fumiyau/python_comments_free_500000 · Datasets at Hugging Face

1c4577df150e0de677cd366f5bf958d6cbeb0911

2,234

py

Python

src/the_tale/the_tale/game/heroes/conf.py

Alacrate/the-tale

43b211f3a99e93964e95abc20a8ed649a205ffcf

[ "BSD-3-Clause" ]

85

2017-11-21T12:22:02.000Z

2022-03-27T23:07:17.000Z

src/the_tale/the_tale/game/heroes/conf.py

Alacrate/the-tale

43b211f3a99e93964e95abc20a8ed649a205ffcf

[ "BSD-3-Clause" ]

545

2017-11-04T14:15:04.000Z

2022-03-27T14:19:27.000Z

src/the_tale/the_tale/game/heroes/conf.py

Alacrate/the-tale

43b211f3a99e93964e95abc20a8ed649a205ffcf

[ "BSD-3-Clause" ]

45

2017-11-11T12:36:30.000Z

2022-02-25T06:10:44.000Z

import smart_imports smart_imports.all() NAME_REGEX = r'^[\-\ а-яА-Я«»\'ёЁ]+$' if not django_settings.TESTS_RUNNING else r'^[\-\ а-яА-Я«»\'\,ёЁ]+$' settings = utils_app_settings.app_settings('HEROES', USE_ABILITY_CHANCE=0.1, MESSAGES_LOG_LENGTH=10, DIARY_LOG_LENGTH=50, MIN_PVP_BATTLES=25, UI_CACHING_KEY='hero_ui_%d', # not cache livetime, but time period after setupped ui_caching_started_at # in which ui_caching is turned on UI_CACHING_TIME=10 * 60, # time before caching end, when we send next cache command UI_CACHING_CONTINUE_TIME=60, # cache livetime UI_CACHING_TIMEOUT=60, # should we dump cached heroes to database DUMP_CACHED_HEROES=False, START_ENERGY_BONUS=10, MAX_HELPS_IN_TURN=10, NAME_REGEX=NAME_REGEX, NAME_SYMBOLS_DESCRITION='пробел, -, а-я, А-Я, «», \' ', NAME_MIN_LENGHT=3, ABILITIES_RESET_TIMEOUT=datetime.timedelta(days=30), UNLOAD_TIMEOUT=c.TURN_DELTA * 3, RARE_OPERATIONS_INTERVAL=1000, INACTIVE_HERO_DELAY=int(10), # для неактивных героев замедлять время в N раз TT_DIARY_ENTRY_POINT='http://localhost:10001/', MAX_HERO_DESCRIPTION_LENGTH=10000, REMOVE_HERO_DELAY=10*60)

44.68

120

0.389884

import smart_imports smart_imports.all() NAME_REGEX = r'^[\-\ а-яА-Я«»\'ёЁ]+$' if not django_settings.TESTS_RUNNING else r'^[\-\ а-яА-Я«»\'\,ёЁ]+$' settings = utils_app_settings.app_settings('HEROES', USE_ABILITY_CHANCE=0.1, MESSAGES_LOG_LENGTH=10, DIARY_LOG_LENGTH=50, MIN_PVP_BATTLES=25, UI_CACHING_KEY='hero_ui_%d', UI_CACHING_TIME=10 * 60, UI_CACHING_CONTINUE_TIME=60, UI_CACHING_TIMEOUT=60, DUMP_CACHED_HEROES=False, START_ENERGY_BONUS=10, MAX_HELPS_IN_TURN=10, NAME_REGEX=NAME_REGEX, NAME_SYMBOLS_DESCRITION='пробел, -, а-я, А-Я, «», \' ', NAME_MIN_LENGHT=3, ABILITIES_RESET_TIMEOUT=datetime.timedelta(days=30), UNLOAD_TIMEOUT=c.TURN_DELTA * 3, RARE_OPERATIONS_INTERVAL=1000, INACTIVE_HERO_DELAY=int(10), # для неактивных героев замедлять время в N раз TT_DIARY_ENTRY_POINT='http://localhost:10001/', MAX_HERO_DESCRIPTION_LENGTH=10000, REMOVE_HERO_DELAY=10*60)

true

1c4579efb456751f3e85a187b14430807fac4cfc

1,051

py

Python

solutions/093.restore-ip-addresses/restore-ip-addresses.py

wangsongiam/leetcode

96ff21bca1871816ae51fccb1fa13587b378dc50

[ "MIT" ]

3

2018-11-25T15:19:57.000Z

2019-09-28T03:01:11.000Z

solutions/093.restore-ip-addresses/restore-ip-addresses.py

casprwang/leetcode

96ff21bca1871816ae51fccb1fa13587b378dc50

[ "MIT" ]

null

solutions/093.restore-ip-addresses/restore-ip-addresses.py

casprwang/leetcode

96ff21bca1871816ae51fccb1fa13587b378dc50

[ "MIT" ]

3

2018-02-11T20:23:44.000Z

2020-06-05T15:39:56.000Z

class Solution: def restoreIpAddresses(self, s): """ :type s: str :rtype: List[str] """ ret = [] def traverse(pos, cnt, tmp): print(tmp) nonlocal ret, s if cnt == 0: if not s[pos:]: return if len(s[pos:]) > 1 and s[pos:][0] == '0': return if int(s[pos:]) < 256 and int(s[pos:]) > -1: ret.append(tmp + s[pos:]) return if (cnt + 1) * 3 < len(s) - pos: return for i in range(1, 4): # 1 2 3 if pos + i >= len(s): return if len(s[pos:pos+i]) > 1 and s[pos:pos+i][0] == '0': continue if int(s[pos:pos+i]) < 0 or int(s[pos:pos+i]) > 255 and s[pos:pos+i][0] != '0': continue traverse(pos + i, cnt - 1, tmp + s[pos:pos+i] + '.') traverse(0, 3, '') return ret

26.948718

95

0.358706

class Solution: def restoreIpAddresses(self, s): ret = [] def traverse(pos, cnt, tmp): print(tmp) nonlocal ret, s if cnt == 0: if not s[pos:]: return if len(s[pos:]) > 1 and s[pos:][0] == '0': return if int(s[pos:]) < 256 and int(s[pos:]) > -1: ret.append(tmp + s[pos:]) return if (cnt + 1) * 3 < len(s) - pos: return for i in range(1, 4): if pos + i >= len(s): return if len(s[pos:pos+i]) > 1 and s[pos:pos+i][0] == '0': continue if int(s[pos:pos+i]) < 0 or int(s[pos:pos+i]) > 255 and s[pos:pos+i][0] != '0': continue traverse(pos + i, cnt - 1, tmp + s[pos:pos+i] + '.') traverse(0, 3, '') return ret

true

1c457a9117673b494d492a9f4ab781bd3957996b

1,632

py

Python

Data Scientist Career Path/12. Foundations of Machine Learning Unsupervised Learning/2. KMeans++/1. intro.py

myarist/Codecademy

2ba0f104bc67ab6ef0f8fb869aa12aa02f5f1efb

[ "MIT" ]

23

2021-06-06T15:35:55.000Z

2022-03-21T06:53:42.000Z

Data Scientist Career Path/12. Foundations of Machine Learning Unsupervised Learning/2. KMeans++/1. intro.py

shivaniverma1/Data-Scientist

f82939a411484311171465591455880c8e354750

[ "MIT" ]

null

Data Scientist Career Path/12. Foundations of Machine Learning Unsupervised Learning/2. KMeans++/1. intro.py

shivaniverma1/Data-Scientist

f82939a411484311171465591455880c8e354750

[ "MIT" ]

9

2021-06-08T01:32:04.000Z

2022-03-18T15:38:09.000Z

import codecademylib3_seaborn import matplotlib.pyplot as plt import numpy as np import pandas as pd from sklearn.cluster import KMeans import random import timeit mu = 1 std = 0.5 np.random.seed(100) xs = np.append(np.append(np.append(np.random.normal(0.25,std,100), np.random.normal(0.75,std,100)), np.random.normal(0.25,std,100)), np.random.normal(0.75,std,100)) ys = np.append(np.append(np.append(np.random.normal(0.25,std,100), np.random.normal(0.25,std,100)), np.random.normal(0.75,std,100)), np.random.normal(0.75,std,100)) values = list(zip(xs, ys)) model = KMeans(init='random', n_clusters=2) results = model.fit_predict(values) print("The inertia of model that randomly initialized centroids is " + str(model.inertia_)) colors = ['#6400e4', '#ffc740'] plt.subplot(211) for i in range(2): points = np.array([values[j] for j in range(len(values)) if results[j] == i]) plt.scatter(points[:, 0], points[:, 1], c=colors[i], alpha=0.6) plt.title('Codecademy Mobile Feedback - Centroids Initialized Randomly') plt.xlabel('Learn Python') plt.ylabel('Learn SQL') plt.subplot(212) model = KMeans( n_clusters=2) results = model.fit_predict(values) print("The inertia of model that initialized the centroids using KMeans++ is " + str(model.inertia_)) colors = ['#6400e4', '#ffc740'] for i in range(2): points = np.array([values[j] for j in range(len(values)) if results[j] == i]) plt.scatter(points[:, 0], points[:, 1], c=colors[i], alpha=0.6) plt.title('Codecademy Mobile Feedback - Centroids Initialized Using KMeans++') plt.xlabel('Learn Python') plt.ylabel('Learn SQL') plt.tight_layout() plt.show()

27.2

164

0.712623

import codecademylib3_seaborn import matplotlib.pyplot as plt import numpy as np import pandas as pd from sklearn.cluster import KMeans import random import timeit mu = 1 std = 0.5 np.random.seed(100) xs = np.append(np.append(np.append(np.random.normal(0.25,std,100), np.random.normal(0.75,std,100)), np.random.normal(0.25,std,100)), np.random.normal(0.75,std,100)) ys = np.append(np.append(np.append(np.random.normal(0.25,std,100), np.random.normal(0.25,std,100)), np.random.normal(0.75,std,100)), np.random.normal(0.75,std,100)) values = list(zip(xs, ys)) model = KMeans(init='random', n_clusters=2) results = model.fit_predict(values) print("The inertia of model that randomly initialized centroids is " + str(model.inertia_)) colors = ['#6400e4', '#ffc740'] plt.subplot(211) for i in range(2): points = np.array([values[j] for j in range(len(values)) if results[j] == i]) plt.scatter(points[:, 0], points[:, 1], c=colors[i], alpha=0.6) plt.title('Codecademy Mobile Feedback - Centroids Initialized Randomly') plt.xlabel('Learn Python') plt.ylabel('Learn SQL') plt.subplot(212) model = KMeans( n_clusters=2) results = model.fit_predict(values) print("The inertia of model that initialized the centroids using KMeans++ is " + str(model.inertia_)) colors = ['#6400e4', '#ffc740'] for i in range(2): points = np.array([values[j] for j in range(len(values)) if results[j] == i]) plt.scatter(points[:, 0], points[:, 1], c=colors[i], alpha=0.6) plt.title('Codecademy Mobile Feedback - Centroids Initialized Using KMeans++') plt.xlabel('Learn Python') plt.ylabel('Learn SQL') plt.tight_layout() plt.show()

true

1c457b258f46e8b97aa913da1acea83fba03eaed

944

py

Python

rrpython/tests/types/test_str.py

afoolsbag/rrPython

cb4d376b7c02e39d4e88163f272456ebb9eeafc9

[ "Unlicense" ]

null

rrpython/tests/types/test_str.py

afoolsbag/rrPython

cb4d376b7c02e39d4e88163f272456ebb9eeafc9

[ "Unlicense" ]

null

rrpython/tests/types/test_str.py

afoolsbag/rrPython

cb4d376b7c02e39d4e88163f272456ebb9eeafc9

[ "Unlicense" ]

null

#!/usr/bin/env python3 # coding: utf-8 r""" 字符串类型。 :: +-> Container: obj.__contains__(self, item) # item in obj | +-> Sized: obj.__len__(self) # len(obj) | +-> Iterable: obj.__iter__(self) # iter(obj) | +-> Collection | | +-> Iterable: obj.__iter__(self) # iter(obj) | | +-> Reversible: obj.__reversed__(self) # reversed(obj) | +-> Sequence: obj.__getitem__(self, index) # obj[index] | obj.count(self, value) | obj.index(self, value, start=0, stop=None) | str Notes ----- - `字符串类型 <https://docs.python.org/zh-cn/3/library/stdtypes.html#text-sequence-type-str>`_ """ __version__ = '2020.09.27' __since__ = '2020.09.24' __author__ = 'zhengrr' __license__ = 'UNLICENSE' from typing import Sequence def test_issubclass() -> None: assert issubclass(str, Sequence)

23.02439

89

0.54661

__version__ = '2020.09.27' __since__ = '2020.09.24' __author__ = 'zhengrr' __license__ = 'UNLICENSE' from typing import Sequence def test_issubclass() -> None: assert issubclass(str, Sequence)

true

1c457bc8969abfb76d85c1df6226dd8f0956c564

13,447

py

Python

lime/optics.py

binggu56/lime

07f60c5105f0bedb11ac389fd671f4f1737a71fe

[ "MIT" ]

4

2020-01-15T11:52:23.000Z

2021-01-05T19:40:36.000Z

lime/optics.py

binggu56/lime

07f60c5105f0bedb11ac389fd671f4f1737a71fe

[ "MIT" ]

null

lime/optics.py

binggu56/lime

07f60c5105f0bedb11ac389fd671f4f1737a71fe

[ "MIT" ]

3

2020-02-14T07:10:44.000Z

2021-04-14T17:49:45.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Tue Mar 26 17:26:02 2019 @author: binggu """ import numpy as np from scipy.sparse import lil_matrix, csr_matrix, kron, identity, linalg from numpy import sqrt, exp, pi import matplotlib.pyplot as plt from lime.units import au2k, au2ev from lime.fft import fft2 from lime.phys import rect, sinc, dag, interval from lime.style import set_style, imshow from numba import jit class Pulse: def __init__(self, tau, omegac, delay=0., amplitude=0.001, cep=0., beta=0): """ (linearly chirped) Gaussian pulse The positive frequency component reads E = A/2 * exp(-(t-t0)^2/2/T^2) * exp[-i w (t-t0)(1 + beta (t-t0)/T)] A: electric field amplitude T: time delay sigma: duration """ self.delay = delay self.tau = tau self.sigma = tau # for compatibility only self.omegac = omegac # central frequency self.unit = 'au' self.amplitude = amplitude self.cep = cep self.bandwidth = 1./tau self.duration = 2. * tau self.beta = beta # linear chirping rate, dimensionless self.ndim = 1 def envelop(self, t): return np.exp(-(t-self.delay)**2/2./self.tau**2) def spectrum(self, omega): """ Fourier transform of the Gaussian pulse """ omega0 = self.omegac T = self.tau A0 = self.amplitude beta = self.beta # if beta is None: # return A0 * sigma * np.sqrt(2.*np.pi) * np.exp(-(omega-omega0)**2 * sigma**2/2.) # else: a = 0.5/T**2 + 1j * beta * omega0/T return A0 * np.sqrt(np.pi/a) * np.exp(-(omega - omega0)**2/4./a) def field(self, t): ''' electric field ''' return self.efield(t) def efield(self, t): """ Parameters ---------- t : TYPE DESCRIPTION. Returns ------- electric field at time t. """ omegac = self.omegac t0 = self.delay a = self.amplitude tau = self.sigma beta = self.beta # # if beta is None: # return a * np.exp(-(t-delay)**2/2./sigma**2)*np.cos(omegac * (t-delay)) # else: E = a * np.exp(-(t-t0)**2/2./tau**2)*np.exp(-1j * omegac * (t-t0))\ * np.exp(-1j * beta * omegac * (t-t0)**2/tau) return E.real def spectrogram(self, efield): # from tftb.processing import WignerVilleDistribution # wvd = WignerVilleDistribution(z) # w, ts, fs = wvd.run() return # def heaviside(x): # """ # Heaviside function defined in a grid. # returns 0 if x<=0, and 1 if x>0 # """ # x = np.asarray(x) # y = np.zeros(x.shape) # y[x > 0] = 1.0 # return y class Biphoton: def __init__(self, omegap, bw, Te, p=None, q=None, phase_matching='sinc'): """ Class for entangled photon pair. Parameters ---------- omegap: float pump carrier frequency bw: float pump bandwidth p: signal grid q: idler grid phase_matching: str type of phase matching. Default is 'sinc'. A narrowband approxmation is invoked. """ self.omegap = omegap self.pump_bandwidth = bw self.phase_matching = phase_matching self.signal_center_frequency = omegap / 2. self.idler_center_frequency = omegap / 2. self.entanglement_time = Te self.jsa = None self.jta = None self.p = p self.q = q if p is not None: self.dp = interval(p) self.dq = interval(q) self.grid = [p, q] def pump(self, bandwidth): """ pump pulse envelope Parameters ---------- bandwidth Returns ------- """ alpha = np.sqrt(1. / (np.sqrt(2. * np.pi) * bandwidth)) * \ np.exp(-(p + q) ** 2 / 4. / bandwidth ** 2) return alpha def set_grid(self, p, q): self.p = p self.q = q return def get_jsa(self): """ Returns ------- jsa: array joint spectral amplitude """ p = self.p q = self.q bw = self.pump_bandwidth self.jsa = _jsa(p, q, bw, model=self.phase_matching, Te=self.entanglement_time) return self.jsa def get_jta(self): """ Compute the joint temporal amplitude J(ts, ti) over a temporal meshgrid. Returns ------- ts: 1d array signal time grid ti: 1d array idler temporal grid jta: 2d array joint temporal amplitude """ p = self.p q = self.q dp = p[1] - p[0] dq = q[1] - q[0] if self.jsa is not None: ts, ti, jta = fft2(self.jsa, dp, dq) self.jta = jta return ts, ti, jta else: raise ValueError('jsa is None. Call get_jsa() first.') def jta(self, ts, ti): return def detect(self): """ two-photon detection amplitude in a temporal grid defined by the spectral grid. Returns ------- t1: 1d array t2: 1d array d: detection amplitude in the temporal grid (t1, t2) """ if self.jsa is None: raise ValueError('Please call get_jsa() to compute the jsa first.') bw = self.pump_bandwidth omega_s = self.signal_center_frequency omega_i = self.idler_center_frequency p = self.p q = self.q dp = p[1] - p[0] dq = q[1] - q[0] return _detection_amplitude(self.jsa, omega_s, omega_i, dp, dq) def detect_si(self): pass def detect_is(self): pass def g2(self): pass def bandwidth(self, which='signal'): """ Compute the bandwidth of the signal/idler mode Parameters ---------- which : TYPE, optional DESCRIPTION. The default is 'signal'. Returns ------- None. """ p, q = self.p, self.q dp = interval(p) dq = interval(q) f = self.jsa if which == 'signal': rho = rdm(f, dq, which='x') sigma = sqrt(rho.diagonal().dot(p**2) * dp) elif which == 'idler': rho = rdm(f, dp, which='y') sigma = sqrt(rho.diagonal().dot(q**2) * dq) return sigma def plt_jsa(self, xlabel=None, ylabel=None, fname=None): if self.jsa is None: self.get_jsa() plt, ax = imshow(self.p * au2ev, self.q * au2ev, np.abs(self.jsa)) if xlabel is not None: ax.set_xlabel(xlabel) if ylabel is not None: ax.set_xlabel(ylabel) if fname is not None: plt.savefig(fname) plt.show() return ax def rdm(self, which='signal'): if which == 'signal': return rdm(self.jsa, dy=self.dq, which='x') def jta(t2, t1, omegap, sigmap, Te): """ Analytical form for the joint temporal amplitude for SPDC type-II two-photon state. Note that two single-photon electric field prefactors are neglected. Parameters ---------- t2 : TYPE DESCRIPTION. t1 : TYPE DESCRIPTION. Returns ------- None. """ omegas = omegap/2. omegai = omegap/2. tau = t2 - t1 amp = sqrt(sigmap/Te) * (2.*pi)**(3./4) * \ rect(tau/2./Te) * exp(-sigmap**2*(t1+t2)**2/4.) *\ exp(-1j * omegas * t1 - 1j*omegai * t2) return amp def rdm(f, dx=1, dy=1, which='x'): ''' Compute the reduced density matrix by tracing out the other dof for a 2D wavefunction Parameters ---------- f : 2D array 2D wavefunction dx : float, optional DESCRIPTION. The default is 1. dy : float, optional DESCRIPTION. The default is 1. which: str indicator which rdm is required. Default is 'x'. Returns ------- rho1 : TYPE Reduced density matrix ''' if which == 'x': rho = f.dot(dag(f)) * dy elif which == 'y': rho = f.T.dot(np.conj(f)) * dx else: raise ValueError('The argument which can only be x or y.') return rho def _jsa(p, q, pump_bw, model='sinc', Te=None): ''' Construct the joint spectral amplitude Parameters ---------- p : 1d array signal frequency (detuning from the center frequency) q : 1d array idler frequency pump_bw : float pump bandwidth sm : float 1/entanglement time Te : float Entanglement time. Returns ------- jsa : TYPE DESCRIPTION. ''' P, Q = np.meshgrid(p, q) sigma_plus = pump_bw sigma_minus = 1. / Te # pump envelope alpha = np.sqrt(1. / (np.sqrt(2. * np.pi) * sigma_plus)) * \ np.exp(-(P + Q) ** 2 / 4. / sigma_plus ** 2) # phase-matching function if model == 'Gaussian': beta = np.sqrt(1. / np.sqrt(2. * np.pi) / sigma_minus) * \ np.exp(-(P - Q) ** 2 / 4. / sigma_minus ** 2) jsa = sqrt(2) * alpha * beta elif model == 'sinc': beta = sqrt(0.5 * Te / np.pi) * sinc(Te * (P - Q) / 4.) # const = np.trace(dag(f).dot(f))*dq*dp jsa = alpha * beta return jsa def hom(p, q, f, tau): """ HOM coincidence probability Parameters ---------- p q f tau method: str "brute": directly integrating the JSA over the frequency grid "schmidt": compute the signal using the Schmidt modes of the entangled light nmodes Returns ------- prob: 1d array coincidence probability """ dp = interval(p) dq = interval(q) P, Q = np.meshgrid(p, q) prob = np.zeros(len(tau)) for j in range(len(tau)): t = tau[j] prob[j] = 0.5 - 0.5 * np.sum(f.conj() * f.T * np.exp(1j * (P - Q) * t)).real * dq*dp return prob def hom_schmidt(p, q, f, method='rdm', nmodes=5): """ HOM signal with Schmidt modes Parameters ---------- p q f nmodes Returns ------- """ dp = interval(p) dq = interval(q) # schmidt decompose the JSA s, phi, chi = schmidt_decompose(f, dp, dq, method=method, nmodes=nmodes) prob = np.zeros(len(tau)) for j in range(len(tau)): t = tau[j] for a in range(nmodes): for b in range(nmodes): tmp1 = (phi[:,a].conj() * chi[:, b] * np.exp(1j * p * t)).sum() * dp tmp2 = (phi[:,b] * chi[:, a].conj() * np.exp(-1j * q * t)).sum() * dq prob[j] += -2. * np.real(s[a] * s[b] * tmp1 * tmp2) prob = 0.5 + prob/4. return prob def schmidt_decompose(f, dp, dq, nmodes=5, method='rdm'): """ kernel method f: 2D array, input function to be decomposed nmodes: int number of modes to be kept method: str rdm or svd """ if method == 'rdm': kernel1 = f.dot(dag(f)) * dq * dp kernel2 = f.T.dot(f.conj()) * dp * dq print('c: Schmidt coefficients') s, phi = np.linalg.eig(kernel1) s1, psi = np.linalg.eig(kernel2) phi /= np.sqrt(dp) psi /= np.sqrt(dq) elif method == 'svd': raise NotImplementedError return np.sqrt(s[:nmodes]), phi[:, :nmodes], psi[:, :nmodes] def _detection_amplitude(jsa, omega1, omega2, dp, dq): ''' Detection amplitude <0|E(t)E(t')|Phi> t, t' are defined on a 2D grid used in the FFT, E(t) = Es(t) + Ei(t) is the total electric field operator. This contains two amplitudes corresponding to two different ordering of photon interactions <0|T Ei(t)Es(t')|Phi> + <0|T Es(t)Ei(t')|Phi> The t, t' are defined relative to t0, i.e, they are temporal durations from t0. Parameters ---------- jsa : TYPE DESCRIPTION. m : TYPE DESCRIPTION. n : TYPE DESCRIPTION. omega1 : float central frequency of signal beam omega2 : float central frequency of idler beam Returns ------- d : TYPE DESCRIPTION. ''' t1, t2, jta = fft2(jsa, dp, dq) dt2 = t2[1] - t2[0] T1, T2 = np.meshgrid(t1, t2) # detection amplitude d(t1, t2) ~ JTA(t2, t1) d = np.exp(-1j * omega2 * T1 - 1j * omega1 * T2) * \ np.sqrt(omega1 * omega2) * jta.T + \ np.exp(-1j * omega1 * T1 - 1j * omega2 * T2) * \ np.sqrt(omega1 * omega2) * jta # amp = np.einsum('ij, ij -> i', d, heaviside(T1 - T2) * \ # np.exp(-1j * gap20 * (T1-T2))) * dt2 return t1, t2, d if __name__ == '__main__': from lime.units import au2ev, au2fs p = np.linspace(-2, 2, 128) / au2ev q = p epp = Biphoton(omegap=3 / au2ev, bw=0.2 / au2ev, Te=10/au2fs, p=p, q=q) JSA = epp.get_jsa() # epp.plt_jsa() # t1, t2, d = epp.detect() tau = np.linspace(-10, 10)/au2fs prob = hom(p, q, JSA, tau) fig, ax = plt.subplots() ax.plot(tau, prob) plt.show()

22.791525

93

0.512605

import numpy as np from scipy.sparse import lil_matrix, csr_matrix, kron, identity, linalg from numpy import sqrt, exp, pi import matplotlib.pyplot as plt from lime.units import au2k, au2ev from lime.fft import fft2 from lime.phys import rect, sinc, dag, interval from lime.style import set_style, imshow from numba import jit class Pulse: def __init__(self, tau, omegac, delay=0., amplitude=0.001, cep=0., beta=0): self.delay = delay self.tau = tau self.sigma = tau self.omegac = omegac self.unit = 'au' self.amplitude = amplitude self.cep = cep self.bandwidth = 1./tau self.duration = 2. * tau self.beta = beta self.ndim = 1 def envelop(self, t): return np.exp(-(t-self.delay)**2/2./self.tau**2) def spectrum(self, omega): omega0 = self.omegac T = self.tau A0 = self.amplitude beta = self.beta a = 0.5/T**2 + 1j * beta * omega0/T return A0 * np.sqrt(np.pi/a) * np.exp(-(omega - omega0)**2/4./a) def field(self, t): return self.efield(t) def efield(self, t): omegac = self.omegac t0 = self.delay a = self.amplitude tau = self.sigma beta = self.beta E = a * np.exp(-(t-t0)**2/2./tau**2)*np.exp(-1j * omegac * (t-t0))\ * np.exp(-1j * beta * omegac * (t-t0)**2/tau) return E.real def spectrogram(self, efield): return # Heaviside function defined in a grid. # returns 0 if x<=0, and 1 if x>0 # """ class Biphoton: def __init__(self, omegap, bw, Te, p=None, q=None, phase_matching='sinc'): self.omegap = omegap self.pump_bandwidth = bw self.phase_matching = phase_matching self.signal_center_frequency = omegap / 2. self.idler_center_frequency = omegap / 2. self.entanglement_time = Te self.jsa = None self.jta = None self.p = p self.q = q if p is not None: self.dp = interval(p) self.dq = interval(q) self.grid = [p, q] def pump(self, bandwidth): alpha = np.sqrt(1. / (np.sqrt(2. * np.pi) * bandwidth)) * \ np.exp(-(p + q) ** 2 / 4. / bandwidth ** 2) return alpha def set_grid(self, p, q): self.p = p self.q = q return def get_jsa(self): p = self.p q = self.q bw = self.pump_bandwidth self.jsa = _jsa(p, q, bw, model=self.phase_matching, Te=self.entanglement_time) return self.jsa def get_jta(self): p = self.p q = self.q dp = p[1] - p[0] dq = q[1] - q[0] if self.jsa is not None: ts, ti, jta = fft2(self.jsa, dp, dq) self.jta = jta return ts, ti, jta else: raise ValueError('jsa is None. Call get_jsa() first.') def jta(self, ts, ti): return def detect(self): if self.jsa is None: raise ValueError('Please call get_jsa() to compute the jsa first.') bw = self.pump_bandwidth omega_s = self.signal_center_frequency omega_i = self.idler_center_frequency p = self.p q = self.q dp = p[1] - p[0] dq = q[1] - q[0] return _detection_amplitude(self.jsa, omega_s, omega_i, dp, dq) def detect_si(self): pass def detect_is(self): pass def g2(self): pass def bandwidth(self, which='signal'): p, q = self.p, self.q dp = interval(p) dq = interval(q) f = self.jsa if which == 'signal': rho = rdm(f, dq, which='x') sigma = sqrt(rho.diagonal().dot(p**2) * dp) elif which == 'idler': rho = rdm(f, dp, which='y') sigma = sqrt(rho.diagonal().dot(q**2) * dq) return sigma def plt_jsa(self, xlabel=None, ylabel=None, fname=None): if self.jsa is None: self.get_jsa() plt, ax = imshow(self.p * au2ev, self.q * au2ev, np.abs(self.jsa)) if xlabel is not None: ax.set_xlabel(xlabel) if ylabel is not None: ax.set_xlabel(ylabel) if fname is not None: plt.savefig(fname) plt.show() return ax def rdm(self, which='signal'): if which == 'signal': return rdm(self.jsa, dy=self.dq, which='x') def jta(t2, t1, omegap, sigmap, Te): omegas = omegap/2. omegai = omegap/2. tau = t2 - t1 amp = sqrt(sigmap/Te) * (2.*pi)**(3./4) * \ rect(tau/2./Te) * exp(-sigmap**2*(t1+t2)**2/4.) *\ exp(-1j * omegas * t1 - 1j*omegai * t2) return amp def rdm(f, dx=1, dy=1, which='x'): if which == 'x': rho = f.dot(dag(f)) * dy elif which == 'y': rho = f.T.dot(np.conj(f)) * dx else: raise ValueError('The argument which can only be x or y.') return rho def _jsa(p, q, pump_bw, model='sinc', Te=None): P, Q = np.meshgrid(p, q) sigma_plus = pump_bw sigma_minus = 1. / Te alpha = np.sqrt(1. / (np.sqrt(2. * np.pi) * sigma_plus)) * \ np.exp(-(P + Q) ** 2 / 4. / sigma_plus ** 2) if model == 'Gaussian': beta = np.sqrt(1. / np.sqrt(2. * np.pi) / sigma_minus) * \ np.exp(-(P - Q) ** 2 / 4. / sigma_minus ** 2) jsa = sqrt(2) * alpha * beta elif model == 'sinc': beta = sqrt(0.5 * Te / np.pi) * sinc(Te * (P - Q) / 4.) jsa = alpha * beta return jsa def hom(p, q, f, tau): dp = interval(p) dq = interval(q) P, Q = np.meshgrid(p, q) prob = np.zeros(len(tau)) for j in range(len(tau)): t = tau[j] prob[j] = 0.5 - 0.5 * np.sum(f.conj() * f.T * np.exp(1j * (P - Q) * t)).real * dq*dp return prob def hom_schmidt(p, q, f, method='rdm', nmodes=5): dp = interval(p) dq = interval(q) s, phi, chi = schmidt_decompose(f, dp, dq, method=method, nmodes=nmodes) prob = np.zeros(len(tau)) for j in range(len(tau)): t = tau[j] for a in range(nmodes): for b in range(nmodes): tmp1 = (phi[:,a].conj() * chi[:, b] * np.exp(1j * p * t)).sum() * dp tmp2 = (phi[:,b] * chi[:, a].conj() * np.exp(-1j * q * t)).sum() * dq prob[j] += -2. * np.real(s[a] * s[b] * tmp1 * tmp2) prob = 0.5 + prob/4. return prob def schmidt_decompose(f, dp, dq, nmodes=5, method='rdm'): if method == 'rdm': kernel1 = f.dot(dag(f)) * dq * dp kernel2 = f.T.dot(f.conj()) * dp * dq print('c: Schmidt coefficients') s, phi = np.linalg.eig(kernel1) s1, psi = np.linalg.eig(kernel2) phi /= np.sqrt(dp) psi /= np.sqrt(dq) elif method == 'svd': raise NotImplementedError return np.sqrt(s[:nmodes]), phi[:, :nmodes], psi[:, :nmodes] def _detection_amplitude(jsa, omega1, omega2, dp, dq): t1, t2, jta = fft2(jsa, dp, dq) dt2 = t2[1] - t2[0] T1, T2 = np.meshgrid(t1, t2) d = np.exp(-1j * omega2 * T1 - 1j * omega1 * T2) * \ np.sqrt(omega1 * omega2) * jta.T + \ np.exp(-1j * omega1 * T1 - 1j * omega2 * T2) * \ np.sqrt(omega1 * omega2) * jta return t1, t2, d if __name__ == '__main__': from lime.units import au2ev, au2fs p = np.linspace(-2, 2, 128) / au2ev q = p epp = Biphoton(omegap=3 / au2ev, bw=0.2 / au2ev, Te=10/au2fs, p=p, q=q) JSA = epp.get_jsa() tau = np.linspace(-10, 10)/au2fs prob = hom(p, q, JSA, tau) fig, ax = plt.subplots() ax.plot(tau, prob) plt.show()

true

1c457ce30654b4e60fe6ac59186a1c9d26859b54

10,225

py

Python

glance_docker/glance/common/auth.py

tobegit3hub/dockerized-software

3781bc1145b6fbb8d5fa2e2eaeaa3aa138a69632

[ "Apache-2.0" ]

null

glance_docker/glance/common/auth.py

tobegit3hub/dockerized-software

3781bc1145b6fbb8d5fa2e2eaeaa3aa138a69632

[ "Apache-2.0" ]

null

glance_docker/glance/common/auth.py

tobegit3hub/dockerized-software

3781bc1145b6fbb8d5fa2e2eaeaa3aa138a69632

[ "Apache-2.0" ]

null

# Copyright 2011 OpenStack Foundation # 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. """ This auth module is intended to allow OpenStack client-tools to select from a variety of authentication strategies, including NoAuth (the default), and Keystone (an identity management system). > auth_plugin = AuthPlugin(creds) > auth_plugin.authenticate() > auth_plugin.auth_token abcdefg > auth_plugin.management_url http://service_endpoint/ """ import httplib2 from oslo_log import log as logging from oslo_serialization import jsonutils # NOTE(jokke): simplified transition to py3, behaves like py2 xrange from six.moves import range import six.moves.urllib.parse as urlparse from glance.common import exception from glance import i18n LOG = logging.getLogger(__name__) _ = i18n._ class BaseStrategy(object): def __init__(self): self.auth_token = None # TODO(sirp): Should expose selecting public/internal/admin URL. self.management_url = None def authenticate(self): raise NotImplementedError @property def is_authenticated(self): raise NotImplementedError @property def strategy(self): raise NotImplementedError class NoAuthStrategy(BaseStrategy): def authenticate(self): pass @property def is_authenticated(self): return True @property def strategy(self): return 'noauth' class KeystoneStrategy(BaseStrategy): MAX_REDIRECTS = 10 def __init__(self, creds, insecure=False, configure_via_auth=True): self.creds = creds self.insecure = insecure self.configure_via_auth = configure_via_auth super(KeystoneStrategy, self).__init__() def check_auth_params(self): # Ensure that supplied credential parameters are as required for required in ('username', 'password', 'auth_url', 'strategy'): if self.creds.get(required) is None: raise exception.MissingCredentialError(required=required) if self.creds['strategy'] != 'keystone': raise exception.BadAuthStrategy(expected='keystone', received=self.creds['strategy']) # For v2.0 also check tenant is present if self.creds['auth_url'].rstrip('/').endswith('v2.0'): if self.creds.get("tenant") is None: raise exception.MissingCredentialError(required='tenant') def authenticate(self): """Authenticate with the Keystone service. There are a few scenarios to consider here: 1. Which version of Keystone are we using? v1 which uses headers to pass the credentials, or v2 which uses a JSON encoded request body? 2. Keystone may respond back with a redirection using a 305 status code. 3. We may attempt a v1 auth when v2 is what's called for. In this case, we rewrite the url to contain /v2.0/ and retry using the v2 protocol. """ def _authenticate(auth_url): # If OS_AUTH_URL is missing a trailing slash add one if not auth_url.endswith('/'): auth_url += '/' token_url = urlparse.urljoin(auth_url, "tokens") # 1. Check Keystone version is_v2 = auth_url.rstrip('/').endswith('v2.0') if is_v2: self._v2_auth(token_url) else: self._v1_auth(token_url) self.check_auth_params() auth_url = self.creds['auth_url'] for _ in range(self.MAX_REDIRECTS): try: _authenticate(auth_url) except exception.AuthorizationRedirect as e: # 2. Keystone may redirect us auth_url = e.url except exception.AuthorizationFailure: # 3. In some configurations nova makes redirection to # v2.0 keystone endpoint. Also, new location does not # contain real endpoint, only hostname and port. if 'v2.0' not in auth_url: auth_url = urlparse.urljoin(auth_url, 'v2.0/') else: # If we successfully auth'd, then memorize the correct auth_url # for future use. self.creds['auth_url'] = auth_url break else: # Guard against a redirection loop raise exception.MaxRedirectsExceeded(redirects=self.MAX_REDIRECTS) def _v1_auth(self, token_url): creds = self.creds headers = { 'X-Auth-User': creds['username'], 'X-Auth-Key': creds['password'] } tenant = creds.get('tenant') if tenant: headers['X-Auth-Tenant'] = tenant resp, resp_body = self._do_request(token_url, 'GET', headers=headers) def _management_url(self, resp): for url_header in ('x-image-management-url', 'x-server-management-url', 'x-glance'): try: return resp[url_header] except KeyError as e: not_found = e raise not_found if resp.status in (200, 204): try: if self.configure_via_auth: self.management_url = _management_url(self, resp) self.auth_token = resp['x-auth-token'] except KeyError: raise exception.AuthorizationFailure() elif resp.status == 305: raise exception.AuthorizationRedirect(uri=resp['location']) elif resp.status == 400: raise exception.AuthBadRequest(url=token_url) elif resp.status == 401: raise exception.NotAuthenticated() elif resp.status == 404: raise exception.AuthUrlNotFound(url=token_url) else: raise Exception(_('Unexpected response: %s') % resp.status) def _v2_auth(self, token_url): creds = self.creds creds = { "auth": { "tenantName": creds['tenant'], "passwordCredentials": { "username": creds['username'], "password": creds['password'] } } } headers = {'Content-Type': 'application/json'} req_body = jsonutils.dumps(creds) resp, resp_body = self._do_request( token_url, 'POST', headers=headers, body=req_body) if resp.status == 200: resp_auth = jsonutils.loads(resp_body)['access'] creds_region = self.creds.get('region') if self.configure_via_auth: endpoint = get_endpoint(resp_auth['serviceCatalog'], endpoint_region=creds_region) self.management_url = endpoint self.auth_token = resp_auth['token']['id'] elif resp.status == 305: raise exception.RedirectException(resp['location']) elif resp.status == 400: raise exception.AuthBadRequest(url=token_url) elif resp.status == 401: raise exception.NotAuthenticated() elif resp.status == 404: raise exception.AuthUrlNotFound(url=token_url) else: raise Exception(_('Unexpected response: %s') % resp.status) @property def is_authenticated(self): return self.auth_token is not None @property def strategy(self): return 'keystone' def _do_request(self, url, method, headers=None, body=None): headers = headers or {} conn = httplib2.Http() conn.force_exception_to_status_code = True conn.disable_ssl_certificate_validation = self.insecure headers['User-Agent'] = 'glance-client' resp, resp_body = conn.request(url, method, headers=headers, body=body) return resp, resp_body def get_plugin_from_strategy(strategy, creds=None, insecure=False, configure_via_auth=True): if strategy == 'noauth': return NoAuthStrategy() elif strategy == 'keystone': return KeystoneStrategy(creds, insecure, configure_via_auth=configure_via_auth) else: raise Exception(_("Unknown auth strategy '%s'") % strategy) def get_endpoint(service_catalog, service_type='image', endpoint_region=None, endpoint_type='publicURL'): """ Select an endpoint from the service catalog We search the full service catalog for services matching both type and region. If the client supplied no region then any 'image' endpoint is considered a match. There must be one -- and only one -- successful match in the catalog, otherwise we will raise an exception. """ endpoint = None for service in service_catalog: s_type = None try: s_type = service['type'] except KeyError: msg = _('Encountered service with no "type": %s') % s_type LOG.warn(msg) continue if s_type == service_type: for ep in service['endpoints']: if endpoint_region is None or endpoint_region == ep['region']: if endpoint is not None: # This is a second match, abort raise exception.RegionAmbiguity(region=endpoint_region) endpoint = ep if endpoint and endpoint.get(endpoint_type): return endpoint[endpoint_type] else: raise exception.NoServiceEndpoint()

34.897611

79

0.603619

import httplib2 from oslo_log import log as logging from oslo_serialization import jsonutils from six.moves import range import six.moves.urllib.parse as urlparse from glance.common import exception from glance import i18n LOG = logging.getLogger(__name__) _ = i18n._ class BaseStrategy(object): def __init__(self): self.auth_token = None self.management_url = None def authenticate(self): raise NotImplementedError @property def is_authenticated(self): raise NotImplementedError @property def strategy(self): raise NotImplementedError class NoAuthStrategy(BaseStrategy): def authenticate(self): pass @property def is_authenticated(self): return True @property def strategy(self): return 'noauth' class KeystoneStrategy(BaseStrategy): MAX_REDIRECTS = 10 def __init__(self, creds, insecure=False, configure_via_auth=True): self.creds = creds self.insecure = insecure self.configure_via_auth = configure_via_auth super(KeystoneStrategy, self).__init__() def check_auth_params(self): for required in ('username', 'password', 'auth_url', 'strategy'): if self.creds.get(required) is None: raise exception.MissingCredentialError(required=required) if self.creds['strategy'] != 'keystone': raise exception.BadAuthStrategy(expected='keystone', received=self.creds['strategy']) if self.creds['auth_url'].rstrip('/').endswith('v2.0'): if self.creds.get("tenant") is None: raise exception.MissingCredentialError(required='tenant') def authenticate(self): def _authenticate(auth_url): if not auth_url.endswith('/'): auth_url += '/' token_url = urlparse.urljoin(auth_url, "tokens") is_v2 = auth_url.rstrip('/').endswith('v2.0') if is_v2: self._v2_auth(token_url) else: self._v1_auth(token_url) self.check_auth_params() auth_url = self.creds['auth_url'] for _ in range(self.MAX_REDIRECTS): try: _authenticate(auth_url) except exception.AuthorizationRedirect as e: auth_url = e.url except exception.AuthorizationFailure: if 'v2.0' not in auth_url: auth_url = urlparse.urljoin(auth_url, 'v2.0/') else: # for future use. self.creds['auth_url'] = auth_url break else: # Guard against a redirection loop raise exception.MaxRedirectsExceeded(redirects=self.MAX_REDIRECTS) def _v1_auth(self, token_url): creds = self.creds headers = { 'X-Auth-User': creds['username'], 'X-Auth-Key': creds['password'] } tenant = creds.get('tenant') if tenant: headers['X-Auth-Tenant'] = tenant resp, resp_body = self._do_request(token_url, 'GET', headers=headers) def _management_url(self, resp): for url_header in ('x-image-management-url', 'x-server-management-url', 'x-glance'): try: return resp[url_header] except KeyError as e: not_found = e raise not_found if resp.status in (200, 204): try: if self.configure_via_auth: self.management_url = _management_url(self, resp) self.auth_token = resp['x-auth-token'] except KeyError: raise exception.AuthorizationFailure() elif resp.status == 305: raise exception.AuthorizationRedirect(uri=resp['location']) elif resp.status == 400: raise exception.AuthBadRequest(url=token_url) elif resp.status == 401: raise exception.NotAuthenticated() elif resp.status == 404: raise exception.AuthUrlNotFound(url=token_url) else: raise Exception(_('Unexpected response: %s') % resp.status) def _v2_auth(self, token_url): creds = self.creds creds = { "auth": { "tenantName": creds['tenant'], "passwordCredentials": { "username": creds['username'], "password": creds['password'] } } } headers = {'Content-Type': 'application/json'} req_body = jsonutils.dumps(creds) resp, resp_body = self._do_request( token_url, 'POST', headers=headers, body=req_body) if resp.status == 200: resp_auth = jsonutils.loads(resp_body)['access'] creds_region = self.creds.get('region') if self.configure_via_auth: endpoint = get_endpoint(resp_auth['serviceCatalog'], endpoint_region=creds_region) self.management_url = endpoint self.auth_token = resp_auth['token']['id'] elif resp.status == 305: raise exception.RedirectException(resp['location']) elif resp.status == 400: raise exception.AuthBadRequest(url=token_url) elif resp.status == 401: raise exception.NotAuthenticated() elif resp.status == 404: raise exception.AuthUrlNotFound(url=token_url) else: raise Exception(_('Unexpected response: %s') % resp.status) @property def is_authenticated(self): return self.auth_token is not None @property def strategy(self): return 'keystone' def _do_request(self, url, method, headers=None, body=None): headers = headers or {} conn = httplib2.Http() conn.force_exception_to_status_code = True conn.disable_ssl_certificate_validation = self.insecure headers['User-Agent'] = 'glance-client' resp, resp_body = conn.request(url, method, headers=headers, body=body) return resp, resp_body def get_plugin_from_strategy(strategy, creds=None, insecure=False, configure_via_auth=True): if strategy == 'noauth': return NoAuthStrategy() elif strategy == 'keystone': return KeystoneStrategy(creds, insecure, configure_via_auth=configure_via_auth) else: raise Exception(_("Unknown auth strategy '%s'") % strategy) def get_endpoint(service_catalog, service_type='image', endpoint_region=None, endpoint_type='publicURL'): endpoint = None for service in service_catalog: s_type = None try: s_type = service['type'] except KeyError: msg = _('Encountered service with no "type": %s') % s_type LOG.warn(msg) continue if s_type == service_type: for ep in service['endpoints']: if endpoint_region is None or endpoint_region == ep['region']: if endpoint is not None: # This is a second match, abort raise exception.RegionAmbiguity(region=endpoint_region) endpoint = ep if endpoint and endpoint.get(endpoint_type): return endpoint[endpoint_type] else: raise exception.NoServiceEndpoint()

true

1c457cf430666778cca067fee9e66d2b156178b1

2,193

py

Python

ropgenerator/exploit/syscall/SyscallLinuxX86.py

avltree9798/ropgenerator

c63c81f03e8653dc3911e21300c00003a4224f6a

[ "MIT" ]

1

2021-01-07T13:16:19.000Z

ropgenerator/exploit/syscall/SyscallLinuxX86.py

avltree9798/ropgenerator

c63c81f03e8653dc3911e21300c00003a4224f6a

[ "MIT" ]

null

ropgenerator/exploit/syscall/SyscallLinuxX86.py

avltree9798/ropgenerator

c63c81f03e8653dc3911e21300c00003a4224f6a

[ "MIT" ]

null

# -*- coding:utf-8 -*- # SycallLinuxX86 module: build syscalls for linux on X64 from ropgenerator.exploit.syscall.SyscallGeneric import Syscall, ArgType from ropgenerator.core.Architecture import * mprotect = Syscall('int', 'mprotect', \ [('void*', 'addr'),('size_t','len'),('int','prot')], [ArgType.INT, ArgType.INT, ArgType.INT],\ [RegX86.EBX, RegX86.ECX, RegX86.EDX], [(RegX86.EAX, 0x7d)]) execve = Syscall('int', 'execve', \ [('char*', 'cmd'),('char**','argv'),('char**', 'envp')], [ArgType.STRING, ArgType.INT,ArgType.INT],\ [RegX86.EBX,RegX86.ECX,RegX86.EDX], [(RegX86.EAX, 11)] ) read = Syscall('int', 'read', \ [('unsigned int','fd'),('char*','buf'),('size_t','count')], [ArgType.INT, ArgType.INT_OR_STRING, ArgType.INT], \ [RegX86.EBX,RegX86.ECX,RegX86.EDX], [(RegX86.EAX, 3)]) write = Syscall('int', 'write', \ [('unsigned int','fd'),('const char*','buf'),('size_t','count')], [ArgType.INT, ArgType.INT_OR_STRING, ArgType.INT], \ [RegX86.EBX,RegX86.ECX,RegX86.EDX], [(RegX86.EAX, 4)]) chmod = Syscall('int', 'chmod', \ [('const char*','filename'),('mode_t','mode')], [ArgType.INT_OR_STRING, ArgType.INT], \ [RegX86.EBX, RegX86.ECX], [(RegX86.EAX,15)]) setuid = Syscall('int', 'setuid', \ [('uid_t', 'uid')], [ArgType.INT], \ [RegX86.EBX], [(RegX86.EAX,23)]) # MMAP with flags = MAP_ANONYMOUS (no fd and offset) mmap_anon = Syscall('void*', 'mmap_anon', \ [('unsigned long','addr'),('unsigned long','len'),('unsigned long','prot')],\ [ArgType.INT, ArgType.INT, ArgType.INT], \ [RegX86.EBX,RegX86.ECX,RegX86.EDX], [(RegX86.EAX,9), ('esi', 0x20)], function="mmap") syscalls_list = [mprotect, execve, read, write, chmod, setuid] ## All available syscalls available = dict() for syscall_object in syscalls_list: available[syscall_object.name()] = syscall_object #################### # Useful functions # #################### def is_supported(syscall_name): return (syscall_name in available) def get_syscall(syscall_name): if( not syscall_name in available ): return None return available[syscall_name] def available_syscalls(): global available return available

37.810345

122

0.632011

from ropgenerator.exploit.syscall.SyscallGeneric import Syscall, ArgType from ropgenerator.core.Architecture import * mprotect = Syscall('int', 'mprotect', \ [('void*', 'addr'),('size_t','len'),('int','prot')], [ArgType.INT, ArgType.INT, ArgType.INT],\ [RegX86.EBX, RegX86.ECX, RegX86.EDX], [(RegX86.EAX, 0x7d)]) execve = Syscall('int', 'execve', \ [('char*', 'cmd'),('char**','argv'),('char**', 'envp')], [ArgType.STRING, ArgType.INT,ArgType.INT],\ [RegX86.EBX,RegX86.ECX,RegX86.EDX], [(RegX86.EAX, 11)] ) read = Syscall('int', 'read', \ [('unsigned int','fd'),('char*','buf'),('size_t','count')], [ArgType.INT, ArgType.INT_OR_STRING, ArgType.INT], \ [RegX86.EBX,RegX86.ECX,RegX86.EDX], [(RegX86.EAX, 3)]) write = Syscall('int', 'write', \ [('unsigned int','fd'),('const char*','buf'),('size_t','count')], [ArgType.INT, ArgType.INT_OR_STRING, ArgType.INT], \ [RegX86.EBX,RegX86.ECX,RegX86.EDX], [(RegX86.EAX, 4)]) chmod = Syscall('int', 'chmod', \ [('const char*','filename'),('mode_t','mode')], [ArgType.INT_OR_STRING, ArgType.INT], \ [RegX86.EBX, RegX86.ECX], [(RegX86.EAX,15)]) setuid = Syscall('int', 'setuid', \ [('uid_t', 'uid')], [ArgType.INT], \ [RegX86.EBX], [(RegX86.EAX,23)]) mmap_anon = Syscall('void*', 'mmap_anon', \ [('unsigned long','addr'),('unsigned long','len'),('unsigned long','prot')],\ [ArgType.INT, ArgType.INT, ArgType.INT], \ [RegX86.EBX,RegX86.ECX,RegX86.EDX], [(RegX86.EAX,9), ('esi', 0x20)], function="mmap") syscalls_list = [mprotect, execve, read, write, chmod, setuid] yscall_object in syscalls_list: available[syscall_object.name()] = syscall_object

true

1c457d19c80113b1224bc3ece869c3003a166dee

690

py

Python

molecule/default/tests/test_default.py

dhs-ncats/ansible-role-htop

a7848a00693e9e841e3546d879968704228b47a4

[ "CC0-1.0" ]

null

molecule/default/tests/test_default.py

dhs-ncats/ansible-role-htop

a7848a00693e9e841e3546d879968704228b47a4

[ "CC0-1.0" ]

null

molecule/default/tests/test_default.py

dhs-ncats/ansible-role-htop

a7848a00693e9e841e3546d879968704228b47a4

[ "CC0-1.0" ]

null

"""Module containing the tests for the default scenario.""" # Standard Python Libraries import os # Third-Party Libraries import pytest import testinfra.utils.ansible_runner testinfra_hosts = testinfra.utils.ansible_runner.AnsibleRunner( os.environ["MOLECULE_INVENTORY_FILE"] ).get_hosts("all") @pytest.mark.parametrize("pkg", ["htop"]) def test_packages(host, pkg): """Test that the appropriate packages were installed.""" package = host.package(pkg) assert package.is_installed @pytest.mark.parametrize("file", ["/etc/htoprc"]) def test_files(host, file): """Test that config files were copied over as expected.""" f = host.file(file) assert f.exists

23.793103

63

0.731884

import os import pytest import testinfra.utils.ansible_runner testinfra_hosts = testinfra.utils.ansible_runner.AnsibleRunner( os.environ["MOLECULE_INVENTORY_FILE"] ).get_hosts("all") @pytest.mark.parametrize("pkg", ["htop"]) def test_packages(host, pkg): package = host.package(pkg) assert package.is_installed @pytest.mark.parametrize("file", ["/etc/htoprc"]) def test_files(host, file): f = host.file(file) assert f.exists

true

1c457edb6c9ecbc1d978023d080823ab44d6d1d2

560

py

Python

integration/emulator/test.py

cvlabmiet/master-programming-example

8a4a231ba2b72a93ae14da2c04e17b2ae3fc6651

[ "MIT" ]

null

integration/emulator/test.py

cvlabmiet/master-programming-example

8a4a231ba2b72a93ae14da2c04e17b2ae3fc6651

[ "MIT" ]

null

integration/emulator/test.py

cvlabmiet/master-programming-example

8a4a231ba2b72a93ae14da2c04e17b2ae3fc6651

[ "MIT" ]

null

#!/usr/bin/env python3 import sys, random, array sys.dont_write_bytecode = True from device import Pram, Lram test_vector = list(range(0, 200)) random.shuffle(test_vector) pram = Pram() lram = Lram() lram[:] = bytes(test_vector) pram[:] = b'[u16:200:400]add(u8:0, u8:100)' pram.run(lram) view = memoryview(lram)[200:400].cast('H') error_count = 0 for x in range(len(view)): if view[x] != test_vector[x] + test_vector[x + 100]: print("Error:", x, view[x], test_vector[x], test_vector[x + 100]) error_count += 1 sys.exit(error_count)

20.740741

73

0.664286

import sys, random, array sys.dont_write_bytecode = True from device import Pram, Lram test_vector = list(range(0, 200)) random.shuffle(test_vector) pram = Pram() lram = Lram() lram[:] = bytes(test_vector) pram[:] = b'[u16:200:400]add(u8:0, u8:100)' pram.run(lram) view = memoryview(lram)[200:400].cast('H') error_count = 0 for x in range(len(view)): if view[x] != test_vector[x] + test_vector[x + 100]: print("Error:", x, view[x], test_vector[x], test_vector[x + 100]) error_count += 1 sys.exit(error_count)

true

1c457f19469eb820eb88da2d97435a799d4d316b

1,354

py

Python

crslab/model/__init__.py

Xiaolong-Qi/CRSLab

d507378c86f4996727bf062482e1f224486d4533

[ "MIT" ]

1

2021-01-06T10:39:10.000Z

crslab/model/__init__.py

Xiaolong-Qi/CRSLab

d507378c86f4996727bf062482e1f224486d4533

[ "MIT" ]

null

crslab/model/__init__.py

Xiaolong-Qi/CRSLab

d507378c86f4996727bf062482e1f224486d4533

[ "MIT" ]

null

# @Time : 2020/11/22 # @Author : Kun Zhou # @Email : francis_kun_zhou@163.com # UPDATE: # @Time : 2020/11/24, 2020/12/24 # @Author : Kun Zhou, Xiaolei Wang # @Email : francis_kun_zhou@163.com, wxl1999@foxmail.com from loguru import logger from .conversation import * from .kbrd import * from .kgsf import * from .policy import * from .recommendation import * from .redial import * from .tgredial import * Model_register_table = { 'KGSF': KGSFModel, 'KBRD': KBRDModel, 'TGRec': TGRecModel, 'TGConv': TGConvModel, 'TGPolicy': TGPolicyModel, 'ReDialRec': ReDialRecModel, 'ReDialConv': ReDialConvModel, 'GPT2': GPT2Model, 'Transformer': TransformerModel, 'ConvBERT': ConvBERTModel, 'ProfileBERT': ProfileBERTModel, 'TopicBERT': TopicBERTModel, 'PMI': PMIModel, 'MGCG': MGCGModel, 'BERT': BERTModel, 'SASREC': SASRECModel, 'GRU4REC': GRU4RECModel, 'Popularity': PopularityModel, 'TextCNN': TextCNNModel } def get_model(config, model_name, device, vocab, side_data=None): if model_name in Model_register_table: model = Model_register_table[model_name](config, device, vocab, side_data) logger.info(f'[Build model {model_name}]') return model else: raise NotImplementedError('Model [{}] has not been implemented'.format(model_name))

27.08

91

0.6839

from loguru import logger from .conversation import * from .kbrd import * from .kgsf import * from .policy import * from .recommendation import * from .redial import * from .tgredial import * Model_register_table = { 'KGSF': KGSFModel, 'KBRD': KBRDModel, 'TGRec': TGRecModel, 'TGConv': TGConvModel, 'TGPolicy': TGPolicyModel, 'ReDialRec': ReDialRecModel, 'ReDialConv': ReDialConvModel, 'GPT2': GPT2Model, 'Transformer': TransformerModel, 'ConvBERT': ConvBERTModel, 'ProfileBERT': ProfileBERTModel, 'TopicBERT': TopicBERTModel, 'PMI': PMIModel, 'MGCG': MGCGModel, 'BERT': BERTModel, 'SASREC': SASRECModel, 'GRU4REC': GRU4RECModel, 'Popularity': PopularityModel, 'TextCNN': TextCNNModel } def get_model(config, model_name, device, vocab, side_data=None): if model_name in Model_register_table: model = Model_register_table[model_name](config, device, vocab, side_data) logger.info(f'[Build model {model_name}]') return model else: raise NotImplementedError('Model [{}] has not been implemented'.format(model_name))

true

1c457faa9ac5bd092b0c88919dffda9a035f0f60

8,729

py

Python

ckan_cloud_operator/providers/storage/minio/manager.py

mickeyrouash/ckan-cloud-operator

10e38f13964af30fe57b07e8d8a3b7521ed69cc2

[ "MIT" ]

null

ckan_cloud_operator/providers/storage/minio/manager.py

mickeyrouash/ckan-cloud-operator

10e38f13964af30fe57b07e8d8a3b7521ed69cc2

[ "MIT" ]

null

ckan_cloud_operator/providers/storage/minio/manager.py

mickeyrouash/ckan-cloud-operator

10e38f13964af30fe57b07e8d8a3b7521ed69cc2

[ "MIT" ]

null

#### standard provider code #### # import the correct PROVIDER_SUBMODULE and PROVIDER_ID constants for your provider from .constants import PROVIDER_ID from ..constants import PROVIDER_SUBMODULE # define common provider functions based on the constants from ckan_cloud_operator.providers import manager as providers_manager def _get_resource_name(suffix=None): return providers_manager.get_resource_name(PROVIDER_SUBMODULE, PROVIDER_ID, suffix=suffix) def _get_resource_labels(for_deployment=False, suffix=None): return providers_manager.get_resource_labels(PROVIDER_SUBMODULE, PROVIDER_ID, for_deployment=for_deployment, suffix=suffix) def _get_resource_annotations(suffix=None): return providers_manager.get_resource_annotations(PROVIDER_SUBMODULE, PROVIDER_ID, suffix=suffix) def _set_provider(): providers_manager.set_provider(PROVIDER_SUBMODULE, PROVIDER_ID) def _config_set(key=None, value=None, values=None, namespace=None, is_secret=False, suffix=None): providers_manager.config_set(PROVIDER_SUBMODULE, PROVIDER_ID, key=key, value=value, values=values, namespace=namespace, is_secret=is_secret, suffix=suffix) def _config_get(key=None, default=None, required=False, namespace=None, is_secret=False, suffix=None): return providers_manager.config_get(PROVIDER_SUBMODULE, PROVIDER_ID, key=key, default=default, required=required, namespace=namespace, is_secret=is_secret, suffix=suffix) def _config_interactive_set(default_values, namespace=None, is_secret=False, suffix=None, from_file=False, interactive=False): providers_manager.config_interactive_set(PROVIDER_SUBMODULE, PROVIDER_ID, default_values, namespace, is_secret, suffix, from_file, interactive) ################################ # custom provider code starts here # import os import binascii import yaml import json from ckan_cloud_operator import kubectl from ckan_cloud_operator import logs from ckan_cloud_operator.routers import manager as routers_manager def initialize(interactive=False, storage_suffix=None, use_existing_disk_name=None, dry_run=False): _config_interactive_set({ 'disk-size-gb': None, **({} if storage_suffix else {'router-name': routers_manager.get_default_infra_router_name()}) }, interactive=interactive, suffix=storage_suffix) _apply_secret(storage_suffix=storage_suffix) _apply_deployment( _get_or_create_volume( storage_suffix=storage_suffix, use_existing_disk_name=use_existing_disk_name ), storage_suffix=storage_suffix, dry_run=dry_run ) _apply_service(storage_suffix=storage_suffix, dry_run=dry_run) if not storage_suffix: _update_route(storage_suffix=storage_suffix, dry_run=dry_run) _set_provider() def print_credentials(raw=False, storage_suffix=None): hostname, access_key, secret_key = get_credentials(storage_suffix=storage_suffix) if raw: print(f'https://{hostname} {access_key} {secret_key}') else: print('Minio admin credentials:') print('External Domain: ' + hostname) print('Access Key: ' + access_key) print('Secret Key: ' + secret_key) print('\nto use with minio-client, run the following command:') print(f'mc config host add my-storage https://{hostname} {access_key} {secret_key}') def get_credentials(storage_suffix=None): return [_get_frontend_hostname(storage_suffix=storage_suffix)] + [ _config_get(key, required=True, is_secret=True, suffix=storage_suffix) for key in ['MINIO_ACCESS_KEY', 'MINIO_SECRET_KEY'] ] def _generate_password(l): return binascii.hexlify(os.urandom(l)).decode() def _apply_secret(storage_suffix=None): access_key = _config_get('MINIO_ACCESS_KEY', required=False, is_secret=True, suffix=storage_suffix) or _generate_password(8) secret_key = _config_get('MINIO_SECRET_KEY', required=False, is_secret=True, suffix=storage_suffix) or _generate_password(12) _config_set(values={'MINIO_ACCESS_KEY': access_key, 'MINIO_SECRET_KEY': secret_key}, is_secret=True, suffix=storage_suffix) def _apply_deployment(volume_spec, storage_suffix=None, dry_run=False): node_selector = volume_spec.pop('nodeSelector', None) if node_selector: pod_scheduling = {'nodeSelector': node_selector} else: pod_scheduling = {} container_spec_overrides = _config_get('container-spec-overrides', required=False, default=None, suffix=storage_suffix) kubectl.apply(kubectl.get_deployment( _get_resource_name(suffix=storage_suffix), _get_resource_labels(for_deployment=True, suffix=storage_suffix), { 'replicas': 1, 'revisionHistoryLimit': 10, 'strategy': {'type': 'Recreate', }, 'template': { 'metadata': { 'labels': _get_resource_labels(for_deployment=True, suffix=storage_suffix), 'annotations': _get_resource_annotations(suffix=storage_suffix) }, 'spec': { **pod_scheduling, 'containers': [ { 'name': 'minio', 'image': 'minio/minio', 'args': ['server', '/export'], 'envFrom': [{'secretRef': {'name': _get_resource_name(suffix=storage_suffix)}}], 'ports': [{'containerPort': 9000}], 'volumeMounts': [ { 'name': 'minio-data', 'mountPath': '/export', } ], **(json.loads(container_spec_overrides) if container_spec_overrides else {}) } ], 'volumes': [ dict(volume_spec, name='minio-data') ] } } } ), dry_run=dry_run) def _apply_service(storage_suffix=None, dry_run=False): kubectl.apply(kubectl.get_resource( 'v1', 'Service', _get_resource_name(suffix=storage_suffix), _get_resource_labels(suffix=storage_suffix), spec={ 'ports': [ {'name': '9000', 'port': 9000} ], 'selector': { 'app': _get_resource_labels(for_deployment=True, suffix=storage_suffix)['app'] } } ), dry_run=dry_run) def _get_or_create_volume(storage_suffix=None, use_existing_disk_name=None): disk_size_gb = _config_get('disk-size-gb', required=True, suffix=storage_suffix) volume_spec = _config_get('volume-spec', required=False, suffix=storage_suffix) if volume_spec: volume_spec = yaml.load(volume_spec) else: from ckan_cloud_operator.providers.cluster import manager as cluster_manager volume_spec = cluster_manager.create_volume( disk_size_gb, _get_resource_labels(suffix=storage_suffix), use_existing_disk_name=use_existing_disk_name ) _config_set('volume-spec', yaml.dump(volume_spec, default_flow_style=False), suffix=storage_suffix) return volume_spec def _update_route(storage_suffix=None, dry_run=False): backend_url_target_id = _get_backend_url_target_id(storage_suffix=storage_suffix) router_name = _config_get('router-name', required=True, suffix=storage_suffix) if not routers_manager.get_backend_url_routes(backend_url_target_id): deployment_name = _get_resource_name(suffix=storage_suffix) namespace = _get_namespace() subdomain_route = { 'target-type': 'backend-url', 'target-resource-id': backend_url_target_id, 'backend-url': f'http://{deployment_name}.{namespace}:9000', } if dry_run: logs.info('create_subdomain_route', router_name, subdomain_route) else: routers_manager.create_subdomain_route(router_name, subdomain_route) if not dry_run: routers_manager.update(router_name, wait_ready=True) def _get_namespace(): return 'ckan-cloud' def _get_frontend_hostname(storage_suffix=None): backend_url_target_id = _get_backend_url_target_id(storage_suffix=storage_suffix) routes = routers_manager.get_backend_url_routes(backend_url_target_id) assert storage_suffix or len(routes) == 1 if len(routes) < 1: return 'localhost:9000' else: return routers_manager.get_route_frontend_hostname(routes[0]) def _get_backend_url_target_id(storage_suffix=None): return f'minio-{storage_suffix}' if storage_suffix else 'minio'

44.764103

273

0.680719

perator.providers import manager as providers_manager def _get_resource_name(suffix=None): return providers_manager.get_resource_name(PROVIDER_SUBMODULE, PROVIDER_ID, suffix=suffix) def _get_resource_labels(for_deployment=False, suffix=None): return providers_manager.get_resource_labels(PROVIDER_SUBMODULE, PROVIDER_ID, for_deployment=for_deployment, suffix=suffix) def _get_resource_annotations(suffix=None): return providers_manager.get_resource_annotations(PROVIDER_SUBMODULE, PROVIDER_ID, suffix=suffix) def _set_provider(): providers_manager.set_provider(PROVIDER_SUBMODULE, PROVIDER_ID) def _config_set(key=None, value=None, values=None, namespace=None, is_secret=False, suffix=None): providers_manager.config_set(PROVIDER_SUBMODULE, PROVIDER_ID, key=key, value=value, values=values, namespace=namespace, is_secret=is_secret, suffix=suffix) def _config_get(key=None, default=None, required=False, namespace=None, is_secret=False, suffix=None): return providers_manager.config_get(PROVIDER_SUBMODULE, PROVIDER_ID, key=key, default=default, required=required, namespace=namespace, is_secret=is_secret, suffix=suffix) def _config_interactive_set(default_values, namespace=None, is_secret=False, suffix=None, from_file=False, interactive=False): providers_manager.config_interactive_set(PROVIDER_SUBMODULE, PROVIDER_ID, default_values, namespace, is_secret, suffix, from_file, interactive) suffix=storage_suffix) _apply_secret(storage_suffix=storage_suffix) _apply_deployment( _get_or_create_volume( storage_suffix=storage_suffix, use_existing_disk_name=use_existing_disk_name ), storage_suffix=storage_suffix, dry_run=dry_run ) _apply_service(storage_suffix=storage_suffix, dry_run=dry_run) if not storage_suffix: _update_route(storage_suffix=storage_suffix, dry_run=dry_run) _set_provider() def print_credentials(raw=False, storage_suffix=None): hostname, access_key, secret_key = get_credentials(storage_suffix=storage_suffix) if raw: print(f'https://{hostname} {access_key} {secret_key}') else: print('Minio admin credentials:') print('External Domain: ' + hostname) print('Access Key: ' + access_key) print('Secret Key: ' + secret_key) print('\nto use with minio-client, run the following command:') print(f'mc config host add my-storage https://{hostname} {access_key} {secret_key}') def get_credentials(storage_suffix=None): return [_get_frontend_hostname(storage_suffix=storage_suffix)] + [ _config_get(key, required=True, is_secret=True, suffix=storage_suffix) for key in ['MINIO_ACCESS_KEY', 'MINIO_SECRET_KEY'] ] def _generate_password(l): return binascii.hexlify(os.urandom(l)).decode() def _apply_secret(storage_suffix=None): access_key = _config_get('MINIO_ACCESS_KEY', required=False, is_secret=True, suffix=storage_suffix) or _generate_password(8) secret_key = _config_get('MINIO_SECRET_KEY', required=False, is_secret=True, suffix=storage_suffix) or _generate_password(12) _config_set(values={'MINIO_ACCESS_KEY': access_key, 'MINIO_SECRET_KEY': secret_key}, is_secret=True, suffix=storage_suffix) def _apply_deployment(volume_spec, storage_suffix=None, dry_run=False): node_selector = volume_spec.pop('nodeSelector', None) if node_selector: pod_scheduling = {'nodeSelector': node_selector} else: pod_scheduling = {} container_spec_overrides = _config_get('container-spec-overrides', required=False, default=None, suffix=storage_suffix) kubectl.apply(kubectl.get_deployment( _get_resource_name(suffix=storage_suffix), _get_resource_labels(for_deployment=True, suffix=storage_suffix), { 'replicas': 1, 'revisionHistoryLimit': 10, 'strategy': {'type': 'Recreate', }, 'template': { 'metadata': { 'labels': _get_resource_labels(for_deployment=True, suffix=storage_suffix), 'annotations': _get_resource_annotations(suffix=storage_suffix) }, 'spec': { **pod_scheduling, 'containers': [ { 'name': 'minio', 'image': 'minio/minio', 'args': ['server', '/export'], 'envFrom': [{'secretRef': {'name': _get_resource_name(suffix=storage_suffix)}}], 'ports': [{'containerPort': 9000}], 'volumeMounts': [ { 'name': 'minio-data', 'mountPath': '/export', } ], **(json.loads(container_spec_overrides) if container_spec_overrides else {}) } ], 'volumes': [ dict(volume_spec, name='minio-data') ] } } } ), dry_run=dry_run) def _apply_service(storage_suffix=None, dry_run=False): kubectl.apply(kubectl.get_resource( 'v1', 'Service', _get_resource_name(suffix=storage_suffix), _get_resource_labels(suffix=storage_suffix), spec={ 'ports': [ {'name': '9000', 'port': 9000} ], 'selector': { 'app': _get_resource_labels(for_deployment=True, suffix=storage_suffix)['app'] } } ), dry_run=dry_run) def _get_or_create_volume(storage_suffix=None, use_existing_disk_name=None): disk_size_gb = _config_get('disk-size-gb', required=True, suffix=storage_suffix) volume_spec = _config_get('volume-spec', required=False, suffix=storage_suffix) if volume_spec: volume_spec = yaml.load(volume_spec) else: from ckan_cloud_operator.providers.cluster import manager as cluster_manager volume_spec = cluster_manager.create_volume( disk_size_gb, _get_resource_labels(suffix=storage_suffix), use_existing_disk_name=use_existing_disk_name ) _config_set('volume-spec', yaml.dump(volume_spec, default_flow_style=False), suffix=storage_suffix) return volume_spec def _update_route(storage_suffix=None, dry_run=False): backend_url_target_id = _get_backend_url_target_id(storage_suffix=storage_suffix) router_name = _config_get('router-name', required=True, suffix=storage_suffix) if not routers_manager.get_backend_url_routes(backend_url_target_id): deployment_name = _get_resource_name(suffix=storage_suffix) namespace = _get_namespace() subdomain_route = { 'target-type': 'backend-url', 'target-resource-id': backend_url_target_id, 'backend-url': f'http://{deployment_name}.{namespace}:9000', } if dry_run: logs.info('create_subdomain_route', router_name, subdomain_route) else: routers_manager.create_subdomain_route(router_name, subdomain_route) if not dry_run: routers_manager.update(router_name, wait_ready=True) def _get_namespace(): return 'ckan-cloud' def _get_frontend_hostname(storage_suffix=None): backend_url_target_id = _get_backend_url_target_id(storage_suffix=storage_suffix) routes = routers_manager.get_backend_url_routes(backend_url_target_id) assert storage_suffix or len(routes) == 1 if len(routes) < 1: return 'localhost:9000' else: return routers_manager.get_route_frontend_hostname(routes[0]) def _get_backend_url_target_id(storage_suffix=None): return f'minio-{storage_suffix}' if storage_suffix else 'minio'

true

1c4580a46e7319d59ea9439c79f77deb41aaa8c2

5,708

py

Python

luigi/rpc.py

miku/luigi

889ef2af64e2aa7d0cc65caef69a241ac91e5ff9

[ "Apache-2.0" ]

4

2017-03-21T20:01:19.000Z

2022-03-29T16:31:41.000Z

luigi/rpc.py

miku/luigi

889ef2af64e2aa7d0cc65caef69a241ac91e5ff9

[ "Apache-2.0" ]

9

2017-03-22T23:38:48.000Z

2019-01-28T21:13:06.000Z

luigi/rpc.py

miku/luigi

889ef2af64e2aa7d0cc65caef69a241ac91e5ff9

[ "Apache-2.0" ]

2

2015-05-04T22:46:20.000Z

2016-07-14T17:58:57.000Z

# -*- coding: utf-8 -*- # # Copyright 2012-2015 Spotify AB # # 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. # """ Implementation of the REST interface between the workers and the server. rpc.py implements the client side of it, server.py implements the server side. See :doc:`/central_scheduler` for more info. """ import os import json import logging import socket import time from luigi.six.moves.urllib.parse import urljoin, urlencode, urlparse from luigi.six.moves.urllib.request import urlopen from luigi.six.moves.urllib.error import URLError from luigi import configuration from luigi.scheduler import RPC_METHODS HAS_UNIX_SOCKET = True HAS_REQUESTS = True try: import requests_unixsocket as requests except ImportError: HAS_UNIX_SOCKET = False try: import requests except ImportError: HAS_REQUESTS = False logger = logging.getLogger('luigi-interface') # TODO: 'interface'? def _urljoin(base, url): """ Join relative URLs to base URLs like urllib.parse.urljoin but support arbitrary URIs (esp. 'http+unix://'). """ parsed = urlparse(base) scheme = parsed.scheme return urlparse( urljoin(parsed._replace(scheme='http').geturl(), url) )._replace(scheme=scheme).geturl() class RPCError(Exception): def __init__(self, message, sub_exception=None): super(RPCError, self).__init__(message) self.sub_exception = sub_exception class URLLibFetcher(object): raises = (URLError, socket.timeout) def fetch(self, full_url, body, timeout): body = urlencode(body).encode('utf-8') return urlopen(full_url, body, timeout).read().decode('utf-8') class RequestsFetcher(object): def __init__(self, session): from requests import exceptions as requests_exceptions self.raises = requests_exceptions.RequestException self.session = session self.process_id = os.getpid() def check_pid(self): # if the process id change changed from when the session was created # a new session needs to be setup since requests isn't multiprocessing safe. if os.getpid() != self.process_id: self.session = requests.Session() self.process_id = os.getpid() def fetch(self, full_url, body, timeout): self.check_pid() resp = self.session.get(full_url, data=body, timeout=timeout) resp.raise_for_status() return resp.text class RemoteScheduler(object): """ Scheduler proxy object. Talks to a RemoteSchedulerResponder. """ def __init__(self, url='http://localhost:8082/', connect_timeout=None): assert not url.startswith('http+unix://') or HAS_UNIX_SOCKET, ( 'You need to install requests-unixsocket for Unix socket support.' ) self._url = url.rstrip('/') config = configuration.get_config() if connect_timeout is None: connect_timeout = config.getfloat('core', 'rpc-connect-timeout', 10.0) self._connect_timeout = connect_timeout self._rpc_retry_attempts = config.getint('core', 'rpc-retry-attempts', 3) self._rpc_retry_wait = config.getint('core', 'rpc-retry-wait', 30) self._rpc_log_retries = config.getboolean('core', 'rpc-log-retries', True) if HAS_REQUESTS: self._fetcher = RequestsFetcher(requests.Session()) else: self._fetcher = URLLibFetcher() def _wait(self): if self._rpc_log_retries: logger.info("Wait for %d seconds" % self._rpc_retry_wait) time.sleep(self._rpc_retry_wait) def _fetch(self, url_suffix, body): full_url = _urljoin(self._url, url_suffix) last_exception = None attempt = 0 while attempt < self._rpc_retry_attempts: attempt += 1 if last_exception: if self._rpc_log_retries: logger.info("Retrying attempt %r of %r (max)" % (attempt, self._rpc_retry_attempts)) self._wait() # wait for a bit and retry try: response = self._fetcher.fetch(full_url, body, self._connect_timeout) break except self._fetcher.raises as e: last_exception = e if self._rpc_log_retries: logger.warning("Failed connecting to remote scheduler %r", self._url, exc_info=True) continue else: raise RPCError( "Errors (%d attempts) when connecting to remote scheduler %r" % (self._rpc_retry_attempts, self._url), last_exception ) return response def _request(self, url, data, attempts=3, allow_null=True): body = {'data': json.dumps(data)} for _ in range(attempts): page = self._fetch(url, body) response = json.loads(page)["response"] if allow_null or response is not None: return response raise RPCError("Received null response from remote scheduler %r" % self._url) for method_name, method in RPC_METHODS.items(): setattr(RemoteScheduler, method_name, method)

33.380117

104

0.653644

import os import json import logging import socket import time from luigi.six.moves.urllib.parse import urljoin, urlencode, urlparse from luigi.six.moves.urllib.request import urlopen from luigi.six.moves.urllib.error import URLError from luigi import configuration from luigi.scheduler import RPC_METHODS HAS_UNIX_SOCKET = True HAS_REQUESTS = True try: import requests_unixsocket as requests except ImportError: HAS_UNIX_SOCKET = False try: import requests except ImportError: HAS_REQUESTS = False logger = logging.getLogger('luigi-interface') def _urljoin(base, url): parsed = urlparse(base) scheme = parsed.scheme return urlparse( urljoin(parsed._replace(scheme='http').geturl(), url) )._replace(scheme=scheme).geturl() class RPCError(Exception): def __init__(self, message, sub_exception=None): super(RPCError, self).__init__(message) self.sub_exception = sub_exception class URLLibFetcher(object): raises = (URLError, socket.timeout) def fetch(self, full_url, body, timeout): body = urlencode(body).encode('utf-8') return urlopen(full_url, body, timeout).read().decode('utf-8') class RequestsFetcher(object): def __init__(self, session): from requests import exceptions as requests_exceptions self.raises = requests_exceptions.RequestException self.session = session self.process_id = os.getpid() def check_pid(self): if os.getpid() != self.process_id: self.session = requests.Session() self.process_id = os.getpid() def fetch(self, full_url, body, timeout): self.check_pid() resp = self.session.get(full_url, data=body, timeout=timeout) resp.raise_for_status() return resp.text class RemoteScheduler(object): def __init__(self, url='http://localhost:8082/', connect_timeout=None): assert not url.startswith('http+unix://') or HAS_UNIX_SOCKET, ( 'You need to install requests-unixsocket for Unix socket support.' ) self._url = url.rstrip('/') config = configuration.get_config() if connect_timeout is None: connect_timeout = config.getfloat('core', 'rpc-connect-timeout', 10.0) self._connect_timeout = connect_timeout self._rpc_retry_attempts = config.getint('core', 'rpc-retry-attempts', 3) self._rpc_retry_wait = config.getint('core', 'rpc-retry-wait', 30) self._rpc_log_retries = config.getboolean('core', 'rpc-log-retries', True) if HAS_REQUESTS: self._fetcher = RequestsFetcher(requests.Session()) else: self._fetcher = URLLibFetcher() def _wait(self): if self._rpc_log_retries: logger.info("Wait for %d seconds" % self._rpc_retry_wait) time.sleep(self._rpc_retry_wait) def _fetch(self, url_suffix, body): full_url = _urljoin(self._url, url_suffix) last_exception = None attempt = 0 while attempt < self._rpc_retry_attempts: attempt += 1 if last_exception: if self._rpc_log_retries: logger.info("Retrying attempt %r of %r (max)" % (attempt, self._rpc_retry_attempts)) self._wait() # wait for a bit and retry try: response = self._fetcher.fetch(full_url, body, self._connect_timeout) break except self._fetcher.raises as e: last_exception = e if self._rpc_log_retries: logger.warning("Failed connecting to remote scheduler %r", self._url, exc_info=True) continue else: raise RPCError( "Errors (%d attempts) when connecting to remote scheduler %r" % (self._rpc_retry_attempts, self._url), last_exception ) return response def _request(self, url, data, attempts=3, allow_null=True): body = {'data': json.dumps(data)} for _ in range(attempts): page = self._fetch(url, body) response = json.loads(page)["response"] if allow_null or response is not None: return response raise RPCError("Received null response from remote scheduler %r" % self._url) for method_name, method in RPC_METHODS.items(): setattr(RemoteScheduler, method_name, method)

true

1c4581505fbb614f1ce2848ca80ed21dafdc2751

1,094

py

Python

quick_start.py

willin007/kucoin_sdk

a4967c9f684aa4917a4b9e668d43520307eb9d30

[ "MIT" ]

null

quick_start.py

willin007/kucoin_sdk

a4967c9f684aa4917a4b9e668d43520307eb9d30

[ "MIT" ]

null

quick_start.py

willin007/kucoin_sdk

a4967c9f684aa4917a4b9e668d43520307eb9d30

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- # @Time : 2021/11/4 10:50 上午 # @Author : william.li # @File : quick_start.py # @Software: PyCharm # MarketData import asyncio from kucoin.client import WsToken from kucoin.ws_client import KucoinWsClient async def main(): async def deal_msg(msg): if msg['topic'] == '/spotMarket/level2Depth5:BTC-USDT': print(msg["data"]) elif msg['topic'] == '/spotMarket/level2Depth5:KCS-USDT': print(f'Get KCS level3:{msg["data"]}') # is public client = WsToken() #is private # client = WsToken(key='', secret='', passphrase='', is_sandbox=False, url='') # is sandbox # client = WsToken(is_sandbox=True) ws_client = await KucoinWsClient.create(None, client, deal_msg, private=False) # await ws_client.subscribe('/market/ticker:BTC-USDT,ETH-USDT') await ws_client.subscribe('/spotMarket/level2Depth5:KCS-USDT') while True: await asyncio.sleep(60, loop=loop) if __name__ == "__main__": loop = asyncio.get_event_loop() loop.run_until_complete(main())

29.567568

82

0.652651

import asyncio from kucoin.client import WsToken from kucoin.ws_client import KucoinWsClient async def main(): async def deal_msg(msg): if msg['topic'] == '/spotMarket/level2Depth5:BTC-USDT': print(msg["data"]) elif msg['topic'] == '/spotMarket/level2Depth5:KCS-USDT': print(f'Get KCS level3:{msg["data"]}') client = WsToken() ws_client = await KucoinWsClient.create(None, client, deal_msg, private=False) await ws_client.subscribe('/spotMarket/level2Depth5:KCS-USDT') while True: await asyncio.sleep(60, loop=loop) if __name__ == "__main__": loop = asyncio.get_event_loop() loop.run_until_complete(main())

true

1c45828c2da100de725a4b389922ca6abe3ce11d

1,901

py

Python

setup.py

cajfisher/vasppy

a460db14163b7db3bce54d754dd476c45a3ed85b

[ "MIT" ]

28

2017-02-16T13:22:34.000Z

2021-04-29T06:10:10.000Z

setup.py

cajfisher/vasppy

a460db14163b7db3bce54d754dd476c45a3ed85b

[ "MIT" ]

15

2016-05-09T13:08:42.000Z

2021-08-09T10:59:58.000Z

setup.py

cajfisher/vasppy

a460db14163b7db3bce54d754dd476c45a3ed85b

[ "MIT" ]

25

2015-10-12T11:29:22.000Z

2021-08-20T17:33:27.000Z

""" vasppy: Python utilities for working with VASP inputs and outputs. """ from setuptools import setup, find_packages from vasppy.version import __version__ as VERSION readme = 'README.md' long_description = open(readme).read() scripts = ['check_species', 'murnfit', 'vasp_summary', 'poscar_to_cif', 'potcar_spec', 'effective_mass', 'fat_bands', 'pimaim_to_poscar', 'pimaim_to_xtl', 'poscar_sort', 'poscar_to_pimaim', 'poscar_to_xtl', 'proc_poscar', 'rotate_poscar', 'spacegroup', 'vasp_grid', 'xdatcar_to_disp', 'xdatcar_to_poscart', 'xdatcar_to_rdf'] setup( name='vasppy', version=VERSION, description='Python utilities for working with VASP inputs and outputs', long_description=long_description, long_description_content_type="text/markdown", author='Benjamin J. Morgan', author_email='bjm42@bath.ac.uk', url='https://github.com/bjmorgan/vasppy', download_url='https://github.com/bjmorgan/vasppy/archive/{}.tar.gz'.format(VERSION), keywords=['vasp'], # keywords packages=find_packages(exclude=['docs', 'tests*']), package_data={'vasppy': ['data/*.yaml']}, entry_points={'console_scripts':[ '{} = vasppy.scripts.{}:main'.format(s, s) for s in scripts]}, license='MIT', install_requires=['monty', 'numpy>=1.16.2', 'pandas', 'pymatgen>=2022.0.0', 'PyYAML', 'coverage==4.3.4', 'codeclimate-test-reporter', 'fortranformat', 'scipy>=1.4.1', 'tqdm', 'lxml'], python_requires='>=3.7' )

31.683333

88

0.538138

from setuptools import setup, find_packages from vasppy.version import __version__ as VERSION readme = 'README.md' long_description = open(readme).read() scripts = ['check_species', 'murnfit', 'vasp_summary', 'poscar_to_cif', 'potcar_spec', 'effective_mass', 'fat_bands', 'pimaim_to_poscar', 'pimaim_to_xtl', 'poscar_sort', 'poscar_to_pimaim', 'poscar_to_xtl', 'proc_poscar', 'rotate_poscar', 'spacegroup', 'vasp_grid', 'xdatcar_to_disp', 'xdatcar_to_poscart', 'xdatcar_to_rdf'] setup( name='vasppy', version=VERSION, description='Python utilities for working with VASP inputs and outputs', long_description=long_description, long_description_content_type="text/markdown", author='Benjamin J. Morgan', author_email='bjm42@bath.ac.uk', url='https://github.com/bjmorgan/vasppy', download_url='https://github.com/bjmorgan/vasppy/archive/{}.tar.gz'.format(VERSION), keywords=['vasp'], packages=find_packages(exclude=['docs', 'tests*']), package_data={'vasppy': ['data/*.yaml']}, entry_points={'console_scripts':[ '{} = vasppy.scripts.{}:main'.format(s, s) for s in scripts]}, license='MIT', install_requires=['monty', 'numpy>=1.16.2', 'pandas', 'pymatgen>=2022.0.0', 'PyYAML', 'coverage==4.3.4', 'codeclimate-test-reporter', 'fortranformat', 'scipy>=1.4.1', 'tqdm', 'lxml'], python_requires='>=3.7' )

true

1c4582bb37d8bf82a9eadb8ac9e0bbddd1dde76a

7,194

py

Python

hack/boilerplate/boilerplate.py

moelsayed/kubeone

bec424b09d2d0cb5d97347469c947ab66c5c1d91

[ "Apache-2.0" ]

1

2020-02-13T17:46:28.000Z

hack/boilerplate/boilerplate.py

moelsayed/kubeone

bec424b09d2d0cb5d97347469c947ab66c5c1d91

[ "Apache-2.0" ]

null

hack/boilerplate/boilerplate.py

moelsayed/kubeone

bec424b09d2d0cb5d97347469c947ab66c5c1d91

[ "Apache-2.0" ]

1

2020-05-06T15:33:38.000Z

#!/usr/bin/env python # Copyright 2019 The KubeOne Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from __future__ import print_function import argparse import datetime import difflib import glob import os import re import sys parser = argparse.ArgumentParser() parser.add_argument( "filenames", help="list of files to check, all files if unspecified", nargs='*') rootdir = os.path.dirname(__file__) + "/../../" rootdir = os.path.abspath(rootdir) parser.add_argument( "--rootdir", default=rootdir, help="root directory to examine") default_boilerplate_dir = os.path.join(rootdir, "hack/boilerplate") parser.add_argument( "--boilerplate-dir", default=default_boilerplate_dir) parser.add_argument( "-v", "--verbose", help="give verbose output regarding why a file does not pass", action="store_true") args = parser.parse_args() verbose_out = sys.stderr if args.verbose else open("/dev/null", "w") def get_refs(): refs = {} for path in glob.glob(os.path.join(args.boilerplate_dir, "boilerplate.*.txt")): extension = os.path.basename(path).split(".")[1] ref_file = open(path, 'r') ref = ref_file.read().splitlines() ref_file.close() refs[extension] = ref return refs def is_generated_file(filename, data, regexs): for d in skipped_ungenerated_files: if d in filename: return False p = regexs["generated"] return p.search(data) def file_passes(filename, refs, regexs): try: f = open(filename, 'r') except Exception as exc: print("Unable to open %s: %s" % (filename, exc), file=verbose_out) return False data = f.read() f.close() # determine if the file is automatically generated generated = is_generated_file(filename, data, regexs) basename = os.path.basename(filename) if generated: extension = "generatego" else: extension = file_extension(filename) if extension != "": ref = refs[extension] else: ref = refs[basename] # remove extra content from the top of files if extension == "go" or extension == "generatego": p = regexs["go_build_constraints"] (data, found) = p.subn("", data, 1) elif extension == "sh": p = regexs["shebang"] (data, found) = p.subn("", data, 1) data = data.splitlines() # if our test file is smaller than the reference it surely fails! if len(ref) > len(data): print('File %s smaller than reference (%d < %d)' % (filename, len(data), len(ref)), file=verbose_out) return False # trim our file to the same number of lines as the reference file data = data[:len(ref)] p = regexs["year"] for d in data: if p.search(d): if generated: print('File %s has the YEAR field, but it should not be in generated file' % filename, file=verbose_out) else: print('File %s has the YEAR field, but missing the year of date' % filename, file=verbose_out) return False if not generated: # Replace all occurrences of the regex "2014|2015|2016|2017|2018" with "YEAR" p = regexs["date"] for i, d in enumerate(data): (data[i], found) = p.subn('YEAR', d) if found != 0: break # if we don't match the reference at this point, fail if ref != data: print("Header in %s does not match reference, diff:" % filename, file=verbose_out) if args.verbose: print(file=verbose_out) for line in difflib.unified_diff(ref, data, 'reference', filename, lineterm=''): print(line, file=verbose_out) print(file=verbose_out) return False return True def file_extension(filename): return os.path.splitext(filename)[1].split(".")[-1].lower() skipped_dirs = [ 'bin', 'Godeps', '.git', 'vendor', 'hack/boilerplate/test', 'pkg/apis/kubeadm/v1beta1', 'pkg/apis/kubeadm/v1beta2', ] # list all the files contain 'DO NOT EDIT', but are not generated skipped_ungenerated_files = ['hack/boilerplate/boilerplate.py'] def normalize_files(files): newfiles = [] for pathname in files: if any(x in pathname for x in skipped_dirs): continue newfiles.append(pathname) for i, pathname in enumerate(newfiles): if not os.path.isabs(pathname): newfiles[i] = os.path.join(args.rootdir, pathname) return newfiles def get_files(extensions): files = [] if len(args.filenames) > 0: files = args.filenames else: for root, dirs, walkfiles in os.walk(args.rootdir): # don't visit certain dirs. This is just a performance improvement # as we would prune these later in normalize_files(). But doing it # cuts down the amount of filesystem walking we do and cuts down # the size of the file list for d in skipped_dirs: if d in dirs: dirs.remove(d) for name in walkfiles: pathname = os.path.join(root, name) files.append(pathname) files = normalize_files(files) outfiles = [] for pathname in files: basename = os.path.basename(pathname) extension = file_extension(pathname) if extension in extensions or basename in extensions: outfiles.append(pathname) return outfiles def get_dates(): years = datetime.datetime.now().year return '(%s)' % '|'.join((str(year) for year in range(2014, years+1))) def get_regexs(): regexs = {} # Search for "YEAR" which exists in the boilerplate, but shouldn't in the real thing regexs["year"] = re.compile('YEAR') # get_dates return 2014, 2015, 2016, 2017, or 2018 until the current year as a regex like: "(2014|2015|2016|2017|2018)"; # company holder names can be anything regexs["date"] = re.compile(get_dates()) # strip // +build \n\n build constraints regexs["go_build_constraints"] = re.compile( r"^(// \+build.*\n)+\n", re.MULTILINE) # strip #!.* from shell scripts regexs["shebang"] = re.compile(r"^(#!.*\n)\n*", re.MULTILINE) # Search for generated files regexs["generated"] = re.compile('DO NOT EDIT') return regexs def main(): regexs = get_regexs() refs = get_refs() filenames = get_files(refs.keys()) for filename in filenames: if not file_passes(filename, refs, regexs): print(filename, file=sys.stdout) return 0 if __name__ == "__main__": sys.exit(main())

29.604938

124

0.630108

from __future__ import print_function import argparse import datetime import difflib import glob import os import re import sys parser = argparse.ArgumentParser() parser.add_argument( "filenames", help="list of files to check, all files if unspecified", nargs='*') rootdir = os.path.dirname(__file__) + "/../../" rootdir = os.path.abspath(rootdir) parser.add_argument( "--rootdir", default=rootdir, help="root directory to examine") default_boilerplate_dir = os.path.join(rootdir, "hack/boilerplate") parser.add_argument( "--boilerplate-dir", default=default_boilerplate_dir) parser.add_argument( "-v", "--verbose", help="give verbose output regarding why a file does not pass", action="store_true") args = parser.parse_args() verbose_out = sys.stderr if args.verbose else open("/dev/null", "w") def get_refs(): refs = {} for path in glob.glob(os.path.join(args.boilerplate_dir, "boilerplate.*.txt")): extension = os.path.basename(path).split(".")[1] ref_file = open(path, 'r') ref = ref_file.read().splitlines() ref_file.close() refs[extension] = ref return refs def is_generated_file(filename, data, regexs): for d in skipped_ungenerated_files: if d in filename: return False p = regexs["generated"] return p.search(data) def file_passes(filename, refs, regexs): try: f = open(filename, 'r') except Exception as exc: print("Unable to open %s: %s" % (filename, exc), file=verbose_out) return False data = f.read() f.close() generated = is_generated_file(filename, data, regexs) basename = os.path.basename(filename) if generated: extension = "generatego" else: extension = file_extension(filename) if extension != "": ref = refs[extension] else: ref = refs[basename] if extension == "go" or extension == "generatego": p = regexs["go_build_constraints"] (data, found) = p.subn("", data, 1) elif extension == "sh": p = regexs["shebang"] (data, found) = p.subn("", data, 1) data = data.splitlines() if len(ref) > len(data): print('File %s smaller than reference (%d < %d)' % (filename, len(data), len(ref)), file=verbose_out) return False data = data[:len(ref)] p = regexs["year"] for d in data: if p.search(d): if generated: print('File %s has the YEAR field, but it should not be in generated file' % filename, file=verbose_out) else: print('File %s has the YEAR field, but missing the year of date' % filename, file=verbose_out) return False if not generated: p = regexs["date"] for i, d in enumerate(data): (data[i], found) = p.subn('YEAR', d) if found != 0: break if ref != data: print("Header in %s does not match reference, diff:" % filename, file=verbose_out) if args.verbose: print(file=verbose_out) for line in difflib.unified_diff(ref, data, 'reference', filename, lineterm=''): print(line, file=verbose_out) print(file=verbose_out) return False return True def file_extension(filename): return os.path.splitext(filename)[1].split(".")[-1].lower() skipped_dirs = [ 'bin', 'Godeps', '.git', 'vendor', 'hack/boilerplate/test', 'pkg/apis/kubeadm/v1beta1', 'pkg/apis/kubeadm/v1beta2', ] # list all the files contain 'DO NOT EDIT', but are not generated skipped_ungenerated_files = ['hack/boilerplate/boilerplate.py'] def normalize_files(files): newfiles = [] for pathname in files: if any(x in pathname for x in skipped_dirs): continue newfiles.append(pathname) for i, pathname in enumerate(newfiles): if not os.path.isabs(pathname): newfiles[i] = os.path.join(args.rootdir, pathname) return newfiles def get_files(extensions): files = [] if len(args.filenames) > 0: files = args.filenames else: for root, dirs, walkfiles in os.walk(args.rootdir): # don't visit certain dirs. This is just a performance improvement for d in skipped_dirs: if d in dirs: dirs.remove(d) for name in walkfiles: pathname = os.path.join(root, name) files.append(pathname) files = normalize_files(files) outfiles = [] for pathname in files: basename = os.path.basename(pathname) extension = file_extension(pathname) if extension in extensions or basename in extensions: outfiles.append(pathname) return outfiles def get_dates(): years = datetime.datetime.now().year return '(%s)' % '|'.join((str(year) for year in range(2014, years+1))) def get_regexs(): regexs = {} regexs["year"] = re.compile('YEAR') # get_dates return 2014, 2015, 2016, 2017, or 2018 until the current year as a regex like: "(2014|2015|2016|2017|2018)"; # company holder names can be anything regexs["date"] = re.compile(get_dates()) # strip // +build \n\n build constraints regexs["go_build_constraints"] = re.compile( r"^(// \+build.*\n)+\n", re.MULTILINE) # strip #!.* from shell scripts regexs["shebang"] = re.compile(r"^(#!.*\n)\n*", re.MULTILINE) # Search for generated files regexs["generated"] = re.compile('DO NOT EDIT') return regexs def main(): regexs = get_regexs() refs = get_refs() filenames = get_files(refs.keys()) for filename in filenames: if not file_passes(filename, refs, regexs): print(filename, file=sys.stdout) return 0 if __name__ == "__main__": sys.exit(main())

true

1c45839120b9c193c462707af258c3c9bfffdfa3

568

py

Python

tests/test_level1/test_visited.py

kianmeng/soupsieve

a8640aad6ae0476e6b62f4f15e12ad4efc7605c4

[ "MIT" ]

130

2018-12-27T06:00:32.000Z

2022-03-29T05:47:18.000Z

tests/test_level1/test_visited.py

kianmeng/soupsieve

a8640aad6ae0476e6b62f4f15e12ad4efc7605c4

[ "MIT" ]

157

2018-12-07T07:44:15.000Z

2022-02-05T16:20:08.000Z

tests/test_level1/test_visited.py

kianmeng/soupsieve

a8640aad6ae0476e6b62f4f15e12ad4efc7605c4

[ "MIT" ]

32

2018-12-31T03:11:55.000Z

2022-03-06T09:06:43.000Z

"""Test visited selectors.""" from .. import util class TestVisited(util.TestCase): """Test visited selectors.""" def test_visited(self): """Test visited.""" markup = """ <div> <p>Some text <span id="1" class="foo:bar:foobar"> in a paragraph</span>. <a id="2" class="bar" href="http://google.com">Link</a> <a id="3">Placeholder text.</a> </p> </div> """ self.assert_selector( markup, "a:visited", [], flags=util.HTML )

21.846154

80

0.482394

from .. import util class TestVisited(util.TestCase): def test_visited(self): markup = """ <div> <p>Some text <span id="1" class="foo:bar:foobar"> in a paragraph</span>. <a id="2" class="bar" href="http://google.com">Link</a> <a id="3">Placeholder text.</a> </p> </div> """ self.assert_selector( markup, "a:visited", [], flags=util.HTML )

true

1c4584ac1bc01ab917fbb00db92b230e45196a27

5,228

py

Python

export.py

OleksandrBlack/safecoinnodes

0021edc8e72e078fcd7bedb465292c96caeeb148

[ "MIT" ]

null

export.py

OleksandrBlack/safecoinnodes

0021edc8e72e078fcd7bedb465292c96caeeb148

[ "MIT" ]

null

export.py

OleksandrBlack/safecoinnodes

0021edc8e72e078fcd7bedb465292c96caeeb148

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- # # export.py - Exports enumerated data for reachable nodes into a JSON file. # # Copyright (c) Addy Yeow Chin Heng <ayeowch@gmail.com> # # Permission is hereby granted, free of charge, to any person obtaining # a copy of this software and associated documentation files (the # "Software"), to deal in the Software without restriction, including # without limitation the rights to use, copy, modify, merge, publish, # distribute, sublicense, and/or sell copies of the Software, and to # permit persons to whom the Software is furnished to do so, subject to # the following conditions: # # The above copyright notice and this permission notice shall be # included in all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, # EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF # MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND # NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE # LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION # OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION # WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ Exports enumerated data for reachable nodes into a JSON file. """ import json import logging import os import sys import time from binascii import hexlify, unhexlify from ConfigParser import ConfigParser from utils import new_redis_conn REDIS_CONN = None CONF = {} def get_row(node): """ Returns enumerated row data from Redis for the specified node. """ # address, port, version, user_agent, timestamp, services node = eval(node) address = node[0] port = node[1] services = node[-1] height = REDIS_CONN.get('height:{}-{}-{}'.format(address, port, services)) if height is None: height = (0,) else: height = (int(height),) hostname = REDIS_CONN.hget('resolve:{}'.format(address), 'hostname') hostname = (hostname,) geoip = REDIS_CONN.hget('resolve:{}'.format(address), 'geoip') if geoip is None: # city, country, latitude, longitude, timezone, asn, org geoip = (None, None, 0.0, 0.0, None, None, None) else: geoip = eval(geoip) return node + height + hostname + geoip MAX_DUMPED_SNAPSHOTS = 500 def export_nodes(nodes, timestamp): """ Merges enumerated data for the specified nodes and exports them into timestamp-prefixed JSON file. """ rows = [] start = time.time() for node in nodes: row = get_row(node) rows.append(row) end = time.time() elapsed = end - start logging.info("Elapsed: %d", elapsed) dump = os.path.join(CONF['export_dir'], "{}.json".format(timestamp)) open(dump, 'w').write(json.dumps(rows, encoding="latin-1")) REDIS_CONN.lpush('dumped_snapshots', timestamp) REDIS_CONN.ltrim('dumped_snapshots', 0, MAX_DUMPED_SNAPSHOTS) logging.info("Wrote %s", dump) def init_conf(argv): """ Populates CONF with key-value pairs from configuration file. """ conf = ConfigParser() conf.read(argv[1]) CONF['logfile'] = conf.get('export', 'logfile') CONF['magic_number'] = unhexlify(conf.get('export', 'magic_number')) CONF['db'] = conf.getint('export', 'db') CONF['debug'] = conf.getboolean('export', 'debug') CONF['export_dir'] = conf.get('export', 'export_dir') if not os.path.exists(CONF['export_dir']): os.makedirs(CONF['export_dir']) def main(argv): if len(argv) < 2 or not os.path.exists(argv[1]): print("Usage: export.py [config]") return 1 # Initialize global conf init_conf(argv) # Initialize logger loglevel = logging.INFO if CONF['debug']: loglevel = logging.DEBUG logformat = ("%(asctime)s,%(msecs)05.1f %(levelname)s (%(funcName)s) " "%(message)s") logging.basicConfig(level=loglevel, format=logformat, filename=CONF['logfile'], filemode='w') print("Log: {}, press CTRL+C to terminate..".format(CONF['logfile'])) global REDIS_CONN REDIS_CONN = new_redis_conn(db=CONF['db']) subscribe_key = 'resolve:{}'.format(hexlify(CONF['magic_number'])) publish_key = 'export:{}'.format(hexlify(CONF['magic_number'])) pubsub = REDIS_CONN.pubsub() pubsub.subscribe(subscribe_key) while True: msg = pubsub.get_message() if msg is None: time.sleep(0.001) # 1 ms artificial intrinsic latency. continue # 'resolve' message is published by resolve.py after resolving hostname # and GeoIP data for all reachable nodes. if msg['channel'] == subscribe_key and msg['type'] == 'message': timestamp = int(msg['data']) # From ping.py's 'snapshot' message logging.info("Timestamp: %d", timestamp) nodes = REDIS_CONN.smembers('opendata') logging.info("Nodes: %d", len(nodes)) export_nodes(nodes, timestamp) REDIS_CONN.publish(publish_key, timestamp) return 0 if __name__ == '__main__': sys.exit(main(sys.argv))

32.271605

79

0.655318

import json import logging import os import sys import time from binascii import hexlify, unhexlify from ConfigParser import ConfigParser from utils import new_redis_conn REDIS_CONN = None CONF = {} def get_row(node): node = eval(node) address = node[0] port = node[1] services = node[-1] height = REDIS_CONN.get('height:{}-{}-{}'.format(address, port, services)) if height is None: height = (0,) else: height = (int(height),) hostname = REDIS_CONN.hget('resolve:{}'.format(address), 'hostname') hostname = (hostname,) geoip = REDIS_CONN.hget('resolve:{}'.format(address), 'geoip') if geoip is None: geoip = (None, None, 0.0, 0.0, None, None, None) else: geoip = eval(geoip) return node + height + hostname + geoip MAX_DUMPED_SNAPSHOTS = 500 def export_nodes(nodes, timestamp): rows = [] start = time.time() for node in nodes: row = get_row(node) rows.append(row) end = time.time() elapsed = end - start logging.info("Elapsed: %d", elapsed) dump = os.path.join(CONF['export_dir'], "{}.json".format(timestamp)) open(dump, 'w').write(json.dumps(rows, encoding="latin-1")) REDIS_CONN.lpush('dumped_snapshots', timestamp) REDIS_CONN.ltrim('dumped_snapshots', 0, MAX_DUMPED_SNAPSHOTS) logging.info("Wrote %s", dump) def init_conf(argv): conf = ConfigParser() conf.read(argv[1]) CONF['logfile'] = conf.get('export', 'logfile') CONF['magic_number'] = unhexlify(conf.get('export', 'magic_number')) CONF['db'] = conf.getint('export', 'db') CONF['debug'] = conf.getboolean('export', 'debug') CONF['export_dir'] = conf.get('export', 'export_dir') if not os.path.exists(CONF['export_dir']): os.makedirs(CONF['export_dir']) def main(argv): if len(argv) < 2 or not os.path.exists(argv[1]): print("Usage: export.py [config]") return 1 init_conf(argv) loglevel = logging.INFO if CONF['debug']: loglevel = logging.DEBUG logformat = ("%(asctime)s,%(msecs)05.1f %(levelname)s (%(funcName)s) " "%(message)s") logging.basicConfig(level=loglevel, format=logformat, filename=CONF['logfile'], filemode='w') print("Log: {}, press CTRL+C to terminate..".format(CONF['logfile'])) global REDIS_CONN REDIS_CONN = new_redis_conn(db=CONF['db']) subscribe_key = 'resolve:{}'.format(hexlify(CONF['magic_number'])) publish_key = 'export:{}'.format(hexlify(CONF['magic_number'])) pubsub = REDIS_CONN.pubsub() pubsub.subscribe(subscribe_key) while True: msg = pubsub.get_message() if msg is None: time.sleep(0.001) continue if msg['channel'] == subscribe_key and msg['type'] == 'message': timestamp = int(msg['data']) logging.info("Timestamp: %d", timestamp) nodes = REDIS_CONN.smembers('opendata') logging.info("Nodes: %d", len(nodes)) export_nodes(nodes, timestamp) REDIS_CONN.publish(publish_key, timestamp) return 0 if __name__ == '__main__': sys.exit(main(sys.argv))

true

1c4584cb83547e7b831785c85e43413291a71a8c

2,135

py

Python

Stopwatch.py

arapawa/stopwatch-game

5ee64e04a8dc15ead2dcd8a661105ae1c9087317

[ "MIT" ]

null

Stopwatch.py

arapawa/stopwatch-game

5ee64e04a8dc15ead2dcd8a661105ae1c9087317

[ "MIT" ]

1

2016-12-30T06:59:12.000Z

Stopwatch.py

arapawa/stopwatch-game

5ee64e04a8dc15ead2dcd8a661105ae1c9087317

[ "MIT" ]

null

# "Stopwatch: The Game" # tenth of a second between every tick # every time timer ticks, it will update a global variable by one import simplegui # define global variables time = 0 success = 0 attempts = 0 counter = 0 # variable to ensure score can only be increased after stopwatch was running stopwatch_running = False # define helper function format that converts time # in tenths of seconds into formatted string A:BC.D def format(t): a_time = t // 600 b_time = ((t / 10) % 60) // 10 c_time = ((t / 10) % 60) % 10 d_time = t % 10 return str(a_time) + ":" + str(b_time) + str(c_time) + "." + str(d_time) # define event handlers for buttons; "Start", "Stop", "Reset" def button_start(): stopwatch_timer() def button_stop(): timer.stop() global success, attempts, stopwatch_running if stopwatch_running == True: if (time % 10) == 0: success += 1 attempts += 1 else: attempts += 1 else: return stopwatch_running = False def button_reset(): global time, success, attempts time = 0 success = 0 attempts = 0 return time, success, attempts # define event handler for timer with 0.1 sec interval # stopwatch timer event handler def stopwatch_timer(): timer.start() global time, stopwatch_running time += 1 stopwatch_running = True return time, stopwatch_running # define draw handler def draw_handler(canvas): # stopwatch display on canvas canvas.draw_text(format(time), [90, 140], 50, "White") # score display canvas.draw_text(str(success) + "/" + str(attempts), [220, 50], 25, "Red") # create frame frame = simplegui.create_frame("Stopwatch: The Game", 300, 200) # register event handlers timer = simplegui.create_timer(100, button_start) start = frame.add_button("Start", button_start, 100) stop = frame.add_button("Stop", button_stop, 100) reset = frame.add_button("Reset", button_reset, 100) frame.set_draw_handler(draw_handler) # start frame frame.start()

26.036585

79

0.640281

import simplegui time = 0 success = 0 attempts = 0 counter = 0 stopwatch_running = False def format(t): a_time = t // 600 b_time = ((t / 10) % 60) // 10 c_time = ((t / 10) % 60) % 10 d_time = t % 10 return str(a_time) + ":" + str(b_time) + str(c_time) + "." + str(d_time) def button_start(): stopwatch_timer() def button_stop(): timer.stop() global success, attempts, stopwatch_running if stopwatch_running == True: if (time % 10) == 0: success += 1 attempts += 1 else: attempts += 1 else: return stopwatch_running = False def button_reset(): global time, success, attempts time = 0 success = 0 attempts = 0 return time, success, attempts def stopwatch_timer(): timer.start() global time, stopwatch_running time += 1 stopwatch_running = True return time, stopwatch_running def draw_handler(canvas): canvas.draw_text(format(time), [90, 140], 50, "White") canvas.draw_text(str(success) + "/" + str(attempts), [220, 50], 25, "Red") frame = simplegui.create_frame("Stopwatch: The Game", 300, 200) timer = simplegui.create_timer(100, button_start) start = frame.add_button("Start", button_start, 100) stop = frame.add_button("Stop", button_stop, 100) reset = frame.add_button("Reset", button_reset, 100) frame.set_draw_handler(draw_handler) frame.start()

true

1c458641abbee4ca565c0de49e6620d72012ccb6

20,836

py

Python

cripts/relationships/handlers.py

lakiw/cripts

43f62891a3724e1ec60629887d97c421fb302163

[ "MIT" ]

2

2017-04-06T12:26:11.000Z

2018-11-05T19:17:15.000Z

cripts/relationships/handlers.py

lakiw/cripts

43f62891a3724e1ec60629887d97c421fb302163

[ "MIT" ]

9

2016-09-28T10:19:10.000Z

2017-02-24T17:58:43.000Z

cripts/relationships/handlers.py

lakiw/cripts

43f62891a3724e1ec60629887d97c421fb302163

[ "MIT" ]

null

import datetime from dateutil.parser import parse from cripts.core.class_mapper import class_from_id def get_relationships(obj=None, type_=None, id_=None, analyst=None): """ Get relationships for a top-level object. :param obj: The top-level object to get relationships for. :type obj: :class:`cripts.core.cripts_mongoengine.CriptsBaseAttributes` :param type_: The top-level object type to get relationships for. :type type_: str :param id_: The ObjectId of the top-level object. :type id_: str :param analyst: The user requesting the relationships. :type analyst: str :returns: dict """ if obj: return obj.sort_relationships("%s" % analyst, meta=True) elif type_ and id_: obj = class_from_id(type_, id_) if not obj: return {} return obj.sort_relationships("%s" % analyst, meta=True) else: return {} def forge_relationship(type_=None, id_=None, class_=None, right_type=None, right_id=None, right_class=None, rel_type=None, rel_date=None, user=None, rel_reason="", rel_confidence='unknown', get_rels=False, **kwargs): """ Forge a relationship between two top-level objects. :param type_: The type of first top-level object to relate to. :type type_: str :param id_: The ObjectId of the first top-level object. :type id_: str :param class_: The first top-level object to relate to. :type class_: :class:`cripts.core.cripts_mongoengine.CriptsBaseAttributes` :param right_type: The type of second top-level object to relate to. :type right_type: str :param right_id: The ObjectId of the second top-level object. :type right_id: str :param right_class: The second top-level object to relate to. :type right_class: :class:`cripts.core.cripts_mongoengine.CriptsBaseAttributes` :param rel_type: The type of relationship. :type rel_type: str :param rel_date: The date this relationship applies. :type rel_date: datetime.datetime :param user: The user forging this relationship. :type user: str :param rel_reason: The reason for the relationship. :type rel_reason: str :param rel_confidence: The confidence of the relationship. :type rel_confidence: str :param get_rels: Return the relationships after forging. :type get_rels: boolean :returns: dict with keys: "success" (boolean) "message" (str if fail, EmbeddedObject if success) "relationships" (dict) """ if rel_date == 'None': rel_date = None elif isinstance(rel_date, basestring) and rel_date != '': rel_date = parse(rel_date, fuzzy=True) elif not isinstance(rel_date, datetime.datetime): rel_date = None if not class_: if type_ and id_: class_ = class_from_id(type_, id_) if not class_: return {'success': False, 'message': "Failed to get left TLO"} if not right_class: if right_type and right_id: print ("right type:" + str(right_type)) print ("right id:" + str(right_id)) right_class = class_from_id(right_type, right_id) if not right_class: return {'success': False, 'message': "Failed to get right TLO"} try: # forge relationship results = class_.add_relationship(right_class, rel_type, rel_date, user, rel_confidence, rel_reason) except Exception as e: return {'success': False, 'message': e} if results['success']: class_.update(add_to_set__relationships=results['message']) if get_rels: results['relationships'] = class_.sort_relationships("%s" % user, meta=True) return results def delete_all_relationships(left_class=None, left_type=None, left_id=None, analyst=None): """ Delete all relationships for this top-level object. :param left_class: The top-level object to delete relationships for. :type left_class: :class:`cripts.core.cripts_mongoengine.CriptsBaseAttributes` :param left_type: The type of the top-level object. :type left_type: str :param left_id: The ObjectId of the top-level object. :type left_id: str :param analyst: The user deleting these relationships. :type analyst: str :returns: dict with keys "success" (boolean) and "message" (str) """ if not left_class: if left_type and left_id: left_class = class_from_id(left_type, left_id) if not left_class: return {'success': False, 'message': "Unable to get object."} else: return {'success': False, 'message': "Need a valid left type and id"} return left_class.delete_all_relationships() def delete_relationship(left_class=None, right_class=None, left_type=None, left_id=None, right_type=None, right_id=None, rel_type=None, rel_date=None, analyst=None, get_rels=True): """ Delete a relationship between two top-level objects. :param left_class: The first top-level object. :type left_class: :class:`cripts.core.cripts_mongoengine.CriptsBaseAttributes` :param right_class: The second top-level object. :type right_class: :class:`cripts.core.cripts_mongoengine.CriptsBaseAttributes` :param left_type: The type of first top-level object. :type left_type: str :param left_id: The ObjectId of the first top-level object. :type left_id: str :param right_type: The type of second top-level object. :type right_type: str :param right_id: The ObjectId of the second top-level object. :type right_id: str :param rel_type: The type of relationship. :type rel_type: str :param rel_date: The date this relationship applies. :type rel_date: datetime.datetime :param analyst: The user deleting this relationship. :type analyst: str :param get_rels: Return the relationships after forging. :type get_rels: boolean :returns: dict with keys "success" (boolean) and "message" (str if failed, dict if successful) """ if rel_date is None or rel_date == 'None': rel_date = None elif isinstance(rel_date, basestring) and rel_date != '': rel_date = parse(rel_date, fuzzy=True) elif not isinstance(rel_date, datetime.datetime): rel_date = None if not left_class: if left_type and left_id: left_class = class_from_id(left_type, left_id) if not left_class: return {'success': False, 'message': "Unable to get object."} else: return {'success': False, 'message': "Need a valid left type and id"} # delete relationship if right_class: results = left_class.delete_relationship(rel_item=right_class, rel_type=rel_type, rel_date=rel_date, analyst=analyst) else: if right_type and right_id: results = left_class.delete_relationship(type_=right_type, rel_id=right_id, rel_type=rel_type, rel_date=rel_date, analyst=analyst) else: return {'success': False, 'message': "Need a valid right type and id"} if results['success']: left_class.save(username=analyst) if get_rels: results['relationships'] = left_class.sort_relationships("%s" % analyst, meta=True) return results def update_relationship_types(left_class=None, right_class=None, left_type=None, left_id=None, right_type=None, right_id=None, rel_type=None, rel_date=None, new_type=None,analyst=None): """ Update the relationship type between two top-level objects. :param left_class: The first top-level object. :type left_class: :class:`cripts.core.cripts_mongoengine.CriptsBaseAttributes` :param right_class: The second top-level object. :type right_class: :class:`cripts.core.cripts_mongoengine.CriptsBaseAttributes` :param left_type: The type of first top-level object. :type left_type: str :param left_id: The ObjectId of the first top-level object. :type left_id: str :param right_type: The type of second top-level object. :type right_type: str :param right_id: The ObjectId of the second top-level object. :type right_id: str :param rel_type: The type of relationship. :type rel_type: str :param rel_date: The date this relationship applies. :type rel_date: datetime.datetime :param new_type: The new type of relationship. :type new_type: str :param analyst: The user updating this relationship. :type analyst: str :returns: dict with keys "success" (boolean) and "message" (str) """ if rel_date is None or rel_date == 'None': rel_date = None elif isinstance(rel_date, basestring) and rel_date != '': rel_date = parse(rel_date, fuzzy=True) elif not isinstance(rel_date, datetime.datetime): rel_date = None if not left_class: if left_type and left_id: left_class = class_from_id(left_type, left_id) if not left_class: return {'success': False, 'message': "Unable to get object."} else: return {'success': False, 'message': "Need a valid left type and id"} # update relationship if right_class: results = left_class.edit_relationship_type(rel_item=right_class, rel_type=rel_type, rel_date=rel_date, new_type=new_type, analyst=analyst) left_class.save(username=analyst) right_class.save(username=analyst) else: if right_type and right_id: results = left_class.edit_relationship_type(type_=right_type, rel_id=right_id, rel_type=rel_type, rel_date=rel_date, new_type=new_type, analyst=analyst) left_class.save(username=analyst) else: return {'success': False, 'message': "Need a valid right type and id"} return results def update_relationship_confidences(left_class=None, right_class=None, left_type=None, left_id=None, right_type=None, right_id=None, rel_type=None, rel_date=None, new_type=None,analyst=None, new_confidence='unknown'): """ Update the relationship type between two top-level objects. :param left_class: The first top-level object. :type left_class: :class:`cripts.core.cripts_mongoengine.CriptsBaseAttributes` :param right_class: The second top-level object. :type right_class: :class:`cripts.core.cripts_mongoengine.CriptsBaseAttributes` :param left_type: The type of first top-level object. :type left_type: str :param left_id: The ObjectId of the first top-level object. :type left_id: str :param right_type: The type of second top-level object. :type right_type: str :param right_id: The ObjectId of the second top-level object. :type right_id: str :param rel_type: The type of relationship. :type rel_type: str :param rel_date: The date this relationship applies. :type rel_date: datetime.datetime :param analyst: The user updating this relationship. :type analyst: str :param new_confidence: The new confidence level. :type new_confidence: str :returns: dict with keys "success" (boolean) and "message" (str) """ if rel_date is None or rel_date == 'None': rel_date = None elif isinstance(rel_date, basestring) and rel_date != '': rel_date = parse(rel_date, fuzzy=True) elif not isinstance(rel_date, datetime.datetime): rel_date = None if not left_class: if left_type and left_id: left_class = class_from_id(left_type, left_id) else: return {'success': False, 'message': "Need a valid left type and id"} # update relationship if right_class: results = left_class.edit_relationship_confidence(rel_item=right_class, rel_type=rel_type, rel_date=rel_date, new_confidence=new_confidence, analyst=analyst) left_class.save(username=analyst) right_class.save(username=analyst) else: if right_type and right_id: results = left_class.edit_relationship_confidence(type_=right_type, rel_id=right_id, rel_type=rel_type, rel_date=rel_date, new_confidence=new_confidence, analyst=analyst) left_class.save(username=analyst) else: return {'success': False, 'message': "Need a valid right type and id"} return results def update_relationship_reasons(left_class=None, right_class=None, left_type=None, left_id=None, right_type=None, right_id=None, rel_type=None, rel_date=None, new_type=None,analyst=None, new_reason="N/A"): """ Update the relationship type between two top-level objects. :param left_class: The first top-level object. :type left_class: :class:`cripts.core.cripts_mongoengine.CriptsBaseAttributes` :param right_class: The second top-level object. :type right_class: :class:`cripts.core.cripts_mongoengine.CriptsBaseAttributes` :param left_type: The type of first top-level object. :type left_type: str :param left_id: The ObjectId of the first top-level object. :type left_id: str :param right_type: The type of second top-level object. :type right_type: str :param right_id: The ObjectId of the second top-level object. :type right_id: str :param rel_type: The type of relationship. :type rel_type: str :param rel_date: The date this relationship applies. :type rel_date: datetime.datetime :param analyst: The user updating this relationship. :type analyst: str :returns: dict with keys "success" (boolean) and "message" (str) """ if rel_date is None or rel_date == 'None': rel_date = None elif isinstance(rel_date, basestring) and rel_date != '': rel_date = parse(rel_date, fuzzy=True) elif not isinstance(rel_date, datetime.datetime): rel_date = None if not left_class: if left_type and left_id: left_class = class_from_id(left_type, left_id) else: return {'success': False, 'message': "Need a valid left type and id"} # update relationship if right_class: results = left_class.edit_relationship_reason(rel_item=right_class, rel_type=rel_type, rel_date=rel_date, new_reason=new_reason, analyst=analyst) left_class.save(username=analyst) right_class.save(username=analyst) else: if right_type and right_id: results = left_class.edit_relationship_reason(type_=right_type, rel_id=right_id, rel_type=rel_type, rel_date=rel_date, new_reason=new_reason, analyst=analyst) left_class.save(username=analyst) else: return {'success': False, 'message': "Need a valid right type and id"} return results def update_relationship_dates(left_class=None, right_class=None, left_type=None, left_id=None, right_type=None, right_id=None, rel_type=None, rel_date=None, new_date=None,analyst=None): """ Update the relationship date between two top-level objects. :param left_class: The first top-level object. :type left_class: :class:`cripts.core.cripts_mongoengine.CriptsBaseAttributes` :param right_class: The second top-level object. :type right_class: :class:`cripts.core.cripts_mongoengine.CriptsBaseAttributes` :param left_type: The type of first top-level object. :type left_type: str :param left_id: The ObjectId of the first top-level object. :type left_id: str :param right_type: The type of second top-level object. :type right_type: str :param right_id: The ObjectId of the second top-level object. :type right_id: str :param rel_type: The type of relationship. :type rel_type: str :param rel_date: The date this relationship applies. :type rel_date: datetime.datetime :param new_date: The new date of the relationship. :type new_date: str :param analyst: The user updating this relationship. :type analyst: str :returns: dict with keys "success" (boolean) and "message" (str) """ if rel_date is None or rel_date == 'None': rel_date = None elif isinstance(rel_date, basestring) and rel_date != '': rel_date = parse(rel_date, fuzzy=True) elif not isinstance(rel_date, datetime.datetime): rel_date = None if new_date is None or new_date == 'None': new_date = None elif isinstance(new_date, basestring) and new_date != '': new_date = parse(new_date, fuzzy=True) elif not isinstance(new_date, datetime.datetime): new_date = None if not left_class: if left_type and left_id: left_class = class_from_id(left_type, left_id) if not left_class: return {'success': False, 'message': "Unable to get object."} else: return {'success': False, 'message': "Need a valid left type and id"} # update relationship if right_class: results = left_class.edit_relationship_date(rel_item=right_class, rel_type=rel_type, rel_date=rel_date, new_date=new_date, analyst=analyst) left_class.save(username=analyst) right_class.save(username=analyst) else: if right_type and right_id: results = left_class.edit_relationship_date(type_=right_type, rel_id=right_id, rel_type=rel_type, rel_date=rel_date, new_date=new_date, analyst=analyst) left_class.save(username=analyst) else: return {'success': False, 'message': "Need a valid right type and id"} return results

42.522449

95

0.578038

import datetime from dateutil.parser import parse from cripts.core.class_mapper import class_from_id def get_relationships(obj=None, type_=None, id_=None, analyst=None): if obj: return obj.sort_relationships("%s" % analyst, meta=True) elif type_ and id_: obj = class_from_id(type_, id_) if not obj: return {} return obj.sort_relationships("%s" % analyst, meta=True) else: return {} def forge_relationship(type_=None, id_=None, class_=None, right_type=None, right_id=None, right_class=None, rel_type=None, rel_date=None, user=None, rel_reason="", rel_confidence='unknown', get_rels=False, **kwargs): if rel_date == 'None': rel_date = None elif isinstance(rel_date, basestring) and rel_date != '': rel_date = parse(rel_date, fuzzy=True) elif not isinstance(rel_date, datetime.datetime): rel_date = None if not class_: if type_ and id_: class_ = class_from_id(type_, id_) if not class_: return {'success': False, 'message': "Failed to get left TLO"} if not right_class: if right_type and right_id: print ("right type:" + str(right_type)) print ("right id:" + str(right_id)) right_class = class_from_id(right_type, right_id) if not right_class: return {'success': False, 'message': "Failed to get right TLO"} try: results = class_.add_relationship(right_class, rel_type, rel_date, user, rel_confidence, rel_reason) except Exception as e: return {'success': False, 'message': e} if results['success']: class_.update(add_to_set__relationships=results['message']) if get_rels: results['relationships'] = class_.sort_relationships("%s" % user, meta=True) return results def delete_all_relationships(left_class=None, left_type=None, left_id=None, analyst=None): if not left_class: if left_type and left_id: left_class = class_from_id(left_type, left_id) if not left_class: return {'success': False, 'message': "Unable to get object."} else: return {'success': False, 'message': "Need a valid left type and id"} return left_class.delete_all_relationships() def delete_relationship(left_class=None, right_class=None, left_type=None, left_id=None, right_type=None, right_id=None, rel_type=None, rel_date=None, analyst=None, get_rels=True): if rel_date is None or rel_date == 'None': rel_date = None elif isinstance(rel_date, basestring) and rel_date != '': rel_date = parse(rel_date, fuzzy=True) elif not isinstance(rel_date, datetime.datetime): rel_date = None if not left_class: if left_type and left_id: left_class = class_from_id(left_type, left_id) if not left_class: return {'success': False, 'message': "Unable to get object."} else: return {'success': False, 'message': "Need a valid left type and id"} if right_class: results = left_class.delete_relationship(rel_item=right_class, rel_type=rel_type, rel_date=rel_date, analyst=analyst) else: if right_type and right_id: results = left_class.delete_relationship(type_=right_type, rel_id=right_id, rel_type=rel_type, rel_date=rel_date, analyst=analyst) else: return {'success': False, 'message': "Need a valid right type and id"} if results['success']: left_class.save(username=analyst) if get_rels: results['relationships'] = left_class.sort_relationships("%s" % analyst, meta=True) return results def update_relationship_types(left_class=None, right_class=None, left_type=None, left_id=None, right_type=None, right_id=None, rel_type=None, rel_date=None, new_type=None,analyst=None): if rel_date is None or rel_date == 'None': rel_date = None elif isinstance(rel_date, basestring) and rel_date != '': rel_date = parse(rel_date, fuzzy=True) elif not isinstance(rel_date, datetime.datetime): rel_date = None if not left_class: if left_type and left_id: left_class = class_from_id(left_type, left_id) if not left_class: return {'success': False, 'message': "Unable to get object."} else: return {'success': False, 'message': "Need a valid left type and id"} if right_class: results = left_class.edit_relationship_type(rel_item=right_class, rel_type=rel_type, rel_date=rel_date, new_type=new_type, analyst=analyst) left_class.save(username=analyst) right_class.save(username=analyst) else: if right_type and right_id: results = left_class.edit_relationship_type(type_=right_type, rel_id=right_id, rel_type=rel_type, rel_date=rel_date, new_type=new_type, analyst=analyst) left_class.save(username=analyst) else: return {'success': False, 'message': "Need a valid right type and id"} return results def update_relationship_confidences(left_class=None, right_class=None, left_type=None, left_id=None, right_type=None, right_id=None, rel_type=None, rel_date=None, new_type=None,analyst=None, new_confidence='unknown'): if rel_date is None or rel_date == 'None': rel_date = None elif isinstance(rel_date, basestring) and rel_date != '': rel_date = parse(rel_date, fuzzy=True) elif not isinstance(rel_date, datetime.datetime): rel_date = None if not left_class: if left_type and left_id: left_class = class_from_id(left_type, left_id) else: return {'success': False, 'message': "Need a valid left type and id"} if right_class: results = left_class.edit_relationship_confidence(rel_item=right_class, rel_type=rel_type, rel_date=rel_date, new_confidence=new_confidence, analyst=analyst) left_class.save(username=analyst) right_class.save(username=analyst) else: if right_type and right_id: results = left_class.edit_relationship_confidence(type_=right_type, rel_id=right_id, rel_type=rel_type, rel_date=rel_date, new_confidence=new_confidence, analyst=analyst) left_class.save(username=analyst) else: return {'success': False, 'message': "Need a valid right type and id"} return results def update_relationship_reasons(left_class=None, right_class=None, left_type=None, left_id=None, right_type=None, right_id=None, rel_type=None, rel_date=None, new_type=None,analyst=None, new_reason="N/A"): if rel_date is None or rel_date == 'None': rel_date = None elif isinstance(rel_date, basestring) and rel_date != '': rel_date = parse(rel_date, fuzzy=True) elif not isinstance(rel_date, datetime.datetime): rel_date = None if not left_class: if left_type and left_id: left_class = class_from_id(left_type, left_id) else: return {'success': False, 'message': "Need a valid left type and id"} if right_class: results = left_class.edit_relationship_reason(rel_item=right_class, rel_type=rel_type, rel_date=rel_date, new_reason=new_reason, analyst=analyst) left_class.save(username=analyst) right_class.save(username=analyst) else: if right_type and right_id: results = left_class.edit_relationship_reason(type_=right_type, rel_id=right_id, rel_type=rel_type, rel_date=rel_date, new_reason=new_reason, analyst=analyst) left_class.save(username=analyst) else: return {'success': False, 'message': "Need a valid right type and id"} return results def update_relationship_dates(left_class=None, right_class=None, left_type=None, left_id=None, right_type=None, right_id=None, rel_type=None, rel_date=None, new_date=None,analyst=None): if rel_date is None or rel_date == 'None': rel_date = None elif isinstance(rel_date, basestring) and rel_date != '': rel_date = parse(rel_date, fuzzy=True) elif not isinstance(rel_date, datetime.datetime): rel_date = None if new_date is None or new_date == 'None': new_date = None elif isinstance(new_date, basestring) and new_date != '': new_date = parse(new_date, fuzzy=True) elif not isinstance(new_date, datetime.datetime): new_date = None if not left_class: if left_type and left_id: left_class = class_from_id(left_type, left_id) if not left_class: return {'success': False, 'message': "Unable to get object."} else: return {'success': False, 'message': "Need a valid left type and id"} if right_class: results = left_class.edit_relationship_date(rel_item=right_class, rel_type=rel_type, rel_date=rel_date, new_date=new_date, analyst=analyst) left_class.save(username=analyst) right_class.save(username=analyst) else: if right_type and right_id: results = left_class.edit_relationship_date(type_=right_type, rel_id=right_id, rel_type=rel_type, rel_date=rel_date, new_date=new_date, analyst=analyst) left_class.save(username=analyst) else: return {'success': False, 'message': "Need a valid right type and id"} return results

true

1c45866e5a644fc50a8ed3659b45f9a0dee3b769

1,731

py

Python

pytorch/skin_lesion_classification/plots.py

deephealthproject/use-case-pipelines

ea9c8aedfbc9084e1a5350f6f73def2578258c77

[ "MIT" ]

1

2020-05-20T16:57:11.000Z

pytorch/skin_lesion_classification/plots.py

deephealthproject/use-case-pipelines

ea9c8aedfbc9084e1a5350f6f73def2578258c77

[ "MIT" ]

5

2021-03-26T16:01:51.000Z

2021-09-20T13:53:22.000Z

pytorch/skin_lesion_classification/plots.py

deephealthproject/use-case-pipelines

ea9c8aedfbc9084e1a5350f6f73def2578258c77

[ "MIT" ]

5

2020-05-18T09:44:03.000Z

2020-11-29T12:58:28.000Z

import itertools import matplotlib.pyplot as plt import numpy as np def plot_sequence(filename, sequences, legend=None): """Plots one or more sequences of values into a file :param filename: output filename :param sequences: (M x N) array-like structure containing M sequences of N values :param legend: (M) array-like legend :return: """ fig = plt.figure() for sequence in sequences: plt.plot(range(len(sequence)), sequence) if legend: plt.legend(legend) plt.savefig(filename) plt.close(fig) def plot_confusion_matrix(cm, classes, normalize=False, title='Confusion matrix', cmap=plt.cm.Blues): """ This function prints and plots the confusion matrix. Normalization can be applied by setting `normalize=True`. """ if normalize: cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis] print("Normalized confusion matrix") else: print('Confusion matrix, without normalization') print(cm) plt.imshow(cm, interpolation='nearest', cmap=cmap) plt.title(title) plt.colorbar() tick_marks = np.arange(len(classes)) plt.xticks(tick_marks, classes, rotation=45) plt.yticks(tick_marks, classes) plt.ylim(-0.5, len(classes) - 0.5) fmt = '.2f' if normalize else 'd' thresh = cm.max() / 2. for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])): plt.text(j, i, format(cm[i, j], fmt), horizontalalignment="center", color="white" if cm[i, j] > thresh else "black") plt.tight_layout() plt.ylabel('True label') plt.xlabel('Predicted label')

29.844828

85

0.617562

import itertools import matplotlib.pyplot as plt import numpy as np def plot_sequence(filename, sequences, legend=None): fig = plt.figure() for sequence in sequences: plt.plot(range(len(sequence)), sequence) if legend: plt.legend(legend) plt.savefig(filename) plt.close(fig) def plot_confusion_matrix(cm, classes, normalize=False, title='Confusion matrix', cmap=plt.cm.Blues): if normalize: cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis] print("Normalized confusion matrix") else: print('Confusion matrix, without normalization') print(cm) plt.imshow(cm, interpolation='nearest', cmap=cmap) plt.title(title) plt.colorbar() tick_marks = np.arange(len(classes)) plt.xticks(tick_marks, classes, rotation=45) plt.yticks(tick_marks, classes) plt.ylim(-0.5, len(classes) - 0.5) fmt = '.2f' if normalize else 'd' thresh = cm.max() / 2. for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])): plt.text(j, i, format(cm[i, j], fmt), horizontalalignment="center", color="white" if cm[i, j] > thresh else "black") plt.tight_layout() plt.ylabel('True label') plt.xlabel('Predicted label')

true

1c4586bd66611dfec7cf8c2a805839086f354af2

232

py

Python

lib/JumpScale/baselib/dnsman/dnsFactory.py

rudecs/jumpscale_core7

30c03f26f1cdad3edbb9d79d50fbada8acc974f5

[ "Apache-2.0" ]

null

lib/JumpScale/baselib/dnsman/dnsFactory.py

rudecs/jumpscale_core7

30c03f26f1cdad3edbb9d79d50fbada8acc974f5

[ "Apache-2.0" ]

4

2016-08-25T12:08:39.000Z

2018-04-12T12:36:01.000Z

lib/JumpScale/baselib/dnsman/dnsFactory.py

rudecs/jumpscale_core7

30c03f26f1cdad3edbb9d79d50fbada8acc974f5

[ "Apache-2.0" ]

3

2016-03-08T07:49:34.000Z

2018-10-19T13:56:43.000Z

from bind import BindDNS class DNSFactory(object): def __init__(self): self.bindObj = None @property def bind(self): if not self.bindObj: self.bindObj = BindDNS() return self.bindObj

21.090909

36

0.612069

from bind import BindDNS class DNSFactory(object): def __init__(self): self.bindObj = None @property def bind(self): if not self.bindObj: self.bindObj = BindDNS() return self.bindObj

true

1c45875f0c9405efffecbefbf3c272cc94cee782

7,536

py

Python

main/cloudfoundry_client/v2/entities.py

subhash12/cf-python-client

c0ecbb8ec85040fc2f74b6c52e1f9a6c6c16c4b0

[ "Apache-2.0" ]

null

main/cloudfoundry_client/v2/entities.py

subhash12/cf-python-client

c0ecbb8ec85040fc2f74b6c52e1f9a6c6c16c4b0

[ "Apache-2.0" ]

null

main/cloudfoundry_client/v2/entities.py

subhash12/cf-python-client

c0ecbb8ec85040fc2f74b6c52e1f9a6c6c16c4b0

[ "Apache-2.0" ]

null

from functools import partial, reduce from typing import Callable, List, Tuple, Any, Optional, Generator, TYPE_CHECKING from urllib.parse import quote from requests import Response from cloudfoundry_client.errors import InvalidEntity from cloudfoundry_client.json_object import JsonObject from cloudfoundry_client.request_object import Request if TYPE_CHECKING: from cloudfoundry_client.client import CloudFoundryClient class Entity(JsonObject): def __init__(self, target_endpoint: str, client: "CloudFoundryClient", *args, **kwargs): super(Entity, self).__init__(*args, **kwargs) self.target_endpoint = target_endpoint self.client = client try: if not (isinstance(self.get("entity"), dict)): raise InvalidEntity(**self) for attribute, value in list(self["entity"].items()): domain_name, suffix = attribute.rpartition("_")[::2] if suffix == "url": manager_name = domain_name if domain_name.endswith("s") else "%ss" % domain_name try: other_manager = getattr(client.v2, manager_name) except AttributeError: # generic manager other_manager = EntityManager(target_endpoint, client, "") if domain_name.endswith("s"): new_method = partial(other_manager._list, value) else: new_method = partial(other_manager._get, value) new_method.__name__ = domain_name setattr(self, domain_name, new_method) except KeyError: raise InvalidEntity(**self) EntityBuilder = Callable[[List[Tuple[str, Any]]], Entity] PaginateEntities = Generator[Entity, None, None] class EntityManager(object): list_query_parameters = ["page", "results-per-page", "order-direction"] list_multi_parameters = ["order-by"] timestamp_parameters = ["timestamp"] def __init__( self, target_endpoint: str, client: "CloudFoundryClient", entity_uri: str, entity_builder: Optional[EntityBuilder] = None ): self.target_endpoint = target_endpoint self.entity_uri = entity_uri self.client = client self.entity_builder = ( entity_builder if entity_builder is not None else lambda pairs: Entity(target_endpoint, client, pairs) ) def _list(self, requested_path: str, entity_builder: Optional[EntityBuilder] = None, **kwargs) -> PaginateEntities: url_requested = self._get_url_filtered("%s%s" % (self.target_endpoint, requested_path), **kwargs) response = self.client.get(url_requested) entity_builder = self._get_entity_builder(entity_builder) while True: response_json = self._read_response(response, JsonObject) for resource in response_json["resources"]: yield entity_builder(list(resource.items())) if response_json["next_url"] is None: break else: url_requested = "%s%s" % (self.target_endpoint, response_json["next_url"]) response = self.client.get(url_requested) def _create(self, data: dict, **kwargs) -> Entity: url = "%s%s" % (self.target_endpoint, self.entity_uri) return self._post(url, data, **kwargs) def _update(self, resource_id: str, data: dict, **kwargs): url = "%s%s/%s" % (self.target_endpoint, self.entity_uri, resource_id) return self._put(url, data, **kwargs) def _remove(self, resource_id: str, **kwargs): url = "%s%s/%s" % (self.target_endpoint, self.entity_uri, resource_id) self._delete(url, **kwargs) def _get(self, requested_path: str, entity_builder: Optional[EntityBuilder] = None) -> Entity: url = "%s%s" % (self.target_endpoint, requested_path) response = self.client.get(url) return self._read_response(response, entity_builder) def _post(self, url: str, data: Optional[dict] = None, **kwargs): response = self.client.post(url, json=data, **kwargs) return self._read_response(response) def _put(self, url: str, data: Optional[dict] = None, **kwargs): response = self.client.put(url, json=data, **kwargs) return self._read_response(response) def _delete(self, url: str, **kwargs): self.client.delete(url, **kwargs) def __iter__(self) -> PaginateEntities: return self.list() def __getitem__(self, entity_guid) -> Entity: return self.get(entity_guid) def list(self, **kwargs) -> PaginateEntities: return self._list(self.entity_uri, **kwargs) def get_first(self, **kwargs) -> Optional[Entity]: kwargs.setdefault("results-per-page", 1) for entity in self._list(self.entity_uri, **kwargs): return entity return None def get(self, entity_id: str, *extra_paths) -> Entity: if len(extra_paths) == 0: requested_path = "%s/%s" % (self.entity_uri, entity_id) else: requested_path = "%s/%s/%s" % (self.entity_uri, entity_id, "/".join(extra_paths)) return self._get(requested_path) def _read_response(self, response: Response, other_entity_builder: Optional[EntityBuilder] = None): entity_builder = self._get_entity_builder(other_entity_builder) result = response.json(object_pairs_hook=JsonObject) return entity_builder(list(result.items())) @staticmethod def _request(**mandatory_parameters) -> Request: return Request(**mandatory_parameters) def _get_entity_builder(self, entity_builder: Optional[EntityBuilder]) -> EntityBuilder: if entity_builder is None: return self.entity_builder else: return entity_builder def _get_url_filtered(self, url: str, **kwargs) -> str: def _append_encoded_parameter(parameters: List[str], args: Tuple[str, Any]) -> List[str]: parameter_name, parameter_value = args[0], args[1] if parameter_name in self.list_query_parameters: parameters.append("%s=%s" % (parameter_name, str(parameter_value))) elif parameter_name in self.list_multi_parameters: value_list = parameter_value if not isinstance(value_list, (list, tuple)): value_list = [value_list] for value in value_list: parameters.append("%s=%s" % (parameter_name, str(value))) elif parameter_name in self.timestamp_parameters: if isinstance(args[1], dict): operator_list = args[1].keys() for operator in operator_list: parameters.append("q=%s" % quote("%s%s%s" % (parameter_name, operator, args[1][operator]))) else: parameters.append("q=%s" % quote("%s:%s" % (parameter_name, str(parameter_value)))) elif isinstance(parameter_value, (list, tuple)): parameters.append("q=%s" % quote("%s IN %s" % (parameter_name, ",".join(parameter_value)))) else: parameters.append("q=%s" % quote("%s:%s" % (parameter_name, str(parameter_value)))) return parameters if len(kwargs) > 0: return "%s?%s" % (url, "&".join(reduce(_append_encoded_parameter, sorted(list(kwargs.items())), []))) else: return url

43.813953

129

0.625398

from functools import partial, reduce from typing import Callable, List, Tuple, Any, Optional, Generator, TYPE_CHECKING from urllib.parse import quote from requests import Response from cloudfoundry_client.errors import InvalidEntity from cloudfoundry_client.json_object import JsonObject from cloudfoundry_client.request_object import Request if TYPE_CHECKING: from cloudfoundry_client.client import CloudFoundryClient class Entity(JsonObject): def __init__(self, target_endpoint: str, client: "CloudFoundryClient", *args, **kwargs): super(Entity, self).__init__(*args, **kwargs) self.target_endpoint = target_endpoint self.client = client try: if not (isinstance(self.get("entity"), dict)): raise InvalidEntity(**self) for attribute, value in list(self["entity"].items()): domain_name, suffix = attribute.rpartition("_")[::2] if suffix == "url": manager_name = domain_name if domain_name.endswith("s") else "%ss" % domain_name try: other_manager = getattr(client.v2, manager_name) except AttributeError: other_manager = EntityManager(target_endpoint, client, "") if domain_name.endswith("s"): new_method = partial(other_manager._list, value) else: new_method = partial(other_manager._get, value) new_method.__name__ = domain_name setattr(self, domain_name, new_method) except KeyError: raise InvalidEntity(**self) EntityBuilder = Callable[[List[Tuple[str, Any]]], Entity] PaginateEntities = Generator[Entity, None, None] class EntityManager(object): list_query_parameters = ["page", "results-per-page", "order-direction"] list_multi_parameters = ["order-by"] timestamp_parameters = ["timestamp"] def __init__( self, target_endpoint: str, client: "CloudFoundryClient", entity_uri: str, entity_builder: Optional[EntityBuilder] = None ): self.target_endpoint = target_endpoint self.entity_uri = entity_uri self.client = client self.entity_builder = ( entity_builder if entity_builder is not None else lambda pairs: Entity(target_endpoint, client, pairs) ) def _list(self, requested_path: str, entity_builder: Optional[EntityBuilder] = None, **kwargs) -> PaginateEntities: url_requested = self._get_url_filtered("%s%s" % (self.target_endpoint, requested_path), **kwargs) response = self.client.get(url_requested) entity_builder = self._get_entity_builder(entity_builder) while True: response_json = self._read_response(response, JsonObject) for resource in response_json["resources"]: yield entity_builder(list(resource.items())) if response_json["next_url"] is None: break else: url_requested = "%s%s" % (self.target_endpoint, response_json["next_url"]) response = self.client.get(url_requested) def _create(self, data: dict, **kwargs) -> Entity: url = "%s%s" % (self.target_endpoint, self.entity_uri) return self._post(url, data, **kwargs) def _update(self, resource_id: str, data: dict, **kwargs): url = "%s%s/%s" % (self.target_endpoint, self.entity_uri, resource_id) return self._put(url, data, **kwargs) def _remove(self, resource_id: str, **kwargs): url = "%s%s/%s" % (self.target_endpoint, self.entity_uri, resource_id) self._delete(url, **kwargs) def _get(self, requested_path: str, entity_builder: Optional[EntityBuilder] = None) -> Entity: url = "%s%s" % (self.target_endpoint, requested_path) response = self.client.get(url) return self._read_response(response, entity_builder) def _post(self, url: str, data: Optional[dict] = None, **kwargs): response = self.client.post(url, json=data, **kwargs) return self._read_response(response) def _put(self, url: str, data: Optional[dict] = None, **kwargs): response = self.client.put(url, json=data, **kwargs) return self._read_response(response) def _delete(self, url: str, **kwargs): self.client.delete(url, **kwargs) def __iter__(self) -> PaginateEntities: return self.list() def __getitem__(self, entity_guid) -> Entity: return self.get(entity_guid) def list(self, **kwargs) -> PaginateEntities: return self._list(self.entity_uri, **kwargs) def get_first(self, **kwargs) -> Optional[Entity]: kwargs.setdefault("results-per-page", 1) for entity in self._list(self.entity_uri, **kwargs): return entity return None def get(self, entity_id: str, *extra_paths) -> Entity: if len(extra_paths) == 0: requested_path = "%s/%s" % (self.entity_uri, entity_id) else: requested_path = "%s/%s/%s" % (self.entity_uri, entity_id, "/".join(extra_paths)) return self._get(requested_path) def _read_response(self, response: Response, other_entity_builder: Optional[EntityBuilder] = None): entity_builder = self._get_entity_builder(other_entity_builder) result = response.json(object_pairs_hook=JsonObject) return entity_builder(list(result.items())) @staticmethod def _request(**mandatory_parameters) -> Request: return Request(**mandatory_parameters) def _get_entity_builder(self, entity_builder: Optional[EntityBuilder]) -> EntityBuilder: if entity_builder is None: return self.entity_builder else: return entity_builder def _get_url_filtered(self, url: str, **kwargs) -> str: def _append_encoded_parameter(parameters: List[str], args: Tuple[str, Any]) -> List[str]: parameter_name, parameter_value = args[0], args[1] if parameter_name in self.list_query_parameters: parameters.append("%s=%s" % (parameter_name, str(parameter_value))) elif parameter_name in self.list_multi_parameters: value_list = parameter_value if not isinstance(value_list, (list, tuple)): value_list = [value_list] for value in value_list: parameters.append("%s=%s" % (parameter_name, str(value))) elif parameter_name in self.timestamp_parameters: if isinstance(args[1], dict): operator_list = args[1].keys() for operator in operator_list: parameters.append("q=%s" % quote("%s%s%s" % (parameter_name, operator, args[1][operator]))) else: parameters.append("q=%s" % quote("%s:%s" % (parameter_name, str(parameter_value)))) elif isinstance(parameter_value, (list, tuple)): parameters.append("q=%s" % quote("%s IN %s" % (parameter_name, ",".join(parameter_value)))) else: parameters.append("q=%s" % quote("%s:%s" % (parameter_name, str(parameter_value)))) return parameters if len(kwargs) > 0: return "%s?%s" % (url, "&".join(reduce(_append_encoded_parameter, sorted(list(kwargs.items())), []))) else: return url

true

1c4587d7f261fcbda3642a50322883ae48f591a2

8,013

py

Python

karton/config_extractor/config_extractor.py

kscieslinski/karton-config-extractor

c0eb0bddeed2b217abe517ca1b8a20e679506dba

[ "BSD-3-Clause" ]

null

karton/config_extractor/config_extractor.py

kscieslinski/karton-config-extractor

c0eb0bddeed2b217abe517ca1b8a20e679506dba

[ "BSD-3-Clause" ]

null

karton/config_extractor/config_extractor.py

kscieslinski/karton-config-extractor

c0eb0bddeed2b217abe517ca1b8a20e679506dba

[ "BSD-3-Clause" ]

null

#!/usr/bin/python3 import gc import hashlib import json import os import re from karton.core import Config, Karton, Resource, Task from karton.core.resource import ResourceBase from malduck.extractor import ExtractManager, ExtractorModules from .__version__ import __version__ class AnalysisExtractManager(ExtractManager): """ Patched version of original ExtractManager, providing current karton interface """ def __init__(self, karton: "ConfigExtractor") -> None: super(AnalysisExtractManager, self).__init__(karton.modules) self.karton = karton def create_extractor(karton: "ConfigExtractor") -> AnalysisExtractManager: return AnalysisExtractManager(karton) class ConfigExtractor(Karton): """ Extracts configuration from samples and Drakvuf Sandbox analyses """ identity = "karton.config-extractor" version = __version__ persistent = True filters = [ { "type": "sample", "stage": "recognized", "kind": "runnable", "platform": "win32", }, { "type": "sample", "stage": "recognized", "kind": "runnable", "platform": "win64", }, { "type": "sample", "stage": "recognized", "kind": "runnable", "platform": "linux", }, {"type": "analysis", "kind": "drakrun-prod"}, {"type": "analysis", "kind": "drakrun"}, ] @classmethod def args_parser(cls): parser = super().args_parser() parser.add_argument( "--modules", help="Malduck extractor modules directory", default="extractor/modules", ) return parser @classmethod def main(cls): parser = cls.args_parser() args = parser.parse_args() config = Config(args.config_file) service = ConfigExtractor(config, modules=args.modules) service.loop() def __init__(self, config: Config, modules: str) -> None: super().__init__(config) self.modules = ExtractorModules(modules) def report_config(self, config, sample, parent=None): legacy_config = dict(config) legacy_config["type"] = config["family"] del legacy_config["family"] # This allows us to spawn karton tasks for special config handling if "store-in-karton" in legacy_config: self.log.info("Karton tasks found in config, sending") for karton_task in legacy_config["store-in-karton"]: task_data = karton_task["task"] payload_data = karton_task["payload"] payload_data["parent"] = parent or sample task = Task(headers=task_data, payload=payload_data) self.send_task(task) self.log.info("Sending ripped task %s", task.uid) del legacy_config["store-in-karton"] if len(legacy_config.items()) == 1: self.log.info("Final config is empty, not sending it to the reporter") return task = Task( { "type": "config", "kind": "static", "family": config["family"], "quality": self.current_task.headers.get("quality", "high"), }, payload={ "config": legacy_config, "sample": sample, "parent": parent or sample, }, ) self.send_task(task) # analyze a standard, non-dump sample def analyze_sample(self, sample: ResourceBase) -> None: extractor = create_extractor(self) with sample.download_temporary_file() as temp: # type: ignore extractor.push_file(temp.name) configs = extractor.config if configs: config = configs[0] self.log.info("Got config: {}".format(json.dumps(config))) self.report_config(config, sample) else: self.log.info("Failed to get config") # analyze a drakrun analysis def analyze_drakrun(self, sample, path): extractor = create_extractor(self) dumps_path = os.path.join(path, "dumps") dump_candidates = {} results = { "analysed": 0, "crashed": 0, } analysis_dumps = sorted(os.listdir(dumps_path)) for i, dump in enumerate(analysis_dumps): # catch only dumps if re.match(r"^[a-f0-9]{4,16}_[a-f0-9]{16}$", dump): results["analysed"] += 1 self.log.debug( "Analyzing dump %d/%d %s", i, len(analysis_dumps), str(dump) ) dump_path = os.path.join(dumps_path, dump) with open(dump_path, "rb") as f: dump_data = f.read() if not dump_data: self.log.warning("Dump {} is empty".format(dump)) continue base = int(dump.split("_")[0], 16) try: family = extractor.push_file(dump_path, base=base) if family: self.log.info("Found better %s config in %s", family, dump) dump_candidates[family] = (dump, dump_data) except Exception: self.log.exception("Error while extracting from {}".format(dump)) results["crashed"] += 1 self.log.debug("Finished analysing dump no. %d", i) self.log.info("Merging and reporting extracted configs") for family, config in extractor.configs.items(): dump, dump_data = dump_candidates[family] self.log.info("* (%s) %s => %s", family, dump, json.dumps(config)) parent = Resource(name=dump, content=dump_data) task = Task( { "type": "sample", "stage": "analyzed", "kind": "dump", "platform": "win32", "extension": "exe", }, payload={ "sample": parent, "parent": sample, "tags": ["dump:win32:exe"], }, ) self.send_task(task) self.report_config(config, sample, parent=parent) self.log.info("done analysing, results: {}".format(json.dumps(results))) def process(self, task: Task) -> None: # type: ignore sample = task.get_resource("sample") headers = task.headers if headers["type"] == "sample": self.log.info("Analyzing original binary") self.analyze_sample(sample) elif headers["type"] == "analysis" and headers["kind"] == "drakrun-prod": analysis = task.get_resource("analysis") if analysis.size > 1024 * 1024 * 128: self.log.info("Analysis is too large, aborting") return with analysis.extract_temporary() as fpath: # type: ignore with open(os.path.join(fpath, "sample.txt"), "r") as f: sample_hash = f.read() self.log.info( "Processing drakmon analysis, sample: {}".format(sample_hash) ) self.analyze_drakrun(sample, fpath) elif headers["type"] == "analysis" and headers["kind"] == "drakrun": # DRAKVUF Sandbox (codename: drakmon OSS) sample_hash = hashlib.sha256(sample.content or b"").hexdigest() self.log.info( "Processing drakmon OSS analysis, sample: {}".format(sample_hash) ) dumps = task.get_resource("dumps.zip") with dumps.extract_temporary() as tmpdir: # type: ignore self.analyze_drakrun(sample, tmpdir) self.log.debug("Printing gc stats") self.log.debug(gc.get_stats())

34.097872

85

0.539998

import gc import hashlib import json import os import re from karton.core import Config, Karton, Resource, Task from karton.core.resource import ResourceBase from malduck.extractor import ExtractManager, ExtractorModules from .__version__ import __version__ class AnalysisExtractManager(ExtractManager): def __init__(self, karton: "ConfigExtractor") -> None: super(AnalysisExtractManager, self).__init__(karton.modules) self.karton = karton def create_extractor(karton: "ConfigExtractor") -> AnalysisExtractManager: return AnalysisExtractManager(karton) class ConfigExtractor(Karton): identity = "karton.config-extractor" version = __version__ persistent = True filters = [ { "type": "sample", "stage": "recognized", "kind": "runnable", "platform": "win32", }, { "type": "sample", "stage": "recognized", "kind": "runnable", "platform": "win64", }, { "type": "sample", "stage": "recognized", "kind": "runnable", "platform": "linux", }, {"type": "analysis", "kind": "drakrun-prod"}, {"type": "analysis", "kind": "drakrun"}, ] @classmethod def args_parser(cls): parser = super().args_parser() parser.add_argument( "--modules", help="Malduck extractor modules directory", default="extractor/modules", ) return parser @classmethod def main(cls): parser = cls.args_parser() args = parser.parse_args() config = Config(args.config_file) service = ConfigExtractor(config, modules=args.modules) service.loop() def __init__(self, config: Config, modules: str) -> None: super().__init__(config) self.modules = ExtractorModules(modules) def report_config(self, config, sample, parent=None): legacy_config = dict(config) legacy_config["type"] = config["family"] del legacy_config["family"] if "store-in-karton" in legacy_config: self.log.info("Karton tasks found in config, sending") for karton_task in legacy_config["store-in-karton"]: task_data = karton_task["task"] payload_data = karton_task["payload"] payload_data["parent"] = parent or sample task = Task(headers=task_data, payload=payload_data) self.send_task(task) self.log.info("Sending ripped task %s", task.uid) del legacy_config["store-in-karton"] if len(legacy_config.items()) == 1: self.log.info("Final config is empty, not sending it to the reporter") return task = Task( { "type": "config", "kind": "static", "family": config["family"], "quality": self.current_task.headers.get("quality", "high"), }, payload={ "config": legacy_config, "sample": sample, "parent": parent or sample, }, ) self.send_task(task) def analyze_sample(self, sample: ResourceBase) -> None: extractor = create_extractor(self) with sample.download_temporary_file() as temp: extractor.push_file(temp.name) configs = extractor.config if configs: config = configs[0] self.log.info("Got config: {}".format(json.dumps(config))) self.report_config(config, sample) else: self.log.info("Failed to get config") def analyze_drakrun(self, sample, path): extractor = create_extractor(self) dumps_path = os.path.join(path, "dumps") dump_candidates = {} results = { "analysed": 0, "crashed": 0, } analysis_dumps = sorted(os.listdir(dumps_path)) for i, dump in enumerate(analysis_dumps): if re.match(r"^[a-f0-9]{4,16}_[a-f0-9]{16}$", dump): results["analysed"] += 1 self.log.debug( "Analyzing dump %d/%d %s", i, len(analysis_dumps), str(dump) ) dump_path = os.path.join(dumps_path, dump) with open(dump_path, "rb") as f: dump_data = f.read() if not dump_data: self.log.warning("Dump {} is empty".format(dump)) continue base = int(dump.split("_")[0], 16) try: family = extractor.push_file(dump_path, base=base) if family: self.log.info("Found better %s config in %s", family, dump) dump_candidates[family] = (dump, dump_data) except Exception: self.log.exception("Error while extracting from {}".format(dump)) results["crashed"] += 1 self.log.debug("Finished analysing dump no. %d", i) self.log.info("Merging and reporting extracted configs") for family, config in extractor.configs.items(): dump, dump_data = dump_candidates[family] self.log.info("* (%s) %s => %s", family, dump, json.dumps(config)) parent = Resource(name=dump, content=dump_data) task = Task( { "type": "sample", "stage": "analyzed", "kind": "dump", "platform": "win32", "extension": "exe", }, payload={ "sample": parent, "parent": sample, "tags": ["dump:win32:exe"], }, ) self.send_task(task) self.report_config(config, sample, parent=parent) self.log.info("done analysing, results: {}".format(json.dumps(results))) def process(self, task: Task) -> None: sample = task.get_resource("sample") headers = task.headers if headers["type"] == "sample": self.log.info("Analyzing original binary") self.analyze_sample(sample) elif headers["type"] == "analysis" and headers["kind"] == "drakrun-prod": analysis = task.get_resource("analysis") if analysis.size > 1024 * 1024 * 128: self.log.info("Analysis is too large, aborting") return with analysis.extract_temporary() as fpath: with open(os.path.join(fpath, "sample.txt"), "r") as f: sample_hash = f.read() self.log.info( "Processing drakmon analysis, sample: {}".format(sample_hash) ) self.analyze_drakrun(sample, fpath) elif headers["type"] == "analysis" and headers["kind"] == "drakrun": sample_hash = hashlib.sha256(sample.content or b"").hexdigest() self.log.info( "Processing drakmon OSS analysis, sample: {}".format(sample_hash) ) dumps = task.get_resource("dumps.zip") with dumps.extract_temporary() as tmpdir: self.analyze_drakrun(sample, tmpdir) self.log.debug("Printing gc stats") self.log.debug(gc.get_stats())

true

1c458914cb33dd348d349ab2d97c4bf9208ef056

6,011

py

Python

Code/PrepareTables/SelectedROICorrs_positionVar.py

cirmuw/functional-twin-analysis

b6730f09f2143d5372f1a90d5fac47e3385e54fb

[ "Apache-2.0" ]

null

Code/PrepareTables/SelectedROICorrs_positionVar.py

cirmuw/functional-twin-analysis

b6730f09f2143d5372f1a90d5fac47e3385e54fb

[ "Apache-2.0" ]

null

Code/PrepareTables/SelectedROICorrs_positionVar.py

cirmuw/functional-twin-analysis

b6730f09f2143d5372f1a90d5fac47e3385e54fb

[ "Apache-2.0" ]

null

#script to create tabels containig x, y and z coordinates of functionally corresponding vertices (position variability) for each twin, one table per vertex #input:id of functionally corresponding vetices of each twin to reference #output: tables with vertex position in each subject, one table per vetex import numpy as np import nibabel as nib import pandas as pd from glob import glob import os, sys currentdir = os.path.dirname(os.path.realpath(__file__)) parentdir = os.path.dirname(currentdir) sys.path.append(parentdir) import settings as s import pickle #paths to subject data,id of vertices without signal, surface file, parcelation, chosen rois infile =s.HCP_information_sheet_path #\ subjectpath1=s.HCProot+'HCP_3T_RESTA_fmri/'# used obtain subject ids subjectpath2=s.HCProot+'HCP_3T_RESTB_fmri/'#/ source_dir=s.projectfolder+'7NETS_vertex/5_7nets_corresponding/' # path containing id of functionally corresponding vetices of each twin to reference target_dir=s.projectfolder+'/7NETS_vertex/10_PositionVar_cosine/'# output tables with vertex position in each subject if not os.path.exists(target_dir): os.mkdir(target_dir) zerovertexlh=np.load('../../Deliveries/0verticeslh.npy')#ids of vertices without signal zerovertexrh=np.load('../../Deliveries/0verticesrh.npy') surfacedirlh='../../Deliveries/fsaverage4/lh.inflated' # surface on which vertex coordinates are based surfacedirrh='../../Deliveries/fsaverage4/rh.inflated' lhsurf=nib.freesurfer.io.read_geometry(surfacedirlh) rhsurf=nib.freesurfer.io.read_geometry(surfacedirrh) lhsurf=lhsurf[0] lhsurf=np.delete(lhsurf,zerovertexlh,0) rhsurf=rhsurf[0] rhsurf=np.delete(rhsurf,zerovertexrh,0) surf=np.concatenate([lhsurf,rhsurf],axis=0) lhparpath='../../Deliveries/lh.Schaefer2018_600Parcels_7Networks_order.annot' rhparpath='../../Deliveries/rh.Schaefer2018_600Parcels_7Networks_order.annot' lhannot=nib.freesurfer.io.read_annot(lhparpath) lhlabels=lhannot[0] rhannot=nib.freesurfer.io.read_annot(rhparpath) rhlabels=rhannot[0] labelslh=np.delete(lhlabels,zerovertexlh,0) labelsrh=np.delete(rhlabels,zerovertexrh,0) lhrois=list(np.load('../../Deliveries/chosenroislh.npy'))#save id of chosen rois rhrois=list(np.load('../../Deliveries/chosenroisrh.npy')) lhrois=lhrois[1:] rhrois=rhrois[1:] nameslhrois=['l_'+str(s) for s in lhrois] namesrhrois=['r_'+str(s) for s in rhrois] #get assigenment of parcels to yeo nets based on color table lhnetwork=np.zeros((9)) rhnetwork=np.zeros((9)) lhnetwork[8]=301 rhnetwork[8]=301 c1=1 c2=1 for i in range(1,301): if abs(lhannot[1][i][0]-lhannot[1][i-1][0])>5: lhnetwork[c1]=int(i) c1=c1+1 if abs(rhannot[1][i][0]-rhannot[1][i-1][0])>5: rhnetwork[c2]=int(i) c2=c2+1 #Get paths to mgh-files of available subjects xl=pd.ExcelFile(infile) dataframe1=xl.parse('Sheet1') isNotTwin=dataframe1['Twin_Stat']=='NotTwin' isNotTwin=np.where(isNotTwin)[0] dataframe2=dataframe1.drop(isNotTwin,0) Subjects=dataframe2['Subject'].values path1=[] path2=[] for i in range(Subjects.shape[0]): path1.append(subjectpath1+str(Subjects[i])) path2.append(subjectpath2+str(Subjects[i])) truesubjects=[] for i in range(Subjects.shape[0]): if os.path.isdir(path1[i])==True: truesubjects.append(Subjects[i]) if os.path.isdir(path2[i])==True: truesubjects.append(Subjects[i]) name=['Subject','Zygosity','Mother_ID'] nonvertexdat=np.zeros((len(truesubjects),3),dtype=object) for j in range(len(labelslh)): if labelslh[j]!=0: positionvar=[] for i in range(len(truesubjects)): functional=pickle.load(open(source_dir+'lh_'+str(j+1)+'correspondingvertices.p','rb')) index=np.where(functional[1]==-1)[0] index=functional[0][i][index] index=index[0] coords=surf[index] positionframe=pd.DataFrame(coords) positionframe.columns=['x','y','z'] positionvar.append(positionframe) if j==0: index=dataframe2[dataframe2['Subject']==truesubjects[i]].index.tolist() tmp1=np.array([str(truesubjects[i]),dataframe2['Zygosity'][index].values[0], str(dataframe2['Mother_ID'][index].values[0])]) nonvertexdat[i,:]=tmp1 nonvertextable=pd.DataFrame(data=nonvertexdat) nonvertextable.columns=name positionframe=pd.concat(positionvar,axis=0,ignore_index=True) table=pd.concat([nonvertextable,positionframe],axis=1) table=table.sort_values(['Zygosity', 'Mother_ID'], axis=0, ascending=[True,True]) table.reset_index(inplace=True) table=table.drop('index',axis=1) writefile=target_dir+'lh_'+str(j+1)+'_mean_position.csv.gz' table.to_csv(writefile, compression='gzip') for j in range(len(labelsrh)): if labelsrh[j]!=0: positionvar=[] for i in range(len(truesubjects)): functional=pickle.load(open(source_dir+'rh_'+str(j+1)+'correspondingvertices.p','rb')) index=np.where(functional[1]==-1)[0] index=functional[0][i][index] index=index[0] coords=surf[index] positionframe=pd.DataFrame(coords) positionframe.columns=['x','y','z'] positionvar.append(positionframe) nonvertextable=pd.DataFrame(data=nonvertexdat) nonvertextable.columns=name positionframe=pd.concat(positionvar,axis=0,ignore_index=True) table=pd.concat([nonvertextable,positionframe],axis=1) table=table.sort_values(['Zygosity', 'Mother_ID'], axis=0, ascending=[True,True]) table.reset_index(inplace=True) table=table.drop('index',axis=1) writefile=target_dir+'rh_'+str(j+1)+'_mean_position.csv.gz' table.to_csv(writefile, compression='gzip') print('Finished')

38.044304

155

0.683081

import numpy as np import nibabel as nib import pandas as pd from glob import glob import os, sys currentdir = os.path.dirname(os.path.realpath(__file__)) parentdir = os.path.dirname(currentdir) sys.path.append(parentdir) import settings as s import pickle infile =s.HCP_information_sheet_path subjectpath1=s.HCProot+'HCP_3T_RESTA_fmri/' subjectpath2=s.HCProot+'HCP_3T_RESTB_fmri/' source_dir=s.projectfolder+'7NETS_vertex/5_7nets_corresponding/' target_dir=s.projectfolder+'/7NETS_vertex/10_PositionVar_cosine/' if not os.path.exists(target_dir): os.mkdir(target_dir) zerovertexlh=np.load('../../Deliveries/0verticeslh.npy') zerovertexrh=np.load('../../Deliveries/0verticesrh.npy') surfacedirlh='../../Deliveries/fsaverage4/lh.inflated' surfacedirrh='../../Deliveries/fsaverage4/rh.inflated' lhsurf=nib.freesurfer.io.read_geometry(surfacedirlh) rhsurf=nib.freesurfer.io.read_geometry(surfacedirrh) lhsurf=lhsurf[0] lhsurf=np.delete(lhsurf,zerovertexlh,0) rhsurf=rhsurf[0] rhsurf=np.delete(rhsurf,zerovertexrh,0) surf=np.concatenate([lhsurf,rhsurf],axis=0) lhparpath='../../Deliveries/lh.Schaefer2018_600Parcels_7Networks_order.annot' rhparpath='../../Deliveries/rh.Schaefer2018_600Parcels_7Networks_order.annot' lhannot=nib.freesurfer.io.read_annot(lhparpath) lhlabels=lhannot[0] rhannot=nib.freesurfer.io.read_annot(rhparpath) rhlabels=rhannot[0] labelslh=np.delete(lhlabels,zerovertexlh,0) labelsrh=np.delete(rhlabels,zerovertexrh,0) lhrois=list(np.load('../../Deliveries/chosenroislh.npy')) rhrois=list(np.load('../../Deliveries/chosenroisrh.npy')) lhrois=lhrois[1:] rhrois=rhrois[1:] nameslhrois=['l_'+str(s) for s in lhrois] namesrhrois=['r_'+str(s) for s in rhrois] lhnetwork=np.zeros((9)) rhnetwork=np.zeros((9)) lhnetwork[8]=301 rhnetwork[8]=301 c1=1 c2=1 for i in range(1,301): if abs(lhannot[1][i][0]-lhannot[1][i-1][0])>5: lhnetwork[c1]=int(i) c1=c1+1 if abs(rhannot[1][i][0]-rhannot[1][i-1][0])>5: rhnetwork[c2]=int(i) c2=c2+1 xl=pd.ExcelFile(infile) dataframe1=xl.parse('Sheet1') isNotTwin=dataframe1['Twin_Stat']=='NotTwin' isNotTwin=np.where(isNotTwin)[0] dataframe2=dataframe1.drop(isNotTwin,0) Subjects=dataframe2['Subject'].values path1=[] path2=[] for i in range(Subjects.shape[0]): path1.append(subjectpath1+str(Subjects[i])) path2.append(subjectpath2+str(Subjects[i])) truesubjects=[] for i in range(Subjects.shape[0]): if os.path.isdir(path1[i])==True: truesubjects.append(Subjects[i]) if os.path.isdir(path2[i])==True: truesubjects.append(Subjects[i]) name=['Subject','Zygosity','Mother_ID'] nonvertexdat=np.zeros((len(truesubjects),3),dtype=object) for j in range(len(labelslh)): if labelslh[j]!=0: positionvar=[] for i in range(len(truesubjects)): functional=pickle.load(open(source_dir+'lh_'+str(j+1)+'correspondingvertices.p','rb')) index=np.where(functional[1]==-1)[0] index=functional[0][i][index] index=index[0] coords=surf[index] positionframe=pd.DataFrame(coords) positionframe.columns=['x','y','z'] positionvar.append(positionframe) if j==0: index=dataframe2[dataframe2['Subject']==truesubjects[i]].index.tolist() tmp1=np.array([str(truesubjects[i]),dataframe2['Zygosity'][index].values[0], str(dataframe2['Mother_ID'][index].values[0])]) nonvertexdat[i,:]=tmp1 nonvertextable=pd.DataFrame(data=nonvertexdat) nonvertextable.columns=name positionframe=pd.concat(positionvar,axis=0,ignore_index=True) table=pd.concat([nonvertextable,positionframe],axis=1) table=table.sort_values(['Zygosity', 'Mother_ID'], axis=0, ascending=[True,True]) table.reset_index(inplace=True) table=table.drop('index',axis=1) writefile=target_dir+'lh_'+str(j+1)+'_mean_position.csv.gz' table.to_csv(writefile, compression='gzip') for j in range(len(labelsrh)): if labelsrh[j]!=0: positionvar=[] for i in range(len(truesubjects)): functional=pickle.load(open(source_dir+'rh_'+str(j+1)+'correspondingvertices.p','rb')) index=np.where(functional[1]==-1)[0] index=functional[0][i][index] index=index[0] coords=surf[index] positionframe=pd.DataFrame(coords) positionframe.columns=['x','y','z'] positionvar.append(positionframe) nonvertextable=pd.DataFrame(data=nonvertexdat) nonvertextable.columns=name positionframe=pd.concat(positionvar,axis=0,ignore_index=True) table=pd.concat([nonvertextable,positionframe],axis=1) table=table.sort_values(['Zygosity', 'Mother_ID'], axis=0, ascending=[True,True]) table.reset_index(inplace=True) table=table.drop('index',axis=1) writefile=target_dir+'rh_'+str(j+1)+'_mean_position.csv.gz' table.to_csv(writefile, compression='gzip') print('Finished')

true

1c458bedfb80717a0139eb3f7187e74d5601bb56

477

py

Python

{{cookiecutter.project_slug}}/{{cookiecutter.project_slug}}/basic/templatetags/form_tags.py

cubicuboctahedron/cookiecutter-django-wagtail

d7f668ce09ba2c4a3f98045ab8a6fcd286d36553

[ "Apache-2.0" ]

null

{{cookiecutter.project_slug}}/{{cookiecutter.project_slug}}/basic/templatetags/form_tags.py

cubicuboctahedron/cookiecutter-django-wagtail

d7f668ce09ba2c4a3f98045ab8a6fcd286d36553

[ "Apache-2.0" ]

null

{{cookiecutter.project_slug}}/{{cookiecutter.project_slug}}/basic/templatetags/form_tags.py

cubicuboctahedron/cookiecutter-django-wagtail

d7f668ce09ba2c4a3f98045ab8a6fcd286d36553

[ "Apache-2.0" ]

1

2020-04-07T10:07:07.000Z

from django import template register = template.Library() @register.filter(name='addcss') def addcss(field, css): return field.as_widget(attrs={"class":css}) @register.filter(name='add_attributes') def add_attributes(field, css): attrs = {} definition = css.split(',') for d in definition: if ':' not in d: attrs['class'] = d else: t, v = d.split(':') attrs[t] = v return field.as_widget(attrs=attrs)

21.681818

46

0.597484

from django import template register = template.Library() @register.filter(name='addcss') def addcss(field, css): return field.as_widget(attrs={"class":css}) @register.filter(name='add_attributes') def add_attributes(field, css): attrs = {} definition = css.split(',') for d in definition: if ':' not in d: attrs['class'] = d else: t, v = d.split(':') attrs[t] = v return field.as_widget(attrs=attrs)

true

1c458c303d4a0d97db1662628a538701eb8cf2dd

1,049

py

Python

test/hlt/pytest/python/com/huawei/iotplatform/client/dto/BatchTaskCreateInDTO.py

yuanyi-thu/AIOT-

27f67d98324593c4c6c66bbd5e2a4aa7b9a4ac1e

[ "BSD-3-Clause" ]

128

2018-10-29T04:11:47.000Z

2022-03-07T02:19:14.000Z

test/hlt/pytest/python/com/huawei/iotplatform/client/dto/BatchTaskCreateInDTO.py

yuanyi-thu/AIOT-

27f67d98324593c4c6c66bbd5e2a4aa7b9a4ac1e

[ "BSD-3-Clause" ]

40

2018-11-02T00:40:48.000Z

2021-12-07T09:33:56.000Z

test/hlt/pytest/python/com/huawei/iotplatform/client/dto/BatchTaskCreateInDTO.py

yuanyi-thu/AIOT-

27f67d98324593c4c6c66bbd5e2a4aa7b9a4ac1e

[ "BSD-3-Clause" ]

118

2018-10-29T08:43:57.000Z

2022-01-07T06:49:25.000Z

from com.huawei.iotplatform.client.dto.ObjectNode import ObjectNode from com.huawei.iotplatform.client.dto.TagDTO2 import TagDTO2 class BatchTaskCreateInDTO(object): tags = TagDTO2 param = ObjectNode def __init__(self): self.appId = None self.taskName = None self.taskType = None self.timeout = None def getAppId(self): return self.appId def setAppId(self, appId): self.appId = appId def getTaskName(self): return self.taskName def setTaskName(self, taskName): self.taskName = taskName def getTaskType(self): return self.taskType def setTaskType(self, taskType): self.taskType = taskType def getTimeout(self): return self.timeout def setTimeout(self, timeout): self.timeout = timeout def getTags(self): return self.tags def setTags(self, tags): self.tags = tags def getParam(self): return self.param def setParam(self, param): self.param = param

20.98

67

0.638704

from com.huawei.iotplatform.client.dto.ObjectNode import ObjectNode from com.huawei.iotplatform.client.dto.TagDTO2 import TagDTO2 class BatchTaskCreateInDTO(object): tags = TagDTO2 param = ObjectNode def __init__(self): self.appId = None self.taskName = None self.taskType = None self.timeout = None def getAppId(self): return self.appId def setAppId(self, appId): self.appId = appId def getTaskName(self): return self.taskName def setTaskName(self, taskName): self.taskName = taskName def getTaskType(self): return self.taskType def setTaskType(self, taskType): self.taskType = taskType def getTimeout(self): return self.timeout def setTimeout(self, timeout): self.timeout = timeout def getTags(self): return self.tags def setTags(self, tags): self.tags = tags def getParam(self): return self.param def setParam(self, param): self.param = param

true

1c458e127c7a31bedae9e99bb85864dbcdac3092

20,718

py

Python

nova/api/openstack/compute/legacy_v2/contrib/security_groups.py

ebalduf/nova-backports

6bf97ec73467de522d34ab7a17ca0e0874baa7f9

[ "Apache-2.0" ]

5

2016-04-28T16:20:38.000Z

2021-04-25T11:19:03.000Z

nova/api/openstack/compute/legacy_v2/contrib/security_groups.py

ebalduf/nova-backports

6bf97ec73467de522d34ab7a17ca0e0874baa7f9

[ "Apache-2.0" ]

null

nova/api/openstack/compute/legacy_v2/contrib/security_groups.py

ebalduf/nova-backports

6bf97ec73467de522d34ab7a17ca0e0874baa7f9

[ "Apache-2.0" ]

5

2020-04-08T20:24:45.000Z

2020-10-05T19:02:13.000Z

# Copyright 2011 OpenStack Foundation # Copyright 2012 Justin Santa Barbara # 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. """The security groups extension.""" import contextlib from xml.dom import minidom from oslo_log import log as logging from oslo_serialization import jsonutils import six import webob from webob import exc from nova.api.openstack import common from nova.api.openstack import extensions from nova.api.openstack import wsgi from nova import compute from nova import exception from nova.i18n import _ from nova.network.security_group import openstack_driver from nova.virt import netutils LOG = logging.getLogger(__name__) authorize = extensions.extension_authorizer('compute', 'security_groups') softauth = extensions.soft_extension_authorizer('compute', 'security_groups') def _authorize_context(req): context = req.environ['nova.context'] authorize(context) return context @contextlib.contextmanager def translate_exceptions(): """Translate nova exceptions to http exceptions.""" try: yield except exception.Invalid as exp: msg = exp.format_message() raise exc.HTTPBadRequest(explanation=msg) except exception.SecurityGroupNotFound as exp: msg = exp.format_message() raise exc.HTTPNotFound(explanation=msg) except exception.InstanceNotFound as exp: msg = exp.format_message() raise exc.HTTPNotFound(explanation=msg) except exception.SecurityGroupLimitExceeded as exp: msg = exp.format_message() raise exc.HTTPForbidden(explanation=msg) except exception.NoUniqueMatch as exp: msg = exp.format_message() raise exc.HTTPConflict(explanation=msg) class SecurityGroupControllerBase(object): """Base class for Security Group controllers.""" def __init__(self): self.security_group_api = ( openstack_driver.get_openstack_security_group_driver()) self.compute_api = compute.API( security_group_api=self.security_group_api) def _format_security_group_rule(self, context, rule, group_rule_data=None): """Return a security group rule in desired API response format. If group_rule_data is passed in that is used rather than querying for it. """ sg_rule = {} sg_rule['id'] = rule['id'] sg_rule['parent_group_id'] = rule['parent_group_id'] sg_rule['ip_protocol'] = rule['protocol'] sg_rule['from_port'] = rule['from_port'] sg_rule['to_port'] = rule['to_port'] sg_rule['group'] = {} sg_rule['ip_range'] = {} if rule['group_id']: with translate_exceptions(): try: source_group = self.security_group_api.get( context, id=rule['group_id']) except exception.SecurityGroupNotFound: # NOTE(arosen): There is a possible race condition that can # occur here if two api calls occur concurrently: one that # lists the security groups and another one that deletes a # security group rule that has a group_id before the # group_id is fetched. To handle this if # SecurityGroupNotFound is raised we return None instead # of the rule and the caller should ignore the rule. LOG.debug("Security Group ID %s does not exist", rule['group_id']) return sg_rule['group'] = {'name': source_group.get('name'), 'tenant_id': source_group.get('project_id')} elif group_rule_data: sg_rule['group'] = group_rule_data else: sg_rule['ip_range'] = {'cidr': rule['cidr']} return sg_rule def _format_security_group(self, context, group): security_group = {} security_group['id'] = group['id'] security_group['description'] = group['description'] security_group['name'] = group['name'] security_group['tenant_id'] = group['project_id'] security_group['rules'] = [] for rule in group['rules']: formatted_rule = self._format_security_group_rule(context, rule) if formatted_rule: security_group['rules'] += [formatted_rule] return security_group def _from_body(self, body, key): if not body: raise exc.HTTPBadRequest( explanation=_("The request body can't be empty")) value = body.get(key, None) if value is None: raise exc.HTTPBadRequest( explanation=_("Missing parameter %s") % key) return value class SecurityGroupController(SecurityGroupControllerBase): """The Security group API controller for the OpenStack API.""" def show(self, req, id): """Return data about the given security group.""" context = _authorize_context(req) with translate_exceptions(): id = self.security_group_api.validate_id(id) security_group = self.security_group_api.get(context, None, id, map_exception=True) return {'security_group': self._format_security_group(context, security_group)} def delete(self, req, id): """Delete a security group.""" context = _authorize_context(req) with translate_exceptions(): id = self.security_group_api.validate_id(id) security_group = self.security_group_api.get(context, None, id, map_exception=True) self.security_group_api.destroy(context, security_group) return webob.Response(status_int=202) def index(self, req): """Returns a list of security groups.""" context = _authorize_context(req) search_opts = {} search_opts.update(req.GET) with translate_exceptions(): project_id = context.project_id raw_groups = self.security_group_api.list(context, project=project_id, search_opts=search_opts) limited_list = common.limited(raw_groups, req) result = [self._format_security_group(context, group) for group in limited_list] return {'security_groups': list(sorted(result, key=lambda k: (k['tenant_id'], k['name'])))} def create(self, req, body): """Creates a new security group.""" context = _authorize_context(req) security_group = self._from_body(body, 'security_group') group_name = security_group.get('name', None) group_description = security_group.get('description', None) with translate_exceptions(): self.security_group_api.validate_property(group_name, 'name', None) self.security_group_api.validate_property(group_description, 'description', None) group_ref = self.security_group_api.create_security_group( context, group_name, group_description) return {'security_group': self._format_security_group(context, group_ref)} def update(self, req, id, body): """Update a security group.""" context = _authorize_context(req) with translate_exceptions(): id = self.security_group_api.validate_id(id) security_group = self.security_group_api.get(context, None, id, map_exception=True) security_group_data = self._from_body(body, 'security_group') group_name = security_group_data.get('name', None) group_description = security_group_data.get('description', None) with translate_exceptions(): self.security_group_api.validate_property(group_name, 'name', None) self.security_group_api.validate_property(group_description, 'description', None) group_ref = self.security_group_api.update_security_group( context, security_group, group_name, group_description) return {'security_group': self._format_security_group(context, group_ref)} class SecurityGroupRulesController(SecurityGroupControllerBase): def create(self, req, body): context = _authorize_context(req) sg_rule = self._from_body(body, 'security_group_rule') with translate_exceptions(): parent_group_id = self.security_group_api.validate_id( sg_rule.get('parent_group_id', None)) security_group = self.security_group_api.get(context, None, parent_group_id, map_exception=True) try: new_rule = self._rule_args_to_dict(context, to_port=sg_rule.get('to_port'), from_port=sg_rule.get('from_port'), ip_protocol=sg_rule.get('ip_protocol'), cidr=sg_rule.get('cidr'), group_id=sg_rule.get('group_id')) except exception.SecurityGroupNotFound as e: raise exc.HTTPNotFound(explanation=e.format_message()) except Exception as exp: raise exc.HTTPBadRequest(explanation=six.text_type(exp)) if new_rule is None: msg = _("Not enough parameters to build a valid rule.") raise exc.HTTPBadRequest(explanation=msg) new_rule['parent_group_id'] = security_group['id'] if 'cidr' in new_rule: net, prefixlen = netutils.get_net_and_prefixlen(new_rule['cidr']) if net not in ('0.0.0.0', '::') and prefixlen == '0': msg = _("Bad prefix for network in cidr %s") % new_rule['cidr'] raise exc.HTTPBadRequest(explanation=msg) group_rule_data = None with translate_exceptions(): if sg_rule.get('group_id'): source_group = self.security_group_api.get( context, id=sg_rule['group_id']) group_rule_data = {'name': source_group.get('name'), 'tenant_id': source_group.get('project_id')} security_group_rule = ( self.security_group_api.create_security_group_rule( context, security_group, new_rule)) formatted_rule = self._format_security_group_rule(context, security_group_rule, group_rule_data) return {"security_group_rule": formatted_rule} def _rule_args_to_dict(self, context, to_port=None, from_port=None, ip_protocol=None, cidr=None, group_id=None): if group_id is not None: group_id = self.security_group_api.validate_id(group_id) # check if groupId exists self.security_group_api.get(context, id=group_id) return self.security_group_api.new_group_ingress_rule( group_id, ip_protocol, from_port, to_port) else: cidr = self.security_group_api.parse_cidr(cidr) return self.security_group_api.new_cidr_ingress_rule( cidr, ip_protocol, from_port, to_port) def delete(self, req, id): context = _authorize_context(req) with translate_exceptions(): id = self.security_group_api.validate_id(id) rule = self.security_group_api.get_rule(context, id) group_id = rule['parent_group_id'] security_group = self.security_group_api.get(context, None, group_id, map_exception=True) self.security_group_api.remove_rules(context, security_group, [rule['id']]) return webob.Response(status_int=202) class ServerSecurityGroupController(SecurityGroupControllerBase): def index(self, req, server_id): """Returns a list of security groups for the given instance.""" context = _authorize_context(req) self.security_group_api.ensure_default(context) with translate_exceptions(): instance = common.get_instance(self.compute_api, context, server_id) groups = self.security_group_api.get_instance_security_groups( context, instance, True) result = [self._format_security_group(context, group) for group in groups] return {'security_groups': list(sorted(result, key=lambda k: (k['tenant_id'], k['name'])))} class SecurityGroupActionController(wsgi.Controller): def __init__(self, *args, **kwargs): super(SecurityGroupActionController, self).__init__(*args, **kwargs) self.security_group_api = ( openstack_driver.get_openstack_security_group_driver()) self.compute_api = compute.API( security_group_api=self.security_group_api) def _parse(self, body, action): try: body = body[action] group_name = body['name'] except TypeError: msg = _("Missing parameter dict") raise webob.exc.HTTPBadRequest(explanation=msg) except KeyError: msg = _("Security group not specified") raise webob.exc.HTTPBadRequest(explanation=msg) if not group_name or group_name.strip() == '': msg = _("Security group name cannot be empty") raise webob.exc.HTTPBadRequest(explanation=msg) return group_name def _invoke(self, method, context, id, group_name): with translate_exceptions(): instance = common.get_instance(self.compute_api, context, id) method(context, instance, group_name) return webob.Response(status_int=202) @wsgi.action('addSecurityGroup') def _addSecurityGroup(self, req, id, body): context = req.environ['nova.context'] authorize(context) group_name = self._parse(body, 'addSecurityGroup') return self._invoke(self.security_group_api.add_to_instance, context, id, group_name) @wsgi.action('removeSecurityGroup') def _removeSecurityGroup(self, req, id, body): context = req.environ['nova.context'] authorize(context) group_name = self._parse(body, 'removeSecurityGroup') return self._invoke(self.security_group_api.remove_from_instance, context, id, group_name) class SecurityGroupsOutputController(wsgi.Controller): def __init__(self, *args, **kwargs): super(SecurityGroupsOutputController, self).__init__(*args, **kwargs) self.compute_api = compute.API() self.security_group_api = ( openstack_driver.get_openstack_security_group_driver()) def _extend_servers(self, req, servers): # TODO(arosen) this function should be refactored to reduce duplicate # code and use get_instance_security_groups instead of get_db_instance. if not len(servers): return key = "security_groups" context = _authorize_context(req) if not openstack_driver.is_neutron_security_groups(): for server in servers: instance = req.get_db_instance(server['id']) groups = instance.get(key) if groups: server[key] = [{"name": group["name"]} for group in groups] else: # If method is a POST we get the security groups intended for an # instance from the request. The reason for this is if using # neutron security groups the requested security groups for the # instance are not in the db and have not been sent to neutron yet. if req.method != 'POST': sg_instance_bindings = ( self.security_group_api .get_instances_security_groups_bindings(context, servers)) for server in servers: groups = sg_instance_bindings.get(server['id']) if groups: server[key] = groups # In this section of code len(servers) == 1 as you can only POST # one server in an API request. else: try: # try converting to json req_obj = jsonutils.loads(req.body) # Add security group to server, if no security group was in # request add default since that is the group it is part of servers[0][key] = req_obj['server'].get( key, [{'name': 'default'}]) except ValueError: root = minidom.parseString(req.body) sg_root = root.getElementsByTagName(key) groups = [] if sg_root: security_groups = sg_root[0].getElementsByTagName( 'security_group') for security_group in security_groups: groups.append( {'name': security_group.getAttribute('name')}) if not groups: groups = [{'name': 'default'}] servers[0][key] = groups def _show(self, req, resp_obj): if not softauth(req.environ['nova.context']): return if 'server' in resp_obj.obj: self._extend_servers(req, [resp_obj.obj['server']]) @wsgi.extends def show(self, req, resp_obj, id): return self._show(req, resp_obj) @wsgi.extends def create(self, req, resp_obj, body): return self._show(req, resp_obj) @wsgi.extends def detail(self, req, resp_obj): if not softauth(req.environ['nova.context']): return self._extend_servers(req, list(resp_obj.obj['servers'])) class Security_groups(extensions.ExtensionDescriptor): """Security group support.""" name = "SecurityGroups" alias = "os-security-groups" namespace = "http://docs.openstack.org/compute/ext/securitygroups/api/v1.1" updated = "2013-05-28T00:00:00Z" def get_controller_extensions(self): controller = SecurityGroupActionController() actions = extensions.ControllerExtension(self, 'servers', controller) controller = SecurityGroupsOutputController() output = extensions.ControllerExtension(self, 'servers', controller) return [actions, output] def get_resources(self): resources = [] res = extensions.ResourceExtension('os-security-groups', controller=SecurityGroupController()) resources.append(res) res = extensions.ResourceExtension('os-security-group-rules', controller=SecurityGroupRulesController()) resources.append(res) res = extensions.ResourceExtension( 'os-security-groups', controller=ServerSecurityGroupController(), parent=dict(member_name='server', collection_name='servers')) resources.append(res) return resources

40.863905

79

0.592383

import contextlib from xml.dom import minidom from oslo_log import log as logging from oslo_serialization import jsonutils import six import webob from webob import exc from nova.api.openstack import common from nova.api.openstack import extensions from nova.api.openstack import wsgi from nova import compute from nova import exception from nova.i18n import _ from nova.network.security_group import openstack_driver from nova.virt import netutils LOG = logging.getLogger(__name__) authorize = extensions.extension_authorizer('compute', 'security_groups') softauth = extensions.soft_extension_authorizer('compute', 'security_groups') def _authorize_context(req): context = req.environ['nova.context'] authorize(context) return context @contextlib.contextmanager def translate_exceptions(): try: yield except exception.Invalid as exp: msg = exp.format_message() raise exc.HTTPBadRequest(explanation=msg) except exception.SecurityGroupNotFound as exp: msg = exp.format_message() raise exc.HTTPNotFound(explanation=msg) except exception.InstanceNotFound as exp: msg = exp.format_message() raise exc.HTTPNotFound(explanation=msg) except exception.SecurityGroupLimitExceeded as exp: msg = exp.format_message() raise exc.HTTPForbidden(explanation=msg) except exception.NoUniqueMatch as exp: msg = exp.format_message() raise exc.HTTPConflict(explanation=msg) class SecurityGroupControllerBase(object): def __init__(self): self.security_group_api = ( openstack_driver.get_openstack_security_group_driver()) self.compute_api = compute.API( security_group_api=self.security_group_api) def _format_security_group_rule(self, context, rule, group_rule_data=None): sg_rule = {} sg_rule['id'] = rule['id'] sg_rule['parent_group_id'] = rule['parent_group_id'] sg_rule['ip_protocol'] = rule['protocol'] sg_rule['from_port'] = rule['from_port'] sg_rule['to_port'] = rule['to_port'] sg_rule['group'] = {} sg_rule['ip_range'] = {} if rule['group_id']: with translate_exceptions(): try: source_group = self.security_group_api.get( context, id=rule['group_id']) except exception.SecurityGroupNotFound: LOG.debug("Security Group ID %s does not exist", rule['group_id']) return sg_rule['group'] = {'name': source_group.get('name'), 'tenant_id': source_group.get('project_id')} elif group_rule_data: sg_rule['group'] = group_rule_data else: sg_rule['ip_range'] = {'cidr': rule['cidr']} return sg_rule def _format_security_group(self, context, group): security_group = {} security_group['id'] = group['id'] security_group['description'] = group['description'] security_group['name'] = group['name'] security_group['tenant_id'] = group['project_id'] security_group['rules'] = [] for rule in group['rules']: formatted_rule = self._format_security_group_rule(context, rule) if formatted_rule: security_group['rules'] += [formatted_rule] return security_group def _from_body(self, body, key): if not body: raise exc.HTTPBadRequest( explanation=_("The request body can't be empty")) value = body.get(key, None) if value is None: raise exc.HTTPBadRequest( explanation=_("Missing parameter %s") % key) return value class SecurityGroupController(SecurityGroupControllerBase): def show(self, req, id): context = _authorize_context(req) with translate_exceptions(): id = self.security_group_api.validate_id(id) security_group = self.security_group_api.get(context, None, id, map_exception=True) return {'security_group': self._format_security_group(context, security_group)} def delete(self, req, id): context = _authorize_context(req) with translate_exceptions(): id = self.security_group_api.validate_id(id) security_group = self.security_group_api.get(context, None, id, map_exception=True) self.security_group_api.destroy(context, security_group) return webob.Response(status_int=202) def index(self, req): context = _authorize_context(req) search_opts = {} search_opts.update(req.GET) with translate_exceptions(): project_id = context.project_id raw_groups = self.security_group_api.list(context, project=project_id, search_opts=search_opts) limited_list = common.limited(raw_groups, req) result = [self._format_security_group(context, group) for group in limited_list] return {'security_groups': list(sorted(result, key=lambda k: (k['tenant_id'], k['name'])))} def create(self, req, body): context = _authorize_context(req) security_group = self._from_body(body, 'security_group') group_name = security_group.get('name', None) group_description = security_group.get('description', None) with translate_exceptions(): self.security_group_api.validate_property(group_name, 'name', None) self.security_group_api.validate_property(group_description, 'description', None) group_ref = self.security_group_api.create_security_group( context, group_name, group_description) return {'security_group': self._format_security_group(context, group_ref)} def update(self, req, id, body): context = _authorize_context(req) with translate_exceptions(): id = self.security_group_api.validate_id(id) security_group = self.security_group_api.get(context, None, id, map_exception=True) security_group_data = self._from_body(body, 'security_group') group_name = security_group_data.get('name', None) group_description = security_group_data.get('description', None) with translate_exceptions(): self.security_group_api.validate_property(group_name, 'name', None) self.security_group_api.validate_property(group_description, 'description', None) group_ref = self.security_group_api.update_security_group( context, security_group, group_name, group_description) return {'security_group': self._format_security_group(context, group_ref)} class SecurityGroupRulesController(SecurityGroupControllerBase): def create(self, req, body): context = _authorize_context(req) sg_rule = self._from_body(body, 'security_group_rule') with translate_exceptions(): parent_group_id = self.security_group_api.validate_id( sg_rule.get('parent_group_id', None)) security_group = self.security_group_api.get(context, None, parent_group_id, map_exception=True) try: new_rule = self._rule_args_to_dict(context, to_port=sg_rule.get('to_port'), from_port=sg_rule.get('from_port'), ip_protocol=sg_rule.get('ip_protocol'), cidr=sg_rule.get('cidr'), group_id=sg_rule.get('group_id')) except exception.SecurityGroupNotFound as e: raise exc.HTTPNotFound(explanation=e.format_message()) except Exception as exp: raise exc.HTTPBadRequest(explanation=six.text_type(exp)) if new_rule is None: msg = _("Not enough parameters to build a valid rule.") raise exc.HTTPBadRequest(explanation=msg) new_rule['parent_group_id'] = security_group['id'] if 'cidr' in new_rule: net, prefixlen = netutils.get_net_and_prefixlen(new_rule['cidr']) if net not in ('0.0.0.0', '::') and prefixlen == '0': msg = _("Bad prefix for network in cidr %s") % new_rule['cidr'] raise exc.HTTPBadRequest(explanation=msg) group_rule_data = None with translate_exceptions(): if sg_rule.get('group_id'): source_group = self.security_group_api.get( context, id=sg_rule['group_id']) group_rule_data = {'name': source_group.get('name'), 'tenant_id': source_group.get('project_id')} security_group_rule = ( self.security_group_api.create_security_group_rule( context, security_group, new_rule)) formatted_rule = self._format_security_group_rule(context, security_group_rule, group_rule_data) return {"security_group_rule": formatted_rule} def _rule_args_to_dict(self, context, to_port=None, from_port=None, ip_protocol=None, cidr=None, group_id=None): if group_id is not None: group_id = self.security_group_api.validate_id(group_id) # check if groupId exists self.security_group_api.get(context, id=group_id) return self.security_group_api.new_group_ingress_rule( group_id, ip_protocol, from_port, to_port) else: cidr = self.security_group_api.parse_cidr(cidr) return self.security_group_api.new_cidr_ingress_rule( cidr, ip_protocol, from_port, to_port) def delete(self, req, id): context = _authorize_context(req) with translate_exceptions(): id = self.security_group_api.validate_id(id) rule = self.security_group_api.get_rule(context, id) group_id = rule['parent_group_id'] security_group = self.security_group_api.get(context, None, group_id, map_exception=True) self.security_group_api.remove_rules(context, security_group, [rule['id']]) return webob.Response(status_int=202) class ServerSecurityGroupController(SecurityGroupControllerBase): def index(self, req, server_id): context = _authorize_context(req) self.security_group_api.ensure_default(context) with translate_exceptions(): instance = common.get_instance(self.compute_api, context, server_id) groups = self.security_group_api.get_instance_security_groups( context, instance, True) result = [self._format_security_group(context, group) for group in groups] return {'security_groups': list(sorted(result, key=lambda k: (k['tenant_id'], k['name'])))} class SecurityGroupActionController(wsgi.Controller): def __init__(self, *args, **kwargs): super(SecurityGroupActionController, self).__init__(*args, **kwargs) self.security_group_api = ( openstack_driver.get_openstack_security_group_driver()) self.compute_api = compute.API( security_group_api=self.security_group_api) def _parse(self, body, action): try: body = body[action] group_name = body['name'] except TypeError: msg = _("Missing parameter dict") raise webob.exc.HTTPBadRequest(explanation=msg) except KeyError: msg = _("Security group not specified") raise webob.exc.HTTPBadRequest(explanation=msg) if not group_name or group_name.strip() == '': msg = _("Security group name cannot be empty") raise webob.exc.HTTPBadRequest(explanation=msg) return group_name def _invoke(self, method, context, id, group_name): with translate_exceptions(): instance = common.get_instance(self.compute_api, context, id) method(context, instance, group_name) return webob.Response(status_int=202) @wsgi.action('addSecurityGroup') def _addSecurityGroup(self, req, id, body): context = req.environ['nova.context'] authorize(context) group_name = self._parse(body, 'addSecurityGroup') return self._invoke(self.security_group_api.add_to_instance, context, id, group_name) @wsgi.action('removeSecurityGroup') def _removeSecurityGroup(self, req, id, body): context = req.environ['nova.context'] authorize(context) group_name = self._parse(body, 'removeSecurityGroup') return self._invoke(self.security_group_api.remove_from_instance, context, id, group_name) class SecurityGroupsOutputController(wsgi.Controller): def __init__(self, *args, **kwargs): super(SecurityGroupsOutputController, self).__init__(*args, **kwargs) self.compute_api = compute.API() self.security_group_api = ( openstack_driver.get_openstack_security_group_driver()) def _extend_servers(self, req, servers): # TODO(arosen) this function should be refactored to reduce duplicate # code and use get_instance_security_groups instead of get_db_instance. if not len(servers): return key = "security_groups" context = _authorize_context(req) if not openstack_driver.is_neutron_security_groups(): for server in servers: instance = req.get_db_instance(server['id']) groups = instance.get(key) if groups: server[key] = [{"name": group["name"]} for group in groups] else: # If method is a POST we get the security groups intended for an # instance from the request. The reason for this is if using # neutron security groups the requested security groups for the # instance are not in the db and have not been sent to neutron yet. if req.method != 'POST': sg_instance_bindings = ( self.security_group_api .get_instances_security_groups_bindings(context, servers)) for server in servers: groups = sg_instance_bindings.get(server['id']) if groups: server[key] = groups # In this section of code len(servers) == 1 as you can only POST # one server in an API request. else: try: # try converting to json req_obj = jsonutils.loads(req.body) # Add security group to server, if no security group was in # request add default since that is the group it is part of servers[0][key] = req_obj['server'].get( key, [{'name': 'default'}]) except ValueError: root = minidom.parseString(req.body) sg_root = root.getElementsByTagName(key) groups = [] if sg_root: security_groups = sg_root[0].getElementsByTagName( 'security_group') for security_group in security_groups: groups.append( {'name': security_group.getAttribute('name')}) if not groups: groups = [{'name': 'default'}] servers[0][key] = groups def _show(self, req, resp_obj): if not softauth(req.environ['nova.context']): return if 'server' in resp_obj.obj: self._extend_servers(req, [resp_obj.obj['server']]) @wsgi.extends def show(self, req, resp_obj, id): return self._show(req, resp_obj) @wsgi.extends def create(self, req, resp_obj, body): return self._show(req, resp_obj) @wsgi.extends def detail(self, req, resp_obj): if not softauth(req.environ['nova.context']): return self._extend_servers(req, list(resp_obj.obj['servers'])) class Security_groups(extensions.ExtensionDescriptor): name = "SecurityGroups" alias = "os-security-groups" namespace = "http://docs.openstack.org/compute/ext/securitygroups/api/v1.1" updated = "2013-05-28T00:00:00Z" def get_controller_extensions(self): controller = SecurityGroupActionController() actions = extensions.ControllerExtension(self, 'servers', controller) controller = SecurityGroupsOutputController() output = extensions.ControllerExtension(self, 'servers', controller) return [actions, output] def get_resources(self): resources = [] res = extensions.ResourceExtension('os-security-groups', controller=SecurityGroupController()) resources.append(res) res = extensions.ResourceExtension('os-security-group-rules', controller=SecurityGroupRulesController()) resources.append(res) res = extensions.ResourceExtension( 'os-security-groups', controller=ServerSecurityGroupController(), parent=dict(member_name='server', collection_name='servers')) resources.append(res) return resources

true

1c458edcdd1b7f3f78cef784442634fe79c4c946

78

py

Python

ass_17.py

Divyanshi0409/Python-Programs

7fb8ab2159cc69de7168bf19f91325b9c7a908c7

[ "MIT" ]

null

ass_17.py

Divyanshi0409/Python-Programs

7fb8ab2159cc69de7168bf19f91325b9c7a908c7

[ "MIT" ]

null

ass_17.py

Divyanshi0409/Python-Programs

7fb8ab2159cc69de7168bf19f91325b9c7a908c7

[ "MIT" ]

null

for i in range(50,81): if i%2==0: print(i) else: break

15.6

22

0.448718

for i in range(50,81): if i%2==0: print(i) else: break

true

1c458f5175cf9bf35887e6e17a55a96733dcd698

2,954

py

Python

pint/testing.py

fernandezc/pint

37a61ede6fbd628c7dc160eb36278cf41c96484c

[ "BSD-3-Clause" ]

null

pint/testing.py

fernandezc/pint

37a61ede6fbd628c7dc160eb36278cf41c96484c

[ "BSD-3-Clause" ]

null

pint/testing.py

fernandezc/pint

37a61ede6fbd628c7dc160eb36278cf41c96484c

[ "BSD-3-Clause" ]

null

from __future__ import annotations import math import warnings from numbers import Number from . import Quantity from .compat import ndarray try: import numpy as np except ImportError: np = None def _get_comparable_magnitudes(first, second, msg): if isinstance(first, Quantity) and isinstance(second, Quantity): ctx = first._REGISTRY._active_ctx.contexts if first.is_compatible_with(second, *ctx): second = second.to(first) assert first.units == second.units, msg + " Units are not equal." m1, m2 = first.magnitude, second.magnitude elif isinstance(first, Quantity): assert first.dimensionless, msg + " The first is not dimensionless." first = first.to("") m1, m2 = first.magnitude, second elif isinstance(second, Quantity): assert second.dimensionless, msg + " The second is not dimensionless." second = second.to("") m1, m2 = first, second.magnitude else: m1, m2 = first, second return m1, m2 def assert_equal(first, second, msg=None): if msg is None: msg = "Comparing %r and %r. " % (first, second) m1, m2 = _get_comparable_magnitudes(first, second, msg) msg += " (Converted to %r and %r): Magnitudes are not equal" % (m1, m2) if isinstance(m1, ndarray) or isinstance(m2, ndarray): np.testing.assert_array_equal(m1, m2, err_msg=msg) elif not isinstance(m1, Number): warnings.warn(RuntimeWarning) return elif not isinstance(m2, Number): warnings.warn(RuntimeWarning) return elif math.isnan(m1): assert math.isnan(m2), msg elif math.isnan(m2): assert math.isnan(m1), msg else: assert m1 == m2, msg def assert_allclose(first, second, rtol=1e-07, atol=0, msg=None): if msg is None: try: msg = "Comparing %r and %r. " % (first, second) except TypeError: try: msg = "Comparing %s and %s. " % (first, second) except Exception: msg = "Comparing" m1, m2 = _get_comparable_magnitudes(first, second, msg) msg += " (Converted to %r and %r)" % (m1, m2) if isinstance(m1, ndarray) or isinstance(m2, ndarray): np.testing.assert_allclose(m1, m2, rtol=rtol, atol=atol, err_msg=msg) elif not isinstance(m1, Number): warnings.warn(RuntimeWarning) return elif not isinstance(m2, Number): warnings.warn(RuntimeWarning) return elif math.isnan(m1): assert math.isnan(m2), msg elif math.isnan(m2): assert math.isnan(m1), msg elif math.isinf(m1): assert math.isinf(m2), msg elif math.isinf(m2): assert math.isinf(m1), msg else: # Numpy version (don't like because is not symmetric) # assert abs(m1 - m2) <= atol + rtol * abs(m2), msg assert abs(m1 - m2) <= max(rtol * max(abs(m1), abs(m2)), atol), msg

31.763441

78

0.618822

from __future__ import annotations import math import warnings from numbers import Number from . import Quantity from .compat import ndarray try: import numpy as np except ImportError: np = None def _get_comparable_magnitudes(first, second, msg): if isinstance(first, Quantity) and isinstance(second, Quantity): ctx = first._REGISTRY._active_ctx.contexts if first.is_compatible_with(second, *ctx): second = second.to(first) assert first.units == second.units, msg + " Units are not equal." m1, m2 = first.magnitude, second.magnitude elif isinstance(first, Quantity): assert first.dimensionless, msg + " The first is not dimensionless." first = first.to("") m1, m2 = first.magnitude, second elif isinstance(second, Quantity): assert second.dimensionless, msg + " The second is not dimensionless." second = second.to("") m1, m2 = first, second.magnitude else: m1, m2 = first, second return m1, m2 def assert_equal(first, second, msg=None): if msg is None: msg = "Comparing %r and %r. " % (first, second) m1, m2 = _get_comparable_magnitudes(first, second, msg) msg += " (Converted to %r and %r): Magnitudes are not equal" % (m1, m2) if isinstance(m1, ndarray) or isinstance(m2, ndarray): np.testing.assert_array_equal(m1, m2, err_msg=msg) elif not isinstance(m1, Number): warnings.warn(RuntimeWarning) return elif not isinstance(m2, Number): warnings.warn(RuntimeWarning) return elif math.isnan(m1): assert math.isnan(m2), msg elif math.isnan(m2): assert math.isnan(m1), msg else: assert m1 == m2, msg def assert_allclose(first, second, rtol=1e-07, atol=0, msg=None): if msg is None: try: msg = "Comparing %r and %r. " % (first, second) except TypeError: try: msg = "Comparing %s and %s. " % (first, second) except Exception: msg = "Comparing" m1, m2 = _get_comparable_magnitudes(first, second, msg) msg += " (Converted to %r and %r)" % (m1, m2) if isinstance(m1, ndarray) or isinstance(m2, ndarray): np.testing.assert_allclose(m1, m2, rtol=rtol, atol=atol, err_msg=msg) elif not isinstance(m1, Number): warnings.warn(RuntimeWarning) return elif not isinstance(m2, Number): warnings.warn(RuntimeWarning) return elif math.isnan(m1): assert math.isnan(m2), msg elif math.isnan(m2): assert math.isnan(m1), msg elif math.isinf(m1): assert math.isinf(m2), msg elif math.isinf(m2): assert math.isinf(m1), msg else: # assert abs(m1 - m2) <= atol + rtol * abs(m2), msg assert abs(m1 - m2) <= max(rtol * max(abs(m1), abs(m2)), atol), msg

true

1c458f9ed188a3d53e4a024d3cb10478bdd12173

4,733

py

Python

sudoku/sudoku/gensudoku.py

PoojithRachakada/sudoku-django

723de992821e54b63259c00fb949fdfa1e05ac04

[ "MIT" ]

null

sudoku/sudoku/gensudoku.py

PoojithRachakada/sudoku-django

723de992821e54b63259c00fb949fdfa1e05ac04

[ "MIT" ]

5

2020-12-31T09:42:57.000Z

2021-01-05T13:59:14.000Z

sudoku/sudoku/gensudoku.py

PoojithRachakada/sudoku-django

723de992821e54b63259c00fb949fdfa1e05ac04

[ "MIT" ]

null

# pylint: disable=unused-variable import os import sys from io import BytesIO, IOBase import math import itertools as ITER from collections import defaultdict as D from collections import Counter as CO from collections import deque as Q import threading from functools import lru_cache, reduce from functools import cmp_to_key as CMP from bisect import bisect_left as BL from bisect import bisect_right as BR import random as RA import cmath, time # ? Variables MOD = (10 ** 9) + 7 MA = float("inf") MI = float("-inf") # * gui will be here # * backend code for sudoku start_time = time.time() class Sudoku: def check_row(self, i, board): values = set() for k in range(0, 9): p = board[i][k] if p == 0: continue if p in values: return False values.add(p) return True def check_col(self, j, board): values = set() for k in range(0, 9): p = board[k][j] if p == 0: continue if p in values: return False values.add(p) return True def check_sgrid(self, i, j, board): x, y = i // 3, j // 3 has = set() for i in range(3): for j in range(3): ele = board[x + i][y + j] if ele in has: return False has.add(ele) return True def IsValidSudoku(self, board): def check_sub_grid(i, j): values = set() for m in range(i, i + 3): for n in range(j, j + 3): p = board[n][m] if m == n: if not self.check_row(m, board): return False if not self.check_col(n, board): return False if p == 0: continue if p in values: return False values.add(p) return True for i in range(0, 9, 3): for j in range(0, 9, 3): if not check_sub_grid(i, j): return False return True # * this is the sudoku generator def Sudoku_generator(self, board): def next_pos(grid, store): for i in range(9): for j in range(9): if grid[i][j] == 0: store[0] = i store[1] = j return True return False def create(grid, row, col): for i in range(9): for j in range(9): w = grid[i][j] if w != 0: row[i].add(w) col[j].add(w) def is_valid(i, j, key, row, col, grid): if key in row[i]: return False if key in col[j]: return False p = (i // 3) * 3 q = (j // 3) * 3 for x in range(3): for y in range(3): if grid[x + p][y + q] == key: return False return True arr = [1, 2, 3, 4, 5, 6, 7, 8, 9] RA.shuffle(arr) def sudoku_solver(row, col, grid): store = [0, 0] if not next_pos(grid, store): return True r = store[0] c = store[1] for i in arr: if is_valid(r, c, i, row, col, grid): grid[r][c] = i row[r].add(i) col[c].add(i) if sudoku_solver(row, col, grid): return True grid[r][c] = 0 row[r].remove(i) col[c].remove(i) return False row = D(set) col = D(set) create(board, row, col) sudoku_solver(row, col, board) return board def question(board): hint = RA.randint(18, 30) totalpos = [(i, j) for i in range(9) for j in range(9)] wanted = RA.choices(totalpos, k=hint) qs = [[0] * 9 for i in range(9)] for i, j in wanted: qs[i][j] = board[i][j] return qs def valid(arr): sudokuobj = Sudoku() return sudokuobj.IsValidSudoku(arr) def all(): board = [[0] * 9 for i in range(9)] sudokuobj = Sudoku() ans = sudokuobj.Sudoku_generator((board)) return question(ans), ans

27.358382

60

0.427002

import os import sys from io import BytesIO, IOBase import math import itertools as ITER from collections import defaultdict as D from collections import Counter as CO from collections import deque as Q import threading from functools import lru_cache, reduce from functools import cmp_to_key as CMP from bisect import bisect_left as BL from bisect import bisect_right as BR import random as RA import cmath, time MOD = (10 ** 9) + 7 MA = float("inf") MI = float("-inf") start_time = time.time() class Sudoku: def check_row(self, i, board): values = set() for k in range(0, 9): p = board[i][k] if p == 0: continue if p in values: return False values.add(p) return True def check_col(self, j, board): values = set() for k in range(0, 9): p = board[k][j] if p == 0: continue if p in values: return False values.add(p) return True def check_sgrid(self, i, j, board): x, y = i // 3, j // 3 has = set() for i in range(3): for j in range(3): ele = board[x + i][y + j] if ele in has: return False has.add(ele) return True def IsValidSudoku(self, board): def check_sub_grid(i, j): values = set() for m in range(i, i + 3): for n in range(j, j + 3): p = board[n][m] if m == n: if not self.check_row(m, board): return False if not self.check_col(n, board): return False if p == 0: continue if p in values: return False values.add(p) return True for i in range(0, 9, 3): for j in range(0, 9, 3): if not check_sub_grid(i, j): return False return True def Sudoku_generator(self, board): def next_pos(grid, store): for i in range(9): for j in range(9): if grid[i][j] == 0: store[0] = i store[1] = j return True return False def create(grid, row, col): for i in range(9): for j in range(9): w = grid[i][j] if w != 0: row[i].add(w) col[j].add(w) def is_valid(i, j, key, row, col, grid): if key in row[i]: return False if key in col[j]: return False p = (i // 3) * 3 q = (j // 3) * 3 for x in range(3): for y in range(3): if grid[x + p][y + q] == key: return False return True arr = [1, 2, 3, 4, 5, 6, 7, 8, 9] RA.shuffle(arr) def sudoku_solver(row, col, grid): store = [0, 0] if not next_pos(grid, store): return True r = store[0] c = store[1] for i in arr: if is_valid(r, c, i, row, col, grid): grid[r][c] = i row[r].add(i) col[c].add(i) if sudoku_solver(row, col, grid): return True grid[r][c] = 0 row[r].remove(i) col[c].remove(i) return False row = D(set) col = D(set) create(board, row, col) sudoku_solver(row, col, board) return board def question(board): hint = RA.randint(18, 30) totalpos = [(i, j) for i in range(9) for j in range(9)] wanted = RA.choices(totalpos, k=hint) qs = [[0] * 9 for i in range(9)] for i, j in wanted: qs[i][j] = board[i][j] return qs def valid(arr): sudokuobj = Sudoku() return sudokuobj.IsValidSudoku(arr) def all(): board = [[0] * 9 for i in range(9)] sudokuobj = Sudoku() ans = sudokuobj.Sudoku_generator((board)) return question(ans), ans

true

1c4590d51df3d7bf9eea558bb224c176d93b580d

4,832

py

Python

fastmot/utils/visualization.py

rafcy/FastMOT

9aee101b1ac83a5fea8cece1f8cfda8030adb743

[ "MIT" ]

null

fastmot/utils/visualization.py

rafcy/FastMOT

9aee101b1ac83a5fea8cece1f8cfda8030adb743

[ "MIT" ]

null

fastmot/utils/visualization.py

rafcy/FastMOT

9aee101b1ac83a5fea8cece1f8cfda8030adb743

[ "MIT" ]

null

import colorsys import numpy as np import cv2 GOLDEN_RATIO = 0.618033988749895 def draw_tracks(frame, tracks, show_flow=False, show_cov=False): for track in tracks: draw_bbox(frame, track.tlbr, get_color(track.trk_id), 2, str(track.trk_id)) if show_flow: draw_feature_match(frame, track.prev_keypoints, track.keypoints, (0, 255, 255)) if show_cov: draw_covariance(frame, track.tlbr, track.state[1]) def draw_detections(frame, detections, color=(255, 255, 255), show_conf=False): for det in detections: text = f'{det.label}: {det.conf:.2f}' if show_conf else None draw_bbox(frame, det.tlbr, color, 1, text) def draw_klt_bboxes(frame, klt_bboxes, color=(0, 0, 0)): for tlbr in klt_bboxes: draw_bbox(frame, tlbr, color, 1) def draw_tiles(frame, tiles, scale_factor, color=(0, 0, 0)): for tile in tiles: tlbr = np.rint(tile * np.tile(scale_factor, 2)) draw_bbox(frame, tlbr, color, 1) def draw_background_flow(frame, prev_bg_keypoints, bg_keypoints, color=(0, 0, 255)): draw_feature_match(frame, prev_bg_keypoints, bg_keypoints, color) def get_color(idx, s=0.8, vmin=0.7): h = np.fmod(idx * GOLDEN_RATIO, 1.) v = 1. - np.fmod(idx * GOLDEN_RATIO, 1. - vmin) r, g, b = colorsys.hsv_to_rgb(h, s, v) return int(255 * b), int(255 * g), int(255 * r) def draw_bbox(frame, tlbr, color, thickness, text=None): tlbr = tlbr.astype(int) tl, br = tuple(tlbr[:2]), tuple(tlbr[2:]) cv2.rectangle(frame, tl, br, color, thickness) if text is not None: (text_width, text_height), _ = cv2.getTextSize(text, cv2.FONT_HERSHEY_DUPLEX, 0.5, 1) cv2.rectangle(frame, tl, (tl[0] + text_width - 1, tl[1] + text_height - 1), color, cv2.FILLED) cv2.putText(frame, text, (tl[0], tl[1] + text_height - 1), cv2.FONT_HERSHEY_DUPLEX, 0.5, 0, 1, cv2.LINE_AA) def draw_feature_match(frame, prev_pts, cur_pts, color): if len(cur_pts) > 0: cur_pts = np.rint(cur_pts).astype(np.int32) for pt in cur_pts: cv2.circle(frame, tuple(pt), 1, color, cv2.FILLED) if len(prev_pts) > 0: prev_pts = np.rint(prev_pts).astype(np.int32) for pt1, pt2 in zip(prev_pts, cur_pts): cv2.line(frame, tuple(pt1), tuple(pt2), color, 1, cv2.LINE_AA) def draw_covariance(frame, tlbr, covariance): tlbr = tlbr.astype(int) tl, br = tuple(tlbr[:2]), tuple(tlbr[2:]) def ellipse(cov): vals, vecs = np.linalg.eigh(cov) order = vals.argsort()[::-1] # 95% confidence ellipse vals, vecs = np.sqrt(vals[order] * 5.9915), vecs[:, order] axes = int(vals[0] + 0.5), int(vals[1] + 0.5) angle = np.degrees(np.arctan2(vecs[1, 0], vecs[0, 0])) return axes, angle axes, angle = ellipse(covariance[:2, :2]) cv2.ellipse(frame, tl, axes, angle, 0, 360, (255, 255, 255), 1, cv2.LINE_AA) axes, angle = ellipse(covariance[2:4, 2:4]) cv2.ellipse(frame, br, axes, angle, 0, 360, (255, 255, 255), 1, cv2.LINE_AA) class Visualizer: def __init__(self, draw_detections=False, draw_confidence=False, draw_covariance=False, draw_klt=False, draw_obj_flow=False, draw_bg_flow=False): """Class for visualization. Parameters ---------- draw_detections : bool, optional Enable drawing detections. draw_confidence : bool, optional Enable drawing detection confidence, ignored if `draw_detections` is disabled. draw_covariance : bool, optional Enable drawing Kalman filter position covariance. draw_klt : bool, optional Enable drawing KLT bounding boxes. draw_obj_flow : bool, optional Enable drawing object flow matches. draw_bg_flow : bool, optional Enable drawing background flow matches. """ self.draw_detections = draw_detections self.draw_confidence = draw_confidence self.draw_covariance = draw_covariance self.draw_klt = draw_klt self.draw_obj_flow = draw_obj_flow self.draw_bg_flow = draw_bg_flow def render(self, frame, tracks, detections, klt_bboxes, prev_bg_keypoints, bg_keypoints): """Render visualizations onto the frame.""" draw_tracks(frame, tracks, show_flow=self.draw_obj_flow, show_cov=self.draw_covariance) if self.draw_detections: draw_detections(frame, detections, show_conf=self.draw_confidence) if self.draw_klt: draw_klt_bboxes(frame, klt_bboxes) if self.draw_bg_flow: draw_background_flow(frame, prev_bg_keypoints, bg_keypoints)

37.457364

95

0.627276

import colorsys import numpy as np import cv2 GOLDEN_RATIO = 0.618033988749895 def draw_tracks(frame, tracks, show_flow=False, show_cov=False): for track in tracks: draw_bbox(frame, track.tlbr, get_color(track.trk_id), 2, str(track.trk_id)) if show_flow: draw_feature_match(frame, track.prev_keypoints, track.keypoints, (0, 255, 255)) if show_cov: draw_covariance(frame, track.tlbr, track.state[1]) def draw_detections(frame, detections, color=(255, 255, 255), show_conf=False): for det in detections: text = f'{det.label}: {det.conf:.2f}' if show_conf else None draw_bbox(frame, det.tlbr, color, 1, text) def draw_klt_bboxes(frame, klt_bboxes, color=(0, 0, 0)): for tlbr in klt_bboxes: draw_bbox(frame, tlbr, color, 1) def draw_tiles(frame, tiles, scale_factor, color=(0, 0, 0)): for tile in tiles: tlbr = np.rint(tile * np.tile(scale_factor, 2)) draw_bbox(frame, tlbr, color, 1) def draw_background_flow(frame, prev_bg_keypoints, bg_keypoints, color=(0, 0, 255)): draw_feature_match(frame, prev_bg_keypoints, bg_keypoints, color) def get_color(idx, s=0.8, vmin=0.7): h = np.fmod(idx * GOLDEN_RATIO, 1.) v = 1. - np.fmod(idx * GOLDEN_RATIO, 1. - vmin) r, g, b = colorsys.hsv_to_rgb(h, s, v) return int(255 * b), int(255 * g), int(255 * r) def draw_bbox(frame, tlbr, color, thickness, text=None): tlbr = tlbr.astype(int) tl, br = tuple(tlbr[:2]), tuple(tlbr[2:]) cv2.rectangle(frame, tl, br, color, thickness) if text is not None: (text_width, text_height), _ = cv2.getTextSize(text, cv2.FONT_HERSHEY_DUPLEX, 0.5, 1) cv2.rectangle(frame, tl, (tl[0] + text_width - 1, tl[1] + text_height - 1), color, cv2.FILLED) cv2.putText(frame, text, (tl[0], tl[1] + text_height - 1), cv2.FONT_HERSHEY_DUPLEX, 0.5, 0, 1, cv2.LINE_AA) def draw_feature_match(frame, prev_pts, cur_pts, color): if len(cur_pts) > 0: cur_pts = np.rint(cur_pts).astype(np.int32) for pt in cur_pts: cv2.circle(frame, tuple(pt), 1, color, cv2.FILLED) if len(prev_pts) > 0: prev_pts = np.rint(prev_pts).astype(np.int32) for pt1, pt2 in zip(prev_pts, cur_pts): cv2.line(frame, tuple(pt1), tuple(pt2), color, 1, cv2.LINE_AA) def draw_covariance(frame, tlbr, covariance): tlbr = tlbr.astype(int) tl, br = tuple(tlbr[:2]), tuple(tlbr[2:]) def ellipse(cov): vals, vecs = np.linalg.eigh(cov) order = vals.argsort()[::-1] vals, vecs = np.sqrt(vals[order] * 5.9915), vecs[:, order] axes = int(vals[0] + 0.5), int(vals[1] + 0.5) angle = np.degrees(np.arctan2(vecs[1, 0], vecs[0, 0])) return axes, angle axes, angle = ellipse(covariance[:2, :2]) cv2.ellipse(frame, tl, axes, angle, 0, 360, (255, 255, 255), 1, cv2.LINE_AA) axes, angle = ellipse(covariance[2:4, 2:4]) cv2.ellipse(frame, br, axes, angle, 0, 360, (255, 255, 255), 1, cv2.LINE_AA) class Visualizer: def __init__(self, draw_detections=False, draw_confidence=False, draw_covariance=False, draw_klt=False, draw_obj_flow=False, draw_bg_flow=False): self.draw_detections = draw_detections self.draw_confidence = draw_confidence self.draw_covariance = draw_covariance self.draw_klt = draw_klt self.draw_obj_flow = draw_obj_flow self.draw_bg_flow = draw_bg_flow def render(self, frame, tracks, detections, klt_bboxes, prev_bg_keypoints, bg_keypoints): draw_tracks(frame, tracks, show_flow=self.draw_obj_flow, show_cov=self.draw_covariance) if self.draw_detections: draw_detections(frame, detections, show_conf=self.draw_confidence) if self.draw_klt: draw_klt_bboxes(frame, klt_bboxes) if self.draw_bg_flow: draw_background_flow(frame, prev_bg_keypoints, bg_keypoints)

true

1c4591a6e22722c8a1760289f625d852a5960577

2,354

py

Python

tests/io/simple_process.py

rajgiriUW/pyUSID

064dcd81d9c42f4eb4782f0a41fd437b3f56f50c

[ "MIT" ]

25

2018-07-11T21:43:56.000Z

2021-11-17T11:40:00.000Z

tests/io/simple_process.py

rajgiriUW/pyUSID

064dcd81d9c42f4eb4782f0a41fd437b3f56f50c

[ "MIT" ]

62

2018-07-05T20:28:52.000Z

2021-12-14T09:49:35.000Z

tests/io/simple_process.py

rajgiriUW/pyUSID

064dcd81d9c42f4eb4782f0a41fd437b3f56f50c

[ "MIT" ]

15

2019-03-27T22:28:47.000Z

2021-01-03T20:23:42.000Z

""" Simple process class for purpose of testing. Created on: Jul 19, 2019 Author: Emily Costa """ import h5py from pyUSID.processing.process import Process import numpy as np from pyUSID import hdf_utils import matplotlib.pyplot as plt class SimpleProcess(Process): def __init__(self, h5_main, verbose=True, **kwargs): super(SimpleProcess, self).__init__(h5_main, verbose, **kwargs) self.data = None self.test_data = None self.results = None self.chunk_amount = 0 self.process_name = 'Simple_Process' if self.verbose: print('Done with initializing book-keepings') def test(self): if self.mpi_rank > 0: return ran_ind = np.random.randint(0, high=self.h5_main.shape[0]) self.test_data = np.fft.fftshift(np.fft.fft(self.h5_main[ran_ind])) def _create_results_datasets(self): self.h5_results_grp = hdf_utils.create_results_group(self.h5_main, self.process_name) assert isinstance(self.h5_results_grp, h5py.Group) if self.verbose: print('Results group created.') self.results = hdf_utils.create_empty_dataset(self.h5_main, self.h5_main.dtype, 'Filtered_Data', h5_group=self.h5_results_grp) #self.results = hdf_utils.write_main_dataset(self.h5_results_grp, (self.h5_main.shape[0], 1), "Results", "Results", "Units", None, #usid.io.write_utils.Dimension('arb', '', [1]), h5_pos_inds=self.h5_main.h5_pos_inds, h5_pos_vals=self.h5_main.h5_pos_vals, dtype=np.float32) if self.verbose: print('Empty main dataset for results written') def _write_results_chunk(self): pos_in_batch = self._get_pixels_in_current_batch() print(type(self.data)) print(type(self.results)) self.results[pos_in_batch, :] = self.data #self.results = self.h5_results_grp['Simple_Data'] self.chunk_amount = self.chunk_amount + 1 if self.verbose: print('Chunk {} written.'.format(self.chunk_amount)) def _unit_computation(self): self.data = np.fft.fftshift(np.fft.fft(self.data, axis=1), axes=1) def plot_test(self): fig, axis = plt.subplots() axis.plot(self.test_data) plt.savefig('test_partial.png') if self.verbose: print('Test image created.')

39.898305

149

0.666525

import h5py from pyUSID.processing.process import Process import numpy as np from pyUSID import hdf_utils import matplotlib.pyplot as plt class SimpleProcess(Process): def __init__(self, h5_main, verbose=True, **kwargs): super(SimpleProcess, self).__init__(h5_main, verbose, **kwargs) self.data = None self.test_data = None self.results = None self.chunk_amount = 0 self.process_name = 'Simple_Process' if self.verbose: print('Done with initializing book-keepings') def test(self): if self.mpi_rank > 0: return ran_ind = np.random.randint(0, high=self.h5_main.shape[0]) self.test_data = np.fft.fftshift(np.fft.fft(self.h5_main[ran_ind])) def _create_results_datasets(self): self.h5_results_grp = hdf_utils.create_results_group(self.h5_main, self.process_name) assert isinstance(self.h5_results_grp, h5py.Group) if self.verbose: print('Results group created.') self.results = hdf_utils.create_empty_dataset(self.h5_main, self.h5_main.dtype, 'Filtered_Data', h5_group=self.h5_results_grp) if self.verbose: print('Empty main dataset for results written') def _write_results_chunk(self): pos_in_batch = self._get_pixels_in_current_batch() print(type(self.data)) print(type(self.results)) self.results[pos_in_batch, :] = self.data self.chunk_amount = self.chunk_amount + 1 if self.verbose: print('Chunk {} written.'.format(self.chunk_amount)) def _unit_computation(self): self.data = np.fft.fftshift(np.fft.fft(self.data, axis=1), axes=1) def plot_test(self): fig, axis = plt.subplots() axis.plot(self.test_data) plt.savefig('test_partial.png') if self.verbose: print('Test image created.')

true

1c4591b85ef0cb783c72ba1b6a6beb97dbfb0aa3

2,482

py

Python

pysnmp/CISCO-SCTP-CAPABILITY.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

11

2021-02-02T16:27:16.000Z

2021-08-31T06:22:49.000Z

pysnmp/CISCO-SCTP-CAPABILITY.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

75

2021-02-24T17:30:31.000Z

2021-12-08T00:01:18.000Z

pysnmp/CISCO-SCTP-CAPABILITY.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

10

2019-04-30T05:51:36.000Z

2022-02-16T03:33:41.000Z

# # PySNMP MIB module CISCO-SCTP-CAPABILITY (http://snmplabs.com/pysmi) # ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/CISCO-SCTP-CAPABILITY # Produced by pysmi-0.3.4 at Mon Apr 29 17:54:50 2019 # On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4 # Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15) # ObjectIdentifier, Integer, OctetString = mibBuilder.importSymbols("ASN1", "ObjectIdentifier", "Integer", "OctetString") NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues") ConstraintsIntersection, ValueSizeConstraint, SingleValueConstraint, ConstraintsUnion, ValueRangeConstraint = mibBuilder.importSymbols("ASN1-REFINEMENT", "ConstraintsIntersection", "ValueSizeConstraint", "SingleValueConstraint", "ConstraintsUnion", "ValueRangeConstraint") ciscoAgentCapability, = mibBuilder.importSymbols("CISCO-SMI", "ciscoAgentCapability") AgentCapabilities, NotificationGroup, ModuleCompliance = mibBuilder.importSymbols("SNMPv2-CONF", "AgentCapabilities", "NotificationGroup", "ModuleCompliance") Counter64, MibScalar, MibTable, MibTableRow, MibTableColumn, ObjectIdentity, ModuleIdentity, Bits, MibIdentifier, Gauge32, TimeTicks, NotificationType, iso, IpAddress, Unsigned32, Counter32, Integer32 = mibBuilder.importSymbols("SNMPv2-SMI", "Counter64", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "ObjectIdentity", "ModuleIdentity", "Bits", "MibIdentifier", "Gauge32", "TimeTicks", "NotificationType", "iso", "IpAddress", "Unsigned32", "Counter32", "Integer32") TextualConvention, DisplayString = mibBuilder.importSymbols("SNMPv2-TC", "TextualConvention", "DisplayString") ceSctpCapability = ModuleIdentity((1, 3, 6, 1, 4, 1, 9, 7, 190)) ceSctpCapability.setRevisions(('2001-06-05 00:00',)) if mibBuilder.loadTexts: ceSctpCapability.setLastUpdated('200106050000Z') if mibBuilder.loadTexts: ceSctpCapability.setOrganization('Cisco Systems, Inc.') ceSctpCapabilityV12R021MB1 = AgentCapabilities((1, 3, 6, 1, 4, 1, 9, 7, 190, 1)) if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): ceSctpCapabilityV12R021MB1 = ceSctpCapabilityV12R021MB1.setProductRelease('Cisco IOS 12.2(1)MB1') if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): ceSctpCapabilityV12R021MB1 = ceSctpCapabilityV12R021MB1.setStatus('current') mibBuilder.exportSymbols("CISCO-SCTP-CAPABILITY", ceSctpCapability=ceSctpCapability, ceSctpCapabilityV12R021MB1=ceSctpCapabilityV12R021MB1, PYSNMP_MODULE_ID=ceSctpCapability)

99.28

477

0.787671

ObjectIdentifier, Integer, OctetString = mibBuilder.importSymbols("ASN1", "ObjectIdentifier", "Integer", "OctetString") NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues") ConstraintsIntersection, ValueSizeConstraint, SingleValueConstraint, ConstraintsUnion, ValueRangeConstraint = mibBuilder.importSymbols("ASN1-REFINEMENT", "ConstraintsIntersection", "ValueSizeConstraint", "SingleValueConstraint", "ConstraintsUnion", "ValueRangeConstraint") ciscoAgentCapability, = mibBuilder.importSymbols("CISCO-SMI", "ciscoAgentCapability") AgentCapabilities, NotificationGroup, ModuleCompliance = mibBuilder.importSymbols("SNMPv2-CONF", "AgentCapabilities", "NotificationGroup", "ModuleCompliance") Counter64, MibScalar, MibTable, MibTableRow, MibTableColumn, ObjectIdentity, ModuleIdentity, Bits, MibIdentifier, Gauge32, TimeTicks, NotificationType, iso, IpAddress, Unsigned32, Counter32, Integer32 = mibBuilder.importSymbols("SNMPv2-SMI", "Counter64", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "ObjectIdentity", "ModuleIdentity", "Bits", "MibIdentifier", "Gauge32", "TimeTicks", "NotificationType", "iso", "IpAddress", "Unsigned32", "Counter32", "Integer32") TextualConvention, DisplayString = mibBuilder.importSymbols("SNMPv2-TC", "TextualConvention", "DisplayString") ceSctpCapability = ModuleIdentity((1, 3, 6, 1, 4, 1, 9, 7, 190)) ceSctpCapability.setRevisions(('2001-06-05 00:00',)) if mibBuilder.loadTexts: ceSctpCapability.setLastUpdated('200106050000Z') if mibBuilder.loadTexts: ceSctpCapability.setOrganization('Cisco Systems, Inc.') ceSctpCapabilityV12R021MB1 = AgentCapabilities((1, 3, 6, 1, 4, 1, 9, 7, 190, 1)) if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): ceSctpCapabilityV12R021MB1 = ceSctpCapabilityV12R021MB1.setProductRelease('Cisco IOS 12.2(1)MB1') if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0): ceSctpCapabilityV12R021MB1 = ceSctpCapabilityV12R021MB1.setStatus('current') mibBuilder.exportSymbols("CISCO-SCTP-CAPABILITY", ceSctpCapability=ceSctpCapability, ceSctpCapabilityV12R021MB1=ceSctpCapabilityV12R021MB1, PYSNMP_MODULE_ID=ceSctpCapability)

true

1c45922460b3274c214c472b39912156f5a9ae77

1,632

py

Python

game/startMk2.py

Penniling/launchpad-dont-choose-the-wrong

490e814a531168ae3b4cbbd0db89a9887b5d0bb3

[ "MIT" ]

null

game/startMk2.py

Penniling/launchpad-dont-choose-the-wrong

490e814a531168ae3b4cbbd0db89a9887b5d0bb3

[ "MIT" ]

null

game/startMk2.py

Penniling/launchpad-dont-choose-the-wrong

490e814a531168ae3b4cbbd0db89a9887b5d0bb3

[ "MIT" ]

null

import LaunchpadMk2 import atexit import os import random def on_exit(): os.system(f"python {os.getcwd()}/startMk2.py") class Game: def __init__(self): self.n = int(input("Please choose a number of wrong pads: ")) self.lp = LaunchpadMk2.LaunchpadMk2() self.lp.Reset() self.lp.register_on_button_press(on_button=self.on_button_press) self.wrong = [] self.pres = [] self.isDead = False self.start_game() def start_game(self): self.lp.LedAllOn(colorcode=self.lp.COLORS["green"]) for i in range(self.n): x = (random.randint(0, 7), random.randint(1, 8)) while x in self.wrong: x = (random.randint(0, 7), random.randint(1, 8)) self.wrong.append(x) while len(self.pres) <= 63: pass self.on_win() def on_button_press(self, x, y, pres): if pres > 0 and (x, y) != self.pres: if (x, y) in self.wrong: self.on_death() else: self.pres.append((x, y)) self.lp.LedCtrlXY(x, y, 0, 0, 0) def on_win(self): self.lp.Reset() self.lp.LedCtrlString("Win", 0, 255, 0, direction=self.lp.SCROLL_LEFT, waitms=50) self.lp.continue_listener = False self.lp.Close() exit() def on_death(self): self.lp.Reset() for i in self.wrong: self.lp.LedCtrlXY(i[0], i[1], 255, 0, 0) self.lp.continue_listener = False self.lp.Close() exit() if __name__ == "__main__": atexit.register(on_exit) Game()

26.754098

89

0.550858

import LaunchpadMk2 import atexit import os import random def on_exit(): os.system(f"python {os.getcwd()}/startMk2.py") class Game: def __init__(self): self.n = int(input("Please choose a number of wrong pads: ")) self.lp = LaunchpadMk2.LaunchpadMk2() self.lp.Reset() self.lp.register_on_button_press(on_button=self.on_button_press) self.wrong = [] self.pres = [] self.isDead = False self.start_game() def start_game(self): self.lp.LedAllOn(colorcode=self.lp.COLORS["green"]) for i in range(self.n): x = (random.randint(0, 7), random.randint(1, 8)) while x in self.wrong: x = (random.randint(0, 7), random.randint(1, 8)) self.wrong.append(x) while len(self.pres) <= 63: pass self.on_win() def on_button_press(self, x, y, pres): if pres > 0 and (x, y) != self.pres: if (x, y) in self.wrong: self.on_death() else: self.pres.append((x, y)) self.lp.LedCtrlXY(x, y, 0, 0, 0) def on_win(self): self.lp.Reset() self.lp.LedCtrlString("Win", 0, 255, 0, direction=self.lp.SCROLL_LEFT, waitms=50) self.lp.continue_listener = False self.lp.Close() exit() def on_death(self): self.lp.Reset() for i in self.wrong: self.lp.LedCtrlXY(i[0], i[1], 255, 0, 0) self.lp.continue_listener = False self.lp.Close() exit() if __name__ == "__main__": atexit.register(on_exit) Game()

true

1c4592dbfd3957588d06fd935ce4c485dc1377a0

7,268

py

Python

pennylane/interfaces/batch/tensorflow.py

ral9000/pennylane

0afbd155d044730af546c6d90cef9d01f931632d

[ "Apache-2.0" ]

712

2020-07-29T03:46:52.000Z

2022-03-27T11:21:51.000Z

pennylane/interfaces/batch/tensorflow.py

ral9000/pennylane

0afbd155d044730af546c6d90cef9d01f931632d

[ "Apache-2.0" ]

1,627

2020-07-28T13:07:58.000Z

2022-03-31T21:47:29.000Z

pennylane/interfaces/batch/tensorflow.py

ral9000/pennylane

0afbd155d044730af546c6d90cef9d01f931632d

[ "Apache-2.0" ]

249

2020-07-29T03:26:18.000Z

2022-03-31T19:59:48.000Z

# Copyright 2018-2021 Xanadu Quantum Technologies Inc. # 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. """ This module contains functions for adding the TensorFlow interface to a PennyLane Device class. """ # pylint: disable=too-many-arguments,too-many-branches import numpy as np import tensorflow as tf from tensorflow.python.eager import context import pennylane as qml def _compute_vjp(dy, jacs): # compute the vector-Jacobian product dy @ jac # for a list of dy's and Jacobian matrices. vjps = [] for d, jac in zip(dy, jacs): vjp = qml.gradients.compute_vjp(d, jac) if not context.executing_eagerly(): vjp = qml.math.unstack(vjp) vjps.extend(vjp) return vjps def execute(tapes, device, execute_fn, gradient_fn, gradient_kwargs, _n=1, max_diff=2): """Execute a batch of tapes with TensorFlow parameters on a device. Args: tapes (Sequence[.QuantumTape]): batch of tapes to execute device (.Device): Device to use to execute the batch of tapes. If the device does not provide a ``batch_execute`` method, by default the tapes will be executed in serial. execute_fn (callable): The execution function used to execute the tapes during the forward pass. This function must return a tuple ``(results, jacobians)``. If ``jacobians`` is an empty list, then ``gradient_fn`` is used to compute the gradients during the backwards pass. gradient_kwargs (dict): dictionary of keyword arguments to pass when determining the gradients of tapes gradient_fn (callable): the gradient function to use to compute quantum gradients _n (int): a positive integer used to track nesting of derivatives, for example if the nth-order derivative is requested. max_diff (int): If ``gradient_fn`` is a gradient transform, this option specifies the maximum number of derivatives to support. Increasing this value allows for higher order derivatives to be extracted, at the cost of additional (classical) computational overhead during the backwards pass. Returns: list[list[tf.Tensor]]: A nested list of tape results. Each element in the returned list corresponds in order to the provided tapes. """ parameters = [] params_unwrapped = [] for i, tape in enumerate(tapes): # store the trainable parameters params = tape.get_parameters(trainable_only=False) tape.trainable_params = qml.math.get_trainable_indices(params) parameters += [p for i, p in enumerate(params) if i in tape.trainable_params] # store all unwrapped parameters params_unwrapped.append( [i.numpy() if isinstance(i, (tf.Variable, tf.Tensor)) else i for i in params] ) with qml.tape.Unwrap(*tapes, set_trainable=False): # Forward pass: execute the tapes res, jacs = execute_fn(tapes, **gradient_kwargs) for i, tape in enumerate(tapes): # convert output to TensorFlow tensors r = np.hstack(res[i]) if res[i].dtype == np.dtype("object") else res[i] res[i] = tf.convert_to_tensor(r) @tf.custom_gradient def _execute(*parameters): # pylint:disable=unused-argument def grad_fn(*dy, **tfkwargs): """Returns the vector-Jacobian product with given parameter values and output gradient dy""" dy = [qml.math.T(d) for d in dy] if jacs: # Jacobians were computed on the forward pass (mode="forward") # No additional quantum evaluations needed; simply compute the VJPs directly. vjps = _compute_vjp(dy, jacs) else: # Need to compute the Jacobians on the backward pass (accumulation="backward") if isinstance(gradient_fn, qml.gradients.gradient_transform): # Gradient function is a gradient transform. # Generate and execute the required gradient tapes if _n == max_diff or not context.executing_eagerly(): with qml.tape.Unwrap(*tapes, params=params_unwrapped, set_trainable=False): vjp_tapes, processing_fn = qml.gradients.batch_vjp( tapes, dy, gradient_fn, reduction=lambda vjps, x: vjps.extend(qml.math.unstack(x)), gradient_kwargs=gradient_kwargs, ) vjps = processing_fn(execute_fn(vjp_tapes)[0]) else: vjp_tapes, processing_fn = qml.gradients.batch_vjp( tapes, dy, gradient_fn, reduction="extend", gradient_kwargs=gradient_kwargs, ) # This is where the magic happens. Note that we call ``execute``. # This recursion, coupled with the fact that the gradient transforms # are differentiable, allows for arbitrary order differentiation. vjps = processing_fn( execute( vjp_tapes, device, execute_fn, gradient_fn, gradient_kwargs, _n=_n + 1, max_diff=max_diff, ) ) else: # Gradient function is not a gradient transform # (e.g., it might be a device method). # Note that unlike the previous branch: # # - there is no recursion here # - gradient_fn is not differentiable # # so we cannot support higher-order derivatives. with qml.tape.Unwrap(*tapes, params=params_unwrapped, set_trainable=False): vjps = _compute_vjp(dy, gradient_fn(tapes, **gradient_kwargs)) variables = tfkwargs.get("variables", None) return (vjps, variables) if variables is not None else vjps return res, grad_fn return _execute(*parameters)

43.261905

100

0.569895

import numpy as np import tensorflow as tf from tensorflow.python.eager import context import pennylane as qml def _compute_vjp(dy, jacs): vjps = [] for d, jac in zip(dy, jacs): vjp = qml.gradients.compute_vjp(d, jac) if not context.executing_eagerly(): vjp = qml.math.unstack(vjp) vjps.extend(vjp) return vjps def execute(tapes, device, execute_fn, gradient_fn, gradient_kwargs, _n=1, max_diff=2): parameters = [] params_unwrapped = [] for i, tape in enumerate(tapes): # store the trainable parameters params = tape.get_parameters(trainable_only=False) tape.trainable_params = qml.math.get_trainable_indices(params) parameters += [p for i, p in enumerate(params) if i in tape.trainable_params] # store all unwrapped parameters params_unwrapped.append( [i.numpy() if isinstance(i, (tf.Variable, tf.Tensor)) else i for i in params] ) with qml.tape.Unwrap(*tapes, set_trainable=False): # Forward pass: execute the tapes res, jacs = execute_fn(tapes, **gradient_kwargs) for i, tape in enumerate(tapes): # convert output to TensorFlow tensors r = np.hstack(res[i]) if res[i].dtype == np.dtype("object") else res[i] res[i] = tf.convert_to_tensor(r) @tf.custom_gradient def _execute(*parameters): # pylint:disable=unused-argument def grad_fn(*dy, **tfkwargs): dy = [qml.math.T(d) for d in dy] if jacs: # Jacobians were computed on the forward pass (mode="forward") # No additional quantum evaluations needed; simply compute the VJPs directly. vjps = _compute_vjp(dy, jacs) else: # Need to compute the Jacobians on the backward pass (accumulation="backward") if isinstance(gradient_fn, qml.gradients.gradient_transform): # Gradient function is a gradient transform. # Generate and execute the required gradient tapes if _n == max_diff or not context.executing_eagerly(): with qml.tape.Unwrap(*tapes, params=params_unwrapped, set_trainable=False): vjp_tapes, processing_fn = qml.gradients.batch_vjp( tapes, dy, gradient_fn, reduction=lambda vjps, x: vjps.extend(qml.math.unstack(x)), gradient_kwargs=gradient_kwargs, ) vjps = processing_fn(execute_fn(vjp_tapes)[0]) else: vjp_tapes, processing_fn = qml.gradients.batch_vjp( tapes, dy, gradient_fn, reduction="extend", gradient_kwargs=gradient_kwargs, ) # This is where the magic happens. Note that we call ``execute``. # This recursion, coupled with the fact that the gradient transforms # are differentiable, allows for arbitrary order differentiation. vjps = processing_fn( execute( vjp_tapes, device, execute_fn, gradient_fn, gradient_kwargs, _n=_n + 1, max_diff=max_diff, ) ) else: # Gradient function is not a gradient transform # (e.g., it might be a device method). # Note that unlike the previous branch: # # - there is no recursion here # - gradient_fn is not differentiable # # so we cannot support higher-order derivatives. with qml.tape.Unwrap(*tapes, params=params_unwrapped, set_trainable=False): vjps = _compute_vjp(dy, gradient_fn(tapes, **gradient_kwargs)) variables = tfkwargs.get("variables", None) return (vjps, variables) if variables is not None else vjps return res, grad_fn return _execute(*parameters)

true

1c459309ba1a81398fc095a2ca8f6f6f4053e120

990

py

Python

linkv_sdk/config/bindings/ffi.py

linkv-io/python2-sdk

45699372ffcf6e3e745d870cfca004fc885ee15f

[ "Apache-2.0" ]

null

linkv_sdk/config/bindings/ffi.py

linkv-io/python2-sdk

45699372ffcf6e3e745d870cfca004fc885ee15f

[ "Apache-2.0" ]

null

linkv_sdk/config/bindings/ffi.py

linkv-io/python2-sdk

45699372ffcf6e3e745d870cfca004fc885ee15f

[ "Apache-2.0" ]

null

# -*- coding: UTF-8 -*- import platform import os from requests import get from tempfile import gettempdir from ctypes import CDLL def _platform_file(name): ext = '' if platform.uname()[0] == "Linux": ext = 'so' elif platform.uname()[0] == "Darwin": ext = 'dylib' elif platform.uname()[0] == "Windows": ext = 'dll' return "lib{}.{}".format(name, ext) def dlopen_platform_specific(name, path): return CDLL('{}/{}'.format(gettempdir() if path == "" else path, _platform_file(name))) DownloadURL = 'http://dl.linkv.fun/static/server' def download(name, path, version): filepath = '{}/{}'.format(gettempdir() if path == "" else path, _platform_file(name)) if os.path.exists(filepath): return True r = get('{}/{}/{}'.format(DownloadURL, version, _platform_file(name))) if r.status_code != 200: return False with open(filepath, 'wb') as f: f.write(r.content) r.close() return True

22

91

0.611111

import platform import os from requests import get from tempfile import gettempdir from ctypes import CDLL def _platform_file(name): ext = '' if platform.uname()[0] == "Linux": ext = 'so' elif platform.uname()[0] == "Darwin": ext = 'dylib' elif platform.uname()[0] == "Windows": ext = 'dll' return "lib{}.{}".format(name, ext) def dlopen_platform_specific(name, path): return CDLL('{}/{}'.format(gettempdir() if path == "" else path, _platform_file(name))) DownloadURL = 'http://dl.linkv.fun/static/server' def download(name, path, version): filepath = '{}/{}'.format(gettempdir() if path == "" else path, _platform_file(name)) if os.path.exists(filepath): return True r = get('{}/{}/{}'.format(DownloadURL, version, _platform_file(name))) if r.status_code != 200: return False with open(filepath, 'wb') as f: f.write(r.content) r.close() return True

true

1c4595dae899b6160a00fb35d2139755cf007c2b

2,254

py

Python

backend/pyrogram/raw/functions/messages/get_attached_stickers.py

appheap/social-media-analyzer

0f9da098bfb0b4f9eb38e0244aa3a168cf97d51c

[ "Apache-2.0" ]

5

2021-09-11T22:01:15.000Z

2022-03-16T21:33:42.000Z

backend/pyrogram/raw/functions/messages/get_attached_stickers.py

iamatlasss/social-media-analyzer

429d1d2bbd8bfce80c50c5f8edda58f87ace668d

[ "Apache-2.0" ]

null

backend/pyrogram/raw/functions/messages/get_attached_stickers.py

iamatlasss/social-media-analyzer

429d1d2bbd8bfce80c50c5f8edda58f87ace668d

[ "Apache-2.0" ]

3

2022-01-18T11:06:22.000Z

2022-02-26T13:39:28.000Z

# Pyrogram - Telegram MTProto API Client Library for Python # Copyright (C) 2017-2021 Dan <https://github.com/delivrance> # # This file is part of Pyrogram. # # Pyrogram is free software: you can redistribute it and/or modify # it under the terms of the GNU Lesser General Public License as published # by the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # Pyrogram is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public License # along with Pyrogram. If not, see <http://www.gnu.org/licenses/>. from io import BytesIO from pyrogram.raw.core.primitives import Int, Long, Int128, Int256, Bool, Bytes, String, Double, Vector from pyrogram.raw.core import TLObject from pyrogram import raw from typing import List, Union, Any # # # # # # # # # # # # # # # # # # # # # # # # # !!! WARNING !!! # # This is a generated file! # # All changes made in this file will be lost! # # # # # # # # # # # # # # # # # # # # # # # # # class GetAttachedStickers(TLObject): # type: ignore """Telegram API method. Details: - Layer: ``123`` - ID: ``0xcc5b67cc`` Parameters: media: :obj:`InputStickeredMedia <pyrogram.raw.base.InputStickeredMedia>` Returns: List of :obj:`StickerSetCovered <pyrogram.raw.base.StickerSetCovered>` """ __slots__: List[str] = ["media"] ID = 0xcc5b67cc QUALNAME = "functions.messages.GetAttachedStickers" def __init__(self, *, media: "raw.base.InputStickeredMedia") -> None: self.media = media # InputStickeredMedia @staticmethod def read(data: BytesIO, *args: Any) -> "GetAttachedStickers": # No flags media = TLObject.read(data) return GetAttachedStickers(media=media) def write(self) -> bytes: data = BytesIO() data.write(Int(self.ID, False)) # No flags data.write(self.media.write()) return data.getvalue()

31.305556

103

0.645519

from io import BytesIO from pyrogram.raw.core.primitives import Int, Long, Int128, Int256, Bool, Bytes, String, Double, Vector from pyrogram.raw.core import TLObject from pyrogram import raw from typing import List, Union, Any

true

1c459686e0c6196509dccaf4fcbecf5fdc393fc7

41,713

py

Python

xform/models.py

alisonamerico/Django-XForm

ad2e96455307b57ef3c485a006db478fe4352a36

[ "MIT" ]

3

2019-07-25T14:46:14.000Z

2020-12-14T22:43:46.000Z

xform/models.py

alisonamerico/Django-XForm

ad2e96455307b57ef3c485a006db478fe4352a36

[ "MIT" ]

4

2019-09-04T17:39:04.000Z

2021-11-05T23:14:58.000Z

xform/models.py

alisonamerico/Django-XForm

ad2e96455307b57ef3c485a006db478fe4352a36

[ "MIT" ]

1

2021-11-05T23:05:48.000Z

import csv import json import mimetypes import os import random import re import requests import xlrd from contextlib import closing from hashlib import md5 from io import BytesIO from io import StringIO from pyxform import SurveyElementBuilder from pyxform.builder import create_survey_element_from_dict from pyxform.utils import has_external_choices from pyxform.xform2json import create_survey_element_from_xml from pyxform.xls2json import parse_file_to_json from xml.dom import Node from django.conf import settings from django.contrib.contenttypes.fields import GenericForeignKey from django.contrib.contenttypes.fields import GenericRelation from django.contrib.contenttypes.models import ContentType from django.contrib.gis.db import models from django.contrib.gis.geos import GeometryCollection, Point from django.core.exceptions import ValidationError from django.core.files.temp import NamedTemporaryFile from django.core.files.uploadedfile import InMemoryUploadedFile from django.core.validators import URLValidator from django.db.models.signals import post_save from django.utils import timezone from .tags import ( UUID, ID, ATTACHMENTS, STATUS, NOTES, VERSION, DURATION, XFORM_ID_STRING, XFORM_ID, GEOLOCATION, SUBMITTED_BY, SUBMISSION_TIME, TOTAL_MEDIA, MEDIA_COUNT, MEDIA_ALL_RECEIVED, EDITED, LAST_EDITED, KNOWN_MEDIA_TYPES, START, END ) from .utils import ( get_values_matching_key, get_uuid_from_xml, set_uuid, XFormInstanceParser, clean_and_parse_xml, get_numeric_fields, numeric_checker, _get_tag_or_element_type_xpath, calculate_duration ) if 'postg' in settings.DATABASES['default']['ENGINE']: from django.contrib.postgres.fields import JSONField else: from jsonfield import JSONField CHUNK_SIZE = 1024 XFORM_TITLE_LENGTH = 255 title_pattern = re.compile(r"<h:title>(.*?)</h:title>") def contains_xml_invalid_char(text, invalids=['&', '>', '<']): """Check whether 'text' contains ANY invalid xml chars""" return 1 in [c in text for c in invalids] def convert_to_serializable_date(date): if hasattr(date, 'isoformat'): return date.isoformat() return date def _get_attachments_from_instance(instance): attachments = [] for a in instance.attachments.all(): attachment = dict() attachment['download_url'] = a.media_file.url attachment['small_download_url'] = a.media_file.url attachment['medium_download_url'] = a.media_file.url attachment['mimetype'] = a.mimetype attachment['filename'] = a.media_file.name attachment['name'] = a.name attachment['instance'] = a.instance.pk attachment['xform'] = instance.xform.id attachment['id'] = a.id attachments.append(attachment) return attachments def get_default_content_type(): content_object, created = ContentType.objects.get_or_create( app_label="xform", model='xform') return content_object.id def upload_to(instance, filename): try: return os.path.join( instance.user.username, 'xls', os.path.split(filename)[1]) except Exception: folder = "{}_{}".format(instance.instance.xform.id, instance.instance.xform.id_string) return os.path.join( instance.instance.xform.user.username, 'attachments', folder, os.path.split(filename)[1]) class XLSFormError(Exception): pass class FormInactiveError(Exception): pass class XForm(models.Model): dynamic_choices = True xls = models.FileField(upload_to=upload_to, null=True) json = models.TextField(default=u'') description = models.TextField(default=u'', null=True, blank=True) xml = models.TextField() user = models.ForeignKey( settings.AUTH_USER_MODEL, related_name='xforms', null=True, on_delete=models.CASCADE) id_string = models.SlugField( editable=False, verbose_name="ID", max_length=100) title = models.CharField(editable=False, max_length=255) date_created = models.DateTimeField(auto_now_add=True) date_modified = models.DateTimeField(auto_now=True) last_submission_time = models.DateTimeField(blank=True, null=True) has_start_time = models.BooleanField(default=False) uuid = models.CharField(max_length=36, default=u'') uuid_regex = re.compile(r'(<instance>.*?id="[^"]+">)(.*</instance>)(.*)', re.DOTALL) instance_id_regex = re.compile(r'<instance>.*?id="([^"]+)".*</instance>', re.DOTALL) instances_with_geopoints = models.BooleanField(default=False) num_of_submissions = models.IntegerField(default=0) version = models.CharField( max_length=255, null=True, blank=True) created_by = models.ForeignKey( settings.AUTH_USER_MODEL, null=True, blank=True, on_delete=models.CASCADE) metadata_set = GenericRelation( 'MetaData', content_type_field='content_type_id', object_id_field="object_id") has_hxl_support = models.BooleanField(default=False) last_updated_at = models.DateTimeField(auto_now=True) hash = models.CharField("Hash", max_length=36, blank=True, null=True, default=None) class Meta: unique_together = ("user", "id_string",) verbose_name = "XForm" verbose_name_plural = "XForms" ordering = ("pk", ) def get_osm_survey_xpaths(self): """ Returns abbreviated_xpath for OSM question types in the survey. """ return [ elem.get_abbreviated_xpath() for elem in self.get_survey_elements_of_type('osm')] def get_media_survey_xpaths(self): return [ e.get_abbreviated_xpath() for e in sum([ self.get_survey_elements_of_type(m) for m in KNOWN_MEDIA_TYPES ], []) ] def file_name(self): return self.id_string + ".xml" def get_survey_elements_of_type(self, element_type): return [ e for e in self.get_survey_elements() if e.type == element_type ] def _set_uuid_in_xml(self, file_name=None): """ Add bind to automatically set UUID node in XML. """ if not file_name: file_name = self.file_name() file_name, file_ext = os.path.splitext(file_name) doc = clean_and_parse_xml(self.xml) model_nodes = doc.getElementsByTagName("model") if len(model_nodes) != 1: raise Exception(u"xml contains multiple model nodes") model_node = model_nodes[0] instance_nodes = [ node for node in model_node.childNodes if node.nodeType == Node.ELEMENT_NODE and node.tagName.lower() == "instance" and not node.hasAttribute("id") ] if len(instance_nodes) != 1: raise Exception("Multiple instance nodes without the id " "attribute, can't tell which is the main one") instance_node = instance_nodes[0] # get the first child whose id attribute matches our id_string survey_nodes = [ node for node in instance_node.childNodes if node.nodeType == Node.ELEMENT_NODE and (node.tagName == file_name or node.attributes.get('id')) ] if len(survey_nodes) != 1: raise Exception( "Multiple survey nodes with the id '%s'" % self.id_string) survey_node = survey_nodes[0] formhub_nodes = [ n for n in survey_node.childNodes if n.nodeType == Node.ELEMENT_NODE and n.tagName == "formhub" ] if len(formhub_nodes) > 1: raise Exception( "Multiple formhub nodes within main instance node") elif len(formhub_nodes) == 1: formhub_node = formhub_nodes[0] else: formhub_node = survey_node.insertBefore( doc.createElement("formhub"), survey_node.firstChild) uuid_nodes = [ node for node in formhub_node.childNodes if node.nodeType == Node.ELEMENT_NODE and node.tagName == "uuid" ] if len(uuid_nodes) == 0: formhub_node.appendChild(doc.createElement("uuid")) if len(formhub_nodes) == 0: # append the calculate bind node calculate_node = doc.createElement("bind") calculate_node.setAttribute( "nodeset", "/%s/formhub/uuid" % survey_node.tagName) calculate_node.setAttribute("type", "string") calculate_node.setAttribute("calculate", "'%s'" % self.uuid) model_node.appendChild(calculate_node) self.xml = doc.toprettyxml(indent=" ", encoding='utf-8') # hack # http://ronrothman.com/public/leftbraned/xml-dom-minidom-toprettyxml-\ # and-silly-whitespace/ text_re = re.compile('(>)\n\s*(\s[^<>\s].*?)\n\s*(\s</)', re.DOTALL) output_re = re.compile('\n.*(<output.*>)\n( )*') pretty_xml = text_re.sub(lambda m: ''.join(m.group(1, 2, 3)), self.xml.decode('utf-8')) inline_output = output_re.sub('\g<1>', pretty_xml) inline_output = re.compile('<label>\s*\n*\s*\n*\s*</label>').sub( '<label></label>', inline_output) self.xml = inline_output def _mark_start_time_boolean(self): starttime_substring = 'jr:preloadParams="start"' if self.xml.find(starttime_substring) != -1: self.has_start_time = True else: self.has_start_time = False def _id_string_already_exists_in_account(self, id_string): try: XForm.objects.get(id_string__iexact=id_string) except XForm.DoesNotExist: return False return True def get_unique_id_string(self, id_string, count=0): # used to generate a new id_string for new data_dictionary object if # id_string already existed if self._id_string_already_exists_in_account(id_string): if count != 0: if re.match(r'\w+_\d+$', id_string): a = id_string.split('_') id_string = "_".join(a[:-1]) count += 1 id_string = "{}_{}".format(id_string, count) return self.get_unique_id_string(id_string, count) return id_string def _set_title(self): xml = re.sub(r"\s+", " ", self.xml) matches = title_pattern.findall(xml) if len(matches) != 1: raise XLSFormError(("There should be a single title."), matches) if matches: title_xml = matches[0][:XFORM_TITLE_LENGTH] else: title_xml = self.title[:XFORM_TITLE_LENGTH] if self.title else '' if self.title and title_xml != self.title: title_xml = self.title[:XFORM_TITLE_LENGTH] if isinstance(self.xml, bytes): self.xml = self.xml.decode('utf-8') self.xml = title_pattern.sub(u"<h:title>%s</h:title>" % title_xml, self.xml) self._set_hash() if contains_xml_invalid_char(title_xml): raise XLSFormError( "Title shouldn't have any invalid xml " "characters ('>' '&' '<')" ) self.title = title_xml def get_hash(self): return u'md5:%s' % md5(self.xml.encode('utf8')).hexdigest() def get_random_hash(self): return u'md5:%s' % md5( ("%s-%s" % ( self.xml, random.randint(0, 25101991) )).encode('utf8') ).hexdigest() @property def random_hash(self): return self.get_random_hash() def _set_hash(self): self.hash = self.get_hash() def _set_id_string(self): matches = self.instance_id_regex.findall(self.xml) if len(matches) != 1: raise XLSFormError("There should be a single id string.") self.id_string = matches[0] def save(self, *args, **kwargs): update_fields = kwargs.get('update_fields') if update_fields: kwargs['update_fields'] = list( set(list(update_fields) + ['date_modified'])) if update_fields is None or 'title' in update_fields: self._set_title() if self.pk is None: self._set_hash() if update_fields is None or 'id_string' in update_fields: old_id_string = self.id_string self._set_id_string() # check if we have an existing id_string, # if so, the one must match but only if xform is NOT new if self.pk and old_id_string and old_id_string != self.id_string \ and self.num_of_submissions > 0: raise XLSFormError( "Your updated form's id_string '%(new_id)s' must match " "the existing forms' id_string '%(old_id)s'." % { 'new_id': self.id_string, 'old_id': old_id_string }) if getattr(settings, 'STRICT', True) and \ not re.search(r"^[\w-]+$", self.id_string): raise XLSFormError( 'In strict mode, the XForm ID must be a ' 'valid slug and contain no spaces.') if 'skip_xls_read' in kwargs: del kwargs['skip_xls_read'] super(XForm, self).save(*args, **kwargs) def get_survey(self): if not hasattr(self, "_survey"): try: builder = SurveyElementBuilder() self._survey = \ builder.create_survey_element_from_json(self.json) except ValueError: xml = bytes(bytearray(self.xml, encoding='utf-8')) self._survey = create_survey_element_from_xml(xml) return self._survey survey = property(get_survey) def get_survey_elements(self): return self.survey.iter_descendants() def geopoint_xpaths(self): survey_elements = self.get_survey_elements() return [ e.get_abbreviated_xpath() for e in survey_elements if e.bind.get(u'type') == u'geopoint' ] def __str__(self): return self.id_string def type_for_form(content_object, data_type): content_type = ContentType.objects.get_for_model(content_object) return MetaData.objects.filter(object_id=content_object.id, content_type=content_type, data_type=data_type) def is_valid_url(uri): try: URLValidator(uri) except ValidationError: return False return True def create_media(media): """Download media link""" if is_valid_url(media.data_value): filename = media.data_value.split('/')[-1] data_file = NamedTemporaryFile() content_type = mimetypes.guess_type(filename) with closing(requests.get(media.data_value, stream=True)) as r: for chunk in r.iter_content(chunk_size=CHUNK_SIZE): if chunk: data_file.write(chunk) data_file.seek(os.SEEK_SET, os.SEEK_END) size = os.path.getsize(data_file.name) data_file.seek(os.SEEK_SET) media.data_value = filename media.data_file = InMemoryUploadedFile( data_file, 'data_file', filename, content_type, size, charset=None) return media return None def media_resources(media_list, download=False): """List of MetaData objects of type media @param media_list - list of MetaData objects of type `media` @param download - boolean, when True downloads media files when media.data_value is a valid url return a list of MetaData objects """ data = [] for media in media_list: if media.data_file.name == '' and download: media = create_media(media) if media: data.append(media) else: data.append(media) return data def meta_data_upload_to(instance, filename): username = None if instance.content_object.user is None and \ instance.content_type.model == 'instance': username = instance.content_object.xform.user.username else: username = instance.content_object.user.username if instance.data_type == 'media': return os.path.join(username, 'formid-media', filename) return os.path.join(username, 'docs', filename) class MetaData(models.Model): data_type = models.CharField(max_length=255) data_value = models.CharField(max_length=255) data_file = models.FileField( upload_to=meta_data_upload_to, blank=True, null=True) data_file_type = models.CharField(max_length=255, blank=True, null=True) file_hash = models.CharField(max_length=50, blank=True, null=True) date_created = models.DateTimeField(null=True, auto_now_add=True) date_modified = models.DateTimeField(null=True, auto_now=True) deleted_at = models.DateTimeField(null=True, default=None) content_type = models.ForeignKey(ContentType, on_delete=models.CASCADE, default=get_default_content_type) object_id = models.PositiveIntegerField(null=True, blank=True) content_object = GenericForeignKey('content_type', 'object_id') objects = models.Manager() class Meta: unique_together = ('object_id', 'data_type', 'data_value', 'content_type') def __str__(self): return self.data_value def file(self, username=None): if hasattr(self, '_file'): return self._file url = requests.Request( 'GET', self.data_value, params={ 'username': username } ).prepare().url self._file = MetaData.get_file(url) return self._file @staticmethod def media_upload(content_object, data_file=None, download=False): data_type = 'media' if data_file: allowed_types = settings.XFORM_SUPPORTED_MEDIA_UPLOAD_TYPES data_content_type = data_file.content_type \ if data_file.content_type in allowed_types else \ mimetypes.guess_type(data_file.name)[0] if data_content_type in allowed_types: content_type = ContentType.objects.get_for_model( content_object) media, created = MetaData.objects.update_or_create( data_type=data_type, content_type=content_type, object_id=content_object.id, data_value=data_file.name, defaults={ 'data_file': data_file, 'data_file_type': data_content_type }) return media_resources( type_for_form(content_object, data_type), download) @staticmethod def get_md5(data_file): hash_md5 = md5() for chunk in iter(lambda: data_file.read(4096), b""): hash_md5.update(chunk) return 'md5:%s' % hash_md5.hexdigest() @staticmethod def get_file(url): data_file = None output = BytesIO() def getsize(f): f.seek(0) f.read() s = f.tell() f.seek(0) return s r = requests.get(url, allow_redirects=True) d = r.headers['content-disposition'] fname = re.findall("filename=\"(.+)\"", d)[0] content_type = r.headers.get('content-type') output.write(r.content) size = getsize(output) data_file = InMemoryUploadedFile( file=output, name=fname, field_name=None, content_type=content_type, charset='utf-8', size=size ) return data_file @staticmethod def add_url(content_object, url=None, download=False): data_type = 'url' try: data_file = MetaData.get_file(url) except Exception: return None allowed_types = settings.XFORM_SUPPORTED_MEDIA_UPLOAD_TYPES data_content_type = data_file.content_type \ if data_file.content_type in allowed_types else \ mimetypes.guess_type(data_file.name)[0] if data_content_type in allowed_types: content_type = ContentType.objects.get_for_model( content_object) media, created = MetaData.objects.update_or_create( data_type=data_type, content_type=content_type, object_id=content_object.id, data_value=url, defaults={ 'data_file': None, 'data_file_type': data_content_type }) return media_resources( type_for_form(content_object, data_type), download) def save(self, *args, **kwargs): self._set_hash() super(MetaData, self).save(*args, **kwargs) @property def hash(self): if self.file_hash is not None and self.file_hash != '': return self.file_hash else: return self._set_hash() def _set_hash(self): if not self.data_file: return None file_exists = self.data_file.storage.exists(self.data_file.name) if (file_exists and self.data_file.name != '') \ or (not file_exists and self.data_file): try: self.data_file.seek(os.SEEK_SET) except IOError: return '' else: self.file_hash = 'md5:%s' % md5( self.data_file.read()).hexdigest() return self.file_hash return '' class Instance(models.Model): """ Model representing a single submission to an XForm """ json = JSONField(default=dict, null=False) xml = models.TextField() user = models.ForeignKey( settings.AUTH_USER_MODEL, related_name='instances', null=True, on_delete=models.CASCADE) xform = models.ForeignKey('xform.XForm', null=False, related_name='instances', on_delete=models.CASCADE) # shows when we first received this instance date_created = models.DateTimeField(auto_now_add=True) # this will end up representing "date last parsed" date_modified = models.DateTimeField(auto_now=True) # this will be edited when we need to create a new InstanceHistory object last_edited = models.DateTimeField(null=True, default=None) # ODK keeps track of three statuses for an instance: # incomplete, submitted, complete # we add a fourth status: submitted_via_web status = models.CharField(max_length=20, default=u'submitted_via_web') uuid = models.CharField(max_length=249, default=u'', db_index=True) version = models.CharField(max_length=255, null=True) # store a geographic objects associated with this instance geom = models.GeometryCollectionField(null=True) # Keep track of whether all media attachments have been received media_all_received = models.NullBooleanField( "Received All Media Attachemts", null=True, default=True) total_media = models.PositiveIntegerField("Total Media Attachments", null=True, default=0) media_count = models.PositiveIntegerField("Received Media Attachments", null=True, default=0) checksum = models.CharField(max_length=64, null=True, blank=True, db_index=True) class Meta: unique_together = ('xform', 'uuid') def __str__(self): return "Status: %s" % self.status @property def point(self): gc = self.geom if gc and len(gc): return gc[0] def get_duration(self): data = self.get_dict() # pylint: disable=no-member start_name = _get_tag_or_element_type_xpath(self.xform, START) end_name = _get_tag_or_element_type_xpath(self.xform, END) start_time, end_time = data.get(start_name), data.get(end_name) return calculate_duration(start_time, end_time) @property def num_of_media(self): """ Returns number of media attachments expected in the submission. """ if not hasattr(self, '_num_of_media'): # pylint: disable=attribute-defined-outside-init self._num_of_media = len(self.get_expected_media()) return self._num_of_media @property def attachments_count(self): return len(set(self.attachments.filter( name__in=self.get_expected_media() ).values_list('name', flat=True))) def get_expected_media(self): """ Returns a list of expected media files from the submission data. """ if not hasattr(self, '_expected_media'): # pylint: disable=no-member data = self.get_dict() media_list = [] if 'encryptedXmlFile' in data and self.xform.encrypted: media_list.append(data['encryptedXmlFile']) if 'media' in data: # pylint: disable=no-member media_list.extend([i['media/file'] for i in data['media']]) else: media_xpaths = (self.xform.get_media_survey_xpaths() + self.xform.get_osm_survey_xpaths()) for media_xpath in media_xpaths: media_list.extend( get_values_matching_key(data, media_xpath)) # pylint: disable=attribute-defined-outside-init self._expected_media = list(set(media_list)) return self._expected_media def numeric_converter(self, json_dict, numeric_fields=None): if numeric_fields is None: # pylint: disable=no-member numeric_fields = get_numeric_fields(self.xform) for key, value in json_dict.items(): if isinstance(value, (str, bytes)) and key in numeric_fields: converted_value = numeric_checker(value) if converted_value: json_dict[key] = converted_value elif isinstance(value, dict): json_dict[key] = self.numeric_converter( value, numeric_fields) elif isinstance(value, list): for k, v in enumerate(value): if isinstance(v, (str, bytes)) and key in numeric_fields: converted_value = numeric_checker(v) if converted_value: json_dict[key] = converted_value elif isinstance(v, dict): value[k] = self.numeric_converter( v, numeric_fields) return json_dict def _set_geom(self): # pylint: disable=no-member xform = self.xform geo_xpaths = xform.geopoint_xpaths() doc = self.get_dict() points = [] if geo_xpaths: for xpath in geo_xpaths: for gps in get_values_matching_key(doc, xpath): try: geometry = [float(s) for s in gps.split()] lat, lng = geometry[0:2] points.append(Point(lng, lat)) except ValueError: return if not xform.instances_with_geopoints and len(points): xform.instances_with_geopoints = True xform.save() self.geom = GeometryCollection(points) def _check_active(self, force): """Check that form is active and raise exception if not. :param force: Ignore restrictions on saving. """ # pylint: disable=no-member # if not force and self.xform and not self.xform.downloadable: # raise FormInactiveError() pass def _set_json(self): self.json = self.get_full_dict() def get_full_dict(self, load_existing=True): doc = self.json or {} if load_existing else {} # Get latest dict doc = self.get_dict() # pylint: disable=no-member if self.id: doc.update({ UUID: self.uuid, ID: self.id, # BAMBOO_DATASET_ID: self.xform.bamboo_dataset, ATTACHMENTS: _get_attachments_from_instance(self), STATUS: self.status, # TAGS: list(self.tags.names()), NOTES: [], VERSION: self.version, DURATION: self.get_duration(), XFORM_ID_STRING: self._parser.get_xform_id_string(), XFORM_ID: self.xform.pk, GEOLOCATION: [self.point.y, self.point.x] if self.point else [None, None], SUBMITTED_BY: self.user.username if self.user else None }) # for osm in self.osm_data.all(): # doc.update(osm.get_tags_with_prefix()) if not self.date_created: self.date_created = timezone.now() doc[SUBMISSION_TIME] = self.date_created.strftime( '%Y-%m-%dT%H:%M:%S') doc[TOTAL_MEDIA] = self.total_media doc[MEDIA_COUNT] = self.media_count doc[MEDIA_ALL_RECEIVED] = self.media_all_received edited = False if hasattr(self, 'last_edited'): edited = self.last_edited is not None doc[EDITED] = edited edited and doc.update({ LAST_EDITED: convert_to_serializable_date(self.last_edited) }) return doc def get_dict(self, force_new=False, flat=True): """Return a python object representation of this instance's XML.""" self._set_parser() instance_dict = self._parser.get_flat_dict_with_attributes() if flat \ else self._parser.to_dict() return self.numeric_converter(instance_dict) def _set_survey_type(self): self.survey_type = self.get_root_node_name() def _set_parser(self): if not hasattr(self, "_parser"): # pylint: disable=no-member self._parser = XFormInstanceParser(self.xml, self.xform) def get_root_node_name(self): self._set_parser() return self._parser.get_root_node_name() def _set_uuid(self): # pylint: disable=no-member, attribute-defined-outside-init if self.xml and not self.uuid: # pylint: disable=no-member uuid = get_uuid_from_xml(self.xml) if uuid is not None: self.uuid = uuid set_uuid(self) def save(self, *args, **kwargs): force = kwargs.get('force') if force: del kwargs['force'] # self._check_is_merged_dataset() self._check_active(force) self._set_geom() self._set_json() self._set_survey_type() self._set_uuid() # pylint: disable=no-member self.version = self.json.get(VERSION, self.xform.version) super(Instance, self).save(*args, **kwargs) class Attachment(models.Model): OSM = 'osm' instance = models.ForeignKey( Instance, related_name="attachments", on_delete=models.CASCADE) media_file = models.FileField( max_length=255, upload_to=upload_to) mimetype = models.CharField( max_length=100, null=False, blank=True, default='') extension = models.CharField( max_length=10, null=False, blank=False, default=u"non", db_index=True) date_created = models.DateTimeField(null=True, auto_now_add=True) date_modified = models.DateTimeField(null=True, auto_now=True) file_size = models.PositiveIntegerField(default=0) name = models.CharField(max_length=100, null=True, blank=True) class Meta: ordering = ("pk", ) def save(self, *args, **kwargs): if self.media_file and self.mimetype == '': # guess mimetype mimetype, encoding = mimetypes.guess_type(self.media_file.name) if mimetype: self.mimetype = mimetype if self.media_file and len(self.media_file.name) > 255: raise ValueError( "Length of the media file should be less or equal to 255") try: f_size = self.media_file.size if f_size: self.file_size = f_size except (OSError, AttributeError): pass try: self.name = self.filename self.extension = self.name.rsplit('.', 1)[1] except Exception: pass super(Attachment, self).save(*args, **kwargs) @property def file_hash(self): if self.media_file.storage.exists(self.media_file.name): return u'%s' % md5(self.media_file.read()).hexdigest() return u'' @property def filename(self): if self.media_file: return os.path.basename(self.media_file.name) def is_newline_error(e): """ Return True is e is a new line error based on the error text. Otherwise return False. """ newline_error = u'new-line character seen in unquoted field - do you need'\ u' to open the file in universal-newline mode?' return newline_error == str(e) def process_xlsform(xls, default_name): """ Process XLSForm file and return the survey dictionary for the XLSForm. """ # FLOW Results package is a JSON file. file_object = None if xls.name.endswith('csv'): # a csv file gets closed in pyxform, make a copy xls.seek(0) file_object = BytesIO() file_object.write(xls.read()) file_object.seek(0) xls.seek(0) try: return parse_file_to_json(xls.name, file_object=file_object or xls) except csv.Error as e: if is_newline_error(e): xls.seek(0) file_object = StringIO( u'\n'.join(xls.read().splitlines())) return parse_file_to_json( xls.name, default_name=default_name, file_object=file_object) raise e def get_columns_with_hxl(survey_elements): ''' Returns a dictionary whose keys are xform field names and values are `instance::hxl` values set on the xform :param include_hxl - boolean value :param survey_elements - survey elements of an xform return dictionary or None ''' return survey_elements and { se.get('name'): val.get('hxl') for se in survey_elements for key, val in se.items() if key == 'instance' and val and 'hxl' in val } def check_version_set(survey): """ Checks if the version has been set in the xls file and if not adds the default version in this datetime (yyyymmddhhmm) format. """ # get the json and check for the version key survey_json = json.loads(survey.to_json()) if not survey_json.get("version"): # set utc time as the default version survey_json['version'] = \ timezone.now().strftime("%Y%m%d%H%M") builder = SurveyElementBuilder() survey = builder.create_survey_element_from_json( json.dumps(survey_json)) return survey class DataDictionary(XForm): # pylint: disable=too-many-instance-attributes """ DataDictionary model class. """ def __init__(self, *args, **kwargs): self.instances_for_export = lambda d: d.instances.all() self.has_external_choices = False self._id_string_changed = False super(DataDictionary, self).__init__(*args, **kwargs) def __str__(self): return getattr(self, "id_string", "") def save(self, *args, **kwargs): skip_xls_read = kwargs.get('skip_xls_read') if self.xls and not skip_xls_read: default_name = None \ if not self.pk else self.survey.xml_instance().tagName survey_dict = process_xlsform(self.xls, default_name) if has_external_choices(survey_dict): self.has_external_choices = True survey = create_survey_element_from_dict(survey_dict) survey = check_version_set(survey) if get_columns_with_hxl(survey.get('children')): self.has_hxl_support = True # if form is being replaced, don't check for id_string uniqueness if self.pk is None: new_id_string = self.get_unique_id_string( survey.get('id_string')) self._id_string_changed = \ new_id_string != survey.get('id_string') survey['id_string'] = new_id_string # For flow results packages use the user defined id/uuid elif self.id_string != survey.get('id_string'): raise XLSFormError( ("Your updated form's id_string '%(new_id)s' must match " "the existing forms' id_string '%(old_id)s'." % { 'new_id': survey.get('id_string'), 'old_id': self.id_string})) elif default_name and default_name != survey.get('name'): survey['name'] = default_name else: survey['id_string'] = self.id_string self.json = survey.to_json() self.xml = survey.to_xml() self.version = survey.get('version') self.last_updated_at = timezone.now() self.title = survey.get('title') self._mark_start_time_boolean() set_uuid(self) self._set_uuid_in_xml() self._set_hash() if 'skip_xls_read' in kwargs: del kwargs['skip_xls_read'] super(DataDictionary, self).save(*args, **kwargs) def file_name(self): return os.path.split(self.xls.name)[-1] def sheet_to_csv(xls_content, sheet_name): """Writes a csv file of a specified sheet from a an excel file :param xls_content: Excel file contents :param sheet_name: the name of the excel sheet to generate the csv file :returns: a (StrionIO) csv file object """ workbook = xlrd.open_workbook(file_contents=xls_content) sheet = workbook.sheet_by_name(sheet_name) if not sheet or sheet.nrows < 2: raise Exception("Sheet <'%(sheet_name)s'> has no data." % { 'sheet_name': sheet_name}) csv_file = BytesIO() writer = csv.writer(csv_file, encoding='utf-8', quoting=csv.QUOTE_ALL) mask = [v and len(v.strip()) > 0 for v in sheet.row_values(0)] header = [v for v, m in zip(sheet.row_values(0), mask) if m] writer.writerow(header) name_column = None try: name_column = header.index('name') except ValueError: pass integer_fields = False date_fields = False if name_column: name_column_values = sheet.col_values(name_column) for index in range(len(name_column_values)): if sheet.cell_type(index, name_column) == xlrd.XL_CELL_NUMBER: integer_fields = True elif sheet.cell_type(index, name_column) == xlrd.XL_CELL_DATE: date_fields = True for row in range(1, sheet.nrows): if integer_fields or date_fields: # convert integers to string/datetime if name has numbers/dates row_values = [] for index, val in enumerate(sheet.row_values(row)): if sheet.cell_type(row, index) == xlrd.XL_CELL_NUMBER: try: val = str( float(val) if ( float(val) > int(val) ) else int(val) ) except ValueError: pass elif sheet.cell_type(row, index) == xlrd.XL_CELL_DATE: val = xlrd.xldate_as_datetime( val, workbook.datemode).isoformat() row_values.append(val) writer.writerow([v for v, m in zip(row_values, mask) if m]) else: writer.writerow( [v for v, m in zip(sheet.row_values(row), mask) if m]) return csv_file def set_object_permissions(sender, instance=None, created=False, **kwargs): """ Apply the relevant object permissions for the form to all users who should have access to it. """ # seems the super is not called, have to get xform from here xform = XForm.objects.get(pk=instance.pk) if hasattr(instance, 'has_external_choices') \ and instance.has_external_choices: instance.xls.seek(0) f = sheet_to_csv(instance.xls.read(), 'external_choices') f.seek(0, os.SEEK_END) size = f.tell() f.seek(0) data_file = InMemoryUploadedFile( file=f, field_name='data_file', name='itemsets.csv', content_type='text/csv', size=size, charset=None ) MetaData.media_upload(xform, data_file) post_save.connect(set_object_permissions, sender=DataDictionary, dispatch_uid='xform_object_permissions')

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import csv import json import mimetypes import os import random import re import requests import xlrd from contextlib import closing from hashlib import md5 from io import BytesIO from io import StringIO from pyxform import SurveyElementBuilder from pyxform.builder import create_survey_element_from_dict from pyxform.utils import has_external_choices from pyxform.xform2json import create_survey_element_from_xml from pyxform.xls2json import parse_file_to_json from xml.dom import Node from django.conf import settings from django.contrib.contenttypes.fields import GenericForeignKey from django.contrib.contenttypes.fields import GenericRelation from django.contrib.contenttypes.models import ContentType from django.contrib.gis.db import models from django.contrib.gis.geos import GeometryCollection, Point from django.core.exceptions import ValidationError from django.core.files.temp import NamedTemporaryFile from django.core.files.uploadedfile import InMemoryUploadedFile from django.core.validators import URLValidator from django.db.models.signals import post_save from django.utils import timezone from .tags import ( UUID, ID, ATTACHMENTS, STATUS, NOTES, VERSION, DURATION, XFORM_ID_STRING, XFORM_ID, GEOLOCATION, SUBMITTED_BY, SUBMISSION_TIME, TOTAL_MEDIA, MEDIA_COUNT, MEDIA_ALL_RECEIVED, EDITED, LAST_EDITED, KNOWN_MEDIA_TYPES, START, END ) from .utils import ( get_values_matching_key, get_uuid_from_xml, set_uuid, XFormInstanceParser, clean_and_parse_xml, get_numeric_fields, numeric_checker, _get_tag_or_element_type_xpath, calculate_duration ) if 'postg' in settings.DATABASES['default']['ENGINE']: from django.contrib.postgres.fields import JSONField else: from jsonfield import JSONField CHUNK_SIZE = 1024 XFORM_TITLE_LENGTH = 255 title_pattern = re.compile(r"<h:title>(.*?)</h:title>") def contains_xml_invalid_char(text, invalids=['&', '>', '<']): return 1 in [c in text for c in invalids] def convert_to_serializable_date(date): if hasattr(date, 'isoformat'): return date.isoformat() return date def _get_attachments_from_instance(instance): attachments = [] for a in instance.attachments.all(): attachment = dict() attachment['download_url'] = a.media_file.url attachment['small_download_url'] = a.media_file.url attachment['medium_download_url'] = a.media_file.url attachment['mimetype'] = a.mimetype attachment['filename'] = a.media_file.name attachment['name'] = a.name attachment['instance'] = a.instance.pk attachment['xform'] = instance.xform.id attachment['id'] = a.id attachments.append(attachment) return attachments def get_default_content_type(): content_object, created = ContentType.objects.get_or_create( app_label="xform", model='xform') return content_object.id def upload_to(instance, filename): try: return os.path.join( instance.user.username, 'xls', os.path.split(filename)[1]) except Exception: folder = "{}_{}".format(instance.instance.xform.id, instance.instance.xform.id_string) return os.path.join( instance.instance.xform.user.username, 'attachments', folder, os.path.split(filename)[1]) class XLSFormError(Exception): pass class FormInactiveError(Exception): pass class XForm(models.Model): dynamic_choices = True xls = models.FileField(upload_to=upload_to, null=True) json = models.TextField(default=u'') description = models.TextField(default=u'', null=True, blank=True) xml = models.TextField() user = models.ForeignKey( settings.AUTH_USER_MODEL, related_name='xforms', null=True, on_delete=models.CASCADE) id_string = models.SlugField( editable=False, verbose_name="ID", max_length=100) title = models.CharField(editable=False, max_length=255) date_created = models.DateTimeField(auto_now_add=True) date_modified = models.DateTimeField(auto_now=True) last_submission_time = models.DateTimeField(blank=True, null=True) has_start_time = models.BooleanField(default=False) uuid = models.CharField(max_length=36, default=u'') uuid_regex = re.compile(r'(<instance>.*?id="[^"]+">)(.*</instance>)(.*)', re.DOTALL) instance_id_regex = re.compile(r'<instance>.*?id="([^"]+)".*</instance>', re.DOTALL) instances_with_geopoints = models.BooleanField(default=False) num_of_submissions = models.IntegerField(default=0) version = models.CharField( max_length=255, null=True, blank=True) created_by = models.ForeignKey( settings.AUTH_USER_MODEL, null=True, blank=True, on_delete=models.CASCADE) metadata_set = GenericRelation( 'MetaData', content_type_field='content_type_id', object_id_field="object_id") has_hxl_support = models.BooleanField(default=False) last_updated_at = models.DateTimeField(auto_now=True) hash = models.CharField("Hash", max_length=36, blank=True, null=True, default=None) class Meta: unique_together = ("user", "id_string",) verbose_name = "XForm" verbose_name_plural = "XForms" ordering = ("pk", ) def get_osm_survey_xpaths(self): return [ elem.get_abbreviated_xpath() for elem in self.get_survey_elements_of_type('osm')] def get_media_survey_xpaths(self): return [ e.get_abbreviated_xpath() for e in sum([ self.get_survey_elements_of_type(m) for m in KNOWN_MEDIA_TYPES ], []) ] def file_name(self): return self.id_string + ".xml" def get_survey_elements_of_type(self, element_type): return [ e for e in self.get_survey_elements() if e.type == element_type ] def _set_uuid_in_xml(self, file_name=None): if not file_name: file_name = self.file_name() file_name, file_ext = os.path.splitext(file_name) doc = clean_and_parse_xml(self.xml) model_nodes = doc.getElementsByTagName("model") if len(model_nodes) != 1: raise Exception(u"xml contains multiple model nodes") model_node = model_nodes[0] instance_nodes = [ node for node in model_node.childNodes if node.nodeType == Node.ELEMENT_NODE and node.tagName.lower() == "instance" and not node.hasAttribute("id") ] if len(instance_nodes) != 1: raise Exception("Multiple instance nodes without the id " "attribute, can't tell which is the main one") instance_node = instance_nodes[0] # get the first child whose id attribute matches our id_string survey_nodes = [ node for node in instance_node.childNodes if node.nodeType == Node.ELEMENT_NODE and (node.tagName == file_name or node.attributes.get('id')) ] if len(survey_nodes) != 1: raise Exception( "Multiple survey nodes with the id '%s'" % self.id_string) survey_node = survey_nodes[0] formhub_nodes = [ n for n in survey_node.childNodes if n.nodeType == Node.ELEMENT_NODE and n.tagName == "formhub" ] if len(formhub_nodes) > 1: raise Exception( "Multiple formhub nodes within main instance node") elif len(formhub_nodes) == 1: formhub_node = formhub_nodes[0] else: formhub_node = survey_node.insertBefore( doc.createElement("formhub"), survey_node.firstChild) uuid_nodes = [ node for node in formhub_node.childNodes if node.nodeType == Node.ELEMENT_NODE and node.tagName == "uuid" ] if len(uuid_nodes) == 0: formhub_node.appendChild(doc.createElement("uuid")) if len(formhub_nodes) == 0: # append the calculate bind node calculate_node = doc.createElement("bind") calculate_node.setAttribute( "nodeset", "/%s/formhub/uuid" % survey_node.tagName) calculate_node.setAttribute("type", "string") calculate_node.setAttribute("calculate", "'%s'" % self.uuid) model_node.appendChild(calculate_node) self.xml = doc.toprettyxml(indent=" ", encoding='utf-8') # hack # http://ronrothman.com/public/leftbraned/xml-dom-minidom-toprettyxml-\ # and-silly-whitespace/ text_re = re.compile('(>)\n\s*(\s[^<>\s].*?)\n\s*(\s</)', re.DOTALL) output_re = re.compile('\n.*(<output.*>)\n( )*') pretty_xml = text_re.sub(lambda m: ''.join(m.group(1, 2, 3)), self.xml.decode('utf-8')) inline_output = output_re.sub('\g<1>', pretty_xml) inline_output = re.compile('<label>\s*\n*\s*\n*\s*</label>').sub( '<label></label>', inline_output) self.xml = inline_output def _mark_start_time_boolean(self): starttime_substring = 'jr:preloadParams="start"' if self.xml.find(starttime_substring) != -1: self.has_start_time = True else: self.has_start_time = False def _id_string_already_exists_in_account(self, id_string): try: XForm.objects.get(id_string__iexact=id_string) except XForm.DoesNotExist: return False return True def get_unique_id_string(self, id_string, count=0): # used to generate a new id_string for new data_dictionary object if # id_string already existed if self._id_string_already_exists_in_account(id_string): if count != 0: if re.match(r'\w+_\d+$', id_string): a = id_string.split('_') id_string = "_".join(a[:-1]) count += 1 id_string = "{}_{}".format(id_string, count) return self.get_unique_id_string(id_string, count) return id_string def _set_title(self): xml = re.sub(r"\s+", " ", self.xml) matches = title_pattern.findall(xml) if len(matches) != 1: raise XLSFormError(("There should be a single title."), matches) if matches: title_xml = matches[0][:XFORM_TITLE_LENGTH] else: title_xml = self.title[:XFORM_TITLE_LENGTH] if self.title else '' if self.title and title_xml != self.title: title_xml = self.title[:XFORM_TITLE_LENGTH] if isinstance(self.xml, bytes): self.xml = self.xml.decode('utf-8') self.xml = title_pattern.sub(u"<h:title>%s</h:title>" % title_xml, self.xml) self._set_hash() if contains_xml_invalid_char(title_xml): raise XLSFormError( "Title shouldn't have any invalid xml " "characters ('>' '&' '<')" ) self.title = title_xml def get_hash(self): return u'md5:%s' % md5(self.xml.encode('utf8')).hexdigest() def get_random_hash(self): return u'md5:%s' % md5( ("%s-%s" % ( self.xml, random.randint(0, 25101991) )).encode('utf8') ).hexdigest() @property def random_hash(self): return self.get_random_hash() def _set_hash(self): self.hash = self.get_hash() def _set_id_string(self): matches = self.instance_id_regex.findall(self.xml) if len(matches) != 1: raise XLSFormError("There should be a single id string.") self.id_string = matches[0] def save(self, *args, **kwargs): update_fields = kwargs.get('update_fields') if update_fields: kwargs['update_fields'] = list( set(list(update_fields) + ['date_modified'])) if update_fields is None or 'title' in update_fields: self._set_title() if self.pk is None: self._set_hash() if update_fields is None or 'id_string' in update_fields: old_id_string = self.id_string self._set_id_string() if self.pk and old_id_string and old_id_string != self.id_string \ and self.num_of_submissions > 0: raise XLSFormError( "Your updated form's id_string '%(new_id)s' must match " "the existing forms' id_string '%(old_id)s'." % { 'new_id': self.id_string, 'old_id': old_id_string }) if getattr(settings, 'STRICT', True) and \ not re.search(r"^[\w-]+$", self.id_string): raise XLSFormError( 'In strict mode, the XForm ID must be a ' 'valid slug and contain no spaces.') if 'skip_xls_read' in kwargs: del kwargs['skip_xls_read'] super(XForm, self).save(*args, **kwargs) def get_survey(self): if not hasattr(self, "_survey"): try: builder = SurveyElementBuilder() self._survey = \ builder.create_survey_element_from_json(self.json) except ValueError: xml = bytes(bytearray(self.xml, encoding='utf-8')) self._survey = create_survey_element_from_xml(xml) return self._survey survey = property(get_survey) def get_survey_elements(self): return self.survey.iter_descendants() def geopoint_xpaths(self): survey_elements = self.get_survey_elements() return [ e.get_abbreviated_xpath() for e in survey_elements if e.bind.get(u'type') == u'geopoint' ] def __str__(self): return self.id_string def type_for_form(content_object, data_type): content_type = ContentType.objects.get_for_model(content_object) return MetaData.objects.filter(object_id=content_object.id, content_type=content_type, data_type=data_type) def is_valid_url(uri): try: URLValidator(uri) except ValidationError: return False return True def create_media(media): if is_valid_url(media.data_value): filename = media.data_value.split('/')[-1] data_file = NamedTemporaryFile() content_type = mimetypes.guess_type(filename) with closing(requests.get(media.data_value, stream=True)) as r: for chunk in r.iter_content(chunk_size=CHUNK_SIZE): if chunk: data_file.write(chunk) data_file.seek(os.SEEK_SET, os.SEEK_END) size = os.path.getsize(data_file.name) data_file.seek(os.SEEK_SET) media.data_value = filename media.data_file = InMemoryUploadedFile( data_file, 'data_file', filename, content_type, size, charset=None) return media return None def media_resources(media_list, download=False): data = [] for media in media_list: if media.data_file.name == '' and download: media = create_media(media) if media: data.append(media) else: data.append(media) return data def meta_data_upload_to(instance, filename): username = None if instance.content_object.user is None and \ instance.content_type.model == 'instance': username = instance.content_object.xform.user.username else: username = instance.content_object.user.username if instance.data_type == 'media': return os.path.join(username, 'formid-media', filename) return os.path.join(username, 'docs', filename) class MetaData(models.Model): data_type = models.CharField(max_length=255) data_value = models.CharField(max_length=255) data_file = models.FileField( upload_to=meta_data_upload_to, blank=True, null=True) data_file_type = models.CharField(max_length=255, blank=True, null=True) file_hash = models.CharField(max_length=50, blank=True, null=True) date_created = models.DateTimeField(null=True, auto_now_add=True) date_modified = models.DateTimeField(null=True, auto_now=True) deleted_at = models.DateTimeField(null=True, default=None) content_type = models.ForeignKey(ContentType, on_delete=models.CASCADE, default=get_default_content_type) object_id = models.PositiveIntegerField(null=True, blank=True) content_object = GenericForeignKey('content_type', 'object_id') objects = models.Manager() class Meta: unique_together = ('object_id', 'data_type', 'data_value', 'content_type') def __str__(self): return self.data_value def file(self, username=None): if hasattr(self, '_file'): return self._file url = requests.Request( 'GET', self.data_value, params={ 'username': username } ).prepare().url self._file = MetaData.get_file(url) return self._file @staticmethod def media_upload(content_object, data_file=None, download=False): data_type = 'media' if data_file: allowed_types = settings.XFORM_SUPPORTED_MEDIA_UPLOAD_TYPES data_content_type = data_file.content_type \ if data_file.content_type in allowed_types else \ mimetypes.guess_type(data_file.name)[0] if data_content_type in allowed_types: content_type = ContentType.objects.get_for_model( content_object) media, created = MetaData.objects.update_or_create( data_type=data_type, content_type=content_type, object_id=content_object.id, data_value=data_file.name, defaults={ 'data_file': data_file, 'data_file_type': data_content_type }) return media_resources( type_for_form(content_object, data_type), download) @staticmethod def get_md5(data_file): hash_md5 = md5() for chunk in iter(lambda: data_file.read(4096), b""): hash_md5.update(chunk) return 'md5:%s' % hash_md5.hexdigest() @staticmethod def get_file(url): data_file = None output = BytesIO() def getsize(f): f.seek(0) f.read() s = f.tell() f.seek(0) return s r = requests.get(url, allow_redirects=True) d = r.headers['content-disposition'] fname = re.findall("filename=\"(.+)\"", d)[0] content_type = r.headers.get('content-type') output.write(r.content) size = getsize(output) data_file = InMemoryUploadedFile( file=output, name=fname, field_name=None, content_type=content_type, charset='utf-8', size=size ) return data_file @staticmethod def add_url(content_object, url=None, download=False): data_type = 'url' try: data_file = MetaData.get_file(url) except Exception: return None allowed_types = settings.XFORM_SUPPORTED_MEDIA_UPLOAD_TYPES data_content_type = data_file.content_type \ if data_file.content_type in allowed_types else \ mimetypes.guess_type(data_file.name)[0] if data_content_type in allowed_types: content_type = ContentType.objects.get_for_model( content_object) media, created = MetaData.objects.update_or_create( data_type=data_type, content_type=content_type, object_id=content_object.id, data_value=url, defaults={ 'data_file': None, 'data_file_type': data_content_type }) return media_resources( type_for_form(content_object, data_type), download) def save(self, *args, **kwargs): self._set_hash() super(MetaData, self).save(*args, **kwargs) @property def hash(self): if self.file_hash is not None and self.file_hash != '': return self.file_hash else: return self._set_hash() def _set_hash(self): if not self.data_file: return None file_exists = self.data_file.storage.exists(self.data_file.name) if (file_exists and self.data_file.name != '') \ or (not file_exists and self.data_file): try: self.data_file.seek(os.SEEK_SET) except IOError: return '' else: self.file_hash = 'md5:%s' % md5( self.data_file.read()).hexdigest() return self.file_hash return '' class Instance(models.Model): json = JSONField(default=dict, null=False) xml = models.TextField() user = models.ForeignKey( settings.AUTH_USER_MODEL, related_name='instances', null=True, on_delete=models.CASCADE) xform = models.ForeignKey('xform.XForm', null=False, related_name='instances', on_delete=models.CASCADE) date_created = models.DateTimeField(auto_now_add=True) date_modified = models.DateTimeField(auto_now=True) last_edited = models.DateTimeField(null=True, default=None) status = models.CharField(max_length=20, default=u'submitted_via_web') uuid = models.CharField(max_length=249, default=u'', db_index=True) version = models.CharField(max_length=255, null=True) geom = models.GeometryCollectionField(null=True) media_all_received = models.NullBooleanField( "Received All Media Attachemts", null=True, default=True) total_media = models.PositiveIntegerField("Total Media Attachments", null=True, default=0) media_count = models.PositiveIntegerField("Received Media Attachments", null=True, default=0) checksum = models.CharField(max_length=64, null=True, blank=True, db_index=True) class Meta: unique_together = ('xform', 'uuid') def __str__(self): return "Status: %s" % self.status @property def point(self): gc = self.geom if gc and len(gc): return gc[0] def get_duration(self): data = self.get_dict() start_name = _get_tag_or_element_type_xpath(self.xform, START) end_name = _get_tag_or_element_type_xpath(self.xform, END) start_time, end_time = data.get(start_name), data.get(end_name) return calculate_duration(start_time, end_time) @property def num_of_media(self): if not hasattr(self, '_num_of_media'): self._num_of_media = len(self.get_expected_media()) return self._num_of_media @property def attachments_count(self): return len(set(self.attachments.filter( name__in=self.get_expected_media() ).values_list('name', flat=True))) def get_expected_media(self): if not hasattr(self, '_expected_media'): data = self.get_dict() media_list = [] if 'encryptedXmlFile' in data and self.xform.encrypted: media_list.append(data['encryptedXmlFile']) if 'media' in data: media_list.extend([i['media/file'] for i in data['media']]) else: media_xpaths = (self.xform.get_media_survey_xpaths() + self.xform.get_osm_survey_xpaths()) for media_xpath in media_xpaths: media_list.extend( get_values_matching_key(data, media_xpath)) self._expected_media = list(set(media_list)) return self._expected_media def numeric_converter(self, json_dict, numeric_fields=None): if numeric_fields is None: numeric_fields = get_numeric_fields(self.xform) for key, value in json_dict.items(): if isinstance(value, (str, bytes)) and key in numeric_fields: converted_value = numeric_checker(value) if converted_value: json_dict[key] = converted_value elif isinstance(value, dict): json_dict[key] = self.numeric_converter( value, numeric_fields) elif isinstance(value, list): for k, v in enumerate(value): if isinstance(v, (str, bytes)) and key in numeric_fields: converted_value = numeric_checker(v) if converted_value: json_dict[key] = converted_value elif isinstance(v, dict): value[k] = self.numeric_converter( v, numeric_fields) return json_dict def _set_geom(self): xform = self.xform geo_xpaths = xform.geopoint_xpaths() doc = self.get_dict() points = [] if geo_xpaths: for xpath in geo_xpaths: for gps in get_values_matching_key(doc, xpath): try: geometry = [float(s) for s in gps.split()] lat, lng = geometry[0:2] points.append(Point(lng, lat)) except ValueError: return if not xform.instances_with_geopoints and len(points): xform.instances_with_geopoints = True xform.save() self.geom = GeometryCollection(points) def _check_active(self, force): pass def _set_json(self): self.json = self.get_full_dict() def get_full_dict(self, load_existing=True): doc = self.json or {} if load_existing else {} doc = self.get_dict() if self.id: doc.update({ UUID: self.uuid, ID: self.id, ATTACHMENTS: _get_attachments_from_instance(self), STATUS: self.status, NOTES: [], VERSION: self.version, DURATION: self.get_duration(), XFORM_ID_STRING: self._parser.get_xform_id_string(), XFORM_ID: self.xform.pk, GEOLOCATION: [self.point.y, self.point.x] if self.point else [None, None], SUBMITTED_BY: self.user.username if self.user else None }) if not self.date_created: self.date_created = timezone.now() doc[SUBMISSION_TIME] = self.date_created.strftime( '%Y-%m-%dT%H:%M:%S') doc[TOTAL_MEDIA] = self.total_media doc[MEDIA_COUNT] = self.media_count doc[MEDIA_ALL_RECEIVED] = self.media_all_received edited = False if hasattr(self, 'last_edited'): edited = self.last_edited is not None doc[EDITED] = edited edited and doc.update({ LAST_EDITED: convert_to_serializable_date(self.last_edited) }) return doc def get_dict(self, force_new=False, flat=True): self._set_parser() instance_dict = self._parser.get_flat_dict_with_attributes() if flat \ else self._parser.to_dict() return self.numeric_converter(instance_dict) def _set_survey_type(self): self.survey_type = self.get_root_node_name() def _set_parser(self): if not hasattr(self, "_parser"): self._parser = XFormInstanceParser(self.xml, self.xform) def get_root_node_name(self): self._set_parser() return self._parser.get_root_node_name() def _set_uuid(self): if self.xml and not self.uuid: uuid = get_uuid_from_xml(self.xml) if uuid is not None: self.uuid = uuid set_uuid(self) def save(self, *args, **kwargs): force = kwargs.get('force') if force: del kwargs['force'] self._check_active(force) self._set_geom() self._set_json() self._set_survey_type() self._set_uuid() self.version = self.json.get(VERSION, self.xform.version) super(Instance, self).save(*args, **kwargs) class Attachment(models.Model): OSM = 'osm' instance = models.ForeignKey( Instance, related_name="attachments", on_delete=models.CASCADE) media_file = models.FileField( max_length=255, upload_to=upload_to) mimetype = models.CharField( max_length=100, null=False, blank=True, default='') extension = models.CharField( max_length=10, null=False, blank=False, default=u"non", db_index=True) date_created = models.DateTimeField(null=True, auto_now_add=True) date_modified = models.DateTimeField(null=True, auto_now=True) file_size = models.PositiveIntegerField(default=0) name = models.CharField(max_length=100, null=True, blank=True) class Meta: ordering = ("pk", ) def save(self, *args, **kwargs): if self.media_file and self.mimetype == '': mimetype, encoding = mimetypes.guess_type(self.media_file.name) if mimetype: self.mimetype = mimetype if self.media_file and len(self.media_file.name) > 255: raise ValueError( "Length of the media file should be less or equal to 255") try: f_size = self.media_file.size if f_size: self.file_size = f_size except (OSError, AttributeError): pass try: self.name = self.filename self.extension = self.name.rsplit('.', 1)[1] except Exception: pass super(Attachment, self).save(*args, **kwargs) @property def file_hash(self): if self.media_file.storage.exists(self.media_file.name): return u'%s' % md5(self.media_file.read()).hexdigest() return u'' @property def filename(self): if self.media_file: return os.path.basename(self.media_file.name) def is_newline_error(e): newline_error = u'new-line character seen in unquoted field - do you need'\ u' to open the file in universal-newline mode?' return newline_error == str(e) def process_xlsform(xls, default_name): file_object = None if xls.name.endswith('csv'): xls.seek(0) file_object = BytesIO() file_object.write(xls.read()) file_object.seek(0) xls.seek(0) try: return parse_file_to_json(xls.name, file_object=file_object or xls) except csv.Error as e: if is_newline_error(e): xls.seek(0) file_object = StringIO( u'\n'.join(xls.read().splitlines())) return parse_file_to_json( xls.name, default_name=default_name, file_object=file_object) raise e def get_columns_with_hxl(survey_elements): return survey_elements and { se.get('name'): val.get('hxl') for se in survey_elements for key, val in se.items() if key == 'instance' and val and 'hxl' in val } def check_version_set(survey): survey_json = json.loads(survey.to_json()) if not survey_json.get("version"): survey_json['version'] = \ timezone.now().strftime("%Y%m%d%H%M") builder = SurveyElementBuilder() survey = builder.create_survey_element_from_json( json.dumps(survey_json)) return survey class DataDictionary(XForm): def __init__(self, *args, **kwargs): self.instances_for_export = lambda d: d.instances.all() self.has_external_choices = False self._id_string_changed = False super(DataDictionary, self).__init__(*args, **kwargs) def __str__(self): return getattr(self, "id_string", "") def save(self, *args, **kwargs): skip_xls_read = kwargs.get('skip_xls_read') if self.xls and not skip_xls_read: default_name = None \ if not self.pk else self.survey.xml_instance().tagName survey_dict = process_xlsform(self.xls, default_name) if has_external_choices(survey_dict): self.has_external_choices = True survey = create_survey_element_from_dict(survey_dict) survey = check_version_set(survey) if get_columns_with_hxl(survey.get('children')): self.has_hxl_support = True if self.pk is None: new_id_string = self.get_unique_id_string( survey.get('id_string')) self._id_string_changed = \ new_id_string != survey.get('id_string') survey['id_string'] = new_id_string # For flow results packages use the user defined id/uuid elif self.id_string != survey.get('id_string'): raise XLSFormError( ("Your updated form's id_string '%(new_id)s' must match " "the existing forms' id_string '%(old_id)s'." % { 'new_id': survey.get('id_string'), 'old_id': self.id_string})) elif default_name and default_name != survey.get('name'): survey['name'] = default_name else: survey['id_string'] = self.id_string self.json = survey.to_json() self.xml = survey.to_xml() self.version = survey.get('version') self.last_updated_at = timezone.now() self.title = survey.get('title') self._mark_start_time_boolean() set_uuid(self) self._set_uuid_in_xml() self._set_hash() if 'skip_xls_read' in kwargs: del kwargs['skip_xls_read'] super(DataDictionary, self).save(*args, **kwargs) def file_name(self): return os.path.split(self.xls.name)[-1] def sheet_to_csv(xls_content, sheet_name): workbook = xlrd.open_workbook(file_contents=xls_content) sheet = workbook.sheet_by_name(sheet_name) if not sheet or sheet.nrows < 2: raise Exception("Sheet <'%(sheet_name)s'> has no data." % { 'sheet_name': sheet_name}) csv_file = BytesIO() writer = csv.writer(csv_file, encoding='utf-8', quoting=csv.QUOTE_ALL) mask = [v and len(v.strip()) > 0 for v in sheet.row_values(0)] header = [v for v, m in zip(sheet.row_values(0), mask) if m] writer.writerow(header) name_column = None try: name_column = header.index('name') except ValueError: pass integer_fields = False date_fields = False if name_column: name_column_values = sheet.col_values(name_column) for index in range(len(name_column_values)): if sheet.cell_type(index, name_column) == xlrd.XL_CELL_NUMBER: integer_fields = True elif sheet.cell_type(index, name_column) == xlrd.XL_CELL_DATE: date_fields = True for row in range(1, sheet.nrows): if integer_fields or date_fields: # convert integers to string/datetime if name has numbers/dates row_values = [] for index, val in enumerate(sheet.row_values(row)): if sheet.cell_type(row, index) == xlrd.XL_CELL_NUMBER: try: val = str( float(val) if ( float(val) > int(val) ) else int(val) ) except ValueError: pass elif sheet.cell_type(row, index) == xlrd.XL_CELL_DATE: val = xlrd.xldate_as_datetime( val, workbook.datemode).isoformat() row_values.append(val) writer.writerow([v for v, m in zip(row_values, mask) if m]) else: writer.writerow( [v for v, m in zip(sheet.row_values(row), mask) if m]) return csv_file def set_object_permissions(sender, instance=None, created=False, **kwargs): # seems the super is not called, have to get xform from here xform = XForm.objects.get(pk=instance.pk) if hasattr(instance, 'has_external_choices') \ and instance.has_external_choices: instance.xls.seek(0) f = sheet_to_csv(instance.xls.read(), 'external_choices') f.seek(0, os.SEEK_END) size = f.tell() f.seek(0) data_file = InMemoryUploadedFile( file=f, field_name='data_file', name='itemsets.csv', content_type='text/csv', size=size, charset=None ) MetaData.media_upload(xform, data_file) post_save.connect(set_object_permissions, sender=DataDictionary, dispatch_uid='xform_object_permissions')

true

1c459720c843885a8386143a876fd1904e17dd73

3,345

py

Python

leaderboard_service/leaderboard_service/settings.py

AVatch/leaderboard-service

9b70e24866fe862ba5d71dc3404e123303325431

[ "Apache-2.0" ]

1

2016-02-25T22:50:22.000Z

leaderboard_service/leaderboard_service/settings.py

AVatch/leaderboard-service

9b70e24866fe862ba5d71dc3404e123303325431

[ "Apache-2.0" ]

null

leaderboard_service/leaderboard_service/settings.py

AVatch/leaderboard-service

9b70e24866fe862ba5d71dc3404e123303325431

[ "Apache-2.0" ]

null

""" Django settings for leaderboard_service project. Generated by 'django-admin startproject' using Django 1.9.2. For more information on this file, see https://docs.djangoproject.com/en/1.9/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/1.9/ref/settings/ """ import os # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/1.9/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = 'y(9k(&i#f11*to()nc^qy9nnokkwg^d(7g1zk9^p8%4!@cz)td' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = [] # Application definition CORE_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', ] THIRD_PARTY_APPS = ['rest_framework', 'rest_framework.authtoken'] APPS = ['leaderboards'] INSTALLED_APPS = CORE_APPS + THIRD_PARTY_APPS + APPS MIDDLEWARE_CLASSES = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.auth.middleware.SessionAuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'leaderboard_service.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'leaderboard_service.wsgi.application' # Database # https://docs.djangoproject.com/en/1.9/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Password validation # https://docs.djangoproject.com/en/1.9/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/1.9/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/1.9/howto/static-files/ STATIC_URL = '/static/'

26.338583

91

0.704933

import os BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) SECRET_KEY = 'y(9k(&i#f11*to()nc^qy9nnokkwg^d(7g1zk9^p8%4!@cz)td' DEBUG = True ALLOWED_HOSTS = [] # Application definition CORE_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', ] THIRD_PARTY_APPS = ['rest_framework', 'rest_framework.authtoken'] APPS = ['leaderboards'] INSTALLED_APPS = CORE_APPS + THIRD_PARTY_APPS + APPS MIDDLEWARE_CLASSES = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.auth.middleware.SessionAuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'leaderboard_service.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'leaderboard_service.wsgi.application' # Database # https://docs.djangoproject.com/en/1.9/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Password validation # https://docs.djangoproject.com/en/1.9/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/1.9/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/1.9/howto/static-files/ STATIC_URL = '/static/'

true

1c459747e39517110330c01929492f60ac06c5aa

503

py

Python

vqseg/wordseg_algorithms.py

janinerugayan/VectorQuantizedCPC

b4e9fe6aeebca3b792ab604a770e8c3e289a46a1

[ "MIT" ]

null

vqseg/wordseg_algorithms.py

janinerugayan/VectorQuantizedCPC

b4e9fe6aeebca3b792ab604a770e8c3e289a46a1

[ "MIT" ]

null

vqseg/wordseg_algorithms.py

janinerugayan/VectorQuantizedCPC

b4e9fe6aeebca3b792ab604a770e8c3e289a46a1

[ "MIT" ]

null

""" Word segmentation algorithms. Author: Herman Kamper Contact: kamperh@gmail.com Date: 2020 """ from wordseg.algos import tp, puddle, dpseg, baseline, dibs, ag import wordseg.algos def ag(utterance_list, **kwargs): return list(wordseg.algos.ag.segment(utterance_list, **kwargs)) def tp(utterance_list, **kwargs): return list(wordseg.algos.tp.segment(utterance_list, **kwargs)) def dpseg(utterance_list, **kwargs): return list(wordseg.algos.dpseg.segment(utterance_list, **kwargs))

21.869565

70

0.745527

from wordseg.algos import tp, puddle, dpseg, baseline, dibs, ag import wordseg.algos def ag(utterance_list, **kwargs): return list(wordseg.algos.ag.segment(utterance_list, **kwargs)) def tp(utterance_list, **kwargs): return list(wordseg.algos.tp.segment(utterance_list, **kwargs)) def dpseg(utterance_list, **kwargs): return list(wordseg.algos.dpseg.segment(utterance_list, **kwargs))

true

1c45984c4c6ee38da52bda0420ddc998d5a7f5a2

2,024

py

Python

tests/test_git.py

igorbernstein2/synthtool

6b33cffb4301c3f05cc6976fff0022d98b47772f

[ "Apache-2.0" ]

null

tests/test_git.py

igorbernstein2/synthtool

6b33cffb4301c3f05cc6976fff0022d98b47772f

[ "Apache-2.0" ]

null

tests/test_git.py

igorbernstein2/synthtool

6b33cffb4301c3f05cc6976fff0022d98b47772f

[ "Apache-2.0" ]

null

# Copyright 2018 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from unittest import mock import pytest from synthtool.sources import git def test_make_repo_clone_url(monkeypatch): monkeypatch.setattr(git, "USE_SSH", True) assert ( git.make_repo_clone_url("theacodes/nox") == "git@github.com:theacodes/nox.git" ) def test_make_repo_clone_url_https(monkeypatch): monkeypatch.setattr(git, "USE_SSH", False) assert ( git.make_repo_clone_url("theacodes/nox") == "https://github.com/theacodes/nox.git" ) @pytest.mark.parametrize( ("input, expected"), [ ("git@github.com:theacodes/nox.git", {"owner": "theacodes", "name": "nox"}), ("https://github.com/theacodes/nox.git", {"owner": "theacodes", "name": "nox"}), ("theacodes/nox", {"owner": "theacodes", "name": "nox"}), ("theacodes/nox.git", {"owner": "theacodes", "name": "nox"}), ], ) def test_parse_repo_url(input, expected): assert git.parse_repo_url(input) == expected @mock.patch("subprocess.check_output", autospec=True) def test_get_latest_commit(check_call): check_call.return_value = b"abc123\ncommit\nmessage." sha, message = git.get_latest_commit() assert sha == "abc123" assert message == "commit\nmessage." def test_extract_commit_message_metadata(): message = """\ Hello, world! One: Hello! Two: 1234 """ metadata = git.extract_commit_message_metadata(message) assert metadata == {"One": "Hello!", "Two": "1234"}

28.914286

88

0.6917

from unittest import mock import pytest from synthtool.sources import git def test_make_repo_clone_url(monkeypatch): monkeypatch.setattr(git, "USE_SSH", True) assert ( git.make_repo_clone_url("theacodes/nox") == "git@github.com:theacodes/nox.git" ) def test_make_repo_clone_url_https(monkeypatch): monkeypatch.setattr(git, "USE_SSH", False) assert ( git.make_repo_clone_url("theacodes/nox") == "https://github.com/theacodes/nox.git" ) @pytest.mark.parametrize( ("input, expected"), [ ("git@github.com:theacodes/nox.git", {"owner": "theacodes", "name": "nox"}), ("https://github.com/theacodes/nox.git", {"owner": "theacodes", "name": "nox"}), ("theacodes/nox", {"owner": "theacodes", "name": "nox"}), ("theacodes/nox.git", {"owner": "theacodes", "name": "nox"}), ], ) def test_parse_repo_url(input, expected): assert git.parse_repo_url(input) == expected @mock.patch("subprocess.check_output", autospec=True) def test_get_latest_commit(check_call): check_call.return_value = b"abc123\ncommit\nmessage." sha, message = git.get_latest_commit() assert sha == "abc123" assert message == "commit\nmessage." def test_extract_commit_message_metadata(): message = """\ Hello, world! One: Hello! Two: 1234 """ metadata = git.extract_commit_message_metadata(message) assert metadata == {"One": "Hello!", "Two": "1234"}

true

1c45988afdd14740a571c6b781a72451a6d25636

3,162

py

Python

dispel4py/seismo/obspy_stream.py

AndreiFrunze/wrangler

076a07de00fc966dcf18ca6b6a6e804be5245ed9

[ "Apache-2.0" ]

2

2017-09-07T04:33:18.000Z

2019-01-07T13:32:15.000Z

dispel4py/seismo/obspy_stream.py

AndreiFrunze/wrangler

076a07de00fc966dcf18ca6b6a6e804be5245ed9

[ "Apache-2.0" ]

2

2016-10-06T13:07:05.000Z

2017-12-20T09:47:08.000Z

dispel4py/seismo/obspy_stream.py

AndreiFrunze/wrangler

076a07de00fc966dcf18ca6b6a6e804be5245ed9

[ "Apache-2.0" ]

5

2016-09-01T08:38:20.000Z

2018-08-28T12:08:39.000Z

from dispel4py.seismo.seismo import SeismoPE import traceback INPUT_NAME = 'input' OUTPUT_NAME = 'output' class ObspyStreamPE(SeismoPE): ''' A SeismoPE that calls a function to process an input stream. ''' def __init__(self): SeismoPE.__init__(self) def setCompute(self, compute_fn, params={}): ''' Define the compute function that this PE uses for processing input streams, and any input parameters for the function. The function must have at least one input, an obspy stream, and can accept more input parameters that must be provided before the PE is executed. ''' self.compute_fn = compute_fn, dict(params) def setInputTypes(self, types): self.inout_types = { OUTPUT_NAME : types[INPUT_NAME] } def getOutputTypes(self): # output = input return self.inout_types def compute(self): ''' Calls the processing function with the given parameters and one input stream. ''' try: try: func, params = self.compute_fn except TypeError: func = self.compute_fn params = {} output = func(self, self.st, **params) self.outputstreams.append(output) except: self.log(traceback.format_exc()) self.error+=traceback.format_exc() self.log("Failed to execute function '%s' with parameters %s" % (func.__name__, params)) from dispel4py.workflow_graph import WorkflowGraph def createProcessingComposite(chain, suffix='', controlParameters={}, provRecorder=None): ''' Creates a composite PE wrapping a pipeline that processes obspy streams. :param chain: list of functions that process obspy streams. The function takes one input parameter, stream, and returns an output stream. :param requestId: id of the request that the stream is associated with :param controlParameters: environment parameters for the processing elements :rtype: dictionary inputs and outputs of the composite PE that was created ''' prev = None first = None graph = WorkflowGraph() for fn_desc in chain: pe = ObspyStreamPE() try: fn = fn_desc[0] params = fn_desc[1] except TypeError: fn = fn_desc params = {} pe.compute_fn = fn pe.name = 'ObspyStreamPE_' + fn.__name__ + suffix pe.controlParameters = controlParameters pe.appParameters = dict(params) pe.setCompute(fn, params) # connect the metadata output to the provenance recorder PE if there is one if provRecorder: graph.connect(pe, 'metadata', provRecorder, 'metadata') if prev: graph.connect(prev, OUTPUT_NAME, pe, INPUT_NAME) else: first = pe prev = pe # Map inputs and outputs of the wrapper to the nodes in the subgraph graph.inputmappings = { 'input' : (first, INPUT_NAME) } graph.outputmappings = { 'output' : (prev, OUTPUT_NAME) } return graph

34.747253

141

0.624921

from dispel4py.seismo.seismo import SeismoPE import traceback INPUT_NAME = 'input' OUTPUT_NAME = 'output' class ObspyStreamPE(SeismoPE): def __init__(self): SeismoPE.__init__(self) def setCompute(self, compute_fn, params={}): self.compute_fn = compute_fn, dict(params) def setInputTypes(self, types): self.inout_types = { OUTPUT_NAME : types[INPUT_NAME] } def getOutputTypes(self): return self.inout_types def compute(self): try: try: func, params = self.compute_fn except TypeError: func = self.compute_fn params = {} output = func(self, self.st, **params) self.outputstreams.append(output) except: self.log(traceback.format_exc()) self.error+=traceback.format_exc() self.log("Failed to execute function '%s' with parameters %s" % (func.__name__, params)) from dispel4py.workflow_graph import WorkflowGraph def createProcessingComposite(chain, suffix='', controlParameters={}, provRecorder=None): prev = None first = None graph = WorkflowGraph() for fn_desc in chain: pe = ObspyStreamPE() try: fn = fn_desc[0] params = fn_desc[1] except TypeError: fn = fn_desc params = {} pe.compute_fn = fn pe.name = 'ObspyStreamPE_' + fn.__name__ + suffix pe.controlParameters = controlParameters pe.appParameters = dict(params) pe.setCompute(fn, params) if provRecorder: graph.connect(pe, 'metadata', provRecorder, 'metadata') if prev: graph.connect(prev, OUTPUT_NAME, pe, INPUT_NAME) else: first = pe prev = pe graph.inputmappings = { 'input' : (first, INPUT_NAME) } graph.outputmappings = { 'output' : (prev, OUTPUT_NAME) } return graph

true

1c4598e6f314bfee7c1a31680ad93afaa47b3067

4,132

py

Python

plugins/samanage/komand_samanage/actions/list_users/action.py

lukaszlaszuk/insightconnect-plugins

8c6ce323bfbb12c55f8b5a9c08975d25eb9f8892

[ "MIT" ]

46

2019-06-05T20:47:58.000Z

2022-03-29T10:18:01.000Z

plugins/samanage/komand_samanage/actions/list_users/action.py

lukaszlaszuk/insightconnect-plugins

8c6ce323bfbb12c55f8b5a9c08975d25eb9f8892

[ "MIT" ]

386

2019-06-07T20:20:39.000Z

2022-03-30T17:35:01.000Z

plugins/samanage/komand_samanage/actions/list_users/action.py

lukaszlaszuk/insightconnect-plugins

8c6ce323bfbb12c55f8b5a9c08975d25eb9f8892

[ "MIT" ]

43

2019-07-09T14:13:58.000Z

2022-03-28T12:04:46.000Z

import komand from .schema import ListUsersInput, ListUsersOutput # Custom imports below class ListUsers(komand.Action): def __init__(self): super(self.__class__, self).__init__( name="list_users", description="List all users", input=ListUsersInput(), output=ListUsersOutput(), ) def run(self, params={}): return {"users": self.connection.api.list_users()} def test(self): return { "users": [ { "id": 4245115, "name": "Anon", "disabled": False, "email": "123@service.hmail.eu", "created_at": "2018-11-22T08:13:00.000-05:00", "role": { "id": 461180, "name": "Requester", "description": "Requester role to view and submit service request.", "portal": True, "show_my_tasks": False, }, "salt": "04f20390ecf0c97571167c6c3350782663b6a7e0", "group_ids": [4492327], "custom_fields_values": [], "avatar": {"type": "initials", "color": "#dfcd00", "initials": "AN"}, "mfa_enabled": False, }, { "id": 4244043, "name": "Tom", "disabled": False, "title": "Panic", "email": "20180913dp@gmail.com", "created_at": "2018-11-21T12:28:31.000-05:00", "phone": "12345678", "mobile_phone": "87654321", "department": { "id": 133361, "name": "Information Technology", "default_assignee_id": 4485265, }, "role": { "id": 461179, "name": "Service Agent User", "description": "Almost like an administrator but no access to setup.", "portal": False, "show_my_tasks": False, }, "salt": "b3e360e65de5b592ce1ff92e1d90acedbaddbcf7", "group_ids": [4491226], "custom_fields_values": [], "avatar": {"type": "initials", "color": "#dfcd00", "initials": "TO"}, "mfa_enabled": False, "reports_to": { "id": 4485266, "name": "Helpdesk", "disabled": False, "is_user": False, "reports_to": {"id": -1, "href": "https://api.samanage.com/groups/-1.json"}, "avatar": {"type": "group", "color": "#0bc46f"}, }, "site": {"id": 96691, "name": "Headquarters", "location": "Main Office"}, }, { "id": 4238379, "name": "WW WW", "disabled": False, "email": "wwww@service.hmail.eu", "created_at": "2018-11-20T05:29:00.000-05:00", "last_login": "2018-11-21T17:20:46.000-05:00", "phone": "+37254312367", "role": { "id": 461178, "name": "Administrator", "description": "This is the all powerful administrator user!", "portal": False, "show_my_tasks": False, }, "salt": "7e2c35f51cc6ccdf727f7e48bc42403adbf6534d", "group_ids": [4485265, 4485266], "custom_fields_values": [], "avatar": {"type": "initials", "color": "#dfcd00", "initials": "WW"}, "mfa_enabled": False, }, ] }

41.32

100

0.393272

import komand from .schema import ListUsersInput, ListUsersOutput class ListUsers(komand.Action): def __init__(self): super(self.__class__, self).__init__( name="list_users", description="List all users", input=ListUsersInput(), output=ListUsersOutput(), ) def run(self, params={}): return {"users": self.connection.api.list_users()} def test(self): return { "users": [ { "id": 4245115, "name": "Anon", "disabled": False, "email": "123@service.hmail.eu", "created_at": "2018-11-22T08:13:00.000-05:00", "role": { "id": 461180, "name": "Requester", "description": "Requester role to view and submit service request.", "portal": True, "show_my_tasks": False, }, "salt": "04f20390ecf0c97571167c6c3350782663b6a7e0", "group_ids": [4492327], "custom_fields_values": [], "avatar": {"type": "initials", "color": "#dfcd00", "initials": "AN"}, "mfa_enabled": False, }, { "id": 4244043, "name": "Tom", "disabled": False, "title": "Panic", "email": "20180913dp@gmail.com", "created_at": "2018-11-21T12:28:31.000-05:00", "phone": "12345678", "mobile_phone": "87654321", "department": { "id": 133361, "name": "Information Technology", "default_assignee_id": 4485265, }, "role": { "id": 461179, "name": "Service Agent User", "description": "Almost like an administrator but no access to setup.", "portal": False, "show_my_tasks": False, }, "salt": "b3e360e65de5b592ce1ff92e1d90acedbaddbcf7", "group_ids": [4491226], "custom_fields_values": [], "avatar": {"type": "initials", "color": "#dfcd00", "initials": "TO"}, "mfa_enabled": False, "reports_to": { "id": 4485266, "name": "Helpdesk", "disabled": False, "is_user": False, "reports_to": {"id": -1, "href": "https://api.samanage.com/groups/-1.json"}, "avatar": {"type": "group", "color": "#0bc46f"}, }, "site": {"id": 96691, "name": "Headquarters", "location": "Main Office"}, }, { "id": 4238379, "name": "WW WW", "disabled": False, "email": "wwww@service.hmail.eu", "created_at": "2018-11-20T05:29:00.000-05:00", "last_login": "2018-11-21T17:20:46.000-05:00", "phone": "+37254312367", "role": { "id": 461178, "name": "Administrator", "description": "This is the all powerful administrator user!", "portal": False, "show_my_tasks": False, }, "salt": "7e2c35f51cc6ccdf727f7e48bc42403adbf6534d", "group_ids": [4485265, 4485266], "custom_fields_values": [], "avatar": {"type": "initials", "color": "#dfcd00", "initials": "WW"}, "mfa_enabled": False, }, ] }

true

1c4598f31962fb4914c01183dfd2b5367f20731a

136

py

Python

al_phonebook/types.py

vtrvtr/al_phonebook

7bcdb7fa0323c873c523036da99b4b1616c0e00e

[ "MIT" ]

null

al_phonebook/types.py

vtrvtr/al_phonebook

7bcdb7fa0323c873c523036da99b4b1616c0e00e

[ "MIT" ]

1

2022-01-17T14:45:50.000Z

2022-01-17T14:45:51.000Z

al_phonebook/types.py

vtrvtr/al_phonebook

7bcdb7fa0323c873c523036da99b4b1616c0e00e

[ "MIT" ]

null

from typing import Any, Union import os DictItem = dict[str, Any] OptionalDictItem = DictItem | None PathLike = Union[os.PathLike, str]

22.666667

34

0.764706

from typing import Any, Union import os DictItem = dict[str, Any] OptionalDictItem = DictItem | None PathLike = Union[os.PathLike, str]

true

1c459b1eb973ce00d988425faa2a536d4bd861cd

744

py

Python

dm_control/composer/constants.py

h8907283/dm_control

fe4449606742a7b8bec81930790b98244cddc538

[ "Apache-2.0" ]

2,863

2018-01-03T01:38:52.000Z

2022-03-30T09:49:50.000Z

dm_control/composer/constants.py

krakhit/dm_control

4e1a35595124742015ae0c7a829e099a5aa100f5

[ "Apache-2.0" ]

266

2018-01-03T16:00:04.000Z

2022-03-26T15:45:48.000Z

dm_control/composer/constants.py

krakhit/dm_control

4e1a35595124742015ae0c7a829e099a5aa100f5

[ "Apache-2.0" ]

580

2018-01-03T03:17:27.000Z

2022-03-31T19:29:32.000Z

# Copyright 2018 The dm_control Authors. # # 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. # ============================================================================ """Module defining constant values for Composer.""" SENSOR_SITES_GROUP = 4

37.2

78

0.681452

SENSOR_SITES_GROUP = 4

true

1c459b5a3be59498565c981523bb698670abd0ef

255

py

Python

manage.py

justsostephen/track

b1749f7db664d76fab0c501c23f0d0705cc95fce

[ "MIT" ]

null

manage.py

justsostephen/track

b1749f7db664d76fab0c501c23f0d0705cc95fce

[ "MIT" ]

null

manage.py

justsostephen/track

b1749f7db664d76fab0c501c23f0d0705cc95fce

[ "MIT" ]

null

#!/usr/bin/env python import os import sys if __name__ == "__main__": os.environ.setdefault("DJANGO_SETTINGS_MODULE", "stockcontrol.settings") from django.core.management import execute_from_command_line execute_from_command_line(sys.argv)

23.181818

76

0.776471

import os import sys if __name__ == "__main__": os.environ.setdefault("DJANGO_SETTINGS_MODULE", "stockcontrol.settings") from django.core.management import execute_from_command_line execute_from_command_line(sys.argv)

true

1c459b9e9ba258120e841df624eb7641c3121e90

4,297

py

Python

aiograph/utils/html.py

fakegit/aiograph

a00aacebb04c1e743055ba524b978a06027e31ed

[ "MIT" ]

45

2018-05-05T12:31:43.000Z

2022-03-23T11:20:03.000Z

aiographfix/utils/html.py

Yyonging/aiograph

78d291f9e1157720c949e336a9aa2711ad707285

[ "MIT" ]

6

2019-03-04T11:23:49.000Z

2022-03-30T11:25:46.000Z

aiographfix/utils/html.py

Yyonging/aiograph

78d291f9e1157720c949e336a9aa2711ad707285

[ "MIT" ]

16

2019-02-22T19:10:19.000Z

2021-09-15T22:12:55.000Z

from html import escape from html.entities import name2codepoint from html.parser import HTMLParser from typing import List, Union import attr from ..types import NodeElement ALLOWED_TAGS = [ 'a', 'aside', 'b', 'blockquote', 'br', 'code', 'em', 'figcaption', 'figure', 'h3', 'h4', 'hr', 'i', 'iframe', 'img', 'li', 'ol', 'p', 'pre', 's', 'strong', 'u', 'ul', 'video' ] VOID_ELEMENTS = { 'area', 'base', 'br', 'col', 'embed', 'hr', 'img', 'input', 'keygen', 'link', 'menuitem', 'meta', 'param', 'source', 'track', 'wbr' } ALLOWED_ATTRS = ['href', 'src'] def node_to_html(node: Union[str, NodeElement, list]) -> str: """ Convert Nodes to HTML :param node: :return: """ if isinstance(node, str): # Text return escape(node) elif isinstance(node, list): # List of nodes result = '' for child_node in node: result += node_to_html(child_node) return result elif not isinstance(node, NodeElement): raise TypeError(f"Node must be instance of str or NodeElement, not {type(node)}") # NodeElement # Open result = "<" + node.tag if node.attrs: result += ' ' + ' '.join(f"{k}=\"{v}\"" for k, v in node.attrs.items()) if node.tag in VOID_ELEMENTS: # Close void element result += '/>' else: result += '>' for child_node in node.children: # Container body result += node_to_html(child_node) result += '</' + node.tag + '>' # Close tag return result def html_to_nodes(html_content: str) -> List[Union[str, NodeElement]]: """ Convert HTML code to Nodes :param html_content: :return: """ parser = HtmlToNodesParser() parser.feed(html_content) return parser.get_nodes() def _node_converter_filter(attribute, value) -> bool: return bool(value) def nodes_to_json(nodes: List[Union[str, NodeElement]]) -> List[Union[str, dict]]: """ Convert Nodes to JSON :param nodes: :return: """ result = [] for node in nodes: if isinstance(node, str): result.append(node) elif isinstance(node, NodeElement): result.append(attr.asdict(node, filter=_node_converter_filter)) return result def html_to_json(content: str) -> List[Union[str, dict]]: """ Convert HTML to JSON :param content: :return: """ return nodes_to_json(html_to_nodes(content)) class HtmlToNodesParser(HTMLParser): def __init__(self): super(HtmlToNodesParser, self).__init__() self.current_nodes = [] self.parent_nodes = [] def error(self, message): raise ValueError(message) def add_str_node(self, s): if self.current_nodes and isinstance(self.current_nodes[-1], str): self.current_nodes[-1] += s else: self.current_nodes.append(s) def handle_starttag(self, tag, attrs_list): if tag not in ALLOWED_TAGS: self.error(f"{tag} tag is not allowed") node = NodeElement(tag=tag) if attrs_list: for attr, value in attrs_list: node.attrs[attr] = value self.current_nodes.append(node) if tag not in VOID_ELEMENTS: self.parent_nodes.append(self.current_nodes) self.current_nodes = node.children = [] def handle_endtag(self, tag): if tag in VOID_ELEMENTS: return self.current_nodes = self.parent_nodes.pop() last_node = self.current_nodes[-1] if last_node.tag != tag: self.error(f"\"{tag}\" tag closed instead of \"{last_node.tag}\"") if not last_node.children: last_node.children.clear() def handle_data(self, data): self.add_str_node(data) def handle_entityref(self, name): self.add_str_node(chr(name2codepoint[name])) def handle_charref(self, name): if name.startswith('x'): c = chr(int(name[1:], 16)) else: c = chr(int(name)) self.add_str_node(c) def get_nodes(self): if self.parent_nodes: not_closed_tag = self.parent_nodes[-1][-1].tag self.error(f"\"{not_closed_tag}\" tag is not closed") return self.current_nodes

25.577381

89

0.594601

from html import escape from html.entities import name2codepoint from html.parser import HTMLParser from typing import List, Union import attr from ..types import NodeElement ALLOWED_TAGS = [ 'a', 'aside', 'b', 'blockquote', 'br', 'code', 'em', 'figcaption', 'figure', 'h3', 'h4', 'hr', 'i', 'iframe', 'img', 'li', 'ol', 'p', 'pre', 's', 'strong', 'u', 'ul', 'video' ] VOID_ELEMENTS = { 'area', 'base', 'br', 'col', 'embed', 'hr', 'img', 'input', 'keygen', 'link', 'menuitem', 'meta', 'param', 'source', 'track', 'wbr' } ALLOWED_ATTRS = ['href', 'src'] def node_to_html(node: Union[str, NodeElement, list]) -> str: if isinstance(node, str): return escape(node) elif isinstance(node, list): result = '' for child_node in node: result += node_to_html(child_node) return result elif not isinstance(node, NodeElement): raise TypeError(f"Node must be instance of str or NodeElement, not {type(node)}") result = "<" + node.tag if node.attrs: result += ' ' + ' '.join(f"{k}=\"{v}\"" for k, v in node.attrs.items()) if node.tag in VOID_ELEMENTS: result += '/>' else: result += '>' for child_node in node.children: result += node_to_html(child_node) result += '</' + node.tag + '>' return result def html_to_nodes(html_content: str) -> List[Union[str, NodeElement]]: parser = HtmlToNodesParser() parser.feed(html_content) return parser.get_nodes() def _node_converter_filter(attribute, value) -> bool: return bool(value) def nodes_to_json(nodes: List[Union[str, NodeElement]]) -> List[Union[str, dict]]: result = [] for node in nodes: if isinstance(node, str): result.append(node) elif isinstance(node, NodeElement): result.append(attr.asdict(node, filter=_node_converter_filter)) return result def html_to_json(content: str) -> List[Union[str, dict]]: return nodes_to_json(html_to_nodes(content)) class HtmlToNodesParser(HTMLParser): def __init__(self): super(HtmlToNodesParser, self).__init__() self.current_nodes = [] self.parent_nodes = [] def error(self, message): raise ValueError(message) def add_str_node(self, s): if self.current_nodes and isinstance(self.current_nodes[-1], str): self.current_nodes[-1] += s else: self.current_nodes.append(s) def handle_starttag(self, tag, attrs_list): if tag not in ALLOWED_TAGS: self.error(f"{tag} tag is not allowed") node = NodeElement(tag=tag) if attrs_list: for attr, value in attrs_list: node.attrs[attr] = value self.current_nodes.append(node) if tag not in VOID_ELEMENTS: self.parent_nodes.append(self.current_nodes) self.current_nodes = node.children = [] def handle_endtag(self, tag): if tag in VOID_ELEMENTS: return self.current_nodes = self.parent_nodes.pop() last_node = self.current_nodes[-1] if last_node.tag != tag: self.error(f"\"{tag}\" tag closed instead of \"{last_node.tag}\"") if not last_node.children: last_node.children.clear() def handle_data(self, data): self.add_str_node(data) def handle_entityref(self, name): self.add_str_node(chr(name2codepoint[name])) def handle_charref(self, name): if name.startswith('x'): c = chr(int(name[1:], 16)) else: c = chr(int(name)) self.add_str_node(c) def get_nodes(self): if self.parent_nodes: not_closed_tag = self.parent_nodes[-1][-1].tag self.error(f"\"{not_closed_tag}\" tag is not closed") return self.current_nodes

true

1c459cb9695ce51149e5eae19d31908ca788d5d5

6,562

py

Python

seq2seq/tasks/decode_text.py

chunfengh/seq2seq

cc6e1a15f523c2ead809d48b1f6eebbeb94e3f0b

[ "Apache-2.0" ]

null

seq2seq/tasks/decode_text.py

chunfengh/seq2seq

cc6e1a15f523c2ead809d48b1f6eebbeb94e3f0b

[ "Apache-2.0" ]

null

seq2seq/tasks/decode_text.py

chunfengh/seq2seq

cc6e1a15f523c2ead809d48b1f6eebbeb94e3f0b

[ "Apache-2.0" ]

null

# Copyright 2017 Google Inc. # # 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. """ Task where both the input and output sequence are plain text. """ from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import functools from pydoc import locate import numpy as np import tensorflow as tf from tensorflow import gfile from seq2seq.tasks.inference_task import InferenceTask, unbatch_dict def _get_prediction_length(predictions_dict): """Returns the length of the prediction based on the index of the first SEQUENCE_END token. """ tokens_iter = enumerate(predictions_dict["predicted_tokens"]) return next(((i + 1) for i, _ in tokens_iter if _ == "SEQUENCE_END"), len(predictions_dict["predicted_tokens"])) def _get_unk_mapping(filename): """Reads a file that specifies a mapping from source to target tokens. The file must contain lines of the form <source>\t<target>" Args: filename: path to the mapping file Returns: A dictionary that maps from source -> target tokens. """ with gfile.GFile(filename, "r") as mapping_file: lines = mapping_file.readlines() mapping = dict([_.split("\t")[0:2] for _ in lines]) mapping = {k.strip(): v.strip() for k, v in mapping.items()} return mapping def _unk_replace(source_tokens, predicted_tokens, attention_scores, mapping=None): """Replaces UNK tokens with tokens from the source or a provided mapping based on the attention scores. Args: source_tokens: A numpy array of strings. predicted_tokens: A numpy array of strings. attention_scores: A numeric numpy array of shape `[prediction_length, source_length]` that contains the attention scores. mapping: If not provided, an UNK token is replaced with the source token that has the highest attention score. If provided the token is insead replaced with `mapping[chosen_source_token]`. Returns: A new `predicted_tokens` array. """ result = [] for token, scores in zip(predicted_tokens, attention_scores): if token == "UNK": max_score_index = np.argmax(scores) chosen_source_token = source_tokens[max_score_index] new_target = chosen_source_token if mapping is not None and chosen_source_token in mapping: new_target = mapping[chosen_source_token] result.append(new_target) else: result.append(token) return np.array(result) class DecodeText(InferenceTask): """Defines inference for tasks where both the input and output sequences are plain text. Params: delimiter: Character by which tokens are delimited. Defaults to space. unk_replace: If true, enable unknown token replacement based on attention scores. unk_mapping: If `unk_replace` is true, this can be the path to a file defining a dictionary to improve UNK token replacement. Refer to the documentation for more details. dump_attention_dir: Save attention scores and plots to this directory. dump_attention_no_plot: If true, only save attention scores, not attention plots. dump_beams: Write beam search debugging information to this file. """ def __init__(self, params): super(DecodeText, self).__init__(params) self._unk_mapping = None self._unk_replace_fn = None if self.params["unk_mapping"] is not None: self._unk_mapping = _get_unk_mapping(self.params["unk_mapping"]) if self.params["unk_replace"]: self._unk_replace_fn = functools.partial( _unk_replace, mapping=self._unk_mapping) self._postproc_fn = None if self.params["postproc_fn"]: self._postproc_fn = locate(self.params["postproc_fn"]) if self._postproc_fn is None: raise ValueError("postproc_fn not found: {}".format( self.params["postproc_fn"])) @staticmethod def default_params(): params = {} params.update({ "delimiter": " ", "postproc_fn": "", "unk_replace": False, "unk_mapping": None, }) return params def before_run(self, _run_context): fetches = {} fetches["predicted_tokens"] = self._predictions["predicted_tokens"] fetches["features.source_len"] = self._predictions["features.source_len"] fetches["features.source_tokens"] = self._predictions[ "features.source_tokens"] if "attention_scores" in self._predictions: fetches["attention_scores"] = self._predictions["attention_scores"] return tf.train.SessionRunArgs(fetches) def after_run(self, _run_context, run_values): fetches_batch = run_values.results print (fetches_batch) for fetches in unbatch_dict(fetches_batch): # Convert to unicode fetches["predicted_tokens"] = np.char.decode( fetches["predicted_tokens"].astype("S"), "utf-8") predicted_tokens = fetches["predicted_tokens"] # If we're using beam search we take the first beam if np.ndim(predicted_tokens) > 1: predicted_tokens = predicted_tokens[:, 0] fetches["features.source_tokens"] = np.char.decode( fetches["features.source_tokens"].astype("S"), "utf-8") source_tokens = fetches["features.source_tokens"] source_len = fetches["features.source_len"] if self._unk_replace_fn is not None: # We slice the attention scores so that we do not # accidentially replace UNK with a SEQUENCE_END token attention_scores = fetches["attention_scores"] attention_scores = attention_scores[:, :source_len - 1] predicted_tokens = self._unk_replace_fn( source_tokens=source_tokens, predicted_tokens=predicted_tokens, attention_scores=attention_scores) sent = self.params["delimiter"].join(predicted_tokens).split( "SEQUENCE_END")[0] # Apply postproc if self._postproc_fn: sent = self._postproc_fn(sent) sent = sent.strip() print(sent.encode('utf-8'))

34.536842

77

0.704358

from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import functools from pydoc import locate import numpy as np import tensorflow as tf from tensorflow import gfile from seq2seq.tasks.inference_task import InferenceTask, unbatch_dict def _get_prediction_length(predictions_dict): tokens_iter = enumerate(predictions_dict["predicted_tokens"]) return next(((i + 1) for i, _ in tokens_iter if _ == "SEQUENCE_END"), len(predictions_dict["predicted_tokens"])) def _get_unk_mapping(filename): with gfile.GFile(filename, "r") as mapping_file: lines = mapping_file.readlines() mapping = dict([_.split("\t")[0:2] for _ in lines]) mapping = {k.strip(): v.strip() for k, v in mapping.items()} return mapping def _unk_replace(source_tokens, predicted_tokens, attention_scores, mapping=None): result = [] for token, scores in zip(predicted_tokens, attention_scores): if token == "UNK": max_score_index = np.argmax(scores) chosen_source_token = source_tokens[max_score_index] new_target = chosen_source_token if mapping is not None and chosen_source_token in mapping: new_target = mapping[chosen_source_token] result.append(new_target) else: result.append(token) return np.array(result) class DecodeText(InferenceTask): def __init__(self, params): super(DecodeText, self).__init__(params) self._unk_mapping = None self._unk_replace_fn = None if self.params["unk_mapping"] is not None: self._unk_mapping = _get_unk_mapping(self.params["unk_mapping"]) if self.params["unk_replace"]: self._unk_replace_fn = functools.partial( _unk_replace, mapping=self._unk_mapping) self._postproc_fn = None if self.params["postproc_fn"]: self._postproc_fn = locate(self.params["postproc_fn"]) if self._postproc_fn is None: raise ValueError("postproc_fn not found: {}".format( self.params["postproc_fn"])) @staticmethod def default_params(): params = {} params.update({ "delimiter": " ", "postproc_fn": "", "unk_replace": False, "unk_mapping": None, }) return params def before_run(self, _run_context): fetches = {} fetches["predicted_tokens"] = self._predictions["predicted_tokens"] fetches["features.source_len"] = self._predictions["features.source_len"] fetches["features.source_tokens"] = self._predictions[ "features.source_tokens"] if "attention_scores" in self._predictions: fetches["attention_scores"] = self._predictions["attention_scores"] return tf.train.SessionRunArgs(fetches) def after_run(self, _run_context, run_values): fetches_batch = run_values.results print (fetches_batch) for fetches in unbatch_dict(fetches_batch): fetches["predicted_tokens"] = np.char.decode( fetches["predicted_tokens"].astype("S"), "utf-8") predicted_tokens = fetches["predicted_tokens"] if np.ndim(predicted_tokens) > 1: predicted_tokens = predicted_tokens[:, 0] fetches["features.source_tokens"] = np.char.decode( fetches["features.source_tokens"].astype("S"), "utf-8") source_tokens = fetches["features.source_tokens"] source_len = fetches["features.source_len"] if self._unk_replace_fn is not None: # We slice the attention scores so that we do not # accidentially replace UNK with a SEQUENCE_END token attention_scores = fetches["attention_scores"] attention_scores = attention_scores[:, :source_len - 1] predicted_tokens = self._unk_replace_fn( source_tokens=source_tokens, predicted_tokens=predicted_tokens, attention_scores=attention_scores) sent = self.params["delimiter"].join(predicted_tokens).split( "SEQUENCE_END")[0] # Apply postproc if self._postproc_fn: sent = self._postproc_fn(sent) sent = sent.strip() print(sent.encode('utf-8'))

true

1c459cbafa7959829a0eb6b44a0612c737b7663e

782

py

Python

jorldy/config/m_dqn/cartpole.py

Kyushik/JORLDY

6a24a2195e5e87ade157ee53f631af2221f0a188

[ "Apache-2.0" ]

300

2021-11-03T07:06:34.000Z

2022-03-24T02:23:56.000Z

jorldy/config/m_dqn/cartpole.py

Kyushik/JORLDY

6a24a2195e5e87ade157ee53f631af2221f0a188

[ "Apache-2.0" ]

37

2021-11-04T04:31:07.000Z

2022-03-30T01:40:49.000Z

jorldy/config/m_dqn/cartpole.py

Kyushik/JORLDY

6a24a2195e5e87ade157ee53f631af2221f0a188

[ "Apache-2.0" ]

45

2021-11-03T08:05:56.000Z

2022-03-24T08:35:05.000Z

### Munchausen DQN CartPole Config ### env = { "name": "cartpole", "action_type": "discrete", "render": False, } agent = { "name": "m_dqn", "network": "discrete_q_network", "gamma": 0.99, "epsilon_init": 1.0, "epsilon_min": 0.01, "explore_ratio": 0.2, "buffer_size": 50000, "batch_size": 32, "start_train_step": 2000, "target_update_period": 500, "lr_decay": True, # M-DQN Parameters "alpha": 0.9, "tau": 0.03, "l_0": -1, } optim = { "name": "adam", "lr": 0.0001, } train = { "training": True, "load_path": None, "run_step": 100000, "print_period": 1000, "save_period": 10000, "eval_iteration": 10, # distributed setting "update_period": 32, "num_workers": 8, }

18.186047

38

0.553708

False, } agent = { "name": "m_dqn", "network": "discrete_q_network", "gamma": 0.99, "epsilon_init": 1.0, "epsilon_min": 0.01, "explore_ratio": 0.2, "buffer_size": 50000, "batch_size": 32, "start_train_step": 2000, "target_update_period": 500, "lr_decay": True, "alpha": 0.9, "tau": 0.03, "l_0": -1, } optim = { "name": "adam", "lr": 0.0001, } train = { "training": True, "load_path": None, "run_step": 100000, "print_period": 1000, "save_period": 10000, "eval_iteration": 10, "update_period": 32, "num_workers": 8, }

true

1c459d4fd01576a1d2a19cab06b15dcefae8bd24

336

py

Python

setup.py

ippee/py_init

0d997ec5ddaee95ef71562f14542e74f40e88646

[ "CC0-1.0" ]

null

setup.py

ippee/py_init

0d997ec5ddaee95ef71562f14542e74f40e88646

[ "CC0-1.0" ]

null

setup.py

ippee/py_init

0d997ec5ddaee95ef71562f14542e74f40e88646

[ "CC0-1.0" ]

null

# coding: UTF-8 from setuptools import setup install_requires = [] packages = [] setup( name='', version='0.1.0', license='', description='', author='you', author_email='', url='', packages=packages, install_requires=install_requires, setup_requires=['pytest-runner'], tests_require=['pytest', "pytest-cov"] )

15.272727

40

0.660714

from setuptools import setup install_requires = [] packages = [] setup( name='', version='0.1.0', license='', description='', author='you', author_email='', url='', packages=packages, install_requires=install_requires, setup_requires=['pytest-runner'], tests_require=['pytest', "pytest-cov"] )

true

1c459d5ed4db13f7e8ef93008315c97790ecb9b7

5,618

py

Python

commitizen/commands/init.py

christian-hawk/commitizen

5c0dd546866f2bd2ab6b4ecd27035441b7b4692b

[ "MIT" ]

null

commitizen/commands/init.py

christian-hawk/commitizen

5c0dd546866f2bd2ab6b4ecd27035441b7b4692b

[ "MIT" ]

null

commitizen/commands/init.py

christian-hawk/commitizen

5c0dd546866f2bd2ab6b4ecd27035441b7b4692b

[ "MIT" ]

null

import os import questionary import yaml from packaging.version import Version from commitizen import cmd, factory, out from commitizen.__version__ import __version__ from commitizen.config import BaseConfig, TomlConfig from commitizen.cz import registry from commitizen.defaults import config_files from commitizen.exceptions import NoAnswersError from commitizen.git import get_latest_tag_name, get_tag_names class Init: def __init__(self, config: BaseConfig, *args): self.config: BaseConfig = config self.cz = factory.commiter_factory(self.config) def __call__(self): values_to_add = {} # No config for commitizen exist if not self.config.path: config_path = self._ask_config_path() if "toml" in config_path: self.config = TomlConfig(data="", path=config_path) self.config.init_empty_config_content() values_to_add["name"] = self._ask_name() tag = self._ask_tag() values_to_add["version"] = Version(tag).public values_to_add["tag_format"] = self._ask_tag_format(tag) self._update_config_file(values_to_add) if questionary.confirm("Do you want to install pre-commit hook?").ask(): self._install_pre_commit_hook() out.write("You can bump the version and create changelog running:\n") out.info("cz bump --changelog") out.success("The configuration are all set.") else: out.line(f"Config file {self.config.path} already exists") def _ask_config_path(self) -> str: name = questionary.select( "Please choose a supported config file: (default: pyproject.toml)", choices=config_files, default="pyproject.toml", style=self.cz.style, ).ask() return name def _ask_name(self) -> str: name = questionary.select( "Please choose a cz (commit rule): (default: cz_conventional_commits)", choices=list(registry.keys()), default="cz_conventional_commits", style=self.cz.style, ).ask() return name def _ask_tag(self) -> str: latest_tag = get_latest_tag_name() if not latest_tag: out.error("No Existing Tag. Set tag to v0.0.1") return "0.0.1" is_correct_tag = questionary.confirm( f"Is {latest_tag} the latest tag?", style=self.cz.style, default=False ).ask() if not is_correct_tag: tags = get_tag_names() if not tags: out.error("No Existing Tag. Set tag to v0.0.1") return "0.0.1" latest_tag = questionary.select( "Please choose the latest tag: ", choices=get_tag_names(), style=self.cz.style, ).ask() if not latest_tag: raise NoAnswersError("Tag is required!") return latest_tag def _ask_tag_format(self, latest_tag) -> str: is_correct_format = False if latest_tag.startswith("v"): tag_format = r"v$version" is_correct_format = questionary.confirm( f'Is "{tag_format}" the correct tag format?', style=self.cz.style ).ask() if not is_correct_format: tag_format = questionary.text( 'Please enter the correct version format: (default: "$version")', style=self.cz.style, ).ask() if not tag_format: tag_format = "$version" return tag_format def _install_pre_commit_hook(self): pre_commit_config_filename = ".pre-commit-config.yaml" cz_hook_config = { "repo": "https://github.com/commitizen-tools/commitizen", "rev": f"v{__version__}", "hooks": [{"id": "commitizen", "stages": ["commit-msg"]}], } config_data = {} if not os.path.isfile(pre_commit_config_filename): # .pre-commit-config does not exist config_data["repos"] = [cz_hook_config] else: # breakpoint() with open(pre_commit_config_filename) as config_file: yaml_data = yaml.safe_load(config_file) if yaml_data: config_data = yaml_data if "repos" in config_data: for pre_commit_hook in config_data["repos"]: if "commitizen" in pre_commit_hook["repo"]: out.write("commitizen already in pre-commit config") break else: config_data["repos"].append(cz_hook_config) else: # .pre-commit-config exists but there's no "repos" key config_data["repos"] = [cz_hook_config] with open(pre_commit_config_filename, "w") as config_file: yaml.safe_dump(config_data, stream=config_file) c = cmd.run("pre-commit install --hook-type commit-msg") if c.return_code == 127: out.error( "pre-commit is not installed in current environement.\n" "Run 'pre-commit install --hook-type commit-msg' again after it's installed" ) elif c.return_code != 0: out.error(c.err) else: out.write("commitizen pre-commit hook is now installed in your '.git'\n") def _update_config_file(self, values): for key, value in values.items(): self.config.set_key(key, value)

36.245161

92

0.58455

import os import questionary import yaml from packaging.version import Version from commitizen import cmd, factory, out from commitizen.__version__ import __version__ from commitizen.config import BaseConfig, TomlConfig from commitizen.cz import registry from commitizen.defaults import config_files from commitizen.exceptions import NoAnswersError from commitizen.git import get_latest_tag_name, get_tag_names class Init: def __init__(self, config: BaseConfig, *args): self.config: BaseConfig = config self.cz = factory.commiter_factory(self.config) def __call__(self): values_to_add = {} if not self.config.path: config_path = self._ask_config_path() if "toml" in config_path: self.config = TomlConfig(data="", path=config_path) self.config.init_empty_config_content() values_to_add["name"] = self._ask_name() tag = self._ask_tag() values_to_add["version"] = Version(tag).public values_to_add["tag_format"] = self._ask_tag_format(tag) self._update_config_file(values_to_add) if questionary.confirm("Do you want to install pre-commit hook?").ask(): self._install_pre_commit_hook() out.write("You can bump the version and create changelog running:\n") out.info("cz bump --changelog") out.success("The configuration are all set.") else: out.line(f"Config file {self.config.path} already exists") def _ask_config_path(self) -> str: name = questionary.select( "Please choose a supported config file: (default: pyproject.toml)", choices=config_files, default="pyproject.toml", style=self.cz.style, ).ask() return name def _ask_name(self) -> str: name = questionary.select( "Please choose a cz (commit rule): (default: cz_conventional_commits)", choices=list(registry.keys()), default="cz_conventional_commits", style=self.cz.style, ).ask() return name def _ask_tag(self) -> str: latest_tag = get_latest_tag_name() if not latest_tag: out.error("No Existing Tag. Set tag to v0.0.1") return "0.0.1" is_correct_tag = questionary.confirm( f"Is {latest_tag} the latest tag?", style=self.cz.style, default=False ).ask() if not is_correct_tag: tags = get_tag_names() if not tags: out.error("No Existing Tag. Set tag to v0.0.1") return "0.0.1" latest_tag = questionary.select( "Please choose the latest tag: ", choices=get_tag_names(), style=self.cz.style, ).ask() if not latest_tag: raise NoAnswersError("Tag is required!") return latest_tag def _ask_tag_format(self, latest_tag) -> str: is_correct_format = False if latest_tag.startswith("v"): tag_format = r"v$version" is_correct_format = questionary.confirm( f'Is "{tag_format}" the correct tag format?', style=self.cz.style ).ask() if not is_correct_format: tag_format = questionary.text( 'Please enter the correct version format: (default: "$version")', style=self.cz.style, ).ask() if not tag_format: tag_format = "$version" return tag_format def _install_pre_commit_hook(self): pre_commit_config_filename = ".pre-commit-config.yaml" cz_hook_config = { "repo": "https://github.com/commitizen-tools/commitizen", "rev": f"v{__version__}", "hooks": [{"id": "commitizen", "stages": ["commit-msg"]}], } config_data = {} if not os.path.isfile(pre_commit_config_filename): config_data["repos"] = [cz_hook_config] else: with open(pre_commit_config_filename) as config_file: yaml_data = yaml.safe_load(config_file) if yaml_data: config_data = yaml_data if "repos" in config_data: for pre_commit_hook in config_data["repos"]: if "commitizen" in pre_commit_hook["repo"]: out.write("commitizen already in pre-commit config") break else: config_data["repos"].append(cz_hook_config) else: config_data["repos"] = [cz_hook_config] with open(pre_commit_config_filename, "w") as config_file: yaml.safe_dump(config_data, stream=config_file) c = cmd.run("pre-commit install --hook-type commit-msg") if c.return_code == 127: out.error( "pre-commit is not installed in current environement.\n" "Run 'pre-commit install --hook-type commit-msg' again after it's installed" ) elif c.return_code != 0: out.error(c.err) else: out.write("commitizen pre-commit hook is now installed in your '.git'\n") def _update_config_file(self, values): for key, value in values.items(): self.config.set_key(key, value)

true

1c459db6c393559c2cd965467577c6bdcb250d28

1,090

py

Python

hpc-historias-clinicas/fojas_quirurgicas/migrations/0005_auto_20150505_0101.py

btenaglia/hpc-historias-clinicas

649d8660381381b1c591667760c122d73071d5ec

[ "BSD-3-Clause" ]

null

hpc-historias-clinicas/fojas_quirurgicas/migrations/0005_auto_20150505_0101.py

btenaglia/hpc-historias-clinicas

649d8660381381b1c591667760c122d73071d5ec

[ "BSD-3-Clause" ]

null

hpc-historias-clinicas/fojas_quirurgicas/migrations/0005_auto_20150505_0101.py

btenaglia/hpc-historias-clinicas

649d8660381381b1c591667760c122d73071d5ec

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations import datetime class Migration(migrations.Migration): dependencies = [ ('fojas_quirurgicas', '0004_auto_20150504_2120'), ] operations = [ migrations.AlterField( model_name='fojasquirurgicas', name='fecha', field=models.DateField(default=datetime.datetime(2015, 5, 5, 1, 1, 1, 702694)), preserve_default=True, ), migrations.AlterField( model_name='fojasquirurgicas', name='hora_comienzo', field=models.TimeField(default=datetime.datetime(2015, 5, 5, 1, 1, 1, 702739), verbose_name='Hora / Comienzo Operac\xf3n'), preserve_default=True, ), migrations.AlterField( model_name='fojasquirurgicas', name='hora_fin', field=models.TimeField(default=datetime.datetime(2015, 5, 5, 1, 1, 1, 702778), verbose_name='Hora / Termin\xf3 Operac\xf3n'), preserve_default=True, ), ]

32.058824

137

0.612844

from __future__ import unicode_literals from django.db import models, migrations import datetime class Migration(migrations.Migration): dependencies = [ ('fojas_quirurgicas', '0004_auto_20150504_2120'), ] operations = [ migrations.AlterField( model_name='fojasquirurgicas', name='fecha', field=models.DateField(default=datetime.datetime(2015, 5, 5, 1, 1, 1, 702694)), preserve_default=True, ), migrations.AlterField( model_name='fojasquirurgicas', name='hora_comienzo', field=models.TimeField(default=datetime.datetime(2015, 5, 5, 1, 1, 1, 702739), verbose_name='Hora / Comienzo Operac\xf3n'), preserve_default=True, ), migrations.AlterField( model_name='fojasquirurgicas', name='hora_fin', field=models.TimeField(default=datetime.datetime(2015, 5, 5, 1, 1, 1, 702778), verbose_name='Hora / Termin\xf3 Operac\xf3n'), preserve_default=True, ), ]

true

1c459dbc87ad166cc650a1298f694761c0c2d4ae

14,998

py

Python

utils.py

RachithP/rpg_public_dronet

244b44c6d321e77cfe326071f8413ea1f7e438cb

[ "MIT" ]

null

utils.py

RachithP/rpg_public_dronet

244b44c6d321e77cfe326071f8413ea1f7e438cb

[ "MIT" ]

null

utils.py

RachithP/rpg_public_dronet

244b44c6d321e77cfe326071f8413ea1f7e438cb

[ "MIT" ]

1

2019-12-10T02:48:20.000Z

import re import os import numpy as np import tensorflow as tf import json import time from keras import backend as K from keras.preprocessing.image import Iterator from keras.preprocessing.image import ImageDataGenerator from keras.utils.generic_utils import Progbar from keras.models import model_from_json import img_utils class DroneDataGenerator(ImageDataGenerator): """ Generate minibatches of images and labels with real-time augmentation. The only function that changes w.r.t. parent class is the flow that generates data. This function needed in fact adaptation for different directory structure and labels. All the remaining functions remain unchanged. For an example usage, see the evaluate.py script """ def flow_from_directory(self, directory, target_size=(224,224), crop_size=(250,250), color_mode='grayscale', batch_size=32, shuffle=True, seed=None, follow_links=False): return DroneDirectoryIterator( directory, self, target_size=target_size, crop_size=crop_size, color_mode=color_mode, batch_size=batch_size, shuffle=shuffle, seed=seed, follow_links=follow_links) class DroneDirectoryIterator(Iterator): """ Class for managing data loading.of images and labels We assume that the folder structure is: root_folder/ folder_1/ images/ sync_steering.txt or labels.txt folder_2/ images/ sync_steering.txt or labels.txt . . folder_n/ images/ sync_steering.txt or labels.txt # Arguments directory: Path to the root directory to read data from. image_data_generator: Image Generator. target_size: tuple of integers, dimensions to resize input images to. crop_size: tuple of integers, dimensions to crop input images. color_mode: One of `"rgb"`, `"grayscale"`. Color mode to read images. batch_size: The desired batch size shuffle: Whether to shuffle data or not seed : numpy seed to shuffle data follow_links: Bool, whether to follow symbolic links or not # TODO: Add functionality to save images to have a look at the augmentation """ def __init__(self, directory, image_data_generator, target_size=(224,224), crop_size = (250,250), color_mode='grayscale', batch_size=32, shuffle=True, seed=None, follow_links=False): self.directory = directory self.image_data_generator = image_data_generator self.target_size = tuple(target_size) self.crop_size = tuple(crop_size) self.follow_links = follow_links if color_mode not in {'rgb', 'grayscale'}: raise ValueError('Invalid color mode:', color_mode, '; expected "rgb" or "grayscale".') self.color_mode = color_mode if self.color_mode == 'rgb': self.image_shape = self.crop_size + (3,) else: self.image_shape = self.crop_size + (1,) # First count how many experiments are out there self.samples = 0 experiments = [] for subdir in sorted(os.listdir(directory)): if os.path.isdir(os.path.join(directory, subdir)): experiments.append(subdir) self.num_experiments = len(experiments) self.formats = {'png', 'jpg'} # Idea = associate each filename with a corresponding steering or label self.filenames = [] self.ground_truth = [] # Determine the type of experiment (steering or collision) to compute # the loss self.exp_type = [] for subdir in experiments: subpath = os.path.join(directory, subdir) self._decode_experiment_dir(subpath) # Conversion of list into array self.ground_truth = np.array(self.ground_truth, dtype = K.floatx()) assert self.samples > 0, "Did not find any data" print('Found {} images belonging to {} experiments.'.format( self.samples, self.num_experiments)) super(DroneDirectoryIterator, self).__init__(self.samples, batch_size, shuffle, seed) def _recursive_list(self, subpath): return sorted(os.walk(subpath, followlinks=self.follow_links), key=lambda tpl: tpl[0]) def _decode_experiment_dir(self, dir_subpath): # Load steerings or labels in the experiment dir steerings_filename = os.path.join(dir_subpath, "sync_steering.txt") labels_filename = os.path.join(dir_subpath, "labels.txt") # Try to load steerings first. Make sure that the steering angle or the # label file is in the first column. Note also that the first line are # comments so it should be skipped. try: ground_truth = np.loadtxt(steerings_filename, usecols=0, delimiter=',', skiprows=1) exp_type = 1 except OSError as e: # Try load collision labels if there are no steerings try: ground_truth = np.loadtxt(labels_filename, usecols=0) exp_type = 0 except OSError as e: print("Neither steerings nor labels found in dir {}".format( dir_subpath)) raise IOError # Now fetch all images in the image subdir image_dir_path = os.path.join(dir_subpath, "images") for root, _, files in self._recursive_list(image_dir_path): sorted_files = sorted(files, key = lambda fname: int(re.search(r'\d+',fname).group())) for frame_number, fname in enumerate(sorted_files): is_valid = False for extension in self.formats: if fname.lower().endswith('.' + extension): is_valid = True break if is_valid: absolute_path = os.path.join(root, fname) self.filenames.append(os.path.relpath(absolute_path, self.directory)) self.ground_truth.append(ground_truth[frame_number]) self.exp_type.append(exp_type) self.samples += 1 def next(self): with self.lock: index_array = next(self.index_generator) # The transformation of images is not under thread lock # so it can be done in parallel return self._get_batches_of_transformed_samples(index_array) def _get_batches_of_transformed_samples(self, index_array) : """ Public function to fetch next batch. # Returns The next batch of images and labels. """ current_batch_size = index_array.shape[0] # Image transformation is not under thread lock, so it can be done in # parallel batch_x = np.zeros((current_batch_size,) + self.image_shape, dtype=K.floatx()) batch_steer = np.zeros((current_batch_size, 2,), dtype=K.floatx()) batch_coll = np.zeros((current_batch_size, 2,), dtype=K.floatx()) grayscale = self.color_mode == 'grayscale' # Build batch of image data for i, j in enumerate(index_array): fname = self.filenames[j] x = img_utils.load_img(os.path.join(self.directory, fname), grayscale=grayscale, crop_size=self.crop_size, target_size=self.target_size) x = self.image_data_generator.random_transform(x) x = self.image_data_generator.standardize(x) batch_x[i] = x # Build batch of steering and collision data if self.exp_type[index_array[i]] == 1: # Steering experiment (t=1) batch_steer[i,0] =1.0 batch_steer[i,1] = self.ground_truth[index_array[i]] batch_coll[i] = np.array([1.0, 0.0]) else: # Collision experiment (t=0) batch_steer[i] = np.array([0.0, 0.0]) batch_coll[i,0] = 0.0 batch_coll[i,1] = self.ground_truth[index_array[i]] batch_y = [batch_steer, batch_coll] return batch_x, batch_y def compute_predictions_and_gt(model, generator, steps, max_q_size=10, pickle_safe=False, verbose=0): """ Generate predictions and associated ground truth for the input samples from a data generator. The generator should return the same kind of data as accepted by `predict_on_batch`. Function adapted from keras `predict_generator`. # Arguments generator: Generator yielding batches of input samples. steps: Total number of steps (batches of samples) to yield from `generator` before stopping. max_q_size: Maximum size for the generator queue. pickle_safe: If `True`, use process based threading. Note that because this implementation relies on multiprocessing, you should not pass non picklable arguments to the generator as they can't be passed easily to children processes. verbose: verbosity mode, 0 or 1. # Returns Numpy array(s) of predictions and associated ground truth. # Raises ValueError: In case the generator yields data in an invalid format. """ steps_done = 0 all_outs = [] all_labels = [] all_ts = [] if verbose == 1: progbar = Progbar(target=steps) while steps_done < steps: generator_output = next(generator) if isinstance(generator_output, tuple): if len(generator_output) == 2: x, gt_lab = generator_output elif len(generator_output) == 3: x, gt_lab, _ = generator_output else: raise ValueError('output of generator should be ' 'a tuple `(x, y, sample_weight)` ' 'or `(x, y)`. Found: ' + str(generator_output)) else: raise ValueError('Output not valid for current evaluation') start_time = time.time() outs = model.predict_on_batch(x) time_diff = time.time() - start_time print("\n Time Diff: ", time_diff) print("Batch Size: ", len(x)) print("FPS: ", len(x)/time_diff) if not isinstance(outs, list): outs = [outs] if not isinstance(gt_lab, list): gt_lab = [gt_lab] if not all_outs: for out in outs: # Len of this list is related to the number of # outputs per model(1 in our case) all_outs.append([]) if not all_labels: # Len of list related to the number of gt_commands # per model (1 in our case ) for lab in gt_lab: all_labels.append([]) all_ts.append([]) for i, out in enumerate(outs): all_outs[i].append(out) for i, lab in enumerate(gt_lab): all_labels[i].append(lab[:,1]) all_ts[i].append(lab[:,0]) steps_done += 1 if verbose == 1: progbar.update(steps_done) if steps_done == 1: return [out for out in all_outs], [lab for lab in all_labels], np.concatenate(all_ts[0]) else: return np.squeeze(np.array([np.concatenate(out) for out in all_outs])).T, \ np.array([np.concatenate(lab) for lab in all_labels]).T, \ np.concatenate(all_ts[0]) def hard_mining_mse(k): """ Compute MSE for steering evaluation and hard-mining for the current batch. # Arguments k: number of samples for hard-mining. # Returns custom_mse: average MSE for the current batch. """ def custom_mse(y_true, y_pred): # Parameter t indicates the type of experiment t = y_true[:,0] # Number of steering samples samples_steer = tf.cast(tf.equal(t,1), tf.int32) n_samples_steer = tf.reduce_sum(samples_steer) if n_samples_steer == 0: return 0.0 else: # Predicted and real steerings pred_steer = tf.squeeze(y_pred, squeeze_dims=-1) true_steer = y_true[:,1] # Steering loss l_steer = tf.multiply(t, K.square(pred_steer - true_steer)) # Hard mining k_min = tf.minimum(k, n_samples_steer) _, indices = tf.nn.top_k(l_steer, k=k_min) max_l_steer = tf.gather(l_steer, indices) hard_l_steer = tf.divide(tf.reduce_sum(max_l_steer), tf.cast(k,tf.float32)) return hard_l_steer return custom_mse def hard_mining_entropy(k): """ Compute binary cross-entropy for collision evaluation and hard-mining. # Arguments k: Number of samples for hard-mining. # Returns custom_bin_crossentropy: average binary cross-entropy for the current batch. """ def custom_bin_crossentropy(y_true, y_pred): # Parameter t indicates the type of experiment t = y_true[:,0] # Number of collision samples samples_coll = tf.cast(tf.equal(t,0), tf.int32) n_samples_coll = tf.reduce_sum(samples_coll) if n_samples_coll == 0: return 0.0 else: # Predicted and real labels pred_coll = tf.squeeze(y_pred, squeeze_dims=-1) true_coll = y_true[:,1] # Collision loss l_coll = tf.multiply((1-t), K.binary_crossentropy(true_coll, pred_coll)) # Hard mining k_min = tf.minimum(k, n_samples_coll) _, indices = tf.nn.top_k(l_coll, k=k_min) max_l_coll = tf.gather(l_coll, indices) hard_l_coll = tf.divide(tf.reduce_sum(max_l_coll), tf.cast(k, tf.float32)) return hard_l_coll return custom_bin_crossentropy def modelToJson(model, json_model_path): """ Serialize model into json. """ model_json = model.to_json() with open(json_model_path,"w") as f: f.write(model_json) def jsonToModel(json_model_path): """ Serialize json into model. """ with open(json_model_path, 'r') as json_file: loaded_model_json = json_file.read() model = model_from_json(loaded_model_json) return model def write_to_file(dictionary, fname): """ Writes everything is in a dictionary in json model. """ with open(fname, "w") as f: json.dump(dictionary,f) print("Written file {}".format(fname))

35.206573

96

0.595146

import re import os import numpy as np import tensorflow as tf import json import time from keras import backend as K from keras.preprocessing.image import Iterator from keras.preprocessing.image import ImageDataGenerator from keras.utils.generic_utils import Progbar from keras.models import model_from_json import img_utils class DroneDataGenerator(ImageDataGenerator): def flow_from_directory(self, directory, target_size=(224,224), crop_size=(250,250), color_mode='grayscale', batch_size=32, shuffle=True, seed=None, follow_links=False): return DroneDirectoryIterator( directory, self, target_size=target_size, crop_size=crop_size, color_mode=color_mode, batch_size=batch_size, shuffle=shuffle, seed=seed, follow_links=follow_links) class DroneDirectoryIterator(Iterator): def __init__(self, directory, image_data_generator, target_size=(224,224), crop_size = (250,250), color_mode='grayscale', batch_size=32, shuffle=True, seed=None, follow_links=False): self.directory = directory self.image_data_generator = image_data_generator self.target_size = tuple(target_size) self.crop_size = tuple(crop_size) self.follow_links = follow_links if color_mode not in {'rgb', 'grayscale'}: raise ValueError('Invalid color mode:', color_mode, '; expected "rgb" or "grayscale".') self.color_mode = color_mode if self.color_mode == 'rgb': self.image_shape = self.crop_size + (3,) else: self.image_shape = self.crop_size + (1,) self.samples = 0 experiments = [] for subdir in sorted(os.listdir(directory)): if os.path.isdir(os.path.join(directory, subdir)): experiments.append(subdir) self.num_experiments = len(experiments) self.formats = {'png', 'jpg'} self.filenames = [] self.ground_truth = [] self.exp_type = [] for subdir in experiments: subpath = os.path.join(directory, subdir) self._decode_experiment_dir(subpath) self.ground_truth = np.array(self.ground_truth, dtype = K.floatx()) assert self.samples > 0, "Did not find any data" print('Found {} images belonging to {} experiments.'.format( self.samples, self.num_experiments)) super(DroneDirectoryIterator, self).__init__(self.samples, batch_size, shuffle, seed) def _recursive_list(self, subpath): return sorted(os.walk(subpath, followlinks=self.follow_links), key=lambda tpl: tpl[0]) def _decode_experiment_dir(self, dir_subpath): steerings_filename = os.path.join(dir_subpath, "sync_steering.txt") labels_filename = os.path.join(dir_subpath, "labels.txt") try: ground_truth = np.loadtxt(steerings_filename, usecols=0, delimiter=',', skiprows=1) exp_type = 1 except OSError as e: try: ground_truth = np.loadtxt(labels_filename, usecols=0) exp_type = 0 except OSError as e: print("Neither steerings nor labels found in dir {}".format( dir_subpath)) raise IOError image_dir_path = os.path.join(dir_subpath, "images") for root, _, files in self._recursive_list(image_dir_path): sorted_files = sorted(files, key = lambda fname: int(re.search(r'\d+',fname).group())) for frame_number, fname in enumerate(sorted_files): is_valid = False for extension in self.formats: if fname.lower().endswith('.' + extension): is_valid = True break if is_valid: absolute_path = os.path.join(root, fname) self.filenames.append(os.path.relpath(absolute_path, self.directory)) self.ground_truth.append(ground_truth[frame_number]) self.exp_type.append(exp_type) self.samples += 1 def next(self): with self.lock: index_array = next(self.index_generator) return self._get_batches_of_transformed_samples(index_array) def _get_batches_of_transformed_samples(self, index_array) : current_batch_size = index_array.shape[0] batch_x = np.zeros((current_batch_size,) + self.image_shape, dtype=K.floatx()) batch_steer = np.zeros((current_batch_size, 2,), dtype=K.floatx()) batch_coll = np.zeros((current_batch_size, 2,), dtype=K.floatx()) grayscale = self.color_mode == 'grayscale' for i, j in enumerate(index_array): fname = self.filenames[j] x = img_utils.load_img(os.path.join(self.directory, fname), grayscale=grayscale, crop_size=self.crop_size, target_size=self.target_size) x = self.image_data_generator.random_transform(x) x = self.image_data_generator.standardize(x) batch_x[i] = x if self.exp_type[index_array[i]] == 1: batch_steer[i,0] =1.0 batch_steer[i,1] = self.ground_truth[index_array[i]] batch_coll[i] = np.array([1.0, 0.0]) else: batch_steer[i] = np.array([0.0, 0.0]) batch_coll[i,0] = 0.0 batch_coll[i,1] = self.ground_truth[index_array[i]] batch_y = [batch_steer, batch_coll] return batch_x, batch_y def compute_predictions_and_gt(model, generator, steps, max_q_size=10, pickle_safe=False, verbose=0): steps_done = 0 all_outs = [] all_labels = [] all_ts = [] if verbose == 1: progbar = Progbar(target=steps) while steps_done < steps: generator_output = next(generator) if isinstance(generator_output, tuple): if len(generator_output) == 2: x, gt_lab = generator_output elif len(generator_output) == 3: x, gt_lab, _ = generator_output else: raise ValueError('output of generator should be ' 'a tuple `(x, y, sample_weight)` ' 'or `(x, y)`. Found: ' + str(generator_output)) else: raise ValueError('Output not valid for current evaluation') start_time = time.time() outs = model.predict_on_batch(x) time_diff = time.time() - start_time print("\n Time Diff: ", time_diff) print("Batch Size: ", len(x)) print("FPS: ", len(x)/time_diff) if not isinstance(outs, list): outs = [outs] if not isinstance(gt_lab, list): gt_lab = [gt_lab] if not all_outs: for out in outs: all_outs.append([]) if not all_labels: for lab in gt_lab: all_labels.append([]) all_ts.append([]) for i, out in enumerate(outs): all_outs[i].append(out) for i, lab in enumerate(gt_lab): all_labels[i].append(lab[:,1]) all_ts[i].append(lab[:,0]) steps_done += 1 if verbose == 1: progbar.update(steps_done) if steps_done == 1: return [out for out in all_outs], [lab for lab in all_labels], np.concatenate(all_ts[0]) else: return np.squeeze(np.array([np.concatenate(out) for out in all_outs])).T, \ np.array([np.concatenate(lab) for lab in all_labels]).T, \ np.concatenate(all_ts[0]) def hard_mining_mse(k): def custom_mse(y_true, y_pred): t = y_true[:,0] samples_steer = tf.cast(tf.equal(t,1), tf.int32) n_samples_steer = tf.reduce_sum(samples_steer) if n_samples_steer == 0: return 0.0 else: pred_steer = tf.squeeze(y_pred, squeeze_dims=-1) true_steer = y_true[:,1] l_steer = tf.multiply(t, K.square(pred_steer - true_steer)) k_min = tf.minimum(k, n_samples_steer) _, indices = tf.nn.top_k(l_steer, k=k_min) max_l_steer = tf.gather(l_steer, indices) hard_l_steer = tf.divide(tf.reduce_sum(max_l_steer), tf.cast(k,tf.float32)) return hard_l_steer return custom_mse def hard_mining_entropy(k): def custom_bin_crossentropy(y_true, y_pred): t = y_true[:,0] samples_coll = tf.cast(tf.equal(t,0), tf.int32) n_samples_coll = tf.reduce_sum(samples_coll) if n_samples_coll == 0: return 0.0 else: pred_coll = tf.squeeze(y_pred, squeeze_dims=-1) true_coll = y_true[:,1] l_coll = tf.multiply((1-t), K.binary_crossentropy(true_coll, pred_coll)) k_min = tf.minimum(k, n_samples_coll) _, indices = tf.nn.top_k(l_coll, k=k_min) max_l_coll = tf.gather(l_coll, indices) hard_l_coll = tf.divide(tf.reduce_sum(max_l_coll), tf.cast(k, tf.float32)) return hard_l_coll return custom_bin_crossentropy def modelToJson(model, json_model_path): model_json = model.to_json() with open(json_model_path,"w") as f: f.write(model_json) def jsonToModel(json_model_path): with open(json_model_path, 'r') as json_file: loaded_model_json = json_file.read() model = model_from_json(loaded_model_json) return model def write_to_file(dictionary, fname): with open(fname, "w") as f: json.dump(dictionary,f) print("Written file {}".format(fname))

true

1c459f2b6ff309defaa99622a9e67444b25d1a67

309

py

Python

testing_8709/main.py

akvrdata/testing_8709

b9987a6a14d582a062f08d9de13f9b46f38989b1

[ "MIT" ]

null

testing_8709/main.py

akvrdata/testing_8709

b9987a6a14d582a062f08d9de13f9b46f38989b1

[ "MIT" ]

null

testing_8709/main.py

akvrdata/testing_8709

b9987a6a14d582a062f08d9de13f9b46f38989b1

[ "MIT" ]

null

import sys import click @click.command() @click.option('--count',default=1,help='Number of prints required') @click.option('--name',help='name to print') def hello(count,name): '''Click Cli testing''' for x in range(count): click.echo('Hello %s' %name) if __name__ == '__main__': hello()

23.769231

67

0.653722

import sys import click @click.command() @click.option('--count',default=1,help='Number of prints required') @click.option('--name',help='name to print') def hello(count,name): for x in range(count): click.echo('Hello %s' %name) if __name__ == '__main__': hello()

true

1c459f2e63f5d6cbc44f6b3304bb888e1f9f90a0

3,711

py

Python

bauh/api/http.py

Flash1232/bauh

6f65556c05ae272c1dbbd557c7f80a606658eb56

[ "Zlib" ]

507

2019-08-12T16:15:55.000Z

2022-03-28T15:49:39.000Z

bauh/api/http.py

Flash1232/bauh

6f65556c05ae272c1dbbd557c7f80a606658eb56

[ "Zlib" ]

176

2019-08-14T02:35:21.000Z

2022-03-31T21:43:56.000Z

bauh/api/http.py

Flash1232/bauh

6f65556c05ae272c1dbbd557c7f80a606658eb56

[ "Zlib" ]

57

2019-09-02T04:09:22.000Z

2022-03-21T21:37:16.000Z

import logging import time import traceback from typing import Optional import requests import yaml from bauh.commons import system class HttpClient: def __init__(self, logger: logging.Logger, max_attempts: int = 2, timeout: int = 30, sleep: float = 0.5): self.max_attempts = max_attempts self.session = requests.Session() self.timeout = timeout self.sleep = sleep self.logger = logger def get(self, url: str, params: dict = None, headers: dict = None, allow_redirects: bool = True, ignore_ssl: bool = False, single_call: bool = False, session: bool = True) -> Optional[requests.Response]: cur_attempts = 1 while cur_attempts <= self.max_attempts: cur_attempts += 1 try: args = {'timeout': self.timeout, 'allow_redirects': allow_redirects} if params: args['params'] = params if headers: args['headers'] = headers if ignore_ssl: args['verify'] = False if session: res = self.session.get(url, **args) else: res = requests.get(url, **args) if res.status_code == 200: return res if single_call: return res if self.sleep > 0: time.sleep(self.sleep) except Exception as e: if isinstance(e, requests.exceptions.ConnectionError): self.logger.error('Internet seems to be off') raise self.logger.error("Could not retrieve data from '{}'".format(url)) traceback.print_exc() continue self.logger.warning("Could not retrieve data from '{}'".format(url)) def get_json(self, url: str, params: dict = None, headers: dict = None, allow_redirects: bool = True, session: bool = True): res = self.get(url, params=params, headers=headers, allow_redirects=allow_redirects, session=session) return res.json() if res else None def get_yaml(self, url: str, params: dict = None, headers: dict = None, allow_redirects: bool = True, session: bool = True): res = self.get(url, params=params, headers=headers, allow_redirects=allow_redirects, session=session) return yaml.safe_load(res.text) if res else None def get_content_length_in_bytes(self, url: str, session: bool = True) -> Optional[int]: params = {'url': url, 'allow_redirects': True, 'stream': True} try: if session: res = self.session.get(**params) else: res = requests.get(**params) except requests.exceptions.ConnectionError: self.logger.info("Internet seems to be off. Could not reach '{}'".format(url)) return if res.status_code == 200: size = res.headers.get('Content-Length') if size: try: return int(size) except: pass def get_content_length(self, url: str, session: bool = True) -> Optional[str]: size = self.get_content_length_in_bytes(url, session) if size: return system.get_human_size_str(size) def exists(self, url: str, session: bool = True, timeout: int = 5) -> bool: params = {'url': url, 'allow_redirects': True, 'verify': False, 'timeout': timeout} if session: res = self.session.head(**params) else: res = self.session.get(**params) return res.status_code in (200, 403)

35.009434

207

0.565346

import logging import time import traceback from typing import Optional import requests import yaml from bauh.commons import system class HttpClient: def __init__(self, logger: logging.Logger, max_attempts: int = 2, timeout: int = 30, sleep: float = 0.5): self.max_attempts = max_attempts self.session = requests.Session() self.timeout = timeout self.sleep = sleep self.logger = logger def get(self, url: str, params: dict = None, headers: dict = None, allow_redirects: bool = True, ignore_ssl: bool = False, single_call: bool = False, session: bool = True) -> Optional[requests.Response]: cur_attempts = 1 while cur_attempts <= self.max_attempts: cur_attempts += 1 try: args = {'timeout': self.timeout, 'allow_redirects': allow_redirects} if params: args['params'] = params if headers: args['headers'] = headers if ignore_ssl: args['verify'] = False if session: res = self.session.get(url, **args) else: res = requests.get(url, **args) if res.status_code == 200: return res if single_call: return res if self.sleep > 0: time.sleep(self.sleep) except Exception as e: if isinstance(e, requests.exceptions.ConnectionError): self.logger.error('Internet seems to be off') raise self.logger.error("Could not retrieve data from '{}'".format(url)) traceback.print_exc() continue self.logger.warning("Could not retrieve data from '{}'".format(url)) def get_json(self, url: str, params: dict = None, headers: dict = None, allow_redirects: bool = True, session: bool = True): res = self.get(url, params=params, headers=headers, allow_redirects=allow_redirects, session=session) return res.json() if res else None def get_yaml(self, url: str, params: dict = None, headers: dict = None, allow_redirects: bool = True, session: bool = True): res = self.get(url, params=params, headers=headers, allow_redirects=allow_redirects, session=session) return yaml.safe_load(res.text) if res else None def get_content_length_in_bytes(self, url: str, session: bool = True) -> Optional[int]: params = {'url': url, 'allow_redirects': True, 'stream': True} try: if session: res = self.session.get(**params) else: res = requests.get(**params) except requests.exceptions.ConnectionError: self.logger.info("Internet seems to be off. Could not reach '{}'".format(url)) return if res.status_code == 200: size = res.headers.get('Content-Length') if size: try: return int(size) except: pass def get_content_length(self, url: str, session: bool = True) -> Optional[str]: size = self.get_content_length_in_bytes(url, session) if size: return system.get_human_size_str(size) def exists(self, url: str, session: bool = True, timeout: int = 5) -> bool: params = {'url': url, 'allow_redirects': True, 'verify': False, 'timeout': timeout} if session: res = self.session.head(**params) else: res = self.session.get(**params) return res.status_code in (200, 403)

true

1c459fbfb4d5f376b961ba213a2581525628f906

398

py

Python

accounts/migrations/0002_account_points.py

ebar0n/palermo-coin

63dc14fce31fbeae50ec7ebf5ea97efbb1ec18fd

[ "MIT" ]

null

accounts/migrations/0002_account_points.py

ebar0n/palermo-coin

63dc14fce31fbeae50ec7ebf5ea97efbb1ec18fd

[ "MIT" ]

15

2019-05-13T23:40:06.000Z

2022-03-11T23:39:57.000Z

accounts/migrations/0002_account_points.py

ebar0n/leviatan-backend

63dc14fce31fbeae50ec7ebf5ea97efbb1ec18fd

[ "MIT" ]

null

# Generated by Django 2.1.7 on 2019-03-07 07:57 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('accounts', '0001_initial'), ] operations = [ migrations.AddField( model_name='account', name='points', field=models.PositiveIntegerField(default=0, editable=False), ), ]

20.947368

73

0.603015

from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('accounts', '0001_initial'), ] operations = [ migrations.AddField( model_name='account', name='points', field=models.PositiveIntegerField(default=0, editable=False), ), ]

true

1c45a0ca7dda5396a87bdbca7a0a71105cce95b6

1,359

py

Python

python2/timeout.py

SLongofono/Python-Misc

c6c2735f65b7f06e31996140c2921315b1a6cf9e

[ "MIT" ]

2

2017-07-24T17:46:13.000Z

2017-12-09T16:00:40.000Z

python2/timeout.py

SLongofono/Python-Misc

c6c2735f65b7f06e31996140c2921315b1a6cf9e

[ "MIT" ]

null

python2/timeout.py

SLongofono/Python-Misc

c6c2735f65b7f06e31996140c2921315b1a6cf9e

[ "MIT" ]

1

2018-09-18T15:18:47.000Z

def timed_func(f, args=(), kwargs=None, timeout=30, default=None, errormsg="Timeout error"): # Since kwargs are mutable, assume they don't exist via optional arguments. If they do in fact exist, # they will exist in this context and be assigned. Otherwise, set to an empty dict and proceed. kwargs = kwargs or {} import signal class TimeoutError(Exception): pass def timeout_handler(signum, frame): raise TimeoutError # Register a signal to our handler signal.signal(signal.SIGALRM, timeout_handler) # Trigger an alarm after timeout seconds signal.alarm(timeout) # Try a function call: # If it returns normally before the timeout, pass along the value # Otherwise, print the specific error and return the default value try: result = f(*args, **kwargs) except TimeoutError: result = default print(errormsg) finally: signal.alarm(0) return result # Silly function that never returns def forever(): import time while True: time.sleep(1) # Function that may or may not complete depending on the timeout def andever(a,b): result = a while True: result += b #if result > 200000000: if result > 100000000: return result # Test print(timed_func(forever, timeout=2, default="no response", errormsg="failed to update")) print(timed_func(andever, (1,2), timeout=5, default=-1, errormsg="computation timeout"))

28.3125

103

0.734364

def timed_func(f, args=(), kwargs=None, timeout=30, default=None, errormsg="Timeout error"): # they will exist in this context and be assigned. Otherwise, set to an empty dict and proceed. kwargs = kwargs or {} import signal class TimeoutError(Exception): pass def timeout_handler(signum, frame): raise TimeoutError # Register a signal to our handler signal.signal(signal.SIGALRM, timeout_handler) # Trigger an alarm after timeout seconds signal.alarm(timeout) # Try a function call: # If it returns normally before the timeout, pass along the value # Otherwise, print the specific error and return the default value try: result = f(*args, **kwargs) except TimeoutError: result = default print(errormsg) finally: signal.alarm(0) return result # Silly function that never returns def forever(): import time while True: time.sleep(1) # Function that may or may not complete depending on the timeout def andever(a,b): result = a while True: result += b #if result > 200000000: if result > 100000000: return result # Test print(timed_func(forever, timeout=2, default="no response", errormsg="failed to update")) print(timed_func(andever, (1,2), timeout=5, default=-1, errormsg="computation timeout"))

true

1c45a0f0a16e4c957d53072ae53309de03cc22ef

6,090

py

Python

docs/conf.py

open-datastudio/datastudio

5055579adf969ad6d7491454b30ab2fedbaaa067

[ "MIT" ]

10

2020-06-23T13:45:44.000Z

2021-11-04T13:31:43.000Z

docs/conf.py

open-datastudio/datastudio

5055579adf969ad6d7491454b30ab2fedbaaa067

[ "MIT" ]

1

2020-06-23T23:15:10.000Z

2020-08-11T04:41:25.000Z

docs/conf.py

open-datastudio/datastudio

5055579adf969ad6d7491454b30ab2fedbaaa067

[ "MIT" ]

2

2021-11-20T21:24:36.000Z

2022-01-05T03:35:32.000Z

# -*- coding: utf-8 -*- # # Configuration file for the Sphinx documentation builder. # # This file does only contain a selection of the most common options. For a # full list see the documentation: # http://www.sphinx-doc.org/en/master/config # -- Path setup -------------------------------------------------------------- # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. # # import os # import sys # sys.path.insert(0, os.path.abspath('.')) # -- Project information ----------------------------------------------------- project = u'Open Data Studio' copyright = u'Open Data Studio Authors' author = u'Open Data Studio Authors' # The short X.Y version version = u'' # The full version, including alpha/beta/rc tags release = u'' # -- General configuration --------------------------------------------------- # If your documentation needs a minimal Sphinx version, state it here. # # needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. extensions = [ 'sphinx.ext.autosectionlabel', 'aafigure.sphinxext' ] # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # The suffix(es) of source filenames. # You can specify multiple suffix as a list of string: # # source_suffix = ['.rst', '.md'] source_suffix = '.rst' # The master toctree document. master_doc = 'index' # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. # # This is also used if you do content translation via gettext catalogs. # Usually you set "language" from the command line for these cases. language = None # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. # This pattern also affects html_static_path and html_extra_path. exclude_patterns = [u'_build', 'Thumbs.db', '.DS_Store'] # The name of the Pygments (syntax highlighting) style to use. pygments_style = None # -- Options for HTML output ------------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. # html_theme = 'sphinx_rtd_theme' # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. # # html_theme_options = {} # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] # Custom sidebar templates, must be a dictionary that maps document names # to template names. # # The default sidebars (for documents that don't match any pattern) are # defined by theme itself. Builtin themes are using these templates by # default: ``['localtoc.html', 'relations.html', 'sourcelink.html', # 'searchbox.html']``. # # html_sidebars = {} html_logo = '_static/open-datastudio-logo.svg' # Enable link of 'View page source' #html_show_sourcelink = False # Add 'Edit on Github' link instead of 'View page source' # reference:https://docs.readthedocs.io/en/latest/vcs.html html_context = { # Enable the "Edit in GitHub link within the header of each page. 'display_github': True, # Set the following variables to generate the resulting github URL for each page. # Format Template: https://{{ github_host|default("github.com") }}/{{ github_user }} #/{{ github_repo }}/blob/{{ github_version }}{{ conf_py_path }}{{ pagename }}{{ suffix }} #https://github.com/runawayhorse001/SphinxGithub/blob/master/doc/index.rst 'github_user': 'open-datastudio', 'github_repo': 'datastudio', 'github_version': 'master/docs/', } # -- Options for HTMLHelp output --------------------------------------------- # Output file base name for HTML help builder. htmlhelp_basename = 'OpenDataStudioDoc' # -- Options for LaTeX output ------------------------------------------------ latex_elements = { # The paper size ('letterpaper' or 'a4paper'). # # 'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). # # 'pointsize': '10pt', # Additional stuff for the LaTeX preamble. # # 'preamble': '', # Latex figure (float) alignment # # 'figure_align': 'htbp', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ (master_doc, 'OPENDATASTUDIO.tex', u'Open Data Studio Documentation', u'Open Data Studio', 'manual'), ] # -- Options for manual page output ------------------------------------------ # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ (master_doc, 'open data studio', u'Open Data Studio Documentation', [author], 1) ] # -- Options for Texinfo output ---------------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ (master_doc, 'Open Data Studio', u'Open Data Studio Documentation', author, 'Open Data Studio', 'Cloud data tools', 'Miscellaneous'), ] # -- Options for Epub output ------------------------------------------------- # Bibliographic Dublin Core info. epub_title = project # The unique identifier of the text. This can be a ISBN number # or the project homepage. # # epub_identifier = '' # A unique identification for the text. # # epub_uid = '' # A list of files that should not be packed into the epub file. epub_exclude_files = ['search.html']

31.71875

93

0.663054

project = u'Open Data Studio' copyright = u'Open Data Studio Authors' author = u'Open Data Studio Authors' version = u'' release = u'' extensions = [ 'sphinx.ext.autosectionlabel', 'aafigure.sphinxext' ] templates_path = ['_templates'] source_suffix = '.rst' master_doc = 'index' language = None exclude_patterns = [u'_build', 'Thumbs.db', '.DS_Store'] pygments_style = None html_theme = 'sphinx_rtd_theme' html_static_path = ['_static'] # defined by theme itself. Builtin themes are using these templates by # default: ``['localtoc.html', 'relations.html', 'sourcelink.html', # 'searchbox.html']``. # # html_sidebars = {} html_logo = '_static/open-datastudio-logo.svg' # Enable link of 'View page source' #html_show_sourcelink = False # Add 'Edit on Github' link instead of 'View page source' # reference:https://docs.readthedocs.io/en/latest/vcs.html html_context = { # Enable the "Edit in GitHub link within the header of each page. 'display_github': True, # Set the following variables to generate the resulting github URL for each page. # Format Template: https://{{ github_host|default("github.com") }}/{{ github_user }} #/{{ github_repo }}/blob/{{ github_version }}{{ conf_py_path }}{{ pagename }}{{ suffix }} #https://github.com/runawayhorse001/SphinxGithub/blob/master/doc/index.rst 'github_user': 'open-datastudio', 'github_repo': 'datastudio', 'github_version': 'master/docs/', } # -- Options for HTMLHelp output --------------------------------------------- # Output file base name for HTML help builder. htmlhelp_basename = 'OpenDataStudioDoc' # -- Options for LaTeX output ------------------------------------------------ latex_elements = { # The paper size ('letterpaper' or 'a4paper'). # # 'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). # # 'pointsize': '10pt', # Additional stuff for the LaTeX preamble. # # 'preamble': '', # Latex figure (float) alignment # # 'figure_align': 'htbp', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ (master_doc, 'OPENDATASTUDIO.tex', u'Open Data Studio Documentation', u'Open Data Studio', 'manual'), ] # -- Options for manual page output ------------------------------------------ # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ (master_doc, 'open data studio', u'Open Data Studio Documentation', [author], 1) ] # -- Options for Texinfo output ---------------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ (master_doc, 'Open Data Studio', u'Open Data Studio Documentation', author, 'Open Data Studio', 'Cloud data tools', 'Miscellaneous'), ] # -- Options for Epub output ------------------------------------------------- # Bibliographic Dublin Core info. epub_title = project # The unique identifier of the text. This can be a ISBN number # or the project homepage. # # epub_identifier = '' # A unique identification for the text. # # epub_uid = '' # A list of files that should not be packed into the epub file. epub_exclude_files = ['search.html']

true

1c45a10a9ddde743dce9b343e4d18f568bb05e72

3,531

py

Python

python/paddle/fluid/tests/unittests/dist_mnist.py

hshen14/Paddle

0962be9c800d29e0804fc3135163bdfba1564c61

[ "Apache-2.0" ]

2

2019-04-03T05:36:17.000Z

2020-04-29T03:38:54.000Z

python/paddle/fluid/tests/unittests/dist_mnist.py

hshen14/Paddle

0962be9c800d29e0804fc3135163bdfba1564c61

[ "Apache-2.0" ]

null

python/paddle/fluid/tests/unittests/dist_mnist.py

hshen14/Paddle

0962be9c800d29e0804fc3135163bdfba1564c61

[ "Apache-2.0" ]

3

2019-01-07T06:50:29.000Z

2019-03-13T08:48:23.000Z

# Copyright (c) 2018 PaddlePaddle Authors. 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. from __future__ import print_function import numpy as np import argparse import time import math import paddle import paddle.fluid as fluid import paddle.fluid.profiler as profiler from paddle.fluid import core import unittest from multiprocessing import Process import os import signal from functools import reduce from test_dist_base import TestDistRunnerBase, runtime_main DTYPE = "float32" paddle.dataset.mnist.fetch() # Fix seed for test fluid.default_startup_program().random_seed = 1 fluid.default_main_program().random_seed = 1 def cnn_model(data): conv_pool_1 = fluid.nets.simple_img_conv_pool( input=data, filter_size=5, num_filters=20, pool_size=2, pool_stride=2, act="relu", param_attr=fluid.ParamAttr(initializer=fluid.initializer.Constant( value=0.01))) conv_pool_2 = fluid.nets.simple_img_conv_pool( input=conv_pool_1, filter_size=5, num_filters=50, pool_size=2, pool_stride=2, act="relu", param_attr=fluid.ParamAttr(initializer=fluid.initializer.Constant( value=0.01))) SIZE = 10 input_shape = conv_pool_2.shape param_shape = [reduce(lambda a, b: a * b, input_shape[1:], 1)] + [SIZE] scale = (2.0 / (param_shape[0]**2 * SIZE))**0.5 predict = fluid.layers.fc( input=conv_pool_2, size=SIZE, act="softmax", param_attr=fluid.param_attr.ParamAttr( initializer=fluid.initializer.Constant(value=0.01))) return predict class TestDistMnist2x2(TestDistRunnerBase): def get_model(self, batch_size=2): # Input data images = fluid.layers.data(name='pixel', shape=[1, 28, 28], dtype=DTYPE) label = fluid.layers.data(name='label', shape=[1], dtype='int64') # Train program predict = cnn_model(images) cost = fluid.layers.cross_entropy(input=predict, label=label) avg_cost = fluid.layers.mean(x=cost) # Evaluator batch_size_tensor = fluid.layers.create_tensor(dtype='int64') batch_acc = fluid.layers.accuracy( input=predict, label=label, total=batch_size_tensor) inference_program = fluid.default_main_program().clone() # Optimization # TODO(typhoonzero): fix distributed adam optimizer # opt = fluid.optimizer.AdamOptimizer( # learning_rate=0.001, beta1=0.9, beta2=0.999) opt = fluid.optimizer.Momentum(learning_rate=self.lr, momentum=0.9) # Reader train_reader = paddle.batch( paddle.dataset.mnist.test(), batch_size=batch_size) test_reader = paddle.batch( paddle.dataset.mnist.test(), batch_size=batch_size) opt.minimize(avg_cost) return inference_program, avg_cost, train_reader, test_reader, batch_acc, predict if __name__ == "__main__": runtime_main(TestDistMnist2x2)

32.394495

89

0.687624

from __future__ import print_function import numpy as np import argparse import time import math import paddle import paddle.fluid as fluid import paddle.fluid.profiler as profiler from paddle.fluid import core import unittest from multiprocessing import Process import os import signal from functools import reduce from test_dist_base import TestDistRunnerBase, runtime_main DTYPE = "float32" paddle.dataset.mnist.fetch() fluid.default_startup_program().random_seed = 1 fluid.default_main_program().random_seed = 1 def cnn_model(data): conv_pool_1 = fluid.nets.simple_img_conv_pool( input=data, filter_size=5, num_filters=20, pool_size=2, pool_stride=2, act="relu", param_attr=fluid.ParamAttr(initializer=fluid.initializer.Constant( value=0.01))) conv_pool_2 = fluid.nets.simple_img_conv_pool( input=conv_pool_1, filter_size=5, num_filters=50, pool_size=2, pool_stride=2, act="relu", param_attr=fluid.ParamAttr(initializer=fluid.initializer.Constant( value=0.01))) SIZE = 10 input_shape = conv_pool_2.shape param_shape = [reduce(lambda a, b: a * b, input_shape[1:], 1)] + [SIZE] scale = (2.0 / (param_shape[0]**2 * SIZE))**0.5 predict = fluid.layers.fc( input=conv_pool_2, size=SIZE, act="softmax", param_attr=fluid.param_attr.ParamAttr( initializer=fluid.initializer.Constant(value=0.01))) return predict class TestDistMnist2x2(TestDistRunnerBase): def get_model(self, batch_size=2): images = fluid.layers.data(name='pixel', shape=[1, 28, 28], dtype=DTYPE) label = fluid.layers.data(name='label', shape=[1], dtype='int64') predict = cnn_model(images) cost = fluid.layers.cross_entropy(input=predict, label=label) avg_cost = fluid.layers.mean(x=cost) batch_size_tensor = fluid.layers.create_tensor(dtype='int64') batch_acc = fluid.layers.accuracy( input=predict, label=label, total=batch_size_tensor) inference_program = fluid.default_main_program().clone() opt = fluid.optimizer.Momentum(learning_rate=self.lr, momentum=0.9) train_reader = paddle.batch( paddle.dataset.mnist.test(), batch_size=batch_size) test_reader = paddle.batch( paddle.dataset.mnist.test(), batch_size=batch_size) opt.minimize(avg_cost) return inference_program, avg_cost, train_reader, test_reader, batch_acc, predict if __name__ == "__main__": runtime_main(TestDistMnist2x2)

true

1c45a12fb0bf22d70b2259e645866d62d1c2fa9f

5,240

py

Python

tests/test_cli.py

steffenschumacher/NIPAP

200ec08ce02ba9f782b276510bc7bb23b20d7570

[ "MIT" ]

1

2018-12-07T15:59:27.000Z

tests/test_cli.py

steffenschumacher/NIPAP

200ec08ce02ba9f782b276510bc7bb23b20d7570

[ "MIT" ]

1

2021-07-24T14:44:10.000Z

tests/test_cli.py

steffenschumacher/NIPAP

200ec08ce02ba9f782b276510bc7bb23b20d7570

[ "MIT" ]

1

2020-05-27T15:28:03.000Z

#!/usr/bin/env python # vim: et : import logging import unittest import sys sys.path.append('../nipap/') from nipap.backend import Nipap from nipap.authlib import SqliteAuth from nipap.nipapconfig import NipapConfig logger = logging.getLogger() logger.setLevel(logging.DEBUG) log_format = "%(levelname)-8s %(message)s" import xmlrpclib server_url = "http://unittest:gottatest@127.0.0.1:1337/XMLRPC" s = xmlrpclib.Server(server_url, allow_none=1); ad = { 'authoritative_source': 'nipap' } nipap_bin = '../nipap-cli/nipap' class NipapCliTest(unittest.TestCase): """ Tests the NIPAP CLI We presume the database is empty """ maxDiff = None logger = None cfg = None nipap = None def setUp(self): # logging self.logger = logging.getLogger(self.__class__.__name__) # NIPAP self.cfg = NipapConfig('/etc/nipap/nipap.conf') self.nipap = Nipap() # create dummy auth object # As the authentication is performed before the query hits the Nipap # class, it does not matter what user we use here self.auth = SqliteAuth('local', 'unittest', 'unittest', 'unittest') self.auth.authenticated_as = 'unittest' self.auth.full_name = 'Unit test' # have to delete hosts before we can delete the rest self.nipap._execute("DELETE FROM ip_net_plan WHERE masklen(prefix) = 32") # the rest self.nipap._execute("DELETE FROM ip_net_plan") # delete all except for the default VRF with id 0 self.nipap._execute("DELETE FROM ip_net_vrf WHERE id > 0") # set default info for VRF 0 self.nipap._execute("UPDATE ip_net_vrf SET name = 'default', description = 'The default VRF, typically the Internet.' WHERE id = 0") self.nipap._execute("DELETE FROM ip_net_pool") self.nipap._execute("DELETE FROM ip_net_asn") def _mangle_prefix_result(self, res): """ Mangle prefix result for easier testing We can never predict the values of things like the ID (okay, that one is actually kind of doable) or the added and last_modified timestamp. This function will make sure the values are present but then strip them to make it easier to test against an expected result. """ if isinstance(res, list): # res from list_prefix for p in res: self.assertIn('added', p) self.assertIn('last_modified', p) del(p['added']) del(p['last_modified']) del(p['total_addresses']) del(p['used_addresses']) del(p['free_addresses']) elif isinstance(res, dict) and 'result' in res: # res from smart search for p in res['result']: self.assertIn('added', p) self.assertIn('last_modified', p) del(p['added']) del(p['last_modified']) del(p['total_addresses']) del(p['used_addresses']) del(p['free_addresses']) elif isinstance(res, dict): # just one single prefix self.assertIn('added', p) self.assertIn('last_modified', p) del(p['added']) del(p['last_modified']) del(res['total_addresses']) del(res['used_addresses']) del(res['free_addresses']) return res def _run_cmd(self, cmd): """ Run a command """ import subprocess return subprocess.check_output(cmd) def test_prefix_add_list(self): """ Add a prefix and verify result in database """ ref = { 'prefix': '1.3.3.0/24', 'type': 'assignment', 'status': 'assigned', 'description': 'foo description', 'comment': 'comment bar', 'country': 'AB', 'alarm_priority': 'high', 'monitor': 'true', 'order_id': '123', 'customer_id': '66' } cmd = [nipap_bin, 'address', 'add'] for key in ref: cmd.append(key) cmd.append(ref[key]) ref['display_prefix'] = '1.3.3.0/24' ref['indent'] = 0 ref['family'] = 4 ref['monitor'] = True ref['pool_id'] = None ref['pool_name'] = None ref['vrf_id'] = 0 ref['vrf_name'] = 'default' ref['vrf_rt'] = None ref['external_key'] = None ref['node'] = None ref['authoritative_source'] = 'nipap' ref['vlan'] = None ref['inherited_tags'] = [] ref['tags'] = [] ref['avps'] = {} ref['expires'] = None self._run_cmd(cmd) res = self._mangle_prefix_result(s.list_prefix({ 'auth': ad, 'spec': {} })) del(res[0]['id']) self.assertEqual(res, [ ref, ]) if __name__ == '__main__': # set up logging log = logging.getLogger() logging.basicConfig() log.setLevel(logging.INFO) if sys.version_info >= (2,7): unittest.main(verbosity=2) else: unittest.main()

29.438202

140

0.55687

import logging import unittest import sys sys.path.append('../nipap/') from nipap.backend import Nipap from nipap.authlib import SqliteAuth from nipap.nipapconfig import NipapConfig logger = logging.getLogger() logger.setLevel(logging.DEBUG) log_format = "%(levelname)-8s %(message)s" import xmlrpclib server_url = "http://unittest:gottatest@127.0.0.1:1337/XMLRPC" s = xmlrpclib.Server(server_url, allow_none=1); ad = { 'authoritative_source': 'nipap' } nipap_bin = '../nipap-cli/nipap' class NipapCliTest(unittest.TestCase): maxDiff = None logger = None cfg = None nipap = None def setUp(self): self.logger = logging.getLogger(self.__class__.__name__) self.cfg = NipapConfig('/etc/nipap/nipap.conf') self.nipap = Nipap() self.auth = SqliteAuth('local', 'unittest', 'unittest', 'unittest') self.auth.authenticated_as = 'unittest' self.auth.full_name = 'Unit test' self.nipap._execute("DELETE FROM ip_net_plan WHERE masklen(prefix) = 32") self.nipap._execute("DELETE FROM ip_net_plan") self.nipap._execute("DELETE FROM ip_net_vrf WHERE id > 0") self.nipap._execute("UPDATE ip_net_vrf SET name = 'default', description = 'The default VRF, typically the Internet.' WHERE id = 0") self.nipap._execute("DELETE FROM ip_net_pool") self.nipap._execute("DELETE FROM ip_net_asn") def _mangle_prefix_result(self, res): if isinstance(res, list): for p in res: self.assertIn('added', p) self.assertIn('last_modified', p) del(p['added']) del(p['last_modified']) del(p['total_addresses']) del(p['used_addresses']) del(p['free_addresses']) elif isinstance(res, dict) and 'result' in res: for p in res['result']: self.assertIn('added', p) self.assertIn('last_modified', p) del(p['added']) del(p['last_modified']) del(p['total_addresses']) del(p['used_addresses']) del(p['free_addresses']) elif isinstance(res, dict): self.assertIn('added', p) self.assertIn('last_modified', p) del(p['added']) del(p['last_modified']) del(res['total_addresses']) del(res['used_addresses']) del(res['free_addresses']) return res def _run_cmd(self, cmd): import subprocess return subprocess.check_output(cmd) def test_prefix_add_list(self): ref = { 'prefix': '1.3.3.0/24', 'type': 'assignment', 'status': 'assigned', 'description': 'foo description', 'comment': 'comment bar', 'country': 'AB', 'alarm_priority': 'high', 'monitor': 'true', 'order_id': '123', 'customer_id': '66' } cmd = [nipap_bin, 'address', 'add'] for key in ref: cmd.append(key) cmd.append(ref[key]) ref['display_prefix'] = '1.3.3.0/24' ref['indent'] = 0 ref['family'] = 4 ref['monitor'] = True ref['pool_id'] = None ref['pool_name'] = None ref['vrf_id'] = 0 ref['vrf_name'] = 'default' ref['vrf_rt'] = None ref['external_key'] = None ref['node'] = None ref['authoritative_source'] = 'nipap' ref['vlan'] = None ref['inherited_tags'] = [] ref['tags'] = [] ref['avps'] = {} ref['expires'] = None self._run_cmd(cmd) res = self._mangle_prefix_result(s.list_prefix({ 'auth': ad, 'spec': {} })) del(res[0]['id']) self.assertEqual(res, [ ref, ]) if __name__ == '__main__': log = logging.getLogger() logging.basicConfig() log.setLevel(logging.INFO) if sys.version_info >= (2,7): unittest.main(verbosity=2) else: unittest.main()

true

1c45a18a21fd6fbd0b288b2271b398a0ed9f080d

12,540

py

Python

napari/_qt/widgets/qt_viewer_dock_widget.py

Mishrasubha/napari

c4d1038fc3ed30dc228949cbdedf12826ec2efc2

[ "BSD-3-Clause" ]

null

napari/_qt/widgets/qt_viewer_dock_widget.py

Mishrasubha/napari

c4d1038fc3ed30dc228949cbdedf12826ec2efc2

[ "BSD-3-Clause" ]

3

2020-11-14T08:35:18.000Z

2021-07-26T10:06:32.000Z

napari/_qt/widgets/qt_viewer_dock_widget.py

Mishrasubha/napari

c4d1038fc3ed30dc228949cbdedf12826ec2efc2

[ "BSD-3-Clause" ]

null

import warnings from functools import reduce from itertools import count from operator import ior from typing import List, Optional from qtpy.QtCore import Qt from qtpy.QtWidgets import ( QDockWidget, QFrame, QHBoxLayout, QLabel, QPushButton, QSizePolicy, QVBoxLayout, QWidget, ) from ...utils.translations import trans from ..utils import combine_widgets, qt_signals_blocked counter = count() _sentinel = object() _SHORTCUT_DEPRECATION_STRING = trans._( 'The shortcut parameter is deprecated since version 0.4.8, please use the action and shortcut manager APIs. The new action manager and shortcut API allow user configuration and localisation. (got {shortcut})', shortcut="{shortcut}", ) class QtViewerDockWidget(QDockWidget): """Wrap a QWidget in a QDockWidget and forward viewer events Parameters ---------- qt_viewer : QtViewer The QtViewer instance that this dock widget will belong to. widget : QWidget `widget` that will be added as QDockWidget's main widget. name : str Name of dock widget. area : str Side of the main window to which the new dock widget will be added. Must be in {'left', 'right', 'top', 'bottom'} allowed_areas : list[str], optional Areas, relative to main window, that the widget is allowed dock. Each item in list must be in {'left', 'right', 'top', 'bottom'} By default, all areas are allowed. shortcut : str, optional Keyboard shortcut to appear in dropdown menu. .. deprecated:: 0.4.8 The shortcut parameter is deprecated since version 0.4.8, please use the action and shortcut manager APIs. The new action manager and shortcut API allow user configuration and localisation. add_vertical_stretch : bool, optional Whether to add stretch to the bottom of vertical widgets (pushing widgets up towards the top of the allotted area, instead of letting them distribute across the vertical space). By default, True. """ def __init__( self, qt_viewer, widget: QWidget, *, name: str = '', area: str = 'right', allowed_areas: Optional[List[str]] = None, shortcut=_sentinel, object_name: str = '', add_vertical_stretch=True, ): self.qt_viewer = qt_viewer super().__init__(name) self._parent = qt_viewer self.name = name areas = { 'left': Qt.LeftDockWidgetArea, 'right': Qt.RightDockWidgetArea, 'top': Qt.TopDockWidgetArea, 'bottom': Qt.BottomDockWidgetArea, } if area not in areas: raise ValueError( trans._( 'area argument must be in {areas}', deferred=True, areas=list(areas.keys()), ) ) self.area = area self.qt_area = areas[area] if shortcut is not _sentinel: warnings.warn( _SHORTCUT_DEPRECATION_STRING.format(shortcut=shortcut), FutureWarning, stacklevel=2, ) else: shortcut = None self._shortcut = shortcut if allowed_areas: if not isinstance(allowed_areas, (list, tuple)): raise TypeError( trans._( '`allowed_areas` must be a list or tuple', deferred=True, ) ) if any(area not in areas for area in allowed_areas): raise ValueError( trans._( 'all allowed_areas argument must be in {areas}', deferred=True, areas=list(areas.keys()), ) ) allowed_areas = reduce(ior, [areas[a] for a in allowed_areas]) else: allowed_areas = Qt.AllDockWidgetAreas self.setAllowedAreas(allowed_areas) self.setMinimumHeight(50) self.setMinimumWidth(50) # FIXME: self.setObjectName(object_name or name) is_vertical = area in {'left', 'right'} widget = combine_widgets(widget, vertical=is_vertical) self.setWidget(widget) if is_vertical and add_vertical_stretch: self._maybe_add_vertical_stretch(widget) self._features = self.features() self.dockLocationChanged.connect(self._set_title_orientation) # custom title bar self.title = QtCustomTitleBar(self, title=self.name) self.setTitleBarWidget(self.title) self.visibilityChanged.connect(self._on_visibility_changed) def destroyOnClose(self): """Destroys dock plugin dock widget when 'x' is clicked.""" self.qt_viewer.viewer.window.remove_dock_widget(self) def _maybe_add_vertical_stretch(self, widget): """Add vertical stretch to the bottom of a vertical layout only ...if there is not already a widget that wants vertical space (like a textedit or listwidget or something). """ exempt_policies = { QSizePolicy.Expanding, QSizePolicy.MinimumExpanding, QSizePolicy.Ignored, } if widget.sizePolicy().verticalPolicy() in exempt_policies: return # not uncommon to see people shadow the builtin layout() method # which breaks our ability to add vertical stretch... try: wlayout = widget.layout() if wlayout is None: return except TypeError: return for i in range(wlayout.count()): wdg = wlayout.itemAt(i).widget() if ( wdg is not None and wdg.sizePolicy().verticalPolicy() in exempt_policies ): return # not all widgets have addStretch... if hasattr(wlayout, 'addStretch'): wlayout.addStretch(next(counter)) @property def shortcut(self): warnings.warn( _SHORTCUT_DEPRECATION_STRING, FutureWarning, stacklevel=2, ) return self._shortcut def setFeatures(self, features): super().setFeatures(features) self._features = self.features() def keyPressEvent(self, event): # if you subclass QtViewerDockWidget and override the keyPressEvent # method, be sure to call super().keyPressEvent(event) at the end of # your method to pass uncaught key-combinations to the viewer. return self.qt_viewer.keyPressEvent(event) def _set_title_orientation(self, area): if area in (Qt.LeftDockWidgetArea, Qt.RightDockWidgetArea): features = self._features if features & self.DockWidgetVerticalTitleBar: features = features ^ self.DockWidgetVerticalTitleBar else: features = self._features | self.DockWidgetVerticalTitleBar self.setFeatures(features) @property def is_vertical(self): if not self.isFloating(): par = self.parent() if par and hasattr(par, 'dockWidgetArea'): return par.dockWidgetArea(self) in ( Qt.LeftDockWidgetArea, Qt.RightDockWidgetArea, ) return self.size().height() > self.size().width() def _on_visibility_changed(self, visible): try: actions = [ action.text() for action in self.qt_viewer.viewer.window.plugins_menu.actions() ] idx = actions.index(self.name) current_action = ( self.qt_viewer.viewer.window.plugins_menu.actions()[idx] ) current_action.setChecked(visible) self.setVisible(visible) except (AttributeError, ValueError): # AttributeError: This error happens when the plugins menu is not yet built. # ValueError: This error is when the action is from the windows menu. pass if not visible: return with qt_signals_blocked(self): self.setTitleBarWidget(None) if not self.isFloating(): self.title = QtCustomTitleBar( self, title=self.name, vertical=not self.is_vertical ) self.setTitleBarWidget(self.title) def setWidget(self, widget): widget._parent = self super().setWidget(widget) class QtCustomTitleBar(QLabel): """A widget to be used as the titleBar in the QtViewerDockWidget. Keeps vertical size minimal, has a hand cursor and styles (in stylesheet) for hover. Close and float buttons. Parameters ---------- parent : QDockWidget The QtViewerDockWidget to which this titlebar belongs title : str A string to put in the titlebar. vertical : bool Whether this titlebar is oriented vertically or not. """ def __init__(self, parent, title: str = '', vertical=False): super().__init__(parent) self.setObjectName("QtCustomTitleBar") self.setProperty('vertical', str(vertical)) self.vertical = vertical self.setToolTip(trans._('drag to move. double-click to float')) line = QFrame(self) line.setObjectName("QtCustomTitleBarLine") add_close = False try: # if the plugins menu is already created, check to see if this is a plugin # dock widget. If it is, then add the close button option to the title bar. actions = [ action.text() for action in self.parent().qt_viewer.viewer.window.plugins_menu.actions() ] if self.parent().name in actions: add_close = True self.close_button = QPushButton(self) self.close_button.setToolTip(trans._('close this panel')) self.close_button.setObjectName("QTitleBarCloseButton") self.close_button.setCursor(Qt.ArrowCursor) self.close_button.clicked.connect( lambda: self.parent().destroyOnClose() ) else: add_close = False except AttributeError: pass self.hide_button = QPushButton(self) self.hide_button.setToolTip(trans._('hide this panel')) self.hide_button.setObjectName("QTitleBarHideButton") self.hide_button.setCursor(Qt.ArrowCursor) self.hide_button.clicked.connect(lambda: self.parent().close()) self.float_button = QPushButton(self) self.float_button.setToolTip(trans._('float this panel')) self.float_button.setObjectName("QTitleBarFloatButton") self.float_button.setCursor(Qt.ArrowCursor) self.float_button.clicked.connect( lambda: self.parent().setFloating(not self.parent().isFloating()) ) self.title = QLabel(title, self) self.title.setSizePolicy( QSizePolicy(QSizePolicy.Policy.Maximum, QSizePolicy.Policy.Maximum) ) if vertical: layout = QVBoxLayout() layout.setSpacing(4) layout.setContentsMargins(0, 8, 0, 8) line.setFixedWidth(1) if add_close: layout.addWidget(self.close_button, 0, Qt.AlignHCenter) layout.addWidget(self.hide_button, 0, Qt.AlignHCenter) layout.addWidget(self.float_button, 0, Qt.AlignHCenter) layout.addWidget(line, 0, Qt.AlignHCenter) self.title.hide() else: layout = QHBoxLayout() layout.setSpacing(4) layout.setContentsMargins(8, 1, 8, 0) line.setFixedHeight(1) if add_close: layout.addWidget(self.close_button) layout.addWidget(self.hide_button) layout.addWidget(self.float_button) layout.addWidget(line) layout.addWidget(self.title) self.setLayout(layout) self.setCursor(Qt.OpenHandCursor) def sizeHint(self): # this seems to be the correct way to set the height of the titlebar szh = super().sizeHint() if self.vertical: szh.setWidth(20) else: szh.setHeight(20) return szh

35.12605

213

0.596332

import warnings from functools import reduce from itertools import count from operator import ior from typing import List, Optional from qtpy.QtCore import Qt from qtpy.QtWidgets import ( QDockWidget, QFrame, QHBoxLayout, QLabel, QPushButton, QSizePolicy, QVBoxLayout, QWidget, ) from ...utils.translations import trans from ..utils import combine_widgets, qt_signals_blocked counter = count() _sentinel = object() _SHORTCUT_DEPRECATION_STRING = trans._( 'The shortcut parameter is deprecated since version 0.4.8, please use the action and shortcut manager APIs. The new action manager and shortcut API allow user configuration and localisation. (got {shortcut})', shortcut="{shortcut}", ) class QtViewerDockWidget(QDockWidget): def __init__( self, qt_viewer, widget: QWidget, *, name: str = '', area: str = 'right', allowed_areas: Optional[List[str]] = None, shortcut=_sentinel, object_name: str = '', add_vertical_stretch=True, ): self.qt_viewer = qt_viewer super().__init__(name) self._parent = qt_viewer self.name = name areas = { 'left': Qt.LeftDockWidgetArea, 'right': Qt.RightDockWidgetArea, 'top': Qt.TopDockWidgetArea, 'bottom': Qt.BottomDockWidgetArea, } if area not in areas: raise ValueError( trans._( 'area argument must be in {areas}', deferred=True, areas=list(areas.keys()), ) ) self.area = area self.qt_area = areas[area] if shortcut is not _sentinel: warnings.warn( _SHORTCUT_DEPRECATION_STRING.format(shortcut=shortcut), FutureWarning, stacklevel=2, ) else: shortcut = None self._shortcut = shortcut if allowed_areas: if not isinstance(allowed_areas, (list, tuple)): raise TypeError( trans._( '`allowed_areas` must be a list or tuple', deferred=True, ) ) if any(area not in areas for area in allowed_areas): raise ValueError( trans._( 'all allowed_areas argument must be in {areas}', deferred=True, areas=list(areas.keys()), ) ) allowed_areas = reduce(ior, [areas[a] for a in allowed_areas]) else: allowed_areas = Qt.AllDockWidgetAreas self.setAllowedAreas(allowed_areas) self.setMinimumHeight(50) self.setMinimumWidth(50) self.setObjectName(object_name or name) is_vertical = area in {'left', 'right'} widget = combine_widgets(widget, vertical=is_vertical) self.setWidget(widget) if is_vertical and add_vertical_stretch: self._maybe_add_vertical_stretch(widget) self._features = self.features() self.dockLocationChanged.connect(self._set_title_orientation) self.title = QtCustomTitleBar(self, title=self.name) self.setTitleBarWidget(self.title) self.visibilityChanged.connect(self._on_visibility_changed) def destroyOnClose(self): self.qt_viewer.viewer.window.remove_dock_widget(self) def _maybe_add_vertical_stretch(self, widget): exempt_policies = { QSizePolicy.Expanding, QSizePolicy.MinimumExpanding, QSizePolicy.Ignored, } if widget.sizePolicy().verticalPolicy() in exempt_policies: return try: wlayout = widget.layout() if wlayout is None: return except TypeError: return for i in range(wlayout.count()): wdg = wlayout.itemAt(i).widget() if ( wdg is not None and wdg.sizePolicy().verticalPolicy() in exempt_policies ): return if hasattr(wlayout, 'addStretch'): wlayout.addStretch(next(counter)) @property def shortcut(self): warnings.warn( _SHORTCUT_DEPRECATION_STRING, FutureWarning, stacklevel=2, ) return self._shortcut def setFeatures(self, features): super().setFeatures(features) self._features = self.features() def keyPressEvent(self, event): return self.qt_viewer.keyPressEvent(event) def _set_title_orientation(self, area): if area in (Qt.LeftDockWidgetArea, Qt.RightDockWidgetArea): features = self._features if features & self.DockWidgetVerticalTitleBar: features = features ^ self.DockWidgetVerticalTitleBar else: features = self._features | self.DockWidgetVerticalTitleBar self.setFeatures(features) @property def is_vertical(self): if not self.isFloating(): par = self.parent() if par and hasattr(par, 'dockWidgetArea'): return par.dockWidgetArea(self) in ( Qt.LeftDockWidgetArea, Qt.RightDockWidgetArea, ) return self.size().height() > self.size().width() def _on_visibility_changed(self, visible): try: actions = [ action.text() for action in self.qt_viewer.viewer.window.plugins_menu.actions() ] idx = actions.index(self.name) current_action = ( self.qt_viewer.viewer.window.plugins_menu.actions()[idx] ) current_action.setChecked(visible) self.setVisible(visible) except (AttributeError, ValueError): pass if not visible: return with qt_signals_blocked(self): self.setTitleBarWidget(None) if not self.isFloating(): self.title = QtCustomTitleBar( self, title=self.name, vertical=not self.is_vertical ) self.setTitleBarWidget(self.title) def setWidget(self, widget): widget._parent = self super().setWidget(widget) class QtCustomTitleBar(QLabel): def __init__(self, parent, title: str = '', vertical=False): super().__init__(parent) self.setObjectName("QtCustomTitleBar") self.setProperty('vertical', str(vertical)) self.vertical = vertical self.setToolTip(trans._('drag to move. double-click to float')) line = QFrame(self) line.setObjectName("QtCustomTitleBarLine") add_close = False try: actions = [ action.text() for action in self.parent().qt_viewer.viewer.window.plugins_menu.actions() ] if self.parent().name in actions: add_close = True self.close_button = QPushButton(self) self.close_button.setToolTip(trans._('close this panel')) self.close_button.setObjectName("QTitleBarCloseButton") self.close_button.setCursor(Qt.ArrowCursor) self.close_button.clicked.connect( lambda: self.parent().destroyOnClose() ) else: add_close = False except AttributeError: pass self.hide_button = QPushButton(self) self.hide_button.setToolTip(trans._('hide this panel')) self.hide_button.setObjectName("QTitleBarHideButton") self.hide_button.setCursor(Qt.ArrowCursor) self.hide_button.clicked.connect(lambda: self.parent().close()) self.float_button = QPushButton(self) self.float_button.setToolTip(trans._('float this panel')) self.float_button.setObjectName("QTitleBarFloatButton") self.float_button.setCursor(Qt.ArrowCursor) self.float_button.clicked.connect( lambda: self.parent().setFloating(not self.parent().isFloating()) ) self.title = QLabel(title, self) self.title.setSizePolicy( QSizePolicy(QSizePolicy.Policy.Maximum, QSizePolicy.Policy.Maximum) ) if vertical: layout = QVBoxLayout() layout.setSpacing(4) layout.setContentsMargins(0, 8, 0, 8) line.setFixedWidth(1) if add_close: layout.addWidget(self.close_button, 0, Qt.AlignHCenter) layout.addWidget(self.hide_button, 0, Qt.AlignHCenter) layout.addWidget(self.float_button, 0, Qt.AlignHCenter) layout.addWidget(line, 0, Qt.AlignHCenter) self.title.hide() else: layout = QHBoxLayout() layout.setSpacing(4) layout.setContentsMargins(8, 1, 8, 0) line.setFixedHeight(1) if add_close: layout.addWidget(self.close_button) layout.addWidget(self.hide_button) layout.addWidget(self.float_button) layout.addWidget(line) layout.addWidget(self.title) self.setLayout(layout) self.setCursor(Qt.OpenHandCursor) def sizeHint(self): szh = super().sizeHint() if self.vertical: szh.setWidth(20) else: szh.setHeight(20) return szh

true

1c45a1a090a13d50476e4eb2e61b77dfeabe3a7e

22,311

py

Python

test/functional/importmulti.py

DeepPool/test

c6d99f019667ea4bf51139adff2a98d46c0015ed

[ "MIT" ]

null

test/functional/importmulti.py

DeepPool/test

c6d99f019667ea4bf51139adff2a98d46c0015ed

[ "MIT" ]

null

test/functional/importmulti.py

DeepPool/test

c6d99f019667ea4bf51139adff2a98d46c0015ed

[ "MIT" ]

null

#!/usr/bin/env python3 # Copyright (c) 2014-2016 The Bitcoin Core developers # Distributed under the MIT software license, see the accompanying # file COPYING or http://www.opensource.org/licenses/mit-license.php. """Test the importmulti RPC.""" from test_framework.test_framework import DietBitcoinTestFramework from test_framework.util import * class ImportMultiTest (DietBitcoinTestFramework): def set_test_params(self): self.num_nodes = 2 self.setup_clean_chain = True def setup_network(self): self.setup_nodes() def run_test (self): self.log.info("Mining blocks...") self.nodes[0].generate(1) self.nodes[1].generate(1) timestamp = self.nodes[1].getblock(self.nodes[1].getbestblockhash())['mediantime'] # keyword definition PRIV_KEY = 'privkey' PUB_KEY = 'pubkey' ADDRESS_KEY = 'address' SCRIPT_KEY = 'script' node0_address1 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) node0_address2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) node0_address3 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) #Check only one address assert_equal(node0_address1['ismine'], True) #Node 1 sync test assert_equal(self.nodes[1].getblockcount(),1) #Address Test - before import address_info = self.nodes[1].validateaddress(node0_address1['address']) assert_equal(address_info['iswatchonly'], False) assert_equal(address_info['ismine'], False) # RPC importmulti ----------------------------------------------- # DietBitcoin Address self.log.info("Should import an address") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": address['address'] }, "timestamp": "now", }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], True) assert_equal(address_assert['ismine'], False) assert_equal(address_assert['timestamp'], timestamp) watchonly_address = address['address'] watchonly_timestamp = timestamp self.log.info("Should not import an invalid address") result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": "not valid address", }, "timestamp": "now", }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -5) assert_equal(result[0]['error']['message'], 'Invalid address') # ScriptPubKey + internal self.log.info("Should import a scriptPubKey with internal flag") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": address['scriptPubKey'], "timestamp": "now", "internal": True }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], True) assert_equal(address_assert['ismine'], False) assert_equal(address_assert['timestamp'], timestamp) # ScriptPubKey + !internal self.log.info("Should not import a scriptPubKey without internal flag") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": address['scriptPubKey'], "timestamp": "now", }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -8) assert_equal(result[0]['error']['message'], 'Internal must be set for hex scriptPubKey') address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], False) assert_equal('timestamp' in address_assert, False) # Address + Public key + !Internal self.log.info("Should import an address with public key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": address['address'] }, "timestamp": "now", "pubkeys": [ address['pubkey'] ] }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], True) assert_equal(address_assert['ismine'], False) assert_equal(address_assert['timestamp'], timestamp) # ScriptPubKey + Public key + internal self.log.info("Should import a scriptPubKey with internal and with public key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) request = [{ "scriptPubKey": address['scriptPubKey'], "timestamp": "now", "pubkeys": [ address['pubkey'] ], "internal": True }] result = self.nodes[1].importmulti(request) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], True) assert_equal(address_assert['ismine'], False) assert_equal(address_assert['timestamp'], timestamp) # ScriptPubKey + Public key + !internal self.log.info("Should not import a scriptPubKey without internal and with public key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) request = [{ "scriptPubKey": address['scriptPubKey'], "timestamp": "now", "pubkeys": [ address['pubkey'] ] }] result = self.nodes[1].importmulti(request) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -8) assert_equal(result[0]['error']['message'], 'Internal must be set for hex scriptPubKey') address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], False) assert_equal('timestamp' in address_assert, False) # Address + Private key + !watchonly self.log.info("Should import an address with private key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": address['address'] }, "timestamp": "now", "keys": [ self.nodes[0].dumpprivkey(address['address']) ] }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], True) assert_equal(address_assert['timestamp'], timestamp) self.log.info("Should not import an address with private key if is already imported") result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": address['address'] }, "timestamp": "now", "keys": [ self.nodes[0].dumpprivkey(address['address']) ] }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -4) assert_equal(result[0]['error']['message'], 'The wallet already contains the private key for this address or script') # Address + Private key + watchonly self.log.info("Should not import an address with private key and with watchonly") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": address['address'] }, "timestamp": "now", "keys": [ self.nodes[0].dumpprivkey(address['address']) ], "watchonly": True }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -8) assert_equal(result[0]['error']['message'], 'Incompatibility found between watchonly and keys') address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], False) assert_equal('timestamp' in address_assert, False) # ScriptPubKey + Private key + internal self.log.info("Should import a scriptPubKey with internal and with private key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": address['scriptPubKey'], "timestamp": "now", "keys": [ self.nodes[0].dumpprivkey(address['address']) ], "internal": True }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], True) assert_equal(address_assert['timestamp'], timestamp) # ScriptPubKey + Private key + !internal self.log.info("Should not import a scriptPubKey without internal and with private key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": address['scriptPubKey'], "timestamp": "now", "keys": [ self.nodes[0].dumpprivkey(address['address']) ] }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -8) assert_equal(result[0]['error']['message'], 'Internal must be set for hex scriptPubKey') address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], False) assert_equal('timestamp' in address_assert, False) # P2SH address sig_address_1 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) sig_address_2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) sig_address_3 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) multi_sig_script = self.nodes[0].createmultisig(2, [sig_address_1['address'], sig_address_2['address'], sig_address_3['pubkey']]) self.nodes[1].generate(100) transactionid = self.nodes[1].sendtoaddress(multi_sig_script['address'], 10.00) self.nodes[1].generate(1) timestamp = self.nodes[1].getblock(self.nodes[1].getbestblockhash())['mediantime'] transaction = self.nodes[1].gettransaction(transactionid) self.log.info("Should import a p2sh") result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": multi_sig_script['address'] }, "timestamp": "now", }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(multi_sig_script['address']) assert_equal(address_assert['isscript'], True) assert_equal(address_assert['iswatchonly'], True) assert_equal(address_assert['timestamp'], timestamp) p2shunspent = self.nodes[1].listunspent(0,999999, [multi_sig_script['address']])[0] assert_equal(p2shunspent['spendable'], False) assert_equal(p2shunspent['solvable'], False) # P2SH + Redeem script sig_address_1 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) sig_address_2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) sig_address_3 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) multi_sig_script = self.nodes[0].createmultisig(2, [sig_address_1['address'], sig_address_2['address'], sig_address_3['pubkey']]) self.nodes[1].generate(100) transactionid = self.nodes[1].sendtoaddress(multi_sig_script['address'], 10.00) self.nodes[1].generate(1) timestamp = self.nodes[1].getblock(self.nodes[1].getbestblockhash())['mediantime'] transaction = self.nodes[1].gettransaction(transactionid) self.log.info("Should import a p2sh with respective redeem script") result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": multi_sig_script['address'] }, "timestamp": "now", "redeemscript": multi_sig_script['redeemScript'] }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(multi_sig_script['address']) assert_equal(address_assert['timestamp'], timestamp) p2shunspent = self.nodes[1].listunspent(0,999999, [multi_sig_script['address']])[0] assert_equal(p2shunspent['spendable'], False) assert_equal(p2shunspent['solvable'], True) # P2SH + Redeem script + Private Keys + !Watchonly sig_address_1 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) sig_address_2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) sig_address_3 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) multi_sig_script = self.nodes[0].createmultisig(2, [sig_address_1['address'], sig_address_2['address'], sig_address_3['pubkey']]) self.nodes[1].generate(100) transactionid = self.nodes[1].sendtoaddress(multi_sig_script['address'], 10.00) self.nodes[1].generate(1) timestamp = self.nodes[1].getblock(self.nodes[1].getbestblockhash())['mediantime'] transaction = self.nodes[1].gettransaction(transactionid) self.log.info("Should import a p2sh with respective redeem script and private keys") result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": multi_sig_script['address'] }, "timestamp": "now", "redeemscript": multi_sig_script['redeemScript'], "keys": [ self.nodes[0].dumpprivkey(sig_address_1['address']), self.nodes[0].dumpprivkey(sig_address_2['address'])] }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(multi_sig_script['address']) assert_equal(address_assert['timestamp'], timestamp) p2shunspent = self.nodes[1].listunspent(0,999999, [multi_sig_script['address']])[0] assert_equal(p2shunspent['spendable'], False) assert_equal(p2shunspent['solvable'], True) # P2SH + Redeem script + Private Keys + Watchonly sig_address_1 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) sig_address_2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) sig_address_3 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) multi_sig_script = self.nodes[0].createmultisig(2, [sig_address_1['address'], sig_address_2['address'], sig_address_3['pubkey']]) self.nodes[1].generate(100) transactionid = self.nodes[1].sendtoaddress(multi_sig_script['address'], 10.00) self.nodes[1].generate(1) timestamp = self.nodes[1].getblock(self.nodes[1].getbestblockhash())['mediantime'] transaction = self.nodes[1].gettransaction(transactionid) self.log.info("Should import a p2sh with respective redeem script and private keys") result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": multi_sig_script['address'] }, "timestamp": "now", "redeemscript": multi_sig_script['redeemScript'], "keys": [ self.nodes[0].dumpprivkey(sig_address_1['address']), self.nodes[0].dumpprivkey(sig_address_2['address'])], "watchonly": True }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -8) assert_equal(result[0]['error']['message'], 'Incompatibility found between watchonly and keys') # Address + Public key + !Internal + Wrong pubkey self.log.info("Should not import an address with a wrong public key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) address2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": address['address'] }, "timestamp": "now", "pubkeys": [ address2['pubkey'] ] }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -5) assert_equal(result[0]['error']['message'], 'Consistency check failed') address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], False) assert_equal('timestamp' in address_assert, False) # ScriptPubKey + Public key + internal + Wrong pubkey self.log.info("Should not import a scriptPubKey with internal and with a wrong public key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) address2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) request = [{ "scriptPubKey": address['scriptPubKey'], "timestamp": "now", "pubkeys": [ address2['pubkey'] ], "internal": True }] result = self.nodes[1].importmulti(request) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -5) assert_equal(result[0]['error']['message'], 'Consistency check failed') address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], False) assert_equal('timestamp' in address_assert, False) # Address + Private key + !watchonly + Wrong private key self.log.info("Should not import an address with a wrong private key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) address2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": address['address'] }, "timestamp": "now", "keys": [ self.nodes[0].dumpprivkey(address2['address']) ] }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -5) assert_equal(result[0]['error']['message'], 'Consistency check failed') address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], False) assert_equal('timestamp' in address_assert, False) # ScriptPubKey + Private key + internal + Wrong private key self.log.info("Should not import a scriptPubKey with internal and with a wrong private key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) address2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": address['scriptPubKey'], "timestamp": "now", "keys": [ self.nodes[0].dumpprivkey(address2['address']) ], "internal": True }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -5) assert_equal(result[0]['error']['message'], 'Consistency check failed') address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], False) assert_equal('timestamp' in address_assert, False) # Importing existing watch only address with new timestamp should replace saved timestamp. assert_greater_than(timestamp, watchonly_timestamp) self.log.info("Should replace previously saved watch only timestamp.") result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": watchonly_address, }, "timestamp": "now", }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(watchonly_address) assert_equal(address_assert['iswatchonly'], True) assert_equal(address_assert['ismine'], False) assert_equal(address_assert['timestamp'], timestamp) watchonly_timestamp = timestamp # restart nodes to check for proper serialization/deserialization of watch only address self.stop_nodes() self.start_nodes() address_assert = self.nodes[1].validateaddress(watchonly_address) assert_equal(address_assert['iswatchonly'], True) assert_equal(address_assert['ismine'], False) assert_equal(address_assert['timestamp'], watchonly_timestamp) # Bad or missing timestamps self.log.info("Should throw on invalid or missing timestamp values") assert_raises_message(JSONRPCException, 'Missing required timestamp field for key', self.nodes[1].importmulti, [{ "scriptPubKey": address['scriptPubKey'], }]) assert_raises_message(JSONRPCException, 'Expected number or "now" timestamp value for key. got type string', self.nodes[1].importmulti, [{ "scriptPubKey": address['scriptPubKey'], "timestamp": "", }]) if __name__ == '__main__': ImportMultiTest ().main ()

48.084052

137

0.631841

from test_framework.test_framework import DietBitcoinTestFramework from test_framework.util import * class ImportMultiTest (DietBitcoinTestFramework): def set_test_params(self): self.num_nodes = 2 self.setup_clean_chain = True def setup_network(self): self.setup_nodes() def run_test (self): self.log.info("Mining blocks...") self.nodes[0].generate(1) self.nodes[1].generate(1) timestamp = self.nodes[1].getblock(self.nodes[1].getbestblockhash())['mediantime'] PRIV_KEY = 'privkey' PUB_KEY = 'pubkey' ADDRESS_KEY = 'address' SCRIPT_KEY = 'script' node0_address1 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) node0_address2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) node0_address3 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) assert_equal(node0_address1['ismine'], True) assert_equal(self.nodes[1].getblockcount(),1) address_info = self.nodes[1].validateaddress(node0_address1['address']) assert_equal(address_info['iswatchonly'], False) assert_equal(address_info['ismine'], False) self.log.info("Should import an address") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": address['address'] }, "timestamp": "now", }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], True) assert_equal(address_assert['ismine'], False) assert_equal(address_assert['timestamp'], timestamp) watchonly_address = address['address'] watchonly_timestamp = timestamp self.log.info("Should not import an invalid address") result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": "not valid address", }, "timestamp": "now", }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -5) assert_equal(result[0]['error']['message'], 'Invalid address') self.log.info("Should import a scriptPubKey with internal flag") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": address['scriptPubKey'], "timestamp": "now", "internal": True }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], True) assert_equal(address_assert['ismine'], False) assert_equal(address_assert['timestamp'], timestamp) self.log.info("Should not import a scriptPubKey without internal flag") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": address['scriptPubKey'], "timestamp": "now", }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -8) assert_equal(result[0]['error']['message'], 'Internal must be set for hex scriptPubKey') address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], False) assert_equal('timestamp' in address_assert, False) self.log.info("Should import an address with public key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": address['address'] }, "timestamp": "now", "pubkeys": [ address['pubkey'] ] }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], True) assert_equal(address_assert['ismine'], False) assert_equal(address_assert['timestamp'], timestamp) self.log.info("Should import a scriptPubKey with internal and with public key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) request = [{ "scriptPubKey": address['scriptPubKey'], "timestamp": "now", "pubkeys": [ address['pubkey'] ], "internal": True }] result = self.nodes[1].importmulti(request) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], True) assert_equal(address_assert['ismine'], False) assert_equal(address_assert['timestamp'], timestamp) self.log.info("Should not import a scriptPubKey without internal and with public key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) request = [{ "scriptPubKey": address['scriptPubKey'], "timestamp": "now", "pubkeys": [ address['pubkey'] ] }] result = self.nodes[1].importmulti(request) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -8) assert_equal(result[0]['error']['message'], 'Internal must be set for hex scriptPubKey') address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], False) assert_equal('timestamp' in address_assert, False) self.log.info("Should import an address with private key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": address['address'] }, "timestamp": "now", "keys": [ self.nodes[0].dumpprivkey(address['address']) ] }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], True) assert_equal(address_assert['timestamp'], timestamp) self.log.info("Should not import an address with private key if is already imported") result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": address['address'] }, "timestamp": "now", "keys": [ self.nodes[0].dumpprivkey(address['address']) ] }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -4) assert_equal(result[0]['error']['message'], 'The wallet already contains the private key for this address or script') self.log.info("Should not import an address with private key and with watchonly") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": address['address'] }, "timestamp": "now", "keys": [ self.nodes[0].dumpprivkey(address['address']) ], "watchonly": True }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -8) assert_equal(result[0]['error']['message'], 'Incompatibility found between watchonly and keys') address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], False) assert_equal('timestamp' in address_assert, False) self.log.info("Should import a scriptPubKey with internal and with private key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": address['scriptPubKey'], "timestamp": "now", "keys": [ self.nodes[0].dumpprivkey(address['address']) ], "internal": True }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], True) assert_equal(address_assert['timestamp'], timestamp) self.log.info("Should not import a scriptPubKey without internal and with private key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": address['scriptPubKey'], "timestamp": "now", "keys": [ self.nodes[0].dumpprivkey(address['address']) ] }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -8) assert_equal(result[0]['error']['message'], 'Internal must be set for hex scriptPubKey') address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], False) assert_equal('timestamp' in address_assert, False) sig_address_1 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) sig_address_2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) sig_address_3 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) multi_sig_script = self.nodes[0].createmultisig(2, [sig_address_1['address'], sig_address_2['address'], sig_address_3['pubkey']]) self.nodes[1].generate(100) transactionid = self.nodes[1].sendtoaddress(multi_sig_script['address'], 10.00) self.nodes[1].generate(1) timestamp = self.nodes[1].getblock(self.nodes[1].getbestblockhash())['mediantime'] transaction = self.nodes[1].gettransaction(transactionid) self.log.info("Should import a p2sh") result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": multi_sig_script['address'] }, "timestamp": "now", }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(multi_sig_script['address']) assert_equal(address_assert['isscript'], True) assert_equal(address_assert['iswatchonly'], True) assert_equal(address_assert['timestamp'], timestamp) p2shunspent = self.nodes[1].listunspent(0,999999, [multi_sig_script['address']])[0] assert_equal(p2shunspent['spendable'], False) assert_equal(p2shunspent['solvable'], False) sig_address_1 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) sig_address_2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) sig_address_3 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) multi_sig_script = self.nodes[0].createmultisig(2, [sig_address_1['address'], sig_address_2['address'], sig_address_3['pubkey']]) self.nodes[1].generate(100) transactionid = self.nodes[1].sendtoaddress(multi_sig_script['address'], 10.00) self.nodes[1].generate(1) timestamp = self.nodes[1].getblock(self.nodes[1].getbestblockhash())['mediantime'] transaction = self.nodes[1].gettransaction(transactionid) self.log.info("Should import a p2sh with respective redeem script") result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": multi_sig_script['address'] }, "timestamp": "now", "redeemscript": multi_sig_script['redeemScript'] }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(multi_sig_script['address']) assert_equal(address_assert['timestamp'], timestamp) p2shunspent = self.nodes[1].listunspent(0,999999, [multi_sig_script['address']])[0] assert_equal(p2shunspent['spendable'], False) assert_equal(p2shunspent['solvable'], True) sig_address_1 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) sig_address_2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) sig_address_3 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) multi_sig_script = self.nodes[0].createmultisig(2, [sig_address_1['address'], sig_address_2['address'], sig_address_3['pubkey']]) self.nodes[1].generate(100) transactionid = self.nodes[1].sendtoaddress(multi_sig_script['address'], 10.00) self.nodes[1].generate(1) timestamp = self.nodes[1].getblock(self.nodes[1].getbestblockhash())['mediantime'] transaction = self.nodes[1].gettransaction(transactionid) self.log.info("Should import a p2sh with respective redeem script and private keys") result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": multi_sig_script['address'] }, "timestamp": "now", "redeemscript": multi_sig_script['redeemScript'], "keys": [ self.nodes[0].dumpprivkey(sig_address_1['address']), self.nodes[0].dumpprivkey(sig_address_2['address'])] }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(multi_sig_script['address']) assert_equal(address_assert['timestamp'], timestamp) p2shunspent = self.nodes[1].listunspent(0,999999, [multi_sig_script['address']])[0] assert_equal(p2shunspent['spendable'], False) assert_equal(p2shunspent['solvable'], True) sig_address_1 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) sig_address_2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) sig_address_3 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) multi_sig_script = self.nodes[0].createmultisig(2, [sig_address_1['address'], sig_address_2['address'], sig_address_3['pubkey']]) self.nodes[1].generate(100) transactionid = self.nodes[1].sendtoaddress(multi_sig_script['address'], 10.00) self.nodes[1].generate(1) timestamp = self.nodes[1].getblock(self.nodes[1].getbestblockhash())['mediantime'] transaction = self.nodes[1].gettransaction(transactionid) self.log.info("Should import a p2sh with respective redeem script and private keys") result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": multi_sig_script['address'] }, "timestamp": "now", "redeemscript": multi_sig_script['redeemScript'], "keys": [ self.nodes[0].dumpprivkey(sig_address_1['address']), self.nodes[0].dumpprivkey(sig_address_2['address'])], "watchonly": True }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -8) assert_equal(result[0]['error']['message'], 'Incompatibility found between watchonly and keys') self.log.info("Should not import an address with a wrong public key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) address2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": address['address'] }, "timestamp": "now", "pubkeys": [ address2['pubkey'] ] }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -5) assert_equal(result[0]['error']['message'], 'Consistency check failed') address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], False) assert_equal('timestamp' in address_assert, False) self.log.info("Should not import a scriptPubKey with internal and with a wrong public key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) address2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) request = [{ "scriptPubKey": address['scriptPubKey'], "timestamp": "now", "pubkeys": [ address2['pubkey'] ], "internal": True }] result = self.nodes[1].importmulti(request) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -5) assert_equal(result[0]['error']['message'], 'Consistency check failed') address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], False) assert_equal('timestamp' in address_assert, False) self.log.info("Should not import an address with a wrong private key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) address2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": address['address'] }, "timestamp": "now", "keys": [ self.nodes[0].dumpprivkey(address2['address']) ] }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -5) assert_equal(result[0]['error']['message'], 'Consistency check failed') address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], False) assert_equal('timestamp' in address_assert, False) self.log.info("Should not import a scriptPubKey with internal and with a wrong private key") address = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) address2 = self.nodes[0].validateaddress(self.nodes[0].getnewaddress()) result = self.nodes[1].importmulti([{ "scriptPubKey": address['scriptPubKey'], "timestamp": "now", "keys": [ self.nodes[0].dumpprivkey(address2['address']) ], "internal": True }]) assert_equal(result[0]['success'], False) assert_equal(result[0]['error']['code'], -5) assert_equal(result[0]['error']['message'], 'Consistency check failed') address_assert = self.nodes[1].validateaddress(address['address']) assert_equal(address_assert['iswatchonly'], False) assert_equal(address_assert['ismine'], False) assert_equal('timestamp' in address_assert, False) assert_greater_than(timestamp, watchonly_timestamp) self.log.info("Should replace previously saved watch only timestamp.") result = self.nodes[1].importmulti([{ "scriptPubKey": { "address": watchonly_address, }, "timestamp": "now", }]) assert_equal(result[0]['success'], True) address_assert = self.nodes[1].validateaddress(watchonly_address) assert_equal(address_assert['iswatchonly'], True) assert_equal(address_assert['ismine'], False) assert_equal(address_assert['timestamp'], timestamp) watchonly_timestamp = timestamp self.stop_nodes() self.start_nodes() address_assert = self.nodes[1].validateaddress(watchonly_address) assert_equal(address_assert['iswatchonly'], True) assert_equal(address_assert['ismine'], False) assert_equal(address_assert['timestamp'], watchonly_timestamp) self.log.info("Should throw on invalid or missing timestamp values") assert_raises_message(JSONRPCException, 'Missing required timestamp field for key', self.nodes[1].importmulti, [{ "scriptPubKey": address['scriptPubKey'], }]) assert_raises_message(JSONRPCException, 'Expected number or "now" timestamp value for key. got type string', self.nodes[1].importmulti, [{ "scriptPubKey": address['scriptPubKey'], "timestamp": "", }]) if __name__ == '__main__': ImportMultiTest ().main ()

true

1c45a2de98069c080d2cca90e61524a21453a51c

1,957

py

Python

examples/get-started/play_mp3/example_test.py

kigor302/esp-adf

7feaf6c4b23d2a06850f96c302eebb814516239c

[ "MIT-0" ]

12

2021-04-15T14:15:27.000Z

2022-01-17T03:40:35.000Z

examples/get-started/play_mp3/example_test.py

Tianxiaomo/esp-adf

fae539c3035b2c041f49c5b01cdc4c99038595b0

[ "MIT-0" ]

2

2021-04-03T22:00:11.000Z

2021-10-03T18:27:39.000Z

examples/get-started/play_mp3/example_test.py

Tianxiaomo/esp-adf

fae539c3035b2c041f49c5b01cdc4c99038595b0

[ "MIT-0" ]

4

2021-06-22T10:08:07.000Z

2021-11-17T23:21:04.000Z

import os import sys # this is a test case written with tiny-test-fw. # to run test cases outside tiny-test-fw, # we need to set environment variable `TEST_FW_PATH`, # then get and insert `TEST_FW_PATH` to sys path before import FW module test_fw_path = os.getenv("TEST_FW_PATH") if test_fw_path and test_fw_path not in sys.path: sys.path.insert(0, test_fw_path) auto_test_path = os.getenv("AUTO_TEST_PATH") if auto_test_path and auto_test_path not in sys.path: sys.path.insert(0, auto_test_path) import TinyFW import NormalProject from NormalProject.ProjectDUT import ProDUT from NormalProject.ProjectApp import Example from BasicUtility.RecordAudioFile import AudioRecord import ADFExampleTest @NormalProject.example_test(env_tag="Example_AUDIO_PLAY", ignore=True) @ADFExampleTest.play_test(os.path.join(os.getenv("ADF_PATH"), "examples/get-started/play_mp3/main/adf_music.mp3"), os.path.join(os.getenv("ADF_PATH"), "examples/get-started/play_mp3/main/dest.wav")) def example_test_play_mp3(env, extra_data): dut1 = env.get_dut("play_mp3", "examples/get-started/play_mp3", pro_path=os.getenv("ADF_PATH")) # start test dut1.start_app() dut1.reset() dut1.expect("[ 1 ] Start audio codec chip", timeout=30) dut1.expect("[ 2 ] Create audio pipeline, add all elements to pipeline, and subscribe pipeline event") dut1.expect("[2.1] Create mp3 decoder to decode mp3 file and set custom read callback") dut1.expect("[2.2] Create i2s stream to write data to codec chip") dut1.expect("[2.3] Register all elements to audio pipeline") dut1.expect("[2.4] Link it together [mp3_music_read_cb]-->mp3_decoder-->i2s_stream-->[codec_chip]") dut1.expect("[ 3 ] Setup event listener") dut1.expect("[3.1] Listening event from all elements of pipeline") dut1.expect("[ 4 ] Start audio_pipeline") dut1.expect("[ 5 ] Stop audio_pipeline", timeout=30) if __name__ == '__main__': example_test_play_mp3()

39.938776

114

0.748084

import os import sys test_fw_path = os.getenv("TEST_FW_PATH") if test_fw_path and test_fw_path not in sys.path: sys.path.insert(0, test_fw_path) auto_test_path = os.getenv("AUTO_TEST_PATH") if auto_test_path and auto_test_path not in sys.path: sys.path.insert(0, auto_test_path) import TinyFW import NormalProject from NormalProject.ProjectDUT import ProDUT from NormalProject.ProjectApp import Example from BasicUtility.RecordAudioFile import AudioRecord import ADFExampleTest @NormalProject.example_test(env_tag="Example_AUDIO_PLAY", ignore=True) @ADFExampleTest.play_test(os.path.join(os.getenv("ADF_PATH"), "examples/get-started/play_mp3/main/adf_music.mp3"), os.path.join(os.getenv("ADF_PATH"), "examples/get-started/play_mp3/main/dest.wav")) def example_test_play_mp3(env, extra_data): dut1 = env.get_dut("play_mp3", "examples/get-started/play_mp3", pro_path=os.getenv("ADF_PATH")) dut1.start_app() dut1.reset() dut1.expect("[ 1 ] Start audio codec chip", timeout=30) dut1.expect("[ 2 ] Create audio pipeline, add all elements to pipeline, and subscribe pipeline event") dut1.expect("[2.1] Create mp3 decoder to decode mp3 file and set custom read callback") dut1.expect("[2.2] Create i2s stream to write data to codec chip") dut1.expect("[2.3] Register all elements to audio pipeline") dut1.expect("[2.4] Link it together [mp3_music_read_cb]-->mp3_decoder-->i2s_stream-->[codec_chip]") dut1.expect("[ 3 ] Setup event listener") dut1.expect("[3.1] Listening event from all elements of pipeline") dut1.expect("[ 4 ] Start audio_pipeline") dut1.expect("[ 5 ] Stop audio_pipeline", timeout=30) if __name__ == '__main__': example_test_play_mp3()

true

1c45a4aba3bdd23727ad80971a816dcd80684560

2,390

py

Python

lib/util.py

ks-tec/Hydroponic

d9347f82698841d85c0a45908e8671b36c50ffce

[ "MIT" ]

1

2021-05-27T13:32:45.000Z

lib/util.py

ks-tec/Hydroponic

d9347f82698841d85c0a45908e8671b36c50ffce

[ "MIT" ]

null

lib/util.py

ks-tec/Hydroponic

d9347f82698841d85c0a45908e8671b36c50ffce

[ "MIT" ]

null

# MicroPython utility methods. # # Copyright (c) 2020 ks-tec # # Permission is hereby granted, free of charge, to any person obtaining # a copy of this software and associated documentation files (the "Software"), # to dealin the Software without restriction, including without limitation # the rights to use, copy, modify, merge, publish, distribute, sublicense, # and/or sellcopies of the Software, and to permit persons to whom the Software # is furnished to do so, subject to the following conditions: # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL # THE AUTHORS OR COPYRIGHT HOLDERS BE NOT LIABLE FOR ANY CLAIM, DAMAGES OR # OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, # ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR # OTHER DEALINGS INTHE SOFTWARE. def strtobool(value): """ This method convert string to bool. Return False for values of the keywords "false" "f" "no" "n" "off" "0" or 0. Or, return True for values of the keywords "true" "t" "yes" "y" "on" "1" or 1. Or, othres return None. Args: value : string value Return: Return False for values of the keywords "false" "f" "no" "n" "off" "0" or 0. Or, return True for values of the keywords "true" "t" "yes" "y" "on" "1" or 1. Or, othres return None. Raises: TypeError : The type of parameter is not string. ValueError : The parameter value can not be interpreted as a bool value. """ if type(value) is not str and value not in [0, 1]: raise TypeError("The type of parameter value must be string.") ret_value = None if value.lower() in ["false", "f", "no", "n", "off", "0"] or value == 0: ret_value = False elif value.lower() in ["true", "t", "yes", "y", "on", "1"] or value == 1: ret_value = True else: raise ValueError("not supported bool value.") return ret_value def conv_temperature_unit(value, unit): """ """ if type(value) is str and value.upper() in ["C", "F"]: raise TypeError("the type of paramter unit must be string.") if unit.upper() == "C": pass elif unit.upper() == "F": value = value * 1.8 + 32 else: raise ValueError("not supported temperature unit.") return value

35.147059

82

0.684519

def strtobool(value): if type(value) is not str and value not in [0, 1]: raise TypeError("The type of parameter value must be string.") ret_value = None if value.lower() in ["false", "f", "no", "n", "off", "0"] or value == 0: ret_value = False elif value.lower() in ["true", "t", "yes", "y", "on", "1"] or value == 1: ret_value = True else: raise ValueError("not supported bool value.") return ret_value def conv_temperature_unit(value, unit): if type(value) is str and value.upper() in ["C", "F"]: raise TypeError("the type of paramter unit must be string.") if unit.upper() == "C": pass elif unit.upper() == "F": value = value * 1.8 + 32 else: raise ValueError("not supported temperature unit.") return value

true

1c45a56482a78277a224da1cf5efdb87161f30b9

626

py

Python

manage.py

agamgn/django-Tourism

ee8fae54981d135cbd7ddaf9131eb77ea7b2fb8a

[ "MIT" ]

9

2019-06-30T06:34:22.000Z

2021-11-09T17:21:16.000Z

manage.py

agamgn/django-Tourism

ee8fae54981d135cbd7ddaf9131eb77ea7b2fb8a

[ "MIT" ]

14

2019-12-22T02:04:18.000Z

2022-03-11T23:44:38.000Z

manage.py

agamgn/django-Tourism

ee8fae54981d135cbd7ddaf9131eb77ea7b2fb8a

[ "MIT" ]

3

2019-06-30T06:35:57.000Z

2019-12-18T03:42:43.000Z

#!/usr/bin/env python """Django's command-line utility for administrative tasks.""" import os import sys def main(): os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'treval.settings') try: from django.core.management import execute_from_command_line except ImportError as exc: raise ImportError( "Couldn't import Django. Are you sure it's installed and " "available on your PYTHONPATH environment variable? Did you " "forget to activate a virtual environment?" ) from exc execute_from_command_line(sys.argv) if __name__ == '__main__': main()

28.454545

73

0.682109

import os import sys def main(): os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'treval.settings') try: from django.core.management import execute_from_command_line except ImportError as exc: raise ImportError( "Couldn't import Django. Are you sure it's installed and " "available on your PYTHONPATH environment variable? Did you " "forget to activate a virtual environment?" ) from exc execute_from_command_line(sys.argv) if __name__ == '__main__': main()

true

1c45a58e90e653de1bb431003c78566d25a7d67b

57,074

py

Python

improver/ensemble_copula_coupling/ensemble_copula_coupling.py

VictoriaLouiseS/improver

86470bff973e21fbd5f24e26047871ad3bc2f3db

[ "BSD-3-Clause" ]

null

improver/ensemble_copula_coupling/ensemble_copula_coupling.py

VictoriaLouiseS/improver

86470bff973e21fbd5f24e26047871ad3bc2f3db

[ "BSD-3-Clause" ]

3

2020-04-25T12:55:42.000Z

2020-07-23T11:50:46.000Z

improver/ensemble_copula_coupling/ensemble_copula_coupling.py

Kat-90/improver

a5c31be3430df429ae38e7c16e267fcbc2af1858

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- # ----------------------------------------------------------------------------- # (C) British Crown Copyright 2017-2020 Met Office. # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # * Redistributions of source code must retain the above copyright notice, this # list of conditions and the following disclaimer. # # * Redistributions in binary form must reproduce the above copyright notice, # this list of conditions and the following disclaimer in the documentation # and/or other materials provided with the distribution. # # * Neither the name of the copyright holder nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE # ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE # LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR # CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF # SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS # INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN # CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) # ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE # POSSIBILITY OF SUCH DAMAGE. """ This module defines the plugins required for Ensemble Copula Coupling. """ import warnings import iris import numpy as np from iris.exceptions import CoordinateNotFoundError, InvalidCubeError from scipy import stats from improver import BasePlugin from improver.calibration.utilities import convert_cube_data_to_2d from improver.ensemble_copula_coupling.utilities import ( choose_set_of_percentiles, concatenate_2d_array_with_2d_array_endpoints, create_cube_with_percentiles, get_bounds_of_distribution, insert_lower_and_upper_endpoint_to_1d_array, restore_non_percentile_dimensions, ) from improver.metadata.probabilistic import ( extract_diagnostic_name, find_percentile_coordinate, find_threshold_coordinate, ) from improver.utilities.cube_checker import ( check_cube_coordinates, check_for_x_and_y_axes, ) from improver.utilities.cube_manipulation import ( MergeCubes, enforce_coordinate_ordering, get_dim_coord_names, ) from improver.utilities.indexing_operations import choose class RebadgePercentilesAsRealizations(BasePlugin): """ Class to rebadge percentiles as ensemble realizations. This will allow the quantisation to percentiles to be completed, without a subsequent EnsembleReordering step to restore spatial correlations, if required. """ @staticmethod def process(cube, ensemble_realization_numbers=None): """ Rebadge percentiles as ensemble realizations. The ensemble realization numbering will depend upon the number of percentiles in the input cube i.e. 0, 1, 2, 3, ..., n-1, if there are n percentiles. Args: cube (iris.cube.Cube): Cube containing a percentile coordinate, which will be rebadged as ensemble realization. ensemble_realization_numbers (numpy.ndarray): An array containing the ensemble numbers required in the output realization coordinate. Default is None, meaning the realization coordinate will be numbered 0, 1, 2 ... n-1 for n percentiles on the input cube. Raises: InvalidCubeError: If the realization coordinate already exists on the cube. """ percentile_coord_name = find_percentile_coordinate(cube).name() if ensemble_realization_numbers is None: ensemble_realization_numbers = np.arange( len(cube.coord(percentile_coord_name).points), dtype=np.int32 ) cube.coord(percentile_coord_name).points = ensemble_realization_numbers # we can't rebadge if the realization coordinate already exists: try: realization_coord = cube.coord("realization") except CoordinateNotFoundError: realization_coord = None if realization_coord: raise InvalidCubeError( "Cannot rebadge percentile coordinate to realization " "coordinate because a realization coordinate already exists." ) cube.coord(percentile_coord_name).rename("realization") cube.coord("realization").units = "1" cube.coord("realization").points = cube.coord("realization").points.astype( np.int32 ) return cube class ResamplePercentiles(BasePlugin): """ Class for resampling percentiles from an existing set of percentiles. In combination with the Ensemble Reordering plugin, this is a variant of Ensemble Copula Coupling. This class includes the ability to linearly interpolate from an input set of percentiles to a different output set of percentiles. """ def __init__(self, ecc_bounds_warning=False): """ Initialise the class. Args: ecc_bounds_warning (bool): If true and ECC bounds are exceeded by the percentile values, a warning will be generated rather than an exception. Default value is FALSE. """ self.ecc_bounds_warning = ecc_bounds_warning def _add_bounds_to_percentiles_and_forecast_at_percentiles( self, percentiles, forecast_at_percentiles, bounds_pairing ): """ Padding of the lower and upper bounds of the percentiles for a given phenomenon, and padding of forecast values using the constant lower and upper bounds. Args: percentiles (numpy.ndarray): Array of percentiles from a Cumulative Distribution Function. forecast_at_percentiles (numpy.ndarray): Array containing the underlying forecast values at each percentile. bounds_pairing (tuple): Lower and upper bound to be used as the ends of the cumulative distribution function. Raises: ValueError: If the percentile points are outside the ECC bounds and self.ecc_bounds_warning is False. ValueError: If the percentiles are not in ascending order. Warns: Warning: If the percentile points are outside the ECC bounds and self.ecc_bounds_warning is True. """ lower_bound, upper_bound = bounds_pairing percentiles = insert_lower_and_upper_endpoint_to_1d_array(percentiles, 0, 100) forecast_at_percentiles_with_endpoints = concatenate_2d_array_with_2d_array_endpoints( forecast_at_percentiles, lower_bound, upper_bound ) if np.any(np.diff(forecast_at_percentiles_with_endpoints) < 0): out_of_bounds_vals = forecast_at_percentiles_with_endpoints[ np.where(np.diff(forecast_at_percentiles_with_endpoints) < 0) ] msg = ( "Forecast values exist that fall outside the expected extrema " "values that are defined as bounds in " "ensemble_copula_coupling/constants.py. " "Applying the extrema values as end points to the distribution " "would result in non-monotonically increasing values. " "The defined extremes are {}, whilst the following forecast " "values exist outside this range: {}.".format( bounds_pairing, out_of_bounds_vals ) ) if self.ecc_bounds_warning: warn_msg = msg + ( " The percentile values that have " "exceeded the existing bounds will be used " "as new bounds." ) warnings.warn(warn_msg) if upper_bound < forecast_at_percentiles_with_endpoints.max(): upper_bound = forecast_at_percentiles_with_endpoints.max() if lower_bound > forecast_at_percentiles_with_endpoints.min(): lower_bound = forecast_at_percentiles_with_endpoints.min() forecast_at_percentiles_with_endpoints = concatenate_2d_array_with_2d_array_endpoints( forecast_at_percentiles, lower_bound, upper_bound ) else: raise ValueError(msg) if np.any(np.diff(percentiles) < 0): msg = ( "The percentiles must be in ascending order." "The input percentiles were {}".format(percentiles) ) raise ValueError(msg) return percentiles, forecast_at_percentiles_with_endpoints def _interpolate_percentiles( self, forecast_at_percentiles, desired_percentiles, bounds_pairing, percentile_coord_name, ): """ Interpolation of forecast for a set of percentiles from an initial set of percentiles to a new set of percentiles. This is constructed by linearly interpolating between the original set of percentiles to a new set of percentiles. Args: forecast_at_percentiles (iris.cube.Cube): Cube containing a percentile coordinate. desired_percentiles (numpy.ndarray): Array of the desired percentiles. bounds_pairing (tuple): Lower and upper bound to be used as the ends of the cumulative distribution function. percentile_coord_name (str): Name of required percentile coordinate. Returns: iris.cube.Cube: Cube containing values for the required diagnostic e.g. air_temperature at the required percentiles. """ original_percentiles = forecast_at_percentiles.coord( percentile_coord_name ).points # Ensure that the percentile dimension is first, so that the # conversion to a 2d array produces data in the desired order. enforce_coordinate_ordering(forecast_at_percentiles, percentile_coord_name) forecast_at_reshaped_percentiles = convert_cube_data_to_2d( forecast_at_percentiles, coord=percentile_coord_name ) ( original_percentiles, forecast_at_reshaped_percentiles, ) = self._add_bounds_to_percentiles_and_forecast_at_percentiles( original_percentiles, forecast_at_reshaped_percentiles, bounds_pairing ) forecast_at_interpolated_percentiles = np.empty( (len(desired_percentiles), forecast_at_reshaped_percentiles.shape[0]), dtype=np.float32, ) for index in range(forecast_at_reshaped_percentiles.shape[0]): forecast_at_interpolated_percentiles[:, index] = np.interp( desired_percentiles, original_percentiles, forecast_at_reshaped_percentiles[index, :], ) # Reshape forecast_at_percentiles, so the percentiles dimension is # first, and any other dimension coordinates follow. forecast_at_percentiles_data = restore_non_percentile_dimensions( forecast_at_interpolated_percentiles, next(forecast_at_percentiles.slices_over(percentile_coord_name)), len(desired_percentiles), ) template_cube = next(forecast_at_percentiles.slices_over(percentile_coord_name)) template_cube.remove_coord(percentile_coord_name) percentile_cube = create_cube_with_percentiles( desired_percentiles, template_cube, forecast_at_percentiles_data, ) return percentile_cube def process( self, forecast_at_percentiles, no_of_percentiles=None, sampling="quantile" ): """ 1. Creates a list of percentiles. 2. Accesses the lower and upper bound pair of the forecast values, in order to specify lower and upper bounds for the percentiles. 3. Interpolate the percentile coordinate into an alternative set of percentiles using linear interpolation. Args: forecast_at_percentiles (iris.cube.Cube): Cube expected to contain a percentile coordinate. no_of_percentiles (int or None): Number of percentiles If None, the number of percentiles within the input forecast_at_percentiles cube is used as the number of percentiles. sampling (str): Type of sampling of the distribution to produce a set of percentiles e.g. quantile or random. Accepted options for sampling are: * Quantile: A regular set of equally-spaced percentiles aimed at dividing a Cumulative Distribution Function into blocks of equal probability. * Random: A random set of ordered percentiles. Returns: iris.cube.Cube: Cube with forecast values at the desired set of percentiles. The percentile coordinate is always the zeroth dimension. """ percentile_coord = find_percentile_coordinate(forecast_at_percentiles) if no_of_percentiles is None: no_of_percentiles = len( forecast_at_percentiles.coord(percentile_coord).points ) percentiles = choose_set_of_percentiles(no_of_percentiles, sampling=sampling) cube_units = forecast_at_percentiles.units bounds_pairing = get_bounds_of_distribution( forecast_at_percentiles.name(), cube_units ) forecast_at_percentiles = self._interpolate_percentiles( forecast_at_percentiles, percentiles, bounds_pairing, percentile_coord.name(), ) return forecast_at_percentiles class ConvertProbabilitiesToPercentiles(BasePlugin): """ Class for generating percentiles from probabilities. In combination with the Ensemble Reordering plugin, this is a variant Ensemble Copula Coupling. This class includes the ability to interpolate between probabilities specified using multiple thresholds in order to generate the percentiles, see Figure 1 from Flowerdew, 2014. Scientific Reference: Flowerdew, J., 2014. Calibrated ensemble reliability whilst preserving spatial structure. Tellus Series A, Dynamic Meteorology and Oceanography, 66, 22662. """ def __init__(self, ecc_bounds_warning=False): """ Initialise the class. Args: ecc_bounds_warning (bool): If true and ECC bounds are exceeded by the percentile values, a warning will be generated rather than an exception. Default value is FALSE. """ self.ecc_bounds_warning = ecc_bounds_warning def _add_bounds_to_thresholds_and_probabilities( self, threshold_points, probabilities_for_cdf, bounds_pairing ): """ Padding of the lower and upper bounds of the distribution for a given phenomenon for the threshold_points, and padding of probabilities of 0 and 1 to the forecast probabilities. Args: threshold_points (numpy.ndarray): Array of threshold values used to calculate the probabilities. probabilities_for_cdf (numpy.ndarray): Array containing the probabilities used for constructing an cumulative distribution function i.e. probabilities below threshold. bounds_pairing (tuple): Lower and upper bound to be used as the ends of the cumulative distribution function. Returns: (tuple): tuple containing: **threshold_points** (numpy.ndarray): Array of threshold values padded with the lower and upper bound of the distribution. **probabilities_for_cdf** (numpy.ndarray): Array containing the probabilities padded with 0 and 1 at each end. Raises: ValueError: If the thresholds exceed the ECC bounds for the diagnostic and self.ecc_bounds_warning is False. Warns: Warning: If the thresholds exceed the ECC bounds for the diagnostic and self.ecc_bounds_warning is True. """ lower_bound, upper_bound = bounds_pairing threshold_points_with_endpoints = insert_lower_and_upper_endpoint_to_1d_array( threshold_points, lower_bound, upper_bound ) probabilities_for_cdf = concatenate_2d_array_with_2d_array_endpoints( probabilities_for_cdf, 0, 1 ) if np.any(np.diff(threshold_points_with_endpoints) < 0): msg = ( "The calculated threshold values {} are not in ascending " "order as required for the cumulative distribution " "function (CDF). This is due to the threshold values " "exceeding the range given by the ECC bounds {}.".format( threshold_points_with_endpoints, bounds_pairing ) ) # If ecc_bounds_warning has been set, generate a warning message # rather than raising an exception so that subsequent processing # can continue. Then apply the new bounds as necessary to # ensure the threshold values and endpoints are in ascending # order and avoid problems further along the processing chain. if self.ecc_bounds_warning: warn_msg = msg + ( " The threshold points that have " "exceeded the existing bounds will be used " "as new bounds." ) warnings.warn(warn_msg) if upper_bound < max(threshold_points_with_endpoints): upper_bound = max(threshold_points_with_endpoints) if lower_bound > min(threshold_points_with_endpoints): lower_bound = min(threshold_points_with_endpoints) threshold_points_with_endpoints = insert_lower_and_upper_endpoint_to_1d_array( threshold_points, lower_bound, upper_bound ) else: raise ValueError(msg) return threshold_points_with_endpoints, probabilities_for_cdf def _probabilities_to_percentiles( self, forecast_probabilities, percentiles, bounds_pairing ): """ Conversion of probabilities to percentiles through the construction of an cumulative distribution function. This is effectively constructed by linear interpolation from the probabilities associated with each threshold to a set of percentiles. Args: forecast_probabilities (iris.cube.Cube): Cube with a threshold coordinate. percentiles (numpy.ndarray): Array of percentiles, at which the corresponding values will be calculated. bounds_pairing (tuple): Lower and upper bound to be used as the ends of the cumulative distribution function. Returns: iris.cube.Cube: Cube containing values for the required diagnostic e.g. air_temperature at the required percentiles. Raises: NotImplementedError: If the threshold coordinate has an spp__relative_to_threshold attribute that is not either "above" or "below". Warns: Warning: If the probability values are not ascending, so the resulting cdf is not monotonically increasing. """ threshold_coord = find_threshold_coordinate(forecast_probabilities) threshold_unit = threshold_coord.units threshold_points = threshold_coord.points # Ensure that the percentile dimension is first, so that the # conversion to a 2d array produces data in the desired order. enforce_coordinate_ordering(forecast_probabilities, threshold_coord.name()) prob_slices = convert_cube_data_to_2d( forecast_probabilities, coord=threshold_coord.name() ) # The requirement below for a monotonically changing probability # across thresholds can be thwarted by precision errors of order 1E-10, # as such, here we round to a precision of 9 decimal places. prob_slices = np.around(prob_slices, 9) # Invert probabilities for data thresholded above thresholds. relation = find_threshold_coordinate(forecast_probabilities).attributes[ "spp__relative_to_threshold" ] if relation == "above": probabilities_for_cdf = 1 - prob_slices elif relation == "below": probabilities_for_cdf = prob_slices else: msg = ( "Probabilities to percentiles only implemented for " "thresholds above or below a given value." "The relation to threshold is given as {}".format(relation) ) raise NotImplementedError(msg) ( threshold_points, probabilities_for_cdf, ) = self._add_bounds_to_thresholds_and_probabilities( threshold_points, probabilities_for_cdf, bounds_pairing ) if np.any(np.diff(probabilities_for_cdf) < 0): msg = ( "The probability values used to construct the " "Cumulative Distribution Function (CDF) " "must be ascending i.e. in order to yield " "a monotonically increasing CDF." "The probabilities are {}".format(probabilities_for_cdf) ) warnings.warn(msg) # Convert percentiles into fractions. percentiles_as_fractions = np.array( [x / 100.0 for x in percentiles], dtype=np.float32 ) forecast_at_percentiles = ( # pylint: disable=unsubscriptable-object np.empty( (len(percentiles), probabilities_for_cdf.shape[0]), dtype=np.float32 ) ) # pylint: disable=unsubscriptable-object for index in range(probabilities_for_cdf.shape[0]): forecast_at_percentiles[:, index] = np.interp( percentiles_as_fractions, probabilities_for_cdf[index, :], threshold_points, ) # Reshape forecast_at_percentiles, so the percentiles dimension is # first, and any other dimension coordinates follow. forecast_at_percentiles = restore_non_percentile_dimensions( forecast_at_percentiles, next(forecast_probabilities.slices_over(threshold_coord)), len(percentiles), ) template_cube = next(forecast_probabilities.slices_over(threshold_coord.name())) template_cube.rename(extract_diagnostic_name(template_cube.name())) template_cube.remove_coord(threshold_coord.name()) percentile_cube = create_cube_with_percentiles( percentiles, template_cube, forecast_at_percentiles, cube_unit=threshold_unit, ) return percentile_cube def process( self, forecast_probabilities, no_of_percentiles=None, percentiles=None, sampling="quantile", ): """ 1. Concatenates cubes with a threshold coordinate. 2. Creates a list of percentiles. 3. Accesses the lower and upper bound pair to find the ends of the cumulative distribution function. 4. Convert the threshold coordinate into values at a set of percentiles using linear interpolation, see Figure 1 from Flowerdew, 2014. Args: forecast_probabilities (iris.cube.Cube): Cube containing a threshold coordinate. no_of_percentiles (int): Number of percentiles. If None and percentiles is not set, the number of thresholds within the input forecast_probabilities cube is used as the number of percentiles. This argument is mutually exclusive with percentiles. percentiles (list of float): The desired percentile values in the interval [0, 100]. This argument is mutually exclusive with no_of_percentiles. sampling (str): Type of sampling of the distribution to produce a set of percentiles e.g. quantile or random. Accepted options for sampling are: * Quantile: A regular set of equally-spaced percentiles aimed at dividing a Cumulative Distribution Function into blocks of equal probability. * Random: A random set of ordered percentiles. Returns: iris.cube.Cube: Cube with forecast values at the desired set of percentiles. The threshold coordinate is always the zeroth dimension. Raises: ValueError: If both no_of_percentiles and percentiles are provided """ if no_of_percentiles is not None and percentiles is not None: raise ValueError( "Cannot specify both no_of_percentiles and percentiles to " "{}".format(self.__class__.__name__) ) threshold_coord = find_threshold_coordinate(forecast_probabilities) phenom_name = extract_diagnostic_name(forecast_probabilities.name()) if no_of_percentiles is None: no_of_percentiles = len( forecast_probabilities.coord(threshold_coord.name()).points ) if percentiles is None: percentiles = choose_set_of_percentiles( no_of_percentiles, sampling=sampling ) elif not isinstance(percentiles, (tuple, list)): percentiles = [percentiles] percentiles = np.array(percentiles, dtype=np.float32) cube_units = forecast_probabilities.coord(threshold_coord.name()).units bounds_pairing = get_bounds_of_distribution(phenom_name, cube_units) # If a cube still has multiple realizations, slice over these to reduce # the memory requirements into manageable chunks. try: slices_over_realization = forecast_probabilities.slices_over("realization") except CoordinateNotFoundError: slices_over_realization = [forecast_probabilities] cubelist = iris.cube.CubeList([]) for cube_realization in slices_over_realization: cubelist.append( self._probabilities_to_percentiles( cube_realization, percentiles, bounds_pairing ) ) forecast_at_percentiles = cubelist.merge_cube() return forecast_at_percentiles class ConvertLocationAndScaleParameters: """ Base Class to support the plugins that compute percentiles and probabilities from the location and scale parameters. """ def __init__(self, distribution="norm", shape_parameters=None): """ Initialise the class. In order to construct percentiles or probabilities from the location or scale parameter, the distribution for the resulting output needs to be selected. For use with the outputs from EMOS, where it has been assumed that the outputs from minimising the CRPS follow a particular distribution, then the same distribution should be selected, as used for the CRPS minimisation. The conversion to percentiles and probabilities from the location and scale parameter relies upon functionality within scipy.stats. Args: distribution (str): Name of a distribution supported by scipy.stats. shape_parameters (numpy.ndarray or None): For use with distributions in scipy.stats (e.g. truncnorm) that require the specification of shape parameters to be able to define the shape of the distribution. For the truncated normal distribution, the shape parameters should be appropriate for the distribution constructed from the location and scale parameters provided. Please note that for use with :meth:`~improver.calibration.\ ensemble_calibration.ContinuousRankedProbabilityScoreMinimisers.\ calculate_truncated_normal_crps`, the shape parameters for a truncated normal distribution with a lower bound of zero should be [0, np.inf]. """ try: self.distribution = getattr(stats, distribution) except AttributeError as err: msg = ( "The distribution requested {} is not a valid distribution " "in scipy.stats. {}".format(distribution, err) ) raise AttributeError(msg) if shape_parameters is None: if self.distribution.name == "truncnorm": raise ValueError( "For the truncated normal distribution, " "shape parameters must be specified." ) shape_parameters = [] self.shape_parameters = shape_parameters def __repr__(self): """Represent the configured plugin instance as a string.""" result = ( "<ConvertLocationAndScaleParameters: distribution: {}; " "shape_parameters: {}>" ) return result.format(self.distribution.name, self.shape_parameters) def _rescale_shape_parameters(self, location_parameter, scale_parameter): """ Rescale the shape parameters for the desired location and scale parameters for the truncated normal distribution. The shape parameters for any other distribution will remain unchanged. For the truncated normal distribution, if the shape parameters are not rescaled, then :data:`scipy.stats.truncnorm` will assume that the shape parameters are appropriate for a standard normal distribution. As the aim is to construct a distribution using specific values for the location and scale parameters, the assumption of a standard normal distribution is not appropriate. Therefore the shape parameters are rescaled using the equations: .. math:: a\\_rescaled = (a - location\\_parameter)/scale\\_parameter b\\_rescaled = (b - location\\_parameter)/scale\\_parameter Please see :data:`scipy.stats.truncnorm` for some further information. Args: location_parameter (numpy.ndarray): Location parameter to be used to scale the shape parameters. scale_parameter (numpy.ndarray): Scale parameter to be used to scale the shape parameters. """ if self.distribution.name == "truncnorm": rescaled_values = [] for value in self.shape_parameters: rescaled_values.append((value - location_parameter) / scale_parameter) self.shape_parameters = rescaled_values class ConvertLocationAndScaleParametersToPercentiles( BasePlugin, ConvertLocationAndScaleParameters ): """ Plugin focusing on generating percentiles from location and scale parameters. In combination with the EnsembleReordering plugin, this is Ensemble Copula Coupling. """ def __repr__(self): """Represent the configured plugin instance as a string.""" result = ( "<ConvertLocationAndScaleParametersToPercentiles: " "distribution: {}; shape_parameters: {}>" ) return result.format(self.distribution.name, self.shape_parameters) def _location_and_scale_parameters_to_percentiles( self, location_parameter, scale_parameter, template_cube, percentiles ): """ Function returning percentiles based on the supplied location and scale parameters. Args: location_parameter (iris.cube.Cube): Location parameter of calibrated distribution. scale_parameter (iris.cube.Cube): Scale parameter of the calibrated distribution. template_cube (iris.cube.Cube): Template cube containing either a percentile or realization coordinate. All coordinates apart from the percentile or realization coordinate will be copied from the template cube. Metadata will also be copied from this cube. percentiles (list): Percentiles at which to calculate the value of the phenomenon at. Returns: iris.cube.Cube: Cube containing the values for the phenomenon at each of the percentiles requested. Raises: ValueError: If any of the resulting percentile values are nans and these nans are not caused by a scale parameter of zero. """ # Remove any mask that may be applied to location and scale parameters # and replace with ones location_data = np.ma.filled(location_parameter.data, 1).flatten() scale_data = np.ma.filled(scale_parameter.data, 1).flatten() # Convert percentiles into fractions. percentiles = np.array([x / 100.0 for x in percentiles], dtype=np.float32) result = np.zeros((len(percentiles), location_data.shape[0]), dtype=np.float32) self._rescale_shape_parameters(location_data, np.sqrt(scale_data)) percentile_method = self.distribution( *self.shape_parameters, loc=location_data, scale=np.sqrt(scale_data) ) # Loop over percentiles, and use the distribution as the # "percentile_method" with the location and scale parameter to # calculate the values at each percentile. for index, percentile in enumerate(percentiles): percentile_list = np.repeat(percentile, len(location_data)) result[index, :] = percentile_method.ppf(percentile_list) # If percent point function (PPF) returns NaNs, fill in # mean instead of NaN values. NaN will only be generated if the # variance is zero. Therefore, if the variance is zero, the mean # value is used for all gridpoints with a NaN. if np.any(scale_data == 0): nan_index = np.argwhere(np.isnan(result[index, :])) result[index, nan_index] = location_data[nan_index] if np.any(np.isnan(result)): msg = ( "NaNs are present within the result for the {} " "percentile. Unable to calculate the percent point " "function." ) raise ValueError(msg) # Convert percentiles back into percentages. percentiles = [x * 100.0 for x in percentiles] # Reshape forecast_at_percentiles, so the percentiles dimension is # first, and any other dimension coordinates follow. result = result.reshape((len(percentiles),) + location_parameter.data.shape) for prob_coord_name in ["realization", "percentile"]: if template_cube.coords(prob_coord_name, dim_coords=True): prob_coord = template_cube.coord(prob_coord_name) template_slice = next(template_cube.slices_over(prob_coord)) template_slice.remove_coord(prob_coord) percentile_cube = create_cube_with_percentiles( percentiles, template_slice, result ) # Define a mask to be reapplied later mask = np.logical_or( np.ma.getmaskarray(location_parameter.data), np.ma.getmaskarray(scale_parameter.data), ) # Make the mask defined above fit the data size and then apply to the # percentile cube. mask_array = np.stack([mask] * len(percentiles)) percentile_cube.data = np.ma.masked_where(mask_array, percentile_cube.data) # Remove cell methods associated with finding the ensemble mean percentile_cube.cell_methods = {} return percentile_cube def process( self, location_parameter, scale_parameter, template_cube, no_of_percentiles=None, percentiles=None, ): """ Generate ensemble percentiles from the location and scale parameters. Args: location_parameter (iris.cube.Cube): Cube containing the location parameters. scale_parameter (iris.cube.Cube): Cube containing the scale parameters. template_cube (iris.cube.Cube): Template cube containing either a percentile or realization coordinate. All coordinates apart from the percentile or realization coordinate will be copied from the template cube. Metadata will also be copied from this cube. no_of_percentiles (int): Integer defining the number of percentiles that will be calculated from the location and scale parameters. percentiles (list): List of percentiles that will be generated from the location and scale parameters provided. Returns: iris.cube.Cube: Cube for calibrated percentiles. The percentile coordinate is always the zeroth dimension. Raises: ValueError: Ensure that it is not possible to supply "no_of_percentiles" and "percentiles" simultaneously as keyword arguments. """ if no_of_percentiles and percentiles: msg = ( "Please specify either the number of percentiles or " "provide a list of percentiles. The number of percentiles " "provided was {} and the list of percentiles " "provided was {}".format(no_of_percentiles, percentiles) ) raise ValueError(msg) if no_of_percentiles: percentiles = choose_set_of_percentiles(no_of_percentiles) calibrated_forecast_percentiles = self._location_and_scale_parameters_to_percentiles( location_parameter, scale_parameter, template_cube, percentiles ) return calibrated_forecast_percentiles class ConvertLocationAndScaleParametersToProbabilities( BasePlugin, ConvertLocationAndScaleParameters ): """ Plugin to generate probabilities relative to given thresholds from the location and scale parameters of a distribution. """ def __repr__(self): """Represent the configured plugin instance as a string.""" result = ( "<ConvertLocationAndScaleParametersToProbabilities: " "distribution: {}; shape_parameters: {}>" ) return result.format(self.distribution.name, self.shape_parameters) def _check_template_cube(self, cube): """ The template cube is expected to contain a leading threshold dimension followed by spatial (y/x) dimensions. This check raises an error if this is not the case. If the cube contains the expected dimensions, a threshold leading order is enforced. Args: cube (iris.cube.Cube): A cube whose dimensions are checked to ensure they match what is expected. Raises: ValueError: If cube is not of the expected dimensions. """ check_for_x_and_y_axes(cube, require_dim_coords=True) dim_coords = get_dim_coord_names(cube) msg = ( "{} expects a cube with only a leading threshold dimension, " "followed by spatial (y/x) dimensions. " "Got dimensions: {}".format(self.__class__.__name__, dim_coords) ) try: threshold_coord = find_threshold_coordinate(cube) except CoordinateNotFoundError: raise ValueError(msg) if len(dim_coords) < 4: enforce_coordinate_ordering(cube, threshold_coord.name()) return raise ValueError(msg) @staticmethod def _check_unit_compatibility( location_parameter, scale_parameter, probability_cube_template ): """ The location parameter, scale parameters, and threshold values come from three different cubes. They should all be in the same base unit, with the units of the scale parameter being the squared units of the location parameter and threshold values. This is a sanity check to ensure the units are as expected, converting units of the location parameter and scale parameter if possible. Args: location_parameter (iris.cube.Cube): Cube of location parameter values. scale_parameter (iris.cube.Cube): Cube of scale parameter values. probability_cube_template (iris.cube.Cube): Cube containing threshold values. Raises: ValueError: If units of input cubes are not compatible. """ threshold_units = find_threshold_coordinate(probability_cube_template).units try: location_parameter.convert_units(threshold_units) scale_parameter.convert_units(threshold_units ** 2) except ValueError as err: msg = ( "Error: {} This is likely because the mean " "variance and template cube threshold units are " "not equivalent/compatible.".format(err) ) raise ValueError(msg) def _location_and_scale_parameters_to_probabilities( self, location_parameter, scale_parameter, probability_cube_template ): """ Function returning probabilities relative to provided thresholds based on the supplied location and scale parameters. Args: location_parameter (iris.cube.Cube): Predictor for the calibrated forecast location parameter. scale_parameter (iris.cube.Cube): Scale parameter for the calibrated forecast. probability_cube_template (iris.cube.Cube): A probability cube that has a threshold coordinate, where the probabilities are defined as above or below the threshold by the spp__relative_to_threshold attribute. This cube matches the desired output cube format. Returns: iris.cube.Cube: Cube containing the data expressed as probabilities relative to the provided thresholds in the way described by spp__relative_to_threshold. """ # Define a mask to be reapplied later loc_mask = np.ma.getmaskarray(location_parameter.data) scale_mask = np.ma.getmaskarray(scale_parameter.data) mask = np.logical_or(loc_mask, scale_mask) # Remove any mask that may be applied to location and scale parameters # and replace with ones location_parameter.data = np.ma.filled(location_parameter.data, 1) scale_parameter.data = np.ma.filled(scale_parameter.data, 1) thresholds = find_threshold_coordinate(probability_cube_template).points relative_to_threshold = find_threshold_coordinate( probability_cube_template ).attributes["spp__relative_to_threshold"] self._rescale_shape_parameters( location_parameter.data.flatten(), np.sqrt(scale_parameter.data).flatten() ) # Loop over thresholds, and use the specified distribution with the # location and scale parameter to calculate the probabilities relative # to each threshold. probabilities = np.empty_like(probability_cube_template.data) distribution = self.distribution( *self.shape_parameters, loc=location_parameter.data.flatten(), scale=np.sqrt(scale_parameter.data.flatten()), ) probability_method = distribution.cdf if relative_to_threshold == "above": probability_method = distribution.sf for index, threshold in enumerate(thresholds): # pylint: disable=unsubscriptable-object probabilities[index, ...] = np.reshape( probability_method(threshold), probabilities.shape[1:] ) probability_cube = probability_cube_template.copy(data=probabilities) # Make the mask defined above fit the data size and then apply to the # probability cube. mask_array = np.array([mask] * len(probabilities)) probability_cube.data = np.ma.masked_where(mask_array, probability_cube.data) return probability_cube def process(self, location_parameter, scale_parameter, probability_cube_template): """ Generate probabilities from the location and scale parameters of the distribution. Args: location_parameter (iris.cube.Cube): Cube containing the location parameters. scale_parameter (iris.cube.Cube): Cube containing the scale parameters. probability_cube_template (iris.cube.Cube): A probability cube that has a threshold coordinate, where the probabilities are defined as above or below the threshold by the spp__relative_to_threshold attribute. This cube matches the desired output cube format. Returns: iris.cube.Cube: A cube of diagnostic data expressed as probabilities relative to the thresholds found in the probability_cube_template. """ self._check_template_cube(probability_cube_template) self._check_unit_compatibility( location_parameter, scale_parameter, probability_cube_template ) probability_cube = self._location_and_scale_parameters_to_probabilities( location_parameter, scale_parameter, probability_cube_template ) return probability_cube class EnsembleReordering(BasePlugin): """ Plugin for applying the reordering step of Ensemble Copula Coupling, in order to generate ensemble realizations with multivariate structure from percentiles. The percentiles are assumed to be in ascending order. Reference: Schefzik, R., Thorarinsdottir, T.L. & Gneiting, T., 2013. Uncertainty Quantification in Complex Simulation Models Using Ensemble Copula Coupling. Statistical Science, 28(4), pp.616-640. """ @staticmethod def _recycle_raw_ensemble_realizations( post_processed_forecast_percentiles, raw_forecast_realizations, percentile_coord_name, ): """ Function to determine whether there is a mismatch between the number of percentiles and the number of raw forecast realizations. If more percentiles are requested than ensemble realizations, then the ensemble realizations are recycled. This assumes that the identity of the ensemble realizations within the raw ensemble forecast is random, such that the raw ensemble realizations are exchangeable. If fewer percentiles are requested than ensemble realizations, then only the first n ensemble realizations are used. Args: post_processed_forecast_percentiles (iris.cube.Cube): Cube for post-processed percentiles. The percentiles are assumed to be in ascending order. raw_forecast_realizations (iris.cube.Cube): Cube containing the raw (not post-processed) forecasts. percentile_coord_name (str): Name of required percentile coordinate. Returns: iris cube.Cube: Cube for the raw ensemble forecast, where the raw ensemble realizations have either been recycled or constrained, depending upon the number of percentiles present in the post-processed forecast cube. """ plen = len( post_processed_forecast_percentiles.coord(percentile_coord_name).points ) mlen = len(raw_forecast_realizations.coord("realization").points) if plen == mlen: pass else: raw_forecast_realizations_extended = iris.cube.CubeList() realization_list = [] mpoints = raw_forecast_realizations.coord("realization").points # Loop over the number of percentiles and finding the # corresponding ensemble realization number. The ensemble # realization numbers are recycled e.g. 1, 2, 3, 1, 2, 3, etc. for index in range(plen): realization_list.append(mpoints[index % len(mpoints)]) # Assume that the ensemble realizations are ascending linearly. new_realization_numbers = realization_list[0] + list(range(plen)) # Extract the realizations required in the realization_list from # the raw_forecast_realizations. Edit the realization number as # appropriate and append to a cubelist containing rebadged # raw ensemble realizations. for realization, index in zip(realization_list, new_realization_numbers): constr = iris.Constraint(realization=realization) raw_forecast_realization = raw_forecast_realizations.extract(constr) raw_forecast_realization.coord("realization").points = index raw_forecast_realizations_extended.append(raw_forecast_realization) raw_forecast_realizations = MergeCubes()( raw_forecast_realizations_extended, slice_over_realization=True ) return raw_forecast_realizations @staticmethod def rank_ecc( post_processed_forecast_percentiles, raw_forecast_realizations, random_ordering=False, random_seed=None, ): """ Function to apply Ensemble Copula Coupling. This ranks the post-processed forecast realizations based on a ranking determined from the raw forecast realizations. Args: post_processed_forecast_percentiles (iris.cube.Cube): Cube for post-processed percentiles. The percentiles are assumed to be in ascending order. raw_forecast_realizations (iris.cube.Cube): Cube containing the raw (not post-processed) forecasts. The probabilistic dimension is assumed to be the zeroth dimension. random_ordering (bool): If random_ordering is True, the post-processed forecasts are reordered randomly, rather than using the ordering of the raw ensemble. random_seed (int or None): If random_seed is an integer, the integer value is used for the random seed. If random_seed is None, no random seed is set, so the random values generated are not reproducible. Returns: iris.cube.Cube: Cube for post-processed realizations where at a particular grid point, the ranking of the values within the ensemble matches the ranking from the raw ensemble. """ results = iris.cube.CubeList([]) for rawfc, calfc in zip( raw_forecast_realizations.slices_over("time"), post_processed_forecast_percentiles.slices_over("time"), ): if random_seed is not None: random_seed = int(random_seed) random_seed = np.random.RandomState(random_seed) random_data = random_seed.rand(*rawfc.data.shape) if random_ordering: # Returns the indices that would sort the array. # As these indices are from a random dataset, only an argsort # is used. ranking = np.argsort(random_data, axis=0) else: # Lexsort returns the indices sorted firstly by the # primary key, the raw forecast data (unless random_ordering # is enabled), and secondly by the secondary key, an array of # random data, in order to split tied values randomly. sorting_index = np.lexsort((random_data, rawfc.data), axis=0) # Returns the indices that would sort the array. ranking = np.argsort(sorting_index, axis=0) # Index the post-processed forecast data using the ranking array. # The following uses a custom choose function that reproduces the # required elements of the np.choose method without the limitation # of having < 32 arrays or a leading dimension < 32 in the # input data array. This function allows indexing of a 3d array # using a 3d array. mask = np.ma.getmask(calfc.data) calfc.data = choose(ranking, calfc.data) if mask is not np.ma.nomask: calfc.data = np.ma.MaskedArray(calfc.data, mask, dtype=np.float32) results.append(calfc) # Ensure we haven't lost any dimensional coordinates with only one # value in. results = results.merge_cube() results = check_cube_coordinates(post_processed_forecast_percentiles, results) return results def process( self, post_processed_forecast, raw_forecast, random_ordering=False, random_seed=None, ): """ Reorder post-processed forecast using the ordering of the raw ensemble. Args: post_processed_forecast (iris.cube.Cube): The cube containing the post-processed forecast realizations. raw_forecast (iris.cube.Cube): The cube containing the raw (not post-processed) forecast. random_ordering (bool): If random_ordering is True, the post-processed forecasts are reordered randomly, rather than using the ordering of the raw ensemble. random_seed (int): If random_seed is an integer, the integer value is used for the random seed. If random_seed is None, no random seed is set, so the random values generated are not reproducible. Returns: iris.cube.Cube: Cube containing the new ensemble realizations where all points within the dataset have been reordered in comparison to the input percentiles. """ percentile_coord_name = find_percentile_coordinate( post_processed_forecast ).name() enforce_coordinate_ordering(post_processed_forecast, percentile_coord_name) enforce_coordinate_ordering(raw_forecast, "realization") raw_forecast = self._recycle_raw_ensemble_realizations( post_processed_forecast, raw_forecast, percentile_coord_name ) post_processed_forecast_realizations = self.rank_ecc( post_processed_forecast, raw_forecast, random_ordering=random_ordering, random_seed=random_seed, ) plugin = RebadgePercentilesAsRealizations() post_processed_forecast_realizations = plugin( post_processed_forecast_realizations ) enforce_coordinate_ordering(post_processed_forecast_realizations, "realization") return post_processed_forecast_realizations

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import warnings import iris import numpy as np from iris.exceptions import CoordinateNotFoundError, InvalidCubeError from scipy import stats from improver import BasePlugin from improver.calibration.utilities import convert_cube_data_to_2d from improver.ensemble_copula_coupling.utilities import ( choose_set_of_percentiles, concatenate_2d_array_with_2d_array_endpoints, create_cube_with_percentiles, get_bounds_of_distribution, insert_lower_and_upper_endpoint_to_1d_array, restore_non_percentile_dimensions, ) from improver.metadata.probabilistic import ( extract_diagnostic_name, find_percentile_coordinate, find_threshold_coordinate, ) from improver.utilities.cube_checker import ( check_cube_coordinates, check_for_x_and_y_axes, ) from improver.utilities.cube_manipulation import ( MergeCubes, enforce_coordinate_ordering, get_dim_coord_names, ) from improver.utilities.indexing_operations import choose class RebadgePercentilesAsRealizations(BasePlugin): @staticmethod def process(cube, ensemble_realization_numbers=None): percentile_coord_name = find_percentile_coordinate(cube).name() if ensemble_realization_numbers is None: ensemble_realization_numbers = np.arange( len(cube.coord(percentile_coord_name).points), dtype=np.int32 ) cube.coord(percentile_coord_name).points = ensemble_realization_numbers try: realization_coord = cube.coord("realization") except CoordinateNotFoundError: realization_coord = None if realization_coord: raise InvalidCubeError( "Cannot rebadge percentile coordinate to realization " "coordinate because a realization coordinate already exists." ) cube.coord(percentile_coord_name).rename("realization") cube.coord("realization").units = "1" cube.coord("realization").points = cube.coord("realization").points.astype( np.int32 ) return cube class ResamplePercentiles(BasePlugin): def __init__(self, ecc_bounds_warning=False): self.ecc_bounds_warning = ecc_bounds_warning def _add_bounds_to_percentiles_and_forecast_at_percentiles( self, percentiles, forecast_at_percentiles, bounds_pairing ): lower_bound, upper_bound = bounds_pairing percentiles = insert_lower_and_upper_endpoint_to_1d_array(percentiles, 0, 100) forecast_at_percentiles_with_endpoints = concatenate_2d_array_with_2d_array_endpoints( forecast_at_percentiles, lower_bound, upper_bound ) if np.any(np.diff(forecast_at_percentiles_with_endpoints) < 0): out_of_bounds_vals = forecast_at_percentiles_with_endpoints[ np.where(np.diff(forecast_at_percentiles_with_endpoints) < 0) ] msg = ( "Forecast values exist that fall outside the expected extrema " "values that are defined as bounds in " "ensemble_copula_coupling/constants.py. " "Applying the extrema values as end points to the distribution " "would result in non-monotonically increasing values. " "The defined extremes are {}, whilst the following forecast " "values exist outside this range: {}.".format( bounds_pairing, out_of_bounds_vals ) ) if self.ecc_bounds_warning: warn_msg = msg + ( " The percentile values that have " "exceeded the existing bounds will be used " "as new bounds." ) warnings.warn(warn_msg) if upper_bound < forecast_at_percentiles_with_endpoints.max(): upper_bound = forecast_at_percentiles_with_endpoints.max() if lower_bound > forecast_at_percentiles_with_endpoints.min(): lower_bound = forecast_at_percentiles_with_endpoints.min() forecast_at_percentiles_with_endpoints = concatenate_2d_array_with_2d_array_endpoints( forecast_at_percentiles, lower_bound, upper_bound ) else: raise ValueError(msg) if np.any(np.diff(percentiles) < 0): msg = ( "The percentiles must be in ascending order." "The input percentiles were {}".format(percentiles) ) raise ValueError(msg) return percentiles, forecast_at_percentiles_with_endpoints def _interpolate_percentiles( self, forecast_at_percentiles, desired_percentiles, bounds_pairing, percentile_coord_name, ): original_percentiles = forecast_at_percentiles.coord( percentile_coord_name ).points # Ensure that the percentile dimension is first, so that the # conversion to a 2d array produces data in the desired order. enforce_coordinate_ordering(forecast_at_percentiles, percentile_coord_name) forecast_at_reshaped_percentiles = convert_cube_data_to_2d( forecast_at_percentiles, coord=percentile_coord_name ) ( original_percentiles, forecast_at_reshaped_percentiles, ) = self._add_bounds_to_percentiles_and_forecast_at_percentiles( original_percentiles, forecast_at_reshaped_percentiles, bounds_pairing ) forecast_at_interpolated_percentiles = np.empty( (len(desired_percentiles), forecast_at_reshaped_percentiles.shape[0]), dtype=np.float32, ) for index in range(forecast_at_reshaped_percentiles.shape[0]): forecast_at_interpolated_percentiles[:, index] = np.interp( desired_percentiles, original_percentiles, forecast_at_reshaped_percentiles[index, :], ) # Reshape forecast_at_percentiles, so the percentiles dimension is # first, and any other dimension coordinates follow. forecast_at_percentiles_data = restore_non_percentile_dimensions( forecast_at_interpolated_percentiles, next(forecast_at_percentiles.slices_over(percentile_coord_name)), len(desired_percentiles), ) template_cube = next(forecast_at_percentiles.slices_over(percentile_coord_name)) template_cube.remove_coord(percentile_coord_name) percentile_cube = create_cube_with_percentiles( desired_percentiles, template_cube, forecast_at_percentiles_data, ) return percentile_cube def process( self, forecast_at_percentiles, no_of_percentiles=None, sampling="quantile" ): percentile_coord = find_percentile_coordinate(forecast_at_percentiles) if no_of_percentiles is None: no_of_percentiles = len( forecast_at_percentiles.coord(percentile_coord).points ) percentiles = choose_set_of_percentiles(no_of_percentiles, sampling=sampling) cube_units = forecast_at_percentiles.units bounds_pairing = get_bounds_of_distribution( forecast_at_percentiles.name(), cube_units ) forecast_at_percentiles = self._interpolate_percentiles( forecast_at_percentiles, percentiles, bounds_pairing, percentile_coord.name(), ) return forecast_at_percentiles class ConvertProbabilitiesToPercentiles(BasePlugin): def __init__(self, ecc_bounds_warning=False): self.ecc_bounds_warning = ecc_bounds_warning def _add_bounds_to_thresholds_and_probabilities( self, threshold_points, probabilities_for_cdf, bounds_pairing ): lower_bound, upper_bound = bounds_pairing threshold_points_with_endpoints = insert_lower_and_upper_endpoint_to_1d_array( threshold_points, lower_bound, upper_bound ) probabilities_for_cdf = concatenate_2d_array_with_2d_array_endpoints( probabilities_for_cdf, 0, 1 ) if np.any(np.diff(threshold_points_with_endpoints) < 0): msg = ( "The calculated threshold values {} are not in ascending " "order as required for the cumulative distribution " "function (CDF). This is due to the threshold values " "exceeding the range given by the ECC bounds {}.".format( threshold_points_with_endpoints, bounds_pairing ) ) # If ecc_bounds_warning has been set, generate a warning message # rather than raising an exception so that subsequent processing # can continue. Then apply the new bounds as necessary to # ensure the threshold values and endpoints are in ascending # order and avoid problems further along the processing chain. if self.ecc_bounds_warning: warn_msg = msg + ( " The threshold points that have " "exceeded the existing bounds will be used " "as new bounds." ) warnings.warn(warn_msg) if upper_bound < max(threshold_points_with_endpoints): upper_bound = max(threshold_points_with_endpoints) if lower_bound > min(threshold_points_with_endpoints): lower_bound = min(threshold_points_with_endpoints) threshold_points_with_endpoints = insert_lower_and_upper_endpoint_to_1d_array( threshold_points, lower_bound, upper_bound ) else: raise ValueError(msg) return threshold_points_with_endpoints, probabilities_for_cdf def _probabilities_to_percentiles( self, forecast_probabilities, percentiles, bounds_pairing ): threshold_coord = find_threshold_coordinate(forecast_probabilities) threshold_unit = threshold_coord.units threshold_points = threshold_coord.points # Ensure that the percentile dimension is first, so that the # conversion to a 2d array produces data in the desired order. enforce_coordinate_ordering(forecast_probabilities, threshold_coord.name()) prob_slices = convert_cube_data_to_2d( forecast_probabilities, coord=threshold_coord.name() ) # The requirement below for a monotonically changing probability # across thresholds can be thwarted by precision errors of order 1E-10, # as such, here we round to a precision of 9 decimal places. prob_slices = np.around(prob_slices, 9) # Invert probabilities for data thresholded above thresholds. relation = find_threshold_coordinate(forecast_probabilities).attributes[ "spp__relative_to_threshold" ] if relation == "above": probabilities_for_cdf = 1 - prob_slices elif relation == "below": probabilities_for_cdf = prob_slices else: msg = ( "Probabilities to percentiles only implemented for " "thresholds above or below a given value." "The relation to threshold is given as {}".format(relation) ) raise NotImplementedError(msg) ( threshold_points, probabilities_for_cdf, ) = self._add_bounds_to_thresholds_and_probabilities( threshold_points, probabilities_for_cdf, bounds_pairing ) if np.any(np.diff(probabilities_for_cdf) < 0): msg = ( "The probability values used to construct the " "Cumulative Distribution Function (CDF) " "must be ascending i.e. in order to yield " "a monotonically increasing CDF." "The probabilities are {}".format(probabilities_for_cdf) ) warnings.warn(msg) # Convert percentiles into fractions. percentiles_as_fractions = np.array( [x / 100.0 for x in percentiles], dtype=np.float32 ) forecast_at_percentiles = ( # pylint: disable=unsubscriptable-object np.empty( (len(percentiles), probabilities_for_cdf.shape[0]), dtype=np.float32 ) ) # pylint: disable=unsubscriptable-object for index in range(probabilities_for_cdf.shape[0]): forecast_at_percentiles[:, index] = np.interp( percentiles_as_fractions, probabilities_for_cdf[index, :], threshold_points, ) # Reshape forecast_at_percentiles, so the percentiles dimension is # first, and any other dimension coordinates follow. forecast_at_percentiles = restore_non_percentile_dimensions( forecast_at_percentiles, next(forecast_probabilities.slices_over(threshold_coord)), len(percentiles), ) template_cube = next(forecast_probabilities.slices_over(threshold_coord.name())) template_cube.rename(extract_diagnostic_name(template_cube.name())) template_cube.remove_coord(threshold_coord.name()) percentile_cube = create_cube_with_percentiles( percentiles, template_cube, forecast_at_percentiles, cube_unit=threshold_unit, ) return percentile_cube def process( self, forecast_probabilities, no_of_percentiles=None, percentiles=None, sampling="quantile", ): if no_of_percentiles is not None and percentiles is not None: raise ValueError( "Cannot specify both no_of_percentiles and percentiles to " "{}".format(self.__class__.__name__) ) threshold_coord = find_threshold_coordinate(forecast_probabilities) phenom_name = extract_diagnostic_name(forecast_probabilities.name()) if no_of_percentiles is None: no_of_percentiles = len( forecast_probabilities.coord(threshold_coord.name()).points ) if percentiles is None: percentiles = choose_set_of_percentiles( no_of_percentiles, sampling=sampling ) elif not isinstance(percentiles, (tuple, list)): percentiles = [percentiles] percentiles = np.array(percentiles, dtype=np.float32) cube_units = forecast_probabilities.coord(threshold_coord.name()).units bounds_pairing = get_bounds_of_distribution(phenom_name, cube_units) # If a cube still has multiple realizations, slice over these to reduce # the memory requirements into manageable chunks. try: slices_over_realization = forecast_probabilities.slices_over("realization") except CoordinateNotFoundError: slices_over_realization = [forecast_probabilities] cubelist = iris.cube.CubeList([]) for cube_realization in slices_over_realization: cubelist.append( self._probabilities_to_percentiles( cube_realization, percentiles, bounds_pairing ) ) forecast_at_percentiles = cubelist.merge_cube() return forecast_at_percentiles class ConvertLocationAndScaleParameters: def __init__(self, distribution="norm", shape_parameters=None): try: self.distribution = getattr(stats, distribution) except AttributeError as err: msg = ( "The distribution requested {} is not a valid distribution " "in scipy.stats. {}".format(distribution, err) ) raise AttributeError(msg) if shape_parameters is None: if self.distribution.name == "truncnorm": raise ValueError( "For the truncated normal distribution, " "shape parameters must be specified." ) shape_parameters = [] self.shape_parameters = shape_parameters def __repr__(self): result = ( "<ConvertLocationAndScaleParameters: distribution: {}; " "shape_parameters: {}>" ) return result.format(self.distribution.name, self.shape_parameters) def _rescale_shape_parameters(self, location_parameter, scale_parameter): if self.distribution.name == "truncnorm": rescaled_values = [] for value in self.shape_parameters: rescaled_values.append((value - location_parameter) / scale_parameter) self.shape_parameters = rescaled_values class ConvertLocationAndScaleParametersToPercentiles( BasePlugin, ConvertLocationAndScaleParameters ): def __repr__(self): result = ( "<ConvertLocationAndScaleParametersToPercentiles: " "distribution: {}; shape_parameters: {}>" ) return result.format(self.distribution.name, self.shape_parameters) def _location_and_scale_parameters_to_percentiles( self, location_parameter, scale_parameter, template_cube, percentiles ): # Remove any mask that may be applied to location and scale parameters # and replace with ones location_data = np.ma.filled(location_parameter.data, 1).flatten() scale_data = np.ma.filled(scale_parameter.data, 1).flatten() # Convert percentiles into fractions. percentiles = np.array([x / 100.0 for x in percentiles], dtype=np.float32) result = np.zeros((len(percentiles), location_data.shape[0]), dtype=np.float32) self._rescale_shape_parameters(location_data, np.sqrt(scale_data)) percentile_method = self.distribution( *self.shape_parameters, loc=location_data, scale=np.sqrt(scale_data) ) # Loop over percentiles, and use the distribution as the # "percentile_method" with the location and scale parameter to # calculate the values at each percentile. for index, percentile in enumerate(percentiles): percentile_list = np.repeat(percentile, len(location_data)) result[index, :] = percentile_method.ppf(percentile_list) # If percent point function (PPF) returns NaNs, fill in # mean instead of NaN values. NaN will only be generated if the # variance is zero. Therefore, if the variance is zero, the mean # value is used for all gridpoints with a NaN. if np.any(scale_data == 0): nan_index = np.argwhere(np.isnan(result[index, :])) result[index, nan_index] = location_data[nan_index] if np.any(np.isnan(result)): msg = ( "NaNs are present within the result for the {} " "percentile. Unable to calculate the percent point " "function." ) raise ValueError(msg) # Convert percentiles back into percentages. percentiles = [x * 100.0 for x in percentiles] # Reshape forecast_at_percentiles, so the percentiles dimension is # first, and any other dimension coordinates follow. result = result.reshape((len(percentiles),) + location_parameter.data.shape) for prob_coord_name in ["realization", "percentile"]: if template_cube.coords(prob_coord_name, dim_coords=True): prob_coord = template_cube.coord(prob_coord_name) template_slice = next(template_cube.slices_over(prob_coord)) template_slice.remove_coord(prob_coord) percentile_cube = create_cube_with_percentiles( percentiles, template_slice, result ) # Define a mask to be reapplied later mask = np.logical_or( np.ma.getmaskarray(location_parameter.data), np.ma.getmaskarray(scale_parameter.data), ) # Make the mask defined above fit the data size and then apply to the # percentile cube. mask_array = np.stack([mask] * len(percentiles)) percentile_cube.data = np.ma.masked_where(mask_array, percentile_cube.data) # Remove cell methods associated with finding the ensemble mean percentile_cube.cell_methods = {} return percentile_cube def process( self, location_parameter, scale_parameter, template_cube, no_of_percentiles=None, percentiles=None, ): if no_of_percentiles and percentiles: msg = ( "Please specify either the number of percentiles or " "provide a list of percentiles. The number of percentiles " "provided was {} and the list of percentiles " "provided was {}".format(no_of_percentiles, percentiles) ) raise ValueError(msg) if no_of_percentiles: percentiles = choose_set_of_percentiles(no_of_percentiles) calibrated_forecast_percentiles = self._location_and_scale_parameters_to_percentiles( location_parameter, scale_parameter, template_cube, percentiles ) return calibrated_forecast_percentiles class ConvertLocationAndScaleParametersToProbabilities( BasePlugin, ConvertLocationAndScaleParameters ): def __repr__(self): result = ( "<ConvertLocationAndScaleParametersToProbabilities: " "distribution: {}; shape_parameters: {}>" ) return result.format(self.distribution.name, self.shape_parameters) def _check_template_cube(self, cube): check_for_x_and_y_axes(cube, require_dim_coords=True) dim_coords = get_dim_coord_names(cube) msg = ( "{} expects a cube with only a leading threshold dimension, " "followed by spatial (y/x) dimensions. " "Got dimensions: {}".format(self.__class__.__name__, dim_coords) ) try: threshold_coord = find_threshold_coordinate(cube) except CoordinateNotFoundError: raise ValueError(msg) if len(dim_coords) < 4: enforce_coordinate_ordering(cube, threshold_coord.name()) return raise ValueError(msg) @staticmethod def _check_unit_compatibility( location_parameter, scale_parameter, probability_cube_template ): threshold_units = find_threshold_coordinate(probability_cube_template).units try: location_parameter.convert_units(threshold_units) scale_parameter.convert_units(threshold_units ** 2) except ValueError as err: msg = ( "Error: {} This is likely because the mean " "variance and template cube threshold units are " "not equivalent/compatible.".format(err) ) raise ValueError(msg) def _location_and_scale_parameters_to_probabilities( self, location_parameter, scale_parameter, probability_cube_template ): # Define a mask to be reapplied later loc_mask = np.ma.getmaskarray(location_parameter.data) scale_mask = np.ma.getmaskarray(scale_parameter.data) mask = np.logical_or(loc_mask, scale_mask) # Remove any mask that may be applied to location and scale parameters # and replace with ones location_parameter.data = np.ma.filled(location_parameter.data, 1) scale_parameter.data = np.ma.filled(scale_parameter.data, 1) thresholds = find_threshold_coordinate(probability_cube_template).points relative_to_threshold = find_threshold_coordinate( probability_cube_template ).attributes["spp__relative_to_threshold"] self._rescale_shape_parameters( location_parameter.data.flatten(), np.sqrt(scale_parameter.data).flatten() ) # Loop over thresholds, and use the specified distribution with the # location and scale parameter to calculate the probabilities relative # to each threshold. probabilities = np.empty_like(probability_cube_template.data) distribution = self.distribution( *self.shape_parameters, loc=location_parameter.data.flatten(), scale=np.sqrt(scale_parameter.data.flatten()), ) probability_method = distribution.cdf if relative_to_threshold == "above": probability_method = distribution.sf for index, threshold in enumerate(thresholds): # pylint: disable=unsubscriptable-object probabilities[index, ...] = np.reshape( probability_method(threshold), probabilities.shape[1:] ) probability_cube = probability_cube_template.copy(data=probabilities) # Make the mask defined above fit the data size and then apply to the # probability cube. mask_array = np.array([mask] * len(probabilities)) probability_cube.data = np.ma.masked_where(mask_array, probability_cube.data) return probability_cube def process(self, location_parameter, scale_parameter, probability_cube_template): self._check_template_cube(probability_cube_template) self._check_unit_compatibility( location_parameter, scale_parameter, probability_cube_template ) probability_cube = self._location_and_scale_parameters_to_probabilities( location_parameter, scale_parameter, probability_cube_template ) return probability_cube class EnsembleReordering(BasePlugin): @staticmethod def _recycle_raw_ensemble_realizations( post_processed_forecast_percentiles, raw_forecast_realizations, percentile_coord_name, ): plen = len( post_processed_forecast_percentiles.coord(percentile_coord_name).points ) mlen = len(raw_forecast_realizations.coord("realization").points) if plen == mlen: pass else: raw_forecast_realizations_extended = iris.cube.CubeList() realization_list = [] mpoints = raw_forecast_realizations.coord("realization").points # Loop over the number of percentiles and finding the # corresponding ensemble realization number. The ensemble # realization numbers are recycled e.g. 1, 2, 3, 1, 2, 3, etc. for index in range(plen): realization_list.append(mpoints[index % len(mpoints)]) # Assume that the ensemble realizations are ascending linearly. new_realization_numbers = realization_list[0] + list(range(plen)) # Extract the realizations required in the realization_list from # the raw_forecast_realizations. Edit the realization number as # appropriate and append to a cubelist containing rebadged # raw ensemble realizations. for realization, index in zip(realization_list, new_realization_numbers): constr = iris.Constraint(realization=realization) raw_forecast_realization = raw_forecast_realizations.extract(constr) raw_forecast_realization.coord("realization").points = index raw_forecast_realizations_extended.append(raw_forecast_realization) raw_forecast_realizations = MergeCubes()( raw_forecast_realizations_extended, slice_over_realization=True ) return raw_forecast_realizations @staticmethod def rank_ecc( post_processed_forecast_percentiles, raw_forecast_realizations, random_ordering=False, random_seed=None, ): results = iris.cube.CubeList([]) for rawfc, calfc in zip( raw_forecast_realizations.slices_over("time"), post_processed_forecast_percentiles.slices_over("time"), ): if random_seed is not None: random_seed = int(random_seed) random_seed = np.random.RandomState(random_seed) random_data = random_seed.rand(*rawfc.data.shape) if random_ordering: # Returns the indices that would sort the array. # As these indices are from a random dataset, only an argsort # is used. ranking = np.argsort(random_data, axis=0) else: # Lexsort returns the indices sorted firstly by the # primary key, the raw forecast data (unless random_ordering # is enabled), and secondly by the secondary key, an array of # random data, in order to split tied values randomly. sorting_index = np.lexsort((random_data, rawfc.data), axis=0) # Returns the indices that would sort the array. ranking = np.argsort(sorting_index, axis=0) # Index the post-processed forecast data using the ranking array. # The following uses a custom choose function that reproduces the # required elements of the np.choose method without the limitation # of having < 32 arrays or a leading dimension < 32 in the # input data array. This function allows indexing of a 3d array # using a 3d array. mask = np.ma.getmask(calfc.data) calfc.data = choose(ranking, calfc.data) if mask is not np.ma.nomask: calfc.data = np.ma.MaskedArray(calfc.data, mask, dtype=np.float32) results.append(calfc) # Ensure we haven't lost any dimensional coordinates with only one results = results.merge_cube() results = check_cube_coordinates(post_processed_forecast_percentiles, results) return results def process( self, post_processed_forecast, raw_forecast, random_ordering=False, random_seed=None, ): percentile_coord_name = find_percentile_coordinate( post_processed_forecast ).name() enforce_coordinate_ordering(post_processed_forecast, percentile_coord_name) enforce_coordinate_ordering(raw_forecast, "realization") raw_forecast = self._recycle_raw_ensemble_realizations( post_processed_forecast, raw_forecast, percentile_coord_name ) post_processed_forecast_realizations = self.rank_ecc( post_processed_forecast, raw_forecast, random_ordering=random_ordering, random_seed=random_seed, ) plugin = RebadgePercentilesAsRealizations() post_processed_forecast_realizations = plugin( post_processed_forecast_realizations ) enforce_coordinate_ordering(post_processed_forecast_realizations, "realization") return post_processed_forecast_realizations

true

1c45a614492dc6ca48e3d950527282f5ff9aa377

784

py

Python

examples/dagster_examples/intro_tutorial/config.py

bambielli-flex/dagster

30b75ba7c62fc536bc827f177c1dc6ba20f5ae20

[ "Apache-2.0" ]

null

examples/dagster_examples/intro_tutorial/config.py

bambielli-flex/dagster

30b75ba7c62fc536bc827f177c1dc6ba20f5ae20

[ "Apache-2.0" ]

null

examples/dagster_examples/intro_tutorial/config.py

bambielli-flex/dagster

30b75ba7c62fc536bc827f177c1dc6ba20f5ae20

[ "Apache-2.0" ]

null

# encoding: utf-8 # py27 compat from dagster import Field, PipelineDefinition, execute_pipeline, solid, types @solid(config_field=Field(types.String, is_optional=True, default_value='en-us')) def configurable_hello(context): if len(context.solid_config) >= 3 and context.solid_config[:3] == 'haw': return 'Aloha honua!' elif len(context.solid_config) >= 2 and context.solid_config[:2] == 'cn': return '你好, 世界!' else: return 'Hello, world!' def define_configurable_hello_pipeline(): return PipelineDefinition(name='configurable_hello_pipeline', solids=[configurable_hello]) def test_intro_tutorial_part_four(): execute_pipeline( define_configurable_hello_pipeline(), {'solids': {'configurable_hello': {'config': 'cn'}}} )

31.36

98

0.714286

from dagster import Field, PipelineDefinition, execute_pipeline, solid, types @solid(config_field=Field(types.String, is_optional=True, default_value='en-us')) def configurable_hello(context): if len(context.solid_config) >= 3 and context.solid_config[:3] == 'haw': return 'Aloha honua!' elif len(context.solid_config) >= 2 and context.solid_config[:2] == 'cn': return '你好, 世界!' else: return 'Hello, world!' def define_configurable_hello_pipeline(): return PipelineDefinition(name='configurable_hello_pipeline', solids=[configurable_hello]) def test_intro_tutorial_part_four(): execute_pipeline( define_configurable_hello_pipeline(), {'solids': {'configurable_hello': {'config': 'cn'}}} )

true

1c45a68d0192fabe44b1195622b98bb7d5868d24

3,238

py

Python

kaplot/astro/wcsgrid.py

maartenbreddels/kaplot

305026209f8026094d54373e14541f4f039501d5

[ "MIT" ]

null

kaplot/astro/wcsgrid.py

maartenbreddels/kaplot

305026209f8026094d54373e14541f4f039501d5

[ "MIT" ]

null

kaplot/astro/wcsgrid.py

maartenbreddels/kaplot

305026209f8026094d54373e14541f4f039501d5

[ "MIT" ]

null

from kaplot.objects import PlotObject import numarray import kaplot import kaplot.context import kaplot.vector class WcsGrid(PlotObject): def __init__(self, xticks, yticks, projection, longitudeoffset, lock=True, context=None, **kwargs): PlotObject.__init__(self, lock=False, context=kaplot.context.mergeDicts(context, kwargs)) self.xticks = xticks self.yticks = yticks self.projection = projection self.longitudeoffset = longitudeoffset self.context = kaplot.context.buildContext(kwargs) self.callback = self.notifyChange self.context.addWeakListener(self.callback) if lock: self._lock() def plot(self, device): #xticks = self.xticks #yticks = self.yticks #xmask = (xticks >= lomin) == (xticks <= lomax) #ymask = (yticks >= lamin) == (yticks <= lamax) #xticks = compress(xmask, xticks) #yticks = compress(ymask, yticks) #la #yticks = arange(lamin, lamax, lagran) #xticks = arange(lomin, lomax, logran) lines = [] xticks = numarray.array(self.xticks) yticks = numarray.array(self.yticks) #xticks = (xticks + 180) % 360 - 180 lomin, lomax = min(xticks), max(xticks) lamin, lamax = min(yticks), max(yticks) logran = (lomax - lomin) / 40 lagran = (lamax - lamin) / 40 #print lomin, lomax #print lamin, lamax #print lomin, lomax, lamin, lamax #print xticks, yticks #print xticks, yticks #print dev.transformation.transform(xticks, yticks) #print "PHAT", lomin, lomax, len(yticks) for latitude in yticks[:]: #arange(lamin, lamax+lagran/2, lagran): x = numarray.arange(lomin, lomax+logran/2.0, logran) y = numarray.zeros(len(x)) + float(latitude) nx, ny = self.projection.forwardarray(x, y) #print "latitude", latitude #print "x=",x, "y=",y #print "new" #print "nx=",nx, "ny=",ny nx = [] ny = [] longoffset = self.longitudeoffset offset = 0 #(int(self.longitudeoffset) / 180) * 180 longitudebegin = -180 while ((x[0]-offset) >= (longitudebegin+longoffset)): offset += 180 #print "offset", offset sigma = 0.0001 for x, y in zip(x, y): if ((x-offset) >= (longitudebegin+longoffset)): #print "jump", longoffset p = self.projection.forward(longitudebegin+(longoffset-sigma)-offset, y) if p != None: nx.append(p[0]) ny.append(p[1]) offset += (180) if len(nx) >= 2: #print "plot", nx, ny device.plotPolyline(nx, ny) nx = [] ny = [] p = self.projection.forward(longitudebegin+(longoffset+sigma)-(offset-180), y) if p != None: nx.append(p[0]) ny.append(p[1]) #else: # print "no jump" p = self.projection.forward(x, y) if p != None: nx.append(p[0]) ny.append(p[1]) #p = self.projection.forward(lomax, y) #if p != None: # nx.append(p[0]) # ny.append(p[1]) if len(nx) >= 2: #print "plot", nx, ny device.plotPolyline(nx, ny) for longitude in xticks: #arange(lomin, lomax+logran/2, logran): y = numarray.arange(lamin, lamax+lagran/2, lagran) x = numarray.zeros(len(y)) + float(longitude) nx, ny = self.projection.forwardarray(x, y) device.plotPolyline(nx, ny) #line = Polyline(x, y, linestyle="normal", linewidth=self.linewidth, color=self.color) #lines.append(line)

30.261682

100

0.647931

from kaplot.objects import PlotObject import numarray import kaplot import kaplot.context import kaplot.vector class WcsGrid(PlotObject): def __init__(self, xticks, yticks, projection, longitudeoffset, lock=True, context=None, **kwargs): PlotObject.__init__(self, lock=False, context=kaplot.context.mergeDicts(context, kwargs)) self.xticks = xticks self.yticks = yticks self.projection = projection self.longitudeoffset = longitudeoffset self.context = kaplot.context.buildContext(kwargs) self.callback = self.notifyChange self.context.addWeakListener(self.callback) if lock: self._lock() def plot(self, device): lines = [] xticks = numarray.array(self.xticks) yticks = numarray.array(self.yticks) lomin, lomax = min(xticks), max(xticks) lamin, lamax = min(yticks), max(yticks) logran = (lomax - lomin) / 40 lagran = (lamax - lamin) / 40 for latitude in yticks[:]: x = numarray.arange(lomin, lomax+logran/2.0, logran) y = numarray.zeros(len(x)) + float(latitude) nx, ny = self.projection.forwardarray(x, y) nx = [] ny = [] longoffset = self.longitudeoffset offset = 0 longitudebegin = -180 while ((x[0]-offset) >= (longitudebegin+longoffset)): offset += 180 sigma = 0.0001 for x, y in zip(x, y): if ((x-offset) >= (longitudebegin+longoffset)): p = self.projection.forward(longitudebegin+(longoffset-sigma)-offset, y) if p != None: nx.append(p[0]) ny.append(p[1]) offset += (180) if len(nx) >= 2: device.plotPolyline(nx, ny) nx = [] ny = [] p = self.projection.forward(longitudebegin+(longoffset+sigma)-(offset-180), y) if p != None: nx.append(p[0]) ny.append(p[1]) p = self.projection.forward(x, y) if p != None: nx.append(p[0]) ny.append(p[1]) if len(nx) >= 2: device.plotPolyline(nx, ny) for longitude in xticks: y = numarray.arange(lamin, lamax+lagran/2, lagran) x = numarray.zeros(len(y)) + float(longitude) nx, ny = self.projection.forwardarray(x, y) device.plotPolyline(nx, ny)

true

1c45a7a78535500c62f6eb5fd46da6f909d578fb

1,034

py

Python

manage.py

manuelen12/test_sale

1d199fcfca8361edf704e0bb138a07e7d924f327

[ "MIT" ]

null

manage.py

manuelen12/test_sale

1d199fcfca8361edf704e0bb138a07e7d924f327

[ "MIT" ]

null

manage.py

manuelen12/test_sale

1d199fcfca8361edf704e0bb138a07e7d924f327

[ "MIT" ]

null

#!/usr/bin/env python import os import sys if __name__ == '__main__': os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'config.settings.local') try: from django.core.management import execute_from_command_line except ImportError: # The above import may fail for some other reason. Ensure that the # issue is really that Django is missing to avoid masking other # exceptions on Python 2. try: import django # noqa except ImportError: raise ImportError( "Couldn't import Django. Are you sure it's installed and " "available on your PYTHONPATH environment variable? Did you " "forget to activate a virtual environment?" ) raise # This allows easy placement of apps within the interior # test_venta directory. current_path = os.path.dirname(os.path.abspath(__file__)) sys.path.append(os.path.join(current_path, 'test_venta')) execute_from_command_line(sys.argv)

34.466667

77

0.658607

import os import sys if __name__ == '__main__': os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'config.settings.local') try: from django.core.management import execute_from_command_line except ImportError: try: import django except ImportError: raise ImportError( "Couldn't import Django. Are you sure it's installed and " "available on your PYTHONPATH environment variable? Did you " "forget to activate a virtual environment?" ) raise current_path = os.path.dirname(os.path.abspath(__file__)) sys.path.append(os.path.join(current_path, 'test_venta')) execute_from_command_line(sys.argv)

true

1c45a7b3b9bd4e9eca083311a86129a50d7c738e

189

py

Python

tests/web_platform/CSS2/normal_flow/test_block_in_inline_insert_014_nosplit_ref.py

fletchgraham/colosseum

77be4896ee52b8f5956a3d77b5f2ccd2c8608e8f

[ "BSD-3-Clause" ]

null

tests/web_platform/CSS2/normal_flow/test_block_in_inline_insert_014_nosplit_ref.py

fletchgraham/colosseum

77be4896ee52b8f5956a3d77b5f2ccd2c8608e8f

[ "BSD-3-Clause" ]

null

tests/web_platform/CSS2/normal_flow/test_block_in_inline_insert_014_nosplit_ref.py

fletchgraham/colosseum

77be4896ee52b8f5956a3d77b5f2ccd2c8608e8f

[ "BSD-3-Clause" ]

1

2020-01-16T01:56:41.000Z

from tests.utils import W3CTestCase class TestBlockInInlineInsert014NosplitRef(W3CTestCase): vars().update(W3CTestCase.find_tests(__file__, 'block-in-inline-insert-014-nosplit-ref'))

31.5

93

0.814815

from tests.utils import W3CTestCase class TestBlockInInlineInsert014NosplitRef(W3CTestCase): vars().update(W3CTestCase.find_tests(__file__, 'block-in-inline-insert-014-nosplit-ref'))

true

1c45a859a5271dffa80a1d5cc1763cd482c9913a

2,912

py

Python

test/integration_tests/test_roles.py

poldracklab/bids-core

b87a1ef2d3e1c5a79a98c0f0ba82b1b2634bce0e

[ "MIT" ]

1

2016-03-09T01:24:02.000Z

test/integration_tests/test_roles.py

poldracklab/bids-core

b87a1ef2d3e1c5a79a98c0f0ba82b1b2634bce0e

[ "MIT" ]

15

2016-02-17T19:11:32.000Z

2018-04-12T23:33:06.000Z

test/integration_tests/test_roles.py

poldracklab/bids-core

b87a1ef2d3e1c5a79a98c0f0ba82b1b2634bce0e

[ "MIT" ]

4

2017-04-05T17:34:59.000Z

2018-01-22T01:40:51.000Z

import requests import os import json import time from nose.tools import with_setup base_url = 'http://localhost:8080/api' adm_user = 'test@user.com' user = 'other@user.com' test_data = type('',(object,),{})() def setup_db(): global session session = requests.Session() # all the requests will be performed as root session.params = { 'user': adm_user, 'root': True } # Create a group test_data.group_id = 'test_group_' + str(int(time.time()*1000)) payload = { '_id': test_data.group_id } payload = json.dumps(payload) r = session.post(base_url + '/groups', data=payload) assert r.ok payload = { '_id': user, 'firstname': 'Other', 'lastname': 'User', } payload = json.dumps(payload) r = session.post(base_url + '/users', data=payload) assert r.ok session.params = {} def teardown_db(): session.params = { 'user': adm_user, 'root': True } r = session.delete(base_url + '/groups/' + test_data.group_id) assert r.ok r = session.delete(base_url + '/users/' + user) assert r.ok def _build_url_and_payload(method, user, access, site='local'): url = os.path.join(base_url, 'groups', test_data.group_id, 'roles') if method == 'POST': payload = { '_id': user, 'site': site, 'access': access } return url, json.dumps(payload) else: return os.path.join(url, site, user), None @with_setup(setup_db, teardown_db) def test_roles(): session.params = { 'user': adm_user } url_get, _ = _build_url_and_payload('GET', user, None) r = session.get(url_get) assert r.status_code == 404 url_post, payload = _build_url_and_payload('POST', user, 'rw') r = session.post(url_post, data=payload) assert r.ok r = session.get(url_get) assert r.ok content = json.loads(r.content) assert content['access'] == 'rw' assert content['_id'] == user session.params = { 'user': user } url_get_not_auth, _ = _build_url_and_payload('GET', adm_user, None) r = session.get(url_get_not_auth) assert r.status_code == 403 session.params = { 'user': adm_user } payload = json.dumps({'access':'admin'}) r = session.put(url_get, data=payload) assert r.ok session.params = { 'user': user } r = session.get(url_get_not_auth) assert r.ok session.params = { 'user': adm_user } payload = json.dumps({'access':'rw'}) r = session.put(url_get, data=payload) assert r.ok session.params = { 'user': user } r = session.get(url_get_not_auth) assert r.status_code == 403 session.params = { 'user': adm_user } r = session.delete(url_get) assert r.ok r = session.get(url_get) assert r.status_code == 404

25.321739

71

0.595467

import requests import os import json import time from nose.tools import with_setup base_url = 'http://localhost:8080/api' adm_user = 'test@user.com' user = 'other@user.com' test_data = type('',(object,),{})() def setup_db(): global session session = requests.Session() session.params = { 'user': adm_user, 'root': True } test_data.group_id = 'test_group_' + str(int(time.time()*1000)) payload = { '_id': test_data.group_id } payload = json.dumps(payload) r = session.post(base_url + '/groups', data=payload) assert r.ok payload = { '_id': user, 'firstname': 'Other', 'lastname': 'User', } payload = json.dumps(payload) r = session.post(base_url + '/users', data=payload) assert r.ok session.params = {} def teardown_db(): session.params = { 'user': adm_user, 'root': True } r = session.delete(base_url + '/groups/' + test_data.group_id) assert r.ok r = session.delete(base_url + '/users/' + user) assert r.ok def _build_url_and_payload(method, user, access, site='local'): url = os.path.join(base_url, 'groups', test_data.group_id, 'roles') if method == 'POST': payload = { '_id': user, 'site': site, 'access': access } return url, json.dumps(payload) else: return os.path.join(url, site, user), None @with_setup(setup_db, teardown_db) def test_roles(): session.params = { 'user': adm_user } url_get, _ = _build_url_and_payload('GET', user, None) r = session.get(url_get) assert r.status_code == 404 url_post, payload = _build_url_and_payload('POST', user, 'rw') r = session.post(url_post, data=payload) assert r.ok r = session.get(url_get) assert r.ok content = json.loads(r.content) assert content['access'] == 'rw' assert content['_id'] == user session.params = { 'user': user } url_get_not_auth, _ = _build_url_and_payload('GET', adm_user, None) r = session.get(url_get_not_auth) assert r.status_code == 403 session.params = { 'user': adm_user } payload = json.dumps({'access':'admin'}) r = session.put(url_get, data=payload) assert r.ok session.params = { 'user': user } r = session.get(url_get_not_auth) assert r.ok session.params = { 'user': adm_user } payload = json.dumps({'access':'rw'}) r = session.put(url_get, data=payload) assert r.ok session.params = { 'user': user } r = session.get(url_get_not_auth) assert r.status_code == 403 session.params = { 'user': adm_user } r = session.delete(url_get) assert r.ok r = session.get(url_get) assert r.status_code == 404

true

1c45a92868008d359499e2e83998919eb99a0158

5,916

py

Python

sdk/python/pulumi_azure_native/migrate/latest/group.py

pulumi-bot/pulumi-azure-native

f7b9490b5211544318e455e5cceafe47b628e12c

[ "Apache-2.0" ]

null

sdk/python/pulumi_azure_native/migrate/latest/group.py

pulumi-bot/pulumi-azure-native

f7b9490b5211544318e455e5cceafe47b628e12c

[ "Apache-2.0" ]

null

sdk/python/pulumi_azure_native/migrate/latest/group.py

pulumi-bot/pulumi-azure-native

f7b9490b5211544318e455e5cceafe47b628e12c

[ "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union from ... import _utilities, _tables from . import outputs __all__ = ['Group'] warnings.warn("""The 'latest' version is deprecated. Please migrate to the resource in the top-level module: 'azure-native:migrate:Group'.""", DeprecationWarning) class Group(pulumi.CustomResource): warnings.warn("""The 'latest' version is deprecated. Please migrate to the resource in the top-level module: 'azure-native:migrate:Group'.""", DeprecationWarning) def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, e_tag: Optional[pulumi.Input[str]] = None, group_name: Optional[pulumi.Input[str]] = None, project_name: Optional[pulumi.Input[str]] = None, resource_group_name: Optional[pulumi.Input[str]] = None, __props__=None, __name__=None, __opts__=None): """ A group created in a Migration project. Latest API Version: 2019-10-01. :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] e_tag: For optimistic concurrency control. :param pulumi.Input[str] group_name: Unique name of a group within a project. :param pulumi.Input[str] project_name: Name of the Azure Migrate project. :param pulumi.Input[str] resource_group_name: Name of the Azure Resource Group that project is part of. """ pulumi.log.warn("""Group is deprecated: The 'latest' version is deprecated. Please migrate to the resource in the top-level module: 'azure-native:migrate:Group'.""") 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__['e_tag'] = e_tag __props__['group_name'] = group_name if project_name is None and not opts.urn: raise TypeError("Missing required property 'project_name'") __props__['project_name'] = project_name if resource_group_name is None and not opts.urn: raise TypeError("Missing required property 'resource_group_name'") __props__['resource_group_name'] = resource_group_name __props__['name'] = None __props__['properties'] = None __props__['type'] = None alias_opts = pulumi.ResourceOptions(aliases=[pulumi.Alias(type_="azure-nextgen:migrate/latest:Group"), pulumi.Alias(type_="azure-native:migrate:Group"), pulumi.Alias(type_="azure-nextgen:migrate:Group"), pulumi.Alias(type_="azure-native:migrate/v20191001:Group"), pulumi.Alias(type_="azure-nextgen:migrate/v20191001:Group")]) opts = pulumi.ResourceOptions.merge(opts, alias_opts) super(Group, __self__).__init__( 'azure-native:migrate/latest:Group', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None) -> 'Group': """ Get an existing Group 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 pulumi.Input[str] id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = dict() __props__["e_tag"] = None __props__["name"] = None __props__["properties"] = None __props__["type"] = None return Group(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter(name="eTag") def e_tag(self) -> pulumi.Output[Optional[str]]: """ For optimistic concurrency control. """ return pulumi.get(self, "e_tag") @property @pulumi.getter def name(self) -> pulumi.Output[str]: """ Name of the group. """ return pulumi.get(self, "name") @property @pulumi.getter def properties(self) -> pulumi.Output['outputs.GroupPropertiesResponse']: """ Properties of the group. """ return pulumi.get(self, "properties") @property @pulumi.getter def type(self) -> pulumi.Output[str]: """ Type of the object = [Microsoft.Migrate/assessmentProjects/groups]. """ return pulumi.get(self, "type") 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

42.869565

333

0.644523

import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union from ... import _utilities, _tables from . import outputs __all__ = ['Group'] warnings.warn("""The 'latest' version is deprecated. Please migrate to the resource in the top-level module: 'azure-native:migrate:Group'.""", DeprecationWarning) class Group(pulumi.CustomResource): warnings.warn("""The 'latest' version is deprecated. Please migrate to the resource in the top-level module: 'azure-native:migrate:Group'.""", DeprecationWarning) def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, e_tag: Optional[pulumi.Input[str]] = None, group_name: Optional[pulumi.Input[str]] = None, project_name: Optional[pulumi.Input[str]] = None, resource_group_name: Optional[pulumi.Input[str]] = None, __props__=None, __name__=None, __opts__=None): pulumi.log.warn("""Group is deprecated: The 'latest' version is deprecated. Please migrate to the resource in the top-level module: 'azure-native:migrate:Group'.""") 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__['e_tag'] = e_tag __props__['group_name'] = group_name if project_name is None and not opts.urn: raise TypeError("Missing required property 'project_name'") __props__['project_name'] = project_name if resource_group_name is None and not opts.urn: raise TypeError("Missing required property 'resource_group_name'") __props__['resource_group_name'] = resource_group_name __props__['name'] = None __props__['properties'] = None __props__['type'] = None alias_opts = pulumi.ResourceOptions(aliases=[pulumi.Alias(type_="azure-nextgen:migrate/latest:Group"), pulumi.Alias(type_="azure-native:migrate:Group"), pulumi.Alias(type_="azure-nextgen:migrate:Group"), pulumi.Alias(type_="azure-native:migrate/v20191001:Group"), pulumi.Alias(type_="azure-nextgen:migrate/v20191001:Group")]) opts = pulumi.ResourceOptions.merge(opts, alias_opts) super(Group, __self__).__init__( 'azure-native:migrate/latest:Group', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None) -> 'Group': opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = dict() __props__["e_tag"] = None __props__["name"] = None __props__["properties"] = None __props__["type"] = None return Group(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter(name="eTag") def e_tag(self) -> pulumi.Output[Optional[str]]: return pulumi.get(self, "e_tag") @property @pulumi.getter def name(self) -> pulumi.Output[str]: return pulumi.get(self, "name") @property @pulumi.getter def properties(self) -> pulumi.Output['outputs.GroupPropertiesResponse']: return pulumi.get(self, "properties") @property @pulumi.getter def type(self) -> pulumi.Output[str]: return pulumi.get(self, "type") 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

true

1c45a98c9736d722678cfe3cb4948c956cd7f2d7

6,212

py

Python

tempest/api/object_storage/test_container_sync.py

azorge/tempest

549dfc93fb7e3d6d8566064a60a6069deae5c8eb

[ "Apache-2.0" ]

1

2021-05-21T08:24:02.000Z

tempest/api/object_storage/test_container_sync.py

azorge/tempest

549dfc93fb7e3d6d8566064a60a6069deae5c8eb

[ "Apache-2.0" ]

null

tempest/api/object_storage/test_container_sync.py

azorge/tempest

549dfc93fb7e3d6d8566064a60a6069deae5c8eb

[ "Apache-2.0" ]

null

# Copyright 2012 OpenStack Foundation # 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 time from six.moves.urllib import parse as urlparse import testtools from tempest.api.object_storage import base from tempest import config from tempest.lib.common.utils import data_utils from tempest.lib import decorators from tempest import test CONF = config.CONF # This test can be quite long to run due to its # dependency on container-sync process running interval. # You can obviously reduce the container-sync interval in the # container-server configuration. class ContainerSyncTest(base.BaseObjectTest): clients = {} credentials = [['operator', CONF.object_storage.operator_role], ['operator_alt', CONF.object_storage.operator_role]] @classmethod def setup_credentials(cls): super(ContainerSyncTest, cls).setup_credentials() cls.os = cls.os_roles_operator cls.os_alt = cls.os_roles_operator_alt @classmethod def setup_clients(cls): super(ContainerSyncTest, cls).setup_clients() cls.object_client_alt = cls.os_alt.object_client cls.container_client_alt = cls.os_alt.container_client @classmethod def resource_setup(cls): super(ContainerSyncTest, cls).resource_setup() cls.containers = [] cls.objects = [] # Default container-server config only allows localhost cls.local_ip = '127.0.0.1' # Must be configure according to container-sync interval container_sync_timeout = CONF.object_storage.container_sync_timeout cls.container_sync_interval = \ CONF.object_storage.container_sync_interval cls.attempts = \ int(container_sync_timeout / cls.container_sync_interval) # define container and object clients cls.clients[data_utils.rand_name(name='TestContainerSync')] = \ (cls.container_client, cls.object_client) cls.clients[data_utils.rand_name(name='TestContainerSync')] = \ (cls.container_client_alt, cls.object_client_alt) for cont_name, client in cls.clients.items(): client[0].create_container(cont_name) cls.containers.append(cont_name) @classmethod def resource_cleanup(cls): for client in cls.clients.values(): cls.delete_containers(client[0], client[1]) super(ContainerSyncTest, cls).resource_cleanup() def _test_container_synchronization(self, make_headers): # container to container synchronization # to allow/accept sync requests to/from other accounts # turn container synchronization on and create object in container for cont in (self.containers, self.containers[::-1]): cont_client = [self.clients[c][0] for c in cont] obj_client = [self.clients[c][1] for c in cont] headers = make_headers(cont[1], cont_client[1]) resp, body = \ cont_client[0].put(str(cont[0]), body=None, headers=headers) # create object in container object_name = data_utils.rand_name(name='TestSyncObject') data = object_name[::-1].encode() # Raw data, we need bytes resp, _ = obj_client[0].create_object(cont[0], object_name, data) self.objects.append(object_name) # wait until container contents list is not empty cont_client = [self.clients[c][0] for c in self.containers] params = {'format': 'json'} while self.attempts > 0: object_lists = [] for c_client, cont in zip(cont_client, self.containers): resp, object_list = c_client.list_container_contents( cont, params=params) object_lists.append(dict( (obj['name'], obj) for obj in object_list)) # check that containers are not empty and have equal keys() # or wait for next attempt if object_lists[0] and object_lists[1] and \ set(object_lists[0].keys()) == set(object_lists[1].keys()): break else: time.sleep(self.container_sync_interval) self.attempts -= 1 self.assertEqual(object_lists[0], object_lists[1], 'Different object lists in containers.') # Verify object content obj_clients = [(self.clients[c][1], c) for c in self.containers] for obj_client, cont in obj_clients: for obj_name in object_lists[0]: resp, object_content = obj_client.get_object(cont, obj_name) self.assertEqual(object_content, obj_name[::-1].encode()) @test.attr(type='slow') @decorators.skip_because(bug='1317133') @decorators.idempotent_id('be008325-1bba-4925-b7dd-93b58f22ce9b') @testtools.skipIf( not CONF.object_storage_feature_enabled.container_sync, 'Old-style container sync function is disabled') def test_container_synchronization(self): def make_headers(cont, cont_client): # tell first container to synchronize to a second client_proxy_ip = \ urlparse.urlparse(cont_client.base_url).netloc.split(':')[0] client_base_url = \ cont_client.base_url.replace(client_proxy_ip, self.local_ip) headers = {'X-Container-Sync-Key': 'sync_key', 'X-Container-Sync-To': "%s/%s" % (client_base_url, str(cont))} return headers self._test_container_synchronization(make_headers)

41.413333

79

0.650193

import time from six.moves.urllib import parse as urlparse import testtools from tempest.api.object_storage import base from tempest import config from tempest.lib.common.utils import data_utils from tempest.lib import decorators from tempest import test CONF = config.CONF class ContainerSyncTest(base.BaseObjectTest): clients = {} credentials = [['operator', CONF.object_storage.operator_role], ['operator_alt', CONF.object_storage.operator_role]] @classmethod def setup_credentials(cls): super(ContainerSyncTest, cls).setup_credentials() cls.os = cls.os_roles_operator cls.os_alt = cls.os_roles_operator_alt @classmethod def setup_clients(cls): super(ContainerSyncTest, cls).setup_clients() cls.object_client_alt = cls.os_alt.object_client cls.container_client_alt = cls.os_alt.container_client @classmethod def resource_setup(cls): super(ContainerSyncTest, cls).resource_setup() cls.containers = [] cls.objects = [] cls.local_ip = '127.0.0.1' container_sync_timeout = CONF.object_storage.container_sync_timeout cls.container_sync_interval = \ CONF.object_storage.container_sync_interval cls.attempts = \ int(container_sync_timeout / cls.container_sync_interval) cls.clients[data_utils.rand_name(name='TestContainerSync')] = \ (cls.container_client, cls.object_client) cls.clients[data_utils.rand_name(name='TestContainerSync')] = \ (cls.container_client_alt, cls.object_client_alt) for cont_name, client in cls.clients.items(): client[0].create_container(cont_name) cls.containers.append(cont_name) @classmethod def resource_cleanup(cls): for client in cls.clients.values(): cls.delete_containers(client[0], client[1]) super(ContainerSyncTest, cls).resource_cleanup() def _test_container_synchronization(self, make_headers): for cont in (self.containers, self.containers[::-1]): cont_client = [self.clients[c][0] for c in cont] obj_client = [self.clients[c][1] for c in cont] headers = make_headers(cont[1], cont_client[1]) resp, body = \ cont_client[0].put(str(cont[0]), body=None, headers=headers) object_name = data_utils.rand_name(name='TestSyncObject') data = object_name[::-1].encode() resp, _ = obj_client[0].create_object(cont[0], object_name, data) self.objects.append(object_name) cont_client = [self.clients[c][0] for c in self.containers] params = {'format': 'json'} while self.attempts > 0: object_lists = [] for c_client, cont in zip(cont_client, self.containers): resp, object_list = c_client.list_container_contents( cont, params=params) object_lists.append(dict( (obj['name'], obj) for obj in object_list)) if object_lists[0] and object_lists[1] and \ set(object_lists[0].keys()) == set(object_lists[1].keys()): break else: time.sleep(self.container_sync_interval) self.attempts -= 1 self.assertEqual(object_lists[0], object_lists[1], 'Different object lists in containers.') obj_clients = [(self.clients[c][1], c) for c in self.containers] for obj_client, cont in obj_clients: for obj_name in object_lists[0]: resp, object_content = obj_client.get_object(cont, obj_name) self.assertEqual(object_content, obj_name[::-1].encode()) @test.attr(type='slow') @decorators.skip_because(bug='1317133') @decorators.idempotent_id('be008325-1bba-4925-b7dd-93b58f22ce9b') @testtools.skipIf( not CONF.object_storage_feature_enabled.container_sync, 'Old-style container sync function is disabled') def test_container_synchronization(self): def make_headers(cont, cont_client): client_proxy_ip = \ urlparse.urlparse(cont_client.base_url).netloc.split(':')[0] client_base_url = \ cont_client.base_url.replace(client_proxy_ip, self.local_ip) headers = {'X-Container-Sync-Key': 'sync_key', 'X-Container-Sync-To': "%s/%s" % (client_base_url, str(cont))} return headers self._test_container_synchronization(make_headers)

true

1c45ab721c9d7842215f9675276f0e2745f79bac

14,462

py

Python

external/workload-automation/wa/framework/signal.py

qais-yousef/lisa

8343e26bf0565589928a69ccbe67b1be03403db7

[ "Apache-2.0" ]

1

2020-11-30T16:14:02.000Z

external/workload-automation/wa/framework/signal.py

qais-yousef/lisa

8343e26bf0565589928a69ccbe67b1be03403db7

[ "Apache-2.0" ]

null

external/workload-automation/wa/framework/signal.py

qais-yousef/lisa

8343e26bf0565589928a69ccbe67b1be03403db7

[ "Apache-2.0" ]

1

2020-10-09T11:40:00.000Z

# Copyright 2013-2018 ARM Limited # # 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. # """ This module wraps louie signalling mechanism. It relies on modified version of loiue that has prioritization added to handler invocation. """ import sys import logging from contextlib import contextmanager import wrapt from louie import dispatcher # pylint: disable=wrong-import-order from wa.utils.types import prioritylist, enum logger = logging.getLogger('signal') class Signal(object): """ This class implements the signals to be used for notifiying callbacks registered to respond to different states and stages of the execution of workload automation. """ def __init__(self, name, description='no description', invert_priority=False): """ Instantiates a Signal. :param name: name is the identifier of the Signal object. Signal instances with the same name refer to the same execution stage/stage. :param invert_priority: boolean parameter that determines whether multiple callbacks for the same signal should be ordered with ascending or descending priorities. Typically this flag should be set to True if the Signal is triggered AFTER an a state/stage has been reached. That way callbacks with high priorities will be called right after the event has occured. """ self.name = name self.description = description self.invert_priority = invert_priority def __str__(self): return self.name __repr__ = __str__ def __hash__(self): return id(self.name) # Signals associated with run-related events RUN_STARTED = Signal('run-started', 'sent at the beginning of the run') RUN_INITIALIZED = Signal('run-initialized', 'set after the run has been initialized') RUN_ABORTED = Signal('run-aborted', 'set when the run has been aborted due to a keyboard interrupt') RUN_FAILED = Signal('run-failed', 'set if the run has failed to complete all jobs.') RUN_FINALIZED = Signal('run-finalized', 'set after the run has been finalized') RUN_COMPLETED = Signal('run-completed', 'set upon completion of the run (regardless of whether or not it has failed') # Signals associated with job-related events JOB_STARTED = Signal('job-started', 'set when a a new job has been started') JOB_ABORTED = Signal('job-aborted', description=''' sent if a job has been aborted due to a keyboard interrupt. .. note:: While the status of every job that has not had a chance to run due to being interrupted will be set to "ABORTED", this signal will only be sent for the job that was actually running at the time. ''') JOB_FAILED = Signal('job-failed', description='set if the job has failed') JOB_RESTARTED = Signal('job-restarted') JOB_COMPLETED = Signal('job-completed') # Signals associated with particular stages of workload execution BEFORE_WORKLOAD_INITIALIZED = Signal('before-workload-initialized', invert_priority=True) SUCCESSFUL_WORKLOAD_INITIALIZED = Signal('successful-workload-initialized') AFTER_WORKLOAD_INITIALIZED = Signal('after-workload-initialized') BEFORE_WORKLOAD_SETUP = Signal('before-workload-setup', invert_priority=True) SUCCESSFUL_WORKLOAD_SETUP = Signal('successful-workload-setup') AFTER_WORKLOAD_SETUP = Signal('after-workload-setup') BEFORE_WORKLOAD_EXECUTION = Signal('before-workload-execution', invert_priority=True) SUCCESSFUL_WORKLOAD_EXECUTION = Signal('successful-workload-execution') AFTER_WORKLOAD_EXECUTION = Signal('after-workload-execution') BEFORE_WORKLOAD_RESULT_EXTRACTION = Signal('before-workload-result-extracton', invert_priority=True) SUCCESSFUL_WORKLOAD_RESULT_EXTRACTION = Signal('successful-workload-result-extracton') AFTER_WORKLOAD_RESULT_EXTRACTION = Signal('after-workload-result-extracton') BEFORE_WORKLOAD_OUTPUT_UPDATE = Signal('before-workload-output-update', invert_priority=True) SUCCESSFUL_WORKLOAD_OUTPUT_UPDATE = Signal('successful-workload-output-update') AFTER_WORKLOAD_OUTPUT_UPDATE = Signal('after-workload-output-update') BEFORE_WORKLOAD_TEARDOWN = Signal('before-workload-teardown', invert_priority=True) SUCCESSFUL_WORKLOAD_TEARDOWN = Signal('successful-workload-teardown') AFTER_WORKLOAD_TEARDOWN = Signal('after-workload-teardown') BEFORE_WORKLOAD_FINALIZED = Signal('before-workload-finalized', invert_priority=True) SUCCESSFUL_WORKLOAD_FINALIZED = Signal('successful-workload-finalized') AFTER_WORKLOAD_FINALIZED = Signal('after-workload-finalized') # Signals indicating exceptional conditions ERROR_LOGGED = Signal('error-logged') WARNING_LOGGED = Signal('warning-logged') # These are paired events -- if the before_event is sent, the after_ signal is # guaranteed to also be sent. In particular, the after_ signals will be sent # even if there is an error, so you cannot assume in the handler that the # device has booted successfully. In most cases, you should instead use the # non-paired signals below. BEFORE_RUN_INIT = Signal('before-run-init', invert_priority=True) SUCCESSFUL_RUN_INIT = Signal('successful-run-init') AFTER_RUN_INIT = Signal('after-run-init') BEFORE_JOB = Signal('before-job', invert_priority=True) SUCCESSFUL_JOB = Signal('successful-job') AFTER_JOB = Signal('after-job') BEFORE_JOB_QUEUE_EXECUTION = Signal('before-job-queue-execution', invert_priority=True) SUCCESSFUL_JOB_QUEUE_EXECUTION = Signal('successful-job-queue-execution') AFTER_JOB_QUEUE_EXECUTION = Signal('after-job-queue-execution') BEFORE_JOB_TARGET_CONFIG = Signal('before-job-target-config', invert_priority=True) SUCCESSFUL_JOB_TARGET_CONFIG = Signal('successful-job-target-config') AFTER_JOB_TARGET_CONFIG = Signal('after-job-target-config') BEFORE_JOB_OUTPUT_PROCESSED = Signal('before-job-output-processed', invert_priority=True) SUCCESSFUL_JOB_OUTPUT_PROCESSED = Signal('successful-job-output-processed') AFTER_JOB_OUTPUT_PROCESSED = Signal('after-job-output-processed') BEFORE_FLASHING = Signal('before-flashing', invert_priority=True) SUCCESSFUL_FLASHING = Signal('successful-flashing') AFTER_FLASHING = Signal('after-flashing') BEFORE_REBOOT = Signal('before-reboot', invert_priority=True) SUCCESSFUL_REBOOT = Signal('successful-reboot') AFTER_REBOOT = Signal('after-reboot') BEFORE_TARGET_CONNECT = Signal('before-target-connect', invert_priority=True) SUCCESSFUL_TARGET_CONNECT = Signal('successful-target-connect') AFTER_TARGET_CONNECT = Signal('after-target-connect') BEFORE_TARGET_DISCONNECT = Signal('before-target-disconnect', invert_priority=True) SUCCESSFUL_TARGET_DISCONNECT = Signal('successful-target-disconnect') AFTER_TARGET_DISCONNECT = Signal('after-target-disconnect') BEFORE_RUN_OUTPUT_PROCESSED = Signal( 'before-run-output-processed', invert_priority=True) SUCCESSFUL_RUN_OUTPUT_PROCESSED = Signal( 'successful-run-output-processed') AFTER_RUN_OUTPUT_PROCESSED = Signal( 'after-run-output-processed') CallbackPriority = enum(['extremely_low', 'very_low', 'low', 'normal', 'high', 'very_high', 'extremely_high'], -30, 10) class _prioritylist_wrapper(prioritylist): """ This adds a NOP append() method so that when louie invokes it to add the handler to receivers, nothing will happen; the handler is actually added inside the connect() below according to priority, before louie's connect() gets invoked. """ def append(self, *args, **kwargs): pass def connect(handler, signal, sender=dispatcher.Any, priority=0): """ Connects a callback to a signal, so that the callback will be automatically invoked when that signal is sent. Parameters: :handler: This can be any callable that that takes the right arguments for the signal. For most signals this means a single argument that will be an ``ExecutionContext`` instance. But please see documentation for individual signals in the :ref:`signals reference <instruments_method_map>`. :signal: The signal to which the handler will be subscribed. Please see :ref:`signals reference <instruments_method_map>` for the list of standard WA signals. .. note:: There is nothing that prevents instruments from sending their own signals that are not part of the standard set. However the signal must always be an :class:`wa.core.signal.Signal` instance. :sender: The handler will be invoked only for the signals emitted by this sender. By default, this is set to :class:`louie.dispatcher.Any`, so the handler will be invoked for signals from any sender. :priority: An integer (positive or negative) the specifies the priority of the handler. Handlers with higher priority will be called before handlers with lower priority. The call order of handlers with the same priority is not specified. Defaults to 0. .. note:: Priorities for some signals are inverted (so highest priority handlers get executed last). Please see :ref:`signals reference <instruments_method_map>` for details. """ logger.debug('Connecting {} to {}({}) with priority {}'.format(handler, signal, sender, priority)) if getattr(signal, 'invert_priority', False): priority = -priority senderkey = id(sender) if senderkey in dispatcher.connections: signals = dispatcher.connections[senderkey] else: dispatcher.connections[senderkey] = signals = {} if signal in signals: receivers = signals[signal] else: receivers = signals[signal] = _prioritylist_wrapper() receivers.add(handler, priority) dispatcher.connect(handler, signal, sender) def disconnect(handler, signal, sender=dispatcher.Any): """ Disconnect a previously connected handler form the specified signal, optionally, only for the specified sender. Parameters: :handler: The callback to be disconnected. :signal: The signal the handler is to be disconnected form. It will be an :class:`wa.core.signal.Signal` instance. :sender: If specified, the handler will only be disconnected from the signal sent by this sender. """ logger.debug('Disconnecting {} from {}({})'.format(handler, signal, sender)) dispatcher.disconnect(handler, signal, sender) def send(signal, sender=dispatcher.Anonymous, *args, **kwargs): """ Sends a signal, causing connected handlers to be invoked. Paramters: :signal: Signal to be sent. This must be an instance of :class:`wa.core.signal.Signal` or its subclasses. :sender: The sender of the signal (typically, this would be ``self``). Some handlers may only be subscribed to signals from a particular sender. The rest of the parameters will be passed on as aruments to the handler. """ logger.debug('Sending {} from {}'.format(signal, sender)) return dispatcher.send(signal, sender, *args, **kwargs) # This will normally be set to log_error() by init_logging(); see wa.utils.log # Done this way to prevent a circular import dependency. log_error_func = logger.error def safe_send(signal, sender=dispatcher.Anonymous, propagate=None, *args, **kwargs): """ Same as ``send``, except this will catch and log all exceptions raised by handlers, except those specified in ``propagate`` argument (defaults to just ``[KeyboardInterrupt]``). """ if propagate is None: propagate = [KeyboardInterrupt] try: logger.debug('Safe-sending {} from {}'.format(signal, sender)) send(signal, sender, *args, **kwargs) except Exception as e: # pylint: disable=broad-except if any(isinstance(e, p) for p in propagate): raise e log_error_func(e) @contextmanager def wrap(signal_name, sender=dispatcher.Anonymous, *args, **kwargs): # pylint: disable=keyword-arg-before-vararg """Wraps the suite in before/after signals, ensuring that after signal is always sent.""" safe = kwargs.pop('safe', False) signal_name = signal_name.upper().replace('-', '_') send_func = safe_send if safe else send try: before_signal = globals()['BEFORE_' + signal_name] success_signal = globals()['SUCCESSFUL_' + signal_name] after_signal = globals()['AFTER_' + signal_name] except KeyError: raise ValueError('Invalid wrapped signal name: {}'.format(signal_name)) try: send_func(before_signal, sender, *args, **kwargs) yield send_func(success_signal, sender, *args, **kwargs) finally: _, exc, _ = sys.exc_info() if exc: log_error_func(exc) send_func(after_signal, sender, *args, **kwargs) def wrapped(signal_name, sender=dispatcher.Anonymous, safe=False): """A decorator for wrapping function in signal dispatch.""" @wrapt.decorator def signal_wrapped(wrapped_func, _, args, kwargs): def signal_wrapper(*args, **kwargs): with wrap(signal_name, sender, safe): return wrapped_func(*args, **kwargs) return signal_wrapper(*args, **kwargs) return signal_wrapped

42.163265

118

0.691675

import sys import logging from contextlib import contextmanager import wrapt from louie import dispatcher from wa.utils.types import prioritylist, enum logger = logging.getLogger('signal') class Signal(object): def __init__(self, name, description='no description', invert_priority=False): self.name = name self.description = description self.invert_priority = invert_priority def __str__(self): return self.name __repr__ = __str__ def __hash__(self): return id(self.name) RUN_STARTED = Signal('run-started', 'sent at the beginning of the run') RUN_INITIALIZED = Signal('run-initialized', 'set after the run has been initialized') RUN_ABORTED = Signal('run-aborted', 'set when the run has been aborted due to a keyboard interrupt') RUN_FAILED = Signal('run-failed', 'set if the run has failed to complete all jobs.') RUN_FINALIZED = Signal('run-finalized', 'set after the run has been finalized') RUN_COMPLETED = Signal('run-completed', 'set upon completion of the run (regardless of whether or not it has failed') JOB_STARTED = Signal('job-started', 'set when a a new job has been started') JOB_ABORTED = Signal('job-aborted', description=''' sent if a job has been aborted due to a keyboard interrupt. .. note:: While the status of every job that has not had a chance to run due to being interrupted will be set to "ABORTED", this signal will only be sent for the job that was actually running at the time. ''') JOB_FAILED = Signal('job-failed', description='set if the job has failed') JOB_RESTARTED = Signal('job-restarted') JOB_COMPLETED = Signal('job-completed') BEFORE_WORKLOAD_INITIALIZED = Signal('before-workload-initialized', invert_priority=True) SUCCESSFUL_WORKLOAD_INITIALIZED = Signal('successful-workload-initialized') AFTER_WORKLOAD_INITIALIZED = Signal('after-workload-initialized') BEFORE_WORKLOAD_SETUP = Signal('before-workload-setup', invert_priority=True) SUCCESSFUL_WORKLOAD_SETUP = Signal('successful-workload-setup') AFTER_WORKLOAD_SETUP = Signal('after-workload-setup') BEFORE_WORKLOAD_EXECUTION = Signal('before-workload-execution', invert_priority=True) SUCCESSFUL_WORKLOAD_EXECUTION = Signal('successful-workload-execution') AFTER_WORKLOAD_EXECUTION = Signal('after-workload-execution') BEFORE_WORKLOAD_RESULT_EXTRACTION = Signal('before-workload-result-extracton', invert_priority=True) SUCCESSFUL_WORKLOAD_RESULT_EXTRACTION = Signal('successful-workload-result-extracton') AFTER_WORKLOAD_RESULT_EXTRACTION = Signal('after-workload-result-extracton') BEFORE_WORKLOAD_OUTPUT_UPDATE = Signal('before-workload-output-update', invert_priority=True) SUCCESSFUL_WORKLOAD_OUTPUT_UPDATE = Signal('successful-workload-output-update') AFTER_WORKLOAD_OUTPUT_UPDATE = Signal('after-workload-output-update') BEFORE_WORKLOAD_TEARDOWN = Signal('before-workload-teardown', invert_priority=True) SUCCESSFUL_WORKLOAD_TEARDOWN = Signal('successful-workload-teardown') AFTER_WORKLOAD_TEARDOWN = Signal('after-workload-teardown') BEFORE_WORKLOAD_FINALIZED = Signal('before-workload-finalized', invert_priority=True) SUCCESSFUL_WORKLOAD_FINALIZED = Signal('successful-workload-finalized') AFTER_WORKLOAD_FINALIZED = Signal('after-workload-finalized') ERROR_LOGGED = Signal('error-logged') WARNING_LOGGED = Signal('warning-logged') BEFORE_RUN_INIT = Signal('before-run-init', invert_priority=True) SUCCESSFUL_RUN_INIT = Signal('successful-run-init') AFTER_RUN_INIT = Signal('after-run-init') BEFORE_JOB = Signal('before-job', invert_priority=True) SUCCESSFUL_JOB = Signal('successful-job') AFTER_JOB = Signal('after-job') BEFORE_JOB_QUEUE_EXECUTION = Signal('before-job-queue-execution', invert_priority=True) SUCCESSFUL_JOB_QUEUE_EXECUTION = Signal('successful-job-queue-execution') AFTER_JOB_QUEUE_EXECUTION = Signal('after-job-queue-execution') BEFORE_JOB_TARGET_CONFIG = Signal('before-job-target-config', invert_priority=True) SUCCESSFUL_JOB_TARGET_CONFIG = Signal('successful-job-target-config') AFTER_JOB_TARGET_CONFIG = Signal('after-job-target-config') BEFORE_JOB_OUTPUT_PROCESSED = Signal('before-job-output-processed', invert_priority=True) SUCCESSFUL_JOB_OUTPUT_PROCESSED = Signal('successful-job-output-processed') AFTER_JOB_OUTPUT_PROCESSED = Signal('after-job-output-processed') BEFORE_FLASHING = Signal('before-flashing', invert_priority=True) SUCCESSFUL_FLASHING = Signal('successful-flashing') AFTER_FLASHING = Signal('after-flashing') BEFORE_REBOOT = Signal('before-reboot', invert_priority=True) SUCCESSFUL_REBOOT = Signal('successful-reboot') AFTER_REBOOT = Signal('after-reboot') BEFORE_TARGET_CONNECT = Signal('before-target-connect', invert_priority=True) SUCCESSFUL_TARGET_CONNECT = Signal('successful-target-connect') AFTER_TARGET_CONNECT = Signal('after-target-connect') BEFORE_TARGET_DISCONNECT = Signal('before-target-disconnect', invert_priority=True) SUCCESSFUL_TARGET_DISCONNECT = Signal('successful-target-disconnect') AFTER_TARGET_DISCONNECT = Signal('after-target-disconnect') BEFORE_RUN_OUTPUT_PROCESSED = Signal( 'before-run-output-processed', invert_priority=True) SUCCESSFUL_RUN_OUTPUT_PROCESSED = Signal( 'successful-run-output-processed') AFTER_RUN_OUTPUT_PROCESSED = Signal( 'after-run-output-processed') CallbackPriority = enum(['extremely_low', 'very_low', 'low', 'normal', 'high', 'very_high', 'extremely_high'], -30, 10) class _prioritylist_wrapper(prioritylist): def append(self, *args, **kwargs): pass def connect(handler, signal, sender=dispatcher.Any, priority=0): logger.debug('Connecting {} to {}({}) with priority {}'.format(handler, signal, sender, priority)) if getattr(signal, 'invert_priority', False): priority = -priority senderkey = id(sender) if senderkey in dispatcher.connections: signals = dispatcher.connections[senderkey] else: dispatcher.connections[senderkey] = signals = {} if signal in signals: receivers = signals[signal] else: receivers = signals[signal] = _prioritylist_wrapper() receivers.add(handler, priority) dispatcher.connect(handler, signal, sender) def disconnect(handler, signal, sender=dispatcher.Any): logger.debug('Disconnecting {} from {}({})'.format(handler, signal, sender)) dispatcher.disconnect(handler, signal, sender) def send(signal, sender=dispatcher.Anonymous, *args, **kwargs): logger.debug('Sending {} from {}'.format(signal, sender)) return dispatcher.send(signal, sender, *args, **kwargs) log_error_func = logger.error def safe_send(signal, sender=dispatcher.Anonymous, propagate=None, *args, **kwargs): if propagate is None: propagate = [KeyboardInterrupt] try: logger.debug('Safe-sending {} from {}'.format(signal, sender)) send(signal, sender, *args, **kwargs) except Exception as e: if any(isinstance(e, p) for p in propagate): raise e log_error_func(e) @contextmanager def wrap(signal_name, sender=dispatcher.Anonymous, *args, **kwargs): safe = kwargs.pop('safe', False) signal_name = signal_name.upper().replace('-', '_') send_func = safe_send if safe else send try: before_signal = globals()['BEFORE_' + signal_name] success_signal = globals()['SUCCESSFUL_' + signal_name] after_signal = globals()['AFTER_' + signal_name] except KeyError: raise ValueError('Invalid wrapped signal name: {}'.format(signal_name)) try: send_func(before_signal, sender, *args, **kwargs) yield send_func(success_signal, sender, *args, **kwargs) finally: _, exc, _ = sys.exc_info() if exc: log_error_func(exc) send_func(after_signal, sender, *args, **kwargs) def wrapped(signal_name, sender=dispatcher.Anonymous, safe=False): @wrapt.decorator def signal_wrapped(wrapped_func, _, args, kwargs): def signal_wrapper(*args, **kwargs): with wrap(signal_name, sender, safe): return wrapped_func(*args, **kwargs) return signal_wrapper(*args, **kwargs) return signal_wrapped

true

1c45ac250287c61459664f4104f27b4fea00e83d

61

py

Python

language-python-test/test/features/comprehensions/set_comprehension.py

wbadart/language-python

6c048c215ff7fe4a5d5cc36ba3c17a666af74821

[ "BSD-3-Clause" ]

null

language-python-test/test/features/comprehensions/set_comprehension.py

wbadart/language-python

6c048c215ff7fe4a5d5cc36ba3c17a666af74821

[ "BSD-3-Clause" ]

null

language-python-test/test/features/comprehensions/set_comprehension.py

wbadart/language-python

6c048c215ff7fe4a5d5cc36ba3c17a666af74821

[ "BSD-3-Clause" ]

null

{ x + y for x in [1,2,3] if x > 1 for y in [4,5,6] if y < 6}

30.5

60

0.459016

{ x + y for x in [1,2,3] if x > 1 for y in [4,5,6] if y < 6}

true

1c45ad4927dd2f22598e965b4d772bbae5f47434

1,172

py

Python

tests/api/ils/eitems/test_eitems_crud.py

NRodriguezcuellar/invenio-app-ils

144a25a6c56330b214c6fd0b832220fa71f2e68a

[ "MIT" ]

41

2018-09-04T13:00:46.000Z

2022-03-24T20:45:56.000Z

tests/api/ils/eitems/test_eitems_crud.py

NRodriguezcuellar/invenio-app-ils

144a25a6c56330b214c6fd0b832220fa71f2e68a

[ "MIT" ]

720

2017-03-10T08:02:41.000Z

2022-01-14T15:36:37.000Z

tests/api/ils/eitems/test_eitems_crud.py

NRodriguezcuellar/invenio-app-ils

144a25a6c56330b214c6fd0b832220fa71f2e68a

[ "MIT" ]

54

2017-03-09T16:05:29.000Z

2022-03-17T08:34:51.000Z

# -*- coding: utf-8 -*- # # Copyright (C) 2021 CERN. # # Invenio-Circulation is free software; you can redistribute it and/or modify # it under the terms of the MIT License; see LICENSE file for more details. """Tests eitems CRUD.""" import pytest from invenio_app_ils.eitems.api import EItem from invenio_app_ils.errors import DocumentNotFoundError def test_eitem_refs(app, testdata): """Test creation of an eitem.""" eitem = EItem.create( dict( pid="eitemid-99", document_pid="docid-1", created_by=dict(type="script", value="demo"), ) ) assert "$schema" in eitem assert "document" in eitem and "$ref" in eitem["document"] eitem = EItem.get_record_by_pid("eitemid-4") eitem = eitem.replace_refs() assert "document" in eitem and eitem["document"]["title"] def test_eitem_validation(db, testdata): """Test validation when updating an eitem.""" eitem_pid = testdata["eitems"][0]["pid"] eitem = EItem.get_record_by_pid(eitem_pid) # change document pid eitem["document_pid"] = "not_found_doc" with pytest.raises(DocumentNotFoundError): eitem.commit()

27.904762

77

0.669795

import pytest from invenio_app_ils.eitems.api import EItem from invenio_app_ils.errors import DocumentNotFoundError def test_eitem_refs(app, testdata): eitem = EItem.create( dict( pid="eitemid-99", document_pid="docid-1", created_by=dict(type="script", value="demo"), ) ) assert "$schema" in eitem assert "document" in eitem and "$ref" in eitem["document"] eitem = EItem.get_record_by_pid("eitemid-4") eitem = eitem.replace_refs() assert "document" in eitem and eitem["document"]["title"] def test_eitem_validation(db, testdata): eitem_pid = testdata["eitems"][0]["pid"] eitem = EItem.get_record_by_pid(eitem_pid) eitem["document_pid"] = "not_found_doc" with pytest.raises(DocumentNotFoundError): eitem.commit()

true

1c45ad5c3147af9dff358391d91445cf2f8d76bf

3,131

py

Python

from_cpython/Lib/test/test_normalization.py

aisk/pyston

ac69cfef0621dbc8901175e84fa2b5cb5781a646

[ "BSD-2-Clause", "Apache-2.0" ]

9

2015-04-15T10:58:49.000Z

2018-09-24T09:11:33.000Z

Lib/test/test_normalization.py

odsod/cpython-internals-course

55fffca28e83ac0f30029c60113a3110451dfa08

[ "PSF-2.0" ]

2

2020-02-17T22:31:09.000Z

2020-02-18T04:31:55.000Z

Lib/test/test_normalization.py

odsod/cpython-internals-course

55fffca28e83ac0f30029c60113a3110451dfa08

[ "PSF-2.0" ]

9

2015-03-13T18:27:27.000Z

2018-12-03T15:38:51.000Z

from test.test_support import run_unittest, open_urlresource import unittest from httplib import HTTPException import sys import os from unicodedata import normalize, unidata_version TESTDATAFILE = "NormalizationTest.txt" TESTDATAURL = "http://www.unicode.org/Public/" + unidata_version + "/ucd/" + TESTDATAFILE def check_version(testfile): hdr = testfile.readline() return unidata_version in hdr class RangeError(Exception): pass def NFC(str): return normalize("NFC", str) def NFKC(str): return normalize("NFKC", str) def NFD(str): return normalize("NFD", str) def NFKD(str): return normalize("NFKD", str) def unistr(data): data = [int(x, 16) for x in data.split(" ")] for x in data: if x > sys.maxunicode: raise RangeError return u"".join([unichr(x) for x in data]) class NormalizationTest(unittest.TestCase): def test_main(self): part = None part1_data = {} # Hit the exception early try: testdata = open_urlresource(TESTDATAURL, check_version) except (IOError, HTTPException): self.skipTest("Could not retrieve " + TESTDATAURL) for line in testdata: if '#' in line: line = line.split('#')[0] line = line.strip() if not line: continue if line.startswith("@Part"): part = line.split()[0] continue try: c1,c2,c3,c4,c5 = [unistr(x) for x in line.split(';')[:-1]] except RangeError: # Skip unsupported characters; # try at least adding c1 if we are in part1 if part == "@Part1": try: c1 = unistr(line.split(';')[0]) except RangeError: pass else: part1_data[c1] = 1 continue # Perform tests self.assertTrue(c2 == NFC(c1) == NFC(c2) == NFC(c3), line) self.assertTrue(c4 == NFC(c4) == NFC(c5), line) self.assertTrue(c3 == NFD(c1) == NFD(c2) == NFD(c3), line) self.assertTrue(c5 == NFD(c4) == NFD(c5), line) self.assertTrue(c4 == NFKC(c1) == NFKC(c2) == \ NFKC(c3) == NFKC(c4) == NFKC(c5), line) self.assertTrue(c5 == NFKD(c1) == NFKD(c2) == \ NFKD(c3) == NFKD(c4) == NFKD(c5), line) # Record part 1 data if part == "@Part1": part1_data[c1] = 1 # Perform tests for all other data for c in range(sys.maxunicode+1): X = unichr(c) if X in part1_data: continue self.assertTrue(X == NFC(X) == NFD(X) == NFKC(X) == NFKD(X), c) def test_bug_834676(self): # Check for bug 834676 normalize('NFC', u'\ud55c\uae00') def test_main(): run_unittest(NormalizationTest) if __name__ == "__main__": test_main()

30.398058

89

0.516448

from test.test_support import run_unittest, open_urlresource import unittest from httplib import HTTPException import sys import os from unicodedata import normalize, unidata_version TESTDATAFILE = "NormalizationTest.txt" TESTDATAURL = "http://www.unicode.org/Public/" + unidata_version + "/ucd/" + TESTDATAFILE def check_version(testfile): hdr = testfile.readline() return unidata_version in hdr class RangeError(Exception): pass def NFC(str): return normalize("NFC", str) def NFKC(str): return normalize("NFKC", str) def NFD(str): return normalize("NFD", str) def NFKD(str): return normalize("NFKD", str) def unistr(data): data = [int(x, 16) for x in data.split(" ")] for x in data: if x > sys.maxunicode: raise RangeError return u"".join([unichr(x) for x in data]) class NormalizationTest(unittest.TestCase): def test_main(self): part = None part1_data = {} try: testdata = open_urlresource(TESTDATAURL, check_version) except (IOError, HTTPException): self.skipTest("Could not retrieve " + TESTDATAURL) for line in testdata: if '#' in line: line = line.split('#')[0] line = line.strip() if not line: continue if line.startswith("@Part"): part = line.split()[0] continue try: c1,c2,c3,c4,c5 = [unistr(x) for x in line.split(';')[:-1]] except RangeError: if part == "@Part1": try: c1 = unistr(line.split(';')[0]) except RangeError: pass else: part1_data[c1] = 1 continue self.assertTrue(c2 == NFC(c1) == NFC(c2) == NFC(c3), line) self.assertTrue(c4 == NFC(c4) == NFC(c5), line) self.assertTrue(c3 == NFD(c1) == NFD(c2) == NFD(c3), line) self.assertTrue(c5 == NFD(c4) == NFD(c5), line) self.assertTrue(c4 == NFKC(c1) == NFKC(c2) == \ NFKC(c3) == NFKC(c4) == NFKC(c5), line) self.assertTrue(c5 == NFKD(c1) == NFKD(c2) == \ NFKD(c3) == NFKD(c4) == NFKD(c5), line) if part == "@Part1": part1_data[c1] = 1 for c in range(sys.maxunicode+1): X = unichr(c) if X in part1_data: continue self.assertTrue(X == NFC(X) == NFD(X) == NFKC(X) == NFKD(X), c) def test_bug_834676(self): normalize('NFC', u'\ud55c\uae00') def test_main(): run_unittest(NormalizationTest) if __name__ == "__main__": test_main()

true

1c45af1163ca30e3f1de7ee012519613a5a4350b

66,206

py

Python

test/test_datasets.py

CellEight/vision

e8dded4c05ee403633529cef2e09bf94b07f6170

[ "BSD-3-Clause" ]

1

2021-04-12T09:42:25.000Z

test/test_datasets.py

mvpzhangqiu/vision

e8dded4c05ee403633529cef2e09bf94b07f6170

[ "BSD-3-Clause" ]

null

test/test_datasets.py

mvpzhangqiu/vision

e8dded4c05ee403633529cef2e09bf94b07f6170

[ "BSD-3-Clause" ]

null

import contextlib import sys import os import unittest from unittest import mock import numpy as np import PIL from PIL import Image from torch._utils_internal import get_file_path_2 import torchvision from torchvision.datasets import utils from common_utils import get_tmp_dir from fakedata_generation import svhn_root, places365_root, widerface_root, stl10_root import xml.etree.ElementTree as ET from urllib.request import Request, urlopen import itertools import datasets_utils import pathlib import pickle from torchvision import datasets import torch import shutil import json import random import bz2 import torch.nn.functional as F import string import io import zipfile try: import scipy HAS_SCIPY = True except ImportError: HAS_SCIPY = False try: import av HAS_PYAV = True except ImportError: HAS_PYAV = False class DatasetTestcase(unittest.TestCase): def generic_classification_dataset_test(self, dataset, num_images=1): self.assertEqual(len(dataset), num_images) img, target = dataset[0] self.assertTrue(isinstance(img, PIL.Image.Image)) self.assertTrue(isinstance(target, int)) def generic_segmentation_dataset_test(self, dataset, num_images=1): self.assertEqual(len(dataset), num_images) img, target = dataset[0] self.assertTrue(isinstance(img, PIL.Image.Image)) self.assertTrue(isinstance(target, PIL.Image.Image)) class Tester(DatasetTestcase): @mock.patch('torchvision.datasets.SVHN._check_integrity') @unittest.skipIf(not HAS_SCIPY, "scipy unavailable") def test_svhn(self, mock_check): mock_check.return_value = True with svhn_root() as root: dataset = torchvision.datasets.SVHN(root, split="train") self.generic_classification_dataset_test(dataset, num_images=2) dataset = torchvision.datasets.SVHN(root, split="test") self.generic_classification_dataset_test(dataset, num_images=2) dataset = torchvision.datasets.SVHN(root, split="extra") self.generic_classification_dataset_test(dataset, num_images=2) def test_places365(self): for split, small in itertools.product(("train-standard", "train-challenge", "val"), (False, True)): with places365_root(split=split, small=small) as places365: root, data = places365 dataset = torchvision.datasets.Places365(root, split=split, small=small, download=True) self.generic_classification_dataset_test(dataset, num_images=len(data["imgs"])) def test_places365_transforms(self): expected_image = "image" expected_target = "target" def transform(image): return expected_image def target_transform(target): return expected_target with places365_root() as places365: root, data = places365 dataset = torchvision.datasets.Places365( root, transform=transform, target_transform=target_transform, download=True ) actual_image, actual_target = dataset[0] self.assertEqual(actual_image, expected_image) self.assertEqual(actual_target, expected_target) def test_places365_devkit_download(self): for split in ("train-standard", "train-challenge", "val"): with self.subTest(split=split): with places365_root(split=split) as places365: root, data = places365 dataset = torchvision.datasets.Places365(root, split=split, download=True) with self.subTest("classes"): self.assertSequenceEqual(dataset.classes, data["classes"]) with self.subTest("class_to_idx"): self.assertDictEqual(dataset.class_to_idx, data["class_to_idx"]) with self.subTest("imgs"): self.assertSequenceEqual(dataset.imgs, data["imgs"]) def test_places365_devkit_no_download(self): for split in ("train-standard", "train-challenge", "val"): with self.subTest(split=split): with places365_root(split=split) as places365: root, data = places365 with self.assertRaises(RuntimeError): torchvision.datasets.Places365(root, split=split, download=False) def test_places365_images_download(self): for split, small in itertools.product(("train-standard", "train-challenge", "val"), (False, True)): with self.subTest(split=split, small=small): with places365_root(split=split, small=small) as places365: root, data = places365 dataset = torchvision.datasets.Places365(root, split=split, small=small, download=True) assert all(os.path.exists(item[0]) for item in dataset.imgs) def test_places365_images_download_preexisting(self): split = "train-standard" small = False images_dir = "data_large_standard" with places365_root(split=split, small=small) as places365: root, data = places365 os.mkdir(os.path.join(root, images_dir)) with self.assertRaises(RuntimeError): torchvision.datasets.Places365(root, split=split, small=small, download=True) def test_places365_repr_smoke(self): with places365_root() as places365: root, data = places365 dataset = torchvision.datasets.Places365(root, download=True) self.assertIsInstance(repr(dataset), str) class STL10Tester(DatasetTestcase): @contextlib.contextmanager def mocked_root(self): with stl10_root() as (root, data): yield root, data @contextlib.contextmanager def mocked_dataset(self, pre_extract=False, download=True, **kwargs): with self.mocked_root() as (root, data): if pre_extract: utils.extract_archive(os.path.join(root, data["archive"])) dataset = torchvision.datasets.STL10(root, download=download, **kwargs) yield dataset, data def test_not_found(self): with self.assertRaises(RuntimeError): with self.mocked_dataset(download=False): pass def test_splits(self): for split in ('train', 'train+unlabeled', 'unlabeled', 'test'): with self.mocked_dataset(split=split) as (dataset, data): num_images = sum([data["num_images_in_split"][part] for part in split.split("+")]) self.generic_classification_dataset_test(dataset, num_images=num_images) def test_folds(self): for fold in range(10): with self.mocked_dataset(split="train", folds=fold) as (dataset, data): num_images = data["num_images_in_folds"][fold] self.assertEqual(len(dataset), num_images) def test_invalid_folds1(self): with self.assertRaises(ValueError): with self.mocked_dataset(folds=10): pass def test_invalid_folds2(self): with self.assertRaises(ValueError): with self.mocked_dataset(folds="0"): pass def test_transforms(self): expected_image = "image" expected_target = "target" def transform(image): return expected_image def target_transform(target): return expected_target with self.mocked_dataset(transform=transform, target_transform=target_transform) as (dataset, _): actual_image, actual_target = dataset[0] self.assertEqual(actual_image, expected_image) self.assertEqual(actual_target, expected_target) def test_unlabeled(self): with self.mocked_dataset(split="unlabeled") as (dataset, _): labels = [dataset[idx][1] for idx in range(len(dataset))] self.assertTrue(all([label == -1 for label in labels])) @unittest.mock.patch("torchvision.datasets.stl10.download_and_extract_archive") def test_download_preexisting(self, mock): with self.mocked_dataset(pre_extract=True) as (dataset, data): mock.assert_not_called() def test_repr_smoke(self): with self.mocked_dataset() as (dataset, _): self.assertIsInstance(repr(dataset), str) class Caltech101TestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.Caltech101 FEATURE_TYPES = (PIL.Image.Image, (int, np.ndarray, tuple)) ADDITIONAL_CONFIGS = datasets_utils.combinations_grid( target_type=("category", "annotation", ["category", "annotation"]) ) REQUIRED_PACKAGES = ("scipy",) def inject_fake_data(self, tmpdir, config): root = pathlib.Path(tmpdir) / "caltech101" images = root / "101_ObjectCategories" annotations = root / "Annotations" categories = (("Faces", "Faces_2"), ("helicopter", "helicopter"), ("ying_yang", "ying_yang")) num_images_per_category = 2 for image_category, annotation_category in categories: datasets_utils.create_image_folder( root=images, name=image_category, file_name_fn=lambda idx: f"image_{idx + 1:04d}.jpg", num_examples=num_images_per_category, ) self._create_annotation_folder( root=annotations, name=annotation_category, file_name_fn=lambda idx: f"annotation_{idx + 1:04d}.mat", num_examples=num_images_per_category, ) # This is included in the original archive, but is removed by the dataset. Thus, an empty directory suffices. os.makedirs(images / "BACKGROUND_Google") return num_images_per_category * len(categories) def _create_annotation_folder(self, root, name, file_name_fn, num_examples): root = pathlib.Path(root) / name os.makedirs(root) for idx in range(num_examples): self._create_annotation_file(root, file_name_fn(idx)) def _create_annotation_file(self, root, name): mdict = dict(obj_contour=torch.rand((2, torch.randint(3, 6, size=())), dtype=torch.float64).numpy()) datasets_utils.lazy_importer.scipy.io.savemat(str(pathlib.Path(root) / name), mdict) def test_combined_targets(self): target_types = ["category", "annotation"] individual_targets = [] for target_type in target_types: with self.create_dataset(target_type=target_type) as (dataset, _): _, target = dataset[0] individual_targets.append(target) with self.create_dataset(target_type=target_types) as (dataset, _): _, combined_targets = dataset[0] actual = len(individual_targets) expected = len(combined_targets) self.assertEqual( actual, expected, f"The number of the returned combined targets does not match the the number targets if requested " f"individually: {actual} != {expected}", ) for target_type, combined_target, individual_target in zip(target_types, combined_targets, individual_targets): with self.subTest(target_type=target_type): actual = type(combined_target) expected = type(individual_target) self.assertIs( actual, expected, f"Type of the combined target does not match the type of the corresponding individual target: " f"{actual} is not {expected}", ) class Caltech256TestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.Caltech256 def inject_fake_data(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) / "caltech256" / "256_ObjectCategories" categories = ((1, "ak47"), (127, "laptop-101"), (257, "clutter")) num_images_per_category = 2 for idx, category in categories: datasets_utils.create_image_folder( tmpdir, name=f"{idx:03d}.{category}", file_name_fn=lambda image_idx: f"{idx:03d}_{image_idx + 1:04d}.jpg", num_examples=num_images_per_category, ) return num_images_per_category * len(categories) class WIDERFaceTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.WIDERFace FEATURE_TYPES = (PIL.Image.Image, (dict, type(None))) # test split returns None as target ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(split=('train', 'val', 'test')) def inject_fake_data(self, tmpdir, config): widerface_dir = pathlib.Path(tmpdir) / 'widerface' annotations_dir = widerface_dir / 'wider_face_split' os.makedirs(annotations_dir) split_to_idx = split_to_num_examples = { "train": 1, "val": 2, "test": 3, } # We need to create all folders regardless of the split in config for split in ('train', 'val', 'test'): split_idx = split_to_idx[split] num_examples = split_to_num_examples[split] datasets_utils.create_image_folder( root=tmpdir, name=widerface_dir / f'WIDER_{split}' / 'images' / '0--Parade', file_name_fn=lambda image_idx: f"0_Parade_marchingband_1_{split_idx + image_idx}.jpg", num_examples=num_examples, ) annotation_file_name = { 'train': annotations_dir / 'wider_face_train_bbx_gt.txt', 'val': annotations_dir / 'wider_face_val_bbx_gt.txt', 'test': annotations_dir / 'wider_face_test_filelist.txt', }[split] annotation_content = { "train": "".join( f"0--Parade/0_Parade_marchingband_1_{split_idx + image_idx}.jpg\n1\n449 330 122 149 0 0 0 0 0 0\n" for image_idx in range(num_examples) ), "val": "".join( f"0--Parade/0_Parade_marchingband_1_{split_idx + image_idx}.jpg\n1\n501 160 285 443 0 0 0 0 0 0\n" for image_idx in range(num_examples) ), "test": "".join( f"0--Parade/0_Parade_marchingband_1_{split_idx + image_idx}.jpg\n" for image_idx in range(num_examples) ), }[split] with open(annotation_file_name, "w") as annotation_file: annotation_file.write(annotation_content) return split_to_num_examples[config["split"]] class CityScapesTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.Cityscapes TARGET_TYPES = ( "instance", "semantic", "polygon", "color", ) ADDITIONAL_CONFIGS = ( *datasets_utils.combinations_grid( mode=("fine",), split=("train", "test", "val"), target_type=TARGET_TYPES ), *datasets_utils.combinations_grid( mode=("coarse",), split=("train", "train_extra", "val"), target_type=TARGET_TYPES, ), ) FEATURE_TYPES = (PIL.Image.Image, (dict, PIL.Image.Image)) def inject_fake_data(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) mode_to_splits = { "Coarse": ["train", "train_extra", "val"], "Fine": ["train", "test", "val"], } if config["split"] == "train": # just for coverage of the number of samples cities = ["bochum", "bremen"] else: cities = ["bochum"] polygon_target = { "imgHeight": 1024, "imgWidth": 2048, "objects": [ { "label": "sky", "polygon": [ [1241, 0], [1234, 156], [1478, 197], [1611, 172], [1606, 0], ], }, { "label": "road", "polygon": [ [0, 448], [1331, 274], [1473, 265], [2047, 605], [2047, 1023], [0, 1023], ], }, ], } for mode in ["Coarse", "Fine"]: gt_dir = tmpdir / f"gt{mode}" for split in mode_to_splits[mode]: for city in cities: def make_image(name, size=10): datasets_utils.create_image_folder( root=gt_dir / split, name=city, file_name_fn=lambda _: name, size=size, num_examples=1, ) make_image(f"{city}_000000_000000_gt{mode}_instanceIds.png") make_image(f"{city}_000000_000000_gt{mode}_labelIds.png") make_image(f"{city}_000000_000000_gt{mode}_color.png", size=(4, 10, 10)) polygon_target_name = gt_dir / split / city / f"{city}_000000_000000_gt{mode}_polygons.json" with open(polygon_target_name, "w") as outfile: json.dump(polygon_target, outfile) # Create leftImg8bit folder for split in ['test', 'train_extra', 'train', 'val']: for city in cities: datasets_utils.create_image_folder( root=tmpdir / "leftImg8bit" / split, name=city, file_name_fn=lambda _: f"{city}_000000_000000_leftImg8bit.png", num_examples=1, ) info = {'num_examples': len(cities)} if config['target_type'] == 'polygon': info['expected_polygon_target'] = polygon_target return info def test_combined_targets(self): target_types = ['semantic', 'polygon', 'color'] with self.create_dataset(target_type=target_types) as (dataset, _): output = dataset[0] self.assertTrue(isinstance(output, tuple)) self.assertTrue(len(output) == 2) self.assertTrue(isinstance(output[0], PIL.Image.Image)) self.assertTrue(isinstance(output[1], tuple)) self.assertTrue(len(output[1]) == 3) self.assertTrue(isinstance(output[1][0], PIL.Image.Image)) # semantic self.assertTrue(isinstance(output[1][1], dict)) # polygon self.assertTrue(isinstance(output[1][2], PIL.Image.Image)) # color def test_feature_types_target_color(self): with self.create_dataset(target_type='color') as (dataset, _): color_img, color_target = dataset[0] self.assertTrue(isinstance(color_img, PIL.Image.Image)) self.assertTrue(np.array(color_target).shape[2] == 4) def test_feature_types_target_polygon(self): with self.create_dataset(target_type='polygon') as (dataset, info): polygon_img, polygon_target = dataset[0] self.assertTrue(isinstance(polygon_img, PIL.Image.Image)) self.assertEqual(polygon_target, info['expected_polygon_target']) class ImageNetTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.ImageNet REQUIRED_PACKAGES = ('scipy',) ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(split=('train', 'val')) def inject_fake_data(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) wnid = 'n01234567' if config['split'] == 'train': num_examples = 3 datasets_utils.create_image_folder( root=tmpdir, name=tmpdir / 'train' / wnid / wnid, file_name_fn=lambda image_idx: f"{wnid}_{image_idx}.JPEG", num_examples=num_examples, ) else: num_examples = 1 datasets_utils.create_image_folder( root=tmpdir, name=tmpdir / 'val' / wnid, file_name_fn=lambda image_ifx: "ILSVRC2012_val_0000000{image_idx}.JPEG", num_examples=num_examples, ) wnid_to_classes = {wnid: [1]} torch.save((wnid_to_classes, None), tmpdir / 'meta.bin') return num_examples class CIFAR10TestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.CIFAR10 ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(train=(True, False)) _VERSION_CONFIG = dict( base_folder="cifar-10-batches-py", train_files=tuple(f"data_batch_{idx}" for idx in range(1, 6)), test_files=("test_batch",), labels_key="labels", meta_file="batches.meta", num_categories=10, categories_key="label_names", ) def inject_fake_data(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) / self._VERSION_CONFIG["base_folder"] os.makedirs(tmpdir) num_images_per_file = 1 for name in itertools.chain(self._VERSION_CONFIG["train_files"], self._VERSION_CONFIG["test_files"]): self._create_batch_file(tmpdir, name, num_images_per_file) categories = self._create_meta_file(tmpdir) return dict( num_examples=num_images_per_file * len(self._VERSION_CONFIG["train_files"] if config["train"] else self._VERSION_CONFIG["test_files"]), categories=categories, ) def _create_batch_file(self, root, name, num_images): data = datasets_utils.create_image_or_video_tensor((num_images, 32 * 32 * 3)) labels = np.random.randint(0, self._VERSION_CONFIG["num_categories"], size=num_images).tolist() self._create_binary_file(root, name, {"data": data, self._VERSION_CONFIG["labels_key"]: labels}) def _create_meta_file(self, root): categories = [ f"{idx:0{len(str(self._VERSION_CONFIG['num_categories'] - 1))}d}" for idx in range(self._VERSION_CONFIG["num_categories"]) ] self._create_binary_file( root, self._VERSION_CONFIG["meta_file"], {self._VERSION_CONFIG["categories_key"]: categories} ) return categories def _create_binary_file(self, root, name, content): with open(pathlib.Path(root) / name, "wb") as fh: pickle.dump(content, fh) def test_class_to_idx(self): with self.create_dataset() as (dataset, info): expected = {category: label for label, category in enumerate(info["categories"])} actual = dataset.class_to_idx self.assertEqual(actual, expected) class CIFAR100(CIFAR10TestCase): DATASET_CLASS = datasets.CIFAR100 _VERSION_CONFIG = dict( base_folder="cifar-100-python", train_files=("train",), test_files=("test",), labels_key="fine_labels", meta_file="meta", num_categories=100, categories_key="fine_label_names", ) class CelebATestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.CelebA FEATURE_TYPES = (PIL.Image.Image, (torch.Tensor, int, tuple, type(None))) ADDITIONAL_CONFIGS = datasets_utils.combinations_grid( split=("train", "valid", "test", "all"), target_type=("attr", "identity", "bbox", "landmarks", ["attr", "identity"]), ) REQUIRED_PACKAGES = ("pandas",) _SPLIT_TO_IDX = dict(train=0, valid=1, test=2) def inject_fake_data(self, tmpdir, config): base_folder = pathlib.Path(tmpdir) / "celeba" os.makedirs(base_folder) num_images, num_images_per_split = self._create_split_txt(base_folder) datasets_utils.create_image_folder( base_folder, "img_align_celeba", lambda idx: f"{idx + 1:06d}.jpg", num_images ) attr_names = self._create_attr_txt(base_folder, num_images) self._create_identity_txt(base_folder, num_images) self._create_bbox_txt(base_folder, num_images) self._create_landmarks_txt(base_folder, num_images) return dict(num_examples=num_images_per_split[config["split"]], attr_names=attr_names) def _create_split_txt(self, root): num_images_per_split = dict(train=3, valid=2, test=1) data = [ [self._SPLIT_TO_IDX[split]] for split, num_images in num_images_per_split.items() for _ in range(num_images) ] self._create_txt(root, "list_eval_partition.txt", data) num_images_per_split["all"] = num_images = sum(num_images_per_split.values()) return num_images, num_images_per_split def _create_attr_txt(self, root, num_images): header = ("5_o_Clock_Shadow", "Young") data = torch.rand((num_images, len(header))).ge(0.5).int().mul(2).sub(1).tolist() self._create_txt(root, "list_attr_celeba.txt", data, header=header, add_num_examples=True) return header def _create_identity_txt(self, root, num_images): data = torch.randint(1, 4, size=(num_images, 1)).tolist() self._create_txt(root, "identity_CelebA.txt", data) def _create_bbox_txt(self, root, num_images): header = ("x_1", "y_1", "width", "height") data = torch.randint(10, size=(num_images, len(header))).tolist() self._create_txt( root, "list_bbox_celeba.txt", data, header=header, add_num_examples=True, add_image_id_to_header=True ) def _create_landmarks_txt(self, root, num_images): header = ("lefteye_x", "rightmouth_y") data = torch.randint(10, size=(num_images, len(header))).tolist() self._create_txt(root, "list_landmarks_align_celeba.txt", data, header=header, add_num_examples=True) def _create_txt(self, root, name, data, header=None, add_num_examples=False, add_image_id_to_header=False): with open(pathlib.Path(root) / name, "w") as fh: if add_num_examples: fh.write(f"{len(data)}\n") if header: if add_image_id_to_header: header = ("image_id", *header) fh.write(f"{' '.join(header)}\n") for idx, line in enumerate(data, 1): fh.write(f"{' '.join((f'{idx:06d}.jpg', *[str(value) for value in line]))}\n") def test_combined_targets(self): target_types = ["attr", "identity", "bbox", "landmarks"] individual_targets = [] for target_type in target_types: with self.create_dataset(target_type=target_type) as (dataset, _): _, target = dataset[0] individual_targets.append(target) with self.create_dataset(target_type=target_types) as (dataset, _): _, combined_targets = dataset[0] actual = len(individual_targets) expected = len(combined_targets) self.assertEqual( actual, expected, f"The number of the returned combined targets does not match the the number targets if requested " f"individually: {actual} != {expected}", ) for target_type, combined_target, individual_target in zip(target_types, combined_targets, individual_targets): with self.subTest(target_type=target_type): actual = type(combined_target) expected = type(individual_target) self.assertIs( actual, expected, f"Type of the combined target does not match the type of the corresponding individual target: " f"{actual} is not {expected}", ) def test_no_target(self): with self.create_dataset(target_type=[]) as (dataset, _): _, target = dataset[0] self.assertIsNone(target) def test_attr_names(self): with self.create_dataset() as (dataset, info): self.assertEqual(tuple(dataset.attr_names), info["attr_names"]) class VOCSegmentationTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.VOCSegmentation FEATURE_TYPES = (PIL.Image.Image, PIL.Image.Image) ADDITIONAL_CONFIGS = ( *datasets_utils.combinations_grid( year=[f"20{year:02d}" for year in range(7, 13)], image_set=("train", "val", "trainval") ), dict(year="2007", image_set="test"), dict(year="2007-test", image_set="test"), ) def inject_fake_data(self, tmpdir, config): year, is_test_set = ( ("2007", True) if config["year"] == "2007-test" or config["image_set"] == "test" else (config["year"], False) ) image_set = config["image_set"] base_dir = pathlib.Path(tmpdir) if year == "2011": base_dir /= "TrainVal" base_dir = base_dir / "VOCdevkit" / f"VOC{year}" os.makedirs(base_dir) num_images, num_images_per_image_set = self._create_image_set_files(base_dir, "ImageSets", is_test_set) datasets_utils.create_image_folder(base_dir, "JPEGImages", lambda idx: f"{idx:06d}.jpg", num_images) datasets_utils.create_image_folder(base_dir, "SegmentationClass", lambda idx: f"{idx:06d}.png", num_images) annotation = self._create_annotation_files(base_dir, "Annotations", num_images) return dict(num_examples=num_images_per_image_set[image_set], annotation=annotation) def _create_image_set_files(self, root, name, is_test_set): root = pathlib.Path(root) / name src = pathlib.Path(root) / "Main" os.makedirs(src, exist_ok=True) idcs = dict(train=(0, 1, 2), val=(3, 4), test=(5,)) idcs["trainval"] = (*idcs["train"], *idcs["val"]) for image_set in ("test",) if is_test_set else ("train", "val", "trainval"): self._create_image_set_file(src, image_set, idcs[image_set]) shutil.copytree(src, root / "Segmentation") num_images = max(itertools.chain(*idcs.values())) + 1 num_images_per_image_set = dict([(image_set, len(idcs_)) for image_set, idcs_ in idcs.items()]) return num_images, num_images_per_image_set def _create_image_set_file(self, root, image_set, idcs): with open(pathlib.Path(root) / f"{image_set}.txt", "w") as fh: fh.writelines([f"{idx:06d}\n" for idx in idcs]) def _create_annotation_files(self, root, name, num_images): root = pathlib.Path(root) / name os.makedirs(root) for idx in range(num_images): annotation = self._create_annotation_file(root, f"{idx:06d}.xml") return annotation def _create_annotation_file(self, root, name): def add_child(parent, name, text=None): child = ET.SubElement(parent, name) child.text = text return child def add_name(obj, name="dog"): add_child(obj, "name", name) return name def add_bndbox(obj, bndbox=None): if bndbox is None: bndbox = {"xmin": "1", "xmax": "2", "ymin": "3", "ymax": "4"} obj = add_child(obj, "bndbox") for name, text in bndbox.items(): add_child(obj, name, text) return bndbox annotation = ET.Element("annotation") obj = add_child(annotation, "object") data = dict(name=add_name(obj), bndbox=add_bndbox(obj)) with open(pathlib.Path(root) / name, "wb") as fh: fh.write(ET.tostring(annotation)) return data class VOCDetectionTestCase(VOCSegmentationTestCase): DATASET_CLASS = datasets.VOCDetection FEATURE_TYPES = (PIL.Image.Image, dict) def test_annotations(self): with self.create_dataset() as (dataset, info): _, target = dataset[0] self.assertIn("annotation", target) annotation = target["annotation"] self.assertIn("object", annotation) objects = annotation["object"] self.assertEqual(len(objects), 1) object = objects[0] self.assertEqual(object, info["annotation"]) class CocoDetectionTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.CocoDetection FEATURE_TYPES = (PIL.Image.Image, list) REQUIRED_PACKAGES = ("pycocotools",) _IMAGE_FOLDER = "images" _ANNOTATIONS_FOLDER = "annotations" _ANNOTATIONS_FILE = "annotations.json" def dataset_args(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) root = tmpdir / self._IMAGE_FOLDER annotation_file = tmpdir / self._ANNOTATIONS_FOLDER / self._ANNOTATIONS_FILE return root, annotation_file def inject_fake_data(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) num_images = 3 num_annotations_per_image = 2 files = datasets_utils.create_image_folder( tmpdir, name=self._IMAGE_FOLDER, file_name_fn=lambda idx: f"{idx:012d}.jpg", num_examples=num_images ) file_names = [file.relative_to(tmpdir / self._IMAGE_FOLDER) for file in files] annotation_folder = tmpdir / self._ANNOTATIONS_FOLDER os.makedirs(annotation_folder) info = self._create_annotation_file( annotation_folder, self._ANNOTATIONS_FILE, file_names, num_annotations_per_image ) info["num_examples"] = num_images return info def _create_annotation_file(self, root, name, file_names, num_annotations_per_image): image_ids = [int(file_name.stem) for file_name in file_names] images = [dict(file_name=str(file_name), id=id) for file_name, id in zip(file_names, image_ids)] annotations, info = self._create_annotations(image_ids, num_annotations_per_image) self._create_json(root, name, dict(images=images, annotations=annotations)) return info def _create_annotations(self, image_ids, num_annotations_per_image): annotations = datasets_utils.combinations_grid( image_id=image_ids, bbox=([1.0, 2.0, 3.0, 4.0],) * num_annotations_per_image ) for id, annotation in enumerate(annotations): annotation["id"] = id return annotations, dict() def _create_json(self, root, name, content): file = pathlib.Path(root) / name with open(file, "w") as fh: json.dump(content, fh) return file class CocoCaptionsTestCase(CocoDetectionTestCase): DATASET_CLASS = datasets.CocoCaptions def _create_annotations(self, image_ids, num_annotations_per_image): captions = [str(idx) for idx in range(num_annotations_per_image)] annotations = datasets_utils.combinations_grid(image_id=image_ids, caption=captions) for id, annotation in enumerate(annotations): annotation["id"] = id return annotations, dict(captions=captions) def test_captions(self): with self.create_dataset() as (dataset, info): _, captions = dataset[0] self.assertEqual(tuple(captions), tuple(info["captions"])) class UCF101TestCase(datasets_utils.VideoDatasetTestCase): DATASET_CLASS = datasets.UCF101 ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(fold=(1, 2, 3), train=(True, False)) _VIDEO_FOLDER = "videos" _ANNOTATIONS_FOLDER = "annotations" def dataset_args(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) root = tmpdir / self._VIDEO_FOLDER annotation_path = tmpdir / self._ANNOTATIONS_FOLDER return root, annotation_path def inject_fake_data(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) video_folder = tmpdir / self._VIDEO_FOLDER os.makedirs(video_folder) video_files = self._create_videos(video_folder) annotations_folder = tmpdir / self._ANNOTATIONS_FOLDER os.makedirs(annotations_folder) num_examples = self._create_annotation_files(annotations_folder, video_files, config["fold"], config["train"]) return num_examples def _create_videos(self, root, num_examples_per_class=3): def file_name_fn(cls, idx, clips_per_group=2): return f"v_{cls}_g{(idx // clips_per_group) + 1:02d}_c{(idx % clips_per_group) + 1:02d}.avi" video_files = [ datasets_utils.create_video_folder(root, cls, lambda idx: file_name_fn(cls, idx), num_examples_per_class) for cls in ("ApplyEyeMakeup", "YoYo") ] return [path.relative_to(root) for path in itertools.chain(*video_files)] def _create_annotation_files(self, root, video_files, fold, train): current_videos = random.sample(video_files, random.randrange(1, len(video_files) - 1)) current_annotation = self._annotation_file_name(fold, train) self._create_annotation_file(root, current_annotation, current_videos) other_videos = set(video_files) - set(current_videos) other_annotations = [ self._annotation_file_name(fold, train) for fold, train in itertools.product((1, 2, 3), (True, False)) ] other_annotations.remove(current_annotation) for name in other_annotations: self._create_annotation_file(root, name, other_videos) return len(current_videos) def _annotation_file_name(self, fold, train): return f"{'train' if train else 'test'}list{fold:02d}.txt" def _create_annotation_file(self, root, name, video_files): with open(pathlib.Path(root) / name, "w") as fh: fh.writelines(f"{file}\n" for file in sorted(video_files)) class LSUNTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.LSUN REQUIRED_PACKAGES = ("lmdb",) ADDITIONAL_CONFIGS = datasets_utils.combinations_grid( classes=("train", "test", "val", ["bedroom_train", "church_outdoor_train"]) ) _CATEGORIES = ( "bedroom", "bridge", "church_outdoor", "classroom", "conference_room", "dining_room", "kitchen", "living_room", "restaurant", "tower", ) def inject_fake_data(self, tmpdir, config): root = pathlib.Path(tmpdir) num_images = 0 for cls in self._parse_classes(config["classes"]): num_images += self._create_lmdb(root, cls) return num_images @contextlib.contextmanager def create_dataset( self, *args, **kwargs ): with super().create_dataset(*args, **kwargs) as output: yield output # Currently datasets.LSUN caches the keys in the current directory rather than in the root directory. Thus, # this creates a number of unique _cache_* files in the current directory that will not be removed together # with the temporary directory for file in os.listdir(os.getcwd()): if file.startswith("_cache_"): os.remove(file) def _parse_classes(self, classes): if not isinstance(classes, str): return classes split = classes if split == "test": return [split] return [f"{category}_{split}" for category in self._CATEGORIES] def _create_lmdb(self, root, cls): lmdb = datasets_utils.lazy_importer.lmdb hexdigits_lowercase = string.digits + string.ascii_lowercase[:6] folder = f"{cls}_lmdb" num_images = torch.randint(1, 4, size=()).item() format = "png" files = datasets_utils.create_image_folder(root, folder, lambda idx: f"{idx}.{format}", num_images) with lmdb.open(str(root / folder)) as env, env.begin(write=True) as txn: for file in files: key = "".join(random.choice(hexdigits_lowercase) for _ in range(40)).encode() buffer = io.BytesIO() Image.open(file).save(buffer, format) buffer.seek(0) value = buffer.read() txn.put(key, value) os.remove(file) return num_images def test_not_found_or_corrupted(self): # LSUN does not raise built-in exception, but a custom one. It is expressive enough to not 'cast' it to # RuntimeError or FileNotFoundError that are normally checked by this test. with self.assertRaises(datasets_utils.lazy_importer.lmdb.Error): super().test_not_found_or_corrupted() class Kinetics400TestCase(datasets_utils.VideoDatasetTestCase): DATASET_CLASS = datasets.Kinetics400 def inject_fake_data(self, tmpdir, config): classes = ("Abseiling", "Zumba") num_videos_per_class = 2 digits = string.ascii_letters + string.digits + "-_" for cls in classes: datasets_utils.create_video_folder( tmpdir, cls, lambda _: f"{datasets_utils.create_random_string(11, digits)}.avi", num_videos_per_class, ) return num_videos_per_class * len(classes) class HMDB51TestCase(datasets_utils.VideoDatasetTestCase): DATASET_CLASS = datasets.HMDB51 ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(fold=(1, 2, 3), train=(True, False)) _VIDEO_FOLDER = "videos" _SPLITS_FOLDER = "splits" _CLASSES = ("brush_hair", "wave") def dataset_args(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) root = tmpdir / self._VIDEO_FOLDER annotation_path = tmpdir / self._SPLITS_FOLDER return root, annotation_path def inject_fake_data(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) video_folder = tmpdir / self._VIDEO_FOLDER os.makedirs(video_folder) video_files = self._create_videos(video_folder) splits_folder = tmpdir / self._SPLITS_FOLDER os.makedirs(splits_folder) num_examples = self._create_split_files(splits_folder, video_files, config["fold"], config["train"]) return num_examples def _create_videos(self, root, num_examples_per_class=3): def file_name_fn(cls, idx, clips_per_group=2): return f"{cls}_{(idx // clips_per_group) + 1:d}_{(idx % clips_per_group) + 1:d}.avi" return [ ( cls, datasets_utils.create_video_folder( root, cls, lambda idx: file_name_fn(cls, idx), num_examples_per_class, ), ) for cls in self._CLASSES ] def _create_split_files(self, root, video_files, fold, train): num_videos = num_train_videos = 0 for cls, videos in video_files: num_videos += len(videos) train_videos = set(random.sample(videos, random.randrange(1, len(videos) - 1))) num_train_videos += len(train_videos) with open(pathlib.Path(root) / f"{cls}_test_split{fold}.txt", "w") as fh: fh.writelines(f"{file.name} {1 if file in train_videos else 2}\n" for file in videos) return num_train_videos if train else (num_videos - num_train_videos) class OmniglotTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.Omniglot ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(background=(True, False)) def inject_fake_data(self, tmpdir, config): target_folder = ( pathlib.Path(tmpdir) / "omniglot-py" / f"images_{'background' if config['background'] else 'evaluation'}" ) os.makedirs(target_folder) num_images = 0 for name in ("Alphabet_of_the_Magi", "Tifinagh"): num_images += self._create_alphabet_folder(target_folder, name) return num_images def _create_alphabet_folder(self, root, name): num_images_total = 0 for idx in range(torch.randint(1, 4, size=()).item()): num_images = torch.randint(1, 4, size=()).item() num_images_total += num_images datasets_utils.create_image_folder( root / name, f"character{idx:02d}", lambda image_idx: f"{image_idx:02d}.png", num_images ) return num_images_total class SBUTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.SBU FEATURE_TYPES = (PIL.Image.Image, str) def inject_fake_data(self, tmpdir, config): num_images = 3 dataset_folder = pathlib.Path(tmpdir) / "dataset" images = datasets_utils.create_image_folder(tmpdir, "dataset", self._create_file_name, num_images) self._create_urls_txt(dataset_folder, images) self._create_captions_txt(dataset_folder, num_images) return num_images def _create_file_name(self, idx): part1 = datasets_utils.create_random_string(10, string.digits) part2 = datasets_utils.create_random_string(10, string.ascii_lowercase, string.digits[:6]) return f"{part1}_{part2}.jpg" def _create_urls_txt(self, root, images): with open(root / "SBU_captioned_photo_dataset_urls.txt", "w") as fh: for image in images: fh.write( f"http://static.flickr.com/{datasets_utils.create_random_string(4, string.digits)}/{image.name}\n" ) def _create_captions_txt(self, root, num_images): with open(root / "SBU_captioned_photo_dataset_captions.txt", "w") as fh: for _ in range(num_images): fh.write(f"{datasets_utils.create_random_string(10)}\n") class SEMEIONTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.SEMEION def inject_fake_data(self, tmpdir, config): num_images = 3 images = torch.rand(num_images, 256) labels = F.one_hot(torch.randint(10, size=(num_images,))) with open(pathlib.Path(tmpdir) / "semeion.data", "w") as fh: for image, one_hot_labels in zip(images, labels): image_columns = " ".join([f"{pixel.item():.4f}" for pixel in image]) labels_columns = " ".join([str(label.item()) for label in one_hot_labels]) fh.write(f"{image_columns} {labels_columns}\n") return num_images class USPSTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.USPS ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(train=(True, False)) def inject_fake_data(self, tmpdir, config): num_images = 2 if config["train"] else 1 images = torch.rand(num_images, 256) * 2 - 1 labels = torch.randint(1, 11, size=(num_images,)) with bz2.open(pathlib.Path(tmpdir) / f"usps{'.t' if not config['train'] else ''}.bz2", "w") as fh: for image, label in zip(images, labels): line = " ".join((str(label.item()), *[f"{idx}:{pixel:.6f}" for idx, pixel in enumerate(image, 1)])) fh.write(f"{line}\n".encode()) return num_images class SBDatasetTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.SBDataset FEATURE_TYPES = (PIL.Image.Image, (np.ndarray, PIL.Image.Image)) REQUIRED_PACKAGES = ("scipy.io", "scipy.sparse") ADDITIONAL_CONFIGS = datasets_utils.combinations_grid( image_set=("train", "val", "train_noval"), mode=("boundaries", "segmentation") ) _NUM_CLASSES = 20 def inject_fake_data(self, tmpdir, config): num_images, num_images_per_image_set = self._create_split_files(tmpdir) sizes = self._create_target_folder(tmpdir, "cls", num_images) datasets_utils.create_image_folder( tmpdir, "img", lambda idx: f"{self._file_stem(idx)}.jpg", num_images, size=lambda idx: sizes[idx] ) return num_images_per_image_set[config["image_set"]] def _create_split_files(self, root): root = pathlib.Path(root) splits = dict(train=(0, 1, 2), train_noval=(0, 2), val=(3,)) for split, idcs in splits.items(): self._create_split_file(root, split, idcs) num_images = max(itertools.chain(*splits.values())) + 1 num_images_per_split = dict([(split, len(idcs)) for split, idcs in splits.items()]) return num_images, num_images_per_split def _create_split_file(self, root, name, idcs): with open(root / f"{name}.txt", "w") as fh: fh.writelines(f"{self._file_stem(idx)}\n" for idx in idcs) def _create_target_folder(self, root, name, num_images): io = datasets_utils.lazy_importer.scipy.io target_folder = pathlib.Path(root) / name os.makedirs(target_folder) sizes = [torch.randint(1, 4, size=(2,)).tolist() for _ in range(num_images)] for idx, size in enumerate(sizes): content = dict( GTcls=dict(Boundaries=self._create_boundaries(size), Segmentation=self._create_segmentation(size)) ) io.savemat(target_folder / f"{self._file_stem(idx)}.mat", content) return sizes def _create_boundaries(self, size): sparse = datasets_utils.lazy_importer.scipy.sparse return [ [sparse.csc_matrix(torch.randint(0, 2, size=size, dtype=torch.uint8).numpy())] for _ in range(self._NUM_CLASSES) ] def _create_segmentation(self, size): return torch.randint(0, self._NUM_CLASSES + 1, size=size, dtype=torch.uint8).numpy() def _file_stem(self, idx): return f"2008_{idx:06d}" class FakeDataTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.FakeData FEATURE_TYPES = (PIL.Image.Image, int) def dataset_args(self, tmpdir, config): return () def inject_fake_data(self, tmpdir, config): return config["size"] def test_not_found_or_corrupted(self): self.skipTest("The data is generated at creation and thus cannot be non-existent or corrupted.") class PhotoTourTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.PhotoTour # The PhotoTour dataset returns examples with different features with respect to the 'train' parameter. Thus, # we overwrite 'FEATURE_TYPES' with a dummy value to satisfy the initial checks of the base class. Furthermore, we # overwrite the 'test_feature_types()' method to select the correct feature types before the test is run. FEATURE_TYPES = () _TRAIN_FEATURE_TYPES = (torch.Tensor,) _TEST_FEATURE_TYPES = (torch.Tensor, torch.Tensor, torch.Tensor) datasets_utils.combinations_grid(train=(True, False)) _NAME = "liberty" def dataset_args(self, tmpdir, config): return tmpdir, self._NAME def inject_fake_data(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) # In contrast to the original data, the fake images injected here comprise only a single patch. Thus, # num_images == num_patches. num_patches = 5 image_files = self._create_images(tmpdir, self._NAME, num_patches) point_ids, info_file = self._create_info_file(tmpdir / self._NAME, num_patches) num_matches, matches_file = self._create_matches_file(tmpdir / self._NAME, num_patches, point_ids) self._create_archive(tmpdir, self._NAME, *image_files, info_file, matches_file) return num_patches if config["train"] else num_matches def _create_images(self, root, name, num_images): # The images in the PhotoTour dataset comprises of multiple grayscale patches of 64 x 64 pixels. Thus, the # smallest fake image is 64 x 64 pixels and comprises a single patch. return datasets_utils.create_image_folder( root, name, lambda idx: f"patches{idx:04d}.bmp", num_images, size=(1, 64, 64) ) def _create_info_file(self, root, num_images): point_ids = torch.randint(num_images, size=(num_images,)).tolist() file = root / "info.txt" with open(file, "w") as fh: fh.writelines([f"{point_id} 0\n" for point_id in point_ids]) return point_ids, file def _create_matches_file(self, root, num_patches, point_ids): lines = [ f"{patch_id1} {point_ids[patch_id1]} 0 {patch_id2} {point_ids[patch_id2]} 0\n" for patch_id1, patch_id2 in itertools.combinations(range(num_patches), 2) ] file = root / "m50_100000_100000_0.txt" with open(file, "w") as fh: fh.writelines(lines) return len(lines), file def _create_archive(self, root, name, *files): archive = root / f"{name}.zip" with zipfile.ZipFile(archive, "w") as zip: for file in files: zip.write(file, arcname=file.relative_to(root)) return archive @datasets_utils.test_all_configs def test_feature_types(self, config): feature_types = self.FEATURE_TYPES self.FEATURE_TYPES = self._TRAIN_FEATURE_TYPES if config["train"] else self._TEST_FEATURE_TYPES try: super().test_feature_types.__wrapped__(self, config) finally: self.FEATURE_TYPES = feature_types class Flickr8kTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.Flickr8k FEATURE_TYPES = (PIL.Image.Image, list) _IMAGES_FOLDER = "images" _ANNOTATIONS_FILE = "captions.html" def dataset_args(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) root = tmpdir / self._IMAGES_FOLDER ann_file = tmpdir / self._ANNOTATIONS_FILE return str(root), str(ann_file) def inject_fake_data(self, tmpdir, config): num_images = 3 num_captions_per_image = 3 tmpdir = pathlib.Path(tmpdir) images = self._create_images(tmpdir, self._IMAGES_FOLDER, num_images) self._create_annotations_file(tmpdir, self._ANNOTATIONS_FILE, images, num_captions_per_image) return dict(num_examples=num_images, captions=self._create_captions(num_captions_per_image)) def _create_images(self, root, name, num_images): return datasets_utils.create_image_folder(root, name, self._image_file_name, num_images) def _image_file_name(self, idx): id = datasets_utils.create_random_string(10, string.digits) checksum = datasets_utils.create_random_string(10, string.digits, string.ascii_lowercase[:6]) size = datasets_utils.create_random_string(1, "qwcko") return f"{id}_{checksum}_{size}.jpg" def _create_annotations_file(self, root, name, images, num_captions_per_image): with open(root / name, "w") as fh: fh.write("<table>") for image in (None, *images): self._add_image(fh, image, num_captions_per_image) fh.write("</table>") def _add_image(self, fh, image, num_captions_per_image): fh.write("<tr>") self._add_image_header(fh, image) fh.write("</tr><tr><td><ul>") self._add_image_captions(fh, num_captions_per_image) fh.write("</ul></td></tr>") def _add_image_header(self, fh, image=None): if image: url = f"http://www.flickr.com/photos/user/{image.name.split('_')[0]}/" data = f'<a href="{url}">{url}</a>' else: data = "Image Not Found" fh.write(f"<td>{data}</td>") def _add_image_captions(self, fh, num_captions_per_image): for caption in self._create_captions(num_captions_per_image): fh.write(f"<li>{caption}") def _create_captions(self, num_captions_per_image): return [str(idx) for idx in range(num_captions_per_image)] def test_captions(self): with self.create_dataset() as (dataset, info): _, captions = dataset[0] self.assertSequenceEqual(captions, info["captions"]) class Flickr30kTestCase(Flickr8kTestCase): DATASET_CLASS = datasets.Flickr30k FEATURE_TYPES = (PIL.Image.Image, list) _ANNOTATIONS_FILE = "captions.token" def _image_file_name(self, idx): return f"{idx}.jpg" def _create_annotations_file(self, root, name, images, num_captions_per_image): with open(root / name, "w") as fh: for image, (idx, caption) in itertools.product( images, enumerate(self._create_captions(num_captions_per_image)) ): fh.write(f"{image.name}#{idx}\t{caption}\n") class MNISTTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.MNIST ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(train=(True, False)) _MAGIC_DTYPES = { torch.uint8: 8, torch.int8: 9, torch.int16: 11, torch.int32: 12, torch.float32: 13, torch.float64: 14, } _IMAGES_SIZE = (28, 28) _IMAGES_DTYPE = torch.uint8 _LABELS_SIZE = () _LABELS_DTYPE = torch.uint8 def inject_fake_data(self, tmpdir, config): raw_dir = pathlib.Path(tmpdir) / self.DATASET_CLASS.__name__ / "raw" os.makedirs(raw_dir, exist_ok=True) num_images = self._num_images(config) self._create_binary_file( raw_dir, self._images_file(config), (num_images, *self._IMAGES_SIZE), self._IMAGES_DTYPE ) self._create_binary_file( raw_dir, self._labels_file(config), (num_images, *self._LABELS_SIZE), self._LABELS_DTYPE ) return num_images def _num_images(self, config): return 2 if config["train"] else 1 def _images_file(self, config): return f"{self._prefix(config)}-images-idx3-ubyte" def _labels_file(self, config): return f"{self._prefix(config)}-labels-idx1-ubyte" def _prefix(self, config): return "train" if config["train"] else "t10k" def _create_binary_file(self, root, filename, size, dtype): with open(pathlib.Path(root) / filename, "wb") as fh: for meta in (self._magic(dtype, len(size)), *size): fh.write(self._encode(meta)) # If ever an MNIST variant is added that uses floating point data, this should be adapted. data = torch.randint(0, torch.iinfo(dtype).max + 1, size, dtype=dtype) fh.write(data.numpy().tobytes()) def _magic(self, dtype, dims): return self._MAGIC_DTYPES[dtype] * 256 + dims def _encode(self, v): return torch.tensor(v, dtype=torch.int32).numpy().tobytes()[::-1] class FashionMNISTTestCase(MNISTTestCase): DATASET_CLASS = datasets.FashionMNIST class KMNISTTestCase(MNISTTestCase): DATASET_CLASS = datasets.KMNIST class EMNISTTestCase(MNISTTestCase): DATASET_CLASS = datasets.EMNIST DEFAULT_CONFIG = dict(split="byclass") ADDITIONAL_CONFIGS = datasets_utils.combinations_grid( split=("byclass", "bymerge", "balanced", "letters", "digits", "mnist"), train=(True, False) ) def _prefix(self, config): return f"emnist-{config['split']}-{'train' if config['train'] else 'test'}" class QMNISTTestCase(MNISTTestCase): DATASET_CLASS = datasets.QMNIST ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(what=("train", "test", "test10k", "nist")) _LABELS_SIZE = (8,) _LABELS_DTYPE = torch.int32 def _num_images(self, config): if config["what"] == "nist": return 3 elif config["what"] == "train": return 2 elif config["what"] == "test50k": # The split 'test50k' is defined as the last 50k images beginning at index 10000. Thus, we need to create # more than 10000 images for the dataset to not be empty. Since this takes significantly longer than the # creation of all other splits, this is excluded from the 'ADDITIONAL_CONFIGS' and is tested only once in # 'test_num_examples_test50k'. return 10001 else: return 1 def _labels_file(self, config): return f"{self._prefix(config)}-labels-idx2-int" def _prefix(self, config): if config["what"] == "nist": return "xnist" if config["what"] is None: what = "train" if config["train"] else "test" elif config["what"].startswith("test"): what = "test" else: what = config["what"] return f"qmnist-{what}" def test_num_examples_test50k(self): with self.create_dataset(what="test50k") as (dataset, info): # Since the split 'test50k' selects all images beginning from the index 10000, we subtract the number of # created examples by this. self.assertEqual(len(dataset), info["num_examples"] - 10000) class DatasetFolderTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.DatasetFolder # The dataset has no fixed return type since it is defined by the loader parameter. For testing, we use a loader # that simply returns the path as type 'str' instead of loading anything. See the 'dataset_args()' method. FEATURE_TYPES = (str, int) _IMAGE_EXTENSIONS = ("jpg", "png") _VIDEO_EXTENSIONS = ("avi", "mp4") _EXTENSIONS = (*_IMAGE_EXTENSIONS, *_VIDEO_EXTENSIONS) # DatasetFolder has two mutually exclusive parameters: 'extensions' and 'is_valid_file'. One of both is required. # We only iterate over different 'extensions' here and handle the tests for 'is_valid_file' in the # 'test_is_valid_file()' method. DEFAULT_CONFIG = dict(extensions=_EXTENSIONS) ADDITIONAL_CONFIGS = ( *datasets_utils.combinations_grid(extensions=[(ext,) for ext in _IMAGE_EXTENSIONS]), dict(extensions=_IMAGE_EXTENSIONS), *datasets_utils.combinations_grid(extensions=[(ext,) for ext in _VIDEO_EXTENSIONS]), dict(extensions=_VIDEO_EXTENSIONS), ) def dataset_args(self, tmpdir, config): return tmpdir, lambda x: x def inject_fake_data(self, tmpdir, config): extensions = config["extensions"] or self._is_valid_file_to_extensions(config["is_valid_file"]) num_examples_total = 0 classes = [] for ext, cls in zip(self._EXTENSIONS, string.ascii_letters): if ext not in extensions: continue create_example_folder = ( datasets_utils.create_image_folder if ext in self._IMAGE_EXTENSIONS else datasets_utils.create_video_folder ) num_examples = torch.randint(1, 3, size=()).item() create_example_folder(tmpdir, cls, lambda idx: self._file_name_fn(cls, ext, idx), num_examples) num_examples_total += num_examples classes.append(cls) return dict(num_examples=num_examples_total, classes=classes) def _file_name_fn(self, cls, ext, idx): return f"{cls}_{idx}.{ext}" def _is_valid_file_to_extensions(self, is_valid_file): return {ext for ext in self._EXTENSIONS if is_valid_file(f"foo.{ext}")} @datasets_utils.test_all_configs def test_is_valid_file(self, config): extensions = config.pop("extensions") # We need to explicitly pass extensions=None here or otherwise it would be filled by the value from the # DEFAULT_CONFIG. with self.create_dataset( config, extensions=None, is_valid_file=lambda file: pathlib.Path(file).suffix[1:] in extensions ) as (dataset, info): self.assertEqual(len(dataset), info["num_examples"]) @datasets_utils.test_all_configs def test_classes(self, config): with self.create_dataset(config) as (dataset, info): self.assertSequenceEqual(dataset.classes, info["classes"]) class ImageFolderTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.ImageFolder def inject_fake_data(self, tmpdir, config): num_examples_total = 0 classes = ("a", "b") for cls in classes: num_examples = torch.randint(1, 3, size=()).item() num_examples_total += num_examples datasets_utils.create_image_folder(tmpdir, cls, lambda idx: f"{cls}_{idx}.png", num_examples) return dict(num_examples=num_examples_total, classes=classes) @datasets_utils.test_all_configs def test_classes(self, config): with self.create_dataset(config) as (dataset, info): self.assertSequenceEqual(dataset.classes, info["classes"]) class KittiTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.Kitti FEATURE_TYPES = (PIL.Image.Image, (list, type(None))) # test split returns None as target ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(train=(True, False)) def inject_fake_data(self, tmpdir, config): kitti_dir = os.path.join(tmpdir, "Kitti", "raw") os.makedirs(kitti_dir) split_to_num_examples = { True: 1, False: 2, } # We need to create all folders(training and testing). for is_training in (True, False): num_examples = split_to_num_examples[is_training] datasets_utils.create_image_folder( root=kitti_dir, name=os.path.join("training" if is_training else "testing", "image_2"), file_name_fn=lambda image_idx: f"{image_idx:06d}.png", num_examples=num_examples, ) if is_training: for image_idx in range(num_examples): target_file_dir = os.path.join(kitti_dir, "training", "label_2") os.makedirs(target_file_dir) target_file_name = os.path.join(target_file_dir, f"{image_idx:06d}.txt") target_contents = "Pedestrian 0.00 0 -0.20 712.40 143.00 810.73 307.92 1.89 0.48 1.20 1.84 1.47 8.41 0.01\n" # noqa with open(target_file_name, "w") as target_file: target_file.write(target_contents) return split_to_num_examples[config["train"]] if __name__ == "__main__": unittest.main()

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import contextlib import sys import os import unittest from unittest import mock import numpy as np import PIL from PIL import Image from torch._utils_internal import get_file_path_2 import torchvision from torchvision.datasets import utils from common_utils import get_tmp_dir from fakedata_generation import svhn_root, places365_root, widerface_root, stl10_root import xml.etree.ElementTree as ET from urllib.request import Request, urlopen import itertools import datasets_utils import pathlib import pickle from torchvision import datasets import torch import shutil import json import random import bz2 import torch.nn.functional as F import string import io import zipfile try: import scipy HAS_SCIPY = True except ImportError: HAS_SCIPY = False try: import av HAS_PYAV = True except ImportError: HAS_PYAV = False class DatasetTestcase(unittest.TestCase): def generic_classification_dataset_test(self, dataset, num_images=1): self.assertEqual(len(dataset), num_images) img, target = dataset[0] self.assertTrue(isinstance(img, PIL.Image.Image)) self.assertTrue(isinstance(target, int)) def generic_segmentation_dataset_test(self, dataset, num_images=1): self.assertEqual(len(dataset), num_images) img, target = dataset[0] self.assertTrue(isinstance(img, PIL.Image.Image)) self.assertTrue(isinstance(target, PIL.Image.Image)) class Tester(DatasetTestcase): @mock.patch('torchvision.datasets.SVHN._check_integrity') @unittest.skipIf(not HAS_SCIPY, "scipy unavailable") def test_svhn(self, mock_check): mock_check.return_value = True with svhn_root() as root: dataset = torchvision.datasets.SVHN(root, split="train") self.generic_classification_dataset_test(dataset, num_images=2) dataset = torchvision.datasets.SVHN(root, split="test") self.generic_classification_dataset_test(dataset, num_images=2) dataset = torchvision.datasets.SVHN(root, split="extra") self.generic_classification_dataset_test(dataset, num_images=2) def test_places365(self): for split, small in itertools.product(("train-standard", "train-challenge", "val"), (False, True)): with places365_root(split=split, small=small) as places365: root, data = places365 dataset = torchvision.datasets.Places365(root, split=split, small=small, download=True) self.generic_classification_dataset_test(dataset, num_images=len(data["imgs"])) def test_places365_transforms(self): expected_image = "image" expected_target = "target" def transform(image): return expected_image def target_transform(target): return expected_target with places365_root() as places365: root, data = places365 dataset = torchvision.datasets.Places365( root, transform=transform, target_transform=target_transform, download=True ) actual_image, actual_target = dataset[0] self.assertEqual(actual_image, expected_image) self.assertEqual(actual_target, expected_target) def test_places365_devkit_download(self): for split in ("train-standard", "train-challenge", "val"): with self.subTest(split=split): with places365_root(split=split) as places365: root, data = places365 dataset = torchvision.datasets.Places365(root, split=split, download=True) with self.subTest("classes"): self.assertSequenceEqual(dataset.classes, data["classes"]) with self.subTest("class_to_idx"): self.assertDictEqual(dataset.class_to_idx, data["class_to_idx"]) with self.subTest("imgs"): self.assertSequenceEqual(dataset.imgs, data["imgs"]) def test_places365_devkit_no_download(self): for split in ("train-standard", "train-challenge", "val"): with self.subTest(split=split): with places365_root(split=split) as places365: root, data = places365 with self.assertRaises(RuntimeError): torchvision.datasets.Places365(root, split=split, download=False) def test_places365_images_download(self): for split, small in itertools.product(("train-standard", "train-challenge", "val"), (False, True)): with self.subTest(split=split, small=small): with places365_root(split=split, small=small) as places365: root, data = places365 dataset = torchvision.datasets.Places365(root, split=split, small=small, download=True) assert all(os.path.exists(item[0]) for item in dataset.imgs) def test_places365_images_download_preexisting(self): split = "train-standard" small = False images_dir = "data_large_standard" with places365_root(split=split, small=small) as places365: root, data = places365 os.mkdir(os.path.join(root, images_dir)) with self.assertRaises(RuntimeError): torchvision.datasets.Places365(root, split=split, small=small, download=True) def test_places365_repr_smoke(self): with places365_root() as places365: root, data = places365 dataset = torchvision.datasets.Places365(root, download=True) self.assertIsInstance(repr(dataset), str) class STL10Tester(DatasetTestcase): @contextlib.contextmanager def mocked_root(self): with stl10_root() as (root, data): yield root, data @contextlib.contextmanager def mocked_dataset(self, pre_extract=False, download=True, **kwargs): with self.mocked_root() as (root, data): if pre_extract: utils.extract_archive(os.path.join(root, data["archive"])) dataset = torchvision.datasets.STL10(root, download=download, **kwargs) yield dataset, data def test_not_found(self): with self.assertRaises(RuntimeError): with self.mocked_dataset(download=False): pass def test_splits(self): for split in ('train', 'train+unlabeled', 'unlabeled', 'test'): with self.mocked_dataset(split=split) as (dataset, data): num_images = sum([data["num_images_in_split"][part] for part in split.split("+")]) self.generic_classification_dataset_test(dataset, num_images=num_images) def test_folds(self): for fold in range(10): with self.mocked_dataset(split="train", folds=fold) as (dataset, data): num_images = data["num_images_in_folds"][fold] self.assertEqual(len(dataset), num_images) def test_invalid_folds1(self): with self.assertRaises(ValueError): with self.mocked_dataset(folds=10): pass def test_invalid_folds2(self): with self.assertRaises(ValueError): with self.mocked_dataset(folds="0"): pass def test_transforms(self): expected_image = "image" expected_target = "target" def transform(image): return expected_image def target_transform(target): return expected_target with self.mocked_dataset(transform=transform, target_transform=target_transform) as (dataset, _): actual_image, actual_target = dataset[0] self.assertEqual(actual_image, expected_image) self.assertEqual(actual_target, expected_target) def test_unlabeled(self): with self.mocked_dataset(split="unlabeled") as (dataset, _): labels = [dataset[idx][1] for idx in range(len(dataset))] self.assertTrue(all([label == -1 for label in labels])) @unittest.mock.patch("torchvision.datasets.stl10.download_and_extract_archive") def test_download_preexisting(self, mock): with self.mocked_dataset(pre_extract=True) as (dataset, data): mock.assert_not_called() def test_repr_smoke(self): with self.mocked_dataset() as (dataset, _): self.assertIsInstance(repr(dataset), str) class Caltech101TestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.Caltech101 FEATURE_TYPES = (PIL.Image.Image, (int, np.ndarray, tuple)) ADDITIONAL_CONFIGS = datasets_utils.combinations_grid( target_type=("category", "annotation", ["category", "annotation"]) ) REQUIRED_PACKAGES = ("scipy",) def inject_fake_data(self, tmpdir, config): root = pathlib.Path(tmpdir) / "caltech101" images = root / "101_ObjectCategories" annotations = root / "Annotations" categories = (("Faces", "Faces_2"), ("helicopter", "helicopter"), ("ying_yang", "ying_yang")) num_images_per_category = 2 for image_category, annotation_category in categories: datasets_utils.create_image_folder( root=images, name=image_category, file_name_fn=lambda idx: f"image_{idx + 1:04d}.jpg", num_examples=num_images_per_category, ) self._create_annotation_folder( root=annotations, name=annotation_category, file_name_fn=lambda idx: f"annotation_{idx + 1:04d}.mat", num_examples=num_images_per_category, ) os.makedirs(images / "BACKGROUND_Google") return num_images_per_category * len(categories) def _create_annotation_folder(self, root, name, file_name_fn, num_examples): root = pathlib.Path(root) / name os.makedirs(root) for idx in range(num_examples): self._create_annotation_file(root, file_name_fn(idx)) def _create_annotation_file(self, root, name): mdict = dict(obj_contour=torch.rand((2, torch.randint(3, 6, size=())), dtype=torch.float64).numpy()) datasets_utils.lazy_importer.scipy.io.savemat(str(pathlib.Path(root) / name), mdict) def test_combined_targets(self): target_types = ["category", "annotation"] individual_targets = [] for target_type in target_types: with self.create_dataset(target_type=target_type) as (dataset, _): _, target = dataset[0] individual_targets.append(target) with self.create_dataset(target_type=target_types) as (dataset, _): _, combined_targets = dataset[0] actual = len(individual_targets) expected = len(combined_targets) self.assertEqual( actual, expected, f"The number of the returned combined targets does not match the the number targets if requested " f"individually: {actual} != {expected}", ) for target_type, combined_target, individual_target in zip(target_types, combined_targets, individual_targets): with self.subTest(target_type=target_type): actual = type(combined_target) expected = type(individual_target) self.assertIs( actual, expected, f"Type of the combined target does not match the type of the corresponding individual target: " f"{actual} is not {expected}", ) class Caltech256TestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.Caltech256 def inject_fake_data(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) / "caltech256" / "256_ObjectCategories" categories = ((1, "ak47"), (127, "laptop-101"), (257, "clutter")) num_images_per_category = 2 for idx, category in categories: datasets_utils.create_image_folder( tmpdir, name=f"{idx:03d}.{category}", file_name_fn=lambda image_idx: f"{idx:03d}_{image_idx + 1:04d}.jpg", num_examples=num_images_per_category, ) return num_images_per_category * len(categories) class WIDERFaceTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.WIDERFace FEATURE_TYPES = (PIL.Image.Image, (dict, type(None))) ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(split=('train', 'val', 'test')) def inject_fake_data(self, tmpdir, config): widerface_dir = pathlib.Path(tmpdir) / 'widerface' annotations_dir = widerface_dir / 'wider_face_split' os.makedirs(annotations_dir) split_to_idx = split_to_num_examples = { "train": 1, "val": 2, "test": 3, } for split in ('train', 'val', 'test'): split_idx = split_to_idx[split] num_examples = split_to_num_examples[split] datasets_utils.create_image_folder( root=tmpdir, name=widerface_dir / f'WIDER_{split}' / 'images' / '0--Parade', file_name_fn=lambda image_idx: f"0_Parade_marchingband_1_{split_idx + image_idx}.jpg", num_examples=num_examples, ) annotation_file_name = { 'train': annotations_dir / 'wider_face_train_bbx_gt.txt', 'val': annotations_dir / 'wider_face_val_bbx_gt.txt', 'test': annotations_dir / 'wider_face_test_filelist.txt', }[split] annotation_content = { "train": "".join( f"0--Parade/0_Parade_marchingband_1_{split_idx + image_idx}.jpg\n1\n449 330 122 149 0 0 0 0 0 0\n" for image_idx in range(num_examples) ), "val": "".join( f"0--Parade/0_Parade_marchingband_1_{split_idx + image_idx}.jpg\n1\n501 160 285 443 0 0 0 0 0 0\n" for image_idx in range(num_examples) ), "test": "".join( f"0--Parade/0_Parade_marchingband_1_{split_idx + image_idx}.jpg\n" for image_idx in range(num_examples) ), }[split] with open(annotation_file_name, "w") as annotation_file: annotation_file.write(annotation_content) return split_to_num_examples[config["split"]] class CityScapesTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.Cityscapes TARGET_TYPES = ( "instance", "semantic", "polygon", "color", ) ADDITIONAL_CONFIGS = ( *datasets_utils.combinations_grid( mode=("fine",), split=("train", "test", "val"), target_type=TARGET_TYPES ), *datasets_utils.combinations_grid( mode=("coarse",), split=("train", "train_extra", "val"), target_type=TARGET_TYPES, ), ) FEATURE_TYPES = (PIL.Image.Image, (dict, PIL.Image.Image)) def inject_fake_data(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) mode_to_splits = { "Coarse": ["train", "train_extra", "val"], "Fine": ["train", "test", "val"], } if config["split"] == "train": cities = ["bochum", "bremen"] else: cities = ["bochum"] polygon_target = { "imgHeight": 1024, "imgWidth": 2048, "objects": [ { "label": "sky", "polygon": [ [1241, 0], [1234, 156], [1478, 197], [1611, 172], [1606, 0], ], }, { "label": "road", "polygon": [ [0, 448], [1331, 274], [1473, 265], [2047, 605], [2047, 1023], [0, 1023], ], }, ], } for mode in ["Coarse", "Fine"]: gt_dir = tmpdir / f"gt{mode}" for split in mode_to_splits[mode]: for city in cities: def make_image(name, size=10): datasets_utils.create_image_folder( root=gt_dir / split, name=city, file_name_fn=lambda _: name, size=size, num_examples=1, ) make_image(f"{city}_000000_000000_gt{mode}_instanceIds.png") make_image(f"{city}_000000_000000_gt{mode}_labelIds.png") make_image(f"{city}_000000_000000_gt{mode}_color.png", size=(4, 10, 10)) polygon_target_name = gt_dir / split / city / f"{city}_000000_000000_gt{mode}_polygons.json" with open(polygon_target_name, "w") as outfile: json.dump(polygon_target, outfile) for split in ['test', 'train_extra', 'train', 'val']: for city in cities: datasets_utils.create_image_folder( root=tmpdir / "leftImg8bit" / split, name=city, file_name_fn=lambda _: f"{city}_000000_000000_leftImg8bit.png", num_examples=1, ) info = {'num_examples': len(cities)} if config['target_type'] == 'polygon': info['expected_polygon_target'] = polygon_target return info def test_combined_targets(self): target_types = ['semantic', 'polygon', 'color'] with self.create_dataset(target_type=target_types) as (dataset, _): output = dataset[0] self.assertTrue(isinstance(output, tuple)) self.assertTrue(len(output) == 2) self.assertTrue(isinstance(output[0], PIL.Image.Image)) self.assertTrue(isinstance(output[1], tuple)) self.assertTrue(len(output[1]) == 3) self.assertTrue(isinstance(output[1][0], PIL.Image.Image)) self.assertTrue(isinstance(output[1][1], dict)) self.assertTrue(isinstance(output[1][2], PIL.Image.Image)) def test_feature_types_target_color(self): with self.create_dataset(target_type='color') as (dataset, _): color_img, color_target = dataset[0] self.assertTrue(isinstance(color_img, PIL.Image.Image)) self.assertTrue(np.array(color_target).shape[2] == 4) def test_feature_types_target_polygon(self): with self.create_dataset(target_type='polygon') as (dataset, info): polygon_img, polygon_target = dataset[0] self.assertTrue(isinstance(polygon_img, PIL.Image.Image)) self.assertEqual(polygon_target, info['expected_polygon_target']) class ImageNetTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.ImageNet REQUIRED_PACKAGES = ('scipy',) ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(split=('train', 'val')) def inject_fake_data(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) wnid = 'n01234567' if config['split'] == 'train': num_examples = 3 datasets_utils.create_image_folder( root=tmpdir, name=tmpdir / 'train' / wnid / wnid, file_name_fn=lambda image_idx: f"{wnid}_{image_idx}.JPEG", num_examples=num_examples, ) else: num_examples = 1 datasets_utils.create_image_folder( root=tmpdir, name=tmpdir / 'val' / wnid, file_name_fn=lambda image_ifx: "ILSVRC2012_val_0000000{image_idx}.JPEG", num_examples=num_examples, ) wnid_to_classes = {wnid: [1]} torch.save((wnid_to_classes, None), tmpdir / 'meta.bin') return num_examples class CIFAR10TestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.CIFAR10 ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(train=(True, False)) _VERSION_CONFIG = dict( base_folder="cifar-10-batches-py", train_files=tuple(f"data_batch_{idx}" for idx in range(1, 6)), test_files=("test_batch",), labels_key="labels", meta_file="batches.meta", num_categories=10, categories_key="label_names", ) def inject_fake_data(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) / self._VERSION_CONFIG["base_folder"] os.makedirs(tmpdir) num_images_per_file = 1 for name in itertools.chain(self._VERSION_CONFIG["train_files"], self._VERSION_CONFIG["test_files"]): self._create_batch_file(tmpdir, name, num_images_per_file) categories = self._create_meta_file(tmpdir) return dict( num_examples=num_images_per_file * len(self._VERSION_CONFIG["train_files"] if config["train"] else self._VERSION_CONFIG["test_files"]), categories=categories, ) def _create_batch_file(self, root, name, num_images): data = datasets_utils.create_image_or_video_tensor((num_images, 32 * 32 * 3)) labels = np.random.randint(0, self._VERSION_CONFIG["num_categories"], size=num_images).tolist() self._create_binary_file(root, name, {"data": data, self._VERSION_CONFIG["labels_key"]: labels}) def _create_meta_file(self, root): categories = [ f"{idx:0{len(str(self._VERSION_CONFIG['num_categories'] - 1))}d}" for idx in range(self._VERSION_CONFIG["num_categories"]) ] self._create_binary_file( root, self._VERSION_CONFIG["meta_file"], {self._VERSION_CONFIG["categories_key"]: categories} ) return categories def _create_binary_file(self, root, name, content): with open(pathlib.Path(root) / name, "wb") as fh: pickle.dump(content, fh) def test_class_to_idx(self): with self.create_dataset() as (dataset, info): expected = {category: label for label, category in enumerate(info["categories"])} actual = dataset.class_to_idx self.assertEqual(actual, expected) class CIFAR100(CIFAR10TestCase): DATASET_CLASS = datasets.CIFAR100 _VERSION_CONFIG = dict( base_folder="cifar-100-python", train_files=("train",), test_files=("test",), labels_key="fine_labels", meta_file="meta", num_categories=100, categories_key="fine_label_names", ) class CelebATestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.CelebA FEATURE_TYPES = (PIL.Image.Image, (torch.Tensor, int, tuple, type(None))) ADDITIONAL_CONFIGS = datasets_utils.combinations_grid( split=("train", "valid", "test", "all"), target_type=("attr", "identity", "bbox", "landmarks", ["attr", "identity"]), ) REQUIRED_PACKAGES = ("pandas",) _SPLIT_TO_IDX = dict(train=0, valid=1, test=2) def inject_fake_data(self, tmpdir, config): base_folder = pathlib.Path(tmpdir) / "celeba" os.makedirs(base_folder) num_images, num_images_per_split = self._create_split_txt(base_folder) datasets_utils.create_image_folder( base_folder, "img_align_celeba", lambda idx: f"{idx + 1:06d}.jpg", num_images ) attr_names = self._create_attr_txt(base_folder, num_images) self._create_identity_txt(base_folder, num_images) self._create_bbox_txt(base_folder, num_images) self._create_landmarks_txt(base_folder, num_images) return dict(num_examples=num_images_per_split[config["split"]], attr_names=attr_names) def _create_split_txt(self, root): num_images_per_split = dict(train=3, valid=2, test=1) data = [ [self._SPLIT_TO_IDX[split]] for split, num_images in num_images_per_split.items() for _ in range(num_images) ] self._create_txt(root, "list_eval_partition.txt", data) num_images_per_split["all"] = num_images = sum(num_images_per_split.values()) return num_images, num_images_per_split def _create_attr_txt(self, root, num_images): header = ("5_o_Clock_Shadow", "Young") data = torch.rand((num_images, len(header))).ge(0.5).int().mul(2).sub(1).tolist() self._create_txt(root, "list_attr_celeba.txt", data, header=header, add_num_examples=True) return header def _create_identity_txt(self, root, num_images): data = torch.randint(1, 4, size=(num_images, 1)).tolist() self._create_txt(root, "identity_CelebA.txt", data) def _create_bbox_txt(self, root, num_images): header = ("x_1", "y_1", "width", "height") data = torch.randint(10, size=(num_images, len(header))).tolist() self._create_txt( root, "list_bbox_celeba.txt", data, header=header, add_num_examples=True, add_image_id_to_header=True ) def _create_landmarks_txt(self, root, num_images): header = ("lefteye_x", "rightmouth_y") data = torch.randint(10, size=(num_images, len(header))).tolist() self._create_txt(root, "list_landmarks_align_celeba.txt", data, header=header, add_num_examples=True) def _create_txt(self, root, name, data, header=None, add_num_examples=False, add_image_id_to_header=False): with open(pathlib.Path(root) / name, "w") as fh: if add_num_examples: fh.write(f"{len(data)}\n") if header: if add_image_id_to_header: header = ("image_id", *header) fh.write(f"{' '.join(header)}\n") for idx, line in enumerate(data, 1): fh.write(f"{' '.join((f'{idx:06d}.jpg', *[str(value) for value in line]))}\n") def test_combined_targets(self): target_types = ["attr", "identity", "bbox", "landmarks"] individual_targets = [] for target_type in target_types: with self.create_dataset(target_type=target_type) as (dataset, _): _, target = dataset[0] individual_targets.append(target) with self.create_dataset(target_type=target_types) as (dataset, _): _, combined_targets = dataset[0] actual = len(individual_targets) expected = len(combined_targets) self.assertEqual( actual, expected, f"The number of the returned combined targets does not match the the number targets if requested " f"individually: {actual} != {expected}", ) for target_type, combined_target, individual_target in zip(target_types, combined_targets, individual_targets): with self.subTest(target_type=target_type): actual = type(combined_target) expected = type(individual_target) self.assertIs( actual, expected, f"Type of the combined target does not match the type of the corresponding individual target: " f"{actual} is not {expected}", ) def test_no_target(self): with self.create_dataset(target_type=[]) as (dataset, _): _, target = dataset[0] self.assertIsNone(target) def test_attr_names(self): with self.create_dataset() as (dataset, info): self.assertEqual(tuple(dataset.attr_names), info["attr_names"]) class VOCSegmentationTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.VOCSegmentation FEATURE_TYPES = (PIL.Image.Image, PIL.Image.Image) ADDITIONAL_CONFIGS = ( *datasets_utils.combinations_grid( year=[f"20{year:02d}" for year in range(7, 13)], image_set=("train", "val", "trainval") ), dict(year="2007", image_set="test"), dict(year="2007-test", image_set="test"), ) def inject_fake_data(self, tmpdir, config): year, is_test_set = ( ("2007", True) if config["year"] == "2007-test" or config["image_set"] == "test" else (config["year"], False) ) image_set = config["image_set"] base_dir = pathlib.Path(tmpdir) if year == "2011": base_dir /= "TrainVal" base_dir = base_dir / "VOCdevkit" / f"VOC{year}" os.makedirs(base_dir) num_images, num_images_per_image_set = self._create_image_set_files(base_dir, "ImageSets", is_test_set) datasets_utils.create_image_folder(base_dir, "JPEGImages", lambda idx: f"{idx:06d}.jpg", num_images) datasets_utils.create_image_folder(base_dir, "SegmentationClass", lambda idx: f"{idx:06d}.png", num_images) annotation = self._create_annotation_files(base_dir, "Annotations", num_images) return dict(num_examples=num_images_per_image_set[image_set], annotation=annotation) def _create_image_set_files(self, root, name, is_test_set): root = pathlib.Path(root) / name src = pathlib.Path(root) / "Main" os.makedirs(src, exist_ok=True) idcs = dict(train=(0, 1, 2), val=(3, 4), test=(5,)) idcs["trainval"] = (*idcs["train"], *idcs["val"]) for image_set in ("test",) if is_test_set else ("train", "val", "trainval"): self._create_image_set_file(src, image_set, idcs[image_set]) shutil.copytree(src, root / "Segmentation") num_images = max(itertools.chain(*idcs.values())) + 1 num_images_per_image_set = dict([(image_set, len(idcs_)) for image_set, idcs_ in idcs.items()]) return num_images, num_images_per_image_set def _create_image_set_file(self, root, image_set, idcs): with open(pathlib.Path(root) / f"{image_set}.txt", "w") as fh: fh.writelines([f"{idx:06d}\n" for idx in idcs]) def _create_annotation_files(self, root, name, num_images): root = pathlib.Path(root) / name os.makedirs(root) for idx in range(num_images): annotation = self._create_annotation_file(root, f"{idx:06d}.xml") return annotation def _create_annotation_file(self, root, name): def add_child(parent, name, text=None): child = ET.SubElement(parent, name) child.text = text return child def add_name(obj, name="dog"): add_child(obj, "name", name) return name def add_bndbox(obj, bndbox=None): if bndbox is None: bndbox = {"xmin": "1", "xmax": "2", "ymin": "3", "ymax": "4"} obj = add_child(obj, "bndbox") for name, text in bndbox.items(): add_child(obj, name, text) return bndbox annotation = ET.Element("annotation") obj = add_child(annotation, "object") data = dict(name=add_name(obj), bndbox=add_bndbox(obj)) with open(pathlib.Path(root) / name, "wb") as fh: fh.write(ET.tostring(annotation)) return data class VOCDetectionTestCase(VOCSegmentationTestCase): DATASET_CLASS = datasets.VOCDetection FEATURE_TYPES = (PIL.Image.Image, dict) def test_annotations(self): with self.create_dataset() as (dataset, info): _, target = dataset[0] self.assertIn("annotation", target) annotation = target["annotation"] self.assertIn("object", annotation) objects = annotation["object"] self.assertEqual(len(objects), 1) object = objects[0] self.assertEqual(object, info["annotation"]) class CocoDetectionTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.CocoDetection FEATURE_TYPES = (PIL.Image.Image, list) REQUIRED_PACKAGES = ("pycocotools",) _IMAGE_FOLDER = "images" _ANNOTATIONS_FOLDER = "annotations" _ANNOTATIONS_FILE = "annotations.json" def dataset_args(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) root = tmpdir / self._IMAGE_FOLDER annotation_file = tmpdir / self._ANNOTATIONS_FOLDER / self._ANNOTATIONS_FILE return root, annotation_file def inject_fake_data(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) num_images = 3 num_annotations_per_image = 2 files = datasets_utils.create_image_folder( tmpdir, name=self._IMAGE_FOLDER, file_name_fn=lambda idx: f"{idx:012d}.jpg", num_examples=num_images ) file_names = [file.relative_to(tmpdir / self._IMAGE_FOLDER) for file in files] annotation_folder = tmpdir / self._ANNOTATIONS_FOLDER os.makedirs(annotation_folder) info = self._create_annotation_file( annotation_folder, self._ANNOTATIONS_FILE, file_names, num_annotations_per_image ) info["num_examples"] = num_images return info def _create_annotation_file(self, root, name, file_names, num_annotations_per_image): image_ids = [int(file_name.stem) for file_name in file_names] images = [dict(file_name=str(file_name), id=id) for file_name, id in zip(file_names, image_ids)] annotations, info = self._create_annotations(image_ids, num_annotations_per_image) self._create_json(root, name, dict(images=images, annotations=annotations)) return info def _create_annotations(self, image_ids, num_annotations_per_image): annotations = datasets_utils.combinations_grid( image_id=image_ids, bbox=([1.0, 2.0, 3.0, 4.0],) * num_annotations_per_image ) for id, annotation in enumerate(annotations): annotation["id"] = id return annotations, dict() def _create_json(self, root, name, content): file = pathlib.Path(root) / name with open(file, "w") as fh: json.dump(content, fh) return file class CocoCaptionsTestCase(CocoDetectionTestCase): DATASET_CLASS = datasets.CocoCaptions def _create_annotations(self, image_ids, num_annotations_per_image): captions = [str(idx) for idx in range(num_annotations_per_image)] annotations = datasets_utils.combinations_grid(image_id=image_ids, caption=captions) for id, annotation in enumerate(annotations): annotation["id"] = id return annotations, dict(captions=captions) def test_captions(self): with self.create_dataset() as (dataset, info): _, captions = dataset[0] self.assertEqual(tuple(captions), tuple(info["captions"])) class UCF101TestCase(datasets_utils.VideoDatasetTestCase): DATASET_CLASS = datasets.UCF101 ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(fold=(1, 2, 3), train=(True, False)) _VIDEO_FOLDER = "videos" _ANNOTATIONS_FOLDER = "annotations" def dataset_args(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) root = tmpdir / self._VIDEO_FOLDER annotation_path = tmpdir / self._ANNOTATIONS_FOLDER return root, annotation_path def inject_fake_data(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) video_folder = tmpdir / self._VIDEO_FOLDER os.makedirs(video_folder) video_files = self._create_videos(video_folder) annotations_folder = tmpdir / self._ANNOTATIONS_FOLDER os.makedirs(annotations_folder) num_examples = self._create_annotation_files(annotations_folder, video_files, config["fold"], config["train"]) return num_examples def _create_videos(self, root, num_examples_per_class=3): def file_name_fn(cls, idx, clips_per_group=2): return f"v_{cls}_g{(idx // clips_per_group) + 1:02d}_c{(idx % clips_per_group) + 1:02d}.avi" video_files = [ datasets_utils.create_video_folder(root, cls, lambda idx: file_name_fn(cls, idx), num_examples_per_class) for cls in ("ApplyEyeMakeup", "YoYo") ] return [path.relative_to(root) for path in itertools.chain(*video_files)] def _create_annotation_files(self, root, video_files, fold, train): current_videos = random.sample(video_files, random.randrange(1, len(video_files) - 1)) current_annotation = self._annotation_file_name(fold, train) self._create_annotation_file(root, current_annotation, current_videos) other_videos = set(video_files) - set(current_videos) other_annotations = [ self._annotation_file_name(fold, train) for fold, train in itertools.product((1, 2, 3), (True, False)) ] other_annotations.remove(current_annotation) for name in other_annotations: self._create_annotation_file(root, name, other_videos) return len(current_videos) def _annotation_file_name(self, fold, train): return f"{'train' if train else 'test'}list{fold:02d}.txt" def _create_annotation_file(self, root, name, video_files): with open(pathlib.Path(root) / name, "w") as fh: fh.writelines(f"{file}\n" for file in sorted(video_files)) class LSUNTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.LSUN REQUIRED_PACKAGES = ("lmdb",) ADDITIONAL_CONFIGS = datasets_utils.combinations_grid( classes=("train", "test", "val", ["bedroom_train", "church_outdoor_train"]) ) _CATEGORIES = ( "bedroom", "bridge", "church_outdoor", "classroom", "conference_room", "dining_room", "kitchen", "living_room", "restaurant", "tower", ) def inject_fake_data(self, tmpdir, config): root = pathlib.Path(tmpdir) num_images = 0 for cls in self._parse_classes(config["classes"]): num_images += self._create_lmdb(root, cls) return num_images @contextlib.contextmanager def create_dataset( self, *args, **kwargs ): with super().create_dataset(*args, **kwargs) as output: yield output for file in os.listdir(os.getcwd()): if file.startswith("_cache_"): os.remove(file) def _parse_classes(self, classes): if not isinstance(classes, str): return classes split = classes if split == "test": return [split] return [f"{category}_{split}" for category in self._CATEGORIES] def _create_lmdb(self, root, cls): lmdb = datasets_utils.lazy_importer.lmdb hexdigits_lowercase = string.digits + string.ascii_lowercase[:6] folder = f"{cls}_lmdb" num_images = torch.randint(1, 4, size=()).item() format = "png" files = datasets_utils.create_image_folder(root, folder, lambda idx: f"{idx}.{format}", num_images) with lmdb.open(str(root / folder)) as env, env.begin(write=True) as txn: for file in files: key = "".join(random.choice(hexdigits_lowercase) for _ in range(40)).encode() buffer = io.BytesIO() Image.open(file).save(buffer, format) buffer.seek(0) value = buffer.read() txn.put(key, value) os.remove(file) return num_images def test_not_found_or_corrupted(self): with self.assertRaises(datasets_utils.lazy_importer.lmdb.Error): super().test_not_found_or_corrupted() class Kinetics400TestCase(datasets_utils.VideoDatasetTestCase): DATASET_CLASS = datasets.Kinetics400 def inject_fake_data(self, tmpdir, config): classes = ("Abseiling", "Zumba") num_videos_per_class = 2 digits = string.ascii_letters + string.digits + "-_" for cls in classes: datasets_utils.create_video_folder( tmpdir, cls, lambda _: f"{datasets_utils.create_random_string(11, digits)}.avi", num_videos_per_class, ) return num_videos_per_class * len(classes) class HMDB51TestCase(datasets_utils.VideoDatasetTestCase): DATASET_CLASS = datasets.HMDB51 ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(fold=(1, 2, 3), train=(True, False)) _VIDEO_FOLDER = "videos" _SPLITS_FOLDER = "splits" _CLASSES = ("brush_hair", "wave") def dataset_args(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) root = tmpdir / self._VIDEO_FOLDER annotation_path = tmpdir / self._SPLITS_FOLDER return root, annotation_path def inject_fake_data(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) video_folder = tmpdir / self._VIDEO_FOLDER os.makedirs(video_folder) video_files = self._create_videos(video_folder) splits_folder = tmpdir / self._SPLITS_FOLDER os.makedirs(splits_folder) num_examples = self._create_split_files(splits_folder, video_files, config["fold"], config["train"]) return num_examples def _create_videos(self, root, num_examples_per_class=3): def file_name_fn(cls, idx, clips_per_group=2): return f"{cls}_{(idx // clips_per_group) + 1:d}_{(idx % clips_per_group) + 1:d}.avi" return [ ( cls, datasets_utils.create_video_folder( root, cls, lambda idx: file_name_fn(cls, idx), num_examples_per_class, ), ) for cls in self._CLASSES ] def _create_split_files(self, root, video_files, fold, train): num_videos = num_train_videos = 0 for cls, videos in video_files: num_videos += len(videos) train_videos = set(random.sample(videos, random.randrange(1, len(videos) - 1))) num_train_videos += len(train_videos) with open(pathlib.Path(root) / f"{cls}_test_split{fold}.txt", "w") as fh: fh.writelines(f"{file.name} {1 if file in train_videos else 2}\n" for file in videos) return num_train_videos if train else (num_videos - num_train_videos) class OmniglotTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.Omniglot ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(background=(True, False)) def inject_fake_data(self, tmpdir, config): target_folder = ( pathlib.Path(tmpdir) / "omniglot-py" / f"images_{'background' if config['background'] else 'evaluation'}" ) os.makedirs(target_folder) num_images = 0 for name in ("Alphabet_of_the_Magi", "Tifinagh"): num_images += self._create_alphabet_folder(target_folder, name) return num_images def _create_alphabet_folder(self, root, name): num_images_total = 0 for idx in range(torch.randint(1, 4, size=()).item()): num_images = torch.randint(1, 4, size=()).item() num_images_total += num_images datasets_utils.create_image_folder( root / name, f"character{idx:02d}", lambda image_idx: f"{image_idx:02d}.png", num_images ) return num_images_total class SBUTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.SBU FEATURE_TYPES = (PIL.Image.Image, str) def inject_fake_data(self, tmpdir, config): num_images = 3 dataset_folder = pathlib.Path(tmpdir) / "dataset" images = datasets_utils.create_image_folder(tmpdir, "dataset", self._create_file_name, num_images) self._create_urls_txt(dataset_folder, images) self._create_captions_txt(dataset_folder, num_images) return num_images def _create_file_name(self, idx): part1 = datasets_utils.create_random_string(10, string.digits) part2 = datasets_utils.create_random_string(10, string.ascii_lowercase, string.digits[:6]) return f"{part1}_{part2}.jpg" def _create_urls_txt(self, root, images): with open(root / "SBU_captioned_photo_dataset_urls.txt", "w") as fh: for image in images: fh.write( f"http://static.flickr.com/{datasets_utils.create_random_string(4, string.digits)}/{image.name}\n" ) def _create_captions_txt(self, root, num_images): with open(root / "SBU_captioned_photo_dataset_captions.txt", "w") as fh: for _ in range(num_images): fh.write(f"{datasets_utils.create_random_string(10)}\n") class SEMEIONTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.SEMEION def inject_fake_data(self, tmpdir, config): num_images = 3 images = torch.rand(num_images, 256) labels = F.one_hot(torch.randint(10, size=(num_images,))) with open(pathlib.Path(tmpdir) / "semeion.data", "w") as fh: for image, one_hot_labels in zip(images, labels): image_columns = " ".join([f"{pixel.item():.4f}" for pixel in image]) labels_columns = " ".join([str(label.item()) for label in one_hot_labels]) fh.write(f"{image_columns} {labels_columns}\n") return num_images class USPSTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.USPS ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(train=(True, False)) def inject_fake_data(self, tmpdir, config): num_images = 2 if config["train"] else 1 images = torch.rand(num_images, 256) * 2 - 1 labels = torch.randint(1, 11, size=(num_images,)) with bz2.open(pathlib.Path(tmpdir) / f"usps{'.t' if not config['train'] else ''}.bz2", "w") as fh: for image, label in zip(images, labels): line = " ".join((str(label.item()), *[f"{idx}:{pixel:.6f}" for idx, pixel in enumerate(image, 1)])) fh.write(f"{line}\n".encode()) return num_images class SBDatasetTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.SBDataset FEATURE_TYPES = (PIL.Image.Image, (np.ndarray, PIL.Image.Image)) REQUIRED_PACKAGES = ("scipy.io", "scipy.sparse") ADDITIONAL_CONFIGS = datasets_utils.combinations_grid( image_set=("train", "val", "train_noval"), mode=("boundaries", "segmentation") ) _NUM_CLASSES = 20 def inject_fake_data(self, tmpdir, config): num_images, num_images_per_image_set = self._create_split_files(tmpdir) sizes = self._create_target_folder(tmpdir, "cls", num_images) datasets_utils.create_image_folder( tmpdir, "img", lambda idx: f"{self._file_stem(idx)}.jpg", num_images, size=lambda idx: sizes[idx] ) return num_images_per_image_set[config["image_set"]] def _create_split_files(self, root): root = pathlib.Path(root) splits = dict(train=(0, 1, 2), train_noval=(0, 2), val=(3,)) for split, idcs in splits.items(): self._create_split_file(root, split, idcs) num_images = max(itertools.chain(*splits.values())) + 1 num_images_per_split = dict([(split, len(idcs)) for split, idcs in splits.items()]) return num_images, num_images_per_split def _create_split_file(self, root, name, idcs): with open(root / f"{name}.txt", "w") as fh: fh.writelines(f"{self._file_stem(idx)}\n" for idx in idcs) def _create_target_folder(self, root, name, num_images): io = datasets_utils.lazy_importer.scipy.io target_folder = pathlib.Path(root) / name os.makedirs(target_folder) sizes = [torch.randint(1, 4, size=(2,)).tolist() for _ in range(num_images)] for idx, size in enumerate(sizes): content = dict( GTcls=dict(Boundaries=self._create_boundaries(size), Segmentation=self._create_segmentation(size)) ) io.savemat(target_folder / f"{self._file_stem(idx)}.mat", content) return sizes def _create_boundaries(self, size): sparse = datasets_utils.lazy_importer.scipy.sparse return [ [sparse.csc_matrix(torch.randint(0, 2, size=size, dtype=torch.uint8).numpy())] for _ in range(self._NUM_CLASSES) ] def _create_segmentation(self, size): return torch.randint(0, self._NUM_CLASSES + 1, size=size, dtype=torch.uint8).numpy() def _file_stem(self, idx): return f"2008_{idx:06d}" class FakeDataTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.FakeData FEATURE_TYPES = (PIL.Image.Image, int) def dataset_args(self, tmpdir, config): return () def inject_fake_data(self, tmpdir, config): return config["size"] def test_not_found_or_corrupted(self): self.skipTest("The data is generated at creation and thus cannot be non-existent or corrupted.") class PhotoTourTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.PhotoTour FEATURE_TYPES = () _TRAIN_FEATURE_TYPES = (torch.Tensor,) _TEST_FEATURE_TYPES = (torch.Tensor, torch.Tensor, torch.Tensor) datasets_utils.combinations_grid(train=(True, False)) _NAME = "liberty" def dataset_args(self, tmpdir, config): return tmpdir, self._NAME def inject_fake_data(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) num_patches = 5 image_files = self._create_images(tmpdir, self._NAME, num_patches) point_ids, info_file = self._create_info_file(tmpdir / self._NAME, num_patches) num_matches, matches_file = self._create_matches_file(tmpdir / self._NAME, num_patches, point_ids) self._create_archive(tmpdir, self._NAME, *image_files, info_file, matches_file) return num_patches if config["train"] else num_matches def _create_images(self, root, name, num_images): return datasets_utils.create_image_folder( root, name, lambda idx: f"patches{idx:04d}.bmp", num_images, size=(1, 64, 64) ) def _create_info_file(self, root, num_images): point_ids = torch.randint(num_images, size=(num_images,)).tolist() file = root / "info.txt" with open(file, "w") as fh: fh.writelines([f"{point_id} 0\n" for point_id in point_ids]) return point_ids, file def _create_matches_file(self, root, num_patches, point_ids): lines = [ f"{patch_id1} {point_ids[patch_id1]} 0 {patch_id2} {point_ids[patch_id2]} 0\n" for patch_id1, patch_id2 in itertools.combinations(range(num_patches), 2) ] file = root / "m50_100000_100000_0.txt" with open(file, "w") as fh: fh.writelines(lines) return len(lines), file def _create_archive(self, root, name, *files): archive = root / f"{name}.zip" with zipfile.ZipFile(archive, "w") as zip: for file in files: zip.write(file, arcname=file.relative_to(root)) return archive @datasets_utils.test_all_configs def test_feature_types(self, config): feature_types = self.FEATURE_TYPES self.FEATURE_TYPES = self._TRAIN_FEATURE_TYPES if config["train"] else self._TEST_FEATURE_TYPES try: super().test_feature_types.__wrapped__(self, config) finally: self.FEATURE_TYPES = feature_types class Flickr8kTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.Flickr8k FEATURE_TYPES = (PIL.Image.Image, list) _IMAGES_FOLDER = "images" _ANNOTATIONS_FILE = "captions.html" def dataset_args(self, tmpdir, config): tmpdir = pathlib.Path(tmpdir) root = tmpdir / self._IMAGES_FOLDER ann_file = tmpdir / self._ANNOTATIONS_FILE return str(root), str(ann_file) def inject_fake_data(self, tmpdir, config): num_images = 3 num_captions_per_image = 3 tmpdir = pathlib.Path(tmpdir) images = self._create_images(tmpdir, self._IMAGES_FOLDER, num_images) self._create_annotations_file(tmpdir, self._ANNOTATIONS_FILE, images, num_captions_per_image) return dict(num_examples=num_images, captions=self._create_captions(num_captions_per_image)) def _create_images(self, root, name, num_images): return datasets_utils.create_image_folder(root, name, self._image_file_name, num_images) def _image_file_name(self, idx): id = datasets_utils.create_random_string(10, string.digits) checksum = datasets_utils.create_random_string(10, string.digits, string.ascii_lowercase[:6]) size = datasets_utils.create_random_string(1, "qwcko") return f"{id}_{checksum}_{size}.jpg" def _create_annotations_file(self, root, name, images, num_captions_per_image): with open(root / name, "w") as fh: fh.write("<table>") for image in (None, *images): self._add_image(fh, image, num_captions_per_image) fh.write("</table>") def _add_image(self, fh, image, num_captions_per_image): fh.write("<tr>") self._add_image_header(fh, image) fh.write("</tr><tr><td><ul>") self._add_image_captions(fh, num_captions_per_image) fh.write("</ul></td></tr>") def _add_image_header(self, fh, image=None): if image: url = f"http://www.flickr.com/photos/user/{image.name.split('_')[0]}/" data = f'<a href="{url}">{url}</a>' else: data = "Image Not Found" fh.write(f"<td>{data}</td>") def _add_image_captions(self, fh, num_captions_per_image): for caption in self._create_captions(num_captions_per_image): fh.write(f"<li>{caption}") def _create_captions(self, num_captions_per_image): return [str(idx) for idx in range(num_captions_per_image)] def test_captions(self): with self.create_dataset() as (dataset, info): _, captions = dataset[0] self.assertSequenceEqual(captions, info["captions"]) class Flickr30kTestCase(Flickr8kTestCase): DATASET_CLASS = datasets.Flickr30k FEATURE_TYPES = (PIL.Image.Image, list) _ANNOTATIONS_FILE = "captions.token" def _image_file_name(self, idx): return f"{idx}.jpg" def _create_annotations_file(self, root, name, images, num_captions_per_image): with open(root / name, "w") as fh: for image, (idx, caption) in itertools.product( images, enumerate(self._create_captions(num_captions_per_image)) ): fh.write(f"{image.name}#{idx}\t{caption}\n") class MNISTTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.MNIST ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(train=(True, False)) _MAGIC_DTYPES = { torch.uint8: 8, torch.int8: 9, torch.int16: 11, torch.int32: 12, torch.float32: 13, torch.float64: 14, } _IMAGES_SIZE = (28, 28) _IMAGES_DTYPE = torch.uint8 _LABELS_SIZE = () _LABELS_DTYPE = torch.uint8 def inject_fake_data(self, tmpdir, config): raw_dir = pathlib.Path(tmpdir) / self.DATASET_CLASS.__name__ / "raw" os.makedirs(raw_dir, exist_ok=True) num_images = self._num_images(config) self._create_binary_file( raw_dir, self._images_file(config), (num_images, *self._IMAGES_SIZE), self._IMAGES_DTYPE ) self._create_binary_file( raw_dir, self._labels_file(config), (num_images, *self._LABELS_SIZE), self._LABELS_DTYPE ) return num_images def _num_images(self, config): return 2 if config["train"] else 1 def _images_file(self, config): return f"{self._prefix(config)}-images-idx3-ubyte" def _labels_file(self, config): return f"{self._prefix(config)}-labels-idx1-ubyte" def _prefix(self, config): return "train" if config["train"] else "t10k" def _create_binary_file(self, root, filename, size, dtype): with open(pathlib.Path(root) / filename, "wb") as fh: for meta in (self._magic(dtype, len(size)), *size): fh.write(self._encode(meta)) data = torch.randint(0, torch.iinfo(dtype).max + 1, size, dtype=dtype) fh.write(data.numpy().tobytes()) def _magic(self, dtype, dims): return self._MAGIC_DTYPES[dtype] * 256 + dims def _encode(self, v): return torch.tensor(v, dtype=torch.int32).numpy().tobytes()[::-1] class FashionMNISTTestCase(MNISTTestCase): DATASET_CLASS = datasets.FashionMNIST class KMNISTTestCase(MNISTTestCase): DATASET_CLASS = datasets.KMNIST class EMNISTTestCase(MNISTTestCase): DATASET_CLASS = datasets.EMNIST DEFAULT_CONFIG = dict(split="byclass") ADDITIONAL_CONFIGS = datasets_utils.combinations_grid( split=("byclass", "bymerge", "balanced", "letters", "digits", "mnist"), train=(True, False) ) def _prefix(self, config): return f"emnist-{config['split']}-{'train' if config['train'] else 'test'}" class QMNISTTestCase(MNISTTestCase): DATASET_CLASS = datasets.QMNIST ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(what=("train", "test", "test10k", "nist")) _LABELS_SIZE = (8,) _LABELS_DTYPE = torch.int32 def _num_images(self, config): if config["what"] == "nist": return 3 elif config["what"] == "train": return 2 elif config["what"] == "test50k": return 10001 else: return 1 def _labels_file(self, config): return f"{self._prefix(config)}-labels-idx2-int" def _prefix(self, config): if config["what"] == "nist": return "xnist" if config["what"] is None: what = "train" if config["train"] else "test" elif config["what"].startswith("test"): what = "test" else: what = config["what"] return f"qmnist-{what}" def test_num_examples_test50k(self): with self.create_dataset(what="test50k") as (dataset, info): self.assertEqual(len(dataset), info["num_examples"] - 10000) class DatasetFolderTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.DatasetFolder FEATURE_TYPES = (str, int) _IMAGE_EXTENSIONS = ("jpg", "png") _VIDEO_EXTENSIONS = ("avi", "mp4") _EXTENSIONS = (*_IMAGE_EXTENSIONS, *_VIDEO_EXTENSIONS) DEFAULT_CONFIG = dict(extensions=_EXTENSIONS) ADDITIONAL_CONFIGS = ( *datasets_utils.combinations_grid(extensions=[(ext,) for ext in _IMAGE_EXTENSIONS]), dict(extensions=_IMAGE_EXTENSIONS), *datasets_utils.combinations_grid(extensions=[(ext,) for ext in _VIDEO_EXTENSIONS]), dict(extensions=_VIDEO_EXTENSIONS), ) def dataset_args(self, tmpdir, config): return tmpdir, lambda x: x def inject_fake_data(self, tmpdir, config): extensions = config["extensions"] or self._is_valid_file_to_extensions(config["is_valid_file"]) num_examples_total = 0 classes = [] for ext, cls in zip(self._EXTENSIONS, string.ascii_letters): if ext not in extensions: continue create_example_folder = ( datasets_utils.create_image_folder if ext in self._IMAGE_EXTENSIONS else datasets_utils.create_video_folder ) num_examples = torch.randint(1, 3, size=()).item() create_example_folder(tmpdir, cls, lambda idx: self._file_name_fn(cls, ext, idx), num_examples) num_examples_total += num_examples classes.append(cls) return dict(num_examples=num_examples_total, classes=classes) def _file_name_fn(self, cls, ext, idx): return f"{cls}_{idx}.{ext}" def _is_valid_file_to_extensions(self, is_valid_file): return {ext for ext in self._EXTENSIONS if is_valid_file(f"foo.{ext}")} @datasets_utils.test_all_configs def test_is_valid_file(self, config): extensions = config.pop("extensions") with self.create_dataset( config, extensions=None, is_valid_file=lambda file: pathlib.Path(file).suffix[1:] in extensions ) as (dataset, info): self.assertEqual(len(dataset), info["num_examples"]) @datasets_utils.test_all_configs def test_classes(self, config): with self.create_dataset(config) as (dataset, info): self.assertSequenceEqual(dataset.classes, info["classes"]) class ImageFolderTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.ImageFolder def inject_fake_data(self, tmpdir, config): num_examples_total = 0 classes = ("a", "b") for cls in classes: num_examples = torch.randint(1, 3, size=()).item() num_examples_total += num_examples datasets_utils.create_image_folder(tmpdir, cls, lambda idx: f"{cls}_{idx}.png", num_examples) return dict(num_examples=num_examples_total, classes=classes) @datasets_utils.test_all_configs def test_classes(self, config): with self.create_dataset(config) as (dataset, info): self.assertSequenceEqual(dataset.classes, info["classes"]) class KittiTestCase(datasets_utils.ImageDatasetTestCase): DATASET_CLASS = datasets.Kitti FEATURE_TYPES = (PIL.Image.Image, (list, type(None))) ADDITIONAL_CONFIGS = datasets_utils.combinations_grid(train=(True, False)) def inject_fake_data(self, tmpdir, config): kitti_dir = os.path.join(tmpdir, "Kitti", "raw") os.makedirs(kitti_dir) split_to_num_examples = { True: 1, False: 2, } for is_training in (True, False): num_examples = split_to_num_examples[is_training] datasets_utils.create_image_folder( root=kitti_dir, name=os.path.join("training" if is_training else "testing", "image_2"), file_name_fn=lambda image_idx: f"{image_idx:06d}.png", num_examples=num_examples, ) if is_training: for image_idx in range(num_examples): target_file_dir = os.path.join(kitti_dir, "training", "label_2") os.makedirs(target_file_dir) target_file_name = os.path.join(target_file_dir, f"{image_idx:06d}.txt") target_contents = "Pedestrian 0.00 0 -0.20 712.40 143.00 810.73 307.92 1.89 0.48 1.20 1.84 1.47 8.41 0.01\n" with open(target_file_name, "w") as target_file: target_file.write(target_contents) return split_to_num_examples[config["train"]] if __name__ == "__main__": unittest.main()

true

1c45af2d6128c89098abeaec9ca933517547a304

2,864

py

Python

tests/functional/test_email_address.py

AutumnalDream/tartiflette-plugin-scalars

2c73b20eac93b364a97b2192956e5fd4034ec35a

[ "MIT" ]

8

2019-10-02T12:47:15.000Z

2021-12-15T14:29:37.000Z

tests/functional/test_email_address.py

AutumnalDream/tartiflette-plugin-scalars

2c73b20eac93b364a97b2192956e5fd4034ec35a

[ "MIT" ]

109

2019-09-19T13:37:43.000Z

2022-03-28T07:08:50.000Z

tests/functional/test_email_address.py

AutumnalDream/tartiflette-plugin-scalars

2c73b20eac93b364a97b2192956e5fd4034ec35a

[ "MIT" ]

4

2019-10-26T19:57:20.000Z

2021-06-24T14:32:37.000Z

import pytest from tartiflette import Resolver, create_engine @pytest.mark.asyncio async def test_email_address_ok(): @Resolver("Query.email", schema_name="test_email_address_ok") async def email_resolver(*_args, **_kwargs): return "alice.girardguittard@dm.com" sdl = """ type Query { email: EmailAddress } """ engine = await create_engine( sdl=sdl, modules=[{"name": "tartiflette_plugin_scalars", "config": {}}], schema_name="test_email_address_ok", ) assert await engine.execute("query email { email }") == { "data": {"email": "alice.girardguittard@dm.com"} } @pytest.mark.asyncio async def test_email_address_nok(): @Resolver("Query.email", schema_name="test_email_address_nok") async def email_resolver(*_args, **_kwargs): return "nope" sdl = """ type Query { email: EmailAddress } """ engine = await create_engine( sdl=sdl, modules=[{"name": "tartiflette_plugin_scalars", "config": {}}], schema_name="test_email_address_nok", ) result = await engine.execute("query email { email }") assert result["data"]["email"] is None assert len(result["errors"]) == 1 assert ( result["errors"][0]["message"] == "Value is not a valid email address: < nope >" ) @pytest.mark.asyncio async def test_email_address_mutation_ok(): @Resolver("Mutation.email", schema_name="test_email_address_mutation_ok") async def email_resolver(*_args, **_kwargs): return True sdl = """ type Query { email: EmailAddress } type Mutation { email(input: EmailAddress): Boolean } """ engine = await create_engine( sdl=sdl, modules=[{"name": "tartiflette_plugin_scalars", "config": {}}], schema_name="test_email_address_mutation_ok", ) assert await engine.execute( 'mutation email { email(input:"alice.girardguittard@dailymotion.com") }' ) == {"data": {"email": True}} @pytest.mark.asyncio async def test_email_address_mutation_nok(): @Resolver("Mutation.email", schema_name="test_email_address_mutation_nok") async def email_resolver(*_args, **_kwargs): return True sdl = """ type Query { email: EmailAddress } type Mutation { email(input: EmailAddress): Boolean } """ engine = await create_engine( sdl=sdl, modules=[{"name": "tartiflette_plugin_scalars", "config": {}}], schema_name="test_email_address_mutation_nok", ) result = await engine.execute('mutation email { email(input:"nok") }') assert result["data"] is None assert len(result["errors"]) == 1 assert ( result["errors"][0]["message"] == "Value nok is not of correct type EmailAddress" )

25.571429

80

0.623953

import pytest from tartiflette import Resolver, create_engine @pytest.mark.asyncio async def test_email_address_ok(): @Resolver("Query.email", schema_name="test_email_address_ok") async def email_resolver(*_args, **_kwargs): return "alice.girardguittard@dm.com" sdl = """ type Query { email: EmailAddress } """ engine = await create_engine( sdl=sdl, modules=[{"name": "tartiflette_plugin_scalars", "config": {}}], schema_name="test_email_address_ok", ) assert await engine.execute("query email { email }") == { "data": {"email": "alice.girardguittard@dm.com"} } @pytest.mark.asyncio async def test_email_address_nok(): @Resolver("Query.email", schema_name="test_email_address_nok") async def email_resolver(*_args, **_kwargs): return "nope" sdl = """ type Query { email: EmailAddress } """ engine = await create_engine( sdl=sdl, modules=[{"name": "tartiflette_plugin_scalars", "config": {}}], schema_name="test_email_address_nok", ) result = await engine.execute("query email { email }") assert result["data"]["email"] is None assert len(result["errors"]) == 1 assert ( result["errors"][0]["message"] == "Value is not a valid email address: < nope >" ) @pytest.mark.asyncio async def test_email_address_mutation_ok(): @Resolver("Mutation.email", schema_name="test_email_address_mutation_ok") async def email_resolver(*_args, **_kwargs): return True sdl = """ type Query { email: EmailAddress } type Mutation { email(input: EmailAddress): Boolean } """ engine = await create_engine( sdl=sdl, modules=[{"name": "tartiflette_plugin_scalars", "config": {}}], schema_name="test_email_address_mutation_ok", ) assert await engine.execute( 'mutation email { email(input:"alice.girardguittard@dailymotion.com") }' ) == {"data": {"email": True}} @pytest.mark.asyncio async def test_email_address_mutation_nok(): @Resolver("Mutation.email", schema_name="test_email_address_mutation_nok") async def email_resolver(*_args, **_kwargs): return True sdl = """ type Query { email: EmailAddress } type Mutation { email(input: EmailAddress): Boolean } """ engine = await create_engine( sdl=sdl, modules=[{"name": "tartiflette_plugin_scalars", "config": {}}], schema_name="test_email_address_mutation_nok", ) result = await engine.execute('mutation email { email(input:"nok") }') assert result["data"] is None assert len(result["errors"]) == 1 assert ( result["errors"][0]["message"] == "Value nok is not of correct type EmailAddress" )

true

1c45af5f2860e383958cbd656df2e212b922f313

3,327

py

Python

tests/parse/test_parse_reference.py

wbknez/breakdb

f783820425c8cb70d8caedc6f5839a72de7c945e

[ "Apache-2.0" ]

1

2020-02-03T18:31:20.000Z

tests/parse/test_parse_reference.py

wbknez/breakdb

f783820425c8cb70d8caedc6f5839a72de7c945e

[ "Apache-2.0" ]

null

tests/parse/test_parse_reference.py

wbknez/breakdb

f783820425c8cb70d8caedc6f5839a72de7c945e

[ "Apache-2.0" ]

null

""" Contains unit tests to ensure that all functions involved in parsing DICOM references work as intended. """ import pytest from breakdb.parse import has_reference, parse_reference from breakdb.tag import ReferenceTag, get_tag_at, MalformedSequence, \ MissingSequence, MissingTag from tests.helpers.tag import match class TestParseReference: """ Test suite for :function: 'has_reference' and :function: 'parse_reference'. """ def test_has_reference_is_false_when_reference_is_missing(self, create_dataset): ds = create_dataset(excludes=[ReferenceTag.SEQUENCE]) assert not has_reference(ds) def test_has_reference_is_false_when_no_references_exist(self, create_dataset): ds = create_dataset() del ds[ReferenceTag.SEQUENCE.value].value[0] assert not has_reference(ds) def test_has_reference_succeeds(self, create_dataset): ds = create_dataset() assert has_reference(ds) def test_parse_reference_succeeds(self, create_dataset): ds = create_dataset() seq = get_tag_at(ds, 0, ReferenceTag.SEQUENCE) obj = get_tag_at(seq, 0, ReferenceTag.OBJECT) parsed = parse_reference(ds) match(obj, parsed[ReferenceTag.SEQUENCE.value], ReferenceTag.SOP_CLASS) match(obj, parsed[ReferenceTag.SEQUENCE.value], ReferenceTag.SOP_INSTANCE) match(seq, parsed[ReferenceTag.SEQUENCE.value], ReferenceTag.SERIES) def test_parse_reference_throws_when_sequence_is_missing(self, create_dataset): ds = create_dataset() del ds[ReferenceTag.SEQUENCE.value] with pytest.raises(MissingSequence): parse_reference(ds) def test_parse_reference_throws_when_object_is_missing(self, create_dataset): ds = create_dataset() del ds[ReferenceTag.SEQUENCE.value].value[0] with pytest.raises(MalformedSequence): parse_reference(ds) def test_parse_reference_throws_when_class_is_missing(self, create_dataset): ds = create_dataset() seq = get_tag_at(ds, 0, ReferenceTag.SEQUENCE) obj = get_tag_at(seq, 0, ReferenceTag.OBJECT) del obj[ReferenceTag.SOP_CLASS.value] with pytest.raises(MissingTag): parse_reference(ds) def test_parse_reference_throws_when_instance_is_missing(self, create_dataset): ds = create_dataset() seq = get_tag_at(ds, 0, ReferenceTag.SEQUENCE) obj = get_tag_at(seq, 0, ReferenceTag.OBJECT) del obj[ReferenceTag.SOP_INSTANCE.value] with pytest.raises(MissingTag): parse_reference(ds) def test_parse_reference_throws_when_series_is_missing(self, create_dataset): ds = create_dataset() seq = get_tag_at(ds, 0, ReferenceTag.SEQUENCE) del seq[ReferenceTag.SERIES.value] with pytest.raises(MissingTag): parse_reference(ds)

32.940594

82

0.62098

import pytest from breakdb.parse import has_reference, parse_reference from breakdb.tag import ReferenceTag, get_tag_at, MalformedSequence, \ MissingSequence, MissingTag from tests.helpers.tag import match class TestParseReference: def test_has_reference_is_false_when_reference_is_missing(self, create_dataset): ds = create_dataset(excludes=[ReferenceTag.SEQUENCE]) assert not has_reference(ds) def test_has_reference_is_false_when_no_references_exist(self, create_dataset): ds = create_dataset() del ds[ReferenceTag.SEQUENCE.value].value[0] assert not has_reference(ds) def test_has_reference_succeeds(self, create_dataset): ds = create_dataset() assert has_reference(ds) def test_parse_reference_succeeds(self, create_dataset): ds = create_dataset() seq = get_tag_at(ds, 0, ReferenceTag.SEQUENCE) obj = get_tag_at(seq, 0, ReferenceTag.OBJECT) parsed = parse_reference(ds) match(obj, parsed[ReferenceTag.SEQUENCE.value], ReferenceTag.SOP_CLASS) match(obj, parsed[ReferenceTag.SEQUENCE.value], ReferenceTag.SOP_INSTANCE) match(seq, parsed[ReferenceTag.SEQUENCE.value], ReferenceTag.SERIES) def test_parse_reference_throws_when_sequence_is_missing(self, create_dataset): ds = create_dataset() del ds[ReferenceTag.SEQUENCE.value] with pytest.raises(MissingSequence): parse_reference(ds) def test_parse_reference_throws_when_object_is_missing(self, create_dataset): ds = create_dataset() del ds[ReferenceTag.SEQUENCE.value].value[0] with pytest.raises(MalformedSequence): parse_reference(ds) def test_parse_reference_throws_when_class_is_missing(self, create_dataset): ds = create_dataset() seq = get_tag_at(ds, 0, ReferenceTag.SEQUENCE) obj = get_tag_at(seq, 0, ReferenceTag.OBJECT) del obj[ReferenceTag.SOP_CLASS.value] with pytest.raises(MissingTag): parse_reference(ds) def test_parse_reference_throws_when_instance_is_missing(self, create_dataset): ds = create_dataset() seq = get_tag_at(ds, 0, ReferenceTag.SEQUENCE) obj = get_tag_at(seq, 0, ReferenceTag.OBJECT) del obj[ReferenceTag.SOP_INSTANCE.value] with pytest.raises(MissingTag): parse_reference(ds) def test_parse_reference_throws_when_series_is_missing(self, create_dataset): ds = create_dataset() seq = get_tag_at(ds, 0, ReferenceTag.SEQUENCE) del seq[ReferenceTag.SERIES.value] with pytest.raises(MissingTag): parse_reference(ds)

true

1c45b05c5d250ea77c37d28b3bab75d2b9cf9824

143,725

py

Python

corehq/apps/accounting/models.py

satyaakam/commcare-hq

233f255ff20ab3a16013e9fdfdb9c1dcf632e415

[ "BSD-3-Clause" ]

null

corehq/apps/accounting/models.py

satyaakam/commcare-hq

233f255ff20ab3a16013e9fdfdb9c1dcf632e415

[ "BSD-3-Clause" ]

null

corehq/apps/accounting/models.py

satyaakam/commcare-hq

233f255ff20ab3a16013e9fdfdb9c1dcf632e415

[ "BSD-3-Clause" ]

null

import datetime import itertools from decimal import Decimal from io import BytesIO from tempfile import NamedTemporaryFile from django.conf import settings from django.contrib.postgres.fields import ArrayField from django.core.exceptions import ValidationError from django.core.validators import MaxValueValidator, MinValueValidator from django.db import models, transaction from django.db.models import F, Q from django.db.models.manager import Manager from django.template.loader import render_to_string from django.utils.html import strip_tags from django.utils.translation import ugettext_lazy as _ import jsonfield import stripe from django_prbac.models import Role from memoized import memoized from corehq.apps.domain.shortcuts import publish_domain_saved from dimagi.ext.couchdbkit import ( BooleanProperty, DateTimeProperty, SafeSaveDocument, StringProperty, ) from dimagi.utils.web import get_site_domain from corehq.apps.accounting.emails import send_subscription_change_alert from corehq.apps.accounting.exceptions import ( AccountingError, CreditLineError, InvoiceEmailThrottledError, NewSubscriptionError, ProductPlanNotFoundError, SubscriptionAdjustmentError, SubscriptionChangeError, SubscriptionReminderError, SubscriptionRenewalError, ) from corehq.apps.accounting.invoice_pdf import InvoiceTemplate from corehq.apps.accounting.signals import subscription_upgrade_or_downgrade from corehq.apps.accounting.subscription_changes import ( DomainDowngradeActionHandler, DomainUpgradeActionHandler, ) from corehq.apps.accounting.utils import ( EXCHANGE_RATE_DECIMAL_PLACES, ensure_domain_instance, fmt_dollar_amount, get_account_name_from_default_name, get_address_from_invoice, get_change_status, get_dimagi_from_email, get_privileges, is_active_subscription, log_accounting_error, log_accounting_info, quantize_accounting_decimal, ) from corehq.apps.domain import UNKNOWN_DOMAIN from corehq.apps.domain.models import Domain from corehq.apps.hqwebapp.tasks import send_html_email_async from corehq.apps.users.models import WebUser from corehq.blobs.mixin import CODES, BlobMixin from corehq.const import USER_DATE_FORMAT from corehq.privileges import REPORT_BUILDER_ADD_ON_PRIVS from corehq.util.dates import get_first_last_days from corehq.util.mixin import ValidateModelMixin from corehq.util.quickcache import quickcache from corehq.util.soft_assert import soft_assert from corehq.util.view_utils import absolute_reverse integer_field_validators = [MaxValueValidator(2147483647), MinValueValidator(-2147483648)] MAX_INVOICE_COMMUNICATIONS = 5 SMALL_INVOICE_THRESHOLD = 100 UNLIMITED_FEATURE_USAGE = -1 MINIMUM_SUBSCRIPTION_LENGTH = 30 _soft_assert_contact_emails_missing = soft_assert( to=['{}@{}'.format(email, 'dimagi.com') for email in [ 'accounts', 'billing-dev', ]], exponential_backoff=False, ) class BillingAccountType(object): CONTRACT = "CONTRACT" USER_CREATED = "USER_CREATED" GLOBAL_SERVICES = "GLOBAL_SERVICES" INVOICE_GENERATED = "INVOICE_GENERATED" TRIAL = "TRIAL" CHOICES = ( (CONTRACT, "Created by contract"), (USER_CREATED, "Created by user"), (GLOBAL_SERVICES, "Created by Global Services"), (INVOICE_GENERATED, "Generated by an invoice"), (TRIAL, "Is trial account"), ) class InvoicingPlan(object): MONTHLY = "MONTHLY" QUARTERLY = "QUARTERLY" YEARLY = "YEARLY" CHOICES = ( (MONTHLY, "Monthly"), (QUARTERLY, "Quarterly"), (YEARLY, "Yearly") ) class FeatureType(object): USER = "User" SMS = "SMS" CHOICES = ( (USER, USER), (SMS, SMS), ) class SoftwarePlanEdition(object): COMMUNITY = "Community" STANDARD = "Standard" PRO = "Pro" ADVANCED = "Advanced" ENTERPRISE = "Enterprise" RESELLER = "Reseller" MANAGED_HOSTING = "Managed Hosting" PAUSED = "Paused" CHOICES = ( (COMMUNITY, COMMUNITY), (STANDARD, STANDARD), (PRO, PRO), (ADVANCED, ADVANCED), (ENTERPRISE, ENTERPRISE), (PAUSED, PAUSED), (RESELLER, RESELLER), (MANAGED_HOSTING, MANAGED_HOSTING), ) SELF_SERVICE_ORDER = [ PAUSED, COMMUNITY, STANDARD, PRO, ADVANCED, ] class SoftwarePlanVisibility(object): PUBLIC = "PUBLIC" INTERNAL = "INTERNAL" TRIAL = "TRIAL" CHOICES = ( (PUBLIC, "Anyone can subscribe"), (INTERNAL, "Dimagi must create subscription"), (TRIAL, "This is a Trial Plan"), ) class CreditAdjustmentReason(object): DIRECT_PAYMENT = "DIRECT_PAYMENT" SALESFORCE = "SALESFORCE" INVOICE = "INVOICE" LINE_ITEM = "LINE_ITEM" TRANSFER = "TRANSFER" MANUAL = "MANUAL" CHOICES = ( (MANUAL, "manual"), (SALESFORCE, "via Salesforce"), (INVOICE, "invoice generated"), (LINE_ITEM, "line item generated"), (TRANSFER, "transfer from another credit line"), (DIRECT_PAYMENT, "payment from client received"), ) class SubscriptionAdjustmentReason(object): CREATE = "CREATE" MODIFY = "MODIFY" CANCEL = "CANCEL" UPGRADE = "UPGRADE" DOWNGRADE = "DOWNGRADE" SWITCH = "SWITCH" REACTIVATE = "REACTIVATE" RENEW = "RENEW" CHOICES = ( (CREATE, "A new subscription created from scratch."), (MODIFY, "Some part of the subscription was modified...likely a date."), (CANCEL, "The subscription was cancelled with no followup subscription."), (UPGRADE, "The subscription was upgraded to the related subscription."), (DOWNGRADE, "The subscription was downgraded to the related subscription."), (SWITCH, "The plan was changed to the related subscription and " "was neither an upgrade or downgrade."), (REACTIVATE, "The subscription was reactivated."), (RENEW, "The subscription was renewed."), ) class SubscriptionAdjustmentMethod(object): USER = "USER" INTERNAL = "INTERNAL" TASK = "TASK" TRIAL = "TRIAL" AUTOMATIC_DOWNGRADE = 'AUTOMATIC_DOWNGRADE' DEFAULT_COMMUNITY = 'DEFAULT_COMMUNITY' INVOICING = 'INVOICING' CHOICES = ( (USER, "User"), (INTERNAL, "Ops"), (TASK, "[Deprecated] Task (Invoicing)"), (TRIAL, "30 Day Trial"), (AUTOMATIC_DOWNGRADE, "Automatic Downgrade"), (DEFAULT_COMMUNITY, 'Default to Community'), (INVOICING, 'Invoicing') ) class PaymentMethodType(object): STRIPE = "Stripe" CHOICES = ( (STRIPE, STRIPE), ) class SubscriptionType(object): IMPLEMENTATION = "IMPLEMENTATION" PRODUCT = "PRODUCT" TRIAL = "TRIAL" EXTENDED_TRIAL = "EXTENDED_TRIAL" SANDBOX = "SANDBOX" INTERNAL = "INTERNAL" NOT_SET = "NOT_SET" CHOICES = ( (IMPLEMENTATION, "Implementation"), (PRODUCT, "Product"), (TRIAL, "Trial"), (EXTENDED_TRIAL, "Extended Trial"), (SANDBOX, "Sandbox"), (INTERNAL, "Internal"), ) class ProBonoStatus(object): YES = "PRO_BONO" NO = "FULL_PRICE" DISCOUNTED = "DISCOUNTED" CHOICES = ( (NO, "Full Price"), (DISCOUNTED, "Discounted"), (YES, "Pro Bono"), ) class FundingSource(object): DIMAGI = "DIMAGI" CLIENT = "CLIENT" EXTERNAL = "EXTERNAL" CHOICES = ( (DIMAGI, "Dimagi"), (CLIENT, "Client Funding"), (EXTERNAL, "External Funding"), ) class EntryPoint(object): CONTRACTED = "CONTRACTED" SELF_STARTED = "SELF_STARTED" NOT_SET = "NOT_SET" CHOICES = ( (CONTRACTED, "Contracted"), (SELF_STARTED, "Self-started"), (NOT_SET, "Not Set"), ) class LastPayment(object): CC_ONE_TIME = "CC_ONE_TIME" CC_AUTO = "CC_AUTO" WIRE = "WIRE" ACH = "ACH" OTHER = "OTHER" BU_PAYMENT = "BU_PAYMENT" NONE = "NONE" CHOICES = ( (CC_ONE_TIME, "Credit Card - One Time"), (CC_AUTO, "Credit Card - Autopay"), (WIRE, "Wire"), (ACH, "ACH"), (OTHER, "Other"), (BU_PAYMENT, "Payment to local BU"), (NONE, "None"), ) class PreOrPostPay(object): PREPAY = "PREPAY" POSTPAY = "POSTPAY" NOT_SET = "NOT_SET" CHOICES = ( (PREPAY, "Prepay"), (POSTPAY, "Postpay"), (NOT_SET, "Not Set"), ) class Currency(models.Model): """ Keeps track of the current conversion rates so that we don't have to poll the free, but rate limited API from Open Exchange Rates. Necessary for billing things like MACH SMS. """ code = models.CharField(max_length=3, unique=True) name = models.CharField(max_length=25, db_index=True) symbol = models.CharField(max_length=10) rate_to_default = models.DecimalField( default=Decimal('1.0'), max_digits=20, decimal_places=EXCHANGE_RATE_DECIMAL_PLACES, ) date_updated = models.DateField(auto_now=True) class Meta(object): app_label = 'accounting' @classmethod def get_default(cls): default, _ = cls.objects.get_or_create(code=settings.DEFAULT_CURRENCY) return default DEFAULT_ACCOUNT_FORMAT = 'Account for Project %s' class BillingAccount(ValidateModelMixin, models.Model): """ The key model that links a Subscription to its financial source and methods of payment. """ name = models.CharField(max_length=200, db_index=True, unique=True) salesforce_account_id = models.CharField( db_index=True, max_length=80, blank=True, null=True, help_text="This is how we link to the salesforce account", ) created_by = models.CharField(max_length=80, blank=True) created_by_domain = models.CharField(max_length=256, null=True, blank=True) date_created = models.DateTimeField(auto_now_add=True) dimagi_contact = models.EmailField(blank=True) currency = models.ForeignKey(Currency, on_delete=models.PROTECT) is_auto_invoiceable = models.BooleanField(default=False) date_confirmed_extra_charges = models.DateTimeField(null=True, blank=True) account_type = models.CharField( max_length=25, default=BillingAccountType.CONTRACT, choices=BillingAccountType.CHOICES, ) is_active = models.BooleanField(default=True) is_customer_billing_account = models.BooleanField(default=False, db_index=True) enterprise_admin_emails = ArrayField(models.EmailField(), default=list, blank=True) enterprise_restricted_signup_domains = ArrayField(models.CharField(max_length=128), default=list, blank=True) invoicing_plan = models.CharField( max_length=25, default=InvoicingPlan.MONTHLY, choices=InvoicingPlan.CHOICES ) entry_point = models.CharField( max_length=25, default=EntryPoint.NOT_SET, choices=EntryPoint.CHOICES, ) auto_pay_user = models.CharField(max_length=80, null=True, blank=True) last_modified = models.DateTimeField(auto_now=True) last_payment_method = models.CharField( max_length=25, default=LastPayment.NONE, choices=LastPayment.CHOICES, ) pre_or_post_pay = models.CharField( max_length=25, default=PreOrPostPay.NOT_SET, choices=PreOrPostPay.CHOICES, ) # Settings visible to external users restrict_domain_creation = models.BooleanField(default=False) restrict_signup = models.BooleanField(default=False, db_index=True) restrict_signup_message = models.CharField(max_length=512, null=True, blank=True) class Meta(object): app_label = 'accounting' @property def auto_pay_enabled(self): return self.auto_pay_user is not None @classmethod def create_account_for_domain(cls, domain, created_by=None, account_type=None, entry_point=None, last_payment_method=None, pre_or_post_pay=None): account_type = account_type or BillingAccountType.INVOICE_GENERATED entry_point = entry_point or EntryPoint.NOT_SET last_payment_method = last_payment_method or LastPayment.NONE pre_or_post_pay = pre_or_post_pay or PreOrPostPay.POSTPAY default_name = DEFAULT_ACCOUNT_FORMAT % domain name = get_account_name_from_default_name(default_name) return BillingAccount.objects.create( name=name, created_by=created_by, created_by_domain=domain, currency=Currency.get_default(), account_type=account_type, entry_point=entry_point, last_payment_method=last_payment_method, pre_or_post_pay=pre_or_post_pay ) @classmethod def get_or_create_account_by_domain(cls, domain, created_by=None, account_type=None, entry_point=None, last_payment_method=None, pre_or_post_pay=None): """ First try to grab the account used for the last subscription. If an account is not found, create it. """ account = cls.get_account_by_domain(domain) if account: return account, False return cls.create_account_for_domain( domain, created_by=created_by, account_type=account_type, entry_point=entry_point, last_payment_method=last_payment_method, pre_or_post_pay=pre_or_post_pay, ), True @classmethod def get_account_by_domain(cls, domain): current_subscription = Subscription.get_active_subscription_by_domain(domain) if current_subscription is not None: return current_subscription.account else: return cls._get_account_by_created_by_domain(domain) @classmethod def _get_account_by_created_by_domain(cls, domain): try: return cls.objects.get(created_by_domain=domain) except cls.DoesNotExist: return None except cls.MultipleObjectsReturned: log_accounting_error( f"Multiple billing accounts showed up for the domain '{domain}'. The " "latest one was served, but you should reconcile very soon.", show_stack_trace=True, ) return cls.objects.filter(created_by_domain=domain).latest('date_created') return None @classmethod @quickcache([], timeout=60 * 60) def get_enterprise_restricted_signup_accounts(cls): return BillingAccount.objects.filter(is_customer_billing_account=True, restrict_signup=True) @property def autopay_card(self): if not self.auto_pay_enabled: return None return StripePaymentMethod.objects.get(web_user=self.auto_pay_user).get_autopay_card(self) def has_enterprise_admin(self, email): return self.is_customer_billing_account and email in self.enterprise_admin_emails def update_autopay_user(self, new_user, domain): if self.auto_pay_enabled and new_user != self.auto_pay_user: self._send_autopay_card_removed_email(new_user=new_user, domain=domain) self.auto_pay_user = new_user self.save() self._send_autopay_card_added_email(domain) def remove_autopay_user(self): self.auto_pay_user = None self.save() def _send_autopay_card_removed_email(self, new_user, domain): """Sends an email to the old autopayer for this account telling them {new_user} is now the autopayer""" from corehq.apps.domain.views.accounting import EditExistingBillingAccountView old_user = self.auto_pay_user subject = _("Your card is no longer being used to auto-pay for {billing_account}").format( billing_account=self.name) old_web_user = WebUser.get_by_username(old_user) if old_web_user: old_user_name = old_web_user.first_name else: old_user_name = old_user context = { 'new_user': new_user, 'old_user_name': old_user_name, 'billing_account_name': self.name, 'billing_info_url': absolute_reverse(EditExistingBillingAccountView.urlname, args=[domain]), 'invoicing_contact_email': settings.INVOICING_CONTACT_EMAIL, } send_html_email_async( subject, old_user, render_to_string('accounting/email/autopay_card_removed.html', context), text_content=strip_tags(render_to_string('accounting/email/autopay_card_removed.html', context)), ) def _send_autopay_card_added_email(self, domain): """Sends an email to the new autopayer for this account telling them they are now the autopayer""" from corehq.apps.domain.views.accounting import EditExistingBillingAccountView subject = _("Your card is being used to auto-pay for {billing_account}").format( billing_account=self.name) web_user = WebUser.get_by_username(self.auto_pay_user) new_user_name = web_user.first_name if web_user else self.auto_pay_user try: last_4 = self.autopay_card.last4 except StripePaymentMethod.DoesNotExist: last_4 = None context = { 'name': new_user_name, 'email': self.auto_pay_user, 'domain': domain, 'last_4': last_4, 'billing_account_name': self.name, 'billing_info_url': absolute_reverse(EditExistingBillingAccountView.urlname, args=[domain]), 'invoicing_contact_email': settings.INVOICING_CONTACT_EMAIL, } send_html_email_async( subject, self.auto_pay_user, render_to_string('accounting/email/invoice_autopay_setup.html', context), text_content=strip_tags(render_to_string('accounting/email/invoice_autopay_setup.html', context)), ) class BillingContactInfo(models.Model): account = models.OneToOneField(BillingAccount, primary_key=True, null=False, on_delete=models.CASCADE) first_name = models.CharField( max_length=50, null=True, blank=True, verbose_name=_("First Name") ) last_name = models.CharField( max_length=50, null=True, blank=True, verbose_name=_("Last Name") ) # TODO - replace with models.ArrayField once django >= 1.9 email_list = jsonfield.JSONField( default=list, verbose_name=_("Contact Emails"), help_text=_("We will email communications regarding your account " "to the emails specified here.") ) phone_number = models.CharField( max_length=20, null=True, blank=True, verbose_name=_("Phone Number") ) company_name = models.CharField( max_length=50, null=True, blank=True, verbose_name=_("Company / Organization") ) first_line = models.CharField( max_length=50, null=False, verbose_name=_("Address First Line") ) second_line = models.CharField( max_length=50, null=True, blank=True, verbose_name=_("Address Second Line") ) city = models.CharField( max_length=50, null=False, verbose_name=_("City") ) state_province_region = models.CharField( max_length=50, null=False, verbose_name=_("State / Province / Region"), ) postal_code = models.CharField( max_length=20, null=False, verbose_name=_("Postal Code") ) country = models.CharField( max_length=50, null=False, verbose_name=_("Country") ) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' def __init__(self, *args, **kwargs): super(BillingContactInfo, self).__init__(*args, **kwargs) if self.email_list == '[]': self.email_list = [] @property def full_name(self): if not self.first_name: return self.last_name elif not self.last_name: return self.first_name else: return "%s %s" % (self.first_name, self.last_name) class SoftwareProductRate(models.Model): """ Represents the monthly fixed fee for a software product. Once created, SoftwareProductRates cannot be modified. Instead, a new SoftwareProductRate must be created. """ name = models.CharField(max_length=40) monthly_fee = models.DecimalField(default=Decimal('0.00'), max_digits=10, decimal_places=2) date_created = models.DateTimeField(auto_now_add=True) is_active = models.BooleanField(default=True) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' def __str__(self): return '%s @ $%s /month' % (self.name, self.monthly_fee) def __eq__(self, other): if not isinstance(other, self.__class__) or not self.name == other.name: return False for field in ['monthly_fee', 'is_active']: if not getattr(self, field) == getattr(other, field): return False return True @classmethod def new_rate(cls, product_name, monthly_fee, save=True): rate = SoftwareProductRate(name=product_name, monthly_fee=monthly_fee) if save: rate.save() return rate class Feature(models.Model): """ This is what will link a feature type (USER, API, etc.) to a name (Users Pro, API Standard, etc.) and will be what the FeatureRate references to provide a monthly fee, limit and per-excess fee. """ name = models.CharField(max_length=40, unique=True) feature_type = models.CharField(max_length=10, db_index=True, choices=FeatureType.CHOICES) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' def __str__(self): return "Feature '%s' of type '%s'" % (self.name, self.feature_type) def get_rate(self, default_instance=True): try: return self.featurerate_set.filter(is_active=True).latest('date_created') except FeatureRate.DoesNotExist: return FeatureRate() if default_instance else None # the defaults class FeatureRate(models.Model): """ Links a feature to a monthly fee, monthly limit, and a per-excess fee for exceeding the monthly limit. Once created, Feature Rates cannot be modified. Instead, a new Feature Rate must be created. """ feature = models.ForeignKey(Feature, on_delete=models.PROTECT) monthly_fee = models.DecimalField(default=Decimal('0.00'), max_digits=10, decimal_places=2, verbose_name="Monthly Fee") monthly_limit = models.IntegerField(default=0, verbose_name="Monthly Included Limit", validators=integer_field_validators) per_excess_fee = models.DecimalField(default=Decimal('0.00'), max_digits=10, decimal_places=2, verbose_name="Fee Per Excess of Limit") date_created = models.DateTimeField(auto_now_add=True) is_active = models.BooleanField(default=True) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' def __str__(self): return '%s @ $%s /month, $%s /excess, limit: %d' % ( self.feature.name, self.monthly_fee, self.per_excess_fee, self.monthly_limit ) def __eq__(self, other): if not isinstance(other, self.__class__) or not self.feature.pk == other.feature.pk: return False for field in ['monthly_fee', 'monthly_limit', 'per_excess_fee', 'is_active']: if not getattr(self, field) == getattr(other, field): return False return True @classmethod def new_rate(cls, feature_name, feature_type, monthly_fee=None, monthly_limit=None, per_excess_fee=None, save=True): feature, _ = Feature.objects.get_or_create(name=feature_name, feature_type=feature_type) rate = FeatureRate(feature=feature) if monthly_fee is not None: rate.monthly_fee = monthly_fee if monthly_limit is not None: rate.monthly_limit = monthly_limit if per_excess_fee is not None: rate.per_excess_fee = per_excess_fee if save: rate.save() return rate class SoftwarePlan(models.Model): """ Subscriptions are created for Software Plans. Software Plans can have many Software Plan Versions, which link the Software Plan to a set of permissions roles. """ name = models.CharField(max_length=80, unique=True) description = models.TextField(blank=True, help_text="If the visibility is INTERNAL, this description field will be used.") edition = models.CharField( max_length=25, default=SoftwarePlanEdition.ENTERPRISE, choices=SoftwarePlanEdition.CHOICES, ) visibility = models.CharField( max_length=10, default=SoftwarePlanVisibility.INTERNAL, choices=SoftwarePlanVisibility.CHOICES, ) last_modified = models.DateTimeField(auto_now=True) is_customer_software_plan = models.BooleanField(default=False) max_domains = models.IntegerField(blank=True, null=True) is_annual_plan = models.BooleanField(default=False) class Meta(object): app_label = 'accounting' @quickcache(vary_on=['self.pk'], timeout=10) def get_version(self): try: return self.softwareplanversion_set.filter(is_active=True).latest('date_created') except SoftwarePlanVersion.DoesNotExist: return None def at_max_domains(self): if not self.max_domains: return False subscription_count = 0 for version in self.softwareplanversion_set.all(): subscription_count += Subscription.visible_objects.filter(plan_version=version, is_active=True).count() return subscription_count >= self.max_domains class DefaultProductPlan(models.Model): """ This links a product type to its default SoftwarePlan (i.e. the Community Plan). The latest SoftwarePlanVersion that's linked to this plan will be the one used to create a new subscription if nothing is found for that domain. """ edition = models.CharField( default=SoftwarePlanEdition.COMMUNITY, choices=SoftwarePlanEdition.CHOICES, max_length=25, ) plan = models.ForeignKey(SoftwarePlan, on_delete=models.PROTECT) is_trial = models.BooleanField(default=False) is_report_builder_enabled = models.BooleanField(default=False) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' unique_together = ('edition', 'is_trial', 'is_report_builder_enabled') @classmethod @quickcache(['edition', 'is_trial', 'is_report_builder_enabled'], skip_arg=lambda *args, **kwargs: not settings.ENTERPRISE_MODE or settings.UNIT_TESTING) def get_default_plan_version(cls, edition=None, is_trial=False, is_report_builder_enabled=False): if not edition: edition = (SoftwarePlanEdition.ENTERPRISE if settings.ENTERPRISE_MODE else SoftwarePlanEdition.COMMUNITY) try: default_product_plan = DefaultProductPlan.objects.select_related('plan').get( edition=edition, is_trial=is_trial, is_report_builder_enabled=is_report_builder_enabled ) return default_product_plan.plan.get_version() except DefaultProductPlan.DoesNotExist: raise AccountingError( "No default product plan was set up, did you forget to run migrations?" ) @classmethod def get_lowest_edition(cls, requested_privileges, return_plan=False): for edition in SoftwarePlanEdition.SELF_SERVICE_ORDER: plan_version = cls.get_default_plan_version(edition) privileges = get_privileges(plan_version) - REPORT_BUILDER_ADD_ON_PRIVS if privileges.issuperset(requested_privileges): return (plan_version if return_plan else plan_version.plan.edition) return None if return_plan else SoftwarePlanEdition.ENTERPRISE class SoftwarePlanVersion(models.Model): """ Links a plan to its rates and provides versioning information. Once a new SoftwarePlanVersion is created, it cannot be modified. Instead, a new SoftwarePlanVersion must be created. """ plan = models.ForeignKey(SoftwarePlan, on_delete=models.PROTECT) product_rate = models.ForeignKey(SoftwareProductRate, on_delete=models.CASCADE) feature_rates = models.ManyToManyField(FeatureRate, blank=True) date_created = models.DateTimeField(auto_now_add=True) is_active = models.BooleanField(default=True) role = models.ForeignKey(Role, on_delete=models.CASCADE) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' def __str__(self): return "%(plan_name)s (v%(version_num)d)" % { 'plan_name': self.plan.name, 'version_num': self.version, } def save(self, *args, **kwargs): super(SoftwarePlanVersion, self).save(*args, **kwargs) SoftwarePlan.get_version.clear(self.plan) @property def version(self): return (self.plan.softwareplanversion_set.count() - self.plan.softwareplanversion_set.filter( date_created__gt=self.date_created).count()) @property def user_facing_description(self): from corehq.apps.accounting.user_text import DESC_BY_EDITION, FEATURE_TYPE_TO_NAME def _default_description(plan, monthly_limit): if plan.edition in [ SoftwarePlanEdition.COMMUNITY, SoftwarePlanEdition.STANDARD, SoftwarePlanEdition.PRO, SoftwarePlanEdition.ADVANCED, ]: return DESC_BY_EDITION[plan.edition]['description'].format(monthly_limit) else: return DESC_BY_EDITION[plan.edition]['description'] desc = { 'name': self.plan.name, } if ( self.plan.visibility == SoftwarePlanVisibility.PUBLIC or self.plan.visibility == SoftwarePlanVisibility.TRIAL ) or not self.plan.description: desc['description'] = _default_description(self.plan, self.user_feature.monthly_limit) else: desc['description'] = self.plan.description desc.update({ 'monthly_fee': 'USD %s' % self.product_rate.monthly_fee, 'rates': [{'name': FEATURE_TYPE_TO_NAME[r.feature.feature_type], 'included': 'Infinite' if r.monthly_limit == UNLIMITED_FEATURE_USAGE else r.monthly_limit} for r in self.feature_rates.all()], 'edition': self.plan.edition, }) return desc @property @memoized def user_feature(self): user_features = self.feature_rates.filter(feature__feature_type=FeatureType.USER) try: user_feature = user_features.order_by('monthly_limit')[0] if not user_feature.monthly_limit == UNLIMITED_FEATURE_USAGE: user_feature = user_features.order_by('-monthly_limit')[0] return user_feature except IndexError: pass @property def user_limit(self): if self.user_feature is not None: return self.user_feature.monthly_limit return UNLIMITED_FEATURE_USAGE @property def user_fee(self): if self.user_feature is not None: return "USD %d" % self.user_feature.per_excess_fee def feature_charges_exist_for_domain(self, domain, start_date=None, end_date=None): domain_obj = ensure_domain_instance(domain) if domain_obj is None: return False from corehq.apps.accounting.usage import FeatureUsageCalculator for feature_rate in self.feature_rates.all(): if feature_rate.monthly_limit != UNLIMITED_FEATURE_USAGE: calc = FeatureUsageCalculator( feature_rate, domain_obj.name, start_date=start_date, end_date=end_date ) if calc.get_usage() > feature_rate.monthly_limit: return True return False @property def is_paused(self): return self.plan.edition == SoftwarePlanEdition.PAUSED class SubscriberManager(models.Manager): def safe_get(self, *args, **kwargs): try: return self.get(*args, **kwargs) except Subscriber.DoesNotExist: return None class Subscriber(models.Model): """ The objects that can be subscribed to a Subscription. """ domain = models.CharField(max_length=256, unique=True, db_index=True) last_modified = models.DateTimeField(auto_now=True) objects = SubscriberManager() class Meta(object): app_label = 'accounting' def __str__(self): return "DOMAIN %s" % self.domain def create_subscription(self, new_plan_version, new_subscription, is_internal_change): assert new_plan_version assert new_subscription return self._apply_upgrades_and_downgrades( new_plan_version=new_plan_version, new_subscription=new_subscription, internal_change=is_internal_change, ) def change_subscription(self, downgraded_privileges, upgraded_privileges, new_plan_version, old_subscription, new_subscription, internal_change): return self._apply_upgrades_and_downgrades( downgraded_privileges=downgraded_privileges, upgraded_privileges=upgraded_privileges, new_plan_version=new_plan_version, old_subscription=old_subscription, new_subscription=new_subscription, internal_change=internal_change, ) def activate_subscription(self, upgraded_privileges, subscription): return self._apply_upgrades_and_downgrades( upgraded_privileges=upgraded_privileges, new_subscription=subscription, ) def deactivate_subscription(self, downgraded_privileges, upgraded_privileges, old_subscription, new_subscription): return self._apply_upgrades_and_downgrades( downgraded_privileges=downgraded_privileges, upgraded_privileges=upgraded_privileges, old_subscription=old_subscription, new_subscription=new_subscription, ) def reactivate_subscription(self, new_plan_version, subscription): return self._apply_upgrades_and_downgrades( new_plan_version=new_plan_version, old_subscription=subscription, new_subscription=subscription, ) def _apply_upgrades_and_downgrades(self, new_plan_version=None, downgraded_privileges=None, upgraded_privileges=None, old_subscription=None, new_subscription=None, internal_change=False): """ downgraded_privileges is the list of privileges that should be removed upgraded_privileges is the list of privileges that should be added """ if new_plan_version is None: new_plan_version = DefaultProductPlan.get_default_plan_version() if downgraded_privileges is None or upgraded_privileges is None: change_status_result = get_change_status(None, new_plan_version) downgraded_privileges = downgraded_privileges or change_status_result.downgraded_privs upgraded_privileges = upgraded_privileges or change_status_result.upgraded_privs if downgraded_privileges: Subscriber._process_downgrade(self.domain, downgraded_privileges, new_plan_version) if upgraded_privileges: Subscriber._process_upgrade(self.domain, upgraded_privileges, new_plan_version) if Subscriber.should_send_subscription_notification(old_subscription, new_subscription): send_subscription_change_alert(self.domain, new_subscription, old_subscription, internal_change) subscription_upgrade_or_downgrade.send_robust(None, domain=self.domain) @staticmethod def should_send_subscription_notification(old_subscription, new_subscription): if not old_subscription: return False is_new_trial = new_subscription and new_subscription.is_trial expired_trial = old_subscription.is_trial and not new_subscription return not is_new_trial and not expired_trial @staticmethod def _process_downgrade(domain, downgraded_privileges, new_plan_version): downgrade_handler = DomainDowngradeActionHandler( domain, new_plan_version, downgraded_privileges, ) if not downgrade_handler.get_response(): raise SubscriptionChangeError("The downgrade was not successful.") @staticmethod def _process_upgrade(domain, upgraded_privileges, new_plan_version): upgrade_handler = DomainUpgradeActionHandler( domain, new_plan_version, upgraded_privileges, ) if not upgrade_handler.get_response(): raise SubscriptionChangeError("The upgrade was not successful.") class VisibleSubscriptionManager(models.Manager): use_in_migrations = True def get_queryset(self): return super(VisibleSubscriptionManager, self).get_queryset().filter(is_hidden_to_ops=False) class DisabledManager(models.Manager): def get_queryset(self): raise NotImplementedError class Subscription(models.Model): """ Links a Subscriber to a SoftwarePlan and BillingAccount, necessary for invoicing. """ account = models.ForeignKey(BillingAccount, on_delete=models.PROTECT) plan_version = models.ForeignKey(SoftwarePlanVersion, on_delete=models.PROTECT) subscriber = models.ForeignKey(Subscriber, on_delete=models.PROTECT) salesforce_contract_id = models.CharField(blank=True, max_length=80) date_start = models.DateField() date_end = models.DateField(blank=True, null=True) date_created = models.DateTimeField(auto_now_add=True) is_active = models.BooleanField(default=False) do_not_invoice = models.BooleanField(default=False) no_invoice_reason = models.CharField(blank=True, max_length=256) do_not_email_invoice = models.BooleanField(default=False) do_not_email_reminder = models.BooleanField(default=False) auto_generate_credits = models.BooleanField(default=False) is_trial = models.BooleanField(default=False) skip_invoicing_if_no_feature_charges = models.BooleanField(default=False) service_type = models.CharField( max_length=25, choices=SubscriptionType.CHOICES, default=SubscriptionType.NOT_SET ) pro_bono_status = models.CharField( max_length=25, choices=ProBonoStatus.CHOICES, default=ProBonoStatus.NO, ) funding_source = models.CharField( max_length=25, choices=FundingSource.CHOICES, default=FundingSource.CLIENT ) last_modified = models.DateTimeField(auto_now=True) is_hidden_to_ops = models.BooleanField(default=False) skip_auto_downgrade = models.BooleanField(default=False) skip_auto_downgrade_reason = models.CharField(blank=True, max_length=256) visible_objects = VisibleSubscriptionManager() visible_and_suppressed_objects = models.Manager() objects = DisabledManager() class Meta(object): app_label = 'accounting' def __str__(self): return ("Subscription to %(plan_version)s for %(subscriber)s. " "[%(date_start)s - %(date_end)s]" % { 'plan_version': self.plan_version, 'subscriber': self.subscriber, 'date_start': self.date_start.strftime(USER_DATE_FORMAT), 'date_end': (self.date_end.strftime(USER_DATE_FORMAT) if self.date_end is not None else "--"), }) def __eq__(self, other): return ( other is not None and other.__class__.__name__ == self.__class__.__name__ and other.plan_version.pk == self.plan_version.pk and other.date_start == self.date_start and other.date_end == self.date_end and other.subscriber.pk == self.subscriber.pk and other.account.pk == self.account.pk ) def save(self, *args, **kwargs): """ Overloaded to update domain pillow with subscription information """ from corehq.apps.accounting.mixins import get_overdue_invoice super(Subscription, self).save(*args, **kwargs) Subscription._get_active_subscription_by_domain.clear(Subscription, self.subscriber.domain) get_overdue_invoice.clear(self.subscriber.domain) domain = Domain.get_by_name(self.subscriber.domain) # If a subscriber doesn't have a valid domain associated with it # we don't care the pillow won't be updated if domain: publish_domain_saved(domain) def delete(self, *args, **kwargs): super(Subscription, self).delete(*args, **kwargs) Subscription._get_active_subscription_by_domain.clear(Subscription, self.subscriber.domain) @property def is_community(self): return self.plan_version.plan.edition == SoftwarePlanEdition.COMMUNITY @property def allowed_attr_changes(self): """ These are the attributes of a Subscription that can always be changed while the subscription is active (or reactivated) """ return ['do_not_invoice', 'no_invoice_reason', 'salesforce_contract_id', 'skip_auto_downgrade'] @property def next_subscription_filter(self): return (Subscription.visible_objects. filter(subscriber=self.subscriber, date_start__gt=self.date_start). exclude(pk=self.pk). filter(Q(date_end__isnull=True) | ~Q(date_start=F('date_end')))) @property def previous_subscription_filter(self): return Subscription.visible_objects.filter( subscriber=self.subscriber, date_start__lt=self.date_start - datetime.timedelta(days=1) ).exclude(pk=self.pk) @property def is_renewed(self): """ Checks to see if there's another Subscription for this subscriber that starts after this subscription. """ return self.next_subscription_filter.exists() @property def next_subscription(self): try: return self.next_subscription_filter.order_by('date_start')[0] except (Subscription.DoesNotExist, IndexError): return None @property def previous_subscription(self): try: return self.previous_subscription_filter.order_by('-date_end')[0] except (Subscription.DoesNotExist, IndexError): return None def raise_conflicting_dates(self, date_start, date_end): """Raises a subscription Adjustment error if the specified date range conflicts with other subscriptions related to this subscriber. """ assert date_start is not None for sub in Subscription.visible_objects.filter( Q(date_end__isnull=True) | Q(date_end__gt=F('date_start')), subscriber=self.subscriber, ).exclude( id=self.id, ): related_has_no_end = sub.date_end is None current_has_no_end = date_end is None start_before_related_end = sub.date_end is not None and date_start < sub.date_end start_before_related_start = date_start < sub.date_start start_after_related_start = date_start > sub.date_start end_before_related_end = ( date_end is not None and sub.date_end is not None and date_end < sub.date_end ) end_after_related_end = ( date_end is not None and sub.date_end is not None and date_end > sub.date_end ) end_after_related_start = date_end is not None and date_end > sub.date_start if ( (start_before_related_end and start_after_related_start) or (start_after_related_start and related_has_no_end) or (end_after_related_start and end_before_related_end) or (end_after_related_start and related_has_no_end) or (start_before_related_start and end_after_related_end) or (start_before_related_end and current_has_no_end) or (current_has_no_end and related_has_no_end) ): raise SubscriptionAdjustmentError( "The start date of %(start_date)s conflicts with the " "subscription dates to %(related_sub)s." % { 'start_date': self.date_start.strftime(USER_DATE_FORMAT), 'related_sub': sub, } ) def update_subscription(self, date_start, date_end, do_not_invoice=None, no_invoice_reason=None, do_not_email_invoice=None, do_not_email_reminder=None, salesforce_contract_id=None, auto_generate_credits=None, web_user=None, note=None, adjustment_method=None, service_type=None, pro_bono_status=None, funding_source=None, skip_invoicing_if_no_feature_charges=None, skip_auto_downgrade=None, skip_auto_downgrade_reason=None): adjustment_method = adjustment_method or SubscriptionAdjustmentMethod.INTERNAL self._update_dates(date_start, date_end) self._update_properties( do_not_invoice=do_not_invoice, no_invoice_reason=no_invoice_reason, skip_invoicing_if_no_feature_charges=skip_invoicing_if_no_feature_charges, do_not_email_invoice=do_not_email_invoice, do_not_email_reminder=do_not_email_reminder, auto_generate_credits=auto_generate_credits, salesforce_contract_id=salesforce_contract_id, service_type=service_type, pro_bono_status=pro_bono_status, funding_source=funding_source, skip_auto_downgrade=skip_auto_downgrade, skip_auto_downgrade_reason=skip_auto_downgrade_reason, ) self.save() SubscriptionAdjustment.record_adjustment( self, method=adjustment_method, note=note, web_user=web_user, reason=SubscriptionAdjustmentReason.MODIFY ) def _update_dates(self, date_start, date_end): if not date_start: raise SubscriptionAdjustmentError('Start date must be provided') if date_end is not None and date_start > date_end: raise SubscriptionAdjustmentError( "Can't have a subscription start after the end date." ) self.raise_conflicting_dates(date_start, date_end) self.date_start = date_start self.date_end = date_end is_active_dates = is_active_subscription(self.date_start, self.date_end) if self.is_active != is_active_dates: if is_active_dates: self.is_active = True self.subscriber.activate_subscription(get_privileges(self.plan_version), self) else: raise SubscriptionAdjustmentError( 'Cannot deactivate a subscription here. Cancel subscription instead.' ) def _update_properties(self, **kwargs): property_names = { 'do_not_invoice', 'no_invoice_reason', 'skip_invoicing_if_no_feature_charges', 'do_not_email_invoice', 'do_not_email_reminder', 'auto_generate_credits', 'salesforce_contract_id', 'service_type', 'pro_bono_status', 'funding_source', 'skip_auto_downgrade', 'skip_auto_downgrade_reason', } assert property_names >= set(kwargs.keys()) for property_name, property_value in kwargs.items(): if property_value is not None: setattr(self, property_name, property_value) @transaction.atomic def change_plan(self, new_plan_version, date_end=None, note=None, web_user=None, adjustment_method=None, service_type=None, pro_bono_status=None, funding_source=None, transfer_credits=True, internal_change=False, account=None, do_not_invoice=None, no_invoice_reason=None, auto_generate_credits=False, is_trial=False): """ Changing a plan TERMINATES the current subscription and creates a NEW SUBSCRIPTION where the old plan left off. This is not the same thing as simply updating the subscription. """ from corehq.apps.analytics.tasks import track_workflow adjustment_method = adjustment_method or SubscriptionAdjustmentMethod.INTERNAL today = datetime.date.today() assert self.is_active assert date_end is None or date_end >= today if new_plan_version.plan.at_max_domains() and self.plan_version.plan != new_plan_version.plan: raise SubscriptionAdjustmentError( 'The maximum number of project spaces has been reached for %(new_plan_version)s. ' % { 'new_plan_version': new_plan_version, } ) self.date_end = today self.is_active = False self.save() new_subscription = Subscription( account=account if account else self.account, plan_version=new_plan_version, subscriber=self.subscriber, salesforce_contract_id=self.salesforce_contract_id, date_start=today, date_end=date_end, is_active=True, do_not_invoice=do_not_invoice if do_not_invoice is not None else self.do_not_invoice, no_invoice_reason=no_invoice_reason if no_invoice_reason is not None else self.no_invoice_reason, auto_generate_credits=auto_generate_credits, is_trial=is_trial, service_type=(service_type or SubscriptionType.NOT_SET), pro_bono_status=(pro_bono_status or ProBonoStatus.NO), funding_source=(funding_source or FundingSource.CLIENT), skip_auto_downgrade=False, skip_auto_downgrade_reason='', ) new_subscription.save() new_subscription.raise_conflicting_dates(new_subscription.date_start, new_subscription.date_end) new_subscription.set_billing_account_entry_point() change_status_result = get_change_status(self.plan_version, new_plan_version) self.subscriber.change_subscription( downgraded_privileges=change_status_result.downgraded_privs, upgraded_privileges=change_status_result.upgraded_privs, new_plan_version=new_plan_version, old_subscription=self, new_subscription=new_subscription, internal_change=internal_change, ) # transfer existing credit lines to the new subscription if transfer_credits: self.transfer_credits(new_subscription) # record transfer from old subscription SubscriptionAdjustment.record_adjustment( self, method=adjustment_method, note=note, web_user=web_user, reason=change_status_result.adjustment_reason, related_subscription=new_subscription ) SubscriptionAdjustment.record_adjustment( new_subscription, method=adjustment_method, note=note, web_user=web_user, reason=SubscriptionAdjustmentReason.CREATE ) upgrade_reasons = [SubscriptionAdjustmentReason.UPGRADE, SubscriptionAdjustmentReason.CREATE] if web_user and adjustment_method == SubscriptionAdjustmentMethod.USER: if change_status_result.adjustment_reason in upgrade_reasons: track_workflow(web_user, 'Changed Plan: Upgrade') if change_status_result.adjustment_reason == SubscriptionAdjustmentReason.DOWNGRADE: track_workflow(web_user, 'Changed Plan: Downgrade') return new_subscription def reactivate_subscription(self, date_end=None, note=None, web_user=None, adjustment_method=None, **kwargs): """ This assumes that a subscription was cancelled then recreated with the same date_start as the last subscription's date_end (with no other subscriptions created in between). """ adjustment_method = adjustment_method or SubscriptionAdjustmentMethod.INTERNAL self.date_end = date_end self.is_active = True for allowed_attr in self.allowed_attr_changes: if allowed_attr in kwargs: setattr(self, allowed_attr, kwargs[allowed_attr]) self.save() self.subscriber.reactivate_subscription( new_plan_version=self.plan_version, subscription=self, ) SubscriptionAdjustment.record_adjustment( self, reason=SubscriptionAdjustmentReason.REACTIVATE, method=adjustment_method, note=note, web_user=web_user, ) def renew_subscription(self, note=None, web_user=None, adjustment_method=None, service_type=None, pro_bono_status=None, funding_source=None, new_version=None): """ This creates a new subscription with a date_start that is equivalent to the current subscription's date_end. - The date_end is left None. - The plan_version is the cheapest self-subscribable plan with the same set of privileges that the current plan has. """ adjustment_method = adjustment_method or SubscriptionAdjustmentMethod.INTERNAL if self.date_end is None: raise SubscriptionRenewalError( "Cannot renew a subscription with no date_end set." ) if new_version is None: current_privileges = get_privileges(self.plan_version) new_version = DefaultProductPlan.get_lowest_edition( current_privileges, return_plan=True, ) if new_version is None: # this should NEVER happen, but on the off-chance that it does... raise SubscriptionRenewalError( "There was an issue renewing your subscription. Someone " "from Dimagi will get back to you shortly." ) renewed_subscription = Subscription( account=self.account, plan_version=new_version, subscriber=self.subscriber, salesforce_contract_id=self.salesforce_contract_id, date_start=self.date_end, date_end=None, ) if service_type is not None: renewed_subscription.service_type = service_type if pro_bono_status is not None: renewed_subscription.pro_bono_status = pro_bono_status if funding_source is not None: renewed_subscription.funding_source = funding_source if datetime.date.today() == self.date_end: renewed_subscription.is_active = True renewed_subscription.save() # record renewal from old subscription SubscriptionAdjustment.record_adjustment( self, method=adjustment_method, note=note, web_user=web_user, reason=SubscriptionAdjustmentReason.RENEW, ) return renewed_subscription def transfer_credits(self, subscription=None): """Transfers all credit balances related to an account or subscription (if specified). """ if subscription is not None and self.account.pk != subscription.account.pk: raise CreditLineError( "Can only transfer subscription credits under the same " "Billing Account." ) source_credits = CreditLine.objects.filter( account=self.account, subscription=self, ).all() for credit_line in source_credits: transferred_credit = CreditLine.add_credit( credit_line.balance, account=self.account, subscription=subscription, feature_type=credit_line.feature_type, is_product=credit_line.is_product, related_credit=credit_line ) credit_line.is_active = False credit_line.adjust_credit_balance( credit_line.balance * Decimal('-1'), related_credit=transferred_credit, ) def send_ending_reminder_email(self): """ Sends a reminder email to the emails specified in the accounting contacts that the subscription will end on the specified end date. """ if self.date_end is None: raise SubscriptionReminderError( "This subscription has no end date." ) today = datetime.date.today() num_days_left = (self.date_end - today).days domain_name = self.subscriber.domain context = self.ending_reminder_context subject = context['subject'] template = self.ending_reminder_email_html template_plaintext = self.ending_reminder_email_text email_html = render_to_string(template, context) email_plaintext = render_to_string(template_plaintext, context) bcc = [settings.ACCOUNTS_EMAIL] if not self.is_trial else [] if self.account.dimagi_contact is not None: bcc.append(self.account.dimagi_contact) for email in self._reminder_email_contacts(domain_name): send_html_email_async.delay( subject, email, email_html, text_content=email_plaintext, email_from=get_dimagi_from_email(), bcc=bcc, ) log_accounting_info( "Sent %(days_left)s-day subscription reminder " "email for %(domain)s to %(email)s." % { 'days_left': num_days_left, 'domain': domain_name, 'email': email, } ) @property def ending_reminder_email_html(self): if self.account.is_customer_billing_account: return 'accounting/email/customer_subscription_ending_reminder.html' elif self.is_trial: return 'accounting/email/trial_ending_reminder.html' else: return 'accounting/email/subscription_ending_reminder.html' @property def ending_reminder_email_text(self): if self.account.is_customer_billing_account: return 'accounting/email/customer_subscription_ending_reminder.txt' elif self.is_trial: return 'accounting/email/trial_ending_reminder.txt' else: return 'accounting/email/subscription_ending_reminder.txt' @property def ending_reminder_context(self): from corehq.apps.domain.views.accounting import DomainSubscriptionView today = datetime.date.today() num_days_left = (self.date_end - today).days if num_days_left == 1: ending_on = _("tomorrow!") else: ending_on = _("on %s." % self.date_end.strftime(USER_DATE_FORMAT)) user_desc = self.plan_version.user_facing_description plan_name = user_desc['name'] domain_name = self.subscriber.domain context = { 'domain': domain_name, 'plan_name': plan_name, 'account': self.account.name, 'ending_on': ending_on, 'subscription_url': absolute_reverse( DomainSubscriptionView.urlname, args=[self.subscriber.domain]), 'base_url': get_site_domain(), 'invoicing_contact_email': settings.INVOICING_CONTACT_EMAIL, 'sales_email': settings.SALES_EMAIL, } if self.account.is_customer_billing_account: subject = _( "CommCare Alert: %(account_name)s's subscription to " "%(plan_name)s ends %(ending_on)s" ) % { 'account_name': self.account.name, 'plan_name': plan_name, 'ending_on': ending_on, } elif self.is_trial: subject = _("CommCare Alert: 30 day trial for '%(domain)s' " "ends %(ending_on)s") % { 'domain': domain_name, 'ending_on': ending_on, } else: subject = _( "CommCare Alert: %(domain)s's subscription to " "%(plan_name)s ends %(ending_on)s" ) % { 'plan_name': plan_name, 'domain': domain_name, 'ending_on': ending_on, } context.update({'subject': subject}) return context def send_dimagi_ending_reminder_email(self): if self.date_end is None: raise SubscriptionReminderError( "This subscription has no end date." ) if self.account.dimagi_contact is None: raise SubscriptionReminderError( "This subscription has no Dimagi contact." ) subject = self.dimagi_ending_reminder_subject context = self.dimagi_ending_reminder_context email_html = render_to_string(self.dimagi_ending_reminder_email_html, context) email_plaintext = render_to_string(self.dimagi_ending_reminder_email_text, context) send_html_email_async.delay( subject, self.account.dimagi_contact, email_html, text_content=email_plaintext, email_from=settings.DEFAULT_FROM_EMAIL, ) @property def dimagi_ending_reminder_email_html(self): if self.account.is_customer_billing_account: return 'accounting/email/customer_subscription_ending_reminder_dimagi.html' else: return 'accounting/email/subscription_ending_reminder_dimagi.html' @property def dimagi_ending_reminder_email_text(self): if self.account.is_customer_billing_account: return 'accounting/email/customer_subscription_ending_reminder_dimagi.txt' else: return 'accounting/email/subscription_ending_reminder_dimagi.txt' @property def dimagi_ending_reminder_subject(self): if self.account.is_customer_billing_account: return "Alert: {account}'s subscriptions are ending on {end_date}".format( account=self.account.name, end_date=self.date_end.strftime(USER_DATE_FORMAT)) else: return "Alert: {domain}'s subscription is ending on {end_date}".format( domain=self.subscriber.domain, end_date=self.date_end.strftime(USER_DATE_FORMAT)) @property def dimagi_ending_reminder_context(self): end_date = self.date_end.strftime(USER_DATE_FORMAT) email = self.account.dimagi_contact if self.account.is_customer_billing_account: account = self.account.name plan = self.plan_version.plan.edition context = { 'account': account, 'plan': plan, 'end_date': end_date, 'client_reminder_email_date': (self.date_end - datetime.timedelta(days=30)).strftime( USER_DATE_FORMAT), 'contacts': ', '.join(self._reminder_email_contacts(self.subscriber.domain)), 'dimagi_contact': email, 'accounts_email': settings.ACCOUNTS_EMAIL } else: domain = self.subscriber.domain context = { 'domain': domain, 'end_date': end_date, 'client_reminder_email_date': (self.date_end - datetime.timedelta(days=30)).strftime( USER_DATE_FORMAT), 'contacts': ', '.join(self._reminder_email_contacts(domain)), 'dimagi_contact': email, } return context def _reminder_email_contacts(self, domain_name): emails = {a.username for a in WebUser.get_admins_by_domain(domain_name)} emails |= {e for e in WebUser.get_dimagi_emails_by_domain(domain_name)} if not self.is_trial: billing_contact_emails = ( self.account.billingcontactinfo.email_list if BillingContactInfo.objects.filter(account=self.account).exists() else [] ) if not billing_contact_emails: from corehq.apps.accounting.views import ManageBillingAccountView _soft_assert_contact_emails_missing( False, 'Billing Account for project %s is missing client contact emails: %s' % ( domain_name, absolute_reverse(ManageBillingAccountView.urlname, args=[self.account.id]) ) ) emails |= {billing_contact_email for billing_contact_email in billing_contact_emails} if self.account.is_customer_billing_account: enterprise_admin_emails = self.account.enterprise_admin_emails emails |= {enterprise_admin_email for enterprise_admin_email in enterprise_admin_emails} return emails def set_billing_account_entry_point(self): no_current_entry_point = self.account.entry_point == EntryPoint.NOT_SET self_serve = self.service_type == SubscriptionType.PRODUCT if no_current_entry_point and self_serve and not self.is_trial: self.account.entry_point = EntryPoint.SELF_STARTED self.account.save() @classmethod def get_active_subscription_by_domain(cls, domain_name_or_obj): if settings.ENTERPRISE_MODE: # Use the default plan, which is Enterprise when in ENTERPRISE_MODE return None if isinstance(domain_name_or_obj, Domain): return cls._get_active_subscription_by_domain(domain_name_or_obj.name) return cls._get_active_subscription_by_domain(domain_name_or_obj) @classmethod @quickcache(['domain_name'], timeout=60 * 60) def _get_active_subscription_by_domain(cls, domain_name): try: return cls.visible_objects.select_related( 'plan_version__role' ).get( is_active=True, subscriber__domain=domain_name, ) except cls.DoesNotExist: return None @classmethod def get_subscribed_plan_by_domain(cls, domain): """ Returns SoftwarePlanVersion for the given domain. """ domain_obj = ensure_domain_instance(domain) if domain_obj is None: try: return DefaultProductPlan.get_default_plan_version() except DefaultProductPlan.DoesNotExist: raise ProductPlanNotFoundError else: active_subscription = cls.get_active_subscription_by_domain(domain_obj.name) if active_subscription is not None: return active_subscription.plan_version else: return DefaultProductPlan.get_default_plan_version() @classmethod def new_domain_subscription(cls, account, domain, plan_version, date_start=None, date_end=None, note=None, web_user=None, adjustment_method=None, internal_change=False, **kwargs): if plan_version.plan.at_max_domains(): raise NewSubscriptionError( 'The maximum number of project spaces has been reached for %(plan_version)s. ' % { 'plan_version': plan_version, } ) if plan_version.plan.is_customer_software_plan != account.is_customer_billing_account: if plan_version.plan.is_customer_software_plan: raise NewSubscriptionError( 'You are trying to add a Customer Software Plan to a regular Billing Account. ' 'Both or neither must be customer-level.' ) else: raise NewSubscriptionError( 'You are trying to add a regular Software Plan to a Customer Billing Account. ' 'Both or neither must be customer-level.' ) subscriber = Subscriber.objects.get_or_create(domain=domain)[0] today = datetime.date.today() date_start = date_start or today # find subscriptions that end in the future / after this subscription available_subs = Subscription.visible_objects.filter( subscriber=subscriber, ) future_subscription_no_end = available_subs.filter( date_end__exact=None, ) if date_end is not None: future_subscription_no_end = future_subscription_no_end.filter(date_start__lt=date_end) if future_subscription_no_end.count() > 0: raise NewSubscriptionError(_( "There is already a subscription '%s' with no end date " "that conflicts with the start and end dates of this " "subscription.") % future_subscription_no_end.latest('date_created') ) future_subscriptions = available_subs.filter( date_end__gt=date_start ) if date_end is not None: future_subscriptions = future_subscriptions.filter(date_start__lt=date_end) if future_subscriptions.count() > 0: raise NewSubscriptionError(str( _( "There is already a subscription '%(sub)s' that has an end date " "that conflicts with the start and end dates of this " "subscription %(start)s - %(end)s." ) % { 'sub': future_subscriptions.latest('date_created'), 'start': date_start, 'end': date_end } )) can_reactivate, last_subscription = cls.can_reactivate_domain_subscription( account, domain, plan_version, date_start=date_start ) if can_reactivate: last_subscription.reactivate_subscription( date_end=date_end, note=note, web_user=web_user, adjustment_method=adjustment_method, **kwargs ) return last_subscription adjustment_method = adjustment_method or SubscriptionAdjustmentMethod.INTERNAL subscription = Subscription.visible_objects.create( account=account, plan_version=plan_version, subscriber=subscriber, date_start=date_start, date_end=date_end, **kwargs ) subscription.is_active = is_active_subscription(date_start, date_end) if subscription.is_active: subscriber.create_subscription( new_plan_version=plan_version, new_subscription=subscription, is_internal_change=internal_change, ) SubscriptionAdjustment.record_adjustment( subscription, method=adjustment_method, note=note, web_user=web_user ) subscription.save() subscription.set_billing_account_entry_point() return subscription @classmethod def can_reactivate_domain_subscription(cls, account, domain, plan_version, date_start=None): subscriber = Subscriber.objects.get_or_create(domain=domain)[0] date_start = date_start or datetime.date.today() last_subscription = Subscription.visible_objects.filter( subscriber=subscriber, date_end=date_start ) if not last_subscription.exists(): return False, None last_subscription = last_subscription.latest('date_created') return ( last_subscription.account.pk == account.pk and last_subscription.plan_version.pk == plan_version.pk ), last_subscription @property def is_below_minimum_subscription(self): if self.is_trial: return False elif self.date_start < datetime.date(2018, 9, 5): # Only block upgrades for subscriptions created after the date we launched the 30-Day Minimum return False elif self.date_start + datetime.timedelta(days=MINIMUM_SUBSCRIPTION_LENGTH) >= datetime.date.today(): return True else: return False def user_can_change_subscription(self, user): if user.is_superuser: return True elif self.account.is_customer_billing_account: return self.account.has_enterprise_admin(user.email) else: return True class InvoiceBaseManager(models.Manager): def get_queryset(self): return super(InvoiceBaseManager, self).get_queryset().filter(is_hidden_to_ops=False) class InvoiceBase(models.Model): date_created = models.DateTimeField(auto_now_add=True) is_hidden = models.BooleanField(default=False) tax_rate = models.DecimalField(default=Decimal('0.0000'), max_digits=10, decimal_places=4) balance = models.DecimalField(default=Decimal('0.0000'), max_digits=10, decimal_places=4) date_due = models.DateField(db_index=True, null=True) date_paid = models.DateField(blank=True, null=True) date_start = models.DateField() date_end = models.DateField() # If set to True invoice will not appear in invoice report. There is no UI to # control this filter is_hidden_to_ops = models.BooleanField(default=False) last_modified = models.DateTimeField(auto_now=True) objects = InvoiceBaseManager() api_objects = Manager() class Meta(object): abstract = True @property def is_customer_invoice(self): return False @property def invoice_number(self): ops_num = settings.INVOICE_STARTING_NUMBER + self.id return "%s%d" % (settings.INVOICE_PREFIX, ops_num) @property def is_wire(self): return False def get_domain(self): raise NotImplementedError() @property def account(self): raise NotImplementedError() @property def is_paid(self): return bool(self.date_paid) @property def email_recipients(self): raise NotImplementedError class WireInvoice(InvoiceBase): # WireInvoice is tied to a domain, rather than a subscription domain = models.CharField(max_length=100) class Meta(object): app_label = 'accounting' @property @memoized def account(self): return BillingAccount.get_account_by_domain(self.domain) @property def subtotal(self): return self.balance @property def is_wire(self): return True @property def is_prepayment(self): return False def get_domain(self): return self.domain def get_total(self): return self.balance @property def email_recipients(self): try: original_record = WireBillingRecord.objects.filter(invoice=self).order_by('-date_created')[0] return original_record.emailed_to_list except IndexError: log_accounting_error( "Strange that WireInvoice %d has no associated WireBillingRecord. " "Should investigate." % self.id ) return [] class WirePrepaymentInvoice(WireInvoice): class Meta(object): app_label = 'accounting' proxy = True items = [] @property def is_prepayment(self): return True class Invoice(InvoiceBase): """ This is what we'll use to calculate the balance on the accounts based on the current balance held by the Invoice. Balance updates will be tied to CreditAdjustmentTriggers which are tied to CreditAdjustments. """ subscription = models.ForeignKey(Subscription, on_delete=models.PROTECT) class Meta(object): app_label = 'accounting' def save(self, *args, **kwargs): from corehq.apps.accounting.mixins import get_overdue_invoice super(Invoice, self).save(*args, **kwargs) get_overdue_invoice.clear(self.subscription.subscriber.domain) @property def email_recipients(self): if self.subscription.service_type == SubscriptionType.IMPLEMENTATION: return [settings.ACCOUNTS_EMAIL] else: return self.contact_emails @property def contact_emails(self): try: billing_contact_info = BillingContactInfo.objects.get(account=self.account) contact_emails = billing_contact_info.email_list except BillingContactInfo.DoesNotExist: contact_emails = [] if not contact_emails: from corehq.apps.accounting.views import ManageBillingAccountView admins = WebUser.get_admins_by_domain(self.get_domain()) contact_emails = [admin.email if admin.email else admin.username for admin in admins] if not settings.UNIT_TESTING: _soft_assert_contact_emails_missing( False, "Could not find an email to send the invoice " "email to for the domain %s. Sending to domain admins instead: %s." " Add client contact emails here: %s" % ( self.get_domain(), ', '.join(contact_emails), absolute_reverse(ManageBillingAccountView.urlname, args=[self.account.id]), ) ) return contact_emails @property def subtotal(self): """ This will be inserted in the subtotal field on the printed invoice. """ if self.lineitem_set.count() == 0: return Decimal('0.0000') return sum([line_item.total for line_item in self.lineitem_set.all()]) @property def applied_tax(self): return Decimal('%.4f' % round(self.tax_rate * self.subtotal, 4)) @property @memoized def account(self): return self.subscription.account @property def applied_credit(self): if self.creditadjustment_set.count() == 0: return Decimal('0.0000') return sum([credit.amount for credit in self.creditadjustment_set.all()]) def get_total(self): """ This will be inserted in the total field on the printed invoice. """ return self.subtotal + self.applied_tax + self.applied_credit def update_balance(self): self.balance = self.get_total() if self.balance <= 0: self.date_paid = datetime.date.today() else: self.date_paid = None def calculate_credit_adjustments(self): """ This goes through all credit lines that: - do not have feature/product rates, but specify the related subscription and billing account - do not have feature/product rates or a subscription, but specify the related billing account """ # first apply credits to all the line items for line_item in self.lineitem_set.all(): line_item.calculate_credit_adjustments() # finally, apply credits to the leftover invoice balance current_total = self.get_total() credit_lines = CreditLine.get_credits_for_invoice(self) CreditLine.apply_credits_toward_balance(credit_lines, current_total, invoice=self) @classmethod def exists_for_domain(cls, domain): return cls.objects.filter( subscription__subscriber__domain=domain, is_hidden=False ).count() > 0 def get_domain(self): return self.subscription.subscriber.domain @classmethod def autopayable_invoices(cls, date_due): """ Invoices that can be auto paid on date_due """ invoices = cls.objects.select_related('subscription__account').filter( date_due=date_due, is_hidden=False, subscription__account__auto_pay_user__isnull=False, ) return invoices def pay_invoice(self, payment_record): CreditLine.make_payment_towards_invoice( invoice=self, payment_record=payment_record, ) self.update_balance() self.save() class CustomerInvoice(InvoiceBase): # CustomerInvoice is tied to a customer level account, instead of a subscription account = models.ForeignKey(BillingAccount, on_delete=models.PROTECT) subscriptions = models.ManyToManyField(Subscription, default=list, blank=True) class Meta(object): app_label = 'accounting' @property def is_customer_invoice(self): return True def get_domain(self): return None @property def email_recipients(self): try: billing_contact_info = BillingContactInfo.objects.get(account=self.account) contact_emails = billing_contact_info.email_list except BillingContactInfo.DoesNotExist: contact_emails = [] return contact_emails @property def contact_emails(self): return self.account.enterprise_admin_emails @property def subtotal(self): """ This will be inserted in the subtotal field on the printed invoice. """ if self.lineitem_set.count() == 0: return Decimal('0.0000') return sum([line_item.total for line_item in self.lineitem_set.all()]) @property def applied_tax(self): return Decimal('%.4f' % round(self.tax_rate * self.subtotal, 4)) @property def applied_credit(self): if self.creditadjustment_set.count() == 0: return Decimal('0.0000') return sum([credit.amount for credit in self.creditadjustment_set.all()]) def get_total(self): """ This will be inserted in the total field on the printed invoice. """ return self.subtotal + self.applied_tax + self.applied_credit def update_balance(self): self.balance = self.get_total() if self.balance <= 0: self.date_paid = datetime.date.today() else: self.date_paid = None def calculate_credit_adjustments(self): for line_item in self.lineitem_set.all(): line_item.calculate_credit_adjustments() current_total = self.get_total() credit_lines = CreditLine.get_credits_for_customer_invoice(self) CreditLine.apply_credits_toward_balance(credit_lines, current_total, customer_invoice=self) def pay_invoice(self, payment_record): CreditLine.make_payment_towards_invoice( invoice=self, payment_record=payment_record, ) self.update_balance() self.save() @classmethod def exists_for_domain(cls, domain): invoices = cls.objects.filter(is_hidden=False) for subscription in invoices.subscriptions.filter(is_hidden=False): if subscription.subscriber.domain == domain: return True return False @classmethod def autopayable_invoices(cls, date_due): """ Invoices that can be auto paid on date_due """ invoices = cls.objects.select_related('account').filter( date_due=date_due, is_hidden=False, account__auto_pay_user__isnull=False ) return invoices class SubscriptionAdjustment(models.Model): """ A record of any adjustments made to a subscription, so we always have a paper trail. Things that cannot be modified after a subscription is created: - account - plan - subscriber Things that have limited modification abilities: - dates if the current date is today or earlier All other modifications require cancelling the current subscription and creating a new one. Note: related_subscription is the subscription to be filled in when the subscription is upgraded / downgraded. """ subscription = models.ForeignKey(Subscription, on_delete=models.PROTECT) reason = models.CharField(max_length=50, default=SubscriptionAdjustmentReason.CREATE, choices=SubscriptionAdjustmentReason.CHOICES) method = models.CharField(max_length=50, default=SubscriptionAdjustmentMethod.INTERNAL, choices=SubscriptionAdjustmentMethod.CHOICES) note = models.TextField(null=True) web_user = models.CharField(max_length=80, null=True) invoice = models.ForeignKey(Invoice, on_delete=models.PROTECT, null=True) related_subscription = models.ForeignKey(Subscription, on_delete=models.PROTECT, null=True, related_name='subscriptionadjustment_related') date_created = models.DateTimeField(auto_now_add=True) new_date_start = models.DateField() new_date_end = models.DateField(blank=True, null=True) new_date_delay_invoicing = models.DateField(blank=True, null=True) new_salesforce_contract_id = models.CharField(blank=True, null=True, max_length=80) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' @classmethod def record_adjustment(cls, subscription, **kwargs): adjustment = SubscriptionAdjustment( subscription=subscription, new_date_start=subscription.date_start, new_date_end=subscription.date_end, new_salesforce_contract_id=subscription.salesforce_contract_id, **kwargs ) adjustment.save() return adjustment class BillingRecordBase(models.Model): """ This stores any interaction we have with the client in sending a physical / pdf invoice to their contact email. """ date_created = models.DateTimeField(auto_now_add=True, db_index=True) emailed_to_list = ArrayField(models.EmailField(), default=list) skipped_email = models.BooleanField(default=False) pdf_data_id = models.CharField(max_length=48) last_modified = models.DateTimeField(auto_now=True) INVOICE_HTML_TEMPLATE = 'accounting/email/invoice.html' INVOICE_TEXT_TEMPLATE = 'accounting/email/invoice.txt' class Meta(object): abstract = True _pdf = None @property def pdf(self): if self._pdf is None: return InvoicePdf.get(self.pdf_data_id) return self._pdf @property def html_template(self): return self.INVOICE_HTML_TEMPLATE @property def text_template(self): return self.INVOICE_TEXT_TEMPLATE @property def should_send_email(self): raise NotImplementedError("should_send_email is required") @classmethod def generate_record(cls, invoice): record = cls(invoice=invoice) invoice_pdf = InvoicePdf() invoice_pdf.generate_pdf(record.invoice) record.pdf_data_id = invoice_pdf._id record._pdf = invoice_pdf record.save() return record def handle_throttled_email(self, contact_emails): self.skipped_email = True month_name = self.invoice.date_start.strftime("%B") self.save() log_accounting_info( "Throttled billing statements for domain %(domain)s " "to %(emails)s." % { 'domain': self.invoice.get_domain(), 'emails': ', '.join(contact_emails), } ) raise InvoiceEmailThrottledError( "Invoice communications exceeded the maximum limit of " "%(max_limit)d for domain %(domain)s for the month of " "%(month_name)s." % { 'max_limit': MAX_INVOICE_COMMUNICATIONS, 'domain': self.invoice.get_domain(), 'month_name': month_name, }) def email_context(self): from corehq.apps.domain.views.accounting import DomainBillingStatementsView from corehq.apps.domain.views.settings import DefaultProjectSettingsView month_name = self.invoice.date_start.strftime("%B") domain = self.invoice.get_domain() context = { 'month_name': month_name, 'domain': domain, 'domain_url': absolute_reverse(DefaultProjectSettingsView.urlname, args=[domain]), 'statement_number': self.invoice.invoice_number, 'payment_status': (_("Paid") if self.invoice.is_paid else _("Payment Required")), 'amount_due': fmt_dollar_amount(self.invoice.balance), 'statements_url': absolute_reverse( DomainBillingStatementsView.urlname, args=[domain]), 'invoicing_contact_email': settings.INVOICING_CONTACT_EMAIL, 'accounts_email': settings.ACCOUNTS_EMAIL, } return context def email_subject(self): raise NotImplementedError() def can_view_statement(self, web_user): raise NotImplementedError() def send_email(self, contact_email=None, cc_emails=None): pdf_attachment = { 'title': self.pdf.get_filename(self.invoice), 'file_obj': BytesIO(self.pdf.get_data(self.invoice)), 'mimetype': 'application/pdf', } domain = self.invoice.get_domain() subject = self.email_subject() context = self.email_context() email_from = self.email_from() greeting = _("Hello,") can_view_statement = False web_user = WebUser.get_by_username(contact_email) if web_user is not None: if web_user.first_name: greeting = _("Dear %s,") % web_user.first_name can_view_statement = self.can_view_statement(web_user) context['greeting'] = greeting context['can_view_statement'] = can_view_statement email_html = render_to_string(self.html_template, context) email_plaintext = render_to_string(self.text_template, context) send_html_email_async.delay( subject, contact_email, email_html, text_content=email_plaintext, email_from=email_from, file_attachments=[pdf_attachment], cc=cc_emails ) self.emailed_to_list.extend([contact_email]) if cc_emails: self.emailed_to_list.extend(cc_emails) self.save() if self.invoice.is_customer_invoice: log_message = "Sent billing statements for account %(account)s to %(emails)s." % { 'account': self.invoice.account, 'emails': contact_email, } else: log_message = "Sent billing statements for domain %(domain)s to %(emails)s." % { 'domain': domain, 'emails': contact_email, } log_accounting_info(log_message) class WireBillingRecord(BillingRecordBase): invoice = models.ForeignKey(WireInvoice, on_delete=models.PROTECT) INVOICE_HTML_TEMPLATE = 'accounting/email/wire_invoice.html' INVOICE_TEXT_TEMPLATE = 'accounting/email/wire_invoice.txt' class Meta(object): app_label = 'accounting' @property def should_send_email(self): hidden = self.invoice.is_hidden return not hidden @staticmethod def is_email_throttled(): return False def email_subject(self): month_name = self.invoice.date_start.strftime("%B") return "Your %(month)s Bulk Billing Statement for Project Space %(domain)s" % { 'month': month_name, 'domain': self.invoice.get_domain(), } @staticmethod def email_from(): return "Dimagi Accounting <{email}>".format(email=settings.INVOICING_CONTACT_EMAIL) def can_view_statement(self, web_user): return web_user.is_domain_admin(self.invoice.get_domain()) class WirePrepaymentBillingRecord(WireBillingRecord): class Meta(object): app_label = 'accounting' proxy = True def email_subject(self): return _("Your prepayment invoice") def can_view_statement(self, web_user): return web_user.is_domain_admin(self.invoice.get_domain()) class BillingRecord(BillingRecordBase): invoice = models.ForeignKey(Invoice, on_delete=models.PROTECT) INVOICE_CONTRACTED_HTML_TEMPLATE = 'accounting/email/invoice_contracted.html' INVOICE_CONTRACTED_TEXT_TEMPLATE = 'accounting/email/invoice_contracted.txt' INVOICE_AUTOPAY_HTML_TEMPLATE = 'accounting/email/invoice_autopayment.html' INVOICE_AUTOPAY_TEXT_TEMPLATE = 'accounting/email/invoice_autopayment.txt' class Meta(object): app_label = 'accounting' @property def html_template(self): if self.invoice.subscription.service_type == SubscriptionType.IMPLEMENTATION: return self.INVOICE_CONTRACTED_HTML_TEMPLATE if self.invoice.subscription.account.auto_pay_enabled: return self.INVOICE_AUTOPAY_HTML_TEMPLATE return self.INVOICE_HTML_TEMPLATE @property def text_template(self): if self.invoice.subscription.service_type == SubscriptionType.IMPLEMENTATION: return self.INVOICE_CONTRACTED_TEXT_TEMPLATE if self.invoice.subscription.account.auto_pay_enabled: return self.INVOICE_AUTOPAY_TEXT_TEMPLATE return self.INVOICE_TEXT_TEMPLATE @property def should_send_email(self): subscription = self.invoice.subscription autogenerate = (subscription.auto_generate_credits and not self.invoice.balance) small_contracted = (self.invoice.balance <= SMALL_INVOICE_THRESHOLD and subscription.service_type == SubscriptionType.IMPLEMENTATION) hidden = self.invoice.is_hidden do_not_email_invoice = self.invoice.subscription.do_not_email_invoice return not (autogenerate or small_contracted or hidden or do_not_email_invoice) def is_email_throttled(self): month = self.invoice.date_start.month year = self.invoice.date_start.year date_start, date_end = get_first_last_days(year, month) return self.__class__.objects.filter( invoice__date_start__lte=date_end, invoice__date_end__gte=date_start, invoice__subscription__subscriber=self.invoice.subscription.subscriber, invoice__is_hidden_to_ops=False, ).count() > MAX_INVOICE_COMMUNICATIONS def email_context(self): context = super(BillingRecord, self).email_context() total_balance = sum(invoice.balance for invoice in Invoice.objects.filter( is_hidden=False, subscription__subscriber__domain=self.invoice.get_domain(), )) is_small_invoice = self.invoice.balance < SMALL_INVOICE_THRESHOLD payment_status = (_("Paid") if self.invoice.is_paid or total_balance == 0 else _("Payment Required")) context.update({ 'plan_name': self.invoice.subscription.plan_version.plan.name, 'date_due': self.invoice.date_due, 'is_small_invoice': is_small_invoice, 'total_balance': total_balance, 'is_total_balance_due': total_balance >= SMALL_INVOICE_THRESHOLD, 'payment_status': payment_status, }) if self.invoice.subscription.service_type == SubscriptionType.IMPLEMENTATION: from corehq.apps.accounting.dispatcher import AccountingAdminInterfaceDispatcher context.update({ 'salesforce_contract_id': self.invoice.subscription.salesforce_contract_id, 'billing_account': self.invoice.subscription.account.name, 'billing_contacts': self.invoice.contact_emails, 'admin_invoices_url': "{url}?subscriber={domain}".format( url=absolute_reverse(AccountingAdminInterfaceDispatcher.name(), args=['invoices']), domain=self.invoice.get_domain() ) }) if self.invoice.subscription.account.auto_pay_enabled: try: last_4 = getattr(self.invoice.subscription.account.autopay_card, 'last4', None) except StripePaymentMethod.DoesNotExist: last_4 = None context.update({ 'auto_pay_user': self.invoice.subscription.account.auto_pay_user, 'last_4': last_4, }) context.update({ 'credits': self.credits, }) return context def credits(self): credits = { 'account': {}, 'subscription': {}, } self._add_product_credits(credits) self._add_user_credits(credits) self._add_sms_credits(credits) self._add_general_credits(credits) return credits def _add_product_credits(self, credits): credit_adjustments = CreditAdjustment.objects.filter( invoice=self.invoice, line_item__product_rate__isnull=False, ) subscription_credits = BillingRecord._get_total_balance( CreditLine.get_credits_by_subscription_and_features( self.invoice.subscription, is_product=True, ) ) if subscription_credits or credit_adjustments.filter( credit_line__subscription=self.invoice.subscription, ): credits['subscription'].update({ 'product': { 'amount': quantize_accounting_decimal(subscription_credits), } }) account_credits = BillingRecord._get_total_balance( CreditLine.get_credits_for_account( self.invoice.subscription.account, is_product=True, ) ) if account_credits or credit_adjustments.filter( credit_line__subscription=None, ): credits['account'].update({ 'product': { 'amount': quantize_accounting_decimal(account_credits), } }) return credits def _add_user_credits(self, credits): credit_adjustments = CreditAdjustment.objects.filter( invoice=self.invoice, line_item__feature_rate__feature__feature_type=FeatureType.USER, ) subscription_credits = BillingRecord._get_total_balance( CreditLine.get_credits_by_subscription_and_features( self.invoice.subscription, feature_type=FeatureType.USER, ) ) if subscription_credits or credit_adjustments.filter( credit_line__subscription=self.invoice.subscription, ): credits['subscription'].update({ 'user': { 'amount': quantize_accounting_decimal(subscription_credits), } }) account_credits = BillingRecord._get_total_balance( CreditLine.get_credits_for_account( self.invoice.subscription.account, feature_type=FeatureType.USER, ) ) if account_credits or credit_adjustments.filter( credit_line__subscription=None, ): credits['account'].update({ 'user': { 'amount': quantize_accounting_decimal(account_credits), } }) return credits def _add_sms_credits(self, credits): credit_adjustments = CreditAdjustment.objects.filter( invoice=self.invoice, line_item__feature_rate__feature__feature_type=FeatureType.SMS, ) subscription_credits = BillingRecord._get_total_balance( CreditLine.get_credits_by_subscription_and_features( self.invoice.subscription, feature_type=FeatureType.SMS, ) ) if subscription_credits or credit_adjustments.filter( credit_line__subscription=self.invoice.subscription, ): credits['subscription'].update({ 'sms': { 'amount': quantize_accounting_decimal(subscription_credits), } }) account_credits = BillingRecord._get_total_balance( CreditLine.get_credits_for_account( self.invoice.subscription.account, feature_type=FeatureType.SMS, ) ) if account_credits or credit_adjustments.filter( credit_line__subscription=None, ): credits['account'].update({ 'sms': { 'amount': quantize_accounting_decimal(account_credits), } }) return credits def _add_general_credits(self, credits): credit_adjustments = CreditAdjustment.objects.filter( invoice=self.invoice, line_item__feature_rate=None, line_item__product_rate=None, ) subscription_credits = BillingRecord._get_total_balance( CreditLine.get_credits_by_subscription_and_features( self.invoice.subscription, ) ) if subscription_credits or credit_adjustments.filter( credit_line__subscription=self.invoice.subscription, ): credits['subscription'].update({ 'general': { 'amount': quantize_accounting_decimal(subscription_credits), } }) account_credits = BillingRecord._get_total_balance( CreditLine.get_credits_for_account( self.invoice.subscription.account, ) ) if account_credits or credit_adjustments.filter( credit_line__subscription=None, ): credits['account'].update({ 'general': { 'amount': quantize_accounting_decimal(account_credits), } }) return credits def email_subject(self): month_name = self.invoice.date_start.strftime("%B") return "Your %(month)s CommCare Billing Statement for Project Space %(domain)s" % { 'month': month_name, 'domain': self.invoice.subscription.subscriber.domain, } def email_from(self): return get_dimagi_from_email() @staticmethod def _get_total_balance(credit_lines): return ( sum([credit_line.balance for credit_line in credit_lines]) if credit_lines else Decimal('0.0') ) def can_view_statement(self, web_user): return web_user.is_domain_admin(self.invoice.get_domain()) class CustomerBillingRecord(BillingRecordBase): invoice = models.ForeignKey(CustomerInvoice, on_delete=models.PROTECT) INVOICE_AUTOPAY_HTML_TEMPLATE = 'accounting/email/invoice_autopayment.html' INVOICE_AUTOPAY_TEXT_TEMPLATE = 'accounting/email/invoice_autopayment.txt' INVOICE_HTML_TEMPLATE = 'accounting/email/customer_invoice.html' INVOICE_TEXT_TEMPLATE = 'accounting/email/customer_invoice.txt' class Meta(object): app_label = 'accounting' @property def html_template(self): if self.invoice.account.auto_pay_enabled: return self.INVOICE_AUTOPAY_HTML_TEMPLATE return self.INVOICE_HTML_TEMPLATE @property def text_template(self): if self.invoice.account.auto_pay_enabled: return self.INVOICE_AUTOPAY_TEXT_TEMPLATE return self.INVOICE_TEXT_TEMPLATE @property def should_send_email(self): return not self.invoice.is_hidden def email_context(self): from corehq.apps.accounting.views import EnterpriseBillingStatementsView context = super(CustomerBillingRecord, self).email_context() is_small_invoice = self.invoice.balance < SMALL_INVOICE_THRESHOLD payment_status = (_("Paid") if self.invoice.is_paid or self.invoice.balance == 0 else _("Payment Required")) # Random domain, because all subscriptions on a customer account link to the same Enterprise Dashboard domain = self.invoice.subscriptions.first().subscriber.domain context.update({ 'account_name': self.invoice.account.name, 'date_due': self.invoice.date_due, 'is_small_invoice': is_small_invoice, 'total_balance': '{:.2f}'.format(self.invoice.balance), 'is_total_balance_due': self.invoice.balance >= SMALL_INVOICE_THRESHOLD, 'payment_status': payment_status, 'statements_url': absolute_reverse( EnterpriseBillingStatementsView.urlname, args=[domain]), }) if self.invoice.account.auto_pay_enabled: try: last_4 = getattr(self.invoice.account.autopay_card, 'last4', None) except StripePaymentMethod.DoesNotExist: last_4 = None context.update({ 'auto_pay_user': self.invoice.account.auto_pay_user, 'last_4': last_4, }) context.update({ 'credits': self.credits, }) return context def credits(self): credits = { 'account': {}, 'subscription': {}, } self._add_product_credits(credits) self._add_user_credits(credits) self._add_sms_credits(credits) self._add_general_credits(credits) return credits def _add_product_credits(self, credits): credit_adjustments = CreditAdjustment.objects.filter( customer_invoice=self.invoice, line_item__product_rate__isnull=False ) subscription_credits = CustomerBillingRecord._get_total_balance( CreditLine.get_credits_for_subscriptions( self.invoice.subscriptions, is_product=True ) ) if subscription_credits or self._subscriptions_in_credit_adjustments(credit_adjustments): credit_adjustments['subscription'].update({ 'product': { 'amount': quantize_accounting_decimal(subscription_credits) } }) account_credits = CustomerBillingRecord._get_total_balance( CreditLine.get_credits_for_account( self.invoice.account, is_product=True ) ) if account_credits or credit_adjustments.filter(credit_line__subscription=None): credits['account'].update({ 'product': { 'amount': quantize_accounting_decimal(account_credits) } }) return credits def _add_user_credits(self, credits): credit_adjustments = CreditAdjustment.objects.filter( customer_invoice=self.invoice, line_item__feature_rate__feature__feature_type=FeatureType.USER ) subscription_credits = CustomerBillingRecord._get_total_balance( CreditLine.get_credits_for_subscriptions( self.invoice.subscriptions, feature_type=FeatureType.USER ) ) if subscription_credits or self._subscriptions_in_credit_adjustments(credit_adjustments): credits['subscription'].update({ 'user': { 'amount': quantize_accounting_decimal(subscription_credits) } }) account_credits = CustomerBillingRecord._get_total_balance( CreditLine.get_credits_for_account( self.invoice.account, feature_type=FeatureType.USER ) ) if account_credits or credit_adjustments.filter(credit_line__subscription=None): credits['account'].update({ 'user': { 'amount': quantize_accounting_decimal(account_credits) } }) return credits def _add_sms_credits(self, credits): credit_adjustments = CreditAdjustment.objects.filter( customer_invoice=self.invoice, line_item__feature_rate__feature__feature_type=FeatureType.SMS ) subscription_credits = CustomerBillingRecord._get_total_balance( CreditLine.get_credits_for_subscriptions( self.invoice.subscriptions, feature_type=FeatureType.SMS ) ) if subscription_credits or self._subscriptions_in_credit_adjustments(credit_adjustments): credits['subscription'].update({ 'sms': { 'amount': quantize_accounting_decimal(subscription_credits) } }) account_credits = CustomerBillingRecord._get_total_balance( CreditLine.get_credits_for_account( self.invoice.account, feature_type=FeatureType.SMS ) ) if account_credits or credit_adjustments.filter(credit_line__subscription=None): credits['account'].update({ 'sms': { 'amount': quantize_accounting_decimal(account_credits) } }) return credits def _add_general_credits(self, credits): credit_adjustments = CreditAdjustment.objects.filter( customer_invoice=self.invoice, line_item__feature_rate=None, line_item__product_rate=None ) subscription_credits = CustomerBillingRecord._get_total_balance( CreditLine.get_credits_for_subscriptions( self.invoice.subscriptions ) ) if subscription_credits or self._subscriptions_in_credit_adjustments(credit_adjustments): credits['subscription'].update({ 'general': { 'amount': quantize_accounting_decimal(subscription_credits) } }) account_credits = CustomerBillingRecord._get_total_balance( CreditLine.get_credits_for_account( self.invoice.account ) ) if account_credits or credit_adjustments.filter(credit_line__subscription=None): credits['account'].update({ 'general': { 'amount': quantize_accounting_decimal(account_credits) } }) return credits def _subscriptions_in_credit_adjustments(self, credit_adjustments): for subscription in self.invoice.subscriptions.all(): if credit_adjustments.filter( credit_line__subscription=subscription ): return True return False def email_subject(self): month_name = self.invoice.date_start.strftime("%B") return "Your %(month)s CommCare Billing Statement for Customer Account %(account_name)s" % { 'month': month_name, 'account_name': self.invoice.account.name, } def email_from(self): return get_dimagi_from_email() @staticmethod def _get_total_balance(credit_lines): return ( sum([credit_line.balance for credit_line in credit_lines]) if credit_lines else Decimal('0.0') ) def can_view_statement(self, web_user): for subscription in self.invoice.subscriptions.all(): if web_user.is_domain_admin(subscription.subscriber.domain): return True return False class InvoicePdf(BlobMixin, SafeSaveDocument): invoice_id = StringProperty() date_created = DateTimeProperty() is_wire = BooleanProperty(default=False) is_customer = BooleanProperty(default=False) _blobdb_type_code = CODES.invoice def generate_pdf(self, invoice): self.save() domain = invoice.get_domain() pdf_data = NamedTemporaryFile() account_name = '' if invoice.is_customer_invoice: account_name = invoice.account.name template = InvoiceTemplate( pdf_data.name, invoice_number=invoice.invoice_number, to_address=get_address_from_invoice(invoice), project_name=domain, invoice_date=invoice.date_created.date(), due_date=invoice.date_due, date_start=invoice.date_start, date_end=invoice.date_end, subtotal=invoice.subtotal, tax_rate=invoice.tax_rate, applied_tax=getattr(invoice, 'applied_tax', Decimal('0.000')), applied_credit=getattr(invoice, 'applied_credit', Decimal('0.000')), total=invoice.get_total(), is_wire=invoice.is_wire, is_customer=invoice.is_customer_invoice, is_prepayment=invoice.is_wire and invoice.is_prepayment, account_name=account_name ) if not invoice.is_wire: if invoice.is_customer_invoice: line_items = LineItem.objects.filter(customer_invoice=invoice) else: line_items = LineItem.objects.filter(subscription_invoice=invoice) for line_item in line_items: is_unit = line_item.unit_description is not None is_quarterly = line_item.invoice.is_customer_invoice and \ line_item.invoice.account.invoicing_plan != InvoicingPlan.MONTHLY unit_cost = line_item.subtotal if is_unit: unit_cost = line_item.unit_cost if is_quarterly and line_item.base_description is not None: unit_cost = line_item.product_rate.monthly_fee description = line_item.base_description or line_item.unit_description if line_item.quantity > 0: template.add_item( description, line_item.quantity if is_unit or is_quarterly else 1, unit_cost, line_item.subtotal, line_item.applied_credit, line_item.total ) if invoice.is_wire and invoice.is_prepayment: unit_cost = 1 applied_credit = 0 for item in invoice.items: template.add_item(item['type'], item['amount'], unit_cost, item['amount'], applied_credit, item['amount']) template.get_pdf() filename = self.get_filename(invoice) blob_domain = domain or UNKNOWN_DOMAIN # this is slow and not unit tested # best to just skip during unit tests for speed if not settings.UNIT_TESTING: self.put_attachment(pdf_data, filename, 'application/pdf', domain=blob_domain) else: self.put_attachment('', filename, 'application/pdf', domain=blob_domain) pdf_data.close() self.invoice_id = str(invoice.id) self.date_created = datetime.datetime.utcnow() self.is_wire = invoice.is_wire self.is_customer = invoice.is_customer_invoice self.save() @staticmethod def get_filename(invoice): return "statement_%(year)d_%(month)d.pdf" % { 'year': invoice.date_start.year, 'month': invoice.date_start.month, } def get_data(self, invoice): with self.fetch_attachment(self.get_filename(invoice), stream=True) as fh: return fh.read() class LineItemManager(models.Manager): def get_products(self): return self.get_queryset().filter(feature_rate__exact=None) def get_features(self): return self.get_queryset().filter(product_rate__exact=None) def get_feature_by_type(self, feature_type): return self.get_queryset().filter(feature_rate__feature__feature_type=feature_type) class LineItem(models.Model): subscription_invoice = models.ForeignKey(Invoice, on_delete=models.PROTECT, null=True) customer_invoice = models.ForeignKey(CustomerInvoice, on_delete=models.PROTECT, null=True) feature_rate = models.ForeignKey(FeatureRate, on_delete=models.PROTECT, null=True) product_rate = models.ForeignKey(SoftwareProductRate, on_delete=models.PROTECT, null=True) base_description = models.TextField(blank=True, null=True) base_cost = models.DecimalField(default=Decimal('0.0000'), max_digits=10, decimal_places=4) unit_description = models.TextField(blank=True, null=True) unit_cost = models.DecimalField(default=Decimal('0.0000'), max_digits=10, decimal_places=4) quantity = models.IntegerField(default=1, validators=integer_field_validators) last_modified = models.DateTimeField(auto_now=True) objects = LineItemManager() class Meta(object): app_label = 'accounting' @property def invoice(self): if self.subscription_invoice: return self.subscription_invoice else: return self.customer_invoice @invoice.setter def invoice(self, invoice): if invoice.is_customer_invoice: self.customer_invoice = invoice else: self.subscription_invoice = invoice @property def subtotal(self): if self.customer_invoice and self.customer_invoice.account.invoicing_plan != InvoicingPlan.MONTHLY: return self.base_cost * self.quantity + self.unit_cost * self.quantity return self.base_cost + self.unit_cost * self.quantity @property def applied_credit(self): """ The total amount of credit applied specifically to this LineItem. """ if self.creditadjustment_set.count() == 0: return Decimal('0.0000') return sum([credit.amount for credit in self.creditadjustment_set.all()]) @property def total(self): return self.subtotal + self.applied_credit def calculate_credit_adjustments(self): """ This goes through all credit lines that: - specify the related feature or product rate that generated this line item """ current_total = self.total credit_lines = CreditLine.get_credits_for_line_item(self) CreditLine.apply_credits_toward_balance(credit_lines, current_total, line_item=self) class CreditLine(models.Model): """ The amount of money in USD that exists can can be applied toward a specific account, a specific subscription, or specific rates in that subscription. """ account = models.ForeignKey(BillingAccount, on_delete=models.PROTECT) subscription = models.ForeignKey(Subscription, on_delete=models.PROTECT, null=True, blank=True) is_product = models.BooleanField(default=False) feature_type = models.CharField(max_length=10, null=True, blank=True, choices=FeatureType.CHOICES) date_created = models.DateTimeField(auto_now_add=True) balance = models.DecimalField(default=Decimal('0.0000'), max_digits=10, decimal_places=4) is_active = models.BooleanField(default=True) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' def __str__(self): credit_level = ("Account-Level" if self.subscription is None else "Subscription-Level") return ("%(level)s credit [Account %(account_id)d]%(feature)s" "%(product)s, balance %(balance)s" % { 'level': credit_level, 'account_id': self.account.id, 'feature': (' for Feature %s' % self.feature_type if self.feature_type is not None else ""), 'product': (' for Product' if self.is_product else ""), 'balance': self.balance, }) def save(self, *args, **kwargs): from corehq.apps.accounting.mixins import ( get_credits_available_for_product_in_account, get_credits_available_for_product_in_subscription, ) super(CreditLine, self).save(*args, **kwargs) if self.account: get_credits_available_for_product_in_account.clear(self.account) if self.subscription: get_credits_available_for_product_in_subscription.clear(self.subscription) def adjust_credit_balance(self, amount, is_new=False, note=None, line_item=None, invoice=None, customer_invoice=None, payment_record=None, related_credit=None, reason=None, web_user=None): note = note or "" if line_item is not None and (invoice is not None or customer_invoice is not None): raise CreditLineError("You may only have an invoice OR a line item making this adjustment.") if reason is None: reason = CreditAdjustmentReason.MANUAL if payment_record is not None: reason = CreditAdjustmentReason.DIRECT_PAYMENT elif related_credit is not None: reason = CreditAdjustmentReason.TRANSFER elif invoice is not None: reason = CreditAdjustmentReason.INVOICE elif customer_invoice is not None: reason = CreditAdjustmentReason.INVOICE elif line_item is not None: reason = CreditAdjustmentReason.LINE_ITEM if is_new: note = "Initialization of credit line. %s" % note credit_adjustment = CreditAdjustment( credit_line=self, note=note, amount=amount, reason=reason, payment_record=payment_record, line_item=line_item, invoice=invoice, customer_invoice=customer_invoice, related_credit=related_credit, web_user=web_user, ) credit_adjustment.save() self.balance = F('balance') + amount self.save() self.refresh_from_db() @classmethod def get_credits_for_line_item(cls, line_item): is_product = line_item.product_rate is not None feature_type = ( line_item.feature_rate.feature.feature_type if line_item.feature_rate is not None else None ) assert is_product or feature_type assert not (is_product and feature_type) if line_item.invoice.is_customer_invoice: return cls.get_credits_for_line_item_in_customer_invoice(line_item, feature_type, is_product) else: return cls.get_credits_for_line_item_in_invoice(line_item, feature_type, is_product) @classmethod def get_credits_for_line_item_in_invoice(cls, line_item, feature_type, is_product): if feature_type: return itertools.chain( cls.get_credits_by_subscription_and_features( line_item.invoice.subscription, feature_type=feature_type, ), cls.get_credits_for_account( line_item.invoice.subscription.account, feature_type=feature_type, ) ) if is_product: return itertools.chain( cls.get_credits_by_subscription_and_features( line_item.invoice.subscription, is_product=True, ), cls.get_credits_for_account( line_item.invoice.subscription.account, is_product=True, ) ) @classmethod def get_credits_for_line_item_in_customer_invoice(cls, line_item, feature_type, is_product): if feature_type: return itertools.chain( cls.get_credits_for_subscriptions( subscriptions=line_item.invoice.subscriptions.all(), feature_type=feature_type ), cls.get_credits_for_account( account=line_item.invoice.account, feature_type=feature_type ) ) if is_product: return itertools.chain( cls.get_credits_for_subscriptions( subscriptions=line_item.invoice.subscriptions.all(), is_product=is_product ), cls.get_credits_for_account( account=line_item.invoice.account, is_product=is_product ) ) @classmethod def get_credits_for_invoice(cls, invoice): relevant_credits = [ cls.get_credits_by_subscription_and_features(invoice.subscription), cls.get_credits_for_account(invoice.subscription.account) ] if invoice.subscription.next_subscription: # check for a transfer of subscription credits due to upgrades by # looking first at the active subscription or the "next" subscription # if the accounts don't match with the active subscription. active_sub = Subscription.get_active_subscription_by_domain( invoice.subscription.subscriber.domain ) if active_sub.account == invoice.subscription.account: relevant_credits.append( cls.get_credits_by_subscription_and_features(active_sub) ) elif (invoice.subscription.next_subscription.account == invoice.subscription.account): relevant_credits.append( cls.get_credits_by_subscription_and_features( invoice.subscription.next_subscription ) ) return itertools.chain(*relevant_credits) @classmethod def get_credits_for_customer_invoice(cls, invoice): return itertools.chain( cls.get_credits_for_subscriptions(invoice.subscriptions.all()), cls.get_credits_for_account(invoice.account) ) @classmethod def get_credits_for_subscriptions(cls, subscriptions, feature_type=None, is_product=False): credit_list = cls.objects.none() for subscription in subscriptions.all(): credit_list = credit_list.union(cls.get_credits_by_subscription_and_features( subscription, feature_type=feature_type, is_product=is_product )) return credit_list @classmethod def get_credits_for_account(cls, account, feature_type=None, is_product=False): assert not (feature_type and is_product) return cls.objects.filter( account=account, subscription__exact=None, is_active=True ).filter( is_product=is_product, feature_type__exact=feature_type ).all() @classmethod def get_credits_by_subscription_and_features(cls, subscription, feature_type=None, is_product=False): assert not (feature_type and is_product) return cls.objects.filter( subscription=subscription, feature_type__exact=feature_type, is_product=is_product, is_active=True ).all() @classmethod def get_non_general_credits_by_subscription(cls, subscription): return cls.objects.filter(subscription=subscription, is_active=True).filter( Q(is_product=True) | Q(feature_type__in=[f[0] for f in FeatureType.CHOICES]) ).all() @classmethod def add_credit(cls, amount, account=None, subscription=None, is_product=False, feature_type=None, payment_record=None, invoice=None, customer_invoice=None, line_item=None, related_credit=None, note=None, reason=None, web_user=None, permit_inactive=False): if account is None and subscription is None: raise CreditLineError( "You must specify either a subscription " "or account to add this credit to." ) if feature_type is not None and is_product: raise CreditLineError( "Can only add credit for a product OR a feature, but not both." ) account = account or subscription.account try: credit_line = cls.objects.get( account__exact=account, subscription__exact=subscription, is_product=is_product, feature_type__exact=feature_type, is_active=True ) if not permit_inactive and not credit_line.is_active and not invoice: raise CreditLineError( "Could not add credit to CreditLine %s because it is " "inactive." % str(credit_line) ) is_new = False except cls.MultipleObjectsReturned as e: raise CreditLineError( "Could not find a unique credit line for %(account)s" "%(subscription)s%(feature)s%(product)s. %(error)s" "instead." % { 'account': "Account ID %d" % account.id, 'subscription': (" | Subscription ID %d" % subscription.id if subscription is not None else ""), 'feature': (" | Feature %s" % feature_type if feature_type is not None else ""), 'product': (" | Product" if is_product else ""), 'error': str(e), } ) except cls.DoesNotExist: credit_line = cls.objects.create( account=account, subscription=subscription, is_product=is_product, feature_type=feature_type, ) is_new = True credit_line.adjust_credit_balance(amount, is_new=is_new, note=note, payment_record=payment_record, invoice=invoice, customer_invoice=customer_invoice, line_item=line_item, related_credit=related_credit, reason=reason, web_user=web_user) return credit_line @classmethod def apply_credits_toward_balance(cls, credit_lines, balance, **kwargs): for credit_line in credit_lines: if balance == Decimal('0.0000'): return if balance <= Decimal('0.0000'): raise CreditLineError( "A balance went below zero dollars when applying credits " "to credit line %d." % credit_line.pk ) adjustment_amount = min(credit_line.balance, balance) if adjustment_amount > Decimal('0.0000'): credit_line.adjust_credit_balance(-adjustment_amount, **kwargs) balance -= adjustment_amount @classmethod def make_payment_towards_invoice(cls, invoice, payment_record): """ Make a payment for a billing account towards an invoice """ if invoice.is_customer_invoice: billing_account = invoice.account else: billing_account = invoice.subscription.account cls.add_credit( payment_record.amount, account=billing_account, payment_record=payment_record, ) cls.add_credit( -payment_record.amount, account=billing_account, invoice=invoice, ) class PaymentMethod(models.Model): """A link to a particular payment method for an account. Right now the only payment methods are via Stripe, but leaving that open for future changes. :customer_id: is used by the API of the payment method we're using that uniquely identifies the payer on their end. """ web_user = models.CharField(max_length=80, db_index=True) method_type = models.CharField(max_length=50, default=PaymentMethodType.STRIPE, choices=PaymentMethodType.CHOICES, db_index=True) customer_id = models.CharField(max_length=255, null=True, blank=True) date_created = models.DateTimeField(auto_now_add=True) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' unique_together = ('web_user', 'method_type') class StripePaymentMethod(PaymentMethod): """ Do stuff with Stripe """ class Meta(object): proxy = True app_label = 'accounting' STRIPE_GENERIC_ERROR = (stripe.error.AuthenticationError, stripe.error.InvalidRequestError, stripe.error.APIConnectionError, stripe.error.StripeError,) @property def customer(self): return self._get_or_create_stripe_customer() def _get_or_create_stripe_customer(self): customer = None if self.customer_id is not None: try: customer = self._get_stripe_customer() except stripe.InvalidRequestError: pass if customer is None: customer = self._create_stripe_customer() return customer def _create_stripe_customer(self): customer = stripe.Customer.create( description="{}'s cards".format(self.web_user), email=self.web_user, ) self.customer_id = customer.id self.save() return customer def _get_stripe_customer(self): return stripe.Customer.retrieve(self.customer_id) @property def all_cards(self): try: return [card for card in self.customer.cards.data if card is not None] except stripe.error.AuthenticationError: if not settings.STRIPE_PRIVATE_KEY: log_accounting_info("Private key is not defined in settings") return [] else: raise def all_cards_serialized(self, billing_account): return [{ 'brand': card.brand, 'last4': card.last4, 'exp_month': card.exp_month, 'exp_year': card.exp_year, 'token': card.id, 'is_autopay': self._is_autopay(card, billing_account), } for card in self.all_cards] def get_card(self, card_token): return self.customer.cards.retrieve(card_token) def get_autopay_card(self, billing_account): return next(( card for card in self.all_cards if self._is_autopay(card, billing_account) ), None) def remove_card(self, card_token): card = self.get_card(card_token) self._remove_card_from_all_accounts(card) card.delete() def _remove_card_from_all_accounts(self, card): accounts = BillingAccount.objects.filter(auto_pay_user=self.web_user) for account in accounts: if account.autopay_card == card: account.remove_autopay_user() def create_card(self, stripe_token, billing_account, domain, autopay=False): customer = self.customer card = customer.cards.create(card=stripe_token) self.set_default_card(card) if autopay: self.set_autopay(card, billing_account, domain) return card def set_default_card(self, card): self.customer.default_card = card self.customer.save() return card def set_autopay(self, card, billing_account, domain): """ Sets the auto_pay status on the card for a billing account If there are other cards that auto_pay for that billing account, remove them """ if billing_account.auto_pay_enabled: self._remove_other_auto_pay_cards(billing_account) self._update_autopay_status(card, billing_account, autopay=True) billing_account.update_autopay_user(self.web_user, domain) def unset_autopay(self, card, billing_account): """ Unsets the auto_pay status for this card, and removes it from the billing account """ if self._is_autopay(card, billing_account): self._update_autopay_status(card, billing_account, autopay=False) billing_account.remove_autopay_user() def _update_autopay_status(self, card, billing_account, autopay): metadata = card.metadata.copy() metadata.update({self._auto_pay_card_metadata_key(billing_account): autopay}) card.metadata = metadata card.save() def _remove_autopay_card(self, billing_account): autopay_card = self.get_autopay_card(billing_account) if autopay_card is not None: self._update_autopay_status(autopay_card, billing_account, autopay=False) @staticmethod def _remove_other_auto_pay_cards(billing_account): user = billing_account.auto_pay_user try: other_payment_method = StripePaymentMethod.objects.get(web_user=user) other_payment_method._remove_autopay_card(billing_account) except StripePaymentMethod.DoesNotExist: pass @staticmethod def _is_autopay(card, billing_account): return card.metadata.get(StripePaymentMethod._auto_pay_card_metadata_key(billing_account)) == 'True' @staticmethod def _auto_pay_card_metadata_key(billing_account): """ Returns the autopay key for the billing account Cards can be used to autopay for multiple billing accounts. This is stored in the `metadata` property on the card: {metadata: {auto_pay_{billing_account_id_1}: True, auto_pay_{billing_account_id_2}: False}} """ return 'auto_pay_{billing_account_id}'.format(billing_account_id=billing_account.id) def create_charge(self, card, amount_in_dollars, description): """ Charges a stripe card and returns a transaction id """ amount_in_cents = int((amount_in_dollars * Decimal('100')).quantize(Decimal(10))) transaction_record = stripe.Charge.create( card=card, customer=self.customer, amount=amount_in_cents, currency=settings.DEFAULT_CURRENCY, description=description, ) return transaction_record.id class PaymentRecord(models.Model): """Records the transaction with external payment APIs. """ payment_method = models.ForeignKey(PaymentMethod, on_delete=models.PROTECT, db_index=True) date_created = models.DateTimeField(auto_now_add=True) transaction_id = models.CharField(max_length=255, unique=True) amount = models.DecimalField(default=Decimal('0.0000'), max_digits=10, decimal_places=4) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' @property def public_transaction_id(self): ops_num = settings.INVOICE_STARTING_NUMBER + self.id return "%sP-%d" % (settings.INVOICE_PREFIX, ops_num) @classmethod def create_record(cls, payment_method, transaction_id, amount): return cls.objects.create( payment_method=payment_method, transaction_id=transaction_id, amount=amount, ) class CreditAdjustment(ValidateModelMixin, models.Model): """ A record of any additions (positive amounts) or deductions (negative amounts) that contributed to the current balance of the associated CreditLine. """ credit_line = models.ForeignKey(CreditLine, on_delete=models.PROTECT) reason = models.CharField(max_length=25, default=CreditAdjustmentReason.MANUAL, choices=CreditAdjustmentReason.CHOICES) note = models.TextField(blank=True) amount = models.DecimalField(default=Decimal('0.0000'), max_digits=10, decimal_places=4) line_item = models.ForeignKey(LineItem, on_delete=models.PROTECT, null=True, blank=True) invoice = models.ForeignKey(Invoice, on_delete=models.PROTECT, null=True, blank=True) customer_invoice = models.ForeignKey(CustomerInvoice, on_delete=models.PROTECT, null=True, blank=True) payment_record = models.ForeignKey(PaymentRecord, on_delete=models.PROTECT, null=True, blank=True) related_credit = models.ForeignKey(CreditLine, on_delete=models.PROTECT, null=True, blank=True, related_name='creditadjustment_related') date_created = models.DateTimeField(auto_now_add=True) web_user = models.CharField(max_length=80, null=True, blank=True) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' def clean(self): """ Only one of either a line item or invoice may be specified as the adjuster. """ if self.line_item and self.invoice: raise ValidationError(_("You can't specify both an invoice and a line item.")) class DomainUserHistory(models.Model): """ A record of the number of users in a domain at the record_date. Created by task calculate_users_and_sms_in_all_domains on the first of every month. Used to bill clients for the appropriate number of users """ domain = models.CharField(max_length=256) record_date = models.DateField() num_users = models.IntegerField(default=0) class Meta: unique_together = ('domain', 'record_date')

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import datetime import itertools from decimal import Decimal from io import BytesIO from tempfile import NamedTemporaryFile from django.conf import settings from django.contrib.postgres.fields import ArrayField from django.core.exceptions import ValidationError from django.core.validators import MaxValueValidator, MinValueValidator from django.db import models, transaction from django.db.models import F, Q from django.db.models.manager import Manager from django.template.loader import render_to_string from django.utils.html import strip_tags from django.utils.translation import ugettext_lazy as _ import jsonfield import stripe from django_prbac.models import Role from memoized import memoized from corehq.apps.domain.shortcuts import publish_domain_saved from dimagi.ext.couchdbkit import ( BooleanProperty, DateTimeProperty, SafeSaveDocument, StringProperty, ) from dimagi.utils.web import get_site_domain from corehq.apps.accounting.emails import send_subscription_change_alert from corehq.apps.accounting.exceptions import ( AccountingError, CreditLineError, InvoiceEmailThrottledError, NewSubscriptionError, ProductPlanNotFoundError, SubscriptionAdjustmentError, SubscriptionChangeError, SubscriptionReminderError, SubscriptionRenewalError, ) from corehq.apps.accounting.invoice_pdf import InvoiceTemplate from corehq.apps.accounting.signals import subscription_upgrade_or_downgrade from corehq.apps.accounting.subscription_changes import ( DomainDowngradeActionHandler, DomainUpgradeActionHandler, ) from corehq.apps.accounting.utils import ( EXCHANGE_RATE_DECIMAL_PLACES, ensure_domain_instance, fmt_dollar_amount, get_account_name_from_default_name, get_address_from_invoice, get_change_status, get_dimagi_from_email, get_privileges, is_active_subscription, log_accounting_error, log_accounting_info, quantize_accounting_decimal, ) from corehq.apps.domain import UNKNOWN_DOMAIN from corehq.apps.domain.models import Domain from corehq.apps.hqwebapp.tasks import send_html_email_async from corehq.apps.users.models import WebUser from corehq.blobs.mixin import CODES, BlobMixin from corehq.const import USER_DATE_FORMAT from corehq.privileges import REPORT_BUILDER_ADD_ON_PRIVS from corehq.util.dates import get_first_last_days from corehq.util.mixin import ValidateModelMixin from corehq.util.quickcache import quickcache from corehq.util.soft_assert import soft_assert from corehq.util.view_utils import absolute_reverse integer_field_validators = [MaxValueValidator(2147483647), MinValueValidator(-2147483648)] MAX_INVOICE_COMMUNICATIONS = 5 SMALL_INVOICE_THRESHOLD = 100 UNLIMITED_FEATURE_USAGE = -1 MINIMUM_SUBSCRIPTION_LENGTH = 30 _soft_assert_contact_emails_missing = soft_assert( to=['{}@{}'.format(email, 'dimagi.com') for email in [ 'accounts', 'billing-dev', ]], exponential_backoff=False, ) class BillingAccountType(object): CONTRACT = "CONTRACT" USER_CREATED = "USER_CREATED" GLOBAL_SERVICES = "GLOBAL_SERVICES" INVOICE_GENERATED = "INVOICE_GENERATED" TRIAL = "TRIAL" CHOICES = ( (CONTRACT, "Created by contract"), (USER_CREATED, "Created by user"), (GLOBAL_SERVICES, "Created by Global Services"), (INVOICE_GENERATED, "Generated by an invoice"), (TRIAL, "Is trial account"), ) class InvoicingPlan(object): MONTHLY = "MONTHLY" QUARTERLY = "QUARTERLY" YEARLY = "YEARLY" CHOICES = ( (MONTHLY, "Monthly"), (QUARTERLY, "Quarterly"), (YEARLY, "Yearly") ) class FeatureType(object): USER = "User" SMS = "SMS" CHOICES = ( (USER, USER), (SMS, SMS), ) class SoftwarePlanEdition(object): COMMUNITY = "Community" STANDARD = "Standard" PRO = "Pro" ADVANCED = "Advanced" ENTERPRISE = "Enterprise" RESELLER = "Reseller" MANAGED_HOSTING = "Managed Hosting" PAUSED = "Paused" CHOICES = ( (COMMUNITY, COMMUNITY), (STANDARD, STANDARD), (PRO, PRO), (ADVANCED, ADVANCED), (ENTERPRISE, ENTERPRISE), (PAUSED, PAUSED), (RESELLER, RESELLER), (MANAGED_HOSTING, MANAGED_HOSTING), ) SELF_SERVICE_ORDER = [ PAUSED, COMMUNITY, STANDARD, PRO, ADVANCED, ] class SoftwarePlanVisibility(object): PUBLIC = "PUBLIC" INTERNAL = "INTERNAL" TRIAL = "TRIAL" CHOICES = ( (PUBLIC, "Anyone can subscribe"), (INTERNAL, "Dimagi must create subscription"), (TRIAL, "This is a Trial Plan"), ) class CreditAdjustmentReason(object): DIRECT_PAYMENT = "DIRECT_PAYMENT" SALESFORCE = "SALESFORCE" INVOICE = "INVOICE" LINE_ITEM = "LINE_ITEM" TRANSFER = "TRANSFER" MANUAL = "MANUAL" CHOICES = ( (MANUAL, "manual"), (SALESFORCE, "via Salesforce"), (INVOICE, "invoice generated"), (LINE_ITEM, "line item generated"), (TRANSFER, "transfer from another credit line"), (DIRECT_PAYMENT, "payment from client received"), ) class SubscriptionAdjustmentReason(object): CREATE = "CREATE" MODIFY = "MODIFY" CANCEL = "CANCEL" UPGRADE = "UPGRADE" DOWNGRADE = "DOWNGRADE" SWITCH = "SWITCH" REACTIVATE = "REACTIVATE" RENEW = "RENEW" CHOICES = ( (CREATE, "A new subscription created from scratch."), (MODIFY, "Some part of the subscription was modified...likely a date."), (CANCEL, "The subscription was cancelled with no followup subscription."), (UPGRADE, "The subscription was upgraded to the related subscription."), (DOWNGRADE, "The subscription was downgraded to the related subscription."), (SWITCH, "The plan was changed to the related subscription and " "was neither an upgrade or downgrade."), (REACTIVATE, "The subscription was reactivated."), (RENEW, "The subscription was renewed."), ) class SubscriptionAdjustmentMethod(object): USER = "USER" INTERNAL = "INTERNAL" TASK = "TASK" TRIAL = "TRIAL" AUTOMATIC_DOWNGRADE = 'AUTOMATIC_DOWNGRADE' DEFAULT_COMMUNITY = 'DEFAULT_COMMUNITY' INVOICING = 'INVOICING' CHOICES = ( (USER, "User"), (INTERNAL, "Ops"), (TASK, "[Deprecated] Task (Invoicing)"), (TRIAL, "30 Day Trial"), (AUTOMATIC_DOWNGRADE, "Automatic Downgrade"), (DEFAULT_COMMUNITY, 'Default to Community'), (INVOICING, 'Invoicing') ) class PaymentMethodType(object): STRIPE = "Stripe" CHOICES = ( (STRIPE, STRIPE), ) class SubscriptionType(object): IMPLEMENTATION = "IMPLEMENTATION" PRODUCT = "PRODUCT" TRIAL = "TRIAL" EXTENDED_TRIAL = "EXTENDED_TRIAL" SANDBOX = "SANDBOX" INTERNAL = "INTERNAL" NOT_SET = "NOT_SET" CHOICES = ( (IMPLEMENTATION, "Implementation"), (PRODUCT, "Product"), (TRIAL, "Trial"), (EXTENDED_TRIAL, "Extended Trial"), (SANDBOX, "Sandbox"), (INTERNAL, "Internal"), ) class ProBonoStatus(object): YES = "PRO_BONO" NO = "FULL_PRICE" DISCOUNTED = "DISCOUNTED" CHOICES = ( (NO, "Full Price"), (DISCOUNTED, "Discounted"), (YES, "Pro Bono"), ) class FundingSource(object): DIMAGI = "DIMAGI" CLIENT = "CLIENT" EXTERNAL = "EXTERNAL" CHOICES = ( (DIMAGI, "Dimagi"), (CLIENT, "Client Funding"), (EXTERNAL, "External Funding"), ) class EntryPoint(object): CONTRACTED = "CONTRACTED" SELF_STARTED = "SELF_STARTED" NOT_SET = "NOT_SET" CHOICES = ( (CONTRACTED, "Contracted"), (SELF_STARTED, "Self-started"), (NOT_SET, "Not Set"), ) class LastPayment(object): CC_ONE_TIME = "CC_ONE_TIME" CC_AUTO = "CC_AUTO" WIRE = "WIRE" ACH = "ACH" OTHER = "OTHER" BU_PAYMENT = "BU_PAYMENT" NONE = "NONE" CHOICES = ( (CC_ONE_TIME, "Credit Card - One Time"), (CC_AUTO, "Credit Card - Autopay"), (WIRE, "Wire"), (ACH, "ACH"), (OTHER, "Other"), (BU_PAYMENT, "Payment to local BU"), (NONE, "None"), ) class PreOrPostPay(object): PREPAY = "PREPAY" POSTPAY = "POSTPAY" NOT_SET = "NOT_SET" CHOICES = ( (PREPAY, "Prepay"), (POSTPAY, "Postpay"), (NOT_SET, "Not Set"), ) class Currency(models.Model): code = models.CharField(max_length=3, unique=True) name = models.CharField(max_length=25, db_index=True) symbol = models.CharField(max_length=10) rate_to_default = models.DecimalField( default=Decimal('1.0'), max_digits=20, decimal_places=EXCHANGE_RATE_DECIMAL_PLACES, ) date_updated = models.DateField(auto_now=True) class Meta(object): app_label = 'accounting' @classmethod def get_default(cls): default, _ = cls.objects.get_or_create(code=settings.DEFAULT_CURRENCY) return default DEFAULT_ACCOUNT_FORMAT = 'Account for Project %s' class BillingAccount(ValidateModelMixin, models.Model): name = models.CharField(max_length=200, db_index=True, unique=True) salesforce_account_id = models.CharField( db_index=True, max_length=80, blank=True, null=True, help_text="This is how we link to the salesforce account", ) created_by = models.CharField(max_length=80, blank=True) created_by_domain = models.CharField(max_length=256, null=True, blank=True) date_created = models.DateTimeField(auto_now_add=True) dimagi_contact = models.EmailField(blank=True) currency = models.ForeignKey(Currency, on_delete=models.PROTECT) is_auto_invoiceable = models.BooleanField(default=False) date_confirmed_extra_charges = models.DateTimeField(null=True, blank=True) account_type = models.CharField( max_length=25, default=BillingAccountType.CONTRACT, choices=BillingAccountType.CHOICES, ) is_active = models.BooleanField(default=True) is_customer_billing_account = models.BooleanField(default=False, db_index=True) enterprise_admin_emails = ArrayField(models.EmailField(), default=list, blank=True) enterprise_restricted_signup_domains = ArrayField(models.CharField(max_length=128), default=list, blank=True) invoicing_plan = models.CharField( max_length=25, default=InvoicingPlan.MONTHLY, choices=InvoicingPlan.CHOICES ) entry_point = models.CharField( max_length=25, default=EntryPoint.NOT_SET, choices=EntryPoint.CHOICES, ) auto_pay_user = models.CharField(max_length=80, null=True, blank=True) last_modified = models.DateTimeField(auto_now=True) last_payment_method = models.CharField( max_length=25, default=LastPayment.NONE, choices=LastPayment.CHOICES, ) pre_or_post_pay = models.CharField( max_length=25, default=PreOrPostPay.NOT_SET, choices=PreOrPostPay.CHOICES, ) restrict_domain_creation = models.BooleanField(default=False) restrict_signup = models.BooleanField(default=False, db_index=True) restrict_signup_message = models.CharField(max_length=512, null=True, blank=True) class Meta(object): app_label = 'accounting' @property def auto_pay_enabled(self): return self.auto_pay_user is not None @classmethod def create_account_for_domain(cls, domain, created_by=None, account_type=None, entry_point=None, last_payment_method=None, pre_or_post_pay=None): account_type = account_type or BillingAccountType.INVOICE_GENERATED entry_point = entry_point or EntryPoint.NOT_SET last_payment_method = last_payment_method or LastPayment.NONE pre_or_post_pay = pre_or_post_pay or PreOrPostPay.POSTPAY default_name = DEFAULT_ACCOUNT_FORMAT % domain name = get_account_name_from_default_name(default_name) return BillingAccount.objects.create( name=name, created_by=created_by, created_by_domain=domain, currency=Currency.get_default(), account_type=account_type, entry_point=entry_point, last_payment_method=last_payment_method, pre_or_post_pay=pre_or_post_pay ) @classmethod def get_or_create_account_by_domain(cls, domain, created_by=None, account_type=None, entry_point=None, last_payment_method=None, pre_or_post_pay=None): account = cls.get_account_by_domain(domain) if account: return account, False return cls.create_account_for_domain( domain, created_by=created_by, account_type=account_type, entry_point=entry_point, last_payment_method=last_payment_method, pre_or_post_pay=pre_or_post_pay, ), True @classmethod def get_account_by_domain(cls, domain): current_subscription = Subscription.get_active_subscription_by_domain(domain) if current_subscription is not None: return current_subscription.account else: return cls._get_account_by_created_by_domain(domain) @classmethod def _get_account_by_created_by_domain(cls, domain): try: return cls.objects.get(created_by_domain=domain) except cls.DoesNotExist: return None except cls.MultipleObjectsReturned: log_accounting_error( f"Multiple billing accounts showed up for the domain '{domain}'. The " "latest one was served, but you should reconcile very soon.", show_stack_trace=True, ) return cls.objects.filter(created_by_domain=domain).latest('date_created') return None @classmethod @quickcache([], timeout=60 * 60) def get_enterprise_restricted_signup_accounts(cls): return BillingAccount.objects.filter(is_customer_billing_account=True, restrict_signup=True) @property def autopay_card(self): if not self.auto_pay_enabled: return None return StripePaymentMethod.objects.get(web_user=self.auto_pay_user).get_autopay_card(self) def has_enterprise_admin(self, email): return self.is_customer_billing_account and email in self.enterprise_admin_emails def update_autopay_user(self, new_user, domain): if self.auto_pay_enabled and new_user != self.auto_pay_user: self._send_autopay_card_removed_email(new_user=new_user, domain=domain) self.auto_pay_user = new_user self.save() self._send_autopay_card_added_email(domain) def remove_autopay_user(self): self.auto_pay_user = None self.save() def _send_autopay_card_removed_email(self, new_user, domain): from corehq.apps.domain.views.accounting import EditExistingBillingAccountView old_user = self.auto_pay_user subject = _("Your card is no longer being used to auto-pay for {billing_account}").format( billing_account=self.name) old_web_user = WebUser.get_by_username(old_user) if old_web_user: old_user_name = old_web_user.first_name else: old_user_name = old_user context = { 'new_user': new_user, 'old_user_name': old_user_name, 'billing_account_name': self.name, 'billing_info_url': absolute_reverse(EditExistingBillingAccountView.urlname, args=[domain]), 'invoicing_contact_email': settings.INVOICING_CONTACT_EMAIL, } send_html_email_async( subject, old_user, render_to_string('accounting/email/autopay_card_removed.html', context), text_content=strip_tags(render_to_string('accounting/email/autopay_card_removed.html', context)), ) def _send_autopay_card_added_email(self, domain): from corehq.apps.domain.views.accounting import EditExistingBillingAccountView subject = _("Your card is being used to auto-pay for {billing_account}").format( billing_account=self.name) web_user = WebUser.get_by_username(self.auto_pay_user) new_user_name = web_user.first_name if web_user else self.auto_pay_user try: last_4 = self.autopay_card.last4 except StripePaymentMethod.DoesNotExist: last_4 = None context = { 'name': new_user_name, 'email': self.auto_pay_user, 'domain': domain, 'last_4': last_4, 'billing_account_name': self.name, 'billing_info_url': absolute_reverse(EditExistingBillingAccountView.urlname, args=[domain]), 'invoicing_contact_email': settings.INVOICING_CONTACT_EMAIL, } send_html_email_async( subject, self.auto_pay_user, render_to_string('accounting/email/invoice_autopay_setup.html', context), text_content=strip_tags(render_to_string('accounting/email/invoice_autopay_setup.html', context)), ) class BillingContactInfo(models.Model): account = models.OneToOneField(BillingAccount, primary_key=True, null=False, on_delete=models.CASCADE) first_name = models.CharField( max_length=50, null=True, blank=True, verbose_name=_("First Name") ) last_name = models.CharField( max_length=50, null=True, blank=True, verbose_name=_("Last Name") ) email_list = jsonfield.JSONField( default=list, verbose_name=_("Contact Emails"), help_text=_("We will email communications regarding your account " "to the emails specified here.") ) phone_number = models.CharField( max_length=20, null=True, blank=True, verbose_name=_("Phone Number") ) company_name = models.CharField( max_length=50, null=True, blank=True, verbose_name=_("Company / Organization") ) first_line = models.CharField( max_length=50, null=False, verbose_name=_("Address First Line") ) second_line = models.CharField( max_length=50, null=True, blank=True, verbose_name=_("Address Second Line") ) city = models.CharField( max_length=50, null=False, verbose_name=_("City") ) state_province_region = models.CharField( max_length=50, null=False, verbose_name=_("State / Province / Region"), ) postal_code = models.CharField( max_length=20, null=False, verbose_name=_("Postal Code") ) country = models.CharField( max_length=50, null=False, verbose_name=_("Country") ) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' def __init__(self, *args, **kwargs): super(BillingContactInfo, self).__init__(*args, **kwargs) if self.email_list == '[]': self.email_list = [] @property def full_name(self): if not self.first_name: return self.last_name elif not self.last_name: return self.first_name else: return "%s %s" % (self.first_name, self.last_name) class SoftwareProductRate(models.Model): name = models.CharField(max_length=40) monthly_fee = models.DecimalField(default=Decimal('0.00'), max_digits=10, decimal_places=2) date_created = models.DateTimeField(auto_now_add=True) is_active = models.BooleanField(default=True) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' def __str__(self): return '%s @ $%s /month' % (self.name, self.monthly_fee) def __eq__(self, other): if not isinstance(other, self.__class__) or not self.name == other.name: return False for field in ['monthly_fee', 'is_active']: if not getattr(self, field) == getattr(other, field): return False return True @classmethod def new_rate(cls, product_name, monthly_fee, save=True): rate = SoftwareProductRate(name=product_name, monthly_fee=monthly_fee) if save: rate.save() return rate class Feature(models.Model): name = models.CharField(max_length=40, unique=True) feature_type = models.CharField(max_length=10, db_index=True, choices=FeatureType.CHOICES) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' def __str__(self): return "Feature '%s' of type '%s'" % (self.name, self.feature_type) def get_rate(self, default_instance=True): try: return self.featurerate_set.filter(is_active=True).latest('date_created') except FeatureRate.DoesNotExist: return FeatureRate() if default_instance else None class FeatureRate(models.Model): feature = models.ForeignKey(Feature, on_delete=models.PROTECT) monthly_fee = models.DecimalField(default=Decimal('0.00'), max_digits=10, decimal_places=2, verbose_name="Monthly Fee") monthly_limit = models.IntegerField(default=0, verbose_name="Monthly Included Limit", validators=integer_field_validators) per_excess_fee = models.DecimalField(default=Decimal('0.00'), max_digits=10, decimal_places=2, verbose_name="Fee Per Excess of Limit") date_created = models.DateTimeField(auto_now_add=True) is_active = models.BooleanField(default=True) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' def __str__(self): return '%s @ $%s /month, $%s /excess, limit: %d' % ( self.feature.name, self.monthly_fee, self.per_excess_fee, self.monthly_limit ) def __eq__(self, other): if not isinstance(other, self.__class__) or not self.feature.pk == other.feature.pk: return False for field in ['monthly_fee', 'monthly_limit', 'per_excess_fee', 'is_active']: if not getattr(self, field) == getattr(other, field): return False return True @classmethod def new_rate(cls, feature_name, feature_type, monthly_fee=None, monthly_limit=None, per_excess_fee=None, save=True): feature, _ = Feature.objects.get_or_create(name=feature_name, feature_type=feature_type) rate = FeatureRate(feature=feature) if monthly_fee is not None: rate.monthly_fee = monthly_fee if monthly_limit is not None: rate.monthly_limit = monthly_limit if per_excess_fee is not None: rate.per_excess_fee = per_excess_fee if save: rate.save() return rate class SoftwarePlan(models.Model): name = models.CharField(max_length=80, unique=True) description = models.TextField(blank=True, help_text="If the visibility is INTERNAL, this description field will be used.") edition = models.CharField( max_length=25, default=SoftwarePlanEdition.ENTERPRISE, choices=SoftwarePlanEdition.CHOICES, ) visibility = models.CharField( max_length=10, default=SoftwarePlanVisibility.INTERNAL, choices=SoftwarePlanVisibility.CHOICES, ) last_modified = models.DateTimeField(auto_now=True) is_customer_software_plan = models.BooleanField(default=False) max_domains = models.IntegerField(blank=True, null=True) is_annual_plan = models.BooleanField(default=False) class Meta(object): app_label = 'accounting' @quickcache(vary_on=['self.pk'], timeout=10) def get_version(self): try: return self.softwareplanversion_set.filter(is_active=True).latest('date_created') except SoftwarePlanVersion.DoesNotExist: return None def at_max_domains(self): if not self.max_domains: return False subscription_count = 0 for version in self.softwareplanversion_set.all(): subscription_count += Subscription.visible_objects.filter(plan_version=version, is_active=True).count() return subscription_count >= self.max_domains class DefaultProductPlan(models.Model): edition = models.CharField( default=SoftwarePlanEdition.COMMUNITY, choices=SoftwarePlanEdition.CHOICES, max_length=25, ) plan = models.ForeignKey(SoftwarePlan, on_delete=models.PROTECT) is_trial = models.BooleanField(default=False) is_report_builder_enabled = models.BooleanField(default=False) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' unique_together = ('edition', 'is_trial', 'is_report_builder_enabled') @classmethod @quickcache(['edition', 'is_trial', 'is_report_builder_enabled'], skip_arg=lambda *args, **kwargs: not settings.ENTERPRISE_MODE or settings.UNIT_TESTING) def get_default_plan_version(cls, edition=None, is_trial=False, is_report_builder_enabled=False): if not edition: edition = (SoftwarePlanEdition.ENTERPRISE if settings.ENTERPRISE_MODE else SoftwarePlanEdition.COMMUNITY) try: default_product_plan = DefaultProductPlan.objects.select_related('plan').get( edition=edition, is_trial=is_trial, is_report_builder_enabled=is_report_builder_enabled ) return default_product_plan.plan.get_version() except DefaultProductPlan.DoesNotExist: raise AccountingError( "No default product plan was set up, did you forget to run migrations?" ) @classmethod def get_lowest_edition(cls, requested_privileges, return_plan=False): for edition in SoftwarePlanEdition.SELF_SERVICE_ORDER: plan_version = cls.get_default_plan_version(edition) privileges = get_privileges(plan_version) - REPORT_BUILDER_ADD_ON_PRIVS if privileges.issuperset(requested_privileges): return (plan_version if return_plan else plan_version.plan.edition) return None if return_plan else SoftwarePlanEdition.ENTERPRISE class SoftwarePlanVersion(models.Model): plan = models.ForeignKey(SoftwarePlan, on_delete=models.PROTECT) product_rate = models.ForeignKey(SoftwareProductRate, on_delete=models.CASCADE) feature_rates = models.ManyToManyField(FeatureRate, blank=True) date_created = models.DateTimeField(auto_now_add=True) is_active = models.BooleanField(default=True) role = models.ForeignKey(Role, on_delete=models.CASCADE) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' def __str__(self): return "%(plan_name)s (v%(version_num)d)" % { 'plan_name': self.plan.name, 'version_num': self.version, } def save(self, *args, **kwargs): super(SoftwarePlanVersion, self).save(*args, **kwargs) SoftwarePlan.get_version.clear(self.plan) @property def version(self): return (self.plan.softwareplanversion_set.count() - self.plan.softwareplanversion_set.filter( date_created__gt=self.date_created).count()) @property def user_facing_description(self): from corehq.apps.accounting.user_text import DESC_BY_EDITION, FEATURE_TYPE_TO_NAME def _default_description(plan, monthly_limit): if plan.edition in [ SoftwarePlanEdition.COMMUNITY, SoftwarePlanEdition.STANDARD, SoftwarePlanEdition.PRO, SoftwarePlanEdition.ADVANCED, ]: return DESC_BY_EDITION[plan.edition]['description'].format(monthly_limit) else: return DESC_BY_EDITION[plan.edition]['description'] desc = { 'name': self.plan.name, } if ( self.plan.visibility == SoftwarePlanVisibility.PUBLIC or self.plan.visibility == SoftwarePlanVisibility.TRIAL ) or not self.plan.description: desc['description'] = _default_description(self.plan, self.user_feature.monthly_limit) else: desc['description'] = self.plan.description desc.update({ 'monthly_fee': 'USD %s' % self.product_rate.monthly_fee, 'rates': [{'name': FEATURE_TYPE_TO_NAME[r.feature.feature_type], 'included': 'Infinite' if r.monthly_limit == UNLIMITED_FEATURE_USAGE else r.monthly_limit} for r in self.feature_rates.all()], 'edition': self.plan.edition, }) return desc @property @memoized def user_feature(self): user_features = self.feature_rates.filter(feature__feature_type=FeatureType.USER) try: user_feature = user_features.order_by('monthly_limit')[0] if not user_feature.monthly_limit == UNLIMITED_FEATURE_USAGE: user_feature = user_features.order_by('-monthly_limit')[0] return user_feature except IndexError: pass @property def user_limit(self): if self.user_feature is not None: return self.user_feature.monthly_limit return UNLIMITED_FEATURE_USAGE @property def user_fee(self): if self.user_feature is not None: return "USD %d" % self.user_feature.per_excess_fee def feature_charges_exist_for_domain(self, domain, start_date=None, end_date=None): domain_obj = ensure_domain_instance(domain) if domain_obj is None: return False from corehq.apps.accounting.usage import FeatureUsageCalculator for feature_rate in self.feature_rates.all(): if feature_rate.monthly_limit != UNLIMITED_FEATURE_USAGE: calc = FeatureUsageCalculator( feature_rate, domain_obj.name, start_date=start_date, end_date=end_date ) if calc.get_usage() > feature_rate.monthly_limit: return True return False @property def is_paused(self): return self.plan.edition == SoftwarePlanEdition.PAUSED class SubscriberManager(models.Manager): def safe_get(self, *args, **kwargs): try: return self.get(*args, **kwargs) except Subscriber.DoesNotExist: return None class Subscriber(models.Model): domain = models.CharField(max_length=256, unique=True, db_index=True) last_modified = models.DateTimeField(auto_now=True) objects = SubscriberManager() class Meta(object): app_label = 'accounting' def __str__(self): return "DOMAIN %s" % self.domain def create_subscription(self, new_plan_version, new_subscription, is_internal_change): assert new_plan_version assert new_subscription return self._apply_upgrades_and_downgrades( new_plan_version=new_plan_version, new_subscription=new_subscription, internal_change=is_internal_change, ) def change_subscription(self, downgraded_privileges, upgraded_privileges, new_plan_version, old_subscription, new_subscription, internal_change): return self._apply_upgrades_and_downgrades( downgraded_privileges=downgraded_privileges, upgraded_privileges=upgraded_privileges, new_plan_version=new_plan_version, old_subscription=old_subscription, new_subscription=new_subscription, internal_change=internal_change, ) def activate_subscription(self, upgraded_privileges, subscription): return self._apply_upgrades_and_downgrades( upgraded_privileges=upgraded_privileges, new_subscription=subscription, ) def deactivate_subscription(self, downgraded_privileges, upgraded_privileges, old_subscription, new_subscription): return self._apply_upgrades_and_downgrades( downgraded_privileges=downgraded_privileges, upgraded_privileges=upgraded_privileges, old_subscription=old_subscription, new_subscription=new_subscription, ) def reactivate_subscription(self, new_plan_version, subscription): return self._apply_upgrades_and_downgrades( new_plan_version=new_plan_version, old_subscription=subscription, new_subscription=subscription, ) def _apply_upgrades_and_downgrades(self, new_plan_version=None, downgraded_privileges=None, upgraded_privileges=None, old_subscription=None, new_subscription=None, internal_change=False): if new_plan_version is None: new_plan_version = DefaultProductPlan.get_default_plan_version() if downgraded_privileges is None or upgraded_privileges is None: change_status_result = get_change_status(None, new_plan_version) downgraded_privileges = downgraded_privileges or change_status_result.downgraded_privs upgraded_privileges = upgraded_privileges or change_status_result.upgraded_privs if downgraded_privileges: Subscriber._process_downgrade(self.domain, downgraded_privileges, new_plan_version) if upgraded_privileges: Subscriber._process_upgrade(self.domain, upgraded_privileges, new_plan_version) if Subscriber.should_send_subscription_notification(old_subscription, new_subscription): send_subscription_change_alert(self.domain, new_subscription, old_subscription, internal_change) subscription_upgrade_or_downgrade.send_robust(None, domain=self.domain) @staticmethod def should_send_subscription_notification(old_subscription, new_subscription): if not old_subscription: return False is_new_trial = new_subscription and new_subscription.is_trial expired_trial = old_subscription.is_trial and not new_subscription return not is_new_trial and not expired_trial @staticmethod def _process_downgrade(domain, downgraded_privileges, new_plan_version): downgrade_handler = DomainDowngradeActionHandler( domain, new_plan_version, downgraded_privileges, ) if not downgrade_handler.get_response(): raise SubscriptionChangeError("The downgrade was not successful.") @staticmethod def _process_upgrade(domain, upgraded_privileges, new_plan_version): upgrade_handler = DomainUpgradeActionHandler( domain, new_plan_version, upgraded_privileges, ) if not upgrade_handler.get_response(): raise SubscriptionChangeError("The upgrade was not successful.") class VisibleSubscriptionManager(models.Manager): use_in_migrations = True def get_queryset(self): return super(VisibleSubscriptionManager, self).get_queryset().filter(is_hidden_to_ops=False) class DisabledManager(models.Manager): def get_queryset(self): raise NotImplementedError class Subscription(models.Model): account = models.ForeignKey(BillingAccount, on_delete=models.PROTECT) plan_version = models.ForeignKey(SoftwarePlanVersion, on_delete=models.PROTECT) subscriber = models.ForeignKey(Subscriber, on_delete=models.PROTECT) salesforce_contract_id = models.CharField(blank=True, max_length=80) date_start = models.DateField() date_end = models.DateField(blank=True, null=True) date_created = models.DateTimeField(auto_now_add=True) is_active = models.BooleanField(default=False) do_not_invoice = models.BooleanField(default=False) no_invoice_reason = models.CharField(blank=True, max_length=256) do_not_email_invoice = models.BooleanField(default=False) do_not_email_reminder = models.BooleanField(default=False) auto_generate_credits = models.BooleanField(default=False) is_trial = models.BooleanField(default=False) skip_invoicing_if_no_feature_charges = models.BooleanField(default=False) service_type = models.CharField( max_length=25, choices=SubscriptionType.CHOICES, default=SubscriptionType.NOT_SET ) pro_bono_status = models.CharField( max_length=25, choices=ProBonoStatus.CHOICES, default=ProBonoStatus.NO, ) funding_source = models.CharField( max_length=25, choices=FundingSource.CHOICES, default=FundingSource.CLIENT ) last_modified = models.DateTimeField(auto_now=True) is_hidden_to_ops = models.BooleanField(default=False) skip_auto_downgrade = models.BooleanField(default=False) skip_auto_downgrade_reason = models.CharField(blank=True, max_length=256) visible_objects = VisibleSubscriptionManager() visible_and_suppressed_objects = models.Manager() objects = DisabledManager() class Meta(object): app_label = 'accounting' def __str__(self): return ("Subscription to %(plan_version)s for %(subscriber)s. " "[%(date_start)s - %(date_end)s]" % { 'plan_version': self.plan_version, 'subscriber': self.subscriber, 'date_start': self.date_start.strftime(USER_DATE_FORMAT), 'date_end': (self.date_end.strftime(USER_DATE_FORMAT) if self.date_end is not None else "--"), }) def __eq__(self, other): return ( other is not None and other.__class__.__name__ == self.__class__.__name__ and other.plan_version.pk == self.plan_version.pk and other.date_start == self.date_start and other.date_end == self.date_end and other.subscriber.pk == self.subscriber.pk and other.account.pk == self.account.pk ) def save(self, *args, **kwargs): from corehq.apps.accounting.mixins import get_overdue_invoice super(Subscription, self).save(*args, **kwargs) Subscription._get_active_subscription_by_domain.clear(Subscription, self.subscriber.domain) get_overdue_invoice.clear(self.subscriber.domain) domain = Domain.get_by_name(self.subscriber.domain) # we don't care the pillow won't be updated if domain: publish_domain_saved(domain) def delete(self, *args, **kwargs): super(Subscription, self).delete(*args, **kwargs) Subscription._get_active_subscription_by_domain.clear(Subscription, self.subscriber.domain) @property def is_community(self): return self.plan_version.plan.edition == SoftwarePlanEdition.COMMUNITY @property def allowed_attr_changes(self): return ['do_not_invoice', 'no_invoice_reason', 'salesforce_contract_id', 'skip_auto_downgrade'] @property def next_subscription_filter(self): return (Subscription.visible_objects. filter(subscriber=self.subscriber, date_start__gt=self.date_start). exclude(pk=self.pk). filter(Q(date_end__isnull=True) | ~Q(date_start=F('date_end')))) @property def previous_subscription_filter(self): return Subscription.visible_objects.filter( subscriber=self.subscriber, date_start__lt=self.date_start - datetime.timedelta(days=1) ).exclude(pk=self.pk) @property def is_renewed(self): return self.next_subscription_filter.exists() @property def next_subscription(self): try: return self.next_subscription_filter.order_by('date_start')[0] except (Subscription.DoesNotExist, IndexError): return None @property def previous_subscription(self): try: return self.previous_subscription_filter.order_by('-date_end')[0] except (Subscription.DoesNotExist, IndexError): return None def raise_conflicting_dates(self, date_start, date_end): assert date_start is not None for sub in Subscription.visible_objects.filter( Q(date_end__isnull=True) | Q(date_end__gt=F('date_start')), subscriber=self.subscriber, ).exclude( id=self.id, ): related_has_no_end = sub.date_end is None current_has_no_end = date_end is None start_before_related_end = sub.date_end is not None and date_start < sub.date_end start_before_related_start = date_start < sub.date_start start_after_related_start = date_start > sub.date_start end_before_related_end = ( date_end is not None and sub.date_end is not None and date_end < sub.date_end ) end_after_related_end = ( date_end is not None and sub.date_end is not None and date_end > sub.date_end ) end_after_related_start = date_end is not None and date_end > sub.date_start if ( (start_before_related_end and start_after_related_start) or (start_after_related_start and related_has_no_end) or (end_after_related_start and end_before_related_end) or (end_after_related_start and related_has_no_end) or (start_before_related_start and end_after_related_end) or (start_before_related_end and current_has_no_end) or (current_has_no_end and related_has_no_end) ): raise SubscriptionAdjustmentError( "The start date of %(start_date)s conflicts with the " "subscription dates to %(related_sub)s." % { 'start_date': self.date_start.strftime(USER_DATE_FORMAT), 'related_sub': sub, } ) def update_subscription(self, date_start, date_end, do_not_invoice=None, no_invoice_reason=None, do_not_email_invoice=None, do_not_email_reminder=None, salesforce_contract_id=None, auto_generate_credits=None, web_user=None, note=None, adjustment_method=None, service_type=None, pro_bono_status=None, funding_source=None, skip_invoicing_if_no_feature_charges=None, skip_auto_downgrade=None, skip_auto_downgrade_reason=None): adjustment_method = adjustment_method or SubscriptionAdjustmentMethod.INTERNAL self._update_dates(date_start, date_end) self._update_properties( do_not_invoice=do_not_invoice, no_invoice_reason=no_invoice_reason, skip_invoicing_if_no_feature_charges=skip_invoicing_if_no_feature_charges, do_not_email_invoice=do_not_email_invoice, do_not_email_reminder=do_not_email_reminder, auto_generate_credits=auto_generate_credits, salesforce_contract_id=salesforce_contract_id, service_type=service_type, pro_bono_status=pro_bono_status, funding_source=funding_source, skip_auto_downgrade=skip_auto_downgrade, skip_auto_downgrade_reason=skip_auto_downgrade_reason, ) self.save() SubscriptionAdjustment.record_adjustment( self, method=adjustment_method, note=note, web_user=web_user, reason=SubscriptionAdjustmentReason.MODIFY ) def _update_dates(self, date_start, date_end): if not date_start: raise SubscriptionAdjustmentError('Start date must be provided') if date_end is not None and date_start > date_end: raise SubscriptionAdjustmentError( "Can't have a subscription start after the end date." ) self.raise_conflicting_dates(date_start, date_end) self.date_start = date_start self.date_end = date_end is_active_dates = is_active_subscription(self.date_start, self.date_end) if self.is_active != is_active_dates: if is_active_dates: self.is_active = True self.subscriber.activate_subscription(get_privileges(self.plan_version), self) else: raise SubscriptionAdjustmentError( 'Cannot deactivate a subscription here. Cancel subscription instead.' ) def _update_properties(self, **kwargs): property_names = { 'do_not_invoice', 'no_invoice_reason', 'skip_invoicing_if_no_feature_charges', 'do_not_email_invoice', 'do_not_email_reminder', 'auto_generate_credits', 'salesforce_contract_id', 'service_type', 'pro_bono_status', 'funding_source', 'skip_auto_downgrade', 'skip_auto_downgrade_reason', } assert property_names >= set(kwargs.keys()) for property_name, property_value in kwargs.items(): if property_value is not None: setattr(self, property_name, property_value) @transaction.atomic def change_plan(self, new_plan_version, date_end=None, note=None, web_user=None, adjustment_method=None, service_type=None, pro_bono_status=None, funding_source=None, transfer_credits=True, internal_change=False, account=None, do_not_invoice=None, no_invoice_reason=None, auto_generate_credits=False, is_trial=False): from corehq.apps.analytics.tasks import track_workflow adjustment_method = adjustment_method or SubscriptionAdjustmentMethod.INTERNAL today = datetime.date.today() assert self.is_active assert date_end is None or date_end >= today if new_plan_version.plan.at_max_domains() and self.plan_version.plan != new_plan_version.plan: raise SubscriptionAdjustmentError( 'The maximum number of project spaces has been reached for %(new_plan_version)s. ' % { 'new_plan_version': new_plan_version, } ) self.date_end = today self.is_active = False self.save() new_subscription = Subscription( account=account if account else self.account, plan_version=new_plan_version, subscriber=self.subscriber, salesforce_contract_id=self.salesforce_contract_id, date_start=today, date_end=date_end, is_active=True, do_not_invoice=do_not_invoice if do_not_invoice is not None else self.do_not_invoice, no_invoice_reason=no_invoice_reason if no_invoice_reason is not None else self.no_invoice_reason, auto_generate_credits=auto_generate_credits, is_trial=is_trial, service_type=(service_type or SubscriptionType.NOT_SET), pro_bono_status=(pro_bono_status or ProBonoStatus.NO), funding_source=(funding_source or FundingSource.CLIENT), skip_auto_downgrade=False, skip_auto_downgrade_reason='', ) new_subscription.save() new_subscription.raise_conflicting_dates(new_subscription.date_start, new_subscription.date_end) new_subscription.set_billing_account_entry_point() change_status_result = get_change_status(self.plan_version, new_plan_version) self.subscriber.change_subscription( downgraded_privileges=change_status_result.downgraded_privs, upgraded_privileges=change_status_result.upgraded_privs, new_plan_version=new_plan_version, old_subscription=self, new_subscription=new_subscription, internal_change=internal_change, ) if transfer_credits: self.transfer_credits(new_subscription) SubscriptionAdjustment.record_adjustment( self, method=adjustment_method, note=note, web_user=web_user, reason=change_status_result.adjustment_reason, related_subscription=new_subscription ) SubscriptionAdjustment.record_adjustment( new_subscription, method=adjustment_method, note=note, web_user=web_user, reason=SubscriptionAdjustmentReason.CREATE ) upgrade_reasons = [SubscriptionAdjustmentReason.UPGRADE, SubscriptionAdjustmentReason.CREATE] if web_user and adjustment_method == SubscriptionAdjustmentMethod.USER: if change_status_result.adjustment_reason in upgrade_reasons: track_workflow(web_user, 'Changed Plan: Upgrade') if change_status_result.adjustment_reason == SubscriptionAdjustmentReason.DOWNGRADE: track_workflow(web_user, 'Changed Plan: Downgrade') return new_subscription def reactivate_subscription(self, date_end=None, note=None, web_user=None, adjustment_method=None, **kwargs): adjustment_method = adjustment_method or SubscriptionAdjustmentMethod.INTERNAL self.date_end = date_end self.is_active = True for allowed_attr in self.allowed_attr_changes: if allowed_attr in kwargs: setattr(self, allowed_attr, kwargs[allowed_attr]) self.save() self.subscriber.reactivate_subscription( new_plan_version=self.plan_version, subscription=self, ) SubscriptionAdjustment.record_adjustment( self, reason=SubscriptionAdjustmentReason.REACTIVATE, method=adjustment_method, note=note, web_user=web_user, ) def renew_subscription(self, note=None, web_user=None, adjustment_method=None, service_type=None, pro_bono_status=None, funding_source=None, new_version=None): adjustment_method = adjustment_method or SubscriptionAdjustmentMethod.INTERNAL if self.date_end is None: raise SubscriptionRenewalError( "Cannot renew a subscription with no date_end set." ) if new_version is None: current_privileges = get_privileges(self.plan_version) new_version = DefaultProductPlan.get_lowest_edition( current_privileges, return_plan=True, ) if new_version is None: raise SubscriptionRenewalError( "There was an issue renewing your subscription. Someone " "from Dimagi will get back to you shortly." ) renewed_subscription = Subscription( account=self.account, plan_version=new_version, subscriber=self.subscriber, salesforce_contract_id=self.salesforce_contract_id, date_start=self.date_end, date_end=None, ) if service_type is not None: renewed_subscription.service_type = service_type if pro_bono_status is not None: renewed_subscription.pro_bono_status = pro_bono_status if funding_source is not None: renewed_subscription.funding_source = funding_source if datetime.date.today() == self.date_end: renewed_subscription.is_active = True renewed_subscription.save() SubscriptionAdjustment.record_adjustment( self, method=adjustment_method, note=note, web_user=web_user, reason=SubscriptionAdjustmentReason.RENEW, ) return renewed_subscription def transfer_credits(self, subscription=None): if subscription is not None and self.account.pk != subscription.account.pk: raise CreditLineError( "Can only transfer subscription credits under the same " "Billing Account." ) source_credits = CreditLine.objects.filter( account=self.account, subscription=self, ).all() for credit_line in source_credits: transferred_credit = CreditLine.add_credit( credit_line.balance, account=self.account, subscription=subscription, feature_type=credit_line.feature_type, is_product=credit_line.is_product, related_credit=credit_line ) credit_line.is_active = False credit_line.adjust_credit_balance( credit_line.balance * Decimal('-1'), related_credit=transferred_credit, ) def send_ending_reminder_email(self): if self.date_end is None: raise SubscriptionReminderError( "This subscription has no end date." ) today = datetime.date.today() num_days_left = (self.date_end - today).days domain_name = self.subscriber.domain context = self.ending_reminder_context subject = context['subject'] template = self.ending_reminder_email_html template_plaintext = self.ending_reminder_email_text email_html = render_to_string(template, context) email_plaintext = render_to_string(template_plaintext, context) bcc = [settings.ACCOUNTS_EMAIL] if not self.is_trial else [] if self.account.dimagi_contact is not None: bcc.append(self.account.dimagi_contact) for email in self._reminder_email_contacts(domain_name): send_html_email_async.delay( subject, email, email_html, text_content=email_plaintext, email_from=get_dimagi_from_email(), bcc=bcc, ) log_accounting_info( "Sent %(days_left)s-day subscription reminder " "email for %(domain)s to %(email)s." % { 'days_left': num_days_left, 'domain': domain_name, 'email': email, } ) @property def ending_reminder_email_html(self): if self.account.is_customer_billing_account: return 'accounting/email/customer_subscription_ending_reminder.html' elif self.is_trial: return 'accounting/email/trial_ending_reminder.html' else: return 'accounting/email/subscription_ending_reminder.html' @property def ending_reminder_email_text(self): if self.account.is_customer_billing_account: return 'accounting/email/customer_subscription_ending_reminder.txt' elif self.is_trial: return 'accounting/email/trial_ending_reminder.txt' else: return 'accounting/email/subscription_ending_reminder.txt' @property def ending_reminder_context(self): from corehq.apps.domain.views.accounting import DomainSubscriptionView today = datetime.date.today() num_days_left = (self.date_end - today).days if num_days_left == 1: ending_on = _("tomorrow!") else: ending_on = _("on %s." % self.date_end.strftime(USER_DATE_FORMAT)) user_desc = self.plan_version.user_facing_description plan_name = user_desc['name'] domain_name = self.subscriber.domain context = { 'domain': domain_name, 'plan_name': plan_name, 'account': self.account.name, 'ending_on': ending_on, 'subscription_url': absolute_reverse( DomainSubscriptionView.urlname, args=[self.subscriber.domain]), 'base_url': get_site_domain(), 'invoicing_contact_email': settings.INVOICING_CONTACT_EMAIL, 'sales_email': settings.SALES_EMAIL, } if self.account.is_customer_billing_account: subject = _( "CommCare Alert: %(account_name)s's subscription to " "%(plan_name)s ends %(ending_on)s" ) % { 'account_name': self.account.name, 'plan_name': plan_name, 'ending_on': ending_on, } elif self.is_trial: subject = _("CommCare Alert: 30 day trial for '%(domain)s' " "ends %(ending_on)s") % { 'domain': domain_name, 'ending_on': ending_on, } else: subject = _( "CommCare Alert: %(domain)s's subscription to " "%(plan_name)s ends %(ending_on)s" ) % { 'plan_name': plan_name, 'domain': domain_name, 'ending_on': ending_on, } context.update({'subject': subject}) return context def send_dimagi_ending_reminder_email(self): if self.date_end is None: raise SubscriptionReminderError( "This subscription has no end date." ) if self.account.dimagi_contact is None: raise SubscriptionReminderError( "This subscription has no Dimagi contact." ) subject = self.dimagi_ending_reminder_subject context = self.dimagi_ending_reminder_context email_html = render_to_string(self.dimagi_ending_reminder_email_html, context) email_plaintext = render_to_string(self.dimagi_ending_reminder_email_text, context) send_html_email_async.delay( subject, self.account.dimagi_contact, email_html, text_content=email_plaintext, email_from=settings.DEFAULT_FROM_EMAIL, ) @property def dimagi_ending_reminder_email_html(self): if self.account.is_customer_billing_account: return 'accounting/email/customer_subscription_ending_reminder_dimagi.html' else: return 'accounting/email/subscription_ending_reminder_dimagi.html' @property def dimagi_ending_reminder_email_text(self): if self.account.is_customer_billing_account: return 'accounting/email/customer_subscription_ending_reminder_dimagi.txt' else: return 'accounting/email/subscription_ending_reminder_dimagi.txt' @property def dimagi_ending_reminder_subject(self): if self.account.is_customer_billing_account: return "Alert: {account}'s subscriptions are ending on {end_date}".format( account=self.account.name, end_date=self.date_end.strftime(USER_DATE_FORMAT)) else: return "Alert: {domain}'s subscription is ending on {end_date}".format( domain=self.subscriber.domain, end_date=self.date_end.strftime(USER_DATE_FORMAT)) @property def dimagi_ending_reminder_context(self): end_date = self.date_end.strftime(USER_DATE_FORMAT) email = self.account.dimagi_contact if self.account.is_customer_billing_account: account = self.account.name plan = self.plan_version.plan.edition context = { 'account': account, 'plan': plan, 'end_date': end_date, 'client_reminder_email_date': (self.date_end - datetime.timedelta(days=30)).strftime( USER_DATE_FORMAT), 'contacts': ', '.join(self._reminder_email_contacts(self.subscriber.domain)), 'dimagi_contact': email, 'accounts_email': settings.ACCOUNTS_EMAIL } else: domain = self.subscriber.domain context = { 'domain': domain, 'end_date': end_date, 'client_reminder_email_date': (self.date_end - datetime.timedelta(days=30)).strftime( USER_DATE_FORMAT), 'contacts': ', '.join(self._reminder_email_contacts(domain)), 'dimagi_contact': email, } return context def _reminder_email_contacts(self, domain_name): emails = {a.username for a in WebUser.get_admins_by_domain(domain_name)} emails |= {e for e in WebUser.get_dimagi_emails_by_domain(domain_name)} if not self.is_trial: billing_contact_emails = ( self.account.billingcontactinfo.email_list if BillingContactInfo.objects.filter(account=self.account).exists() else [] ) if not billing_contact_emails: from corehq.apps.accounting.views import ManageBillingAccountView _soft_assert_contact_emails_missing( False, 'Billing Account for project %s is missing client contact emails: %s' % ( domain_name, absolute_reverse(ManageBillingAccountView.urlname, args=[self.account.id]) ) ) emails |= {billing_contact_email for billing_contact_email in billing_contact_emails} if self.account.is_customer_billing_account: enterprise_admin_emails = self.account.enterprise_admin_emails emails |= {enterprise_admin_email for enterprise_admin_email in enterprise_admin_emails} return emails def set_billing_account_entry_point(self): no_current_entry_point = self.account.entry_point == EntryPoint.NOT_SET self_serve = self.service_type == SubscriptionType.PRODUCT if no_current_entry_point and self_serve and not self.is_trial: self.account.entry_point = EntryPoint.SELF_STARTED self.account.save() @classmethod def get_active_subscription_by_domain(cls, domain_name_or_obj): if settings.ENTERPRISE_MODE: return None if isinstance(domain_name_or_obj, Domain): return cls._get_active_subscription_by_domain(domain_name_or_obj.name) return cls._get_active_subscription_by_domain(domain_name_or_obj) @classmethod @quickcache(['domain_name'], timeout=60 * 60) def _get_active_subscription_by_domain(cls, domain_name): try: return cls.visible_objects.select_related( 'plan_version__role' ).get( is_active=True, subscriber__domain=domain_name, ) except cls.DoesNotExist: return None @classmethod def get_subscribed_plan_by_domain(cls, domain): domain_obj = ensure_domain_instance(domain) if domain_obj is None: try: return DefaultProductPlan.get_default_plan_version() except DefaultProductPlan.DoesNotExist: raise ProductPlanNotFoundError else: active_subscription = cls.get_active_subscription_by_domain(domain_obj.name) if active_subscription is not None: return active_subscription.plan_version else: return DefaultProductPlan.get_default_plan_version() @classmethod def new_domain_subscription(cls, account, domain, plan_version, date_start=None, date_end=None, note=None, web_user=None, adjustment_method=None, internal_change=False, **kwargs): if plan_version.plan.at_max_domains(): raise NewSubscriptionError( 'The maximum number of project spaces has been reached for %(plan_version)s. ' % { 'plan_version': plan_version, } ) if plan_version.plan.is_customer_software_plan != account.is_customer_billing_account: if plan_version.plan.is_customer_software_plan: raise NewSubscriptionError( 'You are trying to add a Customer Software Plan to a regular Billing Account. ' 'Both or neither must be customer-level.' ) else: raise NewSubscriptionError( 'You are trying to add a regular Software Plan to a Customer Billing Account. ' 'Both or neither must be customer-level.' ) subscriber = Subscriber.objects.get_or_create(domain=domain)[0] today = datetime.date.today() date_start = date_start or today available_subs = Subscription.visible_objects.filter( subscriber=subscriber, ) future_subscription_no_end = available_subs.filter( date_end__exact=None, ) if date_end is not None: future_subscription_no_end = future_subscription_no_end.filter(date_start__lt=date_end) if future_subscription_no_end.count() > 0: raise NewSubscriptionError(_( "There is already a subscription '%s' with no end date " "that conflicts with the start and end dates of this " "subscription.") % future_subscription_no_end.latest('date_created') ) future_subscriptions = available_subs.filter( date_end__gt=date_start ) if date_end is not None: future_subscriptions = future_subscriptions.filter(date_start__lt=date_end) if future_subscriptions.count() > 0: raise NewSubscriptionError(str( _( "There is already a subscription '%(sub)s' that has an end date " "that conflicts with the start and end dates of this " "subscription %(start)s - %(end)s." ) % { 'sub': future_subscriptions.latest('date_created'), 'start': date_start, 'end': date_end } )) can_reactivate, last_subscription = cls.can_reactivate_domain_subscription( account, domain, plan_version, date_start=date_start ) if can_reactivate: last_subscription.reactivate_subscription( date_end=date_end, note=note, web_user=web_user, adjustment_method=adjustment_method, **kwargs ) return last_subscription adjustment_method = adjustment_method or SubscriptionAdjustmentMethod.INTERNAL subscription = Subscription.visible_objects.create( account=account, plan_version=plan_version, subscriber=subscriber, date_start=date_start, date_end=date_end, **kwargs ) subscription.is_active = is_active_subscription(date_start, date_end) if subscription.is_active: subscriber.create_subscription( new_plan_version=plan_version, new_subscription=subscription, is_internal_change=internal_change, ) SubscriptionAdjustment.record_adjustment( subscription, method=adjustment_method, note=note, web_user=web_user ) subscription.save() subscription.set_billing_account_entry_point() return subscription @classmethod def can_reactivate_domain_subscription(cls, account, domain, plan_version, date_start=None): subscriber = Subscriber.objects.get_or_create(domain=domain)[0] date_start = date_start or datetime.date.today() last_subscription = Subscription.visible_objects.filter( subscriber=subscriber, date_end=date_start ) if not last_subscription.exists(): return False, None last_subscription = last_subscription.latest('date_created') return ( last_subscription.account.pk == account.pk and last_subscription.plan_version.pk == plan_version.pk ), last_subscription @property def is_below_minimum_subscription(self): if self.is_trial: return False elif self.date_start < datetime.date(2018, 9, 5): return False elif self.date_start + datetime.timedelta(days=MINIMUM_SUBSCRIPTION_LENGTH) >= datetime.date.today(): return True else: return False def user_can_change_subscription(self, user): if user.is_superuser: return True elif self.account.is_customer_billing_account: return self.account.has_enterprise_admin(user.email) else: return True class InvoiceBaseManager(models.Manager): def get_queryset(self): return super(InvoiceBaseManager, self).get_queryset().filter(is_hidden_to_ops=False) class InvoiceBase(models.Model): date_created = models.DateTimeField(auto_now_add=True) is_hidden = models.BooleanField(default=False) tax_rate = models.DecimalField(default=Decimal('0.0000'), max_digits=10, decimal_places=4) balance = models.DecimalField(default=Decimal('0.0000'), max_digits=10, decimal_places=4) date_due = models.DateField(db_index=True, null=True) date_paid = models.DateField(blank=True, null=True) date_start = models.DateField() date_end = models.DateField() is_hidden_to_ops = models.BooleanField(default=False) last_modified = models.DateTimeField(auto_now=True) objects = InvoiceBaseManager() api_objects = Manager() class Meta(object): abstract = True @property def is_customer_invoice(self): return False @property def invoice_number(self): ops_num = settings.INVOICE_STARTING_NUMBER + self.id return "%s%d" % (settings.INVOICE_PREFIX, ops_num) @property def is_wire(self): return False def get_domain(self): raise NotImplementedError() @property def account(self): raise NotImplementedError() @property def is_paid(self): return bool(self.date_paid) @property def email_recipients(self): raise NotImplementedError class WireInvoice(InvoiceBase): domain = models.CharField(max_length=100) class Meta(object): app_label = 'accounting' @property @memoized def account(self): return BillingAccount.get_account_by_domain(self.domain) @property def subtotal(self): return self.balance @property def is_wire(self): return True @property def is_prepayment(self): return False def get_domain(self): return self.domain def get_total(self): return self.balance @property def email_recipients(self): try: original_record = WireBillingRecord.objects.filter(invoice=self).order_by('-date_created')[0] return original_record.emailed_to_list except IndexError: log_accounting_error( "Strange that WireInvoice %d has no associated WireBillingRecord. " "Should investigate." % self.id ) return [] class WirePrepaymentInvoice(WireInvoice): class Meta(object): app_label = 'accounting' proxy = True items = [] @property def is_prepayment(self): return True class Invoice(InvoiceBase): subscription = models.ForeignKey(Subscription, on_delete=models.PROTECT) class Meta(object): app_label = 'accounting' def save(self, *args, **kwargs): from corehq.apps.accounting.mixins import get_overdue_invoice super(Invoice, self).save(*args, **kwargs) get_overdue_invoice.clear(self.subscription.subscriber.domain) @property def email_recipients(self): if self.subscription.service_type == SubscriptionType.IMPLEMENTATION: return [settings.ACCOUNTS_EMAIL] else: return self.contact_emails @property def contact_emails(self): try: billing_contact_info = BillingContactInfo.objects.get(account=self.account) contact_emails = billing_contact_info.email_list except BillingContactInfo.DoesNotExist: contact_emails = [] if not contact_emails: from corehq.apps.accounting.views import ManageBillingAccountView admins = WebUser.get_admins_by_domain(self.get_domain()) contact_emails = [admin.email if admin.email else admin.username for admin in admins] if not settings.UNIT_TESTING: _soft_assert_contact_emails_missing( False, "Could not find an email to send the invoice " "email to for the domain %s. Sending to domain admins instead: %s." " Add client contact emails here: %s" % ( self.get_domain(), ', '.join(contact_emails), absolute_reverse(ManageBillingAccountView.urlname, args=[self.account.id]), ) ) return contact_emails @property def subtotal(self): if self.lineitem_set.count() == 0: return Decimal('0.0000') return sum([line_item.total for line_item in self.lineitem_set.all()]) @property def applied_tax(self): return Decimal('%.4f' % round(self.tax_rate * self.subtotal, 4)) @property @memoized def account(self): return self.subscription.account @property def applied_credit(self): if self.creditadjustment_set.count() == 0: return Decimal('0.0000') return sum([credit.amount for credit in self.creditadjustment_set.all()]) def get_total(self): return self.subtotal + self.applied_tax + self.applied_credit def update_balance(self): self.balance = self.get_total() if self.balance <= 0: self.date_paid = datetime.date.today() else: self.date_paid = None def calculate_credit_adjustments(self): for line_item in self.lineitem_set.all(): line_item.calculate_credit_adjustments() current_total = self.get_total() credit_lines = CreditLine.get_credits_for_invoice(self) CreditLine.apply_credits_toward_balance(credit_lines, current_total, invoice=self) @classmethod def exists_for_domain(cls, domain): return cls.objects.filter( subscription__subscriber__domain=domain, is_hidden=False ).count() > 0 def get_domain(self): return self.subscription.subscriber.domain @classmethod def autopayable_invoices(cls, date_due): invoices = cls.objects.select_related('subscription__account').filter( date_due=date_due, is_hidden=False, subscription__account__auto_pay_user__isnull=False, ) return invoices def pay_invoice(self, payment_record): CreditLine.make_payment_towards_invoice( invoice=self, payment_record=payment_record, ) self.update_balance() self.save() class CustomerInvoice(InvoiceBase): account = models.ForeignKey(BillingAccount, on_delete=models.PROTECT) subscriptions = models.ManyToManyField(Subscription, default=list, blank=True) class Meta(object): app_label = 'accounting' @property def is_customer_invoice(self): return True def get_domain(self): return None @property def email_recipients(self): try: billing_contact_info = BillingContactInfo.objects.get(account=self.account) contact_emails = billing_contact_info.email_list except BillingContactInfo.DoesNotExist: contact_emails = [] return contact_emails @property def contact_emails(self): return self.account.enterprise_admin_emails @property def subtotal(self): if self.lineitem_set.count() == 0: return Decimal('0.0000') return sum([line_item.total for line_item in self.lineitem_set.all()]) @property def applied_tax(self): return Decimal('%.4f' % round(self.tax_rate * self.subtotal, 4)) @property def applied_credit(self): if self.creditadjustment_set.count() == 0: return Decimal('0.0000') return sum([credit.amount for credit in self.creditadjustment_set.all()]) def get_total(self): return self.subtotal + self.applied_tax + self.applied_credit def update_balance(self): self.balance = self.get_total() if self.balance <= 0: self.date_paid = datetime.date.today() else: self.date_paid = None def calculate_credit_adjustments(self): for line_item in self.lineitem_set.all(): line_item.calculate_credit_adjustments() current_total = self.get_total() credit_lines = CreditLine.get_credits_for_customer_invoice(self) CreditLine.apply_credits_toward_balance(credit_lines, current_total, customer_invoice=self) def pay_invoice(self, payment_record): CreditLine.make_payment_towards_invoice( invoice=self, payment_record=payment_record, ) self.update_balance() self.save() @classmethod def exists_for_domain(cls, domain): invoices = cls.objects.filter(is_hidden=False) for subscription in invoices.subscriptions.filter(is_hidden=False): if subscription.subscriber.domain == domain: return True return False @classmethod def autopayable_invoices(cls, date_due): invoices = cls.objects.select_related('account').filter( date_due=date_due, is_hidden=False, account__auto_pay_user__isnull=False ) return invoices class SubscriptionAdjustment(models.Model): subscription = models.ForeignKey(Subscription, on_delete=models.PROTECT) reason = models.CharField(max_length=50, default=SubscriptionAdjustmentReason.CREATE, choices=SubscriptionAdjustmentReason.CHOICES) method = models.CharField(max_length=50, default=SubscriptionAdjustmentMethod.INTERNAL, choices=SubscriptionAdjustmentMethod.CHOICES) note = models.TextField(null=True) web_user = models.CharField(max_length=80, null=True) invoice = models.ForeignKey(Invoice, on_delete=models.PROTECT, null=True) related_subscription = models.ForeignKey(Subscription, on_delete=models.PROTECT, null=True, related_name='subscriptionadjustment_related') date_created = models.DateTimeField(auto_now_add=True) new_date_start = models.DateField() new_date_end = models.DateField(blank=True, null=True) new_date_delay_invoicing = models.DateField(blank=True, null=True) new_salesforce_contract_id = models.CharField(blank=True, null=True, max_length=80) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' @classmethod def record_adjustment(cls, subscription, **kwargs): adjustment = SubscriptionAdjustment( subscription=subscription, new_date_start=subscription.date_start, new_date_end=subscription.date_end, new_salesforce_contract_id=subscription.salesforce_contract_id, **kwargs ) adjustment.save() return adjustment class BillingRecordBase(models.Model): date_created = models.DateTimeField(auto_now_add=True, db_index=True) emailed_to_list = ArrayField(models.EmailField(), default=list) skipped_email = models.BooleanField(default=False) pdf_data_id = models.CharField(max_length=48) last_modified = models.DateTimeField(auto_now=True) INVOICE_HTML_TEMPLATE = 'accounting/email/invoice.html' INVOICE_TEXT_TEMPLATE = 'accounting/email/invoice.txt' class Meta(object): abstract = True _pdf = None @property def pdf(self): if self._pdf is None: return InvoicePdf.get(self.pdf_data_id) return self._pdf @property def html_template(self): return self.INVOICE_HTML_TEMPLATE @property def text_template(self): return self.INVOICE_TEXT_TEMPLATE @property def should_send_email(self): raise NotImplementedError("should_send_email is required") @classmethod def generate_record(cls, invoice): record = cls(invoice=invoice) invoice_pdf = InvoicePdf() invoice_pdf.generate_pdf(record.invoice) record.pdf_data_id = invoice_pdf._id record._pdf = invoice_pdf record.save() return record def handle_throttled_email(self, contact_emails): self.skipped_email = True month_name = self.invoice.date_start.strftime("%B") self.save() log_accounting_info( "Throttled billing statements for domain %(domain)s " "to %(emails)s." % { 'domain': self.invoice.get_domain(), 'emails': ', '.join(contact_emails), } ) raise InvoiceEmailThrottledError( "Invoice communications exceeded the maximum limit of " "%(max_limit)d for domain %(domain)s for the month of " "%(month_name)s." % { 'max_limit': MAX_INVOICE_COMMUNICATIONS, 'domain': self.invoice.get_domain(), 'month_name': month_name, }) def email_context(self): from corehq.apps.domain.views.accounting import DomainBillingStatementsView from corehq.apps.domain.views.settings import DefaultProjectSettingsView month_name = self.invoice.date_start.strftime("%B") domain = self.invoice.get_domain() context = { 'month_name': month_name, 'domain': domain, 'domain_url': absolute_reverse(DefaultProjectSettingsView.urlname, args=[domain]), 'statement_number': self.invoice.invoice_number, 'payment_status': (_("Paid") if self.invoice.is_paid else _("Payment Required")), 'amount_due': fmt_dollar_amount(self.invoice.balance), 'statements_url': absolute_reverse( DomainBillingStatementsView.urlname, args=[domain]), 'invoicing_contact_email': settings.INVOICING_CONTACT_EMAIL, 'accounts_email': settings.ACCOUNTS_EMAIL, } return context def email_subject(self): raise NotImplementedError() def can_view_statement(self, web_user): raise NotImplementedError() def send_email(self, contact_email=None, cc_emails=None): pdf_attachment = { 'title': self.pdf.get_filename(self.invoice), 'file_obj': BytesIO(self.pdf.get_data(self.invoice)), 'mimetype': 'application/pdf', } domain = self.invoice.get_domain() subject = self.email_subject() context = self.email_context() email_from = self.email_from() greeting = _("Hello,") can_view_statement = False web_user = WebUser.get_by_username(contact_email) if web_user is not None: if web_user.first_name: greeting = _("Dear %s,") % web_user.first_name can_view_statement = self.can_view_statement(web_user) context['greeting'] = greeting context['can_view_statement'] = can_view_statement email_html = render_to_string(self.html_template, context) email_plaintext = render_to_string(self.text_template, context) send_html_email_async.delay( subject, contact_email, email_html, text_content=email_plaintext, email_from=email_from, file_attachments=[pdf_attachment], cc=cc_emails ) self.emailed_to_list.extend([contact_email]) if cc_emails: self.emailed_to_list.extend(cc_emails) self.save() if self.invoice.is_customer_invoice: log_message = "Sent billing statements for account %(account)s to %(emails)s." % { 'account': self.invoice.account, 'emails': contact_email, } else: log_message = "Sent billing statements for domain %(domain)s to %(emails)s." % { 'domain': domain, 'emails': contact_email, } log_accounting_info(log_message) class WireBillingRecord(BillingRecordBase): invoice = models.ForeignKey(WireInvoice, on_delete=models.PROTECT) INVOICE_HTML_TEMPLATE = 'accounting/email/wire_invoice.html' INVOICE_TEXT_TEMPLATE = 'accounting/email/wire_invoice.txt' class Meta(object): app_label = 'accounting' @property def should_send_email(self): hidden = self.invoice.is_hidden return not hidden @staticmethod def is_email_throttled(): return False def email_subject(self): month_name = self.invoice.date_start.strftime("%B") return "Your %(month)s Bulk Billing Statement for Project Space %(domain)s" % { 'month': month_name, 'domain': self.invoice.get_domain(), } @staticmethod def email_from(): return "Dimagi Accounting <{email}>".format(email=settings.INVOICING_CONTACT_EMAIL) def can_view_statement(self, web_user): return web_user.is_domain_admin(self.invoice.get_domain()) class WirePrepaymentBillingRecord(WireBillingRecord): class Meta(object): app_label = 'accounting' proxy = True def email_subject(self): return _("Your prepayment invoice") def can_view_statement(self, web_user): return web_user.is_domain_admin(self.invoice.get_domain()) class BillingRecord(BillingRecordBase): invoice = models.ForeignKey(Invoice, on_delete=models.PROTECT) INVOICE_CONTRACTED_HTML_TEMPLATE = 'accounting/email/invoice_contracted.html' INVOICE_CONTRACTED_TEXT_TEMPLATE = 'accounting/email/invoice_contracted.txt' INVOICE_AUTOPAY_HTML_TEMPLATE = 'accounting/email/invoice_autopayment.html' INVOICE_AUTOPAY_TEXT_TEMPLATE = 'accounting/email/invoice_autopayment.txt' class Meta(object): app_label = 'accounting' @property def html_template(self): if self.invoice.subscription.service_type == SubscriptionType.IMPLEMENTATION: return self.INVOICE_CONTRACTED_HTML_TEMPLATE if self.invoice.subscription.account.auto_pay_enabled: return self.INVOICE_AUTOPAY_HTML_TEMPLATE return self.INVOICE_HTML_TEMPLATE @property def text_template(self): if self.invoice.subscription.service_type == SubscriptionType.IMPLEMENTATION: return self.INVOICE_CONTRACTED_TEXT_TEMPLATE if self.invoice.subscription.account.auto_pay_enabled: return self.INVOICE_AUTOPAY_TEXT_TEMPLATE return self.INVOICE_TEXT_TEMPLATE @property def should_send_email(self): subscription = self.invoice.subscription autogenerate = (subscription.auto_generate_credits and not self.invoice.balance) small_contracted = (self.invoice.balance <= SMALL_INVOICE_THRESHOLD and subscription.service_type == SubscriptionType.IMPLEMENTATION) hidden = self.invoice.is_hidden do_not_email_invoice = self.invoice.subscription.do_not_email_invoice return not (autogenerate or small_contracted or hidden or do_not_email_invoice) def is_email_throttled(self): month = self.invoice.date_start.month year = self.invoice.date_start.year date_start, date_end = get_first_last_days(year, month) return self.__class__.objects.filter( invoice__date_start__lte=date_end, invoice__date_end__gte=date_start, invoice__subscription__subscriber=self.invoice.subscription.subscriber, invoice__is_hidden_to_ops=False, ).count() > MAX_INVOICE_COMMUNICATIONS def email_context(self): context = super(BillingRecord, self).email_context() total_balance = sum(invoice.balance for invoice in Invoice.objects.filter( is_hidden=False, subscription__subscriber__domain=self.invoice.get_domain(), )) is_small_invoice = self.invoice.balance < SMALL_INVOICE_THRESHOLD payment_status = (_("Paid") if self.invoice.is_paid or total_balance == 0 else _("Payment Required")) context.update({ 'plan_name': self.invoice.subscription.plan_version.plan.name, 'date_due': self.invoice.date_due, 'is_small_invoice': is_small_invoice, 'total_balance': total_balance, 'is_total_balance_due': total_balance >= SMALL_INVOICE_THRESHOLD, 'payment_status': payment_status, }) if self.invoice.subscription.service_type == SubscriptionType.IMPLEMENTATION: from corehq.apps.accounting.dispatcher import AccountingAdminInterfaceDispatcher context.update({ 'salesforce_contract_id': self.invoice.subscription.salesforce_contract_id, 'billing_account': self.invoice.subscription.account.name, 'billing_contacts': self.invoice.contact_emails, 'admin_invoices_url': "{url}?subscriber={domain}".format( url=absolute_reverse(AccountingAdminInterfaceDispatcher.name(), args=['invoices']), domain=self.invoice.get_domain() ) }) if self.invoice.subscription.account.auto_pay_enabled: try: last_4 = getattr(self.invoice.subscription.account.autopay_card, 'last4', None) except StripePaymentMethod.DoesNotExist: last_4 = None context.update({ 'auto_pay_user': self.invoice.subscription.account.auto_pay_user, 'last_4': last_4, }) context.update({ 'credits': self.credits, }) return context def credits(self): credits = { 'account': {}, 'subscription': {}, } self._add_product_credits(credits) self._add_user_credits(credits) self._add_sms_credits(credits) self._add_general_credits(credits) return credits def _add_product_credits(self, credits): credit_adjustments = CreditAdjustment.objects.filter( invoice=self.invoice, line_item__product_rate__isnull=False, ) subscription_credits = BillingRecord._get_total_balance( CreditLine.get_credits_by_subscription_and_features( self.invoice.subscription, is_product=True, ) ) if subscription_credits or credit_adjustments.filter( credit_line__subscription=self.invoice.subscription, ): credits['subscription'].update({ 'product': { 'amount': quantize_accounting_decimal(subscription_credits), } }) account_credits = BillingRecord._get_total_balance( CreditLine.get_credits_for_account( self.invoice.subscription.account, is_product=True, ) ) if account_credits or credit_adjustments.filter( credit_line__subscription=None, ): credits['account'].update({ 'product': { 'amount': quantize_accounting_decimal(account_credits), } }) return credits def _add_user_credits(self, credits): credit_adjustments = CreditAdjustment.objects.filter( invoice=self.invoice, line_item__feature_rate__feature__feature_type=FeatureType.USER, ) subscription_credits = BillingRecord._get_total_balance( CreditLine.get_credits_by_subscription_and_features( self.invoice.subscription, feature_type=FeatureType.USER, ) ) if subscription_credits or credit_adjustments.filter( credit_line__subscription=self.invoice.subscription, ): credits['subscription'].update({ 'user': { 'amount': quantize_accounting_decimal(subscription_credits), } }) account_credits = BillingRecord._get_total_balance( CreditLine.get_credits_for_account( self.invoice.subscription.account, feature_type=FeatureType.USER, ) ) if account_credits or credit_adjustments.filter( credit_line__subscription=None, ): credits['account'].update({ 'user': { 'amount': quantize_accounting_decimal(account_credits), } }) return credits def _add_sms_credits(self, credits): credit_adjustments = CreditAdjustment.objects.filter( invoice=self.invoice, line_item__feature_rate__feature__feature_type=FeatureType.SMS, ) subscription_credits = BillingRecord._get_total_balance( CreditLine.get_credits_by_subscription_and_features( self.invoice.subscription, feature_type=FeatureType.SMS, ) ) if subscription_credits or credit_adjustments.filter( credit_line__subscription=self.invoice.subscription, ): credits['subscription'].update({ 'sms': { 'amount': quantize_accounting_decimal(subscription_credits), } }) account_credits = BillingRecord._get_total_balance( CreditLine.get_credits_for_account( self.invoice.subscription.account, feature_type=FeatureType.SMS, ) ) if account_credits or credit_adjustments.filter( credit_line__subscription=None, ): credits['account'].update({ 'sms': { 'amount': quantize_accounting_decimal(account_credits), } }) return credits def _add_general_credits(self, credits): credit_adjustments = CreditAdjustment.objects.filter( invoice=self.invoice, line_item__feature_rate=None, line_item__product_rate=None, ) subscription_credits = BillingRecord._get_total_balance( CreditLine.get_credits_by_subscription_and_features( self.invoice.subscription, ) ) if subscription_credits or credit_adjustments.filter( credit_line__subscription=self.invoice.subscription, ): credits['subscription'].update({ 'general': { 'amount': quantize_accounting_decimal(subscription_credits), } }) account_credits = BillingRecord._get_total_balance( CreditLine.get_credits_for_account( self.invoice.subscription.account, ) ) if account_credits or credit_adjustments.filter( credit_line__subscription=None, ): credits['account'].update({ 'general': { 'amount': quantize_accounting_decimal(account_credits), } }) return credits def email_subject(self): month_name = self.invoice.date_start.strftime("%B") return "Your %(month)s CommCare Billing Statement for Project Space %(domain)s" % { 'month': month_name, 'domain': self.invoice.subscription.subscriber.domain, } def email_from(self): return get_dimagi_from_email() @staticmethod def _get_total_balance(credit_lines): return ( sum([credit_line.balance for credit_line in credit_lines]) if credit_lines else Decimal('0.0') ) def can_view_statement(self, web_user): return web_user.is_domain_admin(self.invoice.get_domain()) class CustomerBillingRecord(BillingRecordBase): invoice = models.ForeignKey(CustomerInvoice, on_delete=models.PROTECT) INVOICE_AUTOPAY_HTML_TEMPLATE = 'accounting/email/invoice_autopayment.html' INVOICE_AUTOPAY_TEXT_TEMPLATE = 'accounting/email/invoice_autopayment.txt' INVOICE_HTML_TEMPLATE = 'accounting/email/customer_invoice.html' INVOICE_TEXT_TEMPLATE = 'accounting/email/customer_invoice.txt' class Meta(object): app_label = 'accounting' @property def html_template(self): if self.invoice.account.auto_pay_enabled: return self.INVOICE_AUTOPAY_HTML_TEMPLATE return self.INVOICE_HTML_TEMPLATE @property def text_template(self): if self.invoice.account.auto_pay_enabled: return self.INVOICE_AUTOPAY_TEXT_TEMPLATE return self.INVOICE_TEXT_TEMPLATE @property def should_send_email(self): return not self.invoice.is_hidden def email_context(self): from corehq.apps.accounting.views import EnterpriseBillingStatementsView context = super(CustomerBillingRecord, self).email_context() is_small_invoice = self.invoice.balance < SMALL_INVOICE_THRESHOLD payment_status = (_("Paid") if self.invoice.is_paid or self.invoice.balance == 0 else _("Payment Required")) domain = self.invoice.subscriptions.first().subscriber.domain context.update({ 'account_name': self.invoice.account.name, 'date_due': self.invoice.date_due, 'is_small_invoice': is_small_invoice, 'total_balance': '{:.2f}'.format(self.invoice.balance), 'is_total_balance_due': self.invoice.balance >= SMALL_INVOICE_THRESHOLD, 'payment_status': payment_status, 'statements_url': absolute_reverse( EnterpriseBillingStatementsView.urlname, args=[domain]), }) if self.invoice.account.auto_pay_enabled: try: last_4 = getattr(self.invoice.account.autopay_card, 'last4', None) except StripePaymentMethod.DoesNotExist: last_4 = None context.update({ 'auto_pay_user': self.invoice.account.auto_pay_user, 'last_4': last_4, }) context.update({ 'credits': self.credits, }) return context def credits(self): credits = { 'account': {}, 'subscription': {}, } self._add_product_credits(credits) self._add_user_credits(credits) self._add_sms_credits(credits) self._add_general_credits(credits) return credits def _add_product_credits(self, credits): credit_adjustments = CreditAdjustment.objects.filter( customer_invoice=self.invoice, line_item__product_rate__isnull=False ) subscription_credits = CustomerBillingRecord._get_total_balance( CreditLine.get_credits_for_subscriptions( self.invoice.subscriptions, is_product=True ) ) if subscription_credits or self._subscriptions_in_credit_adjustments(credit_adjustments): credit_adjustments['subscription'].update({ 'product': { 'amount': quantize_accounting_decimal(subscription_credits) } }) account_credits = CustomerBillingRecord._get_total_balance( CreditLine.get_credits_for_account( self.invoice.account, is_product=True ) ) if account_credits or credit_adjustments.filter(credit_line__subscription=None): credits['account'].update({ 'product': { 'amount': quantize_accounting_decimal(account_credits) } }) return credits def _add_user_credits(self, credits): credit_adjustments = CreditAdjustment.objects.filter( customer_invoice=self.invoice, line_item__feature_rate__feature__feature_type=FeatureType.USER ) subscription_credits = CustomerBillingRecord._get_total_balance( CreditLine.get_credits_for_subscriptions( self.invoice.subscriptions, feature_type=FeatureType.USER ) ) if subscription_credits or self._subscriptions_in_credit_adjustments(credit_adjustments): credits['subscription'].update({ 'user': { 'amount': quantize_accounting_decimal(subscription_credits) } }) account_credits = CustomerBillingRecord._get_total_balance( CreditLine.get_credits_for_account( self.invoice.account, feature_type=FeatureType.USER ) ) if account_credits or credit_adjustments.filter(credit_line__subscription=None): credits['account'].update({ 'user': { 'amount': quantize_accounting_decimal(account_credits) } }) return credits def _add_sms_credits(self, credits): credit_adjustments = CreditAdjustment.objects.filter( customer_invoice=self.invoice, line_item__feature_rate__feature__feature_type=FeatureType.SMS ) subscription_credits = CustomerBillingRecord._get_total_balance( CreditLine.get_credits_for_subscriptions( self.invoice.subscriptions, feature_type=FeatureType.SMS ) ) if subscription_credits or self._subscriptions_in_credit_adjustments(credit_adjustments): credits['subscription'].update({ 'sms': { 'amount': quantize_accounting_decimal(subscription_credits) } }) account_credits = CustomerBillingRecord._get_total_balance( CreditLine.get_credits_for_account( self.invoice.account, feature_type=FeatureType.SMS ) ) if account_credits or credit_adjustments.filter(credit_line__subscription=None): credits['account'].update({ 'sms': { 'amount': quantize_accounting_decimal(account_credits) } }) return credits def _add_general_credits(self, credits): credit_adjustments = CreditAdjustment.objects.filter( customer_invoice=self.invoice, line_item__feature_rate=None, line_item__product_rate=None ) subscription_credits = CustomerBillingRecord._get_total_balance( CreditLine.get_credits_for_subscriptions( self.invoice.subscriptions ) ) if subscription_credits or self._subscriptions_in_credit_adjustments(credit_adjustments): credits['subscription'].update({ 'general': { 'amount': quantize_accounting_decimal(subscription_credits) } }) account_credits = CustomerBillingRecord._get_total_balance( CreditLine.get_credits_for_account( self.invoice.account ) ) if account_credits or credit_adjustments.filter(credit_line__subscription=None): credits['account'].update({ 'general': { 'amount': quantize_accounting_decimal(account_credits) } }) return credits def _subscriptions_in_credit_adjustments(self, credit_adjustments): for subscription in self.invoice.subscriptions.all(): if credit_adjustments.filter( credit_line__subscription=subscription ): return True return False def email_subject(self): month_name = self.invoice.date_start.strftime("%B") return "Your %(month)s CommCare Billing Statement for Customer Account %(account_name)s" % { 'month': month_name, 'account_name': self.invoice.account.name, } def email_from(self): return get_dimagi_from_email() @staticmethod def _get_total_balance(credit_lines): return ( sum([credit_line.balance for credit_line in credit_lines]) if credit_lines else Decimal('0.0') ) def can_view_statement(self, web_user): for subscription in self.invoice.subscriptions.all(): if web_user.is_domain_admin(subscription.subscriber.domain): return True return False class InvoicePdf(BlobMixin, SafeSaveDocument): invoice_id = StringProperty() date_created = DateTimeProperty() is_wire = BooleanProperty(default=False) is_customer = BooleanProperty(default=False) _blobdb_type_code = CODES.invoice def generate_pdf(self, invoice): self.save() domain = invoice.get_domain() pdf_data = NamedTemporaryFile() account_name = '' if invoice.is_customer_invoice: account_name = invoice.account.name template = InvoiceTemplate( pdf_data.name, invoice_number=invoice.invoice_number, to_address=get_address_from_invoice(invoice), project_name=domain, invoice_date=invoice.date_created.date(), due_date=invoice.date_due, date_start=invoice.date_start, date_end=invoice.date_end, subtotal=invoice.subtotal, tax_rate=invoice.tax_rate, applied_tax=getattr(invoice, 'applied_tax', Decimal('0.000')), applied_credit=getattr(invoice, 'applied_credit', Decimal('0.000')), total=invoice.get_total(), is_wire=invoice.is_wire, is_customer=invoice.is_customer_invoice, is_prepayment=invoice.is_wire and invoice.is_prepayment, account_name=account_name ) if not invoice.is_wire: if invoice.is_customer_invoice: line_items = LineItem.objects.filter(customer_invoice=invoice) else: line_items = LineItem.objects.filter(subscription_invoice=invoice) for line_item in line_items: is_unit = line_item.unit_description is not None is_quarterly = line_item.invoice.is_customer_invoice and \ line_item.invoice.account.invoicing_plan != InvoicingPlan.MONTHLY unit_cost = line_item.subtotal if is_unit: unit_cost = line_item.unit_cost if is_quarterly and line_item.base_description is not None: unit_cost = line_item.product_rate.monthly_fee description = line_item.base_description or line_item.unit_description if line_item.quantity > 0: template.add_item( description, line_item.quantity if is_unit or is_quarterly else 1, unit_cost, line_item.subtotal, line_item.applied_credit, line_item.total ) if invoice.is_wire and invoice.is_prepayment: unit_cost = 1 applied_credit = 0 for item in invoice.items: template.add_item(item['type'], item['amount'], unit_cost, item['amount'], applied_credit, item['amount']) template.get_pdf() filename = self.get_filename(invoice) blob_domain = domain or UNKNOWN_DOMAIN if not settings.UNIT_TESTING: self.put_attachment(pdf_data, filename, 'application/pdf', domain=blob_domain) else: self.put_attachment('', filename, 'application/pdf', domain=blob_domain) pdf_data.close() self.invoice_id = str(invoice.id) self.date_created = datetime.datetime.utcnow() self.is_wire = invoice.is_wire self.is_customer = invoice.is_customer_invoice self.save() @staticmethod def get_filename(invoice): return "statement_%(year)d_%(month)d.pdf" % { 'year': invoice.date_start.year, 'month': invoice.date_start.month, } def get_data(self, invoice): with self.fetch_attachment(self.get_filename(invoice), stream=True) as fh: return fh.read() class LineItemManager(models.Manager): def get_products(self): return self.get_queryset().filter(feature_rate__exact=None) def get_features(self): return self.get_queryset().filter(product_rate__exact=None) def get_feature_by_type(self, feature_type): return self.get_queryset().filter(feature_rate__feature__feature_type=feature_type) class LineItem(models.Model): subscription_invoice = models.ForeignKey(Invoice, on_delete=models.PROTECT, null=True) customer_invoice = models.ForeignKey(CustomerInvoice, on_delete=models.PROTECT, null=True) feature_rate = models.ForeignKey(FeatureRate, on_delete=models.PROTECT, null=True) product_rate = models.ForeignKey(SoftwareProductRate, on_delete=models.PROTECT, null=True) base_description = models.TextField(blank=True, null=True) base_cost = models.DecimalField(default=Decimal('0.0000'), max_digits=10, decimal_places=4) unit_description = models.TextField(blank=True, null=True) unit_cost = models.DecimalField(default=Decimal('0.0000'), max_digits=10, decimal_places=4) quantity = models.IntegerField(default=1, validators=integer_field_validators) last_modified = models.DateTimeField(auto_now=True) objects = LineItemManager() class Meta(object): app_label = 'accounting' @property def invoice(self): if self.subscription_invoice: return self.subscription_invoice else: return self.customer_invoice @invoice.setter def invoice(self, invoice): if invoice.is_customer_invoice: self.customer_invoice = invoice else: self.subscription_invoice = invoice @property def subtotal(self): if self.customer_invoice and self.customer_invoice.account.invoicing_plan != InvoicingPlan.MONTHLY: return self.base_cost * self.quantity + self.unit_cost * self.quantity return self.base_cost + self.unit_cost * self.quantity @property def applied_credit(self): if self.creditadjustment_set.count() == 0: return Decimal('0.0000') return sum([credit.amount for credit in self.creditadjustment_set.all()]) @property def total(self): return self.subtotal + self.applied_credit def calculate_credit_adjustments(self): current_total = self.total credit_lines = CreditLine.get_credits_for_line_item(self) CreditLine.apply_credits_toward_balance(credit_lines, current_total, line_item=self) class CreditLine(models.Model): account = models.ForeignKey(BillingAccount, on_delete=models.PROTECT) subscription = models.ForeignKey(Subscription, on_delete=models.PROTECT, null=True, blank=True) is_product = models.BooleanField(default=False) feature_type = models.CharField(max_length=10, null=True, blank=True, choices=FeatureType.CHOICES) date_created = models.DateTimeField(auto_now_add=True) balance = models.DecimalField(default=Decimal('0.0000'), max_digits=10, decimal_places=4) is_active = models.BooleanField(default=True) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' def __str__(self): credit_level = ("Account-Level" if self.subscription is None else "Subscription-Level") return ("%(level)s credit [Account %(account_id)d]%(feature)s" "%(product)s, balance %(balance)s" % { 'level': credit_level, 'account_id': self.account.id, 'feature': (' for Feature %s' % self.feature_type if self.feature_type is not None else ""), 'product': (' for Product' if self.is_product else ""), 'balance': self.balance, }) def save(self, *args, **kwargs): from corehq.apps.accounting.mixins import ( get_credits_available_for_product_in_account, get_credits_available_for_product_in_subscription, ) super(CreditLine, self).save(*args, **kwargs) if self.account: get_credits_available_for_product_in_account.clear(self.account) if self.subscription: get_credits_available_for_product_in_subscription.clear(self.subscription) def adjust_credit_balance(self, amount, is_new=False, note=None, line_item=None, invoice=None, customer_invoice=None, payment_record=None, related_credit=None, reason=None, web_user=None): note = note or "" if line_item is not None and (invoice is not None or customer_invoice is not None): raise CreditLineError("You may only have an invoice OR a line item making this adjustment.") if reason is None: reason = CreditAdjustmentReason.MANUAL if payment_record is not None: reason = CreditAdjustmentReason.DIRECT_PAYMENT elif related_credit is not None: reason = CreditAdjustmentReason.TRANSFER elif invoice is not None: reason = CreditAdjustmentReason.INVOICE elif customer_invoice is not None: reason = CreditAdjustmentReason.INVOICE elif line_item is not None: reason = CreditAdjustmentReason.LINE_ITEM if is_new: note = "Initialization of credit line. %s" % note credit_adjustment = CreditAdjustment( credit_line=self, note=note, amount=amount, reason=reason, payment_record=payment_record, line_item=line_item, invoice=invoice, customer_invoice=customer_invoice, related_credit=related_credit, web_user=web_user, ) credit_adjustment.save() self.balance = F('balance') + amount self.save() self.refresh_from_db() @classmethod def get_credits_for_line_item(cls, line_item): is_product = line_item.product_rate is not None feature_type = ( line_item.feature_rate.feature.feature_type if line_item.feature_rate is not None else None ) assert is_product or feature_type assert not (is_product and feature_type) if line_item.invoice.is_customer_invoice: return cls.get_credits_for_line_item_in_customer_invoice(line_item, feature_type, is_product) else: return cls.get_credits_for_line_item_in_invoice(line_item, feature_type, is_product) @classmethod def get_credits_for_line_item_in_invoice(cls, line_item, feature_type, is_product): if feature_type: return itertools.chain( cls.get_credits_by_subscription_and_features( line_item.invoice.subscription, feature_type=feature_type, ), cls.get_credits_for_account( line_item.invoice.subscription.account, feature_type=feature_type, ) ) if is_product: return itertools.chain( cls.get_credits_by_subscription_and_features( line_item.invoice.subscription, is_product=True, ), cls.get_credits_for_account( line_item.invoice.subscription.account, is_product=True, ) ) @classmethod def get_credits_for_line_item_in_customer_invoice(cls, line_item, feature_type, is_product): if feature_type: return itertools.chain( cls.get_credits_for_subscriptions( subscriptions=line_item.invoice.subscriptions.all(), feature_type=feature_type ), cls.get_credits_for_account( account=line_item.invoice.account, feature_type=feature_type ) ) if is_product: return itertools.chain( cls.get_credits_for_subscriptions( subscriptions=line_item.invoice.subscriptions.all(), is_product=is_product ), cls.get_credits_for_account( account=line_item.invoice.account, is_product=is_product ) ) @classmethod def get_credits_for_invoice(cls, invoice): relevant_credits = [ cls.get_credits_by_subscription_and_features(invoice.subscription), cls.get_credits_for_account(invoice.subscription.account) ] if invoice.subscription.next_subscription: active_sub = Subscription.get_active_subscription_by_domain( invoice.subscription.subscriber.domain ) if active_sub.account == invoice.subscription.account: relevant_credits.append( cls.get_credits_by_subscription_and_features(active_sub) ) elif (invoice.subscription.next_subscription.account == invoice.subscription.account): relevant_credits.append( cls.get_credits_by_subscription_and_features( invoice.subscription.next_subscription ) ) return itertools.chain(*relevant_credits) @classmethod def get_credits_for_customer_invoice(cls, invoice): return itertools.chain( cls.get_credits_for_subscriptions(invoice.subscriptions.all()), cls.get_credits_for_account(invoice.account) ) @classmethod def get_credits_for_subscriptions(cls, subscriptions, feature_type=None, is_product=False): credit_list = cls.objects.none() for subscription in subscriptions.all(): credit_list = credit_list.union(cls.get_credits_by_subscription_and_features( subscription, feature_type=feature_type, is_product=is_product )) return credit_list @classmethod def get_credits_for_account(cls, account, feature_type=None, is_product=False): assert not (feature_type and is_product) return cls.objects.filter( account=account, subscription__exact=None, is_active=True ).filter( is_product=is_product, feature_type__exact=feature_type ).all() @classmethod def get_credits_by_subscription_and_features(cls, subscription, feature_type=None, is_product=False): assert not (feature_type and is_product) return cls.objects.filter( subscription=subscription, feature_type__exact=feature_type, is_product=is_product, is_active=True ).all() @classmethod def get_non_general_credits_by_subscription(cls, subscription): return cls.objects.filter(subscription=subscription, is_active=True).filter( Q(is_product=True) | Q(feature_type__in=[f[0] for f in FeatureType.CHOICES]) ).all() @classmethod def add_credit(cls, amount, account=None, subscription=None, is_product=False, feature_type=None, payment_record=None, invoice=None, customer_invoice=None, line_item=None, related_credit=None, note=None, reason=None, web_user=None, permit_inactive=False): if account is None and subscription is None: raise CreditLineError( "You must specify either a subscription " "or account to add this credit to." ) if feature_type is not None and is_product: raise CreditLineError( "Can only add credit for a product OR a feature, but not both." ) account = account or subscription.account try: credit_line = cls.objects.get( account__exact=account, subscription__exact=subscription, is_product=is_product, feature_type__exact=feature_type, is_active=True ) if not permit_inactive and not credit_line.is_active and not invoice: raise CreditLineError( "Could not add credit to CreditLine %s because it is " "inactive." % str(credit_line) ) is_new = False except cls.MultipleObjectsReturned as e: raise CreditLineError( "Could not find a unique credit line for %(account)s" "%(subscription)s%(feature)s%(product)s. %(error)s" "instead." % { 'account': "Account ID %d" % account.id, 'subscription': (" | Subscription ID %d" % subscription.id if subscription is not None else ""), 'feature': (" | Feature %s" % feature_type if feature_type is not None else ""), 'product': (" | Product" if is_product else ""), 'error': str(e), } ) except cls.DoesNotExist: credit_line = cls.objects.create( account=account, subscription=subscription, is_product=is_product, feature_type=feature_type, ) is_new = True credit_line.adjust_credit_balance(amount, is_new=is_new, note=note, payment_record=payment_record, invoice=invoice, customer_invoice=customer_invoice, line_item=line_item, related_credit=related_credit, reason=reason, web_user=web_user) return credit_line @classmethod def apply_credits_toward_balance(cls, credit_lines, balance, **kwargs): for credit_line in credit_lines: if balance == Decimal('0.0000'): return if balance <= Decimal('0.0000'): raise CreditLineError( "A balance went below zero dollars when applying credits " "to credit line %d." % credit_line.pk ) adjustment_amount = min(credit_line.balance, balance) if adjustment_amount > Decimal('0.0000'): credit_line.adjust_credit_balance(-adjustment_amount, **kwargs) balance -= adjustment_amount @classmethod def make_payment_towards_invoice(cls, invoice, payment_record): if invoice.is_customer_invoice: billing_account = invoice.account else: billing_account = invoice.subscription.account cls.add_credit( payment_record.amount, account=billing_account, payment_record=payment_record, ) cls.add_credit( -payment_record.amount, account=billing_account, invoice=invoice, ) class PaymentMethod(models.Model): web_user = models.CharField(max_length=80, db_index=True) method_type = models.CharField(max_length=50, default=PaymentMethodType.STRIPE, choices=PaymentMethodType.CHOICES, db_index=True) customer_id = models.CharField(max_length=255, null=True, blank=True) date_created = models.DateTimeField(auto_now_add=True) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' unique_together = ('web_user', 'method_type') class StripePaymentMethod(PaymentMethod): class Meta(object): proxy = True app_label = 'accounting' STRIPE_GENERIC_ERROR = (stripe.error.AuthenticationError, stripe.error.InvalidRequestError, stripe.error.APIConnectionError, stripe.error.StripeError,) @property def customer(self): return self._get_or_create_stripe_customer() def _get_or_create_stripe_customer(self): customer = None if self.customer_id is not None: try: customer = self._get_stripe_customer() except stripe.InvalidRequestError: pass if customer is None: customer = self._create_stripe_customer() return customer def _create_stripe_customer(self): customer = stripe.Customer.create( description="{}'s cards".format(self.web_user), email=self.web_user, ) self.customer_id = customer.id self.save() return customer def _get_stripe_customer(self): return stripe.Customer.retrieve(self.customer_id) @property def all_cards(self): try: return [card for card in self.customer.cards.data if card is not None] except stripe.error.AuthenticationError: if not settings.STRIPE_PRIVATE_KEY: log_accounting_info("Private key is not defined in settings") return [] else: raise def all_cards_serialized(self, billing_account): return [{ 'brand': card.brand, 'last4': card.last4, 'exp_month': card.exp_month, 'exp_year': card.exp_year, 'token': card.id, 'is_autopay': self._is_autopay(card, billing_account), } for card in self.all_cards] def get_card(self, card_token): return self.customer.cards.retrieve(card_token) def get_autopay_card(self, billing_account): return next(( card for card in self.all_cards if self._is_autopay(card, billing_account) ), None) def remove_card(self, card_token): card = self.get_card(card_token) self._remove_card_from_all_accounts(card) card.delete() def _remove_card_from_all_accounts(self, card): accounts = BillingAccount.objects.filter(auto_pay_user=self.web_user) for account in accounts: if account.autopay_card == card: account.remove_autopay_user() def create_card(self, stripe_token, billing_account, domain, autopay=False): customer = self.customer card = customer.cards.create(card=stripe_token) self.set_default_card(card) if autopay: self.set_autopay(card, billing_account, domain) return card def set_default_card(self, card): self.customer.default_card = card self.customer.save() return card def set_autopay(self, card, billing_account, domain): if billing_account.auto_pay_enabled: self._remove_other_auto_pay_cards(billing_account) self._update_autopay_status(card, billing_account, autopay=True) billing_account.update_autopay_user(self.web_user, domain) def unset_autopay(self, card, billing_account): if self._is_autopay(card, billing_account): self._update_autopay_status(card, billing_account, autopay=False) billing_account.remove_autopay_user() def _update_autopay_status(self, card, billing_account, autopay): metadata = card.metadata.copy() metadata.update({self._auto_pay_card_metadata_key(billing_account): autopay}) card.metadata = metadata card.save() def _remove_autopay_card(self, billing_account): autopay_card = self.get_autopay_card(billing_account) if autopay_card is not None: self._update_autopay_status(autopay_card, billing_account, autopay=False) @staticmethod def _remove_other_auto_pay_cards(billing_account): user = billing_account.auto_pay_user try: other_payment_method = StripePaymentMethod.objects.get(web_user=user) other_payment_method._remove_autopay_card(billing_account) except StripePaymentMethod.DoesNotExist: pass @staticmethod def _is_autopay(card, billing_account): return card.metadata.get(StripePaymentMethod._auto_pay_card_metadata_key(billing_account)) == 'True' @staticmethod def _auto_pay_card_metadata_key(billing_account): return 'auto_pay_{billing_account_id}'.format(billing_account_id=billing_account.id) def create_charge(self, card, amount_in_dollars, description): amount_in_cents = int((amount_in_dollars * Decimal('100')).quantize(Decimal(10))) transaction_record = stripe.Charge.create( card=card, customer=self.customer, amount=amount_in_cents, currency=settings.DEFAULT_CURRENCY, description=description, ) return transaction_record.id class PaymentRecord(models.Model): payment_method = models.ForeignKey(PaymentMethod, on_delete=models.PROTECT, db_index=True) date_created = models.DateTimeField(auto_now_add=True) transaction_id = models.CharField(max_length=255, unique=True) amount = models.DecimalField(default=Decimal('0.0000'), max_digits=10, decimal_places=4) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' @property def public_transaction_id(self): ops_num = settings.INVOICE_STARTING_NUMBER + self.id return "%sP-%d" % (settings.INVOICE_PREFIX, ops_num) @classmethod def create_record(cls, payment_method, transaction_id, amount): return cls.objects.create( payment_method=payment_method, transaction_id=transaction_id, amount=amount, ) class CreditAdjustment(ValidateModelMixin, models.Model): credit_line = models.ForeignKey(CreditLine, on_delete=models.PROTECT) reason = models.CharField(max_length=25, default=CreditAdjustmentReason.MANUAL, choices=CreditAdjustmentReason.CHOICES) note = models.TextField(blank=True) amount = models.DecimalField(default=Decimal('0.0000'), max_digits=10, decimal_places=4) line_item = models.ForeignKey(LineItem, on_delete=models.PROTECT, null=True, blank=True) invoice = models.ForeignKey(Invoice, on_delete=models.PROTECT, null=True, blank=True) customer_invoice = models.ForeignKey(CustomerInvoice, on_delete=models.PROTECT, null=True, blank=True) payment_record = models.ForeignKey(PaymentRecord, on_delete=models.PROTECT, null=True, blank=True) related_credit = models.ForeignKey(CreditLine, on_delete=models.PROTECT, null=True, blank=True, related_name='creditadjustment_related') date_created = models.DateTimeField(auto_now_add=True) web_user = models.CharField(max_length=80, null=True, blank=True) last_modified = models.DateTimeField(auto_now=True) class Meta(object): app_label = 'accounting' def clean(self): if self.line_item and self.invoice: raise ValidationError(_("You can't specify both an invoice and a line item.")) class DomainUserHistory(models.Model): domain = models.CharField(max_length=256) record_date = models.DateField() num_users = models.IntegerField(default=0) class Meta: unique_together = ('domain', 'record_date')

true

1c45b1afd70b4b9e6a45db74c842c66174c7a49a

2,103

py

Python

guild/main_bootstrap.py

wheatdog/guildai

817cf179d0b6910d3d4fca522045a8139aef6c9e

[ "Apache-2.0" ]

null

guild/main_bootstrap.py

wheatdog/guildai

817cf179d0b6910d3d4fca522045a8139aef6c9e

[ "Apache-2.0" ]

null

guild/main_bootstrap.py

wheatdog/guildai

817cf179d0b6910d3d4fca522045a8139aef6c9e

[ "Apache-2.0" ]

null

# Copyright 2017-2020 TensorHub, Inc. # # 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. """Bootstraps env for guild.main. The primary bootstrap task is to configure sys.path with the location of Guild's external dependencies. This module supports two modes: distribution and dev. External dependencies in distribution mode are assumed to be located in a single `GUILD_PKG_HOME/external` directory where `GUILD_PKG_HOME` is the `guild` directory within the Guild distribution location. As the bootstrap process is used for every Guild command, it must execute as quickly as possible. """ from __future__ import absolute_import from __future__ import division import os import sys def main(): ensure_external_path() import guild.main guild.main.main() def ensure_external_path(): path = _external_libs_path() if path not in sys.path: sys.path.insert(0, path) def _external_libs_path(): guild_pkg_dir = os.path.dirname(__file__) path = os.path.abspath(os.path.join(guild_pkg_dir, "external")) if not os.path.exists(path): import textwrap sys.stderr.write("guild: {} does not exist\n".format(path)) sys.stderr.write( textwrap.fill( "If you're a Guild developer, run 'python setup.py build' " "in the Guild project directory and try again. Otherwise " "please report this as a bug at " "https://github.com/guildai/guildai/issues." ) ) sys.stderr.write("\n") sys.exit(1) return path if __name__ == "__main__": main()

29.619718

75

0.701854

from __future__ import absolute_import from __future__ import division import os import sys def main(): ensure_external_path() import guild.main guild.main.main() def ensure_external_path(): path = _external_libs_path() if path not in sys.path: sys.path.insert(0, path) def _external_libs_path(): guild_pkg_dir = os.path.dirname(__file__) path = os.path.abspath(os.path.join(guild_pkg_dir, "external")) if not os.path.exists(path): import textwrap sys.stderr.write("guild: {} does not exist\n".format(path)) sys.stderr.write( textwrap.fill( "If you're a Guild developer, run 'python setup.py build' " "in the Guild project directory and try again. Otherwise " "please report this as a bug at " "https://github.com/guildai/guildai/issues." ) ) sys.stderr.write("\n") sys.exit(1) return path if __name__ == "__main__": main()

true

1c45b1e58aee7713ff142e357f97c11aaa11ed05

1,246

py

Python

discord/utils.py

rf20008/nextcord

48ae815f226e9f7f2f4076c68b6589563144d67b

[ "MIT" ]

null

discord/utils.py

rf20008/nextcord

48ae815f226e9f7f2f4076c68b6589563144d67b

[ "MIT" ]

null

discord/utils.py

rf20008/nextcord

48ae815f226e9f7f2f4076c68b6589563144d67b

[ "MIT" ]

null

""" The MIT License (MIT) Copyright (c) 2021-present tag-epic Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. Module to allow for backwards compatibility for existing code and extensions """ from nextcord.utils import * from nextcord.utils import MISSING, DISCORD_EPOCH

47.923077

76

0.804173

from nextcord.utils import * from nextcord.utils import MISSING, DISCORD_EPOCH

true

1c45b20896b287eedc789388d42830cf74be6fa6

25,192

py

Python

trac/admin/web_ui.py

mikiec84/trac

d51a7119b9fcb9061d7fe135c7d648fa671555dd

[ "BSD-3-Clause" ]

null

trac/admin/web_ui.py

mikiec84/trac

d51a7119b9fcb9061d7fe135c7d648fa671555dd

[ "BSD-3-Clause" ]

null

trac/admin/web_ui.py

mikiec84/trac

d51a7119b9fcb9061d7fe135c7d648fa671555dd

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- # # Copyright (C) 2005-2020 Edgewall Software # Copyright (C) 2005 Jonas Borgström <jonas@edgewall.com> # All rights reserved. # # This software is licensed as described in the file COPYING, which # you should have received as part of this distribution. The terms # are also available at https://trac.edgewall.org/wiki/TracLicense. # # This software consists of voluntary contributions made by many # individuals. For the exact contribution history, see the revision # history and logs, available at https://trac.edgewall.org/. # # Author: Jonas Borgström <jonas@edgewall.com> import os import pkg_resources import re import shutil from functools import partial from trac import log from trac.admin.api import IAdminPanelProvider from trac.core import * from trac.loader import get_plugin_info from trac.log import LOG_LEVELS, LOG_LEVEL_ALIASES, LOG_LEVEL_ALIASES_MAP from trac.perm import IPermissionRequestor, PermissionExistsError, \ PermissionSystem from trac.util.datefmt import all_timezones, pytz from trac.util.html import tag from trac.util.text import exception_to_unicode, unicode_from_base64, \ unicode_to_base64 from trac.util.translation import _, Locale, get_available_locales, \ ngettext, tag_ from trac.web.api import HTTPNotFound, IRequestHandler, \ is_valid_default_handler from trac.web.chrome import Chrome, INavigationContributor, \ ITemplateProvider, add_notice, add_stylesheet, \ add_warning from trac.wiki.formatter import format_to_html _valid_log_levels = set() _valid_log_levels.update(log.LOG_LEVELS) _valid_log_levels.update(log.LOG_LEVEL_ALIASES) class AdminModule(Component): """Web administration interface provider and panel manager.""" implements(INavigationContributor, IRequestHandler, ITemplateProvider) panel_providers = ExtensionPoint(IAdminPanelProvider) # INavigationContributor methods def get_active_navigation_item(self, req): return 'admin' def get_navigation_items(self, req): # The 'Admin' navigation item is only visible if at least one # admin panel is available panels, providers = self._get_panels(req) if panels: yield 'mainnav', 'admin', tag.a(_("Admin"), href=req.href.admin()) # IRequestHandler methods def match_request(self, req): match = re.match('/admin(?:/([^/]+)(?:/([^/]+)(?:/(.+))?)?)?$', req.path_info) if match: req.args['cat_id'] = match.group(1) req.args['panel_id'] = match.group(2) req.args['path_info'] = match.group(3) return True def process_request(self, req): panels, providers = self._get_panels(req) if not panels: raise HTTPNotFound(_("No administration panels available")) def _panel_order(panel): items = panel[::2] return items[0] != 'general', items != ('general', 'basics'), items panels.sort(key=_panel_order) cat_id = req.args.get('cat_id') or panels[0][0] panel_id = req.args.get('panel_id') path_info = req.args.get('path_info') if not panel_id: try: panel_id = \ filter(lambda panel: panel[0] == cat_id, panels)[0][2] except IndexError: raise HTTPNotFound(_("Unknown administration panel")) provider = providers.get((cat_id, panel_id)) if not provider: raise HTTPNotFound(_("Unknown administration panel")) resp = provider.render_admin_panel(req, cat_id, panel_id, path_info) template, data = resp[:2] data.update({ 'active_cat': cat_id, 'active_panel': panel_id, 'panel_href': partial(req.href, 'admin', cat_id, panel_id), 'panels': [{ 'category': {'id': panel[0], 'label': panel[1]}, 'panel': {'id': panel[2], 'label': panel[3]} } for panel in panels] }) add_stylesheet(req, 'common/css/admin.css') return resp # ITemplateProvider methods def get_htdocs_dirs(self): return [] def get_templates_dirs(self): return [pkg_resources.resource_filename('trac.admin', 'templates')] # Internal methods def _get_panels(self, req): """Return a list of available admin panels.""" panels = [] providers = {} for provider in self.panel_providers: p = list(provider.get_admin_panels(req) or []) for panel in p: providers[(panel[0], panel[2])] = provider panels += p return panels, providers def _save_config(config, req, log, notices=None): """Try to save the config, and display either a success notice or a failure warning. """ try: config.save() if notices is None: notices = [_("Your changes have been saved.")] for notice in notices: add_notice(req, notice) except Exception as e: log.error("Error writing to trac.ini: %s", exception_to_unicode(e)) add_warning(req, _("Error writing to trac.ini, make sure it is " "writable by the web server. Your changes have " "not been saved.")) class BasicsAdminPanel(Component): implements(IAdminPanelProvider) request_handlers = ExtensionPoint(IRequestHandler) # IAdminPanelProvider methods def get_admin_panels(self, req): if 'TRAC_ADMIN' in req.perm('admin', 'general/basics'): yield ('general', _("General"), 'basics', _("Basic Settings")) def render_admin_panel(self, req, cat, page, path_info): valid_default_handlers = [handler.__class__.__name__ for handler in self.request_handlers if is_valid_default_handler(handler)] if Locale: locale_ids = get_available_locales() locales = [Locale.parse(locale) for locale in locale_ids] # don't use str(locale) to prevent storing expanded locale # identifier, see #11258 languages = sorted((id, locale.display_name) for id, locale in zip(locale_ids, locales)) else: locale_ids, locales, languages = [], [], [] if req.method == 'POST': for option in ('name', 'url', 'descr'): self.config.set('project', option, req.args.get(option)) default_handler = req.args.get('default_handler') self.config.set('trac', 'default_handler', default_handler) default_timezone = req.args.get('default_timezone') if default_timezone not in all_timezones: default_timezone = '' self.config.set('trac', 'default_timezone', default_timezone) default_language = req.args.get('default_language') if default_language not in locale_ids: default_language = '' self.config.set('trac', 'default_language', default_language) default_date_format = req.args.get('default_date_format') if default_date_format != 'iso8601': default_date_format = '' self.config.set('trac', 'default_date_format', default_date_format) default_dateinfo_format = req.args.get('default_dateinfo_format') if default_dateinfo_format not in ('relative', 'absolute'): default_dateinfo_format = 'relative' self.config.set('trac', 'default_dateinfo_format', default_dateinfo_format) _save_config(self.config, req, self.log) req.redirect(req.href.admin(cat, page)) default_handler = self.config.get('trac', 'default_handler') default_timezone = self.config.get('trac', 'default_timezone') default_language = self.config.get('trac', 'default_language') default_date_format = self.config.get('trac', 'default_date_format') default_dateinfo_format = self.config.get('trac', 'default_dateinfo_format') data = { 'default_handler': default_handler, 'valid_default_handlers': sorted(valid_default_handlers), 'default_timezone': default_timezone, 'timezones': all_timezones, 'has_pytz': pytz is not None, 'default_language': default_language.replace('-', '_'), 'languages': languages, 'default_date_format': default_date_format, 'default_dateinfo_format': default_dateinfo_format, 'has_babel': Locale is not None, } Chrome(self.env).add_textarea_grips(req) return 'admin_basics.html', data class LoggingAdminPanel(Component): implements(IAdminPanelProvider) # IAdminPanelProvider methods def get_admin_panels(self, req): if 'TRAC_ADMIN' in req.perm('admin', 'general/logging'): yield ('general', _("General"), 'logging', _("Logging")) def render_admin_panel(self, req, cat, page, path_info): log_type = self.env.log_type log_level = self.env.log_level log_file = self.env.log_file log_dir = self.env.log_dir log_types = [ dict(name='none', label=_("None"), selected=log_type == 'none', disabled=False), dict(name='stderr', label=_("Console"), selected=log_type == 'stderr', disabled=False), dict(name='file', label=_("File"), selected=log_type == 'file', disabled=False), dict(name='syslog', label=_("Syslog"), selected=log_type in ('unix', 'syslog'), disabled=os.name != 'posix'), dict(name='eventlog', label=_("Windows event log"), selected=log_type in ('winlog', 'eventlog', 'nteventlog'), disabled=os.name != 'nt'), ] if req.method == 'POST': changed = False new_type = req.args.get('log_type') if new_type not in [t['name'] for t in log_types]: raise TracError( _("Unknown log type %(type)s", type=new_type), _("Invalid log type") ) new_file = req.args.get('log_file', log_file) if not new_file: raise TracError(_("You must specify a log file"), _("Missing field")) new_level = req.args.get('log_level', log_level) if new_level not in _valid_log_levels: raise TracError( _("Unknown log level %(level)s", level=new_level), _("Invalid log level")) # Create logger to be sure the configuration is valid. new_file_path = new_file if not os.path.isabs(new_file_path): new_file_path = os.path.join(self.env.log_dir, new_file) try: logger, handler = \ self.env.create_logger(new_type, new_file_path, new_level, self.env.log_format) except Exception as e: add_warning(req, tag_("Changes not saved. Logger configuration " "error: %(error)s. Inspect the log for more " "information.", error=tag.code(exception_to_unicode(e)))) self.log.error("Logger configuration error: %s", exception_to_unicode(e, traceback=True)) else: handler.close() if new_type != log_type: self.config.set('logging', 'log_type', new_type) changed = True log_type = new_type if new_level != log_level: self.config.set('logging', 'log_level', new_level) changed = True log_level = new_level if new_file != log_file: self.config.set('logging', 'log_file', new_file) changed = True log_file = new_file if changed: _save_config(self.config, req, self.log), req.redirect(req.href.admin(cat, page)) # Order log levels by priority value, with aliases excluded. all_levels = sorted(log.LOG_LEVEL_MAP, key=log.LOG_LEVEL_MAP.get, reverse=True) log_levels = [level for level in all_levels if level in log.LOG_LEVELS] log_level = LOG_LEVEL_ALIASES_MAP.get(log_level, log_level) data = { 'type': log_type, 'types': log_types, 'level': log_level, 'levels': log_levels, 'file': log_file, 'dir': log_dir } return 'admin_logging.html', {'log': data} class PermissionAdminPanel(Component): implements(IAdminPanelProvider, IPermissionRequestor) # IPermissionRequestor methods def get_permission_actions(self): actions = ['PERMISSION_GRANT', 'PERMISSION_REVOKE'] return actions + [('PERMISSION_ADMIN', actions)] # IAdminPanelProvider methods def get_admin_panels(self, req): perm = req.perm('admin', 'general/perm') if 'PERMISSION_GRANT' in perm or 'PERMISSION_REVOKE' in perm: yield ('general', _("General"), 'perm', _("Permissions")) def render_admin_panel(self, req, cat, page, path_info): perm = PermissionSystem(self.env) all_actions = perm.get_actions() if req.method == 'POST': subject = req.args.get('subject', '').strip() target = req.args.get('target', '').strip() action = req.args.get('action') group = req.args.get('group', '').strip() if subject and subject.isupper() or \ group and group.isupper() or \ target and target.isupper(): raise TracError(_("All upper-cased tokens are reserved for " "permission names.")) # Grant permission to subject if 'add' in req.args and subject and action: req.perm('admin', 'general/perm').require('PERMISSION_GRANT') if action not in all_actions: raise TracError(_("Unknown action")) req.perm.require(action) try: perm.grant_permission(subject, action) except TracError as e: add_warning(req, e) else: add_notice(req, _("The subject %(subject)s has been " "granted the permission %(action)s.", subject=subject, action=action)) # Add subject to group elif 'add' in req.args and subject and group: req.perm('admin', 'general/perm').require('PERMISSION_GRANT') for action in sorted( perm.get_user_permissions(group, expand_meta=False)): req.perm.require(action, message=tag_( "The subject %(subject)s was not added to the " "group %(group)s. The group has %(perm)s " "permission and you cannot grant permissions you " "don't possess.", subject=tag.strong(subject), group=tag.strong(group), perm=tag.strong(action))) try: perm.grant_permission(subject, group) except TracError as e: add_warning(req, e) else: add_notice(req, _("The subject %(subject)s has been " "added to the group %(group)s.", subject=subject, group=group)) # Copy permissions to subject elif 'copy' in req.args and subject and target: req.perm('admin', 'general/perm').require('PERMISSION_GRANT') subject_permissions = perm.get_users_dict().get(subject, []) if not subject_permissions: add_warning(req, _("The subject %(subject)s does not " "have any permissions.", subject=subject)) for action in subject_permissions: if action not in all_actions: # plugin disabled? self.log.warning("Skipped granting %s to %s: " "permission unavailable.", action, target) else: if action not in req.perm: add_warning(req, _("The permission %(action)s was " "not granted to %(subject)s " "because users cannot grant " "permissions they don't possess.", action=action, subject=subject)) continue try: perm.grant_permission(target, action) except PermissionExistsError: pass else: add_notice(req, _("The subject %(subject)s has " "been granted the permission " "%(action)s.", subject=target, action=action)) req.redirect(req.href.admin(cat, page)) # Remove permissions action elif 'remove' in req.args and 'sel' in req.args: req.perm('admin', 'general/perm').require('PERMISSION_REVOKE') for key in req.args.getlist('sel'): subject, action = key.split(':', 1) subject = unicode_from_base64(subject) action = unicode_from_base64(action) if (subject, action) in perm.get_all_permissions(): perm.revoke_permission(subject, action) add_notice(req, _("The selected permissions have been " "revoked.")) req.redirect(req.href.admin(cat, page)) return 'admin_perms.html', { 'actions': all_actions, 'allowed_actions': [a for a in all_actions if a in req.perm], 'perms': perm.get_users_dict(), 'groups': perm.get_groups_dict(), 'unicode_to_base64': unicode_to_base64 } class PluginAdminPanel(Component): implements(IAdminPanelProvider) # IAdminPanelProvider methods def get_admin_panels(self, req): if 'TRAC_ADMIN' in req.perm('admin', 'general/plugin'): yield ('general', _("General"), 'plugin', _("Plugins")) def render_admin_panel(self, req, cat, page, path_info): if req.method == 'POST': if 'install' in req.args: self._do_install(req) elif 'uninstall' in req.args: self._do_uninstall(req) else: self._do_update(req) anchor = '' if 'plugin' in req.args: anchor = '#no%d' % (req.args.getint('plugin') + 1) req.redirect(req.href.admin(cat, page) + anchor) return self._render_view(req) # Internal methods def _do_install(self, req): """Install a plugin.""" if 'plugin_file' not in req.args: raise TracError(_("No file uploaded")) upload = req.args['plugin_file'] if isinstance(upload, unicode) or not upload.filename: raise TracError(_("No file uploaded")) plugin_filename = upload.filename.replace('\\', '/').replace(':', '/') plugin_filename = os.path.basename(plugin_filename) if not plugin_filename: raise TracError(_("No file uploaded")) if not plugin_filename.endswith('.egg') and \ not plugin_filename.endswith('.py'): raise TracError(_("Uploaded file is not a Python source file or " "egg")) target_path = os.path.join(self.env.plugins_dir, plugin_filename) if os.path.isfile(target_path): raise TracError(_("Plugin %(name)s already installed", name=plugin_filename)) self.log.info("Installing plugin %s", plugin_filename) flags = os.O_CREAT + os.O_WRONLY + os.O_EXCL try: flags += os.O_BINARY except AttributeError: # OS_BINARY not available on every platform pass with os.fdopen(os.open(target_path, flags, 0o666), 'w') as target_file: shutil.copyfileobj(upload.file, target_file) self.log.info("Plugin %s installed to %s", plugin_filename, target_path) # TODO: Validate that the uploaded file is a valid Trac plugin # Make the environment reset itself on the next request self.env.config.touch() def _do_uninstall(self, req): """Uninstall a plugin.""" plugin_filename = req.args.get('plugin_filename') if not plugin_filename: return plugin_path = os.path.join(self.env.plugins_dir, plugin_filename) if not os.path.isfile(plugin_path): return self.log.info("Uninstalling plugin %s", plugin_filename) os.remove(plugin_path) # Make the environment reset itself on the next request self.env.config.touch() def _do_update(self, req): """Update component enable state.""" components = req.args.getlist('component') enabled = req.args.getlist('enable') added, removed = [], [] # FIXME: this needs to be more intelligent and minimize multiple # component names to prefix rules for component in components: is_enabled = bool(self.env.is_component_enabled(component)) must_enable = component in enabled if is_enabled != must_enable: self.config.set('components', component, 'disabled' if is_enabled else 'enabled') self.log.info("%sabling component %s", "Dis" if is_enabled else "En", component) if must_enable: added.append(component) else: removed.append(component) if added or removed: def make_list(items): parts = [item.rsplit('.', 1) for item in items] return tag.table(tag.tbody( tag.tr(tag.td(c, class_='trac-name'), tag.td('(%s.*)' % m, class_='trac-name')) for m, c in parts), class_='trac-pluglist') added.sort() removed.sort() notices = [] if removed: msg = ngettext("The following component has been disabled:", "The following components have been disabled:", len(removed)) notices.append(tag(msg, make_list(removed))) if added: msg = ngettext("The following component has been enabled:", "The following components have been enabled:", len(added)) notices.append(tag(msg, make_list(added))) # set the default value of options for only the enabled components for component in added: self.config.set_defaults(component=component) _save_config(self.config, req, self.log, notices) def _render_view(self, req): plugins = get_plugin_info(self.env, include_core=True) def safe_wiki_to_html(context, text): try: return format_to_html(self.env, context, text) except Exception as e: self.log.error("Unable to render component documentation: %s", exception_to_unicode(e, traceback=True)) return tag.pre(text) data = { 'plugins': plugins, 'show': req.args.get('show'), 'readonly': not os.access(self.env.plugins_dir, os.F_OK + os.W_OK), 'safe_wiki_to_html': safe_wiki_to_html, } return 'admin_plugins.html', data

41.230769

79

0.551286

import os import pkg_resources import re import shutil from functools import partial from trac import log from trac.admin.api import IAdminPanelProvider from trac.core import * from trac.loader import get_plugin_info from trac.log import LOG_LEVELS, LOG_LEVEL_ALIASES, LOG_LEVEL_ALIASES_MAP from trac.perm import IPermissionRequestor, PermissionExistsError, \ PermissionSystem from trac.util.datefmt import all_timezones, pytz from trac.util.html import tag from trac.util.text import exception_to_unicode, unicode_from_base64, \ unicode_to_base64 from trac.util.translation import _, Locale, get_available_locales, \ ngettext, tag_ from trac.web.api import HTTPNotFound, IRequestHandler, \ is_valid_default_handler from trac.web.chrome import Chrome, INavigationContributor, \ ITemplateProvider, add_notice, add_stylesheet, \ add_warning from trac.wiki.formatter import format_to_html _valid_log_levels = set() _valid_log_levels.update(log.LOG_LEVELS) _valid_log_levels.update(log.LOG_LEVEL_ALIASES) class AdminModule(Component): implements(INavigationContributor, IRequestHandler, ITemplateProvider) panel_providers = ExtensionPoint(IAdminPanelProvider) def get_active_navigation_item(self, req): return 'admin' def get_navigation_items(self, req): panels, providers = self._get_panels(req) if panels: yield 'mainnav', 'admin', tag.a(_("Admin"), href=req.href.admin()) def match_request(self, req): match = re.match('/admin(?:/([^/]+)(?:/([^/]+)(?:/(.+))?)?)?$', req.path_info) if match: req.args['cat_id'] = match.group(1) req.args['panel_id'] = match.group(2) req.args['path_info'] = match.group(3) return True def process_request(self, req): panels, providers = self._get_panels(req) if not panels: raise HTTPNotFound(_("No administration panels available")) def _panel_order(panel): items = panel[::2] return items[0] != 'general', items != ('general', 'basics'), items panels.sort(key=_panel_order) cat_id = req.args.get('cat_id') or panels[0][0] panel_id = req.args.get('panel_id') path_info = req.args.get('path_info') if not panel_id: try: panel_id = \ filter(lambda panel: panel[0] == cat_id, panels)[0][2] except IndexError: raise HTTPNotFound(_("Unknown administration panel")) provider = providers.get((cat_id, panel_id)) if not provider: raise HTTPNotFound(_("Unknown administration panel")) resp = provider.render_admin_panel(req, cat_id, panel_id, path_info) template, data = resp[:2] data.update({ 'active_cat': cat_id, 'active_panel': panel_id, 'panel_href': partial(req.href, 'admin', cat_id, panel_id), 'panels': [{ 'category': {'id': panel[0], 'label': panel[1]}, 'panel': {'id': panel[2], 'label': panel[3]} } for panel in panels] }) add_stylesheet(req, 'common/css/admin.css') return resp def get_htdocs_dirs(self): return [] def get_templates_dirs(self): return [pkg_resources.resource_filename('trac.admin', 'templates')] def _get_panels(self, req): panels = [] providers = {} for provider in self.panel_providers: p = list(provider.get_admin_panels(req) or []) for panel in p: providers[(panel[0], panel[2])] = provider panels += p return panels, providers def _save_config(config, req, log, notices=None): try: config.save() if notices is None: notices = [_("Your changes have been saved.")] for notice in notices: add_notice(req, notice) except Exception as e: log.error("Error writing to trac.ini: %s", exception_to_unicode(e)) add_warning(req, _("Error writing to trac.ini, make sure it is " "writable by the web server. Your changes have " "not been saved.")) class BasicsAdminPanel(Component): implements(IAdminPanelProvider) request_handlers = ExtensionPoint(IRequestHandler) def get_admin_panels(self, req): if 'TRAC_ADMIN' in req.perm('admin', 'general/basics'): yield ('general', _("General"), 'basics', _("Basic Settings")) def render_admin_panel(self, req, cat, page, path_info): valid_default_handlers = [handler.__class__.__name__ for handler in self.request_handlers if is_valid_default_handler(handler)] if Locale: locale_ids = get_available_locales() locales = [Locale.parse(locale) for locale in locale_ids] # identifier, see #11258 languages = sorted((id, locale.display_name) for id, locale in zip(locale_ids, locales)) else: locale_ids, locales, languages = [], [], [] if req.method == 'POST': for option in ('name', 'url', 'descr'): self.config.set('project', option, req.args.get(option)) default_handler = req.args.get('default_handler') self.config.set('trac', 'default_handler', default_handler) default_timezone = req.args.get('default_timezone') if default_timezone not in all_timezones: default_timezone = '' self.config.set('trac', 'default_timezone', default_timezone) default_language = req.args.get('default_language') if default_language not in locale_ids: default_language = '' self.config.set('trac', 'default_language', default_language) default_date_format = req.args.get('default_date_format') if default_date_format != 'iso8601': default_date_format = '' self.config.set('trac', 'default_date_format', default_date_format) default_dateinfo_format = req.args.get('default_dateinfo_format') if default_dateinfo_format not in ('relative', 'absolute'): default_dateinfo_format = 'relative' self.config.set('trac', 'default_dateinfo_format', default_dateinfo_format) _save_config(self.config, req, self.log) req.redirect(req.href.admin(cat, page)) default_handler = self.config.get('trac', 'default_handler') default_timezone = self.config.get('trac', 'default_timezone') default_language = self.config.get('trac', 'default_language') default_date_format = self.config.get('trac', 'default_date_format') default_dateinfo_format = self.config.get('trac', 'default_dateinfo_format') data = { 'default_handler': default_handler, 'valid_default_handlers': sorted(valid_default_handlers), 'default_timezone': default_timezone, 'timezones': all_timezones, 'has_pytz': pytz is not None, 'default_language': default_language.replace('-', '_'), 'languages': languages, 'default_date_format': default_date_format, 'default_dateinfo_format': default_dateinfo_format, 'has_babel': Locale is not None, } Chrome(self.env).add_textarea_grips(req) return 'admin_basics.html', data class LoggingAdminPanel(Component): implements(IAdminPanelProvider) # IAdminPanelProvider methods def get_admin_panels(self, req): if 'TRAC_ADMIN' in req.perm('admin', 'general/logging'): yield ('general', _("General"), 'logging', _("Logging")) def render_admin_panel(self, req, cat, page, path_info): log_type = self.env.log_type log_level = self.env.log_level log_file = self.env.log_file log_dir = self.env.log_dir log_types = [ dict(name='none', label=_("None"), selected=log_type == 'none', disabled=False), dict(name='stderr', label=_("Console"), selected=log_type == 'stderr', disabled=False), dict(name='file', label=_("File"), selected=log_type == 'file', disabled=False), dict(name='syslog', label=_("Syslog"), selected=log_type in ('unix', 'syslog'), disabled=os.name != 'posix'), dict(name='eventlog', label=_("Windows event log"), selected=log_type in ('winlog', 'eventlog', 'nteventlog'), disabled=os.name != 'nt'), ] if req.method == 'POST': changed = False new_type = req.args.get('log_type') if new_type not in [t['name'] for t in log_types]: raise TracError( _("Unknown log type %(type)s", type=new_type), _("Invalid log type") ) new_file = req.args.get('log_file', log_file) if not new_file: raise TracError(_("You must specify a log file"), _("Missing field")) new_level = req.args.get('log_level', log_level) if new_level not in _valid_log_levels: raise TracError( _("Unknown log level %(level)s", level=new_level), _("Invalid log level")) # Create logger to be sure the configuration is valid. new_file_path = new_file if not os.path.isabs(new_file_path): new_file_path = os.path.join(self.env.log_dir, new_file) try: logger, handler = \ self.env.create_logger(new_type, new_file_path, new_level, self.env.log_format) except Exception as e: add_warning(req, tag_("Changes not saved. Logger configuration " "error: %(error)s. Inspect the log for more " "information.", error=tag.code(exception_to_unicode(e)))) self.log.error("Logger configuration error: %s", exception_to_unicode(e, traceback=True)) else: handler.close() if new_type != log_type: self.config.set('logging', 'log_type', new_type) changed = True log_type = new_type if new_level != log_level: self.config.set('logging', 'log_level', new_level) changed = True log_level = new_level if new_file != log_file: self.config.set('logging', 'log_file', new_file) changed = True log_file = new_file if changed: _save_config(self.config, req, self.log), req.redirect(req.href.admin(cat, page)) # Order log levels by priority value, with aliases excluded. all_levels = sorted(log.LOG_LEVEL_MAP, key=log.LOG_LEVEL_MAP.get, reverse=True) log_levels = [level for level in all_levels if level in log.LOG_LEVELS] log_level = LOG_LEVEL_ALIASES_MAP.get(log_level, log_level) data = { 'type': log_type, 'types': log_types, 'level': log_level, 'levels': log_levels, 'file': log_file, 'dir': log_dir } return 'admin_logging.html', {'log': data} class PermissionAdminPanel(Component): implements(IAdminPanelProvider, IPermissionRequestor) # IPermissionRequestor methods def get_permission_actions(self): actions = ['PERMISSION_GRANT', 'PERMISSION_REVOKE'] return actions + [('PERMISSION_ADMIN', actions)] # IAdminPanelProvider methods def get_admin_panels(self, req): perm = req.perm('admin', 'general/perm') if 'PERMISSION_GRANT' in perm or 'PERMISSION_REVOKE' in perm: yield ('general', _("General"), 'perm', _("Permissions")) def render_admin_panel(self, req, cat, page, path_info): perm = PermissionSystem(self.env) all_actions = perm.get_actions() if req.method == 'POST': subject = req.args.get('subject', '').strip() target = req.args.get('target', '').strip() action = req.args.get('action') group = req.args.get('group', '').strip() if subject and subject.isupper() or \ group and group.isupper() or \ target and target.isupper(): raise TracError(_("All upper-cased tokens are reserved for " "permission names.")) # Grant permission to subject if 'add' in req.args and subject and action: req.perm('admin', 'general/perm').require('PERMISSION_GRANT') if action not in all_actions: raise TracError(_("Unknown action")) req.perm.require(action) try: perm.grant_permission(subject, action) except TracError as e: add_warning(req, e) else: add_notice(req, _("The subject %(subject)s has been " "granted the permission %(action)s.", subject=subject, action=action)) # Add subject to group elif 'add' in req.args and subject and group: req.perm('admin', 'general/perm').require('PERMISSION_GRANT') for action in sorted( perm.get_user_permissions(group, expand_meta=False)): req.perm.require(action, message=tag_( "The subject %(subject)s was not added to the " "group %(group)s. The group has %(perm)s " "permission and you cannot grant permissions you " "don't possess.", subject=tag.strong(subject), group=tag.strong(group), perm=tag.strong(action))) try: perm.grant_permission(subject, group) except TracError as e: add_warning(req, e) else: add_notice(req, _("The subject %(subject)s has been " "added to the group %(group)s.", subject=subject, group=group)) elif 'copy' in req.args and subject and target: req.perm('admin', 'general/perm').require('PERMISSION_GRANT') subject_permissions = perm.get_users_dict().get(subject, []) if not subject_permissions: add_warning(req, _("The subject %(subject)s does not " "have any permissions.", subject=subject)) for action in subject_permissions: if action not in all_actions: self.log.warning("Skipped granting %s to %s: " "permission unavailable.", action, target) else: if action not in req.perm: add_warning(req, _("The permission %(action)s was " "not granted to %(subject)s " "because users cannot grant " "permissions they don't possess.", action=action, subject=subject)) continue try: perm.grant_permission(target, action) except PermissionExistsError: pass else: add_notice(req, _("The subject %(subject)s has " "been granted the permission " "%(action)s.", subject=target, action=action)) req.redirect(req.href.admin(cat, page)) # Remove permissions action elif 'remove' in req.args and 'sel' in req.args: req.perm('admin', 'general/perm').require('PERMISSION_REVOKE') for key in req.args.getlist('sel'): subject, action = key.split(':', 1) subject = unicode_from_base64(subject) action = unicode_from_base64(action) if (subject, action) in perm.get_all_permissions(): perm.revoke_permission(subject, action) add_notice(req, _("The selected permissions have been " "revoked.")) req.redirect(req.href.admin(cat, page)) return 'admin_perms.html', { 'actions': all_actions, 'allowed_actions': [a for a in all_actions if a in req.perm], 'perms': perm.get_users_dict(), 'groups': perm.get_groups_dict(), 'unicode_to_base64': unicode_to_base64 } class PluginAdminPanel(Component): implements(IAdminPanelProvider) # IAdminPanelProvider methods def get_admin_panels(self, req): if 'TRAC_ADMIN' in req.perm('admin', 'general/plugin'): yield ('general', _("General"), 'plugin', _("Plugins")) def render_admin_panel(self, req, cat, page, path_info): if req.method == 'POST': if 'install' in req.args: self._do_install(req) elif 'uninstall' in req.args: self._do_uninstall(req) else: self._do_update(req) anchor = '' if 'plugin' in req.args: anchor = ' req.redirect(req.href.admin(cat, page) + anchor) return self._render_view(req) # Internal methods def _do_install(self, req): if 'plugin_file' not in req.args: raise TracError(_("No file uploaded")) upload = req.args['plugin_file'] if isinstance(upload, unicode) or not upload.filename: raise TracError(_("No file uploaded")) plugin_filename = upload.filename.replace('\\', '/').replace(':', '/') plugin_filename = os.path.basename(plugin_filename) if not plugin_filename: raise TracError(_("No file uploaded")) if not plugin_filename.endswith('.egg') and \ not plugin_filename.endswith('.py'): raise TracError(_("Uploaded file is not a Python source file or " "egg")) target_path = os.path.join(self.env.plugins_dir, plugin_filename) if os.path.isfile(target_path): raise TracError(_("Plugin %(name)s already installed", name=plugin_filename)) self.log.info("Installing plugin %s", plugin_filename) flags = os.O_CREAT + os.O_WRONLY + os.O_EXCL try: flags += os.O_BINARY except AttributeError: # OS_BINARY not available on every platform pass with os.fdopen(os.open(target_path, flags, 0o666), 'w') as target_file: shutil.copyfileobj(upload.file, target_file) self.log.info("Plugin %s installed to %s", plugin_filename, target_path) # TODO: Validate that the uploaded file is a valid Trac plugin # Make the environment reset itself on the next request self.env.config.touch() def _do_uninstall(self, req): plugin_filename = req.args.get('plugin_filename') if not plugin_filename: return plugin_path = os.path.join(self.env.plugins_dir, plugin_filename) if not os.path.isfile(plugin_path): return self.log.info("Uninstalling plugin %s", plugin_filename) os.remove(plugin_path) # Make the environment reset itself on the next request self.env.config.touch() def _do_update(self, req): components = req.args.getlist('component') enabled = req.args.getlist('enable') added, removed = [], [] # FIXME: this needs to be more intelligent and minimize multiple # component names to prefix rules for component in components: is_enabled = bool(self.env.is_component_enabled(component)) must_enable = component in enabled if is_enabled != must_enable: self.config.set('components', component, 'disabled' if is_enabled else 'enabled') self.log.info("%sabling component %s", "Dis" if is_enabled else "En", component) if must_enable: added.append(component) else: removed.append(component) if added or removed: def make_list(items): parts = [item.rsplit('.', 1) for item in items] return tag.table(tag.tbody( tag.tr(tag.td(c, class_='trac-name'), tag.td('(%s.*)' % m, class_='trac-name')) for m, c in parts), class_='trac-pluglist') added.sort() removed.sort() notices = [] if removed: msg = ngettext("The following component has been disabled:", "The following components have been disabled:", len(removed)) notices.append(tag(msg, make_list(removed))) if added: msg = ngettext("The following component has been enabled:", "The following components have been enabled:", len(added)) notices.append(tag(msg, make_list(added))) # set the default value of options for only the enabled components for component in added: self.config.set_defaults(component=component) _save_config(self.config, req, self.log, notices) def _render_view(self, req): plugins = get_plugin_info(self.env, include_core=True) def safe_wiki_to_html(context, text): try: return format_to_html(self.env, context, text) except Exception as e: self.log.error("Unable to render component documentation: %s", exception_to_unicode(e, traceback=True)) return tag.pre(text) data = { 'plugins': plugins, 'show': req.args.get('show'), 'readonly': not os.access(self.env.plugins_dir, os.F_OK + os.W_OK), 'safe_wiki_to_html': safe_wiki_to_html, } return 'admin_plugins.html', data

true

1c45b215becc81148e7aeae262a82262f980a51d

2,641

py

Python

render.py

araistrick/camera_pan_renderer

900c6c064ac7d2b460087a16be49204276679e04

[ "BSD-3-Clause" ]

2

2021-10-15T22:49:05.000Z

2022-02-28T20:26:53.000Z

render.py

araistrick/camera_pan_renderer

900c6c064ac7d2b460087a16be49204276679e04

[ "BSD-3-Clause" ]

null

render.py

araistrick/camera_pan_renderer

900c6c064ac7d2b460087a16be49204276679e04

[ "BSD-3-Clause" ]

null

import os import argparse from pathlib import Path import bpy import numpy as np os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID" os.environ["CUDA_VISIBLE_DEVICES"] = "0" def use_cuda(): bpy.context.preferences.addons["cycles"].preferences.compute_device_type = "CUDA" print(bpy.context.preferences.addons["cycles"].preferences.get_devices()) bpy.context.preferences.addons["cycles"].preferences.devices[0].use = True bpy.context.scene.cycles.device = "GPU" bpy.context.scene.render.tile_x = 128 bpy.context.scene.render.tile_x = 128 print('Using GPU device:', bpy.context.preferences.addons["cycles"].preferences.devices[0]) def select_none(): for obj in bpy.data.objects: obj.select_set(False) def render_ply(args, ply_path): ply_name = ply_path.parts[-1] ply_id = '_'.join(list(ply_name.split('_'))[1:]) # import the requisite ply select_none() print(f"Importing {ply_path}") bpy.ops.import_mesh.ply(filepath=str(ply_path)) imported_ply = bpy.context.selected_objects[0] # rotate it correctly imported_ply.rotation_euler = np.radians(np.array(args.override_ply_euler)) # make it colored according to vertex colors material = next(m for m in bpy.data.materials if m.name == args.template_material_name) if imported_ply.data.materials: imported_ply.data.materials[0] = material else: imported_ply.data.materials.append(material) # configure render output location outpath = Path(args.output_folder)/ply_id outpath.mkdir(exist_ok=True, parents=True) bpy.context.scene.render.filepath = str(outpath) + '/' bpy.ops.render.render(animation=True, write_still=True) # clean up select_none() imported_ply.select_set(True) bpy.ops.object.delete() def main(): parser = argparse.ArgumentParser() parser.add_argument('input_folder', type=str) parser.add_argument('output_folder', type=str) parser.add_argument('--template_file', type=str, default='template.blend') parser.add_argument('--override_ply_euler', type=int, nargs='+', default=[90, 0, 0]) parser.add_argument('--template_material_name', type=str, default='vertex color') parser.add_argument('--cuda', action='store_true') args = parser.parse_args() bpy.ops.wm.open_mainfile(filepath=args.template_file) if args.cuda: use_cuda() input_paths = list(Path(args.input_folder).glob('*.ply')) print(f"Starting processing of {len(input_paths)} .plys from {args.input_folder}") for ply_path in input_paths: render_ply(args, ply_path) if __name__ == '__main__': main()

33.43038

95

0.710716

import os import argparse from pathlib import Path import bpy import numpy as np os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID" os.environ["CUDA_VISIBLE_DEVICES"] = "0" def use_cuda(): bpy.context.preferences.addons["cycles"].preferences.compute_device_type = "CUDA" print(bpy.context.preferences.addons["cycles"].preferences.get_devices()) bpy.context.preferences.addons["cycles"].preferences.devices[0].use = True bpy.context.scene.cycles.device = "GPU" bpy.context.scene.render.tile_x = 128 bpy.context.scene.render.tile_x = 128 print('Using GPU device:', bpy.context.preferences.addons["cycles"].preferences.devices[0]) def select_none(): for obj in bpy.data.objects: obj.select_set(False) def render_ply(args, ply_path): ply_name = ply_path.parts[-1] ply_id = '_'.join(list(ply_name.split('_'))[1:]) select_none() print(f"Importing {ply_path}") bpy.ops.import_mesh.ply(filepath=str(ply_path)) imported_ply = bpy.context.selected_objects[0] imported_ply.rotation_euler = np.radians(np.array(args.override_ply_euler)) material = next(m for m in bpy.data.materials if m.name == args.template_material_name) if imported_ply.data.materials: imported_ply.data.materials[0] = material else: imported_ply.data.materials.append(material) outpath = Path(args.output_folder)/ply_id outpath.mkdir(exist_ok=True, parents=True) bpy.context.scene.render.filepath = str(outpath) + '/' bpy.ops.render.render(animation=True, write_still=True) select_none() imported_ply.select_set(True) bpy.ops.object.delete() def main(): parser = argparse.ArgumentParser() parser.add_argument('input_folder', type=str) parser.add_argument('output_folder', type=str) parser.add_argument('--template_file', type=str, default='template.blend') parser.add_argument('--override_ply_euler', type=int, nargs='+', default=[90, 0, 0]) parser.add_argument('--template_material_name', type=str, default='vertex color') parser.add_argument('--cuda', action='store_true') args = parser.parse_args() bpy.ops.wm.open_mainfile(filepath=args.template_file) if args.cuda: use_cuda() input_paths = list(Path(args.input_folder).glob('*.ply')) print(f"Starting processing of {len(input_paths)} .plys from {args.input_folder}") for ply_path in input_paths: render_ply(args, ply_path) if __name__ == '__main__': main()

true

1c45b269ee0360c0a0e853445b9985838bcb82f4

1,210

py

Python

examples/tutorials/pong/steps/step4/main.py

xinmingzhang/kivy

86b6e19d8a02788fe8850b690bcecdff848f3c4e

[ "MIT" ]

9

2016-09-03T07:20:01.000Z

2020-05-21T14:44:48.000Z

examples/tutorials/pong/steps/step4/main.py

xinmingzhang/kivy

86b6e19d8a02788fe8850b690bcecdff848f3c4e

[ "MIT" ]

1

2017-05-30T20:45:15.000Z

examples/tutorials/pong/steps/step4/main.py

xinmingzhang/kivy

86b6e19d8a02788fe8850b690bcecdff848f3c4e

[ "MIT" ]

4

2016-09-10T15:27:54.000Z

2020-03-27T22:05:31.000Z

from kivy.app import App from kivy.uix.widget import Widget from kivy.properties import NumericProperty, ReferenceListProperty,\ ObjectProperty from kivy.vector import Vector from kivy.clock import Clock from random import randint class PongBall(Widget): velocity_x = NumericProperty(0) velocity_y = NumericProperty(0) velocity = ReferenceListProperty(velocity_x, velocity_y) def move(self): self.pos = Vector(*self.velocity) + self.pos class PongGame(Widget): ball = ObjectProperty(None) def serve_ball(self): self.ball.center = self.center self.ball.velocity = Vector(4, 0).rotate(randint(0, 360)) def update(self, dt): self.ball.move() # bounce off top and bottom if (self.ball.y < 0) or (self.ball.top > self.height): self.ball.velocity_y *= -1 # bounce off left and right if (self.ball.x < 0) or (self.ball.right > self.width): self.ball.velocity_x *= -1 class PongApp(App): def build(self): game = PongGame() game.serve_ball() Clock.schedule_interval(game.update, 1.0 / 60.0) return game if __name__ == '__main__': PongApp().run()

25.208333

68

0.65124

from kivy.app import App from kivy.uix.widget import Widget from kivy.properties import NumericProperty, ReferenceListProperty,\ ObjectProperty from kivy.vector import Vector from kivy.clock import Clock from random import randint class PongBall(Widget): velocity_x = NumericProperty(0) velocity_y = NumericProperty(0) velocity = ReferenceListProperty(velocity_x, velocity_y) def move(self): self.pos = Vector(*self.velocity) + self.pos class PongGame(Widget): ball = ObjectProperty(None) def serve_ball(self): self.ball.center = self.center self.ball.velocity = Vector(4, 0).rotate(randint(0, 360)) def update(self, dt): self.ball.move() if (self.ball.y < 0) or (self.ball.top > self.height): self.ball.velocity_y *= -1 if (self.ball.x < 0) or (self.ball.right > self.width): self.ball.velocity_x *= -1 class PongApp(App): def build(self): game = PongGame() game.serve_ball() Clock.schedule_interval(game.update, 1.0 / 60.0) return game if __name__ == '__main__': PongApp().run()

true

1c45b360ed6e478c667bfe1ca7f4f430632593d1

10,978

py

Python

packages/python/plotly/plotly/validators/_candlestick.py

c-chaitanya/plotly.py

7bda89c77559747e67fb1608bf9309e97505a4f2

[ "MIT" ]

7

2021-09-29T09:46:36.000Z

2022-03-24T08:30:41.000Z

packages/python/plotly/plotly/validators/_candlestick.py

c-chaitanya/plotly.py

7bda89c77559747e67fb1608bf9309e97505a4f2

[ "MIT" ]

1

2021-09-30T16:56:21.000Z

2021-10-15T09:14:12.000Z

packages/python/plotly/plotly/validators/_candlestick.py

c-chaitanya/plotly.py

7bda89c77559747e67fb1608bf9309e97505a4f2

[ "MIT" ]

1

2021-09-29T22:34:05.000Z

import _plotly_utils.basevalidators class CandlestickValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="candlestick", parent_name="", **kwargs): super(CandlestickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Candlestick"), data_docs=kwargs.pop( "data_docs", """ close Sets the close values. closesrc Sets the source reference on Chart Studio Cloud for close . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on Chart Studio Cloud for customdata . decreasing :class:`plotly.graph_objects.candlestick.Decrea sing` instance or dict with compatible properties high Sets the high values. highsrc Sets the source reference on Chart Studio Cloud for high . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on Chart Studio Cloud for hoverinfo . hoverlabel :class:`plotly.graph_objects.candlestick.Hoverl abel` instance or dict with compatible properties hovertext Same as `text`. hovertextsrc Sets the source reference on Chart Studio Cloud for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on Chart Studio Cloud for ids . increasing :class:`plotly.graph_objects.candlestick.Increa sing` instance or dict with compatible properties legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. legendrank Sets the legend rank for this trace. Items and groups with smaller ranks are presented on top/left side while with `*reversed* `legend.traceorder` they are on bottom/right side. The default legendrank is 1000, so that you can use ranks less than 1000 to place certain items before all unranked items, and ranks greater than 1000 to go after all unranked items. line :class:`plotly.graph_objects.candlestick.Line` instance or dict with compatible properties low Sets the low values. lowsrc Sets the source reference on Chart Studio Cloud for low . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on Chart Studio Cloud for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. open Sets the open values. opensrc Sets the source reference on Chart Studio Cloud for open . selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream :class:`plotly.graph_objects.candlestick.Stream ` instance or dict with compatible properties text Sets hover text elements associated with each sample point. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to this trace's sample points. textsrc Sets the source reference on Chart Studio Cloud for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). whiskerwidth Sets the width of the whiskers relative to the box' width. For example, with 1, the whiskers are as wide as the box(es). x Sets the x coordinates. If absent, linear coordinate will be generated. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xhoverformat Sets the hover text formatting rule for `x` using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-time- format#locale_format By default the values are formatted using `xaxis.hoverformat`. xperiod Only relevant when the axis `type` is "date". Sets the period positioning in milliseconds or "M<n>" on the x axis. Special values in the form of "M<n>" could be used to declare the number of months. In this case `n` must be a positive integer. xperiod0 Only relevant when the axis `type` is "date". Sets the base for period positioning in milliseconds or date string on the x0 axis. When `x0period` is round number of weeks, the `x0period0` by default would be on a Sunday i.e. 2000-01-02, otherwise it would be at 2000-01-01. xperiodalignment Only relevant when the axis `type` is "date". Sets the alignment of data points on the x axis. xsrc Sets the source reference on Chart Studio Cloud for x . yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. yhoverformat Sets the hover text formatting rule for `y` using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-time- format#locale_format By default the values are formatted using `yaxis.hoverformat`. """, ), **kwargs )

46.12605

76

0.538167

import _plotly_utils.basevalidators class CandlestickValidator(_plotly_utils.basevalidators.CompoundValidator): def __init__(self, plotly_name="candlestick", parent_name="", **kwargs): super(CandlestickValidator, self).__init__( plotly_name=plotly_name, parent_name=parent_name, data_class_str=kwargs.pop("data_class_str", "Candlestick"), data_docs=kwargs.pop( "data_docs", """ close Sets the close values. closesrc Sets the source reference on Chart Studio Cloud for close . customdata Assigns extra data each datum. This may be useful when listening to hover, click and selection events. Note that, "scatter" traces also appends customdata items in the markers DOM elements customdatasrc Sets the source reference on Chart Studio Cloud for customdata . decreasing :class:`plotly.graph_objects.candlestick.Decrea sing` instance or dict with compatible properties high Sets the high values. highsrc Sets the source reference on Chart Studio Cloud for high . hoverinfo Determines which trace information appear on hover. If `none` or `skip` are set, no information is displayed upon hovering. But, if `none` is set, click and hover events are still fired. hoverinfosrc Sets the source reference on Chart Studio Cloud for hoverinfo . hoverlabel :class:`plotly.graph_objects.candlestick.Hoverl abel` instance or dict with compatible properties hovertext Same as `text`. hovertextsrc Sets the source reference on Chart Studio Cloud for hovertext . ids Assigns id labels to each datum. These ids for object constancy of data points during animation. Should be an array of strings, not numbers or any other type. idssrc Sets the source reference on Chart Studio Cloud for ids . increasing :class:`plotly.graph_objects.candlestick.Increa sing` instance or dict with compatible properties legendgroup Sets the legend group for this trace. Traces part of the same legend group hide/show at the same time when toggling legend items. legendrank Sets the legend rank for this trace. Items and groups with smaller ranks are presented on top/left side while with `*reversed* `legend.traceorder` they are on bottom/right side. The default legendrank is 1000, so that you can use ranks less than 1000 to place certain items before all unranked items, and ranks greater than 1000 to go after all unranked items. line :class:`plotly.graph_objects.candlestick.Line` instance or dict with compatible properties low Sets the low values. lowsrc Sets the source reference on Chart Studio Cloud for low . meta Assigns extra meta information associated with this trace that can be used in various text attributes. Attributes such as trace `name`, graph, axis and colorbar `title.text`, annotation `text` `rangeselector`, `updatemenues` and `sliders` `label` text all support `meta`. To access the trace `meta` values in an attribute in the same trace, simply use `%{meta[i]}` where `i` is the index or key of the `meta` item in question. To access trace `meta` in layout attributes, use `%{data[n[.meta[i]}` where `i` is the index or key of the `meta` and `n` is the trace index. metasrc Sets the source reference on Chart Studio Cloud for meta . name Sets the trace name. The trace name appear as the legend item and on hover. opacity Sets the opacity of the trace. open Sets the open values. opensrc Sets the source reference on Chart Studio Cloud for open . selectedpoints Array containing integer indices of selected points. Has an effect only for traces that support selections. Note that an empty array means an empty selection where the `unselected` are turned on for all points, whereas, any other non-array values means no selection all where the `selected` and `unselected` styles have no effect. showlegend Determines whether or not an item corresponding to this trace is shown in the legend. stream :class:`plotly.graph_objects.candlestick.Stream ` instance or dict with compatible properties text Sets hover text elements associated with each sample point. If a single string, the same string appears over all the data points. If an array of string, the items are mapped in order to this trace's sample points. textsrc Sets the source reference on Chart Studio Cloud for text . uid Assign an id to this trace, Use this to provide object constancy between traces during animations and transitions. uirevision Controls persistence of some user-driven changes to the trace: `constraintrange` in `parcoords` traces, as well as some `editable: true` modifications such as `name` and `colorbar.title`. Defaults to `layout.uirevision`. Note that other user- driven trace attribute changes are controlled by `layout` attributes: `trace.visible` is controlled by `layout.legend.uirevision`, `selectedpoints` is controlled by `layout.selectionrevision`, and `colorbar.(x|y)` (accessible with `config: {editable: true}`) is controlled by `layout.editrevision`. Trace changes are tracked by `uid`, which only falls back on trace index if no `uid` is provided. So if your app can add/remove traces before the end of the `data` array, such that the same trace has a different index, you can still preserve user- driven changes if you give each trace a `uid` that stays with it as it moves. visible Determines whether or not this trace is visible. If "legendonly", the trace is not drawn, but can appear as a legend item (provided that the legend itself is visible). whiskerwidth Sets the width of the whiskers relative to the box' width. For example, with 1, the whiskers are as wide as the box(es). x Sets the x coordinates. If absent, linear coordinate will be generated. xaxis Sets a reference between this trace's x coordinates and a 2D cartesian x axis. If "x" (the default value), the x coordinates refer to `layout.xaxis`. If "x2", the x coordinates refer to `layout.xaxis2`, and so on. xcalendar Sets the calendar system to use with `x` date data. xhoverformat Sets the hover text formatting rule for `x` using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-time- format#locale_format By default the values are formatted using `xaxis.hoverformat`. xperiod Only relevant when the axis `type` is "date". Sets the period positioning in milliseconds or "M<n>" on the x axis. Special values in the form of "M<n>" could be used to declare the number of months. In this case `n` must be a positive integer. xperiod0 Only relevant when the axis `type` is "date". Sets the base for period positioning in milliseconds or date string on the x0 axis. When `x0period` is round number of weeks, the `x0period0` by default would be on a Sunday i.e. 2000-01-02, otherwise it would be at 2000-01-01. xperiodalignment Only relevant when the axis `type` is "date". Sets the alignment of data points on the x axis. xsrc Sets the source reference on Chart Studio Cloud for x . yaxis Sets a reference between this trace's y coordinates and a 2D cartesian y axis. If "y" (the default value), the y coordinates refer to `layout.yaxis`. If "y2", the y coordinates refer to `layout.yaxis2`, and so on. yhoverformat Sets the hover text formatting rule for `y` using d3 formatting mini-languages which are very similar to those in Python. See: https://github.com/d3/d3-3.x-api- reference/blob/master/Formatting.md#d3_format And for dates see: https://github.com/d3/d3-time- format#locale_format By default the values are formatted using `yaxis.hoverformat`. """, ), **kwargs )

true

1c45b39ba990a7c522df62adb4f9bedffe167392

60,426

py

Python

pandas/core/internals/managers.py

joybhallaa/pandas

1779155552631a30d4bb176dec70b8cc477defd7

[ "PSF-2.0", "Apache-2.0", "BSD-3-Clause-No-Nuclear-License-2014", "MIT", "ECL-2.0", "BSD-3-Clause" ]

2

2022-02-02T02:05:28.000Z

2022-02-02T02:09:37.000Z

pandas/core/internals/managers.py

north-star-saj/pandas

fc9fdba6592bdb5d0d1147ce4d65639acd897565

[ "PSF-2.0", "Apache-2.0", "BSD-3-Clause-No-Nuclear-License-2014", "MIT", "ECL-2.0", "BSD-3-Clause" ]

null

pandas/core/internals/managers.py

north-star-saj/pandas

fc9fdba6592bdb5d0d1147ce4d65639acd897565

[ "PSF-2.0", "Apache-2.0", "BSD-3-Clause-No-Nuclear-License-2014", "MIT", "ECL-2.0", "BSD-3-Clause" ]

1

2020-10-28T03:32:40.000Z

from __future__ import annotations from collections import defaultdict import itertools from typing import ( Any, Callable, DefaultDict, Dict, Hashable, List, Optional, Sequence, Tuple, TypeVar, Union, ) import warnings import numpy as np from pandas._libs import internals as libinternals, lib from pandas._typing import ArrayLike, Dtype, DtypeObj, Shape from pandas.errors import PerformanceWarning from pandas.util._validators import validate_bool_kwarg from pandas.core.dtypes.cast import find_common_type, infer_dtype_from_scalar from pandas.core.dtypes.common import ( DT64NS_DTYPE, is_dtype_equal, is_extension_array_dtype, is_list_like, ) from pandas.core.dtypes.dtypes import ExtensionDtype from pandas.core.dtypes.generic import ABCDataFrame, ABCPandasArray, ABCSeries from pandas.core.dtypes.missing import array_equals, isna import pandas.core.algorithms as algos from pandas.core.arrays.sparse import SparseDtype from pandas.core.construction import extract_array from pandas.core.indexers import maybe_convert_indices from pandas.core.indexes.api import Float64Index, Index, ensure_index from pandas.core.internals.base import DataManager from pandas.core.internals.blocks import ( Block, CategoricalBlock, DatetimeTZBlock, ExtensionBlock, ObjectValuesExtensionBlock, extend_blocks, get_block_type, make_block, safe_reshape, ) from pandas.core.internals.ops import blockwise_all, operate_blockwise # TODO: flexible with index=None and/or items=None T = TypeVar("T", bound="BlockManager") class BlockManager(DataManager): """ Core internal data structure to implement DataFrame, Series, etc. Manage a bunch of labeled 2D mixed-type ndarrays. Essentially it's a lightweight blocked set of labeled data to be manipulated by the DataFrame public API class Attributes ---------- shape ndim axes values items Methods ------- set_axis(axis, new_labels) copy(deep=True) get_dtypes apply(func, axes, block_filter_fn) get_bool_data get_numeric_data get_slice(slice_like, axis) get(label) iget(loc) take(indexer, axis) reindex_axis(new_labels, axis) reindex_indexer(new_labels, indexer, axis) delete(label) insert(loc, label, value) set(label, value) Parameters ---------- blocks: Sequence of Block axes: Sequence of Index do_integrity_check: bool, default True Notes ----- This is *not* a public API class """ __slots__ = [ "axes", "blocks", "_known_consolidated", "_is_consolidated", "_blknos", "_blklocs", ] _blknos: np.ndarray _blklocs: np.ndarray def __init__( self, blocks: Sequence[Block], axes: Sequence[Index], do_integrity_check: bool = True, ): self.axes = [ensure_index(ax) for ax in axes] self.blocks: Tuple[Block, ...] = tuple(blocks) for block in blocks: if self.ndim != block.ndim: raise AssertionError( f"Number of Block dimensions ({block.ndim}) must equal " f"number of axes ({self.ndim})" ) if do_integrity_check: self._verify_integrity() # Populate known_consolidate, blknos, and blklocs lazily self._known_consolidated = False self._blknos = None self._blklocs = None @classmethod def from_blocks(cls, blocks: List[Block], axes: List[Index]): """ Constructor for BlockManager and SingleBlockManager with same signature. """ return cls(blocks, axes, do_integrity_check=False) @property def blknos(self): """ Suppose we want to find the array corresponding to our i'th column. blknos[i] identifies the block from self.blocks that contains this column. blklocs[i] identifies the column of interest within self.blocks[self.blknos[i]] """ if self._blknos is None: # Note: these can be altered by other BlockManager methods. self._rebuild_blknos_and_blklocs() return self._blknos @property def blklocs(self): """ See blknos.__doc__ """ if self._blklocs is None: # Note: these can be altered by other BlockManager methods. self._rebuild_blknos_and_blklocs() return self._blklocs def make_empty(self: T, axes=None) -> T: """ return an empty BlockManager with the items axis of len 0 """ if axes is None: axes = [Index([])] + self.axes[1:] # preserve dtype if possible if self.ndim == 1: assert isinstance(self, SingleBlockManager) # for mypy blk = self.blocks[0] arr = blk.values[:0] nb = blk.make_block_same_class(arr, placement=slice(0, 0), ndim=1) blocks = [nb] else: blocks = [] return type(self).from_blocks(blocks, axes) def __nonzero__(self) -> bool: return True # Python3 compat __bool__ = __nonzero__ @property def shape(self) -> Shape: return tuple(len(ax) for ax in self.axes) @property def ndim(self) -> int: return len(self.axes) def set_axis(self, axis: int, new_labels: Index) -> None: # Caller is responsible for ensuring we have an Index object. old_len = len(self.axes[axis]) new_len = len(new_labels) if new_len != old_len: raise ValueError( f"Length mismatch: Expected axis has {old_len} elements, new " f"values have {new_len} elements" ) self.axes[axis] = new_labels @property def is_single_block(self) -> bool: # Assumes we are 2D; overridden by SingleBlockManager return len(self.blocks) == 1 def _rebuild_blknos_and_blklocs(self) -> None: """ Update mgr._blknos / mgr._blklocs. """ new_blknos = np.empty(self.shape[0], dtype=np.intp) new_blklocs = np.empty(self.shape[0], dtype=np.intp) new_blknos.fill(-1) new_blklocs.fill(-1) for blkno, blk in enumerate(self.blocks): rl = blk.mgr_locs new_blknos[rl.indexer] = blkno new_blklocs[rl.indexer] = np.arange(len(rl)) if (new_blknos == -1).any(): # TODO: can we avoid this? it isn't cheap raise AssertionError("Gaps in blk ref_locs") self._blknos = new_blknos self._blklocs = new_blklocs @property def items(self) -> Index: return self.axes[0] def get_dtypes(self): dtypes = np.array([blk.dtype for blk in self.blocks]) return algos.take_nd(dtypes, self.blknos, allow_fill=False) def __getstate__(self): block_values = [b.values for b in self.blocks] block_items = [self.items[b.mgr_locs.indexer] for b in self.blocks] axes_array = list(self.axes) extra_state = { "0.14.1": { "axes": axes_array, "blocks": [ {"values": b.values, "mgr_locs": b.mgr_locs.indexer} for b in self.blocks ], } } # First three elements of the state are to maintain forward # compatibility with 0.13.1. return axes_array, block_values, block_items, extra_state def __setstate__(self, state): def unpickle_block(values, mgr_locs, ndim: int): # TODO(EA2D): ndim would be unnecessary with 2D EAs return make_block(values, placement=mgr_locs, ndim=ndim) if isinstance(state, tuple) and len(state) >= 4 and "0.14.1" in state[3]: state = state[3]["0.14.1"] self.axes = [ensure_index(ax) for ax in state["axes"]] ndim = len(self.axes) self.blocks = tuple( unpickle_block(b["values"], b["mgr_locs"], ndim=ndim) for b in state["blocks"] ) else: raise NotImplementedError("pre-0.14.1 pickles are no longer supported") self._post_setstate() def _post_setstate(self) -> None: self._is_consolidated = False self._known_consolidated = False self._rebuild_blknos_and_blklocs() def __len__(self) -> int: return len(self.items) def __repr__(self) -> str: output = type(self).__name__ for i, ax in enumerate(self.axes): if i == 0: output += f"\nItems: {ax}" else: output += f"\nAxis {i}: {ax}" for block in self.blocks: output += f"\n{block}" return output def _verify_integrity(self) -> None: mgr_shape = self.shape tot_items = sum(len(x.mgr_locs) for x in self.blocks) for block in self.blocks: if block.shape[1:] != mgr_shape[1:]: raise construction_error(tot_items, block.shape[1:], self.axes) if len(self.items) != tot_items: raise AssertionError( "Number of manager items must equal union of " f"block items\n# manager items: {len(self.items)}, # " f"tot_items: {tot_items}" ) def reduce( self: T, func: Callable, ignore_failures: bool = False ) -> Tuple[T, np.ndarray]: """ Apply reduction function blockwise, returning a single-row BlockManager. Parameters ---------- func : reduction function ignore_failures : bool, default False Whether to drop blocks where func raises TypeError. Returns ------- BlockManager np.ndarray Indexer of mgr_locs that are retained. """ # If 2D, we assume that we're operating column-wise assert self.ndim == 2 res_blocks: List[Block] = [] for blk in self.blocks: nbs = blk.reduce(func, ignore_failures) res_blocks.extend(nbs) index = Index([None]) # placeholder if ignore_failures: if res_blocks: indexer = np.concatenate([blk.mgr_locs.as_array for blk in res_blocks]) new_mgr = self._combine(res_blocks, copy=False, index=index) else: indexer = [] new_mgr = type(self).from_blocks([], [Index([]), index]) else: indexer = np.arange(self.shape[0]) new_mgr = type(self).from_blocks(res_blocks, [self.items, index]) return new_mgr, indexer def operate_blockwise(self, other: BlockManager, array_op) -> BlockManager: """ Apply array_op blockwise with another (aligned) BlockManager. """ return operate_blockwise(self, other, array_op) def apply( self: T, f, align_keys: Optional[List[str]] = None, ignore_failures: bool = False, **kwargs, ) -> T: """ Iterate over the blocks, collect and create a new BlockManager. Parameters ---------- f : str or callable Name of the Block method to apply. align_keys: List[str] or None, default None ignore_failures: bool, default False **kwargs Keywords to pass to `f` Returns ------- BlockManager """ assert "filter" not in kwargs align_keys = align_keys or [] result_blocks: List[Block] = [] # fillna: Series/DataFrame is responsible for making sure value is aligned aligned_args = {k: kwargs[k] for k in align_keys} for b in self.blocks: if aligned_args: for k, obj in aligned_args.items(): if isinstance(obj, (ABCSeries, ABCDataFrame)): # The caller is responsible for ensuring that # obj.axes[-1].equals(self.items) if obj.ndim == 1: kwargs[k] = obj.iloc[b.mgr_locs.indexer]._values else: kwargs[k] = obj.iloc[:, b.mgr_locs.indexer]._values else: # otherwise we have an ndarray kwargs[k] = obj[b.mgr_locs.indexer] try: if callable(f): applied = b.apply(f, **kwargs) else: applied = getattr(b, f)(**kwargs) except (TypeError, NotImplementedError): if not ignore_failures: raise continue result_blocks = extend_blocks(applied, result_blocks) if ignore_failures: return self._combine(result_blocks) if len(result_blocks) == 0: return self.make_empty(self.axes) return type(self).from_blocks(result_blocks, self.axes) def quantile( self, *, qs: Float64Index, axis: int = 0, transposed: bool = False, interpolation="linear", ) -> BlockManager: """ Iterate over blocks applying quantile reduction. This routine is intended for reduction type operations and will do inference on the generated blocks. Parameters ---------- axis: reduction axis, default 0 consolidate: bool, default True. Join together blocks having same dtype transposed: bool, default False we are holding transposed data interpolation : type of interpolation, default 'linear' qs : list of the quantiles to be computed Returns ------- BlockManager """ # Series dispatches to DataFrame for quantile, which allows us to # simplify some of the code here and in the blocks assert self.ndim >= 2 assert is_list_like(qs) # caller is responsible for this assert axis == 1 # only ever called this way new_axes = list(self.axes) new_axes[1] = Float64Index(qs) blocks = [ blk.quantile(axis=axis, qs=qs, interpolation=interpolation) for blk in self.blocks ] if transposed: new_axes = new_axes[::-1] blocks = [ b.make_block(b.values.T, placement=np.arange(b.shape[1])) for b in blocks ] return type(self)(blocks, new_axes) def isna(self, func) -> BlockManager: return self.apply("apply", func=func) def where(self, other, cond, align: bool, errors: str, axis: int) -> BlockManager: if align: align_keys = ["other", "cond"] else: align_keys = ["cond"] other = extract_array(other, extract_numpy=True) return self.apply( "where", align_keys=align_keys, other=other, cond=cond, errors=errors, axis=axis, ) def setitem(self, indexer, value) -> BlockManager: return self.apply("setitem", indexer=indexer, value=value) def putmask(self, mask, new, align: bool = True): if align: align_keys = ["new", "mask"] else: align_keys = ["mask"] new = extract_array(new, extract_numpy=True) return self.apply( "putmask", align_keys=align_keys, mask=mask, new=new, ) def diff(self, n: int, axis: int) -> BlockManager: return self.apply("diff", n=n, axis=axis) def interpolate(self, **kwargs) -> BlockManager: return self.apply("interpolate", **kwargs) def shift(self, periods: int, axis: int, fill_value) -> BlockManager: if fill_value is lib.no_default: fill_value = None if axis == 0 and self.ndim == 2 and self.nblocks > 1: # GH#35488 we need to watch out for multi-block cases # We only get here with fill_value not-lib.no_default ncols = self.shape[0] if periods > 0: indexer = [-1] * periods + list(range(ncols - periods)) else: nper = abs(periods) indexer = list(range(nper, ncols)) + [-1] * nper result = self.reindex_indexer( self.items, indexer, axis=0, fill_value=fill_value, allow_dups=True, consolidate=False, ) return result return self.apply("shift", periods=periods, axis=axis, fill_value=fill_value) def fillna(self, value, limit, inplace: bool, downcast) -> BlockManager: return self.apply( "fillna", value=value, limit=limit, inplace=inplace, downcast=downcast ) def downcast(self) -> BlockManager: return self.apply("downcast") def astype(self, dtype, copy: bool = False, errors: str = "raise") -> BlockManager: return self.apply("astype", dtype=dtype, copy=copy, errors=errors) def convert( self, copy: bool = True, datetime: bool = True, numeric: bool = True, timedelta: bool = True, ) -> BlockManager: return self.apply( "convert", copy=copy, datetime=datetime, numeric=numeric, timedelta=timedelta, ) def replace(self, to_replace, value, inplace: bool, regex: bool) -> BlockManager: assert np.ndim(value) == 0, value return self.apply( "replace", to_replace=to_replace, value=value, inplace=inplace, regex=regex ) def replace_list( self: T, src_list: List[Any], dest_list: List[Any], inplace: bool = False, regex: bool = False, ) -> T: """ do a list replace """ inplace = validate_bool_kwarg(inplace, "inplace") bm = self.apply( "_replace_list", src_list=src_list, dest_list=dest_list, inplace=inplace, regex=regex, ) bm._consolidate_inplace() return bm def to_native_types(self, **kwargs) -> BlockManager: """ Convert values to native types (strings / python objects) that are used in formatting (repr / csv). """ return self.apply("to_native_types", **kwargs) def is_consolidated(self) -> bool: """ Return True if more than one block with the same dtype """ if not self._known_consolidated: self._consolidate_check() return self._is_consolidated def _consolidate_check(self) -> None: dtypes = [blk.dtype for blk in self.blocks if blk._can_consolidate] self._is_consolidated = len(dtypes) == len(set(dtypes)) self._known_consolidated = True @property def is_numeric_mixed_type(self) -> bool: return all(block.is_numeric for block in self.blocks) @property def any_extension_types(self) -> bool: """Whether any of the blocks in this manager are extension blocks""" return any(block.is_extension for block in self.blocks) @property def is_view(self) -> bool: """ return a boolean if we are a single block and are a view """ if len(self.blocks) == 1: return self.blocks[0].is_view # It is technically possible to figure out which blocks are views # e.g. [ b.values.base is not None for b in self.blocks ] # but then we have the case of possibly some blocks being a view # and some blocks not. setting in theory is possible on the non-view # blocks w/o causing a SettingWithCopy raise/warn. But this is a bit # complicated return False def get_bool_data(self, copy: bool = False) -> BlockManager: """ Select blocks that are bool-dtype and columns from object-dtype blocks that are all-bool. Parameters ---------- copy : bool, default False Whether to copy the blocks """ new_blocks = [] for blk in self.blocks: if blk.dtype == bool: new_blocks.append(blk) elif blk.is_object: nbs = blk._split() for nb in nbs: if nb.is_bool: new_blocks.append(nb) return self._combine(new_blocks, copy) def get_numeric_data(self, copy: bool = False) -> BlockManager: """ Parameters ---------- copy : bool, default False Whether to copy the blocks """ return self._combine([b for b in self.blocks if b.is_numeric], copy) def _combine( self: T, blocks: List[Block], copy: bool = True, index: Optional[Index] = None ) -> T: """ return a new manager with the blocks """ if len(blocks) == 0: return self.make_empty() # FIXME: optimization potential indexer = np.sort(np.concatenate([b.mgr_locs.as_array for b in blocks])) inv_indexer = lib.get_reverse_indexer(indexer, self.shape[0]) new_blocks: List[Block] = [] for b in blocks: b = b.copy(deep=copy) b.mgr_locs = inv_indexer[b.mgr_locs.indexer] new_blocks.append(b) axes = list(self.axes) if index is not None: axes[-1] = index axes[0] = self.items.take(indexer) return type(self).from_blocks(new_blocks, axes) def get_slice(self, slobj: slice, axis: int = 0) -> BlockManager: if axis == 0: new_blocks = self._slice_take_blocks_ax0(slobj) elif axis == 1: slicer = (slice(None), slobj) new_blocks = [blk.getitem_block(slicer) for blk in self.blocks] else: raise IndexError("Requested axis not found in manager") new_axes = list(self.axes) new_axes[axis] = new_axes[axis][slobj] bm = type(self)(new_blocks, new_axes, do_integrity_check=False) return bm @property def nblocks(self) -> int: return len(self.blocks) def copy(self: T, deep=True) -> T: """ Make deep or shallow copy of BlockManager Parameters ---------- deep : bool or string, default True If False, return shallow copy (do not copy data) If 'all', copy data and a deep copy of the index Returns ------- BlockManager """ # this preserves the notion of view copying of axes if deep: # hit in e.g. tests.io.json.test_pandas def copy_func(ax): return ax.copy(deep=True) if deep == "all" else ax.view() new_axes = [copy_func(ax) for ax in self.axes] else: new_axes = list(self.axes) res = self.apply("copy", deep=deep) res.axes = new_axes return res def as_array( self, transpose: bool = False, dtype: Optional[Dtype] = None, copy: bool = False, na_value=lib.no_default, ) -> np.ndarray: """ Convert the blockmanager data into an numpy array. Parameters ---------- transpose : bool, default False If True, transpose the return array. dtype : object, default None Data type of the return array. copy : bool, default False If True then guarantee that a copy is returned. A value of False does not guarantee that the underlying data is not copied. na_value : object, default lib.no_default Value to be used as the missing value sentinel. Returns ------- arr : ndarray """ if len(self.blocks) == 0: arr = np.empty(self.shape, dtype=float) return arr.transpose() if transpose else arr # We want to copy when na_value is provided to avoid # mutating the original object copy = copy or na_value is not lib.no_default if self.is_single_block: blk = self.blocks[0] if blk.is_extension: # Avoid implicit conversion of extension blocks to object arr = blk.values.to_numpy(dtype=dtype, na_value=na_value).reshape( blk.shape ) else: arr = np.asarray(blk.get_values()) if dtype: arr = arr.astype(dtype, copy=False) else: arr = self._interleave(dtype=dtype, na_value=na_value) # The underlying data was copied within _interleave copy = False if copy: arr = arr.copy() if na_value is not lib.no_default: arr[isna(arr)] = na_value return arr.transpose() if transpose else arr def _interleave( self, dtype: Optional[Dtype] = None, na_value=lib.no_default ) -> np.ndarray: """ Return ndarray from blocks with specified item order Items must be contained in the blocks """ if not dtype: dtype = _interleaved_dtype(self.blocks) # TODO: https://github.com/pandas-dev/pandas/issues/22791 # Give EAs some input on what happens here. Sparse needs this. if isinstance(dtype, SparseDtype): dtype = dtype.subtype elif is_extension_array_dtype(dtype): dtype = "object" elif is_dtype_equal(dtype, str): dtype = "object" result = np.empty(self.shape, dtype=dtype) itemmask = np.zeros(self.shape[0]) for blk in self.blocks: rl = blk.mgr_locs if blk.is_extension: # Avoid implicit conversion of extension blocks to object arr = blk.values.to_numpy(dtype=dtype, na_value=na_value) else: arr = blk.get_values(dtype) result[rl.indexer] = arr itemmask[rl.indexer] = 1 if not itemmask.all(): raise AssertionError("Some items were not contained in blocks") return result def to_dict(self, copy: bool = True): """ Return a dict of str(dtype) -> BlockManager Parameters ---------- copy : bool, default True Returns ------- values : a dict of dtype -> BlockManager """ bd: Dict[str, List[Block]] = {} for b in self.blocks: bd.setdefault(str(b.dtype), []).append(b) # TODO(EA2D): the combine will be unnecessary with 2D EAs return {dtype: self._combine(blocks, copy=copy) for dtype, blocks in bd.items()} def fast_xs(self, loc: int) -> ArrayLike: """ Return the array corresponding to `frame.iloc[loc]`. Parameters ---------- loc : int Returns ------- np.ndarray or ExtensionArray """ if len(self.blocks) == 1: return self.blocks[0].iget((slice(None), loc)) dtype = _interleaved_dtype(self.blocks) n = len(self) if is_extension_array_dtype(dtype): # we'll eventually construct an ExtensionArray. result = np.empty(n, dtype=object) else: result = np.empty(n, dtype=dtype) for blk in self.blocks: # Such assignment may incorrectly coerce NaT to None # result[blk.mgr_locs] = blk._slice((slice(None), loc)) for i, rl in enumerate(blk.mgr_locs): result[rl] = blk.iget((i, loc)) if isinstance(dtype, ExtensionDtype): result = dtype.construct_array_type()._from_sequence(result, dtype=dtype) return result def consolidate(self) -> BlockManager: """ Join together blocks having same dtype Returns ------- y : BlockManager """ if self.is_consolidated(): return self bm = type(self)(self.blocks, self.axes) bm._is_consolidated = False bm._consolidate_inplace() return bm def _consolidate_inplace(self) -> None: if not self.is_consolidated(): self.blocks = tuple(_consolidate(self.blocks)) self._is_consolidated = True self._known_consolidated = True self._rebuild_blknos_and_blklocs() def iget(self, i: int) -> SingleBlockManager: """ Return the data as a SingleBlockManager. """ block = self.blocks[self.blknos[i]] values = block.iget(self.blklocs[i]) # shortcut for select a single-dim from a 2-dim BM return SingleBlockManager( block.make_block_same_class( values, placement=slice(0, len(values)), ndim=1 ), self.axes[1], ) def iget_values(self, i: int) -> ArrayLike: """ Return the data for column i as the values (ndarray or ExtensionArray). """ block = self.blocks[self.blknos[i]] values = block.iget(self.blklocs[i]) return values def idelete(self, indexer): """ Delete selected locations in-place (new block and array, same BlockManager) """ is_deleted = np.zeros(self.shape[0], dtype=np.bool_) is_deleted[indexer] = True ref_loc_offset = -is_deleted.cumsum() is_blk_deleted = [False] * len(self.blocks) if isinstance(indexer, int): affected_start = indexer else: affected_start = is_deleted.nonzero()[0][0] for blkno, _ in _fast_count_smallints(self.blknos[affected_start:]): blk = self.blocks[blkno] bml = blk.mgr_locs blk_del = is_deleted[bml.indexer].nonzero()[0] if len(blk_del) == len(bml): is_blk_deleted[blkno] = True continue elif len(blk_del) != 0: blk.delete(blk_del) bml = blk.mgr_locs blk.mgr_locs = bml.add(ref_loc_offset[bml.indexer]) # FIXME: use Index.delete as soon as it uses fastpath=True self.axes[0] = self.items[~is_deleted] self.blocks = tuple( b for blkno, b in enumerate(self.blocks) if not is_blk_deleted[blkno] ) self._rebuild_blknos_and_blklocs() def iset(self, loc: Union[int, slice, np.ndarray], value): """ Set new item in-place. Does not consolidate. Adds new Block if not contained in the current set of items """ value = extract_array(value, extract_numpy=True) # FIXME: refactor, clearly separate broadcasting & zip-like assignment # can prob also fix the various if tests for sparse/categorical if self._blklocs is None and self.ndim > 1: self._rebuild_blknos_and_blklocs() value_is_extension_type = is_extension_array_dtype(value) # categorical/sparse/datetimetz if value_is_extension_type: def value_getitem(placement): return value else: if value.ndim == 2: value = value.T if value.ndim == self.ndim - 1: value = safe_reshape(value, (1,) + value.shape) def value_getitem(placement): return value else: def value_getitem(placement): return value[placement.indexer] if value.shape[1:] != self.shape[1:]: raise AssertionError( "Shape of new values must be compatible with manager shape" ) if lib.is_integer(loc): # We have 6 tests where loc is _not_ an int. # In this case, get_blkno_placements will yield only one tuple, # containing (self._blknos[loc], BlockPlacement(slice(0, 1, 1))) loc = [loc] # Accessing public blknos ensures the public versions are initialized blknos = self.blknos[loc] blklocs = self.blklocs[loc].copy() unfit_mgr_locs = [] unfit_val_locs = [] removed_blknos = [] for blkno, val_locs in libinternals.get_blkno_placements(blknos, group=True): blk = self.blocks[blkno] blk_locs = blklocs[val_locs.indexer] if blk.should_store(value): blk.set_inplace(blk_locs, value_getitem(val_locs)) else: unfit_mgr_locs.append(blk.mgr_locs.as_array[blk_locs]) unfit_val_locs.append(val_locs) # If all block items are unfit, schedule the block for removal. if len(val_locs) == len(blk.mgr_locs): removed_blknos.append(blkno) else: blk.delete(blk_locs) self._blklocs[blk.mgr_locs.indexer] = np.arange(len(blk)) if len(removed_blknos): # Remove blocks & update blknos accordingly is_deleted = np.zeros(self.nblocks, dtype=np.bool_) is_deleted[removed_blknos] = True new_blknos = np.empty(self.nblocks, dtype=np.int64) new_blknos.fill(-1) new_blknos[~is_deleted] = np.arange(self.nblocks - len(removed_blknos)) self._blknos = new_blknos[self._blknos] self.blocks = tuple( blk for i, blk in enumerate(self.blocks) if i not in set(removed_blknos) ) if unfit_val_locs: unfit_mgr_locs = np.concatenate(unfit_mgr_locs) unfit_count = len(unfit_mgr_locs) new_blocks: List[Block] = [] if value_is_extension_type: # This code (ab-)uses the fact that EA blocks contain only # one item. # TODO(EA2D): special casing unnecessary with 2D EAs new_blocks.extend( make_block( values=value, ndim=self.ndim, placement=slice(mgr_loc, mgr_loc + 1), ) for mgr_loc in unfit_mgr_locs ) self._blknos[unfit_mgr_locs] = np.arange(unfit_count) + len(self.blocks) self._blklocs[unfit_mgr_locs] = 0 else: # unfit_val_locs contains BlockPlacement objects unfit_val_items = unfit_val_locs[0].append(unfit_val_locs[1:]) new_blocks.append( make_block( values=value_getitem(unfit_val_items), ndim=self.ndim, placement=unfit_mgr_locs, ) ) self._blknos[unfit_mgr_locs] = len(self.blocks) self._blklocs[unfit_mgr_locs] = np.arange(unfit_count) self.blocks += tuple(new_blocks) # Newly created block's dtype may already be present. self._known_consolidated = False def insert(self, loc: int, item: Hashable, value, allow_duplicates: bool = False): """ Insert item at selected position. Parameters ---------- loc : int item : hashable value : array_like allow_duplicates: bool If False, trying to insert non-unique item will raise """ if not allow_duplicates and item in self.items: # Should this be a different kind of error?? raise ValueError(f"cannot insert {item}, already exists") if not isinstance(loc, int): raise TypeError("loc must be int") # insert to the axis; this could possibly raise a TypeError new_axis = self.items.insert(loc, item) if value.ndim == 2: value = value.T if value.ndim == self.ndim - 1 and not is_extension_array_dtype(value.dtype): # TODO(EA2D): special case not needed with 2D EAs value = safe_reshape(value, (1,) + value.shape) block = make_block(values=value, ndim=self.ndim, placement=slice(loc, loc + 1)) for blkno, count in _fast_count_smallints(self.blknos[loc:]): blk = self.blocks[blkno] if count == len(blk.mgr_locs): blk.mgr_locs = blk.mgr_locs.add(1) else: new_mgr_locs = blk.mgr_locs.as_array.copy() new_mgr_locs[new_mgr_locs >= loc] += 1 blk.mgr_locs = new_mgr_locs # Accessing public blklocs ensures the public versions are initialized if loc == self.blklocs.shape[0]: # np.append is a lot faster, let's use it if we can. self._blklocs = np.append(self._blklocs, 0) self._blknos = np.append(self._blknos, len(self.blocks)) else: self._blklocs = np.insert(self._blklocs, loc, 0) self._blknos = np.insert(self._blknos, loc, len(self.blocks)) self.axes[0] = new_axis self.blocks += (block,) self._known_consolidated = False if len(self.blocks) > 100: warnings.warn( "DataFrame is highly fragmented. This is usually the result " "of calling `frame.insert` many times, which has poor performance. " "Consider using pd.concat instead. To get a de-fragmented frame, " "use `newframe = frame.copy()`", PerformanceWarning, stacklevel=5, ) def reindex_indexer( self: T, new_axis, indexer, axis: int, fill_value=None, allow_dups: bool = False, copy: bool = True, consolidate: bool = True, only_slice: bool = False, ) -> T: """ Parameters ---------- new_axis : Index indexer : ndarray of int64 or None axis : int fill_value : object, default None allow_dups : bool, default False copy : bool, default True consolidate: bool, default True Whether to consolidate inplace before reindexing. only_slice : bool, default False Whether to take views, not copies, along columns. pandas-indexer with -1's only. """ if indexer is None: if new_axis is self.axes[axis] and not copy: return self result = self.copy(deep=copy) result.axes = list(self.axes) result.axes[axis] = new_axis return result if consolidate: self._consolidate_inplace() # some axes don't allow reindexing with dups if not allow_dups: self.axes[axis]._can_reindex(indexer) if axis >= self.ndim: raise IndexError("Requested axis not found in manager") if axis == 0: new_blocks = self._slice_take_blocks_ax0( indexer, fill_value=fill_value, only_slice=only_slice ) else: new_blocks = [ blk.take_nd( indexer, axis=axis, fill_value=( fill_value if fill_value is not None else blk.fill_value ), ) for blk in self.blocks ] new_axes = list(self.axes) new_axes[axis] = new_axis return type(self).from_blocks(new_blocks, new_axes) def _slice_take_blocks_ax0( self, slice_or_indexer, fill_value=lib.no_default, only_slice: bool = False ): """ Slice/take blocks along axis=0. Overloaded for SingleBlock Parameters ---------- slice_or_indexer : slice, ndarray[bool], or list-like of ints fill_value : scalar, default lib.no_default only_slice : bool, default False If True, we always return views on existing arrays, never copies. This is used when called from ops.blockwise.operate_blockwise. Returns ------- new_blocks : list of Block """ allow_fill = fill_value is not lib.no_default sl_type, slobj, sllen = _preprocess_slice_or_indexer( slice_or_indexer, self.shape[0], allow_fill=allow_fill ) if self.is_single_block: blk = self.blocks[0] if sl_type in ("slice", "mask"): # GH#32959 EABlock would fail since we can't make 0-width # TODO(EA2D): special casing unnecessary with 2D EAs if sllen == 0: return [] return [blk.getitem_block(slobj, new_mgr_locs=slice(0, sllen))] elif not allow_fill or self.ndim == 1: if allow_fill and fill_value is None: fill_value = blk.fill_value if not allow_fill and only_slice: # GH#33597 slice instead of take, so we get # views instead of copies blocks = [ blk.getitem_block([ml], new_mgr_locs=i) for i, ml in enumerate(slobj) ] return blocks else: return [ blk.take_nd( slobj, axis=0, new_mgr_locs=slice(0, sllen), fill_value=fill_value, ) ] if sl_type in ("slice", "mask"): blknos = self.blknos[slobj] blklocs = self.blklocs[slobj] else: blknos = algos.take_nd( self.blknos, slobj, fill_value=-1, allow_fill=allow_fill ) blklocs = algos.take_nd( self.blklocs, slobj, fill_value=-1, allow_fill=allow_fill ) # When filling blknos, make sure blknos is updated before appending to # blocks list, that way new blkno is exactly len(blocks). blocks = [] group = not only_slice for blkno, mgr_locs in libinternals.get_blkno_placements(blknos, group=group): if blkno == -1: # If we've got here, fill_value was not lib.no_default blocks.append( self._make_na_block(placement=mgr_locs, fill_value=fill_value) ) else: blk = self.blocks[blkno] # Otherwise, slicing along items axis is necessary. if not blk._can_consolidate: # A non-consolidatable block, it's easy, because there's # only one item and each mgr loc is a copy of that single # item. for mgr_loc in mgr_locs: newblk = blk.copy(deep=False) newblk.mgr_locs = slice(mgr_loc, mgr_loc + 1) blocks.append(newblk) else: # GH#32779 to avoid the performance penalty of copying, # we may try to only slice taker = blklocs[mgr_locs.indexer] max_len = max(len(mgr_locs), taker.max() + 1) if only_slice: taker = lib.maybe_indices_to_slice(taker, max_len) if isinstance(taker, slice): nb = blk.getitem_block(taker, new_mgr_locs=mgr_locs) blocks.append(nb) elif only_slice: # GH#33597 slice instead of take, so we get # views instead of copies for i, ml in zip(taker, mgr_locs): nb = blk.getitem_block([i], new_mgr_locs=ml) blocks.append(nb) else: nb = blk.take_nd(taker, axis=0, new_mgr_locs=mgr_locs) blocks.append(nb) return blocks def _make_na_block(self, placement, fill_value=None): if fill_value is None: fill_value = np.nan block_shape = list(self.shape) block_shape[0] = len(placement) dtype, fill_value = infer_dtype_from_scalar(fill_value) block_values = np.empty(block_shape, dtype=dtype) block_values.fill(fill_value) return make_block(block_values, placement=placement, ndim=block_values.ndim) def take(self, indexer, axis: int = 1, verify: bool = True, convert: bool = True): """ Take items along any axis. """ indexer = ( np.arange(indexer.start, indexer.stop, indexer.step, dtype="int64") if isinstance(indexer, slice) else np.asanyarray(indexer, dtype="int64") ) n = self.shape[axis] if convert: indexer = maybe_convert_indices(indexer, n) if verify: if ((indexer == -1) | (indexer >= n)).any(): raise Exception("Indices must be nonzero and less than the axis length") new_labels = self.axes[axis].take(indexer) return self.reindex_indexer( new_axis=new_labels, indexer=indexer, axis=axis, allow_dups=True, consolidate=False, ) def _equal_values(self: T, other: T) -> bool: """ Used in .equals defined in base class. Only check the column values assuming shape and indexes have already been checked. """ if self.ndim == 1: # For SingleBlockManager (i.e.Series) if other.ndim != 1: return False left = self.blocks[0].values right = other.blocks[0].values return array_equals(left, right) return blockwise_all(self, other, array_equals) def unstack(self, unstacker, fill_value) -> BlockManager: """ Return a BlockManager with all blocks unstacked.. Parameters ---------- unstacker : reshape._Unstacker fill_value : Any fill_value for newly introduced missing values. Returns ------- unstacked : BlockManager """ new_columns = unstacker.get_new_columns(self.items) new_index = unstacker.new_index new_blocks: List[Block] = [] columns_mask: List[np.ndarray] = [] for blk in self.blocks: blk_cols = self.items[blk.mgr_locs.indexer] new_items = unstacker.get_new_columns(blk_cols) new_placement = new_columns.get_indexer(new_items) blocks, mask = blk._unstack( unstacker, fill_value, new_placement=new_placement ) new_blocks.extend(blocks) columns_mask.extend(mask) new_columns = new_columns[columns_mask] bm = BlockManager(new_blocks, [new_columns, new_index]) return bm class SingleBlockManager(BlockManager): """ manage a single block with """ ndim = 1 _is_consolidated = True _known_consolidated = True __slots__ = () is_single_block = True def __init__( self, block: Block, axis: Index, do_integrity_check: bool = False, fastpath=lib.no_default, ): assert isinstance(block, Block), type(block) assert isinstance(axis, Index), type(axis) if fastpath is not lib.no_default: warnings.warn( "The `fastpath` keyword is deprecated and will be removed " "in a future version.", FutureWarning, stacklevel=2, ) self.axes = [axis] self.blocks = (block,) @classmethod def from_blocks(cls, blocks: List[Block], axes: List[Index]) -> SingleBlockManager: """ Constructor for BlockManager and SingleBlockManager with same signature. """ assert len(blocks) == 1 assert len(axes) == 1 return cls(blocks[0], axes[0], do_integrity_check=False) @classmethod def from_array(cls, array: ArrayLike, index: Index) -> SingleBlockManager: """ Constructor for if we have an array that is not yet a Block. """ block = make_block(array, placement=slice(0, len(index)), ndim=1) return cls(block, index) def _post_setstate(self): pass @property def _block(self) -> Block: return self.blocks[0] @property def _blknos(self): """ compat with BlockManager """ return None @property def _blklocs(self): """ compat with BlockManager """ return None def get_slice(self, slobj: slice, axis: int = 0) -> SingleBlockManager: if axis >= self.ndim: raise IndexError("Requested axis not found in manager") blk = self._block array = blk._slice(slobj) block = blk.make_block_same_class(array, placement=slice(0, len(array))) return type(self)(block, self.index[slobj]) @property def index(self) -> Index: return self.axes[0] @property def dtype(self) -> DtypeObj: return self._block.dtype def get_dtypes(self) -> np.ndarray: return np.array([self._block.dtype]) def external_values(self): """The array that Series.values returns""" return self._block.external_values() def internal_values(self): """The array that Series._values returns""" return self._block.internal_values() @property def _can_hold_na(self) -> bool: return self._block._can_hold_na def is_consolidated(self) -> bool: return True def _consolidate_check(self): pass def _consolidate_inplace(self): pass def idelete(self, indexer): """ Delete single location from SingleBlockManager. Ensures that self.blocks doesn't become empty. """ self._block.delete(indexer) self.axes[0] = self.axes[0].delete(indexer) def fast_xs(self, loc): """ fast path for getting a cross-section return a view of the data """ raise NotImplementedError("Use series._values[loc] instead") # -------------------------------------------------------------------- # Constructor Helpers def create_block_manager_from_blocks(blocks, axes: List[Index]) -> BlockManager: try: if len(blocks) == 1 and not isinstance(blocks[0], Block): # if blocks[0] is of length 0, return empty blocks if not len(blocks[0]): blocks = [] else: # It's OK if a single block is passed as values, its placement # is basically "all items", but if there're many, don't bother # converting, it's an error anyway. blocks = [ make_block( values=blocks[0], placement=slice(0, len(axes[0])), ndim=2 ) ] mgr = BlockManager(blocks, axes) mgr._consolidate_inplace() return mgr except ValueError as e: blocks = [getattr(b, "values", b) for b in blocks] tot_items = sum(b.shape[0] for b in blocks) raise construction_error(tot_items, blocks[0].shape[1:], axes, e) def create_block_manager_from_arrays( arrays, names: Index, axes: List[Index] ) -> BlockManager: assert isinstance(names, Index) assert isinstance(axes, list) assert all(isinstance(x, Index) for x in axes) # ensure we dont have any PandasArrays when we call get_block_type # Note: just calling extract_array breaks tests that patch PandasArray._typ. arrays = [x if not isinstance(x, ABCPandasArray) else x.to_numpy() for x in arrays] try: blocks = _form_blocks(arrays, names, axes) mgr = BlockManager(blocks, axes) mgr._consolidate_inplace() return mgr except ValueError as e: raise construction_error(len(arrays), arrays[0].shape, axes, e) def construction_error(tot_items, block_shape, axes, e=None): """ raise a helpful message about our construction """ passed = tuple(map(int, [tot_items] + list(block_shape))) # Correcting the user facing error message during dataframe construction if len(passed) <= 2: passed = passed[::-1] implied = tuple(len(ax) for ax in axes) # Correcting the user facing error message during dataframe construction if len(implied) <= 2: implied = implied[::-1] # We return the exception object instead of raising it so that we # can raise it in the caller; mypy plays better with that if passed == implied and e is not None: return e if block_shape[0] == 0: return ValueError("Empty data passed with indices specified.") return ValueError(f"Shape of passed values is {passed}, indices imply {implied}") # ----------------------------------------------------------------------- def _form_blocks(arrays, names: Index, axes: List[Index]) -> List[Block]: # put "leftover" items in float bucket, where else? # generalize? items_dict: DefaultDict[str, List] = defaultdict(list) extra_locs = [] names_idx = names if names_idx.equals(axes[0]): names_indexer = np.arange(len(names_idx)) else: assert names_idx.intersection(axes[0]).is_unique names_indexer = names_idx.get_indexer_for(axes[0]) for i, name_idx in enumerate(names_indexer): if name_idx == -1: extra_locs.append(i) continue v = arrays[name_idx] block_type = get_block_type(v) items_dict[block_type.__name__].append((i, v)) blocks: List[Block] = [] if len(items_dict["FloatBlock"]): float_blocks = _multi_blockify(items_dict["FloatBlock"]) blocks.extend(float_blocks) if len(items_dict["NumericBlock"]): complex_blocks = _multi_blockify(items_dict["NumericBlock"]) blocks.extend(complex_blocks) if len(items_dict["TimeDeltaBlock"]): timedelta_blocks = _multi_blockify(items_dict["TimeDeltaBlock"]) blocks.extend(timedelta_blocks) if len(items_dict["DatetimeBlock"]): datetime_blocks = _simple_blockify(items_dict["DatetimeBlock"], DT64NS_DTYPE) blocks.extend(datetime_blocks) if len(items_dict["DatetimeTZBlock"]): dttz_blocks = [ make_block(array, klass=DatetimeTZBlock, placement=i, ndim=2) for i, array in items_dict["DatetimeTZBlock"] ] blocks.extend(dttz_blocks) if len(items_dict["ObjectBlock"]) > 0: object_blocks = _simple_blockify(items_dict["ObjectBlock"], np.object_) blocks.extend(object_blocks) if len(items_dict["CategoricalBlock"]) > 0: cat_blocks = [ make_block(array, klass=CategoricalBlock, placement=i, ndim=2) for i, array in items_dict["CategoricalBlock"] ] blocks.extend(cat_blocks) if len(items_dict["ExtensionBlock"]): external_blocks = [ make_block(array, klass=ExtensionBlock, placement=i, ndim=2) for i, array in items_dict["ExtensionBlock"] ] blocks.extend(external_blocks) if len(items_dict["ObjectValuesExtensionBlock"]): external_blocks = [ make_block(array, klass=ObjectValuesExtensionBlock, placement=i, ndim=2) for i, array in items_dict["ObjectValuesExtensionBlock"] ] blocks.extend(external_blocks) if len(extra_locs): shape = (len(extra_locs),) + tuple(len(x) for x in axes[1:]) # empty items -> dtype object block_values = np.empty(shape, dtype=object) block_values.fill(np.nan) na_block = make_block(block_values, placement=extra_locs, ndim=2) blocks.append(na_block) return blocks def _simple_blockify(tuples, dtype) -> List[Block]: """ return a single array of a block that has a single dtype; if dtype is not None, coerce to this dtype """ values, placement = _stack_arrays(tuples, dtype) # TODO: CHECK DTYPE? if dtype is not None and values.dtype != dtype: # pragma: no cover values = values.astype(dtype) block = make_block(values, placement=placement, ndim=2) return [block] def _multi_blockify(tuples, dtype: Optional[Dtype] = None): """ return an array of blocks that potentially have different dtypes """ # group by dtype grouper = itertools.groupby(tuples, lambda x: x[1].dtype) new_blocks = [] for dtype, tup_block in grouper: values, placement = _stack_arrays(list(tup_block), dtype) block = make_block(values, placement=placement, ndim=2) new_blocks.append(block) return new_blocks def _stack_arrays(tuples, dtype: np.dtype): # fml def _asarray_compat(x): if isinstance(x, ABCSeries): return x._values else: return np.asarray(x) placement, arrays = zip(*tuples) first = arrays[0] shape = (len(arrays),) + first.shape stacked = np.empty(shape, dtype=dtype) for i, arr in enumerate(arrays): stacked[i] = _asarray_compat(arr) return stacked, placement def _interleaved_dtype(blocks: Sequence[Block]) -> Optional[DtypeObj]: """ Find the common dtype for `blocks`. Parameters ---------- blocks : List[Block] Returns ------- dtype : np.dtype, ExtensionDtype, or None None is returned when `blocks` is empty. """ if not len(blocks): return None return find_common_type([b.dtype for b in blocks]) def _consolidate(blocks): """ Merge blocks having same dtype, exclude non-consolidating blocks """ # sort by _can_consolidate, dtype gkey = lambda x: x._consolidate_key grouper = itertools.groupby(sorted(blocks, key=gkey), gkey) new_blocks: List[Block] = [] for (_can_consolidate, dtype), group_blocks in grouper: merged_blocks = _merge_blocks( list(group_blocks), dtype=dtype, can_consolidate=_can_consolidate ) new_blocks = extend_blocks(merged_blocks, new_blocks) return new_blocks def _merge_blocks( blocks: List[Block], dtype: DtypeObj, can_consolidate: bool ) -> List[Block]: if len(blocks) == 1: return blocks if can_consolidate: if dtype is None: if len({b.dtype for b in blocks}) != 1: raise AssertionError("_merge_blocks are invalid!") # TODO: optimization potential in case all mgrs contain slices and # combination of those slices is a slice, too. new_mgr_locs = np.concatenate([b.mgr_locs.as_array for b in blocks]) new_values = np.vstack([b.values for b in blocks]) argsort = np.argsort(new_mgr_locs) new_values = new_values[argsort] new_mgr_locs = new_mgr_locs[argsort] return [make_block(new_values, placement=new_mgr_locs, ndim=2)] # can't consolidate --> no merge return blocks def _fast_count_smallints(arr: np.ndarray) -> np.ndarray: """Faster version of set(arr) for sequences of small numbers.""" counts = np.bincount(arr.astype(np.int_)) nz = counts.nonzero()[0] return np.c_[nz, counts[nz]] def _preprocess_slice_or_indexer(slice_or_indexer, length: int, allow_fill: bool): if isinstance(slice_or_indexer, slice): return ( "slice", slice_or_indexer, libinternals.slice_len(slice_or_indexer, length), ) elif ( isinstance(slice_or_indexer, np.ndarray) and slice_or_indexer.dtype == np.bool_ ): return "mask", slice_or_indexer, slice_or_indexer.sum() else: indexer = np.asanyarray(slice_or_indexer, dtype=np.int64) if not allow_fill: indexer = maybe_convert_indices(indexer, length) return "fancy", indexer, len(indexer)

32.175719

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0.574389

from __future__ import annotations from collections import defaultdict import itertools from typing import ( Any, Callable, DefaultDict, Dict, Hashable, List, Optional, Sequence, Tuple, TypeVar, Union, ) import warnings import numpy as np from pandas._libs import internals as libinternals, lib from pandas._typing import ArrayLike, Dtype, DtypeObj, Shape from pandas.errors import PerformanceWarning from pandas.util._validators import validate_bool_kwarg from pandas.core.dtypes.cast import find_common_type, infer_dtype_from_scalar from pandas.core.dtypes.common import ( DT64NS_DTYPE, is_dtype_equal, is_extension_array_dtype, is_list_like, ) from pandas.core.dtypes.dtypes import ExtensionDtype from pandas.core.dtypes.generic import ABCDataFrame, ABCPandasArray, ABCSeries from pandas.core.dtypes.missing import array_equals, isna import pandas.core.algorithms as algos from pandas.core.arrays.sparse import SparseDtype from pandas.core.construction import extract_array from pandas.core.indexers import maybe_convert_indices from pandas.core.indexes.api import Float64Index, Index, ensure_index from pandas.core.internals.base import DataManager from pandas.core.internals.blocks import ( Block, CategoricalBlock, DatetimeTZBlock, ExtensionBlock, ObjectValuesExtensionBlock, extend_blocks, get_block_type, make_block, safe_reshape, ) from pandas.core.internals.ops import blockwise_all, operate_blockwise T = TypeVar("T", bound="BlockManager") class BlockManager(DataManager): __slots__ = [ "axes", "blocks", "_known_consolidated", "_is_consolidated", "_blknos", "_blklocs", ] _blknos: np.ndarray _blklocs: np.ndarray def __init__( self, blocks: Sequence[Block], axes: Sequence[Index], do_integrity_check: bool = True, ): self.axes = [ensure_index(ax) for ax in axes] self.blocks: Tuple[Block, ...] = tuple(blocks) for block in blocks: if self.ndim != block.ndim: raise AssertionError( f"Number of Block dimensions ({block.ndim}) must equal " f"number of axes ({self.ndim})" ) if do_integrity_check: self._verify_integrity() self._known_consolidated = False self._blknos = None self._blklocs = None @classmethod def from_blocks(cls, blocks: List[Block], axes: List[Index]): return cls(blocks, axes, do_integrity_check=False) @property def blknos(self): if self._blknos is None: self._rebuild_blknos_and_blklocs() return self._blknos @property def blklocs(self): if self._blklocs is None: self._rebuild_blknos_and_blklocs() return self._blklocs def make_empty(self: T, axes=None) -> T: if axes is None: axes = [Index([])] + self.axes[1:] if self.ndim == 1: assert isinstance(self, SingleBlockManager) blk = self.blocks[0] arr = blk.values[:0] nb = blk.make_block_same_class(arr, placement=slice(0, 0), ndim=1) blocks = [nb] else: blocks = [] return type(self).from_blocks(blocks, axes) def __nonzero__(self) -> bool: return True __bool__ = __nonzero__ @property def shape(self) -> Shape: return tuple(len(ax) for ax in self.axes) @property def ndim(self) -> int: return len(self.axes) def set_axis(self, axis: int, new_labels: Index) -> None: old_len = len(self.axes[axis]) new_len = len(new_labels) if new_len != old_len: raise ValueError( f"Length mismatch: Expected axis has {old_len} elements, new " f"values have {new_len} elements" ) self.axes[axis] = new_labels @property def is_single_block(self) -> bool: return len(self.blocks) == 1 def _rebuild_blknos_and_blklocs(self) -> None: new_blknos = np.empty(self.shape[0], dtype=np.intp) new_blklocs = np.empty(self.shape[0], dtype=np.intp) new_blknos.fill(-1) new_blklocs.fill(-1) for blkno, blk in enumerate(self.blocks): rl = blk.mgr_locs new_blknos[rl.indexer] = blkno new_blklocs[rl.indexer] = np.arange(len(rl)) if (new_blknos == -1).any(): raise AssertionError("Gaps in blk ref_locs") self._blknos = new_blknos self._blklocs = new_blklocs @property def items(self) -> Index: return self.axes[0] def get_dtypes(self): dtypes = np.array([blk.dtype for blk in self.blocks]) return algos.take_nd(dtypes, self.blknos, allow_fill=False) def __getstate__(self): block_values = [b.values for b in self.blocks] block_items = [self.items[b.mgr_locs.indexer] for b in self.blocks] axes_array = list(self.axes) extra_state = { "0.14.1": { "axes": axes_array, "blocks": [ {"values": b.values, "mgr_locs": b.mgr_locs.indexer} for b in self.blocks ], } } # First three elements of the state are to maintain forward # compatibility with 0.13.1. return axes_array, block_values, block_items, extra_state def __setstate__(self, state): def unpickle_block(values, mgr_locs, ndim: int): # TODO(EA2D): ndim would be unnecessary with 2D EAs return make_block(values, placement=mgr_locs, ndim=ndim) if isinstance(state, tuple) and len(state) >= 4 and "0.14.1" in state[3]: state = state[3]["0.14.1"] self.axes = [ensure_index(ax) for ax in state["axes"]] ndim = len(self.axes) self.blocks = tuple( unpickle_block(b["values"], b["mgr_locs"], ndim=ndim) for b in state["blocks"] ) else: raise NotImplementedError("pre-0.14.1 pickles are no longer supported") self._post_setstate() def _post_setstate(self) -> None: self._is_consolidated = False self._known_consolidated = False self._rebuild_blknos_and_blklocs() def __len__(self) -> int: return len(self.items) def __repr__(self) -> str: output = type(self).__name__ for i, ax in enumerate(self.axes): if i == 0: output += f"\nItems: {ax}" else: output += f"\nAxis {i}: {ax}" for block in self.blocks: output += f"\n{block}" return output def _verify_integrity(self) -> None: mgr_shape = self.shape tot_items = sum(len(x.mgr_locs) for x in self.blocks) for block in self.blocks: if block.shape[1:] != mgr_shape[1:]: raise construction_error(tot_items, block.shape[1:], self.axes) if len(self.items) != tot_items: raise AssertionError( "Number of manager items must equal union of " f"block items\n# manager items: {len(self.items)}, # " f"tot_items: {tot_items}" ) def reduce( self: T, func: Callable, ignore_failures: bool = False ) -> Tuple[T, np.ndarray]: # If 2D, we assume that we're operating column-wise assert self.ndim == 2 res_blocks: List[Block] = [] for blk in self.blocks: nbs = blk.reduce(func, ignore_failures) res_blocks.extend(nbs) index = Index([None]) if ignore_failures: if res_blocks: indexer = np.concatenate([blk.mgr_locs.as_array for blk in res_blocks]) new_mgr = self._combine(res_blocks, copy=False, index=index) else: indexer = [] new_mgr = type(self).from_blocks([], [Index([]), index]) else: indexer = np.arange(self.shape[0]) new_mgr = type(self).from_blocks(res_blocks, [self.items, index]) return new_mgr, indexer def operate_blockwise(self, other: BlockManager, array_op) -> BlockManager: return operate_blockwise(self, other, array_op) def apply( self: T, f, align_keys: Optional[List[str]] = None, ignore_failures: bool = False, **kwargs, ) -> T: assert "filter" not in kwargs align_keys = align_keys or [] result_blocks: List[Block] = [] aligned_args = {k: kwargs[k] for k in align_keys} for b in self.blocks: if aligned_args: for k, obj in aligned_args.items(): if isinstance(obj, (ABCSeries, ABCDataFrame)): if obj.ndim == 1: kwargs[k] = obj.iloc[b.mgr_locs.indexer]._values else: kwargs[k] = obj.iloc[:, b.mgr_locs.indexer]._values else: kwargs[k] = obj[b.mgr_locs.indexer] try: if callable(f): applied = b.apply(f, **kwargs) else: applied = getattr(b, f)(**kwargs) except (TypeError, NotImplementedError): if not ignore_failures: raise continue result_blocks = extend_blocks(applied, result_blocks) if ignore_failures: return self._combine(result_blocks) if len(result_blocks) == 0: return self.make_empty(self.axes) return type(self).from_blocks(result_blocks, self.axes) def quantile( self, *, qs: Float64Index, axis: int = 0, transposed: bool = False, interpolation="linear", ) -> BlockManager: assert self.ndim >= 2 assert is_list_like(qs) assert axis == 1 new_axes = list(self.axes) new_axes[1] = Float64Index(qs) blocks = [ blk.quantile(axis=axis, qs=qs, interpolation=interpolation) for blk in self.blocks ] if transposed: new_axes = new_axes[::-1] blocks = [ b.make_block(b.values.T, placement=np.arange(b.shape[1])) for b in blocks ] return type(self)(blocks, new_axes) def isna(self, func) -> BlockManager: return self.apply("apply", func=func) def where(self, other, cond, align: bool, errors: str, axis: int) -> BlockManager: if align: align_keys = ["other", "cond"] else: align_keys = ["cond"] other = extract_array(other, extract_numpy=True) return self.apply( "where", align_keys=align_keys, other=other, cond=cond, errors=errors, axis=axis, ) def setitem(self, indexer, value) -> BlockManager: return self.apply("setitem", indexer=indexer, value=value) def putmask(self, mask, new, align: bool = True): if align: align_keys = ["new", "mask"] else: align_keys = ["mask"] new = extract_array(new, extract_numpy=True) return self.apply( "putmask", align_keys=align_keys, mask=mask, new=new, ) def diff(self, n: int, axis: int) -> BlockManager: return self.apply("diff", n=n, axis=axis) def interpolate(self, **kwargs) -> BlockManager: return self.apply("interpolate", **kwargs) def shift(self, periods: int, axis: int, fill_value) -> BlockManager: if fill_value is lib.no_default: fill_value = None if axis == 0 and self.ndim == 2 and self.nblocks > 1: if periods > 0: indexer = [-1] * periods + list(range(ncols - periods)) else: nper = abs(periods) indexer = list(range(nper, ncols)) + [-1] * nper result = self.reindex_indexer( self.items, indexer, axis=0, fill_value=fill_value, allow_dups=True, consolidate=False, ) return result return self.apply("shift", periods=periods, axis=axis, fill_value=fill_value) def fillna(self, value, limit, inplace: bool, downcast) -> BlockManager: return self.apply( "fillna", value=value, limit=limit, inplace=inplace, downcast=downcast ) def downcast(self) -> BlockManager: return self.apply("downcast") def astype(self, dtype, copy: bool = False, errors: str = "raise") -> BlockManager: return self.apply("astype", dtype=dtype, copy=copy, errors=errors) def convert( self, copy: bool = True, datetime: bool = True, numeric: bool = True, timedelta: bool = True, ) -> BlockManager: return self.apply( "convert", copy=copy, datetime=datetime, numeric=numeric, timedelta=timedelta, ) def replace(self, to_replace, value, inplace: bool, regex: bool) -> BlockManager: assert np.ndim(value) == 0, value return self.apply( "replace", to_replace=to_replace, value=value, inplace=inplace, regex=regex ) def replace_list( self: T, src_list: List[Any], dest_list: List[Any], inplace: bool = False, regex: bool = False, ) -> T: inplace = validate_bool_kwarg(inplace, "inplace") bm = self.apply( "_replace_list", src_list=src_list, dest_list=dest_list, inplace=inplace, regex=regex, ) bm._consolidate_inplace() return bm def to_native_types(self, **kwargs) -> BlockManager: return self.apply("to_native_types", **kwargs) def is_consolidated(self) -> bool: if not self._known_consolidated: self._consolidate_check() return self._is_consolidated def _consolidate_check(self) -> None: dtypes = [blk.dtype for blk in self.blocks if blk._can_consolidate] self._is_consolidated = len(dtypes) == len(set(dtypes)) self._known_consolidated = True @property def is_numeric_mixed_type(self) -> bool: return all(block.is_numeric for block in self.blocks) @property def any_extension_types(self) -> bool: return any(block.is_extension for block in self.blocks) @property def is_view(self) -> bool: if len(self.blocks) == 1: return self.blocks[0].is_view return False def get_bool_data(self, copy: bool = False) -> BlockManager: new_blocks = [] for blk in self.blocks: if blk.dtype == bool: new_blocks.append(blk) elif blk.is_object: nbs = blk._split() for nb in nbs: if nb.is_bool: new_blocks.append(nb) return self._combine(new_blocks, copy) def get_numeric_data(self, copy: bool = False) -> BlockManager: return self._combine([b for b in self.blocks if b.is_numeric], copy) def _combine( self: T, blocks: List[Block], copy: bool = True, index: Optional[Index] = None ) -> T: if len(blocks) == 0: return self.make_empty() indexer = np.sort(np.concatenate([b.mgr_locs.as_array for b in blocks])) inv_indexer = lib.get_reverse_indexer(indexer, self.shape[0]) new_blocks: List[Block] = [] for b in blocks: b = b.copy(deep=copy) b.mgr_locs = inv_indexer[b.mgr_locs.indexer] new_blocks.append(b) axes = list(self.axes) if index is not None: axes[-1] = index axes[0] = self.items.take(indexer) return type(self).from_blocks(new_blocks, axes) def get_slice(self, slobj: slice, axis: int = 0) -> BlockManager: if axis == 0: new_blocks = self._slice_take_blocks_ax0(slobj) elif axis == 1: slicer = (slice(None), slobj) new_blocks = [blk.getitem_block(slicer) for blk in self.blocks] else: raise IndexError("Requested axis not found in manager") new_axes = list(self.axes) new_axes[axis] = new_axes[axis][slobj] bm = type(self)(new_blocks, new_axes, do_integrity_check=False) return bm @property def nblocks(self) -> int: return len(self.blocks) def copy(self: T, deep=True) -> T: if deep: def copy_func(ax): return ax.copy(deep=True) if deep == "all" else ax.view() new_axes = [copy_func(ax) for ax in self.axes] else: new_axes = list(self.axes) res = self.apply("copy", deep=deep) res.axes = new_axes return res def as_array( self, transpose: bool = False, dtype: Optional[Dtype] = None, copy: bool = False, na_value=lib.no_default, ) -> np.ndarray: if len(self.blocks) == 0: arr = np.empty(self.shape, dtype=float) return arr.transpose() if transpose else arr copy = copy or na_value is not lib.no_default if self.is_single_block: blk = self.blocks[0] if blk.is_extension: arr = blk.values.to_numpy(dtype=dtype, na_value=na_value).reshape( blk.shape ) else: arr = np.asarray(blk.get_values()) if dtype: arr = arr.astype(dtype, copy=False) else: arr = self._interleave(dtype=dtype, na_value=na_value) copy = False if copy: arr = arr.copy() if na_value is not lib.no_default: arr[isna(arr)] = na_value return arr.transpose() if transpose else arr def _interleave( self, dtype: Optional[Dtype] = None, na_value=lib.no_default ) -> np.ndarray: if not dtype: dtype = _interleaved_dtype(self.blocks) if isinstance(dtype, SparseDtype): dtype = dtype.subtype elif is_extension_array_dtype(dtype): dtype = "object" elif is_dtype_equal(dtype, str): dtype = "object" result = np.empty(self.shape, dtype=dtype) itemmask = np.zeros(self.shape[0]) for blk in self.blocks: rl = blk.mgr_locs if blk.is_extension: arr = blk.values.to_numpy(dtype=dtype, na_value=na_value) else: arr = blk.get_values(dtype) result[rl.indexer] = arr itemmask[rl.indexer] = 1 if not itemmask.all(): raise AssertionError("Some items were not contained in blocks") return result def to_dict(self, copy: bool = True): bd: Dict[str, List[Block]] = {} for b in self.blocks: bd.setdefault(str(b.dtype), []).append(b) return {dtype: self._combine(blocks, copy=copy) for dtype, blocks in bd.items()} def fast_xs(self, loc: int) -> ArrayLike: if len(self.blocks) == 1: return self.blocks[0].iget((slice(None), loc)) dtype = _interleaved_dtype(self.blocks) n = len(self) if is_extension_array_dtype(dtype): result = np.empty(n, dtype=object) else: result = np.empty(n, dtype=dtype) for blk in self.blocks: # Such assignment may incorrectly coerce NaT to None # result[blk.mgr_locs] = blk._slice((slice(None), loc)) for i, rl in enumerate(blk.mgr_locs): result[rl] = blk.iget((i, loc)) if isinstance(dtype, ExtensionDtype): result = dtype.construct_array_type()._from_sequence(result, dtype=dtype) return result def consolidate(self) -> BlockManager: if self.is_consolidated(): return self bm = type(self)(self.blocks, self.axes) bm._is_consolidated = False bm._consolidate_inplace() return bm def _consolidate_inplace(self) -> None: if not self.is_consolidated(): self.blocks = tuple(_consolidate(self.blocks)) self._is_consolidated = True self._known_consolidated = True self._rebuild_blknos_and_blklocs() def iget(self, i: int) -> SingleBlockManager: block = self.blocks[self.blknos[i]] values = block.iget(self.blklocs[i]) # shortcut for select a single-dim from a 2-dim BM return SingleBlockManager( block.make_block_same_class( values, placement=slice(0, len(values)), ndim=1 ), self.axes[1], ) def iget_values(self, i: int) -> ArrayLike: block = self.blocks[self.blknos[i]] values = block.iget(self.blklocs[i]) return values def idelete(self, indexer): is_deleted = np.zeros(self.shape[0], dtype=np.bool_) is_deleted[indexer] = True ref_loc_offset = -is_deleted.cumsum() is_blk_deleted = [False] * len(self.blocks) if isinstance(indexer, int): affected_start = indexer else: affected_start = is_deleted.nonzero()[0][0] for blkno, _ in _fast_count_smallints(self.blknos[affected_start:]): blk = self.blocks[blkno] bml = blk.mgr_locs blk_del = is_deleted[bml.indexer].nonzero()[0] if len(blk_del) == len(bml): is_blk_deleted[blkno] = True continue elif len(blk_del) != 0: blk.delete(blk_del) bml = blk.mgr_locs blk.mgr_locs = bml.add(ref_loc_offset[bml.indexer]) # FIXME: use Index.delete as soon as it uses fastpath=True self.axes[0] = self.items[~is_deleted] self.blocks = tuple( b for blkno, b in enumerate(self.blocks) if not is_blk_deleted[blkno] ) self._rebuild_blknos_and_blklocs() def iset(self, loc: Union[int, slice, np.ndarray], value): value = extract_array(value, extract_numpy=True) # FIXME: refactor, clearly separate broadcasting & zip-like assignment # can prob also fix the various if tests for sparse/categorical if self._blklocs is None and self.ndim > 1: self._rebuild_blknos_and_blklocs() value_is_extension_type = is_extension_array_dtype(value) # categorical/sparse/datetimetz if value_is_extension_type: def value_getitem(placement): return value else: if value.ndim == 2: value = value.T if value.ndim == self.ndim - 1: value = safe_reshape(value, (1,) + value.shape) def value_getitem(placement): return value else: def value_getitem(placement): return value[placement.indexer] if value.shape[1:] != self.shape[1:]: raise AssertionError( "Shape of new values must be compatible with manager shape" ) if lib.is_integer(loc): # We have 6 tests where loc is _not_ an int. # In this case, get_blkno_placements will yield only one tuple, # containing (self._blknos[loc], BlockPlacement(slice(0, 1, 1))) loc = [loc] # Accessing public blknos ensures the public versions are initialized blknos = self.blknos[loc] blklocs = self.blklocs[loc].copy() unfit_mgr_locs = [] unfit_val_locs = [] removed_blknos = [] for blkno, val_locs in libinternals.get_blkno_placements(blknos, group=True): blk = self.blocks[blkno] blk_locs = blklocs[val_locs.indexer] if blk.should_store(value): blk.set_inplace(blk_locs, value_getitem(val_locs)) else: unfit_mgr_locs.append(blk.mgr_locs.as_array[blk_locs]) unfit_val_locs.append(val_locs) # If all block items are unfit, schedule the block for removal. if len(val_locs) == len(blk.mgr_locs): removed_blknos.append(blkno) else: blk.delete(blk_locs) self._blklocs[blk.mgr_locs.indexer] = np.arange(len(blk)) if len(removed_blknos): # Remove blocks & update blknos accordingly is_deleted = np.zeros(self.nblocks, dtype=np.bool_) is_deleted[removed_blknos] = True new_blknos = np.empty(self.nblocks, dtype=np.int64) new_blknos.fill(-1) new_blknos[~is_deleted] = np.arange(self.nblocks - len(removed_blknos)) self._blknos = new_blknos[self._blknos] self.blocks = tuple( blk for i, blk in enumerate(self.blocks) if i not in set(removed_blknos) ) if unfit_val_locs: unfit_mgr_locs = np.concatenate(unfit_mgr_locs) unfit_count = len(unfit_mgr_locs) new_blocks: List[Block] = [] if value_is_extension_type: # This code (ab-)uses the fact that EA blocks contain only # one item. # TODO(EA2D): special casing unnecessary with 2D EAs new_blocks.extend( make_block( values=value, ndim=self.ndim, placement=slice(mgr_loc, mgr_loc + 1), ) for mgr_loc in unfit_mgr_locs ) self._blknos[unfit_mgr_locs] = np.arange(unfit_count) + len(self.blocks) self._blklocs[unfit_mgr_locs] = 0 else: # unfit_val_locs contains BlockPlacement objects unfit_val_items = unfit_val_locs[0].append(unfit_val_locs[1:]) new_blocks.append( make_block( values=value_getitem(unfit_val_items), ndim=self.ndim, placement=unfit_mgr_locs, ) ) self._blknos[unfit_mgr_locs] = len(self.blocks) self._blklocs[unfit_mgr_locs] = np.arange(unfit_count) self.blocks += tuple(new_blocks) # Newly created block's dtype may already be present. self._known_consolidated = False def insert(self, loc: int, item: Hashable, value, allow_duplicates: bool = False): if not allow_duplicates and item in self.items: raise ValueError(f"cannot insert {item}, already exists") if not isinstance(loc, int): raise TypeError("loc must be int") new_axis = self.items.insert(loc, item) if value.ndim == 2: value = value.T if value.ndim == self.ndim - 1 and not is_extension_array_dtype(value.dtype): value = safe_reshape(value, (1,) + value.shape) block = make_block(values=value, ndim=self.ndim, placement=slice(loc, loc + 1)) for blkno, count in _fast_count_smallints(self.blknos[loc:]): blk = self.blocks[blkno] if count == len(blk.mgr_locs): blk.mgr_locs = blk.mgr_locs.add(1) else: new_mgr_locs = blk.mgr_locs.as_array.copy() new_mgr_locs[new_mgr_locs >= loc] += 1 blk.mgr_locs = new_mgr_locs if loc == self.blklocs.shape[0]: self._blklocs = np.append(self._blklocs, 0) self._blknos = np.append(self._blknos, len(self.blocks)) else: self._blklocs = np.insert(self._blklocs, loc, 0) self._blknos = np.insert(self._blknos, loc, len(self.blocks)) self.axes[0] = new_axis self.blocks += (block,) self._known_consolidated = False if len(self.blocks) > 100: warnings.warn( "DataFrame is highly fragmented. This is usually the result " "of calling `frame.insert` many times, which has poor performance. " "Consider using pd.concat instead. To get a de-fragmented frame, " "use `newframe = frame.copy()`", PerformanceWarning, stacklevel=5, ) def reindex_indexer( self: T, new_axis, indexer, axis: int, fill_value=None, allow_dups: bool = False, copy: bool = True, consolidate: bool = True, only_slice: bool = False, ) -> T: if indexer is None: if new_axis is self.axes[axis] and not copy: return self result = self.copy(deep=copy) result.axes = list(self.axes) result.axes[axis] = new_axis return result if consolidate: self._consolidate_inplace() # some axes don't allow reindexing with dups if not allow_dups: self.axes[axis]._can_reindex(indexer) if axis >= self.ndim: raise IndexError("Requested axis not found in manager") if axis == 0: new_blocks = self._slice_take_blocks_ax0( indexer, fill_value=fill_value, only_slice=only_slice ) else: new_blocks = [ blk.take_nd( indexer, axis=axis, fill_value=( fill_value if fill_value is not None else blk.fill_value ), ) for blk in self.blocks ] new_axes = list(self.axes) new_axes[axis] = new_axis return type(self).from_blocks(new_blocks, new_axes) def _slice_take_blocks_ax0( self, slice_or_indexer, fill_value=lib.no_default, only_slice: bool = False ): allow_fill = fill_value is not lib.no_default sl_type, slobj, sllen = _preprocess_slice_or_indexer( slice_or_indexer, self.shape[0], allow_fill=allow_fill ) if self.is_single_block: blk = self.blocks[0] if sl_type in ("slice", "mask"): sary with 2D EAs if sllen == 0: return [] return [blk.getitem_block(slobj, new_mgr_locs=slice(0, sllen))] elif not allow_fill or self.ndim == 1: if allow_fill and fill_value is None: fill_value = blk.fill_value if not allow_fill and only_slice: # GH#33597 slice instead of take, so we get # views instead of copies blocks = [ blk.getitem_block([ml], new_mgr_locs=i) for i, ml in enumerate(slobj) ] return blocks else: return [ blk.take_nd( slobj, axis=0, new_mgr_locs=slice(0, sllen), fill_value=fill_value, ) ] if sl_type in ("slice", "mask"): blknos = self.blknos[slobj] blklocs = self.blklocs[slobj] else: blknos = algos.take_nd( self.blknos, slobj, fill_value=-1, allow_fill=allow_fill ) blklocs = algos.take_nd( self.blklocs, slobj, fill_value=-1, allow_fill=allow_fill ) # When filling blknos, make sure blknos is updated before appending to # blocks list, that way new blkno is exactly len(blocks). blocks = [] group = not only_slice for blkno, mgr_locs in libinternals.get_blkno_placements(blknos, group=group): if blkno == -1: # If we've got here, fill_value was not lib.no_default blocks.append( self._make_na_block(placement=mgr_locs, fill_value=fill_value) ) else: blk = self.blocks[blkno] if not blk._can_consolidate: for mgr_loc in mgr_locs: newblk = blk.copy(deep=False) newblk.mgr_locs = slice(mgr_loc, mgr_loc + 1) blocks.append(newblk) else: lklocs[mgr_locs.indexer] max_len = max(len(mgr_locs), taker.max() + 1) if only_slice: taker = lib.maybe_indices_to_slice(taker, max_len) if isinstance(taker, slice): nb = blk.getitem_block(taker, new_mgr_locs=mgr_locs) blocks.append(nb) elif only_slice: for i, ml in zip(taker, mgr_locs): nb = blk.getitem_block([i], new_mgr_locs=ml) blocks.append(nb) else: nb = blk.take_nd(taker, axis=0, new_mgr_locs=mgr_locs) blocks.append(nb) return blocks def _make_na_block(self, placement, fill_value=None): if fill_value is None: fill_value = np.nan block_shape = list(self.shape) block_shape[0] = len(placement) dtype, fill_value = infer_dtype_from_scalar(fill_value) block_values = np.empty(block_shape, dtype=dtype) block_values.fill(fill_value) return make_block(block_values, placement=placement, ndim=block_values.ndim) def take(self, indexer, axis: int = 1, verify: bool = True, convert: bool = True): indexer = ( np.arange(indexer.start, indexer.stop, indexer.step, dtype="int64") if isinstance(indexer, slice) else np.asanyarray(indexer, dtype="int64") ) n = self.shape[axis] if convert: indexer = maybe_convert_indices(indexer, n) if verify: if ((indexer == -1) | (indexer >= n)).any(): raise Exception("Indices must be nonzero and less than the axis length") new_labels = self.axes[axis].take(indexer) return self.reindex_indexer( new_axis=new_labels, indexer=indexer, axis=axis, allow_dups=True, consolidate=False, ) def _equal_values(self: T, other: T) -> bool: if self.ndim == 1: if other.ndim != 1: return False left = self.blocks[0].values right = other.blocks[0].values return array_equals(left, right) return blockwise_all(self, other, array_equals) def unstack(self, unstacker, fill_value) -> BlockManager: new_columns = unstacker.get_new_columns(self.items) new_index = unstacker.new_index new_blocks: List[Block] = [] columns_mask: List[np.ndarray] = [] for blk in self.blocks: blk_cols = self.items[blk.mgr_locs.indexer] new_items = unstacker.get_new_columns(blk_cols) new_placement = new_columns.get_indexer(new_items) blocks, mask = blk._unstack( unstacker, fill_value, new_placement=new_placement ) new_blocks.extend(blocks) columns_mask.extend(mask) new_columns = new_columns[columns_mask] bm = BlockManager(new_blocks, [new_columns, new_index]) return bm class SingleBlockManager(BlockManager): ndim = 1 _is_consolidated = True _known_consolidated = True __slots__ = () is_single_block = True def __init__( self, block: Block, axis: Index, do_integrity_check: bool = False, fastpath=lib.no_default, ): assert isinstance(block, Block), type(block) assert isinstance(axis, Index), type(axis) if fastpath is not lib.no_default: warnings.warn( "The `fastpath` keyword is deprecated and will be removed " "in a future version.", FutureWarning, stacklevel=2, ) self.axes = [axis] self.blocks = (block,) @classmethod def from_blocks(cls, blocks: List[Block], axes: List[Index]) -> SingleBlockManager: assert len(blocks) == 1 assert len(axes) == 1 return cls(blocks[0], axes[0], do_integrity_check=False) @classmethod def from_array(cls, array: ArrayLike, index: Index) -> SingleBlockManager: block = make_block(array, placement=slice(0, len(index)), ndim=1) return cls(block, index) def _post_setstate(self): pass @property def _block(self) -> Block: return self.blocks[0] @property def _blknos(self): return None @property def _blklocs(self): return None def get_slice(self, slobj: slice, axis: int = 0) -> SingleBlockManager: if axis >= self.ndim: raise IndexError("Requested axis not found in manager") blk = self._block array = blk._slice(slobj) block = blk.make_block_same_class(array, placement=slice(0, len(array))) return type(self)(block, self.index[slobj]) @property def index(self) -> Index: return self.axes[0] @property def dtype(self) -> DtypeObj: return self._block.dtype def get_dtypes(self) -> np.ndarray: return np.array([self._block.dtype]) def external_values(self): return self._block.external_values() def internal_values(self): return self._block.internal_values() @property def _can_hold_na(self) -> bool: return self._block._can_hold_na def is_consolidated(self) -> bool: return True def _consolidate_check(self): pass def _consolidate_inplace(self): pass def idelete(self, indexer): self._block.delete(indexer) self.axes[0] = self.axes[0].delete(indexer) def fast_xs(self, loc): raise NotImplementedError("Use series._values[loc] instead") def create_block_manager_from_blocks(blocks, axes: List[Index]) -> BlockManager: try: if len(blocks) == 1 and not isinstance(blocks[0], Block): if not len(blocks[0]): blocks = [] else: # is basically "all items", but if there're many, don't bother # converting, it's an error anyway. blocks = [ make_block( values=blocks[0], placement=slice(0, len(axes[0])), ndim=2 ) ] mgr = BlockManager(blocks, axes) mgr._consolidate_inplace() return mgr except ValueError as e: blocks = [getattr(b, "values", b) for b in blocks] tot_items = sum(b.shape[0] for b in blocks) raise construction_error(tot_items, blocks[0].shape[1:], axes, e) def create_block_manager_from_arrays( arrays, names: Index, axes: List[Index] ) -> BlockManager: assert isinstance(names, Index) assert isinstance(axes, list) assert all(isinstance(x, Index) for x in axes) arrays = [x if not isinstance(x, ABCPandasArray) else x.to_numpy() for x in arrays] try: blocks = _form_blocks(arrays, names, axes) mgr = BlockManager(blocks, axes) mgr._consolidate_inplace() return mgr except ValueError as e: raise construction_error(len(arrays), arrays[0].shape, axes, e) def construction_error(tot_items, block_shape, axes, e=None): passed = tuple(map(int, [tot_items] + list(block_shape))) if len(passed) <= 2: passed = passed[::-1] implied = tuple(len(ax) for ax in axes) if len(implied) <= 2: implied = implied[::-1] if passed == implied and e is not None: return e if block_shape[0] == 0: return ValueError("Empty data passed with indices specified.") return ValueError(f"Shape of passed values is {passed}, indices imply {implied}") def _form_blocks(arrays, names: Index, axes: List[Index]) -> List[Block]: items_dict: DefaultDict[str, List] = defaultdict(list) extra_locs = [] names_idx = names if names_idx.equals(axes[0]): names_indexer = np.arange(len(names_idx)) else: assert names_idx.intersection(axes[0]).is_unique names_indexer = names_idx.get_indexer_for(axes[0]) for i, name_idx in enumerate(names_indexer): if name_idx == -1: extra_locs.append(i) continue v = arrays[name_idx] block_type = get_block_type(v) items_dict[block_type.__name__].append((i, v)) blocks: List[Block] = [] if len(items_dict["FloatBlock"]): float_blocks = _multi_blockify(items_dict["FloatBlock"]) blocks.extend(float_blocks) if len(items_dict["NumericBlock"]): complex_blocks = _multi_blockify(items_dict["NumericBlock"]) blocks.extend(complex_blocks) if len(items_dict["TimeDeltaBlock"]): timedelta_blocks = _multi_blockify(items_dict["TimeDeltaBlock"]) blocks.extend(timedelta_blocks) if len(items_dict["DatetimeBlock"]): datetime_blocks = _simple_blockify(items_dict["DatetimeBlock"], DT64NS_DTYPE) blocks.extend(datetime_blocks) if len(items_dict["DatetimeTZBlock"]): dttz_blocks = [ make_block(array, klass=DatetimeTZBlock, placement=i, ndim=2) for i, array in items_dict["DatetimeTZBlock"] ] blocks.extend(dttz_blocks) if len(items_dict["ObjectBlock"]) > 0: object_blocks = _simple_blockify(items_dict["ObjectBlock"], np.object_) blocks.extend(object_blocks) if len(items_dict["CategoricalBlock"]) > 0: cat_blocks = [ make_block(array, klass=CategoricalBlock, placement=i, ndim=2) for i, array in items_dict["CategoricalBlock"] ] blocks.extend(cat_blocks) if len(items_dict["ExtensionBlock"]): external_blocks = [ make_block(array, klass=ExtensionBlock, placement=i, ndim=2) for i, array in items_dict["ExtensionBlock"] ] blocks.extend(external_blocks) if len(items_dict["ObjectValuesExtensionBlock"]): external_blocks = [ make_block(array, klass=ObjectValuesExtensionBlock, placement=i, ndim=2) for i, array in items_dict["ObjectValuesExtensionBlock"] ] blocks.extend(external_blocks) if len(extra_locs): shape = (len(extra_locs),) + tuple(len(x) for x in axes[1:]) block_values = np.empty(shape, dtype=object) block_values.fill(np.nan) na_block = make_block(block_values, placement=extra_locs, ndim=2) blocks.append(na_block) return blocks def _simple_blockify(tuples, dtype) -> List[Block]: values, placement = _stack_arrays(tuples, dtype) if dtype is not None and values.dtype != dtype: values = values.astype(dtype) block = make_block(values, placement=placement, ndim=2) return [block] def _multi_blockify(tuples, dtype: Optional[Dtype] = None): grouper = itertools.groupby(tuples, lambda x: x[1].dtype) new_blocks = [] for dtype, tup_block in grouper: values, placement = _stack_arrays(list(tup_block), dtype) block = make_block(values, placement=placement, ndim=2) new_blocks.append(block) return new_blocks def _stack_arrays(tuples, dtype: np.dtype): def _asarray_compat(x): if isinstance(x, ABCSeries): return x._values else: return np.asarray(x) placement, arrays = zip(*tuples) first = arrays[0] shape = (len(arrays),) + first.shape stacked = np.empty(shape, dtype=dtype) for i, arr in enumerate(arrays): stacked[i] = _asarray_compat(arr) return stacked, placement def _interleaved_dtype(blocks: Sequence[Block]) -> Optional[DtypeObj]: if not len(blocks): return None return find_common_type([b.dtype for b in blocks]) def _consolidate(blocks): gkey = lambda x: x._consolidate_key grouper = itertools.groupby(sorted(blocks, key=gkey), gkey) new_blocks: List[Block] = [] for (_can_consolidate, dtype), group_blocks in grouper: merged_blocks = _merge_blocks( list(group_blocks), dtype=dtype, can_consolidate=_can_consolidate ) new_blocks = extend_blocks(merged_blocks, new_blocks) return new_blocks def _merge_blocks( blocks: List[Block], dtype: DtypeObj, can_consolidate: bool ) -> List[Block]: if len(blocks) == 1: return blocks if can_consolidate: if dtype is None: if len({b.dtype for b in blocks}) != 1: raise AssertionError("_merge_blocks are invalid!") new_mgr_locs = np.concatenate([b.mgr_locs.as_array for b in blocks]) new_values = np.vstack([b.values for b in blocks]) argsort = np.argsort(new_mgr_locs) new_values = new_values[argsort] new_mgr_locs = new_mgr_locs[argsort] return [make_block(new_values, placement=new_mgr_locs, ndim=2)] return blocks def _fast_count_smallints(arr: np.ndarray) -> np.ndarray: counts = np.bincount(arr.astype(np.int_)) nz = counts.nonzero()[0] return np.c_[nz, counts[nz]] def _preprocess_slice_or_indexer(slice_or_indexer, length: int, allow_fill: bool): if isinstance(slice_or_indexer, slice): return ( "slice", slice_or_indexer, libinternals.slice_len(slice_or_indexer, length), ) elif ( isinstance(slice_or_indexer, np.ndarray) and slice_or_indexer.dtype == np.bool_ ): return "mask", slice_or_indexer, slice_or_indexer.sum() else: indexer = np.asanyarray(slice_or_indexer, dtype=np.int64) if not allow_fill: indexer = maybe_convert_indices(indexer, length) return "fancy", indexer, len(indexer)

true

1c45b3d5de333d6534be0122ea89da552988ca0c

601

py

Python

tests/changes/api/test_build_mark_seen.py

bowlofstew/changes

ebd393520e0fdb07c240a8d4e8747281b6186e28

[ "Apache-2.0" ]

1

2015-11-08T13:00:44.000Z

tests/changes/api/test_build_mark_seen.py

alex/changes

69a17b4c639e7082a75d037384ccb68ead3a0b4b

[ "Apache-2.0" ]

null

tests/changes/api/test_build_mark_seen.py

alex/changes

69a17b4c639e7082a75d037384ccb68ead3a0b4b

[ "Apache-2.0" ]

null

from changes.models import BuildSeen from changes.testutils import APITestCase class BuildMarkSeenTest(APITestCase): def test_simple(self): project = self.create_project() build = self.create_build(project=project) self.login_default() path = '/api/0/builds/{0}/mark_seen/'.format(build.id.hex) resp = self.client.post(path) assert resp.status_code == 200 buildseen = BuildSeen.query.filter( BuildSeen.user_id == self.default_user.id, BuildSeen.build_id == build.id, ).first() assert buildseen

26.130435

66

0.648918

from changes.models import BuildSeen from changes.testutils import APITestCase class BuildMarkSeenTest(APITestCase): def test_simple(self): project = self.create_project() build = self.create_build(project=project) self.login_default() path = '/api/0/builds/{0}/mark_seen/'.format(build.id.hex) resp = self.client.post(path) assert resp.status_code == 200 buildseen = BuildSeen.query.filter( BuildSeen.user_id == self.default_user.id, BuildSeen.build_id == build.id, ).first() assert buildseen

true

1c45b4011172fbf7f667e12379db8e0b37a73ae8

644

py

Python

WebFilm/urls.py

marekbaranowski98/WebFilm

5d78bb9518070c195feffc2181735b93be019ca0

[ "MIT" ]

null

WebFilm/urls.py

marekbaranowski98/WebFilm

5d78bb9518070c195feffc2181735b93be019ca0

[ "MIT" ]

null

WebFilm/urls.py

marekbaranowski98/WebFilm

5d78bb9518070c195feffc2181735b93be019ca0

[ "MIT" ]

null

"""WebFilm URL Configuration path docs/ loads url from apps docs path / loads url from apps frontend path api/users/ loads url from apps users path api/photos loads url from app photos path api/movies loads url from app movies """ from django.contrib import admin from django.urls import path, include urlpatterns = [ path('admin/', admin.site.urls), path('docs/', include('docs.urls')), path('api/users/', include('users.urls')), path('api/photos/', include('photos.urls')), path('api/movies/', include('movies.urls')), path('api/evaluations/', include('evaluations.urls')), path('', include('frontend.urls')), ]

30.666667

58

0.692547

from django.contrib import admin from django.urls import path, include urlpatterns = [ path('admin/', admin.site.urls), path('docs/', include('docs.urls')), path('api/users/', include('users.urls')), path('api/photos/', include('photos.urls')), path('api/movies/', include('movies.urls')), path('api/evaluations/', include('evaluations.urls')), path('', include('frontend.urls')), ]

true

1c45b4b0875ea7d446dba15109b8e98b5d4bdaab

3,439

py

Python

libqtile/widget/windowname.py

Bauthe/qtile

569c4d9aaad1dbd912435648f5f814e084de8365

[ "MIT" ]

null

libqtile/widget/windowname.py

Bauthe/qtile

569c4d9aaad1dbd912435648f5f814e084de8365

[ "MIT" ]

null

libqtile/widget/windowname.py

Bauthe/qtile

569c4d9aaad1dbd912435648f5f814e084de8365

[ "MIT" ]

null

# Copyright (c) 2008, 2010 Aldo Cortesi # Copyright (c) 2010 matt # Copyright (c) 2011 Mounier Florian # Copyright (c) 2012 Tim Neumann # Copyright (c) 2013 Craig Barnes # Copyright (c) 2014 Sean Vig # Copyright (c) 2014 Tycho Andersen # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. from libqtile import bar, hook, pangocffi from libqtile.widget import base class WindowName(base._TextBox): """Displays the name of the window that currently has focus""" orientations = base.ORIENTATION_HORIZONTAL defaults = [ ('for_current_screen', False, 'instead of this bars screen use currently active screen'), ('empty_group_string', ' ', 'string to display when no windows are focused on current group'), ('max_chars', 0, 'max chars before truncating with ellipsis'), ('format', '{state}{name}', 'format of the text'), ] def __init__(self, width=bar.STRETCH, **config): base._TextBox.__init__(self, width=width, **config) self.add_defaults(WindowName.defaults) def _configure(self, qtile, bar): base._TextBox._configure(self, qtile, bar) hook.subscribe.client_name_updated(self.update) hook.subscribe.focus_change(self.update) hook.subscribe.float_change(self.update) @hook.subscribe.current_screen_change def on_screen_changed(): if self.for_current_screen: self.update() def truncate(self, text): if self.max_chars == 0: return text return (text[:self.max_chars - 3].rstrip() + "...") if len(text) > self.max_chars else text def update(self, *args): if self.for_current_screen: w = self.qtile.current_screen.group.current_window else: w = self.bar.screen.group.current_window state = '' if w: if w.maximized: state = '[] ' elif w.minimized: state = '_ ' elif w.floating: state = 'V ' var = {} var["state"] = state var["name"] = w.name var["class"] = w.window.get_wm_class()[0] if len(w.window.get_wm_class()) > 0 else "" text = self.format.format(**var) unescaped = self.truncate(text) else: unescaped = self.empty_group_string self.text = pangocffi.markup_escape_text(unescaped) self.bar.draw()

40.458824

102

0.662402

from libqtile import bar, hook, pangocffi from libqtile.widget import base class WindowName(base._TextBox): orientations = base.ORIENTATION_HORIZONTAL defaults = [ ('for_current_screen', False, 'instead of this bars screen use currently active screen'), ('empty_group_string', ' ', 'string to display when no windows are focused on current group'), ('max_chars', 0, 'max chars before truncating with ellipsis'), ('format', '{state}{name}', 'format of the text'), ] def __init__(self, width=bar.STRETCH, **config): base._TextBox.__init__(self, width=width, **config) self.add_defaults(WindowName.defaults) def _configure(self, qtile, bar): base._TextBox._configure(self, qtile, bar) hook.subscribe.client_name_updated(self.update) hook.subscribe.focus_change(self.update) hook.subscribe.float_change(self.update) @hook.subscribe.current_screen_change def on_screen_changed(): if self.for_current_screen: self.update() def truncate(self, text): if self.max_chars == 0: return text return (text[:self.max_chars - 3].rstrip() + "...") if len(text) > self.max_chars else text def update(self, *args): if self.for_current_screen: w = self.qtile.current_screen.group.current_window else: w = self.bar.screen.group.current_window state = '' if w: if w.maximized: state = '[] ' elif w.minimized: state = '_ ' elif w.floating: state = 'V ' var = {} var["state"] = state var["name"] = w.name var["class"] = w.window.get_wm_class()[0] if len(w.window.get_wm_class()) > 0 else "" text = self.format.format(**var) unescaped = self.truncate(text) else: unescaped = self.empty_group_string self.text = pangocffi.markup_escape_text(unescaped) self.bar.draw()

true

1c45b8317ee2fbfb8197eed5bc2187f391f7f3ad

3,634

py

Python

root/settings.py

henrid3v/pocket-man

d0e7f44674db877b3e658ee7fc8b0fddf79bfcc8

[ "MIT" ]

null

root/settings.py

henrid3v/pocket-man

d0e7f44674db877b3e658ee7fc8b0fddf79bfcc8

[ "MIT" ]

1

2020-11-28T21:27:01.000Z

2020-11-28T21:29:32.000Z

root/settings.py

shadowcompiler/pocket-man

d0e7f44674db877b3e658ee7fc8b0fddf79bfcc8

[ "MIT" ]

null

""" Django settings for root project. Generated by 'django-admin startproject' using Django 3.0. For more information on this file, see https://docs.djangoproject.com/en/3.0/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/3.0/ref/settings/ """ import os import environ env = environ.Env() environ.Env.read_env() # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/3.0/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = os.environ.get('SECRET_KEY') # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True ALLOWED_HOSTS = [] # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'pocket', 'pocket.users', 'pocket.manager', 'crispy_forms', 'widget_tweaks', 'rest_framework', ] MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'whitenoise.middleware.WhiteNoiseMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'root.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'root.wsgi.application' # Database # https://docs.djangoproject.com/en/3.0/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Password validation # https://docs.djangoproject.com/en/3.0/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/3.0/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/3.0/howto/static-files/ STATIC_URL = '/static/' STATIC_ROOT = os.path.join(BASE_DIR, 'staticfiles') STATICFILES_DIRS = [os.path.join(BASE_DIR, 'static/')] STATICFILES_STORAGE = 'whitenoise.storage.CompressedStaticFilesStorage' CRISPY_TEMPLATE_PACK = 'bootstrap4' LOGIN_URL = 'accounts/login' LOGIN_REDIRECT_URL = 'home' LOGOUT_REDIRECT_URL = 'home' DEFAULT_AUTO_FIELD = 'django.db.models.BigAutoField'

26.720588

91

0.705559

import os import environ env = environ.Env() environ.Env.read_env() BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) SECRET_KEY = os.environ.get('SECRET_KEY') DEBUG = True ALLOWED_HOSTS = [] # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'pocket', 'pocket.users', 'pocket.manager', 'crispy_forms', 'widget_tweaks', 'rest_framework', ] MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'whitenoise.middleware.WhiteNoiseMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'root.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'root.wsgi.application' # Database # https://docs.djangoproject.com/en/3.0/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Password validation # https://docs.djangoproject.com/en/3.0/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/3.0/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/3.0/howto/static-files/ STATIC_URL = '/static/' STATIC_ROOT = os.path.join(BASE_DIR, 'staticfiles') STATICFILES_DIRS = [os.path.join(BASE_DIR, 'static/')] STATICFILES_STORAGE = 'whitenoise.storage.CompressedStaticFilesStorage' CRISPY_TEMPLATE_PACK = 'bootstrap4' LOGIN_URL = 'accounts/login' LOGIN_REDIRECT_URL = 'home' LOGOUT_REDIRECT_URL = 'home' DEFAULT_AUTO_FIELD = 'django.db.models.BigAutoField'

true

1c45b92429dcb84d7d15f647c4e3472f81ee716b

4,819

py

Python

pychron/lasers/tasks/panes/uv.py

ASUPychron/pychron

dfe551bdeb4ff8b8ba5cdea0edab336025e8cc76

[ "Apache-2.0" ]

31

2016-03-07T02:38:17.000Z

2022-02-14T18:23:43.000Z

pychron/lasers/tasks/panes/uv.py

ASUPychron/pychron

dfe551bdeb4ff8b8ba5cdea0edab336025e8cc76

[ "Apache-2.0" ]

1,626

2015-01-07T04:52:35.000Z

2022-03-25T19:15:59.000Z

pychron/lasers/tasks/panes/uv.py

UIllinoisHALPychron/pychron

f21b79f4592a9fb9dc9a4cb2e4e943a3885ededc

[ "Apache-2.0" ]

26

2015-05-23T00:10:06.000Z

2022-03-07T16:51:57.000Z

# =============================================================================== # Copyright 2013 Jake Ross # # 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. # =============================================================================== # ============= enthought library imports ======================= from __future__ import absolute_import from pyface.tasks.traits_dock_pane import TraitsDockPane from traitsui.api import ( View, Item, VGroup, HGroup, spring, UItem, ButtonEditor, Group, EnumEditor, ) from pychron.core.ui.led_editor import LEDEditor from pychron.core.ui.qt.reference_mark_editor import ReferenceMarkEditor from pychron.envisage.icon_button_editor import icon_button_editor from pychron.lasers.tasks.laser_panes import ( BaseLaserPane, ClientPane, StageControlPane, AxesPane, SupplementalPane, ) # ============= standard library imports ======================== # ============= local library imports ========================== class FusionsUVClientPane(ClientPane): pass class FusionsUVPane(BaseLaserPane): pass class FusionsUVStagePane(StageControlPane): id = "pychron.fusions.uv.stage" def _get_tabs(self): tabs = super(FusionsUVStagePane, self)._get_tabs() refmark_grp = VGroup( HGroup( UItem( "object.reference_marks.mark", editor=EnumEditor(name="object.reference_marks.mark_ids"), ), icon_button_editor("add_reference_mark_button", "add"), ), Item("object.reference_marks.mark_display", editor=ReferenceMarkEditor()), UItem("reset_reference_marks_button"), Item("object.reference_marks.spacing"), Item("save_reference_marks_canvas_button"), label="Ref. Marks", ) tabs.content.append(refmark_grp) return tabs class FusionsUVAxesPane(AxesPane): id = "pychron.fusions.uv.axes" class FusionsUVSupplementalPane(SupplementalPane): id = "pychron.fusions.uv.supplemental" name = "UV" def traits_view(self): v = View( Group( VGroup( Item("fiber_light", style="custom", show_label=False), label="FiberLight", ), layout="tabbed", ) ) return v def button_editor(name, label, **kw): return UItem(name, editor=ButtonEditor(label_value=label)) class FusionsUVControlPane(TraitsDockPane): id = "pychron.fusions.uv.control" def traits_view(self): grp = VGroup( HGroup( Item( "enabled", show_label=False, style="custom", editor=LEDEditor(colors=["red", "green"]), ), button_editor("enable", "enable_label"), spring, ), HGroup( Item("action_readback", width=100, style="readonly", label="Action"), Item("status_readback", style="readonly", label="Status"), ), HGroup( button_editor("fire_button", "fire_label"), Item("fire_mode", show_label=False), enabled_when='object.enabled and object.status_readback=="Laser On"', ), HGroup( Item("burst_shot", label="N Burst", enabled_when='fire_mode=="Burst"'), Item("reprate", label="Rep. Rate"), ), HGroup( Item("burst_readback", label="Burst Rem.", width=50, style="readonly"), Item( "energy_readback", label="Energy (mJ)", style="readonly", format_str="%0.2f", ), Item( "pressure_readback", label="Pressure (mbar)", style="readonly", width=100, format_str="%0.1f", ), spring, enabled_when="object.enabled", ), ) v = View(grp) return v # ============= EOF =============================================

31.292208

87

0.529155

from __future__ import absolute_import from pyface.tasks.traits_dock_pane import TraitsDockPane from traitsui.api import ( View, Item, VGroup, HGroup, spring, UItem, ButtonEditor, Group, EnumEditor, ) from pychron.core.ui.led_editor import LEDEditor from pychron.core.ui.qt.reference_mark_editor import ReferenceMarkEditor from pychron.envisage.icon_button_editor import icon_button_editor from pychron.lasers.tasks.laser_panes import ( BaseLaserPane, ClientPane, StageControlPane, AxesPane, SupplementalPane, ) class FusionsUVClientPane(ClientPane): pass class FusionsUVPane(BaseLaserPane): pass class FusionsUVStagePane(StageControlPane): id = "pychron.fusions.uv.stage" def _get_tabs(self): tabs = super(FusionsUVStagePane, self)._get_tabs() refmark_grp = VGroup( HGroup( UItem( "object.reference_marks.mark", editor=EnumEditor(name="object.reference_marks.mark_ids"), ), icon_button_editor("add_reference_mark_button", "add"), ), Item("object.reference_marks.mark_display", editor=ReferenceMarkEditor()), UItem("reset_reference_marks_button"), Item("object.reference_marks.spacing"), Item("save_reference_marks_canvas_button"), label="Ref. Marks", ) tabs.content.append(refmark_grp) return tabs class FusionsUVAxesPane(AxesPane): id = "pychron.fusions.uv.axes" class FusionsUVSupplementalPane(SupplementalPane): id = "pychron.fusions.uv.supplemental" name = "UV" def traits_view(self): v = View( Group( VGroup( Item("fiber_light", style="custom", show_label=False), label="FiberLight", ), layout="tabbed", ) ) return v def button_editor(name, label, **kw): return UItem(name, editor=ButtonEditor(label_value=label)) class FusionsUVControlPane(TraitsDockPane): id = "pychron.fusions.uv.control" def traits_view(self): grp = VGroup( HGroup( Item( "enabled", show_label=False, style="custom", editor=LEDEditor(colors=["red", "green"]), ), button_editor("enable", "enable_label"), spring, ), HGroup( Item("action_readback", width=100, style="readonly", label="Action"), Item("status_readback", style="readonly", label="Status"), ), HGroup( button_editor("fire_button", "fire_label"), Item("fire_mode", show_label=False), enabled_when='object.enabled and object.status_readback=="Laser On"', ), HGroup( Item("burst_shot", label="N Burst", enabled_when='fire_mode=="Burst"'), Item("reprate", label="Rep. Rate"), ), HGroup( Item("burst_readback", label="Burst Rem.", width=50, style="readonly"), Item( "energy_readback", label="Energy (mJ)", style="readonly", format_str="%0.2f", ), Item( "pressure_readback", label="Pressure (mbar)", style="readonly", width=100, format_str="%0.1f", ), spring, enabled_when="object.enabled", ), ) v = View(grp) return v

true

1c45b960408ef5e1ab38b4817737225fd34b5a9f

575

py

Python

test/test_ncbi.py

Daniel-Davies/pytaxize

446990c0f64c8360f1ee65fa7beaeb2410f6213d

[ "MIT" ]

21

2015-02-23T19:41:09.000Z

2020-11-04T15:11:20.000Z

test/test_ncbi.py

Daniel-Davies/pytaxize

446990c0f64c8360f1ee65fa7beaeb2410f6213d

[ "MIT" ]

56

2015-01-12T09:05:10.000Z

2020-09-24T01:48:10.000Z

test/test_ncbi.py

Daniel-Davies/pytaxize

446990c0f64c8360f1ee65fa7beaeb2410f6213d

[ "MIT" ]

21

2015-01-12T08:45:02.000Z

2020-09-10T01:01:43.000Z

import os from nose.tools import * import unittest import vcr from pytaxize import ncbi class NcbiTest(unittest.TestCase): @vcr.use_cassette("test/vcr_cassettes/ncbi_search.yml", filter_query_parameters=['api_key']) def test_ncbi_search(self): "ncbi.search" x = ncbi.search(sci_com = "Apis") assert type(x) == dict assert list(x.keys()) == ["Apis"] assert type(x['Apis']) == list assert type(x['Apis'][0]) == dict assert x['Apis'][0]['ScientificName'] == "Apis" assert x['Apis'][0]['TaxId'] == "7459"

30.263158

96

0.61913

import os from nose.tools import * import unittest import vcr from pytaxize import ncbi class NcbiTest(unittest.TestCase): @vcr.use_cassette("test/vcr_cassettes/ncbi_search.yml", filter_query_parameters=['api_key']) def test_ncbi_search(self): x = ncbi.search(sci_com = "Apis") assert type(x) == dict assert list(x.keys()) == ["Apis"] assert type(x['Apis']) == list assert type(x['Apis'][0]) == dict assert x['Apis'][0]['ScientificName'] == "Apis" assert x['Apis'][0]['TaxId'] == "7459"

true

1c45ba8f50be8960f823fac0995df7dfaa1215e0

218

py

Python

models/__init__.py

netotz/p-dispersion-problem

123a6110dbf64d19a221da545c0590f7efc500dc

[ "MIT" ]

1

2021-09-23T06:31:47.000Z

models/__init__.py

binary-hideout/p-dispersion-problem

123a6110dbf64d19a221da545c0590f7efc500dc

[ "MIT" ]

1

2021-08-31T15:15:08.000Z

models/__init__.py

netotz/p-dispersion-problem

123a6110dbf64d19a221da545c0590f7efc500dc

[ "MIT" ]

1

2020-05-19T04:46:47.000Z

''' Package that contains the models of the project. These models are the classes of Point and PDPInstance. ''' # package level imports from .point import Point from .pdp_instance import PDPInstance, Matrix, Solution

24.222222

55

0.784404

from .point import Point from .pdp_instance import PDPInstance, Matrix, Solution

true

1c45bafe765f80375e19d84146bad5379603a450

356

py

Python

Interviews/HUAWEI/19/1.py

cnsteven/online-judge

60ee841a97e2bc0dc9c7b23fe5daa186898ab8b7

[ "MIT" ]

1

2019-05-04T10:28:32.000Z

Interviews/HUAWEI/19/1.py

cnsteven/online-judge

60ee841a97e2bc0dc9c7b23fe5daa186898ab8b7

[ "MIT" ]

null

Interviews/HUAWEI/19/1.py

cnsteven/online-judge

60ee841a97e2bc0dc9c7b23fe5daa186898ab8b7

[ "MIT" ]

3

2020-12-31T04:36:38.000Z

2021-07-25T07:39:31.000Z

import math n = list(map(int, input().split())) length = len(n) dp = [math.inf] * length for i in range(1, int(length / 2)): step = 1 idx = i while idx < length: dp[idx] = min(dp[idx], step) idx = idx + n[idx] step += 1 if dp[length - 1] == math.inf: print(-1) else: print(dp[length - 1])

17.8

37

0.491573

import math n = list(map(int, input().split())) length = len(n) dp = [math.inf] * length for i in range(1, int(length / 2)): step = 1 idx = i while idx < length: dp[idx] = min(dp[idx], step) idx = idx + n[idx] step += 1 if dp[length - 1] == math.inf: print(-1) else: print(dp[length - 1])

true

1c45bb098fd540b0ca4ce20913c1c1b808e0ae7b

1,204

py

Python

tutorial/proxy.py

maksimKorzh/fresh-proxy-list

e9ed2821a8445430aa30252c01b618892093f5ed

[ "MIT" ]

7

2019-05-24T15:08:25.000Z

2020-06-08T07:51:33.000Z

tutorial/proxy.py

maksimKorzh/fresh-proxy-list

e9ed2821a8445430aa30252c01b618892093f5ed

[ "MIT" ]

null

tutorial/proxy.py

maksimKorzh/fresh-proxy-list

e9ed2821a8445430aa30252c01b618892093f5ed

[ "MIT" ]

5

2019-11-19T23:00:57.000Z

2021-12-22T04:01:31.000Z

import requests from bs4 import BeautifulSoup proxyList = [] response = requests.get('https://free-proxy-list.net/') bs = BeautifulSoup(response.text, 'lxml') table = bs.find('table') rows = table.find_all('tr') count = 0 for row in rows: ip = row.contents[0].text port = row.contents[1].text anonym = row.contents[4].text secconn = row.contents[6].text if(secconn == 'yes' and (anonym == 'anonymous' or anonym == 'elite proxy')): line = 'http://' + ip + ':' + port proxies = { 'http': line, 'https': line } try: testIP = requests.get('https://httpbin.org/ip', proxies = proxies, timeout = 3) print(testIP.text) resIP = testIP.json()['origin'] origin = resIP.split(',') if origin[0] == ip: print(' Proxy ok! Appending proxy to proxyList...') proxyList.append(line) count += 1 if count == 5: break except: print('Bad proxy') with open('proxies.txt', 'w') as f: for proxy in proxyList: f.write("%s\n" % proxy)

27.363636

91

0.508306

import requests from bs4 import BeautifulSoup proxyList = [] response = requests.get('https://free-proxy-list.net/') bs = BeautifulSoup(response.text, 'lxml') table = bs.find('table') rows = table.find_all('tr') count = 0 for row in rows: ip = row.contents[0].text port = row.contents[1].text anonym = row.contents[4].text secconn = row.contents[6].text if(secconn == 'yes' and (anonym == 'anonymous' or anonym == 'elite proxy')): line = 'http://' + ip + ':' + port proxies = { 'http': line, 'https': line } try: testIP = requests.get('https://httpbin.org/ip', proxies = proxies, timeout = 3) print(testIP.text) resIP = testIP.json()['origin'] origin = resIP.split(',') if origin[0] == ip: print(' Proxy ok! Appending proxy to proxyList...') proxyList.append(line) count += 1 if count == 5: break except: print('Bad proxy') with open('proxies.txt', 'w') as f: for proxy in proxyList: f.write("%s\n" % proxy)

true

1c45bb97d6036108335eeb9c5089a59bb600968e

8,237

py

Python

bluzelle/codec/crud/KeyValue_pb2.py

hhio618/bluezelle-py

c38a07458a36305457680196e8c47372008db5ab

[ "MIT" ]

3

2021-08-19T10:09:29.000Z

2022-01-05T14:19:59.000Z

bluzelle/codec/crud/KeyValue_pb2.py

hhio618/bluzelle-py

c38a07458a36305457680196e8c47372008db5ab

[ "MIT" ]

null

bluzelle/codec/crud/KeyValue_pb2.py

hhio618/bluzelle-py

c38a07458a36305457680196e8c47372008db5ab

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Generated by the protocol buffer compiler. DO NOT EDIT! # source: crud/KeyValue.proto """Generated protocol buffer code.""" from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() from bluzelle.codec.crud import lease_pb2 as crud_dot_lease__pb2 DESCRIPTOR = _descriptor.FileDescriptor( name="crud/KeyValue.proto", package="bluzelle.curium.crud", syntax="proto3", serialized_options=b"Z'github.com/bluzelle/curium/x/crud/types", create_key=_descriptor._internal_create_key, serialized_pb=b'\n\x13\x63rud/KeyValue.proto\x12\x14\x62luzelle.curium.crud\x1a\x10\x63rud/lease.proto"&\n\x08KeyValue\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\x0c"W\n\rKeyValueLease\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\x0c\x12*\n\x05lease\x18\x03 \x01(\x0b\x32\x1b.bluzelle.curium.crud.Lease"(\n\x08KeyLease\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\x0f\n\x07seconds\x18\x02 \x01(\rB)Z\'github.com/bluzelle/curium/x/crud/typesb\x06proto3', dependencies=[ crud_dot_lease__pb2.DESCRIPTOR, ], ) _KEYVALUE = _descriptor.Descriptor( name="KeyValue", full_name="bluzelle.curium.crud.KeyValue", filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name="key", full_name="bluzelle.curium.crud.KeyValue.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="bluzelle.curium.crud.KeyValue.value", index=1, number=2, type=12, cpp_type=9, label=1, has_default_value=False, default_value=b"", 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=63, serialized_end=101, ) _KEYVALUELEASE = _descriptor.Descriptor( name="KeyValueLease", full_name="bluzelle.curium.crud.KeyValueLease", filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name="key", full_name="bluzelle.curium.crud.KeyValueLease.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="bluzelle.curium.crud.KeyValueLease.value", index=1, number=2, type=12, cpp_type=9, label=1, has_default_value=False, default_value=b"", 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="lease", full_name="bluzelle.curium.crud.KeyValueLease.lease", 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=[], enum_types=[], serialized_options=None, is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[], serialized_start=103, serialized_end=190, ) _KEYLEASE = _descriptor.Descriptor( name="KeyLease", full_name="bluzelle.curium.crud.KeyLease", filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name="key", full_name="bluzelle.curium.crud.KeyLease.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="seconds", full_name="bluzelle.curium.crud.KeyLease.seconds", 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=192, serialized_end=232, ) _KEYVALUELEASE.fields_by_name["lease"].message_type = crud_dot_lease__pb2._LEASE DESCRIPTOR.message_types_by_name["KeyValue"] = _KEYVALUE DESCRIPTOR.message_types_by_name["KeyValueLease"] = _KEYVALUELEASE DESCRIPTOR.message_types_by_name["KeyLease"] = _KEYLEASE _sym_db.RegisterFileDescriptor(DESCRIPTOR) KeyValue = _reflection.GeneratedProtocolMessageType( "KeyValue", (_message.Message,), { "DESCRIPTOR": _KEYVALUE, "__module__": "crud.KeyValue_pb2" # @@protoc_insertion_point(class_scope:bluzelle.curium.crud.KeyValue) }, ) _sym_db.RegisterMessage(KeyValue) KeyValueLease = _reflection.GeneratedProtocolMessageType( "KeyValueLease", (_message.Message,), { "DESCRIPTOR": _KEYVALUELEASE, "__module__": "crud.KeyValue_pb2" # @@protoc_insertion_point(class_scope:bluzelle.curium.crud.KeyValueLease) }, ) _sym_db.RegisterMessage(KeyValueLease) KeyLease = _reflection.GeneratedProtocolMessageType( "KeyLease", (_message.Message,), { "DESCRIPTOR": _KEYLEASE, "__module__": "crud.KeyValue_pb2" # @@protoc_insertion_point(class_scope:bluzelle.curium.crud.KeyLease) }, ) _sym_db.RegisterMessage(KeyLease) DESCRIPTOR._options = None # @@protoc_insertion_point(module_scope)

30.507407

489

0.618308

from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database _sym_db = _symbol_database.Default() from bluzelle.codec.crud import lease_pb2 as crud_dot_lease__pb2 DESCRIPTOR = _descriptor.FileDescriptor( name="crud/KeyValue.proto", package="bluzelle.curium.crud", syntax="proto3", serialized_options=b"Z'github.com/bluzelle/curium/x/crud/types", create_key=_descriptor._internal_create_key, serialized_pb=b'\n\x13\x63rud/KeyValue.proto\x12\x14\x62luzelle.curium.crud\x1a\x10\x63rud/lease.proto"&\n\x08KeyValue\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\x0c"W\n\rKeyValueLease\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\x0c\x12*\n\x05lease\x18\x03 \x01(\x0b\x32\x1b.bluzelle.curium.crud.Lease"(\n\x08KeyLease\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\x0f\n\x07seconds\x18\x02 \x01(\rB)Z\'github.com/bluzelle/curium/x/crud/typesb\x06proto3', dependencies=[ crud_dot_lease__pb2.DESCRIPTOR, ], ) _KEYVALUE = _descriptor.Descriptor( name="KeyValue", full_name="bluzelle.curium.crud.KeyValue", filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name="key", full_name="bluzelle.curium.crud.KeyValue.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="bluzelle.curium.crud.KeyValue.value", index=1, number=2, type=12, cpp_type=9, label=1, has_default_value=False, default_value=b"", 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=63, serialized_end=101, ) _KEYVALUELEASE = _descriptor.Descriptor( name="KeyValueLease", full_name="bluzelle.curium.crud.KeyValueLease", filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name="key", full_name="bluzelle.curium.crud.KeyValueLease.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="bluzelle.curium.crud.KeyValueLease.value", index=1, number=2, type=12, cpp_type=9, label=1, has_default_value=False, default_value=b"", 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="lease", full_name="bluzelle.curium.crud.KeyValueLease.lease", 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=[], enum_types=[], serialized_options=None, is_extendable=False, syntax="proto3", extension_ranges=[], oneofs=[], serialized_start=103, serialized_end=190, ) _KEYLEASE = _descriptor.Descriptor( name="KeyLease", full_name="bluzelle.curium.crud.KeyLease", filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name="key", full_name="bluzelle.curium.crud.KeyLease.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="seconds", full_name="bluzelle.curium.crud.KeyLease.seconds", 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=192, serialized_end=232, ) _KEYVALUELEASE.fields_by_name["lease"].message_type = crud_dot_lease__pb2._LEASE DESCRIPTOR.message_types_by_name["KeyValue"] = _KEYVALUE DESCRIPTOR.message_types_by_name["KeyValueLease"] = _KEYVALUELEASE DESCRIPTOR.message_types_by_name["KeyLease"] = _KEYLEASE _sym_db.RegisterFileDescriptor(DESCRIPTOR) KeyValue = _reflection.GeneratedProtocolMessageType( "KeyValue", (_message.Message,), { "DESCRIPTOR": _KEYVALUE, "__module__": "crud.KeyValue_pb2" # @@protoc_insertion_point(class_scope:bluzelle.curium.crud.KeyValue) }, ) _sym_db.RegisterMessage(KeyValue) KeyValueLease = _reflection.GeneratedProtocolMessageType( "KeyValueLease", (_message.Message,), { "DESCRIPTOR": _KEYVALUELEASE, "__module__": "crud.KeyValue_pb2" # @@protoc_insertion_point(class_scope:bluzelle.curium.crud.KeyValueLease) }, ) _sym_db.RegisterMessage(KeyValueLease) KeyLease = _reflection.GeneratedProtocolMessageType( "KeyLease", (_message.Message,), { "DESCRIPTOR": _KEYLEASE, "__module__": "crud.KeyValue_pb2" # @@protoc_insertion_point(class_scope:bluzelle.curium.crud.KeyLease) }, ) _sym_db.RegisterMessage(KeyLease) DESCRIPTOR._options = None # @@protoc_insertion_point(module_scope)

true

1c45bbaba79b9d8c2de84555e39251039007bf90

2,727

py

Python

crypto/hard1/service/server.py

AnyKeyShik/CTF_Code

32ff5dce6452dbea09eff0a4db7ad603efe4027d

[ "Apache-2.0" ]

null

crypto/hard1/service/server.py

AnyKeyShik/CTF_Code

32ff5dce6452dbea09eff0a4db7ad603efe4027d

[ "Apache-2.0" ]

null

crypto/hard1/service/server.py

AnyKeyShik/CTF_Code

32ff5dce6452dbea09eff0a4db7ad603efe4027d

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- from random import randint from math import pow def gcd(a, b): if a < b: return gcd(b, a) elif a % b == 0: return b; else: return gcd(b, a % b) def gen_key(modulo): key = randint(pow(10, 20), modulo) while gcd(modulo, key) != 1: key = randint(pow(10, 20), modulo) return key def power(num, exp, mod): x = 1 y = num while exp > 0: if exp % 2 != 0: x = (x * y) % mod y = (y * y) % mod exp = exp // 2 return x % mod def encrypt(flag, modulo, generator, pub): sender_key = gen_key(modulo) secret = power(pub, sender_key, modulo) c1 = power(generator, sender_key, modulo) c2 = secret * flag return c1, c2 def decrypt(c1, c2, priv, modulo): c1_x = power(c1, priv, modulo) msg = (c2 // c1_x) % modulo msg = hex(msg)[2:] msg = ''.join([chr(int(''.join(ch), 16)) for ch in zip(msg[0::2], msg[1::2])]) return msg def read_flag(): try: with open("flag", 'r') as flagfile: flag = flagfile.read() except IOError: print('Some files is missing, tell admin') exit(-1) hexflag = "".join("{:02x}".format(ord(ch)) for ch in flag) numflag = int(hexflag, 16) return numflag def prepare_elgamal(): modulo = randint(pow(10, 20), pow(10, 50)) generator = randint(2, modulo) private = gen_key(modulo) public = power(generator, private, modulo) return (modulo, generator, public), private def main(): # Challenge text CHALL_TEXT = "Hi. This is your friendly 'Decryption Oracle'\nWe have implemented a well-known public-key cryptosystem. Guess which ;)\n\nModulo: {modulo}\nGenerator: {generator}\nPublic key: {public}\nCiphertext: {cipher}\n\nInsert your Ciphertext-Tuple for me to decrypt - comma seperated (e.g. 5,6)" SAME_MSG = "Duh! This would be too easy, right?" INVITE = ">>> " INCORRECT_INPUT = "Incorrect input!" flag = read_flag() public, private = prepare_elgamal() cipher = encrypt(flag, *public) print(CHALL_TEXT.format(modulo=public[0], generator=public[1], public=public[2], cipher=cipher)) while True: print(INVITE, end='') user_input = input() try: enc_msg = tuple(map(int, user_input.replace(' ', '').split(','))) if len(enc_msg) != 2: raise ValueException except Exception: print(INCORRECT_INPUT) continue if enc_msg == cipher: msg = SAME_MSG else: msg = decrypt(*enc_msg, private, public[0]) print(msg) if __name__ == '__main__': main()

23.110169

305

0.574624

from random import randint from math import pow def gcd(a, b): if a < b: return gcd(b, a) elif a % b == 0: return b; else: return gcd(b, a % b) def gen_key(modulo): key = randint(pow(10, 20), modulo) while gcd(modulo, key) != 1: key = randint(pow(10, 20), modulo) return key def power(num, exp, mod): x = 1 y = num while exp > 0: if exp % 2 != 0: x = (x * y) % mod y = (y * y) % mod exp = exp // 2 return x % mod def encrypt(flag, modulo, generator, pub): sender_key = gen_key(modulo) secret = power(pub, sender_key, modulo) c1 = power(generator, sender_key, modulo) c2 = secret * flag return c1, c2 def decrypt(c1, c2, priv, modulo): c1_x = power(c1, priv, modulo) msg = (c2 // c1_x) % modulo msg = hex(msg)[2:] msg = ''.join([chr(int(''.join(ch), 16)) for ch in zip(msg[0::2], msg[1::2])]) return msg def read_flag(): try: with open("flag", 'r') as flagfile: flag = flagfile.read() except IOError: print('Some files is missing, tell admin') exit(-1) hexflag = "".join("{:02x}".format(ord(ch)) for ch in flag) numflag = int(hexflag, 16) return numflag def prepare_elgamal(): modulo = randint(pow(10, 20), pow(10, 50)) generator = randint(2, modulo) private = gen_key(modulo) public = power(generator, private, modulo) return (modulo, generator, public), private def main(): CHALL_TEXT = "Hi. This is your friendly 'Decryption Oracle'\nWe have implemented a well-known public-key cryptosystem. Guess which ;)\n\nModulo: {modulo}\nGenerator: {generator}\nPublic key: {public}\nCiphertext: {cipher}\n\nInsert your Ciphertext-Tuple for me to decrypt - comma seperated (e.g. 5,6)" SAME_MSG = "Duh! This would be too easy, right?" INVITE = ">>> " INCORRECT_INPUT = "Incorrect input!" flag = read_flag() public, private = prepare_elgamal() cipher = encrypt(flag, *public) print(CHALL_TEXT.format(modulo=public[0], generator=public[1], public=public[2], cipher=cipher)) while True: print(INVITE, end='') user_input = input() try: enc_msg = tuple(map(int, user_input.replace(' ', '').split(','))) if len(enc_msg) != 2: raise ValueException except Exception: print(INCORRECT_INPUT) continue if enc_msg == cipher: msg = SAME_MSG else: msg = decrypt(*enc_msg, private, public[0]) print(msg) if __name__ == '__main__': main()

true

1c45bd5ae57fb300ba5e328a5611c8d8c5854181

1,330

py

Python

tests/test_data/test_sciense.py

el/elizabeth

dc82cd9d2bb230acdb2f1a49bc16b1c3d12077ff

[ "MIT" ]

null

tests/test_data/test_sciense.py

el/elizabeth

dc82cd9d2bb230acdb2f1a49bc16b1c3d12077ff

[ "MIT" ]

null

tests/test_data/test_sciense.py

el/elizabeth

dc82cd9d2bb230acdb2f1a49bc16b1c3d12077ff

[ "MIT" ]

1

2019-12-27T19:34:17.000Z

# -*- coding: utf-8 -*- import re from unittest import TestCase from elizabeth import Science import elizabeth.core.interdata as common from tests.test_data import DummyCase from ._patterns import STR_REGEX class ScienceBaseTest(TestCase): def setUp(self): self.science = Science() def tearDown(self): del self.science def test_str(self): self.assertTrue(re.match(STR_REGEX, self.science.__str__())) def test_math_formula(self): result = self.science.math_formula() self.assertIn(result, common.MATH_FORMULAS) class ScienceTestCase(DummyCase): def test_scientific_article(self): result = self.generic.science.scientific_article() self.assertIn(result, self.generic.science._data['article']) def test_scientist(self): result = self.generic.science.scientist() self.assertIn(result, self.generic.science._data['scientist']) def test_chemical_element(self): # Because: https://travis-ci.org/lk-geimfari/elizabeth/jobs/196565835 if self.generic.locale != 'fa': result = self.generic.science.chemical_element(name_only=True) self.assertTrue(len(result) >= 1) result = self.generic.science.chemical_element(name_only=False) self.assertIsInstance(result, dict)

30.227273

77

0.695489

import re from unittest import TestCase from elizabeth import Science import elizabeth.core.interdata as common from tests.test_data import DummyCase from ._patterns import STR_REGEX class ScienceBaseTest(TestCase): def setUp(self): self.science = Science() def tearDown(self): del self.science def test_str(self): self.assertTrue(re.match(STR_REGEX, self.science.__str__())) def test_math_formula(self): result = self.science.math_formula() self.assertIn(result, common.MATH_FORMULAS) class ScienceTestCase(DummyCase): def test_scientific_article(self): result = self.generic.science.scientific_article() self.assertIn(result, self.generic.science._data['article']) def test_scientist(self): result = self.generic.science.scientist() self.assertIn(result, self.generic.science._data['scientist']) def test_chemical_element(self): if self.generic.locale != 'fa': result = self.generic.science.chemical_element(name_only=True) self.assertTrue(len(result) >= 1) result = self.generic.science.chemical_element(name_only=False) self.assertIsInstance(result, dict)

true