Everfighting

from itertools import groupby
sep = ',!?:; ：，.。！？《》、|\\/abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ'
eng_split_texts = [''.join(g) for k, g in groupby(self.eng_texts, sep.__contains__) if not k]

Everfighting

select col from yourtable
order by cast(col as unsigned)

Everfighting

from sys import platform
if platform == "linux" or platform == "linux2":
    # linux
elif platform == "darwin":
    # OS X
elif platform == "win32":
    # Windows...

Everfighting

"""
将docx,doc文件转换成pdf的后缀，不考虑大小写
"""
import re
doc_format_list=[r'.docx',r'.doc']
doc_format_pattern='|'.join(doc_format_list)
path = r'C:\Users\Administrator\Desktop\temp\托书2 - Copy.DOCX'
print(re.sub(doc_format_pattern, r'.pdf', path, flags=re.I))

Everfighting

# 获取python解释器的位数
import struct
print(struct.calcsize("P") * 8)

Everfighting

import glob
file_list = []
for ext in ('*.pdf', '*.PDF'):
    res_paths = os.path.join(directory, ext)
    file_list.extend(glob.glob(res_paths))
for file in file_list:
    pass

Everfighting

from sklearn.datasets import load_iris   
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
import matplotlib.pyplot as plt
import numpy as np

# 加载数据集
iris = load_iris()

# 数据特征：150行， 4列

Everfighting

import matplotlib.pyplot as plt
import numpy as np

def sigmoid(x):
    return 1. / (1. + np.exp(-x))
 
x = np.arange(-10, 10, 0.1)
y = sigmoid(x)

plt.plot(x, y)

Everfighting

#!/usr/bin/env python3
# -*- coding: utf-8 -*-

import re
import os
import glob


# clone所有的仓库，如果仓库存在则更新
def clone_all_project():

Everfighting

import operator
x = {1: 2, 3: 4, 4: 3, 2: 1, 0: 0}
sorted_x = sorted(x.items(), key=operator.itemgetter(1))

import operator
x = {1: 2, 3: 4, 4: 3, 2: 1, 0: 0}
sorted_x = sorted(x.items(), key=operator.itemgetter(0))

x = {1: 2, 3: 4, 4: 3, 2: 1, 0: 0}