hexsha string | size int64 | ext string | lang string | max_stars_repo_path string | max_stars_repo_name string | max_stars_repo_head_hexsha string | max_stars_repo_licenses list | max_stars_count int64 | max_stars_repo_stars_event_min_datetime string | max_stars_repo_stars_event_max_datetime string | max_issues_repo_path string | max_issues_repo_name string | max_issues_repo_head_hexsha string | max_issues_repo_licenses list | max_issues_count int64 | max_issues_repo_issues_event_min_datetime string | max_issues_repo_issues_event_max_datetime string | max_forks_repo_path string | max_forks_repo_name string | max_forks_repo_head_hexsha string | max_forks_repo_licenses list | max_forks_count int64 | max_forks_repo_forks_event_min_datetime string | max_forks_repo_forks_event_max_datetime string | content string | avg_line_length float64 | max_line_length int64 | alphanum_fraction float64 | qsc_code_num_words_quality_signal int64 | qsc_code_num_chars_quality_signal float64 | qsc_code_mean_word_length_quality_signal float64 | qsc_code_frac_words_unique_quality_signal float64 | qsc_code_frac_chars_top_2grams_quality_signal float64 | qsc_code_frac_chars_top_3grams_quality_signal float64 | qsc_code_frac_chars_top_4grams_quality_signal float64 | qsc_code_frac_chars_dupe_5grams_quality_signal float64 | qsc_code_frac_chars_dupe_6grams_quality_signal float64 | qsc_code_frac_chars_dupe_7grams_quality_signal float64 | qsc_code_frac_chars_dupe_8grams_quality_signal float64 | qsc_code_frac_chars_dupe_9grams_quality_signal float64 | qsc_code_frac_chars_dupe_10grams_quality_signal float64 | qsc_code_frac_chars_replacement_symbols_quality_signal float64 | qsc_code_frac_chars_digital_quality_signal float64 | qsc_code_frac_chars_whitespace_quality_signal float64 | qsc_code_size_file_byte_quality_signal float64 | qsc_code_num_lines_quality_signal float64 | qsc_code_num_chars_line_max_quality_signal float64 | qsc_code_num_chars_line_mean_quality_signal float64 | qsc_code_frac_chars_alphabet_quality_signal float64 | qsc_code_frac_chars_comments_quality_signal float64 | qsc_code_cate_xml_start_quality_signal float64 | qsc_code_frac_lines_dupe_lines_quality_signal float64 | qsc_code_cate_autogen_quality_signal float64 | qsc_code_frac_lines_long_string_quality_signal float64 | qsc_code_frac_chars_string_length_quality_signal float64 | qsc_code_frac_chars_long_word_length_quality_signal float64 | qsc_code_frac_lines_string_concat_quality_signal float64 | qsc_code_cate_encoded_data_quality_signal float64 | qsc_code_frac_chars_hex_words_quality_signal float64 | qsc_code_frac_lines_prompt_comments_quality_signal float64 | qsc_code_frac_lines_assert_quality_signal float64 | qsc_codepython_cate_ast_quality_signal float64 | qsc_codepython_frac_lines_func_ratio_quality_signal float64 | qsc_codepython_cate_var_zero_quality_signal bool | qsc_codepython_frac_lines_pass_quality_signal float64 | qsc_codepython_frac_lines_import_quality_signal float64 | qsc_codepython_frac_lines_simplefunc_quality_signal float64 | qsc_codepython_score_lines_no_logic_quality_signal float64 | qsc_codepython_frac_lines_print_quality_signal float64 | qsc_code_num_words int64 | qsc_code_num_chars int64 | qsc_code_mean_word_length int64 | qsc_code_frac_words_unique null | qsc_code_frac_chars_top_2grams int64 | qsc_code_frac_chars_top_3grams int64 | qsc_code_frac_chars_top_4grams int64 | qsc_code_frac_chars_dupe_5grams int64 | qsc_code_frac_chars_dupe_6grams int64 | qsc_code_frac_chars_dupe_7grams int64 | qsc_code_frac_chars_dupe_8grams int64 | qsc_code_frac_chars_dupe_9grams int64 | qsc_code_frac_chars_dupe_10grams int64 | qsc_code_frac_chars_replacement_symbols int64 | qsc_code_frac_chars_digital int64 | qsc_code_frac_chars_whitespace int64 | qsc_code_size_file_byte int64 | qsc_code_num_lines int64 | qsc_code_num_chars_line_max int64 | qsc_code_num_chars_line_mean int64 | qsc_code_frac_chars_alphabet int64 | qsc_code_frac_chars_comments int64 | qsc_code_cate_xml_start int64 | qsc_code_frac_lines_dupe_lines int64 | qsc_code_cate_autogen int64 | qsc_code_frac_lines_long_string int64 | qsc_code_frac_chars_string_length int64 | qsc_code_frac_chars_long_word_length int64 | qsc_code_frac_lines_string_concat null | qsc_code_cate_encoded_data int64 | qsc_code_frac_chars_hex_words int64 | qsc_code_frac_lines_prompt_comments int64 | qsc_code_frac_lines_assert int64 | qsc_codepython_cate_ast int64 | qsc_codepython_frac_lines_func_ratio int64 | qsc_codepython_cate_var_zero int64 | qsc_codepython_frac_lines_pass int64 | qsc_codepython_frac_lines_import int64 | qsc_codepython_frac_lines_simplefunc int64 | qsc_codepython_score_lines_no_logic int64 | qsc_codepython_frac_lines_print int64 | effective string | hits int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
b63f1d93e6c8f616eb2e7b7b5c55b606f3632d4d | 1,668 | py | Python | testsuite/compatibleone-testsuite.py | MarouenMechtri/accords-platform-1 | 4f950fffd9fbbf911840cc5ad0fe5b5a331edf42 | [
"Apache-2.0"
] | 1 | 2015-02-28T21:25:54.000Z | 2015-02-28T21:25:54.000Z | testsuite/compatibleone-testsuite.py | MarouenMechtri/compatibleone | 6e1be42ba023bb64421073d139dc57bb0386b180 | [
"Apache-2.0"
] | null | null | null | testsuite/compatibleone-testsuite.py | MarouenMechtri/compatibleone | 6e1be42ba023bb64421073d139dc57bb0386b180 | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/env python
# vim: set et sw=4 ts=4 ai:
from utils import *
# Ensure correct directories
from dirs import *
# Basic checks on all binaries
from basic.accords import *
from basic.cobroker import *
from basic.cocheck import *
from basic.cocommand import *
from basic.coparser import *
from basic.coplatform import *
from basic.coprovider import *
from basic.coprovision import *
from basic.coresolver import *
from basic.costart import *
from basic.costatus import *
from basic.costop import *
from basic.command import *
from basic.parser import *
from basic.azprocci import *
from basic.broker import *
from basic.coees import *
from basic.cops import *
from basic.coips import *
from basic.comons import *
from basic.conets import *
from basic.conagios import *
from basic.coobas import *
from basic.cool import *
from basic.cosacs import *
from basic.cosched import *
from basic.coss import *
from basic.dcprocci import *
from basic.paasprocci import *
from basic.copaas import *
from basic.ezvm import *
# from basic.example import *
from basic.fileserver import *
from basic.onprocci import *
from basic.osocciprocci import *
from basic.osprocci import *
from basic.paprocci import *
from basic.procci import *
from basic.publisher import *
from basic.slam import *
from basic.testaz import *
from basic.testcb import *
from basic.testdc import *
from basic.teston import *
from basic.testos import *
# from basic.testosocci import *
from basic.testresolver import *
# Check platform basic running
from platform.start import *
from platform.status import *
from platform.stop import *
import unittest
if __name__ == '__main__':
unittest.main()
| 25.272727 | 32 | 0.77458 | 237 | 1,668 | 5.417722 | 0.337553 | 0.373832 | 0.537383 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.001411 | 0.15048 | 1,668 | 65 | 33 | 25.661538 | 0.904728 | 0.113909 | 0 | 0 | 0 | 0 | 0.005438 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.962264 | 0 | 0.962264 | 0 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
b6615229c3d6c073a40c0794264cc2f2d4f07067 | 875 | py | Python | test/nr/util/algorithm/test_longest_common_substring.py | NiklasRosenstein/python-nr.util | 087f2410d38006c1005a5fb330c47a56bcdb2279 | [
"MIT"
] | null | null | null | test/nr/util/algorithm/test_longest_common_substring.py | NiklasRosenstein/python-nr.util | 087f2410d38006c1005a5fb330c47a56bcdb2279 | [
"MIT"
] | 3 | 2022-02-16T13:17:28.000Z | 2022-03-14T15:28:41.000Z | test/nr/util/algorithm/test_longest_common_substring.py | NiklasRosenstein/python-nr.util | 087f2410d38006c1005a5fb330c47a56bcdb2279 | [
"MIT"
] | null | null | null |
from nr.util.algorithm import longest_common_substring
def test_longest_common_substring():
assert longest_common_substring('abcdefg', 'gcdefika') == 'cdef'
assert longest_common_substring('abcdefg', 'gcdefika', start_only=True) == ''
assert longest_common_substring('nr.util.parsing', 'nr.util') == 'nr.util'
assert longest_common_substring('nr.util', 'nr.util.parsing') == 'nr.util'
assert longest_common_substring('nr.util', 'nr.util.parsing', start_only=True) == 'nr.util'
assert longest_common_substring('foo', 'bar') == ''
assert longest_common_substring('foo', 'barometer') == 'o'
assert longest_common_substring(['a', 'b'], ['a', 'b', 'c']) == ['a', 'b']
assert longest_common_substring(['a', 'b'], ['a', 'b', 'c'], ['f', 'b', 'c']) == ['b']
assert longest_common_substring(['a', 'b'], ['a', 'b', 'c'], ['f', 'b', 'c'], start_only=True) == []
| 51.470588 | 102 | 0.657143 | 117 | 875 | 4.675214 | 0.222222 | 0.285192 | 0.482633 | 0.511883 | 0.756856 | 0.670932 | 0.389397 | 0.389397 | 0.389397 | 0.329068 | 0 | 0 | 0.113143 | 875 | 16 | 103 | 54.6875 | 0.704897 | 0 | 0 | 0 | 0 | 0 | 0.187643 | 0 | 0 | 0 | 0 | 0 | 0.833333 | 1 | 0.083333 | true | 0 | 0.083333 | 0 | 0.166667 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
b666724ee76da6d241317b9303ca135fa901737a | 124 | py | Python | mlthon/tree.py | pritishmishra703/MLthon | 518faa2aaa0e3a0f81f638710b1e43fca122badf | [
"MIT"
] | 1 | 2022-02-03T03:18:06.000Z | 2022-02-03T03:18:06.000Z | mlthon/tree.py | pritishmishra703/MLthon | 518faa2aaa0e3a0f81f638710b1e43fca122badf | [
"MIT"
] | null | null | null | mlthon/tree.py | pritishmishra703/MLthon | 518faa2aaa0e3a0f81f638710b1e43fca122badf | [
"MIT"
] | null | null | null | import numpy as np
class DecisionTreeClassifier:
def __init__(self, criterion='gini', max_depth=None, ):
pass
| 17.714286 | 59 | 0.701613 | 15 | 124 | 5.466667 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.209677 | 124 | 6 | 60 | 20.666667 | 0.836735 | 0 | 0 | 0 | 0 | 0 | 0.032258 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0.25 | 0.25 | 0 | 0.75 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 5 |
b689ef03cb13020ecb77f11275071a77e1ae8330 | 169 | py | Python | conditional_mutual_information/CMI_Est/Util.py | martinmamql/conditional_infonce | 7c4ac4138ce165720578443eb891c59e10a8b262 | [
"MIT"
] | null | null | null | conditional_mutual_information/CMI_Est/Util.py | martinmamql/conditional_infonce | 7c4ac4138ce165720578443eb891c59e10a8b262 | [
"MIT"
] | null | null | null | conditional_mutual_information/CMI_Est/Util.py | martinmamql/conditional_infonce | 7c4ac4138ce165720578443eb891c59e10a8b262 | [
"MIT"
] | null | null | null |
import numpy as np
def get_true_mi(syn_file_cat, z_dim):
cmi_est = np.load('../data/cat{}/ksg_gt.dz{}.npy'.format(syn_file_cat, z_dim))
return float(cmi_est)
| 21.125 | 82 | 0.698225 | 33 | 169 | 3.242424 | 0.727273 | 0.130841 | 0.186916 | 0.205607 | 0.261682 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.142012 | 169 | 7 | 83 | 24.142857 | 0.737931 | 0 | 0 | 0 | 0 | 0 | 0.172619 | 0.172619 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.25 | 0 | 0.75 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 5 |
b69eff673e0afc110728e29dd6fee993070bd9dc | 462 | py | Python | parse_id/models.py | wkpalan/interpro_rest | a603d91734d9319e69c9a79a9eb5e34e216d913f | [
"MIT"
] | null | null | null | parse_id/models.py | wkpalan/interpro_rest | a603d91734d9319e69c9a79a9eb5e34e216d913f | [
"MIT"
] | null | null | null | parse_id/models.py | wkpalan/interpro_rest | a603d91734d9319e69c9a79a9eb5e34e216d913f | [
"MIT"
] | null | null | null | from django.db import models
# Create your models here.
class id_desc(models.Model):
db_id = models.CharField(max_length=50,primary_key=True)
db = models.CharField(max_length=100)
id_desc = models.CharField(max_length=1000)
def __str__(self):
return self.db
class upload(models.Model):
database = models.CharField(max_length=100)
file_url = models.CharField(max_length=300)
def __str__(self):
return self.database
| 25.666667 | 60 | 0.718615 | 66 | 462 | 4.757576 | 0.454545 | 0.238854 | 0.286624 | 0.382166 | 0.299363 | 0 | 0 | 0 | 0 | 0 | 0 | 0.039683 | 0.181818 | 462 | 17 | 61 | 27.176471 | 0.791005 | 0.051948 | 0 | 0.166667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | false | 0 | 0.083333 | 0.166667 | 1 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 5 |
fcb6c0d2c124ac4284590528ea8cd256754138be | 1,043 | py | Python | lab.py | Aamer98/FeatureNorm | fbf3d3b4cef81b3351347d272eb51b6cdd9f0cc5 | [
"MIT"
] | null | null | null | lab.py | Aamer98/FeatureNorm | fbf3d3b4cef81b3351347d272eb51b6cdd9f0cc5 | [
"MIT"
] | null | null | null | lab.py | Aamer98/FeatureNorm | fbf3d3b4cef81b3351347d272eb51b6cdd9f0cc5 | [
"MIT"
] | null | null | null | # from lab.tsne import generate_features
# from lab.affines import plot
from lab.layers import plot
# from lab.learning_curve import plot
# from lab.tsne import plot
# import os
# dir_list = [o for o in os.listdir('D:/downloaded_DS/miniImagenet')
# if os.path.isdir(os.path.join('D:/downloaded_DS/miniImagenet',o))]
# import csv
# with open('D:/Project/BMS/datasets/split_seed_1/ImageNet_val_labeled.csv', newline='') as f:
# reader = csv.reader(f)
# data = list(reader)
# with open("Output.txt", "w") as text_file:
# for line in data:
# is_in = False
# for dir in dir_list:
# if dir in line[1]:
# is_in = True
# break
# if is_in == False:
# text_file.writelines(line[0]+','+ line[1] + '\n')
# import torch
# import torchvision.models as models
# import copy
# model = models.resnet18(pretrained=True)
# sd = {
# 'model': copy.deepcopy(model.state_dict())
# }
# torch.save(sd, 'resnet18-f37072fd.pkl')
| 27.447368 | 94 | 0.610738 | 146 | 1,043 | 4.253425 | 0.479452 | 0.056361 | 0.067633 | 0.082126 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.016688 | 0.253116 | 1,043 | 37 | 95 | 28.189189 | 0.780488 | 0.887824 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
fcbb126865a810db27d75be5ed69f08a1f9cac62 | 89 | py | Python | auto_ds/__init__.py | Littilabs/auto_ds | ed8c303663df07b42976f51351933b12f2718e6f | [
"BSD-3-Clause"
] | null | null | null | auto_ds/__init__.py | Littilabs/auto_ds | ed8c303663df07b42976f51351933b12f2718e6f | [
"BSD-3-Clause"
] | 1 | 2021-10-10T15:28:37.000Z | 2021-10-10T15:28:37.000Z | auto_ds/__init__.py | Littilabs/auto_ds | ed8c303663df07b42976f51351933b12f2718e6f | [
"BSD-3-Clause"
] | null | null | null | from .autods import AutoDS
from .predictor import AutoDSPredictor
# from .utils import *
| 22.25 | 38 | 0.797753 | 11 | 89 | 6.454545 | 0.545455 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.146067 | 89 | 3 | 39 | 29.666667 | 0.934211 | 0.224719 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
fcbb4a0748d75c6382d525863f112b7cdb7b3676 | 509 | py | Python | expressionable/__init__.py | srp33/ExpressionAble | 2d55c5329ca568769e4d3216ae2154dd5314e094 | [
"MIT"
] | 2 | 2018-09-18T21:14:21.000Z | 2018-12-08T01:39:28.000Z | expressionable/__init__.py | srp33/ShapeShifter | 2d55c5329ca568769e4d3216ae2154dd5314e094 | [
"MIT"
] | 2 | 2019-04-19T14:03:58.000Z | 2019-05-15T19:17:03.000Z | expressionable/__init__.py | srp33/ExpressionAble | 2d55c5329ca568769e4d3216ae2154dd5314e094 | [
"MIT"
] | 4 | 2019-04-24T15:35:42.000Z | 2021-09-08T09:56:56.000Z | # __all__ = ['ColumnInfo', 'ExpressionAble', 'OperatorEnum', 'ContinuousQuery', 'DiscreteQuery', 'FileTypeEnum']
__all__ = ['ExpressionAble']
from expressionable.expressionable import ExpressionAble
# from expressionable.utils.columninfo import ColumnInfo
# from expressionable.utils.continuousquery import ContinuousQuery
# from expressionable.utils.discretequery import DiscreteQuery
# from expressionable.utils.filetypeenum import FileTypeEnum
# from expressionable.utils.operatorenum import OperatorEnum
| 50.9 | 112 | 0.834971 | 44 | 509 | 9.477273 | 0.227273 | 0.258993 | 0.275779 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.082515 | 509 | 9 | 113 | 56.555556 | 0.892934 | 0.803536 | 0 | 0 | 0 | 0 | 0.150538 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 0.5 | 0 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
fcc5d28818247186f3bcb9facfc27ef6b7acae28 | 110,790 | py | Python | tests/test_InputChecker.py | lvgig/input_checker | 541fd7aa4682c658b999858a8500841e22adf47e | [
"BSD-3-Clause"
] | 3 | 2021-07-02T15:13:50.000Z | 2021-11-08T09:11:41.000Z | tests/test_InputChecker.py | lvgig/input_checker | 541fd7aa4682c658b999858a8500841e22adf47e | [
"BSD-3-Clause"
] | null | null | null | tests/test_InputChecker.py | lvgig/input_checker | 541fd7aa4682c658b999858a8500841e22adf47e | [
"BSD-3-Clause"
] | null | null | null | import pandas as pd
import numpy as np
import pytest
import re
import tubular
import tubular.testing.helpers as h
import tubular.testing.test_data as data_generators_p
import input_checker
from input_checker._version import __version__
from input_checker.checker import InputChecker
from input_checker.exceptions import InputCheckerError
class TestInit(object):
"""Tests for InputChecker.init()."""
def test_super_init_called(self, mocker):
"""Test that init calls BaseTransformer.init."""
expected_call_args = {0: {"args": (), "kwargs": {"columns": ["a", "b"]}}}
with h.assert_function_call(
mocker, tubular.base.BaseTransformer, "__init__", expected_call_args
):
InputChecker(columns=["a", "b"])
def test_inheritance(self):
"""Test that InputChecker inherits from tubular.base.BaseTransformer."""
x = InputChecker()
h.assert_inheritance(x, tubular.base.BaseTransformer)
def test_arguments(self):
"""Test that InputChecker init has expected arguments."""
h.test_function_arguments(
func=InputChecker.__init__,
expected_arguments=[
"self",
"columns",
"categorical_columns",
"numerical_columns",
"datetime_columns",
"skip_infer_columns",
],
expected_default_values=(None, None, None, None, None),
)
def test_version_attribute(self):
"""Test that __version__ attribute takes expected value."""
x = InputChecker(columns=["a"])
h.assert_equal_dispatch(
expected=__version__,
actual=x.version_,
msg="__version__ attribute",
)
def test_columns_attributes_generated(self):
"""Test all columns attributes are saved with InputChecker init"""
x = InputChecker(
columns=["a", "b", "c", "d"],
numerical_columns=["a"],
categorical_columns=["b"],
datetime_columns=["d"],
skip_infer_columns=["c"],
)
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x.fit(df)
assert hasattr(x, "columns") is True, "columns attribute not present after init"
assert (
hasattr(x, "numerical_columns") is True
), "numerical_columns attribute not present after init"
assert (
hasattr(x, "categorical_columns") is True
), "categorical_columns attribute not present after init"
assert (
hasattr(x, "datetime_columns") is True
), "datetime_columns attribute not present after init"
assert (
hasattr(x, "skip_infer_columns") is True
), "skip_infer_columns attribute not present after init"
def test_check_type_called(self, mocker):
"""Test all check type is called by the init method."""
spy = mocker.spy(input_checker.checker.InputChecker, "_check_type")
x = InputChecker(
columns=["a", "b", "c", "d"],
numerical_columns=["a"],
categorical_columns=["b"],
datetime_columns=["d"],
skip_infer_columns=["c"],
)
assert (
spy.call_count == 5
), "unexpected number of calls to InputChecker._check_type with init"
call_0_args = spy.call_args_list[0]
call_0_pos_args = call_0_args[0]
call_1_args = spy.call_args_list[1]
call_1_pos_args = call_1_args[0]
call_2_args = spy.call_args_list[2]
call_2_pos_args = call_2_args[0]
call_3_args = spy.call_args_list[3]
call_3_pos_args = call_3_args[0]
call_4_args = spy.call_args_list[4]
call_4_pos_args = call_4_args[0]
expected_pos_args_0 = (
x,
["a", "b", "c", "d"],
"input columns",
[list, type(None), str],
)
expected_pos_args_1 = (
x,
["b"],
"categorical columns",
[list, str, type(None)],
)
expected_pos_args_2 = (
x,
["a"],
"numerical columns",
[list, dict, str, type(None)],
)
expected_pos_args_3 = (
x,
["d"],
"datetime columns",
[list, dict, str, type(None)],
)
expected_pos_args_4 = (
x,
["c"],
"skip infer columns",
[list, type(None)],
)
assert (
expected_pos_args_0 == call_0_pos_args
), "positional args unexpected in _check_type call for columns argument"
assert (
expected_pos_args_1 == call_1_pos_args
), "positional args unexpected in _check_type call for categorical columns argument"
assert (
expected_pos_args_2 == call_2_pos_args
), "positional args unexpected in _check_type call for numerical columns argument"
assert (
expected_pos_args_3 == call_3_pos_args
), "positional args unexpected in _check_type call for datetime columns argument"
assert (
expected_pos_args_4 == call_4_pos_args
), "positional args unexpected in _check_type call for skip infer columns argument"
def test_check_is_string_value_called(self, mocker):
"""Test all check string is called by the init method when option set to infer."""
spy = mocker.spy(input_checker.checker.InputChecker, "_is_string_value")
x = InputChecker(
numerical_columns="infer",
categorical_columns="infer",
datetime_columns="infer",
)
assert (
spy.call_count == 3
), "unexpected number of calls to InputChecker._is_string_value with init"
call_0_args = spy.call_args_list[0]
call_0_pos_args = call_0_args[0]
call_1_args = spy.call_args_list[1]
call_1_pos_args = call_1_args[0]
call_2_args = spy.call_args_list[2]
call_2_pos_args = call_2_args[0]
expected_pos_args_0 = (x, x.categorical_columns, "categorical columns", "infer")
expected_pos_args_1 = (x, x.numerical_columns, "numerical columns", "infer")
expected_pos_args_2 = (x, x.datetime_columns, "datetime columns", "infer")
assert (
expected_pos_args_0 == call_0_pos_args
), "positional args unexpected in _is_string_value call for numerical columns argument"
assert (
expected_pos_args_1 == call_1_pos_args
), "positional args unexpected in _is_string_value call for categorical columns argument"
assert (
expected_pos_args_2 == call_2_pos_args
), "positional args unexpected in _is_string_value call for categorical columns argument"
def test_check_is_empty_called(self, mocker):
"""Test all check is empty is called by the init method."""
spy = mocker.spy(input_checker.checker.InputChecker, "_is_empty")
x = InputChecker(
columns=["a", "b", "c", "d"],
numerical_columns=["a"],
categorical_columns=["b", "c"],
datetime_columns=["d"],
)
assert (
spy.call_count == 4
), "unexpected number of calls to InputChecker._is_empty with init"
call_0_args = spy.call_args_list[0]
call_0_pos_args = call_0_args[0]
call_1_args = spy.call_args_list[1]
call_1_pos_args = call_1_args[0]
call_2_args = spy.call_args_list[2]
call_2_pos_args = call_2_args[0]
call_3_args = spy.call_args_list[3]
call_3_pos_args = call_3_args[0]
expected_pos_args_0 = (x, "input columns", ["a", "b", "c", "d"])
expected_pos_args_1 = (x, "categorical columns", ["b", "c"])
expected_pos_args_2 = (x, "numerical columns", ["a"])
expected_pos_args_3 = (x, "datetime columns", ["d"])
assert (
expected_pos_args_0 == call_0_pos_args
), "positional args unexpected in _is_empty call for categorical columns argument"
assert (
expected_pos_args_1 == call_1_pos_args
), "positional args unexpected in _is_empty call for numerical columns argument"
assert (
expected_pos_args_2 == call_2_pos_args
), "positional args unexpected in _is_empty call for numerical columns argument"
assert (
expected_pos_args_3 == call_3_pos_args
), "positional args unexpected in _is_empty call for numerical columns argument"
def test_check_is_listed_in_columns_called(self, mocker):
spy = mocker.spy(input_checker.checker.InputChecker, "_is_listed_in_columns")
InputChecker(
columns=["a", "b", "c", "d"],
numerical_columns=["a"],
categorical_columns=["b", "c"],
datetime_columns=["d"],
)
assert (
spy.call_count == 1
), "unexpected number of calls to InputChecker._is_listed_in_columns with init"
class TestConsolidateInputs(object):
def test_arguments(self):
"""Test that _consolidate_inputs has expected arguments."""
h.test_function_arguments(
func=InputChecker._consolidate_inputs,
expected_arguments=["self", "X"],
expected_default_values=None,
)
def test_infer_datetime_columns(self):
"""Test that _consolidate_inputs infers the correct datetime columns"""
x = InputChecker(datetime_columns="infer")
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
df["e"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08-04-2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x.fit(df)
assert x.datetime_columns == [
"d",
"e",
], "infer datetime not finding correct columns"
def test_infer_datetime_dict(self):
"""Test that _consolidate_inputs infers the correct datetime dict"""
x = InputChecker(datetime_columns="infer")
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x.fit(df)
assert (
x.datetime_dict["d"]["maximum"] is False
), "infer numerical not specifying maximum value check as true"
assert (
x.datetime_dict["d"]["minimum"] is True
), "infer numerical not specifying maximum value check as true"
def test_infer_categorical_columns(self):
"""Test that _consolidate_inputs infers the correct categorical columns"""
x = InputChecker(categorical_columns="infer")
df = data_generators_p.create_df_2()
df["d"] = [True, True, False, True, True, False, np.nan]
df["d"] = df["d"].astype("bool")
x.fit(df)
assert x.categorical_columns == [
"b",
"c",
"d",
], "infer categorical not finding correct columns"
def test_infer_numerical_columns(self):
"""Test that _consolidate_inputs infers the correct numerical columns"""
x = InputChecker(numerical_columns="infer")
df = data_generators_p.create_df_2()
x.fit(df)
assert x.numerical_columns == [
"a"
], "infer numerical not finding correct columns"
def test_infer_numerical_skips_infer_columns(self):
"""Test that _consolidate_inputs skips right columns when inferring numerical"""
x = InputChecker(numerical_columns="infer", skip_infer_columns=["a"])
df = data_generators_p.create_df_2()
df["d"] = df["a"]
x.fit(df)
assert x.numerical_columns == [
"d"
], "infer numerical not finding correct columns when skipping infer columns"
def test_infer_categorical_skips_infer_columns(self):
"""Test that _consolidate_inputs skips right columns when inferring categorical"""
x = InputChecker(categorical_columns="infer", skip_infer_columns=["b"])
df = data_generators_p.create_df_2()
x.fit(df)
assert x.categorical_columns == [
"c"
], "infer categorical not finding correct columns when skipping infer columns"
def test_infer_datetime_skips_infer_columns(self):
"""Test that _consolidate_inputs skips right columns when inferring datetime"""
x = InputChecker(datetime_columns="infer", skip_infer_columns=["d"])
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
df["a"] = df["d"]
x.fit(df)
assert x.datetime_columns == [
"a"
], "infer datetime not finding correct columns when skipping infer columns"
def test_infer_numerical_dict(self):
"""Test that _consolidate_inputs infers the correct numerical dict"""
x = InputChecker(numerical_columns="infer")
df = data_generators_p.create_df_2()
x.fit(df)
assert (
x.numerical_dict["a"]["maximum"] is True
), "infer numerical not specifying maximum value check as true"
assert (
x.numerical_dict["a"]["minimum"] is True
), "infer numerical not specifying minimum value check as true"
def test_datetime_type(self):
"""Test that datetime columns is a list after calling _consolidate_inputs"""
x = InputChecker(datetime_columns="infer")
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x.fit(df)
assert (
type(x.datetime_columns) is list
), f"incorrect datetime_columns type returned from _consolidate_inputs - expected: list but got: {type(x.datetime_columns)} "
def test_categorical_type(self):
"""Test that categorical columns is a list after calling _consolidate_inputs"""
x = InputChecker(categorical_columns="infer")
df = data_generators_p.create_df_2()
x.fit(df)
assert (
type(x.categorical_columns) is list
), f"incorrect categorical_columns type returned from _consolidate_inputs - expected: list but got: {type(x.categorical_columns)} "
def test_numerical_type(self):
"""Test that numerical columns and dict are a list and dict after calling _consolidate_inputs"""
x = InputChecker(numerical_columns="infer")
df = data_generators_p.create_df_2()
x.fit(df)
assert (
type(x.numerical_columns) is list
), f"incorrect numerical_columns type returned from _consolidate_inputs - expected: list but got: {type(x.numerical_columns)} "
assert (
type(x.numerical_dict) is dict
), f"incorrect numerical_dict type returned from _consolidate_inputs - expected: dict but got: {type(x.numerical_dict)} "
def test_check_is_subset_called(self, mocker):
"""Test all check _is_subset is called by the _consolidate_inputs method."""
x = InputChecker(
columns=["a", "b", "c", "d"],
numerical_columns=["a"],
categorical_columns=["c"],
datetime_columns=["d"],
skip_infer_columns=["b"],
)
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
spy = mocker.spy(input_checker.checker.InputChecker, "_is_subset")
x.fit(df)
assert (
spy.call_count == 5
), "unexpected number of calls to InputChecker._is_subset with _consolidate_inputs"
call_0_args = spy.call_args_list[0]
call_0_pos_args = call_0_args[0]
call_1_args = spy.call_args_list[1]
call_1_pos_args = call_1_args[0]
call_2_args = spy.call_args_list[2]
call_2_pos_args = call_2_args[0]
call_3_args = spy.call_args_list[3]
call_3_pos_args = call_3_args[0]
call_4_args = spy.call_args_list[4]
call_4_pos_args = call_4_args[0]
expected_pos_args_0 = (x, "skip infer columns", ["b"], df)
expected_pos_args_1 = (x, "input columns", ["a", "b", "c", "d"], df)
expected_pos_args_2 = (x, "categorical columns", ["c"], df)
expected_pos_args_3 = (x, "numerical columns", ["a"], df)
expected_pos_args_4 = (x, "datetime columns", ["d"], df)
assert (
expected_pos_args_0 == call_0_pos_args
), "positional args unexpected in _is_subset call for skip_infer_columns columns argument"
assert (
expected_pos_args_1 == call_1_pos_args
), "positional args unexpected in _is_subset call for input columns argument"
assert (
expected_pos_args_2 == call_2_pos_args
), "positional args unexpected in _is_subset call for categorical columns argument"
assert (
expected_pos_args_3 == call_3_pos_args
), "positional args unexpected in _is_subset call for numerical columns argument"
assert (
expected_pos_args_4 == call_4_pos_args
), "positional args unexpected in _is_subset call for datetime columns argument"
class TestFitTypeChecker(object):
"""Tests for InputChecker._fit_type_checker()."""
def test_arguments(self):
"""Test that InputChecker _fit_type_checker has expected arguments."""
h.test_function_arguments(
func=InputChecker._fit_type_checker, expected_arguments=["self", "X"]
)
def test_no_column_classes_before_fit(self):
"""Test column_classes is not present before fit called"""
x = InputChecker()
assert (
hasattr(x, "column_classes") is False
), "column_classes attribute present before fit"
def test_column_classes_after_fit(self):
"""Test column_classes is present after fit called"""
df = data_generators_p.create_df_2()
x = InputChecker()
x.fit(df)
assert hasattr(
x, "column_classes"
), "column_classes attribute not present after fit"
def test_correct_columns_classes(self):
"""Test fit type checker saves types for correct columns after fit called"""
df = data_generators_p.create_df_2()
x = InputChecker(columns=["a"])
x.fit(df)
assert list(x.column_classes.keys()) == [
"a"
], f"incorrect values returned from _fit_value_checker - expected: ['a'] but got: {list(x.column_classes.keys())}"
def test_correct_classes_identified(self):
"""Test fit type checker identifies correct classes is present after fit called"""
df = data_generators_p.create_df_2()
x = InputChecker()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x.fit(df)
assert (
x.column_classes["a"] == "float64"
), f"incorrect type returned from _fit_type_checker for column 'a' - expected: float64 but got: {x.column_classes['a']}"
assert (
x.column_classes["b"] == "object"
), f"incorrect type returned from _fit_type_checker for column 'b' - expected: object but got: {x.column_classes['b']}"
assert (
x.column_classes["c"] == "category"
), f"incorrect type returned from _fit_type_checker for column 'c' - expected: category but got: {x.column_classes['c']}"
assert (
x.column_classes["d"] == "datetime64[ns]"
), f"incorrect type returned from _fit_type_checker for column 'd' - expected: datetime64[ns] but got: {x.column_classes['d']}"
class TestFitNullChecker(object):
"""Tests for InputChecker._fit_null_checker()."""
def test_arguments(self):
"""Test that InputChecker _fit_null_checker has expected arguments."""
h.test_function_arguments(
func=InputChecker._fit_null_checker, expected_arguments=["self", "X"]
)
def test_no_expected_values_before_fit(self):
"""Test null_map is not present before fit called"""
x = InputChecker()
assert hasattr(x, "null_map") is False, "null_map attribute present before fit"
def test_expected_values_after_fit(self):
"""Test null_map is present after fit called"""
df = data_generators_p.create_df_2()
x = InputChecker()
x.fit(df)
assert hasattr(x, "null_map"), "null_map attribute not present after fit"
def test_correct_columns_nulls(self):
"""Test fit nulls checker saves map for correct columns after fit called"""
df = data_generators_p.create_df_2()
x = InputChecker(columns=["a"])
x.fit(df)
assert list(x.null_map.keys()) == [
"a"
], f"incorrect values returned from _fit_null_checker - expected: ['a'] but got: {list(x.null_map.keys())}"
def test_correct_classes_identified(self):
"""Test fit null checker identifies correct columns with nulls after fit called"""
df = data_generators_p.create_df_2()
x = InputChecker()
df["b"] = df["b"].fillna("a")
x.fit(df)
assert (
x.null_map["a"] == 1
), f"incorrect values returned from _fit_null_checker - expected: 1 but got: {x.null_map['a']}"
assert (
x.null_map["b"] == 0
), f"incorrect values returned from _fit_null_checker - expected: 0 but got: {x.null_map['b']}"
assert (
x.null_map["c"] == 1
), f"incorrect values returned from _fit_null_checker - expected: 1 but got: {x.null_map['c']}"
class TestFitValueChecker(object):
"""Tests for InputChecker._fit_value_checker()."""
def test_arguments(self):
"""Test that InputChecker _fit_value_checker has expected arguments."""
h.test_function_arguments(
func=InputChecker._fit_value_checker, expected_arguments=["self", "X"]
)
def test_no_expected_values_before_fit(self):
"""Test expected_values is not present before fit called"""
x = InputChecker(categorical_columns=["b", "c"])
assert (
hasattr(x, "expected_values") is False
), "expected_values attribute present before fit"
def test_expected_values_after_fit(self):
"""Test expected_values is present after fit called"""
df = data_generators_p.create_df_2()
x = InputChecker(categorical_columns=["b", "c"])
x.fit(df)
assert hasattr(
x, "expected_values"
), "expected_values attribute not present after fit"
def test_correct_columns_map(self):
"""Test fit value checker saves levels for correct columns after fit called"""
df = data_generators_p.create_df_2()
x = InputChecker(categorical_columns=["b", "c"])
x.fit(df)
assert list(x.expected_values.keys()) == [
"b",
"c",
], f"incorrect values returned from _fit_value_checker - expected: ['b', 'c'] but got: {list(x.expected_values.keys())}"
def test_correct_values_identified(self):
"""Test fit value checker identifies corrcet levels after fit called"""
df = data_generators_p.create_df_2()
df["d"] = [True, True, False, True, True, False, np.nan]
df["d"] = df["d"].astype("bool")
x = InputChecker(categorical_columns=["b", "c", "d"])
x.fit(df)
assert x.expected_values["b"] == [
"a",
"b",
"c",
"d",
"e",
"f",
np.nan,
], f"incorrect values returned from _fit_value_checker - expected: ['a', 'b', 'c', 'd', 'e', 'f', np.nan] but got: {x.expected_values['b']}"
assert x.expected_values["c"] == [
"a",
"b",
"c",
"d",
"e",
"f",
np.nan,
], f"incorrect values returned from _fit_value_checker - expected: ['a', 'b', 'c', 'd', 'e', 'f', np.nan] but got: {x.expected_values['c']}"
assert x.expected_values["d"] == [
True,
False,
], f"incorrect values returned from _fit_value_checker - expected: [True, False, np.nan] but got: {x.expected_values['d']}"
class TestFitNumericalChecker(object):
"""Tests for InputChecker._fit_numerical_checker()."""
def test_arguments(self):
"""Test that InputChecker _fit_numerical_checker has expected arguments."""
h.test_function_arguments(
func=InputChecker._fit_numerical_checker, expected_arguments=["self", "X"]
)
def test_no_expected_values_before_fit(self):
"""Test numerical_values is not present before fit called"""
x = InputChecker()
assert (
hasattr(x, "numerical_values") is False
), "numerical_values attribute present before fit"
def test_expected_values_after_fit(self):
"""Test numerical_values is present after fit called"""
df = data_generators_p.create_df_2()
x = InputChecker(numerical_columns=["a"])
x.fit(df)
assert hasattr(
x, "numerical_values"
), "numerical_values attribute not present after fit"
def test_correct_columns_num_values(self):
"""Test fit numerical checker saves values for correct columns after fit called"""
df = data_generators_p.create_df_2()
x = InputChecker(numerical_columns=["a"])
x.fit(df)
assert list(x.numerical_values.keys()) == [
"a"
], f"incorrect values returned from numerical_values - expected: ['a'] but got: {list(x.numerical_values.keys())}"
def test_correct_numerical_values_identified(self):
"""Test fit numerical checker identifies correct range values after fit called"""
df = data_generators_p.create_df_2()
x = InputChecker(numerical_columns=["a"])
x.fit(df)
assert (
x.numerical_values["a"]["maximum"] == 6
), f"incorrect values returned from _fit_numerical_checker - expected: 1 but got: {x.numerical_values['a']['maximum']}"
assert (
x.numerical_values["a"]["minimum"] == 1
), f"incorrect values returned from _fit_numerical_checker - expected: 0 but got: {x.numerical_values['a']['minimum']}"
def test_correct_numerical_values_identified_dict(self):
"""Test fit numerical checker identifies correct range values after fit called when inputting a dictionary"""
df = data_generators_p.create_df_2()
numerical_dict = {}
numerical_dict["a"] = {}
numerical_dict["a"]["maximum"] = True
numerical_dict["a"]["minimum"] = False
x = InputChecker(numerical_columns=numerical_dict)
x.fit(df)
assert (
x.numerical_values["a"]["maximum"] == 6
), f"incorrect values returned from _fit_numerical_checker - expected: 1 but got: {x.numerical_values['a']['maximum']}"
assert (
x.numerical_values["a"]["minimum"] is None
), f"incorrect values returned from _fit_numerical_checker - expected: None but got: {x.numerical_values['a']['minimum']}"
class TestFitDatetimeChecker(object):
"""Tests for InputChecker._fit_datetime_checker()."""
def test_arguments(self):
"""Test that InputChecker _fit_value_checker has expected arguments."""
h.test_function_arguments(
func=InputChecker._fit_datetime_checker, expected_arguments=["self", "X"]
)
def test_no_datetime_values_before_fit(self):
"""Test expected_values is not present before fit called"""
x = InputChecker(datetime_columns=["b", "c"])
assert (
hasattr(x, "datetime_values") is False
), "datetime_values attribute present before fit"
def test_datetime_values_after_fit(self):
"""Test datetime_values is present after fit called"""
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
df["e"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08-04-2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x = InputChecker(datetime_columns=["d", "e"])
x.fit(df)
assert hasattr(
x, "datetime_values"
), "datetime_values attribute not present after fit"
def test_correct_columns_map(self):
"""Test fit datetime checker saves minimum dates for correct columns after fit called"""
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
df["e"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08-04-2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x = InputChecker(datetime_columns=["d", "e"])
x.fit(df)
assert list(x.datetime_values.keys()) == [
"d",
"e",
], f"incorrect values returned from _fit_datetime_checker - expected: ['d', 'e'] but got: {list(x.datetime_values.keys())} "
def test_correct_datetime_values_identified(self):
"""Test fit datetime checker identifies correct minimum bound after fit called"""
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x = InputChecker(datetime_columns=["d"])
x.fit(df)
expected_min_d = pd.to_datetime("15/10/2018").date()
actual_min_d = x.datetime_values["d"]["minimum"]
actual_max_d = x.datetime_values["d"]["maximum"]
assert (
actual_min_d == expected_min_d
), f"incorrect values returned from _fit_datetime_checker - expected: {expected_min_d}, but got: {actual_min_d}"
assert (
actual_max_d is None
), f"incorrect values returned from _fit_datetime_checker - expected: None, but got: {actual_max_d}"
def test_correct_datetime_values_identified_dict(self):
"""Test fit datetime checker identifies correct range values after fit called when inputting a dictionary"""
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
datetime_dict = {"d": {"maximum": True, "minimum": True}}
x = InputChecker(datetime_columns=datetime_dict)
x.fit(df)
expected_min_d = pd.to_datetime("15/10/2018").date()
expected_max_d = pd.to_datetime("01/02/2021").date()
actual_min_d = x.datetime_values["d"]["minimum"]
actual_max_d = x.datetime_values["d"]["maximum"]
assert (
actual_min_d == expected_min_d
), f"incorrect values returned from _fit_datetime_checker - expected: {expected_min_d}, but got: {actual_min_d}"
assert (
actual_max_d == expected_max_d
), f"incorrect values returned from _fit_datetime_checker - expected: {expected_max_d}, but got: {actual_max_d}"
class TestFit(object):
"""Tests for InputChecker.fit()."""
def test_arguments(self):
"""Test that InputChecker fit has expected arguments."""
h.test_function_arguments(
func=InputChecker.fit,
expected_arguments=["self", "X", "y"],
expected_default_values=(None,),
)
def test_super_fit_called(self, mocker):
"""Test that BaseTransformer fit called."""
expected_call_args = {
0: {"args": (data_generators_p.create_df_2(), None), "kwargs": {}}
}
df = data_generators_p.create_df_2()
x = InputChecker(columns=["a"])
with h.assert_function_call(
mocker, tubular.base.BaseTransformer, "fit", expected_call_args
):
x.fit(df)
def test_all_columns_selected(self):
"""Test fit selects all columns when columns parameter set to None"""
df = data_generators_p.create_df_2()
x = InputChecker(columns=None)
assert (
x.columns is None
), f"incorrect columns attribute before fit when columns parameter set to None - expected: None but got: {x.columns}"
x.fit(df)
assert x.columns == [
"a",
"b",
"c",
], f"incorrect columns identified when columns parameter set to None - expected: ['a', 'b', 'c'] but got: {x.columns}"
def test_fit_returns_self(self):
"""Test fit returns self?"""
df = data_generators_p.create_df_2()
x = InputChecker()
x_fitted = x.fit(df)
assert x_fitted is x, "Returned value from InputChecker.fit not as expected."
def test_no_optional_calls_fit(self):
"""Test numerical_values and expected_values is not present after fit if parameters set to None"""
x = InputChecker(
numerical_columns=None, categorical_columns=None, datetime_columns=None
)
df = data_generators_p.create_df_2()
x.fit(df)
assert (
hasattr(x, "numerical_values") is False
), "numerical_values attribute present with numerical_columns set to None"
assert (
hasattr(x, "expected_values") is False
), "expected_values attribute present with categorical_columns set to None"
assert (
hasattr(x, "datetime_values") is False
), "datetime_values attribute present with datetime_columns set to None"
def test_compulsory_checks_generated_with_no_optional_calls_fit(self):
"""Test null_map and column_classes are present after fit when optional parameters set to None"""
x = InputChecker(
numerical_columns=None, categorical_columns=None, datetime_columns=None
)
df = data_generators_p.create_df_2()
x.fit(df)
assert (
hasattr(x, "null_map") is True
), "null_map attribute not present when optional checks set to None"
assert (
hasattr(x, "column_classes") is True
), "column_classes attribute not present when optional checks set to None"
def test_all_checks_generated(self):
"""Test all checks are generated when all optional parameters set"""
x = InputChecker(
columns=["a", "b", "c", "d"],
numerical_columns=["a"],
categorical_columns=["b", "c"],
datetime_columns=["d"],
)
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x.fit(df)
assert (
hasattr(x, "numerical_values") is True
), "numerical_values attribute not present after fit with numerical_columns set"
assert (
hasattr(x, "expected_values") is True
), "expected_values attribute not present after fit with categorical_columns set"
assert (
hasattr(x, "datetime_values") is True
), "expected_values attribute not present after fit with datetime_columns set"
assert (
hasattr(x, "null_map") is True
), "null_map attribute not present after fit"
assert (
hasattr(x, "column_classes") is True
), "column_classes attribute not present after fit"
def test_check_df_is_empty_called(self, mocker):
"""Test check is df empty is called by the fit method."""
x = InputChecker(
columns=["a", "b", "c"],
numerical_columns=["a"],
categorical_columns=["b", "c"],
)
df = data_generators_p.create_df_2()
spy = mocker.spy(input_checker.checker.InputChecker, "_df_is_empty")
x.fit(df)
assert (
spy.call_count == 1
), "unexpected number of calls to InputChecker._df_is_empty with fit"
call_0_args = spy.call_args_list[0]
call_0_pos_args = call_0_args[0]
expected_pos_args_0 = (x, "input dataframe", df)
assert (
expected_pos_args_0 == call_0_pos_args
), "positional args unexpected in _df_is_empty call for dataframe argument"
class TestTransformTypeChecker(object):
"""Tests for InputChecker._transform_type_checker()."""
def test_arguments(self):
"""Test that InputChecker _transform_type_checker has expected arguments."""
h.test_function_arguments(
func=InputChecker._transform_type_checker,
expected_arguments=["self", "X", "batch_mode"],
expected_default_values=(False,),
)
def test_check_fitted_called(self, mocker):
"""Test that transform calls BaseTransformer.check_is_fitted."""
expected_call_args = {0: {"args": (["column_classes"],), "kwargs": {}}}
x = InputChecker()
df = data_generators_p.create_df_2()
x.fit(df)
with h.assert_function_call(
mocker, tubular.base.BaseTransformer, "check_is_fitted", expected_call_args
):
x._transform_type_checker(df)
def test_transform_returns_failed_checks_dict(self):
"""Test _transform_type_checker returns results dictionary"""
df = data_generators_p.create_df_2()
x = InputChecker()
x.fit(df)
type_checker_failed_checks = x._transform_type_checker(df)
assert isinstance(
type_checker_failed_checks, dict
), f"incorrect type results type identified - expected: dict but got: {type(type_checker_failed_checks)}"
def test_transform_passes(self):
"""Test _transform_type_checker passes all the checks on the training dataframe"""
df = data_generators_p.create_df_2()
x = InputChecker()
x.fit(df)
type_checker_failed_checks = x._transform_type_checker(df)
assert (
type_checker_failed_checks == {}
), f"Type checker found failed tests - {list(type_checker_failed_checks.keys())}"
def test_transform_passes_column_all_nulls(self):
"""Test _transform_type_checker passes all the checks on the training dataframe when a column contains only nulls"""
df = data_generators_p.create_df_2()
x = InputChecker()
x.fit(df)
df["c"] = np.nan
type_checker_failed_checks = x._transform_type_checker(df)
assert (
type_checker_failed_checks == {}
), f"Type checker found failed tests - {list(type_checker_failed_checks.keys())}"
def test_transform_captures_failed_test(self):
"""Test _transform_type_checker captures a failed check"""
df = data_generators_p.create_df_2()
x = InputChecker()
x.fit(df)
exp_type = df["a"].dtypes
df.loc[5, "a"] = "a"
type_checker_failed_checks = x._transform_type_checker(df)
assert (
type_checker_failed_checks["a"]["actual"] == df["a"].dtypes
), f"incorrect values saved to type_checker_failed_checks bad types - expected: [{type('a')}] but got: {type_checker_failed_checks['a']['types']}"
assert (
type_checker_failed_checks["a"]["expected"] == exp_type
), f"incorrect values saved to type_checker_failed_checks expected types - expected: [{exp_type}] but got: {type_checker_failed_checks['a']['types']}"
def test_transform_passes_batch_mode(self):
"""Test _transform_type_checker passes all the checks on the training dataframe"""
df = data_generators_p.create_df_2()
x = InputChecker()
x.fit(df)
type_checker_failed_checks = x._transform_type_checker(df, batch_mode=True)
assert (
type_checker_failed_checks == {}
), f"Type checker found failed tests - {list(type_checker_failed_checks.keys())}"
def test_transform_captures_failed_test_batch_mode(self):
"""Test _transform_type_checker handles mixed types"""
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
print(df)
x = InputChecker()
x.fit(df)
exp_type = df["a"].dtypes
print(exp_type)
df.loc[5, "a"] = "a"
df.loc[1, "d"] = "a"
df.loc[3, "b"] = 1
type_checker_failed_checks = x._transform_type_checker(df, batch_mode=True)
expected_output = {
"a": {"idxs": [5], "actual": {5: "str"}, "expected": "float"},
"b": {"idxs": [3], "actual": {3: "int"}, "expected": "str"},
"d": {"idxs": [1], "actual": {1: "str"}, "expected": "Timestamp"},
}
for k, v in expected_output.items():
assert (
k in type_checker_failed_checks.keys()
), f"expected column {k} in type_checker_failed_checks output"
assert (
type(type_checker_failed_checks[k]) == dict
), f"expected dict for column {k} in type_checker_failed_checks output"
for sub_k, sub_v in expected_output[k].items():
assert (
sub_k in type_checker_failed_checks[k].keys()
), f"expected {sub_k} as dict key in type_checker_failed_checks output"
assert (
sub_v == type_checker_failed_checks[k][sub_k]
), f"expected {sub_v} as value for {sub_k} in column {k} output of type_checker_failed_checks output"
class TestTransformNullChecker(object):
"""Tests for InputChecker._transform_null_checker()."""
def test_arguments(self):
"""Test that InputChecker _transform_null_checker has expected arguments."""
h.test_function_arguments(
func=InputChecker._transform_null_checker, expected_arguments=["self", "X"]
)
def test_check_fitted_called(self, mocker):
"""Test that transform calls BaseTransformer.check_is_fitted."""
expected_call_args = {0: {"args": (["null_map"],), "kwargs": {}}}
x = InputChecker()
df = data_generators_p.create_df_2()
x.fit(df)
with h.assert_function_call(
mocker, tubular.base.BaseTransformer, "check_is_fitted", expected_call_args
):
x._transform_null_checker(df)
def test_transform_returns_failed_checks_dict(self):
"""Test _transform_null_checker returns results dictionary"""
df = data_generators_p.create_df_2()
x = InputChecker()
x.fit(df)
null_checker_failed_checks = x._transform_null_checker(df)
assert isinstance(
null_checker_failed_checks, dict
), f"incorrect null results type identified - expected: dict but got: {type(null_checker_failed_checks)}"
def test_transform_passes(self):
"""Test _transform_null_checker passes all the checks on the training dataframe"""
df = data_generators_p.create_df_2()
df["b"] = df["b"].fillna("a")
x = InputChecker()
x.fit(df)
null_checker_failed_checks = x._transform_null_checker(df)
assert (
null_checker_failed_checks == {}
), f"Null checker found failed tests - {list(null_checker_failed_checks.keys())}"
def test_transform_captures_failed_test(self):
"""Test _transform_null_checker captures a failed check"""
df = data_generators_p.create_df_2()
df["b"] = df["b"].fillna("a")
x = InputChecker()
x.fit(df)
df.loc[5, "b"] = np.nan
null_checker_failed_checks = x._transform_null_checker(df)
assert null_checker_failed_checks["b"] == [
5
], f"incorrect values saved to value_checker_failed_checks - expected: [5] but got: {null_checker_failed_checks['b']}"
class TestTransformNumericalChecker(object):
"""Tests for InputChecker._transform_numerical_checker()."""
def test_arguments(self):
"""Test that InputChecker _transform_numerical_checker has expected arguments."""
h.test_function_arguments(
func=InputChecker._transform_numerical_checker,
expected_arguments=["self", "X", "type_fails", "batch_mode"],
expected_default_values=(
{},
False,
),
)
def test_check_fitted_called(self, mocker):
"""Test that transform calls BaseTransformer.check_is_fitted."""
expected_call_args = {0: {"args": (["numerical_values"],), "kwargs": {}}}
x = InputChecker(numerical_columns=["a"])
df = data_generators_p.create_df_2()
x.fit(df)
with h.assert_function_call(
mocker, tubular.base.BaseTransformer, "check_is_fitted", expected_call_args
):
x._transform_numerical_checker(df, {})
def test_transform_returns_failed_checks_dict(self):
"""Test _transform_numerical_checker returns results dictionary"""
df = data_generators_p.create_df_2()
x = InputChecker(numerical_columns=["a"])
x.fit(df)
numerical_checker_failed_checks = x._transform_numerical_checker(df, {})
assert isinstance(
numerical_checker_failed_checks, dict
), f"incorrect numerical results type identified - expected: dict but got: {type(numerical_checker_failed_checks)}"
def test_transform_passes(self):
"""Test _transform_numerical_checker passes all the numerical checks on the training dataframe"""
df = data_generators_p.create_df_2()
x = InputChecker(numerical_columns=["a"])
x.fit(df)
numerical_checker_failed_checks = x._transform_numerical_checker(df, {})
assert (
numerical_checker_failed_checks == {}
), f"Numerical checker found failed tests - {list(numerical_checker_failed_checks.keys())}"
def test_transform_captures_failed_test(self):
"""Test _transform_numerical_checker captures a failed check"""
df = data_generators_p.create_df_2()
x = InputChecker(numerical_columns=["a"])
x.fit(df)
df.loc[0, "a"] = -1
df.loc[5, "a"] = 7
numerical_checker_failed_checks = x._transform_numerical_checker(df, {})
expected_max = {5: 7.0}
expected_min = {0: -1.0}
assert (
numerical_checker_failed_checks["a"]["maximum"] == expected_max
), f"incorrect values saved to numerical_checker_failed_checks - expected: {expected_max} but got: {numerical_checker_failed_checks['a']['maximum']}"
assert (
numerical_checker_failed_checks["a"]["minimum"] == expected_min
), f"incorrect values saved to numerical_checker_failed_checks - expected: {expected_min} but got: {numerical_checker_failed_checks['a']['minimum']}"
def test_transform_captures_failed_test_only_maximum(self):
"""Test _transform_numerical_checker captures a failed check when the check includes a maximum value but no minimum value"""
df = data_generators_p.create_df_2()
numerical_dict = {}
numerical_dict["a"] = {}
numerical_dict["a"]["maximum"] = True
numerical_dict["a"]["minimum"] = False
x = InputChecker(numerical_columns=numerical_dict)
x.fit(df)
df.loc[0, "a"] = -1
df.loc[5, "a"] = 7
expected_max = {5: 7.0}
numerical_checker_failed_checks = x._transform_numerical_checker(df, {})
assert (
numerical_checker_failed_checks["a"]["maximum"] == expected_max
), f"incorrect values saved to numerical_checker_failed_checks - expected: {expected_max} but got: {numerical_checker_failed_checks['a']['maximum']}"
assert (
"minimum" not in numerical_checker_failed_checks["a"]
), "No minimum value results expected given input the numerical dict"
def test_transform_captures_failed_test_only_minimum(self):
"""Test _transform_numerical_checker captures a failed check when the check includes a minimum value but no maximum value"""
df = data_generators_p.create_df_2()
numerical_dict = {}
numerical_dict["a"] = {}
numerical_dict["a"]["maximum"] = False
numerical_dict["a"]["minimum"] = True
x = InputChecker(numerical_columns=numerical_dict)
x.fit(df)
df.loc[0, "a"] = -1
df.loc[5, "a"] = 7
numerical_checker_failed_checks = x._transform_numerical_checker(df, {})
expected_min = {0: -1.0}
assert (
numerical_checker_failed_checks["a"]["minimum"] == expected_min
), f"incorrect values saved to numerical_checker_failed_checks - expected: {expected_min} but got: {numerical_checker_failed_checks['a']['minimum']}"
assert (
"maximum" not in numerical_checker_failed_checks["a"]
), "No maximum value results expected given input the numerical dict"
def test_transform_skips_failed_type_checks_batch_mode(self):
"""Test _transform_numerical_checker skips checks for rows which aren't numerical
when operating in batch mode"""
df = data_generators_p.create_df_2()
x = InputChecker(numerical_columns=["a"])
x.fit(df)
df.loc[4, "a"] = "z"
df.loc[1, "a"] = 1
df.loc[2, "a"] = 100
type_fails_dict = {
"a": {"idxs": [1, 4], "actual": {1: "int", 4: "str"}, "expected": "float"}
}
expected_output = {"a": {"max idxs": [2], "maximum": {2: 100}}}
numerical_checker_failed_checks = x._transform_numerical_checker(
df, type_fails_dict, batch_mode=True
)
h.assert_equal_dispatch(
actual=numerical_checker_failed_checks,
expected=expected_output,
msg="rows failing type check have not been removed by _transform_numerical_checker",
)
def test_transform_skips_failed_type_checks(self):
"""Test _transform_numerical_checker skips checks for columns which aren't numerical
when not operating in batch mode"""
df = data_generators_p.create_df_2()
x = InputChecker(numerical_columns=["a"])
x.fit(df)
# Case 1: check will not be performed as column a is not numerical
df_test = pd.DataFrame({"a": ["z", "zz", "zzz"]})
type_fails_dict = {
"a": {"actual": df_test["a"].dtypes, "expected": df["a"].dtypes}
}
numerical_checker_failed_checks = x._transform_numerical_checker(
df_test, type_fails_dict, batch_mode=False
)
h.assert_equal_dispatch(
actual=numerical_checker_failed_checks,
expected={},
msg="rows failing type check have not been removed by _transform_numerical_checker",
)
# Case 2: column a should still get checked because even though type does not match,
# int != float the column is still numerical
df_test2 = pd.DataFrame({"a": [5, 3, 222]})
type_fails_dict2 = {
"a": {"actual": df_test2["a"].dtypes, "expected": df["a"].dtypes}
}
numerical_checker_failed_checks2 = x._transform_numerical_checker(
df_test2, type_fails_dict2, batch_mode=False
)
h.assert_equal_dispatch(
actual=numerical_checker_failed_checks2,
expected={"a": {"max idxs": [2], "maximum": {2: 222}}},
msg="rows failing type check have not been removed by _transform_numerical_checker",
)
class TestTransformValueChecker(object):
"""Tests for InputChecker._transform_value_checker()."""
def test_arguments(self):
"""Test that InputChecker _transform_value_checker has expected arguments."""
h.test_function_arguments(
func=InputChecker._transform_value_checker, expected_arguments=["self", "X"]
)
def test_check_fitted_called(self, mocker):
"""Test that transform calls BaseTransformer.check_is_fitted."""
expected_call_args = {0: {"args": (["expected_values"],), "kwargs": {}}}
x = InputChecker(categorical_columns=["b", "c"])
df = data_generators_p.create_df_2()
x.fit(df)
with h.assert_function_call(
mocker, tubular.base.BaseTransformer, "check_is_fitted", expected_call_args
):
x._transform_value_checker(df)
def test_transform_returns_failed_checks_dict(self):
"""Test _transform_value_checker returns results dictionary"""
df = data_generators_p.create_df_2()
x = InputChecker(categorical_columns=["b", "c"])
x.fit(df)
value_checker_failed_checks = x._transform_value_checker(df)
assert isinstance(
value_checker_failed_checks, dict
), f"incorrect numerical results type identified - expected: dict but got: {type(value_checker_failed_checks)}"
def test_transform_passes(self):
"""Test _transform_value_checker passes all the categorical checks on the training dataframe"""
df = data_generators_p.create_df_2()
x = InputChecker(categorical_columns=["b", "c"])
x.fit(df)
value_checker_failed_checks = x._transform_value_checker(df)
assert (
value_checker_failed_checks == {}
), f"Categorical checker found failed tests - {list(value_checker_failed_checks.keys())}"
def test_transform_captures_failed_test(self):
"""Test _transform_value_checker captures a failed check"""
df = data_generators_p.create_df_2()
x = InputChecker(categorical_columns=["b", "c"])
x.fit(df)
df.loc[5, "b"] = "u"
value_checker_failed_checks = x._transform_value_checker(df)
assert value_checker_failed_checks["b"]["values"] == [
"u"
], f"incorrect values saved to value_checker_failed_checks - expected: ['u'] but got: {value_checker_failed_checks['b']['values']}"
assert value_checker_failed_checks["b"]["idxs"] == [
5
], f"incorrect values saved to value_checker_failed_checks - expected: [5] but got: {value_checker_failed_checks['b']['idxs']}"
class TestTransformDatetimeChecker(object):
"""Tests for InputChecker._transform_datetime_checker()."""
def test_arguments(self):
"""Test that InputChecker _transform_datetime_checker has expected arguments."""
h.test_function_arguments(
func=InputChecker._transform_datetime_checker,
expected_arguments=["self", "X", "type_fails", "batch_mode"],
expected_default_values=(
{},
False,
),
)
def test_check_fitted_called(self, mocker):
"""Test that transform calls BaseTransformer.check_is_fitted."""
expected_call_args = {0: {"args": (["datetime_values"],), "kwargs": {}}}
x = InputChecker(datetime_columns=["d"])
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
np.NAN,
]
)
x.fit(df)
with h.assert_function_call(
mocker, tubular.base.BaseTransformer, "check_is_fitted", expected_call_args
):
x._transform_datetime_checker(df, {})
def test_transform_returns_failed_checks_dict(self):
"""Test _transform_datetime_checker returns results dictionary"""
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
np.NAN,
]
)
x = InputChecker(datetime_columns=["d"])
x.fit(df)
datetime_checker_failed_checks = x._transform_datetime_checker(df, {})
assert isinstance(
datetime_checker_failed_checks, dict
), f"incorrect datetime results type identified - expected: dict but got: {type(datetime_checker_failed_checks)}"
def test_transform_passes(self):
"""Test _transform_datetime_checker passes all the numerical checks on the training dataframe"""
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
np.NAN,
]
)
x = InputChecker(datetime_columns=["d"])
x.fit(df)
datetime_checker_failed_checks = x._transform_datetime_checker(df, {})
assert (
datetime_checker_failed_checks == {}
), f"Datetime checker found failed tests - {list(datetime_checker_failed_checks.keys())}"
def test_transform_captures_failed_test(self):
"""Test _transform_datetime_checker captures a failed check"""
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
np.NAN,
]
)
x = InputChecker(datetime_columns=["d"])
x.fit(df)
outliers_1 = pd.to_datetime("15/09/2017", utc=False)
outliers_2 = pd.to_datetime("13/09/2017", utc=False)
df.loc[0, "d"] = outliers_1
df.loc[1, "d"] = outliers_2
datetime_checker_failed_checks = x._transform_datetime_checker(df, {})
results = datetime_checker_failed_checks["d"]["minimum"]
assert results[0] == outliers_1, (
f"incorrect values saved to datetime_checker_failed_checks - "
f"expected: {outliers_1} but got: {results[0]} "
)
assert results[1] == outliers_2, (
f"incorrect values saved to datetime_checker_failed_checks - "
f"expected: {outliers_2} but got: {results[1]} "
)
def test_transform_captures_failed_test_both_minimum_and_maximum(self):
"""Test _transform_datetime_checker captures a failed check when the check includes a maximum value and a
minimum value"""
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
datetime_dict = {"d": {"maximum": True, "minimum": True}}
x = InputChecker(datetime_columns=datetime_dict)
x.fit(df)
lower_outliers = pd.to_datetime("15/09/2017", utc=False)
upper_outliers = pd.to_datetime("20/01/2021", utc=False)
df.loc[0, "d"] = lower_outliers
df.loc[5, "d"] = upper_outliers
datetime_checker_failed_checks = x._transform_datetime_checker(df, {})
expected_min = {0: lower_outliers}
expected_max = {5: upper_outliers}
assert datetime_checker_failed_checks["d"]["maximum"] == expected_max, (
f"incorrect values saved to "
f"datetime_checker_failed_checks - "
f"expected: {expected_max} but got: "
f"{datetime_checker_failed_checks['d']['maximum']} "
)
assert datetime_checker_failed_checks["d"]["minimum"] == expected_min, (
f"incorrect values saved to "
f"datetime_checker_failed_checks - "
f"expected: {expected_min} but got: "
f"{datetime_checker_failed_checks['d']['minimum']} "
)
def test_transform_skips_failed_type_checks_batch_mode(self):
"""Test _transform_datetime_checker skips checks for rows which aren't datetime type
when operating in batch mode"""
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x = InputChecker(datetime_columns=["d"])
x.fit(df)
df.loc[3, "d"] = 1
df.loc[4, "d"] = "z"
df.loc[5, "d"] = pd.to_datetime("20/09/2011", utc=False)
type_fails_dict = {
"d": {
"idxs": [3, 4],
"actual": {3: "int", 4: "str"},
"expected": "Timestamp",
}
}
datetime_checker_failed_checks = x._transform_datetime_checker(
df, type_fails_dict, batch_mode=True
)
h.assert_equal_dispatch(
actual=datetime_checker_failed_checks,
expected={
"d": {
"minimum": {5: pd.to_datetime("20/09/2011", utc=False)},
"min idxs": [5],
}
},
msg="rows failing type check have not been removed by _transform_datetime_checker",
)
def test_transform_skips_failed_type_checks(self):
"""Test _transform_datetime_checker skips checks for columns which aren't datetime
when not operating in batch mode"""
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x = InputChecker(datetime_columns=["d"])
x.fit(df)
df_test = pd.DataFrame({"d": ["z", "zz", "zzz"]})
type_fails_dict = {
"d": {"actual": df_test["d"].dtypes, "expected": df["d"].dtypes}
}
datetime_checker_failed_checks = x._transform_datetime_checker(
df_test, type_fails_dict, batch_mode=False
)
h.assert_equal_dispatch(
actual=datetime_checker_failed_checks,
expected={},
msg="rows failing type check have not been removed by _transform_datetime_checker",
)
class TestTransform(object):
"""Tests for InputChecker.transform()."""
def test_arguments(self):
"""Test that transform has expected arguments."""
h.test_function_arguments(
func=InputChecker.transform,
expected_arguments=["self", "X", "batch_mode"],
expected_default_values=(False,),
)
def test_super_transform_called(self, mocker):
"""Test super transform is called by the transform method."""
x = InputChecker(
columns=["a", "b", "c", "d"],
numerical_columns=["a"],
categorical_columns=["b", "c"],
datetime_columns=["d"],
)
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x.fit(df)
spy = mocker.spy(tubular.base.BaseTransformer, "transform")
df = x.transform(df)
assert (
spy.call_count == 1
), "unexpected number of calls to tubular.base.BaseTransformer.transform with transform"
def test_transform_returns_df(self):
"""Test fit returns df"""
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x = InputChecker()
x.fit(df)
df_transformed = x.transform(df)
assert df_transformed.equals(
df
), "Returned value from InputChecker.transform not as expected."
def test_batch_mode_transform_returns_df(self):
"""Test fit returns df"""
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x = InputChecker()
x.fit(df)
df_transformed, bad_df = x.transform(df, batch_mode=True)
assert df_transformed.equals(
df
), "Returned value from InputChecker.transform not as expected."
h.assert_equal_dispatch(
expected=df,
actual=df_transformed,
msg="Returned df of passed rows from InputChecker.transform not as expected.",
)
h.assert_equal_dispatch(
expected=pd.DataFrame(
columns=df.columns.values.tolist() + ["failed_checks"]
),
actual=bad_df,
msg="Returned df of failed rows from InputChecker.transform not as expected.",
)
def test_check_df_is_empty_called(self, mocker):
"""Test check is df empty is called by the transform method."""
x = InputChecker(
columns=["a", "b", "c", "d"],
numerical_columns=["a"],
categorical_columns=["b", "c"],
datetime_columns=["d"],
)
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x.fit(df)
spy = mocker.spy(input_checker.checker.InputChecker, "_df_is_empty")
df = x.transform(df)
assert (
spy.call_count == 1
), "unexpected number of calls to InputChecker._df_is_empty with transform"
call_0_args = spy.call_args_list[0]
call_0_pos_args = call_0_args[0]
expected_pos_args_0 = (x, "scoring dataframe", df)
h.assert_equal_dispatch(
expected=expected_pos_args_0,
actual=call_0_pos_args,
msg="positional args unexpected in _df_is_empty call for scoring dataframe argument",
)
def test_non_optional_transforms_always_called(self, mocker):
"""Test non-optional checks are called by the transform method irrespective of categorical_columns,
numerical_columns & datetime_columns values."""
x = InputChecker(
numerical_columns=None, categorical_columns=None, datetime_columns=None
)
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x.fit(df)
spy_null = mocker.spy(
input_checker.checker.InputChecker, "_transform_null_checker"
)
spy_type = mocker.spy(
input_checker.checker.InputChecker, "_transform_type_checker"
)
df = x.transform(df)
assert spy_null.call_count == 1, (
"unexpected number of calls to _transform_null_checker with transform when numerical_columns and "
"categorical_columns set to None "
)
assert spy_type.call_count == 1, (
"unexpected number of calls to _transform_type_checker with transform when numerical_columns and "
"categorical_columns set to None "
)
def test_optional_transforms_not_called(self, mocker):
"""Test optional checks are not called by the transform method."""
x = InputChecker(
numerical_columns=None, categorical_columns=None, datetime_columns=None
)
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x.fit(df)
spy_numerical = mocker.spy(
input_checker.checker.InputChecker, "_transform_numerical_checker"
)
spy_categorical = mocker.spy(
input_checker.checker.InputChecker, "_transform_value_checker"
)
spy_datetime = mocker.spy(
input_checker.checker.InputChecker, "_transform_datetime_checker"
)
df = x.transform(df)
assert (
spy_numerical.call_count == 0
), "unexpected number of calls to _transform_numerical_checker with transform when numerical_columns set to None"
assert (
spy_categorical.call_count == 0
), "unexpected number of calls to _transform_value_checker with transform when categorical_columns set to None"
assert (
spy_datetime.call_count == 0
), "unexpected number of calls to _transform_datetime_checker with transform when datetime_columns set to None"
def test_raise_exception_if_checks_fail_called_no_optionals(self, mocker):
"""Test raise exception is called by the transform method when categorical, numerical_& datetime columns set
to None."""
x = InputChecker()
df = data_generators_p.create_df_2()
x.fit(df)
spy = mocker.spy(
input_checker.checker.InputChecker, "raise_exception_if_checks_fail"
)
df = x.transform(df)
assert (
spy.call_count == 1
), "unexpected number of calls to InputChecker.raise_exception_if_checks_fail with transform"
call_0_args = spy.call_args_list[0]
call_0_pos_args = call_0_args[0]
value_failed_checks = {}
numerical_failed_checks = {}
datetime_failed_checks = {}
type_failed_checks = x._transform_type_checker(df)
null_failed_checks = x._transform_null_checker(df)
expected_pos_args_0 = (
x,
type_failed_checks,
null_failed_checks,
value_failed_checks,
numerical_failed_checks,
datetime_failed_checks,
)
assert (
expected_pos_args_0 == call_0_pos_args
), "positional args unexpected in raise_exception_if_checks_fail call in transform method"
def test_raise_exception_if_checks_fail_called_all_checks(self, mocker):
"""Test raise exception is called by the transform method when categorical_columns and numerical_columns set
to None."""
x = InputChecker(
numerical_columns=["a"],
categorical_columns=["b", "c"],
datetime_columns=["d"],
)
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
x.fit(df)
spy = mocker.spy(
input_checker.checker.InputChecker, "raise_exception_if_checks_fail"
)
df = x.transform(df)
assert (
spy.call_count == 1
), "unexpected number of calls to InputChecker.raise_exception_if_checks_fail with transform"
call_0_args = spy.call_args_list[0]
call_0_pos_args = call_0_args[0]
value_failed_checks = x._transform_value_checker(df)
numerical_failed_checks = x._transform_numerical_checker(df)
datetime_failed_checks = x._transform_datetime_checker(df)
type_failed_checks = x._transform_type_checker(df)
null_failed_checks = x._transform_null_checker(df)
expected_pos_args_0 = (
x,
type_failed_checks,
null_failed_checks,
value_failed_checks,
numerical_failed_checks,
datetime_failed_checks,
)
assert (
expected_pos_args_0 == call_0_pos_args
), "positional args unexpected in raise_exception_if_checks_fail call in transform method"
def test_separate_passes_and_fails_called_no_optionals(self, mocker):
"""Test raise exception is called by the transform method when categorical, numerical_& datetime columns set
to None."""
x = InputChecker()
df = data_generators_p.create_df_2()
orig_df = df.copy(deep=True)
x.fit(df)
spy = mocker.spy(
input_checker.checker.InputChecker, "separate_passes_and_fails"
)
df, bad_df = x.transform(df, batch_mode=True)
assert (
spy.call_count == 1
), "unexpected number of calls to InputChecker.separate_passes_and_fails with transform"
call_0_args = spy.call_args_list[0]
call_0_pos_args = call_0_args[0]
value_failed_checks = {}
numerical_failed_checks = {}
datetime_failed_checks = {}
type_failed_checks = x._transform_type_checker(df)
null_failed_checks = x._transform_null_checker(df)
expected_pos_args_0 = (
x,
type_failed_checks,
null_failed_checks,
value_failed_checks,
numerical_failed_checks,
datetime_failed_checks,
orig_df,
)
h.assert_equal_dispatch(
expected=expected_pos_args_0,
actual=call_0_pos_args,
msg="positional args unexpected in separate_passes_and_fails call in transform method",
)
def test_separate_passes_and_fails_called_all_checks(self, mocker):
"""Test raise exception is called by the transform method when categorical_columns and numerical_columns set
to None."""
x = InputChecker(
numerical_columns=["a"],
categorical_columns=["b", "c"],
datetime_columns=["d"],
)
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
"24/07/2020",
]
)
orig_df = df.copy(deep=True)
x.fit(df)
spy = mocker.spy(
input_checker.checker.InputChecker, "separate_passes_and_fails"
)
df, bad_df = x.transform(df, batch_mode=True)
assert (
spy.call_count == 1
), "unexpected number of calls to InputChecker.separate_passes_and_fails with transform"
call_0_args = spy.call_args_list[0]
call_0_pos_args = call_0_args[0]
value_failed_checks = x._transform_value_checker(df)
numerical_failed_checks = x._transform_numerical_checker(df)
datetime_failed_checks = x._transform_datetime_checker(df)
type_failed_checks = x._transform_type_checker(df)
null_failed_checks = x._transform_null_checker(df)
expected_pos_args_0 = (
x,
type_failed_checks,
null_failed_checks,
value_failed_checks,
numerical_failed_checks,
datetime_failed_checks,
orig_df,
)
h.assert_equal_dispatch(
expected=expected_pos_args_0,
actual=call_0_pos_args,
msg="positional args unexpected in separate_passes_and_fails call in transform method",
)
class TestRaiseExceptionIfChecksFail(object):
"""Tests for InputChecker.raise_exception_if_checks_fail()."""
def test_arguments(self):
"""Test that raise_exception_if_checks_fail has expected arguments."""
h.test_function_arguments(
func=InputChecker.raise_exception_if_checks_fail,
expected_arguments=[
"self",
"type_failed_checks",
"null_failed_checks",
"value_failed_checks",
"numerical_failed_checks",
"datetime_failed_checks",
],
expected_default_values=None,
)
def test_no_failed_checks_before_transform(self):
"""Test validation_failed_checks is not present before transform"""
x = InputChecker()
df = data_generators_p.create_df_2()
x.fit(df)
assert (
hasattr(x, "validation_failed_checks") is False
), "validation_failed_checks attribute present before transform"
def test_validation_failed_checks_saved(self):
"""Test raise_exception_if_checks_fail saves the validation results"""
df = data_generators_p.create_df_2()
x = InputChecker()
x.fit(df)
df = x.transform(df)
assert (
hasattr(x, "validation_failed_checks") is True
), "validation_failed_checks attribute not present after transform"
assert isinstance(
x.validation_failed_checks, dict
), f"incorrect validation results type identified - expected: dict but got: {type(x.validation_failed_checks)}"
def test_correct_validation_failed_checks(self):
"""Test raise_exception_if_checks_fail saves and prints the correct error message"""
df = data_generators_p.create_df_2()
x = InputChecker()
x.fit(df)
df = x.transform(df)
assert isinstance(
x.validation_failed_checks["Failed type checks"], dict
), f"incorrect type validation results type identified - expected: dict but got: {type(x.validation_failed_checks['Failed type checks'])}"
assert isinstance(
x.validation_failed_checks["Failed null checks"], dict
), f"incorrect null validation results type identified - expected: dict but got: {type(x.validation_failed_checks['Failed null checks'])}"
assert isinstance(
x.validation_failed_checks["Failed categorical checks"], dict
), f"incorrect categorical validation results type identified - expected: dict but got: {type(x.validation_failed_checks['Failed categorical checks'])}"
assert isinstance(
x.validation_failed_checks["Failed numerical checks"], dict
), f"incorrect numerical validation results type identified - expected: dict but got: {type(x.validation_failed_checks['Failed numerical checks'])}"
assert isinstance(
x.validation_failed_checks["Failed datetime checks"], dict
), f"incorrect datetime validation results type identified - expected: dict but got: {type(x.validation_failed_checks['Failed datetime checks'])}"
assert isinstance(
x.validation_failed_checks["Exception message"], str
), f"incorrect exception message type identified - expected: str but got: {type(x.validation_failed_checks['Exception message'])}"
def test_input_checker_error_raised_type(self):
"""Test InputCheckerError is raised if type test fails"""
x = InputChecker()
df = data_generators_p.create_df_2()
x.fit(df)
df.loc[5, "a"] = "a"
with pytest.raises(InputCheckerError):
df = x.transform(df)
def test_input_checker_error_raised_nulls(self):
"""Test InputCheckerError is raised if null test fails"""
x = InputChecker()
df = data_generators_p.create_df_2()
df["b"] = df["b"].fillna("a")
x = InputChecker()
x.fit(df)
df.loc[5, "b"] = np.nan
with pytest.raises(InputCheckerError):
df = x.transform(df)
def test_input_checker_error_raised_categorical(self):
"""Test InputCheckerError is raised if categorical test fails"""
x = InputChecker(categorical_columns=["b"])
df = data_generators_p.create_df_2()
x.fit(df)
df.loc[5, "b"] = "u"
with pytest.raises(InputCheckerError):
df = x.transform(df)
def test_input_checker_error_raised_numerical(self):
"""Test InputCheckerError is raised if numerical test fails"""
x = InputChecker(numerical_columns=["a"])
df = data_generators_p.create_df_2()
x.fit(df)
df.loc[0, "a"] = -1
with pytest.raises(InputCheckerError):
df = x.transform(df)
def test_input_checker_error_raised_datetime(self):
"""Test InputCheckerError is raised if datetime test fails"""
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
np.NAN,
]
)
x = InputChecker(datetime_columns=["d"])
x.fit(df)
outliers_1 = pd.to_datetime("15/09/2017")
outliers_2 = pd.to_datetime("13/09/2017")
df.loc[0, "d"] = outliers_1
df.loc[1, "d"] = outliers_2
with pytest.raises(InputCheckerError):
df = x.transform(df)
def test_validation_failed_checks_correctly_stores_fails(self):
"""Test correct data is saved in validation_failed_checks after a failed check exception"""
x = InputChecker()
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
np.NAN,
]
)
df["b"] = df["b"].fillna("a")
x.fit(df)
df.loc[0, "a"] = -1
df.loc[4, "b"] = "u"
df.loc[5, "b"] = np.nan
df["c"] = [True, True, False, True, True, False, np.nan]
df["c"] = df["c"].astype("bool")
df.loc[0, "d"] = pd.to_datetime("15/09/2017")
with pytest.raises(InputCheckerError):
df = x.transform(df)
assert list(x.validation_failed_checks["Failed null checks"]) == [
"b"
], f"incorrect failed null checks identified - expected: ['b'] but got: {list(x.validation_failed_checks['Failed null checks'])}"
assert list(x.validation_failed_checks["Failed type checks"]) == [
"c"
], f"incorrect failed type checks identified - expected: ['b'] but got: {list(x.validation_failed_checks['Failed null checks'])}"
assert x.validation_failed_checks["Failed null checks"]["b"] == [
5
], f"incorrect failed null checks error message - expected: [5] but got: {x.validation_failed_checks['Failed null checks']['b']}"
expected_type_fail_chk = {
"actual": np.dtype("bool"),
"expected": pd.CategoricalDtype(
categories=["a", "b", "c", "d", "e", "f"], ordered=False
),
}
assert (
x.validation_failed_checks["Failed type checks"]["c"]
== expected_type_fail_chk
), f"incorrect failed type checks error message - expected: (CategoricalDtype(categories=['a', 'b', 'c', 'd', 'e', 'f'], ordered=False), dtype('bool')) but got: {x.validation_failed_checks['Failed type checks']['c']}"
assert (
any(x.validation_failed_checks["Failed categorical checks"].values())
is False
), f"incorrect failed categorical checks identified - expected: empty dict but got: {list(x.validation_failed_checks['Failed categorical checks'])}"
assert (
any(x.validation_failed_checks["Failed numerical checks"].values()) is False
), f"incorrect failed numerical checks identified - expected: empty dict but got: {list(x.validation_failed_checks['Failed numerical checks'])}"
assert (
any(x.validation_failed_checks["Failed datetime checks"].values()) is False
), f"incorrect failed datetime checks identified - expected: empty dict but got: {list(x.validation_failed_checks['Failed datetime checks'])}"
class TestSeparatePassAndFails(object):
"""Tests for InputChecker.separate_passes_and_fails()."""
def test_arguments(self):
"""Test that separate_passes_and_fails has expected arguments."""
h.test_function_arguments(
func=InputChecker.separate_passes_and_fails,
expected_arguments=[
"self",
"type_failed_checks",
"null_failed_checks",
"value_failed_checks",
"numerical_failed_checks",
"datetime_failed_checks",
"X",
],
expected_default_values=None,
)
def test_input_checker_type_errors_shape(self):
"""Test correct dataframes are returned if type test fails"""
x = InputChecker()
df = data_generators_p.create_df_2()
x.fit(df)
df.loc[5, "a"] = "a"
good_df, bad_df = x.transform(df, batch_mode=True)
assert not (
5 in good_df.index.tolist()
), "Type failure does not remove the index"
assert good_df.shape[0] == 6, "Wrong shape for the correct return dataframe"
assert 5 in bad_df.index.tolist(), "Type failure does not track mixed index"
assert (
bad_df.shape[0] == 1
), f"Wrong number of rows for bad dataframe. Was expecting one row, instead return {bad_df.shape[0]}"
assert bad_df.shape[1] == (
df.shape[1] + 1
), f"Wrong number of columns for bad dataframe. Was expecting {df.shape[1]+1}, instead returned {bad_df.shape[1]}"
def test_input_checker_type_errors_column(self):
"""Test correct error column message is returned if type test fails"""
x = InputChecker()
df = data_generators_p.create_df_2()
x.fit(df)
df.loc[5, "a"] = "a"
df.loc[5, "b"] = 1
good_df, bad_df = x.transform(df, batch_mode=True)
assert (
"failed_checks" in bad_df.columns.tolist()
), "Bad dataframe does not include the column 'failed_checks'"
expected = "Failed type check for column: a; Expected: float, Found: str\nFailed type check for column: b; Expected: str, Found: int"
actual = bad_df["failed_checks"].unique().tolist()
assert (
len(actual) == 1
), f"Values in failed_checks not as expected: actual: {actual} expected: {expected}"
assert (
actual[0] == expected
), f"Values in failed_checks not as expected: actual: {actual} expected: {expected}"
def test_input_checker_null_errors_shape(self):
"""Test correct dataframes are returned if null test fails"""
x = InputChecker()
df = data_generators_p.create_df_2()
df["b"] = df["b"].fillna("a")
x.fit(df)
df.loc[5, "b"] = np.nan
good_df, bad_df = x.transform(df, batch_mode=True)
assert not (
5 in good_df.index.tolist()
), "Type failure does not remove the index"
assert good_df.shape[0] == (
df.shape[0] - 1
), "Wrong shape for the correct return dataframe"
assert 5 in bad_df.index.tolist(), "Type failure does not track mixed index"
assert (
bad_df.shape[0] == 1
), f"Wrong number of rows for bad dataframe. Was expecting one row, instead return {bad_df.shape[0]}"
assert bad_df.shape[1] == (
df.shape[1] + 1
), f"Wrong number of columns for bad dataframe. Was expecting {df.shape[1]+1}, instead returned {bad_df.shape[1]}"
def test_input_checker_null_errors_column(self):
"""Test correct error column message is returned if null test fails"""
x = InputChecker()
df = data_generators_p.create_df_2()
df["b"] = df["b"].fillna("a")
x.fit(df)
df.loc[5, "b"] = np.nan
good_df, bad_df = x.transform(df, batch_mode=True)
assert (
"failed_checks" in bad_df.columns.tolist()
), "Bad dataframe does not include the column 'failed_checks'"
message = bad_df["failed_checks"].item()
expected = "Failed null check for column: b"
h.assert_equal_msg(message, expected, "Value in Reason Failed not as expected")
def test_input_checker_categorical_errors_shape(self):
"""Test correct dataframes are returned if categorical test fails"""
x = InputChecker(categorical_columns=["b"])
df = data_generators_p.create_df_2()
x.fit(df)
df.loc[5, "b"] = "u"
good_df, bad_df = x.transform(df, batch_mode=True)
assert not (
5 in good_df.index.tolist()
), "Type failure does not remove the index"
assert good_df.shape[0] == (
df.shape[0] - 1
), "Wrong shape for the correct return dataframe"
assert 5 in bad_df.index.tolist(), "Type failure does not track mixed index"
assert (
bad_df.shape[0] == 1
), f"Wrong number of rows for bad dataframe. Was expecting one row, instead return {bad_df.shape[0]}"
assert bad_df.shape[1] == (
df.shape[1] + 1
), f"Wrong number of columns for bad dataframe. Was expecting {df.shape[1]+1}, instead returned {bad_df.shape[1]}"
def test_input_checker_categorical_errors_column(self):
"""Test correct error column message is returned if categorical test fails"""
x = InputChecker(categorical_columns=["b"])
df = data_generators_p.create_df_2()
x.fit(df)
df.loc[5, "b"] = "u"
good_df, bad_df = x.transform(df, batch_mode=True)
assert (
"failed_checks" in bad_df.columns.tolist()
), "Bad dataframe does not include the column 'failed_checks'"
message = bad_df["failed_checks"].item()
expected = "Failed categorical check for column: b. Unexpected values are ['u']"
h.assert_equal_msg(message, expected, "Value in failed_checks not as expected")
def test_input_checker_numerical_errors_shape(self):
"""Test correct dataframes are returned if numerical test fails"""
x = InputChecker(numerical_columns=["a"])
df = data_generators_p.create_df_2()
x.fit(df)
df.loc[0, "a"] = -1
good_df, bad_df = x.transform(df, batch_mode=True)
assert not (
0 in good_df.index.tolist()
), "Type failure does not remove the index"
assert good_df.shape[0] == (
df.shape[0] - 1
), "Wrong shape for the correct return dataframe"
assert 0 in bad_df.index.tolist(), "Type failure does not track mixed index"
assert (
bad_df.shape[0] == 1
), f"Wrong number of rows for bad dataframe. Was expecting one row, instead return {bad_df.shape[0]}"
assert bad_df.shape[1] == (
df.shape[1] + 1
), f"Wrong number of columns for bad dataframe. Was expecting {df.shape[1]+1}, instead returned {bad_df.shape[1]}"
def test_input_checker_numerical_errors_column(self):
"""Test correct error column message is returned if numerical test fails"""
x = InputChecker(numerical_columns=["a"])
df = data_generators_p.create_df_2()
x.fit(df)
df.loc[0, "a"] = -1
good_df, bad_df = x.transform(df, batch_mode=True)
assert (
"failed_checks" in bad_df.columns.tolist()
), "Bad dataframe does not include the column 'failed_checks'"
message = bad_df["failed_checks"].item()
expected = "Failed minimum value check for column: a; Value below minimum: -1.0"
h.assert_equal_msg(message, expected, "Value in Reason Fails not as expected")
def test_input_checker_datetime_errors_shape(self):
"""Test correct dataframes are returned if datetime test fails"""
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
np.NAN,
]
)
x = InputChecker(datetime_columns=["d"])
x.fit(df)
outliers_1 = pd.to_datetime("15/09/2017")
outliers_2 = pd.to_datetime("13/09/2017")
df.loc[0, "d"] = outliers_1
df.loc[1, "d"] = outliers_2
good_df, bad_df = x.transform(df, batch_mode=True)
assert not (
0 in good_df.index.tolist() and (1 in good_df.index.tolist())
), "Type failure does not remove the index"
assert good_df.shape[0] == (
df.shape[0] - 2
), "Wrong shape for the correct return dataframe"
assert (0 in bad_df.index.tolist()) and (
1 in bad_df.index.tolist()
), "Type failure does not track mixed index"
assert (
bad_df.shape[0] == 2
), f"Wrong number of rows for bad dataframe. Was expecting one row, instead return {bad_df.shape[0]}"
assert bad_df.shape[1] == (
df.shape[1] + 1
), f"Wrong number of columns for bad dataframe. Was expecting {df.shape[1]+1}, instead returned {bad_df.shape[1]}"
def test_input_checker_datetime_errors_column(self):
"""Test correct error column message is returned if numerical test fails"""
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
np.NAN,
]
)
x = InputChecker(datetime_columns=["d"])
x.fit(df)
outliers_1 = pd.to_datetime("15/09/2017")
outliers_2 = pd.to_datetime("13/09/2017")
df.loc[0, "d"] = outliers_1
df.loc[1, "d"] = outliers_2
good_df, bad_df = x.transform(df, batch_mode=True)
assert (
"failed_checks" in bad_df.columns.tolist()
), "Bad dataframe does not include the column 'failed_checks'"
message_0 = bad_df.loc[0, "failed_checks"]
message_1 = bad_df.loc[1, "failed_checks"]
expected_0 = (
"Failed minimum value check for column: d; Value below minimum: 2017-09-15"
)
expected_1 = (
"Failed minimum value check for column: d; Value below minimum: 2017-09-13"
)
h.assert_equal_msg(
message_0, expected_0, "Value in Reason Failed not as expected"
)
h.assert_equal_msg(
message_1, expected_1, "Value in Reason Failed not as expected"
)
def test_full_failed_checks(self):
"""Test correct data is outputted for multiple failed exceptions"""
x = InputChecker(
numerical_columns=["a"], datetime_columns=["d"], categorical_columns=["b"]
)
df = data_generators_p.create_df_2()
df["d"] = pd.to_datetime(
[
"01/02/2020",
"01/02/2021",
"08/04/2019",
"01/03/2020",
"29/03/2019",
"15/10/2018",
np.NAN,
]
)
df["b"] = df["b"].fillna("a")
x.fit(df)
df.loc[0, "a"] = -1
df.loc[4, "b"] = "u"
df.loc[5, "b"] = None
# for type check failues
df["c"] = ["a", "b", "c", "d", True, "f", "e"]
df.loc[2, "a"] = "z"
df.loc[2, "d"] = 1
df.loc[0, "d"] = pd.to_datetime("15/09/2017")
good_df, bad_df = x.transform(df, batch_mode=True)
assert good_df.shape[0] == (
3
), f"Incorrect good df num rows. Expected {3} but got {good_df.shape[0]}"
assert (
bad_df.shape[0] == 4
), f"Incorred bad df num rows. Expected {4} but go {bad_df.shape[0]}"
assert bad_df.shape[1] == (
df.shape[1] + 1
), f"Expected bad df to have {df.shape[1]+1} columns, but got {bad_df.shape[1]} instead"
expected_msg_0 = "Failed minimum value check for column: a; Value below minimum: -1.0\nFailed minimum value check for column: d; Value below minimum: 2017-09-15"
expected_msg_2 = "Failed type check for column: a; Expected: float, Found: str\nFailed type check for column: d; Expected: Timestamp, Found: int"
expected_msg_4 = "Failed categorical check for column: b. Unexpected values are ['u']\nFailed type check for column: c; Expected: str, Found: bool"
expected_msg_5 = "Failed null check for column: b"
h.assert_equal_msg(
bad_df["failed_checks"].loc[0],
expected_msg_0,
"Wrong message in reason failed for index 0",
)
h.assert_equal_msg(
bad_df["failed_checks"].loc[2],
expected_msg_2,
"Wrong message in reason failed for index 2",
)
h.assert_equal_msg(
bad_df["failed_checks"].loc[4],
expected_msg_4,
"Wrong message in reason failed for index 4",
)
h.assert_equal_msg(
bad_df["failed_checks"].loc[5],
expected_msg_5,
"Wrong message in reason failed for index 5",
)
def test_multiple_value_error_fails_on_same_row(self):
"""Test that failed checks are updated correctly for rows with multiple
columns which fail _transform_value_checker"""
df = pd.DataFrame({"col1": ["a", "b", "c"], "col2": ["a", "b", "c"]})
checker = InputChecker(
columns=["col1", "col2"],
categorical_columns=["col1", "col2"],
)
checker.fit(df)
df_new = pd.DataFrame({"col1": ["a", "d", "a"], "col2": ["a", "d", "a"]})
good_df, bad_df = checker.transform(df_new, batch_mode=True)
expected_msg = "Failed categorical check for column: col1. Unexpected values are ['d']\nFailed categorical check for column: col2. Unexpected values are ['d']"
assert bad_df.index.tolist() == [
1
], "Wrong rows in bad_df when a row fails multiple value checks"
h.assert_equal_msg(
bad_df["failed_checks"].loc[1],
expected_msg,
"Wrong message in reason failed when a row fails multiple value checks",
)
class TestUpdateBadDF(object):
"""Tests for InputChecker._update_bad_df()."""
def test_arguments(self):
"""Test that _update_bad_df has expected arguments."""
h.test_function_arguments(
func=InputChecker._update_bad_df,
expected_arguments=[
"self",
"bad_df",
"idxs",
"reason_failed",
"error_info_by_row",
],
expected_default_values=(None,),
)
def test_expected_output(self):
"""Test that _update_bad_df works as expected."""
x = InputChecker(numerical_columns=["u"])
df = data_generators_p.create_df_2()
df["failed_checks"] = "fail 1"
bad_df = x._update_bad_df(df, [2, 4], "fail 2")
# check message updated as expected
h.assert_equal_dispatch(
expected=[
"fail 1",
"fail 1",
"fail 1\nfail 2",
"fail 1",
"fail 1\nfail 2",
"fail 1",
"fail 1",
],
actual=bad_df["failed_checks"].values.tolist(),
msg="failed_checks not updated as expected by _update_bad_df",
)
# check other columns unchanged
h.assert_equal_dispatch(
expected=df,
actual=bad_df[df.columns],
msg="other columns have been modified by _update_bad_df",
)
class TestUpdateGoodBadDF(object):
"""Tests for InputChecker._update_good_bad_df()."""
def test_arguments(self):
"""Test that _update_good_bad_df has expected arguments."""
h.test_function_arguments(
func=InputChecker._update_good_bad_df,
expected_arguments=[
"self",
"good_df",
"bad_df",
"idxs",
"reason_failed",
"error_info_by_row",
],
expected_default_values=(None,),
)
def test_expected_output(self):
"""Test that _update_good_bad_df works as expected."""
x = InputChecker(numerical_columns=["u"])
df = data_generators_p.create_df_2()
bad_df = df.loc[[2, 4]]
good_df = df.loc[[0, 1, 3, 5, 6]]
bad_df["failed_checks"] = "fail 1"
good_df_up, bad_df_up = x._update_good_bad_df(good_df, bad_df, [3, 6], "fail 2")
# check message in bad_df updated as expected
h.assert_equal_dispatch(
expected=["fail 1", "fail 1", "fail 2", "fail 2"],
actual=bad_df_up["failed_checks"].values.tolist(),
msg="failed_checks not updated as expected by _update_good_bad_df",
)
# check other columns in bad_df unchanged
h.assert_equal_dispatch(
expected=df.loc[[2, 4, 3, 6], :],
actual=bad_df_up[df.columns],
msg="other columns have been modified in bad_df by _update_good_bad_df",
)
# check good_df
h.assert_equal_dispatch(
expected=df.loc[[0, 1, 5], :],
actual=good_df_up,
msg="wrong good_df returned by _update_good_bad_df",
)
class TestCheckType(object):
"""Tests for InputChecker._check_type()."""
def test_arguments(self):
"""Test that _check_type has expected arguments."""
h.test_function_arguments(
func=InputChecker._check_type,
expected_arguments=["self", "obj", "obj_name", "options"],
expected_default_values=None,
)
def test_exception(self):
"""Test that _check_type fails with the correct error."""
with pytest.raises(TypeError):
InputChecker(numerical_columns=pd.DataFrame())
class TestIsStringValue(object):
"""Tests for InputChecker._is_string_value()."""
def test_arguments(self):
"""Test that _check_type has expected arguments."""
h.test_function_arguments(
func=InputChecker._is_string_value,
expected_arguments=["self", "string", "string_name", "check_value"],
expected_default_values=None,
)
def test_exception(self):
"""Test that _is_string_value fails with the correct error."""
with pytest.raises(ValueError):
InputChecker(numerical_columns="None")
class TestIsSubset(object):
"""Tests for InputChecker._is_subset()."""
def test_arguments(self):
"""Test that _is_subset has expected arguments."""
h.test_function_arguments(
func=InputChecker._is_subset,
expected_arguments=["self", "obj_name", "columns", "dataframe"],
expected_default_values=None,
)
def test_exception(self):
"""Test that _is_subset fails with the correct error."""
x = InputChecker(numerical_columns=["u"])
with pytest.raises(ValueError):
x.fit(data_generators_p.create_df_2())
class TestIsEmpty(object):
"""Tests for InputChecker._is_empty()."""
def test_arguments(self):
"""Test that _is_empty has expected arguments."""
h.test_function_arguments(
func=InputChecker._is_empty,
expected_arguments=["self", "obj_name", "obj"],
expected_default_values=None,
)
def test_check_fails_empty_list(self):
"""Test that _is_empty fails with the correct error."""
with pytest.raises(ValueError):
InputChecker(columns=[])
def test_check_fails_empty_dict(self):
"""Test that _is_empty fails with the correct error."""
with pytest.raises(ValueError):
InputChecker(numerical_columns={})
class TestIsListedInColumns(object):
"""Tests for InputChecker._is_listed_in_columns()."""
def test_arguments(self):
"""Test that _is_empty has expected arguments."""
h.test_function_arguments(
func=InputChecker._is_listed_in_columns,
expected_arguments=["self"],
expected_default_values=None,
)
def test_check_fails_columns_not_listed(self):
"""Test that _is_listed_in_columns fails with the correct error."""
diff_cols = ["b", "c"]
with pytest.raises(
ValueError,
match=re.escape(
f"Column(s); {diff_cols} are not listed when initialising column attribute"
),
):
InputChecker(columns=["a"], numerical_columns=["a", "b", "c"])
def test_check_fails_columns_not_listed_with_infer(self):
"""Test that _is_listed_in_columns fails with the correct error when one of the columns lists are set to infer."""
diff_cols = ["b", "c"]
with pytest.raises(
ValueError,
match=re.escape(
f"Column(s); {diff_cols} are not listed when initialising column attribute"
),
):
InputChecker(
columns=["a"],
numerical_columns=["a", "b", "c"],
categorical_columns="infer",
)
def test_check_fails_columns_not_listed_with_none(self):
"""Test that _is_listed_in_columns fails with the correct error when one of the columns lists are set to None."""
diff_cols = ["b", "c"]
with pytest.raises(
ValueError,
match=re.escape(
f"Column(s); {diff_cols} are not listed when initialising column attribute"
),
):
InputChecker(
columns=["a"],
numerical_columns=["a", "b", "c"],
categorical_columns=None,
)
class TestDfIsEmpty(object):
"""Tests for InputChecker._df_is_empty()."""
def test_arguments(self):
"""Test that _df_is_empty has expected arguments."""
h.test_function_arguments(
func=InputChecker._df_is_empty,
expected_arguments=["self", "obj_name", "df"],
expected_default_values=None,
)
def test_check_fails(self):
"""Test that _df_is_empty fails with the correct error."""
x = InputChecker()
with pytest.raises(ValueError):
x.fit(pd.DataFrame())
| 31.573098 | 225 | 0.586253 | 13,272 | 110,790 | 4.623794 | 0.02833 | 0.043998 | 0.024932 | 0.034563 | 0.86131 | 0.806785 | 0.765297 | 0.721528 | 0.68118 | 0.62237 | 0 | 0.035627 | 0.303042 | 110,790 | 3,508 | 226 | 31.582098 | 0.759117 | 0.100677 | 0 | 0.640086 | 0 | 0.023707 | 0.252087 | 0.041326 | 0 | 0 | 0 | 0 | 0.095259 | 1 | 0.0625 | false | 0.007759 | 0.004741 | 0 | 0.077586 | 0.000862 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
fcc97e7ae3e98875b64a87df4b44d02a32eb0bd6 | 50 | py | Python | DataStructures/Heap/__init__.py | eeshannarula29/structlinks | 06c2ba2c9e0130deaa91ffb92758586361338a1c | [
"MIT"
] | 9 | 2021-04-09T21:20:46.000Z | 2022-03-25T12:14:43.000Z | DataStructures/Heap/__init__.py | eeshannarula29/NetLinks | 06c2ba2c9e0130deaa91ffb92758586361338a1c | [
"MIT"
] | 19 | 2021-03-22T07:52:39.000Z | 2021-04-07T20:04:05.000Z | DataStructures/Heap/__init__.py | eeshannarula29/structlinks | 06c2ba2c9e0130deaa91ffb92758586361338a1c | [
"MIT"
] | 7 | 2021-04-10T21:08:12.000Z | 2022-03-20T12:55:23.000Z | from structlinks.DataStructures.Heap.Heap import * | 50 | 50 | 0.86 | 6 | 50 | 7.166667 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.06 | 50 | 1 | 50 | 50 | 0.914894 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
fccb483844486db97a3d52fd0929d8a8e3063bb3 | 139 | py | Python | q1pulse/lang/base.py | sldesnoo-Delft/q1pulse | f5123b5c1e0dfbb59512d282ec7e3fb833e58b95 | [
"MIT"
] | 1 | 2021-11-12T09:40:14.000Z | 2021-11-12T09:40:14.000Z | q1pulse/lang/base.py | sldesnoo-Delft/q1pulse | f5123b5c1e0dfbb59512d282ec7e3fb833e58b95 | [
"MIT"
] | null | null | null | q1pulse/lang/base.py | sldesnoo-Delft/q1pulse | f5123b5c1e0dfbb59512d282ec7e3fb833e58b95 | [
"MIT"
] | null | null | null | from abc import ABC, abstractmethod
class Statement(ABC):
@abstractmethod
def write_instruction(self, generator):
pass
| 13.9 | 43 | 0.705036 | 15 | 139 | 6.466667 | 0.8 | 0.350515 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.230216 | 139 | 9 | 44 | 15.444444 | 0.906542 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | false | 0.2 | 0.2 | 0 | 0.6 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 5 |
fceb8811ba8755edab6566af7db755484a2edd5f | 303 | py | Python | TinyBox/Content/Source/resource.py | Ellpeck/TinyBox | ee235113a65a67dab945c335e4a3f07a720894fa | [
"MIT"
] | null | null | null | TinyBox/Content/Source/resource.py | Ellpeck/TinyBox | ee235113a65a67dab945c335e4a3f07a720894fa | [
"MIT"
] | null | null | null | TinyBox/Content/Source/resource.py | Ellpeck/TinyBox | ee235113a65a67dab945c335e4a3f07a720894fa | [
"MIT"
] | null | null | null | from TinyBox.Hooks import Resource
def font(name, scale):
return Resource.Font(name, scale)
def tex(name):
return Resource.Tex(name)
def string_width(fnt, string):
return Resource.StringWidth(fnt, string)
def string_height(fnt, string):
return Resource.StringHeight(fnt, string)
| 16.833333 | 45 | 0.732673 | 41 | 303 | 5.365854 | 0.414634 | 0.254545 | 0.118182 | 0.209091 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.165017 | 303 | 17 | 46 | 17.823529 | 0.869565 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.444444 | false | 0 | 0.111111 | 0.444444 | 1 | 0 | 0 | 0 | 0 | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 5 |
1e29ef2d0a47fbd9a5e7bc42c2873b94d28aac52 | 624 | py | Python | main.py | aronifanger/nltsa_app | b3f859a87491c7bcb75f58c49862d3ed752a9887 | [
"MIT"
] | null | null | null | main.py | aronifanger/nltsa_app | b3f859a87491c7bcb75f58c49862d3ed752a9887 | [
"MIT"
] | 1 | 2018-05-14T22:41:21.000Z | 2018-05-14T22:41:21.000Z | main.py | aronifanger/nltsa_app | b3f859a87491c7bcb75f58c49862d3ed752a9887 | [
"MIT"
] | 2 | 2018-05-12T06:10:57.000Z | 2019-04-08T22:35:45.000Z | from flask import Flask
from flask import render_template
from flask import request
app = Flask(__name__)
@app.route("/")
def index():
return render_template('index.html')
@app.route("/logistic")
def logistic():
return render_template('bif.html')
@app.route("/lyap")
def lyap():
return render_template('lyap.html')
@app.route("/baker")
def baker():
return render_template('baker.html');
@app.route("/esticadobra")
def esticadobra():
return render_template("esticadobra.html")
if __name__ == "__main__":
app.config['TEMPLATES_AUTO_RELOAD'] = True
app.run(debug=True, use_reloader=True)
| 18.352941 | 46 | 0.705128 | 81 | 624 | 5.17284 | 0.358025 | 0.200477 | 0.238663 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.141026 | 624 | 33 | 47 | 18.909091 | 0.781716 | 0 | 0 | 0 | 0 | 0 | 0.184295 | 0.033654 | 0 | 0 | 0 | 0 | 0 | 1 | 0.227273 | false | 0 | 0.136364 | 0.227273 | 0.590909 | 0 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 5 |
1eb0bd0cd6d55d2d811f0fbe7f303a8d605b2935 | 3,232 | py | Python | character/migrations/0010_auto_20210116_1516.py | cmerwin3/Adventure_Project | 1816978e952f1250049e8d1e7fcf172620903596 | [
"Apache-2.0"
] | null | null | null | character/migrations/0010_auto_20210116_1516.py | cmerwin3/Adventure_Project | 1816978e952f1250049e8d1e7fcf172620903596 | [
"Apache-2.0"
] | null | null | null | character/migrations/0010_auto_20210116_1516.py | cmerwin3/Adventure_Project | 1816978e952f1250049e8d1e7fcf172620903596 | [
"Apache-2.0"
] | null | null | null | # Generated by Django 3.1.1 on 2021-01-16 21:16
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('game_data', '0003_auto_20210103_1621'),
('ref_data', '0008_auto_20201023_2222'),
('character', '0009_character_game_id'),
]
operations = [
migrations.CreateModel(
name='NPC_Character',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('avatar_id', models.IntegerField()),
('name', models.CharField(max_length=30)),
('hit_dice_current', models.IntegerField()),
('hit_points_total', models.IntegerField()),
('hit_points_current', models.IntegerField()),
('armor_class', models.IntegerField()),
('strength', models.IntegerField()),
('dexterity', models.IntegerField()),
('constitution', models.IntegerField()),
('intelligence', models.IntegerField()),
('wisdom', models.IntegerField()),
('charisma', models.IntegerField()),
('items', models.ManyToManyField(to='ref_data.Item')),
('spells', models.ManyToManyField(to='ref_data.Spell')),
],
options={
'db_table': 'npc_character',
'ordering': ['id'],
'abstract': False,
},
),
migrations.CreateModel(
name='PC_Character',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('avatar_id', models.IntegerField()),
('name', models.CharField(max_length=30)),
('hit_dice_current', models.IntegerField()),
('hit_points_total', models.IntegerField()),
('hit_points_current', models.IntegerField()),
('armor_class', models.IntegerField()),
('strength', models.IntegerField()),
('dexterity', models.IntegerField()),
('constitution', models.IntegerField()),
('intelligence', models.IntegerField()),
('wisdom', models.IntegerField()),
('charisma', models.IntegerField()),
('class_level', models.ForeignKey(null=True, on_delete=django.db.models.deletion.SET_NULL, to='ref_data.classlevel')),
('game_id', models.ForeignKey(null=True, on_delete=django.db.models.deletion.SET_NULL, to='game_data.gamedata')),
('items', models.ManyToManyField(to='ref_data.Item')),
('race', models.ForeignKey(null=True, on_delete=django.db.models.deletion.SET_NULL, to='ref_data.race')),
('spells', models.ManyToManyField(to='ref_data.Spell')),
],
options={
'db_table': 'pc_character',
'ordering': ['id'],
'abstract': False,
},
),
migrations.DeleteModel(
name='Character',
),
]
| 44.273973 | 134 | 0.543007 | 283 | 3,232 | 6.003534 | 0.293286 | 0.233078 | 0.031783 | 0.051795 | 0.789288 | 0.789288 | 0.739847 | 0.693938 | 0.693938 | 0.693938 | 0 | 0.024499 | 0.305384 | 3,232 | 72 | 135 | 44.888889 | 0.732294 | 0.013923 | 0 | 0.681818 | 1 | 0 | 0.194349 | 0.02135 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.030303 | 0 | 0.075758 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
1ec255e3bacf5ccb6f5c14730a55f88c77165c5f | 786 | py | Python | neural_network_preprocessing/importance.py | hengwei-chan/nn_vis_network_visualization | 17403ab33cf215026d0b011d36ef612f1c08055f | [
"MIT"
] | 631 | 2021-02-08T01:11:40.000Z | 2022-03-27T05:33:01.000Z | neural_network_preprocessing/importance.py | hulaba/nn_vis | 17403ab33cf215026d0b011d36ef612f1c08055f | [
"MIT"
] | 9 | 2021-03-08T02:41:59.000Z | 2022-03-12T00:54:30.000Z | neural_network_preprocessing/importance.py | hulaba/nn_vis | 17403ab33cf215026d0b011d36ef612f1c08055f | [
"MIT"
] | 124 | 2021-02-08T05:11:51.000Z | 2022-03-14T13:49:19.000Z | from enum import IntFlag, auto, Enum
class ImportanceType(IntFlag):
CENTERING = auto()
GAMMA = auto()
L1 = auto()
L2 = auto()
def get_importance_type_name(importance_type: ImportanceType) -> str:
name: str = ""
name = name + ("beta_" if importance_type & ImportanceType.CENTERING else "nobeta_")
name = name + ("gammaone" if importance_type & ImportanceType.GAMMA else "gammazero")
if importance_type & ImportanceType.L1:
name = name + '_' + "l1"
if importance_type & ImportanceType.L1 and importance_type & ImportanceType.L2:
name = name + "l2"
elif importance_type & ImportanceType.L2:
name = name + '_' + "l2"
return name
class ImportanceCalculation(Enum):
BNN_EDGE = 1
BNN_ONLY = 2
EDGE_ONLY = 3
| 28.071429 | 89 | 0.660305 | 91 | 786 | 5.516484 | 0.362637 | 0.223108 | 0.390438 | 0.239044 | 0.286853 | 0.159363 | 0.159363 | 0 | 0 | 0 | 0 | 0.019967 | 0.235369 | 786 | 27 | 90 | 29.111111 | 0.815308 | 0 | 0 | 0 | 0 | 0 | 0.047074 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.047619 | false | 0 | 0.428571 | 0 | 0.952381 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
1ed24c2177d7c1ecbbada2a88a7ed0a9b5f88e89 | 239 | py | Python | UrlShortener/UrlShortener/schema.py | SandyUndefined/Django-URL-Shortener | fa6c9d7575b50df887994dd9dad165e89a139658 | [
"MIT"
] | null | null | null | UrlShortener/UrlShortener/schema.py | SandyUndefined/Django-URL-Shortener | fa6c9d7575b50df887994dd9dad165e89a139658 | [
"MIT"
] | null | null | null | UrlShortener/UrlShortener/schema.py | SandyUndefined/Django-URL-Shortener | fa6c9d7575b50df887994dd9dad165e89a139658 | [
"MIT"
] | null | null | null | import graphene
import Shortener.schema
class Query(Shortener.schema.Query,graphene.ObjectType):
pass
class Mutation(Shortener.schema.Mutation, graphene.ObjectType):
pass
schema = graphene.Schema(query=Query,mutation=Mutation) | 19.916667 | 63 | 0.799163 | 28 | 239 | 6.821429 | 0.321429 | 0.235602 | 0.230366 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.108787 | 239 | 12 | 64 | 19.916667 | 0.896714 | 0 | 0 | 0.285714 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.285714 | 0.285714 | 0 | 0.571429 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 5 |
94d2746e878656c5e403e0b18585ea6d0495d5c7 | 245 | py | Python | test/test_tools.py | glongh/frozenpipe | 07a23f25abf1cf54b43a54ec740fbcbb300ea418 | [
"MIT"
] | 1 | 2021-05-06T01:25:38.000Z | 2021-05-06T01:25:38.000Z | test/test_tools.py | glongh/frozenpipe | 07a23f25abf1cf54b43a54ec740fbcbb300ea418 | [
"MIT"
] | null | null | null | test/test_tools.py | glongh/frozenpipe | 07a23f25abf1cf54b43a54ec740fbcbb300ea418 | [
"MIT"
] | null | null | null | class FakeTimer():
"""
A fake timer to test against time
"""
def __init__(self):
self._timestamp = 0.0
def tick(self, seconds):
self._timestamp += seconds
def time(self):
return self._timestamp
| 17.5 | 37 | 0.579592 | 29 | 245 | 4.655172 | 0.586207 | 0.288889 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.011905 | 0.314286 | 245 | 13 | 38 | 18.846154 | 0.791667 | 0.134694 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.428571 | false | 0 | 0 | 0.142857 | 0.714286 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 5 |
94f1ee76d43295932e78dceefcc2c72e6c9084f1 | 290 | py | Python | dbaas/dbaas/views.py | jaeko44/python_dbaas | 4fafa4ad70200fec1436c326c751761922ec9fa8 | [
"BSD-3-Clause"
] | null | null | null | dbaas/dbaas/views.py | jaeko44/python_dbaas | 4fafa4ad70200fec1436c326c751761922ec9fa8 | [
"BSD-3-Clause"
] | null | null | null | dbaas/dbaas/views.py | jaeko44/python_dbaas | 4fafa4ad70200fec1436c326c751761922ec9fa8 | [
"BSD-3-Clause"
] | 1 | 2017-07-02T08:46:17.000Z | 2017-07-02T08:46:17.000Z | from system.models import Configuration
from django.template import Context
def external_links(request):
iaas_status = Configuration.get_by_name('iaas_status')
iaas_quota = Configuration.get_by_name('iaas_quota')
return {'iaas_status': iaas_status, 'iaas_quota': iaas_quota }
| 32.222222 | 66 | 0.786207 | 39 | 290 | 5.512821 | 0.487179 | 0.186047 | 0.195349 | 0.204651 | 0.24186 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.124138 | 290 | 8 | 67 | 36.25 | 0.846457 | 0 | 0 | 0 | 0 | 0 | 0.144828 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | false | 0 | 0.333333 | 0 | 0.666667 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
a20a4739fe06b511b499c335e3c01d000eafc2cd | 58 | py | Python | giant/plugins/servers/web_api_2/web_api_2/__init__.py | lixar/giant | fba966e4389b80b38bee1067ad9173adf4eaa5b5 | [
"MIT"
] | null | null | null | giant/plugins/servers/web_api_2/web_api_2/__init__.py | lixar/giant | fba966e4389b80b38bee1067ad9173adf4eaa5b5 | [
"MIT"
] | 2 | 2016-05-26T14:40:07.000Z | 2017-04-13T21:07:16.000Z | giant/plugins/servers/web_api_2/web_api_2/__init__.py | lixar/giant | fba966e4389b80b38bee1067ad9173adf4eaa5b5 | [
"MIT"
] | null | null | null | #!/usr/bin/env python
from .web_api_2 import SwaggerGiant | 19.333333 | 35 | 0.793103 | 10 | 58 | 4.4 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.019231 | 0.103448 | 58 | 3 | 35 | 19.333333 | 0.826923 | 0.344828 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
bf84ab0bb4280c7dcac056a8de94472de065e94e | 17,457 | py | Python | yandex/cloud/iot/devices/v1/registry_pb2.py | korsar182/python-sdk | 873bf2a9b136a8f2faae72e86fae1f5b5c3d896a | [
"MIT"
] | 36 | 2018-12-23T13:51:50.000Z | 2022-03-25T07:48:24.000Z | yandex/cloud/iot/devices/v1/registry_pb2.py | korsar182/python-sdk | 873bf2a9b136a8f2faae72e86fae1f5b5c3d896a | [
"MIT"
] | 15 | 2019-02-28T04:55:09.000Z | 2022-03-06T23:17:24.000Z | yandex/cloud/iot/devices/v1/registry_pb2.py | korsar182/python-sdk | 873bf2a9b136a8f2faae72e86fae1f5b5c3d896a | [
"MIT"
] | 18 | 2019-02-23T07:10:57.000Z | 2022-03-28T14:41:08.000Z | # -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: yandex/cloud/iot/devices/v1/registry.proto
"""Generated protocol buffer code."""
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
from google.protobuf import timestamp_pb2 as google_dot_protobuf_dot_timestamp__pb2
DESCRIPTOR = _descriptor.FileDescriptor(
name='yandex/cloud/iot/devices/v1/registry.proto',
package='yandex.cloud.iot.devices.v1',
syntax='proto3',
serialized_options=b'\n\037yandex.cloud.api.iot.devices.v1ZGgithub.com/yandex-cloud/go-genproto/yandex/cloud/iot/devices/v1;devices',
create_key=_descriptor._internal_create_key,
serialized_pb=b'\n*yandex/cloud/iot/devices/v1/registry.proto\x12\x1byandex.cloud.iot.devices.v1\x1a\x1fgoogle/protobuf/timestamp.proto\"\x8c\x03\n\x08Registry\x12\n\n\x02id\x18\x01 \x01(\t\x12\x11\n\tfolder_id\x18\x02 \x01(\t\x12.\n\ncreated_at\x18\x03 \x01(\x0b\x32\x1a.google.protobuf.Timestamp\x12\x0c\n\x04name\x18\x04 \x01(\t\x12\x13\n\x0b\x64\x65scription\x18\x05 \x01(\t\x12\x41\n\x06labels\x18\x06 \x03(\x0b\x32\x31.yandex.cloud.iot.devices.v1.Registry.LabelsEntry\x12<\n\x06status\x18\x07 \x01(\x0e\x32,.yandex.cloud.iot.devices.v1.Registry.Status\x12\x14\n\x0clog_group_id\x18\x08 \x01(\t\x1a-\n\x0bLabelsEntry\x12\x0b\n\x03key\x18\x01 \x01(\t\x12\r\n\x05value\x18\x02 \x01(\t:\x02\x38\x01\"H\n\x06Status\x12\x16\n\x12STATUS_UNSPECIFIED\x10\x00\x12\x0c\n\x08\x43REATING\x10\x01\x12\n\n\x06\x41\x43TIVE\x10\x02\x12\x0c\n\x08\x44\x45LETING\x10\x03\"\x89\x01\n\x13RegistryCertificate\x12\x13\n\x0bregistry_id\x18\x01 \x01(\t\x12\x13\n\x0b\x66ingerprint\x18\x02 \x01(\t\x12\x18\n\x10\x63\x65rtificate_data\x18\x03 \x01(\t\x12.\n\ncreated_at\x18\x04 \x01(\x0b\x32\x1a.google.protobuf.Timestamp\"E\n\x0b\x44\x65viceAlias\x12\x11\n\tdevice_id\x18\x01 \x01(\t\x12\x14\n\x0ctopic_prefix\x18\x02 \x01(\t\x12\r\n\x05\x61lias\x18\x03 \x01(\t\"c\n\x10RegistryPassword\x12\x13\n\x0bregistry_id\x18\x01 \x01(\t\x12\n\n\x02id\x18\x02 \x01(\t\x12.\n\ncreated_at\x18\x03 \x01(\x0b\x32\x1a.google.protobuf.TimestampBj\n\x1fyandex.cloud.api.iot.devices.v1ZGgithub.com/yandex-cloud/go-genproto/yandex/cloud/iot/devices/v1;devicesb\x06proto3'
,
dependencies=[google_dot_protobuf_dot_timestamp__pb2.DESCRIPTOR,])
_REGISTRY_STATUS = _descriptor.EnumDescriptor(
name='Status',
full_name='yandex.cloud.iot.devices.v1.Registry.Status',
filename=None,
file=DESCRIPTOR,
create_key=_descriptor._internal_create_key,
values=[
_descriptor.EnumValueDescriptor(
name='STATUS_UNSPECIFIED', index=0, number=0,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
_descriptor.EnumValueDescriptor(
name='CREATING', index=1, number=1,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
_descriptor.EnumValueDescriptor(
name='ACTIVE', index=2, number=2,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
_descriptor.EnumValueDescriptor(
name='DELETING', index=3, number=3,
serialized_options=None,
type=None,
create_key=_descriptor._internal_create_key),
],
containing_type=None,
serialized_options=None,
serialized_start=433,
serialized_end=505,
)
_sym_db.RegisterEnumDescriptor(_REGISTRY_STATUS)
_REGISTRY_LABELSENTRY = _descriptor.Descriptor(
name='LabelsEntry',
full_name='yandex.cloud.iot.devices.v1.Registry.LabelsEntry',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='key', full_name='yandex.cloud.iot.devices.v1.Registry.LabelsEntry.key', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='value', full_name='yandex.cloud.iot.devices.v1.Registry.LabelsEntry.value', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=b'8\001',
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=386,
serialized_end=431,
)
_REGISTRY = _descriptor.Descriptor(
name='Registry',
full_name='yandex.cloud.iot.devices.v1.Registry',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='id', full_name='yandex.cloud.iot.devices.v1.Registry.id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='folder_id', full_name='yandex.cloud.iot.devices.v1.Registry.folder_id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='created_at', full_name='yandex.cloud.iot.devices.v1.Registry.created_at', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='name', full_name='yandex.cloud.iot.devices.v1.Registry.name', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='description', full_name='yandex.cloud.iot.devices.v1.Registry.description', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='labels', full_name='yandex.cloud.iot.devices.v1.Registry.labels', index=5,
number=6, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='status', full_name='yandex.cloud.iot.devices.v1.Registry.status', index=6,
number=7, type=14, cpp_type=8, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='log_group_id', full_name='yandex.cloud.iot.devices.v1.Registry.log_group_id', index=7,
number=8, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[_REGISTRY_LABELSENTRY, ],
enum_types=[
_REGISTRY_STATUS,
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=109,
serialized_end=505,
)
_REGISTRYCERTIFICATE = _descriptor.Descriptor(
name='RegistryCertificate',
full_name='yandex.cloud.iot.devices.v1.RegistryCertificate',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='registry_id', full_name='yandex.cloud.iot.devices.v1.RegistryCertificate.registry_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='fingerprint', full_name='yandex.cloud.iot.devices.v1.RegistryCertificate.fingerprint', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='certificate_data', full_name='yandex.cloud.iot.devices.v1.RegistryCertificate.certificate_data', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='created_at', full_name='yandex.cloud.iot.devices.v1.RegistryCertificate.created_at', index=3,
number=4, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=508,
serialized_end=645,
)
_DEVICEALIAS = _descriptor.Descriptor(
name='DeviceAlias',
full_name='yandex.cloud.iot.devices.v1.DeviceAlias',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='device_id', full_name='yandex.cloud.iot.devices.v1.DeviceAlias.device_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='topic_prefix', full_name='yandex.cloud.iot.devices.v1.DeviceAlias.topic_prefix', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='alias', full_name='yandex.cloud.iot.devices.v1.DeviceAlias.alias', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=647,
serialized_end=716,
)
_REGISTRYPASSWORD = _descriptor.Descriptor(
name='RegistryPassword',
full_name='yandex.cloud.iot.devices.v1.RegistryPassword',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='registry_id', full_name='yandex.cloud.iot.devices.v1.RegistryPassword.registry_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='id', full_name='yandex.cloud.iot.devices.v1.RegistryPassword.id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='created_at', full_name='yandex.cloud.iot.devices.v1.RegistryPassword.created_at', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=718,
serialized_end=817,
)
_REGISTRY_LABELSENTRY.containing_type = _REGISTRY
_REGISTRY.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_REGISTRY.fields_by_name['labels'].message_type = _REGISTRY_LABELSENTRY
_REGISTRY.fields_by_name['status'].enum_type = _REGISTRY_STATUS
_REGISTRY_STATUS.containing_type = _REGISTRY
_REGISTRYCERTIFICATE.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
_REGISTRYPASSWORD.fields_by_name['created_at'].message_type = google_dot_protobuf_dot_timestamp__pb2._TIMESTAMP
DESCRIPTOR.message_types_by_name['Registry'] = _REGISTRY
DESCRIPTOR.message_types_by_name['RegistryCertificate'] = _REGISTRYCERTIFICATE
DESCRIPTOR.message_types_by_name['DeviceAlias'] = _DEVICEALIAS
DESCRIPTOR.message_types_by_name['RegistryPassword'] = _REGISTRYPASSWORD
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
Registry = _reflection.GeneratedProtocolMessageType('Registry', (_message.Message,), {
'LabelsEntry' : _reflection.GeneratedProtocolMessageType('LabelsEntry', (_message.Message,), {
'DESCRIPTOR' : _REGISTRY_LABELSENTRY,
'__module__' : 'yandex.cloud.iot.devices.v1.registry_pb2'
# @@protoc_insertion_point(class_scope:yandex.cloud.iot.devices.v1.Registry.LabelsEntry)
})
,
'DESCRIPTOR' : _REGISTRY,
'__module__' : 'yandex.cloud.iot.devices.v1.registry_pb2'
# @@protoc_insertion_point(class_scope:yandex.cloud.iot.devices.v1.Registry)
})
_sym_db.RegisterMessage(Registry)
_sym_db.RegisterMessage(Registry.LabelsEntry)
RegistryCertificate = _reflection.GeneratedProtocolMessageType('RegistryCertificate', (_message.Message,), {
'DESCRIPTOR' : _REGISTRYCERTIFICATE,
'__module__' : 'yandex.cloud.iot.devices.v1.registry_pb2'
# @@protoc_insertion_point(class_scope:yandex.cloud.iot.devices.v1.RegistryCertificate)
})
_sym_db.RegisterMessage(RegistryCertificate)
DeviceAlias = _reflection.GeneratedProtocolMessageType('DeviceAlias', (_message.Message,), {
'DESCRIPTOR' : _DEVICEALIAS,
'__module__' : 'yandex.cloud.iot.devices.v1.registry_pb2'
# @@protoc_insertion_point(class_scope:yandex.cloud.iot.devices.v1.DeviceAlias)
})
_sym_db.RegisterMessage(DeviceAlias)
RegistryPassword = _reflection.GeneratedProtocolMessageType('RegistryPassword', (_message.Message,), {
'DESCRIPTOR' : _REGISTRYPASSWORD,
'__module__' : 'yandex.cloud.iot.devices.v1.registry_pb2'
# @@protoc_insertion_point(class_scope:yandex.cloud.iot.devices.v1.RegistryPassword)
})
_sym_db.RegisterMessage(RegistryPassword)
DESCRIPTOR._options = None
_REGISTRY_LABELSENTRY._options = None
# @@protoc_insertion_point(module_scope)
| 45.698953 | 1,533 | 0.757977 | 2,287 | 17,457 | 5.486227 | 0.092261 | 0.044632 | 0.074201 | 0.060971 | 0.751335 | 0.728222 | 0.714673 | 0.686698 | 0.637045 | 0.6117 | 0 | 0.036357 | 0.11451 | 17,457 | 381 | 1,534 | 45.818898 | 0.775327 | 0.036891 | 0 | 0.669565 | 1 | 0.005797 | 0.227408 | 0.186689 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.034783 | 0.014493 | 0 | 0.014493 | 0.005797 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
bf883337eba98583299eb78dc07476e50c4613d2 | 101 | py | Python | test/integration/custom_functions.dmx.py | DoctorBazooka/Datamatic | 55e7b1db7722c3c38dc74bce85cafec935abfe4c | [
"MIT"
] | 3 | 2021-06-12T21:06:38.000Z | 2022-01-16T23:30:13.000Z | test/integration/custom_functions.dmx.py | DoctorBazooka/Datamatic | 55e7b1db7722c3c38dc74bce85cafec935abfe4c | [
"MIT"
] | 8 | 2021-05-31T21:24:06.000Z | 2021-06-12T11:17:34.000Z | test/integration/custom_functions.dmx.py | MagicLemma/datamatic | 55e7b1db7722c3c38dc74bce85cafec935abfe4c | [
"MIT"
] | null | null | null | def main(register):
@register.compmethod
def test_function(ctx):
return "foobar" | 20.2 | 27 | 0.633663 | 11 | 101 | 5.727273 | 0.818182 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.267327 | 101 | 5 | 28 | 20.2 | 0.851351 | 0 | 0 | 0 | 0 | 0 | 0.058824 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.5 | false | 0 | 0 | 0.25 | 0.75 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 5 |
bfb967882992777b1baa3386d30c80aaf8c5b8e1 | 101 | py | Python | pyaz/network/nat/__init__.py | py-az-cli/py-az-cli | 9a7dc44e360c096a5a2f15595353e9dad88a9792 | [
"MIT"
] | null | null | null | pyaz/network/nat/__init__.py | py-az-cli/py-az-cli | 9a7dc44e360c096a5a2f15595353e9dad88a9792 | [
"MIT"
] | null | null | null | pyaz/network/nat/__init__.py | py-az-cli/py-az-cli | 9a7dc44e360c096a5a2f15595353e9dad88a9792 | [
"MIT"
] | 1 | 2022-02-03T09:12:01.000Z | 2022-02-03T09:12:01.000Z | '''
Commands to manage NAT resources.
'''
from ... pyaz_utils import _call_az
from . import gateway
| 14.428571 | 35 | 0.722772 | 14 | 101 | 5 | 0.857143 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.168317 | 101 | 6 | 36 | 16.833333 | 0.833333 | 0.326733 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
bfce5aa1176b8932a0c5f194457281a12bfb876a | 1,142 | py | Python | thirdparty/magma/mantle/lattice/mantle40/__init__.py | bjmnbraun/icestick_fastio | 9fc61753e583a5a725688cb324bd1af08c2ddac4 | [
"MIT"
] | null | null | null | thirdparty/magma/mantle/lattice/mantle40/__init__.py | bjmnbraun/icestick_fastio | 9fc61753e583a5a725688cb324bd1af08c2ddac4 | [
"MIT"
] | null | null | null | thirdparty/magma/mantle/lattice/mantle40/__init__.py | bjmnbraun/icestick_fastio | 9fc61753e583a5a725688cb324bd1af08c2ddac4 | [
"MIT"
] | null | null | null | from parts.lattice.ice40.primitives import FAMILY, \
A0, A1, A2, A3, \
I0, I1, I2, I3, \
ALL, ANY, PARITY, ZERO, ONE, \
LUTS_PER_LOGICBLOCK, BITS_PER_LUT, LOG_BITS_PER_LUT
from mantle.lattice.mantle40.IO import *
from mantle.lattice.mantle40.LUT import *
from mantle.lattice.mantle40.ROM import *
from mantle.lattice.mantle40.MUX import *
from mantle.lattice.mantle40.FF import *
from mantle.lattice.mantle40.adder import *
from mantle.lattice.mantle40.cascade import *
from mantle.lattice.mantle40.flatcascade import *
from mantle.lattice.mantle40.logic import *
from mantle.lattice.mantle40.decode import *
from mantle.lattice.mantle40.compare import *
from mantle.lattice.mantle40.encoder import *
from mantle.lattice.mantle40.decoder import *
from mantle.lattice.mantle40.arbiter import *
from mantle.lattice.mantle40.adder import FullAdder, HalfAdder
from mantle.lattice.mantle40.arith import *
from mantle.lattice.mantle40.register import *
from mantle.lattice.mantle40.shift import *
from mantle.lattice.mantle40.ring import *
from mantle.lattice.mantle40.counter import *
print('import lattice mantle40')
| 28.55 | 62 | 0.78634 | 156 | 1,142 | 5.711538 | 0.314103 | 0.353535 | 0.381594 | 0.561167 | 0.64422 | 0.094276 | 0.094276 | 0 | 0 | 0 | 0 | 0.051741 | 0.119965 | 1,142 | 39 | 63 | 29.282051 | 0.834826 | 0 | 0 | 0 | 0 | 0 | 0.02014 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.846154 | 0 | 0.846154 | 0.038462 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
44ba2afdf4f2a36e4481d2647653265c4e7189d2 | 579 | py | Python | koreanbots/abc.py | InsanePhin/py-sdk | 51085c59ccb9e61ac23de2c5eeec898fec3a0275 | [
"MIT"
] | 24 | 2020-05-09T02:58:34.000Z | 2022-03-30T13:44:37.000Z | koreanbots/abc.py | InsanePhin/py-sdk | 51085c59ccb9e61ac23de2c5eeec898fec3a0275 | [
"MIT"
] | 28 | 2020-05-11T23:35:27.000Z | 2021-10-09T04:38:19.000Z | koreanbots/abc.py | InsanePhin/py-sdk | 51085c59ccb9e61ac23de2c5eeec898fec3a0275 | [
"MIT"
] | 22 | 2020-05-11T13:38:37.000Z | 2022-03-30T10:29:42.000Z | from abc import ABCMeta, abstractmethod
from typing import Any, Dict
class KoreanbotsABC(metaclass=ABCMeta):
@abstractmethod
def __init__(self, **response_data: Any) -> None:
self.response_data = response_data
@property
@abstractmethod
def code(self) -> int:
return self.response_data.get("code", 0)
@property
@abstractmethod
def version(self) -> int:
return self.response_data.get("version", 0)
@property
@abstractmethod
def data(self) -> Dict[str, Any]:
return self.response_data.get("data", {})
| 24.125 | 53 | 0.661485 | 67 | 579 | 5.567164 | 0.373134 | 0.193029 | 0.214477 | 0.176944 | 0.238606 | 0.171582 | 0.171582 | 0 | 0 | 0 | 0 | 0.004464 | 0.226252 | 579 | 23 | 54 | 25.173913 | 0.828125 | 0 | 0 | 0.388889 | 0 | 0 | 0.025907 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.222222 | false | 0 | 0.111111 | 0.166667 | 0.555556 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 5 |
44de8e7ee23820594bf44f7f737ea687468515a6 | 120 | py | Python | apps/python/app_with_tox/app.py | farooq-teqniqly/docker-ioml | f42ab7da520d6e549a22e15ba871a9972030062b | [
"MIT"
] | null | null | null | apps/python/app_with_tox/app.py | farooq-teqniqly/docker-ioml | f42ab7da520d6e549a22e15ba871a9972030062b | [
"MIT"
] | null | null | null | apps/python/app_with_tox/app.py | farooq-teqniqly/docker-ioml | f42ab7da520d6e549a22e15ba871a9972030062b | [
"MIT"
] | null | null | null | def say_hello(name: str) -> str:
return f"Hello {name}!"
if __name__ == "__main__":
print(say_hello("Bubba"))
| 17.142857 | 32 | 0.625 | 17 | 120 | 3.823529 | 0.647059 | 0.246154 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.191667 | 120 | 6 | 33 | 20 | 0.670103 | 0 | 0 | 0 | 0 | 0 | 0.216667 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0 | 0.25 | 0.5 | 0.25 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 5 |
44f127f7d9f1bd4178e1738bac07c8bb0dba20a2 | 93 | py | Python | resources/__init__.py | ranusingh1993/flask_restfull | c318f7061f82e2687ec3b60ef7fa14d3a764d6c7 | [
"MIT"
] | null | null | null | resources/__init__.py | ranusingh1993/flask_restfull | c318f7061f82e2687ec3b60ef7fa14d3a764d6c7 | [
"MIT"
] | null | null | null | resources/__init__.py | ranusingh1993/flask_restfull | c318f7061f82e2687ec3b60ef7fa14d3a764d6c7 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
"""
Created on Tue Jan 25 13:58:41 2022
@author: ranusingh1993
"""
| 11.625 | 35 | 0.602151 | 14 | 93 | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.226667 | 0.193548 | 93 | 7 | 36 | 13.285714 | 0.52 | 0.88172 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
7813f5bc41db5218c5544f519ec49db8ce977ac8 | 105 | py | Python | aiodebug/logging_compat.py | qntln/aiodebug | beb0b3f5e94a24c3947da89d3f96ffdbf0da8f96 | [
"Apache-2.0"
] | 51 | 2016-10-29T08:53:58.000Z | 2021-12-22T15:27:46.000Z | aiodebug/logging_compat.py | qntln/aiodebug | beb0b3f5e94a24c3947da89d3f96ffdbf0da8f96 | [
"Apache-2.0"
] | 2 | 2018-11-14T09:03:13.000Z | 2022-01-04T17:19:53.000Z | aiodebug/logging_compat.py | qntln/aiodebug | beb0b3f5e94a24c3947da89d3f96ffdbf0da8f96 | [
"Apache-2.0"
] | 3 | 2016-12-09T11:14:26.000Z | 2018-10-25T09:51:10.000Z | try:
from logwood import get_logger
except ImportError:
import logging
get_logger = logging.getLogger
| 17.5 | 31 | 0.819048 | 14 | 105 | 6 | 0.714286 | 0.214286 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.142857 | 105 | 5 | 32 | 21 | 0.933333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.6 | 0 | 0.6 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
783a3e38c2e611e2d3d17836af5aeeab47b425c0 | 4,622 | py | Python | tests/internal/superagg_tests.py | cyrusradfar/vaex | 6a37bd4509c9a0823b4f01075049f3331fabea77 | [
"MIT"
] | 2 | 2020-12-01T09:41:54.000Z | 2020-12-13T14:10:19.000Z | tests/internal/superagg_tests.py | cyrusradfar/vaex | 6a37bd4509c9a0823b4f01075049f3331fabea77 | [
"MIT"
] | null | null | null | tests/internal/superagg_tests.py | cyrusradfar/vaex | 6a37bd4509c9a0823b4f01075049f3331fabea77 | [
"MIT"
] | null | null | null | import vaex.superagg
import numpy as np
import sys
def test_ref_count():
x = np.array([-1, -2, 0.5, 1.5, 4.5, 5], dtype='f8')
bins = 5
binner = vaex.superagg.BinnerScalar_float64('x', 0, 5, bins)
start_count_binner = sys.getrefcount(binner)
grid = vaex.superagg.Grid([binner])
assert sys.getrefcount(binner) == start_count_binner + 1
start_count_grid = sys.getrefcount(grid)
agg = vaex.superagg.AggCount_float64(grid)
assert sys.getrefcount(binner) == start_count_grid + 1
del agg
assert sys.getrefcount(grid) == start_count_grid
assert sys.getrefcount(binner) == start_count_binner + 1
del grid
assert sys.getrefcount(binner) == start_count_binner
def test_count_1d_scalar():
x = np.array([-1, -2, 0.5, 1.5, 4.5, 5], dtype='f8')
bins = 5
binner = vaex.superagg.BinnerScalar_float64('x', 0, 5, bins)
binner.set_data(x)
grid = vaex.superagg.Grid([binner])
agg = vaex.superagg.AggCount_float64(grid)
agg_data = np.asarray(agg)
grid.bin([agg])
assert agg_data.tolist() == [0, 2, 1, 1, 0, 0, 1, 1]
def test_count_1d_strings():
x = np.array([-1, -2, 0.5, 1.5, 4.5, 5], dtype='f8')
y = x.astype(str).astype('O')
y[2] = None
y = vaex.column._to_string_sequence(y)
bins = 5
binner = vaex.superagg.BinnerScalar_float64('x', 0, 5, bins)
binner.set_data(x)
grid = vaex.superagg.Grid([binner])
agg = vaex.superagg.AggCount_string(grid)
agg.set_data(y, 0)
agg_data = np.asarray(agg)
grid.bin([agg])
assert agg_data.tolist() == [0, 2, 0, 1, 0, 0, 1, 1]
def test_count_1d_scalar_int64():
x = np.array([-1, -2, 0.5, 1.5, 4.5, 5], dtype='i8')
bins = 5
binner = vaex.superagg.BinnerScalar_int64('x', 0, 5, bins)
binner.set_data(x)
grid = vaex.superagg.Grid([binner])
agg = vaex.superagg.AggCount_float64(grid)
agg_data = np.asarray(agg)
grid.bin([agg])
assert agg_data.tolist() == [0, 2, 1, 1, 0, 0, 1, 1]
def test_count_1d_ordinal():
x = np.array([-1, -2, 0, 1, 4, 6, 10], dtype='i8')
ordinal_count = 5
binner = vaex.superagg.BinnerOrdinal_int64('x', ordinal_count, 0)
binner.set_data(x)
grid = vaex.superagg.Grid([binner])
agg = vaex.superagg.AggCount_int64(grid)
agg_data = np.asarray(agg)
grid.bin([agg])
assert agg_data.tolist() == [0, 2, 1, 1, 0, 0, 1, 2]
def test_count_2d_ordinal():
x = np.array([-1, -2, 0, 1, 4, 6, 10], dtype='i8')
ordinal_count = 5
binner1 = vaex.superagg.BinnerOrdinal_int64('x', ordinal_count, 0)
binner2 = vaex.superagg.BinnerOrdinal_int64('x', ordinal_count, 0)
binner1.set_data(x)
binner2.set_data(x)
grid = vaex.superagg.Grid([binner1, binner2])
agg = vaex.superagg.AggCount_int64(grid)
agg_data = np.asarray(agg)
grid.bin([agg])
diagonal = [agg_data[k,k] for k in range(agg_data.shape[0])]
assert diagonal == [0, 2, 1, 1, 0, 0, 1, 2]
def test_min_max_1d_ordinal():
x = np.array([-1, -1, 0, 0, 4, 6, 10], dtype='i8')
y = np.array([-1, 2, 4, 1, 9, 6, 10], dtype='i8')
ordinal_count = 5
binner = vaex.superagg.BinnerOrdinal_int64('x', ordinal_count, 0)
binner.set_data(x)
grid = vaex.superagg.Grid([binner])
agg = vaex.superagg.AggMax_int64(grid)
agg_data = np.asarray(agg)
agg_data -= 100
agg.set_data(y, 0)
grid.bin([agg])
assert agg_data.tolist() == [-100, 2, 4, -100, -100, -100, 9, 10]
grid = vaex.superagg.Grid([binner])
agg = vaex.superagg.AggMin_int64(grid)
agg_data = np.asarray(agg)
agg_data += 100
agg.set_data(y, 0)
grid.bin([agg])
assert agg_data.tolist() == [100, -1, 1, 100, 100, 100, 9, 6]
def test_sum_1d_ordinal():
x = np.array([-1, -1, 0, 0, 4, 6, 10], dtype='i8')
y = np.array([-1, 2, 4, 1, 9, 6, 10], dtype='i8')
ordinal_count = 5
binner = vaex.superagg.BinnerOrdinal_int64('x', ordinal_count, 0)
binner.set_data(x)
grid = vaex.superagg.Grid([binner])
agg = vaex.superagg.AggSum_int64(grid)
agg_data = np.asarray(agg)
agg.set_data(y, 0)
grid.bin([agg])
assert agg_data.tolist() == [0, 1, 5, 0, 0, 0, 9, 16]
def test_count_1d_object():
x = np.array([-1, -1, 0, 0, 2, 6, 10], dtype='i8')
y = np.array([ 1, 1, 1, None, 1, '1', np.nan], dtype='O')
ordinal_count = 5
binner = vaex.superagg.BinnerOrdinal_int64('x', ordinal_count, 0)
binner.set_data(x)
grid = vaex.superagg.Grid([binner])
agg = vaex.superagg.AggCount_object(grid)
agg_data = np.asarray(agg)
agg.set_data(y, 0)
grid.bin([agg])
assert agg_data.tolist() == [0, 2, 1, 0, 1, 0, 0, 1] | 35.015152 | 70 | 0.622891 | 760 | 4,622 | 3.642105 | 0.097368 | 0.134393 | 0.034682 | 0.072254 | 0.826228 | 0.800939 | 0.777457 | 0.748555 | 0.644147 | 0.637283 | 0 | 0.078575 | 0.204241 | 4,622 | 132 | 71 | 35.015152 | 0.674008 | 0 | 0 | 0.613445 | 0 | 0 | 0.007571 | 0 | 0 | 0 | 0 | 0 | 0.117647 | 1 | 0.07563 | false | 0 | 0.02521 | 0 | 0.10084 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
7845e0c99438113c6b72e183e82982848c5f4c77 | 111 | py | Python | room_order/__init__.py | wusri66666/room_order | bc350e6e4169801f29d6826c271b17f696c9a260 | [
"Apache-2.0"
] | null | null | null | room_order/__init__.py | wusri66666/room_order | bc350e6e4169801f29d6826c271b17f696c9a260 | [
"Apache-2.0"
] | null | null | null | room_order/__init__.py | wusri66666/room_order | bc350e6e4169801f29d6826c271b17f696c9a260 | [
"Apache-2.0"
] | null | null | null | from __future__ import absolute_import
#导入工程目录下celery中的app并起别名
from room_order.celery import app as celery_app | 37 | 47 | 0.882883 | 15 | 111 | 6.066667 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.099099 | 111 | 3 | 47 | 37 | 0.91 | 0.198198 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
786192914413175f4b0b52038161b8d68ce96021 | 175 | py | Python | agenda/events.py | hyroai/agenda | 1321e49ec433d62901e1e00dfd546c00d43db544 | [
"MIT"
] | 5 | 2022-02-02T14:00:47.000Z | 2022-03-14T18:51:07.000Z | agenda/events.py | hyroai/agenda | 1321e49ec433d62901e1e00dfd546c00d43db544 | [
"MIT"
] | 21 | 2022-01-30T15:27:49.000Z | 2022-03-31T13:09:28.000Z | agenda/events.py | hyroai/agenda | 1321e49ec433d62901e1e00dfd546c00d43db544 | [
"MIT"
] | null | null | null | import dataclasses
@dataclasses.dataclass(frozen=True)
class ConversationEvent:
type: str
def conversation_start():
return ConversationEvent("CONVERSATION_START")
| 15.909091 | 50 | 0.788571 | 17 | 175 | 8 | 0.764706 | 0.25 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.131429 | 175 | 10 | 51 | 17.5 | 0.894737 | 0 | 0 | 0 | 0 | 0 | 0.102857 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | true | 0 | 0.166667 | 0.166667 | 0.833333 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 5 |
151e66a1c12024b693df48c79fbd73bf784661cb | 259 | py | Python | WEEKS/CD_Sata-Structures/_MISC/misc-examples/python3-book-examples/urllib.parse/urllib_parse_urljoin_with_path.py | webdevhub42/Lambda | b04b84fb5b82fe7c8b12680149e25ae0d27a0960 | [
"MIT"
] | null | null | null | WEEKS/CD_Sata-Structures/_MISC/misc-examples/python3-book-examples/urllib.parse/urllib_parse_urljoin_with_path.py | webdevhub42/Lambda | b04b84fb5b82fe7c8b12680149e25ae0d27a0960 | [
"MIT"
] | null | null | null | WEEKS/CD_Sata-Structures/_MISC/misc-examples/python3-book-examples/urllib.parse/urllib_parse_urljoin_with_path.py | webdevhub42/Lambda | b04b84fb5b82fe7c8b12680149e25ae0d27a0960 | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
"""Joining fragments into absolute URLs
"""
# end_pymotw_header
from urllib.parse import urljoin
print(urljoin("http://www.example.com/path/", "/subpath/file.html"))
print(urljoin("http://www.example.com/path/", "subpath/file.html"))
| 25.9 | 68 | 0.72973 | 37 | 259 | 5.054054 | 0.702703 | 0.128342 | 0.171123 | 0.203209 | 0.513369 | 0.513369 | 0.513369 | 0.513369 | 0.513369 | 0.513369 | 0 | 0.004184 | 0.07722 | 259 | 9 | 69 | 28.777778 | 0.778243 | 0.293436 | 0 | 0 | 0 | 0 | 0.52 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.333333 | 0 | 0.333333 | 0.666667 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 5 |
15644cd5a1d8dc1f34816df272c8ae1fa7582f6d | 749 | py | Python | tests/testrunner.py | knub/skypyblue | 93aa91446c652466b8f9311f0e403c201dbce21b | [
"MIT"
] | 4 | 2019-04-29T15:10:36.000Z | 2021-09-11T23:21:05.000Z | tests/testrunner.py | babelsberg/skypyblue | 6b74344959a734f352925c8c817ec6c89ee31772 | [
"MIT"
] | 1 | 2021-06-30T12:16:34.000Z | 2021-06-30T12:16:34.000Z | tests/testrunner.py | knub/skypyblue | 93aa91446c652466b8f9311f0e403c201dbce21b | [
"MIT"
] | 1 | 2015-07-23T14:01:52.000Z | 2015-07-23T14:01:52.000Z | #!/usr/bin/env python3
"""
Usage:
./testrunner.py -> executes all tests
./testrunner.py <TestCaseClass> -> executes only tests from this testcase
"""
if __name__ != "__main__": exit()
import unittest, sys
sys.path.append("../src")
sys.path.append("./performance")
from constraint_system_tests import *
from variable_tests import *
from helper_method_tests import *
from mvine_tests import *
from exec_tests import *
from midpoint_tests import *
from extended_midpoint_tests import *
from update_method_graph_tests import *
from constraint_tests import *
from constraint_factory_tests import *
from cycle_tests import *
from chain_tests import *
# from benchmark import *
# run_benchmark([2, 0, 50])
unittest.main()
| 23.40625 | 79 | 0.740988 | 98 | 749 | 5.387755 | 0.459184 | 0.25 | 0.340909 | 0.087121 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.007962 | 0.161549 | 749 | 31 | 80 | 24.16129 | 0.832803 | 0.291055 | 0 | 0 | 0 | 0 | 0.051823 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.764706 | 0 | 0.764706 | 0 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
156c16e3076a7a1c6657b90f904d81f735b818b1 | 202 | py | Python | temp.py | boozebrewer/commons | d82794ecc3d218ca25d836c068d680d031383103 | [
"MIT"
] | null | null | null | temp.py | boozebrewer/commons | d82794ecc3d218ca25d836c068d680d031383103 | [
"MIT"
] | null | null | null | temp.py | boozebrewer/commons | d82794ecc3d218ca25d836c068d680d031383103 | [
"MIT"
] | null | null | null | import commons
@commons.timer.timer
def asdf():
print('hi')
asdf()
@commons.timer.timer
def poij():
print('bye')
poij()
with commons.printer.PrintDone("ddddd"):
commons.timer.time.sleep(1) | 15.538462 | 40 | 0.683168 | 28 | 202 | 4.928571 | 0.571429 | 0.26087 | 0.246377 | 0.289855 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.005747 | 0.138614 | 202 | 13 | 41 | 15.538462 | 0.787356 | 0 | 0 | 0.181818 | 0 | 0 | 0.049261 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.181818 | true | 0 | 0.090909 | 0 | 0.272727 | 0.272727 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
ec683df6373947e266b74c84d0b3fe7f75cdd52a | 70 | py | Python | utils/process.py | maxzheng/utils-core | 70947725accac0a4af72d6117322e079bccb9670 | [
"MIT"
] | null | null | null | utils/process.py | maxzheng/utils-core | 70947725accac0a4af72d6117322e079bccb9670 | [
"MIT"
] | null | null | null | utils/process.py | maxzheng/utils-core | 70947725accac0a4af72d6117322e079bccb9670 | [
"MIT"
] | 2 | 2019-04-24T20:48:23.000Z | 2020-06-01T22:59:45.000Z | from utils_core.process import * # noqa / for backward-compatibility
| 35 | 69 | 0.785714 | 9 | 70 | 6 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.142857 | 70 | 1 | 70 | 70 | 0.9 | 0.471429 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
ec7913acfeb3fcd9e40418ba71f1063f6fc2a484 | 99 | py | Python | starter_code/api_keys.py | BankeUCI/API-Challenge | 6b7513dd065ee8aa341e60e3f91eec9af223679c | [
"ADSL"
] | null | null | null | starter_code/api_keys.py | BankeUCI/API-Challenge | 6b7513dd065ee8aa341e60e3f91eec9af223679c | [
"ADSL"
] | null | null | null | starter_code/api_keys.py | BankeUCI/API-Challenge | 6b7513dd065ee8aa341e60e3f91eec9af223679c | [
"ADSL"
] | null | null | null | # OpenWeatherMap API Key
weather_api_key = "API key here"
# Google API Key
g_key = "API key here"
| 16.5 | 32 | 0.727273 | 17 | 99 | 4.058824 | 0.411765 | 0.434783 | 0.26087 | 0.376812 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.191919 | 99 | 5 | 33 | 19.8 | 0.8625 | 0.373737 | 0 | 0 | 0 | 0 | 0.40678 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
ec895bc77cd32c28a9dd332f1c4324e4eb47b854 | 4,699 | py | Python | tests/data/test_export.py | R-C0DE/PySQL | fb5ab210c4d7c7e6208dcce1ac7601496dda67e6 | [
"MIT"
] | 1 | 2021-10-02T10:30:22.000Z | 2021-10-02T10:30:22.000Z | tests/data/test_export.py | R-C0DE/PySQL | fb5ab210c4d7c7e6208dcce1ac7601496dda67e6 | [
"MIT"
] | null | null | null | tests/data/test_export.py | R-C0DE/PySQL | fb5ab210c4d7c7e6208dcce1ac7601496dda67e6 | [
"MIT"
] | null | null | null | """
module for testing export package
of PySQL
"""
import unittest
import pysql.data.export as export
import pathlib
import os
import shutil
# initializing object for Export class of export module
const = export.Export("root", "root")
class TestExport(unittest.TestCase):
"""
class for testing functions of
export package
"""
def test_export_table_json(self):
"""
Test export_table_json function
Parameters
----------
db: str
name of database to use
table: str
name of table to export
path: str
path to export table
Returns
-------
bool
True if table is exported else False
"""
directory = pathlib.Path(__file__).parents[2]
result = const.export_table_json("test", "users", os.path.join(directory, "src"))
self.assertEqual(result, True)
os.remove(os.path.join(directory, "src", "users.json"))
def test_export_table_csv(self):
"""
Test export_table_csv function
Parameters
----------
db: str
name of database to use
table: str
name of table to export
path: str
path to export table
Returns
-------
bool
True if table is exported else False
"""
directory = pathlib.Path(__file__).parents[2]
result = const.export_table_csv("test", "users", os.path.join(directory, "src"))
self.assertEqual(result, True)
os.remove(os.path.join(directory, "src", "users.csv"))
def test_export_table_sql(self):
"""
Test export_table_sql function
Parameters
----------
db: str
name of database to use
table: str
name of table to export
path: str
path to export SQL file
Returns
-------
bool
True if table is exported else False
"""
directory = pathlib.Path(__file__).parents[2]
result = const.export_table_sql("test", "users", os.path.join(directory, "src"))
self.assertEqual(result, True)
os.remove(os.path.join(directory, "src", "test.users.sql"))
def test_export_all_json(self):
"""
Test export_all_json function
Parameters
----------
db: str
name of database to use
path: str
path to export tables
Returns
-------
bool
True if tables are exported else False
"""
directory = pathlib.Path(__file__).parents[2]
result = const.export_all_json("test", os.path.join(directory, "src"))
self.assertEqual(result, True)
shutil.rmtree(os.path.join(directory, "src", "test"))
def test_export_all_csv(self):
"""
Test export_all_csv function
Parameters
----------
db: str
name of database to use
path: str
path to export tables
Returns
-------
bool
True if tables are exported else False
"""
directory = pathlib.Path(__file__).parents[2]
result = const.export_all_csv("test", os.path.join(directory, "src"))
self.assertEqual(result, True)
shutil.rmtree(os.path.join(directory, "src", "test"))
def test_export_all_sql(self):
"""
Test export_all_sql function
Parameters
----------
db: str
name of database to use
path: str
path to export tables
Returns
-------
bool
True if tables are exported else False
"""
directory = pathlib.Path(__file__).parents[2]
result = const.export_all_sql("test", os.path.join(directory, "src"))
self.assertEqual(result, True)
shutil.rmtree(os.path.join(directory, "src", "test"))
def test_export_database(self):
"""
Test export_database function
Parameters
----------
db: str
name of database to export
path: str
path to export SQL file
Returns
-------
bool
True if database is exported else False
"""
directory = pathlib.Path(__file__).parents[2]
result = const.export_database("test", os.path.join(directory, "src"))
self.assertEqual(result, True)
os.remove(os.path.join(directory, "src", "test"))
if __name__ == "__main__":
unittest.main()
"""
PySQL
Devansh Singh, 2021
"""
| 25.818681 | 89 | 0.54352 | 522 | 4,699 | 4.735632 | 0.122605 | 0.056634 | 0.056634 | 0.107605 | 0.767395 | 0.767395 | 0.767395 | 0.767395 | 0.752427 | 0.752427 | 0 | 0.003577 | 0.345605 | 4,699 | 181 | 90 | 25.961326 | 0.800325 | 0.338795 | 0 | 0.386364 | 0 | 0 | 0.067507 | 0 | 0 | 0 | 0 | 0 | 0.159091 | 1 | 0.159091 | false | 0 | 0.113636 | 0 | 0.295455 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
ec98ff3cf2300e8690ceef7c62f3cba5018244c9 | 48 | wsgi | Python | ruben_helloworld/share/flask-ruben-helloworld.wsgi | zenbur/flask-hello-world | 2d0a6d470707558795686ece4da53bc3648ebdf0 | [
"MIT"
] | null | null | null | ruben_helloworld/share/flask-ruben-helloworld.wsgi | zenbur/flask-hello-world | 2d0a6d470707558795686ece4da53bc3648ebdf0 | [
"MIT"
] | null | null | null | ruben_helloworld/share/flask-ruben-helloworld.wsgi | zenbur/flask-hello-world | 2d0a6d470707558795686ece4da53bc3648ebdf0 | [
"MIT"
] | null | null | null | from ruben_helloworld import app as application
| 24 | 47 | 0.875 | 7 | 48 | 5.857143 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.125 | 48 | 1 | 48 | 48 | 0.97619 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
ec9960268a9531dac5ee8a468cfc1a8207b4650f | 16 | py | Python | tests/__init__.py | cclauss/DBUtils | 19a8a33f71bb4295c8b5de364acbb494bd59fa8c | [
"MIT"
] | 178 | 2017-02-07T14:48:45.000Z | 2020-04-02T03:10:46.000Z | tests/__init__.py | mabaoxing/DBUtils | b71bb5d529c0e2ac2da9b729ffde40396925d776 | [
"MIT"
] | 21 | 2017-02-07T16:55:40.000Z | 2019-12-16T22:46:00.000Z | tests/__init__.py | mabaoxing/DBUtils | b71bb5d529c0e2ac2da9b729ffde40396925d776 | [
"MIT"
] | 38 | 2017-02-07T16:14:23.000Z | 2020-02-25T12:03:50.000Z | # DBUtils tests
| 8 | 15 | 0.75 | 2 | 16 | 6 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.1875 | 16 | 1 | 16 | 16 | 0.923077 | 0.8125 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
ec9dee22e2c5bc15337efea7815d8b255810cef8 | 65 | py | Python | friendly_iter/__init__.py | mbillingr/friendly-iter | 77e1ce72100f592b6155a2152fcc03165af22714 | [
"MIT"
] | null | null | null | friendly_iter/__init__.py | mbillingr/friendly-iter | 77e1ce72100f592b6155a2152fcc03165af22714 | [
"MIT"
] | null | null | null | friendly_iter/__init__.py | mbillingr/friendly-iter | 77e1ce72100f592b6155a2152fcc03165af22714 | [
"MIT"
] | null | null | null | from .iters import Iterator, ParallelIterator, UnorderedIterator
| 32.5 | 64 | 0.861538 | 6 | 65 | 9.333333 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.092308 | 65 | 1 | 65 | 65 | 0.949153 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
eca127bb7b9b656b7f5b390fcb0c919bb03c6697 | 1,755 | py | Python | test/test_v1alpha1_application_source.py | RyanSiu1995/argocd-python-client | 2e8f097fe09f247a46ac70692241a93d1acd076a | [
"MIT"
] | 1 | 2021-11-20T13:37:43.000Z | 2021-11-20T13:37:43.000Z | test/test_v1alpha1_application_source.py | RyanSiu1995/argocd-python-client | 2e8f097fe09f247a46ac70692241a93d1acd076a | [
"MIT"
] | null | null | null | test/test_v1alpha1_application_source.py | RyanSiu1995/argocd-python-client | 2e8f097fe09f247a46ac70692241a93d1acd076a | [
"MIT"
] | null | null | null | """
Consolidate Services
Description of all APIs # noqa: E501
The version of the OpenAPI document: version not set
Generated by: https://openapi-generator.tech
"""
import sys
import unittest
import argocd_python_client
from argocd_python_client.model.v1alpha1_application_source_directory import V1alpha1ApplicationSourceDirectory
from argocd_python_client.model.v1alpha1_application_source_helm import V1alpha1ApplicationSourceHelm
from argocd_python_client.model.v1alpha1_application_source_ksonnet import V1alpha1ApplicationSourceKsonnet
from argocd_python_client.model.v1alpha1_application_source_kustomize import V1alpha1ApplicationSourceKustomize
from argocd_python_client.model.v1alpha1_application_source_plugin import V1alpha1ApplicationSourcePlugin
globals()['V1alpha1ApplicationSourceDirectory'] = V1alpha1ApplicationSourceDirectory
globals()['V1alpha1ApplicationSourceHelm'] = V1alpha1ApplicationSourceHelm
globals()['V1alpha1ApplicationSourceKsonnet'] = V1alpha1ApplicationSourceKsonnet
globals()['V1alpha1ApplicationSourceKustomize'] = V1alpha1ApplicationSourceKustomize
globals()['V1alpha1ApplicationSourcePlugin'] = V1alpha1ApplicationSourcePlugin
from argocd_python_client.model.v1alpha1_application_source import V1alpha1ApplicationSource
class TestV1alpha1ApplicationSource(unittest.TestCase):
"""V1alpha1ApplicationSource unit test stubs"""
def setUp(self):
pass
def tearDown(self):
pass
def testV1alpha1ApplicationSource(self):
"""Test V1alpha1ApplicationSource"""
# FIXME: construct object with mandatory attributes with example values
# model = V1alpha1ApplicationSource() # noqa: E501
pass
if __name__ == '__main__':
unittest.main()
| 38.152174 | 111 | 0.824501 | 151 | 1,755 | 9.324503 | 0.423841 | 0.059659 | 0.089489 | 0.09375 | 0.221591 | 0.221591 | 0.221591 | 0.221591 | 0 | 0 | 0 | 0.03871 | 0.116809 | 1,755 | 45 | 112 | 39 | 0.869677 | 0.2 | 0 | 0.130435 | 1 | 0 | 0.122807 | 0.116959 | 0 | 0 | 0 | 0.022222 | 0 | 1 | 0.130435 | false | 0.130435 | 0.391304 | 0 | 0.565217 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 5 |
eca76eb5ff8a6cde8d638535349abb5debe936c3 | 268 | py | Python | chaco/variable_size_scatterplot.py | janvonrickenbach/Chaco_wxPhoenix_py3 | 21a10cfd81100f28e3fbc273357ac45642519f33 | [
"BSD-3-Clause"
] | null | null | null | chaco/variable_size_scatterplot.py | janvonrickenbach/Chaco_wxPhoenix_py3 | 21a10cfd81100f28e3fbc273357ac45642519f33 | [
"BSD-3-Clause"
] | null | null | null | chaco/variable_size_scatterplot.py | janvonrickenbach/Chaco_wxPhoenix_py3 | 21a10cfd81100f28e3fbc273357ac45642519f33 | [
"BSD-3-Clause"
] | null | null | null | """ The base ScatterPlot class now accepts variable sized markers.
This definition remains for backwards compatibility.
"""
from chaco.scatterplot import ScatterPlot
# TODO: This should be officially deprecated.
class VariableSizeScatterPlot(ScatterPlot):
pass
| 24.363636 | 66 | 0.802239 | 30 | 268 | 7.166667 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.141791 | 268 | 10 | 67 | 26.8 | 0.934783 | 0.600746 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.1 | 0 | 1 | 0 | true | 0.333333 | 0.333333 | 0 | 0.666667 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 5 |
01a782e670a1f3fffdf78b0d16faeac130841d80 | 214 | py | Python | mysite/core/models.py | Reymond190/django-celery-myex | 4cfd8a1bed9edccb60f23ab5587e53a60d4a438d | [
"MIT"
] | null | null | null | mysite/core/models.py | Reymond190/django-celery-myex | 4cfd8a1bed9edccb60f23ab5587e53a60d4a438d | [
"MIT"
] | null | null | null | mysite/core/models.py | Reymond190/django-celery-myex | 4cfd8a1bed9edccb60f23ab5587e53a60d4a438d | [
"MIT"
] | null | null | null | from django.db import models
# Create your models here.
class mydetails(models.Model):
name = models.CharField(max_length=20)
age = models.CharField(max_length=20)
sex = models.CharField(max_length=20) | 30.571429 | 42 | 0.747664 | 31 | 214 | 5.064516 | 0.580645 | 0.286624 | 0.343949 | 0.458599 | 0.496815 | 0 | 0 | 0 | 0 | 0 | 0 | 0.032967 | 0.149533 | 214 | 7 | 43 | 30.571429 | 0.82967 | 0.11215 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.2 | 0 | 1 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 5 |
bf22b4ae08afdec094319d3535c2fa74ea58d0cf | 80 | py | Python | danklogs/__init__.py | OofChair/AndyCogs | 0ccc6c3eba6f66051a9acf85fee765aae62c985b | [
"MIT"
] | 8 | 2021-01-26T19:44:13.000Z | 2021-08-03T00:11:39.000Z | danklogs/__init__.py | OofChair/AndyCogs | 0ccc6c3eba6f66051a9acf85fee765aae62c985b | [
"MIT"
] | 6 | 2021-03-02T16:59:40.000Z | 2021-07-21T06:26:00.000Z | danklogs/__init__.py | OofChair/AndyCogs | 0ccc6c3eba6f66051a9acf85fee765aae62c985b | [
"MIT"
] | 6 | 2021-02-11T20:35:10.000Z | 2021-08-07T07:40:17.000Z | from .danklogs import DankLogs
def setup(bot):
bot.add_cog(DankLogs(bot))
| 13.333333 | 30 | 0.725 | 12 | 80 | 4.75 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.1625 | 80 | 5 | 31 | 16 | 0.850746 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0.333333 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
bf384ab666ee49dd73fa017afb733649578eddd3 | 61 | py | Python | src/settings/__init__.py | armatita/pressure_volume_controller | 067508da68a45bcd93fcebc8bac72e9ee39d2e86 | [
"MIT"
] | null | null | null | src/settings/__init__.py | armatita/pressure_volume_controller | 067508da68a45bcd93fcebc8bac72e9ee39d2e86 | [
"MIT"
] | null | null | null | src/settings/__init__.py | armatita/pressure_volume_controller | 067508da68a45bcd93fcebc8bac72e9ee39d2e86 | [
"MIT"
] | null | null | null | from .Settings import Settings
from .Observer import Observer | 30.5 | 30 | 0.852459 | 8 | 61 | 6.5 | 0.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.114754 | 61 | 2 | 31 | 30.5 | 0.962963 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
172ecbb4ef1588cd47b5384ec2da28e24078f3f6 | 5,752 | py | Python | usfm_tools/support/abstractRenderer.py | linearcombination/USFM-Tools | edbaa11375aae377ac9e548f28830a03a61dfe4b | [
"MIT"
] | null | null | null | usfm_tools/support/abstractRenderer.py | linearcombination/USFM-Tools | edbaa11375aae377ac9e548f28830a03a61dfe4b | [
"MIT"
] | null | null | null | usfm_tools/support/abstractRenderer.py | linearcombination/USFM-Tools | edbaa11375aae377ac9e548f28830a03a61dfe4b | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
#
import logging
import pathlib
from typing import Dict, List
try:
from books import loadBook, silNames
from parseUsfm import parseString
except:
from .books import loadBook, silNames
from .parseUsfm import parseString
logger = logging.getLogger("usfm_tools")
class AbstractRenderer(object):
# booksUsfm = None
booksUsfm: Dict
# FIXME This needs to be localized for non-English languages,
# however it is used.
# chapterLabel = "Chapter"
chapterLabel = ""
def writeLog(self, s):
pass
# def loadUSFM(self, usfmDir):
def loadUSFM(self, filePath: pathlib.Path) -> None:
# self.booksUsfm = loadBooks(usfmDir)
# self.booksUsfm = loadBooks(files)
self.booksUsfm = loadBook(filePath)
# def loadUSFM(self, files: List[pathlib.Path]) -> None:
# # self.booksUsfm = loadBooks(usfmDir)
# self.booksUsfm = loadBooks(files)
def run(self):
self.unknowns = []
try:
# self.renderBook = self.booksUsfm[list(self.booksUsfm.keys())[0]]
# bookName = self.renderBook # FIXME renderBook doesn't exist
for bookName in self.booksUsfm:
self.writeLog(" (" + bookName + ")")
# tokens = parseUsfm.parseString(self.booksUsfm[bookName])
tokens = parseString(self.booksUsfm[bookName])
for t in tokens:
t.renderOn(self)
except:
for bookName in silNames:
if bookName in self.booksUsfm:
self.writeLog(" (" + bookName + ")")
# tokens = parseUsfm.parseString(self.booksUsfm[bookName])
tokens = parseString(self.booksUsfm[bookName])
for t in tokens:
t.renderOn(self)
if len(self.unknowns):
print("Skipped unknown tokens: {0}".format(", ".join(set(self.unknowns))))
def renderID(self, token):
pass
def renderIDE(self, token):
pass
def renderSTS(self, token):
pass
def renderH(self, token):
pass
def renderM(self, token):
pass
def renderTOC1(self, token):
pass
def renderTOC2(self, token):
pass
def renderTOC3(self, token):
pass
def renderMT(self, token):
pass
def renderMT2(self, token):
pass
def renderMT3(self, token):
pass
def renderMS(self, token):
pass
def renderMS2(self, token):
pass
def renderMR(self, token):
pass
def renderMI(self, token):
pass
def renderP(self, token):
pass
def renderSP(self, token):
pass
def renderS(self, token):
pass
def renderS2(self, token):
pass
def renderS3(self, token):
pass
def renderC(self, token):
pass
def renderV(self, token):
pass
def renderWJS(self, token):
pass
def renderWJE(self, token):
pass
def renderTEXT(self, token):
pass
def renderQ(self, token):
pass
def renderQ1(self, token):
pass
def renderQ2(self, token):
pass
def renderQ3(self, token):
pass
def renderNB(self, token):
pass
def renderB(self, token):
pass
def renderQTS(self, token):
pass
def renderQTE(self, token):
pass
def renderR(self, token):
pass
def renderFS(self, token):
pass
def renderFE(self, token):
pass
def renderFR(self, token):
pass
def renderFRE(self, token):
pass
def renderFK(self, token):
pass
def renderFT(self, token):
pass
def renderFQ(self, token):
pass
def renderFP(self, token):
pass
def renderIS(self, token):
pass
def renderIE(self, token):
pass
def renderNDS(self, token):
pass
def renderNDE(self, token):
pass
def renderPBR(self, token):
pass
def renderD(self, token):
pass
def renderREM(self, token):
pass
def renderPI(self, token):
pass
def renderPI2(self, token):
pass
def renderLI(self, token):
pass
def renderXS(self, token):
pass
def renderXE(self, token):
pass
def renderXO(self, token):
pass
def renderXT(self, token):
pass
def renderXDCS(self, token):
pass
def renderXDCE(self, token):
pass
def renderTLS(self, token):
pass
def renderTLE(self, token):
pass
def renderADDS(self, token):
pass
def renderADDE(self, token):
pass
def render_is1(self, token):
pass
def render_imt1(self, token):
pass
def render_imt2(self, token):
pass
def render_imt3(self, token):
pass
def render_ip(self, token):
pass
def render_iot(self, token):
pass
def render_io1(self, token):
pass
def render_io2(self, token):
pass
def render_ior_s(self, token):
pass
def render_ior_e(self, token):
pass
def render_bk_s(self, token):
pass
def render_bk_e(self, token):
pass
def renderSCS(self, token):
pass
def renderSCE(self, token):
pass
def renderBDS(self, token):
pass
def renderBDE(self, token):
pass
def renderBDITS(self, token):
pass
def renderBDITE(self, token):
pass
# Add unknown tokens to list
def renderUnknown(self, token):
self.unknowns.append(token.value)
| 18.797386 | 86 | 0.559631 | 629 | 5,752 | 5.09062 | 0.251192 | 0.22767 | 0.324797 | 0.394753 | 0.269831 | 0.209244 | 0.178014 | 0.178014 | 0.178014 | 0.139913 | 0 | 0.00559 | 0.346836 | 5,752 | 305 | 87 | 18.859016 | 0.846686 | 0.111613 | 0 | 0.47449 | 0 | 0 | 0.010413 | 0 | 0 | 0 | 0 | 0.003279 | 0 | 1 | 0.428571 | false | 0.413265 | 0.035714 | 0 | 0.479592 | 0.005102 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 5 |
174c03a0541e1d9bb4c926ac464b2a96a1bb4b06 | 70 | py | Python | kattis/ofugsnuid.py | terror/Solutions | 1ad33daec95b565a38ac4730261593bcf249ac86 | [
"CC0-1.0"
] | 2 | 2021-04-05T14:26:37.000Z | 2021-06-10T04:22:01.000Z | kattis/ofugsnuid.py | terror/Solutions | 1ad33daec95b565a38ac4730261593bcf249ac86 | [
"CC0-1.0"
] | null | null | null | kattis/ofugsnuid.py | terror/Solutions | 1ad33daec95b565a38ac4730261593bcf249ac86 | [
"CC0-1.0"
] | null | null | null | print((*[int(input()) for _ in range(int(input()))][::-1]), sep="\n")
| 35 | 69 | 0.528571 | 11 | 70 | 3.272727 | 0.818182 | 0.444444 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.015625 | 0.085714 | 70 | 1 | 70 | 70 | 0.546875 | 0 | 0 | 0 | 0 | 0 | 0.028571 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 1 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 5 |
174c39ceb51184747621286be634ea522f78983a | 193 | py | Python | tests/ui/pom_pages/home.py | valentinavolgina2/sunny-hikes | 52e66185fb017e27c11b2f81f86c6c77272d868f | [
"MIT"
] | 1 | 2021-12-28T22:08:44.000Z | 2021-12-28T22:08:44.000Z | tests/ui/pom_pages/home.py | valentinavolgina2/sunny-hikes | 52e66185fb017e27c11b2f81f86c6c77272d868f | [
"MIT"
] | 86 | 2021-02-05T01:02:21.000Z | 2022-03-27T00:05:37.000Z | tests/ui/pom_pages/home.py | valentinavolgina2/sunny-hikes | 52e66185fb017e27c11b2f81f86c6c77272d868f | [
"MIT"
] | null | null | null | class HomePage():
def __init__(self, page):
self.page = page
def open(self):
self.page.goto("/")
def login(self):
self.page.click("//*[@id='loginLink']")
| 17.545455 | 47 | 0.533679 | 23 | 193 | 4.304348 | 0.521739 | 0.323232 | 0.242424 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.274611 | 193 | 10 | 48 | 19.3 | 0.707143 | 0 | 0 | 0 | 0 | 0 | 0.108808 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.428571 | false | 0 | 0 | 0 | 0.571429 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 5 |
17717b5d726521af47d61c378282ca5f5dd3d6d7 | 5,147 | py | Python | pepdb/core/migrations/0137_auto_20180219_2155.py | dchaplinsky/pep.org.ua | 8633a65fb657d7f04dbdb12eb8ae705fa6be67e3 | [
"MIT"
] | 7 | 2015-12-21T03:52:46.000Z | 2020-07-24T19:17:23.000Z | pepdb/core/migrations/0137_auto_20180219_2155.py | dchaplinsky/pep.org.ua | 8633a65fb657d7f04dbdb12eb8ae705fa6be67e3 | [
"MIT"
] | 12 | 2016-03-05T18:11:05.000Z | 2021-06-17T20:20:03.000Z | pepdb/core/migrations/0137_auto_20180219_2155.py | dchaplinsky/pep.org.ua | 8633a65fb657d7f04dbdb12eb8ae705fa6be67e3 | [
"MIT"
] | 4 | 2016-07-17T20:19:38.000Z | 2021-03-23T12:47:20.000Z | # -*- coding: utf-8 -*-
# Generated by Django 1.11.5 on 2018-02-19 19:55
from __future__ import unicode_literals
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('core', '0136_auto_20180104_0122'),
]
operations = [
migrations.AddField(
model_name='company',
name='last_change',
field=models.DateTimeField(blank=True, null=True, verbose_name="\u0414\u0430\u0442\u0430 \u043e\u0441\u0442\u0430\u043d\u043d\u044c\u043e\u0457 \u0437\u043c\u0456\u043d\u0438 \u043f\u0440\u043e\u0444\u0456\u043b\u044f \u0430\u0431\u043e \u0437\u0432'\u044f\u0437\u043a\u0456\u0432 \u043f\u0440\u043e\u0444\u0456\u043b\u044f"),
),
migrations.AddField(
model_name='company',
name='last_editor',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to=settings.AUTH_USER_MODEL, verbose_name='\u0410\u0432\u0442\u043e\u0440 \u0437\u043c\u0456\u043d\u0438'),
),
migrations.AddField(
model_name='person',
name='last_change',
field=models.DateTimeField(blank=True, null=True, verbose_name="\u0414\u0430\u0442\u0430 \u043e\u0441\u0442\u0430\u043d\u043d\u044c\u043e\u0457 \u0437\u043c\u0456\u043d\u0438 \u043f\u0440\u043e\u0444\u0456\u043b\u044f \u0430\u0431\u043e \u0437\u0432'\u044f\u0437\u043a\u0456\u0432 \u043f\u0440\u043e\u0444\u0456\u043b\u044f"),
),
migrations.AddField(
model_name='person',
name='last_editor',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL, to=settings.AUTH_USER_MODEL, verbose_name='\u0410\u0432\u0442\u043e\u0440 \u0437\u043c\u0456\u043d\u0438'),
),
migrations.AddField(
model_name='person',
name='reason_of_termination',
field=models.IntegerField(blank=True, choices=[(1, '\u041f\u043e\u043c\u0435\u0440'), (2, '\u0417\u0432\u0456\u043b\u044c\u043d\u0438\u0432\u0441\u044f'), (3, "\u0427\u043b\u0435\u043d \u0441\u0456\u043c'\u0457 - \u041f\u0415\u041f \u043f\u0440\u0438\u043f\u0438\u043d\u0438\u0432 \u0431\u0443\u0442\u0438 \u041f\u0415\u041f\u043e\u043c"), (4, '\u0417\u043c\u0456\u043d\u0438 \u0443 \u0437\u0430\u043a\u043e\u043d\u043e\u0434\u0430\u0432\u0441\u0442\u0432\u0456 \u0449\u043e \u0432\u0438\u0437\u043d\u0430\u0447\u0430\u0454 \u0441\u0442\u0430\u0442\u0443\u0441 \u041f\u0415\u041f\u0430'), (5, '\u0417\u043c\u0456\u043d\u0438 \u0444\u043e\u0440\u043c\u0438 \u0432\u043b\u0430\u0441\u043d\u043e\u0441\u0442\u0456 \u044e\u0440. \u043e\u0441\u043e\u0431\u0438 \u043f\u043e\u0441\u0430\u0434\u0430 \u0432 \u043a\u043e\u0442\u0440\u0456\u0439 \u0434\u0430\u0432\u0430\u043b\u0430 \u0441\u0442\u0430\u0442\u0443\u0441 \u041f\u0415\u041f\u0430')], null=True, verbose_name='\u041f\u0440\u0438\u0447\u0438\u043d\u0430 \u043f\u0440\u0438\u043f\u0438\u043d\u0435\u043d\u043d\u044f \u0441\u0442\u0430\u0442\u0443\u0441\u0443 \u041f\u0415\u041f'),
),
migrations.AddField(
model_name='person',
name='termination_date',
field=models.DateField(blank=True, help_text='\u0412\u043a\u0430\u0437\u0443\u0454\u0442\u044c\u0441\u044f \u0440\u0435\u0430\u043b\u044c\u043d\u0430 \u0434\u0430\u0442\u0430 \u0437\u043c\u0456\u043d\u0438 \u0431\u0435\u0437 \u0432\u0440\u0430\u0445\u0443\u0432\u0430\u043d\u043d\u044f 3 \u0440\u043e\u043a\u0456\u0432 (\u0440\u0435\u0430\u043b\u044c\u043d\u0430 \u0434\u0430\u0442\u0430 \u0437\u0432\u0456\u043b\u044c\u043d\u0435\u043d\u043d\u044f, \u0442\u043e\u0449\u043e)', null=True, verbose_name='\u0414\u0430\u0442\u0430 \u043f\u0440\u0438\u043f\u0438\u043d\u0435\u043d\u043d\u044f \u0441\u0442\u0430\u0442\u0443\u0441\u0443 \u041f\u0415\u041f'),
),
migrations.AddField(
model_name='person',
name='termination_date_details',
field=models.IntegerField(choices=[(0, '\u0422\u043e\u0447\u043d\u0430 \u0434\u0430\u0442\u0430'), (1, '\u0420\u0456\u043a \u0442\u0430 \u043c\u0456\u0441\u044f\u0446\u044c'), (2, '\u0422\u0456\u043b\u044c\u043a\u0438 \u0440\u0456\u043a')], default=0, verbose_name='\u0414\u0430\u0442\u0430 \u043f\u0440\u0438\u043f\u0438\u043d\u0435\u043d\u043d\u044f \u0441\u0442\u0430\u0442\u0443\u0441\u0443 \u041f\u0415\u041f: \u0442\u043e\u0447\u043d\u0456\u0441\u0442\u044c'),
),
migrations.AlterField(
model_name='declaration',
name='submitted',
field=models.DateField(blank=True, db_index=True, null=True, verbose_name='\u041f\u043e\u0434\u0430\u043d\u0430'),
),
migrations.AlterField(
model_name='declaration',
name='to_link',
field=models.BooleanField(db_index=True, default=False, verbose_name='\u0414\u0435\u043a\u043b\u0430\u0440\u0430\u0446\u0456\u044f \u0434\u043b\u044f \u043f\u0440\u043e\u0444\u0456\u043b\u0456\u0432'),
),
]
| 80.421875 | 1,145 | 0.711094 | 698 | 5,147 | 5.17192 | 0.166189 | 0.041551 | 0.044598 | 0.052355 | 0.60831 | 0.539058 | 0.489751 | 0.476731 | 0.474515 | 0.474515 | 0 | 0.376515 | 0.134642 | 5,147 | 63 | 1,146 | 81.698413 | 0.433992 | 0.013212 | 0 | 0.625 | 1 | 0.196429 | 0.587273 | 0.500394 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.071429 | 0 | 0.125 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
179250cbdc00f192461469d6c299a90bc107cf58 | 174 | py | Python | models/SAM-master/datasets/__init__.py | ronentk/dyna-babi-baselines | e3c418477fc81dc440bca4cda9e812de52b3b263 | [
"MIT"
] | null | null | null | models/SAM-master/datasets/__init__.py | ronentk/dyna-babi-baselines | e3c418477fc81dc440bca4cda9e812de52b3b263 | [
"MIT"
] | null | null | null | models/SAM-master/datasets/__init__.py | ronentk/dyna-babi-baselines | e3c418477fc81dc440bca4cda9e812de52b3b263 | [
"MIT"
] | null | null | null | from .nfar import NFarDataset
from .copy import CopyDataset
from .prioritysort import PrioritySortDataset
from .rar import RARDataset
from .number_arecall import NARDataset
| 24.857143 | 45 | 0.850575 | 21 | 174 | 7 | 0.619048 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.12069 | 174 | 6 | 46 | 29 | 0.960784 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
1798273c9bd39279b146219e679b5fe777c7e533 | 72 | py | Python | stream_transformer/__init__.py | technogleb/stream_transformer | ab66e83da6d53221bc9e90d10cdb026cba447a71 | [
"MIT"
] | 2 | 2019-07-29T20:07:58.000Z | 2020-11-20T21:40:42.000Z | stream_transformer/__init__.py | technogleb/stream_transformer | ab66e83da6d53221bc9e90d10cdb026cba447a71 | [
"MIT"
] | null | null | null | stream_transformer/__init__.py | technogleb/stream_transformer | ab66e83da6d53221bc9e90d10cdb026cba447a71 | [
"MIT"
] | null | null | null | from stream_transformer.stream_file_transformer import StreamFileMapper
| 36 | 71 | 0.930556 | 8 | 72 | 8 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.055556 | 72 | 1 | 72 | 72 | 0.941176 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
bd8bf0912ae178b06e49c126b0e108a6b42b30f9 | 61 | py | Python | src/reactive/__init__.py | cholcombe973/charm-glusterfs | 56c424393d38188b0b35e14f9955215d6f6eed79 | [
"Apache-2.0"
] | null | null | null | src/reactive/__init__.py | cholcombe973/charm-glusterfs | 56c424393d38188b0b35e14f9955215d6f6eed79 | [
"Apache-2.0"
] | null | null | null | src/reactive/__init__.py | cholcombe973/charm-glusterfs | 56c424393d38188b0b35e14f9955215d6f6eed79 | [
"Apache-2.0"
] | null | null | null | __author__ = 'Chris Holcombe <chris.holcombe@canonical.com>'
| 30.5 | 60 | 0.786885 | 7 | 61 | 6.285714 | 0.714286 | 0.590909 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.081967 | 61 | 1 | 61 | 61 | 0.785714 | 0 | 0 | 0 | 0 | 0 | 0.737705 | 0.491803 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
bd9f8a2df6e024a902210aa9729c25352cb230b2 | 6,430 | py | Python | parsetab.py | DhruvPatel01/NotAeroCalc | d4db34c88eaf55e198c9205eb2868bb6c2aca701 | [
"MIT"
] | null | null | null | parsetab.py | DhruvPatel01/NotAeroCalc | d4db34c88eaf55e198c9205eb2868bb6c2aca701 | [
"MIT"
] | null | null | null | parsetab.py | DhruvPatel01/NotAeroCalc | d4db34c88eaf55e198c9205eb2868bb6c2aca701 | [
"MIT"
] | null | null | null |
# parsetab.py
# This file is automatically generated. Do not edit.
# pylint: disable=W,C,R
_tabversion = '3.10'
_lr_method = 'LALR'
_lr_signature = 'nonassocINleft+-left*/rightUMINUSrightUPLUSright^DEL EQUATION FLOAT IMPORT IN RAWSTR RESET SI SOLVE STRING UNIVARIATE_FN VARIABLESstart : statement\n | command \';\'\n | command \n |\n command : DEL STRING\n | VARIABLES\n | IMPORT RAWSTR \n | RESET\n | SOLVE to_solve\n | EQUATION RAWSTRto_solve : STRING\n | to_solve \',\' STRING\n statement : STRING "=" expression\n | STRING "=" expression \';\'\n statement : expression\n | expression \';\'\n expression : expression \'+\' expression\n | expression \'-\' expression\n | expression \'*\' expression\n | expression \'/\' expression\n | expression \'^\' expression\n | expression IN expression \n | expression IN SIexpression : \'-\' expression %prec UMINUSexpression : \'+\' expression %prec UPLUSexpression : \'(\' expression \')\'expression : FLOATexpression : STRINGexpression : UNIVARIATE_FN \'(\' expression \')\' '
_lr_action_items = {'$end':([0,1,2,3,4,5,7,9,15,17,19,26,27,28,29,30,31,32,33,36,37,38,39,40,41,42,43,45,47,48,49,],[-4,0,-1,-3,-28,-15,-6,-8,-27,-2,-16,-5,-7,-9,-11,-10,-25,-28,-24,-13,-17,-18,-19,-20,-21,-22,-23,-26,-14,-12,-29,]),'STRING':([0,6,10,12,13,14,18,20,21,22,23,24,25,35,44,],[4,26,29,32,32,32,32,32,32,32,32,32,32,32,48,]),'DEL':([0,],[6,]),'VARIABLES':([0,],[7,]),'IMPORT':([0,],[8,]),'RESET':([0,],[9,]),'SOLVE':([0,],[10,]),'EQUATION':([0,],[11,]),'-':([0,4,5,12,13,14,15,18,20,21,22,23,24,25,31,32,33,34,35,36,37,38,39,40,41,42,43,45,46,49,],[13,-28,21,13,13,13,-27,13,13,13,13,13,13,13,-25,-28,-24,21,13,21,-17,-18,-19,-20,-21,21,-23,-26,21,-29,]),'+':([0,4,5,12,13,14,15,18,20,21,22,23,24,25,31,32,33,34,35,36,37,38,39,40,41,42,43,45,46,49,],[12,-28,20,12,12,12,-27,12,12,12,12,12,12,12,-25,-28,-24,20,12,20,-17,-18,-19,-20,-21,20,-23,-26,20,-29,]),'(':([0,12,13,14,16,18,20,21,22,23,24,25,35,],[14,14,14,14,35,14,14,14,14,14,14,14,14,]),'FLOAT':([0,12,13,14,18,20,21,22,23,24,25,35,],[15,15,15,15,15,15,15,15,15,15,15,15,]),'UNIVARIATE_FN':([0,12,13,14,18,20,21,22,23,24,25,35,],[16,16,16,16,16,16,16,16,16,16,16,16,]),';':([3,4,5,7,9,15,26,27,28,29,30,31,32,33,36,37,38,39,40,41,42,43,45,48,49,],[17,-28,19,-6,-8,-27,-5,-7,-9,-11,-10,-25,-28,-24,47,-17,-18,-19,-20,-21,-22,-23,-26,-12,-29,]),'=':([4,],[18,]),'*':([4,5,15,31,32,33,34,36,37,38,39,40,41,42,43,45,46,49,],[-28,22,-27,-25,-28,-24,22,22,22,22,-19,-20,-21,22,-23,-26,22,-29,]),'/':([4,5,15,31,32,33,34,36,37,38,39,40,41,42,43,45,46,49,],[-28,23,-27,-25,-28,-24,23,23,23,23,-19,-20,-21,23,-23,-26,23,-29,]),'^':([4,5,15,31,32,33,34,36,37,38,39,40,41,42,43,45,46,49,],[-28,24,-27,24,-28,24,24,24,24,24,24,24,24,24,-23,-26,24,-29,]),'IN':([4,5,15,31,32,33,34,36,37,38,39,40,41,42,43,45,46,49,],[-28,25,-27,-25,-28,-24,25,25,-17,-18,-19,-20,-21,25,-23,-26,25,-29,]),'RAWSTR':([8,11,],[27,30,]),')':([15,31,32,33,34,37,38,39,40,41,42,43,45,46,49,],[-27,-25,-28,-24,45,-17,-18,-19,-20,-21,-22,-23,-26,49,-29,]),'SI':([25,],[43,]),',':([28,29,48,],[44,-11,-12,]),}
_lr_action = {}
for _k, _v in _lr_action_items.items():
for _x,_y in zip(_v[0],_v[1]):
if not _x in _lr_action: _lr_action[_x] = {}
_lr_action[_x][_k] = _y
del _lr_action_items
_lr_goto_items = {'start':([0,],[1,]),'statement':([0,],[2,]),'command':([0,],[3,]),'expression':([0,12,13,14,18,20,21,22,23,24,25,35,],[5,31,33,34,36,37,38,39,40,41,42,46,]),'to_solve':([10,],[28,]),}
_lr_goto = {}
for _k, _v in _lr_goto_items.items():
for _x, _y in zip(_v[0], _v[1]):
if not _x in _lr_goto: _lr_goto[_x] = {}
_lr_goto[_x][_k] = _y
del _lr_goto_items
_lr_productions = [
("S' -> start","S'",1,None,None,None),
('start -> statement','start',1,'p_start_statement','parsing.py',86),
('start -> command ;','start',2,'p_start_statement','parsing.py',87),
('start -> command','start',1,'p_start_statement','parsing.py',88),
('start -> <empty>','start',0,'p_start_statement','parsing.py',89),
('command -> DEL STRING','command',2,'p_start_command','parsing.py',95),
('command -> VARIABLES','command',1,'p_start_command','parsing.py',96),
('command -> IMPORT RAWSTR','command',2,'p_start_command','parsing.py',97),
('command -> RESET','command',1,'p_start_command','parsing.py',98),
('command -> SOLVE to_solve','command',2,'p_start_command','parsing.py',99),
('command -> EQUATION RAWSTR','command',2,'p_start_command','parsing.py',100),
('to_solve -> STRING','to_solve',1,'p_to_solve','parsing.py',128),
('to_solve -> to_solve , STRING','to_solve',3,'p_to_solve','parsing.py',129),
('statement -> STRING = expression','statement',3,'p_statement_assign','parsing.py',140),
('statement -> STRING = expression ;','statement',4,'p_statement_assign','parsing.py',141),
('statement -> expression','statement',1,'p_statement_expr','parsing.py',150),
('statement -> expression ;','statement',2,'p_statement_expr','parsing.py',151),
('expression -> expression + expression','expression',3,'p_expression_binop','parsing.py',159),
('expression -> expression - expression','expression',3,'p_expression_binop','parsing.py',160),
('expression -> expression * expression','expression',3,'p_expression_binop','parsing.py',161),
('expression -> expression / expression','expression',3,'p_expression_binop','parsing.py',162),
('expression -> expression ^ expression','expression',3,'p_expression_binop','parsing.py',163),
('expression -> expression IN expression','expression',3,'p_expression_binop','parsing.py',164),
('expression -> expression IN SI','expression',3,'p_expression_binop','parsing.py',165),
('expression -> - expression','expression',2,'p_expression_uminus','parsing.py',199),
('expression -> + expression','expression',2,'p_expression_uplus','parsing.py',204),
('expression -> ( expression )','expression',3,'p_expression_group','parsing.py',209),
('expression -> FLOAT','expression',1,'p_expression_number','parsing.py',214),
('expression -> STRING','expression',1,'p_expression_name','parsing.py',226),
('expression -> UNIVARIATE_FN ( expression )','expression',4,'p_expression_func','parsing.py',244),
]
| 107.166667 | 2,040 | 0.607465 | 1,109 | 6,430 | 3.400361 | 0.139766 | 0.169716 | 0.111376 | 0.023336 | 0.52559 | 0.445505 | 0.397772 | 0.33625 | 0.276319 | 0.271546 | 0 | 0.206241 | 0.107932 | 6,430 | 59 | 2,041 | 108.983051 | 0.451186 | 0.013064 | 0 | 0.040816 | 1 | 0.040816 | 0.474846 | 0.008201 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.061224 | 0 | 0.061224 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
bdae403c1c3d406ddef109a508f9e4e8a66fbf84 | 33 | py | Python | products/models/__init__.py | mrearsbig/store | f311c48f8e79f6d6fb7bf2c8c9a0b65d1b271ff0 | [
"MIT"
] | 1 | 2021-11-26T21:39:52.000Z | 2021-11-26T21:39:52.000Z | products/models/__init__.py | mrearsbig/backend | f311c48f8e79f6d6fb7bf2c8c9a0b65d1b271ff0 | [
"MIT"
] | null | null | null | products/models/__init__.py | mrearsbig/backend | f311c48f8e79f6d6fb7bf2c8c9a0b65d1b271ff0 | [
"MIT"
] | null | null | null | from .productmodel import Product | 33 | 33 | 0.878788 | 4 | 33 | 7.25 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.090909 | 33 | 1 | 33 | 33 | 0.966667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
bdbd264c58bdaee253c498f2bb7e87f47eb937eb | 185 | py | Python | catalyst/rl/offpolicy/algorithms/__init__.py | cgarciae/catalyst | 391ff89ab0d9a1961b88719e894f917ac0fb7fc3 | [
"Apache-2.0"
] | 46 | 2020-03-27T20:12:32.000Z | 2021-11-21T19:08:51.000Z | catalyst/rl/offpolicy/algorithms/__init__.py | cgarciae/catalyst | 391ff89ab0d9a1961b88719e894f917ac0fb7fc3 | [
"Apache-2.0"
] | 2 | 2020-04-06T10:43:04.000Z | 2020-07-01T18:26:10.000Z | catalyst/rl/offpolicy/algorithms/__init__.py | cgarciae/catalyst | 391ff89ab0d9a1961b88719e894f917ac0fb7fc3 | [
"Apache-2.0"
] | 5 | 2020-04-17T14:09:53.000Z | 2021-05-10T08:58:29.000Z | # flake8: noqa
from .actor_critic import OffpolicyActorCritic
from .critic import OffpolicyCritic
from .ddpg import DDPG
from .dqn import DQN
from .sac import SAC
from .td3 import TD3
| 20.555556 | 46 | 0.805405 | 27 | 185 | 5.481481 | 0.444444 | 0.162162 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.019108 | 0.151351 | 185 | 8 | 47 | 23.125 | 0.923567 | 0.064865 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
bdc8514611827ef37dbd1eaef0620d262b9f1321 | 179 | py | Python | pymove/tests/test_base_init.py | JuniorNunes15/PyMove | ee5b68282502bfcb9cf38b52dcdefed5bd927a90 | [
"MIT"
] | 63 | 2019-08-06T14:24:36.000Z | 2022-03-22T11:11:03.000Z | pymove/tests/test_base_init.py | JuniorNunes15/PyMove | ee5b68282502bfcb9cf38b52dcdefed5bd927a90 | [
"MIT"
] | 49 | 2019-09-20T14:06:50.000Z | 2022-03-11T22:13:43.000Z | pymove/tests/test_base_init.py | JuniorNunes15/PyMove | ee5b68282502bfcb9cf38b52dcdefed5bd927a90 | [
"MIT"
] | 18 | 2019-08-15T18:13:10.000Z | 2021-11-30T16:26:19.000Z | try:
from pymove import * # noqa
_top_import_error = None
except Exception as e:
_top_import_error = e
def test_import_skl():
assert _top_import_error is None
| 16.272727 | 36 | 0.709497 | 27 | 179 | 4.296296 | 0.62963 | 0.232759 | 0.362069 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.240223 | 179 | 10 | 37 | 17.9 | 0.852941 | 0.022346 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.142857 | 1 | 0.142857 | false | 0 | 0.714286 | 0 | 0.857143 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
bde51b33f9d59573f9c7e7e70a597fc05fd16a03 | 352 | py | Python | epypes/util.py | semeniuta/EPypes | 4ed2d5389f13e5ebd7e10b8ae93adc25ec4c682b | [
"BSD-3-Clause"
] | 2 | 2019-06-04T02:48:28.000Z | 2020-05-25T09:13:16.000Z | epypes/util.py | semeniuta/EPypes | 4ed2d5389f13e5ebd7e10b8ae93adc25ec4c682b | [
"BSD-3-Clause"
] | null | null | null | epypes/util.py | semeniuta/EPypes | 4ed2d5389f13e5ebd7e10b8ae93adc25ec4c682b | [
"BSD-3-Clause"
] | 2 | 2019-11-12T07:32:23.000Z | 2022-01-29T07:51:03.000Z | import uuid
def generate_short_uuid():
return str(uuid.uuid4())[:8]
def create_name_with_uuid(TargetClass):
return TargetClass.__name__ + generate_short_uuid()
def create_basic_queue():
import sys
ver = sys.version_info[:2]
if ver[0] == 2:
import Queue as queue
else:
import queue
return queue.Queue()
| 17.6 | 55 | 0.667614 | 48 | 352 | 4.604167 | 0.5 | 0.063348 | 0.153846 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.018519 | 0.232955 | 352 | 19 | 56 | 18.526316 | 0.8 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.230769 | false | 0 | 0.307692 | 0.153846 | 0.769231 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 5 |
bdf667091d75eaaf0733a22852e1ecb29deaefa8 | 172 | py | Python | generated-libraries/python/netapp/cifs/nbalias_name_info.py | radekg/netapp-ontap-lib-get | 6445ebb071ec147ea82a486fbe9f094c56c5c40d | [
"MIT"
] | 2 | 2017-03-28T15:31:26.000Z | 2018-08-16T22:15:18.000Z | generated-libraries/python/netapp/cifs/nbalias_name_info.py | radekg/netapp-ontap-lib-get | 6445ebb071ec147ea82a486fbe9f094c56c5c40d | [
"MIT"
] | null | null | null | generated-libraries/python/netapp/cifs/nbalias_name_info.py | radekg/netapp-ontap-lib-get | 6445ebb071ec147ea82a486fbe9f094c56c5c40d | [
"MIT"
] | null | null | null | class NbaliasNameInfo(basestring):
"""
NetBIOS alias for the filer
"""
@staticmethod
def get_api_name():
return "nbalias-name-info"
| 17.2 | 36 | 0.587209 | 17 | 172 | 5.823529 | 0.941176 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.313953 | 172 | 9 | 37 | 19.111111 | 0.838983 | 0.156977 | 0 | 0 | 0 | 0 | 0.131783 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | true | 0 | 0 | 0.25 | 0.75 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 5 |
da09094ae2280f71b7a01877df45966732386395 | 173 | py | Python | Exercism/python/word-count/word_count.py | MrAdityaAlok/learn-to-code | 35ded7a49683659249db89de583ae5fcb1646f9d | [
"MIT"
] | 1 | 2021-08-03T14:00:36.000Z | 2021-08-03T14:00:36.000Z | Exercism/python/word-count/word_count.py | MrAdityaAlok/learn-to-code | 35ded7a49683659249db89de583ae5fcb1646f9d | [
"MIT"
] | null | null | null | Exercism/python/word-count/word_count.py | MrAdityaAlok/learn-to-code | 35ded7a49683659249db89de583ae5fcb1646f9d | [
"MIT"
] | null | null | null | from re import findall
from collections import Counter
def count_words(sentence):
return Counter(
findall("[a-z0-9]+'[st]|[a-z0-9]+", sentence.lower()),
)
| 19.222222 | 62 | 0.647399 | 24 | 173 | 4.625 | 0.666667 | 0.054054 | 0.072072 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.028571 | 0.190751 | 173 | 8 | 63 | 21.625 | 0.764286 | 0 | 0 | 0 | 0 | 0 | 0.138728 | 0.138728 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | false | 0 | 0.333333 | 0.166667 | 0.666667 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 5 |
da0989a6c22b5d238e517cadec40a3b8f5f183e6 | 167 | py | Python | allauth/socialaccount/providers/linkedin/urls.py | mina-gaid/scp | 38e1cd303d4728a987df117f666ce194e241ed1a | [
"MIT"
] | 3 | 2015-02-13T15:06:40.000Z | 2016-05-23T23:23:11.000Z | allauth/socialaccount/providers/linkedin/urls.py | mina-gaid/scp | 38e1cd303d4728a987df117f666ce194e241ed1a | [
"MIT"
] | 9 | 2020-06-05T17:18:43.000Z | 2022-03-11T23:15:04.000Z | allauth/socialaccount/providers/linkedin/urls.py | mina-gaid/scp | 38e1cd303d4728a987df117f666ce194e241ed1a | [
"MIT"
] | 3 | 2018-10-28T13:45:24.000Z | 2020-03-28T02:27:56.000Z | from allauth.socialaccount.providers.oauth.urls import default_urlpatterns
from .provider import LinkedInProvider
urlpatterns = default_urlpatterns(LinkedInProvider)
| 33.4 | 74 | 0.88024 | 17 | 167 | 8.529412 | 0.647059 | 0.248276 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.071856 | 167 | 4 | 75 | 41.75 | 0.935484 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.666667 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
da92f9e0b3f2f8ce168c78dd1358685525bf3f2d | 36 | py | Python | blueplayer/__init__.py | dylwhich/rpi-ipod-emulator | 56d1416a486f48fcbcf425d535268dec19715f2e | [
"MIT"
] | 8 | 2018-04-29T10:24:42.000Z | 2022-01-11T19:28:20.000Z | blueplayer/__init__.py | kataventos/rpi-ipod-emulator | 56d1416a486f48fcbcf425d535268dec19715f2e | [
"MIT"
] | null | null | null | blueplayer/__init__.py | kataventos/rpi-ipod-emulator | 56d1416a486f48fcbcf425d535268dec19715f2e | [
"MIT"
] | 3 | 2018-06-09T23:47:40.000Z | 2021-12-22T17:12:49.000Z | from blueplayer.blueplayer import *
| 18 | 35 | 0.833333 | 4 | 36 | 7.5 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.111111 | 36 | 1 | 36 | 36 | 0.9375 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
e5075b476b1d3d8e26a85769f70d56cdb15bc25e | 4,883 | py | Python | test/ScriptTester.py | AaltoRSE/ImageNetTools | 1ed8b8c38bd14eb47fc6167bf194f327a2696bf1 | [
"BSD-3-Clause"
] | 1 | 2021-11-15T11:21:55.000Z | 2021-11-15T11:21:55.000Z | test/ScriptTester.py | AaltoRSE/ImageNetTools | 1ed8b8c38bd14eb47fc6167bf194f327a2696bf1 | [
"BSD-3-Clause"
] | null | null | null | test/ScriptTester.py | AaltoRSE/ImageNetTools | 1ed8b8c38bd14eb47fc6167bf194f327a2696bf1 | [
"BSD-3-Clause"
] | null | null | null | from dataset_sharding import parse_args
from dataset_sharding import main as shard
import json
import unittest
import tempfile
import os
from webdataset import WebDataset as wds
from torch.utils.data import DataLoader
class ScriptTester(unittest.TestCase):
def setUp(self):
self.tempFolder = tempfile.TemporaryDirectory()
def tearDown(self):
self.tempFolder.cleanup()
def test_shard_parser(self):
# This only tests, whether shards can be written (and checks, whether files were created.
commandlineArgs = "--conf testConfig -x 2"
args = parse_args(commandlineArgs.split())
assert args.maxcount == 2
assert args.dataSource == "../ImageNetTools/tests/Data/Bundle.tar"
def test_shard_Tar_Memory(self):
commandlineArgs = "--conf testConfig -x 2 -r .*?([^/]+)/[^/]*\..*"
args = parse_args(commandlineArgs.split())
shard(commandlineArgs.split())
filesInTempFolder = os.listdir(args.targetFolder)
assert len(filesInTempFolder) == 6 # we have 11 files those go into 6 nw files as a max of 2 files is permitted.
for file in filesInTempFolder:
assert file.startswith(args.datasetName)
#Now, test the contents.
# Since the pictures came from Part1.tars, these will be kept in the key.
pictureNames = {'Part1/PiC1': '1','Part4/Pic10' : '4','Part4/PiC11': '4','Part1/Pic2' : '1','Part1/Pic3': '1','Part2/Pic4': '2','Part2/Pic5' : '2','Part2/Pic6' : '2','Part3/Pic7' : '3','Part3/Pic8' : '3','Part3/Pic9' : '3'}
shardNames = os.path.join('testOutput',"INValidation{0..5}.tar")
ds = wds(shardNames);
loader = DataLoader(ds)
for batch in loader:
assert len(batch["__key__"])>= 1 # we can't make a stronger assertion here.
for key,cls in zip(batch['__key__'],batch['cls']):
assert key in pictureNames
assert cls.decode() == pictureNames[key]
del pictureNames[key]
assert len(pictureNames) == 0
def test_shard_Tar_preproc(self):
commandlineArgs = "--conf testConfig -x 2 -r .*?([^/]+)/[^/]*\..* -p preprocess"
args = parse_args(commandlineArgs.split())
shard(commandlineArgs.split())
filesInTempFolder = os.listdir(args.targetFolder)
assert len(filesInTempFolder) == 6 # we have 11 files those go into 6 nw files as a max of 2 files is permitted.
for file in filesInTempFolder:
assert file.startswith(args.datasetName)
#Now, test the contents.
# Since the pictures came from Part1.tars, these will be kept in the key.
pictureNames = {'Part1/PiC1': '1','Part4/Pic10' : '4','Part4/PiC11': '4','Part1/Pic2' : '1','Part1/Pic3': '1','Part2/Pic4': '2','Part2/Pic5' : '2','Part2/Pic6' : '2','Part3/Pic7' : '3','Part3/Pic8' : '3','Part3/Pic9' : '3'}
shardNames = os.path.join('testOutput',"INValidation{0..5}.tar")
ds = wds(shardNames);
loader = DataLoader(ds)
for batch in loader:
assert len(batch["__key__"])>= 1 # we can't make a stronger assertion here.
for key,cls in zip(batch['__key__'],batch['cls']):
assert key in pictureNames
assert cls.decode() == pictureNames[key]
del pictureNames[key]
assert len(pictureNames) == 0
def test_shard_Folder(self):
commandlineArgs = "--conf testConfig -x 2 -d ../ImageNetTools/tests/Data/Images -m ClassInfo.json"
args = parse_args(commandlineArgs.split())
shard(commandlineArgs.split())
filesInTempFolder = os.listdir(args.targetFolder)
assert len(filesInTempFolder) == 6 # we have 11 files those go into 6 nw files as a max of 2 files is permitted.
for file in filesInTempFolder:
assert file.startswith(args.datasetName)
#Now, test the contents.
# Since the pictures came from Part1.tars, these will be kept in the key.
with open('ClassInfo.json','r') as f:
res = json.load(f)
pictureNames = { n.replace('.JPEG','') : res[n] for n in res}
shardNames = os.path.join('testOutput',"INValidation{0..5}.tar")
ds = wds(shardNames);
loader = DataLoader(ds)
for batch in loader:
assert len(batch["__key__"])>= 1 # we can't make a stronger assertion here.
for key,cls in zip(batch['__key__'],batch['cls']):
assert key in pictureNames
assert cls.decode() == str(pictureNames[key])
del pictureNames[key]
assert len(pictureNames) == 0
| 48.346535 | 231 | 0.590621 | 582 | 4,883 | 4.88488 | 0.250859 | 0.028491 | 0.016884 | 0.042209 | 0.776293 | 0.753781 | 0.74147 | 0.716145 | 0.716145 | 0.696799 | 0 | 0.030095 | 0.28548 | 4,883 | 101 | 232 | 48.346535 | 0.784752 | 0.148679 | 0 | 0.649351 | 0 | 0.012987 | 0.158542 | 0.033301 | 0 | 0 | 0 | 0 | 0.25974 | 1 | 0.077922 | false | 0 | 0.103896 | 0 | 0.194805 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
e56bed5180dc1e30b5b4c37c950cfe7ce6e9f319 | 374 | py | Python | sever/app.py | xiepeiheng/xiepeiheng | fa57a910ea3126b77a4f286c958655350e0d3510 | [
"MIT"
] | null | null | null | sever/app.py | xiepeiheng/xiepeiheng | fa57a910ea3126b77a4f286c958655350e0d3510 | [
"MIT"
] | null | null | null | sever/app.py | xiepeiheng/xiepeiheng | fa57a910ea3126b77a4f286c958655350e0d3510 | [
"MIT"
] | null | null | null | from flask import Flask, render_template
app = Flask(__name__)
#豆瓣爬虫练习
@app.route('/0')
def hello_world1():
return render_template('page1.html')
@app.route('/25')
def hello_world2():
return render_template('page2.html')
#alice练习
@app.route('/alice')
def hello_world3():
return render_template('alice.html')
if __name__ == '__main__':
app.run(debug=True)
| 18.7 | 40 | 0.705882 | 51 | 374 | 4.803922 | 0.529412 | 0.228571 | 0.244898 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.024691 | 0.13369 | 374 | 19 | 41 | 19.684211 | 0.731481 | 0.034759 | 0 | 0 | 0 | 0 | 0.13649 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.230769 | false | 0 | 0.076923 | 0.230769 | 0.538462 | 0 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 5 |
e56eab8cf82b6d2743a0c81c11ac0f987e43309a | 32 | py | Python | aws_security_test.py | fdimant/aws-security-test | f751661e4b9a7a2c09c7a0464700e078820cf384 | [
"Apache-2.0"
] | 9 | 2017-07-07T17:24:05.000Z | 2021-05-18T14:49:29.000Z | aws_security_test.py | mikhailadvani/cis-aws-automation | f751661e4b9a7a2c09c7a0464700e078820cf384 | [
"Apache-2.0"
] | 1 | 2017-08-20T13:54:29.000Z | 2017-08-20T13:54:29.000Z | aws_security_test.py | mikhailadvani/cis-aws-automation | f751661e4b9a7a2c09c7a0464700e078820cf384 | [
"Apache-2.0"
] | 13 | 2017-04-07T16:43:41.000Z | 2020-11-07T15:37:39.000Z | import tests
exit(tests.main())
| 10.666667 | 18 | 0.75 | 5 | 32 | 4.8 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.09375 | 32 | 2 | 19 | 16 | 0.827586 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
e5b66dd8a860fc61040decaa9d241cc645c4e943 | 295 | py | Python | tests/abstract_model/tests/__init__.py | kimgea/django-ordered-field | c3a79cd93b013d90bbe0d6b9c9ede872d16af949 | [
"MIT"
] | null | null | null | tests/abstract_model/tests/__init__.py | kimgea/django-ordered-field | c3a79cd93b013d90bbe0d6b9c9ede872d16af949 | [
"MIT"
] | 1 | 2018-05-10T09:11:49.000Z | 2018-05-10T09:11:49.000Z | tests/abstract_model/tests/__init__.py | kimgea/django-ordered-field | c3a79cd93b013d90bbe0d6b9c9ede872d16af949 | [
"MIT"
] | null | null | null | from .update_tests import ChangeAbstractTests
from .update_two_tests import ChangeAbstractTwoTests
from .insert_tests import InsertAbstractTests
from .insert_two_tests import InsertAbstractTwoTests
from .delete_tests import DeleteAbstractTest
from .delete_two_tests import DeleteAbstractTwoTest
| 42.142857 | 52 | 0.898305 | 33 | 295 | 7.757576 | 0.393939 | 0.257813 | 0.164063 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.081356 | 295 | 6 | 53 | 49.166667 | 0.944649 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
e5d7d171d3ce1e8b8952e498b251165470b9a849 | 33 | py | Python | app/tests/acl_tests/__init__.py | timothyakinyelu/point-of-sale-system-with-flask | f23849ecfdcaa7a7367c4972f020cff8fc1129a9 | [
"MIT"
] | null | null | null | app/tests/acl_tests/__init__.py | timothyakinyelu/point-of-sale-system-with-flask | f23849ecfdcaa7a7367c4972f020cff8fc1129a9 | [
"MIT"
] | null | null | null | app/tests/acl_tests/__init__.py | timothyakinyelu/point-of-sale-system-with-flask | f23849ecfdcaa7a7367c4972f020cff8fc1129a9 | [
"MIT"
] | 1 | 2021-09-13T10:37:48.000Z | 2021-09-13T10:37:48.000Z | # app/tests/acl_tests/__init__.py | 33 | 33 | 0.818182 | 6 | 33 | 3.666667 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.030303 | 33 | 1 | 33 | 33 | 0.6875 | 0.939394 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
e5dbd5b6a842ae4c871cbd91b81eebc977a38032 | 116 | py | Python | utils/__init__.py | alex-ortega-07/hand-writing-recognition-model | 91dc9d7b9e10efe9300249fff569d0ba37c2585e | [
"MIT"
] | 2 | 2021-07-27T17:00:21.000Z | 2021-11-14T11:00:22.000Z | utils/__init__.py | alex-ortega-07/hand-writing-recognition-model | 91dc9d7b9e10efe9300249fff569d0ba37c2585e | [
"MIT"
] | null | null | null | utils/__init__.py | alex-ortega-07/hand-writing-recognition-model | 91dc9d7b9e10efe9300249fff569d0ba37c2585e | [
"MIT"
] | null | null | null | from .settings import *
from .button import Button
from .hand_writing_CNN import *
import pygame
pygame.init() | 19.333333 | 32 | 0.758621 | 16 | 116 | 5.375 | 0.5625 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.172414 | 116 | 6 | 33 | 19.333333 | 0.895833 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.8 | 0 | 0.8 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
e5f024a5d30f492cacddc23804ea3b3507f006fc | 141 | py | Python | vedadet/misc/bbox/iou_calculators/__init__.py | jie311/vedadet | aaf3b3bc3c7944aba1cc28138165d403023a9152 | [
"Apache-2.0"
] | 424 | 2020-10-19T03:56:49.000Z | 2022-03-28T02:47:39.000Z | vedadet/misc/bbox/iou_calculators/__init__.py | jie311/vedadet | aaf3b3bc3c7944aba1cc28138165d403023a9152 | [
"Apache-2.0"
] | 72 | 2020-11-27T17:10:00.000Z | 2022-03-17T02:40:53.000Z | vedadet/misc/bbox/iou_calculators/__init__.py | jie311/vedadet | aaf3b3bc3c7944aba1cc28138165d403023a9152 | [
"Apache-2.0"
] | 116 | 2020-11-03T02:31:17.000Z | 2022-03-08T08:20:48.000Z | from .builder import build_iou_calculator
from .iou2d_calculator import BboxOverlaps2D
__all__ = ['build_iou_calculator', 'BboxOverlaps2D']
| 28.2 | 52 | 0.836879 | 16 | 141 | 6.8125 | 0.5625 | 0.146789 | 0.330275 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.023438 | 0.092199 | 141 | 4 | 53 | 35.25 | 0.828125 | 0 | 0 | 0 | 0 | 0 | 0.241135 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.666667 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
e5f4a2a66fdedc325e682d097c6c7c9f0c718375 | 62 | py | Python | tests/test_cases/multiple_import.py | awiddersheim/flake8-import-single | d4190b395b8da837fc418a2f0b35b0c01af8efbe | [
"MIT"
] | 1 | 2019-02-07T20:42:03.000Z | 2019-02-07T20:42:03.000Z | tests/test_cases/multiple_import.py | awiddersheim/flake8-import-single | d4190b395b8da837fc418a2f0b35b0c01af8efbe | [
"MIT"
] | null | null | null | tests/test_cases/multiple_import.py | awiddersheim/flake8-import-single | d4190b395b8da837fc418a2f0b35b0c01af8efbe | [
"MIT"
] | null | null | null | import doesnotmatter
from foo import bar, baz
import morejunk
| 15.5 | 24 | 0.83871 | 9 | 62 | 5.777778 | 0.777778 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.145161 | 62 | 3 | 25 | 20.666667 | 0.981132 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
f9141c074116c7d5ce1493bcf51a596171e9dd91 | 168 | py | Python | scheduler/__init__.py | MarynaSavchenko/zielbruks | ccebd84adaa71fe5b9735747c8c684ab7e0cbc8e | [
"MIT"
] | null | null | null | scheduler/__init__.py | MarynaSavchenko/zielbruks | ccebd84adaa71fe5b9735747c8c684ab7e0cbc8e | [
"MIT"
] | 9 | 2019-04-01T21:52:12.000Z | 2019-06-11T17:31:10.000Z | scheduler/__init__.py | MarynaSavchenko/zielbruks | ccebd84adaa71fe5b9735747c8c684ab7e0cbc8e | [
"MIT"
] | 2 | 2019-03-31T16:23:04.000Z | 2019-06-15T22:14:41.000Z | '''Init file with celery app added'''
from __future__ import absolute_import, unicode_literals
from scheduler.celery import app as celery_app
__all__ = ['celery_app']
| 28 | 56 | 0.797619 | 24 | 168 | 5.083333 | 0.625 | 0.221311 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.125 | 168 | 5 | 57 | 33.6 | 0.829932 | 0.184524 | 0 | 0 | 0 | 0 | 0.076336 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.666667 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
00579fe2410b9d6d60e01faebbfa72cf1f3d4999 | 162 | py | Python | x_1_6.py | ofl/kuku | 76eefc0d3d859051473ee0d5f48b5d42d17d05a6 | [
"MIT"
] | null | null | null | x_1_6.py | ofl/kuku | 76eefc0d3d859051473ee0d5f48b5d42d17d05a6 | [
"MIT"
] | 4 | 2021-09-23T03:19:52.000Z | 2021-11-13T10:38:21.000Z | x_1_6.py | ofl/kuku | 76eefc0d3d859051473ee0d5f48b5d42d17d05a6 | [
"MIT"
] | null | null | null | # x_1_6
#
# 「onitaiji_members」に「いぬ」と「さる」と「きじ」を順番に追加して表示してください
onitaiji_members = '桃太郎'
print(onitaiji_members)
onitaiji_members += 'いぬ'
print(onitaiji_members)
| 16.2 | 51 | 0.771605 | 24 | 162 | 4.916667 | 0.541667 | 0.635593 | 0.338983 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.013605 | 0.092593 | 162 | 9 | 52 | 18 | 0.789116 | 0.339506 | 0 | 0.5 | 0 | 0 | 0.048544 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.5 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 5 |
006ef9f1401ac7eb40b7113ffb3692b2388a6fcc | 39 | py | Python | nion/ui/test/__init__.py | meyer9/nionui | ca2f9d773bb956e064f40c0cac2465f664447953 | [
"Apache-2.0"
] | 3 | 2018-12-18T23:05:00.000Z | 2019-11-26T19:48:04.000Z | nion/ui/test/__init__.py | meyer9/nionui | ca2f9d773bb956e064f40c0cac2465f664447953 | [
"Apache-2.0"
] | 36 | 2017-07-15T02:07:18.000Z | 2022-03-01T16:59:08.000Z | nion/ui/test/__init__.py | meyer9/nionui | ca2f9d773bb956e064f40c0cac2465f664447953 | [
"Apache-2.0"
] | 12 | 2017-04-03T20:05:46.000Z | 2021-06-09T05:14:44.000Z | # exists to make nion.ui.test a module
| 19.5 | 38 | 0.74359 | 8 | 39 | 3.625 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.179487 | 39 | 1 | 39 | 39 | 0.90625 | 0.923077 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
007e998fdb427a539e34a7002769c6d762f6a81f | 208 | py | Python | z_pictures/admin.py | KenMwaura1/zoo_pictures | 69db5914fea0061eb01f6f1c43196dcd2b266f85 | [
"MIT"
] | null | null | null | z_pictures/admin.py | KenMwaura1/zoo_pictures | 69db5914fea0061eb01f6f1c43196dcd2b266f85 | [
"MIT"
] | null | null | null | z_pictures/admin.py | KenMwaura1/zoo_pictures | 69db5914fea0061eb01f6f1c43196dcd2b266f85 | [
"MIT"
] | null | null | null | from django.contrib import admin
# Register your models here.
from z_pictures.models import Category, Image, Location
admin.site.register(Category)
admin.site.register(Image)
admin.site.register(Location)
| 20.8 | 55 | 0.8125 | 29 | 208 | 5.793103 | 0.517241 | 0.160714 | 0.303571 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.100962 | 208 | 9 | 56 | 23.111111 | 0.898396 | 0.125 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.4 | 0 | 0.4 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
00a48a4099d5d9c5653a072a30ad98b951c52560 | 166 | py | Python | backend/pages/urls.py | ranwise/djangochannel | 9c719d292b5c1d0fd008a16a64509a309bdd642e | [
"BSD-3-Clause"
] | 45 | 2019-10-04T10:12:54.000Z | 2022-03-29T18:12:34.000Z | backend/pages/urls.py | ranwise/djangochannel | 9c719d292b5c1d0fd008a16a64509a309bdd642e | [
"BSD-3-Clause"
] | 6 | 2019-10-09T07:37:14.000Z | 2022-01-27T16:41:16.000Z | backend/pages/urls.py | ranwise/djangochannel | 9c719d292b5c1d0fd008a16a64509a309bdd642e | [
"BSD-3-Clause"
] | 35 | 2019-10-04T10:18:48.000Z | 2022-01-14T22:40:38.000Z | from django.urls import path
from .views import *
urlpatterns = [
path('', Page.as_view(), name="page"),
path('<slug:slug>/', Page.as_view(), name="page")
] | 20.75 | 53 | 0.626506 | 23 | 166 | 4.434783 | 0.521739 | 0.117647 | 0.196078 | 0.27451 | 0.352941 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.162651 | 166 | 8 | 54 | 20.75 | 0.733813 | 0 | 0 | 0 | 0 | 0 | 0.11976 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
dad0690b464aa7b07a3a5530e2df660ecfd08f83 | 193 | py | Python | FINE/expansionModules/__init__.py | sdickler/FINE | 3114fd009e80a7eadacffe26bf5ff8e6a126ac61 | [
"MIT"
] | 34 | 2018-07-02T16:20:39.000Z | 2022-03-30T09:46:44.000Z | FINE/expansionModules/__init__.py | sdickler/FINE | 3114fd009e80a7eadacffe26bf5ff8e6a126ac61 | [
"MIT"
] | 19 | 2018-11-09T07:56:20.000Z | 2022-02-15T10:54:21.000Z | FINE/expansionModules/__init__.py | sdickler/FINE | 3114fd009e80a7eadacffe26bf5ff8e6a126ac61 | [
"MIT"
] | 42 | 2018-09-24T15:07:20.000Z | 2022-02-25T18:41:52.000Z | """
Last edited: February 06, 2020
|br| @author: FINE Developer Team (FZJ IEK-3)
"""
from .transformationPath import *
from .robustPipelineSizing import *
from .optimizeTSAmultiStage import *
| 21.444444 | 45 | 0.751295 | 22 | 193 | 6.590909 | 0.818182 | 0.137931 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.042169 | 0.139896 | 193 | 8 | 46 | 24.125 | 0.831325 | 0.393782 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
dad900bf634cbccd15de6336bee2e867fed28305 | 28,922 | py | Python | venv/lib/python3.8/site-packages/spaceone/api/inventory/v1/region_pb2.py | choonho/plugin-prometheus-mon-webhook | afa7d65d12715fd0480fb4f92a9c62da2d6128e0 | [
"Apache-2.0"
] | null | null | null | venv/lib/python3.8/site-packages/spaceone/api/inventory/v1/region_pb2.py | choonho/plugin-prometheus-mon-webhook | afa7d65d12715fd0480fb4f92a9c62da2d6128e0 | [
"Apache-2.0"
] | null | null | null | venv/lib/python3.8/site-packages/spaceone/api/inventory/v1/region_pb2.py | choonho/plugin-prometheus-mon-webhook | afa7d65d12715fd0480fb4f92a9c62da2d6128e0 | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
# Generated by the protocol buffer compiler. DO NOT EDIT!
# source: spaceone/api/inventory/v1/region.proto
"""Generated protocol buffer code."""
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import symbol_database as _symbol_database
# @@protoc_insertion_point(imports)
_sym_db = _symbol_database.Default()
from google.protobuf import empty_pb2 as google_dot_protobuf_dot_empty__pb2
from google.protobuf import struct_pb2 as google_dot_protobuf_dot_struct__pb2
from google.api import annotations_pb2 as google_dot_api_dot_annotations__pb2
from spaceone.api.core.v1 import query_pb2 as spaceone_dot_api_dot_core_dot_v1_dot_query__pb2
DESCRIPTOR = _descriptor.FileDescriptor(
name='spaceone/api/inventory/v1/region.proto',
package='spaceone.api.inventory.v1',
syntax='proto3',
serialized_options=None,
create_key=_descriptor._internal_create_key,
serialized_pb=b'\n&spaceone/api/inventory/v1/region.proto\x12\x19spaceone.api.inventory.v1\x1a\x1bgoogle/protobuf/empty.proto\x1a\x1cgoogle/protobuf/struct.proto\x1a\x1cgoogle/api/annotations.proto\x1a spaceone/api/core/v1/query.proto\"\x84\x01\n\x13\x43reateRegionRequest\x12\x0c\n\x04name\x18\x01 \x01(\t\x12%\n\x04tags\x18\x02 \x01(\x0b\x32\x17.google.protobuf.Struct\x12\x11\n\tdomain_id\x18\x03 \x01(\t\x12\x13\n\x0bregion_code\x18\x04 \x01(\t\x12\x10\n\x08provider\x18\x05 \x01(\t\"p\n\x13UpdateRegionRequest\x12\x11\n\tregion_id\x18\x01 \x01(\t\x12\x0c\n\x04name\x18\x02 \x01(\t\x12%\n\x04tags\x18\x03 \x01(\x0b\x32\x17.google.protobuf.Struct\x12\x11\n\tdomain_id\x18\x04 \x01(\t\"5\n\rRegionRequest\x12\x11\n\tregion_id\x18\x01 \x01(\t\x12\x11\n\tdomain_id\x18\x02 \x01(\t\"F\n\x10GetRegionRequest\x12\x11\n\tregion_id\x18\x01 \x01(\t\x12\x11\n\tdomain_id\x18\x02 \x01(\t\x12\x0c\n\x04only\x18\x03 \x03(\t\"\x94\x01\n\x0bRegionQuery\x12*\n\x05query\x18\x01 \x01(\x0b\x32\x1b.spaceone.api.core.v1.Query\x12\x11\n\tregion_id\x18\x02 \x01(\t\x12\x0c\n\x04name\x18\x03 \x01(\t\x12\x11\n\tdomain_id\x18\x04 \x01(\t\x12\x13\n\x0bregion_code\x18\x05 \x01(\t\x12\x10\n\x08provider\x18\x06 \x01(\t\"\xe8\x01\n\nRegionInfo\x12\x11\n\tregion_id\x18\x01 \x01(\t\x12\x0c\n\x04name\x18\x02 \x01(\t\x12%\n\x04tags\x18\x03 \x01(\x0b\x32\x17.google.protobuf.Struct\x12\x11\n\tdomain_id\x18\x04 \x01(\t\x12\x12\n\ncreated_at\x18\x05 \x01(\t\x12\x12\n\nupdated_at\x18\x06 \x01(\t\x12\x13\n\x0bregion_code\x18\x08 \x01(\t\x12\x10\n\x08provider\x18\t \x01(\t\x12\x30\n\x0f\x63ollection_info\x18\n \x01(\x0b\x32\x17.google.protobuf.Struct\"Z\n\x0bRegionsInfo\x12\x36\n\x07results\x18\x01 \x03(\x0b\x32%.spaceone.api.inventory.v1.RegionInfo\x12\x13\n\x0btotal_count\x18\x02 \x01(\x05\"Z\n\x0fRegionStatQuery\x12\x34\n\x05query\x18\x01 \x01(\x0b\x32%.spaceone.api.core.v1.StatisticsQuery\x12\x11\n\tdomain_id\x18\x02 \x01(\t2\x99\x06\n\x06Region\x12~\n\x06\x63reate\x12..spaceone.api.inventory.v1.CreateRegionRequest\x1a%.spaceone.api.inventory.v1.RegionInfo\"\x1d\x82\xd3\xe4\x93\x02\x17\"\x15/inventory/v1/regions\x12\x89\x01\n\x06update\x12..spaceone.api.inventory.v1.UpdateRegionRequest\x1a%.spaceone.api.inventory.v1.RegionInfo\"(\x82\xd3\xe4\x93\x02\"\x1a /inventory/v1/region/{region_id}\x12t\n\x06\x64\x65lete\x12(.spaceone.api.inventory.v1.RegionRequest\x1a\x16.google.protobuf.Empty\"(\x82\xd3\xe4\x93\x02\"* /inventory/v1/region/{region_id}\x12\x83\x01\n\x03get\x12+.spaceone.api.inventory.v1.GetRegionRequest\x1a%.spaceone.api.inventory.v1.RegionInfo\"(\x82\xd3\xe4\x93\x02\"\x12 /inventory/v1/region/{region_id}\x12\x95\x01\n\x04list\x12&.spaceone.api.inventory.v1.RegionQuery\x1a&.spaceone.api.inventory.v1.RegionsInfo\"=\x82\xd3\xe4\x93\x02\x37\x12\x15/inventory/v1/regionsZ\x1e\"\x1c/inventory/v1/regions/search\x12o\n\x04stat\x12*.spaceone.api.inventory.v1.RegionStatQuery\x1a\x17.google.protobuf.Struct\"\"\x82\xd3\xe4\x93\x02\x1c\"\x1a/inventory/v1/regions/statb\x06proto3'
,
dependencies=[google_dot_protobuf_dot_empty__pb2.DESCRIPTOR,google_dot_protobuf_dot_struct__pb2.DESCRIPTOR,google_dot_api_dot_annotations__pb2.DESCRIPTOR,spaceone_dot_api_dot_core_dot_v1_dot_query__pb2.DESCRIPTOR,])
_CREATEREGIONREQUEST = _descriptor.Descriptor(
name='CreateRegionRequest',
full_name='spaceone.api.inventory.v1.CreateRegionRequest',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='name', full_name='spaceone.api.inventory.v1.CreateRegionRequest.name', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='tags', full_name='spaceone.api.inventory.v1.CreateRegionRequest.tags', index=1,
number=2, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='domain_id', full_name='spaceone.api.inventory.v1.CreateRegionRequest.domain_id', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='region_code', full_name='spaceone.api.inventory.v1.CreateRegionRequest.region_code', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='provider', full_name='spaceone.api.inventory.v1.CreateRegionRequest.provider', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=193,
serialized_end=325,
)
_UPDATEREGIONREQUEST = _descriptor.Descriptor(
name='UpdateRegionRequest',
full_name='spaceone.api.inventory.v1.UpdateRegionRequest',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='region_id', full_name='spaceone.api.inventory.v1.UpdateRegionRequest.region_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='name', full_name='spaceone.api.inventory.v1.UpdateRegionRequest.name', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='tags', full_name='spaceone.api.inventory.v1.UpdateRegionRequest.tags', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='domain_id', full_name='spaceone.api.inventory.v1.UpdateRegionRequest.domain_id', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=327,
serialized_end=439,
)
_REGIONREQUEST = _descriptor.Descriptor(
name='RegionRequest',
full_name='spaceone.api.inventory.v1.RegionRequest',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='region_id', full_name='spaceone.api.inventory.v1.RegionRequest.region_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='domain_id', full_name='spaceone.api.inventory.v1.RegionRequest.domain_id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=441,
serialized_end=494,
)
_GETREGIONREQUEST = _descriptor.Descriptor(
name='GetRegionRequest',
full_name='spaceone.api.inventory.v1.GetRegionRequest',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='region_id', full_name='spaceone.api.inventory.v1.GetRegionRequest.region_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='domain_id', full_name='spaceone.api.inventory.v1.GetRegionRequest.domain_id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='only', full_name='spaceone.api.inventory.v1.GetRegionRequest.only', index=2,
number=3, type=9, cpp_type=9, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=496,
serialized_end=566,
)
_REGIONQUERY = _descriptor.Descriptor(
name='RegionQuery',
full_name='spaceone.api.inventory.v1.RegionQuery',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='query', full_name='spaceone.api.inventory.v1.RegionQuery.query', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='region_id', full_name='spaceone.api.inventory.v1.RegionQuery.region_id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='name', full_name='spaceone.api.inventory.v1.RegionQuery.name', index=2,
number=3, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='domain_id', full_name='spaceone.api.inventory.v1.RegionQuery.domain_id', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='region_code', full_name='spaceone.api.inventory.v1.RegionQuery.region_code', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='provider', full_name='spaceone.api.inventory.v1.RegionQuery.provider', index=5,
number=6, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=569,
serialized_end=717,
)
_REGIONINFO = _descriptor.Descriptor(
name='RegionInfo',
full_name='spaceone.api.inventory.v1.RegionInfo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='region_id', full_name='spaceone.api.inventory.v1.RegionInfo.region_id', index=0,
number=1, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='name', full_name='spaceone.api.inventory.v1.RegionInfo.name', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='tags', full_name='spaceone.api.inventory.v1.RegionInfo.tags', index=2,
number=3, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='domain_id', full_name='spaceone.api.inventory.v1.RegionInfo.domain_id', index=3,
number=4, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='created_at', full_name='spaceone.api.inventory.v1.RegionInfo.created_at', index=4,
number=5, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='updated_at', full_name='spaceone.api.inventory.v1.RegionInfo.updated_at', index=5,
number=6, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='region_code', full_name='spaceone.api.inventory.v1.RegionInfo.region_code', index=6,
number=8, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='provider', full_name='spaceone.api.inventory.v1.RegionInfo.provider', index=7,
number=9, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='collection_info', full_name='spaceone.api.inventory.v1.RegionInfo.collection_info', index=8,
number=10, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=720,
serialized_end=952,
)
_REGIONSINFO = _descriptor.Descriptor(
name='RegionsInfo',
full_name='spaceone.api.inventory.v1.RegionsInfo',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='results', full_name='spaceone.api.inventory.v1.RegionsInfo.results', index=0,
number=1, type=11, cpp_type=10, label=3,
has_default_value=False, default_value=[],
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='total_count', full_name='spaceone.api.inventory.v1.RegionsInfo.total_count', index=1,
number=2, type=5, cpp_type=1, label=1,
has_default_value=False, default_value=0,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=954,
serialized_end=1044,
)
_REGIONSTATQUERY = _descriptor.Descriptor(
name='RegionStatQuery',
full_name='spaceone.api.inventory.v1.RegionStatQuery',
filename=None,
file=DESCRIPTOR,
containing_type=None,
create_key=_descriptor._internal_create_key,
fields=[
_descriptor.FieldDescriptor(
name='query', full_name='spaceone.api.inventory.v1.RegionStatQuery.query', index=0,
number=1, type=11, cpp_type=10, label=1,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
_descriptor.FieldDescriptor(
name='domain_id', full_name='spaceone.api.inventory.v1.RegionStatQuery.domain_id', index=1,
number=2, type=9, cpp_type=9, label=1,
has_default_value=False, default_value=b"".decode('utf-8'),
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key),
],
extensions=[
],
nested_types=[],
enum_types=[
],
serialized_options=None,
is_extendable=False,
syntax='proto3',
extension_ranges=[],
oneofs=[
],
serialized_start=1046,
serialized_end=1136,
)
_CREATEREGIONREQUEST.fields_by_name['tags'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_UPDATEREGIONREQUEST.fields_by_name['tags'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_REGIONQUERY.fields_by_name['query'].message_type = spaceone_dot_api_dot_core_dot_v1_dot_query__pb2._QUERY
_REGIONINFO.fields_by_name['tags'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_REGIONINFO.fields_by_name['collection_info'].message_type = google_dot_protobuf_dot_struct__pb2._STRUCT
_REGIONSINFO.fields_by_name['results'].message_type = _REGIONINFO
_REGIONSTATQUERY.fields_by_name['query'].message_type = spaceone_dot_api_dot_core_dot_v1_dot_query__pb2._STATISTICSQUERY
DESCRIPTOR.message_types_by_name['CreateRegionRequest'] = _CREATEREGIONREQUEST
DESCRIPTOR.message_types_by_name['UpdateRegionRequest'] = _UPDATEREGIONREQUEST
DESCRIPTOR.message_types_by_name['RegionRequest'] = _REGIONREQUEST
DESCRIPTOR.message_types_by_name['GetRegionRequest'] = _GETREGIONREQUEST
DESCRIPTOR.message_types_by_name['RegionQuery'] = _REGIONQUERY
DESCRIPTOR.message_types_by_name['RegionInfo'] = _REGIONINFO
DESCRIPTOR.message_types_by_name['RegionsInfo'] = _REGIONSINFO
DESCRIPTOR.message_types_by_name['RegionStatQuery'] = _REGIONSTATQUERY
_sym_db.RegisterFileDescriptor(DESCRIPTOR)
CreateRegionRequest = _reflection.GeneratedProtocolMessageType('CreateRegionRequest', (_message.Message,), {
'DESCRIPTOR' : _CREATEREGIONREQUEST,
'__module__' : 'spaceone.api.inventory.v1.region_pb2'
# @@protoc_insertion_point(class_scope:spaceone.api.inventory.v1.CreateRegionRequest)
})
_sym_db.RegisterMessage(CreateRegionRequest)
UpdateRegionRequest = _reflection.GeneratedProtocolMessageType('UpdateRegionRequest', (_message.Message,), {
'DESCRIPTOR' : _UPDATEREGIONREQUEST,
'__module__' : 'spaceone.api.inventory.v1.region_pb2'
# @@protoc_insertion_point(class_scope:spaceone.api.inventory.v1.UpdateRegionRequest)
})
_sym_db.RegisterMessage(UpdateRegionRequest)
RegionRequest = _reflection.GeneratedProtocolMessageType('RegionRequest', (_message.Message,), {
'DESCRIPTOR' : _REGIONREQUEST,
'__module__' : 'spaceone.api.inventory.v1.region_pb2'
# @@protoc_insertion_point(class_scope:spaceone.api.inventory.v1.RegionRequest)
})
_sym_db.RegisterMessage(RegionRequest)
GetRegionRequest = _reflection.GeneratedProtocolMessageType('GetRegionRequest', (_message.Message,), {
'DESCRIPTOR' : _GETREGIONREQUEST,
'__module__' : 'spaceone.api.inventory.v1.region_pb2'
# @@protoc_insertion_point(class_scope:spaceone.api.inventory.v1.GetRegionRequest)
})
_sym_db.RegisterMessage(GetRegionRequest)
RegionQuery = _reflection.GeneratedProtocolMessageType('RegionQuery', (_message.Message,), {
'DESCRIPTOR' : _REGIONQUERY,
'__module__' : 'spaceone.api.inventory.v1.region_pb2'
# @@protoc_insertion_point(class_scope:spaceone.api.inventory.v1.RegionQuery)
})
_sym_db.RegisterMessage(RegionQuery)
RegionInfo = _reflection.GeneratedProtocolMessageType('RegionInfo', (_message.Message,), {
'DESCRIPTOR' : _REGIONINFO,
'__module__' : 'spaceone.api.inventory.v1.region_pb2'
# @@protoc_insertion_point(class_scope:spaceone.api.inventory.v1.RegionInfo)
})
_sym_db.RegisterMessage(RegionInfo)
RegionsInfo = _reflection.GeneratedProtocolMessageType('RegionsInfo', (_message.Message,), {
'DESCRIPTOR' : _REGIONSINFO,
'__module__' : 'spaceone.api.inventory.v1.region_pb2'
# @@protoc_insertion_point(class_scope:spaceone.api.inventory.v1.RegionsInfo)
})
_sym_db.RegisterMessage(RegionsInfo)
RegionStatQuery = _reflection.GeneratedProtocolMessageType('RegionStatQuery', (_message.Message,), {
'DESCRIPTOR' : _REGIONSTATQUERY,
'__module__' : 'spaceone.api.inventory.v1.region_pb2'
# @@protoc_insertion_point(class_scope:spaceone.api.inventory.v1.RegionStatQuery)
})
_sym_db.RegisterMessage(RegionStatQuery)
_REGION = _descriptor.ServiceDescriptor(
name='Region',
full_name='spaceone.api.inventory.v1.Region',
file=DESCRIPTOR,
index=0,
serialized_options=None,
create_key=_descriptor._internal_create_key,
serialized_start=1139,
serialized_end=1932,
methods=[
_descriptor.MethodDescriptor(
name='create',
full_name='spaceone.api.inventory.v1.Region.create',
index=0,
containing_service=None,
input_type=_CREATEREGIONREQUEST,
output_type=_REGIONINFO,
serialized_options=b'\202\323\344\223\002\027\"\025/inventory/v1/regions',
create_key=_descriptor._internal_create_key,
),
_descriptor.MethodDescriptor(
name='update',
full_name='spaceone.api.inventory.v1.Region.update',
index=1,
containing_service=None,
input_type=_UPDATEREGIONREQUEST,
output_type=_REGIONINFO,
serialized_options=b'\202\323\344\223\002\"\032 /inventory/v1/region/{region_id}',
create_key=_descriptor._internal_create_key,
),
_descriptor.MethodDescriptor(
name='delete',
full_name='spaceone.api.inventory.v1.Region.delete',
index=2,
containing_service=None,
input_type=_REGIONREQUEST,
output_type=google_dot_protobuf_dot_empty__pb2._EMPTY,
serialized_options=b'\202\323\344\223\002\"* /inventory/v1/region/{region_id}',
create_key=_descriptor._internal_create_key,
),
_descriptor.MethodDescriptor(
name='get',
full_name='spaceone.api.inventory.v1.Region.get',
index=3,
containing_service=None,
input_type=_GETREGIONREQUEST,
output_type=_REGIONINFO,
serialized_options=b'\202\323\344\223\002\"\022 /inventory/v1/region/{region_id}',
create_key=_descriptor._internal_create_key,
),
_descriptor.MethodDescriptor(
name='list',
full_name='spaceone.api.inventory.v1.Region.list',
index=4,
containing_service=None,
input_type=_REGIONQUERY,
output_type=_REGIONSINFO,
serialized_options=b'\202\323\344\223\0027\022\025/inventory/v1/regionsZ\036\"\034/inventory/v1/regions/search',
create_key=_descriptor._internal_create_key,
),
_descriptor.MethodDescriptor(
name='stat',
full_name='spaceone.api.inventory.v1.Region.stat',
index=5,
containing_service=None,
input_type=_REGIONSTATQUERY,
output_type=google_dot_protobuf_dot_struct__pb2._STRUCT,
serialized_options=b'\202\323\344\223\002\034\"\032/inventory/v1/regions/stat',
create_key=_descriptor._internal_create_key,
),
])
_sym_db.RegisterServiceDescriptor(_REGION)
DESCRIPTOR.services_by_name['Region'] = _REGION
# @@protoc_insertion_point(module_scope)
| 47.104235 | 2,978 | 0.761082 | 3,789 | 28,922 | 5.503299 | 0.06598 | 0.041051 | 0.053712 | 0.083349 | 0.795463 | 0.74554 | 0.722137 | 0.664828 | 0.639267 | 0.630731 | 0 | 0.042231 | 0.11085 | 28,922 | 613 | 2,979 | 47.181077 | 0.768627 | 0.029908 | 0 | 0.670819 | 1 | 0.008897 | 0.245587 | 0.207746 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.014235 | 0 | 0.014235 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
dae405d44f49c158cd9f30d80136d860d3e537ac | 804 | py | Python | model/provider/modelproviderteam.py | ChatNoir76/Championnat | f5cd7422b812a04ea8bbe1156c3e7021b4d730bf | [
"MIT"
] | 1 | 2020-05-27T20:34:59.000Z | 2020-05-27T20:34:59.000Z | model/provider/modelproviderteam.py | ChatNoir76/Championnat | f5cd7422b812a04ea8bbe1156c3e7021b4d730bf | [
"MIT"
] | null | null | null | model/provider/modelproviderteam.py | ChatNoir76/Championnat | f5cd7422b812a04ea8bbe1156c3e7021b4d730bf | [
"MIT"
] | null | null | null | from model.team import Team
class ModelProviderTeam(object):
@staticmethod
def get_new(id_competition, name, comment=None):
obj = Team(id_competition, name, comment)
return obj
@staticmethod
def get_paris_team(id_competition):
obj = Team(id_competition, "Paris St Germain", "equipe test 1")
return obj
@staticmethod
def get_lyon_team(id_competition):
obj = Team(id_competition, "Olympique Lyonnais", "equipe test 2")
return obj
@staticmethod
def get_marseille_team(id_competition):
obj = Team(id_competition, "Olympique de Marseille", "equipe test 3")
return obj
@staticmethod
def get_lille_team(id_competition):
obj = Team(id_competition, "Lille", "equipe test 4")
return obj
| 26.8 | 77 | 0.669154 | 98 | 804 | 5.295918 | 0.336735 | 0.250482 | 0.294798 | 0.192678 | 0.527938 | 0.319846 | 0.319846 | 0.177264 | 0 | 0 | 0 | 0.006601 | 0.246269 | 804 | 29 | 78 | 27.724138 | 0.849835 | 0 | 0 | 0.454545 | 0 | 0 | 0.140547 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.227273 | false | 0 | 0.045455 | 0 | 0.545455 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 5 |
daf4d582810156103d6977bf8bd30ff313e9d499 | 195,971 | py | Python | run.py | chaitanyarahalkar/WebTTY | cb7c511969f69217436c17a214da319d6c49f870 | [
"MIT"
] | 3 | 2019-10-15T06:52:24.000Z | 2021-02-18T21:38:56.000Z | run.py | chaitanyarahalkar/WebTTY | cb7c511969f69217436c17a214da319d6c49f870 | [
"MIT"
] | null | null | null | run.py | chaitanyarahalkar/WebTTY | cb7c511969f69217436c17a214da319d6c49f870 | [
"MIT"
] | 3 | 2020-11-03T17:18:17.000Z | 2021-06-12T12:31:20.000Z | import argparse
import single
import unique
import pyqrcode
from socket import socket,AF_INET,SOCK_DGRAM
from os import system
from os.path import isfile
rc_conf = '''
###[ Current settings for pagekite.py v1.0.0.190225. ]#########
#
## NOTE: This file may be rewritten/reordered by pagekite.py.
#
##[ Default kite and account details ]##
kitename = test181999.pagekite.me
kitesecret = kz8e3cb97d78d3fkxb9de2846z29c6z3
##[ Front-end settings: use pagekite.net defaults ]##
defaults
##[ Back-ends and local services ]##
service_on = http:tty.test181999.pagekite.me: localhost:80 : @kitesecret
service_on = http:tty.webhop.me: localhost:80 : @kitesecret
service_on = https:tty.test181999.pagekite.me: localhost:443 : @kitesecret
service_on = https:tty.webhop.me: localhost:443 : @kitesecret
##[ Miscellaneous settings ]##
###[ End of pagekite.py configuration ]#########
END
'''
pg_kite = '''
#!/usr/bin/python
# vim: set fileencoding=utf-8 :
# WARNING: This file is a combination of multiple Python files.
# The source code lives here: http://pagekite.org/
#
# This file is part of pagekite.py (version 1.0.0.190225)
# Copyright 2010-2019, the Beanstalks Project ehf. and Bjarni Runar Einarsson
#
# This program is free software: you can redistribute it and/or modify it under
# the terms of the GNU Affero General Public License as published by the Free
# Software Foundation, either version 3 of the License, or (at your option) any
# later version.
#
# This program is distributed in the hope that it will be useful, but WITHOUT
# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
# FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more
# details.
#
##[ Combined with Breeder: http://pagekite.net/wiki/Floss/PyBreeder/ ]#########
import base64, imp, os, sys, StringIO, zlib
__FILES = {}
__os_path_exists = os.path.exists
__os_path_getsize = os.path.getsize
__builtin_open = open
def __comb_open(filename, *args, **kwargs):
if filename in __FILES:
return StringIO.StringIO(__FILES[filename])
else:
return __builtin_open(filename, *args, **kwargs)
def __comb_exists(filename, *args, **kwargs):
if filename in __FILES:
return True
else:
return __os_path_exists(filename, *args, **kwargs)
def __comb_getsize(filename, *args, **kwargs):
if filename in __FILES:
return len(__FILES[filename])
else:
return __os_path_getsize(filename, *args, **kwargs)
if 'b64decode' in dir(base64):
__b64d = base64.b64decode
else:
__b64d = base64.decodestring
open = __comb_open
os.path.exists = __comb_exists
os.path.getsize = __comb_getsize
sys.path[0:0] = ['.SELF/']
###############################################################################
__FILES[".SELF/sockschain/__init__.py"] = zlib.decompress(__b64d("""\
eNrtffF32ziO8O/+KzjO65M84yhxms5NfZPZdROn8Zs0ztnOdHvZPD/FlhNNFMkryUm9e/u/HwCSEil
RstN2bu++93V3YlsiQQAEQQAEyZ3v9lZJvHfrh3vLdXofhY1mszmOZg+Jf7lmu+ySHrLx8PjXMXuM5q
vAcxq/eXHiw9MDZ3+/0TiOluvYv7tP2cF+p7MLf96wd7+7ceizkcP6fujGSRKFDusFAaOCCYu9xIufv
Lmj1d7/kZ244e6Z6z9WlG6MvLmfpLF/u0oRAzecs1XiMT9kSbSKZx49ucU212wRxY9Jmz376T2LYvqM
VilS4S/8mYsA2g039tjSix/9NPXmbBlHT/4cvqT3bgp/PAASBNGzH96xWRTOfayUMKz06KXdRsdhOkY
JixYSlVk0h2KrJAUCUhdQRHjubfSEryTVYZT6M68N7/ykwRgLABjCUFsL5wVUoMVZAFzyYqdxUEYBml
JYIFEA2uYrQKsGC0QAEXkpFkwQN49mq0cvTIm3CAwq7QHrI3gZs0c39WLfDZKczdQ3VFMhwGm8dtiF5
1MlfBm6jx5iA8LBUDgA3fwFcRxxBlw5iChOoK01u/VQNuZEVMS8cA4vPJQEaP4xSj3GOQICNge8QL7Y
Al5wBiTRIn3GbpZSkyy9GYoNQlvGPspTjDITculJEkK8MTkbjGG0nE4+9kZ9Bt8vR8PfBif9E/buEzv
pXbCz3uADa/bG8K7Jehcn8N8n1v/L5ag/HrPhiA0+XJ4P+icNqD/qXUwG/XGbDS6Oz69OBhfv2+zd1Y
RdDCfsfPBhMAGok2GbTc76shrLq7HhaeNDf3R8Bj977wbng8knau90MLnAtk6hsR677I0mg+Or896IX
V6NLofjPkPETwbj43PAtH/iQOvQYqP/W/9iwsZnvfPznA4AgfQeDy8mowGgNhyN2bs+INd7d97nLQB1
J4NR/3iCZIhvDSAIeAJ4nbfZ+LJ/PMAv/b/0gYje6FMb4QLMcf8/rqAQvIQWP/TeA012mRUNlRXA7eO
rUf8D4jo8ZeOrd+PJYHI16bP3w+EJMXjcH/02OO6P/52dD5Hlp+xq3G9DC5NeA14DBOAQvIXv767GA+
LV4GLSH42uLieD4UWLnQ0/AjcAxR7UPCGmDi+IUuiJ4egTch5ZQDwnYoAxEwV3dtF/fz5437847uPbI
VQbfRyM+y3g/WCMBQYc3sceALuaNABJ7GRojtFXRcaAb9AzbHDKeie/DRAfURj6cjwQ/U6sOD4jNl68
74OcNiYo5Vyhy+EIY5wlKQxZN57DAJg9eOlu4D+gdoWBu3BnOPhjMSU08Gu6CkMvEMox9GZcU6T3cbS
6uxeTBgD/7HsJtAkzi/gz8gAajFNUtBFzUaFQuTWb3YOiRIBSs7uI1Sx6fIQHgE0Ig95LQXkTZo00ig
J2uzbNN8y+T9Nld2/vNvach8B98B2oudciGhAy6Z5L98771U+9hiy9hAcP8IAXBqw/+Kht1EkDtQtod
mj2+D4GvRUtUVG994NbL06zZkHDRI9ukq5hxgT891oN2TAoy8v1eQRVs8LLdYC/HT5zQME7gUB9+x9c
0ETsNz9wE5VcoDW8w9nHeY7i+RKmz0Sg8AjcDdbIdNDadwBjdccW/mfo+kW0Ao4DauMcBdFb/uMyAsJ
u3cT78bDNvDgOozaLYGrlQgKfa/zhBSAB8JnGK/wEMfDcOWDSOOm/u3rPjtgp6H6vsTP3QJXjI3sRRa
0uqtMwBQQiEMudnWs2Hp9jjy+B2Fs/8NM1n0lvdl78r9FI43UXVLYg4d5N7gP/Fh4gDsm927n3PttzN
3VbWIqx+wDQFKUcfG+3xHNntYRyHi9Mz2BSX8UhvgIgc//OS1K75YAoezHU8j7PvGXKBtRwP46jWMED
IFfjIODCGxCBZ/7G2ESjgRCAW9Pje2/2cAGToY0jJQrxa5vxCm325Ab+fEpzpWhi6fowRx6xa6289Sr
Ze5VY7BUzgGm1bqgqAYOqYPjhT3/B8rIOaI84TXBg2db3jiVaw395Iaib/7judG8yemRZHCc05YM0Kr
jnwPBfyEGF1OwSpMS29qzW9X4ZnEDTthzrByzecsAU4EjmiLR06BmTHHe5hOK2HRZZFGrMaXF2IOoq7
2b4cUJlkBoCmbeEWCk4FOhtoaliFyCo7ws485754Yh1sq6hUdYVgw265Pvv2THqqGQGurfLXoHWgP/+
dATfWlaJAfSvhbQS6DZHX5cnbSjQCxDLs95v/SmOYjnk6cHlp+Fl/0J9PDkfT4970+P+aDKGh8090Ox
7SRLszQDJZG/m7uIXrvdgBpnFaVMOaCLP2t0NwYSNoIeglkVewBq6LL57Qt7R6+KLnGex64MyVgaobS
3XQ4CFKII96t4G3tySHYuWoXwpRjF8pXcKuSVCJ/HK4xCyscpnSnuWfuYKtG1kPHk88TSBefmIuNVm7
gxVijeXv8Wcmz0wwgEg/mLNe+voIgpVSS9KCAkIdArzFRMdppmMLVZLrauC1kURaX2a3dqIYZt9frP/
Nps25kDCfZvFM8OIA5hUin0H+qUrpYrLiqEsgdLLEruLRcU7W9eUiJVz56XTZHX7O3ZIy1E0mVAiZp6
W/xEwoaAt1OlWywGPKwCbyba6VtuytgalcrXFfmH7uiYDsXESwJoXQ5ocsEUHp5+ml32wSf+rrhWl8G
lvcD4dnE4vhlSPxmAb+yxvzQO2f0m3ZvzmfXl0tD0JF8OLvsAiqxHiGIGRhMWOMyszHz6aSMoh0uXVq
Bn+bApzE0zfWulsAKnFxUNTeU3gRZV5NL0H0xT6/AFLNwpCR4UaFdYA+KVSm6karVplVagtk8IigMLa
SILskaKrctVEnQI2ZIJMtiMaDoXhCVrhqTP90J+cDU+gLoB0wFOaDI+H51N6p5X+6IbpCIw/wk8UB9D
0UxcFapWT0SceQd+iSQiPDQXH6+QYvIWtyyMeH8FN97au8Z9eHI2o67auAkKZep9TM9/ksJlOwa1Jp1
MbrORFG4NH99HcUJar/mDh8BLAO/6luiBYz08gqQ/eerrwA7SJUMtXl8cplbysLYu7U5qNNxf00Q3aX
C5ach8GTUgTp8BDmhZoEkxbhHUMK/NhEVY2oNgV05wZW7VT4l9FM6RLiCdTjKYJ2IJLtQ1kjBTfjOCD
yJ0LDToNIuEYikaW3iPiBq254ETdF6f9uj4WVSspEr0nGhK/YGywHXY6+MuHfpeHz+YRuJRhBN/B/dt
CFMS3hqoLwQ1z0zS2QXmA4Z1pG9AjTwevrQI9ODvwNxVKir/MG9Bcp0vPi8koWICVqzpK2UhHqxm6eo
4WwxJK44OCj4GP0HXEloVXVyjPg7JTDMoeofZtlZwUYBnBySbR0ljK/S/1KfodC98LyINHANeWMGusG
6OdRYXBW1IcJpypLW4CIQsss8BkXoZuTWXwOhm8dsYRydNGkVyJZC9IEYolsS83XU2grHtjxlehVSN0
HiYVFCreJa/ZMfuUW3NFYcmWNmBJpjIOmuxa3jhZimXx3s7b+JYexyav4yWeRwh67cmTq1BoGBVZ8Dd
UH7baHoUOceyjTTsd9f/jajDqn6BDmD1EO1MHpBlimdDNhRZ5jt3llAe7bGIig2kG9eQR2rKFmedFnY
wdnAHSp5YXw5kiN47wz8uqCu3PURA/XgRBtYGnUShN6E1CYpLBJMBJDRdTCB1u/LyMHD5pcmr495eho
AwD5bsuLtye//8S8/+ExFT2eFFlVQc8eN8XnUHDXIQTvNns0Px+88zEXT80dbhzYlsUzUOYMCvyaF5V
HM8c11PabJMybRmnmMWc86LKjd3CgdxhH9CPTyMWeCmLVjGq3D0BEOqCVZ6wWw9XgpCehesHzv+0q5i
5rP8i35IH9E+4Jw+cPI4eafEG4x2CnTvs4/36T6IMX3jLyqAQyBAlrn/HHq33P3qPUbwGt8e989j3QZ
Qm3zsNAWywwHX02MN518Wx9PfAv40WC7ky6D5BPyA24FTE3oLW493UEbXHnsdw1Snp7u3d+en96paWm
e6xM8M9QOM/AdoQoKH19hzFDxzhuecYgh9ZrEKg0FBGuHjkiCAHglWGFxfShkkvc7ZybIdI6bOPdswC
JCNbpgSR1PMa7t3ZQ0YirYZJ3jMmFtl+h8ehGzhLdxU4f1t58MOJ4rs9F9zKWeAle5gKs7d/uLf/Zk+
Ep3d5P+wCb/YqyZ+l66WXFJ/eBdFt9kyAQ/eQCjvHJ+fnNtpYbflkNDk/mb4/H77rnedcKlk4C/K7CJ
hDKmn44XJ6RxGwTKSmXJ3mGIkB20t5qoVXUAKiv6B/cB4E3L25jdg7+MduUq4RvMT/sNkkcr5vtnDVR
oNgJpHDNRNZ5M5Gghz4jXDyNmbTp8ifT5clUMnD9O8wcjEURyVx3axQ56aqkr0tPrZQvIK/mWqoCdbP
TXqiy05hxPIwIGmTDzAVvQNa+wsYhCkV5uGqZ899kHZ94N25s3Vm9YdRuH6MVslW07G0txQrX5mT2/Q
jd/Rx8lJjiW3hyCr+PhQBf19z5q0WGfWEMxryHF9lhlFaFI1o9RvmNoaXGP+mkqIFnHqwke0hq+Ukmf
/FCyrgTXGNIg6vFRw4gaVxVd3C64xECiHwPtGEJ+vV4rw8CBNvtoq9POUCSkoQbJcHdOD/v2Ma2cx9j
BYBzCQNgwwAgyz34ur83KpZRFDKng3en3V3qUZ31+Mfl+Nfu6Pjw93xWY8+P5y8sThtYN3lywAkwkrf
tBrqykIWpcpZphdQA3MyJKeuZEI5mYwgcyH9FGNWX5KFkCUjXI6Gf/k0nXy67E9P+qe9q/MJELTbUZ+
jZ0rRHeUZ5dEcMlzYLT59A08P1Kdnk8klPHutlaRw/2Hh0fRjv/crPH9TfN4DHOD5j+rzyXAEj/6t2B
Ku2v5UfAh67uKif4y0vS1VUF529iVHsFUsguBsHRtK6SpibdRIBiq0ytT8ppoaji2BHhFlwg9flNtQq
x1X1pONtDc2zzvazCB6pYGAnpIVhYxhpX80CoSinHXZfrv4XNQxvULkuuyn/Z/MryTaFUW4EHeh16te
vql4CRR12dv9N/Dmn4o8SbIs0Fae1S0Sh2AsmADBQEv1t4JEtUBSXQINPv0t9bp8NSu/y3oWy6DvX4A
uOi17e2h4fai8duvfv6mEnkax/g44iTxswGwg1wG7CrelvMhUp380qkZIlx0evm43Ng2g6mLYct1LGu
b1JXCAKyX+2SrIjYEM6rGk3GOKWuCdaiqjdqsoi/HIbgEv/fUuzqWlMlw56QXR6igXzLUd0NfgWohPD
9Oz4XjC54TpJaaX0kQwHZ1cjLn+n16N+yOu96eXvTE+BdHsyWQbUPtZ4s2PjYbo++loiMmyMDd/bzWm
lJIJTlJKRu8/2D8bU3ByeFSL7Hv84vAPejWLPeA4BnPgNVi6fP1GJAla/O00TxW12rS+0ZJJPVOeMkj
rWQE2maUQOvSIfD5aTVUL2nnKgQ4gW3Yveys77BIMngPnsA3mHlhkTx66geBuBR7mr1N8InoOnSJS07
k/Q9L/8c9GFmiAYQb2UBb1kN6/CU/u99H6TQKcyckD+yuGdif0QPoCwpjD8n5owKNreHYNpW/QTBJYa
VZNRXGwdDgpl9jfFbEJXuK9F3qxGygF8696SbKb3vRW6f025bYoc1hfBsdoVYkGeF2Et4dPacGgmaxm
M3CZmnx0Nf2Qr6JgtqV8Rpa0XPFQH2ZREfnw1p2L/GX0C9WnfrhcpU0Yu1OurIsYePMctEBS5E3zSCQ
FwsA4l2XywUOyQanTfKkkXgUemLay4IWXYsSFrULo8tm9iu1ZBIa84XmeXQMCs8CtE/LNZHIOnunSj/
NHxzwlm7BIVssl+fryZW8+R3+UuGEucRU+hDDAGPFD4Y+7wihNNY/ofZiKTGh0S2LvbysVMQztRIuFh
8nlhdLC14YhD4M/9n7XOnYlMAK6Y77hBLe1cKlAKcJU6mLZAvaHCuaIFuZs3sVuqLQiH8vWsZUFeeyV
JW69GQbUdLGYuaEinqS85kApwOM7cWaBDz83wsyLovwCro/kBQpYsUfhp7lP7IQyyJtdf55U8oFCDks
3TjwaDrYb32WBS9pxkPhBsGaLVcjl7Bl+snnEXAadOHvYxST/uR+naw4Et/agKgYwtK9IQPJD3DUgRp
zcmMO72I1jd+2wAbrQacKWXgQqnUWPPshgulosnCx39DtabQbI0j2lOQFDnN8hO7vtjElQF4dSwncMD
C6ffmQuF3Dc1sArAxzsd/iQ2cjfiaVK1QMWTKBg6y2AfcSgDQZVI7HUKpKH2dXonCXrMHU/N3IHHmBn
mcuY7Jz71fCKN37d3e3clFHKUxH39mDStbpqeuJeVz4SmHcF5gjgeh9nE8WqupZPMcGWjOObLPRgB16
IXZ60kLX26zaD+fVNSwRvrD9LjifXBzcK9jts5O3C6AJGiPAqylkXB92f70FXdVEK99jRL/x19qibFc
vjvc/zNsMCnHBsSFL1Z2XpGCvKEp0blY3wu/saSb5GKDdqACUn7ghsrS6VlunhugEteXTTqqz/Wq9Pg
baWhojjfU7x1TUi20bKbqRAlVl90GbIbROrOyqrOSyVQR0jg8Qr3AwBZf+VXBCvEPFWJmhfjIRW9xdZ
FaQEKAWtYkvhzFqiB9zuvqGNO3rAQnKWJx6A3hfl0TjnQyQfVu2Mv1ohvochyWPgz/eYV5aj+TMZ7mi
qd42ssTVucBeAywHmGCES3MjW2iZ42DjVzpKNOyIESRh1ukQC/WiodiTC4Koe9CBX9HPaaULfcdI/4u
sRqCbFVxyw4ms8DxPKfzJGY+T8K+uJqVf8xKXmUlYJLi6A3aT6Kxxd/Ao0qi8wIYuwzdOUcvbwGQWYk
hHCaeDoc8zbGYY5cgpemZzxxkHVI3hl10EVTpoH1mbXN63r7k1OhuxtqsYbUUFcqyRhv9Jj4z4Qa8Q9
OpdvAaHNLCqoNsPdLCLhT+3d77Hf4eP7h2cSt3rmYx3AQ8VLHVSSIyUiSPnKsSAFThezIiKleZY2B/A
NMyr8rpIeFdSwL6NehIdkyoWN2ZQ62eoWloZIlFb3tGCNIjhOipmbzWazWLAgi9dcGK+5NF7n4nidy+
O1IpA3+I+zaIwmkcsEdCHtoG5m9+hIgFUW05ZrsmW5k8+d2oTbaSu5FrQKA7TuwSMI/JmfBrRtM7zDD
fqCBrWnSaNoevToyBRyLGzM+c0NVmJtvXnsx7NV4MaMDDQvnJG7rtHhNDVXNxPdwrAqiY5UY1v0zb+S
nmwEbEUPJlOsk9R7lPFNGXsQC8qR0OdhNJUq79qiqABO92gOZj945GUe4c5RfNE5+DdnH/7XsW40ENJ
cicBwCZ/8OApJq1m4wQR5Y22VkvN1tQv/YO5VJ99WtkOP7B8/zHBXVvuk2GCRdjGmrGzye3Lp0APb6p
2fSxSZxQOF2U80V3kLqrEOLiWuvOuUArx8Qiq/E5OUvhvFDQoLhEUNozhiULiQ2pM3cg0NoNa1LEPuj
1BeoA7y4F7F+ChEuxwl3ietTWHkKLkI8RNOhlrs0Dbq92woxE+8F/wQlFYGBzS6XYNAS8a4cuVma/FL
Rf/mJa4X7qMfrEGdov69JgMnjVCfst1fmKYjqTZm34CC5Z66F9KGHBkmBdfPQ68WdHKK6594uAS63wn
GGlw+Z6YgduT00gt9Kz7DDSTg2YaMu0oohbwhUB3on/Ihso5W/MAP7heDr00kHPVOp4OL/oRTcoQVp+
PJqN/7QOqM6Draz/V3o2LjioAmaNKBiocK7LYErC7VY+b/dMoBYY41fSm+FrkZ+FF8RSBxasXP4kuxW
SyPU9scflsF3NZAtQwNkErUcu/VdwhZZIhXlsGk/5oyj+6DhybFFGYAfS+MKHC7wqCLPirFq9C7i1Lf
TTFX6aiwPVIUiZ68OPbnHil2OXegSpIKrl6hWneimKQUq8pnkrINIGYByDLWEzEqCSKrzSzJhA2QYm/
2ZN2wHUI/nFviE0a/jD1wQRULDhTpzwQ21Dd3Y0y9uFN9mo/46VTfWCJUDh/iTl0TSsaDaIO28Ond8d
WgExMIudBSD6qpkYmfzbr9CLxlhbsJB6qhRnvBV9+Qv3WNbGJD8kexIUNA4QbKJAig3NUVrUI14RU0a
F6Ev8QJAxcXsjIjb+bh3ob+X3rHk/NP/Dyj1eMtDHqYAG7X6KKJuG1+MpEnZ5MMzLsAyQGTPPUDKiDj
4SVgtMp163kY3aemKficI5T6jx6edBTNZqs4cVRiTFoW82husXFQQ3anJs+wUEc0Yx8ou4JN6fQ7ctf
HgXNQOA4EEzQTPTs4T/SkPgJG4xobtozdIPoge5+HWOh0DfYz78HCbucyhN2sSmnn1px2FRm2FHHrv7
xwZu+3teUc0pdz6EhwqyhIH6ybhWYEWfTxA5sX9xqTeGUySvBIPvXhaZyAfmad6k7jkOo2hhth7mYnU
SA68p3cABvNvSMrBl0OE13i/9072u2UjQQdIB1tUSlmUgvw8UH7IbgmUFrMWmtz9vBdeMXk1glMcYa8
1pcJ5IvQUVRL5uiJrZwvjKh9Sfgsjzt864BDFnRAxSQWSCN5LlvOr6xBtkshFChMv4QhXKrIcJ2clyl
vjkW7OltuNGTOMNsPZ8EKl92ZSLAxTADlRDs0kws5IXk4FtjEcZf4iwWizJbnq3b24BJ1LgZoFerRI9
cqcx9dremwE+HJIx8wTSq3/xvm/Sw8TvGTLEqJgWLFjL/PMcB+zTEY30erYI5IMsxs92lfBqX/R/Gjl
60wxh6doYc7ZUoY2LErDu9zeWHyyKhsiztCMtbhJxSldkogLgB4ly+X3bu4l5h5YBDPUr4IJ7qyREm2
eEvUXMlfuL6WLwWLo79E3r9gcAmBApZhVFhNdrRNBjgIeKOX8teXNDrE07liL/Ce3BBIhco5SbhqGCR
Rtj/SPEN/sxC2koGi+jXdopd0fWP0fwrx6oayiVzVb+ZIwh+rkVBAE8/LVG2rztSpIjPT0+UIXG4lSk
/N48kNgmaMNfMuwW+8WzgiBQvypdWz2hdZRTo8L7Mx5JYXEaJ4U5JDlQE77NSPE8yHtwIYu544/7OQU
7GEqc+98zCpQqpdRzvgilC75uloN9/xeYevUso3mJ0m3xSnXByFsnf3soE2x/NUA5HIga0GPj9KEFAr
AJAyJJI/QOUrmBJBiNhF70N/D/H4OBydFCAUCLZ9isb6nKGRHqrBXNSWU7aNhL9q87PxHGSabb2Df2A
A7X/ef0N/D+jvPv/eqrO3dkA9GthC7PDwsEZv3uYbu0Bng+YpMiVCNSN5oB7dSDqqRtVtJEilp8PpUS
jZYR9JmIQDoqhCi075XQIOIhSe4qmqoceXJxQAohufYU7gBw56uR08w/BZiLhL0z33wg70k3+yktf73
c4NHiI1u49tRB2Ph8M9anbLYOMWTeFaAx/o1xPPcC1eZQZtAuU5OISPOV+pAu9O94BWHgTe+1V4k6xU
p02VvSgtkFHd4EF1g8MHd02JlaHHh+XSi+kkYhcPkfRnZdGtHXI14idw6eS4sB+qnXksjR6cppJaUIV
pT14CgnSXBoI/0SAgOXicVK1UyhUmUbYol50qdnOOvXPn2QBqmA95MYju14hvEV8Sj+82yyPHt6cLJE
+B+xLEi3mmmHVUyiW8fl3EvIRBlmlYq3ZHmDNJe0Tlptng2V2DgezOt1MWhSGlDKjT0zqOVRB7YCL2o
EhsmZKv01sX0TOO7pkbyggVtwxm6Qqs/Hw+UQIUf+MpzxvnCqUVvjeZ3cFEEZKp44cix0/4Vsj+kIFL
JR60uamigJApjoPLp8OsmkTZQ7iYqMEdGXgXBU/YtzS38KxC1couRRz8Jfl9WSI8TFfp1E2j0JYmWum
wEkzMgL8/MJPiEgCL4QgB3TNFJD56MJv6qZXwbGDiBo/7tRmaOvQKNNOtewszvktOHcVni0IptRcmD9
2YBuyI2CPdPmXBpsQN4/FfKu1Sa7/eTmurajdjrMY3M7vNUp9TQj5pHSGlbhUP7nBaTtLbNXJSQamW6
G06XC2vDpbmL2fN3NovrFfJqRCqqaPnvZcKN70wKeCD8kR0qJlHWOZfZxiR4UEobDun7DAld90wl9Sp
Y7A+7Kyx1s9HP9UrX0GCXmur7ARtB8C1DuAlGlvD4227APetrqqlGNzS8d5CBe6hGBnY/bp7qFp4lSY
HAZODpFKOKuG+roIrRJM+flBi753Wts1nXD3svrlpbQxZv1Bq64SWkCJ/KpvoVqEyekuGn3bqQcXqsp
2R2s4b0EaqUFbfHRXSDGuWo21Vr4Vp5NocSMukYipj/SWo5bCEEgopricX1yWazSYUyd7Salk2zYeLS
Fk1w7B6osh0Pv/zTAbsArH0Ja5w4fEoY4wjWzoss7+MvKTWjLxeZDsKEPcCzmrMuxbnPMXBUZbVOW46
7vVovxzjCm4LzBVLLYPwSFazx+yQorpFbgmSlGWC1ra9JUFUR90Ovy7qdvjNo26HG6JuPCrgl7iZMT4
7IK9oAOeMekzjJHgqZYd8lQm7hTk6QHNTsTIFLc/cW8J7D2hp4VZa26p5vZ0hmiOs2kcYSWsq0TP1b8
dgl2XsKZ0Xbp54v94kJAuF45yt0qMTgvh7aY2j1Pzl3bszTtuh9JQyBVs2IfWIaZ5vxvgFSbgCg7kBW
MCf52tIhw1DF/BgiHFqUS1VrXijxvZVzDcFXyksRlfMFKjawVt/+t18KxW5nejehIySUBMlMitGHCV6
zSLVN0TjHzjBC/RIm+GhWehH3SoriLSPBpysmavs9uJGMpeiasZIMajnwEuMeCUNhFTIBqP+p41GfY1
FjRElLWHlj7CazIb+m141WmO+ksqnAtziKXYffqG9T0m8b2FMvT2A/14bIi/bxqAOzZ4B07aGFsx+ts
ve7r/Y9pctvT0sQj98sfFfZXiWbERhVW/j65jMX6p+AH4Amr0twzD6X2/CUj4ZVcFQ273ngiZVkzT0L
Btdh4oU2zw+rOIj1isKIWjW7DaLUeVyzluThtouRgSj2P872QldGLoYZH+V/DX+a9hkr8TNTc7tj4di
VGGTG/Pp9CxgvOZqSgntWfopTn+6SXm7WuRaiGewZu94Rr1iOOUllYTWyjRYY+6rKbNW5lo6OJk8eTb
PGW1tVQxTSovnCoITtlq0y+grokFOqjkTME+4UjAvmU3c1sMZSZ6QCKYaJl7ALIYZ7TAj0UKeSj2dsh
4W9tDtMDdJVpjxICZHnM74MUW3rh/wrStp6j0u+WMmDjVxak9nbuLpzBcZJAywIAa3Lj/QUwPULPjqR
t7l/WkWq5ZpuGZ2OR3RIs61NnRLde4hn2MBpWImIJqB3c3nQev+BwE1ZRcqxjKdF6ecRFoJs7D3Qqmu
HUxquqVKJj7y7IpwvjGzYguZ1EffD/rujbp+4TkRdcrXwETCujqPIltr/r9IFyK+VYoItvLFrmqO4rf
zVsNyzpjZZRW7LSkWQJvRwZw6AHPq4DX896bNOnhPUKcD7ljnEB8dwDc8t4m9fUt/3pSMvPcRGhEuXU
1bUDDks7jhmq6WwFQpN+VrzN7uI+ilojocj8/aLPWCEE8gOkXtRYfKOY6ztYrZgpdlaTAfcB+7YQIuG
R6lofAWU0EBIatW6/EJbxtkTJOcPEugvIGiWhhzeaoVuy+TOCFc+fLhS4XuG5ga+lojnjMi9ALMm1AA
UxhcPyWBQ0fIKR5jgBMJ7s5/3c32ymkQQ2XGBA/SOF2qMAEe+Gev83sqxMHeNu6bwU5bRgltK/TcLfd
DWssVVZx7AX5ESw4mjqwN9zF8xYz/v2RiV3cw5r1yhnsgnj12F3HPCJPaRNySW/TJnwo94ix8GDgWmt
L4n5U5pi30WHYLafPHo/NT3LNFRfWVEAVWuD2c0NqQBrb0NpA8IvuWxBsZtSe4BYMkUnPWN3SbmhUYx
Y9qZF0OYkcbfzi5Wt1XczxeQPM4BZ+BOuQI356L5Or3f97PaX+tKFwSVngtR4m21YjOhmEg3fKMEyh4
/WO3GJYSYPFOGLE/mMHAUCKFeQHshVeJPJjmVSIOTAA48FKatvirc1OuTieoCM4avEcu1+Dl5eVVRo9
ROv30u0btKL1U+6D71/BVAk/R60OmOr9HfmgL8K1Wo274lMvnMlo5Scjh+jWGy1fNINIsePkMQjpaSV
KL9bwASmCbR9yTCqPnYlJ0TaBaDxZXxIZrxrWoL4vW9prdlBxo1k8JPzARi+SBBTx/UI0jN4ltex2nQ
1GDTbA2CfWm+nQIXZc19TBpU6rZDe2rkqkmw3BnWYuY8o1xqPK9VIGP2zCaqIibG2KonaKvSJEwrslz
cIo2P0Jtjo52o+Tp5fVCQ53Ni+FGrIhuOpubCzJeZUB523RZOsj1TF1PMiRn7fCEJ34e4mKVx8gxrW+
VEBiOB1eW+CCxW7nybLKcFjDvteheDgN1qTRomkLW9tWK8mFH4cwfnGlS3qtI6FIAhh8IpeCvKnjhn+
dnevzBiGacJNTAYDjY339Rk/nxmHYOqK12j5Y1WBUWbu7T4R/7uCDV2rTv3a6PpU7lzUFFH0Pe5aser
WNc3k2CTVNHpZms3n5QuO+gej14c3tVUxUewZ7wGxrMk9GzG6ZTnCbo3sf8PkZsbypuH9SinWIWohsR
5DmclUf8T7JoIJhuASaj0IH/j9lVLGpPyub0gLQ4Rkw/yl/iqZQWJwxThXySyPu6ZYSkkZ+BygBdy0d
0ZJpiJJUGML8koP7SC/yj9nr2rbRWlLGjHHfDmwQ23CRK71qVNU2XnBqqYMaw5DN2dM4qM1Lmi0EliM
KlVlvs5y4frlG+VzB/ve05PflNgnzbqnZhYE5i/RZxY5AFhxpmvAbeIx5vtkf/J5sd71MGMFNMbvmCu
xgrGPJVcBRKDVq7UdSwMC/Ga7yQsZi6YOTExxj34M2BCd1XCb8hjPhg0F6Nr+WC7iKIfZNTOlxN0Zmt
Lc7Bk4ZpKz8PSTkLT1F9HAJoB/qCd49ueR5X1jxfDd/qLL6CEcjbxuH4xY07y2hp75dWm/i5fSovo6n
uZGHXYXp6SzntzuryAz/FK8Cnu/lkHP0Qnx+3OiLHEOWW2GV4NUx+TUFTb4nUVji9CKtiHtOd65dSmb
4px7bELj+3oeRRL10/1o2SUhkqkpUQyjnJtifKzQxaOlmelkbzFsbBcBz4apoLbx73tvdYuqKjlBciD
3APE3fUXMBU7lzn+YA5EJuOk/ZxBzggxHloJZJQZbvkJBJ7+pTgktzMjls5sv3AfAMpoS0eVK5MlNWi
4A5ODmxP1YnIxLZmzCpKWRZQLjYoHDem33BgKX2nBnVO8OTqRz/0wRDjp8MLB42cNm3nrE2n/4NoZdj
xdBW8tajNu6OF5pSmW7JtErz8z+CPoY60NTiYg4FeBD3EY/JKUPTiHV4cHKKiS1bp0LwpOTSUkG1YrC
scwZdtYufmVO6R00P9PBQxzShHjQrqaoIrRtj6hKWyqa5BbZpoaPFLLrzQhNJcyXjJdhHymQOqFQ8cl
B6zfqjxC/ZyHZa64VDrBskHBU11qqUHciv/dfGKHZXjyo9O4chnwxAkdsixR43wU2czFlIEo2DkgKbB
wxgKjhCfkA0Mlis/nAYx21alm249d2dcAeNh/6ZagnJBMd4Du4En1ILBdQA3xg9XXiUZeBNMRcqmPGo
EtLPiY1GFLdLP8pqF87U3ifBNCVfet2pKFHl13S3ZlGvvrpAfDUxbomrcjyUESPZZblpVAylv3yxJGh
0UBu7lfYQRO1uIx41+Dnib4knKO95X8G6/2IpRNqsPH9+Ca5PzMd7HiofxrJbZwBM409Crse+1AIioQ
yNefu/cbAi3kNtt1401edlRpVuWu+sb4eDtSi9jqXJV2wuYqq4/fDFP1UWUWt4aCKJ1xRqSNlCElgJX
NHjye7fSB9zhuonnW1AydlKTPPbHsO0LWfdFfm3NCoZZORZXlPAIqsDlZwzz0x1ogsPFJCUD5NG982d
fwjvq4K/m3IulrUYjKTcUvmD8yFv/vlQb8UNxvsGgKagQflPhC+k4/Do6Dr89HXTFYxUV+SSct6v97N
xUy/m2M7OAVbMYWDMj11auH4dfbg6rtiffOrWVL+nNv2P2q6SFRHOSynEdesxP036O3SW/YN3mH/nh0
+VX9KbHc3ZFQjBd3INuJJWwEnlCdODfxm685qf4yGOo1QNDaR2AzvKnE4DogjA8Z4bgJHS3e3YROwc5
B20/wxP+6c4lebwShWmXgMS/Q90kO6tOnI84lqchnQt8MP0pkRBwIxJI/V0Ur/XrAjgWjnYqt1hFF1c
MlkuVrhQUFfLDxOkaX3bhpdDobuA/iLjC7kxOaWkUAXL89neGt/RiD4VU3k7AaGuzqM0ePG85xbu8jy
wrvw1A3uQMBSyeOoaZJ3g2deQoKWn6Re98gSDEUr7DvyordiC3eDr8Nbas3CpOadQJ/Y2gRMQ/6Crym
7byX8ErQmgFrzOcxlB5leIHDIGpyK3HE3P5h42VRDM/UCttxh919vGAjsaONlVCrzJrEGKEebhK8QOG
mrTMy62Vl1hwGsFy5eGMVEvfM+GZ1of7b380qFVCFpkR3TQqDB0Edr2LgQzQkvtbavf+8JRkIGxZZj2
EjJE7CJKyrxAhcUS+gTrnOfZTjyNWDDQUECekO7WGnARTQ56RxOPz4bhvR1UEckyrtj+pG9GpH1F6cR
axfEuGLrKh0601xlRO+vXpI34tPvVTQ+QsglVyX1E3ykdYNrQa2zdAAlsRaPCr5TxR5DxCQXfndqYm2
qxG5kkBJJUyn3ypzPvbyLtfJjKpkfeEp/knG8Q92U7ck63FPdEFM3mxYJpHTFI3YgyqoXYdbeMA22Dv
mNAcn11NToYfL1CBfRxtwhZ6536VzqPnbEsz1p9CRbMNmw2U5EsGSmIaKDLPms7NhwJdITKY70Rnbht
LRlRSKlNermFaMC4lT574SbYKjUZr07BGnAUldZ2jd1iuHxt8yU4EUznwqbAlcJVXHLlK+SLCKcykUN
4OrBoLiWb/lNfGShdutMxBaEPMKlFOMC04vEm2PFVAWmihImeRZ0k6h/ld9ILFU6JwB2JoVXC1YB7n5
xTkppeAi1wSX0G1qBxTL0iiSLHgPx4bPlUi2rayUUgGvIW80m6S+E7eltg1R74LN5pqDVNB3vKJd7u6
u0STyMZsE2pxmf/khT4gQgKZjBTMMk6ssgCIOzyRfPj6hFfyqQJt7e7iFgWrjH4Zuq/vMKMbBOXeRwG
mVYAdRttCr4UtwBShz5FbFcDF7Wo0UrUX9ASXXjJW17XMm9AHhehtjthyjRTgPe5tTjB+LSxxcVPaKC
SmZlFAGuqB1MWbuBramuKUZ5DTV3F8EEFD7ajcyKplp6uFUbqy363Suk7VYDAOZEV+8yG8aQCXRr9tX
SXuHd0tyKyaSce6/pmWyrt8ARDx/4WZnjmOc3NTD+rn7FLYX0DltABlMKTw7j0H9z7z02/kGNI23HPC
gMcd0S+6s8YzTSo0uqn7KvV6qcEDtQ/Yr976NgKfeYCn98aronqlGjhZ+pQBCfRMp2j6NLF/wVacNnl
5rlwajf8GxnApuQ==
"""))
m = sys.modules["sockschain"] = imp.new_module("sockschain")
m.__file__ = "sockschain/__init__.py"
m.open = __comb_open
exec __FILES[".SELF/sockschain/__init__.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/__init__.py"] = zlib.decompress(__b64d("""\
eNqtk0+P2jAQxe/+FE/spZVo2Lanbv9IAcFuJAooCVoh9WKSSeJdY0e2A8q33wnsikOl9rI52LI98/x
748nNzXt+YpnM5qtsjp8YjUZ/RN4oj0ppAs+tdAG24rmmZxUoavtIzGzbO1U3AV9uP99+4uHbGKEhTE
kaH6R+9tg4+0RFADVVBGlKTJ+kMwppZ6TDXPHovTXicl3rbO3kYbixckTwtgon6egOve1QSANHpfLBq
X0XGCwMkhPrcLClqvphozMlOTFQBHIHP0APC9yvtkBcVeQs7smQkxqbbq9VgaUqyHiCZIBhxzdUYt+f
8xaMIbJXDCwsy8ugrBmDFJ87HMl5XuPr202vamMw1gcZBnIH2w5JHxm3F1qGa170t/OrwRLKnDUb27K
fhtXY4UlpjT2h81R1egxwKPCY5A/rbS7i1Q6PcZrGq3z3nWNDY/mYjnRRUodWKxZmO06a0A/Uv+fp7I
Hj42myTPLdAL5I8tU8y8RinSLGJk7zZLZdxik223SzzuYRkBGdFYfC/ruu1fmBHImSglTas+cdP6dnM
l2ikUfiZy1IHZlLouCueqvlf7WF1NbUZ5uccK0j8yUVjA1jeOL2+dGE0N5NJqfTKapNF1lXT/RFwk9+
CW54cfO+f9MLyqgY9g==
"""))
m = sys.modules["pagekite"] = imp.new_module("pagekite")
m.__file__ = "pagekite/__init__.py"
m.open = __comb_open
exec __FILES[".SELF/pagekite/__init__.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/common.py"] = zlib.decompress(__b64d("""\
eNq1WH172roV/9+fQk+y1HAvGCdN+rTZul4DJuEpsZkxSbO24xG2ADdG8iQ5Cb27/ez3SObFQNK7dRs
JNtJ5P5KOftLBwYHRYlRITKVAmMZomrIxTlHG2ZTjOQKKJJZxAHyH/9OP0eu2XG/gorcIlH8ywlki0C
RJCYJ3hrlEbALvKblLwIFsYYGf2YIn05lEJ/axXYfHmxqSM4KaBKsI0juB+px9IZFEZDaxdDjNL5jTB
AU5xRy5CTyFYNQozK2CVJY5IUiwiXzAnJyjBctRhCniJE6E5Mk4l+CYVCobjKM5i5PJQnXkNCbcUF5I
wudCOa0a6MIbIuRMJoQzdEEo4ZDTfj5Okwj1kohQQRAGB1SPmJEYjRdargNuGIOlG6jDQD2WCaM1RBK
gc3RPuIA2ermytNRWQ+BWBUvlOUcsU0JVcHdhpDCAazlrP/JNgDFKqNY5YxnEMwNtEOFDkqZoTFAuyC
RPawgBK0I33fDSH4aG492iGycIHC+8/TPwyhkDMrknhaZknqUJKIZwOEyxhfL6yg1al8DvNLu9bnirH
O90Q88dDIyOHyAH9Z0g7LaGPSdA/WHQ9weuhdCAEK1RJfb7eZ3oAeLEiInESSog5lsYTgGepTGa4XsC
wxqR5B78wiiCWbXK5R/qNnDK6FSHCQKbPIJ/3QmiTNaQIDB9/jKTMjtvNB4eHqwpzS3Gp420UCEaf/1
/rCZINIM1A0mO2XzVksmcGEY/8EP/2g1gpZm29do0nH5/2Ty2bPg7fmOfnJxB/xDGVPc/vWpqaBnWmB
PrLsV3iUWJbJjGzc3NpX+llrKpOASwrFduwbFc7KNh0FtxPZcePM1SaybnqWkYV85FtzXqB26n+0HJN
b6d90Hxe1B8/g3ULulOeKmoR+L+SJjoCFXKcjW0SkC1xD8AgcqmWQPd6zLy7QpPk+ibbjds68RcCQ6H
3bY29FhX/4WtIuWWeiVUVuwash8nxada00NgqUcFGkXiq4YxcINryAh46F9328VYrAJTGTPXHG3/yul
62ltzndM5McHhl/aJlQj1SxIhEzpdtu7w168WnoPXO0pGgy7M8P6+rg3nh6te0G+VhmhrHB/nKc+ixs
a70B+Uh3Rv4Gf5HHJoycdSRC03CFU8H83xWWbl2uUJZ1QSGgtr01dWtNVWHhto97OhR2y+xQ+zaz9Jy
+R9NoxD1E9xRASSDBYv5tFMVxBVD1oOahEuk0kSQRGFwkfjlBgQc8tZh1EBVw4aREaN7C5pyFQ0IhCB
J64X/FbE5UFt5eYh6pCYcdwILt3eWlSIdCMWbUyKsvAhapNxgmljCIpl3oASJRlDIG9tK1pbzsh8Y3n
zOUR+RuhgOHD3fcfK+jOChZzbc1t7jj9nqiTXHLS1WC54I2URThtiBpvcJm7OmKxTsY75UO+GINZocz
xltJMudhQoD2Cros94AXYH6AOqXLI5gZL1UNXisDf+Z+J9KKXiXSEsFkKSeRE6iXKeyMUyZ+Kguh2zQ
2POktgwWrBCyjNmvVRAHiodfny0BKQBl5IPpc9oux1n2AtHsFcGAzdUgrmc1KF+ryjNYafjBqMrR9XG
Y/vk1NAlfOQGgR8MSs6A6MnZmbX6mmu2EcwBeHjvPf/GU2yWXSJ2vWunBxVvpcM6XhL/NvRDR9t9ysC
pekME190gHDq9UV9rvk+4zDEU9ZYTQki93uhS9+f0jrIHCluE7/ebTuv9sj9lLBvj6K5E6Kgdpsz2Mz
LPj0sMzacYTjYMQP3V7LjmOSrphGLQ3Opqur+pqhCQOrnHaa5WvsJU0YzBFqWgwrpaKZzDF+j0rP7KR
vOE5mrFGh2o613vAtIXQslzessMVU7P0E/olV0Fr/b3jDe2XVVWNTqDf7wC4hFgQI2FAadFjFKNbjln
XADc0qhMIxEQhfqF4y+5kLp2ZVDrAM8B9oMgEANHi73IaHcHLd/z3BZMLX/oqYllA0goezy66nqF0ye
2sR+Lphwfv1Kz3GMS/TOHMotO1hmwLHRer+6q9AHuqfE5fm3bu7RiJpVpF4GjNq5ipmva6RZl6aGmnB
nGjdsc9X1AGbdrGZhDMZngPIW9p0TuD5vwVlQNvqNtYtC9dkINZDKe3MPQb5H9UG2eJpNZqbvr6m1g3
4Ma2jO7v2/tG98SA4vVIrqu13Y/jGDdKA9wmpqlXl+vGEa3+jod3TmZlHrD2/7G27XGwuJK1Var0wHz
TQ1UQl/PFNXwA5XeY/W7gBZqpqhW89IfKNJL3VjynarGwG0Fuoid6VbohEPlyCtj0xwF7pUfQmvQ08N
qP9pwzoNPicV/v1XWFIvmKbGoytX2BlssimeHBWrFNgvw7LCEQ1gmvTKLfbzDoo4/W1oA9ZVYVpV1xV
IiwTJ0mj23vZZ+XVjYZ4Exabma5XTD0vWcVti9Vv2VfaU19LSWYjA933M1AFNACL4eo2T7qXr3ogCs1
L712hqM/mqgHYR2DqByiRnzzNqB/0+AAvPdjAlJ8Zy8PapAMcQJrYoX80WSQTvJBDREMqXQUK+qMKtq
8Zjj9Vn/CasFeHza3g9bfJhBHCkek7RsLaYCDB49aaxsaM/StqlnbYm1MfEH1v4Lc/GCgmYNkMvWjiq
wq/CqOD+qZFiA9C9zMh8TLqySwBNhN2gSwTDEUDbfPSRpHGEev/X81uXFC7WTzx+LxlOiL747NGuHKa
snmQb43/cX/Cz8sDYSxnf9/Tfsa1TQ4mQFCMDmPSCCesGP5lhGM7XpcjIlj9n6RE52jmFQ5mABcX1Oy
ZKUVMxPVsVUUOVfpvWFJbSyc2xTgMGs/ql0nhsMm8/o4uY/Kh+d+t9x/atdfzOqf/75k1X9abtHaTKM
KIVUoRajk2TqKjxRcR8jUtwbnSuse3CgsYjGGmhKJByQZhyQGmIUQIkSy7m+m1rCEUvdamzUKqDyI3q
V3NNKm/lUX4g9qxW0FLcymC4eZoQTQFHjfKovuYgEverCh8YKNj1gAFUYRRyLWWHDODz8iIbTdIEmuX
oW8Eugzz96I6PBHFnBuFs8h6DAE5iqcXFFRbCAA8QKpVFg0pety/srmkimqMa0EH2rS7PSOgCuXN80q
lk4ztWFlQJdRvGTxKPxAmCYqvD2Z+N339ZRyA==
"""))
m = sys.modules["pagekite.common"] = imp.new_module("pagekite.common")
m.__file__ = "pagekite/common.py"
m.open = __comb_open
sys.modules["pagekite"].__setattr__("common", m)
exec __FILES[".SELF/pagekite/common.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/compat.py"] = zlib.decompress(__b64d("""\
eNq1V1lz28gRfsev6FgPIr00dNi1lSjxVlESJLNCkSweUZTNFmoINomxAAwyMyDNf59vcPCwZSupZPl
ADPqavrvx5s0b70alubByLhNptxSL6NmQVbRR+pmEVkW2oIVcLllzFrGhOdsNc0ajrY1VRmvWRqrM+N
4byDr5v/68fu8mGEwC+kgQ/k9vGktDS5kw4ZkLbUkt8Vzxs7Ts51sftuRbLVexpcvzi/N3+PtTh2zMd
M0iM1YksG2k1WeOLHG89EnAuuvPQmeSxkUmNAUS/8aozKuuy7VaaZG6G5eamYxa2o3QfEVbVVAkMtK8
kMZqOS8sFLNO5JnSlCp4besA8CBrz2lhWafGKe1e6H4wI+o6zyq654y1SGhUzBMZUV9GnBkmAQUcxMS
8oPm25LuDGt6kVoPuXIAQPpV1iCXwugkJvW9uqqV1CGq1hHWaa1K5Y2pD3a2XCLvn87+1fG/ggmRWyo
xVDntiSIOFG5kkSAwqDC+LpEMEUqLH3vTTcDb1uoMneuyOx93B9OnPoEXeAM1rriTJNE8kBMMcLTKkI
LR+CMY3n0Dfve71e9Mnp/hdbzoIJhPvbjimLo2642nvZtbvjmk0G4+Gk8AnmjCXEp1jf+zXZRkgzd6C
rZAJstd7QjgNNEsWqIE1I6wRyzX0EhQhqxpfvirbE4nKVqWZYNj7Efr1lpQp2yHDSJ+/xNbmV2dnm83
GX2WFr/TqLKlEmLNffo9qgqMVaiZSaYr0XmqV1meqMW89zzuhydZYTilRq5WEIUDPMvnFs3p75VFDar
YGBB5/iTi31CuBgdZKO5ooEcbAv9HzpCRzMKIFL5F0nAHQeiv0yrSvSAuJaNyobClXJXvrdKCo4nI3l
w5MRRTLjE/bOzHV7f+LlP7wPrztBg/DAZrL+R4UXM/ujyDBeIyEO4SMerf1e6UGXvamttqlD6/RRZHP
C+M8fNBdXd4pZFjVPJF2jTshgK2nxaY6QWZ18GuMLFOHTiefZtNwfHvqynAhdatCt52Ha4aaolHxAPj
o7Lj4hrIEX3pfBRg9ha1MGRBrQqtCBwBhA/d3B5dI7oD2muZeFaCKRRrVsubjQGXcrnJAsy109oKQwk
ZHcsDX9sEPh6XCwqsvZ9qRauhROxBYa0hjlwEfL1q/XnToskPvf2tEXtUq1/ik1tSmOQQkv1791rz6j
qLVPrQD0L38Iv2BcCAbyWaXTS4b1i6SSYVxuJ8+0vrwCrO7oCzYQicYfIabMJUv4b9MZ4d5wVOYDDsB
0Up+zfs92TuJx5kRCxMnct5YFouLmL+0EANRGxgnsLCm8h2+dlqc+EXuYlURH1oJFIQs5ArRb7X9RG1
YfzfoTc3E4vs6NN6LhZ/xpsK8eIVXtUD/oXvfuwlns7K4G4Hf4NrH0bBaRDxHrTc6VekaQu8f675j3I
MmmLDZqjesbdpLajV5I11KN2R+c6idu5Po54BXjG5V+gi2I1fj3V+xXYukYGf/CQ33DYkSZ4w2mMjWc
2pUx1YUd2jnXbd5maoVCL/BuzvQpFoJZ62SoE2/0GVTTJixYCjhfq7y1ruLI53A739WsuHslAyOghPD
RwEtCcopNemfTfsTV+LIqNX2CnOWMZYp3w4xZIDuuO1JlvMOa2s5j+eFTOw7FBxmheUvFnLU3C2Dxnf
DuVxnlm4f6GD8qeeyQOs999L/+SfK0MmxGhiToKLzMmzY9iAl0ux6kPiq3W+0yHPWpfC5ggJOeAfHdF
4pJA6nFuRs4nopwialEVPJ5S7OmZhj68WqhlGGmQzr3ml2W9vC904Oh4iJYiEzrzzWQ6QGyWX15n/q/
i0IR0/DEVbrSd95F4+G1sfZQYLBbdjtP3afJuH17O4uGE9AcScQjgb70P17eP00DRzi4md6Sxfnlx+A
nM4Gg6AfToY3fw2m4XUfzz2vx8mxHv+lBlNdvKjAh1fvd5x0Qo/4qqk/alxw6x1sXqyQl2Wgyz1MGlP
wHy8/nDuFqwz8vTzSbEuwulXlYl0zSO71RfgQYIe+3U0MUK0v338NrSRUm09Qth232aMiAD4gwIZyI5
LkVbpHbOFjFov/iPBR49vrVcp/YF8elxX8KmldmsfOqHpiGMpM2jBsGU6WHUoZAVvsKOjFPbD+Jtp1B
axR7m1f06c79m9/p67S8SFXJKjDpcuaP2B/9P4NGOXGyg==
"""))
m = sys.modules["pagekite.compat"] = imp.new_module("pagekite.compat")
m.__file__ = "pagekite/compat.py"
m.open = __comb_open
sys.modules["pagekite"].__setattr__("compat", m)
exec __FILES[".SELF/pagekite/compat.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/logging.py"] = zlib.decompress(__b64d("""\
eNq1VlFv2zgMftevIDoMsXc+N9nuDrjuOiDtkjZAlhRJekORBYUay45WxTIkJWn+/UgpbroOWK/FzQ+
2SJEfP1Gk5IODA9bXRSHLImUHKLz6Xx/W7512BuMOHAOCf2GThbSQSyUAvxU3DnSO30LcSifSapuyU1
1tjSwWDt42W83f8fV3Am4h4ETw0jqubi1cGP1VzB2IRZ4CLzM4+cpNKWG0KrmBjsS3tbpkIVxldGH4k
iLmRgiwOncbbsQRbPUK5rwEIzJpnZE3K4fEHEEeagNLncl8S4pVmQnDiIUTZmmJNAlwNrgEaOe5MBrO
RCkMV3CxulFyDn05F6UVwJEAaexCZHCz9X5dpMHGOxrQ1QjPndRlAkLivIG1MBZleFdH2qElgLQi7oi
5AV2RU4x0t0xxt/dLf1z5foEZyNJjLnSF61kgGq5wI5WCGwErK/KVSgDQFOBzb3I+vJyw9uAKPrdHo/
ZgcvUebd1C47RYi4Akl5WSCIzLMbx0W2L9qTM6PUf79kmv35tcEfFubzLojMesOxxBGy7ao0nv9LLfH
sHF5ehiOO6kAGMhPCIl9ud5zf0GGcEy4bhUFtd8hdtpkZnKYMHXArd1LuQaeXGYY1XVuXwSm3Gly8Iv
Ex32eUR+vRxK7RKwAsvnn4Vz1dHh4WazSYtylWpTHKoAYQ8//IpuwkRr7Bknl6Ie261l9XiulxVHdvh
dYvnnRi93OthZvLlXosFeyRBF6QK7NJinQWa4omvrMtrsY4qUBoGxj52Ty7Pr3hDVXa4wZaw/PENhOq
PBdb83oJZvBqEzOJuco/iuGRST81FnfD7sf0Td2z//gjfQar79g+FO5oBn0b9crYSN1v6DvS+sowUfD
3Qp4iMGUCh9g5uGUAnU0Xaj9nhyPel96qBVqTeIL0sX1QhUg/RN6RXFMRpttMks8Y4azjYSaLy+a8Br
8o0TnL5/cBpncdrStLPXTl9LqyMyfGyp1B6ophfP6mCpuHOizKJpdLueNmcJOgRQFFuzODWiUnwuosY
XitiARvwQ/SfPA0/zYs/ypZ7vgTyTZ7jSeVThLvhOvl3TqRS2fOY3JpNzKjr6RD5xpL2vrd+OoRXklF
cV5dM7eM8FXS9KlBHOxvAB9jV45LmhPG0eRXv1YasZz0LxooERbmVKCEET2OHWxTn2jXFfnH7WV2YSt
ndfpTLfrSdEfQiHsR7XeRw8GsKYBqXC2wXP0Iu7lox2ErHvjEaYcMx8+lXLMpo2jneju5DUOw9EcWe+
2IWiCJm4WRX/OYZv9GdGseIJ0N6gO3wGZp37ie7i1v6a3DuzDbb14aILChYKJozTjcGflOgZqfjBFfv
Lp+huLioHEd55xmiTQG/oB3Gg8Araay0zmBtuF/hjRsuhiwvv8Fv6eVIWVhUdZlYvhfMWiuPxpuRtuN
A9SsWtfZC6TwJvy+0LkvdjtjxoV63sAud2uI8OZhQoIYoSguI9UrSL6KOrOvQ02iSgpptZSOOGvNRsv
/E+OdHSFgn9My4fcBWoDMc3NU4CKPqjVubB8shb1GeuV/lzBJnQRMyCbbgP0+KK4yeQ/U6VrnmW+Rja
0DXRQuaGV8etpn/2TD9Scz3BNDTgS7jugvTKXD8RQ6LJi0OMhBWOdN9taqjkhAb0G1r/GLD7IsfIj9W
h2eriY2yPzNg35saz7g==
"""))
m = sys.modules["pagekite.logging"] = imp.new_module("pagekite.logging")
m.__file__ = "pagekite/logging.py"
m.open = __comb_open
sys.modules["pagekite"].__setattr__("logging", m)
exec __FILES[".SELF/pagekite/logging.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/manual.py"] = zlib.decompress(__b64d("""\
eNq1fXt3G7eS5//6FIiyOSRjPpz7mDOjcXyXluSYN7KkEal1MnGWarJBsqNmd99Gt2Tm3LOffepXBaA
fpCxnd1YnkchuoAAU6l0F+OuvRqXJR4soGenkQWW7YpMmR8fHx0ezjVZZnq7zYKu2QVIG8Vf8PNpmaV
6o1LhPuXafimirj45WebpVy3S7TRNlX3zrH2ZB4R4WZl6k88ikR0fvx5fzy/H7c/W96tIYH48U/WTBW
t9HhR5mOzVQ74N7reJ0GcSb1BTK6PxB50Zl5SKOlvFOPUQmWsQaU+wxvOnPl1fX08m0AfPV4nUN7KvR
4rX65VXwejBIsyJKE/NqFLz+lR9hgGip5QF9R5dBEmz5Cbd4sYqDtfSoRj07n57eTK5nk6vLxsDXNOq
PBEJFRgXK7Eyht2qV5kp/ylITJWv1qihe+/W9GtE3v8giVcVGC1J4vWqSFDpPdDFUalIA5hZIEaQTMk
qjQ/TaeqSpR73w8NKcYU2n757EY18FMZFCud7QBwYeJDs1O70eLAIAJ8oo0mUaq2WQMLDHNL9X0QoTV
cs40kmh7pP00ahN+oip0JQIhHo3m12j86fd8KiJGGoA1NAaiBgD7IZKCVyZJDqmF0lIhIapMlV+ijSj
BRSlExMUgh0gFBNYBUuirw3R2gGsloZomVYapgQjSQu1CR5obh611wwqCMNcGxmY8JuuCp0oUy5+0wC
d0nuZDG0CL32ZJmHENNRXUbKMy5A2VSCt14AU0SCrKNePNLiA3ZZxEWUx7VCw421ZqcvxzOJltqFRHf
8Rx8R6Szg1apEWG6WTkJtjrYKhE/4sW328CJb3A2pzLOPTUHiZ621KeD4mVkwKfu0wOuANoW80EaKot
4RFWs6DTmgbl7r/FOcEsUntWnnriDIIf7zDQla8H/8oo+U9odsRumxUFGtBQkgoWRZpbjcUE/2Q5nGo
PkQhfSSqBZBlgE1TZhPk4BXqyGCIAONgkeZMLsOKC89/Gr+/vjhv8X6W69dveI6loaX01Zr2xDCJbIo
iOxmNPKWc/OvLkVCLpwvw/gkD+h8N0QS5NfQPIAB5+1JZsFYm08toRQBWaRwStvt28bQq5okYnEwEbD
cPotEcGmcUjEh4bkZ7A6oXURLqTwRSfa0WZRQXg0gY7ewAmG+Hm2Ib0+M9MNXPF4D588uXL7ntZ8Fwb
0WcjOZtxFTkzwt3kqgLsQTKQOfeIUwYs6G92ht4fHkm02q/eTXCzlfU8eNk1iIN6DovQUlKMX2AwQ5Q
PQS4ULswWV89bnROgr1gUPTaSV+7zmp5pE88kadlYUDhjyB2y/PnnwIwOrO2bx/k+oSGEyg15ur7h5U
cF1YNLKmBxAKmNgt/7KBiljK7UC1IEmqzzKMFOCsqsF0sxBkVoYqjhLVBSm8fIxI+ThVRL+Ld0PEHcM
RMMlSTFY3rv2OwXP+j1KTzQkJWtNxUsjeIcx2EOwaoP0W0BZEbPllF61JYmxfBROElIsEsyb6AHiRhT
4wc7/rckbAv6u0ximO1YHWxzTA0+oPlZQDR+IzqaJ1g7WWGJiOIG5pUwYKG5PsjQ7sXHYWH6F0nDFIB
TBkWuRbZ7x15VztJ46ODgdLEzKxooKnRRMgqIOCxR/yAEc+gjM4CQoRsFkYnoglVhwi+o7oJhPoyyKK
CSCHWRQEmIqJhnGODesNKoWyDHbUtRYmSmt8a6OxdWooS3ELJV7LZSiwZNRD6xo72ST5Y/WrIRiBhvd
CsPWQfVE7DD9XJoNfkucNieeb3wgCrA1q3YXz25Ssp4tq3MDIBzVv0D03x4xE/hm57kKcWt5YJeQhaV
pSVMYQssCd7gN6OHUK9ihLR3qA/wkd+gABlMyy+SKSsiMVAw2B10v3gHcLUhgAPK14+OaqUzziEUQCS
kjkckG283i+Q9U92/deX6mr27vxm8KReIhRmpOiFy8o8h6nWWOxB2NgVAXEmWwDpEmoiOIfQrkwg1yQ
V0cD0DgKyO/jULA91kd19Vq6/vRj/0KStt7DQmRmcTCZrSYhgoYniI1pDCmFF/FVESyKRnBfTt6Y5by
FDoo3lVbFQWC5hGRLOijyNWZNXSp4ER5lrb501FKllZkjqYWva89Or9+9bPsOLKANFj8jX+G74p+Gfh
39h3wM/8/k54xiTSMh+Yspl058drQK8Prl2RuzwIDgP7MvAjf70Fxi7C9I593uzZ73UmHsWGAMx5YZ0
rtP39Bnv8PmoZiyoGxFXtBmQ4Kw4WOBbOKrLY4j9Ni4JtwntGNNrT+jyBdnWOW2eWPqL17KwG3nIm0G
2arrFDr6Diac2pHmwE4c6Y5qXgiHAIIYhMVHvph6CuNSiES8djOBRXho3PnU+S1lIWPiqC6Uchj32p3
hJtosKoA1jt1eJ0cSc2gMCqHEckzNlyY+IOdtk73fjkJbUJ5Ehf3WxHKpupoWQe3s79eZ2cjGbtAnNG
ZAtcnDG+U7ZFsNGe4comrYjpqe7Vl6R2kRhSFq4G6bFoCf6xgLewCSqfubzq8WqNEtI7tubCzGMyAcg
Xq73KrM4DcLa9MeEoqwQq8G+bDZ1M785r7GU7eWgAcEkhKE0i+UG8871mqwmdXPugMVzDAFa9RCvGeB
8fstQoC7RM0vJRCLfCkxCoixnWuire60ziI+cYVgyXq4jB0xUYYtRxgqPgQr9iZxSIz4nBJbYVqK/K8
VcwJiB+WMaYE5/mCiYfRk5lV0r6k7YGcIMvqf/+1ncNxt2g3rWqHmRbcjvh+lbZm6SFae3JmopwYvAa
/R9w32dg+gMSmuXOVDDBpyp1goOmiGrvzb+cE2dy8UwSke8+lAXQRSbGsVfcRxm39xYlTEcrUedP2Hj
xxHTK88sKbc6T0vjjRTGsrifB8y4tumM7Y0SDmzsGbRdo6GIiKkdfi9TFlUkCtgUs0MSV/MYHLbAAM5
uYQc63QY0QM2EsV4AZGmImMSDNCTDRbDsHS+3oqIW6mOrOSArkmxmZz+lC83jbllAKXVl+2EI6gdxRI
unSdDWEU7tYNRhx01I/LmQiswGwlviFQEIWQxxHhi8kUMGBNghkiCaBUaagNfFh3FhqUMBCWZgOGdr0
HwLh+zgiVpmSIhWNpZOKAwINUam8veSmn9I8/smQR1S1IPBMtZEC5UAmt5HmYIAcP6ChX2ACoYWBLwQ
YgwPYlJ3bdhHgYMCQq87HpXTIVD8GtxEqIl/trIxB+a6z0EhEi/InCfS/P7sIJRGZ2494OZmH4IhEH8
Egury9GYX054DlqTLPDCbXHPcGCo16WDOCXy6NNltwZ7cREkbK7yrEVp7+GZ8+uP55VlrE81Gx3FtE2
/IwazitgnClzV/U3FzP0USKWVUIwDohULdTnixImeJFoZqbAwJFKN+ho2YMJ2zawwatSQuxnZdC17gO
5o68tHWk3TDw/CudyBPgy0NscR7EhRNYT6AILlrXxm4fALRwbGWdoUC+f6l3Z1t77o7V+FL+7PJWVuG
64+li8v5HBwLyJlPf9xyWsekXuJetRUIsXhVB9qyFsN8fuo2g/e4FuZhiUUrId/cRV190NUT9SOsipa
pWS2bPTQJdJOID4pAdTfRekPSFaJnm9KgJCoXqYmKXTXZJJVIrpch6wQtbbqhmzqvlgVPT+LwNOUCpF
lRHz92Myt2GdvtJzYnonP3DcjA5z7xDzvhhjwDE61812eaI+j7XGNaQ9NoEf/EBdE8Vo0NzUynF/1mm
gFhsunV6Y9T+7UBzqYLZrDJWZAQNl1Efyi2AtbvFD2rk5XqGBN3+qoDm6TThtdhLPy1Y7tbO4fdGUDR
JNvo+4ITDjEUNzwODqo0IMEH+p/ulY0V5yfOPvJvbLSelt1w3ZyKq0NjH5cDQDJ4AMsrhWEi2Zqlptf
X5+9FKSkE8Zyh0IDlsi/Q7Gx06LAvut4F3JabAE+htVWwKtgiSLFsT2FW3czTxHMW8klu98HYzl/Ed3
HKmpQh9LjM9UE6Of+UkcEd7elbjog664mVg1I/6IRkOkwrGxjKmwteWvu5adxxeK4WEHRAye7Oi8HGZ
Sjcjw2xwgxfkER1ETTyq80uKYJPPm7cCH/Wg7c1rK1W/5/QNmWv2zR2iATjJ/aLrHC3EWNW5XtTW67W
bmrD4ZDZXZj9US9Aca2X7fGJY0xllvq4zdMhYSJgU7CIkwk0oHEIMw7WXsKJwc0b0BvawTAI59Ti6B6
GFpKKtHtraPwGNPYFdJCT94AID+kdUiNk9hGM32AqkrVawCJBcDCMQlgoRPUgCVjOHlMssqidw8ShTX
pG6mGPw0r2uYgSOJYpyhrUHHbPmHabssXb/3WR4Zh3G4R6b7LeuyVnyE02TMygTm1PTn6TIgtSda5Lb
Rte0uTUkrFPks1IPO6MvDZxbBqwJPhcMZ31GmEVEvAFkHBmDW0f34tE4efkxDSpA36OxMdsNBimsWSP
SV3CV0h0TbO2Nw7RtM+v/BLZVYfk5zaPw/MHYtfuh5gQeVaiuq3ew2BQFumgwR7VFhJTkmSXnZKZC2I
/R2h1Zco+Fb4+BHEUspowNtFOMxZYoL0WsxymQ6dCK0wAHiKnAUSvJcLmPvEE0NdbgFFOu1OldxCIJ4
u4vmTyGAjucqOX9+wZPrfOEbkbMkAo4TraEzJO6nnz2kSHLaFFK6T/4iBfQ4J42xPgyLCnaRabxwBog
/5md7woArISVFtLZEjII8ufp6XkcSDCfNGALaLJ81J2BLPzDorUAXgkLAPed8+5klAo0hHk5qG9v7YG
ASc/irzkbF2eEi7YuqhvU0MrhbskTPwwPx0CfaPX5MCAF1iyGnFAz3YJ2Jw48yFC2OAn0sU/tYwkg8q
H3b4cZqNoxRaGpaaOCzN1PETyDVjf395cgGC3NoPlfkzBtQRsE4SDTbok/zrktJ9fG+JzRPUPummnt5
ZHFhikfB6skAFACENFYax97QrEwI7sdiKLlFi2L4UrmfjhDUjVVnMM6B60w6Bmp9d1aT1UCKNBfMDPO
EG0hXRcE02pOoZYOFbdWvyh17eBcNqNB1QFWSYKwt94w5ucR90JabTpMZM1cYLJaHRWu2QN2AlVjkNQ
c5/hfsx0vo24toH0JkCsmP8dXlZBFANUbsnD+9L6sQFG3P0qJlUXqYDHZltHpXFNrnrPmAzUtc7rtse
1C+szxZPaiTLtK4dg00sXn+B35Uo1F2uhTeUhc0WQxKv4BTv8zhosWFw0gg9vb64uZ/vRh8g4DdOIo1
eagiimJdudIK/Zgn3+/ad+dun1tJf2n7f9bPRbNkei3RyYMB43IrBd5ZfNoLrYZ9Pa5TH3NbWMPkQM+
1vnirCy44oKIsZwGeRNUIzNciEQOdfmJzD0opcbFSDVppFo+nuwSFwFW2rXTuI55X9HZFwWGxnvTm01
ZFZkKgOueusQT1JsYEpi/k8N/3a/oZfBQZY905TLDZtb98XDHOjbHrm9+bdioTWHYHxZ7Yc3UvkXNHJ
vJH4bgHyKTejIE1Ff4uAP6T2XASJzkSckgGg+sQW1t1VsRGRljjoVcUiTVL2KmuuLuCKHyQv0pvfNkM
A0IrCt+W91sUmRsEeWQRy55d5sOEbPDqCsqgUDk12VOSstl4Wg+dp4+IF1aazbu+BcPLFM10n0u7CCK
ZebPsoJtiXXJJGDiPBjU8DD9WAbVY2gVxGVrHnYmGGxQW2N+azumhaIClwq29aayswaAOH3rzKsCaPf
NYaBGJ8vYxQTHbK1UAzUQhcQ1CfQUkvZJBT2y/xmRaat1FhpkChMWPwEHNdzCsWWn/LE2fYTH3KRE9V
VUpPoOdzjSHl4AD/aVk8uWTYXNrEfGe9/Qls5VSGlYQ0Ax1vCpa0mYzIMdsd+KvVsswvp2Fkg5EuLtE
EHEZ9VPIi0vlNINibZTBhWYWOBEUjYYlBVErkcInevwyJ7J/Dwxidv7HxuJPjOv8ZYJn96w/Qrtgi51
wstxUXejvHRThbah6bp066cD4rY6qxUDLOL00gebXnweHjVrc2z62cxFjy2I2QoguLFS6BOrMHON6bT
dhNRxRzki4gsPLLjJL9gKzrU6dXl5fnpzE8N1h/yPm5qkJmIFDVEtms0X2ala7jitALCLS8H3x1uvdX
bJ1vvBcDEejh2nY/JsI5R4GKTYZIqlt1qRFLbfick03aLFxWRr1NF7KZt3SNoyNii8TRZ1sMKzThaWo
J/qDNHYECT5FRAsjnfHfvgEMZ+O5uqUREFcTPMahdFMvBBx+K3RcWeMet0PZuvorxaU2IgAUEDg3ZPr
2+hQXpSnE16L99JJag1NBg+iUmAAwc2QHER+CMSSMRuF1FSfnJ50HrpPxceJpzF5UIIUgM6cUXRfnnC
89sAVQc0+FTCVxKmcjvPovqlC8oZt9amh0NLr/ONpyTxAVsi0GH+WQ9Rakr7e2JRaMqlcA3bxG7IJiX
USPFg5AOZW2wJ70+9dSuqLbXglTXhVBcyHbYUr6/0cD0UvQbhx6Z+MxwWwB1KAiLd3rCWgSdLo+JmMj
NYGYu9u0NhaJoMftd5k1scDokTYA08RsxeiPLaPYS9ykmZsCbNCuqzjYp5lHmRNrk2I+svNoTBwcbtw
G+r875YpP58LoMT5GG0WmmpAuRMAKGPAPR4S6xWlgwUwg9N2eiUNxxZLnIQPfUYJSHspRXn2O0O/HX0
5395+dLb7O38xKqMoVWs60+yIUe0C2474JydpVNFs47WgYg9OO1tVettdX/0pV6a7Mtwy6SUrCKnoWk
2G+aRRuTOEwHjWswInazg6JN60vnALhzVt8oXW/X3AjrOMnFpQR96lVQDSxQngn2UulajUI9VLDkoKU
mLCzstsp45ZF3zkAgtEENDVHtzQXHTGrt2fheLY1oN5xJprYkIbxJYbtNdYVoX9mi7fIg8hnwwXhO99
CwFVUYhK/R5sIwPC5qn5MspMThb6HX/oOGmidG10CvMuYpMBslhH6RSREP1HziG0kk6YZQXO956R04A
sCgNS3ndNta3AVu8MLPzksbGXoPBT9SdfOfCLiU6srizZwGadMkN4YgkQD/7VFxHxuWN0p/edtjS6HA
OMdTJrlOF8pgtgc8qD41ejt0FXDO3ynT3JV32wgBhWMsJegQqb4i1twSra3LPNYaKGjVoe4vr29Dqmm
tuaS58RKqlnqv+qJeDKceMXRA1Tq4f/gJo9PdfqjC+eIkuK7kXRjaGZyvszA7CftVSgq3mMbSc5GJSa
hky+2kTcWZqUr2Izdx6MT55Uln3DXjOs2LT3h6VW0lWt48pTS8nqjuVRPIl2kyS0Je+NgjfEFEb1ooc
Kq7qXclUnTYCiPVpkk2XpaQD2/M8+RKmrWJ8Noxuk6y8GNHQ93o34uyy5Cps+LgRE5v+PJ2dv29FxNK
s+EPy44bkVSVFeTCWFz81nFdUOP6fUVVHni+5wrEykrKCZMTeoL6e9QtHxjD7nUffuvH67fxirD9FSx
SikUpCJQlTZZVgJSv1DyFjSh1qc3J0WmMk78U2BqkHXgHj6WMCLqPlplZLBsugh6IBZ+U2a4D0MyRo0
9nZ1e2sb+Vu4eKC+4cTqnh5jMMwIiTqVTA7RAiMidm/fEgjSe5ZFzzbXdFbZDXiaME+HatxkgT16hgP
jMH4QiIPDP0R1Mh1bAGwjJN0dQOQh/T7clMm96ZZ2/Q7TcKJVhxntYLQlwWamFs0C7P5Ua01xrSLch0
XJZSy2aswms/f8BvUm3NJ5KW6fwPUsI1ndStX+XuzCFVQ6zr1va3FGNI1h2WwE2/7TPaGGCiV05NbHZ
CQNAUJ1yAPcegtKwtfLRaQj4WgV1Vux/stz31JWplU8YhbJ5d+qGaA0sLbydnJD5MzW26SilOlkMnik
AJ/Q2GOrsU6orC+pOsK4Acu1L8mcM2cba1Yk1ycNC/zuDEv7oxkE+c0hOfx+RHlrrUQkZTEEpWXSfgU
wLOTW8vVp+R2kDzhBi6V5Yp+z2o8F69QI/pEttPWqe2dSLG4ZpisJPo2u7rmohgxjpopeP2oMBjXqzb
zt1bckwFiuU/OS5JO1dC9xGhV4KsosrCRMzxxe+BtGLSRkyK1Zv5tprf17fvpCYPymYUPD9Wc+EqQpt
Z3VSH7lSC2DORABYjRrvzDq7vTq8u3kx/mbyftg3ATOVgmVS8WkXsVzsaF8nwFUhHFUbHruwDIkY9rw
EFolcxU+tcfc9ugnsDrJ1u1Ji2MP/AXMl/v6UxEKm6T6JMtMCRPoTrj8T5Yqqup+qnXd9cNAISHwIVC
FsQHdhedTfLFaJBBrRSxwQdTcJ69zOQEKBjPHubbZsioq0WaIhkRsSmw9pVftbpaYlhGn1NMcl7dq3R
dLEd+OmGlz7H2wzrclWdOEongLIlWTP+Jiibjw/2pnB1g98wqLhPYA3KeWmtFUgeP7frzFc7JX1q/1g
p/gZb407DWN4RagXKmJzpYbtwZYBsKz4Ic9YR86wR4K40Ji2i9slhHfsZkwVJbciL2YJroDAYdHoJvD
qBxyDplNS+JpiAMFkzM3o1exEFyz6NLtlE+LfQ6Slik8/I6X3cYC9U5F+eOOZIiCrq8mp2fMO18AFF4
yhqktcOlNYMTqHfPrDl4EMNyJJSpKQgfXLmz2PDcn08GcHd20zPW2E8fCagJiun56e3NZPZz8x4RETV
8cIiIhExvrr4MCiZ2LjjyN4oErvrUqjGJhlhalPtDHCfIlSzYRDEMCevBIkX9CkpZaEuG6h2i/CHuEX
En9V2h5IoDBklBfMSONG8BV5sS3T5EeYki7SzYqlq8hbhgmwWkQuwNG2LXcXET84cfWC1ykKA9NM0mD
1GNDZmI/eUy49DxLBPstk8BDbuy1Cd8/tbJ82/VlCiH6NqHZtPVSqQFFLMQR1QMq/a3pqVD2uljLEIs
wmW+ywpvwHHvC+0MaZcYsYX5ZEkmMeD4E9jrNMUR2sCkiT1bXIPDd+AY6DO0B4lxc1cVbCtNOARR6zX
1iXFEarHbXI+ygUFGu72hff2qaj2OH4OdwYF//JUwmttgJQevpEYv2dWohgum7Xnc1kGmgJuDYCBgXg
7/2j94q0J1jQjPju8SOZIEhESjHOpc7sLWg9iUJddNHSzw98KEI7I4NWLkFJJVWhIziGDyFNXpb1p83
x30bxzGFIpHVamTEI2jmlaOtsLZZCYkfLXCamVp860V7d54wL07xYl65Q+61U6vjCA3CNMjxxSj2qnn
2e3l5fnFfHw7e9eQFCznyHhOPqdDq7QPX/7SZ8LiEiymT7nnwVVMtBP/Tyb72Uh6TIFEJ4KvEn/DT1V
K4C8RWtmz5C4c1xyJUw5Sh1A/Qc2qJZECWwnipbamui81hzEI2O5EqLM43UF+RTg/Zg+kcfSbzfSKcn
j7uWCeniFGyo7RgoXSACurzor3rW2MNMAAtx3RCrj8PY412YojXy/lF+qqvIWExTuSQBhNVswtluFkN
8oLe9pVCmc8PdUQVF1p4C8O0rbSzNY2OMxqcwixzVqMf2f82ds4qscOiy56wFy1U6Sd1yXyNKAaWM19
UBXfFEJ/3YUo1d1FzeM7DTM2yNclNzqprkuwQgm1jJlYBpGtu7rOI3C7T2I3GvhAAgtlssgKD8jqw1r
gxvmcx/LquM92CKZHpMyXEhGeCNzkci+23/jBYTR7UlEWlBPBNWYz9LPg+oRX4sK9lvARC4i/T68u67
EPNMMS/lGm5JnbwhIP5fd7CwgT3RGciUM047nisiZ1OlIUNI88nmebRhVKA6OwrqbnN//r/Kav/vPHA
YsaTAwfhszatAf4cmQPwbhG9uaXqEp3YRhep62zuvNFhfVwcRhxmDLgDRBekUu6Cil78WarlhX31Z1w
yB1Gv2Nf+W7oWAGcEx1iJ+vh1QT1HmPZqlopSnGz2lVGrLXW7flWEuJIGsuG8QUB5BPd8df5/eKOpim
fQ5JMd4xC+wChWXNXSyBNrlXOl0Ih0cMnyIOcrH8uCu7eRZmZk80zp3UM6LMFVX9K/xO8ukggsYabTi
KkkhalE+GfV8VyblFcQIZ0F5IYngNLcxIL1OPObk+Dy+XmMiazmj17MTk9v5w27/g7TbNdHq03hfrTy
+9eDujXv4nafQPRWATxvSFmT7lQSG9WQ17om9+CPInUzVCdR7QbxviSyOalaYjEaqx8VTzyLUpOuSE4
Y9GAe5vcrT/bNERq18qLMkFWgGlA51t/occPl7dqDF8qdQeH1LVkGS9IFUHYB/Y2PbPhszJHrmj5LSY
ztZMhA4AGsMlMm/R0NtKf3VgWImc7u7b8i9WTWBk9K4SLqu8TeKiW6w/TbFCAzAZarXJC8rBcUCE2xG
T2DoJ0fPmz+jC+uRlfzn7+d6dCYW0KLGw+zinSwuAIcoX/+/Ob03fUfvxmckFOjJMMbyezy/PpVL29u
lFjdT2+mU1Oby/GN+r69ub6ano+9HV4TyL6SHLYguyVc5H96X9+/TPttBUnLDhwkjxCQBzRk2z3xZsp
fF2/+6pCrCtJJOlD6tqabmS5PT4+DtdJOUzz9SgWMKZusL25bd1Sc2v+gIlWufQJX7ekrvnKTjgfctd
RGiLdCAFFkpVzHjghA9dL56xcEvbLrSPpks9VTPwxR1FKLoqGbNuC9GHDKz2fjy+mV40VxEFGErP7HQ
kwhwW/FqDhdf8Jw7aGltOb87PJ7MCVfYNDDO/HIfdweB8H95GFx8qRJd5TIuTwTPhu0mTXgHATkPVs1
EwvN0kap+udOkPBUZqxln1LDNzY9JybDyPjgfw9DXL1gcTLgrBQtbUPhkb7lhflcnAd4RwLMmo5jhxX
lxsBP7fji/ns6hTooS7dzvQdjqAiHUh/3f2pvX7t3XSXpJmJjH3v7kNttDnT9mh6mthmtQtMGy1rFyf
alu42r+age5ed2dZ86V6jKTvejeBHrelh6Hyfk23F19m4t1O8PZU7Z1ftRvbKhkZbd0DY+h97XfjywX
qHN40bEQ/0sBfrNOZrL8qw7ex1JIfmnLYbHprzG3cgYb+1vdCg0fxt7eRAu707g9DoMJVj4vutJTvbW
NnpfuTSdqjHt1ukIc6ro0cb3mq0mYkjeWN9/uY9T7ZjzeFtUmjpdwQitjW2VmOy1/zYIsSaS4JZUPhl
iDhqLdpZKxL/Y9lu21vrhtoTv747v7ieT+n3RTN4x7G/c8L8DefM4p2oc3uRwens5uLFKd6QyVxAW64
5TsFhLOcfOaMVzinUriEfQTSgv4OsCIy7tIQn0rzvsnpeFyfsPNNS6KczZkfaxcbk4aGfw+KCIzeGe9
WFhrtNzRyCd0CcONkBMAeFyhMTqssZES4yFbl7r28LJtlVk8MND/4qCW74lAByDF+bj6o9q346H5PO8
Lc0Srq/eOHQf9pxfOanLcT+OyBBgv13wLES79eeQ1Hkt7fzQeqgbOqtlg43f2sg7AmJYSpZ0RmrlX5U
EuBsBaX3QLWEytKztOp485xoqPb84KZZZv6/R1LHio+Tzv8boi0Yj2K5iJ0lpWQiMr6AUR7bQyzwS09
U2wyDjUPNRtT3kjznHsTUUahXCqKgS+LF8F27XLbzvSqiIua/+lNBfzqoicfpPWp2YpM8AV7gwS8vfx
3Cvci6vSEKIPJuz1/GLQe2GVpfgEGDWuFzYlGDDDEP+z2DPfEYQ+j//qjRwGFAGtnpnV2d8pg65gKug
p83WnTc7lrYnRmu9bjb6DhTs6vryekdh2lTjv5YKqsOl/KJx4yk2snHhAjFbakH2lHqm8F3L4ffvTTq
G0Mt1DeqS35d0WMk8Me++tSrL/7XngdTA1kpDn7wK1aVS3SoTHCRXlJ0OaM0x8K6+NVzG9l+flL1JRv
ZlItu59Xob92i+GfUew0SujtAnPWWwT8X/yQjVBp3ZP+GudyF2O2o+RzPsYAe5oAp+Dk+NYHu37a9/8
2LrkC6+b+fXE54J2v9RGW9fv1afdDxMpX6uPrloA/fmK+Ojr4x7nJTd08We0lOhfEdU1Cn9CcIH+ABh
eza5KWUw50cvHZUbuQ6+AqE00hXuyyFvfe4dcuxv9n4szfL7l3DlnKdDnI0oFMM01jeQT/GX/ku15Yg
jUWGR7S8tzV5cgQfn74SWwC0Or6+5uBejYQaKtltkd+eMF06sQAK3/TdsbmKyyufRbCLLi++xwEbMJF
nkw1zNdlX9kJeKdct4YJ2e1wvSsTywkH/nDDd5wtPRjS2I7LxZTfD6r9nKYip4RI6W9zxPan0lBzZ1A
x18hCRAT0kmiHz7+r25vR8fjaGXXB9dfruC8U6wUGdHoBsUQrfNTszJJn5QDKzxxPEbePOMht+/Hjsr
mlOmOA4rVwWqa3GkYsjtjYJX9Gjz0paPXA0nL1T1+MfzmHIqOPvjtXxN4Z+HSQYej5+1GxknkpE3hwf
DZPN0RAHbByJ+H+so1uhqzc0ZIASemadHi3oD9AC1ke00O0MvxGJKQRBJNFAK9MmwXuWRp4mDyd4PtK
AkDmQtfz7BUszq7d6h3azEnUfk8FAug1n1zTNj6s39ODZTi9afV4818WKVGp7QzN8prHM6OOz8+AYip
1JsgLc2rtR7eUqen7QV4vXdoZvmnD885tnQQSu6aQJIvhyENETIKIvB1EUT8CoXjwLhDdKNsv36Im9k
lX/XISwOP2uOtaYl3py25q0oqZeWt38eHb1YU9kbe/DPyp+MSnPR97E2gDM119btsOhvvYr9w5DMssy
xzLTfo5l/Xw2n2HK7qvRL0G0+PX1P+96FQl9d1C4uj7qxatFrkavu7+MB//5cvBvv/bQS65J/ihXcD4
Foi4MnJ3OpG8/HhTpzT6fESG9wxph32CS+XeebV9JHS7M4FqDL+n1otnpxfN9LEveHeLHuy/oblnm7i
Aj3cE8PMAVTML0+4u54j4kriAg8znezOdMzPM5sqiEWUC1/7AUKVkZriO14B3wg9O8Mnpm/Rw/ZueoT
v7uNRjuyMMivjwEinPR3q7wfgh3yO/D9PFzver83egaJRFZLU/3dMZyc978Tp7/FwOSNG8=
"""))
m = sys.modules["pagekite.manual"] = imp.new_module("pagekite.manual")
m.__file__ = "pagekite/manual.py"
m.open = __comb_open
sys.modules["pagekite"].__setattr__("manual", m)
exec __FILES[".SELF/pagekite/manual.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/proto/__init__.py"] = zlib.decompress(__b64d("""\
eNq1k8tu2zAQRff8igt30wKunLarpg9AMexEqGsbsozAQDe0NJKY0KRAUjb09xnaCbIo0G5aLkjwMZf
nDoej0UgULXmCdITQEtayoR8qEDpngy2tRitNpZVpUGrpPflEjDjqzT9tYpFNZ8vNDN/A4r+YSXnUSh
N47KQLsDWPDT0yWtINiZjabnCqaQM+Xn24es/d5/HZwA1J44PUjx5rZx+oDKC2TsAucPMgnVHIeyMdZ
op7760Rl+vYcOPkId5YOyJ4W4cTp+Uag+1RSgNHlfLBqX3P+VEhSk6sw8FWqh7iQm8qciJSBHIHH6Hj
BLfLLZDWNTmLWzLkpMa632tVYqFKMjH/DBBXfEsV9sM5bs4YYvOMgblleRmUNWOQ4n2HIznPc3x6uel
ZbQzGeitDJHewXQx6x7iD0DK8xiW/O381WEGZs2Zru1garMYOT0pr7Am9p7rXY4CPAvdZcbfaFiJd7n
Cf5nm6LHZf+GxoLW/TkS5K6tBpxcJsx0kThkj9c5ZP7/h8epMtsmIXwedZsZxtNmK+ypFineZFNt0u0
hzrbb5ebWYJsKFLtcbE/jmv9fmBHImKglSaq1fs+Dk9k+mKa/tI/KwlqSNzSZRcVS+5/Ku2kNryt4g2
OeA1j8yX1TA2jOGJy+drG0J3PZmcTqekMX1iXTPRFwk/+f4/fpN4AroeK/k=
"""))
m = sys.modules["pagekite.proto"] = imp.new_module("pagekite.proto")
m.__file__ = "pagekite/proto/__init__.py"
m.open = __comb_open
sys.modules["pagekite"].__setattr__("proto", m)
exec __FILES[".SELF/pagekite/proto/__init__.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/proto/proto.py"] = zlib.decompress(__b64d("""\
eNrtWnlT4zgW/z+fQpOpXidDEoeG5sgAW04wIQ05yNE0zVCUYyu2wbaCj4T01n73fU/ylTTQvbUzs1t
bk6KwLUvvfr8nySoWi4WBZtILO6Rk7rOQ6cwhmmeQ8/F4kLX41NFCahCdGZS/1pkXhJoXBrVCEWj8/L
v+CpedltobqeSYAPHfCmPLDsjMdiiB61zzQ8JmcDXpI4hdm69qhRabr3zbtELyvr5dr8K/wwoJLUqaV
ENBnceADHz2QPWQUGtW4zo0HzTfs8kw8jSfqDb8DwLmFQQ7UN30NRc5znxKScBm4VLzaYOsWER0zQOb
GHYQ+vY0AtvZIZKUmU9cZtizFTZEnkH9AkoRUt8NUGh8IO3ehBBlNqM+I23qUV9zyCCaOrZOLm2degG
YGATAlsACo09XfNwZiFEYxWKQMwbktdBmXoVQG977ZEH9AJ7JTsIpplYhIFZJC1Fyn7A5DiqDuKsCOj
UdV/tW80xBg9gep2mxOehjATXQcGk7DplSEgV0FjkVQqArIded8Xl/Mi4ovRtyrQyHSm988yv0DS0Gr
+mCCkq2O3dsIAzq+BBJK5S6qw5b59BfaXYuO+MbFPysM+6po1HhrD8kChkow3GnNblUhmQwGQ76I7VG
yIhSThEN+7ZdZ9xBPi0YNNRsB6K3cAPuDEAyxyCWtqDgVp3aC5BLgyCfrxJbfpd2QXOYZ3I1YUBmR5C
vMyMeCyskoBA+R1YYzhuyvFwua6YX1Zhvyo4gEcgnf0Q2gaEZ5MxUC+jebvLEguQOjG8wN3kCh0d6mD
yFtksLhZnP3CzfdObO0f2ixy/fvnUhBtO38U363mGmaYOdIMLj20KhYI6o7tMQ8r3HPHTOjJgOm2qOa
C+VGwUSt5C4LzTY3KxJA3Yh5GfCY1hzltoqIEvmPwa1Wo2/yphI7w5qB8/vAn6RyDtSEjao4cX2wlK9
QurP+2f8p5YrfPhbPzRTDf+VfqDzm7zKhViNHn0WEYNqLilHHC0yXeqFIv14oAXMxYgFswiqHg0CoW3
orxqxKB5dpqoHlrZt0ecSZLFXkmSDLuRIDJXKNSBklPZ2y2QrMVY5JpHZLiUWv4mdWLtk5imdRmZJgm
w0IH0C2/S0MPJpAPCAHs8zqwCOMF9b/SQJDvRZp/MwETgn+yvSB7WY0MviviXwvyNyjk95U+RNodfod
rwZK0kAfr1Or91AgDKQXo6BwIksbnhF2giNssTDAWSPfC8N/MK4f6H27i/VXnt8fryzx9MFKY/ZIzg1
xP/HmEcYPjgifphrK4dpxrEkVThjKIvuXLzbiFmHemZoHef58AxEbCIiwTjymxwIofppseSEMxe6aZm
2ZGnZugVwiiDLPGclkBagggI9jh8cMQPqQy0SgKnFtASQLmzwTwVLDjz7tIqk0WGMYzOD0g/l2wFimC
ZTThrmCVhcUJQlzxcQI0P5RHQgijUB2NozW+f1FCqvP2eAxjU0vhAlMVdenHwBpO6UGkZWJTPVQ0Y07
sOAOREnDwVlu05c24OyGlS439eHxERBpaSaUHBJiKVaCiUUqsdCqCTcEfDHLaqh+XQcDnebccStJtpS
N8boKUKkEV8hX9aBN+vI3dGIvZKlopSH0fWx34fCH8XF0/LWdjmWJfWFSDyQBxE9lAAFuGy324078Sb
gUM8lQ4LpQHmvXhc5HGcWjLutNw7ugESiVmyOrSRrkHogWPCuZfgv0qR6gOyoE9DGBk2Q5Qeopv3WSf
Ks1i2qP46SwChhiPD0jfMab7OszqVoC8etZSAPcs2xDTtc1ci1BT4UEJdaZQ3/KpguGFdATNMR5vLYF
WcspFnk+1iQMIbnPl3YLEJoAD8ug7VIw8G39TtyzF3VyPyTOCZGQeEWFFZQwXzCSNguJzDLlcD42wA8
fE4NIy6ZceLr6wGZ4WEpDKolwfwXjJNygvaxFqgCl6GReHrsRzTv+TMNYmEtJP4TmdcCdU0AESLJ6m1
InyJQ4RxKOEznSwJKKzDp04GTAQ7lLIO4FgDyhFmh4Mb16ROIeIvBLLrCU3wD7vjHPwvCLxziEqq1R7
oKSrFvwECl5MWtcXfbVO+b5/3R+A7DI7X8Ro+R2hqq3+kyVsaT0R0HIeANLZ2e0hp3PqnAOB70MywNw
H9TWCKWUEqfzh0N5u4epJDmYFbRMl+cRJ4JZgp4z0BzwlpMwF3dbyLbOphhFnObws3LOryOduXbRr6W
3mVSJxDOkymRlJRQsnKWZnDjhVXgWEEjw8ItkVpIlEouyo/wGS8r/BakRA9KUsa2D+vABIJi7iW+1q8
QT3PBVFA/p7aX1M8pw6kmyBTEFGDhqXFwDRr8j4M/SJdYsbImWTljjFjG2SXc0wIHVsd6HSNkPCHnTM
uptjz6c1kUZ87L7ng12ZMEQyVe7SSSI02TVAXIkpo2h8mzUZI+V5PkaxBuht/83zxhCiTNBeXwEWcvj
BU5i3sr9xuJ+72M9dhX3Yq8x+CY48sbtTV0kj4baV4RaaHTb5JeavV7PbU1TtGksc2FlLdrda5Ujl1O
7eoZFRWhQRTDwJbgrd6fxD4DGiuxlDIYfFKHPCHiaUaqZ1JNX7J3jvGXFu/NCcYzhFjLNwkM4z45WeJ
hyTTD+VEJxpejmLswaA1Wbtj7R5H5h2ZJcSyIS96xWYiWC+vCpiaJw0+Sag/M9krQp5yLwyEN5swLqJ
CvhDt8uD4IHbi4UBbD1ZweSyEoJVuh68CUY2b7QXhvCX2yWAKjJf1rgMV+GGByl8RQSSxwpF+lBMeTv
sLKyRPZOiYl6VcEQz+A3BbYcqqeKZPL8X3rXBmO1HFOqZIUx+k2eDJ25rugBXgJ85LqGOnHrQNfM12t
AeyrugYTK26enO0l9Xluc4fykG9hnyoS8pnDRwUh8/koaPSoHvJQ1h1YKayREWZHFFgzZWL9NeMhLt/
elTND5x0TOwQBuYIVP0pSVngTECcXvGvdckRG6IgmM1altcFC+axbrFL/Yr1bggHkfb1OMrWJymst35
1ESq9Qa2oGt8Hxh/pOBctzGAXH0sTTFprtYAWWXmaWOjJVTlhSUHgpdtdNPQV1X8qql6M5H8cvjQp9S
FSUNgFVBumLBYQaoiUJ/qwd3ZoOE/GdOPyYrLk+Br6sMxbJQRSK9TCPlWT7KqNwmw+PPCZNJp1T0Kir
tDute3wo4+IjHljYlJLz6kHJn6/x++lHufVTSsBTGjHfX0mbDDeg55bT/mHY2YSa+BovLDfjW7QmrDA
Iynf5YOmxM5rFsJjvJL7jDzWEY4FZtYeAeVI8sS25MC3XBaSUCeITQKwT7xbIvCcY4B/FZI+zKgK12C
BFWEV41Rkt/pMDcbYi+Jak7cJo2bRnUiXeqa0ZFK2CO/CeWYojUxrWnXb/1LFapnKhdK9aSm/X6szkL
Xkhy/KW+rW7pUSXi/bjvD/sjAbXW4vIMG/6ln2zuJg/0S83CVZJ14Opsuwb2nU03zZmMCNcXO9HW1vD
Rzpf6dHe4GGpvPlLCX3zpnX+oamocNNRLkXLhaIwuExC1lL0larUH1aWetUP9pRo0E8JXX08v/IfVOW
Kbu30Dw8GerfbPFWMh/H4tDn6NLpS3baldiaKcgowkp9YrWMBYBW4o38hpRbOFTKwe8wuCapX43vEvY
iuPUUvnqnStzsaa2MVWCgHQVIzqorjsGW1z/emkMov0mY8Nv878Tj9w+JxoIPTDy11L3x/tpDbykzun
cvysDuTLWM/2osWsvsge+HTwWf1uTs9e9b3e6n3v+py/+tCfl7OHna2tx68D1uLpz0Mavx9Jxbfjsd/
8/cXob8I/UXo/4ZQUo2am9XIOlVak47TVMxlt3WqDNlu99y+SgntdtT2qaK3L3CIOlKbLWbbTcu8Um+
U5tebi/2+PbzqqKdNswv/WyZ7dCcXjt6/OHs0v+jtaUqoOZqoTUXZ//NLVvP3Llltxow/v2ixxz+qXv
UmLUW9CAf1UXg1O1CU9ntZO9xf7jxNb+aG/LzjRrKmPXyZy9P9w8V477DrpUtGaXWxr/ufx6f6k6896
TP3Obz065/a9XHdXgzn06Fz9n732t9/WNDz1e5gcbj1YWfiDbyDLf3Be9697KSEzN4s2sZCt7N/PruY
fZk/ybrvtvc+m/9zOfTNjO5L56rTVianZldVRtZuU1V6Sjsj9DxUNO2c3SjKoNX6MmH9zulAMVrKldU
Zmh/bttKuR+qWbSrdZr1r3TDlzA0/qh/1ptm5/DQ5aKaEYD6rKstu3zQ/Nv/06R/Q+n3TKLcELi0t6u
PHWbH7ajBXsz2U3MUv/fwLz8yHpf195DuvLlHh9/Y6+/urXPhtrmsrRDOgKbQDeozfOCr8FNjqPmD6I
+42vEkLDyTdx4ds1raIUpoikUE+6uA5r8TuRd6MX2xt/v0uWTlKRxqxfDo7LoI219fX5/2uCqYtnhzZ
J9DC6cDzkWyfHMnaiXS3Dhgpnwy8NjgV9dwbISs/7XZ8THbr22+v4nPvku23tfgAeatKBDbxQkQ8dIj
U1AJb52c33HiXi8soToC4+I3CpOsGsLZP+Cr7J4C7CokDRyofyfBCesUR0tH8ZGxRIsUhVotAPB9PM0
iEE0Ht8QG/mhxNX6WTBCYYeHqC3wyiLLyIFvItfJdhzNaO5Pmb4gwcCviMhzyIZgJRwk+h8WFHP1WrR
ErDH+WqVmNfgj/STEg/OEl/l3AvceMFyRrEfuLfNHf+KzcYmJo/cGMkD0I59MKLUr8jIksz261la/4L
4XqGoJ1wtxPjPzsm8pJsfFwcBus0but3CX100SNd8V0+/mF0LcvEV7pyDXLITb/JvcbvXRAzKyUEy2s
fGl/aXRPA8sZ2NYZo6DonR5xjQEPwI2R/8Zfiq/EQBwUfQELNN2l4XLwP2bxIAl/nuZ6Kj9lO5O+R8p
jgjqAQZxGP2lz7m+PlRHiAEa7Nb55098aQjb2pt77LpBuJAk1zeJvdll86S/CfeQN3wjatwdv+SwryO
ji+HK2VQYjtqW0Y1EtqTw5fctusxWKxnR06AiJEcyieYYSpnm8QbcqgtuCpBtzOTADdq4lzCD+Ts87n
rtogI3HccymOzjkrPMFjmx7DiSJJJeEfLHJi/J2TmHjQIYTmkDqQOS3LB9ST7ciNDzYxIBOIyrF7iKd
7VqIYiiY82sPJ6FoU8FPDIUO7eQEeV/JCoAA+B2Tk30VHo8vFTo2MGGiJh2fN+GQpHnDkVKZAwLUDAF
Q8XlZJ3yYHngKoRGL/ODlAwE931ubgqJJ00hQ/CU/abH+okB3+B9On9/xv97AMPHYPoQqJCQ4Bq9jUK
PwLUgqlsQ==
"""))
m = sys.modules["pagekite.proto.proto"] = imp.new_module("pagekite.proto.proto")
m.__file__ = "pagekite/proto/proto.py"
m.open = __comb_open
sys.modules["pagekite.proto"].__setattr__("proto", m)
exec __FILES[".SELF/pagekite/proto/proto.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/proto/parsers.py"] = zlib.decompress(__b64d("""\
eNrVWW1z4sgR/q5f0bdXW0JZIYP3krsl8Z0xFjZlGwjg3XJ5CSXQAFoLSRkJc1Ry/z3dM3rH2HjjfIh
r15J6Znr65emXGb97907pcz/yZ74LgcVDxkOY+xxmrhWGznzreAtwvJm/ohePRRufP8DM9zw2ixzfCw
3lHbL48U1/lOtOy+wOTTgBZP5VGS0dFMpxGeAThYzAn+NzwR6ciBnB1lBafrDlzmIZwXGtXqvir086R
EsGZ8zywshyH0JANb+h0MCWcwMsz4azbxb3HBisPYuD6eDvMPQ9RW4XcH/BrRXtOOeMQejPo43FWQO2
/hpmlgec2U4YcWe6jlCwiFgeoeFWvo1mI8LasxlXSIqI8VVIQtMHXHRvAZrzOeM+XDCPccuF/nrqOjO
4dmbMCxlYKABRwiWzYboV69oohjKMxYC2j+wtcoEOzMFxDo/oO/yGj8lOMTcdUKyKFZHkHPyAFmko7l
ZxrShbZ+xqniloIwgEz6UfoD5L5IYabhzXhSmDdcjma1cHwKkAXzqjy97tSGl27+BLczBodkd3f8W50
dLHYfbIJCdnFbgOMkZ1uOVFW5L6xhy0LnF+86xz3RndkeDtzqhrDodKuzeAJvSbg1GndXvdHED/dtDv
DU0DYMiY4EiGfd6uc+EgzhSbRZbjInqVO3RniJK5NiytR4ZunTHnEeWyEObBNrHli7wVy/UxREhNXJD
ZEeXrzMHzIx1ChvD52zKKgsbR0WazMRbe2vD54siVLMKjX/8X0YSG9jFmUGtlzv1VFjkY1QE5Uo7/aX
d0hWhKR+OXdNz1FwtKCojV+FVRLkej/uTGRP+fDzF679Vef9TpdYeqDmqr1+2arRG9XpjicWk2z+mJb
hTf/VvxGA2aLVPVFSj9qP1Br9/udOUafO83R61L+ri5avWu6eXcvDZHptytfyeGep+f5HXda13R+G03
eet3uhfiKbiOpS6fzcGQFBDKEOWobtSE7PK9jhMV8+bMPD83zyed/mRAWYtL22LGqnD1H7XfK7817mv
VT1Z13qy2x//6Rf/lj3/nCR+P9Y/Hf2jVqqopCmJzDkOMu8DEvGszu9Ov2P7KcjytgXo4c5BfDaEUZ9
Gae1AUwQjX04qKYmL4Jms1JZ0sKbiTSPJwZoXs2vFYX6T/ij+lNCn2QjDSIEE5XyFkcTAIqjgJPTHqo
dLq2nvw/I2nJjRptIQ6JnJzMDQnt92rbu9LF0erxymx3excm+dEq6e03hV+12s12oWMMpk4nhNNJpWQ
uXMdXJQ5POn6HiNFMZWdFPjrUuwTIYsmrUULDTEXOYtnRk6VPJELsxGxESkzzmjShkik/XNTrTCaxFY
6ESQxhk6TTDAvYCoQixoxKCkn0SBlWDGpkaLVEYlDchbeqdAErQFTzqyHxCxixO5dCbNoBVhU8gqfxI
xi22qF9Tmb5m0lBDKsIGCeLTfPs29bLia+mI3Juc8HLHC3MS9KF8I9RZlUNUXejbVwZjnoFZGYQFB8Y
b2CGEpZP5L1Icj8n2sWRlKD6nRbpecORFe0oXownoryGEV47eQU8RP3UCf347wZk84KMRRUNOHygPwd
0yWuSrs9JV0smB57UiA7Adgu/qTDEzjtwWci2321Pj4AUWUuRjr3JTyVjVmepRwqZBI0woKF0cY4UTa
OnKAQNqnH8osMzlb+I6sEWjzMXFwc5PQqrStKFxQH07QQxK+lPXM5Jv0oTkmyU2Bk+elJHI3ToTQbFD
NGPDkRPy7SxrW/OGfT9aKidn3RDCUo/EHVlELycJlXyXPS4FeoaWn0XmIjc3jwUsE8MEqpQypVEUEij
TtdrG9/vzWHI6oNdUmhRgILNVGOJeWsd35Hnx+TJcN+T54o6j8dHP7ZXniYQLGnvr09ETkvH9srho2t
vVMJsLNa7hCTFr1Mpzq/Q1yxMMRma4e+ZJYdgyBXkEi4CWfh2o1wJBH3v0os+XgesDDA496+OhErpmf
q6GUlhKtD7PmjirYL1uQQssZSwzFFOhIxaQO2H8Ud79FyHTs5xjTgfajC+wLXJLTLZavcENBHBqd8LI
z4mpXsIZC8xxwSE3qGBL3s/+etEWMqMULcUb9sA7muYAJJ2m+B/2cnXIpI2PVB3G6R/KINVr9y8duT7
/jUClWxvDdlj6K0ydYAMvp0QH3XJVirDeRfTwuynEE3DeKNduFRSAfEigooQcpCPO/rjbGyE+RJ61WR
33jo2pBn4u017VnznGEC2DXOj9ASp108t2Pd49yxbTyRT7eAhwaR2CkbUH3FXgs2DL6tQyykrrUFe72
aGjvNQC7xfGdHGlv8TRqIiG9zPcCe3ZJykCvteY2KCU/yzjcHe7mKWvE8U5k1DuYZR8FzPOMgOJilMP
Uz/ARqctzY7zMWRPCZACd6fB0QNftTgaz4cwtPvyIT6fF/ygc5kQQXPXfK0LQnssGTHbg8K+49iBSyg
oybIgbvl/f1sUFXW0kzvkxbyaS4ov2W97UxGa4YeuO0/2mj3owf3gGlxxa58MBmaC4ml9qhmKjLXin+
ombgS7M7mrQ73QtzgBN/rh/c6+QWPh1ur+0aXjwOUpdNF0po4Z8/NYrpllC0YFcOYmBjeVEIkQ909tN
hQ1ePsrX+7au4ayhc64ww/EHag24l+Qc59VQ+KPFLTCNcSluq6lukH1QKc3tylG8U8ZlM+JBNiGWw+K
Kml04QsrBIkCYF5kNWYESIq6ffzepUsiqcHvMXS4cEYu+qcLYkSNAJjWD7PkRjY8STOE+U0rITXhX05
bCP47HDZ98RjJ1BK3eP8EIwOnxWikSipIF3OxRh95dXhh0tK1xQMeZl3f3bxmHpLqaRXOfCT3+uQ4OM
cYGcNljtKT05WNdFHJ1e9vDERU2BM3sQHxR8bxMwWatWaNB28JKgNK1oBYcbqSkTTOVaAQB/tsJ+HNG
4Jxwgiyz6wdk4kRYleb90SkcXJb0ZTspGcQc6meEj46zlL/QEZ4RSgJBVG0r+5igM008R3TRV2IU8QJ
Yh46taflGWA2hjLFgNpXQbFcXi0GAW+1phWunqghalNy05xWoUAqeq8c13vIqc1cBpeV4yKwk505Iq4
ExtsNRjl56eP4r5Jw51y8GIFSgWNxaxmHP6+5eaNjz7s9irc9n+jAbin8xrlRRQmG3Rx9Iows7YyGta
zpNZlvuOTBd3X6Z4yL/2Zc3XG7dfrxZxX2P/w7PLNOU/COAnEA==
"""))
m = sys.modules["pagekite.proto.parsers"] = imp.new_module("pagekite.proto.parsers")
m.__file__ = "pagekite/proto/parsers.py"
m.open = __comb_open
sys.modules["pagekite.proto"].__setattr__("parsers", m)
exec __FILES[".SELF/pagekite/proto/parsers.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/proto/selectables.py"] = zlib.decompress(__b64d("""\
eNrtPWtz2ziS3/UrMMm5SI5lWXYeO6uNvKvYcqyK/FhJntmM41NREiRzQpMakrLsXN399utuPAi+ZDu
Zvdu6ukxGEgmg0Wg0+oUG8uLFi9qQ+3yauBOfx8yNOPPDNfP5HffZxI05m/puHEPR+sab3rBpGC555C
acrb3khoWriMXUfseHkkbtBQB8+Yf+qfV7h92zYZe1GQD/XBvdeDGbez5n8L10o4SFc/he8C9ewhvLh
0btMFw+RN7iJmH7zb3mDnz8uc6SG87eczeIE9f/ErOLKPwNsGb8Zt5gbjBj739zo8Bjg1XgRqzrwWcc
h0FNdLeMwkXk3mKP84hzFofzZA20arGHcMWmbsAiPvPiJPImKyCNlyDI3TBit+HMmz/gi1Uw41ENsUh
4dBsj0vjAPpxdMtaZz3kUsg88ANr67GI18b0p63tTHsAMuIAAvolv+IxNHqjdMaBRG0o02HEI4N3EC4
M64zAvPGJ3PIrhmb1SPUlodQZo2W6CmEcsXGIjB9B9qPkwq7pdozjydIAz5gUE8waYAX4ANBjh2vOBZ
ThbxXy+8uuMQVXGfumNTs4vR7XO2Sf2S2cw6JyNPv2FmCeEYmAzAcm7XfoeAIbhRG6QPCDWp93B4QnU
77zv9XujT4j4cW901h0Oa8fnA9ZhF53BqHd42e8M2MXl4OJ82G0wNuScICJhN9N1ThMU8dqMJ67nxzD
mTzCdMWDmz9iNe8dhWqfcuwO8XOD85YOi5aOwa64fBguxRhKDjoBfb86CMKnDsgH2eXeTJMvW7u56vW
4sglUjjBa7vgAR7x78M1YTEDqENcOjKAjVA5BA/oIZXk0T9ZTcRNydecFCv/BuddWvvjep1eZReJuuv
ml4u0RmEDV+LJbeAkdWlAKFklB8qiono9HF+DJw72B2UD6prnUbP1wsAD1cIfJnoYpECWqIX2UVECtR
4RaXPPDDnIWT+aq3tL2l06ox9vvKncUggWxrK7bYFoPXjYgvfXfKbatl1ZnVsJxGDDyc2PgTmkQ8WUU
Bs/5LtIC3jd9CL7CvfifG+x3XEIG92tlvXV870O+w2+8eArv3u+P++eFH6E/PQKMfTr/YjlmldwQVms
abITz/x38S9guepGK9N7PXsEZpIAs/nAC3Go3qLAMz84hYQKMkesC2LF/UcKe/r7yI2w6VTkEKJYQTP
oG+ABmdxReGbPQsYLJcne022yst2ALI93tN+COLvTmzc1WgRrP5U7PpsDbUVh0wxR1AxcURn6wWtpWS
h926yxYTs2RnCOM4EoAYmYEZdC3eHUic9tK+ItcD4fKz6694N4rCyLZGYQidBA/QJgjiHywnR8zhVWY
Y10BDnDCqJdkoUwEK5qChfL9iWiIYG6huG3mK1DdLR2uHE1R8xAwgXjpsHblLUOmg+lGJgKCLgdM4CC
jkUpDlQogJJd9AgQQNTzqDU0B7OO4OBmfnyHc2CZRGt3c2GtSZfOh86PTO9NPZ+Wn3VD+9vxx+qmuaZ
f7IGkfdzlH/o27wy/ll/+g9js+A+P7yeLgZSqc/ADifHEQbV8Z47AVeMh7bMKI5DHLWPgsD0IrubBbx
OJZPYTBGKSGfbt17XIbtvbc/7jX3X1d0uPJk9SRygYKz9ihawdPEC1QfE3gPnNgGhnHEzCESjfkMCIg
1avROrzZiM2xOBgr+uGpe0++IN27dZHpjR9a/f55tf25kPv7Nqqvazia27NyF3oz1zrqjtzTZvYu716
DS4yS2FOMTfkOeHB/ZgCXUidy14A9bfDU6x2OCUJd80xjCDI2HI6D6qQMvvXuig5MdUYqWpEAj5gkCA
IPE1oD6YwTWHRmwx4Pu5RAm9Ai4bM8pQEHYNn4Ui8B+Snhgyzlw/kAE+P2UL5PWc0lWSrH/q3RKuV0u
NGB5+SstkqsOiuSvtGgKCxANz7Z4nDwkPB6jVKd3aJc08ENqIqoDgi8Zu9PEu/PAnlRqiYpmsJrhzbH
rg6mm3648eLfyBK4v2d9XYeLugCyljuNkNZ+ndX/HQrVs07djkvAl72fuQ5xZ5S/ZAJDQ4O/cyCMXLG
0kpQ60kr/SInwaEw0UQUAZgGDLjpJqcTBZCyNdcrB9wG4qLSCKNhWWv0RgJG1Ccw0WGy8ig9Z9Bps1A
hpPfGQQ7MGy8mUx9I4lKGObhZalAxFFoCOjhxx1j9GNhdlIotBnd3tpEzCpwiTx+RjUt+ej6jK4h+2o
1aKmYExUVKj9WWiA0j72DR7HMY6/TMYz7hObaHIeghGKTI+uWY6lkDJlJp+u8HVdYKyvwlFXhol4B/B
5omklO+5L+zjF0U/G3qwAkcwaF6fSitPAwNgHL8iYsNjTS3EhfuctThOYXP4g0+SSV2INH1NBQJ6pdd
+g/9Cmvs/qIVjuAmMr3rrf3Ypb0mZTGNWV0Y7wUPkJrX61dy3lNJCjVQkQQSlIGl/hEjQWn1z4amlr0
HjZuIM+MqM1BG5JTZOqlhKNaJgcYutOLO0SbbB/Bxo7m/DADuoZZk9nXhufRW+hYLlqHkCrFbwjZk6K
RgWf0pGCdRqslnKkUz+MubARWiWCKOV8U2AcedyeefHUjUAOrtATN6wMJBgCNawoqbxSdQrvlE9wBLb
oh3HvvGWYdVQ/dRYOARzKy+Mj5SiIAeV1I3VrLtl5ZoF55PqnKijDjFIn4TDM14otMqsR61qGqZAZbo
r9KHLnc29qk7MgCaTNYBBN0gqWdM/anaUs9yymewr772RMKNZJZISJLFTV69KVRoKBYQVn4uD8Cv40O
7I/8gfqo85GD0vRnZPpT9MpTqIsnZRjDwIImOHdVoz/HaRML6SK4PnGeEwO2Hhc4TTkWE6rbLTyrR0L
RaIVWU9rnOpJs/X68dY+2HtFHe0YzHKT3FZzC6zVSK1UWASgCfBN4GpzjJFZmK2Cb4wqWRtaQqxSBgJ
YodScHdt6Nzk4XyWLENftr4c3q+BL/G53ckBzNokOrAxRsPZ7kiMUYgVbZnPdAb8Fq0cprs11QY0Dpz
6p6nuyosCO22VgP6m68FTV4FCYxZuhDhM3WW3q+XNgOZp9QdYi+9iWMC22ZloxCmPDIa4K5/Mqvqrgp
oraqewzmNaWihz5QChy+gWK/FugIL8IKPTrESjSkt7OW9qPtUGDd7tgEle0IpMTJMuczE5r69PO1u3O
1oxtnbS2Tltbw8fXrIbiI3sRGNNRcp5IKdIkNKMumXh6zQ/QiJTrxlz3Spl+XWe0lzY68/qLVDfGiik
Si0sgnPxmm/ykeuwGqBXMLutiH6q9Z1oG2uSl79ojHWW7EG65ivyI6ARZybnBzbOquVKzz2eqWbEFkI
NYH+SP3XRKNCx0/hT3vndxMTgfnY97Fz+nQRZ8GP/89vys/6nOmkowvmS0Z3OzipKY3YYTDMDO+J03B
T4EciVWjCgwmGhPbk4g03qJav5cF/9jt3vR6fd+7hom7yNARocXGgL8JhC9oz5AeNv8DhCHZ4DY3vdA
6J2Nfu5XhHRMgwBY6BB8fGW8wk+TOQWD4Vvo3YxFKE+DisRThTtPNdI3VY42VTNeKfzA7JO43WGoL85
xtui6JQsbGPoNZrZteTOrbtaQgSgjbm5LeEZHIo4oeuPCmlq6kXsroqiyZ9EMMBZFKGuurv8gnAQCsu
sifsJ6F/jdgkBwF/x/GkOBgu68iGMvmIf/uygSBhswlF6EsCKU8CSPokx0rryMIFx5DdnQSgQcqwT2o
1BN3g+j/KpRPQbhuiQYmNfR7QLIWon6b+c7qdVKnSs5OkLdqX2L//RCBDOh4xf1KtQe/1O0V2hnp00b
ZvTHxI7QLTqM9pVtUedoUhuWn4FQqV0BrSbLuNBIB/UqGiGyuUYp/hVtwL3BJnuWc62m14zr/IuO5dr
JsE8ufA18W8v4cYWIakZDNGU0Kz+P5sgzZPonxnKG7sMJ9/3QNBFNdXkRhWB9xEdu4spFPoOfpsrUYt
zYkm21jHYtNhQZGRPOwjsQ9t5sxgO1iyr9PR3rNDrthnMTrT+YAKZ4yrjtJb64jvpkXKLMvKmgmGLqz
LiMF2RfF8aJewnmWPPxf22VP05yCe17qE57BgV0zDD+8/AheM9HqOsmFxRGVCaKm4g1JLdjv3C+HMut
kLzW0TMmy1uyB1WuYWFmFIJrGa/aZgyTWshYZRrFFNkR6CrLIoe9SyEozjAchhTGdhpHifj0zk773ck
A1OJRhLykvSuNJbFfDzZHvHCKspNMAovmhMndCGZvzXa3AE0Bh+ISAkh7K3ZolVTpKo1g3aQL9S238p
00Zig8Yx+mxm429tKdg6po7TLygoRZ7Xb7inVGXQZO9EW3+7F7xN5/GnWH7BpKPgeIn0ajEGXeaVcVi
k0yk1EMbktdZXdmCDiVLWCYb3k50Spb5LVqE6awFaiNIHNrcO6H4SwNmh+LRxtAammlqhyU7m9lRFV2
D6ulXczj3j9Ouy3hacLfuz0EqrfBYFVhGiCmA97wgDUbrxt/wmovwA+PHuBdxF9IULg/q3DNbsrpvo6
8mDJ0KMbBZCWck7lgTN9/YLHsPQDB4YVB/BcowOCcBqJgA78mkUcqd/LA1EakYOcY+DpBxNdh9KWR2z
fIUemANihzi6azSsKR7MhOuTmdOL1tKMXLGuAQBbTKkJbnAdv/saTbXH85nH6EDhr7bzbW2U43ksuiE
aawS2WOS9uXGXkjgWgP+nT4YYxLLrcdondwSCah0n/q5otc0u/abVrKrH21FcMytj8HIGnaba2RhS1x
1dp726ywBTeg/0xsbEKnd0bIsL+BmAEj0USqKPycFM+S6Sgir7YmhsN+4xc3SFCsyD0K9YoUodisIMm
ZkyNaq0pQvXPZ3qiKuiuKGiR2abEDyxF6uZyuolKQe2FZrWBqA6UHAHY97cQp7Acd9YaH52dnYHWND8
8vz0ZmYl2J4ZOf1IrBEt0Mev3Ko3BAVY2Xw4f4ENZZCQmfMErqwlE7gNA2t726aVyFUT1ZK4sJg8l6d
KLyhKnyjMq0e7VWL9XSz5/J6rwc5f3AQGm9SoMKVZxYv2g0ZaapzLB9ZB0bMkUuYly83fNjKVAQbnaq
qCfTfbGsYhpBmaVYK+7oCfNsu0IWblC3VRklAMrWsHZRtxQhGj0fpPGe8w/j0cmgOzw57x+1CjvFziM
0ELhLu0cZGELGwTSaJo/KfLHR/sC5NGwaTLPJbFbo+adGB8BEigA5m8akpqk1c7V32uVaEuyRP7+BL+
onO1TZtDDDsriZGnvTMJpdYDo/EEXJ9y+TOgOFYJh7XyY4Dp2CjGhKS8DeuM3ksN2crbCRPcrTjWDc9
l497XQH8XGqJPoRtfJwOzsNXmRhOmnIAYaZGRnV1qYPUpyI3YZ6dWmKZVMPdF1tLssWwiuTTUhq1HGm
3Id2s7GfklY3yGBQSNXS1Wo54xiJs7NXzxrJTtahL7e9CBmE4AX2XpNQRyelroDvlrQ1MzoVDu+Aehp
Ys2Zwv6tNsnCzbVyeymZmsm0LeEauvF3WaAd6ckBAvGrCIjWkjg3y0saiH9oMf5a0dch2FeM4YD85lY
6kmvEZ22rszWMmet66ZzZRpL01o9UDKqfONjuT1Fm9bPR6Ejbte+ZNsEhu4+NOqPgt9kLJ37CcbEqBG
XnJmPvfwsemgC0uHtVatjP2L4OZYfpiqvnDeO6v4hvVj9Kr8rnKJf9tBTpYJk6plj44UmO1ZZmJh5Tk
aCJL2IVo5XYm1O5sCl7vKiGVS7/MbmI7Kn2xN2drDnMEaOIEav+tTkNhYijAWD7mEfL7pe9NvQS8Qzd
GJyQJGVGpUdNrwaCAY3I+6qskpSvxeDoOuyK5Ac+BIOeIM0aNYffsaNzp/9L5NBy/vzw+7g6GTro8St
JhMaaTRGBiiDNCpGadEuNeTkcwE4EJVf+qCLJeAvDaeUI6bpDkAs0kE6nH0rDUGvySMVZg7WJOLp6wg
+4F1QiGgweMgDqnnX+MKUJjqiWjb500Jze2ARjMIsEWJ1OW+PwGGoHvP4vZhMNbzhZib3u11G2xMk7n
2vXI2bFBcONflNuwHrMfr/DjjfzYU3+bjmmPZUZfwDvdeaalSmO+amkiXWcXxSO+p+l/ttsH7PxyRLY
raurdLZmptNkLLXiigQ7GaaTqTCNKqu1t06zo5HAurvq2UbtWkZaWydE260xgPX8x3uTd4NTnTf1g7R
pnfbhn0hSDhuyXQW/URcBs0B0NPrUUfWNNXCPeoClWmEXFYfmejHCmqpKz1IN8ILkkDdX02NRaZPpUG
SIvFgYS2ePp8R0NIx+bNys8yZcr98urwwzfEmh4ZLwFt/ufPLq8+/wEzirw1Unv8PDy4huYqmTl6HrP
j+vrGMIfMw9PChH8/9x8d0xq40RURqMeJfw3h+E2JWmn2WcuKmOOTAYf8qKAteeDlvEwKw2sNd/7wjF
yH97iVQp0g4MBJXKnnM1WEYWlblbJLFwHDdbasSuoksWnrjRwO03U17lYTyBOMWiFx1akVZ09PZKLY5
mbNtV2ltK0qeBvXdcqc13A0S6P3JQno9hOHtQzd6HL6VLiAKEnQpmaPOuQqNxLefj1K3BEEkYP0icqu
B3KG6KdIGmC6gxTSiktzzI12VI2HljKVxgm4VIjQlyUgI1xG4ubKshfWACUCe4FRdolUKiK7Gf1hCdu
3+kyzB1uadAZPAyrMGMgpvlZ0y8FEYsvc4foqUzuW2Ss9wJEmaitscEHMrSpOngkb19vNFu/mrsjX9c
6bVYB2NYl5AnZlFv763j46exwfNy/HJ4UjCBFprwRZBKzbeBYVW1PVftarGY6zuQOX1lb979u3W/Fny
Oxz2unHdQNKHVkFPikp+tH8quf6EZrykonnHxH07PMsrxZUrR4ib48K1NL8x2lHjA4HOMFsDAS46xDw
yqx2jNJ3TolqYKoFRQVVIwfo+KTKfg91JOUuwy8aTjjRxw/c1qpSL1ibbqXIhVooPaT+V8tp1oXZm5f
qFrj6Qo37mNQkXNcUDLFPQyXcftNE40NL3lCNEakjtjUDqNzzWyIovIABsUoclWNGb82o0lCej95DnP
YZh8dcyuLvHAtqcqRbFUmg1Rd5kH0xFeNlO0FfXbQpinRiUr5PSnPqhejw0m3Z8S00ZEN4tkxngYgtU
EqVu9PlQTAqFacj9i/A1nt6OSKyla50O072jtLj2n14vdiVHZciSCRvYTmJpQjSiYrgMgmuZXZFjm4C
iIe1pQ2QvbIZi7nKlu6IVqWPQtq7AZW55mVzKp5u1Cazj/3Fnj6lkeYh42XEdXpSow6+/HHL2s3Wii6
iIcrax65tzAhkW9di6x8ACCkOL7MnSohUhFwikRZx11M0pxzSy8RBRYP3D+M1SE5gl1+eE7aPEchW3N
xZ5VLl1qxeMmnHtiEIjOfXQ76IhSGNvosvHW94K86iceVUEC0JHzHdyfcZ3PuAsm4uAdmHuKlaTjJ6O
mgmklCBpXJuL9wF/wjXqUU8EQCinmEF4kxvHnJ9xusF7ApXiaH3MLo6pI64gvzH+K0i2t4wCLGY/HSG
Xip4TIvwbErX+JkdNpnkxCEYLTEWwmEBTfDq+DQJMPZUjcxtSwHbI7svUxKgIoGep9xVTJ7MdLa1jc3
iRaglWib09jWWSENkTjZ+E05i8xXhQruDIiVeLGY56yfa4bHBAKNZbi0m9m9ifxNWfZGDtbXAvW9gF+
4EcyWnWZeplcDGXckidv/llg3Fhe2BcsVXavlAwxxnR2/1xcEfeNNO8+4WEeumBTFRqE/3ZXupY6wVl
4KSX6bJ3X4PAmJd0nKbDgBq25mMjEwaz3xuLvRvqwmfT6K38Y0azFDauNZA9imKmJxUBU7PUJf0ZXOW
8XqitHxAe11fKd4M43JwNsG2Bcxnjaz6aRp0TeS2CM32tigLoA5uKxoNbQeiUNmqpRm7+YGtC3wrZVn
Z5alP6gka+eRZGwahLTsjKGUJryny09nO+Or52Q610b94fiw3+uejU66/f455a1P0Whv7r+tDYf9fOH
n+5+aVu20d9Y9HHSOR+OTztnR8KTzsZu2tJv3zf06c2rH/c7wZHxx3u8dfhoPun/HKu+Woe9NH3bwBs
6diP++4nGyewDcoTND/3F6ccHi1ZIu8BFy5tRdeNMLlEXT0JcCJx38BoETgZG+CLyvwL8o4uoMhoubS
tTHEr16vEjgO6WOEjByklLEvkmkCKOmchWle9F4Q+l4wseJHxcy4r1Yvs7dd3P7kHn/uHSic/BHPAGy
guEE1NtwDHwrNo6BCwwqJHKGRGbfJPQ0Jxx1Lwbdw84Ifp66X7iwPcAeYIuQuWvayAexANMMxoQMRTa
yq4kYpyjRUIuJyw7zVxFEfO7d1zGNdxbXVf4nfikjgHzaOttXMgqtGwCHxgU1UvX+wkxJ9YU/0NE4vK
wmWqg6bStzuRYpc6iJShzqZk78pGcR0lMIaIsLhJ3t/W18IgzgIZMQml7ZVme8VbUpbBJB3KFl4beFA
yNyoekpzA16f43LyNiMAyGI71v5m7hwox9/PhklI3IqLvNETPBHKSpUkMUFMRG3gCL74gWpaCTj9776
8Qp/rPlE7H2kEyVRMNizQjEK/IQZjAiKX2UYypIKFDE3ERGKrVKlMfJjW8RFBRin2Dpy15bIo6EapWB
IckpA1CALb8NhnHKD4CW7DHATAAxukaYPQo3ipEJo05oI+FpgCRJbqvqXtfRstfa9beuoM+q02AGIFE
tCL+4+W0xlKlhb+419umwJeN0G5xM7owuFKaLkpBFssWoTNHnJeDjtfOgdjkGigHTJz7hJLSEzjGnWS
V2GxM3mjmVFsWlaSGPCziOTU7tONnlK5Z6bLXK6uJAtlUoIIzBnHLfg6D4F/gMdUaAtZ7DC5yuQpkIj
M6mMZc4Fn0buPDEAyT83wGvxDUpjvDgaA4jIBdK1mnsYTCepuXRpW9G0qvIjypsHTomZZk7MMdgCNxe
E7EDgas5S1awXLZVMPytY5XXpb9aV6KNeP/DkVNGBdorywWToDVvLExgIoFUZai5biZrKlkKgGFJ9qi
jK6/1UsCvuFUUb+F4Jm4rLzkz++gYUUaggReNFUZ7cJg9LvCbV33+NnxxFqrhJurEKkJFs6+D9+xNLn
nlotl7LlBKqi+dSoCVm5xrX+0rkJGhq97r1ehtbXKtnehLbZxK9Q98DdqYTqd37hAd4z55K0k23xEH+
LW7w/IrIn7hFgcGC1e0ErLQf5FLD1eFOp6vblbz/kYxQHZvA1TLz6MIgWD5zj/uzmCIaGNpZBCHtXsp
VhTbrDfgOAF2sp7iCRBYhefUKyHPVFMf7pxV1T1TdN9tYo/XqT/RtNLx9pBPRYHuabQY+fDhHBnz1en
sPrBL8P623TVD1GUhR9x3Fcom6etagA1HaujZnU13QKGdrGHhn7i1XE8T1jMl5whAX4iKvOhC+Z1pLs
TcXPMIrKIWkShsZ3CcGgY1zt0W/ZOcfKT41F1cig5N/1kth1Gn7EGcW70pNRSSii28ACaO/t8C1iNp1
mjFH41C1TZkTiJEEFVOHI1HNYByvrnPSLEjHIminroHQjV61Xm0j9OuGH67BCcvkaxj4pw2oeutab7i
ocWUHKYaYnWzCIDvbRdFxg0sVTOtb9ze6wwNkKn5XChFTiryR4zes/Ks3Eoc48PKMg+WK2EpiYeKKuQ
0qJZypKTDjXNF1z+QRQ9b8kKrywGsQXeS9eHkub1QKKVxATsagA1im5M3osgIhDfvfFrq7rv4thzrlx
QZOCUEnk5uiVGaiPh4q3Fcgb/BNnZXB0BBeb1O71lvxraHdFKAJx7kMmKeASSDb1Li11zQfDTyBsGrq
UT2Ijhsz2tuzrVUyH++9BcvOcho80O92fkrvkjMhvNUDoG6eD01OHKFVF7CFTVJyqZAhEuvGZ86AL7G
ZHrtGoSTYosNLRXDffM4fzQ0z80N4JGYg5Rl4AbBvRkTYZCYqMuotfaRnI0OvnxWEE1Eu2j7+3nD6VO
ze/6ERrW8Kkpu54pjdNs1mhacFJe9VagIvuWVbWEK5YBiNOvfua6QudMMFmF7p5vzrBeW/6vsv1UCyQ
y1Z2BWhetq0BkXzRpvB8cpHjUx7ekaYUOg0WYweDFUQe7wE5MBIW8/vhW848V054ZsmvXJyyyY4h4EJ
LmOFmQDxvCPpaTydYxVzoUS1xhyvtRchPodOWWXto9I7GCr9qWzEvyLsVpJZhZ5C1qqQ2GUjkHuFlFK
TeDnEAaSxizKwnFYxuad6vWSqAijEC75A5e/sXee6sn6lKBiWZ/uYinF9NQCoEf1almuUkQHGMd1KNs
NIo+xk761TUdus/LWscj4veLNE2txBCr+Wy9XKBECzBxByisZQCrlbjarz2eUdThNgVGQjaRJlz2EUo
61PWlTlDZcCL2UHtXIwlPUveVqKIqqaq9m6zoQzxKqHxSs7qJVTe0dk+8lKzpMlhKqQTu7GhMdpRjh/
jYx1YqfoPiMzb1qUamrbE4YjSukAZZ7b87JHynhT+hyGUbRaJsQ+VdgVWL0cEoGY5przwrZqZdOy3ku
FOgw8p5Dyeco6BU/ONSzHmbEYTL9L/Hs171cL+sftzH9JaQWmE60L41Typut1SoW6/Hd0ENuqM9+yNK
u3C/NSFyZbuZlZvfpLwFGk+Vmm7x+GxVO7/2+KqgXC
"""))
m = sys.modules["pagekite.proto.selectables"] = imp.new_module("pagekite.proto.selectables")
m.__file__ = "pagekite/proto/selectables.py"
m.open = __comb_open
sys.modules["pagekite.proto"].__setattr__("selectables", m)
exec __FILES[".SELF/pagekite/proto/selectables.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/proto/filters.py"] = zlib.decompress(__b64d("""\
eNrVWf9T28oR/91/xTYpI4nYsk3mTVs3JjVgwC8EPMZMkmKeR0hn+4Is6d2dIX51//fu3umbjYFM3ut
M6wEj3e3tfvbb7d7x6tWrynDGJANPMJjwUDEhIQk9nwXgKVAzBiwKIJ6AB2oRRSyESSzgwVP+jEdTwO
d5HPDJEl8qRK2EN5lw3628Qtav/9BP5ax32D2/7EIbkPkIgXNJmBng38QTimAm3pTdccXcZOlWDuNkK
fh0pmCv0WzU8OtvVa3TAfMiqbzwTkJfxF+Zr4DNJi54qOvBV09EHAaLyBPQ5fgtZRxVjLhExFPhzUni
RDAGMp6oB7RdC5bxAnwvAsECLpXgtwuFwBSxrOdWooFFFDBhbMXEXBJoeoGT8yuAzmTCRAwnLGLCC6G
/uA25D2fcZxE5CQHQiJyhe26Xet0xwqhcpjDgOEb2nuJxVAXGcV7APboU3+FtJinlViXn2ehkRC4gTm
iRg3CXldBTxTr3seaFggHwSPOcxQnqM0NuqOEDD0O4ZbCQbLIIqwBICvCpNzy9uBpWOudf4FNnMOicD
7/8HWnVLMZpds8MJz5PQo6MUR3hRWpJqD92B4enSN856J31hl8I+HFveN69vKwcXwygA/3OYNg7vDrr
DKB/NehfXHZdgEvGNEcy7PN2nWgHCVYJmPJ4KFHnL+hOicjCAGbePUO3+ozfU1aAj1GV2fJF3hUvjDF
PSE1cUNgR8fUmEMWqCpJh+LybKZW06vWHhwd3Gi3cWEzroWEh6/v/jWxCQ8eYM6h1+qT4nFUmIp4XSe
TH84R8agh2K5WKH3pSwlBvBcd6v2hVgPLxwENDmtl8h8AIqmebCg1iZHowjWnj4FGd3I5mNLykSyoiq
97RWXc87H3sYqxgpjf/2mjQcMAmMB7ziKvx2JYsnFRhwR2SDUCvruQBkv/r38XIguPAgmer/RCTfsyD
kI2RVqZMovihfR5HLGWFr7iIvhEuGcSlL9vRk6QCicGYz0S6d2wp7XQxAJ/kM9f4e3NtjZW0buCdZlk
zk2UNs4UEMVxfm+E2BhxLpgh3ChufqohjEq/h3gRMcBAvRlkZcyZzTdqG7bJhd5Gg05itRT2ezvTTJi
umN01NRsZfZ0MlCgd0aaqSKS+pajSVqvb7lShQbhpIMLUQkZa2DRtG6P8KuLXE+2SSyy6nofMH5+HWh
KsafuMQt+uw3UiNUIbhPk7SQufSYtS39JYbPxZzT2njp+vpsQqaqDC5NRKjiH4tsjqRZBafMQ8dRJs4
CqAJV2I5UXaxogpNJyVGxRPUvW3AlWUbNkbqGvF1rXkDb9qIAJkht7VJ10sS7JbsbNIpdgVCVOR6Ss6
+KSJ/JJ2IM+kZjzQYzEo9hr5irU1NtMos8uOA2RZV6Wg6ZtL3EmY5rmC6syN8ZAf6s44yxeVjE0EmG1
kO7EPDbf60G7LINrNOoQauML7ch71itITm+toiOdbNTWlWc8fJRmlMB+WmLzftft0wpt/Zc/e+WbCDW
3RgB85T1KmjdnwitW1DjFDfNnWbl76/g+beXxw9QmNgudY6RwMXOTXXhlF320ztwJ4DbdRnHfc25GA9
zaPxHJMssjJ7liGmkXFt7dR+akjYkVrfEGViDKEVHG3dkKxrmBXOKIfQGqt37+CAOt8ldpmKyRbsBLC
/T4wpEPT+l3FZ57EWpi4FYGI7JgdDHjEslVmqYz3QkZ/GU7pQybGKx1zGWHGU3WzsljZFp95suI0N+6
SfUnAPyURQDvcGfbThfrgC6R2TgmRzHyPX7hduSxsP9zxW2O7bVrvdvobe+eHFx975CfwDvQM3OEaW1
KRkBae6XSc/DmPRzjh+Ou0Nu1VsH9mEf0MG43EeqNq/aN28BJU3E7OBboFdSuQN1MSrJOld2zJ9Uq1Z
3QB1Muh2z9eq1Vot+E4r/3DpfcErzWe9gt3XycX/r1fa+0965eDsqvt9TnnOynnPcYonk1MsiEwYDlv
bDvNmjoBeEEj4XDuOBR7iAhbQk3ZTeQzP3SoG/BHs1wWTKm88TofD/vi02znqDrBKCHMIwVO+bdnvuZ
w7v9j2daf2z5s3DtjXv4wieqA19VHwZuTSl9x1/qzdcNS77Byc0YWBJbyHmdZBWj+2B2ADnHUK1PdPG
VqOB3mfrTtkUrKojjigyayEVMVaioFgW3TOo72I/u5lD2/p4YHdyti/Y8py1hiZ5jJlpgGkelXh2MPd
10GIKfFrPBd//thtweGM+XcYFhF2GKqGm/YUz586U+54ArdxwJkEnOKChcusd0Ig41kgMjVLjnAl84Q
/Mzt/0S9kK0qnGMrIrKEy9jVmz82crclaO3Oy+IO3kA2ZZtVWyQa6ObCkAUKNS9Z1YczNOYbc55rdx0
PxBzwUr/IYdmo2Pq90JK/6eEJ2Wo6p8KY4Yh5s4WltZEYrLdlFvAg2jxUbcx0ni+gOsxzbtOq29Vp2x
sEuWCwkdX4qlCaWTJQhEXU4OgLL7DLNaqTDYzh09kckDSdVLQv5MuAHgetnsSRCE5RZTJSMkPfHp0i4
Te2CS973rnkmY5C7RTNyLCfHlPnYnYp4kdhNBw+wCW5ZafL1Ly51e9C/Glo5wjxp9D0X/nhwS/d00zw
ztulwGGMM+nRp1kKQsWTW90Eu1q0+MJbUOiG/R2sVbTja47q8XdHRcCgWrJLfQaB+Y6HrypqoTJ80B3
HnlItb2xBXyc8XYVAbjZpWKWfypEupNxN/WxHEg0FzFO3IkSD/6ZOV5X7F06RdstPW8vm4rlwyf4FOX
6aVZbPUbKsutyFukhJ0VtRUXLtltcCLpgwdLh8Vk1IFUGIhFQusrMQcdc5Pni4xGJGrBKNrhX3sKqES
vQpYyBRzNpr4jc9r+ObNkwRwyUxW6TpV6YtyqTyheHYTWPeC+e5zbCzbft+qv8Evza6+kqmh6qv8VnC
FBcML+W9M0LS4Z6KG9ChILeRKb24rFOM8C9da6RK6W3+WitT6hAemvmDoN2SKoUd3hPL5RWjN1kNS0/
R1+/2f9EPN++p9W/lS1p0VTmKJmvDpyE1myYsQTj3/7je6lxMcI+AF2Su5RHfP3+7VV9gVuPg1U4jH8
33UAT0qpfOiQAT1cdnR6urayec89FB+HIcvikdZuHwlfw2d9/MlOYaeCEEwX829CM0nXkZwidmZGFvr
1MdAnccR9E/7340C5RkfY0zQ/zzC9E0Sa0db/oUYccyKF6ieasIG3Z+7h3SVa/U7J90P2C+PzdDY+p1
V26T9Wrtikvpxu6IPC0T91JHg4Ozi8EP3iKpSVk3NgrSS7DlVWBt463zfCWHQPSq69t3d3Xyj30RA/6
7QVbpVr+cX8BFTdYklDEtwPd8C8v9XPOEQC7L/Y1gb10daprH+G32vuHmCL985/gfMCkHB
"""))
m = sys.modules["pagekite.proto.filters"] = imp.new_module("pagekite.proto.filters")
m.__file__ = "pagekite/proto/filters.py"
m.open = __comb_open
sys.modules["pagekite.proto"].__setattr__("filters", m)
exec __FILES[".SELF/pagekite/proto/filters.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/proto/conns.py"] = zlib.decompress(__b64d("""\
eNrVfWt320aS6Hf+Ctg+viASCnrEmc1wTefIEhXrRpa0ohxPVqPDA5KghBFFMABomfP477ce/QQaIGl
79tz1TEQS6K5+VVdXVdfj+fPnrev7OI+9KIu94j72jtL5PB4XSTr3xrMoz+O842XxLCqST/Fs5d0nd/
feLIbv8jXUigrvPppPZnErmY/Tx2R+56WZly6LuxS/z+PiKc0evLECnYet59Dyi2/6r3V2etQ/H/S9n
gfA/wrjSnJvmsxiDz4XUVZ46RQ+7+KHpIjDxSpsHaWLVQYDKryDvf29Hfjz5w5Nwts4mudFNHvIvcss
/Rt02ovvp6EHg/Te/i3K5ol3tZxHmddP4G+ep/MWN7fI0rssesQWp1kce3k6LZ5garveKl1642gOczl
J8iJLRssCOlYgyF2YrMd0kkxX+GA5n8RZC3tRxNljjp3GH94v5x8873A6jbPU+yWex1k08y6Xo1ky9s
6ScTzHNYQO4JP8Pp54oxXVO4FutAaiG95JCuAjXIKOFyfwPvM+xVmOq/2DbElA6+AatmFpoeewmAusF
EB3Vy1ABl0vrI5cD3DiJXOCeZ8uYkYUGOFTMpt5o9hb5vF0Oet4HhT1vI+n1+8uPly3Ds9/9z4eXl0d
nl///p9QtrgHRPIA4xhS8riYJQAYhpNF82KFvX7fvzp6B+UP356enV7/jh0/Ob0+7w8GrZOLK+/Quzy
8uj49+nB2eOVdfri6vBj0Q88bxIzxOLHN8zqlBcri1iQuomQG2Nv6HZYzh57NJoD6n2JY1nEMO2TiRY
Dmi5Wcy7WwW9EshS2Cw4QKeh6hf6dTb54WHS+PAX1e3xfForu7+/T0FN7Nl2Ga3e3OGES+++bfsZtgo
lPYM3k6fogL9WuVy6/FfRZHE9jf6kHyGKvvWTSOR9H4odWaZumj3nZAHhaIBVzsu+rbR0BF9VZ8Kb8H
POdvlQKz9O4OSQ6UEF9FB4AOANLmEvQ7mM1BPF5mSbE6oVdcLI9nsNmj0SzOK33McgOAfJqlRaqftVp
EFL3rJVC6Wfvofjl/uKSKQbflIVk6BLSTTQDSLDKgvfOCuuxdwih+hVF4BVUPcVGh1mB4fvgeqdoe/b
i8uLoewK99+nV1+FE9OeD3VxfXF/jzB/p5eHw8/PX0uo9PXtGT08Hw/QXsFAT5Iz35rX81OL04h99/w
gYn8dQbDpN5UgyHbZiRaYdId05j8DxjVGGp2DLpUUlYqPk0uQuXSUBV8G0I5YFmQIVpCi3d+J9D+l/3
s9/xbm71fyfRDKmP+DhP5/GtBnIKzbW5N/TwhfcxBlowB5RLkabkSzzHUg9xk3Ygzi48GmOnPcC8dD4
GqHBOzZaEvAzkHorj6kLNHLfzeDWe4cmXp95T7E3SJS4XgsuTv0N7sQ8gkYzhwhWpAEJtAkmNQ93fx+
gzPf4Ol0fMLY2hOq9Unh7A9NCnfrwk3Ot5//iXfpbFj2kRD/N8Vnrxd6AjRZqtSo9xO8bzSRkMIGwxX
OBAGMPE46cYD8Z4MsyKAt7s7JudgdLDYoaQaJX0K7nNYH2NRUsWw1nymBT4HNdTTsTRDM7Z5ULOxSzN
4951tozFhCRTY/D8yCNanCd0sOiX4UO8ytuBLCOaPUKAgwLm/7ENVYIK9rrap79BCeGw04HeGvfF40z
gvGgzi4tlNvfa/uvRmwHhuTePHuPXu6M3Xe9l/nqUvfFV5/Cf/zL3A++l1y5vjRt6wHseNoO92cyGVX
/O0rvrLJpOk/GgiIplLoYzBdZk1qP1Kc9nIicKnlAxPXGPcZ4DGYKF8o+TXHBscKwhtcOR+NDnxi7bS
7BMQtEpf5I+zX3E+Fma9eTLX676v3dkoz3xGQgYMXS9Wwuv4DH7ah5+iQuknlfxH8s4L+Q0EN1Wq8Sv
NHoiNgENniafEaHa/l92FOsHfYWfkib7gYmAoxyLE+jwHZGONkMxUPCFp2t3+aDoPq7CSfoYJXM8ybp
FCvuxmyd3cxhRFquaVLbjcUmgQcDnTIAvxdLwC4pD/0d5mAMjVLT9rh+omnKAYbRYwFZvtwkUnIpP0M
NAglS/LYy0/lXb7Ih5CgIT4WWDcg2uYmSWBTqqfZUAER4iLnW8aDKBIw8o632aF2K2XnjMqi/nLHdEM
+hgTuSWT0Im6MSGAwetZAwtTwgwoygHVE2ZUWTyKBsk1p0fU4+hHPYgBI4Ytmr6BDRdAEnnIOY84KN7
+A9aBnZ2nAH5glWKkasWgE8vQ3MmCD15+FdU4PSybY0ceOK26MzN3m0gZoB4VaKh1gwqEI4pTBbW7CX
EJpYIrURD0TnVAhWfxfO2XTzwesBQyEpP94CyIEUg3bfLQcdFmUk8KyJ4D+dbssipYDyX5L28eU2Aqo
CA0REgOhKC3WJLrMoxHcTEakca3g4t1iIFTnhFG5NYaEaan+VwVWlzB+tNX3lNlZJFCFQgK3LkzKubu
zSzBoUCatzPsjRr+7ySNqISHQURD8SF9G4OvMQE8EhtYAHTh/Ucqm7FE985CTR7u2L+eQrUkHl1EOX5
fbfVkkRpANsHkVduDGB0UTAEARFmP7+H77DvoZUC+AdCfpRekIki7M9gY8J5q6CpHTeNn6TMI3aY4qm
AF3+KZ7MQObVJOvdZOkB1QPqQxBpWTj0DCCvkrh6XQOe1GJsnJC7zdoC5Gd97TyR9zYjRS72psRAvYD
6gAshjucGPeWIbAY4lC/EEhATFkN7qQ/E+yqMC9qu173wWAfzAQhRH0ZALQg0+G3wLcVQnYLL37+PPb
X/XD/+WJvP2TbK49b63iLIDrDxw/A/wY+fwDl77REZuboMtah+Ox/Gi2DmL5ndLOKUUiCDYeHSPMcjm
E3t0ckLlCWT3J3eCChlQwDTS8R4kxvuAGR78h7S5R+JmiH/agV44MbnEHMLZajAP8fyGX95CXYDQcm5
kk8mEKsNkIWFVWEzipgCqKHfrvaaO7fDmM+cEHthFW7rDTIsV+MB701N71uJ8NqErc9iEPEi/7my/af
uyhCh6090/uK3nBdo+9GW4AFYvj8fIE72c7L6cEB/YlpSbRhw0wWDGwxcHF2C5QpSgvBBWezWc4BaL+
cI7nM0IAKqmiLWIJy1XWeLtT7J0XvQBcXnPj9LJypbSQCgnbgX+/4T6LCROU6y0A+gO9C3G50BKIw/l
LXqo2M6IVsiQ7uXqwiiEysAQbYECu0+sjdhUrjSNibXEWg4iwCC/93dOuFhu72XBWVgSPTBDqLoY/p0
E6rxrLTmKE6JB4Cf8/ybhJfe7JbwgfO7PEY4o0iaNcm8/sErC8WcDPJxMcJA1EB0SiVJ+IJ6gZNkM/3
06SmbxxtCVIkVBN5j/azrj+KQSqlI8BxF5pVL0KZlNQlVF6mGhH+ls4lvL+GndAv7Gle310xA/mVSLV
Wfh3e8RfFgnk/ki/AQMQtsXMHZY8hO/Ot4+HMJZtOjt7/G/oLVusoSOCadKQGlZQ8zixSwar8XUKy5W
QVSjutaj8N/haDVMJvaiYnHJa1aK3ghgt60KFgAVPoVBtQ3hmG47gBHhbS1lZAQRVJoMj5O4jfJElE2
GoyWyVqzwaLVsAU72rSzTGlMj6sSf8Rz3+vTBev0s67o50mNu2T46ZI+hWtCytCesHCkxp1J/o1pmBX
EYYxPOxvWEfbu2DdooZAcAOlGKM0mtYPqO42m0nBWnl/llnA2oWNtq68NiEqGoNTwjgaNtwgvMgf4Wz
ZYxzaRsehHlQkDRmrQIBvYpKVYODoWHli7nxWHe9qU6DgSdT7FvlBjEBV7C0VoHLYXfjAGyaR5mtATh
JAjH9/H4oS2L3HRv+chqkO9n0eNoEnmwYICx1OohgDqC4xG7JQ4/fGuL+1hSC6rU7H8t0yIytZkdOv9
6pDLrahkMjkQ4MvFpl39V5wfKsVz6B8JE8cWmKvQYRFAEhAcTAqsrtX9rvTHg3hwgq4Zd2PkzEK7AQl
dVokclSph8HI+Wd8iA0cgBlSX+GuA7nuKgHWtk9bBDgLdaJZpta5lytU5iXS6zdAxyHa7nVZwD6ktNW
Ma/gF1bLkBaBKTPh+lDT+jZgdoPmYTlpg42fdCi0QgkLfpR0TtQR7pK+iIGCS87RzHyhtEK5DjA+mRG
x55BNwW7fkeS2nIhJDsF5xGZHDw0H6OVEHtnqE1fAfDZDIAiOQ3wqmzOl4vjCIfytyVIn9EozYrQph/
6jE4fhmI66CpCM1A7F7/6arR1ZU7nn6JZMhEFUd42ZxTRE1uS86HbCuPPBQpFFrBjWde/FeRm5oJIyy
RBGn1bD1MpOjM8HUU1QwOc0ZaaG/3UZ2X6IAW5DBBWK2aNakZfdD142FwR2S2jwwPAWDgPTo/9ktjDe
whI4iHQ8InEZALZEvJmojFUargbmbWulv0TpSj1H5n3A24a184PgnUANW/pBogb6oG41c1hSibJDVHw
TX5nbX0pK0NTsBKW5ppPHbFwljRrvLLui6qirPHyRnyRvJJLd43qai5V1VlL0toGwfRtH6fqGDa4H3R
AyiFYfodh0hMlRvIXKUgmFjRGGbr8EUJVuVN4fSKlQz7+USGW4SdrHTtE3WKko1G24g2UZKS/VFLEBj
uqbRENyYH4HVOLYHMvN8m8aH8OCDjJeojqctZ2/aB0vdLEu3QQyDjuUcc1KyrHoRWXdAmU2epRAxfSB
91bg+36ksV2DNjmwBt4NrHirRJDvp57a+TgbC4OZsI4Bo0FLd1i4jBdSvQ33oEGbO9dS4niPvFNzUpJ
7S55BUsTb2jEGpbM2Nh4XDdtbvfGFqYGX7ri1Q1+RvyuaxIqW77VqEuqIQIWGWiiAJaWozRnG2gUIjG
lFh2tMIvnqZAM0WYFEXxJGvZkgrYDYRj6FZRWR97pZBaLE+9PhoRtK8M2bRDvtW3hy9E08VOtloNlQs
7SZj4tll/xlkqtJ6/2QGBH2xhUfH3C7Uc2FsgGSvUYzAEwhzO8o0PdP91G8GEcWselEgosZh4I7Zuet
xd07dXcnAtQQtd8wqJMYEh0Dl66hovGebKZaL55/6KjAnhQS6tn8HPG0VGSyXCyz9PiHhcZ+MWLX9FW
D63WOsRfA3tNk5ffLwsP7+KN+1XDXgV3qq2atcX4K+Dq0R4vnXq8IDC0aDxGoRaZg7gwcU1AN4VbxrA
akdKSQTV+1aMXKtDFE4NlQrOv0kCY6V8WiyWefTfvrq8vh7Cii3Sex0LFdLC3B5MOU18hO1Ra3ptcA8
nLp3G205+PU1Rn4FKRMjSerKlqLKhSuHYMrebGtS+RmlFd+L+4O/JZEl3US5NSj1zVkeGxKzYLEcr8N
ti8L7C77a409kD2s74DAA+EqygP7+KiDSLhImgEuMmYsIswpDrBdY1um9FGHuWbrKhUfBtseG3nsuiJ
O+hurrVu/q+iJ7kGznlyoAhPWfOseo0zqjqtmZA6GmcPB7qAOpO/Zn+dk5bU2pnWFA/w9v1tOlm1tdi
klg2pdZsrAdEVGjepyUDx31KumjqzLzko8cAByjmN4EyaBKEtu9RqdGuINCngoR/6ONM/4SyoaqOETp
N/OKWmHTq4pFgoIQW3JeyrP8xsHRgvOFCltmaTTJ6jhlMwCTnhv4Oafxs6vsWANMn3zy8uLrvePqHer
cE3u5B2Pdo6S+H7ZzZ6IKYe8enQ9sVG5FoBHm6PaACc12Kuupa8isef0GaZCYAy8ZuYalYQhBBZfL46
miJfDn/oJhstM1kZ+nSPDhG4kbB4iJw+WbhQ32l8gWJsyyXmfzUumCxREPpMrYUZ9LOtrvFY7DJN4uT
VaT5LF4tVhyz/TWaQfQNIgSf2n5enj/ETWnEQEhqwknlewHSQke4s+nsyRxaSCgrD/FGM1o1xWOqmYY
GEwhE8E4ppnCsqgpNYvX5X2l8y/8LOkq3opIalNu8shPIEF+j7HrZhoghqNIejFXAA+BLlSigQGPuC9
sFx/+2HX4anF+ruIUuA5fJfQ2dPz722MLYJvN7Ny/y212v/df4yD3o9JU12qHmL9cIHCsOE348oy3Re
sfdkB5iXdPoCrSyyAChAk6K46HwRj2HOMyUZStiBZY2GxQLvtZafZUV+BeSs47169YPW2uRo0g2yHEz
/IB0/5MklmSvlaNMPC7nM6DZzOUeumbxUCCiW5JlE0OWppb2ii/BGMOgQIYAChMoLKkx/6RJM32Pwm3
eHv/WHg8GZWrOFqkR3eMBsfV7JwwlHg4RqsQARlxUgWt/j5CCm8XAOFDAr6G5BIyyBkkTphtu7vLr4y
+/D698vqUPDj/3DXzuenltUO/GvfTo4DHWts11sFQ2caxrFMaDDyrOX+TN5Q6LaUu0YpkaV2nk+w8qw
5ljb7wjS2dgZDRDp+n1KXCFBNjYzzEYIYhpNffs7KGTfvJ0ct7FIULlmJOEq7jIFI0mW7Em8x+guGXv
z5eMozsR1vyA/4zQjx7mYvHsUGEGK0BErR8s5vB8SzjQgUsUAF3bEXXGPG4X0NXi+XdP7cJgt5+0gLO
04KIe3aHCstH/YC/cCbOV9khMXA/UvV8U9tHMQHrSqRNmAMZqldKmF9LvlIHxH+t4GdhqciA0r27Iog
iAt7Rp8U3eMdOs+zPkuIJk41YNMPXJdigUFSbDYUl/eJtoMI/GVknEWV+qy4jpu2LSSMHojtWUb12dK
umHxeSpEkV6TnLIZMDG7vcos15ptlflq2AzD6WyZ30tlB9pSDSXWmPoOYo0yza6fYK32U5QUTVWDrvu
69YT4bqbuQJDxTkVehytuXR+8WZTA2XB6IUweNq1sclDUfoXlsqQQLLm2u0TjZZOsa9imw+uqt+r2r9
AVcv0e+bqdwUnJXiTtGTJKPeLt6FCm343OANAK2uL2bEDh6fnwqj+4vDgf9G1JAGELxwstEMAJdZJm1
4T+DteMglVI0gWJt4n2VGILIbYrLnteWPeIyd0cKbTmUxucKZAvYZhVxTV3AEVmSeYsQAGqxamMLM/9
/14qy8VU8GPJQKkreuy+7PNRtIhGCTSfxK6JIVkdRG0yn28aOisB7E3k0ICSs+CtvDWWkOUEdDx5S7l
xu1oBsbZt5ay4afs45esHztqw9SMnx0jdtARebXtbDVHJ0rK2py4zyw1sJmvtJf9sXgpsYiu5vZ3kJj
aSW9lHIv6XL+0Y612Xly73tY3u4ZQQS3Bkb+fx05CueUFYnaVRgdeFwW5bXkfCMirZNZ1N7KKVKzks/
mf4RwBKd3MWKLpLFg2/VoBLAqZVuyfnoa7M/i15MeRu5Yzpb3ljj05M8z/+dSsX4x1FbtBsEZ80DkrE
e8DFlNFrtM9hgwdFxdUj6WOhDfhyZNglrEZfQuVKHAIDnkxX7F6p5FS7eiCNQu7iCXVD0ZLHJB83bk7
gmMd6Y0bZHY6DSg//yNtYPdCqKcEp3MB5jXeaNJrA1CpBfWwNwVhXwnTuyltheNuhIjfw55audN3aLy
26Ezb5j2kx8SV8QnWCws9vDTVidfreX1yDiIP97ZQrmY3D9NFZJuTtk9O/vO93vasYOLcV+QcJIechj
hfCn0ddCU1AGJmzwTNMRcsUe7w4AgGJXPU975B1P4/pIxqBcXSIHP2DKNhDRheHMd4PqkVk+E2ryKrQ
wKlGveGNTD8DFhVM/3JbrWqsK1qe/CFUrFy5fqo27CXKUuUj64+hdP42+7lB17jet+vccbSq9m0CD7+
ga1jtm/VMm9BUZAVH47bfSkMPHArN8q5RLbe/IxOdhE10EuwuQTZtdGz1p9PqxLA5YVvCIcj3efolLK
8wRtz5eL/S06I1rdMlHt07HHcjARaiw+4HsNlgF6ORZjSZUHQTb5rEMzgnKLxLqHw0KeJJlVX+T8Uql
0ZwI6oAQcFDSv7av21a+y0GqgdZOV4MzqXGUKWW3+fO46Fqj4aUC0pg9IH5mqMf+zrcb1XNVuIsQxaT
vbdcd8Wb2L+0fe6X3xE9dpapWMgYFskWWvOJzx0q28gwfJA4MyG2l4AM4uItaz+ER76sKOAAWvXe9oe
D68PrD4Nh/+pqeP3h/Lx/FnwtHjiMIb4lJlSXtIlFaVpqo6NfttbfZB39ie7Gv3kF83w2jD7BdqfoNt
sL74MzNH3RtN0EdyMglCSUL8Yis6Em9DHYWuOw+CKk2tQiLafVAHB68i9+NUyG9OisGTIECgbwTxPCV
R84P1L+2zKFjiJz41BxGBOxBanbHrNdZaBLUKBdN9ygsh02wWeemloMFhdu8aRs/Kmv62tdUeq5B+0j
oyp2TL6qYzGAgXbWP5zh3WZ6xy7wHFdmbOiLHNLCjfZ5cS8TLI8y2TFvVWp1RYFdGedynM42A8AqFxu
CMh7ZBIJWGUn/dDRrMFVspc2LS6T3rLreRMRAt155T6AU97SdkiwegmRT6+lrXVHjfyDrRBs78pajL8
mvZign1QdBRcSvVpN+hQ4gkqHxFRUlrxdz3xpcrcXgGjpapfHWV8DG5W/dXb6Bc0JzTR/SfxPgSOcoo
MiPUTEEAG3jxo/U3oYjPEnUuHjUJ9Nm4CidYcQ0j5d3hNaH2uHa3A0d5snnwL7S3UXsGeoJbdNZq3xl
ZYftlqovoxpPLuW+Yod6cDmv6IuXVs2lUvWK64Yf8WKLhy3TKj+6I0Kn1Obsamgr3cXwDMWjrFjypd3
c48VyWoVmS5dr2lrFQKgvvjozFfO2TaDEeuu6T1rdtE3LH7bhYTudLdrFSF3SekeMNtjqynCdnY9ZWu
iW5N40DEhc1t8Vp4ytdnfHOZ/lvf5tdrxj3zfufM+T2kQaQI2esoTVGhnaXFvY9lB4E/Hotbcf1Lowd
7/EB9r0vq7xvRbTL6wIlePzdm7P6KCCw6sP7+Qy3rP9jol2Oh2Pm/yXXZZ+MlYGrhCwVcmY47i0VRAN
hC0O3koZ8VyZuNENvTZUMq+bpYdqg50nP6rbkaXrZsMo1PQjn3os3gwHF0e/9q+Hb8/gc8DaVQuAuls
welB1HplO3Mxhrc2FtaRm3L+GqVHftqGiaiLll20qm7NufN+qfXs57J/i9g+jEs7+P1mbPQtJjyPL31
2uSZ6wMSaHuBFfiVmW32Hf8tf1U0XXi0Nh02ea3eVkFUPWMwnZdpJpsApuKYyLu0ZozBt4eStsiK3LT
SOGpgwY2rV/yqo3ex1v71ZeBVxigFsV25uId3Gfpcu7e3Q4wWkiqzwRCVTJ5FPVmnhTy5aillkUGuLv
IRo2Cd4pmZh2jBtwpW3/9G6eZtjVWJ5WAjYykmzX28QKUJDOacc+05TxxXzCgVNv/MHpsWkijFMnp5t
jP8rSylr4kh/rOiwuy1qIRtVK7+iprkPxlFRDxtGA3xOBK/g9cFkSsjsVF13nQUFOGVaI1dJwsHFzBt
YCu6GGb+vCfTaD12NCpDf3i3krP75nG0DzdQW0bdw9vg9arg6wcbTcBYNHlNWiRzxVKUY7Ye5TzLbLO
fu1mSauhLXe6563v3fwSvMIVhsmZpthJU12VlTpeHKX9qw9y8ZwQA9UT8+i7C7OVFefMIpfHD0gYqQg
SEV3ePtGXnkUpD/K0DLRGy3vMMapgIE22DhItKvNceQ7TFlhn8ePo3gyQStoiuWQU5i/KHlkRRyShdl
KRdaMVYPeAvq0QBEAPTjyfPnIxNt7f/0BW9r/cW/PI6Po0Lkagm9BcEOKyUxh09o4uR1v/9Xe3g5Ouq
+0C1RbWhpWfLnZKp6WEEmV6Q0tqt7s0JU7FrnpqlZvHV6HX7RY3VZDXElBFKlt1XT31ozhm5nhK5vJU
sdjVIZPX7uTf9lEVh3K63xHB6SVw1DM/XRqUvOnDFU3cTqVbB2Zw6vfdnzlqkuFMb7+xQlIeS9zLeO9
XcXP2EQVWmo8dduqG9JwUXaDrcD9jz6+8P01YGQtCUWBFWCuBJg10qMtMCr2A6ZOhrPWEwjAh8VqEff
8j1e+YSpTjpGtlZcGX+DggvRMgAy1s+8966km4FTGvffRD4xrs0lj2StdttS2dN9hfRlihVr5hmncmM
/UeNWwtoGORG6ECtdzm9OTIft5VIyRyjOsSAbVknKrHnGrFEPDeFOiI2azvG4M0sm08jsr4AVrJmW/j
QhjpW4rxq/cNYsF1BGfgCtm9xdph1YNgV7doob65b+vBtfiK+tgttkGDf5R11lyB4fcJXLrRpeqcaa8
He/y9PyX4S9Xh0f94fvTc/ng9Py6f/Xb4dnw/eFf3LHxnSIyBYkySFy5B+5QpRXYyKRB0cBhdv8cQT7
voKkR8npr7yNvg41XAwcOxDP8YaoXBKgldOQbLYvY4ZepmBQUguDwqIjenGIAJwHjCX7XNuZrhw1OqF
5Q5mGtHAWvvb2SSV0phQH8rQ8sXyqLfdkL/+x953j7vbcX7sMb+K6UxZubs9kxh/Wi1lym0YVJUXDgV
fI9LIqaYk9WuUq/A5PKVEf1xjsAlqtLviOGS0vXOwh/VPFayOOFEtbg6jxrlSKFVln+JJfqJlPIfoG5
bSgCpuiBd3V9zfcs8AdTTFEapjkm2viEAa8ngDhC2I3F5rPAsfkQWsoTp0r4A/sRjcpg91CwfqBa6Mq
LwSeyFdDUlJIfoYPOKnRH4Chp40l8jCc3tFK3zgDEbgC00eU0DMf3aTKOlYmkuun7lCYYKXanYFJG3D
Dq5j1OUBU9RatyKyWc3WsIw9z2p7MI7zURQU74Kw8ew3OPMlQC+zqeTE0oiKbwoXbw0BkFDxXHEOMlb
ZcNSgs0ruJva7NgjIoUa6pDclXXjjFYg6Y18QRr444YFlfveTIx1jmw0A/khQg1KLQdZbp6ViPa8fUw
krgeyxd/enVbdbveiKJfEEXPLXquYK7jnTam67rTmqr3fIP5xAdaEUFHnG/2jQV4kX1HXbGzjaGDx6k
beulqh7okmyArRvWD7C3tmWltcOdDi1Lyq2+6uf/6Gd501ZuG/nXjC74pmlxiOjMobHLVrDZFpWFRzG
wbf2VpfLEAyoriKB0JSP1kkCAMCgnUEfYT50ojr28kYpg+4jGaxJwF4TFHrLOmyZoSSzK2X/z6Fl5Mh
DO8kB49Dr0bzWakN/yeFa9PGdrOkJoi2EWRWUTuFkPDQ0J+JQLiDy6PFWzUNTEQFE/yRRxPApYOmzk4
KeGyaAvj1HMZfFvG7SjNsuWioJarpFRkPKnIBEGdDgCgjqRjgZHAhIKXGUKJ85ZYRb6MnV6hOmqZlrP
QuT++edsfHl+8Pzw9p5iTpFTV8QDwZ8cbLcSNIRd/++5icA3bXPxC65PbwLBHEBg6YAP4TxGwEwscGa
aqkKHWUAKu3DpYPSZJQXQAuU3qRFCKIedQBznm9XBZpNcCA8T0PkafGaPE5QNbecl1p5isvb3wQO268
xhNixSyirgoYcNK0sa7Tl2ufJqx19cVtunEAC0lDI+DEaWQwXLlgpfHIjPFzv6tWSN/GNXU+PWtu0aT
xF5VTlwBx5sZ1OthhHhiBYR2RCqRdw4shne7ep7QcTwqiD7B8YYqujx+1nj1EDgv0kuLQZy0tETy7jD
7AMb26ihN9F3Kwb7uo4w1CQ8YYAN11xwjwcjIam39fjq9ghk1ZVnBsx2fDo4uzs/7R9fDo4sP59faLN
Id4MvKr6Chf0SqV6c/KHWiQpeQ0NCRR0HJqiiI7lbS62NPMSUWnjR6OZj1q9grqgY1gJt9O9aAFpXrY
NveLSasfZfBYrcmgLazaYZt7BiHmKxcaRrrV31rhAuc1akqTWw0mNxU8ddsV1nGouMkI4nS6XtbmX/k
YUsra+o4XIXVfFaBnZrAyse9C+BpM0DUrhnhe/T5rE5mp92IE5YivA7q6oq1aJwI5gxu1hjyaJWZ0MG
6S2YwuIScs/VUZIIr3w6LQw8FV/Py/Pnz53R5rRLIWZfX4lqaQv+qLFvzlTLv3PwSW5w0EQVj1RGtCI
i82IZVGUIh5i3tPDjSJKrGQsF5RS4saL/xDTl8++IL8po4Q7/EzE4ex3mBGfXg6HEmauR0muUNQHblf
Lr7Pp3u7lyG5XrAWkG1revhZfuX1LvCnG7eF9QTHd263vXZoKafgVbeL2ar69TkwYVZPKGMnVCwSprn
6ZCY3Fzn9IuKDkUVQT24n0m3pg5HKjxPT2KdSr5tmDbooELcF6PlCtS7NFUQf4Hvb2thmskGLRDKbFv
kHxW9q4NUCfaFZoYTEfOG2XwkBGJbIOozC4+tBsHGd5Ustau7Se6ucR3FfXvbN3e1WC6UE3i9oNrpAv
5c0pMMkMCSz3D9YAYwTRzCC6UJvIDDEPiaS2hxAEyrOYYM+Yokix43zD/JsEl0gqgvkx87TJhNLqWdk
nFGkBSMfZLxDgXi4RW5b7z2LUJp1iulXagBKyQ0Leg5mR27opUbzgwSUz6GJPEVZ88/FDzhEiPywHaM
57jju6W550uBLi+RfqqmH17hAlTeCGC8FvqtyteM7xBL9KtRPBRtEbaocJSVWbLriIbq65DQbNQpsiV
lsjTqsEIlF0nYPeEo3hh2ycKJZM7B3nyRKtx0MkEfE2HuU+mmhVe6mIRizarGuq6JEqLIvzSSizzwGM
cZ456hlh0/D+SXH/DLUzxiS2OLhVK945A8OuloNUd9eNX/vyB3WUmGL4HcUOBEkCtjvC1e4s1JIeLeE
bGaRPO7GJic3PtwdZa3rBnV4pp8JDF4nE5iiftoK9Lxftzbc24WUZIWVNtb45B+3PsBD6VXe/utSko5
cxBmTZ31hVgwEJZVpHBHDeqeqFIaOrwVnjRGzTpLnQbi3NpI4qBz5cOc3NParQ3FFPOI7eDO8hWZt/d
+076YxD38s7YsbJD62LhlRr1jWSBV3Q7E4WJYws9MXOb9gPFiEPunCSKgr69KrngveZHHr5QLCVTCiQ
xdbDUZGmG0KoojWwiLKOlrSRZN+4Gd6K7hGJH7/QuPi+qM2JUNMsEhOxChnBpOnoEh5jg1wYkAJMBay
2EDbciSBabxFqevao8npD5DgIK1rqI429r+L/1rz/++sbPf+7RUu/thVbnO9PMvOydp9hRlk3iC35za
di55ZGSEI6OVmnKm9avYpSh+4PjsmAsuh4yKSwa7r7DcQmENcTw7JzTEioNGLb2s7gJJ4Rw7QYdj+va
ECE52SYDQP7a91N95r6+92WmgDi7a0HKwcg2G58ZBWUMYxBzXuUaI1wNpKlsJSdja0OOAd74yny+HJ9
zOIW2TpmwMrIQWnE56YuBB40zsVXaq71sqEn1+l3Rd6DLFUbdceq4X3lmaPpiu8xS5x8hWm9dLhlUTj
3VJLC2XLUduQ+twrE9xuCZ5ntR3VHLoVYOT6wR6pblgHzMyjm6cmO09MB3el8K/ezMjIsOd+B/ev8w0
QHzHwf0wE7IZF2QbX6Fpz062GWYj4DVentq1WvgW1gdEr/HMpPypHHKl9TVXmVt7EKJ1iHIblMo3ZmU
N30F3IPyyZrl6YfrCO8GznC5nFlySEyJicU8IImH5Dk0875hm4IrpkUHbDdanMeynbGTjyJ/1sT/f9Q
+P+1cDI1qBGD0ZVO7i0u7GxbhLyRs5vj5FLMPIYVmxM06y8TLRGRo/yVWq0c5XiMYnt4JUZXTTdjsUQ
hU3Eh70JBkYyd26bGEgNK4GmGj2hJdBOTorRGTzhlIZ9B9HRkHnZRZQdjsvOPY8BrePpkbQ+cqg9MVV
yXfVLGkS7FIxQeuzT60tb1nZTtsu07848be/1FRj6XrCRoCRuPsFN5rupO3QL2HY/LPcmdB9a+cZ1vD
CDt4Ya+US4YUn6JQ3ocsBxBzyGJiBPJ57dzEHo2OzQBHigTDDiO6/1vIb+p0QADgSHzFj+078OckLO5
1ILj2DFP/othOv0Z1tpoGq6kVfeJhpCzD1SaVgxXMtqojXG+gZjZO9os0vb1Tm+CgsBxlfWLoL1Keqk
xUzf90TjZ54k4T8i+bFbAXML1IMT1AMS8Qj4KbSxCcdre+Sa8V9mKEGryjAWw5NiDrLtU7WrY3dnG2s
UduWZddK2tca/6CyNqYkk7wgQyzCbunhpJKAhS4e3vTJl7JMPddtaaPIrjeSXu5kjasykj1lZGyGKT+
eYn82w53He25ZxJkBBKYbJno3XqRYKE0X3jgqxvcitAvih6cPDjOWnnK2M+yqiHlGy6o33p6hBAS6gX
bHr00r3p0fnMnVQtuOzWHBZjAc9o47T419/7PHbiZMVoTXhu3+bzih6Pgg5a4YblRQSLv1sBjjSt/XG
s/w3hMY2wVuduEkwh+0fM+fPz8UgWtEDgMyHsG5z4k+cNI+6LbgW+hWVMbWASY1KYbDchJwAKOZQYEl
3EboqlK+MSgnFjFDYbjMn3fQd8Bwr+AUHXaVLYLwKN/AddF3zoAdeHt49OsNjfhW16GjZBjPHT2nKe4
Z2a65d8S+Du1I6HbwhplYQit4A+VXJ4jAp5/0fdMBVmT65bGGD/HKsAIwk4PmN5NbreSqTfKK/Kc7r+
tWEc6+SZy9zWKN1UbSU9gLO1Fgon377L/M5R2fQlujbMdYS8OPjCN4CLzGDW0SSQHHVYr+8vwwD9IrY
dEaxIKl5HpID+ibLqeyYdFj2brVrug/sPgPqmNUXNtO4DsQWJ7SEiFB8RjYJwRthsKyuknf9eCsdxRO
xJh3LiuXB9uSie5LxARaOyI6zl4pKek2EQRd15ohu4R9XDrCS2rVS9FeiSyKthgnLSpRw9WGYtJq4Lw
14bCWAUtWAqLgw4Bt+oSFqYw+Fnl/j7N0h9PCiLHo1Fl0+5LFsyQmPxdygKEUH3nLiLucmvk+8WaFHE
xEqpnQQ6ftjII7i1skb5EsYpJoOnw190L60lCGrrsUeJ4sS0ZQgc518nSLmM2YA7wTcrV84mscPD9wL
KNVi8934BEj4oo/8jUA1KPTS2RcSsktjs6ddA4tQOfpdfhtgsU0KvnqY8UotymTr+jat8I31RKYnpg0
cqbnjllA52xD7QqcZ0q3x+oWzRuy0ogHSvGMkNcxKiGTg1boexztqHqovMHwA1ay3Lr0YirB2D9f5v8
EMuj9dS6+6fzU4og3IrGLJyY3W3+y2ZyNoghSAqY4K+bg3LHuLdBGhE7nPBvgXHKi4JOkxUR7QIwoBZ
tUXJJ+hkYbwBLijSPtJRTgfEterGeSoskEucmOt0xMCzUNPHRX6JkVl0lQMsRvB5avrnmoUSGx/cv8i
LRNdTJLHIf0/OK8f9O9tepwNgAR5FWc3uI2v2dZ6605FVH8wGfdCjMsSGlQnpw1B6hrQnBBr1cLy+RY
7ujKJV/JFBFoeM/Id+Ws0qmCMjwHHC49eMBsxYRYyFFlRNQAA4O3uS8eZ064bf/16A1P7+vd0Zuu9zr
y7rN42nu+i9iw+zJ//uZl/no3evN6lL2xdTq+uHZrmzilxBARFVPEJ6qNmBDn42gRUwfbvjmz8qymMA
l1yklrLsxBqrGf5mg6ThdhjCXoX20ve03PT/O3TDAa7GXFA6Mbzvas8AICmfmt7aFvXkXL893esMavj
sX0GYNAWd2Cq6xTeWDVGBxhKQQHZ+dScRjM2ISFZF3tQAmhI06CrmZqNB1xHrg5u3mNvDKKXJulbUX5
LPu1dD5kFcwonazs+K06Bj7FAYjmHmb+yebRjEi1JNQ5a8HE7QvOo1ZICThP8WhnEd3FzCeRWQrUoaz
qSSHy2T8+M4PAqiPEpNclW/egSoDp08pHSEDwsRaPQfBCRo/jQ/EsCAcm/BEamTb3jSbExauXyi/0qd
8Lu4UB2hhQavN4cnrZNrRiymkbcybFxGNTs8igwuxiQCfOfMKu1Ub4I9RMi3UKZLTI2qBQSlbhCnJSa
mNImcBVjLJrcvHGIGRC8cVO1AKHcRHh5J7GIsPULjWE2QiTqTAeytnapCPgkTM6wiG1CH5hxaOcEhkU
GSfjYzwakJWX2JNyh4rLBXRWX2IKspm8ZoyQXYdpQesD2cXWpvpNztdOoX5Mw7PctjfrkEUcfiTZ2EG
RfXER37Gu5W+NUGJ5w0LkN12rqMyw5SpPi4alhC4icFW8+UwT87kOWVQEaZyizxh15rfTq+sPh2fDy3
PHgavniL6Vh3Uj0OfWZaWg51DYbupO1ln62elTbYOHGih2beMYoP7d6oRoFIWYAJhKnkXGse7NNPLKw
kQAMlU6GralsIFjeEcmu0MyiymqdXw5HTVYALTpivpsNbde0/ai3NSGDbmbqWuEZo58uI8Or4/eHZ6d
Dd+dG3cVa1qU1W1NpSDxKsu8GWyOY3ygP0DHKsxeUtLiv/QOU/Da9qHh4wrtd7s2cB3cgRwAkN7rUwJ
FQzEcEgtLUxPm0HAb9mBPGEjAWVK44i0gfkEdsimwJ5lN/hPKmgKvQk5AcZ1FU6Ci5UPbXFwy+ZB1Wa
mfR0WRiTo+uaEMReIY8yqHpsJ6e6MdD24pcroAW+/Bpjgq+KKtIzAiXssOEFHDHZZCgEohHdkPsV16W
94GKRLVM+6UepKx2Q6OHTjU+hU4IanhmZxTOUaN0p4qToGQV3TRV1xYTWAaqaLVm4rzM9EhBVKQie2C
PXkmdpvlt1SKaJLP8Y5wMrQ1wMG6ECaGotoOk/xVhty2AhzzoQH3pDd7mbopHd8Hug+KOYVaPBEuaSm
mTcIL2v/jPSZFcof2DNEIuNafq5oTZ67mc2017VPsKMda1azMBghXixHGkpqhpy2Fs2ER53DsG9Z7qU
jpp25naO8U0+d9qOPuat9At4TwFAP6oaSg3Pi1LgfDAYwjWAGh6PGiHJeLLT9CJ+vPbQLfLyhHPfvPB
hzwt8quu7l0ZV1sSQ9mOy0nwYMvTNSBdlJCT+uauIZrVvYBm/DNksdlQ6ev4Zsl6y255434Zg9ldDLq
oznKMcGZAESWBncou2DYUvKJoT7Q9t79YfeV6o2wwdL6LysAe5mhczOZDrawZfOEX8DVN0ArM6uNvWq
A18A1N3Ghgg0TU2YokYd40WEzlpIAlW0TO3XBPX7ReX049ydArXAUzua3h/zvg+vmOKugNSsCJ9epOI
NbkvDWn7l1V6EGsWY6rZ4ztX7bF/e4ylNfEVKDGzi1jl7tidbRpbUFLSkRvHQ6RVJJQXtOLz/9iWhH8
pkcrAt5tTXHV68knxhWumDtkm53Cv+6wscd9SC4OhgjTRa/+Y+uobwVD4kxNAq0WtW1laFBpf5Wp1Bl
4ywZmaCNUpK3gw6gu7ukE/baJ4enZ12O6oGLHdRZwJHOVPcKNZwyn6Bbq1V3GPNE9vyffdR4zdKsJzv
5e//s7OJjVQTGTT4UhwcMYFfsRis+jox4Q2pr6t1Pe3YCM00RR3GJm+K7AGxhWJ8nOBzFQ8MfR3UK8x
GbWa/GZEYKJYsMzwZM6CPcObpsdCnWE3BHYk4sNDbSoCZZDFHBgHuHT4sHqTOT/YP1f7CwK1nsWqyoA
KG35sM+zh4U49lTK6kLHGCBUIgED/tSFxf6wU0Xw9GUZXMoU+4WdvWg9DCoZChoxEeYlcOjo/5g4B33
z0/7x8Fa9/1vgZQmYj5rRMwaogKrNEomk3i+Q3TFL82ylUmmdDbXOT6VL6Vg8fyt8Awxh/iLt1GejEs
ehhLXkB/cGtvQau0pzSY2zilQehT4CFbiCU4bZNvEkGWIFStZuy2/WOq/mmPfwqxGy3Ftdi7Mxq2cOz
AvFdNidLFIs+TvNFeWrVAlY1H7Pn3qgITzp1cBgEFoGMJA+LuJXWTLr5Qg4UlGOSDuZ4RL5JezFqnpI
5uvPP7Tq3ASo3oboc/v2tSo26TJlQaJeH/uYqtlP8Z1QxxTK8sIjK9sBRrLD/OJrmUjS7c6UvXuRtah
cGYwrPJ4BY5YLuscJB5elBJ91V/+GwYAPWjnqv9fH/qDa/LSmMMDGVZyK7L0YdC/+l9OmOiKX5Em/LU
JVTLlLd/fnFhJRPJdDEstbyaSz5oaAKdS5LSsE6kV05WgLobRqoR5E5dVJ8ftLHpiotMWSbUOT4an5/
3rjkyyhQl8hoPrq/7he9Utix4YGXjQLBeTvxyEewEGWE1yktpgt1yugLbMvYPwoCbMTU2OJZVZFoRWm
GK8ymqLCQ1sE2IqQoRlv8vl5RT/tBfYlqmhUBO0i+UCr3+pph1L15lRyJl/rINReGoXl0tyLGKNiPCz
FGV/PbvKPxKOF/ftWNZG9RHNDIdQpW/7t+s43HX79SsRWgv2EiPajj6yNiAeihjfbVG254xgNhSIQxL
KaJnMChC9yBzLVyYkXKRlLpfIWOujCAEY4ttvzcV8bS3my7xm7bZfOTnEwI6EY09trfb035ob7n5ZIJ
pKkz/2CkvnziRuJetxvjLHfTPMBRi6PgcgbVE0sGOTa7PLxeoC9t1gcCZ2qLBqp3CzFERsAb1GSzAJO
bTPV9VRQhZB/959uB5eHdtHraIRcqBBY8ZHVdwcVVtPS/MRY7ZTqtPgPW+G165YdPC62JlbKqldpAHS
J9O6Hm3XVXoOK3KdhNat8xCU0SGLeDYbsv5PenaTFccnrUwQ2UQs+KrZpgY4SmVzC5Y/Xk0IzY5nwjB
s36yhVtwONOJbyKNv+Qyo5Zsq63BeYwFUsvhpiMdZ8XW1Qnk2D9PMLGMiQGlJSpa19RPx8eqbT4TDFq
kcM74aIV5b3kkPDKtMu4LSQeCIgQn80+lEWY/tH+xtuA5b2EKzvdW3yJtJe8WwftsoReUXJ578upyTG
6SbtE27a0jFVniptPOWwXYzRNsu0XlvHVZiqocqglvQSI2MO2s7HYLqk2O36Fgp59KO6ZkwRzXvTasO
vFW45YtzoxOV20v2V1SWU+xM6De5C78lX4Hp1LCIJB87xJNJWGf1SXy+0cWKxyAZ0+/taYc+cWuLrhA
PIhc5qrK1Ry+BU8G4OdB2u7mdnYO9Vz/t7QW7mHftR2huz43YVQgcM77kOFc5N5viKteawDOrSPeYlA
7mUtyNsU5ImsMTq8Q1iGHS96WCU3qK/SxmVED5F6MkYslVXDQYx08nhuGI4k5NAwVHl8KNgDRaYcJsP
nA+JtNtHNPILBcULpv0W5hUMkrmoVGPHpP2z1adqRuV02xsBE+4vLq4vqg1hLTu1Uz4Ugq0gCn6xWGL
vl0rZXhBebwwXFoGQ1MoQPRMeEFrrZlrbc5q58G4Z0Lkm/Od/coNue3KIG/T7ad5lEyG98A4pEphZlx
1TIbs/mo5YlrGR+z8sJmPgwtjN/FikFNmT7xpMTGIVu9wDC7HBj3CWkv2ikONNSsmm8ZuOsIsFzXMBz
8inwJ/Dn48+DGoEMmPMYZa8As89pfkWpYvF1R58P76EmkAEWGAgCRhlN4t87AcKaZ94x8c7BF/uvL6V
E/GbxFpqmBOP6/+OvdvK37pdckLmp0t2nQ71kW5GiVoN6UxvS/WMCFtAwFRCP/Z37CKnOmtKhH2ixrC
mfBwDhNPgKYUVYNMMThgIlmwLxddI+Q1rhfQiSXaSODphhSbwDwkHBMDEVLSeHmLu4o5qM0TLTfeb2D
VxzTjiAPrUwuoSDqTJB9H2aSaE6eWC16bV+ArYNvAkdCJvcpRCOkixMFI8TbtWrhn7qGFIND4QbcrgY
704IyWXoLMNScXv7aDbjXQiU0pzGqccZC+u/qjjHF65SsgPkv0BqcbMVSCkO1PNPPGUR5j5PT5eLakY
MkiQ4QXF+Owng/hcWBbbXNGG5MgWVVpd7atqcGeDuwVKqcjLFUV6rC8ZlkbRT/rbKVoX6wUORzPBHuu
eBAs2mMfJdt2W1zY2UcyNa1CNytXGMPXUgJurTcs7VjrbDrkh5uZmVpYhNPjfc/T1DGNR+si1q9Txjr
j9RhHgNk6iSMUxIXSlvfMQQQ1Z4DV/trcJAZS1m12jCBksQylncR6TFIGUM6GbuVYo+QQRpRHlbFR7s
WouLd02YaKqKJLEd0xroLVxQROdjtolQKvV7sp9qtfFkWN7si71tIt9l2M4bW6ftBdnw1y0w1SQR6aM
4qwK6PwROheMol7r/Z+6JD2eJn3/BN5UVd3XLqwozasDg1ERGwobUA37jvx3tn1oLNtV8w1dhq3l+7U
hSQ2dB0EZjG+Ahgbrla6Fi+77U9m1hWV0ANrbFv0CcBVfzJ6rHMTGHOVTMi6RtyQjK34ufSabGt2tBv
uWIiFZQ8V7fthIKAM1mjr5xuw9Iiy2W+MpeZibxEO2hUEehprd61xsytB0w6or8We9kKG6VXFmlpWsx
5lXUoZfZ0So9U0at28+DMg0zgpJH9Avpd8B0Emau2cIhfA4HXMmnLe2HnqPVI4KG0S/BRTLKYn8vHEo
YSlhR4rmeWnvY73095Pe0HFyKItLP6/R1QMDH8XDqbQqhrBq+IHGxc/2BL8wZbwf9gS/g8O+GWLEksc
MS3+KeZ7zS6scqIlqyJn4QqxRB6304h4DtZB5gERYbxLpASvA0O6AnyyswGalfzvoMj32pbvyXStRXO
+/e5t4EQyOE1fvfqhDrvyLdcn33j9meA6I4wXsxwDayxgIEVd9adNq/8vxQ7LEx2IuvTbYrZOddFe0b
aiG3VpoQ1X1EoCC+2TuhmE0tROBSEkWz7hvSsccyuLQAgGZWqQS75q3udfsZZbrubXrKdbGkQpp7KmM
GpzEK1vzJq1bDtBR0pqOzohLhJyHMTKqTtKh8hwMbh22HSUayBzhsv5/vCX06Ph5eH1u0FVB3fcv7zq
Hx1ew9f3mJKaNDZ3KSXUfdb65uz6N2TW6xbBwR1/FZv+RZjg6ESFQRfTOjFaM2faPnvYWclW19hZyFo
le9C8ImnUR3DIrYRgjcYheiZUfOxXe3voJhKpwBg1vOWN/xojsbx5jb6wb17f77+Bmp5R7/UuPKtjTP
3Xizen80/RLFHlMYaKxykfiNELX+8uGurvcru71AnSCNfIgMBZqqQI7jIpEOZZCtM/6VW3xYV6qRLd1
VMHlyBtCNBi8171Yb8GtcJcw/JWgTOPsgs8ysFtyXO/UhgZbBbkw7/laKTtkGnk3Qn7qHG59dZJdi1/
W1ppdJf1Y85tqxohTlxbzC/usmgS12ynD/zW3lGGsXzjYV1W0rE9t2iPTLr5u7HhajzzXMPQpVqtby6
kbi2g1gqnutPG8ereSNtLqF8knW5Ep8VTMUkSO8RPw+1nXlh8UNCMEOW4NZ73efo0mdYgXykljo2EXB
GxSDuOE/bsH/xHuAf/27ewRw+kTTXJaNWIIdFynExrVcubaJXd67+5PnlzbbK95y2SsC7od+k0K+WjX
OvwXodR9Yfmt1D7bLGztjqmvlwZ5LYt7myx417gRTCGdkc8fLZ5VIBSvnkpuJlGZnyTYXr0Sx7buLMx
5LKvI6VBVY1fTrmkPEV4VuqmyWkvxYNR8UTpF9mU8Neqg7bFJOjyMjD/YJ60K2HlmSOlolZOYd2aW/6
HRYiWs+K2ZN/M1QxnWac513nqDc5PvR3sMQiwMrWWrt1s7aw7Z3jVlP09OJlAhPFooewSQ9DgggpEoT
tvXAGmrnm+fIxFEHq89DagjOKiABF2tqTYsxQgYB5/LryMGNAw5PD1nAhEuKeUUn1oyxEjGqkZa1K+f
u0d/Nht1c5aXyZjlsiPeQIo+C62S5fz8HL/YA8qwkpN8rAuHrfDstStPWskcrpnl3GWUwy4QmeMNjsZ
jeAEQL+yaoecu6aSqGw7EVwjIqfRVGjluo/8FreqKsKabmqL0+8GUfJ2g4tTB+HUuU+i4jKOKUZla/N
r1upa2ytN+vWn2EPbP3SvJBvMOHvE1B4cpgaWbncwOMOhe3mqOzUuPtcFQgCi3Rfaw6Pic9u161F5Wn
x2OCp47DYBKDw4k6J5G4p2ZIFNwyNFYyQXIjZlRzjqYwL2uIJgJVNA+xpOvE5yDMdV95aDddks179lS
/47dtNXA264Wj+ZRfn9ZTpLxiuRO8yZJItVV4P7dDmbiMDhlLKG7JKw+Z9bNUbDlIwpA8I/ma1U+jbE
YmrZ46Y90bbpY8WX8q/HWZrnO4yiOwsq/aaaiNL3XtN11k5EDuQ7lOxH8CLPv3sO7e2QQpd+7LoAvN6
taamMz1tOMOtBTRbJSsLwP8kkOen0V5JeR0aJDUhuDcE1ie235lqlFXVCBtSGES2lPxpcH173h5eHg8
HHi6tjYWDKD89Of+tTj5B1+FLraMNwq1K3Z1TvlcH0rNA8bA2K2d8kabc7/hWGvSz1qdCW9OwPdL8s7
tHQBXkHmLlJQrKaZUF8Dzsvnt9Rl+6j/fv4MzpFvvwp/OkzWQXczYALnA3icYbBv7eJnpcB85A+hviB
KoC9jrf3+T9O6N9x8P2+6RUZf17gjTWG7LqbU27HNqU67Nl9bG49pz46BLcj+thsCItohTLeVg1zzoc
epssJXIS0T6MzGHVjzBWSKa1xf5bJfWV51RllfocrO5M2lKZx5h/jMBpT7h3BzTzdJ7NYEyLClq4qi4
laRUF8I5GTSoWLdNE2hwXlsxj2bB7bll9YWnbsyfBfM04ip3fv0xS6xtZXhnSlJ4SfOWzCG4CGBNTrN
bRYXzdrqpvZdeW2c5Y184bVZwYwaIs1Ojnk4ySX3vDlUTPC/JKmk9Eq9p2medsZ3JoEyqJQSEUtYb2C
YeaESI8HssQt1Zqz43X5sY1SVY5Nm9q5uicJqJmGw8jvrUrzlqvqv1wr161/FRprEjSYr2ocUBl5NsL
Y5pJZbUnH0YIL51BY+xe/PiPisrkoY1QepFm2Ct313X4QNjsgDvOr6KkmKUjZCyqLnnZRRp9slgtk/Y
FenxbEVdfYWUoSKXm3lOSXllazqJDJZ1FenC6O6aERyDSwRW6SuNfpkqU1m+Tbtgpte3Nrz8U6Pqziz
2JQF5kHj5QXcda8lBzmnmPaJyK/ppnFk1VJJFdSGt/HhiXWUfpVfjy0b5uld3gM10wEFqSu9AxvvI4H
ZAzYBuXaO9ssf8womU96bd2PQPdAfJaiPty0fZ4BDjMirS4NCIFGBjyqqV9dI7GpSQVEAAvf2xGzj5O
Zzj0bMHmufOdL+AbfB+PEqEvjmfVoyIaAZoBORYN4EXt6Fg3nCLZbxY8vZ2F1Sj6BTSol30ZuRsRub5
bYhff0+pQueINuTS6N8yVjMOZyWbzRWVYMCx81Q6oRin02hAkWyJMscCt3PKEFdiXFgsJOvTRX5aiD2
Dr/1lGdx0Y6KLZ5Ip4OKAuG4m1L2EhD7PsdwfrRwakt0+kANUuNbS2sedjq66MXfiC9s/GdrX7G8HDJ
3FLkVOKXYZSmXPbGFa5sEaFaGXZvtqTTkCrcdA9uS0a0UU7h1H1P2h1SuYPubSX6mZzYnoTddZnMmZu
kPRt37I50RIs1NnOjNJ21fVJ10K04VrGLEp+TxSGGQoFjvi2gByG12eY+Bv/zPRNWBqfzSfy5YmVQEX
ik2Qmh1EvKmHl4dCbTLmHfZI+VuYcz3JSGeMLpb4uUhJ5dDqxnCFMIyk3JUO70Q6SBYrNxICExVKSPH
OMeqfIxl/AtwUZU03nAItPr/jH6jD0yz4xyHC/yEpMBGlAk1wlyJXEnNVCnfJM+nYR8HLaNUFpc1sHD
KhJj8BZdOwqbEYGeAdtHUTqaLk8XbSujgnH9HZh7azk2xR6idu3SMAxqa+mKalWwdg/1snxZD7k3ymO
nPF8GfbWi4cs0IjhFsyFisA4LZiMXNd9qjOrOe87vlGv+cBvcBhVcr0TWd5hiy4140a/ENittGcmUdb
sSZbt8u4RaCI5zhVMKjwgK3lLP06ApjlqbigDO53eVQBMY0Gptm1S/J1sGMNRypVVXtKQNBidCtznyN
f8/XyCwew==
"""))
m = sys.modules["pagekite.proto.conns"] = imp.new_module("pagekite.proto.conns")
m.__file__ = "pagekite/proto/conns.py"
m.open = __comb_open
sys.modules["pagekite.proto"].__setattr__("conns", m)
exec __FILES[".SELF/pagekite/proto/conns.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/ui/__init__.py"] = zlib.decompress(__b64d("""\
eNoDAAAAAAE=
"""))
m = sys.modules["pagekite.ui"] = imp.new_module("pagekite.ui")
m.__file__ = "pagekite/ui/__init__.py"
m.open = __comb_open
sys.modules["pagekite"].__setattr__("ui", m)
exec __FILES[".SELF/pagekite/ui/__init__.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/ui/nullui.py"] = zlib.decompress(__b64d("""\
eNrFWv9z2sYS/52/YpuOn6AlsuO0fVMat4NtHNPa4AIej8f1MAc6QLHQKXdSMO30/e1v975IAmQnzbz
XOhnQ3e3t7X1ud293xYsXL2qjRagA/zOYMBVO4UUvi6IXkCkuIYxTLmdsymG1CKcLCARXEIt0EcZzYC
mwKPJrL5DJl//Tv9pF96TTG3bgCJD5b0bEWRhxkjNhMgUxw+85fwhT7idrv3YikrUM54sUDg9eHbzEj
++bkC44HHMWq5RFDwqupHjHpynwxcwHFgdw/I7JOIRBFjMJnRA/lRJxzSyXSDGXbEkrziTnoMQsXTHJ
W7AWGUxZDJIHoUplOMlSFCwllvtCwlIE4WxNHVkccFkjKRDFpSKhqQFve9cA7dmMSwFvecwli+Aqm0Q
I/kU45bHiwFAA6lELHsBkreedoRi1oRUDzgSyZ2ko4ibwEMclfOBSYRteu5UstyagWHU8LpRcgkhoUg
PFXdcilhbz/N2dFxsMUBc0z4VIcD8L5IY7XIVRBBNOyjLLoiYAkgLcdEfn/etRrd27hZv2YNDujW5/Q
Np0IXCYf+CGU7hMohAZ43Yki9M1SX3ZGZycI337uHvRHd2S4GfdUa8zHNbO+gNow1V7MOqeXF+0B3B1
PbjqDzs+wJBzzZGAfR7XmT4gyWsBT1kYKdzzLR6nQsmiABbsA8djnfLwA8rFYIpa5bD8KO8aiwRaBW0
TJxQ4onzdGRlNExRH9XmzSNOktb+/Wq38eZz5Qs73I8NC7f/4/7AmBFqgzai1qtVmUiwL05mKZUInaQ
i+2h1dojrlo/YhH4/EfK4dgQL7WKtNI6YUkAu5DutiQgbXaNWA7LhwNNddo0EsWrG1QsTTTMaobXzGs
iiFDyzK0M/gUUkWIirApRRS+QQNsjptdy77vfHZoNvpnV7copMYyYzjQPvion8zHHd7V9cj7D1jkaLu
G9Sn4Xg4Ou0MBqXuQefnzsmoczoedNrDfm+IQ39gN4D3PhMp81rgkWqQrZHaohqY/qYhikWAslsqCSq
bqKkMtW2hHqHMj0mIHqIg/0SuUxHHqkw2i9YEcioELNFmgaBXjh5dV4ZmJcPfcSmc1I0RvBB1dzpF/5
AShmqBXALUvSni7OG0PwlExBrG4zAO0/G4rng0a8KKR3ji/KgnYnQZK/K3R6gzvkrRjckmyHJPGOtjB
QhnpFh+gq4EjWt513p9T66i7q3C2GuCJ9ShZ0kBaCH/5KLTpoPwfot/i/cUfXqwhzOOPPgK/v19o0zc
6w8ukVY/35x3Rx3XeDvo3JaeOz3XuO2QGhB/r8zo+OI6nzvonLrHy/bbDrob1zy5bfeKqRw15QnRD16
/vjvXnz97FfIagoPlxpiT3wy+2hy0+ylmwpfm8fXBD1ukRnw7+uqHXUYaDDt+uD1e4GMIXm8TWKTs8D
fbwwViluLbbQoHohn+Tg/X8lGtWDisv4tuabvlZrdVSqI3TyVOA654Wm8UHUPUQrXAHqvghoCGrAZqq
jAer8LfmQxKzsCtpvvHKcdr7QjIEIoxZJ2O03D6gCMHRTc6drzux+jbUiHX5ET+LAYx8kgzNU7ZvFCq
8sBURE7zSHF2xpdqeyJex+gQjzDMKcmAoRre4WjNM+HEtghYRAwE6LmVciM3Bs6NITsnxQjrRiNhPUM
aphHfJOrEwQbJ+yzkabQ+0oBu8UswgJRVMhxLsVLccshk5FyKuWdWfDLRBLLY6QhPpn7n9RMek1PcU+
RrdFhjSX3fJ2eCzO6NYhRcfIxc4jot49Y/NRdOX55hLJBvhCsTVdnrqPBz7n4KdQyscW7Zy8uNaVJ9a
8GJiGfhvENXV927jjEMXWHUMEEld0u0UH4S1rVzudrq4ULgffqUSNZF8yWKbZ6t+eV/VpExTk/NkTQR
Vby37cwJmz7oR7s5uwkN8SYou3CUhOwsn8HNLpVI/k+KeMtVT3yqiLDm6si7pesVT/jI6wnvHxL7Vzu
4IznJene/uwMM5NJqnP82mX/BwKTHls6eA4HaEauPCv+PyXuJ7TCJ+MlCYPhtpZ7qxmdJ/XfKfoxseB
woKzXFhDFCrzUhFSg+eVD8kmxln3b2U7GDTaX6G3ZyI+QD+nG7iyVXCvlvXRLa5RuCKIzpaHQ64ETaF
gP9tB53cZvNTHx0qNYXg+e/E+hcNbeGizYrnHYVYTkkLLGu39U9Kz4FvVsz7/NFDEY6X7Hb6+n4YRMB
fUaz8BED4m0HlIgkS9zeMXxAIMxxxGJlnzABmMe6GHLkeQUqemZrW2iKGUjiPUX/dBzuhHhSxbf/igV
1WQWFprzD8z6HgwZrA5rL/ujUwoPpaYyKHpRURS9RVhcziXzRgFP2yV2Eoi3DuSW0DM4UqSQmbamLWh
xUZoxCCxtvb2aKrfw0NdlRNdWdGb4vghd71J6jpPu/hSFMfU81NPKVIjZ2YXTa8YXndKBO29Do5xkCp
X5FvN/YQvUC49UcGOKGxp3ypbIMHRbUhRvU33cts5fVQlfiqCtPjhZihWR397ZdItFCRRh4mWUa8LVu
5SZCUxsNeAPffdvKN0qdPkswXgvqmouP2ls/aGymhhZOeEk42liq7naztYADyuxuE4uhDp8tGmLyjgo
1eUBdzhw24+xSa+eMrZwe+pMYldAk8EZ/X+Km8Ggjtqbw1carJV53KIE/HPfal53cSRvZ8zyx8eR6iM
VAs1ZZoh0/7AVG85GFAtRWapu6lR73vRx0BI9OZleUq0F/1B/eI4ZPjPcHIxxuPCstmpWHt5FnrOqJJ
VoV55vLpzfHVjA6udrvXkH9fDS6or09hjxomLKILpiwD3jpUKDtlzzQX0FwJABvU4rUqVToPCY61iCw
1dMWvHyJ3bogsp+wdLGfin3b4T0Jw4bS/Uplnzy8w2f8GlNJib51Echq3nvsuDzW1oUeMBIsrWv6Buz
Dq4PDbxy6RPRG9zgU3zsT8vb8wxlcHutk4/I4PxCzYDmf0dZqu9/ANwcHFbwC0JUv4qUJS+y03BX8TD
9JV8FPQZqhlUSWpdm740mM3ueTCAUPQzZbLU7DpVlhgh+rMEgXXoW71Ui3gOppusCLC0Z8lmq7o6vPu
In3T/vZOkZADvM3GkBzz31h7jmouOhKZ2/rJVvH371SV1wO+dSqQJgocjtTVfY3W6rZnmSK75+e9ofa
pMmvkCpqg9ceRrLZDA2bitxZQg4Hz2oahQiXgoRLbJbtnQy+WNbtYTfy+OheznSF8qyzedGSeynusgk
vB2nl3dU9M1/fhvv7FIbse7uRQ6PigtRlAn0ULe9r3dBxxzM35n/e/JjfmXmtKt+OrnzQzYjiUITdcR
H2Tu3jOaINbI4dKpMwIBSaVBweKxXhLshxqCeCpFCNJ1mICUrsgr0ZrsdlIikcL0FZxsJij1Yy4XfHn
fFp/7Ld7d03bZP8dNEgj2ushXwozqnbyUfGUVsl3/KzNrTLg8qNKXqGPgddAT48RKwPDwkXK5an1CKf
a4Ewk3I+9HbEa+XKaOdRrzIzM0k1My9XFu85xah7LUNBPQ2rHjUngUFiOGqProf3tHreGl/3fun1b3q
uvlM941+lCf1fnNDPknUGg3G7d1sKdXSlj3Y0kmQG3uaVtVnVrm3qM80ix2C7y7lJmbGxrycYkwFUsC
VD2Ul4LBYOjEJHHcHEpKXEwI4Aac/pLqsSpQ6C9Ska2I7P+8NCT4+11jZqFX4DHTn+Z/SJmvCUzzA4N
N2KutCoDeXxaT/hgsjtmNG87rDAFsi6TZHjDRId4aC6YeZhTNx/4GtVbzRKZ7MTv1oEtGxB0tjwUVSQ
bxTKVXIEhe1QxRjDOXr7WLfW8sx6ZyVfYlYuMa32SCV59HuMRiXzOulj95LOrN0bteCM3reyx3CZLem
ayTBLWTfpdTEw0+YwXTC6/b1qP+jRNUaBolzqOm+Vc98SzyY8T2weYE7lCIU5Cks3sMSF+GOCt6rvff
IaxcWBKuGq5WyeJ6g2JS8S9a1LovOYROixTMHBTNfVC1tzb9J7RcpiqyocWgMxGGI4j6rF3kb0bCrll
otHcY5+oRhhUhmsTSDEYvee0IcLMddv+AXKGqPdZtyvOJF7V3yhCoYriGzIo2vSH5PEvaXkL4ma4mqJ
cPlwpTeDccwa2Bxh+emzRFggVOuPiXC+XPowFEuO2WFT/6QjleEcdYEH+nW/StjyJYbzKZd/HQh9+5m
7KGXodGhB06QnPFLbaDwr5O6q3lBIuW6al+eGhy4eUMSdxaW8hzJKozhVXCpZd2caBcnnGNpoGKigYN
SlSdHjgiVKk8ScMBKUF1FCSS6nkiODIKQfTGD4uXXSP1XSf9ZhTxd8+jBD3vT++y+iOaqAkfKNKaKM0
EWYRfMUI+kynp8jY8zTlZAPnyEfggcrRj+ZQCePJ7sE+k1GFodTpmsK+scme2rjwJ9gZm0L8276dZLW
oLXLiBisTCG24gg86NKPwHAP5Blik3Toeyc30y8+9eS23qZvQqB9IK4RcFfLsZ6QAiOzEOjfK32CV6j
9FwK8d80=
"""))
m = sys.modules["pagekite.ui.nullui"] = imp.new_module("pagekite.ui.nullui")
m.__file__ = "pagekite/ui/nullui.py"
m.open = __comb_open
sys.modules["pagekite.ui"].__setattr__("nullui", m)
exec __FILES[".SELF/pagekite/ui/nullui.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/ui/basic.py"] = zlib.decompress(__b64d("""\
eNq1WWt32kgS/a5fUeuMRxIPGTsn2QljnMUOTjhrYwfw5HgwYWXUgMZCYiURwkxmf/tW9UMPXnYyGSd
HSOru6qpbVberW3t7e1p34kaA/+MJg717O3KHexCzz3F5GjgM5hELwfVjFo7sIYOhZ0eRpe3huGff80
+7aJ41Wp0G1ABl3wmlRq7HSLOZHcYQjPB3zB7cmFmzpaWdBbNl6I4nMRxVDitlvLwqcRtOme1Hse09R
HAdBr+xYQxsMrLA9h04/c0OfRfac98OoeHiNYoCXxPTzcJgHNpTmnEUMgZRMIoXdsiqsAzmMLR9CJnj
RnHo3s9jVCwmkQdBCAiUO1rSi7nvsFAjLRCwaURK0wO8bd0A1EcjFgbwlvkstD24nt977hAu3CHzIwY
2KkBvoglz4H7Jx52jGlpHqgHnAYq3YzfwS8BcbA/hEwsjfIbnaiYprQSolmHHpHkIwYwGmajuUvPsOB
1nrVueGuig27nMSTBDeyYoDS1cuJ4H9zwuRnOvBIBdAT40u++ubrpavXULH+rtdr3Vvf0Z+8aTAJvZJ
yYkudOZ56JgNCe0/XhJWl822mfvsH/9tHnR7N6S4ufNbqvR6WjnV22ow3W93W2e3VzU23B9076+6jQs
gA5jXCIBuxvXEXdQyDSHxbbrYfBqt+jOCDXzHJjYnxi6dcjcT6iXDUOMKoXlo7I12wv8MTcTB6Q4on7
NEfhBXIKIYfgcT+J4Vj04WCwW1tifW0E4PvCEiOjg5G9IJsQ5wJRBo+VdtIzUbexOmaaNwmAK/tzz5i
7IhhY+3biiJcm0YTCdYnzJLgVN0951Ly8Gp+1Bm3I15D1mmKdGqB8b9+GXg9kXtO3LQYy3kzvHPLmLC
ropRl00N43y3Gyf1mnnekOvH/37aPaz6tStv+1sEtX7iKL6eO0XTrAvunyEjIV8MJjEU88gVjOrGuCo
eB76kCplRfN7Q4cC6CVsVn9ZhUSPQa4dUixE852vlzh3mqac/f3mSaUBYhSOWVUSR2ucauGUCPnGNYR
3uCCMl07suAEgWWPQ5hnaomjCTm/qjcur1uC83Wy03lzcIlTntochi7mKydYZdLpvGu02vu6Gc3rbuK
w3LzZg+rFnl3+vlF/949kP+z/e6XeFu+LdQe31x8F//vjy5//K/aKeBST/pxuvq3dWXkChmBttFv71i
AA5vJ/elvsF9dJ8fWeZhSdIqJd/7f9xVDp8+af5A0YGADmnFcTI20bEvFEJpiyKMOpLmMRs5H6u6flY
wL9ZMJvPahxG9FjgBWGtFfh47wcLeWd77tjnq1JN17mzgFoRVHSQQXfIRpSBFl0M0+Q9uCzsI37xP2l
kta7alxpvfwYfcDWaz1AzjAhnjiQ6RBqPBCnT0iCXA5/xCaKYSDoQnBsNcRFBpidBD2wZ4TxcvM+NHy
BtxUG4tKjJEOq4I/CYb9AbE05wea1KHIhK8S2tC9RYTeDBERtk9rBTH44JgPLzSqWaQdNh3tYRwmbpD
tRW34902FcvlIaqHQWQPhuEVTU54TN440YzzxZrKgHPfUL1AL6Q0HChBklLfUhdMkpz/53UgAeMhdkZ
D2J3+ABFeFkxzdXOBKFU0kQQXv5kmikCMamXdl4RWCP9smjhG1z4GQ+c5IaImm6w1pnOSDczMyRjBCL
Y2z+yjpwqv/YJTMOxcP0LS+BYU9fHxT4dyz4P2SzOajcjHnqG/IGrJ0XV9RKXdR9QmJZCR8jJ+OYwQc
bfmzwtoennjJ1GY1L3LtyPYD9S/5BVSWVDJCaS9HOzV6k+78skzKRukjel7YyQ4QYgxjf++aKc9RV/S
OEzzSfJygzQMkYvqIS1FiEupQYal2vrxHY8j0QwRfx+ENtjaYR8wcfk2OryqvtGMhYGALK+7yAAQewM
lAECd2+ISB5qyWyS63Q0W2hByey5PqPseW/kJFiYLW5MjUgJ1azOUopBbRYVijPDJJdLKL1h8WgzYAm
pFou6Ik8u8cO7ZrehcEGli5u1TsXnSbZHeACvWfYjHtoKFXOT7WS8hDMDP67ZBLw0X1J5SvASghVHIb
x4XWvBYWtMnmnKkfvqWBn+gu9UQK5KScJIJh1vc/3Bwv3dDh3lrZQ+V8bmMg0rlhCOj7MbK+ghjkn6U
SaurK4m6cbxkl75iWcMvtns+RUEEph71RdH/U0DpNgXR7m0NDPZ/XiKITbcRYgm++zGrj/Wq9sGUdWW
RMUH5mHtw2RYYNRmI0Atc2tor8sU8HE/8sazi0a9LU3gIV9aEWWauSkWQo9dE5BvJDWmvIepnB1vmnm
sxFv0PFm12Sa+Lore/HkQM8/bBR5pQlqsuSfLMGsCN4gqFAqgTHrPKWZF+3T4igXop7+sIcnYMJq6bV
TqiROlbBPGH7gBinKQYXPUokJPiL+3fdxyEh2cnJyACCUxJt8sQq131m1fFM/w+cz2h8zrU0xTZIh+S
a6+FEkl3ppZS1L/16TwtA15nlHdeFSpKHvaDEsYbknWBNGxrChc7njSJjW64Ts5LP47d1nsLUVtvZJs
26IwD9eaDbkAX0YW1n8xuntKrjb0hes/P8KFSA8i9cOmn3VexHFWlRrtiqpjIk5ekTda3UYb4gBp30e
umTNAn3FWyYwO+eiQ2Q4FkZFGxgx3beEalFsZqq0kZEbwGK5tmUeV9PikzJGOya7ivIUh/Ekf240YNK
8aYRiEht64Ok91qEcPjSmWg4n7sAjlx1LYaM+9WC6hRJ+9dY6XHp3glkjtptxpuvDe28MHeSv5qkZ71
DQsFDfm4wAnE0YsJnRsyNtElJrbvQg1yi3gJPreUHbgWpMwj+1HC55oUmAOVq6OtJmHjuqNaatXFcyy
g5bfK6kNtzW14+HEECMtL8Ar7guTweJ9OpbQoXM6ClICaXVaak+npict9WaD1/ZooaF3gwCmto97Ikr
MnGsvgrHrP+JaRu7PuJnffaujN7Egd6cm9oqjAZ+O6zDgu5Fagjqdc8pWLmpLBmVpfM3T2XKKy1IBwx
+U75Og12/pUJWVeU999/ZAoZYxgptNlzS+Be+lTpbz1njfvDOFruI4bsxiQkPbHtuSgqQABZQcZ8lfU
cIrbLORcMuiVvC0JIcli2o6XnQ6D6npfqB//3igt0ufVj1D+R9TgbMDzwO9d3vg97MFKzct11tgLbsv
D1r99dMjMYhaUdg3k8pGXln6jzKL4oB1htmR9pjyibwsIelLne/PfP1JFEKFehhHdKJt6Pe6uU4kXIK
cii+lS1o//UxXI6PWUgXgV9DPe4nWWtypSFuNv2A6w50gor4xF79L0G2qvxMHCw2o9E4cbZprBVB7be
VHW/+Nslp2st9wAkxQP3rU6L/LTHnyJ9UwyYWHW+OcyhJ+0oXba1yM6WwNt9241SJg1Gci23GYw+vsZ
TC3zO0ntVStynl7lf56ObKpKKL31x6zI/45CiiU5aebUeBhFpEuUmY1U46RNuI1RbDqkD+t2jATFEQV
LgaYu7eTX8sZOEVaimQD6avJ4mkFQmLten4zb1cYZFSRlBEyrK2HzEi9h4Sgm9nDYTmENOk02r80zxq
Dzs3pmyssgVqrJZCZPXrMFUHFdIZE1TRAHvVrRhMLA1WQnHRmNReXuy3MW/dXLdxm5fbVhVJORn3ge0
se+sOJHdrDmIUR1Mu/lqBSflWCMldngFn39SR8iVzjzjx2NgncoaKnIX/4Jnr6jiRFbnbJw6Htj5lRK
fFglbqZ5g6+Ar4sO6aoBHdSUVIy1Gpu8VCWCwVdnnWi2sXDBI+e299xJvAoGTgrS7ahp3DuO5xxxJM4
adUfqzt6h+V9Zz/qb6g+skDhJAm75D5HbKWa7E7x+5QSICGU38fkzKIY5RZn55JdT6DCZ5GPx7WcVck
s4oWW/aYBxi+2N2d8Q1uCpu+wz/w+k49JOf3kXOkyT22D+YE5bo1Ipgrv1ZB+5Agxd8LF5W1eCPOHH/
mDLD7ssaMsfpCV2XCQztVd8Sth5V+L1VlpED7gEpv/fvqYnTNRI6hvDcnnyKzpaEyvvx2XNRFFUJ+Ti
jpYlqX3d2H1LRJxNfGZkrvmDR4DyRetdbz+D3MdEbs=
"""))
m = sys.modules["pagekite.ui.basic"] = imp.new_module("pagekite.ui.basic")
m.__file__ = "pagekite/ui/basic.py"
m.open = __comb_open
sys.modules["pagekite.ui"].__setattr__("basic", m)
exec __FILES[".SELF/pagekite/ui/basic.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/ui/remote.py"] = zlib.decompress(__b64d("""\
eNrtG2tz28bxO3/FxY4K0qZgye10Gtp0Ssu0rYlMaSiqGlViWBA8kheBOAQHiGYS97d39x7AAQRoOUn
tZqZORgLudvf2vXuH04MHDxqjJRME/vdIKmhMWJjQeO75lPiBJwRZL5m/JD5frdKQ+V5CBeF3AOeRiE
WU8JgI7t/SxG08AGIPf9d/jZPjo/7gvE+6BIjfKFbnLKDIb+TFCeFz+L2gtyyhbrRxG0c82sRssUzI0
4PDg3348U2bJEtKXlIvFIkX3ApyFvMfqJ8Qupy7xAtn5OUPXhwyMkxDLyZ9Bj+F4GFDLRfFfBF7K1xx
HlMK0s6TtRfTDtnwlPheSGI6YyKJ2TRNgLEEST4Btaz4jM03OJCGMxo3kAtQ7Uog0/hC3gwuCOnN5zT
m5A0NaewF5CydBswnJ8ynoaDEAwZwRCzpjEw3Eu81sNE412yQ1xzIewnjYZtQBvMxAfMIeCd/Nitpam
20VtNLkPOY8AiRWsDuphGAXTM8d1vyXMAZOIikueRg/WQJ1EDCNQsCMqXoQfM0aBMCoIRcHo/enl6MG
r3BFbnsDYe9wejqGcAmSw7T9I4qSmwVBQwIgzixFyYb5Ppdf3j0FuB7L49PjkdXyPjr49Ggf37eeH06
JD1y1huOjo8uTnpDcnYxPDs977uEnFMqKaJid+t1Lg0U08aMJh4LBMh8BeYUwFkwI0vvjoJZfcrugC8
PvD/aGF1+lHbDC3i4kGICQq5H4O94TkKetImg4D7Pl0kSdZ48Wa/X7iJMXR4vngSKhHjy4r8RTaBoDj
EDUusnsRHmMWGrbDhZxtSbsXDRaMxjvsojDLJAhAZXYI+2Z1fgdTWzoIWEA0wYCgMySsOQBnqRMA2Cl
JmpAbxdsEZD5aAhXfGEXrCmGm51GgQTwnkyY5xMPQFGKuUutK988/yEGWtwGR3AiE8FKNlFFQOlV73+
u9PB5PXwuD94dXIFyWYUpxQmeicnp5fnk+PB2cUoH70EtzyfnI9e9YfDfLT/rnd8MhliqoqVoiBNNWP
n+2tv/6eD/W++evj13p9unJtHN49vnnS//X7yr59/+fDv/fFjB5Br/jnNbzs3bpHAo8cF7Najv3+EgE
Yf54/740dmsPXtjdt6dA8Kvf1/jn9+2v7Lh19WoOl01fraaaHuZnROJhMWsmQyaQoazNtkTQMQn3YHP
ISMs8Z03QVHc0UCWTBuk9geYaE0JtEGd2to6d+GnPxpKMmfLUkEkdyjk34PDeM4+djgdPgOhuTz5dvj
Ud+8vBn2r6zn/sC8XPXR+CUyL08uMsxh/5V5fNd704dUZV6PrnoDhagVdJ5AqTqBFAqe+NLzb/vhTEg
BtewSS8rkrmOIlaYzpQsWTqZ0Apk/uQlzXQPqJxGi4ayKzIAnUJte9rWap2wGP0CjS09MhIAEPoM4X4
p22TGYmExTFsD63ddegBVlDqzQOIoh2LTFQ76WT5qnGV95UDK6QP/6ZX/y6hQCZTCWUzLSzcTZ6XCkh
zFT5OPD09FpNvEexpsaAFQce2unJWu4Q5pvR6MzCQPFpOVgydC2Y3NSRJEYcnXgrOk8feq0ydOnrU62
tCPEUuGmcYDvewIy9Z7YEw7Z0wy0tWhtRQlJNp2OgsCRluJA6pyQFaQcSIXIvgOSTaAXSVLR2Qo9h6i
Z7t77Z2iX7p54pheSj0hZPSAP+FRBYrrkQkFNNbz6bxsUnQIlUro+H/VGF+dj7RC2eG21Xrs2UygCL9
+eno8QX71Jm9bjaG9T9ntG4LF7qO1Wj5S7oMEzHvlxXMtZtb2eFRxYGc8ayWxYGV3aptrCWHIwatCnV
Ph0NCNl2+Nkp9qoMKNHoBXYyEcR+/AbDLUtljRdwQuBh78dtCWdOjUo3q7x5/j6YNwuDhyOWxpvp7h5
EtEpRE+in9A5e991SNkOEY/SyKQNnwc8LiWMNvECtghl+94FpXdKgeMo8+iBmoQXSqY6RGoshy4x/e5
09EozDs0H9AnhLBOhNpdCDzJDwhntZoZbX0BL//QabkyjAPqUJgZgGyKWOK1Wy6oXkAE0f4m3yFjTas
qVZ/Oq8sYE4EFX8HNrZiUWuRaNNeUGrgjUMklTg3TqHMLJcSoUrokAJx8lgDAZAXjJNHGp6r5WBbjWl
tQFcrpNyGlBpqY6hCtVXqjQl+wnL54ZtbMkqF9IIPxkLREsziWOoTmkSbzZqs6wjYId9H6XHBoFWcPP
yYHRVewx2Kb03/tUbtOazohzsoK9GpGgOiXFNEnj0CJh9QkFcX5MGU2CjQq/nd1CWaimRlXZVr+oTDs
DW9hKjEC9sS1xBM27me2J2z4kqiBjiAq1aYVJLw1M94A2vt6uGYqryRKztE4hbJVHxBSaIdNw6pYR+3
LNxnqJRwaqa5NGadV7pOq8PHE7ocitbJp04cEuIguGKlyc91bTwHJAdDb3B85C9MQaH8zIa03sXMLAZ
Cvogdqs7WSqLthUDe2MjVqC9H1EfWChrKFqhyrqUoN6oVjDXkx3zLKFd3HTGbCQNlsunjZETUs1Eszs
sdyVl/jLpqIBXZuOAvWe46BT4OEFlASCviE92CwMiRDnnQwb3yxfPeHgBx/xVSmV5bfy6dd67m/y1QC
5/ay+KmX/NE+VKP+bfpqBYsZa83h2L6/OtV7wauXt9/ftHX5qSNV6q7Uqsv77LKoo7VxzZ0gqrltlkr
m3aIIF8LYN2rIi8YqKAb9f1SAbKroOIDjYVXadAXe+TDwCHyEvxiMM7QwXnM8cH14s1JDvxITpDDHk/
y9XdbFdNkp9YOeQn1Su3IAD1D2jrC7AMlwNJk8oNigm8NMphY4ksrHdLB8HpppG24azDF9PWGH2HWhg
4GW9ttpVCjvkTJAVQq9i5/NZIgzPlENg9/MVPdzf68Ms3OEr/ex2fglj+b58/wNHUIXS64OoAPzF4yj
XsbRjpQktcBekEPjRoDmTZ0Dbo9VtJymOPtZrXB+MrVDDo1tqjm7bmVb1GZtQRznwK/bW+mkrCCvCrl
gRP0sQTrUgny8IfZ6GeGZ8UOpDBI3voHdg4dyqlUqdxtsskGv15ck9V6fL5+McBfW9G+N0OLIQjI124
gx7l0W8Cq0YL8i1YkZ2BKaS0FIkqMsoEmd2BbVkuxIVJ3ZhGpmrkM3cH7lRqHDr+jRXAP5Saa6YivJM
8w40yKKAHi05801p9+XLryrtn7HArzTritsvl2GwXCgesGZo3eWrK/DH5jyvhiGFNtmzz9UkprHGHzl
ctHAsnNH39wqZCtP+lsABl7LssQRscExzOtSwSjvMvSAHMqjg8XmXBDRsaovm9dxfahwqD1+tcoKnmb
/D6dKIBuYUFOWCQKRxzGMTSuXwmTEv4HhyL6HUMax8VIew+rzdqTnSTWCxyZ6VqpuKnjKvCgnJhfX94
ZLHtyxcFL/s1B+6K+iqTy76+sYZvOH2YiTvlTSz6yWuGpCUKy4SyEP2NJp48ULo1DKj03RROMQuEyve
ILA+3EW3oEKkYg9NpHNxH+dySkc8nDF56m7hL1L2CdCSUQCTv/PhmAqaNDNFq9fyJwJgi4U+X+G9lS6
5HhdmKJ/DoNRAkTcLxb6ygFM2Dsw8JKMlLExiniZoeYLXyFKRXzAz9iIXx22ScPvyn7pIkwrXdTMZdH
haYlgRWVa06/k/piymWfSq6tDEMCpLr06QClMgCkTqFtG1x5Kt42KLUh7EyKrJLxaAG/GoeWAoUNDUF
orjlOhL29rdJn5Wdl68OPvuxQuivrIhaunsTScEnGnob9JeENTrK6YB9QTNnUaFnd6le4mndV7JVcbT
m4vjjClEKjBVNpft6lv2wgIFBErVqeCBUA0RpFKZJafUt6eql1bfcvXKVXoqQBcU9ZD0wHUS6edl935
T59bG73PX9u/MDZlNQmXBrvHwnSrTLo7VZktZLfLcIl5yeK2nVoX6ql0f1W68217l+qCTLTJu1NmtCj
FD64yLDpxZ+NMMg3oV0AhUOjAKLr0z22erCyqoFSnaVxiGxU+k//CClPaxHjadM7kQ8YK1txFyGdA9B
93LCue0Phooz5+ffff8+X3jZFdaqw4TO+N4UYR6kBqoD5Us5ZcjxV78o4GyM6GgnrysJbEsYn9dFjmv
Gs0PuKBbxUvCFW/MqDbBsdbDqo7RZ05Aols+/aFYAkFiOaq+I+OTCz4lGw8zBQOuGUCsImhcBo1tUBP
haWhLsPXR/SLEy8l0RcOEzpztjmZIZZMCzWixxwF69+xp9MpF9B1NzMSmgNJYrzlcwHmkIrrUKYiEg9
vNjD8ZU/JwzhaTdYw+GVcYhQczXOEOF9wIFx+vO2PVtT+U13PvcHt05wUMmuB4kaLGhLoePgWJbrFly
G5J0TsWqHPt/X117Rd3G/v7U08w37zMYwauFGycLPvhV0eNaZiwgkWPgHsjM02E1NsKqx+wtZUFiBHo
sHM4tloDG/a6My6FU8kMWWNp5YjCvkQHR+75Sr3lY0MJpsyRQjYpAJX3IxVtbebElZlACwoIxp7aiBW
hUHKjLPtYm3k9a8hDYCQTHNMbMLxR7uKPZqvwLSspeGJJHNMgF9WmdF0eVgmoNFhxM+kVE940oLOb0L
5uxGaBfapQo07g2JJrW7CcfTkqAkqj5mGe6jTnn5RjFGrERRLx0HR68zT021loFRM0zjWzqXxtHpnLT
Esabl/9KeWCYqgUyodK6vQ9g92+xAKzl3f6BX4lbbWuArIrG5N/SBFaqoO3wqYItbZdWTJ2s50Mgid8
sQgKdSg7Ey56mPEvSXybqwwl5wQqerIjJnan1nuqE9dIbHVuuXbd7lVu3fOSdARZ5RM32NGtNf9JW2k
FIKureqzXTz4jj322xJCjhTSqq8oR5C48C7HKmj8FmJ8/ZGULICb+1PytAP6hmgwRUdG/+NNrCTBuSo
AsyrxY4PX4LM7wEdAf2j2htZm77uwfjo1t9e4O/Ek3q+r00imebxqxJfpfO+PSfnBbCT87E7yk3oGt/
wftpsaRJJwVR1sc4BGbY2WlAqKsnEoZ9kcvNWTpUkG3y6zlqVIy5OgjRycjm4NukTd+4ma9vwV9nZEa
P3a2c7JRYI271LbO9gJSo2PTc9vb8nyxQr0m5M6LGdaNNjzBFkNbMDuDFFEA2QGsBO3KYassr7W2oYO
9haSUq1EWAWsHYy+fnTbakhWPOiHiPby4rLVxH/bwFFSh3ccZCisU25BKru37nlX9RO4FVhKu6zSKxy
47+g6Ee9wtrSD37oetUqgU95XlVirPBTILVBwA7SoM2dJytlWfEf8DkqsErA==
"""))
m = sys.modules["pagekite.ui.remote"] = imp.new_module("pagekite.ui.remote")
m.__file__ = "pagekite/ui/remote.py"
m.open = __comb_open
sys.modules["pagekite.ui"].__setattr__("remote", m)
exec __FILES[".SELF/pagekite/ui/remote.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/yamond.py"] = zlib.decompress(__b64d("""\
eNrVWG1v2zgS/q5fweshkLzryE53v5y37iLNJU2AbBo4LoogGxi0NLLUSKJK0m9Y7H+/GZKy5Nhp4b3
eHc5ILHGGM3xmODMc+tWrV944zRTDP86inCt8LaocCih1Vs6QmOSwyqY5sAK0zKJjpYUExssY/9nleH
zr6VQCj1kiJJtKsVQkp1Ng5byYglSh9wpX+ft3/XjXV2fnN3fnbMhQ+e/WhiRDlPisuNRMJPicwVOmI
azWoXcmqrXMZqlmr/sn/WP8+kfXoHwHvFSa50+K3UrxGSLNIE1CY+G7z1yWGRvNSy7ZeYbfSonSs8tV
UswkL2jFRAIwJRK95BIGbC3mLELvSIgzhU6bzjUC06Syh04qRJwlayLMyxikRyg0yEIRaBqw9zcfGTt
NEpCCvYcSJM/Z7XyaZxG7ziIoFW4AAiCKSiFm07WRu0AY3p2DwS4Equc6E2WXQYZ8yRa4HThmP9UrOW
1dhrACrgm5ZKIioQ7CXXs5141cuGt5Y2DMstLoTEWF9qSoDS1cZnnOpsDmCpJ53mUMpzL26Wp8+eHj2
Du9uWefTkej05vx/S84V6cC2bAAq4kiMUPFaI7kpV4T6t/OR2eXOP/03dX11fiegF9cjW/O7+68iw8j
dspuT0fjq7OP16cjdvtxdPvh7jxk7A7AaCTHft2vidkgCV4Mmmc5Rq93j9upEFkes5QvALc1gmyBuDB
jMKpqX35Tt8dzgalBZqJA40fEd5WwUuguU4Dh8ybVuhr0esvlMpyV81DIWS+3KlTv7X8imzz0tMCkmY
HGza9HQtVv6P1YFJsR1G8KcsyXzUhET9CMtJy3eOuNMlsusEhsCFmx0aglj2DKo6eaMJd5nk09Vo/fc
QVUde5ALih35HrgMUxAUdBUTH1l4oammsHki+puOB6sIqg0OzcPmxkb8WiWPZd8SfNGn+fZmnnPC1GO
4MsclL5EZ+Ugg22kYT3cntWh5WNIWCwma1IyWaDiAB2bGBYjHyehgjKeSFCVwCAIXvf7nWe8FF2Ka/p
notRYuo/H6wr8LvM1rHSvynlW+i+K8CiFYxKUIieZUhxHRGtLNAIqaJGXVHPDpcQqGzjNxlhjShxKoA
JnTJoQkqDT8Rp7UV+1bptqfD2bV5hTztFptf7/cgICDjohWbZt68/9n7+xqTjjIHtSXeQHgvPfpCdvc
Z0B+4Tl+Vf8Bgm/sjNeYvHB4xNPvEz/7U0PZ/lt8FII/Z1D8q+iv4Q8F88hpiaXJhXXqYHZZfTaZZho
cu0wZ4khsuGQ+T0KyFCvtG95brHtFLQoIN8SpI3dK2hjea/MzlzjznqqgudsCpW299+fj9vODxRGZYF
Hdgk6F1FtK9YjXihncxdTic862B3VlcpmJ021C39RyKzLXGAdZRgS9FyWFkzbr22Pbpe9SzytbI17Xv
Ka102Zm0yyMtOTidsnWye6bgelM/FFNeFe8VCpCqJGSRM+lo+W2pdt3P8MNidRODZvZnk8Xm1tNs0tN
TUclZF7NbizK6QjeL9BForb0c3HVsXhM3ftTHMGDPecJs4zzxFvO6RlOUbGE9rdzL9GQrCVogQBp9iX
huFAIMe9tWTIOBKhZ0sCLSIn34gSGqqclyXdBIbsgmOUN4wFz9EwpP/xZwsv9pHPaYsMlo7mnL0o+Mo
5GnOUvlBV7RrbCWx5IOTRl3kmwRluqoCRYW/bWB5Q2ePAa3Zrm4MQzMieUXgLyPM9S0nshTBum9RdqI
jn0IYrqRvvMh7Hw/7BqCV1iBSOLXhfxdz3XmD9MLRIXuL/OCSIB1sL+t/amu/ldYS+g6PLlpJXQwrQ/
6Hff2xbZLQTKrpF0QoEzlw6d+TeDs3Eryx6bGcc6qoiK79PNr35L2RTDHkD9i/s4ks7iHp3MB6ILY+w
yuo61amU0cUih0IdnACmDj4YFeSpB6Oly/pd9uD75nK6IktWeCObQdCvl3k8GHKTJg7vwbufK22Oj2e
oG+7D68cHepw8bm+6ZZ6YhDjZphwNzVv/UHN2LhouUvAEaWc9hQKSBq3IwKFp00wD5zdh8fJdpNUltb
t9x2t3dMwarayPVe0tc6490PfjThO4X8ARG197ZnrMNacgcd7C4HCBvh3jNC3kVYU+CvwjNWBH6vfSZ
0csaNLexr29slhVeckLIGVmwVpX4AJSJAkW/C7tFrWZLgBIZBMAzO6lnTnYkEPcHkJCvIFlPna+idSo
xssD88PPAsvWA7INY9VlnSYvcjSh0zgnVLhxwVZj6zsFxN6EDwb21gUHA6PpbLbCb19Xw9yPFCE+BGI
PfPcDDlpwpHqwyuin1B7BbdqonebPfiopVhmo4R9/dkJq3fKsBNWK83m5cxGr269WW1c3o61+rrOnjd
tIO7EJFgW80al9TdxYuuxdpvQza5s7aGtydwZpu1dC7mXUJdP+TSYm1SaTAq/ik4nJtjVBd/144OP9s
N/pGHJoOgp/an6CRfqJvWEioy63fiIEMl7XZCppjnayh7Zv3k+ORn5FqP8C4LMetw==
"""))
m = sys.modules["pagekite.yamond"] = imp.new_module("pagekite.yamond")
m.__file__ = "pagekite/yamond.py"
m.open = __comb_open
sys.modules["pagekite"].__setattr__("yamond", m)
exec __FILES[".SELF/pagekite/yamond.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/httpd.py"] = zlib.decompress(__b64d("""\
eNrdfWtz4zay6Hf9CsQpH5KJJNszk9RexXLKY2tmvPHr2vLO5joqFSVBEmOK5JCUH5ua/366Gw8CfMi
e2eTUnpvaHYt4NBqNRqPRaDS2trZaw2WQMfhfvuQs8Rf8Lsh5N3lik3UQ5p0gYh+Gw0uW8fSep93WFt
T49k/9r3V6cjQ4vx6wPgPgvwl85kHIEanET3MWz03Euq2jOHlKg8UyZ69293Y78M//aRP6b7kfZbkf3
mXsMo1/59Oc8eW8y/xoxt7+7qdRwK7WkZ+yQQD/ZlkctURzSRovUn+FLc5TzlkWz/MHP+U99hSv2dSP
WMpnQZanwWSdA2I5gtyJU7aKZ8H8CRPW0YynLcQi5+kqQ6Txg70/v2HscD7nacze84infsgu15MwmLL
TYMqjjDMfEMCUbMlnbPJE9d4BGq1riQZ7FwN4Pw/iqM14APkpg9HI4Ju9Vi1JaG0GaLl+jpinLE6wkg
foPrVCPy/qdas9Lzo4YzDsCHMZJ9CfJUCDHj4EYcgmnK0zPl+HbQYckjP28WT44eJm2Do8/5V9PLy6O
jwf/voTlM2XMWTzey4gBaskDAAwdCf1o/wJsT4bXB19gPKHb09OT4a/IuLvTobng+vr1ruLK3bILg+v
hidHN6eHV+zy5ury4nrQZeyac4KIhN1M1zkNUMpbM577QZhBn3+F4cwAs3DGlv49h2Gd8uAe8PLZFLh
K0fJZ2C0/jKMFdRMqFHQE/E7mLIrzNswYYJ/9ZZ4nvZ2dh4eH7iJad+N0sRMKENnOwV8xm4DQMcyZiZ
/xH9+or+kiaM3TeIU/mEzj2dRPiPnEr/EyX4WqQpypX0A++SuLp3c8119PukjOVwlOWP29TLk/C6KFT
ghWRWbqT/nEn96phHUahsGkpT6vqZVrEjcC56P3JyiCRJLCXiZe8U9rnuUfYDqGqvw18hr/59np1eWR
Xama07bSStBUU3F8F/CWAK4F0TRerWD6yTLfVXMTnDUqV/4o1wbii1+VAmG8WAAFsYT8WSkCLJfH3Yy
HIOf8ScgzLGx8muOWTZd+QO3RV6sFbHcLPYtmAQoI4G9ROGP/xQTuwSQIA5inK38RTL9ho+f4rpWnT7
0WU10GacVp2BnLs3EejzEBRLxK7+ofSDj8AYJ7lbT445QnOTshKIM0jdNeGQRIKd1aBqX4zL3da7NXb
fZ65EkAmDfjc5UfepgAcFYJAAhveyP12cUSrkefKc/XaYSpSB92HKAE4FHOLp9AmkXsVfdRiU8atyQk
mk5Q0M14ArKERDT+5hHyP4OB/ZY9gLjm7AFW1zUIUBAvKJqg013VCWIdmAaw2GWc6WGGj/GnrK1zamg
Dq4EGYExtVbcJtoZoj9nSz5Y4FSXplv7ekj+6QHVfkm8ZAvVkqS7mS8Itw+46wdERhU1iQhYAmQULGF
/XA7Z+4KnrNQyzYtil34yDhAs53Yg/iJzaJgSLX8Js+QVmC2kxxzBqM1jdcx85HYflecY2Wbw1Df0sY
4frfEk4uwPqBq6wiFwCmVAIEZ+v8nEW/Iu7U1i5c8oN5ow+2AF79Z27t/vqzXf6H7tvzvbs/VuHbTNR
m+2wcnGvGV4F1FkTqAYoFQC/2ACoTMssQPmUrUkE4vlj6icJjEStpPbUBB2PgyjIx2MXBNe8DUCpVBt
omS/HwNISG8ztYhowoMoqMuADwMxjyHTjjMp1Z0Ea+SvuakBtKl/5T5XHBdOu4BUNSLQAvvxVZAnFuM
iRCQZyIOBRAS1KyJSiyBKWS5ArRhGZYkAB7SnKx/5slvIMS7rOOrqL4ofIabNdE1VSnQtI9F1kP8hst
WZ3hxwnnZ8+vYMvnDZiXGCZjjLUGMdIDzk6+NPrqZHHL1UcaDcbA2YJiEYuS+NcazMQ7BnMQXMcCYfu
QwrT0nX+2bmS1TpHUKHHtrPf0t8iwVIz7j1f7Uy0YNZUjVrocZqyzbgpySJG1eyPXVoBha0EQTO7lq4
j5B23gjZog3furldpiHL1tLkJ7GniNmsn0CoA+5ad+XegxMHCgsOR7QDeSRxEIN5CvvBBS4d1Bz55Cs
sTamZ8BSo8iMguzuBkSqNL7MSoX4Px5Vv4+oM52Genx97s7raZs8oW8Nt5B1o0nzmYAAt2/pRgCSfnj
/kOKo+ONcWcPMhDKnC5BEXlLah864SR3CwVnMSzJyy3nxxUiu7vJAcO+4yovdnds1BzIMExkIvTSTCb
8eiL8UPARu0m3A6nU5x6xzyCjUwXFNU0ffrGwu91Gb/XfxJ+r/8c/N6U8Xtj4Hce57Bjgn3mV+D3hhm
1m/BDAYN7PJDMoKLG6RPuk0SlGmx/2N21sYUEA9sT5GnUWyVDfSHKCL0Mognv6xgAL1Gdg33eKsimcT
QPFusUdo3Qm0ka3/Go2oGri7cXw+vhP4d2L15Zvbj4pRZzUiyd6oKlsHKdG1hlOiCMorzHvgOZV7+2U
Z3jIAPxED/02M7mgt9a5h+QcP46hP1fPInzrJs/5lDbg64BhLOTs8F4+Ovl4Bo7RyCd14sE8b8PZjze
gY8EemZC9/0p5vvrWRDv4IfonuPn8YoykgQ2xqRA72Da9484epB+HxRw8UPWm6yovQD2J3wHP9olUv3
rVRnsY2fyryB5pSBMy/Qu0WOaJLUj4kyzTGfgb5UMfLEBpDOdL+rhzfJZBdVV2MHkNuXH03L+KnuIUz
XXnEUwL2iBHyVaLP5VJcUCSKHqL5+hxLKJEjDFStOtVBHTauajs/z0WOmSP+1MgghU+Te7qtjv/r2/i
aS/+2kZDFbp+Ol0GdxzDSZZFPT5PeGLEm9SUqmArJnVwc+maZDkRZk4qpTCtDbT+cnzYGCbX0/k1WzT
8ID0mAXFzHrs0LeqGt8Xk+fTOpje4U5bAXBWst8if2X0e5W8KmCuyhSD7NflbFnvzb0J8E0ZV0ixs1U
134Sn0+PFoki/xyVQz7ZkNi/TFJNU15LKwCVxltsUT8KNhE0igynwQ1UDCCXY97CErbJOgltPUr902a
fNTTw91I95ctfJaiaPrnfXeQlnphtFnJPmFRJikqqcVVqAJCmWmZMtDOzoQ9bLNkoTx+6W1ens3iA4f
Ki2VM2HeVWMZct4evfg3/POHDTopQKVVwXDYwcT2yK7TiJStqwezA2JSl9tU414zOt7AIgU/IofMv1R
dLkk4TWzPoZZA0ehnURT9jGt8jykyTFxUKCXcg0Zfzx4d3hzOiyXiKc5zztZnnJ/hcoBqi7Dwdnl6eF
wML46/Eg7zW0XFQ8vczwz9+/XF+eXlP8QRDPYUiR3x37uQ8p29pNd9MPw7JRK7uPoH+zj9vagRhtx9s
MguoMNUtjfyvKnkGdLzvMt2HrNAh+SpinnUZuJv1tVZcZhy5TP+1vbLqps8czLejs7WquJOK3XRQJ81
AJBZay/pdb3LUZqY3/rWKpEJmY79d2gGgfbLv31MtZh2y4eEcDP+233HrZv2f6OKFSt7+zvEIH2ker1
8Jd7BXAovVdfahbcs2DWJzBqDPd3IHVj8Xkcg2IMgwT/Dw4uUaaJc6n9yYGhIdYRrujb5ACPyOrK7Pt
ykJzv2cePHz9cnA3Y984WtSWNdThS+zvBwf6Of9Ddn6QHNXBO4ymo7ricoVq+7Ubxg5d1Ra36HgJZiR
L7JEyxgGEfyNdJZTOfrZMErS1jrAbs+84PM2FKCeam8afLIzS4j7Ms7Mk2peUnimCngybhvmVHMgspe
404XemO8TOe4Nmla1Zps610stWWdSbrOVoXPRPQw4sBPWhADxYgDt1THWg2PHQNYin6ge4yluYRaWCZ
x+nKh8a+89NFJokqDzK6p/HCvXWdNewDPzmqKNtmVHRkG22EIUwCFR9tdu+H62aL0nZmmoJcu5KGXgD
PKgNvgSNAFlLX+ezDTFZTSI3DIMv7t6M2m/rTJRA9DftOkgb3fs6ddvOuq/Sf2gr2jVVfYgY8p3K7wo
KNp4+uKOh4dMjt/OTQpjqIdFk1oOqbfY9y+Cc2XeIJQN7fzpBKcnUYH304vLoeDD3TvlmMgnOEfescx
VGexrh86b42VoCisEntDHF729ZIiOJ4PisKIsIGHa1ZZMITf253R4rst3sjo2lzTK0RO1quoztl+sPf
BU3FTMU0PlPtBnPNq8eDtzfvxycXPQaDGeUgRPp9dj04Pz45f8+OPtyc/8L6/f5vETCcsFkipMq01Kz
5qNgy5JErMPGaSovsRliSL8sT96W4vxxriYdBzkE8N+dMiYrEiciFVSHaq+nHLnakOsmubGOylC7Cct
t/hVbJVbboCwtK3azZMOcqM1bg3Sf53sahWeTL/nkcWTIGZZyUobZBmPqL46kMxGgWcjpOk+kaT0N29
rp7IKRMOSVhZgvJEXQyMwOJ3mdvdvcap4QDa2gHT6RgmqFSt0HaOG/9LJiCduWHq/7lL9szapcOYfEf
19t5/ePurhCRzB7SviKSRs2eMVW0hniAMOdpZxBBNwLcPjFH1mpgW6J7T2PfLE1OqaSjhkrNER4G5Ht
RRu6loNQA0vg5Fh1MsW+yj/HbYENbzKHgNjilYWaUCSlEVvnMgSx5N0kY+zO1/szXYTgWJzMEYy1ylc
qxhG3vWJgsuwuew7Ir8qHLxO/WkYSrKiOirv4CBWuYrgVjp7wLq/V0qTJNBIrVNeJ8dulnZKWqExVSc
UpIl1wH40SW1YdL2J7oDhS940/Yn9s7WjLucLWo9A3LuB42cGctjwoyLJEjs6sKrsIYF7I7NKviIaBC
HeeVJPNaZrWZgqjoLQABfkVbYlFVVVTPVcka9I1pUM66ldVGKAk0nTRri+60VBvuRvIydeyI/+nEfn/
zoHiqtVJbVMka6aKkH2TcOCjfOolA/wpmutEtzyK8VDENemeQjtSGrUAYT8XZY5t9ykqM9MLmy40ILQ
lV3BVIAV5G5zJ+ES7wCwry2b+Bk2qpGaGEp6ghY6EjrJG9jEDStQP/89d0bm4eNQtRgBlxGvyLTAGOV
/AgZhQs5i7jhzbzJz++8QAM5nXRUzBxvW6WhIFyn5F1obDywUDOcia46Dg9Y1Fya+YSABYua90Zx2UP
G4gWLjUqW3F6jmdAketT06ytacOobEqZVhmexYxNVG41AJKeLe4/cLshnXR+4U/ylx5+T7rulPZFx3y
yXggVgcqyOR254oYGJUrNRu0llW8iNdK09trLmla0yKpgFlWGBal0gRYila7iMNJaPcT+2GZbxd8vYt
3SfDJYuBicYmo+B6RmhIwB0iNRWXn/BILUk2QWj2/Or28uLy+uhoPjqrnBavsmQv2A3NeULwcTRq3ub
1Gjjkd4/bD7WuJFh5JVBVnYLD3pQBBkUwk5Q2+BGYgC0FBE48x94rlX4H9xOTy5OL+WuAu8S90ySh8P
TgfDwQsLX94MN5eURUFyfYABPonmsUlCdLQd47JZK+k+XFwPnXZNBtZAzVQ50xTKtwGwX+STd7XOsjS
NEC1SmNoTu/HKEBXVUg5DMOUo0qBt3L3LXXt1HZ5wqQfohcTsKW5SZDKqRsCEBEV4PdYA86d3wGWZ1J
a8QipPOKvTAlSFW4A8MqW8O+G3bwfjtzg6o0YNIssSPoU9eoUcovb18HB4cz1SnYeUk/PDo+HJPwaeu
V6YHUbrjpCFEoPji7PDk/PRC0wsorxAGGj1t1091Ni+bqSsitWPhqRggabFf430L1XfhLR3uzsqGGUH
GaVYAM0VoEQgxamGe5mRrX8b2YWuWc8D3Nw/IM+SucYC9JX/4TbjTwGEA6oBfe/0/rbrfDU4rzo92+y
Pz54hxt8PhtqRjHz5+g4kKUtdw9KU+Km/guUJZHn6BNum1F+g2qOccV3t4ygG+VNGvo7Ck9elSoZFwZ
SCRjIufegn7ZuyoeSGaLofSuYXdauKZqOKqbYCpWXa9Gxbkrn4AwyK1KdeTpaX2UtxqScjjbmsS+s3N
1d28ss1ymiv3XodDG3TUB+HHgaVESiGBupMqWGuwJx73sh7gdmtD+JxcHV1cSUMbvCJQITZeww4ud5m
FcR2VCopIT9oU5hwYzLZ9MPg8PjZUw2tGKlVF5lbszWCsGBewkpa5n1M+w9g/iqL/yk8TkCETlmZVeZ
8a3Sp1aXjcDbW5z368Kc8ib5l74IU7UmTNV5AoAtJSGFG7eQx8+l6XLfblRWmwgyG/Q75HKU8sJ1b1X
Wm0uYlijva8vywRJRE3QO2a9gWJk85x5FYBZH7o/Aab4uCnm1b03SQRs6id128C+QKSF5RS7TW6cs2W
rrvf18vFiHe8IKphLdVqPuCEtIFL4jug2wCkFu1CJietuUzNqukanOKmjEM/CyYIu2mi6ArOM84e6on
JDnteYYIIFDW7ne1DvMAbzHuIN91sF2n10Q7G3WD6RCndwEPZ9c5MNaCu4aAnCd9G4wpPSXafbMPZj4
HWqZx1P/DuRr835vB9XB8Nhh+uDh2emoOgRQ8ujgfDs6H5PGHGdjJz5bRtdpv27Xi4eGhQ/2H+c7RHg
z70J6pTioWPuizH3aLiw6mFijsJ1p2u+7WFZ+vM2QKmBPifssi8EHgSrKR1GBbm9aSLWFmYO52xgSHd
rc8PA+xDculkdByqczlqlqb7VnkqTfEPq7CNJlqO2zR12/ZR84eUj8h3hdnsHoPKJZVOjEbvx28Pznf
GQ/Oj/EzTvEkLY8NOPwREBfXJVV9OeJoZUK6YRaCn68jOqnOurr61dFJSR+ElJLdEQt1EYENnupdtWp
QWcJZLErKwr5xHvwl6zqJ05ct7H/OmtwkjPSKUEsIe4NXsr6W17SypeVZG8t/ig5nmmv+ktGmQRATBy
c7Df7/zLC3XjLq9WMuNa444dHR+5PyWY8iPHnTje9BIEn5gVehZFPGHazySVEX766IrgJJaIlXFYUke
/1KXBETplcq49IRkOI+cfyMYocyexoO/b3d7dHfbhDN+KM6q/5+b9TSMtH5kupWZdj5imJd7Fw0cx1F
aeM0Do+L1HmPGMCxOE1lr3Z37XR1ONcnf/xSnvKa6Jt+mNp7AdHQnbjtdfZGihNhf08uJ7JLJYM5euE
ZiwQeWuEJEjRSug7lmAc9dj8AuLnG1ACQF6PqYBR9roKx1nFL1akDVBDoGUhoHqNzhuYuvd591ao5pF
fj7Cqieg1mkM1VGiytONvkBLbw2SzAcJqXqflMDWWDrdBucz3lnYDTz/Y2Mn571uQXC2i2Xrm3eKwde
oJZNaeOPMtur6opmZNyjGVxQnOvInewYGY6R1ACDJ74C+3culBDXav8PYatg1ndazJ6IYpzw3oJELBn
syB1jRPmkRjGb9kVX8X3aK3OO6Jl3Pnp275AWJ+kKeW1Go5WhR5GQoZnjse+6bOPg7fjk/PjwT/Hh6e
nirVUF2/nBZYiTa7D7hyNdaYxuOvgafmLbVCV+mPlaenoPs9R9iAWzj5d8D9wRqpjhEzPMAS7c1gW50
QyjWwxUebGrFUb6jNIQi8tqFmMkKEWUD30FYQ6anChGl1ylg2R24QuLpfpi2vrlMUEs6vT4oTIyywTs
2olyIgHDBcHCUbcmUSCQAFnZGTJYZlH6BImKbrjgMozj9D/DX4bhT/NI2GJwFvtn9ZxbtPAljHPFmeM
8ivXiktlCtxxbCzkgRh6ZZvFDxG6WVgnn2h+n2/0BaxwnmsMeX+DBzjNIjE+++yHPVgrdz2L6DZ69wF
/MFBz19E647BlBDQ8gwi06EGaRQToBSRVB1QBh8zCENtFPQ5Sxo4hP+zydI1uLBS6gjq2AX3sFHsO7I
mcUZglJBUojfs+I7j9re1sS/mTZz9vZ/0dSDjYztAr+RnrMu4h3ThpI7OALCx+bLT408yNE1MGJlmhk
lamI4XNQMmrxCONHtp+jAlKhYwZarh7eS+Yq6oNhFpblaSSXm5BNKUG+ZrpBAVnqiD0UtA1n72sAvLn
l9WgbnxZFZy1WwfaW70Y+40gHMhNG3OJLxzFbIJ/vbZkxLaYeBu1AZimbhEMxaVueZ5gr031QBLqmbC
P7P5fYf6T0xQTgXlVPwNrnHGYD4BW6LTPV0n+JPzuMYG677VqquzIVcvSPRxFCyxbOOHE0T1P80u8nG
7FHhC2WBEHQorgdSSEcGE8DuZUpDsPsN0uLsUHsNr0pAnp5EI64Azug3BLygN1D77BEQoyqRggp6/M0
1+hQnzniBOi+oNo64ALtz497aVdnDoa9XCF0idYpK5Um9xwllygQqEsEgp2Iuqq7ceOYxRIubldKoRJ
X63maRznpSRhMkblsmjDQ+OxdnHUcPT+fc5o5RXjbVRT+WheS+bfF4vzyrZ/AOUICpJNE6VHpYrv22Q
+Mnchyey58jO7PMHXwyyK68966M2lNWz0Ae0Z1kRYffHsZQVqX7EbMsi8ut0rMswhsfRqXaPNvtNDWb
830tmwpwb2zt3dtsEe3SROXLU0qsg9mkaG/q8mqDAM4fmGcEY1JmlbeqCCHtAkkVAz74t9V2HAUAnrC
Whz5gajFhE1uSxJYYkAoZdrxMvHziXtUu8wKgUpxBCunNSe5YBrer72Ghx/rFVbohVkAcYpjGDWalox
2sYVA6YycGaq3yNDwxdpyH4q19DvazVQ81jAz/wclhJRFcQGKqFYSN4jEeldlUqaPW0sgRaOoUFh5lh
zc4O/cThWcNDp2LnjPHEsNdCEIuWiK4pBcdjkpXSm5Fh6KOiCdKGwS0Yk6DAprpEScCDzbzt75OfhCJ
xL+rl0g+5sP3alDdDQboQC2zJxFGxpaatNs9LY7YpaXnVnoirwRxh1k5FKunbWXd2V+LPQBv0UCLyhd
VPbFtGb+mxPpwgRXkJEwBRMYA4L7IyNkejZHdKDYCM/idpymFD70ANj2L3qtld2vba5o3xBlyfWLksW
x/V0LG47iChVFva4CTFLSn6A5JbpV4fk+x7pV8wynJton5VUA1wfJganzWfyMFQJEDmrxEU0s9g0jDM
Ze6nZY7G3wbNQiGMjeI4lj4WBvSJrtTal3MAbJnCCYCcE1r408HLBTAqHNNxQ2FESoyLmLDrq4klUls
cpZ7+vMwpTxK4/HML+UwYiDVJt2pFQpL8SCSWGDsCZCMbJH/1pHj6xvVd/oytuunvQJoDHm8MPfNYt9
MTCMZ65Qp9RHsnA8wDFM88fJJ2MEHiAY1HFjEPX0pcDEl8G7FLlaLbIE0VsV/y8LfJHehEzVwoJqrRS
GC2on0qpMKdWTTHBiC1TZSbjwE4OHXBKS1b14kHBTSr4H407hmmyDz9xnZFNElG/BNTryt2egtFgRpm
itLyQPw/+h93demWp5vCn7p6ZcqOtVMP7cV6r0ddcqI6a3I5lZhSmMddRH03MovNHtkDxw8l6RRDoV1
N1kVmqSzNdxJYjT5amyjJ3ZNVTp1euK8ColVyodUJsiIWF8kXL8qpVy7h6QPjTdDSvDEivQ8ot2bdQu
jTn/fZbcyYl3vb2yIEVdQaDacResfDid52TkEKqSQyFtqQPsBtYbHz51rMnkhq3Ova8FWGiAB2Mu2Zt
NIikZXI+C2PvL5qIJCj1oBMwNBCpvj2L2N5e1T2ivKMgix018oKjZNpRFBjpbQSN1QvqG0tj5Uj1r5U
ItfKnjmggrVoVsd48YG/s3ZylLojbjH4eTC/t4I5Fh5q0hSAbZ8JYBb+mi4D+AqVVeIS29UdUwfMVdS
ir9/PGruhLN3jFhKoYGViBzjMbPJvipj9F4wGRnnY2Uc1dQm39ZTDjTZUNZx0RaTznLMn4ehZ3qNkCu
hH9tIx2IFR4+6hDVCiddiQwc/FIGuZvYG93rVG6dZNbLNrDi/aGrWSE9+1p+5l8jXt1YdgugKqrCF8F
DwSjef4hujSqkEd3rYn4NUYvK2ZC9fTfYjXzGhkpbZSuLGE1g7NJrhT+JK93X0l/kjPYe2EwOOvm+ka
KuRQghc7b23hpYgf3NFUDh/3faIPSIjlEnIOKKdGVQamKLzpj0TFiKHukqs+eYMkMpuNsPZ8HEs6o9c
zU0XGwDJpJPG53e7sjAxldtBj/uiadoiCe+ohIWhpJPAqvQxDT7SsSFVShiL09Eo6NuqLt72jAE/zTs
9sgcC3zYEighXOoKKjMHW3bONJAIbGxFXDMA0ez09pcb5XWMhcRIWCIh2ymV5FRTbtzquDVnfFK80NQ
sYE8MwXtqRuULH320mRkTFLu35UufqpAB2bZdD4G8UJxn+djqZrbFum6FUhJgC/qR9FAOrdbsREBiuG
vOotl2ZRCXEMG6tI8sO0tZi8KOYUO8GqxN28JlECbvPMFYDFYfQWoto7KVpUAFeV7hkZSRyBljDH4DU
MmWfYg+/y0RNY50TWdC7NnXF6TzAGiWjAOlGJZJU1LTS17le+huvI4qq1OX82bwdXVqggVrrwlgGqqG
4pgrmR8nKyKmOJ3EVEdNY7B0F9kYixJG2TS26uH90DzVJlikB6d7An2fivlHcxznyShjM8PuzN5fu5I
sVFwyK0xIAblVs+6WNljhHWCKLZgzPj9l4KIMMCcBWQdzL4UyAKqlLngRTBwk2TSgI5vv6bmlGqORp4
HQv7VG2MdFSNTdwc2mHcimDQdCt/hyLtTxoZ3ru2QG7STQjd5I3UTjPx8hs8gBaSiNARBecm2R2GrnQ
mQPwEkdqnw2/iWvTv559mgx67lFeXUjxZcMFzKs/WKnk2ZiJvTuYxCk/3cKkxqJE1am2enlCjCXVf64
G7yvq3uzBocDSv0eW74ZTgiKX6eK628Ba1+oUOYITyDjKQEjf9z8Kr+hpkcCQKuRKJrCW10HcZG9370
2Hf0VUiqnnXpaHMwHLGvJ4krL1joNi0tQpTC98N6cmm31+ICs4IKvXIoiSLoDoHbroxu3RJbU1NHAJj
bdn1h6ihG4QWxgAwzgIhcPqIj9J3tTJ5ZmSW0R4Azalua/gscH9GwJPxLC//Hi/P21+zJLAfKBkMQhT
EfFUERC3fTiqNpsXfznjWVaLAuhm3fDw6OdaR5BEAXymZBhl4oZM9EpxX23D1hY6vDAGQRsl64vCQHl
vXS2PptOi7eiD8G6GuZHkXQF7zgIYM09LfwAsMW49FUxCmtuWJmO145+0GUrHMZ1jRbT1ZBviXiIfa3
BHIMDW+bauFobJHRs78lzrG2oPfYYIkIpRlBn3YcWHtmtRrsZKUNqIz8oL1UK05Bhm4nDg9Nfxd5HKz
fBjL0L+I7y+1NVHeOT64GR8OLq18dvXRgjgrSUMTA71lXZor0Wyg+qjz4YeTrmLwjHd5rNhvfqfuTdT
GPCr8m01Ep49MUT21BBHb2SrrjH43PCxSPHKjgTAKO87mlDwbtA0brItCGSC5fcR2oEvxFSv4/Wirkd
Urx0av+WZhBgX5aOiC67m/FuZkYRpdEiUh2/J66cbTAKSYSXeHQ/Cs+o3gUr2Aq8OKRCEPa9kpeXroI
9X4sbhhCKUEMlSnfg8BAhq3SkxNFI8YrESopijFiOPkqAOQ5+Ss42792tled7Rnb/tDbPuttX8PgUhE
KSSI9NjUIIB2AOLy8/MfgitI+6/ssVnQyqY3ZgS5wWORa43xvXPEY1YVdgXxPT57Clxmb+JTZEPWg0R
K3KUK1vCFJbzhOQIMIppyOjzm+1CcuqxwHoHJl9LIdZMVd49YReSw/j4AxT1otoxBJYCpCFxWFeReJ8
dhRZq8OvcuH0wszHONBMkUIqjClVwUJFQSlkBHJuL8Tzw52xb1K8eEa1Jf1R1XNswDxx2d16H4c45bO
uA6qX3cFhSCLQ/6z0OnER7ONS+QXdi4J/lA8cKfjl9GlXLy2bjznQ2SZxqFoyXAq+DLHg/JxdX3VJ39
Flk/7nIxCauJzi93Fr1igYoc1xMoF/BR+VS4B61s1PUtDNVQPq5RUbWilG5MD/Ce5FyM2bLNb1MFHGO
mlXrspAXccQ5VUY0UnqrTWGRcBdrQVdieMF/E6N6zOmxxC8QqlfMWwLwreviYvKgqrjJonGZJdezq0T
bEgVFBvw0XKP8PC7TrXIBXEtMC5RoM2zvEtnv5P1LX+jrNxd2NZyFWvm63jI6/mGu6XDkQQPTsObfZG
tUS9McahaYTelEaoaLJurL4yLk7zCAMJaG3rFZjhqdPPDvteZBTlZI9sN2uhdfyPnIk088x2prkGaEZ
pz+yNv5B/ak5Xaqd8JZ6fDp1JSLUxavA3+MTCFjktUtrXhjqq0SFtwdZ0qPxFfO94JV8i16Q8rYBqyU
JQ8vetVUg6qtSzzubzNLy2rePzVSL4vW6M4GfP9JKLlNG7+kPk0hE7nsBNRdj04vyJ/BGJhm32ssjVt
Q4LxuOoG4mgn2irEEGZ8s6CDONpOI2MqnYgDSP9aR3k6v/PHXMiRr/4kzheNd6iPwShiGpyySApgmnP
w3W2NGyVcdYd80eQoa+8l6KrdlsWqhW213syvRurNmCc7urTz3TaBNbekjXqug18oPcJQDJhdK8qL8q
V4IhUIlD+P78UZ3zo7WV4b3yp7i/HFB9T+4vJm34l2mUFrsGVqhT93FSIyftN+t2ZxlqZgVIIhKa40i
i8Nb1e1Q2l4hPc6A1ckSDVad+IjnSkN1wFm1AxfLtMTG4VhNFmnIp4jJZkFaDKe7jNoEodrJp1Nwxbj
efQn4VWCSlrwSmeYXQ2IqqfnfS+qHNvio1VZTtM1zGap5ElCYxrMELQq82d9abUNjXSaprlXfFi3vOw
xAtUUsVts+q8aqwpDZFFGLDqCqXqisVIUiVbvESDpnVM1BDue89X0cdCFZZ5vjXz+Qqvzp6qnhfGmAk
ks1APoVA2c7w5KF4JInIfHp2OLy4H58oPCr+vBofH+J2qhI9XJ8MBpjw4rfpnvHGbACKGZCUu61GUmS
EIKVsGIzWewabiuKu5U37++hklilCDf4vklTxz1C4b5lMd0zsMyLfEQyOhTE/v3Nr3vFWsHTpXJI/yh
zb8Q7ERMbxB0eGiNgaEFnopGVmoF2oXI0oosmn7yxGIwAg4ky4hBFFnBSOBxxLxIsOTsOmSTf0IzVk5
hexmeNcGI391ri6PuhLG3/X7fgxmY0Y1oE30GMyXHJicnHNME8x06eeM59Ou+aCHRAQQd04v3sNK94f
j08vBTgn5ZzjPERRQtQyiPFdRBMErdjoX7z9/1oxUxAfTr8GPDQY1RrjrTz/hG1LupofaZV3TDF/KUQ
1jEDPZ7L3l8Tq3QFvnuyU+MnIIwZSH3Ncn6qr5e+OWs3wfTF1yLohYNO7qPYV+HP45s5zp5m4NqRVm2
hgxAlN8t4taKAy8xjcMnLrI8rKft384WYBPl067WcXFwpnBzKQ8/FHOlE9ETrvjMS2XY9f7TNw91ciT
MBD/Np2emP2hreQsXsEaJT/IHPnnU1nIxr+YzOXTGQBLHf//io2oQ8a9dCO8uV4sdHxybVPDUQW9i0Y
a35QIZtXXI+Zy9HGpwb+qREeXIA4JonlsnEDhUTCy7MRkZke0BMmSuYoc1QrkqZ/4cJldIE7xAIkunq
lCeI1+T+jWup68yerYteVxXa+OIBSwnWKsD46uBkOz3UmB2KaKl1cXwwurnijxTLW3h0e/gCgtdRStc
1ARZII8b5tzuaEam2d3lSWGHkaFshTncwyfTSWFqEGowUzIijkvCYvhGlc+12IR7Sz+2Rh57YGk2cAS
4FTkeZlTRlS0W06VTNDGH2UWUs6qqsiksUi2BL1iNrbMYf8bhZr07SoCkWGMr40yPZj9L+2uQlr24hm
5NuNh7ayTtUf18S9TLvq+TslS7uxhcBBMXknbuSKhHfbS0Ky1P5zpwlAsN8ZCo8ZsdTeWOmbNkMmcYs
heMGJSYa0c5r2IwNNlMBOvRuwolymrNX1or1ErHrgzBkUhYbct2x2Q77rT4AKoqt4iwBGp3VV1mzjux
fr2HwVJyzA+v1D3vh19rgn3KsSeHr+akWsD+mLPQdqbSPxsvs3ynzX6vn56V0EScF/OD88QtAq7oNRn
HWbxEz2g6Efy2S0x/u3S2GnWw/JS+hSV5Oi3KwLJK0ukf+cdDVuYfY3aX2BMrNYGViteL7T5q5FD5GO
9me0KpGXPBv4UNFyE8cQPGWwsx6cn52LnLiAWNuKcnlzffqTjPjP0hxOGRY4CIc276lNEgtDGNKkuSK
RNaoikmukx9ue5DsxbS4LQR89yeu8cUYvX+deSQ0OScdwMyHs/ah8OimXr5zJYOBqK8I3kNn5H7IE79
5hMJynyNni2JB8cNDMxDprcE8Xs16EVXKPZPtslbypXE3C/wKq4EqmtgtrHW5eXQ4qKnR+Gqn/Zz4yd
YBgJH1+smt79rDrzkZOlxZ/EawpzjsE9spDz5KmNbwrIjTlD3y4zIDrt2gtrAtkENIFO5lQ+UCGgNW4
UHARDsmcshImN6FDUChk1JJ7TB/aXYX8luAFdk33wgxypjvhAURiCDBdtoPvh+bHIpT6ziD+IIYLeTD
jqnejeHktg1EC8YG4s3ouQHIOF+WMSpNwT3RKOY0gId89gjjCUHk3oJXmLM2BkhPlyFbQDHEYdE6koi
wMs4WiZUW2Jaaw6Oo4KxnGloS8YSFAuDHA8ln6Gj5H5IRrynoh6XcvGEAqWCEPlR0VOuMjjoUCNWBwQ
19w20tbQmwD9Ga9pF+Jek/+f+OgOleHwLHg8gVlixrYXRaibNYZPevDKNnxW5LGM4N+/Cew4+VWtPgv
HCV/p8EmmVaqKUrceFdma97VmVrGnUMW74sDrmhJd23tX7+ZQONHDXzIOiZlPNzZU/t6oeEu01FftzJ
Y/yjfts+719WmXXPwec7dIGZ5e3+/JZyu8ohY+Uz+eBslS+oa4zoeT9x9635wNjk9uznrfnF587H3jn
9+cnva+Ef9efzh0TADrDDfK9IL7HX8SUdXdMp7lClOe5qA840PMKJiDiEo2VhOkId4zuzk+EqZBF8C2
lW+q+KMPpem6wNxfBeHTv7HkGwiM6bbOS2HJ8YTtNu8XkeHtwZ6go3Jdhj/Nia52JlBmEvIx0Mq6J1f
WqK1i9XHW5mm8YuqsGG3iyHXkxqeeoRMOemWHPfgWpbr0eewSn3pWne59htqNXAmddiU0am1x6HUmXI
WE421tITpJwI6NRR9nSt0rulxbj95JQN1wt5QdCl3d3crJ9jFO83wLJOLuc+UeGgviVufWEe/x8NmYH
k0h38TbPWi+rchpFxiVkA74AwCBngGLY8cEBNdI6F4PTgdHw8O3p4Prtm2CC9F8dLtLrRnWHcwwjU6U
WltSGo2l3cerCbGlbKuS4cRDKA2HZ9JT3zzpMo8jFkAwYPgAayEvobV/rB9bcevLyohPqnGtP89BwGd
L/Qq9dUjSlmvmWIqG6rWImiXjiwBat1bNFzrahnz+fzyNxZI+KGeJ261lGlM8kuU6R+/wEiLf+emiph
9y7a/pzkY4Jvp4F8C689EMk+5w1QP8b2njct0=
"""))
m = sys.modules["pagekite.httpd"] = imp.new_module("pagekite.httpd")
m.__file__ = "pagekite/httpd.py"
m.open = __comb_open
sys.modules["pagekite"].__setattr__("httpd", m)
exec __FILES[".SELF/pagekite/httpd.py"] in m.__dict__
###############################################################################
__FILES[".SELF/pagekite/pk.py"] = zlib.decompress(__b64d("""\
eNrsvWt720aSMPpdvwKJjw5Am6IkO87McMNkFEmO9USWtKIUT1bR4YIkKGIEEgwAWlJm5/3tpy59R4O
knMzslze7YxFAd3V3dXV1dXVdvvzyy62raVoG8P8P07jCv1kyqYJ8ElTTJMiL9C6dx1kwy+d5llbTdB
Qs4rvkPq2SzuKpoyqXWf6QPQXDJJ3fBUUyiUdVXiTjIJ1XeVDO4ixLiqBcDndm+XiZJWVn60to+sUf+
t/W6cnh8Vn/OOgFAPwX7tskzRLs4CIuaFRW7w/zxROMcFoFr/f293bgn7+0adzfJ/G8rOLsvgwuivzv
yagKkumkE8TzcfD93+NingaXy3lcBMeAnaIs8/kWN7co8rsinmGLkyJJgjKfVA9xkXSDp3wZjOI5IGe
cllWRDpcVdKxCkLt5AQgep5MnfLGcj5NiC3tRJcWslFMR/HB2HQQHk0lS5MEPyTwpYFoulsMMpuQ0HS
XzMgli6AC+KaeA+uET1XsH3djqi24E73IAH1dpPm8HCcwnzMqnpCjhOXgjWxLQ2jD7QQQ0AT0vgnyBl
VrQ3aetLK50vU595HqASAAEc5ovYDxEYVXwkGYZkEqwLJPJMmsHARQNgo8nV+/Pr6+2Ds5+Dj4eXF4e
nF39/B9Qtprm8Dn5lDCkdLbIUgAMwyniefWEvf5wfHn4HsoffH9yenL1M3b83cnV2XG/v/Xu/DI4CC4
OLq9ODq9PDy6Di+vLi/P+cScI+klCEBGxq/E6oQkqkq1xUsVpBtS79TNMZwk9y8bBNP6UwLSOkvQT9C
sORkBVEpdrYW/FWQ5LBocJFTQeoX8nk2CeV+2gTIB8vplW1aK7u/vw8NC5my87eXG3mzGIcvfbf8VqA
kTnsGaGcZl8/ZV8Gt2lW5Min+GPQLxLylG8IOLjX4NpNctkhaQo5rl8uEsqoCP5hCPK0qF8zEv5C+Z1
nM/UUyJ/lUkGK1E95aP7RD9VxdL49qSAVclsgUxAPU+LJB4Dm1Iv0pn+WMSjZBiP7uWLZZEZXXycZcV
iZLz4DX/Lhz51qJ8UsDIYSYc/nLy/urrgVxJd4uVl8usyKav3MNZMlu8jcSd/+3B6eXFoV6p/aVvvHG
iyqTy/T5MtMWP5bIHrjz+9VC+BteuXcpqprPEEheRTlt/dIfq2XgS08IG35w8lLOYAWH2xBMYyToCCx
8kYOMg8uHiCBTwPvgled77ubFXFU3crgP/kRC2HQPCjpCzNt39Hhpo8jpJFFZzQq+OiyAuuqasAo8eS
8Ocsn8Mwt84vrgbvTg9+6MOrMO+ed/vd992L7t+6p93/OulODrqX3Wl30Y2Putfds+NuSBUOLqn8TQg
7XJ4vwnYQjjLg//hjDksZONe8LDN+VD9GRVwCJWHfwjb1S/4XzpdZtkyxWJHM8irh38sUy/bw5zTJqJ
kyqSrAZOkCgDWCFEtl4fc4LehnCXxGvLfLT4o0gXl/okIAPHMLlCmwDGoS9oYK/8bjMUGfcy3g2PEwS
2SfPyWyvRokoD3gOgNeCdStUT6vijxbxPMks57L2sBwxY+p0iKZqSHiWyxNDwlONKw6enhIhkCG09qA
gQRV7XEMHZ6nvyU8L9YjUGPMYBfp2Iu6tIRlMK8AfVzdfm6aoDEIOMusKqmPU5AmsniYiC6rR244y0c
xfwGWFqfzWg/iZTVlnsQV8FkV5ccJ7DmDUZaXyditDfTFCC2SO5jahCllmpdMafN8uaC1mM4nOVGhfq
z1BOlTYKvIq1z8hJdxlgo0FvGDLGXXrbJykCV38YjICZ8EjnryGVC6yEEcZFJOsgkSZY2Sk8EoKap5P
OPJhWdYavBmNE1G90RdMZWo9wCFOlUPH8pkVCTc3AQmMSm8pITMHrrGMwTLa54MzFdD6FA+n6R3dcqB
nXe0LJjOQCDK0llaDdJFvWdyzeRzMXbxOJlYz6NJvZFqOYdVNYhHTEKw9STzSj3GI+SQ+Dho4AtMyoI
UrEf5wPN6nyQLmOVPdRggxoNcyh2F/a2UD0Aij08CMP2uccHkgfqYCYYpfoyf5uN5KSr+Npou5/e0jI
Cx4mZam54lCk+lbmiYlDxVw+VdSiT9EAN11PoNPKzI8pgHKx8Go8XSfjFLZvYLHyJfBEfHF5fHhwdXx
0ddu5kiwVqKGcFqzZlt0pCNJ2BlRZ5XtX4+oLiBm5lkeCmI/49JKQgySyqDIG+3cNc9niOvRhkHZBuU
Fx/TpJS7McnWgOsAmUaQToKHJBjn87BiMfXiqU+zuHg6nAKLCeJPUAzBdQDAu5O/fTjuBh8AGSyLjvI
xHmFmyQMcFJIAeFry3RaRQQdkd+6A5IVRS3x5KOIFn/IiKNERB76bwQBX52Bw2wKBaRJw2fcHPx0P+v
1TxOoLEMhxQQU5HkseUpC7cR8uquQRRRBYCCM8gpCYoU5x86TCIwaACHitgGwegAAyGcCJA3Z1bgYOf
2VCVBpJ3h22oBzK9WMQmxBEFJpAmVd2PK+Gbxcw+LDFhIB7V9nU1pax7Y3KL7bLL7766k0YbAdhO+z8
HZhhdIOt377qH1/+BGfXweHx5VW/1WIxh6DBDsSwsGA7eClGZhaBrdwqorrU2sIJY9SKqe3ziaUEzgh
HNTzNlnS6iof4bwZ0hgcXYmxp9YSoxI0Zqe7FTXAByPiRj86CMiqYnTJA2vgiuH3W4YKlT9pnOvSvI5
eKL4jLovR+48MAkq7/O6zJqqkuUpP7ZZl2WHCT78/g6TqFsY8ywEFwABvxwWIR5UNUB9D0w2QEg0E6B
74/iHBLawfxYjHAfUaQB1SEzSoyRFZYVXCoI4FVTCLU68hqQEXyp/4IZ6p4mGZpBcscBVV47iwXi6SI
WkTB8AwELIhNN9WhPXMAE7tYVtGNhAtUvLNjggxvW50SDmIVgIOFCZ9uWRafBCES5vFliOuj1hXJCek
DiDn30Dd1uOqcwouoZRYp+UDTM7t4gcK10zcuF97ajLLxvxLk43nPhHlycbx5XUCPW5l7LddOvf902K
iPnc8ggip+lfRQ3JWCFpDpGXAMQpDNqMORBboTj35dpkWisGn1p0PjB6YLCzMKA8FXqNngVRD+Mg9XV
Ztky3JqAAaBaVnM3YKAow7OawbSUQTEUhXpQlWaoH4w83YcNsckLmXHTYTKdpqI1VoUtzAQGpBqWWAZ
ZWOBZ5aYBaYFdDwbdnB7LqlQByblBugLa4Wyxm1LQfvtfmAAhON08SThiYOmB9hv9xIeVbgVzFv0ICp
uSBbHnQ8IOig6d0kVhSRP43YSttQ7EBzhzU0YGj0qYZWjtD0wu2aPMQr/68edg+ur9/41WgfVCGclEI
MHXtESj/RK5xcE7ssvv2QNBE0NiKrpiHSNwUNe3CPsGKADUwdxWbCKDiquoIt0agM0XxVLvYhs1kpMW
/Tabb1jlTUY668jiysd5vNxij2KjDJ/z4fEV28NlksbRI/bNKChrghe73Vev93DbfUAOjqCcQbYehpn
AWzB6QyGJ8dAZC0GULCOpuShwL+wblC0E2MS/XWWu+ohLgcQAqOoEYw17A4wF5DVI/ulXpGif9BUZZL
Dik7gGWEAJ+o5qvh7wbsY1vNzWnQ4nBhYKqdCqHsul3NEsqHvkTIIdxg6UOuv0zOiIfwIZ3GUk90ize
wWSyjGJjp0TH9YYa6LCyUYbHN31FVYP2ptBOM0GXeD7RJFvUQzVxxXp8ygJ9FbfmtAOcIDjQmli2J7E
qqZGvhGXpupNUOe5w+AIDiFR9QZ/CdqyR6mpG/WFKdH20xzYt9rG//aKIUePsQoW0isGrvAGsCa9Bf5
ItrTiISOSswdHX9//cPg5LwLkh0MKwh7vV6ArCy4PP7P6+P+Vf+X+Xb5yxxe42zI5mp9tBYG//frMq9
igzHQu4HkDNbLcfzkvEsXA1IIOK+LpMSzkv0SxjJAhYz9Fs5XdC3TC8Ltx+522cX+RzCB7eAuy4dx1i
f9hp4+Ps6IESKzlYM1j6wWzdPaQoFY7obtoETdexuOWHDghKf0Dv5dFMkkfYSOCIBGfV4jNsT60jiZf
4Itbyzry6UhJ78dGGPA/1CDmM55I5D/0e0k4qLs0v8TAF/nTVASh696VN/4ImidxonXRUT4MNquc/Dv
A8vFK50p3mDO75JOcL4s9GMZ4KUaLqMdOAzNFqjzLnM8c4/iuQMKBBsQONNRFQzxEq5E5fgihw7iYb5
IFln8FMRVBcRfBtHrvWAGKKiwhWrW6liwBBWpHQGQstOHzqMCAPHCE7ZaBg41FhE1PNdXiI5oET+R5o
TebyZI1/9DnBBKekCyrZY1wzYPYOyc5VXSDa6mCRz799/iETRHHCF642AW36WjYL6cDUFwBhY3msq7t
2ECyM4yBxj/N0wyYHd0kQqdwQMuLArjANi5Io1BZ3DIyoXIQTPQSBQpjshVWBnYcbSyLQ+W8HANNBIp
LtYKvu0FEYxt1xAmWq2uU7e+fP4TGRG8z++Xi6C8TxdEZqixAkyVKFvBwRGO7STHwIpaJuPQ7VFE3Ay
WCnAqIUq1gUmN8J8SRZO4xNtd6GBtKDuv2zUeb/5rN1WfW5wQaSYQB8MU9QwzqIuXvrBQ8AqCxSSeKl
qRKd+eUqdrwJDNCfWUVAoFU+DU8wRRMkygPvxIJ7ALd5zK1R6Kg3rr++OwVKeRH5LqiBgTzV/kIZH1v
NdTiQ9KVKgXYYMd6jRil2aj5Q4qyeIF0Cj22hh5sAPIcItaQu4sfoxA0G0H8O9fgpcm0cKBDF7uw0sB
vNXaskCNl4sMZX9SWBio4RVn8+2Wu+hwydGYXDoS33gauuIvbgpUOnRK+7ik2IkMJkkbQw1nK+rufJw
+bcpkic3+h8VmBQ3VWpRCQCd5RLV8dBOFRYKaJrzzkZhay40jgYo2I3CTCtyhUPXs1l3PgHU9nfWlfa
S+dTodpEKyGwLWDMQIgms8/i4AiTy9u4O1GQcLZG0ODNJhAXkge25uicSCeUeAugA40Sazprq3ds7/q
BlQQ8AT/lNShnWU1lmkr+vnP67tM8uoqpZgX0KuqpVG7R4uw66UY2VFPlrXSyMf7Ar5VpbF3y3/wgRO
WZ+1msQpBWTmqjZ/MFgnq+lPLsqLpOiTNBD5+IVxUvspzpb2wdFitnFZ1rsN3aCdGnpSr6SEeIXgCQh
GVQSVWru0I8hR+FAdCT01KcnRvieii4AQbajGng560XCVlcfi4vSwepQYaNX76pUJ+6d+ItpaWYuF5p
OjTbgcn0300aScxvvT5DESkrcl+Pka+5CWI7ODbG/TgT/JHO8Yon+sWHB0+x12g6iOOvwyAAm0jO/Qi
pFUbY2Q/tlyDlHillxrw0zQ4iPxCnMefMO75rLmCMP/EDpaAadlzkc6EUvaBAwHgcGv8twJD5E8hUJP
b/Ys5oL1xUekal2zu/YA8Z8oBZvHB6O2vb3Te3Hk5e7QQ0Nv6JvqDHGU9X05gmK1rhDnqfXEPGljb/Q
zdijas0TV29bNfvd2y2EBsoLspXoD41nfWcWirFneLnd5XVgA7e7PfxtoJcOvCyK9X/EuR+oeEIEL6A
T1jH99G+w5/VdQ7K6yVMg4UUVaN1ZtsafKojdi/4C+3OzfGt1R9W/bpvR8u34iSRox8MJiiX0YhDH4V
BVqW9F9dNme3XueZ61RauypbwPWoG5e3zqHhOcqnvrXpzW9E+FGAZJqrkh8aCvpo1VTTWkFn9b7sVkE
qzv3mjS8dGnbN65Jb3+nRai4BTjUd/HmbeiXX355QKob2KFA1pNSnby1j4yetOhwBcyUCJsv7gOSvfA
6oFH9DxVM5acA0ROf9AdYbmjIeU+3df/4p/EBryb8mv7au8HwaZCOHQDCxsB5i9qAwSLPM4Yjr1xw45
fXgFhCWnkxnRqvgGMv51Vv3xycCdOsTVzt1tD1Kh2DqtEKvqlDt9TuqqhcrMbFDqmYmQr5oK12QVVLK
dCnLN3o64SD8di4rXEmy5Y367d4+p6UDU47dz/H8Ee2Zr3sfCrpJs3ADIjbHly0Nqs9oINtuEK8L5ez
6CauxPEYURNXddTcrj4ftILd39NJ1PCs7SPCh36yyqmxn/ZFpf3xhg2wO/gH7wr2vJjd2W8pWu8n1QE
I6+bkt4N58gAryJxVYLFxVuGywnVvPluSFi89Oe9j4A3utxujrrJW4PYsQjer8Odbcau3pZi+6EFP1D
eGdDJGGyZjREIradI1shS15Zn6lVeyNFfuAOtEU70q/ZRWT2J9qDVwhezq5EI0li6cC+0qJQuDcJs0F
2Yzu/uvW3L8VIrOYXOXD2pc8i2+ugQa3cM87m1p0ddbvXOfPJWRcepAsQnq5xXyGgnU3FLVpGkgN3l1
a86N8QX7cctMdUtJZQ1D4cLdVZBu0gVCu9lXt/x+iw5fPZSxXvWC/bXl9rEJBi9n8RSm+GTBSj81lQJ
rXNK0HiHuilOGY8yLKuHVU0e7wjujZR1KjLZW9d5c/vYwLskC3CJ8KFc89fBiVVKkPtV//sredG2rNm
xgzuUt7zBsvi52GCGYzhbm1RriPclGGo+wgi3Kho83Ozi9zCmsM95sIRc7lGrVIUIBp1vEIESvnDpVi
upeIVLI7kgzxrRKZu6akzgQZayLPVHNM37zvqte0ZgE8RXIRCBeKFYirVlpBz8mT/RL9exFcJpUIVsz
xeUiQ8tAaC6ekx2nML4I0LGGnESk9l5qAev3He9ikGvG5E1Cgwm2S3VlyOQIMGZxNYDuRS3z+prItOu
1ZrrUeJHkTBYMigUjs6cjsMc65mZBBIFdX1h0ozdA8v3x1i07kzFVLW3yvdXrLR6jWGxWVhab8ubkPB
LzyVf47h3GusbI+qxzUqq28FZO9eB7NNcS/GdtB14EH+g6rkzHyU4C55BR1Q2WizEa9fC5hJwP4YkEz
6SgWkNuAhdiuaqDsiviyCYkIgl3gHDxWE5mhELYKdn6bSCaaGnw4s3tKhzJMhIXR4ChRjpY2XWsGWmk
HqIT0buxBSf5lGaaF3lgeW1T0naQt4OEGTqgW9i+RjQSOJK7f/dsExYNCJuX/Kts2X3Ab936mhR2KbR
88Lw5LOiCTh/m5NJUSuGyQyNfLmzzT7mrqAWnj5Fiq5lIWdG8EKijRu43MInAoSfj2npX4p14Ng0z+Q
KKPehK25yGXumTnWDQLl/umvxbHlzr7NPcBITZKH8WZpV01r8Rr/qDs4MPx7cmp282EjU6e8N/cTHs2
9I8fRbig6bHvEzEBRwj3Ll/NI5sFQnEYYOlhSFxNuLH3bGbkON88u1fpl2SH4x/B5PjxgtTm7u3kYtK
E20UyRN7UTaJB8njIi3g7O6R5QEA1HJI1CoXfGvX093nLngEC9KNcaMgZ0OfvQZoYon+mGYZrlBScmj
Ni1yftkRA3TtKk2iclqO4AMZKHJZFPLN1KojuAujMTX0IdoL9rg2oHz+9T7IsjzRPWcRpQRafNDZb7D
YkIizWshdnM3GS5uR5FMo0WF9FgnjNI0ZNNqpRlClF1inX1W2sWyGmdFKXvIyzirUXjBfkcyGPHsJyP
+yEtmZb64a4Qguob99kIQ9pNh5oJL7s2GgEgHxLIao7sqSq3Yi8phHKmqaiRI+JfhgDcTcwaQlq7sm3
yjz5fVUtrtPNDJTRBTu4Pvm9RskL9A6SpiJbtRs95MNC3zdl12zxVJbZYJHMyN2MvBZN0t7AuFnwxEj
sE3joEg206k4LlrWu+ECuuLYzAyPU0DIv00FZLhI0oaZxqhdbNTDcj8iqtgY76j+JGfG3uWANae6Llt
OxDscIQC8q/JUvqki86Z+fDvrnhz8eX7UD9WpweXzdPz44OrpsB/utDfCANjVWCZBMN7WYq/fyjnuJA
4lgNd8aPZDTaFKi13S7Pt8G97ifs6dKET9wkxIbB+8GJ2cWKg5/HPSvLo8PPrTMuh2xrdiDdoqgmGHb
dJ+c1825P98a3BaNJyYdkkObi1dbcHKRbna3qcMrLdANi2tCfrN1ObfLVD4Q11Ruy3C6HuawH5/gwal
YmryvcT1vaqh+AiJnFErGN4qXGPgmkbUcg3ULsd01iKsLIyYr1pbsgk9fp4dwrFvO0UoGDvxNnPoUHd
rnJE2kiA4hqeGREHBYPs91ZJLefaYLCQaF8Lo8NN4/1b1H6ghiHHSDQxattJ2/z8xfd8Hn2yC+dj3is
uiiNHDWr2Dxdg5OT88/9mHlX1xfdX1eCvuWvGiZZAslchg+77xqd6BAvo3nVvG/fcvEn2Szrm55vUQg
aZZbMNYAd9bXerNfG9/2pu7BC0BcoFdqhJ+EnNc0u5LCXVeOy8Tko457oOig8PwHSo/vtP7eGUK/iqt
liXZq/C5secrZkDrGMbCMNij/flkUT9eG1x0PnxcWIaGmERYrlL0fAfFYSgqq3SA0Jrp5XWyX0XbZEj
o/A5y2oEAdI7wA8n8gV9heD33uAc9d2a4h29BZpla8gtWki6u11VR8gutfl2d2YB75qJ9UNHlMq7Cuo
Eb8kl+Oj6m4BVG+p4Iuv8+cxoqErmH/yPZcXJjNCVozz4DiI3yD7e0O+ZIInOJt6JD+LIuEXCh520Gc
3raamkwo5AHKXv5m+XtABcz1SzOFZeiHoU7CboiwCmVtgTvfb6hvN98fg0h0cHXdx3Ogehhcn/14dv7
xzIWh17hmKK7dSRFjkAO1b0fhWR6Uy9GUxiH3YyL6JryIuD3NiBEF/lcwc3TSP/j+9Pjofwk1SdaMFn
Gx8PuxYl5g1THzvzPyeDxuHjmrcvCu2xm9YGrkOi4sJuWOqMIDoO1JGN7WpG8x+EsRg+gsecA4EZEKy
YMwn3E0QpOQfCSZBOmkgPmX94NhYt5BrkRsDSsUiMWLEvwSyObIX9nPtvpQ7hoEcGZfEZy/kqrH+OqR
EwI8Z0+h3KEarZKbN71hfrdUd10sYBiQ+hRv5Rh2Fp84sILNr99UbKmquYMTvpoTuiIM7wI1SZcdtQw
3PkdMuUqyDFj9eb4ovyC3d/ifvuTbLjFiHMVV7LKikrf7VcRCIJp6AZIkRRETysxVx+VVsv3cEiF+j+
eyOPaw0PWB5arGU8+hXqDyaph8mzBKQlw84Rq8xxg/pOaF3pWfqa167jGI6koNSNNZx1S583DJArSud
XdvV/jyfv0di1XOuQUQtynAC7B59rrSldD4PZmTN6KSZGHYUhJ2O4hGLYZFyguMxvkAOwasMgxjidIN
xjkVbAcd8mbxE3kjcqClOJjHZfUUTNIieYiFh+ILFXInG5MrDEUVxUixvy6TOTCPTnDEG/YYrbbQk0b
G6frCOPVF4lYUNtjD87Oz48OrweH59dkVOhi+dr0L1MGPVVc6wN2agiokWMsxwKu1ugOt2kUuTs5+gH
Pl1fHlTwenwpXM92nw4eRsg01hr/M2eOmF3XyOsBYbiOzjvy9LvMIgrJM64VOctYOLk952GTZ1Ybuh0
X8ZCWPvSmGc5ZuLgG5Gm/HAdw4rLhpP+oMP59+fnB5bhu2yWf8cUXlV+g4tOcScUsEfLg8OjwdHx+8O
rk+v/LOJ9xCiC/ZV/a79ulwkMEUwxr3O3t5+yzcq+0oN9t09ayCmkw+JAGY1mnt5h2X0Haiwa99veBv
7pgZsJ7KhvCLktFzzmnh8IzYrBnCrboNdO/iGdqHHOzRHNmQ5q7CYa/5wbFZfs+Pc33tJgFo11PnAbd
VJGEfT+YQyjWGcZCw/dJvDMmF7/YW3dowT7xsvJOtX2NblPeki7SvcP3plUhPyjo+LtDzooWINaMFv8
PgvwYxXummM2PLvDcNCH5PHRYaOAWOrI//WCC3WltAUpMXn4mHFzxABojvk9kEmaBT9EaXQshqD4Pm8
gC/OPmUrCo/yd2Kz/pgXMowQyqxs028ivy5y1SK8GBvKaR6PP5xfHck1/iK4ZgMuDPWewvrFeAIPIlz
7DIPho6QO4o2Mkyld6+UJkMHKryTmRPvIY3RvAc+v9+zbSa51GGejJcaUPxfVda+EDRphYQfP1VJ44h
VPQhrOBn4zA0BuyAMsmwGyqhsrPWVomJ+EO6GKHWFs1lybggX2ZFRCrr0T+uPdiLJKbW5gAc5JZxRA6
V32BCTy7jgy4Gu7BmlqDAft72Hgx/NxWVuICmAf1YJYFACq0gZbHxoI4kqujmOoFOf295uhvsJ/AXSq
5V44uqPjqSW/4vR8Z+LcHBM0MDTxbqiHtbtNQwwBGzdqvoYJ6qQuLs+vzm85tid53opY06/ljzfsi1u
3ip3G5aAsM1sPKmiqwf5WOfxaXZIGJlWHQ4EjVHvT1U3ZKl6TatwyCu8/JFWAEb1ptXKsbPTC3zLNwB
ds4SG8ESNpTyNQdH55dUvanj/vmQQfWXQkLrvt8wID+P79ef+KTKU9NYTnYr0SN9tQaf/WEKCGyzSr0
rk7E2MaauACYARgPD0x9jYc4PwrUQO2FeIKsjz5+Rfp98fREK23h2TZQdPTFnXXHGjSciDa7om/KyqI
wNW41fQi2WV1y63HjdHUVcmW6Smo+g1r38sJkJsw879OxX2SMsCCg+isrWzJ5tL7TtwQMVfvad8gbku
5H2+tsnwwynZso0xWMwoBSDRVwY6W1ZsSho7aHtHqmCHg2tuUPgM70oXJOOliDZUswC2EI3kv/BindP
In5in2nbITqjspQ4iXfbbEbH8r4/wBA3CM8iwvenaRHy6Pf15DUKpzZzmpdEuM5DF+wg17ghqFQHQaG
IMbC9Qh6ig8qSjOUAlc5T7hxC9kiYBhlo1oOzPKmROu7lc4xMjTD/Mvgo+oryKb+6DM4XwZrhmRDxE/
H+Nt9Zr+G2BDOOKRTIRqH3JEkAl46BRoBZCGybzL87sM6XEWtmrqbYvYMIKm5fcvA3za3MgsLb1tNuu
5r+//vV3+N3UecIoTBGL0kjwRjs76yNZlH+wwBviWJA57j5ddm8XzZZw1DEXWNeQh23f8XzsM1wSV+c
/vXU2Xx0eNpGcsI0XrrKCO509ajAE6zig61IMiar2wzOXPTOgbixt0t1Z1fEKCX0PXmf79vZddj8JzC
qZldn57vLs9Xtv9dV6r6HRoDKttjaplDF5sGv+igepJOnqaA80It5MSda9IU+kcE9dgzPym+XE8AJ/X
NWDGx2cbXWKpfv5IDBmj2DFkvlxE9X1Jges6awJ8crQvqa+EdflWnCPVqUoGACCdEZwv1Ys1Z2sDhOH
v6PcuYpmQ9WayHQ5n9/Ve8DLYf2tIbC+Cy4TzBKWfkjngYbes8GRZ5Mu7KVBnPh8lmM0LNoP9tzLI4Q
qzdueATFdXL7ZB9JJIWaXARRVupEfa9iHVUDMaOITBajlbXS+ym7G4imkL/Vr6Gyy15HEBR/c5BQGei
OgOHX3kcSUpe7PgOx9TsdWxQjLphRUYURXmdyvcAcyt0EGhANXbLs0e0ePRIf1BrfjYRCobhruDcJZC
w/2AU+p5em1TBzwfFUI1vv/K0Gzms6j10jevziWuu5IwMMrXe16SCF5Ra62VRnH2eQIjWConIsRVPAR
iZ9WJnYIjpmjYSANStDKAaCGLAomiyMRxSpG9VTmIdJj0Lh111gyuvt0T53mLiH6zpyn7QwxyXolZN9
RlY4HRSDGke0BT03meCO2orPTa6xl6K5MFm5dwlspK9dFxRAQUAUcBtoXZmhLkA2WFeqCKcpTouKDxl
h0OVF35cwBRGSeGQ0mW1XIy6Zj9sjQsVo+d05LvnLRlKJlTFHAeC7SLQg185Juw3eBtq1W3avbxbYcc
m6A5MY6Cb5sbthUSQ5j8e7v2mnl3PLAdfyt3TnGrkzaFa3c7oNQtDsaAmWGYTUYqvwZ6AAaUQUIkj3i
gfV5pjXNMKzDLx+Lz3td75Bkp1MbnfUO7LS6OhE/JZMzNcoN96BqG103Gh5jMAx0OGOAypW4Y5yeqQN
t88Hrvqz/vYLRTHNlOSfWDq9N+gOmr0glFCAxQNGk78ZgxUFIv3FEyiHH4gZLIO8Yp+ROKxIad2f0Yf
xORYq8foomTCSHHtDTVlPX8AkI7mLA6ET5yJp8oCkWuu+AumRdlHOxg0NztksYSohT4EIX3CZm4+OvB
ogp2hpiQKdhBC4YdKI0ABKDmfRrOCuVy+Pfgy93Ds55MNLN73kPc77zP8ep29/y69zEZlvDhSwcQCai
yb23s5agswlZjNx/f7v0l2KHOUniyN1+/3Qt2YJliV3GqVnZbtkZttAO73aIKRUQ3oBOYJZtyBem0+L
PI2kEUrDBLFsmsstdFZB6PeiVu0KkkbfNFiqMJuWHeUAOYRQz6jX+g5q1aKMIfj2hHoK2YAZlIciFgB
qWjMdTYomU4FYvrFLVCnkHZwkZGTr0TWOrQtM7iOG0xWpoJA3OSClfEjlqm0gmrqhYD2xOLXhmeWpYi
vcjvxHk4IjujuLj7hFpN1JgamYRDaSIX7sIxeWf/9nOiZksQv/zCMMxLmydKY9xTCzkelvjX7JPlrwR
F4R/oJScximxnJrH1SUTgad/Ai1XUwI4sxk9bhu1dmVTWBEWGpXvtm8vzDYOUmhWWGWrRidFlxcSS5x
f9pR5uxf3mDeIVLxa+90ao73onMdRkrSEr/qT7Udz7orZDXwaZXyhVCw74z3u3tY9F/KAL3HrrUoIZZ
xziM30S11Cez5z5kdKhNlyZiB+lSFfH3kArNXphWox0FkYJQD/BgPAPyOPJqIgnVXhr6K+dHIc1XOoM
ibUobipZYqnisslKKltlfTqN3JX1xow8li5+jdSVTkfsJJb2LY7CPWaABOR/Sse00mRGuIvL859Ojo4
v64U5A6tRlBMBG2BVKtT6IEU61NoARWJVD8VWy3Tse33neS34hvcD3fFgrsvGj94PRGW+Lyi4wRblbU
skmW38pG5MfCUo54CkuVBnAqT3odMHdWWk2ZpID1rHvZUs1Kml0o0674UZ/0AkzKwDZQeIgciiWf/ON
iMwKMzjIWy1Bt9fv3t3fDn4cPA3AxDKxINlkdVwor7UKJ8QKfPXhbv/Z7vcFS/DrdpKFX5FNfBiuc4w
fBAJ/uYu/Pg00AE6zLU1zwf02YPmhMJmDlDZVvvI1YaJB5P+dmydecNHTkDg/4b3AA0bAVZ8GFAehKb
eDLDDXkNlWUArfX18HdgWzl7jV5TNoATH5/H0XoRzTsfu3GsNjju28Rw6FQPLc2rgMLwfSPkmZYHBaJ
qnI5cSpEOBs2vqbL/OB042W+dy2JJUHdsDXtC1xzwZjLH/Rhk4uZt7sbSDoDFwhgvMXELZYGBk6vNDE
jygrkJqV0Ac76ywMtfdEyb6e455lccTlOUNn+8WfaH0uLDbfUoyGSTX3AqVyY7bCzNnLqU8+9Nbz8cZ
HXL2On/2ffQyXw13CQTn4b0m7GFcJkZqRYk2zL0+4OTrglWF2+XoLoXz9nyXviYgKGd4Fvn48eP78w/
HBl8YYbegNrQvEiztuV9BOiAbJ3c1iATsdbFyDIUHfPlaF2LTwYOopY3EbHnc/ixyeardhYW12gYlos
543s9mdZyRk4s1VMoUX+8ujmIAA2r44mdT9En6mvm/CpcrS/rB/EpxMZrKK3W8b7YccQLEzBdB8DEJm
EXR6hrno+UMSCcZCyghKgTHcTEOA8y3TgGHOcEM+xFTAymuvuVcKgrJiiKfJfyR0rQLaMljSvGjlyUu
ZoqeShrGjifyIU7ZIosrjEh3030jrI0e0jkllS5fhy1HP8oEZhzlSCcjH5LHBfQLGi6i8P+gSkGfMkF
kcq/vx8knTFmL5A9/wwa99DHetfAok5rr53O7o+UgkOmbu7MLv3fxIbR8oXyWmsQ6MQHxp4S1sHSZx9
mr5zRDwQi4AMxH0rnrYNKsg/m4yNlyrX/61YGltVXjsRG3tVk3RepLzjBvnAKs97U111fZKg4PUENoG
NbUP7FC4uXL+wcjNeyL4DTP72kJHB4Eh1qpUnaE3wnfH4BQReQ7I5syQBsdIc/7bQEFCoI4DGtD0Djb
aQwTg9Dv8nwsa6N6o4gBWEXjsN3QXSx80TN1EbYHWgPG3kF35bjViOuIdhEswUgkmmCEPqdMcPvIBsM
lqixEJMeuxVMw19RyPqLMWGyXJVgIhU2nTRozyZTVLkhfmDGPYTGP4JCF/J0CGdNfZh/ARNvBnpHrMH
+YG0eNL7dh8SSzLzHNtwyiZJCmGbCpS1oeI2QWB9tGi77ovD84PBAJwYNXwY3RyK3Bf/RKRZ4VGamnG
RcfybOxpFMlSsI8yJKzh73e27uXV0uAjxIlqxLOi9qEMKBncVkGxeG/NmlUq7jixuDnAMtoXjAT+aNq
xeiDdceBsL+VeDYvFF4Eh9M8LxNznkTfv9gyMwctMS6AM1FojEv6eYTfDuxmyUqBB9VTkEmhSN3+VsB
o7MykSFC6WNEbpxPcvFxbDuWyoTQlmaPaaPumk2NGguB6JomxyWokWvkmsHN6vfn67cvXX718g1cdLS
NE61lu0TeqBsVzno3bZKfFhtvkeIipmygpOo54dH15GqDWveOzyhcJW6AMaqQxVEIHjS5SkDejQ3irq
LgdqLBN5mi8wVrNFe9f62ujgQCuaaROtDVe3VawREOti5eNtEriES0MkGhgKCBHgCgIjJm4E1Y+ODwd
9N+fX169Pzg7wiMAAQxJiECWjFEuoqjbncB/3dZ3+6//9Eun8/J/ut39ltCUhfH8CUt1XuLe9E/Tb/J
gpNwRUXcF/47HQHTkwJiOpvVQeCJWChZ2RqtOAsRe8iwdPbWRLPHamYPzWQEbC9RuwGmB+ZU1SDKqFT
UViNar8P8JVf9QB21dYUbcohVCA7CbP4QtO2+O3VefU7ywAuvWc5co9w7MNxLIhF3BkO5vYAh4J9Fda
SEiLnT0KBSiHYxZQfBEr7Wk63TR7pzbN7lRch9Db/t2hH4lNSs6OSSFiUktkk5cAjGXlk1ippLUABDy
61DEBPW49f7OZg2trdksv3abBSHqFFdWXwQVkfbJqANvvEmwD8EbaWE+U7ejlPH016si4PVU3F3l3/P
L/iIZleyV0FVcw/glTL27O9o87ODi4qfjy8HRWV+Mv8pkvNx4scB+YI6xfFmhIm40lQd+JYNwfUv8eG
MHRo7CSfLVAMSXEAQOhE6JazrlchgV4c3/98v4VjjvN7ZnTlmf9dRC/JWTNsry4VA4r7U5l6UlvUHlg
dDawH+9IDr6+QyGfBOaBrshLJF/hHgsQRYa0impLOm3sPZHMJIYKKrFvrDzMbAYDt8uOssSjzVfffXG
qJcIsZRuQUShW5TBRhyZmA4eQulOWxutfRSQVWkFTMm4gSU+q++mupXvVbq7u+ZYd/PJBCNB7H4XKja
DWHM4fWTpu3omHuuW+J4l0XNQ1lDJ6G7P6X9DDS3k92yE1MtHZhYE4zqFdg7xzZwgS1gyndjz0X3ZeX
/w0/Gg3z9tNZh+Kt0gSV+CLrVvBX8mXwSNy61G/DVAMQspWArLW37MNsBSJRQg9cbQR1hjdwNC1c9p/
qbcgqpF+WGrYY7XwGuGQwsrYVN1c45dIQCLmEF7DTLxGCQZX1V4XnhueaQkzbg+TmHpZfEwyRze9YCS
Mt/qMM96FjvTvExcDCF2wgfVWBmSVYF+ATxnm9r0iC6/n/sB4EbGh3xvkoiIwDRq+GczDogFP5/5bSP
3e3h4gKYNvkdBXgycCUyF1K3W/+WK/5cr/l+u+K/lij/gyT6uEhH5itlhGU9szZu6ub4RkMIXmIHwUN
zzyJiAQteljKeCTyByGrkJcb0zo2orOKH++SI4O7+S5sCkcxPOH0WClnFAQrtFkhdjkYbEbKkT+iCKX
7dbW270VHndaIaMGOqssFLAr4XD8EPBWVb+i/Il5s/Cl+wYe3T+4eDk7LYe38y4+LRK+sqpm1Au2T8+
vDy+EqND5U5PRg53+uYCkK/kMNVGESyiT5NZ1Q5o3O1gjMb2DueFA69wOKZCRPT8CzYJrLDaQo5UXMj
hsSGAQlVpnUThi0C/H7P/hqW5XjMmQIFxRscIZTLft+pSiGQrNn9yqWSvnRF7y4hYZUixhtnTIgpVw7
jfbaOBlNUf2KgxtoeZiFhUUjNmV+LXUI2n0KyoAghI/TFdscGZzTzcughRYcB1WVtDLQuah8Sd113ZB
iVrHI8/0DFZWvkbZC/bc87Tchqsk7SVQAInQTCiMGw1fcFJ4ba1OxvPgu31KFOn2FnV7E5ZK8xpR25E
PZHXhio+pwka4KoW5nlDG9a0ec7QLGBaIRBX0rCKm6GYb5duNS3vV7GbuQQdyvfqnYpJ4yMC7QIYKfq
yhRk5KI98LWvUxGs93t834O3SHibgXLWpIWjZm9eiv1T470eHebz4X8BG+Ueho0x8QcotmRE5be2L66
nM25ilMW5ChEDFNV3fpBTGBiPBbbwMsH5QWwrWyI2xe1jWIbSWzwwPXBwhCM7xLB2h37OWi0xW5vJS2
+m8gWPRPI27qPAeM1txhe2VnLr7L2GjinZsRup2wdkV/lAu29yFfwkNqtkPzIk560rv9i4qilfsc4HR
743rWKO1auGtFmuvhY1gaLmnGVhuPDq4U2uZOq+aXdv0eRVAo1jYcgP68znTirxEhtIqwrxRyiIhLGg
QECtg3LSqoiWhncEqFJtGWWMjORAg0vCiR2cVZ3CeRE20fbyiOMchlg1vOSTUJ/NIwF/kSQ0Lm9U9lb
F5Nzz1Dat7bldQvjrEb+PtadECfhBhpVb51210V/zUqgWRNkLe37Bu6VkNrIRrX+U1g/JDsOs/k/MHC
rzF688vaxxelsPxdBFZf+VXnby426z8PN9JFxRBJLALW3VB5CcFBes0tMCvtBbCPaK7u4urmO4Cdk3R
n0AI23W2uNZADEvstmOI3bK3rra7d7l2P8rex9V6dP1bnaHtkAzBVHFsuW6tbDT8Rc/KyubANI2LjR1
NR6ZVd9vjfObuE9pc3V3vTivWdHR1mCx3YsobeCnzptdPLdYIlS+DPPyYngrmO7aC2Eia+x7vBNFJET
P4HNlig3WklL4XPJp23fWijQHR0EwBdce0r7RcIc4YiOx31x00toMfe8aEG+V9oMRwXUjivQvINhGhi
Dbkp4ZGb85sq+BfNd5uWlb5atwomLe+jWG5kNuLp8INvrhtZm4iJpuci66mLwWjLcyElgu6+Yc/+7et
BnFSUplHyvxeBqOi3YoukgPhKWQKlkNydyHD5r1aFEADOUq15WBEhwP0BQJ0wykOG8IpmqHjjIhsFP+
XcqqZBdpW0LiWr3ikfvdsYmdbqbB2rx4+1z+TFE9q9kRzhj3IRHemnpIykgjpBY7uj3r3V/kcfo7XqN
NLEXfQtMwVuqUosvSBVm+4kNkffvO5PSI9qdFYk9xKdjGwOHbevMG0Bzv7f+bsB1urDHXkOGTGkTUpR
7xg+B5JeNLlkwnfKKkX82BNiDIx321JCm2BZwPxaqmp6DpI+Wr9GYGsarI8GuvJ9fxFELzPH4Jhjmar
X4RNu89aBqk8y9wljbXQ3b2p/Er+6E6nxCD798G87vG8vt1gXg2WCO20g8Zu3MDn9fuwF9U18XH1jis
jy4phBcljjOGlSozb4KrL7IfAoCX2m+7+fH5teBEmhrXPn/e6QsXbDKIspysgvH69HgJ2YvfPe9DYqp
5s0he2U2mG8tVXb9YDUb7Dv7s7ynH4MyA1gJ1M1s/aV2+/eusB6Wrm/RRG9HWAxpBBkZb3T5g882G+U
+U7w2SH31AwM7RVp4yNMlzNdxbdRZavqeBr8pGZ2otAPesrry2zh1JAM+znnnFPopWM5+Ta4QqkkQub
+6ieVS/1m5o0ii5N7CrGttIOSDHuF4EwDGit6feCxV/r6OR00PXTR//0GB2Vko5IvEyhIo153y6lHaD
Y/UWnoWZbXLLILACPxHQf/ZotNids3YooqE4T0j3/97ZBcHQjLsJZaFZKITe0QKMixww+oOUgDNm1iF
ttndbCBQiC9G2rtW7eYGhF/OBHM4lojtJOh0pwKWR1cqHn4VI3wuj86eTy6vrgdHBxZs0eEB2GktAhK
1bTnhnfAiNi1wApKXsDODLoczjJc5dwI2+UC0KX8zK0LEsAmW4l9OXiTAj4hXy4yuD84vgsEKaipIJ3
LkBF+IzVo8BCqNHAs9Jule/ic6d6rEIv5daOM2bYj3VCjIHcnqEPaNcDiNyM9coZuwerZx+t1h2ulL7
af3qqK9Y0fchBiIjVpmDestKwuxKralN++h2KONkd2lVfWnsqd2a/pmMzq7RJ6GhrqeHq/fEHD5TXtm
pLKhHr09PIZCyRAA0BRLiYhySokgJ2ZAx21O+f7mIwL5xkeJF+SrKnNpE5Cq+7qPTaIU9i2g19RJosX
MqwoousJVOztDXLyaLtiVZykyxu0UPDUMz6pzvxyc2bXXc4XWIble7F8YfBu5PT4022ZTv4iuYJxntg
AwzY4SNWTBe7Jr9usw+FZUXR3lxYu8AwEzujaUybokf3FtkBKYiDznN6kDKOfBR9uNXnNq6j4jSbES8
ajoky7IUIuYVPrZoF0ypAHnGODeXSyZO4Q+JbJ0tEruAgCt+D5hLcMSqB2Q4Uz2afkh1cGugg+VcSqw
4p6OeZuuFqgiRU4krbjgrGv6oO7Db3AAe0qqJDAH5Z2I6U4L4Y2CrcmTT4swq5EshzuZDMjbJC72uEc
tD0L1+izncWP+4orxSUylph2xFR3NgNdUD0BaHpzTh+3JVgd/GrDRUx8iowQHPMiO2dtyUIDHu9SfqY
aOW+GXZiFRCOSrEOCDTV2myJmxaG5qEG40+VFHS0KnIQZyLBhnrjZA4shb2+OFEpzLE5Jyin1YJXaXw
630zphnBY5xE1UcKKJORuGNAzTnz6MmzcQ9xQRIb+3fqEko73Om4tPFd+qoFtrfJPdF3Umu6eVAmrTb
/7nske14N+EVjAb8h/8X9w7m+7Jxc7RXKXPC7C9YMwHN4aWtIlnjmI9aBfBBbwlYNYuzzMhYI6jLmIL
TFMUJlBNjZot09h/pflkgIJo9Hs3RzjD1mGvm3/4vuQlqMky+J5ki9LP7+DtaVDlek1Jd41rSWqx5Gw
7AOYjo7V9gTHatk7fC1oE4yYjLLElp88qO0eftp1zaBUfMTKMlkaf7Z8wgSGqdLSBDxZ4gQ+O9Vq8XH
E1jPP6Qt/YCD2KxNPRrAbRlQ8SQzViPhqolq+02CUbbWzu+rIdNo4lALMGY93xqMMV/cMtRQnSwbEjU
FiRzdujifTsHtGTrcIYepR4lu/aLwvFeMwVEg4kGaGuZw7uhIDStsE0bISWxulNoBt2IJhjedaVmg2I
kFis9Cn0H9PCcSj4wvqRSbe1Rfn5hszzOsxSmQTy3/Ajhjk4y/HZ0ce5afBSGtUhWwyI47OaR35pSid
YWCLoirxuEf26C15SB9lSTzXIfxubt044CoMOBr9c7nWzr7tOYDBuvfYBF7cfaS3dothS+QB4I+0zYe
tusM8fX61f0uWS0TFZgcxyKwL1/GwN0orVxHZ6goTn02qrSikgt8qdwKzcM2WVJbhr9JXnZ76dCsnkz
snD06kGPIhwcg4+VhAAYYRAEqGlDmDbk4p6ds0gU1tklCIEKA+2uWA96JoyFExXmzpWEai4jhZkKCdc
7AdSufq5JkP4rIdMO8lZ5UtmdbNcrdpdQLuaZZUZYDro5jHmWwfNoc7UV5FcRFwREeQkpYifAmnodsR
4mxwcHFC6cWzHGOWYyz85Il27kJE1BeQXmJmiyJ5KRdCxDH0EQzpRnA/o8aTeZnSOIcpebM9PcRPLRN
FhjUI26koVinfdPR7Z2maAQXs0h0eahNplNN4f5o8Uhhtw9/BxbMOUH+a36XzC4qwTKRzl1e5HdUg3B
1IHrSbYeldnWOPIx6YBNgSICz410VmgO+pFSxbUB6RypfGDWxqu0OuuazXhgmWjcS6apwMQeGDhmGlo
aQUN7Wwzsu085Bko5yDNX777bcBRhWQnz6+P7k6hufwZwz5RgYHXfP72fnlhy0jkY6d2/cPM1gZJgMq
sIHBiajOhamW39ZEWpjQnJgWI0O5r04SGdLPzcEolQKGJW+oCEDqcI3Ulm3bGWyTzESyceprVznSite
m4e0GVham6JHlhTaUorR12gSF8mTgYCIRInDcChuOkzYYRQYWGAsHtPdhBGmB/4huS1EDlGIzFl4FMW
lrAXHNQ8225RSDgAL/9zKI9v+yQ655/LrVWodfOW0KwFevCYC6pgQuwIOQx16nQ+awrYjtnSs4D0Wit
Fp8F6iodYKi1JwyOb7xasZHlfAfvbAxvP81nHQsj084uySVBd0Ni2k/S/GdI5+50RMpe4eVHsGqrXTl
YyMHwpoxsG+MUVMmQrAuM2gYjhOwxPFNKBEalJThQGc1sHp326rV7y/iEcY58if/JmhocLkZfJkAfEX
gRF+m6ufkp3bGfUh5c0irgKFCMXVcKbsWOWc+6J53MZCtrEhM3oAcGdMPJIaj/GEuKEuQdjuYJtlCuD
uhTEKPwhlsniePqU1+ymhZphw189DQVd0izzMr4/vUyQhdKwU0Ou1QOvWWV2Dp2iMTUoi/At5Nu+Xxn
a+4HR7bqmV/Miv7AgMb8VUp+QftlVEznvp0n6bzrnqTr9fWkiDM6OScIly1ZTqddnD1tEjEz4NKhE+j
55YTp60WBtkNHu9EtF0RRdzlLXnZGS8XryNN9R2KPpejJCZe5stKvTQXm5XuXrFQOVdIkeTJLahTrcY
Z7avsJaTsYZH3ypIibQl+7xydHzK+xfOHk7MTemfVDF++fBlqT0KShmkRdN3VJbIX4jdOX6hSQkoBCv
fBH/J8vDN8Sr4ItRpRfO/aDXNmJLH6RRGlwqlxHUUwG/Ke5rGYYazNvMwIAQtj9jUVk6C6yspjcd14W
D0KViIsYBWDELfIShFrXor6Dhb2rSnXvpUZXBcx254IGyDtJ70lA0Vihgdcdg9pNh7FxZhsBRXmKFUV
2aN8G7zWhAZvMPwgKeut5N2mizZXNLT7GwzsGUMTBeVyEsFwZLwyMzG0tCYhI6JeyBEARTadcjk0Q8B
ROEEhxtpG0WbOdjcVvZuEHqXRlC4zGB6a+hAYVnzQwkJbc6xDmgwqZt6dK9mxfhQwpFzL1Wo87q4uHf
xPD0tZAU2XQ9bbiPb+X3zTWgdnp4fFfKkcUXCA0iGGOB278mcUcisoVOw9bj8qGaKpodatuXjEzB7FV
awTfuuZQb0ERkhPTHdzfQhyJ1QGeZTV5bNa8LLqijl2Os8/LEwJzzl4c3J2cHh18tOxn9BrQBTvEoPq
KrOdlQtaJlHFdTtWC3e/a2aLF/V5Ee93NRGNAbOS4hx8C0yrpX0D6x7jK4k2NO6tYKe86qF+Vw4WH7a
aVq9ukzOrf8Ysr+i7WL+4FmE6zs7POMT+kI0lh+KEKw9P1unaeGUcsZFG2CoTqGuHDm5k7UR39eb4jM
jLMsyT2WpLtSARcVJi9j5YKkXyU5ylY3lUgpfSbr+GlhIzi7ZBCgZAtlqGXFQVwAih9ExQPQFxxWFxE
T/h7XQvdL2CVnXCXLsHILQeLBYypiLntZTBIEUeKzl9Kq8VhXCVZSXKVem0tDzx7Ko3ohpuUbJtC5K5
+Oq1tNYrv18u2J7qP5e5YjzmOOW8ECpwPjU6Yvih9/VwNyQvWngpO+0O3cAU1bWPgbJ0p1wuyH5z8Ns
9+n9PzUA+ZMjY02Xpu7l3WT42+JXQHAr/mVY9IhC+t6NLf6TLUvz6CckTzrRd1hhj2zich7gMlvP4U5
xmpJnG7bJAZHXMgLRxWibBTxgoR8ScPZD1hSsxnu4MrbYU79zR6Aum+sKpLxlrijZxF/KsLDtmm0bir
0gjg/sh7HA7r2FdUxzrOY3/v5IiDx7oyIr32MJMw9O+Cw3zPYZeVY5bkk4l64qmi3KwSIoB4GQHfj+n
OPxvbfkiicscc0noV3TGDs3EyO71iyFACEo4mRNl0dKi6ZTzH0TbZWull9e2dF8z5tsXCDnSrNn3b6i
a9qRiN9atPs1lxCxMAfjmGXzCvt5jWFo+xA2+K1t4RU00Hm7kkagH+9LB9dX74PT8/Mfri1/m2+Uvc3
iJS4ghbblMVY4vmmKvsnaQLjC2f8tkKJLnMIg6bjx12QAWqQG3vSGGEkngsKVArB3KFC2bf5lT6vRf5
gyYfrJrqt2gzNRy/IjnO2abrOghUZeva4G30KIJKFMjhY4/xGBXeLmVpSK/O2JGqVkS1hBM7+B/MKfT
UTv4+3KO2fGmhhjWDr6StPYrLV2RAByr7H+tP0kNAn0bmd9SypHH5khKbuANZIc2kEQnAa5pPVQ3AUp
bAKE3soc7HEaZMmnnuKzSJIMjH0ako6uPDJi5GY1R9AZ6SRB1N/ljqT6W9kehbdHc3eyjUlSYdMMz1N
NoM5DkokTM8InYF+c0x3jjx6l0JBJ4hnWC7WQ+ynHmY1QpBScX4pi7IOBIOzciYxbeaS/Mm2ZcR4Pjy
8vzy37LiQikKQuwoFesrDG47h/DP2c/np1/PPOFujSw6al9cvbTwenJkXk0lIgKYYeFYedF+lsyDmv4
pPyjODePLe0NgqNSJ4ZbJ/Yo/JcDBl6+fvs1iPY5+nWr36+N329ua5sAT1pbzpmmP2anek1i3+mGGTO
281A4g/skheXdMXngemy6wVOZc6/oC7WnOoPXBSCmkCNbO5jwlXCRL++mqExml/QqKauOJbrv7G/YhB
B969KjZwfwbBR+OjFPPyLA1oBqmechzStUU14dqZDexdFHldW8Av14TIFQ6zDwAsta0mi5hUtI3ak4v
kaNm39TTa61ZRZLBbfhmz+zX/TRcf5SiWO7qrL38w19va3DE4d33UFc5NpZqva9QaQ5gR0mCq/nQmoH
/kMIF/6RUqjprpFryLISeuUhn8+RbkR0pq213LpZNnNHYZ0JG/r3vN655NJAr21jU1BEakaXtXwIu1s
NM6TGRfWfNbBNh4UAJNaFtiWsn6c9rKGlT8oc3qV6WiRO6Ez2NOVjipWVh2L5ak5hffQpBwQXkod+7C
juP1tufIZGZYuFI0Ph0jLDu648ZW7QyNoGTD2dDf2zj4vrz4K4O6yiAufUqgPbmknA5TW06bvX+l0Hp
j/qVORSIAWhMA5Kjm503aAMtcWY3FCMEIX4ZoDGMZZeyPaJrBfuoI1NBL96WTwbjuPgvhtEqA29h+P4
favFqevmlESLdfMPKez7DyKFpROeSYF1LBWF8tU8nqEyVGl7nFF5HDHhwOdqWkzF0IrKts7fruKcBWw
1l0eZtfJ4+oxQKgIfeHaKR0kUvkQV/yCePw0wWYmpylpjIiA1TNxXcshNxm1OrojpujpWud9rUNC0mA
g78rTNfZC6p6Tl9kC5NTjOxd0tV3ITHOL1Og6x5d2eznL3lMOJ0dYrRlas/c9f9dbhQ8m7AzjjD7TjF
Ry/88K0tCMrX3Sg69z9HMMf1OIiAk1NruyT6Uqla4jY5axaktcmAwyuBjS31wpebVANOpSMyGZW1dx3
EKLinrPJgciGTHuNvtE9jLPREk/M0tdN5wyKx+atorxnVQ5vZG00SQu8BEgrel+k46QMEpX71LK18Hr
uWaudnDu0Px2KybhgIp8rXFiEmPQO+otpDot0EbVsva8JS4bVc9Mg10K+e/Ikm4BWCMdb9i2h8hzklF
BEIg/BNhywSU9Tp/OWsvhx++BzBayJo46BiLILUZYiWi5u+TL3vQjenfztg4zwn6Jx8QzvhdBxFFZd9
oT+RcvHAI0uMU1qx61F2X0xEXeeo33FE/xzl46C+XI2RMcf2IiwSC2br6Qq9H4mA2t2m4yHKB8TbwQc
ohU2YI8NmzvKlJ2pZGS5h3oXr3EHEUVc/pueg+1gdzd43Wo58aKdMr0GOjJVG2I+1PhOJsEwxzsBQI6
0xGxzOOQhbQnLqmMLklE9FXjN+xV9LJvbZJyW5I1DKOyoA0M8jj+hwdIEforlFe6iVfuu+BZ615Y4T7
dutJcAdIEUjyqhPIsd5IeGspIBWhQVoBv1fhSB6hNlg0Mo8jq7Hs7OaJ7iUglmAVVr/d27fY5CT2HwH
TmX4uQEUyC92RKkrMuDD7Qy5JWQxsOkSChfK3eJGTQ8qJKhcwsmqujmm2Hga7Er2N9GMZx7xvRJd/sy
GWGwS8zgTvMANfLiKViSNVIqfCjg/9EAnFg3ehd5IjO76eAdw01PtnimJzkp2PMKBJAsvMUEqWIcRor
cfjxPqyc+upUY2It4xzQpE9KqAb+ZJ3i5FBdP361texY/Rn96S2lyvUVa6yGk7i4jvm0mQe51/hK8DH
yDN9ak3GjpmjGdoYp+HCwBDbDLw0TkE944g0x4rGDUaBCRNJURzFWoBkyvHP+MWpP4amtADFnNUyvYZ
bZKR40/vf3x+11KM5mDqDtLy5nMv5sJeJKriFq+MWupgVhySSQ6lm46CgtSxTZzxIDasADddu+xzzQ+
bQq8CgQy1V0egDlHnHJY5OOV9Uns6mw1yiiIzi1D8D8SceY5csAIzrTzO+HfM16OElp8Gh8y469csya
kGAOgoNdqKW6aUzS4AJ5ELrAg2GPc9IBMy4xThbOvBa/bJkza4KeYa5c8m5al3JUks8B86BfXuoe8Rk
0QFHFlZ8dEZm8P6xnvAFhvz+gUrrCZGc0h00ESMvO9KtRqGTPTn+W4iZJUWRJbhsNNWlUZOT3p3NlNU
hzOk9Ym7XX+DATk38ox4sFe5zV8N6da96VR8GsW+gxRLwyi4SzrbY936f//Ixjpp85XE8x0nfCzXFW9
7c7riSktrpAUfVnPNJpnHoy7VUaiKC6MNq8Pt4hgEm3Fktqyq5ZFr89KWe+87eDH5Mm1XW5ZVsDigCK
RmsiTyROehTypmP1TLyya9DnIOaJpg1cpUK6TI6G5p6Zz3xOf00rcoFVtDChWTvNsXIvqIWluVe0pyG
FFns/QvhgYzV4DDODeI0GozcBCyfMFd99d1R95jGS8fNsk+tq+nyA0vQOO9g7OKGK6VAJyPoejJtYze
bJUV/2SMyH8WKyjJL8b8EUSqhG+DV6/VRNLnJK7I5QhZ0lZkdtHDl1NFlIRIpsSa9sADWdqIjnpJKRL
0rXkohKuN6QABxIjYdcuJJIkGB50WjKuzCMwvRYSr5BeDWcT/Ci9MkWRBt9hUdoqgD7YrW4wBJnq3tX
V1QrvkH0G9ybc2WEcWVsSjkmiRCUp/qV82YX/oXDfDduB+b4n3vfgHwSkWLp/FlVMLMOXEzX6OjOBv9
6OrGeoCr1keZRCJVjJT9KoOi1owrracWNuODnmZQfvxKBUJEu6N+eTuYXCjvCIm1iK1WJkzpM9OLVao
DH00GerG9EcrB7DBvF9ki0O5uNjNMnn/tveOnJF1ZwiPtclQjkA7OmE2OPxWfKA3qeiC+RGysGYyTC6
pz0WxRW3stE0Vj1urVhrRZ5uF7CK9lxP9t1ZLtCAL1JQJQP7VR9OPVlXWC3GwRPZWtfIqwaVb7g8uQj
8UihHuAs4SyECLvl27T3wZ6zJhdt6aG1o2oi0U2FsCaGDc7og3nYAKDrdzYxuUE0O7wh1REGTluhWUP
BL/iyvCul0IF71B2gYdGvfHumqGCMh+dXSwot6gN7D6XJ+D6shPDs/v+gG+4iK7RL/xf99EVLCcoksg
rfOKXaUzxaYfN61tEYSy2rAFOnVSIQpELjD84iP71DJ/1bqlIeJCDg7VH7Coci7zv9T5jqop1rgvR4Z
ixZ3S4qDCusLJXGpHWPdNpzoHqZxhTEMH2IpoUvbdajq6jVsX5VeL3hrXRqv7nFb3zcSAO3BZMP86hk
w18F6sxrWJiBeG/w0Eub87F4sfbpFAsoO24JIr516yt41wfEFdwV2BqdM1ZKVs6Kx85QkQlaxLU9KmU
XZ71vtKLjWNCEi33LkXtFBU0PlbdD1oBMu9oqKawCMaVo3O8rpolZDWpl54j4AwxWLhUNtiyiCZLEmL
jSC6mmRY4jsCiNewDqhMltuS+q3vpXbpdXYkqpBu6UkLp+gF5MEBNMRHroB8tBK4KKcHiSCDEKzrPC/
T+fj67SPC1qJY57lYQUjkJ0h5oQsC0UpyQFQv1UmcTGiuF3A1uWZVW6DN7eW8Udp7gBsziFtoUoHHTs
aH5KltB3BUBs9leXUMnqi5qVMd0M2UQDy9etwNWfA6zMqxFxnRVwax5DLvlL0WMMYVp7mfasD1cMt99
3bSrkEXtpXLXVQumjYiBmjpxvx4VtPrm850zfClibcDJIwA1FBJJVM8yJ4hzFt49E0kPkwkMC0BeAUs
ycAw6NQcbI6in+jfPHEtgPCTPgFzihdSpTTGJM4c9syb3RRpXEmK3S2LLpUSKH0TaZXEI2AZB0cuUSD
gNIQtNnnprZRlGZsnmVv/PGFk7OZsh8BHoxAW9psh30ZzRDNXXrtZnOuLSiymOWfqkGOkNHyN8jOVlS
Nfsp1q6uzw1ZTdRVGhMK7s+vVhnV1Vfr1BS2MlgbmwGInMQ8oawIYRYb/XaO/ZU+IaPrKQ5ABHfq0EK
CowwqELPiXRDZyH9oDjcwvIrkA45VKqKwRZjHlIyfZWKSYKyfXCkUuOJHCDZ5U+GuBrj/vtbZWpCzSv
DaFgx/V+Prrr/+0YR2KuM21vvrqzYaVVDIOrvj67duv325YVQyT6v3pL62aSaolVqTCC3WHEp6a3nOK
gpgPNG8HCoYDgGs1UpkwjltJajI2DVPLinIU+6enV4QmfzNwjaemYCYomkB3m8vxQsTFYS7yFeVll/S
qXrGiZC4p5FHPWHimhkSWlmcrU9wRaru8GCVO5DaOGEPbyvVJwHkSnhVfzFWeYBtdN8IYy1K+eB8i6h
h74sjIGGbIHpH/r1fPBxgZ3ICuTGvQodZ7+HudXtG4pJekOqVvcBM4hWFnSdGTcIX97UC83wACn3t7Z
sdEIPFNKpcZBikbuBpUN6ufF9/KWzQefzi/OnIMnlQ+CH+cEmhJG+qItBFF6Fy74vuBDi0mA0FNyNIA
tYMYQkxqQG+6f97/y2u92CcNkVBcQxePcYsIqnCRzByNtB05TcV366kCrrEKOtngQZJNG/BfQHnw+Hb
vL8HOPMdLqR2RI5QUbnjqsBXNFlqE8fTCsbSQbTkDtnqp22AVtJSZe2FLnlBrCPIYAJkYQi8PDrJ9cl
FeJEU/Aaof6+ATQn1PYaQd/b1hwGl49q9y6/d59S+E9aw38gZvR1jCtIm34lrbthxQF+cp2mveibi9h
cnIA0NTTp4wJUvsEbWiQ2tZIcDRGgNh4d7xko+n6hy2G1pLTriZqaQ8qKl09dRaq/XJJFArXA8/4EWt
MhMQwQDl/USpsjRD9+C5w39Qlf6pHZxfXA3enR780OefB5c/9Fs6eBGUo9rirsKMFgGPLCntkDHPzo6
4y9hAvw0ArWi6GtS5AjVOi9WQtAK/GVyfwenAyHWjefmt67ss+gBrIF1gLFIoxflEvnB5mRF9DTri9o
OCKeyU0yTLQmc09NIO+etWA9C1WjGl422uhPYADZVUvkmOm+1EG1bZgbEAxin9pCPI0bt4PLZfCGuBb
s0L3kLiOQYjn2Lc3SDGu3oK4gpIjctEI9MZBDS1dgzYnecOgcb9bxoDt792GKKbq0ZSQ/y/cxgC8tpx
SNOR3zkQRse/YBx4fRd2Lds+h1ucMLcQcbJDGTdIx9L2rG+ueco1Rfh7VVOHyG+s+V9c04hs7uBZx0S
vI1ZZMyzTztHB8Yfzs8G7y5Pjs6PTn7vyA3pVLbPsOo0aeOQ194BCi1sMku8OFw9j99Vdsdiytlf/HY
Yv5tZ+zczaE2qdDvcPY9ynFg8gK0VSzdy6eX27qR8HdBIB3BUawD4BaJYCzADyvaCxB44oW4uY5kfz3
xjNMme3ohEzMfkKOrkQtMmCqaothNnmHXAHi6ErDNQ3BeKJbVOh1ch4Q42RkaAlsvyVr0eTO/3eJUL3
SmViOQ7xWbEPraF/WjI+TAo4ZE9UYnRnQxVjWkwahvReY3IcWkL+SlIUSiF1bWSrhZ5BsU1nS5F0N2K
tp3Vzs4bmNoOojXsdzjbPRZ5zg0fr1OYuRlwnaJWs2MyxTqd2lbXdzr6OKYC7zkWtp4iVm93p8ar+tl
UOl4m/+28M3dCLQJxUSm33F8hh0x8UYgV1zvNihj8iAlyjDKUsNC4JuCukIKIf8Pnj8feDi/PTk8OfB
yJVyZatKKOC4myiCp8c99fsaRdccUbeACC2YJydiTRPMuE4PpdydGmJxik8NOfSBTvD61MZouwiCyEE
YfiV3XDLwkZq6gtwSulkw3P0j3/amEt5oolpKySFi+UQfsNsye7Fw9LAfS16r0k5Yi7SBnI3ctGF3Vp
6ulViuM5FZ1ZUSeuaZWozcKNBtHyO18qC5nU2qh5lMrTOh/g++T4pq+MJnLCqfv/0EMNTP1YRd6TndM
wC0lmWyQCO+5+Aod4nT6TfiSyNjlkQPXbYBgF+Y+K8hvKe4JRkbkFzyoXbCLTVsLcdCSHmaT6el84hi
3BimEWxrr7GArkuNkg2HP8IMWEczBKZXNCGib//6dB++FeOQVbc2feYWeruBH8NnetzDMhFoc6pMCkI
zBLLsgABAJUQf5VBr6lgy15ZChD04ujns6OzftcEzq9u5Jtb5y60S73npuxrSHjXDrgD/LmBrjz4k40
ZSCRoEosA7J+rr1M3AghgVs2MMyX8xsQSPioEwcPtH0ARnq1VQdExFWrkuxCyFUboqMnfZvgOXwgag8
baOgaNwz9UnmWDefCtqEzW3CC0+JM1q0sKeU9Ar/21dFwQXfDWE3jE7TFZF0g2aUWcQCw8qtvK5yFCp
o8O/VhW4VWwjegRKxkBSlAmecTdhedg87Z5mqdCbqRbwG4tw/iqjcNIHO323MwTLWejURo/4C7oDMcO
sxQcwVk86ATZTCKBzx9fTg/OdLx6hZgVTQc+X4F1ODKTVXvwZOaqXrXd4vWAW1+kqdbNq8wo4pai1SQ
cLxd3RTxOyOtQHrr41UA4Ld40UKtVUzWLxqHk5l/FwJdm47ftYLqcxXPM9MY3CpTzzZqw/3DXtNkDaV
gSbQa51TBSDEMfk/+3uwFTAZiAPKzNvqpkh2droBWzNHogXJyc/TA4Obs6vvwJluiHk7O2WgANK2DCK
0Cnd60xXCPzq6PxUO425z8Mrt5fHvffn58eBS97wVcNjD0Wyw0T+4mZNxMA+kmQq55xVcwgaPMKI+/g
KhK27gXCDRY5JXQSlyrNi92dFacWXTrUlkjDfY5xi6Pc5vFEpW+HSg4cPbbB2SlEqQey/i05LxgAG1i
FnXq1xipqWVsbmY5ODmrtrHYO0FWCuZuGVK1Ff97P+slAJfb8PR0wUohu3gGh4JE5rS39jp0K21lH9c
zUJg8MxDGlTCpxpKKiTerDHdk66ppE9mp+4kzVzg5nSRiPTzZDonbj8dhq9yW/XsRFmfAbk73Ul4Q4p
rIRB2O+aBKe/S3y24vL87/9PLj6+eJ40D8//LGPzFhrdjjmiFcZ6835zcoKPPqhTyjIvAE7KpTBXR58
SmOypKCanVr/Hop4McvHSzi6AfvP0mFt869NpiVQe1m5VUUSHUku/ukSs+nRl3q5IqlmxI1AOk/JZhB
HzVFoSoxIEt+XrUZoQLqcTYWBGdAmKjU0lihdCLXcq7yvmRCoiEj7Z4TkUx6x6XyEcX8TSscX5GPMIT
gJlvMiQf/lsYylhnn/KJVQkC1ni2RsAapyDA/LB0OEwiu8zQwb9s57hF7EEzidg1wbZ08lueIWcM4yC
QDdI+Kq0z8+OxocnH48+Lkv8uL25aJu4IsxHf7L54gCfbVNHB6giraMSIcAOBwMl2i1YiUWaiAr2fAq
pj1hzQSqGPz9q/fNqGLzqlrqy6SQ26drasXhevC7aThgQO7W3qi8mEnjQQlKz3P8Tr7R7lZmf1192Qu
kn46SweMsKxYj8+Sl367EqhSoHHFFuHOZK7xBUG6CMMdgBOsByOqlle98OTfizQmLy/WH3RKDMpOVJ3
JbgtLSYOoc2N2UKLoTUC7tRMe1UxYpoXwnLTRbrgnv9W0DO8oBpKAwhz9DTU2RrV4cqsrKeWSTHlKPC
yKiNwOtDW+Q/9Mq4TWlr1PFgllZR4TKN2rpePrF3VbjvRITJkVHN58nE38mTCgjTA2FtpCcIgbyXV1M
EA1ZlYxWbR2izC9T8/pqnpF6FZlX0bA1X+GVSJKFvB/7q4HJtovJ1sb+SQ5Ams62PZ2tDW9AhRsc/2l
Z4QCFgT2MztHRrba8919cfNlHGhMTsyv0BDy546B6SNGsc7v8EpNw6tTXrswkB+dRRBpkDB127W/95R
UBmzVc032v3yhUaBJ0h4lIgGyTIl6MttyLLCN8kcNIXluXb1DO0o6jjpOuZuAD1MXPiiL4m1B+4n3xr
nO7qe4PVU9XXNuMZLSkf4S4J8Hy5xjMIV1iw6PI+hei9ASP+OefBO8ThnmAfxzGrRq1LnFGDQKKUH85
Zv2lEZrU4EENlgVCHUnTI6ztuoZnXNvMVmlpMO3V4HpU+fymmo3V3ewd//51VPeF8RvJBw3ZqRps5Zu
Ka8N3J4BnUwXLSF0miV5ZQZmr17m5n5rSeUl5TOUmJp9XClx0cIb1LivxcZlZ/qparphkKazMpHm1mt
rKp1s37llZE1VYXg3Wylq/jdBfWw1QWGgNxOvVw1xm2TINNzEj0tZuVYJVahZEIk03WilxKffyl+7q3
UKdS/rT3OIypbjahh0NS5dNKnghZpfZb3CEltVga0GUiLcrUfKA7kiugE8vBxTkhzMIrm5dRV9piqKm
wxQ54QY3BOxVqFkfV4mDZhin5i4ulkL9uydjyHgVvg7IWTILV8SO0yAxPJQGC6J3520T8HEyXN6l5ln
WDaC7ckaHy8kEzhqSFvgRDkyPa9ENhzpUIrAOQdZvUD00QUCjMVm1Ke+ma8OI9kouFuHcforvVSZqvh
/k67GF53qsZr5l2EGJ4mXXCvDi8Z+rzQSb4YTaMK3PW5k00Glaxg9TWPZZPEwyo+5H9VJV59gOxNbtY
BGN8MrNAZqaDVfuG2VJLA45sGU8CV8P+UL9LAX6G08/aIW3FHfNkyIFvGaWdhS1Txj0EN3D2U1ojNHN
ynTMflYkECCNtNGJnBx0AWLOwRJnnXpu3/pQHpJhkecV9+EBw0pjYEX1mM7HyWPSPALYh+BUTlbp8h7
TeCoSXMvEf5oAjJMsqbxnPjN8rMDBOFkUCdqujGnAIu8NbtHAsp+Ch7gQEQNLU2fmGz0TBga8cdeOGU
dHRdBhYmhQrMFOX+TZIp4nWX2rAxwCgh9KI+eQftXRflGnOTCp6yIzAxU7EXZWtV1adgTk/GP4R/RJy
orWQK4F8jRRoYIpkMK6XKqAnDgvI+mFgY7SE6Q/mJ2qeKL7+XEe/O3D6c7lxSEcQIGfisAGpMcmnkwu
NC6TRgtwXYRda43gekfI5u2E40LNqPzpnSsL/DiRgcdUaTWs97S8FPWo5aijuFDn2XcR43NiKNK7tKw
KCufSqfnOXeDtxDsBxdUSaM+e5mLK00dmRsD1PSCkD+re/sZHYUrp/6jOZMZnbCOpjCsf9sUKD86ONP
ff0kG+oKyh+ytv9rq0MxCviKiW3lGaCrzCQC5GWIs1bRgOSOS5JHqV6PnW6dBwDnmMuFLQ+4mj2Wp7U
IUE7MLC2hXpgtPKjBW+0vYjMmybpw5ZVNbr6RApwpyXhsPGZX+ErmgT9ZARMc4xyxbdMoNF181QTzA0
CyeLYrco4bYo6m5ppEqyU9p48Q5OUXBqfTRjaAijappbx51/qHAVhibbs8rv2/rbl4pQpSH3d+YbR6m
F7A+wVsEkzihZHG2GDynt6Xn5OnSyXJhDExBv3QKyyzJgjN8kV+BdAGm5YXlWNLK6CceNXpUVgLw8fh
VEozMEontrTrOIt8CWmxhgJyhh9wsEp9XrjGPpcCP2Jc4wcUVhu2ekqKOa9eg+ftXPMIFxKhu0WsCG1
/LHG/mjQagxpBM70IP+hVFy2hzAoTaDAjXDxHUwVSQ/TFrBNzq0lawqud0/uNvdIPzznu689fhGPm6t
6jlZQ3711RvZVXjCSBNraolRqvb085/+sqIqBQ6ioD//vJFouK05/eDQv7WH7uE338djCkFAN7qk7kq
Ri0u+M5R8Zz1ea9liJJ1QgBM3tJMqhGEWEis2vCLKGytSAJW6rSd+8ceQ9w72v7fL/zYSOMYBm1aPpS
uruCFDjrZGyc/Jt0Z5ZiHJuzvSvZHgySrEtODnesOC8+qC42zROlROy+RvYaFeFLZDyJmbHtQS/vxcE
pluy2U2xi6xi9mGZNk3xi5q9Gc9X1C9s+PRCTg3FKqENbeThEKswZ/Xty36u3976+49As7rFQHcHLBy
JfD9JEFtMXiTbDbLJFrvyL6ITOSOS7cqGlI0cJRzePGHeXCX5cMhRUGbBx9BMIPzyNZn7Y/SAxDgWal
aarJAoGUmubuYA1V1Opy/NkKIHfwnWrRavo1J1dgyIkVN/PD9Xmm2U5pndaJvOq49tRxFZJLlXOVLmq
g1Jmm9q2i9Ze6DXS7wikoAeatyQ1VuTdBTk+15DgPywkoEObV7RS9vOGoZpxYzaJAiiQiLZyDfXUG+W
NrQ77cD+YID0iBPgk3CGqSQq81T/Id4Qfzl1STPe8O44Ij5JUanX8BBqwQpVYrrUmHSse6ltKzuPcfw
jZYcgX2thRSBHnNME27fWHTskaAIpWxebdzXwbeb/e6tjqPhXP7TwoRCtvQ/z10x0gH5pgsoNVV7ft+
LekfatvGeaUIKhdduORfkFY3nciRmOO0GXawKx0Y5D5RnLnRklz/sYtKaVXnn+CnWlhLeab5RUywvEs
WXLYv+nHVP5STD8JyRVxHP76Q9TD03KJNEXRI+qkVVX4jGrdjay3x0be/gP1Fr983Xe3uGfR5nbelxd
i89dtEQH7QojpW95ZoOs/E8p3tNY/ScUmaajvFo6UTlhSU7QAWir4ZQLNo2Ykpa467VgzOW95SvGgtJ
di0CXqtKKJutsDprBiCfOdAoD1535VX4t9A04eTohuzx6tuyFhh9HwS0CjM19dTmwmzCdijl22mB3Zp
M2uiJyR6rN3vdnX37wCno1+HX03h/mjxGivJeueNnT0uA95eNvOZldcw+YtR3WV/EZMdhvQQ54IPth8
p1u03DCGtQPdW9kX2VL6sn1rq3sAYcD8s1/SL8I0V1b3HP3q11k8tRaKINx+YyeG9jtkV/lshSJpl0w
sZui1833Z3Xty7j5SUUOVL3KyF1i5qGcmp3l1j5bvismMoqIYkJiOE0KLTIubTuS113GK5RoWR79mbq
YfeeTcSQIOewZAamVtcOED+kUOg+wYslmsgN/28HDfXGPxE2LTrEqLKl6DWbQVlwzYgrjjWFSsBbCy0
jc0asjBZTQ8eN1cVby95Y5JTFCyn4/1pVAzMYrFuY23KFlcrHMyjJiX9FYSF2SyOb5zReJCW7g9OwL6
lEUsiMBRLTPdt+R6CQ667q6pfYVboYoajOIN6ChEXJkLbLdnCXfsLT1nLR+dLtPQrJ1yS6k5wsYutqL
VpBNqiFMn/irpjRcTcmTKkBsQlNYtalK9Gkt5eILfJ2J5P4GWD0UwLDpCxyyZMIxTM2FIGFCLzrzrlh
fegbAUsuFlmy3RX8qzlLN3wlrcTwd+Hk48U5xFpfUDWbZ3oavZkLkynfNyuy8EoAtmlUYYeS4yAZjQ3
Ia5H1KHGjKXVXWzN6AFq33M1hl1xlx8p569ZVZysCNFuEKYzPVmlwW67KruEAa1F624xd7B5ezegnCp
Yb6KTrC2yiNpRNIOlDqAZlWEn6YemSXuQJ9ZHMmLVGo3GWA48aTWn9Ko2qth50aKC2K/wOItjcsq9md
P2vHCJ6KDncKKlZampGKpnkJt1+/gI0RcMXAWwolA8geYQTxajKnqSfEWbrDimqH3RnGn9Kode008Ro
FlpW/2EAOZlwFh66qJ8nD2ifOg8rcjiSyf1K1MSUKQa7mVNgw87mCKnLJQo1UV2gQsGjhrHB+dnh8TO
FS+hWHfOtz0D9lifojKeClCCtiKvaqtrTglIStLaa0k/9oEyi/jbLLhcjM66uMPuVjNP2+jEB8pssHX
Y4TdEFeyzWK9kpz8U5XqY1RxGIMhbqxE1GFNy0HEhYyu1fWeHjnPaPL386OZS8dnB53OFsA0qqaik4y
yGDGOQYcQzejPD7AAnNeMToCU+WSK/kHx23Y1PiVHuLlG04xr4rBzmDthq1Y/3L7bmGFzfUrQRZj3dr
ZL4Q8cecuGVsPApljIi3eMWpM2CgLtBQrNRw64+W62Zy+da8GVkHhJvUGWHc44m1P0TTOYYzaWO03JY
IdpRQsFnc5IZPNNHJo0MjcvOco7i2GZFN53Z8K5umpnb+c1+Cc5nNkKe77aKhXZ9oW31itth2iFitMf
fAYa80EUKZjrJszbhaQxOX98BjRMkA7e6UFZYVmL0QrSa2Lbpn7j5n9CsHrtJlKubizjTtxNho1zUA7
/RRmfMx/S0uxlFIBw/cCs09vU421lgtI9+abZvbAkUkXN2CCQVTiuBMbQI1CZ50Rm0EGbY+o1+cdtiq
7uWmNT5tKkU247Zbpuczuzw7ph3iepnu90gm726XXXUz3gXB+nbLa52n9BryhQzSps24PiZhgUZ4OGi
j6ZJzG5tvgll6N6XQeBk5ysBxO1Fg4JTMedhmwRQoAhlRlj+I9EogAz3M0TZVNjK6vjwN2KfZSha8qQ
e0b8uu7e4ts9QgHpETq2GHZ8qliuk5yh2dh8qGcmPV9GmFnrtjNnJba99co1owCc7LoiXluYFs7f1au
Wfbg/ZKoTXM1LRW9bw9Tp0BRgYmFDrt8dFbkbbmN2paKlzvuCpGlC1cCZrhrZ7ieluN1flUzyXDelI1
XR7JUkKmMwJI26ICLGO6uqa7+C0+UYLsmVd5dEdmAtjHAaqdS+lsYu0gWp9ZK9eVwKX1EnXIMJ2Rzxh
qXrqSUUoRAGVRm4BjcENdU7aBFlU7+37mScMJ4yE6XyiBm2fHlTLh/+U6YfNXRi8US2Z8k6MM04QhLF
qmKxrEfnnFHZTovNNQq0Z+8FMdUbNzUN7/nJRnMILrkvVrMo9oZ55UkmS+C9df2ixg+78Jvxl++zHJR
jnwkCpXsL74Znf4bbihs3C4cUFxnxzPywdAdhxMYJ/6dZmO7gOJAbzs3xjcyLtndv74fn//JPNXwS7Q
xgaD+K5ICGWLLH4K5oDzjaEhr46H6JkxfKIZvEqKGYUJEZtAEFfdjaHtBN/EwbRIJr0vt8svv90uv9m
NvyWdlmTLV+f9AWxa7cB50drgZk9soD3278Vl3dvZbwOF98IDsYLsEBlTlAOwtEel4/HrGaFxUVI40U
GeY5XvaNJw7fkdwuXKl4uOXWoGtJId7R4dWCxOQOmdrJ3IBW7wEItn/I7m/QdGT4MrmZaFHkcQ7NYIQ
PnS9KcgQy0X4jaaktOWIBnxLkzORGjmzSeJL2pgvGM1G6/pU33pFJ+Fs3Kz+R7G44GnC/X6XJsjoAys
7UKHkJWwM/TJEf3y8vCFGyJP7hhIr7yZwLzR/bTdi4g+toNFy94EyAtIWehA+6iQA6E7bDNjf5aSDBm
ccJlBMMDVtss28hBLN6RiuT4PNnLLhzTLyGgVQygB+CXtXUBQdEp5JkDSXxLTh5HuqMSUYnPuPOfy+b
bNyO8JLBODkyhnyabGYXi2KMa5S3A1K2LzsPYxL+6hn1F4amGaBiLltpantiOjUvO3WuREJUmfcm0K3
y1FMKvWNlkR34n00yTD5hgTITH8s1gX/CmNO8HlxaEHmGLU6MPFqmL05IIxiY25BKmC9dIV3nMK5tEM
iW0tvwuC80IaOmP30B8MVwZ5LeIPDGyVwQL+rgbKEdAa2Al3b2CdkO0LhPosSoHPs5Dtab5Ksiy6CWl
9Bhi0NBl/ARviE0gM2OUQSQ5vHzxbHrJa5LJEeG4XWA52XnKaKZsprWa7iju1NhYxoUe4mWwuU26TMi
AOoFURq6Nj6kjaz5C8QDw9O7867qI8ymoG4ELod8osBfGLaINFtDHIKSafQTKSm5mhC2KTd9ztNgYnb
5O3Sxqks8F+roi1oViF7nBM8v69r5nSiVSIqDfZNT93s63v1GwBO20gcy8Q5a22er8WC2TNYjC2f7UU
YOvdcr1UrI3dV8nNk9CkvwCmlGEMTj5+m6WsQg0rUKgFh3k1/W4jkrRX4OHZwYdjUuUI8oz0IjS70tr
IyG8tpdYnxRy754bjZuf17Sv48cpWIfW1I9pK7FxZ2w0OmlPBf4dDVU1vjrZ+XqAfDWOPWISwKJL6Og
83+2Mwt2KNG3K+GlJ90UgliLZ0MYgWOK5YiZsvRV+z5l1er2aQvm75etVH7i644br2Mxqv6C13boN8j
vFVRLoPFEwAASSFJTss2o3HBeww322uA2Hq+ZiQQRlSpCHqouIAvamesUUhA5rnDyRjwo405xv7efIA
S3qYs2r7ObAk9SI8U9zsPAfIc8r+jI2ME7R2LpXsf4+GGSL9SCfcLBcXrRTHjtwRwiWdrt9I6vuQZ//
71+9ACtgm+w/e3dUrtFa6LtYOHO+SakRiuBT0408wbiJQEbvf2d91RH/jkHEgKx3x1yhkb7qt1cKzhn
UTdviy7FEnX3D4/qB/8sPZ9cXt1grZFPWTZ2hiLiBjmDlkSOo8uZHujJcsEaoyUAQqRUUo32NxEqKAO
deGpB/mE3EwTYoyn8eZSMSMZ/uHZEgeTJsvus2XHCGA7XbEIX2Mp8uYtaI7OKj25sC4EvUcFmCZlp0A
8BSM4rncaWd58Qyk8EGSeNg4xShJqExig1CMiQzYmW/GDxq5wWjqOELpTcrYxkZTW7PyuVf4z73KHk1
rxzz3Kvv3X2ivvtZuFts/94rbOWc4V1ifs6O7MLybOR54yJyBeL9ly+AwQXbtqcsoLjsRfpOlIRnzRT
We1G/Q8hP/bpo6MjymmHAiVLe+jTFod3MFXUjLjgP3CIiSwVA6YU5+SiGPN1qNobzeQTvBvGTPSuR1J
3MU8JKqE2y6qgEnUqZVsTLlVX9dZeauT8ssYDQ14outzi3Fc0ozaMYvb2jFe+3afD72iqf41KCcX6FG
X6/9fk5jG5/wnwN086P/xlCfpRPYCOrnHQb8nGO9mIQJRtnzwhWHhCSrxSFs6HohVa2Symp0Lyqyj6M
K2mPfmK9X9Aoo/39v397etpHd/T8/BRy/LomYgkk7dmJ26X0Uibb1VJZUXeKmih4WIkEJNUmwBClZ2+
5377nNFQPqsnmb3UQSgLnPnDnX3zlXNVzUkHBLa8DGSiI8YWKDso9hfoBxYlUY0IPJ9K7O+htiSEhDV
8BUs4auYOVspiJUaEGUzi7EgzQZ3N6Wv1rkzLJIZ8AmTsdA3AiNMFQW5CoUJ9BdGCX/5ZpT2Bt+5Qoz
GgUKakKYksqaOB72GlrPt6TWbBxuUnxxCGWOnaLhIpogi/FijPiTa+B2SEOg1w0jcEFsq/I4QEXvsrL
f/JjPc0KKmRfqjrA1BnHNgg/mY7mxA8EJG+5G497DqBsctEr0uBcg/0EP6RrggScF/ql+vNAnqf2kev
h89CvnJQ5OIIj52XjIzGmAWTKunrpT1ZN4PwkkXb85xEwK6CFKT+v5NxD05wEhKto7DMDCqNqacFnfA
t1q3iN86e9V3C+h+Y0oc1grbkexd4XK91CAE6KT+rMZppuD72SE4VAKKggDOuEDL3aPh3ATcCf+ZzZa
sQUu3iCL2zbWB6qSnBFxyf+TsYQvhD9vOBTxZHR7/NsqhWNIoFPGxv6I0e7N7eDJP2G45thY4piJK/j
zFYfOaqsD8ogZOOAiXMmjJiBoJo8bT2Ot7teIbhzFGZMUwjqdZrNnHi/DiJ9NMgQ/i6IB76dSZDyqJN
DvGveHkOthjQtbAcMuq46S5NPoAs3Ltxo++Iw8xgpKiKQ0mWqOncGhfXhc5BrVItQUg0h46gNVsFcVF
LsbF8KXJb/AjZ0D5dyhIbRkJLAoyqGftCAP16SykmqHZhnmQJu38fK21F0Xj7ouFWfhzIIxnEunz0fX
LpIE2wr6jJYhH8UP8JjxTmjYNyusRQgeD7VYD3HeCWpR76nV3+KWfBXc2jrup8LAyy9OEgUmGFUfgtH
kqpJAVQehO0/Vle5VEAKws7RByFJ7zuIhDZSFIfZ0T7iKYKXVSXdK4qi4XZiJqfFdsyLyWQQD9m0Hv6
MAGZlqlfmjXasgI0Sccppli9brOHoefcJ8pBxLz5SFELPTaFYQki/IQ2hPoyzoJsz+fm3a04au1usBQ
w+POnwR/6mjfoTkgHv6HnHhT+L8hfEXENw46PZoRbNYWmHczcKOK7dtH7/hwVtUrZQZ86N2qsOLm3Mu
dTpyA579oOdrVhUZ/n8tmFaX/rkLJtLPgH5QPuNso0iThSSYR7BLpAUgIo9ahCfw+vIz3sA1PYSXE7e
xkzWh6j/zRcv7RP6KwB+W2nGFAxXfIwr7grDtYqw2cuXidNiAOl2+N3pyKaf5r+ialKcrV4to62MEE0
DcSYkXJ8s4klm/pAS1w0nX6T+15ltNmCw/glb7xbEzwh5zDp0RfraR5zIOfrbiP67xtKh49m3g+OuXX
7Oh+/uHX0+GewdHZ6c9tXQVgSsA668WbsOKbe7GIztR0wV36AHQBiXgcO/UypBZvOGE7yIKxGUBvSTz
xnJtK0ewceD44HFyu0S63Pxj7qJEV8KMKgsV7mul0ZaO+QtPnj07Ev+7gzpRHrQd6G8meFgiFZZD/ms
+H5/lJ/hEqkS3Aw3a5ObydKDOKt9Q4szgFyZRlR/rZVfgwkX5G+Ee9Cb2FEYwJBBM99FVAR2IlYWrjV
RnuZ5HyMCWEcyWipAPwCXQBG5Pp6eUOVdlSIDDPlcyyywvS04SLLCzdEsyuaxNv+akbcPwQH4fxBNmR
2VoMOFOeDnfzGRIT5S8a2NKQTXytmeHmgINme7CESAAE04OLD5+eBSkRDuifCQGvOH0y9Hw7Gxvd/hl
+wiFCqqx+fqnTqf3y3v4T2/SeTPqve9OJr1Jlma9LH3ztoeo4L2o2e28S7q//Jy8f5/89I4etqV42un
2fs784u/f9V6/+UmX/vmX5Of3SfenDvz7xin+Dkq+GXXeVItfTlTxt1Cs+y55+zp53XkXKt2tln77s2
n8TfL6DVTx9m3SffeTXf7de3ySvO524e0vm5v7u8rCgWw9byeTKxz2ps5GVfZfv+0A2c/TkgL1ZaVHB
EW1XvuZAK2E4zpYdGRlAHTy6Bp4Mr6Q39M/bao2dkiElwvbL4i9U8Ws8MVWC5u2Mxxj4eEoHV1nseel
JCoW55tzKH5B2OqVry0o0q1QqfMO/j/6EL3rIMSiCQqltGxW6VA8pSf8GpBbijF3Lr7JWOAlgP7jfwl
ooiV4E9sfgVINTt+1FQAFJm8fnpweD7a/bL6gH1Lt5lqr6vun11kLwjROCDiZzFGtN0kHhcEvQglhuo
7uVtfABsHO39gtrORyCu3iWejaMKjjBEkesMMte2PHDacsKvU+D7Z3o1eUpv3z6enRKziBfyz/mH/G9
aLc7IlK6oeP8V/rdgZWNkV4d4R1G920up3XPzlNjKZFmbUqmcqwmIP8qVqO3nbeRGdz7RXXDIB9a4Gk
5XMZYVHFz0DUaiLliOjgi5iheJeWTUjsgKPwMddBzemiJD8f+2xFW3xmgsdEqA/PA19Z/7alTKFbeDc
A+YvPuwo5JrbygXjbQKqik2xfLCSn4kuvt374s0UvOfUT9kmy/lh9OpTPYLKacfTBSf6CgUMn+Ww9pV
CjKdyHIDj1os/FbTRDUK9xtiBOHzY0wSyiI032fcWK0yVM351TVc7JYOHftfjoTIB/w/xhcLWO8GeSJ
HHbhpXAMkDsZ6VTETvqsNfreraA6pCpSaMpRq3k4wx4sKusuFqmC/iQNBG4ddD2DJvUqQmzdGJztykm
l0IoefZMnKboq+PQI94LL2Ez2DP7Kup2Op1E5xbZkD/AINzoKyh8D3goJB4Zt2H8NXxQ+Jb4AJ3bXNn
5L70LC4ug5qNOj0L/z+1j0I5aMieyD1V+pVtKYID5IvN56027vns8ZfiUAdXL9ax1jmkZ8JZCZisLzA
13qMeNXFzEr/i3hn9iAndfF//PfcTLmQ425bRMOt02X9i43Yij4OBD6Rrh6qVlS/6WjlfID9MfqJYoE
JCe5M0kOof+9RFzdD3nRvv4mKcMnl/UhVLGPtXi0m2Z3rbqnJr8hs97ZDZ9EHwzpP17i+3xeFlaDJbC
JroxO8uiJagAcOCi0HefjNvcu46+H+G+PDs4ORrsbLqFuZX8/Ce9ynlESLGTQhA1+ABtr1bLHE6se4i
odB1yFY3lXCCWZSqWN1pewb0wvm8S5rRzMUGItdUN2+jgR47npXterSSJGNyynl1mS7haOh1SS7z5Lr
FvkknXwpKIdg9OotPT/TZTNl2dlYqGVC9LhNhJQEo++9RD2kHi3LcsW6A/NRqwVreFtEuktrybj57p2
uxezTDQk7B6lldoPybvaaTIsxTmLZveoeONMBqREkt1Kgg6nN8pe8i5mMqqsyJ5xhGEFthVmNgtmAkL
V00jaXolzqHmALhKqG6y2/gbNlgnNH9hQQHZe4BWv1G9gavsBa7StCi+aY8FSyTkWnifLEoXqzpf4Jk
p66aoApzDZehYcEnrXl+U5/niQptNZZvDYwsOR077NjpZZdr5lvd6Ph9N1+OMktlaerOegK9gCU9g35
ArXQnc6AwRCwxwSFBvbYYblVsQnuwdbO+c7v028NDiW36v2S13QzZzH2+eEHOglw5z+mPThprnwSsdg
cYolRnmt0b5gWbUj3guBmZup/DFUOtSFtkyL8b5yJlhR5Oj59mRJzVb5L2fpuVqqI7ikM3DntxmkTBf
nNPqJ0pLLpvTbtI8XfAtZg6XkI5ROh0RK4hhjyRXwEyl09UdamBLjoe4pVgqpCtAX67TsfKRKKUiISm
ihiI+kTvRZm/z6LKYrymFI1SioocpnDil6fWq4fh+qxqmULcpTNJ4SLohG7PT1r9Vn0qywq7GReKXQ7
r7VS9xpP2OC/hM8Seyie090HORX/0RfeBuUhFrRCVxxpSvXnGn5JlhVaZVgcssgl/ugBwtoxR42IRXa
pzOMAsy2x9BUqN7gpZmls7vrIqKCWcbU0p7Ztq5YkzYONdSBPSTFMDSAmzpwqonvSlykANg5bwFLgpq
UtWLWGIwGEp8pVKpu3LCcxWSF43xYgf2Haku21aW1C/TI8Of46ogay4pyklxYq8ECm32poijH6NO8tp
K1wJ393pJDjA0Fj3FBKtgb+Qk+prR8CN2q6XNZ0KNn7slscPYkTalNcJe3mbNGxRvVjBLEg4v+kWoB3
0kLNA8ssKg3GVg8KD743JYAkEEnkfsdC088lvuhqZ3MEUoLKq92zF52vHtUI6vSe3e6v7S6VBNlWZil
HR+6Wg5R8jiNJ1djoEa9OAuiF7KOrjV66y+e3M0AsIHFL7F+hBYVOSwyylyNjDY9ZxlOJzzEhiUDI3F
4zUIh1KJGJVAtgC5dNbjWZ5lKex22lSGMCDFAgmQ9pPOTy21EM7FNMNTmCMflGidvqLa5lpwsjMAr5V
qOlR5bTT4zntOcJMc7R18ghvudHD82/Y+yGahx8MveweauMgHu3snO4cHB4Od0+HO4dnBKaxXx/3CrZ
klr+CrH6Nu8uYBltdw17b/La7ljVgD/yWdA3u77EXpGKc4G7vr3I6O9kDoqYWPeRFsWG+gI8Gl4GzrY
qTUKNz64DFOWQuzuPNi9OEIzrMy/mfOki214dFMp7dE7tA4y07x0/wbcr/6Eo7REoKpx/EnZVNYZuWi
QOKM8BbTRGr7il2Cw7pCpYSiDHDa0YUOJLiCzQeTlIy7TA1RTLLydivVxPPoao25iVYm0BloB1DBBH3
/SVNCu76t82MrOYH24SIb5ZO7KJW6zCyU3A3uNl+30ONLqgI+Q0BTaE1S1iPRBeKdmLtwwVp5nGK9QW
0NpDjPwBVc5QCF/5WbOCiJGS6cvUl8xlduWUexLx9RtkhW72tVC3QWmZ+2oxMgw4JdCOU8KvggDwvbA
NF9/fZh0dVoo6jyEbHb1Wx8brpFYO3uABw9q3oFQtW7jo+1KSzeOZa60EtSUxxuwLfBGnD3h6pYXSP7
UqKXfjrGM0UsattmNoH6v9Wygyyab2jhs6thG7lSxXjzn0hcTum31gpF1FWfNiCnYO+rGy3W8yiVnG9
1L5Jxms0oXZDlZWG/JxFA2GItu8oHulMcb8fqoa414C17sLEmTfssFhK1Z19SncoVWcstCgsnAkM5P6
fKCTxOgjYlLKMPmc24KOOmfei8ckF9MLA3HIDDpIlA7KATgsMgvhtCDZXYT1ctDCWxNYjMtTgOkwEj9
RDTgbrJHJiMXBIZ8ZxafTGzKrtWQrkeJHna9bM8XU9/qKINWH2EYsFamL2jm3eRxleuImTJfORuAvru
658lDRr2RaQFPvzhiKAQvfPpnOVWuoniPZbShWne284jC99P/Nz+ExncSP4eReycFXHIXuftW1oI5cK
uaB7aVe3T1guOVwlzIpbSZS5XtEr8gWClsEVumf3hkczS5bea+oAHTUvDc7DyuYBLe5WzCIBRuViVQs
jGmzxphN3+NpNwhxw+iJA/ikpfWlS6BNEjdhb7Piq9iVKboxyi10+h2jz3hwt4mv+Nc5OFxPSU2b9sX
qyvrm0gP14sqyrfU1WYPFw8XDSgtCslcS8osy6IRFARqpZGmVUPiZQs06TIEV/mc3aeg8KGn6NdYrN3
MOlrdC4urarIRrZC30sj6Fu8IDYwgS1GOrVcuqa3YQFMsy2YIxK8MeEmfhbRh54k1o+e51r73wjHQwb
ptFybxCO6VPTCu2ryBRM/j6oTq46ejWhVFHGylAVpkxlxTKqOyxxukzum1xhuizPrVZTKXGUgJUvASF
YV/y1AV2biYXW9ipRSPl3BiFm+sW2MpB/Gywf1CGz75N2RT7yKkLngDmzl8y0kSLCTjMKkjdoH2BAgP
ANlWbE/+k3mVYJq91uE6SeX17m2XDExuyVRA2EsZ7OMRetxAZJM0nja9eUQ/n/k0vL9g/4B9lyp+eCi
CNGvR5BNW5VfVqJH7mMEHkh0c5s1homLKzfsQwjv/xnxfZJrx9kcmhxdUwI0yuEom0qxw5Zz//NogCc
G9zftWHbvL/kGZhEcCPGB0aKWFWpO1AAXF8k9cSO4sLRJeUXbSrEhK5fkINfDvzPgVRUhYocvrupx3M
Zsb/wdgVDpkmCXDVTp0N9xRRgsz/F77dvlum+ovCG3cI6uSbeGfiDtiFyQ7TPLOKd17leORn3LDdpbG
E4NswupjnOvGo+nCTAs4mGtPBPC6fUaj2YBayrD+Q/XtplxQqOlPToR/wSShvRciEml7FSOcGe0g6pl
SsmmbVoulM7Dc73pBB2/fj48sXPbVhuwjjxKKfZbL9cdnDK4cPE+dIxE8DfqQFm6vUJHNzgFxlRssUP
26jRVI00zqTLT7qv9w8OjX7d3/mX4cSDGrJulL+OSm2bQmHZDk3bjbRo9YzjkG7URoOL7bG+B6vD9Pf
UFvNJUpcobDcMdmFiGG4+1FXeHp/Wj7BvbybodOco4C2RqtS5bTVmQJn49LZZ99f73AbqLBy/HGVCH9
CrrNz9qc5DUokMAuEXWBa3pDiG1b4KC+oD6x9ens2XlT1TU5stsSNpHtsKo4wF1acXLep5MckTD1Nfe
59Vq8Rkuk2z5kV60ZCxxHPCSz+dlNnLgOGpqPMHPgMOrqdMc21vkyoZT2HVTJLECW4peQg72TbUVnpu
vxNTpBtqVSuOAUr11bq+gTPuFZ3vRh9nLhYUrUw2DsWonyLTmcfafdGKhAWjt4yDQkNlWQBHyyZ0phH
k17D1Ry21xQvN+81nNTgwnkKl09iP7WzDYp0zLw3tdKc34+39K9y1yTdwO5W2Q3h9+Ot9623OzjWOEY
ZMtxXOOE26W5VQ/Oaf3F8m0uIVNE4dCg9SozuYKABVGgDr/k5P9CFN25BOKKy1dYAKvOHs9f97+bTA8
+v3waHCApV2niShqAvN2Rq7Li7tD2NT4ze0S9zcc8quiGCfNyIfWNGWAg5yP0+VYOT3DOHsEBoRIQkA
GnHr/uqmzWOfOtjO4SJxW7bixUMoSSUeuL9JJRt9UA+QDTX4lWScdEaea2s1jtVb28/u6bgCYyjtgP2
fRCH27gXulkYDchxHFmyagMsO/ZrcoXE6Aot7CVIq8SQwI9bZYr64KnGCY2len+ye2g8GzR7W0i8nDl
9G/I8ETWxHM4bzA2RBDlzlXivxO75KmE237HOqZzfJVW3w7MMBMcrOTzoGM60C22mybhUMX5Q5/qt2I
dPa6Z8rV8w6jBQMnmA7X5dtFsmaow1bVEQQ2xzmDrF6gV3ZFAxygmiqeER4zEVIdarbt/sQXdZhShpZ
aVamUHZqF9Lb7ffGyQqh+ePaDT6iO7VS8Vk9MFsAN0/jQFEHuzYQ3EKrO8QbCKbYD73Y1s/gArsa7Eg
2jWSH733JybKo6rnGAGLtYlLaHnfK68D4hTzKHYreU4NKXMrKFCOLpXB6dDBEH/qJCQeU1RaSnpWMRU
NKA44XGI9ESP5W2TFW6z/iVdeejbClNoUVYeQOiiNl1WCH8YjfP3MBImjw8LchS4ILp1JPEhBI+R32c
n+1og+gmVkQeJ0EulbENrmGgDaV2YLBokn5WdV8zFnbMRaNEe/L2EMwbBMsFkQQ9Aear6Z2iMaS+1R5
Pz9Xs2a0WMM3i0lQuQBwqMR+TUCTyNSgm0XhZLFDmk1rQbiZ79RqKT9bshTBej5R2Hm8mSj1DSl/UAj
Mhm2QICyYuL+x0877TaUcf4Qp23DRe0bsu+847fkyWL7L2q6+ayypOngR4hPEAHWvPVOJXMaLMVKsff
qh2wwsq8N0hnW8rmd6Djox/8WNs7Mny26s4UD6oJ5ZLpgGAqvgYb3DDDLXeqLGA1nsRH+CXcAwsAFvS
F2sce1RUYdwX1Ak7HG/f0mSqlhMLu6bTeIRNvvu6o105ZP/D7A65cMshvW0PAN2xIztTpIX+c35yEQw
jVNkju1rB60u1LuV39YMtAelrR4cn9EvcC9WrA9/r3Q4e6bJpPus7egmbVOP5Qq2FHDMRhvFPMyZLEI
69oo8WdO8XdjdVfa/EK0fUnpv6AFndl4rrod4WnvNhxWHFvQBe9qMu0tftslwrrHlYVcutitVhE/IV3
BgqaobhD0HcIn02T8cieN+pje0KCirPq0HaU5s38CFnTa1T3VfO4sNN7KzuDx7dONiNDZp//UlV6V+x
Qtg4EGz0on6Lmr1tzbzvU0N/PspE+6j6Rdltmzw5DLd8RctZsu9xWjrbbvtgVzMmiZX3mkxcS3bQ5eJ
tLJrPF2uSswTchO6bZdKwEMFKiVvEI+QpYfz9XlfMTVGj+aa6Iq4yqn7365PZa2zY+xWyHqb+3hEJMW
0uMQ7RWYu9DlAcj5veQJqM7tTRYyPBsiOZGER4yk6k6TzqdjSccEXv9wBy5rEs7zqdOIS+ExB5QsLOE
9fvkWsY3IaOnWJ8Nx/P2WTVOnciPsnCxMJiUa4WsOuGYwxmYvd8wxbSw8kMDiv9hpRK3f1cuZIXTeYS
7U9WF3MkEo0VTusjhYRdwBAjnD+RfSNtOkeAH53zT/JA2hhdhNkKLO0GGmA2CJvi84AhnOz5QOV9u+q
DpFE6BRQEea8k6m4pZFOWenbaWEnsZwDTfmsOx/P5QPu4SwNIdIdZFZI/CIljOVIjMVje1B/dqrcVhr
XJrZMvHpbN9tIrE7TFt3AhaJ8tyniDVd7bF5VT577GqP5qy3I2/C2u7NYmRQp0xWrTNig7pN3zIwAih
8kbo8/kr7ES9wzglKDoQoXhkAuS6ogTW+XUpKgsRiPBgoxWynSufVfQdYbCY4g7oybIM6kdqOcyG6Wo
0RKv0rVKssJucnBHQ+XF9IZ14LN8lV+5WddUPdcppu6musjsgKpjdlCnGMoSxXf4Gx+ocForjMaticQ
swgcgRz0lrDt6xgW5ePUjnXQDV8Y2d6d3JOA7dmy1nFzagX1dVmFH8ZnCi9MUMq754L9djazgTveiUN
6cZr6ANxgk2rmovCnpFfbPe4VQyfAOf5wW30j+t7AD22rEfflJaomr1XW/a8KB8J+/x+6+JCMysWTIw
sOWvF2iIx0SZJ2jyIKLK9cL9AQwLwMrSDR/VExh0c8QmA4oEkwRanxY/V1ihtwsLXN0moTN5fqp6cN4
LiOh1A9yV2E6Q5h1bc8hk9HQnF5NsREbYu68KglSryUPtH1Y2/VQ31H52qhC1O1pafPsEs/6fpO9hsu
ReQ1YdwtSGn6BR1gXd90j9Hu7noBtxH6tCB3/aePT/EktjiS/RuWWbov/IJdKrDvNQVuuzUWiDOTMiD
zGPr7BYn5mEzfJBZokYhzSWGMVp/I99rgUIHWEFbvMUGkJvAKm1uC4VrSUYZ3Iy/61EUStbQqlWi+n0
/wygR+o11Qb8px/XsR0c1MoVKuaQEhAUG0FNRr4mnRvB17Oi9H1VXOTwYQ09mqWuQZEDWmiAxI8ka0T
NpOcZCsFisrrpRa/XF/2dej4cHB8PIQpD1axabv6DtgKEzSKvqTfMlHPoQg4y8gzk31E947goQR0JlX
mx2UzwxARXh8NEoBhPZ2bov7Lcx+kAssi8xPM9BRml1wiF4LH22AJ272bm9BcD29JZPV7TtH5xr1wL0
xtuPc+XUA2N248eSRZ+55uMsGWKncHv559Gu4dVrPWp6MMpYmEkgMMYWwtNKP1DUimh038PPo8m0mIH
/cLL1GyaJS4WTOMWNyKUqUsy6IfgIaUqx+Sxj+wLR+6KZ++Jb1BbhM3eZ3OZhlZQS+XyIAoRq50B+Ok
YoeRuRug1/BM/inhytR+dR+lScfjzZTGVctYaofBdxSNKXjDeNdjp3bNNkNEoAW5m6+iWUFgCVPytr4
u1svEw2wKCduo935pO2Ju+JRUkLg4DQ+wXNsHWm/fRT9GrdfRjz9S9PDb9uamY9vHePOBwlgDrmQcrW
FSptGq/PDie8T40GX/xTiuDQiGA7haL5S5Oax0CHsQ1RdADgnNJ9p5014VYFPJK0X3WKWiKnGhEB95R
UppWfukTnGycfJ6DW8DccR2t62fyDkRY4962rYVN8o6C5N+WohVFkkKI0YTPh+62glE8hjYqSE97J9f
GKxbVYDyucBdVyzvmgHLFXTQ+uu0+EJfqlHoOmQWspv5ejptNLRJwWkFKB7UdX8rJ/TdPW3oaPVFCtw
JlUiQ9YGfsmWWxZVgaPPb/cNPw6O9Xefv3e3Bl8ODuFExCG6Ygo/oK1GZRsoaBPQ8LyhL0GqMOcnClj
SrNqwL6i/KZDImxk1uBSicUNWUSKp520S1Yw1aYLU6U0llXPd0hFAxqSNmQ/2Q/mC1HmFnx+vF69Zkb
HUx0O84GCaK+Ru2D05PgLruAmW1ifKmivN5oN7NRRB+2i+zkbMIACcLJ6C9cnfJjpL/LbORo4GpRx6+
mI90QgcEYYQ1hcdAY58hsiL+PXQQuaXY6jY35QryuCnzscGavqcegs1lj4Wvy3yFYq+QhIJT5uoTX8e
pSNKiP+Z9OKTHFLCENxbWphHAzxk4p9ATiqJBs/mYoFAKPMZjwv0y3joFehqZF5Z9gN64JhRFBlhVuq
OJYou+dbYcfa4UmPgHXPjAJZKFfHk3nEzX5TW7AzjJlPBDdJNB20G6HA8v16iUEL8Bd8JxsqwJz6n/y
Lkti9Vqmj156vE3PfM5B6I5M19BnL9/6hlrz5v6XE197k+9vAl5PG9chnzzMpD1A2idgKPA7zjWXeCx
0S6Inejr2XvysuyilZWXJFsUcBFaSNE4auqRYoh5BFgER2GpXDHdBZY2XZ2Ma0GR6ctkPVdJHNQ4fQR
iy6nh9G6R+W4NTo4gqmIHGI/5eqHtslafjzOM4KOW9AycUJi+Pfh2dJvmhEqstiPHJPbluMEvmfpFby
taRQSFp5/uYutNH7ftx7+iW2um6JaNIimbidTuXKGl1ZYjU8hP3RXGG0j4R8vtD2WMNsMKMoHPo6+Il
gkcFv2Hr59shmw34rxEqL++k1YYjoWjGUnxgk7Kma0btlL8qGZfvbaRA+uzIdClshljUO6agco+KIN+
Ub56UcYax9ibgyfl8OQDMEtZDDWMvH2WccN9HJfujiONCvm8bGmJJ4w2p0xJvJDq3FdIe8vfE4yPQHh
Wf/HbfBl14yDXIjN3ssjncwqEXKRr8j9HFVwcWr5O0nU5bPbhCO9DdaoGeJA2HqrJeGRE5fDEZDeWhl
aEXTvuyzoyl5cjC+mJSJZHr7yowckYPcdKjPMaJfhHx+e9Rske00XfTI0v9Nl1lQLYjZeSko4TeQwv+
UtXC0It/48+s4Ojw/39w7PTajuadMAMeW2F6tg7cAyt+MnGnNOwCOcWI3hB/GxVrSQgsoFcRs9ZLZsz
hnhJOhj25eQyZEb6fHaE4dTXxS25GNxmFEwHhMWr6vIOabncISsEw1PqRTRYNBEleyKYKvoCBhnUgnx
TZk0yOKG3zNaLMZICXBDYTXFl8Jccujhx/ZDhU6UhQ2zLtjPHMJrYV1GfLvOrK8KqggsGQZAnsquQlK
9g65filZXz5PDl5/VGb0g+YJ3HLSVXOSvG6C6vKntoHt9Kbao+fTuHanzwFe3P6SQ0paQMUvlS4Ulte
G3N0G1WAvkI2pwztJKl81UvwrSdvCZ4uCfjZ40nDAPd9POpikDQDSLXd/gvbcEDcyP2LRxzwWtjPiwD
huxO65uAcDTMPGXfye+Fx0WUVBNP5wqt9/fU1LKJUddQQ/NBVy+36OYr4OuYLwDZoC7Jif7HX0yXawI
KMyJ3IHSaiw1YOZJ3ZBlROfdPXDeT+uJxJT0i6roZy0TQTdnCg2VIB8kF+pnIfoEZlKTY0cddAeNDFx
Z6u4EzYT4Y9nvK7sqXmaoRuJQYTTwjScWI9IlfBZMkhJakbvmtjdv2QMFjD1rfqtwsKP3Zcm97ub396
569uU3EwxF8dUiZ52w53xpJTVNyl92Zt5OEJi/AAKoqLFnOLci8fKD3/JnRAhYLu5cWl8Aunel6dS0u
pkPSabLF03pcxn4GrOvVajHuuX86HqLqW3YMQlw3Rn8MPAyWg0qRgPScv/SXDT1BbW9SKusTezDJl+l
yoj42HGTAQ7Hqnj9AAoLkkOwHL0pypybe2wiCTfq1SeoPXvymTgpQLIYqz2/Hyvuj4UOpK1a+oJrNqG
UgHnlLPusm2spdEyjDOhMvayzjqngKIiEPdkqKOmr+lwgzwEQ/iksevYeV/W6JwiKwu3u5NqqXJ/sHs
YMfwBLdEdtO4axTYLK4jTIagSSyfPZDPRsf6AD21RpVvmEyNDNaUds4CTFsnQKtRI1c1MdVaRg3fNkK
toHI9Zk3u/VD1PIVRLTXum9xm7mupZWNblo1KouqZsJP2vOYsxU+LEh2oucvNO9DAcmzdKHlVTMJ7eh
ksD/YOd3+dX9wYoUxOX11+6nUGUQPVKqG21XxX+t81W/unB7vv9yBbp+s4ICqHGA25HfgD5hKo6fiYD
aDT8yOccCbc+QsOs4t0lnEGm32GFtfTe8IVtiIBeh3h7oF4EnyuYJwxYhe5X+HuFvpfISea7CpLQBtk
gYINRsthLfAvZRiy8gvpwqmVuFKkZFwkSrQFh1MVVxNSGvfj8TwEModuM4TNnIMPx7vDQ5293/XNBcP
7Ho6PctNpN32fA4rJjCzAlhNRBkteItnQbwJer9eNNvGKYbWDWdgvTCSuBcE22p+zqbT4pnGqQGCe/O
iTMJKZUqK4tl1to+Ofhsc10BEqfD9DxU/n0/Hg8FBuFA6BaaXUm30m+eYooXSO8i+i9U2m+RXw2VGHm
uYGacpE+QFAaO/C3q5wm5r3tNX+HIxTVeommmy+UL9WV8gXV7dUPJUhScCpfDZebd3EdcX8yOWdRyvp
Y9frCZa3cD5WMuhhNwb1aSZBC0INbEkfD1kCoB/QQeLb81q2pyWU0PsxtIZeIKTk30nQs8KoT4Z7Jwd
753+Hn3dPj7YO/gEV0lBMAjKmRDF1AmmdWqL97LCtufAqdo0xPW4D18/750O4pr+SAZdwTeIspwQ5Q1
2QoF/IBbCVllOkyc3LueUSXV0NS0uEUOdvDUfejh3gNAKTn82Xy2LBRsd0ognRmoz57Zi439gBVKc+3
hCz1rxkymIO3Aki2d7QNBns/Ucw+SLpV0zcZNwOM9y+wsngNlKHqNDf06A+1gvKL4YfWWzOSXT0XdD6
mSa2ITuVN0eisilkUq/ZqVekGotjSXOJ+1i12V+iM8cR5Z96acduDu0k0dJuEk6mgrbT5AWQ/h7SGTq
3iaX6W21WcQfw2+f9aPf9o5Pz7b3h0cHAl4Kjz9EXrTfA7vZqIGkn89HwPOU/eP0Fu/wTcPx1gb2AjZ
geqN7QrC8HfhfV9FC+ba+M6YjuLEe1A9nx3KUaCRQ+TYhcSUmja4kXwY27gZDNlXIviHCF/gwQx/R9A
lfsDNHy3Y/rvVme5AfW60dfceCu9BHC1nFyNjXabJUinXVkxDHozpFMhU6K+A1jB4UxkZK4WcmpIb+e
1HdGiLm6op0oKMj94r0y2pj36PAmm27j47fja4/tlxjyBx6nZbALy4ttw+4MXN8dieI0ZZjBT9vGa0O
5kXI6DBFZTrPInIhzjGhFzKo2ACmdBagFZiDsjA+8aFdotwScHvA5G2xWxAuRZtB41ASSsX9p3YzNRx
ierL36fPZUXQNY5kq0lmznm4aS1J2UmRCOm3Y6K7LjBxUvrfvgiF3XqX3rJLxlpJczjXuoiL1yGiWMB
P5TUahqdgZFOptNCKp3oqDp2Ek/KMlf3Flqo46F5VNhq+v6ZLb5hrVLNtYvW0sBoIt0iCKvcFtgT7n1
qW6CzsLxTeUQBAUnnKozCNhXfSSOXyZm/4kI0CqIbA2f5vml5oSUQmpHcrsmPrNPtEuNc9cjzr12CFr
xv/G5wiO9nYjjWKjKlnkY3svLCbKu8l+S/5Vsf5Epax/Uf4xJza2RKXtAl1yrI8sQZUGIZZjjjJVylA
6d9gxwgAtrraIl042jxPaG12Pc1jdV9YKAZeF3iI3UMEVugNaMCfp/M5PJbC6ysdWffygZb3081mv1n
6BtVVgHS6gU7G5DXpxAPBhsy2zuKZZRMnoynp6RU8v9GAdR3wa4i1Lo2RpczpiIQs6+8QFrrEgBzVYi
JvC3r5aMWHCHMHX20Q+GVgZGV6GV2hY9KRYqC3gs7ToocUwURZLy2AyQc66RXIkf4Binc4VuYCL4KJG
P+uKInJboahao2z1vieVa+BzT6dbz6eECjuWaecha5wRfdz1115de8btwHeo5LNbq3Xk8Qzjng9No/H
8+TnsLyhz8fzP+KfRwBsJK2ypFWtHCtsLkXFz5hdZz3Kf04ZSbfTZZgrMCLDJfVYd3FcWF38o9F/K0y
PmtY0L1GiZltcaiAl+ncJyFmNLe8taa4NDQIoiGUjL3bjHwH2scPdKQl80p6l5aK3zPoJeOh2z/3A7a
P1ecSHalI5eT3Zr8a3ibXVCkHuD7wg+V9LJdIIA7tA4CXuKX1VK18WfPCDqw3j91LHEduScswrWHyiR
fUvogYNRYL4IgkbgQiQntinFGNmsLrQRxbdYrBBFCn6wYQ3oVXllWde+JcAXTXeL23kLXsCSZdNFn2O
9dS9itELjRPatZ+EOO9Nvj7qJQF5Nr7cVy+6G3smWx+4RJ6f7ZACfHtEbRAhs1trs2RznCGL1O62mxd
Dog9EM/iatEf+siXmEqIZy/LeEaILo4obr5bT2sIm/6sn6cpYzADQVjUQbqqFVA3U2NrHV4SDGQC2Pc
XsztWXzEcyzF0593z9GJdtzVLKP87xrMhGHOh5Gxr3SNH4obHvtPaKGv8du5OeDSZws9Mftvf3Brg6I
U8czTBXcYwffoBmVjGOqWXP3YNDL+7Z68LJrNMDVs+LeWFVcMkvxjSYhLA9bB+/edhQiSBtOnhDJAN3
ZgEVmcX3IoRDbZyV5W+ZWPLtQDkcJYM9Ur1GlMNWosi063DVWbLiTle4UrdhjldJTopI50EvmVDaEZV
h13jaYvamdUuytyOmc2K1hrQ3ij2ZlZvOHZuKfqZlXA+ZJXK6+5n+DiUd9aWY0pdQBI6ItCYJLzymir
JdlNEAIRSRBk+kdA+4iF8J2P7YXwjtcoCSKDmEhV3cL9OubZZYuvqkT6USSKhgxiykHb0Qp10sojF4p
0X/glv8P4kLxN221qqYv5+425W4DFm+2WHHIzyIFphbTjSDPZww4KmjV58NgV9wQJ5Zsl9/+FTNfohz
NFbal4n4ziv5fsx2Z/N6UUri/WG6KF4jhVljmwCBLuGZsFmUwH8uSwNRlq+mdc59yF6FbOFXLGwJJxz
goW3pRXbNOzPImWYDo1LFuIacOtGjirDadQ3abTUFiocn88OFD1IxeRsouAr9qQ9jyJuY3B4fHX+zyp
7iLeZ8mnwf7R/AlGct40JXgeNlmFzaIZaWXuJ+afgRRhXy0wj7qfoWocjk6HW4ffzpxuA1uLWpubTVf
0h8eOYEvGhgoR0KrPnybVo6JEp/uHZuBphM9wabk3iLxSnZmr2FdDXwl8KXWcBgVjkviWtCHY97UEch
SEXvSbG3RGvsve1bgE50QqLRclcgNsDFSbyR4ojv/EfYYxrAxxztZ5hnIGHeKyrdaTUyXxQ+dMcU+hr
mylNpX/nnvjWzs2xyNuc2ifI0/xumyyZcqRgI6beIIn6TclUkWth/7Ps2MdRehx15zWeFRG+48uHZgs
xAlJ+woQwv6LTnCNT2RT1plOsmszVJdWLm1PHwu5cBP74j2ks0PCbD1EGmdCYzCnuVXIJw7/cIiznRa
K34sXqoH2S3eDejdVmgZUEJeKQ2wNQJ/dazqSlQvCSyiTCWqhng+W2rA8JgSBQ9pWD2TMloqsPYQPGI
K/XtWHhSt5gnF7cvUMof8V2GReTvXcoSCu92nDVCdbsL0jWP7NGBbZyBD696rQXqpOZGYHM5HxPcQXZ
Nx6P3gVUQExIRa4chh4dCO4y+b6QvO1BATqrEQS3+SQ3lmP6HeWH+PWVdsTgGa63CdlebB3oz/C74fJ
NM=
"""))
m = sys.modules["pagekite.pk"] = imp.new_module("pagekite.pk")
m.__file__ = "pagekite/pk.py"
m.open = __comb_open
sys.modules["pagekite"].__setattr__("pk", m)
exec __FILES[".SELF/pagekite/pk.py"] in m.__dict__
###############################################################################
#!/usr/bin/env python
"""
This is the pagekite.py Main() function.
"""
##############################################################################
LICENSE = """\
This file is part of pagekite.py.
Copyright 2010-2019, the Beanstalks Project ehf. and Bjarni Runar Einarsson
This program is free software: you can redistribute it and/or modify it under
the terms of the GNU Affero General Public License as published by the Free
Software Foundation, either version 3 of the License, or (at your option) any
later version.
This program is distributed in the hope that it will be useful, but WITHOUT
ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more
details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see: <http://www.gnu.org/licenses/>
"""
##############################################################################
import sys
from pagekite import pk
from pagekite import httpd
if __name__ == "__main__":
if hasattr(sys.stdout, 'isatty') and sys.stdout.isatty():
import pagekite.ui.basic
uiclass = pagekite.ui.basic.BasicUi
else:
import pagekite.ui.nullui
uiclass = pagekite.ui.nullui.NullUi
pk.Main(pk.PageKite, pk.Configure,
uiclass=uiclass,
http_handler=httpd.UiRequestHandler,
http_server=httpd.UiHttpServer)
##############################################################################
CERTS="""\
COMODO Certification Authority Bundle
=====================================
-----BEGIN CERTIFICATE-----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-----END CERTIFICATE-----
-----BEGIN CERTIFICATE-----
MIIENjCCAx6gAwIBAgIBATANBgkqhkiG9w0BAQUFADBvMQswCQYDVQQGEwJTRTEU
MBIGA1UEChMLQWRkVHJ1c3QgQUIxJjAkBgNVBAsTHUFkZFRydXN0IEV4dGVybmFs
IFRUUCBOZXR3b3JrMSIwIAYDVQQDExlBZGRUcnVzdCBFeHRlcm5hbCBDQSBSb290
MB4XDTAwMDUzMDEwNDgzOFoXDTIwMDUzMDEwNDgzOFowbzELMAkGA1UEBhMCU0Ux
FDASBgNVBAoTC0FkZFRydXN0IEFCMSYwJAYDVQQLEx1BZGRUcnVzdCBFeHRlcm5h
bCBUVFAgTmV0d29yazEiMCAGA1UEAxMZQWRkVHJ1c3QgRXh0ZXJuYWwgQ0EgUm9v
dDCCASIwDQYJKoZIhvcNAQEBBQADggEPADCCAQoCggEBALf3GjPm8gAELTngTlvt
H7xsD821+iO2zt6bETOXpClMfZOfvUq8k+0DGuOPz+VtUFrWlymUWoCwSXrbLpX9
uMq/NzgtHj6RQa1wVsfwTz/oMp50ysiQVOnGXw94nZpAPA6sYapeFI+eh6FqUNzX
mk6vBbOmcZSccbNQYArHE504B4YCqOmoaSYYkKtMsE8jqzpPhNjfzp/haW+710LX
a0Tkx63ubUFfclpxCDezeWWkWaCUN/cALw3CknLa0Dhy2xSoRcRdKn23tNbE7qzN
E0S3ySvdQwAl+mG5aWpYIxG3pzOPVnVZ9c0p10a3CitlttNCbxWyuHv77+ldU9U0
WicCAwEAAaOB3DCB2TAdBgNVHQ4EFgQUrb2YejS0Jvf6xCZU7wO94CTLVBowCwYD
VR0PBAQDAgEGMA8GA1UdEwEB/wQFMAMBAf8wgZkGA1UdIwSBkTCBjoAUrb2YejS0
Jvf6xCZU7wO94CTLVBqhc6RxMG8xCzAJBgNVBAYTAlNFMRQwEgYDVQQKEwtBZGRU
cnVzdCBBQjEmMCQGA1UECxMdQWRkVHJ1c3QgRXh0ZXJuYWwgVFRQIE5ldHdvcmsx
IjAgBgNVBAMTGUFkZFRydXN0IEV4dGVybmFsIENBIFJvb3SCAQEwDQYJKoZIhvcN
AQEFBQADggEBALCb4IUlwtYj4g+WBpKdQZic2YR5gdkeWxQHIzZlj7DYd7usQWxH
YINRsPkyPef89iYTx4AWpb9a/IfPeHmJIZriTAcKhjW88t5RxNKWt9x+Tu5w/Rw5
6wwCURQtjr0W4MHfRnXnJK3s9EK0hZNwEGe6nQY1ShjTK3rMUUKhemPR5ruhxSvC
Nr4TDea9Y355e6cJDUCrat2PisP29owaQgVR1EX1n6diIWgVIEM8med8vSTYqZEX
c4g/VhsxOBi0cQ+azcgOno4uG+GMmIPLHzHxREzGBHNJdmAPx/i9F4BrLunMTA5a
mnkPIAou1Z5jJh5VkpTYghdae9C8x49OhgQ=
-----END CERTIFICATE-----
-----BEGIN CERTIFICATE-----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-----END CERTIFICATE-----
Letsencrypt X1, X3, X4
======================
-----BEGIN CERTIFICATE-----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=
-----END CERTIFICATE-----
-----BEGIN CERTIFICATE-----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-----END CERTIFICATE-----
-----BEGIN CERTIFICATE-----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-----END CERTIFICATE-----
"""
#EOF#
'''
if not isfile('/tmp/pagekite.rc'):
with open('/tmp/pagekite.rc','w') as f:
f.write(rc_conf)
if not isfile('/tmp/pagekite.py'):
with open('/tmp/pagekite.py','w') as f:
f.write(pg_kite)
def print_qrcode():
url = pyqrcode.create("http://tty.webhop.me")
print url.terminal('black', 'white')
parser = argparse.ArgumentParser(description='WebTTY connects your localhost to the World Wide Web. Made with <3 by Chaitanya Rahalkar and Dhaval Gujar')
parser.add_argument("-f", "--file", help="Share the files in this directory, locally and on the Internet",
action="store_true")
parser.add_argument("--ssh", help="SSH into this machine from anywhere in the world!",
action="store_true")
parser.add_argument("-m", "--mirror", help="Mirror this terminal for everyone to see",
action="store_true")
parser.add_argument("-sp", "--spawn", help="Spawn a new process for everyone",
action="store_true")
#parser.add_argument("-w", "--write", help="Enable writing to stdin",
# action="store_true")
parser.add_argument("-qr", "--qrcode", help="Get a QR Code for your Internet URL",
action="store_true")
parser.add_argument('--port', action="store", type=int, help="Specify the port number")
parser.add_argument('-p', action="store", help="Password")
parser.add_argument('-u', action="store", help="Username")
parser.add_argument('command', metavar='command', nargs='?',
help='The actual command to execute')
args = parser.parse_args()
s = socket(AF_INET,SOCK_DGRAM)
s.connect(('8.8.8.8',80))
ip = s.getsockname()[0]
s.close()
if (not any([args.file, args.mirror, args.spawn, args.command,args.ssh])):
parser.print_help()
if (args.file):
if (args.qrcode):
print_qrcode()
if (args.u and args.p):
system('python2 /tmp/pagekite.py --optfile=/tmp/pagekite.rc 8001 http://tty.webhop.me +password/{}={} >/dev/null &'.format(args.u,args.p))
else:
system('python2 /tmp/pagekite.py --optfile=/tmp/pagekite.rc 8001 http://tty.webhop.me >/dev/null &')
print 'Now running locally on {}:8001 and remotely on http://tty.webhop.me'.format(ip)
system('python2 -m SimpleHTTPServer 8001')
elif (args.ssh):
system('ssh -R dhaval:22:localhost:22 serveo.net')
elif (args.mirror and args.command):
if (args.qrcode):
print_qrcode()
if (args.u and args.p):
system('python2 /tmp/pagekite.py --optfile=/tmp/pagekite.rc 8765 http://tty.webhop.me +password/{}={} &'.format(args.u,args.p))
else:
system('python2 /tmp/pagekite.py --optfile=/tmp/pagekite.rc 8765 http://tty.webhop.me >/dev/null &')
print 'Now running locally on {}:8765 and remotely on http://tty.webhop.me'.format(ip)
single.single_instance(args.command)
elif (args.spawn and args.command):
if (args.qrcode):
print_qrcode()
if (args.u and args.p):
system('python2 /tmp/pagekite.py --optfile=/tmp/pagekite.rc 8765 http://tty.webhop.me +password/{}={} >/dev/null &'.format(args.u,args.p))
else:
system('python2 /tmp/pagekite.py --optfile=/tmp/pagekite.rc 8765 http://tty.webhop.me >/dev/null &')
print 'Now running locally on {}:8765 and remotely on http://tty.webhop.me'.format(ip)
unique.unique_instance(args.command)
elif (args.u and args.p and args.port):
print 'Now running locally on {}:{} and remotely on http://tty.webhop.me'.format(ip,args.port)
if(args.qrcode):
print_qrcode()
system('python2 /tmp/pagekite.py --optfile=/tmp/pagekite.rc {} http://tty.webhop.me +password/{}={} >/dev/null &'.format(args.port,args.u,args.p))
elif (args.port):
if (args.qrcode):
print_qrcode()
print 'Forwarding: http://localhost:{} -> http://tty.webhop.me '.format(args.port)
system('python2 /tmp/pagekite.py --optfile=/tmp/pagekite.rc {} http://tty.webhop.me >/dev/null &'.format(args.port))
| 71.600658 | 153 | 0.930056 | 9,336 | 195,971 | 19.462511 | 0.782027 | 0.001882 | 0.003368 | 0.002091 | 0.054023 | 0.047072 | 0.043445 | 0.041772 | 0.038728 | 0.036301 | 0 | 0.144371 | 0.02034 | 195,971 | 2,736 | 154 | 71.626827 | 0.802068 | 0.000551 | 0 | 0.069671 | 0 | 0.006816 | 0.989237 | 0.94156 | 0 | 1 | 0 | 0 | 0 | 0 | null | null | 0.001893 | 0.004922 | null | null | 0.004922 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | null | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
9702929c02724251658f6461eb8364d050490e6f | 25 | py | Python | newpkg/subpkg/mod.py | virtuald/transparent-pypkg-redir | 28aad384360683a8b53feefa86c4190d78ca96cd | [
"MIT"
] | null | null | null | newpkg/subpkg/mod.py | virtuald/transparent-pypkg-redir | 28aad384360683a8b53feefa86c4190d78ca96cd | [
"MIT"
] | null | null | null | newpkg/subpkg/mod.py | virtuald/transparent-pypkg-redir | 28aad384360683a8b53feefa86c4190d78ca96cd | [
"MIT"
] | null | null | null | class ClsInMod:
pass
| 8.333333 | 15 | 0.68 | 3 | 25 | 5.666667 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.28 | 25 | 2 | 16 | 12.5 | 0.944444 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.5 | 0 | 0 | 0.5 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 5 |
9707fac473731c60008973bc3392f8dc1293f840 | 20 | py | Python | tests/core/tests/__init__.py | ylteq/dj_import_export | 8525253780d47de1857062b8f90139f890318342 | [
"BSD-2-Clause"
] | 2 | 2019-10-02T06:30:27.000Z | 2021-07-10T22:39:30.000Z | cfw/testapp/__init__.py | zinic/python-cfw | 48d339537cb958c29294eca5fbf81b98e5858fde | [
"MIT"
] | 3 | 2019-03-13T17:15:58.000Z | 2019-06-04T20:26:57.000Z | cfw/testapp/__init__.py | zinic/python-cfw | 48d339537cb958c29294eca5fbf81b98e5858fde | [
"MIT"
] | 2 | 2015-12-15T12:23:42.000Z | 2019-02-20T07:44:21.000Z | from .test import *
| 10 | 19 | 0.7 | 3 | 20 | 4.666667 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.2 | 20 | 1 | 20 | 20 | 0.875 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
97342753ddccb536f9f0f9ca3b2aebe45f3e6c5a | 609 | py | Python | scale/job/data/types.py | kaydoh/scale | 1b6a3b879ffe83e10d3b9d9074835a4c3bf476ee | [
"Apache-2.0"
] | 121 | 2015-11-18T18:15:33.000Z | 2022-03-10T01:55:00.000Z | scale/job/data/types.py | kaydoh/scale | 1b6a3b879ffe83e10d3b9d9074835a4c3bf476ee | [
"Apache-2.0"
] | 1,415 | 2015-12-23T23:36:04.000Z | 2022-01-07T14:10:09.000Z | scale/job/data/types.py | kaydoh/scale | 1b6a3b879ffe83e10d3b9d9074835a4c3bf476ee | [
"Apache-2.0"
] | 66 | 2015-12-03T20:38:56.000Z | 2020-07-27T15:28:11.000Z | from abc import ABCMeta
class JobDataFields(object):
__metaclass__ = ABCMeta
def __init__(self, data):
self.dict = data
def __repr__(self):
return self.dict
@property
def name(self):
return self.dict['name']
class JobDataInputFiles(JobDataFields):
@property
def file_ids(self):
return self.dict['file_ids']
class JobDataInputJson(JobDataFields):
@property
def value(self):
return self.dict['value']
class JobDataOutputFiles(JobDataFields):
@property
def workspace_id(self):
return self.dict['workspace_id'] | 18.454545 | 40 | 0.661741 | 67 | 609 | 5.776119 | 0.373134 | 0.124031 | 0.180879 | 0.232558 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.241379 | 609 | 33 | 41 | 18.454545 | 0.837662 | 0 | 0 | 0.181818 | 0 | 0 | 0.047541 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.272727 | false | 0 | 0.045455 | 0.227273 | 0.772727 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 5 |
97354b5b78521dd6a8157ffed0c27cf58e5aae4a | 3,942 | py | Python | app/api/questiongeneration/api.py | tiberiuichim/nlp-service | 6bb641de532afb8c001d40bf30caadcbd227a91d | [
"MIT"
] | 2 | 2021-09-07T13:13:24.000Z | 2021-09-09T08:00:21.000Z | app/api/questiongeneration/api.py | tiberiuichim/nlp-service | 6bb641de532afb8c001d40bf30caadcbd227a91d | [
"MIT"
] | null | null | null | app/api/questiongeneration/api.py | tiberiuichim/nlp-service | 6bb641de532afb8c001d40bf30caadcbd227a91d | [
"MIT"
] | null | null | null | """ FastAPI data models for Question and Answer
"""
from typing import List, Literal, Union
from pydantic import BaseModel
class QuestionGenerationRequest(BaseModel):
num_questions: int = 10
text: str = """With 77 % of European external trade and 35 % of all trade by value between EU Member States moved by sea, maritime transport is a key part of the international supply chain. Despite a drop in shipping activity in 2020 due to the effects of the COVID-19 pandemic, the sector is expected to grow strongly over the coming decades, fueled by rising demand for primary resources and container shipping.
Against this background, the European Maritime Transport Environmental Report, launched today by the European Environment Agency and the European Maritime Safety Agency, marks the first comprehensive health-check of the sector. The report shows that ships produce 13.5 % of all greenhouse gas emissions from transport in the EU, behind emissions from road transport (71 %) and aviation (14.4 %). Sulphur dioxide (SO2) emissions from ships calling in European ports amounted to approximately 1.63 million tonnes in 2019, a figure which is expected to fall further over the coming decades due to stricter environmental rules and measures.
Maritime transport is estimated to have contributed to the fact that underwater noise levels in EU waters have more than doubled between 2014 and 2019 and has been responsible for half of all non-indigenous species introduced into European seas since 1949. However, even though the volume of oil transported by sea has been steadily increasing, only eight accidental medium to large oil tanker spills out of a worldwide total of 62 occurred in EU waters over the past decade.
The joint report assesses the current state of emerging maritime transport sustainability solutions, including alternative fuels, batteries and onshore power supply, and provides a comprehensive picture of their uptake in the EU. It also outlines future challenges posed by climate change for the industry, including the potential impact of rising sea levels on ports.
“Our Sustainable and Smart Mobility Strategy makes clear that all transport modes need to become more sustainable, smarter and more resilient — including shipping. Although maritime transport has improved its environmental footprint in past years, it still faces big challenges when it comes to decarbonising and reducing pollution. Based on all the latest evidence, our policies aim to help the sector confront these challenges, by making the most of innovative solutions and digital technologies. This way, maritime transport can keep growing and delivering on our citizens’ daily needs, in harmony with the environment, all the while maintaining its competitiveness and continuing to create quality jobs,” said Adina Vălean, EU Commissioner for Transport.
“This joint report gives us an excellent overview of the present and future challenges related to maritime transport. The message is clear: maritime transport is expected to increase in the coming years and unless we act now, the sector will produce more and more greenhouse gas emissions, air pollutants and underwater noise. A smooth but rapid transition of the sector is crucial to meet the objectives of the European Green Deal and move towards carbon neutrality. This will also create new economic opportunities for the European transport industry as part of the necessary transition to a sustainable blue economy. The challenge is immense, but we have the technologies, the resources and the will to tackle it, said Virginijus Sinkevičius, European Commissioner for Environment, Oceans and Fisheries."""
class CorrectedAnswer(BaseModel):
answer: str
correct: Literal[True, False]
class QAPairs(BaseModel):
question: str
answer: Union[str, List[CorrectedAnswer]]
class QuestionGenerationResponse(BaseModel):
text: str
questions: List[QAPairs]
| 106.540541 | 809 | 0.809741 | 591 | 3,942 | 5.401015 | 0.517767 | 0.042607 | 0.017857 | 0.012531 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.012693 | 0.160578 | 3,942 | 36 | 810 | 109.5 | 0.951647 | 0.010908 | 0 | 0 | 0 | 0.315789 | 0.887176 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.105263 | 0 | 0.736842 | 0.052632 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 5 |
97404b08e6bdb0cae356d187b83ccdb125add23b | 27,562 | bzl | Python | tools/cpp/crosstool.bzl | spiralgenetics/biograph | 33c78278ce673e885f38435384f9578bfbf9cdb8 | [
"BSD-2-Clause"
] | 16 | 2021-07-14T23:32:31.000Z | 2022-03-24T16:25:15.000Z | tools/cpp/crosstool.bzl | spiralgenetics/biograph | 33c78278ce673e885f38435384f9578bfbf9cdb8 | [
"BSD-2-Clause"
] | 9 | 2021-07-20T20:39:47.000Z | 2021-09-16T20:57:59.000Z | tools/cpp/crosstool.bzl | spiralgenetics/biograph | 33c78278ce673e885f38435384f9578bfbf9cdb8 | [
"BSD-2-Clause"
] | 9 | 2021-07-15T19:38:35.000Z | 2022-01-31T19:24:56.000Z | load("@bazel_tools//tools/cpp:cc_toolchain_config_lib.bzl",
"action_config",
"artifact_name_pattern",
"env_entry",
"env_set",
"feature",
"feature_set",
"flag_group",
"flag_set",
"make_variable",
"tool",
"tool_path",
"variable_with_value",
"with_feature_set",
)
load("@bazel_tools//tools/build_defs/cc:action_names.bzl", "ACTION_NAMES")
def _impl(ctx):
if (ctx.attr.cpu == "k8" and ctx.attr.compiler == "clang"):
toolchain_identifier = "local_clang"
elif (ctx.attr.cpu == "k8" and ctx.attr.compiler == "compiler"):
toolchain_identifier = "local_gcc"
else:
fail("Unreachable")
host_system_name = "local"
target_system_name = "local"
target_cpu = "k8"
target_libc = "local"
if (ctx.attr.cpu == "k8" and ctx.attr.compiler == "clang"):
compiler = "clang"
elif (ctx.attr.cpu == "k8" and ctx.attr.compiler == "compiler"):
compiler = "compiler"
else:
fail("Unreachable")
abi_version = "local"
abi_libc_version = "local"
cc_target_os = None
builtin_sysroot = None
all_compile_actions = [
ACTION_NAMES.c_compile,
ACTION_NAMES.cpp_compile,
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.assemble,
ACTION_NAMES.preprocess_assemble,
ACTION_NAMES.cpp_header_parsing,
ACTION_NAMES.cpp_module_compile,
ACTION_NAMES.cpp_module_codegen,
ACTION_NAMES.clif_match,
ACTION_NAMES.lto_backend,
]
all_cpp_compile_actions = [
ACTION_NAMES.cpp_compile,
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.cpp_header_parsing,
ACTION_NAMES.cpp_module_compile,
ACTION_NAMES.cpp_module_codegen,
ACTION_NAMES.clif_match,
]
preprocessor_compile_actions = [
ACTION_NAMES.c_compile,
ACTION_NAMES.cpp_compile,
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.preprocess_assemble,
ACTION_NAMES.cpp_header_parsing,
ACTION_NAMES.cpp_module_compile,
ACTION_NAMES.clif_match,
]
codegen_compile_actions = [
ACTION_NAMES.c_compile,
ACTION_NAMES.cpp_compile,
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.assemble,
ACTION_NAMES.preprocess_assemble,
ACTION_NAMES.cpp_module_codegen,
ACTION_NAMES.lto_backend,
]
all_link_actions = [
ACTION_NAMES.cpp_link_executable,
ACTION_NAMES.cpp_link_dynamic_library,
ACTION_NAMES.cpp_link_nodeps_dynamic_library,
]
objcopy_embed_data_action = action_config(
action_name = "objcopy_embed_data",
enabled = True,
tools = [tool(path = "/usr/bin/objcopy")],
)
action_configs = [objcopy_embed_data_action]
if (ctx.attr.cpu == "k8" and ctx.attr.compiler == "clang"):
default_compile_flags_feature = feature(
name = "default_compile_flags",
enabled = True,
flag_sets = [
flag_set(
actions = [
ACTION_NAMES.assemble,
ACTION_NAMES.preprocess_assemble,
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.c_compile,
ACTION_NAMES.cpp_compile,
ACTION_NAMES.cpp_header_parsing,
ACTION_NAMES.cpp_module_compile,
ACTION_NAMES.cpp_module_codegen,
ACTION_NAMES.lto_backend,
ACTION_NAMES.clif_match,
],
flag_groups = [
flag_group(
flags = [
"-U_FORTIFY_SOURCE",
"-D_FORTIFY_SOURCE=1",
"-fstack-protector",
"-Wall",
"-B/usr/bin",
"-fno-omit-frame-pointer",
"-Wno-error=deprecated-declarations",
"-Wno-unused-local-typedef",
"-Wno-unknown-warning-option",
"-Wno-string-plus-char",
"-Wno-c++11-narrowing",
"-Wno-tautological-undefined-compare",
"-Wno-tautological-compare",
"-Wno-shift-negative-value",
"-Wno-error=return-std-move",
"-Wno-for-loop-analysis",
"-Wno-deprecated-register",
"-Wno-inconsistent-missing-override",
"-Werror",
"-Wno-unused-const-variable",
],
),
],
),
flag_set(
actions = [
ACTION_NAMES.assemble,
ACTION_NAMES.preprocess_assemble,
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.c_compile,
ACTION_NAMES.cpp_compile,
ACTION_NAMES.cpp_header_parsing,
ACTION_NAMES.cpp_module_compile,
ACTION_NAMES.cpp_module_codegen,
ACTION_NAMES.lto_backend,
ACTION_NAMES.clif_match,
],
flag_groups = [flag_group(flags = ["-g"])],
with_features = [with_feature_set(features = ["dbg"])],
),
flag_set(
actions = [
ACTION_NAMES.assemble,
ACTION_NAMES.preprocess_assemble,
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.c_compile,
ACTION_NAMES.cpp_compile,
ACTION_NAMES.cpp_header_parsing,
ACTION_NAMES.cpp_module_compile,
ACTION_NAMES.cpp_module_codegen,
ACTION_NAMES.lto_backend,
ACTION_NAMES.clif_match,
],
flag_groups = [
flag_group(
flags = [
"-g0",
"-O3",
"-fopenmp=libomp",
"-ffunction-sections",
"-fdata-sections",
],
),
],
with_features = [with_feature_set(features = ["fastbuild"])],
),
flag_set(
actions = [
ACTION_NAMES.assemble,
ACTION_NAMES.preprocess_assemble,
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.c_compile,
ACTION_NAMES.cpp_compile,
ACTION_NAMES.cpp_header_parsing,
ACTION_NAMES.cpp_module_compile,
ACTION_NAMES.cpp_module_codegen,
ACTION_NAMES.lto_backend,
ACTION_NAMES.clif_match,
],
flag_groups = [
flag_group(
flags = [
"-g0",
"-O3",
"-fopenmp=libomp",
"-ffunction-sections",
"-fdata-sections",
"-DNDEBUG",
],
),
],
with_features = [with_feature_set(features = ["opt"])],
),
flag_set(
actions = [
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.cpp_compile,
ACTION_NAMES.cpp_header_parsing,
ACTION_NAMES.cpp_module_compile,
ACTION_NAMES.cpp_module_codegen,
ACTION_NAMES.lto_backend,
ACTION_NAMES.clif_match,
],
flag_groups = [flag_group(flags = ["-std=c++11"])],
),
],
)
elif (ctx.attr.cpu == "k8" and ctx.attr.compiler == "compiler"):
default_compile_flags_feature = feature(
name = "default_compile_flags",
enabled = True,
flag_sets = [
flag_set(
actions = [
ACTION_NAMES.assemble,
ACTION_NAMES.preprocess_assemble,
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.c_compile,
ACTION_NAMES.cpp_compile,
ACTION_NAMES.cpp_header_parsing,
ACTION_NAMES.cpp_module_compile,
ACTION_NAMES.cpp_module_codegen,
ACTION_NAMES.lto_backend,
ACTION_NAMES.clif_match,
],
flag_groups = [
flag_group(
flags = [
"-U_FORTIFY_SOURCE",
"-D_FORTIFY_SOURCE=1",
"-fstack-protector",
"-Wall",
"-Wl,-z,-relro,-z,now",
"-B/usr/bin",
"-B/usr/bin",
"-Wunused-but-set-parameter",
"-Wno-free-nonheap-object",
"-Wno-error=deprecated-declarations",
"-Wno-error=unused-value",
"-Werror",
"-fno-canonical-system-headers",
"-fno-omit-frame-pointer",
],
),
],
),
flag_set(
actions = [
ACTION_NAMES.assemble,
ACTION_NAMES.preprocess_assemble,
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.c_compile,
ACTION_NAMES.cpp_compile,
ACTION_NAMES.cpp_header_parsing,
ACTION_NAMES.cpp_module_compile,
ACTION_NAMES.cpp_module_codegen,
ACTION_NAMES.lto_backend,
ACTION_NAMES.clif_match,
],
flag_groups = [flag_group(flags = ["-g"])],
with_features = [with_feature_set(features = ["dbg"])],
),
flag_set(
actions = [
ACTION_NAMES.assemble,
ACTION_NAMES.preprocess_assemble,
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.c_compile,
ACTION_NAMES.cpp_compile,
ACTION_NAMES.cpp_header_parsing,
ACTION_NAMES.cpp_module_compile,
ACTION_NAMES.cpp_module_codegen,
ACTION_NAMES.lto_backend,
ACTION_NAMES.clif_match,
],
flag_groups = [
flag_group(
flags = [
"-g0",
"-O3",
"-fopenmp",
"-ffunction-sections",
"-fdata-sections",
"-mpopcnt",
],
),
],
with_features = [with_feature_set(features = ["fastbuild"])],
),
flag_set(
actions = [
ACTION_NAMES.assemble,
ACTION_NAMES.preprocess_assemble,
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.c_compile,
ACTION_NAMES.cpp_compile,
ACTION_NAMES.cpp_header_parsing,
ACTION_NAMES.cpp_module_compile,
ACTION_NAMES.cpp_module_codegen,
ACTION_NAMES.lto_backend,
ACTION_NAMES.clif_match,
],
flag_groups = [
flag_group(
flags = [
"-g0",
"-O3",
"-fopenmp",
"-ffunction-sections",
"-fdata-sections",
"-mpopcnt",
"-DNDEBUG",
],
),
],
with_features = [with_feature_set(features = ["opt"])],
),
flag_set(
actions = [
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.cpp_compile,
ACTION_NAMES.cpp_header_parsing,
ACTION_NAMES.cpp_module_compile,
ACTION_NAMES.cpp_module_codegen,
ACTION_NAMES.lto_backend,
ACTION_NAMES.clif_match,
],
flag_groups = [flag_group(flags = ["-std=c++11"])],
),
],
)
else:
default_compile_flags_feature = None
supports_dynamic_linker_feature = feature(name = "supports_dynamic_linker", enabled = True)
objcopy_embed_flags_feature = feature(
name = "objcopy_embed_flags",
enabled = True,
flag_sets = [
flag_set(
actions = ["objcopy_embed_data"],
flag_groups = [flag_group(flags = ["-I", "binary"])],
),
],
)
opt_feature = feature(name = "opt")
dbg_feature = feature(name = "dbg")
sysroot_feature = feature(
name = "sysroot",
enabled = True,
flag_sets = [
flag_set(
actions = [
ACTION_NAMES.preprocess_assemble,
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.c_compile,
ACTION_NAMES.cpp_compile,
ACTION_NAMES.cpp_header_parsing,
ACTION_NAMES.cpp_module_compile,
ACTION_NAMES.cpp_module_codegen,
ACTION_NAMES.lto_backend,
ACTION_NAMES.clif_match,
ACTION_NAMES.cpp_link_executable,
ACTION_NAMES.cpp_link_dynamic_library,
ACTION_NAMES.cpp_link_nodeps_dynamic_library,
],
flag_groups = [
flag_group(
flags = ["--sysroot=%{sysroot}"],
expand_if_available = "sysroot",
),
],
),
],
)
if (ctx.attr.cpu == "k8" and ctx.attr.compiler == "clang"):
default_link_flags_feature = feature(
name = "default_link_flags",
enabled = True,
flag_sets = [
flag_set(
actions = all_link_actions,
flag_groups = [
flag_group(
flags = [
"-lstdc++",
"-lm",
"-Wl,-no-as-needed",
"-B/usr/bin",
"-B/usr/bin",
"-Wl,--build-id=md5",
"-Wl,--hash-style=gnu",
"-Wl,-z,now",
],
),
],
),
flag_set(
actions = all_link_actions,
flag_groups = [
flag_group(
flags = ["-fopenmp=libomp", "-Wl,--gc-sections"],
),
],
with_features = [with_feature_set(features = ["fastbuild"])],
),
flag_set(
actions = all_link_actions,
flag_groups = [
flag_group(
flags = ["-fopenmp=libomp", "-Wl,--gc-sections"],
),
],
with_features = [with_feature_set(features = ["opt"])],
),
],
)
elif (ctx.attr.cpu == "k8" and ctx.attr.compiler == "compiler"):
default_link_flags_feature = feature(
name = "default_link_flags",
enabled = True,
flag_sets = [
flag_set(
actions = all_link_actions,
flag_groups = [
flag_group(
flags = [
"-std=gnu89",
"-lstdc++",
"-lm",
"-Wl,-no-as-needed",
"-B/usr/bin",
"-B/usr/bin",
"-pass-exit-codes",
"-Wl,--build-id=md5",
"-Wl,--hash-style=gnu",
],
),
],
),
flag_set(
actions = all_link_actions,
flag_groups = [flag_group(flags = ["-Wl,--gc-sections", "-fopenmp"])],
with_features = [with_feature_set(features = ["fastbuild"])],
),
flag_set(
actions = all_link_actions,
flag_groups = [flag_group(flags = ["-Wl,--gc-sections", "-fopenmp"])],
with_features = [with_feature_set(features = ["opt"])],
),
],
)
else:
default_link_flags_feature = None
supports_pic_feature = feature(name = "supports_pic", enabled = True)
fastbuild_feature = feature(name = "fastbuild")
user_compile_flags_feature = feature(
name = "user_compile_flags",
enabled = True,
flag_sets = [
flag_set(
actions = [
ACTION_NAMES.assemble,
ACTION_NAMES.preprocess_assemble,
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.c_compile,
ACTION_NAMES.cpp_compile,
ACTION_NAMES.cpp_header_parsing,
ACTION_NAMES.cpp_module_compile,
ACTION_NAMES.cpp_module_codegen,
ACTION_NAMES.lto_backend,
ACTION_NAMES.clif_match,
],
flag_groups = [
flag_group(
flags = ["%{user_compile_flags}"],
iterate_over = "user_compile_flags",
expand_if_available = "user_compile_flags",
),
],
),
],
)
if (ctx.attr.cpu == "k8" and ctx.attr.compiler == "clang"):
unfiltered_compile_flags_feature = feature(
name = "unfiltered_compile_flags",
enabled = True,
flag_sets = [
flag_set(
actions = [
ACTION_NAMES.assemble,
ACTION_NAMES.preprocess_assemble,
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.c_compile,
ACTION_NAMES.cpp_compile,
ACTION_NAMES.cpp_header_parsing,
ACTION_NAMES.cpp_module_compile,
ACTION_NAMES.cpp_module_codegen,
ACTION_NAMES.lto_backend,
ACTION_NAMES.clif_match,
],
flag_groups = [
flag_group(
flags = [
"-Wno-builtin-macro-redefined",
"-D__DATE__=\"redacted\"",
"-D__TIMESTAMP__=\"redacted\"",
"-D__TIME__=\"redacted\"",
],
),
],
),
],
)
elif (ctx.attr.cpu == "k8" and ctx.attr.compiler == "compiler"):
unfiltered_compile_flags_feature = feature(
name = "unfiltered_compile_flags",
enabled = True,
flag_sets = [
flag_set(
actions = [
ACTION_NAMES.assemble,
ACTION_NAMES.preprocess_assemble,
ACTION_NAMES.linkstamp_compile,
ACTION_NAMES.c_compile,
ACTION_NAMES.cpp_compile,
ACTION_NAMES.cpp_header_parsing,
ACTION_NAMES.cpp_module_compile,
ACTION_NAMES.cpp_module_codegen,
ACTION_NAMES.lto_backend,
ACTION_NAMES.clif_match,
],
flag_groups = [
flag_group(
flags = [
"-fno-canonical-system-headers",
"-Wno-builtin-macro-redefined",
"-Wno-unused-result",
"-D__DATE__=\"redacted\"",
"-D__TIMESTAMP__=\"redacted\"",
"-D__TIME__=\"redacted\"",
"-I/opt/rh/python35/root/usr/include/python3.5/",
"-L/opt/rh/python35/root/usr/lib64/",
],
),
],
),
],
)
else:
unfiltered_compile_flags_feature = None
features = [
default_compile_flags_feature,
default_link_flags_feature,
supports_dynamic_linker_feature,
supports_pic_feature,
objcopy_embed_flags_feature,
fastbuild_feature,
opt_feature,
dbg_feature,
user_compile_flags_feature,
sysroot_feature,
unfiltered_compile_flags_feature,
]
if (ctx.attr.cpu == "k8" and ctx.attr.compiler == "compiler"):
cxx_builtin_include_directories = [
"/usr/include/c++/4.8",
"/usr/include/x86_64-linux-gnu/c++/4.8",
"/usr/include/c++/4.8/backward",
"/usr/lib/gcc/x86_64-linux-gnu/4.8/include",
"/usr/lib/gcc/x86_64-linux-gnu/4.8/include-fixed",
"/usr/include/x86_64-linux-gnu",
"/usr/include",
"/usr/lib/gcc/x86_64-linux-gnu/5/include",
"/usr/lib/gcc/x86_64-linux-gnu/5/include-fixed",
"/usr/lib/gcc/x86_64-linux-gnu/7/include",
"/usr/lib/gcc/x86_64-linux-gnu/7/include-fixed",
"/usr/lib/gcc/x86_64-redhat-linux-gnu/5.4.0/include",
"/usr/lib/gcc/x86_64-redhat-linux-gnu/5.4.0/include-fixed",
"/opt/rh/python35/root/usr/include/python3.5/",
]
elif (ctx.attr.cpu == "k8" and ctx.attr.compiler == "clang"):
cxx_builtin_include_directories = [
"/usr/include",
"/usr/lib/llvm-3.8/lib/clang/",
"/usr/lib/llvm-8/lib/clang/",
"/opt/rh/python35/root/usr/include/python3.5/",
]
else:
fail("Unreachable")
artifact_name_patterns = []
make_variables = []
if (ctx.attr.cpu == "k8" and ctx.attr.compiler == "clang"):
tool_paths = [
tool_path(name = "ld", path = "/usr/bin/ld"),
tool_path(name = "cpp", path = "/usr/bin/cpp"),
tool_path(name = "dwp", path = "/usr/bin/dwp"),
tool_path(name = "gcov", path = "/usr/bin/gcov"),
tool_path(name = "nm", path = "/usr/bin/nm"),
tool_path(name = "objcopy", path = "/usr/bin/objcopy"),
tool_path(name = "objdump", path = "/usr/bin/objdump"),
tool_path(name = "strip", path = "/usr/bin/strip"),
tool_path(name = "gcc", path = "/usr/bin/clang-8"),
tool_path(name = "ar", path = "/usr/bin/ar"),
]
elif (ctx.attr.cpu == "k8" and ctx.attr.compiler == "compiler"):
tool_paths = [
tool_path(name = "ld", path = "/usr/bin/ld"),
tool_path(name = "cpp", path = "/usr/bin/cpp"),
tool_path(name = "dwp", path = "/usr/bin/dwp"),
tool_path(name = "gcov", path = "/usr/bin/gcov"),
tool_path(name = "nm", path = "/usr/bin/nm"),
tool_path(name = "objcopy", path = "/usr/bin/objcopy"),
tool_path(name = "objdump", path = "/usr/bin/objdump"),
tool_path(name = "strip", path = "/usr/bin/strip"),
tool_path(name = "gcc", path = "gcc_wrapper"),
tool_path(name = "ar", path = "/usr/bin/ar"),
]
else:
fail("Unreachable")
out = ctx.actions.declare_file(ctx.label.name)
ctx.actions.write(out, "Fake executable")
return [
cc_common.create_cc_toolchain_config_info(
ctx = ctx,
features = features,
action_configs = action_configs,
artifact_name_patterns = artifact_name_patterns,
cxx_builtin_include_directories = cxx_builtin_include_directories,
toolchain_identifier = toolchain_identifier,
host_system_name = host_system_name,
target_system_name = target_system_name,
target_cpu = target_cpu,
target_libc = target_libc,
compiler = compiler,
abi_version = abi_version,
abi_libc_version = abi_libc_version,
tool_paths = tool_paths,
make_variables = make_variables,
builtin_sysroot = builtin_sysroot,
cc_target_os = cc_target_os
),
DefaultInfo(
executable = out,
),
]
cc_toolchain_config = rule(
implementation = _impl,
attrs = {
"cpu": attr.string(mandatory=True, values=["k8"]),
"compiler": attr.string(mandatory=True, values=["clang", "compiler"]),
},
provides = [CcToolchainConfigInfo],
executable = True,
)
| 39.543759 | 95 | 0.434838 | 2,213 | 27,562 | 5.060551 | 0.108902 | 0.167961 | 0.093758 | 0.090008 | 0.753817 | 0.730869 | 0.713189 | 0.71176 | 0.689704 | 0.663452 | 0 | 0.00798 | 0.472607 | 27,562 | 696 | 96 | 39.600575 | 0.762452 | 0 | 0 | 0.748865 | 0 | 0.003026 | 0.126079 | 0.055366 | 0 | 0 | 0 | 0 | 0 | 1 | 0.001513 | false | 0.001513 | 0 | 0 | 0.003026 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
9753c9727d3d22d9a0aefd3b85084725b65684c0 | 140 | py | Python | apps/depot/admin.py | HarrisonHDU/myerp | 61a7822d940ff8451f60ec7b39ff067169293c61 | [
"MIT"
] | 3 | 2016-09-17T13:59:33.000Z | 2017-03-08T01:52:54.000Z | apps/depot/admin.py | HarrisonHDU/myerp | 61a7822d940ff8451f60ec7b39ff067169293c61 | [
"MIT"
] | null | null | null | apps/depot/admin.py | HarrisonHDU/myerp | 61a7822d940ff8451f60ec7b39ff067169293c61 | [
"MIT"
] | null | null | null | from django.contrib import admin
from .models import Product, ProductItem
admin.site.register(Product)
admin.site.register(ProductItem) | 28 | 41 | 0.814286 | 18 | 140 | 6.333333 | 0.555556 | 0.157895 | 0.298246 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.107143 | 140 | 5 | 42 | 28 | 0.912 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
97b465f0492d9b386d466173abd7fd689061cf3a | 85 | py | Python | folder/__init__.py | praveenram/sync_folders | c50feb106510bf43ea4ffef9ccdfb6af0cfbd966 | [
"MIT"
] | null | null | null | folder/__init__.py | praveenram/sync_folders | c50feb106510bf43ea4ffef9ccdfb6af0cfbd966 | [
"MIT"
] | null | null | null | folder/__init__.py | praveenram/sync_folders | c50feb106510bf43ea4ffef9ccdfb6af0cfbd966 | [
"MIT"
] | null | null | null | ''' Folder Operations '''
from .folder import summary_json, init_folder, get_summary
| 28.333333 | 58 | 0.776471 | 11 | 85 | 5.727273 | 0.727273 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.117647 | 85 | 2 | 59 | 42.5 | 0.84 | 0.2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
c1363ae7a02ea0c53a2c3727e154c49e8e46e44f | 121 | py | Python | shutilwhich_cwdpatch/__init__.py | kiwi0fruit/shutilwhich-cwdpatch | b9d7e42bab274005ed536660dd980eb696c7b741 | [
"bzip2-1.0.6"
] | null | null | null | shutilwhich_cwdpatch/__init__.py | kiwi0fruit/shutilwhich-cwdpatch | b9d7e42bab274005ed536660dd980eb696c7b741 | [
"bzip2-1.0.6"
] | null | null | null | shutilwhich_cwdpatch/__init__.py | kiwi0fruit/shutilwhich-cwdpatch | b9d7e42bab274005ed536660dd980eb696c7b741 | [
"bzip2-1.0.6"
] | null | null | null | from ._version import get_versions
__version__ = get_versions()['version']
del get_versions
from .__main__ import which
| 20.166667 | 39 | 0.809917 | 16 | 121 | 5.375 | 0.5 | 0.383721 | 0.418605 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.115702 | 121 | 5 | 40 | 24.2 | 0.803738 | 0 | 0 | 0 | 0 | 0 | 0.057851 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
c13b9e3ffdbed7c2d723adcc90a0ce96b281e693 | 47 | py | Python | examples/_tests_scripts/rl_utils.py | cgarciae/catalyst | 391ff89ab0d9a1961b88719e894f917ac0fb7fc3 | [
"Apache-2.0"
] | 1 | 2019-11-26T06:41:33.000Z | 2019-11-26T06:41:33.000Z | examples/_tests_scripts/rl_utils.py | cgarciae/catalyst | 391ff89ab0d9a1961b88719e894f917ac0fb7fc3 | [
"Apache-2.0"
] | null | null | null | examples/_tests_scripts/rl_utils.py | cgarciae/catalyst | 391ff89ab0d9a1961b88719e894f917ac0fb7fc3 | [
"Apache-2.0"
] | null | null | null | # flake8: noqa
from catalyst.rl.utils import *
| 15.666667 | 31 | 0.744681 | 7 | 47 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.025 | 0.148936 | 47 | 2 | 32 | 23.5 | 0.85 | 0.255319 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
c1435286fe907992d74dc3f2075437ce1f1d6885 | 199 | py | Python | museosMadrid/admin.py | AlbertoCoding/X-Serv-Practica-Museos | 5d3e3c99b8750ece9973f4e04ae3c3bfe77f3946 | [
"Apache-2.0"
] | null | null | null | museosMadrid/admin.py | AlbertoCoding/X-Serv-Practica-Museos | 5d3e3c99b8750ece9973f4e04ae3c3bfe77f3946 | [
"Apache-2.0"
] | null | null | null | museosMadrid/admin.py | AlbertoCoding/X-Serv-Practica-Museos | 5d3e3c99b8750ece9973f4e04ae3c3bfe77f3946 | [
"Apache-2.0"
] | null | null | null | from django.contrib import admin
from .models import Museo, Usuario, Comentario
# Register your models here.
admin.site.register(Museo)
admin.site.register(Usuario)
admin.site.register(Comentario)
| 22.111111 | 46 | 0.809045 | 27 | 199 | 5.962963 | 0.481481 | 0.167702 | 0.31677 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.100503 | 199 | 8 | 47 | 24.875 | 0.899441 | 0.130653 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.4 | 0 | 0.4 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
c1484ffeed6515c37751b0eb4e9efd32403d1091 | 84 | py | Python | mycloud/mycloudapi/requests/__init__.py | ThomasGassmann/swisscom-my-cloud-backup | 97e222c45a54197c82c8f3a5d59aa20bf3382ed8 | [
"MIT"
] | 4 | 2019-11-28T22:10:43.000Z | 2022-01-23T15:18:26.000Z | mycloud/mycloudapi/requests/__init__.py | ThomasGassmann/swisscom-my-cloud-backup | 97e222c45a54197c82c8f3a5d59aa20bf3382ed8 | [
"MIT"
] | 18 | 2019-01-20T22:30:48.000Z | 2020-06-09T21:16:07.000Z | mycloud/mycloudapi/requests/__init__.py | thomasgassmann/mycloud-cli | 97e222c45a54197c82c8f3a5d59aa20bf3382ed8 | [
"MIT"
] | null | null | null | from mycloud.mycloudapi.requests.request import MyCloudRequest, Method, ContentType
| 42 | 83 | 0.869048 | 9 | 84 | 8.111111 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.071429 | 84 | 1 | 84 | 84 | 0.935897 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
c153bbbf6787aaae32320a6b9bb9d341db56c30c | 2,718 | py | Python | tests/test_content_name.py | dominicrodger/django-tinycontent | dfc07afadfe2056b7b61bdbd0275404718ed8b45 | [
"BSD-3-Clause"
] | 16 | 2015-06-05T14:28:12.000Z | 2020-07-14T06:57:34.000Z | tests/test_content_name.py | dominicrodger/django-tinycontent | dfc07afadfe2056b7b61bdbd0275404718ed8b45 | [
"BSD-3-Clause"
] | 23 | 2015-07-19T22:27:49.000Z | 2020-02-11T21:51:13.000Z | tests/test_content_name.py | dominicrodger/django-tinycontent | dfc07afadfe2056b7b61bdbd0275404718ed8b45 | [
"BSD-3-Clause"
] | 9 | 2015-07-20T20:58:08.000Z | 2019-11-04T03:26:49.000Z | import pytest
from .utils import (
render_template,
render_template_with_context
)
@pytest.mark.django_db
def test_allows_context_variables_as_content_names_from_simple(simple_content):
t = ("{% tinycontent_simple content_name %}")
ctx = {'content_name': 'foobar'}
assert "This is a test." == render_template_with_context(t, ctx)
@pytest.mark.django_db
def test_allows_context_variables_as_content_names_from_complex(
simple_content
):
t = ("{% tinycontent content_name %}"
"Text if empty."
"{% endtinycontent %}")
ctx = {'content_name': 'foobar'}
assert "This is a test." == render_template_with_context(t, ctx)
@pytest.mark.django_db
def test_allows_multiple_arguments_and_variables_from_simple(split_content):
t = ("{% tinycontent_simple 'foo' var %}")
ctx = {'var': 'bar'}
assert "This is a second test." == render_template_with_context(t, ctx)
@pytest.mark.django_db
def test_allows_multiple_arguments_and_variables_from_complex(
split_content
):
t = ("{% tinycontent 'foo' key %}"
"Text if empty."
"{% endtinycontent %}")
ctx = {'key': 'bar'}
assert "This is a second test." == render_template_with_context(t, ctx)
@pytest.mark.django_db
def test_allows_with_tag_as_content_names_from_simple(simple_content):
t = ("{% with content_name='foobar' %}"
"{% tinycontent_simple content_name %}"
"{% endwith %}")
assert "This is a test." == render_template(t)
@pytest.mark.django_db
def test_allows_with_tag_as_content_names_from_complex(simple_content):
t = ("{% with content_name='foobar' %}"
"{% tinycontent content_name %}"
"Text if empty."
"{% endtinycontent %}"
"{% endwith %}")
assert "This is a test." == render_template(t)
@pytest.mark.django_db
def test_allows_unprovided_ctx_variables_as_content_name_complex(
simple_content
):
t = ("{% tinycontent content_name %}"
"Text if empty."
"{% endtinycontent %}")
assert "Text if empty." == render_template(t)
@pytest.mark.django_db
def test_allows_unprovided_ctx_variables_as_content_name_simple(
simple_content
):
t = ("{% tinycontent_simple content_name %}")
assert "" == render_template(t)
@pytest.mark.django_db
def test_ctx_variables_with_name_of_content_complex(simple_content):
t = ("{% tinycontent foobar %}"
"Text if empty."
"{% endtinycontent %}")
assert "Text if empty." == render_template(t)
@pytest.mark.django_db
def test_ctx_variables_with_name_of_content_simple(simple_content):
t = ("{% tinycontent_simple foobar %}")
assert "" == render_template(t)
| 25.401869 | 79 | 0.679544 | 338 | 2,718 | 5.071006 | 0.136095 | 0.098016 | 0.093349 | 0.105018 | 0.87748 | 0.842474 | 0.820887 | 0.799883 | 0.682614 | 0.682614 | 0 | 0 | 0.196468 | 2,718 | 106 | 80 | 25.641509 | 0.784799 | 0 | 0 | 0.647887 | 0 | 0 | 0.278514 | 0.015453 | 0 | 0 | 0 | 0 | 0.140845 | 1 | 0.140845 | false | 0 | 0.028169 | 0 | 0.169014 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 |
c15c67e1001158096b72d724bf13aadf28690c25 | 120 | py | Python | api/admin.py | echodelt/django-rest-api-test | 8e595d82fe53a266559076df9ea23b76a7206f09 | [
"MIT"
] | null | null | null | api/admin.py | echodelt/django-rest-api-test | 8e595d82fe53a266559076df9ea23b76a7206f09 | [
"MIT"
] | null | null | null | api/admin.py | echodelt/django-rest-api-test | 8e595d82fe53a266559076df9ea23b76a7206f09 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
from django.contrib import admin
from api.models import Article
admin.site.register(Article)
| 15 | 32 | 0.733333 | 17 | 120 | 5.176471 | 0.764706 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.009709 | 0.141667 | 120 | 7 | 33 | 17.142857 | 0.84466 | 0.175 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.666667 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
c1c3007078eb132675aa81de1528f770d6b397ae | 140 | py | Python | backend/app/auth/__init__.py | Kwsswart/writter | 851b887d0c8b0a9489f530065f0efe744bb149f3 | [
"MIT"
] | null | null | null | backend/app/auth/__init__.py | Kwsswart/writter | 851b887d0c8b0a9489f530065f0efe744bb149f3 | [
"MIT"
] | null | null | null | backend/app/auth/__init__.py | Kwsswart/writter | 851b887d0c8b0a9489f530065f0efe744bb149f3 | [
"MIT"
] | null | null | null | from flask import Blueprint
bp = Blueprint('auth', __name__, static_folder='../../build', static_url_path='/')
from app.auth import routes | 28 | 82 | 0.735714 | 19 | 140 | 5.052632 | 0.736842 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.107143 | 140 | 5 | 83 | 28 | 0.768 | 0 | 0 | 0 | 0 | 0 | 0.113475 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.666667 | 0 | 0.666667 | 0.666667 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 5 |
c1c84da62db365be868e6ecf5449b54f1c892c06 | 2,337 | py | Python | venv1/Lib/site-packages/tensorflow/python/keras/applications/__init__.py | Soum-Soum/Tensorflow_Face_Finder | fec6c15d2df7012608511ad87f4b55731bf99478 | [
"Apache-2.0",
"MIT"
] | null | null | null | venv1/Lib/site-packages/tensorflow/python/keras/applications/__init__.py | Soum-Soum/Tensorflow_Face_Finder | fec6c15d2df7012608511ad87f4b55731bf99478 | [
"Apache-2.0",
"MIT"
] | 1 | 2021-05-20T00:58:04.000Z | 2021-05-20T00:58:04.000Z | venv1/Lib/site-packages/tensorflow/python/keras/applications/__init__.py | Soum-Soum/Tensorflow_Face_Finder | fec6c15d2df7012608511ad87f4b55731bf99478 | [
"Apache-2.0",
"MIT"
] | null | null | null | # Copyright 2016 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.
# ==============================================================================
"""Keras Applications are canned architectures with pre-trained weights."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.python.keras.applications import densenet
from tensorflow.python.keras.applications import inception_resnet_v2
from tensorflow.python.keras.applications import inception_v3
from tensorflow.python.keras.applications import mobilenet
from tensorflow.python.keras.applications import nasnet
from tensorflow.python.keras.applications import resnet50
from tensorflow.python.keras.applications import vgg16
from tensorflow.python.keras.applications import vgg19
from tensorflow.python.keras.applications import xception
from tensorflow.python.keras.applications.densenet import DenseNet121
from tensorflow.python.keras.applications.densenet import DenseNet169
from tensorflow.python.keras.applications.densenet import DenseNet201
from tensorflow.python.keras.applications.inception_resnet_v2 import InceptionResNetV2
from tensorflow.python.keras.applications.inception_v3 import InceptionV3
from tensorflow.python.keras.applications.mobilenet import MobileNet
from tensorflow.python.keras.applications.nasnet import NASNetLarge
from tensorflow.python.keras.applications.nasnet import NASNetMobile
from tensorflow.python.keras.applications.resnet50 import ResNet50
from tensorflow.python.keras.applications.vgg16 import VGG16
from tensorflow.python.keras.applications.vgg19 import VGG19
from tensorflow.python.keras.applications.xception import Xception
del absolute_import
del division
del print_function
| 50.804348 | 87 | 0.801455 | 290 | 2,337 | 6.382759 | 0.348276 | 0.202053 | 0.226904 | 0.28363 | 0.546191 | 0.506213 | 0.386818 | 0 | 0 | 0 | 0 | 0.019769 | 0.112537 | 2,337 | 45 | 88 | 51.933333 | 0.87271 | 0.312794 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.925926 | 0 | 0.925926 | 0.074074 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
c1d3bbe07cb8f3f6d4827ab15edf5ff6c60b4d3a | 171 | py | Python | etudiorder/admin.py | LizzyGC/lizzygc-appsite | 2d15c438a4de2b147f24e0b6ff1ed6b3b4417f84 | [
"BSD-3-Clause"
] | 1 | 2021-06-01T16:57:33.000Z | 2021-06-01T16:57:33.000Z | etudiorder/admin.py | LizzyGC/lizzygc-appsite | 2d15c438a4de2b147f24e0b6ff1ed6b3b4417f84 | [
"BSD-3-Clause"
] | 13 | 2021-08-28T09:27:05.000Z | 2021-08-28T09:33:49.000Z | etudiorder/admin.py | LizzyGC/lizzygc-appsite | 2d15c438a4de2b147f24e0b6ff1ed6b3b4417f84 | [
"BSD-3-Clause"
] | null | null | null | from django.contrib import admin
from etudiorder.models import Topico, Descricao
# Register your models here.
admin.site.register(Topico)
admin.site.register(Descricao)
| 21.375 | 47 | 0.818713 | 23 | 171 | 6.086957 | 0.565217 | 0.128571 | 0.242857 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.105263 | 171 | 7 | 48 | 24.428571 | 0.915033 | 0.152047 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
c1e58ae538d6ced253bd551b67f73b898695ff6a | 168 | py | Python | fabfile/common/lib/directory.py | hnakamur/my-fabfiles | 3b5ac68ebaa185f06a5dffc27533b2906b599c27 | [
"MIT"
] | 1 | 2015-06-12T02:05:02.000Z | 2015-06-12T02:05:02.000Z | fabfile/common/lib/directory.py | hnakamur/my-fabfiles | 3b5ac68ebaa185f06a5dffc27533b2906b599c27 | [
"MIT"
] | null | null | null | fabfile/common/lib/directory.py | hnakamur/my-fabfiles | 3b5ac68ebaa185f06a5dffc27533b2906b599c27 | [
"MIT"
] | null | null | null | from fabtools.require import files
def ensure_exists(path, use_sudo=False, owner=None, group=None, mode=None):
files.directory(path, use_sudo, owner, group, mode)
| 33.6 | 75 | 0.767857 | 26 | 168 | 4.846154 | 0.653846 | 0.111111 | 0.174603 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.119048 | 168 | 4 | 76 | 42 | 0.851351 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0.333333 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
c1f7700401797c693de29e7486fd3940ce254a2f | 114 | py | Python | 03 project/commandr/cmdr/admin.py | Mohamadnaseer/Django | e1b3dd0ea2a2f42e004b04333821c1e0ec1d065f | [
"MIT"
] | null | null | null | 03 project/commandr/cmdr/admin.py | Mohamadnaseer/Django | e1b3dd0ea2a2f42e004b04333821c1e0ec1d065f | [
"MIT"
] | null | null | null | 03 project/commandr/cmdr/admin.py | Mohamadnaseer/Django | e1b3dd0ea2a2f42e004b04333821c1e0ec1d065f | [
"MIT"
] | null | null | null | from django.contrib import admin
# Register your models here.
from.models import cmdr
admin.site.register(cmdr) | 16.285714 | 32 | 0.798246 | 17 | 114 | 5.352941 | 0.647059 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.131579 | 114 | 7 | 33 | 16.285714 | 0.919192 | 0.22807 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.666667 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
de056ce106e8467060551824d1e2d93ada47286b | 48 | py | Python | tests/api/__init__.py | isu-avista/base-server | 266f74becfb19083125c40f3d15bc7c67ebff243 | [
"MIT"
] | null | null | null | tests/api/__init__.py | isu-avista/base-server | 266f74becfb19083125c40f3d15bc7c67ebff243 | [
"MIT"
] | null | null | null | tests/api/__init__.py | isu-avista/base-server | 266f74becfb19083125c40f3d15bc7c67ebff243 | [
"MIT"
] | null | null | null | from tests.api import test_config, test_service
| 24 | 47 | 0.854167 | 8 | 48 | 4.875 | 0.875 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.104167 | 48 | 1 | 48 | 48 | 0.906977 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
de0b30c4127740bac9c008b055be1a3cf4b852fc | 38 | py | Python | thrift/compiler/py/__init__.py | CacheboxInc/fbthrift | b894dd9192ea4684c0067c93bb2ba2b9547749ec | [
"Apache-2.0"
] | 5 | 2015-11-23T00:26:06.000Z | 2020-07-31T12:56:08.000Z | thrift/compiler/py/__init__.py | CacheboxInc/fbthrift | b894dd9192ea4684c0067c93bb2ba2b9547749ec | [
"Apache-2.0"
] | 2 | 2017-05-10T15:43:34.000Z | 2018-01-04T22:36:04.000Z | thrift/compiler/py/__init__.py | CacheboxInc/fbthrift | b894dd9192ea4684c0067c93bb2ba2b9547749ec | [
"Apache-2.0"
] | 7 | 2017-09-01T01:30:25.000Z | 2019-02-04T17:46:24.000Z | import generate
__all__ = [generate]
| 9.5 | 20 | 0.763158 | 4 | 38 | 6.25 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.157895 | 38 | 3 | 21 | 12.666667 | 0.78125 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
a9f39dfc5fc07f006d64be46d0e1ce90c0362a79 | 95 | py | Python | newsletter/admin.py | AdityaJ42/unicode-website | 18892d2d59fb848d4d21c583da299a2d2308bf35 | [
"MIT"
] | null | null | null | newsletter/admin.py | AdityaJ42/unicode-website | 18892d2d59fb848d4d21c583da299a2d2308bf35 | [
"MIT"
] | null | null | null | newsletter/admin.py | AdityaJ42/unicode-website | 18892d2d59fb848d4d21c583da299a2d2308bf35 | [
"MIT"
] | null | null | null | from django.contrib import admin
from .models import newslet
admin.site.register(newslet)
| 19 | 33 | 0.789474 | 13 | 95 | 5.769231 | 0.692308 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.147368 | 95 | 4 | 34 | 23.75 | 0.925926 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.666667 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
e72b8a519dc8d799a2acf3935cae1c5201c7d779 | 302 | py | Python | src/simmate/workflow_engine/common_tasks/__init__.py | laurenmm/simmate-1 | c06b94c46919b01cda50f78221ad14f75c100a14 | [
"BSD-3-Clause"
] | null | null | null | src/simmate/workflow_engine/common_tasks/__init__.py | laurenmm/simmate-1 | c06b94c46919b01cda50f78221ad14f75c100a14 | [
"BSD-3-Clause"
] | null | null | null | src/simmate/workflow_engine/common_tasks/__init__.py | laurenmm/simmate-1 | c06b94c46919b01cda50f78221ad14f75c100a14 | [
"BSD-3-Clause"
] | null | null | null | # -*- coding: utf-8 -*-
from .load_input_and_register import LoadInputAndRegister
from .save_result import SaveOutputTask
from .load_nested_calculation import LoadNestedCalculationTask
from .save_nested_calculation import SaveNestedCalculationTask
from .parse_multi_command import parse_multi_command
| 37.75 | 62 | 0.86755 | 35 | 302 | 7.142857 | 0.571429 | 0.064 | 0.184 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.003623 | 0.086093 | 302 | 7 | 63 | 43.142857 | 0.902174 | 0.069536 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 5 |
e7495d432ba2342093fb7a6ec3149ff5142414be | 155 | py | Python | util/charset/benchmark/to_lower/metrics/main.py | HeyLey/catboost | f472aed90604ebe727537d9d4a37147985e10ec2 | [
"Apache-2.0"
] | 6,989 | 2017-07-18T06:23:18.000Z | 2022-03-31T15:58:36.000Z | util/charset/benchmark/to_lower/metrics/main.py | HeyLey/catboost | f472aed90604ebe727537d9d4a37147985e10ec2 | [
"Apache-2.0"
] | 1,978 | 2017-07-18T09:17:58.000Z | 2022-03-31T14:28:43.000Z | util/charset/benchmark/to_lower/metrics/main.py | HeyLey/catboost | f472aed90604ebe727537d9d4a37147985e10ec2 | [
"Apache-2.0"
] | 1,228 | 2017-07-18T09:03:13.000Z | 2022-03-29T05:57:40.000Z | import yatest.common as yc
def test_export_metrics(metrics):
metrics.set_benchmark(yc.execute_benchmark('util/charset/benchmark/to_lower/to_lower'))
| 25.833333 | 91 | 0.812903 | 23 | 155 | 5.217391 | 0.695652 | 0.233333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.083871 | 155 | 5 | 92 | 31 | 0.84507 | 0 | 0 | 0 | 0 | 0 | 0.258065 | 0.258065 | 0 | 0 | 0 | 0 | 0 | 1 | 0.333333 | false | 0 | 0.333333 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 5 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.