu", 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"cutlass_simt_sdwwgrad_id_f32_128x128x8_32x64x8_2_nchw_nchw_align1x1.cu", "all_dwconv2d_wgrad_simt_operations.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x256x32_64x64x32_2_nchw_nchw_align8x8.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x128x32_32x32x32_2_nchw_nchw_align8x8.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x128x32_32x32x32_2_nchw_nchw_align8x8.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x64x32_32x32x32_2_nchw_nchw_align8x8.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x64x32_32x32x32_2_nchw_nchw_align8x8.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x256x32_64x64x32_2_nchw_nchw_align8x2.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x128x32_32x32x32_2_nchw_nchw_align8x2.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x128x32_32x32x32_2_nchw_nchw_align8x2.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x64x32_32x32x32_2_nchw_nchw_align8x2.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x64x32_32x32x32_2_nchw_nchw_align8x2.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x256x32_64x64x32_2_nchw_nchw_align8x1.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x128x32_32x32x32_2_nchw_nchw_align8x1.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x128x32_32x32x32_2_nchw_nchw_align8x1.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x64x32_32x32x32_2_nchw_nchw_align8x1.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x64x32_32x32x32_2_nchw_nchw_align8x1.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x256x32_64x64x32_2_nchw_nchw_align2x8.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x128x32_32x32x32_2_nchw_nchw_align2x8.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x128x32_32x32x32_2_nchw_nchw_align2x8.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x64x32_32x32x32_2_nchw_nchw_align2x8.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x64x32_32x32x32_2_nchw_nchw_align2x8.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x256x32_64x64x32_2_nchw_nchw_align2x2.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x128x32_32x32x32_2_nchw_nchw_align2x2.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x128x32_32x32x32_2_nchw_nchw_align2x2.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x64x32_32x32x32_2_nchw_nchw_align2x2.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x64x32_32x32x32_2_nchw_nchw_align2x2.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x256x32_64x64x32_2_nchw_nchw_align2x1.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x128x32_32x32x32_2_nchw_nchw_align2x1.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x128x32_32x32x32_2_nchw_nchw_align2x1.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x64x32_32x32x32_2_nchw_nchw_align2x1.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x64x32_32x32x32_2_nchw_nchw_align2x1.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x256x32_64x64x32_2_nchw_nchw_align1x8.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x128x32_32x32x32_2_nchw_nchw_align1x8.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x128x32_32x32x32_2_nchw_nchw_align1x8.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x64x32_32x32x32_2_nchw_nchw_align1x8.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x64x32_32x32x32_2_nchw_nchw_align1x8.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x256x32_64x64x32_2_nchw_nchw_align1x2.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x128x32_32x32x32_2_nchw_nchw_align1x2.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x128x32_32x32x32_2_nchw_nchw_align1x2.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x64x32_32x32x32_2_nchw_nchw_align1x2.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x64x32_32x32x32_2_nchw_nchw_align1x2.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x256x32_64x64x32_2_nchw_nchw_align1x1.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x128x32_32x32x32_2_nchw_nchw_align1x1.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x128x32_32x32x32_2_nchw_nchw_align1x1.cu", "cutlass_tensorop_s884dwwgrad_id_f16_128x64x32_32x32x32_2_nchw_nchw_align1x1.cu", "cutlass_tensorop_s884dwwgrad_id_f16_64x64x32_32x32x32_2_nchw_nchw_align1x1.cu", "all_dwconv2d_wgrad_tensorop884_operations.cu", ]

85.396253

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0.894771

18,050

123,056

5.259778

0.009363

0.134802

0.19679

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0.994228

0.955192

0.944722

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0.267618

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1,441

113

85.396253

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0

1

0

1

0

1

0

1

null

0

11

68440a5018c4b7319d90021ec4c087a4ac490da8

203

py

Python

example_project/__init__.py

ihumphrey/example_project

8d0d765560c8ce0fb65abb61fc8be9d532d7fd79

[ "MIT" ]

null

example_project/__init__.py

ihumphrey/example_project

8d0d765560c8ce0fb65abb61fc8be9d532d7fd79

[ "MIT" ]

null

example_project/__init__.py

ihumphrey/example_project

8d0d765560c8ce0fb65abb61fc8be9d532d7fd79

[ "MIT" ]

null

"""Top-level package for Example Project.""" from . import _version import sys __version__ = _version.get_versions()['version'] from . import _version __version__ = _version.get_versions()['version']

20.3

48

0.753695

24

203

5.791667

0.5

0.302158

0.244604

0.359712

0.460432

0

0.118227

203

9

49

22.555556

0.776536

0.187192

0

0.8

0

0.08805

0

1

0

false

0

0.6

0

0.6

0

1

0

null

1

0

1

0

1

0

null

0

1

0

1

0

8

68ab6e9b4c232f8c1742e5a9cd264d37347a634d

5,883

py

Python

src/genie/libs/parser/iosxr/tests/ShowMldGroupsDetail/cli/equal/golden_output_1_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

204

2018-06-27T00:55:27.000Z

2022-03-06T21:12:18.000Z

src/genie/libs/parser/iosxr/tests/ShowMldGroupsDetail/cli/equal/golden_output_1_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

468

2018-06-19T00:33:18.000Z

2022-03-31T23:23:35.000Z

src/genie/libs/parser/iosxr/tests/ShowMldGroupsDetail/cli/equal/golden_output_1_expected.py

balmasea/genieparser

d1e71a96dfb081e0a8591707b9d4872decd5d9d3

[ "Apache-2.0" ]

309

2019-01-16T20:21:07.000Z

2022-03-30T12:56:41.000Z

expected_output = { 'vrf': { 'default': { 'interface': { 'GigabitEthernet0/0/0/0': { 'group': { 'ff02::16': { 'expire': 'never', 'router_mode': 'exclude', 'host_mode': 'exclude', 'last_reporter': 'fe80::5054:ff:fefa:9ad7', 'up_time': '1d06h' }, 'ff02::1:ff28:cd4b': { 'expire': '01:00:01', 'router_mode': 'exclude', 'host_mode': 'include', 'last_reporter': 'fe80::eca7:a4ff:fe28:cd4b', 'up_time': '1d06h' }, 'ff02::1:ff60:50aa': { 'expire': '01:00:01', 'router_mode': 'exclude', 'host_mode': 'include', 'last_reporter': 'fe80::eca7:a4ff:fe28:cd4b', 'up_time': '1d06h' }, 'ff02::1:ffae:4aba': { 'expire': '01:00:01', 'router_mode': 'exclude', 'host_mode': 'include', 'last_reporter': 'fe80::eca7:a4ff:fe28:cd4b', 'up_time': '1d06h' }, 'ff02::1:ffd7:c01f': { 'expire': '00:29:15', 'router_mode': 'exclude', 'host_mode': 'include', 'last_reporter': 'fe80::5054:ff:fed7:c01f', 'up_time': '00:33:19' }, 'ff02::1:ffda:f428': { 'expire': '01:00:01', 'router_mode': 'exclude', 'host_mode': 'include', 'last_reporter': 'fe80::eca7:a4ff:fe28:cd4b', 'up_time': '06:27:46' }, 'ff02::2': { 'expire': 'never', 'router_mode': 'exclude', 'host_mode': 'exclude', 'last_reporter': 'fe80::5054:ff:fefa:9ad7', 'up_time': '1d06h' }, 'ff02::d': { 'expire': 'never', 'router_mode': 'exclude', 'host_mode': 'exclude', 'last_reporter': 'fe80::5054:ff:fefa:9ad7', 'up_time': '1d06h' }, 'ff15:1::1': { 'router_mode': 'include', 'host_mode': 'include', 'last_reporter': 'fe80::5054:ff:fefa:9ad7', 'source': { '2001:db8:2:2::2': { 'expire': '01:00:00', 'flags': 'Remote Local 2d', 'forward': True, 'up_time': '08:06:00' } }, 'up_time': '08:06:00' }, 'ff25:2::1': { 'expire': 'never', 'router_mode': 'exclude', 'host_mode': 'exclude', 'last_reporter': 'fe80::5054:ff:fefa:9ad7', 'up_time': '08:06:00' }, 'ff35:1::1': { 'router_mode': 'include', 'host_mode': 'include', 'last_reporter': 'fe80::5054:ff:fefa:9ad7', 'source': { '2001:db8:3:3::3': { 'expire': '01:00:00', 'flags': 'Remote Local e', 'forward': True, 'up_time': '00:33:28' } }, 'up_time': '00:33:28' }, 'ff45:1::1': { 'expire': 'never', 'router_mode': 'exclude', 'host_mode': 'exclude', 'last_reporter': 'fe80::5054:ff:fefa:9ad7', 'up_time': '00:33:28' }, 'fffe::1': { 'expire': '00:59:49', 'router_mode': 'exclude', 'host_mode': 'include', 'last_reporter': 'fe80::5054:ff:fed7:c01f', 'up_time': '07:59:31' } }, 'join_group': { 'ff15:1::1 2001:db8:2:2::2': { 'group': 'ff15:1::1', 'source': '2001:db8:2:2::2' } }, 'static_group': { 'ff35:1::1 2001:db8:3:3::3': { 'group': 'ff35:1::1', 'source': '2001:db8:3:3::3' } } } } } } }

44.908397

73

0.264831

388

5,883

3.868557

0.198454

0.117255

0.138574

0.153897

0.830779

0.774151

0.748834

0.711526

0

0.149138

0.605643

5,883

130

74

45.253846

0.497845

0

0.511628

0

0.293268

0.055933

0

1

0

false

0

null

0

1

0

1

0

1

0

null

0

8

d7b15e0ff41af35d85ee96a91978868dba7ecba6

301

py

Python

tests/data/fmtskip5.py

BigNuoLi/black

71e71e5f52e5f6bdeae63cc8c11b1bee44d11c30

[ "MIT" ]

16,110

2019-07-22T21:54:54.000Z

2022-03-31T22:52:39.000Z

tests/data/fmtskip5.py

marnixah/black-but-usable

83b83d3066d1d857983bfa1a666a409e7255d79d

[ "MIT" ]

1,981

2019-07-22T21:26:16.000Z

2022-03-31T23:14:35.000Z

tests/data/fmtskip5.py

marnixah/black-but-usable

83b83d3066d1d857983bfa1a666a409e7255d79d

[ "MIT" ]

1,762

2019-07-22T21:23:00.000Z

2022-03-31T06:10:22.000Z

a, b, c = 3, 4, 5 if ( a == 3 and b != 9 # fmt: skip and c is not None ): print("I'm good!") else: print("I'm bad") # output a, b, c = 3, 4, 5 if ( a == 3 and b != 9 # fmt: skip and c is not None ): print("I'm good!") else: print("I'm bad")

13.086957

30

0.418605

57

301

2.210526

0.368421

0.190476

0.222222

0.063492

0.952381

0

0.055866

0.405316

301

22

31

13.681818

0.648045

0.086379

0

1

0

0.118081

0

1

0

true

0

0.222222

0

null

0

1

0

1

0

1

0

null

0

1

0

9

d7ea7b0c541a7eae6337932663ca96ca35b0b3da

176

py

Python

ocrr.py

Arjitg450/Python-Programs

0630422c9002632a91b5ccf75f6cd02308c6e929

[ "MIT" ]

null

ocrr.py

Arjitg450/Python-Programs

0630422c9002632a91b5ccf75f6cd02308c6e929

[ "MIT" ]

null

ocrr.py

Arjitg450/Python-Programs

0630422c9002632a91b5ccf75f6cd02308c6e929

[ "MIT" ]

null

from PIL import Image import pytesseract print(pytesseract.image_to_string(Image.open('E:\\aa.png'))) print(pytesseract.image_to_string(Image.open('E:\\aa.png'), lang='eng'))

29.333333

72

0.761364

28

176

4.642857

0.5

0.246154

0.323077

0.353846

0.676923

0

0.056818

176

5

73

35.2

0.783133

0

0.130682

0

1

0

true

0

0.5

0

0.5

1

0

null

1

0

1

0

1

0

null

0

1

0

1

0

1

0

9

cc2032061afb599f9c1abfbcba8193fb1728c5f8

134

py

Python

pyautofinance/common/plotting/__init__.py

webclinic017/PyAutoFinance

532cb1c5418dd9eeb07f2f08646170cde1fe0303

[ "MIT" ]

null

pyautofinance/common/plotting/__init__.py

webclinic017/PyAutoFinance

532cb1c5418dd9eeb07f2f08646170cde1fe0303

[ "MIT" ]

null

pyautofinance/common/plotting/__init__.py

webclinic017/PyAutoFinance

532cb1c5418dd9eeb07f2f08646170cde1fe0303

[ "MIT" ]

1

2022-02-24T09:18:13.000Z

from pyautofinance.common.plotting.live_plotter import LivePlotter from pyautofinance.common.plotting.back_plotter import BackPlotter

44.666667

66

0.895522

16

134

7.375

0.625

0.288136

0.389831

0.525424

0

0.059701

134

2

67

0.936508

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

8

cc2fbf1668de8ddea5a97de5a3526a2ed4340909

470

py

Python

gameOfLife/test.py

Bertik23/spg

f6449f1ca8f3a869f0f493f3988b3d84901c1be0

[ "MIT" ]

null

gameOfLife/test.py

Bertik23/spg

f6449f1ca8f3a869f0f493f3988b3d84901c1be0

[ "MIT" ]

null

gameOfLife/test.py

Bertik23/spg

f6449f1ca8f3a869f0f493f3988b3d84901c1be0

[ "MIT" ]

null

for a in range(2): for b in range(2): for c in range(2): for d in range(2): for e in range(2): for f in range(2): for g in range(2): for h in range(2): print(f"{a}{b}{c}{d}{e}{f}{g}{h}") for a in range(2): for b in range(2): for c in range(2): for d in range(2): print(f"{a}{b}{c}{d}")

31.333333

66

0.357447

76

470

2.210526

0.171053

0.5

0.571429

0.654762

0.738095

0.571429

0

0.050847

0.497872

470

15

67

31.333333

0.661017

0

0.571429

0

0.076433

0.050955

0

1

0

false

0

0.142857

0

null

1

0

1

0

null

0

7

0400059a157f4aa825beaef36545cbf62762aecf

18,237

py

Python

sdk/python/pulumi_aws/ec2/fleet.py

johnktims/pulumi-aws

c838bc79043f5376c66fc66275a1e012edd3ab7d

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

null

sdk/python/pulumi_aws/ec2/fleet.py

johnktims/pulumi-aws

c838bc79043f5376c66fc66275a1e012edd3ab7d

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

null

sdk/python/pulumi_aws/ec2/fleet.py

johnktims/pulumi-aws

c838bc79043f5376c66fc66275a1e012edd3ab7d

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

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import json import warnings import pulumi import pulumi.runtime from typing import Union from .. import utilities, tables class Fleet(pulumi.CustomResource): excess_capacity_termination_policy: pulumi.Output[str] """ Whether running instances should be terminated if the total target capacity of the EC2 Fleet is decreased below the current size of the EC2. Valid values: `no-termination`, `termination`. Defaults to `termination`. """ launch_template_config: pulumi.Output[dict] """ Nested argument containing EC2 Launch Template configurations. Defined below. * `launchTemplateSpecification` (`dict`) - Nested argument containing EC2 Launch Template to use. Defined below. * `launchTemplateId` (`str`) - ID of the launch template. * `launchTemplateName` (`str`) - Name of the launch template. * `version` (`str`) - Version number of the launch template. * `overrides` (`list`) - Nested argument(s) containing parameters to override the same parameters in the Launch Template. Defined below. * `availability_zone` (`str`) - Availability Zone in which to launch the instances. * `instance_type` (`str`) - Instance type. * `maxPrice` (`str`) - Maximum price per unit hour that you are willing to pay for a Spot Instance. * `priority` (`float`) - Priority for the launch template override. If `on_demand_options` `allocation_strategy` is set to `prioritized`, EC2 Fleet uses priority to determine which launch template override to use first in fulfilling On-Demand capacity. The highest priority is launched first. The lower the number, the higher the priority. If no number is set, the launch template override has the lowest priority. Valid values are whole numbers starting at 0. * `subnet_id` (`str`) - ID of the subnet in which to launch the instances. * `weightedCapacity` (`float`) - Number of units provided by the specified instance type. """ on_demand_options: pulumi.Output[dict] """ Nested argument containing On-Demand configurations. Defined below. * `allocation_strategy` (`str`) - How to allocate the target capacity across the Spot pools. Valid values: `diversified`, `lowestPrice`. Default: `lowestPrice`. """ replace_unhealthy_instances: pulumi.Output[bool] """ Whether EC2 Fleet should replace unhealthy instances. Defaults to `false`. """ spot_options: pulumi.Output[dict] """ Nested argument containing Spot configurations. Defined below. * `allocation_strategy` (`str`) - How to allocate the target capacity across the Spot pools. Valid values: `diversified`, `lowestPrice`. Default: `lowestPrice`. * `instanceInterruptionBehavior` (`str`) - Behavior when a Spot Instance is interrupted. Valid values: `hibernate`, `stop`, `terminate`. Default: `terminate`. * `instance_pools_to_use_count` (`float`) - Number of Spot pools across which to allocate your target Spot capacity. Valid only when Spot `allocation_strategy` is set to `lowestPrice`. Default: `1`. """ tags: pulumi.Output[dict] """ Map of Fleet tags. To tag instances at launch, specify the tags in the Launch Template. """ target_capacity_specification: pulumi.Output[dict] """ Nested argument containing target capacity configurations. Defined below. * `defaultTargetCapacityType` (`str`) - Default target capacity type. Valid values: `on-demand`, `spot`. * `onDemandTargetCapacity` (`float`) - The number of On-Demand units to request. * `spotTargetCapacity` (`float`) - The number of Spot units to request. * `totalTargetCapacity` (`float`) - The number of units to request, filled using `default_target_capacity_type`. """ terminate_instances: pulumi.Output[bool] """ Whether to terminate instances for an EC2 Fleet if it is deleted successfully. Defaults to `false`. """ terminate_instances_with_expiration: pulumi.Output[bool] """ Whether running instances should be terminated when the EC2 Fleet expires. Defaults to `false`. """ type: pulumi.Output[str] """ The type of request. Indicates whether the EC2 Fleet only requests the target capacity, or also attempts to maintain it. Valid values: `maintain`, `request`. Defaults to `maintain`. """ def __init__(__self__, resource_name, opts=None, excess_capacity_termination_policy=None, launch_template_config=None, on_demand_options=None, replace_unhealthy_instances=None, spot_options=None, tags=None, target_capacity_specification=None, terminate_instances=None, terminate_instances_with_expiration=None, type=None, __props__=None, __name__=None, __opts__=None): """ Provides a resource to manage EC2 Fleets. :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] excess_capacity_termination_policy: Whether running instances should be terminated if the total target capacity of the EC2 Fleet is decreased below the current size of the EC2. Valid values: `no-termination`, `termination`. Defaults to `termination`. :param pulumi.Input[dict] launch_template_config: Nested argument containing EC2 Launch Template configurations. Defined below. :param pulumi.Input[dict] on_demand_options: Nested argument containing On-Demand configurations. Defined below. :param pulumi.Input[bool] replace_unhealthy_instances: Whether EC2 Fleet should replace unhealthy instances. Defaults to `false`. :param pulumi.Input[dict] spot_options: Nested argument containing Spot configurations. Defined below. :param pulumi.Input[dict] tags: Map of Fleet tags. To tag instances at launch, specify the tags in the Launch Template. :param pulumi.Input[dict] target_capacity_specification: Nested argument containing target capacity configurations. Defined below. :param pulumi.Input[bool] terminate_instances: Whether to terminate instances for an EC2 Fleet if it is deleted successfully. Defaults to `false`. :param pulumi.Input[bool] terminate_instances_with_expiration: Whether running instances should be terminated when the EC2 Fleet expires. Defaults to `false`. :param pulumi.Input[str] type: The type of request. Indicates whether the EC2 Fleet only requests the target capacity, or also attempts to maintain it. Valid values: `maintain`, `request`. Defaults to `maintain`. The **launch_template_config** object supports the following: * `launchTemplateSpecification` (`pulumi.Input[dict]`) - Nested argument containing EC2 Launch Template to use. Defined below. * `launchTemplateId` (`pulumi.Input[str]`) - ID of the launch template. * `launchTemplateName` (`pulumi.Input[str]`) - Name of the launch template. * `version` (`pulumi.Input[str]`) - Version number of the launch template. * `overrides` (`pulumi.Input[list]`) - Nested argument(s) containing parameters to override the same parameters in the Launch Template. Defined below. * `availability_zone` (`pulumi.Input[str]`) - Availability Zone in which to launch the instances. * `instance_type` (`pulumi.Input[str]`) - Instance type. * `maxPrice` (`pulumi.Input[str]`) - Maximum price per unit hour that you are willing to pay for a Spot Instance. * `priority` (`pulumi.Input[float]`) - Priority for the launch template override. If `on_demand_options` `allocation_strategy` is set to `prioritized`, EC2 Fleet uses priority to determine which launch template override to use first in fulfilling On-Demand capacity. The highest priority is launched first. The lower the number, the higher the priority. If no number is set, the launch template override has the lowest priority. Valid values are whole numbers starting at 0. * `subnet_id` (`pulumi.Input[str]`) - ID of the subnet in which to launch the instances. * `weightedCapacity` (`pulumi.Input[float]`) - Number of units provided by the specified instance type. The **on_demand_options** object supports the following: * `allocation_strategy` (`pulumi.Input[str]`) - How to allocate the target capacity across the Spot pools. Valid values: `diversified`, `lowestPrice`. Default: `lowestPrice`. The **spot_options** object supports the following: * `allocation_strategy` (`pulumi.Input[str]`) - How to allocate the target capacity across the Spot pools. Valid values: `diversified`, `lowestPrice`. Default: `lowestPrice`. * `instanceInterruptionBehavior` (`pulumi.Input[str]`) - Behavior when a Spot Instance is interrupted. Valid values: `hibernate`, `stop`, `terminate`. Default: `terminate`. * `instance_pools_to_use_count` (`pulumi.Input[float]`) - Number of Spot pools across which to allocate your target Spot capacity. Valid only when Spot `allocation_strategy` is set to `lowestPrice`. Default: `1`. The **target_capacity_specification** object supports the following: * `defaultTargetCapacityType` (`pulumi.Input[str]`) - Default target capacity type. Valid values: `on-demand`, `spot`. * `onDemandTargetCapacity` (`pulumi.Input[float]`) - The number of On-Demand units to request. * `spotTargetCapacity` (`pulumi.Input[float]`) - The number of Spot units to request. * `totalTargetCapacity` (`pulumi.Input[float]`) - The number of units to request, filled using `default_target_capacity_type`. """ if __name__ is not None: warnings.warn("explicit use of __name__ is deprecated", DeprecationWarning) resource_name = __name__ if __opts__ is not None: warnings.warn("explicit use of __opts__ is deprecated, use 'opts' instead", DeprecationWarning) opts = __opts__ if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = dict() __props__['excess_capacity_termination_policy'] = excess_capacity_termination_policy if launch_template_config is None: raise TypeError("Missing required property 'launch_template_config'") __props__['launch_template_config'] = launch_template_config __props__['on_demand_options'] = on_demand_options __props__['replace_unhealthy_instances'] = replace_unhealthy_instances __props__['spot_options'] = spot_options __props__['tags'] = tags if target_capacity_specification is None: raise TypeError("Missing required property 'target_capacity_specification'") __props__['target_capacity_specification'] = target_capacity_specification __props__['terminate_instances'] = terminate_instances __props__['terminate_instances_with_expiration'] = terminate_instances_with_expiration __props__['type'] = type super(Fleet, __self__).__init__( 'aws:ec2/fleet:Fleet', resource_name, __props__, opts) @staticmethod def get(resource_name, id, opts=None, excess_capacity_termination_policy=None, launch_template_config=None, on_demand_options=None, replace_unhealthy_instances=None, spot_options=None, tags=None, target_capacity_specification=None, terminate_instances=None, terminate_instances_with_expiration=None, type=None): """ Get an existing Fleet resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param str id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] excess_capacity_termination_policy: Whether running instances should be terminated if the total target capacity of the EC2 Fleet is decreased below the current size of the EC2. Valid values: `no-termination`, `termination`. Defaults to `termination`. :param pulumi.Input[dict] launch_template_config: Nested argument containing EC2 Launch Template configurations. Defined below. :param pulumi.Input[dict] on_demand_options: Nested argument containing On-Demand configurations. Defined below. :param pulumi.Input[bool] replace_unhealthy_instances: Whether EC2 Fleet should replace unhealthy instances. Defaults to `false`. :param pulumi.Input[dict] spot_options: Nested argument containing Spot configurations. Defined below. :param pulumi.Input[dict] tags: Map of Fleet tags. To tag instances at launch, specify the tags in the Launch Template. :param pulumi.Input[dict] target_capacity_specification: Nested argument containing target capacity configurations. Defined below. :param pulumi.Input[bool] terminate_instances: Whether to terminate instances for an EC2 Fleet if it is deleted successfully. Defaults to `false`. :param pulumi.Input[bool] terminate_instances_with_expiration: Whether running instances should be terminated when the EC2 Fleet expires. Defaults to `false`. :param pulumi.Input[str] type: The type of request. Indicates whether the EC2 Fleet only requests the target capacity, or also attempts to maintain it. Valid values: `maintain`, `request`. Defaults to `maintain`. The **launch_template_config** object supports the following: * `launchTemplateSpecification` (`pulumi.Input[dict]`) - Nested argument containing EC2 Launch Template to use. Defined below. * `launchTemplateId` (`pulumi.Input[str]`) - ID of the launch template. * `launchTemplateName` (`pulumi.Input[str]`) - Name of the launch template. * `version` (`pulumi.Input[str]`) - Version number of the launch template. * `overrides` (`pulumi.Input[list]`) - Nested argument(s) containing parameters to override the same parameters in the Launch Template. Defined below. * `availability_zone` (`pulumi.Input[str]`) - Availability Zone in which to launch the instances. * `instance_type` (`pulumi.Input[str]`) - Instance type. * `maxPrice` (`pulumi.Input[str]`) - Maximum price per unit hour that you are willing to pay for a Spot Instance. * `priority` (`pulumi.Input[float]`) - Priority for the launch template override. If `on_demand_options` `allocation_strategy` is set to `prioritized`, EC2 Fleet uses priority to determine which launch template override to use first in fulfilling On-Demand capacity. The highest priority is launched first. The lower the number, the higher the priority. If no number is set, the launch template override has the lowest priority. Valid values are whole numbers starting at 0. * `subnet_id` (`pulumi.Input[str]`) - ID of the subnet in which to launch the instances. * `weightedCapacity` (`pulumi.Input[float]`) - Number of units provided by the specified instance type. The **on_demand_options** object supports the following: * `allocation_strategy` (`pulumi.Input[str]`) - How to allocate the target capacity across the Spot pools. Valid values: `diversified`, `lowestPrice`. Default: `lowestPrice`. The **spot_options** object supports the following: * `allocation_strategy` (`pulumi.Input[str]`) - How to allocate the target capacity across the Spot pools. Valid values: `diversified`, `lowestPrice`. Default: `lowestPrice`. * `instanceInterruptionBehavior` (`pulumi.Input[str]`) - Behavior when a Spot Instance is interrupted. Valid values: `hibernate`, `stop`, `terminate`. Default: `terminate`. * `instance_pools_to_use_count` (`pulumi.Input[float]`) - Number of Spot pools across which to allocate your target Spot capacity. Valid only when Spot `allocation_strategy` is set to `lowestPrice`. Default: `1`. The **target_capacity_specification** object supports the following: * `defaultTargetCapacityType` (`pulumi.Input[str]`) - Default target capacity type. Valid values: `on-demand`, `spot`. * `onDemandTargetCapacity` (`pulumi.Input[float]`) - The number of On-Demand units to request. * `spotTargetCapacity` (`pulumi.Input[float]`) - The number of Spot units to request. * `totalTargetCapacity` (`pulumi.Input[float]`) - The number of units to request, filled using `default_target_capacity_type`. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = dict() __props__["excess_capacity_termination_policy"] = excess_capacity_termination_policy __props__["launch_template_config"] = launch_template_config __props__["on_demand_options"] = on_demand_options __props__["replace_unhealthy_instances"] = replace_unhealthy_instances __props__["spot_options"] = spot_options __props__["tags"] = tags __props__["target_capacity_specification"] = target_capacity_specification __props__["terminate_instances"] = terminate_instances __props__["terminate_instances_with_expiration"] = terminate_instances_with_expiration __props__["type"] = type return Fleet(resource_name, opts=opts, __props__=__props__) def translate_output_property(self, prop): return tables._CAMEL_TO_SNAKE_CASE_TABLE.get(prop) or prop def translate_input_property(self, prop): return tables._SNAKE_TO_CAMEL_CASE_TABLE.get(prop) or prop

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0.874038

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0.856447

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0.821344

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18,237

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0.863222

0.521358

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0.027778

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false

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0.027778

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0

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042ae980ee8fddcecd775808d54d940227f36412

312,036

py

Python

msgraph-cli-extensions/beta/teams_beta/azext_teams_beta/generated/_params.py

thewahome/msgraph-cli

33127d9efa23a0e5f5303c93242fbdbb73348671

[ "MIT" ]

null

msgraph-cli-extensions/beta/teams_beta/azext_teams_beta/generated/_params.py

thewahome/msgraph-cli

33127d9efa23a0e5f5303c93242fbdbb73348671

[ "MIT" ]

null

msgraph-cli-extensions/beta/teams_beta/azext_teams_beta/generated/_params.py

thewahome/msgraph-cli

33127d9efa23a0e5f5303c93242fbdbb73348671

[ "MIT" ]

null

# -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- # pylint: disable=too-many-lines # pylint: disable=too-many-statements from msgraph.cli.core.commands.parameters import ( get_three_state_flag, get_enum_type, get_location_type ) from msgraph.cli.core.commands.validators import validate_file_or_dict from azext_teams_beta.action import ( AddApplication, AddUsersMembers, AddAttachments, AddBody, AddChannelIdentity, AddHostedContents, AddPolicyTip, AddConfiguration, AddTopic, AddChatsTemplateParameters, AddChatsMembersValues, AddFunSettings, AddGuestSettings, AddMemberSettings, AddMessagingSettings, AddGroupsMembers, AddGroupsPhoto, AddOfferShiftRequests, AddOpenShiftChangeRequests, AddSchedulingGroups, AddSwapShiftsChangeRequests, AddTimeOffReasons, AddTimeOffRequests, AddApprovedLocation, AddModerationSettings, AddTeamsMembers, AddError, AddTeamsTemplateParameters, AddSharepointIds, AddAudio, AddFileSystemInfo, AddImage, AddTeamsChannelsPhoto, AddPublication, AddVideo, AddSubscriptions, AddVersions, AddMicrosoftGraphWorkbookApplication, AddFunctions, AddPackage, AddSpecialFolder, AddView, AddHashes, AddAlbum, AddTeamsChannelsMembersValues, AddTeamsMembersValues, AddTeamsPrimarychannelMembersValues, AddDraftOpenShift, AddActivities, AddDraftTimeOff, AddEncryption ) def load_arguments(self, _): with self.argument_context('teams app-catalog create-team-app') as c: c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('display_name', type=str, help='The name of the catalog app provided by the app developer in the ' 'Microsoft Teams zip app package.') c.argument('distribution_method', arg_type=get_enum_type(['store', 'organization', 'sideloaded', 'unknownFutureValue']), help='') c.argument('external_id', type=str, help='The ID of the catalog provided by the app developer in the Microsoft ' 'Teams zip app package.') c.argument('app_definitions', type=validate_file_or_dict, help='The details for each version of the app. ' 'Expected value: json-string/@json-file.') with self.argument_context('teams app-catalog delete-team-app') as c: c.argument('teams_app_id', type=str, help='key: id of teamsApp') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams app-catalog list-team-app') as c: c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams app-catalog show-team-app') as c: c.argument('teams_app_id', type=str, help='key: id of teamsApp') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams app-catalog update-team-app') as c: c.argument('teams_app_id', type=str, help='key: id of teamsApp') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('display_name', type=str, help='The name of the catalog app provided by the app developer in the ' 'Microsoft Teams zip app package.') c.argument('distribution_method', arg_type=get_enum_type(['store', 'organization', 'sideloaded', 'unknownFutureValue']), help='') c.argument('external_id', type=str, help='The ID of the catalog provided by the app developer in the Microsoft ' 'Teams zip app package.') c.argument('app_definitions', type=validate_file_or_dict, help='The details for each version of the app. ' 'Expected value: json-string/@json-file.') with self.argument_context('teams app-catalog-team-app create-app-definition') as c: c.argument('teams_app_id', type=str, help='key: id of teamsApp') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('azure_ad_app_id', type=str, help='') c.argument('description', type=str, help='') c.argument('display_name', type=str, help='The name of the app provided by the app developer.') c.argument('last_modified_date_time', help='') c.argument('publishing_state', arg_type=get_enum_type(['submitted', 'rejected', 'published', 'unknownFutureValue']), help='') c.argument('shortdescription', type=str, help='') c.argument('microsoft_graph_teams_app_definition_teams_app_id_teams_app_id', type=str, help='The ID from the ' 'Teams app manifest.') c.argument('version', type=str, help='The version number of the application.') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') with self.argument_context('teams app-catalog-team-app delete-app-definition') as c: c.argument('teams_app_id', type=str, help='key: id of teamsApp') c.argument('teams_app_definition_id', type=str, help='key: id of teamsAppDefinition') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams app-catalog-team-app list-app-definition') as c: c.argument('teams_app_id', type=str, help='key: id of teamsApp') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams app-catalog-team-app show-app-definition') as c: c.argument('teams_app_id', type=str, help='key: id of teamsApp') c.argument('teams_app_definition_id', type=str, help='key: id of teamsAppDefinition') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams app-catalog-team-app update-app-definition') as c: c.argument('teams_app_id', type=str, help='key: id of teamsApp') c.argument('teams_app_definition_id', type=str, help='key: id of teamsAppDefinition') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('azure_ad_app_id', type=str, help='') c.argument('description', type=str, help='') c.argument('display_name', type=str, help='The name of the app provided by the app developer.') c.argument('last_modified_date_time', help='') c.argument('publishing_state', arg_type=get_enum_type(['submitted', 'rejected', 'published', 'unknownFutureValue']), help='') c.argument('shortdescription', type=str, help='') c.argument('microsoft_graph_teams_app_definition_teams_app_id_teams_app_id', type=str, help='The ID from the ' 'Teams app manifest.') c.argument('version', type=str, help='The version number of the application.') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') with self.argument_context('teams chat-chat create-chat') as c: c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='') c.argument('last_updated_date_time', help='') c.argument('topic', type=str, help='') c.argument('installed_apps', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('members', action=AddUsersMembers, nargs='+', help='') c.argument('messages', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('tabs', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') with self.argument_context('teams chat-chat delete-chat') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams chat-chat list-chat') as c: c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams chat-chat show-chat') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams chat-chat update-chat') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='') c.argument('last_updated_date_time', help='') c.argument('topic', type=str, help='') c.argument('installed_apps', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('members', action=AddUsersMembers, nargs='+', help='') c.argument('messages', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('tabs', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') with self.argument_context('teams chat create-installed-app') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Teams App Definition') c.argument('azure_ad_app_id', type=str, help='', arg_group='Teams App Definition') c.argument('description', type=str, help='', arg_group='Teams App Definition') c.argument('display_name', type=str, help='The name of the app provided by the app developer.', arg_group='Teams App Definition') c.argument('last_modified_date_time', help='', arg_group='Teams App Definition') c.argument('publishing_state', arg_type=get_enum_type(['submitted', 'rejected', 'published', 'unknownFutureValue']), help='', arg_group='Teams App ' 'Definition') c.argument('shortdescription', type=str, help='', arg_group='Teams App Definition') c.argument('teams_app_id', type=str, help='The ID from the Teams app manifest.', arg_group='Teams App ' 'Definition') c.argument('version', type=str, help='The version number of the application.', arg_group='Teams App Definition') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition ' 'Created By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition ' 'Created By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition Created ' 'By') c.argument('id1', type=str, help='Read-only.', arg_group='Teams App') c.argument('microsoft_graph_teams_app_display_name', type=str, help='The name of the catalog app provided by ' 'the app developer in the Microsoft Teams zip app package.', arg_group='Teams App') c.argument('distribution_method', arg_type=get_enum_type(['store', 'organization', 'sideloaded', 'unknownFutureValue']), help='', arg_group='Teams ' 'App') c.argument('external_id', type=str, help='The ID of the catalog provided by the app developer in the Microsoft ' 'Teams zip app package.', arg_group='Teams App') c.argument('app_definitions', type=validate_file_or_dict, help='The details for each version of the app. ' 'Expected value: json-string/@json-file.', arg_group='Teams App') with self.argument_context('teams chat create-member') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('display_name', type=str, help='The display name of the user.') c.argument('roles', nargs='+', help='The roles for that user.') with self.argument_context('teams chat create-message') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('attachments', action=AddAttachments, nargs='+', help='Attached files. Attachments are currently ' 'read-only – sending attachments is not supported.') c.argument('body', action=AddBody, nargs='+', help='itemBody') c.argument('channel_identity', action=AddChannelIdentity, nargs='+', help='channelIdentity') c.argument('microsoft_graph_chat_message_chat_id', type=str, help='') c.argument('created_date_time', help='Read only. Timestamp of when the chat message was created.') c.argument('deleted_date_time', help='Read only. Timestamp at which the chat message was deleted, or null if ' 'not deleted.') c.argument('etag', type=str, help='Read-only. Version number of the chat message.') c.argument('importance', arg_type=get_enum_type(['normal', 'high', 'urgent']), help='') c.argument('last_edited_date_time', help='Read only. Timestamp when edits to the chat message were made. ' 'Triggers an \'Edited\' flag in the Microsoft Teams UI. If no edits are made the value is null.') c.argument('last_modified_date_time', help='Read only. Timestamp when the chat message is created (initial ' 'setting) or edited, including when a reaction is added or removed.') c.argument('locale', type=str, help='Locale of the chat message set by the client.') c.argument('mentions', type=validate_file_or_dict, help='List of entities mentioned in the chat message. ' 'Currently supports user, bot, team, channel. Expected value: json-string/@json-file.') c.argument('message_type', arg_type=get_enum_type(['message', 'chatEvent', 'typing']), help='') c.argument('reactions', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('reply_to_id', type=str, help='Read-only. Id of the parent chat message or root chat message of the ' 'thread. (Only applies to chat messages in channels not chats)') c.argument('subject', type=str, help='The subject of the chat message, in plaintext.') c.argument('summary', type=str, help='Summary text of the chat message that could be used for push ' 'notifications and summary views or fall back views. Only applies to channel chat messages, not ' 'chat messages in a chat.') c.argument('web_url', type=str, help='') c.argument('hosted_contents', action=AddHostedContents, nargs='+', help='') c.argument('replies', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('dlp_action', arg_type=get_enum_type(['none', 'notifySender', 'blockAccess', 'blockAccessExternal']), help='', arg_group='Policy Violation') c.argument('justification_text', type=str, help='Justification text provided by the sender of the message when ' 'overriding a policy violation.', arg_group='Policy Violation') c.argument('policy_tip', action=AddPolicyTip, nargs='+', help='chatMessagePolicyViolationPolicyTip', arg_group='Policy Violation') c.argument('user_action', arg_type=get_enum_type(['none', 'override', 'reportFalsePositive']), help='', arg_group='Policy Violation') c.argument('verdict_details', arg_type=get_enum_type(['none', 'allowFalsePositiveOverride', 'allowOverrideWithoutJustification', 'allowOverrideWithJustification']), help='', arg_group='Policy Violation') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='From') with self.argument_context('teams chat create-tab') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('configuration', action=AddConfiguration, nargs='+', help='teamsTabConfiguration') c.argument('display_name', type=str, help='Name of the tab.') c.argument('message_id', type=str, help='') c.argument('sort_order_index', type=str, help='') c.argument('teams_app_id', type=str, help='') c.argument('web_url', type=str, help='Deep link URL of the tab instance. Read only.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Teams App') c.argument('microsoft_graph_teams_app_display_name', type=str, help='The name of the catalog app provided by ' 'the app developer in the Microsoft Teams zip app package.', arg_group='Teams App') c.argument('distribution_method', arg_type=get_enum_type(['store', 'organization', 'sideloaded', 'unknownFutureValue']), help='', arg_group='Teams ' 'App') c.argument('external_id', type=str, help='The ID of the catalog provided by the app developer in the Microsoft ' 'Teams zip app package.', arg_group='Teams App') c.argument('app_definitions', type=validate_file_or_dict, help='The details for each version of the app. ' 'Expected value: json-string/@json-file.', arg_group='Teams App') with self.argument_context('teams chat delete-installed-app') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams chat delete-member') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('conversation_member_id', type=str, help='key: id of conversationMember') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams chat delete-message') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams chat delete-tab') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams chat list-installed-app') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams chat list-member') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams chat list-message') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams chat list-tab') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams chat send-activity-notification') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('topic', action=AddTopic, nargs='+', help='teamworkActivityTopic') c.argument('activity_type', type=str, help='') c.argument('chain_id', type=int, help='') c.argument('preview_text', action=AddBody, nargs='+', help='itemBody') c.argument('template_parameters', action=AddChatsTemplateParameters, nargs='+', help='') c.argument('recipient', type=validate_file_or_dict, help='teamworkNotificationRecipient Expected value: ' 'json-string/@json-file.') with self.argument_context('teams chat show-installed-app') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams chat show-member') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('conversation_member_id', type=str, help='key: id of conversationMember') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams chat show-message') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams chat show-tab') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams chat update-installed-app') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Teams App Definition') c.argument('azure_ad_app_id', type=str, help='', arg_group='Teams App Definition') c.argument('description', type=str, help='', arg_group='Teams App Definition') c.argument('display_name', type=str, help='The name of the app provided by the app developer.', arg_group='Teams App Definition') c.argument('last_modified_date_time', help='', arg_group='Teams App Definition') c.argument('publishing_state', arg_type=get_enum_type(['submitted', 'rejected', 'published', 'unknownFutureValue']), help='', arg_group='Teams App ' 'Definition') c.argument('shortdescription', type=str, help='', arg_group='Teams App Definition') c.argument('teams_app_id', type=str, help='The ID from the Teams app manifest.', arg_group='Teams App ' 'Definition') c.argument('version', type=str, help='The version number of the application.', arg_group='Teams App Definition') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition ' 'Created By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition ' 'Created By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition Created ' 'By') c.argument('id1', type=str, help='Read-only.', arg_group='Teams App') c.argument('microsoft_graph_teams_app_display_name', type=str, help='The name of the catalog app provided by ' 'the app developer in the Microsoft Teams zip app package.', arg_group='Teams App') c.argument('distribution_method', arg_type=get_enum_type(['store', 'organization', 'sideloaded', 'unknownFutureValue']), help='', arg_group='Teams ' 'App') c.argument('external_id', type=str, help='The ID of the catalog provided by the app developer in the Microsoft ' 'Teams zip app package.', arg_group='Teams App') c.argument('app_definitions', type=validate_file_or_dict, help='The details for each version of the app. ' 'Expected value: json-string/@json-file.', arg_group='Teams App') with self.argument_context('teams chat update-member') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('conversation_member_id', type=str, help='key: id of conversationMember') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('display_name', type=str, help='The display name of the user.') c.argument('roles', nargs='+', help='The roles for that user.') with self.argument_context('teams chat update-message') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('attachments', action=AddAttachments, nargs='+', help='Attached files. Attachments are currently ' 'read-only – sending attachments is not supported.') c.argument('body', action=AddBody, nargs='+', help='itemBody') c.argument('channel_identity', action=AddChannelIdentity, nargs='+', help='channelIdentity') c.argument('microsoft_graph_chat_message_chat_id', type=str, help='') c.argument('created_date_time', help='Read only. Timestamp of when the chat message was created.') c.argument('deleted_date_time', help='Read only. Timestamp at which the chat message was deleted, or null if ' 'not deleted.') c.argument('etag', type=str, help='Read-only. Version number of the chat message.') c.argument('importance', arg_type=get_enum_type(['normal', 'high', 'urgent']), help='') c.argument('last_edited_date_time', help='Read only. Timestamp when edits to the chat message were made. ' 'Triggers an \'Edited\' flag in the Microsoft Teams UI. If no edits are made the value is null.') c.argument('last_modified_date_time', help='Read only. Timestamp when the chat message is created (initial ' 'setting) or edited, including when a reaction is added or removed.') c.argument('locale', type=str, help='Locale of the chat message set by the client.') c.argument('mentions', type=validate_file_or_dict, help='List of entities mentioned in the chat message. ' 'Currently supports user, bot, team, channel. Expected value: json-string/@json-file.') c.argument('message_type', arg_type=get_enum_type(['message', 'chatEvent', 'typing']), help='') c.argument('reactions', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('reply_to_id', type=str, help='Read-only. Id of the parent chat message or root chat message of the ' 'thread. (Only applies to chat messages in channels not chats)') c.argument('subject', type=str, help='The subject of the chat message, in plaintext.') c.argument('summary', type=str, help='Summary text of the chat message that could be used for push ' 'notifications and summary views or fall back views. Only applies to channel chat messages, not ' 'chat messages in a chat.') c.argument('web_url', type=str, help='') c.argument('hosted_contents', action=AddHostedContents, nargs='+', help='') c.argument('replies', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('dlp_action', arg_type=get_enum_type(['none', 'notifySender', 'blockAccess', 'blockAccessExternal']), help='', arg_group='Policy Violation') c.argument('justification_text', type=str, help='Justification text provided by the sender of the message when ' 'overriding a policy violation.', arg_group='Policy Violation') c.argument('policy_tip', action=AddPolicyTip, nargs='+', help='chatMessagePolicyViolationPolicyTip', arg_group='Policy Violation') c.argument('user_action', arg_type=get_enum_type(['none', 'override', 'reportFalsePositive']), help='', arg_group='Policy Violation') c.argument('verdict_details', arg_type=get_enum_type(['none', 'allowFalsePositiveOverride', 'allowOverrideWithoutJustification', 'allowOverrideWithJustification']), help='', arg_group='Policy Violation') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='From') with self.argument_context('teams chat update-tab') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('configuration', action=AddConfiguration, nargs='+', help='teamsTabConfiguration') c.argument('display_name', type=str, help='Name of the tab.') c.argument('message_id', type=str, help='') c.argument('sort_order_index', type=str, help='') c.argument('teams_app_id', type=str, help='') c.argument('web_url', type=str, help='Deep link URL of the tab instance. Read only.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Teams App') c.argument('microsoft_graph_teams_app_display_name', type=str, help='The name of the catalog app provided by ' 'the app developer in the Microsoft Teams zip app package.', arg_group='Teams App') c.argument('distribution_method', arg_type=get_enum_type(['store', 'organization', 'sideloaded', 'unknownFutureValue']), help='', arg_group='Teams ' 'App') c.argument('external_id', type=str, help='The ID of the catalog provided by the app developer in the Microsoft ' 'Teams zip app package.', arg_group='Teams App') c.argument('app_definitions', type=validate_file_or_dict, help='The details for each version of the app. ' 'Expected value: json-string/@json-file.', arg_group='Teams App') with self.argument_context('teams chat-installed-app delete-ref-team-app') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams chat-installed-app delete-ref-team-app-definition') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams chat-installed-app set-ref-team-app') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('body', type=validate_file_or_dict, help='New navigation property ref values Expected value: ' 'json-string/@json-file.') with self.argument_context('teams chat-installed-app set-ref-team-app-definition') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('body', type=validate_file_or_dict, help='New navigation property ref values Expected value: ' 'json-string/@json-file.') with self.argument_context('teams chat-installed-app show-ref-team-app') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') with self.argument_context('teams chat-installed-app show-ref-team-app-definition') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') with self.argument_context('teams chat-installed-app show-team-app') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams chat-installed-app show-team-app-definition') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams chat-installed-app upgrade') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') with self.argument_context('teams chat-member add') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('values', action=AddChatsMembersValues, nargs='+', help='') with self.argument_context('teams chat-message create-hosted-content') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('content_bytes', help='') c.argument('content_type', type=str, help='') with self.argument_context('teams chat-message create-reply') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('attachments', action=AddAttachments, nargs='+', help='Attached files. Attachments are currently ' 'read-only – sending attachments is not supported.') c.argument('body', action=AddBody, nargs='+', help='itemBody') c.argument('channel_identity', action=AddChannelIdentity, nargs='+', help='channelIdentity') c.argument('microsoft_graph_chat_message_chat_id', type=str, help='') c.argument('created_date_time', help='Read only. Timestamp of when the chat message was created.') c.argument('deleted_date_time', help='Read only. Timestamp at which the chat message was deleted, or null if ' 'not deleted.') c.argument('etag', type=str, help='Read-only. Version number of the chat message.') c.argument('importance', arg_type=get_enum_type(['normal', 'high', 'urgent']), help='') c.argument('last_edited_date_time', help='Read only. Timestamp when edits to the chat message were made. ' 'Triggers an \'Edited\' flag in the Microsoft Teams UI. If no edits are made the value is null.') c.argument('last_modified_date_time', help='Read only. Timestamp when the chat message is created (initial ' 'setting) or edited, including when a reaction is added or removed.') c.argument('locale', type=str, help='Locale of the chat message set by the client.') c.argument('mentions', type=validate_file_or_dict, help='List of entities mentioned in the chat message. ' 'Currently supports user, bot, team, channel. Expected value: json-string/@json-file.') c.argument('message_type', arg_type=get_enum_type(['message', 'chatEvent', 'typing']), help='') c.argument('reactions', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('reply_to_id', type=str, help='Read-only. Id of the parent chat message or root chat message of the ' 'thread. (Only applies to chat messages in channels not chats)') c.argument('subject', type=str, help='The subject of the chat message, in plaintext.') c.argument('summary', type=str, help='Summary text of the chat message that could be used for push ' 'notifications and summary views or fall back views. Only applies to channel chat messages, not ' 'chat messages in a chat.') c.argument('web_url', type=str, help='') c.argument('hosted_contents', action=AddHostedContents, nargs='+', help='') c.argument('replies', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('dlp_action', arg_type=get_enum_type(['none', 'notifySender', 'blockAccess', 'blockAccessExternal']), help='', arg_group='Policy Violation') c.argument('justification_text', type=str, help='Justification text provided by the sender of the message when ' 'overriding a policy violation.', arg_group='Policy Violation') c.argument('policy_tip', action=AddPolicyTip, nargs='+', help='chatMessagePolicyViolationPolicyTip', arg_group='Policy Violation') c.argument('user_action', arg_type=get_enum_type(['none', 'override', 'reportFalsePositive']), help='', arg_group='Policy Violation') c.argument('verdict_details', arg_type=get_enum_type(['none', 'allowFalsePositiveOverride', 'allowOverrideWithoutJustification', 'allowOverrideWithJustification']), help='', arg_group='Policy Violation') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='From') with self.argument_context('teams chat-message delete-hosted-content') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_hosted_content_id', type=str, help='key: id of chatMessageHostedContent') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams chat-message delete-reply') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_id1', type=str, help='key: id of chatMessage') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams chat-message delta') as c: c.argument('chat_id', type=str, help='key: id of chat') with self.argument_context('teams chat-message list-hosted-content') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams chat-message list-reply') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams chat-message set-hosted-content-content') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_hosted_content_id', type=str, help='key: id of chatMessageHostedContent') c.argument('data', help='New media content.') with self.argument_context('teams chat-message show-hosted-content') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_hosted_content_id', type=str, help='key: id of chatMessageHostedContent') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams chat-message show-hosted-content-content') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_hosted_content_id', type=str, help='key: id of chatMessageHostedContent') with self.argument_context('teams chat-message show-reply') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_id1', type=str, help='key: id of chatMessage') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams chat-message update-hosted-content') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_hosted_content_id', type=str, help='key: id of chatMessageHostedContent') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('content_bytes', help='') c.argument('content_type', type=str, help='') with self.argument_context('teams chat-message update-reply') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_id1', type=str, help='key: id of chatMessage') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('attachments', action=AddAttachments, nargs='+', help='Attached files. Attachments are currently ' 'read-only – sending attachments is not supported.') c.argument('body', action=AddBody, nargs='+', help='itemBody') c.argument('channel_identity', action=AddChannelIdentity, nargs='+', help='channelIdentity') c.argument('microsoft_graph_chat_message_chat_id', type=str, help='') c.argument('created_date_time', help='Read only. Timestamp of when the chat message was created.') c.argument('deleted_date_time', help='Read only. Timestamp at which the chat message was deleted, or null if ' 'not deleted.') c.argument('etag', type=str, help='Read-only. Version number of the chat message.') c.argument('importance', arg_type=get_enum_type(['normal', 'high', 'urgent']), help='') c.argument('last_edited_date_time', help='Read only. Timestamp when edits to the chat message were made. ' 'Triggers an \'Edited\' flag in the Microsoft Teams UI. If no edits are made the value is null.') c.argument('last_modified_date_time', help='Read only. Timestamp when the chat message is created (initial ' 'setting) or edited, including when a reaction is added or removed.') c.argument('locale', type=str, help='Locale of the chat message set by the client.') c.argument('mentions', type=validate_file_or_dict, help='List of entities mentioned in the chat message. ' 'Currently supports user, bot, team, channel. Expected value: json-string/@json-file.') c.argument('message_type', arg_type=get_enum_type(['message', 'chatEvent', 'typing']), help='') c.argument('reactions', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('reply_to_id', type=str, help='Read-only. Id of the parent chat message or root chat message of the ' 'thread. (Only applies to chat messages in channels not chats)') c.argument('subject', type=str, help='The subject of the chat message, in plaintext.') c.argument('summary', type=str, help='Summary text of the chat message that could be used for push ' 'notifications and summary views or fall back views. Only applies to channel chat messages, not ' 'chat messages in a chat.') c.argument('web_url', type=str, help='') c.argument('hosted_contents', action=AddHostedContents, nargs='+', help='') c.argument('replies', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('dlp_action', arg_type=get_enum_type(['none', 'notifySender', 'blockAccess', 'blockAccessExternal']), help='', arg_group='Policy Violation') c.argument('justification_text', type=str, help='Justification text provided by the sender of the message when ' 'overriding a policy violation.', arg_group='Policy Violation') c.argument('policy_tip', action=AddPolicyTip, nargs='+', help='chatMessagePolicyViolationPolicyTip', arg_group='Policy Violation') c.argument('user_action', arg_type=get_enum_type(['none', 'override', 'reportFalsePositive']), help='', arg_group='Policy Violation') c.argument('verdict_details', arg_type=get_enum_type(['none', 'allowFalsePositiveOverride', 'allowOverrideWithoutJustification', 'allowOverrideWithJustification']), help='', arg_group='Policy Violation') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='From') with self.argument_context('teams chat-message-reply delta') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('chat_message_id', type=str, help='key: id of chatMessage') with self.argument_context('teams chat-tab delete-ref-team-app') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams chat-tab set-ref-team-app') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('body', type=validate_file_or_dict, help='New navigation property ref values Expected value: ' 'json-string/@json-file.') with self.argument_context('teams chat-tab show-ref-team-app') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') with self.argument_context('teams chat-tab show-team-app') as c: c.argument('chat_id', type=str, help='key: id of chat') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams group delete-team') as c: c.argument('group_id', type=str, help='key: id of group') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams group show-team') as c: c.argument('group_id', type=str, help='key: id of group') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams group update-team') as c: c.argument('group_id', type=str, help='key: id of group') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('classification', type=str, help='An optional label. Typically describes the data or business ' 'sensitivity of the team. Must match one of a pre-configured set in the tenant\'s directory.') c.argument('created_date_time', help='') c.argument('description', type=str, help='An optional description for the team.') c.argument('display_name', type=str, help='The name of the team.') c.argument('fun_settings', action=AddFunSettings, nargs='+', help='teamFunSettings') c.argument('guest_settings', action=AddGuestSettings, nargs='+', help='teamGuestSettings') c.argument('internal_id', type=str, help='A unique ID for the team that has been used in a few places such as ' 'the audit log/Office 365 Management Activity API.') c.argument('is_archived', arg_type=get_three_state_flag(), help='Whether this team is in read-only mode.') c.argument('is_membership_limited_to_owners', arg_type=get_three_state_flag(), help='') c.argument('member_settings', action=AddMemberSettings, nargs='+', help='teamMemberSettings') c.argument('messaging_settings', action=AddMessagingSettings, nargs='+', help='teamMessagingSettings') c.argument('specialization', arg_type=get_enum_type(['none', 'educationStandard', 'educationClass', 'educationProfessionalLearningCommunity', 'educationStaff', 'healthcareStandard', 'healthcareCareCoordination', 'unknownFutureValue']), help='') c.argument('visibility', arg_type=get_enum_type(['private', 'public', 'hiddenMembership', 'unknownFutureValue']), help='') c.argument('web_url', type=str, help='A hyperlink that will go to the team in the Microsoft Teams client. This ' 'is the URL that you get when you right-click a team in the Microsoft Teams client and select Get ' 'link to team. This URL should be treated as an opaque blob, and not parsed.') c.argument('channels', type=validate_file_or_dict, help='The collection of channels & messages associated with ' 'the team. Expected value: json-string/@json-file.') c.argument('group', type=validate_file_or_dict, help='Represents an Azure Active Directory object. The ' 'directoryObject type is the base type for many other directory entity types. Expected value: ' 'json-string/@json-file.') c.argument('installed_apps', type=validate_file_or_dict, help='The apps installed in this team. Expected ' 'value: json-string/@json-file.') c.argument('members', action=AddGroupsMembers, nargs='+', help='Members and owners of the team.') c.argument('operations', type=validate_file_or_dict, help='The async operations that ran or are running on ' 'this team. Expected value: json-string/@json-file.') c.argument('owners', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('photo', action=AddGroupsPhoto, nargs='+', help='profilePhoto') c.argument('primary_channel', type=validate_file_or_dict, help='channel Expected value: ' 'json-string/@json-file.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Template') c.argument('id1', type=str, help='Read-only.', arg_group='Schedule') c.argument('enabled', arg_type=get_three_state_flag(), help='Indicates whether the schedule is enabled for the ' 'team. Required.', arg_group='Schedule') c.argument('offer_shift_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether offer ' 'shift requests are enabled for the schedule.', arg_group='Schedule') c.argument('open_shifts_enabled', arg_type=get_three_state_flag(), help='Indicates whether open shifts are ' 'enabled for the schedule.', arg_group='Schedule') c.argument('provision_status', arg_type=get_enum_type(['NotStarted', 'Running', 'Completed', 'Failed']), help='', arg_group='Schedule') c.argument('provision_status_code', type=str, help='Additional information about why schedule provisioning ' 'failed.', arg_group='Schedule') c.argument('swap_shifts_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether swap ' 'shifts requests are enabled for the schedule.', arg_group='Schedule') c.argument('time_clock_enabled', arg_type=get_three_state_flag(), help='Indicates whether time clock is ' 'enabled for the schedule.', arg_group='Schedule') c.argument('time_off_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether time off ' 'requests are enabled for the schedule.', arg_group='Schedule') c.argument('time_zone', type=str, help='Indicates the time zone of the schedule team using tz database format. ' 'Required.', arg_group='Schedule') c.argument('workforce_integration_ids', nargs='+', help='', arg_group='Schedule') c.argument('offer_shift_requests', action=AddOfferShiftRequests, nargs='+', help='', arg_group='Schedule') c.argument('open_shift_change_requests', action=AddOpenShiftChangeRequests, nargs='+', help='', arg_group='Schedule') c.argument('open_shifts', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Schedule') c.argument('scheduling_groups', action=AddSchedulingGroups, nargs='+', help='The logical grouping of users in ' 'the schedule (usually by role).', arg_group='Schedule') c.argument('shifts', type=validate_file_or_dict, help='The shifts in the schedule. Expected value: ' 'json-string/@json-file.', arg_group='Schedule') c.argument('swap_shifts_change_requests', action=AddSwapShiftsChangeRequests, nargs='+', help='', arg_group='Schedule') c.argument('time_cards', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Schedule') c.argument('time_off_reasons', action=AddTimeOffReasons, nargs='+', help='The set of reasons for a time off in ' 'the schedule.', arg_group='Schedule') c.argument('time_off_requests', action=AddTimeOffRequests, nargs='+', help='', arg_group='Schedule') c.argument('times_off', type=validate_file_or_dict, help='The instances of times off in the schedule. Expected ' 'value: json-string/@json-file.', arg_group='Schedule') c.argument('approved_location', action=AddApprovedLocation, nargs='+', help='geoCoordinates', arg_group='Schedule Time Clock Settings') c.argument('show_in_teams_search_and_suggestions', arg_type=get_three_state_flag(), help='', arg_group='Discovery Settings') with self.argument_context('teams team list') as c: c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team create') as c: c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('classification', type=str, help='An optional label. Typically describes the data or business ' 'sensitivity of the team. Must match one of a pre-configured set in the tenant\'s directory.') c.argument('created_date_time', help='') c.argument('description', type=str, help='An optional description for the team.') c.argument('display_name', type=str, help='The name of the team.') c.argument('fun_settings', action=AddFunSettings, nargs='+', help='teamFunSettings') c.argument('guest_settings', action=AddGuestSettings, nargs='+', help='teamGuestSettings') c.argument('internal_id', type=str, help='A unique ID for the team that has been used in a few places such as ' 'the audit log/Office 365 Management Activity API.') c.argument('is_archived', arg_type=get_three_state_flag(), help='Whether this team is in read-only mode.') c.argument('is_membership_limited_to_owners', arg_type=get_three_state_flag(), help='') c.argument('member_settings', action=AddMemberSettings, nargs='+', help='teamMemberSettings') c.argument('messaging_settings', action=AddMessagingSettings, nargs='+', help='teamMessagingSettings') c.argument('specialization', arg_type=get_enum_type(['none', 'educationStandard', 'educationClass', 'educationProfessionalLearningCommunity', 'educationStaff', 'healthcareStandard', 'healthcareCareCoordination', 'unknownFutureValue']), help='') c.argument('visibility', arg_type=get_enum_type(['private', 'public', 'hiddenMembership', 'unknownFutureValue']), help='') c.argument('web_url', type=str, help='A hyperlink that will go to the team in the Microsoft Teams client. This ' 'is the URL that you get when you right-click a team in the Microsoft Teams client and select Get ' 'link to team. This URL should be treated as an opaque blob, and not parsed.') c.argument('channels', type=validate_file_or_dict, help='The collection of channels & messages associated with ' 'the team. Expected value: json-string/@json-file.') c.argument('group', type=validate_file_or_dict, help='Represents an Azure Active Directory object. The ' 'directoryObject type is the base type for many other directory entity types. Expected value: ' 'json-string/@json-file.') c.argument('installed_apps', type=validate_file_or_dict, help='The apps installed in this team. Expected ' 'value: json-string/@json-file.') c.argument('members', action=AddGroupsMembers, nargs='+', help='Members and owners of the team.') c.argument('operations', type=validate_file_or_dict, help='The async operations that ran or are running on ' 'this team. Expected value: json-string/@json-file.') c.argument('owners', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('photo', action=AddGroupsPhoto, nargs='+', help='profilePhoto') c.argument('primary_channel', type=validate_file_or_dict, help='channel Expected value: ' 'json-string/@json-file.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Template') c.argument('id1', type=str, help='Read-only.', arg_group='Schedule') c.argument('enabled', arg_type=get_three_state_flag(), help='Indicates whether the schedule is enabled for the ' 'team. Required.', arg_group='Schedule') c.argument('offer_shift_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether offer ' 'shift requests are enabled for the schedule.', arg_group='Schedule') c.argument('open_shifts_enabled', arg_type=get_three_state_flag(), help='Indicates whether open shifts are ' 'enabled for the schedule.', arg_group='Schedule') c.argument('provision_status', arg_type=get_enum_type(['NotStarted', 'Running', 'Completed', 'Failed']), help='', arg_group='Schedule') c.argument('provision_status_code', type=str, help='Additional information about why schedule provisioning ' 'failed.', arg_group='Schedule') c.argument('swap_shifts_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether swap ' 'shifts requests are enabled for the schedule.', arg_group='Schedule') c.argument('time_clock_enabled', arg_type=get_three_state_flag(), help='Indicates whether time clock is ' 'enabled for the schedule.', arg_group='Schedule') c.argument('time_off_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether time off ' 'requests are enabled for the schedule.', arg_group='Schedule') c.argument('time_zone', type=str, help='Indicates the time zone of the schedule team using tz database format. ' 'Required.', arg_group='Schedule') c.argument('workforce_integration_ids', nargs='+', help='', arg_group='Schedule') c.argument('offer_shift_requests', action=AddOfferShiftRequests, nargs='+', help='', arg_group='Schedule') c.argument('open_shift_change_requests', action=AddOpenShiftChangeRequests, nargs='+', help='', arg_group='Schedule') c.argument('open_shifts', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Schedule') c.argument('scheduling_groups', action=AddSchedulingGroups, nargs='+', help='The logical grouping of users in ' 'the schedule (usually by role).', arg_group='Schedule') c.argument('shifts', type=validate_file_or_dict, help='The shifts in the schedule. Expected value: ' 'json-string/@json-file.', arg_group='Schedule') c.argument('swap_shifts_change_requests', action=AddSwapShiftsChangeRequests, nargs='+', help='', arg_group='Schedule') c.argument('time_cards', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Schedule') c.argument('time_off_reasons', action=AddTimeOffReasons, nargs='+', help='The set of reasons for a time off in ' 'the schedule.', arg_group='Schedule') c.argument('time_off_requests', action=AddTimeOffRequests, nargs='+', help='', arg_group='Schedule') c.argument('times_off', type=validate_file_or_dict, help='The instances of times off in the schedule. Expected ' 'value: json-string/@json-file.', arg_group='Schedule') c.argument('approved_location', action=AddApprovedLocation, nargs='+', help='geoCoordinates', arg_group='Schedule Time Clock Settings') c.argument('show_in_teams_search_and_suggestions', arg_type=get_three_state_flag(), help='', arg_group='Discovery Settings') with self.argument_context('teams team update') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('classification', type=str, help='An optional label. Typically describes the data or business ' 'sensitivity of the team. Must match one of a pre-configured set in the tenant\'s directory.') c.argument('created_date_time', help='') c.argument('description', type=str, help='An optional description for the team.') c.argument('display_name', type=str, help='The name of the team.') c.argument('fun_settings', action=AddFunSettings, nargs='+', help='teamFunSettings') c.argument('guest_settings', action=AddGuestSettings, nargs='+', help='teamGuestSettings') c.argument('internal_id', type=str, help='A unique ID for the team that has been used in a few places such as ' 'the audit log/Office 365 Management Activity API.') c.argument('is_archived', arg_type=get_three_state_flag(), help='Whether this team is in read-only mode.') c.argument('is_membership_limited_to_owners', arg_type=get_three_state_flag(), help='') c.argument('member_settings', action=AddMemberSettings, nargs='+', help='teamMemberSettings') c.argument('messaging_settings', action=AddMessagingSettings, nargs='+', help='teamMessagingSettings') c.argument('specialization', arg_type=get_enum_type(['none', 'educationStandard', 'educationClass', 'educationProfessionalLearningCommunity', 'educationStaff', 'healthcareStandard', 'healthcareCareCoordination', 'unknownFutureValue']), help='') c.argument('visibility', arg_type=get_enum_type(['private', 'public', 'hiddenMembership', 'unknownFutureValue']), help='') c.argument('web_url', type=str, help='A hyperlink that will go to the team in the Microsoft Teams client. This ' 'is the URL that you get when you right-click a team in the Microsoft Teams client and select Get ' 'link to team. This URL should be treated as an opaque blob, and not parsed.') c.argument('channels', type=validate_file_or_dict, help='The collection of channels & messages associated with ' 'the team. Expected value: json-string/@json-file.') c.argument('group', type=validate_file_or_dict, help='Represents an Azure Active Directory object. The ' 'directoryObject type is the base type for many other directory entity types. Expected value: ' 'json-string/@json-file.') c.argument('installed_apps', type=validate_file_or_dict, help='The apps installed in this team. Expected ' 'value: json-string/@json-file.') c.argument('members', action=AddGroupsMembers, nargs='+', help='Members and owners of the team.') c.argument('operations', type=validate_file_or_dict, help='The async operations that ran or are running on ' 'this team. Expected value: json-string/@json-file.') c.argument('owners', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('photo', action=AddGroupsPhoto, nargs='+', help='profilePhoto') c.argument('primary_channel', type=validate_file_or_dict, help='channel Expected value: ' 'json-string/@json-file.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Template') c.argument('id1', type=str, help='Read-only.', arg_group='Schedule') c.argument('enabled', arg_type=get_three_state_flag(), help='Indicates whether the schedule is enabled for the ' 'team. Required.', arg_group='Schedule') c.argument('offer_shift_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether offer ' 'shift requests are enabled for the schedule.', arg_group='Schedule') c.argument('open_shifts_enabled', arg_type=get_three_state_flag(), help='Indicates whether open shifts are ' 'enabled for the schedule.', arg_group='Schedule') c.argument('provision_status', arg_type=get_enum_type(['NotStarted', 'Running', 'Completed', 'Failed']), help='', arg_group='Schedule') c.argument('provision_status_code', type=str, help='Additional information about why schedule provisioning ' 'failed.', arg_group='Schedule') c.argument('swap_shifts_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether swap ' 'shifts requests are enabled for the schedule.', arg_group='Schedule') c.argument('time_clock_enabled', arg_type=get_three_state_flag(), help='Indicates whether time clock is ' 'enabled for the schedule.', arg_group='Schedule') c.argument('time_off_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether time off ' 'requests are enabled for the schedule.', arg_group='Schedule') c.argument('time_zone', type=str, help='Indicates the time zone of the schedule team using tz database format. ' 'Required.', arg_group='Schedule') c.argument('workforce_integration_ids', nargs='+', help='', arg_group='Schedule') c.argument('offer_shift_requests', action=AddOfferShiftRequests, nargs='+', help='', arg_group='Schedule') c.argument('open_shift_change_requests', action=AddOpenShiftChangeRequests, nargs='+', help='', arg_group='Schedule') c.argument('open_shifts', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Schedule') c.argument('scheduling_groups', action=AddSchedulingGroups, nargs='+', help='The logical grouping of users in ' 'the schedule (usually by role).', arg_group='Schedule') c.argument('shifts', type=validate_file_or_dict, help='The shifts in the schedule. Expected value: ' 'json-string/@json-file.', arg_group='Schedule') c.argument('swap_shifts_change_requests', action=AddSwapShiftsChangeRequests, nargs='+', help='', arg_group='Schedule') c.argument('time_cards', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Schedule') c.argument('time_off_reasons', action=AddTimeOffReasons, nargs='+', help='The set of reasons for a time off in ' 'the schedule.', arg_group='Schedule') c.argument('time_off_requests', action=AddTimeOffRequests, nargs='+', help='', arg_group='Schedule') c.argument('times_off', type=validate_file_or_dict, help='The instances of times off in the schedule. Expected ' 'value: json-string/@json-file.', arg_group='Schedule') c.argument('approved_location', action=AddApprovedLocation, nargs='+', help='geoCoordinates', arg_group='Schedule Time Clock Settings') c.argument('show_in_teams_search_and_suggestions', arg_type=get_three_state_flag(), help='', arg_group='Discovery Settings') with self.argument_context('teams team delete-team') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team show-team') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team archive') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('should_set_spo_site_read_only_for_members', arg_type=get_three_state_flag(), help='') with self.argument_context('teams team clone') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('display_name', type=str, help='') c.argument('description', type=str, help='') c.argument('mail_nickname', type=str, help='') c.argument('classification', type=str, help='') c.argument('visibility', arg_type=get_enum_type(['private', 'public', 'hiddenMembership', 'unknownFutureValue']), help='') c.argument('parts_to_clone', arg_type=get_enum_type(['apps', 'tabs', 'settings', 'channels', 'members']), help='') with self.argument_context('teams team complete-migration') as c: c.argument('team_id', type=str, help='key: id of team') with self.argument_context('teams team create-channel') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='Read only. Timestamp at which the channel was created.') c.argument('description', type=str, help='Optional textual description for the channel.') c.argument('display_name', type=str, help='Channel name as it will appear to the user in Microsoft Teams.') c.argument('email', type=str, help='The email address for sending messages to the channel. Read-only.') c.argument('is_favorite_by_default', arg_type=get_three_state_flag(), help='Indicates whether the channel ' 'should automatically be marked \'favorite\' for all members of the team. Can only be set ' 'programmatically with Create team. Default: false.') c.argument('membership_type', arg_type=get_enum_type(['standard', 'private', 'unknownFutureValue']), help='') c.argument('moderation_settings', action=AddModerationSettings, nargs='+', help='channelModerationSettings') c.argument('web_url', type=str, help='A hyperlink that will go to the channel in Microsoft Teams. This is the ' 'URL that you get when you right-click a channel in Microsoft Teams and select Get link to channel. ' 'This URL should be treated as an opaque blob, and not parsed. Read-only.') c.argument('files_folder', type=validate_file_or_dict, help='driveItem Expected value: json-string/@json-file.') c.argument('members', action=AddTeamsMembers, nargs='+', help='') c.argument('messages', type=validate_file_or_dict, help='A collection of all the messages in the channel. A ' 'navigation property. Nullable. Expected value: json-string/@json-file.') c.argument('tabs', type=validate_file_or_dict, help='A collection of all the tabs in the channel. A navigation ' 'property. Expected value: json-string/@json-file.') with self.argument_context('teams team create-installed-app') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Teams App Definition') c.argument('azure_ad_app_id', type=str, help='', arg_group='Teams App Definition') c.argument('description', type=str, help='', arg_group='Teams App Definition') c.argument('display_name', type=str, help='The name of the app provided by the app developer.', arg_group='Teams App Definition') c.argument('last_modified_date_time', help='', arg_group='Teams App Definition') c.argument('publishing_state', arg_type=get_enum_type(['submitted', 'rejected', 'published', 'unknownFutureValue']), help='', arg_group='Teams App ' 'Definition') c.argument('shortdescription', type=str, help='', arg_group='Teams App Definition') c.argument('teams_app_id', type=str, help='The ID from the Teams app manifest.', arg_group='Teams App ' 'Definition') c.argument('version', type=str, help='The version number of the application.', arg_group='Teams App Definition') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition ' 'Created By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition ' 'Created By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition Created ' 'By') c.argument('id1', type=str, help='Read-only.', arg_group='Teams App') c.argument('microsoft_graph_teams_app_display_name', type=str, help='The name of the catalog app provided by ' 'the app developer in the Microsoft Teams zip app package.', arg_group='Teams App') c.argument('distribution_method', arg_type=get_enum_type(['store', 'organization', 'sideloaded', 'unknownFutureValue']), help='', arg_group='Teams ' 'App') c.argument('external_id', type=str, help='The ID of the catalog provided by the app developer in the Microsoft ' 'Teams zip app package.', arg_group='Teams App') c.argument('app_definitions', type=validate_file_or_dict, help='The details for each version of the app. ' 'Expected value: json-string/@json-file.', arg_group='Teams App') with self.argument_context('teams team create-member') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('display_name', type=str, help='The display name of the user.') c.argument('roles', nargs='+', help='The roles for that user.') with self.argument_context('teams team create-operation') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('attempts_count', type=int, help='Number of times the operation was attempted before being marked ' 'successful or failed.') c.argument('created_date_time', help='Time when the operation was created.') c.argument('error', action=AddError, nargs='+', help='operationError') c.argument('last_action_date_time', help='Time when the async operation was last updated.') c.argument('operation_type', arg_type=get_enum_type(['invalid', 'cloneTeam', 'archiveTeam', 'unarchiveTeam', 'createTeam', 'unknownFutureValue']), help='') c.argument('status', arg_type=get_enum_type(['invalid', 'notStarted', 'inProgress', 'succeeded', 'failed', 'unknownFutureValue']), help='') c.argument('target_resource_id', type=str, help='The ID of the object that\'s created or modified as result of ' 'this async operation, typically a team.') c.argument('target_resource_location', type=str, help='The location of the object that\'s created or modified ' 'as result of this async operation. This URL should be treated as an opaque value and not parsed ' 'into its component paths.') with self.argument_context('teams team create-ref-owner') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('body', type=validate_file_or_dict, help='New navigation property ref value Expected value: ' 'json-string/@json-file.') with self.argument_context('teams team delete-channel') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team delete-installed-app') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team delete-member') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('conversation_member_id', type=str, help='key: id of conversationMember') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team delete-operation') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_async_operation_id', type=str, help='key: id of teamsAsyncOperation') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team delete-photo') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team delete-primary-channel') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team delete-ref-group') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team delete-ref-template') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team delete-schedule') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team list-channel') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team list-installed-app') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team list-member') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team list-operation') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team list-owner') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team list-ref-owner') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') with self.argument_context('teams team send-activity-notification') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('topic', action=AddTopic, nargs='+', help='teamworkActivityTopic') c.argument('activity_type', type=str, help='') c.argument('chain_id', type=int, help='') c.argument('preview_text', action=AddBody, nargs='+', help='itemBody') c.argument('template_parameters', action=AddTeamsTemplateParameters, nargs='+', help='') c.argument('recipient', type=validate_file_or_dict, help='teamworkNotificationRecipient Expected value: ' 'json-string/@json-file.') with self.argument_context('teams team set-photo-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('data', help='New media content.') with self.argument_context('teams team set-ref-group') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('body', type=validate_file_or_dict, help='New navigation property ref values Expected value: ' 'json-string/@json-file.') with self.argument_context('teams team set-ref-template') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('body', type=validate_file_or_dict, help='New navigation property ref values Expected value: ' 'json-string/@json-file.') with self.argument_context('teams team show-channel') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team show-group') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team show-installed-app') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team show-member') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('conversation_member_id', type=str, help='key: id of conversationMember') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team show-operation') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_async_operation_id', type=str, help='key: id of teamsAsyncOperation') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team show-photo') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team show-photo-content') as c: c.argument('team_id', type=str, help='key: id of team') with self.argument_context('teams team show-primary-channel') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team show-ref-group') as c: c.argument('team_id', type=str, help='key: id of team') with self.argument_context('teams team show-ref-template') as c: c.argument('team_id', type=str, help='key: id of team') with self.argument_context('teams team show-schedule') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team show-template') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team unarchive') as c: c.argument('team_id', type=str, help='key: id of team') with self.argument_context('teams team update-channel') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='Read only. Timestamp at which the channel was created.') c.argument('description', type=str, help='Optional textual description for the channel.') c.argument('display_name', type=str, help='Channel name as it will appear to the user in Microsoft Teams.') c.argument('email', type=str, help='The email address for sending messages to the channel. Read-only.') c.argument('is_favorite_by_default', arg_type=get_three_state_flag(), help='Indicates whether the channel ' 'should automatically be marked \'favorite\' for all members of the team. Can only be set ' 'programmatically with Create team. Default: false.') c.argument('membership_type', arg_type=get_enum_type(['standard', 'private', 'unknownFutureValue']), help='') c.argument('moderation_settings', action=AddModerationSettings, nargs='+', help='channelModerationSettings') c.argument('web_url', type=str, help='A hyperlink that will go to the channel in Microsoft Teams. This is the ' 'URL that you get when you right-click a channel in Microsoft Teams and select Get link to channel. ' 'This URL should be treated as an opaque blob, and not parsed. Read-only.') c.argument('files_folder', type=validate_file_or_dict, help='driveItem Expected value: json-string/@json-file.') c.argument('members', action=AddTeamsMembers, nargs='+', help='') c.argument('messages', type=validate_file_or_dict, help='A collection of all the messages in the channel. A ' 'navigation property. Nullable. Expected value: json-string/@json-file.') c.argument('tabs', type=validate_file_or_dict, help='A collection of all the tabs in the channel. A navigation ' 'property. Expected value: json-string/@json-file.') with self.argument_context('teams team update-installed-app') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Teams App Definition') c.argument('azure_ad_app_id', type=str, help='', arg_group='Teams App Definition') c.argument('description', type=str, help='', arg_group='Teams App Definition') c.argument('display_name', type=str, help='The name of the app provided by the app developer.', arg_group='Teams App Definition') c.argument('last_modified_date_time', help='', arg_group='Teams App Definition') c.argument('publishing_state', arg_type=get_enum_type(['submitted', 'rejected', 'published', 'unknownFutureValue']), help='', arg_group='Teams App ' 'Definition') c.argument('shortdescription', type=str, help='', arg_group='Teams App Definition') c.argument('teams_app_id', type=str, help='The ID from the Teams app manifest.', arg_group='Teams App ' 'Definition') c.argument('version', type=str, help='The version number of the application.', arg_group='Teams App Definition') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition ' 'Created By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition ' 'Created By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition Created ' 'By') c.argument('id1', type=str, help='Read-only.', arg_group='Teams App') c.argument('microsoft_graph_teams_app_display_name', type=str, help='The name of the catalog app provided by ' 'the app developer in the Microsoft Teams zip app package.', arg_group='Teams App') c.argument('distribution_method', arg_type=get_enum_type(['store', 'organization', 'sideloaded', 'unknownFutureValue']), help='', arg_group='Teams ' 'App') c.argument('external_id', type=str, help='The ID of the catalog provided by the app developer in the Microsoft ' 'Teams zip app package.', arg_group='Teams App') c.argument('app_definitions', type=validate_file_or_dict, help='The details for each version of the app. ' 'Expected value: json-string/@json-file.', arg_group='Teams App') with self.argument_context('teams team update-member') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('conversation_member_id', type=str, help='key: id of conversationMember') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('display_name', type=str, help='The display name of the user.') c.argument('roles', nargs='+', help='The roles for that user.') with self.argument_context('teams team update-operation') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_async_operation_id', type=str, help='key: id of teamsAsyncOperation') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('attempts_count', type=int, help='Number of times the operation was attempted before being marked ' 'successful or failed.') c.argument('created_date_time', help='Time when the operation was created.') c.argument('error', action=AddError, nargs='+', help='operationError') c.argument('last_action_date_time', help='Time when the async operation was last updated.') c.argument('operation_type', arg_type=get_enum_type(['invalid', 'cloneTeam', 'archiveTeam', 'unarchiveTeam', 'createTeam', 'unknownFutureValue']), help='') c.argument('status', arg_type=get_enum_type(['invalid', 'notStarted', 'inProgress', 'succeeded', 'failed', 'unknownFutureValue']), help='') c.argument('target_resource_id', type=str, help='The ID of the object that\'s created or modified as result of ' 'this async operation, typically a team.') c.argument('target_resource_location', type=str, help='The location of the object that\'s created or modified ' 'as result of this async operation. This URL should be treated as an opaque value and not parsed ' 'into its component paths.') with self.argument_context('teams team update-photo') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('height', type=int, help='The height of the photo. Read-only.') c.argument('width', type=int, help='The width of the photo. Read-only.') with self.argument_context('teams team update-primary-channel') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='Read only. Timestamp at which the channel was created.') c.argument('description', type=str, help='Optional textual description for the channel.') c.argument('display_name', type=str, help='Channel name as it will appear to the user in Microsoft Teams.') c.argument('email', type=str, help='The email address for sending messages to the channel. Read-only.') c.argument('is_favorite_by_default', arg_type=get_three_state_flag(), help='Indicates whether the channel ' 'should automatically be marked \'favorite\' for all members of the team. Can only be set ' 'programmatically with Create team. Default: false.') c.argument('membership_type', arg_type=get_enum_type(['standard', 'private', 'unknownFutureValue']), help='') c.argument('moderation_settings', action=AddModerationSettings, nargs='+', help='channelModerationSettings') c.argument('web_url', type=str, help='A hyperlink that will go to the channel in Microsoft Teams. This is the ' 'URL that you get when you right-click a channel in Microsoft Teams and select Get link to channel. ' 'This URL should be treated as an opaque blob, and not parsed. Read-only.') c.argument('files_folder', type=validate_file_or_dict, help='driveItem Expected value: json-string/@json-file.') c.argument('members', action=AddTeamsMembers, nargs='+', help='') c.argument('messages', type=validate_file_or_dict, help='A collection of all the messages in the channel. A ' 'navigation property. Nullable. Expected value: json-string/@json-file.') c.argument('tabs', type=validate_file_or_dict, help='A collection of all the tabs in the channel. A navigation ' 'property. Expected value: json-string/@json-file.') with self.argument_context('teams team update-schedule') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('enabled', arg_type=get_three_state_flag(), help='Indicates whether the schedule is enabled for the ' 'team. Required.') c.argument('offer_shift_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether offer ' 'shift requests are enabled for the schedule.') c.argument('open_shifts_enabled', arg_type=get_three_state_flag(), help='Indicates whether open shifts are ' 'enabled for the schedule.') c.argument('provision_status', arg_type=get_enum_type(['NotStarted', 'Running', 'Completed', 'Failed']), help='') c.argument('provision_status_code', type=str, help='Additional information about why schedule provisioning ' 'failed.') c.argument('swap_shifts_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether swap ' 'shifts requests are enabled for the schedule.') c.argument('time_clock_enabled', arg_type=get_three_state_flag(), help='Indicates whether time clock is ' 'enabled for the schedule.') c.argument('time_off_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether time off ' 'requests are enabled for the schedule.') c.argument('time_zone', type=str, help='Indicates the time zone of the schedule team using tz database format. ' 'Required.') c.argument('workforce_integration_ids', nargs='+', help='') c.argument('offer_shift_requests', action=AddOfferShiftRequests, nargs='+', help='') c.argument('open_shift_change_requests', action=AddOpenShiftChangeRequests, nargs='+', help='') c.argument('open_shifts', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('scheduling_groups', action=AddSchedulingGroups, nargs='+', help='The logical grouping of users in ' 'the schedule (usually by role).') c.argument('shifts', type=validate_file_or_dict, help='The shifts in the schedule. Expected value: ' 'json-string/@json-file.') c.argument('swap_shifts_change_requests', action=AddSwapShiftsChangeRequests, nargs='+', help='') c.argument('time_cards', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('time_off_reasons', action=AddTimeOffReasons, nargs='+', help='The set of reasons for a time off in ' 'the schedule.') c.argument('time_off_requests', action=AddTimeOffRequests, nargs='+', help='') c.argument('times_off', type=validate_file_or_dict, help='The instances of times off in the schedule. Expected ' 'value: json-string/@json-file.') c.argument('approved_location', action=AddApprovedLocation, nargs='+', help='geoCoordinates', arg_group='Time ' 'Clock Settings') with self.argument_context('teams team-channel all-message') as c: c.argument('team_id', type=str, help='key: id of team') with self.argument_context('teams team-channel complete-migration') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') with self.argument_context('teams team-channel create-member') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('display_name', type=str, help='The display name of the user.') c.argument('roles', nargs='+', help='The roles for that user.') with self.argument_context('teams team-channel create-message') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('attachments', action=AddAttachments, nargs='+', help='Attached files. Attachments are currently ' 'read-only – sending attachments is not supported.') c.argument('body', action=AddBody, nargs='+', help='itemBody') c.argument('channel_identity', action=AddChannelIdentity, nargs='+', help='channelIdentity') c.argument('chat_id', type=str, help='') c.argument('created_date_time', help='Read only. Timestamp of when the chat message was created.') c.argument('deleted_date_time', help='Read only. Timestamp at which the chat message was deleted, or null if ' 'not deleted.') c.argument('etag', type=str, help='Read-only. Version number of the chat message.') c.argument('importance', arg_type=get_enum_type(['normal', 'high', 'urgent']), help='') c.argument('last_edited_date_time', help='Read only. Timestamp when edits to the chat message were made. ' 'Triggers an \'Edited\' flag in the Microsoft Teams UI. If no edits are made the value is null.') c.argument('last_modified_date_time', help='Read only. Timestamp when the chat message is created (initial ' 'setting) or edited, including when a reaction is added or removed.') c.argument('locale', type=str, help='Locale of the chat message set by the client.') c.argument('mentions', type=validate_file_or_dict, help='List of entities mentioned in the chat message. ' 'Currently supports user, bot, team, channel. Expected value: json-string/@json-file.') c.argument('message_type', arg_type=get_enum_type(['message', 'chatEvent', 'typing']), help='') c.argument('reactions', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('reply_to_id', type=str, help='Read-only. Id of the parent chat message or root chat message of the ' 'thread. (Only applies to chat messages in channels not chats)') c.argument('subject', type=str, help='The subject of the chat message, in plaintext.') c.argument('summary', type=str, help='Summary text of the chat message that could be used for push ' 'notifications and summary views or fall back views. Only applies to channel chat messages, not ' 'chat messages in a chat.') c.argument('web_url', type=str, help='') c.argument('hosted_contents', action=AddHostedContents, nargs='+', help='') c.argument('replies', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('dlp_action', arg_type=get_enum_type(['none', 'notifySender', 'blockAccess', 'blockAccessExternal']), help='', arg_group='Policy Violation') c.argument('justification_text', type=str, help='Justification text provided by the sender of the message when ' 'overriding a policy violation.', arg_group='Policy Violation') c.argument('policy_tip', action=AddPolicyTip, nargs='+', help='chatMessagePolicyViolationPolicyTip', arg_group='Policy Violation') c.argument('user_action', arg_type=get_enum_type(['none', 'override', 'reportFalsePositive']), help='', arg_group='Policy Violation') c.argument('verdict_details', arg_type=get_enum_type(['none', 'allowFalsePositiveOverride', 'allowOverrideWithoutJustification', 'allowOverrideWithJustification']), help='', arg_group='Policy Violation') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='From') with self.argument_context('teams team-channel create-tab') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('configuration', action=AddConfiguration, nargs='+', help='teamsTabConfiguration') c.argument('display_name', type=str, help='Name of the tab.') c.argument('message_id', type=str, help='') c.argument('sort_order_index', type=str, help='') c.argument('teams_app_id', type=str, help='') c.argument('web_url', type=str, help='Deep link URL of the tab instance. Read only.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Teams App') c.argument('microsoft_graph_teams_app_display_name', type=str, help='The name of the catalog app provided by ' 'the app developer in the Microsoft Teams zip app package.', arg_group='Teams App') c.argument('distribution_method', arg_type=get_enum_type(['store', 'organization', 'sideloaded', 'unknownFutureValue']), help='', arg_group='Teams ' 'App') c.argument('external_id', type=str, help='The ID of the catalog provided by the app developer in the Microsoft ' 'Teams zip app package.', arg_group='Teams App') c.argument('app_definitions', type=validate_file_or_dict, help='The details for each version of the app. ' 'Expected value: json-string/@json-file.', arg_group='Teams App') with self.argument_context('teams team-channel delete-file-folder') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-channel delete-member') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('conversation_member_id', type=str, help='key: id of conversationMember') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-channel delete-message') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-channel delete-tab') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-channel list-member') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-channel list-message') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-channel list-tab') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-channel set-file-folder-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('data', help='New media content.') with self.argument_context('teams team-channel show-file-folder') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-channel show-file-folder-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') with self.argument_context('teams team-channel show-member') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('conversation_member_id', type=str, help='key: id of conversationMember') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-channel show-message') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-channel show-tab') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-channel update-file-folder') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='Date and time of item creation. Read-only.') c.argument('description', type=str, help='Provides a user-visible description of the item. Optional.') c.argument('e_tag', type=str, help='ETag for the item. Read-only.') c.argument('last_modified_date_time', help='Date and time the item was last modified. Read-only.') c.argument('name', type=str, help='The name of the item. Read-write.') c.argument('web_url', type=str, help='URL that displays the resource in the browser. Read-only.') c.argument('created_by_user', type=validate_file_or_dict, help='Represents an Azure Active Directory user ' 'object. Expected value: json-string/@json-file.') c.argument('last_modified_by_user', type=validate_file_or_dict, help='Represents an Azure Active Directory ' 'user object. Expected value: json-string/@json-file.') c.argument('drive_id', type=str, help='Unique identifier of the drive instance that contains the item. ' 'Read-only.', arg_group='Parent Reference') c.argument('drive_type', type=str, help='Identifies the type of drive. See [drive][] resource for values.', arg_group='Parent Reference') c.argument('microsoft_graph_item_reference_id', type=str, help='Unique identifier of the item in the drive. ' 'Read-only.', arg_group='Parent Reference') c.argument('microsoft_graph_item_reference_name', type=str, help='The name of the item being referenced. ' 'Read-only.', arg_group='Parent Reference') c.argument('path', type=str, help='Path that can be used to navigate to the item. Read-only.', arg_group='Parent Reference') c.argument('share_id', type=str, help='A unique identifier for a shared resource that can be accessed via the ' '[Shares][] API.', arg_group='Parent Reference') c.argument('sharepoint_ids', action=AddSharepointIds, nargs='+', help='sharepointIds', arg_group='Parent ' 'Reference') c.argument('site_id', type=str, help='', arg_group='Parent Reference') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('audio', action=AddAudio, nargs='+', help='audio') c.argument('content', help='The content stream, if the item represents a file.') c.argument('c_tag', type=str, help='An eTag for the content of the item. This eTag is not changed if only the ' 'metadata is changed. Note This property is not returned if the item is a folder. Read-only.') c.argument('file_system_info', action=AddFileSystemInfo, nargs='+', help='fileSystemInfo') c.argument('image', action=AddImage, nargs='+', help='image') c.argument('location', arg_type=get_location_type(self.cli_ctx)) c.argument('photo', action=AddTeamsChannelsPhoto, nargs='+', help='photo') c.argument('publication', action=AddPublication, nargs='+', help='publicationFacet') c.argument('root', type=validate_file_or_dict, help='root Expected value: json-string/@json-file.') c.argument('microsoft_graph_sharepoint_ids', action=AddSharepointIds, nargs='+', help='sharepointIds') c.argument('size', type=int, help='Size of the item in bytes. Read-only.') c.argument('video', action=AddVideo, nargs='+', help='video') c.argument('web_dav_url', type=str, help='WebDAV compatible URL for the item.') c.argument('activities', type=validate_file_or_dict, help='The list of recent activities that took place on ' 'this item. Expected value: json-string/@json-file.') c.argument('children', type=validate_file_or_dict, help='Collection containing Item objects for the immediate ' 'children of Item. Only items representing folders have children. Read-only. Nullable. Expected ' 'value: json-string/@json-file.') c.argument('list_item', type=validate_file_or_dict, help='listItem Expected value: json-string/@json-file.') c.argument('permissions', type=validate_file_or_dict, help='The set of permissions for the item. Read-only. ' 'Nullable. Expected value: json-string/@json-file.') c.argument('subscriptions', action=AddSubscriptions, nargs='+', help='The set of subscriptions on the item. ' 'Only supported on the root of a drive.') c.argument('thumbnails', type=validate_file_or_dict, help='Collection containing [ThumbnailSet][] objects ' 'associated with the item. For more info, see [getting thumbnails][]. Read-only. Nullable. Expected ' 'value: json-string/@json-file.') c.argument('versions', action=AddVersions, nargs='+', help='The list of previous versions of the item. For ' 'more info, see [getting previous versions][]. Read-only. Nullable.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Analytics') c.argument('all_time', type=validate_file_or_dict, help='itemActivityStat Expected value: ' 'json-string/@json-file.', arg_group='Analytics') c.argument('item_activity_stats', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Analytics') c.argument('last_seven_days', type=validate_file_or_dict, help='itemActivityStat Expected value: ' 'json-string/@json-file.', arg_group='Analytics') c.argument('id1', type=str, help='Read-only.', arg_group='Workbook') c.argument('microsoft_graph_workbook_application', action=AddMicrosoftGraphWorkbookApplication, nargs='+', help='workbookApplication', arg_group='Workbook') c.argument('comments', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Workbook') c.argument('functions', action=AddFunctions, nargs='+', help='workbookFunctions', arg_group='Workbook') c.argument('names', type=validate_file_or_dict, help='Represents a collection of workbook scoped named items ' '(named ranges and constants). Read-only. Expected value: json-string/@json-file.', arg_group='Workbook') c.argument('operations', type=validate_file_or_dict, help='The status of workbook operations. Getting an ' 'operation collection is not supported, but you can get the status of a long-running operation if ' 'the Location header is returned in the response. Read-only. Expected value: ' 'json-string/@json-file.', arg_group='Workbook') c.argument('tables', type=validate_file_or_dict, help='Represents a collection of tables associated with the ' 'workbook. Read-only. Expected value: json-string/@json-file.', arg_group='Workbook') c.argument('worksheets', type=validate_file_or_dict, help='Represents a collection of worksheets associated ' 'with the workbook. Read-only. Expected value: json-string/@json-file.', arg_group='Workbook') c.argument('microsoft_graph_special_folder_name', type=str, help='The unique identifier for this item in the ' '/drive/special collection', arg_group='Special Folder') c.argument('owner', type=validate_file_or_dict, help='identitySet Expected value: json-string/@json-file.', arg_group='Shared') c.argument('scope', type=str, help='Indicates the scope of how the item is shared: anonymous, organization, or ' 'users. Read-only.', arg_group='Shared') c.argument('shared_by', type=validate_file_or_dict, help='identitySet Expected value: json-string/@json-file.', arg_group='Shared') c.argument('shared_date_time', help='The UTC date and time when the item was shared. Read-only.', arg_group='Shared') c.argument('on_click_telemetry_url', type=str, help='A callback URL that can be used to record telemetry ' 'information. The application should issue a GET on this URL if the user interacts with this item ' 'to improve the quality of results.', arg_group='Search Result') c.argument('created_by', type=validate_file_or_dict, help='identitySet Expected value: json-string/@json-file.', arg_group='Remote Item') c.argument('microsoft_graph_remote_item_created_date_time_created_date_time', help='Date and time of item ' 'creation. Read-only.', arg_group='Remote Item') c.argument('file', type=validate_file_or_dict, help='file Expected value: json-string/@json-file.', arg_group='Remote Item') c.argument('microsoft_graph_file_system_info_file_system_info', action=AddFileSystemInfo, nargs='+', help='fileSystemInfo', arg_group='Remote Item') c.argument('folder', type=validate_file_or_dict, help='folder Expected value: json-string/@json-file.', arg_group='Remote Item') c.argument('microsoft_graph_remote_item_id', type=str, help='Unique identifier for the remote item in its ' 'drive. Read-only.', arg_group='Remote Item') c.argument('microsoft_graph_image', action=AddImage, nargs='+', help='image', arg_group='Remote Item') c.argument('last_modified_by', type=validate_file_or_dict, help='identitySet Expected value: ' 'json-string/@json-file.', arg_group='Remote Item') c.argument('microsoft_graph_remote_item_last_modified_date_time_last_modified_date_time', help='Date and time ' 'the item was last modified. Read-only.', arg_group='Remote Item') c.argument('microsoft_graph_remote_item_name', type=str, help='Optional. Filename of the remote item. ' 'Read-only.', arg_group='Remote Item') c.argument('package', action=AddPackage, nargs='+', help='package', arg_group='Remote Item') c.argument('parent_reference', type=validate_file_or_dict, help='itemReference Expected value: ' 'json-string/@json-file.', arg_group='Remote Item') c.argument('shared', type=validate_file_or_dict, help='shared Expected value: json-string/@json-file.', arg_group='Remote Item') c.argument('sharepoint_ids1', action=AddSharepointIds, nargs='+', help='sharepointIds', arg_group='Remote Item') c.argument('integer_size', type=int, help='Size of the remote item. Read-only.', arg_group='Remote Item') c.argument('special_folder', action=AddSpecialFolder, nargs='+', help='specialFolder', arg_group='Remote Item') c.argument('microsoft_graph_video', action=AddVideo, nargs='+', help='video', arg_group='Remote Item') c.argument('microsoft_graph_remote_item_web_dav_url_web_dav_url', type=str, help='DAV compatible URL for the ' 'item.', arg_group='Remote Item') c.argument('microsoft_graph_remote_item_web_url', type=str, help='URL that displays the resource in the ' 'browser. Read-only.', arg_group='Remote Item') c.argument('queued_date_time', help='Date and time the pending binary operation was queued in UTC time. ' 'Read-only.', arg_group='Pending Operations Pending Content Update') c.argument('type_', options_list=['--type'], type=str, help='A string indicating the type of package. While ' 'oneNote is the only currently defined value, you should expect other package types to be returned ' 'and handle them accordingly.', arg_group='Package') c.argument('child_count', type=int, help='Number of children contained immediately within this container.', arg_group='Folder') c.argument('view', action=AddView, nargs='+', help='folderView', arg_group='Folder') c.argument('hashes', action=AddHashes, nargs='+', help='hashes', arg_group='File') c.argument('mime_type', type=str, help='The MIME type for the file. This is determined by logic on the server ' 'and might not be the value provided when the file was uploaded. Read-only.', arg_group='File') c.argument('processing_metadata', arg_type=get_three_state_flag(), help='', arg_group='File') c.argument('state', type=str, help='Represents the state of the deleted item.', arg_group='Deleted') c.argument('album', action=AddAlbum, nargs='+', help='album', arg_group='Bundle') c.argument('integer_child_count', type=int, help='', arg_group='Bundle') with self.argument_context('teams team-channel update-member') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('conversation_member_id', type=str, help='key: id of conversationMember') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('display_name', type=str, help='The display name of the user.') c.argument('roles', nargs='+', help='The roles for that user.') with self.argument_context('teams team-channel update-message') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('attachments', action=AddAttachments, nargs='+', help='Attached files. Attachments are currently ' 'read-only – sending attachments is not supported.') c.argument('body', action=AddBody, nargs='+', help='itemBody') c.argument('channel_identity', action=AddChannelIdentity, nargs='+', help='channelIdentity') c.argument('chat_id', type=str, help='') c.argument('created_date_time', help='Read only. Timestamp of when the chat message was created.') c.argument('deleted_date_time', help='Read only. Timestamp at which the chat message was deleted, or null if ' 'not deleted.') c.argument('etag', type=str, help='Read-only. Version number of the chat message.') c.argument('importance', arg_type=get_enum_type(['normal', 'high', 'urgent']), help='') c.argument('last_edited_date_time', help='Read only. Timestamp when edits to the chat message were made. ' 'Triggers an \'Edited\' flag in the Microsoft Teams UI. If no edits are made the value is null.') c.argument('last_modified_date_time', help='Read only. Timestamp when the chat message is created (initial ' 'setting) or edited, including when a reaction is added or removed.') c.argument('locale', type=str, help='Locale of the chat message set by the client.') c.argument('mentions', type=validate_file_or_dict, help='List of entities mentioned in the chat message. ' 'Currently supports user, bot, team, channel. Expected value: json-string/@json-file.') c.argument('message_type', arg_type=get_enum_type(['message', 'chatEvent', 'typing']), help='') c.argument('reactions', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('reply_to_id', type=str, help='Read-only. Id of the parent chat message or root chat message of the ' 'thread. (Only applies to chat messages in channels not chats)') c.argument('subject', type=str, help='The subject of the chat message, in plaintext.') c.argument('summary', type=str, help='Summary text of the chat message that could be used for push ' 'notifications and summary views or fall back views. Only applies to channel chat messages, not ' 'chat messages in a chat.') c.argument('web_url', type=str, help='') c.argument('hosted_contents', action=AddHostedContents, nargs='+', help='') c.argument('replies', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('dlp_action', arg_type=get_enum_type(['none', 'notifySender', 'blockAccess', 'blockAccessExternal']), help='', arg_group='Policy Violation') c.argument('justification_text', type=str, help='Justification text provided by the sender of the message when ' 'overriding a policy violation.', arg_group='Policy Violation') c.argument('policy_tip', action=AddPolicyTip, nargs='+', help='chatMessagePolicyViolationPolicyTip', arg_group='Policy Violation') c.argument('user_action', arg_type=get_enum_type(['none', 'override', 'reportFalsePositive']), help='', arg_group='Policy Violation') c.argument('verdict_details', arg_type=get_enum_type(['none', 'allowFalsePositiveOverride', 'allowOverrideWithoutJustification', 'allowOverrideWithJustification']), help='', arg_group='Policy Violation') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='From') with self.argument_context('teams team-channel update-tab') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('configuration', action=AddConfiguration, nargs='+', help='teamsTabConfiguration') c.argument('display_name', type=str, help='Name of the tab.') c.argument('message_id', type=str, help='') c.argument('sort_order_index', type=str, help='') c.argument('teams_app_id', type=str, help='') c.argument('web_url', type=str, help='Deep link URL of the tab instance. Read only.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Teams App') c.argument('microsoft_graph_teams_app_display_name', type=str, help='The name of the catalog app provided by ' 'the app developer in the Microsoft Teams zip app package.', arg_group='Teams App') c.argument('distribution_method', arg_type=get_enum_type(['store', 'organization', 'sideloaded', 'unknownFutureValue']), help='', arg_group='Teams ' 'App') c.argument('external_id', type=str, help='The ID of the catalog provided by the app developer in the Microsoft ' 'Teams zip app package.', arg_group='Teams App') c.argument('app_definitions', type=validate_file_or_dict, help='The details for each version of the app. ' 'Expected value: json-string/@json-file.', arg_group='Teams App') with self.argument_context('teams team-channel-member add') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('values', action=AddTeamsChannelsMembersValues, nargs='+', help='') with self.argument_context('teams team-channel-message create-hosted-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('content_bytes', help='') c.argument('content_type', type=str, help='') with self.argument_context('teams team-channel-message create-reply') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('attachments', action=AddAttachments, nargs='+', help='Attached files. Attachments are currently ' 'read-only – sending attachments is not supported.') c.argument('body', action=AddBody, nargs='+', help='itemBody') c.argument('channel_identity', action=AddChannelIdentity, nargs='+', help='channelIdentity') c.argument('chat_id', type=str, help='') c.argument('created_date_time', help='Read only. Timestamp of when the chat message was created.') c.argument('deleted_date_time', help='Read only. Timestamp at which the chat message was deleted, or null if ' 'not deleted.') c.argument('etag', type=str, help='Read-only. Version number of the chat message.') c.argument('importance', arg_type=get_enum_type(['normal', 'high', 'urgent']), help='') c.argument('last_edited_date_time', help='Read only. Timestamp when edits to the chat message were made. ' 'Triggers an \'Edited\' flag in the Microsoft Teams UI. If no edits are made the value is null.') c.argument('last_modified_date_time', help='Read only. Timestamp when the chat message is created (initial ' 'setting) or edited, including when a reaction is added or removed.') c.argument('locale', type=str, help='Locale of the chat message set by the client.') c.argument('mentions', type=validate_file_or_dict, help='List of entities mentioned in the chat message. ' 'Currently supports user, bot, team, channel. Expected value: json-string/@json-file.') c.argument('message_type', arg_type=get_enum_type(['message', 'chatEvent', 'typing']), help='') c.argument('reactions', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('reply_to_id', type=str, help='Read-only. Id of the parent chat message or root chat message of the ' 'thread. (Only applies to chat messages in channels not chats)') c.argument('subject', type=str, help='The subject of the chat message, in plaintext.') c.argument('summary', type=str, help='Summary text of the chat message that could be used for push ' 'notifications and summary views or fall back views. Only applies to channel chat messages, not ' 'chat messages in a chat.') c.argument('web_url', type=str, help='') c.argument('hosted_contents', action=AddHostedContents, nargs='+', help='') c.argument('replies', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('dlp_action', arg_type=get_enum_type(['none', 'notifySender', 'blockAccess', 'blockAccessExternal']), help='', arg_group='Policy Violation') c.argument('justification_text', type=str, help='Justification text provided by the sender of the message when ' 'overriding a policy violation.', arg_group='Policy Violation') c.argument('policy_tip', action=AddPolicyTip, nargs='+', help='chatMessagePolicyViolationPolicyTip', arg_group='Policy Violation') c.argument('user_action', arg_type=get_enum_type(['none', 'override', 'reportFalsePositive']), help='', arg_group='Policy Violation') c.argument('verdict_details', arg_type=get_enum_type(['none', 'allowFalsePositiveOverride', 'allowOverrideWithoutJustification', 'allowOverrideWithJustification']), help='', arg_group='Policy Violation') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='From') with self.argument_context('teams team-channel-message delete-hosted-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_hosted_content_id', type=str, help='key: id of chatMessageHostedContent') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-channel-message delete-reply') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_id1', type=str, help='key: id of chatMessage') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-channel-message delta') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') with self.argument_context('teams team-channel-message list-hosted-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-channel-message list-reply') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-channel-message set-hosted-content-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_hosted_content_id', type=str, help='key: id of chatMessageHostedContent') c.argument('data', help='New media content.') with self.argument_context('teams team-channel-message show-hosted-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_hosted_content_id', type=str, help='key: id of chatMessageHostedContent') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-channel-message show-hosted-content-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_hosted_content_id', type=str, help='key: id of chatMessageHostedContent') with self.argument_context('teams team-channel-message show-reply') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_id1', type=str, help='key: id of chatMessage') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-channel-message update-hosted-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_hosted_content_id', type=str, help='key: id of chatMessageHostedContent') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('content_bytes', help='') c.argument('content_type', type=str, help='') with self.argument_context('teams team-channel-message update-reply') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_id1', type=str, help='key: id of chatMessage') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('attachments', action=AddAttachments, nargs='+', help='Attached files. Attachments are currently ' 'read-only – sending attachments is not supported.') c.argument('body', action=AddBody, nargs='+', help='itemBody') c.argument('channel_identity', action=AddChannelIdentity, nargs='+', help='channelIdentity') c.argument('chat_id', type=str, help='') c.argument('created_date_time', help='Read only. Timestamp of when the chat message was created.') c.argument('deleted_date_time', help='Read only. Timestamp at which the chat message was deleted, or null if ' 'not deleted.') c.argument('etag', type=str, help='Read-only. Version number of the chat message.') c.argument('importance', arg_type=get_enum_type(['normal', 'high', 'urgent']), help='') c.argument('last_edited_date_time', help='Read only. Timestamp when edits to the chat message were made. ' 'Triggers an \'Edited\' flag in the Microsoft Teams UI. If no edits are made the value is null.') c.argument('last_modified_date_time', help='Read only. Timestamp when the chat message is created (initial ' 'setting) or edited, including when a reaction is added or removed.') c.argument('locale', type=str, help='Locale of the chat message set by the client.') c.argument('mentions', type=validate_file_or_dict, help='List of entities mentioned in the chat message. ' 'Currently supports user, bot, team, channel. Expected value: json-string/@json-file.') c.argument('message_type', arg_type=get_enum_type(['message', 'chatEvent', 'typing']), help='') c.argument('reactions', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('reply_to_id', type=str, help='Read-only. Id of the parent chat message or root chat message of the ' 'thread. (Only applies to chat messages in channels not chats)') c.argument('subject', type=str, help='The subject of the chat message, in plaintext.') c.argument('summary', type=str, help='Summary text of the chat message that could be used for push ' 'notifications and summary views or fall back views. Only applies to channel chat messages, not ' 'chat messages in a chat.') c.argument('web_url', type=str, help='') c.argument('hosted_contents', action=AddHostedContents, nargs='+', help='') c.argument('replies', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('dlp_action', arg_type=get_enum_type(['none', 'notifySender', 'blockAccess', 'blockAccessExternal']), help='', arg_group='Policy Violation') c.argument('justification_text', type=str, help='Justification text provided by the sender of the message when ' 'overriding a policy violation.', arg_group='Policy Violation') c.argument('policy_tip', action=AddPolicyTip, nargs='+', help='chatMessagePolicyViolationPolicyTip', arg_group='Policy Violation') c.argument('user_action', arg_type=get_enum_type(['none', 'override', 'reportFalsePositive']), help='', arg_group='Policy Violation') c.argument('verdict_details', arg_type=get_enum_type(['none', 'allowFalsePositiveOverride', 'allowOverrideWithoutJustification', 'allowOverrideWithJustification']), help='', arg_group='Policy Violation') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='From') with self.argument_context('teams team-channel-message-reply delta') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('chat_message_id', type=str, help='key: id of chatMessage') with self.argument_context('teams team-channel-tab delete-ref-team-app') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-channel-tab set-ref-team-app') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('body', type=validate_file_or_dict, help='New navigation property ref values Expected value: ' 'json-string/@json-file.') with self.argument_context('teams team-channel-tab show-ref-team-app') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') with self.argument_context('teams team-channel-tab show-team-app') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('channel_id', type=str, help='key: id of channel') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-installed-app delete-ref-team-app') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-installed-app delete-ref-team-app-definition') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-installed-app set-ref-team-app') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('body', type=validate_file_or_dict, help='New navigation property ref values Expected value: ' 'json-string/@json-file.') with self.argument_context('teams team-installed-app set-ref-team-app-definition') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('body', type=validate_file_or_dict, help='New navigation property ref values Expected value: ' 'json-string/@json-file.') with self.argument_context('teams team-installed-app show-ref-team-app') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') with self.argument_context('teams team-installed-app show-ref-team-app-definition') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') with self.argument_context('teams team-installed-app show-team-app') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-installed-app show-team-app-definition') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-installed-app upgrade') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_app_installation_id', type=str, help='key: id of teamsAppInstallation') with self.argument_context('teams team-member add') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('values', action=AddTeamsMembersValues, nargs='+', help='') with self.argument_context('teams team-primary-channel complete-migration') as c: c.argument('team_id', type=str, help='key: id of team') with self.argument_context('teams team-primary-channel create-member') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('display_name', type=str, help='The display name of the user.') c.argument('roles', nargs='+', help='The roles for that user.') with self.argument_context('teams team-primary-channel create-message') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('attachments', action=AddAttachments, nargs='+', help='Attached files. Attachments are currently ' 'read-only – sending attachments is not supported.') c.argument('body', action=AddBody, nargs='+', help='itemBody') c.argument('channel_identity', action=AddChannelIdentity, nargs='+', help='channelIdentity') c.argument('chat_id', type=str, help='') c.argument('created_date_time', help='Read only. Timestamp of when the chat message was created.') c.argument('deleted_date_time', help='Read only. Timestamp at which the chat message was deleted, or null if ' 'not deleted.') c.argument('etag', type=str, help='Read-only. Version number of the chat message.') c.argument('importance', arg_type=get_enum_type(['normal', 'high', 'urgent']), help='') c.argument('last_edited_date_time', help='Read only. Timestamp when edits to the chat message were made. ' 'Triggers an \'Edited\' flag in the Microsoft Teams UI. If no edits are made the value is null.') c.argument('last_modified_date_time', help='Read only. Timestamp when the chat message is created (initial ' 'setting) or edited, including when a reaction is added or removed.') c.argument('locale', type=str, help='Locale of the chat message set by the client.') c.argument('mentions', type=validate_file_or_dict, help='List of entities mentioned in the chat message. ' 'Currently supports user, bot, team, channel. Expected value: json-string/@json-file.') c.argument('message_type', arg_type=get_enum_type(['message', 'chatEvent', 'typing']), help='') c.argument('reactions', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('reply_to_id', type=str, help='Read-only. Id of the parent chat message or root chat message of the ' 'thread. (Only applies to chat messages in channels not chats)') c.argument('subject', type=str, help='The subject of the chat message, in plaintext.') c.argument('summary', type=str, help='Summary text of the chat message that could be used for push ' 'notifications and summary views or fall back views. Only applies to channel chat messages, not ' 'chat messages in a chat.') c.argument('web_url', type=str, help='') c.argument('hosted_contents', action=AddHostedContents, nargs='+', help='') c.argument('replies', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('dlp_action', arg_type=get_enum_type(['none', 'notifySender', 'blockAccess', 'blockAccessExternal']), help='', arg_group='Policy Violation') c.argument('justification_text', type=str, help='Justification text provided by the sender of the message when ' 'overriding a policy violation.', arg_group='Policy Violation') c.argument('policy_tip', action=AddPolicyTip, nargs='+', help='chatMessagePolicyViolationPolicyTip', arg_group='Policy Violation') c.argument('user_action', arg_type=get_enum_type(['none', 'override', 'reportFalsePositive']), help='', arg_group='Policy Violation') c.argument('verdict_details', arg_type=get_enum_type(['none', 'allowFalsePositiveOverride', 'allowOverrideWithoutJustification', 'allowOverrideWithJustification']), help='', arg_group='Policy Violation') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='From') with self.argument_context('teams team-primary-channel create-tab') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('configuration', action=AddConfiguration, nargs='+', help='teamsTabConfiguration') c.argument('display_name', type=str, help='Name of the tab.') c.argument('message_id', type=str, help='') c.argument('sort_order_index', type=str, help='') c.argument('teams_app_id', type=str, help='') c.argument('web_url', type=str, help='Deep link URL of the tab instance. Read only.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Teams App') c.argument('microsoft_graph_teams_app_display_name', type=str, help='The name of the catalog app provided by ' 'the app developer in the Microsoft Teams zip app package.', arg_group='Teams App') c.argument('distribution_method', arg_type=get_enum_type(['store', 'organization', 'sideloaded', 'unknownFutureValue']), help='', arg_group='Teams ' 'App') c.argument('external_id', type=str, help='The ID of the catalog provided by the app developer in the Microsoft ' 'Teams zip app package.', arg_group='Teams App') c.argument('app_definitions', type=validate_file_or_dict, help='The details for each version of the app. ' 'Expected value: json-string/@json-file.', arg_group='Teams App') with self.argument_context('teams team-primary-channel delete-file-folder') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-primary-channel delete-member') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('conversation_member_id', type=str, help='key: id of conversationMember') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-primary-channel delete-message') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-primary-channel delete-tab') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-primary-channel list-member') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-primary-channel list-message') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-primary-channel list-tab') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-primary-channel set-file-folder-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('data', help='New media content.') with self.argument_context('teams team-primary-channel show-file-folder') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-primary-channel show-file-folder-content') as c: c.argument('team_id', type=str, help='key: id of team') with self.argument_context('teams team-primary-channel show-member') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('conversation_member_id', type=str, help='key: id of conversationMember') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-primary-channel show-message') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-primary-channel show-tab') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-primary-channel update-file-folder') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='Date and time of item creation. Read-only.') c.argument('description', type=str, help='Provides a user-visible description of the item. Optional.') c.argument('e_tag', type=str, help='ETag for the item. Read-only.') c.argument('last_modified_date_time', help='Date and time the item was last modified. Read-only.') c.argument('name', type=str, help='The name of the item. Read-write.') c.argument('web_url', type=str, help='URL that displays the resource in the browser. Read-only.') c.argument('created_by_user', type=validate_file_or_dict, help='Represents an Azure Active Directory user ' 'object. Expected value: json-string/@json-file.') c.argument('last_modified_by_user', type=validate_file_or_dict, help='Represents an Azure Active Directory ' 'user object. Expected value: json-string/@json-file.') c.argument('drive_id', type=str, help='Unique identifier of the drive instance that contains the item. ' 'Read-only.', arg_group='Parent Reference') c.argument('drive_type', type=str, help='Identifies the type of drive. See [drive][] resource for values.', arg_group='Parent Reference') c.argument('microsoft_graph_item_reference_id', type=str, help='Unique identifier of the item in the drive. ' 'Read-only.', arg_group='Parent Reference') c.argument('microsoft_graph_item_reference_name', type=str, help='The name of the item being referenced. ' 'Read-only.', arg_group='Parent Reference') c.argument('path', type=str, help='Path that can be used to navigate to the item. Read-only.', arg_group='Parent Reference') c.argument('share_id', type=str, help='A unique identifier for a shared resource that can be accessed via the ' '[Shares][] API.', arg_group='Parent Reference') c.argument('sharepoint_ids', action=AddSharepointIds, nargs='+', help='sharepointIds', arg_group='Parent ' 'Reference') c.argument('site_id', type=str, help='', arg_group='Parent Reference') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('audio', action=AddAudio, nargs='+', help='audio') c.argument('content', help='The content stream, if the item represents a file.') c.argument('c_tag', type=str, help='An eTag for the content of the item. This eTag is not changed if only the ' 'metadata is changed. Note This property is not returned if the item is a folder. Read-only.') c.argument('file_system_info', action=AddFileSystemInfo, nargs='+', help='fileSystemInfo') c.argument('image', action=AddImage, nargs='+', help='image') c.argument('location', arg_type=get_location_type(self.cli_ctx)) c.argument('photo', action=AddTeamsChannelsPhoto, nargs='+', help='photo') c.argument('publication', action=AddPublication, nargs='+', help='publicationFacet') c.argument('root', type=validate_file_or_dict, help='root Expected value: json-string/@json-file.') c.argument('microsoft_graph_sharepoint_ids', action=AddSharepointIds, nargs='+', help='sharepointIds') c.argument('size', type=int, help='Size of the item in bytes. Read-only.') c.argument('video', action=AddVideo, nargs='+', help='video') c.argument('web_dav_url', type=str, help='WebDAV compatible URL for the item.') c.argument('activities', type=validate_file_or_dict, help='The list of recent activities that took place on ' 'this item. Expected value: json-string/@json-file.') c.argument('children', type=validate_file_or_dict, help='Collection containing Item objects for the immediate ' 'children of Item. Only items representing folders have children. Read-only. Nullable. Expected ' 'value: json-string/@json-file.') c.argument('list_item', type=validate_file_or_dict, help='listItem Expected value: json-string/@json-file.') c.argument('permissions', type=validate_file_or_dict, help='The set of permissions for the item. Read-only. ' 'Nullable. Expected value: json-string/@json-file.') c.argument('subscriptions', action=AddSubscriptions, nargs='+', help='The set of subscriptions on the item. ' 'Only supported on the root of a drive.') c.argument('thumbnails', type=validate_file_or_dict, help='Collection containing [ThumbnailSet][] objects ' 'associated with the item. For more info, see [getting thumbnails][]. Read-only. Nullable. Expected ' 'value: json-string/@json-file.') c.argument('versions', action=AddVersions, nargs='+', help='The list of previous versions of the item. For ' 'more info, see [getting previous versions][]. Read-only. Nullable.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Analytics') c.argument('all_time', type=validate_file_or_dict, help='itemActivityStat Expected value: ' 'json-string/@json-file.', arg_group='Analytics') c.argument('item_activity_stats', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Analytics') c.argument('last_seven_days', type=validate_file_or_dict, help='itemActivityStat Expected value: ' 'json-string/@json-file.', arg_group='Analytics') c.argument('id1', type=str, help='Read-only.', arg_group='Workbook') c.argument('microsoft_graph_workbook_application', action=AddMicrosoftGraphWorkbookApplication, nargs='+', help='workbookApplication', arg_group='Workbook') c.argument('comments', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Workbook') c.argument('functions', action=AddFunctions, nargs='+', help='workbookFunctions', arg_group='Workbook') c.argument('names', type=validate_file_or_dict, help='Represents a collection of workbook scoped named items ' '(named ranges and constants). Read-only. Expected value: json-string/@json-file.', arg_group='Workbook') c.argument('operations', type=validate_file_or_dict, help='The status of workbook operations. Getting an ' 'operation collection is not supported, but you can get the status of a long-running operation if ' 'the Location header is returned in the response. Read-only. Expected value: ' 'json-string/@json-file.', arg_group='Workbook') c.argument('tables', type=validate_file_or_dict, help='Represents a collection of tables associated with the ' 'workbook. Read-only. Expected value: json-string/@json-file.', arg_group='Workbook') c.argument('worksheets', type=validate_file_or_dict, help='Represents a collection of worksheets associated ' 'with the workbook. Read-only. Expected value: json-string/@json-file.', arg_group='Workbook') c.argument('microsoft_graph_special_folder_name', type=str, help='The unique identifier for this item in the ' '/drive/special collection', arg_group='Special Folder') c.argument('owner', type=validate_file_or_dict, help='identitySet Expected value: json-string/@json-file.', arg_group='Shared') c.argument('scope', type=str, help='Indicates the scope of how the item is shared: anonymous, organization, or ' 'users. Read-only.', arg_group='Shared') c.argument('shared_by', type=validate_file_or_dict, help='identitySet Expected value: json-string/@json-file.', arg_group='Shared') c.argument('shared_date_time', help='The UTC date and time when the item was shared. Read-only.', arg_group='Shared') c.argument('on_click_telemetry_url', type=str, help='A callback URL that can be used to record telemetry ' 'information. The application should issue a GET on this URL if the user interacts with this item ' 'to improve the quality of results.', arg_group='Search Result') c.argument('created_by', type=validate_file_or_dict, help='identitySet Expected value: json-string/@json-file.', arg_group='Remote Item') c.argument('microsoft_graph_remote_item_created_date_time_created_date_time', help='Date and time of item ' 'creation. Read-only.', arg_group='Remote Item') c.argument('file', type=validate_file_or_dict, help='file Expected value: json-string/@json-file.', arg_group='Remote Item') c.argument('microsoft_graph_file_system_info_file_system_info', action=AddFileSystemInfo, nargs='+', help='fileSystemInfo', arg_group='Remote Item') c.argument('folder', type=validate_file_or_dict, help='folder Expected value: json-string/@json-file.', arg_group='Remote Item') c.argument('microsoft_graph_remote_item_id', type=str, help='Unique identifier for the remote item in its ' 'drive. Read-only.', arg_group='Remote Item') c.argument('microsoft_graph_image', action=AddImage, nargs='+', help='image', arg_group='Remote Item') c.argument('last_modified_by', type=validate_file_or_dict, help='identitySet Expected value: ' 'json-string/@json-file.', arg_group='Remote Item') c.argument('microsoft_graph_remote_item_last_modified_date_time_last_modified_date_time', help='Date and time ' 'the item was last modified. Read-only.', arg_group='Remote Item') c.argument('microsoft_graph_remote_item_name', type=str, help='Optional. Filename of the remote item. ' 'Read-only.', arg_group='Remote Item') c.argument('package', action=AddPackage, nargs='+', help='package', arg_group='Remote Item') c.argument('parent_reference', type=validate_file_or_dict, help='itemReference Expected value: ' 'json-string/@json-file.', arg_group='Remote Item') c.argument('shared', type=validate_file_or_dict, help='shared Expected value: json-string/@json-file.', arg_group='Remote Item') c.argument('sharepoint_ids1', action=AddSharepointIds, nargs='+', help='sharepointIds', arg_group='Remote Item') c.argument('integer_size', type=int, help='Size of the remote item. Read-only.', arg_group='Remote Item') c.argument('special_folder', action=AddSpecialFolder, nargs='+', help='specialFolder', arg_group='Remote Item') c.argument('microsoft_graph_video', action=AddVideo, nargs='+', help='video', arg_group='Remote Item') c.argument('microsoft_graph_remote_item_web_dav_url_web_dav_url', type=str, help='DAV compatible URL for the ' 'item.', arg_group='Remote Item') c.argument('microsoft_graph_remote_item_web_url', type=str, help='URL that displays the resource in the ' 'browser. Read-only.', arg_group='Remote Item') c.argument('queued_date_time', help='Date and time the pending binary operation was queued in UTC time. ' 'Read-only.', arg_group='Pending Operations Pending Content Update') c.argument('type_', options_list=['--type'], type=str, help='A string indicating the type of package. While ' 'oneNote is the only currently defined value, you should expect other package types to be returned ' 'and handle them accordingly.', arg_group='Package') c.argument('child_count', type=int, help='Number of children contained immediately within this container.', arg_group='Folder') c.argument('view', action=AddView, nargs='+', help='folderView', arg_group='Folder') c.argument('hashes', action=AddHashes, nargs='+', help='hashes', arg_group='File') c.argument('mime_type', type=str, help='The MIME type for the file. This is determined by logic on the server ' 'and might not be the value provided when the file was uploaded. Read-only.', arg_group='File') c.argument('processing_metadata', arg_type=get_three_state_flag(), help='', arg_group='File') c.argument('state', type=str, help='Represents the state of the deleted item.', arg_group='Deleted') c.argument('album', action=AddAlbum, nargs='+', help='album', arg_group='Bundle') c.argument('integer_child_count', type=int, help='', arg_group='Bundle') with self.argument_context('teams team-primary-channel update-member') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('conversation_member_id', type=str, help='key: id of conversationMember') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('display_name', type=str, help='The display name of the user.') c.argument('roles', nargs='+', help='The roles for that user.') with self.argument_context('teams team-primary-channel update-message') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('attachments', action=AddAttachments, nargs='+', help='Attached files. Attachments are currently ' 'read-only – sending attachments is not supported.') c.argument('body', action=AddBody, nargs='+', help='itemBody') c.argument('channel_identity', action=AddChannelIdentity, nargs='+', help='channelIdentity') c.argument('chat_id', type=str, help='') c.argument('created_date_time', help='Read only. Timestamp of when the chat message was created.') c.argument('deleted_date_time', help='Read only. Timestamp at which the chat message was deleted, or null if ' 'not deleted.') c.argument('etag', type=str, help='Read-only. Version number of the chat message.') c.argument('importance', arg_type=get_enum_type(['normal', 'high', 'urgent']), help='') c.argument('last_edited_date_time', help='Read only. Timestamp when edits to the chat message were made. ' 'Triggers an \'Edited\' flag in the Microsoft Teams UI. If no edits are made the value is null.') c.argument('last_modified_date_time', help='Read only. Timestamp when the chat message is created (initial ' 'setting) or edited, including when a reaction is added or removed.') c.argument('locale', type=str, help='Locale of the chat message set by the client.') c.argument('mentions', type=validate_file_or_dict, help='List of entities mentioned in the chat message. ' 'Currently supports user, bot, team, channel. Expected value: json-string/@json-file.') c.argument('message_type', arg_type=get_enum_type(['message', 'chatEvent', 'typing']), help='') c.argument('reactions', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('reply_to_id', type=str, help='Read-only. Id of the parent chat message or root chat message of the ' 'thread. (Only applies to chat messages in channels not chats)') c.argument('subject', type=str, help='The subject of the chat message, in plaintext.') c.argument('summary', type=str, help='Summary text of the chat message that could be used for push ' 'notifications and summary views or fall back views. Only applies to channel chat messages, not ' 'chat messages in a chat.') c.argument('web_url', type=str, help='') c.argument('hosted_contents', action=AddHostedContents, nargs='+', help='') c.argument('replies', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('dlp_action', arg_type=get_enum_type(['none', 'notifySender', 'blockAccess', 'blockAccessExternal']), help='', arg_group='Policy Violation') c.argument('justification_text', type=str, help='Justification text provided by the sender of the message when ' 'overriding a policy violation.', arg_group='Policy Violation') c.argument('policy_tip', action=AddPolicyTip, nargs='+', help='chatMessagePolicyViolationPolicyTip', arg_group='Policy Violation') c.argument('user_action', arg_type=get_enum_type(['none', 'override', 'reportFalsePositive']), help='', arg_group='Policy Violation') c.argument('verdict_details', arg_type=get_enum_type(['none', 'allowFalsePositiveOverride', 'allowOverrideWithoutJustification', 'allowOverrideWithJustification']), help='', arg_group='Policy Violation') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='From') with self.argument_context('teams team-primary-channel update-tab') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('configuration', action=AddConfiguration, nargs='+', help='teamsTabConfiguration') c.argument('display_name', type=str, help='Name of the tab.') c.argument('message_id', type=str, help='') c.argument('sort_order_index', type=str, help='') c.argument('teams_app_id', type=str, help='') c.argument('web_url', type=str, help='Deep link URL of the tab instance. Read only.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Teams App') c.argument('microsoft_graph_teams_app_display_name', type=str, help='The name of the catalog app provided by ' 'the app developer in the Microsoft Teams zip app package.', arg_group='Teams App') c.argument('distribution_method', arg_type=get_enum_type(['store', 'organization', 'sideloaded', 'unknownFutureValue']), help='', arg_group='Teams ' 'App') c.argument('external_id', type=str, help='The ID of the catalog provided by the app developer in the Microsoft ' 'Teams zip app package.', arg_group='Teams App') c.argument('app_definitions', type=validate_file_or_dict, help='The details for each version of the app. ' 'Expected value: json-string/@json-file.', arg_group='Teams App') with self.argument_context('teams team-primary-channel-member add') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('values', action=AddTeamsPrimarychannelMembersValues, nargs='+', help='') with self.argument_context('teams team-primary-channel-message create-hosted-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('content_bytes', help='') c.argument('content_type', type=str, help='') with self.argument_context('teams team-primary-channel-message create-reply') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('attachments', action=AddAttachments, nargs='+', help='Attached files. Attachments are currently ' 'read-only – sending attachments is not supported.') c.argument('body', action=AddBody, nargs='+', help='itemBody') c.argument('channel_identity', action=AddChannelIdentity, nargs='+', help='channelIdentity') c.argument('chat_id', type=str, help='') c.argument('created_date_time', help='Read only. Timestamp of when the chat message was created.') c.argument('deleted_date_time', help='Read only. Timestamp at which the chat message was deleted, or null if ' 'not deleted.') c.argument('etag', type=str, help='Read-only. Version number of the chat message.') c.argument('importance', arg_type=get_enum_type(['normal', 'high', 'urgent']), help='') c.argument('last_edited_date_time', help='Read only. Timestamp when edits to the chat message were made. ' 'Triggers an \'Edited\' flag in the Microsoft Teams UI. If no edits are made the value is null.') c.argument('last_modified_date_time', help='Read only. Timestamp when the chat message is created (initial ' 'setting) or edited, including when a reaction is added or removed.') c.argument('locale', type=str, help='Locale of the chat message set by the client.') c.argument('mentions', type=validate_file_or_dict, help='List of entities mentioned in the chat message. ' 'Currently supports user, bot, team, channel. Expected value: json-string/@json-file.') c.argument('message_type', arg_type=get_enum_type(['message', 'chatEvent', 'typing']), help='') c.argument('reactions', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('reply_to_id', type=str, help='Read-only. Id of the parent chat message or root chat message of the ' 'thread. (Only applies to chat messages in channels not chats)') c.argument('subject', type=str, help='The subject of the chat message, in plaintext.') c.argument('summary', type=str, help='Summary text of the chat message that could be used for push ' 'notifications and summary views or fall back views. Only applies to channel chat messages, not ' 'chat messages in a chat.') c.argument('web_url', type=str, help='') c.argument('hosted_contents', action=AddHostedContents, nargs='+', help='') c.argument('replies', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('dlp_action', arg_type=get_enum_type(['none', 'notifySender', 'blockAccess', 'blockAccessExternal']), help='', arg_group='Policy Violation') c.argument('justification_text', type=str, help='Justification text provided by the sender of the message when ' 'overriding a policy violation.', arg_group='Policy Violation') c.argument('policy_tip', action=AddPolicyTip, nargs='+', help='chatMessagePolicyViolationPolicyTip', arg_group='Policy Violation') c.argument('user_action', arg_type=get_enum_type(['none', 'override', 'reportFalsePositive']), help='', arg_group='Policy Violation') c.argument('verdict_details', arg_type=get_enum_type(['none', 'allowFalsePositiveOverride', 'allowOverrideWithoutJustification', 'allowOverrideWithJustification']), help='', arg_group='Policy Violation') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='From') with self.argument_context('teams team-primary-channel-message delete-hosted-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_hosted_content_id', type=str, help='key: id of chatMessageHostedContent') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-primary-channel-message delete-reply') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_id1', type=str, help='key: id of chatMessage') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-primary-channel-message delta') as c: c.argument('team_id', type=str, help='key: id of team') with self.argument_context('teams team-primary-channel-message list-hosted-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-primary-channel-message list-reply') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-primary-channel-message set-hosted-content-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_hosted_content_id', type=str, help='key: id of chatMessageHostedContent') c.argument('data', help='New media content.') with self.argument_context('teams team-primary-channel-message show-hosted-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_hosted_content_id', type=str, help='key: id of chatMessageHostedContent') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-primary-channel-message show-hosted-content-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_hosted_content_id', type=str, help='key: id of chatMessageHostedContent') with self.argument_context('teams team-primary-channel-message show-reply') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_id1', type=str, help='key: id of chatMessage') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-primary-channel-message update-hosted-content') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_hosted_content_id', type=str, help='key: id of chatMessageHostedContent') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('content_bytes', help='') c.argument('content_type', type=str, help='') with self.argument_context('teams team-primary-channel-message update-reply') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('chat_message_id', type=str, help='key: id of chatMessage') c.argument('chat_message_id1', type=str, help='key: id of chatMessage') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('attachments', action=AddAttachments, nargs='+', help='Attached files. Attachments are currently ' 'read-only – sending attachments is not supported.') c.argument('body', action=AddBody, nargs='+', help='itemBody') c.argument('channel_identity', action=AddChannelIdentity, nargs='+', help='channelIdentity') c.argument('chat_id', type=str, help='') c.argument('created_date_time', help='Read only. Timestamp of when the chat message was created.') c.argument('deleted_date_time', help='Read only. Timestamp at which the chat message was deleted, or null if ' 'not deleted.') c.argument('etag', type=str, help='Read-only. Version number of the chat message.') c.argument('importance', arg_type=get_enum_type(['normal', 'high', 'urgent']), help='') c.argument('last_edited_date_time', help='Read only. Timestamp when edits to the chat message were made. ' 'Triggers an \'Edited\' flag in the Microsoft Teams UI. If no edits are made the value is null.') c.argument('last_modified_date_time', help='Read only. Timestamp when the chat message is created (initial ' 'setting) or edited, including when a reaction is added or removed.') c.argument('locale', type=str, help='Locale of the chat message set by the client.') c.argument('mentions', type=validate_file_or_dict, help='List of entities mentioned in the chat message. ' 'Currently supports user, bot, team, channel. Expected value: json-string/@json-file.') c.argument('message_type', arg_type=get_enum_type(['message', 'chatEvent', 'typing']), help='') c.argument('reactions', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('reply_to_id', type=str, help='Read-only. Id of the parent chat message or root chat message of the ' 'thread. (Only applies to chat messages in channels not chats)') c.argument('subject', type=str, help='The subject of the chat message, in plaintext.') c.argument('summary', type=str, help='Summary text of the chat message that could be used for push ' 'notifications and summary views or fall back views. Only applies to channel chat messages, not ' 'chat messages in a chat.') c.argument('web_url', type=str, help='') c.argument('hosted_contents', action=AddHostedContents, nargs='+', help='') c.argument('replies', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('dlp_action', arg_type=get_enum_type(['none', 'notifySender', 'blockAccess', 'blockAccessExternal']), help='', arg_group='Policy Violation') c.argument('justification_text', type=str, help='Justification text provided by the sender of the message when ' 'overriding a policy violation.', arg_group='Policy Violation') c.argument('policy_tip', action=AddPolicyTip, nargs='+', help='chatMessagePolicyViolationPolicyTip', arg_group='Policy Violation') c.argument('user_action', arg_type=get_enum_type(['none', 'override', 'reportFalsePositive']), help='', arg_group='Policy Violation') c.argument('verdict_details', arg_type=get_enum_type(['none', 'allowFalsePositiveOverride', 'allowOverrideWithoutJustification', 'allowOverrideWithJustification']), help='', arg_group='Policy Violation') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='From') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='From') with self.argument_context('teams team-primary-channel-message-reply delta') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('chat_message_id', type=str, help='key: id of chatMessage') with self.argument_context('teams team-primary-channel-tab delete-ref-team-app') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-primary-channel-tab set-ref-team-app') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('body', type=validate_file_or_dict, help='New navigation property ref values Expected value: ' 'json-string/@json-file.') with self.argument_context('teams team-primary-channel-tab show-ref-team-app') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') with self.argument_context('teams team-primary-channel-tab show-team-app') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('teams_tab_id', type=str, help='key: id of teamsTab') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule create-offer-shift-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('assigned_to', arg_type=get_enum_type(['sender', 'recipient', 'manager', 'system', 'unknownFutureValue']), help='') c.argument('manager_action_date_time', help='') c.argument('manager_action_message', type=str, help='') c.argument('manager_user_id', type=str, help='') c.argument('sender_date_time', help='') c.argument('sender_message', type=str, help='') c.argument('sender_user_id', type=str, help='') c.argument('state', arg_type=get_enum_type(['pending', 'approved', 'declined', 'unknownFutureValue']), help='') c.argument('recipient_action_date_time', help='The Timestamp type represents date and time information using ' 'ISO 8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look ' 'like this: \'2014-01-01T00:00:00Z\'') c.argument('recipient_action_message', type=str, help='Custom message sent by recipient of the offer shift ' 'request.') c.argument('recipient_user_id', type=str, help='User ID of the recipient of the offer shift request.') c.argument('sender_shift_id', type=str, help='User ID of the sender of the offer shift request.') with self.argument_context('teams team-schedule create-open-shift') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('draft_open_shift', action=AddDraftOpenShift, nargs='+', help='openShiftItem') c.argument('is_staged_for_deletion', arg_type=get_three_state_flag(), help='') c.argument('scheduling_group_id', type=str, help='ID for the scheduling group that the open shift belongs to.') c.argument('shared_open_shift', action=AddDraftOpenShift, nargs='+', help='openShiftItem') with self.argument_context('teams team-schedule create-open-shift-change-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('assigned_to', arg_type=get_enum_type(['sender', 'recipient', 'manager', 'system', 'unknownFutureValue']), help='') c.argument('manager_action_date_time', help='') c.argument('manager_action_message', type=str, help='') c.argument('manager_user_id', type=str, help='') c.argument('sender_date_time', help='') c.argument('sender_message', type=str, help='') c.argument('sender_user_id', type=str, help='') c.argument('state', arg_type=get_enum_type(['pending', 'approved', 'declined', 'unknownFutureValue']), help='') c.argument('open_shift_id', type=str, help='ID for the open shift.') with self.argument_context('teams team-schedule create-scheduling-group') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('display_name', type=str, help='The display name for the schedulingGroup. Required.') c.argument('is_active', arg_type=get_three_state_flag(), help='Indicates whether the schedulingGroup can be ' 'used when creating new entities or updating existing ones. Required.') c.argument('user_ids', nargs='+', help='The list of user IDs that are a member of the schedulingGroup. ' 'Required.') with self.argument_context('teams team-schedule create-shift') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('is_staged_for_deletion', arg_type=get_three_state_flag(), help='') c.argument('scheduling_group_id', type=str, help='ID of the scheduling group the shift is part of. Required.') c.argument('user_id', type=str, help='ID of the user assigned to the shift. Required.') c.argument('end_date_time', help='', arg_group='Shared Shift') c.argument('start_date_time', help='', arg_group='Shared Shift') c.argument('theme', arg_type=get_enum_type(['white', 'blue', 'green', 'purple', 'pink', 'yellow', 'gray', 'darkBlue', 'darkGreen', 'darkPurple', 'darkPink', 'darkYellow', 'unknownFutureValue']), help='', arg_group='Shared Shift') c.argument('activities', action=AddActivities, nargs='+', help='An incremental part of a shift which can cover ' 'details of when and where an employee is during their shift. For example, an assignment or a ' 'scheduled break or lunch. Required.', arg_group='Shared Shift') c.argument('display_name', type=str, help='The shift label of the shiftItem.', arg_group='Shared Shift') c.argument('notes', type=str, help='The shift notes for the shiftItem.', arg_group='Shared Shift') c.argument('microsoft_graph_schedule_entity_end_date_time_end_date_time', help='', arg_group='Draft Shift') c.argument('microsoft_graph_schedule_entity_start_date_time_start_date_time', help='', arg_group='Draft Shift') c.argument('microsoft_graph_schedule_entity_theme', arg_type=get_enum_type(['white', 'blue', 'green', 'purple', 'pink', 'yellow', 'gray', 'darkBlue', 'darkGreen', 'darkPurple', 'darkPink', 'darkYellow', 'unknownFutureValue']), help='', arg_group='Draft Shift') c.argument('microsoft_graph_shift_item_activities', action=AddActivities, nargs='+', help='An incremental part ' 'of a shift which can cover details of when and where an employee is during their shift. For ' 'example, an assignment or a scheduled break or lunch. Required.', arg_group='Draft Shift') c.argument('microsoft_graph_shift_item_display_name', type=str, help='The shift label of the shiftItem.', arg_group='Draft Shift') c.argument('microsoft_graph_shift_item_notes', type=str, help='The shift notes for the shiftItem.', arg_group='Draft Shift') with self.argument_context('teams team-schedule create-swap-shift-change-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('assigned_to', arg_type=get_enum_type(['sender', 'recipient', 'manager', 'system', 'unknownFutureValue']), help='') c.argument('manager_action_date_time', help='') c.argument('manager_action_message', type=str, help='') c.argument('manager_user_id', type=str, help='') c.argument('sender_date_time', help='') c.argument('sender_message', type=str, help='') c.argument('sender_user_id', type=str, help='') c.argument('state', arg_type=get_enum_type(['pending', 'approved', 'declined', 'unknownFutureValue']), help='') c.argument('recipient_action_date_time', help='The Timestamp type represents date and time information using ' 'ISO 8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look ' 'like this: \'2014-01-01T00:00:00Z\'') c.argument('recipient_action_message', type=str, help='Custom message sent by recipient of the offer shift ' 'request.') c.argument('recipient_user_id', type=str, help='User ID of the recipient of the offer shift request.') c.argument('sender_shift_id', type=str, help='User ID of the sender of the offer shift request.') c.argument('recipient_shift_id', type=str, help='ShiftId for the recipient user with whom the request is to ' 'swap.') with self.argument_context('teams team-schedule create-time-card') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('breaks', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('confirmed_by', arg_type=get_enum_type(['none', 'user', 'manager', 'unknownFutureValue']), help='') c.argument('notes', action=AddBody, nargs='+', help='itemBody') c.argument('state', arg_type=get_enum_type(['clockedIn', 'onBreak', 'clockedOut', 'unknownFutureValue']), help='') c.argument('user_id', type=str, help='') c.argument('microsoft_graph_time_card_entry_breaks', type=validate_file_or_dict, help=' Expected value: ' 'json-string/@json-file.', arg_group='Original Entry') c.argument('clock_in_event', type=validate_file_or_dict, help='timeCardEvent Expected value: ' 'json-string/@json-file.', arg_group='Original Entry') c.argument('clock_out_event', type=validate_file_or_dict, help='timeCardEvent Expected value: ' 'json-string/@json-file.', arg_group='Original Entry') c.argument('at_approved_location', arg_type=get_three_state_flag(), help='', arg_group='Clock Out Event') c.argument('date_time', help='', arg_group='Clock Out Event') c.argument('microsoft_graph_item_body_notes', action=AddBody, nargs='+', help='itemBody', arg_group='Clock Out ' 'Event') c.argument('boolean_at_approved_location', arg_type=get_three_state_flag(), help='', arg_group='Clock In Event') c.argument('microsoft_graph_time_card_event_date_time', help='', arg_group='Clock In Event') c.argument('notes1', action=AddBody, nargs='+', help='itemBody', arg_group='Clock In Event') with self.argument_context('teams team-schedule create-time-off') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('draft_time_off', action=AddDraftTimeOff, nargs='+', help='timeOffItem') c.argument('is_staged_for_deletion', arg_type=get_three_state_flag(), help='') c.argument('shared_time_off', action=AddDraftTimeOff, nargs='+', help='timeOffItem') c.argument('user_id', type=str, help='ID of the user assigned to the timeOff. Required.') with self.argument_context('teams team-schedule create-time-off-reason') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('display_name', type=str, help='The name of the timeOffReason. Required.') c.argument('icon_type', arg_type=get_enum_type(['none', 'car', 'calendar', 'running', 'plane', 'firstAid', 'doctor', 'notWorking', 'clock', 'juryDuty', 'globe', 'cup', 'phone', 'weather', 'umbrella', 'piggyBank', 'dog', 'cake', 'trafficCone', 'pin', 'sunny', 'unknownFutureValue']), help='') c.argument('is_active', arg_type=get_three_state_flag(), help='Indicates whether the timeOffReason can be used ' 'when creating new entities or updating existing ones. Required.') with self.argument_context('teams team-schedule create-time-off-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('assigned_to', arg_type=get_enum_type(['sender', 'recipient', 'manager', 'system', 'unknownFutureValue']), help='') c.argument('manager_action_date_time', help='') c.argument('manager_action_message', type=str, help='') c.argument('manager_user_id', type=str, help='') c.argument('sender_date_time', help='') c.argument('sender_message', type=str, help='') c.argument('sender_user_id', type=str, help='') c.argument('state', arg_type=get_enum_type(['pending', 'approved', 'declined', 'unknownFutureValue']), help='') c.argument('end_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('start_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('time_off_reason_id', type=str, help='The reason for the time off.') with self.argument_context('teams team-schedule delete-offer-shift-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('offer_shift_request_id', type=str, help='key: id of offerShiftRequest') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-schedule delete-open-shift') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('open_shift_id', type=str, help='key: id of openShift') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-schedule delete-open-shift-change-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('open_shift_change_request_id', type=str, help='key: id of openShiftChangeRequest') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-schedule delete-scheduling-group') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('scheduling_group_id', type=str, help='key: id of schedulingGroup') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-schedule delete-shift') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('shift_id', type=str, help='key: id of shift') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-schedule delete-swap-shift-change-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('swap_shifts_change_request_id', type=str, help='key: id of swapShiftsChangeRequest') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-schedule delete-time-card') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('time_card_id', type=str, help='key: id of timeCard') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-schedule delete-time-off') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('time_off_id', type=str, help='key: id of timeOff') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-schedule delete-time-off-reason') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('time_off_reason_id', type=str, help='key: id of timeOffReason') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-schedule delete-time-off-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('time_off_request_id', type=str, help='key: id of timeOffRequest') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams team-schedule list-offer-shift-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule list-open-shift') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule list-open-shift-change-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule list-scheduling-group') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule list-shift') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule list-swap-shift-change-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule list-time-card') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule list-time-off') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule list-time-off-reason') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule list-time-off-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule share') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('notify_team', arg_type=get_three_state_flag(), help='') c.argument('start_date_time', help='') c.argument('end_date_time', help='') with self.argument_context('teams team-schedule show-offer-shift-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('offer_shift_request_id', type=str, help='key: id of offerShiftRequest') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule show-open-shift') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('open_shift_id', type=str, help='key: id of openShift') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule show-open-shift-change-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('open_shift_change_request_id', type=str, help='key: id of openShiftChangeRequest') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule show-scheduling-group') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('scheduling_group_id', type=str, help='key: id of schedulingGroup') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule show-shift') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('shift_id', type=str, help='key: id of shift') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule show-swap-shift-change-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('swap_shifts_change_request_id', type=str, help='key: id of swapShiftsChangeRequest') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule show-time-card') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('time_card_id', type=str, help='key: id of timeCard') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule show-time-off') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('time_off_id', type=str, help='key: id of timeOff') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule show-time-off-reason') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('time_off_reason_id', type=str, help='key: id of timeOffReason') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule show-time-off-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('time_off_request_id', type=str, help='key: id of timeOffRequest') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams team-schedule update-offer-shift-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('offer_shift_request_id', type=str, help='key: id of offerShiftRequest') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('assigned_to', arg_type=get_enum_type(['sender', 'recipient', 'manager', 'system', 'unknownFutureValue']), help='') c.argument('manager_action_date_time', help='') c.argument('manager_action_message', type=str, help='') c.argument('manager_user_id', type=str, help='') c.argument('sender_date_time', help='') c.argument('sender_message', type=str, help='') c.argument('sender_user_id', type=str, help='') c.argument('state', arg_type=get_enum_type(['pending', 'approved', 'declined', 'unknownFutureValue']), help='') c.argument('recipient_action_date_time', help='The Timestamp type represents date and time information using ' 'ISO 8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look ' 'like this: \'2014-01-01T00:00:00Z\'') c.argument('recipient_action_message', type=str, help='Custom message sent by recipient of the offer shift ' 'request.') c.argument('recipient_user_id', type=str, help='User ID of the recipient of the offer shift request.') c.argument('sender_shift_id', type=str, help='User ID of the sender of the offer shift request.') with self.argument_context('teams team-schedule update-open-shift') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('open_shift_id', type=str, help='key: id of openShift') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('draft_open_shift', action=AddDraftOpenShift, nargs='+', help='openShiftItem') c.argument('is_staged_for_deletion', arg_type=get_three_state_flag(), help='') c.argument('scheduling_group_id', type=str, help='ID for the scheduling group that the open shift belongs to.') c.argument('shared_open_shift', action=AddDraftOpenShift, nargs='+', help='openShiftItem') with self.argument_context('teams team-schedule update-open-shift-change-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('open_shift_change_request_id', type=str, help='key: id of openShiftChangeRequest') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('assigned_to', arg_type=get_enum_type(['sender', 'recipient', 'manager', 'system', 'unknownFutureValue']), help='') c.argument('manager_action_date_time', help='') c.argument('manager_action_message', type=str, help='') c.argument('manager_user_id', type=str, help='') c.argument('sender_date_time', help='') c.argument('sender_message', type=str, help='') c.argument('sender_user_id', type=str, help='') c.argument('state', arg_type=get_enum_type(['pending', 'approved', 'declined', 'unknownFutureValue']), help='') c.argument('open_shift_id', type=str, help='ID for the open shift.') with self.argument_context('teams team-schedule update-scheduling-group') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('scheduling_group_id', type=str, help='key: id of schedulingGroup') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('display_name', type=str, help='The display name for the schedulingGroup. Required.') c.argument('is_active', arg_type=get_three_state_flag(), help='Indicates whether the schedulingGroup can be ' 'used when creating new entities or updating existing ones. Required.') c.argument('user_ids', nargs='+', help='The list of user IDs that are a member of the schedulingGroup. ' 'Required.') with self.argument_context('teams team-schedule update-shift') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('shift_id', type=str, help='key: id of shift') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('is_staged_for_deletion', arg_type=get_three_state_flag(), help='') c.argument('scheduling_group_id', type=str, help='ID of the scheduling group the shift is part of. Required.') c.argument('user_id', type=str, help='ID of the user assigned to the shift. Required.') c.argument('end_date_time', help='', arg_group='Shared Shift') c.argument('start_date_time', help='', arg_group='Shared Shift') c.argument('theme', arg_type=get_enum_type(['white', 'blue', 'green', 'purple', 'pink', 'yellow', 'gray', 'darkBlue', 'darkGreen', 'darkPurple', 'darkPink', 'darkYellow', 'unknownFutureValue']), help='', arg_group='Shared Shift') c.argument('activities', action=AddActivities, nargs='+', help='An incremental part of a shift which can cover ' 'details of when and where an employee is during their shift. For example, an assignment or a ' 'scheduled break or lunch. Required.', arg_group='Shared Shift') c.argument('display_name', type=str, help='The shift label of the shiftItem.', arg_group='Shared Shift') c.argument('notes', type=str, help='The shift notes for the shiftItem.', arg_group='Shared Shift') c.argument('microsoft_graph_schedule_entity_end_date_time_end_date_time', help='', arg_group='Draft Shift') c.argument('microsoft_graph_schedule_entity_start_date_time_start_date_time', help='', arg_group='Draft Shift') c.argument('microsoft_graph_schedule_entity_theme', arg_type=get_enum_type(['white', 'blue', 'green', 'purple', 'pink', 'yellow', 'gray', 'darkBlue', 'darkGreen', 'darkPurple', 'darkPink', 'darkYellow', 'unknownFutureValue']), help='', arg_group='Draft Shift') c.argument('microsoft_graph_shift_item_activities', action=AddActivities, nargs='+', help='An incremental part ' 'of a shift which can cover details of when and where an employee is during their shift. For ' 'example, an assignment or a scheduled break or lunch. Required.', arg_group='Draft Shift') c.argument('microsoft_graph_shift_item_display_name', type=str, help='The shift label of the shiftItem.', arg_group='Draft Shift') c.argument('microsoft_graph_shift_item_notes', type=str, help='The shift notes for the shiftItem.', arg_group='Draft Shift') with self.argument_context('teams team-schedule update-swap-shift-change-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('swap_shifts_change_request_id', type=str, help='key: id of swapShiftsChangeRequest') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('assigned_to', arg_type=get_enum_type(['sender', 'recipient', 'manager', 'system', 'unknownFutureValue']), help='') c.argument('manager_action_date_time', help='') c.argument('manager_action_message', type=str, help='') c.argument('manager_user_id', type=str, help='') c.argument('sender_date_time', help='') c.argument('sender_message', type=str, help='') c.argument('sender_user_id', type=str, help='') c.argument('state', arg_type=get_enum_type(['pending', 'approved', 'declined', 'unknownFutureValue']), help='') c.argument('recipient_action_date_time', help='The Timestamp type represents date and time information using ' 'ISO 8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look ' 'like this: \'2014-01-01T00:00:00Z\'') c.argument('recipient_action_message', type=str, help='Custom message sent by recipient of the offer shift ' 'request.') c.argument('recipient_user_id', type=str, help='User ID of the recipient of the offer shift request.') c.argument('sender_shift_id', type=str, help='User ID of the sender of the offer shift request.') c.argument('recipient_shift_id', type=str, help='ShiftId for the recipient user with whom the request is to ' 'swap.') with self.argument_context('teams team-schedule update-time-card') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('time_card_id', type=str, help='key: id of timeCard') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('breaks', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('confirmed_by', arg_type=get_enum_type(['none', 'user', 'manager', 'unknownFutureValue']), help='') c.argument('notes', action=AddBody, nargs='+', help='itemBody') c.argument('state', arg_type=get_enum_type(['clockedIn', 'onBreak', 'clockedOut', 'unknownFutureValue']), help='') c.argument('user_id', type=str, help='') c.argument('microsoft_graph_time_card_entry_breaks', type=validate_file_or_dict, help=' Expected value: ' 'json-string/@json-file.', arg_group='Original Entry') c.argument('clock_in_event', type=validate_file_or_dict, help='timeCardEvent Expected value: ' 'json-string/@json-file.', arg_group='Original Entry') c.argument('clock_out_event', type=validate_file_or_dict, help='timeCardEvent Expected value: ' 'json-string/@json-file.', arg_group='Original Entry') c.argument('at_approved_location', arg_type=get_three_state_flag(), help='', arg_group='Clock Out Event') c.argument('date_time', help='', arg_group='Clock Out Event') c.argument('microsoft_graph_item_body_notes', action=AddBody, nargs='+', help='itemBody', arg_group='Clock Out ' 'Event') c.argument('boolean_at_approved_location', arg_type=get_three_state_flag(), help='', arg_group='Clock In Event') c.argument('microsoft_graph_time_card_event_date_time', help='', arg_group='Clock In Event') c.argument('notes1', action=AddBody, nargs='+', help='itemBody', arg_group='Clock In Event') with self.argument_context('teams team-schedule update-time-off') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('time_off_id', type=str, help='key: id of timeOff') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('draft_time_off', action=AddDraftTimeOff, nargs='+', help='timeOffItem') c.argument('is_staged_for_deletion', arg_type=get_three_state_flag(), help='') c.argument('shared_time_off', action=AddDraftTimeOff, nargs='+', help='timeOffItem') c.argument('user_id', type=str, help='ID of the user assigned to the timeOff. Required.') with self.argument_context('teams team-schedule update-time-off-reason') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('time_off_reason_id', type=str, help='key: id of timeOffReason') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('display_name', type=str, help='The name of the timeOffReason. Required.') c.argument('icon_type', arg_type=get_enum_type(['none', 'car', 'calendar', 'running', 'plane', 'firstAid', 'doctor', 'notWorking', 'clock', 'juryDuty', 'globe', 'cup', 'phone', 'weather', 'umbrella', 'piggyBank', 'dog', 'cake', 'trafficCone', 'pin', 'sunny', 'unknownFutureValue']), help='') c.argument('is_active', arg_type=get_three_state_flag(), help='Indicates whether the timeOffReason can be used ' 'when creating new entities or updating existing ones. Required.') with self.argument_context('teams team-schedule update-time-off-request') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('time_off_request_id', type=str, help='key: id of timeOffRequest') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('assigned_to', arg_type=get_enum_type(['sender', 'recipient', 'manager', 'system', 'unknownFutureValue']), help='') c.argument('manager_action_date_time', help='') c.argument('manager_action_message', type=str, help='') c.argument('manager_user_id', type=str, help='') c.argument('sender_date_time', help='') c.argument('sender_message', type=str, help='') c.argument('sender_user_id', type=str, help='') c.argument('state', arg_type=get_enum_type(['pending', 'approved', 'declined', 'unknownFutureValue']), help='') c.argument('end_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('start_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('time_off_reason_id', type=str, help='The reason for the time off.') with self.argument_context('teams team-schedule-time-card clock-in') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('at_approved_location', arg_type=get_three_state_flag(), help='') c.argument('on_behalf_of_user_id', type=str, help='') c.argument('notes', action=AddBody, nargs='+', help='itemBody') with self.argument_context('teams team-schedule-time-card clock-out') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('time_card_id', type=str, help='key: id of timeCard') c.argument('at_approved_location', arg_type=get_three_state_flag(), help='') c.argument('notes', action=AddBody, nargs='+', help='itemBody') with self.argument_context('teams team-schedule-time-card confirm') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('time_card_id', type=str, help='key: id of timeCard') with self.argument_context('teams team-schedule-time-card end-break') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('time_card_id', type=str, help='key: id of timeCard') c.argument('at_approved_location', arg_type=get_three_state_flag(), help='') c.argument('notes', action=AddBody, nargs='+', help='itemBody') with self.argument_context('teams team-schedule-time-card start-break') as c: c.argument('team_id', type=str, help='key: id of team') c.argument('time_card_id', type=str, help='key: id of timeCard') c.argument('at_approved_location', arg_type=get_three_state_flag(), help='') c.argument('notes', action=AddBody, nargs='+', help='itemBody') with self.argument_context('teams teamwork-teamwork show-teamwork') as c: c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams teamwork-teamwork update-teamwork') as c: c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('workforce_integrations', type=validate_file_or_dict, help=' Expected value: ' 'json-string/@json-file.') with self.argument_context('teams teamwork create-workforce-integration') as c: c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('api_version', type=int, help='API version for the call back URL. Start with 1.') c.argument('display_name', type=str, help='Name of the workforce integration.') c.argument('eligibility_filtering_enabled_entities', arg_type=get_enum_type(['none', 'swapRequest', 'offerShiftRequest', 'unknownFutureValue']), help='') c.argument('encryption', action=AddEncryption, nargs='+', help='workforceIntegrationEncryption') c.argument('is_active', arg_type=get_three_state_flag(), help='Indicates whether this workforce integration is ' 'currently active and available.') c.argument('supported_entities', arg_type=get_enum_type(['none', 'shift', 'swapRequest', 'userShiftPreferences', 'openShift', 'openShiftRequest', 'offerShiftRequest', 'unknownFutureValue']), help='') c.argument('supports', arg_type=get_enum_type(['none', 'shift', 'swapRequest', 'userShiftPreferences', 'openShift', 'openShiftRequest', 'offerShiftRequest', 'unknownFutureValue']), help='') c.argument('url', type=str, help='Workforce Integration URL for callbacks from the Shifts service.') with self.argument_context('teams teamwork delete-workforce-integration') as c: c.argument('workforce_integration_id', type=str, help='key: id of workforceIntegration') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams teamwork list-workforce-integration') as c: c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams teamwork show-workforce-integration') as c: c.argument('workforce_integration_id', type=str, help='key: id of workforceIntegration') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams teamwork update-workforce-integration') as c: c.argument('workforce_integration_id', type=str, help='key: id of workforceIntegration') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='The Timestamp type represents date and time information using ISO 8601 ' 'format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like this: ' '\'2014-01-01T00:00:00Z\'') c.argument('last_modified_date_time', help='The Timestamp type represents date and time information using ISO ' '8601 format and is always in UTC time. For example, midnight UTC on Jan 1, 2014 would look like ' 'this: \'2014-01-01T00:00:00Z\'') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Last Modified By') c.argument('microsoft_graph_identity_application', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_device', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('microsoft_graph_identity_user', action=AddApplication, nargs='+', help='identity', arg_group='Created By') c.argument('api_version', type=int, help='API version for the call back URL. Start with 1.') c.argument('display_name', type=str, help='Name of the workforce integration.') c.argument('eligibility_filtering_enabled_entities', arg_type=get_enum_type(['none', 'swapRequest', 'offerShiftRequest', 'unknownFutureValue']), help='') c.argument('encryption', action=AddEncryption, nargs='+', help='workforceIntegrationEncryption') c.argument('is_active', arg_type=get_three_state_flag(), help='Indicates whether this workforce integration is ' 'currently active and available.') c.argument('supported_entities', arg_type=get_enum_type(['none', 'shift', 'swapRequest', 'userShiftPreferences', 'openShift', 'openShiftRequest', 'offerShiftRequest', 'unknownFutureValue']), help='') c.argument('supports', arg_type=get_enum_type(['none', 'shift', 'swapRequest', 'userShiftPreferences', 'openShift', 'openShiftRequest', 'offerShiftRequest', 'unknownFutureValue']), help='') c.argument('url', type=str, help='Workforce Integration URL for callbacks from the Shifts service.') with self.argument_context('teams user create-chat') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='') c.argument('last_updated_date_time', help='') c.argument('topic', type=str, help='') c.argument('installed_apps', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('members', action=AddUsersMembers, nargs='+', help='') c.argument('messages', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('tabs', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') with self.argument_context('teams user create-joined-team') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('classification', type=str, help='An optional label. Typically describes the data or business ' 'sensitivity of the team. Must match one of a pre-configured set in the tenant\'s directory.') c.argument('created_date_time', help='') c.argument('description', type=str, help='An optional description for the team.') c.argument('display_name', type=str, help='The name of the team.') c.argument('fun_settings', action=AddFunSettings, nargs='+', help='teamFunSettings') c.argument('guest_settings', action=AddGuestSettings, nargs='+', help='teamGuestSettings') c.argument('internal_id', type=str, help='A unique ID for the team that has been used in a few places such as ' 'the audit log/Office 365 Management Activity API.') c.argument('is_archived', arg_type=get_three_state_flag(), help='Whether this team is in read-only mode.') c.argument('is_membership_limited_to_owners', arg_type=get_three_state_flag(), help='') c.argument('member_settings', action=AddMemberSettings, nargs='+', help='teamMemberSettings') c.argument('messaging_settings', action=AddMessagingSettings, nargs='+', help='teamMessagingSettings') c.argument('specialization', arg_type=get_enum_type(['none', 'educationStandard', 'educationClass', 'educationProfessionalLearningCommunity', 'educationStaff', 'healthcareStandard', 'healthcareCareCoordination', 'unknownFutureValue']), help='') c.argument('visibility', arg_type=get_enum_type(['private', 'public', 'hiddenMembership', 'unknownFutureValue']), help='') c.argument('web_url', type=str, help='A hyperlink that will go to the team in the Microsoft Teams client. This ' 'is the URL that you get when you right-click a team in the Microsoft Teams client and select Get ' 'link to team. This URL should be treated as an opaque blob, and not parsed.') c.argument('channels', type=validate_file_or_dict, help='The collection of channels & messages associated with ' 'the team. Expected value: json-string/@json-file.') c.argument('group', type=validate_file_or_dict, help='Represents an Azure Active Directory object. The ' 'directoryObject type is the base type for many other directory entity types. Expected value: ' 'json-string/@json-file.') c.argument('installed_apps', type=validate_file_or_dict, help='The apps installed in this team. Expected ' 'value: json-string/@json-file.') c.argument('members', action=AddGroupsMembers, nargs='+', help='Members and owners of the team.') c.argument('operations', type=validate_file_or_dict, help='The async operations that ran or are running on ' 'this team. Expected value: json-string/@json-file.') c.argument('owners', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('photo', action=AddGroupsPhoto, nargs='+', help='profilePhoto') c.argument('primary_channel', type=validate_file_or_dict, help='channel Expected value: ' 'json-string/@json-file.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Template') c.argument('id1', type=str, help='Read-only.', arg_group='Schedule') c.argument('enabled', arg_type=get_three_state_flag(), help='Indicates whether the schedule is enabled for the ' 'team. Required.', arg_group='Schedule') c.argument('offer_shift_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether offer ' 'shift requests are enabled for the schedule.', arg_group='Schedule') c.argument('open_shifts_enabled', arg_type=get_three_state_flag(), help='Indicates whether open shifts are ' 'enabled for the schedule.', arg_group='Schedule') c.argument('provision_status', arg_type=get_enum_type(['NotStarted', 'Running', 'Completed', 'Failed']), help='', arg_group='Schedule') c.argument('provision_status_code', type=str, help='Additional information about why schedule provisioning ' 'failed.', arg_group='Schedule') c.argument('swap_shifts_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether swap ' 'shifts requests are enabled for the schedule.', arg_group='Schedule') c.argument('time_clock_enabled', arg_type=get_three_state_flag(), help='Indicates whether time clock is ' 'enabled for the schedule.', arg_group='Schedule') c.argument('time_off_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether time off ' 'requests are enabled for the schedule.', arg_group='Schedule') c.argument('time_zone', type=str, help='Indicates the time zone of the schedule team using tz database format. ' 'Required.', arg_group='Schedule') c.argument('workforce_integration_ids', nargs='+', help='', arg_group='Schedule') c.argument('offer_shift_requests', action=AddOfferShiftRequests, nargs='+', help='', arg_group='Schedule') c.argument('open_shift_change_requests', action=AddOpenShiftChangeRequests, nargs='+', help='', arg_group='Schedule') c.argument('open_shifts', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Schedule') c.argument('scheduling_groups', action=AddSchedulingGroups, nargs='+', help='The logical grouping of users in ' 'the schedule (usually by role).', arg_group='Schedule') c.argument('shifts', type=validate_file_or_dict, help='The shifts in the schedule. Expected value: ' 'json-string/@json-file.', arg_group='Schedule') c.argument('swap_shifts_change_requests', action=AddSwapShiftsChangeRequests, nargs='+', help='', arg_group='Schedule') c.argument('time_cards', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Schedule') c.argument('time_off_reasons', action=AddTimeOffReasons, nargs='+', help='The set of reasons for a time off in ' 'the schedule.', arg_group='Schedule') c.argument('time_off_requests', action=AddTimeOffRequests, nargs='+', help='', arg_group='Schedule') c.argument('times_off', type=validate_file_or_dict, help='The instances of times off in the schedule. Expected ' 'value: json-string/@json-file.', arg_group='Schedule') c.argument('approved_location', action=AddApprovedLocation, nargs='+', help='geoCoordinates', arg_group='Schedule Time Clock Settings') c.argument('show_in_teams_search_and_suggestions', arg_type=get_three_state_flag(), help='', arg_group='Discovery Settings') with self.argument_context('teams user delete-chat') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('chat_id', type=str, help='key: id of chat') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams user delete-joined-team') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('team_id', type=str, help='key: id of team') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams user delete-teamwork') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams user list-chat') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams user list-joined-team') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams user show-chat') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('chat_id', type=str, help='key: id of chat') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams user show-joined-team') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('team_id', type=str, help='key: id of team') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams user show-teamwork') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams user update-chat') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('chat_id', type=str, help='key: id of chat') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('created_date_time', help='') c.argument('last_updated_date_time', help='') c.argument('topic', type=str, help='') c.argument('installed_apps', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('members', action=AddUsersMembers, nargs='+', help='') c.argument('messages', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('tabs', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') with self.argument_context('teams user update-joined-team') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('team_id', type=str, help='key: id of team') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('classification', type=str, help='An optional label. Typically describes the data or business ' 'sensitivity of the team. Must match one of a pre-configured set in the tenant\'s directory.') c.argument('created_date_time', help='') c.argument('description', type=str, help='An optional description for the team.') c.argument('display_name', type=str, help='The name of the team.') c.argument('fun_settings', action=AddFunSettings, nargs='+', help='teamFunSettings') c.argument('guest_settings', action=AddGuestSettings, nargs='+', help='teamGuestSettings') c.argument('internal_id', type=str, help='A unique ID for the team that has been used in a few places such as ' 'the audit log/Office 365 Management Activity API.') c.argument('is_archived', arg_type=get_three_state_flag(), help='Whether this team is in read-only mode.') c.argument('is_membership_limited_to_owners', arg_type=get_three_state_flag(), help='') c.argument('member_settings', action=AddMemberSettings, nargs='+', help='teamMemberSettings') c.argument('messaging_settings', action=AddMessagingSettings, nargs='+', help='teamMessagingSettings') c.argument('specialization', arg_type=get_enum_type(['none', 'educationStandard', 'educationClass', 'educationProfessionalLearningCommunity', 'educationStaff', 'healthcareStandard', 'healthcareCareCoordination', 'unknownFutureValue']), help='') c.argument('visibility', arg_type=get_enum_type(['private', 'public', 'hiddenMembership', 'unknownFutureValue']), help='') c.argument('web_url', type=str, help='A hyperlink that will go to the team in the Microsoft Teams client. This ' 'is the URL that you get when you right-click a team in the Microsoft Teams client and select Get ' 'link to team. This URL should be treated as an opaque blob, and not parsed.') c.argument('channels', type=validate_file_or_dict, help='The collection of channels & messages associated with ' 'the team. Expected value: json-string/@json-file.') c.argument('group', type=validate_file_or_dict, help='Represents an Azure Active Directory object. The ' 'directoryObject type is the base type for many other directory entity types. Expected value: ' 'json-string/@json-file.') c.argument('installed_apps', type=validate_file_or_dict, help='The apps installed in this team. Expected ' 'value: json-string/@json-file.') c.argument('members', action=AddGroupsMembers, nargs='+', help='Members and owners of the team.') c.argument('operations', type=validate_file_or_dict, help='The async operations that ran or are running on ' 'this team. Expected value: json-string/@json-file.') c.argument('owners', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.') c.argument('photo', action=AddGroupsPhoto, nargs='+', help='profilePhoto') c.argument('primary_channel', type=validate_file_or_dict, help='channel Expected value: ' 'json-string/@json-file.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Template') c.argument('id1', type=str, help='Read-only.', arg_group='Schedule') c.argument('enabled', arg_type=get_three_state_flag(), help='Indicates whether the schedule is enabled for the ' 'team. Required.', arg_group='Schedule') c.argument('offer_shift_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether offer ' 'shift requests are enabled for the schedule.', arg_group='Schedule') c.argument('open_shifts_enabled', arg_type=get_three_state_flag(), help='Indicates whether open shifts are ' 'enabled for the schedule.', arg_group='Schedule') c.argument('provision_status', arg_type=get_enum_type(['NotStarted', 'Running', 'Completed', 'Failed']), help='', arg_group='Schedule') c.argument('provision_status_code', type=str, help='Additional information about why schedule provisioning ' 'failed.', arg_group='Schedule') c.argument('swap_shifts_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether swap ' 'shifts requests are enabled for the schedule.', arg_group='Schedule') c.argument('time_clock_enabled', arg_type=get_three_state_flag(), help='Indicates whether time clock is ' 'enabled for the schedule.', arg_group='Schedule') c.argument('time_off_requests_enabled', arg_type=get_three_state_flag(), help='Indicates whether time off ' 'requests are enabled for the schedule.', arg_group='Schedule') c.argument('time_zone', type=str, help='Indicates the time zone of the schedule team using tz database format. ' 'Required.', arg_group='Schedule') c.argument('workforce_integration_ids', nargs='+', help='', arg_group='Schedule') c.argument('offer_shift_requests', action=AddOfferShiftRequests, nargs='+', help='', arg_group='Schedule') c.argument('open_shift_change_requests', action=AddOpenShiftChangeRequests, nargs='+', help='', arg_group='Schedule') c.argument('open_shifts', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Schedule') c.argument('scheduling_groups', action=AddSchedulingGroups, nargs='+', help='The logical grouping of users in ' 'the schedule (usually by role).', arg_group='Schedule') c.argument('shifts', type=validate_file_or_dict, help='The shifts in the schedule. Expected value: ' 'json-string/@json-file.', arg_group='Schedule') c.argument('swap_shifts_change_requests', action=AddSwapShiftsChangeRequests, nargs='+', help='', arg_group='Schedule') c.argument('time_cards', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Schedule') c.argument('time_off_reasons', action=AddTimeOffReasons, nargs='+', help='The set of reasons for a time off in ' 'the schedule.', arg_group='Schedule') c.argument('time_off_requests', action=AddTimeOffRequests, nargs='+', help='', arg_group='Schedule') c.argument('times_off', type=validate_file_or_dict, help='The instances of times off in the schedule. Expected ' 'value: json-string/@json-file.', arg_group='Schedule') c.argument('approved_location', action=AddApprovedLocation, nargs='+', help='geoCoordinates', arg_group='Schedule Time Clock Settings') c.argument('show_in_teams_search_and_suggestions', arg_type=get_three_state_flag(), help='', arg_group='Discovery Settings') with self.argument_context('teams user update-teamwork') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('installed_apps', type=validate_file_or_dict, help='The apps installed in the personal scope of ' 'this user. Expected value: json-string/@json-file.') with self.argument_context('teams user-teamwork create-installed-app') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Teams App Definition') c.argument('azure_ad_app_id', type=str, help='', arg_group='Teams App Definition') c.argument('description', type=str, help='', arg_group='Teams App Definition') c.argument('display_name', type=str, help='The name of the app provided by the app developer.', arg_group='Teams App Definition') c.argument('last_modified_date_time', help='', arg_group='Teams App Definition') c.argument('publishing_state', arg_type=get_enum_type(['submitted', 'rejected', 'published', 'unknownFutureValue']), help='', arg_group='Teams App ' 'Definition') c.argument('shortdescription', type=str, help='', arg_group='Teams App Definition') c.argument('teams_app_id', type=str, help='The ID from the Teams app manifest.', arg_group='Teams App ' 'Definition') c.argument('version', type=str, help='The version number of the application.', arg_group='Teams App Definition') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition ' 'Created By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition ' 'Created By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition Created ' 'By') c.argument('id1', type=str, help='Read-only.', arg_group='Teams App') c.argument('microsoft_graph_teams_app_display_name', type=str, help='The name of the catalog app provided by ' 'the app developer in the Microsoft Teams zip app package.', arg_group='Teams App') c.argument('distribution_method', arg_type=get_enum_type(['store', 'organization', 'sideloaded', 'unknownFutureValue']), help='', arg_group='Teams ' 'App') c.argument('external_id', type=str, help='The ID of the catalog provided by the app developer in the Microsoft ' 'Teams zip app package.', arg_group='Teams App') c.argument('app_definitions', type=validate_file_or_dict, help='The details for each version of the app. ' 'Expected value: json-string/@json-file.', arg_group='Teams App') c.argument('id2', type=str, help='Read-only.', arg_group='Chat') c.argument('created_date_time', help='', arg_group='Chat') c.argument('last_updated_date_time', help='', arg_group='Chat') c.argument('topic', type=str, help='', arg_group='Chat') c.argument('installed_apps', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Chat') c.argument('members', action=AddUsersMembers, nargs='+', help='', arg_group='Chat') c.argument('messages', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Chat') c.argument('tabs', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Chat') with self.argument_context('teams user-teamwork delete-installed-app') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('user_scope_teams_app_installation_id', type=str, help='key: id of userScopeTeamsAppInstallation') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams user-teamwork list-installed-app') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('orderby', nargs='+', help='Order items by property values') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams user-teamwork show-installed-app') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('user_scope_teams_app_installation_id', type=str, help='key: id of userScopeTeamsAppInstallation') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams user-teamwork update-installed-app') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('user_scope_teams_app_installation_id', type=str, help='key: id of userScopeTeamsAppInstallation') c.argument('id_', options_list=['--id'], type=str, help='Read-only.') c.argument('microsoft_graph_entity_id', type=str, help='Read-only.', arg_group='Teams App Definition') c.argument('azure_ad_app_id', type=str, help='', arg_group='Teams App Definition') c.argument('description', type=str, help='', arg_group='Teams App Definition') c.argument('display_name', type=str, help='The name of the app provided by the app developer.', arg_group='Teams App Definition') c.argument('last_modified_date_time', help='', arg_group='Teams App Definition') c.argument('publishing_state', arg_type=get_enum_type(['submitted', 'rejected', 'published', 'unknownFutureValue']), help='', arg_group='Teams App ' 'Definition') c.argument('shortdescription', type=str, help='', arg_group='Teams App Definition') c.argument('teams_app_id', type=str, help='The ID from the Teams app manifest.', arg_group='Teams App ' 'Definition') c.argument('version', type=str, help='The version number of the application.', arg_group='Teams App Definition') c.argument('application', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition ' 'Created By') c.argument('device', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition ' 'Created By') c.argument('user', action=AddApplication, nargs='+', help='identity', arg_group='Teams App Definition Created ' 'By') c.argument('id1', type=str, help='Read-only.', arg_group='Teams App') c.argument('microsoft_graph_teams_app_display_name', type=str, help='The name of the catalog app provided by ' 'the app developer in the Microsoft Teams zip app package.', arg_group='Teams App') c.argument('distribution_method', arg_type=get_enum_type(['store', 'organization', 'sideloaded', 'unknownFutureValue']), help='', arg_group='Teams ' 'App') c.argument('external_id', type=str, help='The ID of the catalog provided by the app developer in the Microsoft ' 'Teams zip app package.', arg_group='Teams App') c.argument('app_definitions', type=validate_file_or_dict, help='The details for each version of the app. ' 'Expected value: json-string/@json-file.', arg_group='Teams App') c.argument('id2', type=str, help='Read-only.', arg_group='Chat') c.argument('created_date_time', help='', arg_group='Chat') c.argument('last_updated_date_time', help='', arg_group='Chat') c.argument('topic', type=str, help='', arg_group='Chat') c.argument('installed_apps', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Chat') c.argument('members', action=AddUsersMembers, nargs='+', help='', arg_group='Chat') c.argument('messages', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Chat') c.argument('tabs', type=validate_file_or_dict, help=' Expected value: json-string/@json-file.', arg_group='Chat') with self.argument_context('teams user-teamwork-installed-app delete-ref-chat') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('user_scope_teams_app_installation_id', type=str, help='key: id of userScopeTeamsAppInstallation') c.argument('if_match', type=str, help='ETag') with self.argument_context('teams user-teamwork-installed-app set-ref-chat') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('user_scope_teams_app_installation_id', type=str, help='key: id of userScopeTeamsAppInstallation') c.argument('body', type=validate_file_or_dict, help='New navigation property ref values Expected value: ' 'json-string/@json-file.') with self.argument_context('teams user-teamwork-installed-app show-chat') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('user_scope_teams_app_installation_id', type=str, help='key: id of userScopeTeamsAppInstallation') c.argument('select', nargs='+', help='Select properties to be returned') c.argument('expand', nargs='+', help='Expand related entities') with self.argument_context('teams user-teamwork-installed-app show-ref-chat') as c: c.argument('user_id', type=str, help='key: id of user') c.argument('user_scope_teams_app_installation_id', type=str, help='key: id of userScopeTeamsAppInstallation')

78.145755

121

0.634702

39,453

312,036

4.885357

0.019644

0.1116

0.062036

0.049102

0.990531

0.989924

0.988679

0.985364

0.98444

0.982718

0

0.005158

0.228877

312,036

3,992

122

78.165331

0.795822

0.001622

0

0.893565

0

0.001629

0.444262

0.069529

0

1

0.000272

false

0

0.004073

0

0.004344

0

null

0

1

0

1

0

null

0

7

f0c090de85dddfbd20c171ef4711b116d67361f2

1,405

py

Python

problems/8.py

christofferaakre/project-euler

4b42802233be10e4a592798205171fb5156dae6b

[ "MIT" ]

null

problems/8.py

christofferaakre/project-euler

4b42802233be10e4a592798205171fb5156dae6b

[ "MIT" ]

null

problems/8.py

christofferaakre/project-euler

4b42802233be10e4a592798205171fb5156dae6b

[ "MIT" ]

null

from main import Solver solver = Solver() input = "7316717653133062491922511967442657474235534919493496983520312774506326239578318016984801869478851843858615607891129494954595017379583319528532088055111254069874715852386305071569329096329522744304355766896648950445244523161731856403098711121722383113622298934233803081353362766142828064444866452387493035890729629049156044077239071381051585930796086670172427121883998797908792274921901699720888093776657273330010533678812202354218097512545405947522435258490771167055601360483958644670632441572215539753697817977846174064955149290862569321978468622482839722413756570560574902614079729686524145351004748216637048440319989000889524345065854122758866688116427171479924442928230863465674813919123162824586178664583591245665294765456828489128831426076900422421902267105562632111110937054421750694165896040807198403850962455444362981230987879927244284909188845801561660979191338754992005240636899125607176060588611646710940507754100225698315520005593572972571636269561882670428252483600823257530420752963450" def biggest_product_of_adjacents(n): biggest_product = 1 for i in range(0, len(input) - n - 1): product = 1 for j in range(i, i + n): product *= int(input[j]) if product > biggest_product: biggest_product = product return biggest_product solver.solve(8, biggest_product_of_adjacents(13))

78.055556

1,010

0.892527

57

1,405

21.824561

0.45614

0.067524

0.025723

0.040193

0

0.778809

0.079715

1,405

17

1,011

82.647059

0.183295

0

0.711744

0

1

0

1

0.076923

false

0

0.076923

0

0.230769

0

1

null

0

1

0

1

0

1

0

1

null

1

0

7

9bf4f1a9d6c6af5fe92f6425bc9d18a9d42a8c72

37,472

py

Python

tests/test_control.py

madkote/fastapi-plugins

04d251c4c88317e1c8f35dad66771020dcb35112

[ "MIT" ]

211

2019-11-20T11:19:44.000Z

2022-03-28T08:43:27.000Z

tests/test_control.py

madkote/fastapi-plugins

04d251c4c88317e1c8f35dad66771020dcb35112

[ "MIT" ]

16

2020-01-24T14:31:30.000Z

2021-09-23T10:27:39.000Z

tests/test_control.py

madkote/fastapi-plugins

04d251c4c88317e1c8f35dad66771020dcb35112

[ "MIT" ]

12

2020-07-25T14:33:46.000Z

2022-01-11T06:42:32.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- # tests.test_control ''' :author: madkote :contact: madkote(at)bluewin.ch :copyright: Copyright 2021, madkote RES tests.test_control ------------------ Control plugin tests ''' from __future__ import absolute_import import asyncio import typing import unittest import fastapi import pydantic import pytest import starlette.testclient import fastapi_plugins from fastapi_plugins.memcached import memcached_plugin from fastapi_plugins.memcached import MemcachedSettings from . import VERSION from . import d2json __all__ = [] __author__ = 'madkote <madkote(at)bluewin.ch>' __version__ = '.'.join(str(x) for x in VERSION) __copyright__ = 'Copyright 2021, madkote RES' class DummyPluginHealthOK( fastapi_plugins.Plugin, fastapi_plugins.ControlHealthMixin ): async def init_app( self, app: fastapi.FastAPI, config: pydantic.BaseSettings=None, # @UnusedVariable *args, # @UnusedVariable **kwargs # @UnusedVariable ) -> None: app.state.DUMMY_PLUGIN_HEALTH_OK = self async def health(self) -> typing.Dict: return dict(dummy='OK') class DummyPluginHealthOKOnce( fastapi_plugins.Plugin, fastapi_plugins.ControlHealthMixin ): async def init_app( self, app: fastapi.FastAPI, config: pydantic.BaseSettings=None, # @UnusedVariable *args, # @UnusedVariable **kwargs # @UnusedVariable ) -> None: self.counter = 0 app.state.DUMMY_PLUGIN_HEALTH_OK_ONCE = self async def health(self) -> typing.Dict: if self.counter > 0: raise Exception('Health check failed') else: self.counter += 1 return dict(dummy='OK') class DummyPluginHealthFail( fastapi_plugins.Plugin, fastapi_plugins.ControlHealthMixin ): async def init_app( self, app: fastapi.FastAPI, config: pydantic.BaseSettings=None, # @UnusedVariable *args, # @UnusedVariable **kwargs # @UnusedVariable ) -> None: app.state.DUMMY_PLUGIN_HEALTH_FAIL = self async def health(self) -> typing.Dict: raise Exception('Health check failed') class DummyPluginHealthNotDefined( fastapi_plugins.Plugin, fastapi_plugins.ControlHealthMixin ): async def init_app( self, app: fastapi.FastAPI, config: pydantic.BaseSettings=None, # @UnusedVariable *args, # @UnusedVariable **kwargs # @UnusedVariable ) -> None: app.state.DUMMY_PLUGIN_NOT_DEFINED = self @pytest.mark.control class ControlTest(unittest.TestCase): def setUp(self): pass def tearDown(self): pass def make_app(self, config=None, version=None, environ=None, plugins=None): if plugins is None: plugins = [] app = fastapi_plugins.register_middleware(fastapi.FastAPI()) if config is None: config = fastapi_plugins.ControlSettings() @app.on_event('startup') async def on_startup() -> None: for p in plugins: await p.init_app(app, config) await p.init() kwargs = {} if version: kwargs.update(**dict(version=version)) if environ: kwargs.update(**dict(environ=environ)) await fastapi_plugins.control_plugin.init_app(app, config, **kwargs) # noqa E501 await fastapi_plugins.control_plugin.init() @app.on_event('shutdown') async def on_shutdown() -> None: await fastapi_plugins.control_plugin.terminate() for p in plugins: await p.terminate() return app # ========================================================================= # CONTROLLER # ========================================================================= def test_controller_environ(self): async def _test(): c = fastapi_plugins.Controller() res = await c.get_environ() exp = {} self.assertTrue(d2json(exp) == d2json(res), 'environ failed') event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) coro = asyncio.coroutine(_test) event_loop.run_until_complete(coro()) event_loop.close() def test_controller_environ_custom(self): async def _test(): exp = dict(ping='pong') c = fastapi_plugins.Controller(environ=exp) res = await c.get_environ() self.assertTrue(d2json(exp) == d2json(res), 'environ failed') event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) coro = asyncio.coroutine(_test) event_loop.run_until_complete(coro()) event_loop.close() def test_controller_health(self): async def _test(): c = fastapi_plugins.Controller() exp = dict(status=True, checks=[]) res = (await c.get_health()).dict() self.assertTrue( d2json(exp) == d2json(res), 'health failed: %s != %s' % (exp, res) ) event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) coro = asyncio.coroutine(_test) event_loop.run_until_complete(coro()) event_loop.close() def test_controller_health_plugin_ok(self): async def _test(): app = fastapi_plugins.register_middleware(fastapi.FastAPI()) config = fastapi_plugins.ControlSettings() dummy = DummyPluginHealthOK() await dummy.init_app(app, config) await dummy.init() try: c = fastapi_plugins.Controller() c.plugins.append(('DUMMY_PLUGIN_OK', dummy)) exp = dict( status=True, checks=[ dict( name='DUMMY_PLUGIN_OK', status=True, details=dict(dummy='OK') ) ] ) res = (await c.get_health()).dict() self.assertTrue( d2json(exp) == d2json(res), 'health failed: %s != %s' % (exp, res) ) finally: await dummy.terminate() event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) coro = asyncio.coroutine(_test) event_loop.run_until_complete(coro()) event_loop.close() def test_controller_health_plugin_notdefined(self): async def _test(): app = fastapi_plugins.register_middleware(fastapi.FastAPI()) config = fastapi_plugins.ControlSettings() dummy = DummyPluginHealthNotDefined() await dummy.init_app(app, config) await dummy.init() try: c = fastapi_plugins.Controller() c.plugins.append(('DUMMY_PLUGIN_NOT_DEFINED', dummy)) exp = dict( status=True, checks=[ dict( name='DUMMY_PLUGIN_NOT_DEFINED', status=True, details={} ) ] ) res = (await c.get_health()).dict() self.assertTrue( d2json(exp) == d2json(res), 'health failed: %s != %s' % (exp, res) ) finally: await dummy.terminate() event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) coro = asyncio.coroutine(_test) event_loop.run_until_complete(coro()) event_loop.close() def test_controller_health_plugin_failing(self): async def _test(): app = fastapi_plugins.register_middleware(fastapi.FastAPI()) config = fastapi_plugins.ControlSettings() dummy = DummyPluginHealthFail() await dummy.init_app(app, config) await dummy.init() try: c = fastapi_plugins.Controller() c.plugins.append(('DUMMY_PLUGIN_HEALTH_FAIL', dummy)) exp = dict( status=False, checks=[ dict( name='DUMMY_PLUGIN_HEALTH_FAIL', status=False, details=dict(error='Health check failed') ) ] ) res = (await c.get_health()).dict() self.assertTrue( d2json(exp) == d2json(res), 'health failed: %s != %s' % (exp, res) ) finally: await dummy.terminate() event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) coro = asyncio.coroutine(_test) event_loop.run_until_complete(coro()) event_loop.close() def test_controller_heartbeat(self): async def _test(): c = fastapi_plugins.Controller() exp = True res = await c.get_heart_beat() self.assertTrue( exp == res, 'heart beat failed: %s != %s' % (exp, res) ) event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) coro = asyncio.coroutine(_test) event_loop.run_until_complete(coro()) event_loop.close() def test_controller_version(self): async def _test(): from fastapi_plugins.control import DEFAULT_CONTROL_VERSION c = fastapi_plugins.Controller() r = await c.get_version() self.assertTrue(r == DEFAULT_CONTROL_VERSION, 'version failed') event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) coro = asyncio.coroutine(_test) event_loop.run_until_complete(coro()) event_loop.close() def test_controller_version_custom(self): async def _test(): v = '1.2.3' c = fastapi_plugins.Controller(version=v) r = await c.get_version() self.assertTrue(r == v, 'version failed') event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) coro = asyncio.coroutine(_test) event_loop.run_until_complete(coro()) event_loop.close() # ========================================================================= # ROUTER # ========================================================================= def test_router_environ(self): event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) try: client = starlette.testclient.TestClient(self.make_app()) with client as c: endpoint = '/control/environ' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = dict(environ={}) res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 finally: event_loop.close() def test_router_environ_custom(self): myenviron = dict(ping='pong') event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) try: client = starlette.testclient.TestClient( self.make_app(environ=myenviron) ) with client as c: endpoint = '/control/environ' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = dict(environ=myenviron) res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 finally: event_loop.close() def test_router_version(self): from fastapi_plugins.control import DEFAULT_CONTROL_VERSION event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) try: client = starlette.testclient.TestClient(self.make_app()) with client as c: endpoint = '/control/version' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = {'version': DEFAULT_CONTROL_VERSION} res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 finally: event_loop.close() def test_router_version_custom(self): myversion = '1.2.3' event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) try: client = starlette.testclient.TestClient( self.make_app(version=myversion) ) with client as c: endpoint = '/control/version' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = {'version': myversion} res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 finally: event_loop.close() def test_router_heartbeat(self): event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) try: client = starlette.testclient.TestClient( self.make_app() ) with client as c: endpoint = '/control/heartbeat' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = dict(is_alive=True) res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 finally: event_loop.close() def test_router_health(self): event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) try: client = starlette.testclient.TestClient( self.make_app() ) with client as c: endpoint = '/control/health' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = dict(status=True, checks=[]) res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 finally: event_loop.close() def test_router_health_with_plugins(self): event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) try: client = starlette.testclient.TestClient( self.make_app( plugins=[ DummyPluginHealthNotDefined(), DummyPluginHealthOK() ] ) ) with client as c: endpoint = '/control/health' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = dict( status=True, checks=[ dict( name='DUMMY_PLUGIN_NOT_DEFINED', status=True, details={} ), dict( name='DUMMY_PLUGIN_HEALTH_OK', status=True, details=dict(dummy='OK') ) ] ) res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 finally: event_loop.close() def test_router_health_with_plugins_full(self): event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) try: class MyConfig( fastapi_plugins.RedisSettings, fastapi_plugins.SchedulerSettings, fastapi_plugins.ControlSettings, MemcachedSettings ): pass client = starlette.testclient.TestClient( self.make_app( config=MyConfig(), plugins=[ fastapi_plugins.redis_plugin, fastapi_plugins.scheduler_plugin, memcached_plugin ] ) ) with client as c: endpoint = '/control/health' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = dict( status=True, checks=[ { 'name': 'REDIS', 'status': True, 'details': { 'redis_type': 'redis', 'redis_address': 'redis://localhost:6379/0', 'redis_pong': 'PONG' } }, { 'name': 'AIOJOBS_SCHEDULER', 'status': True, 'details': { 'jobs': 0, 'active': 0, 'pending': 0, 'limit': 100, 'closed': False } }, { 'name': 'MEMCACHED', 'status': True, 'details': { 'host': 'localhost', 'port': 11211, 'version': '1.6.9' } } ] ) res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 finally: event_loop.close() def test_router_health_with_plugins_broken(self): event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) try: client = starlette.testclient.TestClient( self.make_app( plugins=[ DummyPluginHealthNotDefined(), DummyPluginHealthOK(), DummyPluginHealthOKOnce() ] ) ) with client as c: endpoint = '/control/health' response = c.get(endpoint) exp = 417 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = { 'detail': { 'status': False, 'checks': [ { 'name': 'DUMMY_PLUGIN_NOT_DEFINED', 'status': True, 'details': {} }, { 'name': 'DUMMY_PLUGIN_HEALTH_OK', 'status': True, 'details': {'dummy': 'OK'} }, { 'name': 'DUMMY_PLUGIN_HEALTH_OK_ONCE', 'status': False, 'details': {'error': 'Health check failed'} } ] } } res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 finally: event_loop.close() def test_router_health_with_plugins_broken_init(self): event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) try: client = starlette.testclient.TestClient( self.make_app( plugins=[ DummyPluginHealthFail(), DummyPluginHealthOK() ] ) ) try: with client as c: endpoint = '/control/version' c.get(endpoint) except fastapi_plugins.ControlError: pass else: self.fail('health on app initialization should fail') finally: event_loop.close() def test_router_prefix_custom(self): from fastapi_plugins.control import DEFAULT_CONTROL_VERSION event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) try: config = fastapi_plugins.ControlSettings( control_router_prefix='outofcontrol' ) client = starlette.testclient.TestClient( self.make_app(config=config) ) with client as c: # endpoint = '/%s/health' % config.control_router_prefix response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = dict(status=True, checks=[]) res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 # endpoint = '/%s/version' % config.control_router_prefix response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = {'version': DEFAULT_CONTROL_VERSION} res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 finally: event_loop.close() def test_router_prefix_version_custom(self): event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) try: myversion = '3.2.1' config = fastapi_plugins.ControlSettings( control_router_prefix='outofcontrol' ) client = starlette.testclient.TestClient( self.make_app(config=config, version=myversion) ) with client as c: # endpoint = '/%s/health' % config.control_router_prefix response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = dict(status=True, checks=[]) res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 # endpoint = '/%s/version' % config.control_router_prefix response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = {'version': myversion} res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 finally: event_loop.close() def test_router_disable(self): event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) try: config = fastapi_plugins.ControlSettings( control_enable_environ=False, control_enable_health=False, control_enable_heartbeat=False, control_enable_version=False ) client = starlette.testclient.TestClient( self.make_app(config=config) ) with client as c: # endpoint = '/control/environ' response = c.get(endpoint) exp = 404 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 # endpoint = '/control/version' response = c.get(endpoint) exp = 404 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 # endpoint = '/control/heartbeat' response = c.get(endpoint) exp = 404 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 # endpoint = '/control/health' response = c.get(endpoint) exp = 404 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 finally: event_loop.close() def test_router_disable_environ(self): event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) try: from fastapi_plugins.control import DEFAULT_CONTROL_VERSION config = fastapi_plugins.ControlSettings( control_enable_environ=False, control_enable_health=True, control_enable_heartbeat=True, control_enable_version=True ) client = starlette.testclient.TestClient( self.make_app(config=config) ) with client as c: # endpoint = '/control/environ' response = c.get(endpoint) exp = 404 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 # endpoint = '/control/version' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = {'version': DEFAULT_CONTROL_VERSION} res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 # endpoint = '/control/heartbeat' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = {'is_alive': True} res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 # endpoint = '/control/health' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = dict(status=True, checks=[]) res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 finally: event_loop.close() def test_router_disable_version(self): event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) try: config = fastapi_plugins.ControlSettings( control_enable_environ=True, control_enable_heartbeat=True, control_enable_health=True, control_enable_version=False ) client = starlette.testclient.TestClient( self.make_app(config=config) ) with client as c: # endpoint = '/control/environ' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = dict(environ={}) res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 # endpoint = '/control/version' response = c.get(endpoint) exp = 404 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 # endpoint = '/control/heartbeat' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = {'is_alive': True} res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 # endpoint = '/control/health' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = dict(status=True, checks=[]) res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 finally: event_loop.close() def test_router_disable_health(self): event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) try: from fastapi_plugins.control import DEFAULT_CONTROL_VERSION config = fastapi_plugins.ControlSettings( control_enable_environ=True, control_enable_health=False, control_enable_heartbeat=True, control_enable_version=True ) client = starlette.testclient.TestClient( self.make_app(config=config, plugins=[DummyPluginHealthFail()]) ) with client as c: # endpoint = '/control/environ' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = dict(environ={}) res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 # endpoint = '/control/version' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = {'version': DEFAULT_CONTROL_VERSION} res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 # endpoint = '/control/heartbeat' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = {'is_alive': True} res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 # endpoint = '/control/health' response = c.get(endpoint) exp = 404 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 finally: event_loop.close() def test_router_disable_heartbeat(self): event_loop = asyncio.new_event_loop() asyncio.set_event_loop(event_loop) try: from fastapi_plugins.control import DEFAULT_CONTROL_VERSION config = fastapi_plugins.ControlSettings( control_enable_environ=True, control_enable_health=True, control_enable_heartbeat=False, control_enable_version=True ) client = starlette.testclient.TestClient( self.make_app(config=config) ) with client as c: # endpoint = '/control/environ' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = dict(environ={}) res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 # endpoint = '/control/version' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = {'version': DEFAULT_CONTROL_VERSION} res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 # endpoint = '/control/heartbeat' response = c.get(endpoint) exp = 404 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 # endpoint = '/control/health' response = c.get(endpoint) exp = 200 res = response.status_code self.assertTrue(exp == res, '[%s] status code : %s != %s' % (endpoint, exp, res)) # noqa E501 exp = dict(status=True, checks=[]) res = response.json() self.assertTrue(d2json(exp) == d2json(res), '[%s] json : %s != %s' % (endpoint, exp, res)) # noqa E501 finally: event_loop.close() if __name__ == "__main__": # import sys;sys.argv = ['', 'Test.testName'] unittest.main()

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0

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1

0

1

0

null

0

7

50513c49e9384ee8374c93257bda92f350682b4b

317

py

Python

SimCalorimetry/HGCalSimProducers/python/hgcHitAssociation_cfi.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

852

2015-01-11T21:03:51.000Z

2022-03-25T21:14:00.000Z

SimCalorimetry/HGCalSimProducers/python/hgcHitAssociation_cfi.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

30,371

2015-01-02T00:14:40.000Z

2022-03-31T23:26:05.000Z

SimCalorimetry/HGCalSimProducers/python/hgcHitAssociation_cfi.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

3,240

2015-01-02T05:53:18.000Z

2022-03-31T17:24:21.000Z

from SimCalorimetry.HGCalAssociatorProducers.layerClusterAssociatorByEnergyScore_cfi import layerClusterAssociatorByEnergyScore as lcAssocByEnergyScoreProducer from SimCalorimetry.HGCalAssociatorProducers.simClusterAssociatorByEnergyScore_cfi import simClusterAssociatorByEnergyScore as scAssocByEnergyScoreProducer

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null

0

1

0

1

0

1

0

8

505aa41c67cd2ed4b63a6e36f75de2f82d28a41f

1,337

py

Python

accounts/urls.py

Alwin1847207/Hackathon

473adea12822cbe2be9a7525ac29391659f0ab6b

[ "bzip2-1.0.6" ]

null

accounts/urls.py

Alwin1847207/Hackathon

473adea12822cbe2be9a7525ac29391659f0ab6b

[ "bzip2-1.0.6" ]

null

accounts/urls.py

Alwin1847207/Hackathon

473adea12822cbe2be9a7525ac29391659f0ab6b

[ "bzip2-1.0.6" ]

null

from django.urls import path, include from accounts import views urlpatterns = [ path('', views.indx, name='accounts'), <<<<<<< HEAD path('/signup', views.signup, name='signup'), path('logout', views.logout, name='logout'), path('/login', views.loginn, name='login'), path('/usertpe/<int:pk>/', views.usertype, name='usertpe/'), path('/userSelection/<int:id>', views.UserSelection, name='userSelection'), path('dashboard', views.dashboard, name='dashboard'), path('/organiser', include('Organizer.urls'), name='organiserIndex'), path('/sponsor', include('Sponsor.urls'), name='sponsorIndex'), path('/participant/', include('Participant.urls'), name='participantIndex'), ======= path('signup', views.signup, name='signup'), path('logout', views.logout, name='logout'), path('login', views.loginn, name='login'), path('usertpe/<int:pk>/', views.usertype, name='usertpe/'), path('userSelection/<int:id>', views.UserSelection, name='userSelection'), path('dashboard', views.dashboard, name='dashboard'), path('organiser', include('Organizer.urls'), name='organiserIndex'), path('sponsor', include('Sponsor.urls'), name='sponsorIndex'), path('participant/', include('Participant.urls'), name='participantIndex'), >>>>>>> 00486efd62bd717f2eaff3e6c9f80a737c54bef9 ]

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null

0

null

0

1

0

null

0

1

0

7

aca13ddd1f522190f254afaf3832df6b06bbc2a3

452

py

Python

webdjango/signals/WebDjangoSignals.py

myog-io/WebDjangular

73d3c40aa449eec5acc59d4493ee94059bddabbd

[ "MIT" ]

1

2018-09-14T15:17:19.000Z

webdjango/signals/WebDjangoSignals.py

MyOwnGamesLLC/WebDjangular

73d3c40aa449eec5acc59d4493ee94059bddabbd

[ "MIT" ]

41

2018-12-16T16:58:54.000Z

2019-02-22T20:08:58.000Z

webdjango/signals/WebDjangoSignals.py

myog-io/WebDjangular

73d3c40aa449eec5acc59d4493ee94059bddabbd

[ "MIT" ]

1

2019-12-10T09:32:49.000Z

from django.dispatch import Signal pre_init_serializer = Signal( providing_args=["serializer", "args", "kwargs"], use_caching=True ) post_init_serializer = Signal( providing_args=["serializer", "args", "kwargs"], use_caching=True ) pre_init_filter = Signal( providing_args=["serializer", "args", "kwargs"], use_caching=True ) post_init_filter = Signal( providing_args=["serializer", "args", "kwargs"], use_caching=True )

30.133333

70

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452

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0.25

0.381579

0.881579

0

0.14823

452

14

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32.285714

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0.076923

0

null

0

1

0

null

0

8

acae396920d61d3600aee2e70255b3f5aee64288

52,628

py

Python

custompackage/.ipynb_checkpoints/load_architecture-checkpoint.py

ilennaj/ktree_constraints

2a25e93c9b4f113caf633b08abb3e48e1c566c59

[ "CC0-1.0" ]

4

2021-03-11T21:46:41.000Z

2021-12-01T06:32:42.000Z

custompackage/.ipynb_checkpoints/load_architecture-checkpoint.py

ilennaj/ktree_constraints

2a25e93c9b4f113caf633b08abb3e48e1c566c59

[ "CC0-1.0" ]

null

custompackage/.ipynb_checkpoints/load_architecture-checkpoint.py

ilennaj/ktree_constraints

2a25e93c9b4f113caf633b08abb3e48e1c566c59

[ "CC0-1.0" ]

1

2021-08-12T19:32:37.000Z

import torch import torch.nn as nn from torch.nn.parameter import Parameter import custompackage.sl_custom as slc from torch import Tensor from torch.nn.init import xavier_uniform_ from torch.nn.init import constant_ from torch.nn.init import xavier_normal_ from torch.nn.parameter import Parameter from torch.nn import Module from torch import functional as F import numpy as np import math def kronecker(matrix1, matrix2): return torch.ger(matrix1.view(-1), matrix2.view(-1)).reshape(*(matrix1.size() + matrix2.size())).permute([0, 2, 1, 3]).reshape(matrix1.size(0) * matrix2.size(0), matrix1.size(1) * matrix2.size(1)) class NCK(nn.Module): def __init__(self, alpha=1, beta=0.6, gamma=1, learn=True, scale=1): super(NCK, self).__init__() if learn: self.alpha = Parameter(torch.tensor([float(alpha)]).requires_grad_()) # create a tensor out of alpha self.beta = Parameter(torch.tensor([float(beta)]).requires_grad_()) # create a tensor out of beta self.gamma = Parameter(torch.tensor([float(gamma)]).requires_grad_()) # create a tensor out of gamma else: self.alpha = alpha self.beta = beta self.gamma = gamma self.scale = scale def forward(self, x): return(self.alpha*self.f_Na(x) + self.beta*self.f_Ca(x) + self.gamma*self.f_K(x)) def f_Na(self, x, a=0.0878, b=113.68, c=6.39, d=8.98): x = x*self.scale return(a*(x-b)/(1+torch.exp((c - x/d)))) def f_Ca(self, x, a=0.129, b=69.62, c=-4.40, d=4.25): x = x*self.scale return(a*(x-b)/(1+torch.exp((c - x/d)))) def f_K (self, x, a=2.23, b=0.132, c=16.74, d=0.436): x = x*self.scale return(a/(d+torch.exp(-b*(x-c)))) class SQGL(nn.Module): def __init__(self, alpha=1, beta=0.6, gamma=1, learn=True, scale=1, atten=1, linscale=1): super(SQGL, self).__init__() self.learn = learn if learn: self.alpha = Parameter(torch.tensor([float(alpha)]).requires_grad_()) # create a tensor out of alpha self.beta = Parameter(torch.tensor([float(beta)]).requires_grad_()) # create a tensor out of beta self.gamma = Parameter(torch.tensor([float(gamma)]).requires_grad_()) # create a tensor out of gamma else: self.alpha = alpha self.beta = beta self.gamma = gamma self.scale = scale self.atten = atten self.linscale = linscale def forward(self, x): if self.learn: self.alpha.data = torch.abs(self.alpha.data) self.beta.data = torch.abs(self.beta.data) self.gamma.data = torch.abs(self.gamma.data) I_ion = self.alpha*self.f_Na(x) + self.beta*self.f_Ca(x) + self.gamma*self.f_K(x) return((x*self.linscale + I_ion)*self.atten) #Attenuation 0.5 def f_Na(self, x, a=0.0878, b=113.68, c=6.39, d=8.98): x = x*self.scale return(-a*(x-b)/(1+torch.exp((c - x/d).clamp(-60, 60)))) def f_Ca(self, x, a=0.129, b=69.62, c=-4.40, d=4.25): x = x*self.scale return(-a*(x-b)/(1+torch.exp((c - x/d).clamp(-60, 60)))) def f_K (self, x, a=2.23, b=0.132, c=16.74, d=0.436): x = x*self.scale return(-a/(d+torch.exp((-b*(x-c)).clamp(-60, 60)))) class Synapse(nn.Module): def __init__(self, in_features: int, Ep = 50, Em = -70, E0 = -65, learn: bool = True): super(Synapse, self).__init__() self.in_features = in_features # Note: Find reversal potential sources or choose new reversal potentials self.Ep = Ep self.Em = Em self.E0 = E0 self.learn = learn # Initialize presynaptic activation dynamics(a1) and synapse size (a2, weights) self.register_parameter('ap1', Parameter(torch.Tensor(1, in_features))) self.register_parameter('ap2', Parameter(torch.Tensor(1, in_features))) self.register_parameter('am1', Parameter(torch.Tensor(1, in_features))) self.register_parameter('am2', Parameter(torch.Tensor(1, in_features))) self.register_parameter('g0', Parameter(torch.Tensor(1, in_features))) torch.nn.init.normal_(self.ap1, mean=0.0, std=math.sqrt(2/(self.ap1.shape[1]))) torch.nn.init.normal_(self.ap2, mean=0.0, std=math.sqrt(2/(self.ap2.shape[1]))) torch.nn.init.normal_(self.am1, mean=0.0, std=math.sqrt(2/(self.am1.shape[1]))) torch.nn.init.normal_(self.am2, mean=0.0, std=math.sqrt(2/(self.am2.shape[1]))) torch.nn.init.normal_(self.g0, mean=0.0, std=math.sqrt(2/(self.g0.shape[1]))) def forward(self, x): top = self.g_n(x, self.ap1, self.ap2) * self.Ep + self.g_n(x, self.am1, self.am2) * self.Em + self.g0*self.E0 bottom = self.g_n(x, self.ap1, self.ap2) + self.g_n(x, self.am1, self.am2) + self.g0 # Should I assume 1/R ~= 0? return(top / bottom) def g_n(self, x, a1, a2): return(torch.exp((a1 * x + a2).clamp(-60, 60))) class F_Na(nn.Module): def __init__(self, scale=1): super(F_Na, self).__init__() self.scale = scale def forward(self, x, a=0.0878, b=113.68, c=6.39, d=8.98): x = x*self.scale return(-a*(x-b)/(1+torch.exp((c - x/d).clamp(-60, 60)))) class F_Ca(nn.Module): def __init__(self, scale=1): super(F_Ca, self).__init__() self.scale = scale def forward(self, x, a=0.129, b=69.62, c=-4.40, d=4.25): x = x*self.scale return(-a*(x-b)/(1+torch.exp((c - x/d).clamp(-60, 60)))) class F_K(nn.Module): def __init__(self, scale=1): super(F_K, self).__init__() self.scale = scale def forward(self, x, a=2.23, b=0.132, c=16.74, d=0.436): x = x*self.scale return(-a/(d+torch.exp((-b*(x-c)).clamp(-60, 60)))) class Hinge_loss(nn.Module): def __init__(self, margin = 1, reduction='mean'): super(Hinge_loss, self).__init__() self.margin = margin self.reduction = reduction def forward(self, y, target): if self.reduction == 'sum': return(torch.sum(torch.max(torch.Tensor([0]).cuda(), self.margin - y*target))) elif self.reduction == 'mean': return(torch.mean(torch.max(torch.Tensor([0]).cuda(), self.margin - y*target))) else: return(torch.max(torch.Tensor([0]).cuda(), self.margin - y*target)) class simple_fcnn(nn.Module): ''' 2 layer feed forward neural network. Will use leaky ReLU activation functions. Activation = {'relu', 'linear','nck','sqgl'} ''' def __init__(self, Input_size=3072, Hidden_size=3072, Output_size=1, Activation="relu", alpha=1, beta=0.6, gamma=1, learn=True, scale=1, atten=1, leak=0.01): super(simple_fcnn, self).__init__() ''' Inputs: Input_size, Hidden_size, Output_size, Activation ''' # Initialize architecture parameters self.Input_size = Input_size self.Hidden_size = Hidden_size self.Output_size = Output_size self.Activation = Activation self.learn = learn self.scale = scale self.atten = atten self.leak = leak # Initialize weights through He initialization (by default in nn.Linear) self.i2h = nn.Linear(Input_size, Hidden_size, bias=True) self.i2h.bias = torch.nn.Parameter(torch.zeros_like(self.i2h.bias)) # self.i2h.weight = torch.nn.init.normal_(self.i2h.weight, mean=0.0, std=math.sqrt(2/(Input_size))) self.i2h.weight = torch.nn.init.kaiming_normal_(self.i2h.weight, a=0.01) # Initialize densly connected output layer self.h2o = nn.Linear(Hidden_size, Output_size) self.h2o.bias = torch.nn.Parameter(torch.zeros_like(self.h2o.bias)) self.h2o.weight = torch.nn.init.kaiming_normal_(self.h2o.weight, a=0.01) # Initialize nonlinearities self.relu = nn.LeakyReLU(negative_slope=self.leak) self.sigmoid = nn.Sigmoid() if Activation=='nck': self.nck = NCK(alpha, beta, gamma, learn=self.learn, scale=self.scale) if Activation=='sqgl': self.sqgl = SQGL(alpha, beta, gamma, learn=self.learn, scale=self.scale, atten=self.atten) def forward(self, x): ''' Forward step for network. Establishes Architecture. Inputs: Input Outputs: Output ''' # Prepare input for appropriate architecture # Set Activation function to calculate hidden layer if self.Activation == 'relu': Hidden = self.relu(self.i2h(x)) elif self.Activation == 'nck': Hidden = self.nck(self.i2h(x)) elif self.Activation == 'sqgl': Hidden = self.sqgl(self.i2h(x)) else: Hidden = self.i2h(x) # Calculate Output layer # Output = self.sigmoid(self.h2o(Hidden)) Output = self.h2o(Hidden) return(Output) class ktree_gen(nn.Module): ''' k-Tree neural network ''' def __init__(self, ds='mnist', Activation="relu", Sparse=True, Input_order=None, Repeats=1, Padded=False, alpha=1, beta=0.6, gamma=1, learn=True, scale=1, atten=1): super(ktree_gen, self).__init__() ''' Inputs: ds (dataset), activation, sparse, input_order, repeats, padded ''' # Initialize architecture parameters self.ds = ds self.Activation = Activation self.Sparse = Sparse self.Input_order = Input_order self.Repeats = Repeats self.learn = learn self.scale = scale self.atten = atten # Initialize weights # Set biases to 0 # Set kaiming initialize weights with gain to correct for sparsity # Set freeze masks #Specify tree dimensions # If using 28x28 datasets... if (ds == 'mnist') or (ds == 'fmnist') or (ds == 'kmnist') or (ds == 'emnist'): # If padded, use 1024 sized tree, completely binary tree if Padded: self.k = [1024, 512, 256, 128, 64, 32, 16, 8, 4, 2, 1] # If not padded, use 784 sized tree, # 7:1 between layers 1 and 2, and layers 2 and 3 else: self.k = [784, 112, 16, 8, 4, 2, 1] # If using 3x32x32 datasets... elif (ds == 'svhn') or (ds == 'cifar10'): # Use 3072 sized tree # 3:1 between layers 1 and 2, otherwise binary self.k = [3072, 1024, 512, 256, 128, 64, 32, 16, 8, 4, 2, 1] # If using 16x16 datasets... elif ds == 'usps': # Use 256 sized tree self.k = [256, 128, 64, 32, 16, 8, 4, 2, 1] else: print('Select a dataset') return(None) # Make layers of tree architecture # Name each layer in each subtree for reference later self.names = np.empty((self.Repeats, len(self.k)-1),dtype=object) # Initialize freeze mask for use in training loop self.freeze_mask_set = [] # For each repeat or subtree, make a sparse layer that is initialized correctly for j in range(self.Repeats): # For each layer within each subtree for i in range(len(self.k)-1): # Assign name of the layer, indexed by layer (i) and subtree (j) name = ''.join(['w',str(j),'_',str(i)]) # Initialize the layer with the appropriate name self.add_module(name, nn.Linear(self.k[i],self.k[i+1])) # Set bias of layer to zeros self._modules[name].bias = nn.Parameter(torch.zeros_like(self._modules[name].bias)) # Use custom method to re-initialize the layer weights and create freeze mask for that layer self._modules[name].weight.data, freeze_mask = self.initialize(self._modules[name]) # Add the layer name to the list of names self.names[j,i] = name # Set the freeze mask for the first subtree, which should be the same for all subtrees if j < 1: self.freeze_mask_set.append(freeze_mask) # Initialize root node, aka soma node aka output node self.root = nn.Linear(Repeats, 1) # Initialize nonlinearities self.relu = nn.LeakyReLU() self.sigmoid = nn.Sigmoid() self.nck = NCK(alpha, beta, gamma, learn=self.learn, scale=self.scale) self.sqgl = SQGL(alpha, beta, gamma, learn=self.learn, scale=self.scale, atten=self.atten) def forward(self, x): ''' Forward step for network. Establishes Architecture. Inputs: Input Outputs: Output ''' y_out = [] # Step through every layer in each subtree of model, applying nonlinearities for j in range(self.Repeats): y = x for i in range(len(self.k)-1): if self.Activation == 'relu': y = self.relu(self._modules[self.names[j,i]](y)) elif self.Activation == 'nck': y = self.nck(self._modules[self.names[j,i]](y)) elif self.Activation == 'sqgl': y = self.sqgl(self._modules[self.names[j,i]](y)) else: y = self._modules[self.names[j,i]](y) # keep track of pen-ultimate layer outputs y_out.append(y) # Calculate final output, joining the outputs of each subtree together # output = self.sigmoid(self.root(torch.cat((y_out), dim=1))) output = self.root(torch.cat((y_out), dim=1)) return(output) def initialize(self, layer): # Kaiming initialize weights accounting for sparsity # Extract weights from layer we are reinitializing weights = layer.weight.data # If sparse, change the initializations based on density (sparsity) if self.Sparse: if weights.shape[1] == 3072: # first layer of 3x32x32 image datasets inp_block = torch.ones((1,3)) elif (weights.shape[1] == 784) or (weights.shape[1] == 112): # first or second layer of 28x28 datasets inp_block = torch.ones((1,7)) else: inp_block = torch.ones((1,2)) # all other layers (or 32x32) # Set up mask for where each node receives a set of inputs of equal size to the input block inp_mask = kronecker(torch.eye(weights.shape[0]), inp_block) # Calculate density density = len(np.where(inp_mask)[0])/len(inp_mask.reshape(-1)) # Generate Kaiming initialization with gain = 1/density weights = torch.nn.init.normal_(weights, mean=0.0, std=math.sqrt(2/(weights.shape[1]*density))) # Where no inputs will be received, set weights to zero weights[inp_mask == 0] = 0 else: # If not sparse, use typical kaiming normalization weights = torch.nn.init.normal_(weights, mean=0.0, std=math.sqrt(2/(weights.shape[1]))) # Generate freeze mask for use in training to keep weights initialized to zero at zero mask_gen = torch.zeros_like(weights) # Indicate where weights are equal to zero freeze_mask = mask_gen == weights return(weights, freeze_mask) class synapse_fcnn(nn.Module): ''' 2 layer feed forward neural network. Will use leaky ReLU activation functions. Activation = {'relu', 'linear','nck','sqgl'} ''' def __init__(self, Input_size=3072, Hidden_size=3072, Output_size=1, Activation="relu", alpha=1, beta=0.6, gamma=1, learn=True, scale=1, atten=1, leak=0.01): super(synapse_fcnn, self).__init__() ''' Inputs: Input_size, Hidden_size, Output_size, Activation ''' # Initialize architecture parameters self.Input_size = Input_size self.Hidden_size = Hidden_size self.Output_size = Output_size self.Activation = Activation self.learn = learn self.scale = scale self.atten = atten self.leak = leak # Initialize Synapse layer self.syn = Synapse(Input_size) # Initialize weights through He initialization (by default in nn.Linear) self.i2h = nn.Linear(Input_size, Hidden_size, bias=True) self.i2h.bias = torch.nn.Parameter(torch.zeros_like(self.i2h.bias)) # self.i2h.weight = torch.nn.init.normal_(self.i2h.weight, mean=0.0, std=math.sqrt(2/(Input_size))) self.i2h.weight = torch.nn.init.kaiming_normal_(self.i2h.weight, a=0.01) # Initialize densly connected output layer self.h2o = nn.Linear(Hidden_size, Output_size) self.h2o.bias = torch.nn.Parameter(torch.zeros_like(self.h2o.bias)) self.h2o.weight = torch.nn.init.kaiming_normal_(self.h2o.weight, a=0.01) # Initialize nonlinearities self.relu = nn.LeakyReLU(negative_slope=self.leak) self.sigmoid = nn.Sigmoid() self.swish = nn.Hardswish() if Activation=='nck': self.nck = NCK(alpha, beta, gamma, learn=self.learn, scale=self.scale) if Activation=='sqgl': self.sqgl = SQGL(alpha, beta, gamma, learn=self.learn, scale=self.scale, atten=self.atten) def forward(self, x): ''' Forward step for network. Establishes Architecture. Inputs: Input Outputs: Output ''' # Receive inputs into synapse layer x = self.syn(x) # Set Activation function to calculate hidden layer if self.Activation == 'relu': Hidden = self.relu(self.i2h(x)) elif self.Activation == 'nck': Hidden = self.nck(self.i2h(x)) elif self.Activation == 'sqgl': Hidden = self.sqgl(self.i2h(x)) elif self.Activation == 'swish': Hidden = self.swish(self.i2h(x)) else: Hidden = self.i2h(x) # Calculate Output layer # Output = self.sigmoid(self.h2o(Hidden)) Output = self.h2o(Hidden) return(Output) class synapse_ktree_gen(nn.Module): ''' k-Tree neural network ''' def __init__(self, ds='mnist', Activation="relu", Sparse=True, Input_order=None, Repeats=1, Padded=False, alpha=1, beta=0.6, gamma=1, learn=True, scale=1, atten=1): super(synapse_ktree_gen, self).__init__() ''' Inputs: ds (dataset), activation, sparse, input_order, repeats, padded ''' # Initialize architecture parameters self.ds = ds self.Activation = Activation self.Sparse = Sparse self.Input_order = Input_order self.Repeats = Repeats self.learn = learn self.scale = scale self.atten = atten # Initialize weights # Set biases to 0 # Set kaiming initialize weights with gain to correct for sparsity # Set freeze masks #Specify tree dimensions # If using 28x28 datasets... if (ds == 'mnist') or (ds == 'fmnist') or (ds == 'kmnist') or (ds == 'emnist'): # If padded, use 1024 sized tree, completely binary tree if Padded: self.k = [1024, 512, 256, 128, 64, 32, 16, 8, 4, 2, 1] # If not padded, use 784 sized tree, # 7:1 between layers 1 and 2, and layers 2 and 3 else: self.k = [784, 112, 16, 8, 4, 2, 1] # If using 3x32x32 datasets... elif (ds == 'svhn') or (ds == 'cifar10'): # Use 3072 sized tree # 3:1 between layers 1 and 2, otherwise binary self.k = [3072, 1024, 512, 256, 128, 64, 32, 16, 8, 4, 2, 1] # If using 16x16 datasets... elif ds == 'usps': # Use 256 sized tree self.k = [256, 128, 64, 32, 16, 8, 4, 2, 1] else: print('Select a dataset') return(None) # Make layers of tree architecture # Name each layer in each subtree for reference later self.names = np.empty((self.Repeats, len(self.k)-1),dtype=object) self.syn_names = np.empty((self.Repeats), dtype=object) # Initialize freeze mask for use in training loop self.freeze_mask_set = [] # For each repeat or subtree, make a sparse layer that is initialized correctly for j in range(self.Repeats): #Initialize synapse layer for each subtree syn_name = ''.join(['s',str(j)]) self.add_module(syn_name, Synapse(self.k[0])) self.syn_names[j] = syn_name # For each layer within each subtree for i in range(len(self.k)-1): # Assign name of the layer, indexed by layer (i) and subtree (j) name = ''.join(['w',str(j),'_',str(i)]) # Initialize the layer with the appropriate name self.add_module(name, nn.Linear(self.k[i],self.k[i+1])) # Set bias of layer to zeros self._modules[name].bias = nn.Parameter(torch.zeros_like(self._modules[name].bias)) # Use custom method to re-initialize the layer weights and create freeze mask for that layer self._modules[name].weight.data, freeze_mask = self.initialize(self._modules[name]) # Add the layer name to the list of names self.names[j,i] = name # Set the freeze mask for the first subtree, which should be the same for all subtrees if j < 1: self.freeze_mask_set.append(freeze_mask) # Initialize root node, aka soma node aka output node self.root = nn.Linear(Repeats, 1) # Initialize nonlinearities self.relu = nn.LeakyReLU() self.sigmoid = nn.Sigmoid() self.nck = NCK(alpha, beta, gamma, learn=self.learn, scale=self.scale) self.sqgl = SQGL(alpha, beta, gamma, learn=self.learn, scale=self.scale, atten=self.atten) def forward(self, x): ''' Forward step for network. Establishes Architecture. Inputs: Input Outputs: Output ''' y_out = [] # Step through every layer in each subtree of model, applying nonlinearities for j in range(self.Repeats): y = self._modules[self.syn_names[j]](x) # Synapse layer for each subtree for i in range(len(self.k)-1): if self.Activation == 'relu': y = self.relu(self._modules[self.names[j,i]](y)) elif self.Activation == 'nck': y = self.nck(self._modules[self.names[j,i]](y)) elif self.Activation == 'sqgl': y = self.sqgl(self._modules[self.names[j,i]](y)) else: y = self._modules[self.names[j,i]](y) # keep track of pen-ultimate layer outputs y_out.append(y) # Calculate final output, joining the outputs of each subtree together # output = self.sigmoid(self.root(torch.cat((y_out), dim=1))) output = self.root(torch.cat((y_out), dim=1)) return(output) def initialize(self, layer): # Kaiming initialize weights accounting for sparsity # Extract weights from layer we are reinitializing weights = layer.weight.data # If sparse, change the initializations based on density (sparsity) if self.Sparse: if weights.shape[1] == 3072: # first layer of 3x32x32 image datasets inp_block = torch.ones((1,3)) elif (weights.shape[1] == 784) or (weights.shape[1] == 112): # first or second layer of 28x28 datasets inp_block = torch.ones((1,7)) else: inp_block = torch.ones((1,2)) # all other layers (or 32x32) # Set up mask for where each node receives a set of inputs of equal size to the input block inp_mask = kronecker(torch.eye(weights.shape[0]), inp_block) # Calculate density density = len(np.where(inp_mask)[0])/len(inp_mask.reshape(-1)) # Generate Kaiming initialization with gain = 1/density weights = torch.nn.init.normal_(weights, mean=0.0, std=math.sqrt(2/(weights.shape[1]*density))) # Where no inputs will be received, set weights to zero weights[inp_mask == 0] = 0 else: # If not sparse, use typical kaiming normalization weights = torch.nn.init.normal_(weights, mean=0.0, std=math.sqrt(2/(weights.shape[1]))) # Generate freeze mask for use in training to keep weights initialized to zero at zero mask_gen = torch.zeros_like(weights) # Indicate where weights are equal to zero freeze_mask = mask_gen == weights return(weights, freeze_mask) class ktree_sparse(nn.Module): ''' k-Tree neural network ''' def __init__(self, ds='mnist', Activation="relu", Input_order=None, Repeats=1, Padded=True, alpha=1, beta=1, gamma=1, learn=True, scale=1, atten=1, synapse=True, leak=0.01, Node_vary=True, positive=False): super(ktree_sparse, self).__init__() ''' Inputs: ds (dataset), activation, sparse, input_order, repeats, padded ''' # Initialize architecture parameters self.ds = ds self.Activation = Activation self.Input_order = Input_order self.Repeats = Repeats self.learn = learn self.scale = scale self.atten = atten self.synapse = synapse self.leak = leak self.Node_vary = Node_vary self.positive = positive # Initialize weights # Set biases to 0 # Set kaiming initialize weights with gain to correct for sparsity # Set freeze masks #Specify tree dimensions # If using 28x28 datasets... if (ds == 'mnist') or (ds == 'fmnist') or (ds == 'kmnist') or (ds == 'emnist'): # If padded, use 1024 sized tree, completely binary tree if Padded: self.k = [1024, 512, 256, 128, 64, 32, 16, 8, 4, 2, 1] # If not padded, use 784 sized tree, # 7:1 between layers 1 and 2, and layers 2 and 3 else: self.k = [784, 112, 16, 8, 4, 2, 1] # If using 3x32x32 datasets... elif (ds == 'svhn') or (ds == 'cifar10'): # Use 3072 sized tree # 3:1 between layers 1 and 2, otherwise binary self.k = [3072, 1024, 512, 256, 128, 64, 32, 16, 8, 4, 2, 1] # If using 16x16 datasets... elif ds == 'usps': # Use 256 sized tree self.k = [256, 128, 64, 32, 16, 8, 4, 2, 1] else: print('Select a dataset') return(None) # Make layers of tree architecture # Name each layer in each subtree for reference later self.names = np.empty((self.Repeats, len(self.k)-1),dtype=object) if self.synapse: self.syn_names = np.empty((self.Repeats), dtype=object) if self.Node_vary: self.sqgl_names = np.empty((self.Repeats, len(self.k)-1),dtype=object) # Initialize freeze mask for use in training loop self.freeze_mask_set = [] # For each repeat or subtree, make a sparse layer that is initialized correctly for j in range(self.Repeats): if self.synapse: #Initialize synapse layer for each subtree syn_name = ''.join(['s',str(j)]) self.add_module(syn_name, Synapse(self.k[0])) self.syn_names[j] = syn_name if self.Node_vary == True: for i in range(len(self.k)-1): # Assign name of each sqgl layer, indexed by layer (i) and subtree (j) sqgl_name = ''.join(['sq',str(j),'_',str(i)]) # Initialize the layer with the appropriate name self.add_module(sqgl_name, slc.SparseLinear(3*self.k[i+1], self.k[i+1], connectivity=self.sqgl_connectivity(self.k[i+1]), bias=False, sqgl_true=True)) # Add activation layer name to list of names self.sqgl_names[j,i] = sqgl_name # For each layer within each subtree for i in range(len(self.k)-1): # Assign name of the layer, indexed by layer (i) and subtree (j) name = ''.join(['w',str(j),'_',str(i)]) # Initialize the layer with the appropriate name self.add_module(name, slc.SparseLinear(self.k[i], self.k[i+1], connectivity=self.layer_connectivity(self.k[i]), bias=True, positive=self.positive)) # Add the layer name to the list of names self.names[j,i] = name self._modules[self.names[j,i]].bias.data.zero_() # Initialize root node, aka soma node aka output node self.root = nn.Linear(Repeats, 1, bias=True) self.root.bias.data.zero_() # Initialize nonlinearities self.relu = nn.LeakyReLU(negative_slope=leak) self.sigmoid = nn.Sigmoid() self.swish = nn.Hardswish() self.nck = NCK(alpha, beta, gamma, learn=self.learn, scale=self.scale) self.sqgl = SQGL(alpha, beta, gamma, learn=self.learn, scale=self.scale, atten=self.atten) if self.Node_vary == True: self.f_na = F_Na(self.scale) self.f_ca = F_Ca(self.scale) self.f_k = F_K(self.scale) def forward(self, x): ''' Forward step for network. Establishes Architecture. Inputs: Input Outputs: Output ''' y_out = [] # Step through every layer in each subtree of model, applying nonlinearities for j in range(self.Repeats): if self.synapse: y = self._modules[self.syn_names[j]](x) # Synapse layer for each subtree else: y = x for i in range(len(self.k)-1): if self.Activation == 'relu': y = self.relu(self._modules[self.names[j,i]](y)) elif self.Activation == 'nck': y = self.nck(self._modules[self.names[j,i]](y)) elif self.Activation == 'sqgl': if self.Node_vary == True: # If varying sqgl by node # First put through linear layer y = self._modules[self.names[j,i]](y) # Then do step one of sqgl nonlinearity interm_act = torch.cat((self.f_na(y), self.f_ca(y), self.f_k(y)), axis=1) # Weighted sum of nonlinearities, added to linear component # Then multiplied by an attenuation factor y = self.atten*(y + self._modules[self.sqgl_names[j,i]](interm_act)) else: y = self.sqgl(self._modules[self.names[j,i]](y)) elif self.Activation == 'sigmoid': y = self.sigmoid(self._modules[self.names[j,i]](y)) elif self.Activation == 'silu': y = self.silu(self._modules[self.names[j,i]](y)) elif self.Activation == 'swish': y = self.swish(self._modules[self.names[j,i]](y)) else: y = self._modules[self.names[j,i]](y) # keep track of pen-ultimate layer outputs y_out.append(y) # Calculate final output, joining the outputs of each subtree together # output = self.sigmoid(self.root(torch.cat((y_out), dim=1))) output = self.root(torch.cat((y_out), dim=1)) return(output) def layer_connectivity(self, in_features): if in_features == 3072: inp_block = torch.ones((1,3)) elif (in_features == 784) or (in_features == 112): # first or second layer of 28x28 datasets inp_block = torch.ones((1,7)) else: inp_block = torch.ones((1,2)) # all other layers (or 32x32) inp_mask = kronecker(torch.eye(int(in_features/inp_block.size()[1])), inp_block) ix = inp_mask.nonzero(as_tuple=False) return(ix.t()) def sqgl_connectivity(self, in_features): # Only works as an activation function layer if input to this layer is 1x1x3N where N is original input size inp_block = torch.eye(in_features) inp_mask = torch.cat((inp_block, inp_block, inp_block), axis=0) inp_mask = inp_mask.t() ix = inp_mask.nonzero(as_tuple=False) return(ix.t()) class asym_tree_gen(nn.Module): ''' asym-Tree neural network ''' def __init__(self, ds='mnist', Activation="relu", Input_order=None, Repeats=1, Padded=True, alpha=1, beta=0.6, gamma=1, learn=True, scale=1, atten=1, synapse=False, tree=None, leak=0.01): super(asym_tree_gen, self).__init__() ''' Inputs: ds (dataset), activation, sparse, input_order, repeats, padded ''' # Initialize architecture parameters self.ds = ds self.Activation = Activation self.Input_order = Input_order self.Repeats = Repeats self.learn = learn self.scale = scale self.atten = atten self.Synapse = synapse self.tree = tree self.num_leaves = len(self.find_all_leaf_ids(self.tree)) self.leak = leak if self.tree is None: raise TypeError('Did not specify tree') # Initialize weights # Set biases to 0 # Set kaiming initialize weights with gain to correct for sparsity # Set freeze masks #Specify tree dimensions # If using 28x28 datasets... if (ds == 'mnist') or (ds == 'fmnist') or (ds == 'kmnist') or (ds == 'emnist'): # If padded, use 1024 sized tree, completely binary tree if Padded: self.input_size = 1024 # If not padded, use 784 sized tree, else: self.input_size = 784 # If using 3x32x32 datasets... elif (ds == 'svhn') or (ds == 'cifar10'): # Use 3072 sized tree self.input_size = 3072 # If using 16x16 datasets... elif ds == 'usps': # Use 256 sized tree self.input_size = 256 else: print('Select a dataset') return(None) # Make layers of tree architecture # Make list of connectivity matrices for purpose of making sparse layers self.connectivity_matrices = self.seq_adj_mat(self.tree) # Name each layer in each subtree for reference later self.names = np.empty((self.Repeats, len(self.connectivity_matrices)),dtype=object) if self.Synapse: self.syn_names = np.empty((self.Repeats), dtype=object) # For each repeat or subtree, make a sparse layer that is initialized correctly for j in range(self.Repeats): if self.Synapse: #Initialize synapse layer for each subtree syn_name = ''.join(['s',str(j)]) self.add_module(syn_name, Synapse(self.input_size)) self.syn_names[j] = syn_name # For each layer within each subtree for i, connectivity_matrix in enumerate(self.connectivity_matrices): # Assign name of the layer, indexed by layer (i) and subtree (j) name = ''.join(['w',str(j),'_',str(i)]) # Initialize the layer with the appropriate name self.add_module(name, slc.SparseLinear(self.num_leaves + len(self.tree), len(self.tree), connectivity=connectivity_matrix, bias=True)) # print(i,connectivity_matrix) # print(self._modules[name]) # Add the layer name to the list of names self.names[j,i] = name self._modules[self.names[j,i]].bias.data.zero_() # Initialize root node, aka soma node aka output node self.root = nn.Linear(Repeats, 1, bias=True) self.root.bias.data.zero_() # Initialize nonlinearities self.relu = nn.LeakyReLU(negative_slope=self.leak) self.sigmoid = nn.Sigmoid() self.nck = NCK(alpha, beta, gamma, learn=self.learn, scale=self.scale) self.sqgl = SQGL(alpha, beta, gamma, learn=self.learn, scale=self.scale, atten=self.atten) def find_all_leaf_ids(self,tree): """ just see which nodes are not in the list like in tree = [-1,0,0,1,1,2,2] leaves are [3, 4, 5, 6] """ all_leaf_ids = [i for i in range(len(tree)) if i not in tree and tree[i] is not None] return(np.array(all_leaf_ids)) def find_all_branch_ids(self,tree): ''' just see which nodes are not in the list like in tree = [-1,0,0,1,1,2,2] leaves are [3, 4, 5, 6] ''' all_branch_ids = [i for i in range(len(tree)) if i in tree and tree[i] is not None] return(np.array(all_branch_ids)) def path_lengths(self, tree): paths = np.zeros(len(tree)) for i in range(len(tree)): node = i branch = node path_length = 0 while branch != 0: branch = tree[node] node = branch path_length += 1 paths[i] = path_length return(paths.astype(int)) def seq_adj_mat(self, tree): paths = self.path_lengths(tree) leaves = self.find_all_leaf_ids(tree) branches = self.find_all_branch_ids(tree) ids = np.arange(len(tree)) i = 1 j = 1 adj_mats = [] for path_len in reversed(range(max(paths)+1)): adj_mat = np.zeros((len(tree), len(tree) + self.num_leaves)) idx = np.where(path_len == paths, True, False) nodes = ids[idx] leaf_nodes = list(filter(lambda x: x in leaves, nodes)) branch_nodes = list(filter(lambda x: x in branches, nodes)) for leaf in leaf_nodes: adj_mat[leaf, len(leaves) - i] = 1 i += 1 for branch in branch_nodes: adj_mat[branch, len(tree) + len(leaves) - j] = 1 j += 1 adj_mat[branch, len(tree) + len(leaves) - j] = 1 j += 1 # Change adj_mats into sparse format sparse_idx = [] idxs = np.where(adj_mat) for idx in idxs: sparse_idx.append(list(idx)) sparse_idx = torch.LongTensor(sparse_idx) adj_mats.append(sparse_idx) return(adj_mats) def forward(self, x): ''' Forward step for network. Establishes Architecture. Inputs: Input Outputs: Output ''' y_out = [] # Step through every layer in each subtree of model, applying nonlinearities for j in range(self.Repeats): y = x.clone() # print(self.num_leaves) if y.shape[1] < self.num_leaves: filler = torch.zeros((y.shape[0], self.num_leaves)).cuda() filler[:,:y.shape[1]] = y y = filler elif y.shape[1] > self.num_leaves: y = y[:, :self.num_leaves] hidden = torch.cat((y, torch.zeros(y.shape[0], len(self.tree)).cuda()), dim=1) for i in range(len(self.connectivity_matrices)): # print(i,j) if self.Activation == 'relu': hidden = self.relu(self._modules[self.names[j,i]](hidden)) hidden = torch.cat((y, hidden), dim=1) elif self.Activation == 'nck': hidden = self.nck(self._modules[self.names[j,i]](hidden)) hidden = torch.cat((y, hidden), dim=1) elif self.Activation == 'sqgl': hidden = self.sqgl(self._modules[self.names[j,i]](hidden)) hidden = torch.cat((y, hidden), dim=1) else: hidden = self._modules[self.names[j,i]](hidden) hidden = torch.cat((y, hidden), dim=1) # # keep track of pen-ultimate layer outputs y_out.append(hidden[:,self.num_leaves].reshape(y.shape[0],1)) # print('yout',y_out[0].shape) # Calculate final output, joining the outputs of each subtree together # output = self.sigmoid(self.root(torch.cat((y_out), dim=1))) output = self.root(torch.cat((y_out), dim=1)) # output = y return(output) def prepare_tree(n): return(np.array(n[0][:,-1]).astype(int)-1) def find_all_leaf_ids(tree): """ just see which nodes are not in the list like in tree = [-1,0,0,1,1,2,2] leaves are [3, 4, 5, 6] """ all_leaf_ids = [i for i in range(len(tree)) if i not in tree and tree[i] is not None] return(np.array(all_leaf_ids)) def find_target_tree(mcn_trees): leaves = np.zeros((len(mcn_trees),2)) for i in range(len(mcn_trees)): n = mcn_trees[i] tree = (n[0][:,-1]).astype(int) -1 leaves[i,1] = len(find_all_leaf_ids(tree)) leaves[i,0] = i num_leafs = leaves[0,1] if num_leafs > 14**2 and num_leafs < 18**2 : targ_diff = 256 if num_leafs > 26**2 and num_leafs < 34**2 : targ_diff = 1024 if num_leafs > 3*30**2 and num_leafs < 3*34**2 : targ_diff = 3072 leaves = np.concatenate((leaves,abs(leaves[:,1]-targ_diff).reshape(-1,1)),1) # print(leaves) target = np.argmin(leaves[:,2]) print('Target Tree:', leaves[target,:]) return(target) class ktree_synapse(nn.Module): ''' k-Tree neural network ''' def __init__(self, ds='mnist', Activation="relu", Input_order=None, Repeats=1, Padded=True, alpha=1, beta=1, gamma=1, learn=True, scale=1, atten=1, leak=0.01, Node_vary=True, positive=False): super(ktree_synapse, self).__init__() ''' Inputs: ds (dataset), activation, sparse, input_order, repeats, padded ''' # Initialize architecture parameters self.ds = ds self.Activation = Activation self.Input_order = Input_order self.Repeats = Repeats self.learn = learn self.scale = scale self.atten = atten self.leak = leak self.Node_vary = Node_vary self.positive = positive # Initialize weights # Set biases to 0 # Set kaiming initialize weights with gain to correct for sparsity # Set freeze masks #Specify tree dimensions # If using 28x28 datasets... if (ds == 'mnist') or (ds == 'fmnist') or (ds == 'kmnist') or (ds == 'emnist'): # If padded, use 1024 sized tree, completely binary tree if Padded: self.k = [1024, 512, 256, 128, 64, 32, 16, 8, 4, 2, 1] # If not padded, use 784 sized tree, # 7:1 between layers 1 and 2, and layers 2 and 3 else: self.k = [784, 112, 16, 8, 4, 2, 1] # If using 3x32x32 datasets... elif (ds == 'svhn') or (ds == 'cifar10'): # Use 3072 sized tree # 3:1 between layers 1 and 2, otherwise binary self.k = [3072, 1024, 512, 256, 128, 64, 32, 16, 8, 4, 2, 1] # If using 16x16 datasets... elif ds == 'usps': # Use 256 sized tree self.k = [256, 128, 64, 32, 16, 8, 4, 2, 1] else: print('Select a dataset') return(None) # Make layers of tree architecture # Name each layer in each subtree for reference later self.names = np.empty((self.Repeats, len(self.k)-1),dtype=object) self.syn_names = np.empty((self.Repeats), dtype=object) if self.Node_vary: self.sqgl_names = np.empty((self.Repeats, len(self.k)-1),dtype=object) # Initialize freeze mask for use in training loop self.freeze_mask_set = [] # For each repeat or subtree, make a sparse layer that is initialized correctly for j in range(self.Repeats): #Initialize synapse layer for each subtree syn_name = ''.join(['s',str(j)]) self.add_module(syn_name, Synapse(self.k[0])) self.syn_names[j] = syn_name if self.Node_vary == True: for i in range(len(self.k)-1): # Assign name of each sqgl layer, indexed by layer (i) and subtree (j) sqgl_name = ''.join(['sq',str(j),'_',str(i)]) # Initialize the layer with the appropriate name self.add_module(sqgl_name, slc.SparseLinear(3*self.k[i+1], self.k[i+1], connectivity=self.sqgl_connectivity(self.k[i+1]), bias=False, sqgl_true=True)) # Add activation layer name to list of names self.sqgl_names[j,i] = sqgl_name # For each layer within each subtree for i in range(len(self.k)-1): # Assign name of the layer, indexed by layer (i) and subtree (j) name = ''.join(['w',str(j),'_',str(i)]) # Initialize the layer with the appropriate name self.add_module(name, slc.SparseLinear(self.k[i], self.k[i+1], connectivity=self.layer_connectivity(self.k[i]), bias=True, positive=self.positive)) # Add the layer name to the list of names self.names[j,i] = name self._modules[self.names[j,i]].bias.data.zero_() # Initialize root node, aka soma node aka output node self.root = nn.Linear(Repeats, 1, bias=True) self.root.bias.data.zero_() # Initialize nonlinearities self.relu = nn.LeakyReLU(negative_slope=leak) self.sigmoid = nn.Sigmoid() self.swish = nn.Hardswish() self.nck = NCK(alpha, beta, gamma, learn=self.learn, scale=self.scale) if self.Node_vary == True: self.f_na = F_Na(self.scale) self.f_ca = F_Ca(self.scale) self.f_k = F_K(self.scale) else: self.sqgl = SQGL(alpha, beta, gamma, learn=self.learn, scale=self.scale, atten=self.atten) def forward(self, x): ''' Forward step for network. Establishes Architecture. Inputs: Input Outputs: Output ''' y_out = [] loss = 0 hinge_loss = Hinge_loss(margin=0.5) # Step through every layer in each subtree of model, applying nonlinearities for j in range(self.Repeats): y = self._modules[self.syn_names[j]](x) # Synapse layer for each subtree for i in range(len(self.k)-1): if self.Activation == 'relu': y = self.relu(self._modules[self.names[j,i]](y)) loss += self.hinge_criterion(y) elif self.Activation == 'nck': y = self.nck(self._modules[self.names[j,i]](y)) loss += self.hinge_criterion(y) elif self.Activation == 'sqgl': if self.Node_vary == True: # If varying sqgl by node # First put through linear layer y = self._modules[self.names[j,i]](y) # Then do step one of sqgl nonlinearity interm_act = torch.cat((self.f_na(y), self.f_ca(y), self.f_k(y)), axis=1) # Weighted sum of nonlinearities, added to linear component # Then multiplied by an attenuation factor y = self.atten*(y + self._modules[self.sqgl_names[j,i]](interm_act)) #Calculate loss loss += self.hinge_criterion(y) else: y = self.sqgl(self._modules[self.names[j,i]](y)) loss += self.hinge_criterion(y) elif self.Activation == 'sigmoid': y = self.sigmoid(self._modules[self.names[j,i]](y)) loss += self.hinge_criterion(y) elif self.Activation == 'silu': y = self.silu(self._modules[self.names[j,i]](y)) loss += self.hinge_criterion(y) elif self.Activation == 'swish': y = self.swish(self._modules[self.names[j,i]](y)) loss += self.hinge_criterion(y) else: y = self._modules[self.names[j,i]](y) loss += self.hinge_criterion(y) # keep track of pen-ultimate layer outputs y_out.append(y) # Calculate final output, joining the outputs of each subtree together # output = self.sigmoid(self.root(torch.cat((y_out), dim=1))) output = self.root(torch.cat((y_out), dim=1)) return(output, loss) def layer_connectivity(self, in_features): if in_features == 3072: inp_block = torch.ones((1,3)) elif (in_features == 784) or (in_features == 112): # first or second layer of 28x28 datasets inp_block = torch.ones((1,7)) else: inp_block = torch.ones((1,2)) # all other layers (or 32x32) inp_mask = kronecker(torch.eye(int(in_features/inp_block.size()[1])), inp_block) ix = inp_mask.nonzero(as_tuple=False) return(ix.t()) def sqgl_connectivity(self, in_features): # Only works as an activation function layer if input to this layer is 1x1x3N where N is original input size inp_block = torch.eye(in_features) inp_mask = torch.cat((inp_block, inp_block, inp_block), axis=0) inp_mask = inp_mask.t() ix = inp_mask.nonzero(as_tuple=False) return(ix.t()) def hinge_criterion(self, activity): # Specify targets with same size as layer hinge_loss = Hinge_loss(margin=0.5) target = - torch.ones_like(activity) # Loss = hinge(v-vmax) + hinge(vmin-v) return(hinge_loss(activity-51, target) + hinge_loss(-71-activity, target))

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c57ec75da3006ec44756edcd1a07672efc8946f7

4,938

py

Python

tests/agents/network/test_BlockDNS.py

nafri-irfan96/ychaos

33542ef061b25f7a3770cb40c10c394dc123c475

[ "Apache-2.0" ]

1

2021-09-27T16:18:33.000Z

tests/agents/network/test_BlockDNS.py

nafri-irfan96/ychaos

33542ef061b25f7a3770cb40c10c394dc123c475

[ "Apache-2.0" ]

null

tests/agents/network/test_BlockDNS.py

nafri-irfan96/ychaos

33542ef061b25f7a3770cb40c10c394dc123c475

[ "Apache-2.0" ]

null

# Copyright 2021, Yahoo # Licensed under the terms of the Apache 2.0 license. See the LICENSE file in the project root for terms import os import subprocess from unittest import TestCase from mockito import any, unstub, verify, when from ychaos.agents.agent import AgentState from ychaos.agents.exceptions import AgentError from ychaos.agents.network.iptables import DNSBlock, DNSBlockConfig class TestBlockDNSConfig(TestCase): def test_block_dns_setup(self): config = DNSBlockConfig() agent = DNSBlock(config) agent.setup() agent.monitor() # coverage self.assertEqual(agent.current_state, AgentState.SETUP) def test_block_dns_teardown_does_not_modify_iptables_rule_when_in_setup(self): config = DNSBlockConfig() agent = DNSBlock(config) agent.setup() self.assertEqual(agent.current_state, AgentState.SETUP) when(subprocess).run( any, stdout=subprocess.PIPE, stderr=subprocess.PIPE, ).thenReturn(subprocess.CompletedProcess(args=[], returncode=0)) agent.teardown() verify(subprocess, times=0).run( any, stdout=subprocess.PIPE, stderr=subprocess.PIPE, ) def test_block_dns_run(self): config = DNSBlockConfig() agent = DNSBlock(config) agent.setup() self.assertEqual(agent.current_state, AgentState.SETUP) when(os).geteuid().thenReturn(0) when(subprocess).run( "sudo /sbin/iptables -I OUTPUT -p udp --dport 53 -j DROP -w 3".split(), stdout=subprocess.PIPE, stderr=subprocess.PIPE, ).thenReturn(subprocess.CompletedProcess(args=[], returncode=0)) when(subprocess).run( f"sudo /sbin/iptables -I OUTPUT -p tcp --dport 53 -j DROP -w 3".split(), stdout=subprocess.PIPE, stderr=subprocess.PIPE, ).thenReturn(subprocess.CompletedProcess(args=[], returncode=0)) agent.run() self.assertEqual(agent.current_state, AgentState.RUNNING) def test_block_dns_run_raises_io_error(self): config = DNSBlockConfig() agent = DNSBlock(config) agent.setup() self.assertEqual(agent.current_state, AgentState.SETUP) when(os).geteuid().thenReturn(0) when(subprocess).run( "sudo /sbin/iptables -I OUTPUT -p udp --dport 53 -j DROP -w 3".split(), stdout=subprocess.PIPE, stderr=subprocess.PIPE, ).thenReturn(subprocess.CompletedProcess(args=[], returncode=0)) when(subprocess).run( f"sudo /sbin/iptables -I OUTPUT -p tcp --dport 53 -j DROP -w 3".split(), stdout=subprocess.PIPE, stderr=subprocess.PIPE, ).thenReturn(subprocess.CompletedProcess(args=[], returncode=1)) with self.assertRaises(IOError): agent.run() def test_block_dns_teardown_restores_after_running(self): config = DNSBlockConfig() agent = DNSBlock(config) agent.setup() self.assertEqual(agent.current_state, AgentState.SETUP) agent.advance_state(AgentState.RUNNING) when(subprocess).run( "sudo /sbin/iptables -D OUTPUT -p udp --dport 53 -j DROP -w 3".split(), stdout=subprocess.PIPE, stderr=subprocess.PIPE, ).thenReturn(subprocess.CompletedProcess(args=[], returncode=0)) when(subprocess).run( "sudo /sbin/iptables -D OUTPUT -p tcp --dport 53 -j DROP -w 3".split(), stdout=subprocess.PIPE, stderr=subprocess.PIPE, ).thenReturn(subprocess.CompletedProcess(args=[], returncode=0)) agent.teardown() verify(subprocess, times=2).run( any, stdout=subprocess.PIPE, stderr=subprocess.PIPE, ) def test_block_dns_teardown_raises_error_when_failed(self): config = DNSBlockConfig() agent = DNSBlock(config) agent.setup() self.assertEqual(agent.current_state, AgentState.SETUP) agent.advance_state(AgentState.RUNNING) when(subprocess).run( "sudo /sbin/iptables -D OUTPUT -p udp --dport 53 -j DROP -w 3".split(), stdout=subprocess.PIPE, stderr=subprocess.PIPE, ).thenReturn(subprocess.CompletedProcess(args=[], returncode=0)) when(subprocess).run( "sudo /sbin/iptables -D OUTPUT -p tcp --dport 53 -j DROP -w 3".split(), stdout=subprocess.PIPE, stderr=subprocess.PIPE, ).thenReturn(subprocess.CompletedProcess(args=[], returncode=1)) with self.assertRaises(AgentError): agent.teardown() verify(subprocess, times=2).run( any, stdout=subprocess.PIPE, stderr=subprocess.PIPE, ) def tearDown(self) -> None: unstub()

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null

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null

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7

c5a0b6eddf51d7b9b140e0450f5565c3eaa05aa5

213

py

Python

src/cms/views/bed_target_groups/__init__.py

digitalfabrik/coldaid-backend

b769510570d5921e30876565263813c0362994e2

[ "Apache-2.0" ]

4

2019-12-05T16:45:17.000Z

2020-05-09T07:26:34.000Z

src/cms/views/bed_target_groups/__init__.py

digitalfabrik/coldaid-backend

b769510570d5921e30876565263813c0362994e2

[ "Apache-2.0" ]

56

2019-12-05T12:31:37.000Z

2021-01-07T15:47:45.000Z

src/cms/views/bed_target_groups/__init__.py

digitalfabrik/coldaid-backend

b769510570d5921e30876565263813c0362994e2

[ "Apache-2.0" ]

2

2019-12-11T09:52:26.000Z

2020-05-09T07:26:38.000Z

""" Python standard Init-File """ from .bed_target_group_actions import delete_bed_target_group from .bed_target_group_view import BedTargetGroupView from .bed_target_group_list_view import BedTargetGroupListView

30.428571

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c5b042f4b326db28b70c281fd1a227d11c88daaa

14,144

py

Python

DGBO_GN-batch/gen_synthetic_dataset.py

csjtx1021/Scalable_and_Parallel_Deep_Bayesian_Optimization_on_Attributed_Graphs

68c3d1119be6cafdb32d00dbc8a291047c1639a4

[ "MIT" ]

6

2020-10-19T05:10:33.000Z

2022-01-17T04:33:45.000Z

DGBO_GN-batch/gen_synthetic_dataset.py

csjtx1021/Scalable_and_Parallel_Deep_Bayesian_Optimization_on_Attributed_Graphs

68c3d1119be6cafdb32d00dbc8a291047c1639a4

[ "MIT" ]

null

DGBO_GN-batch/gen_synthetic_dataset.py

csjtx1021/Scalable_and_Parallel_Deep_Bayesian_Optimization_on_Attributed_Graphs

68c3d1119be6cafdb32d00dbc8a291047c1639a4

[ "MIT" ]

null

#!/usr/bin/env python2 # -*- coding: utf-8 -*- """ Created on Mon Dec 18 10:18:43 2017 @author: cuijiaxu """ import numpy as np import multiprocessing as mp import networkx as nx #from gensim.models import Word2Vec from itertools import chain, combinations from collections import defaultdict import os,sys, copy, time, math, pickle import itertools import scipy.io #import pynauty import random from scipy.spatial.distance import pdist, squareform #import pyGPs import scipy.stats import pylab as pl #import GraphMeasure def gen_syn_ds(OUTPUTDIR): print "genrating synthetic dataset..." GraphSet=[] numgraphs=2000 n_set=np.array((20,30,40,50,60,70,80,90,100,110))#for ER and BA p_set=np.array((0.075,0.1,0.125,0.15,0.175,0.2,0.225,0.25,0.275,0.3))#for ER m_set=np.array((1,2,3,4,5,6,7,8,9,10))#for BA rseed_set=np.array((314150,312213,434234,264852,231255,659956,435347,898232,675665,234690)) key=-1 ##ER for n in range(len(n_set)): for p in range(len(p_set)): for rseed in range(len(rseed_set)): key+=1 G1=nx.fast_gnp_random_graph(n_set[n],p_set[p],rseed_set[rseed]) nx.write_edgelist(G1, "%s/%s-ER_%s_%s_%s.edgelist"%(OUTPUTDIR,key,n_set[n],p_set[p],rseed_set[rseed])) GraphSet.append(G1) if np.mod(key,50)==0: nx.draw_circular(G1, with_labels=True, font_weight='bold') pl.savefig("%s/%s-ER_%s_%s_%s.svg"%(OUTPUTDIR,key,n_set[n],p_set[p],rseed_set[rseed])) # pl.show() ##BA for n in range(len(n_set)): for m in range(len(m_set)): for rseed in range(len(rseed_set)): key+=1 G1=nx.barabasi_albert_graph(n_set[n],m_set[m],rseed_set[rseed]) nx.write_edgelist(G1, "%s/%s-BA_%s_%s_%s.edgelist"%(OUTPUTDIR,key,n_set[n],m_set[m],rseed_set[rseed])) GraphSet.append(G1) if np.mod(key,50)==0: nx.draw_circular(G1, with_labels=True, font_weight='bold') pl.savefig("%s/%s-BA_%s_%s_%s.svg"%(OUTPUTDIR,key,n_set[n],m_set[m],rseed_set[rseed])) # pl.show() def get_syn_ds_name_idx(idx): numgraphs=2000 n_set=np.array((20,30,40,50,60,70,80,90,100,110))#for ER and BA p_set=np.array((0.075,0.1,0.125,0.15,0.175,0.2,0.225,0.25,0.275,0.3))#for ER m_set=np.array((1,2,3,4,5,6,7,8,9,10))#for BA rseed_set=np.array((314150,312213,434234,264852,231255,659956,435347,898232,675665,234690)) filename="%s-ER_%s_%s_%s.edgelist"%(idx,n_set[n],p_set[p],rseed_set[rseed]) def read_syn_ds(OUTPUTDIR): print "loading synthetic dataset..." GraphSet=[] numgraphs=500 n_set=np.array((20,30,40,50,60))#for ER and BA p_set=np.array((0.1,0.15,0.2,0.25,0.3))#for ER m_set=np.array((1,2,3,4,5))#for BA rseed_set=np.array((314150,312213,434234,264852,231255,659956,435347,898232,675665,234690)) # nodenum_max=0 nodenum_min=1000000000 edgenum_max=0 edgenum_min=1000000000 avgdeg_max=0 avgdeg_min=1000000000 avgbet_max=0 avgbet_min=1000000000 avgclo_max=0 avgclo_min=1000000000 avgclu_max=0 avgclu_min=1000000000 num_cliques_max=0 num_cliques_min=100000000 num_con_max=0 num_con_min=100000000 # test=[] key=-1 ##ER for n in range(len(n_set)): for p in range(len(p_set)): for rseed in range(len(rseed_set)): key+=1 G1=nx.read_edgelist("%s/%s-ER_%s_%s_%s.edgelist"%(OUTPUTDIR,key,n_set[n],p_set[p],rseed_set[rseed])) GraphSet.append(G1) """ nodenum_max=max(nodenum_max,G1.number_of_nodes()) nodenum_min=min(nodenum_min,G1.number_of_nodes()) edgenum_max=max(edgenum_max,G1.number_of_edges()) edgenum_min=min(edgenum_min,G1.number_of_edges()) avgdeg_max=max(avgdeg_max,np.mean(nx.degree_centrality(G1).values())) avgdeg_min=min(avgdeg_min,np.mean(nx.degree_centrality(G1).values())) avgbet_max=max(avgbet_max,np.mean(nx.betweenness_centrality(G1).values())) avgbet_min=min(avgbet_min,np.mean(nx.betweenness_centrality(G1).values())) #avgclo_max=max(avgclo_max,np.mean(nx.closeness_centrality(G1).values())) #avgclo_min=min(avgclo_min,np.mean(nx.closeness_centrality(G1).values())) avgclu_max=max(avgclu_max,nx.average_clustering(G1)) avgclu_min=min(avgclu_min,nx.average_clustering(G1)) # num_cliques_max=max(num_cliques_max,nx.graph_number_of_cliques(G1)) # num_cliques_min=min(num_cliques_min,nx.graph_number_of_cliques(G1)) # num_con_max=max(num_con_max,nx.number_connected_components(G1)) # num_con_min=min(num_con_min,nx.number_connected_components(G1)) # c=nx.degree_histogram(G1) # idxc=c.index(max(c)) # num_con_max=max(num_con_max,idxc+1) # num_con_min=min(num_con_min,idxc+1) # print idxc+1 # test.append(idxc+1) """ ##BA for n in range(len(n_set)): for m in range(len(m_set)): for rseed in range(len(rseed_set)): key+=1 G1=nx.read_edgelist("%s/%s-BA_%s_%s_%s.edgelist"%(OUTPUTDIR,key,n_set[n],m_set[m],rseed_set[rseed])) GraphSet.append(G1) """ nodenum_max=max(nodenum_max,G1.number_of_nodes()) nodenum_min=min(nodenum_min,G1.number_of_nodes()) edgenum_max=max(edgenum_max,G1.number_of_edges()) edgenum_min=min(edgenum_min,G1.number_of_edges()) avgdeg_max=max(avgdeg_max,np.mean(nx.degree_centrality(G1).values())) avgdeg_min=min(avgdeg_min,np.mean(nx.degree_centrality(G1).values())) avgbet_max=max(avgbet_max,np.mean(nx.betweenness_centrality(G1).values())) avgbet_min=min(avgbet_min,np.mean(nx.betweenness_centrality(G1).values())) # avgclo_max=max(avgclo_max,np.mean(nx.closeness_centrality(G1).values())) # avgclo_min=min(avgclo_min,np.mean(nx.closeness_centrality(G1).values())) avgclu_max=max(avgclu_max,nx.average_clustering(G1)) avgclu_min=min(avgclu_min,nx.average_clustering(G1)) # num_cliques_max=max(num_cliques_max,nx.graph_number_of_cliques(G1)) # num_cliques_min=min(num_cliques_min,nx.graph_number_of_cliques(G1)) # num_con_max=max(num_con_max,nx.number_connected_components(G1)) # num_con_min=min(num_con_min,nx.number_connected_components(G1)) # c=nx.degree_histogram(G1) # idxc=c.index(max(c)) # num_con_max=max(num_con_max,idxc+1) # num_con_min=min(num_con_min,idxc+1) # print idxc+1 # test.append(idxc+1) """ # print num_con_max,num_con_min # print num_cliques_max,num_cliques_min ,num_con_max,num_con_min # print nodenum_max,nodenum_min,edgenum_max,edgenum_min,avgdeg_max,avgdeg_min,avgbet_max,avgbet_min,avgclo_max,avgclo_min,avgclu_max,avgclu_min # print nodenum_max,nodenum_min,edgenum_max,edgenum_min,avgdeg_max,avgdeg_min,avgbet_max,avgbet_min,avgclu_max,avgclu_min # pl.plot(range(500),test) return GraphSet def read_syn_ds_2000(OUTPUTDIR): print "loading synthetic dataset..." GraphSet=[] numgraphs=2000 n_set=np.array((20,30,40,50,60,70,80,90,100,110))#for ER and BA p_set=np.array((0.075,0.1,0.125,0.15,0.175,0.2,0.225,0.25,0.275,0.3))#for ER m_set=np.array((1,2,3,4,5,6,7,8,9,10))#for BA rseed_set=np.array((314150,312213,434234,264852,231255,659956,435347,898232,675665,234690)) # nodenum_max=0 nodenum_min=1000000000 edgenum_max=0 edgenum_min=1000000000 avgdeg_max=0 avgdeg_min=1000000000 avgbet_max=0 avgbet_min=1000000000 avgclo_max=0 avgclo_min=1000000000 avgclu_max=0 avgclu_min=1000000000 num_cliques_max=0 num_cliques_min=100000000 num_con_max=0 num_con_min=100000000 # test=[] key=-1 ##ER for n in range(len(n_set)): for p in range(len(p_set)): for rseed in range(len(rseed_set)): key+=1 G1=nx.read_edgelist("%s/%s-ER_%s_%s_%s.edgelist"%(OUTPUTDIR,key,n_set[n],p_set[p],rseed_set[rseed])) GraphSet.append(G1) """ nodenum_max=max(nodenum_max,G1.number_of_nodes()) nodenum_min=min(nodenum_min,G1.number_of_nodes()) edgenum_max=max(edgenum_max,G1.number_of_edges()) edgenum_min=min(edgenum_min,G1.number_of_edges()) avgdeg_max=max(avgdeg_max,np.mean(nx.degree_centrality(G1).values())) avgdeg_min=min(avgdeg_min,np.mean(nx.degree_centrality(G1).values())) avgbet_max=max(avgbet_max,np.mean(nx.betweenness_centrality(G1).values())) avgbet_min=min(avgbet_min,np.mean(nx.betweenness_centrality(G1).values())) #avgclo_max=max(avgclo_max,np.mean(nx.closeness_centrality(G1).values())) #avgclo_min=min(avgclo_min,np.mean(nx.closeness_centrality(G1).values())) avgclu_max=max(avgclu_max,nx.average_clustering(G1)) avgclu_min=min(avgclu_min,nx.average_clustering(G1)) # num_cliques_max=max(num_cliques_max,nx.graph_number_of_cliques(G1)) # num_cliques_min=min(num_cliques_min,nx.graph_number_of_cliques(G1)) # num_con_max=max(num_con_max,nx.number_connected_components(G1)) # num_con_min=min(num_con_min,nx.number_connected_components(G1)) # c=nx.degree_histogram(G1) # idxc=c.index(max(c)) # num_con_max=max(num_con_max,idxc+1) # num_con_min=min(num_con_min,idxc+1) # print idxc+1 # test.append(idxc+1) """ ##BA for n in range(len(n_set)): for m in range(len(m_set)): for rseed in range(len(rseed_set)): key+=1 G1=nx.read_edgelist("%s/%s-BA_%s_%s_%s.edgelist"%(OUTPUTDIR,key,n_set[n],m_set[m],rseed_set[rseed])) GraphSet.append(G1) """ nodenum_max=max(nodenum_max,G1.number_of_nodes()) nodenum_min=min(nodenum_min,G1.number_of_nodes()) edgenum_max=max(edgenum_max,G1.number_of_edges()) edgenum_min=min(edgenum_min,G1.number_of_edges()) avgdeg_max=max(avgdeg_max,np.mean(nx.degree_centrality(G1).values())) avgdeg_min=min(avgdeg_min,np.mean(nx.degree_centrality(G1).values())) avgbet_max=max(avgbet_max,np.mean(nx.betweenness_centrality(G1).values())) avgbet_min=min(avgbet_min,np.mean(nx.betweenness_centrality(G1).values())) # avgclo_max=max(avgclo_max,np.mean(nx.closeness_centrality(G1).values())) # avgclo_min=min(avgclo_min,np.mean(nx.closeness_centrality(G1).values())) avgclu_max=max(avgclu_max,nx.average_clustering(G1)) avgclu_min=min(avgclu_min,nx.average_clustering(G1)) # num_cliques_max=max(num_cliques_max,nx.graph_number_of_cliques(G1)) # num_cliques_min=min(num_cliques_min,nx.graph_number_of_cliques(G1)) # num_con_max=max(num_con_max,nx.number_connected_components(G1)) # num_con_min=min(num_con_min,nx.number_connected_components(G1)) # c=nx.degree_histogram(G1) # idxc=c.index(max(c)) # num_con_max=max(num_con_max,idxc+1) # num_con_min=min(num_con_min,idxc+1) # print idxc+1 # test.append(idxc+1) """ # print num_con_max,num_con_min # print num_cliques_max,num_cliques_min ,num_con_max,num_con_min # print nodenum_max,nodenum_min,edgenum_max,edgenum_min,avgdeg_max,avgdeg_min,avgbet_max,avgbet_min,avgclo_max,avgclo_min,avgclu_max,avgclu_min # print nodenum_max,nodenum_min,edgenum_max,edgenum_min,avgdeg_max,avgdeg_min,avgbet_max,avgbet_min,avgclu_max,avgclu_min # pl.plot(range(500),test) return GraphSet def statistics_info(GraphSet): x1set=[] x2set=[] x3set=[] x4set=[] for idx in range(len(GraphSet)): G=GraphSet[idx] nodenum=G.number_of_nodes() edgenum=G.number_of_edges() avgdeg=np.mean(nx.degree_centrality(G).values()) avgbet=np.mean(nx.betweenness_centrality(G).values()) x1=(nodenum-12.0)/(60.0-12.0) x2=(edgenum-11.0)/(579.0-11.0) x3=(avgdeg-0.0333)/(0.3948-0.0333) x4=(avgbet-0.0116)/(0.1683-0.0116) x1set.append(x1) x2set.append(x2) x3set.append(x3) x4set.append(x4) pl.figure(1) pl.hist(np.array(x1set)) pl.title('x1') pl.figure(2) pl.hist(np.array(x2set)) pl.title('x2') pl.figure(3) pl.hist(np.array(x3set)) pl.title('x3') pl.figure(4) pl.hist(np.array(x4set)) pl.title('x4') pl.show() if __name__ == "__main__": OUTPUTDIR="datasets/synthetic_datasets_2000" #gen_syn_ds(OUTPUTDIR) read_syn_ds(OUTPUTDIR) #statistics_info(read_syn_ds(OUTPUTDIR))

46.990033

146

0.602022

2,073

14,144

3.840328

0.097443

0.033162

0.026127

0.016581

0.862329

0.854164

0.851903

0.842482

0.822635

0

0.083936

0.26718

14,144

300

147

47.146667

0.684129

0.081731

0

0.603774

0

0.059304

0.041333

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null

0

0.075472

null

0.018868

0

null

0

1

0

null

0

1

0

7

c5ecaee4addc619678819d205e71153d4f372c1b

620

py

Python

eval_covid20cases_timm-regnetx_002_RandomBrightnessContrast.py

BrunoKrinski/segtool

cb604b5f38104c43a76450136e37c3d1c4b6d275

[ "MIT" ]

null

eval_covid20cases_timm-regnetx_002_RandomBrightnessContrast.py

BrunoKrinski/segtool

cb604b5f38104c43a76450136e37c3d1c4b6d275

[ "MIT" ]

null

eval_covid20cases_timm-regnetx_002_RandomBrightnessContrast.py

BrunoKrinski/segtool

cb604b5f38104c43a76450136e37c3d1c4b6d275

[ "MIT" ]

null

import os ls=["python main.py --configs configs/eval_covid20cases_unetplusplus_timm-regnetx_002_0_RandomBrightnessContrast.yml", "python main.py --configs configs/eval_covid20cases_unetplusplus_timm-regnetx_002_1_RandomBrightnessContrast.yml", "python main.py --configs configs/eval_covid20cases_unetplusplus_timm-regnetx_002_2_RandomBrightnessContrast.yml", "python main.py --configs configs/eval_covid20cases_unetplusplus_timm-regnetx_002_3_RandomBrightnessContrast.yml", "python main.py --configs configs/eval_covid20cases_unetplusplus_timm-regnetx_002_4_RandomBrightnessContrast.yml", ] for l in ls: os.system(l)

56.363636

118

0.866129

80

620

6.3375

0.3

0.098619

0.118343

0.187377

0.883629

0

0.050934

0.05

620

11

119

56.363636

0.809847

0

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0

1

0

false

0

0.111111

0

0.111111

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null

0

1

0

1

null

0

9

c5ef2e8c59a8186345c55bf98c78d7d1353e1d73

4,232

py

Python

test/test_modify_contact.py

AndreyTracevsky/AddressBook

8f27fb333ee18956c9a272c04b948aaec929e60e

[ "Apache-2.0" ]

null

test/test_modify_contact.py

AndreyTracevsky/AddressBook

8f27fb333ee18956c9a272c04b948aaec929e60e

[ "Apache-2.0" ]

null

test/test_modify_contact.py

AndreyTracevsky/AddressBook

8f27fb333ee18956c9a272c04b948aaec929e60e

[ "Apache-2.0" ]

null

from model.contact import Contact def test_modify_contact_firstname(app): if app.contact.count() == 0: app.contact.create_contact(Contact(firstname = "add contact", email = "test")) old_contacts = app.contact.get_contact_list() app.contact.modify_first_contact(Contact(firstname = "Vasilii")) new_contacts = app.contact.get_contact_list() assert len(old_contacts) == len(new_contacts) def test_modify_contact_middlename(app): if app.contact.count() == 0: app.contact.create_contact(Contact(firstname = "add contact", email = "test")) old_contacts = app.contact.get_contact_list() app.contact.modify_first_contact(Contact(middlename = "Vasilievich")) new_contacts = app.contact.get_contact_list() assert len(old_contacts) == len(new_contacts) def test_modify_contact_lastname(app): if app.contact.count() == 0: app.contact.create_contact(Contact(firstname = "add contact", email = "test")) old_contacts = app.contact.get_contact_list() app.contact.modify_first_contact(Contact(lastname="Vasilkov")) new_contacts = app.contact.get_contact_list() assert len(old_contacts) == len(new_contacts) def test_modify_contact_nickname(app): if app.contact.count() == 0: app.contact.create_contact(Contact(firstname = "add contact", email = "test")) old_contacts = app.contact.get_contact_list() app.contact.modify_first_contact(Contact(nickname = "ZverOK")) new_contacts = app.contact.get_contact_list() assert len(old_contacts) == len(new_contacts) def test_modify_contact_title(app): if app.contact.count() == 0: app.contact.create_contact(Contact(firstname = "add contact", email = "test")) old_contacts = app.contact.get_contact_list() app.contact.modify_first_contact(Contact(title = "Automated")) new_contacts = app.contact.get_contact_list() assert len(old_contacts) == len(new_contacts) def test_modify_contact_company(app): if app.contact.count() == 0: app.contact.create_contact(Contact(firstname = "add contact", email = "test")) old_contacts = app.contact.get_contact_list() app.contact.modify_first_contact(Contact(company = "Nike")) new_contacts = app.contact.get_contact_list() assert len(old_contacts) == len(new_contacts) def test_modify_contact_address(app): if app.contact.count() == 0: app.contact.create_contact(Contact(firstname = "add contact", email = "test")) old_contacts = app.contact.get_contact_list() app.contact.modify_first_contact(Contact(address = "M.Tanka 34/1")) new_contacts = app.contact.get_contact_list() assert len(old_contacts) == len(new_contacts) def test_modify_contact_phone_home(app): if app.contact.count() == 0: app.contact.create_contact(Contact(firstname = "add contact", email = "test")) old_contacts = app.contact.get_contact_list() app.contact.modify_first_contact(Contact(phone_home = "80171111111")) new_contacts = app.contact.get_contact_list() assert len(old_contacts) == len(new_contacts) def test_modify_contact_phone_mobile(app): if app.contact.count() == 0: app.contact.create_contact(Contact(firstname = "add contact", email = "test")) old_contacts = app.contact.get_contact_list() app.contact.modify_first_contact(Contact(phone_mobile = "80442222222")) new_contacts = app.contact.get_contact_list() assert len(old_contacts) == len(new_contacts) def test_modify_contact_phone_work(app): if app.contact.count() == 0: app.contact.create_contact(Contact(firstname = "add contact", email = "test")) old_contacts = app.contact.get_contact_list() app.contact.modify_first_contact(Contact(phone_work = "80443333333")) new_contacts = app.contact.get_contact_list() assert len(old_contacts) == len(new_contacts) def test_modify_contact_email(app): if app.contact.count() == 0: app.contact.create_contact(Contact(firstname = "add contact", email = "test")) old_contacts = app.contact.get_contact_list() app.contact.modify_first_contact(Contact(email = "tester@ya.ru")) new_contacts = app.contact.get_contact_list() assert len(old_contacts) == len(new_contacts)

41.90099

86

0.727788

566

4,232

5.159011

0.086572

0.188356

0.135616

0.158219

0.9

0

0.013009

0.146267

4,232

100

87

42.32

0.795184

0

0.705128

0

0.063091

0

0.141026

1

0.141026

false

0

0.012821

0

0.153846

0

null

0

1

0

1

0

null

0

7

c5fe0ac02cb8345f7a4aca525c25645d941801b5

14,267

py

Python

test/test_function/test_lambda_expression.py

takahish/lispy

8a6eaf209d1564d20b457cbac7428b78dc529241

[ "Apache-2.0" ]

4

2018-04-07T09:11:29.000Z

2021-11-20T03:02:07.000Z

test/test_function/test_lambda_expression.py

takahish/clispy

8a6eaf209d1564d20b457cbac7428b78dc529241

[ "Apache-2.0" ]

null

test/test_function/test_lambda_expression.py

takahish/clispy

8a6eaf209d1564d20b457cbac7428b78dc529241

[ "Apache-2.0" ]

null

# Copyright 2019 Takahiro Ishikawa. 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. # 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 unittest from clispy.evaluator import Evaluator from clispy.expander import Expander from clispy.function.lambda_expression import Lambda from clispy.package import PackageManager from clispy.parser import Parser from clispy.type import Integer class LambdaUnitTestCase(unittest.TestCase): """This test is to check clispy.function_.lambda_expression.Lambda. Lambda is base of user defined function and macro. """ def testLambda(self): """Checks an instance of Lambda and object official representation. """ # Makes an instance of Lambda. forms = Parser.parse('((x) (* x x x))') lambda_func = Lambda( forms, PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # Checks lambda function. self.assertTrue(callable(lambda_func)) # Checks official representation. self.assertRegex(str(lambda_func), r"<FUNCTION LAMBDA \{[0-9A-Z]+\}") def testLambda_properties(self): """Checks object properties. Properties are as follow, self.params: Parameters. self.forms: Body (forms). self.var_env: Lexical variable environment. self.func_env: Lexical function environment. self.macro_env: Lexical macro environment. """ # makes an instance of Lmabda. forms = Parser.parse('((x) (* x x x))') lambda_func = Lambda( forms, PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # Checks properties. # Checks lambda_func.params. self.assertEqual(lambda_func.params, ['X']) # Checks lambda_func.forms. self.assertEqual(str(lambda_func.forms), '(* X X X)') # Checks lambda_func lexical scope. self.assertTrue(lambda_func.var_env is PackageManager.current_package.env['VARIABLE']) self.assertTrue(lambda_func.func_env is PackageManager.current_package.env['FUNCTION']) self.assertTrue(lambda_func.macro_env is PackageManager.current_package.env['MACRO']) def testLambda_call(self): """Checks call method of Lambda. The body of Lmabda is expanded and executed when the method is called. """ # Makes an instance of Lambda. forms = Parser.parse('((x) (* x x x))') lambda_func = Lambda( forms, PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # Checks call. retval = lambda_func( Parser.parse('(2)'), PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # Checks return value. self.assertTrue(retval, Integer(8)) def testLambda_call_evaluate_argument(self): """Arguments are evaluated before the call method is executed. """ # Makes an instance of Lambda. forms = Parser.parse('((x) (* x x x))') lambda_func = Lambda( forms, PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # Checks call. retval = lambda_func( Parser.parse('((* 2 2 2))'), # an argument is expression. PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # Checks return value. self.assertTrue(retval, Integer(512)) def testLambda_call_expand_argument(self): """Arguments are expanded before the call method is executed. """ # Makes an instance of Lambda. forms = Parser.parse('((x) (* x x x))') lambda_func = Lambda( forms, PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # Define macro. forms = Parser.parse('(defmacro cube (x) `(* ,x ,x ,x))') exp = Expander.expand( forms, PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) Evaluator.eval( exp, PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # Checks call. retval = lambda_func( Parser.parse('((cube 2))'), # an argument is expression. PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # Checks return value. self.assertTrue(retval, Integer(512)) def testLambda_properties_optional_accessor(self): """Checks a propertie of optional accessor for arguments. """ # Makes an instance of Lmabda. forms = Parser.parse('((x &optional y) (* x x x))') lambda_func = Lambda( forms, PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # Checks properties. # Checks lambda_func.params. self.assertEqual(lambda_func.params, ['X', 'Y']) # Checks lambda_func.accessor_index. self.assertEqual(lambda_func.accessor_index['&OPTIONAL'], 1) def testLambda_properties_rest_accessor(self): """Checks a propertie of rest accessor for arguments. """ # Makes an instance of Lmabda. forms = Parser.parse('((x &rest y) (* x x x))') lambda_func = Lambda( forms, PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # Checks properties. # Checks lambda_func.params. self.assertEqual(lambda_func.params, ['X', 'Y']) # Checks lambda_func.accessor_index. self.assertEqual(lambda_func.accessor_index['&REST'], 1) def testLambda_properties_keyword_accessor(self): # Makes an instance of Lambda. forms = Parser.parse('((x &key y) (* x x x))') lambda_func = Lambda( forms, PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # Checks properties. # Checks lambda_func.params. self.assertEqual(lambda_func.params, ['X', 'Y']) # Checks lambda_func.accessor_index. self.assertEqual(lambda_func.accessor_index['&KEY'], 1) def testLambda_call_optional_argument(self): """Checks assigning optinal arguments. """ # Makes an instance of Lmabda. forms = Parser.parse('((x &optional y) (if y (* x x) (* x x x))))') lambda_func = Lambda( forms, PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # Checks call. # When an optional argumet is not given, Null() is set to an argument. retval = lambda_func( Parser.parse('(2)'), PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # retval is result of (* x x x). self.assertTrue(retval is Integer(8)) # When an optional argumet is given, this is set to an argument. retval = lambda_func( Parser.parse('(2 t)'), PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # retval is result of (* x x). self.assertTrue(retval is Integer(4)) def testLambda_call_optional_argument_with_default_value(self): """Checks assigning optinal arguments. """ # Makes an instance of Lmabda. forms = Parser.parse('((x &optional (y t)) (if y (* x x) (* x x x))))') lambda_func = Lambda( forms, PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # Checks call. # When an optional argumet is not given, Null() is set to an argument. retval = lambda_func( Parser.parse('(2)'), PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # retval is result of (* x x x). self.assertTrue(retval is Integer(4)) # When an optional argumet is given, this is set to an argument. retval = lambda_func( Parser.parse('(2 nil)'), PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # retval is result of (* x x). self.assertTrue(retval is Integer(8)) def testLambda_call_rest_argument(self): """Checks assigning rest arguments. """ # Makes an instance of Lmabda. forms = Parser.parse('((x &rest y) (cons x y))') lambda_func = Lambda( forms, PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # Checks call. # When an optional argumet is not given, Null() is set to an argument. retval = lambda_func( Parser.parse('(1 2 3 4 5)'), PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # retval is result of being given &rest parameter. self.assertEqual(str(retval), '(1 2 3 4 5)') def testLambda_call_keyword_argument(self): """Checks assigning keyword arguments. """ # Makes an instance of Lmabda. forms = Parser.parse('((x &key y) (if y (* x x) (* x x x))))') lambda_func = Lambda( forms, PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # Checks call. # When a keyword argumet is not given, Null() is set to an argument. retval = lambda_func( Parser.parse('(2)'), PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # retval is result of (* x x x). self.assertTrue(retval is Integer(8)) # When an keyword argumet is given, this is set to an argument. retval = lambda_func( Parser.parse('(2 :y t)'), PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # retval is result of (* x x). self.assertTrue(retval is Integer(4)) def testLambda_call_keyword_argument_with_default_value(self): """Checks assigning keyword arguments. """ # Makes an instance of Lmabda. forms = Parser.parse('((x &key (y t)) (if y (* x x) (* x x x))))') lambda_func = Lambda( forms, PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # Checks call. # When a keyword argumet is not given, Null() is set to an argument. retval = lambda_func( Parser.parse('(2)'), PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # retval is result of (* x x x). self.assertTrue(retval is Integer(4)) # When an keyword argumet is given, this is set to an argument. retval = lambda_func( Parser.parse('(2 :y nil)'), PackageManager.current_package.env['VARIABLE'], PackageManager.current_package.env['FUNCTION'], PackageManager.current_package.env['MACRO'] ) # retval is result of (* x x). self.assertTrue(retval is Integer(8))

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a8638ada9ca0da9ca27f9b77d1e3ea4c20a522da

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Python

scripts/main_12_binary_classification_00.py

AshivDhondea/ENSC813_Project

3606abff4b9e42282b5f7a6971f0554704bb037d

[ "MIT" ]

2

2020-05-01T17:00:37.000Z

2020-05-14T09:03:16.000Z

scripts/main_12_binary_classification_00.py

AshivDhondea/ENSC813_Project

3606abff4b9e42282b5f7a6971f0554704bb037d

[ "MIT" ]

null

scripts/main_12_binary_classification_00.py

AshivDhondea/ENSC813_Project

3606abff4b9e42282b5f7a6971f0554704bb037d

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Mon Apr 13 03:57:32 2020 Binary classification Ensembling the classifiers using normalized correlation combination Saving the results in tex files for easy importing in the report @author: Ashiv Hans Dhondea """ # --------------------------------------------------------------------------- # # Import the necessary packages # numpy for linear algebra, cv2 for image processing # glob and os to navigate directories import numpy as np import pandas as pd import os import sys from sklearn.metrics import classification_report from sklearn.metrics import confusion_matrix # --------------------------------------------------------------------------- # # Sort out utilities for file naming # get the name of this script file_name = os.path.basename(sys.argv[0]); if file_name[-3:] == '.py': script_name = file_name[:-3]; elif file_name[-3:] == '.ipynb': script_name = file_name[:-6]; else: script_name = 'main_xx'; full_name = script_name+'_'; # --------------------------------------------------------------------------- # # Classification task number 3 is Honda v. Toyota -> task = 2 names_1 = ['Audi','Lexus','Honda']; names_2 = ['BMW','Mercedes-Benz','Toyota']; """ Model 1 - Simple CNN implemented in 'main_08_binary_classification_00.py' Model 2 - implemented in 'main_09_binary_classification_00.py' Model 3 - implemented in 'main_10_binary_classification_00.py' Model 4 - implemented in 'main_11_binary_classification_00.py' """ script_names = ['main_08_binary_classification_00','main_09_binary_classification_00','main_10_binary_classification_00','main_11_binary_classification_00']; model_names = ['__model_1','__model_2','__model_3','__model_4']; num_comparisons = len(names_2); num_methods = len(model_names); # --------------------------------------------------------------------------- # # Audi vs BMW classification comparison = 0; print('Classifying %s vs. %s' %(names_1[comparison],names_2[comparison])) model = 0; y_test_1 = np.load(script_names[0]+'_'+names_1[comparison]+'_'+names_2[comparison]+model_names[model]+'y_test.npy') y_pred_test_continuous_arr_1 = np.zeros([num_methods,len(y_test_1)],dtype=np.float64); y_pred_train_continuous_1 = np.load(script_names[0]+'_'+names_1[comparison]+'_'+names_2[comparison]+model_names[model]+'y_pred_train_continuous.npy') y_pred_train_continuous_arr_1 = np.zeros([num_methods,len(y_pred_train_continuous_1)],dtype=np.float64); y_train_1 = np.load(script_names[0]+'_'+names_1[comparison]+'_'+names_2[comparison]+model_names[model]+'y_train.npy') for script in range(0,len(script_names)): npy_file_name = script_names[script]+'_'+names_1[comparison]+'_'+names_2[comparison]+model_names[script]; y_pred_test_continuous_arr_1[script,:] = np.ravel(np.load(npy_file_name+'y_pred_test_continuous.npy')); y_pred_train_continuous_arr_1[script,:] = np.ravel(np.load(npy_file_name+'y_pred_train_continuous.npy')); r_y_pred_train_1 = np.dot(y_train_1.astype(np.float32), y_pred_train_continuous_arr_1[0,:])/len(y_pred_train_continuous_arr_1[0,:]); r_y_pred_train_2 = np.dot(y_train_1.astype(np.float32), y_pred_train_continuous_arr_1[1,:])/len(y_pred_train_continuous_arr_1[1,:]); r_y_pred_train_3 = np.dot(y_train_1.astype(np.float32), y_pred_train_continuous_arr_1[2,:])/len(y_pred_train_continuous_arr_1[2,:]); r_y_pred_train_4 = np.dot(y_train_1.astype(np.float32), y_pred_train_continuous_arr_1[3,:])/len(y_pred_train_continuous_arr_1[3,:]); # Correlation vector r_mat = np.array([[r_y_pred_train_1],[r_y_pred_train_2],[r_y_pred_train_3],[r_y_pred_train_4]]) # normalized correlation vector a_weights = r_mat/np.sum(r_mat); # binarize predictions y_pred_test_1_b = (y_pred_test_continuous_arr_1[0,:] > 0.5).astype(int) y_pred_test_2_b = (y_pred_test_continuous_arr_1[1,:] > 0.5).astype(int) y_pred_test_3_b = (y_pred_test_continuous_arr_1[2,:] > 0.5).astype(int) y_pred_test_4_b = (y_pred_test_continuous_arr_1[3,:] > 0.5).astype(int) # model average prob_arr = np.transpose(y_pred_test_continuous_arr_1); y_pred_test_continuous_mean = np.dot(prob_arr,a_weights); y_pred_test_mean_b = (y_pred_test_continuous_mean > 0.5).astype(int); # compute accuracies y_pred_test_1_b_acc = np.mean(y_pred_test_1_b.ravel() == y_test_1) y_pred_test_2_b_acc = np.mean(y_pred_test_2_b.ravel() == y_test_1) y_pred_test_3_b_acc = np.mean(y_pred_test_3_b.ravel() == y_test_1) y_pred_test_4_b_acc = np.mean(y_pred_test_4_b.ravel() == y_test_1) y_pred_test_mean_acc = np.mean(y_pred_test_mean_b.ravel() == y_test_1) columns_names = ['Accuracy']; method_names = ['Model 1','Model 2','Model 3','Model 4','Ensemble']; data_results = np.array([y_pred_test_1_b_acc,y_pred_test_2_b_acc,y_pred_test_3_b_acc,y_pred_test_4_b_acc,y_pred_test_mean_acc]) df_table_acc = pd.DataFrame(data = data_results,index=method_names, columns=columns_names) print('Binary classification task %d' %(comparison+1)) print(df_table_acc) results_table_name = full_name+'_'+names_1[comparison]+'_'+names_2[comparison]; with open(results_table_name+'_accuracy.tex', 'w') as texfile: texfile.write(df_table_acc.to_latex()) report = classification_report(y_test_1,y_pred_test_1_b, target_names=[names_1[comparison],names_2[comparison]], output_dict=True); classification_report_df = pd.DataFrame(report).transpose(); with open(results_table_name+method_names[0]+'.tex', 'w') as texfile: texfile.write(classification_report_df.to_latex()) report = classification_report(y_test_1,y_pred_test_2_b, target_names=[names_1[comparison],names_2[comparison]], output_dict=True); classification_report_df = pd.DataFrame(report).transpose(); with open(results_table_name+method_names[1]+'.tex', 'w') as texfile: texfile.write(classification_report_df.to_latex()) report = classification_report(y_test_1,y_pred_test_3_b, target_names=[names_1[comparison],names_2[comparison]], output_dict=True); classification_report_df = pd.DataFrame(report).transpose(); with open(results_table_name+method_names[2]+'.tex', 'w') as texfile: texfile.write(classification_report_df.to_latex()) report = classification_report(y_test_1,y_pred_test_4_b, target_names=[names_1[comparison],names_2[comparison]], output_dict=True); classification_report_df = pd.DataFrame(report).transpose(); with open(results_table_name+method_names[3]+'.tex', 'w') as texfile: texfile.write(classification_report_df.to_latex()) report = classification_report(y_test_1,y_pred_test_mean_b, target_names=[names_1[comparison],names_2[comparison]], output_dict=True); classification_report_df = pd.DataFrame(report).transpose(); with open(results_table_name+method_names[4]+'.tex', 'w') as texfile: texfile.write(classification_report_df.to_latex()) confusion_matrix_test = confusion_matrix(y_test_1,y_pred_test_mean_b); confusion_matrix_test_df = pd.DataFrame(confusion_matrix_test).transpose(); with open(results_table_name+method_names[4]+'_ensemble_confusion_matrix.tex', 'w') as texfile: texfile.write(confusion_matrix_test_df.to_latex()); # --------------------------------------------------------------------------- # # Lexus vs Mercedes-Benz classification comparison = 1; print('Classifying %s vs. %s' %(names_1[comparison],names_2[comparison])) model = 0; y_test_1 = np.load(script_names[0]+'_'+names_1[comparison]+'_'+names_2[comparison]+model_names[model]+'y_test.npy') y_pred_test_continuous_arr_1 = np.zeros([num_methods,len(y_test_1)],dtype=np.float64); y_pred_train_continuous_1 = np.load(script_names[0]+'_'+names_1[comparison]+'_'+names_2[comparison]+model_names[model]+'y_pred_train_continuous.npy') y_pred_train_continuous_arr_1 = np.zeros([num_methods,len(y_pred_train_continuous_1)],dtype=np.float64); y_train_1 = np.load(script_names[0]+'_'+names_1[comparison]+'_'+names_2[comparison]+model_names[model]+'y_train.npy') for script in range(0,len(script_names)): npy_file_name = script_names[script]+'_'+names_1[comparison]+'_'+names_2[comparison]+model_names[script]; y_pred_test_continuous_arr_1[script,:] = np.ravel(np.load(npy_file_name+'y_pred_test_continuous.npy')); y_pred_train_continuous_arr_1[script,:] = np.ravel(np.load(npy_file_name+'y_pred_train_continuous.npy')); r_y_pred_train_1 = np.dot(y_train_1.astype(np.float32), y_pred_train_continuous_arr_1[0,:])/len(y_pred_train_continuous_arr_1[0,:]); r_y_pred_train_2 = np.dot(y_train_1.astype(np.float32), y_pred_train_continuous_arr_1[1,:])/len(y_pred_train_continuous_arr_1[1,:]); r_y_pred_train_3 = np.dot(y_train_1.astype(np.float32), y_pred_train_continuous_arr_1[2,:])/len(y_pred_train_continuous_arr_1[2,:]); r_y_pred_train_4 = np.dot(y_train_1.astype(np.float32), y_pred_train_continuous_arr_1[3,:])/len(y_pred_train_continuous_arr_1[3,:]); # Correlation vector r_mat = np.array([[r_y_pred_train_1],[r_y_pred_train_2],[r_y_pred_train_3],[r_y_pred_train_4]]) # normalized correlation vector a_weights = r_mat/np.sum(r_mat); # binarize predictions y_pred_test_1_b = (y_pred_test_continuous_arr_1[0,:] > 0.5).astype(int) y_pred_test_2_b = (y_pred_test_continuous_arr_1[1,:] > 0.5).astype(int) y_pred_test_3_b = (y_pred_test_continuous_arr_1[2,:] > 0.5).astype(int) y_pred_test_4_b = (y_pred_test_continuous_arr_1[3,:] > 0.5).astype(int) # model average prob_arr = np.transpose(y_pred_test_continuous_arr_1); y_pred_test_continuous_mean = np.dot(prob_arr,a_weights); y_pred_test_mean_b = (y_pred_test_continuous_mean > 0.5).astype(int); # compute accuracies y_pred_test_1_b_acc = np.mean(y_pred_test_1_b.ravel() == y_test_1) y_pred_test_2_b_acc = np.mean(y_pred_test_2_b.ravel() == y_test_1) y_pred_test_3_b_acc = np.mean(y_pred_test_3_b.ravel() == y_test_1) y_pred_test_4_b_acc = np.mean(y_pred_test_4_b.ravel() == y_test_1) y_pred_test_mean_acc = np.mean(y_pred_test_mean_b.ravel() == y_test_1) columns_names = ['Accuracy']; method_names = ['Model 1','Model 2','Model 3','Model 4','Ensemble']; data_results = np.array([y_pred_test_1_b_acc,y_pred_test_2_b_acc,y_pred_test_3_b_acc,y_pred_test_4_b_acc,y_pred_test_mean_acc]) df_table_acc = pd.DataFrame(data = data_results,index=method_names, columns=columns_names) print('Binary classification task %d' %(comparison+1)) print(df_table_acc) results_table_name = full_name+'_'+names_1[comparison]+'_'+names_2[comparison]; with open(results_table_name+'_accuracy.tex', 'w') as texfile: texfile.write(df_table_acc.to_latex()) report = classification_report(y_test_1,y_pred_test_1_b, target_names=[names_1[comparison],names_2[comparison]], output_dict=True); classification_report_df = pd.DataFrame(report).transpose(); with open(results_table_name+method_names[0]+'.tex', 'w') as texfile: texfile.write(classification_report_df.to_latex()) report = classification_report(y_test_1,y_pred_test_2_b, target_names=[names_1[comparison],names_2[comparison]], output_dict=True); classification_report_df = pd.DataFrame(report).transpose(); with open(results_table_name+method_names[1]+'.tex', 'w') as texfile: texfile.write(classification_report_df.to_latex()) report = classification_report(y_test_1,y_pred_test_3_b, target_names=[names_1[comparison],names_2[comparison]], output_dict=True); classification_report_df = pd.DataFrame(report).transpose(); with open(results_table_name+method_names[2]+'.tex', 'w') as texfile: texfile.write(classification_report_df.to_latex()) report = classification_report(y_test_1,y_pred_test_4_b, target_names=[names_1[comparison],names_2[comparison]], output_dict=True); classification_report_df = pd.DataFrame(report).transpose(); with open(results_table_name+method_names[3]+'.tex', 'w') as texfile: texfile.write(classification_report_df.to_latex()) report = classification_report(y_test_1,y_pred_test_mean_b, target_names=[names_1[comparison],names_2[comparison]], output_dict=True); classification_report_df = pd.DataFrame(report).transpose(); with open(results_table_name+method_names[4]+'.tex', 'w') as texfile: texfile.write(classification_report_df.to_latex()) confusion_matrix_test = confusion_matrix(y_test_1,y_pred_test_mean_b); confusion_matrix_test_df = pd.DataFrame(confusion_matrix_test).transpose(); with open(results_table_name+method_names[4]+'_ensemble_confusion_matrix.tex', 'w') as texfile: texfile.write(confusion_matrix_test_df.to_latex()); # --------------------------------------------------------------------------- # # Honda vs Toyota classification comparison = 2; model = 0; print('Classifying %s vs. %s' %(names_1[comparison],names_2[comparison])) y_test_1 = np.load(script_names[0]+'_'+names_1[comparison]+'_'+names_2[comparison]+model_names[model]+'y_test.npy') y_pred_test_continuous_arr_1 = np.zeros([num_methods,len(y_test_1)],dtype=np.float64); y_pred_train_continuous_1 = np.load(script_names[0]+'_'+names_1[comparison]+'_'+names_2[comparison]+model_names[model]+'y_pred_train_continuous.npy') y_pred_train_continuous_arr_1 = np.zeros([num_methods,len(y_pred_train_continuous_1)],dtype=np.float64); y_train_1 = np.load(script_names[0]+'_'+names_1[comparison]+'_'+names_2[comparison]+model_names[model]+'y_train.npy') for script in range(0,len(script_names)): npy_file_name = script_names[script]+'_'+names_1[comparison]+'_'+names_2[comparison]+model_names[script]; y_pred_test_continuous_arr_1[script,:] = np.ravel(np.load(npy_file_name+'y_pred_test_continuous.npy')); y_pred_train_continuous_arr_1[script,:] = np.ravel(np.load(npy_file_name+'y_pred_train_continuous.npy')); r_y_pred_train_1 = np.dot(y_train_1.astype(np.float32), y_pred_train_continuous_arr_1[0,:])/len(y_pred_train_continuous_arr_1[0,:]); r_y_pred_train_2 = np.dot(y_train_1.astype(np.float32), y_pred_train_continuous_arr_1[1,:])/len(y_pred_train_continuous_arr_1[1,:]); r_y_pred_train_3 = np.dot(y_train_1.astype(np.float32), y_pred_train_continuous_arr_1[2,:])/len(y_pred_train_continuous_arr_1[2,:]); r_y_pred_train_4 = np.dot(y_train_1.astype(np.float32), y_pred_train_continuous_arr_1[3,:])/len(y_pred_train_continuous_arr_1[3,:]); # Correlation vector r_mat = np.array([[r_y_pred_train_1],[r_y_pred_train_2],[r_y_pred_train_3],[r_y_pred_train_4]]) # normalized correlation vector a_weights = r_mat/np.sum(r_mat); # binarize predictions y_pred_test_1_b = (y_pred_test_continuous_arr_1[0,:] > 0.5).astype(int) y_pred_test_2_b = (y_pred_test_continuous_arr_1[1,:] > 0.5).astype(int) y_pred_test_3_b = (y_pred_test_continuous_arr_1[2,:] > 0.5).astype(int) y_pred_test_4_b = (y_pred_test_continuous_arr_1[3,:] > 0.5).astype(int) # model average prob_arr = np.transpose(y_pred_test_continuous_arr_1); y_pred_test_continuous_mean = np.dot(prob_arr,a_weights); y_pred_test_mean_b = (y_pred_test_continuous_mean > 0.5).astype(int); # compute accuracies y_pred_test_1_b_acc = np.mean(y_pred_test_1_b.ravel() == y_test_1) y_pred_test_2_b_acc = np.mean(y_pred_test_2_b.ravel() == y_test_1) y_pred_test_3_b_acc = np.mean(y_pred_test_3_b.ravel() == y_test_1) y_pred_test_4_b_acc = np.mean(y_pred_test_4_b.ravel() == y_test_1) y_pred_test_mean_acc = np.mean(y_pred_test_mean_b.ravel() == y_test_1) columns_names = ['Accuracy']; method_names = ['Model 1','Model 2','Model 3','Model 4','Ensemble']; data_results = np.array([y_pred_test_1_b_acc,y_pred_test_2_b_acc,y_pred_test_3_b_acc,y_pred_test_4_b_acc,y_pred_test_mean_acc]) df_table_acc = pd.DataFrame(data = data_results,index=method_names, columns=columns_names) print('Binary classification task %d' %(comparison+1)) print(df_table_acc) results_table_name = full_name+'_'+names_1[comparison]+'_'+names_2[comparison]; with open(results_table_name+'_accuracy.tex', 'w') as texfile: texfile.write(df_table_acc.to_latex()) with open(results_table_name+'_accuracy.tex', 'w') as texfile: texfile.write(df_table_acc.to_latex()) report = classification_report(y_test_1,y_pred_test_1_b, target_names=[names_1[comparison],names_2[comparison]], output_dict=True); classification_report_df = pd.DataFrame(report).transpose(); with open(results_table_name+method_names[0]+'.tex', 'w') as texfile: texfile.write(classification_report_df.to_latex()) report = classification_report(y_test_1,y_pred_test_2_b, target_names=[names_1[comparison],names_2[comparison]], output_dict=True); classification_report_df = pd.DataFrame(report).transpose(); with open(results_table_name+method_names[1]+'.tex', 'w') as texfile: texfile.write(classification_report_df.to_latex()) report = classification_report(y_test_1,y_pred_test_3_b, target_names=[names_1[comparison],names_2[comparison]], output_dict=True); classification_report_df = pd.DataFrame(report).transpose(); with open(results_table_name+method_names[2]+'.tex', 'w') as texfile: texfile.write(classification_report_df.to_latex()) report = classification_report(y_test_1,y_pred_test_4_b, target_names=[names_1[comparison],names_2[comparison]], output_dict=True); classification_report_df = pd.DataFrame(report).transpose(); with open(results_table_name+method_names[3]+'.tex', 'w') as texfile: texfile.write(classification_report_df.to_latex()) report = classification_report(y_test_1,y_pred_test_mean_b, target_names=[names_1[comparison],names_2[comparison]], output_dict=True); classification_report_df = pd.DataFrame(report).transpose(); with open(results_table_name+method_names[4]+'.tex', 'w') as texfile: texfile.write(classification_report_df.to_latex()) confusion_matrix_test = confusion_matrix(y_test_1,y_pred_test_mean_b); confusion_matrix_test_df = pd.DataFrame(confusion_matrix_test).transpose(); with open(results_table_name+method_names[4]+'_ensemble_confusion_matrix.tex', 'w') as texfile: texfile.write(confusion_matrix_test_df.to_latex()); # --------------------------------------------------------------------------- #

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Python

gym/common/protobuf/vnf_bd_pb2.py

raphaelvrosa/gym

f1d20b444050ab0f445681ae39e93ffd44610f21

[ "Apache-2.0" ]

3

2020-03-13T20:18:22.000Z

2021-03-21T20:23:00.000Z

gym/common/protobuf/vnf_bd_pb2.py

raphaelvrosa/gym

f1d20b444050ab0f445681ae39e93ffd44610f21

[ "Apache-2.0" ]

null

gym/common/protobuf/vnf_bd_pb2.py

raphaelvrosa/gym

f1d20b444050ab0f445681ae39e93ffd44610f21

[ "Apache-2.0" ]

1

2020-12-02T18:06:47.000Z

# -*- coding: utf-8 -*- # Generated by the protocol buffer compiler. 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_SCENARIO_NODE_LIFECYCLE_WORKFLOWS = _descriptor.EnumDescriptor( name='Workflows', full_name='gym.Scenario.Node.Lifecycle.Workflows', filename=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key, values=[ _descriptor.EnumValueDescriptor( name='VNFBDWORKFLOWS_UNSET', index=0, number=0, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), _descriptor.EnumValueDescriptor( name='create', index=1, number=1, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), _descriptor.EnumValueDescriptor( name='configure', index=2, number=2, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), _descriptor.EnumValueDescriptor( name='start', index=3, number=3, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), _descriptor.EnumValueDescriptor( name='stop', index=4, number=4, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), _descriptor.EnumValueDescriptor( name='delete', index=5, number=5, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), _descriptor.EnumValueDescriptor( name='custom', index=6, number=6, serialized_options=None, type=None, create_key=_descriptor._internal_create_key), ], containing_type=None, serialized_options=None, serialized_start=960, serialized_end=1069, ) _sym_db.RegisterEnumDescriptor(_SCENARIO_NODE_LIFECYCLE_WORKFLOWS) _SCENARIO_LINK = _descriptor.Descriptor( name='Link', full_name='gym.Scenario.Link', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='id', full_name='gym.Scenario.Link.id', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='name', full_name='gym.Scenario.Link.name', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='network', full_name='gym.Scenario.Link.network', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='type', full_name='gym.Scenario.Link.type', index=3, number=4, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='connection_points', full_name='gym.Scenario.Link.connection_points', index=4, number=5, type=9, cpp_type=9, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=163, serialized_end=253, ) _SCENARIO_NODE_CONNECTIONPOINT = _descriptor.Descriptor( name='ConnectionPoint', full_name='gym.Scenario.Node.ConnectionPoint', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='id', full_name='gym.Scenario.Node.ConnectionPoint.id', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='address', full_name='gym.Scenario.Node.ConnectionPoint.address', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='interface', full_name='gym.Scenario.Node.ConnectionPoint.interface', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='type', full_name='gym.Scenario.Node.ConnectionPoint.type', index=3, number=4, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=569, serialized_end=648, ) _SCENARIO_NODE_LIFECYCLE_PARAMETER = _descriptor.Descriptor( name='Parameter', full_name='gym.Scenario.Node.Lifecycle.Parameter', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='input', full_name='gym.Scenario.Node.Lifecycle.Parameter.input', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.Scenario.Node.Lifecycle.Parameter.value', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=826, serialized_end=867, ) _SCENARIO_NODE_LIFECYCLE_PARAMETERSENTRY = _descriptor.Descriptor( name='ParametersEntry', full_name='gym.Scenario.Node.Lifecycle.ParametersEntry', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='key', full_name='gym.Scenario.Node.Lifecycle.ParametersEntry.key', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.Scenario.Node.Lifecycle.ParametersEntry.value', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=b'8\001', is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=869, serialized_end=958, ) _SCENARIO_NODE_LIFECYCLE = _descriptor.Descriptor( name='Lifecycle', full_name='gym.Scenario.Node.Lifecycle', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='name', full_name='gym.Scenario.Node.Lifecycle.name', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='implementation', full_name='gym.Scenario.Node.Lifecycle.implementation', index=1, number=2, type=9, cpp_type=9, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='parameters', full_name='gym.Scenario.Node.Lifecycle.parameters', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='workflow', full_name='gym.Scenario.Node.Lifecycle.workflow', index=3, number=4, type=14, cpp_type=8, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[_SCENARIO_NODE_LIFECYCLE_PARAMETER, _SCENARIO_NODE_LIFECYCLE_PARAMETERSENTRY, ], enum_types=[ _SCENARIO_NODE_LIFECYCLE_WORKFLOWS, ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=651, serialized_end=1069, ) _SCENARIO_NODE_RELATIONSHIP = _descriptor.Descriptor( name='Relationship', full_name='gym.Scenario.Node.Relationship', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='name', full_name='gym.Scenario.Node.Relationship.name', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='target', full_name='gym.Scenario.Node.Relationship.target', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='type', full_name='gym.Scenario.Node.Relationship.type', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1071, serialized_end=1129, ) _SCENARIO_NODE_RESOURCES_CPU = _descriptor.Descriptor( name='Cpu', full_name='gym.Scenario.Node.Resources.Cpu', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='cpu_bw', full_name='gym.Scenario.Node.Resources.Cpu.cpu_bw', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='pinning', full_name='gym.Scenario.Node.Resources.Cpu.pinning', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='vcpus', full_name='gym.Scenario.Node.Resources.Cpu.vcpus', index=2, number=3, type=4, cpp_type=4, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1300, serialized_end=1353, ) _SCENARIO_NODE_RESOURCES_MEMORY = _descriptor.Descriptor( name='Memory', full_name='gym.Scenario.Node.Resources.Memory', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='size', full_name='gym.Scenario.Node.Resources.Memory.size', index=0, number=1, type=4, cpp_type=4, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='unit', full_name='gym.Scenario.Node.Resources.Memory.unit', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1355, serialized_end=1391, ) _SCENARIO_NODE_RESOURCES_STORAGE = _descriptor.Descriptor( name='Storage', full_name='gym.Scenario.Node.Resources.Storage', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='size', full_name='gym.Scenario.Node.Resources.Storage.size', index=0, number=1, type=4, cpp_type=4, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='unit', full_name='gym.Scenario.Node.Resources.Storage.unit', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='volumes', full_name='gym.Scenario.Node.Resources.Storage.volumes', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1393, serialized_end=1447, ) _SCENARIO_NODE_RESOURCES = _descriptor.Descriptor( name='Resources', full_name='gym.Scenario.Node.Resources', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='cpu', full_name='gym.Scenario.Node.Resources.cpu', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='memory', full_name='gym.Scenario.Node.Resources.memory', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='storage', full_name='gym.Scenario.Node.Resources.storage', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[_SCENARIO_NODE_RESOURCES_CPU, _SCENARIO_NODE_RESOURCES_MEMORY, _SCENARIO_NODE_RESOURCES_STORAGE, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1132, serialized_end=1447, ) _SCENARIO_NODE_CONNECTIONPOINTSENTRY = _descriptor.Descriptor( name='ConnectionPointsEntry', full_name='gym.Scenario.Node.ConnectionPointsEntry', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='key', full_name='gym.Scenario.Node.ConnectionPointsEntry.key', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.Scenario.Node.ConnectionPointsEntry.value', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=b'8\001', is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1449, serialized_end=1540, ) _SCENARIO_NODE_LIFECYCLEENTRY = _descriptor.Descriptor( name='LifecycleEntry', full_name='gym.Scenario.Node.LifecycleEntry', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='key', full_name='gym.Scenario.Node.LifecycleEntry.key', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.Scenario.Node.LifecycleEntry.value', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=b'8\001', is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1542, serialized_end=1620, ) _SCENARIO_NODE_RELATIONSHIPSENTRY = _descriptor.Descriptor( name='RelationshipsEntry', full_name='gym.Scenario.Node.RelationshipsEntry', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='key', full_name='gym.Scenario.Node.RelationshipsEntry.key', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.Scenario.Node.RelationshipsEntry.value', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=b'8\001', is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1622, serialized_end=1707, ) _SCENARIO_NODE = _descriptor.Descriptor( name='Node', full_name='gym.Scenario.Node', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='id', full_name='gym.Scenario.Node.id', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='image', full_name='gym.Scenario.Node.image', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='format', full_name='gym.Scenario.Node.format', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='type', full_name='gym.Scenario.Node.type', index=3, number=4, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='role', full_name='gym.Scenario.Node.role', index=4, number=5, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='resources', full_name='gym.Scenario.Node.resources', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='connection_points', full_name='gym.Scenario.Node.connection_points', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='lifecycle', full_name='gym.Scenario.Node.lifecycle', index=7, number=8, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='relationships', full_name='gym.Scenario.Node.relationships', index=8, number=9, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[_SCENARIO_NODE_CONNECTIONPOINT, _SCENARIO_NODE_LIFECYCLE, _SCENARIO_NODE_RELATIONSHIP, _SCENARIO_NODE_RESOURCES, _SCENARIO_NODE_CONNECTIONPOINTSENTRY, _SCENARIO_NODE_LIFECYCLEENTRY, _SCENARIO_NODE_RELATIONSHIPSENTRY, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=256, serialized_end=1707, ) _SCENARIO_POLICY = _descriptor.Descriptor( name='Policy', full_name='gym.Scenario.Policy', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='name', full_name='gym.Scenario.Policy.name', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='action', full_name='gym.Scenario.Policy.action', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='targets', full_name='gym.Scenario.Policy.targets', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='type', full_name='gym.Scenario.Policy.type', index=3, number=4, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1709, serialized_end=1778, ) _SCENARIO_LINKSENTRY = _descriptor.Descriptor( name='LinksEntry', full_name='gym.Scenario.LinksEntry', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='key', full_name='gym.Scenario.LinksEntry.key', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.Scenario.LinksEntry.value', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=b'8\001', is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1780, serialized_end=1844, ) _SCENARIO_NODESENTRY = _descriptor.Descriptor( name='NodesEntry', full_name='gym.Scenario.NodesEntry', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='key', full_name='gym.Scenario.NodesEntry.key', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.Scenario.NodesEntry.value', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=b'8\001', is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1846, serialized_end=1910, ) _SCENARIO_POLICIESENTRY = _descriptor.Descriptor( name='PoliciesEntry', full_name='gym.Scenario.PoliciesEntry', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='key', full_name='gym.Scenario.PoliciesEntry.key', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.Scenario.PoliciesEntry.value', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=b'8\001', is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1912, serialized_end=1981, ) _SCENARIO = _descriptor.Descriptor( name='Scenario', full_name='gym.Scenario', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='links', full_name='gym.Scenario.links', index=0, number=1, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='nodes', full_name='gym.Scenario.nodes', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='policies', full_name='gym.Scenario.policies', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[_SCENARIO_LINK, _SCENARIO_NODE, _SCENARIO_POLICY, _SCENARIO_LINKSENTRY, _SCENARIO_NODESENTRY, _SCENARIO_POLICIESENTRY, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=22, serialized_end=1981, ) _VNFBD_EXPERIMENTS = _descriptor.Descriptor( name='Experiments', full_name='gym.VnfBd.Experiments', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='tests', full_name='gym.VnfBd.Experiments.tests', index=0, number=1, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='trials', full_name='gym.VnfBd.Experiments.trials', index=1, number=2, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2196, serialized_end=2240, ) _VNFBD_PROCEEDINGS_ATTRIBUTE = _descriptor.Descriptor( name='Attribute', full_name='gym.VnfBd.Proceedings.Attribute', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='name', full_name='gym.VnfBd.Proceedings.Attribute.name', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.VnfBd.Proceedings.Attribute.value', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2426, serialized_end=2466, ) _VNFBD_PROCEEDINGS_AGENT_PROBER_PARAMETER = _descriptor.Descriptor( name='Parameter', full_name='gym.VnfBd.Proceedings.Agent.Prober.Parameter', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='input', full_name='gym.VnfBd.Proceedings.Agent.Prober.Parameter.input', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.VnfBd.Proceedings.Agent.Prober.Parameter.value', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=826, serialized_end=867, ) _VNFBD_PROCEEDINGS_AGENT_PROBER_SCHED = _descriptor.Descriptor( name='Sched', full_name='gym.VnfBd.Proceedings.Agent.Prober.Sched', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='from', full_name='gym.VnfBd.Proceedings.Agent.Prober.Sched.from', index=0, number=1, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='until', full_name='gym.VnfBd.Proceedings.Agent.Prober.Sched.until', index=1, number=2, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='duration', full_name='gym.VnfBd.Proceedings.Agent.Prober.Sched.duration', index=2, number=3, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='interval', full_name='gym.VnfBd.Proceedings.Agent.Prober.Sched.interval', index=3, number=4, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='repeat', full_name='gym.VnfBd.Proceedings.Agent.Prober.Sched.repeat', index=4, number=5, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2796, serialized_end=2884, ) _VNFBD_PROCEEDINGS_AGENT_PROBER_PARAMETERSENTRY = _descriptor.Descriptor( name='ParametersEntry', full_name='gym.VnfBd.Proceedings.Agent.Prober.ParametersEntry', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='key', full_name='gym.VnfBd.Proceedings.Agent.Prober.ParametersEntry.key', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.VnfBd.Proceedings.Agent.Prober.ParametersEntry.value', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=b'8\001', is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2886, serialized_end=2982, ) _VNFBD_PROCEEDINGS_AGENT_PROBER = _descriptor.Descriptor( name='Prober', full_name='gym.VnfBd.Proceedings.Agent.Prober', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='id', full_name='gym.VnfBd.Proceedings.Agent.Prober.id', index=0, number=1, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='instances', full_name='gym.VnfBd.Proceedings.Agent.Prober.instances', index=1, number=2, type=4, cpp_type=4, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='name', full_name='gym.VnfBd.Proceedings.Agent.Prober.name', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='parameters', full_name='gym.VnfBd.Proceedings.Agent.Prober.parameters', index=3, number=4, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='sched', full_name='gym.VnfBd.Proceedings.Agent.Prober.sched', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[_VNFBD_PROCEEDINGS_AGENT_PROBER_PARAMETER, _VNFBD_PROCEEDINGS_AGENT_PROBER_SCHED, _VNFBD_PROCEEDINGS_AGENT_PROBER_PARAMETERSENTRY, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2567, serialized_end=2982, ) _VNFBD_PROCEEDINGS_AGENT_PROBERSENTRY = _descriptor.Descriptor( name='ProbersEntry', full_name='gym.VnfBd.Proceedings.Agent.ProbersEntry', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='key', full_name='gym.VnfBd.Proceedings.Agent.ProbersEntry.key', index=0, number=1, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.VnfBd.Proceedings.Agent.ProbersEntry.value', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=b'8\001', is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2984, serialized_end=3067, ) _VNFBD_PROCEEDINGS_AGENT = _descriptor.Descriptor( name='Agent', full_name='gym.VnfBd.Proceedings.Agent', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='uuid', full_name='gym.VnfBd.Proceedings.Agent.uuid', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='name', full_name='gym.VnfBd.Proceedings.Agent.name', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='probers', full_name='gym.VnfBd.Proceedings.Agent.probers', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[_VNFBD_PROCEEDINGS_AGENT_PROBER, _VNFBD_PROCEEDINGS_AGENT_PROBERSENTRY, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2469, serialized_end=3067, ) _VNFBD_PROCEEDINGS_MONITOR_HOST = _descriptor.Descriptor( name='Host', full_name='gym.VnfBd.Proceedings.Monitor.Host', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='node', full_name='gym.VnfBd.Proceedings.Monitor.Host.node', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='setting', full_name='gym.VnfBd.Proceedings.Monitor.Host.setting', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=3175, serialized_end=3212, ) _VNFBD_PROCEEDINGS_MONITOR_LISTENER_PARAMETER = _descriptor.Descriptor( name='Parameter', full_name='gym.VnfBd.Proceedings.Monitor.Listener.Parameter', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='input', full_name='gym.VnfBd.Proceedings.Monitor.Listener.Parameter.input', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.VnfBd.Proceedings.Monitor.Listener.Parameter.value', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=826, serialized_end=867, ) _VNFBD_PROCEEDINGS_MONITOR_LISTENER_SCHED = _descriptor.Descriptor( name='Sched', full_name='gym.VnfBd.Proceedings.Monitor.Listener.Sched', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='from', full_name='gym.VnfBd.Proceedings.Monitor.Listener.Sched.from', index=0, number=1, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='until', full_name='gym.VnfBd.Proceedings.Monitor.Listener.Sched.until', index=1, number=2, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='duration', full_name='gym.VnfBd.Proceedings.Monitor.Listener.Sched.duration', index=2, number=3, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='interval', full_name='gym.VnfBd.Proceedings.Monitor.Listener.Sched.interval', index=3, number=4, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='repeat', full_name='gym.VnfBd.Proceedings.Monitor.Listener.Sched.repeat', index=4, number=5, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2796, serialized_end=2884, ) _VNFBD_PROCEEDINGS_MONITOR_LISTENER_PARAMETERSENTRY = _descriptor.Descriptor( name='ParametersEntry', full_name='gym.VnfBd.Proceedings.Monitor.Listener.ParametersEntry', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='key', full_name='gym.VnfBd.Proceedings.Monitor.Listener.ParametersEntry.key', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.VnfBd.Proceedings.Monitor.Listener.ParametersEntry.value', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=b'8\001', is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=3544, serialized_end=3644, ) _VNFBD_PROCEEDINGS_MONITOR_LISTENER = _descriptor.Descriptor( name='Listener', full_name='gym.VnfBd.Proceedings.Monitor.Listener', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='id', full_name='gym.VnfBd.Proceedings.Monitor.Listener.id', index=0, number=1, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='instances', full_name='gym.VnfBd.Proceedings.Monitor.Listener.instances', index=1, number=2, type=4, cpp_type=4, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='name', full_name='gym.VnfBd.Proceedings.Monitor.Listener.name', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='parameters', full_name='gym.VnfBd.Proceedings.Monitor.Listener.parameters', index=3, number=4, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='sched', full_name='gym.VnfBd.Proceedings.Monitor.Listener.sched', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[_VNFBD_PROCEEDINGS_MONITOR_LISTENER_PARAMETER, _VNFBD_PROCEEDINGS_MONITOR_LISTENER_SCHED, _VNFBD_PROCEEDINGS_MONITOR_LISTENER_PARAMETERSENTRY, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=3215, serialized_end=3644, ) _VNFBD_PROCEEDINGS_MONITOR_LISTENERSENTRY = _descriptor.Descriptor( name='ListenersEntry', full_name='gym.VnfBd.Proceedings.Monitor.ListenersEntry', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='key', full_name='gym.VnfBd.Proceedings.Monitor.ListenersEntry.key', index=0, number=1, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.VnfBd.Proceedings.Monitor.ListenersEntry.value', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=b'8\001', is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=3646, serialized_end=3735, ) _VNFBD_PROCEEDINGS_MONITOR = _descriptor.Descriptor( name='Monitor', full_name='gym.VnfBd.Proceedings.Monitor', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='uuid', full_name='gym.VnfBd.Proceedings.Monitor.uuid', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='name', full_name='gym.VnfBd.Proceedings.Monitor.name', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='listeners', full_name='gym.VnfBd.Proceedings.Monitor.listeners', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[_VNFBD_PROCEEDINGS_MONITOR_HOST, _VNFBD_PROCEEDINGS_MONITOR_LISTENER, _VNFBD_PROCEEDINGS_MONITOR_LISTENERSENTRY, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=3070, serialized_end=3735, ) _VNFBD_PROCEEDINGS_ATTRIBUTESENTRY = _descriptor.Descriptor( name='AttributesEntry', full_name='gym.VnfBd.Proceedings.AttributesEntry', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='key', full_name='gym.VnfBd.Proceedings.AttributesEntry.key', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.VnfBd.Proceedings.AttributesEntry.value', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=b'8\001', is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=3737, serialized_end=3820, ) _VNFBD_PROCEEDINGS_AGENTSENTRY = _descriptor.Descriptor( name='AgentsEntry', full_name='gym.VnfBd.Proceedings.AgentsEntry', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='key', full_name='gym.VnfBd.Proceedings.AgentsEntry.key', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.VnfBd.Proceedings.AgentsEntry.value', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=b'8\001', is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=3822, serialized_end=3897, ) _VNFBD_PROCEEDINGS_MONITORSENTRY = _descriptor.Descriptor( name='MonitorsEntry', full_name='gym.VnfBd.Proceedings.MonitorsEntry', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='key', full_name='gym.VnfBd.Proceedings.MonitorsEntry.key', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='value', full_name='gym.VnfBd.Proceedings.MonitorsEntry.value', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=b'8\001', is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=3899, serialized_end=3978, ) _VNFBD_PROCEEDINGS = _descriptor.Descriptor( name='Proceedings', full_name='gym.VnfBd.Proceedings', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='attributes', full_name='gym.VnfBd.Proceedings.attributes', index=0, number=1, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='agents', full_name='gym.VnfBd.Proceedings.agents', index=1, number=2, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='monitors', full_name='gym.VnfBd.Proceedings.monitors', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[_VNFBD_PROCEEDINGS_ATTRIBUTE, _VNFBD_PROCEEDINGS_AGENT, _VNFBD_PROCEEDINGS_MONITOR, _VNFBD_PROCEEDINGS_ATTRIBUTESENTRY, _VNFBD_PROCEEDINGS_AGENTSENTRY, _VNFBD_PROCEEDINGS_MONITORSENTRY, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2243, serialized_end=3978, ) _VNFBD = _descriptor.Descriptor( name='VnfBd', full_name='gym.VnfBd', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='id', full_name='gym.VnfBd.id', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='name', full_name='gym.VnfBd.name', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='version', full_name='gym.VnfBd.version', index=2, number=3, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='author', full_name='gym.VnfBd.author', index=3, number=4, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='description', full_name='gym.VnfBd.description', index=4, number=5, type=9, cpp_type=9, label=1, has_default_value=False, default_value=b"".decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='experiments', full_name='gym.VnfBd.experiments', index=5, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='scenario', full_name='gym.VnfBd.scenario', index=6, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='proceedings', full_name='gym.VnfBd.proceedings', index=7, number=8, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[_VNFBD_EXPERIMENTS, _VNFBD_PROCEEDINGS, ], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1984, serialized_end=3978, ) _SCENARIO_LINK.containing_type = _SCENARIO _SCENARIO_NODE_CONNECTIONPOINT.containing_type = _SCENARIO_NODE _SCENARIO_NODE_LIFECYCLE_PARAMETER.containing_type = _SCENARIO_NODE_LIFECYCLE _SCENARIO_NODE_LIFECYCLE_PARAMETERSENTRY.fields_by_name['value'].message_type = _SCENARIO_NODE_LIFECYCLE_PARAMETER _SCENARIO_NODE_LIFECYCLE_PARAMETERSENTRY.containing_type = _SCENARIO_NODE_LIFECYCLE _SCENARIO_NODE_LIFECYCLE.fields_by_name['parameters'].message_type = _SCENARIO_NODE_LIFECYCLE_PARAMETERSENTRY _SCENARIO_NODE_LIFECYCLE.fields_by_name['workflow'].enum_type = _SCENARIO_NODE_LIFECYCLE_WORKFLOWS _SCENARIO_NODE_LIFECYCLE.containing_type = _SCENARIO_NODE _SCENARIO_NODE_LIFECYCLE_WORKFLOWS.containing_type = _SCENARIO_NODE_LIFECYCLE _SCENARIO_NODE_RELATIONSHIP.containing_type = _SCENARIO_NODE _SCENARIO_NODE_RESOURCES_CPU.containing_type = _SCENARIO_NODE_RESOURCES _SCENARIO_NODE_RESOURCES_MEMORY.containing_type = _SCENARIO_NODE_RESOURCES _SCENARIO_NODE_RESOURCES_STORAGE.containing_type = _SCENARIO_NODE_RESOURCES _SCENARIO_NODE_RESOURCES.fields_by_name['cpu'].message_type = _SCENARIO_NODE_RESOURCES_CPU _SCENARIO_NODE_RESOURCES.fields_by_name['memory'].message_type = _SCENARIO_NODE_RESOURCES_MEMORY _SCENARIO_NODE_RESOURCES.fields_by_name['storage'].message_type = _SCENARIO_NODE_RESOURCES_STORAGE _SCENARIO_NODE_RESOURCES.containing_type = _SCENARIO_NODE _SCENARIO_NODE_CONNECTIONPOINTSENTRY.fields_by_name['value'].message_type = _SCENARIO_NODE_CONNECTIONPOINT _SCENARIO_NODE_CONNECTIONPOINTSENTRY.containing_type = _SCENARIO_NODE _SCENARIO_NODE_LIFECYCLEENTRY.fields_by_name['value'].message_type = _SCENARIO_NODE_LIFECYCLE _SCENARIO_NODE_LIFECYCLEENTRY.containing_type = _SCENARIO_NODE _SCENARIO_NODE_RELATIONSHIPSENTRY.fields_by_name['value'].message_type = _SCENARIO_NODE_RELATIONSHIP _SCENARIO_NODE_RELATIONSHIPSENTRY.containing_type = _SCENARIO_NODE _SCENARIO_NODE.fields_by_name['resources'].message_type = _SCENARIO_NODE_RESOURCES _SCENARIO_NODE.fields_by_name['connection_points'].message_type = _SCENARIO_NODE_CONNECTIONPOINTSENTRY _SCENARIO_NODE.fields_by_name['lifecycle'].message_type = _SCENARIO_NODE_LIFECYCLEENTRY _SCENARIO_NODE.fields_by_name['relationships'].message_type = _SCENARIO_NODE_RELATIONSHIPSENTRY _SCENARIO_NODE.containing_type = _SCENARIO _SCENARIO_POLICY.containing_type = _SCENARIO _SCENARIO_LINKSENTRY.fields_by_name['value'].message_type = _SCENARIO_LINK _SCENARIO_LINKSENTRY.containing_type = _SCENARIO _SCENARIO_NODESENTRY.fields_by_name['value'].message_type = _SCENARIO_NODE _SCENARIO_NODESENTRY.containing_type = _SCENARIO _SCENARIO_POLICIESENTRY.fields_by_name['value'].message_type = _SCENARIO_POLICY _SCENARIO_POLICIESENTRY.containing_type = _SCENARIO _SCENARIO.fields_by_name['links'].message_type = _SCENARIO_LINKSENTRY _SCENARIO.fields_by_name['nodes'].message_type = _SCENARIO_NODESENTRY _SCENARIO.fields_by_name['policies'].message_type = _SCENARIO_POLICIESENTRY _VNFBD_EXPERIMENTS.containing_type = _VNFBD _VNFBD_PROCEEDINGS_ATTRIBUTE.containing_type = _VNFBD_PROCEEDINGS _VNFBD_PROCEEDINGS_AGENT_PROBER_PARAMETER.containing_type = _VNFBD_PROCEEDINGS_AGENT_PROBER _VNFBD_PROCEEDINGS_AGENT_PROBER_SCHED.containing_type = _VNFBD_PROCEEDINGS_AGENT_PROBER _VNFBD_PROCEEDINGS_AGENT_PROBER_PARAMETERSENTRY.fields_by_name['value'].message_type = _VNFBD_PROCEEDINGS_AGENT_PROBER_PARAMETER _VNFBD_PROCEEDINGS_AGENT_PROBER_PARAMETERSENTRY.containing_type = _VNFBD_PROCEEDINGS_AGENT_PROBER _VNFBD_PROCEEDINGS_AGENT_PROBER.fields_by_name['parameters'].message_type = _VNFBD_PROCEEDINGS_AGENT_PROBER_PARAMETERSENTRY _VNFBD_PROCEEDINGS_AGENT_PROBER.fields_by_name['sched'].message_type = _VNFBD_PROCEEDINGS_AGENT_PROBER_SCHED _VNFBD_PROCEEDINGS_AGENT_PROBER.containing_type = _VNFBD_PROCEEDINGS_AGENT _VNFBD_PROCEEDINGS_AGENT_PROBERSENTRY.fields_by_name['value'].message_type = _VNFBD_PROCEEDINGS_AGENT_PROBER _VNFBD_PROCEEDINGS_AGENT_PROBERSENTRY.containing_type = _VNFBD_PROCEEDINGS_AGENT _VNFBD_PROCEEDINGS_AGENT.fields_by_name['probers'].message_type = _VNFBD_PROCEEDINGS_AGENT_PROBERSENTRY _VNFBD_PROCEEDINGS_AGENT.containing_type = _VNFBD_PROCEEDINGS _VNFBD_PROCEEDINGS_MONITOR_HOST.containing_type = _VNFBD_PROCEEDINGS_MONITOR _VNFBD_PROCEEDINGS_MONITOR_LISTENER_PARAMETER.containing_type = _VNFBD_PROCEEDINGS_MONITOR_LISTENER _VNFBD_PROCEEDINGS_MONITOR_LISTENER_SCHED.containing_type = _VNFBD_PROCEEDINGS_MONITOR_LISTENER _VNFBD_PROCEEDINGS_MONITOR_LISTENER_PARAMETERSENTRY.fields_by_name['value'].message_type = _VNFBD_PROCEEDINGS_MONITOR_LISTENER_PARAMETER _VNFBD_PROCEEDINGS_MONITOR_LISTENER_PARAMETERSENTRY.containing_type = _VNFBD_PROCEEDINGS_MONITOR_LISTENER _VNFBD_PROCEEDINGS_MONITOR_LISTENER.fields_by_name['parameters'].message_type = _VNFBD_PROCEEDINGS_MONITOR_LISTENER_PARAMETERSENTRY _VNFBD_PROCEEDINGS_MONITOR_LISTENER.fields_by_name['sched'].message_type = _VNFBD_PROCEEDINGS_MONITOR_LISTENER_SCHED _VNFBD_PROCEEDINGS_MONITOR_LISTENER.containing_type = _VNFBD_PROCEEDINGS_MONITOR _VNFBD_PROCEEDINGS_MONITOR_LISTENERSENTRY.fields_by_name['value'].message_type = _VNFBD_PROCEEDINGS_MONITOR_LISTENER _VNFBD_PROCEEDINGS_MONITOR_LISTENERSENTRY.containing_type = _VNFBD_PROCEEDINGS_MONITOR _VNFBD_PROCEEDINGS_MONITOR.fields_by_name['listeners'].message_type = _VNFBD_PROCEEDINGS_MONITOR_LISTENERSENTRY _VNFBD_PROCEEDINGS_MONITOR.containing_type = _VNFBD_PROCEEDINGS _VNFBD_PROCEEDINGS_ATTRIBUTESENTRY.fields_by_name['value'].message_type = _VNFBD_PROCEEDINGS_ATTRIBUTE _VNFBD_PROCEEDINGS_ATTRIBUTESENTRY.containing_type = _VNFBD_PROCEEDINGS _VNFBD_PROCEEDINGS_AGENTSENTRY.fields_by_name['value'].message_type = _VNFBD_PROCEEDINGS_AGENT _VNFBD_PROCEEDINGS_AGENTSENTRY.containing_type = _VNFBD_PROCEEDINGS _VNFBD_PROCEEDINGS_MONITORSENTRY.fields_by_name['value'].message_type = _VNFBD_PROCEEDINGS_MONITOR _VNFBD_PROCEEDINGS_MONITORSENTRY.containing_type = _VNFBD_PROCEEDINGS _VNFBD_PROCEEDINGS.fields_by_name['attributes'].message_type = _VNFBD_PROCEEDINGS_ATTRIBUTESENTRY _VNFBD_PROCEEDINGS.fields_by_name['agents'].message_type = _VNFBD_PROCEEDINGS_AGENTSENTRY _VNFBD_PROCEEDINGS.fields_by_name['monitors'].message_type = _VNFBD_PROCEEDINGS_MONITORSENTRY _VNFBD_PROCEEDINGS.containing_type = _VNFBD _VNFBD.fields_by_name['experiments'].message_type = _VNFBD_EXPERIMENTS _VNFBD.fields_by_name['scenario'].message_type = _SCENARIO _VNFBD.fields_by_name['proceedings'].message_type = _VNFBD_PROCEEDINGS DESCRIPTOR.message_types_by_name['Scenario'] = _SCENARIO DESCRIPTOR.message_types_by_name['VnfBd'] = _VNFBD _sym_db.RegisterFileDescriptor(DESCRIPTOR) Scenario = _reflection.GeneratedProtocolMessageType('Scenario', (_message.Message,), { 'Link' : _reflection.GeneratedProtocolMessageType('Link', (_message.Message,), { 'DESCRIPTOR' : _SCENARIO_LINK, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.Link) }) , 'Node' : _reflection.GeneratedProtocolMessageType('Node', (_message.Message,), { 'ConnectionPoint' : _reflection.GeneratedProtocolMessageType('ConnectionPoint', (_message.Message,), { 'DESCRIPTOR' : _SCENARIO_NODE_CONNECTIONPOINT, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.Node.ConnectionPoint) }) , 'Lifecycle' : _reflection.GeneratedProtocolMessageType('Lifecycle', (_message.Message,), { 'Parameter' : _reflection.GeneratedProtocolMessageType('Parameter', (_message.Message,), { 'DESCRIPTOR' : _SCENARIO_NODE_LIFECYCLE_PARAMETER, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.Node.Lifecycle.Parameter) }) , 'ParametersEntry' : _reflection.GeneratedProtocolMessageType('ParametersEntry', (_message.Message,), { 'DESCRIPTOR' : _SCENARIO_NODE_LIFECYCLE_PARAMETERSENTRY, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.Node.Lifecycle.ParametersEntry) }) , 'DESCRIPTOR' : _SCENARIO_NODE_LIFECYCLE, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.Node.Lifecycle) }) , 'Relationship' : _reflection.GeneratedProtocolMessageType('Relationship', (_message.Message,), { 'DESCRIPTOR' : _SCENARIO_NODE_RELATIONSHIP, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.Node.Relationship) }) , 'Resources' : _reflection.GeneratedProtocolMessageType('Resources', (_message.Message,), { 'Cpu' : _reflection.GeneratedProtocolMessageType('Cpu', (_message.Message,), { 'DESCRIPTOR' : _SCENARIO_NODE_RESOURCES_CPU, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.Node.Resources.Cpu) }) , 'Memory' : _reflection.GeneratedProtocolMessageType('Memory', (_message.Message,), { 'DESCRIPTOR' : _SCENARIO_NODE_RESOURCES_MEMORY, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.Node.Resources.Memory) }) , 'Storage' : _reflection.GeneratedProtocolMessageType('Storage', (_message.Message,), { 'DESCRIPTOR' : _SCENARIO_NODE_RESOURCES_STORAGE, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.Node.Resources.Storage) }) , 'DESCRIPTOR' : _SCENARIO_NODE_RESOURCES, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.Node.Resources) }) , 'ConnectionPointsEntry' : _reflection.GeneratedProtocolMessageType('ConnectionPointsEntry', (_message.Message,), { 'DESCRIPTOR' : _SCENARIO_NODE_CONNECTIONPOINTSENTRY, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.Node.ConnectionPointsEntry) }) , 'LifecycleEntry' : _reflection.GeneratedProtocolMessageType('LifecycleEntry', (_message.Message,), { 'DESCRIPTOR' : _SCENARIO_NODE_LIFECYCLEENTRY, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.Node.LifecycleEntry) }) , 'RelationshipsEntry' : _reflection.GeneratedProtocolMessageType('RelationshipsEntry', (_message.Message,), { 'DESCRIPTOR' : _SCENARIO_NODE_RELATIONSHIPSENTRY, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.Node.RelationshipsEntry) }) , 'DESCRIPTOR' : _SCENARIO_NODE, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.Node) }) , 'Policy' : _reflection.GeneratedProtocolMessageType('Policy', (_message.Message,), { 'DESCRIPTOR' : _SCENARIO_POLICY, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.Policy) }) , 'LinksEntry' : _reflection.GeneratedProtocolMessageType('LinksEntry', (_message.Message,), { 'DESCRIPTOR' : _SCENARIO_LINKSENTRY, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.LinksEntry) }) , 'NodesEntry' : _reflection.GeneratedProtocolMessageType('NodesEntry', (_message.Message,), { 'DESCRIPTOR' : _SCENARIO_NODESENTRY, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.NodesEntry) }) , 'PoliciesEntry' : _reflection.GeneratedProtocolMessageType('PoliciesEntry', (_message.Message,), { 'DESCRIPTOR' : _SCENARIO_POLICIESENTRY, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario.PoliciesEntry) }) , 'DESCRIPTOR' : _SCENARIO, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.Scenario) }) _sym_db.RegisterMessage(Scenario) _sym_db.RegisterMessage(Scenario.Link) _sym_db.RegisterMessage(Scenario.Node) _sym_db.RegisterMessage(Scenario.Node.ConnectionPoint) _sym_db.RegisterMessage(Scenario.Node.Lifecycle) _sym_db.RegisterMessage(Scenario.Node.Lifecycle.Parameter) _sym_db.RegisterMessage(Scenario.Node.Lifecycle.ParametersEntry) _sym_db.RegisterMessage(Scenario.Node.Relationship) _sym_db.RegisterMessage(Scenario.Node.Resources) _sym_db.RegisterMessage(Scenario.Node.Resources.Cpu) _sym_db.RegisterMessage(Scenario.Node.Resources.Memory) _sym_db.RegisterMessage(Scenario.Node.Resources.Storage) _sym_db.RegisterMessage(Scenario.Node.ConnectionPointsEntry) _sym_db.RegisterMessage(Scenario.Node.LifecycleEntry) _sym_db.RegisterMessage(Scenario.Node.RelationshipsEntry) _sym_db.RegisterMessage(Scenario.Policy) _sym_db.RegisterMessage(Scenario.LinksEntry) _sym_db.RegisterMessage(Scenario.NodesEntry) _sym_db.RegisterMessage(Scenario.PoliciesEntry) VnfBd = _reflection.GeneratedProtocolMessageType('VnfBd', (_message.Message,), { 'Experiments' : _reflection.GeneratedProtocolMessageType('Experiments', (_message.Message,), { 'DESCRIPTOR' : _VNFBD_EXPERIMENTS, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Experiments) }) , 'Proceedings' : _reflection.GeneratedProtocolMessageType('Proceedings', (_message.Message,), { 'Attribute' : _reflection.GeneratedProtocolMessageType('Attribute', (_message.Message,), { 'DESCRIPTOR' : _VNFBD_PROCEEDINGS_ATTRIBUTE, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings.Attribute) }) , 'Agent' : _reflection.GeneratedProtocolMessageType('Agent', (_message.Message,), { 'Prober' : _reflection.GeneratedProtocolMessageType('Prober', (_message.Message,), { 'Parameter' : _reflection.GeneratedProtocolMessageType('Parameter', (_message.Message,), { 'DESCRIPTOR' : _VNFBD_PROCEEDINGS_AGENT_PROBER_PARAMETER, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings.Agent.Prober.Parameter) }) , 'Sched' : _reflection.GeneratedProtocolMessageType('Sched', (_message.Message,), { 'DESCRIPTOR' : _VNFBD_PROCEEDINGS_AGENT_PROBER_SCHED, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings.Agent.Prober.Sched) }) , 'ParametersEntry' : _reflection.GeneratedProtocolMessageType('ParametersEntry', (_message.Message,), { 'DESCRIPTOR' : _VNFBD_PROCEEDINGS_AGENT_PROBER_PARAMETERSENTRY, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings.Agent.Prober.ParametersEntry) }) , 'DESCRIPTOR' : _VNFBD_PROCEEDINGS_AGENT_PROBER, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings.Agent.Prober) }) , 'ProbersEntry' : _reflection.GeneratedProtocolMessageType('ProbersEntry', (_message.Message,), { 'DESCRIPTOR' : _VNFBD_PROCEEDINGS_AGENT_PROBERSENTRY, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings.Agent.ProbersEntry) }) , 'DESCRIPTOR' : _VNFBD_PROCEEDINGS_AGENT, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings.Agent) }) , 'Monitor' : _reflection.GeneratedProtocolMessageType('Monitor', (_message.Message,), { 'Host' : _reflection.GeneratedProtocolMessageType('Host', (_message.Message,), { 'DESCRIPTOR' : _VNFBD_PROCEEDINGS_MONITOR_HOST, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings.Monitor.Host) }) , 'Listener' : _reflection.GeneratedProtocolMessageType('Listener', (_message.Message,), { 'Parameter' : _reflection.GeneratedProtocolMessageType('Parameter', (_message.Message,), { 'DESCRIPTOR' : _VNFBD_PROCEEDINGS_MONITOR_LISTENER_PARAMETER, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings.Monitor.Listener.Parameter) }) , 'Sched' : _reflection.GeneratedProtocolMessageType('Sched', (_message.Message,), { 'DESCRIPTOR' : _VNFBD_PROCEEDINGS_MONITOR_LISTENER_SCHED, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings.Monitor.Listener.Sched) }) , 'ParametersEntry' : _reflection.GeneratedProtocolMessageType('ParametersEntry', (_message.Message,), { 'DESCRIPTOR' : _VNFBD_PROCEEDINGS_MONITOR_LISTENER_PARAMETERSENTRY, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings.Monitor.Listener.ParametersEntry) }) , 'DESCRIPTOR' : _VNFBD_PROCEEDINGS_MONITOR_LISTENER, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings.Monitor.Listener) }) , 'ListenersEntry' : _reflection.GeneratedProtocolMessageType('ListenersEntry', (_message.Message,), { 'DESCRIPTOR' : _VNFBD_PROCEEDINGS_MONITOR_LISTENERSENTRY, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings.Monitor.ListenersEntry) }) , 'DESCRIPTOR' : _VNFBD_PROCEEDINGS_MONITOR, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings.Monitor) }) , 'AttributesEntry' : _reflection.GeneratedProtocolMessageType('AttributesEntry', (_message.Message,), { 'DESCRIPTOR' : _VNFBD_PROCEEDINGS_ATTRIBUTESENTRY, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings.AttributesEntry) }) , 'AgentsEntry' : _reflection.GeneratedProtocolMessageType('AgentsEntry', (_message.Message,), { 'DESCRIPTOR' : _VNFBD_PROCEEDINGS_AGENTSENTRY, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings.AgentsEntry) }) , 'MonitorsEntry' : _reflection.GeneratedProtocolMessageType('MonitorsEntry', (_message.Message,), { 'DESCRIPTOR' : _VNFBD_PROCEEDINGS_MONITORSENTRY, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings.MonitorsEntry) }) , 'DESCRIPTOR' : _VNFBD_PROCEEDINGS, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd.Proceedings) }) , 'DESCRIPTOR' : _VNFBD, '__module__' : 'vnf_bd_pb2' # @@protoc_insertion_point(class_scope:gym.VnfBd) }) _sym_db.RegisterMessage(VnfBd) _sym_db.RegisterMessage(VnfBd.Experiments) _sym_db.RegisterMessage(VnfBd.Proceedings) _sym_db.RegisterMessage(VnfBd.Proceedings.Attribute) _sym_db.RegisterMessage(VnfBd.Proceedings.Agent) _sym_db.RegisterMessage(VnfBd.Proceedings.Agent.Prober) _sym_db.RegisterMessage(VnfBd.Proceedings.Agent.Prober.Parameter) _sym_db.RegisterMessage(VnfBd.Proceedings.Agent.Prober.Sched) _sym_db.RegisterMessage(VnfBd.Proceedings.Agent.Prober.ParametersEntry) _sym_db.RegisterMessage(VnfBd.Proceedings.Agent.ProbersEntry) _sym_db.RegisterMessage(VnfBd.Proceedings.Monitor) _sym_db.RegisterMessage(VnfBd.Proceedings.Monitor.Host) _sym_db.RegisterMessage(VnfBd.Proceedings.Monitor.Listener) _sym_db.RegisterMessage(VnfBd.Proceedings.Monitor.Listener.Parameter) _sym_db.RegisterMessage(VnfBd.Proceedings.Monitor.Listener.Sched) _sym_db.RegisterMessage(VnfBd.Proceedings.Monitor.Listener.ParametersEntry) _sym_db.RegisterMessage(VnfBd.Proceedings.Monitor.ListenersEntry) _sym_db.RegisterMessage(VnfBd.Proceedings.AttributesEntry) _sym_db.RegisterMessage(VnfBd.Proceedings.AgentsEntry) _sym_db.RegisterMessage(VnfBd.Proceedings.MonitorsEntry) _SCENARIO_NODE_LIFECYCLE_PARAMETERSENTRY._options = None _SCENARIO_NODE_CONNECTIONPOINTSENTRY._options = None _SCENARIO_NODE_LIFECYCLEENTRY._options = None _SCENARIO_NODE_RELATIONSHIPSENTRY._options = None _SCENARIO_LINKSENTRY._options = None _SCENARIO_NODESENTRY._options = None _SCENARIO_POLICIESENTRY._options = None _VNFBD_PROCEEDINGS_AGENT_PROBER_PARAMETERSENTRY._options = None _VNFBD_PROCEEDINGS_AGENT_PROBERSENTRY._options = None _VNFBD_PROCEEDINGS_MONITOR_LISTENER_PARAMETERSENTRY._options = None _VNFBD_PROCEEDINGS_MONITOR_LISTENERSENTRY._options = None _VNFBD_PROCEEDINGS_ATTRIBUTESENTRY._options = None _VNFBD_PROCEEDINGS_AGENTSENTRY._options = None _VNFBD_PROCEEDINGS_MONITORSENTRY._options = None # @@protoc_insertion_point(module_scope)

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76772a7b638b0274112781a14a649b9fa820e40b

6,583

py

Python

tests/sortedsets_tests.py

gmr/tredis

2e91c6a58a35460be0525c51ac6a98fde3b506ad

[ "BSD-3-Clause" ]

22

2015-11-16T18:24:23.000Z

2019-01-22T06:41:51.000Z

tests/sortedsets_tests.py

gmr/tredis

2e91c6a58a35460be0525c51ac6a98fde3b506ad

[ "BSD-3-Clause" ]

8

2016-01-26T21:55:15.000Z

2020-11-17T18:00:13.000Z

tests/sortedsets_tests.py

gmr/tredis

2e91c6a58a35460be0525c51ac6a98fde3b506ad

[ "BSD-3-Clause" ]

9

2015-11-28T19:32:14.000Z

2020-10-19T06:47:26.000Z

import mock from tornado import testing from tredis import exceptions from . import base class SortedSetTests(base.AsyncTestCase): @testing.gen_test def test_zadd_single(self): key, value = self.uuid4(2) result = yield self.client.zadd(key, '1', value) self.assertEqual(result, 1) @testing.gen_test def test_zadd_multiple(self): key, value1, value2, value3 = self.uuid4(4) result = yield self.client.zadd(key, '1', value1, '2', value2, '3', value3) self.assertEqual(result, 3) @testing.gen_test def test_zadd_dict(self): key, value1, value2, value3 = self.uuid4(4) result = yield self.client.zadd(key, {'1': value1, '2': value2, '3': value3}) self.assertEqual(result, 3) @testing.gen_test def test_zadd_multiple_dupe(self): key, value1, value2, value3 = self.uuid4(4) result = yield self.client.zadd(key, '1', value1, '2', value2, '3', value3, '4', value3) self.assertEqual(result, 3) @testing.gen_test def test_zadd_ch(self): key, value1, value2, value3 = self.uuid4(4) result = yield self.client.zadd(key, '1', value1, '2', value2) self.assertEqual(result, 2) result = yield self.client.zadd(key, '2', value1, '3', value2, '4', value3, ch=True) self.assertEqual(result, 3) @testing.gen_test def test_zadd_xx(self): key, value1, value2, value3 = self.uuid4(4) result = yield self.client.zadd(key, '1', value1, '2', value2) self.assertEqual(result, 2) result = yield self.client.zadd(key, '2', value1, '3', value2, '4', value3, xx=True) self.assertEqual(result, 0) @testing.gen_test def test_zadd_nx(self): key, value1, value2, value3 = self.uuid4(4) result = yield self.client.zadd(key, '1', value1, '2', value2) self.assertEqual(result, 2) result = yield self.client.zadd(key, '2', value1, '3', value2, '4', value3, nx=True, ch=True) self.assertEqual(result, 1) @testing.gen_test def test_zadd_incr(self): key, value = self.uuid4(2) result = yield self.client.zadd(key, '1', value) self.assertEqual(result, 1) result = yield self.client.zadd(key, '10', value, incr=True) self.assertEqual(result, b'11') @testing.gen_test def test_zadd_with_error(self): key, score, value = self.uuid4(3) self._execute_result = exceptions.RedisError('Test Exception') with mock.patch.object(self.client, '_execute', self._execute): with self.assertRaises(exceptions.RedisError): yield self.client.zadd(key, score, value) @testing.gen_test def test_zcard_with_extant_set(self): key, value1, value2, value3 = self.uuid4(4) result = yield self.client.zadd(key, '1', value1, '2', value2, '3', value3) self.assertEqual(result, 3) result = yield self.client.zcard(key) self.assertEqual(result, 3) @testing.gen_test def test_zcard_with_nonextant_set(self): key = self.uuid4() result = yield self.client.zcard(key) self.assertEqual(result, 0) @testing.gen_test def test_zrangebyscore(self): key, value1, value2, value3 = self.uuid4(4) result = yield self.client.zadd(key, '1', value1, '2', value2, '3', value3) self.assertEqual(result, 3) result = yield self.client.zrangebyscore(key, '1', '2') self.assertListEqual(result, [value1, value2]) @testing.gen_test def test_zrangebyscore_withitems(self): key, value1, value2, value3 = self.uuid4(4) result = yield self.client.zadd(key, '1', value1, '2', value2, '3', value3) self.assertEqual(result, 3) result = yield self.client.zrangebyscore(key, '1', '2', with_scores=True) self.assertListEqual(result, [value1, b'1', value2, b'2']) @testing.gen_test def test_zrangebyscore_offset(self): key, value1, value2, value3 = self.uuid4(4) result = yield self.client.zadd(key, '1', value1, '2', value2, '3', value3) self.assertEqual(result, 3) result = yield self.client.zrangebyscore(key, '1', '2', offset=1, count=20) self.assertListEqual(result, [value2]) @testing.gen_test def test_zrangebyscore_count(self): key, value1, value2, value3 = self.uuid4(4) result = yield self.client.zadd(key, '1', value1, '2', value2, '3', value3) self.assertEqual(result, 3) result = yield self.client.zrangebyscore(key, '1', '3', offset=0, count=1) self.assertListEqual(result, [value1]) @testing.gen_test def test_zremrangebyscore(self): key, value1, value2, value3 = self.uuid4(4) result = yield self.client.zadd(key, '1', value1, '2', value2, '3', value3) self.assertEqual(result, 3) result = yield self.client.zremrangebyscore(key, '1', '2') self.assertEqual(result, 2) @testing.gen_test def test_zremrangebyscore_inf(self): key, value1, value2, value3 = self.uuid4(4) result = yield self.client.zadd(key, '1', value1, '2', value2, '3', value3) self.assertEqual(result, 3) result = yield self.client.zremrangebyscore(key, '(1', 'inf') self.assertEqual(result, 2) @testing.gen_test def test_zscore_with_member_of_set(self): key, value1, value2, value3 = self.uuid4(4) result = yield self.client.zadd(key, '1', value1, '2', value2, '3', value3) self.assertEqual(result, 3) result = yield self.client.zscore(key, value1) self.assertEqual(result, b'1') @testing.gen_test def test_zscore_with_nonmember_of_set(self): key, value1 = self.uuid4(2) result = yield self.client.zscore(key, value1) self.assertEqual(result, None)

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null

0

1

0

null

0

7

7688fc92c897ede515ed83c65f35a5b94f7d4d17

1,418

py

Python

logger.py

misc77/wordDSEGenerator

f879a8140f322b1f59cd45d0f512327cd9a648ed

[ "MIT" ]

null

logger.py

misc77/wordDSEGenerator

f879a8140f322b1f59cd45d0f512327cd9a648ed

[ "MIT" ]

1

2020-11-10T14:18:33.000Z

logger.py

misc77/wordDSEGenerator

f879a8140f322b1f59cd45d0f512327cd9a648ed

[ "MIT" ]

null

import logging import configProvider import configparser from resources import Resources def getLogger(): logLevel = configProvider.getConfigEntryOrDefault('Logging', 'APPLICATION_LOG_LEVEL', logging.DEBUG) logger = logging.getLogger("DSEGenerator") logger.setLevel(logLevel) fileHandler = logging.FileHandler(Resources.getLogFile()) fileHandler.setLevel(logLevel) consoleHandler = logging.StreamHandler() consoleHandler.setLevel(logLevel) formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s") fileHandler.setFormatter(formatter) consoleHandler.setFormatter(formatter) logger.addHandler(fileHandler) logger.addHandler(consoleHandler) return logger def getLoggerCtx(context): logLevel = configProvider.getConfigEntryOrDefault('Logging', 'APPLICATION_LOG_LEVEL', logging.DEBUG) logger = logging.getLogger(context) logger.setLevel(logLevel) fileHandler = logging.FileHandler(Resources.getLogFile()) fileHandler.setLevel(logLevel) consoleHandler = logging.StreamHandler() consoleHandler.setLevel(logLevel) formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s") fileHandler.setFormatter(formatter) consoleHandler.setFormatter(formatter) logger.addHandler(fileHandler) logger.addHandler(consoleHandler) return logger

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null

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null

0

7

768fd3657a7863da03e95ea6d670825f79ad7212

3,250

py

Python

migrations/0045_auto_20190225_1821.py

audaciouscode/PassiveDataKit-Django

ed1e00c436801b9f49a3e0e6657c2adb6b2ba3d4

[ "Apache-2.0" ]

5

2016-01-26T19:19:44.000Z

2018-12-12T18:04:04.000Z

migrations/0045_auto_20190225_1821.py

audacious-software/PassiveDataKit-Django

da91a375c075ceec938f2c9bb6b011f9f019b024

[ "Apache-2.0" ]

6

2020-02-17T20:16:28.000Z

2021-12-13T21:51:20.000Z

migrations/0045_auto_20190225_1821.py

audacious-software/PassiveDataKit-Django

da91a375c075ceec938f2c9bb6b011f9f019b024

[ "Apache-2.0" ]

4

2020-01-29T15:36:58.000Z

2021-06-01T18:55:26.000Z

# pylint: skip-file # -*- coding: utf-8 -*- # Generated by Django 1.11.20 on 2019-02-25 18:21 import django.contrib.postgres.fields.jsonb from django.db import migrations, models import django.db.models.deletion from ..models import install_supports_jsonfield class Migration(migrations.Migration): dependencies = [ ('passive_data_kit', '0044_dataserverapitoken'), ] if install_supports_jsonfield(): operations = [ migrations.CreateModel( name='AppConfiguration', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=1024)), ('id_pattern', models.CharField(max_length=1024)), ('context_pattern', models.CharField(default='.*', max_length=1024)), ('configuration_json', django.contrib.postgres.fields.jsonb.JSONField()), ('evaluate_order', models.IntegerField(default=1)), ('is_valid', models.BooleanField(default=False)), ('is_enabled', models.BooleanField(default=True)), ], ), migrations.AlterField( model_name='datafile', name='data_bundle', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='data_files', to='passive_data_kit.DataBundle'), ), migrations.AlterField( model_name='datafile', name='data_point', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='data_files', to='passive_data_kit.DataPoint'), ), ] else: operations = [ migrations.CreateModel( name='AppConfiguration', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('name', models.CharField(max_length=1024)), ('id_pattern', models.CharField(max_length=1024)), ('context_pattern', models.CharField(default='.*', max_length=1024)), ('configuration_json', models.TextField(max_length=34359738368)), ('evaluate_order', models.IntegerField(default=1)), ('is_valid', models.BooleanField(default=False)), ('is_enabled', models.BooleanField(default=True)), ], ), migrations.AlterField( model_name='datafile', name='data_bundle', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='data_files', to='passive_data_kit.DataBundle'), ), migrations.AlterField( model_name='datafile', name='data_point', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, related_name='data_files', to='passive_data_kit.DataPoint'), ), ]

46.428571

170

0.582462

317

3,250

5.769716

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0.034992

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0.060142

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1

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null

0

1

0

9

4f24614860941426487d1c898cb9c8d2e5316e0c

5,079

py

Python

tests/test_deque.py

duruyi/fastrq

39b64f278a234acf231b62d684494bad13d8feb7

[ "MIT" ]

17

2018-11-24T08:02:25.000Z

2022-02-25T15:43:23.000Z

tests/test_deque.py

duruyi/fastrq

39b64f278a234acf231b62d684494bad13d8feb7

[ "MIT" ]

null

tests/test_deque.py

duruyi/fastrq

39b64f278a234acf231b62d684494bad13d8feb7

[ "MIT" ]

1

2019-03-14T04:55:04.000Z

import time import unittest from fastrq.deque import Deque, CappedDeque, OfCappedDeque class TestDeque(unittest.TestCase): def setUp(self): self.queue = Deque("fastrq_deque") self.queue.destruct() def tearDown(self): self.queue.destruct() def test_push_pop(self): ql = self.queue.push_back([1, 2]) self.assertEqual(ql, 2) self.assertEqual(self.queue.length(), 2) head = self.queue.pop_front() self.assertEqual(head, '1') self.assertEqual(self.queue.length(), 1) self.assertEqual(len(self.queue), 1) self.queue.push_front([3, 4, 5, 6, 7]) head3 = self.queue.pop_front(3) self.assertEqual(head3, ['7', '6', '5']) self.assertEqual(self.queue.pop_back(3), ['2', '3', '4']) self.assertEqual(self.queue.pop_back(), None) def test_push_e(self): self.assertEqual(self.queue.push_front_ne(1), 1) self.assertFalse(self.queue.push_back_ne(1)) self.queue.destruct() self.assertFalse(self.queue.push_front_ae(1)) self.queue.push_front(1) self.assertEqual(self.queue.push_front_ae(1), 2) def test_push_ni(self): self.assertEqual(self.queue.push_back_ni(1), (1, True)) self.assertEqual(self.queue.push_back_ni(2), (2, True)) self.assertEqual(self.queue.push_back_ni(4), (3, True)) self.assertEqual(self.queue.push_back_ni(4), (3, False)) self.assertEqual(self.queue.push_back_ni('apple'), (4, True)) self.assertEqual(self.queue.pop_front(), '1') self.assertEqual(self.queue.pop_back(), 'apple') def test_range(self): self.queue.push_back([1, 2, 3, 4]) self.assertEqual(self.queue.range(0, -1), ['1', '2', '3', '4']) self.assertEqual(self.queue.range(0, 2), ['1', '2', '3']) self.assertEqual(self.queue.range(0, 0), ['1']) self.queue.destruct() self.assertEqual(self.queue.range(0, -1), []) def test_expire(self): self.queue.push_back([1, 2]) self.assertEqual(self.queue.ttl(), -1) self.queue.expire(10) self.assertEqual(self.queue.ttl(), 10) time.sleep(11) self.assertEqual(self.queue.ttl(), -2) class TestCappedDeque(unittest.TestCase): def setUp(self): self.queue = CappedDeque("fastrq_capped_deque", 3) self.queue.destruct() def tearDown(self): self.queue.destruct() def test_push(self): self.queue.push_back([1, 2]) self.queue.push_front(3) self.assertEqual(self.queue.range(0, -1), ['3', '1', '2']) self.assertEqual(self.queue.push_back(4), 'err_qf') def test_push_e(self): self.assertEqual(self.queue.push_front_ne(1), 1) self.assertFalse(self.queue.push_back_ne(1)) self.queue.destruct() self.assertFalse(self.queue.push_front_ae(1)) self.queue.push_front(1) self.assertEqual(self.queue.push_front_ae(1), 2) def test_push_ni(self): self.assertEqual(self.queue.push_back_ni(1), (1, True)) self.assertEqual(self.queue.push_back_ni(1), (1, False)) self.assertEqual(self.queue.push_front_ni(2), (2, True)) self.assertEqual(self.queue.push_front_ni(2), (2, False)) self.assertEqual(self.queue.push_back_ni(3), (3, True)) self.assertEqual(self.queue.push_back_ni(3), 'err_qf') self.assertEqual(self.queue.push_back_ni(4), 'err_qf') self.assertEqual(self.queue.pop_front(), '2') self.assertEqual(self.queue.pop_back(), '3') class TestOfCappedDeque(unittest.TestCase): def setUp(self): self.queue = OfCappedDeque("fastrq_of_capped_deque", 3) self.queue.destruct() def tearDown(self): self.queue.destruct() def test_push(self): self.assertEqual(self.queue.push_back([1, 2]), (2, [])) self.assertEqual(self.queue.push_front(3), (3, [])) self.assertEqual(self.queue.push_back(4), (3, ['3'])) self.assertEqual(self.queue.pop_front(), '1') self.assertEqual(self.queue.pop_back(), '4') def test_push_e(self): self.assertEqual(self.queue.push_front_ne(1), (1, [])) self.assertFalse(self.queue.push_back_ne(1)) self.queue.destruct() self.assertFalse(self.queue.push_front_ae(1)) self.queue.push_front(1) self.assertEqual(self.queue.push_front_ae(1), (2, [])) def test_push_ni(self): self.assertEqual(self.queue.push_back_ni('apple'), (1, [], True)) self.assertEqual(self.queue.push_back_ni('banana'), (2, [], True)) self.assertEqual(self.queue.push_back_ni('banana'), (2, [], False)) self.assertEqual(self.queue.push_front_ni('pear'), (3, [], True)) self.assertEqual(self.queue.push_front_ni('pear'), (3, [], False)) self.assertEqual(self.queue.push_front_ni('grape'), (3, ['banana'], True)) self.assertEqual(self.queue.pop_front(), 'grape') self.assertEqual(self.queue.pop_back(), 'apple')

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82

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703

5,079

4.339972

0.085349

0.235988

0.298918

0.377581

0.867584

0.811209

0.778433

0.616847

0.528351

0.462144

0

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5,079

131

83

38.770992

0.72938

0

0.420561

0

0.029736

0.004332

0

0.542056

1

0.158879

false

0

0.028037

0

0.214953

0

null

1

0

null

0

1

0

7

4f339e21a690e3ce557adcf61b159a4c40e4f406

2,607

py

Python

imlib/transform.py

potekang/shallow-fake

24b67ee4249d90f53db1516cdf262644a21a56be

[ "MIT" ]

null

imlib/transform.py

potekang/shallow-fake

24b67ee4249d90f53db1516cdf262644a21a56be

[ "MIT" ]

null

imlib/transform.py

potekang/shallow-fake

24b67ee4249d90f53db1516cdf262644a21a56be

[ "MIT" ]

null

import numpy as np import skimage.color as color import skimage.transform as transform rgb2gray = color.rgb2gray gray2rgb = color.gray2rgb imresize = transform.resize imrescale = transform.rescale def immerge(images, n_rows=None, n_cols=None, padding=0, pad_value=0): """Merge images to an image with (n_rows * h) * (n_cols * w). Parameters ---------- images : numpy.array or object which can be converted to numpy.array Images in shape of N * H * W(* C=1 or 3). """ images = np.array(images) n = images.shape[0] if n_rows: n_rows = max(min(n_rows, n), 1) n_cols = int(n - 0.5) // n_rows + 1 elif n_cols: n_cols = max(min(n_cols, n), 1) n_rows = int(n - 0.5) // n_cols + 1 else: n_rows = int(n ** 0.5) n_cols = int(n - 0.5) // n_rows + 1 h, w = images.shape[1], images.shape[2] shape = (h * n_rows + padding * (n_rows - 1), w * n_cols + padding * (n_cols - 1)) if images.ndim == 4: shape += (images.shape[3],) img = np.full(shape, pad_value, dtype=images.dtype) for idx, image in enumerate(images): i = idx % n_cols j = idx // n_cols img[j * (h + padding):j * (h + padding) + h, i * (w + padding):i * (w + padding) + w, ...] = image return img def immerge_(images, n_rows=None, n_cols=None, padding=0, pad_value=0): """Merge images to an image with (n_rows * h) * (n_cols * w). Parameters ---------- images : numpy.array or object which can be converted to numpy.array Images in shape of N * H * W(* C=1 or 3). """ images = np.array(images) n = images.shape[0] if n_rows: n_rows = max(min(n_rows, n), 1) n_cols = int(n - 0.5) // n_rows + 1 elif n_cols: n_cols = max(min(n_cols, n), 1) n_rows = int(n - 0.5) // n_cols + 1 else: n_rows = int(n ** 0.5) n_cols = int(n - 0.5) // n_rows + 1 h, w = images.shape[1], images.shape[2] n_rows = 1; n_cols = 1; padding = 0; #print(h); #print(w); #shape = (h * n_rows + padding * (n_rows - 1), # w * n_cols + padding * (n_cols - 1)) shape = (h * n_rows, w * n_cols ) if images.ndim == 4: shape += (images.shape[3],) img = np.full(shape, pad_value, dtype=images.dtype) for idx, image in enumerate(images): i = idx % n_cols j = idx // n_cols img[j * (h + padding):j * (h + padding) + h, i * (w + padding):i * (w + padding) + w, ...] = image #print(np.shape(img)) return img

28.648352

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0.540084

421

2,607

3.213777

0.154394

0.096083

0.029564

0.035477

0.818921

0

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0.305715

2,607

90

73

28.966667

0.717127

0.20023

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0.736842

0

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false

0

0.052632

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0.122807

0

null

0

1

0

1

0

null

0

7

96d6e84d11dc4119e4ef50096a79bc6c48617039

5,140

py

Python

entangld/test/test_gets.py

DaxBot/python-entangld

24aafad6c0235fb02ac94fe28ae46c3eb6a158e0

[ "MIT" ]

null

entangld/test/test_gets.py

DaxBot/python-entangld

24aafad6c0235fb02ac94fe28ae46c3eb6a158e0

[ "MIT" ]

null

entangld/test/test_gets.py

DaxBot/python-entangld

24aafad6c0235fb02ac94fe28ae46c3eb6a158e0

[ "MIT" ]

null

import unittest import asyncio from .helpers import block_until from .. import entangld class LocalGetExamples(unittest.TestCase): def setUp(self): self.store = entangld.Entangld() self.store.set("some_data",0.0) async def get_later(): await asyncio.sleep(0.01) return 1 async def get_async(): return 1 def get_now(): return 1 self.store.set("later",get_later) self.store.set("async",get_async) self.store.set("now",get_now) def tearDown(self): self.store.subscriptions = [] del self.store def test_simple_get(self): """Get data locally """ self.assertEqual(0.0,block_until(self.store.get("some_data"))) def test_get_function(self): """Get data from a function """ self.assertEqual(1,block_until(self.store.get("now"))) def test_get_async_function(self): """Get data from an async function """ self.assertEqual(1,block_until(self.store.get("async"))) def test_get_async_function_delay(self): """Get data from a delaying async function """ self.assertEqual(1,block_until(self.store.get("later"))) class LocalSynchronousGetExamples(unittest.TestCase): def setUp(self): self.store = entangld.Entangld() self.store.set("some_data",0.0) async def get_later(): await asyncio.sleep(0.01) return 1 async def get_async(): return 1 def get_now(): return 1 self.store.set("later",get_later) self.store.set("async",get_async) self.store.set("now",get_now) def tearDown(self): self.store.subscriptions = [] del self.store def test_simple_get(self): """Get data locally """ self.assertEqual(0.0,self.store.get_sync("some_data")) def test_get_function(self): """Get data from a function """ self.assertEqual(1,self.store.get_sync("now")) def test_get_async_function(self): """Get data from an async function """ self.assertEqual(1,self.store.get_sync("async")) def test_get_async_function_delay(self): """Get data from a delaying async function """ self.assertEqual(1,self.store.get_sync("later")) class LocalGetExamples(unittest.TestCase): def setUp(self): self.store = entangld.Entangld() self.store.set("some_data",0.0) async def get_later(): await asyncio.sleep(0.01) return 1 async def get_async(): return 1 def get_now(): return 1 self.store.set("later",get_later) self.store.set("async",get_async) self.store.set("now",get_now) def tearDown(self): self.store.subscriptions = [] del self.store def test_simple_get(self): """Get data locally """ self.assertEqual(0.0,block_until(self.store.get("some_data"))) def test_get_function(self): """Get data from a function """ self.assertEqual(1,block_until(self.store.get("now"))) def test_get_async_function(self): """Get data from an async function """ self.assertEqual(1,block_until(self.store.get("async"))) def test_get_async_function_delay(self): """Get data from a delaying async function """ self.assertEqual(1,block_until(self.store.get("later"))) class RemoteGetExamples(unittest.TestCase): def setUp(self): self.store = entangld.Entangld() self.remote = entangld.Entangld() self.store.transmit(lambda msg, obj: obj.receive_sync(msg,self.store)) self.remote.transmit(lambda msg, obj: obj.receive_sync(msg,self.remote)) self.store.attach("other",self.remote) self.remote.set("some_data",0.0) async def get_later(): await asyncio.sleep(0.01) return 1 async def get_async(): return 1 def get_now(): return 1 self.remote.set("later",get_later) self.remote.set("async",get_async) self.remote.set("now",get_now) def tearDown(self): self.store.subscriptions = [] self.remote.subscriptions = [] del self.store del self.remote def test_simple_get(self): """Get data remote """ self.assertEqual(0.0,block_until(self.store.get("other.some_data"))) def test_get_function(self): """Get remote data from a function """ self.assertEqual(1,block_until(self.store.get("other.now"))) def test_get_async_function(self): """Get remote data from an async function """ self.assertEqual(1,block_until(self.store.get("other.async"))) def test_get_async_function_delay(self): """Get remote data from a delaying async function """ self.assertEqual(1,block_until(self.store.get("other.later"))) if __name__ == "__main__": unittest.main()

27.634409

80

0.601946

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4.559451

0.082317

0.129388

0.064193

0.076229

0.890338

0.876964

0.869274

0.860247

0.832832

0.768305

0

0.013926

0.273541

5,140

185

81

27.783784

0.787092

0.118677

0

0.767857

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0.047973

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1

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false

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null

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8c573ea0957a787f6bc98546a09a25835b1809f9

87,501

py

Python

test/scenarios/msgraphuser/output/users_v1_0/azext_users_v1_0/generated/custom.py

necusjz/autorest.az

08dd5d35bd7f54f306917d0f1dfa1be4520c4059

[ "MIT" ]

null

test/scenarios/msgraphuser/output/users_v1_0/azext_users_v1_0/generated/custom.py

necusjz/autorest.az

08dd5d35bd7f54f306917d0f1dfa1be4520c4059

[ "MIT" ]

null

test/scenarios/msgraphuser/output/users_v1_0/azext_users_v1_0/generated/custom.py

necusjz/autorest.az

08dd5d35bd7f54f306917d0f1dfa1be4520c4059

[ "MIT" ]

null

# -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- # pylint: disable=line-too-long # pylint: disable=too-many-lines def users_user_list(client, orderby=None, select=None, expand=None): return client.list_user(orderby=orderby, select=select, expand=expand) def users_user_show(client, user_id, select=None, expand=None): return client.get_user(user_id=user_id, select=select, expand=expand) def users_user_create(client, id_=None, deleted_date_time=None, account_enabled=None, age_group=None, assigned_licenses=None, assigned_plans=None, business_phones=None, city=None, company_name=None, consent_provided_for_minor=None, country=None, created_date_time=None, creation_type=None, department=None, display_name=None, employee_id=None, external_user_state=None, external_user_state_change_date_time=None, fax_number=None, given_name=None, identities=None, im_addresses=None, is_resource_account=None, job_title=None, last_password_change_date_time=None, legal_age_group_classification=None, license_assignment_states=None, mail=None, mail_nickname=None, mobile_phone=None, office_location=None, on_premises_distinguished_name=None, on_premises_domain_name=None, on_premises_extension_attributes=None, on_premises_immutable_id=None, on_premises_last_sync_date_time=None, on_premises_provisioning_errors=None, on_premises_sam_account_name=None, on_premises_security_identifier=None, on_premises_sync_enabled=None, on_premises_user_principal_name=None, other_mails=None, password_policies=None, password_profile=None, postal_code=None, preferred_language=None, provisioned_plans=None, proxy_addresses=None, show_in_address_list=None, sign_in_sessions_valid_from_date_time=None, state=None, street_address=None, surname=None, usage_location=None, user_principal_name=None, user_type=None, device_enrollment_limit=None, about_me=None, birthday=None, hire_date=None, interests=None, my_site=None, past_projects=None, preferred_name=None, responsibilities=None, schools=None, skills=None, app_role_assignments=None, created_objects=None, direct_reports=None, license_details=None, manager=None, member_of=None, oauth2_permission_grants=None, owned_devices=None, owned_objects=None, registered_devices=None, scoped_role_member_of=None, transitive_member_of=None, calendar=None, calendar_groups=None, calendars=None, calendar_view=None, contact_folders=None, contacts=None, events=None, mail_folders=None, messages=None, people=None, photo=None, photos=None, drive=None, drives=None, followed_sites=None, extensions=None, managed_devices=None, managed_app_registrations=None, device_management_troubleshooting_events=None, activities=None, online_meetings=None, joined_teams=None, body_contains=None, body_or_subject_contains=None, categories=None, from_addresses=None, has_attachments=None, header_contains=None, importance=None, exceptions_is_approval_request=None, exceptions_is_automatic_forward=None, exceptions_is_automatic_reply=None, exceptions_is_encrypted=None, exceptions_is_meeting_request=None, exceptions_is_meeting_response=None, exceptions_is_non_delivery_report=None, exceptions_is_permission_controlled=None, exceptions_is_read_receipt=None, exceptions_is_signed=None, exceptions_is_voicemail=None, message_action_flag=None, not_sent_to_me=None, recipient_contains=None, sender_contains=None, sensitivity=None, sent_cc_me=None, sent_only_to_me=None, sent_to_addresses=None, sent_to_me=None, sent_to_or_cc_me=None, subject_contains=None, within_size_range=None, microsoft_graph_message_rule_predicates_body_contains=None, microsoft_graph_message_rule_predicates_body_or_subject_contains_body_or_subject_contains=None, microsoft_graph_message_rule_predicates_categories=None, microsoft_graph_message_rule_predicates_from_addresses=None, boolean_has_attachments=None, microsoft_graph_message_rule_predicates_header_contains=None, microsoft_graph_importance=None, is_approval_request=None, is_automatic_forward=None, is_automatic_reply=None, is_encrypted=None, is_meeting_request=None, is_meeting_response=None, is_non_delivery_report=None, is_permission_controlled=None, is_read_receipt=None, is_signed=None, is_voicemail=None, microsoft_graph_message_action_flag_message_action_flag=None, boolean_not_sent_to_me=None, microsoft_graph_message_rule_predicates_recipient_contains=None, microsoft_graph_message_rule_predicates_sender_contains=None, microsoft_graph_sensitivity=None, boolean_sent_cc_me=None, boolean_sent_only_to_me=None, microsoft_graph_message_rule_predicates_sent_to_addresses_sent_to_addresses=None, boolean_sent_to_me=None, boolean_sent_to_or_cc_me=None, microsoft_graph_message_rule_predicates_subject_contains=None, microsoft_graph_size_range_within_size_range=None, microsoft_graph_entity_id=None, notebooks=None, operations=None, pages=None, resources=None, section_groups=None, sections=None, id1=None, contribution_to_content_discovery_as_organization_disabled=None, contribution_to_content_discovery_disabled=None, id2=None, microsoft_graph_change_tracked_entity_created_date_time_created_date_time=None, last_modified_date_time=None, application=None, device=None, user=None, availability=None, id3=None, shared=None, trending=None, used=None, id4=None, plans=None, tasks=None, id5=None, master_categories=None, id6=None, overrides=None, archive_folder=None, automatic_replies_setting=None, date_format=None, delegate_meeting_message_delivery_options=None, language=None, time_format=None, time_zone=None, working_hours=None): body = {} if id_ is not None: body['id'] = id_ if deleted_date_time is not None: body['deleted_date_time'] = deleted_date_time if account_enabled is not None: body['account_enabled'] = account_enabled if age_group is not None: body['age_group'] = age_group if assigned_licenses is not None: body['assigned_licenses'] = assigned_licenses if assigned_plans is not None: body['assigned_plans'] = assigned_plans if business_phones is not None: body['business_phones'] = business_phones if city is not None: body['city'] = city if company_name is not None: body['company_name'] = company_name if consent_provided_for_minor is not None: body['consent_provided_for_minor'] = consent_provided_for_minor if country is not None: body['country'] = country if created_date_time is not None: body['created_date_time'] = created_date_time if creation_type is not None: body['creation_type'] = creation_type if department is not None: body['department'] = department if display_name is not None: body['display_name'] = display_name if employee_id is not None: body['employee_id'] = employee_id if external_user_state is not None: body['external_user_state'] = external_user_state if external_user_state_change_date_time is not None: body['external_user_state_change_date_time'] = external_user_state_change_date_time if fax_number is not None: body['fax_number'] = fax_number if given_name is not None: body['given_name'] = given_name if identities is not None: body['identities'] = identities if im_addresses is not None: body['im_addresses'] = im_addresses if is_resource_account is not None: body['is_resource_account'] = is_resource_account if job_title is not None: body['job_title'] = job_title if last_password_change_date_time is not None: body['last_password_change_date_time'] = last_password_change_date_time if legal_age_group_classification is not None: body['legal_age_group_classification'] = legal_age_group_classification if license_assignment_states is not None: body['license_assignment_states'] = license_assignment_states if mail is not None: body['mail'] = mail if mail_nickname is not None: body['mail_nickname'] = mail_nickname if mobile_phone is not None: body['mobile_phone'] = mobile_phone if office_location is not None: body['office_location'] = office_location if on_premises_distinguished_name is not None: body['on_premises_distinguished_name'] = on_premises_distinguished_name if on_premises_domain_name is not None: body['on_premises_domain_name'] = on_premises_domain_name if on_premises_extension_attributes is not None: body['on_premises_extension_attributes'] = on_premises_extension_attributes if on_premises_immutable_id is not None: body['on_premises_immutable_id'] = on_premises_immutable_id if on_premises_last_sync_date_time is not None: body['on_premises_last_sync_date_time'] = on_premises_last_sync_date_time if on_premises_provisioning_errors is not None: body['on_premises_provisioning_errors'] = on_premises_provisioning_errors if on_premises_sam_account_name is not None: body['on_premises_sam_account_name'] = on_premises_sam_account_name if on_premises_security_identifier is not None: body['on_premises_security_identifier'] = on_premises_security_identifier if on_premises_sync_enabled is not None: body['on_premises_sync_enabled'] = on_premises_sync_enabled if on_premises_user_principal_name is not None: body['on_premises_user_principal_name'] = on_premises_user_principal_name if other_mails is not None: body['other_mails'] = other_mails if password_policies is not None: body['password_policies'] = password_policies if password_profile is not None: body['password_profile'] = password_profile if postal_code is not None: body['postal_code'] = postal_code if preferred_language is not None: body['preferred_language'] = preferred_language if provisioned_plans is not None: body['provisioned_plans'] = provisioned_plans if proxy_addresses is not None: body['proxy_addresses'] = proxy_addresses if show_in_address_list is not None: body['show_in_address_list'] = show_in_address_list if sign_in_sessions_valid_from_date_time is not None: body['sign_in_sessions_valid_from_date_time'] = sign_in_sessions_valid_from_date_time if state is not None: body['state'] = state if street_address is not None: body['street_address'] = street_address if surname is not None: body['surname'] = surname if usage_location is not None: body['usage_location'] = usage_location if user_principal_name is not None: body['user_principal_name'] = user_principal_name if user_type is not None: body['user_type'] = user_type if device_enrollment_limit is not None: body['device_enrollment_limit'] = device_enrollment_limit if about_me is not None: body['about_me'] = about_me if birthday is not None: body['birthday'] = birthday if hire_date is not None: body['hire_date'] = hire_date if interests is not None: body['interests'] = interests if my_site is not None: body['my_site'] = my_site if past_projects is not None: body['past_projects'] = past_projects if preferred_name is not None: body['preferred_name'] = preferred_name if responsibilities is not None: body['responsibilities'] = responsibilities if schools is not None: body['schools'] = schools if skills is not None: body['skills'] = skills if app_role_assignments is not None: body['app_role_assignments'] = app_role_assignments if created_objects is not None: body['created_objects'] = created_objects if direct_reports is not None: body['direct_reports'] = direct_reports if license_details is not None: body['license_details'] = license_details if manager is not None: body['manager'] = manager if member_of is not None: body['member_of'] = member_of if oauth2_permission_grants is not None: body['oauth2_permission_grants'] = oauth2_permission_grants if owned_devices is not None: body['owned_devices'] = owned_devices if owned_objects is not None: body['owned_objects'] = owned_objects if registered_devices is not None: body['registered_devices'] = registered_devices if scoped_role_member_of is not None: body['scoped_role_member_of'] = scoped_role_member_of if transitive_member_of is not None: body['transitive_member_of'] = transitive_member_of if calendar is not None: body['calendar'] = calendar if calendar_groups is not None: body['calendar_groups'] = calendar_groups if calendars is not None: body['calendars'] = calendars if calendar_view is not None: body['calendar_view'] = calendar_view if contact_folders is not None: body['contact_folders'] = contact_folders if contacts is not None: body['contacts'] = contacts if events is not None: body['events'] = events if mail_folders is not None: body['mail_folders'] = mail_folders if messages is not None: body['messages'] = messages if people is not None: body['people'] = people if photo is not None: body['photo'] = photo if photos is not None: body['photos'] = photos if drive is not None: body['drive'] = drive if drives is not None: body['drives'] = drives if followed_sites is not None: body['followed_sites'] = followed_sites if extensions is not None: body['extensions'] = extensions if managed_devices is not None: body['managed_devices'] = managed_devices if managed_app_registrations is not None: body['managed_app_registrations'] = managed_app_registrations if device_management_troubleshooting_events is not None: body['device_management_troubleshooting_events'] = device_management_troubleshooting_events if activities is not None: body['activities'] = activities if online_meetings is not None: body['online_meetings'] = online_meetings if joined_teams is not None: body['joined_teams'] = joined_teams body['exceptions'] = {} if body_contains is not None: body['exceptions']['body_contains'] = body_contains if body_or_subject_contains is not None: body['exceptions']['body_or_subject_contains'] = body_or_subject_contains if categories is not None: body['exceptions']['categories'] = categories if from_addresses is not None: body['exceptions']['from_addresses'] = from_addresses if has_attachments is not None: body['exceptions']['has_attachments'] = has_attachments if header_contains is not None: body['exceptions']['header_contains'] = header_contains if importance is not None: body['exceptions']['importance'] = importance if exceptions_is_approval_request is not None: body['exceptions']['is_approval_request'] = exceptions_is_approval_request if exceptions_is_automatic_forward is not None: body['exceptions']['is_automatic_forward'] = exceptions_is_automatic_forward if exceptions_is_automatic_reply is not None: body['exceptions']['is_automatic_reply'] = exceptions_is_automatic_reply if exceptions_is_encrypted is not None: body['exceptions']['is_encrypted'] = exceptions_is_encrypted if exceptions_is_meeting_request is not None: body['exceptions']['is_meeting_request'] = exceptions_is_meeting_request if exceptions_is_meeting_response is not None: body['exceptions']['is_meeting_response'] = exceptions_is_meeting_response if exceptions_is_non_delivery_report is not None: body['exceptions']['is_non_delivery_report'] = exceptions_is_non_delivery_report if exceptions_is_permission_controlled is not None: body['exceptions']['is_permission_controlled'] = exceptions_is_permission_controlled if exceptions_is_read_receipt is not None: body['exceptions']['is_read_receipt'] = exceptions_is_read_receipt if exceptions_is_signed is not None: body['exceptions']['is_signed'] = exceptions_is_signed if exceptions_is_voicemail is not None: body['exceptions']['is_voicemail'] = exceptions_is_voicemail if message_action_flag is not None: body['exceptions']['message_action_flag'] = message_action_flag if not_sent_to_me is not None: body['exceptions']['not_sent_to_me'] = not_sent_to_me if recipient_contains is not None: body['exceptions']['recipient_contains'] = recipient_contains if sender_contains is not None: body['exceptions']['sender_contains'] = sender_contains if sensitivity is not None: body['exceptions']['sensitivity'] = sensitivity if sent_cc_me is not None: body['exceptions']['sent_cc_me'] = sent_cc_me if sent_only_to_me is not None: body['exceptions']['sent_only_to_me'] = sent_only_to_me if sent_to_addresses is not None: body['exceptions']['sent_to_addresses'] = sent_to_addresses if sent_to_me is not None: body['exceptions']['sent_to_me'] = sent_to_me if sent_to_or_cc_me is not None: body['exceptions']['sent_to_or_cc_me'] = sent_to_or_cc_me if subject_contains is not None: body['exceptions']['subject_contains'] = subject_contains if within_size_range is not None: body['exceptions']['within_size_range'] = within_size_range if len(body['exceptions']) == 0: del body['exceptions'] body['conditions'] = {} if microsoft_graph_message_rule_predicates_body_contains is not None: body['conditions']['body_contains'] = microsoft_graph_message_rule_predicates_body_contains if microsoft_graph_message_rule_predicates_body_or_subject_contains_body_or_subject_contains is not None: body['conditions']['body_or_subject_contains'] = microsoft_graph_message_rule_predicates_body_or_subject_contains_body_or_subject_contains if microsoft_graph_message_rule_predicates_categories is not None: body['conditions']['categories'] = microsoft_graph_message_rule_predicates_categories if microsoft_graph_message_rule_predicates_from_addresses is not None: body['conditions']['from_addresses'] = microsoft_graph_message_rule_predicates_from_addresses if boolean_has_attachments is not None: body['conditions']['has_attachments'] = boolean_has_attachments if microsoft_graph_message_rule_predicates_header_contains is not None: body['conditions']['header_contains'] = microsoft_graph_message_rule_predicates_header_contains if microsoft_graph_importance is not None: body['conditions']['importance'] = microsoft_graph_importance if is_approval_request is not None: body['conditions']['is_approval_request'] = is_approval_request if is_automatic_forward is not None: body['conditions']['is_automatic_forward'] = is_automatic_forward if is_automatic_reply is not None: body['conditions']['is_automatic_reply'] = is_automatic_reply if is_encrypted is not None: body['conditions']['is_encrypted'] = is_encrypted if is_meeting_request is not None: body['conditions']['is_meeting_request'] = is_meeting_request if is_meeting_response is not None: body['conditions']['is_meeting_response'] = is_meeting_response if is_non_delivery_report is not None: body['conditions']['is_non_delivery_report'] = is_non_delivery_report if is_permission_controlled is not None: body['conditions']['is_permission_controlled'] = is_permission_controlled if is_read_receipt is not None: body['conditions']['is_read_receipt'] = is_read_receipt if is_signed is not None: body['conditions']['is_signed'] = is_signed if is_voicemail is not None: body['conditions']['is_voicemail'] = is_voicemail if microsoft_graph_message_action_flag_message_action_flag is not None: body['conditions']['message_action_flag'] = microsoft_graph_message_action_flag_message_action_flag if boolean_not_sent_to_me is not None: body['conditions']['not_sent_to_me'] = boolean_not_sent_to_me if microsoft_graph_message_rule_predicates_recipient_contains is not None: body['conditions']['recipient_contains'] = microsoft_graph_message_rule_predicates_recipient_contains if microsoft_graph_message_rule_predicates_sender_contains is not None: body['conditions']['sender_contains'] = microsoft_graph_message_rule_predicates_sender_contains if microsoft_graph_sensitivity is not None: body['conditions']['sensitivity'] = microsoft_graph_sensitivity if boolean_sent_cc_me is not None: body['conditions']['sent_cc_me'] = boolean_sent_cc_me if boolean_sent_only_to_me is not None: body['conditions']['sent_only_to_me'] = boolean_sent_only_to_me if microsoft_graph_message_rule_predicates_sent_to_addresses_sent_to_addresses is not None: body['conditions']['sent_to_addresses'] = microsoft_graph_message_rule_predicates_sent_to_addresses_sent_to_addresses if boolean_sent_to_me is not None: body['conditions']['sent_to_me'] = boolean_sent_to_me if boolean_sent_to_or_cc_me is not None: body['conditions']['sent_to_or_cc_me'] = boolean_sent_to_or_cc_me if microsoft_graph_message_rule_predicates_subject_contains is not None: body['conditions']['subject_contains'] = microsoft_graph_message_rule_predicates_subject_contains if microsoft_graph_size_range_within_size_range is not None: body['conditions']['within_size_range'] = microsoft_graph_size_range_within_size_range if len(body['conditions']) == 0: del body['conditions'] body['onenote'] = {} if microsoft_graph_entity_id is not None: body['onenote']['id'] = microsoft_graph_entity_id if notebooks is not None: body['onenote']['notebooks'] = notebooks if operations is not None: body['onenote']['operations'] = operations if pages is not None: body['onenote']['pages'] = pages if resources is not None: body['onenote']['resources'] = resources if section_groups is not None: body['onenote']['section_groups'] = section_groups if sections is not None: body['onenote']['sections'] = sections if len(body['onenote']) == 0: del body['onenote'] body['settings'] = {} if id1 is not None: body['settings']['id'] = id1 if contribution_to_content_discovery_as_organization_disabled is not None: body['settings']['contribution_to_content_discovery_as_organization_disabled'] = contribution_to_content_discovery_as_organization_disabled if contribution_to_content_discovery_disabled is not None: body['settings']['contribution_to_content_discovery_disabled'] = contribution_to_content_discovery_disabled body['settings']['shift_preferences'] = {} if id2 is not None: body['settings']['shift_preferences']['id'] = id2 if microsoft_graph_change_tracked_entity_created_date_time_created_date_time is not None: body['settings']['shift_preferences']['created_date_time'] = microsoft_graph_change_tracked_entity_created_date_time_created_date_time if last_modified_date_time is not None: body['settings']['shift_preferences']['last_modified_date_time'] = last_modified_date_time body['settings']['shift_preferences']['last_modified_by'] = {} if application is not None: body['settings']['shift_preferences']['last_modified_by']['application'] = application if device is not None: body['settings']['shift_preferences']['last_modified_by']['device'] = device if user is not None: body['settings']['shift_preferences']['last_modified_by']['user'] = user if len(body['settings']['shift_preferences']['last_modified_by']) == 0: del body['settings']['shift_preferences']['last_modified_by'] if availability is not None: body['settings']['shift_preferences']['availability'] = availability if len(body['settings']['shift_preferences']) == 0: del body['settings']['shift_preferences'] if len(body['settings']) == 0: del body['settings'] body['insights'] = {} if id3 is not None: body['insights']['id'] = id3 if shared is not None: body['insights']['shared'] = shared if trending is not None: body['insights']['trending'] = trending if used is not None: body['insights']['used'] = used if len(body['insights']) == 0: del body['insights'] body['planner'] = {} if id4 is not None: body['planner']['id'] = id4 if plans is not None: body['planner']['plans'] = plans if tasks is not None: body['planner']['tasks'] = tasks if len(body['planner']) == 0: del body['planner'] body['outlook'] = {} if id5 is not None: body['outlook']['id'] = id5 if master_categories is not None: body['outlook']['master_categories'] = master_categories if len(body['outlook']) == 0: del body['outlook'] body['inference_classification'] = {} if id6 is not None: body['inference_classification']['id'] = id6 if overrides is not None: body['inference_classification']['overrides'] = overrides if len(body['inference_classification']) == 0: del body['inference_classification'] body['mailbox_settings'] = {} if archive_folder is not None: body['mailbox_settings']['archive_folder'] = archive_folder if automatic_replies_setting is not None: body['mailbox_settings']['automatic_replies_setting'] = automatic_replies_setting if date_format is not None: body['mailbox_settings']['date_format'] = date_format if delegate_meeting_message_delivery_options is not None: body['mailbox_settings']['delegate_meeting_message_delivery_options'] = delegate_meeting_message_delivery_options if language is not None: body['mailbox_settings']['language'] = language if time_format is not None: body['mailbox_settings']['time_format'] = time_format if time_zone is not None: body['mailbox_settings']['time_zone'] = time_zone if working_hours is not None: body['mailbox_settings']['working_hours'] = working_hours if len(body['mailbox_settings']) == 0: del body['mailbox_settings'] return client.create_user(body=body) def users_user_update(client, user_id, id_=None, deleted_date_time=None, account_enabled=None, age_group=None, assigned_licenses=None, assigned_plans=None, business_phones=None, city=None, company_name=None, consent_provided_for_minor=None, country=None, created_date_time=None, creation_type=None, department=None, display_name=None, employee_id=None, external_user_state=None, external_user_state_change_date_time=None, fax_number=None, given_name=None, identities=None, im_addresses=None, is_resource_account=None, job_title=None, last_password_change_date_time=None, legal_age_group_classification=None, license_assignment_states=None, mail=None, mail_nickname=None, mobile_phone=None, office_location=None, on_premises_distinguished_name=None, on_premises_domain_name=None, on_premises_extension_attributes=None, on_premises_immutable_id=None, on_premises_last_sync_date_time=None, on_premises_provisioning_errors=None, on_premises_sam_account_name=None, on_premises_security_identifier=None, on_premises_sync_enabled=None, on_premises_user_principal_name=None, other_mails=None, password_policies=None, password_profile=None, postal_code=None, preferred_language=None, provisioned_plans=None, proxy_addresses=None, show_in_address_list=None, sign_in_sessions_valid_from_date_time=None, state=None, street_address=None, surname=None, usage_location=None, user_principal_name=None, user_type=None, device_enrollment_limit=None, about_me=None, birthday=None, hire_date=None, interests=None, my_site=None, past_projects=None, preferred_name=None, responsibilities=None, schools=None, skills=None, app_role_assignments=None, created_objects=None, direct_reports=None, license_details=None, manager=None, member_of=None, oauth2_permission_grants=None, owned_devices=None, owned_objects=None, registered_devices=None, scoped_role_member_of=None, transitive_member_of=None, calendar=None, calendar_groups=None, calendars=None, calendar_view=None, contact_folders=None, contacts=None, events=None, mail_folders=None, messages=None, people=None, photo=None, photos=None, drive=None, drives=None, followed_sites=None, extensions=None, managed_devices=None, managed_app_registrations=None, device_management_troubleshooting_events=None, activities=None, online_meetings=None, joined_teams=None, body_contains=None, body_or_subject_contains=None, categories=None, from_addresses=None, has_attachments=None, header_contains=None, importance=None, exceptions_is_approval_request=None, exceptions_is_automatic_forward=None, exceptions_is_automatic_reply=None, exceptions_is_encrypted=None, exceptions_is_meeting_request=None, exceptions_is_meeting_response=None, exceptions_is_non_delivery_report=None, exceptions_is_permission_controlled=None, exceptions_is_read_receipt=None, exceptions_is_signed=None, exceptions_is_voicemail=None, message_action_flag=None, not_sent_to_me=None, recipient_contains=None, sender_contains=None, sensitivity=None, sent_cc_me=None, sent_only_to_me=None, sent_to_addresses=None, sent_to_me=None, sent_to_or_cc_me=None, subject_contains=None, within_size_range=None, microsoft_graph_message_rule_predicates_body_contains=None, microsoft_graph_message_rule_predicates_body_or_subject_contains_body_or_subject_contains=None, microsoft_graph_message_rule_predicates_categories=None, microsoft_graph_message_rule_predicates_from_addresses=None, boolean_has_attachments=None, microsoft_graph_message_rule_predicates_header_contains=None, microsoft_graph_importance=None, is_approval_request=None, is_automatic_forward=None, is_automatic_reply=None, is_encrypted=None, is_meeting_request=None, is_meeting_response=None, is_non_delivery_report=None, is_permission_controlled=None, is_read_receipt=None, is_signed=None, is_voicemail=None, microsoft_graph_message_action_flag_message_action_flag=None, boolean_not_sent_to_me=None, microsoft_graph_message_rule_predicates_recipient_contains=None, microsoft_graph_message_rule_predicates_sender_contains=None, microsoft_graph_sensitivity=None, boolean_sent_cc_me=None, boolean_sent_only_to_me=None, microsoft_graph_message_rule_predicates_sent_to_addresses_sent_to_addresses=None, boolean_sent_to_me=None, boolean_sent_to_or_cc_me=None, microsoft_graph_message_rule_predicates_subject_contains=None, microsoft_graph_size_range_within_size_range=None, microsoft_graph_entity_id=None, notebooks=None, operations=None, pages=None, resources=None, section_groups=None, sections=None, id1=None, contribution_to_content_discovery_as_organization_disabled=None, contribution_to_content_discovery_disabled=None, id2=None, microsoft_graph_change_tracked_entity_created_date_time_created_date_time=None, last_modified_date_time=None, application=None, device=None, user=None, availability=None, id3=None, shared=None, trending=None, used=None, id4=None, plans=None, tasks=None, id5=None, master_categories=None, id6=None, overrides=None, archive_folder=None, automatic_replies_setting=None, date_format=None, delegate_meeting_message_delivery_options=None, language=None, time_format=None, time_zone=None, working_hours=None): body = {} if id_ is not None: body['id'] = id_ if deleted_date_time is not None: body['deleted_date_time'] = deleted_date_time if account_enabled is not None: body['account_enabled'] = account_enabled if age_group is not None: body['age_group'] = age_group if assigned_licenses is not None: body['assigned_licenses'] = assigned_licenses if assigned_plans is not None: body['assigned_plans'] = assigned_plans if business_phones is not None: body['business_phones'] = business_phones if city is not None: body['city'] = city if company_name is not None: body['company_name'] = company_name if consent_provided_for_minor is not None: body['consent_provided_for_minor'] = consent_provided_for_minor if country is not None: body['country'] = country if created_date_time is not None: body['created_date_time'] = created_date_time if creation_type is not None: body['creation_type'] = creation_type if department is not None: body['department'] = department if display_name is not None: body['display_name'] = display_name if employee_id is not None: body['employee_id'] = employee_id if external_user_state is not None: body['external_user_state'] = external_user_state if external_user_state_change_date_time is not None: body['external_user_state_change_date_time'] = external_user_state_change_date_time if fax_number is not None: body['fax_number'] = fax_number if given_name is not None: body['given_name'] = given_name if identities is not None: body['identities'] = identities if im_addresses is not None: body['im_addresses'] = im_addresses if is_resource_account is not None: body['is_resource_account'] = is_resource_account if job_title is not None: body['job_title'] = job_title if last_password_change_date_time is not None: body['last_password_change_date_time'] = last_password_change_date_time if legal_age_group_classification is not None: body['legal_age_group_classification'] = legal_age_group_classification if license_assignment_states is not None: body['license_assignment_states'] = license_assignment_states if mail is not None: body['mail'] = mail if mail_nickname is not None: body['mail_nickname'] = mail_nickname if mobile_phone is not None: body['mobile_phone'] = mobile_phone if office_location is not None: body['office_location'] = office_location if on_premises_distinguished_name is not None: body['on_premises_distinguished_name'] = on_premises_distinguished_name if on_premises_domain_name is not None: body['on_premises_domain_name'] = on_premises_domain_name if on_premises_extension_attributes is not None: body['on_premises_extension_attributes'] = on_premises_extension_attributes if on_premises_immutable_id is not None: body['on_premises_immutable_id'] = on_premises_immutable_id if on_premises_last_sync_date_time is not None: body['on_premises_last_sync_date_time'] = on_premises_last_sync_date_time if on_premises_provisioning_errors is not None: body['on_premises_provisioning_errors'] = on_premises_provisioning_errors if on_premises_sam_account_name is not None: body['on_premises_sam_account_name'] = on_premises_sam_account_name if on_premises_security_identifier is not None: body['on_premises_security_identifier'] = on_premises_security_identifier if on_premises_sync_enabled is not None: body['on_premises_sync_enabled'] = on_premises_sync_enabled if on_premises_user_principal_name is not None: body['on_premises_user_principal_name'] = on_premises_user_principal_name if other_mails is not None: body['other_mails'] = other_mails if password_policies is not None: body['password_policies'] = password_policies if password_profile is not None: body['password_profile'] = password_profile if postal_code is not None: body['postal_code'] = postal_code if preferred_language is not None: body['preferred_language'] = preferred_language if provisioned_plans is not None: body['provisioned_plans'] = provisioned_plans if proxy_addresses is not None: body['proxy_addresses'] = proxy_addresses if show_in_address_list is not None: body['show_in_address_list'] = show_in_address_list if sign_in_sessions_valid_from_date_time is not None: body['sign_in_sessions_valid_from_date_time'] = sign_in_sessions_valid_from_date_time if state is not None: body['state'] = state if street_address is not None: body['street_address'] = street_address if surname is not None: body['surname'] = surname if usage_location is not None: body['usage_location'] = usage_location if user_principal_name is not None: body['user_principal_name'] = user_principal_name if user_type is not None: body['user_type'] = user_type if device_enrollment_limit is not None: body['device_enrollment_limit'] = device_enrollment_limit if about_me is not None: body['about_me'] = about_me if birthday is not None: body['birthday'] = birthday if hire_date is not None: body['hire_date'] = hire_date if interests is not None: body['interests'] = interests if my_site is not None: body['my_site'] = my_site if past_projects is not None: body['past_projects'] = past_projects if preferred_name is not None: body['preferred_name'] = preferred_name if responsibilities is not None: body['responsibilities'] = responsibilities if schools is not None: body['schools'] = schools if skills is not None: body['skills'] = skills if app_role_assignments is not None: body['app_role_assignments'] = app_role_assignments if created_objects is not None: body['created_objects'] = created_objects if direct_reports is not None: body['direct_reports'] = direct_reports if license_details is not None: body['license_details'] = license_details if manager is not None: body['manager'] = manager if member_of is not None: body['member_of'] = member_of if oauth2_permission_grants is not None: body['oauth2_permission_grants'] = oauth2_permission_grants if owned_devices is not None: body['owned_devices'] = owned_devices if owned_objects is not None: body['owned_objects'] = owned_objects if registered_devices is not None: body['registered_devices'] = registered_devices if scoped_role_member_of is not None: body['scoped_role_member_of'] = scoped_role_member_of if transitive_member_of is not None: body['transitive_member_of'] = transitive_member_of if calendar is not None: body['calendar'] = calendar if calendar_groups is not None: body['calendar_groups'] = calendar_groups if calendars is not None: body['calendars'] = calendars if calendar_view is not None: body['calendar_view'] = calendar_view if contact_folders is not None: body['contact_folders'] = contact_folders if contacts is not None: body['contacts'] = contacts if events is not None: body['events'] = events if mail_folders is not None: body['mail_folders'] = mail_folders if messages is not None: body['messages'] = messages if people is not None: body['people'] = people if photo is not None: body['photo'] = photo if photos is not None: body['photos'] = photos if drive is not None: body['drive'] = drive if drives is not None: body['drives'] = drives if followed_sites is not None: body['followed_sites'] = followed_sites if extensions is not None: body['extensions'] = extensions if managed_devices is not None: body['managed_devices'] = managed_devices if managed_app_registrations is not None: body['managed_app_registrations'] = managed_app_registrations if device_management_troubleshooting_events is not None: body['device_management_troubleshooting_events'] = device_management_troubleshooting_events if activities is not None: body['activities'] = activities if online_meetings is not None: body['online_meetings'] = online_meetings if joined_teams is not None: body['joined_teams'] = joined_teams body['exceptions'] = {} if body_contains is not None: body['exceptions']['body_contains'] = body_contains if body_or_subject_contains is not None: body['exceptions']['body_or_subject_contains'] = body_or_subject_contains if categories is not None: body['exceptions']['categories'] = categories if from_addresses is not None: body['exceptions']['from_addresses'] = from_addresses if has_attachments is not None: body['exceptions']['has_attachments'] = has_attachments if header_contains is not None: body['exceptions']['header_contains'] = header_contains if importance is not None: body['exceptions']['importance'] = importance if exceptions_is_approval_request is not None: body['exceptions']['is_approval_request'] = exceptions_is_approval_request if exceptions_is_automatic_forward is not None: body['exceptions']['is_automatic_forward'] = exceptions_is_automatic_forward if exceptions_is_automatic_reply is not None: body['exceptions']['is_automatic_reply'] = exceptions_is_automatic_reply if exceptions_is_encrypted is not None: body['exceptions']['is_encrypted'] = exceptions_is_encrypted if exceptions_is_meeting_request is not None: body['exceptions']['is_meeting_request'] = exceptions_is_meeting_request if exceptions_is_meeting_response is not None: body['exceptions']['is_meeting_response'] = exceptions_is_meeting_response if exceptions_is_non_delivery_report is not None: body['exceptions']['is_non_delivery_report'] = exceptions_is_non_delivery_report if exceptions_is_permission_controlled is not None: body['exceptions']['is_permission_controlled'] = exceptions_is_permission_controlled if exceptions_is_read_receipt is not None: body['exceptions']['is_read_receipt'] = exceptions_is_read_receipt if exceptions_is_signed is not None: body['exceptions']['is_signed'] = exceptions_is_signed if exceptions_is_voicemail is not None: body['exceptions']['is_voicemail'] = exceptions_is_voicemail if message_action_flag is not None: body['exceptions']['message_action_flag'] = message_action_flag if not_sent_to_me is not None: body['exceptions']['not_sent_to_me'] = not_sent_to_me if recipient_contains is not None: body['exceptions']['recipient_contains'] = recipient_contains if sender_contains is not None: body['exceptions']['sender_contains'] = sender_contains if sensitivity is not None: body['exceptions']['sensitivity'] = sensitivity if sent_cc_me is not None: body['exceptions']['sent_cc_me'] = sent_cc_me if sent_only_to_me is not None: body['exceptions']['sent_only_to_me'] = sent_only_to_me if sent_to_addresses is not None: body['exceptions']['sent_to_addresses'] = sent_to_addresses if sent_to_me is not None: body['exceptions']['sent_to_me'] = sent_to_me if sent_to_or_cc_me is not None: body['exceptions']['sent_to_or_cc_me'] = sent_to_or_cc_me if subject_contains is not None: body['exceptions']['subject_contains'] = subject_contains if within_size_range is not None: body['exceptions']['within_size_range'] = within_size_range if len(body['exceptions']) == 0: del body['exceptions'] body['conditions'] = {} if microsoft_graph_message_rule_predicates_body_contains is not None: body['conditions']['body_contains'] = microsoft_graph_message_rule_predicates_body_contains if microsoft_graph_message_rule_predicates_body_or_subject_contains_body_or_subject_contains is not None: body['conditions']['body_or_subject_contains'] = microsoft_graph_message_rule_predicates_body_or_subject_contains_body_or_subject_contains if microsoft_graph_message_rule_predicates_categories is not None: body['conditions']['categories'] = microsoft_graph_message_rule_predicates_categories if microsoft_graph_message_rule_predicates_from_addresses is not None: body['conditions']['from_addresses'] = microsoft_graph_message_rule_predicates_from_addresses if boolean_has_attachments is not None: body['conditions']['has_attachments'] = boolean_has_attachments if microsoft_graph_message_rule_predicates_header_contains is not None: body['conditions']['header_contains'] = microsoft_graph_message_rule_predicates_header_contains if microsoft_graph_importance is not None: body['conditions']['importance'] = microsoft_graph_importance if is_approval_request is not None: body['conditions']['is_approval_request'] = is_approval_request if is_automatic_forward is not None: body['conditions']['is_automatic_forward'] = is_automatic_forward if is_automatic_reply is not None: body['conditions']['is_automatic_reply'] = is_automatic_reply if is_encrypted is not None: body['conditions']['is_encrypted'] = is_encrypted if is_meeting_request is not None: body['conditions']['is_meeting_request'] = is_meeting_request if is_meeting_response is not None: body['conditions']['is_meeting_response'] = is_meeting_response if is_non_delivery_report is not None: body['conditions']['is_non_delivery_report'] = is_non_delivery_report if is_permission_controlled is not None: body['conditions']['is_permission_controlled'] = is_permission_controlled if is_read_receipt is not None: body['conditions']['is_read_receipt'] = is_read_receipt if is_signed is not None: body['conditions']['is_signed'] = is_signed if is_voicemail is not None: body['conditions']['is_voicemail'] = is_voicemail if microsoft_graph_message_action_flag_message_action_flag is not None: body['conditions']['message_action_flag'] = microsoft_graph_message_action_flag_message_action_flag if boolean_not_sent_to_me is not None: body['conditions']['not_sent_to_me'] = boolean_not_sent_to_me if microsoft_graph_message_rule_predicates_recipient_contains is not None: body['conditions']['recipient_contains'] = microsoft_graph_message_rule_predicates_recipient_contains if microsoft_graph_message_rule_predicates_sender_contains is not None: body['conditions']['sender_contains'] = microsoft_graph_message_rule_predicates_sender_contains if microsoft_graph_sensitivity is not None: body['conditions']['sensitivity'] = microsoft_graph_sensitivity if boolean_sent_cc_me is not None: body['conditions']['sent_cc_me'] = boolean_sent_cc_me if boolean_sent_only_to_me is not None: body['conditions']['sent_only_to_me'] = boolean_sent_only_to_me if microsoft_graph_message_rule_predicates_sent_to_addresses_sent_to_addresses is not None: body['conditions']['sent_to_addresses'] = microsoft_graph_message_rule_predicates_sent_to_addresses_sent_to_addresses if boolean_sent_to_me is not None: body['conditions']['sent_to_me'] = boolean_sent_to_me if boolean_sent_to_or_cc_me is not None: body['conditions']['sent_to_or_cc_me'] = boolean_sent_to_or_cc_me if microsoft_graph_message_rule_predicates_subject_contains is not None: body['conditions']['subject_contains'] = microsoft_graph_message_rule_predicates_subject_contains if microsoft_graph_size_range_within_size_range is not None: body['conditions']['within_size_range'] = microsoft_graph_size_range_within_size_range if len(body['conditions']) == 0: del body['conditions'] body['onenote'] = {} if microsoft_graph_entity_id is not None: body['onenote']['id'] = microsoft_graph_entity_id if notebooks is not None: body['onenote']['notebooks'] = notebooks if operations is not None: body['onenote']['operations'] = operations if pages is not None: body['onenote']['pages'] = pages if resources is not None: body['onenote']['resources'] = resources if section_groups is not None: body['onenote']['section_groups'] = section_groups if sections is not None: body['onenote']['sections'] = sections if len(body['onenote']) == 0: del body['onenote'] body['settings'] = {} if id1 is not None: body['settings']['id'] = id1 if contribution_to_content_discovery_as_organization_disabled is not None: body['settings']['contribution_to_content_discovery_as_organization_disabled'] = contribution_to_content_discovery_as_organization_disabled if contribution_to_content_discovery_disabled is not None: body['settings']['contribution_to_content_discovery_disabled'] = contribution_to_content_discovery_disabled body['settings']['shift_preferences'] = {} if id2 is not None: body['settings']['shift_preferences']['id'] = id2 if microsoft_graph_change_tracked_entity_created_date_time_created_date_time is not None: body['settings']['shift_preferences']['created_date_time'] = microsoft_graph_change_tracked_entity_created_date_time_created_date_time if last_modified_date_time is not None: body['settings']['shift_preferences']['last_modified_date_time'] = last_modified_date_time body['settings']['shift_preferences']['last_modified_by'] = {} if application is not None: body['settings']['shift_preferences']['last_modified_by']['application'] = application if device is not None: body['settings']['shift_preferences']['last_modified_by']['device'] = device if user is not None: body['settings']['shift_preferences']['last_modified_by']['user'] = user if len(body['settings']['shift_preferences']['last_modified_by']) == 0: del body['settings']['shift_preferences']['last_modified_by'] if availability is not None: body['settings']['shift_preferences']['availability'] = availability if len(body['settings']['shift_preferences']) == 0: del body['settings']['shift_preferences'] if len(body['settings']) == 0: del body['settings'] body['insights'] = {} if id3 is not None: body['insights']['id'] = id3 if shared is not None: body['insights']['shared'] = shared if trending is not None: body['insights']['trending'] = trending if used is not None: body['insights']['used'] = used if len(body['insights']) == 0: del body['insights'] body['planner'] = {} if id4 is not None: body['planner']['id'] = id4 if plans is not None: body['planner']['plans'] = plans if tasks is not None: body['planner']['tasks'] = tasks if len(body['planner']) == 0: del body['planner'] body['outlook'] = {} if id5 is not None: body['outlook']['id'] = id5 if master_categories is not None: body['outlook']['master_categories'] = master_categories if len(body['outlook']) == 0: del body['outlook'] body['inference_classification'] = {} if id6 is not None: body['inference_classification']['id'] = id6 if overrides is not None: body['inference_classification']['overrides'] = overrides if len(body['inference_classification']) == 0: del body['inference_classification'] body['mailbox_settings'] = {} if archive_folder is not None: body['mailbox_settings']['archive_folder'] = archive_folder if automatic_replies_setting is not None: body['mailbox_settings']['automatic_replies_setting'] = automatic_replies_setting if date_format is not None: body['mailbox_settings']['date_format'] = date_format if delegate_meeting_message_delivery_options is not None: body['mailbox_settings']['delegate_meeting_message_delivery_options'] = delegate_meeting_message_delivery_options if language is not None: body['mailbox_settings']['language'] = language if time_format is not None: body['mailbox_settings']['time_format'] = time_format if time_zone is not None: body['mailbox_settings']['time_zone'] = time_zone if working_hours is not None: body['mailbox_settings']['working_hours'] = working_hours if len(body['mailbox_settings']) == 0: del body['mailbox_settings'] return client.update_user(user_id=user_id, body=body) def users_user_delete(client, user_id, if_match=None): return client.delete_user(user_id=user_id, if_match=if_match) def users_user_create_extension(client, user_id, id_=None): body = {} if id_ is not None: body['id'] = id_ return client.create_extensions(user_id=user_id, body=body) def users_user_create_license_detail(client, user_id, id_=None, service_plans=None, sku_id=None, sku_part_number=None): body = {} if id_ is not None: body['id'] = id_ if service_plans is not None: body['service_plans'] = service_plans if sku_id is not None: body['sku_id'] = sku_id if sku_part_number is not None: body['sku_part_number'] = sku_part_number return client.create_license_details(user_id=user_id, body=body) def users_user_create_photo(client, user_id, id_=None, height=None, width=None): body = {} if id_ is not None: body['id'] = id_ if height is not None: body['height'] = height if width is not None: body['width'] = width return client.create_photos(user_id=user_id, body=body) def users_user_create_ref_created_object(client, user_id, body): return client.create_ref_created_objects(user_id=user_id, body=body) def users_user_create_ref_direct_report(client, user_id, body): return client.create_ref_direct_reports(user_id=user_id, body=body) def users_user_create_ref_member_of(client, user_id, body): return client.create_ref_member_of(user_id=user_id, body=body) def users_user_create_ref_oauth2_permission_grant(client, user_id, body): return client.create_ref_oauth2_permission_grants(user_id=user_id, body=body) def users_user_create_ref_owned_device(client, user_id, body): return client.create_ref_owned_devices(user_id=user_id, body=body) def users_user_create_ref_owned_object(client, user_id, body): return client.create_ref_owned_objects(user_id=user_id, body=body) def users_user_create_ref_registered_device(client, user_id, body): return client.create_ref_registered_devices(user_id=user_id, body=body) def users_user_create_ref_transitive_member_of(client, user_id, body): return client.create_ref_transitive_member_of(user_id=user_id, body=body) def users_user_delete_extension(client, user_id, extension_id, if_match=None): return client.delete_extensions(user_id=user_id, extension_id=extension_id, if_match=if_match) def users_user_delete_license_detail(client, user_id, license_details_id, if_match=None): return client.delete_license_details(user_id=user_id, license_details_id=license_details_id, if_match=if_match) def users_user_delete_outlook(client, user_id, if_match=None): return client.delete_outlook(user_id=user_id, if_match=if_match) def users_user_delete_photo(client, user_id, profile_photo_id=None, if_match=None): if user_id is not None and profile_photo_id is not None: return client.delete_photos(user_id=user_id, profile_photo_id=profile_photo_id, if_match=if_match) return client.delete_photo(user_id=user_id, if_match=if_match) def users_user_delete_ref_manager(client, user_id, if_match=None): return client.delete_ref_manager(user_id=user_id, if_match=if_match) def users_user_delete_setting(client, user_id, if_match=None): return client.delete_settings(user_id=user_id, if_match=if_match) def users_user_list_created_object(client, user_id, orderby=None, select=None, expand=None): return client.list_created_objects(user_id=user_id, orderby=orderby, select=select, expand=expand) def users_user_list_direct_report(client, user_id, orderby=None, select=None, expand=None): return client.list_direct_reports(user_id=user_id, orderby=orderby, select=select, expand=expand) def users_user_list_extension(client, user_id, orderby=None, select=None, expand=None): return client.list_extensions(user_id=user_id, orderby=orderby, select=select, expand=expand) def users_user_list_license_detail(client, user_id, orderby=None, select=None, expand=None): return client.list_license_details(user_id=user_id, orderby=orderby, select=select, expand=expand) def users_user_list_member_of(client, user_id, orderby=None, select=None, expand=None): return client.list_member_of(user_id=user_id, orderby=orderby, select=select, expand=expand) def users_user_list_oauth2_permission_grant(client, user_id, orderby=None, select=None, expand=None): return client.list_oauth2_permission_grants(user_id=user_id, orderby=orderby, select=select, expand=expand) def users_user_list_owned_device(client, user_id, orderby=None, select=None, expand=None): return client.list_owned_devices(user_id=user_id, orderby=orderby, select=select, expand=expand) def users_user_list_owned_object(client, user_id, orderby=None, select=None, expand=None): return client.list_owned_objects(user_id=user_id, orderby=orderby, select=select, expand=expand) def users_user_list_photo(client, user_id, orderby=None, select=None, expand=None): return client.list_photos(user_id=user_id, orderby=orderby, select=select, expand=expand) def users_user_list_ref_created_object(client, user_id, orderby=None): return client.list_ref_created_objects(user_id=user_id, orderby=orderby) def users_user_list_ref_direct_report(client, user_id, orderby=None): return client.list_ref_direct_reports(user_id=user_id, orderby=orderby) def users_user_list_ref_member_of(client, user_id, orderby=None): return client.list_ref_member_of(user_id=user_id, orderby=orderby) def users_user_list_ref_oauth2_permission_grant(client, user_id, orderby=None): return client.list_ref_oauth2_permission_grants(user_id=user_id, orderby=orderby) def users_user_list_ref_owned_device(client, user_id, orderby=None): return client.list_ref_owned_devices(user_id=user_id, orderby=orderby) def users_user_list_ref_owned_object(client, user_id, orderby=None): return client.list_ref_owned_objects(user_id=user_id, orderby=orderby) def users_user_list_ref_registered_device(client, user_id, orderby=None): return client.list_ref_registered_devices(user_id=user_id, orderby=orderby) def users_user_list_ref_transitive_member_of(client, user_id, orderby=None): return client.list_ref_transitive_member_of(user_id=user_id, orderby=orderby) def users_user_list_registered_device(client, user_id, orderby=None, select=None, expand=None): return client.list_registered_devices(user_id=user_id, orderby=orderby, select=select, expand=expand) def users_user_list_transitive_member_of(client, user_id, orderby=None, select=None, expand=None): return client.list_transitive_member_of(user_id=user_id, orderby=orderby, select=select, expand=expand) def users_user_set_ref_manager(client, user_id, body): return client.set_ref_manager(user_id=user_id, body=body) def users_user_show_extension(client, user_id, extension_id, select=None, expand=None): return client.get_extensions(user_id=user_id, extension_id=extension_id, select=select, expand=expand) def users_user_show_license_detail(client, user_id, license_details_id, select=None, expand=None): return client.get_license_details(user_id=user_id, license_details_id=license_details_id, select=select, expand=expand) def users_user_show_manager(client, user_id, select=None, expand=None): return client.get_manager(user_id=user_id, select=select, expand=expand) def users_user_show_outlook(client, user_id, select=None, expand=None): return client.get_outlook(user_id=user_id, select=select, expand=expand) def users_user_show_photo(client, user_id, profile_photo_id=None, select=None, expand=None): if user_id is not None and profile_photo_id is not None: return client.get_photos(user_id=user_id, profile_photo_id=profile_photo_id, select=select, expand=expand) return client.get_photo(user_id=user_id, select=select, expand=expand) def users_user_show_ref_manager(client, user_id): return client.get_ref_manager(user_id=user_id) def users_user_show_setting(client, user_id, select=None, expand=None): return client.get_settings(user_id=user_id, select=select, expand=expand) def users_user_update_extension(client, user_id, extension_id, id_=None): body = {} if id_ is not None: body['id'] = id_ return client.update_extensions(user_id=user_id, extension_id=extension_id, body=body) def users_user_update_license_detail(client, user_id, license_details_id, id_=None, service_plans=None, sku_id=None, sku_part_number=None): body = {} if id_ is not None: body['id'] = id_ if service_plans is not None: body['service_plans'] = service_plans if sku_id is not None: body['sku_id'] = sku_id if sku_part_number is not None: body['sku_part_number'] = sku_part_number return client.update_license_details(user_id=user_id, license_details_id=license_details_id, body=body) def users_user_update_outlook(client, user_id, id_=None, master_categories=None): body = {} if id_ is not None: body['id'] = id_ if master_categories is not None: body['master_categories'] = master_categories return client.update_outlook(user_id=user_id, body=body) def users_user_update_photo(client, user_id, profile_photo_id=None, id_=None, height=None, width=None): body = {} if id_ is not None: body['id'] = id_ if height is not None: body['height'] = height if width is not None: body['width'] = width if user_id is not None and profile_photo_id is not None: return client.update_photos(user_id=user_id, profile_photo_id=profile_photo_id, body=body) return client.update_photo(user_id=user_id, body=body) def users_user_update_setting(client, user_id, id_=None, contribution_to_content_discovery_as_organization_disabled=None, contribution_to_content_discovery_disabled=None, microsoft_graph_entity_id=None, created_date_time=None, last_modified_date_time=None, application=None, device=None, user=None, availability=None): body = {} if id_ is not None: body['id'] = id_ if contribution_to_content_discovery_as_organization_disabled is not None: body['contribution_to_content_discovery_as_organization_disabled'] = contribution_to_content_discovery_as_organization_disabled if contribution_to_content_discovery_disabled is not None: body['contribution_to_content_discovery_disabled'] = contribution_to_content_discovery_disabled body['shift_preferences'] = {} if microsoft_graph_entity_id is not None: body['shift_preferences']['id'] = microsoft_graph_entity_id if created_date_time is not None: body['shift_preferences']['created_date_time'] = created_date_time if last_modified_date_time is not None: body['shift_preferences']['last_modified_date_time'] = last_modified_date_time body['shift_preferences']['last_modified_by'] = {} if application is not None: body['shift_preferences']['last_modified_by']['application'] = application if device is not None: body['shift_preferences']['last_modified_by']['device'] = device if user is not None: body['shift_preferences']['last_modified_by']['user'] = user if len(body['shift_preferences']['last_modified_by']) == 0: del body['shift_preferences']['last_modified_by'] if availability is not None: body['shift_preferences']['availability'] = availability if len(body['shift_preferences']) == 0: del body['shift_preferences'] return client.update_settings(user_id=user_id, body=body) def users_user_outlook_create_master_category(client, user_id, id_=None, color=None, display_name=None): body = {} if id_ is not None: body['id'] = id_ if color is not None: body['color'] = color if display_name is not None: body['display_name'] = display_name return client.create_master_categories(user_id=user_id, body=body) def users_user_outlook_delete_master_category(client, user_id, outlook_category_id, if_match=None): return client.delete_master_categories(user_id=user_id, outlook_category_id=outlook_category_id, if_match=if_match) def users_user_outlook_list_master_category(client, user_id, orderby=None, select=None, expand=None): return client.list_master_categories(user_id=user_id, orderby=orderby, select=select, expand=expand) def users_user_outlook_show_master_category(client, user_id, outlook_category_id, select=None, expand=None): return client.get_master_categories(user_id=user_id, outlook_category_id=outlook_category_id, select=select, expand=expand) def users_user_outlook_update_master_category(client, user_id, outlook_category_id, id_=None, color=None, display_name=None): body = {} if id_ is not None: body['id'] = id_ if color is not None: body['color'] = color if display_name is not None: body['display_name'] = display_name return client.update_master_categories(user_id=user_id, outlook_category_id=outlook_category_id, body=body) def users_user_setting_delete_shift_preference(client, user_id, if_match=None): return client.delete_shift_preferences(user_id=user_id, if_match=if_match) def users_user_setting_show_shift_preference(client, user_id, select=None, expand=None): return client.get_shift_preferences(user_id=user_id, select=select, expand=expand) def users_user_setting_update_shift_preference(client, user_id, id_=None, created_date_time=None, last_modified_date_time=None, application=None, device=None, user=None, availability=None): body = {} if id_ is not None: body['id'] = id_ if created_date_time is not None: body['created_date_time'] = created_date_time if last_modified_date_time is not None: body['last_modified_date_time'] = last_modified_date_time body['last_modified_by'] = {} if application is not None: body['last_modified_by']['application'] = application if device is not None: body['last_modified_by']['device'] = device if user is not None: body['last_modified_by']['user'] = user if len(body['last_modified_by']) == 0: del body['last_modified_by'] if availability is not None: body['availability'] = availability return client.update_shift_preferences(user_id=user_id, body=body)

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4febd304d82e50721c70b4bc213392eed9cad639

78,867

py

Python

savecode/threeyears/idownserver/config_outputstandard.py

Octoberr/swm0920

8f05a6b91fc205960edd57f9076facec04f49a1a

[ "Apache-2.0" ]

2

2019-05-19T11:54:26.000Z

2019-05-19T12:03:49.000Z

savecode/threeyears/idownserver/config_outputstandard.py

Octoberr/swm0920

8f05a6b91fc205960edd57f9076facec04f49a1a

[ "Apache-2.0" ]

1

2020-11-27T07:55:15.000Z

savecode/threeyears/idownserver/config_outputstandard.py

Octoberr/swm0920

8f05a6b91fc205960edd57f9076facec04f49a1a

[ "Apache-2.0" ]

2

2021-09-06T18:06:12.000Z

2021-12-31T07:44:43.000Z

"""配置输出标准""" # -*- coding:utf-8 -*- import os from datacontract import EStandardDataType from outputmanagement import ( ECrypto, EDataName, OutputDataConfig, OutputFieldConfig, OutputPlatformConfig, OutputStandardConfig, ) stdconfig = OutputStandardConfig( platforms=[ OutputPlatformConfig( "zplus", enabled=True, datas=[ OutputDataConfig( datatype=EStandardDataType.Task, suffix="idown_task", dataname=EDataName.Guid, fields=[ OutputFieldConfig( # 控制端输出子任务到采集端时，不输出此字段 destfield="progress", srcfield="progress", isfiltered=True, ), OutputFieldConfig( destfield="platform", srcfield="platform", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="parenttaskid", srcfield="parenttaskid", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="batchid", srcfield="batchid", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="tokenid", srcfield="tokenid", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="parentbatchid", srcfield="parentbatchid", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="tasktype", srcfield="tasktype", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="tokentype", srcfield="tokentype", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="apptype", srcfield="apptype", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="forcedownload", srcfield="forcedownload", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="casenode", srcfield="casenode", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="input", srcfield="input", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="preglobaltelcode", srcfield="preglobaltelcode", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="preaccount", srcfield="preaccount", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="globaltelcode", srcfield="globaltelcode", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="phone", srcfield="phone", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="account", srcfield="account", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="password", srcfield="password", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="url", srcfield="url", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="host", srcfield="host", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cookie", srcfield="cookie", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="source", srcfield="source", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmdid", srcfield="cmdid", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmd", srcfield="cmd", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.TaskBack, suffix="idown_task_back", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="state", srcfield="state", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="batchcompletecount", srcfield="batchcompletecount", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="recvmsg", srcfield="recvmsg", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="progress", srcfield="progress", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="time", srcfield="time", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="result", srcfield="result", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="sequence", srcfield="sequence", isrequired=True, crypto=ECrypto.Null, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.TaskBatchBack, suffix="idown_btask_back", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="batchid", srcfield="batchid", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="state", srcfield="state", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="recvmsg", srcfield="recvmsg", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="time", srcfield="time", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="result", srcfield="result", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="progress", srcfield="progress", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="sequence", srcfield="sequence", isrequired=True, crypto=ECrypto.Null, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.IDownCmd, suffix="idown_cmd", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="platform", srcfield="platform", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmdid", srcfield="cmdid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmd", srcfield="cmd", isrequired=True, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="source", srcfield="source", isrequired=False, crypto=ECrypto.Null, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.TaskCmdBack, suffix="idown_cmd_back", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="cmdid", srcfield="cmdid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="clientid", srcfield="clientid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="source", srcfield="source", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="state", srcfield="state", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="recvmsg", srcfield="recvmsg", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="time", srcfield="time", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="sequence", srcfield="sequence", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="platform", srcfield="platform", isrequired=False, crypto=ECrypto.Null, dftval=None, isfiltered=True, ), ], ), OutputDataConfig( datatype=EStandardDataType.IScanTask, suffix="iscan_task", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="periodnum", srcfield="periodnum", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="createtime", srcfield="createtime", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="source", srcfield="source", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="scantype", srcfield="scantype", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmdid", srcfield="cmdid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmd", srcfield="cmd", isrequired=True, crypto=ECrypto.Base64, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.IscanTaskBack, suffix="iscan_task_back", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="periodnum", srcfield="periodnum", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="state", srcfield="state", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="recvmsg", srcfield="recvmsg", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="time", srcfield="time", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="sequence", srcfield="sequence", isrequired=True, crypto=ECrypto.Null, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.IScoutTask, suffix="iscout_task", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="periodnum", srcfield="periodnum", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="platform", srcfield="platform", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="createtime", srcfield="createtime", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="batchid", srcfield="batchid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="source", srcfield="source", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="objecttype", srcfield="objecttype", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="object", srcfield="object", isrequired=True, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="cmdid", srcfield="cmdid", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmd", srcfield="cmd", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.IscoutTaskBack, suffix="iscout_task_back", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="periodnum", srcfield="periodnum", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="state", srcfield="state", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="progress", srcfield="progress", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="elapsed", srcfield="elapsed", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="recvmsg", srcfield="recvmsg", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="time", srcfield="time", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="sequence", srcfield="sequence", isrequired=True, crypto=ECrypto.Null, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.IscoutBtaskBack, suffix="iscout_btask_back", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="periodnum", srcfield="periodnum", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="batchid", srcfield="batchid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="state", srcfield="state", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="progress", srcfield="progress", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="elapsed", srcfield="elapsed", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="recvmsg", srcfield="recvmsg", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="time", srcfield="time", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="sequence", srcfield="sequence", isrequired=True, crypto=ECrypto.Null, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.Autotask, suffix="automated_task", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="platform", srcfield="platform", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="source", srcfield="source", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="batchid", srcfield="batchid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="autotasktype", srcfield="autotasktype", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="createtime", srcfield="createtime", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmdid", srcfield="cmdid", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmd", srcfield="cmd", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), ], ), OutputDataConfig( enable=False, # 暂不输出此回馈数据，不回传中心 datatype=EStandardDataType.Autotaskback, suffix="automated_task_back", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="periodnum", srcfield="periodnum", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="state", srcfield="state", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="recvmsg", srcfield="recvmsg", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="progress", srcfield="progress", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="endtime", srcfield="endtime", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="source", srcfield="source", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="sequence", srcfield="sequence", isrequired=True, crypto=ECrypto.Null, dftval=None, ), ], ), OutputDataConfig( enable=False, # 暂不输出此回馈数据，不回传中心 datatype=EStandardDataType.AutoBatchTaskBack, suffix="automated_btask_back", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="batchid", srcfield="batchid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="periodnum", srcfield="periodnum", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="state", srcfield="state", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="recvmsg", srcfield="recvmsg", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="progress", srcfield="progress", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="endtime", srcfield="endtime", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="source", srcfield="source", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="sequence", srcfield="sequence", isrequired=True, crypto=ECrypto.Null, dftval=None, ), ], ), ], ), OutputPlatformConfig( "zplan", enabled=True, datas=[ OutputDataConfig( datatype=EStandardDataType.Task, suffix="idown_task", dataname=EDataName.Guid, fields=[ OutputFieldConfig( # 控制端输出子任务到采集端时，不输出此字段 destfield="progress", srcfield="progress", isfiltered=True, ), OutputFieldConfig( destfield="platform", srcfield="platform", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="parenttaskid", srcfield="parenttaskid", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="batchid", srcfield="batchid", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="tokenid", srcfield="tokenid", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="parentbatchid", srcfield="parentbatchid", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="tasktype", srcfield="tasktype", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="tokentype", srcfield="tokentype", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="apptype", srcfield="apptype", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="forcedownload", srcfield="forcedownload", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="casenode", srcfield="casenode", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="input", srcfield="input", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="preglobaltelcode", srcfield="preglobaltelcode", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="preaccount", srcfield="preaccount", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="globaltelcode", srcfield="globaltelcode", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="phone", srcfield="phone", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="account", srcfield="account", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="password", srcfield="password", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="url", srcfield="url", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="host", srcfield="host", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cookie", srcfield="cookie", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="source", srcfield="source", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmdid", srcfield="cmdid", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmd", srcfield="cmd", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.TaskBack, suffix="idown_task_back", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="state", srcfield="state", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="batchcompletecount", srcfield="batchcompletecount", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="recvmsg", srcfield="recvmsg", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="progress", srcfield="progress", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="time", srcfield="time", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="result", srcfield="result", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="sequence", srcfield="sequence", isrequired=True, crypto=ECrypto.Null, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.TaskBatchBack, suffix="idown_btask_back", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="batchid", srcfield="batchid", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="state", srcfield="state", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="recvmsg", srcfield="recvmsg", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="time", srcfield="time", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="result", srcfield="result", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="progress", srcfield="progress", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="sequence", srcfield="sequence", isrequired=True, crypto=ECrypto.Null, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.IDownCmd, suffix="idown_cmd", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="platform", srcfield="platform", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmdid", srcfield="cmdid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmd", srcfield="cmd", isrequired=True, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="source", srcfield="source", isrequired=False, crypto=ECrypto.Null, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.TaskCmdBack, suffix="idown_cmd_back", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="cmdid", srcfield="cmdid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="clientid", srcfield="clientid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="source", srcfield="source", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="state", srcfield="state", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="recvmsg", srcfield="recvmsg", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="time", srcfield="time", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="sequence", srcfield="sequence", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="platform", srcfield="platform", isrequired=False, crypto=ECrypto.Null, dftval=None, isfiltered=True, ), ], ), OutputDataConfig( datatype=EStandardDataType.IScanTask, suffix="iscan_task", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="periodnum", srcfield="periodnum", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="createtime", srcfield="createtime", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="source", srcfield="source", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="scantype", srcfield="scantype", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmdid", srcfield="cmdid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmd", srcfield="cmd", isrequired=True, crypto=ECrypto.Base64, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.IscanTaskBack, suffix="iscan_task_back", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="periodnum", srcfield="periodnum", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="state", srcfield="state", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="recvmsg", srcfield="recvmsg", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="time", srcfield="time", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="sequence", srcfield="sequence", isrequired=True, crypto=ECrypto.Null, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.IScoutTask, suffix="iscout_task", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="periodnum", srcfield="periodnum", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="platform", srcfield="platform", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="createtime", srcfield="createtime", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="batchid", srcfield="batchid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="source", srcfield="source", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="objecttype", srcfield="objecttype", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="object", srcfield="object", isrequired=True, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="cmdid", srcfield="cmdid", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmd", srcfield="cmd", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.IscoutTaskBack, suffix="iscout_task_back", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="periodnum", srcfield="periodnum", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="state", srcfield="state", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="progress", srcfield="progress", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="elapsed", srcfield="elapsed", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="recvmsg", srcfield="recvmsg", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="time", srcfield="time", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="sequence", srcfield="sequence", isrequired=True, crypto=ECrypto.Null, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.IscoutBtaskBack, suffix="iscout_btask_back", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="periodnum", srcfield="periodnum", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="batchid", srcfield="batchid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="state", srcfield="state", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="progress", srcfield="progress", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="elapsed", srcfield="elapsed", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="recvmsg", srcfield="recvmsg", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="time", srcfield="time", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="sequence", srcfield="sequence", isrequired=True, crypto=ECrypto.Null, dftval=None, ), ], ), OutputDataConfig( datatype=EStandardDataType.Autotask, suffix="automated_task", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="platform", srcfield="platform", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="source", srcfield="source", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="batchid", srcfield="batchid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="autotasktype", srcfield="autotasktype", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="createtime", srcfield="createtime", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmdid", srcfield="cmdid", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="cmd", srcfield="cmd", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), ], ), OutputDataConfig( enable=False, # 暂不输出此回馈数据，不回传中心 datatype=EStandardDataType.Autotaskback, suffix="automated_task_back", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="periodnum", srcfield="periodnum", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="state", srcfield="state", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="recvmsg", srcfield="recvmsg", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="progress", srcfield="progress", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="endtime", srcfield="endtime", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="source", srcfield="source", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="sequence", srcfield="sequence", isrequired=True, crypto=ECrypto.Null, dftval=None, ), ], ), OutputDataConfig( enable=False, # 暂不输出此回馈数据，不回传中心 datatype=EStandardDataType.AutoBatchTaskBack, suffix="automated_btask_back", dataname=EDataName.Guid, fields=[ OutputFieldConfig( destfield="taskid", srcfield="taskid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="batchid", srcfield="batchid", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="periodnum", srcfield="periodnum", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="state", srcfield="state", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="recvmsg", srcfield="recvmsg", isrequired=False, crypto=ECrypto.Base64, dftval=None, ), OutputFieldConfig( destfield="progress", srcfield="progress", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="endtime", srcfield="endtime", isrequired=True, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="source", srcfield="source", isrequired=False, crypto=ECrypto.Null, dftval=None, ), OutputFieldConfig( destfield="sequence", srcfield="sequence", isrequired=True, crypto=ECrypto.Null, dftval=None, ), ], ), ], ), ] )

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8b08f69e6f0e5eb0e8ce4166041963dbce880767

395

py

Python

rcnn/lib/python3.6/site-packages/tensorflow/debugging/__init__.py

dreamingweaver/making_passportImage

68f23411780ff82abe934dfae5fc04acb80f2c49

[ "MIT" ]

1

2019-01-12T13:17:32.000Z

rcnn/lib/python3.6/site-packages/tensorflow/debugging/__init__.py

dreamingweaver/making_passportImage

68f23411780ff82abe934dfae5fc04acb80f2c49

[ "MIT" ]

null

rcnn/lib/python3.6/site-packages/tensorflow/debugging/__init__.py

dreamingweaver/making_passportImage

68f23411780ff82abe934dfae5fc04acb80f2c49

[ "MIT" ]

null

# This file is MACHINE GENERATED! Do not edit. # Generated by: tensorflow/python/tools/api/generator/create_python_api.py script. """Public API for tf.debugging namespace. """ from __future__ import print_function from tensorflow.python import check_numerics from tensorflow.python import is_finite from tensorflow.python import is_inf from tensorflow.python import is_nan del print_function

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py

Python

tests/test_routes.py

trailrunnervolunteers/trv-website

cba66812d18caf3fa584219c6249302ea41b7cbc

[ "MIT" ]

null

tests/test_routes.py

trailrunnervolunteers/trv-website

cba66812d18caf3fa584219c6249302ea41b7cbc

[ "MIT" ]

10

2022-03-07T15:36:05.000Z

2022-03-22T19:34:40.000Z

tests/test_routes.py

trailrunnervolunteers/trv-website

cba66812d18caf3fa584219c6249302ea41b7cbc

[ "MIT" ]

2

2022-03-06T01:11:33.000Z

2022-03-06T01:14:54.000Z

import pytest @pytest.mark.parametrize("method", ("get", "put")) def test_create_volunteer_wrong_method(client, method): """/volunteer only supports POST for creation""" call = getattr(client, method) response = call("/api/volunteer") # Should return HTTP 405 "Method Not Allowed" assert response.status_code == 405 def test_create_volunteer(client): """/volunteer only supports POST for creation""" response = client.post("/api/volunteer") assert response.status_code == 200 json = response.get_json() assert json["volunteer_id"] == 0 def test_update_volunteer_wrong_method(client): """Update happens via PUT but try POST""" response = client.post("/api/volunteer/1") assert response.status_code == 405 def test_update_volunteer(client): """Update a volunteer""" id = 123 response = client.put(f"/api/volunteer/{id}") assert response.status_code == 200 json = response.get_json() assert json["volunteer_id"] == id @pytest.mark.parametrize("method", ("get", "put")) def test_get_volunteers_wrong_method(client, method): """/volunteers only supports POST, try it with others""" call = getattr(client, method) response = call("/api/volunteers") # Should return HTTP 405 "Method Not Allowed" assert response.status_code == 405 def test_list_volunteers(client): response = client.post("/api/volunteers") assert response.status_code == 200 # There's no content yet except an empty list assert "volunteers" in response.get_json() def test_get_volunteer(client): """Get one volunteer""" id = 123 response = client.get(f"/api/volunteer/{id}") # TODO: test that a volunteer which doesn't exists returns 404 assert response.status_code == 200 json = response.get_json() assert json["volunteer_id"] == id @pytest.mark.parametrize("method", ("get", "put")) def test_create_event_wrong_method(client, method): """/event only supports POST for creation""" call = getattr(client, method) response = call("/api/event") # Should return HTTP 405 "Method Not Allowed" assert response.status_code == 405 def test_create_event(client): """/event only supports POST for creation""" response = client.post("/api/event") assert response.status_code == 200 json = response.get_json() assert json["event_id"] == 0 def test_update_event_wrong_method(client): """Update happens via PUT but try POST""" response = client.post("/api/event/1") assert response.status_code == 405 def test_update_event(client): """Update an event""" id = 123 response = client.put(f"/api/event/{id}") assert response.status_code == 200 json = response.get_json() assert json["event_id"] == id @pytest.mark.parametrize("method", ("get", "put")) def test_get_event_wrong_method(client, method): """/events only supports POST, try it with others""" call = getattr(client, method) response = call("/api/event") # Should return HTTP 405 "Method Not Allowed" assert response.status_code == 405 def test_list_event(client): response = client.post("/api/events") assert response.status_code == 200 # There's no content yet except an empty list assert "events" in response.get_json() def test_get_event(client): """Get one event""" id = 123 response = client.get(f"/api/event/{id}") # TODO: test that an event which doesn't exists returns 404 assert response.status_code == 200 json = response.get_json() assert json["event_id"] == id def test_list_event_participants_post(client): """Listing participants only supports GET, no need to filter by POST""" response = client.post(f"/api/event/789/participants") assert response.status_code == 405 def test_list_event_participants(client): event_id = 456 response = client.get(f"/api/event/{event_id}/participants") assert response.status_code == 200 # There's no content yet except an empty list assert "participants" in response.get_json() def test_update_event_participant_post(client): """Updating participants happens via PUT""" response = client.post(f"/api/event/789/participant/234") assert response.status_code == 405 def test_update_event_participant(client): response = client.put(f"/api/event/789/participant/234") assert response.status_code == 200 json = response.get_json() assert json["attended"] == True def test_list_event_pictures_post(client): """Listing participants only supports GET, no need to filter by POST""" response = client.post("/api/event/789/pictures") assert response.status_code == 405 def test_list_event_pictures(client): response = client.get("/api/event/345/pictures") assert response.status_code == 200 # There's no content yet except an empty list assert "pictures" in response.get_json() @pytest.mark.parametrize("method", ("get", "put")) def test_create_group_wrong_method(client, method): """/group only supports POST for creation""" call = getattr(client, method) response = call("/api/group") # Should return HTTP 405 "Method Not Allowed" assert response.status_code == 405 def test_create_group(client): """/group only supports POST for creation""" response = client.post("/api/group") assert response.status_code == 200 json = response.get_json() assert json["group_id"] == 0 def test_update_group_wrong_method(client): """Update happens via PUT but try POST""" response = client.post("/api/group/1") assert response.status_code == 405 def test_update_group(client): """Update a group""" id = 123 response = client.put(f"/api/group/{id}") assert response.status_code == 200 json = response.get_json() assert json["group_id"] == id def test_list_groups(client): response = client.get("/api/groups") assert response.status_code == 200 json = response.get_json() assert {"group_id": 0, "name": "TRV"} in json["groups"] def test_get_group(client): """Get one volunteer""" id = 123 response = client.get(f"/api/group/{id}") # TODO: test that a volunteer which doesn't exists returns 404 assert response.status_code == 200 json = response.get_json() assert json["group_id"] == id assert json["name"] == "TRV" def test_create_picture(client): """/picture only supports POST for creation""" response = client.post("/api/event/123/picture") assert response.status_code == 200 json = response.get_json() assert json["picture_id"] == 0 def test_update_picture_wrong_method(client): """Update happens via PUT but try POST""" response = client.post("/api/event/456/picture/1") assert response.status_code == 405 def test_update_picture(client): """Update a group""" id = 123 response = client.put(f"/api/event/345/picture/{id}") assert response.status_code == 200 json = response.get_json() assert json["picture_id"] == id

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gyp

Python

syzygy/test_data/test_data.gyp

nzeh/syzygy

3573e3d458dbb4285753c28a7cb42ced739f9f55

[ "Apache-2.0" ]

343

2015-01-07T05:58:44.000Z

2022-03-15T14:55:21.000Z

syzygy/test_data/test_data.gyp

nzeh/syzygy-nzeh

3757e53f850644721284073de318e218224dd411

[ "Apache-2.0" ]

61

2015-03-19T18:20:21.000Z

2019-10-23T12:58:23.000Z

syzygy/test_data/test_data.gyp

nzeh/syzygy-nzeh

3757e53f850644721284073de318e218224dd411

[ "Apache-2.0" ]

66

2015-01-20T15:35:05.000Z

2021-11-25T16:49:41.000Z

# Copyright 2012 Google Inc. 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. # 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. { 'variables': { 'chromium_code': 1, }, 'targets': [ { 'target_name': 'copy_test_dll', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ ], 'dependencies': [ '<(src)/syzygy/pe/pe.gyp:test_dll', ], 'copies': [ { 'destination': '<(PRODUCT_DIR)/test_data', 'files': [ '<(PRODUCT_DIR)/test_dll.dll', '<(PRODUCT_DIR)/test_dll.dll.pdb', ], }, ], }, { 'target_name': 'copy_test_dll_compilands', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ ], 'dependencies': [ '<(src)/syzygy/pe/pe.gyp:test_dll', ], 'copies': [ { 'destination': '<(PRODUCT_DIR)/test_data', 'files': [ # We rely on pe.gyp:test_dll producing these # intermediate/auxiliary output files. '<(PRODUCT_DIR)/obj/syzygy/pe/test_dll.gen/' 'test_dll_label_test_func.obj', '<(PRODUCT_DIR)/export_dll.dll.lib', '<(PRODUCT_DIR)/obj/syzygy/pe/test_dll_no_private_symbols.lib', ], }, ], }, { 'target_name': 'call_trace_instrumented_test_dll', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ ], 'dependencies': [ '<(src)/syzygy/instrument/instrument.gyp:instrument', 'copy_test_dll', ], 'actions': [ { 'action_name': 'call_trace_instrument_test_data_test_dll', 'inputs': [ '<(PRODUCT_DIR)/instrument.exe', '<(PRODUCT_DIR)/test_data/test_dll.dll', '<(PRODUCT_DIR)/test_data/test_dll.dll.pdb', ], 'outputs': [ '<(PRODUCT_DIR)/test_data/call_trace_instrumented_test_dll.dll', '<(PRODUCT_DIR)/test_data/call_trace_instrumented_test_dll.dll.pdb', ], 'action': [ '<(PRODUCT_DIR)/instrument.exe', '--mode=calltrace', '--input-image=<(PRODUCT_DIR)/test_data/test_dll.dll', '--input-pdb=<(PRODUCT_DIR)/test_data/test_dll.dll.pdb', '--output-image=' '<(PRODUCT_DIR)/test_data/call_trace_instrumented_test_dll.dll', '--output-pdb=<(PRODUCT_DIR)/test_data/' 'call_trace_instrumented_test_dll.dll.pdb', '--overwrite', ], }, ], }, { 'target_name': 'profile_instrumented_test_dll', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ ], 'dependencies': [ '<(src)/syzygy/instrument/instrument.gyp:instrument', 'copy_test_dll', ], 'actions': [ { 'action_name': 'profile_instrument_test_data_test_dll', 'inputs': [ '<(PRODUCT_DIR)/instrument.exe', '<(PRODUCT_DIR)/test_data/test_dll.dll', '<(PRODUCT_DIR)/test_data/test_dll.dll.pdb', ], 'outputs': [ '<(PRODUCT_DIR)/test_data/profile_instrumented_test_dll.dll', '<(PRODUCT_DIR)/test_data/profile_instrumented_test_dll.dll.pdb', ], 'action': [ '<(PRODUCT_DIR)/instrument.exe', '--mode=profile', '--input-image=<(PRODUCT_DIR)/test_data/test_dll.dll', '--input-pdb=<(PRODUCT_DIR)/test_data/test_dll.dll.pdb', '--output-image=<(PRODUCT_DIR)/test_data/' 'profile_instrumented_test_dll.dll', '--output-pdb=<(PRODUCT_DIR)/test_data/' 'profile_instrumented_test_dll.dll.pdb', '--overwrite', ], }, ], }, { 'target_name': 'basic_block_entry_instrumented_test_dll', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ ], 'dependencies': [ '<(src)/syzygy/instrument/instrument.gyp:instrument', 'copy_test_dll', ], 'actions': [ { 'action_name': 'basic_block_entry_instrument_test_data_test_dll', 'inputs': [ '<(PRODUCT_DIR)/instrument.exe', '<(PRODUCT_DIR)/test_data/test_dll.dll', '<(PRODUCT_DIR)/test_data/test_dll.dll.pdb', ], 'outputs': [ '<(PRODUCT_DIR)/test_data/' 'basic_block_entry_instrumented_test_dll.dll', '<(PRODUCT_DIR)/test_data/' 'basic_block_entry_instrumented_test_dll.dll.pdb', ], 'action': [ '<(PRODUCT_DIR)/instrument.exe', '--mode=bbentry', '--input-image=<(PRODUCT_DIR)/test_data/test_dll.dll', '--input-pdb=<(PRODUCT_DIR)/test_data/test_dll.dll.pdb', '--output-image=<(PRODUCT_DIR)/test_data/' 'basic_block_entry_instrumented_test_dll.dll', '--output-pdb=<(PRODUCT_DIR)/test_data/' 'basic_block_entry_instrumented_test_dll.dll.pdb', '--overwrite', ], }, ], }, { 'target_name': 'branch_instrumented_test_dll', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ ], 'dependencies': [ '<(src)/syzygy/instrument/instrument.gyp:instrument', 'copy_test_dll', ], 'actions': [ { 'action_name': 'branch_instrument_test_data_test_dll', 'inputs': [ '<(PRODUCT_DIR)/instrument.exe', '<(PRODUCT_DIR)/test_data/test_dll.dll', '<(PRODUCT_DIR)/test_data/test_dll.dll.pdb', ], 'outputs': [ '<(PRODUCT_DIR)/test_data/branch_instrumented_test_dll.dll', '<(PRODUCT_DIR)/test_data/branch_instrumented_test_dll.dll.pdb', ], 'action': [ '<(PRODUCT_DIR)/instrument.exe', '--mode=branch', '--input-image=<(PRODUCT_DIR)/test_data/test_dll.dll', '--input-pdb=<(PRODUCT_DIR)/test_data/test_dll.dll.pdb', '--output-image=<(PRODUCT_DIR)/test_data/' 'branch_instrumented_test_dll.dll', '--output-pdb=<(PRODUCT_DIR)/test_data/' 'branch_instrumented_test_dll.dll.pdb', '--overwrite', ], }, ], }, { 'target_name': 'coverage_instrumented_test_dll', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ ], 'dependencies': [ '<(src)/syzygy/instrument/instrument.gyp:instrument', 'copy_test_dll', ], 'actions': [ { 'action_name': 'coverage_instrument_test_data_test_dll', 'inputs': [ '<(PRODUCT_DIR)/instrument.exe', '<(PRODUCT_DIR)/test_data/test_dll.dll', '<(PRODUCT_DIR)/test_data/test_dll.dll.pdb', ], 'outputs': [ '<(PRODUCT_DIR)/test_data/coverage_instrumented_test_dll.dll', '<(PRODUCT_DIR)/test_data/coverage_instrumented_test_dll.dll.pdb', ], 'action': [ '<(PRODUCT_DIR)/instrument.exe', '--mode=coverage', '--input-image=<(PRODUCT_DIR)/test_data/test_dll.dll', '--input-pdb=<(PRODUCT_DIR)/test_data/test_dll.dll.pdb', '--output-image=<(PRODUCT_DIR)/test_data/' 'coverage_instrumented_test_dll.dll', '--output-pdb=<(PRODUCT_DIR)/test_data/' 'coverage_instrumented_test_dll.dll.pdb', '--overwrite', ], }, ], }, { 'target_name': 'asan_instrumented_test_dll', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ ], 'dependencies': [ '<(src)/syzygy/instrument/instrument.gyp:instrument', 'copy_test_dll', ], 'actions': [ { 'action_name': 'asan_instrument_test_data_test_dll', 'inputs': [ '<(PRODUCT_DIR)/instrument.exe', '<(PRODUCT_DIR)/test_data/test_dll.dll', '<(PRODUCT_DIR)/test_data/test_dll.dll.pdb', ], 'outputs': [ '<(PRODUCT_DIR)/test_data/asan_instrumented_test_dll.dll', '<(PRODUCT_DIR)/test_data/asan_instrumented_test_dll.dll.pdb', ], 'action': [ '<(PRODUCT_DIR)/instrument.exe', '--mode=asan', '--input-image=<(PRODUCT_DIR)/test_data/test_dll.dll', '--input-pdb=<(PRODUCT_DIR)/test_data/test_dll.dll.pdb', '--output-image=<(PRODUCT_DIR)/test_data/' 'asan_instrumented_test_dll.dll', '--output-pdb=<(PRODUCT_DIR)/test_data/' 'asan_instrumented_test_dll.dll.pdb', '--overwrite', ], }, ], }, { 'target_name': 'randomized_test_dll', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ ], 'dependencies': [ '<(src)/syzygy/relink/relink.gyp:relink', 'copy_test_dll' ], 'actions': [ { 'action_name': 'randomize_test_data_test_dll', 'inputs': [ '<(PRODUCT_DIR)/relink.exe', '<(PRODUCT_DIR)/test_data/test_dll.dll', '<(PRODUCT_DIR)/test_data/test_dll.dll.pdb', ], 'outputs': [ '<(PRODUCT_DIR)/test_data/randomized_test_dll.dll', '<(PRODUCT_DIR)/test_data/randomized_test_dll.dll.pdb', ], 'action': [ '<(PRODUCT_DIR)/relink.exe', '--seed=0', '--input-image=<(PRODUCT_DIR)/test_data/test_dll.dll', '--input-pdb=<(PRODUCT_DIR)/test_data/test_dll.dll.pdb', '--output-image=<(PRODUCT_DIR)/test_data/randomized_test_dll.dll', '--output-pdb=<(PRODUCT_DIR)/test_data/randomized_test_dll.dll.pdb', '--overwrite', ], }, ], }, { 'target_name': 'signed_test_dll', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ ], 'dependencies': [ 'copy_test_dll', ], 'actions': [ { 'action_name': 'sign_test_dll', 'inputs': [ '<(src)/syzygy/test_data/syzygy.pfx', '<(src)/syzygy/test_data/sign_image.bat', '<(PRODUCT_DIR)/test_data/test_dll.dll', ], 'outputs': [ '<(PRODUCT_DIR)/test_data/signed_test_dll.dll', ], 'action': [ '<(src)/syzygy/test_data/sign_image.bat', # This tool requires Windows-style paths, hence the use of # backslashes. '<(PRODUCT_DIR)\\test_data\\test_dll.dll', '<(PRODUCT_DIR)\\test_data\\signed_test_dll.dll', ], }, ], }, { 'target_name': 'memprof_instrumented_memprof_harness', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ ], 'dependencies': [ '<(src)/syzygy/instrument/instrument.gyp:instrument', '<(src)/syzygy/agent/memprof/memprof.gyp:memprof_harness', ], 'actions': [ { 'action_name': 'memprof_instrument_memprof_harness', 'inputs': [ '<(PRODUCT_DIR)/instrument.exe', '<(PRODUCT_DIR)/memprof_harness.exe', '<(PRODUCT_DIR)/memprof_harness.exe.pdb', ], 'outputs': [ '<(PRODUCT_DIR)/test_data/' 'memprof_instrumented_memprof_harness.exe', '<(PRODUCT_DIR)/test_data/' 'memprof_instrumented_memprof_harness.exe.pdb', ], 'action': [ '<(PRODUCT_DIR)/instrument.exe', '--mode=asan', '--agent=memprof.dll', '--input-image=<(PRODUCT_DIR)/memprof_harness.exe', '--input-pdb=<(PRODUCT_DIR)/memprof_harness.exe.pdb', '--output-image=<(PRODUCT_DIR)/test_data/' 'memprof_instrumented_memprof_harness.exe', '--output-pdb=<(PRODUCT_DIR)/test_data/' 'memprof_instrumented_memprof_harness.exe.pdb', '--overwrite', ], }, ], }, # TODO(rogerm): The GYP snippets to generate the trace files are all # pretty much identical to one other if parameterized by the mode, # dll/pdb name, and output directory. Find a way to consolidate to # a reusable rule or gypi. { 'target_name': 'call_trace_traces', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ 'generate_traces.py', ], 'dependencies': [ '<(src)/syzygy/agent/call_trace/call_trace.gyp:call_trace_client', '<(src)/syzygy/trace/service/service.gyp:call_trace_service_exe', 'call_trace_instrumented_test_dll', ], 'actions': [ { 'action_name': 'generate_call_trace_traces', 'inputs': [ '<(PRODUCT_DIR)/call_trace_client.dll', '<(PRODUCT_DIR)/call_trace_service.exe', '<(PRODUCT_DIR)/test_data/call_trace_instrumented_test_dll.dll', '<(PRODUCT_DIR)/test_data/call_trace_instrumented_test_dll.dll.pdb', '<(src)/syzygy/test_data/generate_traces.py', ], 'outputs': [ '<(PRODUCT_DIR)/test_data/call_trace_traces/trace-1.bin', '<(PRODUCT_DIR)/test_data/call_trace_traces/trace-2.bin', '<(PRODUCT_DIR)/test_data/call_trace_traces/trace-3.bin', '<(PRODUCT_DIR)/test_data/call_trace_traces/trace-4.bin', ], 'action': [ '<(python_exe)', '<(src)/syzygy/test_data/generate_traces.py', '--output-dir=<(PRODUCT_DIR)/test_data/call_trace_traces', '--instrumented-image=' '<(PRODUCT_DIR)/test_data/call_trace_instrumented_test_dll.dll', '--verbose', # The build-dir arg must be last to work around a bug in the # interaction between GYP and VS2010. # See: http://code.google.com/p/gyp/issues/detail?id=272 '--build-dir=<(PRODUCT_DIR)', ], }, ], }, { 'target_name': 'profile_traces', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ 'generate_traces.py', ], 'dependencies': [ '<(src)/syzygy/agent/profiler/profiler.gyp:profile_client', '<(src)/syzygy/trace/service/service.gyp:call_trace_service_exe', 'profile_instrumented_test_dll', ], 'actions': [ { 'action_name': 'generate_profile_traces', 'inputs': [ '<(PRODUCT_DIR)/profile_client.dll', '<(PRODUCT_DIR)/call_trace_service.exe', '<(PRODUCT_DIR)/test_data/profile_instrumented_test_dll.dll', '<(PRODUCT_DIR)/test_data/profile_instrumented_test_dll.dll.pdb', '<(src)/syzygy/test_data/generate_traces.py', ], 'outputs': [ '<(PRODUCT_DIR)/test_data/profile_traces/trace-1.bin', '<(PRODUCT_DIR)/test_data/profile_traces/trace-2.bin', '<(PRODUCT_DIR)/test_data/profile_traces/trace-3.bin', '<(PRODUCT_DIR)/test_data/profile_traces/trace-4.bin', ], 'action': [ '<(python_exe)', '<(src)/syzygy/test_data/generate_traces.py', '--output-dir=<(PRODUCT_DIR)/test_data/profile_traces', '--instrumented-image=' '<(PRODUCT_DIR)/test_data/profile_instrumented_test_dll.dll', '--verbose', # The build-dir arg must be last to work around a bug in the # interaction between GYP and VS2010. # See: http://code.google.com/p/gyp/issues/detail?id=272 '--build-dir=<(PRODUCT_DIR)', ], }, ], }, { 'target_name': 'test_dll_order_json', 'type': 'none', 'msvs_cygwin_shell': 0, 'dependencies': [ 'call_trace_traces', 'call_trace_instrumented_test_dll', '<(src)/syzygy/reorder/reorder.gyp:reorder', ], 'actions': [ { 'action_name': 'generate_test_dll_order_file', 'inputs': [ '<(PRODUCT_DIR)/reorder.exe', '<(PRODUCT_DIR)/test_data/call_trace_instrumented_test_dll.dll', '<(PRODUCT_DIR)/test_data/call_trace_instrumented_test_dll.dll.pdb', '<(PRODUCT_DIR)/test_data/call_trace_traces/trace-1.bin', '<(PRODUCT_DIR)/test_data/call_trace_traces/trace-2.bin', '<(PRODUCT_DIR)/test_data/call_trace_traces/trace-3.bin', '<(PRODUCT_DIR)/test_data/call_trace_traces/trace-4.bin', ], 'outputs': [ '<(PRODUCT_DIR)/test_data/test_dll_order.json', ], 'action': [ '<(PRODUCT_DIR)/reorder.exe', '--instrumented-image=' '<(PRODUCT_DIR)/test_data/call_trace_instrumented_test_dll.dll', '--output-file=<(PRODUCT_DIR)/test_data/test_dll_order.json', '<(PRODUCT_DIR)/test_data/call_trace_traces/trace-1.bin', '<(PRODUCT_DIR)/test_data/call_trace_traces/trace-2.bin', '<(PRODUCT_DIR)/test_data/call_trace_traces/trace-3.bin', '<(PRODUCT_DIR)/test_data/call_trace_traces/trace-4.bin', ], } ], }, { 'target_name': 'coverage_traces', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ 'generate_traces.py', ], 'dependencies': [ '<(src)/syzygy/agent/coverage/coverage.gyp:coverage_client', '<(src)/syzygy/trace/service/service.gyp:call_trace_service_exe', 'coverage_instrumented_test_dll', ], 'actions': [ { 'action_name': 'generate_coverage_traces', 'inputs': [ '<(PRODUCT_DIR)/coverage_client.dll', '<(PRODUCT_DIR)/call_trace_service.exe', '<(PRODUCT_DIR)/test_data/coverage_instrumented_test_dll.dll', '<(PRODUCT_DIR)/test_data/coverage_instrumented_test_dll.dll.pdb', '<(src)/syzygy/test_data/generate_traces.py', ], 'outputs': [ '<(PRODUCT_DIR)/test_data/coverage_traces/trace-1.bin', '<(PRODUCT_DIR)/test_data/coverage_traces/trace-2.bin', '<(PRODUCT_DIR)/test_data/coverage_traces/trace-3.bin', '<(PRODUCT_DIR)/test_data/coverage_traces/trace-4.bin', ], 'action': [ '<(python_exe)', '<(src)/syzygy/test_data/generate_traces.py', '--output-dir=<(PRODUCT_DIR)/test_data/coverage_traces', '--instrumented-image=' '<(PRODUCT_DIR)/test_data/coverage_instrumented_test_dll.dll', '--verbose', # The build-dir arg must be last to work around a bug in the # interaction between GYP and VS2010. # See: http://code.google.com/p/gyp/issues/detail?id=272 '--build-dir=<(PRODUCT_DIR)', ], }, ], }, { 'target_name': 'basic_block_entry_traces', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ 'generate_traces.py', ], 'dependencies': [ '<(src)/syzygy/agent/basic_block_entry/basic_block_entry.gyp:' 'basic_block_entry_client', '<(src)/syzygy/trace/service/service.gyp:call_trace_service_exe', 'basic_block_entry_instrumented_test_dll', ], 'actions': [ { 'action_name': 'generate_basic_block_entry_traces', 'inputs': [ '<(PRODUCT_DIR)/basic_block_entry_client.dll', '<(PRODUCT_DIR)/call_trace_service.exe', '<(PRODUCT_DIR)/test_data/' 'basic_block_entry_instrumented_test_dll.dll', '<(PRODUCT_DIR)/test_data/' 'basic_block_entry_instrumented_test_dll.dll.pdb', '<(src)/syzygy/test_data/generate_traces.py', ], 'outputs': [ '<(PRODUCT_DIR)/test_data/basic_block_entry_traces/trace-1.bin', '<(PRODUCT_DIR)/test_data/basic_block_entry_traces/trace-2.bin', '<(PRODUCT_DIR)/test_data/basic_block_entry_traces/trace-3.bin', '<(PRODUCT_DIR)/test_data/basic_block_entry_traces/trace-4.bin', ], 'action': [ '<(python_exe)', '<(src)/syzygy/test_data/generate_traces.py', '--output-dir=<(PRODUCT_DIR)/test_data/basic_block_entry_traces', '--instrumented-image=<(PRODUCT_DIR)/test_data/' 'basic_block_entry_instrumented_test_dll.dll', '--verbose', # The build-dir arg must be last to work around a bug in the # interaction between GYP and VS2010. # See: http://code.google.com/p/gyp/issues/detail?id=272 '--build-dir=<(PRODUCT_DIR)', ], }, ], }, { 'target_name': 'basic_block_entry_counts', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ ], 'dependencies': [ 'basic_block_entry_traces', '<(src)/syzygy/grinder/grinder.gyp:grinder', ], 'actions': [ { 'action_name': 'generate_basic_block_entry_counts', 'inputs': [ '<(PRODUCT_DIR)/grinder.exe', '<(PRODUCT_DIR)/test_data/basic_block_entry_traces/trace-1.bin', '<(PRODUCT_DIR)/test_data/basic_block_entry_traces/trace-2.bin', '<(PRODUCT_DIR)/test_data/basic_block_entry_traces/trace-3.bin', '<(PRODUCT_DIR)/test_data/basic_block_entry_traces/trace-4.bin', ], 'outputs': [ '<(PRODUCT_DIR)/test_data/basic_block_entry_traces/' 'entry_counts.json', ], 'action': [ '<(PRODUCT_DIR)/grinder.exe', '--mode=bbentry', '--output-file=<(PRODUCT_DIR)/test_data/basic_block_entry_traces/' 'entry_counts.json', '<(PRODUCT_DIR)/test_data/basic_block_entry_traces/trace-1.bin', '<(PRODUCT_DIR)/test_data/basic_block_entry_traces/trace-2.bin', '<(PRODUCT_DIR)/test_data/basic_block_entry_traces/trace-3.bin', '<(PRODUCT_DIR)/test_data/basic_block_entry_traces/trace-4.bin', ], }, ], }, { 'target_name': 'branch_traces', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ 'generate_traces.py', ], 'dependencies': [ '<(src)/syzygy/agent/basic_block_entry/basic_block_entry.gyp:' 'basic_block_entry_client', '<(src)/syzygy/trace/service/service.gyp:call_trace_service_exe', 'branch_instrumented_test_dll', ], 'actions': [ { 'action_name': 'generate_branch_traces', 'inputs': [ '<(PRODUCT_DIR)/basic_block_entry_client.dll', '<(PRODUCT_DIR)/call_trace_service.exe', '<(PRODUCT_DIR)/test_data/' 'branch_instrumented_test_dll.dll', '<(PRODUCT_DIR)/test_data/' 'branch_instrumented_test_dll.dll.pdb', '<(src)/syzygy/test_data/generate_traces.py', ], 'outputs': [ '<(PRODUCT_DIR)/test_data/branch_traces/trace-1.bin', '<(PRODUCT_DIR)/test_data/branch_traces/trace-2.bin', '<(PRODUCT_DIR)/test_data/branch_traces/trace-3.bin', '<(PRODUCT_DIR)/test_data/branch_traces/trace-4.bin', ], 'action': [ '<(python_exe)', '<(src)/syzygy/test_data/generate_traces.py', '--output-dir=<(PRODUCT_DIR)/test_data/branch_traces', '--instrumented-image=<(PRODUCT_DIR)/test_data/' 'branch_instrumented_test_dll.dll', '--verbose', # The build-dir arg must be last to work around a bug in the # interaction between GYP and VS2010. # See: http://code.google.com/p/gyp/issues/detail?id=272 '--build-dir=<(PRODUCT_DIR)', ], }, ], }, { 'target_name': 'memprof_traces', 'type': 'none', 'msvs_cygwin_shell': 0, 'sources': [ 'generate_traces.py', ], 'dependencies': [ '<(src)/syzygy/agent/memprof/memprof.gyp:memprof', '<(src)/syzygy/trace/service/service.gyp:call_trace_service_exe', 'memprof_instrumented_memprof_harness', ], 'actions': [ { 'action_name': 'generate_memprof_traces', 'inputs': [ '<(PRODUCT_DIR)/memprof.dll', '<(PRODUCT_DIR)/call_trace_service.exe', '<(PRODUCT_DIR)/test_data/' 'memprof_instrumented_memprof_harness.exe', '<(PRODUCT_DIR)/test_data/' 'memprof_instrumented_memprof_harness.exe.pdb', '<(src)/syzygy/test_data/generate_traces.py', ], 'outputs': [ '<(PRODUCT_DIR)/test_data/memprof_traces/trace-1.bin', ], 'action': [ '<(python_exe)', '<(src)/syzygy/test_data/generate_traces.py', '--env=SYZYGY_MEMPROF_OPTIONS=--stack-trace-tracking ' '--serialize-timestamps', '--instrumented-image=<(PRODUCT_DIR)/test_data/' 'memprof_instrumented_memprof_harness.exe', '--iterations=1', '--output-dir=<(PRODUCT_DIR)/test_data/memprof_traces', '--verbose', # The build-dir arg must be last to work around a bug in the # interaction between GYP and VS2010. # See: http://code.google.com/p/gyp/issues/detail?id=272 '--build-dir=<(PRODUCT_DIR)', ], }, ], }, ], }

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0.001374

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true

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null

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1

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1

null

0

1

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11

0fed1a6bce9a3625a44ad4322d1c590a3e2234bd

140

py

Python

restler/authentication_settings.py

SmartSleepIoT/SmartSleepCoding

21c19489f0c477cbfbabd3a1d232f526f84a9e49

[ "BSD-3-Clause" ]

null

restler/authentication_settings.py

SmartSleepIoT/SmartSleepCoding

21c19489f0c477cbfbabd3a1d232f526f84a9e49

[ "BSD-3-Clause" ]

41

2021-10-20T17:54:59.000Z

2022-02-02T20:43:53.000Z

restler/authentication_settings.py

SmartSleepIoT/SmartSleepCoding

21c19489f0c477cbfbabd3a1d232f526f84a9e49

[ "BSD-3-Clause" ]

null

print("{'user1':{}, 'user2':{}}") print("Authorization: Bearer valid_unit_test_token") print("Authorization: Bearer shadow_unit_test_token")

46.666667

53

0.757143

17

140

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0.015038

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140

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0ffe48ded8a28d4e99f7a8806ac5c3f9ab001d0b

21,365

py

Python

usersec/migrations/0003_link_version_objects_to_nonversion_objects.py

bihealth/hpc-access

ff606b18b18230af2876a791ca706d3b24addb59

[ "MIT" ]

null

usersec/migrations/0003_link_version_objects_to_nonversion_objects.py

bihealth/hpc-access

ff606b18b18230af2876a791ca706d3b24addb59

[ "MIT" ]

27

2022-02-11T15:51:24.000Z

2022-03-31T12:11:20.000Z

usersec/migrations/0003_link_version_objects_to_nonversion_objects.py

bihealth/hpc-access

ff606b18b18230af2876a791ca706d3b24addb59

[ "MIT" ]

null

# Generated by Django 4.0.2 on 2022-03-21 13:37 from django.conf import settings from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ migrations.swappable_dependency(settings.AUTH_USER_MODEL), ("usersec", "0002_hpcgroup_adjustments"), ] operations = [ migrations.RemoveField( model_name="hpcgroupcreaterequest", name="delegate", ), migrations.RemoveField( model_name="hpcuserchangerequest", name="group", ), migrations.RemoveField( model_name="hpcusercreaterequest", name="group", ), migrations.RemoveField( model_name="hpcusercreaterequestversion", name="group", ), migrations.RemoveField( model_name="hpcuserdeleterequest", name="group", ), migrations.AddField( model_name="hpcgroupchangerequestversion", name="belongs_to", field=models.ForeignKey( help_text="Object this version belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="version_history", to="usersec.hpcgroupchangerequest", ), ), migrations.AddField( model_name="hpcgroupcreaterequest", name="delegate_email", field=models.CharField( blank=True, help_text="Email address of the delegate", max_length=64, null=True, ), ), migrations.AddField( model_name="hpcgroupcreaterequest", name="member_emails", field=models.TextField( blank=True, help_text="Email addresses of the group members, comma separated", null=True, ), ), migrations.AddField( model_name="hpcgroupcreaterequestversion", name="belongs_to", field=models.ForeignKey( help_text="Object this version belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="version_history", to="usersec.hpcgroupcreaterequest", ), ), migrations.AddField( model_name="hpcgroupcreaterequestversion", name="delegate_email", field=models.CharField( blank=True, help_text="Email address of the delegate", max_length=64, null=True, ), ), migrations.AddField( model_name="hpcgroupcreaterequestversion", name="member_emails", field=models.TextField( blank=True, help_text="Email addresses of the group members, comma separated", null=True, ), ), migrations.AddField( model_name="hpcgroupdeleterequestversion", name="belongs_to", field=models.ForeignKey( help_text="Object this version belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="version_history", to="usersec.hpcgroupdeleterequest", ), ), migrations.AddField( model_name="hpcgroupversion", name="belongs_to", field=models.ForeignKey( help_text="Object this version belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="version_history", to="usersec.hpcgroup", ), ), migrations.AddField( model_name="hpcuserchangerequest", name="user", field=models.ForeignKey( help_text="User the request belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="%(class)s", to="usersec.hpcuser", ), ), migrations.AddField( model_name="hpcuserchangerequestversion", name="belongs_to", field=models.ForeignKey( help_text="Object this version belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="version_history", to="usersec.hpcuserchangerequest", ), ), migrations.AddField( model_name="hpcuserchangerequestversion", name="user", field=models.ForeignKey( help_text="User the request belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="%(class)s", to="usersec.hpcuser", ), ), migrations.AddField( model_name="hpcusercreaterequest", name="user", field=models.ForeignKey( help_text="User the request belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="%(class)s", to="usersec.hpcuser", ), ), migrations.AddField( model_name="hpcusercreaterequestversion", name="belongs_to", field=models.ForeignKey( help_text="Object this version belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="version_history", to="usersec.hpcusercreaterequest", ), ), migrations.AddField( model_name="hpcusercreaterequestversion", name="user", field=models.ForeignKey( help_text="User the request belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="%(class)s", to="usersec.hpcuser", ), ), migrations.AddField( model_name="hpcuserdeleterequest", name="user", field=models.ForeignKey( help_text="User the request belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="%(class)s", to="usersec.hpcuser", ), ), migrations.AddField( model_name="hpcuserdeleterequestversion", name="belongs_to", field=models.ForeignKey( help_text="Object this version belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="version_history", to="usersec.hpcuserdeleterequest", ), ), migrations.AddField( model_name="hpcuserdeleterequestversion", name="user", field=models.ForeignKey( help_text="User the request belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="%(class)s", to="usersec.hpcuser", ), ), migrations.AddField( model_name="hpcuserversion", name="belongs_to", field=models.ForeignKey( help_text="Object this version belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="version_history", to="usersec.hpcuser", ), ), migrations.AlterField( model_name="hpcgroup", name="folder", field=models.CharField( help_text="Path to the group folder on the cluster", max_length=64, ), ), migrations.AlterField( model_name="hpcgroup", name="name", field=models.CharField(help_text="Name of the group on the cluster", max_length=64), ), migrations.AlterField( model_name="hpcgroupchangerequest", name="comment", field=models.TextField( blank=True, help_text="Comment on request or revision", null=True, ), ), migrations.AlterField( model_name="hpcgroupchangerequest", name="group", field=models.ForeignKey( help_text="Group the request belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="%(class)s", to="usersec.hpcgroup", ), ), migrations.AlterField( model_name="hpcgroupchangerequest", name="requester", field=models.ForeignKey( help_text="User creating the request", null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="%(class)s_requester", to=settings.AUTH_USER_MODEL, ), ), migrations.AlterField( model_name="hpcgroupchangerequestversion", name="comment", field=models.TextField( blank=True, help_text="Comment on request or revision", null=True, ), ), migrations.AlterField( model_name="hpcgroupchangerequestversion", name="group", field=models.ForeignKey( help_text="Group the request belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="%(class)s", to="usersec.hpcgroup", ), ), migrations.AlterField( model_name="hpcgroupchangerequestversion", name="requester", field=models.ForeignKey( help_text="User creating the request", null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="%(class)s_requester", to=settings.AUTH_USER_MODEL, ), ), migrations.AlterField( model_name="hpcgroupcreaterequest", name="comment", field=models.TextField( blank=True, help_text="Comment on request or revision", null=True, ), ), migrations.AlterField( model_name="hpcgroupcreaterequest", name="group", field=models.ForeignKey( help_text="Group the request belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="%(class)s", to="usersec.hpcgroup", ), ), migrations.AlterField( model_name="hpcgroupcreaterequest", name="requester", field=models.ForeignKey( help_text="User creating the request", null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="%(class)s_requester", to=settings.AUTH_USER_MODEL, ), ), migrations.AlterField( model_name="hpcgroupcreaterequestversion", name="comment", field=models.TextField( blank=True, help_text="Comment on request or revision", null=True, ), ), migrations.AlterField( model_name="hpcgroupcreaterequestversion", name="group", field=models.ForeignKey( help_text="Group the request belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="%(class)s", to="usersec.hpcgroup", ), ), migrations.AlterField( model_name="hpcgroupcreaterequestversion", name="requester", field=models.ForeignKey( help_text="User creating the request", null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="%(class)s_requester", to=settings.AUTH_USER_MODEL, ), ), migrations.AlterField( model_name="hpcgroupdeleterequest", name="comment", field=models.TextField( blank=True, help_text="Comment on request or revision", null=True, ), ), migrations.AlterField( model_name="hpcgroupdeleterequest", name="group", field=models.ForeignKey( help_text="Group the request belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="%(class)s", to="usersec.hpcgroup", ), ), migrations.AlterField( model_name="hpcgroupdeleterequest", name="requester", field=models.ForeignKey( help_text="User creating the request", null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="%(class)s_requester", to=settings.AUTH_USER_MODEL, ), ), migrations.AlterField( model_name="hpcgroupdeleterequestversion", name="comment", field=models.TextField( blank=True, help_text="Comment on request or revision", null=True, ), ), migrations.AlterField( model_name="hpcgroupdeleterequestversion", name="group", field=models.ForeignKey( help_text="Group the request belongs to", null=True, on_delete=django.db.models.deletion.CASCADE, related_name="%(class)s", to="usersec.hpcgroup", ), ), migrations.AlterField( model_name="hpcgroupdeleterequestversion", name="requester", field=models.ForeignKey( help_text="User creating the request", null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="%(class)s_requester", to=settings.AUTH_USER_MODEL, ), ), migrations.AlterField( model_name="hpcgroupversion", name="folder", field=models.CharField( help_text="Path to the group folder on the cluster", max_length=64, ), ), migrations.AlterField( model_name="hpcgroupversion", name="name", field=models.CharField(help_text="Name of the group on the cluster", max_length=64), ), migrations.AlterField( model_name="hpcuserchangerequest", name="comment", field=models.TextField( blank=True, help_text="Comment on request or revision", null=True, ), ), migrations.AlterField( model_name="hpcuserchangerequest", name="requester", field=models.ForeignKey( help_text="User creating the request", null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="%(class)s_requester", to=settings.AUTH_USER_MODEL, ), ), migrations.AlterField( model_name="hpcuserchangerequestversion", name="comment", field=models.TextField( blank=True, help_text="Comment on request or revision", null=True, ), ), migrations.AlterField( model_name="hpcuserchangerequestversion", name="requester", field=models.ForeignKey( help_text="User creating the request", null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="%(class)s_requester", to=settings.AUTH_USER_MODEL, ), ), migrations.AlterField( model_name="hpcusercreaterequest", name="comment", field=models.TextField( blank=True, help_text="Comment on request or revision", null=True, ), ), migrations.AlterField( model_name="hpcusercreaterequest", name="requester", field=models.ForeignKey( help_text="User creating the request", null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="%(class)s_requester", to=settings.AUTH_USER_MODEL, ), ), migrations.AlterField( model_name="hpcusercreaterequestversion", name="comment", field=models.TextField( blank=True, help_text="Comment on request or revision", null=True, ), ), migrations.AlterField( model_name="hpcusercreaterequestversion", name="requester", field=models.ForeignKey( help_text="User creating the request", null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="%(class)s_requester", to=settings.AUTH_USER_MODEL, ), ), migrations.AlterField( model_name="hpcuserdeleterequest", name="comment", field=models.TextField( blank=True, help_text="Comment on request or revision", null=True, ), ), migrations.AlterField( model_name="hpcuserdeleterequest", name="requester", field=models.ForeignKey( help_text="User creating the request", null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="%(class)s_requester", to=settings.AUTH_USER_MODEL, ), ), migrations.AlterField( model_name="hpcuserdeleterequestversion", name="comment", field=models.TextField( blank=True, help_text="Comment on request or revision", null=True, ), ), migrations.AlterField( model_name="hpcuserdeleterequestversion", name="requester", field=models.ForeignKey( help_text="User creating the request", null=True, on_delete=django.db.models.deletion.SET_NULL, related_name="%(class)s_requester", to=settings.AUTH_USER_MODEL, ), ), migrations.AlterUniqueTogether( name="hpcgroup", unique_together={("name",)}, ), migrations.AlterUniqueTogether( name="hpcgroupchangerequestversion", unique_together={("belongs_to", "version")}, ), migrations.AlterUniqueTogether( name="hpcgroupcreaterequestversion", unique_together={("belongs_to", "version")}, ), migrations.AlterUniqueTogether( name="hpcgroupdeleterequestversion", unique_together={("belongs_to", "version")}, ), migrations.AlterUniqueTogether( name="hpcgroupversion", unique_together={("name", "version")}, ), migrations.AlterUniqueTogether( name="hpcuser", unique_together={("username",)}, ), migrations.AlterUniqueTogether( name="hpcuserchangerequestversion", unique_together={("belongs_to", "version")}, ), migrations.AlterUniqueTogether( name="hpcuserdeleterequestversion", unique_together={("belongs_to", "version")}, ), migrations.AlterUniqueTogether( name="hpcuserversion", unique_together={("username", "version")}, ), migrations.RemoveField( model_name="hpcgroupcreaterequestversion", name="delegate", ), migrations.RemoveField( model_name="hpcuserchangerequestversion", name="group", ), migrations.RemoveField( model_name="hpcuserdeleterequestversion", name="group", ), ]

35.082102

96

0.515656

1,718

21,365

6.256112

0.058207

0.050242

0.079084

0.091738

0.886304

0.880071

0.749349

0.714831

0

0.002371

0.388018

21,365

608

97

35.139803

0.819656

0.002106

0

0.950166

1

0

0.213669

0.066188

0

1

0

false

0

0.004983

0

0.009967

0

null

0

1

0

1

0

null

0

8

e83bcdfe5a6f7dbf43a9b471fb6776d62de8c38d

10,271

py

Python

Facebook.py

Babuperumana/Fbvdo_downloader

bbcd9761181de082df4cecb20274af20b63c4f21

[ "MIT" ]

null

Facebook.py

Babuperumana/Fbvdo_downloader

bbcd9761181de082df4cecb20274af20b63c4f21

[ "MIT" ]

null

Facebook.py

Babuperumana/Fbvdo_downloader

bbcd9761181de082df4cecb20274af20b63c4f21

[ "MIT" ]

null

#!/usr/bin/env python import os os.system('clear') import signal def keyboardInterruptHandler(signal, frame): print("\nპროგრამა გაითიშა.".format(signal)) exit(0) signal.signal(signal.SIGINT, keyboardInterruptHandler) import pyfiglet result = pyfiglet.figlet_format("Facebook.com") print(result) print("Facebook-Video-Downloader-HD ფეისბუქიდან ვიდეოების გადმომწერი") print("--------------------------------------------------------------------") print("https://github.com/AnonymousFromGeorgia/Facebook-Video-Downloader-HD") print("--------------------------------------------------------------------") from datetime import datetime from tqdm import tqdm import requests import re url = input("შეიყვანეთ ვიდეოს ბმული (URL): ") x = re.match(r'^(https:|)[/][/]www.([^/]+[.])*facebook.com', url) if x: html = requests.get(url).content.decode('utf-8') else: print("--------------------------------------------------") print("მითითებული ვიდეო ვერ მოიძებნა.") print("--------------------------------------------------") print("პროგრამის ავტორი: გიო რგი") print("--------------------------------------------------") print("YouTube - https://youtube.com/AnonymousFromGeorgia") print("--------------------------------------------------") print("Github - https://github.com/AnonymousFromGeorgia") print("--------------------------------------------------") print("Facebook - https://facebook.com/anonimaluri") print("--------------------------------------------------") print("Twitter - https://twitter.com/anonimaluri") print("--------------------------------------------------") print("ანონიმუსი საქართველოდან - Anonymous From Georgia") print("--------------------------------------------------") exit() _qualityhd = re.search('hd_src:"https', html) _qualitysd = re.search('sd_src:"https', html) _hd = re.search('hd_src:null', html) _sd = re.search('sd_src:null', html) list = [] _thelist = [_qualityhd, _qualitysd, _hd, _sd] for id,val in enumerate(_thelist): if val != None: list.append(id) try: if len(list) == 2: if 0 in list and 1 in list: _input_1 = str(input("\nდააჭირეთ კლავიშ 'A'-ს რათა გადმოწეროთ ვიდეო HD ხარისხში.\nდააჭირეთ კლავიშ 'B'-ს რათა გადმოწეროთ ვიდეო SD ხარისხში.\n: ")).upper() if _input_1 == 'A': print("\nმიმდინარეობს ვიდეოს გადმოწერა HD ხარისხით.") video_url = re.search(r'hd_src:"(.+?)"', html).group(1) file_size_request = requests.get(video_url, stream=True) file_size = int(file_size_request.headers['Content-Length']) block_size = 1024 filename = datetime.strftime(datetime.now(), '%Y-%m-%d-%H-%M-%S') t=tqdm(total=file_size, unit='B', unit_scale=True, desc=filename, ascii=True) with open(filename + '.mp4', 'wb') as f: for data in file_size_request.iter_content(block_size): t.update(len(data)) f.write(data) t.close() print("--------------------------------------------------") print("ვიდეოს გადმოწერა წარმატებით დასრულდა.") print("--------------------------------------------------") print("პროგრამის ავტორი: გიო რგი") print("--------------------------------------------------") print("YouTube - https://youtube.com/AnonymousFromGeorgia") print("--------------------------------------------------") print("Github - https://github.com/AnonymousFromGeorgia") print("--------------------------------------------------") print("Facebook - https://facebook.com/anonimaluri") print("--------------------------------------------------") print("Twitter - https://twitter.com/anonimaluri") print("--------------------------------------------------") print("ანონიმუსი საქართველოდან - Anonymous From Georgia") print("--------------------------------------------------") if _input_1 == 'B': print("\nმიმდინარეობს ვიდეოს გადმოწერა SD ხარისხით.") video_url = re.search(r'sd_src:"(.+?)"', html).group(1) file_size_request = requests.get(video_url, stream=True) file_size = int(file_size_request.headers['Content-Length']) block_size = 1024 filename = datetime.strftime(datetime.now(), '%Y-%m-%d-%H-%M-%S') t=tqdm(total=file_size, unit='B', unit_scale=True, desc=filename, ascii=True) with open(filename + '.mp4', 'wb') as f: for data in file_size_request.iter_content(block_size): t.update(len(data)) f.write(data) t.close() print("--------------------------------------------------") print("ვიდეოს გადმოწერა წარმატებით დასრულდა.") print("--------------------------------------------------") print("პროგრამის ავტორი: გიო რგი") print("--------------------------------------------------") print("YouTube - https://youtube.com/AnonymousFromGeorgia") print("--------------------------------------------------") print("Github - https://github.com/AnonymousFromGeorgia") print("--------------------------------------------------") print("Facebook - https://facebook.com/anonimaluri") print("--------------------------------------------------") print("Twitter - https://twitter.com/anonimaluri") print("--------------------------------------------------") print("ანონიმუსი საქართველოდან - Anonymous From Georgia") print("--------------------------------------------------") if len(list) == 2: if 1 in list and 2 in list: _input_2 = str(input("ბოდიში! სამწუხაროდ ვიდეო არაა ხელმისაწვდომი HD ხარისხში. გნებავთ, რომ მაინც გადმოწეროთ? ('Y' ან 'N'): ")).upper() if _input_2 == 'Y': print("\nმიმდინარეობს ვიდეოს გადმოწერა SD ხარისხით.") video_url = re.search(r'sd_src:"(.+?)"', html).group(1) file_size_request = requests.get(video_url, stream=True) file_size = int(file_size_request.headers['Content-Length']) block_size = 1024 filename = datetime.strftime(datetime.now(), '%Y-%m-%d-%H-%M-%S') t=tqdm(total=file_size, unit='B', unit_scale=True, desc=filename, ascii=True) with open(filename + '.mp4', 'wb') as f: for data in file_size_request.iter_content(block_size): t.update(len(data)) f.write(data) t.close() print("--------------------------------------------------") print("ვიდეოს გადმოწერა წარმატებით დასრულდა.") print("--------------------------------------------------") print("პროგრამის ავტორი: გიო რგი") print("--------------------------------------------------") print("YouTube - https://youtube.com/AnonymousFromGeorgia") print("--------------------------------------------------") print("Github - https://github.com/AnonymousFromGeorgia") print("--------------------------------------------------") print("Facebook - https://facebook.com/anonimaluri") print("--------------------------------------------------") print("Twitter - https://twitter.com/anonimaluri") print("--------------------------------------------------") print("ანონიმუსი საქართველოდან - Anonymous From Georgia") print("--------------------------------------------------") if _input_2 == 'N': exit() if len(list) == 2: if 0 in list and 3 in list: _input_2 = str(input("ბოდიში! სამწუხაროდ ვიდეო არაა ხელმისაწვდომი SD ხარისხში. გნებავთ, რომ მაინც გადმოწეროთ? ('Y' ან 'N'): \n")).upper() if _input_2 == 'Y': print("\nმიმდინარეობს ვიდეოს გადმოწერა HD ხარისხით.") video_url = re.search(r'hd_src:"(.+?)"', html).group(1) file_size_request = requests.get(video_url, stream=True) file_size = int(file_size_request.headers['Content-Length']) block_size = 1024 filename = datetime.strftime(datetime.now(), '%Y-%m-%d-%H-%M-%S') t=tqdm(total=file_size, unit='B', unit_scale=True, desc=filename, ascii=True) with open(filename + '.mp4', 'wb') as f: for data in file_size_request.iter_content(block_size): t.update(len(data)) f.write(data) t.close() print("ვიდეოს გადმოწერა წარმატებით დასრულდა.") print("--------------------------------------------------") print("Author of the program: Babu") print("--------------------------------------------------") print("YouTube - https://youtube.com/AnonymousFromGeorgia") print("--------------------------------------------------") print("Github - https://github.com/AnonymousFromGeorgia") print("--------------------------------------------------") print("Facebook - https://facebook.com/anonimaluri") print("--------------------------------------------------") print("Twitter - https://twitter.com/anonimaluri") print("--------------------------------------------------") print("Anonymous from Georgia - Anonymous From Georgia") print("--------------------------------------------------") if _input_2 == 'N': exit() except(KeyboardInterrupt): print("\nThe program is off.")

53.217617

165

0.429559

867

10,271

4.981546

0.185698

0.081037

0.041676

0.076407

0.768233

0.765918

0.755962

0.73906

0.718685

0

0.005767

0.257132

10,271

192

166

53.494792

0.560288

0.001947

0

0.748571

0

0.017143

0.445659

0.210439

0

1

0.005714

false

0

0.04

0

0.045714

0.485714

0

null

0

1

0

1

0

null

0

1

0

7

fa0d93438adcee59e6b32cb1f2b3c21038b49431

5,626

py

Python

tests/test_actual.py

TalAmuyal/py-cpuinfo

6423f9a0ee46c8e4be21a70d38b6ebafb9b6d645

[ "MIT" ]

211

2015-01-13T20:00:20.000Z

2022-03-24T19:01:43.000Z

tests/test_actual.py

TalAmuyal/py-cpuinfo

6423f9a0ee46c8e4be21a70d38b6ebafb9b6d645

[ "MIT" ]

133

2015-01-20T01:27:31.000Z

2022-03-14T09:45:16.000Z

tests/test_actual.py

TalAmuyal/py-cpuinfo

6423f9a0ee46c8e4be21a70d38b6ebafb9b6d645

[ "MIT" ]

50

2015-01-13T20:00:23.000Z

2021-09-24T15:24:06.000Z

import unittest from cpuinfo import * import helpers class TestActual(unittest.TestCase): def setUp(self): helpers.backup_data_source(cpuinfo) def tearDown(self): helpers.restore_data_source(cpuinfo) def test_all(self): os_type = helpers.get_os_type() if os_type == 'BeOS': self.assertEqual({}, cpuinfo._get_cpu_info_from_registry()) self.assertEqual({}, cpuinfo._get_cpu_info_from_cpufreq_info()) self.assertEqual({}, cpuinfo._get_cpu_info_from_lscpu()) self.assertEqual({}, cpuinfo._get_cpu_info_from_proc_cpuinfo()) self.assertEqual({}, cpuinfo._get_cpu_info_from_sysctl()) self.assertEqual({}, cpuinfo._get_cpu_info_from_kstat()) self.assertEqual({}, cpuinfo._get_cpu_info_from_dmesg()) self.assertEqual({}, cpuinfo._get_cpu_info_from_cat_var_run_dmesg_boot()) self.assertTrue(len(cpuinfo._get_cpu_info_from_sysinfo()) > 0) #self.assertTrue(len(cpuinfo._get_cpu_info_from_cpuid()) > 0) self.assertTrue(len(cpuinfo.get_cpu_info()) > 0) elif os_type == 'BSD': self.assertEqual({}, cpuinfo._get_cpu_info_from_registry()) self.assertEqual({}, cpuinfo._get_cpu_info_from_cpufreq_info()) self.assertEqual({}, cpuinfo._get_cpu_info_from_lscpu()) self.assertEqual({}, cpuinfo._get_cpu_info_from_proc_cpuinfo()) self.assertEqual({}, cpuinfo._get_cpu_info_from_sysctl()) self.assertEqual({}, cpuinfo._get_cpu_info_from_kstat()) self.assertTrue(len(cpuinfo._get_cpu_info_from_dmesg()) > 0) self.assertEqual({}, cpuinfo._get_cpu_info_from_cat_var_run_dmesg_boot()) self.assertEqual({}, cpuinfo._get_cpu_info_from_sysinfo()) # FIXME: This fails by segfaulting for some reason #self.assertEqual({}, cpuinfo._get_cpu_info_from_cpuid()) self.assertTrue(len(cpuinfo.get_cpu_info()) > 0) elif os_type == 'Cygwin': self.assertEqual({}, cpuinfo._get_cpu_info_from_registry()) self.assertEqual({}, cpuinfo._get_cpu_info_from_cpufreq_info()) self.assertEqual({}, cpuinfo._get_cpu_info_from_lscpu()) self.assertTrue(len(cpuinfo._get_cpu_info_from_proc_cpuinfo()) > 0) self.assertEqual({}, cpuinfo._get_cpu_info_from_sysctl()) self.assertEqual({}, cpuinfo._get_cpu_info_from_kstat()) self.assertEqual({}, cpuinfo._get_cpu_info_from_dmesg()) self.assertEqual({}, cpuinfo._get_cpu_info_from_cat_var_run_dmesg_boot()) self.assertEqual({}, cpuinfo._get_cpu_info_from_sysinfo()) # FIXME: This fails by segfaulting for some reason #self.assertEqual({}, cpuinfo._get_cpu_info_from_cpuid()) self.assertTrue(len(cpuinfo.get_cpu_info()) > 0) elif os_type == 'MacOS': self.assertEqual({}, cpuinfo._get_cpu_info_from_registry()) self.assertEqual({}, cpuinfo._get_cpu_info_from_cpufreq_info()) self.assertEqual({}, cpuinfo._get_cpu_info_from_lscpu()) self.assertEqual({}, cpuinfo._get_cpu_info_from_proc_cpuinfo()) self.assertTrue(len(cpuinfo._get_cpu_info_from_sysctl()) > 0) self.assertEqual({}, cpuinfo._get_cpu_info_from_kstat()) self.assertEqual({}, cpuinfo._get_cpu_info_from_dmesg()) self.assertEqual({}, cpuinfo._get_cpu_info_from_cat_var_run_dmesg_boot()) self.assertEqual({}, cpuinfo._get_cpu_info_from_sysinfo()) # FIXME: This fails by segfaulting for some reason #self.assertEqual({}, cpuinfo._get_cpu_info_from_cpuid()) self.assertTrue(len(cpuinfo.get_cpu_info()) > 0) elif os_type == 'Linux': self.assertEqual({}, cpuinfo._get_cpu_info_from_registry()) self.assertEqual({}, cpuinfo._get_cpu_info_from_cpufreq_info()) #self.assertTrue(len(cpuinfo._get_cpu_info_from_lscpu()) > 0) self.assertTrue(len(cpuinfo._get_cpu_info_from_proc_cpuinfo()) > 0) self.assertEqual({}, cpuinfo._get_cpu_info_from_sysctl()) self.assertEqual({}, cpuinfo._get_cpu_info_from_kstat()) self.assertEqual({}, cpuinfo._get_cpu_info_from_dmesg()) self.assertEqual({}, cpuinfo._get_cpu_info_from_cat_var_run_dmesg_boot()) self.assertEqual({}, cpuinfo._get_cpu_info_from_sysinfo()) #self.assertTrue(len(cpuinfo._get_cpu_info_from_cpuid()) > 0) self.assertTrue(len(cpuinfo.get_cpu_info()) > 0) elif os_type == 'Solaris': self.assertEqual({}, cpuinfo._get_cpu_info_from_registry()) self.assertEqual({}, cpuinfo._get_cpu_info_from_cpufreq_info()) self.assertEqual({}, cpuinfo._get_cpu_info_from_lscpu()) self.assertEqual({}, cpuinfo._get_cpu_info_from_proc_cpuinfo()) self.assertEqual({}, cpuinfo._get_cpu_info_from_sysctl()) self.assertTrue(len(cpuinfo._get_cpu_info_from_kstat()) > 0) self.assertEqual({}, cpuinfo._get_cpu_info_from_dmesg()) self.assertEqual({}, cpuinfo._get_cpu_info_from_cat_var_run_dmesg_boot()) self.assertEqual({}, cpuinfo._get_cpu_info_from_sysinfo()) # FIXME: This fails by segfaulting for some reason #self.assertEqual({}, cpuinfo._get_cpu_info_from_cpuid()) self.assertTrue(len(cpuinfo.get_cpu_info()) > 0) elif os_type == 'Windows': self.assertTrue(len(cpuinfo._get_cpu_info_from_registry()) > 0) self.assertEqual({}, cpuinfo._get_cpu_info_from_cpufreq_info()) self.assertEqual({}, cpuinfo._get_cpu_info_from_lscpu()) self.assertEqual({}, cpuinfo._get_cpu_info_from_proc_cpuinfo()) self.assertEqual({}, cpuinfo._get_cpu_info_from_sysctl()) self.assertEqual({}, cpuinfo._get_cpu_info_from_kstat()) self.assertEqual({}, cpuinfo._get_cpu_info_from_dmesg()) self.assertEqual({}, cpuinfo._get_cpu_info_from_cat_var_run_dmesg_boot()) self.assertEqual({}, cpuinfo._get_cpu_info_from_sysinfo()) #self.assertTrue(len(cpuinfo._get_cpu_info_from_cpuid()) > 0) self.assertTrue(len(cpuinfo.get_cpu_info()) > 0) else: raise AssertionError('Unexpected OS type "{0}".'.format(os_type))

51.614679

76

0.764842

787

5,626

4.931385

0.07878

0.198402

0.257923

0.337284

0.923731

0.914455

0.85983

0.859315

0

0.003737

0.096338

5,626

108

77

52.092593

0.759638

0.117312

0

0.727273

0

0.01252

0

0.009259

0.795455

1

0.034091

false

0

0.034091

0

0.079545

0

null

0

1

0

1

0

null

0

1

0

10

fa297e2470ee272c9cc96cb0be3c3e5a10b1d168

6,545

py

Python

loldib/getratings/models/NA/na_kennen/na_kennen_bot.py

koliupy/loldib

c9ab94deb07213cdc42b5a7c26467cdafaf81b7f

[ "Apache-2.0" ]

null

loldib/getratings/models/NA/na_kennen/na_kennen_bot.py

koliupy/loldib

c9ab94deb07213cdc42b5a7c26467cdafaf81b7f

[ "Apache-2.0" ]

null

loldib/getratings/models/NA/na_kennen/na_kennen_bot.py

koliupy/loldib

c9ab94deb07213cdc42b5a7c26467cdafaf81b7f

[ "Apache-2.0" ]

null

from getratings.models.ratings import Ratings class NA_Kennen_Bot_Aatrox(Ratings): pass class NA_Kennen_Bot_Ahri(Ratings): pass class NA_Kennen_Bot_Akali(Ratings): pass class NA_Kennen_Bot_Alistar(Ratings): pass class NA_Kennen_Bot_Amumu(Ratings): pass class NA_Kennen_Bot_Anivia(Ratings): pass class NA_Kennen_Bot_Annie(Ratings): pass class NA_Kennen_Bot_Ashe(Ratings): pass class NA_Kennen_Bot_AurelionSol(Ratings): pass class NA_Kennen_Bot_Azir(Ratings): pass class NA_Kennen_Bot_Bard(Ratings): pass class NA_Kennen_Bot_Blitzcrank(Ratings): pass class NA_Kennen_Bot_Brand(Ratings): pass class NA_Kennen_Bot_Braum(Ratings): pass class NA_Kennen_Bot_Caitlyn(Ratings): pass class NA_Kennen_Bot_Camille(Ratings): pass class NA_Kennen_Bot_Cassiopeia(Ratings): pass class NA_Kennen_Bot_Chogath(Ratings): pass class NA_Kennen_Bot_Corki(Ratings): pass class NA_Kennen_Bot_Darius(Ratings): pass class NA_Kennen_Bot_Diana(Ratings): pass class NA_Kennen_Bot_Draven(Ratings): pass class NA_Kennen_Bot_DrMundo(Ratings): pass class NA_Kennen_Bot_Ekko(Ratings): pass class NA_Kennen_Bot_Elise(Ratings): pass class NA_Kennen_Bot_Evelynn(Ratings): pass class NA_Kennen_Bot_Ezreal(Ratings): pass class NA_Kennen_Bot_Fiddlesticks(Ratings): pass class NA_Kennen_Bot_Fiora(Ratings): pass class NA_Kennen_Bot_Fizz(Ratings): pass class NA_Kennen_Bot_Galio(Ratings): pass class NA_Kennen_Bot_Gangplank(Ratings): pass class NA_Kennen_Bot_Garen(Ratings): pass class NA_Kennen_Bot_Gnar(Ratings): pass class NA_Kennen_Bot_Gragas(Ratings): pass class NA_Kennen_Bot_Graves(Ratings): pass class NA_Kennen_Bot_Hecarim(Ratings): pass class NA_Kennen_Bot_Heimerdinger(Ratings): pass class NA_Kennen_Bot_Illaoi(Ratings): pass class NA_Kennen_Bot_Irelia(Ratings): pass class NA_Kennen_Bot_Ivern(Ratings): pass class NA_Kennen_Bot_Janna(Ratings): pass class NA_Kennen_Bot_JarvanIV(Ratings): pass class NA_Kennen_Bot_Jax(Ratings): pass class NA_Kennen_Bot_Jayce(Ratings): pass class NA_Kennen_Bot_Jhin(Ratings): pass class NA_Kennen_Bot_Jinx(Ratings): pass class NA_Kennen_Bot_Kalista(Ratings): pass class NA_Kennen_Bot_Karma(Ratings): pass class NA_Kennen_Bot_Karthus(Ratings): pass class NA_Kennen_Bot_Kassadin(Ratings): pass class NA_Kennen_Bot_Katarina(Ratings): pass class NA_Kennen_Bot_Kayle(Ratings): pass class NA_Kennen_Bot_Kayn(Ratings): pass class NA_Kennen_Bot_Kennen(Ratings): pass class NA_Kennen_Bot_Khazix(Ratings): pass class NA_Kennen_Bot_Kindred(Ratings): pass class NA_Kennen_Bot_Kled(Ratings): pass class NA_Kennen_Bot_KogMaw(Ratings): pass class NA_Kennen_Bot_Leblanc(Ratings): pass class NA_Kennen_Bot_LeeSin(Ratings): pass class NA_Kennen_Bot_Leona(Ratings): pass class NA_Kennen_Bot_Lissandra(Ratings): pass class NA_Kennen_Bot_Lucian(Ratings): pass class NA_Kennen_Bot_Lulu(Ratings): pass class NA_Kennen_Bot_Lux(Ratings): pass class NA_Kennen_Bot_Malphite(Ratings): pass class NA_Kennen_Bot_Malzahar(Ratings): pass class NA_Kennen_Bot_Maokai(Ratings): pass class NA_Kennen_Bot_MasterYi(Ratings): pass class NA_Kennen_Bot_MissFortune(Ratings): pass class NA_Kennen_Bot_MonkeyKing(Ratings): pass class NA_Kennen_Bot_Mordekaiser(Ratings): pass class NA_Kennen_Bot_Morgana(Ratings): pass class NA_Kennen_Bot_Nami(Ratings): pass class NA_Kennen_Bot_Nasus(Ratings): pass class NA_Kennen_Bot_Nautilus(Ratings): pass class NA_Kennen_Bot_Nidalee(Ratings): pass class NA_Kennen_Bot_Nocturne(Ratings): pass class NA_Kennen_Bot_Nunu(Ratings): pass class NA_Kennen_Bot_Olaf(Ratings): pass class NA_Kennen_Bot_Orianna(Ratings): pass class NA_Kennen_Bot_Ornn(Ratings): pass class NA_Kennen_Bot_Pantheon(Ratings): pass class NA_Kennen_Bot_Poppy(Ratings): pass class NA_Kennen_Bot_Quinn(Ratings): pass class NA_Kennen_Bot_Rakan(Ratings): pass class NA_Kennen_Bot_Rammus(Ratings): pass class NA_Kennen_Bot_RekSai(Ratings): pass class NA_Kennen_Bot_Renekton(Ratings): pass class NA_Kennen_Bot_Rengar(Ratings): pass class NA_Kennen_Bot_Riven(Ratings): pass class NA_Kennen_Bot_Rumble(Ratings): pass class NA_Kennen_Bot_Ryze(Ratings): pass class NA_Kennen_Bot_Sejuani(Ratings): pass class NA_Kennen_Bot_Shaco(Ratings): pass class NA_Kennen_Bot_Shen(Ratings): pass class NA_Kennen_Bot_Shyvana(Ratings): pass class NA_Kennen_Bot_Singed(Ratings): pass class NA_Kennen_Bot_Sion(Ratings): pass class NA_Kennen_Bot_Sivir(Ratings): pass class NA_Kennen_Bot_Skarner(Ratings): pass class NA_Kennen_Bot_Sona(Ratings): pass class NA_Kennen_Bot_Soraka(Ratings): pass class NA_Kennen_Bot_Swain(Ratings): pass class NA_Kennen_Bot_Syndra(Ratings): pass class NA_Kennen_Bot_TahmKench(Ratings): pass class NA_Kennen_Bot_Taliyah(Ratings): pass class NA_Kennen_Bot_Talon(Ratings): pass class NA_Kennen_Bot_Taric(Ratings): pass class NA_Kennen_Bot_Teemo(Ratings): pass class NA_Kennen_Bot_Thresh(Ratings): pass class NA_Kennen_Bot_Tristana(Ratings): pass class NA_Kennen_Bot_Trundle(Ratings): pass class NA_Kennen_Bot_Tryndamere(Ratings): pass class NA_Kennen_Bot_TwistedFate(Ratings): pass class NA_Kennen_Bot_Twitch(Ratings): pass class NA_Kennen_Bot_Udyr(Ratings): pass class NA_Kennen_Bot_Urgot(Ratings): pass class NA_Kennen_Bot_Varus(Ratings): pass class NA_Kennen_Bot_Vayne(Ratings): pass class NA_Kennen_Bot_Veigar(Ratings): pass class NA_Kennen_Bot_Velkoz(Ratings): pass class NA_Kennen_Bot_Vi(Ratings): pass class NA_Kennen_Bot_Viktor(Ratings): pass class NA_Kennen_Bot_Vladimir(Ratings): pass class NA_Kennen_Bot_Volibear(Ratings): pass class NA_Kennen_Bot_Warwick(Ratings): pass class NA_Kennen_Bot_Xayah(Ratings): pass class NA_Kennen_Bot_Xerath(Ratings): pass class NA_Kennen_Bot_XinZhao(Ratings): pass class NA_Kennen_Bot_Yasuo(Ratings): pass class NA_Kennen_Bot_Yorick(Ratings): pass class NA_Kennen_Bot_Zac(Ratings): pass class NA_Kennen_Bot_Zed(Ratings): pass class NA_Kennen_Bot_Ziggs(Ratings): pass class NA_Kennen_Bot_Zilean(Ratings): pass class NA_Kennen_Bot_Zyra(Ratings): pass

15.695444

46

0.766692

972

6,545

4.736626

0.151235

0.209818

0.389661

0.479583

0.803432

0

0.169748

6,545

416

47

15.733173

0.847258

0

0.498195

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1

0

true

0.498195

0.00361

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1

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null

0

1

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1

0

8

fa465f14d7c2aa192af8f47750c27f610542c69d

30,509

py

Python

testcases/generated/ipanti_test.py

Tanc009/jdcloud-cli

4e11de77c68501f44e7026c0ad1c24e5d043197e

[ "Apache-2.0" ]

null

testcases/generated/ipanti_test.py

Tanc009/jdcloud-cli

4e11de77c68501f44e7026c0ad1c24e5d043197e

[ "Apache-2.0" ]

null

testcases/generated/ipanti_test.py

Tanc009/jdcloud-cli

4e11de77c68501f44e7026c0ad1c24e5d043197e

[ "Apache-2.0" ]

null

# coding=utf8 # Copyright 2018 JDCLOUD.COM # # 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. # # NOTE: This class is auto generated by the jdcloud code generator program. import unittest import os import json class IpantiTest(unittest.TestCase): def test_describe_ddo_sattack_logs(self): cmd = """python ../../main.py ipanti describe-ddo-sattack-logs --start-time 'xxx' --end-time 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_ccattack_logs(self): cmd = """python ../../main.py ipanti describe-ccattack-logs --start-time 'xxx' --end-time 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_ccattack_log_details(self): cmd = """python ../../main.py ipanti describe-ccattack-log-details --start-time 'xxx' --end-time 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_attack_statistics(self): cmd = """python ../../main.py ipanti describe-attack-statistics --start-time 'xxx' --end-time 'xxx' --type '5'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_attack_type_count(self): cmd = """python ../../main.py ipanti describe-attack-type-count --start-time 'xxx' --end-time 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_ddo_sgraph(self): cmd = """python ../../main.py ipanti describe-ddo-sgraph --start-time 'xxx' --end-time 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_fwd_graph(self): cmd = """python ../../main.py ipanti describe-fwd-graph --start-time 'xxx' --end-time 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_ccgraph(self): cmd = """python ../../main.py ipanti describe-ccgraph --start-time 'xxx' --end-time 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_forward_rules(self): cmd = """python ../../main.py ipanti describe-forward-rules --instance-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_create_forward_rule(self): cmd = """python ../../main.py ipanti create-forward-rule --instance-id 'xxx' --forward-rule-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_forward_rule(self): cmd = """python ../../main.py ipanti describe-forward-rule --instance-id 'xxx' --forward-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_modify_forward_rule(self): cmd = """python ../../main.py ipanti modify-forward-rule --instance-id 'xxx' --forward-rule-id 'xxx' --forward-rule-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_delete_forward_rule(self): cmd = """python ../../main.py ipanti delete-forward-rule --instance-id 'xxx' --forward-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_switch_forward_rule_protect(self): cmd = """python ../../main.py ipanti switch-forward-rule-protect --instance-id 'xxx' --forward-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_switch_forward_rule_origin(self): cmd = """python ../../main.py ipanti switch-forward-rule-origin --instance-id 'xxx' --forward-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_protection_rule_of_forward_rule(self): cmd = """python ../../main.py ipanti describe-protection-rule-of-forward-rule --instance-id 'xxx' --forward-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_modify_protection_rule_of_forward_rule(self): cmd = """python ../../main.py ipanti modify-protection-rule-of-forward-rule --instance-id 'xxx' --forward-rule-id 'xxx' --forward-protection-rule-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_geo_areas(self): cmd = """python ../../main.py ipanti describe-geo-areas """ with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_black_list_rule_of_forward_rule(self): cmd = """python ../../main.py ipanti describe-black-list-rule-of-forward-rule --instance-id 'xxx' --forward-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_modify_black_list_rule_of_forward_rule(self): cmd = """python ../../main.py ipanti modify-black-list-rule-of-forward-rule --instance-id 'xxx' --forward-rule-id 'xxx' --modify-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_enable_black_list_rule_of_forward_rule(self): cmd = """python ../../main.py ipanti enable-black-list-rule-of-forward-rule --instance-id 'xxx' --forward-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_disable_black_list_rule_of_forward_rule(self): cmd = """python ../../main.py ipanti disable-black-list-rule-of-forward-rule --instance-id 'xxx' --forward-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_white_list_rule_of_forward_rule(self): cmd = """python ../../main.py ipanti describe-white-list-rule-of-forward-rule --instance-id 'xxx' --forward-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_modify_white_list_rule_of_forward_rule(self): cmd = """python ../../main.py ipanti modify-white-list-rule-of-forward-rule --instance-id 'xxx' --forward-rule-id 'xxx' --modify-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_enable_white_list_rule_of_forward_rule(self): cmd = """python ../../main.py ipanti enable-white-list-rule-of-forward-rule --instance-id 'xxx' --forward-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_disable_white_list_rule_of_forward_rule(self): cmd = """python ../../main.py ipanti disable-white-list-rule-of-forward-rule --instance-id 'xxx' --forward-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_instances(self): cmd = """python ../../main.py ipanti describe-instances """ with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_create_instance(self): cmd = """python ../../main.py ipanti create-instance --create-instance-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_instance(self): cmd = """python ../../main.py ipanti describe-instance --instance-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_modify_instance_name(self): cmd = """python ../../main.py ipanti modify-instance-name --instance-id 'xxx' --rename-instance-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_modify_epb(self): cmd = """python ../../main.py ipanti modify-epb --instance-id 'xxx' --modify-instance-epbspec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_alarm_config(self): cmd = """python ../../main.py ipanti describe-alarm-config --instance-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_modify_alarm_config(self): cmd = """python ../../main.py ipanti modify-alarm-config --instance-id 'xxx' --alarm-config-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_name_list(self): cmd = """python ../../main.py ipanti describe-name-list """ with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_protection_statistics(self): cmd = """python ../../main.py ipanti describe-protection-statistics """ with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_check_name(self): cmd = """python ../../main.py ipanti check-name --name 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_vpc_ip_list(self): cmd = """python ../../main.py ipanti describe-vpc-ip-list """ with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_cps_ip_list(self): cmd = """python ../../main.py ipanti describe-cps-ip-list """ with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_ip_sets(self): cmd = """python ../../main.py ipanti describe-ip-sets --instance-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_create_ip_set(self): cmd = """python ../../main.py ipanti create-ip-set --instance-id 'xxx' --ip-set-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_ip_set(self): cmd = """python ../../main.py ipanti describe-ip-set --instance-id 'xxx' --ip-set-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_delete_ip_set(self): cmd = """python ../../main.py ipanti delete-ip-set --instance-id 'xxx' --ip-set-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_ip_set_usage(self): cmd = """python ../../main.py ipanti describe-ip-set-usage --instance-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_web_rules(self): cmd = """python ../../main.py ipanti describe-web-rules --instance-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_create_web_rule(self): cmd = """python ../../main.py ipanti create-web-rule --instance-id 'xxx' --web-rule-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_web_rule(self): cmd = """python ../../main.py ipanti describe-web-rule --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_modify_web_rule(self): cmd = """python ../../main.py ipanti modify-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --web-rule-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_delete_web_rule(self): cmd = """python ../../main.py ipanti delete-web-rule --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_switch_web_rule_protect(self): cmd = """python ../../main.py ipanti switch-web-rule-protect --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_switch_web_rule_origin(self): cmd = """python ../../main.py ipanti switch-web-rule-origin --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_enable_web_rule_cc(self): cmd = """python ../../main.py ipanti enable-web-rule-cc --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_disable_web_rule_cc(self): cmd = """python ../../main.py ipanti disable-web-rule-cc --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_enable_web_rule_ccobserver_mode(self): cmd = """python ../../main.py ipanti enable-web-rule-ccobserver-mode --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_disable_web_rule_ccobserver_mode(self): cmd = """python ../../main.py ipanti disable-web-rule-ccobserver-mode --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_ccprotection_rules_of_web_rule(self): cmd = """python ../../main.py ipanti describe-ccprotection-rules-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_create_ccprotection_rule_of_web_rule(self): cmd = """python ../../main.py ipanti create-ccprotection-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --cc-protection-rule-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_ccprotection_rule_of_web_rule(self): cmd = """python ../../main.py ipanti describe-ccprotection-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --cc-protection-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_modify_ccprotection_rule_of_web_rule(self): cmd = """python ../../main.py ipanti modify-ccprotection-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --cc-protection-rule-id 'xxx' --cc-protection-rule-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_delete_ccprotection_rule_of_web_rule(self): cmd = """python ../../main.py ipanti delete-ccprotection-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --cc-protection-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_enable_ccprotection_rule_of_web_rule(self): cmd = """python ../../main.py ipanti enable-ccprotection-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --cc-protection-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_disable_ccprotection_rule_of_web_rule(self): cmd = """python ../../main.py ipanti disable-ccprotection-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --cc-protection-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_ccprotection_config_of_web_rule(self): cmd = """python ../../main.py ipanti describe-ccprotection-config-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_modify_ccprotection_config_of_web_rule(self): cmd = """python ../../main.py ipanti modify-ccprotection-config-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --cc-protection-config-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_ccprotection_default_config_of_web_rule(self): cmd = """python ../../main.py ipanti describe-ccprotection-default-config-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_modify_cert_info(self): cmd = """python ../../main.py ipanti modify-cert-info --instance-id 'xxx' --web-rule-id 'xxx' --cert-info-modify-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_web_rule_black_list_usage(self): cmd = """python ../../main.py ipanti describe-web-rule-black-list-usage --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_black_list_rules_of_web_rule(self): cmd = """python ../../main.py ipanti describe-black-list-rules-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_create_black_list_rule_of_web_rule(self): cmd = """python ../../main.py ipanti create-black-list-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --web-black-list-rule-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_black_list_rule_of_web_rule(self): cmd = """python ../../main.py ipanti describe-black-list-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --web-black-list-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_modify_black_list_rule_of_web_rule(self): cmd = """python ../../main.py ipanti modify-black-list-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --web-black-list-rule-id 'xxx' --web-black-list-rule-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_delete_black_list_rule_of_web_rule(self): cmd = """python ../../main.py ipanti delete-black-list-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --web-black-list-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_enable_web_rule_black_list(self): cmd = """python ../../main.py ipanti enable-web-rule-black-list --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_enable_black_list_rule_of_web_rule(self): cmd = """python ../../main.py ipanti enable-black-list-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --web-black-list-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_disable_web_rule_black_list(self): cmd = """python ../../main.py ipanti disable-web-rule-black-list --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_disable_black_list_rule_of_web_rule(self): cmd = """python ../../main.py ipanti disable-black-list-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --web-black-list-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_web_rule_white_list_usage(self): cmd = """python ../../main.py ipanti describe-web-rule-white-list-usage --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_white_list_rules_of_web_rule(self): cmd = """python ../../main.py ipanti describe-white-list-rules-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_create_white_list_rule_of_web_rule(self): cmd = """python ../../main.py ipanti create-white-list-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --web-white-list-rule-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_white_list_rule_of_web_rule(self): cmd = """python ../../main.py ipanti describe-white-list-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --web-white-list-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_modify_white_list_rule_of_web_rule(self): cmd = """python ../../main.py ipanti modify-white-list-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --web-white-list-rule-id 'xxx' --web-white-list-rule-spec '{"":""}'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_delete_white_list_rule_of_web_rule(self): cmd = """python ../../main.py ipanti delete-white-list-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --web-white-list-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_enable_web_rule_white_list(self): cmd = """python ../../main.py ipanti enable-web-rule-white-list --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_enable_white_list_rule_of_web_rule(self): cmd = """python ../../main.py ipanti enable-white-list-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --web-white-list-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_disable_web_rule_white_list(self): cmd = """python ../../main.py ipanti disable-web-rule-white-list --instance-id 'xxx' --web-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_disable_white_list_rule_of_web_rule(self): cmd = """python ../../main.py ipanti disable-white-list-rule-of-web-rule --instance-id 'xxx' --web-rule-id 'xxx' --web-white-list-rule-id 'xxx'""" with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_web_rule_black_list_geo_areas(self): cmd = """python ../../main.py ipanti describe-web-rule-black-list-geo-areas """ with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict) def test_describe_web_rule_white_list_geo_areas(self): cmd = """python ../../main.py ipanti describe-web-rule-white-list-geo-areas """ with os.popen(cmd) as f: content = f.read() print(content) result = json.loads(content) self.assertIsInstance(result, dict)

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null

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1

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0

7

d710e1f67c4c77e907a35c2015734cab4608ac99

4,292

py

Python

PyBank/main.py

MAICATRAN/python-challenge

748ea0b3c480740a19a3710725899d62e01bdcdc

[ "Apache-2.0" ]

null

PyBank/main.py

MAICATRAN/python-challenge

748ea0b3c480740a19a3710725899d62e01bdcdc

[ "Apache-2.0" ]

null

PyBank/main.py

MAICATRAN/python-challenge

748ea0b3c480740a19a3710725899d62e01bdcdc

[ "Apache-2.0" ]

null

<<<<<<< HEAD import os import csv budget_data_csv = os.path.join("C:\MAICA\MONASH\Python\python-challenge\PyBank\Resources", "budget_data.csv") months = [] profit_loss = [] count_month = 0 current_month = 0 net_change = 0 prev_month = 0 profit_loss_change = 0 with open(budget_data_csv) as csvfile: csv_header = next(csvfile) csvreader = csv.reader(csvfile, delimiter=",") for row in csvreader: count_month = count_month + 1 current_month = int(row[1]) net_change += current_month if (count_month) == 1: prev_month = current_month else: profit_loss_change = current_month - prev_month months.append(row[0]) profit_loss.append(profit_loss_change) prev_month = current_month Total_profit_loss = sum(profit_loss) Average_profit_loss = round(Total_profit_loss/(count_month -1),2) max_value = max(profit_loss) min_value = min(profit_loss) highest_month_index = profit_loss.index(max_value) lowest_month_index = profit_loss.index(min_value) greatest_month = months[highest_month_index] lowest_month = months[lowest_month_index] print("Financial Analysis") print("-------------------------------") print(f"Total Months: {count_month}") print(f"Total: ${net_change}") print(f"Average Change: ${Average_profit_loss}") print(f"Greatest Increase in Profits: {greatest_month} (${max_value})") print(f"Greatest Decrease in Profits: {lowest_month} (${min_value})") budget_file = os.path.join("C:\\MAICA\\MONASH\\Python\\python-challenge\\PyBank\\analysis", "budget_data.text") with open(budget_file, "w") as outfile: outfile.write("Financial Analysis") outfile.write("-------------------------------\n") outfile.write(f"Total Months: {count_month}\n") outfile.write(f"Total: ${net_change}\n") outfile.write(f"Average Change: ${Average_profit_loss}\n") outfile.write(f"Greatest Increase in Profits: {greatest_month} (${max_value})\n") outfile.write(f"Greatest Decrease in Profits: {lowest_month} (${min_value})\n") ======= import os import csv budget_data_csv = os.path.join("C:\MAICA\MONASH\Python\python-challenge\PyBank\Resources", "budget_data.csv") months = [] profit_loss = [] count_month = 0 current_month = 0 net_change = 0 prev_month = 0 profit_loss_change = 0 with open(budget_data_csv) as csvfile: csv_header = next(csvfile) csvreader = csv.reader(csvfile, delimiter=",") for row in csvreader: count_month = count_month + 1 current_month = int(row[1]) net_change += current_month if (count_month) == 1: prev_month = current_month else: profit_loss_change = current_month - prev_month months.append(row[0]) profit_loss.append(profit_loss_change) prev_month = current_month Total_profit_loss = sum(profit_loss) Average_profit_loss = round(Total_profit_loss/(count_month -1),2) max_value = max(profit_loss) min_value = min(profit_loss) highest_month_index = profit_loss.index(max_value) lowest_month_index = profit_loss.index(min_value) greatest_month = months[highest_month_index] lowest_month = months[lowest_month_index] print("Financial Analysis") print("-------------------------------") print(f"Total Months: {count_month}") print(f"Total: ${net_change}") print(f"Average Change: ${Average_profit_loss}") print(f"Greatest Increase in Profits: {greatest_month} (${max_value})") print(f"Greatest Decrease in Profits: {lowest_month} (${min_value})") budget_file = os.path.join("C:\\MAICA\\MONASH\\Python\\python-challenge\\PyBank\\analysis", "budget_data.text") with open(budget_file, "w") as outfile: outfile.write("Financial Analysis") outfile.write("-------------------------------\n") outfile.write(f"Total Months: {count_month}\n") outfile.write(f"Total: ${net_change}\n") outfile.write(f"Average Change: ${Average_profit_loss}\n") outfile.write(f"Greatest Increase in Profits: {greatest_month} (${max_value})\n") outfile.write(f"Greatest Decrease in Profits: {lowest_month} (${min_value})\n") >>>>>>> 16cefa0361fdc1efdbbfa4c4a19743b570eb55b1

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null

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8

d73ede2a11fa2331c72622e69edfd2b34e0df5f7

59,243

py

Python

pyordle_single_file.py

cmglee/pyordle

cee4dc600866faab9ff03245a25901cdd105cf08

[ "MIT" ]

2

2022-02-27T12:57:50.000Z

2022-03-01T19:08:18.000Z

pyordle_single_file.py

cmglee/pyordle

cee4dc600866faab9ff03245a25901cdd105cf08

[ "MIT" ]

null

pyordle_single_file.py

cmglee/pyordle

cee4dc600866faab9ff03245a25901cdd105cf08

[ "MIT" ]

null

""" Python 3 implementation of a popular 2022 word game by CMG Lee licensed under CC-BY-SA 4.0 Usage: python3 pyordle.py [GAME_MODE] [0 for no GUI or 1 to use tkinter] [ANSWER for testing] where GAME_MODE is one of game: Player guesses a word computer picks hint: Player guesses a word computer picks (possible words shown) solver: Computer solves a word player or http://hellowordl.net picks demo: Computer plays against itself TODO: Reimplement as a class TODO: Improve error-handling """ import sys, time, random DEFAULT_ANSWER = None DEFAULT_GAME_MODE = 'game' FIRST_GUESS = 'RAISE' LABEL_PX = 70 COLOUR_BG = 'white' COLOUR_MARK_L = ['white', 'grey', 'yellow', 'lime'] FREQUENCY_TIEBREAK_D = {letter:i_letter * 0.01 for (i_letter, letter) in enumerate('EARIOTNSLCUDPMHGBFYWKVXZJQ'[::-1])} FORMAT_KEYBOARD_MARK_L = [' {} ', ' ' , '<{}>', '[{}]'] ## 0=white, 1=grey, 2=amber, 3=green FORMAT_GUESS_MARK_L = [' {} ', ' {} ', '<{}>', '[{}]'] N_LETTER = 5 FILE_ANSWER = 'pyordle_answers.txt' FILE_VALID = 'pyordle_valid.txt' KEYBOARD = ''' Q W E R T Y U I O P A S D F G H J K L Z X C V B N M''' PRAISE_L = ['Genius', 'Magnificent', 'Impressive', 'Splendid', 'Great', 'Phew'] n_guess = len(PRAISE_L) ## Remove possible words not matching evaluation def trim_possible(possible_s, guess, guess_mark_l): for word in possible_s.copy(): if evaluate_guess(guess, word) != guess_mark_l: possible_s.remove(word) ## Choose next guess ## TODO: Implement a better algorithm using word commonness def choose_guess(possible_s): n_possible = len(possible_s) ## Rank letters by descending frequency in possible_s frequency_d = {} for word in possible_s: for letter in word: if letter not in frequency_d: frequency_d[letter] = 0 frequency_d[letter] += 1 # print(sorted(frequency_d.items(), key=lambda x:x[1])[:9]) ## Assign scores to words in possible_s score_d = {} for word in possible_s: score_d[word] = sum([frequency_d[letter] + FREQUENCY_TIEBREAK_D[letter] for letter in word]) / (N_LETTER - len(set(word)) + 2) sorted_score_l = sorted(list(score_d), key=lambda word:score_d[word], reverse=True) print(', '.join(['{}:{:.2f}'.format(word, score_d[word]) for word in sorted_score_l][:5])) if is_gui: label_title.configure(text=','.join(['{}'.format(word) for word in sorted_score_l][:5])) return sorted_score_l[0] ## Input guess for computer's word def input_guess(i_guess, n_guess, valid_s): global gui_input ## must set as global as value will be changed gui_input = '' prompt_guess = 'Enter guess {} out of {}: '.format(i_guess, n_guess) if game_mode == 'GAME' or i_guess == 1: display_message(prompt_guess, False) while True: if is_gui: window.mainloop() guess = gui_input else: guess = raw_input('\n{}'.format(prompt_guess)).strip().upper() if guess in valid_s: break display_message('"{}" is not in the word list.'.format(guess)) if i_guess == 1: print('\n[ ] = letter exactly right, < > = letter in wrong position') return guess ## Input results for computer's guess def input_evaluation(guess): prompt_mark = ''' Play {} and then enter the result as 5 digits, such as 12231 where 1=totally wrong, 2=wrong position, 3=exactly right: '''.format(guess) return [int(mark) for mark in raw_input(prompt_mark).strip()] ## Evaluate result for a given answer def evaluate_guess(guess, answer): guess_mark_l = [1] * N_LETTER for (i_letter_answer, letter_answer) in enumerate(answer): ## Mark greens if guess[i_letter_answer] == letter_answer: guess_mark_l[i_letter_answer] = 3 else: ## Mark ambers and greys for (i_letter_guess, letter_guess) in enumerate(guess): if letter_guess == letter_answer and guess_mark_l[i_letter_guess] < 2: guess_mark_l[i_letter_guess] = 2 break return guess_mark_l ## Animate letter def animate_letter(label, i_fraction): label.configure(width=LABEL_PX * i_fraction // 5) label.update() time.sleep(0.03) ## Output result def display_result(guess, i_guess, guess_mark_l, keyboard_mark_d): ## Update keyboard for (i_letter_guess, letter_guess) in enumerate(guess): if keyboard_mark_d[letter_guess] < guess_mark_l[i_letter_guess]: keyboard_mark_d[letter_guess] = guess_mark_l[i_letter_guess] ## Print evaluation output = '\n' for (i_letter, letter) in enumerate(guess): output += ' ' + FORMAT_GUESS_MARK_L[guess_mark_l[i_letter]].format(letter) print(output) ## Print keyboard output = KEYBOARD for letter in keyboard_mark_d: output = output.replace(letter, FORMAT_KEYBOARD_MARK_L[keyboard_mark_d[letter]].format(letter)) print(output) if is_gui: for (i_letter, letter) in enumerate(guess): label = label_ll[i_guess][i_letter] for i_frame in range(5): animate_letter(label, 4.5 - i_frame) label.configure(bg=COLOUR_MARK_L[guess_mark_l[i_letter]]) for i_frame in range(5): animate_letter(label, 1 + i_frame) button_d[letter].configure(bg=COLOUR_MARK_L[keyboard_mark_d[letter]]) ## Output message def display_message(message, is_print=True): if is_print: print('\n{}'.format(message)) if is_gui: for length in range(len(message)): label_title.configure(text=message[:length + 1]) label_title.update() time.sleep(0.01) ## Make compatible with both Python 2 and 3 try: raw_input except NameError: raw_input = input ## Set game mode (GAME by default) game_mode = (sys.argv[1] if len(sys.argv) > 1 else DEFAULT_GAME_MODE).upper() print('PYORDLE IN {} MODE'.format(game_mode)) ## TODO: Make GUI for solver mode is_gui = game_mode != 'SOLVER' and (len(sys.argv) <= 2 or sys.argv[2] == '1') ## Set up GUI if needed ## TODO: Run all program logic in mainloop instead of starting and stopping it ## TODO: Make window resizable if is_gui: try: import tkinter as tk, tkinter.font as tkFont except ImportError: is_gui = False if is_gui: window = tk.Tk(className='Pyordle') window.configure(bg=COLOUR_BG) window.resizable(False, False) window.bind_all('<Key>', lambda event:input_key(event.char)) window.bind_all('<Control-c>', exit) tkFont.nametofont('TkDefaultFont').configure(family='Courier', size=18) frame_header = tk.Frame(master=window, bg=COLOUR_BG) frame_guess = tk.Frame(master=window, bg=COLOUR_BG) frame_footer = tk.Frame(master=window, bg=COLOUR_BG, padx=20, pady=4) frame_header.pack() frame_guess .pack() frame_footer.pack() label_title = tk.Label(master=frame_header, font=('sans-serif', 10), bg=COLOUR_BG) label_title.pack() ## Draw guesses image_dummy = tk.PhotoImage() label_ll = [None] for i_guess in range(n_guess): label_l = [] for i_letter in range(N_LETTER): label = tk.Label(master=frame_guess, width=LABEL_PX, height=LABEL_PX, relief='groove', image=image_dummy, compound=tk.CENTER, bg=COLOUR_BG, text=' ') label.grid(row=i_guess, column=i_letter, padx=2, pady=4) label_l.append(label) label_ll.append(label_l) ## Draw keyboard button_d = {} button_label_d = {'ENTER':'\u21B5', 'BACKSPACE': '\u232B'} for (i_row, row) in enumerate(KEYBOARD.strip().split('\n')): i_column = i_row % 2 if i_row == 2: row = 'ENTER {} BACKSPACE'.format(row) for (i_key, key) in enumerate(row.split()): columnspan = 3 if key in button_label_d else 2 width = 2 if key in button_label_d else 1 button_d[key] = tk.Button(master=frame_footer, width=width, height=1, padx=1, pady=1, relief='raised', bg=COLOUR_BG, text=button_label_d.get(key, key), command=lambda key=key:input_key(key)) ## see Python closure button_d[key].grid(row=i_row, column=i_column, columnspan=columnspan, padx=2, pady=2) i_column += columnspan gui_input = '' ## input from GUI def input_key(key): ## callback on keypress or click on GUI global gui_input ## must set as global as value will be changed key = key.upper() if key == '\x1b': ## Escape exit() elif key == '\x08' or key == 'BACKSPACE': if len(gui_input) > 0: gui_input = gui_input[:-1] label_ll[i_guess][len(gui_input)].configure(text=' ') ## label shrinks if text='' elif key == '\x0d' or key == 'ENTER': window.quit() elif key >= 'A' and key <= 'Z' and len(gui_input) < N_LETTER: label_ll[i_guess][len(gui_input)].configure(text=key) gui_input += key ## Read words import base64, bz2 answer_s = set([line.strip().upper() for line in bz2.decompress(base64.b64decode('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')).decode('utf-8').strip().split('\n')]) # print(len(answer_s), list(answer_s)[0]) valid_s = set([line.strip().upper() for line in bz2.decompress(base64.b64decode('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')).decode('utf-8').strip().split('\n')]).union(answer_s) # print(len(valid_s), list(valid_s)[0]) ## Set puzzle if game_mode != 'SOLVER': answer = DEFAULT_ANSWER or random.choice(list(answer_s)) if len(sys.argv) > 3: answer = sys.argv[3] answer = answer.upper() i_guess = 0 keyboard_mark_d = {letter:0 for letter in KEYBOARD if 'A' <= letter <= 'Z'} status = 0 ## 0=answer not found, 1=answer found, 2=results do not match possible answers while i_guess < n_guess: i_guess += 1 ## Get guess if game_mode != 'GAME': if i_guess == 1: guess = FIRST_GUESS possible_s = valid_s.copy() ## set of words matching results so far else: trim_possible(possible_s, guess, guess_mark_l) n_possible = len(possible_s) print('\nPossible words left: {}'.format(n_possible)) if n_possible < 1: status = 2 break guess = choose_guess(possible_s) if game_mode in ['GAME', 'HINT']: guess = input_guess(i_guess, n_guess, valid_s) ## Evaluate guess if game_mode == 'SOLVER': guess_mark_l = input_evaluation(guess) else: guess_mark_l = evaluate_guess(guess, answer) display_result(guess, i_guess, guess_mark_l, keyboard_mark_d) if guess_mark_l == [3] * N_LETTER: status = 1 break if status == 0: display_message('Sorry, the answer is {}.'.format(answer)) elif status == 1: display_message('{}, got {} in {}!'.format(PRAISE_L[i_guess - 1], guess, i_guess)) else: display_message('No words fit the results above.') ## Wait until Esc is pressed or window is closed ## TODO: Disable backspace and letter keys if is_gui: window.mainloop()

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d755e8829d171553e384347599ac1f24c5638345

153

py

Python

models/__init__.py

cadkins052/tab-vcr

ea713a6ef7ca54eb3123d8729dfc26dc604644c5

[ "MIT" ]

17

2019-11-01T04:57:40.000Z

2021-04-17T14:49:47.000Z

models/__init__.py

cadkins052/tab-vcr

ea713a6ef7ca54eb3123d8729dfc26dc604644c5

[ "MIT" ]

8

2019-11-05T10:18:12.000Z

2021-12-22T01:59:28.000Z

models/__init__.py

cadkins052/tab-vcr

ea713a6ef7ca54eb3123d8729dfc26dc604644c5

[ "MIT" ]

8

2019-10-28T17:54:54.000Z

2021-12-08T02:21:00.000Z

from models import * from models.base_res101_attribute import model # You can add more models in this folder. like # from models.base import modelbase

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0.666667

0.25

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0.914063

0.509804

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1

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1

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7

d116d9a532930d68aa02b348ff24612cec66158c

368

py

Python

deegan_client/test.py

tadeegan/eiger-application-aware

0c1faf6ed2de35d6913dfce7cb1badcc555cbef8

[ "Apache-2.0" ]

3

2015-03-05T05:31:19.000Z

2015-08-19T10:02:42.000Z

deegan_client/test.py

tadeegan/eiger

0c1faf6ed2de35d6913dfce7cb1badcc555cbef8

[ "Apache-2.0" ]

null

deegan_client/test.py

tadeegan/eiger

0c1faf6ed2de35d6913dfce7cb1badcc555cbef8

[ "Apache-2.0" ]

null

import os os.system("sshpass -p Bs81tu93 ssh eiger@104.236.140.240 'cd eiger; bash deegan_burn_it_all.bash; bash deegan_datacenter_launcher.bash'") # 'source ~/.bashrc; echo $local_token; cd eiger; source ~/.bashrc; echo $CASSANDRA_HOME; bash deegan_burn_it_all.bash; export max_mutation_delay_ms=200; ./deegan_datacenter_launcher.bash'") #os.system("echo $PATH")

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368

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6

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7

d12b8e20d08f12a640eefc2ff01d3b29772e84b9

2,129

py

Python

scripts/pleftmatrix_gen.py

boviex/GBA-FlightSim

d16bf876dbe38b437f8d041ffb435cb6aa06a112

[ "MIT" ]

7

2021-11-02T16:59:53.000Z

2021-12-25T20:14:39.000Z

scripts/pleftmatrix_gen.py

boviex/GBA-FlightSim

d16bf876dbe38b437f8d041ffb435cb6aa06a112

[ "MIT" ]

null

scripts/pleftmatrix_gen.py

boviex/GBA-FlightSim

d16bf876dbe38b437f8d041ffb435cb6aa06a112

[ "MIT" ]

null

# Pointer Finder finds pointers # Given Rom, Pointer, New Pointer # prints event format to stdout import struct def to_bytes(val): #pack into little endian, signed halfwords return struct.pack('<h', val) def main(): with open('pleftmatrix.dmp', 'wb') as out: # angle 0 for zdist in range(256): bytevalue = to_bytes(- (zdist - (zdist>>2) - (zdist>>5))) out.write(bytevalue) #angle 1 for zdist in range(256): bytevalue = to_bytes(- ((zdist>>1) - (zdist>>3))) out.write(bytevalue) # angle 2 for zdist in range(256): bytevalue = to_bytes(0) out.write(bytevalue) #angle 3 for zdist in range(256): bytevalue = to_bytes((zdist>>1) - (zdist>>3)) out.write(bytevalue) # angle 4 for zdist in range(256): bytevalue = to_bytes((zdist - (zdist>>2) - (zdist>>5))) out.write(bytevalue) #angle 5 for zdist in range(256): bytevalue = to_bytes(zdist - (zdist>>4) - (zdist>>6)) out.write(bytevalue) # angle 6 for zdist in range(256): bytevalue = to_bytes(zdist) out.write(bytevalue) #angle 7 for zdist in range(256): bytevalue = to_bytes((zdist - (zdist>>4) - (zdist>>6))) out.write(bytevalue) # angle 8 for zdist in range(256): bytevalue = to_bytes((zdist - (zdist>>2) - (zdist>>5))) out.write(bytevalue) #angle 9 for zdist in range(256): bytevalue = to_bytes(((zdist>>1) - (zdist>>3))) out.write(bytevalue) # angle 10 for zdist in range(256): bytevalue = to_bytes(0) out.write(bytevalue) #angle 11 for zdist in range(256): bytevalue = to_bytes(- ((zdist>>1) - (zdist>>3))) out.write(bytevalue) # angle 12 for zdist in range(256): bytevalue = to_bytes(- (zdist - (zdist>>2) - (zdist>>5))) out.write(bytevalue) #angle 13 for zdist in range(256): bytevalue = to_bytes(- (zdist - (zdist>>4) - (zdist>>6))) out.write(bytevalue) # angle 14 for zdist in range(256): bytevalue = to_bytes(-zdist) out.write(bytevalue) #angle 15 for zdist in range(256): bytevalue = to_bytes(- (zdist - (zdist>>4) - (zdist>>6))) out.write(bytevalue) print("done!") if __name__ == '__main__': main()

25.650602

60

0.635979

314

2,129

4.232484

0.194268

0.089541

0.120391

0.180587

0.817908

0

0.056537

0.202442

2,129

83

61

25.650602

0.726148

0.121184

0

0.75

0

0.017288

0

1

0.035714

false

0

0.017857

0.071429

0.017857

0

null

0

1

0

1

0

null

0

8

d13f158cbc74c2307f3a4cc54a62bc7bcad704fe

7,585

py

Python

runtime/bamboo-pipeline/test/eri_imp_test_use/tests/control/test_pause_and_resume_pipeline.py

wheel-w/bamboo-engine

482e89c039100142e3b400e6ac0c54df031b8156

[ "MIT" ]

55

2021-09-07T11:50:35.000Z

2022-03-23T13:19:38.000Z

runtime/bamboo-pipeline/test/eri_imp_test_use/tests/control/test_pause_and_resume_pipeline.py

wheel-w/bamboo-engine

482e89c039100142e3b400e6ac0c54df031b8156

[ "MIT" ]

64

2021-09-07T12:04:12.000Z

2022-03-29T03:47:18.000Z

runtime/bamboo-pipeline/test/eri_imp_test_use/tests/control/test_pause_and_resume_pipeline.py

wheel-w/bamboo-engine

482e89c039100142e3b400e6ac0c54df031b8156

[ "MIT" ]

20

2021-09-07T11:52:08.000Z

2022-03-28T08:05:22.000Z

# -*- coding: utf-8 -*- from bamboo_engine.builder import * # noqa from bamboo_engine.engine import Engine from pipeline.eri.runtime import BambooDjangoRuntime from ..utils import * # noqa def test_pause_and_resume_pipeline_with_nest_parallel(): parallel_count = 5 start = EmptyStartEvent() pg_1 = ParallelGateway() pg_2 = ParallelGateway() sleep_group_1 = [] for _ in range(parallel_count): act = ServiceActivity(component_code="sleep_timer") act.component.inputs.bk_timing = Var(type=Var.PLAIN, value=3) sleep_group_1.append(act) sleep_group_2 = [] for _ in range(parallel_count): act = ServiceActivity(component_code="sleep_timer") act.component.inputs.bk_timing = Var(type=Var.PLAIN, value=3) sleep_group_2.append(act) acts_group_1 = [ServiceActivity(component_code="debug_node") for _ in range(parallel_count)] acts_group_2 = [ServiceActivity(component_code="debug_node") for _ in range(parallel_count)] cg_1 = ConvergeGateway() cg_2 = ConvergeGateway() end = EmptyEndEvent() for i in range(parallel_count): sleep_group_1[i].connect(acts_group_1[i]) sleep_group_2[i].connect(acts_group_2[i]) start.extend(pg_1).connect(pg_2, *sleep_group_1).to(pg_2).connect(*sleep_group_2).converge(cg_1).to(pg_1).converge( cg_2 ).extend(end) pipeline = build_tree(start) runtime = BambooDjangoRuntime() engine = Engine(runtime) engine.run_pipeline(pipeline=pipeline, root_pipeline_data={}) sleep(2) engine.pause_pipeline(pipeline["id"]) finished = [start.id, pg_1.id, pg_2.id] finished.extend([a.id for a in sleep_group_1]) finished.extend([a.id for a in sleep_group_2]) sleep(6) state = runtime.get_state(pipeline["id"]) assert state.name == states.SUSPENDED assert_all_finish(finished) not_execute = [cg_1.id, cg_2.id, end.id] not_execute.extend([a.id for a in acts_group_1]) not_execute.extend([a.id for a in acts_group_2]) assert_not_executed(not_execute) engine.resume_pipeline(pipeline["id"]) sleep(2) finished.extend(not_execute) finished.append(pipeline["id"]) assert_all_finish(finished) def test_pause_and_resume_pipeline_with_nest_parallel_early_resume(): parallel_count = 5 start = EmptyStartEvent() pg_1 = ParallelGateway() pg_2 = ParallelGateway() sleep_group_1 = [] for _ in range(parallel_count): act = ServiceActivity(component_code="sleep_timer") act.component.inputs.bk_timing = Var(type=Var.PLAIN, value=5) sleep_group_1.append(act) sleep_group_2 = [] for _ in range(parallel_count): act = ServiceActivity(component_code="sleep_timer") act.component.inputs.bk_timing = Var(type=Var.PLAIN, value=5) sleep_group_2.append(act) acts_group_1 = [ServiceActivity(component_code="debug_node") for _ in range(parallel_count)] acts_group_2 = [ServiceActivity(component_code="debug_node") for _ in range(parallel_count)] cg_1 = ConvergeGateway() cg_2 = ConvergeGateway() end = EmptyEndEvent() for i in range(parallel_count): sleep_group_1[i].connect(acts_group_1[i]) sleep_group_2[i].connect(acts_group_2[i]) start.extend(pg_1).connect(pg_2, *sleep_group_1).to(pg_2).connect(*sleep_group_2).converge(cg_1).to(pg_1).converge( cg_2 ).extend(end) pipeline = build_tree(start) runtime = BambooDjangoRuntime() engine = Engine(runtime) engine.run_pipeline(pipeline=pipeline, root_pipeline_data={}) sleep(2) engine.pause_pipeline(pipeline["id"]) state = runtime.get_state(pipeline["id"]) assert state.name == states.SUSPENDED engine.resume_pipeline(pipeline["id"]) finished = [start.id, pg_1.id, pg_2.id] finished.extend([a.id for a in sleep_group_1]) finished.extend([a.id for a in sleep_group_2]) finished.extend([cg_1.id, cg_2.id, end.id]) finished.extend([a.id for a in acts_group_1]) finished.extend([a.id for a in acts_group_2]) finished.append(pipeline["id"]) sleep(10) assert_all_finish(finished) def test_pause_and_resume_pipeline_with_subprocess(): subproc_start = EmptyStartEvent() subproc_act = ServiceActivity(component_code="sleep_timer") subproc_act.component.inputs.bk_timing = Var(type=Var.PLAIN, value=3) subproc_end = EmptyEndEvent() subproc_start.extend(subproc_act).extend(subproc_end) start = EmptyStartEvent() subproc = SubProcess(start=subproc_start) end = EmptyEndEvent() start.extend(subproc).extend(end) pipeline = build_tree(start) runtime = BambooDjangoRuntime() engine = Engine(runtime) engine.run_pipeline(pipeline=pipeline, root_pipeline_data={}) sleep(2) engine.pause_pipeline(pipeline["id"]) sleep(6) assert_all_finish([start.id, subproc_start.id, subproc_act.id]) state = runtime.get_state(pipeline["id"]) assert state.name == states.SUSPENDED assert_not_executed([subproc_end.id, end.id]) assert_all_running([subproc.id]) engine.resume_pipeline(pipeline["id"]) sleep(2) assert_all_finish([pipeline["id"], start.id, subproc.id, end.id, subproc_start.id, subproc_act.id, subproc_end.id]) def test_pause_and_resume_pipeline_with_subprocess_has_parallel(): parallel_count = 5 start = EmptyStartEvent() pg_1 = ParallelGateway() pg_2 = ParallelGateway() sleep_group_1 = [] for _ in range(parallel_count): act = ServiceActivity(component_code="sleep_timer") act.component.inputs.bk_timing = Var(type=Var.PLAIN, value=3) sleep_group_1.append(act) sleep_group_2 = [] for _ in range(parallel_count): act = ServiceActivity(component_code="sleep_timer") act.component.inputs.bk_timing = Var(type=Var.PLAIN, value=3) sleep_group_2.append(act) acts_group_1 = [ServiceActivity(component_code="debug_node") for _ in range(parallel_count)] acts_group_2 = [ServiceActivity(component_code="debug_node") for _ in range(parallel_count)] cg_1 = ConvergeGateway() cg_2 = ConvergeGateway() end = EmptyEndEvent() for i in range(parallel_count): sleep_group_1[i].connect(acts_group_1[i]) sleep_group_2[i].connect(acts_group_2[i]) start.extend(pg_1).connect(pg_2, *sleep_group_1).to(pg_2).connect(*sleep_group_2).converge(cg_1).to(pg_1).converge( cg_2 ).extend(end) parent_start = EmptyStartEvent() subproc = SubProcess(start=start) parent_end = EmptyEndEvent() parent_start.extend(subproc).extend(parent_end) pipeline = build_tree(parent_start) runtime = BambooDjangoRuntime() engine = Engine(runtime) engine.run_pipeline(pipeline=pipeline, root_pipeline_data={}) sleep(2) engine.pause_pipeline(pipeline["id"]) sleep(10) finished = [parent_start.id, start.id, pg_1.id, pg_2.id] finished.extend([a.id for a in sleep_group_1]) finished.extend([a.id for a in sleep_group_2]) state = runtime.get_state(pipeline["id"]) assert state.name == states.SUSPENDED assert_all_finish(finished) assert_all_running([subproc.id]) not_execute = [cg_1.id, cg_2.id, end.id, parent_end.id] not_execute.extend([a.id for a in acts_group_1]) not_execute.extend([a.id for a in acts_group_2]) assert_not_executed(not_execute) engine.resume_pipeline(pipeline["id"]) sleep(2) finished.extend(not_execute) finished.append(pipeline["id"]) assert_all_finish(finished)

30.584677

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0.827332

0.813805

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0

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null

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1

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1

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null

0

7

d1734dc4e60e18781b20c52c259f749eeadb5f14

105

py

Python

Utils/Pruebas-Pytorch/pytorch_utils/__init__.py

LautaroEst/cs231n-Computer-Vision

f353a3d376d452dd1f9ef8979ddc96de91a45605

[ "MIT" ]

null

Utils/Pruebas-Pytorch/pytorch_utils/__init__.py

LautaroEst/cs231n-Computer-Vision

f353a3d376d452dd1f9ef8979ddc96de91a45605

[ "MIT" ]

null

Utils/Pruebas-Pytorch/pytorch_utils/__init__.py

LautaroEst/cs231n-Computer-Vision

f353a3d376d452dd1f9ef8979ddc96de91a45605

[ "MIT" ]

null

from pytorch_utils.Datasets import * from pytorch_utils.utils import * from pytorch_utils.Models import *

35

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8

66f82528fdff5e646cf424e9f8f67fda8a16c534

176,876

py

Python

fairdiplomacy/models/consts.py

RomanGaraev/diplomacy_searchbot

bf3f38e5a68bfd3c6fa58e47351fcae3eed88557

[ "MIT" ]

32

2021-05-04T17:05:19.000Z

2022-03-21T07:56:53.000Z

fairdiplomacy/models/consts.py

RomanGaraev/diplomacy_searchbot

bf3f38e5a68bfd3c6fa58e47351fcae3eed88557

[ "MIT" ]

3

2022-01-22T19:44:10.000Z

2022-03-02T23:20:52.000Z

fairdiplomacy/models/consts.py

facebookresearch/diplomacy_searchbot

44d6f3272be7567060ba7d0e41f4e44b1bb8b5ca

[ "MIT" ]

10

2021-05-07T11:51:29.000Z

2022-02-18T18:29:57.000Z

# Copyright (c) Facebook, Inc. and its affiliates. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. from typing import List import numpy as np from .preprocess_adjacency import preprocess_adjacency LOCS = [ "YOR", "EDI", "LON", "LVP", "NTH", "WAL", "CLY", "NWG", "ENG", "IRI", "NAO", "BEL", "DEN", "HEL", "HOL", "NWY", "SKA", "BAR", "BRE", "MAO", "PIC", "BUR", "RUH", "BAL", "KIE", "SWE", "FIN", "STP", "STP/NC", "GAS", "PAR", "NAF", "POR", "SPA", "SPA/NC", "SPA/SC", "WES", "MAR", "MUN", "BER", "BOT", "LVN", "PRU", "STP/SC", "MOS", "TUN", "LYO", "TYS", "PIE", "BOH", "SIL", "TYR", "WAR", "SEV", "UKR", "ION", "TUS", "NAP", "ROM", "VEN", "GAL", "VIE", "TRI", "ARM", "BLA", "RUM", "ADR", "AEG", "ALB", "APU", "EAS", "GRE", "BUD", "SER", "ANK", "SMY", "SYR", "BUL", "BUL/EC", "CON", "BUL/SC", ] LOC_TYPES = { "ADR": "WATER", "AEG": "WATER", "ALB": "COAST", "ANK": "COAST", "APU": "COAST", "ARM": "COAST", "BAL": "WATER", "BAR": "WATER", "BEL": "COAST", "BER": "COAST", "BLA": "WATER", "BOH": "LAND", "BOT": "WATER", "BRE": "COAST", "BUD": "LAND", "BUL/EC": "COAST", "BUL/SC": "COAST", "BUL": "COAST", "BUR": "LAND", "CLY": "COAST", "CON": "COAST", "DEN": "COAST", "EAS": "WATER", "EDI": "COAST", "ENG": "WATER", "FIN": "COAST", "GAL": "LAND", "GAS": "COAST", "GRE": "COAST", "HEL": "WATER", "HOL": "COAST", "ION": "WATER", "IRI": "WATER", "KIE": "COAST", "LON": "COAST", "LVN": "COAST", "LVP": "COAST", "LYO": "WATER", "MAO": "WATER", "MAR": "COAST", "MOS": "LAND", "MUN": "LAND", "NAF": "COAST", "NAO": "WATER", "NAP": "COAST", "NWY": "COAST", "NTH": "WATER", "NWG": "WATER", "PAR": "LAND", "PIC": "COAST", "PIE": "COAST", "POR": "COAST", "PRU": "COAST", "ROM": "COAST", "RUH": "LAND", "RUM": "COAST", "SER": "LAND", "SEV": "COAST", "SIL": "LAND", "SKA": "WATER", "SMY": "COAST", "SPA/NC": "COAST", "SPA/SC": "COAST", "SPA": "COAST", "STP/NC": "COAST", "STP/SC": "COAST", "STP": "COAST", "SWE": "COAST", "SYR": "COAST", "TRI": "COAST", "TUN": "COAST", "TUS": "COAST", "TYR": "LAND", "TYS": "WATER", "UKR": "LAND", "VEN": "COAST", "VIE": "LAND", "WAL": "COAST", "WAR": "LAND", "WES": "WATER", "YOR": "COAST", "SWI": "SHUT", } POWERS = ["AUSTRIA", "ENGLAND", "FRANCE", "GERMANY", "ITALY", "RUSSIA", "TURKEY"] POWER2IDX = {v: k for k, v in enumerate(POWERS)} SEASONS = ["SPRING", "FALL", "WINTER"] MAX_SEQ_LEN = 17 # can't have 18 orders in one phase or you've already won N_SCS = 34 # number of supply centers RAW_ADJACENCY_MATRIX = [ [ 0, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ], [ 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ], [ 1, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ], [ 1, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ], [ 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ], [ 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ], 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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, ], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 0, 1, 1, 0, 1, ], [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 0, ], ] ADJACENCY_MATRIX = preprocess_adjacency(np.array(RAW_ADJACENCY_MATRIX)) MASTER_ALIGNMENTS = np.array( [ [ 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ], [ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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12.949411

81

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13,513

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1.66227

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3.140299

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55,780

py

Python

influxdb_client/service/checks_service.py

bonitoo-io/influxdb-client-python

465476b33648ba399a8f3e13d8780f7b3fe51950

[ "MIT" ]

1

2019-09-06T10:06:09.000Z

influxdb_client/service/checks_service.py

bonitoo-io/influxdb-client-python

465476b33648ba399a8f3e13d8780f7b3fe51950

[ "MIT" ]

5

2019-08-06T04:58:58.000Z

2019-09-05T09:09:40.000Z

influxdb_client/service/checks_service.py

bonitoo-io/influxdb-client-python

465476b33648ba399a8f3e13d8780f7b3fe51950

[ "MIT" ]

1

2019-08-05T05:46:55.000Z

# coding: utf-8 """ InfluxDB OSS API Service. The InfluxDB v2 API provides a programmatic interface for all interactions with InfluxDB. Access the InfluxDB API using the `/api/v2/` endpoint. # noqa: E501 OpenAPI spec version: 2.0.0 Generated by: https://openapi-generator.tech """ from __future__ import absolute_import import re # noqa: F401 from influxdb_client.service._base_service import _BaseService class ChecksService(_BaseService): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. """ def __init__(self, api_client=None): # noqa: E501,D401,D403 """ChecksService - a operation defined in OpenAPI.""" if api_client is None: raise ValueError("Invalid value for `api_client`, must be defined.") self.api_client = api_client def create_check(self, post_check, **kwargs): # noqa: E501,D401,D403 """Add new check. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_check(post_check, async_req=True) >>> result = thread.get() :param async_req bool :param PostCheck post_check: Check to create (required) :return: Check If the method is called asynchronously, returns the request thread. """ # noqa: E501 kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.create_check_with_http_info(post_check, **kwargs) # noqa: E501 else: (data) = self.create_check_with_http_info(post_check, **kwargs) # noqa: E501 return data def create_check_with_http_info(self, post_check, **kwargs): # noqa: E501,D401,D403 """Add new check. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.create_check_with_http_info(post_check, async_req=True) >>> result = thread.get() :param async_req bool :param PostCheck post_check: Check to create (required) :return: Check If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._create_check_prepare(post_check, **kwargs) return self.api_client.call_api( '/api/v2/checks', 'POST', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type='Check', # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) async def create_check_async(self, post_check, **kwargs): # noqa: E501,D401,D403 """Add new check. This method makes an asynchronous HTTP request. :param async_req bool :param PostCheck post_check: Check to create (required) :return: Check If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._create_check_prepare(post_check, **kwargs) return await self.api_client.call_api( '/api/v2/checks', 'POST', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type='Check', # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) def _create_check_prepare(self, post_check, **kwargs): # noqa: E501,D401,D403 local_var_params = locals() all_params = ['post_check'] # noqa: E501 self._check_operation_params('create_check', all_params, local_var_params) # verify the required parameter 'post_check' is set if ('post_check' not in local_var_params or local_var_params['post_check'] is None): raise ValueError("Missing the required parameter `post_check` when calling `create_check`") # noqa: E501 path_params = {} query_params = [] header_params = {} body_params = None if 'post_check' in local_var_params: body_params = local_var_params['post_check'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 return local_var_params, path_params, query_params, header_params, body_params def delete_checks_id(self, check_id, **kwargs): # noqa: E501,D401,D403 """Delete a check. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_checks_id(check_id, async_req=True) >>> result = thread.get() :param async_req bool :param str check_id: The check ID. (required) :param str zap_trace_span: OpenTracing span context :return: None If the method is called asynchronously, returns the request thread. """ # noqa: E501 kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.delete_checks_id_with_http_info(check_id, **kwargs) # noqa: E501 else: (data) = self.delete_checks_id_with_http_info(check_id, **kwargs) # noqa: E501 return data def delete_checks_id_with_http_info(self, check_id, **kwargs): # noqa: E501,D401,D403 """Delete a check. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_checks_id_with_http_info(check_id, async_req=True) >>> result = thread.get() :param async_req bool :param str check_id: The check ID. (required) :param str zap_trace_span: OpenTracing span context :return: None If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._delete_checks_id_prepare(check_id, **kwargs) return self.api_client.call_api( '/api/v2/checks/{checkID}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type=None, # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) async def delete_checks_id_async(self, check_id, **kwargs): # noqa: E501,D401,D403 """Delete a check. This method makes an asynchronous HTTP request. :param async_req bool :param str check_id: The check ID. (required) :param str zap_trace_span: OpenTracing span context :return: None If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._delete_checks_id_prepare(check_id, **kwargs) return await self.api_client.call_api( '/api/v2/checks/{checkID}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type=None, # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) def _delete_checks_id_prepare(self, check_id, **kwargs): # noqa: E501,D401,D403 local_var_params = locals() all_params = ['check_id', 'zap_trace_span'] # noqa: E501 self._check_operation_params('delete_checks_id', all_params, local_var_params) # verify the required parameter 'check_id' is set if ('check_id' not in local_var_params or local_var_params['check_id'] is None): raise ValueError("Missing the required parameter `check_id` when calling `delete_checks_id`") # noqa: E501 path_params = {} if 'check_id' in local_var_params: path_params['checkID'] = local_var_params['check_id'] # noqa: E501 query_params = [] header_params = {} if 'zap_trace_span' in local_var_params: header_params['Zap-Trace-Span'] = local_var_params['zap_trace_span'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 return local_var_params, path_params, query_params, header_params, body_params def delete_checks_id_labels_id(self, check_id, label_id, **kwargs): # noqa: E501,D401,D403 """Delete label from a check. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_checks_id_labels_id(check_id, label_id, async_req=True) >>> result = thread.get() :param async_req bool :param str check_id: The check ID. (required) :param str label_id: The ID of the label to delete. (required) :param str zap_trace_span: OpenTracing span context :return: None If the method is called asynchronously, returns the request thread. """ # noqa: E501 kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.delete_checks_id_labels_id_with_http_info(check_id, label_id, **kwargs) # noqa: E501 else: (data) = self.delete_checks_id_labels_id_with_http_info(check_id, label_id, **kwargs) # noqa: E501 return data def delete_checks_id_labels_id_with_http_info(self, check_id, label_id, **kwargs): # noqa: E501,D401,D403 """Delete label from a check. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.delete_checks_id_labels_id_with_http_info(check_id, label_id, async_req=True) >>> result = thread.get() :param async_req bool :param str check_id: The check ID. (required) :param str label_id: The ID of the label to delete. (required) :param str zap_trace_span: OpenTracing span context :return: None If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._delete_checks_id_labels_id_prepare(check_id, label_id, **kwargs) return self.api_client.call_api( '/api/v2/checks/{checkID}/labels/{labelID}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type=None, # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) async def delete_checks_id_labels_id_async(self, check_id, label_id, **kwargs): # noqa: E501,D401,D403 """Delete label from a check. This method makes an asynchronous HTTP request. :param async_req bool :param str check_id: The check ID. (required) :param str label_id: The ID of the label to delete. (required) :param str zap_trace_span: OpenTracing span context :return: None If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._delete_checks_id_labels_id_prepare(check_id, label_id, **kwargs) return await self.api_client.call_api( '/api/v2/checks/{checkID}/labels/{labelID}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type=None, # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) def _delete_checks_id_labels_id_prepare(self, check_id, label_id, **kwargs): # noqa: E501,D401,D403 local_var_params = locals() all_params = ['check_id', 'label_id', 'zap_trace_span'] # noqa: E501 self._check_operation_params('delete_checks_id_labels_id', all_params, local_var_params) # verify the required parameter 'check_id' is set if ('check_id' not in local_var_params or local_var_params['check_id'] is None): raise ValueError("Missing the required parameter `check_id` when calling `delete_checks_id_labels_id`") # noqa: E501 # verify the required parameter 'label_id' is set if ('label_id' not in local_var_params or local_var_params['label_id'] is None): raise ValueError("Missing the required parameter `label_id` when calling `delete_checks_id_labels_id`") # noqa: E501 path_params = {} if 'check_id' in local_var_params: path_params['checkID'] = local_var_params['check_id'] # noqa: E501 if 'label_id' in local_var_params: path_params['labelID'] = local_var_params['label_id'] # noqa: E501 query_params = [] header_params = {} if 'zap_trace_span' in local_var_params: header_params['Zap-Trace-Span'] = local_var_params['zap_trace_span'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 return local_var_params, path_params, query_params, header_params, body_params def get_checks(self, org_id, **kwargs): # noqa: E501,D401,D403 """List all checks. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_checks(org_id, async_req=True) >>> result = thread.get() :param async_req bool :param str org_id: Only show checks that belong to a specific organization ID. (required) :param str zap_trace_span: OpenTracing span context :param int offset: :param int limit: :return: Checks If the method is called asynchronously, returns the request thread. """ # noqa: E501 kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_checks_with_http_info(org_id, **kwargs) # noqa: E501 else: (data) = self.get_checks_with_http_info(org_id, **kwargs) # noqa: E501 return data def get_checks_with_http_info(self, org_id, **kwargs): # noqa: E501,D401,D403 """List all checks. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_checks_with_http_info(org_id, async_req=True) >>> result = thread.get() :param async_req bool :param str org_id: Only show checks that belong to a specific organization ID. (required) :param str zap_trace_span: OpenTracing span context :param int offset: :param int limit: :return: Checks If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._get_checks_prepare(org_id, **kwargs) return self.api_client.call_api( '/api/v2/checks', 'GET', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type='Checks', # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) async def get_checks_async(self, org_id, **kwargs): # noqa: E501,D401,D403 """List all checks. This method makes an asynchronous HTTP request. :param async_req bool :param str org_id: Only show checks that belong to a specific organization ID. (required) :param str zap_trace_span: OpenTracing span context :param int offset: :param int limit: :return: Checks If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._get_checks_prepare(org_id, **kwargs) return await self.api_client.call_api( '/api/v2/checks', 'GET', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type='Checks', # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) def _get_checks_prepare(self, org_id, **kwargs): # noqa: E501,D401,D403 local_var_params = locals() all_params = ['org_id', 'zap_trace_span', 'offset', 'limit'] # noqa: E501 self._check_operation_params('get_checks', all_params, local_var_params) # verify the required parameter 'org_id' is set if ('org_id' not in local_var_params or local_var_params['org_id'] is None): raise ValueError("Missing the required parameter `org_id` when calling `get_checks`") # noqa: E501 if 'offset' in local_var_params and local_var_params['offset'] < 0: # noqa: E501 raise ValueError("Invalid value for parameter `offset` when calling `get_checks`, must be a value greater than or equal to `0`") # noqa: E501 if 'limit' in local_var_params and local_var_params['limit'] > 100: # noqa: E501 raise ValueError("Invalid value for parameter `limit` when calling `get_checks`, must be a value less than or equal to `100`") # noqa: E501 if 'limit' in local_var_params and local_var_params['limit'] < 1: # noqa: E501 raise ValueError("Invalid value for parameter `limit` when calling `get_checks`, must be a value greater than or equal to `1`") # noqa: E501 path_params = {} query_params = [] if 'offset' in local_var_params: query_params.append(('offset', local_var_params['offset'])) # noqa: E501 if 'limit' in local_var_params: query_params.append(('limit', local_var_params['limit'])) # noqa: E501 if 'org_id' in local_var_params: query_params.append(('orgID', local_var_params['org_id'])) # noqa: E501 header_params = {} if 'zap_trace_span' in local_var_params: header_params['Zap-Trace-Span'] = local_var_params['zap_trace_span'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 return local_var_params, path_params, query_params, header_params, body_params def get_checks_id(self, check_id, **kwargs): # noqa: E501,D401,D403 """Retrieve a check. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_checks_id(check_id, async_req=True) >>> result = thread.get() :param async_req bool :param str check_id: The check ID. (required) :param str zap_trace_span: OpenTracing span context :return: Check If the method is called asynchronously, returns the request thread. """ # noqa: E501 kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_checks_id_with_http_info(check_id, **kwargs) # noqa: E501 else: (data) = self.get_checks_id_with_http_info(check_id, **kwargs) # noqa: E501 return data def get_checks_id_with_http_info(self, check_id, **kwargs): # noqa: E501,D401,D403 """Retrieve a check. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_checks_id_with_http_info(check_id, async_req=True) >>> result = thread.get() :param async_req bool :param str check_id: The check ID. (required) :param str zap_trace_span: OpenTracing span context :return: Check If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._get_checks_id_prepare(check_id, **kwargs) return self.api_client.call_api( '/api/v2/checks/{checkID}', 'GET', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type='Check', # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) async def get_checks_id_async(self, check_id, **kwargs): # noqa: E501,D401,D403 """Retrieve a check. This method makes an asynchronous HTTP request. :param async_req bool :param str check_id: The check ID. (required) :param str zap_trace_span: OpenTracing span context :return: Check If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._get_checks_id_prepare(check_id, **kwargs) return await self.api_client.call_api( '/api/v2/checks/{checkID}', 'GET', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type='Check', # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) def _get_checks_id_prepare(self, check_id, **kwargs): # noqa: E501,D401,D403 local_var_params = locals() all_params = ['check_id', 'zap_trace_span'] # noqa: E501 self._check_operation_params('get_checks_id', all_params, local_var_params) # verify the required parameter 'check_id' is set if ('check_id' not in local_var_params or local_var_params['check_id'] is None): raise ValueError("Missing the required parameter `check_id` when calling `get_checks_id`") # noqa: E501 path_params = {} if 'check_id' in local_var_params: path_params['checkID'] = local_var_params['check_id'] # noqa: E501 query_params = [] header_params = {} if 'zap_trace_span' in local_var_params: header_params['Zap-Trace-Span'] = local_var_params['zap_trace_span'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 return local_var_params, path_params, query_params, header_params, body_params def get_checks_id_labels(self, check_id, **kwargs): # noqa: E501,D401,D403 """List all labels for a check. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_checks_id_labels(check_id, async_req=True) >>> result = thread.get() :param async_req bool :param str check_id: The check ID. (required) :param str zap_trace_span: OpenTracing span context :return: LabelsResponse If the method is called asynchronously, returns the request thread. """ # noqa: E501 kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_checks_id_labels_with_http_info(check_id, **kwargs) # noqa: E501 else: (data) = self.get_checks_id_labels_with_http_info(check_id, **kwargs) # noqa: E501 return data def get_checks_id_labels_with_http_info(self, check_id, **kwargs): # noqa: E501,D401,D403 """List all labels for a check. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_checks_id_labels_with_http_info(check_id, async_req=True) >>> result = thread.get() :param async_req bool :param str check_id: The check ID. (required) :param str zap_trace_span: OpenTracing span context :return: LabelsResponse If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._get_checks_id_labels_prepare(check_id, **kwargs) return self.api_client.call_api( '/api/v2/checks/{checkID}/labels', 'GET', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type='LabelsResponse', # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) async def get_checks_id_labels_async(self, check_id, **kwargs): # noqa: E501,D401,D403 """List all labels for a check. This method makes an asynchronous HTTP request. :param async_req bool :param str check_id: The check ID. (required) :param str zap_trace_span: OpenTracing span context :return: LabelsResponse If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._get_checks_id_labels_prepare(check_id, **kwargs) return await self.api_client.call_api( '/api/v2/checks/{checkID}/labels', 'GET', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type='LabelsResponse', # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) def _get_checks_id_labels_prepare(self, check_id, **kwargs): # noqa: E501,D401,D403 local_var_params = locals() all_params = ['check_id', 'zap_trace_span'] # noqa: E501 self._check_operation_params('get_checks_id_labels', all_params, local_var_params) # verify the required parameter 'check_id' is set if ('check_id' not in local_var_params or local_var_params['check_id'] is None): raise ValueError("Missing the required parameter `check_id` when calling `get_checks_id_labels`") # noqa: E501 path_params = {} if 'check_id' in local_var_params: path_params['checkID'] = local_var_params['check_id'] # noqa: E501 query_params = [] header_params = {} if 'zap_trace_span' in local_var_params: header_params['Zap-Trace-Span'] = local_var_params['zap_trace_span'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 return local_var_params, path_params, query_params, header_params, body_params def get_checks_id_query(self, check_id, **kwargs): # noqa: E501,D401,D403 """Retrieve a check query. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_checks_id_query(check_id, async_req=True) >>> result = thread.get() :param async_req bool :param str check_id: The check ID. (required) :param str zap_trace_span: OpenTracing span context :return: FluxResponse If the method is called asynchronously, returns the request thread. """ # noqa: E501 kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.get_checks_id_query_with_http_info(check_id, **kwargs) # noqa: E501 else: (data) = self.get_checks_id_query_with_http_info(check_id, **kwargs) # noqa: E501 return data def get_checks_id_query_with_http_info(self, check_id, **kwargs): # noqa: E501,D401,D403 """Retrieve a check query. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.get_checks_id_query_with_http_info(check_id, async_req=True) >>> result = thread.get() :param async_req bool :param str check_id: The check ID. (required) :param str zap_trace_span: OpenTracing span context :return: FluxResponse If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._get_checks_id_query_prepare(check_id, **kwargs) return self.api_client.call_api( '/api/v2/checks/{checkID}/query', 'GET', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type='FluxResponse', # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) async def get_checks_id_query_async(self, check_id, **kwargs): # noqa: E501,D401,D403 """Retrieve a check query. This method makes an asynchronous HTTP request. :param async_req bool :param str check_id: The check ID. (required) :param str zap_trace_span: OpenTracing span context :return: FluxResponse If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._get_checks_id_query_prepare(check_id, **kwargs) return await self.api_client.call_api( '/api/v2/checks/{checkID}/query', 'GET', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type='FluxResponse', # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) def _get_checks_id_query_prepare(self, check_id, **kwargs): # noqa: E501,D401,D403 local_var_params = locals() all_params = ['check_id', 'zap_trace_span'] # noqa: E501 self._check_operation_params('get_checks_id_query', all_params, local_var_params) # verify the required parameter 'check_id' is set if ('check_id' not in local_var_params or local_var_params['check_id'] is None): raise ValueError("Missing the required parameter `check_id` when calling `get_checks_id_query`") # noqa: E501 path_params = {} if 'check_id' in local_var_params: path_params['checkID'] = local_var_params['check_id'] # noqa: E501 query_params = [] header_params = {} if 'zap_trace_span' in local_var_params: header_params['Zap-Trace-Span'] = local_var_params['zap_trace_span'] # noqa: E501 body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 return local_var_params, path_params, query_params, header_params, body_params def patch_checks_id(self, check_id, check_patch, **kwargs): # noqa: E501,D401,D403 """Update a check. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.patch_checks_id(check_id, check_patch, async_req=True) >>> result = thread.get() :param async_req bool :param str check_id: The check ID. (required) :param CheckPatch check_patch: Check update to apply (required) :param str zap_trace_span: OpenTracing span context :return: Check If the method is called asynchronously, returns the request thread. """ # noqa: E501 kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.patch_checks_id_with_http_info(check_id, check_patch, **kwargs) # noqa: E501 else: (data) = self.patch_checks_id_with_http_info(check_id, check_patch, **kwargs) # noqa: E501 return data def patch_checks_id_with_http_info(self, check_id, check_patch, **kwargs): # noqa: E501,D401,D403 """Update a check. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.patch_checks_id_with_http_info(check_id, check_patch, async_req=True) >>> result = thread.get() :param async_req bool :param str check_id: The check ID. (required) :param CheckPatch check_patch: Check update to apply (required) :param str zap_trace_span: OpenTracing span context :return: Check If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._patch_checks_id_prepare(check_id, check_patch, **kwargs) return self.api_client.call_api( '/api/v2/checks/{checkID}', 'PATCH', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type='Check', # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) async def patch_checks_id_async(self, check_id, check_patch, **kwargs): # noqa: E501,D401,D403 """Update a check. This method makes an asynchronous HTTP request. :param async_req bool :param str check_id: The check ID. (required) :param CheckPatch check_patch: Check update to apply (required) :param str zap_trace_span: OpenTracing span context :return: Check If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._patch_checks_id_prepare(check_id, check_patch, **kwargs) return await self.api_client.call_api( '/api/v2/checks/{checkID}', 'PATCH', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type='Check', # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) def _patch_checks_id_prepare(self, check_id, check_patch, **kwargs): # noqa: E501,D401,D403 local_var_params = locals() all_params = ['check_id', 'check_patch', 'zap_trace_span'] # noqa: E501 self._check_operation_params('patch_checks_id', all_params, local_var_params) # verify the required parameter 'check_id' is set if ('check_id' not in local_var_params or local_var_params['check_id'] is None): raise ValueError("Missing the required parameter `check_id` when calling `patch_checks_id`") # noqa: E501 # verify the required parameter 'check_patch' is set if ('check_patch' not in local_var_params or local_var_params['check_patch'] is None): raise ValueError("Missing the required parameter `check_patch` when calling `patch_checks_id`") # noqa: E501 path_params = {} if 'check_id' in local_var_params: path_params['checkID'] = local_var_params['check_id'] # noqa: E501 query_params = [] header_params = {} if 'zap_trace_span' in local_var_params: header_params['Zap-Trace-Span'] = local_var_params['zap_trace_span'] # noqa: E501 body_params = None if 'check_patch' in local_var_params: body_params = local_var_params['check_patch'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 return local_var_params, path_params, query_params, header_params, body_params def post_checks_id_labels(self, check_id, label_mapping, **kwargs): # noqa: E501,D401,D403 """Add a label to a check. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.post_checks_id_labels(check_id, label_mapping, async_req=True) >>> result = thread.get() :param async_req bool :param str check_id: The check ID. (required) :param LabelMapping label_mapping: Label to add (required) :param str zap_trace_span: OpenTracing span context :return: LabelResponse If the method is called asynchronously, returns the request thread. """ # noqa: E501 kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.post_checks_id_labels_with_http_info(check_id, label_mapping, **kwargs) # noqa: E501 else: (data) = self.post_checks_id_labels_with_http_info(check_id, label_mapping, **kwargs) # noqa: E501 return data def post_checks_id_labels_with_http_info(self, check_id, label_mapping, **kwargs): # noqa: E501,D401,D403 """Add a label to a check. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.post_checks_id_labels_with_http_info(check_id, label_mapping, async_req=True) >>> result = thread.get() :param async_req bool :param str check_id: The check ID. (required) :param LabelMapping label_mapping: Label to add (required) :param str zap_trace_span: OpenTracing span context :return: LabelResponse If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._post_checks_id_labels_prepare(check_id, label_mapping, **kwargs) return self.api_client.call_api( '/api/v2/checks/{checkID}/labels', 'POST', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type='LabelResponse', # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) async def post_checks_id_labels_async(self, check_id, label_mapping, **kwargs): # noqa: E501,D401,D403 """Add a label to a check. This method makes an asynchronous HTTP request. :param async_req bool :param str check_id: The check ID. (required) :param LabelMapping label_mapping: Label to add (required) :param str zap_trace_span: OpenTracing span context :return: LabelResponse If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._post_checks_id_labels_prepare(check_id, label_mapping, **kwargs) return await self.api_client.call_api( '/api/v2/checks/{checkID}/labels', 'POST', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type='LabelResponse', # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) def _post_checks_id_labels_prepare(self, check_id, label_mapping, **kwargs): # noqa: E501,D401,D403 local_var_params = locals() all_params = ['check_id', 'label_mapping', 'zap_trace_span'] # noqa: E501 self._check_operation_params('post_checks_id_labels', all_params, local_var_params) # verify the required parameter 'check_id' is set if ('check_id' not in local_var_params or local_var_params['check_id'] is None): raise ValueError("Missing the required parameter `check_id` when calling `post_checks_id_labels`") # noqa: E501 # verify the required parameter 'label_mapping' is set if ('label_mapping' not in local_var_params or local_var_params['label_mapping'] is None): raise ValueError("Missing the required parameter `label_mapping` when calling `post_checks_id_labels`") # noqa: E501 path_params = {} if 'check_id' in local_var_params: path_params['checkID'] = local_var_params['check_id'] # noqa: E501 query_params = [] header_params = {} if 'zap_trace_span' in local_var_params: header_params['Zap-Trace-Span'] = local_var_params['zap_trace_span'] # noqa: E501 body_params = None if 'label_mapping' in local_var_params: body_params = local_var_params['label_mapping'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 return local_var_params, path_params, query_params, header_params, body_params def put_checks_id(self, check_id, check, **kwargs): # noqa: E501,D401,D403 """Update a check. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.put_checks_id(check_id, check, async_req=True) >>> result = thread.get() :param async_req bool :param str check_id: The check ID. (required) :param Check check: Check update to apply (required) :param str zap_trace_span: OpenTracing span context :return: Check If the method is called asynchronously, returns the request thread. """ # noqa: E501 kwargs['_return_http_data_only'] = True if kwargs.get('async_req'): return self.put_checks_id_with_http_info(check_id, check, **kwargs) # noqa: E501 else: (data) = self.put_checks_id_with_http_info(check_id, check, **kwargs) # noqa: E501 return data def put_checks_id_with_http_info(self, check_id, check, **kwargs): # noqa: E501,D401,D403 """Update a check. This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async_req=True >>> thread = api.put_checks_id_with_http_info(check_id, check, async_req=True) >>> result = thread.get() :param async_req bool :param str check_id: The check ID. (required) :param Check check: Check update to apply (required) :param str zap_trace_span: OpenTracing span context :return: Check If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._put_checks_id_prepare(check_id, check, **kwargs) return self.api_client.call_api( '/api/v2/checks/{checkID}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type='Check', # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) async def put_checks_id_async(self, check_id, check, **kwargs): # noqa: E501,D401,D403 """Update a check. This method makes an asynchronous HTTP request. :param async_req bool :param str check_id: The check ID. (required) :param Check check: Check update to apply (required) :param str zap_trace_span: OpenTracing span context :return: Check If the method is called asynchronously, returns the request thread. """ # noqa: E501 local_var_params, path_params, query_params, header_params, body_params = \ self._put_checks_id_prepare(check_id, check, **kwargs) return await self.api_client.call_api( '/api/v2/checks/{checkID}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=[], files={}, response_type='Check', # noqa: E501 auth_settings=[], async_req=local_var_params.get('async_req'), _return_http_data_only=local_var_params.get('_return_http_data_only'), # noqa: E501 _preload_content=local_var_params.get('_preload_content', True), _request_timeout=local_var_params.get('_request_timeout'), collection_formats={}, urlopen_kw=kwargs.get('urlopen_kw', None)) def _put_checks_id_prepare(self, check_id, check, **kwargs): # noqa: E501,D401,D403 local_var_params = locals() all_params = ['check_id', 'check', 'zap_trace_span'] # noqa: E501 self._check_operation_params('put_checks_id', all_params, local_var_params) # verify the required parameter 'check_id' is set if ('check_id' not in local_var_params or local_var_params['check_id'] is None): raise ValueError("Missing the required parameter `check_id` when calling `put_checks_id`") # noqa: E501 # verify the required parameter 'check' is set if ('check' not in local_var_params or local_var_params['check'] is None): raise ValueError("Missing the required parameter `check` when calling `put_checks_id`") # noqa: E501 path_params = {} if 'check_id' in local_var_params: path_params['checkID'] = local_var_params['check_id'] # noqa: E501 query_params = [] header_params = {} if 'zap_trace_span' in local_var_params: header_params['Zap-Trace-Span'] = local_var_params['zap_trace_span'] # noqa: E501 body_params = None if 'check' in local_var_params: body_params = local_var_params['check'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 return local_var_params, path_params, query_params, header_params, body_params

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0.633776

6,956

55,780

4.750144

0.026164

0.051813

0.090672

0.04116

0.969493

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0.273664

55,780

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null

0

1

0

1

0

null

0

7

7e200443c90d9ec90f6fe1a83c71f4b659b88637

1,955

py

Python

tests/test_prometheus_rules.py

app-sre/app-bouncer

1153e21872f0c929904da32e34785286149302a4

[ "Apache-2.0" ]

1

2020-07-05T21:23:05.000Z

tests/test_prometheus_rules.py

app-sre/app-bouncer

1153e21872f0c929904da32e34785286149302a4

[ "Apache-2.0" ]

4

2019-12-03T16:26:57.000Z

2020-09-30T22:14:46.000Z

tests/test_prometheus_rules.py

app-sre/app-bouncer

1153e21872f0c929904da32e34785286149302a4

[ "Apache-2.0" ]

7

2019-09-05T08:15:14.000Z

2020-04-21T15:15:08.000Z

import yaml from textwrap import dedent from checks.prometheus_rule import (CheckPrometheusRuleSeverity, CheckPrometheusRuleLabels) from lib.result import CheckError, CheckSuccess def test_prometheus_rule_severity_valid(): manifest = yaml.safe_load(dedent(""" --- apiVersion: monitoring.coreos.com/v1 kind: PrometheusRule metadata: name: rule spec: groups: - name: group rules: - alert: alert labels: severity: high """)) c = CheckPrometheusRuleSeverity() result = c.check_severity(manifest) assert isinstance(result, CheckSuccess) def test_prometheus_rule_severity_invalid(): manifest = yaml.safe_load(dedent(""" --- apiVersion: monitoring.coreos.com/v1 kind: PrometheusRule metadata: name: rule spec: groups: - name: group rules: - alert: alert labels: severity: critical """)) c = CheckPrometheusRuleSeverity() result = c.check_severity(manifest) assert isinstance(result, CheckError) def test_prometheus_rule_labels_valid(): manifest = yaml.safe_load(dedent(""" --- apiVersion: monitoring.coreos.com/v1 kind: PrometheusRule metadata: name: rule labels: prometheus: app-sre role: alert-rules """)) c = CheckPrometheusRuleLabels() result = c.check_labels(manifest) assert isinstance(result, CheckSuccess) def test_prometheus_rule_labels_invalid(): manifest = yaml.safe_load(dedent(""" --- apiVersion: monitoring.coreos.com/v1 kind: PrometheusRule metadata: name: rule labels: promethues: app-sre role: alert-rules """)) c = CheckPrometheusRuleLabels() result = c.check_labels(manifest) assert isinstance(result, CheckError)

22.471264

64

0.618926

181

1,955

6.546961

0.259669

0.059072

0.057384

0.070886

0.850633

0.805907

0.764557

0.708861

0

0.00289

0.292072

1,955

86

65

22.732558

0.853324

0

0.811594

0

0.455243

0.049105

0

0.057971

1

0.057971

false

0

0.057971

0

0.115942

0

null

0

1

0

1

0

null

0

7

7e67a6bef329fdda05430df45d815e11a2b7f9b2

200

py

Python

spotdl/providers/lyrics/__init__.py

phcreery/spotdl-v4

3bd3768de10ae80b5e1ba3bbe6b792f7fc9f8dfc

[ "MIT" ]

10

2022-01-03T15:00:34.000Z

2022-03-18T19:55:37.000Z

spotdl/providers/lyrics/__init__.py

phcreery/spotdl-v4

3bd3768de10ae80b5e1ba3bbe6b792f7fc9f8dfc

[ "MIT" ]

9

2022-01-15T05:43:35.000Z

2022-03-16T17:57:47.000Z

spotdl/providers/lyrics/__init__.py

phcreery/spotdl-v4

3bd3768de10ae80b5e1ba3bbe6b792f7fc9f8dfc

[ "MIT" ]

11

2022-01-03T15:00:22.000Z

2022-03-27T19:27:05.000Z

""" Lyrics providers for spotdl. """ from spotdl.providers.lyrics.genius import Genius from spotdl.providers.lyrics.musixmatch import MusixMatch from spotdl.providers.lyrics.azlyrics import AzLyrics

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py

Python

infoblox_netmri/api/broker/v3_6_0/config_error_broker.py

IngmarVG-IB/infoblox-netmri

b0c725fd64aee1890d83917d911b89236207e564

[ "Apache-2.0" ]

null

infoblox_netmri/api/broker/v3_6_0/config_error_broker.py

IngmarVG-IB/infoblox-netmri

b0c725fd64aee1890d83917d911b89236207e564

[ "Apache-2.0" ]

null

infoblox_netmri/api/broker/v3_6_0/config_error_broker.py

IngmarVG-IB/infoblox-netmri

b0c725fd64aee1890d83917d911b89236207e564

[ "Apache-2.0" ]

null

from ..broker import Broker class ConfigErrorBroker(Broker): controller = "config_errors" def index(self, **kwargs): """Lists the available config errors. Any of the inputs listed may be be used to narrow the list; other inputs will be ignored. Of the various ways to query lists, using this method is most efficient. **Inputs** | ``api version min:`` 2.4 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param ConfigErrorID: The internal NetMRI identifier of the Configuration Error. :type ConfigErrorID: Integer | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param ConfigErrorID: The internal NetMRI identifier of the Configuration Error. :type ConfigErrorID: Array of Integer | ``api version min:`` 2.4 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param DeviceID: The internal NetMRI identifier for the device from which configuration error was collected. :type DeviceID: Integer | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param DeviceID: The internal NetMRI identifier for the device from which configuration error was collected. :type DeviceID: Array of Integer | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param DeviceGroupID: The internal NetMRI identifier of the device groups to which to limit the results. :type DeviceGroupID: Array of Integer | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` today :param starttime: The data returned will represent the config errors with this date and time as lower boundary. If omitted, the result will indicate the most recently collected data. :type starttime: DateTime | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` tomorrow :param endtime: The data returned will represent the config errors with this date and time as upper boundary. If omitted, the result will indicate the most recently collected data. :type endtime: DateTime | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` 0 :param start: The record number to return in the selected page of data. It will always appear, although it may not be the first record. See the :limit for more information. :type start: Integer | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` 1000 :param limit: The size of the page of data, that is, the maximum number of records returned. The limit size will be used to break the data up into pages and the first page with the start record will be returned. So if you have 100 records and use a :limit of 10 and a :start of 10, you will get records 10-19. The maximum limit is 10000. :type limit: Integer | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` ConfigErrorID :param sort: The data field(s) to use for sorting the output. Default is ConfigErrorID. Valid values are ConfigErrorID, DeviceID, Timestamp, ErrMsg, DatasourceID. :type sort: Array of String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` asc :param dir: The direction(s) in which to sort the data. Default is 'asc'. Valid values are 'asc' and 'desc'. :type dir: Array of String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param select: The list of attributes to return for each ConfigError. Valid values are ConfigErrorID, DeviceID, Timestamp, ErrMsg, DatasourceID. If empty or omitted, all attributes will be returned. :type select: Array | ``api version min:`` 2.8 | ``api version max:`` None | ``required:`` False | ``default:`` None :param goto_field: The field name for NIOS GOTO that is used for locating a row position of records. :type goto_field: String | ``api version min:`` 2.8 | ``api version max:`` None | ``required:`` False | ``default:`` None :param goto_value: The value of goto_field for NIOS GOTO that is used for locating a row position of records. :type goto_value: String **Outputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :return config_errors: An array of the ConfigError objects that match the specified input criteria. :rtype config_errors: Array of ConfigError """ return self.api_list_request(self._get_method_fullname("index"), kwargs) def show(self, **kwargs): """Shows the details for the specified config error. **Inputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` True | ``default:`` None :param ConfigErrorID: The internal NetMRI identifier of the Configuration Error. :type ConfigErrorID: Integer **Outputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :return config_error: The config error identified by the specified ConfigErrorID. :rtype config_error: ConfigError """ return self.api_request(self._get_method_fullname("show"), kwargs) def search(self, **kwargs): """Lists the available config errors matching the input criteria. This method provides a more flexible search interface than the index method, but searching using this method is more demanding on the system and will not perform to the same level as the index method. The input fields listed below will be used as in the index method, to filter the result, along with the optional query string and XML filter described below. **Inputs** | ``api version min:`` 2.4 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param ConfigErrorID: The internal NetMRI identifier of the Configuration Error. :type ConfigErrorID: Integer | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param ConfigErrorID: The internal NetMRI identifier of the Configuration Error. :type ConfigErrorID: Array of Integer | ``api version min:`` 2.4 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param DatasourceID: The internal NetMRI identifier for the collector NetMRI that collected this data record. :type DatasourceID: Integer | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param DatasourceID: The internal NetMRI identifier for the collector NetMRI that collected this data record. :type DatasourceID: Array of Integer | ``api version min:`` 2.4 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param DeviceID: The internal NetMRI identifier for the device from which configuration error was collected. :type DeviceID: Integer | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param DeviceID: The internal NetMRI identifier for the device from which configuration error was collected. :type DeviceID: Array of Integer | ``api version min:`` 2.4 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param ErrMsg: The total inbound and outbound error message of the device configuration. :type ErrMsg: String | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param ErrMsg: The total inbound and outbound error message of the device configuration. :type ErrMsg: Array of String | ``api version min:`` 2.4 | ``api version max:`` 2.4 | ``required:`` False | ``default:`` None :param Timestamp: The date and time at which the session was updated. :type Timestamp: DateTime | ``api version min:`` 2.5 | ``api version max:`` None | ``required:`` False | ``default:`` None :param Timestamp: The date and time at which the session was updated. :type Timestamp: Array of DateTime | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param DeviceGroupID: The internal NetMRI identifier of the device groups to which to limit the results. :type DeviceGroupID: Array of Integer | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` today :param starttime: The data returned will represent the config errors with this date and time as lower boundary. If omitted, the result will indicate the most recently collected data. :type starttime: DateTime | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` tomorrow :param endtime: The data returned will represent the config errors with this date and time as upper boundary. If omitted, the result will indicate the most recently collected data. :type endtime: DateTime | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` 0 :param start: The record number to return in the selected page of data. It will always appear, although it may not be the first record. See the :limit for more information. :type start: Integer | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` 1000 :param limit: The size of the page of data, that is, the maximum number of records returned. The limit size will be used to break the data up into pages and the first page with the start record will be returned. So if you have 100 records and use a :limit of 10 and a :start of 10, you will get records 10-19. The maximum limit is 10000. :type limit: Integer | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` ConfigErrorID :param sort: The data field(s) to use for sorting the output. Default is ConfigErrorID. Valid values are ConfigErrorID, DeviceID, Timestamp, ErrMsg, DatasourceID. :type sort: Array of String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` asc :param dir: The direction(s) in which to sort the data. Default is 'asc'. Valid values are 'asc' and 'desc'. :type dir: Array of String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param select: The list of attributes to return for each ConfigError. Valid values are ConfigErrorID, DeviceID, Timestamp, ErrMsg, DatasourceID. If empty or omitted, all attributes will be returned. :type select: Array | ``api version min:`` 2.8 | ``api version max:`` None | ``required:`` False | ``default:`` None :param goto_field: The field name for NIOS GOTO that is used for locating a row position of records. :type goto_field: String | ``api version min:`` 2.8 | ``api version max:`` None | ``required:`` False | ``default:`` None :param goto_value: The value of goto_field for NIOS GOTO that is used for locating a row position of records. :type goto_value: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param query: This value will be matched against config errors, looking to see if one or more of the listed attributes contain the passed value. You may also surround the value with '/' and '/' to perform a regular expression search rather than a containment operation. Any record that matches will be returned. The attributes searched are: ConfigErrorID, DatasourceID, DeviceID, ErrMsg, Timestamp. :type query: String | ``api version min:`` 2.3 | ``api version max:`` None | ``required:`` False | ``default:`` None :param xml_filter: A SetFilter XML structure to further refine the search. The SetFilter will be applied AFTER any search query or field values, but before any limit options. The limit and pagination will be enforced after the filter. Remind that this kind of filter may be costly and inefficient if not associated with a database filtering. :type xml_filter: String **Outputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :return config_errors: An array of the ConfigError objects that match the specified input criteria. :rtype config_errors: Array of ConfigError """ return self.api_list_request(self._get_method_fullname("search"), kwargs) def find(self, **kwargs): """Lists the available config errors matching the input specification. This provides the most flexible search specification of all the query mechanisms, enabling searching using comparison operations other than equality. However, it is more complex to use and will not perform as efficiently as the index or search methods. In the input descriptions below, 'field names' refers to the following fields: ConfigErrorID, DatasourceID, DeviceID, ErrMsg, Timestamp. **Inputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_ConfigErrorID: The operator to apply to the field ConfigErrorID. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. ConfigErrorID: The internal NetMRI identifier of the Configuration Error. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_ConfigErrorID: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_ConfigErrorID: If op_ConfigErrorID is specified, the field named in this input will be compared to the value in ConfigErrorID using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_ConfigErrorID must be specified if op_ConfigErrorID is specified. :type val_f_ConfigErrorID: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_ConfigErrorID: If op_ConfigErrorID is specified, this value will be compared to the value in ConfigErrorID using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_ConfigErrorID must be specified if op_ConfigErrorID is specified. :type val_c_ConfigErrorID: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_DatasourceID: The operator to apply to the field DatasourceID. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. DatasourceID: The internal NetMRI identifier for the collector NetMRI that collected this data record. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_DatasourceID: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_DatasourceID: If op_DatasourceID is specified, the field named in this input will be compared to the value in DatasourceID using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_DatasourceID must be specified if op_DatasourceID is specified. :type val_f_DatasourceID: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_DatasourceID: If op_DatasourceID is specified, this value will be compared to the value in DatasourceID using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_DatasourceID must be specified if op_DatasourceID is specified. :type val_c_DatasourceID: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_DeviceID: The operator to apply to the field DeviceID. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. DeviceID: The internal NetMRI identifier for the device from which configuration error was collected. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_DeviceID: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_DeviceID: If op_DeviceID is specified, the field named in this input will be compared to the value in DeviceID using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_DeviceID must be specified if op_DeviceID is specified. :type val_f_DeviceID: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_DeviceID: If op_DeviceID is specified, this value will be compared to the value in DeviceID using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_DeviceID must be specified if op_DeviceID is specified. :type val_c_DeviceID: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_ErrMsg: The operator to apply to the field ErrMsg. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. ErrMsg: The total inbound and outbound error message of the device configuration. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_ErrMsg: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_ErrMsg: If op_ErrMsg is specified, the field named in this input will be compared to the value in ErrMsg using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_ErrMsg must be specified if op_ErrMsg is specified. :type val_f_ErrMsg: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_ErrMsg: If op_ErrMsg is specified, this value will be compared to the value in ErrMsg using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_ErrMsg must be specified if op_ErrMsg is specified. :type val_c_ErrMsg: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param op_Timestamp: The operator to apply to the field Timestamp. Valid values are: =, <>, rlike, not rlike, >, >=, <, <=, like, not like, is null, is not null, between. Timestamp: The date and time at which the session was updated. For the between operator the value will be treated as an Array if comma delimited string is passed, and it must contain an even number of values. :type op_Timestamp: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_f_Timestamp: If op_Timestamp is specified, the field named in this input will be compared to the value in Timestamp using the specified operator. That is, the value in this input will be treated as another field name, rather than a constant value. Either this field or val_c_Timestamp must be specified if op_Timestamp is specified. :type val_f_Timestamp: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param val_c_Timestamp: If op_Timestamp is specified, this value will be compared to the value in Timestamp using the specified operator. The value in this input will be treated as an explicit constant value. Either this field or val_f_Timestamp must be specified if op_Timestamp is specified. :type val_c_Timestamp: String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param DeviceGroupID: The internal NetMRI identifier of the device groups to which to limit the results. :type DeviceGroupID: Array of Integer | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` today :param starttime: The data returned will represent the config errors with this date and time as lower boundary. If omitted, the result will indicate the most recently collected data. :type starttime: DateTime | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` tomorrow :param endtime: The data returned will represent the config errors with this date and time as upper boundary. If omitted, the result will indicate the most recently collected data. :type endtime: DateTime | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` 0 :param start: The record number to return in the selected page of data. It will always appear, although it may not be the first record. See the :limit for more information. :type start: Integer | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` 1000 :param limit: The size of the page of data, that is, the maximum number of records returned. The limit size will be used to break the data up into pages and the first page with the start record will be returned. So if you have 100 records and use a :limit of 10 and a :start of 10, you will get records 10-19. The maximum limit is 10000. :type limit: Integer | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` ConfigErrorID :param sort: The data field(s) to use for sorting the output. Default is ConfigErrorID. Valid values are ConfigErrorID, DeviceID, Timestamp, ErrMsg, DatasourceID. :type sort: Array of String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` asc :param dir: The direction(s) in which to sort the data. Default is 'asc'. Valid values are 'asc' and 'desc'. :type dir: Array of String | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :param select: The list of attributes to return for each ConfigError. Valid values are ConfigErrorID, DeviceID, Timestamp, ErrMsg, DatasourceID. If empty or omitted, all attributes will be returned. :type select: Array | ``api version min:`` 2.8 | ``api version max:`` None | ``required:`` False | ``default:`` None :param goto_field: The field name for NIOS GOTO that is used for locating a row position of records. :type goto_field: String | ``api version min:`` 2.8 | ``api version max:`` None | ``required:`` False | ``default:`` None :param goto_value: The value of goto_field for NIOS GOTO that is used for locating a row position of records. :type goto_value: String | ``api version min:`` 2.3 | ``api version max:`` None | ``required:`` False | ``default:`` None :param xml_filter: A SetFilter XML structure to further refine the search. The SetFilter will be applied AFTER any search query or field values, but before any limit options. The limit and pagination will be enforced after the filter. Remind that this kind of filter may be costly and inefficient if not associated with a database filtering. :type xml_filter: String **Outputs** | ``api version min:`` None | ``api version max:`` None | ``required:`` False | ``default:`` None :return config_errors: An array of the ConfigError objects that match the specified input criteria. :rtype config_errors: Array of ConfigError """ return self.api_list_request(self._get_method_fullname("find"), kwargs)

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0ea10fe00626898aba3cd53349d279e23972bf9c

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py

Python

pigments_from_rrs/_version.py

alisonpchase/pigments-from-rrs

33323e1e6ebe486ae15a8724d5539883284bcff5

[ "MIT" ]

null

pigments_from_rrs/_version.py

alisonpchase/pigments-from-rrs

33323e1e6ebe486ae15a8724d5539883284bcff5

[ "MIT" ]

8

2021-07-22T18:19:08.000Z

2022-02-10T01:17:02.000Z

pigments_from_rrs/_version.py

alisonpchase/pigments-from-rrs

33323e1e6ebe486ae15a8724d5539883284bcff5

[ "MIT" ]

1

2021-07-22T17:57:33.000Z

__version__ = '0.1.dev16+g2693076.d20211117'

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