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8b9f52988b8506d1eb0785b2864f23355a95bc22 | 1,098 | py | Python | alipay/aop/api/response/AlipayUserCertinfoMaskedQueryResponse.py | articuly/alipay-sdk-python-all | 0259cd28eca0f219b97dac7f41c2458441d5e7a6 | [
"Apache-2.0"
] | null | null | null | alipay/aop/api/response/AlipayUserCertinfoMaskedQueryResponse.py | articuly/alipay-sdk-python-all | 0259cd28eca0f219b97dac7f41c2458441d5e7a6 | [
"Apache-2.0"
] | null | null | null | alipay/aop/api/response/AlipayUserCertinfoMaskedQueryResponse.py | articuly/alipay-sdk-python-all | 0259cd28eca0f219b97dac7f41c2458441d5e7a6 | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/env python
# -*- coding: utf-8 -*-
import simplejson as json
from alipay.aop.api.response.AlipayResponse import AlipayResponse
from alipay.aop.api.domain.MaskedUserCertView import MaskedUserCertView
class AlipayUserCertinfoMaskedQueryResponse(AlipayResponse):
def __init__(self):
super(AlipayUserCertinfoMaskedQueryResponse, self).__init__()
self._cert_views = None
@property
def cert_views(self):
return self._cert_views
@cert_views.setter
def cert_views(self, value):
if isinstance(value, list):
self._cert_views = list()
for i in value:
if isinstance(i, MaskedUserCertView):
self._cert_views.append(i)
else:
self._cert_views.append(MaskedUserCertView.from_alipay_dict(i))
def parse_response_content(self, response_content):
response = super(AlipayUserCertinfoMaskedQueryResponse, self).parse_response_content(response_content)
if 'cert_views' in response:
self.cert_views = response['cert_views']
| 33.272727 | 110 | 0.684882 |
3895bb42085142c7617be2fe829c2f4c12d07740 | 5,234 | py | Python | tfmiss/keras/callbacks/lrfind.py | shkarupa-alex/tfmiss | 4fe1bb3a47327c07711f910ee53319167032b6af | [
"MIT"
] | 1 | 2019-06-25T15:58:20.000Z | 2019-06-25T15:58:20.000Z | tfmiss/keras/callbacks/lrfind.py | shkarupa-alex/tfmiss | 4fe1bb3a47327c07711f910ee53319167032b6af | [
"MIT"
] | 1 | 2021-11-11T12:56:51.000Z | 2021-11-11T12:56:51.000Z | tfmiss/keras/callbacks/lrfind.py | shkarupa-alex/tfmiss | 4fe1bb3a47327c07711f910ee53319167032b6af | [
"MIT"
] | 2 | 2020-02-11T15:46:58.000Z | 2021-11-21T02:47:36.000Z | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import tensorflow as tf
import tempfile
from keras import backend, callbacks
from keras.utils.generic_utils import register_keras_serializable
@register_keras_serializable(package='Miss')
class LRFinder(callbacks.Callback):
"""Stop training when a monitored quantity has stopped improving.
Arguments:
max_steps: Number of steps to run experiment.
min_lr: The lower bound of the learning rate range for the experiment.
max_lr: The upper bound of the learning rate range for the experiment.
smooth: Parameter for averaging the loss. Pick between 0 and 1.
"""
def __init__(self, max_steps, min_lr=1e-7, max_lr=10., smooth=0.98):
super(LRFinder, self).__init__()
self.max_steps = max_steps
self.min_lr = min_lr
self.max_lr = max_lr
self.smooth = smooth
self.stop_training = None
self.curr_step = None
self.best_value = None
self.avg_loss = None
self.losses = None
self.lrs = None
def on_train_begin(self, logs=None):
self.stop_training = False
self.curr_step = 0
self.best_value = 0.
self.avg_loss = 0.
self.losses = []
self.lrs = []
backend.set_value(self.model.optimizer.lr, self.min_lr)
tf.get_logger().warning('Don\'t forget to set "epochs=1" and "steps_per_epoch={}" '
'in model.fit() call'.format(self.max_steps))
def on_train_batch_end(self, batch, logs=None):
if self.stop_training:
return
logs = logs or {}
current_loss = logs.get('loss', None)
# Check preconditions
if current_loss is None:
self.stop_training = True
self.model.stop_training = True
tf.get_logger().error('LRFinder conditioned on "loss" which is not available. '
'Training will be stopped.')
return
if np.isnan(current_loss) or np.isinf(current_loss):
self.stop_training = True
self.model.stop_training = True
tf.get_logger().error('LRFinder got Nan/Inf loss value. Training will be stopped.')
return
# Smooth the loss
self.avg_loss = self.smooth * self.avg_loss + (1 - self.smooth) * current_loss
smooth_loss = self.avg_loss / (1 - self.smooth ** (self.curr_step + 1))
# Check if the loss is not exploding
if self.curr_step > 0 and smooth_loss > self.best_value * 4:
self.stop_training = True
self.model.stop_training = True
tf.get_logger().error('LRFinder found loss explosion. Training will be stopped.')
return
# Remember best loss
if self.curr_step == 0 or smooth_loss < self.best_value:
self.best_value = smooth_loss
curr_lr = backend.get_value(self.model.optimizer.lr)
self.lrs.append(curr_lr)
self.losses.append(smooth_loss)
if self.curr_step > self.max_steps:
self.stop_training = True
self.model.stop_training = True
tf.get_logger().info('LRFinder reached final step. Training will be stopped.')
return
# Set next lr (annealing exponential)
next_lr = self.min_lr * (self.max_lr / self.min_lr) ** (self.curr_step / self.max_steps)
backend.set_value(self.model.optimizer.lr, next_lr)
self.curr_step += 1
def on_train_end(self, logs=None):
if self.curr_step < self.max_steps:
tf.get_logger().error('LRFinder finished before "max_steps" reached. Run training with more data.')
else:
tf.get_logger().info('LRFinder finished. Use ".plot()" method see the graph.')
def plot(self, skip_start=10, skip_end=5):
if not len(self.losses):
raise ValueError('Observations are empty. Run training first.')
losses = self.losses[skip_start:-skip_end]
lrs = self.lrs[skip_start:-skip_end]
try:
min_grad = np.gradient(losses).argmin()
except ValueError:
raise ValueError('Failed to compute gradients, there might not be enough points.')
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
plt.figure(figsize=(12, 6))
plt.plot(lrs, losses)
plt.xscale('log')
plt.xlabel('Log(Learning rate), best {:.2e}'.format(lrs[min_grad]))
plt.ylabel('Loss')
plt.plot(lrs[min_grad], losses[min_grad], markersize=10, marker='o', color='red')
with tempfile.NamedTemporaryFile(suffix='.png', delete=False) as tmp:
plt.savefig(tmp, format='png')
tf.get_logger().info('Graph saved to {}'.format(tmp.name))
return lrs[min_grad], tmp.name
def get_config(self):
config = super(LRFinder, self).get_config()
config.update({
'max_steps': self.max_steps,
'min_lr': self.min_lr,
'max_lr': self.max_lr,
'smooth': self.smooth,
})
return config
| 36.096552 | 111 | 0.619985 |
10322f3467a2b9cbebec8237a571a55f8704fcb2 | 186 | py | Python | flaskrestful/FlaskProject/App/views/__init__.py | riverstation/project-all | c56f1879e1303d561e95a3ff3a70f94fb5fa2191 | [
"Apache-2.0"
] | null | null | null | flaskrestful/FlaskProject/App/views/__init__.py | riverstation/project-all | c56f1879e1303d561e95a3ff3a70f94fb5fa2191 | [
"Apache-2.0"
] | null | null | null | flaskrestful/FlaskProject/App/views/__init__.py | riverstation/project-all | c56f1879e1303d561e95a3ff3a70f94fb5fa2191 | [
"Apache-2.0"
] | null | null | null | from App.views.MovieView import movie
from App.views.UserView import user
def init_views(app):
app.register_blueprint(blueprint=user)
app.register_blueprint(blueprint=movie)
| 18.6 | 43 | 0.790323 |
edb8a8b13cd64f1d686aff3cb249685039d73c20 | 44,023 | py | Python | examples/plotter.py | Guo-Jian-Wang/cmbNNCS | cd55e0a2344aa5182d099cf559bc986ae0351cb7 | [
"MIT"
] | null | null | null | examples/plotter.py | Guo-Jian-Wang/cmbNNCS | cd55e0a2344aa5182d099cf559bc986ae0351cb7 | [
"MIT"
] | null | null | null | examples/plotter.py | Guo-Jian-Wang/cmbNNCS | cd55e0a2344aa5182d099cf559bc986ae0351cb7 | [
"MIT"
] | null | null | null | import sys
sys.path.append('..')
sys.path.append('../..')
sys.path.append('../../..')
import coplot.plots as pl
import coplot.plot_settings as pls
import cmbnncs.simulator as simulator
import cmbnncs.utils as utils
import cmbnncs.spherical as spherical
import loader
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
import matplotlib.gridspec as gridspec
import healpy as hp
import math
import pymaster as nmt
def change_randn_num(randn_num):
randn_num_change = randn_num.split('.')
randn_num_change = randn_num_change[0]+randn_num_change[1]
return randn_num_change
def change_randn_nums(randn_nums):
rdns = ''
rdns_list = []
for rdn in randn_nums:
rdns = rdns + change_randn_num(rdn)
rdns_list.append(change_randn_num(rdn))
return rdns, rdns_list
def mse(true, predict):
'''mean square error'''
return np.mean( (predict-true)**2 )
def cl2dl(Cl, ell_start, ell_in=None, get_ell=True):
'''
ell_start: 0 or 2, which should depend on Dl
ell_in: the ell of Cl (as the input of this function)
'''
if ell_start==0:
lmax_cl = len(Cl) - 1
elif ell_start==2:
lmax_cl = len(Cl) + 1
ell = np.arange(lmax_cl + 1)
if ell_in is not None:
if ell_start==2:
ell[2:] = ell_in
factor = ell * (ell + 1.) / 2. / np.pi
if ell_start==0:
Dl = np.zeros_like(Cl)
Dl[2:] = Cl[2:] * factor[2:]
ell_2 = ell
elif ell_start==2:
Dl = Cl * factor[2:]
ell_2 = ell[2:]
if get_ell:
return ell_2, Dl
else:
return Dl
# The function defined below will compute the power spectrum between two
# NmtFields f_a and f_b, using the coupling matrix stored in the
# NmtWorkspace wsp and subtracting the deprojection bias clb.
# Note that the most expensive operations in the MASTER algorithm are
# the computation of the coupling matrix and the deprojection bias. Since
# these two objects are precomputed, this function should be pretty fast!
def compute_master(f_a, f_b, wsp, clb):
# Compute the power spectrum (a la anafast) of the masked fields
# Note that we only use n_iter=0 here to speed up the computation,
# but the default value of 3 is recommended in general.
cl_coupled = nmt.compute_coupled_cell(f_a, f_b)
# Decouple power spectrum into bandpowers inverting the coupling matrix
cl_decoupled = wsp.decouple_cell(cl_coupled, cl_bias=clb)
return cl_decoupled
def namaster_dl_TT_QQ_UU(cmb_t, mask, bl=None, nside=512, aposize=1, nlb=10,
cl_th=None, cls_th=None, cmb_t_th=None, sim_n=2):
'''Calculate Cl * ell*(ell+1)/2/np.pi of TT, QQ, and UU.
cmb_t : 1-D array with shape (nside**2*12,), the (recovered) CMB I, Q, or U map.
mask : 1-D array with shape (nside**2*12,), the mask file used to the CMB map.
bl : 1-D array with shape (3*nside,), the beam file used to the CMB map, the multipoles starts from 0 to 3*nside-1, so, lmax=3*nside - 1
aposize : float or None, apodization scale in degrees.
nlb : int, the bin size (\delta_\ell) of multipoles, it can be set to ~ 1/fsky
cl_th : 1-D array, the theoretical TT, QQ, or UU power spectrum, where ell start from 0.
cls_th : 6-D array with shape (6, M), the theoretical Cls and ell start from 0.
cls_th[:4, :] correspongding to TT, EE, BB, and TE power spectra, respectively, and cls_th[4:, :] is 0.
cmb_t_th : 1-D array with shape (nside**2*12,), the simulated CMB map based on the theoretical power spectrum.
sim_n : int, the number of simulation.
'''
if aposize is not None:
mask = nmt.mask_apodization(mask, aposize=aposize, apotype="Smooth")
if cmb_t_th is None:
f_t = nmt.NmtField(mask, [cmb_t], templates=None, beam=bl)
else:
f_t = nmt.NmtField(mask, [cmb_t], templates=[[cmb_t-cmb_t_th]], beam=bl)
#method 1
# b = nmt.NmtBin.from_nside_linear(nside, nlb=nlb, is_Dell=True) #nlb=\delta_ell ~ 1/fsky
# dl_TT = nmt.compute_full_master(f_t, f_t, b)[0]
#method 2
b = nmt.NmtBin.from_nside_linear(nside, nlb=nlb, is_Dell=False) #nlb=\delta_ell ~ 1/fsky
if cl_th is None:
cl_bias = None
else:
cl_00_th = cl_th.reshape(1, -1)
cl_bias = nmt.deprojection_bias(f_t, f_t, cl_00_th)
w = nmt.NmtWorkspace()
w.compute_coupling_matrix(f_t, f_t, b)
cl_master = compute_master(f_t, f_t, w, cl_bias)
ell = b.get_effective_ells()
#get error
if cl_th is not None:
cl_mean = np.zeros_like(cl_master)
cl_std = np.zeros_like(cl_master)
for i in np.arange(sim_n):
print("Simulating %s/%s"%(i+1, sim_n))
t, q, u = hp.synfast(cls_th, nside, pol=True, new=True, verbose=False, pixwin=False)
f0_sim = nmt.NmtField(mask, [t], templates=[[cmb_t-cmb_t_th]])
cl = compute_master(f0_sim, f0_sim, w, cl_bias)
cl_mean += cl
cl_std += cl*cl
cl_mean /= sim_n
cl_std = np.sqrt(cl_std / sim_n - cl_mean*cl_mean)
factor = ell*(ell+1)/2/np.pi
dl_std = factor * cl_std
ell, dl_master = cl2dl(cl_master[0], ell_start=2, ell_in=ell)
hp.mollview(mask, title='Mask')
if cl_th is None:
return ell, dl_master
else:
return ell, dl_master, dl_std[0]
def namaster_dl_EE_BB(cmb_qu, mask, bl=None, nside=512, aposize=1, nlb=10):
'''
cmb_qu : 2-D array with shape (2, nside**2*12), CMB Q and U maps.
mask : 1-D array with shape (nside**2*12,), the mask file used to the Q and U maps.
bl : 1-D array with shape (3*nside,), the beam file used to the CMB map, the multipoles starts from 0 to 3*nside-1, so, lmax=3*nside - 1
aposize : float or None, apodization scale in degrees.
nlb : int, the bin size (\delta_\ell) of multipoles, it can be set to ~ 1/fsky
'''
if aposize is not None:
mask = nmt.mask_apodization(mask, aposize=aposize, apotype="Smooth")
f_qu = nmt.NmtField(mask, cmb_qu, beam=bl)
b = nmt.NmtBin.from_nside_linear(nside, nlb=nlb, is_Dell=True) #nlb=10, \delta_ell ~ 1/fsky
dl_22 = nmt.compute_full_master(f_qu, f_qu, b)
ell = b.get_effective_ells()
hp.mollview(mask, title='Mask')
#dl_22[0]: EE, dl_22[3]: BB
return ell, dl_22
class PlotCMBFull(object):
def __init__(self, cmb, cmb_ML, randn_num='', map_type='I', fig_type='test',
map_n=0, input_freqs=[100,143,217,353], out_freq=143, extra_suffix=''):
"""
map_type: 'I', 'Q' or 'U'
fig_type: 'test' or 'obs'
"""
self.cmb = cmb
self.cmb_ML = cmb_ML
self.randn_num = randn_num
self.map_type = map_type
self.fig_type = fig_type
self.map_n = map_n
self.input_freqs = input_freqs
self.freq_num = len(input_freqs)
self.out_freq = out_freq
self.ell = None
self.extra_suffix = extra_suffix
@property
def minmax(self):
if self.map_type=='I':
return 500
else:
return 10
@property
def nside(self):
return int(np.sqrt(len(self.cmb)/12))
@property
def lmax(self):
if self.nside==512:
self.xlim_max = 1500
elif self.nside==256:
self.xlim_max = 760
return 3*self.nside - 1
@property
def randn_marker(self):
return change_randn_num(self.randn_num)
@property
def fig_prefix(self):
if self.fig_type=='obs':
return 'plkcmb'
elif self.fig_type=='test':
return 'simcmb'
def bl_plk(self):
beams = loader.get_planck_beams(nside=self.nside, relative_dir='obs_data')
return beams[str(self.out_freq)][:self.lmax+1]
def bl_fwhm(self, fwhm):
bl = hp.gauss_beam(fwhm*np.pi/10800., lmax=self.lmax)
return bl[:self.lmax+1]
def bl(self, fwhm=None):
if fwhm is None:
print("Using Planck beam file !!!")
return self.bl_plk()
else:
return self.bl_fwhm(fwhm)
@property
def bin_lengh(self):
return 30
@property
def bin_n(self):
return int(math.ceil( (self.lmax-1)/float(self.bin_lengh) ))
def get_plk_fwhm(self):
"""
The recovered CMB map has beam with fwhm=9.43 (for output with 100GHz), while the Planck CMB has 5 arcmin beam.
The generated beam map is used to calculate residual and MSE of CMB map.
Note
----
Note that this procedure is not right!!! The right way is remove the beam from the CMB map, and then add 9.43 arcmin beam,
but it is not feasible. Therefore, this operation is only an approximate method, since the area where the beams work is much
smaller than that of a pixel when nside=256
"""
if self.out_freq == 100:
self.plk_fwhm = 9.43
elif self.out_freq == 143:
self.plk_fwhm = 7.27
elif self.out_freq == 217:
self.plk_fwhm = 5.01
elif self.out_freq == 70:
self.plk_fwhm = 13.31
elif self.out_freq == 353:
self.plk_fwhm = 4.86
@property
def residual_map(self):
return self.cmb_ML - self.cmb
def mask_plk(self):
print("Using Planck mask !!!")
if self.map_type=='I':
self.mask = np.load('obs_data/mask/COM_Mask_CMB-common-Mask-Int_%s_R3.00.npy'%self.nside)
else:
self.mask = np.load('obs_data/mask/COM_Mask_CMB-common-Mask-Pol_%s_R3.00.npy'%self.nside)
self.fsky = np.count_nonzero(self.mask) / float(len(self.mask))
def mask_manual(self):
self.mask = np.ones(self.nside**2*12)
self.fsky = np.count_nonzero(self.mask) / float(len(self.mask))
def plot_cmb(self, savefig=False, root='figures', hold=False):
if self.fig_type=='obs':
title = 'Planck CMB'
elif self.fig_type=='test':
title = 'Simulated CMB'
matplotlib.rcParams.update({'font.size': 16})
hp.mollview(self.cmb, cmap='jet', min=-self.minmax, max=self.minmax, title=title, hold=hold)
if savefig:
utils.mkdir(root)
plt.savefig(root + '/%s_%s_%s.pdf'%(self.fig_prefix,self.map_type,self.map_n), bbox_inches='tight')
def plot_cmb_ML(self, savefig=False, root='figures', hold=False):
matplotlib.rcParams.update({'font.size': 16})
hp.mollview(self.cmb_ML, cmap='jet', min=-self.minmax, max=self.minmax, title='Recovered CMB', hold=hold)
if savefig:
utils.mkdir(root)
if self.extra_suffix:
plt.savefig(root + '/ML_%s_%s_%s_%s_%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker,self.extra_suffix), bbox_inches='tight')
else:
plt.savefig(root + '/ML_%s_%s_%s_%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker), bbox_inches='tight')
def plot_residual(self, savefig=False, root='figures', hold=False):
matplotlib.rcParams.update({'font.size': 16})
hp.mollview(self.residual_map, cmap='jet', min=-self.minmax/10., max=self.minmax/10., title='Residual', hold=hold)
if savefig:
utils.mkdir(root)
if self.extra_suffix:
plt.savefig(root+'/residual_%s_%s_%s_%s_%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker,self.extra_suffix), bbox_inches='tight')
else:
plt.savefig(root+'/residual_%s_%s_%s_%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker), bbox_inches='tight')
def get_dl(self, fwhm=None, aposize=1, nlb=None, bin_residual=True):
'''
aposize : float or None
nlb : int or None
'''
if nlb is None:
self.nlb = math.ceil(1/self.fsky)
else:
self.nlb = nlb
self.get_plk_fwhm()
if self.fig_type=='obs':
self.ell, self.dl = namaster_dl_TT_QQ_UU(self.cmb, self.mask, bl=self.bl(fwhm=5.0), nside=self.nside, aposize=aposize, nlb=self.nlb)
self.ell, self.dl_ML = namaster_dl_TT_QQ_UU(self.cmb_ML, self.mask, bl=self.bl(fwhm=self.plk_fwhm), nside=self.nside, aposize=aposize, nlb=self.nlb)
else:
self.ell, self.dl = namaster_dl_TT_QQ_UU(self.cmb, self.mask, bl=self.bl(fwhm=fwhm), nside=self.nside, aposize=aposize, nlb=self.nlb, cl_th=None)
self.ell, self.dl_ML = namaster_dl_TT_QQ_UU(self.cmb_ML, self.mask, bl=self.bl(fwhm=fwhm), nside=self.nside, aposize=aposize, nlb=self.nlb, cl_th=None)
self.mse_map = mse(self.cmb, self.cmb_ML)
self.mse_dl = mse(self.dl, self.dl_ML)##
print('mseSpectra:%s'%self.mse_dl)
#different from sim_tt
self.dl_diff = self.dl_ML - self.dl
if bin_residual:
self.ell_bined = [np.mean(self.ell[i*self.bin_lengh:(i+1)*self.bin_lengh]) for i in range(self.bin_n)]
self.dl_diff_bined = [self.dl_diff[i*self.bin_lengh:(i+1)*self.bin_lengh] for i in range(self.bin_n)]
self.dl_diff_bined_best = [np.mean(self.dl_diff_bined[i]) for i in range(self.bin_n)]
self.dl_diff_bined_err = [np.std(self.dl_diff_bined[i]) for i in range(self.bin_n)]
def plot_dl(self, savefig=False, root='figures', one_panel=True,
show_title=False, title_str=None, show_mse=False,
fwhm=None, aposize=1, nlb=None, bin_residual=True):
if self.ell is None:
self.get_dl(fwhm=fwhm, aposize=aposize, nlb=nlb, bin_residual=bin_residual)
if one_panel:
fig_spectra = plt.figure(figsize=(6*1.2, 4.5*1.2))
fig_spectra.subplots_adjust(hspace=0)
gs = gridspec.GridSpec(2, 1, height_ratios=[3, 1])
ticks_size = 12
fontsize = 16
else:
gs = gridspec.GridSpec(3, 2, height_ratios=[5.5, 3, 1])
ticks_size = 12
fontsize = 18
if one_panel:
ax_0 = plt.subplot(gs[0])
else:
ax_0 = plt.subplot(gs[3])
ax_0 = pls.PlotSettings().setting(ax=ax_0,labels=[r'$\ell$', r'$D_\ell^{TT}[\mu k^2]$'],
ticks_size=ticks_size,show_xticks=False,minor_locator_N=8,major_locator_N=5)
if self.fig_type=='obs':
ax_0.plot(self.ell, self.dl, label='Planck CMB')
elif self.fig_type=='test':
ax_0.plot(self.ell, self.dl, label='Simulated CMB')
if self.map_type=='I':
ax_0.plot(self.ell, self.dl_ML, label='Recovered CMB')
ax_0.set_xlim(0, self.xlim_max)
ax_0.set_ylim(10, 7100)
else:
ax_0.plot(self.ell, self.dl_ML, label='Recovered CMB')
ax_0.set_xlim(0, self.xlim_max)
if show_mse:
ax_0.text(self.lmax*0.6, max(self.dl)*0.52, r'$MSE_{CMB}:%.2f$'%self.mse_map, fontsize=fontsize)
ax_0.text(self.lmax*0.6, max(self.dl)*0.35, r'$MSE_{D_\ell}:%.2f$'%self.mse_dl, fontsize=fontsize)
ax_0.legend(fontsize=fontsize)
if show_title:
if self.freq_num==1:
if title_str is None:
plt.title('%s frequency: %s'%(self.freq_num, self.input_freqs), fontsize=fontsize)
else:
plt.title(title_str, fontsize=fontsize)
else:
if title_str is None:
plt.title('%s frequencies: %s'%(self.freq_num, self.input_freqs), fontsize=fontsize)
else:
plt.title(title_str, fontsize=fontsize)
if one_panel:
ax_1 = plt.subplot(gs[1])
else:
ax_1 = plt.subplot(gs[5])
ax_1 = pls.PlotSettings().setting(ax=ax_1,labels=[r'$\ell$', r'$\Delta D_\ell^{TT}[\mu k^2]$'],
ticks_size=ticks_size,minor_locator_N=8,major_locator_N=5)
ax_1.plot([0, max(self.ell)], [0,0], '--', color=pl.fiducial_colors[9])
if bin_residual:
ax_1.errorbar(self.ell_bined, self.dl_diff_bined_best, yerr=self.dl_diff_bined_err, fmt='.')
else:
ax_1.plot(self.ell, self.dl_diff, color=pl.fiducial_colors[8])
if not savefig:
plt.plot([768,768], [-280,280])
plt.text(768-50, 20, '768')
plt.plot([1000,1000], [-280,280])
plt.text(1000-50, 20, '1000')
ax_1.set_xlim(0, self.xlim_max)
if self.map_type=='I':
ax_1.set_ylim(-100, 100)
else:
ax_1.set_ylim(-3, 3)
if savefig:
if self.extra_suffix:
pl.savefig(root, 'spectra_%s_%s_%s_%s_%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker,self.extra_suffix), fig_spectra)
else:
pl.savefig(root, 'spectra_%s_%s_%s_%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker), fig_spectra)
def plot_all(self, savefig=False, root='figures', fwhm=None, aposize=1, nlb=None, bin_residual=True):
if self.ell is None:
self.get_dl(fwhm=fwhm, aposize=aposize, nlb=nlb, bin_residual=bin_residual)
fig = plt.figure(figsize=(6*1.2*2, 4.5*1.2*2))
fig.subplots_adjust(wspace=0.21, hspace=0)
pls.PlotSettings().setting(location=(2,2,1),set_labels=False)
self.plot_cmb(hold=True)
pls.PlotSettings().setting(location=(2,2,2),set_labels=False)
self.plot_cmb_ML(hold=True)
pls.PlotSettings().setting(location=(2,2,3),set_labels=False)
self.plot_residual(hold=True)
self.plot_dl(one_panel=False, show_title=True, show_mse=True, fwhm=fwhm, aposize=aposize, nlb=nlb, bin_residual=bin_residual)
if savefig:
if self.extra_suffix:
pl.savefig(root, '%s_%s_%s_%s_%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker,self.extra_suffix), fig)
else:
pl.savefig(root, '%s_%s_%s_%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker), fig)
def _get_miniPatch(self, Map):
'''
select a 3*3 deg^2 patch
'''
ps = spherical.PixelSize(nside=self.nside)
patch_size = int(3/ps.pixel_length)
map_blocks = spherical.Cut(Map).block_all()
patch_0 = map_blocks[0][:patch_size, :patch_size]
patch_1 = map_blocks[4][:patch_size, :patch_size]
start_pix = (self.nside-patch_size)//2
patch_2 = map_blocks[4][start_pix:start_pix+patch_size, start_pix:start_pix+patch_size]
patch_3 = map_blocks[4][-patch_size:, -patch_size:]
patch_4 = map_blocks[11][-patch_size:, -patch_size:]
return [patch_0, patch_1, patch_2, patch_3, patch_4]
def get_miniPatch(self):
self.cmb_miniBatches = self._get_miniPatch(self.cmb)
self.cmb_ML_miniBatches = self._get_miniPatch(self.cmb_ML)
self.residual_map_miniBatches = self._get_miniPatch(self.residual_map)
def plot_miniPatch(self, savefig=False, root='figures'):
self.get_miniPatch()
fig = plt.figure(figsize=(3*5, 3*3))
fig.subplots_adjust(left=0,bottom=0,right=1,top=1,wspace=0.15,hspace=0.25)
for row in range(3):
for column in range(5):
pls.PlotSettings().setting(location=(3,5,row*5+column+1),set_labels=False,minor_locator_N=1)
# plt.subplot(3,5,row*5+column+1)
if row==0:
im = plt.imshow(self.cmb_miniBatches[column], cmap='jet', vmin=-500, vmax=500)
if self.fig_type=='obs':
plt.title('Planck CMB', fontsize=16)
elif self.fig_type=='test':
plt.title('Simulated CMB', fontsize=16)
elif row==1:
im = plt.imshow(self.cmb_ML_miniBatches[column], cmap='jet', vmin=-500, vmax=500)
plt.title('Recovered CMB', fontsize=16)
if column==4:
cbar_ax = fig.add_axes([1.01, 0.358, 0.01, 0.641])
plt.colorbar(im, cax=cbar_ax)
elif row==2:
im = plt.imshow(self.residual_map_miniBatches[column], cmap='jet', vmin=-50, vmax=50)
plt.title('Residual', fontsize=16)
if column==4:
cbar_ax = fig.add_axes([1.01, 0., 0.01, 0.287])
plt.colorbar(im, cax=cbar_ax)
if savefig:
utils.mkdir(root)
if self.extra_suffix:
plt.savefig(root + '/miniPatch_%s_%s_%s_%s_%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker,self.extra_suffix), bbox_inches='tight')
else:
plt.savefig(root + '/miniPatch_%s_%s_%s_%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker), bbox_inches='tight')
#%%
class PlotCMBBlock(object):
def __init__(self, cmb, cmb_ML, randn_num='', map_type='I', fig_type='test',
map_n=0, input_freqs=[100,143,217,353], out_freq=143, block_n=0, extra_suffix=''):
"""
map_type: 'I', 'Q' or 'U'
fig_type: 'test' or 'obs'
"""
self.cmb = cmb
self.cmb_ML = cmb_ML
self.randn_num = randn_num
self.map_type = map_type
self.fig_type = fig_type
self.map_n = map_n
self.input_freqs = input_freqs
self.freq_num = len(input_freqs)
self.out_freq = out_freq
self.block_n = block_n
self.extra_suffix = extra_suffix
self.ell = None
@property
def minmax(self):
if self.map_type=='I':
return 500
else:
return 10
@property
def dl_type(self):
if self.map_type=='I':
return 'TT'
else:
return '%s%s'%(self.map_type, self.map_type)
@property
def nside(self):
return int(len(self.cmb))
@property
def lmax(self):
if self.nside==512:
self.xlim_max = 1500
elif self.nside==256:
self.xlim_max = 760
return 3*self.nside - 1
@property
def randn_marker(self):
return change_randn_num(self.randn_num)
@property
def fig_prefix(self):
if self.fig_type=='obs':
return 'plkcmb'
elif self.fig_type=='test':
return 'simcmb'
def bl_plk(self):
beams = loader.get_planck_beams(nside=self.nside, relative_dir='obs_data')
return beams[str(self.out_freq)][:self.lmax+1]
def bl_fwhm(self, fwhm):
bl = hp.gauss_beam(fwhm*np.pi/10800., lmax=self.lmax)
return bl[:self.lmax+1]
def bl(self, fwhm=None):
if fwhm is None:
print("Using Planck beam file !!!")
return self.bl_plk()
else:
return self.bl_fwhm(fwhm)
@property
def bin_lengh(self):
return 6 #6*nlb = 30, let nlb=5
@property
def bin_n(self):
return int(math.ceil( (self.lmax-1)/float(self.bin_lengh) ))
@property
def residual_map(self):
if self.fig_type=='obs':
return self.cmb_ML - self.cmb_beam
else:
return self.cmb_ML - self.cmb
def mask_plk(self):
if self.map_type=='I':
mask = np.load('obs_data/mask/COM_Mask_CMB-common-Mask-Int_%s_R3.00.npy'%self.nside)
else:
mask = np.load('obs_data/mask/COM_Mask_CMB-common-Mask-Pol_%s_R3.00.npy'%self.nside)
mask_0 = spherical.Cut(mask).block(self.block_n)
self.mask = spherical.Block2Full(mask_0, self.block_n).full()
self.fsky = np.count_nonzero(self.mask) / float(len(self.mask))
def mask_manual(self):
mask_0 = np.ones((self.nside, self.nside))
self.mask = spherical.Block2Full(mask_0, self.block_n).full()
self.fsky = np.count_nonzero(self.mask) / float(len(self.mask))
def plot_cmb(self, savefig=False, root='figures', hold=False, one_panel=True):
if self.fig_type=='obs':
title = 'Planck CMB'
elif self.fig_type=='test':
title = 'Simulated CMB'
if one_panel:
plt.figure()#
matplotlib.rcParams.update({'font.size': 16})
plt.imshow(self.cmb, cmap='jet', vmin=-self.minmax, vmax=self.minmax)
plt.colorbar()
plt.title(title, fontsize=16)
if savefig:
utils.mkdir(root)
if self.use_mask:
plt.savefig(root + '/%s_%s_%s_block%s_mask.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.block_n), bbox_inches='tight')
else:
plt.savefig(root + '/%s_%s_%s_block%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.block_n), bbox_inches='tight')
def plot_cmb_ML(self, savefig=False, root='figures', hold=False, one_panel=True):
if one_panel:
plt.figure()#
matplotlib.rcParams.update({'font.size': 16})
plt.imshow(self.cmb_ML, cmap='jet', vmin=-self.minmax, vmax=self.minmax)
plt.colorbar()
plt.title('Recovered CMB', fontsize=16)
if savefig:
utils.mkdir(root)
if self.extra_suffix:
plt.savefig(root + '/ML_%s_%s_%s_%s_block%s_%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker,self.block_n,self.extra_suffix), bbox_inches='tight')
else:
plt.savefig(root + '/ML_%s_%s_%s_%s_block%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker,self.block_n), bbox_inches='tight')
def plot_residual(self, savefig=False, root='figures', hold=False, one_panel=True):
if one_panel:
plt.figure()#
matplotlib.rcParams.update({'font.size': 16})
if self.map_type=='I':
plt.imshow(self.residual_map, cmap='jet', vmin=-self.minmax/50., vmax=self.minmax/50.)
else:
plt.imshow(self.residual_map, cmap='jet', vmin=-self.minmax/50., vmax=self.minmax/50.)
plt.colorbar()
plt.title('Residual', fontsize=16)
if savefig:
utils.mkdir(root)
if self.extra_suffix:
plt.savefig(root+'/residual_%s_%s_%s_%s_block%s_%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker,self.block_n,self.extra_suffix), bbox_inches='tight')
else:
plt.savefig(root+'/residual_%s_%s_%s_%s_block%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker,self.block_n), bbox_inches='tight')
def get_dl(self, fwhm=None, aposize=1, nlb=None, bin_residual=True):
'''
aposize : float or None
nlb : int or None
'''
if nlb is None:
self.nlb = math.ceil(1/self.fsky)
else:
self.nlb = nlb
self.cmb_sp = spherical.Block2Full(self.cmb, self.block_n).full()
self.cmb_ML_sp = spherical.Block2Full(self.cmb_ML, self.block_n).full()
self.ell, self.dl = namaster_dl_TT_QQ_UU(self.cmb_sp, self.mask, bl=self.bl(fwhm=fwhm), nside=self.nside, aposize=aposize, nlb=self.nlb)
self.ell, self.dl_ML = namaster_dl_TT_QQ_UU(self.cmb_ML_sp, self.mask, bl=self.bl(fwhm=fwhm), nside=self.nside, aposize=aposize, nlb=self.nlb)
self.mse_map = mse(self.cmb, self.cmb_ML)
self.mse_dl = mse(self.dl, self.dl_ML)##
print('mseSpectra:%s'%self.mse_dl)
self.dl_diff = self.dl_ML - self.dl
if bin_residual:
self.ell_bined = [np.mean(self.ell[i*self.bin_lengh:(i+1)*self.bin_lengh]) for i in range(self.bin_n)]
self.dl_diff_bined = [self.dl_diff[i*self.bin_lengh:(i+1)*self.bin_lengh] for i in range(self.bin_n)]
self.dl_diff_bined_best = [np.mean(self.dl_diff_bined[i]) for i in range(self.bin_n)]
self.dl_diff_bined_err = [np.std(self.dl_diff_bined[i]) for i in range(self.bin_n)]
def plot_dl(self, savefig=False, root='figures', one_panel=True,
show_title=False, title_str=None, show_mse=False,
fwhm=None, aposize=1, nlb=None, bin_residual=True):
if self.ell is None:
self.get_dl(fwhm=fwhm, aposize=aposize, nlb=nlb, bin_residual=bin_residual)
if one_panel:
fig_spectra = plt.figure(figsize=(6*1.2, 4.5*1.2))
fig_spectra.subplots_adjust(hspace=0)
gs = gridspec.GridSpec(2, 1, height_ratios=[3, 1])
ticks_size = 12 + 4
fontsize = 16 + 2
else:
gs = gridspec.GridSpec(3, 2, height_ratios=[5.5, 3, 1])
ticks_size = 12
fontsize = 18
if one_panel:
ax_0 = plt.subplot(gs[0])
else:
ax_0 = plt.subplot(gs[3])
ax_0 = pls.PlotSettings().setting(ax=ax_0,labels=[r'$\ell$', r'$D_\ell^{%s}[\mu k^2]$'%self.dl_type],
ticks_size=ticks_size,show_xticks=False,minor_locator_N=8,major_locator_N=5)
if self.fig_type=='obs':
ax_0.plot(self.ell, self.dl, label='Planck CMB')
elif self.fig_type=='test':
ax_0.plot(self.ell, self.dl, label='Simulated CMB')
if self.map_type=='I':
ax_0.plot(self.ell, self.dl_ML, label='Recovered CMB')
ax_0.set_xlim(0, self.xlim_max)
ax_0.set_ylim(10, 7100)
# if self.fig_type=='obs':
# ax_0.set_ylim(10, 8000)
# else:
# ax_0.set_ylim(10, 7500)
else:
ax_0.plot(self.ell, self.dl_ML, 'r', label='Recovered CMB') ## *2 !!!
ax_0.set_xlim(0, self.xlim_max)
# ax_0.set_ylim(0.001, 2.6)
if show_mse:
ax_0.text(self.lmax*0.62, max(self.dl)*0.4, r'$MSE_{CMB}:%.2f$'%self.mse_map, fontsize=fontsize)
ax_0.text(self.lmax*0.62, max(self.dl)*0.3, r'$MSE_{D_\ell}:%.2f$'%self.mse_dl, fontsize=fontsize)
ax_0.legend(fontsize=fontsize)
if show_title:
if self.freq_num==1:
if title_str is None:
plt.title('%s frequency: %s'%(self.freq_num, self.input_freqs), fontsize=fontsize)
else:
plt.title(title_str, fontsize=fontsize)
else:
if title_str is None:
plt.title('%s frequencies: %s'%(self.freq_num, self.input_freqs), fontsize=fontsize)
else:
plt.title(title_str, fontsize=fontsize)
if one_panel:
ax_1 = plt.subplot(gs[1])
else:
ax_1 = plt.subplot(gs[5])
ax_1 = pls.PlotSettings().setting(ax=ax_1,labels=[r'$\ell$', r'$\Delta D_\ell^{%s}[\mu k^2]$'%self.dl_type],
ticks_size=ticks_size,minor_locator_N=8,major_locator_N=5)
ax_1.plot([0, max(self.ell)], [0,0], '--', color=pl.fiducial_colors[9])
if bin_residual:
ax_1.errorbar(self.ell_bined, self.dl_diff_bined_best, yerr=self.dl_diff_bined_err, fmt='.')
else:
ax_1.plot(self.ell, self.dl_diff, color=pl.fiducial_colors[8])
if not savefig:
plt.plot([768,768], [-280,280])###
plt.plot([1000,1000], [-280,280])###
plt.plot([1250,1250], [-280,280])###
plt.plot([1300,1300], [-280,280])###
ax_1.set_xlim(0, self.xlim_max)
if self.map_type=='I':
ax_1.set_ylim(-100, 100)
else:
ax_1.set_ylim(-0.5, 0.5)
if savefig:
if self.extra_suffix:
pl.savefig(root, 'spectra_%s_%s_%s_%s_block%s_%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker,self.block_n,self.extra_suffix), fig_spectra)
else:
pl.savefig(root, 'spectra_%s_%s_%s_%s_block%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker,self.block_n), fig_spectra)
def plot_all(self, savefig=False, root='figures', fwhm=None, aposize=1, nlb=None, bin_residual=True):
if self.ell is None:
self.get_dl(fwhm=fwhm, aposize=aposize, nlb=nlb, bin_residual=bin_residual)
fig = plt.figure(figsize=(6*1.2*2, 4.5*1.2*2))
fig.subplots_adjust(wspace=0.2, hspace=0.2)
pls.PlotSettings().setting(location=(2,2,1),set_labels=False)
self.plot_cmb(hold=True, one_panel=False)
pls.PlotSettings().setting(location=(2,2,2),set_labels=False)
self.plot_cmb_ML(hold=True, one_panel=False)
pls.PlotSettings().setting(location=(2,2,3),set_labels=False)
self.plot_residual(hold=True, one_panel=False)
# pls.PlotSettings().setting(location=(2,2,4),set_labels=False)
self.plot_dl(one_panel=False, show_title=True, show_mse=True, fwhm=fwhm, aposize=aposize, nlb=nlb)#True
# plt.suptitle(self.case_labels[str(self.case)], fontsize=22)
if savefig:
if self.extra_suffix:
pl.savefig(root, '%s_%s_%s_%s_block%s_%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker,self.block_n,self.extra_suffix), fig)
else:
pl.savefig(root, '%s_%s_%s_%s_block%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker,self.block_n), fig)
def _get_miniPatch(self, Map):
'''
select a 3*3 deg^2 patch
'''
ps = spherical.PixelSize(nside=self.nside)
patch_size = int(3/ps.pixel_length)
start_pix = (self.nside-patch_size)//2
patch_0 = Map[start_pix:start_pix+patch_size, :patch_size]
patch_1 = Map[start_pix:start_pix+patch_size, start_pix:start_pix+patch_size]
patch_2 = Map[start_pix:start_pix+patch_size, -patch_size:]
return [patch_0, patch_1, patch_2]
def get_miniPatch(self):
self.cmb_miniBatches = self._get_miniPatch(self.cmb)
self.cmb_ML_miniBatches = self._get_miniPatch(self.cmb_ML)
self.residual_map_miniBatches = self._get_miniPatch(self.residual_map)
def plot_miniPatch(self, savefig=False, root='figures'):
self.get_miniPatch()
fig = plt.figure(figsize=(3*3, 3*3))
fig.subplots_adjust(left=0,bottom=0,right=1,top=1,wspace=0.15,hspace=0.25)
for row in range(3):
for column in range(3):
pls.PlotSettings().setting(location=(3,3,row*3+column+1),set_labels=False,minor_locator_N=1)
# plt.subplot(3,3,row*3+column+1)
if row==0:
im = plt.imshow(self.cmb_miniBatches[column], cmap='jet', vmin=-500, vmax=500)
if self.fig_type=='obs':
plt.title('Planck CMB', fontsize=16)
elif self.fig_type=='test':
plt.title('Simulated CMB', fontsize=16)
elif row==1:
im = plt.imshow(self.cmb_ML_miniBatches[column], cmap='jet', vmin=-500, vmax=500)
plt.title('Recovered CMB', fontsize=16)
if column==2:
cbar_ax = fig.add_axes([1.01, 0.358, 0.015, 0.641])
plt.colorbar(im, cax=cbar_ax)
elif row==2:
im = plt.imshow(self.residual_map_miniBatches[column], cmap='jet', vmin=-10, vmax=10)
plt.title('Residual', fontsize=16)
if column==2:
cbar_ax = fig.add_axes([1.01, 0., 0.015, 0.287])
plt.colorbar(im, cax=cbar_ax)
if savefig:
utils.mkdir(root)
if self.extra_suffix:
plt.savefig(root + '/miniPatch_%s_%s_%s_%s_block%s_%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker,self.block_n,self.extra_suffix), bbox_inches='tight')
else:
plt.savefig(root + '/miniPatch_%s_%s_%s_%s_block%s.pdf'%(self.fig_prefix,self.map_type,self.map_n,self.randn_marker,self.block_n), bbox_inches='tight')
#%%
class PlotCMB_EEBB(object):
def __init__(self, cmb_qu, cmb_ML_qu, map_n=0, nside=512, block_n=0, randn_marker='',extra_suffix=''):
self.cmb_qu = cmb_qu
self.cmb_ML_qu = cmb_ML_qu
self.map_n = map_n
self.nside = nside
self.block_n = block_n
self.randn_marker = randn_marker
self.extra_suffix = extra_suffix
self.ell = None
@property
def lmax(self):
if self.nside==512:
self.xlim_max = 1500
elif self.nside==256:
self.xlim_max = 760
return 3*self.nside - 1
@property
def bin_lengh(self):
return 6 #6*nlb = 30, let nlb=5
@property
def bin_n(self):
return int(math.ceil( (self.lmax-1)/float(self.bin_lengh) ))
@property
def fig_prefix(self):
return 'simcmb'
def mask_manual(self):
mask_0 = np.ones((self.nside, self.nside))
self.mask = spherical.Block2Full(mask_0, self.block_n).full()
self.fsky = np.count_nonzero(self.mask) / float(len(self.mask))
def bl_fwhm(self, fwhm):
bl = hp.gauss_beam(fwhm*np.pi/10800., lmax=self.lmax)
return bl[:self.lmax+1]
def get_dl(self, fwhm=None, aposize=1, nlb=None, bin_residual=True):
'''
aposize : float or None
nlb : int or None
'''
# self.get_fiducial_dls()
if nlb is None:
self.nlb = math.ceil(1/self.fsky)
else:
self.nlb = nlb
self.ell, self.dl = namaster_dl_EE_BB(self.cmb_qu, self.mask, bl=self.bl_fwhm(fwhm=fwhm), nside=self.nside, aposize=aposize, nlb=self.nlb)
self.ell, self.dl_ML = namaster_dl_EE_BB(self.cmb_ML_qu, self.mask, bl=self.bl_fwhm(fwhm=fwhm), nside=self.nside, aposize=aposize, nlb=self.nlb)
self.dl_EE, self.dl_BB = self.dl[0], self.dl[3]
self.dl_ML_EE, self.dl_ML_BB = self.dl_ML[0], self.dl_ML[3]
self.diff_EE = self.dl_ML_EE - self.dl_EE
self.diff_BB = self.dl_ML_BB - self.dl_BB
# print(self.diff_BB)
#bined ell & dl residual
if bin_residual:
self.ell_bined = [np.mean(self.ell[i*self.bin_lengh:(i+1)*self.bin_lengh]) for i in range(self.bin_n)]
#residual of EE
self.diff_EE_bined = [self.diff_EE[i*self.bin_lengh:(i+1)*self.bin_lengh] for i in range(self.bin_n)]
self.diff_EE_bined_best = [np.mean(self.diff_EE_bined[i]) for i in range(self.bin_n)]
self.diff_EE_bined_err = [np.std(self.diff_EE_bined[i]) for i in range(self.bin_n)]
#residual of BB
self.diff_BB_bined = [self.diff_BB[i*self.bin_lengh:(i+1)*self.bin_lengh] for i in range(self.bin_n)]
self.diff_BB_bined_best = [np.mean(self.diff_BB_bined[i]) for i in range(self.bin_n)]
self.diff_BB_bined_err = [np.std(self.diff_BB_bined[i]) for i in range(self.bin_n)]
def plot_dl(self, savefig=False, root='figures', dl_type='', bin_residual=True):
'''
dl_type: EE or BB
'''
fig_spectra = plt.figure(figsize=(6*1.*2, 4.5*1.))
fig_spectra.subplots_adjust(left=0, bottom=0, right=1, top=1, wspace=0.23)
# gs = gridspec.GridSpec(2, 1, height_ratios=[3, 1])
ticks_size = 12 #+ 4
fontsize = 16 #+ 2
ax_0 = pls.PlotSettings().setting(location=[1,2,1],labels=[r'$\ell$', r'$D_\ell^{%s}[\mu k^2]$'%dl_type],
ticks_size=ticks_size,show_xticks=False,minor_locator_N=8,major_locator_N=5)
ax_0.loglog(self.ell, eval('self.dl_%s'%dl_type), label='Simulated CMB')
ax_0.loglog(self.ell, eval('self.dl_ML_%s'%dl_type), label='Recovered CMB')
ax_0.set_xlim(0, self.xlim_max)
# if dl_type=='EE':
# ax_0.set_ylim(-0.05, 0.05)
# elif dl_type=='BB':
# ax_0.set_ylim(-0.003, 0.003)
ax_0.legend(loc=2, fontsize=fontsize)
ax_1 = pls.PlotSettings().setting(location=[1,2,2],labels=[r'$\ell$', r'$\Delta D_\ell^{%s}[\mu k^2]$'%dl_type],
ticks_size=ticks_size,minor_locator_N=8,major_locator_N=5)
ax_1.plot([0, max(self.ell)], [0,0], '--', color=pl.fiducial_colors[9])
if bin_residual:
ax_1.errorbar(self.ell_bined, eval('self.diff_%s_bined_best'%dl_type), yerr=eval('self.diff_%s_bined_err'%dl_type), fmt='.')
else:
ax_1.plot(self.ell, eval('self.diff_%s'%dl_type), color=pl.fiducial_colors[8])
ax_1.set_xlim(0, self.xlim_max)
if dl_type=='EE':
# pass
ax_1.set_ylim(-0.9, 0.1)
# ax_1.set_ylim(-2e-5, 2e-5) #test, plot CL
elif dl_type=='BB':
ax_1.set_ylim(-0.04, 0.04)
if not savefig:
plt.plot([768,768], [-280,280])###
plt.plot([1000,1000], [-280,280])###
plt.plot([1250,1250], [-280,280])###
plt.plot([1300,1300], [-280,280])###
if savefig:
if self.extra_suffix:
pl.savefig(root+'/pdf', 'spectra_%s_%s_%s_%s_block%s_%s.pdf'%(self.fig_prefix,dl_type,self.map_n,self.randn_marker,self.block_n,self.extra_suffix), fig_spectra)
pl.savefig(root+'/jpg', 'spectra_%s_%s_%s_%s_block%s_%s.jpg'%(self.fig_prefix,dl_type,self.map_n,self.randn_marker,self.block_n,self.extra_suffix), fig_spectra)
else:
pl.savefig(root+'/pdf', 'spectra_%s_%s_%s_%s_block%s.pdf'%(self.fig_prefix,dl_type,self.map_n,self.randn_marker,self.block_n), fig_spectra)
pl.savefig(root+'/jpg', 'spectra_%s_%s_%s_%s_block%s.jpg'%(self.fig_prefix,dl_type,self.map_n,self.randn_marker,self.block_n), fig_spectra)
def plot_all(self, savefig=False, root='figures', fwhm=None, aposize=1, nlb=None, bin_residual=True):
if self.ell is None:
self.get_dl(fwhm=fwhm, aposize=aposize, nlb=nlb, bin_residual=True)
self.plot_dl(savefig=savefig, root=root, dl_type='EE') #EE
self.plot_dl(savefig=savefig, root=root, dl_type='BB') #BB
#%% RMS of the residual maps
def mask_latitude(Map, nside=256, degree=30, inclusive=False, start_southPole=True):
'''
mask the map according to latitude
:param start_southPole: if True, start from the south pole, otherwise, start from the north pole
'''
npix = hp.nside2npix(nside)
if start_southPole:
theta, phi = hp.pix2ang(nside=nside, ipix=npix-1)
else:
theta, phi = hp.pix2ang(nside=nside, ipix=0)
idx_list = hp.query_disc(nside=nside, vec=hp.ang2vec(theta=theta, phi=phi), radius=degree/180.*np.pi, inclusive=inclusive)
mask = np.zeros(npix)
mask[idx_list] = 1
map_mask = Map * mask
return map_mask, idx_list
def get_RMS(Map, nside=256, degree_bin=10, inclusive=False):
rms_num = 180//degree_bin
rms_all = []
for i in range(rms_num):
mask_1, idx_1 = mask_latitude(Map, nside=nside, degree=degree_bin*i, inclusive=inclusive)
mask_2, idx_2 = mask_latitude(Map, nside=nside, degree=degree_bin*(i+1), inclusive=inclusive)
diff = mask_2 - mask_1
pix_num = len(idx_2) - len(idx_1)
rms_all.append( np.sqrt(sum(diff**2)/pix_num) )# RMS, this is right !!!
rms_all = np.array(rms_all)
degs = np.arange(-90, 90, degree_bin) + degree_bin/2.
return degs, rms_all
#%% calcualte cosmic variance
def cosmic_variance(ell, get_std=True):
'''
sigma^2 = (delta_C_ell/C_ell)^2 = 2/(2*ell + 1)
'''
cv = 2/(2*ell + 1)
if get_std:
return np.sqrt(cv)
else:
return cv
| 43.287119 | 188 | 0.595416 |
e09a57fdeb86422c954754b01621e7ae486fc69c | 232 | py | Python | ersilia/db/hubdata/tables.py | ersilia-os/ersilia | eded117d6c7029ce4a497effdb514c21edfe3673 | [
"MIT"
] | 32 | 2020-07-30T20:31:05.000Z | 2022-03-31T17:27:14.000Z | ersilia/db/hubdata/tables.py | ersilia-os/ersilia | eded117d6c7029ce4a497effdb514c21edfe3673 | [
"MIT"
] | 59 | 2022-03-21T10:00:04.000Z | 2022-03-31T23:03:14.000Z | ersilia/db/hubdata/tables.py | ersilia-os/ersilia | eded117d6c7029ce4a497effdb514c21edfe3673 | [
"MIT"
] | 44 | 2022-03-17T13:11:07.000Z | 2022-03-31T19:44:16.000Z | import boto3
class DynamoDbTable(object):
def __init__(self):
pass
class PredictionsTable(DynamoDbTable):
def __init__(self):
pass
class ModelsTable(DynamoDbTable):
def __init__(self):
pass
| 13.647059 | 38 | 0.668103 |
d86b61afcee259774ea259045eeddfe085769f3f | 1,325 | py | Python | Thief Detection System/Model-1/detect.py | sams14/PropTech-Hackathon | b4d750918d4bc1f141f3778647d1a928fd37266d | [
"MIT"
] | 1 | 2021-07-31T14:55:04.000Z | 2021-07-31T14:55:04.000Z | Thief Detection System/Model-1/detect.py | sams14/PropTech-Hackathon | b4d750918d4bc1f141f3778647d1a928fd37266d | [
"MIT"
] | null | null | null | Thief Detection System/Model-1/detect.py | sams14/PropTech-Hackathon | b4d750918d4bc1f141f3778647d1a928fd37266d | [
"MIT"
] | null | null | null | import numpy as np
import cv2
import matplotlib.pyplot as plt
from keras.models import load_model
print('model loading...')
model = load_model('face_CET.h5')
print('model loaded')
def preprocess(img):
img = cv2.resize(img,(200,200))
img = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
img = img.reshape(1,200,200,1)
img = img/255
return img
face_data = "haarcascade_frontalface_default.xml"
classifier = cv2.CascadeClassifier(cv2.data.haarcascades + face_data)
label_map = ['bishal', 'debashish' ,'deepak', 'hitesh', 'sambid']
video_capture = cv2.VideoCapture(0)
ret = True
while ret:
ret, frame = video_capture.read()
image = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = classifier.detectMultiScale(image,1.2,5)
for x,y,w,h in faces:
face_img = frame[y:y+h,x:x+w].copy()
# face_img = np.array(face_img)
# face_img = np.expand_dims(face_img, axis=0)
face_img = preprocess(face_img)
pred = np.argmax(model.predict(face_img), axis=-1) # model.predict_classes(face_img)[0]
# print(pred)
cv2.rectangle(frame,(x,y),(x+w,y+h),(0,0,255),5)
cv2.putText(frame,label_map[pred[0]],(x,y),cv2.FONT_HERSHEY_PLAIN,3,(0,0,255),3)
cv2.imshow('live video',frame)
if cv2.waitKey(1)==ord('q'):
break
cv2.destroyAllWindows()
| 31.547619 | 95 | 0.669434 |
3e89da075e1e7b0f70bbbb82fd91e99a6cf0b25a | 3,301 | py | Python | templates.py | jha8/cgi-lab | 1229f8ccb5036c76ba9bc6bbf55e00921fa5d822 | [
"Apache-2.0"
] | null | null | null | templates.py | jha8/cgi-lab | 1229f8ccb5036c76ba9bc6bbf55e00921fa5d822 | [
"Apache-2.0"
] | null | null | null | templates.py | jha8/cgi-lab | 1229f8ccb5036c76ba9bc6bbf55e00921fa5d822 | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/env python3
# -*- coding: UTF-8 -*-
# Copyright 2016 Eddie Antonio Santos <easantos@ualberta.ca>
#
# 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.
"""
Roll my own "template system".
"""
import cgi
import cgitb
cgitb.enable()
# from cgi import escape
from html import escapse
__all__ = ['login_page', 'secret_page', 'after_login_incorrect']
def login_page():
"""
Returns the HTML for the login page.
"""
return _wrapper(r"""
<h1> Welcome! </h1>
<form method="POST" action="login.py">
<label> <span>Username:</span> <input autofocus type="text" name="username"></label> <br>
<label> <span>Password:</span> <input type="password" name="password"></label>
<button type="submit"> Login! </button>
</form>
""")
def secret_page(username=None, password=None):
"""
Returns the HTML for the page visited after the user has logged-in.
"""
if username is None or password is None:
raise ValueError("You need to pass both username and password!")
return _wrapper("""
<h1> Welcome, {username}! </h1>
<p> <small> Pst! I know your password is
<span class="spoilers"> {password}</span>.
</small>
</p>
""".format(username=escape(username.capitalize()),
password=escape(password)))
def after_login_incorrect():
"""
Returns the HTML for the page when the login credentials were typed
incorrectly.
"""
return _wrapper(r"""
<h1> Login incorrect :c </h1>
<p> Incorrect username or password (hint: <span class="spoilers"> Check
<code>secret.py</code>!</span>)
<p> <a href="login.py"> Try again. </a>
""")
def _wrapper(page):
"""
Wraps some text in common HTML.
"""
return ("""
<!DOCTYPE HTML>
<html>
<head>
<meta charset="utf-8">
<style>
body {
font-family: -apple-system, BlinkMacSystemFont, sans-serif;
max-width: 24em;
margin: auto;
color: #333;
background-color: #fdfdfd
}
.spoilers {
color: rgba(0,0,0,0); border-bottom: 1px dashed #ccc
}
.spoilers:hover {
transition: color 250ms;
color: rgba(36, 36, 36, 1)
}
label {
display: flex;
flex-direction: row;
}
label > span {
flex: 0;
}
label> input {
flex: 1;
}
button {
font-size: larger;
float: right;
margin-top: 6px;
}
</style>
</head>
<body>
""" + page + """
</body>
</html>
""")
| 25.007576 | 97 | 0.557104 |
04027b722b61e15a71dcfaebab56da5c07e9ab62 | 9,249 | py | Python | projects/PanopticFCN_cityscapes/data/cityscapes/dataset_mapper.py | fatihyildiz-cs/detectron2 | 700b1e6685ca95a60e27cb961f363a2ca7f30d3c | [
"Apache-2.0"
] | 4 | 2021-07-13T13:36:38.000Z | 2022-01-27T09:51:26.000Z | projects/PanopticFCN_cityscapes/data/cityscapes/dataset_mapper.py | fatihyildiz-cs/detectron2 | 700b1e6685ca95a60e27cb961f363a2ca7f30d3c | [
"Apache-2.0"
] | null | null | null | projects/PanopticFCN_cityscapes/data/cityscapes/dataset_mapper.py | fatihyildiz-cs/detectron2 | 700b1e6685ca95a60e27cb961f363a2ca7f30d3c | [
"Apache-2.0"
] | 2 | 2021-09-10T11:26:26.000Z | 2022-01-27T09:51:40.000Z | # Copyright (c) Facebook, Inc. and its affiliates.
# Adapted from detectron2/data/dataset_mapper.py
import copy
import logging
import numpy as np
from typing import Callable, List, Union
import torch
import pycocotools
from detectron2.config import configurable
from detectron2.data import MetadataCatalog
from detectron2.data import detection_utils as utils
from detectron2.data import transforms as T
from detectron2.structures import BoxMode
from data.cityscapes.augmentations import RandomCropWithInstance, AugInput
__all__ = ["CityscapesPanopticDatasetMapper"]
class CityscapesPanopticDatasetMapper:
"""
A callable which takes a dataset dict in Detectron2 Dataset format,
and map it into a format used by the model.
This is the default callable to be used to map your dataset dict into training data.
You may need to follow it to implement your own one for customized logic,
such as a different way to read or transform images.
See :doc:`/tutorials/data_loading` for details.
The callable currently does the following:
1. Read the image from "file_name"
2. Applies cropping/geometric transforms to the image and annotations
3. Prepare data and annotations to Tensor and :class:`Instances`
"""
@configurable
def __init__(
self,
cfg,
is_train: bool,
*,
augmentations: List[Union[T.Augmentation, T.Transform]],
image_format: str,
use_instance_mask: bool = False,
instance_mask_format: str = "polygon",
recompute_boxes: bool = False,
):
"""
NOTE: this interface is experimental.
Args:
cfg: config dict
is_train: whether it's used in training or inference
augmentations: a list of augmentations or deterministic transforms to apply
image_format: an image format supported by :func:`detection_utils.read_image`.
use_instance_mask: whether to process instance segmentation annotations, if available
instance_mask_format: one of "polygon" or "bitmask". Process instance segmentation
masks into this format.
recompute_boxes: whether to overwrite bounding box annotations
by computing tight bounding boxes from instance mask annotations.
"""
if recompute_boxes:
assert use_instance_mask, "recompute_boxes requires instance masks"
# fmt: off
self.cfg = cfg
dataset_names = self.cfg.DATASETS.TRAIN
self.meta = MetadataCatalog.get(dataset_names[0])
self.is_train = is_train
self.augmentations = T.AugmentationList(augmentations)
self.image_format = image_format
self.use_instance_mask = use_instance_mask
self.instance_mask_format = instance_mask_format
self.recompute_boxes = recompute_boxes
# fmt: on
logger = logging.getLogger(__name__)
mode = "training" if is_train else "inference"
logger.info(f"[DatasetMapper] Augmentations used in {mode}: {augmentations}")
@classmethod
def from_config(cls, cfg, is_train: bool = True):
augs = utils.build_augmentation(cfg, is_train)
if cfg.INPUT.CROP.ENABLED and is_train:
if cfg.INPUT.CROP.MINIMUM_INST_AREA == 0:
augs.insert(1, T.RandomCrop(cfg.INPUT.CROP.TYPE,
cfg.INPUT.CROP.SIZE))
else:
assert cfg.INPUT.CROP.MINIMUM_INST_AREA > 0
augs.insert(1, RandomCropWithInstance(cfg.INPUT.CROP.TYPE,
cfg.INPUT.CROP.SIZE,
cfg.INPUT.CROP.MINIMUM_INST_AREA))
recompute_boxes = cfg.MODEL.MASK_ON
else:
recompute_boxes = False
ret = {
"cfg": cfg,
"is_train": is_train,
"augmentations": augs,
"image_format": cfg.INPUT.FORMAT,
"use_instance_mask": cfg.MODEL.MASK_ON,
"instance_mask_format": cfg.INPUT.MASK_FORMAT,
"recompute_boxes": recompute_boxes,
}
return ret
def __call__(self, dataset_dict):
"""
Args:
dataset_dict (dict): Metadata of one image, in Detectron2 Dataset format.
Returns:
dict: a format that builtin models in detectron2 accept
"""
dataset_dict = copy.deepcopy(dataset_dict) # it will be modified by code below
# USER: Write your own image loading if it's not from a file
image = utils.read_image(dataset_dict["file_name"], format=self.image_format)
utils.check_image_size(dataset_dict, image)
things_classes = list(self.meta.thing_dataset_id_to_contiguous_id.values())
stuff_classes = np.array(list(self.meta.stuff_dataset_id_to_contiguous_id.values()))
# USER: Remove if you don't do semantic/panoptic segmentation.
if "pan_seg_file_name" in dataset_dict:
pan_seg_gt = utils.read_image(dataset_dict.pop("pan_seg_file_name"))
pan_seg_gt = pan_seg_gt[:, :, 0] + 256 * pan_seg_gt[:, :, 1] + 256 * 256 * pan_seg_gt[:, :, 2]
else:
raise NotImplementedError("Currently only possible if pan seg GT image file name is given")
# pan_seg_gt = None
inst_map = np.zeros_like(pan_seg_gt, dtype=np.uint8)
# Create annotations in desired instance segmentation format
annotations = list()
for segment in dataset_dict['segments_info']:
if segment['category_id'] in things_classes:
annotation = dict()
annotation['bbox'] = segment['bbox']
annotation['bbox_mode'] = BoxMode.XYWH_ABS
annotation['category_id'] = self.meta.contiguous_id_to_thing_train_id[segment['category_id']]
mask = (pan_seg_gt == segment['id']).astype(np.uint8)
if segment['iscrowd'] == 0:
inst_map = inst_map + mask
annotation['segmentation'] = pycocotools.mask.encode(np.asarray(mask, order="F"))
annotation['iscrowd'] = segment['iscrowd']
annotations.append(annotation)
if np.any(inst_map > 1):
raise ValueError("There cannot be multiple instances at a single pixel")
if len(annotations) > 0:
dataset_dict['annotations'] = annotations
# USER: Remove if you don't do semantic/panoptic segmentation.
if "sem_seg_file_name" in dataset_dict:
sem_seg_gt_tmp = utils.read_image(dataset_dict.pop("sem_seg_file_name"), "L").squeeze(2)
else:
raise NotImplementedError("Currently only possible if sem seg GT image file name is given")
# sem_seg_gt = None
# For Cityscapes, the contiguous ids for stuff are equal to the stuff train ids. Change for other datasets.
if self.cfg.MODEL.POSITION_HEAD.STUFF.ALL_CLASSES:
sem_seg_gt = np.where(np.isin(sem_seg_gt_tmp, stuff_classes), sem_seg_gt_tmp, self.meta.ignore_label)
else:
if self.cfg.MODEL.POSITION_HEAD.STUFF.WITH_THING:
sem_seg_gt = np.where(np.isin(sem_seg_gt_tmp, stuff_classes), sem_seg_gt_tmp + 1, self.meta.ignore_label)
# Set things class pixels to 0
sem_seg_gt = np.where(np.isin(sem_seg_gt_tmp, np.array(things_classes)), 0, sem_seg_gt)
else:
sem_seg_gt = np.where(np.isin(sem_seg_gt_tmp, stuff_classes), sem_seg_gt_tmp + 1, self.meta.ignore_label)
aug_input = AugInput(image, sem_seg=sem_seg_gt, inst_map=inst_map)
transforms = self.augmentations(aug_input)
image, sem_seg_gt = aug_input.image, aug_input.sem_seg
image_shape = image.shape[:2] # h, w
# Pytorch's dataloader is efficient on torch.Tensor due to shared-memory,
# but not efficient on large generic data structures due to the use of pickle & mp.Queue.
# Therefore it's important to use torch.Tensor.
dataset_dict["image"] = torch.as_tensor(np.ascontiguousarray(image.transpose(2, 0, 1)))
if sem_seg_gt is not None:
dataset_dict["sem_seg"] = torch.as_tensor(sem_seg_gt.astype("long"))
if not self.is_train:
# USER: Modify this if you want to keep them for some reason.
dataset_dict.pop("annotations", None)
dataset_dict.pop("sem_seg_file_name", None)
return dataset_dict
if "annotations" in dataset_dict:
# USER: Modify this if you want to keep them for some reason.
for anno in dataset_dict["annotations"]:
if not self.use_instance_mask:
anno.pop("segmentation", None)
# USER: Implement additional transformations if you have other types of data
annos = [
utils.transform_instance_annotations(
obj, transforms, image_shape
)
for obj in dataset_dict.pop("annotations")
if obj.get("iscrowd", 0) == 0
]
instances = utils.annotations_to_instances(
annos, image_shape, mask_format=self.instance_mask_format
)
# After transforms such as cropping are applied, the bounding box may no longer
# tightly bound the object. As an example, imagine a triangle object
# [(0,0), (2,0), (0,2)] cropped by a box [(1,0),(2,2)] (XYXY format). The tight
# bounding box of the cropped triangle should be [(1,0),(2,1)], which is not equal to
# the intersection of original bounding box and the cropping box.
if self.recompute_boxes and len(instances) > 0:
instances.gt_boxes = instances.gt_masks.get_bounding_boxes()
dataset_dict["instances"] = utils.filter_empty_instances(instances)
if len(dataset_dict['instances']) == 0:
del dataset_dict["instances"]
return dataset_dict | 41.290179 | 113 | 0.697048 |
d8448caeba16b979c9ff5707d328b907fc2e7114 | 95 | py | Python | code_gazay/salt/src/components/TernausNetV2/abn/__init__.py | artyompal/kaggle_salt | 3c323755730745ac7bbfd106f1f20919cceef0ee | [
"MIT"
] | null | null | null | code_gazay/salt/src/components/TernausNetV2/abn/__init__.py | artyompal/kaggle_salt | 3c323755730745ac7bbfd106f1f20919cceef0ee | [
"MIT"
] | 1 | 2021-03-25T23:31:26.000Z | 2021-03-25T23:31:28.000Z | code_gazay/salt/src/components/TernausNetV2/abn/__init__.py | artyompal/kaggle_salt | 3c323755730745ac7bbfd106f1f20919cceef0ee | [
"MIT"
] | 1 | 2018-11-08T09:30:38.000Z | 2018-11-08T09:30:38.000Z | from .bn import ABN, InPlaceABN, InPlaceABNWrapper
from .residual import IdentityResidualBlock
| 31.666667 | 50 | 0.852632 |
f7a1231e5ca25cb855f87d50eb014c851eddf4e0 | 1,253 | py | Python | ML/Minor/code/common/generate_images_labels.py | SIgnlngX/Minor-Project | f000e16c67f8ce738af96556c161e9087d7bee0f | [
"MIT"
] | 4 | 2017-10-09T19:00:08.000Z | 2019-02-04T14:05:58.000Z | ML/Minor/code/common/generate_images_labels.py | SIgnlngX/Minor-Project | f000e16c67f8ce738af96556c161e9087d7bee0f | [
"MIT"
] | 6 | 2017-10-07T05:46:59.000Z | 2017-12-17T06:57:43.000Z | ML/Minor/code/common/generate_images_labels.py | SIgnlngX/sign-language-interpreter | f000e16c67f8ce738af96556c161e9087d7bee0f | [
"MIT"
] | 8 | 2017-10-06T11:21:07.000Z | 2021-05-02T18:40:41.000Z | #!/usr/bin/env python
from os import walk
from os.path import join, splitext
from ntpath import basename
def get_images_labels_list(images_dir_path):
"""
Recursively iterates through a directory and its subdirectories to list the info all the images found in it.
Returns a list of dictionary where each dictionary contains `image_path` and `image_label`.
"""
images_labels_list = []
for (dirpath, dirnames, filenames) in walk(images_dir_path):
for filename in filenames:
image_path = join(dirpath, filename)
image_label = splitext(basename(dirpath))[0]
image_info = {}
image_info['image_path'] = image_path
image_info['image_label'] = image_label
images_labels_list.append(image_info)
return images_labels_list
def write_images_labels_to_file(images_labels_list, output_file_path):
"""
Writes the list of images-labels to a file.
"""
with open(output_file_path, "w") as output_file:
for image_info in images_labels_list:
image_path = image_info['image_path']
image_label = image_info['image_label']
line = image_path + "\t" + image_label + '\n'
output_file.write(line)
| 36.852941 | 112 | 0.676776 |
b718ae114d6a000b2b381425892ed83ec8453ccc | 1,317 | py | Python | profdispatch.py | morepath/reg | 0ba834088c74f5478dd66e9eab771d1e09fbeb97 | [
"BSD-3-Clause"
] | 48 | 2015-01-10T02:32:25.000Z | 2021-12-16T15:17:25.000Z | profdispatch.py | morepath/reg | 0ba834088c74f5478dd66e9eab771d1e09fbeb97 | [
"BSD-3-Clause"
] | 42 | 2015-01-06T12:06:30.000Z | 2021-04-05T12:41:33.000Z | profdispatch.py | morepath/reg | 0ba834088c74f5478dd66e9eab771d1e09fbeb97 | [
"BSD-3-Clause"
] | 6 | 2015-05-28T07:02:04.000Z | 2020-09-29T20:44:05.000Z | from cProfile import run
from reg import dispatch
from reg import LruCachingKeyLookup
def get_key_lookup(r):
return LruCachingKeyLookup(
r,
component_cache_size=5000,
all_cache_size=5000,
fallback_cache_size=5000,
)
@dispatch(get_key_lookup=get_key_lookup)
def args0():
raise NotImplementedError()
@dispatch("a", get_key_lookup=get_key_lookup)
def args1(a):
raise NotImplementedError()
@dispatch("a", "b", get_key_lookup=get_key_lookup)
def args2(a, b):
raise NotImplementedError()
@dispatch("a", "b", "c", get_key_lookup=get_key_lookup)
def args3(a, b, c):
raise NotImplementedError()
@dispatch("a", "b", "c", "d", get_key_lookup=get_key_lookup)
def args4(a, b, c, d):
raise NotImplementedError()
class Foo:
pass
def myargs0():
return "args0"
def myargs1(a):
return "args1"
def myargs2(a, b):
return "args2"
def myargs3(a, b, c):
return "args3"
def myargs4(a, b, c, d):
return "args4"
args0.register(myargs0)
args1.register(myargs1, a=Foo)
args2.register(myargs2, a=Foo, b=Foo)
args3.register(myargs3, a=Foo, b=Foo, c=Foo)
args4.register(myargs4, a=Foo, b=Foo, c=Foo, d=Foo)
def repeat_args4():
for i in range(10000):
args4(Foo(), Foo(), Foo(), Foo())
run("repeat_args4()", sort="tottime")
| 17.103896 | 60 | 0.671222 |
c4180077c94a1c9221fd49afd14c2fd6fa26a6f0 | 731 | py | Python | apps/articles/models.py | Pavel1114/blogger | 37e20d94b8d78d65d0a3ef7ce0f68cf71baf24fa | [
"MIT"
] | null | null | null | apps/articles/models.py | Pavel1114/blogger | 37e20d94b8d78d65d0a3ef7ce0f68cf71baf24fa | [
"MIT"
] | null | null | null | apps/articles/models.py | Pavel1114/blogger | 37e20d94b8d78d65d0a3ef7ce0f68cf71baf24fa | [
"MIT"
] | null | null | null | from django.db.models import SET_NULL, CharField, ForeignKey, ImageField, TextField
from django.urls import reverse
from model_utils.models import TimeStampedModel
class Article(TimeStampedModel):
title = CharField("Название", max_length=1000)
text = TextField("Текст")
image = ImageField("изображение", upload_to="articles/%Y/%m/")
author = ForeignKey("users.User", verbose_name="автор", on_delete=SET_NULL, null=True, editable=False)
class Meta:
verbose_name = "статья"
verbose_name_plural = "статьи"
ordering = ["-created"]
def __str__(self):
return self.title
def get_absolute_url(self):
return reverse('articles:article_detail', kwargs={'pk': self.pk})
| 33.227273 | 106 | 0.704514 |
43cad4b8611d6a458b6df69e780e2b5bd2db5ff3 | 5,054 | py | Python | autosklearn/pipeline/components/classification/liblinear_svc.py | FelixNeutatz/auto-sklearn | b5d141603332041475ed746aa1640334f5561aea | [
"BSD-3-Clause"
] | 2 | 2020-02-22T15:00:49.000Z | 2020-06-28T08:20:19.000Z | autosklearn/pipeline/components/classification/liblinear_svc.py | FelixNeutatz/auto-sklearn | b5d141603332041475ed746aa1640334f5561aea | [
"BSD-3-Clause"
] | null | null | null | autosklearn/pipeline/components/classification/liblinear_svc.py | FelixNeutatz/auto-sklearn | b5d141603332041475ed746aa1640334f5561aea | [
"BSD-3-Clause"
] | null | null | null | from ConfigSpace.configuration_space import ConfigurationSpace
from ConfigSpace.hyperparameters import UniformFloatHyperparameter, \
CategoricalHyperparameter, Constant
from ConfigSpace.forbidden import ForbiddenEqualsClause, \
ForbiddenAndConjunction
from autosklearn.pipeline.components.base import AutoSklearnClassificationAlgorithm
from autosklearn.pipeline.implementations.util import softmax
from autosklearn.pipeline.constants import DENSE, UNSIGNED_DATA, PREDICTIONS, SPARSE
from autosklearn.util.common import check_for_bool, check_none
class LibLinear_SVC(AutoSklearnClassificationAlgorithm):
# Liblinear is not deterministic as it uses a RNG inside
def __init__(self, penalty, loss, dual, tol, C, multi_class,
fit_intercept, intercept_scaling, class_weight=None,
random_state=None):
self.penalty = penalty
self.loss = loss
self.dual = dual
self.tol = tol
self.C = C
self.multi_class = multi_class
self.fit_intercept = fit_intercept
self.intercept_scaling = intercept_scaling
self.class_weight = class_weight
self.random_state = random_state
self.estimator = None
def fit(self, X, Y):
import sklearn.svm
import sklearn.multiclass
self.C = float(self.C)
self.tol = float(self.tol)
self.dual = check_for_bool(self.dual)
self.fit_intercept = check_for_bool(self.fit_intercept)
self.intercept_scaling = float(self.intercept_scaling)
if check_none(self.class_weight):
self.class_weight = None
estimator = sklearn.svm.LinearSVC(penalty=self.penalty,
loss=self.loss,
dual=self.dual,
tol=self.tol,
C=self.C,
class_weight=self.class_weight,
fit_intercept=self.fit_intercept,
intercept_scaling=self.intercept_scaling,
multi_class=self.multi_class,
random_state=self.random_state)
if len(Y.shape) == 2 and Y.shape[1] > 1:
self.estimator = sklearn.multiclass.OneVsRestClassifier(estimator, n_jobs=1)
else:
self.estimator = estimator
self.estimator.fit(X, Y)
return self
def predict(self, X):
if self.estimator is None:
raise NotImplementedError()
return self.estimator.predict(X)
def predict_proba(self, X):
if self.estimator is None:
raise NotImplementedError()
df = self.estimator.decision_function(X)
return softmax(df)
@staticmethod
def get_properties(dataset_properties=None):
return {'shortname': 'Liblinear-SVC',
'name': 'Liblinear Support Vector Classification',
'handles_regression': False,
'handles_classification': True,
'handles_multiclass': True,
'handles_multilabel': True,
'is_deterministic': False,
'input': (SPARSE, DENSE, UNSIGNED_DATA),
'output': (PREDICTIONS,)}
@staticmethod
def get_hyperparameter_search_space(dataset_properties=None):
cs = ConfigurationSpace()
penalty = CategoricalHyperparameter(
"penalty", ["l1", "l2"], default_value="l2")
loss = CategoricalHyperparameter(
"loss", ["hinge", "squared_hinge"], default_value="squared_hinge")
dual = Constant("dual", "False")
# This is set ad-hoc
tol = UniformFloatHyperparameter(
"tol", 1e-5, 1e-1, default_value=1e-4, log=True)
C = UniformFloatHyperparameter(
"C", 0.03125, 32768, log=True, default_value=1.0)
multi_class = Constant("multi_class", "ovr")
# These are set ad-hoc
fit_intercept = Constant("fit_intercept", "True")
intercept_scaling = Constant("intercept_scaling", 1)
cs.add_hyperparameters([penalty, loss, dual, tol, C, multi_class,
fit_intercept, intercept_scaling])
penalty_and_loss = ForbiddenAndConjunction(
ForbiddenEqualsClause(penalty, "l1"),
ForbiddenEqualsClause(loss, "hinge")
)
constant_penalty_and_loss = ForbiddenAndConjunction(
ForbiddenEqualsClause(dual, "False"),
ForbiddenEqualsClause(penalty, "l2"),
ForbiddenEqualsClause(loss, "hinge")
)
penalty_and_dual = ForbiddenAndConjunction(
ForbiddenEqualsClause(dual, "False"),
ForbiddenEqualsClause(penalty, "l1")
)
cs.add_forbidden_clause(penalty_and_loss)
cs.add_forbidden_clause(constant_penalty_and_loss)
cs.add_forbidden_clause(penalty_and_dual)
return cs
| 39.795276 | 88 | 0.611199 |
ce80da60e0dec7923295a60d598ed9f8bace9c7e | 4,871 | py | Python | reporter.py | ubiquill/infiltration-detection | 687a64a0917a3f02eff9d7697cead247a0c933e0 | [
"Unlicense"
] | 2 | 2015-04-17T04:30:28.000Z | 2015-04-17T21:03:45.000Z | reporter.py | ubiquill/infiltration-detection | 687a64a0917a3f02eff9d7697cead247a0c933e0 | [
"Unlicense"
] | null | null | null | reporter.py | ubiquill/infiltration-detection | 687a64a0917a3f02eff9d7697cead247a0c933e0 | [
"Unlicense"
] | null | null | null | try:
from cStringIO import StringIO
except:
from StringIO import StringIO
class UserReport:
def __init__(self, user, suspicious_subs):
self.first = True
self.user = user
self.suspicious_subs = suspicious_subs
self.outString = None
def __str__(self):
return self.write()
def write(self):
if self.outString == None:
self.output = StringIO()
self._process_data()
self.outString = self.output.getvalue()
self.output.close()
return self.outString
def _process_data(self):
data = {}
post_dic = self.user.get_submitted().get_posts()
comment_dic = self.user.get_comments().get_posts()
for subreddit in sorted(post_dic, key=lambda k: len(post_dic[k]), reverse=True):
if subreddit.lower() in self.suspicious_subs:
if subreddit.lower() not in data:
data[subreddit.lower()] = {}
data[subreddit.lower()]['posts'] = self.user.submitted.get_subreddit_posts(subreddit)
for subreddit in sorted(comment_dic, key=lambda k: len(comment_dic[k]), reverse=True):
if subreddit.lower() in self.suspicious_subs:
if subreddit.lower() not in data:
data[subreddit.lower()] = {}
data[subreddit.lower()]['comments'] = self.user.comments.get_subreddit_posts(subreddit)
if len(data.keys()) < 1:
self.output.write("User has not posted in monitored subreddits")
return
else:
self.output.write("/u/%s " % self.user.username)
self.output.write("post history contains participation in the ")
self.output.write("following subreddits:\n\n")
for subreddit in sorted(data, key=lambda k: ((0 if 'posts' not in data[k] else len(data[k]['posts'])), (0 if 'comments' not in data[k] else len(data[k]['comments']))), reverse=True):
self._write_data(subreddit, data[subreddit])
self.output.write(".")
def _write_data(self, subreddit, sub_data):
prefix = ""
if self.first:
self.first = False
else:
prefix = ".\n\n"
self.output.write("%s/r/%s: " % (prefix, subreddit))
if 'posts' in sub_data:
self._write_post_data(sub_data['posts'])
if 'comments' in sub_data:
if 'posts' in sub_data:
self.output.write("; ")
self._write_comment_data(subreddit, sub_data['comments'])
def _write_post_data(self, posts):
if len(posts) < 1:
return
elif len(posts) == 1:
score = posts[0].score
link = posts[0].permalink
link = link.replace("http://www.", "http://np.")
self.output.write("%d post ([1](%s)), **total score: %d**" % (len(posts), link, score))
elif len(posts) > 1:
score = 0
self.output.write("%d posts (" % (len(posts)))
for post_counter in range(0, len(posts)):
prefix = "" if post_counter == 0 else ", "
# limit due to a limit in reddit comment character length
if post_counter < 8:
link = posts[post_counter].permalink
link = link.replace("http://www.", "http://np.")
self.output.write("%s[%d](%s)" % (prefix, post_counter + 1, link))
score += posts[post_counter].score
self.output.write("), **total score: %d**" % (score))
def _write_comment_data(self, subreddit, comments):
if len(comments) < 1:
return
elif len(comments) == 1:
score = comments[0].score
permalink = "http://www.reddit.com/r/%s/comments/%s/_/%s" % (subreddit, comments[0].link_id[3:], comments[0].id)
link = permalink.replace("http://www.", "http://np.")
self.output.write("%d comment ([1](%s))" % (len(comments), link))
self.output.write(", **total score: %d**" % score)
elif len(comments) > 1:
score = 0
self.output.write("%d comments (" % len(comments))
# loop through each of these comments
for comment_counter in range(0, len(comments)):
score += comments[comment_counter].score
permalink = "http://www.reddit.com/r/%s/comments/%s/_/%s" % (subreddit, comments[comment_counter].link_id[3:], comments[comment_counter].id)
link = permalink.replace("http://www.", "http://np.")
prefix = "" if comment_counter == 0 else ", "
if comment_counter < 8:
self.output.write("%s[%d](%s)" % (prefix, comment_counter + 1, link))
self.output.write("), **combined score: %d**" % score)
| 39.601626 | 194 | 0.552864 |
7b72fd0b01526189ee9750690c5d5ba61691ce85 | 6,206 | py | Python | code/multiagent/scenarios/simple_tag_1v1.py | rahul-dhavalikar/dqn-predator-prey-dynamics | 58c26d71c87bcfaaf729d1f710b9c4458ca4f473 | [
"MIT"
] | 1 | 2021-12-15T10:58:09.000Z | 2021-12-15T10:58:09.000Z | code/multiagent/scenarios/simple_tag_1v1.py | rahul-dhavalikar/dqn-predator-prey-dynamics | 58c26d71c87bcfaaf729d1f710b9c4458ca4f473 | [
"MIT"
] | null | null | null | code/multiagent/scenarios/simple_tag_1v1.py | rahul-dhavalikar/dqn-predator-prey-dynamics | 58c26d71c87bcfaaf729d1f710b9c4458ca4f473 | [
"MIT"
] | 2 | 2018-10-04T02:39:23.000Z | 2021-12-15T10:59:16.000Z | import numpy as np
from multiagent.core import World, Agent, Landmark
from multiagent.scenario import BaseScenario
class Scenario(BaseScenario):
def make_world(self):
world = World()
# set any world properties first
world.dim_c = 2
num_good_agents = 1
num_adversaries = 1
num_agents = num_adversaries + num_good_agents
num_landmarks = 0
# add agents
world.agents = [Agent() for i in range(num_agents)]
for i, agent in enumerate(world.agents):
agent.name = 'agent %d' % i
agent.collide = True
agent.silent = True
agent.adversary = True if i < num_adversaries else False
agent.size = 0.075 if agent.adversary else 0.05
agent.accel = 3.0 if agent.adversary else 4.0
#agent.accel = 20.0 if agent.adversary else 25.0
agent.max_speed = 1.0 if agent.adversary else 1.3
# add landmarks
world.landmarks = [Landmark() for i in range(num_landmarks)]
for i, landmark in enumerate(world.landmarks):
landmark.name = 'landmark %d' % i
landmark.collide = True
landmark.movable = False
landmark.size = 0.11
landmark.boundary = False
# make initial conditions
self.reset_world(world)
return world
def reset_world(self, world):
# random properties for agents
for i, agent in enumerate(world.agents):
agent.color = np.array(
[0.35, 0.85, 0.35]) if not agent.adversary else np.array([0.85, 0.35, 0.35])
# random properties for landmarks
for i, landmark in enumerate(world.landmarks):
landmark.color = np.array([0.25, 0.25, 0.25])
# set random initial states
for agent in world.agents:
agent.state.p_pos = np.random.uniform(-1, +1, world.dim_p)
agent.state.p_vel = np.zeros(world.dim_p)
agent.state.c = np.zeros(world.dim_c)
for i, landmark in enumerate(world.landmarks):
if not landmark.boundary:
landmark.state.p_pos = np.random.uniform(
-0.9, +0.9, world.dim_p)
landmark.state.p_vel = np.zeros(world.dim_p)
def benchmark_data(self, agent, world):
# returns data for benchmarking purposes
if agent.adversary:
collisions = 0
for a in self.good_agents(world):
if self.is_collision(a, agent):
collisions += 1
return collisions
else:
return 0
def is_collision(self, agent1, agent2):
delta_pos = agent1.state.p_pos - agent2.state.p_pos
dist = np.sqrt(np.sum(np.square(delta_pos)))
dist_min = agent1.size + agent2.size
return True if dist < dist_min else False
# return all agents that are not adversaries
def good_agents(self, world):
return [agent for agent in world.agents if not agent.adversary]
# return all adversarial agents
def adversaries(self, world):
return [agent for agent in world.agents if agent.adversary]
def reward(self, agent, world):
# Agents are rewarded based on minimum agent distance to each landmark
main_reward = self.adversary_reward(
agent, world) if agent.adversary else self.agent_reward(agent, world)
return main_reward
def agent_reward(self, agent, world):
# Agents are negatively rewarded if caught by adversaries
rew = 0
shape = True
adversaries = self.adversaries(world)
# reward can optionally be shaped (increased reward for increased
# distance from adversary)
if shape:
for adv in adversaries:
rew += 0.1 * \
np.sqrt(np.sum(np.square(agent.state.p_pos - adv.state.p_pos)))
if agent.collide:
for a in adversaries:
if self.is_collision(a, agent):
rew -= 100
# agents are penalized for exiting the screen, so that they can be
# caught by the adversaries
def bound(x):
if x < 0.9:
return 0
if x < 1.0:
return (x - 0.9) * 10
return min(np.exp(2 * x - 2), 10)
for p in range(world.dim_p):
x = abs(agent.state.p_pos[p])
rew -= bound(x)
return rew
def adversary_reward(self, agent, world):
# Adversaries are rewarded for collisions with agents
rew = 0
shape = True
agents = self.good_agents(world)
adversaries = self.adversaries(world)
# reward can optionally be shaped (decreased reward for increased
# distance from agents)
if shape:
for adv in adversaries:
rew -= 0.1 * \
min([np.sqrt(np.sum(np.square(a.state.p_pos - adv.state.p_pos)))
for a in agents])
if agent.collide:
for ag in agents:
for adv in adversaries:
if self.is_collision(ag, adv):
rew += 100
return rew
def observation(self, agent, world):
# get positions of all entities in this agent's reference frame
entity_pos = []
for entity in world.landmarks:
if not entity.boundary:
entity_pos.append(entity.state.p_pos - agent.state.p_pos)
# communication of all other agents
comm = []
other_pos = []
other_vel = []
for other in world.agents:
if other is agent:
continue
comm.append(other.state.c)
other_pos.append(other.state.p_pos - agent.state.p_pos)
if not other.adversary:
other_vel.append(other.state.p_vel)
return np.concatenate([agent.state.p_vel] + [agent.state.p_pos] + entity_pos + other_pos + other_vel)
def done(self, agent, world):
for p in range(world.dim_p):
x = abs(agent.state.p_pos[p])
if (x > 1.0):
return True
return False
| 37.841463 | 109 | 0.573638 |
b2a47ed1a0312af5e9062703589654adce7be82f | 3,034 | py | Python | meiduo_29/meiduo_29/apps/oauth/serializers.py | Adolph-Anthony/Django_meiduo-shopping-mall | 4437ad1b9ed99ab9447b41406535fbfe2d0fa53c | [
"MIT"
] | null | null | null | meiduo_29/meiduo_29/apps/oauth/serializers.py | Adolph-Anthony/Django_meiduo-shopping-mall | 4437ad1b9ed99ab9447b41406535fbfe2d0fa53c | [
"MIT"
] | null | null | null | meiduo_29/meiduo_29/apps/oauth/serializers.py | Adolph-Anthony/Django_meiduo-shopping-mall | 4437ad1b9ed99ab9447b41406535fbfe2d0fa53c | [
"MIT"
] | null | null | null | from django_redis import get_redis_connection
from rest_framework import serializers
from rest_framework_jwt.settings import api_settings
from users.models import User
from .utils import OAuthQQ
from .models import OAuthQQUser
class OAuthQQUserSerializer(serializers.ModelSerializer):
'''
QQ登录绑定用户
'''
sms_code = serializers.CharField(label='短信验证码',write_only=True)
access_token = serializers.CharField(label='操作凭证',write_only=True)
token=serializers.CharField(read_only=True)
mobile = serializers.RegexField(label='手机号', regex=r'^1[3-9]\d{9}$')
# password = serializers.CharField(label='密码', max_length=20, min_length=8)
class Meta:
model=User
fields=('mobile','password','sms_code','access_token','id','username','token')
extra_kwargs={
'username':{
'read_only':True
},
'password': {
'write_only': True,
'min_length': 8,
'max_length': 20,
'error_messages': {
'min_length': '仅允许8-20个字符的密码',
'max_length': '仅允许8-20个字符的密码',
}
}
}
# 校验数据
def validate(self,attrs):
# 检验access_token
access_token = attrs['access_token']
openid = OAuthQQ.check_bind_user_access(access_token)
if not openid:
raise serializers.ValidationError('无效的access_token')
attrs['openid'] = openid
# 检验短信验证码
mobile = attrs['mobile']
sms_code = attrs['sms_code']
# 连接redis verify_codes数据库
redis_conn = get_redis_connection('verify_code')
real_sms_code = redis_conn.get('sms_%s' % mobile)
if real_sms_code.decode() != sms_code:
raise serializers.ValidationError('短信验证码错误')
# 如果用户存在，检查用户密码
try:
user = User.objects.get(mobile=mobile)
except User.DoesNotExist:
pass
else:
# 判断用户是否被绑定过
if OAuthQQUser.objects.get(user_id=user.id):
raise serializers.ValidationError('账号已绑定')
password = attrs['password']
if not user.check_password(password):
raise serializers.ValidationError('密码错误')
attrs['user'] = user
return attrs
def create(self,validated_data):
openid=validated_data['openid']
user=validated_data.get('user')
mobile=validated_data['mobile']
password=validated_data['password']
# 判断用户是否存在
if not user:
# 如果不存在，绑定 创建OAuthQQUser数据
user=User.objects.create_user(username=mobile,mobile=mobile,password=password)
OAuthQQUser.objects.create(user=user,openid=openid)
# 签发JWT_token
jwt_payload_handler = api_settings.JWT_PAYLOAD_HANDLER
jwt_encode_handler = api_settings.JWT_ENCODE_HANDLER
payload = jwt_payload_handler(user)
token = jwt_encode_handler(payload)
user.token = token
return user
| 33.711111 | 90 | 0.614041 |
ebd2c853428dc5c72d2d6b84a3e5d7e2f29e500b | 2,890 | py | Python | sketch/sketch.py | jack1142/GrandeCogs-V3 | 3a92096c96c98abe5d34998b00dea4967a30647f | [
"MIT"
] | 3 | 2018-06-09T21:56:58.000Z | 2018-08-26T01:34:55.000Z | sketch/sketch.py | jack1142/GrandeCogs-V3 | 3a92096c96c98abe5d34998b00dea4967a30647f | [
"MIT"
] | 4 | 2018-10-06T16:37:57.000Z | 2020-12-01T14:16:11.000Z | sketch/sketch.py | jack1142/GrandeCogs-V3 | 3a92096c96c98abe5d34998b00dea4967a30647f | [
"MIT"
] | 8 | 2018-08-26T01:29:41.000Z | 2020-01-17T16:06:31.000Z | import discord, base64, re
from redbot.core import checks, commands
from redbot.core import Config
from redbot.core.data_manager import bundled_data_path
from PIL import Image, ImageDraw
from io import BytesIO
BaseCog = getattr(commands, "Cog", object)
class Sketch(BaseCog):
def __init__(self,bot):
self.bot = bot
self.config = Config.get_conf(self, identifier=3715378133574, force_registration=True)
default_user = {
"image_data": False,
"coords": (0, 0),
}
self.config.register_user(**default_user)
@commands.group()
async def sketch(self, ctx):
"""Sketch"""
pass
@sketch.command()
async def view(self, ctx):
"""View your Sketch"""
sketch = await self.config.user(ctx.author).image_data()
if sketch == False:
sketch = bundled_data_path(self) / "sketch.png"
else:
sketch = BytesIO(base64.b64decode(sketch))
await ctx.send(file=discord.File(sketch, "sketch.png"))
@sketch.command()
async def draw(self, ctx, x_coord, y_coord, colour="#000000", width=1):
"""Draw your Sketch"""
hex_match = re.search(r"^#(?:[0-9a-fA-F]{3}){1,2}$", colour)
if not hex_match:
await ctx.send("Please use a valid hex colour.")
return
new_coords = (int(x_coord), int(y_coord))
await self._make_line(ctx.author, new_coords, colour, width)
img = await self.config.user(ctx.author).image_data()
img = BytesIO(base64.b64decode(img))
await ctx.send(file=discord.File(img, "sketch.png"))
@sketch.command()
async def reset(self, ctx):
"""Reset your Sketch"""
await self.config.user(ctx.author).image_data.set(False)
await self.config.user(ctx.author).coords.set(False)
await ctx.send("Your personal Sketch has been reset!")
async def _make_line(self, author, new_coords, colour, width):
sketch = await self.config.user(author).image_data()
if sketch == False:
sketch = bundled_data_path(self) / "sketch.png"
else:
sketch = BytesIO(base64.b64decode(sketch))
im = Image.open(sketch)
old_coords = await self.config.user(author).coords()
hex = colour.replace("#", "")
colour = tuple(int(hex[i:i + 2], 16) for i in (0, 2, 4)) + (255,)
canvas = Image.new('RGBA', (600, 400), (255, 0, 0, 0))
draw = ImageDraw.Draw(canvas)
if width != 0:
draw.line([old_coords, new_coords], fill=colour, width=width)
im.paste(canvas, (100, 100), mask=canvas)
img = BytesIO()
im.save(img, "png")
img.seek(0)
await self.config.user(author).image_data.set(base64.b64encode(img.read()).decode())
await self.config.user(author).coords.set(new_coords)
return
| 35.243902 | 94 | 0.608997 |
b4da5739cc2e9098d28fae1b899ac67e0e4f633d | 3,393 | py | Python | train_with_manifold/train_mlp.py | CarolMazini/Manifold-Learning-for-Real-World-Event-Understanding | 36151165f0ce23c168b893a9e916023b34630cf3 | [
"MIT"
] | null | null | null | train_with_manifold/train_mlp.py | CarolMazini/Manifold-Learning-for-Real-World-Event-Understanding | 36151165f0ce23c168b893a9e916023b34630cf3 | [
"MIT"
] | null | null | null | train_with_manifold/train_mlp.py | CarolMazini/Manifold-Learning-for-Real-World-Event-Understanding | 36151165f0ce23c168b893a9e916023b34630cf3 | [
"MIT"
] | null | null | null | from sklearn.neural_network import MLPClassifier
from sklearn.model_selection import train_test_split
import numpy as np
import random
import time
import argparse
##################################MAIN#####################################
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Training MLP classifier with combined features.')
parser.add_argument('--dataset', dest='dataset', type=str,help='include the name of the dataset to extract image features',default='bombing')
parser.add_argument('--method', dest='method', type=str,help='type of train combination: contrastive or triplet',default='triplet')
parser.add_argument('--aug', dest='aug', type=str,help='include _aug to use augmented data', default='')
args = parser.parse_args()
dataset = args.dataset #'wedding', 'fire', 'bombing', 'museu_nacional' or 'bangladesh_fire'
aug=args.aug
method = args.method
random.seed(a=0)
def compute_normalized_accuracy(y_true, y_pred):
correct_pos = 0
correct_neg = 0
incorrect_pos = 0
incorrect_neg = 0
total_pos = np.sum(y_true)
total_neg = len(y_true) - total_pos
for i in range(len(y_pred)):
if y_true[i] == 1:
if y_pred[i] == 1:
correct_pos+=1
else:
incorrect_pos+=1
else:
if y_pred[i] == 0:
correct_neg+=1
else:
incorrect_neg+=1
norm_acc = (correct_pos/total_pos + correct_neg/total_neg)/2.0
precision = correct_pos/(correct_pos+incorrect_neg)
recall = correct_pos/total_pos
print('correct pos: ', correct_pos)
print('correct neg: ', correct_neg)
print('incorrect pos: ', incorrect_pos)
print('incorrect pos: ', incorrect_neg)
return norm_acc,precision,recall
X_train_positive = np.load('../out_files/features/'+method+'/'+dataset+'/1024_512_positive_'+dataset+aug+'_train.npy')
X_train_negative = np.load('../out_files/features/'+method+'/'+dataset+'/1024_512_negative_'+dataset+aug+'_train.npy')
Y_train_positive = np.ones(len(X_train_positive))
Y_train_negative = np.zeros(len(X_train_negative))
X_train = np.concatenate([X_train_positive, X_train_negative], axis=0)
Y_train = np.concatenate([Y_train_positive, Y_train_negative], axis=0)
print(X_train.shape)
total_train = len(X_train)
sampled_list = random.sample(range(total_train), total_train)
X_train = X_train[sampled_list,:]
Y_train = Y_train[sampled_list]
X_test_positive = np.load('../out_files/features/'+method+'/'+dataset+'/1024_512_positive_'+dataset+aug+'_test.npy')
X_test_negative = np.load('../out_files/features/'+method+'/'+dataset+'/1024_512_negative_'+dataset+aug+'_test.npy')
Y_test_positive = np.ones(len(X_test_positive))
Y_test_negative = np.zeros(len(X_test_negative))
X_test = np.concatenate([X_test_positive, X_test_negative], axis=0)
Y_test = np.concatenate([Y_test_positive, Y_test_negative], axis=0)
print('Total pos: ', X_test_positive.shape)
print('Total neg: ', len(X_test_negative))
start_time = time.time()
clf = MLPClassifier(hidden_layer_sizes = (64,),random_state=1, max_iter=1000, activation = 'tanh', learning_rate = 'adaptive').fit(X_train, Y_train)
y_pred =clf.predict(X_test) #classe
print("--- %s seconds ---" % (time.time() - start_time))
norm_acc,precision,recall = compute_normalized_accuracy(Y_test, y_pred)
print('Norm Acc: ', norm_acc)
print('Precision: ', precision)
print('Recall: ', recall)
| 32.009434 | 149 | 0.714412 |
cdbd5f0d9f375d91b92b86c1a1fb2faef1528ffe | 11,332 | py | Python | legion/robot/legion/robot/libraries/utils.py | legion-platform/legion | db3a1d99f1005cb881b16af6075a806725123031 | [
"ECL-2.0",
"Apache-2.0"
] | 19 | 2018-05-20T17:06:55.000Z | 2022-01-04T14:15:09.000Z | legion/robot/legion/robot/libraries/utils.py | legion-platform/legion | db3a1d99f1005cb881b16af6075a806725123031 | [
"ECL-2.0",
"Apache-2.0"
] | 917 | 2018-05-18T18:54:54.000Z | 2021-09-01T10:41:56.000Z | legion/robot/legion/robot/libraries/utils.py | legion-platform/legion | db3a1d99f1005cb881b16af6075a806725123031 | [
"ECL-2.0",
"Apache-2.0"
] | 13 | 2018-07-23T18:09:51.000Z | 2019-08-05T15:37:30.000Z | #
# Copyright 2017 EPAM Systems
#
# 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.
#
"""
Robot test library - utils
"""
import datetime
import socket
import time
import json
import requests
from legion.robot.libraries.auth_client import get_authorization_headers
class Utils:
"""
Utilities for robot tests
"""
@staticmethod
def request_as_authorized_user(service_url):
"""
Request resource as authorized user
:param service_url: target URL
:type service_url: str
:return: final response - Response
"""
return requests.get(service_url, headers=get_authorization_headers())
@staticmethod
def request_as_unauthorized_user(service_url):
"""
Request resource as authorized user
:param service_url: target URL
:type service_url: str
:return: final response - Response
"""
return requests.get(service_url)
@staticmethod
def check_domain_exists(domain):
"""
Check that domain (DNS name) has been registered
:param domain: domain name (A record)
:type domain: str
:raises: Exception
:return: None
"""
try:
return socket.gethostbyname(domain)
except socket.gaierror as exception:
if exception.errno == -2:
raise Exception('Unknown domain name: {}'.format(domain))
else:
raise
@staticmethod
def check_remote_file_exists(url, login=None, password=None):
"""
Check that remote file exists (through HTTP/HTTPS)
:param url: remote file URL
:type url: str
:param login: login
:type login: str or None
:param password: password
:type password: str or None
:raises: Exception
:return: None
"""
credentials = None
if login and password:
credentials = login, password
response = requests.get(url,
stream=True,
verify=False,
auth=credentials)
if response.status_code >= 400 or response.status_code < 200:
raise Exception('Returned wrong status code: {}'.format(response.status_code))
response.close()
@staticmethod
def sum_up(*values):
"""
Sum up arguments
:param values: Values to sum up
:type values: int[]
:return: Sum
:rtype: int
"""
result = 0
for value in values:
result += value
return result
@staticmethod
def subtract(minuend, *values):
"""
Subtract arguments from minuend
:param minuend: A Minuend
:type minuend: int
:param values: Values to subtract from minuend
:type values: int[]
:rtype: int
"""
result = minuend
for value in values:
result -= value
return result
@staticmethod
def parse_edi_inspect_columns_info(edi_output):
"""
Parse EDI inspect output
:param edi_output: EDI stdout
:type edi_output: str
:return: list[list[str]] -- parsed EDI output
"""
lines = edi_output.splitlines()
if len(lines) < 2:
return []
return [[item.strip() for item in line.split('|') if item] for line in lines[1:]]
@staticmethod
def find_model_information_in_edi(parsed_edi_output, model_name):
"""
Get specific model EDI output
:param parsed_edi_output: parsed EDI output
:type parsed_edi_output: list[list[str]]
:param model_name: model deployment name
:type model_name: str
:return: list[str] -- parsed EDI output for specific model
"""
founded = [info for info in parsed_edi_output if info[0] == model_name]
if not founded:
raise Exception(f'Info about model {model_name} not found')
return founded[0]
@staticmethod
def check_valid_http_response(url, token=None):
"""
Check if model return valid code for get request
:param url: url with model_name for checking
:type url: str
:param token: token for the authorization
:type token: str
:return: str -- response text
"""
tries = 6
error = None
for i in range(tries):
try:
if token:
headers = {"Authorization": "Bearer {}".format(token)}
response = requests.get(url, timeout=10, headers=headers)
else:
response = requests.get(url, timeout=10)
if response.status_code == 200:
return response.text
elif i >= 5:
raise Exception('Returned wrong status code: {}'.format(response.status_code))
elif response.status_code >= 400 or response.status_code < 200:
print('Response code = {}, sleep and try again'.format(response.status_code))
time.sleep(3)
except requests.exceptions.Timeout as e:
error = e
time.sleep(3)
if error:
raise error
else:
raise Exception('Unexpected case happen!')
@staticmethod
def execute_post_request_as_authorized_user(url, data=None, json_data=None):
"""
Execute post request as authorized user
:param url: url for request
:type url: str
:param data: data to send in request
:type data: dict
:param json_data: json data to send in request
:type json_data: dict
:return: str -- response text
"""
response = requests.post(url, json=json_data, data=data, headers=get_authorization_headers())
return {"text": response.text, "code": response.status_code}
@staticmethod
def get_component_auth_page(url, token=None):
"""
Get component main auth page
:param url: component url
:type url: str
:param token: token for the authorization
:type url: str
:return: response_code and response_text
:rtype: dict
"""
if token:
headers = {"Authorization": "Bearer {}".format(token)}
response = requests.get(url, timeout=10, headers=headers)
else:
response = requests.get(url, timeout=10)
return {"response_code": response.status_code, "response_text": response.text}
@staticmethod
def parse_json_string(string):
"""
Parse JSON string
:param string: JSON string
:type string: str
:return: dict -- object
"""
return json.loads(string)
@staticmethod
def get_current_time(time_template):
"""
Get templated time
:param time_template: time template
:type time_template: str
:return: None or str -- time from template
"""
return datetime.datetime.utcnow().strftime(time_template)
@staticmethod
def get_future_time(offset, time_template):
"""
Get templated time on `offset` seconds in future
:param offset: time offset from current time in seconds
:type offset: int
:param time_template: time template
:type time_template: str
:return: str -- time from template
"""
return (datetime.datetime.utcnow() +
datetime.timedelta(seconds=offset)).strftime(time_template)
@staticmethod
def reformat_time(time_str, initial_format, target_format):
"""
Convert date/time string from initial_format to target_format
:param time_str: date/time string
:type time_str: str
:param initial_format: initial format of date/time string
:type initial_format: str
:param target_format: format to convert date/time object to
:type target_format: str
:return: str -- date/time string according to target_format
"""
datetime_obj = datetime.datetime.strptime(time_str, initial_format)
return datetime.datetime.strftime(datetime_obj, target_format)
@staticmethod
def get_timestamp_from_string(time_string, string_format):
"""
Get timestamp from date/time string
:param time_string: date/time string
:type time_string: str
:param string_format: format of time_string
:type string_format: str
:return: float -- timestamp
"""
return datetime.datetime.strptime(time_string, string_format).timestamp()
@staticmethod
def wait_up_to_second(second, time_template=None):
"""
Wait up to second then generate time from template
:param second: target second (0..59)
:type second: int
:param time_template: (Optional) time template
:type time_template: str
:return: None or str -- time from template
"""
current_second = datetime.datetime.now().second
target_second = int(second)
if current_second > target_second:
sleep_time = 60 - (current_second - target_second)
else:
sleep_time = target_second - current_second
if sleep_time:
print('Waiting {} second(s)'.format(sleep_time))
time.sleep(sleep_time)
if time_template:
return Utils.get_current_time(time_template)
@staticmethod
def order_list_of_dicts_by_key(list_of_dicts, field_key):
"""
Order list of dictionaries by key as integer
:param list_of_dicts: list of dictionaries
:type list_of_dicts: List[dict]
:param field_key: key to be ordered by
:type field_key: str
:return: List[dict] -- ordered list
"""
return sorted(list_of_dicts, key=lambda item: int(item[field_key]))
@staticmethod
def concatinate_list_of_dicts_field(list_of_dicts, field_key):
"""
Concatinate list of dicts field to string
:param list_of_dicts: list of dictionaries
:type list_of_dicts: List[dict]
:param field_key: key of field to be concatinated
:type field_key: str
:return: str -- concatinated string
"""
return ''.join([item[field_key] for item in list_of_dicts])
@staticmethod
def repeat_string_n_times(string, count):
"""
Repeat string N times
:param string: string to be repeated
:type string: str
:param count: count
:type count: int
:return: str -- result string
"""
return string * int(count)
| 31.131868 | 101 | 0.602277 |
aad951bf268fec1fadbc38a10c07a7a6e525dcc5 | 505 | py | Python | tests/test_wrapper_instance.py | shadowlion/transact_api | 101b05216ddcbf8ee6d4da6db28c3450499177d3 | [
"MIT"
] | null | null | null | tests/test_wrapper_instance.py | shadowlion/transact_api | 101b05216ddcbf8ee6d4da6db28c3450499177d3 | [
"MIT"
] | 4 | 2022-02-08T14:00:38.000Z | 2022-03-16T12:14:14.000Z | tests/test_wrapper_instance.py | shadowlion/transact_api | 101b05216ddcbf8ee6d4da6db28c3450499177d3 | [
"MIT"
] | null | null | null | import pytest
from transact_api import TransactApi
def test_class_instantiation_no_key():
with pytest.raises(TypeError):
TransactApi()
def test_class_instantiation_with_keys():
client = TransactApi(client_id="asdf", developer_api_key="qwer")
assert isinstance(client, TransactApi)
assert client.client_id == "asdf"
assert client.developer_api_key == "qwer"
assert not client.sandbox
assert client.base_url == "https://api.norcapsecurities.com/tapiv3/index.php/v3"
| 28.055556 | 84 | 0.750495 |
2c45f0377e6d77fa983cef7cad5d0018c89fc638 | 575 | py | Python | Py/datastructures/queue.py | Zotyamester/datastructures | b743e203434138a2a12aa5cc876f59cbb338280d | [
"MIT"
] | null | null | null | Py/datastructures/queue.py | Zotyamester/datastructures | b743e203434138a2a12aa5cc876f59cbb338280d | [
"MIT"
] | null | null | null | Py/datastructures/queue.py | Zotyamester/datastructures | b743e203434138a2a12aa5cc876f59cbb338280d | [
"MIT"
] | null | null | null | class Queue:
def __init__(self):
self.data = []
def push(self, data):
self.data = [data] + self.data
def pop(self):
self.data.pop(-1)
def top(self):
self.data[-1]
def __len__(self):
return len(self.data)
def __str__(self):
if len(self.data) == 0:
return ''
s = str(self.data[0])
for i in range(1, len(self.data)):
s += ' ' + str(self.data[i])
return s
def empty(self):
return len(self.data) == 0
def clear(self):
self.data.clear()
| 25 | 42 | 0.495652 |
d9c7b87c13b626d0ed0ea5af5677c3a0ffa0db2d | 235 | py | Python | appengine_config.py | SalamiArmy/InfoBoet | 71df751e50b4b458db44444ef7d6dfe6f68e648f | [
"Apache-2.0"
] | 1 | 2021-07-14T21:48:48.000Z | 2021-07-14T21:48:48.000Z | appengine_config.py | SalamiArmy/InfoBoet | 71df751e50b4b458db44444ef7d6dfe6f68e648f | [
"Apache-2.0"
] | 6 | 2017-11-27T06:04:34.000Z | 2020-02-19T05:15:02.000Z | appengine_config.py | SalamiArmy/InfoBoet | 71df751e50b4b458db44444ef7d6dfe6f68e648f | [
"Apache-2.0"
] | 2 | 2017-08-16T20:26:02.000Z | 2020-11-10T18:44:11.000Z | from google.appengine.ext import vendor
# Add any third-party libraries installed in the "lib" folder.
try:
vendor.add('lib')
except:
print('InfoBoet failed to add it\'s third-party libraries folder to app engine\'s vendor.')
| 29.375 | 95 | 0.73617 |
8f336e51322f2adfd73e2631f1db7c000d646b92 | 4,448 | py | Python | ocr.py | vanatteveldt/teletekst_scraper | f112319ff577cd62818f530696ff737b1e9dcc39 | [
"MIT"
] | null | null | null | ocr.py | vanatteveldt/teletekst_scraper | f112319ff577cd62818f530696ff737b1e9dcc39 | [
"MIT"
] | null | null | null | ocr.py | vanatteveldt/teletekst_scraper | f112319ff577cd62818f530696ff737b1e9dcc39 | [
"MIT"
] | null | null | null | import logging
import re
import sys
from io import StringIO
from pathlib import Path
from subprocess import check_call, check_output
from PIL import Image
LETTERPATH = Path.cwd()/"letters"
def get_letter_img(img, x, y):
return img.crop((6 + x*11, y*22, 6+(x+1)*11, (y+1)*22)).convert("L")
def get_headline_img(img, x):
return img.crop((6 + x * 11, 22, 6 + (x + 1) * 11, 66)).convert("L")
def gocr(letter, h):
f = Path("/tmp/{hash}.png")
letter.save(f)
l = check_output(f"gocr {f}", shell=True).decode("utf-8").strip()
if l == "/":
l = '⁄' # linux does not like slashes in file names
f2 = LETTERPATH/f"letter_{h}__{l}.png"
f.rename(f2)
return l
KNOWN = None
def initialize_known():
global KNOWN
if KNOWN is not None:
return
KNOWN = {}
for f in LETTERPATH.glob("*.png"):
m = re.match(r"letter_(-?\d+)__(.)\.png", f.name)
if not m:
print(f.name)
raise
h, letter = m.groups()
img = Image.open(f)
KNOWN[int(h)] = (letter, img)
def compare_images(img1, img2):
if img1.size[1] != img2.size[1]:
return None
return sum((x1-x2)**2 for (x1, x2) in zip(list(img1.getdata()),list(img2.getdata())))
def closest(letter: Image, accept_zero=True):
winner, winning_score, winning_hash = None, None, None
for hash_, (l, img) in KNOWN.items():
score = compare_images(letter, img)
if score is None:
continue
if (not accept_zero) and (score == 0):
continue
if winning_score is None or score < winning_score:
winner = l
winning_score = score
winning_hash = hash_
return winner, winning_score, winning_hash
def guess(letter: Image, accept_zero=True):
winner, winning_score, winning_hash = closest(letter, accept_zero=accept_zero)
if winning_score < 90000:
return winner
if letter.size[1] == 44:
# Try resizing
img = letter.resize((11, 22))
winner2, winning_score2, _ = closest(img, accept_zero=accept_zero)
if winning_score2 < 350000:
return winner2
hash_ = hash(tuple(letter.getdata()))
logging.warning(f"Bad match: letters/letter_{hash_}__{winner}.png (score: {winning_score}, best match letters/letter_{winning_hash}__{winner}.png, size {letter.size})")
return winner
# letters/letter_-3616073949698735120__-.png
# letters/letter_7901707541910618925__-.png
def ocr(letter: Image):
initialize_known()
h = hash(tuple(letter.getdata()))
if h in KNOWN:
l, img = KNOWN[h]
#logging.info(f"KNOWN: {l} letters/letter_{h}__{l}.png")
else:
l = guess(letter)
fn = LETTERPATH/f"letter_{h}__{l}.png"
letter.save(fn)
KNOWN[h] = (l, letter)
logging.info(f"GUESS: {l} letters/letter_{h}__{l}.png")
return l
def get_body(img):
out = StringIO()
width, height = img.size
nrows = height // 22
text = []
for y in range(4, nrows):
prev = None
for x in range(0, 39):
i = get_letter_img(img, x, y)
l = ocr(i)
if prev in (".", ",", ":") and l.isalpha():
out.write(" ")
out.write(l)
prev=l
out.write("\n")
txt = out.getvalue()
txt = "\n\n".join(re.sub(r"\s+", " ", x).strip()
for x in re.split(r"\n\s*\n", txt))
return txt.strip()
def get_headline(img):
out = StringIO()
prev = None
for x in range(0, 39):
i = get_headline_img(img, x)
l = ocr(i)
if prev in (".", ",", ":") and l.isalpha():
out.write(" ")
out.write(l)
prev = l
return out.getvalue().strip()
def get_text(img_fn: str):
img = Image.open(img_fn)
headline = get_headline(img)
body = get_body(img)
return f"{headline}\n\n{body}"
if __name__ == '__main__':
logging.basicConfig(level=logging.INFO, format='[%(asctime)s %(name)-12s %(levelname)-5s] %(message)s')
print(get_text(sys.argv[1]))
sys.exit()
initialize_known()
for f in LETTERPATH.glob("*.png"):
image = Image.open(f)
if image.size[1] != 44:
continue
m = re.match(r"letter_(-?\d+)__(.)\.png", f.name)
h, letter = m.groups()
winner = guess(image)
if letter != winner:# and score > 90000:
print(letter, winner) | 27.974843 | 172 | 0.573741 |
4ad46ff3bce6f4d782cd8155e1d3dd750dc6e7c9 | 763 | py | Python | setup.py | namuyan/rpvm | 2137ae4c578287c4cf4edd6b53c32eefc54649d6 | [
"MIT"
] | 1 | 2019-07-18T06:56:46.000Z | 2019-07-18T06:56:46.000Z | setup.py | namuyan/rpvm | 2137ae4c578287c4cf4edd6b53c32eefc54649d6 | [
"MIT"
] | null | null | null | setup.py | namuyan/rpvm | 2137ae4c578287c4cf4edd6b53c32eefc54649d6 | [
"MIT"
] | null | null | null | #!/user/env python3
# -*- coding: utf-8 -*-
from setuptools import setup, find_packages
try:
readme = open('README.md', mode='r').read()
except Exception:
readme = ''
try:
install_requires = open('requirements.txt', mode='r').read()
except Exception:
install_requires = None
setup(
name="rpvm",
version='0.1.0a1',
url='https://github.com/namuyan/rpvm',
author='namuyan',
description='Restricted Python Virtual Machine',
long_description=readme,
long_description_content_type='text/markdown',
packages=find_packages(),
install_requires=install_requires,
license="MIT Licence",
classifiers=[
'Programming Language :: Python :: 3.6',
'License :: OSI Approved :: MIT License',
],
)
| 23.121212 | 64 | 0.656619 |
81abdf559593ee6a303b493415aae3263255cb0e | 89,072 | py | Python | wandb/sdk/data_types.py | Qwasser/client | 15cc5baea4a6a8cfa3406111a4f6283917bb6e00 | [
"MIT"
] | null | null | null | wandb/sdk/data_types.py | Qwasser/client | 15cc5baea4a6a8cfa3406111a4f6283917bb6e00 | [
"MIT"
] | null | null | null | wandb/sdk/data_types.py | Qwasser/client | 15cc5baea4a6a8cfa3406111a4f6283917bb6e00 | [
"MIT"
] | null | null | null | import codecs
import hashlib
import json
import logging
import numbers
import os
import re
import shutil
import sys
import six
from six.moves.collections_abc import Sequence as SixSequence
import wandb
from wandb import util
from wandb._globals import _datatypes_callback
from wandb.compat import tempfile
from wandb.util import has_num
from .interface import _dtypes
if wandb.TYPE_CHECKING:
from typing import (
TYPE_CHECKING,
ClassVar,
Dict,
Optional,
Type,
Union,
Sequence,
Tuple,
Set,
Any,
List,
cast,
)
if TYPE_CHECKING: # pragma: no cover
from .interface.artifacts import ArtifactEntry
from .wandb_artifacts import Artifact as LocalArtifact
from .wandb_run import Run as LocalRun
from wandb.apis.public import Artifact as PublicArtifact
import numpy as np # type: ignore
import pandas as pd # type: ignore
import matplotlib # type: ignore
import plotly # type: ignore
import PIL # type: ignore
import torch # type: ignore
from typing import TextIO
TypeMappingType = Dict[str, Type["WBValue"]]
NumpyHistogram = Tuple[np.ndarray, np.ndarray]
ValToJsonType = Union[
dict,
"WBValue",
Sequence["WBValue"],
"plotly.Figure",
"matplotlib.artist.Artist",
"pd.DataFrame",
object,
]
ImageDataType = Union[
"matplotlib.artist.Artist", "PIL.Image", "TorchTensorType", "np.ndarray"
]
ImageDataOrPathType = Union[str, "Image", ImageDataType]
TorchTensorType = Union["torch.Tensor", "torch.Variable"]
_MEDIA_TMP = tempfile.TemporaryDirectory("wandb-media")
_DATA_FRAMES_SUBDIR = os.path.join("media", "data_frames")
def _safe_sdk_import() -> Tuple[Type["LocalRun"], Type["LocalArtifact"]]:
"""Safely import due to circular deps"""
from .wandb_artifacts import Artifact as LocalArtifact
from .wandb_run import Run as LocalRun
return LocalRun, LocalArtifact
class _WBValueArtifactSource(object):
artifact: "PublicArtifact"
name: Optional[str]
def __init__(self, artifact: "PublicArtifact", name: Optional[str] = None) -> None:
self.artifact = artifact
self.name = name
class _WBValueArtifactTarget(object):
artifact: "LocalArtifact"
name: Optional[str]
def __init__(self, artifact: "LocalArtifact", name: Optional[str] = None) -> None:
self.artifact = artifact
self.name = name
class WBValue(object):
"""
Abstract parent class for things that can be logged by `wandb.log()` and
visualized by wandb.
The objects will be serialized as JSON and always have a _type attribute
that indicates how to interpret the other fields.
"""
# Class Attributes
_type_mapping: ClassVar[Optional["TypeMappingType"]] = None
# override _log_type to indicate the type which the subclass deserializes
_log_type: ClassVar[Optional[str]] = None
# Instance Attributes
_artifact_source: Optional[_WBValueArtifactSource]
_artifact_target: Optional[_WBValueArtifactTarget]
def __init__(self) -> None:
self._artifact_source = None
self._artifact_target = None
def to_json(self, run_or_artifact: Union["LocalRun", "LocalArtifact"]) -> dict:
"""Serializes the object into a JSON blob, using a run or artifact to store additional data.
Args:
run_or_artifact (wandb.Run | wandb.Artifact): the Run or Artifact for which this object should be generating
JSON for - this is useful to to store additional data if needed.
Returns:
dict: JSON representation
"""
raise NotImplementedError
@classmethod
def from_json(
cls: Type["WBValue"], json_obj: dict, source_artifact: "PublicArtifact"
) -> "WBValue":
"""Deserialize a `json_obj` into it's class representation. If additional resources were stored in the
`run_or_artifact` artifact during the `to_json` call, then those resources are expected to be in
the `source_artifact`.
Args:
json_obj (dict): A JSON dictionary to deserialize
source_artifact (wandb.Artifact): An artifact which will hold any additional resources which were stored
during the `to_json` function.
"""
raise NotImplementedError
@classmethod
def with_suffix(cls: Type["WBValue"], name: str, filetype: str = "json") -> str:
"""Helper function to return the name with suffix added if not already
Args:
name (str): the name of the file
filetype (str, optional): the filetype to use. Defaults to "json".
Returns:
str: a filename which is suffixed with it's `_log_type` followed by the filetype
"""
if cls._log_type is not None:
suffix = cls._log_type + "." + filetype
else:
suffix = filetype
if not name.endswith(suffix):
return name + "." + suffix
return name
@staticmethod
def init_from_json(
json_obj: dict, source_artifact: "PublicArtifact"
) -> "Optional[WBValue]":
"""Looks through all subclasses and tries to match the json obj with the class which created it. It will then
call that subclass' `from_json` method. Importantly, this function will set the return object's `source_artifact`
attribute to the passed in source artifact. This is critical for artifact bookkeeping. If you choose to create
a wandb.Value via it's `from_json` method, make sure to properly set this `artifact_source` to avoid data duplication.
Args:
json_obj (dict): A JSON dictionary to deserialize. It must contain a `_type` key. The value of
this key is used to lookup the correct subclass to use.
source_artifact (wandb.Artifact): An artifact which will hold any additional resources which were stored
during the `to_json` function.
Returns:
wandb.Value: a newly created instance of a subclass of wandb.Value
"""
class_option = WBValue.type_mapping().get(json_obj["_type"])
if class_option is not None:
obj = class_option.from_json(json_obj, source_artifact)
obj._set_artifact_source(source_artifact)
return obj
return None
@staticmethod
def type_mapping() -> "TypeMappingType":
"""Returns a map from `_log_type` to subclass. Used to lookup correct types for deserialization.
Returns:
dict: dictionary of str:class
"""
if WBValue._type_mapping is None:
WBValue._type_mapping = {}
frontier = [WBValue]
explored = set([])
while len(frontier) > 0:
class_option = frontier.pop()
explored.add(class_option)
if class_option._log_type is not None:
WBValue._type_mapping[class_option._log_type] = class_option
for subclass in class_option.__subclasses__():
if subclass not in explored:
frontier.append(subclass)
return WBValue._type_mapping
def __eq__(self, other: object) -> bool:
return id(self) == id(other)
def __ne__(self, other: object) -> bool:
return not self.__eq__(other)
def to_data_array(self) -> List[Any]:
"""Converts the object to a list of primitives representing the underlying data"""
raise NotImplementedError
def _set_artifact_source(
self, artifact: "PublicArtifact", name: Optional[str] = None
) -> None:
assert (
self._artifact_source is None
), "Cannot update artifact_source. Existing source: {}/{}".format(
self._artifact_source.artifact, self._artifact_source.name
)
self._artifact_source = _WBValueArtifactSource(artifact, name)
def _set_artifact_target(
self, artifact: "LocalArtifact", name: Optional[str] = None
) -> None:
assert (
self._artifact_target is None
), "Cannot update artifact_target. Existing target: {}/{}".format(
self._artifact_target.artifact, self._artifact_target.name
)
self._artifact_target = _WBValueArtifactTarget(artifact, name)
def _get_artifact_reference_entry(self) -> Optional["ArtifactEntry"]:
ref_entry = None
# If the object is coming from another artifact
if self._artifact_source and self._artifact_source.name:
ref_entry = self._artifact_source.artifact.get_path(
type(self).with_suffix(self._artifact_source.name)
)
# Else, if the object is destined for another artifact
elif (
self._artifact_target
and self._artifact_target.name
and self._artifact_target.artifact._logged_artifact is not None
):
# Currently, we do not have a way to obtain a reference URL without waiting for the
# upstream artifact to be logged. This implies that this only works online as well.
self._artifact_target.artifact.wait()
ref_entry = self._artifact_target.artifact.get_path(
type(self).with_suffix(self._artifact_target.name)
)
return ref_entry
class Histogram(WBValue):
"""wandb class for histograms.
This object works just like numpy's histogram function
https://docs.scipy.org/doc/numpy/reference/generated/numpy.histogram.html
Examples:
Generate histogram from a sequence
```python
wandb.Histogram([1,2,3])
```
Efficiently initialize from np.histogram.
```python
hist = np.histogram(data)
wandb.Histogram(np_histogram=hist)
```
Arguments:
sequence: (array_like) input data for histogram
np_histogram: (numpy histogram) alternative input of a precoomputed histogram
num_bins: (int) Number of bins for the histogram. The default number of bins
is 64. The maximum number of bins is 512
Attributes:
bins: ([float]) edges of bins
histogram: ([int]) number of elements falling in each bin
"""
MAX_LENGTH: int = 512
_log_type = "histogram"
def __init__(
self,
sequence: Optional[Sequence] = None,
np_histogram: Optional["NumpyHistogram"] = None,
num_bins: int = 64,
) -> None:
if np_histogram:
if len(np_histogram) == 2:
self.histogram = (
np_histogram[0].tolist()
if hasattr(np_histogram[0], "tolist")
else np_histogram[0]
)
self.bins = (
np_histogram[1].tolist()
if hasattr(np_histogram[1], "tolist")
else np_histogram[1]
)
else:
raise ValueError(
"Expected np_histogram to be a tuple of (values, bin_edges) or sequence to be specified"
)
else:
np = util.get_module(
"numpy", required="Auto creation of histograms requires numpy"
)
self.histogram, self.bins = np.histogram(sequence, bins=num_bins)
self.histogram = self.histogram.tolist()
self.bins = self.bins.tolist()
if len(self.histogram) > self.MAX_LENGTH:
raise ValueError(
"The maximum length of a histogram is %i" % self.MAX_LENGTH
)
if len(self.histogram) + 1 != len(self.bins):
raise ValueError("len(bins) must be len(histogram) + 1")
def to_json(self, run: Union["LocalRun", "LocalArtifact"] = None) -> dict:
return {"_type": self._log_type, "values": self.histogram, "bins": self.bins}
def __sizeof__(self) -> int:
"""This returns an estimated size in bytes, currently the factor of 1.7
is used to account for the JSON encoding. We use this in tb_watcher.TBHistory
"""
return int((sys.getsizeof(self.histogram) + sys.getsizeof(self.bins)) * 1.7)
class Media(WBValue):
"""A WBValue that we store as a file outside JSON and show in a media panel
on the front end.
If necessary, we move or copy the file into the Run's media directory so that it gets
uploaded.
"""
_path: Optional[str]
_run: Optional["LocalRun"]
_caption: Optional[str]
_is_tmp: Optional[bool]
_extension: Optional[str]
_sha256: Optional[str]
_size: Optional[int]
def __init__(self, caption: Optional[str] = None) -> None:
super(Media, self).__init__()
self._path = None
# The run under which this object is bound, if any.
self._run = None
self._caption = caption
def _set_file(
self, path: str, is_tmp: bool = False, extension: Optional[str] = None
) -> None:
self._path = path
self._is_tmp = is_tmp
self._extension = extension
if extension is not None and not path.endswith(extension):
raise ValueError(
'Media file extension "{}" must occur at the end of path "{}".'.format(
extension, path
)
)
with open(self._path, "rb") as f:
self._sha256 = hashlib.sha256(f.read()).hexdigest()
self._size = os.path.getsize(self._path)
@classmethod
def get_media_subdir(cls: Type["Media"]) -> str:
raise NotImplementedError
@staticmethod
def captions(
media_items: Sequence["Media"],
) -> Union[bool, Sequence[Optional[str]]]:
if media_items[0]._caption is not None:
return [m._caption for m in media_items]
else:
return False
def is_bound(self) -> bool:
return self._run is not None
def file_is_set(self) -> bool:
return self._path is not None and self._sha256 is not None
def bind_to_run(
self,
run: "LocalRun",
key: Union[int, str],
step: Union[int, str],
id_: Optional[Union[int, str]] = None,
) -> None:
"""Bind this object to a particular Run.
Calling this function is necessary so that we have somewhere specific to
put the file associated with this object, from which other Runs can
refer to it.
"""
if not self.file_is_set():
raise AssertionError("bind_to_run called before _set_file")
# The following two assertions are guaranteed to pass
# by definition file_is_set, but are needed for
# mypy to understand that these are strings below.
assert isinstance(self._path, six.string_types)
assert isinstance(self._sha256, six.string_types)
if run is None:
raise TypeError('Argument "run" must not be None.')
self._run = run
# Following assertion required for mypy
assert self._run is not None
if self._extension is None:
_, extension = os.path.splitext(os.path.basename(self._path))
else:
extension = self._extension
if id_ is None:
id_ = self._sha256[:8]
file_path = _wb_filename(key, step, id_, extension)
media_path = os.path.join(self.get_media_subdir(), file_path)
new_path = os.path.join(self._run.dir, media_path)
util.mkdir_exists_ok(os.path.dirname(new_path))
if self._is_tmp:
shutil.move(self._path, new_path)
self._path = new_path
self._is_tmp = False
_datatypes_callback(media_path)
else:
shutil.copy(self._path, new_path)
self._path = new_path
_datatypes_callback(media_path)
def to_json(self, run: Union["LocalRun", "LocalArtifact"]) -> dict:
"""Serializes the object into a JSON blob, using a run or artifact to store additional data. If `run_or_artifact`
is a wandb.Run then `self.bind_to_run()` must have been previously been called.
Args:
run_or_artifact (wandb.Run | wandb.Artifact): the Run or Artifact for which this object should be generating
JSON for - this is useful to to store additional data if needed.
Returns:
dict: JSON representation
"""
# NOTE: uses of Audio in this class are a temporary hack -- when Ref support moves up
# into Media itself we should get rid of them
from wandb.data_types import Audio
json_obj = {}
run_class, artifact_class = _safe_sdk_import()
if isinstance(run, run_class):
if not self.is_bound():
raise RuntimeError(
"Value of type {} must be bound to a run with bind_to_run() before being serialized to JSON.".format(
type(self).__name__
)
)
assert (
self._run is run
), "We don't support referring to media files across runs."
# The following two assertions are guaranteed to pass
# by definition is_bound, but are needed for
# mypy to understand that these are strings below.
assert isinstance(self._path, six.string_types)
json_obj.update(
{
"_type": "file", # TODO(adrian): This isn't (yet) a real media type we support on the frontend.
"path": util.to_forward_slash_path(
os.path.relpath(self._path, self._run.dir)
),
"sha256": self._sha256,
"size": self._size,
}
)
artifact_entry = self._get_artifact_reference_entry()
if artifact_entry is not None:
json_obj["artifact_path"] = artifact_entry.ref_url()
elif isinstance(run, artifact_class):
if self.file_is_set():
# The following two assertions are guaranteed to pass
# by definition of the call above, but are needed for
# mypy to understand that these are strings below.
assert isinstance(self._path, six.string_types)
assert isinstance(self._sha256, six.string_types)
artifact = run # Checks if the concrete image has already been added to this artifact
name = artifact.get_added_local_path_name(self._path)
if name is None:
if self._is_tmp:
name = os.path.join(
self.get_media_subdir(), os.path.basename(self._path)
)
else:
# If the files is not temporary, include the first 8 characters of the file's SHA256 to
# avoid name collisions. This way, if there are two images `dir1/img.png` and `dir2/img.png`
# we end up with a unique path for each.
name = os.path.join(
self.get_media_subdir(),
self._sha256[:8],
os.path.basename(self._path),
)
# if not, check to see if there is a source artifact for this object
if (
self._artifact_source
is not None
# and self._artifact_source.artifact != artifact
):
default_root = self._artifact_source.artifact._default_root()
# if there is, get the name of the entry (this might make sense to move to a helper off artifact)
if self._path.startswith(default_root):
name = self._path[len(default_root) :]
name = name.lstrip(os.sep)
# Add this image as a reference
path = self._artifact_source.artifact.get_path(name)
artifact.add_reference(path.ref_url(), name=name)
elif isinstance(self, Audio) and Audio.path_is_reference(
self._path
):
artifact.add_reference(self._path, name=name)
else:
entry = artifact.add_file(
self._path, name=name, is_tmp=self._is_tmp
)
name = entry.path
json_obj["path"] = name
json_obj["_type"] = self._log_type
return json_obj
@classmethod
def from_json(
cls: Type["Media"], json_obj: dict, source_artifact: "PublicArtifact"
) -> "Media":
"""Likely will need to override for any more complicated media objects"""
return cls(source_artifact.get_path(json_obj["path"]).download())
def __eq__(self, other: object) -> bool:
"""Likely will need to override for any more complicated media objects"""
return (
isinstance(other, self.__class__)
and hasattr(self, "_sha256")
and hasattr(other, "_sha256")
and self._sha256 == other._sha256
)
class BatchableMedia(Media):
"""Parent class for Media we treat specially in batches, like images and
thumbnails.
Apart from images, we just use these batches to help organize files by name
in the media directory.
"""
def __init__(self) -> None:
super(BatchableMedia, self).__init__()
@classmethod
def seq_to_json(
cls: Type["BatchableMedia"],
seq: Sequence["BatchableMedia"],
run: "LocalRun",
key: str,
step: Union[int, str],
) -> dict:
raise NotImplementedError
class Object3D(BatchableMedia):
"""
Wandb class for 3D point clouds.
Arguments:
data_or_path: (numpy array, string, io)
Object3D can be initialized from a file or a numpy array.
The file types supported are obj, gltf, babylon, stl. You can pass a path to
a file or an io object and a file_type which must be one of `'obj', 'gltf', 'babylon', 'stl'`.
The shape of the numpy array must be one of either:
```python
[[x y z], ...] nx3
[x y z c], ...] nx4 where c is a category with supported range [1, 14]
[x y z r g b], ...] nx4 where is rgb is color
```
"""
SUPPORTED_TYPES: ClassVar[Set[str]] = set(
["obj", "gltf", "glb", "babylon", "stl", "pts.json"]
)
_log_type: ClassVar[str] = "object3D-file"
def __init__(
self, data_or_path: Union["np.ndarray", str, "TextIO"], **kwargs: str
) -> None:
super(Object3D, self).__init__()
if hasattr(data_or_path, "name"):
# if the file has a path, we just detect the type and copy it from there
data_or_path = data_or_path.name # type: ignore
if hasattr(data_or_path, "read"):
if hasattr(data_or_path, "seek"):
data_or_path.seek(0) # type: ignore
object_3d = data_or_path.read() # type: ignore
extension = kwargs.pop("file_type", None)
if extension is None:
raise ValueError(
"Must pass file type keyword argument when using io objects."
)
if extension not in Object3D.SUPPORTED_TYPES:
raise ValueError(
"Object 3D only supports numpy arrays or files of the type: "
+ ", ".join(Object3D.SUPPORTED_TYPES)
)
tmp_path = os.path.join(
_MEDIA_TMP.name, util.generate_id() + "." + extension
)
with open(tmp_path, "w") as f:
f.write(object_3d)
self._set_file(tmp_path, is_tmp=True)
elif isinstance(data_or_path, six.string_types):
path = data_or_path
extension = None
for supported_type in Object3D.SUPPORTED_TYPES:
if path.endswith(supported_type):
extension = supported_type
break
if not extension:
raise ValueError(
"File '"
+ path
+ "' is not compatible with Object3D: supported types are: "
+ ", ".join(Object3D.SUPPORTED_TYPES)
)
self._set_file(data_or_path, is_tmp=False)
# Supported different types and scene for 3D scenes
elif isinstance(data_or_path, dict) and "type" in data_or_path:
if data_or_path["type"] == "lidar/beta":
data = {
"type": data_or_path["type"],
"vectors": data_or_path["vectors"].tolist()
if "vectors" in data_or_path
else [],
"points": data_or_path["points"].tolist()
if "points" in data_or_path
else [],
"boxes": data_or_path["boxes"].tolist()
if "boxes" in data_or_path
else [],
}
else:
raise ValueError(
"Type not supported, only 'lidar/beta' is currently supported"
)
tmp_path = os.path.join(_MEDIA_TMP.name, util.generate_id() + ".pts.json")
json.dump(
data,
codecs.open(tmp_path, "w", encoding="utf-8"),
separators=(",", ":"),
sort_keys=True,
indent=4,
)
self._set_file(tmp_path, is_tmp=True, extension=".pts.json")
elif _is_numpy_array(data_or_path):
np_data = data_or_path
# The following assertion is required for numpy to trust that
# np_data is numpy array. The reason it is behind a False
# guard is to ensure that this line does not run at runtime,
# which would cause a runtime error if the user's machine did
# not have numpy installed.
if wandb.TYPE_CHECKING and TYPE_CHECKING:
assert isinstance(np_data, np.ndarray)
if len(np_data.shape) != 2 or np_data.shape[1] not in {3, 4, 6}:
raise ValueError(
"""The shape of the numpy array must be one of either
[[x y z], ...] nx3
[x y z c], ...] nx4 where c is a category with supported range [1, 14]
[x y z r g b], ...] nx4 where is rgb is color"""
)
list_data = np_data.tolist()
tmp_path = os.path.join(_MEDIA_TMP.name, util.generate_id() + ".pts.json")
json.dump(
list_data,
codecs.open(tmp_path, "w", encoding="utf-8"),
separators=(",", ":"),
sort_keys=True,
indent=4,
)
self._set_file(tmp_path, is_tmp=True, extension=".pts.json")
else:
raise ValueError("data must be a numpy array, dict or a file object")
@classmethod
def get_media_subdir(cls: Type["Object3D"]) -> str:
return os.path.join("media", "object3D")
def to_json(self, run_or_artifact: Union["LocalRun", "LocalArtifact"]) -> dict:
json_dict = super(Object3D, self).to_json(run_or_artifact)
json_dict["_type"] = Object3D._log_type
_, artifact_class = _safe_sdk_import()
if isinstance(run_or_artifact, artifact_class):
if self._path is None or not self._path.endswith(".pts.json"):
raise ValueError(
"Non-point cloud 3D objects are not yet supported with Artifacts"
)
return json_dict
@classmethod
def seq_to_json(
cls: Type["Object3D"],
seq: Sequence["BatchableMedia"],
run: "LocalRun",
key: str,
step: Union[int, str],
) -> dict:
seq = list(seq)
jsons = [obj.to_json(run) for obj in seq]
for obj in jsons:
expected = util.to_forward_slash_path(cls.get_media_subdir())
if not obj["path"].startswith(expected):
raise ValueError(
"Files in an array of Object3D's must be in the {} directory, not {}".format(
expected, obj["path"]
)
)
return {
"_type": "object3D",
"filenames": [
os.path.relpath(j["path"], cls.get_media_subdir()) for j in jsons
],
"count": len(jsons),
"objects": jsons,
}
class Molecule(BatchableMedia):
"""
Wandb class for Molecular data
Arguments:
data_or_path: (string, io)
Molecule can be initialized from a file name or an io object.
"""
SUPPORTED_TYPES = set(
["pdb", "pqr", "mmcif", "mcif", "cif", "sdf", "sd", "gro", "mol2", "mmtf"]
)
_log_type = "molecule-file"
def __init__(self, data_or_path: Union[str, "TextIO"], **kwargs: str) -> None:
super(Molecule, self).__init__()
if hasattr(data_or_path, "name"):
# if the file has a path, we just detect the type and copy it from there
data_or_path = data_or_path.name # type: ignore
if hasattr(data_or_path, "read"):
if hasattr(data_or_path, "seek"):
data_or_path.seek(0) # type: ignore
molecule = data_or_path.read() # type: ignore
extension = kwargs.pop("file_type", None)
if extension is None:
raise ValueError(
"Must pass file type keyword argument when using io objects."
)
if extension not in Molecule.SUPPORTED_TYPES:
raise ValueError(
"Molecule 3D only supports files of the type: "
+ ", ".join(Molecule.SUPPORTED_TYPES)
)
tmp_path = os.path.join(
_MEDIA_TMP.name, util.generate_id() + "." + extension
)
with open(tmp_path, "w") as f:
f.write(molecule)
self._set_file(tmp_path, is_tmp=True)
elif isinstance(data_or_path, six.string_types):
extension = os.path.splitext(data_or_path)[1][1:]
if extension not in Molecule.SUPPORTED_TYPES:
raise ValueError(
"Molecule only supports files of the type: "
+ ", ".join(Molecule.SUPPORTED_TYPES)
)
self._set_file(data_or_path, is_tmp=False)
else:
raise ValueError("Data must be file name or a file object")
@classmethod
def get_media_subdir(cls: Type["Molecule"]) -> str:
return os.path.join("media", "molecule")
def to_json(self, run_or_artifact: Union["LocalRun", "LocalArtifact"]) -> dict:
json_dict = super(Molecule, self).to_json(run_or_artifact)
json_dict["_type"] = self._log_type
if self._caption:
json_dict["caption"] = self._caption
return json_dict
@classmethod
def seq_to_json(
cls: Type["Molecule"],
seq: Sequence["BatchableMedia"],
run: "LocalRun",
key: str,
step: Union[int, str],
) -> dict:
seq = list(seq)
jsons = [obj.to_json(run) for obj in seq]
for obj in jsons:
expected = util.to_forward_slash_path(cls.get_media_subdir())
if not obj["path"].startswith(expected):
raise ValueError(
"Files in an array of Molecule's must be in the {} directory, not {}".format(
cls.get_media_subdir(), obj["path"]
)
)
return {
"_type": "molecule",
"filenames": [obj["path"] for obj in jsons],
"count": len(jsons),
"captions": Media.captions(seq),
}
class Html(BatchableMedia):
"""
Wandb class for arbitrary html
Arguments:
data: (string or io object) HTML to display in wandb
inject: (boolean) Add a stylesheet to the HTML object. If set
to False the HTML will pass through unchanged.
"""
_log_type = "html-file"
def __init__(self, data: Union[str, "TextIO"], inject: bool = True) -> None:
super(Html, self).__init__()
data_is_path = isinstance(data, six.string_types) and os.path.exists(data)
data_path = ""
if data_is_path:
assert isinstance(data, six.string_types)
data_path = data
with open(data_path, "r") as file:
self.html = file.read()
elif isinstance(data, six.string_types):
self.html = data
elif hasattr(data, "read"):
if hasattr(data, "seek"):
data.seek(0)
self.html = data.read()
else:
raise ValueError("data must be a string or an io object")
if inject:
self.inject_head()
if inject or not data_is_path:
tmp_path = os.path.join(_MEDIA_TMP.name, util.generate_id() + ".html")
with open(tmp_path, "w") as out:
out.write(self.html)
self._set_file(tmp_path, is_tmp=True)
else:
self._set_file(data_path, is_tmp=False)
def inject_head(self) -> None:
join = ""
if "<head>" in self.html:
parts = self.html.split("<head>", 1)
parts[0] = parts[0] + "<head>"
elif "<html>" in self.html:
parts = self.html.split("<html>", 1)
parts[0] = parts[0] + "<html><head>"
parts[1] = "</head>" + parts[1]
else:
parts = ["", self.html]
parts.insert(
1,
'<base target="_blank"><link rel="stylesheet" type="text/css" href="https://app.wandb.ai/normalize.css" />',
)
self.html = join.join(parts).strip()
@classmethod
def get_media_subdir(cls: Type["Html"]) -> str:
return os.path.join("media", "html")
def to_json(self, run_or_artifact: Union["LocalRun", "LocalArtifact"]) -> dict:
json_dict = super(Html, self).to_json(run_or_artifact)
json_dict["_type"] = self._log_type
return json_dict
@classmethod
def from_json(
cls: Type["Html"], json_obj: dict, source_artifact: "PublicArtifact"
) -> "Html":
return cls(source_artifact.get_path(json_obj["path"]).download(), inject=False)
@classmethod
def seq_to_json(
cls: Type["Html"],
seq: Sequence["BatchableMedia"],
run: "LocalRun",
key: str,
step: Union[int, str],
) -> dict:
base_path = os.path.join(run.dir, cls.get_media_subdir())
util.mkdir_exists_ok(base_path)
meta = {
"_type": "html",
"count": len(seq),
"html": [h.to_json(run) for h in seq],
}
return meta
class Video(BatchableMedia):
"""
Wandb representation of video.
Arguments:
data_or_path: (numpy array, string, io)
Video can be initialized with a path to a file or an io object.
The format must be "gif", "mp4", "webm" or "ogg".
The format must be specified with the format argument.
Video can be initialized with a numpy tensor.
The numpy tensor must be either 4 dimensional or 5 dimensional.
Channels should be (time, channel, height, width) or
(batch, time, channel, height width)
caption: (string) caption associated with the video for display
fps: (int) frames per second for video. Default is 4.
format: (string) format of video, necessary if initializing with path or io object.
"""
_log_type = "video-file"
EXTS = ("gif", "mp4", "webm", "ogg")
_width: Optional[int]
_height: Optional[int]
def __init__(
self,
data_or_path: Union["np.ndarray", str, "TextIO"],
caption: Optional[str] = None,
fps: int = 4,
format: Optional[str] = None,
):
super(Video, self).__init__()
self._fps = fps
self._format = format or "gif"
self._width = None
self._height = None
self._channels = None
self._caption = caption
if self._format not in Video.EXTS:
raise ValueError("wandb.Video accepts %s formats" % ", ".join(Video.EXTS))
if isinstance(data_or_path, six.BytesIO):
filename = os.path.join(
_MEDIA_TMP.name, util.generate_id() + "." + self._format
)
with open(filename, "wb") as f:
f.write(data_or_path.read())
self._set_file(filename, is_tmp=True)
elif isinstance(data_or_path, six.string_types):
_, ext = os.path.splitext(data_or_path)
ext = ext[1:].lower()
if ext not in Video.EXTS:
raise ValueError(
"wandb.Video accepts %s formats" % ", ".join(Video.EXTS)
)
self._set_file(data_or_path, is_tmp=False)
# ffprobe -v error -select_streams v:0 -show_entries stream=width,height -of csv=p=0 data_or_path
else:
if hasattr(data_or_path, "numpy"): # TF data eager tensors
self.data = data_or_path.numpy() # type: ignore
elif _is_numpy_array(data_or_path):
self.data = data_or_path
else:
raise ValueError(
"wandb.Video accepts a file path or numpy like data as input"
)
self.encode()
def encode(self) -> None:
mpy = util.get_module(
"moviepy.editor",
required='wandb.Video requires moviepy and imageio when passing raw data. Install with "pip install moviepy imageio"',
)
tensor = self._prepare_video(self.data)
_, self._height, self._width, self._channels = tensor.shape
# encode sequence of images into gif string
clip = mpy.ImageSequenceClip(list(tensor), fps=self._fps)
filename = os.path.join(
_MEDIA_TMP.name, util.generate_id() + "." + self._format
)
if wandb.TYPE_CHECKING and TYPE_CHECKING:
kwargs: Dict[str, Optional[bool]] = {}
try: # older versions of moviepy do not support logger argument
kwargs = {"logger": None}
if self._format == "gif":
clip.write_gif(filename, **kwargs)
else:
clip.write_videofile(filename, **kwargs)
except TypeError:
try: # even older versions of moviepy do not support progress_bar argument
kwargs = {"verbose": False, "progress_bar": False}
if self._format == "gif":
clip.write_gif(filename, **kwargs)
else:
clip.write_videofile(filename, **kwargs)
except TypeError:
kwargs = {
"verbose": False,
}
if self._format == "gif":
clip.write_gif(filename, **kwargs)
else:
clip.write_videofile(filename, **kwargs)
self._set_file(filename, is_tmp=True)
@classmethod
def get_media_subdir(cls: Type["Video"]) -> str:
return os.path.join("media", "videos")
def to_json(self, run_or_artifact: Union["LocalRun", "LocalArtifact"]) -> dict:
json_dict = super(Video, self).to_json(run_or_artifact)
json_dict["_type"] = self._log_type
if self._width is not None:
json_dict["width"] = self._width
if self._height is not None:
json_dict["height"] = self._height
if self._caption:
json_dict["caption"] = self._caption
return json_dict
def _prepare_video(self, video: "np.ndarray") -> "np.ndarray":
"""This logic was mostly taken from tensorboardX"""
np = util.get_module(
"numpy",
required='wandb.Video requires numpy when passing raw data. To get it, run "pip install numpy".',
)
if video.ndim < 4:
raise ValueError(
"Video must be atleast 4 dimensions: time, channels, height, width"
)
if video.ndim == 4:
video = video.reshape(1, *video.shape)
b, t, c, h, w = video.shape
if video.dtype != np.uint8:
logging.warning("Converting video data to uint8")
video = video.astype(np.uint8)
def is_power2(num: int) -> bool:
return num != 0 and ((num & (num - 1)) == 0)
# pad to nearest power of 2, all at once
if not is_power2(video.shape[0]):
len_addition = int(2 ** video.shape[0].bit_length() - video.shape[0])
video = np.concatenate(
(video, np.zeros(shape=(len_addition, t, c, h, w))), axis=0
)
n_rows = 2 ** ((b.bit_length() - 1) // 2)
n_cols = video.shape[0] // n_rows
video = np.reshape(video, newshape=(n_rows, n_cols, t, c, h, w))
video = np.transpose(video, axes=(2, 0, 4, 1, 5, 3))
video = np.reshape(video, newshape=(t, n_rows * h, n_cols * w, c))
return video
@classmethod
def seq_to_json(
cls: Type["Video"],
seq: Sequence["BatchableMedia"],
run: "LocalRun",
key: str,
step: Union[int, str],
) -> dict:
base_path = os.path.join(run.dir, cls.get_media_subdir())
util.mkdir_exists_ok(base_path)
meta = {
"_type": "videos",
"count": len(seq),
"videos": [v.to_json(run) for v in seq],
"captions": Video.captions(seq),
}
return meta
# Allows encoding of arbitrary JSON structures
# as a file
#
# This class should be used as an abstract class
# extended to have validation methods
class JSONMetadata(Media):
"""
JSONMetadata is a type for encoding arbitrary metadata as files.
"""
def __init__(self, val: dict) -> None:
super(JSONMetadata, self).__init__()
self.validate(val)
self._val = val
ext = "." + self.type_name() + ".json"
tmp_path = os.path.join(_MEDIA_TMP.name, util.generate_id() + ext)
util.json_dump_uncompressed(
self._val, codecs.open(tmp_path, "w", encoding="utf-8")
)
self._set_file(tmp_path, is_tmp=True, extension=ext)
@classmethod
def get_media_subdir(cls: Type["JSONMetadata"]) -> str:
return os.path.join("media", "metadata", cls.type_name())
def to_json(self, run_or_artifact: Union["LocalRun", "LocalArtifact"]) -> dict:
json_dict = super(JSONMetadata, self).to_json(run_or_artifact)
json_dict["_type"] = self.type_name()
return json_dict
# These methods should be overridden in the child class
@classmethod
def type_name(cls) -> str:
return "metadata"
def validate(self, val: dict) -> bool:
return True
class ImageMask(Media):
"""
Wandb class for image masks, useful for segmentation tasks
"""
_log_type = "mask"
def __init__(self, val: dict, key: str) -> None:
"""
Args:
val (dict): dictionary following 1 of two forms:
{
"mask_data": 2d array of integers corresponding to classes,
"class_labels": optional mapping from class ids to strings {id: str}
}
{
"path": path to an image file containing integers corresponding to classes,
"class_labels": optional mapping from class ids to strings {id: str}
}
key (str): id for set of masks
"""
super(ImageMask, self).__init__()
if "path" in val:
self._set_file(val["path"])
else:
np = util.get_module(
"numpy", required="Semantic Segmentation mask support requires numpy"
)
# Add default class mapping
if "class_labels" not in val:
classes = np.unique(val["mask_data"]).astype(np.int32).tolist()
class_labels = dict((c, "class_" + str(c)) for c in classes)
val["class_labels"] = class_labels
self.validate(val)
self._val = val
self._key = key
ext = "." + self.type_name() + ".png"
tmp_path = os.path.join(_MEDIA_TMP.name, util.generate_id() + ext)
pil_image = util.get_module(
"PIL.Image",
required='wandb.Image needs the PIL package. To get it, run "pip install pillow".',
)
image = pil_image.fromarray(val["mask_data"].astype(np.int8), mode="L")
image.save(tmp_path, transparency=None)
self._set_file(tmp_path, is_tmp=True, extension=ext)
def bind_to_run(
self,
run: "LocalRun",
key: Union[int, str],
step: Union[int, str],
id_: Optional[Union[int, str]] = None,
) -> None:
# bind_to_run key argument is the Image parent key
# the self._key value is the mask's sub key
super(ImageMask, self).bind_to_run(run, key, step, id_=id_)
class_labels = self._val["class_labels"]
run._add_singleton(
"mask/class_labels",
str(key) + "_wandb_delimeter_" + self._key,
class_labels,
)
@classmethod
def get_media_subdir(cls: Type["ImageMask"]) -> str:
return os.path.join("media", "images", cls.type_name())
@classmethod
def from_json(
cls: Type["ImageMask"], json_obj: dict, source_artifact: "PublicArtifact"
) -> "ImageMask":
return cls(
{"path": source_artifact.get_path(json_obj["path"]).download()}, key="",
)
def to_json(self, run_or_artifact: Union["LocalRun", "LocalArtifact"]) -> dict:
json_dict = super(ImageMask, self).to_json(run_or_artifact)
run_class, artifact_class = _safe_sdk_import()
if isinstance(run_or_artifact, run_class):
json_dict["_type"] = self.type_name()
return json_dict
elif isinstance(run_or_artifact, artifact_class):
# Nothing special to add (used to add "digest", but no longer used.)
return json_dict
else:
raise ValueError("to_json accepts wandb_run.Run or wandb_artifact.Artifact")
@classmethod
def type_name(cls: Type["ImageMask"]) -> str:
return cls._log_type
def validate(self, val: dict) -> bool:
np = util.get_module(
"numpy", required="Semantic Segmentation mask support requires numpy"
)
# 2D Make this work with all tensor(like) types
if "mask_data" not in val:
raise TypeError(
'Missing key "mask_data": A mask requires mask data(A 2D array representing the predctions)'
)
else:
error_str = "mask_data must be a 2d array"
shape = val["mask_data"].shape
if len(shape) != 2:
raise TypeError(error_str)
if not (
(val["mask_data"] >= 0).all() and (val["mask_data"] <= 255).all()
) and issubclass(val["mask_data"].dtype.type, np.integer):
raise TypeError("Mask data must be integers between 0 and 255")
# Optional argument
if "class_labels" in val:
for k, v in list(val["class_labels"].items()):
if (not isinstance(k, numbers.Number)) or (
not isinstance(v, six.string_types)
):
raise TypeError(
"Class labels must be a dictionary of numbers to string"
)
return True
class BoundingBoxes2D(JSONMetadata):
"""
Wandb class for 2D bounding boxes
"""
_log_type = "bounding-boxes"
# TODO: when the change is made to have this produce a dict with a _type, define
# it here as _log_type, associate it in to_json
def __init__(self, val: dict, key: str) -> None:
"""
Args:
val (dict): dictionary following the form:
{
"class_labels": optional mapping from class ids to strings {id: str}
"box_data": list of boxes: [
{
"position": {
"minX": float,
"maxX": float,
"minY": float,
"maxY": float,
},
"class_id": 1,
"box_caption": optional str
"scores": optional dict of scores
},
...
],
}
key (str): id for set of bounding boxes
"""
super(BoundingBoxes2D, self).__init__(val)
self._val = val["box_data"]
self._key = key
# Add default class mapping
if "class_labels" not in val:
np = util.get_module(
"numpy", required="Semantic Segmentation mask support requires numpy"
)
classes = (
np.unique(list([box["class_id"] for box in val["box_data"]]))
.astype(np.int32)
.tolist()
)
class_labels = dict((c, "class_" + str(c)) for c in classes)
self._class_labels = class_labels
else:
self._class_labels = val["class_labels"]
def bind_to_run(
self,
run: "LocalRun",
key: Union[int, str],
step: Union[int, str],
id_: Optional[Union[int, str]] = None,
) -> None:
# bind_to_run key argument is the Image parent key
# the self._key value is the mask's sub key
super(BoundingBoxes2D, self).bind_to_run(run, key, step, id_=id_)
run._add_singleton(
"bounding_box/class_labels",
str(key) + "_wandb_delimeter_" + self._key,
self._class_labels,
)
@classmethod
def type_name(cls) -> str:
return "boxes2D"
def validate(self, val: dict) -> bool:
# Optional argument
if "class_labels" in val:
for k, v in list(val["class_labels"].items()):
if (not isinstance(k, numbers.Number)) or (
not isinstance(v, six.string_types)
):
raise TypeError(
"Class labels must be a dictionary of numbers to string"
)
boxes = val["box_data"]
if not isinstance(boxes, list):
raise TypeError("Boxes must be a list")
for box in boxes:
# Required arguments
error_str = "Each box must contain a position with: middle, width, and height or \
\nminX, maxX, minY, maxY."
if "position" not in box:
raise TypeError(error_str)
else:
valid = False
if (
"middle" in box["position"]
and len(box["position"]["middle"]) == 2
and has_num(box["position"], "width")
and has_num(box["position"], "height")
):
valid = True
elif (
has_num(box["position"], "minX")
and has_num(box["position"], "maxX")
and has_num(box["position"], "minY")
and has_num(box["position"], "maxY")
):
valid = True
if not valid:
raise TypeError(error_str)
# Optional arguments
if ("scores" in box) and not isinstance(box["scores"], dict):
raise TypeError("Box scores must be a dictionary")
elif "scores" in box:
for k, v in list(box["scores"].items()):
if not isinstance(k, six.string_types):
raise TypeError("A score key must be a string")
if not isinstance(v, numbers.Number):
raise TypeError("A score value must be a number")
if ("class_id" in box) and not isinstance(
box["class_id"], six.integer_types
):
raise TypeError("A box's class_id must be an integer")
# Optional
if ("box_caption" in box) and not isinstance(
box["box_caption"], six.string_types
):
raise TypeError("A box's caption must be a string")
return True
def to_json(self, run_or_artifact: Union["LocalRun", "LocalArtifact"]) -> dict:
run_class, artifact_class = _safe_sdk_import()
if isinstance(run_or_artifact, run_class):
return super(BoundingBoxes2D, self).to_json(run_or_artifact)
elif isinstance(run_or_artifact, artifact_class):
# TODO (tim): I would like to log out a proper dictionary representing this object, but don't
# want to mess with the visualizations that are currently available in the UI. This really should output
# an object with a _type key. Will need to push this change to the UI first to ensure backwards compat
return self._val
else:
raise ValueError("to_json accepts wandb_run.Run or wandb_artifact.Artifact")
@classmethod
def from_json(
cls: Type["BoundingBoxes2D"], json_obj: dict, source_artifact: "PublicArtifact"
) -> "BoundingBoxes2D":
return cls({"box_data": json_obj}, "")
class Classes(Media):
_log_type = "classes"
_class_set: Sequence[dict]
def __init__(self, class_set: Sequence[dict]) -> None:
"""Classes is holds class metadata intended to be used in concert with other objects when visualizing artifacts
Args:
class_set (list): list of dicts in the form of {"id":int|str, "name":str}
"""
super(Classes, self).__init__()
for class_obj in class_set:
assert "id" in class_obj and "name" in class_obj
self._class_set = class_set
@classmethod
def from_json(
cls: Type["Classes"],
json_obj: dict,
source_artifact: Optional["PublicArtifact"],
) -> "Classes":
return cls(json_obj.get("class_set")) # type: ignore
def to_json(
self, run_or_artifact: Optional[Union["LocalRun", "LocalArtifact"]]
) -> dict:
json_obj = {}
# This is a bit of a hack to allow _ClassesIdType to
# be able to operate fully without an artifact in play.
# In all other cases, artifact should be a true artifact.
if run_or_artifact is not None:
json_obj = super(Classes, self).to_json(run_or_artifact)
json_obj["_type"] = Classes._log_type
json_obj["class_set"] = self._class_set
return json_obj
def get_type(self) -> "_ClassesIdType":
return _ClassesIdType(self)
def __ne__(self, other: object) -> bool:
return not self.__eq__(other)
def __eq__(self, other: object) -> bool:
if isinstance(other, Classes):
return self._class_set == other._class_set
else:
return False
class Image(BatchableMedia):
"""
Wandb class for images.
Arguments:
data_or_path: (numpy array, string, io) Accepts numpy array of
image data, or a PIL image. The class attempts to infer
the data format and converts it.
mode: (string) The PIL mode for an image. Most common are "L", "RGB",
"RGBA". Full explanation at https://pillow.readthedocs.io/en/4.2.x/handbook/concepts.html#concept-modes.
caption: (string) Label for display of image.
"""
MAX_ITEMS = 108
# PIL limit
MAX_DIMENSION = 65500
_log_type = "image-file"
format: Optional[str]
_grouping: Optional[str]
_caption: Optional[str]
_width: Optional[int]
_height: Optional[int]
_image: Optional["PIL.Image"]
_classes: Optional["Classes"]
_boxes: Optional[Dict[str, "BoundingBoxes2D"]]
_masks: Optional[Dict[str, "ImageMask"]]
def __init__(
self,
data_or_path: "ImageDataOrPathType",
mode: Optional[str] = None,
caption: Optional[str] = None,
grouping: Optional[str] = None,
classes: Optional[Union["Classes", Sequence[dict]]] = None,
boxes: Optional[Union[Dict[str, "BoundingBoxes2D"], Dict[str, dict]]] = None,
masks: Optional[Union[Dict[str, "ImageMask"], Dict[str, dict]]] = None,
) -> None:
super(Image, self).__init__()
# TODO: We should remove grouping, it's a terrible name and I don't
# think anyone uses it.
self._grouping = None
self._caption = None
self._width = None
self._height = None
self._image = None
self._classes = None
self._boxes = None
self._masks = None
# Allows the user to pass an Image object as the first parameter and have a perfect copy,
# only overriding additional metdata passed in. If this pattern is compelling, we can generalize.
if isinstance(data_or_path, Image):
self._initialize_from_wbimage(data_or_path)
elif isinstance(data_or_path, six.string_types):
self._initialize_from_path(data_or_path)
else:
self._initialize_from_data(data_or_path, mode)
self._set_initialization_meta(grouping, caption, classes, boxes, masks)
def _set_initialization_meta(
self,
grouping: Optional[str] = None,
caption: Optional[str] = None,
classes: Optional[Union["Classes", Sequence[dict]]] = None,
boxes: Optional[Union[Dict[str, "BoundingBoxes2D"], Dict[str, dict]]] = None,
masks: Optional[Union[Dict[str, "ImageMask"], Dict[str, dict]]] = None,
) -> None:
if grouping is not None:
self._grouping = grouping
if caption is not None:
self._caption = caption
if classes is not None:
if not isinstance(classes, Classes):
self._classes = Classes(classes)
else:
self._classes = classes
if boxes:
if not isinstance(boxes, dict):
raise ValueError('Images "boxes" argument must be a dictionary')
boxes_final: Dict[str, BoundingBoxes2D] = {}
for key in boxes:
box_item = boxes[key]
if isinstance(box_item, BoundingBoxes2D):
boxes_final[key] = box_item
elif isinstance(box_item, dict):
boxes_final[key] = BoundingBoxes2D(box_item, key)
self._boxes = boxes_final
if masks:
if not isinstance(masks, dict):
raise ValueError('Images "masks" argument must be a dictionary')
masks_final: Dict[str, ImageMask] = {}
for key in masks:
mask_item = masks[key]
if isinstance(mask_item, ImageMask):
masks_final[key] = mask_item
elif isinstance(mask_item, dict):
masks_final[key] = ImageMask(mask_item, key)
self._masks = masks_final
self._width, self._height = self._image.size # type: ignore
def _initialize_from_wbimage(self, wbimage: "Image") -> None:
self._grouping = wbimage._grouping
self._caption = wbimage._caption
self._width = wbimage._width
self._height = wbimage._height
self._image = wbimage._image
self._classes = wbimage._classes
self._path = wbimage._path
self._is_tmp = wbimage._is_tmp
self._extension = wbimage._extension
self._sha256 = wbimage._sha256
self._size = wbimage._size
self.format = wbimage.format
self._artifact_source = wbimage._artifact_source
self._artifact_target = wbimage._artifact_target
# We do not want to implicitly copy boxes or masks, just the image-related data.
# self._boxes = wbimage._boxes
# self._masks = wbimage._masks
def _initialize_from_path(self, path: str) -> None:
pil_image = util.get_module(
"PIL.Image",
required='wandb.Image needs the PIL package. To get it, run "pip install pillow".',
)
self._set_file(path, is_tmp=False)
self._image = pil_image.open(path)
self._image.load()
ext = os.path.splitext(path)[1][1:]
self.format = ext
def _initialize_from_data(self, data: "ImageDataType", mode: str = None,) -> None:
pil_image = util.get_module(
"PIL.Image",
required='wandb.Image needs the PIL package. To get it, run "pip install pillow".',
)
if util.is_matplotlib_typename(util.get_full_typename(data)):
buf = six.BytesIO()
util.ensure_matplotlib_figure(data).savefig(buf)
self._image = pil_image.open(buf)
elif isinstance(data, pil_image.Image):
self._image = data
elif util.is_pytorch_tensor_typename(util.get_full_typename(data)):
vis_util = util.get_module(
"torchvision.utils", "torchvision is required to render images"
)
if hasattr(data, "requires_grad") and data.requires_grad:
data = data.detach()
data = vis_util.make_grid(data, normalize=True)
self._image = pil_image.fromarray(
data.mul(255).clamp(0, 255).byte().permute(1, 2, 0).cpu().numpy()
)
else:
if hasattr(data, "numpy"): # TF data eager tensors
data = data.numpy()
if data.ndim > 2:
data = data.squeeze() # get rid of trivial dimensions as a convenience
self._image = pil_image.fromarray(
self.to_uint8(data), mode=mode or self.guess_mode(data)
)
tmp_path = os.path.join(_MEDIA_TMP.name, util.generate_id() + ".png")
self.format = "png"
self._image.save(tmp_path, transparency=None)
self._set_file(tmp_path, is_tmp=True)
@classmethod
def from_json(
cls: Type["Image"], json_obj: dict, source_artifact: "PublicArtifact"
) -> "Image":
classes = None
if json_obj.get("classes") is not None:
classes = source_artifact.get(json_obj["classes"]["path"])
masks = json_obj.get("masks")
_masks: Optional[Dict[str, ImageMask]] = None
if masks:
_masks = {}
for key in masks:
_masks[key] = ImageMask.from_json(masks[key], source_artifact)
_masks[key]._set_artifact_source(source_artifact)
_masks[key]._key = key
boxes = json_obj.get("boxes")
_boxes: Optional[Dict[str, BoundingBoxes2D]] = None
if boxes:
_boxes = {}
for key in boxes:
_boxes[key] = BoundingBoxes2D.from_json(boxes[key], source_artifact)
_boxes[key]._key = key
return cls(
source_artifact.get_path(json_obj["path"]).download(),
caption=json_obj.get("caption"),
grouping=json_obj.get("grouping"),
classes=classes,
boxes=_boxes,
masks=_masks,
)
@classmethod
def get_media_subdir(cls: Type["Image"]) -> str:
return os.path.join("media", "images")
def bind_to_run(
self,
run: "LocalRun",
key: Union[int, str],
step: Union[int, str],
id_: Optional[Union[int, str]] = None,
) -> None:
super(Image, self).bind_to_run(run, key, step, id_)
if self._boxes is not None:
for i, k in enumerate(self._boxes):
id_ = "{}{}".format(id_, i) if id_ is not None else None
self._boxes[k].bind_to_run(run, key, step, id_)
if self._masks is not None:
for i, k in enumerate(self._masks):
id_ = "{}{}".format(id_, i) if id_ is not None else None
self._masks[k].bind_to_run(run, key, step, id_)
def to_json(self, run_or_artifact: Union["LocalRun", "LocalArtifact"]) -> dict:
json_dict = super(Image, self).to_json(run_or_artifact)
json_dict["_type"] = Image._log_type
json_dict["format"] = self.format
if self._width is not None:
json_dict["width"] = self._width
if self._height is not None:
json_dict["height"] = self._height
if self._grouping:
json_dict["grouping"] = self._grouping
if self._caption:
json_dict["caption"] = self._caption
run_class, artifact_class = _safe_sdk_import()
if isinstance(run_or_artifact, artifact_class):
artifact = run_or_artifact
if (
self._masks is not None or self._boxes is not None
) and self._classes is None:
raise ValueError(
"classes must be passed to wandb.Image which have masks or bounding boxes when adding to artifacts"
)
if self._classes is not None:
# Here, rather than give each class definition it's own name (and entry), we
# purposely are giving a non-unique class name of /media/cls.classes.json.
# This may create user confusion if if multiple different class definitions
# are expected in a single artifact. However, we want to catch this user pattern
# if it exists and dive deeper. The alternative code is provided below.
#
class_name = os.path.join("media", "cls")
#
# class_name = os.path.join(
# "media", "classes", os.path.basename(self._path) + "_cls"
# )
#
classes_entry = artifact.add(self._classes, class_name)
json_dict["classes"] = {
"type": "classes-file",
"path": classes_entry.path,
"digest": classes_entry.digest,
}
elif not isinstance(run_or_artifact, run_class):
raise ValueError("to_json accepts wandb_run.Run or wandb_artifact.Artifact")
if self._boxes:
json_dict["boxes"] = {
k: box.to_json(run_or_artifact) for (k, box) in self._boxes.items()
}
if self._masks:
json_dict["masks"] = {
k: mask.to_json(run_or_artifact) for (k, mask) in self._masks.items()
}
return json_dict
def guess_mode(self, data: "np.ndarray") -> str:
"""
Guess what type of image the np.array is representing
"""
# TODO: do we want to support dimensions being at the beginning of the array?
if data.ndim == 2:
return "L"
elif data.shape[-1] == 3:
return "RGB"
elif data.shape[-1] == 4:
return "RGBA"
else:
raise ValueError(
"Un-supported shape for image conversion %s" % list(data.shape)
)
@classmethod
def to_uint8(cls, data: "np.ndarray") -> "np.ndarray":
"""
Converts floating point image on the range [0,1] and integer images
on the range [0,255] to uint8, clipping if necessary.
"""
np = util.get_module(
"numpy",
required="wandb.Image requires numpy if not supplying PIL Images: pip install numpy",
)
# I think it's better to check the image range vs the data type, since many
# image libraries will return floats between 0 and 255
# some images have range -1...1 or 0-1
dmin = np.min(data)
if dmin < 0:
data = (data - np.min(data)) / np.ptp(data)
if np.max(data) <= 1.0:
data = (data * 255).astype(np.int32)
# assert issubclass(data.dtype.type, np.integer), 'Illegal image format.'
return data.clip(0, 255).astype(np.uint8)
@classmethod
def seq_to_json(
cls: Type["Image"],
seq: Sequence["BatchableMedia"],
run: "LocalRun",
key: str,
step: Union[int, str],
) -> dict:
"""
Combines a list of images into a meta dictionary object describing the child images.
"""
if wandb.TYPE_CHECKING and TYPE_CHECKING:
seq = cast(Sequence["Image"], seq)
jsons = [obj.to_json(run) for obj in seq]
media_dir = cls.get_media_subdir()
for obj in jsons:
expected = util.to_forward_slash_path(media_dir)
if not obj["path"].startswith(expected):
raise ValueError(
"Files in an array of Image's must be in the {} directory, not {}".format(
cls.get_media_subdir(), obj["path"]
)
)
num_images_to_log = len(seq)
width, height = seq[0]._image.size # type: ignore
format = jsons[0]["format"]
def size_equals_image(image: "Image") -> bool:
img_width, img_height = image._image.size # type: ignore
return img_width == width and img_height == height # type: ignore
sizes_match = all(size_equals_image(img) for img in seq)
if not sizes_match:
logging.warning(
"Images sizes do not match. This will causes images to be display incorrectly in the UI."
)
meta = {
"_type": "images/separated",
"width": width,
"height": height,
"format": format,
"count": num_images_to_log,
}
captions = Image.all_captions(seq)
if captions:
meta["captions"] = captions
all_masks = Image.all_masks(seq, run, key, step)
if all_masks:
meta["all_masks"] = all_masks
all_boxes = Image.all_boxes(seq, run, key, step)
if all_boxes:
meta["all_boxes"] = all_boxes
return meta
@classmethod
def all_masks(
cls: Type["Image"],
images: Sequence["Image"],
run: "LocalRun",
run_key: str,
step: Union[int, str],
) -> Union[List[Optional[dict]], bool]:
all_mask_groups: List[Optional[dict]] = []
for image in images:
if image._masks:
mask_group = {}
for k in image._masks:
mask = image._masks[k]
mask_group[k] = mask.to_json(run)
all_mask_groups.append(mask_group)
else:
all_mask_groups.append(None)
if all_mask_groups and not all(x is None for x in all_mask_groups):
return all_mask_groups
else:
return False
@classmethod
def all_boxes(
cls: Type["Image"],
images: Sequence["Image"],
run: "LocalRun",
run_key: str,
step: Union[int, str],
) -> Union[List[Optional[dict]], bool]:
all_box_groups: List[Optional[dict]] = []
for image in images:
if image._boxes:
box_group = {}
for k in image._boxes:
box = image._boxes[k]
box_group[k] = box.to_json(run)
all_box_groups.append(box_group)
else:
all_box_groups.append(None)
if all_box_groups and not all(x is None for x in all_box_groups):
return all_box_groups
else:
return False
@classmethod
def all_captions(
cls: Type["Image"], images: Sequence["Media"]
) -> Union[bool, Sequence[Optional[str]]]:
return cls.captions(images)
def __ne__(self, other: object) -> bool:
return not self.__eq__(other)
def __eq__(self, other: object) -> bool:
if not isinstance(other, Image):
return False
else:
return (
self._grouping == other._grouping
and self._caption == other._caption
and self._width == other._width
and self._height == other._height
and self._image == other._image
and self._classes == other._classes
)
def to_data_array(self) -> List[Any]:
res = []
if self._image is not None:
data = list(self._image.getdata())
for i in range(self._image.height):
res.append(data[i * self._image.width : (i + 1) * self._image.width])
return res
class Plotly(Media):
"""
Wandb class for plotly plots.
Arguments:
val: matplotlib or plotly figure
"""
_log_type = "plotly-file"
@classmethod
def make_plot_media(
cls: Type["Plotly"], val: Union["plotly.Figure", "matplotlib.artist.Artist"]
) -> Union[Image, "Plotly"]:
if util.is_matplotlib_typename(util.get_full_typename(val)):
if util.matplotlib_contains_images(val):
return Image(val)
val = util.matplotlib_to_plotly(val)
return cls(val)
def __init__(self, val: Union["plotly.Figure", "matplotlib.artist.Artist"]):
super(Plotly, self).__init__()
# First, check to see if the incoming `val` object is a plotfly figure
if not util.is_plotly_figure_typename(util.get_full_typename(val)):
# If it is not, but it is a matplotlib figure, then attempt to convert it to plotly
if util.is_matplotlib_typename(util.get_full_typename(val)):
if util.matplotlib_contains_images(val):
raise ValueError(
"Plotly does not currently support converting matplotlib figures containing images. \
You can convert the plot to a static image with `wandb.Image(plt)` "
)
val = util.matplotlib_to_plotly(val)
else:
raise ValueError(
"Logged plots must be plotly figures, or matplotlib plots convertible to plotly via mpl_to_plotly"
)
tmp_path = os.path.join(_MEDIA_TMP.name, util.generate_id() + ".plotly.json")
val = _numpy_arrays_to_lists(val.to_plotly_json())
util.json_dump_safer(val, codecs.open(tmp_path, "w", encoding="utf-8"))
self._set_file(tmp_path, is_tmp=True, extension=".plotly.json")
@classmethod
def get_media_subdir(cls: Type["Plotly"]) -> str:
return os.path.join("media", "plotly")
def to_json(self, run_or_artifact: Union["LocalRun", "LocalArtifact"]) -> dict:
json_dict = super(Plotly, self).to_json(run_or_artifact)
json_dict["_type"] = self._log_type
return json_dict
def history_dict_to_json(
run: "Optional[LocalRun]", payload: dict, step: Optional[int] = None
) -> dict:
# Converts a History row dict's elements so they're friendly for JSON serialization.
if step is None:
# We should be at the top level of the History row; assume this key is set.
step = payload["_step"]
# We use list here because we were still seeing cases of RuntimeError dict changed size
for key in list(payload):
val = payload[key]
if isinstance(val, dict):
payload[key] = history_dict_to_json(run, val, step=step)
else:
payload[key] = val_to_json(run, key, val, namespace=step)
return payload
# TODO: refine this
def val_to_json(
run: "Optional[LocalRun]",
key: str,
val: "ValToJsonType",
namespace: Optional[Union[str, int]] = None,
) -> Union[Sequence, dict]:
# Converts a wandb datatype to its JSON representation.
if namespace is None:
raise ValueError(
"val_to_json must be called with a namespace(a step number, or 'summary') argument"
)
converted = val
typename = util.get_full_typename(val)
if util.is_pandas_data_frame(val):
raise ValueError(
"We do not support DataFrames in the Summary or History. Try run.log({{'{}': wandb.Table(dataframe=df)}})".format(
key
)
)
elif util.is_matplotlib_typename(typename) or util.is_plotly_typename(typename):
val = Plotly.make_plot_media(val)
elif isinstance(val, SixSequence) and all(isinstance(v, WBValue) for v in val):
assert run
# This check will break down if Image/Audio/... have child classes.
if (
len(val)
and isinstance(val[0], BatchableMedia)
and all(isinstance(v, type(val[0])) for v in val)
):
if wandb.TYPE_CHECKING and TYPE_CHECKING:
val = cast(Sequence["BatchableMedia"], val)
items = _prune_max_seq(val)
for i, item in enumerate(items):
item.bind_to_run(run, key, namespace, id_=i)
return items[0].seq_to_json(items, run, key, namespace)
else:
# TODO(adrian): Good idea to pass on the same key here? Maybe include
# the array index?
# There is a bug here: if this array contains two arrays of the same type of
# anonymous media objects, their eventual names will collide.
# This used to happen. The frontend doesn't handle heterogenous arrays
# raise ValueError(
# "Mixed media types in the same list aren't supported")
return [val_to_json(run, key, v, namespace=namespace) for v in val]
if isinstance(val, WBValue):
assert run
if isinstance(val, Media) and not val.is_bound():
if hasattr(val, "_log_type") and val._log_type == "table":
# Special conditional to log tables as artifact entries as well.
# I suspect we will generalize this as we transition to storing all
# files in an artifact
_, artifact_class = _safe_sdk_import()
# we sanitize the key to meet the constraints defined in wandb_artifacts.py
# in this case, leaving only alpha numerics or underscores.
sanitized_key = re.sub(r"[^a-zA-Z0-9_]+", "", key)
art = artifact_class(
"run-{}-{}".format(run.id, sanitized_key), "run_table"
)
art.add(val, key)
run.log_artifact(art)
val.bind_to_run(run, key, namespace)
return val.to_json(run)
return converted # type: ignore
def _is_numpy_array(data: object) -> bool:
np = util.get_module(
"numpy", required="Logging raw point cloud data requires numpy"
)
return isinstance(data, np.ndarray)
def _wb_filename(
key: Union[str, int], step: Union[str, int], id: Union[str, int], extension: str
) -> str:
return "{}_{}_{}{}".format(str(key), str(step), str(id), extension)
def _numpy_arrays_to_lists(
payload: Union[dict, Sequence, "np.ndarray"]
) -> Union[Sequence, dict, str, int, float, bool]:
# Casts all numpy arrays to lists so we don't convert them to histograms, primarily for Plotly
if isinstance(payload, dict):
res = {}
for key, val in six.iteritems(payload):
res[key] = _numpy_arrays_to_lists(val)
return res
elif isinstance(payload, SixSequence) and not isinstance(payload, six.string_types):
return [_numpy_arrays_to_lists(v) for v in payload]
elif util.is_numpy_array(payload):
if wandb.TYPE_CHECKING and TYPE_CHECKING:
payload = cast("np.ndarray", payload)
return [_numpy_arrays_to_lists(v) for v in payload.tolist()]
# Protects against logging non serializable objects
elif isinstance(payload, Media):
return str(payload.__class__.__name__)
return payload
def _prune_max_seq(seq: Sequence["BatchableMedia"]) -> Sequence["BatchableMedia"]:
# If media type has a max respect it
items = seq
if hasattr(seq[0], "MAX_ITEMS") and seq[0].MAX_ITEMS < len(seq): # type: ignore
logging.warning(
"Only %i %s will be uploaded."
% (seq[0].MAX_ITEMS, seq[0].__class__.__name__) # type: ignore
)
items = seq[: seq[0].MAX_ITEMS] # type: ignore
return items
def _data_frame_to_json(
df: "pd.DataFraome", run: "LocalRun", key: str, step: Union[int, str]
) -> dict:
"""!NODOC Encode a Pandas DataFrame into the JSON/backend format.
Writes the data to a file and returns a dictionary that we use to represent
it in `Summary`'s.
Arguments:
df (pandas.DataFrame): The DataFrame. Must not have columns named
"wandb_run_id" or "wandb_data_frame_id". They will be added to the
DataFrame here.
run (wandb_run.Run): The Run the DataFrame is associated with. We need
this because the information we store on the DataFrame is derived
from the Run it's in.
key (str): Name of the DataFrame, ie. the summary key path in which it's
stored. This is for convenience, so people exploring the
directory tree can have some idea of what is in the Parquet files.
step: History step or "summary".
Returns:
A dict representing the DataFrame that we can store in summaries or
histories. This is the format:
{
'_type': 'data-frame',
# Magic field that indicates that this object is a data frame as
# opposed to a normal dictionary or anything else.
'id': 'asdf',
# ID for the data frame that is unique to this Run.
'format': 'parquet',
# The file format in which the data frame is stored. Currently can
# only be Parquet.
'project': 'wfeas',
# (Current) name of the project that this Run is in. It'd be
# better to store the project's ID because we know it'll never
# change but we don't have that here. We store this just in
# case because we use the project name in identifiers on the
# back end.
'path': 'media/data_frames/sdlk.parquet',
# Path to the Parquet file in the Run directory.
}
"""
pandas = util.get_module("pandas")
fastparquet = util.get_module("fastparquet")
missing_reqs = []
if not pandas:
missing_reqs.append("pandas")
if not fastparquet:
missing_reqs.append("fastparquet")
if len(missing_reqs) > 0:
raise wandb.Error(
"Failed to save data frame. Please run 'pip install %s'"
% " ".join(missing_reqs)
)
data_frame_id = util.generate_id()
df = df.copy() # we don't want to modify the user's DataFrame instance.
for _, series in df.items():
for i, val in enumerate(series):
if isinstance(val, WBValue):
series.iat[i] = six.text_type(
json.dumps(val_to_json(run, key, val, namespace=step))
)
# We have to call this wandb_run_id because that name is treated specially by
# our filtering code
df["wandb_run_id"] = pandas.Series(
[six.text_type(run.id)] * len(df.index), index=df.index
)
df["wandb_data_frame_id"] = pandas.Series(
[six.text_type(data_frame_id)] * len(df.index), index=df.index
)
frames_dir = os.path.join(run.dir, _DATA_FRAMES_SUBDIR)
util.mkdir_exists_ok(frames_dir)
path = os.path.join(frames_dir, "{}-{}.parquet".format(key, data_frame_id))
fastparquet.write(path, df)
return {
"id": data_frame_id,
"_type": "data-frame",
"format": "parquet",
"project": run.project_name(), # we don't have the project ID here
"entity": run.entity,
"run": run.id,
"path": path,
}
class _ClassesIdType(_dtypes.Type):
name = "classesId"
legacy_names = ["wandb.Classes_id"]
types = [Classes]
def __init__(
self,
classes_obj: Optional[Classes] = None,
valid_ids: Optional["_dtypes.UnionType"] = None,
):
if valid_ids is None:
valid_ids = _dtypes.UnionType()
elif isinstance(valid_ids, list):
valid_ids = _dtypes.UnionType(
[_dtypes.ConstType(item) for item in valid_ids]
)
elif isinstance(valid_ids, _dtypes.UnionType):
valid_ids = valid_ids
else:
raise TypeError("valid_ids must be None, list, or UnionType")
if classes_obj is None:
classes_obj = Classes(
[
{"id": _id.params["val"], "name": str(_id.params["val"])}
for _id in valid_ids.params["allowed_types"]
]
)
elif not isinstance(classes_obj, Classes):
raise TypeError("valid_ids must be None, or instance of Classes")
else:
valid_ids = _dtypes.UnionType(
[
_dtypes.ConstType(class_obj["id"])
for class_obj in classes_obj._class_set
]
)
self.wb_classes_obj_ref = classes_obj
self.params.update({"valid_ids": valid_ids})
def assign(self, py_obj: Optional[Any] = None) -> "_dtypes.Type":
return self.assign_type(_dtypes.ConstType(py_obj))
def assign_type(self, wb_type: "_dtypes.Type") -> "_dtypes.Type":
valid_ids = self.params["valid_ids"].assign_type(wb_type)
if not isinstance(valid_ids, _dtypes.InvalidType):
return self
return _dtypes.InvalidType()
@classmethod
def from_obj(cls, py_obj: Optional[Any] = None) -> "_dtypes.Type":
return cls(py_obj)
def to_json(self, artifact: Optional["LocalArtifact"] = None) -> Dict[str, Any]:
cl_dict = super(_ClassesIdType, self).to_json(artifact)
# TODO (tss): Refactor this block with the similar one in wandb.Image.
# This is a bit of a smell that the classes object does not follow
# the same file-pattern as other media types.
if artifact is not None:
class_name = os.path.join("media", "cls")
classes_entry = artifact.add(self.wb_classes_obj_ref, class_name)
cl_dict["params"]["classes_obj"] = {
"type": "classes-file",
"path": classes_entry.path,
"digest": classes_entry.digest, # is this needed really?
}
else:
cl_dict["params"]["classes_obj"] = self.wb_classes_obj_ref.to_json(artifact)
return cl_dict
@classmethod
def from_json(
cls, json_dict: Dict[str, Any], artifact: Optional["PublicArtifact"] = None,
) -> "_dtypes.Type":
classes_obj = None
if (
json_dict.get("params", {}).get("classes_obj", {}).get("type")
== "classes-file"
):
if artifact is not None:
classes_obj = artifact.get(
json_dict.get("params", {}).get("classes_obj", {}).get("path")
)
else:
raise RuntimeError("Expected artifact to be non-null.")
else:
classes_obj = Classes.from_json(
json_dict["params"]["classes_obj"], artifact
)
return cls(classes_obj)
class _VideoFileType(_dtypes.Type):
name = "video-file"
types = [Video]
class _HtmlFileType(_dtypes.Type):
name = "html-file"
types = [Html]
class _Object3DFileType(_dtypes.Type):
name = "object3D-file"
types = [Object3D]
_dtypes.TypeRegistry.add(_ClassesIdType)
_dtypes.TypeRegistry.add(_VideoFileType)
_dtypes.TypeRegistry.add(_HtmlFileType)
_dtypes.TypeRegistry.add(_Object3DFileType)
__all__ = [
"Histogram",
"Object3D",
"Molecule",
"Html",
"Video",
"ImageMask",
"BoundingBoxes2D",
"Classes",
"Image",
"Plotly",
"history_dict_to_json",
"val_to_json",
]
| 36.92869 | 131 | 0.572627 |
eeb1e7a60d6ea1ffc91e6fc9a9c245ce02db42e3 | 543 | py | Python | week02/week02.py | duongoku/int3404 | 6dd3ec4566de848d529629eada6f4f167fd3de93 | [
"MIT"
] | 9 | 2021-09-09T08:17:49.000Z | 2022-02-21T09:25:12.000Z | week02/week02.py | duongoku/int3404 | 6dd3ec4566de848d529629eada6f4f167fd3de93 | [
"MIT"
] | 1 | 2021-09-21T04:48:53.000Z | 2021-09-21T04:48:53.000Z | week02/week02.py | duongoku/int3404 | 6dd3ec4566de848d529629eada6f4f167fd3de93 | [
"MIT"
] | 11 | 2021-09-14T02:57:51.000Z | 2021-10-14T14:40:04.000Z | """
Name:
Class:
MSSV:
You should understand the code you write.
"""
import numpy as np
import cv2
def q_0(input_file, output_file, delay=1):
"""
:param input_file:
:param output_file:
:param delay:
:return:
"""
img = cv2.imread(input_file, cv2.IMREAD_COLOR)
cv2.imshow('Test img', img)
cv2.waitKey(delay)
cv2.imwrite(output_file, img)
def q_1():
print("Task 1")
def q_2():
print("Task 2")
if __name__ == "__main__":
q_0('apple.png', 'test_apple.png', 1000)
q_1()
q_2()
| 13.243902 | 50 | 0.607735 |
3fb5aaabb642b2c92b5f4ef0c5344a71bf3cdfd1 | 3,566 | py | Python | dingdang/client/WechatBot.py | Suhine/SmartAudioHome | d213c13fe00d75b51016c20c0167e8fde9f3b564 | [
"MIT"
] | null | null | null | dingdang/client/WechatBot.py | Suhine/SmartAudioHome | d213c13fe00d75b51016c20c0167e8fde9f3b564 | [
"MIT"
] | null | null | null | dingdang/client/WechatBot.py | Suhine/SmartAudioHome | d213c13fe00d75b51016c20c0167e8fde9f3b564 | [
"MIT"
] | null | null | null | #!/usr/bin/env python2
# -*- coding: utf-8-*-
import time
import os
from client.wxbot import WXBot
from client import dingdangpath
from client.audio_utils import mp3_to_wav
from client import player
from client import config
class WechatBot(WXBot):
def __init__(self, brain):
WXBot.__init__(self)
self.brain = brain
self.music_mode = None
self.last = time.time()
def handle_music_mode(self, msg_data):
# avoid repeating command
now = time.time()
if (now - self.last) > 0.5:
# stop passive listening
# self.brain.mic.stopPassiveListen()
self.last = now
if not self.music_mode.delegating:
self.music_mode.delegating = True
self.music_mode.delegateInput(msg_data, True)
if self.music_mode is not None:
self.music_mode.delegating = False
def handle_msg_all(self, msg):
# ignore the msg when handling plugins
profile = config.get()
if (msg['msg_type_id'] == 1 and
(msg['to_user_id'] == self.my_account['UserName'] or
msg['to_user_id'] == u'filehelper')):
from_user = profile['first_name'] + '说：'
msg_data = from_user + msg['content']['data']
if msg['content']['type'] == 0:
if msg_data.startswith(profile['robot_name_cn']+": "):
return
if self.music_mode is not None:
return self.handle_music_mode(msg_data)
self.brain.query([msg_data], self, True)
elif msg['content']['type'] == 4:
mp3_file = os.path.join(dingdangpath.TEMP_PATH,
'voice_%s.mp3' % msg['msg_id'])
# echo or command?
if 'wechat_echo' in profile and not profile['wechat_echo']:
# 执行命令
mic = self.brain.mic
wav_file = mp3_to_wav(mp3_file)
with open(wav_file) as f:
command = mic.active_stt_engine.transcribe(f)
if command:
if self.music_mode is not None:
return self.handle_music_mode(msg_data)
self.brain.query(command, self, True)
else:
mic.say("什么？")
else:
# 播放语音
player.get_music_manager().play_block(mp3_file)
elif msg['msg_type_id'] == 4:
if 'wechat_echo_text_friends' in profile and \
(
msg['user']['name'] in profile['wechat_echo_text_friends']
or
'ALL' in profile['wechat_echo_text_friends']
) and msg['content']['type'] == 0:
from_user = msg['user']['name'] + '说：'
msg_data = from_user + msg['content']['data']
self.brain.query([msg_data], self, True)
elif 'wechat_echo_voice_friends' in profile and \
(
msg['user']['name'] in profile['wechat_echo_voice_friends']
or
'ALL' in profile['wechat_echo_voice_friends']
) and msg['content']['type'] == 4:
mp3_file = os.path.join(dingdangpath.TEMP_PATH,
'voice_%s.mp3' % msg['msg_id'])
player.get_music_manager().play_block(mp3_file)
| 41.465116 | 79 | 0.508413 |
08c126ead859151881bca90ec834ec06152df06c | 3,206 | py | Python | jcvi/apps/vecscreen.py | l-Imoon/jcvi | db70bb98c7969bb0cc7b9941a2cc2dc8c5d1b783 | [
"BSD-2-Clause"
] | null | null | null | jcvi/apps/vecscreen.py | l-Imoon/jcvi | db70bb98c7969bb0cc7b9941a2cc2dc8c5d1b783 | [
"BSD-2-Clause"
] | null | null | null | jcvi/apps/vecscreen.py | l-Imoon/jcvi | db70bb98c7969bb0cc7b9941a2cc2dc8c5d1b783 | [
"BSD-2-Clause"
] | null | null | null | #!/usr/bin/env python
# -*- coding: UTF-8 -*-
"""
Run through NCBI vecscreen on a local machine.
"""
from __future__ import print_function
import os.path as op
import sys
from jcvi.utils.range import range_merge
from jcvi.formats.fasta import tidy
from jcvi.formats.blast import BlastLine
from jcvi.formats.base import must_open
from jcvi.apps.align import run_vecscreen, run_megablast
from jcvi.apps.base import OptionParser, ActionDispatcher, download, sh
def main():
actions = (
('mask', 'mask the contaminants'),
)
p = ActionDispatcher(actions)
p.dispatch(globals())
def mask(args):
"""
%prog mask fastafile
Mask the contaminants. By default, this will compare against UniVec_Core and
Ecoli.fasta. Merge the contaminant results, and use `maskFastaFromBed`. Can
perform FASTA tidy if requested.
"""
p = OptionParser(mask.__doc__)
p.add_option("--db",
help="Contaminant db other than Ecoli K12 [default: %default]")
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
fastafile, = args
assert op.exists(fastafile)
outfastafile = fastafile.rsplit(".", 1)[0] + ".masked.fasta"
vecbedfile = blast([fastafile])
ecoliurl = \
"ftp://ftp.ncbi.nih.gov/genomes/Bacteria/Escherichia_coli_K_12_substr__DH10B_uid58979/NC_010473.fna"
ecolifile = opts.db or download(ecoliurl, filename="Ecoli.fasta")
assert op.exists(ecolifile)
ecolibedfile = blast([fastafile, "--db={0}".format(ecolifile)])
cmd = "cat {0} {1}".format(vecbedfile, ecolibedfile)
cmd += " | mergeBed -nms -d 100 -i stdin"
cmd += " | maskFastaFromBed -fi {0} -bed stdin -fo {1}".\
format(fastafile, outfastafile)
sh(cmd)
return tidy([outfastafile])
def blast(args):
"""
%prog blast fastafile
Run BLASTN against database (default is UniVec_Core). Output .bed format
on the vector/contaminant ranges.
"""
p = OptionParser(blast.__doc__)
p.add_option("--dist", default=100, type="int",
help="Merge adjacent HSPs separated by [default: %default]")
p.add_option("--db",
help="Use a different database rather than UniVec_Core")
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
fastafile, = args
fastaprefix = fastafile.split(".", 1)[0]
univec = opts.db or download("ftp://ftp.ncbi.nih.gov/pub/UniVec/UniVec_Core")
uniprefix = univec.split(".", 1)[0]
fastablast = fastaprefix + ".{0}.blast".format(uniprefix)
prog = run_megablast if opts.db else run_vecscreen
prog(infile=fastafile, outfile=fastablast, db=univec, pctid=95, hitlen=50)
fp = open(fastablast)
ranges = []
for row in fp:
b = BlastLine(row)
ranges.append((b.query, b.qstart, b.qstop))
merged_ranges = range_merge(ranges, dist=opts.dist)
bedfile = fastaprefix + ".{0}.bed".format(uniprefix)
fw = must_open(bedfile, "w")
for seqid, start, end in merged_ranges:
print("\t".join(str(x) for x in (seqid, start - 1, end, uniprefix)), file=fw)
return bedfile
if __name__ == '__main__':
main()
| 29.145455 | 104 | 0.656893 |
9f95a1668deef85a1301b21ba0b51ce5f2d3631b | 749 | py | Python | build.py | pakit/test_recipes | aa5379e4a4ef2d4019f6e8e3a87a06d529e0f910 | [
"BSD-3-Clause"
] | null | null | null | build.py | pakit/test_recipes | aa5379e4a4ef2d4019f6e8e3a87a06d529e0f910 | [
"BSD-3-Clause"
] | null | null | null | build.py | pakit/test_recipes | aa5379e4a4ef2d4019f6e8e3a87a06d529e0f910 | [
"BSD-3-Clause"
] | null | null | null | """ Formula that always errors on build """
import os
from pakit import Git, Recipe
from pakit.exc import PakitCmdError
import tests.common as tc
class Build(Recipe):
"""
Formula that always errors on build
"""
def __init__(self):
super(Build, self).__init__()
self.src = os.path.join(tc.STAGING, 'git')
self.homepage = self.src
self.repos = {
'stable': Git(self.src, tag='0.31.0'),
'unstable': Git(self.src),
}
def build(self):
self.cmd('./build.sh --prefix {prefix}')
self.cmd('make install')
raise PakitCmdError
def verify(self):
lines = self.cmd('ag --version').output()
assert lines[0].find('ag version') != -1
| 24.966667 | 50 | 0.580774 |
62fa1c2d112403eb5724618605cafbdd6ce6a72e | 2,220 | py | Python | lib/spack/spack/test/cmd/resource.py | whitfin/spack | aabd2be31a511d0e00c1017f7311a421659319d9 | [
"ECL-2.0",
"Apache-2.0",
"MIT"
] | 3 | 2019-06-27T13:26:50.000Z | 2019-07-01T16:24:54.000Z | lib/spack/spack/test/cmd/resource.py | openbiox/spack | bb6ec7fb40c14b37e094a860e3625af53f633174 | [
"ECL-2.0",
"Apache-2.0",
"MIT"
] | 75 | 2016-07-27T11:43:00.000Z | 2020-12-08T15:56:53.000Z | lib/spack/spack/test/cmd/resource.py | openbiox/spack | bb6ec7fb40c14b37e094a860e3625af53f633174 | [
"ECL-2.0",
"Apache-2.0",
"MIT"
] | 8 | 2015-10-16T13:51:49.000Z | 2021-10-18T13:58:03.000Z | # Copyright 2013-2019 Lawrence Livermore National Security, LLC and other
# Spack Project Developers. See the top-level COPYRIGHT file for details.
#
# SPDX-License-Identifier: (Apache-2.0 OR MIT)
from spack.main import SpackCommand
resource = SpackCommand('resource')
#: these are hashes used in mock packages
mock_hashes = [
'abcd1234abcd1234abcd1234abcd1234abcd1234abcd1234abcd1234abcd1234',
'1234abcd1234abcd1234abcd1234abcd1234abcd1234abcd1234abcd1234abcd',
'b5bb9d8014a0f9b1d61e21e796d78dccdf1352f23cd32812f4850b878ae4944c',
'c45c1564f70def3fc1a6e22139f62cb21cd190cc3a7dbe6f4120fa59ce33dcb8',
'24eceabef5fe8f575ff4b438313dc3e7b30f6a2d1c78841fbbe3b9293a589277',
'689b8f9b32cb1d2f9271d29ea3fca2e1de5df665e121fca14e1364b711450deb',
'ebe27f9930b99ebd8761ed2db3ea365142d0bafd78317efb4baadf62c7bf94d0',
'208fcfb50e5a965d5757d151b675ca4af4ce2dfd56401721b6168fae60ab798f',
'bf07a7fbb825fc0aae7bf4a1177b2b31fcf8a3feeaf7092761e18c859ee52a9c',
'7d865e959b2466918c9863afca942d0fb89d7c9ac0c99bafc3749504ded97730',
]
def test_resource_list(mock_packages, capfd):
with capfd.disabled():
out = resource('list')
for h in mock_hashes:
assert h in out
assert 'url:' in out
assert 'applies to:' in out
assert 'patched by:' in out
assert 'path:' in out
assert 'repos/builtin.mock/packages/patch-a-dependency/libelf.patch' in out
assert 'applies to: builtin.mock.libelf' in out
assert 'patched by: builtin.mock.patch-a-dependency' in out
def test_resource_list_only_hashes(mock_packages, capfd):
with capfd.disabled():
out = resource('list', '--only-hashes')
for h in mock_hashes:
assert h in out
def test_resource_show(mock_packages, capfd):
with capfd.disabled():
out = resource('show', 'c45c1564f70def3fc1a6e22139f62cb21cd190cc3a7dbe6f4120fa59ce33dcb8')
assert out.startswith('c45c1564f70def3fc1a6e22139f62cb21cd190cc3a7dbe6f4120fa59ce33dcb8')
assert 'repos/builtin.mock/packages/patch-a-dependency/libelf.patch' in out
assert 'applies to: builtin.mock.libelf' in out
assert 'patched by: builtin.mock.patch-a-dependency' in out
assert len(out.strip().split('\n')) == 4
| 36.393443 | 98 | 0.775225 |
31e1c78b5394c0608171f94dccca164f3c8b6ad8 | 2,372 | py | Python | airbyte-integrations/connectors/source-zendesk-singer/source_zendesk_singer/source.py | psiva2020/airbyte | 1741a0252c2fc0bf72df2232379ed29b99ab8b51 | [
"MIT"
] | null | null | null | airbyte-integrations/connectors/source-zendesk-singer/source_zendesk_singer/source.py | psiva2020/airbyte | 1741a0252c2fc0bf72df2232379ed29b99ab8b51 | [
"MIT"
] | null | null | null | airbyte-integrations/connectors/source-zendesk-singer/source_zendesk_singer/source.py | psiva2020/airbyte | 1741a0252c2fc0bf72df2232379ed29b99ab8b51 | [
"MIT"
] | null | null | null | """
MIT License
Copyright (c) 2020 Airbyte
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 airbyte_protocol import AirbyteConnectionStatus, Status
from base_python import AirbyteLogger, ConfigContainer
from base_singer import SingerSource
TAP_CMD = "tap-zendesk"
class SourceZendeskSinger(SingerSource):
def check(self, logger: AirbyteLogger, config_container: ConfigContainer) -> AirbyteConnectionStatus:
try:
self.discover(logger, config_container)
return AirbyteConnectionStatus(status=Status.SUCCEEDED)
except Exception:
logger.error("Exception while connecting to the Zendesk API")
return AirbyteConnectionStatus(
status=Status.FAILED,
message="Unable to connect to the Zendesk API with the provided credentials. Please make sure the "
"input credentials and environment are correct. ",
)
def discover_cmd(self, logger: AirbyteLogger, config_path: str) -> str:
return f"{TAP_CMD} -c {config_path} --discover"
def read_cmd(self, logger: AirbyteLogger, config_path: str, catalog_path: str, state_path: str = None) -> str:
# We don't pass state because this source does not respect replication-key so temporarily we're forcing it to be full refresh
return f"{TAP_CMD} --config {config_path} --catalog {catalog_path}"
| 46.509804 | 133 | 0.747892 |
f71563a970e54d91f082ae73af7abad4a8b23fdf | 205 | py | Python | exe.curso em video/def 20.py | Lorenzo-Lopes/Python-Estudo | 7ee623ce29b6a0e9fac48189fbd9c641be84d418 | [
"MIT"
] | null | null | null | exe.curso em video/def 20.py | Lorenzo-Lopes/Python-Estudo | 7ee623ce29b6a0e9fac48189fbd9c641be84d418 | [
"MIT"
] | null | null | null | exe.curso em video/def 20.py | Lorenzo-Lopes/Python-Estudo | 7ee623ce29b6a0e9fac48189fbd9c641be84d418 | [
"MIT"
] | null | null | null | import random
n1 = str(input('nome 1='))
n2 = str(input('nome 2='))
n3 = str(input('nome 3='))
n4 = str(input('nome 4='))
lista = [n1, n2, n3, n4]
random.shuffle(lista)
print('nova ordem{}'.format(lista))
| 22.777778 | 35 | 0.62439 |
ee43322391dd2368e10ad2af8cf24b9f93de180d | 608 | py | Python | dramkit/_tmp/test_code.py | Genlovy-Hoo/dramkit | fa3d2f35ebe9effea88a19e49d876b43d3c5c4c7 | [
"MIT"
] | null | null | null | dramkit/_tmp/test_code.py | Genlovy-Hoo/dramkit | fa3d2f35ebe9effea88a19e49d876b43d3c5c4c7 | [
"MIT"
] | null | null | null | dramkit/_tmp/test_code.py | Genlovy-Hoo/dramkit | fa3d2f35ebe9effea88a19e49d876b43d3c5c4c7 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
if __name__ == '__main__':
oath = '我爱妞'
print(type(oath))
print(len(oath))
oath1 = u'我爱妞'
print(type(oath1))
print(len(oath1))
print(oath==oath1)
utf8 = oath.encode('utf-8')
print(type(utf8))
print(len(utf8))
print(utf8)
gbk = oath.encode('gbk')
print(type(gbk))
print(len(gbk))
print(gbk)
out = open('test.txt','w',encoding = 'utf-8')
test = u'\u5220\u9664'
print(len(test))
print(test)
test1 = test.encode('utf-8')
print(test1)
print(type(test1))
out.write(test)
out.close()
| 16 | 49 | 0.550987 |
a96e575072862b75ddc6b7f07be271425ed4b375 | 6,573 | py | Python | certbot/tests/account_test.py | ccppuu/certbot | 9fead41aaf93dde0d36d4aef6fded8dd306c1ddc | [
"Apache-2.0"
] | 1 | 2017-12-20T20:06:11.000Z | 2017-12-20T20:06:11.000Z | certbot/tests/account_test.py | cpu/certbot | 9fead41aaf93dde0d36d4aef6fded8dd306c1ddc | [
"Apache-2.0"
] | null | null | null | certbot/tests/account_test.py | cpu/certbot | 9fead41aaf93dde0d36d4aef6fded8dd306c1ddc | [
"Apache-2.0"
] | null | null | null | """Tests for certbot.account."""
import datetime
import os
import shutil
import stat
import tempfile
import unittest
import mock
import pytz
from acme import jose
from acme import messages
from certbot import errors
from certbot.tests import test_util
KEY = jose.JWKRSA.load(test_util.load_vector("rsa512_key_2.pem"))
class AccountTest(unittest.TestCase):
"""Tests for certbot.account.Account."""
def setUp(self):
from certbot.account import Account
self.regr = mock.MagicMock()
self.meta = Account.Meta(
creation_host="test.certbot.org",
creation_dt=datetime.datetime(
2015, 7, 4, 14, 4, 10, tzinfo=pytz.UTC))
self.acc = Account(self.regr, KEY, self.meta)
with mock.patch("certbot.account.socket") as mock_socket:
mock_socket.getfqdn.return_value = "test.certbot.org"
with mock.patch("certbot.account.datetime") as mock_dt:
mock_dt.datetime.now.return_value = self.meta.creation_dt
self.acc_no_meta = Account(self.regr, KEY)
def test_init(self):
self.assertEqual(self.regr, self.acc.regr)
self.assertEqual(KEY, self.acc.key)
self.assertEqual(self.meta, self.acc_no_meta.meta)
def test_id(self):
self.assertEqual(
self.acc.id, "bca5889f66457d5b62fbba7b25f9ab6f")
def test_slug(self):
self.assertEqual(
self.acc.slug, "test.certbot.org@2015-07-04T14:04:10Z (bca5)")
def test_repr(self):
self.assertEqual(
repr(self.acc),
"<Account(bca5889f66457d5b62fbba7b25f9ab6f)>")
class ReportNewAccountTest(unittest.TestCase):
"""Tests for certbot.account.report_new_account."""
def setUp(self):
self.config = mock.MagicMock(config_dir="/etc/letsencrypt")
reg = messages.Registration.from_data(email="rhino@jungle.io")
self.acc = mock.MagicMock(regr=messages.RegistrationResource(
uri=None, new_authzr_uri=None, body=reg))
def _call(self):
from certbot.account import report_new_account
report_new_account(self.acc, self.config)
@mock.patch("certbot.account.zope.component.queryUtility")
def test_no_reporter(self, mock_zope):
mock_zope.return_value = None
self._call()
@mock.patch("certbot.account.zope.component.queryUtility")
def test_it(self, mock_zope):
self._call()
call_list = mock_zope().add_message.call_args_list
self.assertTrue(self.config.config_dir in call_list[0][0][0])
self.assertTrue(
", ".join(self.acc.regr.body.emails) in call_list[1][0][0])
class AccountMemoryStorageTest(unittest.TestCase):
"""Tests for certbot.account.AccountMemoryStorage."""
def setUp(self):
from certbot.account import AccountMemoryStorage
self.storage = AccountMemoryStorage()
def test_it(self):
account = mock.Mock(id="x")
self.assertEqual([], self.storage.find_all())
self.assertRaises(errors.AccountNotFound, self.storage.load, "x")
self.storage.save(account)
self.assertEqual([account], self.storage.find_all())
self.assertEqual(account, self.storage.load("x"))
self.storage.save(account)
self.assertEqual([account], self.storage.find_all())
class AccountFileStorageTest(unittest.TestCase):
"""Tests for certbot.account.AccountFileStorage."""
def setUp(self):
self.tmp = tempfile.mkdtemp()
self.config = mock.MagicMock(
accounts_dir=os.path.join(self.tmp, "accounts"))
from certbot.account import AccountFileStorage
self.storage = AccountFileStorage(self.config)
from certbot.account import Account
self.acc = Account(
regr=messages.RegistrationResource(
uri=None, new_authzr_uri=None, body=messages.Registration()),
key=KEY)
def tearDown(self):
shutil.rmtree(self.tmp)
def test_init_creates_dir(self):
self.assertTrue(os.path.isdir(self.config.accounts_dir))
def test_save_and_restore(self):
self.storage.save(self.acc)
account_path = os.path.join(self.config.accounts_dir, self.acc.id)
self.assertTrue(os.path.exists(account_path))
for file_name in "regr.json", "meta.json", "private_key.json":
self.assertTrue(os.path.exists(
os.path.join(account_path, file_name)))
self.assertEqual("0400", oct(os.stat(os.path.join(
account_path, "private_key.json"))[stat.ST_MODE] & 0o777))
# restore
self.assertEqual(self.acc, self.storage.load(self.acc.id))
def test_find_all(self):
self.storage.save(self.acc)
self.assertEqual([self.acc], self.storage.find_all())
def test_find_all_none_empty_list(self):
self.assertEqual([], self.storage.find_all())
def test_find_all_accounts_dir_absent(self):
os.rmdir(self.config.accounts_dir)
self.assertEqual([], self.storage.find_all())
def test_find_all_load_skips(self):
self.storage.load = mock.MagicMock(
side_effect=["x", errors.AccountStorageError, "z"])
with mock.patch("certbot.account.os.listdir") as mock_listdir:
mock_listdir.return_value = ["x", "y", "z"]
self.assertEqual(["x", "z"], self.storage.find_all())
def test_load_non_existent_raises_error(self):
self.assertRaises(errors.AccountNotFound, self.storage.load, "missing")
def test_load_id_mismatch_raises_error(self):
self.storage.save(self.acc)
shutil.move(os.path.join(self.config.accounts_dir, self.acc.id),
os.path.join(self.config.accounts_dir, "x" + self.acc.id))
self.assertRaises(errors.AccountStorageError, self.storage.load,
"x" + self.acc.id)
def test_load_ioerror(self):
self.storage.save(self.acc)
mock_open = mock.mock_open()
mock_open.side_effect = IOError
with mock.patch("__builtin__.open", mock_open):
self.assertRaises(
errors.AccountStorageError, self.storage.load, self.acc.id)
def test_save_ioerrors(self):
mock_open = mock.mock_open()
mock_open.side_effect = IOError # TODO: [None, None, IOError]
with mock.patch("__builtin__.open", mock_open):
self.assertRaises(
errors.AccountStorageError, self.storage.save, self.acc)
if __name__ == "__main__":
unittest.main() # pragma: no cover
| 35.33871 | 79 | 0.659364 |
fc3b42ae0843a53a401c890e21e960a798adf8cf | 1,703 | py | Python | cape_privacy/pandas/registry.py | vismaya-Kalaiselvan/cape-python | 2b93696cec43c4bab9098c35eccf6f2f66d9e5c0 | [
"Apache-2.0"
] | 144 | 2020-06-23T21:31:49.000Z | 2022-02-25T15:51:00.000Z | cape_privacy/pandas/registry.py | vismaya-Kalaiselvan/cape-python | 2b93696cec43c4bab9098c35eccf6f2f66d9e5c0 | [
"Apache-2.0"
] | 44 | 2020-06-24T14:42:23.000Z | 2022-02-21T03:30:58.000Z | cape_privacy/pandas/registry.py | vismaya-Kalaiselvan/cape-python | 2b93696cec43c4bab9098c35eccf6f2f66d9e5c0 | [
"Apache-2.0"
] | 16 | 2020-06-26T20:05:51.000Z | 2022-01-12T05:23:58.000Z | from typing import Callable
from typing import Dict
from cape_privacy.pandas.transformations import ColumnRedact
from cape_privacy.pandas.transformations import DatePerturbation
from cape_privacy.pandas.transformations import DateTruncation
from cape_privacy.pandas.transformations import NumericPerturbation
from cape_privacy.pandas.transformations import NumericRounding
from cape_privacy.pandas.transformations import ReversibleTokenizer
from cape_privacy.pandas.transformations import RowRedact
from cape_privacy.pandas.transformations import Tokenizer
from cape_privacy.pandas.transformations import TokenReverser
TransformationCtor = Callable
_registry: Dict[str, TransformationCtor] = {}
def get(transformation: str) -> TransformationCtor:
"""Returns the constructor for the given key.
Arguments:
transformation: The key of transformation to retrieve.
"""
return _registry.get(transformation, None)
def register(label: str, ctor: TransformationCtor):
"""Registers a new transformation constructor under the label provided.
Arguments:
label: The label that will be used as the key in the registry
ctor: The transformation constructor
"""
_registry[label] = ctor
register(DatePerturbation.identifier, DatePerturbation)
register(NumericPerturbation.identifier, NumericPerturbation)
register(NumericRounding.identifier, NumericRounding)
register(Tokenizer.identifier, Tokenizer)
register(DateTruncation.identifier, DateTruncation)
register(ColumnRedact.identifier, ColumnRedact)
register(RowRedact.identifier, RowRedact)
register(TokenReverser.identifier, TokenReverser)
register(ReversibleTokenizer.identifier, ReversibleTokenizer)
| 36.234043 | 75 | 0.825015 |
30ab50f2ef94955a33d9f8e68b5bbd31416ac595 | 2,368 | py | Python | server-reverse-shell.py | punyaslokdutta/Reverse-Shell-scripts | 8362c09243fd0578854512ecbe55403b66310392 | [
"MIT"
] | null | null | null | server-reverse-shell.py | punyaslokdutta/Reverse-Shell-scripts | 8362c09243fd0578854512ecbe55403b66310392 | [
"MIT"
] | null | null | null | server-reverse-shell.py | punyaslokdutta/Reverse-Shell-scripts | 8362c09243fd0578854512ecbe55403b66310392 | [
"MIT"
] | null | null | null |
# Notice that I've used 0.0.0.0 as the server IP address, this means all IPv4 addresses on the local machine. You may wonder, why we don't just use our local IP address or localhost or 127.0.0.1 ? Well, if the server has two IP addresses, let's say 192.168.1.101 on a network, and 10.0.1.1 on another, and the server listens on 0.0.0.0, then it will be reachable at both of those IPs.
# We then specified some variables and initiated the TCP socket. Notice I used 5003 as the TCP port, feel free to choose any port above 1024, just make sure it's not used and you should use it on both sides (i.e server and client).
# However, malicious reverse shells usually uses the popular port 80 (i.e http) or 443 (i.e https), this will allow it to bypass firewall restrictions of the target client.
# 0.0.0.0 has a couple of different meanings, but in this context,
# when a server is told to listen on 0.0.0.0 that means
# "listen on every available network interface".
# The loopback adapter with IP address 127.0.0.1 from the perspective of the server
# process looks just like any other network adapter on the machine, so a server
# told to listen on 0.0.0.0 will accept connections on that interface too.
import socket
SERVER_HOST = "0.0.0.0"
SERVER_PORT = 5003
BUFFER_SIZE = 1024 * 128 # 128KB max size of messages, feel free to increase
# separator string for sending 2 messages in one go
SEPARATOR = "<sep>"
# create a socket object
s = socket.socket()
s.bind((SERVER_HOST, SERVER_PORT))
s.listen(5)
print(f"Listening as {SERVER_HOST}:{SERVER_PORT} ...")
client_socket, client_address = s.accept()
print(f"{client_address[0]}:{client_address[1]} Connected!")
# receiving the current working directory of the client
cwd = client_socket.recv(BUFFER_SIZE).decode()
print("[+] Current working directory:", cwd)
while True:
# get the command from prompt
command = input(f"{cwd} $> ")
if not command.strip():
# empty command
continue
# send the command to the client
client_socket.send(command.encode())
if command.lower() == "exit":
# if the command is exit, just break out of the loop
break
# retrieve command results
output = client_socket.recv(BUFFER_SIZE).decode()
# split command output and current directory
results, cwd = output.split(SEPARATOR)
# print output
print(results)
| 45.538462 | 384 | 0.724662 |
70f58a864ad808722f1b9a459eee7eb12af34613 | 8,568 | py | Python | s3/replication/common/src/s3replicationcommon/aws_v4_signer.py | kaustubh-d/cortx-multisite | 125463bfd0f65df6aecff078b5ef1487451aac7d | [
"Apache-2.0"
] | null | null | null | s3/replication/common/src/s3replicationcommon/aws_v4_signer.py | kaustubh-d/cortx-multisite | 125463bfd0f65df6aecff078b5ef1487451aac7d | [
"Apache-2.0"
] | null | null | null | s3/replication/common/src/s3replicationcommon/aws_v4_signer.py | kaustubh-d/cortx-multisite | 125463bfd0f65df6aecff078b5ef1487451aac7d | [
"Apache-2.0"
] | null | null | null | #
# Copyright (c) 2021 Seagate Technology LLC and/or its Affiliates
#
# 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.
#
# For any questions about this software or licensing,
# please email opensource@seagate.com or cortx-questions@seagate.com.
#
"""Utility class used for Authentication using V4 signature."""
import hmac
import hashlib
import urllib
import datetime
class AWSV4Signer(object):
"""Generate Authentication headers to validate requests."""
def __init__(self, endpoint, service_name, region, access_key, secret_key):
"""Initialise config."""
self._endpoint = endpoint
self._service_name = service_name
self._region = region
self._access_key = access_key
self._secret_key = secret_key
# Helper method.
def _get_headers(host, epoch_t, body_256hash):
headers = {
'host': host,
'x-amz-content-sha256': body_256hash,
'x-amz-date': AWSV4Signer._get_amz_timestamp(epoch_t)
}
return headers
def _create_canonical_request(
self,
method,
canonical_uri,
canonical_query_string,
body,
epoch_t,
host):
"""Create canonical request based on uri and query string."""
body_256sha_hex = 'UNSIGNED-PAYLOAD'
if body:
# body has some content.
body_256sha_hex = hashlib.sha256(body.encode('utf-8')).hexdigest()
self._body_hash_hex = body_256sha_hex
headers = AWSV4Signer._get_headers(host, epoch_t, body_256sha_hex)
sorted_headers = sorted([k for k in headers])
canonical_headers = ""
for key in sorted_headers:
canonical_headers += "{}:{}\n".format(
key.lower(), headers[key].strip())
signed_headers = "{}".format(";".join(sorted_headers))
canonical_request = method + '\n' + canonical_uri + '\n' + \
canonical_query_string + '\n' + canonical_headers + '\n' + \
signed_headers + '\n' + body_256sha_hex
return canonical_request
# Helper method.
def _sign(key, msg):
"""Return hmac value based on key and msg."""
return hmac.new(key, msg.encode('utf-8'), hashlib.sha256).digest()
# Helper method.
def _getV4SignatureKey(key, dateStamp, regionName, serviceName):
"""Generate v4 signature.
Generate v4 signature based on key, datestamp, region and
service name.
"""
kDate = AWSV4Signer._sign(('AWS4' + key).encode('utf-8'), dateStamp)
kRegion = AWSV4Signer._sign(kDate, regionName)
kService = AWSV4Signer._sign(kRegion, serviceName)
kSigning = AWSV4Signer._sign(kService, 'aws4_request')
return kSigning
def _create_string_to_sign_v4(
self,
method='',
canonical_uri='',
canonical_query_string='',
body='',
epoch_t='',
algorithm='',
host='',
service='',
region=''):
"""Generates string_to_sign for authorization key generation."""
canonical_request = self._create_canonical_request(
method, canonical_uri, canonical_query_string, body, epoch_t, host)
credential_scope = AWSV4Signer._get_date(epoch_t) + '/' + \
region + '/' + service + '/' + 'aws4_request'
string_to_sign = algorithm + '\n' + \
AWSV4Signer._get_amz_timestamp(epoch_t) + '\n' + \
credential_scope + '\n' + \
hashlib.sha256(canonical_request.encode('utf-8')).hexdigest()
return string_to_sign
# Helper method.
def _get_date(epoch_t):
"""Return date in Ymd format."""
return epoch_t.strftime('%Y%m%d')
# Helper method.
def _get_amz_timestamp(epoch_t):
"""Return timestamp in YMDTHMSZ format."""
return epoch_t.strftime('%Y%m%dT%H%M%SZ')
# Helper Helper method for generating request_uri for v4 signing.
def fmt_s3_request_uri(bucket_name, object_name):
# The URL quoting functions focus on taking program data and making
# it safe for use as URL components by quoting special characters
# and appropriately encoding non-ASCII text.
# urllib.parse.urlencode converts a mapping object or a sequence of
# two-element tuples, which may contain str or bytes objects,
# to a percent-encoded ASCII text string.
# https://docs.python.org/3/library/urllib.parse.html
request_uri = '/' + urllib.parse.quote(bucket_name, safe='') + '/' + \
urllib.parse.quote(object_name, safe='')
return request_uri
# generating AWS v4 Authorization signature
def sign_request_v4(
self,
method=None,
canonical_uri='/',
canonical_query_string='',
body='',
epoch_t='',
host='',
service='',
region=''):
"""Generate authorization signature."""
if method is None:
print("method can not be null")
return None
credential_scope = AWSV4Signer._get_date(epoch_t) + '/' + region + \
'/' + service + '/' + 'aws4_request'
headers = AWSV4Signer._get_headers(host, epoch_t, body)
sorted_headers = sorted([k for k in headers])
signed_headers = "{}".format(";".join(sorted_headers))
algorithm = 'AWS4-HMAC-SHA256'
string_to_sign = self._create_string_to_sign_v4(
method,
canonical_uri,
canonical_query_string,
body,
epoch_t,
algorithm,
host,
service,
region)
signing_key = AWSV4Signer._getV4SignatureKey(
self._secret_key, AWSV4Signer._get_date(epoch_t), region, service)
signature = hmac.new(
signing_key,
(string_to_sign).encode('utf-8'),
hashlib.sha256).hexdigest()
authorization_header = algorithm + ' ' + 'Credential=' + \
self._access_key + '/' + credential_scope + ', ' + \
'SignedHeaders=' + signed_headers + \
', ' + 'Signature=' + signature
return authorization_header
# generating AWS v4 signature header
def prepare_signed_header(
self,
http_request,
request_uri,
query_params,
body):
"""
Generate headers used for authorization requests.
Parameters:
http_request - Any of http verbs: GET, PUT, DELETE, POST
request_uri - URL safe resource string,
example /bucket_name/object_name
query_params - URL safe query param string,
example param1=abc¶m2=somevalue
body - content
Returns:
headers dictionary with following header keys: Authorization,
x-amz-date, and x-amz-content-sha256
Sample usage: headers =
AWSV4Signer("http://s3.seagate.com", "cortxs3", 'us-west2',
access_key, secret_key).prepare_signed_header(
'PUT', request_uri, query_params, body)
"""
url_parse_result = urllib.parse.urlparse(self._endpoint)
epoch_t = datetime.datetime.utcnow()
headers = {'content-type': 'application/x-www-form-urlencoded',
'Accept': 'text/plain'}
# Generate the signature and setup Authorization header.
headers['Authorization'] = self.sign_request_v4(
http_request,
request_uri,
query_params,
body,
epoch_t,
url_parse_result.netloc,
self._service_name,
self._region)
# Setup std headers
headers['x-amz-date'] = AWSV4Signer._get_amz_timestamp(epoch_t)
# generated in _create_canonical_request()
headers['x-amz-content-sha256'] = self._body_hash_hex
return headers
| 35.7 | 79 | 0.602941 |
97eae18fd20d31a26c2ed3268bb7f7cd547b201c | 4,162 | py | Python | src/_pytest/stepwise.py | charlesaracil-ulti/pytest | dbd082af961871c59f2dbcda2fcb27faf4fa2ebc | [
"MIT"
] | null | null | null | src/_pytest/stepwise.py | charlesaracil-ulti/pytest | dbd082af961871c59f2dbcda2fcb27faf4fa2ebc | [
"MIT"
] | null | null | null | src/_pytest/stepwise.py | charlesaracil-ulti/pytest | dbd082af961871c59f2dbcda2fcb27faf4fa2ebc | [
"MIT"
] | null | null | null | from typing import List
from typing import Optional
import pytest
from _pytest import nodes
from _pytest.config import Config
from _pytest.config.argparsing import Parser
from _pytest.main import Session
from _pytest.reports import TestReport
def pytest_addoption(parser: Parser) -> None:
group = parser.getgroup("general")
group.addoption(
"--sw",
"--stepwise",
action="store_true",
dest="stepwise",
help="exit on test failure and continue from last failing test next time",
)
group.addoption(
"--stepwise-skip",
action="store_true",
dest="stepwise_skip",
help="ignore the first failing test but stop on the next failing test",
)
@pytest.hookimpl
def pytest_configure(config: Config) -> None:
config.pluginmanager.register(StepwisePlugin(config), "stepwiseplugin")
class StepwisePlugin:
def __init__(self, config: Config) -> None:
self.config = config
self.active = config.getvalue("stepwise")
self.session: Optional[Session] = None
self.report_status = ""
if self.active:
assert config.cache is not None
self.lastfailed = config.cache.get("cache/stepwise", None)
self.skip = config.getvalue("stepwise_skip")
def pytest_sessionstart(self, session: Session) -> None:
self.session = session
def pytest_collection_modifyitems(
self, session: Session, config: Config, items: List[nodes.Item]
) -> None:
if not self.active:
return
if not self.lastfailed:
self.report_status = "no previously failed tests, not skipping."
return
already_passed = []
found = False
# Make a list of all tests that have been run before the last failing one.
for item in items:
if item.nodeid == self.lastfailed:
found = True
break
else:
already_passed.append(item)
# If the previously failed test was not found among the test items,
# do not skip any tests.
if not found:
self.report_status = "previously failed test not found, not skipping."
already_passed = []
else:
self.report_status = "skipping {} already passed items.".format(
len(already_passed)
)
for item in already_passed:
items.remove(item)
config.hook.pytest_deselected(items=already_passed)
def pytest_runtest_logreport(self, report: TestReport) -> None:
if not self.active:
return
if report.failed:
if self.skip:
# Remove test from the failed ones (if it exists) and unset the skip option
# to make sure the following tests will not be skipped.
if report.nodeid == self.lastfailed:
self.lastfailed = None
self.skip = False
else:
# Mark test as the last failing and interrupt the test session.
self.lastfailed = report.nodeid
assert self.session is not None
self.session.shouldstop = (
"Test failed, continuing from this test next run."
)
else:
# If the test was actually run and did pass.
if report.when == "call":
# Remove test from the failed ones, if exists.
if report.nodeid == self.lastfailed:
self.lastfailed = None
def pytest_report_collectionfinish(self) -> Optional[str]:
if self.active and self.config.getoption("verbose") >= 0 and self.report_status:
return "stepwise: %s" % self.report_status
return None
def pytest_sessionfinish(self, session: Session) -> None:
assert self.config.cache is not None
if self.active:
self.config.cache.set("cache/stepwise", self.lastfailed)
else:
# Clear the list of failing tests if the plugin is not active.
self.config.cache.set("cache/stepwise", [])
| 33.837398 | 91 | 0.600913 |
2abcc90a1d83dc4d7537d08d2399dff19138b638 | 2,858 | py | Python | view.py | IDA-TUBS/MCC | bbc149796b09d0895d899f3f31e1da199950e85e | [
"BSD-3-Clause"
] | null | null | null | view.py | IDA-TUBS/MCC | bbc149796b09d0895d899f3f31e1da199950e85e | [
"BSD-3-Clause"
] | null | null | null | view.py | IDA-TUBS/MCC | bbc149796b09d0895d899f3f31e1da199950e85e | [
"BSD-3-Clause"
] | null | null | null | #!/usr/bin/env python
import sys
import gi
gi.require_version('Gtk', '3.0')
from gi.repository import GLib, Gio, Gtk
from viewer.window import Window
MENU_XML="""
<?xml version="1.0" encoding="UTF-8"?>
<interface>
<menu id="app-menu">
<section>
<item>
<attribute name="action">app.open</attribute>
<attribute name="label" translatable="yes">_Open</attribute>
</item>
<item>
<attribute name="action">app.quit</attribute>
<attribute name="label" translatable="yes">_Quit</attribute>
<attribute name="accel"><Primary>q</attribute>
</item>
</section>
</menu>
</interface>
"""
class Application(Gtk.Application):
def __init__(self, *args, **kwargs):
super().__init__(*args, application_id="org.example.myapp",
flags=Gio.ApplicationFlags.HANDLES_COMMAND_LINE,
**kwargs)
self.window = None
self.add_main_option("test", ord("t"), GLib.OptionFlags.NONE,
GLib.OptionArg.NONE, "Command line test", None)
#TODO let GTK open files?
self.add_main_option("pickle", ord("p"), GLib.OptionFlags.NONE,
GLib.OptionArg.STRING_ARRAY,
"Open pickle file(s)", None)
def do_startup(self):
Gtk.Application.do_startup(self)
action = Gio.SimpleAction.new("open", None)
action.connect("activate", self.on_open)
self.add_action(action)
action = Gio.SimpleAction.new("quit", None)
action.connect("activate", self.on_quit)
self.add_action(action)
builder = Gtk.Builder.new_from_string(MENU_XML, -1)
self.set_app_menu(builder.get_object("app-menu"))
def do_activate(self):
# We only allow a single window and raise any existing ones
if not self.window:
# Windows are associated with the application
# when the last one is closed the application shuts down
self.window = Window(application=self, title="MCC Model Viewer")
self.window.present()
def do_command_line(self, command_line):
options = command_line.get_options_dict()
# convert GVariantDict -> GVariant -> dict
options = options.end().unpack()
if "test" in options:
# This is printed on the main instance
print("Test argument recieved: %s" % options["test"])
self.activate()
if 'pickle' in options:
for path in options['pickle']:
self.window.open_file(path)
return 0
def on_open(self, action, param):
if self.window:
self.window.on_open(action)
def on_quit(self, action, param):
self.quit()
if __name__ == "__main__":
app = Application()
app.run(sys.argv)
| 30.084211 | 76 | 0.601819 |
601328b9b0235d26e1d3a3b855b272a0e4163020 | 5,774 | py | Python | textcatvis/distinctive_words.py | cod3licious/textcatvis | 2d1befbb27606bc9f965a0a76e205d8d56ee321a | [
"MIT"
] | 13 | 2017-06-18T18:02:39.000Z | 2021-02-15T17:04:15.000Z | textcatvis/distinctive_words.py | cod3licious/textcatvis | 2d1befbb27606bc9f965a0a76e205d8d56ee321a | [
"MIT"
] | null | null | null | textcatvis/distinctive_words.py | cod3licious/textcatvis | 2d1befbb27606bc9f965a0a76e205d8d56ee321a | [
"MIT"
] | 1 | 2018-09-03T14:52:27.000Z | 2018-09-03T14:52:27.000Z | from __future__ import unicode_literals, division, print_function, absolute_import
import sys
import numpy as np
from nlputils.dict_utils import invert_dict0, invert_dict2
from nlputils.features import FeatureTransform
def distinctive_fun_tpr(tpr, fpr):
# to get the development of word occurrences
return tpr
def distinctive_fun_diff(tpr, fpr):
# computes the distinctive score as the difference between tpr and fpr rate (not below 0 though)
return np.maximum(tpr - fpr, 0.)
def distinctive_fun_tprmean(tpr, fpr):
# computes the distinctive score as the mean between the tpr and the difference between tpr and fpr rate
return 0.5 * (tpr + np.maximum(tpr - fpr, 0.))
def distinctive_fun_tprmult(tpr, fpr):
return tpr * np.maximum(tpr - fpr, 0.)
def distinctive_fun_quot(tpr, fpr):
# return 1./(1.+np.exp(-tpr/np.maximum(fpr,sys.float_info.epsilon)))
return (np.minimum(np.maximum(tpr / np.maximum(fpr, sys.float_info.epsilon), 1.), 4.) - 1) / 3.
def distinctive_fun_quotdiff(tpr, fpr):
# return 1./(1.+np.exp(-tpr/np.maximum(fpr,sys.float_info.epsilon)))
return 0.5 * (distinctive_fun_quot(tpr, fpr) + distinctive_fun_diff(tpr, fpr))
def get_distinctive_words(textdict, doccats, distinctive_fun=distinctive_fun_quotdiff):
"""
For every category, find distinctive (i.e. `distinguishing') words by comparing how often the word each word
occurs in this target category compared to all other categories.
Input:
- textdict: a dict with {docid: text}
- doccats: a dict with {docid: cat} (to get trends in time, cat could also be a year/day/week)
- distinctive_fun: which formula should be used when computing the score (default: distinctive_fun_quotdiff)
Returns:
- distinctive_words: a dict with {cat: {word: score}},
i.e. for every category the words and a score indicating
how relevant the word is for this category (the higher the better)
you could then do sorted(distinctive_words[cat], key=distinctive_words[cat].get, reverse=True)[:10]
to get the 10 most distinguishing words for that category
"""
# transform all texts into sets of preprocessed words and bigrams
print("computing features")
ft = FeatureTransform(norm='max', weight=False, renorm=False, identify_bigrams=True, norm_num=False)
docfeats = ft.texts2features(textdict)
#docfeats = {did: set(docfeats[did].keys()) for did in docfeats}
# invert this dict to get for every word the documents it occurs in
# word_dids = {word: set(dids) for word, dids in invert_dict1(docfeats).items()}
# invert the doccats dict to get for every category a list of documents belonging to it
cats_dids = {cat: set(dids) for cat, dids in invert_dict0(doccats).items()}
# get a list of all words
word_list = list(invert_dict2(docfeats).keys())
# count the true positives for every word and category
print("computing tpr for all words and categories")
tpc_words = {}
for word in word_list:
tpc_words[word] = {}
for cat in cats_dids:
# out of all docs in this category, in how many did the word occur?
#tpc_words[word][cat] = len(cats_dids[cat].intersection(word_dids[word])) / len(cats_dids[cat])
# average tf score in the category
# (don't just take mean of the list comprehension otherwise you're missing zero counts)
tpc_words[word][cat] = sum([docfeats[did][word] for did in cats_dids[cat] if word in docfeats[did]]) / len(cats_dids[cat])
# for every category, compute a score for every word
distinctive_words = {}
for cat in cats_dids:
print("computing distinctive words for category %r" % cat)
distinctive_words[cat] = {}
# compute a score for every word
for word in word_list:
# in how many of the target category documents the word occurs
tpr = tpc_words[word][cat]
if tpr:
# in how many of the non-target category documents the word occurs (mean+std)
fprs = [tpc_words[word][c] for c in cats_dids if not c == cat]
fpr = np.mean(fprs) + np.std(fprs)
# compute score
distinctive_words[cat][word] = distinctive_fun(tpr, fpr)
return distinctive_words
def test_distinctive_computations(distinctive_fun=distinctive_fun_diff, fun_name='Rate difference'):
"""
given a function to compute the "distinctive score" of a word given its true and false positive rate,
plot the distribution of scores (2D) corresponding to the different tpr and fpr
"""
# make a grid of possible tpr and fpr combinations
import matplotlib.pyplot as plt
x, y = np.linspace(0, 1, 101), np.linspace(1, 0, 101)
fpr, tpr = np.meshgrid(x, y)
score = distinctive_fun(tpr, fpr)
plt.figure()
plt.imshow(score, cmap=plt.get_cmap('viridis'))
plt.xlabel('FPR$_c(t_i)$')
plt.ylabel('TPR$_c(t_i)$')
plt.xticks(np.linspace(0, 101, 11), np.linspace(0, 1, 11))
plt.yticks(np.linspace(0, 101, 11), np.linspace(1, 0, 11))
plt.title('Score using %s' % fun_name)
plt.colorbar()
if __name__ == '__main__':
import matplotlib.pyplot as plt
test_distinctive_computations(distinctive_fun_tpr, 'TPR')
test_distinctive_computations(distinctive_fun_diff, 'Rate Difference')
test_distinctive_computations(distinctive_fun_tprmean, 'Mean of TPR and Rate Difference')
test_distinctive_computations(distinctive_fun_tprmult, 'TPR weighted Rate Difference')
test_distinctive_computations(distinctive_fun_quot, 'Rate Quotient')
test_distinctive_computations(distinctive_fun_quotdiff, 'Mean of Rate Quotient and Difference')
plt.show()
| 47.327869 | 134 | 0.696571 |
0085a1c0b5552fdb22ff9f243bdfefa4c0c28bd7 | 7,192 | py | Python | tests/melody_tests/constraints_tests/test_fit_pitch_to_function_constraint.py | dpazel/music_rep | 2f9de9b98b13df98f1a0a2120b84714725ce527e | [
"MIT"
] | 1 | 2021-05-06T19:45:54.000Z | 2021-05-06T19:45:54.000Z | tests/melody_tests/constraints_tests/test_fit_pitch_to_function_constraint.py | dpazel/music_rep | 2f9de9b98b13df98f1a0a2120b84714725ce527e | [
"MIT"
] | null | null | null | tests/melody_tests/constraints_tests/test_fit_pitch_to_function_constraint.py | dpazel/music_rep | 2f9de9b98b13df98f1a0a2120b84714725ce527e | [
"MIT"
] | null | null | null | import unittest
import math
from function.generic_univariate_pitch_function import GenericUnivariatePitchFunction
from harmonicmodel.tertian_chord_template import TertianChordTemplate
from melody.constraints.contextual_note import ContextualNote
from melody.constraints.fit_pitch_to_function_constraint import FitPitchToFunctionConstraint
from melody.solver.p_map import PMap
from structure.line import Line
from structure.note import Note
from structure.tempo import Tempo
from structure.time_signature import TimeSignature
from timemodel.duration import Duration
from timemodel.event_sequence import EventSequence
from timemodel.offset import Offset
from timemodel.position import Position
from timemodel.tempo_event import TempoEvent
from timemodel.tempo_event_sequence import TempoEventSequence
from timemodel.time_signature_event import TimeSignatureEvent
from tonalmodel.diatonic_pitch import DiatonicPitch
from tonalmodel.diatonic_tone import DiatonicTone
from tonalmodel.modality import ModalityType
from tonalmodel.pitch_range import PitchRange
from tonalmodel.tonality import Tonality
from harmoniccontext.harmonic_context import HarmonicContext
from melody.constraints.policy_context import PolicyContext
import logging
import sys
class TestFitPitchToFunctionConstraint(unittest.TestCase):
logging.basicConfig(stream=sys.stdout, level=logging.DEBUG)
# Note: add -s --nologcapture to 'additional arguments in configuration to see logging
def setUp(self):
pass
def tearDown(self):
pass
def test_sample(self):
# index = min(enumerate(self.candidate_pitches), key=lambda x: abs(x[0] - self.function_value))[0]
p = [(32, True), (25, True)]
lll = min(enumerate(p), key=lambda x: abs(x[1][0]))
index = lll[0]
print('---v={0}'.format(index))
def test_compute_simple_function_tone(self):
print('--- test_compute_simple_function_tone ---')
line = Line()
f = GenericUnivariatePitchFunction(TestFitPitchToFunctionConstraint.sinasoidal, Position(0), Position(2))
v_note = Note(DiatonicPitch.parse('A:4'), Duration(1, 32))
line.pin(v_note, Offset(0))
constraint, lower_policy_context = TestFitPitchToFunctionConstraint.build_simple_constraint(v_note, f,
ModalityType.Major,
'G', 'tV')
p_map = PMap()
p_map[v_note] = ContextualNote(lower_policy_context)
results = constraint.values(p_map, v_note)
assert results is not None
assert len(results) == 1
print(next(iter(results)).diatonic_pitch)
assert 'C:4' == str(next(iter(results)).diatonic_pitch)
v_note = Note(DiatonicPitch.parse('A:4'), Duration(1, 32))
line.pin(v_note, Offset(1, 32))
constraint, lower_policy_context = TestFitPitchToFunctionConstraint.build_simple_constraint(v_note, f,
ModalityType.Major,
'G', 'tV')
p_map = PMap()
p_map[v_note] = ContextualNote(lower_policy_context)
results = constraint.values(p_map, v_note)
assert results is not None
assert len(results) == 1
print(next(iter(results)).diatonic_pitch)
assert 'E:4' == str(next(iter(results)).diatonic_pitch)
p_map[v_note].note = next(iter(results))
assert constraint.verify(p_map)
def test_compute_with_minor_key(self):
print('-- test_compute_with_minor_key ---')
line = Line()
f = GenericUnivariatePitchFunction(TestFitPitchToFunctionConstraint.sinasoidal, Position(0), Position(2))
v_notes = [Note(DiatonicPitch.parse('A:4'), Duration(1, 16)) for _ in range(0, 33)]
for i in range(0, 33):
line.pin(v_notes[i], Offset(i, 16))
constraint, lower_policy_context = \
TestFitPitchToFunctionConstraint.build_simple_constraint(v_notes[0], f, ModalityType.NaturalMinor,
'C', 'tV')
constraints = list()
constraints.append(constraint)
for i in range(1, 33):
c, _ = \
TestFitPitchToFunctionConstraint.build_simple_constraint(v_notes[i], f, ModalityType.NaturalMinor,
'C', 'tV')
constraints.append(c)
p_map = PMap()
p_map[v_notes[0]] = ContextualNote(lower_policy_context)
results = constraint.values(p_map, v_notes[0])
assert results is not None
assert len(results) == 1
print(next(iter(results)).diatonic_pitch)
assert 'C:4' == str(next(iter(results)).diatonic_pitch)
result_pitches = []
for i in range(0, 33):
p_map = PMap()
p_map[v_notes[i]] = ContextualNote(lower_policy_context)
results = constraints[i].values(p_map, v_notes[i])
result_pitches.append(next(iter(results)).diatonic_pitch)
assert len(result_pitches) == 33
for i in range(0, 33):
print('[{0}] {1}'.format(i, str(result_pitches[i])))
# checks = ['C:4', 'Ab:4', 'D:5', 'F:5', 'G:5', 'F:5', 'D:5', 'Ab:4', 'C:4']
checks = ['C:4', 'G:4', 'D:5', 'F:5', 'G:5', 'F:5', 'D:5', 'G:4', 'C:4']
for i in range(0, len(checks)):
assert checks[i] == str(result_pitches[i])
BASE = DiatonicPitch.parse('C:4').chromatic_distance
@staticmethod
def sinasoidal(v):
return TestFitPitchToFunctionConstraint.BASE + 19 * math.sin(2 * math.pi * v)
@staticmethod
def policy_creator(modality_type, modality_tone, tertian_chord_txt, low_pitch_txt, hi_pitch_txt):
diatonic_tonality = Tonality.create(modality_type, modality_tone)
chord = TertianChordTemplate.parse(tertian_chord_txt).create_chord(diatonic_tonality)
hc = HarmonicContext(diatonic_tonality, chord, Duration(1, 2))
pitch_range = PitchRange(DiatonicPitch.parse(low_pitch_txt).chromatic_distance,
DiatonicPitch.parse(hi_pitch_txt).chromatic_distance)
return PolicyContext(hc, pitch_range)
@staticmethod
def build_simple_constraint(v_note, f, modality_type, key_str, chord_str):
lower_policy_context = TestFitPitchToFunctionConstraint.policy_creator(modality_type, DiatonicTone(key_str),
chord_str, 'C:2', 'C:8')
tempo_seq = TempoEventSequence()
ts_seq = EventSequence()
tempo_seq.add(TempoEvent(Tempo(60, Duration(1, 4)), Position(0)))
ts_seq.add(TimeSignatureEvent(TimeSignature(3, Duration(1, 4), 'sww'), Position(0)))
return FitPitchToFunctionConstraint(v_note, f, tempo_seq, ts_seq), lower_policy_context
if __name__ == "__main__":
unittest.main()
| 43.587879 | 119 | 0.635011 |
815d4348248157beed179b0fc89a4d9c53490724 | 774 | py | Python | tests/functional/scripts/pyi_lib_PIL_img_conversion.py | BearerPipelineTest/pyinstaller | 0de9d6cf1701689c53161610acdab143a76d40b5 | [
"Apache-2.0"
] | null | null | null | tests/functional/scripts/pyi_lib_PIL_img_conversion.py | BearerPipelineTest/pyinstaller | 0de9d6cf1701689c53161610acdab143a76d40b5 | [
"Apache-2.0"
] | null | null | null | tests/functional/scripts/pyi_lib_PIL_img_conversion.py | BearerPipelineTest/pyinstaller | 0de9d6cf1701689c53161610acdab143a76d40b5 | [
"Apache-2.0"
] | null | null | null | #-----------------------------------------------------------------------------
# Copyright (c) 2005-2022, PyInstaller Development Team.
#
# Distributed under the terms of the GNU General Public License (version 2
# or later) with exception for distributing the bootloader.
#
# The full license is in the file COPYING.txt, distributed with this software.
#
# SPDX-License-Identifier: (GPL-2.0-or-later WITH Bootloader-exception)
#-----------------------------------------------------------------------------
import sys
import os
import PIL.Image
# Disable "leaking" the installed version.
PIL.Image.__file__ = '/'
# Convert tiff to png.
basedir = sys._MEIPASS
im = PIL.Image.open(os.path.join(basedir, "tinysample.tiff"))
im.save(os.path.join(basedir, "tinysample.png"))
| 32.25 | 78 | 0.600775 |
3e69033514e8d5f6e203cba88b6a9f4ba29668c6 | 4,029 | py | Python | t5/myip.py | LorhanSohaky/matias.exe | 367157ff330901f9b736d71315d92cab2ad7c50c | [
"MIT"
] | 2 | 2019-10-31T03:51:49.000Z | 2019-12-03T00:53:50.000Z | t3/myip.py | LorhanSohaky/matias.exe | 367157ff330901f9b736d71315d92cab2ad7c50c | [
"MIT"
] | null | null | null | t3/myip.py | LorhanSohaky/matias.exe | 367157ff330901f9b736d71315d92cab2ad7c50c | [
"MIT"
] | 3 | 2019-09-03T00:48:16.000Z | 2019-10-22T17:47:06.000Z | from myiputils import *
from mytcputils import *
from ipaddress import ip_network, ip_address
from random import randint
def make_icmp(datagrama):
unused = 0
checksum = 0
tipo = 11
codigo = 0
payload = datagrama[:28]
comprimento = 8 + len(payload)
icmp = struct.pack('!bbhi', tipo, codigo, checksum, comprimento) + payload
checksum = twos_comp(calc_checksum(icmp), 16)
icmp = struct.pack('!bbhi', tipo, codigo, checksum, comprimento) + payload
return icmp
class CamadaRede:
def __init__(self, enlace):
"""
Inicia a camada de rede. Recebe como argumento uma implementação
de camada de enlace capaz de localizar os next_hop (por exemplo,
Ethernet com ARP).
"""
self.callback = None
self.enlace = enlace
self.enlace.registrar_recebedor(self.__raw_recv)
self.meu_endereco = None
self.tabela = None
def __raw_recv(self, datagrama):
dscp, ecn, identification, flags, frag_offset, ttl, proto, \
src_addr, dst_addr, payload = read_ipv4_header(datagrama)
if dst_addr == self.meu_endereco:
# atua como host
if proto == IPPROTO_TCP and self.callback:
self.callback(src_addr, dst_addr, payload)
else:
# atua como roteador
ttl = ttl - 1
next_hop = self._next_hop(dst_addr)
if ttl > 0:
header = make_ipv4_header(len(payload), src_addr, dst_addr, dscp, ecn,
identification, flags, frag_offset, ttl, proto, verify_checksum=True)
datagrama = header + payload
self.enlace.enviar(datagrama, next_hop)
else:
next_hop = self._next_hop(src_addr)
icmp = make_icmp(datagrama)
new_header = make_ipv4_header(len(icmp), self.meu_endereco, src_addr, dscp, ecn,
identification, flags, frag_offset, randint(100,255), IPPROTO_ICMP, verify_checksum=True)
self.enlace.enviar(new_header+icmp, next_hop)
def _next_hop(self, dest_addr):
# TODO: Use a tabela de encaminhamento para determinar o próximo salto
# (next_hop) a partir do endereço de destino do datagrama (dest_addr).
# Retorne o next_hop para o dest_addr fornecido.
dest_addr = ip_address(dest_addr)
for item in self.tabela:
network = item[0]
if dest_addr in network:
return str(item[1])
return None
def definir_endereco_host(self, meu_endereco):
"""
Define qual o endereço IPv4 (string no formato x.y.z.w) deste host.
Se recebermos datagramas destinados a outros endereços em vez desse,
atuaremos como roteador em vez de atuar como host.
"""
self.meu_endereco = meu_endereco
def definir_tabela_encaminhamento(self, tabela):
"""
Define a tabela de encaminhamento no formato
[(cidr0, next_hop0), (cidr1, next_hop1), ...]
Onde os CIDR são fornecidos no formato 'x.y.z.w/n', e os
next_hop são fornecidos no formato 'x.y.z.w'.
"""
# AQUI A MÁGICA!!!
self.tabela = [(ip_network(item[0]), ip_address(item[1]))
for item in tabela]
self.tabela.sort(key=lambda tup: tup[0].prefixlen)
self.tabela.reverse()
def registrar_recebedor(self, callback):
"""
Registra uma função para ser chamada quando dados vierem da camada de rede
"""
self.callback = callback
def enviar(self, segmento, dest_addr):
"""
Envia segmento para dest_addr, onde dest_addr é um endereço IPv4
(string no formato x.y.z.w).
"""
next_hop = self._next_hop(dest_addr)
header = make_ipv4_header(
len(segmento), self.meu_endereco, dest_addr, verify_checksum=True)
self.enlace.enviar(header+segmento, next_hop)
| 36.963303 | 131 | 0.610325 |
d60ce2f1f3161e3b514fd11f5a8f3593864a1864 | 908 | py | Python | Leetcode_palindrome.py | gouthi007/Problems-Solution | 281023be2025bfe865d26b3b7dc64c92d148a5cc | [
"MIT"
] | null | null | null | Leetcode_palindrome.py | gouthi007/Problems-Solution | 281023be2025bfe865d26b3b7dc64c92d148a5cc | [
"MIT"
] | null | null | null | Leetcode_palindrome.py | gouthi007/Problems-Solution | 281023be2025bfe865d26b3b7dc64c92d148a5cc | [
"MIT"
] | null | null | null | """
Determine whether an integer is a palindrome. An integer is a palindrome when it reads the same backward as forward.
Example 1:
Input: 121
Output: true
Example 2:
Input: -121
Output: false
Explanation: From left to right, it reads -121. From right to left, it becomes 121-. Therefore it is not a palindrome.
Example 3:
Input: 10
Output: false
Explanation: Reads 01 from right to left. Therefore it is not a palindrome.
"""
class Solution:
def isPalindrome(self, x):
"""
:type x: int
:rtype: bool
"""
#print(id(x))
x = str(x)
#print(id(x))
temp = str(x)
#rint(id(temp))
temp = temp[::-1]
#print(id(temp))
if x.lstrip() == temp.lstrip():
return (True)
else:
return (False)
solution = Solution()
print(solution.isPalindrome(12321)) | 23.282051 | 119 | 0.575991 |
6f0160c082d00356898a61a7bc625c846aa32384 | 14,777 | py | Python | testtrail/examples/util.py | hongzhangMu/testrun | 39b573c26b24733383d840c6d89a6b22e758ad5d | [
"MIT"
] | null | null | null | testtrail/examples/util.py | hongzhangMu/testrun | 39b573c26b24733383d840c6d89a6b22e758ad5d | [
"MIT"
] | null | null | null | testtrail/examples/util.py | hongzhangMu/testrun | 39b573c26b24733383d840c6d89a6b22e758ad5d | [
"MIT"
] | null | null | null | #-*-coding:utf-8-*-
import json
from flask import make_response
import datetime,time
from math import sin, asin, cos, radians, fabs, sqrt
from testtrail.examples.allroadstime import *
from testtrail.models.trail import Trail
from testtrail.models.test_roads_name import TestRoadsName
from testtrail.models.roadname import Roadname
import numpy as np
def built_response(code, msg, data):
"""
根据code，msg，data构造合适的返回数据
:param code: 状态码
:param msg: 消息
:param data: 数据
:return: 构造好的数据，可以直接返回
"""
res = dict(code=code, msg=msg, data=data)
rsp = make_response(json.dumps(res))
rsp.headers['Access-Control-Allow-Origin'] = '*'
rsp.headers['Access-Control-Allow-Headers'] ='Content-Type, Content-Length, Authorization, Accept, X-Requested-With , yourHeaderFeild'
rsp.headers['Access-Control-Allow-Methods'] ='PUT,POST,GET,DELETE,OPTIONS'
rsp.headers['Content-Type'] = 'application/json;charset=utf-8'
return rsp
def built_resp(code, msg, data,nowspeed,speed,stopcishu,stoptime):
"""
根据code，msg，data构造合适的返回数据
:param code: 状态码
:param msg: 消息
:param data: 数据
:return: 构造好的数据，可以直接返回
"""
res = dict(code=code, msg=msg, data=data,nowspeed=nowspeed,speed=speed,stopcishu=stopcishu,stoptime=stoptime)
rsp = make_response(json.dumps(res))
rsp.headers['Access-Control-Allow-Origin'] = '*'
rsp.headers['Access-Control-Allow-Headers'] ='Content-Type, Content-Length, Authorization, Accept, X-Requested-With , yourHeaderFeild'
rsp.headers['Access-Control-Allow-Methods'] ='PUT,POST,GET,DELETE,OPTIONS'
rsp.headers['Content-Type'] = 'application/json;charset=utf-8'
return rsp
# 分割字符
def str2list(str):
if str == '':
return []
else:
return str.split(',')
def str2intList(str):
if str == '':
return []
else:
return [int(each) for each in str.split(',')]
def time2str(strtime):
year = datetime.datetime.now().year
mon = datetime.datetime.now().month
day = datetime.datetime.now().day
tss1 = str(year)+"-"+str(mon)+"-"+str(day)+" "+strtime
timeArray = time.strptime(tss1, "%Y-%m-%d %H:%M:%S")
timeStamp = int(time.mktime(timeArray))
print(timeStamp)
return timeStamp
def hav(theta):
s = sin(theta / 2)
return s * s
def get_distance_hav(lat0, lng0, lat1, lng1):
try:
EARTH_RADIUS = 6371
distance = 0
"用haversine公式计算球面两点间的距离。"
# 经纬度转换成弧度
lat0 = float(lat0)
lat1 = float(lat1)
lng0 = float(lng0)
lng1 = float(lng1)
lat0 = radians(lat0)
lat1 = radians(lat1)
lng0 = radians(lng0)
lng1 = radians(lng1)
dlng = fabs(lng0 - lng1)
dlat = fabs(lat0 - lat1)
h = hav(dlat) + cos(lat0) * cos(lat1) * hav(dlng)
distance = int(2 * EARTH_RADIUS * asin(sqrt(h))*3600)
if distance>700:
distance = 0
print('aaaa---11',distance)
except:
print('except----1')
distance =0
return distance
def pre_processroads(inttime,start_time,greentime,yellowtime,redtime,distance,roadname,index):
"""
:param inttime: 当前时刻事件time.time
:param start_time: 绿灯开始时间
:param greentime: 绿灯间隔时间
:param yellowtime: 黄灯间隔时间
:param redtime: 红灯间隔时间
:param roadname:路口名字
:return: x轴数据和visualmap数据
"""
# inttime = int(time.time())
# final_lists = []
# start_time = 1587605400000
# miletime_now = inttime * 1000
# greentime = 109
# yellowtime = 4
# redtime = 2
miletime_now = inttime * 1000
allroadtimes, flagleftcolor = concattimes(miletime_now, start_time, greentime, yellowtime, redtime)
tendata = ten_minsdata(inttime,400)
fin_list = []
count = 0
aaa = []
aaa.append(0)
# print('aa1111111time-----------',allroadtimes)
for i in tendata:
if i in allroadtimes:
# print('ok')
aaa.append(count)
fin_list.append([i, distance])
else:
fin_list.append([i, ''])
count += 1
fin_list[0][1] = distance
fin_list[len(fin_list) - 1][1] = distance
serices = []
print('-=-=-=-=-=-111111----',aaa)
for i in range(0, len(aaa) - 3, 3):
print('-000--------',i,aaa[i])
if flagleftcolor == 'green':
serices.append(dict(gt=aaa[i], lte=aaa[i + 1], color='green'))
serices.append(dict(gt=aaa[i + 1], lte=aaa[i + 2], color='yellow'))
serices.append(dict(gt=aaa[i + 2], lte=aaa[i + 3], color='red'))
elif flagleftcolor == 'yellow':
serices.append(dict(gt=aaa[i], lte=aaa[i + 1], color='yellow'))
serices.append(dict(gt=aaa[i + 1], lte=aaa[i + 2], color='red'))
serices.append(dict(gt=aaa[i + 2], lte=aaa[i + 3], color='green'))
else:
serices.append(dict(gt=aaa[i], lte=aaa[i + 1], color='red'))
serices.append(dict(gt=aaa[i + 1], lte=aaa[i + 2], color='green'))
serices.append(dict(gt=aaa[i + 2], lte=aaa[i + 3], color='yellow'))
if len(aaa) % 3 == 1:
serices.append(dict(gt=aaa[len(aaa) - 1], lte=len(fin_list), color=flagleftcolor))
elif len(aaa) % 3 == 2:
serices.append(dict(gt=aaa[len(aaa) - 2], lte=aaa[len(aaa) - 1], color=flagleftcolor))
serices.append(dict(gt=aaa[len(aaa) - 1], lte=len(fin_list), color=nextcolor(flagleftcolor)))
else:
serices.append(dict(gt=aaa[len(aaa) - 3], lte=aaa[len(aaa) - 2], color=flagleftcolor))
serices.append(dict(gt=aaa[len(aaa) - 2], lte=aaa[len(aaa) - 1], color=nextcolor(flagleftcolor)))
serices.append(dict(gt=aaa[len(aaa) - 1], lte=len(fin_list), color=nextnextcolor(flagleftcolor)))
makeseriesitems = makeseriesdict(roadname,fin_list)
makevisualMapitems = makevisualMap(index,serices)
return makeseriesitems,makevisualMapitems
def makeseriesdict(name,data):
tmp = {
"name": name,
"type": 'line',
"smooth": "true",
"symbolSize": 5,
"connectNulls": 'true',
"data":data
}
return tmp
def makevisualMap(seriesIndex,data):
tmp = {
"hoverLink":"false",
"show": False,
"showSymbol": "false",
"dimension": 0,
"seriesIndex":seriesIndex,
"pieces": data
}
return tmp
#计算下时刻的红绿灯情况
def nextcolor(flagleftcolor):
nextcolor ='green'
if flagleftcolor == 'green':
nextcolor = 'yellow'
elif flagleftcolor == 'yellow':
nextcolor = 'red'
else:
nextcolor = 'green'
return nextcolor
#计算下下时刻的红绿灯情况
def nextnextcolor(flagleftcolor):
nextcolor ='green'
if flagleftcolor == 'green':
nextcolor = 'red'
elif flagleftcolor == 'yellow':
nextcolor = 'green'
else:
nextcolor = 'yellow'
return nextcolor
#单次平均时间
# processing
def per_processing_speed(la0,la1,long1,long2,time1,time2):
try:
distance_tmp = get_distance_hav_dis(la0,long1,la1,long2)
left_time = int(time2-time1)
# left_time = getcalc_time(time1,time2)
ave_speed = int(distance_tmp/left_time)
except:
ave_speed = 0
return ave_speed
#获取当前场景初始点
def getscenesPoint(type):
points =[]
try:
first_data = TestRoadsName.query.filter(type==TestRoadsName.name).first()
type_roadname = first_data.type
#根据type寻找当前路段
data_filter = Roadname.query.filter(type_roadname==Roadname.type).all()
for i in data_filter:
if i.distance==0:
points=[i.latitude,i.longitude]
break
print('========217===',points)
except:
points = [40.011467, 116.406784]
print('points----------',points)
return points
def get_distance_hav_dis(lat0, lng0, lat1, lng1):
try:
EARTH_RADIUS = 6371
distance = 0
"用haversine公式计算球面两点间的距离。"
# 经纬度转换成弧度
lat0 = float(lat0)
lat1 = float(lat1)
lng0 = float(lng0)
lng1 = float(lng1)
lat0 = radians(lat0)
lat1 = radians(lat1)
lng0 = radians(lng0)
lng1 = radians(lng1)
dlng = fabs(lng0 - lng1)
dlat = fabs(lat0 - lat1)
h = hav(dlat) + cos(lat0) * cos(lat1) * hav(dlng)
distance = int(2 * EARTH_RADIUS * asin(sqrt(h))*1000)
print('a-------aaa---11',distance)
except:
print('except----1')
distance =0
return distance
#计算平均速度
def aveDisSpeed(distance,times):
try:
allroaddis_first = Trail.query.filter().order_by('id').limit(2)
print('new--new1--------',allroaddis_first[0].latitude)
print('new--new222--------',allroaddis_first[1].latitude)
lat1 = allroaddis_first[0].latitude
lat2 = allroaddis_first[1].latitude
long1 = allroaddis_first[0].longitude
long2 = allroaddis_first[1].longitude
print('====end=====',long1,long2,lat2,lat1)
distance = get_distance_hav_dis(lat1,long1,lat2,long2)
print('start---------')
speed = int(float(distance)*3.6)
print('speed--------',speed)
except:
speed = 0
return int(speed)
#获取当前时刻速度
def getallpoint_distance(imei):
try:
count_data = Trail.query.filter(Trail.imei == imei).all()
tmp_len = len(count_data)
time1 = count_data[0].date_time
time2 = count_data[tmp_len - 1].date_time
tmp_dis = 0
for i in range(0, len(count_data) - 1):
sp = get_distance_hav(count_data[i].latitude, count_data[i].longitude, count_data[i + 1].latitude,
count_data[i + 1].longitude)
print ('sp----------', sp)
tmp_dis += sp
except:
tmp_dis = 0
return tmp_dis
#获取当前时刻产生的数据
def getspeed_data(imei):
count_data = Trail.query.filter(Trail.imei ==imei).all()
tmp_len = len(count_data)
time1 = count_data[0].date_time
time2 = count_data[tmp_len - 1].date_time
tmp_speed =0
for i in range(0,len(count_data)-1):
sp = get_distance_hav(count_data[i].latitude,count_data[i].longitude,count_data[i+1].latitude,count_data[i+1].longitude)
print ('sp----------',sp)
tmp_speed += sp
try:
final_speed = tmp_speed/(len(count_data)-1)
except:
final_speed = 0
return final_speed
#获取当前路段的运行情况，剔除少于180秒的情况
def getSomeroadCishu(roadname):
num = Trail.query.filter(Trail.type==roadname).distinct().values("imei")
num_list = []
for i in num:
count_times = Trail.query.filter(Trail.imei==i.imei).all()
print(type(count_times))
tmp_len = len(count_times)
if tmp_len>120:
cishu,time_stop = computer_cishu_time(count_times)
la0 = count_times[0].latitude
la1 = count_times[tmp_len-1].latitude
long1 = count_times[0].longitude
long2 = count_times[tmp_len-1].longitude
time1 = count_times[0].date_time
time2 = count_times[tmp_len-1].date_time
ave_speed = processing_time(la0,la1,long1,long2,time1,time2)
if ave_speed<120 and ave_speed>1:
num_list.append([ave_speed,cishu,time_stop])
print(num_list)
a = np.array(num_list)
bb = np.mean(a,axis=0)
print(int(bb[0]),int(bb[1]),int(bb[2]))
return int(bb[0]),int(bb[1]),int(bb[2]),len(num_list[0])
# processing
def processing_time(la0,la1,long1,long2,time1,time2):
distance_tmp = get_distance_hav_dis(la0,long1,la1,long2)
left_time = getcalc_time(time1,time2)
ave_speed = distance_tmp/left_time
return ave_speed
#时间差
def getcalc_time(aaa,bbb):
aaa = aaa
bbb = bbb
# dd = datetime.datetime.strptime(aaa, "%Y-%m-%d %H:%M:%S")
dd = aaa
t = dd.timetuple()
timeStamp1 = int(time.mktime(t))
dd1 = bbb
t = dd1.timetuple()
timeStamp2 = int(time.mktime(t))
time_cishu = timeStamp2 - timeStamp1
return time_cishu
#计算停车次数和时间
def computer_cishu_time(items):
sequence = []
for i in items:
sequence.append(i.latitude+i.longitude)
counts = {}
for x in sequence:
if x in counts:
counts[x] += 1
else:
counts[x] = 1
tmp = counts
counts = 0
stoptime = 0
for i in tmp:
#停留3秒以上算停车
if tmp[i] > 5:
counts += 1
stoptime += tmp[i] - 1
return counts,int(stoptime)
def real_trackLength(imei):
all_trail = Trail.query.filter(Trail.imei == imei).all()
all_distance_real = 0
first_point = []
end_point = []
print (type(all_trail),len(all_trail))
tmp_all_trail = []
for i in range(0, len(all_trail), 1):
print (all_trail[len(all_trail)-1].longitude)
if all_trail[i].latitude==all_trail[len(all_trail)-1].latitude and all_trail[i].longitude==all_trail[len(all_trail)-1].longitude:
continue
else:
tmp_all_trail.append(all_trail[i])
print ('----',len(all_trail),tmp_all_trail)
all_trail = tmp_all_trail
for i in range(0,len(all_trail),1):
print(all_trail[i].imei)
try:
if i==0:
first_point = [all_trail[i].latitude,all_trail[i].longitude]
distance =get_distance_hav_dis(all_trail[i].latitude,all_trail[i].longitude,all_trail[i+1].latitude,all_trail[i+1].longitude)
dat_time = getcalc_time(all_trail[i].date_time,all_trail[i+1].date_time)
# print ('distance-----------',distance)
real_per_distance = per_track_distance(distance,dat_time)
# print ('--------',real_per_distance)
all_distance_real +=real_per_distance
end_point = [all_trail[i].latitude,all_trail[i].longitude]
except:
continue
dream_distance = get_distance_hav_dis(first_point[0],first_point[1],end_point[0],end_point[1])
return all_distance_real,dream_distance
def per_track_distance(distance,dis_time):
dis = ((dis_time*11.11)*(dis_time*11.11) +distance*distance) **0.5
return dis
def rate_trackLength(imei):
try:
real_track_length ,think_length= real_trackLength(imei=imei)
think_length = think_length*(2**0.5)
print (real_track_length,think_length)
rate_real = real_track_length/think_length
final_rate_real = round(rate_real,2)
return final_rate_real
except:
return 0
| 35.016588 | 139 | 0.594708 |
7ead84f0155eb572ba2eaca1e4d1b676764cc320 | 309,753 | py | Python | python/phonenumbers/carrierdata/data0.py | CrHD/python-phonenumbers | e30be8952b4ad9d92902c27cafd7947b93225ce4 | [
"Apache-2.0"
] | null | null | null | python/phonenumbers/carrierdata/data0.py | CrHD/python-phonenumbers | e30be8952b4ad9d92902c27cafd7947b93225ce4 | [
"Apache-2.0"
] | null | null | null | python/phonenumbers/carrierdata/data0.py | CrHD/python-phonenumbers | e30be8952b4ad9d92902c27cafd7947b93225ce4 | [
"Apache-2.0"
] | 1 | 2020-09-08T14:45:34.000Z | 2020-09-08T14:45:34.000Z | """Per-prefix data, mapping each prefix to a dict of locale:name.
Auto-generated file, do not edit by hand.
"""
from ..util import u
# Copyright (C) 2011-2018 The Libphonenumber 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.
data = {
'554198474':{'en': 'Brasil Telecom GSM'},
'554198475':{'en': 'Brasil Telecom GSM'},
'551698157':{'en': 'TIM'},
'554198477':{'en': 'Brasil Telecom GSM'},
'554198471':{'en': 'Brasil Telecom GSM'},
'554198472':{'en': 'Brasil Telecom GSM'},
'554198473':{'en': 'Brasil Telecom GSM'},
'554198478':{'en': 'Brasil Telecom GSM'},
'554198476':{'en': 'Brasil Telecom GSM'},
'551698156':{'en': 'TIM'},
'551698155':{'en': 'TIM'},
'551698154':{'en': 'TIM'},
'551599186':{'en': 'Claro BR'},
'551599187':{'en': 'Claro BR'},
'551599184':{'en': 'Claro BR'},
'551599185':{'en': 'Claro BR'},
'551599182':{'en': 'Claro BR'},
'551599183':{'en': 'Claro BR'},
'25288':{'en': 'Somali Networks'},
'551599181':{'en': 'Claro BR'},
'25280':{'en': 'Somali Networks'},
'375294':{'be': u('\u0411\u0435\u043b\u0421\u0435\u043b'), 'en': 'Belcel', 'ru': u('\u0411\u0435\u043b\u0421\u0435\u043b')},
'551498810':{'en': 'Oi'},
'1787589':{'en': 'CENTENNIAL'},
'1787588':{'en': 'CENTENNIAL'},
'551498811':{'en': 'Oi'},
'459314':{'en': 'SimService'},
'459315':{'en': 'SimService'},
'1787580':{'en': 'CENTENNIAL'},
'459310':{'en': 'Justfone'},
'459311':{'en': 'MobiWeb Limited'},
'1787585':{'en': 'CENTENNIAL'},
'459313':{'en': 'SimService'},
'44798':{'en': 'EE'},
'44790':{'en': 'EE'},
'44793':{'en': 'O2'},
'44792':{'en': 'O2'},
'44795':{'en': 'EE'},
'44794':{'en': 'EE'},
'44796':{'en': 'Orange'},
'336051':{'en': 'SFR'},
'336050':{'en': 'SFR'},
'336053':{'en': 'SFR'},
'336052':{'en': 'SFR'},
'22870':{'en': 'TOGOCEL'},
'336054':{'en': 'SFR'},
'553499183':{'en': 'TIM'},
'553499182':{'en': 'TIM'},
'553499181':{'en': 'TIM'},
'553499187':{'en': 'TIM'},
'22879':{'en': 'Moov'},
'553499185':{'en': 'TIM'},
'553499184':{'en': 'TIM'},
'551398136':{'en': 'TIM'},
'551398137':{'en': 'TIM'},
'551398134':{'en': 'TIM'},
'551398135':{'en': 'TIM'},
'551398132':{'en': 'TIM'},
'551398133':{'en': 'TIM'},
'551398131':{'en': 'TIM'},
'551398138':{'en': 'TIM'},
'551398139':{'en': 'TIM'},
'2348479':{'en': 'Starcomms'},
'2348478':{'en': 'Starcomms'},
'516596531':{'en': 'Claro'},
'516596530':{'en': 'Claro'},
'516596533':{'en': 'Claro'},
'516596532':{'en': 'Claro'},
'2348475':{'en': 'Starcomms'},
'2348474':{'en': 'Starcomms'},
'2348477':{'en': 'Starcomms'},
'2348476':{'en': 'Starcomms'},
'479257':{'en': 'NetCom'},
'1876442':{'en': 'Digicel'},
'554498412':{'en': 'Brasil Telecom GSM'},
'553199308':{'en': 'TIM'},
'38640':{'en': 'A1'},
'38641':{'en': 'Telekom Slovenije'},
'38643':{'en': 'Telekom Slovenije'},
'554898415':{'en': 'Brasil Telecom GSM'},
'1242457':{'en': 'BaTelCo'},
'554898417':{'en': 'Brasil Telecom GSM'},
'2347027':{'en': 'Multilinks'},
'554898411':{'en': 'Brasil Telecom GSM'},
'38649':{'en': 'Telekom Slovenije'},
'554898413':{'en': 'Brasil Telecom GSM'},
'554898412':{'en': 'Brasil Telecom GSM'},
'2348783':{'en': 'Starcomms'},
'2348782':{'en': 'Starcomms'},
'2348787':{'en': 'Starcomms'},
'2348786':{'en': 'Starcomms'},
'2348785':{'en': 'Starcomms'},
'2348784':{'en': 'Starcomms'},
'2348789':{'en': 'Starcomms'},
'2348788':{'en': 'Starcomms'},
'551798138':{'en': 'TIM'},
'551798139':{'en': 'TIM'},
'1242456':{'en': 'BaTelCo'},
'551798132':{'en': 'TIM'},
'551798133':{'en': 'TIM'},
'551798131':{'en': 'TIM'},
'551798136':{'en': 'TIM'},
'551798137':{'en': 'TIM'},
'551798134':{'en': 'TIM'},
'551798135':{'en': 'TIM'},
'5511988':{'en': 'Claro BR'},
'5511989':{'en': 'Claro BR'},
'5511982':{'en': 'TIM'},
'5511983':{'en': 'TIM'},
'5511981':{'en': 'TIM'},
'5511986':{'en': 'TIM'},
'5511987':{'en': 'TIM'},
'5511984':{'en': 'TIM'},
'5511985':{'en': 'TIM'},
'29769':{'en': 'SETAR'},
'29764':{'en': 'Digicel'},
'29766':{'en': 'SETAR'},
'29763':{'en': 'Digicel'},
'554799909':{'en': 'TIM'},
'552799231':{'en': 'Claro BR'},
'554799905':{'en': 'TIM'},
'554799904':{'en': 'TIM'},
'554799907':{'en': 'TIM'},
'554799906':{'en': 'TIM'},
'554799901':{'en': 'TIM'},
'554799903':{'en': 'TIM'},
'554799902':{'en': 'TIM'},
'27614':{'en': 'Telkom Mobile'},
'551598808':{'en': 'Oi'},
'551598809':{'en': 'Oi'},
'551498164':{'en': 'TIM'},
'551498165':{'en': 'TIM'},
'551498166':{'en': 'TIM'},
'551598804':{'en': 'Oi'},
'551498161':{'en': 'TIM'},
'551498162':{'en': 'TIM'},
'551498163':{'en': 'TIM'},
'554498418':{'en': 'Brasil Telecom GSM'},
'552799233':{'en': 'Claro BR'},
'554799638':{'en': 'TIM'},
'554799637':{'en': 'TIM'},
'554799636':{'en': 'TIM'},
'554799635':{'en': 'TIM'},
'553199239':{'en': 'TIM'},
'554799633':{'en': 'TIM'},
'554799632':{'en': 'TIM'},
'554799631':{'en': 'TIM'},
'553199691':{'en': 'Telemig Celular'},
'553199692':{'en': 'Telemig Celular'},
'553199693':{'en': 'Telemig Celular'},
'553199694':{'en': 'Telemig Celular'},
'553199695':{'en': 'Telemig Celular'},
'553199696':{'en': 'Telemig Celular'},
'553199697':{'en': 'Telemig Celular'},
'553199698':{'en': 'Telemig Celular'},
'553199699':{'en': 'Telemig Celular'},
'2347782':{'en': 'Starcomms'},
'2347783':{'en': 'Starcomms'},
'22678':{'en': 'Telecel Faso'},
'22679':{'en': 'Telecel Faso'},
'22676':{'en': 'Airtel'},
'22677':{'en': 'Airtel'},
'22674':{'en': 'Airtel'},
'22675':{'en': 'Airtel'},
'22672':{'en': 'Telmob'},
'22673':{'en': 'Telmob'},
'22670':{'en': 'Telmob'},
'22671':{'en': 'Telmob'},
'553199346':{'en': 'TIM'},
'553199347':{'en': 'TIM'},
'1787619':{'en': 'SunCom Wireless Puerto Rico'},
'553199345':{'en': 'TIM'},
'553199342':{'en': 'TIM'},
'50672':{'en': 'Claro'},
'50671':{'en': 'Claro'},
'553199341':{'en': 'TIM'},
'1787613':{'en': 'Claro'},
'1787612':{'en': 'Claro'},
'1787617':{'en': 'Claro'},
'1787616':{'en': 'Claro'},
'1787615':{'en': 'Claro'},
'1787614':{'en': 'Claro'},
'552799237':{'en': 'Claro BR'},
'551298823':{'en': 'Oi'},
'551298822':{'en': 'Oi'},
'551298821':{'en': 'Oi'},
'551298820':{'en': 'Oi'},
'551899714':{'en': 'Vivo'},
'551899715':{'en': 'Vivo'},
'551899716':{'en': 'Vivo'},
'551899717':{'en': 'Vivo'},
'551899718':{'en': 'Vivo'},
'551899719':{'en': 'Vivo'},
'553199203':{'en': 'TIM'},
'553199202':{'en': 'TIM'},
'551598118':{'en': 'TIM'},
'551598119':{'en': 'TIM'},
'553199207':{'en': 'TIM'},
'553199206':{'en': 'TIM'},
'553199205':{'en': 'TIM'},
'553199204':{'en': 'TIM'},
'551598112':{'en': 'TIM'},
'551499831':{'en': 'Vivo'},
'553199209':{'en': 'TIM'},
'551598111':{'en': 'TIM'},
'551598116':{'en': 'TIM'},
'551598117':{'en': 'TIM'},
'551598114':{'en': 'TIM'},
'551598115':{'en': 'TIM'},
'354644':{'en': 'Nova'},
'354646':{'en': 'IMC'},
'354647':{'en': 'IMC'},
'354640':{'en': u('\u00d6ryggisfjarskipti')},
'354641':{'en': u('\u00d6ryggisfjarskipti')},
'354649':{'en': 'Vodafone'},
'2626920':{'en': 'Orange'},
'2626922':{'en': 'Orange'},
'2626923':{'en': 'Orange'},
'3747':{'en': 'VivaCell-MTS', 'ru': u('\u0412\u0438\u0432\u0430\u0421\u0435\u043b\u043b-\u041c\u0422\u0421')},
'3745':{'en': 'Ucom', 'ru': u('\u042e\u043a\u043e\u043c')},
'551197058':{'en': 'Claro BR'},
'1787260':{'en': 'Claro'},
'551197059':{'en': 'Claro BR'},
'554698826':{'en': 'Claro BR'},
'43688':{'en': 'Orange AT'},
'55469910':{'en': 'Vivo'},
'551899199':{'en': 'Claro BR'},
'49172':{'en': 'Vodafone'},
'49173':{'en': 'Vodafone'},
'49170':{'en': 'T-Mobile'},
'49171':{'en': 'T-Mobile'},
'49176':{'en': 'O2'},
'49177':{'en': 'Eplus'},
'49174':{'en': 'Vodafone'},
'49175':{'en': 'T-Mobile'},
'49178':{'en': 'Eplus'},
'49179':{'en': 'O2'},
'4476006':{'en': '24 Seven'},
'4476007':{'en': 'Relax'},
'4476002':{'en': 'PageOne'},
'4476000':{'en': 'Mediatel'},
'50370737':{'en': 'Claro'},
'50370736':{'en': 'Claro'},
'50370735':{'en': 'Claro'},
'50370734':{'en': 'Digicel'},
'50370733':{'en': 'Digicel'},
'50370732':{'en': 'Digicel'},
'50370731':{'en': 'Digicel'},
'50370730':{'en': 'Digicel'},
'50370739':{'en': 'Claro'},
'50370738':{'en': 'Claro'},
'551799728':{'en': 'Vivo'},
'551799729':{'en': 'Vivo'},
'551799721':{'en': 'Vivo'},
'551799722':{'en': 'Vivo'},
'551799723':{'en': 'Vivo'},
'551799724':{'en': 'Vivo'},
'551799725':{'en': 'Vivo'},
'551799726':{'en': 'Vivo'},
'551799727':{'en': 'Vivo'},
'4236639':{'en': 'Emnify'},
'552899915':{'en': 'Vivo'},
'32460':{'en': 'Proximus'},
'552899917':{'en': 'Vivo'},
'552899916':{'en': 'Vivo'},
'552899919':{'en': 'Vivo'},
'552899918':{'en': 'Vivo'},
'1345649':{'en': 'Digicel'},
'551499171':{'en': 'Claro BR'},
'551499172':{'en': 'Claro BR'},
'551499173':{'en': 'Claro BR'},
'487209':{'en': 'CenterNet'},
'551499175':{'en': 'Claro BR'},
'551499176':{'en': 'Claro BR'},
'551499177':{'en': 'Claro BR'},
'487205':{'en': 'CenterNet'},
'487204':{'en': 'CenterNet'},
'487207':{'en': 'CenterNet'},
'487206':{'en': 'CenterNet'},
'487201':{'en': 'CenterNet'},
'487200':{'en': 'CenterNet'},
'487203':{'en': 'CenterNet'},
'487202':{'en': 'CenterNet'},
'554599972':{'en': 'TIM'},
'553899907':{'en': 'Telemig Celular'},
'554199221':{'en': 'Vivo'},
'4531312':{'en': 'MI Carrier Services'},
'447380':{'en': 'Three'},
'447381':{'en': 'O2'},
'447382':{'en': 'O2'},
'447383':{'en': 'Three'},
'447384':{'en': 'Vodafone'},
'447385':{'en': 'Vodafone'},
'447386':{'en': 'Vodafone'},
'447387':{'en': 'Vodafone'},
'447388':{'en': 'Vodafone'},
'447437':{'en': 'Vodafone'},
'447434':{'en': 'EE'},
'1671858':{'en': 'i CAN_GSM'},
'447432':{'en': 'EE'},
'3460224':{'en': 'Oceans'},
'447430':{'en': 'O2'},
'447431':{'en': 'O2'},
'1242565':{'en': 'BaTelCo'},
'3460225':{'en': 'VozTelecom'},
'554699978':{'en': 'TIM'},
'518298232':{'en': 'Claro'},
'518298231':{'en': 'Claro'},
'518298230':{'en': 'Claro'},
'554699973':{'en': 'TIM'},
'554699972':{'en': 'TIM'},
'554699971':{'en': 'TIM'},
'26269331':{'en': 'Only'},
'26269330':{'en': 'Only'},
'554199229':{'en': 'Vivo'},
'26269333':{'en': 'Orange'},
'26269332':{'en': 'Only'},
'553499801':{'en': 'Telemig Celular'},
'551898125':{'en': 'TIM'},
'4477008':{'en': 'Sure'},
'553499804':{'en': 'Telemig Celular'},
'553499805':{'en': 'Telemig Celular'},
'551898126':{'en': 'TIM'},
'3866570':{'en': 'Novatel'},
'23266':{'en': 'Onlime'},
'551898127':{'en': 'TIM'},
'551898128':{'en': 'TIM'},
'1939628':{'en': 'CENTENNIAL'},
'552299272':{'en': 'Claro BR'},
'552299273':{'en': 'Claro BR'},
'552299271':{'en': 'Claro BR'},
'552299276':{'en': 'Claro BR'},
'552299277':{'en': 'Claro BR'},
'552299274':{'en': 'Claro BR'},
'552299275':{'en': 'Claro BR'},
'552299278':{'en': 'Claro BR'},
'552299279':{'en': 'Claro BR'},
'55119692':{'en': 'Claro BR'},
'55119690':{'en': 'Vivo'},
'1284347':{'en': 'Digicel'},
'1284346':{'en': 'Digicel'},
'1284345':{'en': 'Digicel'},
'1284344':{'en': 'Digicel'},
'1284343':{'en': 'Digicel'},
'1284342':{'en': 'Digicel'},
'1284341':{'en': 'Digicel'},
'1284340':{'en': 'Digicel'},
'552799316':{'en': 'Claro BR'},
'551898122':{'en': 'TIM'},
'552799279':{'en': 'Claro BR'},
'552799278':{'en': 'Claro BR'},
'552799275':{'en': 'Claro BR'},
'552799274':{'en': 'Claro BR'},
'552799277':{'en': 'Claro BR'},
'552799276':{'en': 'Claro BR'},
'552799271':{'en': 'Claro BR'},
'552799273':{'en': 'Claro BR'},
'552799272':{'en': 'Claro BR'},
'55439910':{'en': 'Vivo'},
'554398850':{'en': 'Claro BR'},
'554299939':{'en': 'TIM'},
'554398852':{'en': 'Claro BR'},
'554299938':{'en': 'TIM'},
'346816':{'en': 'MasMovil'},
'346814':{'en': 'Movistar'},
'346815':{'en': 'Movistar'},
'346812':{'en': 'Movistar'},
'346813':{'en': 'Movistar'},
'346810':{'en': 'Movistar'},
'346811':{'en': 'Movistar'},
'4477001':{'en': 'Nationwide Telephone'},
'4477000':{'en': 'Cloud9'},
'423661':{'en': 'Dimoco'},
'423660':{'en': 'Telecom Liechtenstein'},
'55329996':{'en': 'Telemig Celular'},
'55329998':{'en': 'Telemig Celular'},
'554399116':{'en': 'Vivo'},
'2519':{'en': 'Ethio Telecom'},
'554399117':{'en': 'Vivo'},
'1767615':{'en': 'Digicel'},
'347124':{'en': 'Yoigo'},
'347127':{'en': 'Yoigo'},
'1767616':{'en': 'Digicel'},
'551398118':{'en': 'TIM'},
'551398119':{'en': 'TIM'},
'551398114':{'en': 'TIM'},
'5055':{'en': 'Claro'},
'5056':{'en': 'CooTel'},
'5057':{'en': 'Movistar'},
'551398111':{'en': 'TIM'},
'551398112':{'en': 'TIM'},
'551398113':{'en': 'TIM'},
'459190':{'en': 'Interactive digital media GmbH'},
'459191':{'en': 'Maxtel.dk'},
'1767613':{'en': 'Digicel'},
'5036313':{'en': 'Claro'},
'5036312':{'en': 'Claro'},
'5036311':{'en': 'Claro'},
'1767612':{'en': 'Digicel'},
'5036316':{'en': 'Claro'},
'5036315':{'en': 'Claro'},
'5036314':{'en': 'Claro'},
'2344880':{'en': 'Starcomms'},
'2344881':{'en': 'Starcomms'},
'2344882':{'en': 'Starcomms'},
'3584579':{'en': 'DNA'},
'3584578':{'en': 'DNA'},
'3584577':{'en': 'DNA'},
'3584576':{'en': 'DNA'},
'3584575':{'en': 'AMT'},
'3584574':{'en': 'DNA'},
'3584573':{'en': 'AMT'},
'3584571':{'en': 'Tismi'},
'3584570':{'en': 'AMT'},
'554898433':{'en': 'Brasil Telecom GSM'},
'554898432':{'en': 'Brasil Telecom GSM'},
'554898431':{'en': 'Brasil Telecom GSM'},
'554898436':{'en': 'Brasil Telecom GSM'},
'554898435':{'en': 'Brasil Telecom GSM'},
'554898434':{'en': 'Brasil Telecom GSM'},
'447784':{'en': 'O2'},
'551798111':{'en': 'TIM'},
'551798112':{'en': 'TIM'},
'551798113':{'en': 'TIM'},
'551798114':{'en': 'TIM'},
'459312':{'en': 'SimService'},
'551798116':{'en': 'TIM'},
'551798117':{'en': 'TIM'},
'551798118':{'en': 'TIM'},
'551798119':{'en': 'TIM'},
'5538989':{'en': 'Oi'},
'5538988':{'en': 'Oi'},
'50374':{'en': 'Digicel'},
'554398111':{'en': 'TIM'},
'553199901':{'en': 'Telemig Celular'},
'551698173':{'en': 'TIM'},
'50375':{'en': 'Tigo'},
'5538987':{'en': 'Oi'},
'5538986':{'en': 'Oi'},
'5538985':{'en': 'Oi'},
'2345685':{'en': 'Starcomms'},
'2345684':{'en': 'Starcomms'},
'2345687':{'en': 'Starcomms'},
'2345686':{'en': 'Starcomms'},
'553199905':{'en': 'Telemig Celular'},
'30690299':{'en': 'BWS'},
'553199907':{'en': 'Telemig Celular'},
'554799923':{'en': 'TIM'},
'212641':{'en': 'Maroc Telecom'},
'554799921':{'en': 'TIM'},
'554799927':{'en': 'TIM'},
'554799926':{'en': 'TIM'},
'554799925':{'en': 'TIM'},
'212640':{'en': 'Inwi'},
'554799929':{'en': 'TIM'},
'554799928':{'en': 'TIM'},
'212643':{'en': 'Maroc Telecom'},
'4474413':{'en': 'Stour Marine'},
'4474411':{'en': 'Andrews & Arnold'},
'4474410':{'en': 'Mediatel'},
'4474417':{'en': 'Synectiv'},
'4474416':{'en': 'Vodafone'},
'4474415':{'en': 'Synectiv'},
'4474414':{'en': 'Tismi'},
'212645':{'en': u('M\u00e9ditel')},
'4474419':{'en': 'Voxbone'},
'4474418':{'en': 'Core Telecom'},
'51849747':{'en': 'Claro'},
'51849742':{'en': 'Claro'},
'212647':{'en': 'Inwi'},
'455319':{'en': 'Telia'},
'5522985':{'en': 'Oi'},
'5522986':{'en': 'Oi'},
'5522987':{'en': 'Oi'},
'553499189':{'en': 'TIM'},
'554499173':{'en': 'Vivo'},
'553499188':{'en': 'TIM'},
'212648':{'en': 'Maroc Telecom'},
'554799655':{'en': 'TIM'},
'554799654':{'en': 'TIM'},
'554799657':{'en': 'TIM'},
'554799656':{'en': 'TIM'},
'554799651':{'en': 'TIM'},
'554598418':{'en': 'Brasil Telecom GSM'},
'554799652':{'en': 'TIM'},
'554598416':{'en': 'Brasil Telecom GSM'},
'554598417':{'en': 'Brasil Telecom GSM'},
'554598414':{'en': 'Brasil Telecom GSM'},
'554598415':{'en': 'Brasil Telecom GSM'},
'554598412':{'en': 'Brasil Telecom GSM'},
'554598413':{'en': 'Brasil Telecom GSM'},
'554598411':{'en': 'Brasil Telecom GSM'},
'554499172':{'en': 'Vivo'},
'553499186':{'en': 'TIM'},
'551899198':{'en': 'Claro BR'},
'22654':{'en': 'Orange'},
'22655':{'en': 'Airtel'},
'22656':{'en': 'Airtel'},
'22657':{'en': 'Orange'},
'22651':{'en': 'Telmob'},
'22652':{'en': 'Telmob'},
'552198371':{'en': 'TIM'},
'552198373':{'en': 'TIM'},
'551699975':{'en': 'Vivo'},
'22658':{'en': 'Telecel Faso'},
'552198374':{'en': 'TIM'},
'552198377':{'en': 'TIM'},
'552198376':{'en': 'TIM'},
'22389':{'en': 'Sotelma'},
'553199368':{'en': 'TIM'},
'553199369':{'en': 'TIM'},
'22382':{'en': 'Orange'},
'22383':{'en': 'Orange'},
'553199366':{'en': 'TIM'},
'553199367':{'en': 'TIM'},
'553199361':{'en': 'TIM'},
'553199362':{'en': 'TIM'},
'553199363':{'en': 'TIM'},
'551699609':{'en': 'Vivo'},
'503703':{'en': 'Claro'},
'187659':{'en': 'Digicel'},
'503701':{'en': 'Claro'},
'503700':{'en': 'Claro'},
'503706':{'en': 'Claro'},
'503705':{'en': 'Claro'},
'503704':{'en': 'Claro'},
'503709':{'en': 'Claro'},
'503708':{'en': 'Claro'},
'1242802':{'en': 'aliv'},
'1242803':{'en': 'aliv'},
'551899774':{'en': 'Vivo'},
'1242801':{'en': 'aliv'},
'1242806':{'en': 'aliv'},
'1242807':{'en': 'aliv'},
'1242804':{'en': 'aliv'},
'1242805':{'en': 'aliv'},
'1242808':{'en': 'aliv'},
'1242809':{'en': 'aliv'},
'551899778':{'en': 'Vivo'},
'551899779':{'en': 'Vivo'},
'551598131':{'en': 'TIM'},
'551598132':{'en': 'TIM'},
'551598133':{'en': 'TIM'},
'551598134':{'en': 'TIM'},
'551598135':{'en': 'TIM'},
'551598136':{'en': 'TIM'},
'551598138':{'en': 'TIM'},
'551598139':{'en': 'TIM'},
'370686':{'en': 'Omnitel'},
'370687':{'en': 'Omnitel'},
'370684':{'en': 'Tele 2'},
'370685':{'en': u('BIT\u0116')},
'370682':{'en': 'Omnitel'},
'370683':{'en': 'Tele 2'},
'370680':{'en': 'Omnitel'},
'370681':{'en': u('BIT\u0116')},
'507656':{'en': u('Telef\u00f3nica M\u00f3viles')},
'370688':{'en': 'Omnitel'},
'370689':{'en': u('BIT\u0116')},
'553499951':{'en': 'Telemig Celular'},
'553499952':{'en': 'Telemig Celular'},
'553499953':{'en': 'Telemig Celular'},
'553499954':{'en': 'Telemig Celular'},
'553499955':{'en': 'Telemig Celular'},
'553499956':{'en': 'Telemig Celular'},
'507658':{'en': u('Telef\u00f3nica M\u00f3viles')},
'553499958':{'en': 'Telemig Celular'},
'553499959':{'en': 'Telemig Celular'},
'553199212':{'en': 'TIM'},
'30688500':{'en': 'BWS'},
'554598822':{'en': 'Claro BR'},
'554198751':{'en': 'Claro BR'},
'554198750':{'en': 'Claro BR'},
'554198752':{'en': 'Claro BR'},
'55119577':{'en': 'Vivo'},
'553199213':{'en': 'TIM'},
'554598821':{'en': 'Claro BR'},
'55199986':{'en': 'Vivo'},
'55199987':{'en': 'Vivo'},
'55199984':{'en': 'Vivo'},
'55199985':{'en': 'Vivo'},
'55199982':{'en': 'Vivo'},
'55199983':{'en': 'Vivo'},
'55199980':{'en': 'Vivo'},
'55199981':{'en': 'Vivo'},
'55199988':{'en': 'Vivo'},
'553599188':{'en': 'TIM'},
'51829827':{'en': 'Claro'},
'25563':{'en': 'MTC'},
'25562':{'en': 'Viettel'},
'25567':{'en': 'tiGO'},
'25566':{'en': 'SMILE'},
'25565':{'en': 'tiGO'},
'25564':{'en': 'Cootel'},
'25569':{'en': 'Airtel'},
'25568':{'en': 'Airtel'},
'1939339':{'en': 'SunCom Wireless Puerto Rico'},
'1939334':{'en': 'Claro'},
'3465329':{'en': 'DIA'},
'55129881':{'en': 'Oi'},
'49151':{'en': 'T-Mobile'},
'4473683':{'en': 'Sky'},
'4473682':{'en': 'Sky'},
'4473680':{'en': 'Teleena'},
'50370719':{'en': 'Tigo'},
'50370715':{'en': 'Tigo'},
'50370714':{'en': 'Tigo'},
'50370717':{'en': 'Claro'},
'50370716':{'en': 'Movistar'},
'50370711':{'en': 'Movistar'},
'50370710':{'en': 'Claro'},
'50370713':{'en': 'Tigo'},
'50370712':{'en': 'Claro'},
'553799102':{'en': 'TIM'},
'554898419':{'en': 'Brasil Telecom GSM'},
'554898418':{'en': 'Brasil Telecom GSM'},
'554898414':{'en': 'Brasil Telecom GSM'},
'553299146':{'en': 'TIM'},
'37360':{'en': 'Orange'},
'554898416':{'en': 'Brasil Telecom GSM'},
'551799748':{'en': 'Vivo'},
'551799749':{'en': 'Vivo'},
'551799746':{'en': 'Vivo'},
'551799747':{'en': 'Vivo'},
'37368':{'en': 'Orange'},
'37369':{'en': 'Orange'},
'551799742':{'en': 'Vivo'},
'551799743':{'en': 'Vivo'},
'551799741':{'en': 'Vivo'},
'30695410':{'en': 'MI Carrier Services'},
'346016':{'en': 'Lcrcom'},
'346017':{'en': 'Vodafone'},
'346014':{'en': 'Vodafone'},
'346015':{'en': 'HITS'},
'346012':{'en': 'Vodafone'},
'346013':{'en': 'Vodafone'},
'346010':{'en': 'Vodafone'},
'346011':{'en': 'Vodafone'},
'554499162':{'en': 'Vivo'},
'554499163':{'en': 'Vivo'},
'554499161':{'en': 'Vivo'},
'554499166':{'en': 'Vivo'},
'554499167':{'en': 'Vivo'},
'554499164':{'en': 'Vivo'},
'554499165':{'en': 'Vivo'},
'554499168':{'en': 'Vivo'},
'554499169':{'en': 'Vivo'},
'552899935':{'en': 'Vivo'},
'552899939':{'en': 'Vivo'},
'552899938':{'en': 'Vivo'},
'551499116':{'en': 'Claro BR'},
'551499117':{'en': 'Claro BR'},
'551499114':{'en': 'Claro BR'},
'551499115':{'en': 'Claro BR'},
'551499112':{'en': 'Claro BR'},
'551499113':{'en': 'Claro BR'},
'551499111':{'en': 'Claro BR'},
'551999627':{'en': 'Vivo'},
'551499118':{'en': 'Claro BR'},
'551499119':{'en': 'Claro BR'},
'553898412':{'en': 'Claro BR'},
'553898413':{'en': 'Claro BR'},
'553898411':{'en': 'Claro BR'},
'553898416':{'en': 'Claro BR'},
'553898417':{'en': 'Claro BR'},
'553898414':{'en': 'Claro BR'},
'553898415':{'en': 'Claro BR'},
'553898418':{'en': 'Claro BR'},
'551999624':{'en': 'Vivo'},
'447419':{'en': 'Orange'},
'1671878':{'en': 'Choice Phone'},
'447410':{'en': 'Orange'},
'447411':{'en': 'Three'},
'447412':{'en': 'Three'},
'447413':{'en': 'Three'},
'447414':{'en': 'Three'},
'447415':{'en': 'EE'},
'447416':{'en': 'Orange'},
'554699915':{'en': 'TIM'},
'554699914':{'en': 'TIM'},
'554699917':{'en': 'TIM'},
'554699916':{'en': 'TIM'},
'554699911':{'en': 'TIM'},
'554699913':{'en': 'TIM'},
'554699912':{'en': 'TIM'},
'554699919':{'en': 'TIM'},
'554699918':{'en': 'TIM'},
'479650':{'en': 'Telenor'},
'456050':{'en': 'Telenor'},
'474625':{'en': 'Telenor'},
'474624':{'en': 'Telenor'},
'474627':{'en': 'Telenor'},
'474626':{'en': 'Telenor'},
'474621':{'en': 'Telenor'},
'474623':{'en': 'NetCom'},
'551499830':{'en': 'Vivo'},
'552198414':{'en': 'Oi'},
'552198415':{'en': 'Oi'},
'552198416':{'en': 'Oi'},
'552198417':{'en': 'Oi'},
'551799739':{'en': 'Vivo'},
'552198412':{'en': 'Oi'},
'552198413':{'en': 'Oi'},
'551499832':{'en': 'Vivo'},
'552198418':{'en': 'Oi'},
'1473424':{'en': 'Digicel Grenada'},
'554699126':{'en': 'Vivo'},
'3866555':{'en': 'Telekom Slovenije'},
'549349':{'en': 'Personal'},
'549348':{'en': 'Personal'},
'23244':{'en': 'Intergroup'},
'549340':{'en': 'Personal'},
'549343':{'en': 'Personal'},
'549342':{'en': 'Personal'},
'23240':{'en': 'Datatel/Cellcom'},
'549344':{'en': 'Personal'},
'549347':{'en': 'Personal'},
'549346':{'en': 'Personal'},
'5541999':{'en': 'TIM'},
'1284368':{'en': 'Digicel'},
'5541996':{'en': 'TIM'},
'551298181':{'en': 'TIM'},
'551298182':{'en': 'TIM'},
'55449910':{'en': 'Vivo'},
'552799253':{'en': 'Claro BR'},
'552799252':{'en': 'Claro BR'},
'552799251':{'en': 'Claro BR'},
'552799257':{'en': 'Claro BR'},
'552799256':{'en': 'Claro BR'},
'552799255':{'en': 'Claro BR'},
'552799254':{'en': 'Claro BR'},
'552799259':{'en': 'Claro BR'},
'552799258':{'en': 'Claro BR'},
'24391':{'en': 'Africell'},
'552198308':{'en': 'TIM'},
'552198309':{'en': 'TIM'},
'553199166':{'en': 'TIM'},
'553599132':{'en': 'TIM'},
'552198306':{'en': 'TIM'},
'45402':{'en': 'TDC'},
'45403':{'en': 'TDC'},
'45401':{'en': 'TDC'},
'45406':{'en': 'Telenor'},
'45407':{'en': 'Telenor'},
'45404':{'en': 'TDC'},
'45405':{'en': 'Telenor'},
'1787546':{'en': 'SunCom Wireless Puerto Rico'},
'45408':{'en': 'Telenor'},
'1787544':{'en': 'CENTENNIAL'},
'551599142':{'en': 'Claro BR'},
'551599143':{'en': 'Claro BR'},
'554399125':{'en': 'Vivo'},
'551599141':{'en': 'Claro BR'},
'551599146':{'en': 'Claro BR'},
'551599147':{'en': 'Claro BR'},
'551599144':{'en': 'Claro BR'},
'551599145':{'en': 'Claro BR'},
'551599148':{'en': 'Claro BR'},
'551599149':{'en': 'Claro BR'},
'2537':{'en': 'Evatis'},
'554399129':{'en': 'Vivo'},
'554399128':{'en': 'Vivo'},
'552798122':{'en': 'TIM'},
'552798123':{'en': 'TIM'},
'552798121':{'en': 'TIM'},
'552798126':{'en': 'TIM'},
'552798127':{'en': 'TIM'},
'552798124':{'en': 'TIM'},
'552798125':{'en': 'TIM'},
'552798128':{'en': 'TIM'},
'552798129':{'en': 'TIM'},
'554799933':{'en': 'TIM'},
'2348439':{'en': 'Starcomms'},
'2348438':{'en': 'Starcomms'},
'2348434':{'en': 'Starcomms'},
'2348437':{'en': 'Starcomms'},
'2348431':{'en': 'Starcomms'},
'479815':{'en': 'NetCom'},
'3584559':{'en': 'MI'},
'3584558':{'en': 'Suomen Virveverkko'},
'479749':{'en': 'Telenor'},
'479748':{'en': 'Telenor'},
'3584550':{'en': 'Suomen Virveverkko'},
'479747':{'en': 'Telenor'},
'479746':{'en': 'Telenor'},
'479217':{'en': 'NetCom'},
'479740':{'en': 'Telenor'},
'3584557':{'en': 'Compatel'},
'479742':{'en': 'Telenor'},
'48691':{'en': 'Plus'},
'48692':{'en': 'T-Mobile'},
'48693':{'en': 'Plus'},
'48694':{'en': 'T-Mobile'},
'48695':{'en': 'Plus'},
'48696':{'en': 'T-Mobile'},
'48697':{'en': 'Plus'},
'48698':{'en': 'T-Mobile'},
'551898137':{'en': 'TIM'},
'474190':{'en': 'NetCom'},
'551898136':{'en': 'TIM'},
'551499164':{'en': 'Claro BR'},
'30690100':{'en': 'MI Carrier Services'},
'44759':{'en': 'O2'},
'44754':{'en': 'O2'},
'44756':{'en': 'O2'},
'44751':{'en': 'O2'},
'29729':{'en': 'Digicel'},
'24398':{'en': 'Zain'},
'2413':{'en': 'Libertis'},
'4476600':{'en': 'Plus'},
'4476606':{'en': '24 Seven'},
'1264583':{'en': 'Digicel'},
'1264582':{'en': 'Digicel'},
'1264581':{'en': 'Digicel'},
'4476607':{'en': 'Premium O'},
'1264584':{'en': 'Digicel'},
'554199132':{'en': 'Vivo'},
'1345516':{'en': 'Digicel'},
'554199131':{'en': 'Vivo'},
'554199136':{'en': 'Vivo'},
'552298138':{'en': 'TIM'},
'554199134':{'en': 'Vivo'},
'1345517':{'en': 'Digicel'},
'554199138':{'en': 'Vivo'},
'552298139':{'en': 'TIM'},
'553199847':{'en': 'Telemig Celular'},
'552298136':{'en': 'TIM'},
'553199846':{'en': 'Telemig Celular'},
'552298137':{'en': 'TIM'},
'552298134':{'en': 'TIM'},
'552298135':{'en': 'TIM'},
'554599961':{'en': 'TIM'},
'552298132':{'en': 'TIM'},
'212619':{'en': u('M\u00e9ditel')},
'212617':{'en': u('M\u00e9ditel')},
'212614':{'en': u('M\u00e9ditel')},
'212612':{'en': u('M\u00e9ditel')},
'552198359':{'en': 'TIM'},
'552198358':{'en': 'TIM'},
'552198357':{'en': 'TIM'},
'552198356':{'en': 'TIM'},
'552198355':{'en': 'TIM'},
'552198354':{'en': 'TIM'},
'552198353':{'en': 'TIM'},
'552198352':{'en': 'TIM'},
'552198351':{'en': 'TIM'},
'553199848':{'en': 'Telemig Celular'},
'553199382':{'en': 'TIM'},
'553199383':{'en': 'TIM'},
'553199381':{'en': 'TIM'},
'553199386':{'en': 'TIM'},
'553199387':{'en': 'TIM'},
'553199384':{'en': 'TIM'},
'553199385':{'en': 'TIM'},
'553199388':{'en': 'TIM'},
'553199389':{'en': 'TIM'},
'551998215':{'en': 'TIM'},
'551998214':{'en': 'TIM'},
'551998217':{'en': 'TIM'},
'551998216':{'en': 'TIM'},
'551998211':{'en': 'TIM'},
'551998213':{'en': 'TIM'},
'551998212':{'en': 'TIM'},
'4479245':{'en': 'Cloud9'},
'551998219':{'en': 'TIM'},
'551998218':{'en': 'TIM'},
'551598805':{'en': 'Oi'},
'551598806':{'en': 'Oi'},
'551598807':{'en': 'Oi'},
'553499814':{'en': 'Telemig Celular'},
'553499936':{'en': 'Telemig Celular'},
'553499937':{'en': 'Telemig Celular'},
'553499934':{'en': 'Telemig Celular'},
'553499935':{'en': 'Telemig Celular'},
'553499932':{'en': 'Telemig Celular'},
'553499933':{'en': 'Telemig Celular'},
'553499931':{'en': 'Telemig Celular'},
'553499938':{'en': 'Telemig Celular'},
'553499939':{'en': 'Telemig Celular'},
'514494907':{'en': 'Claro'},
'514494906':{'en': 'Movistar'},
'514494905':{'en': 'Movistar'},
'514494904':{'en': 'Movistar'},
'514494903':{'en': 'Movistar'},
'514494902':{'en': 'Movistar'},
'514494901':{'en': 'Movistar'},
'514494900':{'en': 'Movistar'},
'516596534':{'en': 'Claro'},
'514494909':{'en': 'Claro'},
'514494908':{'en': 'Claro'},
'554299982':{'en': 'TIM'},
'2346437':{'en': 'Starcomms'},
'230529':{'en': 'MTML'},
'554299981':{'en': 'TIM'},
'230525':{'en': 'Cellplus'},
'2346439':{'en': 'Starcomms'},
'2346438':{'en': 'Starcomms'},
'51669669':{'en': 'Movistar'},
'51669668':{'en': 'Movistar'},
'551899754':{'en': 'Vivo'},
'551899755':{'en': 'Vivo'},
'51669667':{'en': 'Claro'},
'51669666':{'en': 'Movistar'},
'554699123':{'en': 'Vivo'},
'551899751':{'en': 'Vivo'},
'551899752':{'en': 'Vivo'},
'551899753':{'en': 'Vivo'},
'4476598':{'en': 'Vodafone'},
'4476599':{'en': 'PageOne'},
'553599168':{'en': 'TIM'},
'553599169':{'en': 'TIM'},
'553599162':{'en': 'TIM'},
'4476591':{'en': 'Vodafone'},
'4476592':{'en': 'PageOne'},
'4476593':{'en': 'Vodafone'},
'4476594':{'en': 'Vodafone'},
'4476595':{'en': 'Vodafone'},
'4476596':{'en': 'Vodafone'},
'553599165':{'en': 'TIM'},
'454298':{'en': 'Telia'},
'454299':{'en': 'Telia'},
'454292':{'en': '3'},
'454293':{'en': 'CBB Mobil'},
'454290':{'en': 'Mundio Mobile'},
'2341804':{'en': 'Starcomms'},
'454296':{'en': 'Telia'},
'454297':{'en': 'Telia'},
'454294':{'en': '3'},
'454295':{'en': '3'},
'42373':{'en': 'Telecom Liechtenstein'},
'42374':{'en': 'First Mobile'},
'42377':{'en': 'Swisscom'},
'42379':{'en': 'Telecom Liechtenstein'},
'42378':{'en': 'Salt'},
'554599968':{'en': 'TIM'},
'554799634':{'en': 'TIM'},
'552499924':{'en': 'Vivo'},
'552499925':{'en': 'Vivo'},
'552499920':{'en': 'Vivo'},
'552499921':{'en': 'Vivo'},
'552499922':{'en': 'Vivo'},
'552499923':{'en': 'Vivo'},
'19392416':{'en': 'Claro'},
'19392415':{'en': 'Claro'},
'19392414':{'en': 'Claro'},
'19392413':{'en': 'Claro'},
'19392412':{'en': 'Claro'},
'19392411':{'en': 'Claro'},
'19392410':{'en': 'Claro'},
'22997':{'en': 'MTN'},
'551799765':{'en': 'Vivo'},
'22995':{'en': 'Moov'},
'22994':{'en': 'Moov'},
'22993':{'en': 'BLK'},
'551799761':{'en': 'Vivo'},
'551799762':{'en': 'Vivo'},
'22990':{'en': 'Libercom'},
'3584941':{'en': 'Ukkoverkot'},
'24106':{'en': 'Libertis'},
'24107':{'en': 'Airtel'},
'22999':{'en': 'Moov'},
'22998':{'en': 'Moov'},
'45617':{'en': 'TDC'},
'346039':{'en': 'Lebara'},
'1787376':{'en': 'Claro'},
'45614':{'en': 'TDC'},
'45613':{'en': 'TDC'},
'1787371':{'en': 'Claro'},
'1787372':{'en': 'Claro'},
'346031':{'en': 'Lebara'},
'346032':{'en': 'Lebara'},
'346033':{'en': 'Lebara'},
'346034':{'en': 'Vodafone'},
'346035':{'en': 'Vodafone'},
'346036':{'en': 'Vodafone'},
'45618':{'en': 'Telenor'},
'551197018':{'en': 'TIM'},
'551197019':{'en': 'TIM'},
'552899959':{'en': 'Vivo'},
'552899958':{'en': 'Vivo'},
'551197012':{'en': 'TIM'},
'551197013':{'en': 'TIM'},
'552899957':{'en': 'Vivo'},
'551197011':{'en': 'TIM'},
'551197016':{'en': 'TIM'},
'551197017':{'en': 'TIM'},
'551197014':{'en': 'TIM'},
'551197015':{'en': 'TIM'},
'55319999':{'en': 'Telemig Celular'},
'55319998':{'en': 'Telemig Celular'},
'55319997':{'en': 'Telemig Celular'},
'55319996':{'en': 'Telemig Celular'},
'55319995':{'en': 'Telemig Celular'},
'551499138':{'en': 'Claro BR'},
'551499134':{'en': 'Claro BR'},
'551499135':{'en': 'Claro BR'},
'551499136':{'en': 'Claro BR'},
'551499137':{'en': 'Claro BR'},
'551499131':{'en': 'Claro BR'},
'551499132':{'en': 'Claro BR'},
'551499133':{'en': 'Claro BR'},
'2345277':{'en': 'Starcomms'},
'2345278':{'en': 'Starcomms'},
'2345279':{'en': 'Starcomms'},
'552798144':{'en': 'TIM'},
'447470':{'en': 'Vodafone'},
'447471':{'en': 'Vodafone'},
'552798145':{'en': 'TIM'},
'479552':{'en': 'Telenor'},
'479555':{'en': 'Telenor'},
'234528':{'en': 'Starcomms'},
'552798143':{'en': 'TIM'},
'554499148':{'en': 'Vivo'},
'554499149':{'en': 'Vivo'},
'554499141':{'en': 'Vivo'},
'554499142':{'en': 'Vivo'},
'554499143':{'en': 'Vivo'},
'554499144':{'en': 'Vivo'},
'554499145':{'en': 'Vivo'},
'554499146':{'en': 'Vivo'},
'554499147':{'en': 'Vivo'},
'447699':{'en': 'Vodafone'},
'447693':{'en': 'O2'},
'554299155':{'en': 'Vivo'},
'55119709':{'en': 'Vivo'},
'553599843':{'en': 'Telemig Celular'},
'553599842':{'en': 'Telemig Celular'},
'507161':{'en': 'Cable & Wireless'},
'553599845':{'en': 'Telemig Celular'},
'553898432':{'en': 'Claro BR'},
'553898433':{'en': 'Claro BR'},
'553898434':{'en': 'Claro BR'},
'553898435':{'en': 'Claro BR'},
'553898436':{'en': 'Claro BR'},
'553599844':{'en': 'Telemig Celular'},
'549362':{'en': 'Personal'},
'549364':{'en': 'Personal'},
'553599846':{'en': 'Telemig Celular'},
'553199175':{'en': 'TIM'},
'552299238':{'en': 'Claro BR'},
'552299239':{'en': 'Claro BR'},
'552299236':{'en': 'Claro BR'},
'552299237':{'en': 'Claro BR'},
'552299234':{'en': 'Claro BR'},
'23221':{'en': 'Sierratel'},
'552299232':{'en': 'Claro BR'},
'516596599':{'en': 'Movistar'},
'23225':{'en': 'Sierratel'},
'553799143':{'en': 'TIM'},
'553799141':{'en': 'TIM'},
'553799146':{'en': 'TIM'},
'553799147':{'en': 'TIM'},
'553199174':{'en': 'TIM'},
'553799145':{'en': 'TIM'},
'50844':{'en': 'Globaltel'},
'50840':{'en': 'Globaltel'},
'50842':{'en': 'Equant'},
'50843':{'en': 'Equant'},
'1284300':{'en': 'Digicel'},
'553199787':{'en': 'Telemig Celular'},
'549332':{'en': 'Personal'},
'2347784':{'en': 'Starcomms'},
'347277':{'en': 'Vodafone'},
'4478927':{'en': 'O2'},
'4478926':{'en': 'O2'},
'22177':{'en': 'Orange'},
'4478924':{'en': 'O2'},
'4478923':{'en': 'O2'},
'22170':{'en': 'Expresso'},
'4478921':{'en': 'Vectone Mobile'},
'4478920':{'en': 'HSL'},
'553199719':{'en': 'Telemig Celular'},
'22179':{'en': 'ADIE'},
'22178':{'en': 'Orange'},
'4478929':{'en': 'O2'},
'4478928':{'en': 'O2'},
'25772':{'en': 'Leo'},
'25771':{'en': 'Leo'},
'25776':{'en': 'Leo'},
'25777':{'en': 'Onatel'},
'25775':{'en': 'Smart Mobile'},
'25778':{'en': 'Smart Mobile'},
'25779':{'en': 'Leo'},
'553199717':{'en': 'Telemig Celular'},
'554299919':{'en': 'TIM'},
'553199173':{'en': 'TIM'},
'24828':{'en': 'Airtel'},
'24825':{'en': 'CWS'},
'553199711':{'en': 'Telemig Celular'},
'24827':{'en': 'Airtel'},
'24826':{'en': 'CWS'},
'553199344':{'en': 'TIM'},
'346931':{'en': 'Orange'},
'346933':{'en': 'Carrefour'},
'346932':{'en': 'MasMovil'},
'346935':{'en': 'MasMovil'},
'553199713':{'en': 'Telemig Celular'},
'346937':{'en': 'MasMovil'},
'553199712':{'en': 'Telemig Celular'},
'553199343':{'en': 'TIM'},
'1787569':{'en': 'CENTENNIAL'},
'1787568':{'en': 'SunCom Wireless Puerto Rico'},
'553199172':{'en': 'TIM'},
'554399149':{'en': 'Vivo'},
'554399148':{'en': 'Vivo'},
'1787561':{'en': 'CENTENNIAL'},
'45421':{'en': 'Telia'},
'1787563':{'en': 'CENTENNIAL'},
'45423':{'en': 'Telia'},
'45424':{'en': 'BiBoB'},
'45425':{'en': 'BiBoB'},
'45426':{'en': '3'},
'551599167':{'en': 'Claro BR'},
'447999':{'en': 'O2'},
'447990':{'en': 'Vodafone'},
'386651':{'en': u('S\u017d - Infrastruktura')},
'554299119':{'en': 'Vivo'},
'554299118':{'en': 'Vivo'},
'474049':{'en': 'NetCom'},
'474048':{'en': 'NetCom'},
'474045':{'en': 'NetCom'},
'474047':{'en': 'NetCom'},
'474046':{'en': 'NetCom'},
'554299115':{'en': 'Vivo'},
'553199821':{'en': 'Telemig Celular'},
'554299117':{'en': 'Vivo'},
'554299116':{'en': 'Vivo'},
'479837':{'en': 'NetCom'},
'551798154':{'en': 'TIM'},
'551798155':{'en': 'TIM'},
'551798156':{'en': 'TIM'},
'551798151':{'en': 'TIM'},
'551798152':{'en': 'TIM'},
'551798153':{'en': 'TIM'},
'44778':{'en': 'Vodafone'},
'44773':{'en': 'O2'},
'44772':{'en': 'O2'},
'44771':{'en': 'O2'},
'44777':{'en': 'Vodafone'},
'44776':{'en': 'Vodafone'},
'554498402':{'en': 'Brasil Telecom GSM'},
'554498403':{'en': 'Brasil Telecom GSM'},
'554498401':{'en': 'Brasil Telecom GSM'},
'554498406':{'en': 'Brasil Telecom GSM'},
'554498407':{'en': 'Brasil Telecom GSM'},
'421908':{'en': 'Orange'},
'421909':{'en': 'Juro'},
'421906':{'en': 'Orange'},
'421907':{'en': 'Orange'},
'421904':{'en': 'Telekom'},
'421905':{'en': 'Orange'},
'421902':{'en': 'Telekom'},
'421903':{'en': 'Telekom'},
'421901':{'en': 'Telekom'},
'551899713':{'en': 'Vivo'},
'5521975':{'en': 'Claro BR'},
'2348011':{'en': 'Megatech'},
'2348010':{'en': 'Megatech'},
'407018':{'en': 'Lycamobile'},
'407019':{'en': 'Lycamobile'},
'407013':{'en': 'Lycamobile'},
'407014':{'en': 'Lycamobile'},
'407015':{'en': 'Lycamobile'},
'407016':{'en': 'Lycamobile'},
'407017':{'en': 'Lycamobile'},
'479497':{'en': 'Telenor'},
'479498':{'en': 'Telenor'},
'553199632':{'en': 'Telemig Celular'},
'553199633':{'en': 'Telemig Celular'},
'553199631':{'en': 'Telemig Celular'},
'553199636':{'en': 'Telemig Celular'},
'553199637':{'en': 'Telemig Celular'},
'553199634':{'en': 'Telemig Celular'},
'551598113':{'en': 'TIM'},
'1767315':{'en': 'Digicel'},
'1767316':{'en': 'Digicel'},
'1767317':{'en': 'Digicel'},
'554599924':{'en': 'TIM'},
'1758384':{'en': 'Cable & Wireless'},
'553199208':{'en': 'TIM'},
'551999697':{'en': 'Vivo'},
'551999694':{'en': 'Vivo'},
'1242424':{'en': 'BaTelCo'},
'1242425':{'en': 'BaTelCo'},
'1242426':{'en': 'BaTelCo'},
'1242427':{'en': 'BaTelCo'},
'1242421':{'en': 'BaTelCo'},
'1242422':{'en': 'BaTelCo'},
'1242423':{'en': 'BaTelCo'},
'212630':{'en': 'Inwi'},
'212631':{'en': u('M\u00e9ditel')},
'212632':{'en': u('M\u00e9ditel')},
'212633':{'en': 'Inwi'},
'1242428':{'en': 'BaTelCo'},
'212635':{'en': 'Inwi'},
'212636':{'en': 'Maroc Telecom'},
'212637':{'en': 'Maroc Telecom'},
'552198335':{'en': 'TIM'},
'552198334':{'en': 'TIM'},
'552198337':{'en': 'TIM'},
'552198336':{'en': 'TIM'},
'552198331':{'en': 'TIM'},
'552198333':{'en': 'TIM'},
'552198332':{'en': 'TIM'},
'552198339':{'en': 'TIM'},
'552198338':{'en': 'TIM'},
'5532987':{'en': 'Oi'},
'5532986':{'en': 'Oi'},
'554199118':{'en': 'Vivo'},
'554199119':{'en': 'Vivo'},
'554199111':{'en': 'Vivo'},
'554199112':{'en': 'Vivo'},
'554199113':{'en': 'Vivo'},
'554199114':{'en': 'Vivo'},
'554199115':{'en': 'Vivo'},
'554199116':{'en': 'Vivo'},
'554199117':{'en': 'Vivo'},
'553499918':{'en': 'Telemig Celular'},
'553499919':{'en': 'Telemig Celular'},
'553499914':{'en': 'Telemig Celular'},
'553499915':{'en': 'Telemig Celular'},
'553499916':{'en': 'Telemig Celular'},
'553499917':{'en': 'Telemig Celular'},
'553499911':{'en': 'Telemig Celular'},
'553499912':{'en': 'Telemig Celular'},
'553499913':{'en': 'Telemig Celular'},
'5535988':{'en': 'Oi'},
'5535989':{'en': 'Oi'},
'517297271':{'en': 'Claro'},
'517297270':{'en': 'Claro'},
'517297273':{'en': 'Claro'},
'517297272':{'en': 'Claro'},
'5535985':{'en': 'Oi'},
'5535986':{'en': 'Oi'},
'5535987':{'en': 'Oi'},
'230544':{'en': 'Emtel'},
'230548':{'en': 'Emtel'},
'230549':{'en': 'Emtel'},
'553399199':{'en': 'TIM'},
'553399198':{'en': 'TIM'},
'553399191':{'en': 'TIM'},
'553399193':{'en': 'TIM'},
'553399197':{'en': 'TIM'},
'553599141':{'en': 'TIM'},
'553599142':{'en': 'TIM'},
'553599143':{'en': 'TIM'},
'553599144':{'en': 'TIM'},
'553599145':{'en': 'TIM'},
'553599146':{'en': 'TIM'},
'553599147':{'en': 'TIM'},
'553599148':{'en': 'TIM'},
'553599149':{'en': 'TIM'},
'551197968':{'en': 'Claro BR'},
'551197969':{'en': 'Claro BR'},
'458141':{'en': 'Simpl Telecom'},
'458146':{'en': 'Mundio Mobile'},
'458147':{'en': 'Mundio Mobile'},
'458145':{'en': 'Telavox'},
'458148':{'en': 'Mundio Mobile'},
'458149':{'en': 'Mundio Mobile'},
'5544999':{'en': 'TIM'},
'2763':{'en': 'MTN'},
'2762':{'en': 'Cell C'},
'2761':{'en': 'Cell C'},
'3584944':{'en': 'DNA'},
'551197974':{'en': 'Oi'},
'21192':{'en': 'MTN'},
'21191':{'en': 'Zain'},
'21197':{'en': 'Gemtel'},
'21195':{'en': 'Vivacell'},
'553199199':{'en': 'TIM'},
'553199198':{'en': 'TIM'},
'553199197':{'en': 'TIM'},
'553199196':{'en': 'TIM'},
'553199195':{'en': 'TIM'},
'553199194':{'en': 'TIM'},
'553199193':{'en': 'TIM'},
'553199192':{'en': 'TIM'},
'553199191':{'en': 'TIM'},
'24120':{'en': 'Libertis'},
'24121':{'en': 'Libertis'},
'24122':{'en': 'Libertis'},
'24123':{'en': 'Libertis'},
'24124':{'en': 'Libertis'},
'24125':{'en': 'Libertis'},
'24126':{'en': 'Libertis'},
'24127':{'en': 'Libertis'},
'30695328':{'en': 'Premium Net International'},
'1787359':{'en': 'SunCom Wireless Puerto Rico'},
'1787357':{'en': 'CENTENNIAL'},
'1787355':{'en': 'CENTENNIAL'},
'26878':{'en': 'Swazi MTN'},
'26879':{'en': 'Swazi MTN'},
'551197032':{'en': 'TIM'},
'551197033':{'en': 'TIM'},
'551197034':{'en': 'TIM'},
'551197035':{'en': 'TIM'},
'551197036':{'en': 'TIM'},
'551197037':{'en': 'TIM'},
'551197038':{'en': 'TIM'},
'552899979':{'en': 'Vivo'},
'552899978':{'en': 'Vivo'},
'26876':{'en': 'Swazi MTN'},
'26877':{'en': 'SPTC'},
'554199215':{'en': 'Vivo'},
'51449485':{'en': 'Movistar'},
'51449484':{'en': 'Movistar'},
'51449486':{'en': 'Movistar'},
'51449483':{'en': 'Claro'},
'51449482':{'en': 'Claro'},
'51449489':{'en': 'Movistar'},
'51449488':{'en': 'Movistar'},
'1242636':{'en': 'BaTelCo'},
'554299144':{'en': 'Vivo'},
'19392439':{'en': 'Claro'},
'19392438':{'en': 'Claro'},
'19392435':{'en': 'Claro'},
'19392434':{'en': 'Claro'},
'19392437':{'en': 'Claro'},
'19392436':{'en': 'Claro'},
'19392433':{'en': 'Claro'},
'447458':{'en': 'Gamma Telecom'},
'447459':{'en': 'Lycamobile'},
'447457':{'en': 'Vectone Mobile'},
'517497956':{'en': 'Movistar'},
'447451':{'en': 'Vectone Mobile'},
'447452':{'en': 'Manx Telecom'},
'26269313':{'en': 'SFR'},
'26269311':{'en': 'Orange'},
'26269310':{'en': 'SFR'},
'518298298':{'en': 'Movistar'},
'479536':{'en': 'Telenor'},
'234818':{'en': '9mobile'},
'38039':{'en': 'Golden Telecom'},
'554299912':{'en': 'TIM'},
'554299915':{'en': 'TIM'},
'554299914':{'en': 'TIM'},
'554299917':{'en': 'TIM'},
'554299916':{'en': 'TIM'},
'234810':{'en': 'MTN'},
'234811':{'en': 'Glo'},
'234812':{'en': 'Airtel'},
'234813':{'en': 'MTN'},
'234814':{'en': 'MTN'},
'234815':{'en': 'Glo'},
'234816':{'en': 'MTN'},
'234817':{'en': '9mobile'},
'554499128':{'en': 'Vivo'},
'554499129':{'en': 'Vivo'},
'554499126':{'en': 'Vivo'},
'554499127':{'en': 'Vivo'},
'554499124':{'en': 'Vivo'},
'34676':{'en': 'Movistar'},
'554499122':{'en': 'Vivo'},
'554499123':{'en': 'Vivo'},
'554499121':{'en': 'Vivo'},
'474661':{'en': 'NetCom'},
'474660':{'en': 'NetCom'},
'474663':{'en': 'NetCom'},
'474662':{'en': 'NetCom'},
'554599949':{'en': 'TIM'},
'5527989':{'en': 'Oi'},
'474666':{'en': 'Telenor'},
'5527987':{'en': 'Oi'},
'5527986':{'en': 'Oi'},
'5527985':{'en': 'Oi'},
'47591':{'en': 'Telenor'},
'50363171':{'en': 'Claro'},
'50363170':{'en': 'Claro'},
'50363173':{'en': 'Claro'},
'50363172':{'en': 'Claro'},
'50363174':{'en': 'Claro'},
'515495826':{'en': 'Claro'},
'549389':{'en': 'Personal'},
'549388':{'en': 'Personal'},
'4477977':{'en': 'JT'},
'4477979':{'en': 'JT'},
'4477978':{'en': 'JT'},
'549387':{'en': 'Personal'},
'549386':{'en': 'Personal'},
'549381':{'en': 'Personal'},
'549380':{'en': 'Personal'},
'549383':{'en': 'Personal'},
'549382':{'en': 'Personal'},
'552299214':{'en': 'Claro BR'},
'552299215':{'en': 'Claro BR'},
'552299216':{'en': 'Claro BR'},
'552299217':{'en': 'Claro BR'},
'552299211':{'en': 'Claro BR'},
'552299212':{'en': 'Claro BR'},
'552299213':{'en': 'Claro BR'},
'552299218':{'en': 'Claro BR'},
'552299219':{'en': 'Claro BR'},
'4473898':{'en': 'Vodafone'},
'4473892':{'en': 'TalkTalk'},
'4473893':{'en': 'TalkTalk'},
'4473890':{'en': 'Three'},
'4473891':{'en': 'Three'},
'4473896':{'en': 'Hanhaa'},
'4473897':{'en': 'Vodafone'},
'4473894':{'en': 'TalkTalk'},
'4473895':{'en': 'TalkTalk'},
'385905':{'en': 'Tele2'},
'385904':{'en': 'Tele2'},
'385907':{'en': 'Tele2'},
'385906':{'en': 'Tele2'},
'385901':{'en': 'Tele2'},
'385903':{'en': 'Tele2'},
'385902':{'en': 'Tele2'},
'385909':{'en': 'Tele2'},
'385908':{'en': 'Tele2'},
'554298408':{'en': 'Brasil Telecom GSM'},
'554298409':{'en': 'Brasil Telecom GSM'},
'3939':{'en': '3 Italia'},
'3938':{'en': 'Wind'},
'3934':{'en': 'Vodafone'},
'554298402':{'en': 'Brasil Telecom GSM'},
'3936':{'en': 'TIM'},
'554298404':{'en': 'Brasil Telecom GSM'},
'554298405':{'en': 'Brasil Telecom GSM'},
'3933':{'en': 'TIM'},
'3932':{'en': 'Wind'},
'5524988':{'en': 'Oi'},
'5524989':{'en': 'Oi'},
'5524986':{'en': 'Oi'},
'5524987':{'en': 'Oi'},
'5524985':{'en': 'Oi'},
'1787992':{'en': 'CENTENNIAL'},
'1787993':{'en': 'CENTENNIAL'},
'1787998':{'en': 'CENTENNIAL'},
'1787999':{'en': 'CENTENNIAL'},
'551899659':{'en': 'Vivo'},
'551899658':{'en': 'Vivo'},
'551899651':{'en': 'Vivo'},
'551899653':{'en': 'Vivo'},
'551899652':{'en': 'Vivo'},
'551899655':{'en': 'Vivo'},
'551899654':{'en': 'Vivo'},
'551899657':{'en': 'Vivo'},
'551899656':{'en': 'Vivo'},
'552197370':{'en': 'Claro BR'},
'552197371':{'en': 'Claro BR'},
'552197372':{'en': 'Claro BR'},
'552197373':{'en': 'Claro BR'},
'4368183':{'en': 'Orange AT'},
'553299911':{'en': 'Telemig Celular'},
'553598408':{'en': 'Claro BR'},
'553598409':{'en': 'Claro BR'},
'553598402':{'en': 'Claro BR'},
'553598403':{'en': 'Claro BR'},
'553598401':{'en': 'Claro BR'},
'553598406':{'en': 'Claro BR'},
'553598407':{'en': 'Claro BR'},
'553598404':{'en': 'Claro BR'},
'516196152':{'en': 'Movistar'},
'346919':{'en': 'MasMovil'},
'553299918':{'en': 'Telemig Celular'},
'554399163':{'en': 'Vivo'},
'554399162':{'en': 'Vivo'},
'554399161':{'en': 'Vivo'},
'554399167':{'en': 'Vivo'},
'554399166':{'en': 'Vivo'},
'551599108':{'en': 'Claro BR'},
'551599109':{'en': 'Claro BR'},
'2576':{'en': 'Viettel'},
'551599107':{'en': 'Claro BR'},
'551599104':{'en': 'Claro BR'},
'551599105':{'en': 'Claro BR'},
'551599102':{'en': 'Claro BR'},
'2573':{'en': 'Viettel'},
'551599101':{'en': 'Claro BR'},
'553499103':{'en': 'TIM'},
'553499102':{'en': 'TIM'},
'553499101':{'en': 'TIM'},
'474064':{'en': 'NetCom'},
'474063':{'en': 'NetCom'},
'474062':{'en': 'NetCom'},
'474061':{'en': 'NetCom'},
'474060':{'en': 'NetCom'},
'552798166':{'en': 'TIM'},
'552798167':{'en': 'TIM'},
'552798164':{'en': 'TIM'},
'552798165':{'en': 'TIM'},
'552798162':{'en': 'TIM'},
'552798163':{'en': 'TIM'},
'552798161':{'en': 'TIM'},
'124685':{'en': 'Digicel'},
'124684':{'en': 'Digicel'},
'124683':{'en': 'Digicel'},
'124682':{'en': 'Digicel'},
'554299137':{'en': 'Vivo'},
'554299136':{'en': 'Vivo'},
'554299135':{'en': 'Vivo'},
'554299134':{'en': 'Vivo'},
'554299133':{'en': 'Vivo'},
'554299132':{'en': 'Vivo'},
'554299131':{'en': 'Vivo'},
'553199679':{'en': 'Telemig Celular'},
'479854':{'en': 'NetCom'},
'459282':{'en': 'Flexfone'},
'459280':{'en': 'Voxbone'},
'306956':{'en': 'Vodafone'},
'553899191':{'en': 'TIM'},
'553899192':{'en': 'TIM'},
'553899193':{'en': 'TIM'},
'553899194':{'en': 'TIM'},
'553899195':{'en': 'TIM'},
'553899196':{'en': 'TIM'},
'5037786':{'en': 'Tigo'},
'5037785':{'en': 'Tigo'},
'37065':{'en': u('BIT\u0116')},
'37067':{'en': 'Tele 2'},
'30685501':{'en': 'BWS'},
'37060':{'en': 'Tele 2'},
'37062':{'en': 'Omnitel'},
'51749798':{'en': 'Movistar'},
'51749796':{'en': 'Movistar'},
'51749797':{'en': 'Claro'},
'51749790':{'en': 'Movistar'},
'51749791':{'en': 'Movistar'},
'51749792':{'en': 'Movistar'},
'51749793':{'en': 'Claro'},
'5037783':{'en': 'Movistar'},
'455282':{'en': 'Lebara Limited'},
'455280':{'en': 'Lebara Limited'},
'455281':{'en': 'Lebara Limited'},
'554498428':{'en': 'Brasil Telecom GSM'},
'554498429':{'en': 'Brasil Telecom GSM'},
'212675':{'en': u('M\u00e9ditel')},
'554498421':{'en': 'Brasil Telecom GSM'},
'554498422':{'en': 'Brasil Telecom GSM'},
'554498423':{'en': 'Brasil Telecom GSM'},
'554498424':{'en': 'Brasil Telecom GSM'},
'554498425':{'en': 'Brasil Telecom GSM'},
'554498426':{'en': 'Brasil Telecom GSM'},
'5037782':{'en': 'Movistar'},
'55249968':{'en': 'Vivo'},
'55249969':{'en': 'Vivo'},
'553199611':{'en': 'Telemig Celular'},
'55249962':{'en': 'Vivo'},
'30690500':{'en': 'MI Carrier Services'},
'55249964':{'en': 'Vivo'},
'55249965':{'en': 'Vivo'},
'55249966':{'en': 'Vivo'},
'55249967':{'en': 'Vivo'},
'212656':{'en': u('M\u00e9ditel')},
'212657':{'en': u('M\u00e9ditel')},
'551699961':{'en': 'Vivo'},
'553899999':{'en': 'Telemig Celular'},
'551699963':{'en': 'Vivo'},
'47928':{'en': 'NetCom'},
'551699964':{'en': 'Vivo'},
'553899990':{'en': 'Telemig Celular'},
'47922':{'en': 'NetCom'},
'553899992':{'en': 'Telemig Celular'},
'47920':{'en': 'NetCom'},
'47926':{'en': 'NetCom'},
'553899996':{'en': 'Telemig Celular'},
'47924':{'en': 'NetCom'},
'1787693':{'en': 'CENTENNIAL'},
'1787692':{'en': 'CENTENNIAL'},
'1787690':{'en': 'CENTENNIAL'},
'1787695':{'en': 'CENTENNIAL'},
'4478220':{'en': 'FleXtel'},
'4478221':{'en': 'Swiftnet'},
'4478222':{'en': 'TalkTalk'},
'4478224':{'en': 'aql'},
'4478225':{'en': 'Icron Network'},
'4478226':{'en': 'aql'},
'4478227':{'en': 'Cheers'},
'1242462':{'en': 'BaTelCo'},
'551698175':{'en': 'TIM'},
'1242463':{'en': 'BaTelCo'},
'551698174':{'en': 'TIM'},
'1242464':{'en': 'BaTelCo'},
'551698177':{'en': 'TIM'},
'1242465':{'en': 'BaTelCo'},
'551698176':{'en': 'TIM'},
'1242466':{'en': 'BaTelCo'},
'554199178':{'en': 'Vivo'},
'554199179':{'en': 'Vivo'},
'554199176':{'en': 'Vivo'},
'551698171':{'en': 'TIM'},
'554199174':{'en': 'Vivo'},
'175828':{'en': 'Cable & Wireless'},
'554199172':{'en': 'Vivo'},
'554199173':{'en': 'Vivo'},
'554199171':{'en': 'Vivo'},
'517396994':{'en': 'Movistar'},
'50584':{'en': 'Claro'},
'517396996':{'en': 'Movistar'},
'517396997':{'en': 'Movistar'},
'517396990':{'en': 'Movistar'},
'517396991':{'en': 'Movistar'},
'554698824':{'en': 'Claro BR'},
'50582':{'en': 'Movistar'},
'551698172':{'en': 'TIM'},
'517396998':{'en': 'Movistar'},
'50588':{'en': 'Movistar'},
'35193':{'en': 'NOS'},
'474830':{'en': 'Telenor'},
'474831':{'en': 'Telenor'},
'474832':{'en': 'Telenor'},
'551698178':{'en': 'TIM'},
'552198319':{'en': 'TIM'},
'552198318':{'en': 'TIM'},
'4478730':{'en': 'Telesign'},
'552198313':{'en': 'TIM'},
'552198312':{'en': 'TIM'},
'552198311':{'en': 'TIM'},
'552198317':{'en': 'TIM'},
'552198316':{'en': 'TIM'},
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'552198314':{'en': 'TIM'},
'5023534':{'en': 'Movistar'},
'551899798':{'en': 'Vivo'},
'551899799':{'en': 'Vivo'},
'2346479':{'en': 'Starcomms'},
'2694':{'en': 'TELCO'},
'2693':{'en': 'Comores Telecom'},
'551899792':{'en': 'Vivo'},
'2346470':{'en': 'Starcomms'},
'551899794':{'en': 'Vivo'},
'2346476':{'en': 'Starcomms'},
'2346475':{'en': 'Starcomms'},
'2346474':{'en': 'Starcomms'},
'5023533':{'en': 'Movistar'},
'5023532':{'en': 'Movistar'},
'486998':{'en': 'Plus'},
'553599126':{'en': 'TIM'},
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'553599124':{'en': 'TIM'},
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'553599122':{'en': 'TIM'},
'553599123':{'en': 'TIM'},
'553599121':{'en': 'TIM'},
'3069530':{'en': 'Cyta'},
'553599128':{'en': 'TIM'},
'553599129':{'en': 'TIM'},
'2982':{'en': 'Faroese Telecom'},
'553799118':{'en': 'TIM'},
'458161':{'en': 'YouSee'},
'3469199':{'en': 'Carrefour'},
'3469198':{'en': 'Carrefour'},
'297996':{'en': 'SETAR'},
'297997':{'en': 'SETAR'},
'297995':{'en': 'SETAR'},
'297998':{'en': 'SETAR'},
'5547991':{'en': 'Vivo'},
'474586':{'en': 'NetCom'},
'2346987':{'en': 'Starcomms'},
'551898144':{'en': 'TIM'},
'55169930':{'en': 'Claro BR'},
'2987':{'en': 'Vodafone'},
'55169931':{'en': 'Claro BR'},
'2346989':{'en': 'Starcomms'},
'1767285':{'en': 'Cable & Wireless'},
'212666':{'en': 'Maroc Telecom'},
'55169934':{'en': 'Claro BR'},
'55169935':{'en': 'Claro BR'},
'2986':{'en': 'Vodafone'},
'554898407':{'en': 'Brasil Telecom GSM'},
'554199156':{'en': 'Vivo'},
'4476778':{'en': 'Core Telecom'},
'554199157':{'en': 'Vivo'},
'4476770':{'en': '24 Seven'},
'4476772':{'en': 'Relax'},
'4476776':{'en': 'Telsis'},
'551197056':{'en': 'Claro BR'},
'551197057':{'en': 'Claro BR'},
'551197054':{'en': 'Claro BR'},
'551197055':{'en': 'Claro BR'},
'551197052':{'en': 'Claro BR'},
'551197053':{'en': 'Claro BR'},
'551197050':{'en': 'TIM'},
'551197051':{'en': 'TIM'},
'552299229':{'en': 'Claro BR'},
'1869565':{'en': 'The Cable St. Kitts'},
'1869566':{'en': 'The Cable St. Kitts'},
'1869567':{'en': 'The Cable St. Kitts'},
'515495929':{'en': 'Movistar'},
'515495928':{'en': 'Movistar'},
'515495927':{'en': 'Claro'},
'515495926':{'en': 'Claro'},
'515495925':{'en': 'Claro'},
'515495924':{'en': 'Claro'},
'515495923':{'en': 'Claro'},
'515495922':{'en': 'Claro'},
'515495921':{'en': 'Claro'},
'515495920':{'en': 'Claro'},
'553599904':{'en': 'Telemig Celular'},
'3469229':{'en': 'Carrefour'},
'26269339':{'en': 'Orange'},
'554599973':{'en': 'TIM'},
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'554598817':{'en': 'Claro BR'},
'554599977':{'en': 'TIM'},
'554599974':{'en': 'TIM'},
'554599975':{'en': 'TIM'},
'447300':{'en': 'EE'},
'447301':{'en': 'EE'},
'447302':{'en': 'EE'},
'447303':{'en': 'EE'},
'447304':{'en': 'EE'},
'447305':{'en': 'Virgin Mobile'},
'447306':{'en': 'Virgin Mobile'},
'38050':{'en': 'Vodafone'},
'553599905':{'en': 'Telemig Celular'},
'554299937':{'en': 'TIM'},
'554299936':{'en': 'TIM'},
'554299935':{'en': 'TIM'},
'554299934':{'en': 'TIM'},
'554299933':{'en': 'TIM'},
'554299932':{'en': 'TIM'},
'554299931':{'en': 'TIM'},
'45523':{'en': 'Telia'},
'45921':{'en': 'Companymobile'},
'45925':{'en': 'Telenor Connexion AB'},
'45927':{'en': 'Telenor Connexion AB'},
'45926':{'en': 'Telenor Connexion AB'},
'553299901':{'en': 'Telemig Celular'},
'553299903':{'en': 'Telemig Celular'},
'553299902':{'en': 'Telemig Celular'},
'553299905':{'en': 'Telemig Celular'},
'553299904':{'en': 'Telemig Celular'},
'553299907':{'en': 'Telemig Celular'},
'553299906':{'en': 'Telemig Celular'},
'553299909':{'en': 'Telemig Celular'},
'553299908':{'en': 'Telemig Celular'},
'553599907':{'en': 'Telemig Celular'},
'554199158':{'en': 'Vivo'},
'3876711':{'en': 'm:tel'},
'3876713':{'en': 'm:tel'},
'3876717':{'en': 'm:tel'},
'502449':{'en': 'Tigo'},
'502448':{'en': 'Tigo'},
'502335':{'en': 'Tigo'},
'502334':{'en': 'Tigo'},
'502331':{'en': 'Tigo'},
'502330':{'en': 'Tigo'},
'502333':{'en': 'Tigo'},
'502332':{'en': 'Tigo'},
'1684272':{'en': 'Blue Sky'},
'553599901':{'en': 'Telemig Celular'},
'553799106':{'en': 'TIM'},
'553799107':{'en': 'TIM'},
'553799104':{'en': 'TIM'},
'553799105':{'en': 'TIM'},
'1767295':{'en': 'Cable & Wireless'},
'553799103':{'en': 'TIM'},
'553799101':{'en': 'TIM'},
'5023531':{'en': 'Movistar'},
'553798416':{'en': 'Claro BR'},
'553799108':{'en': 'TIM'},
'553799109':{'en': 'TIM'},
'1868268':{'en': 'bmobile'},
'5037848':{'en': 'Movistar'},
'5037849':{'en': 'Movistar'},
'5023530':{'en': 'Movistar'},
'5037844':{'en': 'Claro'},
'5037845':{'en': 'Movistar'},
'5037846':{'en': 'Movistar'},
'5037847':{'en': 'Movistar'},
'5037840':{'en': 'Claro'},
'5037841':{'en': 'Claro'},
'5037842':{'en': 'Claro'},
'5037843':{'en': 'Claro'},
'4869961':{'en': 'Cyfrowy Polsat'},
'4869963':{'en': 'Cyfrowy Polsat'},
'4869962':{'en': 'Cyfrowy Polsat'},
'4869965':{'en': 'Cyfrowy Polsat'},
'4869964':{'en': 'Cyfrowy Polsat'},
'4869967':{'en': 'Plus'},
'4869966':{'en': 'Cyfrowy Polsat'},
'4869969':{'en': 'Plus'},
'4869968':{'en': 'Cyfrowy Polsat'},
'2428001':{'en': 'Hightech Pro'},
'553199405':{'en': 'TIM'},
'553199404':{'en': 'TIM'},
'553199407':{'en': 'TIM'},
'553199406':{'en': 'TIM'},
'553199401':{'en': 'TIM'},
'553199403':{'en': 'TIM'},
'553199402':{'en': 'TIM'},
'553199411':{'en': 'TIM'},
'553199409':{'en': 'TIM'},
'553199408':{'en': 'TIM'},
'554398427':{'en': 'Brasil Telecom GSM'},
'2232079':{'en': 'Sotelma'},
'551899679':{'en': 'Vivo'},
'551899678':{'en': 'Vivo'},
'551899677':{'en': 'Vivo'},
'551899676':{'en': 'Vivo'},
'551899675':{'en': 'Vivo'},
'551899674':{'en': 'Vivo'},
'551899673':{'en': 'Vivo'},
'551899672':{'en': 'Vivo'},
'551899671':{'en': 'Vivo'},
'507873':{'en': 'Cable & Wireless'},
'507872':{'en': 'Cable & Wireless'},
'553398439':{'en': 'Claro BR'},
'553398438':{'en': 'Claro BR'},
'553398431':{'en': 'Claro BR'},
'553398433':{'en': 'Claro BR'},
'553398432':{'en': 'Claro BR'},
'553398435':{'en': 'Claro BR'},
'553398434':{'en': 'Claro BR'},
'553398437':{'en': 'Claro BR'},
'553398436':{'en': 'Claro BR'},
'553598421':{'en': 'Claro BR'},
'553598422':{'en': 'Claro BR'},
'553598423':{'en': 'Claro BR'},
'553598424':{'en': 'Claro BR'},
'553598425':{'en': 'Claro BR'},
'553598426':{'en': 'Claro BR'},
'553598427':{'en': 'Claro BR'},
'553598428':{'en': 'Claro BR'},
'553598429':{'en': 'Claro BR'},
'1787528':{'en': 'SunCom Wireless Puerto Rico'},
'553199271':{'en': 'TIM'},
'1787521':{'en': 'CENTENNIAL'},
'1787520':{'en': 'CENTENNIAL'},
'1787523':{'en': 'CENTENNIAL'},
'1787522':{'en': 'CENTENNIAL'},
'551599124':{'en': 'Claro BR'},
'551599125':{'en': 'Claro BR'},
'551599126':{'en': 'Claro BR'},
'551599127':{'en': 'Claro BR'},
'551599121':{'en': 'Claro BR'},
'551599122':{'en': 'Claro BR'},
'551599123':{'en': 'Claro BR'},
'447955':{'en': 'O2'},
'551599128':{'en': 'Claro BR'},
'551599129':{'en': 'Claro BR'},
'474001':{'en': 'NetCom'},
'474000':{'en': 'NetCom'},
'552798146':{'en': 'TIM'},
'552798147':{'en': 'TIM'},
'552798141':{'en': 'TIM'},
'552798142':{'en': 'TIM'},
'551899661':{'en': 'Vivo'},
'552798148':{'en': 'TIM'},
'552798149':{'en': 'TIM'},
'553599841':{'en': 'Telemig Celular'},
'516596592':{'en': 'Movistar'},
'516596591':{'en': 'Movistar'},
'516596590':{'en': 'Movistar'},
'516596597':{'en': 'Movistar'},
'516596596':{'en': 'Movistar'},
'554299153':{'en': 'Vivo'},
'553199277':{'en': 'TIM'},
'55119702':{'en': 'TIM'},
'516596598':{'en': 'Movistar'},
'554299159':{'en': 'Vivo'},
'554299158':{'en': 'Vivo'},
'55119706':{'en': 'Claro BR'},
'55119707':{'en': 'Claro BR'},
'479876':{'en': 'NetCom'},
'554199139':{'en': 'Vivo'},
'42093':{'en': 'T-Mobile'},
'551499174':{'en': 'Claro BR'},
'551898124':{'en': 'TIM'},
'45515':{'en': 'TDC'},
'45516':{'en': 'TDC'},
'551499178':{'en': 'Claro BR'},
'45517':{'en': 'TDC'},
'40776':{'en': 'Digi Mobil'},
'5521971':{'en': 'Vivo'},
'5521972':{'en': 'Vivo'},
'5521974':{'en': 'Claro BR'},
'40775':{'en': 'Digi Mobil'},
'5521976':{'en': 'Claro BR'},
'551898121':{'en': 'TIM'},
'50378027':{'en': 'Claro'},
'50378026':{'en': 'Claro'},
'50378025':{'en': 'Claro'},
'50378024':{'en': 'Digicel'},
'50378023':{'en': 'Digicel'},
'50378022':{'en': 'Digicel'},
'50378021':{'en': 'Digicel'},
'50378020':{'en': 'Digicel'},
'551898123':{'en': 'TIM'},
'50378029':{'en': 'Claro'},
'50378028':{'en': 'Claro'},
'5119955':{'en': 'Movistar'},
'5119954':{'en': 'Movistar'},
'5119957':{'en': 'Movistar'},
'5119956':{'en': 'Movistar'},
'551999692':{'en': 'Vivo'},
'551999693':{'en': 'Vivo'},
'5119953':{'en': 'Movistar'},
'551999691':{'en': 'Vivo'},
'5119959':{'en': 'Movistar'},
'5119958':{'en': 'Movistar'},
'551999698':{'en': 'Vivo'},
'551999699':{'en': 'Vivo'},
'2348581':{'en': 'Starcomms'},
'2348583':{'en': 'Starcomms'},
'2348582':{'en': 'Starcomms'},
'2348585':{'en': 'Starcomms'},
'2348584':{'en': 'Starcomms'},
'2348587':{'en': 'Starcomms'},
'2348586':{'en': 'Starcomms'},
'2348588':{'en': 'Starcomms'},
'551898129':{'en': 'TIM'},
'552799291':{'en': 'Claro BR'},
'554799913':{'en': 'TIM'},
'407050':{'en': 'Iristel'},
'421940':{'en': 'O2'},
'421944':{'en': 'O2'},
'421945':{'en': 'Orange'},
'421948':{'en': 'O2'},
'421949':{'en': 'O2'},
'45315':{'en': '3'},
'347110':{'en': 'Zinnia'},
'347111':{'en': 'Vodafone'},
'447438':{'en': 'Lycamobile'},
'553199678':{'en': 'Telemig Celular'},
'347117':{'en': 'Vodafone'},
'553199676':{'en': 'Telemig Celular'},
'553199677':{'en': 'Telemig Celular'},
'553199674':{'en': 'Telemig Celular'},
'553199675':{'en': 'Telemig Celular'},
'553199672':{'en': 'Telemig Celular'},
'553199673':{'en': 'Telemig Celular'},
'553199671':{'en': 'Telemig Celular'},
'447793':{'en': 'O2'},
'447792':{'en': 'Orange'},
'447791':{'en': 'Orange'},
'447790':{'en': 'Orange'},
'447796':{'en': 'Vodafone'},
'447795':{'en': 'Vodafone'},
'447794':{'en': 'Orange'},
'447799':{'en': 'Vodafone'},
'447798':{'en': 'Vodafone'},
'447435':{'en': 'Vodafone'},
'212679':{'en': u('M\u00e9ditel')},
'554698809':{'en': 'Claro BR'},
'212674':{'en': u('M\u00e9ditel')},
'47948':{'en': 'Telenor'},
'26269294':{'en': 'Only'},
'26269292':{'en': 'Only'},
'26269293':{'en': 'Only'},
'447433':{'en': 'EE'},
'1242468':{'en': 'BaTelCo'},
'553499957':{'en': 'Telemig Celular'},
'324688':{'en': 'Premium Routing GmbH'},
'324687':{'en': 'Premium Routing GmbH'},
'324685':{'en': 'Telenet'},
'324684':{'en': 'Telenet'},
'324683':{'en': 'Telenet'},
'324682':{'en': 'Telenet'},
'324681':{'en': 'Telenet'},
'1242467':{'en': 'BaTelCo'},
'35196':{'en': 'MEO'},
'507668':{'en': 'Cable & Wireless'},
'507669':{'en': 'Cable & Wireless'},
'35191':{'en': 'Vodafone'},
'507664':{'en': u('Telef\u00f3nica M\u00f3viles')},
'507665':{'en': 'Cable & Wireless'},
'507666':{'en': 'Cable & Wireless'},
'507667':{'en': 'Cable & Wireless'},
'507660':{'en': u('Telef\u00f3nica M\u00f3viles')},
'507661':{'en': u('Telef\u00f3nica M\u00f3viles')},
'507662':{'en': u('Telef\u00f3nica M\u00f3viles')},
'507663':{'en': u('Telef\u00f3nica M\u00f3viles')},
'549280':{'en': 'Personal'},
'554799616':{'en': 'TIM'},
'503789':{'en': 'Tigo'},
'503788':{'en': 'Tigo'},
'474580':{'en': 'Telenor'},
'503783':{'en': 'Movistar'},
'503782':{'en': 'Movistar'},
'503781':{'en': 'Movistar'},
'2346988':{'en': 'Starcomms'},
'503787':{'en': 'Tigo'},
'503786':{'en': 'Claro'},
'503785':{'en': 'Claro'},
'554199154':{'en': 'Vivo'},
'554199155':{'en': 'Vivo'},
'38268':{'en': 'm:tel'},
'38269':{'en': 'Telenor'},
'554199151':{'en': 'Vivo'},
'554199152':{'en': 'Vivo'},
'554199153':{'en': 'Vivo'},
'38263':{'en': 'Telenor'},
'38260':{'en': 'm:tel'},
'38266':{'en': 'Telekom'},
'38267':{'en': 'Telekom'},
'554699974':{'en': 'TIM'},
'554198442':{'en': 'Brasil Telecom GSM'},
'423650':{'en': 'Soracom'},
'4474583':{'en': 'Virgin Mobile'},
'4474582':{'en': 'Premium Routing'},
'4474585':{'en': 'Marathon Telecom'},
'4474584':{'en': 'Airwave'},
'4474587':{'en': 'Limitless'},
'4474586':{'en': 'Three'},
'4474589':{'en': 'Three'},
'4474588':{'en': 'Limitless'},
'553899154':{'en': 'TIM'},
'553899155':{'en': 'TIM'},
'553899156':{'en': 'TIM'},
'553899157':{'en': 'TIM'},
'553899151':{'en': 'TIM'},
'551999506':{'en': 'Claro BR'},
'551999507':{'en': 'Claro BR'},
'551999504':{'en': 'Claro BR'},
'551999505':{'en': 'Claro BR'},
'551999502':{'en': 'Claro BR'},
'551999503':{'en': 'Claro BR'},
'551999500':{'en': 'Claro BR'},
'551999501':{'en': 'Claro BR'},
'516296251':{'en': 'Movistar'},
'516296250':{'en': 'Movistar'},
'516296253':{'en': 'Movistar'},
'516296252':{'en': 'Movistar'},
'516296254':{'en': 'Movistar'},
'551999508':{'en': 'Claro BR'},
'554698808':{'en': 'Claro BR'},
'515495808':{'en': 'Claro'},
'1242889':{'en': 'aliv'},
'517697605':{'en': 'Movistar'},
'5531984':{'en': 'Claro BR'},
'554698801':{'en': 'Claro BR'},
'554698802':{'en': 'Claro BR'},
'554698803':{'en': 'Claro BR'},
'554698804':{'en': 'Claro BR'},
'554698805':{'en': 'Claro BR'},
'554698806':{'en': 'Claro BR'},
'554698807':{'en': 'Claro BR'},
'454278':{'en': 'Telia'},
'454279':{'en': 'Telia'},
'454270':{'en': 'BiBoB'},
'454271':{'en': '3'},
'454272':{'en': '3'},
'454273':{'en': '3'},
'454274':{'en': '3'},
'454275':{'en': 'YouSee'},
'454276':{'en': 'Telia'},
'454277':{'en': 'Telia'},
'554799624':{'en': 'TIM'},
'554799625':{'en': 'TIM'},
'553899162':{'en': 'TIM'},
'554799628':{'en': 'TIM'},
'554799629':{'en': 'TIM'},
'553599108':{'en': 'TIM'},
'553599109':{'en': 'TIM'},
'553599104':{'en': 'TIM'},
'553599105':{'en': 'TIM'},
'553599106':{'en': 'TIM'},
'553599107':{'en': 'TIM'},
'553599101':{'en': 'TIM'},
'553599102':{'en': 'TIM'},
'553599103':{'en': 'TIM'},
'21379':{'en': 'Djezzy'},
'554799951':{'en': 'TIM'},
'553399968':{'en': 'Telemig Celular'},
'21377':{'en': 'Djezzy'},
'553799954':{'en': 'Telemig Celular'},
'1787312':{'en': 'Claro'},
'1787313':{'en': 'Claro'},
'1787310':{'en': 'SunCom Wireless Puerto Rico'},
'1787316':{'en': 'Claro'},
'1787317':{'en': 'Claro'},
'1787314':{'en': 'Claro'},
'1787315':{'en': 'Claro'},
'1787318':{'en': 'Claro'},
'553799959':{'en': 'Telemig Celular'},
'553799958':{'en': 'Telemig Celular'},
'2015':{'en': 'TE'},
'2011':{'en': 'Etisalat'},
'2010':{'en': 'Vodafone'},
'2012':{'en': 'Orange'},
'553399961':{'en': 'Telemig Celular'},
'164934':{'en': 'Digicel'},
'164933':{'en': 'Digicel'},
'551499196':{'en': 'Claro BR'},
'551499197':{'en': 'Claro BR'},
'551499194':{'en': 'Claro BR'},
'551499195':{'en': 'Claro BR'},
'551499192':{'en': 'Claro BR'},
'551499193':{'en': 'Claro BR'},
'551499191':{'en': 'Claro BR'},
'553798426':{'en': 'Claro BR'},
'552499282':{'en': 'Claro BR'},
'553798424':{'en': 'Claro BR'},
'553798425':{'en': 'Claro BR'},
'553798422':{'en': 'Claro BR'},
'553798423':{'en': 'Claro BR'},
'26269355':{'en': 'Orange'},
'553798421':{'en': 'Claro BR'},
'26269350':{'en': 'Only'},
'38073':{'en': 'lifecell'},
'45254':{'en': 'Telenor'},
'51439436':{'en': 'Movistar'},
'51439435':{'en': 'Claro'},
'51439434':{'en': 'Movistar'},
'553299923':{'en': 'Telemig Celular'},
'553299922':{'en': 'Telemig Celular'},
'51439431':{'en': 'Movistar'},
'51439430':{'en': 'Movistar'},
'51439438':{'en': 'Movistar'},
'553899810':{'en': 'Telemig Celular'},
'352668':{'en': 'Orange'},
'554299146':{'en': 'Vivo'},
'352661':{'en': 'Orange'},
'55349840':{'en': 'Claro BR'},
'55349841':{'en': 'Claro BR'},
'554299145':{'en': 'Vivo'},
'447366':{'en': 'Three'},
'447367':{'en': 'Three'},
'447365':{'en': 'Three'},
'554299142':{'en': 'Vivo'},
'554599952':{'en': 'TIM'},
'554599953':{'en': 'TIM'},
'554599954':{'en': 'TIM'},
'38163':{'en': 'Telenor'},
'554299143':{'en': 'Vivo'},
'554299141':{'en': 'Vivo'},
'553799128':{'en': 'TIM'},
'553799129':{'en': 'TIM'},
'553799124':{'en': 'TIM'},
'553799125':{'en': 'TIM'},
'553799126':{'en': 'TIM'},
'553799127':{'en': 'TIM'},
'553799121':{'en': 'TIM'},
'553799122':{'en': 'TIM'},
'553799123':{'en': 'TIM'},
'553199795':{'en': 'Telemig Celular'},
'553199794':{'en': 'Telemig Celular'},
'553199797':{'en': 'Telemig Celular'},
'3468870':{'en': 'OpenMovil'},
'553199791':{'en': 'Telemig Celular'},
'553199793':{'en': 'Telemig Celular'},
'553199792':{'en': 'Telemig Celular'},
'553199799':{'en': 'Telemig Celular'},
'553199798':{'en': 'Telemig Celular'},
'187688':{'en': 'Digicel'},
'187689':{'en': 'Digicel'},
'554299149':{'en': 'Vivo'},
'1784432':{'en': 'AT&T'},
'187687':{'en': 'Digicel'},
'187684':{'en': 'Digicel'},
'187685':{'en': 'Digicel'},
'4869909':{'en': 'Cyfrowy Polsat'},
'4869908':{'en': 'Cyfrowy Polsat'},
'4869903':{'en': 'Cyfrowy Polsat'},
'4869902':{'en': 'Cyfrowy Polsat'},
'4869907':{'en': 'Cyfrowy Polsat'},
'4869906':{'en': 'Cyfrowy Polsat'},
'4869905':{'en': 'Cyfrowy Polsat'},
'4869904':{'en': 'Cyfrowy Polsat'},
'447586':{'en': 'Vodafone'},
'447587':{'en': 'Vodafone'},
'447584':{'en': 'Vodafone'},
'447585':{'en': 'Vodafone'},
'447582':{'en': 'Orange'},
'447583':{'en': 'Orange'},
'447580':{'en': 'Orange'},
'447581':{'en': 'Orange'},
'447588':{'en': 'Three'},
'1684254':{'en': 'Blue Sky'},
'1684256':{'en': 'Blue Sky'},
'1684252':{'en': 'Blue Sky'},
'1684258':{'en': 'Blue Sky'},
'551899615':{'en': 'Vivo'},
'551899614':{'en': 'Vivo'},
'551899617':{'en': 'Vivo'},
'551899616':{'en': 'Vivo'},
'551899611':{'en': 'Vivo'},
'551899613':{'en': 'Vivo'},
'551899612':{'en': 'Vivo'},
'551899618':{'en': 'Vivo'},
'553199373':{'en': 'TIM'},
'553199372':{'en': 'TIM'},
'553199371':{'en': 'TIM'},
'551196930':{'en': 'Claro BR'},
'551196931':{'en': 'Claro BR'},
'553199377':{'en': 'TIM'},
'553199376':{'en': 'TIM'},
'553199375':{'en': 'TIM'},
'553398419':{'en': 'Claro BR'},
'553398418':{'en': 'Claro BR'},
'553398417':{'en': 'Claro BR'},
'553398416':{'en': 'Claro BR'},
'553398415':{'en': 'Claro BR'},
'553199374':{'en': 'TIM'},
'553398413':{'en': 'Claro BR'},
'553199704':{'en': 'Telemig Celular'},
'553398411':{'en': 'Claro BR'},
'553598446':{'en': 'Claro BR'},
'552899258':{'en': 'Claro BR'},
'389792':{'en': 'Lycamobile'},
'389793':{'en': 'Lycamobile'},
'553598442':{'en': 'Claro BR'},
'553598443':{'en': 'Claro BR'},
'553598441':{'en': 'Claro BR'},
'3620':{'en': 'Telenor'},
'553598448':{'en': 'Claro BR'},
'553598449':{'en': 'Claro BR'},
'447977':{'en': 'Orange'},
'447976':{'en': 'Orange'},
'447975':{'en': 'Orange'},
'447974':{'en': 'Orange'},
'447973':{'en': 'Orange'},
'447972':{'en': 'Orange'},
'447971':{'en': 'Orange'},
'447970':{'en': 'Orange'},
'447979':{'en': 'Vodafone'},
'552899256':{'en': 'Claro BR'},
'474029':{'en': 'NetCom'},
'474028':{'en': 'Telenor'},
'474022':{'en': 'Telenor'},
'5515997':{'en': 'Vivo'},
'479899':{'en': 'NetCom'},
'48607':{'en': 'Plus'},
'45234':{'en': 'TDC'},
'4915020':{'en': 'Interactive digital media'},
'42077':{'en': 'Vodafone'},
'42072':{'en': 'O2'},
'45237':{'en': 'TDC'},
'45236':{'en': 'TDC'},
'459248':{'en': 'Telenor Connexion AB'},
'459249':{'en': 'Telenor Connexion AB'},
'459246':{'en': 'Telenor Connexion AB'},
'45231':{'en': 'TDC'},
'459244':{'en': 'Ipnordic'},
'459245':{'en': 'Compatel Limited'},
'459243':{'en': 'Companymobile'},
'48601':{'en': 'Plus'},
'45232':{'en': 'TDC'},
'1939891':{'en': 'SunCom Wireless Puerto Rico'},
'551899765':{'en': 'Vivo'},
'551899764':{'en': 'Vivo'},
'491529':{'en': 'Vodafone/Truphone'},
'551899766':{'en': 'Vivo'},
'551899763':{'en': 'Vivo'},
'551899762':{'en': 'Vivo'},
'553799805':{'en': 'Telemig Celular'},
'553799804':{'en': 'Telemig Celular'},
'553799803':{'en': 'Telemig Celular'},
'553799802':{'en': 'Telemig Celular'},
'553799801':{'en': 'Telemig Celular'},
'491526':{'en': 'Vodafone'},
'2344687':{'en': 'Starcomms'},
'2344684':{'en': 'Starcomms'},
'2344682':{'en': 'Starcomms'},
'2344683':{'en': 'Starcomms'},
'2344680':{'en': 'Starcomms'},
'55249924':{'en': 'Claro BR'},
'55249925':{'en': 'Claro BR'},
'55249926':{'en': 'Claro BR'},
'55249927':{'en': 'Claro BR'},
'55249920':{'en': 'Claro BR'},
'55249921':{'en': 'Claro BR'},
'55249922':{'en': 'Claro BR'},
'55249923':{'en': 'Claro BR'},
'347170':{'en': 'Movistar'},
'347171':{'en': 'Vodafone'},
'553199658':{'en': 'Telemig Celular'},
'347177':{'en': 'Movistar'},
'447779':{'en': 'Orange'},
'447777':{'en': 'EE'},
'447773':{'en': 'Orange'},
'447772':{'en': 'Orange'},
'1242442':{'en': 'BaTelCo'},
'1242443':{'en': 'BaTelCo'},
'1242441':{'en': 'BaTelCo'},
'3368':{'en': 'Orange France'},
'1242447':{'en': 'BaTelCo'},
'1242445':{'en': 'BaTelCo'},
'553199218':{'en': 'TIM'},
'3366':{'en': 'Bouygues'},
'3367':{'en': 'Orange France'},
'3361':{'en': 'SFR'},
'3362':{'en': 'SFR'},
'553199219':{'en': 'TIM'},
'502502':{'en': 'Movistar'},
'549266':{'en': 'Personal'},
'549264':{'en': 'Personal'},
'549265':{'en': 'Personal'},
'549262':{'en': 'Personal'},
'549263':{'en': 'Personal'},
'549260':{'en': 'Personal'},
'549261':{'en': 'Personal'},
'474566':{'en': 'Telenor'},
'234628':{'en': 'Starcomms'},
'474563':{'en': 'NetCom'},
'474560':{'en': 'Telenor'},
'474561':{'en': 'Telenor'},
'27741':{'en': 'Virgin Mobile'},
'553599803':{'en': 'Telemig Celular'},
'25679':{'en': 'Africell'},
'25678':{'en': 'MTN'},
'25671':{'en': 'UTL'},
'25670':{'en': 'Airtel'},
'25677':{'en': 'MTN'},
'554798456':{'en': 'Brasil Telecom GSM'},
'25675':{'en': 'Airtel'},
'25674':{'en': 'Sure Telecom'},
'553199245':{'en': 'TIM'},
'554199216':{'en': 'Vivo'},
'486901':{'en': 'Orange'},
'486903':{'en': 'Orange'},
'486902':{'en': 'Orange'},
'486905':{'en': 'Orange'},
'486904':{'en': 'Orange'},
'486907':{'en': 'CenterNet'},
'486906':{'en': 'Orange'},
'22588':{'en': 'Orange'},
'22589':{'en': 'Orange'},
'51839837':{'en': 'Claro'},
'51839836':{'en': 'Movistar'},
'22586':{'en': 'MTN'},
'22587':{'en': 'Orange'},
'1671488':{'en': 'GTA'},
'1671489':{'en': 'GTA'},
'1671480':{'en': 'GTA'},
'1671482':{'en': 'GTA'},
'1671483':{'en': 'GTA'},
'1671486':{'en': 'GTA'},
'1671487':{'en': 'GTA'},
'1787481':{'en': 'Claro'},
'551196059':{'en': 'Vivo'},
'551196058':{'en': 'Vivo'},
'1787484':{'en': 'Claro'},
'1787485':{'en': 'Claro'},
'551196057':{'en': 'Vivo'},
'554398851':{'en': 'Claro BR'},
'5067300':{'en': 'Claro'},
'5067301':{'en': 'Claro'},
'30695340':{'en': 'AMD Telecom'},
'2784':{'en': 'Cell C'},
'2783':{'en': 'MTN'},
'2782':{'en': 'Vodacom'},
'51549588':{'en': 'Movistar'},
'51549583':{'en': 'Claro'},
'51549587':{'en': 'Claro'},
'51549586':{'en': 'Movistar'},
'51549585':{'en': 'Movistar'},
'55319913':{'en': 'TIM'},
'55319912':{'en': 'TIM'},
'55319911':{'en': 'TIM'},
'50946':{'en': 'Digicel'},
'55319915':{'en': 'TIM'},
'55319914':{'en': 'TIM'},
'551599168':{'en': 'Claro BR'},
'3471777':{'en': 'PepePhone'},
'2126921':{'en': 'Al Hourria Telecom'},
'2126922':{'en': 'Al Hourria Telecom'},
'551799636':{'en': 'Vivo'},
'551799637':{'en': 'Vivo'},
'26269377':{'en': 'Orange'},
'551799635':{'en': 'Vivo'},
'26269371':{'en': 'Only'},
'26269370':{'en': 'Only'},
'26269372':{'en': 'Only'},
'3471771':{'en': 'PepePhone'},
'551799638':{'en': 'Vivo'},
'551799639':{'en': 'Vivo'},
'554299973':{'en': 'TIM'},
'554299972':{'en': 'TIM'},
'554299971':{'en': 'TIM'},
'554299977':{'en': 'TIM'},
'554299976':{'en': 'TIM'},
'554299975':{'en': 'TIM'},
'554299974':{'en': 'TIM'},
'554299979':{'en': 'TIM'},
'554299978':{'en': 'TIM'},
'553299949':{'en': 'Telemig Celular'},
'553299948':{'en': 'Telemig Celular'},
'553299945':{'en': 'Telemig Celular'},
'553299944':{'en': 'Telemig Celular'},
'553299947':{'en': 'Telemig Celular'},
'30690399':{'en': 'BWS'},
'553299941':{'en': 'Telemig Celular'},
'553299943':{'en': 'Telemig Celular'},
'553299942':{'en': 'Telemig Celular'},
'51739689':{'en': 'Movistar'},
'51739688':{'en': 'Movistar'},
'553399919':{'en': 'Telemig Celular'},
'553399918':{'en': 'Telemig Celular'},
'553399911':{'en': 'Telemig Celular'},
'553399913':{'en': 'Telemig Celular'},
'553399912':{'en': 'Telemig Celular'},
'553399915':{'en': 'Telemig Celular'},
'553399914':{'en': 'Telemig Celular'},
'553399917':{'en': 'Telemig Celular'},
'553399916':{'en': 'Telemig Celular'},
'3584320':{'en': 'Cuuma'},
'3584321':{'en': 'Cuuma'},
'554599936':{'en': 'TIM'},
'554599937':{'en': 'TIM'},
'554599934':{'en': 'TIM'},
'554599935':{'en': 'TIM'},
'447340':{'en': 'Vodafone'},
'447341':{'en': 'Vodafone'},
'447342':{'en': 'Vodafone'},
'554599931':{'en': 'TIM'},
'553199651':{'en': 'Telemig Celular'},
'180984':{'en': 'Orange'},
'180985':{'en': 'Orange'},
'180986':{'en': 'Orange'},
'180987':{'en': 'Tricom'},
'180980':{'en': 'Orange'},
'180981':{'en': 'Viva'},
'180982':{'en': 'Claro'},
'180983':{'en': 'Claro'},
'180988':{'en': 'Orange'},
'180989':{'en': 'Orange'},
'4869925':{'en': 'Cyfrowy Polsat'},
'4869924':{'en': 'Cyfrowy Polsat'},
'4869927':{'en': 'Cyfrowy Polsat'},
'4869926':{'en': 'Cyfrowy Polsat'},
'4869921':{'en': 'Cyfrowy Polsat'},
'4869920':{'en': 'Cyfrowy Polsat'},
'4869923':{'en': 'Cyfrowy Polsat'},
'4869929':{'en': 'Cyfrowy Polsat'},
'4869928':{'en': 'Cyfrowy Polsat'},
'502595':{'en': 'Telgua'},
'502594':{'en': 'Telgua'},
'502597':{'en': 'Telgua'},
'502596':{'en': 'Telgua'},
'502593':{'en': 'Telgua'},
'502592':{'en': 'Telgua'},
'502599':{'en': 'Tigo'},
'502598':{'en': 'Telgua'},
'5511976':{'en': 'Claro BR'},
'5511975':{'en': 'Vivo'},
'5511974':{'en': 'Vivo'},
'5511973':{'en': 'Vivo'},
'5511972':{'en': 'Vivo'},
'5511971':{'en': 'Vivo'},
'554799658':{'en': 'TIM'},
'22466':{'en': 'Areeba'},
'22465':{'en': 'Cellcom'},
'22463':{'en': 'Intercel'},
'22462':{'en': 'Orange'},
'22460':{'en': 'Sotelgui'},
'551196914':{'en': 'Claro BR'},
'551196915':{'en': 'Claro BR'},
'551196916':{'en': 'Claro BR'},
'551196917':{'en': 'Claro BR'},
'551196910':{'en': 'Vivo'},
'551196911':{'en': 'Vivo'},
'551196912':{'en': 'Vivo'},
'26378':{'en': 'Econet'},
'26377':{'en': 'Econet'},
'26373':{'en': 'Telecel'},
'551196919':{'en': 'Claro BR'},
'26371':{'en': 'Net*One'},
'553299925':{'en': 'Telemig Celular'},
'5037800':{'en': 'Movistar'},
'5037801':{'en': 'Digicel'},
'5037803':{'en': 'Claro'},
'474791':{'en': 'Network Norway'},
'474790':{'en': 'Telenor'},
'474793':{'en': 'Network Norway'},
'474792':{'en': 'Network Norway'},
'5037808':{'en': 'Claro'},
'5037809':{'en': 'Claro'},
'553299921':{'en': 'Telemig Celular'},
'447910':{'en': 'EE'},
'447913':{'en': 'EE'},
'447912':{'en': 'O2'},
'447915':{'en': 'Three'},
'447914':{'en': 'EE'},
'447917':{'en': 'Vodafone'},
'447916':{'en': 'Three'},
'447919':{'en': 'Vodafone'},
'447918':{'en': 'Vodafone'},
'23846':{'en': 'CVMOVEL'},
'23843':{'en': 'T+'},
'554798900':{'en': 'Claro BR'},
'551899639':{'en': 'Vivo'},
'551899638':{'en': 'Vivo'},
'551899633':{'en': 'Vivo'},
'383459':{'en': 'vala'},
'551899631':{'en': 'Vivo'},
'551899637':{'en': 'Vivo'},
'551899636':{'en': 'Vivo'},
'551899635':{'en': 'Vivo'},
'267763':{'en': 'Orange'},
'553599809':{'en': 'Telemig Celular'},
'553599808':{'en': 'Telemig Celular'},
'553199642':{'en': 'Telemig Celular'},
'553599805':{'en': 'Telemig Celular'},
'553599804':{'en': 'Telemig Celular'},
'553599807':{'en': 'Telemig Celular'},
'553599806':{'en': 'Telemig Celular'},
'553599801':{'en': 'Telemig Celular'},
'30691700':{'en': 'Inter Telecom'},
'553599802':{'en': 'Telemig Celular'},
'553199646':{'en': 'Telemig Celular'},
'4915555':{'en': 'Tismi BV'},
'553598468':{'en': 'Claro BR'},
'383453':{'en': 'vala'},
'553598464':{'en': 'Claro BR'},
'553598465':{'en': 'Claro BR'},
'553598466':{'en': 'Claro BR'},
'267769':{'en': 'BTC Mobile/Orange'},
'553598461':{'en': 'Claro BR'},
'553598462':{'en': 'Claro BR'},
'553598463':{'en': 'Claro BR'},
'553199648':{'en': 'Telemig Celular'},
'5025313':{'en': 'Movistar'},
'5025312':{'en': 'Movistar'},
'551999652':{'en': 'Vivo'},
'35988':{'en': 'Mtel'},
'551999651':{'en': 'Vivo'},
'551999656':{'en': 'Vivo'},
'551999657':{'en': 'Vivo'},
'551999654':{'en': 'Vivo'},
'1784433':{'en': 'Digicel'},
'551999658':{'en': 'Vivo'},
'551999659':{'en': 'Vivo'},
'554398426':{'en': 'Brasil Telecom GSM'},
'553599943':{'en': 'Telemig Celular'},
'3469364':{'en': 'DIA'},
'3469365':{'en': 'Carrefour'},
'3469366':{'en': 'Carrefour'},
'3469367':{'en': 'MasMovil'},
'3469360':{'en': 'DIA'},
'3469361':{'en': 'DIA'},
'3469362':{'en': 'DIA'},
'3469363':{'en': 'DIA'},
'1784435':{'en': 'Digicel'},
'3469368':{'en': 'MasMovil'},
'3469369':{'en': 'MasMovil'},
'553599944':{'en': 'Telemig Celular'},
'551899681':{'en': 'Vivo'},
'45204':{'en': 'TDC'},
'45205':{'en': 'TDC'},
'45206':{'en': 'Telenor'},
'45207':{'en': 'Telenor'},
'551898146':{'en': 'TIM'},
'45201':{'en': 'TDC'},
'1787291':{'en': 'CENTENNIAL'},
'45203':{'en': 'TDC'},
'551898148':{'en': 'TIM'},
'35987':{'en': 'Vivacom'},
'45208':{'en': 'Telenor'},
'45209':{'en': 'Telenor'},
'1787299':{'en': 'SunCom Wireless Puerto Rico'},
'1869667':{'en': 'Cable & Wireless'},
'1242455':{'en': 'BaTelCo'},
'1869665':{'en': 'Cable & Wireless'},
'1869664':{'en': 'Cable & Wireless'},
'1869663':{'en': 'Cable & Wireless'},
'1869662':{'en': 'Cable & Wireless'},
'1869661':{'en': 'Cable & Wireless'},
'1869660':{'en': 'Cable & Wireless'},
'50370706':{'en': 'Tigo'},
'47950':{'en': 'Telenor'},
'1869669':{'en': 'Cable & Wireless'},
'1869668':{'en': 'Cable & Wireless'},
'47951':{'en': 'Telenor'},
'50370705':{'en': 'Claro'},
'1242453':{'en': 'BaTelCo'},
'551499169':{'en': 'Claro BR'},
'553899132':{'en': 'TIM'},
'553899133':{'en': 'TIM'},
'553899131':{'en': 'TIM'},
'553899136':{'en': 'TIM'},
'553899137':{'en': 'TIM'},
'553899134':{'en': 'TIM'},
'553899135':{'en': 'TIM'},
'553899138':{'en': 'TIM'},
'553899139':{'en': 'TIM'},
'212661':{'en': 'Maroc Telecom'},
'55429910':{'en': 'Vivo'},
'447757':{'en': 'EE'},
'447756':{'en': 'O2'},
'212660':{'en': u('M\u00e9ditel')},
'447753':{'en': 'O2'},
'447752':{'en': 'O2'},
'447751':{'en': 'O2'},
'447750':{'en': 'O2'},
'551298137':{'en': 'TIM'},
'447759':{'en': 'O2'},
'447758':{'en': 'EE'},
'33696':{'en': 'Bouygues'},
'551298136':{'en': 'TIM'},
'33692':{'en': 'Bouygues'},
'33693':{'en': 'Bouygues'},
'551398115':{'en': 'TIM'},
'551298131':{'en': 'TIM'},
'212664':{'en': u('M\u00e9ditel')},
'551398116':{'en': 'TIM'},
'33698':{'en': 'Bouygues'},
'33699':{'en': 'Bouygues'},
'551398117':{'en': 'TIM'},
'3068519':{'en': 'Cyta'},
'551298132':{'en': 'TIM'},
'5512991':{'en': 'Claro BR'},
'553398454':{'en': 'Claro BR'},
'551298138':{'en': 'TIM'},
'549249':{'en': 'Personal'},
'554599951':{'en': 'TIM'},
'549247':{'en': 'Personal'},
'554198401':{'en': 'Brasil Telecom GSM'},
'554198403':{'en': 'Brasil Telecom GSM'},
'554198402':{'en': 'Brasil Telecom GSM'},
'554198405':{'en': 'Brasil Telecom GSM'},
'554198404':{'en': 'Brasil Telecom GSM'},
'370642':{'en': u('BIT\u0116')},
'370643':{'en': u('BIT\u0116')},
'370640':{'en': u('BIT\u0116')},
'370641':{'en': u('BIT\u0116')},
'370646':{'en': 'Tele 2'},
'370647':{'en': 'Tele 2'},
'370644':{'en': u('BIT\u0116')},
'370645':{'en': 'Tele 2'},
'370648':{'en': 'Tele 2'},
'370649':{'en': u('BIT\u0116')},
'511997':{'en': 'Claro'},
'511996':{'en': 'Movistar'},
'511991':{'en': 'Claro'},
'474087':{'en': 'Telenor'},
'511993':{'en': 'Claro'},
'511992':{'en': 'Claro'},
'551999890':{'en': 'Vivo'},
'554398424':{'en': 'Brasil Telecom GSM'},
'554798432':{'en': 'Brasil Telecom GSM'},
'3468447':{'en': 'Quattre'},
'3468444':{'en': 'BT'},
'3468445':{'en': 'Ion mobile'},
'3468442':{'en': 'BluePhone'},
'3468443':{'en': 'BT'},
'3468440':{'en': 'Eurona'},
'3468441':{'en': 'Lemonvil'},
'554798438':{'en': 'Brasil Telecom GSM'},
'554798439':{'en': 'Brasil Telecom GSM'},
'3468448':{'en': 'Nethits'},
'551299240':{'en': 'Claro BR'},
'551299241':{'en': 'Claro BR'},
'551299242':{'en': 'Claro BR'},
'551299243':{'en': 'Claro BR'},
'551299244':{'en': 'Claro BR'},
'551299245':{'en': 'Claro BR'},
'553198244':{'en': 'Claro BR'},
'2346498':{'en': 'Starcomms'},
'553198240':{'en': 'Claro BR'},
'553198241':{'en': 'Claro BR'},
'553198242':{'en': 'Claro BR'},
'553198243':{'en': 'Claro BR'},
'2346491':{'en': 'Starcomms'},
'554199263':{'en': 'Vivo'},
'2346493':{'en': 'Starcomms'},
'2346492':{'en': 'Starcomms'},
'2346495':{'en': 'Starcomms'},
'2346494':{'en': 'Starcomms'},
'2346497':{'en': 'Starcomms'},
'2346496':{'en': 'Starcomms'},
'553399111':{'en': 'TIM'},
'515195158':{'en': 'Movistar'},
'553399113':{'en': 'TIM'},
'553399112':{'en': 'TIM'},
'553399115':{'en': 'TIM'},
'553399114':{'en': 'TIM'},
'553399117':{'en': 'TIM'},
'479317':{'en': 'NetCom'},
'515195151':{'en': 'Movistar'},
'515195150':{'en': 'Movistar'},
'515195153':{'en': 'Movistar'},
'515195152':{'en': 'Movistar'},
'515195155':{'en': 'Movistar'},
'515195154':{'en': 'Movistar'},
'515195157':{'en': 'Movistar'},
'515195156':{'en': 'Movistar'},
'35844':{'en': 'DNA'},
'35846':{'en': 'Elisa'},
'35841':{'en': 'DNA'},
'35840':{'en': 'Telia'},
'35842':{'en': 'Telia'},
'479237':{'en': 'NetCom'},
'4479117':{'en': 'JT'},
'354882':{'en': u('S\u00edminn')},
'4479110':{'en': 'Marathon Telecom'},
'4479112':{'en': '24 Seven'},
'4479118':{'en': '24 Seven'},
'354888':{'en': u('S\u00edminn')},
'551195472':{'en': 'Vivo'},
'551195473':{'en': 'Vivo'},
'551195474':{'en': 'Vivo'},
'553199796':{'en': 'Telemig Celular'},
'1787465':{'en': 'CENTENNIAL'},
'1787466':{'en': 'SunCom Wireless Puerto Rico'},
'1787460':{'en': 'SunCom Wireless Puerto Rico'},
'1787462':{'en': 'SunCom Wireless Puerto Rico'},
'1787463':{'en': 'SunCom Wireless Puerto Rico'},
'552198325':{'en': 'TIM'},
'4475328':{'en': 'Three'},
'4475329':{'en': 'Mobiweb'},
'4475326':{'en': 'Three'},
'4475327':{'en': 'Three'},
'4475325':{'en': 'SMSRelay AG'},
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'455018':{'en': 'Lebara Limited'},
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'455016':{'en': 'Lebara Limited'},
'455015':{'en': 'Lebara Limited'},
'4530':{'en': 'TDC'},
'479915':{'en': 'Telenor'},
'479916':{'en': 'Telenor'},
'515495981':{'en': 'Movistar'},
'515495980':{'en': 'Movistar'},
'515495982':{'en': 'Movistar'},
'515495985':{'en': 'Movistar'},
'515495984':{'en': 'Movistar'},
'515495987':{'en': 'Movistar'},
'515495986':{'en': 'Movistar'},
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'553199804':{'en': 'Telemig Celular'},
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'456093':{'en': 'Telenor'},
'456090':{'en': 'Lebara Limited'},
'456091':{'en': 'Telenor'},
'456096':{'en': 'Tripple Track Europe'},
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'456094':{'en': 'Telenor'},
'456095':{'en': 'Telenor'},
'456098':{'en': 'Telavox'},
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'352628':{'en': 'POST'},
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'502352':{'en': 'Movistar'},
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'553199756':{'en': 'Telemig Celular'},
'553199759':{'en': 'Telemig Celular'},
'553199758':{'en': 'Telemig Celular'},
'1767235':{'en': 'Cable & Wireless'},
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'24397':{'en': 'Zain'},
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'187646':{'en': 'Digicel'},
'187647':{'en': 'Digicel'},
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'1787916':{'en': 'CENTENNIAL'},
'1787917':{'en': 'CENTENNIAL'},
'1787912':{'en': 'CENTENNIAL'},
'5025544':{'en': 'Telgua'},
'5025543':{'en': 'Telgua'},
'23288':{'en': 'Africell'},
'234987':{'en': 'Starcomms'},
'38166':{'en': 'mts'},
'38161':{'en': 'VIP'},
'38160':{'en': 'VIP'},
'505839':{'en': 'Movistar'},
'38162':{'en': 'Telenor'},
'23280':{'en': 'Africell'},
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'505835':{'en': 'Claro'},
'38169':{'en': 'Telenor'},
'38168':{'en': 'VIP'},
'551198026':{'en': 'Oi'},
'551198027':{'en': 'Oi'},
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'551198029':{'en': 'Oi'},
'554199239':{'en': 'Vivo'},
'1345329':{'en': 'Digicel'},
'1345328':{'en': 'Digicel'},
'1345321':{'en': 'Digicel'},
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'234187':{'en': 'Starcomms'},
'234184':{'en': 'Starcomms'},
'234185':{'en': 'Starcomms'},
'234182':{'en': 'Starcomms'},
'234181':{'en': 'Starcomms'},
'447939':{'en': 'EE'},
'447932':{'en': 'EE'},
'447931':{'en': 'EE'},
'447930':{'en': 'EE'},
'447937':{'en': 'JT'},
'373782':{'en': 'Moldcell'},
'373783':{'en': 'Moldcell'},
'373780':{'en': 'Moldcell'},
'373781':{'en': 'Moldcell'},
'373786':{'en': 'Moldcell'},
'373787':{'en': 'Moldcell'},
'373784':{'en': 'Moldcell'},
'373785':{'en': 'Moldcell'},
'373788':{'en': 'Moldcell'},
'553599823':{'en': 'Telemig Celular'},
'553599822':{'en': 'Telemig Celular'},
'553599821':{'en': 'Telemig Celular'},
'553599827':{'en': 'Telemig Celular'},
'553599826':{'en': 'Telemig Celular'},
'553599825':{'en': 'Telemig Celular'},
'553599824':{'en': 'Telemig Celular'},
'553599829':{'en': 'Telemig Celular'},
'553599828':{'en': 'Telemig Celular'},
'553899158':{'en': 'TIM'},
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'4473780':{'en': 'Limitless'},
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'551999671':{'en': 'Vivo'},
'551999672':{'en': 'Vivo'},
'551999673':{'en': 'Vivo'},
'551999674':{'en': 'Vivo'},
'551999675':{'en': 'Vivo'},
'551999676':{'en': 'Vivo'},
'551999677':{'en': 'Vivo'},
'3469348':{'en': 'MasMovil'},
'3469349':{'en': 'MasMovil'},
'3469346':{'en': 'MasMovil'},
'3469347':{'en': 'MasMovil'},
'3469344':{'en': 'DIA'},
'3469345':{'en': 'MasMovil'},
'3469342':{'en': 'DIA'},
'3469343':{'en': 'DIA'},
'3469340':{'en': 'DIA'},
'3469341':{'en': 'DIA'},
'553898404':{'en': 'Claro BR'},
'30685585':{'en': 'Cyta'},
'553898407':{'en': 'Claro BR'},
'553898406':{'en': 'Claro BR'},
'5521996':{'en': 'Vivo'},
'5521997':{'en': 'Vivo'},
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'5521995':{'en': 'Vivo'},
'5521992':{'en': 'Claro BR'},
'5521993':{'en': 'Claro BR'},
'5521991':{'en': 'Claro BR'},
'5521998':{'en': 'Vivo'},
'5521999':{'en': 'Vivo'},
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'55429885':{'en': 'Claro BR'},
'55429884':{'en': 'Claro BR'},
'55429883':{'en': 'Claro BR'},
'55429882':{'en': 'Claro BR'},
'55429881':{'en': 'Claro BR'},
'55429880':{'en': 'Claro BR'},
'554398434':{'en': 'Brasil Telecom GSM'},
'554398435':{'en': 'Brasil Telecom GSM'},
'516796766':{'en': 'Movistar'},
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'1345529':{'en': 'Digicel'},
'516796765':{'en': 'Movistar'},
'1345527':{'en': 'Digicel'},
'1345526':{'en': 'Digicel'},
'1345525':{'en': 'Digicel'},
'516796769':{'en': 'Movistar'},
'553899118':{'en': 'TIM'},
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'551599164':{'en': 'Claro BR'},
'553899112':{'en': 'TIM'},
'553899113':{'en': 'TIM'},
'553899114':{'en': 'TIM'},
'553899115':{'en': 'TIM'},
'553899116':{'en': 'TIM'},
'553899117':{'en': 'TIM'},
'2344673':{'en': 'Starcomms'},
'447733':{'en': 'Vodafone'},
'447735':{'en': 'Three'},
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'447737':{'en': 'Three'},
'455250':{'en': 'YouSee'},
'517497871':{'en': 'Claro'},
'517497870':{'en': 'Claro'},
'517497873':{'en': 'Claro'},
'517497872':{'en': 'Claro'},
'517497875':{'en': 'Claro'},
'517497874':{'en': 'Claro'},
'517497877':{'en': 'Claro'},
'517497876':{'en': 'Claro'},
'447425':{'en': 'Vodafone'},
'1242481':{'en': 'BaTelCo'},
'2344677':{'en': 'Starcomms'},
'2344676':{'en': 'Starcomms'},
'2344675':{'en': 'Starcomms'},
'447393':{'en': 'Vodafone'},
'2344674':{'en': 'Starcomms'},
'447392':{'en': 'Vodafone'},
'447391':{'en': 'Vodafone'},
'549222':{'en': 'Personal'},
'549223':{'en': 'Personal'},
'549220':{'en': 'Personal'},
'549221':{'en': 'Personal'},
'549226':{'en': 'Personal'},
'549227':{'en': 'Personal'},
'549224':{'en': 'Personal'},
'549225':{'en': 'Personal'},
'551798806':{'en': 'Oi'},
'551798807':{'en': 'Oi'},
'549228':{'en': 'Personal'},
'549229':{'en': 'Personal'},
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'5522988':{'en': 'Oi'},
'5522989':{'en': 'Oi'},
'553398414':{'en': 'Claro BR'},
'553398412':{'en': 'Claro BR'},
'535':{'en': 'CUBACEL'},
'551499141':{'en': 'Claro BR'},
'23670':{'en': 'TC'},
'23672':{'en': 'Orange'},
'23675':{'en': 'CTP'},
'23677':{'en': 'Nationlink'},
'553598447':{'en': 'Claro BR'},
'370660':{'en': u('BIT\u0116')},
'553598444':{'en': 'Claro BR'},
'370662':{'en': 'Omnitel'},
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'256730':{'en': 'K2'},
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'551699781':{'en': 'Vivo'},
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'551699783':{'en': 'Vivo'},
'551699782':{'en': 'Vivo'},
'551699788':{'en': 'Vivo'},
'554798418':{'en': 'Brasil Telecom GSM'},
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'4473979':{'en': 'Three'},
'4473978':{'en': 'Three'},
'4474529':{'en': 'Three'},
'4474528':{'en': 'Three'},
'4473975':{'en': 'Three'},
'554798411':{'en': 'Brasil Telecom GSM'},
'4473977':{'en': 'Three'},
'4473976':{'en': 'Three'},
'4473971':{'en': 'Three'},
'4473970':{'en': 'Three'},
'4473973':{'en': 'Three'},
'4473972':{'en': 'Three'},
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'34626':{'en': 'Movistar'},
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'554199242':{'en': 'Vivo'},
'34625':{'en': 'Orange'},
'34622':{'en': 'Yoigo'},
'554199245':{'en': 'Vivo'},
'34620':{'en': 'Movistar'},
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'554199248':{'en': 'Vivo'},
'554199249':{'en': 'Vivo'},
'34628':{'en': 'Movistar'},
'34629':{'en': 'Movistar'},
'553399137':{'en': 'TIM'},
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'553399139':{'en': 'TIM'},
'553399138':{'en': 'TIM'},
'554799998':{'en': 'TIM'},
'3474443':{'en': 'InfoVOIP'},
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'2347691':{'en': 'Starcomms'},
'2347692':{'en': 'Starcomms'},
'2347693':{'en': 'Starcomms'},
'2347694':{'en': 'Starcomms'},
'2347695':{'en': 'Starcomms'},
'2347696':{'en': 'Starcomms'},
'2347697':{'en': 'Starcomms'},
'551298179':{'en': 'TIM'},
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'551298171':{'en': 'TIM'},
'551298173':{'en': 'TIM'},
'551298172':{'en': 'TIM'},
'551298175':{'en': 'TIM'},
'551298174':{'en': 'TIM'},
'551298177':{'en': 'TIM'},
'551298176':{'en': 'TIM'},
'1787447':{'en': 'CENTENNIAL'},
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'553199179':{'en': 'TIM'},
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'551698122':{'en': 'TIM'},
'551698123':{'en': 'TIM'},
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'1787448':{'en': 'CENTENNIAL'},
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'447894':{'en': 'O2'},
'447895':{'en': 'O2'},
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'447890':{'en': 'Orange'},
'447891':{'en': 'Orange'},
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'3464529':{'en': 'MasMovil'},
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'447899':{'en': 'Vodafone'},
'553799943':{'en': 'Telemig Celular'},
'554198469':{'en': 'Brasil Telecom GSM'},
'553798413':{'en': 'Claro BR'},
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'26263902':{'en': 'Orange'},
'33601':{'en': 'SFR'},
'26263905':{'en': 'Only'},
'479620':{'en': 'Telenor'},
'306999':{'en': 'Wind'},
'306998':{'en': 'Wind'},
'306997':{'en': 'Wind'},
'306996':{'en': 'Wind'},
'306995':{'en': 'Wind'},
'306994':{'en': 'Wind'},
'306993':{'en': 'Wind'},
'306992':{'en': 'Wind'},
'306991':{'en': 'Wind'},
'4915630':{'en': 'Multiconnect'},
'553199718':{'en': 'Telemig Celular'},
'553199829':{'en': 'Telemig Celular'},
'553199828':{'en': 'Telemig Celular'},
'346122':{'en': 'Lycamobile'},
'51659656':{'en': 'Movistar'},
'346120':{'en': 'Syma'},
'346121':{'en': 'Syma'},
'553199823':{'en': 'Telemig Celular'},
'553199822':{'en': 'Telemig Celular'},
'346124':{'en': 'Lycamobile'},
'346125':{'en': 'Lycamobile'},
'554399930':{'en': 'TIM'},
'554399931':{'en': 'TIM'},
'554399932':{'en': 'TIM'},
'554399933':{'en': 'TIM'},
'554399934':{'en': 'TIM'},
'554399935':{'en': 'TIM'},
'554399936':{'en': 'TIM'},
'554399937':{'en': 'TIM'},
'554399938':{'en': 'TIM'},
'554399939':{'en': 'TIM'},
'55469881':{'en': 'Claro BR'},
'553399955':{'en': 'Telemig Celular'},
'553399954':{'en': 'Telemig Celular'},
'553399957':{'en': 'Telemig Celular'},
'553399956':{'en': 'Telemig Celular'},
'553399951':{'en': 'Telemig Celular'},
'553399953':{'en': 'Telemig Celular'},
'553399952':{'en': 'Telemig Celular'},
'18686':{'en': 'bmobile'},
'553399959':{'en': 'Telemig Celular'},
'553399958':{'en': 'Telemig Celular'},
'553199714':{'en': 'Telemig Celular'},
'552198379':{'en': 'TIM'},
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'553799186':{'en': 'TIM'},
'553199777':{'en': 'Telemig Celular'},
'553199776':{'en': 'Telemig Celular'},
'553199775':{'en': 'Telemig Celular'},
'553199774':{'en': 'Telemig Celular'},
'553199773':{'en': 'Telemig Celular'},
'553199772':{'en': 'Telemig Celular'},
'553199771':{'en': 'Telemig Celular'},
'553199779':{'en': 'Telemig Celular'},
'553199778':{'en': 'Telemig Celular'},
'180948':{'en': 'Claro'},
'180949':{'en': 'Claro'},
'5037798':{'en': 'Tigo'},
'5037799':{'en': 'Tigo'},
'5037794':{'en': 'Movistar'},
'180941':{'en': 'Viva'},
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'180943':{'en': 'Viva'},
'180944':{'en': 'Viva'},
'180945':{'en': 'Claro'},
'2985':{'en': 'Vodafone'},
'180947':{'en': 'Tricom'},
'4477449':{'en': 'Core Communication'},
'4477448':{'en': 'Core Communication'},
'4477443':{'en': 'Core Communication'},
'4477442':{'en': 'Core Communication'},
'4477445':{'en': 'Core Communication'},
'4477444':{'en': 'Core Communication'},
'4477447':{'en': 'Core Communication'},
'4477446':{'en': 'Core Communication'},
'1787937':{'en': 'CENTENNIAL'},
'1787935':{'en': 'CENTENNIAL'},
'1787933':{'en': 'CENTENNIAL'},
'552198375':{'en': 'TIM'},
'549358':{'en': 'Personal'},
'505859':{'en': 'Movistar'},
'505858':{'en': 'Movistar'},
'505851':{'en': 'Claro'},
'505850':{'en': 'Claro'},
'505853':{'en': 'Claro'},
'505852':{'en': 'Claro'},
'505855':{'en': 'Movistar'},
'505854':{'en': 'Claro'},
'505857':{'en': 'Movistar'},
'505856':{'en': 'Movistar'},
'517396873':{'en': 'Claro'},
'517396872':{'en': 'Claro'},
'517396871':{'en': 'Claro'},
'517396870':{'en': 'Claro'},
'517396877':{'en': 'Claro'},
'517396876':{'en': 'Claro'},
'517396875':{'en': 'Claro'},
'517396879':{'en': 'Claro'},
'517396878':{'en': 'Claro'},
'553199364':{'en': 'TIM'},
'4475599':{'en': 'Resilient'},
'4475598':{'en': 'Nodemax'},
'553199365':{'en': 'TIM'},
'4475595':{'en': 'Confabulate'},
'4475594':{'en': 'Truphone'},
'4475597':{'en': 'Core Telecom'},
'4475596':{'en': 'Lleida.net'},
'4475591':{'en': 'LegendTel'},
'4475590':{'en': 'Mars'},
'4475593':{'en': 'Globecom'},
'4475592':{'en': 'IPV6'},
'553499811':{'en': 'Telemig Celular'},
'553499813':{'en': 'Telemig Celular'},
'549351':{'en': 'Personal'},
'553499815':{'en': 'Telemig Celular'},
'47468':{'en': 'Telenor'},
'553499817':{'en': 'Telemig Celular'},
'553499816':{'en': 'Telemig Celular'},
'35476':{'en': 'Nova'},
'35477':{'en': 'Nova'},
'35478':{'en': 'Nova'},
'35479':{'en': 'Nova'},
'516196173':{'en': 'Claro'},
'516196172':{'en': 'Claro'},
'516196175':{'en': 'Claro'},
'516196174':{'en': 'Claro'},
'42073':{'en': 'T-Mobile'},
'55479922':{'en': 'Vivo'},
'55129962':{'en': 'Vivo'},
'55129961':{'en': 'Vivo'},
'55129960':{'en': 'Vivo'},
'503702':{'en': 'Claro'},
'514494808':{'en': 'Claro'},
'514494809':{'en': 'Claro'},
'514494806':{'en': 'Claro'},
'514494807':{'en': 'Claro'},
'389734':{'en': 'Vip'},
'514494805':{'en': 'Claro'},
'389732':{'en': 'Vip'},
'389733':{'en': 'Telekom'},
'514494801':{'en': 'Movistar'},
'553199612':{'en': 'Telemig Celular'},
'231330':{'en': 'West Africa Telecom'},
'553199613':{'en': 'Telemig Celular'},
'124626':{'en': 'Digicel'},
'124624':{'en': 'LIME'},
'124623':{'en': 'LIME'},
'124628':{'en': 'LIME'},
'3469329':{'en': 'Orange'},
'551899777':{'en': 'Vivo'},
'3469320':{'en': 'Carrefour'},
'3469321':{'en': 'Carrefour'},
'21270':{'en': 'Inwi'},
'21277':{'en': u('M\u00e9ditel')},
'21276':{'en': 'Maroc Telecom'},
'553499199':{'en': 'TIM'},
'551899772':{'en': 'Vivo'},
'551899773':{'en': 'Vivo'},
'358438':{'en': 'DNA'},
'358436':{'en': 'DNA'},
'551899771':{'en': 'Vivo'},
'459228':{'en': 'Mundio Mobile'},
'459229':{'en': 'Beepsend AB'},
'45538':{'en': '3'},
'45539':{'en': 'CBB Mobil'},
'459224':{'en': 'SimService'},
'45537':{'en': '3'},
'45534':{'en': 'Telia'},
'459227':{'en': 'Mundio Mobile'},
'459220':{'en': 'Telenor Connexion AB'},
'459221':{'en': 'SimService'},
'459222':{'en': 'Bolignet-Aarhus F.M.B.A.'},
'45531':{'en': 'CBB Mobil'},
'254748':{'en': 'Safaricom'},
'254749':{'en': 'WiAfrica'},
'554398418':{'en': 'Brasil Telecom GSM'},
'554398419':{'en': 'Brasil Telecom GSM'},
'254742':{'en': 'Safaricom'},
'254743':{'en': 'Safaricom'},
'254740':{'en': 'Safaricom'},
'254741':{'en': 'Safaricom'},
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'447873':{'en': 'O2'},
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'552899952':{'en': 'Vivo'},
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'551196169':{'en': 'Claro BR'},
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'240222':{'en': 'GETESA'},
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'554198447':{'en': 'Brasil Telecom GSM'},
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'553199843':{'en': 'Telemig Celular'},
'553199842':{'en': 'Telemig Celular'},
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'554699115':{'en': 'Vivo'},
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'553399978':{'en': 'Telemig Celular'},
'553399973':{'en': 'Telemig Celular'},
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'553399976':{'en': 'Telemig Celular'},
'553399975':{'en': 'Telemig Celular'},
'553399974':{'en': 'Telemig Celular'},
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'517497999':{'en': 'Movistar'},
'517497996':{'en': 'Movistar'},
'517497997':{'en': 'Movistar'},
'517497992':{'en': 'Movistar'},
'517497993':{'en': 'Movistar'},
'517497990':{'en': 'Movistar'},
'517497991':{'en': 'Movistar'},
'1268729':{'en': 'APUA'},
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'1767276':{'en': 'Cable & Wireless'},
'1767275':{'en': 'Cable & Wireless'},
'553199715':{'en': 'Telemig Celular'},
'1268722':{'en': 'Digicel'},
'1268721':{'en': 'Digicel'},
'1268720':{'en': 'Digicel'},
'1268727':{'en': 'APUA'},
'1268726':{'en': 'Digicel'},
'1268725':{'en': 'Digicel'},
'1268724':{'en': 'Digicel'},
'180922':{'en': 'Claro'},
'180923':{'en': 'Claro'},
'180920':{'en': 'Tricom'},
'180926':{'en': 'Claro'},
'180927':{'en': 'Claro'},
'180924':{'en': 'Claro'},
'180925':{'en': 'Claro'},
'180928':{'en': 'Claro'},
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'554799240':{'en': 'Vivo'},
'554799241':{'en': 'Vivo'},
'554799246':{'en': 'Vivo'},
'554799244':{'en': 'Vivo'},
'554799245':{'en': 'Vivo'},
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'1242727':{'en': 'BaTelCo'},
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'1787952':{'en': 'CENTENNIAL'},
'1787953':{'en': 'CENTENNIAL'},
'1787954':{'en': 'CENTENNIAL'},
'1787957':{'en': 'CENTENNIAL'},
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'447508':{'en': 'EE'},
'447506':{'en': 'EE'},
'447507':{'en': 'EE'},
'447504':{'en': 'EE'},
'447505':{'en': 'EE'},
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'447503':{'en': 'Vodafone'},
'447500':{'en': 'Vodafone'},
'447501':{'en': 'Vodafone'},
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'505871':{'en': 'Claro'},
'505870':{'en': 'Claro'},
'505877':{'en': 'Movistar'},
'505876':{'en': 'Movistar'},
'505875':{'en': 'Movistar'},
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'505879':{'en': 'Movistar'},
'505878':{'en': 'Movistar'},
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'22571':{'en': 'Moov'},
'22575':{'en': 'MTN'},
'22574':{'en': 'MTN'},
'22577':{'en': 'Orange'},
'22576':{'en': 'MTN'},
'45411':{'en': 'Telenor'},
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'516196155':{'en': 'Movistar'},
'516196154':{'en': 'Movistar'},
'516196153':{'en': 'Movistar'},
'45413':{'en': 'Telenor'},
'516196151':{'en': 'Movistar'},
'516196150':{'en': 'Movistar'},
'23357':{'en': 'tiGO'},
'23354':{'en': 'MTN'},
'4476243':{'en': 'Manx Telecom'},
'553299924':{'en': 'Telemig Celular'},
'23350':{'en': 'Vodafone'},
'552899257':{'en': 'Claro BR'},
'45415':{'en': 'Telenor'},
'552899254':{'en': 'Claro BR'},
'4476246':{'en': 'Manx Telecom'},
'552899252':{'en': 'Claro BR'},
'45419':{'en': 'Telenor'},
'45418':{'en': 'Telenor'},
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'553199654':{'en': 'Telemig Celular'},
'553199655':{'en': 'Telemig Celular'},
'553598475':{'en': 'Claro BR'},
'553199656':{'en': 'Telemig Celular'},
'552498123':{'en': 'TIM'},
'553199657':{'en': 'Telemig Celular'},
'262692':{'en': 'SFR'},
'554399112':{'en': 'Vivo'},
'553199652':{'en': 'Telemig Celular'},
'552299104':{'en': 'Claro BR'},
'553199653':{'en': 'Telemig Celular'},
'553199391':{'en': 'TIM'},
'389718':{'en': 'T-Mobile'},
'389719':{'en': 'T-Mobile'},
'554399111':{'en': 'Vivo'},
'389711':{'en': 'T-Mobile'},
'389712':{'en': 'T-Mobile'},
'389713':{'en': 'T-Mobile'},
'389714':{'en': 'T-Mobile'},
'389715':{'en': 'T-Mobile'},
'389716':{'en': 'T-Mobile'},
'389717':{'en': 'T-Mobile'},
'554399114':{'en': 'Vivo'},
'554399115':{'en': 'Vivo'},
'553199659':{'en': 'Telemig Celular'},
'551999634':{'en': 'Vivo'},
'551999635':{'en': 'Vivo'},
'551999636':{'en': 'Vivo'},
'551999637':{'en': 'Vivo'},
'551999631':{'en': 'Vivo'},
'551999632':{'en': 'Vivo'},
'551999633':{'en': 'Vivo'},
'551999638':{'en': 'Vivo'},
'551999639':{'en': 'Vivo'},
'515695622':{'en': 'Claro'},
'515695623':{'en': 'Claro'},
'515695620':{'en': 'Claro'},
'515695621':{'en': 'Claro'},
'515695626':{'en': 'Claro'},
'515695624':{'en': 'Claro'},
'515695625':{'en': 'Claro'},
'124645':{'en': 'Sunbeach Communications'},
'1868269':{'en': 'bmobile'},
'1868266':{'en': 'bmobile'},
'1868267':{'en': 'bmobile'},
'553899111':{'en': 'TIM'},
'506573':{'en': 'OMV'},
'506572':{'en': 'OMV'},
'506571':{'en': 'OMV'},
'506570':{'en': 'OMV'},
'37533':{'be': u('\u041c\u0422\u0421'), 'en': 'MTS', 'ru': u('\u041c\u0422\u0421')},
'45514':{'en': 'TDC'},
'358458':{'en': 'Elisa'},
'4476637':{'en': 'Vodafone'},
'4476636':{'en': 'Relax'},
'45511':{'en': 'TDC'},
'45512':{'en': 'TDC'},
'45513':{'en': 'TDC'},
'358451':{'en': 'Elisa'},
'358450':{'en': 'Telia'},
'358453':{'en': 'Elisa'},
'358452':{'en': 'Elisa'},
'45518':{'en': 'TDC'},
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'455242':{'en': 'CBB Mobil'},
'455240':{'en': 'YouSee'},
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'455244':{'en': 'CBB Mobil'},
'1242446':{'en': 'BaTelCo'},
'515495800':{'en': 'Movistar'},
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'515495802':{'en': 'Movistar'},
'515495803':{'en': 'Movistar'},
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'517697604':{'en': 'Movistar'},
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'517697606':{'en': 'Movistar'},
'517697600':{'en': 'Movistar'},
'517697601':{'en': 'Movistar'},
'517697602':{'en': 'Movistar'},
'517697603':{'en': 'Movistar'},
'3469302':{'en': 'MasMovil'},
'3469303':{'en': 'MasMovil'},
'3469300':{'en': 'MasMovil'},
'3469301':{'en': 'MasMovil'},
'3469306':{'en': 'MasMovil'},
'3469304':{'en': 'MasMovil'},
'3469305':{'en': 'MasMovil'},
'25293':{'en': 'STG'},
'1242448':{'en': 'BaTelCo'},
'1242449':{'en': 'BaTelCo'},
'551698159':{'en': 'TIM'},
'324661':{'en': 'Lycamobile'},
'324660':{'en': 'Lycamobile'},
'324663':{'en': 'Lycamobile'},
'324662':{'en': 'Lycamobile'},
'324665':{'en': 'Vectone'},
'324664':{'en': 'Lycamobile'},
'324667':{'en': 'Vectone'},
'324666':{'en': 'Vectone'},
'324669':{'en': 'Voxbone SA'},
'551298122':{'en': 'TIM'},
'551298123':{'en': 'TIM'},
'254764':{'en': 'Finserve'},
'254765':{'en': 'Finserve'},
'254766':{'en': 'Finserve'},
'254767':{'en': 'Sema Mobile'},
'254760':{'en': 'Mobile Pay'},
'254761':{'en': 'Airtel'},
'254762':{'en': 'Airtel'},
'254763':{'en': 'Finserve'},
'554599929':{'en': 'TIM'},
'254768':{'en': 'Airtel'},
'254769':{'en': 'Airtel'},
'375298':{'be': u('\u041c\u0422\u0421'), 'en': 'MTS', 'ru': u('\u041c\u0422\u0421')},
'375299':{'be': 'Velcom', 'en': 'Velcom', 'ru': 'Velcom'},
'47478':{'en': 'Telenor'},
'375292':{'be': u('\u041c\u0422\u0421'), 'en': 'MTS', 'ru': u('\u041c\u0422\u0421')},
'375293':{'be': 'Velcom', 'en': 'Velcom', 'ru': 'Velcom'},
'375291':{'be': 'Velcom', 'en': 'Velcom', 'ru': 'Velcom'},
'375296':{'be': 'Velcom', 'en': 'Velcom', 'ru': 'Velcom'},
'375297':{'be': u('\u041c\u0422\u0421'), 'en': 'MTS', 'ru': u('\u041c\u0422\u0421')},
'47473':{'en': 'Tele2'},
'375295':{'be': u('\u041c\u0422\u0421'), 'en': 'MTS', 'ru': u('\u041c\u0422\u0421')},
'554599925':{'en': 'TIM'},
'2348382':{'en': 'Starcomms'},
'2348381':{'en': 'Starcomms'},
'2348380':{'en': 'Starcomms'},
'551298129':{'en': 'TIM'},
'554198412':{'en': 'Brasil Telecom GSM'},
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'447871':{'en': 'O2'},
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'551699743':{'en': 'Vivo'},
'551699742':{'en': 'Vivo'},
'551699745':{'en': 'Vivo'},
'551699744':{'en': 'Vivo'},
'551699747':{'en': 'Vivo'},
'551699746':{'en': 'Vivo'},
'551699749':{'en': 'Vivo'},
'551699748':{'en': 'Vivo'},
'231555':{'en': 'Novafone'},
'554798454':{'en': 'Brasil Telecom GSM'},
'554798455':{'en': 'Brasil Telecom GSM'},
'55419910':{'en': 'Vivo'},
'554798457':{'en': 'Brasil Telecom GSM'},
'554798451':{'en': 'Brasil Telecom GSM'},
'554798452':{'en': 'Brasil Telecom GSM'},
'554798453':{'en': 'Brasil Telecom GSM'},
'31636':{'en': 'Tele2'},
'31637':{'en': 'Teleena (MVNE)'},
'31634':{'en': 'T-Mobile'},
'31633':{'en': 'Telfort'},
'31630':{'en': 'KPN'},
'31631':{'en': 'Vodafone Libertel B.V.'},
'554199208':{'en': 'Vivo'},
'554199209':{'en': 'Vivo'},
'554199204':{'en': 'Vivo'},
'554199205':{'en': 'Vivo'},
'554199206':{'en': 'Vivo'},
'554199207':{'en': 'Vivo'},
'554199201':{'en': 'Vivo'},
'554199202':{'en': 'Vivo'},
'554199203':{'en': 'Vivo'},
'34669':{'en': 'Movistar'},
'514194188':{'en': 'Movistar'},
'514194189':{'en': 'Movistar'},
'34662':{'en': 'Vodafone'},
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'34660':{'en': 'Movistar'},
'34661':{'en': 'Vodafone'},
'34666':{'en': 'Vodafone'},
'34667':{'en': 'Vodafone'},
'34664':{'en': 'Vodafone'},
'34665':{'en': 'Orange'},
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'22504':{'en': 'MTN'},
'22505':{'en': 'MTN'},
'22506':{'en': 'MTN'},
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'22501':{'en': 'Moov'},
'22502':{'en': 'Moov'},
'22503':{'en': 'Moov'},
'22508':{'en': 'Orange'},
'22509':{'en': 'Orange'},
'267766':{'en': 'Mascom'},
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'267765':{'en': 'Orange'},
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'383458':{'en': 'vala'},
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'267761':{'en': 'Mascom'},
'383455':{'en': 'Z Mobile'},
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'383457':{'en': 'vala'},
'383456':{'en': 'Z Mobile'},
'383451':{'en': 'vala'},
'267768':{'en': 'BTC Mobile'},
'383452':{'en': 'vala'},
'517297292':{'en': 'Movistar'},
'517297291':{'en': 'Movistar'},
'517297290':{'en': 'Movistar'},
'517297297':{'en': 'Movistar'},
'517297296':{'en': 'Movistar'},
'5025311':{'en': 'Telgua'},
'5025310':{'en': 'Telgua'},
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'2347386':{'en': 'Starcomms'},
'2347387':{'en': 'Starcomms'},
'2347384':{'en': 'Starcomms'},
'2347385':{'en': 'Starcomms'},
'2347382':{'en': 'Starcomms'},
'2347383':{'en': 'Starcomms'},
'2347380':{'en': 'Starcomms'},
'2347381':{'en': 'Starcomms'},
'551298139':{'en': 'TIM'},
'26771':{'en': 'Mascom'},
'551698166':{'en': 'TIM'},
'551698167':{'en': 'TIM'},
'551698164':{'en': 'TIM'},
'551698165':{'en': 'TIM'},
'551698162':{'en': 'TIM'},
'551698163':{'en': 'TIM'},
'554198407':{'en': 'Brasil Telecom GSM'},
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'554198409':{'en': 'Brasil Telecom GSM'},
'553199782':{'en': 'Telemig Celular'},
'1787400':{'en': 'CENTENNIAL'},
'551698168':{'en': 'TIM'},
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'447859':{'en': 'Three'},
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'447853':{'en': 'Three'},
'447854':{'en': 'Orange'},
'447855':{'en': 'Orange'},
'5514997':{'en': 'Vivo'},
'553399123':{'en': 'TIM'},
'515295299':{'en': 'Movistar'},
'515295298':{'en': 'Movistar'},
'515295297':{'en': 'Movistar'},
'515295296':{'en': 'Movistar'},
'515295295':{'en': 'Movistar'},
'515295294':{'en': 'Movistar'},
'515295293':{'en': 'Movistar'},
'515295292':{'en': 'Movistar'},
'25235':{'en': 'AirSom'},
'25239':{'en': 'AirSom'},
'552799281':{'en': 'Claro BR'},
'552799282':{'en': 'Claro BR'},
'552799283':{'en': 'Claro BR'},
'552799284':{'en': 'Claro BR'},
'552799285':{'en': 'Claro BR'},
'552799286':{'en': 'Claro BR'},
'552799287':{'en': 'Claro BR'},
'552799288':{'en': 'Claro BR'},
'552799289':{'en': 'Claro BR'},
'4915678':{'en': 'Argon Networks'},
'1939201':{'en': 'CENTENNIAL'},
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'551799745':{'en': 'Vivo'},
'551298135':{'en': 'TIM'},
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'553799942':{'en': 'Telemig Celular'},
'356989':{'en': 'Vodafone'},
'553799941':{'en': 'Telemig Celular'},
'553799946':{'en': 'Telemig Celular'},
'553799947':{'en': 'Telemig Celular'},
'553799944':{'en': 'Telemig Celular'},
'553799945':{'en': 'Telemig Celular'},
'553799948':{'en': 'Telemig Celular'},
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'553199861':{'en': 'Telemig Celular'},
'553199867':{'en': 'Telemig Celular'},
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'553199732':{'en': 'Telemig Celular'},
'553199731':{'en': 'Telemig Celular'},
'30690200':{'en': 'MI Carrier Services'},
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'553199735':{'en': 'Telemig Celular'},
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'17873191':{'en': 'Claro'},
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'502515':{'en': 'Tigo'},
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'502516':{'en': 'Tigo'},
'502511':{'en': 'Telgua'},
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'51619619':{'en': 'Movistar'},
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'447522':{'en': 'O2'},
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'447526':{'en': 'O2'},
'447527':{'en': 'Orange'},
'505899':{'en': 'Movistar'},
'505898':{'en': 'Movistar'},
'505895':{'en': 'Movistar'},
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'505897':{'en': 'Movistar'},
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'554799996':{'en': 'TIM'},
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'3519234':{'en': 'Vectone'},
'3519232':{'en': 'Vectone'},
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'3519230':{'en': 'Vectone'},
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'551498118':{'en': 'TIM'},
'4474178':{'en': 'Truphone'},
'4474179':{'en': 'Core Telecom'},
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'4474174':{'en': 'Lycamobile'},
'4474175':{'en': 'Lycamobile'},
'551498113':{'en': 'TIM'},
'551498112':{'en': 'TIM'},
'551498115':{'en': 'TIM'},
'4474171':{'en': 'CardBoardFish'},
'4474172':{'en': 'Core Telecom'},
'4474173':{'en': 'Lycamobile'},
'552299101':{'en': 'Claro BR'},
'552299102':{'en': 'Claro BR'},
'552299103':{'en': 'Claro BR'},
'516796772':{'en': 'Claro'},
'552299105':{'en': 'Claro BR'},
'554198424':{'en': 'Brasil Telecom GSM'},
'551698803':{'en': 'Oi'},
'551698805':{'en': 'Oi'},
'551698804':{'en': 'Oi'},
'551698807':{'en': 'Oi'},
'551698806':{'en': 'Oi'},
'551698809':{'en': 'Oi'},
'551698808':{'en': 'Oi'},
'554198423':{'en': 'Brasil Telecom GSM'},
'551899775':{'en': 'Vivo'},
'4915080':{'en': 'Easy World'},
'55129923':{'en': 'Claro BR'},
'55129922':{'en': 'Claro BR'},
'55129921':{'en': 'Claro BR'},
'55129920':{'en': 'Claro BR'},
'389772':{'en': 'Vip'},
'389773':{'en': 'Vip'},
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'389776':{'en': 'Vip'},
'389777':{'en': 'Vip'},
'389774':{'en': 'Vip'},
'389775':{'en': 'Vip'},
'389778':{'en': 'Vip'},
'389779':{'en': 'Vip'},
'4915888':{'en': 'TelcoVillage'},
'4476433':{'en': 'Yim Siam'},
'356988':{'en': 'GO Mobile'},
'553199298':{'en': 'TIM'},
'553199299':{'en': 'TIM'},
'356981':{'en': 'Redtouch Fone'},
'553199295':{'en': 'TIM'},
'553199296':{'en': 'TIM'},
'553199297':{'en': 'TIM'},
'553199291':{'en': 'TIM'},
'553199292':{'en': 'TIM'},
'553199293':{'en': 'TIM'},
'1939214':{'en': 'CENTENNIAL'},
'5531985':{'en': 'Oi'},
'5531986':{'en': 'Oi'},
'5531987':{'en': 'Oi'},
'554799935':{'en': 'TIM'},
'55439996':{'en': 'TIM'},
'5531983':{'en': 'Claro BR'},
'30695200':{'en': 'Compatel'},
'5531988':{'en': 'Oi'},
'5531989':{'en': 'Oi'},
'1787219':{'en': 'Claro'},
'1787218':{'en': 'Claro'},
'1787217':{'en': 'Claro'},
'1787216':{'en': 'Claro'},
'1787215':{'en': 'Claro'},
'1787214':{'en': 'Claro'},
'1787213':{'en': 'Claro'},
'1787212':{'en': 'Claro'},
'1787210':{'en': 'SunCom Wireless Puerto Rico'},
'5119807':{'en': 'Claro'},
'5119806':{'en': 'Claro'},
'5119805':{'en': 'Claro'},
'553898419':{'en': 'Claro BR'},
'1345549':{'en': 'Digicel'},
'1345548':{'en': 'Digicel'},
'5119801':{'en': 'Movistar'},
'1345547':{'en': 'Digicel'},
'1345546':{'en': 'Digicel'},
'455262':{'en': 'CBB Mobil'},
'5119808':{'en': 'Claro'},
'553499217':{'en': 'TIM'},
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'553499215':{'en': 'TIM'},
'553499214':{'en': 'TIM'},
'553499213':{'en': 'TIM'},
'553499212':{'en': 'TIM'},
'553499211':{'en': 'TIM'},
'553499218':{'en': 'TIM'},
'26263919':{'en': 'Only'},
'553798408':{'en': 'Claro BR'},
'553798409':{'en': 'Claro BR'},
'553798404':{'en': 'Claro BR'},
'553798405':{'en': 'Claro BR'},
'26263911':{'en': 'SFR'},
'26263910':{'en': 'SFR'},
'459118':{'en': 'Companymobile'},
'553798402':{'en': 'Claro BR'},
'553798403':{'en': 'Claro BR'},
'5119803':{'en': 'Movistar'},
'5119802':{'en': 'Movistar'},
'459112':{'en': 'SimService'},
'459113':{'en': 'SimService'},
'455266':{'en': 'CBB Mobil'},
'2348490':{'en': 'Starcomms'},
'554698823':{'en': 'Claro BR'},
'459116':{'en': 'Companymobile'},
'553398407':{'en': 'Claro BR'},
'47454':{'en': 'NetCom'},
'459114':{'en': 'SimService'},
'48724':{'en': 'Plus'},
'48725':{'en': 'Plus'},
'48726':{'en': 'Plus'},
'459115':{'en': 'Companymobile'},
'48721':{'en': 'Plus'},
'48722':{'en': 'Plus'},
'48723':{'en': 'Plus'},
'551799701':{'en': 'Vivo'},
'551197089':{'en': 'Vivo'},
'551699767':{'en': 'Vivo'},
'551699766':{'en': 'Vivo'},
'551699765':{'en': 'Vivo'},
'551699764':{'en': 'Vivo'},
'551699763':{'en': 'Vivo'},
'551699762':{'en': 'Vivo'},
'551699761':{'en': 'Vivo'},
'551699769':{'en': 'Vivo'},
'551699768':{'en': 'Vivo'},
'553199322':{'en': 'TIM'},
'551799706':{'en': 'Vivo'},
'31614':{'en': 'T-Mobile'},
'31615':{'en': 'Vodafone Libertel B.V.'},
'31616':{'en': 'Telfort'},
'31617':{'en': 'Telfort'},
'31610':{'en': 'KPN'},
'31611':{'en': 'Vodafone Libertel B.V.'},
'31612':{'en': 'KPN'},
'31613':{'en': 'KPN'},
'552899982':{'en': 'Vivo'},
'552899983':{'en': 'Vivo'},
'552899981':{'en': 'Vivo'},
'552899986':{'en': 'Vivo'},
'552899987':{'en': 'Vivo'},
'552899984':{'en': 'Vivo'},
'552899985':{'en': 'Vivo'},
'389787':{'en': 'Vip'},
'551799707':{'en': 'Vivo'},
'516496490':{'en': 'Movistar'},
'34640':{'en': 'Orange'},
'554598813':{'en': 'Claro BR'},
'34642':{'en': 'DigiMobil'},
'389784':{'en': 'Vip'},
'34644':{'en': 'Simyo'},
'34645':{'en': 'Orange'},
'34646':{'en': 'Movistar'},
'34647':{'en': 'Vodafone'},
'34648':{'en': 'Movistar'},
'34649':{'en': 'Movistar'},
'554598818':{'en': 'Claro BR'},
'554598819':{'en': 'Claro BR'},
'553299118':{'en': 'TIM'},
'553299119':{'en': 'TIM'},
'389781':{'en': 'Vip'},
'553299112':{'en': 'TIM'},
'553299113':{'en': 'TIM'},
'553299111':{'en': 'TIM'},
'553299116':{'en': 'TIM'},
'553299117':{'en': 'TIM'},
'553299114':{'en': 'TIM'},
'553299115':{'en': 'TIM'},
'51629629':{'en': 'Movistar'},
'51629626':{'en': 'Movistar'},
'22560':{'en': 'GreenN'},
'22561':{'en': 'GreenN'},
'22566':{'en': 'MTN'},
'22567':{'en': 'Orange'},
'22564':{'en': 'MTN'},
'22565':{'en': 'MTN'},
'22568':{'en': 'Orange'},
'22569':{'en': 'Aircom'},
'267743':{'en': 'Orange'},
'267744':{'en': 'Orange'},
'267748':{'en': 'Orange'},
'267749':{'en': 'BTC Mobile'},
'554599149':{'en': 'Vivo'},
'554599148':{'en': 'Vivo'},
'554599147':{'en': 'Vivo'},
'554599146':{'en': 'Vivo'},
'554599145':{'en': 'Vivo'},
'554599144':{'en': 'Vivo'},
'554599143':{'en': 'Vivo'},
'554599142':{'en': 'Vivo'},
'554599141':{'en': 'Vivo'},
'554699121':{'en': 'Vivo'},
'551698148':{'en': 'TIM'},
'551698149':{'en': 'TIM'},
'22788':{'en': 'Airtel'},
'22789':{'en': 'Airtel'},
'551698144':{'en': 'TIM'},
'551698145':{'en': 'TIM'},
'551698146':{'en': 'TIM'},
'551698147':{'en': 'TIM'},
'551698141':{'en': 'TIM'},
'22780':{'en': 'Orange'},
'551698143':{'en': 'TIM'},
'447832':{'en': 'Three'},
'447833':{'en': 'Vodafone'},
'447830':{'en': 'Three'},
'447831':{'en': 'Vodafone'},
'447836':{'en': 'Vodafone'},
'447837':{'en': 'Orange'},
'447834':{'en': 'O2'},
'447835':{'en': 'O2'},
'447838':{'en': 'Three'},
'554198429':{'en': 'Brasil Telecom GSM'},
'554198428':{'en': 'Brasil Telecom GSM'},
'4476633':{'en': 'Syntec'},
'34675':{'en': 'Orange'},
'22584':{'en': 'MTN'},
'22585':{'en': 'MTN'},
'553599948':{'en': 'Telemig Celular'},
'553599949':{'en': 'Telemig Celular'},
'51769768':{'en': 'Movistar'},
'51769767':{'en': 'Movistar'},
'51769766':{'en': 'Movistar'},
'553599942':{'en': 'Telemig Celular'},
'346038':{'en': 'Vodafone'},
'51769763':{'en': 'Claro'},
'553599945':{'en': 'Telemig Celular'},
'553599946':{'en': 'Telemig Celular'},
'553599947':{'en': 'Telemig Celular'},
'372538':{'en': 'EMT'},
'372539':{'en': 'EMT'},
'372533':{'en': 'EMT'},
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'372536':{'en': 'EMT'},
'372537':{'en': 'EMT'},
'372534':{'en': 'EMT'},
'551298119':{'en': 'TIM'},
'51519509':{'en': 'Movistar'},
'551298113':{'en': 'TIM'},
'551298112':{'en': 'TIM'},
'551298111':{'en': 'TIM'},
'551298117':{'en': 'TIM'},
'551298116':{'en': 'TIM'},
'551298115':{'en': 'TIM'},
'551298114':{'en': 'TIM'},
'553798407':{'en': 'Claro BR'},
'554399192':{'en': 'Vivo'},
'554399193':{'en': 'Vivo'},
'554399191':{'en': 'Vivo'},
'554399194':{'en': 'Vivo'},
'553798401':{'en': 'Claro BR'},
'386689':{'en': 'A1'},
'386686':{'en': 'A1'},
'386681':{'en': 'A1'},
'551999771':{'en': 'Vivo'},
'551999773':{'en': 'Vivo'},
'5037072':{'en': 'Digicel'},
'551999775':{'en': 'Vivo'},
'551999774':{'en': 'Vivo'},
'551999777':{'en': 'Vivo'},
'551999776':{'en': 'Vivo'},
'551999779':{'en': 'Vivo'},
'551999778':{'en': 'Vivo'},
'55359997':{'en': 'Telemig Celular'},
'55359996':{'en': 'Telemig Celular'},
'55359998':{'en': 'Telemig Celular'},
'2348488':{'en': 'Starcomms'},
'2348489':{'en': 'Starcomms'},
'552898114':{'en': 'TIM'},
'552898115':{'en': 'TIM'},
'552898112':{'en': 'TIM'},
'552898113':{'en': 'TIM'},
'552898111':{'en': 'TIM'},
'2348480':{'en': 'Starcomms'},
'2348481':{'en': 'Starcomms'},
'2348484':{'en': 'Starcomms'},
'2348485':{'en': 'Starcomms'},
'2348486':{'en': 'Starcomms'},
'552898119':{'en': 'TIM'},
'552198411':{'en': 'Oi'},
'30690199':{'en': 'BWS'},
'55329846':{'en': 'Claro BR'},
'55329847':{'en': 'Claro BR'},
'55329844':{'en': 'Claro BR'},
'55329845':{'en': 'Claro BR'},
'55329842':{'en': 'Claro BR'},
'55329843':{'en': 'Claro BR'},
'336008':{'en': 'Orange France'},
'336009':{'en': 'Bouygues'},
'551398161':{'en': 'TIM'},
'336007':{'en': 'SFR'},
'336002':{'en': 'SFR'},
'336003':{'en': 'Bouygues'},
'336001':{'en': 'Orange France'},
'553199881':{'en': 'Telemig Celular'},
'553199883':{'en': 'Telemig Celular'},
'552198419':{'en': 'Oi'},
'553199885':{'en': 'Telemig Celular'},
'553199884':{'en': 'Telemig Celular'},
'553199887':{'en': 'Telemig Celular'},
'553199886':{'en': 'Telemig Celular'},
'553199889':{'en': 'Telemig Celular'},
'553199888':{'en': 'Telemig Celular'},
'40711':{'en': 'Telekom'},
'40712':{'en': '2K Telecom'},
'553799968':{'en': 'Telemig Celular'},
'553799969':{'en': 'Telemig Celular'},
'553799961':{'en': 'Telemig Celular'},
'553799962':{'en': 'Telemig Celular'},
'553799963':{'en': 'Telemig Celular'},
'553799964':{'en': 'Telemig Celular'},
'553799965':{'en': 'Telemig Celular'},
'553799966':{'en': 'Telemig Celular'},
'553799967':{'en': 'Telemig Celular'},
'553199874':{'en': 'Telemig Celular'},
'553199875':{'en': 'Telemig Celular'},
'1787486':{'en': 'Claro'},
'553199876':{'en': 'Telemig Celular'},
'1787487':{'en': 'Claro'},
'552299258':{'en': 'Claro BR'},
'553199877':{'en': 'Telemig Celular'},
'234908':{'en': '9mobile'},
'234909':{'en': '9mobile'},
'234906':{'en': 'MTN'},
'234907':{'en': 'Airtel'},
'234905':{'en': 'Glo'},
'234902':{'en': 'Airtel'},
'234903':{'en': 'MTN'},
'553199871':{'en': 'Telemig Celular'},
'553199392':{'en': 'TIM'},
'553199395':{'en': 'TIM'},
'553199397':{'en': 'TIM'},
'553199396':{'en': 'TIM'},
'553199726':{'en': 'Telemig Celular'},
'549341':{'en': 'Personal'},
'552299251':{'en': 'Claro BR'},
'552299252':{'en': 'Claro BR'},
'552299253':{'en': 'Claro BR'},
'549345':{'en': 'Personal'},
'27664':{'en': 'Vodacom'},
'27665':{'en': 'Vodacom'},
'27662':{'en': 'Vodacom'},
'27663':{'en': 'Vodacom'},
'27660':{'en': 'Vodacom'},
'27661':{'en': 'Vodacom'},
'552299256':{'en': 'Claro BR'},
'551498139':{'en': 'TIM'},
'47452':{'en': 'NetCom'},
'551498137':{'en': 'TIM'},
'551498136':{'en': 'TIM'},
'551498135':{'en': 'TIM'},
'551498134':{'en': 'TIM'},
'551498133':{'en': 'TIM'},
'551498132':{'en': 'TIM'},
'502539':{'en': 'Movistar'},
'503776':{'en': 'Digicel'},
'503777':{'en': 'Digicel'},
'503774':{'en': 'Claro'},
'503775':{'en': 'Claro'},
'503772':{'en': 'Tigo'},
'503773':{'en': 'Tigo'},
'503770':{'en': 'Movistar'},
'503771':{'en': 'Movistar'},
'553199728':{'en': 'Telemig Celular'},
'553199729':{'en': 'Telemig Celular'},
'347225':{'en': 'Yoigo'},
'551698823':{'en': 'Oi'},
'551698822':{'en': 'Oi'},
'551698821':{'en': 'Oi'},
'551698820':{'en': 'Oi'},
'50683':{'en': 'Kolbi ICE'},
'553199319':{'en': 'TIM'},
'553199318':{'en': 'TIM'},
'389758':{'en': 'Vip'},
'389759':{'en': 'Vip'},
'389754':{'en': 'Vip'},
'389755':{'en': 'Vip'},
'389756':{'en': 'Vip'},
'389757':{'en': 'Vip'},
'553199315':{'en': 'TIM'},
'553199314':{'en': 'TIM'},
'389752':{'en': 'Vip'},
'389753':{'en': 'Vip'},
'51679674':{'en': 'Claro'},
'5119751':{'en': 'Movistar'},
'551899711':{'en': 'Vivo'},
'5119750':{'en': 'Movistar'},
'552798168':{'en': 'TIM'},
'551899712':{'en': 'Vivo'},
'457194':{'en': 'Telenor'},
'457195':{'en': 'Telenor'},
'457196':{'en': 'Mundio Mobile'},
'457197':{'en': 'Mundio Mobile'},
'457190':{'en': 'Phone-IT'},
'457191':{'en': 'Telecom X'},
'457192':{'en': 'Justfone'},
'457193':{'en': 'CBB Mobil'},
'2347023':{'en': 'Zoom'},
'2347022':{'en': 'Ntel'},
'2347021':{'en': 'Ntel'},
'2347020':{'en': 'Smile'},
'4476411':{'en': 'Orange'},
'457199':{'en': 'Firmafon'},
'2347025':{'en': 'Visafone'},
'2347024':{'en': 'Prestel'},
'552798169':{'en': 'TIM'},
'354637':{'en': u('\u00d6ryggisfjarskipti')},
'2359':{'en': 'Millicom'},
'354630':{'en': 'IMC'},
'354632':{'en': 'Tismi'},
'354639':{'en': u('\u00d6ryggisfjarskipti')},
'354638':{'en': u('\u00d6ryggisfjarskipti')},
'458195':{'en': 'CBB Mobil'},
'458194':{'en': 'Lebara Limited'},
'458197':{'en': 'CBB Mobil'},
'458196':{'en': 'CBB Mobil'},
'458191':{'en': 'Lebara Limited'},
'458190':{'en': 'Lebara Limited'},
'458193':{'en': 'Lebara Limited'},
'458192':{'en': 'Lebara Limited'},
'458199':{'en': 'Banedanmark'},
'458198':{'en': 'CBB Mobil'},
'2136':{'en': 'Mobilis'},
'2135':{'en': 'Ooredoo'},
'230595':{'en': 'MTML'},
'230594':{'en': 'Cellplus'},
'230597':{'en': 'Emtel'},
'230596':{'en': 'MTML'},
'230591':{'en': 'Cellplus'},
'230590':{'en': 'Cellplus'},
'230593':{'en': 'Emtel'},
'230592':{'en': 'Cellplus'},
'43650':{'en': 'tele.ring'},
'554198406':{'en': 'Brasil Telecom GSM'},
'230598':{'en': 'Emtel'},
'551599169':{'en': 'Claro BR'},
'515495840':{'en': 'Movistar'},
'515495841':{'en': 'Movistar'},
'515495842':{'en': 'Movistar'},
'515495843':{'en': 'Movistar'},
'554198408':{'en': 'Brasil Telecom GSM'},
'551598141':{'en': 'TIM'},
'551197995':{'en': 'Oi'},
'551197994':{'en': 'Oi'},
'551197993':{'en': 'Oi'},
'551197992':{'en': 'Oi'},
'551197991':{'en': 'Oi'},
'551197990':{'en': 'Oi'},
'26263930':{'en': 'BJT'},
'26263939':{'en': 'Only'},
'552299761':{'en': 'Vivo'},
'552299762':{'en': 'Vivo'},
'552299763':{'en': 'Vivo'},
'552299764':{'en': 'Vivo'},
'552299765':{'en': 'Vivo'},
'552299766':{'en': 'Vivo'},
'552299767':{'en': 'Vivo'},
'447534':{'en': 'EE'},
'554399168':{'en': 'Vivo'},
'554399612':{'en': 'TIM'},
'447538':{'en': 'EE'},
'33634':{'en': 'SFR'},
'33635':{'en': 'SFR'},
'147341':{'en': 'Digicel Grenada'},
'51619627':{'en': 'Claro'},
'24493':{'en': 'UNITEL'},
'554399133':{'en': 'Vivo'},
'552799236':{'en': 'Claro BR'},
'552899988':{'en': 'Vivo'},
'553299131':{'en': 'TIM'},
'553299132':{'en': 'TIM'},
'552899989':{'en': 'Vivo'},
'553299134':{'en': 'TIM'},
'553299135':{'en': 'TIM'},
'553299136':{'en': 'TIM'},
'553299137':{'en': 'TIM'},
'553299138':{'en': 'TIM'},
'553299139':{'en': 'TIM'},
'551599162':{'en': 'Claro BR'},
'447489':{'en': 'O2'},
'447488':{'en': 'Three'},
'515395350':{'en': 'Claro'},
'515395352':{'en': 'Movistar'},
'447482':{'en': 'Three'},
'447481':{'en': 'Three'},
'447480':{'en': 'Three'},
'551699709':{'en': 'Vivo'},
'551699708':{'en': 'Vivo'},
'551699705':{'en': 'Vivo'},
'551699704':{'en': 'Vivo'},
'551699707':{'en': 'Vivo'},
'551699706':{'en': 'Vivo'},
'551699701':{'en': 'Vivo'},
'551699703':{'en': 'Vivo'},
'551699702':{'en': 'Vivo'},
'22548':{'en': 'Orange'},
'22549':{'en': 'Orange'},
'22540':{'en': 'Moov'},
'22541':{'en': 'Moov'},
'22542':{'en': 'Moov'},
'22543':{'en': 'Moov'},
'22544':{'en': 'MTN'},
'22545':{'en': 'MTN'},
'22546':{'en': 'MTN'},
'22547':{'en': 'Orange'},
'381677':{'en': 'GLOBALTEL'},
'553399971':{'en': 'Telemig Celular'},
'381678':{'en': 'Vectone Mobile'},
'554599125':{'en': 'Vivo'},
'50240':{'en': 'Tigo'},
'554599127':{'en': 'Vivo'},
'554599126':{'en': 'Vivo'},
'554599121':{'en': 'Vivo'},
'554599123':{'en': 'Vivo'},
'554599122':{'en': 'Vivo'},
'554599129':{'en': 'Vivo'},
'554599128':{'en': 'Vivo'},
'551699722':{'en': 'Vivo'},
'474690':{'en': 'Telenor'},
'474691':{'en': 'Telenor'},
'474692':{'en': 'Telenor'},
'474693':{'en': 'Telenor'},
'474694':{'en': 'Telenor'},
'474695':{'en': 'Telenor'},
'474696':{'en': 'Telenor'},
'554598831':{'en': 'Claro BR'},
'554598832':{'en': 'Claro BR'},
'554598833':{'en': 'Claro BR'},
'554598834':{'en': 'Claro BR'},
'554598835':{'en': 'Claro BR'},
'554598836':{'en': 'Claro BR'},
'554598837':{'en': 'Claro BR'},
'554198449':{'en': 'Brasil Telecom GSM'},
'554198448':{'en': 'Brasil Telecom GSM'},
'554198445':{'en': 'Brasil Telecom GSM'},
'554198444':{'en': 'Brasil Telecom GSM'},
'514394324':{'en': 'Movistar'},
'554198446':{'en': 'Brasil Telecom GSM'},
'514394322':{'en': 'Movistar'},
'514394323':{'en': 'Movistar'},
'514394320':{'en': 'Movistar'},
'514394321':{'en': 'Movistar'},
'515495893':{'en': 'Movistar'},
'447818':{'en': 'Vodafone'},
'447819':{'en': 'O2'},
'447810':{'en': 'Vodafone'},
'553499983':{'en': 'Telemig Celular'},
'515495892':{'en': 'Movistar'},
'554598812':{'en': 'Claro BR'},
'553499982':{'en': 'Telemig Celular'},
'553599928':{'en': 'Telemig Celular'},
'553599929':{'en': 'Telemig Celular'},
'553599926':{'en': 'Telemig Celular'},
'553599927':{'en': 'Telemig Celular'},
'553599924':{'en': 'Telemig Celular'},
'553599925':{'en': 'Telemig Celular'},
'553599922':{'en': 'Telemig Celular'},
'372519':{'en': 'EMT'},
'553599921':{'en': 'Telemig Celular'},
'55119664':{'en': 'Claro BR'},
'55119663':{'en': 'Claro BR'},
'55119662':{'en': 'Claro BR'},
'55119661':{'en': 'Claro BR'},
'55119660':{'en': 'Claro BR'},
'554598816':{'en': 'Claro BR'},
'553199312':{'en': 'TIM'},
'553799924':{'en': 'Telemig Celular'},
'554598814':{'en': 'Claro BR'},
'554598815':{'en': 'Claro BR'},
'30695290':{'en': 'MI Carrier Services'},
'25279':{'en': 'Somtel'},
'1939242':{'en': 'Claro'},
'1939240':{'en': 'SunCom Wireless Puerto Rico'},
'1939247':{'en': 'Claro'},
'1939246':{'en': 'Claro'},
'1939245':{'en': 'Claro'},
'1939244':{'en': 'Claro'},
'1939249':{'en': 'Claro'},
'1939248':{'en': 'Claro'},
'551999757':{'en': 'Vivo'},
'551999756':{'en': 'Vivo'},
'551999755':{'en': 'Vivo'},
'551999754':{'en': 'Vivo'},
'551999753':{'en': 'Vivo'},
'551999752':{'en': 'Vivo'},
'551999751':{'en': 'Vivo'},
'551999759':{'en': 'Vivo'},
'551999758':{'en': 'Vivo'},
'553799927':{'en': 'Telemig Celular'},
'2659':{'en': 'Airtel'},
'2658':{'en': 'TNM'},
'551599201':{'en': 'Claro BR'},
'551799634':{'en': 'Vivo'},
'4525984':{'en': 'CoolTEL'},
'4525985':{'en': '42 Telecom AB'},
'4525986':{'en': '42 Telecom AB'},
'4525987':{'en': 'Netfors Unified Messaging'},
'4525980':{'en': 'Uni-tel'},
'4525981':{'en': 'MobiWeb Limited'},
'4525982':{'en': 'Jay.net'},
'4525983':{'en': '42 Telecom AB'},
'551799632':{'en': 'Vivo'},
'4525988':{'en': 'CoolTEL'},
'4525989':{'en': 'Ipnordic'},
'552498129':{'en': 'TIM'},
'551799633':{'en': 'Vivo'},
'551799631':{'en': 'Vivo'},
'459340':{'en': 'Justfone'},
'1939865':{'en': 'SunCom Wireless Puerto Rico'},
'1758520':{'en': 'Digicel'},
'551899742':{'en': 'Vivo'},
'39370':{'en': 'TIM'},
'346434':{'en': 'DigiMobil'},
'346435':{'en': 'DigiMobil'},
'346436':{'en': 'DigiMobil'},
'346430':{'en': 'DigiMobil'},
'346431':{'en': 'DigiMobil'},
'346432':{'en': 'DigiMobil'},
'346433':{'en': 'DigiMobil'},
'551398147':{'en': 'TIM'},
'551398146':{'en': 'TIM'},
'551398145':{'en': 'TIM'},
'551398144':{'en': 'TIM'},
'551398143':{'en': 'TIM'},
'551398142':{'en': 'TIM'},
'551398141':{'en': 'TIM'},
'459123':{'en': 'Companymobile'},
'459122':{'en': 'Companymobile'},
'459121':{'en': 'SimService'},
'459120':{'en': 'Tismi BV'},
'459127':{'en': 'Mundio Mobile'},
'459126':{'en': 'Mundio Mobile'},
'459125':{'en': 'Companymobile'},
'459124':{'en': 'Companymobile'},
'459129':{'en': 'Mundio Mobile'},
'459128':{'en': 'Mundio Mobile'},
'552899883':{'en': 'Vivo'},
'552899882':{'en': 'Vivo'},
'552899881':{'en': 'Vivo'},
'474723':{'en': 'Tele2'},
'552899886':{'en': 'Vivo'},
'552899885':{'en': 'Vivo'},
'552899884':{'en': 'Vivo'},
'474727':{'en': 'Tele2'},
'38671':{'en': 'Telekom Slovenije'},
'38670':{'en': 'Telemach'},
'1767611':{'en': 'Digicel'},
'553799908':{'en': 'Telemig Celular'},
'553799909':{'en': 'Telemig Celular'},
'553799906':{'en': 'Telemig Celular'},
'553799907':{'en': 'Telemig Celular'},
'553799904':{'en': 'Telemig Celular'},
'553799905':{'en': 'Telemig Celular'},
'553799902':{'en': 'Telemig Celular'},
'553799903':{'en': 'Telemig Celular'},
'553799901':{'en': 'Telemig Celular'},
'479403':{'en': 'Telenor'},
'479405':{'en': 'Telenor'},
'551899758':{'en': 'Vivo'},
'2626392':{'en': 'SFR'},
'212684':{'en': u('M\u00e9ditel')},
'212687':{'en': 'Inwi'},
'553299946':{'en': 'Telemig Celular'},
'212681':{'en': 'Inwi'},
'212680':{'en': 'Inwi'},
'212682':{'en': 'Maroc Telecom'},
'212689':{'en': 'Maroc Telecom'},
'212688':{'en': u('M\u00e9ditel')},
'27644':{'en': 'Cell C'},
'27645':{'en': 'Cell C'},
'27646':{'en': 'Vodacom'},
'27647':{'en': 'Vodacom'},
'27640':{'en': 'MTN'},
'27641':{'en': 'Cell C'},
'27642':{'en': 'Cell C'},
'27643':{'en': 'Cell C'},
'554799958':{'en': 'TIM'},
'554799959':{'en': 'TIM'},
'27648':{'en': 'Vodacom'},
'27649':{'en': 'Vodacom'},
'51849849':{'en': 'Movistar'},
'51849848':{'en': 'Movistar'},
'554299962':{'en': 'TIM'},
'553799929':{'en': 'Telemig Celular'},
'51849841':{'en': 'Claro'},
'51849843':{'en': 'Claro'},
'51849842':{'en': 'Claro'},
'51849845':{'en': 'Movistar'},
'51849844':{'en': 'Claro'},
'51849847':{'en': 'Claro'},
'51849846':{'en': 'Movistar'},
'502551':{'en': 'Telgua'},
'502550':{'en': 'Movistar'},
'551498157':{'en': 'TIM'},
'502552':{'en': 'Tigo'},
'502555':{'en': 'Telgua'},
'502554':{'en': 'Movistar'},
'502557':{'en': 'Telgua'},
'502556':{'en': 'Telgua'},
'502559':{'en': 'Telgua'},
'502558':{'en': 'Telgua'},
'25292':{'en': 'STG'},
'551498159':{'en': 'TIM'},
'551498158':{'en': 'TIM'},
'554199189':{'en': 'Vivo'},
'554199188':{'en': 'Vivo'},
'554199187':{'en': 'Vivo'},
'554199186':{'en': 'Vivo'},
'554199185':{'en': 'Vivo'},
'554199184':{'en': 'Vivo'},
'554199183':{'en': 'Vivo'},
'554199182':{'en': 'Vivo'},
'554199181':{'en': 'Vivo'},
'553899152':{'en': 'TIM'},
'1787545':{'en': 'CENTENNIAL'},
'45409':{'en': 'Telenor'},
'55149980':{'en': 'Vivo'},
'554399127':{'en': 'Vivo'},
'507697':{'en': u('Telef\u00f3nica M\u00f3viles')},
'507693':{'en': u('Telef\u00f3nica M\u00f3viles')},
'507692':{'en': u('Telef\u00f3nica M\u00f3viles')},
'553199337':{'en': 'TIM'},
'553199336':{'en': 'TIM'},
'553199335':{'en': 'TIM'},
'553199334':{'en': 'TIM'},
'553199333':{'en': 'TIM'},
'553199332':{'en': 'TIM'},
'553199331':{'en': 'TIM'},
'554399124':{'en': 'Vivo'},
'554399123':{'en': 'Vivo'},
'554399122':{'en': 'Vivo'},
'551899729':{'en': 'Vivo'},
'551899728':{'en': 'Vivo'},
'55439880':{'en': 'Claro BR'},
'55199974':{'en': 'Vivo'},
'55199973':{'en': 'Vivo'},
'55199972':{'en': 'Vivo'},
'55199971':{'en': 'Vivo'},
'55199970':{'en': 'Vivo'},
'551899721':{'en': 'Vivo'},
'551899723':{'en': 'Vivo'},
'551899722':{'en': 'Vivo'},
'551899725':{'en': 'Vivo'},
'551899724':{'en': 'Vivo'},
'551899727':{'en': 'Vivo'},
'551899726':{'en': 'Vivo'},
'553199258':{'en': 'TIM'},
'553199259':{'en': 'TIM'},
'5519981':{'en': 'TIM'},
'553199251':{'en': 'TIM'},
'553199252':{'en': 'TIM'},
'553199253':{'en': 'TIM'},
'553199254':{'en': 'TIM'},
'553199255':{'en': 'TIM'},
'553199256':{'en': 'TIM'},
'553199257':{'en': 'TIM'},
'457178':{'en': 'Telenor'},
'457179':{'en': 'Telenor'},
'457176':{'en': 'Telenor'},
'457177':{'en': 'TDC'},
'457175':{'en': 'Telenor'},
'457172':{'en': 'YouSee'},
'457173':{'en': 'CBB Mobil'},
'457170':{'en': 'YouSee'},
'457171':{'en': 'Maxtel.dk'},
'4479788':{'en': 'Truphone'},
'4479789':{'en': 'IV Response'},
'354618':{'en': 'Vodafone'},
'4479784':{'en': 'Cheers'},
'4479785':{'en': 'Icron Network'},
'4479786':{'en': 'Oxygen8'},
'4479787':{'en': 'TeleWare'},
'354613':{'en': 'Tal'},
'354612':{'en': 'Tal'},
'4479782':{'en': 'Cloud9'},
'4479783':{'en': 'Cloud9'},
'4476693':{'en': 'Confabulate'},
'4476692':{'en': 'O2'},
'4476691':{'en': 'O2'},
'4476690':{'en': 'O2'},
'1787257':{'en': 'Claro'},
'4476696':{'en': 'Cheers'},
'514494996':{'en': 'Movistar'},
'1787254':{'en': 'Claro'},
'514494998':{'en': 'Movistar'},
'514494999':{'en': 'Movistar'},
'4476699':{'en': 'O2'},
'4476698':{'en': 'O2'},
'43676':{'en': 'T-Mobile AT'},
'50370702':{'en': 'Movistar'},
'50370703':{'en': 'Claro'},
'551398808':{'en': 'Oi'},
'474114':{'en': 'NetCom'},
'474110':{'en': 'NetCom'},
'551398803':{'en': 'Oi'},
'551398806':{'en': 'Oi'},
'551398807':{'en': 'Oi'},
'551398804':{'en': 'Oi'},
'551398805':{'en': 'Oi'},
'50370700':{'en': 'Claro'},
'5067005':{'en': 'Claro'},
'5067004':{'en': 'Claro'},
'5067007':{'en': 'Claro'},
'5067006':{'en': 'Claro'},
'5067003':{'en': 'Claro'},
'5067002':{'en': 'Claro'},
'5067009':{'en': 'Claro'},
'5067008':{'en': 'Claro'},
'553199928':{'en': 'Telemig Celular'},
'553199929':{'en': 'Telemig Celular'},
'553199922':{'en': 'Telemig Celular'},
'553199923':{'en': 'Telemig Celular'},
'553199921':{'en': 'Telemig Celular'},
'553199926':{'en': 'Telemig Celular'},
'553199927':{'en': 'Telemig Celular'},
'553199924':{'en': 'Telemig Celular'},
'47975':{'en': 'Telenor'},
'4477007':{'en': 'Sure'},
'50370746':{'en': 'Claro'},
'551599693':{'en': 'Vivo'},
'50370744':{'en': 'Claro'},
'50370745':{'en': 'Claro'},
'50370742':{'en': 'Claro'},
'50370743':{'en': 'Claro'},
'50370740':{'en': 'Claro'},
'50370741':{'en': 'Claro'},
'551599188':{'en': 'Claro BR'},
'50370707':{'en': 'Claro'},
'553399122':{'en': 'TIM'},
'5119809':{'en': 'Claro'},
'554599938':{'en': 'TIM'},
'554399144':{'en': 'Vivo'},
'554599939':{'en': 'TIM'},
'551698142':{'en': 'TIM'},
'554198427':{'en': 'Brasil Telecom GSM'},
'554399147':{'en': 'Vivo'},
'554198426':{'en': 'Brasil Telecom GSM'},
'554599932':{'en': 'TIM'},
'554198425':{'en': 'Brasil Telecom GSM'},
'554599933':{'en': 'TIM'},
'551799711':{'en': 'Vivo'},
'33653':{'en': 'Bouygues'},
'33650':{'en': 'Bouygues'},
'551799712':{'en': 'Vivo'},
'551799715':{'en': 'Vivo'},
'551799714':{'en': 'Vivo'},
'33654':{'en': 'Orange France'},
'33655':{'en': 'SFR'},
'551799719':{'en': 'Vivo'},
'551799718':{'en': 'Vivo'},
'33658':{'en': 'Bouygues'},
'37488':{'en': 'VivaCell-MTS', 'ru': u('\u0412\u0438\u0432\u0430\u0421\u0435\u043b\u043b-\u041c\u0422\u0421')},
'554198422':{'en': 'Brasil Telecom GSM'},
'554399146':{'en': 'Vivo'},
'554198421':{'en': 'Brasil Telecom GSM'},
'31658':{'en': 'Telfort'},
'31659':{'en': 'Vectone Mobile/Delight Mobile'},
'31650':{'en': 'Vodafone Libertel B.V.'},
'31651':{'en': 'KPN'},
'31652':{'en': 'Vodafone Libertel B.V.'},
'31653':{'en': 'KPN'},
'31654':{'en': 'Vodafone Libertel B.V.'},
'31655':{'en': 'Vodafone Libertel B.V.'},
'31656':{'en': 'T-Mobile'},
'31657':{'en': 'KPN'},
'551499149':{'en': 'Claro BR'},
'551499148':{'en': 'Claro BR'},
'47417':{'en': 'Telenor'},
'47416':{'en': 'Telenor'},
'47415':{'en': 'Telenor'},
'47414':{'en': 'Telenor'},
'47413':{'en': 'Tele2'},
'47412':{'en': 'Tele2'},
'551499147':{'en': 'Claro BR'},
'551499146':{'en': 'Claro BR'},
'515195199':{'en': 'Movistar'},
'515195198':{'en': 'Movistar'},
'515195195':{'en': 'Movistar'},
'515195194':{'en': 'Movistar'},
'515195197':{'en': 'Movistar'},
'515195196':{'en': 'Movistar'},
'515195191':{'en': 'Movistar'},
'515195190':{'en': 'Movistar'},
'515195193':{'en': 'Movistar'},
'551498813':{'en': 'Oi'},
'552298151':{'en': 'TIM'},
'554399143':{'en': 'Vivo'},
'26269388':{'en': 'Orange'},
'26269380':{'en': 'Only'},
'515395376':{'en': 'Claro'},
'515395375':{'en': 'Claro'},
'515395374':{'en': 'Claro'},
'515395373':{'en': 'Claro'},
'515395372':{'en': 'Claro'},
'515395371':{'en': 'Claro'},
'515395370':{'en': 'Claro'},
'518298260':{'en': 'Movistar'},
'518298261':{'en': 'Movistar'},
'551699721':{'en': 'Vivo'},
'551699727':{'en': 'Vivo'},
'551699726':{'en': 'Vivo'},
'551699725':{'en': 'Vivo'},
'551699724':{'en': 'Vivo'},
'518298268':{'en': 'Movistar'},
'551699729':{'en': 'Vivo'},
'1242535':{'en': 'BaTelCo'},
'1242533':{'en': 'BaTelCo'},
'383433':{'en': 'D3 Mobile'},
'383432':{'en': 'D3 Mobile'},
'383434':{'en': 'D3 Mobile'},
'34685':{'en': 'Orange'},
'3834715':{'en': 'mts d.o.o.'},
'3834714':{'en': 'mts d.o.o.'},
'3834713':{'en': 'mts d.o.o.'},
'3834712':{'en': 'mts d.o.o.'},
'3834711':{'en': 'mts d.o.o.'},
'3834710':{'en': 'mts d.o.o.'},
'34689':{'en': 'Movistar'},
'554198463':{'en': 'Brasil Telecom GSM'},
'554198462':{'en': 'Brasil Telecom GSM'},
'554198461':{'en': 'Brasil Telecom GSM'},
'3584552':{'en': 'Suomen Virveverkko'},
'554198467':{'en': 'Brasil Telecom GSM'},
'554198466':{'en': 'Brasil Telecom GSM'},
'554198465':{'en': 'Brasil Telecom GSM'},
'554198464':{'en': 'Brasil Telecom GSM'},
'3584555':{'en': 'Nokia Solutions and Networks'},
'455253':{'en': 'CBB Mobil'},
'554198468':{'en': 'Brasil Telecom GSM'},
'3584554':{'en': 'Suomen Virveverkko'},
'479743':{'en': 'Telenor'},
'3584556':{'en': 'Liikennevirasto'},
'552299289':{'en': 'Claro BR'},
'552299288':{'en': 'Claro BR'},
'552299283':{'en': 'Claro BR'},
'552299282':{'en': 'Claro BR'},
'552299281':{'en': 'Claro BR'},
'1246697':{'en': 'Ozone'},
'1246696':{'en': 'Ozone'},
'1246695':{'en': 'Ozone'},
'552299284':{'en': 'Claro BR'},
'4473800':{'en': 'AMSUK'},
'4475094':{'en': 'JT'},
'4475095':{'en': 'JT'},
'4475096':{'en': 'JT'},
'4475097':{'en': 'JT'},
'55119649':{'en': 'Vivo'},
'55119648':{'en': 'Vivo'},
'4475092':{'en': 'JT'},
'4475093':{'en': 'JT'},
'25078':{'en': 'MTN'},
'55119647':{'en': 'Vivo'},
'55119641':{'en': 'Vivo'},
'55119640':{'en': 'Vivo'},
'51649641':{'en': 'Claro'},
'51649640':{'en': 'Movistar'},
'51649643':{'en': 'Claro'},
'51649642':{'en': 'Claro'},
'51649645':{'en': 'Movistar'},
'51649644':{'en': 'Movistar'},
'51649647':{'en': 'Movistar'},
'51649646':{'en': 'Movistar'},
'51649648':{'en': 'Movistar'},
'553599941':{'en': 'Telemig Celular'},
'551698181':{'en': 'TIM'},
'551698182':{'en': 'TIM'},
'551698183':{'en': 'TIM'},
'551698184':{'en': 'TIM'},
'51769764':{'en': 'Movistar'},
'4475898':{'en': 'Test2date'},
'25298':{'en': 'STG'},
'4475894':{'en': 'Vectone Mobile'},
'4475895':{'en': 'Vectone Mobile'},
'4475896':{'en': 'Vectone Mobile'},
'4475897':{'en': 'Vectone Mobile'},
'4475890':{'en': 'Yim Siam'},
'4475891':{'en': 'Oxygen8'},
'4475892':{'en': 'Oxygen8'},
'4475893':{'en': 'Oxygen8'},
'552799222':{'en': 'Claro BR'},
'552799223':{'en': 'Claro BR'},
'552799226':{'en': 'Claro BR'},
'552799227':{'en': 'Claro BR'},
'552799224':{'en': 'Claro BR'},
'552799225':{'en': 'Claro BR'},
'552799228':{'en': 'Claro BR'},
'552799229':{'en': 'Claro BR'},
'447754':{'en': 'O2'},
'37356':{'en': 'IDC'},
'552498145':{'en': 'TIM'},
'552498144':{'en': 'TIM'},
'552498141':{'en': 'TIM'},
'552498143':{'en': 'TIM'},
'552498142':{'en': 'TIM'},
'5534989':{'en': 'Oi'},
'5534988':{'en': 'Oi'},
'5534987':{'en': 'Oi'},
'5534986':{'en': 'Oi'},
'5534985':{'en': 'Oi'},
'346981':{'en': 'R'},
'346989':{'en': 'Eroski movil'},
'459320':{'en': 'Justfone'},
'554299152':{'en': 'Vivo'},
'336040':{'en': 'SFR'},
'336041':{'en': 'SFR'},
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'551798141':{'en': 'TIM'},
'551798147':{'en': 'TIM'},
'551798146':{'en': 'TIM'},
'551798145':{'en': 'TIM'},
'551798144':{'en': 'TIM'},
'552899955':{'en': 'Vivo'},
'551196862':{'en': 'Vivo'},
'44748':{'en': 'EE'},
'44749':{'en': 'EE'},
'44746':{'en': 'Three'},
'44747':{'en': 'Three'},
'44745':{'en': 'Three'},
'44742':{'en': 'Three'},
'554498411':{'en': 'Brasil Telecom GSM'},
'346212':{'en': 'Ion mobile'},
'552899956':{'en': 'Vivo'},
'554498415':{'en': 'Brasil Telecom GSM'},
'554498414':{'en': 'Brasil Telecom GSM'},
'554498417':{'en': 'Brasil Telecom GSM'},
'554498416':{'en': 'Brasil Telecom GSM'},
'554498419':{'en': 'Brasil Telecom GSM'},
'552899951':{'en': 'Vivo'},
'553499209':{'en': 'TIM'},
'552899953':{'en': 'Vivo'},
'2348288':{'en': 'Starcomms'},
'2348286':{'en': 'Starcomms'},
'2348287':{'en': 'Starcomms'},
'2348284':{'en': 'Starcomms'},
'2348285':{'en': 'Starcomms'},
'2348283':{'en': 'Starcomms'},
'2356':{'en': 'Airtel'},
'2357':{'en': 'Sotel'},
'3584546':{'en': 'NextGen Mobile / CardBoardFish'},
'3584547':{'en': 'SMS Provider Corp'},
'3584544':{'en': 'Nokia'},
'3584545':{'en': 'Interactive Digital Media'},
'3584542':{'en': 'Nokia'},
'3584543':{'en': 'Nokia'},
'3584540':{'en': 'MobiWeb'},
'3584541':{'en': 'AinaCom'},
'3584548':{'en': 'Voxbone'},
'3584549':{'en': 'Beepsend'},
'479210':{'en': 'NetCom'},
'554798433':{'en': 'Brasil Telecom GSM'},
'407020':{'en': 'Lycamobile'},
'554798431':{'en': 'Brasil Telecom GSM'},
'551799232':{'en': 'Claro BR'},
'551799233':{'en': 'Claro BR'},
'551799230':{'en': 'Claro BR'},
'551799231':{'en': 'Claro BR'},
'551799236':{'en': 'Claro BR'},
'551799234':{'en': 'Claro BR'},
'551799235':{'en': 'Claro BR'},
'554798434':{'en': 'Brasil Telecom GSM'},
'554199159':{'en': 'Vivo'},
'554798435':{'en': 'Brasil Telecom GSM'},
'553199621':{'en': 'Telemig Celular'},
'553199622':{'en': 'Telemig Celular'},
'553199625':{'en': 'Telemig Celular'},
'553199624':{'en': 'Telemig Celular'},
'553199627':{'en': 'Telemig Celular'},
'553199626':{'en': 'Telemig Celular'},
'553199629':{'en': 'Telemig Celular'},
'553199628':{'en': 'Telemig Celular'},
'1784454':{'en': 'Cable & Wireless'},
'1784455':{'en': 'Cable & Wireless'},
'1242437':{'en': 'BaTelCo'},
'1242436':{'en': 'BaTelCo'},
'1242435':{'en': 'BaTelCo'},
'1242434':{'en': 'BaTelCo'},
'1242433':{'en': 'BaTelCo'},
'1242432':{'en': 'BaTelCo'},
'1242431':{'en': 'BaTelCo'},
'1242439':{'en': 'BaTelCo'},
'1242438':{'en': 'BaTelCo'},
'552198341':{'en': 'TIM'},
'552198342':{'en': 'TIM'},
'552198343':{'en': 'TIM'},
'552198344':{'en': 'TIM'},
'552198345':{'en': 'TIM'},
'552198346':{'en': 'TIM'},
'552198347':{'en': 'TIM'},
'552198348':{'en': 'TIM'},
'552198349':{'en': 'TIM'},
'22350':{'en': 'Atel'},
'551998206':{'en': 'TIM'},
'551998207':{'en': 'TIM'},
'551998204':{'en': 'TIM'},
'551998205':{'en': 'TIM'},
'551998202':{'en': 'TIM'},
'551998203':{'en': 'TIM'},
'551998201':{'en': 'TIM'},
'551998208':{'en': 'TIM'},
'551998209':{'en': 'TIM'},
'4477553':{'en': 'Core Communication'},
'4477552':{'en': 'Core Communication'},
'4477555':{'en': 'Core Communication'},
'4477554':{'en': 'Core Communication'},
'4790':{'en': 'Telenor'},
'1939777':{'en': 'Claro'},
'553499909':{'en': 'Telemig Celular'},
'553499908':{'en': 'Telemig Celular'},
'553198245':{'en': 'Claro BR'},
'553499903':{'en': 'Telemig Celular'},
'553499902':{'en': 'Telemig Celular'},
'553499901':{'en': 'Telemig Celular'},
'553499907':{'en': 'Telemig Celular'},
'553499906':{'en': 'Telemig Celular'},
'553499905':{'en': 'Telemig Celular'},
'553499904':{'en': 'Telemig Celular'},
'30692428':{'en': 'Premium Net International'},
'554199262':{'en': 'Vivo'},
'554199261':{'en': 'Vivo'},
'554199266':{'en': 'Vivo'},
'554199264':{'en': 'Vivo'},
'554199265':{'en': 'Vivo'},
'553599159':{'en': 'TIM'},
'553599158':{'en': 'TIM'},
'553599157':{'en': 'TIM'},
'553599156':{'en': 'TIM'},
'553599155':{'en': 'TIM'},
'553599154':{'en': 'TIM'},
'553599153':{'en': 'TIM'},
'553599152':{'en': 'TIM'},
'553599151':{'en': 'TIM'},
'1939307':{'en': 'CENTENNIAL'},
'551197979':{'en': 'Oi'},
'551197978':{'en': 'Oi'},
'551197975':{'en': 'Oi'},
'454280':{'en': 'BiBoB'},
'454283':{'en': '3'},
'454282':{'en': 'Telia'},
'551197971':{'en': 'Oi'},
'551197970':{'en': 'Claro BR'},
'551197973':{'en': 'Oi'},
'454286':{'en': 'Telia'},
'458136':{'en': 'CBB Mobil'},
'458135':{'en': 'CBB Mobil'},
'458134':{'en': 'CBB Mobil'},
'458133':{'en': 'CBB Mobil'},
'458132':{'en': 'CBB Mobil'},
'458131':{'en': 'CBB Mobil'},
'458130':{'en': 'CBB Mobil'},
'553399116':{'en': 'TIM'},
'554699939':{'en': 'TIM'},
'458139':{'en': 'Mundio Mobile'},
'458138':{'en': 'Mundio Mobile'},
'553399119':{'en': 'TIM'},
'553399118':{'en': 'TIM'},
'2778':{'en': 'MTN'},
'2779':{'en': 'Vodacom'},
'2771':{'en': 'Vodacom'},
'2772':{'en': 'Vodacom'},
'2773':{'en': 'MTN'},
'2774':{'en': 'Cell C'},
'2776':{'en': 'Vodacom'},
'552499296':{'en': 'Claro BR'},
'552499295':{'en': 'Claro BR'},
'552499292':{'en': 'Claro BR'},
'552499291':{'en': 'Claro BR'},
'1671747':{'en': 'PTI PACIFICA'},
'346027':{'en': 'Lebara'},
'346026':{'en': 'Lebara'},
'346025':{'en': 'Lebara'},
'346024':{'en': 'Lebara'},
'346023':{'en': 'Lycamobile'},
'346021':{'en': 'Lycamobile'},
'346020':{'en': 'Lycamobile'},
'346029':{'en': 'DIA'},
'346028':{'en': 'Lycamobile'},
'1787341':{'en': 'SunCom Wireless Puerto Rico'},
'45601':{'en': 'Telia'},
'45602':{'en': 'Telia'},
'45603':{'en': 'Telia'},
'45604':{'en': 'Telia'},
'1787344':{'en': 'SunCom Wireless Puerto Rico'},
'45606':{'en': 'CBB Mobil'},
'45607':{'en': 'CBB Mobil'},
'45608':{'en': 'CBB Mobil'},
'552498114':{'en': 'TIM'},
'552899946':{'en': 'Vivo'},
'552899945':{'en': 'Vivo'},
'51449492':{'en': 'Claro'},
'51449493':{'en': 'Claro'},
'51449491':{'en': 'Claro'},
'487278':{'en': 'Plus'},
'487279':{'en': 'Plus'},
'51449494':{'en': 'Movistar'},
'487274':{'en': 'Plus'},
'487275':{'en': 'Plus'},
'487276':{'en': 'Plus'},
'487277':{'en': 'Plus'},
'487270':{'en': 'Plus'},
'487272':{'en': 'T-Mobile'},
'487273':{'en': 'T-Mobile'},
'447461':{'en': 'O2'},
'447464':{'en': 'Vodafone'},
'447467':{'en': 'Vodafone'},
'447466':{'en': 'Lycamobile'},
'447469':{'en': 'Vodafone'},
'447468':{'en': 'Vodafone'},
'554599981':{'en': 'TIM'},
'554599984':{'en': 'TIM'},
'26269300':{'en': 'Orange'},
'26269301':{'en': 'SFR'},
'26269302':{'en': 'SFR'},
'26269303':{'en': 'SFR'},
'26269304':{'en': 'SFR'},
'26269306':{'en': 'Orange'},
'554699921':{'en': 'TIM'},
'554699922':{'en': 'TIM'},
'554699923':{'en': 'TIM'},
'554499139':{'en': 'Vivo'},
'554499138':{'en': 'Vivo'},
'554499135':{'en': 'Vivo'},
'554499134':{'en': 'Vivo'},
'554499137':{'en': 'Vivo'},
'554499136':{'en': 'Vivo'},
'554499131':{'en': 'Vivo'},
'30690300':{'en': 'MI Carrier Services'},
'554499133':{'en': 'Vivo'},
'554499132':{'en': 'Vivo'},
'553899172':{'en': 'TIM'},
'474673':{'en': 'NetCom'},
'474670':{'en': 'NetCom'},
'552499301':{'en': 'Claro BR'},
'474674':{'en': 'NetCom'},
'474675':{'en': 'NetCom'},
'553199167':{'en': 'TIM'},
'1876443':{'en': 'Digicel'},
'352698':{'en': 'Tango'},
'1876441':{'en': 'Digicel'},
'507111':{'en': 'Digicel'},
'1876447':{'en': 'Digicel'},
'1876446':{'en': 'Digicel'},
'1876445':{'en': 'Digicel'},
'352691':{'en': 'Tango'},
'502478':{'en': 'Tigo'},
'1876448':{'en': 'Digicel'},
'552299203':{'en': 'Claro BR'},
'552299202':{'en': 'Claro BR'},
'552299201':{'en': 'Claro BR'},
'552299207':{'en': 'Claro BR'},
'552299206':{'en': 'Claro BR'},
'552299205':{'en': 'Claro BR'},
'552299204':{'en': 'Claro BR'},
'552299209':{'en': 'Claro BR'},
'552299208':{'en': 'Claro BR'},
'4478391':{'en': 'Airtel'},
'4478392':{'en': 'Airtel'},
'4478397':{'en': 'Airtel'},
'4478398':{'en': 'Sure'},
'50781':{'en': 'Mobilphone'},
'551699363':{'en': 'Claro BR'},
'551699362':{'en': 'Claro BR'},
'551699361':{'en': 'Claro BR'},
'551699360':{'en': 'Claro BR'},
'551699364':{'en': 'Claro BR'},
'554298417':{'en': 'Brasil Telecom GSM'},
'30699022':{'en': 'Yuboto'},
'554298415':{'en': 'Brasil Telecom GSM'},
'554298414':{'en': 'Brasil Telecom GSM'},
'554298413':{'en': 'Brasil Telecom GSM'},
'554298412':{'en': 'Brasil Telecom GSM'},
'5524997':{'en': 'Vivo'},
'5524998':{'en': 'Vivo'},
'55139962':{'en': 'Vivo'},
'55139960':{'en': 'Vivo'},
'55139961':{'en': 'Vivo'},
'552299760':{'en': 'Vivo'},
'4479111':{'en': 'JT'},
'553599992':{'en': 'Telemig Celular'},
'4478930':{'en': 'Magrathea'},
'4478931':{'en': '24 Seven'},
'4478933':{'en': 'Yim Siam'},
'553199103':{'en': 'TIM'},
'4478938':{'en': 'aql'},
'4478939':{'en': 'Citrus'},
'346841':{'en': 'Tuenti'},
'346840':{'en': 'Tuenti'},
'346843':{'en': 'Tuenti'},
'346842':{'en': 'Tuenti'},
'346845':{'en': 'Tuenti'},
'346846':{'en': 'Telecable'},
'452395':{'en': 'Telia'},
'553199104':{'en': 'TIM'},
'553598419':{'en': 'Claro BR'},
'553598418':{'en': 'Claro BR'},
'4581371':{'en': 'CLX Networks AB'},
'4581370':{'en': 'Flexonet'},
'4581373':{'en': 'M Mobility'},
'4581372':{'en': 'Interfone International'},
'553598411':{'en': 'Claro BR'},
'553598413':{'en': 'Claro BR'},
'553598412':{'en': 'Claro BR'},
'553598415':{'en': 'Claro BR'},
'553598414':{'en': 'Claro BR'},
'553598417':{'en': 'Claro BR'},
'553598416':{'en': 'Claro BR'},
'3670':{'en': 'Vodafone'},
'1787579':{'en': 'Claro'},
'551599119':{'en': 'Claro BR'},
'551599118':{'en': 'Claro BR'},
'554399158':{'en': 'Vivo'},
'554399159':{'en': 'Vivo'},
'26096':{'en': 'MTN'},
'26097':{'en': 'Airtel'},
'551599117':{'en': 'Claro BR'},
'26095':{'en': 'ZAMTEL'},
'551599111':{'en': 'Claro BR'},
'554399153':{'en': 'Vivo'},
'551599113':{'en': 'Claro BR'},
'551599112':{'en': 'Claro BR'},
'1758518':{'en': 'Digicel'},
'552798178':{'en': 'TIM'},
'1758519':{'en': 'Digicel'},
'552798175':{'en': 'TIM'},
'552798174':{'en': 'TIM'},
'552798177':{'en': 'TIM'},
'552798176':{'en': 'TIM'},
'552798171':{'en': 'TIM'},
'552798173':{'en': 'TIM'},
'552798172':{'en': 'TIM'},
'553898431':{'en': 'Claro BR'},
'474077':{'en': 'NetCom'},
'553898437':{'en': 'Claro BR'},
'45616':{'en': 'TDC'},
'553199896':{'en': 'Telemig Celular'},
'421919':{'en': 'Orange'},
'421918':{'en': 'Orange'},
'45615':{'en': 'TDC'},
'421915':{'en': 'Orange'},
'421914':{'en': 'Telekom'},
'421917':{'en': 'Orange'},
'421916':{'en': 'Orange'},
'421911':{'en': 'Telekom'},
'421910':{'en': 'Telekom'},
'553899181':{'en': 'TIM'},
'421912':{'en': 'Telekom'},
'2345389':{'en': 'Starcomms'},
'2345381':{'en': 'Starcomms'},
'2345382':{'en': 'Starcomms'},
'2345383':{'en': 'Starcomms'},
'2345384':{'en': 'Starcomms'},
'2345385':{'en': 'Starcomms'},
'2345386':{'en': 'Starcomms'},
'2345387':{'en': 'Starcomms'},
'554598838':{'en': 'Claro BR'},
'551195780':{'en': 'Vivo'},
'551195781':{'en': 'Vivo'},
'551195782':{'en': 'Vivo'},
'551195783':{'en': 'Vivo'},
'3460309':{'en': 'Lebara'},
'3460308':{'en': 'Lebara'},
'549385':{'en': 'Personal'},
'3460305':{'en': 'Lebara'},
'3460304':{'en': 'Vodafone'},
'3460307':{'en': 'Lebara'},
'3460306':{'en': 'Lebara'},
'3460301':{'en': 'Vodafone'},
'3460300':{'en': 'Vodafone'},
'3460303':{'en': 'Vodafone'},
'551195785':{'en': 'Vivo'},
'551195786':{'en': 'Vivo'},
'407000':{'en': 'Enigma-System'},
'552299235':{'en': 'Claro BR'},
'552299233':{'en': 'Claro BR'},
'552299231':{'en': 'Claro BR'},
'553199607':{'en': 'Telemig Celular'},
'553199606':{'en': 'Telemig Celular'},
'553199605':{'en': 'Telemig Celular'},
'553199604':{'en': 'Telemig Celular'},
'553199603':{'en': 'Telemig Celular'},
'553199602':{'en': 'Telemig Celular'},
'553199601':{'en': 'Telemig Celular'},
'553199609':{'en': 'Telemig Celular'},
'553199608':{'en': 'Telemig Celular'},
'212627':{'en': 'Inwi'},
'212626':{'en': 'Inwi'},
'212625':{'en': u('M\u00e9ditel')},
'212624':{'en': 'Maroc Telecom'},
'212623':{'en': 'Maroc Telecom'},
'212622':{'en': 'Maroc Telecom'},
'212621':{'en': u('M\u00e9ditel')},
'212620':{'en': u('M\u00e9ditel')},
'212629':{'en': 'Inwi'},
'212628':{'en': 'Maroc Telecom'},
'47918':{'en': 'Telenor'},
'47916':{'en': 'Telenor'},
'47917':{'en': 'Telenor'},
'47915':{'en': 'Telenor'},
'47913':{'en': 'Telenor'},
'551699992':{'en': 'Vivo'},
'551699993':{'en': 'Vivo'},
'507637':{'en': 'Cable & Wireless'},
'507636':{'en': u('Telef\u00f3nica M\u00f3viles')},
'507635':{'en': u('Telef\u00f3nica M\u00f3viles')},
'507634':{'en': 'Cable & Wireless'},
'507633':{'en': 'Cable & Wireless'},
'507632':{'en': 'Claro'},
'507631':{'en': 'Claro'},
'507630':{'en': 'Claro'},
'4478722':{'en': 'Cloud9'},
'4478727':{'en': 'Telecom 10'},
'507638':{'en': u('Telef\u00f3nica M\u00f3viles')},
'554399141':{'en': 'Vivo'},
'4475710':{'en': '09 Mobile'},
'551998229':{'en': 'TIM'},
'551998224':{'en': 'TIM'},
'551998225':{'en': 'TIM'},
'551998226':{'en': 'TIM'},
'4475718':{'en': 'Alliance'},
'551998221':{'en': 'TIM'},
'551998222':{'en': 'TIM'},
'551998223':{'en': 'TIM'},
'554199169':{'en': 'Vivo'},
'554199168':{'en': 'Vivo'},
'554199165':{'en': 'Vivo'},
'554199164':{'en': 'Vivo'},
'554199167':{'en': 'Vivo'},
'554199166':{'en': 'Vivo'},
'554199161':{'en': 'Vivo'},
'554199163':{'en': 'Vivo'},
'554199162':{'en': 'Vivo'},
'554199246':{'en': 'Vivo'},
'553899902':{'en': 'Telemig Celular'},
'30691234':{'en': 'M-STAT'},
'517297269':{'en': 'Movistar'},
'553899901':{'en': 'Telemig Celular'},
'517297262':{'en': 'Movistar'},
'517297263':{'en': 'Movistar'},
'517297260':{'en': 'Movistar'},
'517297261':{'en': 'Movistar'},
'553599135':{'en': 'TIM'},
'551999667':{'en': 'Vivo'},
'553599137':{'en': 'TIM'},
'553599136':{'en': 'TIM'},
'553599131':{'en': 'TIM'},
'553599133':{'en': 'TIM'},
'551999666':{'en': 'Vivo'},
'553599139':{'en': 'TIM'},
'551999665':{'en': 'Vivo'},
'3465429':{'en': 'DIA'},
'551698152':{'en': 'TIM'},
'514494978':{'en': 'Movistar'},
'514494979':{'en': 'Movistar'},
'514494976':{'en': 'Claro'},
'514494977':{'en': 'Claro'},
'514494974':{'en': 'Claro'},
'514494975':{'en': 'Claro'},
'514494972':{'en': 'Claro'},
'514494973':{'en': 'Claro'},
'514494970':{'en': 'Claro'},
'514494971':{'en': 'Claro'},
'5547988':{'en': 'Claro BR'},
'551999669':{'en': 'Vivo'},
'551999668':{'en': 'Vivo'},
'193924199':{'en': 'Claro'},
'26134':{'en': 'Telma'},
'553199182':{'en': 'TIM'},
'553199183':{'en': 'TIM'},
'553199184':{'en': 'TIM'},
'553199185':{'en': 'TIM'},
'26133':{'en': 'Airtel'},
'26132':{'en': 'Orange'},
'553199188':{'en': 'TIM'},
'4476546':{'en': 'PageOne'},
'4476545':{'en': 'PageOne'},
'4476543':{'en': 'PageOne'},
'4476542':{'en': 'PageOne'},
'455068':{'en': 'CBB Mobil'},
'455066':{'en': 'CBB Mobil'},
'455067':{'en': 'CBB Mobil'},
'455064':{'en': 'Lycamobile Denmark Ltd'},
'455065':{'en': 'Lebara Limited'},
'455062':{'en': 'CBB Mobil'},
'455063':{'en': 'Mundio Mobile'},
'455060':{'en': 'ipvision'},
'455061':{'en': 'Mach Connectivity'},
'346041':{'en': 'Lebara'},
'346040':{'en': 'R'},
'346043':{'en': 'Lebara'},
'30695330':{'en': 'Apifon'},
'22968':{'en': 'Moov'},
'22969':{'en': 'MTN'},
'22966':{'en': 'MTN'},
'22967':{'en': 'MTN'},
'22964':{'en': 'Moov'},
'22965':{'en': 'Moov'},
'22962':{'en': 'MTN'},
'22963':{'en': 'Moov'},
'22960':{'en': 'Moov'},
'22961':{'en': 'MTN'},
'552899964':{'en': 'Vivo'},
'552899965':{'en': 'Vivo'},
'552899210':{'en': 'Claro BR'},
'552899967':{'en': 'Vivo'},
'552899961':{'en': 'Vivo'},
'552899962':{'en': 'Vivo'},
'552899963':{'en': 'Vivo'},
'551197049':{'en': 'TIM'},
'552899969':{'en': 'Vivo'},
'30685185':{'en': 'Cyta'},
'554299154':{'en': 'Vivo'},
'447449':{'en': 'Three'},
'447448':{'en': 'Lycamobile'},
'554599965':{'en': 'TIM'},
'554599964':{'en': 'TIM'},
'554599967':{'en': 'TIM'},
'554599966':{'en': 'TIM'},
'447443':{'en': 'Vodafone'},
'447442':{'en': 'Vodafone'},
'447440':{'en': 'Lycamobile'},
'447447':{'en': 'Three'},
'447446':{'en': 'Three'},
'447445':{'en': 'Three'},
'447444':{'en': 'Vodafone'},
'234807':{'en': 'Glo'},
'234806':{'en': 'MTN'},
'234805':{'en': 'Glo'},
'234804':{'en': 'Ntel'},
'234803':{'en': 'MTN'},
'234802':{'en': 'Airtel'},
'26269320':{'en': 'SFR'},
'26269321':{'en': 'Orange'},
'234809':{'en': '9mobile'},
'234808':{'en': 'Airtel'},
'554299902':{'en': 'TIM'},
'554299903':{'en': 'TIM'},
'554299901':{'en': 'TIM'},
'554299906':{'en': 'TIM'},
'554299907':{'en': 'TIM'},
'554299904':{'en': 'TIM'},
'554299905':{'en': 'TIM'},
'554299908':{'en': 'TIM'},
'554499113':{'en': 'Vivo'},
'554499112':{'en': 'Vivo'},
'554499111':{'en': 'Vivo'},
'554499117':{'en': 'Vivo'},
'554499116':{'en': 'Vivo'},
'554499115':{'en': 'Vivo'},
'554499114':{'en': 'Vivo'},
'554499119':{'en': 'Vivo'},
'554499118':{'en': 'Vivo'},
'554299156':{'en': 'Vivo'},
'55169881':{'en': 'Oi'},
'5527998':{'en': 'Vivo'},
'5527999':{'en': 'Vivo'},
'474654':{'en': 'NetCom'},
'554299151':{'en': 'Vivo'},
'5527997':{'en': 'Vivo'},
'474650':{'en': 'NetCom'},
'23769':{'en': 'Orange'},
'23768':{'en': 'MTN Cameroon'},
'23767':{'en': 'MTN Cameroon'},
'23766':{'en': 'NEXTTEL'},
'553799115':{'en': 'TIM'},
'553799114':{'en': 'TIM'},
'553799117':{'en': 'TIM'},
'553799116':{'en': 'TIM'},
'553799111':{'en': 'TIM'},
'553799113':{'en': 'TIM'},
'553799112':{'en': 'TIM'},
'553799119':{'en': 'TIM'},
'4478925':{'en': 'FleXtel'},
'22176':{'en': 'Tigo'},
'50769':{'en': 'Cable & Wireless'},
'50768':{'en': u('Telef\u00f3nica M\u00f3viles')},
'178765':{'en': 'CENTENNIAL'},
'178764':{'en': 'CENTENNIAL'},
'50765':{'en': 'Cable & Wireless'},
'50764':{'en': u('Telef\u00f3nica M\u00f3viles')},
'50767':{'en': 'Cable & Wireless'},
'50761':{'en': 'Digicel'},
'50760':{'en': 'Digicel'},
'50762':{'en': 'Claro'},
'22172':{'en': 'HAYO'},
'554699976':{'en': 'TIM'},
'551899648':{'en': 'Vivo'},
'551899649':{'en': 'Vivo'},
'55439960':{'en': 'TIM'},
'551899642':{'en': 'Vivo'},
'551899643':{'en': 'Vivo'},
'551899641':{'en': 'Vivo'},
'551899646':{'en': 'Vivo'},
'551899647':{'en': 'Vivo'},
'551899644':{'en': 'Vivo'},
'551899645':{'en': 'Vivo'},
'554799943':{'en': 'TIM'},
'553299133':{'en': 'TIM'},
'554799945':{'en': 'TIM'},
'1242395':{'en': 'BaTelCo'},
'554799947':{'en': 'TIM'},
'553598439':{'en': 'Claro BR'},
'553598438':{'en': 'Claro BR'},
'553598437':{'en': 'Claro BR'},
'553598436':{'en': 'Claro BR'},
'553598435':{'en': 'Claro BR'},
'553598434':{'en': 'Claro BR'},
'553598433':{'en': 'Claro BR'},
'553598432':{'en': 'Claro BR'},
'553598431':{'en': 'Claro BR'},
'551195769':{'en': 'Vivo'},
'1787513':{'en': 'SunCom Wireless Puerto Rico'},
'1787514':{'en': 'Claro'},
'1787515':{'en': 'Claro'},
'1787516':{'en': 'Claro'},
'1787517':{'en': 'Claro'},
'1787518':{'en': 'Claro'},
'1787519':{'en': 'Claro'},
'551599133':{'en': 'Claro BR'},
'551599132':{'en': 'Claro BR'},
'551599131':{'en': 'Claro BR'},
'554399177':{'en': 'Vivo'},
'551599137':{'en': 'Claro BR'},
'551599136':{'en': 'Claro BR'},
'551599135':{'en': 'Claro BR'},
'551599134':{'en': 'Claro BR'},
'551599139':{'en': 'Claro BR'},
'551599138':{'en': 'Claro BR'},
'554399178':{'en': 'Vivo'},
'554399179':{'en': 'Vivo'},
'552798153':{'en': 'TIM'},
'38595':{'en': 'Tele2'},
'474010':{'en': 'NetCom'},
'474011':{'en': 'NetCom'},
'552798157':{'en': 'TIM'},
'38591':{'en': 'Vip'},
'38592':{'en': 'Vip'},
'552798154':{'en': 'TIM'},
'552798159':{'en': 'TIM'},
'552798158':{'en': 'TIM'},
'38598':{'en': 'Hrvatski Telekom'},
'38599':{'en': 'Hrvatski Telekom'},
'30691000':{'en': 'BWS'},
'554299122':{'en': 'Vivo'},
'554299123':{'en': 'Vivo'},
'554299124':{'en': 'Vivo'},
'554299125':{'en': 'Vivo'},
'554299126':{'en': 'Vivo'},
'554299127':{'en': 'Vivo'},
'554299128':{'en': 'Vivo'},
'554299129':{'en': 'Vivo'},
'554398425':{'en': 'Brasil Telecom GSM'},
'506701':{'en': 'Claro'},
'516796773':{'en': 'Claro'},
'4915050':{'en': 'NAKA AG'},
'506703':{'en': 'Claro'},
'554398421':{'en': 'Brasil Telecom GSM'},
'554398423':{'en': 'Brasil Telecom GSM'},
'553599906':{'en': 'Telemig Celular'},
'554398422':{'en': 'Brasil Telecom GSM'},
'459299':{'en': 'ipvision'},
'459298':{'en': 'SimService'},
'459290':{'en': 'Justfone'},
'459293':{'en': 'SimService'},
'459292':{'en': 'Mobil Data'},
'459295':{'en': 'SimService'},
'459294':{'en': 'SimService'},
'459297':{'en': 'SimService'},
'459296':{'en': 'SimService'},
'554398429':{'en': 'Brasil Telecom GSM'},
'551498122':{'en': 'TIM'},
'554398428':{'en': 'Brasil Telecom GSM'},
'551999685':{'en': 'Vivo'},
'551999684':{'en': 'Vivo'},
'551999687':{'en': 'Vivo'},
'551999686':{'en': 'Vivo'},
'551999681':{'en': 'Vivo'},
'551999683':{'en': 'Vivo'},
'551999682':{'en': 'Vivo'},
'551999689':{'en': 'Vivo'},
'551999688':{'en': 'Vivo'},
'552899222':{'en': 'Claro BR'},
'5024479':{'en': 'Tigo'},
'5024478':{'en': 'Tigo'},
'5024477':{'en': 'Tigo'},
'5024476':{'en': 'Tigo'},
'23327':{'en': 'tiGO'},
'553498422':{'en': 'Claro BR'},
'553498421':{'en': 'Claro BR'},
'553498420':{'en': 'Claro BR'},
'23893':{'en': 'T+'},
'23324':{'en': 'MTN'},
'51749789':{'en': 'Movistar'},
'51749788':{'en': 'Movistar'},
'23323':{'en': 'Globacom (Zain)'},
'551197977':{'en': 'Oi'},
'551197976':{'en': 'Oi'},
'455290':{'en': 'Lebara Limited'},
'551197972':{'en': 'Oi'},
'506702':{'en': 'Claro'},
'347125':{'en': 'Yoigo'},
'1767614':{'en': 'Digicel'},
'1767617':{'en': 'Digicel'},
'347126':{'en': 'Yoigo'},
'347121':{'en': 'Yoigo'},
'553199668':{'en': 'Telemig Celular'},
'347123':{'en': 'Yoigo'},
'347122':{'en': 'Yoigo'},
'553199665':{'en': 'Telemig Celular'},
'553199664':{'en': 'Telemig Celular'},
'553199667':{'en': 'Telemig Celular'},
'553199666':{'en': 'Telemig Celular'},
'553199661':{'en': 'Telemig Celular'},
'347128':{'en': 'Yoigo'},
'553199663':{'en': 'Telemig Celular'},
'553199662':{'en': 'Telemig Celular'},
'50372':{'en': 'Tigo'},
'50373':{'en': 'Digicel'},
'50371':{'en': 'Movistar'},
'50376':{'en': 'Claro'},
'447781':{'en': 'Sure'},
'447782':{'en': 'Three'},
'447783':{'en': 'O2'},
'47934':{'en': 'NetCom'},
'479191':{'en': 'Telenor'},
'47936':{'en': 'NetCom'},
'212642':{'en': 'Maroc Telecom'},
'47930':{'en': 'NetCom'},
'212644':{'en': u('M\u00e9ditel')},
'47932':{'en': 'NetCom'},
'212646':{'en': 'Inwi'},
'212649':{'en': u('M\u00e9ditel')},
'479199':{'en': 'Telenor'},
'47938':{'en': 'NetCom'},
'554399145':{'en': 'Vivo'},
'551699606':{'en': 'Vivo'},
'551699607':{'en': 'Vivo'},
'551699601':{'en': 'Vivo'},
'551599161':{'en': 'Claro BR'},
'553899108':{'en': 'TIM'},
'551699608':{'en': 'Vivo'},
'45422':{'en': 'Telia'},
'551599163':{'en': 'Claro BR'},
'1787686':{'en': 'CENTENNIAL'},
'1787687':{'en': 'CENTENNIAL'},
'507659':{'en': u('Telef\u00f3nica M\u00f3viles')},
'1787689':{'en': 'CENTENNIAL'},
'551599165':{'en': 'Claro BR'},
'551599166':{'en': 'Claro BR'},
'554399142':{'en': 'Vivo'},
'503799':{'en': 'Movistar'},
'503794':{'en': 'Tigo'},
'503795':{'en': 'Claro'},
'503796':{'en': 'Claro'},
'503797':{'en': 'Digicel'},
'503790':{'en': 'Tigo'},
'503791':{'en': 'Tigo'},
'503792':{'en': 'Tigo'},
'503793':{'en': 'Tigo'},
'554199143':{'en': 'Vivo'},
'554199142':{'en': 'Vivo'},
'554199141':{'en': 'Vivo'},
'554199147':{'en': 'Vivo'},
'554199146':{'en': 'Vivo'},
'554199145':{'en': 'Vivo'},
'554199144':{'en': 'Vivo'},
'554199149':{'en': 'Vivo'},
'554199148':{'en': 'Vivo'},
'554599124':{'en': 'Vivo'},
'1939731':{'en': 'CENTENNIAL'},
'4478743':{'en': 'O2'},
'4478742':{'en': 'O2'},
'4478741':{'en': 'O2'},
'4478740':{'en': 'O2'},
'4478747':{'en': 'O2'},
'4478746':{'en': 'O2'},
'4478744':{'en': 'Citrus'},
'552198304':{'en': 'TIM'},
'552198305':{'en': 'TIM'},
'4478749':{'en': 'O2'},
'4478748':{'en': 'O2'},
'552198301':{'en': 'TIM'},
'552198302':{'en': 'TIM'},
'552198303':{'en': 'TIM'},
'354385':{'en': u('S\u00edminn')},
'354389':{'en': 'IMC'},
'354388':{'en': 'IMC'},
'230579':{'en': 'Cellplus'},
'230578':{'en': 'Cellplus'},
'230573':{'en': 'Emtel'},
'230572':{'en': 'Emtel'},
'230571':{'en': 'Emtel'},
'230570':{'en': 'Cellplus'},
'230577':{'en': 'Cellplus'},
'230576':{'en': 'Cellplus'},
'230575':{'en': 'Cellplus'},
'230574':{'en': 'Emtel'},
'2346469':{'en': 'Starcomms'},
'554598839':{'en': 'Claro BR'},
'2346461':{'en': 'Starcomms'},
'2346462':{'en': 'Starcomms'},
'1242899':{'en': 'aliv'},
'3069522':{'en': 'Vodafone'},
'3069523':{'en': 'Vodafone'},
'553499105':{'en': 'TIM'},
'458179':{'en': 'CBB Mobil'},
'458178':{'en': 'CBB Mobil'},
'458173':{'en': 'YouSee'},
'458172':{'en': 'Fullrate'},
'458171':{'en': 'YouSee'},
'458170':{'en': 'CBB Mobil'},
'458177':{'en': 'ipvision'},
'458176':{'en': 'CBB Mobil'},
'458175':{'en': 'YouSee'},
'458174':{'en': 'YouSee'},
'514494954':{'en': 'Movistar'},
'514494955':{'en': 'Movistar'},
'514494950':{'en': 'Movistar'},
'514494951':{'en': 'Movistar'},
'514494952':{'en': 'Movistar'},
'514494953':{'en': 'Movistar'},
'554299111':{'en': 'Vivo'},
'554299113':{'en': 'Vivo'},
'554299112':{'en': 'Vivo'},
'2992':{'en': 'TELE Greenland A/S'},
'554299114':{'en': 'Vivo'},
'553599119':{'en': 'TIM'},
'553599118':{'en': 'TIM'},
'553599113':{'en': 'TIM'},
'553599112':{'en': 'TIM'},
'553599111':{'en': 'TIM'},
'553599117':{'en': 'TIM'},
'553599116':{'en': 'TIM'},
'553599115':{'en': 'TIM'},
'553599114':{'en': 'TIM'},
'554198441':{'en': 'Brasil Telecom GSM'},
'554599913':{'en': 'TIM'},
'554198443':{'en': 'Brasil Telecom GSM'},
'37449':{'en': 'VivaCell-MTS', 'ru': u('\u0412\u0438\u0432\u0430\u0421\u0435\u043b\u043b-\u041c\u0422\u0421')},
'30695310':{'en': 'MI Carrier Services'},
'37444':{'en': 'Ucom', 'ru': u('\u042e\u043a\u043e\u043c')},
'37443':{'en': 'Beeline', 'ru': u('\u0411\u0438\u043b\u0430\u0439\u043d')},
'37441':{'en': 'Ucom', 'ru': u('\u042e\u043a\u043e\u043c')},
'1787300':{'en': 'CENTENNIAL'},
'553499108':{'en': 'TIM'},
'17587':{'en': 'Digicel'},
'554599919':{'en': 'TIM'},
'4857':{'en': 'Play'},
'4851':{'en': 'Orange'},
'4850':{'en': 'Orange'},
'551499189':{'en': 'Claro BR'},
'551499188':{'en': 'Claro BR'},
'1242646':{'en': 'BaTelCo'},
'551499185':{'en': 'Claro BR'},
'551499184':{'en': 'Claro BR'},
'551499187':{'en': 'Claro BR'},
'551499186':{'en': 'Claro BR'},
'551499181':{'en': 'Claro BR'},
'551499183':{'en': 'Claro BR'},
'551499182':{'en': 'Claro BR'},
'164923':{'en': 'C&W'},
'164924':{'en': 'C&W'},
'554599947':{'en': 'TIM'},
'554599946':{'en': 'TIM'},
'554599945':{'en': 'TIM'},
'554599944':{'en': 'TIM'},
'554599943':{'en': 'TIM'},
'554599942':{'en': 'TIM'},
'554599941':{'en': 'TIM'},
'551799646':{'en': 'Vivo'},
'551799645':{'en': 'Vivo'},
'551799644':{'en': 'Vivo'},
'551799643':{'en': 'Vivo'},
'551799642':{'en': 'Vivo'},
'551799641':{'en': 'Vivo'},
'554599948':{'en': 'TIM'},
'554299928':{'en': 'TIM'},
'554299929':{'en': 'TIM'},
'554299921':{'en': 'TIM'},
'554299922':{'en': 'TIM'},
'554299923':{'en': 'TIM'},
'1787256':{'en': 'Claro'},
'554299925':{'en': 'TIM'},
'554299926':{'en': 'TIM'},
'554299927':{'en': 'TIM'},
'45939':{'en': '3'},
'30698':{'en': 'Cosmote'},
'30697':{'en': 'Cosmote'},
'30694':{'en': 'Vodafone'},
'30693':{'en': 'Wind'},
'45935':{'en': 'Telenor'},
'553299912':{'en': 'Telemig Celular'},
'553299913':{'en': 'Telemig Celular'},
'1869557':{'en': 'CariGlobe St. Kitts'},
'1869556':{'en': 'CariGlobe St. Kitts'},
'553299917':{'en': 'Telemig Celular'},
'553299914':{'en': 'Telemig Celular'},
'553599903':{'en': 'Telemig Celular'},
'1787255':{'en': 'Claro'},
'553299919':{'en': 'Telemig Celular'},
'1869558':{'en': 'CariGlobe St. Kitts'},
'551899776':{'en': 'Vivo'},
'553199304':{'en': 'TIM'},
'352658':{'en': 'POST'},
'352651':{'en': 'POST'},
'553799139':{'en': 'TIM'},
'553799138':{'en': 'TIM'},
'553799133':{'en': 'TIM'},
'553799132':{'en': 'TIM'},
'553799131':{'en': 'TIM'},
'553799137':{'en': 'TIM'},
'553799136':{'en': 'TIM'},
'553799135':{'en': 'TIM'},
'553799134':{'en': 'TIM'},
'50248':{'en': 'Tigo'},
'24390':{'en': 'Africell'},
'50246':{'en': 'Tigo'},
'554799969':{'en': 'TIM'},
'50247':{'en': 'Telgua'},
'50244':{'en': 'Movistar'},
'50245':{'en': 'Tigo'},
'50242':{'en': 'Telgua'},
'180963':{'en': 'Tricom'},
'554799968':{'en': 'TIM'},
'24399':{'en': 'Zain'},
'50241':{'en': 'Telgua'},
'553199416':{'en': 'TIM'},
'553199414':{'en': 'TIM'},
'553199415':{'en': 'TIM'},
'553199412':{'en': 'TIM'},
'553199413':{'en': 'TIM'},
'50121':{'en': 'DigiCell'},
'50120':{'en': 'DigiCell'},
'554299139':{'en': 'Vivo'},
'3467':{'en': 'Vodafone'},
'551899662':{'en': 'Vivo'},
'551899663':{'en': 'Vivo'},
'551899664':{'en': 'Vivo'},
'551899665':{'en': 'Vivo'},
'551899666':{'en': 'Vivo'},
'551899667':{'en': 'Vivo'},
'551899668':{'en': 'Vivo'},
'551899669':{'en': 'Vivo'},
'3465':{'en': 'Orange'},
'553599923':{'en': 'Telemig Celular'},
'554299138':{'en': 'Vivo'},
'346889':{'en': 'PepePhone'},
'346888':{'en': 'Euskaltel'},
'346885':{'en': 'YouMobile'},
'346884':{'en': 'MasMovil'},
'346887':{'en': 'Euskaltel'},
'346886':{'en': 'Euskaltel'},
'346881':{'en': 'YouMobile'},
'346880':{'en': 'YouMobile'},
'346883':{'en': 'MasMovil'},
'346882':{'en': 'MasMovil'},
'4079':{'en': 'Vodafone'},
'4078':{'en': 'Telekom'},
'5519994':{'en': 'Claro BR'},
'4075':{'en': 'Orange'},
'4074':{'en': 'Orange'},
'4076':{'en': 'Telekom'},
'4073':{'en': 'Vodafone'},
'4072':{'en': 'Vodafone'},
'553398428':{'en': 'Claro BR'},
'553398429':{'en': 'Claro BR'},
'553398422':{'en': 'Claro BR'},
'553398423':{'en': 'Claro BR'},
'553398421':{'en': 'Claro BR'},
'553398426':{'en': 'Claro BR'},
'553398427':{'en': 'Claro BR'},
'553398424':{'en': 'Claro BR'},
'553398425':{'en': 'Claro BR'},
'553598455':{'en': 'Claro BR'},
'553598454':{'en': 'Claro BR'},
'553598457':{'en': 'Claro BR'},
'553598456':{'en': 'Claro BR'},
'553598451':{'en': 'Claro BR'},
'553598453':{'en': 'Claro BR'},
'553598452':{'en': 'Claro BR'},
'553598459':{'en': 'Claro BR'},
'553598458':{'en': 'Claro BR'},
'3630':{'en': 'T-Mobile'},
'1787537':{'en': 'CENTENNIAL'},
'1787534':{'en': 'CENTENNIAL'},
'1787535':{'en': 'CENTENNIAL'},
'447960':{'en': 'EE'},
'447961':{'en': 'EE'},
'447962':{'en': 'EE'},
'447963':{'en': 'EE'},
'45605':{'en': '3'},
'553199247':{'en': 'TIM'},
'553199246':{'en': 'TIM'},
'1787346':{'en': 'SunCom Wireless Puerto Rico'},
'474031':{'en': 'NetCom'},
'474032':{'en': 'NetCom'},
'25475':{'en': 'Airtel'},
'554299147':{'en': 'Vivo'},
'25477':{'en': 'Telkom'},
'553199244':{'en': 'TIM'},
'25471':{'en': 'Safaricom'},
'25470':{'en': 'Safaricom'},
'25473':{'en': 'Airtel'},
'25472':{'en': 'Safaricom'},
'553199243':{'en': 'TIM'},
'25479':{'en': 'Safaricom'},
'25478':{'en': 'Airtel'},
'554299148':{'en': 'Vivo'},
'553199242':{'en': 'TIM'},
'553199241':{'en': 'TIM'},
'420967':{'en': 'Vodafone'},
'420966':{'en': 'O2'},
'420965':{'en': 'T-Mobile'},
'420964':{'en': 'T-Mobile'},
'420963':{'en': 'T-Mobile'},
'420962':{'en': 'O2'},
'4476401':{'en': 'Telecom2'},
'45239':{'en': 'TDC'},
'45238':{'en': 'TDC'},
'48609':{'en': 'Plus'},
'48608':{'en': 'T-Mobile'},
'45235':{'en': 'TDC'},
'48606':{'en': 'T-Mobile'},
'48605':{'en': 'Plus'},
'48604':{'en': 'T-Mobile'},
'48603':{'en': 'Plus'},
'48602':{'en': 'T-Mobile'},
'45233':{'en': 'TDC'},
'48600':{'en': 'T-Mobile'},
'553199249':{'en': 'TIM'},
'553199248':{'en': 'TIM'},
'554498404':{'en': 'Brasil Telecom GSM'},
'1869762':{'en': 'Digicel'},
'1869763':{'en': 'Digicel'},
'1869760':{'en': 'Digicel'},
'554498405':{'en': 'Brasil Telecom GSM'},
'1869766':{'en': 'Digicel'},
'1869764':{'en': 'Digicel'},
'1869765':{'en': 'Digicel'},
'5119943':{'en': 'Claro'},
'5119946':{'en': 'Claro'},
'5119947':{'en': 'Claro'},
'5119944':{'en': 'Movistar'},
'5119945':{'en': 'Movistar'},
'5119948':{'en': 'Claro'},
'5119949':{'en': 'Claro'},
'554498408':{'en': 'Brasil Telecom GSM'},
'554498409':{'en': 'Brasil Telecom GSM'},
'553599818':{'en': 'Telemig Celular'},
'553599819':{'en': 'Telemig Celular'},
'38165':{'en': 'mts'},
'452599':{'en': 'Danovation'},
'38164':{'en': 'mts'},
'452597':{'en': '3'},
'452596':{'en': 'Viptel'},
'452595':{'en': 'CoolTEL'},
'452594':{'en': 'Firmafon'},
'452593':{'en': 'Compatel Limited'},
'452592':{'en': 'CoolTEL'},
'452591':{'en': 'CoolTEL'},
'452590':{'en': 'MI Carrier Services'},
'421950':{'en': '4ka of SWAN'},
'553199643':{'en': 'Telemig Celular'},
'30690555':{'en': 'AMD Telecom'},
'553199641':{'en': 'Telemig Celular'},
'553199647':{'en': 'Telemig Celular'},
'234980':{'en': 'Starcomms'},
'553199645':{'en': 'Telemig Celular'},
'553199644':{'en': 'Telemig Celular'},
'553199649':{'en': 'Telemig Celular'},
'505838':{'en': 'Movistar'},
'24201':{'en': 'Equateur Telecom'},
'35989':{'en': 'Telenor'},
'1784430':{'en': 'AT&T'},
'1784431':{'en': 'AT&T'},
'24205':{'en': 'Celtel'},
'24204':{'en': 'Warid'},
'1784434':{'en': 'Digicel'},
'24206':{'en': 'MTN'},
'51449496':{'en': 'Movistar'},
'447764':{'en': 'O2'},
'447762':{'en': 'O2'},
'447763':{'en': 'O2'},
'447761':{'en': 'O2'},
'47952':{'en': 'Telenor'},
'1242454':{'en': 'BaTelCo'},
'212669':{'en': u('M\u00e9ditel')},
'212668':{'en': 'Maroc Telecom'},
'1242451':{'en': 'BaTelCo'},
'47957':{'en': 'Telenor'},
'47954':{'en': 'Telenor'},
'1242452':{'en': 'BaTelCo'},
'212663':{'en': u('M\u00e9ditel')},
'212662':{'en': 'Maroc Telecom'},
'47958':{'en': 'Telenor'},
'47959':{'en': 'Telenor'},
'212667':{'en': 'Maroc Telecom'},
'1242458':{'en': 'BaTelCo'},
'212665':{'en': u('M\u00e9ditel')},
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'175852':{'en': 'AT&T'},
'175851':{'en': 'AT&T'},
'51449498':{'en': 'Movistar'},
'549293':{'en': 'Personal'},
'549292':{'en': 'Personal'},
'549291':{'en': 'Personal'},
'549290':{'en': 'Personal'},
'549297':{'en': 'Personal'},
'549296':{'en': 'Personal'},
'549295':{'en': 'Personal'},
'549294':{'en': 'Personal'},
'549299':{'en': 'Personal'},
'549298':{'en': 'Personal'},
'447106':{'en': 'O2'},
'447107':{'en': 'O2'},
'1787229':{'en': 'CENTENNIAL'},
'1939717':{'en': 'CENTENNIAL'},
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'4473900':{'en': 'Home Office'},
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'553399106':{'en': 'TIM'},
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'553199781':{'en': 'Telemig Celular'},
'554798437':{'en': 'Brasil Telecom GSM'},
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'24999':{'en': 'MTN'},
'554299157':{'en': 'Vivo'},
'553398455':{'en': 'Claro BR'},
'24991':{'en': 'Zain'},
'24990':{'en': 'Zain'},
'24993':{'en': 'MTN'},
'24992':{'en': 'MTN'},
'24995':{'en': 'Network of The World Ltd'},
'24996':{'en': 'Zain'},
'454260':{'en': 'BiBoB'},
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'552498126':{'en': 'TIM'},
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'552498124':{'en': 'TIM'},
'51549590':{'en': 'Movistar'},
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'51549593':{'en': 'Claro'},
'51549594':{'en': 'Movistar'},
'51549596':{'en': 'Movistar'},
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'164943':{'en': 'Islandcom'},
'515495956':{'en': 'Movistar'},
'515495957':{'en': 'Movistar'},
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'515495955':{'en': 'Movistar'},
'515495952':{'en': 'Movistar'},
'515495953':{'en': 'Movistar'},
'515495950':{'en': 'Movistar'},
'515495951':{'en': 'Movistar'},
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'552498128':{'en': 'TIM'},
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'26269360':{'en': 'Only'},
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'551799622':{'en': 'Vivo'},
'551799629':{'en': 'Vivo'},
'551799628':{'en': 'Vivo'},
'38068':{'en': 'Kyivstar'},
'45913':{'en': 'Telenor'},
'45914':{'en': 'Lycamobile Denmark Ltd'},
'45916':{'en': 'Lycamobile Denmark Ltd'},
'45917':{'en': 'Lycamobile Denmark Ltd'},
'45918':{'en': 'Lebara Limited'},
'45919':{'en': 'Lebara Limited'},
'554299944':{'en': 'TIM'},
'38063':{'en': 'lifecell'},
'554299942':{'en': 'TIM'},
'554299943':{'en': 'TIM'},
'38066':{'en': 'Vodafone'},
'38067':{'en': 'Kyivstar'},
'553299938':{'en': 'Telemig Celular'},
'553299939':{'en': 'Telemig Celular'},
'252906':{'en': 'Golis Telecom'},
'252907':{'en': 'Golis Telecom'},
'553299932':{'en': 'Telemig Celular'},
'553299933':{'en': 'Telemig Celular'},
'553299934':{'en': 'Telemig Celular'},
'553299935':{'en': 'Telemig Celular'},
'553299936':{'en': 'Telemig Celular'},
'553299937':{'en': 'Telemig Celular'},
'551197081':{'en': 'Claro BR'},
'551197080':{'en': 'Claro BR'},
'551197083':{'en': 'Claro BR'},
'551197082':{'en': 'Claro BR'},
'551197085':{'en': 'Claro BR'},
'551197084':{'en': 'Claro BR'},
'51739698':{'en': 'Movistar'},
'551197086':{'en': 'Claro BR'},
'51739696':{'en': 'Movistar'},
'551197088':{'en': 'Vivo'},
'51739694':{'en': 'Movistar'},
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'51739692':{'en': 'Movistar'},
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'51739690':{'en': 'Movistar'},
'51739691':{'en': 'Movistar'},
'553899806':{'en': 'Telemig Celular'},
'553899807':{'en': 'Telemig Celular'},
'553899804':{'en': 'Telemig Celular'},
'553899805':{'en': 'Telemig Celular'},
'553899802':{'en': 'Telemig Celular'},
'553899803':{'en': 'Telemig Celular'},
'352671':{'en': 'JOIN'},
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'553899808':{'en': 'Telemig Celular'},
'352678':{'en': 'JOIN'},
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'447375':{'en': 'EE'},
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'447377':{'en': 'EE'},
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'554599921':{'en': 'TIM'},
'554599923':{'en': 'TIM'},
'554599922':{'en': 'TIM'},
'26773':{'en': 'BTC Mobile'},
'26772':{'en': 'Orange'},
'385976':{'en': 'Hrvatski Telekom'},
'385977':{'en': 'Hrvatski Telekom'},
'385970':{'en': 'Hrvatski Telekom'},
'553199783':{'en': 'Telemig Celular'},
'26774':{'en': 'Mascom'},
'385979':{'en': 'Hrvatski Telekom'},
'553199788':{'en': 'Telemig Celular'},
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'551498155':{'en': 'TIM'},
'30699046':{'en': 'Premium Net International'},
'553199635':{'en': 'Telemig Celular'},
'30699048':{'en': 'AMD Telecom'},
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'502589':{'en': 'Tigo'},
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'551899602':{'en': 'Vivo'},
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'551899601':{'en': 'Vivo'},
'551899608':{'en': 'Vivo'},
'551899609':{'en': 'Vivo'},
'35795':{'en': 'PrimeTel'},
'35794':{'en': 'Lemontel'},
'35797':{'en': 'Cytamobile-Vodafone'},
'35796':{'en': 'MTN'},
'35799':{'en': 'Cytamobile-Vodafone'},
'553398401':{'en': 'Claro BR'},
'553398402':{'en': 'Claro BR'},
'553398403':{'en': 'Claro BR'},
'553398404':{'en': 'Claro BR'},
'553398405':{'en': 'Claro BR'},
'553398406':{'en': 'Claro BR'},
'551498151':{'en': 'TIM'},
'553398408':{'en': 'Claro BR'},
'553398409':{'en': 'Claro BR'},
'516496499':{'en': 'Movistar'},
'516496498':{'en': 'Movistar'},
'389789':{'en': 'Vip'},
'389788':{'en': 'Vip'},
'516496491':{'en': 'Movistar'},
'389786':{'en': 'Vip'},
'389785':{'en': 'Vip'},
'516496492':{'en': 'Movistar'},
'389783':{'en': 'Vip'},
'389782':{'en': 'Vip'},
'516496497':{'en': 'Movistar'},
'516496496':{'en': 'Movistar'},
'447902':{'en': 'O2'},
'447900':{'en': 'Vodafone'},
'447901':{'en': 'Vodafone'},
'447907':{'en': 'O2'},
'447909':{'en': 'Vodafone'},
'212638':{'en': 'Inwi'},
'23851':{'en': 'T+'},
'23853':{'en': 'T+'},
'23852':{'en': 'T+'},
'23859':{'en': 'CVMOVEL'},
'23858':{'en': 'CVMOVEL'},
'1876440':{'en': 'Digicel'},
'502477':{'en': 'Tigo'},
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'554299165':{'en': 'Vivo'},
'554299166':{'en': 'Vivo'},
'554299161':{'en': 'Vivo'},
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'1876449':{'en': 'Digicel'},
'553199108':{'en': 'TIM'},
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'551398149':{'en': 'TIM'},
'553199109':{'en': 'TIM'},
'212634':{'en': 'Inwi'},
'1242429':{'en': 'BaTelCo'},
'553598479':{'en': 'Claro BR'},
'553598478':{'en': 'Claro BR'},
'553598473':{'en': 'Claro BR'},
'553598472':{'en': 'Claro BR'},
'553598471':{'en': 'Claro BR'},
'553598477':{'en': 'Claro BR'},
'553598476':{'en': 'Claro BR'},
'553199164':{'en': 'TIM'},
'553598474':{'en': 'Claro BR'},
'5532989':{'en': 'Oi'},
'5532988':{'en': 'Oi'},
'553199102':{'en': 'TIM'},
'551999641':{'en': 'Vivo'},
'551999643':{'en': 'Vivo'},
'551999642':{'en': 'Vivo'},
'551999645':{'en': 'Vivo'},
'551999644':{'en': 'Vivo'},
'551999647':{'en': 'Vivo'},
'551999646':{'en': 'Vivo'},
'551999649':{'en': 'Vivo'},
'551999648':{'en': 'Vivo'},
'553199105':{'en': 'TIM'},
'553199106':{'en': 'TIM'},
'553199107':{'en': 'TIM'},
'4476818':{'en': 'PageOne'},
'5532985':{'en': 'Oi'},
'5025819':{'en': 'Tigo'},
'124282':{'en': 'aliv'},
'551898151':{'en': 'TIM'},
'51539539':{'en': 'Movistar'},
'4476810':{'en': 'PageOne'},
'30695299':{'en': 'BWS'},
'4476814':{'en': 'PageOne'},
'516796798':{'en': 'Movistar'},
'553899121':{'en': 'TIM'},
'553899123':{'en': 'TIM'},
'553899122':{'en': 'TIM'},
'553899125':{'en': 'TIM'},
'553899124':{'en': 'TIM'},
'553899127':{'en': 'TIM'},
'553899126':{'en': 'TIM'},
'553899129':{'en': 'TIM'},
'553899128':{'en': 'TIM'},
'346347':{'en': 'Vodafone'},
'447748':{'en': 'Vodafone'},
'447749':{'en': 'O2'},
'551499179':{'en': 'Claro BR'},
'447740':{'en': 'O2'},
'447741':{'en': 'Vodafone'},
'447742':{'en': 'O2'},
'447743':{'en': 'O2'},
'447745':{'en': 'O2'},
'447746':{'en': 'O2'},
'447747':{'en': 'Vodafone'},
'5036195':{'en': 'Movistar'},
'5036194':{'en': 'Movistar'},
'5036197':{'en': 'Movistar'},
'5036196':{'en': 'Movistar'},
'5036191':{'en': 'Movistar'},
'5036190':{'en': 'Movistar'},
'5036193':{'en': 'Movistar'},
'5036192':{'en': 'Movistar'},
'47970':{'en': 'Telenor'},
'47971':{'en': 'Telenor'},
'4477003':{'en': 'Sure'},
'5036198':{'en': 'Movistar'},
'47976':{'en': 'Telenor'},
'47977':{'en': 'Telenor'},
'553199281':{'en': 'TIM'},
'31683':{'en': 'KPN'},
'31681':{'en': 'T-Mobile'},
'31680':{'en': 'Vodafone Libertel B.V.'},
'31687':{'en': 'Lycamobile'},
'31686':{'en': 'Lycamobile'},
'31685':{'en': 'Lycamobile'},
'31684':{'en': 'Lycamobile'},
'12844966':{'en': 'CCT'},
'12844967':{'en': 'CCT'},
'479337':{'en': 'NetCom'},
'12844968':{'en': 'CCT'},
'12844969':{'en': 'CCT'},
'551599692':{'en': 'Vivo'},
'30690574':{'en': 'BWS'},
'511986':{'en': 'Claro'},
'511987':{'en': 'Claro'},
'553499981':{'en': 'Telemig Celular'},
'511985':{'en': 'Movistar'},
'553499987':{'en': 'Telemig Celular'},
'553499986':{'en': 'Telemig Celular'},
'553499985':{'en': 'Telemig Celular'},
'553499984':{'en': 'Telemig Celular'},
'553499989':{'en': 'Telemig Celular'},
'553499988':{'en': 'Telemig Celular'},
'511988':{'en': 'Movistar'},
'511989':{'en': 'Claro'},
'55189910':{'en': 'Claro BR'},
'55189911':{'en': 'Claro BR'},
'55189912':{'en': 'Claro BR'},
'55189913':{'en': 'Claro BR'},
'55189914':{'en': 'Claro BR'},
'55189915':{'en': 'Claro BR'},
'55189916':{'en': 'Claro BR'},
'55189917':{'en': 'Claro BR'},
'554798421':{'en': 'Brasil Telecom GSM'},
'554798423':{'en': 'Brasil Telecom GSM'},
'554798422':{'en': 'Brasil Telecom GSM'},
'554798425':{'en': 'Brasil Telecom GSM'},
'554798424':{'en': 'Brasil Telecom GSM'},
'554798427':{'en': 'Brasil Telecom GSM'},
'554798426':{'en': 'Brasil Telecom GSM'},
'554798429':{'en': 'Brasil Telecom GSM'},
'554798428':{'en': 'Brasil Telecom GSM'},
'3069900':{'en': 'Wind'},
'23990':{'en': 'Unitel'},
'23998':{'en': 'CSTmovel'},
'23999':{'en': 'CSTmovel'},
'4474062':{'en': 'Cheers'},
'4474060':{'en': 'Cheers'},
'4474061':{'en': 'Cheers'},
'4474066':{'en': '24 Seven'},
'4474067':{'en': 'TGL'},
'4474065':{'en': 'Telecom2'},
'552799653':{'en': 'Vivo'},
'4474068':{'en': '08Direct'},
'4474069':{'en': 'CardBoardFish'},
'552799652':{'en': 'Vivo'},
'552799651':{'en': 'Vivo'},
'552799650':{'en': 'Vivo'},
'373676':{'en': 'Moldtelecom'},
'373677':{'en': 'Moldtelecom'},
'373674':{'en': 'Moldtelecom'},
'373675':{'en': 'Moldtelecom'},
'373672':{'en': 'Moldtelecom'},
'373673':{'en': 'Moldtelecom'},
'373671':{'en': 'Moldtelecom'},
'554398431':{'en': 'Brasil Telecom GSM'},
'554298416':{'en': 'Brasil Telecom GSM'},
'552298113':{'en': 'TIM'},
'26481':{'en': 'MTC'},
'26482':{'en': 'Telecom Namibia'},
'26485':{'en': 'TN Mobile'},
'26484':{'en': 'MTN'},
'554298411':{'en': 'Brasil Telecom GSM'},
'1787479':{'en': 'CENTENNIAL'},
'1787478':{'en': 'SunCom Wireless Puerto Rico'},
'1787474':{'en': 'CENTENNIAL'},
'1787473':{'en': 'CENTENNIAL'},
'1787471':{'en': 'CENTENNIAL'},
'30695355':{'en': 'Cyta'},
'552298118':{'en': 'TIM'},
'552298119':{'en': 'TIM'},
'554199222':{'en': 'Vivo'},
'554299964':{'en': 'TIM'},
'554299965':{'en': 'TIM'},
'554299966':{'en': 'TIM'},
'554299967':{'en': 'TIM'},
'554299961':{'en': 'TIM'},
'554199223':{'en': 'Vivo'},
'554299963':{'en': 'TIM'},
'554299969':{'en': 'TIM'},
'553299958':{'en': 'Telemig Celular'},
'553299959':{'en': 'Telemig Celular'},
'553299956':{'en': 'Telemig Celular'},
'553299957':{'en': 'Telemig Celular'},
'553299954':{'en': 'Telemig Celular'},
'553299955':{'en': 'Telemig Celular'},
'553299952':{'en': 'Telemig Celular'},
'553299953':{'en': 'Telemig Celular'},
'553299951':{'en': 'Telemig Celular'},
'552899274':{'en': 'Claro BR'},
'552899275':{'en': 'Claro BR'},
'552899276':{'en': 'Claro BR'},
'552899277':{'en': 'Claro BR'},
'552899271':{'en': 'Claro BR'},
'552899272':{'en': 'Claro BR'},
'552899273':{'en': 'Claro BR'},
'552899278':{'en': 'Claro BR'},
'552899279':{'en': 'Claro BR'},
'553399908':{'en': 'Telemig Celular'},
'553399909':{'en': 'Telemig Celular'},
'553399902':{'en': 'Telemig Celular'},
'553399903':{'en': 'Telemig Celular'},
'553399901':{'en': 'Telemig Celular'},
'553399906':{'en': 'Telemig Celular'},
'553399907':{'en': 'Telemig Celular'},
'553399904':{'en': 'Telemig Celular'},
'553399905':{'en': 'Telemig Celular'},
'551799609':{'en': 'Vivo'},
'551799608':{'en': 'Vivo'},
'551799603':{'en': 'Vivo'},
'551799602':{'en': 'Vivo'},
'551799601':{'en': 'Vivo'},
'551799607':{'en': 'Vivo'},
'551799606':{'en': 'Vivo'},
'551799605':{'en': 'Vivo'},
'551799604':{'en': 'Vivo'},
'180993':{'en': 'Tricom'},
'180992':{'en': 'Tricom'},
'180991':{'en': 'Orange'},
'180997':{'en': 'Orange'},
'50258':{'en': 'Telgua'},
'180995':{'en': 'Claro'},
'180994':{'en': 'Tricom'},
'3472260':{'en': 'MasMovil'},
'180999':{'en': 'Tricom'},
'180998':{'en': 'Orange'},
'50253':{'en': 'Tigo'},
'50252':{'en': 'Movistar'},
'1787450':{'en': 'Claro'},
'551498809':{'en': 'Oi'},
'551498808':{'en': 'Oi'},
'515195083':{'en': 'Movistar'},
'515195082':{'en': 'Movistar'},
'515195081':{'en': 'Movistar'},
'515195080':{'en': 'Movistar'},
'551196864':{'en': 'Vivo'},
'551196865':{'en': 'Vivo'},
'551196866':{'en': 'Vivo'},
'1787904':{'en': 'SunCom Wireless Puerto Rico'},
'1787903':{'en': 'CENTENNIAL'},
'551196861':{'en': 'Vivo'},
'1787901':{'en': 'SunCom Wireless Puerto Rico'},
'551196863':{'en': 'Vivo'},
'5025551':{'en': 'Tigo'},
'5025550':{'en': 'Tigo'},
'5025553':{'en': 'Tigo'},
'5025552':{'en': 'Tigo'},
'505820':{'en': 'Claro'},
'505821':{'en': 'Claro'},
'505822':{'en': 'Claro'},
'505823':{'en': 'Claro'},
'23299':{'en': 'Africell'},
'551498807':{'en': 'Oi'},
'551498806':{'en': 'Oi'},
'5533986':{'en': 'Oi'},
'5533987':{'en': 'Oi'},
'5533985':{'en': 'Oi'},
'5533988':{'en': 'Oi'},
'5533989':{'en': 'Oi'},
'554799952':{'en': 'TIM'},
'554799953':{'en': 'TIM'},
'234173':{'en': 'Starcomms'},
'552499297':{'en': 'Claro BR'},
'552499294':{'en': 'Claro BR'},
'1284393':{'en': 'Digicel'},
'1284394':{'en': 'Digicel'},
'552499293':{'en': 'Claro BR'},
'234174':{'en': 'Starcomms'},
'554799956':{'en': 'TIM'},
'552499298':{'en': 'Claro BR'},
'552499299':{'en': 'Claro BR'},
'554799954':{'en': 'TIM'},
'554799955':{'en': 'TIM'},
'553199819':{'en': 'Telemig Celular'},
'447929':{'en': 'Orange'},
'447924':{'en': 'Manx Telecom'},
'447920':{'en': 'Vodafone'},
'551899628':{'en': 'Vivo'},
'551899629':{'en': 'Vivo'},
'551899624':{'en': 'Vivo'},
'551899625':{'en': 'Vivo'},
'551899626':{'en': 'Vivo'},
'551899627':{'en': 'Vivo'},
'551899621':{'en': 'Vivo'},
'551899622':{'en': 'Vivo'},
'551899623':{'en': 'Vivo'},
'240550':{'en': 'Muni'},
'240551':{'en': 'HiTS'},
'553599816':{'en': 'Telemig Celular'},
'553599817':{'en': 'Telemig Celular'},
'553599814':{'en': 'Telemig Celular'},
'553599815':{'en': 'Telemig Celular'},
'553599812':{'en': 'Telemig Celular'},
'553599813':{'en': 'Telemig Celular'},
'553599811':{'en': 'Telemig Celular'},
'552299254':{'en': 'Claro BR'},
'1246259':{'en': 'Digicel'},
'1246258':{'en': 'Digicel'},
'1246253':{'en': 'LIME'},
'1246252':{'en': 'LIME'},
'1246251':{'en': 'LIME'},
'1246250':{'en': 'LIME'},
'1246257':{'en': 'Digicel'},
'1246256':{'en': 'Digicel'},
'1246255':{'en': 'LIME'},
'1246254':{'en': 'LIME'},
'554398432':{'en': 'Brasil Telecom GSM'},
'5521989':{'en': 'Oi'},
'5521988':{'en': 'Oi'},
'5521981':{'en': 'TIM'},
'5521982':{'en': 'TIM'},
'5521985':{'en': 'Oi'},
'5521987':{'en': 'Oi'},
'5521986':{'en': 'Oi'},
'516796768':{'en': 'Movistar'},
'5119986':{'en': 'Movistar'},
'5119987':{'en': 'Movistar'},
'5119984':{'en': 'Movistar'},
'551999664':{'en': 'Vivo'},
'551999663':{'en': 'Vivo'},
'551999662':{'en': 'Vivo'},
'5119980':{'en': 'Movistar'},
'551498154':{'en': 'TIM'},
'5119988':{'en': 'Movistar'},
'5119989':{'en': 'Movistar'},
'551498156':{'en': 'TIM'},
'1242525':{'en': 'BaTelCo'},
'551498153':{'en': 'TIM'},
'552899954':{'en': 'Vivo'},
'551498152':{'en': 'TIM'},
'553299971':{'en': 'Telemig Celular'},
'551699712':{'en': 'Vivo'},
'37544':{'be': 'Velcom', 'en': 'Velcom', 'ru': 'Velcom'},
'551699713':{'en': 'Vivo'},
'459272':{'en': 'Thyfon'},
'459271':{'en': 'Naka AG'},
'459270':{'en': 'Ice Danmark'},
'516796771':{'en': 'Claro'},
'516796770':{'en': 'Claro'},
'1264538':{'en': 'Weblinks Limited'},
'1264539':{'en': 'Weblinks Limited'},
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'1787380':{'en': 'Claro'},
'1787383':{'en': 'Claro'},
'1787382':{'en': 'Claro'},
'51198008':{'en': 'Movistar'},
'51198009':{'en': 'Movistar'},
'554299918':{'en': 'TIM'},
'51198003':{'en': 'Movistar'},
'51198004':{'en': 'Movistar'},
'51198005':{'en': 'Movistar'},
'51198006':{'en': 'Movistar'},
'51198007':{'en': 'Movistar'},
'553298482':{'en': 'Claro BR'},
'459156':{'en': 'TDC'},
'459157':{'en': 'Mundio Mobile'},
'48450':{'en': 'Play'},
'459155':{'en': 'TDC'},
'459152':{'en': 'TDC'},
'459153':{'en': 'TDC'},
'459150':{'en': 'Telenor Connexion AB'},
'459151':{'en': 'Telenor Connexion AB'},
'553199838':{'en': 'Telemig Celular'},
'553199839':{'en': 'Telemig Celular'},
'459158':{'en': 'NextGen Mobile Ldt T/A CardBoardFish'},
'459159':{'en': 'SimService'},
'553298485':{'en': 'Claro BR'},
'553298484':{'en': 'Claro BR'},
'554499125':{'en': 'Vivo'},
'553199768':{'en': 'Telemig Celular'},
'553199769':{'en': 'Telemig Celular'},
'553199761':{'en': 'Telemig Celular'},
'553199762':{'en': 'Telemig Celular'},
'553199763':{'en': 'Telemig Celular'},
'553199764':{'en': 'Telemig Celular'},
'553199765':{'en': 'Telemig Celular'},
'553199766':{'en': 'Telemig Celular'},
'553199767':{'en': 'Telemig Celular'},
'180954':{'en': 'Claro'},
'180951':{'en': 'Claro'},
'1684770':{'en': 'ASTCA'},
'1784533':{'en': 'Digicel'},
'1784532':{'en': 'Digicel'},
'1784531':{'en': 'Digicel'},
'1784530':{'en': 'Digicel'},
'551799759':{'en': 'Vivo'},
'1784534':{'en': 'Digicel'},
'1787940':{'en': 'CENTENNIAL'},
'1787947':{'en': 'CENTENNIAL'},
'1787949':{'en': 'SunCom Wireless Puerto Rico'},
'5527988':{'en': 'Oi'},
'5025519':{'en': 'Movistar'},
'5025518':{'en': 'Movistar'},
'505867':{'en': 'Movistar'},
'505868':{'en': 'Movistar'},
'554698404':{'en': 'Brasil Telecom GSM'},
'554698405':{'en': 'Brasil Telecom GSM'},
'554698406':{'en': 'Brasil Telecom GSM'},
'554698407':{'en': 'Brasil Telecom GSM'},
'554698401':{'en': 'Brasil Telecom GSM'},
'554698402':{'en': 'Brasil Telecom GSM'},
'554698403':{'en': 'Brasil Telecom GSM'},
'4475588':{'en': 'Cloud9'},
'4475580':{'en': 'Mobile FX Services Ltd'},
'553199925':{'en': 'Telemig Celular'},
'553499802':{'en': 'Telemig Celular'},
'553499803':{'en': 'Telemig Celular'},
'3519205':{'en': 'Lycamobile'},
'3519204':{'en': 'Lycamobile'},
'3519203':{'en': 'Lycamobile'},
'3519202':{'en': 'Lycamobile'},
'3519201':{'en': 'Lycamobile'},
'3519200':{'en': 'Lycamobile'},
'553499808':{'en': 'Telemig Celular'},
'553499809':{'en': 'Telemig Celular'},
'4474185':{'en': 'Telna'},
'4474184':{'en': 'Manx Telecom'},
'4474187':{'en': 'Teleena'},
'4474186':{'en': 'Ace Call'},
'4474181':{'en': 'Bellingham'},
'4474180':{'en': 'Three'},
'4474183':{'en': 'Tismi'},
'4474182':{'en': 'TGL'},
'4474189':{'en': 'Teleena'},
'35489':{'en': u('S\u00edminn')},
'35485':{'en': u('S\u00edminn')},
'35484':{'en': u('S\u00edminn')},
'35486':{'en': u('S\u00edminn')},
'35483':{'en': u('S\u00edminn')},
'35482':{'en': 'Vodafone'},
'23836':{'en': 'CVMOVEL'},
'23833':{'en': 'T+'},
'551599690':{'en': 'Vivo'},
'551599691':{'en': 'Vivo'},
'551599696':{'en': 'Vivo'},
'551599697':{'en': 'Vivo'},
'551599694':{'en': 'Vivo'},
'551599695':{'en': 'Vivo'},
'551398151':{'en': 'TIM'},
'55119798':{'en': 'Oi'},
'552798182':{'en': 'TIM'},
'551699994':{'en': 'Vivo'},
'551398157':{'en': 'TIM'},
'551699991':{'en': 'Vivo'},
'389729':{'en': 'T-Mobile'},
'389725':{'en': 'T-Mobile'},
'389724':{'en': 'T-Mobile'},
'389727':{'en': 'T-Mobile'},
'389726':{'en': 'T-Mobile'},
'389721':{'en': 'T-Mobile'},
'553899153':{'en': 'TIM'},
'389723':{'en': 'T-Mobile'},
'389722':{'en': 'T-Mobile'},
'552198326':{'en': 'TIM'},
'552198327':{'en': 'TIM'},
'552198324':{'en': 'TIM'},
'551999623':{'en': 'Vivo'},
'551999622':{'en': 'Vivo'},
'551999621':{'en': 'Vivo'},
'2305871':{'en': 'MTML'},
'2305876':{'en': 'Cellplus'},
'2305877':{'en': 'Cellplus'},
'551999625':{'en': 'Vivo'},
'2305875':{'en': 'Cellplus'},
'552198322':{'en': 'TIM'},
'2305878':{'en': 'Cellplus'},
'551999628':{'en': 'Vivo'},
'552198323':{'en': 'TIM'},
'553199176':{'en': 'TIM'},
'553199171':{'en': 'TIM'},
'491590':{'en': 'O2'},
'1473425':{'en': 'Digicel Grenada'},
'1473422':{'en': 'Digicel Grenada'},
'1473423':{'en': 'Digicel Grenada'},
'1473420':{'en': 'Digicel Grenada'},
'1473421':{'en': 'Digicel Grenada'},
'359988':{'en': 'Bob'},
'551698124':{'en': 'TIM'},
'549384':{'en': 'Personal'},
'551698125':{'en': 'TIM'},
'552299259':{'en': 'Claro BR'},
'1473521':{'en': 'Affordable Island Communications'},
'1473520':{'en': 'Affordable Island Communications'},
'507639':{'en': u('Telef\u00f3nica M\u00f3viles')},
'21265':{'en': 'Maroc Telecom'},
'21267':{'en': 'Maroc Telecom'},
'21260':{'en': 'Inwi'},
'21261':{'en': 'Maroc Telecom'},
'551898133':{'en': 'TIM'},
'551898132':{'en': 'TIM'},
'551898131':{'en': 'TIM'},
'346728':{'en': 'Lebara'},
'346729':{'en': 'Lebara'},
'551898135':{'en': 'TIM'},
'551898134':{'en': 'TIM'},
'346725':{'en': 'Lebara'},
'551898139':{'en': 'TIM'},
'551898138':{'en': 'TIM'},
'4476608':{'en': 'Premium O'},
'4476609':{'en': 'Premium O'},
'45509':{'en': 'Telenor'},
'45508':{'en': 'Telenor'},
'2415':{'en': 'Moov'},
'2414':{'en': 'Airtel'},
'2417':{'en': 'Airtel'},
'2416':{'en': 'Libertis'},
'45503':{'en': 'Lebara Limited'},
'45502':{'en': 'Lebara Limited'},
'45507':{'en': 'Telenor'},
'45505':{'en': 'CBB Mobil'},
'45504':{'en': 'CBB Mobil'},
'254759':{'en': 'Safaricom'},
'254758':{'en': 'Safaricom'},
'455233':{'en': 'CBB Mobil'},
'455230':{'en': 'YouSee'},
'254757':{'en': 'Safaricom'},
'553899143':{'en': 'TIM'},
'553899142':{'en': 'TIM'},
'553899141':{'en': 'TIM'},
'551998227':{'en': 'TIM'},
'553899147':{'en': 'TIM'},
'553899146':{'en': 'TIM'},
'553899145':{'en': 'TIM'},
'553899144':{'en': 'TIM'},
'553899149':{'en': 'TIM'},
'553899148':{'en': 'TIM'},
'515495811':{'en': 'Claro'},
'515495810':{'en': 'Claro'},
'3469310':{'en': 'MasMovil'},
'517497840':{'en': 'Movistar'},
'517497841':{'en': 'Movistar'},
'517497842':{'en': 'Movistar'},
'517497843':{'en': 'Movistar'},
'551799783':{'en': 'Vivo'},
'551799780':{'en': 'Vivo'},
'551799784':{'en': 'Vivo'},
'551799785':{'en': 'Vivo'},
'324672':{'en': 'Join Experience Belgium'},
'324671':{'en': 'Join Experience Belgium'},
'324676':{'en': 'Lycamobile'},
'55419871':{'en': 'Claro BR'},
'55419870':{'en': 'Claro BR'},
'55419873':{'en': 'Claro BR'},
'47480':{'en': 'Telenor'},
'47481':{'en': 'Telenor'},
'47482':{'en': 'Telenor'},
'55419872':{'en': 'Claro BR'},
'479391':{'en': 'NetCom'},
'51429429':{'en': 'Movistar'},
'51429424':{'en': 'Movistar'},
'51429427':{'en': 'Claro'},
'51429426':{'en': 'Movistar'},
'554798412':{'en': 'Brasil Telecom GSM'},
'3876441':{'en': 'HT ERONET'},
'3876440':{'en': 'HT ERONET'},
'3876443':{'en': 'HT ERONET'},
'3876442':{'en': 'HT ERONET'},
'3876445':{'en': 'HT ERONET'},
'3876444':{'en': 'HT ERONET'},
'3876446':{'en': 'HT ERONET'},
'55349916':{'en': 'TIM'},
'55349917':{'en': 'TIM'},
'55349914':{'en': 'TIM'},
'55349915':{'en': 'TIM'},
'55349912':{'en': 'TIM'},
'55349913':{'en': 'TIM'},
'55349911':{'en': 'TIM'},
'3468529':{'en': 'Carrefour'},
'554798413':{'en': 'Brasil Telecom GSM'},
'4474516':{'en': 'UK Broadband'},
'4474517':{'en': 'UK Broadband'},
'55189978':{'en': 'Vivo'},
'4474515':{'en': 'Premium O'},
'4474512':{'en': 'Tismi'},
'554798443':{'en': 'Brasil Telecom GSM'},
'554798442':{'en': 'Brasil Telecom GSM'},
'554798441':{'en': 'Brasil Telecom GSM'},
'554798414':{'en': 'Brasil Telecom GSM'},
'554798447':{'en': 'Brasil Telecom GSM'},
'554798446':{'en': 'Brasil Telecom GSM'},
'554798445':{'en': 'Brasil Telecom GSM'},
'554798444':{'en': 'Brasil Telecom GSM'},
'554798449':{'en': 'Brasil Telecom GSM'},
'554798448':{'en': 'Brasil Telecom GSM'},
'31629':{'en': 'Vodafone Libertel B.V.'},
'31625':{'en': 'Vodafone Libertel B.V.'},
'31624':{'en': 'T-Mobile'},
'31627':{'en': 'Vodafone Libertel B.V.'},
'31626':{'en': 'Telfort'},
'31621':{'en': 'Vodafone Libertel B.V.'},
'31620':{'en': 'KPN'},
'31623':{'en': 'KPN'},
'31622':{'en': 'KPN'},
'554798415':{'en': 'Brasil Telecom GSM'},
'554199219':{'en': 'Vivo'},
'554199218':{'en': 'Vivo'},
'554199213':{'en': 'Vivo'},
'554199212':{'en': 'Vivo'},
'554199211':{'en': 'Vivo'},
'554199217':{'en': 'Vivo'},
'32456':{'en': 'Mobile Vikings/JIM Mobile'},
'32455':{'en': 'VOO'},
'554199214':{'en': 'Vivo'},
'34679':{'en': 'Movistar'},
'144159':{'en': 'Digicel Bermuda'},
'144153':{'en': 'Digicel Bermuda'},
'144152':{'en': 'Digicel Bermuda'},
'144151':{'en': 'Digicel Bermuda'},
'144150':{'en': 'Digicel Bermuda'},
'5517991':{'en': 'Claro BR'},
'551799713':{'en': 'Vivo'},
'552299255':{'en': 'Claro BR'},
'554298401':{'en': 'Brasil Telecom GSM'},
'180969':{'en': 'Claro'},
'554298403':{'en': 'Brasil Telecom GSM'},
'373610':{'en': 'Orange'},
'373611':{'en': 'Orange'},
'551799716':{'en': 'Vivo'},
'554298406':{'en': 'Brasil Telecom GSM'},
'554298407':{'en': 'Brasil Telecom GSM'},
'33659':{'en': 'Bouygues'},
'26460':{'en': 'Telecom Namibia'},
'552299257':{'en': 'Claro BR'},
'503620':{'en': 'Digicel'},
'180967':{'en': 'Claro'},
'551298141':{'en': 'TIM'},
'551298142':{'en': 'TIM'},
'551298143':{'en': 'TIM'},
'551298144':{'en': 'TIM'},
'551298145':{'en': 'TIM'},
'551298146':{'en': 'TIM'},
'551298147':{'en': 'TIM'},
'551298148':{'en': 'TIM'},
'551298149':{'en': 'TIM'},
'514394371':{'en': 'Claro'},
'514394370':{'en': 'Claro'},
'514394373':{'en': 'Claro'},
'514394372':{'en': 'Claro'},
'514394375':{'en': 'Claro'},
'514394374':{'en': 'Claro'},
'514394377':{'en': 'Claro'},
'514394376':{'en': 'Claro'},
'514394379':{'en': 'Movistar'},
'514394378':{'en': 'Movistar'},
'551698179':{'en': 'TIM'},
'1787410':{'en': 'SunCom Wireless Puerto Rico'},
'447869':{'en': 'Three'},
'447868':{'en': 'Three'},
'447865':{'en': 'Three'},
'447867':{'en': 'Vodafone'},
'447866':{'en': 'Orange'},
'447861':{'en': 'Three'},
'447860':{'en': 'O2'},
'447863':{'en': 'Three'},
'447862':{'en': 'Three'},
'180962':{'en': 'Tricom'},
'55119638':{'en': 'Vivo'},
'55119639':{'en': 'Vivo'},
'55119630':{'en': 'Claro BR'},
'55119631':{'en': 'Claro BR'},
'55119632':{'en': 'Claro BR'},
'55119633':{'en': 'Claro BR'},
'55119637':{'en': 'Vivo'},
'507657':{'en': u('Telef\u00f3nica M\u00f3viles')},
'24911':{'en': 'Sudatel'},
'24910':{'en': 'Sudatel'},
'24912':{'en': 'Sudatel'},
'237659':{'en': 'Orange'},
'237658':{'en': 'Orange'},
'237653':{'en': 'MTN Cameroon'},
'237652':{'en': 'MTN Cameroon'},
'237651':{'en': 'MTN Cameroon'},
'237650':{'en': 'MTN Cameroon'},
'237657':{'en': 'Orange'},
'237656':{'en': 'Orange'},
'237655':{'en': 'Orange'},
'237654':{'en': 'MTN Cameroon'},
'1939940':{'en': 'CENTENNIAL'},
'553599993':{'en': 'Telemig Celular'},
'552799299':{'en': 'Claro BR'},
'552799298':{'en': 'Claro BR'},
'552799297':{'en': 'Claro BR'},
'552799296':{'en': 'Claro BR'},
'552799295':{'en': 'Claro BR'},
'552799294':{'en': 'Claro BR'},
'552799293':{'en': 'Claro BR'},
'552799292':{'en': 'Claro BR'},
'3462529':{'en': 'MasMovil'},
'553199856':{'en': 'Telemig Celular'},
'553199857':{'en': 'Telemig Celular'},
'553199854':{'en': 'Telemig Celular'},
'553199855':{'en': 'Telemig Celular'},
'553199852':{'en': 'Telemig Celular'},
'553199853':{'en': 'Telemig Celular'},
'553199851':{'en': 'Telemig Celular'},
'553199858':{'en': 'Telemig Celular'},
'553199859':{'en': 'Telemig Celular'},
'553199831':{'en': 'Telemig Celular'},
'2344282':{'en': 'Starcomms'},
'2344280':{'en': 'Starcomms'},
'2344281':{'en': 'Starcomms'},
'553799951':{'en': 'Telemig Celular'},
'553799953':{'en': 'Telemig Celular'},
'553799952':{'en': 'Telemig Celular'},
'30690499':{'en': 'BWS'},
'553399969':{'en': 'Telemig Celular'},
'553799957':{'en': 'Telemig Celular'},
'553799956':{'en': 'Telemig Celular'},
'553399964':{'en': 'Telemig Celular'},
'553399965':{'en': 'Telemig Celular'},
'553399966':{'en': 'Telemig Celular'},
'553399967':{'en': 'Telemig Celular'},
'517297268':{'en': 'Movistar'},
'553399962':{'en': 'Telemig Celular'},
'553399963':{'en': 'Telemig Celular'},
'553199832':{'en': 'Telemig Celular'},
'455398':{'en': 'NextGen Mobile Ldt T/A CardBoardFish'},
'346113':{'en': 'Lebara'},
'346112':{'en': 'Lebara'},
'553199833':{'en': 'Telemig Celular'},
'346110':{'en': 'Republica Movil'},
'553599996':{'en': 'Telemig Celular'},
'1767265':{'en': 'Cable & Wireless'},
'553199708':{'en': 'Telemig Celular'},
'553199709':{'en': 'Telemig Celular'},
'553199706':{'en': 'Telemig Celular'},
'553199707':{'en': 'Telemig Celular'},
'1268732':{'en': 'Digicel'},
'553199705':{'en': 'Telemig Celular'},
'1268734':{'en': 'Digicel'},
'553199703':{'en': 'Telemig Celular'},
'1268736':{'en': 'Digicel'},
'553199701':{'en': 'Telemig Celular'},
'180931':{'en': 'Tricom'},
'180930':{'en': 'Viva'},
'180933':{'en': 'Claro'},
'180932':{'en': 'Tricom'},
'180935':{'en': 'Claro'},
'180934':{'en': 'Tricom'},
'180937':{'en': 'Claro'},
'180936':{'en': 'Claro'},
'180939':{'en': 'Claro'},
'180938':{'en': 'Claro'},
'50234':{'en': 'Movistar'},
'50232':{'en': 'Tigo'},
'50231':{'en': 'Tigo'},
'50230':{'en': 'Tigo'},
'551499142':{'en': 'Claro BR'},
'1242738':{'en': 'aliv'},
'50376869':{'en': 'Movistar'},
'50376868':{'en': 'Movistar'},
'553599994':{'en': 'Telemig Celular'},
'50376865':{'en': 'Movistar'},
'50376867':{'en': 'Movistar'},
'50376866':{'en': 'Movistar'},
'1787969':{'en': 'CENTENNIAL'},
'1787968':{'en': 'CENTENNIAL'},
'502508':{'en': 'Movistar'},
'502509':{'en': 'Movistar'},
'502506':{'en': 'Tigo'},
'502507':{'en': 'Movistar'},
'502504':{'en': 'Tigo'},
'502505':{'en': 'Tigo'},
'1787961':{'en': 'CENTENNIAL'},
'502503':{'en': 'Tigo'},
'502500':{'en': 'Tigo'},
'502501':{'en': 'Telgua'},
'551898112':{'en': 'TIM'},
'505884':{'en': 'Claro'},
'505885':{'en': 'Claro'},
'505882':{'en': 'Claro'},
'505883':{'en': 'Claro'},
'551498814':{'en': 'Oi'},
'50949':{'en': 'Digicel'},
'50948':{'en': 'Digicel'},
'50944':{'en': 'Digicel'},
'50947':{'en': 'Digicel'},
'45258':{'en': 'Telenor'},
'50941':{'en': 'Natcom'},
'50940':{'en': 'Natcom'},
'50943':{'en': 'Natcom'},
'50942':{'en': 'Natcom'},
'459219':{'en': 'Telenor Connexion AB'},
'551498812':{'en': 'Oi'},
'3471770':{'en': 'PepePhone'},
'45524':{'en': 'Telia'},
'553499821':{'en': 'Telemig Celular'},
'553499822':{'en': 'Telemig Celular'},
'553499823':{'en': 'Telemig Celular'},
'553499824':{'en': 'Telemig Celular'},
'45527':{'en': 'Lebara Limited'},
'3519221':{'en': 'CTT'},
'3519220':{'en': 'CTT'},
'3519222':{'en': 'CTT'},
'554799966':{'en': 'TIM'},
'45253':{'en': 'Telenor'},
'474705':{'en': 'NetCom'},
'45251':{'en': 'Telenor'},
'554799963':{'en': 'TIM'},
'554799961':{'en': 'TIM'},
'552198372':{'en': 'TIM'},
'27636':{'en': 'Vodacom'},
'3519285':{'en': 'ONITELECOM'},
'551899686':{'en': 'Vivo'},
'551899687':{'en': 'Vivo'},
'551899684':{'en': 'Vivo'},
'551899685':{'en': 'Vivo'},
'551899682':{'en': 'Vivo'},
'551899683':{'en': 'Vivo'},
'474761':{'en': 'Telenor'},
'51659657':{'en': 'Claro'},
'3519281':{'en': 'NOWO'},
'553199826':{'en': 'Telemig Celular'},
'3519280':{'en': 'NOWO'},
'553199825':{'en': 'Telemig Celular'},
'553199824':{'en': 'Telemig Celular'},
'5037981':{'en': 'Intelfon'},
'5037980':{'en': 'Intelfon'},
'5037983':{'en': 'Intelfon'},
'5037982':{'en': 'Intelfon'},
'5037985':{'en': 'Claro'},
'5037984':{'en': 'Intelfon'},
'5037987':{'en': 'Claro'},
'5037986':{'en': 'Claro'},
'5037989':{'en': 'Claro'},
'5037988':{'en': 'Claro'},
'389707':{'en': 'T-Mobile'},
'389706':{'en': 'T-Mobile'},
'389705':{'en': 'T-Mobile'},
'389704':{'en': 'T-Mobile'},
'389703':{'en': 'T-Mobile'},
'389702':{'en': 'T-Mobile'},
'389701':{'en': 'T-Mobile'},
'389709':{'en': 'T-Mobile'},
'389708':{'en': 'T-Mobile'},
'26269381':{'en': 'Only'},
'26269382':{'en': 'Only'},
'26269383':{'en': 'Only'},
'553599134':{'en': 'TIM'},
'4476446':{'en': 'Media'},
'551699723':{'en': 'Vivo'},
'553199289':{'en': 'TIM'},
'553199288':{'en': 'TIM'},
'4476440':{'en': 'O2'},
'4476441':{'en': 'O2'},
'553199283':{'en': 'TIM'},
'515695616':{'en': 'Movistar'},
'515695615':{'en': 'Movistar'},
'515695614':{'en': 'Movistar'},
'515695613':{'en': 'Movistar'},
'515695612':{'en': 'Movistar'},
'515695611':{'en': 'Movistar'},
'515695610':{'en': 'Movistar'},
'551498143':{'en': 'TIM'},
'506500':{'en': 'OMV'},
'506501':{'en': 'OMV'},
'553599138':{'en': 'TIM'},
'553899169':{'en': 'TIM'},
'553598405':{'en': 'Claro BR'},
'30695210':{'en': 'MI Carrier Services'},
'37525':{'be': u('\u0411\u0435\u0421\u0422'), 'en': 'life:)', 'ru': 'life:)'},
'553899168':{'en': 'TIM'},
'4476620':{'en': 'Premium O'},
'551699728':{'en': 'Vivo'},
'553499106':{'en': 'TIM'},
'553599995':{'en': 'Telemig Celular'},
'2169':{'en': 'Tunisie Telecom'},
'551498148':{'en': 'TIM'},
'553899164':{'en': 'TIM'},
'2165':{'en': 'Orange'},
'551498149':{'en': 'TIM'},
'2162':{'en': 'Ooredoo'},
'455251':{'en': 'Jay.net'},
'2344672':{'en': 'Starcomms'},
'2344671':{'en': 'Starcomms'},
'455252':{'en': 'Lebara Limited'},
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'553599936':{'en': 'Telemig Celular'},
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'553599933':{'en': 'Telemig Celular'},
'553599932':{'en': 'Telemig Celular'},
'186829':{'en': 'bmobile'},
'186828':{'en': 'bmobile'},
'186827':{'en': 'bmobile'},
'515495896':{'en': 'Claro'},
'51519518':{'en': 'Movistar'},
'51519514':{'en': 'Movistar'},
'51519517':{'en': 'Claro'},
'51519516':{'en': 'Movistar'},
'51519511':{'en': 'Claro'},
'51519510':{'en': 'Movistar'},
'51519513':{'en': 'Claro'},
'51519512':{'en': 'Claro'},
'306908':{'en': 'Wind'},
'306909':{'en': 'Wind'},
'517697695':{'en': 'Movistar'},
'306900':{'en': 'BWS'},
'515495890':{'en': 'Movistar'},
'306906':{'en': 'Wind'},
'306907':{'en': 'Wind'},
'25248':{'en': 'AirSom'},
'25249':{'en': 'AirSom'},
'551999762':{'en': 'Vivo'},
'551999763':{'en': 'Vivo'},
'551999761':{'en': 'Vivo'},
'551999766':{'en': 'Vivo'},
'551999767':{'en': 'Vivo'},
'551999764':{'en': 'Vivo'},
'551999765':{'en': 'Vivo'},
'551999768':{'en': 'Vivo'},
'551999769':{'en': 'Vivo'},
'516196171':{'en': 'Claro'},
'516196170':{'en': 'Claro'},
'5025911':{'en': 'Telgua'},
'5025910':{'en': 'Telgua'},
'5025913':{'en': 'Telgua'},
'5025912':{'en': 'Telgua'},
'5025915':{'en': 'Movistar'},
'5025914':{'en': 'Telgua'},
'5025917':{'en': 'Movistar'},
'5025916':{'en': 'Movistar'},
'5025919':{'en': 'Tigo'},
'5025918':{'en': 'Tigo'},
'552498112':{'en': 'TIM'},
'552498113':{'en': 'TIM'},
'552498111':{'en': 'TIM'},
'552498116':{'en': 'TIM'},
'552498117':{'en': 'TIM'},
'45812':{'en': 'CBB Mobil'},
'552498115':{'en': 'TIM'},
'552498118':{'en': 'TIM'},
'552498119':{'en': 'TIM'},
'1264772':{'en': 'Cable & Wireless'},
'554498427':{'en': 'Brasil Telecom GSM'},
'553199618':{'en': 'Telemig Celular'},
'553199619':{'en': 'Telemig Celular'},
'50670011':{'en': 'Claro'},
'50670010':{'en': 'Claro'},
'50670013':{'en': 'Claro'},
'50670012':{'en': 'Claro'},
'50670014':{'en': 'Claro'},
'553199892':{'en': 'Telemig Celular'},
'553199893':{'en': 'Telemig Celular'},
'553199891':{'en': 'Telemig Celular'},
'459130':{'en': 'MobiWeb Limited'},
'553199897':{'en': 'Telemig Celular'},
'553199894':{'en': 'Telemig Celular'},
'553199895':{'en': 'Telemig Celular'},
'553199898':{'en': 'Telemig Celular'},
'553199899':{'en': 'Telemig Celular'},
'346404':{'en': 'MasMovil'},
'55249963':{'en': 'Vivo'},
'553199614':{'en': 'Telemig Celular'},
'553199615':{'en': 'Telemig Celular'},
'479297':{'en': 'NetCom'},
'553199616':{'en': 'Telemig Celular'},
'553199617':{'en': 'Telemig Celular'},
'553799919':{'en': 'Telemig Celular'},
'553799918':{'en': 'Telemig Celular'},
'553799915':{'en': 'Telemig Celular'},
'553799914':{'en': 'Telemig Celular'},
'553799917':{'en': 'Telemig Celular'},
'553799916':{'en': 'Telemig Celular'},
'553799911':{'en': 'Telemig Celular'},
'553799913':{'en': 'Telemig Celular'},
'553799912':{'en': 'Telemig Celular'},
'447551':{'en': 'Vodafone'},
'447550':{'en': 'EE'},
'447553':{'en': 'Vodafone'},
'447552':{'en': 'Vodafone'},
'447555':{'en': 'Vodafone'},
'447554':{'en': 'Vodafone'},
'447557':{'en': 'Vodafone'},
'447556':{'en': 'Orange'},
'479479':{'en': 'Telenor'},
'479478':{'en': 'Telenor'},
'479477':{'en': 'Telenor'},
'479476':{'en': 'Telenor'},
'479475':{'en': 'Telenor'},
'479474':{'en': 'Telenor'},
'553199919':{'en': 'Telemig Celular'},
'447396':{'en': 'EE'},
'212696':{'en': 'Maroc Telecom'},
'212697':{'en': 'Maroc Telecom'},
'212694':{'en': u('M\u00e9ditel')},
'212695':{'en': 'Inwi'},
'212693':{'en': u('M\u00e9ditel')},
'212690':{'en': 'Inwi'},
'212691':{'en': u('M\u00e9ditel')},
'212698':{'en': 'Inwi'},
'212699':{'en': 'Inwi'},
'554799941':{'en': 'TIM'},
'474740':{'en': 'Telenor'},
'554799942':{'en': 'TIM'},
'474746':{'en': 'Telenor'},
'554799944':{'en': 'TIM'},
'474744':{'en': 'NetCom'},
'554799946':{'en': 'TIM'},
'554799949':{'en': 'TIM'},
'554799948':{'en': 'TIM'},
'551498121':{'en': 'TIM'},
'502540':{'en': 'Movistar'},
'551498123':{'en': 'TIM'},
'551498124':{'en': 'TIM'},
'551498125':{'en': 'TIM'},
'551498126':{'en': 'TIM'},
'551498127':{'en': 'TIM'},
'551498128':{'en': 'TIM'},
'551498129':{'en': 'TIM'},
'553199348':{'en': 'TIM'},
'23891':{'en': 'T+'},
'23326':{'en': 'Airtel'},
'503767':{'en': 'Tigo'},
'23892':{'en': 'T+'},
'23895':{'en': 'CVMOVEL'},
'23897':{'en': 'CVMOVEL'},
'23320':{'en': 'Vodafone'},
'23899':{'en': 'CVMOVEL'},
'23898':{'en': 'CVMOVEL'},
'336045':{'en': 'SFR'},
'503768':{'en': 'Tigo'},
'23328':{'en': 'Expresso'},
'50366116':{'en': 'Movistar'},
'554699975':{'en': 'TIM'},
'553199349':{'en': 'TIM'},
'553899998':{'en': 'Telemig Celular'},
'551699962':{'en': 'Vivo'},
'436778':{'en': 'T-Mobile AT'},
'34682':{'en': 'Movistar'},
'3465529':{'en': 'DIA'},
'553899991':{'en': 'Telemig Celular'},
'1284440':{'en': 'CCT'},
'1284441':{'en': 'CCT'},
'1284442':{'en': 'CCT'},
'1284443':{'en': 'CCT'},
'1284444':{'en': 'CCT'},
'1284445':{'en': 'CCT'},
'1284446':{'en': 'CCT'},
'507687':{'en': 'Cable & Wireless'},
'507684':{'en': 'Cable & Wireless'},
'553199309':{'en': 'TIM'},
'507680':{'en': 'Cable & Wireless'},
'553199302':{'en': 'TIM'},
'553199303':{'en': 'TIM'},
'553199301':{'en': 'TIM'},
'553199306':{'en': 'TIM'},
'553199307':{'en': 'TIM'},
'507688':{'en': 'Cable & Wireless'},
'553199305':{'en': 'TIM'},
'553899997':{'en': 'Telemig Celular'},
'4478228':{'en': 'Vodafone'},
'55199961':{'en': 'Vivo'},
'4478229':{'en': 'Oxygen8'},
'551698118':{'en': 'TIM'},
'551398128':{'en': 'TIM'},
'491578':{'en': 'Eplus'},
'491579':{'en': 'Eplus/Sipgate'},
'5519991':{'en': 'Claro BR'},
'5519993':{'en': 'Claro BR'},
'5519992':{'en': 'Claro BR'},
'491570':{'en': 'Eplus/Telogic'},
'491573':{'en': 'Eplus'},
'491575':{'en': 'Eplus'},
'491577':{'en': 'Eplus'},
'517396950':{'en': 'Movistar'},
'517396951':{'en': 'Movistar'},
'517396952':{'en': 'Movistar'},
'517396953':{'en': 'Movistar'},
'517396954':{'en': 'Movistar'},
'517396955':{'en': 'Movistar'},
'517396956':{'en': 'Movistar'},
'517396957':{'en': 'Movistar'},
'4476402':{'en': 'FIO Telecom'},
'4476403':{'en': 'PageOne'},
'4476400':{'en': 'Core Telecom'},
'1939697':{'en': 'CENTENNIAL'},
'4476406':{'en': 'PageOne'},
'4476407':{'en': 'PageOne'},
'4476404':{'en': 'PageOne'},
'553199163':{'en': 'TIM'},
'55479998':{'en': 'TIM'},
'359996':{'en': 'Bulsatcom'},
'5037780':{'en': 'Movistar'},
'447882':{'en': 'Three'},
'40772':{'en': 'Digi Mobil'},
'553599191':{'en': 'TIM'},
'553899995':{'en': 'Telemig Celular'},
'1787226':{'en': 'SunCom Wireless Puerto Rico'},
'1787227':{'en': 'CENTENNIAL'},
'1787224':{'en': 'CENTENNIAL'},
'1787225':{'en': 'SunCom Wireless Puerto Rico'},
'1787222':{'en': 'CENTENNIAL'},
'1787223':{'en': 'CENTENNIAL'},
'1787220':{'en': 'CENTENNIAL'},
'1787221':{'en': 'CENTENNIAL'},
'553599197':{'en': 'TIM'},
'447886':{'en': 'Three'},
'447885':{'en': 'O2'},
'447889':{'en': 'O2'},
'553599198':{'en': 'TIM'},
'4475379':{'en': 'Three'},
'4475378':{'en': 'Three'},
'474104':{'en': 'NetCom'},
'474106':{'en': 'NetCom'},
'2341883':{'en': 'Starcomms'},
'2341882':{'en': 'Starcomms'},
'2341881':{'en': 'Starcomms'},
'2341880':{'en': 'Starcomms'},
'1939394':{'en': 'CENTENNIAL'},
'554399156':{'en': 'Vivo'},
'553199939':{'en': 'Telemig Celular'},
'553199938':{'en': 'Telemig Celular'},
'553199931':{'en': 'Telemig Celular'},
'553199933':{'en': 'Telemig Celular'},
'553199932':{'en': 'Telemig Celular'},
'553199935':{'en': 'Telemig Celular'},
'553199934':{'en': 'Telemig Celular'},
'553199937':{'en': 'Telemig Celular'},
'553199936':{'en': 'Telemig Celular'},
'554399157':{'en': 'Vivo'},
'514494804':{'en': 'Movistar'},
'514494802':{'en': 'Movistar'},
'3069601':{'en': 'OTE'},
'514494803':{'en': 'Movistar'},
'351926':{'en': 'MEO'},
'351927':{'en': 'MEO'},
'351925':{'en': 'MEO'},
'351921':{'en': 'Vodafone'},
'346348':{'en': 'Vodafone'},
'346349':{'en': 'Vodafone'},
'316359':{'en': 'ASPIDER Solutions Nederland B.V.'},
'346342':{'en': 'Vodafone'},
'346343':{'en': 'HITS'},
'346340':{'en': 'Lebara'},
'346341':{'en': 'Lebara'},
'346346':{'en': 'Vodafone'},
'316351':{'en': 'Intercity Zakelijk'},
'346344':{'en': 'Eroski movil'},
'346345':{'en': 'PepePhone'},
'554399155':{'en': 'Vivo'},
'551399632':{'en': 'Vivo'},
'551399633':{'en': 'Vivo'},
'551399630':{'en': 'Vivo'},
'551399631':{'en': 'Vivo'},
'551399636':{'en': 'Vivo'},
'551399637':{'en': 'Vivo'},
'551399634':{'en': 'Vivo'},
'551399635':{'en': 'Vivo'},
'33643':{'en': 'Orange France'},
'33642':{'en': 'Orange France'},
'33645':{'en': 'Orange France'},
'33647':{'en': 'Orange France'},
'33646':{'en': 'SFR'},
'33648':{'en': 'Orange France'},
'554199177':{'en': 'Vivo'},
'554199175':{'en': 'Vivo'},
'31649':{'en': 'Telfort'},
'31647':{'en': 'Telfort'},
'31646':{'en': 'Vodafone Libertel B.V.'},
'31645':{'en': 'Telfort'},
'31644':{'en': 'Telfort'},
'31643':{'en': 'T-Mobile'},
'31642':{'en': 'T-Mobile'},
'31641':{'en': 'T-Mobile'},
'31640':{'en': 'Tele2'},
'1473901':{'en': 'Affordable Island Communications'},
'516396399':{'en': 'Movistar'},
'516396398':{'en': 'Movistar'},
'516396393':{'en': 'Movistar'},
'516396392':{'en': 'Movistar'},
'516396391':{'en': 'Movistar'},
'516396390':{'en': 'Movistar'},
'516396395':{'en': 'Movistar'},
'516396394':{'en': 'Movistar'},
'554698822':{'en': 'Claro BR'},
'34699':{'en': 'Movistar'},
'34698':{'en': 'MasMovil'},
'517396995':{'en': 'Movistar'},
'34692':{'en': 'Orange'},
'34691':{'en': 'Orange'},
'34690':{'en': 'Movistar'},
'34697':{'en': 'Vodafone'},
'34696':{'en': 'Movistar'},
'34695':{'en': 'Orange'},
'34694':{'en': 'Movistar'},
'553299145':{'en': 'TIM'},
'553299144':{'en': 'TIM'},
'50586':{'en': 'Claro'},
'553299141':{'en': 'TIM'},
'553299143':{'en': 'TIM'},
'553299142':{'en': 'TIM'},
'553499806':{'en': 'Telemig Celular'},
'50581':{'en': 'Movistar'},
'554698827':{'en': 'Claro BR'},
'552298147':{'en': 'TIM'},
'552298146':{'en': 'TIM'},
'552298145':{'en': 'TIM'},
'552298144':{'en': 'TIM'},
'552298143':{'en': 'TIM'},
'552298142':{'en': 'TIM'},
'552298141':{'en': 'TIM'},
'553799925':{'en': 'Telemig Celular'},
'553599997':{'en': 'Telemig Celular'},
'554698825':{'en': 'Claro BR'},
'553799926':{'en': 'Telemig Celular'},
'552298149':{'en': 'TIM'},
'552298148':{'en': 'TIM'},
'38095':{'en': 'Vodafone'},
'38094':{'en': 'Intertelecom'},
'38097':{'en': 'Kyivstar'},
'38096':{'en': 'Kyivstar'},
'38091':{'en': 'TriMob'},
'1242524':{'en': 'BaTelCo'},
'38093':{'en': 'lifecell'},
'38092':{'en': 'PEOPLEnet'},
'551699716':{'en': 'Vivo'},
'551699717':{'en': 'Vivo'},
'551699714':{'en': 'Vivo'},
'551699715':{'en': 'Vivo'},
'38099':{'en': 'Vodafone'},
'38098':{'en': 'Kyivstar'},
'551699711':{'en': 'Vivo'},
'5528988':{'en': 'Oi'},
'5528989':{'en': 'Oi'},
'2237':{'en': 'Orange'},
'5528986':{'en': 'Oi'},
'5528987':{'en': 'Oi'},
'517396999':{'en': 'Movistar'},
'507219':{'en': u('Telef\u00f3nica M\u00f3viles')},
'507218':{'en': u('Telef\u00f3nica M\u00f3viles')},
'26263963':{'en': 'Orange'},
'26263960':{'en': 'Orange'},
'554599136':{'en': 'Vivo'},
'554599137':{'en': 'Vivo'},
'554599134':{'en': 'Vivo'},
'551799709':{'en': 'Vivo'},
'554599132':{'en': 'Vivo'},
'554599133':{'en': 'Vivo'},
'554599131':{'en': 'Vivo'},
'553799928':{'en': 'Telemig Celular'},
'552499395':{'en': 'Claro BR'},
'26263967':{'en': 'SFR'},
'234701':{'en': 'Airtel'},
'234703':{'en': 'MTN'},
'234704':{'en': 'Visafone'},
'234705':{'en': 'Glo'},
'234706':{'en': 'MTN'},
'234707':{'en': 'Zoom'},
'234708':{'en': 'Airtel'},
'234709':{'en': 'Multilinks'},
'26263965':{'en': 'SFR'},
'554598841':{'en': 'Claro BR'},
'554598842':{'en': 'Claro BR'},
'554198458':{'en': 'Brasil Telecom GSM'},
'554198459':{'en': 'Brasil Telecom GSM'},
'554198456':{'en': 'Brasil Telecom GSM'},
'554198457':{'en': 'Brasil Telecom GSM'},
'554198454':{'en': 'Brasil Telecom GSM'},
'554198455':{'en': 'Brasil Telecom GSM'},
'554198452':{'en': 'Brasil Telecom GSM'},
'554198453':{'en': 'Brasil Telecom GSM'},
'554198451':{'en': 'Brasil Telecom GSM'},
'454291':{'en': '3'},
'35568':{'en': 'Telekom'},
'35569':{'en': 'Vodafone'},
'518498402':{'en': 'Movistar'},
'518498403':{'en': 'Movistar'},
'518498400':{'en': 'Movistar'},
'518498401':{'en': 'Movistar'},
'518498406':{'en': 'Movistar'},
'447806':{'en': 'EE'},
'518498404':{'en': 'Movistar'},
'447804':{'en': 'EE'},
'45428':{'en': 'CBB Mobil'},
'5511997':{'en': 'Vivo'},
'553599913':{'en': 'Telemig Celular'},
'553599912':{'en': 'Telemig Celular'},
'55119658':{'en': 'Claro BR'},
'55119659':{'en': 'Claro BR'},
'553599917':{'en': 'Telemig Celular'},
'553599916':{'en': 'Telemig Celular'},
'553599915':{'en': 'Telemig Celular'},
'553599914':{'en': 'Telemig Celular'},
'553599919':{'en': 'Telemig Celular'},
'553599918':{'en': 'Telemig Celular'},
'55119657':{'en': 'Claro BR'},
'420608':{'en': 'Vodafone'},
'420606':{'en': 'O2'},
'420607':{'en': 'O2'},
'420604':{'en': 'T-Mobile'},
'420605':{'en': 'T-Mobile'},
'420602':{'en': 'O2'},
'420603':{'en': 'T-Mobile'},
'420601':{'en': 'O2'},
'25262':{'en': 'Somtel'},
'25263':{'en': 'Telesom'},
'25264':{'en': 'Somali Networks'},
'25265':{'en': 'Somtel'},
'25266':{'en': 'Somtel'},
'25267':{'en': 'Nationlink'},
'25268':{'en': 'Nationlink'},
'25269':{'en': 'Nationlink'},
'55249990':{'en': 'Vivo'},
'1939250':{'en': 'Claro'},
'1939251':{'en': 'Claro'},
'1939252':{'en': 'CENTENNIAL'},
'1939253':{'en': 'Claro'},
'1939254':{'en': 'Claro'},
'1939255':{'en': 'Claro'},
'1939256':{'en': 'Claro'},
'1939257':{'en': 'Claro'},
'1939258':{'en': 'Claro'},
'1939259':{'en': 'Claro'},
'553199786':{'en': 'Telemig Celular'},
'551699718':{'en': 'Vivo'},
'552498138':{'en': 'TIM'},
'552498139':{'en': 'TIM'},
'551599175':{'en': 'Claro BR'},
'552498131':{'en': 'TIM'},
'552498132':{'en': 'TIM'},
'552498133':{'en': 'TIM'},
'552498134':{'en': 'TIM'},
'552498135':{'en': 'TIM'},
'552498136':{'en': 'TIM'},
'552498137':{'en': 'TIM'},
'551699719':{'en': 'Vivo'},
'553199784':{'en': 'Telemig Celular'},
'459333':{'en': 'Onoffapp'},
'459330':{'en': 'Justfone'},
'459339':{'en': 'Uni-tel'},
'553199785':{'en': 'Telemig Celular'},
'455333':{'en': 'Lebara Limited'},
'33700003':{'en': 'Bouygues'},
'551398152':{'en': 'TIM'},
'551398153':{'en': 'TIM'},
'551398154':{'en': 'TIM'},
'551398155':{'en': 'TIM'},
'551398156':{'en': 'TIM'},
'33700002':{'en': 'Mobiquithings'},
'551398158':{'en': 'TIM'},
'551398159':{'en': 'TIM'},
'33700001':{'en': 'SFR'},
'33700000':{'en': 'Orange France'},
'2348456':{'en': 'Starcomms'},
'2348454':{'en': 'Starcomms'},
'2348453':{'en': 'Starcomms'},
'479277':{'en': 'NetCom'},
'38664':{'en': 'T-2'},
'553799933':{'en': 'Telemig Celular'},
'553799932':{'en': 'Telemig Celular'},
'553799931':{'en': 'Telemig Celular'},
'553799937':{'en': 'Telemig Celular'},
'553799936':{'en': 'Telemig Celular'},
'553799935':{'en': 'Telemig Celular'},
'553799934':{'en': 'Telemig Celular'},
'553799939':{'en': 'Telemig Celular'},
'553799938':{'en': 'Telemig Celular'},
'554799978':{'en': 'TIM'},
'447579':{'en': 'Orange'},
'447578':{'en': 'Three'},
'554799979':{'en': 'TIM'},
'447573':{'en': 'EE'},
'447572':{'en': 'EE'},
'447570':{'en': 'Vodafone'},
'447577':{'en': 'Three'},
'447576':{'en': 'Three'},
'447575':{'en': 'Three'},
'447574':{'en': 'EE'},
'479419':{'en': 'Telenor'},
'479418':{'en': 'Telenor'},
'554799957':{'en': 'TIM'},
'479413':{'en': 'Telenor'},
'479415':{'en': 'Telenor'},
'479414':{'en': 'Telenor'},
'479417':{'en': 'Telenor'},
'479416':{'en': 'Telenor'},
'551298134':{'en': 'TIM'},
'47984':{'en': 'NetCom'},
'47986':{'en': 'NetCom'},
'47980':{'en': 'NetCom'},
'47982':{'en': 'NetCom'},
'47988':{'en': 'NetCom'},
'554799967':{'en': 'TIM'},
'45536':{'en': '3'},
'554799965':{'en': 'TIM'},
'554799964':{'en': 'TIM'},
'474768':{'en': 'Telenor'},
'554799962':{'en': 'TIM'},
'27637':{'en': 'Vodacom'},
'459225':{'en': 'Mundio Mobile'},
'474764':{'en': 'Telenor'},
'474765':{'en': 'Telenor'},
'474766':{'en': 'Telenor'},
'474767':{'en': 'Telenor'},
'474760':{'en': 'Telenor'},
'459226':{'en': 'Mundio Mobile'},
'474762':{'en': 'Telenor'},
'474763':{'en': 'Telenor'},
'45535':{'en': '3'},
'45532':{'en': 'Telia'},
'45533':{'en': 'Telia'},
'551498146':{'en': 'TIM'},
'551498147':{'en': 'TIM'},
'551498144':{'en': 'TIM'},
'551498145':{'en': 'TIM'},
'551498142':{'en': 'TIM'},
'502569':{'en': 'Telgua'},
'551498141':{'en': 'TIM'},
'459223':{'en': '42 Telecom AB'},
'502561':{'en': 'Telgua'},
'502562':{'en': 'Telgua'},
'502563':{'en': 'Telgua'},
'554799619':{'en': 'TIM'},
'554799618':{'en': 'TIM'},
'551899793':{'en': 'Vivo'},
'503749':{'en': 'Tigo'},
'503748':{'en': 'Tigo'},
'503747':{'en': 'Tigo'},
'3465729':{'en': 'DIA'},
'503745':{'en': 'Movistar'},
'554799612':{'en': 'TIM'},
'554799615':{'en': 'TIM'},
'459154':{'en': 'TDC'},
'554799617':{'en': 'TIM'},
'551899795':{'en': 'Vivo'},
'3519294':{'en': 'NOS'},
'554199192':{'en': 'Vivo'},
'551999661':{'en': 'Vivo'},
'554199194':{'en': 'Vivo'},
'551899796':{'en': 'Vivo'},
'554199196':{'en': 'Vivo'},
'553899906':{'en': 'Telemig Celular'},
'554199198':{'en': 'Vivo'},
'553199834':{'en': 'Telemig Celular'},
'551899797':{'en': 'Vivo'},
'553899905':{'en': 'Telemig Celular'},
'553199835':{'en': 'Telemig Celular'},
'553899904':{'en': 'Telemig Celular'},
'553199836':{'en': 'Telemig Celular'},
'553899903':{'en': 'Telemig Celular'},
'55279964':{'en': 'Vivo'},
'55279963':{'en': 'Vivo'},
'55279962':{'en': 'Vivo'},
'55279961':{'en': 'Vivo'},
'3519291':{'en': 'NOS'},
'554398414':{'en': 'Brasil Telecom GSM'},
'3519292':{'en': 'NOS'},
'554398415':{'en': 'Brasil Telecom GSM'},
'3519293':{'en': 'NOS'},
'551298133':{'en': 'TIM'},
'554398416':{'en': 'Brasil Telecom GSM'},
'554398417':{'en': 'Brasil Telecom GSM'},
'1671838':{'en': 'i CAN_GSM'},
'554398411':{'en': 'Brasil Telecom GSM'},
'554398412':{'en': 'Brasil Telecom GSM'},
'14417':{'en': 'Cellular One'},
'554398413':{'en': 'Brasil Telecom GSM'},
'553199321':{'en': 'TIM'},
'1787673':{'en': 'SunCom Wireless Puerto Rico'},
'553199323':{'en': 'TIM'},
'1787675':{'en': 'CENTENNIAL'},
'553199325':{'en': 'TIM'},
'553199326':{'en': 'TIM'},
'553199327':{'en': 'TIM'},
'553199328':{'en': 'TIM'},
'1787678':{'en': 'SunCom Wireless Puerto Rico'},
'26269393':{'en': 'Orange'},
'553799955':{'en': 'Telemig Celular'},
'551899738':{'en': 'Vivo'},
'551899739':{'en': 'Vivo'},
'551298809':{'en': 'Oi'},
'551298808':{'en': 'Oi'},
'551899732':{'en': 'Vivo'},
'551899733':{'en': 'Vivo'},
'551899731':{'en': 'Vivo'},
'551899736':{'en': 'Vivo'},
'551899737':{'en': 'Vivo'},
'551899734':{'en': 'Vivo'},
'551899735':{'en': 'Vivo'},
'553599125':{'en': 'TIM'},
'553199229':{'en': 'TIM'},
'553199228':{'en': 'TIM'},
'553199225':{'en': 'TIM'},
'553199224':{'en': 'TIM'},
'553199227':{'en': 'TIM'},
'553199226':{'en': 'TIM'},
'553199221':{'en': 'TIM'},
'553199223':{'en': 'TIM'},
'553199222':{'en': 'TIM'},
'551598815':{'en': 'Oi'},
'553798411':{'en': 'Claro BR'},
'5036310':{'en': 'Claro'},
'3763':{'en': 'Mobiland'},
'554399139':{'en': 'Vivo'},
'55179922':{'en': 'Claro BR'},
'55179920':{'en': 'Claro BR'},
'55179921':{'en': 'Claro BR'},
'515495828':{'en': 'Claro'},
'515495829':{'en': 'Claro'},
'43660':{'en': 'Hutchison Drei Austria'},
'43664':{'en': 'A1 TA'},
'553899177':{'en': 'TIM'},
'553798417':{'en': 'Claro BR'},
'553899174':{'en': 'TIM'},
'553899175':{'en': 'TIM'},
'516495410':{'en': 'Claro'},
'516495411':{'en': 'Claro'},
'516495412':{'en': 'Claro'},
'553899173':{'en': 'TIM'},
'517697693':{'en': 'Movistar'},
'517697692':{'en': 'Movistar'},
'515495895':{'en': 'Claro'},
'515495894':{'en': 'Movistar'},
'517697697':{'en': 'Movistar'},
'517697696':{'en': 'Movistar'},
'515495891':{'en': 'Movistar'},
'517697694':{'en': 'Movistar'},
'517697699':{'en': 'Movistar'},
'517697698':{'en': 'Movistar'},
'515495898':{'en': 'Claro'},
'3469399':{'en': 'MasMovil'},
'3469398':{'en': 'MasMovil'},
'3469395':{'en': 'MasMovil'},
'3469394':{'en': 'MasMovil'},
'3469397':{'en': 'MasMovil'},
'3469396':{'en': 'MasMovil'},
'3469391':{'en': 'MasMovil'},
'3469393':{'en': 'MasMovil'},
'3469392':{'en': 'MasMovil'},
'553798415':{'en': 'Claro BR'},
'554399174':{'en': 'Vivo'},
'4476020':{'en': 'O2'},
'4476022':{'en': 'Relax'},
'553199918':{'en': 'Telemig Celular'},
'553199917':{'en': 'Telemig Celular'},
'553199916':{'en': 'Telemig Celular'},
'553199915':{'en': 'Telemig Celular'},
'553199914':{'en': 'Telemig Celular'},
'553199913':{'en': 'Telemig Celular'},
'553199912':{'en': 'Telemig Celular'},
'553199911':{'en': 'Telemig Celular'},
'553798414':{'en': 'Claro BR'},
'359999':{'en': 'MAX'},
'554399171':{'en': 'Vivo'},
'554399172':{'en': 'Vivo'},
'554399173':{'en': 'Vivo'},
'551698158':{'en': 'TIM'},
'5516991':{'en': 'Claro BR'},
'5516992':{'en': 'Claro BR'},
'503642':{'en': 'Movistar'},
'551799702':{'en': 'Vivo'},
'551799703':{'en': 'Vivo'},
'26263968':{'en': 'SFR'},
'26263969':{'en': 'SFR'},
'37498':{'en': 'VivaCell-MTS', 'ru': u('\u0412\u0438\u0432\u0430\u0421\u0435\u043b\u043b-\u041c\u0422\u0421')},
'37499':{'en': 'Beeline', 'ru': u('\u0411\u0438\u043b\u0430\u0439\u043d')},
'551799704':{'en': 'Vivo'},
'551799705':{'en': 'Vivo'},
'37494':{'en': 'VivaCell-MTS', 'ru': u('\u0412\u0438\u0432\u0430\u0421\u0435\u043b\u043b-\u041c\u0422\u0421')},
'37495':{'en': 'Ucom', 'ru': u('\u042e\u043a\u043e\u043c')},
'37496':{'en': 'Beeline', 'ru': u('\u0411\u0438\u043b\u0430\u0439\u043d')},
'26263961':{'en': 'Orange'},
'26263966':{'en': 'SFR'},
'37491':{'en': 'Beeline', 'ru': u('\u0411\u0438\u043b\u0430\u0439\u043d')},
'26263964':{'en': 'Orange'},
'37493':{'en': 'VivaCell-MTS', 'ru': u('\u0412\u0438\u0432\u0430\u0421\u0435\u043b\u043b-\u041c\u0422\u0421')},
'212639':{'en': 'Maroc Telecom'},
'516396371':{'en': 'Claro'},
'516396370':{'en': 'Claro'},
'516396373':{'en': 'Claro'},
'516396372':{'en': 'Claro'},
'33700004':{'en': 'Afone'},
'551499152':{'en': 'Claro BR'},
'551499153':{'en': 'Claro BR'},
'551499151':{'en': 'Claro BR'},
'551499156':{'en': 'Claro BR'},
'551499157':{'en': 'Claro BR'},
'551499154':{'en': 'Claro BR'},
'551499155':{'en': 'Claro BR'},
'552798152':{'en': 'TIM'},
'551698153':{'en': 'TIM'},
'552798151':{'en': 'TIM'},
'552298129':{'en': 'TIM'},
'552298128':{'en': 'TIM'},
'552298125':{'en': 'TIM'},
'552298124':{'en': 'TIM'},
'552298127':{'en': 'TIM'},
'552298126':{'en': 'TIM'},
'552298121':{'en': 'TIM'},
'552298123':{'en': 'TIM'},
'552298122':{'en': 'TIM'},
'14413':{'en': 'Mobility'},
'515395361':{'en': 'Movistar'},
'26269399':{'en': 'Orange'},
'515395363':{'en': 'Movistar'},
'515395364':{'en': 'Movistar'},
'552798155':{'en': 'TIM'},
'515395366':{'en': 'Movistar'},
'515395367':{'en': 'Movistar'},
'515395368':{'en': 'Movistar'},
'26269392':{'en': 'Orange'},
'26269391':{'en': 'Orange'},
'26269390':{'en': 'Orange'},
'26269397':{'en': 'SFR'},
'554399135':{'en': 'Vivo'},
'26269394':{'en': 'SFR'},
'551699734':{'en': 'Vivo'},
'551699735':{'en': 'Vivo'},
'551699736':{'en': 'Vivo'},
'551699737':{'en': 'Vivo'},
'551699731':{'en': 'Vivo'},
'551699732':{'en': 'Vivo'},
'551699733':{'en': 'Vivo'},
'551699738':{'en': 'Vivo'},
'551699739':{'en': 'Vivo'},
'1242544':{'en': 'BaTelCo'},
'3859751':{'en': 'Telefocus'},
'551698151':{'en': 'TIM'},
'554599118':{'en': 'Vivo'},
'554599119':{'en': 'Vivo'},
'554599114':{'en': 'Vivo'},
'554599115':{'en': 'Vivo'},
'554599116':{'en': 'Vivo'},
'554599117':{'en': 'Vivo'},
'554599111':{'en': 'Vivo'},
'554599112':{'en': 'Vivo'},
'554599113':{'en': 'Vivo'},
'554299121':{'en': 'Vivo'},
'554399137':{'en': 'Vivo'},
'38349':{'en': 'IPKO'},
'38343':{'en': 'IPKO'},
'38344':{'en': 'vala'},
}
| 30.90422 | 125 | 0.534352 |
853ce69d490231a61e4aa709851cc82f2604cd6d | 181 | py | Python | EvenOdd.py | rajatgarg149/Daily_python_practice | 2f077e9f6432cc1c2232377256743a7dbdc25a28 | [
"MIT"
] | null | null | null | EvenOdd.py | rajatgarg149/Daily_python_practice | 2f077e9f6432cc1c2232377256743a7dbdc25a28 | [
"MIT"
] | null | null | null | EvenOdd.py | rajatgarg149/Daily_python_practice | 2f077e9f6432cc1c2232377256743a7dbdc25a28 | [
"MIT"
] | null | null | null | '''This program defines a number as odd/even'''
print('Hello user!')
number = input('Type a number.\n')
if int(number)%2: print('\nNumber is ODD.')
else: print('\nNumber is Even.')
| 30.166667 | 47 | 0.674033 |
7eedcf135de978fae49476805aab413f0bea9ed2 | 2,056 | py | Python | asreview/models/feature_extraction/utils.py | BartJanBoverhof/asreview | 33894ebebf7bda2c552b707c3725c0287ac00369 | [
"Apache-2.0"
] | null | null | null | asreview/models/feature_extraction/utils.py | BartJanBoverhof/asreview | 33894ebebf7bda2c552b707c3725c0287ac00369 | [
"Apache-2.0"
] | null | null | null | asreview/models/feature_extraction/utils.py | BartJanBoverhof/asreview | 33894ebebf7bda2c552b707c3725c0287ac00369 | [
"Apache-2.0"
] | null | null | null | # Copyright 2019-2020 The ASReview 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 asreview.utils import list_model_names
from asreview.utils import _model_class_from_entry_point
def list_feature_extraction():
"""List available feature extraction methods.
Returns
-------
list:
Names of available feature extraction methods in alphabetical order.
"""
return list_model_names(entry_name="asreview.models.feature_extraction")
def get_feature_class(name):
"""Get class of feature extraction from string.
Arguments
---------
name: str
Name of the feature model, e.g. 'doc2vec', 'tfidf' or 'embedding-lstm'.
Returns
-------
BaseFeatureExtraction:
Class corresponding to the name.
"""
return _model_class_from_entry_point(name, "asreview.models.feature_extraction")
def get_feature_model(name, *args, random_state=None, **kwargs):
"""Get an instance of a feature extraction model from a string.
Arguments
---------
name: str
Name of the feature extraction model.
*args:
Arguments for the feature extraction model.
**kwargs:
Keyword arguments for thefeature extraction model.
Returns
-------
BaseFeatureExtraction:
Initialized instance of feature extraction algorithm.
"""
model_class = get_feature_class(name)
try:
return model_class(*args, random_state=random_state, **kwargs)
except TypeError:
return model_class(*args, **kwargs)
| 30.235294 | 84 | 0.704767 |
b24eec5dd08d94581f27a930dd7a27380f32ff6b | 501 | py | Python | channelshowdown/event/migrations/0004_auto_20180405_2212.py | channelfix/cshowdown-backend | 4225ad4f2bd56112f627e6fe1f26c281484d804e | [
"MIT"
] | null | null | null | channelshowdown/event/migrations/0004_auto_20180405_2212.py | channelfix/cshowdown-backend | 4225ad4f2bd56112f627e6fe1f26c281484d804e | [
"MIT"
] | 6 | 2018-02-19T02:41:20.000Z | 2022-03-11T23:19:40.000Z | channelshowdown/event/migrations/0004_auto_20180405_2212.py | emilarran/channelshowdown_final | 0bcc8766af66719934bf744d0be2a90e96359761 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
# Generated by Django 1.11.10 on 2018-04-05 14:12
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('event', '0003_auto_20180404_2245'),
]
operations = [
migrations.AlterField(
model_name='event',
name='event_image',
field=models.ImageField(default='event_image/default.png', upload_to='event_image/'),
),
]
| 23.857143 | 97 | 0.634731 |
bd0057fb1a0175a805a0f7a1e4dcaa2bdc3c435a | 5,721 | py | Python | tensorflow/contrib/eager/python/examples/densenet/densenet_graph_test.py | kekeblom/tensorflow | be8184f8e002576aa2ef3274436dea68e9173c5f | [
"Apache-2.0"
] | 3 | 2020-01-13T19:44:49.000Z | 2020-10-10T02:26:52.000Z | tensorflow/contrib/eager/python/examples/densenet/densenet_graph_test.py | AKIRA-MIYAKE/tensorflow | 89e06304aad35bfb019a8c10f39fc1ead83e0f99 | [
"Apache-2.0"
] | 4 | 2019-08-14T22:32:51.000Z | 2020-03-09T14:59:18.000Z | tensorflow/contrib/eager/python/examples/densenet/densenet_graph_test.py | AKIRA-MIYAKE/tensorflow | 89e06304aad35bfb019a8c10f39fc1ead83e0f99 | [
"Apache-2.0"
] | 1 | 2018-08-21T21:53:14.000Z | 2018-08-21T21:53:14.000Z | # Copyright 2018 The TensorFlow 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.
# ==============================================================================
"""Tests and Benchmarks for Densenet model under graph execution."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import time
import numpy as np
import tensorflow as tf
from tensorflow.contrib.eager.python.examples.densenet import densenet
def data_format():
return 'channels_first' if tf.test.is_gpu_available() else 'channels_last'
def image_shape(batch_size):
if data_format() == 'channels_first':
return [batch_size, 3, 224, 224]
return [batch_size, 224, 224, 3]
def random_batch(batch_size):
images = np.random.rand(*image_shape(batch_size)).astype(np.float32)
num_classes = 1000
labels = np.random.randint(
low=0, high=num_classes, size=[batch_size]).astype(np.int32)
one_hot = np.zeros((batch_size, num_classes)).astype(np.float32)
one_hot[np.arange(batch_size), labels] = 1.
return images, one_hot
class DensenetGraphTest(tf.test.TestCase):
def testApply(self):
depth = 7
growth_rate = 2
num_blocks = 3
output_classes = 10
num_layers_in_each_block = -1
batch_size = 1
with tf.Graph().as_default():
images = tf.placeholder(tf.float32, image_shape(None))
model = densenet.DenseNet(depth, growth_rate, num_blocks,
output_classes, num_layers_in_each_block,
data_format(), bottleneck=True, compression=0.5,
weight_decay=1e-4, dropout_rate=0,
pool_initial=False, include_top=True)
predictions = model(images, training=False)
init = tf.global_variables_initializer()
with tf.Session() as sess:
sess.run(init)
np_images, _ = random_batch(batch_size)
out = sess.run(predictions, feed_dict={images: np_images})
self.assertAllEqual([batch_size, output_classes], out.shape)
class DensenetBenchmark(tf.test.Benchmark):
def __init__(self):
self.depth = 121
self.growth_rate = 32
self.num_blocks = 4
self.output_classes = 1000
self.num_layers_in_each_block = [6, 12, 24, 16]
def _report(self, label, start, num_iters, batch_size):
avg_time = (time.time() - start) / num_iters
dev = 'gpu' if tf.test.is_gpu_available() else 'cpu'
name = 'graph_%s_%s_batch_%d_%s' % (label, dev, batch_size, data_format())
extras = {'examples_per_sec': batch_size / avg_time}
self.report_benchmark(
iters=num_iters, wall_time=avg_time, name=name, extras=extras)
def benchmark_graph_apply(self):
with tf.Graph().as_default():
images = tf.placeholder(tf.float32, image_shape(None))
model = densenet.DenseNet(self.depth, self.growth_rate, self.num_blocks,
self.output_classes,
self.num_layers_in_each_block, data_format(),
bottleneck=True, compression=0.5,
weight_decay=1e-4, dropout_rate=0,
pool_initial=True, include_top=True)
predictions = model(images, training=False)
init = tf.global_variables_initializer()
batch_size = 64
with tf.Session() as sess:
sess.run(init)
np_images, _ = random_batch(batch_size)
num_burn, num_iters = (3, 30)
for _ in range(num_burn):
sess.run(predictions, feed_dict={images: np_images})
start = time.time()
for _ in range(num_iters):
sess.run(predictions, feed_dict={images: np_images})
self._report('apply', start, num_iters, batch_size)
def benchmark_graph_train(self):
for batch_size in [16, 32, 64]:
with tf.Graph().as_default():
np_images, np_labels = random_batch(batch_size)
dataset = tf.data.Dataset.from_tensors((np_images, np_labels)).repeat()
(images, labels) = dataset.make_one_shot_iterator().get_next()
model = densenet.DenseNet(self.depth, self.growth_rate, self.num_blocks,
self.output_classes,
self.num_layers_in_each_block, data_format(),
bottleneck=True, compression=0.5,
weight_decay=1e-4, dropout_rate=0,
pool_initial=True, include_top=True)
logits = model(images, training=True)
loss = tf.losses.softmax_cross_entropy(
logits=logits, onehot_labels=labels)
optimizer = tf.train.GradientDescentOptimizer(learning_rate=1.0)
train_op = optimizer.minimize(loss)
init = tf.global_variables_initializer()
with tf.Session() as sess:
sess.run(init)
(num_burn, num_iters) = (5, 10)
for _ in range(num_burn):
sess.run(train_op)
start = time.time()
for _ in range(num_iters):
sess.run(train_op)
self._report('train', start, num_iters, batch_size)
if __name__ == '__main__':
tf.test.main()
| 38.14 | 80 | 0.638 |
dcec7fb3361983d4752052a8876dec25290a247b | 3,032 | py | Python | Source/GUI_2/alertloop.py | sameertodkar/Car-Health-Monitor | ff43dbe513e2fd35e37909b0021c3e08e95cc959 | [
"RSA-MD"
] | null | null | null | Source/GUI_2/alertloop.py | sameertodkar/Car-Health-Monitor | ff43dbe513e2fd35e37909b0021c3e08e95cc959 | [
"RSA-MD"
] | null | null | null | Source/GUI_2/alertloop.py | sameertodkar/Car-Health-Monitor | ff43dbe513e2fd35e37909b0021c3e08e95cc959 | [
"RSA-MD"
] | null | null | null | from alertsys import checkcond
import time
import json
debug = True
def select_thresh():
"""This is a function to set thresholds of parameters
These would be used by the notification system to compare
with the sensor values and send an email.
Returns:
{(int,int,str)} -- (threshold 1, thereshold 2,user's email)
"""
# load data from the parameters.txt file
with open('parameters.txt', 'r') as f:
data = f.read()
data = data.replace('\'', '\"')
json_dict = json.loads(data)
# extract data from the json
category1 = json_dict['category1']
category2 = json_dict['category2']
email = json_dict['email']
# set default values for category1 and category2, in case they have not been set
if category1 == "":
category1 = "Summer"
if category2 == "":
category2 = "Car"
# for debuging
if debug:
print('Selected categories: ')
print('category2: ' , category2, end = ', ')
print('category1: ', category1 )
print('-'*100)
# threshold selection criterion
if category2 == "Car":
if category1 == "Summer":
# Temperature in celsius
thresh_engineTemp = 107
print('Engine temperature threshold set to: ', thresh_engineTemp)
# Pressure in psi
thresh_tirePressure = 28
print('Time pressure threshold set to: ', thresh_tirePressure)
elif category1 == "Winter":
thresh_engineTemp = 102
print('Engine temperature threshold set to: ', thresh_engineTemp)
thresh_tirePressure = 31
print('Time pressure threshold set to: ', thresh_tirePressure)
elif category2 == "Truck":
if category1 == "Summer":
thresh_engineTemp = 115
print('Engine temperature threshold set to: ', thresh_engineTemp)
thresh_tirePressure = 31
print('Time pressure threshold set to: ', thresh_tirePressure)
elif category1 == "Winter":
thresh_engineTemp = 110
print('Engine temperature threshold set to: ', thresh_engineTemp)
thresh_tirePressure = 34
print('Time pressure threshold set to: ', thresh_tirePressure)
thresh_tireDistanceKm = 60000
print('Tire max distance threshold set to: ', thresh_tireDistanceKm)
thresh_oilTimehrs = 5000
print('oil max time threshold set to: ', thresh_oilTimehrs)
print('\n')
return (thresh_engineTemp, thresh_tirePressure, thresh_oilTimehrs, thresh_tireDistanceKm, email)
# intialize flag as false indicating no maintainance or replacement is required
f = False
# an infite loop which will continue running until maintainance or replacement is required
while True:
print('_'*100)
if not f:
print('waiting for update')
print('Comparing data with thresholds ... ')
(t1, t2, t3, t4, email) = select_thresh()
f = checkcond(f, t1, t2, t3, t4, email)
else:
break
time.sleep(5)
| 33.318681 | 100 | 0.634894 |
b260a16d32b75dfda3b55385801f3a27e2c6195e | 558 | py | Python | morango/migrations/0004_auto_20170520_2112.py | indirectlylit/morango | 380cab228a72a0ac6a20926ae6963cb76054b9e1 | [
"MIT"
] | 9 | 2016-09-16T03:13:41.000Z | 2021-07-23T20:48:50.000Z | docker/alpine/kolibri/dist/morango/migrations/0004_auto_20170520_2112.py | sanmoy/kolibri-azure | 9becf1c167225e6cf20f25b379f3d7f27486e56d | [
"MIT"
] | 117 | 2016-09-13T22:21:12.000Z | 2022-03-09T16:31:12.000Z | docker/alpine/kolibri/dist/morango/migrations/0004_auto_20170520_2112.py | sanmoy/kolibri-azure | 9becf1c167225e6cf20f25b379f3d7f27486e56d | [
"MIT"
] | 11 | 2016-09-13T20:13:58.000Z | 2022-02-03T07:59:41.000Z | # -*- coding: utf-8 -*-
# Generated by Django 1.9 on 2017-05-20 21:12
from __future__ import unicode_literals
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [("morango", "0003_auto_20170519_0543")]
operations = [
migrations.RemoveField(model_name="scopedefinition", name="key"),
migrations.RemoveField(model_name="scopedefinition", name="serialized"),
migrations.RemoveField(model_name="scopedefinition", name="signature"),
migrations.DeleteModel(name="TrustedKey"),
]
| 31 | 80 | 0.715054 |
7d3ad3242f85e43b5cbae4ddb63f2cec498916c7 | 22,583 | py | Python | src/genie/libs/parser/iosxe/show_monitor.py | ykoehler/genieparser | b62cf622c3d8eab77c7b69e932c214ed04a2565a | [
"Apache-2.0"
] | null | null | null | src/genie/libs/parser/iosxe/show_monitor.py | ykoehler/genieparser | b62cf622c3d8eab77c7b69e932c214ed04a2565a | [
"Apache-2.0"
] | null | null | null | src/genie/libs/parser/iosxe/show_monitor.py | ykoehler/genieparser | b62cf622c3d8eab77c7b69e932c214ed04a2565a | [
"Apache-2.0"
] | null | null | null | ''' show_monitor.py
IOSXE parsers for the following show commands:
* show monitor
* show monitor session {session}
* show monitor session all
* show monitor capture
'''
# Python
import re
import xmltodict
from netaddr import IPAddress, IPNetwork
# Metaparser
from genie.metaparser import MetaParser
from genie.metaparser.util.schemaengine import Schema, Any, Or, Optional, And, Default, Use
# import parser utils
from genie.libs.parser.utils.common import Common
# =========================================
# Schema for 'show monitor'
# =========================================
class ShowMonitorSchema(MetaParser):
''' Schema for "show monitor" '''
schema = {
'session':
{Any():
{'type':str,
Optional('status'):str,
Optional('source_ports'):
{Any(): str,
},
Optional('source_subinterfaces'):
{Any(): str,
},
Optional('source_vlans'):
{Any():str,
},
Optional('filter_access_group'): int,
Optional('destination_ports'): str,
Optional('destination_ip_address'): str,
Optional('destination_erspan_id'): str,
Optional('origin_ip_address'): str,
Optional('source_erspan_id'): str,
Optional('source_ip_address'): str,
Optional('source_rspan_vlan'): int,
Optional('dest_rspan_vlan'): int,
Optional('mtu'): int,
},
},
}
# =========================================
# Parser for 'show monitor'
# =========================================
class ShowMonitor(ShowMonitorSchema):
''' Parser for
"show monitor"
"show monitor session {session}"
"show monitor session all"
'''
cli_command = ['show monitor', 'show monitor session {session}', 'show monitor session all']
def cli(self, session="", all="", output=None):
if output is None:
if all:
cmd = self.cli_command[2]
elif session:
cmd = self.cli_command[1].format(session=session)
else:
cmd = self.cli_command[0]
out = self.device.execute(cmd)
else:
out = output
# Init vars
ret_dict = {}
src_ports = False
source_subintfs = False
# Session 1
p1 = re.compile(r'Session +(?P<session>(\d+))')
# Type : ERSPAN Source Session
# Type: ERSPAN Source Session
p2 = re.compile(r'^Type *: +(?P<type>([a-zA-Z\s]+))$')
# Status : Admin Enabled
# Status: Admin Enabled
p3 = re.compile(r'^Status *: +(?P<status>([a-zA-Z\s]+))$')
# Source Ports :
p4_1 = re.compile(r'^Source +Ports +:$')
# TX Only : Gi0/1/4
# Both : Gi0/1/4
p4_2 = re.compile(r'(?P<key>(TX Only|Both)) *: +(?P<src_val>(\S+))$')
# Source Subinterfaces:
p5_1 = re.compile(r'^Source +Subinterfaces:$')
# Both: Gi2/2/0.100
#p5_2 = re.compile(r'^(?P<key>(Both)) *: +(?P<val>([\w\/\.]+))$')
# Source VLANs :
p6_1 = re.compile(r'^Source +VLANs +:$')
# RX Only : 20
p6_2 = re.compile(r'^(?P<key>(RX Only)) *: +(?P<rx_val>(\d+))$')
# Filter Access-Group: 100
p7 = re.compile(r'^Filter +Access-Group: +(?P<filter_access_group>(\d+))$')
# Destination Ports : Gi0/1/6 Gi0/1/2
p8 = re.compile(r'^Destination +Ports +: +(?P<destination_ports>([a-zA-Z0-9\/\s]+))$')
# Destination IP Address : 172.18.197.254
p9 = re.compile(r'^Destination +IP +Address +: +(?P<destination_ip_address>([0-9\.\:]+))$')
# Destination ERSPAN ID : 1
p10 = re.compile(r'^Destination +ERSPAN +ID +: +(?P<destination_erspan_Id>([0-9]+))$')
# Origin IP Address : 172.18.197.254
p11 = re.compile(r'^Origin +IP +Address *: +(?P<origin_ip_address>([0-9\.\:]+))$')
# Source ERSPAN ID : 1
p12 = re.compile(r'^Source +ERSPAN +ID +: +(?P<source_erspan_Id>([0-9]+))$')
# Source IP Address : 172.18.197.254
p13 = re.compile(r'^Source +IP +Address +: +(?P<source_ip_address>([0-9\.\:]+))$')
# Source RSPAN VLAN : 100
p14 = re.compile(r'^Source +RSPAN +VLAN :+ (?P<source_rspan_vlan>(\d+))$')
# Dest RSPAN VLAN : 100
p15 = re.compile(r'^Dest +RSPAN +VLAN :+ (?P<dest_rspan_vlan>(\d+))$')
# MTU : 1464
p16 = re.compile(r'^MTU +: +(?P<mtu>([0-9]+))$')
for line in out.splitlines():
line = line.strip()
# Session 1
m = p1.match(line)
if m:
session = m.groupdict()['session']
session_dict = ret_dict.setdefault('session', {}).setdefault(session, {})
continue
# Type : ERSPAN Source Session
m = p2.match(line)
if m:
session_dict['type'] = str(m.groupdict()['type'])
continue
# Status : Admin Enabled
m = p3.match(line)
if m:
session_dict['status'] = str(m.groupdict()['status'])
continue
# Source Ports :
m = p4_1.match(line)
if m:
src_ports_dict = session_dict.setdefault('source_ports', {})
src_ports = True
source_subintfs = False
continue
# TX Only : Gi0/1/4
# Both : Gi0/1/4
m = p4_2.match(line)
if m:
group = m.groupdict()
key = group['key'].lower().replace(" ", "_")
# Set keys
if src_ports:
src_ports_dict[key] = group['src_val']
elif source_subintfs:
source_sub_dict[key] = group['src_val']
continue
# Source Subinterfaces:
m = p5_1.match(line)
if m:
source_sub_dict = session_dict.setdefault('source_subinterfaces', {})
src_ports = False
source_subintfs = True
continue
# Source VLANs :
m = p6_1.match(line)
if m:
source_vlan_dict = session_dict.setdefault('source_vlans', {})
continue
# RX Only : 20
m = p6_2.match(line)
if m:
group = m.groupdict()
key = group['key'].lower().replace(" ", "_")
source_vlan_dict[key] = group['rx_val']
continue
# Filter Access-Group: 100
m = p7.match(line)
if m:
session_dict['filter_access_group'] = int(m.groupdict()['filter_access_group'])
continue
# Destination Ports : Gi0/1/6 Gi0/1/2
m = p8.match(line)
if m:
session_dict['destination_ports'] = str(m.groupdict()['destination_ports'])
continue
# Destination IP Address : 172.18.197.254
m = p9.match(line)
if m:
session_dict['destination_ip_address'] = str(m.groupdict()['destination_ip_address'])
continue
# Destination ERSPAN ID : 1
m = p10.match(line)
if m:
session_dict['destination_erspan_id'] = str(m.groupdict()['destination_erspan_Id'])
continue
# Origin IP Address : 172.18.197.254
m = p11.match(line)
if m:
session_dict['origin_ip_address'] = str(m.groupdict()['origin_ip_address'])
continue
# Source ERSPAN ID : 1
m = p12.match(line)
if m:
session_dict['source_erspan_id'] = str(m.groupdict()['source_erspan_Id'])
continue
# Source IP Address : 172.18.197.254
m = p13.match(line)
if m:
session_dict['source_ip_address'] = str(m.groupdict()['source_ip_address'])
continue
# Source RSPAN VLAN : 100
m = p14.match(line)
if m:
session_dict['source_rspan_vlan'] = int(m.groupdict()['source_rspan_vlan'])
continue
# Dest RSPAN VLAN : 100
m = p15.match(line)
if m:
session_dict['dest_rspan_vlan'] = int(m.groupdict()['dest_rspan_vlan'])
continue
# MTU : 1464
m = p16.match(line)
if m:
session_dict['mtu'] = int(m.groupdict()['mtu'])
continue
return ret_dict
# =========================================
# Schema for 'show monitor capture'
# =========================================
class ShowMonitorCaptureSchema(MetaParser):
''' Schema for "show monitor capture" '''
schema = {
'status_information':
{Any():
{'target_type':
{'interface': str,
'direction': str,
'status': str,
},
'filter_details':
{'filter_details_type':str,
Optional('source_ip'):str,
Optional('destination_ip'): str,
Optional('protocol'): str,
},
'buffer_details':
{'buffer_type': str,
Optional('buffer_size'): int,
},
Optional('file_details'):
{Optional('file_name'): str,
Optional('file_size'): int,
Optional('file_number'): int,
Optional('size_of_buffer'): int
},
'limit_details':
{'packets_number': int,
'packets_capture_duaration': int,
'packets_size': int,
Optional('maximum_packets_number'): int,
Optional('packets_per_second'): int,
'packet_sampling_rate': int,
},
},
},
}
# =========================================
# Parser for 'show monitor capture'
# =========================================
class ShowMonitorCapture(ShowMonitorCaptureSchema):
''' Parser for
"show monitor capture"
'''
cli_command = 'show monitor capture'
def cli(self, output=None):
if output is None:
# Execute command on device
out = self.device.execute(self.cli_command)
else:
out = output
# Init vars
ret_dict = {}
# Status Information for Capture CAPTURE
# Status Information for Capture NTP
p1 = re.compile(r'^Status +Information +for +Capture +(?P<status_information>(\w+))$')
# Target Type:
p2 = re.compile(r'^Target +Type:+$')
# Interface: Control Plane, Direction : both
# Interface: GigabitEthernet0/0/0, Direction: both
p2_1 = re.compile(r'^Interface: +(?P<interface>([\w\s\/]+)), +Direction *:+ (?P<direction>(\w+))$')
# Status : Inactive
p2_2 = re.compile(r'^Status +: +(?P<status>(\w+))$')
# Filter Details:
p3=re.compile(r'^Filter +Details:+$')
# Capture all packets
# IPv4
p3_1 = re.compile(r'^(?P<filter_details_type>([\w\s]+))$')
# Source IP: any
p3_2=re.compile(r'^Source +IP: +(?P<source_ip>(\w+))$')
# Destination IP: any
p3_3 = re.compile(r'^Destination +IP: +(?P<destination_ip>(\w+))$')
#Protocol: any
p3_4 = re.compile(r'^Protocol: +(?P<protocol>(\w+))$')
# Buffer Details:
p4 = re.compile(r'^Buffer +Details:+$')
# Buffer Type: LINEAR (default)
p4_1 = re.compile(r'^Buffer +Type: +(?P<buffer_type>(.*))$')
# Buffer Size (in MB): 10
p4_2 = re.compile(r'^Buffer +Size +\(in MB\): +(?P<buffer_size>(\d+))$')
# File Details:
p5 = re.compile(r'^File +Details:+$')
# Associated file name: flash:mycap.pcap
p5_1 = re.compile(r'^Associated +file +name: +(?P<file_name>(.*))$')
# Total size of files(in MB): 5
p5_2 = re.compile(r'^Total +size +of +files+\(in MB\): +(?P<file_size>(\d+))$')
# Number of files in ring: 2
p5_3 = re.compile(r'^Number +of +files +in +ring: +(?P<file_number>(\d+))$')
# Size of buffer(in MB): 10
p5_4 = re.compile(r'^Size +of +buffer+\(in MB\): +(?P<size_of_buffer>(\d+))$')
# Limit Details:
p6 = re.compile(r'^Limit +Details:+$')
# Number of Packets to capture: 0 (no limit)
p6_1 = re.compile(r'^Number +of +Packets +to +capture: +(?P<packets_number>(\d+))')
# Packet Capture duration: 0 (no limit)
p6_2 = re.compile(r'^Packet +Capture +duration: +(?P<packets_capture_duaration>(\d+))')
# Packet Size to capture: 0 (no limit)
p6_3 = re.compile(r'^Packet +Size +to +capture: +(?P<packets_size>(\d+))')
# Maximum number of packets to capture per second: 1000
p6_4 = re.compile(r'^Maximum +number +of +packets +to +capture +per +second: +(?P<maximum_packets_number>(\d+))$')
# Packets per second: 0 (no limit)
p6_5=re.compile(r'Packets +per +second: +(?P<packets_per_second>(\d+))')
# Packet sampling rate: 0 (no sampling)
p6_6 = re.compile(r'^Packet +sampling +rate: +(?P<packet_sampling_rate>(\d+))')
for line in out.splitlines():
line = line.strip()
# Status Information for Capture CAPTURE
# Status Information for Capture NTP
m = p1.match(line)
if m:
status_information = m.groupdict()['status_information']
status_dict = ret_dict.setdefault('status_information', {}).setdefault(status_information, {})
continue
# Target Type:
m = p2.match(line)
if m:
target_type_dict = status_dict.setdefault('target_type',{})
continue
# Interface: Control Plane, Direction : both
# Interface: GigabitEthernet0/0/0, Direction: both
m = p2_1.match(line)
if m:
target_type_dict['interface'] = str(m.groupdict()['interface'])
target_type_dict['direction'] = str(m.groupdict()['direction'])
continue
# Status : Active
m = p2_2.match(line)
if m:
target_type_dict['status'] = str(m.groupdict()['status'])
continue
# Filter Details:
m=p3.match(line)
if m:
filter_dict = status_dict.setdefault('filter_details',{})
continue
# Capture all packets
m = p3_1.match(line)
if m:
filter_dict['filter_details_type']=str(m.groupdict()['filter_details_type'])
continue
# Source IP: any
m = p3_2.match(line)
if m:
filter_dict['source_ip'] = str(m.groupdict()['source_ip'])
continue
# Destination IP: any
m = p3_3.match(line)
if m:
filter_dict['destination_ip'] = str(m.groupdict()['destination_ip'])
continue
# Protocol: any
m = p3_4.match(line)
if m:
filter_dict['protocol'] = str(m.groupdict()['protocol'])
continue
# Buffer Details:
m = p4.match(line)
if m:
buffer_dict = status_dict.setdefault('buffer_details',{})
continue
# Buffer Type: LINEAR (default)
m = p4_1.match(line)
if m:
buffer_dict['buffer_type'] = str(m.groupdict()['buffer_type'])
continue
# Buffer Size (in MB): 10
m = p4_2.match(line)
if m:
buffer_dict['buffer_size'] = int(m.groupdict()['buffer_size'])
continue
# File Details:
m = p5.match(line)
if m:
file_dict = status_dict.setdefault('file_details', {})
continue
# Associated file name: flash:mycap.pcap
m = p5_1.match(line)
if m:
file_dict['file_name'] = str(m.groupdict()['file_name'])
continue
# Total size of files(in MB): 5
m = p5_2.match(line)
if m:
file_dict['file_size'] = int(m.groupdict()['file_size'])
continue
# Number of files in ring: 2
m = p5_3.match(line)
if m:
file_dict['file_number'] = int(m.groupdict()['file_number'])
continue
# Size of buffer(in MB): 10
m = p5_4.match(line)
if m:
file_dict['size_of_buffer'] = int(m.groupdict()['size_of_buffer'])
continue
# Limit Details:
m = p6.match(line)
if m:
limit_dict = status_dict.setdefault('limit_details', {})
continue
# Number of Packets to capture: 0 (no limit)
m = p6_1.match(line)
if m:
limit_dict['packets_number'] = int(m.groupdict()['packets_number'])
continue
# Packet Capture duration: 0 (no limit)
m = p6_2.match(line)
if m:
limit_dict['packets_capture_duaration'] = int(m.groupdict()['packets_capture_duaration'])
continue
# Packet Size to capture: 0 (no limit)
m = p6_3.match(line)
if m:
limit_dict['packets_size'] = int(m.groupdict()['packets_size'])
continue
# Maximum number of packets to capture per second: 1000
m = p6_4.match(line)
if m:
limit_dict['maximum_packets_number'] = int(m.groupdict()['maximum_packets_number'])
continue
# Packets per second: 0 (no limit)
m = p6_5.match(line)
if m:
limit_dict['packets_per_second'] = int(m.groupdict()['packets_per_second'])
continue
# Packet sampling rate: 0 (no sampling)
m = p6_6.match(line)
if m:
limit_dict['packet_sampling_rate'] = int(m.groupdict()['packet_sampling_rate'])
continue
return ret_dict
#=================================================
# Schema for 'monitor capture {capture_name} stop'
#=================================================
class MonitorCaptureStopSchema(MetaParser):
schema = {
'capture_duration': int,
'packets_received': int,
'packets_dropped': int,
'packets_oversized': int,
'bytes_dropped_in_asic': int,
'stopped_capture_name': str
}
#=================================================
# Parser for 'monitor capture {capture_name} stop'
#=================================================
class MonitorCaptureStop(MonitorCaptureStopSchema):
cli_command = 'monitor capture {capture_name} stop'
def cli(self, capture_name=None, output=None):
if output is None:
output = self.device.execute(self.cli_command.format(capture_name=capture_name))
# Capture duration - 56 seconds
p1 = re.compile(r'Capture\sduration\s\-\s+(?P<capture_duration>\d+)\s+seconds')
# Packets received - 0
p2 = re.compile(r'Packets\sreceived\s+\-\s+(?P<packets_received>\d+)')
# Packets dropped - 0
p3 = re.compile(r'Packets\sdropped\s+\-\s+(?P<packets_dropped>\d+)')
# Packets oversized - 0
p4 = re.compile(r'Packets\soversized\s+\-\s+(?P<packets_oversized>\d+)')
# Bytes dropped in asic - 0
p5 = re.compile(r'Bytes\sdropped\sin\sasic\s+\-\s+(?P<bytes_dropped_in_asic>\d+)')
# Stopped capture point : cap1
p6 = re.compile(r'Stopped\scapture\spoint\s\:\s+(?P<stopped_capture_name>\S+)')
ret_dict = {}
for line in output.splitlines():
line = line.strip()
# Capture duration - 56 seconds
m = p1.match(line)
if m:
capture_duration = m.groupdict()['capture_duration']
ret_dict.update({'capture_duration': int(capture_duration)})
continue
# Packets received - 0
m = p2.match(line)
if m:
packets_received = m.groupdict()['packets_received']
ret_dict.update({'packets_received': int(packets_received)})
continue
# Packets dropped - 0
m = p3.match(line)
if m:
packets_dropped = m.groupdict()['packets_dropped']
ret_dict.update({'packets_dropped': int(packets_dropped)})
continue
# Packets oversized - 0
m = p4.match(line)
if m:
packets_oversized = m.groupdict()['packets_oversized']
ret_dict.update({'packets_oversized': int(packets_oversized)})
continue
# Bytes dropped in asic - 0
m = p5.match(line)
if m:
bytes_dropped_in_asic = m.groupdict()['bytes_dropped_in_asic']
ret_dict.update({'bytes_dropped_in_asic': int(bytes_dropped_in_asic)})
continue
# Stopped capture point : cap1
m = p6.match(line)
if m:
stopped_capture_name = m.groupdict()['stopped_capture_name']
ret_dict.update({'stopped_capture_name': stopped_capture_name})
continue
return ret_dict
| 34.113293 | 122 | 0.48842 |
c680a27e700c14fb00ea4a0c4f05ca80be97f0bb | 15,886 | py | Python | visualize.py | designer357/MSLSTM | 923f29f5a274ae41dbfe79d99e1ea28bb0cf5109 | [
"MIT"
] | 14 | 2017-07-21T18:31:21.000Z | 2022-01-21T11:39:45.000Z | visualize.py | designer357/MSLSTM | 923f29f5a274ae41dbfe79d99e1ea28bb0cf5109 | [
"MIT"
] | 3 | 2019-06-02T13:00:58.000Z | 2020-04-24T14:40:50.000Z | visualize.py | designer357/MSLSTM | 923f29f5a274ae41dbfe79d99e1ea28bb0cf5109 | [
"MIT"
] | 6 | 2018-02-22T08:26:11.000Z | 2022-03-08T23:32:06.000Z | import matplotlib
#matplotlib.use('GTKAgg')
#matplotlib.rcParams['backend'] = 'GTKCairo'
import os
import loaddata
import numpy as np
#import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import cm
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d import axes3d, Axes3D
import pylab as p
from sklearn import decomposition
def set_style():
plt.style.use(['seaborn-paper'])
matplotlib.rc("font", family="serif")
set_style()
def epoch_acc_plotting(filename,case_list,sequence_window,learning_rate,train_acc_list,val_acc_list):
if not os.path.isdir(os.path.join(os.getcwd(),'picture')):
os.makedirs(os.path.join(os.getcwd(),'picture'))
epoch = len(train_acc_list[0])
color_list = ['y', 'g','#FF8C00','#FD8CD0','c', 'b', 'r', 'm']
#color_list = ['y', 'g', 'c', 'b', 'r', 'm']
x = [i+1 for i in range(epoch)]
plt.figure()
for tab in range(len(case_list)):
plt.plot(x,train_acc_list[tab],color_list[tab],label=case_list[tab] + ' train acc')
plt.plot(x, val_acc_list[tab], color_list[len(case_list)+tab],label=case_list[tab] +' val acc')
plt.xlabel('Epoch',fontsize=12)
if 'AS' in filename:
plt.ylim(0.3,1.05)
else:
plt.ylim(0.05,1.05)
plt.ylabel('Accuracy',fontsize=12)
plt.tick_params(labelsize=12)
plt.grid()
plt.legend(loc='lower right',fontsize=8)
plt.title(filename.split('.')[0].replace('HB_','')+'/sw: '+str(sequence_window))
plt.savefig(os.path.join(os.path.join(os.getcwd(),'picture'),"Epoch_ACC_"+filename + "_SW_"+str(sequence_window)+".pdf"),dpi=400)
#if corss_val_label == 0:
#plt.savefig(os.path.join(os.path.join(os.getcwd(),'picture'),"2Tab_A_Epoch_ACC_"+filename + "_SW_"+str(sequence_window)+".pdf"),dpi=400)
#plt.savefig(os.path.join(os.path.join(os.getcwd(),'picture'),"Tab_A_Epoch_ACC_"+filename + "_SW_"+str(sequence_window)+"_LR_"+str(learning_rate)+".png"),dpi=400)
#else:
#plt.savefig(os.path.join(os.path.join(os.getcwd(),'picture'),"2Tab_B_Epoch_ACC_" + filename + "_SW_"+str(sequence_window)+".pdf"), dpi=400)
#plt.savefig(os.path.join(os.path.join(os.getcwd(),'picture'),"Tab_B_Epoch_ACC_" + filename + "_SW_"+str(sequence_window)+"_LR_"+str(learning_rate)+".png"), dpi=400)
def epoch_loss_plotting(filename,case_list,sequence_window,learning_rate,train_loss_list,val_loss_list):
if not os.path.isdir(os.path.join(os.getcwd(),'picture')):
os.makedirs(os.path.join(os.getcwd(),'picture'))
epoch = len(train_loss_list[0])
color_list = ['y', 'g','#FF8C00','#FD8CD0','c', 'b', 'r', 'm']
x = [i+1 for i in range(epoch)]
plt.figure()
for tab in range(len(case_list)):
plt.plot(x,train_loss_list[tab],color_list[tab],label=case_list[tab] + ' train loss')
plt.plot(x, val_loss_list[tab], color_list[len(case_list)+tab],label=case_list[tab] +' val loss')
plt.xlabel('Epoch',fontsize=12)
plt.ylabel('Loss',fontsize=12)
plt.grid()
plt.tick_params(labelsize=12)
plt.legend(loc='upper right',fontsize=8)
plt.title(filename.split('.')[0].replace('HB_','')+'/sw: '+str(sequence_window))
plt.savefig(os.path.join(os.path.join(os.getcwd(),'picture'),"Epoch_Loss_"+filename+"_SW_"+str(sequence_window)+"_LR_"+".pdf"),dpi=400)
#if cross_val_label == 0:
#plt.savefig(os.path.join(os.path.join(os.getcwd(),'picture'),"2Tab_A_Epoch_Loss_"+filename+"_SW_"+str(sequence_window)+"_LR_"+".pdf"),dpi=400)
#plt.savefig(os.path.join(os.path.join(os.getcwd(),'picture'),"Tab_A_Epoch_Loss_"+filename+"_SW_"+str(sequence_window)+"_LR_"+str(learning_rate)+".png"),dpi=400)
#else:
#plt.savefig(os.path.join(os.path.join(os.getcwd(),'picture'),"2Tab_B_Epoch_Loss_" + filename + "_SW_" + str(sequence_window) + ".pdf"), dpi=400)
#plt.savefig(os.path.join(os.path.join(os.getcwd(),'picture'),"Tab_B_Epoch_Loss_" + filename + "_SW_" + str(sequence_window)+"_LR_"+str(learning_rate) + ".png"), dpi=400)
def weight_plotting(filename,sequence_window,corss_val_label,learning_rate,weight_list):
if not os.path.isdir(os.path.join(os.getcwd(),'picture')):
os.makedirs(os.path.join(os.getcwd(),'picture'))
weight_list_new = np.transpose(weight_list)
#a,b,c = weight_list_new.shape
subtitle = ['a', 'b', 'c', 'd', 'e', 'f','g','h','i','j']
X = [i for i in range(len(weight_list_new[0][0]))]
plt.figure(figsize=(24,12),dpi=600)
count = 0
for tab in range(10):
index = tab
plt.subplot(1,4,count+1)
if tab == 9:
index = -1
elif tab == 8:
index = -2
plt.plot(X,weight_list_new[0][index])
plt.xlabel('Epoch\n('+subtitle[count]+') Scale '+str(tab+1), fontsize=12)
plt.ylabel('Weight', fontsize=12)
plt.grid()
count += 1
"""
plt.subplot(2,5,2)
plt.plot(X,weight_list_new[0][1])
plt.xlabel('Epoch\n('+subtitle[1]+')', fontsize=10)
plt.ylabel('Scale Weight', fontsize=10)
plt.grid()
plt.subplot(2,5,3)
plt.plot(X,weight_list_new[0][2])
plt.xlabel('Epoch\n('+subtitle[1]+')', fontsize=10)
plt.ylabel('Scale Weight', fontsize=10)
plt.grid()
"""
plt.tight_layout()
if corss_val_label == 0:
plt.savefig(os.path.join(os.path.join(os.getcwd(),'picture'),"ATab_A_Weight_list_" + filename + "_SW_" + str(sequence_window) +"_LR_"+str(learning_rate) + ".pdf"), dpi=600)
#plt.savefig(os.path.join(os.path.join(os.getcwd(),'picture'),"Tab_A_Weight_list_" + filename + "_SW_" + str(sequence_window) +"_LR_"+str(learning_rate) + ".png"), dpi=600)
else:
plt.savefig(os.path.join(os.path.join(os.getcwd(),'picture'),"ATab_B_Weight_list_"+filename+"_SW_"+str(sequence_window)+".pdf"),dpi=600)
#plt.savefig(os.path.join(os.path.join(os.getcwd(),'picture'),"Tab_B_Weight_list_"+filename+"_SW_"+str(sequence_window)+".png"),dpi=600)
def curve_plotting_withWindow(dataX,dataY,feature,name):
y = list(dataX[0][:,feature])
for i in range(1,len(dataX)):
y.append(dataX[i][:,feature][-1])
x = [i for i in range(len(y))]
z = [i for i in range(len(dataY)) if int(dataY[i][0]) == 1]
print(len(y))
plt.plot(x,np.array(y),'b')
plt.plot(z,np.array(y)[z],'r.')
plt.tight_layout()
plt.grid()
plt.show()
plt.savefig(name + '.pdf', dpi=400)
def curve_plotting(dataX,dataY,name,method):
np.random.seed(5)
target_names = ['Regular','Anomalous']
centers = [[1, 1], [-1, -1]]
X = dataX
y = dataY
plt.clf()
plt.cla()
pca = decomposition.PCA(n_components=2)
pca.fit(X)
X = pca.transform(X)
plt.figure()
colors = ['navy', 'turquoise', 'darkorange']
try:
y = loaddata.reverse_one_hot(y)
except:
pass
print(y[0])
for color, i, target_name in zip(colors, [0, 1], target_names):
plt.scatter(X[y == i, 0], X[y == i, 1], color=color, alpha=.8, lw=2,
label=target_name)
plt.legend(loc='lower right', fontsize = 16, shadow=False, scatterpoints=1)
plt.tick_params(labelsize = 15)
plt.grid()
#plt.title('PCA of the dataset')
plt.savefig(name + method +"_PCA.pdf", dpi=400)
plt.show()
def plotAUC(results,method_list,filename):
plt.figure()
#color_list = ['y', 'g', '#FF8C00', 'c', 'b', 'r', 'm']
color_list = ['y', 'g','#FF8C00','#FD8CD0','c', 'b', 'r', 'm']
for tab in range(len(method_list)):
fpr = results[method_list[tab]]['FPR']
tpr = results[method_list[tab]]['TPR']
auc = results[method_list[tab]]['AUC']
plt.plot(fpr, tpr, color_list[tab], label=method_list[tab] + ' ROC curve (area = %0.2f)' % auc)
plt.plot([0, 1], [0, 1], 'k--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate',fontsize=12)
plt.ylabel('True Positive Rate',fontsize=12)
plt.title('Receiver operating characteristic of '+filename.replace('HB_','').split('.')[0],fontsize=12)
plt.legend(loc="lower right", fontsize=10)
plt.tick_params(labelsize=12)
plt.grid()
#plt.savefig("_AUC.png", dpi=800)
plt.savefig(filename+"TP_FP_AUC.pdf", dpi=800)
#------------------------------------------Plotting STAT-----------------------------------------------------
def _plotting(filename, subtitle, method,method_dict):
temp = []
try:
with open(os.path.join(os.path.join(os.getcwd(),'stat'), filename))as fin:
for each in fin.readlines():
temp.append(int(each))
except:
with open(os.path.join(os.path.join(os.getcwd(),'stat'), filename).replace('Predict.txt','Predict'))as fin:
for each in fin.readlines():
temp.append(int(each))
temp = np.array(temp)
X = [i + 1 for i in range(len(temp))]
X = np.array(X)
plt.xlim(0, len(X))
plt.ylim(-0.5, 2.0)
#if 'True' in method:
#p1_,= plt.plot(X[temp==0], temp[temp==0], 'b.', markersize=2, label='Regular')
#l1 = plt.legend([p1_], ["Regular"])
#p2_,= plt.plot(X[temp==1], temp[temp==1], 'r.', markersize=2,label='Anomalous')
#plt.legend()
#plt.gca().add_artist(l1)
#l2 = plt.legend([p2_], ["Anomalousppppppp"])
#plt.gca().add_artist(l1)
if 1>0:
p1, = plt.plot(X[temp==1], temp[temp==1], 'b.', markersize=4, label='Regular')
p2, = plt.plot(X[temp==0], temp[temp==0], 'r.', markersize=4, label='Anomalous')
l1 = plt.legend([p1], ["Regular"], loc=2,fontsize=10)
plt.gca().add_artist(l1)
l2 = plt.legend([p2], ["Anomalous"], loc=0,fontsize=10)
plt.gca().add_artist(l2)
#plt.legend(loc=1, fontsize=12)
#plt.legend(bbox_to_anchor=(1, 1),
#bbox_transform=plt.gcf().transFigure)
#plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
try:
plt.xlabel('(' + subtitle + ')' + " " + method_dict[method]+' Predicted',fontsize=10)
except:
if 'True' in method:
plt.xlabel('(' + subtitle + ')' + " " + method,fontsize=10)
else:
plt.xlabel('(' + subtitle + ')' + " " + method+' Predicted',fontsize=10)
x = (len(X) / 2)
#plt.xticks([1, 400, 800, 1200, 1600, 2000, 2500])
plt.xticks([1, 100, 200, 300, 400, 500, 600,700,800])
plt.tick_params(labelsize=10)
# plt.grid(b=True, which='minor', color='k', linestyle='-', alpha=0.1)
# plt.minorticks_on()
#plt.grid()
plt.grid(b=True, which='minor')
plt.axvline(x, ymin=-1, ymax=2, linewidth=2, color='g') # plt.title('Testing Sequence')
# plt.axvline(x+30, ymin=-1, ymax=2, linewidth=2, color='g') #plt.title('Testing Sequence')
# plt.grid()
def plotStat(filename, Method_List,Method_Label):
subtitle = ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i']
plt.figure(figsize=(15, 4), dpi=400)
#plt.figure()
plt.subplot(2, 4, 1)
filename_ = "StatFalseAlarm_" + filename + "_True.txt"
_plotting(filename_, subtitle[0], "True Label",Method_Label)
for tab in range(len(Method_List)):
filename_ = "StatFalseAlarm_" + filename + "_" + Method_List[tab] + "_" + "_Predict.txt"
plt.subplot(2, 4, tab + 2)
_plotting(filename_, subtitle[tab + 1], Method_List[tab],Method_Label)
plt.tight_layout()
plt.savefig("StateFalseAlarm_" + filename + ".pdf", dpi=400)
plt.show()
#------------------------------------------Plotting Wavelet-----------------------------------------------------
def plotWavelet(filename_result,filename_result2):
filename_list_label = ["AS_Leak","Slammer","Nimda","Code_Red_I"]
#wave_type_db=[81.66,82.79,85.47,80.25,80.90,81.55,82.80,87.57,92.82,93.35,95.64]
#wave_type_haar=[81.66,82.79,85.47,80.25,80.90,81.55,82.80,87.57,92.82,93.35,95.64]
color_type = ['y.', 'gs','#FF8C00','#FD8CD0','c>', 'b<', 'r.', 'm*']
#wave_type_sym= []
with open("aaa.txt","a")as fout:
for eachk,eachv in filename_result.items():
fout.write(eachk)
fout.write(''.join(eachv))
for eachk,eachv in filename_result2.items():
fout.write(eachk)
fout.write(''.join(eachv))
count = 0
for eachk,eachv in filename_result.items():
X = [i+2 for i in range(len(eachv))]
eachv = map(lambda a:100*a,eachv)
print(eachv)
plt.plot(X,eachv,color_type[count],label=filename_list_label[eachk])
count += 1
plt.legend(loc="lower right",fontsize=12)
plt.ylabel("Accuracy",fontsize=12)
#if "AS" in Parameters["filename"]:
#plt.ylim(35,75)
#else:
#plt.ylim(50,100)
plt.ylim(0,100)
plt.tick_params(labelsize=12)
plt.xlabel("Scale Levels",fontsize=12)
plt.grid()
plt.savefig("Wave_Let_"+'_'+str(0)+'_'+".df",dpi=400)
plt.title("Wavelet Family: Daubechies/Filter Length: 2")
#plt.show()
def MC_Plotting(Data,row,col,x_label='x_label',y_label='y_label',suptitle='super_title',save_fig='save_fig'):
X = [i+1 for i in range(len(Data[0]))]
plt.figure(figsize=(row*col*4,col))
for tab in range(row*col):
plt.subplot(row,col,tab+1)
plt.plot(X,Data[tab],'s-')
plt.xlabel(x_label,fontsize=10)
plt.ylabel(y_label,fontsize=10)
plt.ylim(40,100)
plt.grid()
plt.tick_params(labelsize=10)
plt.tight_layout()
plt.suptitle(suptitle)
plt.savefig(save_fig,dpi=200)
plt.show()
#A1 = [51.5,54.2,55.1,55.4,55.8,57.3,49.6,52.2,63.4,63.5]#"AS_LEAK"
#A2 = [50.6,53.9,55.3,54.3,56.8,52.7,54.7,52.1,63.3,63.3]
#A3 = [50.4,54.5,55.7,54.3,56.1,51.0,54.6,51.9,63.3,63.3]
#A = []
#A.append(A1)
#A.append(A2)
#A.append(A3)
#MC_Plotting(A,1,3)
def plot3D(X=[],Y=[],Z=[]):
X = [1, 2, 3, 4, 5, 6]
Y = [10, 20, 30, 40]
X = np.array(X)
Y = np.array(Y)
Z1 = [69.28982, 71.03682, 70.99231, 70.9999, 75.01086, 76.0222,
68.18597, 70.9997, 71.0195, 73.04, 75.11, 76.15133,
70.1123,73.04807, 76.04694, 77.0245, 78.01838, 79.01737,
69.18136, 70.05632, 69.01083, 69.99859, 70.99589, 70.99618]
Z1 = np.array(Z1)
max_ = np.max(Z1)
min_ = np.min(Z1)
XX, YY = np.meshgrid(X, Y)
Z1 = np.reshape(Z1, (XX.shape))
fig = plt.figure()
ax = fig.gca(projection='3d')
surf = ax.plot_surface(XX, YY, Z1, rstride=1, cstride=1, alpha=1, cmap=cm.jet, linewidth=0.5, antialiased=False)
fig.colorbar(surf, shrink=0.6, aspect=6)
surf.set_clim(vmin=min_, vmax=max_)
plt.xlabel('scale level')
plt.ylabel('window size')
plt.tight_layout()
plt.savefig('wqf.pdf', dpi=400)
plt.show()
#plot3D()
def plotConfusionMatrix(confmat):
import seaborn
seaborn.set_context('poster')
#seaborn.set_style("white")
seaborn.set_style("ticks")
plt.style.use(['seaborn-paper'])
font = {'family': 'serif',
#'weight': 'bold',
'size': 12}
matplotlib.rc("font", **font)
fig, ax = plt.subplots()
labels = ['','Regular','AS Leak',' Code Red I','Nimda','Slammer']
#labels = ['a','b','c','d','e']
#ticks=np.linspace(0, 5,num=5)
#res = plt.imshow(confmat, interpolation='none')
#res = ax.imshow(np.array(confmat), cmap=plt.cm.jet,interpolation='nearest')
res = ax.imshow(np.array(confmat), interpolation='nearest')
#plt.xlabel('kkk')
width, height = confmat.shape
#plt.xticks(labels)
#plt.tick_params(labelbottom=labels,labelleft=labels)
for x in xrange(width):
for y in xrange(height):
ax.annotate(str(confmat[x][y]), xy=(y, x),
horizontalalignment='center',
verticalalignment='center')
ax.set_xticklabels(labels)
ax.set_yticklabels(labels)
plt.tick_params(labelsize=10)
plt.colorbar(res,shrink=1, pad=.01, aspect=10)
plt.savefig("Fig_10.pdf",dpi=400)
#plt.show()
print(confmat.shape)
| 40.943299 | 180 | 0.608586 |
125e451ea3f29a28fbe077f8b237dc7d79e4f4e0 | 6,466 | py | Python | benchmarks/f3_wrong_hints/scaling_nonlinear_software/6-19_19.py | EnricoMagnago/F3 | c863215c318d7d5f258eb9be38c6962cf6863b52 | [
"MIT"
] | 3 | 2021-04-23T23:29:26.000Z | 2022-03-23T10:00:30.000Z | benchmarks/f3_wrong_hints/scaling_nonlinear_software/6-19_19.py | EnricoMagnago/F3 | c863215c318d7d5f258eb9be38c6962cf6863b52 | [
"MIT"
] | null | null | null | benchmarks/f3_wrong_hints/scaling_nonlinear_software/6-19_19.py | EnricoMagnago/F3 | c863215c318d7d5f258eb9be38c6962cf6863b52 | [
"MIT"
] | 1 | 2021-11-17T22:02:56.000Z | 2021-11-17T22:02:56.000Z | from typing import FrozenSet, Tuple
import pysmt.typing as types
from pysmt.environment import Environment as PysmtEnv
from pysmt.fnode import FNode
from utils import symb_to_next
from hint import Hint, Location
def transition_system(env: PysmtEnv) -> Tuple[FrozenSet[FNode], FNode, FNode,
FNode]:
assert isinstance(env, PysmtEnv)
mgr = env.formula_manager
pc = mgr.Symbol("pc", types.INT)
x = mgr.Symbol("x", types.INT)
y = mgr.Symbol("y", types.INT)
z = mgr.Symbol("z", types.INT)
x_pc = symb_to_next(mgr, pc)
x_x = symb_to_next(mgr, x)
x_y = symb_to_next(mgr, y)
x_z = symb_to_next(mgr, z)
symbols = frozenset([pc, x, y, z])
n_locs = 5
int_bound = n_locs
pcs = []
x_pcs = []
ints = [mgr.Int(i) for i in range(int_bound)]
for l in range(n_locs):
n = ints[l]
pcs.append(mgr.Equals(pc, n))
x_pcs.append(mgr.Equals(x_pc, n))
m_1 = mgr.Int(-1)
pcend = mgr.Equals(pc, m_1)
x_pcend = mgr.Equals(x_pc, m_1)
# initial location.
init = pcs[0]
# control flow graph.
cfg = mgr.And(
# pc = -1 : -1,
mgr.Implies(pcend, x_pcend),
# pc = 0 & !(y >= 1) : -1,
mgr.Implies(mgr.And(pcs[0], mgr.Not(mgr.GE(y, ints[1]))), x_pcend),
# pc = 0 & y >= 1 : 1,
mgr.Implies(mgr.And(pcs[0], mgr.GE(y, ints[1])), x_pcs[1]),
# pc = 1 & !(z >= 1) : -1,
mgr.Implies(mgr.And(pcs[1], mgr.Not(mgr.GE(z, ints[1]))), x_pcend),
# pc = 1 & z >= 1 : 2,
mgr.Implies(mgr.And(pcs[1], mgr.GE(z, ints[1])), x_pcs[2]),
# pc = 2 & !(x >= 0) : -1,
mgr.Implies(mgr.And(pcs[2], mgr.Not(mgr.GE(x, ints[0]))), x_pcend),
# pc = 2 & x >= 0 : 3,
mgr.Implies(mgr.And(pcs[2], mgr.GE(x, ints[0])), x_pcs[3]),
# pc = 3 : 4,
mgr.Implies(pcs[3], x_pcs[4]),
# pc = 4 : 2,
mgr.Implies(pcs[4], x_pcs[2]))
# transition labels.
labels = mgr.And(
# (pc = -1 & pc' = -1) -> (x' = x & y' = y & z' = z),
mgr.Implies(
mgr.And(pcend, x_pcend),
mgr.And(mgr.Equals(x_x, x), mgr.Equals(x_y, y),
mgr.Equals(x_z, z))),
# (pc = 0 & pc' = -1) -> (x' = x & y' = y & z' = z),
mgr.Implies(
mgr.And(pcs[0], x_pcend),
mgr.And(mgr.Equals(x_x, x), mgr.Equals(x_y, y),
mgr.Equals(x_z, z))),
# (pc = 0 & pc' = 1) -> (x' = x & y' = y & z' = z),
mgr.Implies(
mgr.And(pcs[0], x_pcs[1]),
mgr.And(mgr.Equals(x_x, x), mgr.Equals(x_y, y),
mgr.Equals(x_z, z))),
# (pc = 1 & pc' = -1) -> (x' = x & y' = y & z' = z),
mgr.Implies(
mgr.And(pcs[1], x_pcend),
mgr.And(mgr.Equals(x_x, x), mgr.Equals(x_y, y),
mgr.Equals(x_z, z))),
# (pc = 1 & pc' = 2) -> (x' = x & y' = y & z' = z),
mgr.Implies(
mgr.And(pcs[1], x_pcs[2]),
mgr.And(mgr.Equals(x_x, x), mgr.Equals(x_y, y),
mgr.Equals(x_z, z))),
# (pc = 2 & pc' = -1) -> (x' = x & y' = y & z' = z),
mgr.Implies(
mgr.And(pcs[2], x_pcend),
mgr.And(mgr.Equals(x_x, x), mgr.Equals(x_y, y),
mgr.Equals(x_z, z))),
# (pc = 2 & pc' = 3) -> (x' = x & y' = y & z' = z),
mgr.Implies(
mgr.And(pcs[2], x_pcs[3]),
mgr.And(mgr.Equals(x_x, x), mgr.Equals(x_y, y),
mgr.Equals(x_z, z))),
# (pc = 3 & pc' = 4) -> (x' = y*z - 1 & y' = y & z' = z),
mgr.Implies(
mgr.And(pcs[3], x_pcs[4]),
mgr.And(mgr.Equals(x_x, mgr.Minus(mgr.Times(y, z), ints[1])),
mgr.Equals(x_y, y), mgr.Equals(x_z, z))),
# (pc = 4 & pc' = 2) -> (x' = x & y' = y+1 & z' = z),
mgr.Implies(
mgr.And(pcs[4], x_pcs[2]),
mgr.And(mgr.Equals(x_x, x), mgr.Equals(x_y, mgr.Plus(y, ints[1])),
mgr.Equals(x_z, z))))
# transition relation.
trans = mgr.And(cfg, labels)
# fairness.
fairness = mgr.Not(pcend)
return symbols, init, trans, fairness
def hints(env: PysmtEnv) -> FrozenSet[Hint]:
assert isinstance(env, PysmtEnv)
mgr = env.formula_manager
pc = mgr.Symbol("pc", types.INT)
x = mgr.Symbol("x", types.INT)
y = mgr.Symbol("y", types.INT)
z = mgr.Symbol("z", types.INT)
symbs = frozenset([pc, x, y, z])
x_pc = symb_to_next(mgr, pc)
x_x = symb_to_next(mgr, x)
x_y = symb_to_next(mgr, y)
x_z = symb_to_next(mgr, z)
res = []
i_0 = mgr.Int(0)
i_1 = mgr.Int(1)
i_2 = mgr.Int(2)
i_3 = mgr.Int(3)
stutter = mgr.Equals(x_y, y)
loc = Location(env, mgr.TRUE(), mgr.LE(x, i_0), stutterT=stutter)
loc.set_progress(0, mgr.Equals(x_y, mgr.Minus(y, i_1)))
h_y = Hint("h_y0", env, frozenset([y]), symbs)
h_y.set_locs([loc])
res.append(h_y)
loc = Location(env, mgr.LE(z, i_0))
loc.set_progress(0, mgr.Equals(x_z, z))
h_z = Hint("h_z0", env, frozenset([z]), symbs)
h_z.set_locs([loc])
res.append(h_z)
loc0 = Location(env, mgr.Equals(pc, i_1))
loc0.set_progress(1, mgr.Equals(x_pc, i_3))
loc1 = Location(env, mgr.Equals(pc, i_3))
loc1.set_progress(0, mgr.Equals(x_pc, i_1))
h_pc = Hint("h_pc2", env, frozenset([pc]), symbs)
h_pc.set_locs([loc0, loc1])
res.append(h_pc)
loc0 = Location(env, mgr.Equals(pc, i_2))
loc0.set_progress(1, mgr.GT(x_pc, i_2))
loc1 = Location(env, mgr.GE(pc, i_3))
loc1.set_progress(0, mgr.Equals(x_pc, i_2))
h_pc = Hint("h_pc3", env, frozenset([pc]), symbs)
h_pc.set_locs([loc0, loc1])
res.append(h_pc)
loc0 = Location(env, mgr.GE(z, i_0))
loc0.set_progress(1, mgr.Equals(x_z, z))
loc1 = Location(env, mgr.GE(z, i_0))
loc1.set_progress(0, mgr.Equals(x_z, mgr.Plus(z, i_3)))
h_z = Hint("h_z4", env, frozenset([z]), symbs)
h_z.set_locs([loc0, loc1])
res.append(h_z)
loc0 = Location(env, mgr.Equals(pc, i_2))
loc0.set_progress(1, mgr.GT(x_pc, i_2))
loc1 = Location(env, mgr.GE(pc, i_3))
loc1.set_progress(2, mgr.GE(x_pc, i_3))
loc2 = Location(env, mgr.GE(pc, i_3))
loc2.set_progress(0, mgr.Equals(x_pc, i_2))
h_pc = Hint("h_pc4", env, frozenset([pc]), symbs)
h_pc.set_locs([loc0, loc1, loc2])
res.append(h_pc)
return frozenset(res)
| 33.502591 | 78 | 0.51562 |
da43a23c3b16dfd35a11b8a841eda16786cd693b | 91 | py | Python | bitmovin_api_sdk/encoding/inputs/local/customdata/__init__.py | jaythecaesarean/bitmovin-api-sdk-python | 48166511fcb9082041c552ace55a9b66cc59b794 | [
"MIT"
] | 11 | 2019-07-03T10:41:16.000Z | 2022-02-25T21:48:06.000Z | bitmovin_api_sdk/encoding/inputs/local/customdata/__init__.py | jaythecaesarean/bitmovin-api-sdk-python | 48166511fcb9082041c552ace55a9b66cc59b794 | [
"MIT"
] | 8 | 2019-11-23T00:01:25.000Z | 2021-04-29T12:30:31.000Z | bitmovin_api_sdk/encoding/inputs/local/customdata/__init__.py | jaythecaesarean/bitmovin-api-sdk-python | 48166511fcb9082041c552ace55a9b66cc59b794 | [
"MIT"
] | 13 | 2020-01-02T14:58:18.000Z | 2022-03-26T12:10:30.000Z | from bitmovin_api_sdk.encoding.inputs.local.customdata.customdata_api import CustomdataApi
| 45.5 | 90 | 0.901099 |
7274648ac1f330e88d95a95b3df3b27f080eeb90 | 3,342 | py | Python | webapp/upload.py | CozyDoomer/deep-learning-webapp | eb0f432765459a1712080f5b25e8e01594336f4f | [
"BSD-3-Clause"
] | null | null | null | webapp/upload.py | CozyDoomer/deep-learning-webapp | eb0f432765459a1712080f5b25e8e01594336f4f | [
"BSD-3-Clause"
] | null | null | null | webapp/upload.py | CozyDoomer/deep-learning-webapp | eb0f432765459a1712080f5b25e8e01594336f4f | [
"BSD-3-Clause"
] | null | null | null | #!/venv/bin python
import os
from flask import Flask, flash, request, redirect, url_for, Blueprint, current_app, render_template, send_from_directory
from werkzeug.utils import secure_filename
from PIL import Image, ExifTags
import piexif
upload = Blueprint('upload', __name__)
ALLOWED_EXTENSIONS = set(['png', 'jpg', 'jpeg', 'gif'])
app = Flask(__name__)
def allowed_file(filename):
return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
def preprocess_image(filepath, min_size=299):
img = Image.open(filepath)
# rotate if exif encoded
exif_bytes = None
if "exif" in img.info:
exif_dict = piexif.load(img.info["exif"])
if piexif.ImageIFD.Orientation in exif_dict["0th"]:
orientation = exif_dict["0th"].pop(piexif.ImageIFD.Orientation)
exif_bytes = piexif.dump(exif_dict)
if orientation == 2:
img = img.transpose(Image.FLIP_LEFT_RIGHT)
elif orientation == 3:
img = img.rotate(180)
elif orientation == 4:
img = img.rotate(180).transpose(Image.FLIP_LEFT_RIGHT)
elif orientation == 5:
img = img.rotate(-90,
expand=True).transpose(Image.FLIP_LEFT_RIGHT)
elif orientation == 6:
img = img.rotate(-90, expand=True)
elif orientation == 7:
img = img.rotate(90, expand=True).transpose(
Image.FLIP_LEFT_RIGHT)
elif orientation == 8:
img = img.rotate(90, expand=True)
# resize image to min_size (keep aspect ratio)
ratio = max(min_size/img.width, min_size/img.height)
img.thumbnail((img.width * ratio, img.height * ratio), Image.ANTIALIAS)
print(f'resized image: {img.size}')
if exif_bytes:
img.save(filepath, exif=exif_bytes)
img.save(filepath)
@upload.route('/upload/<reason>', methods=['POST', 'GET'])
def upload_file(reason):
if request.method == 'POST':
# check if the post request has the file part
if 'file' not in request.files:
return redirect(request.url)
file = request.files['file']
# if user does not select file, browser submit a empty part without filename
if file.filename == '':
return redirect(request.url)
# check if file extension is in ALLOWED_EXTENSIONS
if file and allowed_file(file.filename):
filename = secure_filename(file.filename)
filepath = os.path.join(
current_app.config['UPLOAD_FOLDER'], filename)
file.save(filepath)
size = 299
if reason == 'object-detection':
size = 500
preprocess_image(filepath, min_size=size)
return render_template(f'{reason}.html', filename=filename, mail=current_app.config['MAIL_USERNAME'])
return render_template(f'{reason}.html', error='error', mail=current_app.config['MAIL_USERNAME'])
@upload.route('/upload/<reason>/<filename>', methods=['GET'])
def send_file(reason, filename):
if request.method == 'GET':
return send_from_directory(current_app.config['UPLOAD_FOLDER'], filename)
return render_template(f'{reason}.html', error='error', mail=current_app.config['MAIL_USERNAME'])
| 36.326087 | 120 | 0.628366 |
1c3b1fd2feb6059341825a17cd39398395bdea6d | 864 | py | Python | python/509.fibonacci-number.py | fengbaoheng/leetcode | 2b6ec9adea383503acc23622ca5623161f7ca520 | [
"MIT"
] | 1 | 2019-04-11T12:34:55.000Z | 2019-04-11T12:34:55.000Z | python/509.fibonacci-number.py | fengbaoheng/leetcode | 2b6ec9adea383503acc23622ca5623161f7ca520 | [
"MIT"
] | null | null | null | python/509.fibonacci-number.py | fengbaoheng/leetcode | 2b6ec9adea383503acc23622ca5623161f7ca520 | [
"MIT"
] | null | null | null | #
# @lc app=leetcode.cn id=509 lang=python3
#
# [509] Fibonacci Number
#
# https://leetcode-cn.com/problems/fibonacci-number/description/
#
# algorithms
# Easy (65.10%)
# Total Accepted: 5.9K
# Total Submissions: 9K
# Testcase Example: '2'
#
# 斐波那契数，通常用 F(n) 表示，形成的序列称为斐波那契数列。该数列由 0 和 1 开始，后面的每一项数字都是前面两项数字的和。也就是：
#
# F(0) = 0, F(1) = 1
# F(N) = F(N - 1) + F(N - 2), 其中 N > 1.
#
#
# 给定 N，计算 F(N)。
#
#
#
# 示例 1：
#
# 输入：2
# 输出：1
# 解释：F(2) = F(1) + F(0) = 1 + 0 = 1.
#
#
# 示例 2：
#
# 输入：3
# 输出：2
# 解释：F(3) = F(2) + F(1) = 1 + 1 = 2.
#
#
# 示例 3：
#
# 输入：4
# 输出：3
# 解释：F(4) = F(3) + F(2) = 2 + 1 = 3.
#
#
#
#
# 提示：
#
#
# 0 ≤ N ≤ 30
#
#
#
class Solution:
# 正向计算, 逆向递归会超时
def fib(self, N: int) -> int:
f = [0,1]
for i in range(2, N+1):
f.append(f[i-1] + f[i-2])
return f[N]
| 13.292308 | 71 | 0.456019 |
0fd1cdf3068c926b67443c63ba5c2d072ed8e91f | 224 | py | Python | Curso/Challenges/URI/1958ScientificNotation.py | DavidBitner/Aprendizado-Python | e1dcf18f9473c697fc2302f34a2d3e025ca6c969 | [
"MIT"
] | null | null | null | Curso/Challenges/URI/1958ScientificNotation.py | DavidBitner/Aprendizado-Python | e1dcf18f9473c697fc2302f34a2d3e025ca6c969 | [
"MIT"
] | null | null | null | Curso/Challenges/URI/1958ScientificNotation.py | DavidBitner/Aprendizado-Python | e1dcf18f9473c697fc2302f34a2d3e025ca6c969 | [
"MIT"
] | null | null | null | n = str(input())
negativo = False
if "-" in n:
negativo = True
entrada = float(n)
if entrada == 0:
if not negativo:
print("+", end="")
elif entrada > 0:
print("+", end="")
print(f"{entrada:.4e}".upper())
| 18.666667 | 31 | 0.549107 |
17b260187bb9ac1e93f51ec59045d06ead911848 | 5,911 | py | Python | auxiliar_constantes.py | lucasHashi/coleta-dados-acoes-bdrs-b3 | a2d2c3343378ee70a134bd0bbec11685d896971d | [
"MIT"
] | null | null | null | auxiliar_constantes.py | lucasHashi/coleta-dados-acoes-bdrs-b3 | a2d2c3343378ee70a134bd0bbec11685d896971d | [
"MIT"
] | null | null | null | auxiliar_constantes.py | lucasHashi/coleta-dados-acoes-bdrs-b3 | a2d2c3343378ee70a134bd0bbec11685d896971d | [
"MIT"
] | null | null | null |
# ---------------- ETFS ----------------
URL_LINKS_ETFS = 'https://sistemaswebb3-listados.b3.com.br/fundsPage/3'
# ---------------- FIIS ----------------
URL_LINKS_FIIS = 'https://fiis.com.br/lista-de-fundos-imobiliarios/'
# ---------------- ACOES ----------------
URL_BASE_DADOS_ACAO = 'https://sistemaswebb3-listados.b3.com.br/listedCompaniesPage/main/{}/{}/overview?language=pt-br' # .format(codigo_acao, ticker)
URLS_IPOS_POR_ANO = {
2022: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDIyfQ=='
],
2021: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjEyMCwieWVhciI6MjAyMX0='
],
2020: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjEyMCwieWVhciI6MjAyMH0='
],
2019: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDE5fQ=='
],
2018: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDE4fQ=='
],
2017: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDE3fQ=='
],
2016: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDE2fQ=='
],
2015: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDE1fQ=='
],
2014: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDE0fQ=='
],
2013: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDEzfQ=='
],
2012: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDEyfQ=='
],
2011: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDExfQ=='
],
2010: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDEwfQ=='
],
2009: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDA5fQ=='
],
2008: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDA4fQ=='
],
2007: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDA3fQ=='
],
2006: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDA2fQ=='
],
2005: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDA1fQ=='
],
2004: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDA0fQ=='
],
2003: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDAzfQ=='
],
2002: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDAyfQ=='
],
2001: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDAxfQ=='
],
2000: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoyMDAwfQ=='
],
1999: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoxOTk5fQ=='
],
1998: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjIwLCJ5ZWFyIjoxOTk4fQ=='
],
1997: [
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MSwicGFnZVNpemUiOjEyMCwieWVhciI6MTk5N30=',
'https://sistemaswebb3-listados.b3.com.br/listedCompaniesProxy/CompanyCall/GetYearListing/eyJsYW5ndWFnZSI6InB0LWJyIiwicGFnZU51bWJlciI6MiwicGFnZVNpemUiOjEyMCwieWVhciI6MTk5N30='
]
} | 60.938144 | 184 | 0.792759 |
5a5cd2e4cc4fc8bf1d07367233754ca5833eed65 | 4,027 | py | Python | sdk/python/pulumi_aws/lambda_/get_invocation.py | mdop-wh/pulumi-aws | 05bb32e9d694dde1c3b76d440fd2cd0344d23376 | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | sdk/python/pulumi_aws/lambda_/get_invocation.py | mdop-wh/pulumi-aws | 05bb32e9d694dde1c3b76d440fd2cd0344d23376 | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | sdk/python/pulumi_aws/lambda_/get_invocation.py | mdop-wh/pulumi-aws | 05bb32e9d694dde1c3b76d440fd2cd0344d23376 | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | # coding=utf-8
# *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Dict, List, Mapping, Optional, Tuple, Union
from .. import _utilities, _tables
__all__ = [
'GetInvocationResult',
'AwaitableGetInvocationResult',
'get_invocation',
]
@pulumi.output_type
class GetInvocationResult:
"""
A collection of values returned by getInvocation.
"""
def __init__(__self__, function_name=None, id=None, input=None, qualifier=None, result=None):
if function_name and not isinstance(function_name, str):
raise TypeError("Expected argument 'function_name' to be a str")
pulumi.set(__self__, "function_name", function_name)
if id and not isinstance(id, str):
raise TypeError("Expected argument 'id' to be a str")
pulumi.set(__self__, "id", id)
if input and not isinstance(input, str):
raise TypeError("Expected argument 'input' to be a str")
pulumi.set(__self__, "input", input)
if qualifier and not isinstance(qualifier, str):
raise TypeError("Expected argument 'qualifier' to be a str")
pulumi.set(__self__, "qualifier", qualifier)
if result and not isinstance(result, str):
raise TypeError("Expected argument 'result' to be a str")
pulumi.set(__self__, "result", result)
@property
@pulumi.getter(name="functionName")
def function_name(self) -> str:
return pulumi.get(self, "function_name")
@property
@pulumi.getter
def id(self) -> str:
"""
The provider-assigned unique ID for this managed resource.
"""
return pulumi.get(self, "id")
@property
@pulumi.getter
def input(self) -> str:
return pulumi.get(self, "input")
@property
@pulumi.getter
def qualifier(self) -> Optional[str]:
return pulumi.get(self, "qualifier")
@property
@pulumi.getter
def result(self) -> str:
"""
String result of the lambda function invocation.
"""
return pulumi.get(self, "result")
class AwaitableGetInvocationResult(GetInvocationResult):
# pylint: disable=using-constant-test
def __await__(self):
if False:
yield self
return GetInvocationResult(
function_name=self.function_name,
id=self.id,
input=self.input,
qualifier=self.qualifier,
result=self.result)
def get_invocation(function_name: Optional[str] = None,
input: Optional[str] = None,
qualifier: Optional[str] = None,
opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetInvocationResult:
"""
Use this data source to invoke custom lambda functions as data source.
The lambda function is invoked with [RequestResponse](https://docs.aws.amazon.com/lambda/latest/dg/API_Invoke.html#API_Invoke_RequestSyntax)
invocation type.
:param str function_name: The name of the lambda function.
:param str input: A string in JSON format that is passed as payload to the lambda function.
:param str qualifier: The qualifier (a.k.a version) of the lambda function. Defaults
to `$LATEST`.
"""
__args__ = dict()
__args__['functionName'] = function_name
__args__['input'] = input
__args__['qualifier'] = qualifier
if opts is None:
opts = pulumi.InvokeOptions()
if opts.version is None:
opts.version = _utilities.get_version()
__ret__ = pulumi.runtime.invoke('aws:lambda/getInvocation:getInvocation', __args__, opts=opts, typ=GetInvocationResult).value
return AwaitableGetInvocationResult(
function_name=__ret__.function_name,
id=__ret__.id,
input=__ret__.input,
qualifier=__ret__.qualifier,
result=__ret__.result)
| 35.017391 | 144 | 0.656072 |
6aab762e5367f0a9d47a441d4a731e5d7266ae92 | 92 | py | Python | pycl/Code/readfilel.py | dcavar/dcavar.github.io | bf96820f41563bab73ba35a98142da4ab5ad50a1 | [
"Apache-2.0"
] | 4 | 2018-01-11T22:14:11.000Z | 2019-06-13T09:56:18.000Z | pycl/Code/readfilel.py | dcavar/dcavar.github.io | bf96820f41563bab73ba35a98142da4ab5ad50a1 | [
"Apache-2.0"
] | null | null | null | pycl/Code/readfilel.py | dcavar/dcavar.github.io | bf96820f41563bab73ba35a98142da4ab5ad50a1 | [
"Apache-2.0"
] | 1 | 2020-01-25T02:16:38.000Z | 2020-01-25T02:16:38.000Z | file = open("readfilel.py")
text = file.readlines()
file.close()
for i in text:
print i,
| 15.333333 | 27 | 0.663043 |
6f04feb0bd64dca0c4623adcb00757414b5c66ff | 1,852 | py | Python | homeauto/views.py | 7ooL/web_home_auto | 66d1a96359154a2a8015fb8ebfabfedcf38f69a9 | [
"MIT"
] | null | null | null | homeauto/views.py | 7ooL/web_home_auto | 66d1a96359154a2a8015fb8ebfabfedcf38f69a9 | [
"MIT"
] | 8 | 2020-12-30T17:41:41.000Z | 2021-01-24T19:16:54.000Z | homeauto/views.py | 7ooL/HomeAuto | 66d1a96359154a2a8015fb8ebfabfedcf38f69a9 | [
"MIT"
] | null | null | null |
from django.shortcuts import render
#import homeauto.models as house
#import hue.models as hue
#import homeauto.models.wemo as device
from django.http import JsonResponse
import simplejson as json
def dashboard_index(request):
# persons = house.Person.objects.all()
# services = house.Service.objects.all()
# lights = hue.Light.objects.all()
# context = {'persons':persons,
# 'services':services,
# 'lights':lights}
context = {}
return render(request, 'dashboard_index.html', context)
"""
def people_index(request):
persons = house.Person.objects.all()
context = {'persons': persons}
return render(request, 'people_index.html', context)
def person_detail(request, pk):
person = house.Person.objects.get(pk=pk)
context = {'person': person}
return render(request, 'person_detail.html', context)
def services_index(request):
services = house.Service.objects.all()
context = {'services': services}
return render(request, 'services_index.html', context)
def service_detail(request, pk):
service = house.Service.objects.get(pk=pk)
context = {'service': service}
return render(request, 'service_detail.html', context)
#def lights_index(request):
# lights = hue.Light.objects.all()
# wemos = device.Wemo.objects.all()
# context = {'lights':lights,
# 'wemos':wemos}
# return render(request, 'lights_index.html', context)
def light_detail(request):
return render(request, 'light_detail.html', context)
def groups_index(request):
return render(request, 'groups_index.html', context)
def group_detail(request):
return render(request, 'group_detail.html', context)
def scenes_index(request):
return render(request, 'scenes_index.html', context)
def scene_detail(request):
return render(request, 'scene_detail.html', context)
"""
| 26.084507 | 59 | 0.707343 |
9dfaeecc26a59d83c868cee9e76cbb7f12f867da | 1,527 | py | Python | StupidBenchmark/PyTorch/upsample.py | tobyclh/StupidBenchmark | 0b4f821bdb54522b32de3e340f4f73597043e4f3 | [
"Apache-2.0"
] | null | null | null | StupidBenchmark/PyTorch/upsample.py | tobyclh/StupidBenchmark | 0b4f821bdb54522b32de3e340f4f73597043e4f3 | [
"Apache-2.0"
] | null | null | null | StupidBenchmark/PyTorch/upsample.py | tobyclh/StupidBenchmark | 0b4f821bdb54522b32de3e340f4f73597043e4f3 | [
"Apache-2.0"
] | null | null | null | import torch
from skimage import io, transform
from time import time
from torch import nn
from time import time
from torchvision.transforms.functional import resize
from PIL import Image
from torch.nn.functional import upsample
img = io.imread('data/britney.png')
def timereps(reps, func):
start = time()
[func() for _ in range(0, reps)]
end = time()
return (end - start) / reps
average_duration = timereps(10, lambda : transform.rescale(img, [2,2], mode='constant'))
print(f'transform.rescale : {average_duration}')
tensor_img = torch.Tensor(img)
tensor_img = tensor_img.cuda().unsqueeze(0)
tensor_img = tensor_img.expand(1, -1, -1, -1).permute(0, 3, 1, 2)
up = nn.Upsample(scale_factor=2, mode='bilinear', align_corners=False)
average_duration = timereps(1000, lambda : up(tensor_img))
print(f'nn.Upsample (GPU): {average_duration}')
average_duration = timereps(1000, lambda : upsample(tensor_img, scale_factor=2, mode='bilinear', align_corners=False))
print(f'nn.functional.upsample (GPU) : {average_duration}')
tensor_img = tensor_img.cpu()
average_duration = timereps(100, lambda : up(tensor_img))
print(f'nn.Upsample (CPU): {average_duration}')
average_duration = timereps(100, lambda : upsample(tensor_img, scale_factor=2, mode='bilinear', align_corners=False))
print(f'nn.functional.upsample (CPU) : {average_duration}')
img = Image.open('data/britney.png')
average_duration = timereps(100, lambda : resize(img, [img.size[0]*2, img.size[1]*2]))
print(f'torchvision resize : {average_duration}')
| 37.243902 | 118 | 0.743287 |
027e03b517621cceeeeab1a769afd4c8ca57a3db | 3,408 | py | Python | bin/BuildSystem/PerlBuildSystem.py | Inokinoki/craft | dd09fb3ba0714ed19d9ab15bdd402fecf9c64405 | [
"BSD-2-Clause"
] | null | null | null | bin/BuildSystem/PerlBuildSystem.py | Inokinoki/craft | dd09fb3ba0714ed19d9ab15bdd402fecf9c64405 | [
"BSD-2-Clause"
] | null | null | null | bin/BuildSystem/PerlBuildSystem.py | Inokinoki/craft | dd09fb3ba0714ed19d9ab15bdd402fecf9c64405 | [
"BSD-2-Clause"
] | null | null | null | # -*- coding: utf-8 -*-
# Copyright Hannah von Reth <vonreth@kde.org>
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# 1. Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# 2. Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE REGENTS 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 REGENTS 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.
from BuildSystem.MakeFileBuildSystem import *
# based on https://wiki.archlinux.org/index.php/Perl_package_guidelines
class PerlBuildSystem(MakeFileBuildSystem):
def __init__(self):
MakeFileBuildSystem.__init__(self)
self.subinfo.options.make.supportsMultijob = False
self.subinfo.options.useShadowBuild = False
def configure(self):
self.enterBuildDir()
env = {"PERL5LIB": None,
"PERL_MM_OPT": None,
"PERL_LOCAL_LIB_ROOT": None,
"PERL_MM_USE_DEFAULT": "1",
"PERL_AUTOINSTALL": "--skipdeps"}
with utils.ScopedEnv(env):
return utils.system(" ".join(["perl", "Makefile.PL", self.subinfo.options.configure.args]))
def make(self):
self.enterBuildDir()
env = {"PERL5LIB" : None,
"PERL_MM_OPT" : None,
"PERL_LOCAL_LIB_ROOT" : None,
"PERL_MM_USE_DEFAULT" : "1",
"PERL_AUTOINSTALL" : "--skipdeps"}
if CraftCore.compiler.isMSVC():
root = OsUtils.toUnixPath(CraftCore.standardDirs.craftRoot())
env.update({"INCLUDE": f"{os.environ['INCLUDE']};{root}/include",
"LIB": f"{os.environ['LIB']};{root}/lib"})
with utils.ScopedEnv(env):
return utils.system([self.makeProgram])
def install(self):
env = {"PERL5LIB": None,
"PERL_MM_OPT": None,
"PERL_LOCAL_LIB_ROOT": None}
with utils.ScopedEnv(env):
if 1 and CraftCore.compiler.isWindows:
#ugly hack to make destdir work, it probably breaks some scripts
makeFile = os.path.join(self.buildDir(), "Makefile")
with open(makeFile, "rt") as make:
txt = make.read()
with open(makeFile, "wt") as make:
txt = txt.replace(CraftCore.standardDirs.craftRoot(), CraftCore.standardDirs.craftRoot()[2:])
make.write(txt)
return super().install() and self._fixInstallPrefix() | 48.685714 | 113 | 0.656984 |
0b8904b5c7dce13fd933435d6f8cdb2b6dc63a18 | 1,182 | py | Python | src/stereo_cam/setup.py | frank20a/collaborative-sats | 9d26d3c8f66cf43bbd514f02434851439e746797 | [
"MIT"
] | null | null | null | src/stereo_cam/setup.py | frank20a/collaborative-sats | 9d26d3c8f66cf43bbd514f02434851439e746797 | [
"MIT"
] | 6 | 2022-03-22T18:54:38.000Z | 2022-03-31T16:42:37.000Z | src/stereo_cam/setup.py | frank20a/collaborative-sats | 9d26d3c8f66cf43bbd514f02434851439e746797 | [
"MIT"
] | null | null | null | from setuptools import setup
import os
from glob import glob
package_name = 'stereo_cam'
setup(
name=package_name,
version='1.0.0',
packages=[package_name],
data_files=[
('share/ament_index/resource_index/packages',
['resource/' + package_name]),
('share/' + package_name, ['package.xml']),
(os.path.join('share', package_name, 'launch'),
glob('launch/*.launch.py')),
(os.path.join('share', package_name, 'rviz_config'),
glob('rviz_config/*.rviz')),
],
install_requires=['setuptools'],
zip_safe=True,
maintainer='Frank Fourlas',
maintainer_email='frank.fourlas@gmail.com',
description='Fetch stereoscopic data from sensors and process them',
license='Apache 2.0',
tests_require=['pytest'],
entry_points={
'console_scripts': [
'stereo_viewer = ' + package_name + '.stereo_viewer:main',
'disparity_viewer = ' + package_name + '.disparity_viewer:main',
'disparity_publisher = ' + package_name + '.disparity_publisher:main',
'pcd_publisher = ' + package_name + '.pcd_publisher:main'
],
},
)
| 30.307692 | 82 | 0.615059 |
f85cbe392f54c51a5b9b02a9979eeca1002b0469 | 3,296 | py | Python | orgdown/paragraph.py | dcheno/orgdown | f67b2333413587fe27070ad7283101791bade374 | [
"MIT"
] | null | null | null | orgdown/paragraph.py | dcheno/orgdown | f67b2333413587fe27070ad7283101791bade374 | [
"MIT"
] | null | null | null | orgdown/paragraph.py | dcheno/orgdown | f67b2333413587fe27070ad7283101791bade374 | [
"MIT"
] | null | null | null | from paragraph_type import ParagraphType
from xmlobject import XmlObject
SCENE_BREAK_CHARACTER = "#"
ONE_THIRD_PAGE = 12
STANDARD_BUFFER = 2
# I imagine these might someday be better
# placed in their own configuration file.
LEVELS = {
ParagraphType.PART: 0,
ParagraphType.PROLOGUE: 1,
ParagraphType.CHAPTER: 1,
ParagraphType.PART_ENDER: 1,
ParagraphType.EPILOGUE: 1,
ParagraphType.CHAPTER_PART: 2,
ParagraphType.SCENE: 3,
ParagraphType.NORMAL: 4
}
CENTERED = [
ParagraphType.PART,
ParagraphType.CHAPTER,
ParagraphType.CHAPTER_PART,
ParagraphType.SCENE,
ParagraphType.PROLOGUE,
ParagraphType.EPILOGUE,
ParagraphType.PART_ENDER
]
UPPER = [
ParagraphType.PART,
ParagraphType.CHAPTER
]
PAGE_BREAK_BEFORE = [
ParagraphType.PART,
ParagraphType.CHAPTER,
ParagraphType.PROLOGUE,
ParagraphType.EPILOGUE,
ParagraphType.PART_ENDER
]
PAGE_BREAK_AFTER = [
ParagraphType.PART
]
BUFFER_SPACES = {
ParagraphType.CHAPTER_PART: 2,
ParagraphType.SCENE: 1
}
HIDE_TITLE = [
ParagraphType.PART_ENDER
]
INDENT = [
ParagraphType.NORMAL
]
class Paragraph:
def __init__(self, paragraph_type, line, previous_paragraph_type):
self._display_xml = True
if paragraph_type != ParagraphType.SCENE:
self._text = line
else:
self._text = SCENE_BREAK_CHARACTER
if previous_paragraph_type != ParagraphType.NORMAL:
self._display_xml = False
self._paragraph_type = paragraph_type
self._previous_paragraph_type = previous_paragraph_type
if paragraph_type == ParagraphType.PROLOGUE:
self._text = 'Prologue'
elif paragraph_type == ParagraphType.EPILOGUE:
self._text = 'Epilogue'
def get_type(self):
return self._paragraph_type
def getXml(self):
# Special Case where the line does not represent any
# displayable text.
if self._display_xml == False:
return ''
xmlObject = XmlObject(self._text)
if self._paragraph_type in CENTERED:
xmlObject.center()
if self._paragraph_type in UPPER:
xmlObject.upper()
if self._paragraph_type in PAGE_BREAK_BEFORE:
if self._previous_paragraph_type not in PAGE_BREAK_AFTER:
xmlObject.pre_page_break()
xmlObject.set_pre_buffer(ONE_THIRD_PAGE)
xmlObject.set_post_buffer(STANDARD_BUFFER)
if self._paragraph_type in PAGE_BREAK_AFTER:
xmlObject.post_page_break()
if self._paragraph_type in BUFFER_SPACES:
previous_buffer = BUFFER_SPACES.get(
self._previous_paragraph_type, 0)
def_pre_buffer = BUFFER_SPACES[self._paragraph_type]
print(previous_buffer)
print(def_pre_buffer)
pre_buffer = max(def_pre_buffer - previous_buffer, 0)
print(pre_buffer)
xmlObject.set_pre_buffer(pre_buffer)
xmlObject.set_post_buffer(def_pre_buffer)
if self._paragraph_type in HIDE_TITLE:
xmlObject.remove_text()
if self._paragraph_type in INDENT:
xmlObject.indent()
output = xmlObject.getXml()
return output
| 25.550388 | 70 | 0.668083 |
5f14d8a7d511b2aba14538a318734e4f05a21590 | 322 | py | Python | awesome_template/__about__.py | enpaul/pyproject-template | 8abfe9aecd263ba5679532ccc5a6546473992e65 | [
"MIT"
] | null | null | null | awesome_template/__about__.py | enpaul/pyproject-template | 8abfe9aecd263ba5679532ccc5a6546473992e65 | [
"MIT"
] | null | null | null | awesome_template/__about__.py | enpaul/pyproject-template | 8abfe9aecd263ba5679532ccc5a6546473992e65 | [
"MIT"
] | null | null | null | """Programatically accessible project metadata"""
__title__ = "awesome-template"
__summary__ = "An awesome python template project that does nothing"
__version__ = "0.0.0"
__url__ = "https://github.com/enpaul/awesome-template/"
__license__ = "MIT"
__authors__ = ["Ethan Paul <24588726+enpaul@users.noreply.github.com>"]
| 32.2 | 71 | 0.76087 |
5d1abb41d48ace514998d88e5113906d864a1544 | 2,380 | py | Python | src/waldur_openstack/openstack/tests/test_service.py | geant-multicloud/MCMS-mastermind | 81333180f5e56a0bc88d7dad448505448e01f24e | [
"MIT"
] | 26 | 2017-10-18T13:49:58.000Z | 2021-09-19T04:44:09.000Z | src/waldur_openstack/openstack/tests/test_service.py | geant-multicloud/MCMS-mastermind | 81333180f5e56a0bc88d7dad448505448e01f24e | [
"MIT"
] | 14 | 2018-12-10T14:14:51.000Z | 2021-06-07T10:33:39.000Z | src/waldur_openstack/openstack/tests/test_service.py | geant-multicloud/MCMS-mastermind | 81333180f5e56a0bc88d7dad448505448e01f24e | [
"MIT"
] | 32 | 2017-09-24T03:10:45.000Z | 2021-10-16T16:41:09.000Z | from unittest.mock import patch
from django.core.exceptions import ValidationError
from rest_framework import status, test
from waldur_core.structure.models import ServiceSettings
from waldur_core.structure.tests import factories, fixtures
@patch('waldur_core.structure.models.ServiceSettings.get_backend')
class OpenStackServiceCreateTest(test.APITransactionTestCase):
def setUp(self):
super(OpenStackServiceCreateTest, self).setUp()
self.fixture = fixtures.CustomerFixture()
self.url = factories.ServiceSettingsFactory.get_list_url()
def test_user_can_add_service_to_the_customer_he_owns(self, mocked_backend):
mocked_backend().check_admin_tenant.return_value = True
self.client.force_authenticate(user=self.fixture.owner)
payload = self.get_payload()
with patch(
'waldur_core.structure.executors.ServiceSettingsCreateExecutor.execute'
) as mocked:
response = self.client.post(self.url, payload)
self.assertEqual(
response.status_code, status.HTTP_201_CREATED, response.data
)
settings = ServiceSettings.objects.get(name=payload['name'])
self.assertFalse(settings.shared)
mocked.assert_any_call(settings)
mocked_backend().validate_settings.assert_called_once()
def test_admin_service_credentials_are_validated(self, mocked_backend):
mocked_backend().validate_settings.side_effect = ValidationError(
'Provided credentials are not for admin tenant.'
)
self.client.force_authenticate(user=self.fixture.owner)
payload = self.get_payload()
response = self.client.post(self.url, payload)
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)
self.assertEqual(
response.data['non_field_errors'],
['Provided credentials are not for admin tenant.'],
)
def get_payload(self):
return {
'name': 'service_settings name',
'customer': factories.CustomerFactory.get_url(self.fixture.customer),
'type': 'OpenStack',
'options': {
'backend_url': 'http://example.com',
'username': 'user',
'password': 'secret',
'tenant_name': 'admin',
},
}
| 37.777778 | 83 | 0.668067 |
5522713a4190d3b4e6c3a9a428f18f3151dc36cb | 45,254 | py | Python | lib/aff4_objects/stats_store_test.py | pchaigno/grr | 69c81624c281216a45c4bb88a9d4e4b0613a3556 | [
"Apache-2.0"
] | null | null | null | lib/aff4_objects/stats_store_test.py | pchaigno/grr | 69c81624c281216a45c4bb88a9d4e4b0613a3556 | [
"Apache-2.0"
] | null | null | null | lib/aff4_objects/stats_store_test.py | pchaigno/grr | 69c81624c281216a45c4bb88a9d4e4b0613a3556 | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/env python
"""Tests for the stats_store classes."""
import math
import pandas
from grr.lib import aff4
from grr.lib import data_store
from grr.lib import flags
from grr.lib import rdfvalue
from grr.lib import stats
from grr.lib import test_lib
from grr.lib.aff4_objects import stats_store
class StatsStoreTest(test_lib.AFF4ObjectTest):
def setUp(self):
super(StatsStoreTest, self).setUp()
self.process_id = "some_pid"
self.stats_store = aff4.FACTORY.Create(
None, "StatsStore", mode="w", token=self.token)
def testCountersAreWrittenToDataStore(self):
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(process_id=self.process_id, timestamp=42,
sync=True)
row = data_store.DB.ResolveRegex("aff4:/stats_store/some_pid", ".*",
token=self.token)
counter = [x for x in row if x[0] == "aff4:stats_store/counter"]
self.assertTrue(counter)
stored_value = stats_store.StatsStoreValue(
value_type=stats.MetricMetadata.ValueType.INT,
int_value=1)
self.assertEqual(counter[0], ("aff4:stats_store/counter",
stored_value.SerializeToString(),
42))
def testCountersWithFieldsAreWrittenToDataStore(self):
stats.STATS.RegisterCounterMetric("counter", fields=[("source", str)])
stats.STATS.IncrementCounter("counter", fields=["http"])
stats.STATS.IncrementCounter("counter", delta=2, fields=["rpc"])
self.stats_store.WriteStats(process_id=self.process_id, timestamp=42,
sync=True)
row = data_store.DB.ResolveRegex("aff4:/stats_store/some_pid", ".*",
token=self.token)
# Check that no plain counter is written.
values = [stats_store.StatsStoreValue(x[1]) for x in row
if x[0] == "aff4:stats_store/counter"]
self.assertEqual(len(values), 2)
http_field_value = stats_store.StatsStoreFieldValue(
field_type=stats.MetricFieldDefinition.FieldType.STR,
str_value="http")
rpc_field_value = stats_store.StatsStoreFieldValue(
field_type=stats.MetricFieldDefinition.FieldType.STR,
str_value="rpc")
# Check that counter with source=http is written.
http_counter = [x for x in values
if x.fields_values == [http_field_value]]
self.assertTrue(http_counter)
self.assertEqual(http_counter[0].value_type,
stats.MetricMetadata.ValueType.INT)
self.assertEqual(http_counter[0].int_value, 1)
# Check that counter with source=rpc is written.
rpc_counter = [x for x in values
if x.fields_values == [rpc_field_value]]
self.assertTrue(rpc_counter)
self.assertEqual(rpc_counter[0].value_type,
stats.MetricMetadata.ValueType.INT)
self.assertEqual(rpc_counter[0].int_value, 2)
def testEventMetricsAreWrittenToDataStore(self):
stats.STATS.RegisterEventMetric("foo_event")
stats.STATS.RecordEvent("foo_event", 5)
stats.STATS.RecordEvent("foo_event", 15)
self.stats_store.WriteStats(process_id=self.process_id, timestamp=42,
sync=True)
row = data_store.DB.ResolveRegex("aff4:/stats_store/some_pid", ".*",
token=self.token)
values = [stats_store.StatsStoreValue(x[1]) for x in row
if x[0] == "aff4:stats_store/foo_event"]
self.assertEqual(len(values), 1)
stored_value = values[0]
self.assertEqual(stored_value.value_type,
stats.MetricMetadata.ValueType.DISTRIBUTION)
self.assertEqual(stored_value.distribution_value.count, 2)
self.assertEqual(stored_value.distribution_value.sum, 20)
def testEventMetricsWithFieldsAreWrittenToDataStore(self):
stats.STATS.RegisterEventMetric("foo_event", fields=[("source", str)])
stats.STATS.RecordEvent("foo_event", 5, fields=["http"])
stats.STATS.RecordEvent("foo_event", 15, fields=["rpc"])
self.stats_store.WriteStats(process_id=self.process_id, timestamp=42,
sync=True)
row = data_store.DB.ResolveRegex("aff4:/stats_store/some_pid", ".*",
token=self.token)
values = [stats_store.StatsStoreValue(x[1]) for x in row
if x[0] == "aff4:stats_store/foo_event"]
self.assertEqual(len(values), 2)
http_field_value = stats_store.StatsStoreFieldValue(
field_type=stats.MetricFieldDefinition.FieldType.STR,
str_value="http")
rpc_field_value = stats_store.StatsStoreFieldValue(
field_type=stats.MetricFieldDefinition.FieldType.STR,
str_value="rpc")
# Check that distribution with source=http is written.
http_events = [x for x in values
if x.fields_values == [http_field_value]]
self.assertTrue(http_events)
self.assertEqual(http_events[0].value_type,
stats.MetricMetadata.ValueType.DISTRIBUTION)
self.assertEqual(http_events[0].distribution_value.count, 1)
self.assertEqual(http_events[0].distribution_value.sum, 5)
# Check that distribution with source=rpc is written.
rpc_events = [x for x in values
if x.fields_values == [rpc_field_value]]
self.assertTrue(rpc_events)
self.assertEqual(rpc_events[0].value_type,
stats.MetricMetadata.ValueType.DISTRIBUTION)
self.assertEqual(rpc_events[0].distribution_value.count, 1)
self.assertEqual(rpc_events[0].distribution_value.sum, 15)
def testStringGaugeValuesAreWrittenToDataStore(self):
stats.STATS.RegisterGaugeMetric("str_gauge", str)
stats.STATS.SetGaugeValue("str_gauge", "some_value")
self.stats_store.WriteStats(process_id=self.process_id, timestamp=42,
sync=True)
row = data_store.DB.ResolveRegex("aff4:/stats_store/some_pid", ".*",
token=self.token)
counter = [x for x in row if x[0] == "aff4:stats_store/str_gauge"]
self.assertTrue(counter)
stored_value = stats_store.StatsStoreValue(
value_type=stats.MetricMetadata.ValueType.STR,
str_value="some_value")
self.assertEqual(counter[0], ("aff4:stats_store/str_gauge",
stored_value.SerializeToString(),
42))
def testIntGaugeValuesAreWrittenToDataStore(self):
stats.STATS.RegisterGaugeMetric("int_gauge", int)
stats.STATS.SetGaugeValue("int_gauge", 4242)
self.stats_store.WriteStats(process_id=self.process_id, timestamp=42,
sync=True)
row = data_store.DB.ResolveRegex("aff4:/stats_store/some_pid", ".*",
token=self.token)
counter = [x for x in row if x[0] == "aff4:stats_store/int_gauge"]
self.assertTrue(counter)
stored_value = stats_store.StatsStoreValue(
value_type=stats.MetricMetadata.ValueType.INT,
int_value=4242)
self.assertEqual(counter[0], ("aff4:stats_store/int_gauge",
stored_value.SerializeToString(),
42))
def testLaterValuesDoNotOverridePrevious(self):
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(process_id=self.process_id, timestamp=42,
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(process_id=self.process_id, timestamp=43,
sync=True)
row = data_store.DB.ResolveRegex("aff4:/stats_store/some_pid", ".*",
token=self.token)
counters = [x for x in row if x[0] == "aff4:stats_store/counter"]
self.assertEqual(len(counters), 2)
counters = sorted(counters, key=lambda x: x[2])
stored_value = stats_store.StatsStoreValue(
value_type=stats.MetricMetadata.ValueType.INT,
int_value=1)
self.assertEqual(counters[0], ("aff4:stats_store/counter",
stored_value.SerializeToString(),
42))
stored_value = stats_store.StatsStoreValue(
value_type=stats.MetricMetadata.ValueType.INT,
int_value=2)
self.assertEqual(counters[1], ("aff4:stats_store/counter",
stored_value.SerializeToString(),
43))
def testValuesAreFetchedCorrectly(self):
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.RegisterGaugeMetric("int_gauge", int)
stats.STATS.SetGaugeValue("int_gauge", 4242)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(process_id=self.process_id, timestamp=42,
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(process_id=self.process_id, timestamp=43,
sync=True)
stats_history = self.stats_store.ReadStats(
process_id=self.process_id,
timestamp=self.stats_store.ALL_TIMESTAMPS)
self.assertEqual(stats_history["counter"], [(1, 42), (2, 43)])
self.assertEqual(stats_history["int_gauge"], [(4242, 42), (4242, 43)])
def testFetchedValuesCanBeLimitedByTimeRange(self):
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.RegisterGaugeMetric("int_gauge", int)
stats.STATS.SetGaugeValue("int_gauge", 4242)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(process_id=self.process_id, timestamp=42,
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(process_id=self.process_id, timestamp=43,
sync=True)
stats_history = self.stats_store.ReadStats(process_id=self.process_id,
timestamp=(0, 42))
self.assertEqual(stats_history["counter"], [(1, 42)])
self.assertEqual(stats_history["int_gauge"], [(4242, 42)])
def testFetchedValuesCanBeLimitedByName(self):
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.RegisterGaugeMetric("int_gauge", int)
stats.STATS.SetGaugeValue("int_gauge", 4242)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(process_id=self.process_id, timestamp=42,
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(process_id=self.process_id, timestamp=43,
sync=True)
stats_history = self.stats_store.ReadStats(process_id=self.process_id,
predicate_regex="counter")
self.assertEqual(stats_history["counter"], [(1, 42), (2, 43)])
self.assertTrue("int_gauge" not in stats_history)
def testDeleteStatsInTimeRangeWorksCorrectly(self):
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.RegisterGaugeMetric("int_gauge", int)
stats.STATS.SetGaugeValue("int_gauge", 4242)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(process_id=self.process_id, timestamp=42,
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(process_id=self.process_id, timestamp=44,
sync=True)
self.stats_store.DeleteStats(process_id=self.process_id, timestamp=(0, 43),
sync=True)
stats_history = self.stats_store.ReadStats(process_id=self.process_id)
self.assertEqual(stats_history["counter"], [(2, 44)])
self.assertEqual(stats_history["int_gauge"], [(4242, 44)])
def testDeleteStatsInTimeRangeWorksCorrectlyWithFields(self):
stats.STATS.RegisterCounterMetric("counter", fields=[("source", str)])
stats.STATS.IncrementCounter("counter", fields=["http"])
self.stats_store.WriteStats(process_id=self.process_id, timestamp=42,
sync=True)
stats.STATS.IncrementCounter("counter", fields=["http"])
stats.STATS.IncrementCounter("counter", fields=["rpc"])
self.stats_store.WriteStats(process_id=self.process_id, timestamp=44,
sync=True)
self.stats_store.DeleteStats(process_id=self.process_id, timestamp=(0, 43),
sync=True)
stats_history = self.stats_store.ReadStats(process_id=self.process_id)
self.assertEqual(stats_history["counter"]["http"], [(2, 44)])
self.assertEqual(stats_history["counter"]["rpc"], [(1, 44)])
def testReturnsListOfAllUsedProcessIds(self):
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.RegisterGaugeMetric("int_gauge", int)
self.stats_store.WriteStats(process_id="pid1", sync=True)
self.stats_store.WriteStats(process_id="pid2", sync=True)
self.assertEqual(sorted(self.stats_store.ListUsedProcessIds()),
["pid1", "pid2"])
def testMultiReadStatsWorksCorrectly(self):
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(process_id="pid1", timestamp=42, sync=True)
self.stats_store.WriteStats(process_id="pid2", timestamp=42, sync=True)
self.stats_store.WriteStats(process_id="pid2", timestamp=43, sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(process_id="pid1", timestamp=43, sync=True)
results = self.stats_store.MultiReadStats()
self.assertEqual(sorted(results.keys()), ["pid1", "pid2"])
self.assertEqual(results["pid1"]["counter"], [(1, 42), (2, 43)])
self.assertEqual(results["pid2"]["counter"], [(1, 42), (1, 43)])
def testMultiReadStatsLimitsResultsByTimeRange(self):
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(process_id="pid1", timestamp=42, sync=True)
self.stats_store.WriteStats(process_id="pid2", timestamp=42, sync=True)
self.stats_store.WriteStats(process_id="pid2", timestamp=44, sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(process_id="pid1", timestamp=44, sync=True)
results = self.stats_store.MultiReadStats(
timestamp=(43, 100))
self.assertEqual(sorted(results.keys()), ["pid1", "pid2"])
self.assertEqual(results["pid1"]["counter"], [(2, 44)])
self.assertEqual(results["pid2"]["counter"], [(1, 44)])
def testReadMetadataReturnsAllUsedMetadata(self):
# Register metrics
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.RegisterCounterMetric("counter_with_fields",
fields=[("source", str)])
stats.STATS.RegisterEventMetric("events")
stats.STATS.RegisterEventMetric("events_with_fields",
fields=[("source", str)])
stats.STATS.RegisterGaugeMetric("str_gauge", str)
stats.STATS.RegisterGaugeMetric("str_gauge_with_fields", str,
fields=[("task", int)])
# Check that there are no metadata for registered metrics.
metadata = self.stats_store.ReadMetadata(process_id=self.process_id)
self.assertFalse("counter" in metadata)
self.assertFalse("counter_with_fields" in metadata)
self.assertFalse("events" in metadata)
self.assertFalse("events_with_fields" in metadata)
self.assertFalse("str_gauge" in metadata)
self.assertFalse("str_gauge_with_fields" in metadata)
# Write stats to the data store. Metadata should be
# written as well.
self.stats_store.WriteStats(process_id=self.process_id,
timestamp=42, sync=True)
# Check that metadata were written into the store.
metadata = self.stats_store.ReadMetadata(process_id=self.process_id)
# Field definitions used in assertions below.
source_field_def = stats.MetricFieldDefinition(
field_name="source",
field_type=stats.MetricFieldDefinition.FieldType.STR)
task_field_def = stats.MetricFieldDefinition(
field_name="task",
field_type=stats.MetricFieldDefinition.FieldType.INT)
self.assertTrue("counter" in metadata)
self.assertEqual(metadata["counter"].varname, "counter")
self.assertEqual(metadata["counter"].metric_type, stats.MetricType.COUNTER)
self.assertEqual(metadata["counter"].value_type,
stats.MetricMetadata.ValueType.INT)
self.assertListEqual(list(metadata["counter"].fields_defs), [])
self.assertTrue("counter_with_fields" in metadata)
self.assertEqual(metadata["counter_with_fields"].varname,
"counter_with_fields")
self.assertEqual(metadata["counter_with_fields"].metric_type,
stats.MetricType.COUNTER)
self.assertEqual(metadata["counter_with_fields"].value_type,
stats.MetricMetadata.ValueType.INT)
self.assertListEqual(list(metadata["counter_with_fields"].fields_defs),
[source_field_def])
self.assertTrue("events" in metadata)
self.assertEqual(metadata["events"].varname, "events")
self.assertEqual(metadata["events"].metric_type, stats.MetricType.EVENT)
self.assertEqual(metadata["events"].value_type,
stats.MetricMetadata.ValueType.DISTRIBUTION)
self.assertListEqual(list(metadata["events"].fields_defs), [])
self.assertTrue("events_with_fields" in metadata)
self.assertEqual(metadata["events_with_fields"].varname,
"events_with_fields")
self.assertEqual(metadata["events_with_fields"].metric_type,
stats.MetricType.EVENT)
self.assertEqual(metadata["events_with_fields"].value_type,
stats.MetricMetadata.ValueType.DISTRIBUTION)
self.assertListEqual(list(metadata["events_with_fields"].fields_defs),
[source_field_def])
self.assertTrue("str_gauge" in metadata)
self.assertEqual(metadata["str_gauge"].varname, "str_gauge")
self.assertEqual(metadata["str_gauge"].metric_type, stats.MetricType.GAUGE)
self.assertEqual(metadata["str_gauge"].value_type,
stats.MetricMetadata.ValueType.STR)
self.assertListEqual(list(metadata["str_gauge"].fields_defs), [])
self.assertTrue("str_gauge_with_fields" in metadata)
self.assertEqual(metadata["str_gauge_with_fields"].varname,
"str_gauge_with_fields")
self.assertEqual(metadata["str_gauge_with_fields"].metric_type,
stats.MetricType.GAUGE)
self.assertEqual(metadata["str_gauge_with_fields"].value_type,
stats.MetricMetadata.ValueType.STR)
self.assertListEqual(list(metadata["str_gauge_with_fields"].fields_defs),
[task_field_def])
def testMultiReadMetadataReturnsAllUsedMetadata(self):
stats.STATS.RegisterCounterMetric("counter")
# Check that there are no metadata for registered metrics.
metadata_by_id = self.stats_store.MultiReadMetadata(
process_ids=["pid1", "pid2"])
self.assertFalse("counter" in metadata_by_id["pid1"])
self.assertFalse("counter" in metadata_by_id["pid2"])
# Write stats to the data store. Metadata should be
# written as well.
self.stats_store.WriteStats(process_id="pid1",
timestamp=42, sync=True)
# Now metadata should be found only for the pid1.
metadata_by_id = self.stats_store.MultiReadMetadata(
process_ids=["pid1", "pid2"])
self.assertTrue("counter" in metadata_by_id["pid1"])
self.assertFalse("counter" in metadata_by_id["pid2"])
# Write stats for the pid2 and check again.
self.stats_store.WriteStats(process_id="pid2",
timestamp=42, sync=True)
metadata_by_id = self.stats_store.MultiReadMetadata(
process_ids=["pid1", "pid2"])
self.assertTrue("counter" in metadata_by_id["pid1"])
self.assertTrue("counter" in metadata_by_id["pid2"])
class StatsStoreDataQueryTest(test_lib.AFF4ObjectTest):
"""Tests for StatsStoreDataQuery class."""
def setUp(self):
super(StatsStoreDataQueryTest, self).setUp()
self.process_id = "some_pid"
self.stats_store = aff4.FACTORY.Create(
None, "StatsStore", mode="w", token=self.token)
def testUsingInCallNarrowsQuerySpace(self):
# Create sample data.
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.RegisterCounterMetric("counter_with_fields",
fields=[("source", str)])
stats.STATS.IncrementCounter("counter")
stats.STATS.IncrementCounter("counter_with_fields",
fields=["http"])
stats.STATS.IncrementCounter("counter_with_fields",
fields=["rpc"])
# Write to data store.
self.stats_store.WriteStats(process_id=self.process_id,
timestamp=42, sync=True)
# Read them back and apply queries with In() and InAll() calls.
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertEqual(query.In("counter").SeriesCount(), 1)
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertEqual(query.In("counter_with_fields").InAll().SeriesCount(), 2)
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertEqual(query.In("counter_with_fields").In("http").SeriesCount(),
1)
def testInCallAcceptsRegularExpressions(self):
# Initialize and write test data.
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id="pid1",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(0),
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id="pid1",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(90),
sync=True)
self.stats_store.WriteStats(
process_id="pid2",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(90),
sync=True)
stats_data = self.stats_store.MultiReadStats(process_ids=["pid1", "pid2"])
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertEqual(query.In("pid1").In("counter").SeriesCount(), 1)
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertEqual(query.In("pid2").In("counter").SeriesCount(), 1)
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertEqual(query.In("pid.*").In("counter").SeriesCount(), 2)
def testInTimeRangeLimitsQueriesByTime(self):
# Initialize and write test data.
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(42),
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(100),
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(140),
sync=True)
# Read data back.
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
# Check that InTimeRange works as expected.
query = stats_store.StatsStoreDataQuery(stats_data)
ts = query.In("counter").TakeValue().InTimeRange(
rdfvalue.RDFDatetime().FromSecondsFromEpoch(80),
rdfvalue.RDFDatetime().FromSecondsFromEpoch(120)).ts
self.assertListEqual(list(ts), [2])
self.assertListEqual(list(ts.index), [pandas.Timestamp(100 * 1e9)])
def testInTimeRangeRaisesIfAppliedBeforeTakeMethod(self):
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertRaises(RuntimeError, query.In("counter").InTimeRange,
rdfvalue.RDFDatetime().FromSecondsFromEpoch(80),
rdfvalue.RDFDatetime().FromSecondsFromEpoch(120))
def testTakeValueUsesPlainValuesToBuildTimeSeries(self):
# Initialize and write test data.
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(42),
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(100),
sync=True)
# Read data back.
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
# Get time series generated with TakeValue().
query = stats_store.StatsStoreDataQuery(stats_data)
ts = query.In("counter").TakeValue().ts
self.assertListEqual(list(ts), [1, 2])
self.assertListEqual(list(ts.index), [pandas.Timestamp(42 * 1e9),
pandas.Timestamp(100 * 1e9)])
def testTakeValueRaisesIfDistributionIsEncountered(self):
# Initialize and write test data.
stats.STATS.RegisterEventMetric("events")
stats.STATS.RecordEvent("events", 42)
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(42),
sync=True)
# Read data back.
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertRaises(ValueError, query.In("events").TakeValue)
def testTakeDistributionCountUsesDistributionCountsToBuildTimeSeries(self):
# Initialize and write test data.
stats.STATS.RegisterEventMetric("events")
stats.STATS.RecordEvent("events", 42)
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(42),
sync=True)
stats.STATS.RecordEvent("events", 43)
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(100),
sync=True)
# Read data back.
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
query = stats_store.StatsStoreDataQuery(stats_data)
ts = query.In("events").TakeDistributionCount().ts
self.assertListEqual(list(ts), [1, 2])
self.assertListEqual(list(ts.index), [pandas.Timestamp(42 * 1e9),
pandas.Timestamp(100 * 1e9)])
def testTakeDistributionCountRaisesIfPlainValueIsEncountered(self):
# Initialize and write test data.
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(42),
sync=True)
# Read data back.
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertRaises(ValueError, query.In("counter").TakeDistributionCount)
def testTakeDistributionSumUsesDistributionSumsToBuildTimeSeries(self):
# Initialize and write test data.
stats.STATS.RegisterEventMetric("events")
stats.STATS.RecordEvent("events", 42)
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(42),
sync=True)
stats.STATS.RecordEvent("events", 43)
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(100),
sync=True)
# Read data back.
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
query = stats_store.StatsStoreDataQuery(stats_data)
ts = query.In("events").TakeDistributionSum().ts
self.assertListEqual(list(ts), [42, 85])
self.assertListEqual(list(ts.index), [pandas.Timestamp(42 * 1e9),
pandas.Timestamp(100 * 1e9)])
def testTakeDistributionSumRaisesIfPlainValueIsEncountered(self):
# Initialize and write test data.
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(42),
sync=True)
# Read data back.
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertRaises(ValueError, query.In("counter").TakeDistributionSum)
def testResampleCallResamplesTimeSeries(self):
# Initialize and write test data.
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(0),
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(15),
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(45),
sync=True)
# Read data back.
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
query = stats_store.StatsStoreDataQuery(stats_data)
ts = query.In("counter").TakeValue().Resample(
rdfvalue.Duration("30s")).ts
self.assertAlmostEqual(ts[0], 1.5)
self.assertAlmostEqual(ts[1], 3.0)
self.assertListEqual(list(ts.index), [pandas.Timestamp(0 * 1e9),
pandas.Timestamp(30 * 1e9)])
def testResampleCallDoesNotFillGaps(self):
# Initialize and write test data.
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(0),
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(75),
sync=True)
# Read data back.
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
query = stats_store.StatsStoreDataQuery(stats_data)
ts = query.In("counter").TakeValue().Resample(
rdfvalue.Duration("30s")).ts
self.assertAlmostEqual(ts[0], 1.0)
self.assertTrue(math.isnan(ts[1]))
self.assertAlmostEqual(ts[2], 2.0)
self.assertListEqual(list(ts.index), [pandas.Timestamp(0 * 1e9),
pandas.Timestamp(30 * 1e9),
pandas.Timestamp(60 * 1e9)])
def testResampleRaisesIfAppliedBeforeTakeMethod(self):
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertRaises(RuntimeError, query.In("counter").Resample,
rdfvalue.Duration("30s"))
def testFillMissingCallFillsGapsInTimeSeries(self):
# Initialize and write test data.
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(0),
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(120),
sync=True)
# Read data back.
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
query = stats_store.StatsStoreDataQuery(stats_data)
ts = query.In("counter").TakeValue().Resample(
rdfvalue.Duration("30s")).FillMissing(rdfvalue.Duration("60s")).ts
self.assertAlmostEqual(ts[0], 1.0)
self.assertAlmostEqual(ts[1], 1.0)
self.assertAlmostEqual(ts[2], 1.0)
self.assertAlmostEqual(ts[3], 2.0)
self.assertAlmostEqual(ts[4], 2.0)
self.assertListEqual(list(ts.index), [pandas.Timestamp(0 * 1e9),
pandas.Timestamp(30 * 1e9),
pandas.Timestamp(60 * 1e9),
pandas.Timestamp(90 * 1e9),
pandas.Timestamp(120 * 1e9)])
def testFillMissingRaisesIfAppliedBeforeTakeMethod(self):
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertRaises(RuntimeError, query.In("counter").FillMissing, 3)
def testFillMissingRaisesIfTimeWindowIsNotDivisibleBySamplingInterval(self):
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertRaises(RuntimeError, query.In("counter").TakeValue().Resample(
rdfvalue.Duration("25s")).FillMissing, rdfvalue.Duration("60s"))
def testAggregateViaSumAggregatesMultipleTimeSeriesIntoOne(self):
# Initialize and write test data.
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id="pid1",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(0),
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id="pid2",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(0),
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id="pid1",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(90),
sync=True)
self.stats_store.WriteStats(
process_id="pid2",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(90),
sync=True)
stats_data = self.stats_store.MultiReadStats(process_ids=["pid1", "pid2"])
query = stats_store.StatsStoreDataQuery(stats_data)
ts = query.In("pid.*").In("counter").TakeValue().Resample(
rdfvalue.Duration("30s")).FillMissing(
rdfvalue.Duration("10m")).AggregateViaSum().ts
# We expect 2 time series in the query:
# 1970-01-01 00:00:00 1
# 1970-01-01 00:00:30 1
# 1970-01-01 00:01:00 1
# 1970-01-01 00:01:30 3
#
# and:
# 1970-01-01 00:00:00 2
# 1970-01-01 00:00:30 2
# 1970-01-01 00:01:00 2
# 1970-01-01 00:01:30 3
#
# Therefore we expect the sum to look like:
# 1970-01-01 00:00:00 3
# 1970-01-01 00:00:30 3
# 1970-01-01 00:01:00 3
# 1970-01-01 00:01:30 6
self.assertAlmostEqual(ts[0], 3)
self.assertAlmostEqual(ts[1], 3)
self.assertAlmostEqual(ts[2], 3)
self.assertAlmostEqual(ts[3], 6)
self.assertListEqual(list(ts.index), [pandas.Timestamp(0 * 1e9),
pandas.Timestamp(30 * 1e9),
pandas.Timestamp(60 * 1e9),
pandas.Timestamp(90 * 1e9)])
def testAggregateViaSumAlignsMultipleTimeSeriesBeforeAggregation(self):
# Initialize and write test data.
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id="pid1",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(0),
sync=True)
self.stats_store.WriteStats(
process_id="pid1",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(50),
sync=True)
self.stats_store.WriteStats(
process_id="pid2",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(0),
sync=True)
self.stats_store.WriteStats(
process_id="pid2",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(50),
sync=True)
self.stats_store.WriteStats(
process_id="pid2",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(150),
sync=True)
# After Resample and FillMissing call we end up with 2 time series:
# 1970-01-01 00:00:00 1
# 1970-01-01 00:00:30 1
#
# And:
# 1970-01-01 00:00:30 1
# 1970-01-01 00:01:00 1
# 1970-01-01 00:01:30 1
# 1970-01-01 00:02:00 1
# 1970-01-01 00:02:30 1
#
# Before they're agrregated, first time series should be interpolated
# to contain all the timestamps that the second one contains.
# Otherwise we'll get incorrect aggregation results.
stats_data = self.stats_store.MultiReadStats(process_ids=["pid1", "pid2"])
query = stats_store.StatsStoreDataQuery(stats_data)
ts = query.In("pid.*").In("counter").TakeValue().Resample(
rdfvalue.Duration("30s")).FillMissing(
rdfvalue.Duration("10m")).AggregateViaSum().ts
# Therefore we expect the sum to look like:
# 1970-01-01 00:00:00 2
# 1970-01-01 00:00:30 2
# 1970-01-01 00:01:00 2
# 1970-01-01 00:01:30 2
# 1970-01-01 00:02:00 2
# 1970-01-01 00:02:30 2
self.assertAlmostEqual(ts[0], 2)
self.assertAlmostEqual(ts[1], 2)
self.assertAlmostEqual(ts[2], 2)
self.assertAlmostEqual(ts[3], 2)
self.assertAlmostEqual(ts[4], 2)
self.assertAlmostEqual(ts[5], 2)
self.assertListEqual(list(ts.index), [pandas.Timestamp(0 * 1e9),
pandas.Timestamp(30 * 1e9),
pandas.Timestamp(60 * 1e9),
pandas.Timestamp(90 * 1e9),
pandas.Timestamp(120 * 1e9),
pandas.Timestamp(150 * 1e9)])
def testEnsureIsIncrementalHandlesValuesResets(self):
# Initialize and write test data.
stats.STATS.RegisterCounterMetric("counter")
self.stats_store.WriteStats(
process_id="pid1",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(0),
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id="pid1",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(30),
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id="pid1",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(60),
sync=True)
stats.STATS.RegisterCounterMetric("counter")
self.stats_store.WriteStats(
process_id="pid1",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(90),
sync=True)
# We've reset the counter on 60th second, so we get following time series:
# 1970-01-01 00:00:00 0
# 1970-01-01 00:00:30 1
# 1970-01-01 00:01:00 2
# 1970-01-01 00:01:30 0
stats_data = self.stats_store.ReadStats(process_id="pid1")
query = stats_store.StatsStoreDataQuery(stats_data)
ts = query.In("counter").TakeValue().Resample(
rdfvalue.Duration("30s")).FillMissing(
rdfvalue.Duration("10m")).ts
self.assertAlmostEqual(ts[0], 0)
self.assertAlmostEqual(ts[1], 1)
self.assertAlmostEqual(ts[2], 2)
self.assertAlmostEqual(ts[3], 0)
# EnsureIsIncremental detects the reset and increments values that follow
# the reset point:
# 1970-01-01 00:00:00 0
# 1970-01-01 00:00:30 1
# 1970-01-01 00:01:00 2
# 1970-01-01 00:01:30 2
ts = query.EnsureIsIncremental().ts
self.assertAlmostEqual(ts[0], 0)
self.assertAlmostEqual(ts[1], 1)
self.assertAlmostEqual(ts[2], 2)
self.assertAlmostEqual(ts[3], 2)
def testSeriesCountReturnsNumberOfDataSeriesInCurrentQuery(self):
# Initialize and write test data.
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id="pid1",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(0),
sync=True)
self.stats_store.WriteStats(
process_id="pid2",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(90),
sync=True)
stats_data = self.stats_store.MultiReadStats(process_ids=["pid1", "pid2"])
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertEqual(query.In("pid.*").SeriesCount(), 2)
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertEqual(query.In("pid1").In("counter").SeriesCount(), 1)
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertEqual(query.In("pid.*").In("counter").SeriesCount(), 2)
def testRateAppliesRateRollingFunctionToSingleTimeSerie(self):
# Initialize and write test data.
stats.STATS.RegisterCounterMetric("counter")
for i in range(5):
for _ in range(i):
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(10 * i),
sync=True)
# Read data back.
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
# Get time series generated with TakeValue().
query = stats_store.StatsStoreDataQuery(stats_data)
ts = query.In("counter").TakeValue().Resample(
rdfvalue.Duration("10s")).Rate(rdfvalue.Duration("30s")).ts
# We expect following time serie:
# 1970-01-01 00:00:00 0
# 1970-01-01 00:00:10 1
# 1970-01-01 00:00:20 3
# 1970-01-01 00:00:30 6
# 1970-01-01 00:00:40 10
#
# Therefore we expect the following after applying Rate():
# 1970-01-01 00:00:30 0.2
# 1970-01-01 00:00:40 0.3
self.assertAlmostEqual(ts[0], 0.2)
self.assertAlmostEqual(ts[1], 0.3)
self.assertListEqual(list(ts.index), [pandas.Timestamp(30 * 1e9),
pandas.Timestamp(40 * 1e9)])
def testScaleAppliesScaleFunctionToSingleTimeSerie(self):
# Initialize and write test data.
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(42),
sync=True)
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(100),
sync=True)
# Read data back.
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
# Get time series generated with TakeValue().
query = stats_store.StatsStoreDataQuery(stats_data)
ts = query.In("counter").TakeValue().Scale(3).ts
self.assertListEqual(list(ts), [3, 6])
self.assertListEqual(list(ts.index), [pandas.Timestamp(42 * 1e9),
pandas.Timestamp(100 * 1e9)])
def testMeanReturnsZeroIfQueryHasNoTimeSeries(self):
# Read data back.
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
# Get time series generated with TakeValue().
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertEqual(query.In("counter").TakeValue().Mean(), 0)
def testMeanRaisesIfCalledOnMultipleTimeSeries(self):
# Initialize and write test data.
stats.STATS.RegisterCounterMetric("counter")
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id="pid1",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(0),
sync=True)
self.stats_store.WriteStats(
process_id="pid2",
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(90),
sync=True)
stats_data = self.stats_store.MultiReadStats(process_ids=["pid1", "pid2"])
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertRaises(RuntimeError,
query.In("pid.*").In("counter").TakeValue().Mean)
def testMeanReducesTimeSerieToSingleNumber(self):
# Initialize and write test data.
stats.STATS.RegisterCounterMetric("counter")
for i in range(5):
stats.STATS.IncrementCounter("counter")
self.stats_store.WriteStats(
process_id=self.process_id,
timestamp=rdfvalue.RDFDatetime().FromSecondsFromEpoch(10 * i),
sync=True)
# Read data back.
stats_data = self.stats_store.ReadStats(process_id=self.process_id)
# Get time series generated with TakeValue().
query = stats_store.StatsStoreDataQuery(stats_data)
self.assertAlmostEqual(query.In("counter").TakeValue().Mean(), 3)
def main(argv):
test_lib.main(argv)
if __name__ == "__main__":
flags.StartMain(main)
| 39.696491 | 79 | 0.671521 |
ee2f33b4342d24be437bad19986af1689bac8c69 | 396 | py | Python | ml_source/src/blocktorch/blocktorch/objectives/time_series_regression_objective.py | blocktorch/blocktorch | 044aa269813ab22c5fd27f84272e5fb540fc522b | [
"MIT"
] | 1 | 2021-09-23T12:23:02.000Z | 2021-09-23T12:23:02.000Z | ml_source/src/blocktorch/blocktorch/objectives/time_series_regression_objective.py | blocktorch/blocktorch | 044aa269813ab22c5fd27f84272e5fb540fc522b | [
"MIT"
] | null | null | null | ml_source/src/blocktorch/blocktorch/objectives/time_series_regression_objective.py | blocktorch/blocktorch | 044aa269813ab22c5fd27f84272e5fb540fc522b | [
"MIT"
] | null | null | null | """Base class for all time series regression objectives."""
from .regression_objective import RegressionObjective
from blocktorch.problem_types import ProblemTypes
class TimeSeriesRegressionObjective(RegressionObjective):
"""Base class for all time series regression objectives."""
problem_types = [ProblemTypes.TIME_SERIES_REGRESSION]
"""[ProblemTypes.TIME_SERIES_REGRESSION]"""
| 33 | 63 | 0.80303 |
1bc06fbaf395428985b9e9527192910c089789f5 | 1,774 | py | Python | Python/eight_kyu/greet_welcome.py | Brokenshire/codewars-projects | db9cd09618b8a7085b0d53ad76f73f9e249b9396 | [
"Apache-2.0"
] | 1 | 2019-12-20T04:09:56.000Z | 2019-12-20T04:09:56.000Z | Python/eight_kyu/greet_welcome.py | Brokenshire/codewars-projects | db9cd09618b8a7085b0d53ad76f73f9e249b9396 | [
"Apache-2.0"
] | null | null | null | Python/eight_kyu/greet_welcome.py | Brokenshire/codewars-projects | db9cd09618b8a7085b0d53ad76f73f9e249b9396 | [
"Apache-2.0"
] | null | null | null | # Python solution for 'Welcome!' codewars question.
# Level: 8 kyu
# Tags: FUNDAMENTALS, HASHES, DATA STRUCTURES, amd OBJECTS.
# Author: Jack Brokenshire
# Date: 22/05/2020
import unittest
def greet_welcome(language):
"""
Greets a given language in their language otherwise uses Welcome.
:param language: string determining language to greet.
:return: A greeting - if you have it in your database. It should default to English if the language is not in the
database, or in the event of an invalid input.
"""
database = {'english': 'Welcome',
'czech': 'Vitejte',
'danish': 'Velkomst',
'dutch': 'Welkom',
'estonian': 'Tere tulemast',
'finnish': 'Tervetuloa',
'flemish': 'Welgekomen',
'french': 'Bienvenue',
'german': 'Willkommen',
'irish': 'Failte',
'italian': 'Benvenuto',
'latvian': 'Gaidits',
'lithuanian': 'Laukiamas',
'polish': 'Witamy',
'spanish': 'Bienvenido',
'swedish': 'Valkommen',
'welsh': 'Croeso'}
if language not in database:
return "Welcome"
return database[language]
class TestGreetWelcome(unittest.TestCase):
"""Class to test 'greet_welcome' function"""
def test_greet_welcome(self):
self.assertEqual(greet_welcome('english'), 'Welcome')
self.assertEqual(greet_welcome('dutch'), 'Welkom')
self.assertEqual(greet_welcome('IP_ADDRESS_INVALID'), 'Welcome')
self.assertEqual(greet_welcome(''), 'Welcome')
self.assertEqual(greet_welcome(2), 'Welcome')
if __name__ == '__main__':
unittest.main()
| 34.115385 | 117 | 0.583991 |
0c11823815c158eb4b0f7687322e3e1cd8d231bc | 10,748 | py | Python | learn/legacy/20211007/learn_record.py | Nyanyan/Egaroucid | f8a5a46466f59a528244f44d80b1aa2e6c76c651 | [
"MIT"
] | 2 | 2021-07-28T09:25:26.000Z | 2021-08-22T14:44:21.000Z | learn/legacy/20211007/learn_record.py | Nyanyan/Egaroucid | f8a5a46466f59a528244f44d80b1aa2e6c76c651 | [
"MIT"
] | null | null | null | learn/legacy/20211007/learn_record.py | Nyanyan/Egaroucid | f8a5a46466f59a528244f44d80b1aa2e6c76c651 | [
"MIT"
] | null | null | null | import tensorflow as tf
from tensorflow.keras.datasets import boston_housing
from tensorflow.keras.layers import Activation, Add, BatchNormalization, Conv2D, Dense, GlobalAveragePooling2D, Input, concatenate, Flatten
from tensorflow.keras.models import Sequential, Model, load_model
from tensorflow.keras.callbacks import EarlyStopping, LearningRateScheduler, LambdaCallback
from tensorflow.keras.optimizers import Adam
#from keras.layers.advanced_activations import LeakyReLU
from tensorflow.keras.regularizers import l2
from tensorflow.python.keras.utils.vis_utils import plot_model
import numpy as np
import matplotlib.pyplot as plt
from tqdm import trange
from random import random, randint, shuffle, sample
import subprocess
from math import exp
from os import rename, path, listdir
from time import time
import datetime
def LeakyReLU(x):
return tf.math.maximum(0.01 * x, x)
hw = 8
hw2 = 64
all_data = []
n_epochs = 1000
max_learn_data = 1000
game_num = 1000
game_strt = 0
use_ratio = 1.0
test_ratio = 0.15
n_additional_param = 15
n_boards = 3
kernel_size = 3
n_kernels = 32
n_residual = 2
leakyrelu_alpha = 0.01
n_train_data = int(game_num * (1.0 - test_ratio))
n_test_data = int(game_num * test_ratio)
train_board = np.zeros((n_train_data * 60, hw, hw, n_boards))
train_param = np.zeros((n_train_data * 60, n_additional_param))
train_policies = np.zeros((n_train_data * 60, hw2))
train_value = np.zeros(n_train_data * 60)
test_raw_board = []
test_board = []
test_param = []
test_policies = []
test_value = []
mean = []
std= []
'''
with open('param/mean.txt', 'r') as f:
mean = np.array([float(i) for i in f.read().splitlines()])
with open('param/std.txt', 'r') as f:
std = np.array([float(i) for i in f.read().splitlines()])
'''
#my_evaluate = subprocess.Popen('./evaluation.out'.split(), stdin=subprocess.PIPE, stdout=subprocess.PIPE)
def digit(n, r):
n = str(n)
l = len(n)
for i in range(r - l):
n = '0' + n
return n
def join_yx(y, x):
return y * hw + x
def calc_idx(i, j, rnd):
if rnd == 0:
return join_yx(i, j)
elif rnd == 1:
return join_yx(j, hw - 1 - i)
elif rnd == 2:
return join_yx(hw - 1 - i, hw - 1 - j)
else:
return join_yx(hw - 1 - j, i)
def collect_data(num, use_ratio):
global all_data
score = -1000
grids = []
with open('learn_data/' + digit(num, 7) + '.txt', 'r') as f:
point = float(f.readline())
score = 1.0 if point > 0.0 else -1.0 if point < 0.0 else 0.0
ln = int(f.readline())
for _ in range(ln):
s, y, x = f.readline().split()
y = int(y)
x = int(x)
if random() < use_ratio:
grids.append([score, s, y, x])
'''
ln = int(f.readline())
for _ in range(ln):
s, y, x = f.readline().split()
y = int(y)
x = int(x)
if random() < use_ratio:
grids.append([-score, s, y, x])
'''
for score, grid_str, y, x in grids:
all_data.append([grid_str, y * hw + x, score])
def reshape_data_train():
global train_board, train_param, train_policies, train_value, mean, std
tmp_data = []
print('calculating score & additional data')
for itr in trange(len(all_data)):
board, policy, score = all_data[itr]
policies = [0.0 for _ in range(hw2)]
policies[policy] = 1.0
'''
my_evaluate.stdin.write(board.encode('utf-8'))
my_evaluate.stdin.flush()
additional_data = my_evaluate.stdout.readline().decode().strip()
'''
additional_data = None
tmp_data.append([board, additional_data, policies, score])
#tmp_data.append([board, policies, score])
shuffle(tmp_data)
ln = len(tmp_data)
print('got', ln)
print('creating train data & labels')
train_idx = 0
for ii in trange(ln):
board, param, policies, score = tmp_data[ii]
#board, policies, score = tmp_data[ii]
stone_num = 0
grid_space0 = ''
grid_space0_rev = ''
grid_space1 = ''
grid_space1_rev = ''
grid_space_fill = ''
grid_space_vacant = ''
for i in range(hw):
for j in range(hw):
idx = i * hw + j
grid_space0 += '1 ' if board[idx] == '0' else '0 '
grid_space0_rev += '0 ' if board[idx] == '0' else '1 '
grid_space1 += '1 ' if board[idx] == '1' else '0 '
grid_space1_rev += '0 ' if board[idx] == '1' else '1 '
grid_space_vacant += '1 ' if board[idx] == '.' else '0 '
grid_space_fill += '0 ' if board[idx] == '.' else '1 '
stone_num += board[idx] != '.'
if stone_num < 10 or stone_num > 56:
continue
grid_flat = [float(i) for i in (grid_space0 + grid_space1 + grid_space_vacant).split()]
for i in range(hw):
for j in range(hw):
for k in range(n_boards):
train_board[train_idx][i][j][k] = grid_flat[k * hw2 + j * hw + i]
'''
for i, elem in zip(range(15), param.split()):
train_param[train_idx][i] = float(elem)
'''
for i in range(hw2):
train_policies[train_idx][i] = policies[i]
train_value[train_idx] = score
train_idx += 1
train_board = train_board[0:train_idx]
#train_param = train_param[0:train_idx]
train_policies = train_policies[0:train_idx]
train_value = train_value[0:train_idx]
#mean = train_param.mean(axis=0)
#std = train_param.std(axis=0)
#print('mean', mean)
#print('std', std)
#train_param = (train_param - mean) / std
'''
print(train_board[0])
print(train_param[0])
print(train_policies[0])
print(train_value[0])
'''
#print('train', train_board.shape, train_param.shape, train_policies.shape, train_value.shape)
def reshape_data_test():
global test_board, test_param, test_policies, test_value, test_raw_board
tmp_data = []
print('calculating score & additional data')
for itr in trange(len(all_data)):
board, policy, score = all_data[itr]
policies = [0.0 for _ in range(hw2)]
policies[policy] = 1.0
'''
my_evaluate.stdin.write(board.encode('utf-8'))
my_evaluate.stdin.flush()
additional_data = my_evaluate.stdout.readline().decode().strip()
'''
additional_data = None
tmp_data.append([board, additional_data, policies, score])
#tmp_data.append([board, policies, score])
shuffle(tmp_data)
ln = len(tmp_data)
print('got', ln)
print('creating test data & labels')
for ii in trange(ln):
board, param, policies, score = tmp_data[ii]
#board, policies, score = tmp_data[ii]
stone_num = 0
grid_space0 = ''
grid_space0_rev = ''
grid_space1 = ''
grid_space1_rev = ''
grid_space_fill = ''
grid_space_vacant = ''
for i in range(hw):
for j in range(hw):
idx = i * hw + j
grid_space0 += '1 ' if board[idx] == '0' else '0 '
grid_space0_rev += '0 ' if board[idx] == '0' else '1 '
grid_space1 += '1 ' if board[idx] == '1' else '0 '
grid_space1_rev += '0 ' if board[idx] == '1' else '1 '
grid_space_vacant += '1 ' if board[idx] == '.' else '0 '
grid_space_fill += '0 ' if board[idx] == '.' else '1 '
stone_num += board[idx] != '.'
if stone_num < 10 or stone_num > 56:
continue
if stone_num < 10 or stone_num > 56:
continue
test_raw_board.append(board)
#grid_flat = [float(i) for i in (grid_space0 + grid_space0_rev + grid_space1 + grid_space1_rev + grid_space_fill + grid_space_vacant).split()]
grid_flat = [float(i) for i in (grid_space0 + grid_space1 + grid_space_vacant).split()]
test_board.append([[[grid_flat[k * hw2 + j * hw + i] for k in range(n_boards)] for j in range(hw)] for i in range(hw)])
#test_param.append([float(i) for i in param.split()])
test_policies.append(policies)
test_value.append(score)
test_board = np.array(test_board)
#test_param = np.array(test_param)
test_policies = np.array(test_policies)
test_value = np.array(test_value)
#test_param = (test_param - mean) / std
'''
print(test_board[0])
print(test_param[0])
print(test_policies[0])
print(test_value[0])
'''
#print('test', test_board.shape, test_param.shape, test_policies.shape, test_value.shape)
'''
inputs = Input(shape=(hw, hw, n_boards,))
x = Conv2D(n_kernels, kernel_size, padding='same', use_bias=False)(inputs)
x = LeakyReLU(x)
for _ in range(n_residual):
sc = x
x = Conv2D(n_kernels, kernel_size, padding='same', use_bias=False)(x)
x = Add()([x, sc])
x = LeakyReLU(x)
x = GlobalAveragePooling2D()(x)
yp = Dense(64)(x)
yp = LeakyReLU(yp)
yp = Dense(hw2)(yp)
yp = Activation('softmax', name='policy')(yp)
yv = Dense(32)(x)
yv = LeakyReLU(yv)
yv = Dense(16)(yv)
yv = LeakyReLU(yv)
yv = Dense(1)(yv)
yv = Activation('tanh', name='value')(yv)
model = Model(inputs=inputs, outputs=[yp, yv])
'''
model = load_model('param/best.h5')
model.compile(loss=['categorical_crossentropy', 'mse'], optimizer='adam')
model.save('a.h5')
exit()
test_num = int(game_num * test_ratio)
train_num = game_num - test_num
print('loading data from files')
range_lst = list(range(max_learn_data))
shuffle(range_lst)
records = range_lst[:game_num]
for i in trange(game_strt, game_strt + train_num):
try:
collect_data(records[i], use_ratio)
except:
continue
reshape_data_train()
all_data = []
for i in trange(game_strt + train_num, game_strt + game_num):
try:
collect_data(records[i], use_ratio)
except:
continue
reshape_data_test()
#my_evaluate.kill()
model.compile(loss=['categorical_crossentropy', 'mse'], optimizer='adam')
early_stop = EarlyStopping(monitor='val_loss', patience=10)
history = model.fit(train_board, [train_policies, train_value], epochs=n_epochs, validation_data=(test_board, [test_policies, test_value]), callbacks=[early_stop])
model.save('param/model.h5')
for key in ['policy_loss', 'val_policy_loss']:
plt.plot(history.history[key], label=key)
plt.xlabel('epoch')
plt.ylabel('policy loss')
plt.legend(loc='best')
plt.savefig('graph/policy_loss.png')
plt.clf()
for key in ['value_loss', 'val_value_loss']:
plt.plot(history.history[key], label=key)
plt.xlabel('epoch')
plt.ylabel('value loss')
plt.legend(loc='best')
plt.savefig('graph/value_loss.png')
plt.clf()
| 33.275542 | 163 | 0.616208 |
803f9e3f10d501911693c45631e2bdf7b5aa8df2 | 75 | py | Python | stubs/3.2/docutils/parsers/rst/states.py | zyga/mypy | 5b7e222568cd20c31cde4e02adc9fd77d949197a | [
"PSF-2.0"
] | 1 | 2019-06-16T07:05:32.000Z | 2019-06-16T07:05:32.000Z | stubs/3.2/docutils/parsers/rst/states.py | zyga/mypy | 5b7e222568cd20c31cde4e02adc9fd77d949197a | [
"PSF-2.0"
] | null | null | null | stubs/3.2/docutils/parsers/rst/states.py | zyga/mypy | 5b7e222568cd20c31cde4e02adc9fd77d949197a | [
"PSF-2.0"
] | null | null | null | import typing
class Inliner:
def __init__(self) -> None:
pass
| 12.5 | 31 | 0.626667 |
d8c9f4be74baeeccd4f4cece950aab0dabc75ec7 | 666 | py | Python | pyqubo/utils/__init__.py | OpenJij/pyqubo | 47190d3391c83c1c84636ab8f8bff67c8f935dc0 | [
"Apache-2.0"
] | 1 | 2019-03-17T11:26:36.000Z | 2019-03-17T11:26:36.000Z | pyqubo/utils/__init__.py | OpenJij/pyqubo | 47190d3391c83c1c84636ab8f8bff67c8f935dc0 | [
"Apache-2.0"
] | null | null | null | pyqubo/utils/__init__.py | OpenJij/pyqubo | 47190d3391c83c1c84636ab8f8bff67c8f935dc0 | [
"Apache-2.0"
] | null | null | null | # Copyright 2018 Recruit Communications Co., Ltd.
#
# 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 pyqubo.utils.solver import *
from pyqubo.utils.asserts import *
| 39.176471 | 74 | 0.765766 |
7ce111c4d336088ee4f892ab35bc06d16d99a309 | 1,526 | py | Python | client/migrations/0001_initial.py | My-Garage/resourceideaapi | b872a6f15277989870572ba6e523c9dc378b7a24 | [
"MIT"
] | 1 | 2021-01-20T14:40:06.000Z | 2021-01-20T14:40:06.000Z | client/migrations/0001_initial.py | My-Garage/resourceideaapi | b872a6f15277989870572ba6e523c9dc378b7a24 | [
"MIT"
] | null | null | null | client/migrations/0001_initial.py | My-Garage/resourceideaapi | b872a6f15277989870572ba6e523c9dc378b7a24 | [
"MIT"
] | null | null | null | # Generated by Django 2.2.13 on 2020-07-17 22:42
from django.db import migrations, models
import django.db.models.deletion
import uuid
class Migration(migrations.Migration):
initial = True
dependencies = [
('client_industry', '__first__'),
('organization', '__first__'),
]
operations = [
migrations.CreateModel(
name='Client',
fields=[
('id', models.UUIDField(default=uuid.uuid4, editable=False, primary_key=True, serialize=False, unique=True)),
('created_at', models.DateTimeField(auto_now_add=True)),
('updated_at', models.DateTimeField(auto_now=True)),
('is_deleted', models.BooleanField(default=False)),
('deleted_at', models.DateTimeField(blank=True, null=True)),
('name', models.CharField(max_length=256)),
('name_slug', models.CharField(editable=False, max_length=256, unique=True)),
('address', models.CharField(max_length=256)),
('src_client_id', models.CharField(blank=True, max_length=40, null=True)),
('client_industry', models.ForeignKey(null=True, on_delete=django.db.models.deletion.SET_NULL, to='client_industry.ClientIndustry')),
('organization', models.ForeignKey(null=True, on_delete=django.db.models.deletion.SET_NULL, to='organization.Organization')),
],
options={
'db_table': 'client',
},
),
]
| 40.157895 | 149 | 0.607471 |
bf698c1f8d3313f54f4608c07e3a403b891ab56b | 66,217 | py | Python | cinder/tests/unit/volume/drivers/dell_emc/test_xtremio.py | alexisries/openstack-cinder | 7cc6e45c5ddb8bf771bdb01b867628e41761ae11 | [
"Apache-2.0"
] | 2 | 2019-05-24T14:13:50.000Z | 2019-05-24T14:21:13.000Z | cinder/tests/unit/volume/drivers/dell_emc/test_xtremio.py | vexata/cinder | 7b84c0842b685de7ee012acec40fb4064edde5e9 | [
"Apache-2.0"
] | 5 | 2019-08-14T06:46:03.000Z | 2021-12-13T20:01:25.000Z | cinder/tests/unit/volume/drivers/dell_emc/test_xtremio.py | vexata/cinder | 7b84c0842b685de7ee012acec40fb4064edde5e9 | [
"Apache-2.0"
] | 2 | 2020-03-15T01:24:15.000Z | 2020-07-22T20:34:26.000Z | # Copyright (c) 2018 Dell Inc. or its subsidiaries.
# 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 copy
import re
import time
import mock
import six
from cinder import context
from cinder import exception
from cinder.objects import volume_attachment
from cinder import test
from cinder.tests.unit.consistencygroup import fake_consistencygroup as fake_cg
from cinder.tests.unit import fake_constants as fake
from cinder.tests.unit import fake_snapshot
from cinder.tests.unit.fake_volume import fake_volume_obj
from cinder.tests.unit.fake_volume import fake_volume_type_obj
from cinder.volume.drivers.dell_emc import xtremio
typ2id = {'volumes': 'vol-id',
'snapshots': 'vol-id',
'initiators': 'initiator-id',
'initiator-groups': 'ig-id',
'lun-maps': 'mapping-id',
'consistency-groups': 'cg-id',
'consistency-group-volumes': 'cg-vol-id',
}
xms_init = {'xms': {1: {'version': '4.2.0',
'sw-version': '4.2.0-30'}},
'clusters': {1: {'name': 'brick1',
'sys-sw-version': "4.2.0-devel_ba23ee5381eeab73",
'ud-ssd-space': '8146708710',
'ud-ssd-space-in-use': '708710',
'vol-size': '29884416',
'chap-authentication-mode': 'disabled',
'chap-discovery-mode': 'disabled',
"index": 1,
},
},
'target-groups': {'Default': {"index": 1, "name": "Default"},
},
'iscsi-portals': {'10.205.68.5/16':
{"port-address":
"iqn.2008-05.com.xtremio:001e67939c34",
"ip-port": 3260,
"ip-addr": "10.205.68.5/16",
"name": "10.205.68.5/16",
"index": 1,
},
},
'targets': {'X1-SC2-target1': {'index': 1, "name": "X1-SC2-fc1",
"port-address":
"21:00:00:24:ff:57:b2:36",
'port-type': 'fc',
'port-state': 'up',
},
'X1-SC2-target2': {'index': 2, "name": "X1-SC2-fc2",
"port-address":
"21:00:00:24:ff:57:b2:55",
'port-type': 'fc',
'port-state': 'up',
}
},
'volumes': {},
'initiator-groups': {},
'initiators': {},
'lun-maps': {},
'consistency-groups': {},
'consistency-group-volumes': {},
}
xms_data = None
xms_filters = {
'eq': lambda x, y: x == y,
'ne': lambda x, y: x != y,
'gt': lambda x, y: x > y,
'ge': lambda x, y: x >= y,
'lt': lambda x, y: x < y,
'le': lambda x, y: x <= y,
}
def get_xms_obj_by_name(typ, name):
for item in xms_data[typ].values():
if 'name' in item and item['name'] == name:
return item
raise exception.NotFound()
def clean_xms_data():
global xms_data
xms_data = copy.deepcopy(xms_init)
def fix_data(data, object_type):
d = {}
for key, value in data.items():
if 'name' in key:
key = 'name'
d[key] = value
if object_type == 'lun-maps':
d['lun'] = 1
vol_idx = get_xms_obj_by_name('volumes', data['vol-id'])['index']
ig_idx = get_xms_obj_by_name('initiator-groups',
data['ig-id'])['index']
d['name'] = '_'.join([six.text_type(vol_idx),
six.text_type(ig_idx),
'1'])
d[typ2id[object_type]] = ["a91e8c81c2d14ae4865187ce4f866f8a",
d.get('name'),
len(xms_data.get(object_type, [])) + 1]
d['index'] = len(xms_data[object_type]) + 1
return d
def get_xms_obj_key(data):
for key in data.keys():
if 'name' in key:
return key
def get_obj(typ, name, idx):
if name:
return {"content": get_xms_obj_by_name(typ, name)}
elif idx:
if idx not in xms_data.get(typ, {}):
raise exception.NotFound()
return {"content": xms_data[typ][idx]}
def xms_request(object_type='volumes', method='GET', data=None,
name=None, idx=None, ver='v1'):
if object_type == 'snapshots':
object_type = 'volumes'
try:
res = xms_data[object_type]
except KeyError:
raise exception.VolumeDriverException
if method == 'GET':
if name or idx:
return get_obj(object_type, name, idx)
else:
if data and data.get('full') == 1:
filter_term = data.get('filter')
if not filter_term:
entities = list(res.values())
else:
field, oper, value = filter_term.split(':', 2)
comp = xms_filters[oper]
entities = [o for o in res.values()
if comp(o.get(field), value)]
return {object_type: entities}
else:
return {object_type: [{"href": "/%s/%d" % (object_type,
obj['index']),
"name": obj.get('name')}
for obj in res.values()]}
elif method == 'POST':
data = fix_data(data, object_type)
name_key = get_xms_obj_key(data)
try:
if name_key and get_xms_obj_by_name(object_type, data[name_key]):
raise (exception
.VolumeBackendAPIException
('Volume by this name already exists'))
except exception.NotFound:
pass
data['index'] = len(xms_data[object_type]) + 1
xms_data[object_type][data['index']] = data
# find the name key
if name_key:
data['name'] = data[name_key]
if object_type == 'lun-maps':
data['ig-name'] = data['ig-id']
return {"links": [{"href": "/%s/%d" %
(object_type, data[typ2id[object_type]][2])}]}
elif method == 'DELETE':
if object_type == 'consistency-group-volumes':
data = [cgv for cgv in
xms_data['consistency-group-volumes'].values()
if cgv['vol-id'] == data['vol-id']
and cgv['cg-id'] == data['cg-id']][0]
else:
data = get_obj(object_type, name, idx)['content']
if data:
del xms_data[object_type][data['index']]
else:
raise exception.NotFound()
elif method == 'PUT':
obj = get_obj(object_type, name, idx)['content']
data = fix_data(data, object_type)
del data['index']
obj.update(data)
def xms_bad_request(object_type='volumes', method='GET', data=None,
name=None, idx=None, ver='v1'):
if method == 'GET':
raise exception.NotFound()
elif method == 'POST':
raise exception.VolumeBackendAPIException('Failed to create ig')
def xms_failed_rename_snapshot_request(object_type='volumes',
method='GET', data=None,
name=None, idx=None, ver='v1'):
if method == 'POST':
xms_data['volumes'][27] = {}
return {
"links": [
{
"href": "https://host/api/json/v2/types/snapshots/27",
"rel": "self"}]}
elif method == 'PUT':
raise exception.VolumeBackendAPIException(data='Failed to delete')
elif method == 'DELETE':
del xms_data['volumes'][27]
class D(dict):
def update(self, *args, **kwargs):
self.__dict__.update(*args, **kwargs)
return dict.update(self, *args, **kwargs)
class CommonData(object):
context = context.RequestContext('admin', 'fake', True)
connector = {'ip': '10.0.0.2',
'initiator': 'iqn.1993-08.org.debian:01:222',
'wwpns': ["123456789012345", "123456789054321"],
'wwnns': ["223456789012345", "223456789054321"],
'host': 'fakehost',
}
test_volume_type = fake_volume_type_obj(
context=context
)
test_volume = fake_volume_obj(context,
volume_type = test_volume_type,
name='vol1',
volume_name='vol1',
display_name='vol1',
display_description='test volume',
size=1,
id='192eb39b-6c2f-420c-bae3-3cfd117f0001',
provider_auth=None,
project_id='project',
volume_type_id=None,
consistencygroup_id=
'192eb39b-6c2f-420c-bae3-3cfd117f0345',
)
test_snapshot = D()
test_snapshot.update({'name': 'snapshot1',
'size': 1,
'volume_size': 1,
'id': '192eb39b-6c2f-420c-bae3-3cfd117f0002',
'volume_name': 'vol-vol1',
'volume_id': '192eb39b-6c2f-420c-bae3-3cfd117f0001',
'project_id': 'project',
'consistencygroup_id':
'192eb39b-6c2f-420c-bae3-3cfd117f0345',
})
test_snapshot.__dict__.update(test_snapshot)
test_volume2 = {'name': 'vol2',
'size': 1,
'volume_name': 'vol2',
'id': '192eb39b-6c2f-420c-bae3-3cfd117f0004',
'provider_auth': None,
'project_id': 'project',
'display_name': 'vol2',
'display_description': 'test volume 2',
'volume_type_id': None,
'consistencygroup_id':
'192eb39b-6c2f-420c-bae3-3cfd117f0345',
}
test_clone = {'name': 'clone1',
'size': 1,
'volume_name': 'vol3',
'id': '192eb39b-6c2f-420c-bae3-3cfd117f0003',
'provider_auth': None,
'project_id': 'project',
'display_name': 'clone1',
'display_description': 'volume created from snapshot',
'volume_type_id': None,
'consistencygroup_id':
'192eb39b-6c2f-420c-bae3-3cfd117f0345',
}
unmanaged1 = {'id': 'unmanaged1',
'name': 'unmanaged1',
'size': 3,
}
group = {'id': '192eb39b-6c2f-420c-bae3-3cfd117f0345',
'name': 'cg1',
'status': 'OK',
}
cgsnapshot = {
'id': '192eb39b-6c2f-420c-bae3-3cfd117f9876',
'consistencygroup_id': group['id'],
'group_id': None, }
cgsnapshot_as_group_id = {
'id': '192eb39b-6c2f-420c-bae3-3cfd117f9876',
'consistencygroup_id': None,
'group_id': group['id'], }
test_volume_attachment = volume_attachment.VolumeAttachment(
id='2b06255d-f5f0-4520-a953-b029196add6b', volume_id=test_volume.id,
connector=connector)
class BaseXtremIODriverTestCase(test.TestCase):
def __init__(self, *args, **kwargs):
super(BaseXtremIODriverTestCase, self).__init__(*args, **kwargs)
self.config = mock.Mock(san_login='',
san_password='',
san_ip='',
xtremio_cluster_name='brick1',
xtremio_provisioning_factor=20.0,
max_over_subscription_ratio=20.0,
xtremio_volumes_per_glance_cache=100,
driver_ssl_cert_verify=True,
driver_ssl_cert_path='/test/path/root_ca.crt',
xtremio_array_busy_retry_count=5,
xtremio_array_busy_retry_interval=5,
xtremio_clean_unused_ig=False)
def safe_get(key):
return getattr(self.config, key)
self.config.safe_get = safe_get
def setUp(self):
super(BaseXtremIODriverTestCase, self).setUp()
clean_xms_data()
self.driver = xtremio.XtremIOISCSIDriver(configuration=self.config)
self.driver.client = xtremio.XtremIOClient42(self.config,
self.config
.xtremio_cluster_name)
self.data = CommonData()
@mock.patch('cinder.volume.drivers.dell_emc.xtremio.XtremIOClient.req')
class XtremIODriverISCSITestCase(BaseXtremIODriverTestCase):
# ##### SetUp Check #####
def test_check_for_setup_error(self, req):
req.side_effect = xms_request
self.driver.check_for_setup_error()
self.assertEqual(self.driver.client.__class__.__name__,
'XtremIOClient42')
def test_fail_check_for_setup_error(self, req):
req.side_effect = xms_request
clusters = xms_data.pop('clusters')
self.assertRaises(exception.VolumeDriverException,
self.driver.check_for_setup_error)
xms_data['clusters'] = clusters
def test_check_for_setup_error_ver4(self, req):
req.side_effect = xms_request
xms_data['xms'][1]['sw-version'] = '4.0.10-34.hotfix1'
self.driver.check_for_setup_error()
self.assertEqual(self.driver.client.__class__.__name__,
'XtremIOClient4')
def test_fail_check_for_array_version(self, req):
req.side_effect = xms_request
cluster = xms_data['clusters'][1]
ver = cluster['sys-sw-version']
cluster['sys-sw-version'] = '2.0.0-test'
self.assertRaises(exception.VolumeBackendAPIException,
self.driver.check_for_setup_error)
cluster['sys-sw-version'] = ver
def test_client4_uses_v2(self, req):
def base_req(*args, **kwargs):
self.assertIn('v2', args)
req.side_effect = base_req
self.driver.client.req('volumes')
def test_get_stats(self, req):
req.side_effect = xms_request
stats = self.driver.get_volume_stats(True)
self.assertEqual(self.driver.backend_name,
stats['volume_backend_name'])
# ##### Volumes #####
def test_create_volume_with_cg(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
def test_extend_volume(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
self.driver.extend_volume(self.data.test_volume, 5)
def test_fail_extend_volume(self, req):
req.side_effect = xms_request
self.assertRaises(exception.VolumeDriverException,
self.driver.extend_volume, self.data.test_volume, 5)
def test_delete_volume(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
self.driver.delete_volume(self.data.test_volume)
def test_duplicate_volume(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
self.assertRaises(exception.VolumeBackendAPIException,
self.driver.create_volume, self.data.test_volume)
# ##### Snapshots #####
def test_create_snapshot(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
self.driver.create_snapshot(self.data.test_snapshot)
self.assertEqual(self.data.test_snapshot['id'],
xms_data['volumes'][2]['name'])
def test_create_delete_snapshot(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
self.driver.create_snapshot(self.data.test_snapshot)
self.assertEqual(self.data.test_snapshot['id'],
xms_data['volumes'][2]['name'])
self.driver.delete_snapshot(self.data.test_snapshot)
def test_failed_rename_snapshot(self, req):
req.side_effect = xms_failed_rename_snapshot_request
self.assertRaises(exception.VolumeBackendAPIException,
self.driver.create_snapshot,
self.data.test_snapshot)
self.assertEqual(0, len(xms_data['volumes']))
def test_volume_from_snapshot(self, req):
req.side_effect = xms_request
xms_data['volumes'] = {}
self.driver.create_volume(self.data.test_volume)
self.driver.create_snapshot(self.data.test_snapshot)
self.driver.create_volume_from_snapshot(self.data.test_volume2,
self.data.test_snapshot)
def test_volume_from_snapshot_and_resize(self, req):
req.side_effect = xms_request
xms_data['volumes'] = {}
self.driver.create_volume(self.data.test_volume)
clone_volume = self.data.test_clone.copy()
clone_volume['size'] = 2
self.driver.create_snapshot(self.data.test_snapshot)
with mock.patch.object(self.driver,
'extend_volume') as extend:
self.driver.create_volume_from_snapshot(clone_volume,
self.data.test_snapshot)
extend.assert_called_once_with(clone_volume, clone_volume['size'])
def test_volume_from_snapshot_and_resize_fail(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
vol = xms_data['volumes'][1]
def failed_extend(obj_type='volumes', method='GET', data=None,
*args, **kwargs):
if method == 'GET':
return {'content': vol}
elif method == 'POST':
return {'links': [{'href': 'volume/2'}]}
elif method == 'PUT':
if 'name' in data:
return
raise exception.VolumeBackendAPIException('Failed Clone')
self.driver.create_snapshot(self.data.test_snapshot)
req.side_effect = failed_extend
self.driver.db = mock.Mock()
(self.driver.db.
image_volume_cache_get_by_volume_id.return_value) = mock.MagicMock()
clone = self.data.test_clone.copy()
clone['size'] = 2
with mock.patch.object(self.driver,
'delete_volume') as delete:
self.assertRaises(exception.VolumeBackendAPIException,
self.driver.create_volume_from_snapshot,
clone,
self.data.test_snapshot)
self.assertTrue(delete.called)
# ##### Clone Volume #####
def test_clone_volume(self, req):
req.side_effect = xms_request
self.driver.db = mock.Mock()
(self.driver.db.
image_volume_cache_get_by_volume_id.return_value) = mock.MagicMock()
self.driver.create_volume(self.data.test_volume)
xms_data['volumes'][1]['num-of-dest-snaps'] = 50
self.driver.create_cloned_volume(self.data.test_clone,
self.data.test_volume)
def test_clone_volume_exceed_conf_limit(self, req):
req.side_effect = xms_request
self.driver.db = mock.Mock()
(self.driver.db.
image_volume_cache_get_by_volume_id.return_value) = mock.MagicMock()
self.driver.create_volume(self.data.test_volume)
xms_data['volumes'][1]['num-of-dest-snaps'] = 200
self.assertRaises(exception.CinderException,
self.driver.create_cloned_volume,
self.data.test_clone,
self.data.test_volume)
@mock.patch.object(xtremio.XtremIOClient4, 'create_snapshot')
def test_clone_volume_exceed_array_limit(self, create_snap, req):
create_snap.side_effect = exception.XtremIOSnapshotsLimitExceeded()
req.side_effect = xms_request
self.driver.db = mock.Mock()
(self.driver.db.
image_volume_cache_get_by_volume_id.return_value) = mock.MagicMock()
self.driver.create_volume(self.data.test_volume)
xms_data['volumes'][1]['num-of-dest-snaps'] = 50
self.assertRaises(exception.CinderException,
self.driver.create_cloned_volume,
self.data.test_clone,
self.data.test_volume)
def test_clone_volume_too_many_snaps(self, req):
req.side_effect = xms_request
response = mock.MagicMock()
response.status_code = 400
response.json.return_value = {
"message": "too_many_snapshots_per_vol",
"error_code": 400
}
self.assertRaises(exception.XtremIOSnapshotsLimitExceeded,
self.driver.client.handle_errors,
response, '', '')
def test_clone_volume_too_many_objs(self, req):
req.side_effect = xms_request
response = mock.MagicMock()
response.status_code = 400
response.json.return_value = {
"message": "too_many_objs",
"error_code": 400
}
self.assertRaises(exception.XtremIOSnapshotsLimitExceeded,
self.driver.client.handle_errors,
response, '', '')
def test_update_migrated_volume(self, req):
original = self.data.test_volume
new = self.data.test_volume2
update = (self.driver.
update_migrated_volume({},
original, new, 'available'))
req.assert_called_once_with('volumes', 'PUT',
{'name': original['id']}, new['id'],
None, 'v2')
self.assertEqual({'_name_id': None,
'provider_location': None}, update)
def test_update_migrated_volume_failed_rename(self, req):
req.side_effect = exception.VolumeBackendAPIException(
data='failed rename')
original = self.data.test_volume
new = copy.deepcopy(self.data.test_volume2)
fake_provider = '__provider'
new['provider_location'] = fake_provider
new['_name_id'] = None
update = (self.driver.
update_migrated_volume({},
original, new, 'available'))
self.assertEqual({'_name_id': new['id'],
'provider_location': fake_provider},
update)
def test_clone_volume_and_resize(self, req):
req.side_effect = xms_request
self.driver.db = mock.Mock()
(self.driver.db.
image_volume_cache_get_by_volume_id.return_value) = mock.MagicMock()
self.driver.create_volume(self.data.test_volume)
vol = xms_data['volumes'][1]
vol['num-of-dest-snaps'] = 0
clone = self.data.test_clone.copy()
clone['size'] = 2
with mock.patch.object(self.driver,
'extend_volume') as extend:
self.driver.create_cloned_volume(clone, self.data.test_volume)
extend.assert_called_once_with(clone, clone['size'])
def test_clone_volume_and_resize_fail(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
vol = xms_data['volumes'][1]
def failed_extend(obj_type='volumes', method='GET', data=None,
*args, **kwargs):
if method == 'GET':
return {'content': vol}
elif method == 'POST':
return {'links': [{'href': 'volume/2'}]}
elif method == 'PUT':
if 'name' in data:
return
raise exception.VolumeBackendAPIException('Failed Clone')
req.side_effect = failed_extend
self.driver.db = mock.Mock()
(self.driver.db.
image_volume_cache_get_by_volume_id.return_value) = mock.MagicMock()
vol['num-of-dest-snaps'] = 0
clone = self.data.test_clone.copy()
clone['size'] = 2
with mock.patch.object(self.driver,
'delete_volume') as delete:
self.assertRaises(exception.VolumeBackendAPIException,
self.driver.create_cloned_volume,
clone,
self.data.test_volume)
self.assertTrue(delete.called)
# ##### Connection #####
def test_no_portals_configured(self, req):
req.side_effect = xms_request
portals = xms_data['iscsi-portals'].copy()
xms_data['iscsi-portals'].clear()
lunmap = {'lun': 4}
self.assertRaises(exception.VolumeDriverException,
self.driver._get_iscsi_properties, lunmap)
xms_data['iscsi-portals'] = portals
def test_initialize_connection(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
self.driver.create_volume(self.data.test_volume2)
map_data = self.driver.initialize_connection(self.data.test_volume,
self.data.connector)
self.assertEqual(1, map_data['data']['target_lun'])
def test_initialize_connection_existing_ig(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
self.driver.create_volume(self.data.test_volume2)
self.driver.initialize_connection(self.data.test_volume,
self.data.connector)
i1 = xms_data['initiators'][1]
i1['ig-id'] = ['', i1['ig-id'], 1]
i1['chap-authentication-initiator-password'] = 'chap_password1'
i1['chap-discovery-initiator-password'] = 'chap_password2'
self.driver.initialize_connection(self.data.test_volume2,
self.data.connector)
def test_terminate_connection(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
self.driver.initialize_connection(self.data.test_volume,
self.data.connector)
i1 = xms_data['initiators'][1]
i1['ig-id'] = ['', i1['ig-id'], 1]
self.driver.terminate_connection(self.data.test_volume,
self.data.connector)
self.assertEqual(1, len(xms_data['initiator-groups']))
def test_terminate_connection_clean_ig(self, req):
self.driver.clean_ig = True
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
self.driver.initialize_connection(self.data.test_volume,
self.data.connector)
i1 = xms_data['initiators'][1]
i1['ig-id'] = ['', i1['ig-id'], 1]
xms_data['initiator-groups'][1]['num-of-vols'] = 0
# lun mapping list is a list of triplets (IG OID, TG OID, lun number)
self.driver.terminate_connection(self.data.test_volume,
self.data.connector)
self.assertEqual(0, len(xms_data['initiator-groups']))
def test_terminate_connection_fail_on_bad_volume(self, req):
req.side_effect = xms_request
self.assertRaises(exception.NotFound,
self.driver.terminate_connection,
self.data.test_volume,
self.data.connector)
def test_get_ig_indexes_from_initiators_called_once(self, req):
req.side_effect = xms_request
volume1 = copy.deepcopy(self.data.test_volume)
volume1.volume_attachment.objects = [self.data.test_volume_attachment]
self.driver.create_volume(volume1)
map_data = self.driver.initialize_connection(self.data.test_volume,
self.data.connector)
i1 = xms_data['initiators'][1]
i1['ig-id'] = ['', i1['ig-id'], 1]
self.assertEqual(1, map_data['data']['target_lun'])
with mock.patch.object(self.driver,
'_get_ig_indexes_from_initiators') as get_idx:
get_idx.return_value = [1]
self.driver.terminate_connection(self.data.test_volume,
self.data.connector)
get_idx.assert_called_once_with(self.data.connector)
def test_initialize_connection_after_enabling_chap(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
self.driver.create_volume(self.data.test_volume2)
map_data = self.driver.initialize_connection(self.data.test_volume,
self.data.connector)
self.assertIsNone(map_data['data'].get('access_mode'))
c1 = xms_data['clusters'][1]
c1['chap-authentication-mode'] = 'initiator'
c1['chap-discovery-mode'] = 'initiator'
i1 = xms_data['initiators'][1]
i1['ig-id'] = ['', i1['ig-id'], 1]
i1['chap-authentication-initiator-password'] = 'chap_password1'
i1['chap-discovery-initiator-password'] = 'chap_password2'
map_data = self.driver.initialize_connection(self.data.test_volume2,
self.data.connector)
self.assertEqual('chap_password1', map_data['data']['auth_password'])
self.assertEqual('chap_password2',
map_data['data']['discovery_auth_password'])
def test_initialize_connection_after_disabling_chap(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
self.driver.create_volume(self.data.test_volume2)
c1 = xms_data['clusters'][1]
c1['chap-authentication-mode'] = 'initiator'
c1['chap-discovery-mode'] = 'initiator'
self.driver.initialize_connection(self.data.test_volume,
self.data.connector)
i1 = xms_data['initiators'][1]
i1['ig-id'] = ['', i1['ig-id'], 1]
i1['chap-authentication-initiator-password'] = 'chap_password1'
i1['chap-discovery-initiator-password'] = 'chap_password2'
i1['chap-authentication-initiator-password'] = None
i1['chap-discovery-initiator-password'] = None
self.driver.initialize_connection(self.data.test_volume2,
self.data.connector)
@mock.patch('oslo_utils.strutils.mask_dict_password')
def test_initialize_connection_masks_password(self, mask_dict, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
self.driver.initialize_connection(self.data.test_volume,
self.data.connector)
self.assertTrue(mask_dict.called)
def test_add_auth(self, req):
req.side_effect = xms_request
data = {}
self.driver._add_auth(data, True, True)
self.assertIn('initiator-discovery-user-name', data,
'Missing discovery user in data')
self.assertIn('initiator-discovery-password', data,
'Missing discovery password in data')
def test_initialize_connection_bad_ig(self, req):
req.side_effect = xms_bad_request
self.assertRaises(exception.VolumeBackendAPIException,
self.driver.initialize_connection,
self.data.test_volume,
self.data.connector)
self.driver.delete_volume(self.data.test_volume)
# ##### Manage Volumes #####
def test_manage_volume(self, req):
req.side_effect = xms_request
xms_data['volumes'] = {1: {'name': 'unmanaged1',
'index': 1,
'vol-size': '3',
},
}
ref_vol = {"source-name": "unmanaged1"}
self.driver.manage_existing(self.data.test_volume, ref_vol)
def test_failed_manage_volume(self, req):
req.side_effect = xms_request
xms_data['volumes'] = {1: {'name': 'unmanaged1',
'index': 1,
'vol-size': '3',
},
}
invalid_ref = {"source-name": "invalid"}
self.assertRaises(exception.ManageExistingInvalidReference,
self.driver.manage_existing,
self.data.test_volume, invalid_ref)
def test_get_manage_volume_size(self, req):
req.side_effect = xms_request
xms_data['volumes'] = {1: {'name': 'unmanaged1',
'index': 1,
'vol-size': '1000000',
},
}
ref_vol = {"source-name": "unmanaged1"}
size = self.driver.manage_existing_get_size(self.data.test_volume,
ref_vol)
self.assertEqual(1, size)
def test_manage_volume_size_invalid_input(self, req):
self.assertRaises(exception.ManageExistingInvalidReference,
self.driver.manage_existing_get_size,
self.data.test_volume, {})
def test_failed_manage_volume_size(self, req):
req.side_effect = xms_request
xms_data['volumes'] = {1: {'name': 'unmanaged1',
'index': 1,
'vol-size': '3',
},
}
invalid_ref = {"source-name": "invalid"}
self.assertRaises(exception.ManageExistingInvalidReference,
self.driver.manage_existing_get_size,
self.data.test_volume, invalid_ref)
def test_unmanage_volume(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
self.driver.unmanage(self.data.test_volume)
def test_failed_unmanage_volume(self, req):
req.side_effect = xms_request
self.assertRaises(exception.VolumeNotFound, self.driver.unmanage,
self.data.test_volume2)
def test_manage_snapshot(self, req):
req.side_effect = xms_request
vol_uid = self.data.test_snapshot.volume_id
xms_data['volumes'] = {1: {'name': vol_uid,
'index': 1,
'vol-size': '3',
},
2: {'name': 'unmanaged',
'index': 2,
'ancestor-vol-id': ['', vol_uid, 1],
'vol-size': '3'}
}
ref_vol = {"source-name": "unmanaged"}
self.driver.manage_existing_snapshot(self.data.test_snapshot, ref_vol)
def test_get_manage_snapshot_size(self, req):
req.side_effect = xms_request
vol_uid = self.data.test_snapshot.volume_id
xms_data['volumes'] = {1: {'name': vol_uid,
'index': 1,
'vol-size': '3',
},
2: {'name': 'unmanaged',
'index': 2,
'ancestor-vol-id': ['', vol_uid, 1],
'vol-size': '3'}
}
ref_vol = {"source-name": "unmanaged"}
self.driver.manage_existing_snapshot_get_size(self.data.test_snapshot,
ref_vol)
def test_manage_snapshot_invalid_snapshot(self, req):
req.side_effect = xms_request
xms_data['volumes'] = {1: {'name': 'unmanaged1',
'index': 1,
'vol-size': '3',
'ancestor-vol-id': []}
}
ref_vol = {"source-name": "unmanaged1"}
self.assertRaises(exception.ManageExistingInvalidReference,
self.driver.manage_existing_snapshot,
self.data.test_snapshot, ref_vol)
def test_unmanage_snapshot(self, req):
req.side_effect = xms_request
vol_uid = self.data.test_snapshot.volume_id
xms_data['volumes'] = {1: {'name': vol_uid,
'index': 1,
'vol-size': '3',
},
2: {'name': 'unmanaged',
'index': 2,
'ancestor-vol-id': ['', vol_uid, 1],
'vol-size': '3'}
}
ref_vol = {"source-name": "unmanaged"}
self.driver.manage_existing_snapshot(self.data.test_snapshot, ref_vol)
self.driver.unmanage_snapshot(self.data.test_snapshot)
# ##### Consistancy Groups #####
@mock.patch('cinder.objects.snapshot.SnapshotList.get_all_for_cgsnapshot')
def test_cg_create(self, get_all_for_cgsnapshot, req):
req.side_effect = xms_request
d = self.data
snapshot_obj = fake_snapshot.fake_snapshot_obj(d.context)
snapshot_obj.consistencygroup_id = d.group['id']
get_all_for_cgsnapshot.return_value = [snapshot_obj]
self.driver.create_consistencygroup(d.context, d.group)
self.assertEqual(1, len(xms_data['consistency-groups']))
@mock.patch('cinder.objects.snapshot.SnapshotList.get_all_for_cgsnapshot')
def test_cg_update(self, get_all_for_cgsnapshot, req):
req.side_effect = xms_request
d = self.data
snapshot_obj = fake_snapshot.fake_snapshot_obj(d.context)
snapshot_obj.consistencygroup_id = d.group['id']
get_all_for_cgsnapshot.return_value = [snapshot_obj]
self.driver.create_consistencygroup(d.context, d.group)
self.driver.update_consistencygroup(d.context, d.group,
add_volumes=[d.test_volume,
d.test_volume2])
self.assertEqual(2, len(xms_data['consistency-group-volumes']))
self.driver.update_consistencygroup(d.context, d.group,
remove_volumes=[d.test_volume2])
self.assertEqual(1, len(xms_data['consistency-group-volumes']))
@mock.patch('cinder.objects.snapshot.SnapshotList.get_all_for_cgsnapshot')
def test_create_cg(self, get_all_for_cgsnapshot, req):
req.side_effect = xms_request
d = self.data
snapshot_obj = fake_snapshot.fake_snapshot_obj(d.context)
snapshot_obj.consistencygroup_id = d.group['id']
get_all_for_cgsnapshot.return_value = [snapshot_obj]
self.driver.create_consistencygroup(d.context, d.group)
self.driver.update_consistencygroup(d.context, d.group,
add_volumes=[d.test_volume,
d.test_volume2])
self.driver.db = mock.Mock()
(self.driver.db.
volume_get_all_by_group.return_value) = [mock.MagicMock()]
res = self.driver.create_cgsnapshot(d.context, d.cgsnapshot,
[snapshot_obj])
self.assertEqual((None, None), res)
@mock.patch('cinder.objects.snapshot.SnapshotList.get_all_for_cgsnapshot')
def test_cg_delete(self, get_all_for_cgsnapshot, req):
req.side_effect = xms_request
d = self.data
snapshot_obj = fake_snapshot.fake_snapshot_obj(d.context)
snapshot_obj.consistencygroup_id = d.group['id']
get_all_for_cgsnapshot.return_value = [snapshot_obj]
self.driver.create_consistencygroup(d.context, d.group)
self.driver.update_consistencygroup(d.context, d.group,
add_volumes=[d.test_volume,
d.test_volume2])
self.driver.db = mock.Mock()
self.driver.create_cgsnapshot(d.context, d.cgsnapshot, [snapshot_obj])
self.driver.delete_consistencygroup(d.context, d.group, [])
def test_cg_delete_with_volume(self, req):
req.side_effect = xms_request
d = self.data
self.driver.create_consistencygroup(d.context, d.group)
self.driver.create_volume(d.test_volume)
self.driver.update_consistencygroup(d.context, d.group,
add_volumes=[d.test_volume])
self.driver.db = mock.Mock()
results, volumes = \
self.driver.delete_consistencygroup(d.context,
d.group,
[d.test_volume])
self.assertTrue(all(volume['status'] == 'deleted' for volume in
volumes))
@mock.patch('cinder.objects.snapshot.SnapshotList.get_all_for_cgsnapshot')
def test_cg_snapshot(self, get_all_for_cgsnapshot, req):
req.side_effect = xms_request
d = self.data
snapshot_obj = fake_snapshot.fake_snapshot_obj(d.context)
snapshot_obj.consistencygroup_id = d.group['id']
get_all_for_cgsnapshot.return_value = [snapshot_obj]
self.driver.create_consistencygroup(d.context, d.group)
self.driver.update_consistencygroup(d.context, d.group,
add_volumes=[d.test_volume,
d.test_volume2])
snapset_name = self.driver._get_cgsnap_name(d.cgsnapshot)
self.assertEqual(snapset_name,
'192eb39b6c2f420cbae33cfd117f0345192eb39b6c2f420cbae'
'33cfd117f9876')
snapset1 = {'ancestor-vol-id': ['', d.test_volume['id'], 2],
'consistencygroup_id': d.group['id'],
'name': snapset_name,
'index': 1}
xms_data['snapshot-sets'] = {snapset_name: snapset1, 1: snapset1}
res = self.driver.delete_cgsnapshot(d.context, d.cgsnapshot,
[snapshot_obj])
self.assertEqual((None, None), res)
def test_delete_cgsnapshot(self, req):
d = self.data
snapshot_obj = fake_snapshot.fake_snapshot_obj(d.context)
snapshot_obj.consistencygroup_id = d.group['id']
self.driver.delete_cgsnapshot(d.context, d.cgsnapshot,
[snapshot_obj])
req.assert_called_once_with('snapshot-sets', 'DELETE', None,
'192eb39b6c2f420cbae33cfd117f0345192eb39'
'b6c2f420cbae33cfd117f9876', None, 'v2')
@mock.patch('cinder.objects.snapshot.SnapshotList.get_all_for_cgsnapshot')
def test_cg_from_src_snapshot(self, get_all_for_cgsnapshot, req):
req.side_effect = xms_request
d = self.data
snapshot_obj = fake_snapshot.fake_snapshot_obj(d.context)
snapshot_obj.consistencygroup_id = d.group['id']
snapshot_obj.volume_id = d.test_volume['id']
get_all_for_cgsnapshot.return_value = [snapshot_obj]
self.driver.create_consistencygroup(d.context, d.group)
self.driver.create_volume(d.test_volume)
self.driver.create_cgsnapshot(d.context, d.cgsnapshot, [])
xms_data['volumes'][2]['ancestor-vol-id'] = (xms_data['volumes'][1]
['vol-id'])
snapset_name = self.driver._get_cgsnap_name(d.cgsnapshot)
snapset1 = {'vol-list': [xms_data['volumes'][2]['vol-id']],
'name': snapset_name,
'index': 1}
xms_data['snapshot-sets'] = {snapset_name: snapset1, 1: snapset1}
cg_obj = fake_cg.fake_consistencyobject_obj(d.context)
new_vol1 = fake_volume_obj(d.context)
snapshot1 = (fake_snapshot
.fake_snapshot_obj
(d.context, volume_id=d.test_volume['id']))
res = self.driver.create_consistencygroup_from_src(d.context, cg_obj,
[new_vol1],
d.cgsnapshot,
[snapshot1])
self.assertEqual((None, None), res)
@mock.patch('cinder.objects.snapshot.SnapshotList.get_all_for_cgsnapshot')
def test_cg_from_src_cg(self, get_all_for_cgsnapshot, req):
req.side_effect = xms_request
d = self.data
snapshot_obj = fake_snapshot.fake_snapshot_obj(d.context)
snapshot_obj.consistencygroup_id = d.group['id']
snapshot_obj.volume_id = d.test_volume['id']
get_all_for_cgsnapshot.return_value = [snapshot_obj]
self.driver.create_consistencygroup(d.context, d.group)
self.driver.create_volume(d.test_volume)
self.driver.create_cgsnapshot(d.context, d.cgsnapshot, [])
xms_data['volumes'][2]['ancestor-vol-id'] = (xms_data['volumes'][1]
['vol-id'])
snapset_name = self.driver._get_cgsnap_name(d.cgsnapshot)
snapset1 = {'vol-list': [xms_data['volumes'][2]['vol-id']],
'name': snapset_name,
'index': 1}
xms_data['snapshot-sets'] = {snapset_name: snapset1, 1: snapset1}
cg_obj = fake_cg.fake_consistencyobject_obj(d.context)
new_vol1 = fake_volume_obj(d.context)
new_cg_obj = fake_cg.fake_consistencyobject_obj(
d.context, id=fake.CONSISTENCY_GROUP2_ID)
snapset2_name = new_cg_obj.id
new_vol1.id = '192eb39b-6c2f-420c-bae3-3cfd117f0001'
new_vol2 = fake_volume_obj(d.context)
snapset2 = {'vol-list': [xms_data['volumes'][2]['vol-id']],
'name': snapset2_name,
'index': 1}
xms_data['snapshot-sets'].update({5: snapset2,
snapset2_name: snapset2})
self.driver.create_consistencygroup_from_src(d.context, new_cg_obj,
[new_vol2],
None, None,
cg_obj, [new_vol1])
@mock.patch('cinder.objects.snapshot.SnapshotList.get_all_for_cgsnapshot')
def test_invalid_cg_from_src_input(self, get_all_for_cgsnapshot, req):
req.side_effect = xms_request
d = self.data
self.assertRaises(exception.InvalidInput,
self.driver.create_consistencygroup_from_src,
d.context, d.group, [], None, None, None, None)
# #### Groups ####
def test_group_create(self, req):
"""Test group create."""
req.side_effect = xms_request
d = self.data
self.driver.create_group(d.context, d.group)
self.assertEqual(1, len(xms_data['consistency-groups']))
def test_group_update(self, req):
"""Test group update."""
req.side_effect = xms_request
d = self.data
self.driver.create_consistencygroup(d.context, d.group)
self.driver.update_consistencygroup(d.context, d.group,
add_volumes=[d.test_volume,
d.test_volume2])
self.assertEqual(2, len(xms_data['consistency-group-volumes']))
self.driver.update_group(d.context, d.group,
remove_volumes=[d.test_volume2])
self.assertEqual(1, len(xms_data['consistency-group-volumes']))
def test_create_group_snapshot(self, req):
"""Test create group snapshot."""
req.side_effect = xms_request
d = self.data
snapshot_obj = fake_snapshot.fake_snapshot_obj(d.context)
snapshot_obj.consistencygroup_id = d.group['id']
self.driver.create_group(d.context, d.group)
self.driver.update_group(d.context, d.group,
add_volumes=[d.test_volume,
d.test_volume2])
res = self.driver.create_group_snapshot(d.context, d.cgsnapshot,
[snapshot_obj])
self.assertEqual((None, None), res)
def test_group_delete(self, req):
""""Test delete group."""
req.side_effect = xms_request
d = self.data
snapshot_obj = fake_snapshot.fake_snapshot_obj(d.context)
snapshot_obj.consistencygroup_id = d.group['id']
self.driver.create_group(d.context, d.group)
self.driver.update_group(d.context, d.group,
add_volumes=[d.test_volume,
d.test_volume2])
self.driver.db = mock.Mock()
(self.driver.db.
volume_get_all_by_group.return_value) = [mock.MagicMock()]
self.driver.create_group_snapshot(d.context, d.cgsnapshot,
[snapshot_obj])
self.driver.delete_group(d.context, d.group, [])
def test_group_delete_with_volume(self, req):
req.side_effect = xms_request
d = self.data
self.driver.create_consistencygroup(d.context, d.group)
self.driver.create_volume(d.test_volume)
self.driver.update_consistencygroup(d.context, d.group,
add_volumes=[d.test_volume])
self.driver.db = mock.Mock()
results, volumes = \
self.driver.delete_group(d.context, d.group, [d.test_volume])
self.assertTrue(all(volume['status'] == 'deleted' for volume in
volumes))
def test_group_snapshot(self, req):
"""test group snapshot."""
req.side_effect = xms_request
d = self.data
snapshot_obj = fake_snapshot.fake_snapshot_obj(d.context)
snapshot_obj.consistencygroup_id = d.group['id']
self.driver.create_group(d.context, d.group)
self.driver.update_group(d.context, d.group,
add_volumes=[d.test_volume,
d.test_volume2])
snapset_name = self.driver._get_cgsnap_name(d.cgsnapshot)
self.assertEqual(snapset_name,
'192eb39b6c2f420cbae33cfd117f0345192eb39b6c2f420cbae'
'33cfd117f9876')
snapset1 = {'ancestor-vol-id': ['', d.test_volume['id'], 2],
'consistencygroup_id': d.group['id'],
'name': snapset_name,
'index': 1}
xms_data['snapshot-sets'] = {snapset_name: snapset1, 1: snapset1}
res = self.driver.delete_group_snapshot(d.context, d.cgsnapshot,
[snapshot_obj])
self.assertEqual((None, None), res)
def test_group_snapshot_with_generic_group(self, req):
"""test group snapshot shot with generic group ."""
req.side_effect = xms_request
d = self.data
snapshot_obj = fake_snapshot.fake_snapshot_obj(d.context)
snapshot_obj.consistencygroup_id = d.group['id']
self.driver.create_group(d.context, d.group)
self.driver.update_group(d.context, d.group,
add_volumes=[d.test_volume,
d.test_volume2])
snapset_name = self.driver._get_cgsnap_name(d.cgsnapshot_as_group_id)
self.assertEqual(snapset_name,
'192eb39b6c2f420cbae33cfd117f0345192eb39b6c2f420cbae'
'33cfd117f9876')
snapset1 = {'ancestor-vol-id': ['', d.test_volume['id'], 2],
'consistencygroup_id': d.group['id'],
'name': snapset_name,
'index': 1}
xms_data['snapshot-sets'] = {snapset_name: snapset1, 1: snapset1}
res = self.driver.delete_group_snapshot(d.context, d.cgsnapshot,
[snapshot_obj])
self.assertEqual((None, None), res)
def test_delete_group_snapshot(self, req):
"""test delete group snapshot."""
d = self.data
snapshot_obj = fake_snapshot.fake_snapshot_obj(d.context)
snapshot_obj.consistencygroup_id = d.group['id']
self.driver.delete_group_snapshot(d.context, d.cgsnapshot,
[snapshot_obj])
req.assert_called_once_with('snapshot-sets', 'DELETE', None,
'192eb39b6c2f420cbae33cfd117f0345192eb39'
'b6c2f420cbae33cfd117f9876', None, 'v2')
def test_delete_group_snapshot_with_generic_group(self, req):
"""test delete group snapshot."""
d = self.data
snapshot_obj = fake_snapshot.fake_snapshot_obj(d.context)
snapshot_obj.consistencygroup_id = d.group['id']
self.driver.delete_group_snapshot(d.context, d.cgsnapshot_as_group_id,
[snapshot_obj])
req.assert_called_once_with('snapshot-sets', 'DELETE', None,
'192eb39b6c2f420cbae33cfd117f0345192eb39'
'b6c2f420cbae33cfd117f9876', None, 'v2')
def test_group_from_src_snapshot(self, req):
"""test group from source snapshot."""
req.side_effect = xms_request
d = self.data
self.driver.create_group(d.context, d.group)
self.driver.create_volume(d.test_volume)
self.driver.create_group_snapshot(d.context, d.cgsnapshot, [])
xms_data['volumes'][2]['ancestor-vol-id'] = (xms_data['volumes'][1]
['vol-id'])
snapset_name = self.driver._get_cgsnap_name(d.cgsnapshot)
snapset1 = {'vol-list': [xms_data['volumes'][2]['vol-id']],
'name': snapset_name,
'index': 1}
xms_data['snapshot-sets'] = {snapset_name: snapset1, 1: snapset1}
cg_obj = fake_cg.fake_consistencyobject_obj(d.context)
new_vol1 = fake_volume_obj(d.context)
snapshot1 = (fake_snapshot
.fake_snapshot_obj
(d.context, volume_id=d.test_volume['id']))
res = self.driver.create_group_from_src(d.context, cg_obj,
[new_vol1],
d.cgsnapshot,
[snapshot1])
self.assertEqual((None, None), res)
def test_group_from_src_group(self, req):
"""test group from source group."""
req.side_effect = xms_request
d = self.data
self.driver.create_group(d.context, d.group)
self.driver.create_volume(d.test_volume)
self.driver.create_group_snapshot(d.context, d.cgsnapshot, [])
xms_data['volumes'][2]['ancestor-vol-id'] = (xms_data['volumes'][1]
['vol-id'])
snapset_name = self.driver._get_cgsnap_name(d.cgsnapshot)
snapset1 = {'vol-list': [xms_data['volumes'][2]['vol-id']],
'name': snapset_name,
'index': 1}
xms_data['snapshot-sets'] = {snapset_name: snapset1, 1: snapset1}
cg_obj = fake_cg.fake_consistencyobject_obj(d.context)
new_vol1 = fake_volume_obj(d.context)
new_cg_obj = fake_cg.fake_consistencyobject_obj(
d.context, id=fake.CONSISTENCY_GROUP2_ID)
snapset2_name = new_cg_obj.id
new_vol1.id = '192eb39b-6c2f-420c-bae3-3cfd117f0001'
new_vol2 = fake_volume_obj(d.context)
snapset2 = {'vol-list': [xms_data['volumes'][2]['vol-id']],
'name': snapset2_name,
'index': 1}
xms_data['snapshot-sets'].update({5: snapset2,
snapset2_name: snapset2})
self.driver.create_group_from_src(d.context, new_cg_obj,
[new_vol2],
None, None,
cg_obj, [new_vol1])
def test_invalid_group_from_src_input(self, req):
"""test invalid group from source."""
req.side_effect = xms_request
d = self.data
self.assertRaises(exception.InvalidInput,
self.driver.create_group_from_src,
d.context, d.group, [], None, None, None, None)
def test_get_password(self, _req):
p = self.driver._get_password()
self.assertEqual(len(p), 12)
self.assertIsNotNone(re.match(r'[A-Z0-9]{12}', p), p)
@mock.patch('requests.request')
class XtremIODriverTestCase(BaseXtremIODriverTestCase):
# ##### XMS Client #####
@mock.patch.object(time, 'sleep', mock.Mock(return_value=0))
def test_retry_request(self, req):
busy_response = mock.MagicMock()
busy_response.status_code = 400
busy_response.json.return_value = {
"message": "system_is_busy",
"error_code": 400
}
good_response = mock.MagicMock()
good_response.status_code = 200
XtremIODriverTestCase.req_count = 0
def busy_request(*args, **kwargs):
if XtremIODriverTestCase.req_count < 1:
XtremIODriverTestCase.req_count += 1
return busy_response
return good_response
req.side_effect = busy_request
self.driver.create_volume(self.data.test_volume)
def test_verify_cert(self, req):
good_response = mock.MagicMock()
good_response.status_code = 200
def request_verify_cert(*args, **kwargs):
self.assertEqual(kwargs['verify'], '/test/path/root_ca.crt')
return good_response
req.side_effect = request_verify_cert
self.driver.client.req('volumes')
@mock.patch('cinder.volume.drivers.dell_emc.xtremio.XtremIOClient.req')
class XtremIODriverFCTestCase(BaseXtremIODriverTestCase):
def setUp(self):
super(XtremIODriverFCTestCase, self).setUp()
self.driver = xtremio.XtremIOFCDriver(
configuration=self.config)
# ##### Connection FC#####
def test_initialize_connection(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
map_data = self.driver.initialize_connection(self.data.test_volume,
self.data.connector)
self.assertEqual(1, map_data['data']['target_lun'])
def test_terminate_connection(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
self.driver.initialize_connection(self.data.test_volume,
self.data.connector)
for i1 in xms_data['initiators'].values():
i1['ig-id'] = ['', i1['ig-id'], 1]
self.driver.terminate_connection(self.data.test_volume,
self.data.connector)
def test_force_terminate_connection(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
self.driver.initialize_connection(self.data.test_volume,
self.data.connector)
vol1 = xms_data['volumes'][1]
# lun mapping list is a list of triplets (IG OID, TG OID, lun number)
vol1['lun-mapping-list'] = [[['a91e8c81c2d14ae4865187ce4f866f8a',
'iqn.1993-08.org.debian:01:222',
1],
['', 'Default', 1],
1]]
self.driver.terminate_connection(self.data.test_volume, None)
def test_initialize_existing_ig_connection(self, req):
req.side_effect = xms_request
self.driver.create_volume(self.data.test_volume)
pre_existing = 'pre_existing_host'
self.driver._create_ig(pre_existing)
wwpns = self.driver._get_initiator_names(self.data.connector)
for wwpn in wwpns:
data = {'initiator-name': wwpn, 'ig-id': pre_existing,
'port-address': wwpn}
self.driver.client.req('initiators', 'POST', data)
def get_fake_initiator(wwpn):
return {'port-address': wwpn, 'ig-id': ['', pre_existing, 1]}
with mock.patch.object(self.driver.client, 'get_initiator',
side_effect=get_fake_initiator):
map_data = self.driver.initialize_connection(self.data.test_volume,
self.data.connector)
self.assertEqual(1, map_data['data']['target_lun'])
self.assertEqual(1, len(xms_data['initiator-groups']))
def test_get_initiator_igs_ver4(self, req):
req.side_effect = xms_request
wwpn1 = '11:22:33:44:55:66:77:88'
wwpn2 = '11:22:33:44:55:66:77:89'
port_addresses = [wwpn1, wwpn2]
ig_id = ['', 'my_ig', 1]
self.driver.client = xtremio.XtremIOClient4(self.config,
self.config
.xtremio_cluster_name)
def get_fake_initiator(wwpn):
return {'port-address': wwpn, 'ig-id': ig_id}
with mock.patch.object(self.driver.client, 'get_initiator',
side_effect=get_fake_initiator):
self.driver.client.get_initiators_igs(port_addresses)
def test_get_free_lun(self, req):
def lm_response(*args, **kwargs):
return {'lun-maps': [{'lun': 1}]}
req.side_effect = lm_response
ig_names = ['test1', 'test2']
self.driver._get_free_lun(ig_names)
def test_race_on_terminate_connection(self, req):
"""Test for race conditions on num_of_mapped_volumes.
This test confirms that num_of_mapped_volumes won't break even if we
receive a NotFound exception when retrieving info on a specific
mapping, as that specific mapping could have been deleted between
the request to get the list of exiting mappings and the request to get
the info on one of them.
"""
req.side_effect = xms_request
self.driver.client = xtremio.XtremIOClient3(
self.config, self.config.xtremio_cluster_name)
# We'll wrap num_of_mapped_volumes, we'll store here original method
original_method = self.driver.client.num_of_mapped_volumes
def fake_num_of_mapped_volumes(*args, **kwargs):
# Add a nonexistent mapping
mappings = [{'href': 'volumes/1'}, {'href': 'volumes/12'}]
# Side effects will be: 1st call returns the list, then we return
# data for existing mappings, and on the nonexistent one we added
# we return NotFound
side_effect = [{'lun-maps': mappings},
{'content': xms_data['lun-maps'][1]},
exception.NotFound]
with mock.patch.object(self.driver.client, 'req',
side_effect=side_effect):
return original_method(*args, **kwargs)
self.driver.create_volume(self.data.test_volume)
map_data = self.driver.initialize_connection(self.data.test_volume,
self.data.connector)
self.assertEqual(1, map_data['data']['target_lun'])
with mock.patch.object(self.driver.client, 'num_of_mapped_volumes',
side_effect=fake_num_of_mapped_volumes):
self.driver.terminate_connection(self.data.test_volume,
self.data.connector)
self.driver.delete_volume(self.data.test_volume)
| 44.560565 | 79 | 0.553846 |
acbc77e6837d56f25fafc6c43bdf000553710645 | 3,161 | py | Python | test/tservers.py | codders/netlib | 137ae524c958cea9c96990587dafdd05b8d9cca0 | [
"MIT"
] | null | null | null | test/tservers.py | codders/netlib | 137ae524c958cea9c96990587dafdd05b8d9cca0 | [
"MIT"
] | null | null | null | test/tservers.py | codders/netlib | 137ae524c958cea9c96990587dafdd05b8d9cca0 | [
"MIT"
] | null | null | null | from __future__ import (absolute_import, print_function, division)
import threading
import queue
import io
import OpenSSL
from netlib import tcp, certutils
from . import tutils
class ServerThread(threading.Thread):
def __init__(self, server):
self.server = server
threading.Thread.__init__(self)
def run(self):
self.server.serve_forever()
def shutdown(self):
self.server.shutdown()
class ServerTestBase(object):
ssl = None
handler = None
port = None
addr = ("localhost", 0)
@classmethod
def setup_class(cls):
cls.q = queue.Queue()
s = cls.makeserver()
cls.port = s.address.port
cls.server = ServerThread(s)
cls.server.start()
@classmethod
def makeserver(cls):
return TServer(cls.ssl, cls.q, cls.handler, cls.addr)
@classmethod
def teardown_class(cls):
cls.server.shutdown()
@property
def last_handler(self):
return self.server.server.last_handler
class TServer(tcp.TCPServer):
def __init__(self, ssl, q, handler_klass, addr):
"""
ssl: A dictionary of SSL parameters:
cert, key, request_client_cert, cipher_list,
dhparams, v3_only
"""
tcp.TCPServer.__init__(self, addr)
if ssl is True:
self.ssl = dict()
elif isinstance(ssl, dict):
self.ssl = ssl
else:
self.ssl = None
self.q = q
self.handler_klass = handler_klass
self.last_handler = None
def handle_client_connection(self, request, client_address):
h = self.handler_klass(request, client_address, self)
self.last_handler = h
if self.ssl is not None:
cert = self.ssl.get(
"cert",
tutils.test_data.path("data/server.crt"))
raw_key = self.ssl.get(
"key",
tutils.test_data.path("data/server.key"))
key = OpenSSL.crypto.load_privatekey(
OpenSSL.crypto.FILETYPE_PEM,
open(raw_key, "rb").read())
if self.ssl.get("v3_only", False):
method = OpenSSL.SSL.SSLv3_METHOD
options = OpenSSL.SSL.OP_NO_SSLv2 | OpenSSL.SSL.OP_NO_TLSv1
else:
method = OpenSSL.SSL.SSLv23_METHOD
options = None
h.convert_to_ssl(
cert, key,
method=method,
options=options,
handle_sni=getattr(h, "handle_sni", None),
request_client_cert=self.ssl.get("request_client_cert", None),
cipher_list=self.ssl.get("cipher_list", None),
dhparams=self.ssl.get("dhparams", None),
chain_file=self.ssl.get("chain_file", None),
alpn_select=self.ssl.get("alpn_select", None)
)
h.handle()
h.finish()
def handle_error(self, connection, client_address, fp=None):
s = io.StringIO()
tcp.TCPServer.handle_error(self, connection, client_address, s)
self.q.put(s.getvalue())
| 29.268519 | 78 | 0.574818 |
719cc805ad781c57f52921d4eaf72b451f8fabf6 | 6,844 | py | Python | scripts/dataset.py | max-simon/master-thesis | b0db01008d52317bc036f8a0f20671ce49108a12 | [
"CC-BY-4.0"
] | 4 | 2021-01-03T06:57:47.000Z | 2022-02-05T15:31:44.000Z | scripts/dataset.py | max-simon/master-thesis | b0db01008d52317bc036f8a0f20671ce49108a12 | [
"CC-BY-4.0"
] | null | null | null | scripts/dataset.py | max-simon/master-thesis | b0db01008d52317bc036f8a0f20671ce49108a12 | [
"CC-BY-4.0"
] | 2 | 2021-03-20T18:39:39.000Z | 2022-01-17T12:55:28.000Z | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Author: Max Simon
# Year: 2020
import sys
sys.path.append('/nfs/kryo/work/maxsimon/master-thesis/scripts')
import xarray as xr
import numpy as np
from datetime import timedelta as tdelta
from datetime import datetime
import argparse
from romstools.utils import parse_slice
from romstools.slice import slice_on_rho_grid
xr.set_options(keep_attrs=True) # this is required to keep the attributes when modifying time!
def get_drop_except_fn(*keep_vars):
"""
Drop all but some variables in a netCDF file
"""
def drop_except(ds):
# do nothing when nothing to drop and avoid dropping time
if len(keep_vars) == 0 or (len(keep_vars) == 1 and keep_vars[0] == 'time'):
return ds
# xarray only allows to specify what to drop, but not which to keep. So we need
# to invert this set
drop_vars = []
for v in ds.variables:
if v not in keep_vars:
drop_vars.append(v)
return ds.drop_vars(drop_vars)
return drop_except
def open_glob_dataset(data_files, keep_vars=[], time_slice=None):
"""
Open a Multifile Dataset with xarray using a glob expression.
"""
sm_ds = None
# if a list of files or a star in name, use xarray.mfdataset
if type(data_files) == list or '*' in data_files:
sm_ds = xr.open_mfdataset(
data_files,
decode_times=False,
combine="nested",
parallel=True,
concat_dim='time', # concatenate on time
preprocess=get_drop_except_fn(*keep_vars) # drop all values except keep_vars
)
# slice time
if time_slice is not None:
sm_ds = sm_ds.isel(time=time_slice)
# just open.
else:
drop_fn = get_drop_except_fn(*keep_vars)
sm_ds = xr.open_dataset(data_files, decode_times=False)
# slice time
if time_slice is not None:
sm_ds = sm_ds.isel(time=time_slice)
# drop all values except keep_vars
sm_ds = drop_fn(sm_ds)
return sm_ds
def set_time(ds, dt=tdelta(seconds=0)):
"""
Fix time loading errors of xarray, i.e. it keeps the time attributes. Also allows for specifying an offset.
"""
# get calendar and units attribute
calendar = ds.time.attrs['calendar']
units = ds.time.attrs['units']
# decode times
TimeCoder = xr.coding.times.CFDatetimeCoder()
ds['time'] = ds.time.fillna(0) + dt.total_seconds()
ds['time'] = xr.DataArray(TimeCoder.decode(ds.variables['time'], 'time'))
ds = ds.set_coords(['time'])
# restore attributes
ds.time.attrs['calendar'] = calendar
ds.time.attrs['units'] = units
return ds
def open_dataset(input, variables=[], time_calendar=None, time_raw=None, time_units=None, time_offset=0, time_from=None, eta_rho_slice=None, xi_rho_slice=None, s_rho_slice=None):
"""
Load dataset and grid file, overwrite calendar and units.
"""
# open data
dataset = open_glob_dataset(input, keep_vars=variables+['time'], time_slice=None)
# slice data
if eta_rho_slice is not None or xi_rho_slice is not None or s_rho_slice is not None:
dataset = slice_on_rho_grid(dataset, eta_rho_slice=eta_rho_slice, xi_rho_slice=xi_rho_slice, s_rho_slice=s_rho_slice)
# open another dataset to copy its time array to the opened dataset
if time_from is not None:
aux_ds = open_glob_dataset(time_from, keep_vars=['time'], time_slice=None)
attrs = aux_ds.time.attrs
dataset['time'] = xr.DataArray(aux_ds['time'].values, dims=('time',))
dataset['time'].attrs = attrs
aux_ds.close()
# if no time to process, skip
if 'time' not in dataset:
return dataset
# reset calendar and units
if time_raw is not None:
dataset['time'] = xr.DataArray(time_raw, dims=('time',))
if time_calendar is not None:
dataset.time.attrs['calendar'] = time_calendar
if time_units is not None:
dataset.time.attrs['units'] = time_units
# initialize time
dataset = set_time(dataset, dt=tdelta(seconds=time_offset))
# calculate day of year
time_attrs = {**dataset.time.attrs}
doy = np.array([a.dayofyr for a in dataset.time.values]) - 1
# create doy variable on data
dataset['doy'] = xr.DataArray(doy, dims=('time',))
dataset.time.attrs = time_attrs
return dataset
def dataset_from_args(parser):
"""
Add a group to input arguments for opening a dataset
"""
# create a parsing group
group = parser.add_argument_group("dataset")
# add items to group
group.add_argument("-i", "--input", type=str, nargs='+', help="Input path, glob is supported", required=True)
# spatial slicing
group.add_argument("--eta-rho", type=parse_slice, help="Slice input data at eta coordinates")
group.add_argument("--xi-rho", type=parse_slice, help="Slice input data at xi coordinates")
group.add_argument("--s-rho", type=parse_slice, help="Slice input data at s_rho coordinates (or depth if present)")
## Removed to reduce verbosity on --help. Add them to open_dataset when needed
# group.add_argument("--time-units", type=str, help="Overwrite time units attribute")
# group.add_argument("--time-calendar", type=str, help="Overwrite time calendar attribute")
# group.add_argument("--time-from", type=str, help="Overwrite time data")
group.add_argument("-v", "--variables", type=str, nargs="+", help="Choose variables to load", default=[])
# create a loading function
def load(args, variables=None, s_rho_slice=None):
# variables and s_rho_slice can be overwritten
vars_to_load = args.variables if variables is None else variables
s_rho_to_use = args.s_rho if s_rho_slice is None else s_rho_slice
input_to_use = args.input[0] if len(args.input) == 1 else args.input
ds = open_dataset(input_to_use, variables=vars_to_load, eta_rho_slice=args.eta_rho, xi_rho_slice=args.xi_rho, s_rho_slice=s_rho_to_use)
return ds
return load
| 41.478788 | 178 | 0.598919 |
499142ce26609c0925531d306fde6effe88c8cb3 | 7,564 | py | Python | automation/devops_automation_infra/plugins/memsql.py | AnyVisionltd/devops-automation-infra | 7d6e75dc96ffa53d07e1dbd2c4ddb0fcdcf92cd1 | [
"MIT"
] | 2 | 2021-03-10T14:52:24.000Z | 2021-03-10T18:50:20.000Z | automation/devops_automation_infra/plugins/memsql.py | solganik/devops-automation-infra | 2ef2ac80a52d2f2abd037ad24cbf7f98b0c50bc6 | [
"MIT"
] | 4 | 2021-03-14T11:30:11.000Z | 2022-01-30T16:01:41.000Z | automation/devops_automation_infra/plugins/memsql.py | solganik/devops-automation-infra | 2ef2ac80a52d2f2abd037ad24cbf7f98b0c50bc6 | [
"MIT"
] | 5 | 2021-03-10T14:52:14.000Z | 2021-11-17T16:00:18.000Z | import logging
from contextlib import closing
import pymysql
from infra.model import plugins
from pytest_automation_infra import helpers
from pymysql.constants import CLIENT
import copy
from automation_infra.utils import waiter
import json
class Connection(object):
def __init__(self, memsql_connection):
self.connection = memsql_connection
def upsert(self, query):
with closing(self.connection.cursor()) as cursor:
res = cursor.execute(query)
self.connection.commit()
return res
def fetchall(self, query):
with closing(self.connection.cursor()) as c:
c.execute(query)
return c.fetchall()
def fetch_one(self, query):
with closing(self.connection.cursor()) as cursor:
cursor.execute(query)
res = cursor.fetchone()
return res
def fetch_count(self, query):
with closing(self.connection.cursor()) as cursor:
cursor.execute(query)
return cursor.rowcount
def execute(self, query):
with closing(self.connection.cursor()) as c:
c.execute(query)
self.connection.commit()
def truncate_all(self):
logging.debug('Truncating all memsql dbs')
truncate_commands = self.fetchall(
f"""select concat('truncate table ', TABLE_SCHEMA, '.', TABLE_NAME) as truncate_command
from information_schema.tables t
where TABLE_SCHEMA not in ('information_schema', 'memsql')
and TABLE_NAME not in ('DATABASECHANGELOG', 'DATABASECHANGELOGLOCK'); """)
commands = ''.join([f"{command['truncate_command']};" for command in truncate_commands])
self.execute(commands)
logging.debug('Done Truncating all memsql dbs')
@staticmethod
def _reset_pipeline_cmd(pipline):
return f"alter pipeline {pipline} set offsets earliest;"
@staticmethod
def _stop_pipeline_cmd(pipline):
return f"stop pipeline {pipline};"
@staticmethod
def _start_pipeline_cmd(pipline):
return f"start pipeline {pipline};"
@staticmethod
def _drop_pipeline_cmd(pipline):
return f"drop pipeline {pipline};"
@staticmethod
def _get_pipeline_partitions_cmd(pipeline):
return f"select SOURCE_PARTITION_ID from information_schema.pipelines_cursors WHERE PIPELINE_NAME=\"{pipeline}\"";
def get_pipeline_partitions(self, pipeline):
query = Connection._get_pipeline_partitions_cmd(pipeline)
result = self.fetchall(query)
return [partition['SOURCE_PARTITION_ID'] for partition in result]
def delete_pipeline_partitions(self, pipeline, *partitions):
partitions = partitions or self.get_pipeline_partitions(pipeline)
if not partitions:
return
queries = [f"ALTER PIPELINE {pipeline} DROP PARTITION '{partition}'"
for partition in partitions]
joined = ";".join(queries)
self.execute(joined)
def reset_pipeline(self, pipeline_name):
logging.debug(f'Reset pipeline {pipeline_name}')
try:
self.execute(Connection._stop_pipeline_cmd(pipeline_name))
except pymysql.err.InternalError as e:
logging.debug('pipeline might be stopped in this case just continue')
err_code = e.args[0]
PIPELINE_ALREADY_STOPPED = 1939
if err_code != PIPELINE_ALREADY_STOPPED:
raise
self.execute(Connection._reset_pipeline_cmd(pipeline_name))
self.delete_pipeline_partitions(pipeline_name)
self.execute(Connection._start_pipeline_cmd(pipeline_name))
def close(self):
self.connection.close()
class Memsql(object):
def __init__(self, host):
self._host = host
self.DNS_NAME = 'memsql.tls.ai' if not helpers.is_k8s(self._host.SshDirect) else 'memsql.default.svc.cluster.local'
self.PORT = 3306
self._connection = None
@property
def connection(self):
host, port = self.tunnel.host_port
return self._create_connection(host=host,
port=port,
cursorclass=pymysql.cursors.DictCursor,
client_flag=CLIENT.MULTI_STATEMENTS)
def tunneled_connection(self, database=None):
host, port = self.tunnel.host_port
return self._create_connection(host=host,
port=port,
database=database)
def direct_connection(self, ip = None, port=3306, password=None, database=None):
if ip is None:
ip = self._host.ip
if password is None:
password = self.password
return self._create_connection(host=ip, port=port,
password = password,
cursorclass=pymysql.cursors.DictCursor,
client_flag=CLIENT.MULTI_STATEMENTS,
database=database)
@property
def password(self):
if not helpers.is_k8s(self._host.SshDirect):
return 'password'
return self._host.SshDirect.execute("kubectl get secret --namespace default memsql-secret -o jsonpath='{.data.password}' | base64 --decode")
def _create_connection(self, **kwargs):
password = "password" if not helpers.is_k8s(self._host.SshDirect) else self._host.SshDirect.execute("kubectl get secret --namespace default memsql-secret -o jsonpath='{.data.password}' | base64 --decode")
memsql_kwargs = copy.copy(kwargs)
if memsql_kwargs.get('password', None) is None:
memsql_kwargs['password'] = self.password
memsql_kwargs.setdefault('password', password)
memsql_kwargs.setdefault('user', 'root')
memsql_kwargs.setdefault('client_flag', CLIENT.MULTI_STATEMENTS)
memsql_kwargs.setdefault('cursorclass', pymysql.cursors.DictCursor)
return Connection(pymysql.connect(**memsql_kwargs))
@property
def tunnel(self):
return self._host.TunnelManager.get_or_create(self.DNS_NAME, self.DNS_NAME, self.PORT)
def upsert(self, query):
return self.connection.upsert(query)
def fetch_all(self, query):
return self.connection.fetchall(query)
def fetch_one(self, query):
return self.connection.fetch_one(query)
def fetch_count(self, query):
return self.connection.fetch_count(query)
def ping(self):
try:
nodes_status = json.loads(self._host.Docker.run_cmd_in_service('memsql', 'gosu memsql memsql-admin list-nodes --json'))
except Exception as e:
raise Exception("Failed to execute node-status command") from e
else:
if not all([node['processState'] == 'Running' and node['isConnectable'] and node['recoveryState'] == 'Online'
for node in nodes_status['nodes']]):
raise Exception(f"memsql is not ready {nodes_status}")
def reset_state(self):
self.connection.truncate_all()
def verify_functionality(self):
dbs = self.fetch_all("show databases")
def stop_service(self):
self._host.Docker.stop_container("memsql")
def start_service(self):
self._host.Docker.start_container("memsql")
self._host.Docker.wait_container_up("memsql")
waiter.wait_nothrow(self.ping, timeout=30)
plugins.register('Memsql', Memsql)
| 37.82 | 212 | 0.64146 |
0548191a889dcbb43909e44549def48dbb6af616 | 10,570 | py | Python | grimagents/tests/unit/test_parameter_search.py | PinataMostGrim/grimagents_cli | ad3461a6f331256586d9848a9eaa0a9095d65161 | [
"Apache-2.0"
] | 1 | 2019-08-18T21:00:22.000Z | 2019-08-18T21:00:22.000Z | grimagents/tests/unit/test_parameter_search.py | PinataMostGrim/grimagents_cli | ad3461a6f331256586d9848a9eaa0a9095d65161 | [
"Apache-2.0"
] | 6 | 2019-08-18T15:22:44.000Z | 2020-04-24T01:09:37.000Z | grimagents/tests/unit/test_parameter_search.py | PinataMostGrim/grimagents_cli | ad3461a6f331256586d9848a9eaa0a9095d65161 | [
"Apache-2.0"
] | null | null | null | import numpy
import pytest
from grimagents.parameter_search import (
GridSearch,
RandomSearch,
BayesianSearch,
InvalidGridSearchIndex,
)
@pytest.fixture
def search_config():
return {
'behavior_name': 'BEHAVIOR_NAME',
'search_parameters': {
'hyperparameters.beta': [1e-4, 1e-2],
'hyperparameters.num_epoch': [3, 10],
'hyperparameters.learning_rate': [1e-5, 1e-3],
'network_settings.hidden_units': [32, 512],
'network_settings.num_layers': [1, 3],
},
}
@pytest.fixture
def trainer_config():
return {
'behaviors': {
'BEHAVIOR_NAME': {
'trainer_type': 'ppo',
'hyperparameters': {
'batch_size': 1024,
'beta': 5.0e-3,
'buffer_size': 10240,
'epsilon': 0.2,
'lambd': 0.95,
},
'network_settings': {
'hidden_units': 128,
},
'reward_signals': {
'extrinsic': {
'gamma': 0.99,
'strength': 1.0,
},
},
},
'OTHER_BEHAVIOR_NAME': {
'trainer_type': 'ppo',
'hyperparameters': {
'batch_size': 1024,
'buffer_size': 10240,
'epsilon': 0.2,
},
},
},
}
def test_get_search_hyperparameters(search_config):
"""Test for the extraction of hyperparameter names from a search configuration dictionary."""
assert GridSearch.get_search_hyperparameter_names(search_config) == [
'hyperparameters.beta',
'hyperparameters.num_epoch',
'hyperparameters.learning_rate',
'network_settings.hidden_units',
'network_settings.num_layers',
]
def test_get_hyperparameter_sets(search_config):
"""Test for the correct construction of GridSearch hyperparameter sets."""
assert GridSearch.get_hyperparameter_sets(search_config) == [
[0.0001, 0.01],
[3, 10],
[1e-05, 0.001],
[32, 512],
[1, 3],
]
def test_get_search_permutations(search_config):
"""Test for the correct construction of GridSearch hyperparamter permutations."""
sets = [[0.0001, 0.01], [32, 512], [1e-05, 0.001]]
assert GridSearch.get_search_permutations(sets) == [
(0.0001, 32, 1e-05),
(0.0001, 32, 0.001),
(0.0001, 512, 1e-05),
(0.0001, 512, 0.001),
(0.01, 32, 1e-05),
(0.01, 32, 0.001),
(0.01, 512, 1e-05),
(0.01, 512, 0.001),
]
def test_get_grid_search_configuration(search_config, trainer_config):
"""Tests for the correct creation of GridSearch configurations."""
search = GridSearch(search_config, trainer_config)
assert search.get_search_configuration(0) == {
'hyperparameters.beta': 0.0001,
'hyperparameters.learning_rate': 1e-05,
'hyperparameters.num_epoch': 3,
'network_settings.hidden_units': 32,
'network_settings.num_layers': 1,
}
assert search.get_search_configuration(15) == {
'hyperparameters.beta': 0.0001,
'hyperparameters.learning_rate': 0.001,
'hyperparameters.num_epoch': 10,
'network_settings.hidden_units': 512,
'network_settings.num_layers': 3,
}
assert search.get_search_configuration(31) == {
'hyperparameters.beta': 0.01,
'hyperparameters.learning_rate': 0.001,
'hyperparameters.num_epoch': 10,
'network_settings.hidden_units': 512,
'network_settings.num_layers': 3,
}
def test_get_grid_search_count(search_config, trainer_config):
"""Tests for the correct calculation of permutation count."""
search = GridSearch(search_config, trainer_config)
assert search.get_grid_search_count() == 32
def test_invalid_grid_search_index(search_config, trainer_config):
"""Tests that InvalidGridSearchIndex exceptions are raised."""
search = GridSearch(search_config, trainer_config)
with pytest.raises(InvalidGridSearchIndex):
search.get_search_configuration(32)
def test_get_trainer_config_with_overrides(search_config, trainer_config):
"""Tests that flattened period separated keys are correctly expanded for the search configuration. Additionally tests to ensure nested sibling keys do not get overwritten."""
search = GridSearch(search_config, trainer_config)
overrides = {
'reward_signals.extrinsic.gamma': 0.91,
'reward_signals.curiosity.encoding_size': 256,
'reward_signals.curiosity.strength': 1.0,
'reward_signals.curiosity.gamma': 0.99,
}
search_config = search.get_trainer_config_with_overrides(overrides)
assert search_config == {
'behaviors': {
'BEHAVIOR_NAME': {
'hyperparameters': {
'batch_size': 1024,
'beta': 0.005,
'buffer_size': 10240,
'epsilon': 0.2,
'lambd': 0.95,
},
'network_settings': {'hidden_units': 128},
'reward_signals': {
'curiosity': {'encoding_size': 256, 'gamma': 0.99, 'strength': 1.0},
'extrinsic': {'gamma': 0.91, 'strength': 1.0},
},
'trainer_type': 'ppo',
},
'OTHER_BEHAVIOR_NAME': {
'hyperparameters': {'batch_size': 1024, 'buffer_size': 10240, 'epsilon': 0.2},
'trainer_type': 'ppo',
},
}
}
def test_buffer_size_multiple(search_config, trainer_config):
"""Tests that 'buffer_size' is correctly calculated if 'buffer_size_multiple' is present and that 'buffer_size_multiple' is stripped from 'trainer_config'."""
search_config['search_parameters']['hyperparameters.buffer_size_multiple'] = [4]
search = GridSearch(search_config, trainer_config)
search_overrides = search.get_search_configuration(0)
trainer_config = search.get_trainer_config_with_overrides(search_overrides)
assert 'buffer_size_multiple' not in trainer_config['behaviors']['BEHAVIOR_NAME']
assert trainer_config == {
'behaviors': {
'BEHAVIOR_NAME': {
'hyperparameters': {
'batch_size': 1024,
'beta': 0.0001,
'buffer_size': 4096,
'epsilon': 0.2,
'lambd': 0.95,
'learning_rate': 1e-05,
'num_epoch': 3,
},
'network_settings': {'hidden_units': 32, 'num_layers': 1},
'reward_signals': {'extrinsic': {'gamma': 0.99, 'strength': 1.0}},
'trainer_type': 'ppo',
},
'OTHER_BEHAVIOR_NAME': {
'hyperparameters': {'batch_size': 1024, 'buffer_size': 10240, 'epsilon': 0.2},
'trainer_type': 'ppo',
},
}
}
def test_get_random_value():
"""Test for the correct randomization of ints and floats."""
assert RandomSearch.get_random_value([1, 5, 8], seed=10) == 1
assert RandomSearch.get_random_value([0.01, 0.0001, 1], seed=5) == 0.6229394047202129
def test_get_random_search(search_config, trainer_config):
"""Tests for the correct generation of a randomized search configuration."""
search = RandomSearch(search_config, trainer_config)
random_search_config = search.get_randomized_search_configuration(seed=9871237)
assert random_search_config == {
'hyperparameters.beta': 0.008715030393329336,
'hyperparameters.learning_rate': 0.0008715030393329336,
'hyperparameters.num_epoch': 4,
'network_settings.hidden_units': 477,
'network_settings.num_layers': 1,
}
def test_get_parameter_bounds():
"""Tests for the correct construction of a parameter bounds dictionary."""
parameter_names = ['batch_size', 'buffer_size_multiple', 'beta']
parameter_values = [[64, 128], [4], [0.001, 0.0001]]
result = BayesianSearch.get_parameter_bounds(parameter_names, parameter_values)
# Test for a dictionary return type
assert type(result) is dict
# Test for a second value inserted for any parameter that only contains one value
assert result == {
'batch_size': [64, 128],
'buffer_size_multiple': [4, 4],
'beta': [0.001, 0.0001],
}
def test_get_search_config_from_bounds():
"""Tests that
- Only standard Python value types are returned
- Values that should be int are converted to int
- The item() method is not called on non-numpy value types
"""
bounds = {
'hyperparameters.batch_size': numpy.float64(144.0682249028942),
'hyperparameters.beta': numpy.float64(0.0028687875149226343),
'hyperparameters.buffer_size_multiple': numpy.float64(50.017156222601734),
'hyperparameters.num_epoch': numpy.float64(5.028942),
'network_settings.hidden_units': numpy.float64(121.0682249028942),
'network_settings.num_layers': numpy.float64(2.49028942),
'network_settings.memory.memory_size': numpy.float64(154.9019),
'network_settings.memory.sequence_length': numpy.float64(144.9028),
'reward_signal.extrinsic.strength': numpy.float64(1.0),
'reward_signal.strength.encoding_size': numpy.float64(184.6824928),
'reward_signal.curiosity.encoding_size': numpy.float64(184.6824928),
'reward_signal.gail.encoding_size': numpy.float64(184.6824928),
'max_steps': numpy.float64(500000.1),
'time_horizon': numpy.float64(64.049292),
}
assert BayesianSearch.get_search_config_from_bounds(bounds) == {
'hyperparameters.batch_size': 144,
'hyperparameters.beta': 0.0028687875149226343,
'hyperparameters.buffer_size_multiple': 50,
'hyperparameters.num_epoch': 5,
'max_steps': 500000,
'network_settings.hidden_units': 121,
'network_settings.memory.memory_size': 152,
'network_settings.memory.sequence_length': 145,
'network_settings.num_layers': 2,
'reward_signal.curiosity.encoding_size': 185,
'reward_signal.extrinsic.strength': 1.0,
'reward_signal.gail.encoding_size': 185,
'reward_signal.strength.encoding_size': 185,
'time_horizon': 64,
}
| 35.116279 | 178 | 0.609272 |
6786e272c3fb74cb1b2b4b2ccd42c7ef608e6d9e | 998 | py | Python | api/api_personal_pay/resources/baseApi.py | HJaycee/PersonalPay | 8999e9322a7739f3f736f89d5c984e296b19aa79 | [
"MIT"
] | 71 | 2018-05-23T02:29:06.000Z | 2022-02-28T16:37:54.000Z | api/api_personal_pay/resources/baseApi.py | HJaycee/PersonalPay | 8999e9322a7739f3f736f89d5c984e296b19aa79 | [
"MIT"
] | 4 | 2019-02-18T11:49:52.000Z | 2021-01-27T03:00:22.000Z | api/api_personal_pay/resources/baseApi.py | HJaycee/PersonalPay | 8999e9322a7739f3f736f89d5c984e296b19aa79 | [
"MIT"
] | 26 | 2018-05-29T03:35:21.000Z | 2022-02-28T16:37:53.000Z | from flask_restful import Resource
from flask import request, session, make_response
import os
import hashlib
from util.log import Logger
import json
from util.commonUtil import CommonUtil
import time
def output_json(data, code, headers=None):
"""Makes a Flask response with a JSON encoded body"""
# 如果是app接口，且不是支付回调，加密后返回
Logger.log("请求id：%s 响应\n返回JSON：%s\n" % (session['requestId'], data))
resp = make_response(json.dumps(data), code)
resp.headers.extend(headers or {})
return resp
# 这个是Api基类，可以做统一处理
class BaseApi(Resource):
def __init__(self):
md5 = hashlib.md5()
md5.update(os.urandom(24))
session['requestId'] = md5.hexdigest()
Logger.log(">>>>>>>>>>>>>>>>>>>>>>> 请求 请求id：%s >>>>>>>>>>>>>>>>>>>>>>>\n%s|%s|%s|%s|%s" % (session['requestId'], time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()), request.environ['REMOTE_ADDR'], request.environ['REQUEST_METHOD'], request.url, request.get_data()))
Resource.__init__(self)
| 35.642857 | 275 | 0.657315 |
957dc7bc64328fb9303f0831ae6396eca69e3dd3 | 32,834 | py | Python | extensions/aria_extension_tosca/simple_v1_0/modeling/__init__.py | enricorusso/incubator-ariatosca | 3748b1962697712bde29c9de781d867c6c5ffad1 | [
"Apache-2.0"
] | null | null | null | extensions/aria_extension_tosca/simple_v1_0/modeling/__init__.py | enricorusso/incubator-ariatosca | 3748b1962697712bde29c9de781d867c6c5ffad1 | [
"Apache-2.0"
] | null | null | null | extensions/aria_extension_tosca/simple_v1_0/modeling/__init__.py | enricorusso/incubator-ariatosca | 3748b1962697712bde29c9de781d867c6c5ffad1 | [
"Apache-2.0"
] | null | null | null | # Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
Creates ARIA service template models based on the TOSCA presentation.
Relies on many helper methods in the presentation classes.
"""
#pylint: disable=unsubscriptable-object
import os
import re
from types import FunctionType
from datetime import datetime
from ruamel import yaml
from aria.parser.validation import Issue
from aria.utils.formatting import string_list_as_string
from aria.utils.collections import (StrictDict, OrderedDict)
from aria.orchestrator import WORKFLOW_DECORATOR_RESERVED_ARGUMENTS
from aria.modeling.models import (Type, ServiceTemplate, NodeTemplate,
RequirementTemplate, RelationshipTemplate, CapabilityTemplate,
GroupTemplate, PolicyTemplate, SubstitutionTemplate,
SubstitutionTemplateMapping, InterfaceTemplate, OperationTemplate,
ArtifactTemplate, Metadata, Input, Output, Property,
Attribute, Configuration, PluginSpecification)
from .parameters import coerce_parameter_value
from .constraints import (Equal, GreaterThan, GreaterOrEqual, LessThan, LessOrEqual, InRange,
ValidValues, Length, MinLength, MaxLength, Pattern)
from ..data_types import coerce_value
# These match the first un-escaped ">"
# See: http://stackoverflow.com/a/11819111/849021
IMPLEMENTATION_PREFIX_REGEX = re.compile(r'(?<!\\)(?:\\\\)*>')
def create_service_template_model(context): # pylint: disable=too-many-locals,too-many-branches
model = ServiceTemplate(created_at=datetime.now(),
main_file_name=os.path.basename(str(context.presentation.location)))
model.description = context.presentation.get('service_template', 'description', 'value')
# Metadata
metadata = context.presentation.get('service_template', 'metadata')
if metadata is not None:
create_metadata_models(context, model, metadata)
# Types
model.node_types = Type(variant='node')
create_types(context,
model.node_types,
context.presentation.get('service_template', 'node_types'))
model.group_types = Type(variant='group')
create_types(context,
model.group_types,
context.presentation.get('service_template', 'group_types'))
model.policy_types = Type(variant='policy')
create_types(context,
model.policy_types,
context.presentation.get('service_template', 'policy_types'))
model.relationship_types = Type(variant='relationship')
create_types(context,
model.relationship_types,
context.presentation.get('service_template', 'relationship_types'))
model.capability_types = Type(variant='capability')
create_types(context,
model.capability_types,
context.presentation.get('service_template', 'capability_types'))
model.interface_types = Type(variant='interface')
create_types(context,
model.interface_types,
context.presentation.get('service_template', 'interface_types'))
model.artifact_types = Type(variant='artifact')
create_types(context,
model.artifact_types,
context.presentation.get('service_template', 'artifact_types'))
# Topology template
topology_template = context.presentation.get('service_template', 'topology_template')
if topology_template is not None:
create_parameter_models_from_values(model.inputs,
topology_template._get_input_values(context),
model_cls=Input)
create_parameter_models_from_values(model.outputs,
topology_template._get_output_values(context),
model_cls=Output)
# Plugin specifications
policies = context.presentation.get('service_template', 'topology_template', 'policies')
if policies:
for policy in policies.itervalues():
role = model.policy_types.get_descendant(policy.type).role
if role == 'plugin':
plugin_specification = create_plugin_specification_model(context, policy)
model.plugin_specifications[plugin_specification.name] = plugin_specification
elif role == 'workflow':
operation_template = create_workflow_operation_template_model(context,
model, policy)
model.workflow_templates[operation_template.name] = operation_template
# Node templates
node_templates = context.presentation.get('service_template', 'topology_template',
'node_templates')
if node_templates:
for node_template in node_templates.itervalues():
node_template_model = create_node_template_model(context, model, node_template)
model.node_templates[node_template_model.name] = node_template_model
for node_template in node_templates.itervalues():
fix_node_template_model(context, model, node_template)
# Group templates
groups = context.presentation.get('service_template', 'topology_template', 'groups')
if groups:
for group in groups.itervalues():
group_template_model = create_group_template_model(context, model, group)
model.group_templates[group_template_model.name] = group_template_model
# Policy templates
policies = context.presentation.get('service_template', 'topology_template', 'policies')
if policies:
for policy in policies.itervalues():
policy_template_model = create_policy_template_model(context, model, policy)
model.policy_templates[policy_template_model.name] = policy_template_model
# Substitution template
substitution_mappings = context.presentation.get('service_template', 'topology_template',
'substitution_mappings')
if substitution_mappings:
model.substitution_template = create_substitution_template_model(context, model,
substitution_mappings)
return model
def create_metadata_models(context, service_template, metadata):
service_template.meta_data['template_name'] = Metadata(name='template_name',
value=metadata.template_name)
service_template.meta_data['template_author'] = Metadata(name='template_author',
value=metadata.template_author)
service_template.meta_data['template_version'] = Metadata(name='template_version',
value=metadata.template_version)
custom = metadata.custom
if custom:
for name, value in custom.iteritems():
service_template.meta_data[name] = Metadata(name=name,
value=value)
def create_node_template_model(context, service_template, node_template):
node_type = node_template._get_type(context)
node_type = service_template.node_types.get_descendant(node_type._name)
model = NodeTemplate(name=node_template._name,
type=node_type)
model.default_instances = 1
model.min_instances = 0
if node_template.description:
model.description = node_template.description.value
create_parameter_models_from_values(model.properties,
node_template._get_property_values(context),
model_cls=Property)
create_parameter_models_from_values(model.attributes,
node_template._get_attribute_default_values(context),
model_cls=Attribute)
create_interface_template_models(context, service_template, model.interface_templates,
node_template._get_interfaces(context))
artifacts = node_template._get_artifacts(context)
if artifacts:
for artifact_name, artifact in artifacts.iteritems():
model.artifact_templates[artifact_name] = \
create_artifact_template_model(context, service_template, artifact)
capabilities = node_template._get_capabilities(context)
if capabilities:
for capability_name, capability in capabilities.iteritems():
model.capability_templates[capability_name] = \
create_capability_template_model(context, service_template, capability)
if node_template.node_filter:
model.target_node_template_constraints = []
create_node_filter_constraints(context, node_template.node_filter,
model.target_node_template_constraints)
return model
def fix_node_template_model(context, service_template, node_template):
# Requirements have to be created after all node templates have been created, because
# requirements might reference another node template
model = service_template.node_templates[node_template._name]
requirements = node_template._get_requirements(context)
if requirements:
for _, requirement in requirements:
model.requirement_templates.append(create_requirement_template_model(context,
service_template,
requirement))
def create_group_template_model(context, service_template, group):
group_type = group._get_type(context)
group_type = service_template.group_types.get_descendant(group_type._name)
model = GroupTemplate(name=group._name,
type=group_type)
if group.description:
model.description = group.description.value
create_parameter_models_from_values(model.properties, group._get_property_values(context),
model_cls=Property)
create_interface_template_models(context, service_template, model.interface_templates,
group._get_interfaces(context))
members = group.members
if members:
for member in members:
node_template = service_template.node_templates[member]
assert node_template
model.node_templates.append(node_template)
return model
def create_policy_template_model(context, service_template, policy):
policy_type = policy._get_type(context)
policy_type = service_template.policy_types.get_descendant(policy_type._name)
model = PolicyTemplate(name=policy._name,
type=policy_type)
if policy.description:
model.description = policy.description.value
create_parameter_models_from_values(model.properties, policy._get_property_values(context),
model_cls=Property)
node_templates, groups = policy._get_targets(context)
if node_templates:
for target in node_templates:
node_template = service_template.node_templates[target._name]
assert node_template
model.node_templates.append(node_template)
if groups:
for target in groups:
group_template = service_template.group_templates[target._name]
assert group_template
model.group_templates.append(group_template)
return model
def create_requirement_template_model(context, service_template, requirement):
model = {'name': requirement._name}
node, node_variant = requirement._get_node(context)
if node is not None:
if node_variant == 'node_type':
node_type = service_template.node_types.get_descendant(node._name)
model['target_node_type'] = node_type
else:
node_template = service_template.node_templates[node._name]
model['target_node_template'] = node_template
capability, capability_variant = requirement._get_capability(context)
if capability is not None:
if capability_variant == 'capability_type':
capability_type = \
service_template.capability_types.get_descendant(capability._name)
model['target_capability_type'] = capability_type
else:
model['target_capability_name'] = capability._name
model = RequirementTemplate(**model)
if requirement.node_filter:
model.target_node_template_constraints = []
create_node_filter_constraints(context, requirement.node_filter,
model.target_node_template_constraints)
relationship = requirement.relationship
if relationship is not None:
model.relationship_template = \
create_relationship_template_model(context, service_template, relationship)
model.relationship_template.name = requirement._name
return model
def create_relationship_template_model(context, service_template, relationship):
relationship_type, relationship_type_variant = relationship._get_type(context)
if relationship_type_variant == 'relationship_type':
relationship_type = service_template.relationship_types.get_descendant(
relationship_type._name)
model = RelationshipTemplate(type=relationship_type)
else:
relationship_template = relationship_type
relationship_type = relationship_template._get_type(context)
relationship_type = service_template.relationship_types.get_descendant(
relationship_type._name)
model = RelationshipTemplate(type=relationship_type)
if relationship_template.description:
model.description = relationship_template.description.value
create_parameter_models_from_assignments(model.properties,
relationship.properties,
model_cls=Property)
create_interface_template_models(context, service_template, model.interface_templates,
relationship.interfaces)
return model
def create_capability_template_model(context, service_template, capability):
capability_type = capability._get_type(context)
capability_type = service_template.capability_types.get_descendant(capability_type._name)
model = CapabilityTemplate(name=capability._name,
type=capability_type)
capability_definition = capability._get_definition(context)
if capability_definition.description:
model.description = capability_definition.description.value
occurrences = capability_definition.occurrences
if occurrences is not None:
model.min_occurrences = occurrences.value[0]
if occurrences.value[1] != 'UNBOUNDED':
model.max_occurrences = occurrences.value[1]
valid_source_types = capability_definition.valid_source_types
if valid_source_types:
for valid_source_type in valid_source_types:
# TODO: handle shortcut type names
node_type = service_template.node_types.get_descendant(valid_source_type)
model.valid_source_node_types.append(node_type)
create_parameter_models_from_assignments(model.properties,
capability.properties,
model_cls=Property)
return model
def create_interface_template_model(context, service_template, interface):
interface_type = interface._get_type(context)
interface_type = service_template.interface_types.get_descendant(interface_type._name)
model = InterfaceTemplate(name=interface._name,
type=interface_type)
if interface_type.description:
model.description = interface_type.description
inputs = interface.inputs
if inputs:
for input_name, the_input in inputs.iteritems():
model.inputs[input_name] = Input(name=input_name, # pylint: disable=unexpected-keyword-arg
type_name=the_input.value.type,
value=the_input.value.value,
description=the_input.value.description)
operations = interface.operations
if operations:
for operation_name, operation in operations.iteritems():
model.operation_templates[operation_name] = \
create_operation_template_model(context, service_template, operation)
return model if model.operation_templates else None
def create_operation_template_model(context, service_template, operation):
model = OperationTemplate(name=operation._name)
if operation.description:
model.description = operation.description.value
implementation = operation.implementation
if implementation is not None:
primary = implementation.primary
extract_implementation_primary(context, service_template, operation, model, primary)
relationship_edge = operation._get_extensions(context).get('relationship_edge')
if relationship_edge is not None:
if relationship_edge == 'source':
model.relationship_edge = False
elif relationship_edge == 'target':
model.relationship_edge = True
dependencies = implementation.dependencies
configuration = OrderedDict()
if dependencies:
for dependency in dependencies:
key, value = split_prefix(dependency)
if key is not None:
# Special ARIA prefix: signifies configuration parameters
# Parse as YAML
try:
value = yaml.load(value)
except yaml.parser.MarkedYAMLError as e:
context.validation.report(
'YAML parser {0} in operation configuration: {1}'
.format(e.problem, value),
locator=implementation._locator,
level=Issue.FIELD)
continue
# Coerce to intrinsic functions, if there are any
value = coerce_parameter_value(context, implementation, None, value).value
# Support dot-notation nesting
set_nested(configuration, key.split('.'), value)
else:
if model.dependencies is None:
model.dependencies = []
model.dependencies.append(dependency)
# Convert configuration to Configuration models
for key, value in configuration.iteritems():
model.configurations[key] = Configuration.wrap(key, value,
description='Operation configuration.')
inputs = operation.inputs
if inputs:
for input_name, the_input in inputs.iteritems():
model.inputs[input_name] = Input(name=input_name, # pylint: disable=unexpected-keyword-arg
type_name=the_input.value.type,
value=the_input.value.value,
description=the_input.value.description)
return model
def create_artifact_template_model(context, service_template, artifact):
artifact_type = artifact._get_type(context)
artifact_type = service_template.artifact_types.get_descendant(artifact_type._name)
model = ArtifactTemplate(name=artifact._name,
type=artifact_type,
source_path=artifact.file)
if artifact.description:
model.description = artifact.description.value
model.target_path = artifact.deploy_path
repository = artifact._get_repository(context)
if repository is not None:
model.repository_url = repository.url
credential = repository._get_credential(context)
if credential:
model.repository_credential = {}
for k, v in credential.iteritems():
model.repository_credential[k] = v
create_parameter_models_from_values(model.properties, artifact._get_property_values(context),
model_cls=Property)
return model
def create_substitution_template_model(context, service_template, substitution_mappings):
node_type = service_template.node_types.get_descendant(substitution_mappings.node_type)
model = SubstitutionTemplate(node_type=node_type)
capabilities = substitution_mappings.capabilities
if capabilities:
for mapped_capability_name, capability in capabilities.iteritems():
name = 'capability.' + mapped_capability_name
node_template_model = service_template.node_templates[capability.node_template]
capability_template_model = \
node_template_model.capability_templates[capability.capability]
model.mappings[name] = \
SubstitutionTemplateMapping(name=name,
capability_template=capability_template_model)
requirements = substitution_mappings.requirements
if requirements:
for mapped_requirement_name, requirement in requirements.iteritems():
name = 'requirement.' + mapped_requirement_name
node_template_model = service_template.node_templates[requirement.node_template]
requirement_template_model = None
for a_model in node_template_model.requirement_templates:
if a_model.name == requirement.requirement:
requirement_template_model = a_model
break
model.mappings[name] = \
SubstitutionTemplateMapping(name=name,
requirement_template=requirement_template_model)
return model
def create_plugin_specification_model(context, policy):
properties = policy.properties
def get(name, default=None):
prop = properties.get(name)
return prop.value if prop is not None else default
model = PluginSpecification(name=policy._name,
version=get('version'),
enabled=get('enabled', True))
return model
def create_workflow_operation_template_model(context, service_template, policy):
model = OperationTemplate(name=policy._name,
service_template=service_template)
if policy.description:
model.description = policy.description.value
properties = policy._get_property_values(context)
for prop_name, prop in properties.iteritems():
if prop_name == 'implementation':
model.function = prop.value
else:
model.inputs[prop_name] = Input(name=prop_name, # pylint: disable=unexpected-keyword-arg
type_name=prop.type,
value=prop.value,
description=prop.description)
used_reserved_names = WORKFLOW_DECORATOR_RESERVED_ARGUMENTS.intersection(model.inputs.keys())
if used_reserved_names:
context.validation.report('using reserved arguments in workflow policy "{0}": {1}'
.format(
policy._name,
string_list_as_string(used_reserved_names)),
locator=policy._locator,
level=Issue.EXTERNAL)
return model
#
# Utils
#
def create_types(context, root, types):
if types is None:
return
def added_all():
for name in types:
if root.get_descendant(name) is None:
return False
return True
while not added_all():
for name, the_type in types.iteritems():
if root.get_descendant(name) is None:
parent_type = the_type._get_parent(context)
model = Type(name=the_type._name,
role=the_type._get_extension('role'))
if the_type.description:
model.description = the_type.description.value
if parent_type is None:
model.parent = root
model.variant = root.variant
root.children.append(model)
else:
container = root.get_descendant(parent_type._name)
if container is not None:
model.parent = container
model.variant = container.variant
container.children.append(model)
def create_parameter_models_from_values(properties, source_properties, model_cls):
if source_properties:
for property_name, prop in source_properties.iteritems():
properties[property_name] = model_cls(name=property_name, # pylint: disable=unexpected-keyword-arg
type_name=prop.type,
value=prop.value,
description=prop.description)
def create_parameter_models_from_assignments(properties, source_properties, model_cls):
if source_properties:
for property_name, prop in source_properties.iteritems():
properties[property_name] = model_cls(name=property_name, # pylint: disable=unexpected-keyword-arg
type_name=prop.value.type,
value=prop.value.value,
description=prop.value.description)
def create_interface_template_models(context, service_template, interfaces, source_interfaces):
if source_interfaces:
for interface_name, interface in source_interfaces.iteritems():
interface = create_interface_template_model(context, service_template, interface)
if interface is not None:
interfaces[interface_name] = interface
def create_node_filter_constraints(context, node_filter, target_node_template_constraints):
properties = node_filter.properties
if properties is not None:
for property_name, constraint_clause in properties:
constraint = create_constraint(context, node_filter, constraint_clause, property_name,
None)
target_node_template_constraints.append(constraint)
capabilities = node_filter.capabilities
if capabilities is not None:
for capability_name, capability in capabilities:
properties = capability.properties
if properties is not None:
for property_name, constraint_clause in properties:
constraint = create_constraint(context, node_filter, constraint_clause,
property_name, capability_name)
target_node_template_constraints.append(constraint)
def create_constraint(context, node_filter, constraint_clause, property_name, capability_name): # pylint: disable=too-many-return-statements
constraint_key = constraint_clause._raw.keys()[0]
the_type = constraint_clause._get_type(context)
def coerce_constraint(constraint):
if the_type is not None:
return coerce_value(context, node_filter, the_type, None, None, constraint,
constraint_key)
else:
return constraint
def coerce_constraints(constraints):
if the_type is not None:
return tuple(coerce_constraint(constraint) for constraint in constraints)
else:
return constraints
if constraint_key == 'equal':
return Equal(property_name, capability_name,
coerce_constraint(constraint_clause.equal))
elif constraint_key == 'greater_than':
return GreaterThan(property_name, capability_name,
coerce_constraint(constraint_clause.greater_than))
elif constraint_key == 'greater_or_equal':
return GreaterOrEqual(property_name, capability_name,
coerce_constraint(constraint_clause.greater_or_equal))
elif constraint_key == 'less_than':
return LessThan(property_name, capability_name,
coerce_constraint(constraint_clause.less_than))
elif constraint_key == 'less_or_equal':
return LessOrEqual(property_name, capability_name,
coerce_constraint(constraint_clause.less_or_equal))
elif constraint_key == 'in_range':
return InRange(property_name, capability_name,
coerce_constraints(constraint_clause.in_range))
elif constraint_key == 'valid_values':
return ValidValues(property_name, capability_name,
coerce_constraints(constraint_clause.valid_values))
elif constraint_key == 'length':
return Length(property_name, capability_name,
coerce_constraint(constraint_clause.length))
elif constraint_key == 'min_length':
return MinLength(property_name, capability_name,
coerce_constraint(constraint_clause.min_length))
elif constraint_key == 'max_length':
return MaxLength(property_name, capability_name,
coerce_constraint(constraint_clause.max_length))
elif constraint_key == 'pattern':
return Pattern(property_name, capability_name,
coerce_constraint(constraint_clause.pattern))
else:
raise ValueError('malformed node_filter: {0}'.format(constraint_key))
def split_prefix(string):
"""
Splits the prefix on the first non-escaped ">".
"""
split = IMPLEMENTATION_PREFIX_REGEX.split(string, 1)
if len(split) < 2:
return None, None
return split[0].strip(), split[1].strip()
def set_nested(the_dict, keys, value):
"""
If the ``keys`` list has just one item, puts the value in the the dict. If there are more items,
puts the value in a sub-dict, creating sub-dicts as necessary for each key.
For example, if ``the_dict`` is an empty dict, keys is ``['first', 'second', 'third']`` and
value is ``'value'``, then the_dict will be: ``{'first':{'second':{'third':'value'}}}``.
:param the_dict: Dict to change
:type the_dict: {}
:param keys: Keys
:type keys: [basestring]
:param value: Value
"""
key = keys.pop(0)
if len(keys) == 0:
the_dict[key] = value
else:
if key not in the_dict:
the_dict[key] = StrictDict(key_class=basestring)
set_nested(the_dict[key], keys, value)
def extract_implementation_primary(context, service_template, presentation, model, primary):
prefix, postfix = split_prefix(primary)
if prefix:
# Special ARIA prefix
model.plugin_specification = service_template.plugin_specifications.get(prefix)
model.function = postfix
if model.plugin_specification is None:
context.validation.report(
'no policy for plugin "{0}" specified in operation implementation: {1}'
.format(prefix, primary),
locator=presentation._get_child_locator('properties', 'implementation'),
level=Issue.BETWEEN_TYPES)
else:
# Standard TOSCA artifact with default plugin
model.implementation = primary
| 44.793997 | 140 | 0.646312 |
796b9eba3d8b6666757a920bcbdf5f2634b908a4 | 1,518 | py | Python | acheron/model.py | superphy/acheron | cd9838f000085409e306a5f66b04276a1e4eb5f5 | [
"Apache-2.0"
] | 1 | 2022-01-07T17:23:14.000Z | 2022-01-07T17:23:14.000Z | acheron/model.py | superphy/acheron | cd9838f000085409e306a5f66b04276a1e4eb5f5 | [
"Apache-2.0"
] | null | null | null | acheron/model.py | superphy/acheron | cd9838f000085409e306a5f66b04276a1e4eb5f5 | [
"Apache-2.0"
] | 1 | 2021-06-18T17:36:08.000Z | 2021-06-18T17:36:08.000Z | import os
MAX_RAM = '1000G'
def build_model(arguments):
model_args = ''
for arg in vars(arguments):
attr = getattr(arguments,arg)
model_args += " {}={}".format(arg, attr)
if arg == 'hyperparam':
# hyperparameter optimizations require additional RAM
# subject to change
if attr == True:
RAM = '250G'
else:
RAM = '125G'
# if using >11mers, max out the ram
greedy_sceduler = False
if getattr(arguments,'type')[-3:] == 'mer':
if int(getattr(arguments,'type')[:2]) > 11:
RAM = MAX_RAM
greedy_sceduler = True
cluster = getattr(arguments,'cluster').upper()
# when not using cluster
if cluster == 'NONE':
os.system("snakemake -s acheron/workflows/modeler.smk -j {} \
--config{}".format(getattr(arguments,'cores'), model_args))
# when using slurm cluster management
elif cluster == 'SLURM':
if greedy_sceduler:
os.system("sbatch -c {0} --mem {1} snakemake -s acheron/workflows/modeler.smk -j {0} \
--config{2} --nolock --scheduler greedy".format(getattr(arguments,'cores'), RAM, model_args))
else:
os.system("sbatch -c {0} --mem {1} snakemake -s acheron/workflows/modeler.smk -j {0} \
--config{2} --nolock".format(getattr(arguments,'cores'), RAM, model_args))
else:
raise Exception("cluster config {} not supported, use slurm or none".format(cluster))
| 35.302326 | 105 | 0.581686 |
618a4307b39aa0012cfde0dcc662084fff55d450 | 726 | py | Python | kolibri/deployment/default/settings/test.py | FollonSaxBass/kolibri | 4cf820b14386aecc228fecff64c847bad407cbb1 | [
"MIT"
] | 2 | 2021-05-13T10:20:46.000Z | 2021-11-15T12:31:03.000Z | kolibri/deployment/default/settings/test.py | Priyaraj17/kolibri | 6d600213871e8a748209870b508dd97a505907c1 | [
"MIT"
] | 8 | 2021-05-21T15:31:24.000Z | 2022-02-24T15:02:14.000Z | kolibri/deployment/default/settings/test.py | Priyaraj17/kolibri | 6d600213871e8a748209870b508dd97a505907c1 | [
"MIT"
] | 4 | 2021-11-15T04:23:34.000Z | 2021-11-25T16:40:11.000Z | from __future__ import absolute_import
from __future__ import print_function
from __future__ import unicode_literals
import os
import tempfile
# If KOLIBRI_HOME isn't defined in the test env, it's okay to just set a
# temp directory for testing.
if "KOLIBRI_HOME" not in os.environ:
os.environ["KOLIBRI_HOME"] = tempfile.mkdtemp()
from .base import * # noqa isort:skip @UnusedWildImport
try:
process_cache = CACHES["process_cache"] # noqa F405
except KeyError:
process_cache = None
# Create a dummy cache for each cache
CACHES = {
key: {"BACKEND": "django.core.cache.backends.dummy.DummyCache"}
for key in CACHES.keys() # noqa F405
}
if process_cache:
CACHES["process_cache"] = process_cache
| 25.034483 | 72 | 0.745179 |
0cc23b5c4c6ca9b398d269d41e764f07800d3eb1 | 11,242 | py | Python | src/syft/core/node/common/action/run_class_method_action.py | ariannmichael/PySyft | 0205898c3268b17ccebc5916f9aff370a1c48a25 | [
"Apache-2.0"
] | null | null | null | src/syft/core/node/common/action/run_class_method_action.py | ariannmichael/PySyft | 0205898c3268b17ccebc5916f9aff370a1c48a25 | [
"Apache-2.0"
] | null | null | null | src/syft/core/node/common/action/run_class_method_action.py | ariannmichael/PySyft | 0205898c3268b17ccebc5916f9aff370a1c48a25 | [
"Apache-2.0"
] | null | null | null | # stdlib
import functools
from typing import Any
from typing import Dict
from typing import List
from typing import Optional
# third party
from google.protobuf.reflection import GeneratedProtocolMessageType
from nacl.signing import VerifyKey
# syft absolute
from syft.core.plan.plan import Plan
# syft relative
from ..... import lib
from ..... import serialize
from .....logger import critical
from .....logger import traceback_and_raise
from .....logger import warning
from .....proto.core.node.common.action.run_class_method_pb2 import (
RunClassMethodAction as RunClassMethodAction_PB,
)
from .....util import inherit_tags
from ....common.serde.deserialize import _deserialize
from ....common.serde.serializable import bind_protobuf
from ....common.uid import UID
from ....io.address import Address
from ....store.storeable_object import StorableObject
from ...abstract.node import AbstractNode
from .common import ImmediateActionWithoutReply
@bind_protobuf
class RunClassMethodAction(ImmediateActionWithoutReply):
"""
When executing a RunClassMethodAction, a :class:`Node` will run a method defined
by the action's path attribute on the object pointed at by _self and keep the returned
value in its store.
Attributes:
path: the dotted path to the method to call
_self: a pointer to the object which the method should be applied to.
args: args to pass to the function. They should be pointers to objects
located on the :class:`Node` that will execute the action.
kwargs: kwargs to pass to the function. They should be pointers to objects
located on the :class:`Node` that will execute the action.
"""
def __init__(
self,
path: str,
_self: Any,
args: List[Any],
kwargs: Dict[Any, Any],
id_at_location: UID,
address: Address,
msg_id: Optional[UID] = None,
is_static: Optional[bool] = False,
):
self.path = path
self._self = _self
self.args = args
self.kwargs = kwargs
self.id_at_location = id_at_location
self.is_static = is_static
# logging needs .path to exist before calling
# this which is why i've put this super().__init__ down here
super().__init__(address=address, msg_id=msg_id)
@staticmethod
def intersect_keys(
left: Dict[VerifyKey, UID], right: Dict[VerifyKey, UID]
) -> Dict[VerifyKey, UID]:
# get the intersection of the dict keys, the value is the request_id
# if the request_id is different for some reason we still want to keep it,
# so only intersect the keys and then copy those over from the main dict
# into a new one
intersection = set(left.keys()).intersection(right.keys())
# left and right have the same keys
return {k: left[k] for k in intersection}
@property
def pprint(self) -> str:
return f"RunClassMethodAction({self.path})"
def execute_action(self, node: AbstractNode, verify_key: VerifyKey) -> None:
method = node.lib_ast(self.path)
mutating_internal = False
if (
self.path.startswith("torch.Tensor")
and self.path.endswith("_")
and not self.path.endswith("__call__")
):
mutating_internal = True
elif not self.path.startswith("torch.Tensor") and self.path.endswith(
"__call__"
):
mutating_internal = True
resolved_self = None
if not self.is_static:
resolved_self = node.store.get_object(key=self._self.id_at_location)
if resolved_self is None:
critical(
f"execute_action on {self.path} failed due to missing object"
+ f" at: {self._self.id_at_location}"
)
return
result_read_permissions = resolved_self.read_permissions
else:
result_read_permissions = {}
resolved_args = list()
tag_args = []
for arg in self.args:
r_arg = node.store[arg.id_at_location]
result_read_permissions = self.intersect_keys(
result_read_permissions, r_arg.read_permissions
)
resolved_args.append(r_arg.data)
tag_args.append(r_arg)
resolved_kwargs = {}
tag_kwargs = {}
for arg_name, arg in self.kwargs.items():
r_arg = node.store[arg.id_at_location]
result_read_permissions = self.intersect_keys(
result_read_permissions, r_arg.read_permissions
)
resolved_kwargs[arg_name] = r_arg.data
tag_kwargs[arg_name] = r_arg
(
upcasted_args,
upcasted_kwargs,
) = lib.python.util.upcast_args_and_kwargs(resolved_args, resolved_kwargs)
if self.is_static:
result = method(*upcasted_args, **upcasted_kwargs)
else:
if resolved_self is None:
traceback_and_raise(
ValueError(f"Method {method} called, but self is None.")
)
# in opacus the step method in torch gets monkey patched on .attach
# this means we can't use the original AST method reference and need to
# get it again from the actual object so for now lets allow the following
# two methods to be resolved at execution time
method_name = self.path.split(".")[-1]
if isinstance(resolved_self.data, Plan) and method_name == "__call__":
result = method(
resolved_self.data,
node,
verify_key,
*self.args,
**upcasted_kwargs,
)
else:
target_method = getattr(resolved_self.data, method_name, None)
if id(target_method) != id(method):
warning(
f"Method {method_name} overwritten on object {resolved_self.data}"
)
method = target_method
else:
method = functools.partial(method, resolved_self.data)
result = method(*upcasted_args, **upcasted_kwargs)
if lib.python.primitive_factory.isprimitive(value=result):
# Wrap in a SyPrimitive
result = lib.python.primitive_factory.PrimitiveFactory.generate_primitive(
value=result, id=self.id_at_location
)
else:
# TODO: overload all methods to incorporate this automatically
if hasattr(result, "id"):
try:
if hasattr(result, "_id"):
# set the underlying id
result._id = self.id_at_location
else:
result.id = self.id_at_location
assert result.id == self.id_at_location
except AttributeError as e:
err = f"Unable to set id on result {type(result)}. {e}"
traceback_and_raise(Exception(err))
if mutating_internal:
if isinstance(resolved_self, StorableObject):
resolved_self.read_permissions = result_read_permissions
if not isinstance(result, StorableObject):
result = StorableObject(
id=self.id_at_location,
data=result,
read_permissions=result_read_permissions,
)
inherit_tags(
attr_path_and_name=self.path,
result=result,
self_obj=resolved_self,
args=tag_args,
kwargs=tag_kwargs,
)
node.store[self.id_at_location] = result
def _object2proto(self) -> RunClassMethodAction_PB:
"""Returns a protobuf serialization of self.
As a requirement of all objects which inherit from Serializable,
this method transforms the current object into the corresponding
Protobuf object so that it can be further serialized.
:return: returns a protobuf object
:rtype: RunClassMethodAction_PB
.. note::
This method is purely an internal method. Please use serialize(object) or one of
the other public serialization methods if you wish to serialize an
object.
"""
return RunClassMethodAction_PB(
path=self.path,
_self=serialize(self._self),
args=list(map(lambda x: serialize(x), self.args)),
kwargs={k: serialize(v) for k, v in self.kwargs.items()},
id_at_location=serialize(self.id_at_location),
address=serialize(self.address),
msg_id=serialize(self.id),
)
@staticmethod
def _proto2object(proto: RunClassMethodAction_PB) -> "RunClassMethodAction":
"""Creates a ObjectWithID from a protobuf
As a requirement of all objects which inherit from Serializable,
this method transforms a protobuf object into an instance of this class.
:return: returns an instance of RunClassMethodAction
:rtype: RunClassMethodAction
.. note::
This method is purely an internal method. Please use syft.deserialize()
if you wish to deserialize an object.
"""
return RunClassMethodAction(
path=proto.path,
_self=_deserialize(blob=proto._self),
args=list(map(lambda x: _deserialize(blob=x), proto.args)),
kwargs={k: _deserialize(blob=v) for k, v in proto.kwargs.items()},
id_at_location=_deserialize(blob=proto.id_at_location),
address=_deserialize(blob=proto.address),
msg_id=_deserialize(blob=proto.msg_id),
)
@staticmethod
def get_protobuf_schema() -> GeneratedProtocolMessageType:
"""Return the type of protobuf object which stores a class of this type
As a part of serialization and deserialization, we need the ability to
lookup the protobuf object type directly from the object type. This
static method allows us to do this.
Importantly, this method is also used to create the reverse lookup ability within
the metaclass of Serializable. In the metaclass, it calls this method and then
it takes whatever type is returned from this method and adds an attribute to it
with the type of this class attached to it. See the MetaSerializable class for details.
:return: the type of protobuf object which corresponds to this class.
:rtype: GeneratedProtocolMessageType
"""
return RunClassMethodAction_PB
def remap_input(self, current_input: Any, new_input: Any) -> None:
"""Redefines some of the arguments, and possibly the _self of the function"""
if self._self.id_at_location == current_input.id_at_location:
self._self = new_input
else:
for i, arg in enumerate(self.args):
if arg.id_at_location == current_input.id_at_location:
self.args[i] = new_input
| 38.108475 | 95 | 0.618929 |
e9590701c27469096ccecc4dd7234479d8177ad6 | 1,689 | py | Python | clowder/cli/checkout.py | JrGoodle/clowder | 864afacfc7122e937f7087e233c61d05fd007af2 | [
"MIT"
] | 12 | 2016-02-12T02:37:24.000Z | 2021-01-04T05:14:12.000Z | clowder/cli/checkout.py | JrGoodle/clowder | 864afacfc7122e937f7087e233c61d05fd007af2 | [
"MIT"
] | 370 | 2015-07-06T22:59:08.000Z | 2021-10-01T14:58:17.000Z | clowder/cli/checkout.py | JrGoodle/clowder | 864afacfc7122e937f7087e233c61d05fd007af2 | [
"MIT"
] | 3 | 2015-10-22T18:45:31.000Z | 2018-10-16T15:30:30.000Z | """Clowder command line checkout controller
.. codeauthor:: Joe DeCapo <joe@polka.cat>
"""
import argparse
import clowder.util.formatting as fmt
from clowder.clowder_controller import CLOWDER_CONTROLLER, print_clowder_name, valid_clowder_yaml_required
from clowder.config import Config
from clowder.git.clowder_repo import print_clowder_repo_status
from clowder.util.console import CONSOLE
from .util import add_parser_arguments
def add_checkout_parser(subparsers: argparse._SubParsersAction) -> None: # noqa
"""Add clowder checkout parser
:param argparse._SubParsersAction subparsers: Subparsers action to add parser to
"""
parser = subparsers.add_parser('checkout', help='Checkout local branch in projects')
parser.formatter_class = argparse.RawTextHelpFormatter
parser.set_defaults(func=checkout)
add_parser_arguments(parser, [
(['branch'], dict(nargs=1, action='store', help='branch to checkout', metavar='<branch>')),
(['projects'], dict(metavar='<project|group>', default='default', nargs='*',
choices=CLOWDER_CONTROLLER.project_choices_with_default,
help=fmt.project_options_help_message('projects and groups to checkout branches for')))
])
@valid_clowder_yaml_required
@print_clowder_name
@print_clowder_repo_status
def checkout(args) -> None:
"""Clowder checkout command private implementation"""
projects = Config().process_projects_arg(args.projects)
projects = CLOWDER_CONTROLLER.filter_projects(CLOWDER_CONTROLLER.projects, projects)
for project in projects:
CONSOLE.stdout(project.status())
project.checkout(args.branch[0])
| 35.1875 | 115 | 0.743635 |
a48e9561ef7bb9e6b36714ec206137625124c50f | 4,232 | py | Python | core/models.py | dongmokevin/ecomv1 | abb3dc5a5476c379c029b8299e820c1979d5eb14 | [
"MIT"
] | null | null | null | core/models.py | dongmokevin/ecomv1 | abb3dc5a5476c379c029b8299e820c1979d5eb14 | [
"MIT"
] | null | null | null | core/models.py | dongmokevin/ecomv1 | abb3dc5a5476c379c029b8299e820c1979d5eb14 | [
"MIT"
] | null | null | null | from django.db import models
from django.conf import settings
from django.contrib.auth.models import User
from django.shortcuts import reverse
from django.utils.text import slugify
# Create your models here.
class ProductManager(models.Manager):
def get_queryset(self):
return super(ProductManager, self).get_queryset().filter(is_active=True)
class Product(models.Model):
name = models.CharField(max_length=210)
price = models.DecimalField(max_digits=9, decimal_places=2)
slug = models.SlugField(max_length=48)
image = models.ImageField(upload_to="product-images", null=True)
thumbnail = models.ImageField(upload_to="product-thumbnails", null=True, blank=True)
generic_name = models.CharField(max_length=100, blank=True, null=True)
decription = models.TextField(blank=True, null=True)
is_active = models.BooleanField(default=True)
created = models.DateTimeField(auto_now_add=True)
updated = models.DateTimeField(auto_now=True)
objects = models.Manager()
products = ProductManager()
def __str__(self):
return self.name
@property
def imageURL(self):
try:
url =self.thumbnail.url
except:
url = self.image.url
return url
def get_absolute_url(self):
return reverse('core:product', kwargs={
'slug': self.slug
})
def get_add_to_cart_url(self):
return reverse('core:add-to-cart', kwargs={
'slug': self.slug
})
def get_remove_from_cart_url(self):
return reverse('core:remove_from_cart', kwargs={
'slug': self.slug
})
def save(self, *args, **kwargs):
value = self.name
self.slug = slugify(value,)# allow_unicode=True)
super(Product, self).save(*args, **kwargs)
# class OrderItem(models.Model):
# customer = models.ForeignKey(Customer, on_delete=models.SET_NULL, blank=True, null=True)
# product = models.ForeignKey(Product, on_delete=models.SET_NULL, blank=True, null=True)
# # order = models.ForeignKey(Order, on_delete=models.SET_NULL, blank=True, null=True)
# quantity = models.IntegerField(default=0, null=True, blank=True)
# date_ordered = models.DateTimeField(auto_now_add=True)
#
# @property
# def get_total(self):
# total =self.product.price * self.quantity
# return total
#
# # def get_total_final_price(self):
# # if self.product.price:
# # return self.get_total
#
# class Order(models.Model):
# customer = models.ForeignKey(Customer, on_delete=models.SET_NULL, blank=True, null=True)
# date_ordered = models.DateTimeField(auto_now_add=True)
# complete = models.BooleanField(default=False, null=True, blank=True)
# transaction_id = models.CharField(max_length=200, null=True)
#
# products = models.ManyToManyField(OrderItem)
#
# def __str__(self):
# return str(self.id)
#
# @property
# def get_cart_total(self):
# orderitems = self.products.all()
# total = sum([item.get_total for item in orderitems])
# return total
# # def get_cart_total(self):
# # total = 0
# # for order_item in self.products.all():
# # total += order_item.get_total()
# # return total
#
#
# @property
# def get_cart_items(self):
# orderitems = self.products.all()
# total = sum([item.quantity for item in orderitems])
# return total
#
#
# class ShippingAdresses(models.Model):
# customer = models.ForeignKey(Customer, on_delete=models.SET_NULL, blank=True, null=True)
# name = models.CharField(max_length=200)
# order = models.ForeignKey(Order, on_delete=models.SET_NULL, blank=True, null=True)
# address = models.CharField(max_length=200, null=True)
# address2 = models.CharField(max_length=200, null=True, blank=True)
# city = models.CharField(max_length=200, null=True)
# state = models.CharField(max_length=200, null=True)
# zipcode = models.CharField(max_length=200, null=True, blank=True)
# phone = models.CharField(max_length=200, null=True)
# phone = models.DateTimeField(auto_now_add=True)
#
# def __str__(self):
# return str(address)
| 36.482759 | 94 | 0.670369 |
85f9c68cad40d6a5b44dbc9ba7bf674212d40121 | 2,391 | py | Python | Code/CreatPath_Labeltxt.py | haoranD/FaceAntiSpoofing_DL | 40e12ee9db6fbaded03c7aff1f933fe8be5e4ff3 | [
"MIT"
] | 19 | 2018-10-30T22:24:54.000Z | 2022-01-11T05:14:38.000Z | Code/CreatPath_Labeltxt.py | coderwangson/FaceAntiSpoofing_DL | 40e12ee9db6fbaded03c7aff1f933fe8be5e4ff3 | [
"MIT"
] | 4 | 2018-11-21T06:09:13.000Z | 2019-04-14T15:09:37.000Z | Code/CreatPath_Labeltxt.py | coderwangson/FaceAntiSpoofing_DL | 40e12ee9db6fbaded03c7aff1f933fe8be5e4ff3 | [
"MIT"
] | 4 | 2018-11-06T00:31:25.000Z | 2021-01-30T12:37:35.000Z | import os
from os import listdir
TRAINING = 0
TESTING = 1
CASIA = 0
REPLAYATTACK = 1
def CreatLabelPath(PROCESSFLAG,DataBaseOpt):
print("In function CreatLabelPath, start processing!")
true_img_dir_CASIA = ['1.avi', '2.avi', 'HR_1.avi', 'HR_4.avi']
if DataBaseOpt == REPLAYATTACK:
path_train_root_img = "../../../Data/ReplayAttack/Train/Train_aligned_5p/"
path_train_output = "../../../Data/ReplayAttack/Train/label_img_train_5p.txt"
path_test_root_img = "../../../Data/ReplayAttack/Test/Test_aligned_5p/"
path_test_output = "../../../Data/ReplayAttack/Test/label_img_test_5p.txt"
elif DataBaseOpt == CASIA:
path_train_root_img = "/media/haoran/Data1/LivenessDetection/Data/CBSR-Antispoofing/Train/Train_aligned_ALL/"
path_train_output = "/media/haoran/Data1/LivenessDetection/Data/CBSR-Antispoofing/Train/label_img_train_all.txt"
path_test_root_img = "/media/haoran/Data1/LivenessDetection/Data/CBSR-Antispoofing/Test/Test_aligned_ALL/"
path_test_output = "/media/haoran/Data1/LivenessDetection/Data/CBSR-Antispoofing/Test/label_img_test_all.txt"
if PROCESSFLAG == TRAINING:
path_root_img = path_train_root_img
path_output = path_train_output
if os.path.exists(path_train_output):
os.remove(path_train_output)
else:
path_root_img = path_test_root_img
path_output = path_test_output
if os.path.exists(path_test_output):
os.remove(path_test_output)
for dir_img in listdir(path_root_img):
dir1_img = os.path.join(path_root_img, dir_img)
#print "dir1_img" + dir1_img
# for g_img in listdir(dir2_img):
# img_path = os.path.join(dir2_img,g_img)
# print(img_path)
print(dir_img)
if dir_img == 'Real':
for f_img in listdir(dir1_img):
img_path = os.path.join(dir1_img, f_img)
with open(path_output, 'a') as f:
f.write(img_path + ' ' + '1' + '\n')
elif dir_img == 'Attack':
for f_img in listdir(dir1_img):
img_path = os.path.join(dir1_img, f_img)
with open(path_output, 'a') as f:
f.write(img_path + ' ' + '0' + '\n')
print("Processing CreatLabelPath Success!")
CreatLabelPath(TRAINING,CASIA)
CreatLabelPath(TESTING,CASIA)
| 40.525424 | 120 | 0.654538 |
d16dee5ec41ff6abda582add48de8c91e77f7912 | 2,301 | py | Python | backend/db/models/user.py | digitaltembo/stylobate | c22dbbb671612b2c95f84b7ee95dcb40f1fb6baa | [
"MIT"
] | 4 | 2020-07-29T02:01:41.000Z | 2022-02-19T13:11:30.000Z | backend/db/models/user.py | digitaltembo/stylobate | c22dbbb671612b2c95f84b7ee95dcb40f1fb6baa | [
"MIT"
] | 4 | 2021-03-11T02:00:08.000Z | 2022-02-19T05:07:33.000Z | backend/db/models/user.py | digitaltembo/stylobate | c22dbbb671612b2c95f84b7ee95dcb40f1fb6baa | [
"MIT"
] | null | null | null | import bcrypt
from sqlalchemy import Column, Boolean, Integer, String
import datetime
import jwt
from pydantic import BaseModel
from sql import Base
from utils.config import SECRET_KEY
TWO_WEEKS = datetime.timedelta(days=14)
# SQLAlchemy ORM Model
class User(Base):
__tablename__ = "users"
id = Column(Integer(), primary_key=True)
email = Column(String(255), unique=True)
password = Column(String(255), nullable=False)
isSuperuser = Column('is_superuser', Boolean(), default=False, nullable=False )
def __init__(self, id: int = 0, email: str = '', password: str = '', isSuperuser: bool = False):
self.email = email
self.password = User.hashed_password(password)
self.isSuperuser = isSuperuser
self.id = id
def generate_token(self, expiration: datetime.timedelta=TWO_WEEKS):
user_dict = UserType.from_orm(self).dict()
user_dict["exp"] = datetime.datetime.utcnow() + TWO_WEEKS
return jwt.encode(user_dict, SECRET_KEY, algorithm='HS256')
@staticmethod
def hashed_password(password: str):
return bcrypt.hashpw(password, bcrypt.gensalt())
@staticmethod
def password_matches(password: str, user):
return bcrypt.checkpw(password, user.password)
@staticmethod
def verify_token(token: str):
try:
data = UserType.parse_obj(jwt.decode(token, SECRET_KEY, algorithms='HS256'))
return data.to_user()
except:
return None
@staticmethod
def create_superuser(email: str, password: str):
print("INSERT INTO users (email, password, is_superuser) VALUES ('{}','{}', 1);".format(email, User.hashed_password(password)))
# Pydantic Data Schemas
class UserBaseType(BaseModel):
email: str
class UserCreateType(UserBaseType):
email: str
password: str
def to_user(self):
return User(
email = self.email,
password = User.hashed_password(self.password)
)
class UserType(UserBaseType):
id: int
email: str
isSuperuser: bool
def to_user(self) -> User:
return User(
id = self.id,
email = self.email,
isSuperuser = self.isSuperuser
)
class Config:
orm_mode = True | 28.060976 | 135 | 0.647545 |
a5baf58d61f2f70d00172aab1433ecf77f1b544c | 1,958 | py | Python | python3/day_003/day-003-dns-lookup-domain-details-info.py | king-md/100DaysOfCode | ab2e2495e804663ca35f72bbc8d8ec06cb202fac | [
"MIT"
] | null | null | null | python3/day_003/day-003-dns-lookup-domain-details-info.py | king-md/100DaysOfCode | ab2e2495e804663ca35f72bbc8d8ec06cb202fac | [
"MIT"
] | null | null | null | python3/day_003/day-003-dns-lookup-domain-details-info.py | king-md/100DaysOfCode | ab2e2495e804663ca35f72bbc8d8ec06cb202fac | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
import sys
import dns.resolver
def main():
# print( len(sys.argv) )
# if( 2 == len(sys.argv) ):
# name_server = '8.8.8.8' #Google's DNS server
# ADDITIONAL_RDCLASS = 65535
# request = dns.message.make_query('google.com', dns.rdatatype.ANY)
# request.flags |= dns.flags.AD
# request.find_rrset(request.additional, dns.name.root, ADDITIONAL_RDCLASS, dns.rdatatype.OPT, create=True, force_unique=True)
# response = dns.query.udp(request, name_server)
# print( "response:", response )
# #answer=dns.resolver.query("google.com", "all")
# #for data in answer:
# # print( data.strings )
# else:
# print( "invalid arguments." )
#
# return
import sys
import socket
import dns.resolver
print( 'Argument List:', str(sys.argv) )
site = sys.argv[1]
dns_server = sys.argv[2]
# Basic CNAME query the host's DNS
#for rdata in dns.resolver.query(site, 'CNAME') :
# print( rdata.target )
# Basic A query the host's DNS
for rdata in dns.resolver.query(site, 'A') :
print( rdata.address )
# Setting an specific DNS Server
resolver = dns.resolver.Resolver()
resolver.nameservers = [socket.gethostbyname(dns_server)]
# Basic CNAME query with the specific DNS server
#answer = resolver.query(site, 'CNAME');
#for rdata in answer :
# print( rdata.target )
# Basic A query with the specific DNS server
answer = resolver.query(site, 'A');
for rdata in answer :
print( rdata.address )
# Basic AAAA query with the specific DNS server
answer = resolver.query(site, 'AAAA');
for rdata in answer :
print( rdata.address )
# Basic TXT query with the specific DNS server
answer = resolver.query(site, 'TXT');
for rdata in answer :
print( rdata.strings )
return
main()
| 26.459459 | 140 | 0.61287 |
8284571593ab09681ccd718ff781b6d0a9ce9dd5 | 720 | py | Python | tables.py | Mr-Hockatt/SIR-Model-Visualizer | 07f044810f46a3b6bc2cc981330b88cdac0446ab | [
"MIT"
] | null | null | null | tables.py | Mr-Hockatt/SIR-Model-Visualizer | 07f044810f46a3b6bc2cc981330b88cdac0446ab | [
"MIT"
] | null | null | null | tables.py | Mr-Hockatt/SIR-Model-Visualizer | 07f044810f46a3b6bc2cc981330b88cdac0446ab | [
"MIT"
] | null | null | null | from tkinter import *
import csv
def createStandardTable(f,window):
handle = csv.reader(f)
length = len(next(handle))
sizes = [0] * length
for record in handle:
for p,column in enumerate(record):
if len(column) > sizes[p]:
sizes[p] = len(column)+3
f.seek(0)
trow = 0
table = Frame(window)
for record in handle:
for w,column in enumerate(record):
Label(table,text=column,width=sizes[w],borderwidth=2,relief="groove",justify=LEFT,anchor=W, background='white').grid(column=w,row=trow,sticky=W)
trow+=1
return table
| 22.5 | 157 | 0.526389 |
e91375611f660eb4dd4bcc854be2e1245d7b6222 | 4,343 | py | Python | antlir/compiler/items/tests/common.py | baioc/antlir | e3b47407b72c4aee835adf4e68fccd9abff457f2 | [
"MIT"
] | 28 | 2020-08-11T16:22:46.000Z | 2022-03-04T15:41:52.000Z | antlir/compiler/items/tests/common.py | baioc/antlir | e3b47407b72c4aee835adf4e68fccd9abff457f2 | [
"MIT"
] | 137 | 2020-08-11T16:07:49.000Z | 2022-02-27T10:59:05.000Z | antlir/compiler/items/tests/common.py | baioc/antlir | e3b47407b72c4aee835adf4e68fccd9abff457f2 | [
"MIT"
] | 10 | 2020-09-10T00:01:28.000Z | 2022-03-08T18:00:28.000Z | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
import subprocess
import tempfile
import unittest
from contextlib import contextmanager
from antlir.compiler.requires_provides import (
ProvidesDirectory,
ProvidesFile,
ProvidesSymlink,
)
from antlir.fs_utils import Path
from antlir.nspawn_in_subvol.args import PopenArgs, new_nspawn_opts
from antlir.nspawn_in_subvol.nspawn import run_nspawn
from antlir.subvol_utils import Subvol
from antlir.tests.layer_resource import layer_resource_subvol
from antlir.tests.subvol_helpers import pop_path, render_subvol
from ..common import LayerOpts
# Re-export for legacy reasons
pop_path = pop_path
render_subvol = render_subvol
DEFAULT_STAT_OPTS = ["--user=root", "--group=root", "--mode=0755"]
DUMMY_LAYER_OPTS = LayerOpts(
layer_target="fake target", # Only used by error messages
build_appliance=None,
# For a handful of tests, this must be a boolean value so the layer
# emits it it into /.meta, but the value is not important.
artifacts_may_require_repo=True,
# pyre-fixme[6]: Expected `Mapping[str, str]` for 4th param but got `None`.
target_to_path=None,
# pyre-fixme[6]: Expected `Path` for 5th param but got `None`.
subvolumes_dir=None,
rpm_installer=None,
version_set_override=None,
rpm_repo_snapshot=None,
# pyre-fixme[6]: Expected `frozenset[str]` for 9th param but got
# `List[Variable[_T]]`.
allowed_host_mount_targets=[],
flavor="antlir_test",
)
# This has to be a function because using `importlib` while loading a module
# results in incorrect behavior (I did not debug the specifics).
def get_dummy_layer_opts_ba():
return DUMMY_LAYER_OPTS._replace(
build_appliance=layer_resource_subvol(
__package__, "test-build-appliance"
)
)
def populate_temp_filesystem(img_path):
"Matching Provides are generated by _temp_filesystem_provides"
def p(img_rel_path):
return os.path.join(img_path, img_rel_path)
os.makedirs(p("a/b/c"))
os.makedirs(p("a/d"))
for filepath in ["a/E", "a/d/F", "a/b/c/G"]:
with open(p(filepath), "w") as f:
f.write("Hello, " + filepath)
os.symlink("a", p("h"))
os.symlink("a/E", p("i"))
os.symlink("./a/b", p("j"))
os.symlink("../a", p("h/k"))
os.symlink("/a", p("l"))
os.symlink("/a/E", p("m"))
@contextmanager
def temp_filesystem():
with tempfile.TemporaryDirectory() as td_path:
populate_temp_filesystem(td_path)
yield td_path
def temp_filesystem_provides(p=""):
"Captures what is provided by _temp_filesystem, if installed at `p`"
"inside the image."
return {
ProvidesDirectory(path=Path(f"{p}/a")),
ProvidesDirectory(path=Path(f"{p}/a/b")),
ProvidesDirectory(path=Path(f"{p}/a/b/c")),
ProvidesDirectory(path=Path(f"{p}/a/d")),
ProvidesFile(path=Path(f"{p}/a/E")),
ProvidesFile(path=Path(f"{p}/a/d/F")),
ProvidesFile(path=Path(f"{p}/a/b/c/G")),
ProvidesSymlink(path=Path(f"{p}/h"), target=(Path("a"))),
ProvidesSymlink(path=Path(f"{p}/i"), target=(Path("a/E"))),
ProvidesSymlink(path=Path(f"{p}/j"), target=(Path("./a/b"))),
ProvidesSymlink(path=Path(f"{p}/a/k"), target=(Path("../a"))),
ProvidesSymlink(path=Path(f"{p}/l"), target=(Path("/a"))),
ProvidesSymlink(path=Path(f"{p}/m"), target=(Path("/a/E"))),
}
def run_in_ba(layer: Subvol, cmd) -> subprocess.CompletedProcess:
res, _ = run_nspawn(
new_nspawn_opts(
cmd=cmd,
layer=layer,
),
PopenArgs(
stdout=subprocess.PIPE,
),
)
return res
def getent(layer: Subvol, dbtype: str, name: str) -> bytes:
return run_in_ba(
cmd=["getent", dbtype, name],
layer=layer,
).stdout
class BaseItemTestCase(unittest.TestCase):
def setUp(self): # More output for easier debugging
unittest.util._MAX_LENGTH = 12345
self.maxDiff = 12345
def _check_item(self, i, provides, requires):
self.assertEqual(provides, set(i.provides()))
self.assertEqual(requires, set(i.requires()))
| 31.244604 | 79 | 0.660373 |
2a26f477047c190c66b985ec41373c5a603d1152 | 544 | py | Python | home/forms.py | akash-kd/Robotics_Club_Website | f8ec81a5afc0048bd32ff1f13e928ba9b31f3b97 | [
"MIT"
] | null | null | null | home/forms.py | akash-kd/Robotics_Club_Website | f8ec81a5afc0048bd32ff1f13e928ba9b31f3b97 | [
"MIT"
] | 20 | 2021-10-19T07:07:44.000Z | 2022-02-04T13:19:44.000Z | home/forms.py | akash-kd/Robotics_Club_Website | f8ec81a5afc0048bd32ff1f13e928ba9b31f3b97 | [
"MIT"
] | 3 | 2021-08-23T17:30:57.000Z | 2022-01-15T16:22:29.000Z | from django import forms
class ContactForm(forms.Form):
name=forms.CharField(max_length=100,label='Your Name',widget=forms.TextInput(attrs={'placeholder': 'Your Name'}))
email = forms.EmailField(label='Email',widget=forms.TextInput(attrs={'placeholder': 'Email'}))
body = forms.CharField(min_length=10,max_length=1000,label='Message',widget=forms.Textarea(attrs={'rows':5,'col':2, 'placeholder':'Message'}))
subject = forms.CharField(max_length=100, label='Subject',widget=forms.TextInput(attrs={'placeholder': 'Subject'}))
| 49.454545 | 146 | 0.737132 |
e2ae773e8d11fadc081d9f560eb98e2e1b230d16 | 899 | py | Python | happy-numbers.py | CoderEren/Python-Algorithms | 3100208f8ffddce537908cc4e2090ae125876327 | [
"MIT"
] | null | null | null | happy-numbers.py | CoderEren/Python-Algorithms | 3100208f8ffddce537908cc4e2090ae125876327 | [
"MIT"
] | null | null | null | happy-numbers.py | CoderEren/Python-Algorithms | 3100208f8ffddce537908cc4e2090ae125876327 | [
"MIT"
] | null | null | null | #input an integer
#square its digits and find the sum of squares
#continue with this number
#repeat until either answer is 1 -> happy
#or until you get trapped in a cycle -> unhappy
number = input("Enter a number: ")
numbers_in_recursive = []
def recursive(number):
if number in numbers_in_recursive:
print("The number is an unhappy number!")
else:
digits = []
sum_of_digits = 0
for digit in number:
digits.append(digit)
print("Digits:", digits)
for digit in digits:
squared_digit = int(digit) ** 2
sum_of_digits += int(squared_digit)
print("Sum of digits:", sum_of_digits)
if sum_of_digits == 1:
print("The number is a happy number!")
else:
numbers_in_recursive.append(str(number))
recursive(str(sum_of_digits))
recursive(number)
| 25.685714 | 52 | 0.61624 |
6bcf40c06838225d160c5bd7ffc8ea98b5c1e4eb | 344 | py | Python | predavanje2/slozene_podatkovne_strukture.py | Miillky/uvod_u_programiranje | 209611e38c8fe84c727649df4b868a4278eb77c3 | [
"MIT"
] | null | null | null | predavanje2/slozene_podatkovne_strukture.py | Miillky/uvod_u_programiranje | 209611e38c8fe84c727649df4b868a4278eb77c3 | [
"MIT"
] | null | null | null | predavanje2/slozene_podatkovne_strukture.py | Miillky/uvod_u_programiranje | 209611e38c8fe84c727649df4b868a4278eb77c3 | [
"MIT"
] | null | null | null | import types
jabuka = types.SimpleNamespace(
vrsta="idared",
boja="crvena",
tezina=89
)
print(jabuka.vrsta)
print(jabuka.boja)
print(jabuka.tezina)
jabuka.versta = "granny smith"
del jabuka.boja
jabuka.tezina = 125
print(jabuka.vrsta)
print(jabuka.tezina)
print(type(jabuka))
print(type(jabuka.vrsta))
print(type(jabuka.tezina)) | 16.380952 | 31 | 0.738372 |
5a1b1d7d8a9efbb14af89e5101a7f0ea47fe1ef9 | 3,375 | py | Python | package/zimagi/facade.py | zimagi/zima | d87b3f91e2fa669a77145413582d636d783a0c71 | [
"Apache-2.0"
] | null | null | null | package/zimagi/facade.py | zimagi/zima | d87b3f91e2fa669a77145413582d636d783a0c71 | [
"Apache-2.0"
] | null | null | null | package/zimagi/facade.py | zimagi/zima | d87b3f91e2fa669a77145413582d636d783a0c71 | [
"Apache-2.0"
] | null | null | null | from .command import client as command_api
from .data import client as data_api
class Client(object):
def __init__(self,
token,
host = 'localhost',
command_port = 5123,
data_port = 5323,
user = 'admin',
options_callback = None,
message_callback = None,
encryption_key = None
):
self.command = command_api.Client(token,
host = host,
port = command_port,
user = user,
options_callback = options_callback,
message_callback = message_callback,
encryption_key = encryption_key
)
self.data = data_api.Client(token,
host = host,
port = data_port,
user = user,
encryption_key = encryption_key
)
@property
def actions(self):
return self.command.actions
def get_action_options(self, action):
return self.command.get_options(action)
@property
def data_types(self):
return self.data.data_types
def get_data_options(self, data_type):
return self.data.get_options(data_type)
def list(self, data_type, **options):
return self.data.list(data_type, options)
def get(self, data_type, key, **options):
return self.data.get(data_type, key, options)
def save(self, data_type, key, fields = None, provider = None, **options):
return self.command.save(data_type, key,
fields = fields,
provider = provider,
**options
)
def remove(self, data_type, key, **options):
return self.command.remove(data_type, key, **options)
def clear(self, data_type, **options):
return self.command.clear(data_type, **options)
def values(self, data_type, field_name, **options):
return self.data.values(data_type, field_name, options)
def count(self, data_type, field_name, **options):
return self.data.count(data_type, field_name, options)
def download(self, dataset_name):
return self.data.download(dataset_name)
def execute(self, action, **options):
return self.command.execute(action, **options)
def run_task(self, module_name, task_name, config = None, **options):
return self.command.run_task(module_name, task_name,
config = config,
**options
)
def run_profile(self, module_name, profile_name, config = None, components = None, **options):
return self.command.run_profile(module_name, profile_name,
config = config,
components = components,
**options
)
def destroy_profile(self, module_name, profile_name, config = None, components = None, **options):
return self.command.destroy_profile(module_name, profile_name,
config = config,
components = components,
**options
)
def run_imports(self, names = None, tags = None, **options):
return self.command.run_imports(names, tags, **options)
def run_calculations(self, names = None, tags = None, **options):
return self.command.run_calculations(names, tags, **options)
def __getattr__(self, attr):
def enclosure(**options):
return self.execute(attr.replace('__', '/'), **options)
return enclosure
| 29.605263 | 102 | 0.616593 |
313c7754ec52a77e1dcc6724c731baaaee8a2aac | 22,653 | py | Python | anomaly_detection/anomaly_detect_ts.py | kingbase/AnomalyDetection | 14e6d029adf906791fb5d4a6c06251c69e3ca20e | [
"Apache-2.0"
] | null | null | null | anomaly_detection/anomaly_detect_ts.py | kingbase/AnomalyDetection | 14e6d029adf906791fb5d4a6c06251c69e3ca20e | [
"Apache-2.0"
] | null | null | null | anomaly_detection/anomaly_detect_ts.py | kingbase/AnomalyDetection | 14e6d029adf906791fb5d4a6c06251c69e3ca20e | [
"Apache-2.0"
] | null | null | null | """
Description:
A technique for detecting anomalies in seasonal univariate time
series where the input is a series of <timestamp, count> pairs.
Usage:
anomaly_detect_ts(x, max_anoms=0.1, direction="pos", alpha=0.05, only_last=None,
threshold="None", e_value=False, longterm=False, piecewise_median_period_weeks=2,
plot=False, y_log=False, xlabel="", ylabel="count", title=None, verbose=False)
Arguments:
x: Time series as a two column data frame where the first column
consists of the timestamps and the second column consists of
the observations.
max_anoms: Maximum number of anomalies that S-H-ESD will detect as a
percentage of the data.
direction: Directionality of the anomalies to be detected. Options are:
"pos" | "neg" | "both".
alpha: The level of statistical significance with which to accept or
reject anomalies.
only_last: Find and report anomalies only within the last day or hr in
the time series. None | "day" | "hr".
threshold: Only report positive going anoms above the threshold
specified. Options are: None | "med_max" | "p95" |
"p99".
e_value: Add an additional column to the anoms output containing the
expected value.
longterm: Increase anom detection efficacy for time series that are
greater than a month. See Details below.
piecewise_median_period_weeks: The piecewise median time window as
described in Vallis, Hochenbaum, and Kejariwal (2014).
Defaults to 2.
plot: A flag indicating if a plot with both the time series and the
estimated anoms, indicated by circles, should also be
returned.
y_log: Apply log scaling to the y-axis. This helps with viewing
plots that have extremely large positive anomalies relative
to the rest of the data.
xlabel: X-axis label to be added to the output plot.
ylabel: Y-axis label to be added to the output plot.
title: Title for the output plot.
verbose: Enable debug messages
resampling: whether ms or sec granularity should be resampled to min granularity.
Defaults to False.
period_override: Override the auto-generated period
Defaults to None
Details:
"longterm" This option should be set when the input time series
is longer than a month. The option enables the approach described
in Vallis, Hochenbaum, and Kejariwal (2014).
"threshold" Filter all negative anomalies and those anomalies
whose magnitude is smaller than one of the specified thresholds
which include: the median of the daily max values (med_max), the
95th percentile of the daily max values (p95), and the 99th
percentile of the daily max values (p99).
Value:
The returned value is a list with the following components.
anoms: Data frame containing timestamps, values, and optionally
expected values.
plot: A graphical object if plotting was requested by the user. The
plot contains the estimated anomalies annotated on the input
time series.
"threshold" Filter all negative anomalies and those anomalies
whose magnitude is smaller than one of the specified thresholds
which include: the median of the daily max values (med_max), the
95th percentile of the daily max values (p95), and the 99th
percentile of the daily max values (p99).
Value:
The returned value is a list with the following components.
anoms: Data frame containing timestamps, values, and optionally
expected values.
plot: A graphical object if plotting was requested by the user. The
plot contains the estimated anomalies annotated on the input
time series.
One can save "anoms" to a file in the following fashion:
write.csv(<return list name>[["anoms"]], file=<filename>)
One can save "plot" to a file in the following fashion:
ggsave(<filename>, plot=<return list name>[["plot"]])
References:
Vallis, O., Hochenbaum, J. and Kejariwal, A., (2014) "A Novel
Technique for Long-Term Anomaly Detection in the Cloud", 6th
USENIX, Philadelphia, PA.
Rosner, B., (May 1983), "Percentage Points for a Generalized ESD
Many-Outlier Procedure" , Technometrics, 25(2), pp. 165-172.
See Also:
anomaly_detect_vec
Examples:
# To detect all anomalies
anomaly_detect_ts(raw_data, max_anoms=0.02, direction="both", plot=True)
# To detect only the anomalies in the last day, run the following:
anomaly_detect_ts(raw_data, max_anoms=0.02, direction="both", only_last="day", plot=True)
# To detect only the anomalies in the last hr, run the following:
anomaly_detect_ts(raw_data, max_anoms=0.02, direction="both", only_last="hr", plot=True)
# To detect only the anomalies in the last hr and resample data of ms or sec granularity:
anomaly_detect_ts(raw_data, max_anoms=0.02, direction="both", only_last="hr", plot=True, resampling=True)
# To detect anomalies in the last day specifying a period of 1440
anomaly_detect_ts(raw_data, max_anoms=0.02, direction="both", only_last="hr", period_override=1440)
"""
import numpy as np
import scipy as sp
import pandas as pd
import datetime
import statsmodels.api as sm
import logging
logger = logging.getLogger(__name__)
def _handle_granularity_error(level):
"""
Raises ValueError with detailed error message if one of the two situations is true:
1. calculated granularity is less than minute (sec or ms)
2. resampling is not enabled for situations where calculated granularity < min
level : String
the granularity that is below the min threshold
"""
e_message = '%s granularity is not supported. Ensure granularity => minute or enable resampling' % level
raise ValueError(e_message)
def _resample_to_min(data, period_override=None):
"""
Resamples a data set to the min level of granularity
data : pandas DataFrame
input Pandas DataFrame
period_override : int
indicates whether resampling should be done with overridden value instead of min (1440)
"""
data = data.resample('60s', label='right').sum()
if _override_period(period_override):
period = period_override
else:
period = 1440
return (data, period)
def _override_period(period_override):
"""
Indicates whether period can be overridden if the period derived from granularity does
not match the generated period.
period_override : int
the user-specified period that overrides the value calculated from granularity
"""
return period_override is not None
def _get_period(gran_period, period_arg=None):
"""
Returns the generated period or overridden period depending upon the period_arg
gran_period : int
the period generated from the granularity
period_arg : the period override value that is either None or an int
the period to override the period generated from granularity
"""
if _override_period(period_arg):
return period_arg
else:
return gran_period
def _get_data_tuple(raw_data, period_override, resampling=False):
"""
Generates a tuple consisting of processed input data, a calculated or overridden period, and granularity
raw_data : pandas DataFrame
input data
period_override : int
period specified in the anomaly_detect_ts parameter list, None if it is not provided
resampling : True | False
indicates whether the raw_data should be resampled to a supporting granularity, if applicable
"""
data = raw_data.sort_index()
timediff = _get_time_diff(data)
if timediff.days > 0:
period = _get_period(7, period_override)
granularity = 'day'
elif timediff.seconds / 60 / 60 >= 1:
granularity = 'hr'
period = _get_period(24, period_override)
elif timediff.seconds / 60 >= 1:
granularity = 'min'
period = _get_period(1440, period_override)
#elif timediff.seconds > 0:
# granularity = 'sec'
elif timediff.seconds > 0:
granularity = 'sec'
period = _get_period(1440*60, period_override)
'''
Aggregate data to minute level of granularity if data stream granularity is sec and
resampling=True. If resampling=False, raise ValueError
'''
#if resampling is True:
# period = _resample_to_min(data, period_override)
#else:
# _handle_granularity_error('sec')
else:
'''
Aggregate data to minute level of granularity if data stream granularity is ms and
resampling=True. If resampling=False, raise ValueError
'''
if resampling is True:
data, period = _resample_to_min(data, period_override)
granularity = None
else:
_handle_granularity_error('ms')
return (data, period, granularity)
def _get_time_diff(data):
"""
Generates the time difference used to determine granularity and
to generate the period
data : pandas DataFrame
composed of input data
"""
return data.index[1] - data.index[0]
def _get_max_anoms(data, max_anoms):
"""
Returns the max_anoms parameter used for S-H-ESD time series anomaly detection
data : pandas DataFrame
composed of input data
max_anoms : float
the input max_anoms
"""
if max_anoms == 0:
logger.warning('0 max_anoms results in max_outliers being 0.')
return 1 / data.size if max_anoms < 1 / data.size else max_anoms
def _process_long_term_data(data, period, granularity, piecewise_median_period_weeks):
"""
Processes result set when longterm is set to true
data : list of floats
the result set of anoms
period : int
the calculated or overridden period value
granularity : string
the calculated or overridden granularity
piecewise_median_period_weeks : int
used to determine days and observations per period
"""
# Pre-allocate list with size equal to the number of piecewise_median_period_weeks chunks in x + any left over chunk
# handle edge cases for daily and single column data period lengths
num_obs_in_period = period * piecewise_median_period_weeks + 1 if granularity == 'day' else period * 7 * piecewise_median_period_weeks
num_days_in_period = (7 * piecewise_median_period_weeks) + 1 if granularity == 'day' else (7 * piecewise_median_period_weeks)
all_data = []
# Subset x into piecewise_median_period_weeks chunks
for i in range(1, data.size + 1, num_obs_in_period):
start_date = data.index[i]
# if there is at least 14 days left, subset it, otherwise subset last_date - 14 days
end_date = start_date + datetime.timedelta(days=num_days_in_period)
if end_date < data.index[-1]:
all_data.append(data.loc[lambda x: (x.index >= start_date) & (x.index <= end_date)])
else:
all_data.append(data.loc[lambda x: x.index >= data.index[-1] - datetime.timedelta(days=num_days_in_period)])
return all_data
def _get_only_last_results(data, all_anoms, granularity, only_last):
"""
Returns the results from the last day or hour only
data : pandas DataFrame
input data set
all_anoms : list of floats
all of the anomalies returned by the algorithm
granularity : string day | hr | min
The supported granularity value
only_last : string day | hr
The subset of anomalies to be returned
"""
start_date = data.index[-1] - datetime.timedelta(days=7)
start_anoms = data.index[-1] - datetime.timedelta(days=1)
if only_last == 'hr':
# We need to change start_date and start_anoms for the hourly only_last option
start_date = datetime.datetime.combine((data.index[-1] - datetime.timedelta(days=2)).date(), datetime.time.min)
start_anoms = data.index[-1] - datetime.timedelta(hours=1)
# subset the last days worth of data
x_subset_single_day = data.loc[data.index > start_anoms]
# When plotting anoms for the last day only we only show the previous weeks data
x_subset_week = data.loc[lambda df: (df.index <= start_anoms) & (df.index > start_date)]
return all_anoms.loc[all_anoms.index >= x_subset_single_day.index[0]]
def _get_plot_breaks(granularity, only_last):
"""
Generates the breaks used in plotting
granularity : string
the supported granularity value
only_last : True | False
indicates whether only the last day or hour is returned and to be plotted
"""
if granularity == 'day':
breaks = 3 * 12
elif only_last == 'day':
breaks = 12
else:
breaks = 3
return breaks
def _perform_threshold_filter(anoms, periodic_max, threshold):
"""
Filters the list of anomalies per the threshold filter
anoms : list of floats
the anoms returned by the algorithm
periodic_max : float
calculated daily max value
threshold : med_max" | "p95" | "p99"
user-specified threshold value used to filter anoms
"""
if threshold == 'med_max':
thresh = periodic_max.median()
elif threshold == 'p95':
thresh = periodic_max.quantile(0.95)
elif threshold == 'p99':
thresh = periodic_max.quantile(0.99)
else:
raise AttributeError('Invalid threshold, threshold options are None | med_max | p95 | p99')
return anoms.loc[anoms.values >= thresh]
def _get_max_outliers(data, max_percent_anomalies):
"""
Calculates the max_outliers for an input data set
data : pandas DataFrame
the input data set
max_percent_anomalies : float
the input maximum number of anomalies per percent of data set values
"""
max_outliers = int(np.trunc(data.size * max_percent_anomalies))
assert max_outliers, 'With longterm=True, AnomalyDetection splits the data into 2 week periods by default. You have {0} observations in a period, which is too few. Set a higher piecewise_median_period_weeks.'.format(data.size)
return max_outliers
def _get_decomposed_data_tuple(data, num_obs_per_period):
"""
Returns a tuple consisting of two versions of the input data set: seasonally-decomposed and smoothed
data : pandas DataFrame
the input data set
num_obs_per_period : int
the number of observations in each period
"""
decomposed = sm.tsa.seasonal_decompose(data, freq=num_obs_per_period, two_sided=False)
smoothed = data - decomposed.resid.fillna(0)
data = data - decomposed.seasonal - data.mean()
return (data, smoothed)
def anomaly_detect_ts(x, max_anoms=0.1, direction="pos", alpha=0.05, only_last=None,
threshold=None, e_value=False, longterm=False, piecewise_median_period_weeks=2,
plot=False, y_log=False, xlabel="", ylabel="count", title='shesd output: ', verbose=False,
dropna=False, resampling=False, period_override=None):
if verbose:
logger.info("Validating input parameters")
# validation
assert isinstance(x, pd.Series), 'Data must be a series(Pandas.Series)'
assert x.values.dtype in [int, float], 'Values of the series must be number'
assert x.index.dtype == np.dtype('datetime64[ns]'), 'Index of the series must be datetime'
assert max_anoms <= 0.49 and max_anoms >= 0, 'max_anoms must be non-negative and less than 50% '
assert direction in ['pos', 'neg', 'both'], 'direction options: pos | neg | both'
assert only_last in [None, 'day', 'hr'], 'only_last options: None | day | hr'
assert threshold in [None, 'med_max', 'p95', 'p99'], 'threshold options: None | med_max | p95 | p99'
assert piecewise_median_period_weeks >= 2, 'piecewise_median_period_weeks must be greater than 2 weeks'
if verbose:
logger.info('Completed validation of input parameters')
if alpha < 0.01 or alpha > 0.1:
logger.warning('alpha is the statistical significance and is usually between 0.01 and 0.1')
# TODO Allow x.index to be number, here we can convert it to datetime
data, period, granularity = _get_data_tuple(x, period_override, resampling)
if granularity is 'day':
num_days_per_line = 7
# TODO determine why this is here
only_last = 'day' if only_last == 'hr' else only_last
max_anoms = _get_max_anoms(data, max_anoms)
# If longterm is enabled, break the data into subset data frames and store in all_data
if longterm:
all_data = _process_long_term_data(data, period, granularity, piecewise_median_period_weeks)
else:
all_data = [data]
all_anoms = pd.Series()
if e_value:
seasonal_plus_trend = pd.Series()
# Detect anomalies on all data (either entire data in one-pass, or in 2 week blocks if longterm=True)
for series in all_data:
shesd = _detect_anoms(series, k=max_anoms, alpha=alpha, num_obs_per_period=period, use_decomp=True,
use_esd=False, direction=direction, verbose=verbose)
shesd_anoms = shesd['anoms']
shesd_stl = shesd['stl']
# -- Step 3: Use detected anomaly timestamps to extract the actual anomalies (timestamp and value) from the data
anoms = pd.Series() if shesd_anoms.empty else series.loc[shesd_anoms.index]
# Filter the anomalies using one of the thresholding functions if applicable
if threshold:
# Calculate daily max values
periodic_max = data.resample('1D').max()
anoms = _perform_threshold_filter(anoms, periodic_max, threshold)
all_anoms = all_anoms.append(anoms)
if e_value:
seasonal_plus_trend = seasonal_plus_trend.append(shesd_stl)
# De-dupe
all_anoms.drop_duplicates(inplace=True)
if e_value:
seasonal_plus_trend.drop_duplicates(inplace=True)
# If only_last is specified, create a subset of the data corresponding to the most recent day or hour
if only_last:
all_anoms = _get_only_last_results(data, all_anoms, granularity, only_last)
# If there are no anoms, log it and return an empty anoms result
if all_anoms.empty:
if verbose:
logger.info('No anomalies detected.')
return {
'anoms': pd.Series(),
'plot': None
}
if plot:
#TODO additional refactoring and logic needed to support plotting
num_days_per_line
#breaks = _get_plot_breaks(granularity, only_last)
#x_subset_week
raise Exception('TODO: Unsupported now')
return {
'anoms': all_anoms,
'expected': seasonal_plus_trend if e_value else None,
'plot': 'TODO' if plot else None
}
def _detect_anoms(data, k=0.49, alpha=0.05, num_obs_per_period=None,
use_decomp=True, use_esd=False, direction="pos", verbose=False):
"""
Detects anomalies in a time series using S-H-ESD.
Args:
data: Time series to perform anomaly detection on.
k: Maximum number of anomalies that S-H-ESD will detect as a percentage of the data.
alpha: The level of statistical significance with which to accept or reject anomalies.
num_obs_per_period: Defines the number of observations in a single period, and used during seasonal decomposition.
use_decomp: Use seasonal decomposition during anomaly detection.
use_esd: Uses regular ESD instead of hybrid-ESD. Note hybrid-ESD is more statistically robust.
one_tail: If TRUE only positive or negative going anomalies are detected depending on if upper_tail is TRUE or FALSE.
upper_tail: If TRUE and one_tail is also TRUE, detect only positive going (right-tailed) anomalies. If FALSE and one_tail is TRUE, only detect negative (left-tailed) anomalies.
verbose: Additionally printing for debugging.
Returns:
A list containing the anomalies (anoms) and decomposition components (stl).
"""
# validation
assert num_obs_per_period, "must supply period length for time series decomposition"
assert direction in ['pos', 'neg', 'both'], 'direction options: pos | neg | both'
assert data.size >= num_obs_per_period * 2, 'Anomaly detection needs at least 2 periods worth of data'
assert data[data.isnull()].empty, 'Data contains NA. We suggest replacing NA with interpolated values before detecting anomaly'
# conversion
one_tail = True if direction in ['pos', 'neg'] else False
upper_tail = True if direction in ['pos', 'both'] else False
# -- Step 1: Decompose data. This returns a univariate remainder which will be used for anomaly detection. Optionally, we might NOT decompose.
# Note: R use stl, but here we will use MA, the result may be different TODO.. Here need improvement
#decomposed = sm.tsa.seasonal_decompose(data, freq=num_obs_per_period, two_sided=False)
#smoothed = data - decomposed.resid.fillna(0)
#data = data - decomposed.seasonal - data.mean()
data, smoothed = _get_decomposed_data_tuple(data, num_obs_per_period)
max_outliers = _get_max_outliers(data, k)
R_idx = pd.Series()
n = data.size
# Compute test statistic until r=max_outliers values have been
# removed from the sample.
for i in range(1, max_outliers + 1):
if verbose:
logger.info(i, '/', max_outliers, ' completed')
mad = np.mean(np.absolute(data - np.mean(data)))
if not mad:
break
if not one_tail:
ares = abs(data - data.median())
elif upper_tail:
ares = data - data.median()
else:
ares = data.median() - data
ares = ares / mad
max_ares = ares.max()
tmp_anom_index = ares[ares.values == max_ares].index
cand = pd.Series(data.loc[tmp_anom_index], index=tmp_anom_index)
data = data.drop(tmp_anom_index)
# Compute critical value.
p = 1 - alpha / (n - i + 1) if one_tail else (1 - alpha / (2 * (n - i + 1)))
t = sp.stats.t.ppf(p, n - i - 1)
lam = t * (n - i) / np.sqrt((n - i - 1 + t ** 2) * (n - i + 1))
if max_ares > lam:
R_idx = R_idx.append(cand)
else:
break
return {
'anoms': R_idx,
'stl': smoothed
}
| 38.656997 | 230 | 0.676378 |
957c620cab09a4b482748d713a28325a747b2f48 | 1,374 | py | Python | normalize_repos/branch_protections.py | shubhanshu02/ccos-scripts | 2411281cc6b7124f8b18a8ce044b9bd51394051b | [
"MIT"
] | 14 | 2020-02-07T22:46:02.000Z | 2021-02-28T16:10:16.000Z | normalize_repos/branch_protections.py | shubhanshu02/ccos-scripts | 2411281cc6b7124f8b18a8ce044b9bd51394051b | [
"MIT"
] | 83 | 2020-02-07T15:57:23.000Z | 2022-02-14T16:04:33.000Z | normalize_repos/branch_protections.py | shubhanshu02/ccos-scripts | 2411281cc6b7124f8b18a8ce044b9bd51394051b | [
"MIT"
] | 32 | 2020-02-24T21:08:40.000Z | 2021-04-12T12:22:32.000Z | EXEMPT_REPOSITORIES = [
# non-engineering repo
"australian-chapter",
# non-engineering repo
"cc-cert-core",
# non-engineering repo
"cc-cert-edu",
# non-engineering repo
"cc-cert-gov",
# non-engineering repo
"cc-cert-lib",
# exempted to allow transifex updates
"cc.i18n",
# exempted to allow community maintainer to self-merge PRs
"ccsearch-browser-extension",
# exempted for bot pushes to default branch
"creativecommons.github.io-source",
# exempted for bot pushes to default branch
"creativecommons.github.io",
# non-engineering repo
"global-network-strategy",
# non-engineering repo
"network-platforms",
# non-engineering repo
"sre-wiki-js",
# non-engineering repo
"tech-support",
]
REQUIRED_STATUS_CHECK_MAP = {
"cccatalog-api": ["Style", "Tests"],
"cccatalog-frontend": ["Run CI tests"],
"creativecommons.github.io-source": ["continuous-integration/travis-ci"],
"fonts": [
"Lint",
"Unit tests",
"Build",
"netlify/cc-fonts/deploy-preview",
],
"vocabulary": [
"Lint",
"Unit tests",
"Build",
"netlify/cc-vocabulary/deploy-preview",
],
"vue-vocabulary": [
"Lint",
"Unit tests",
"Build",
"netlify/cc-vue-vocabulary/deploy-preview",
],
}
| 25.924528 | 77 | 0.604803 |
ec6c0199d717d542d550aa73d814ba9ee30b4a95 | 950 | py | Python | Engine/Tools/install_dependencies.py | ekokturk/ZeronEngine | b0b756a0c8eb0ac09ee288a936857bda607bb3ef | [
"MIT"
] | null | null | null | Engine/Tools/install_dependencies.py | ekokturk/ZeronEngine | b0b756a0c8eb0ac09ee288a936857bda607bb3ef | [
"MIT"
] | null | null | null | Engine/Tools/install_dependencies.py | ekokturk/ZeronEngine | b0b756a0c8eb0ac09ee288a936857bda607bb3ef | [
"MIT"
] | null | null | null | import os, sys, glob, subprocess
script_dir = os.path.abspath(os.path.dirname(sys.argv[0]))
dependency_dir = os.path.join(script_dir, '../ThirdParty/')
os.chdir(dependency_dir)
print("\n================== UPDATING ENGINE DEPENDENCIES ==================\n")
thirdparty_dirs = glob.glob(os.path.realpath(f"{dependency_dir}/*/"))
dependency_count = 0
success_count = 0
for d in thirdparty_dirs:
script_path = os.path.join(d,"install.py")
if os.path.exists(script_path):
dependency_count += 1
print("---------------------------------------------------------------------")
error = subprocess.call(f'py -3 {script_path}')
if error == 0:
success_count +=1
print("========================================================================")
print(f"Engine dependencies updated. Success: {success_count}/{dependency_count}")
print("========================================================================")
| 35.185185 | 85 | 0.507368 |
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