모아두기 추천하는 파이썬 활용팁 20가지!

import random random.choices(seq, k=1) # 长度为k的list，有放回采样 random.sample(seq, k) # 长度为k的list，无放回采样

func = lambda y: x + y # x的值在函数运行时被绑定 func = lambda y, x=x: x + y # x的值在函数定义时被绑定

import copy y = copy.copy(x) # 只复制最顶层 y = copy.deepcopy(x) # 复制所有嵌套部分

a = [1, 2, [3, 4]] # Alias. b_alias = a assert b_alias == a and b_alias is a # Shallow copy. b_shallow_copy = a[:] assert b_shallow_copy == a and b_shallow_copy is not a and b_shallow_copy[2] is a[2] # Deep copy. import copy b_deep_copy = copy.deepcopy(a) assert b_deep_copy == a and b_deep_copy is not a and b_deep_copy[2] is not a[2]

import csv # 无header的读写 with open(name, 'rt', encoding='utf-8', newline='') as f: # newline=''让Python不将换行统一处理 for row in csv.reader(f): print(row[0], row[1]) # CSV读到的数据都是str类型 with open(name, mode='wt') as f: f_csv = csv.writer(f) f_csv.writerow(['symbol', 'change']) # 有header的读写 with open(name, mode='rt', newline='') as f: for row in csv.DictReader(f): print(row['symbol'], row['change']) with open(name, mode='wt') as f: header = ['symbol', 'change'] f_csv = csv.DictWriter(f, header) f_csv.writeheader() f_csv.writerow({'symbol': xx, 'change': xx})

import sys csv.field_size_limit(sys.maxsize)

f = csv.reader(f, delimiter='\t')

import itertools itertools.islice(iterable, start=None, stop, step=None) # islice('ABCDEF', 2, None) -> C, D, E, F itertools.filterfalse(predicate, iterable) # 过滤掉predicate为False的元素 # filterfalse(lambda x: x < 5, [1, 4, 6, 4, 1]) -> 6 itertools.takewhile(predicate, iterable) # 当predicate为False时停止迭代 # takewhile(lambda x: x < 5, [1, 4, 6, 4, 1]) -> 1, 4 itertools.dropwhile(predicate, iterable) # 当predicate为False时开始迭代 # dropwhile(lambda x: x < 5, [1, 4, 6, 4, 1]) -> 6, 4, 1 itertools.compress(iterable, selectors) # 根据selectors每个元素是True或False进行选择 # compress('ABCDEF', [1, 0, 1, 0, 1, 1]) -> A, C, E, F

sorted(iterable, key=None, reverse=False) itertools.groupby(iterable, key=None) # 按值分组，iterable需要先被排序 # groupby(sorted([1, 4, 6, 4, 1])) -> (1, iter1), (4, iter4), (6, iter6) itertools.permutations(iterable, r=None) # 排列，返回值是Tuple # permutations('ABCD', 2) -> AB, AC, AD, BA, BC, BD, CA, CB, CD, DA, DB, DC itertools.combinations(iterable, r=None) # 组合，返回值是Tuple itertools.combinations_with_replacement(...) # combinations('ABCD', 2) -> AB, AC, AD, BC, BD, CD

itertools.chain(*iterables) # 多个序列直接拼接 # chain('ABC', 'DEF') -> A, B, C, D, E, F import heapq heapq.merge(*iterables, key=None, reverse=False) # 多个序列按顺序拼接 # merge('ABF', 'CDE') -> A, B, C, D, E, F zip(*iterables) # 当最短的序列耗尽时停止，结果只能被消耗一次 itertools.zip_longest(*iterables, fillvalue=None) # 当最长的序列耗尽时停止，结果只能被消耗一次

import collections # 创建 collections.Counter(iterable) # 频次 collections.Counter[key] # key出现频次 # 返回n个出现频次最高的元素和其对应出现频次，如果n为None，返回所有元素 collections.Counter.most_common(n=None) # 插入/更新 collections.Counter.update(iterable) counter1 + counter2; counter1 - counter2 # counter加减 # 检查两个字符串的组成元素是否相同 collections.Counter(list1) == collections.Counter(list2)

import collections collections.defaultdict(type) # 当第一次访问dict[key]时，会无参数调用type，给dict[key]提供一个初始值

import collections collections.OrderedDict(items=None) # 迭代时保留原始插入顺序

import sys sys.stderr.write('')

import warnings warnings.warn(message, category=UserWarning) # category的取值有DeprecationWarning, SyntaxWarning, RuntimeWarning, ResourceWarning, FutureWarning

$ python -W all # 输出所有警告，等同于设置warnings.simplefilter('always') $ python -W ignore # 忽略所有警告，等同于设置warnings.simplefilter('ignore') $ python -W error # 将所有警告转换为异常，等同于设置warnings.simplefilter('error')

# 在代码中的debug部分 if __debug__: pass

$ python -0 main.py

pylint main.py

$ python -m cProfile main.py

# 代码块耗时定义 from contextlib import contextmanager from time import perf_counter @contextmanager def timeblock(label): tic = perf_counter() try: yield finally: toc = perf_counter() print('%s : %s' % (label, toc - tic)) # 代码块耗时测试 with timeblock('counting'): pass