w495

[Shortcuts]
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activate_tab_3=Alt+4
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# coding: utf-8

import logging


class AddLoggerMeta(type):
    def __new__(mcs, class_name, bases, attr_dict):
        attr_dict[f'_{class_name}__logger'] = logging.getLogger(class_name)
        return super().__new__(mcs, class_name, bases, attr_dict)

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# coding: utf-8

import logging

__logger = logging.getLogger(__name__)


def global_function():
    __logger.error('global_function')

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#include <stdio.h>
#include <string.h>
#include <stdlib.h>

typedef unsigned char byte_t;


static const byte_t offset =  1;
static const byte_t limit =  4;

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# -*- coding: utf8 -*-
from __future__ import absolute_import, division, print_function

import logging
import sys

import requests

MIN_CHUNK_SIZE = 1.0

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## РОДНОЕ ПРЕДСТАВЛЕНИЕ UTF8-СТРОКИ:

>>> [ord(i) for i in 'Бил Гейтс'] 

[208, 145, 208, 184, 208, 187, 
 32, 
 208, 147, 208, 181, 208, 185, 209, 130, 209, 129]

#   Что тут происходит:
#       *   Я перебираю все символы строки через цикл FOR.

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import sys
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split,GridSearchCV, cross_val_score,StratifiedKFold,validation_curve,learning_curve
from sklearn.metrics import confusion_matrix, f1_score, matthews_corrcoef, precision_recall_curve, auc, classification_report, roc_curve, cohen_kappa_score, make_scorer,accuracy_score,roc_auc_score,precision_score,recall_score, brier_score_loss
from imblearn.ensemble import BalancedBaggingClassifier
from sklearn.tree import DecisionTreeClassifier
from xgboost.sklearn import XGBClassifier
from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier

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[
    {
        "content_id": "87fc1328-cde3-40b0-9b9b-ced0498747c4",
        "content_url": "https://h2.silatv.ru/highlight/12121/1080.mp4",
        "thumbnail": "http://cdn.okultureno.ru/medialibrary/87f/87f2341b53596e8ca592a1e885261ccf/khokkey-_1_.jpg"
        "type" : "game",
        "channel": "telesport1",
        "release_timestamp":  1518421201, // не нужно при наличие start_time & finish_time
        "start_time": 1518421200,
        "finish_time": 1518429600,

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# -*- coding: utf8 -*-

from __future__ import absolute_import, print_function

import six


class BaseFieldDao(object):
    _value = None
    _entity = None

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#!/usr/bin/python
# -*- coding: utf-8 -*-

# http://stackoverflow.com/questions/5574702/how-to-print-to-stderr-in-python
from __future__ import print_function
import sys
def eprint(*args, **kwargs):
    print(*args, file=sys.stderr, **kwargs)

import errno