Python-100-Days-CheatSheet

百日python，路线：语法->爬虫->网站->数据科学->机器学习->深度学习

Day 01：语法

python原生封装的数据结构，按增删改查组织

列表

<list> = <list>[from_inclusive : to_exclusive : step_size]
<list>.append(<el>)
<list>.extend(<collection>)
<list> += [<el>]
<list> += <collection>

<list>.sort()
<list>.reverse()
<list> = sorted(<collection>)
<iter> = reversed(<list>)

sum_of_elements  = sum(<collection>)
elementwise_sum  = [sum(pair) for pair in zip(list_a, list_b)]
sorted_by_second = sorted(<collection>, key=lambda el: el[1])
sorted_by_both   = sorted(<collection>, key=lambda el: (el[1], el[0]))
flattened_list   = list(itertools.chain.from_iterable(<list>))
list_of_chars    = list(<str>)
product_of_elems = functools.reduce(lambda out, x: out * x, <collection>)
no_duplicates    = list(dict.fromkeys(<list>))

index = <list>.index(<el>)  # 返回第一个匹配 <el> 的索引
<list>.insert(index, <el>)  # 在 index 处插入为 <el>，右边元素右移
<el> = <list>.pop([index])  # 移除 index 处的 <el> ，默认移除列表的最后一个元素
<list>.remove(<el>)         # 移除第一次出现的 <el>
<list>.clear()              # 移除所有

字典

<view> = <dict>.keys()
<view> = <dict>.values()
<view> = <dict>.items()

value  = <dict>.get(key, default)            # key 不存在则返回 default 默认值
value  = <dict>.setdefault(key, default)     # 同上，同时给 dict 指定对应 key 的 default 默认值
<dict> = collections.defaultdict(<type>)     # 创建一个字典，值的默认类型为 <type>
<dict> = collections.defaultdict(lambda: 1)  # 创建一个字典，默认值为 1

<dict>.update(<dict>)                        # 或: dict_a = {**dict_a, **dict_b}.
<dict> = dict(<list>)                        # 用键值对列表初始化一个字典
<dict> = dict(zip(keys, values))             # 用两个列表初始化一个字典
<dict> = dict.fromkeys(keys [, value])       # 用键列表初始化一个字典

value = <dict>.pop(key)                         # 移除 key，返回被移除的值
{k: v for k, v in <dict>.items() if k in keys}  # 按多个 key 过滤字典

Counter 计数器

>>> from collections import Counter
>>> colors = ['blue', 'red', 'blue', 'yellow', 'blue', 'red']
>>> counter = Counter(colors)
Counter({'blue': 3, 'red': 2, 'yellow': 1})
>>> counter.most_common()[0][0]
'blue'

Set

<set> = set()
<set>.add(<el>)
<set>.update(<collection>)
<set> |= {<el>}
<set> |= <set>

<set>  = <set>.union(<coll.>)                 # 或: <set> | <set>
<set>  = <set>.intersection(<coll.>)          # 或: <set> & <set>
<set>  = <set>.difference(<coll.>)            # 或: <set> - <set>
<set>  = <set>.symmetric_difference(<coll.>)  # 或: <set> ^ <set>
<bool> = <set>.issubset(<coll.>)              # 或: <set> <= <set>
<bool> = <set>.issuperset(<coll.>)            # 或: <set> >= <set>

<set>.remove(<el>)   # 有错误会抛出.
<set>.discard(<el>)  # 不会抛出错误

Frozenset

是否可作为字典的键

<frozenset> = frozenset(<collection>)

Range

range(to_exclusive)
range(from_inclusive, to_exclusive)
range(from_inclusive, to_exclusive, step_size)
range(from_inclusive, to_exclusive, -step_size)

from_inclusive = <range>.start
to_exclusive   = <range>.stop

Enumerate

for i, el in enumerate(<collection> [, i_start]):
    ...

自定义名字的元组

>>> Point = collections.namedtuple('Point', 'x y')
>>> p = Point(1, y=2)
Point(x=1, y=2)
>>> p[0]
1
>>> p.x
1
>>> getattr(p, 'y')
2
>>> p._fields  # 或: Point._fields
('x', 'y')

Iterator

<iter> = iter(<collection>)
<iter> = iter(<function>, to_exclusive)

读取输入，空行停止

for line in iter(input, ''):
    ...

同上，每次在输入前加一条信息，不计入读取的输入

from functools import partial
for line in iter(partial(input, 'Please enter value: '), ''):
    ...

Next

返回下一个元素。 如果没下一个元素了，抛出错误或返回 default

<el> = next(<iter> [, default])

Skips first item:

next(<iter>)
for element in <iter>:
    ...

Generator

方便实现迭代协议

def step(start, step_size):
    while True:
        yield start
        start += step_size

>>> stepper = step(10, 2)
>>> next(stepper), next(stepper), next(stepper)
(10, 12, 14)

Type

<type> = type(<el>)  # <class 'int'> / <class 'str'> / ...

from numbers import Number, Integral, Real, Rational, Complex
<bool> = isinstance(<el>, Number)

<bool> = callable(<el>)

String

<str>  = <str>.strip()           # 移除 <str> 首尾两边的空白字符
<str>  = <str>.strip('<chars>')  # 移除 <str> 首尾两边由 <chars> 指定的字符

<list> = <str>.split()                       # 按空格字符切分成列表
<list> = <str>.split(sep=None, maxsplit=-1)  # 按 'sep' 字符串切分成列表，至多 'maxsplit' 次.
<str>  = <str>.join(<list>)                  # 以 <str> 为分隔符合并 <list> 的所有元素.

<str>  = <str>.replace(old_str, new_str)
<bool> = <str>.startswith(<sub_str>)      # 可以传字符串元组
<bool> = <str>.endswith(<sub_str>)        # 可以传字符串元组
<int>  = <str>.index(<sub_str>)           # 返回子串的第一个索引
<bool> = <str>.isnumeric()                # <str> 含数字则返回 True
<list> = textwrap.wrap(<str>, width)      # 漂亮地将字符串折叠成行

Char

<str> = chr(<int>)  # int 转换成 unicode
<int> = ord(<str>)  # unicode 转换成 int.

>>> ord('0'), ord('9')
(48, 57)
>>> ord('A'), ord('Z')
(65, 90)
>>> ord('a'), ord('z')
(97, 122)

Regex

import re
<str>   = re.sub(<regex>, new, text, count=0)  # 替换所有
<list>  = re.findall(<regex>, text)            # 返回所有匹配的字符串
<list>  = re.split(<regex>, text, maxsplit=0)  # 按正则表达式来切缝字符串
<Match> = re.search(<regex>, text)             # 找第一次出现正则表达式匹配的
<Match> = re.match(<regex>, text)              # 只在 text 的开始找
<iter>  = re.finditer(<regex>, text)           # 返回所有匹配的对象，是个迭代器

• 参数 'flags=re.IGNORECASE' 可以和所有函数一起使用.
• 参数 'flags=re.DOTALL' 让点也匹配行.
• 使用 r'\1' 或 '\\\\1' 匹配退格符.
• 使用 '?' 实现非贪心.

Match Object

<str>   = <Match>.group()   # Whole match.
<str>   = <Match>.group(1)  # Part in first bracket.
<tuple> = <Match>.groups()  # All bracketed parts.
<int>   = <Match>.start()   # <Match> 的头索引
<int>   = <Match>.end()     # <Match> 的尾索引

Special Sequences

Use capital letter for negation.

'\d' == '[0-9]'          # 匹配数字
'\s' == '[ \t\n\r\f\v]'  # 匹配空白字符
'\w' == '[a-zA-Z0-9_]'   # 匹配字母表

字符串格式化

<str> = f'{<el_1>}, {<el_2>}'
<str> = '{}, {}'.format(<el_1>, <el_2>)

>>> Person = namedtuple('Person', 'name height')
>>> person = Person('Jean-Luc', 187)
>>> f'{person.height:10}'
'       187'
>>> '{p.height:10}'.format(p=person)
'       187'

基本操作

{<el>:<10}       # '<el>      '
{<el>:>10}       # '      <el>'
{<el>:^10}       # '   <el>   '
{<el>:->10}      # '------<el>'
{<el>:>0}        # '<el>'

字符串

'!r' 调用对象的 repr() 方法, 而不是 format(), 返回一个字符串.

{'abcde'!r:<10}  # "'abcde'   "

{'abcde':.3}     # 'abc'
{'abcde':10.3}   # 'abc       '

数字

{1.23456:.3f}    # '1.235'
{1.23456:10.3f}  # '     1.235'

{ 123456:10,}    # '   123,456'
{ 123456:10_}    # '   123_456'
{ 123456:+10}    # '   +123456'
{-123456:=10}    # '-   123456'
{ 123456: }      # ' 123456'
{-123456: }      # '-123456'

{65:c}           # 'A'
{3:08b}          # '00000011' -> Binary with leading zeros.
{3:0<8b}         # '11000000' -> Binary with trailing zeros.

Float

• 'f' - 位小数点: .<precision>f
• '%' - 百分比: .<precision>%
• 'e' - 科学计数法

Integer

• 'c' - character
• 'b' - binary
• 'x' - hex
• 'X' - HEX

Numbers

初等函数

<num>  = pow(<num>, <num>)  # 或: <num> ** <num>
<real> = abs(<num>)
<real> = round(<real> [, ndigits])

常数

from math import e, pi

三角函数

from math import cos, acos, sin, asin, tan, atan, degrees, radians

对数

from math import log, log10, log2
<float> = log(<real> [, base])  # 默认 e

Infinity, nan

from math import inf, nan, isinf, isnan

或:

float('inf'), float('nan')

Random

from random import random, randint, choice, shuffle
<float> = random()
<int>   = randint(from_inclusive, to_inclusive)
<el>    = choice(<list>)
shuffle(<list>)

Datetime

from datetime import datetime
now = datetime.now()
now.month                     # 3
now.strftime('%Y%m%d')        # '20180315'
now.strftime('%Y%m%d%H%M%S')  # '20180315002834'
<datetime> = datetime.strptime('2015-05-12 00:39', '%Y-%m-%d %H:%M')

函数参数

'*' 是运算符，参数以一个'*'号开头的代表着一个任意长度的元组(tuple)，可以接收连续一串参数，如上面代码里传的是1，2，3，你可以更多。 参数以两个'*'号开头的代表着一个字典，参数的形式是“key=value”，接受连续任意多个参数。

args   = (1, 2)
kwargs = {'x': 3, 'y': 4, 'z': 5}
func(*args, **kwargs)

等价于:

func(1, 2, x=3, y=4, z=5)

你的函数声明里也可以用

def add(*a):
    return sum(a)

>>> add(1, 2, 3)
6

一些其他地方也可以用

>>> a = (1, 2, 3)
>>> [*a]
[1, 2, 3]

>>> head, *body, tail = [1, 2, 3, 4]
>>> body
[2, 3]

Inline

Lambda

lambda: <return_value>
lambda <argument_1>, <argument_2>: <return_value>

Comprehension

<list> = [i+1 for i in range(10)]         # [1, 2, ..., 10]
<set>  = {i for i in range(10) if i > 5}  # {6, 7, 8, 9}
<dict> = {i: i*2 for i in range(10)}      # {0: 0, 1: 2, ..., 9: 18}
<iter> = (i+5 for i in range(10))         # (5, 6, ..., 14)

out = [i+j for i in range(10) for j in range(10)]

等价于:

out = []
for i in range(10):
    for j in range(10):
        out.append(i+j)

Map, Filter, Reduce

from functools import reduce
<iter> = map(lambda x: x + 1, range(10))            # (1, 2, ..., 10)
<iter> = filter(lambda x: x > 5, range(10))         # (6, 7, 8, 9)
<int>  = reduce(lambda out, x: out + x, range(10))  # 45

Any, All

<bool> = any(<collection>)                  # False if empty.
<bool> = all(el[1] for el in <collection>)  # True if empty.

If - Else

<expression_if_true> if <condition> else <expression_if_false>

>>> [a if a else 'zero' for a in (0, 1, 0, 3)]
['zero', 1, 'zero', 3]

Namedtuple, Enum, Class

from collections import namedtuple
Point     = namedtuple('Point', 'x y')
point     = Point(0, 0)

from enum import Enum
Direction = Enum('Direction', 'n e s w')
Cutlery   = Enum('Cutlery', {'fork': 1, 'knife': 2, 'spoon': 3})

# 注意: 初始化时对象共享
Creature  = type('Creature', (), {'p': Point(0, 0), 'd': Direction.n})
creature  = Creature()

Day02：进阶

Closure

We have a closure in Python when:

• A nested function references a value of its enclosing function and then
• the enclosing function returns the nested function.

def get_multiplier(a):
    def out(b):
        return a * b
    return out

>>> multiply_by_3 = get_multiplier(3)
>>> multiply_by_3(10)
30

• If multiple nested functions within enclosing function reference the same value, that value gets shared.
• To dynamicaly acces functions first free variable use '<function>.__closure__[0].cell_contents'.

或:

from functools import partial
<function> = partial(<function>, <argument_1> [, <argument_2>, ...])

>>> multiply_by_3 = partial(operator.mul, 3)
>>> multiply_by_3(10)
30

Nonlocal

If variable is assigned to anywhere in the scope, it is regarded as a local variable, unless it is declared as global or nonlocal.

def get_counter():
    a = 0
    def out():
        nonlocal a
        a += 1
        return a
    return out

>>> counter = get_counter()
>>> counter(), counter(), counter()
(1, 2, 3)

Decorator

A decorator takes a function, adds some functionality and returns it.

@decorator_name
def function_that_gets_passed_to_decorator():
    ...

Debugger Example

Decorator that prints function's name every time it gets called.

from functools import wraps

def debug(func):
    @wraps(func)
    def out(*args, **kwargs):
        print(func.__name__)
        return func(*args, **kwargs)
    return out

@debug
def add(x, y):
    return x + y

• Wraps is a helper decorator that copies metadata of function add() to function out().
• Without it 'add.__name__' would return 'out'.

LRU Cache

Decorator that caches function's return values. All function's arguments must be hashable.

from functools import lru_cache

@lru_cache(maxsize=None)
def fib(n):
    return n if n < 2 else fib(n-1) + fib(n-2)

>>> [fib(n) for n in range(10)]
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34]
>>> fib.cache_info()
CacheInfo(hits=16, misses=10, maxsize=None, currsize=10)

Parametrized Decorator

from functools import wraps

def debug(print_result=False):
    def decorator(func):
        @wraps(func)
        def out(*args, **kwargs):
            result = func(*args, **kwargs)
            print(func.__name__, result if print_result else '')
            return result
        return out
    return decorator

@debug(print_result=True)
def add(x, y):
    return x + y

Class

class <name>:
    def __init__(self, a):
        self.a = a
    def __repr__(self):
        class_name = type(self).__name__
        return f'{class_name}({self.a!r})'
    def __str__(self):
        return str(self.a)

    @classmethod
    def get_class_name(cls):
        return cls.__name__

Constructor Overloading

class <name>:
    def __init__(self, a=None):
        self.a = a

Inheritance

class Person:
    def __init__(self, name, age):
        self.name = name
        self.age  = age

class Employee(Person):
    def __init__(self, name, age, staff_num):
        super().__init__(name, age)
        self.staff_num = staff_num

Comparable

• If eq() method is not overridden, it returns 'id(self) == id(other)', which is the same as 'self is other'.
• That means all objects compare not equal by default.

class MyComparable:
    def __init__(self, a):
        self.a = a
    def __eq__(self, other):
        if isinstance(other, type(self)):
            return self.a == other.a
        return False

Hashable

• Hashable object needs both hash() and eq() methods and it's hash value should never change.
• Hashable objects that compare equal must have the same hash value, meaning default hash() that returns 'id(self)' will not do.
• That is why Python automatically makes classes unhashable if you only implement eq().

class MyHashable:
    def __init__(self, a):
        self.__a = copy.deepcopy(a)
    @property
    def a(self):
        return self.__a
    def __eq__(self, other):
        if isinstance(other, type(self)):
            return self.a == other.a
        return False
    def __hash__(self):
        return hash(self.a)

Sequence

• Methods do not depend on each other, so they can be skipped if not needed.
• Any object with defined getitem() is considered iterable, even if it lacks iter().

class MySequence:
    def __init__(self, a):
        self.a = a
    def __len__(self):
        return len(self.a)
    def __getitem__(self, i):
        return self.a[i]
    def __iter__(self):
        for el in self.a:
            yield el

Callable

class Counter:
    def __init__(self):
        self.a = 0
    def __call__(self):
        self.a += 1
        return self.a

Copy

from copy import copy, deepcopy
<object> = copy(<object>)
<object> = deepcopy(<object>)

Enum

from enum import Enum, auto

class <enum_name>(Enum):
    <member_name_1> = <value_1>
    <member_name_2> = <value_2_a>, <value_2_b>
    <member_name_3> = auto()

    @classmethod
    def get_member_names(cls):
        return [a.name for a in cls.__members__.values()]

<member> = <enum>.<member_name>
<member> = <enum>['<member_name>']
<member> = <enum>(<value>)
name     = <member>.name
value    = <member>.value

list_of_members = list(<enum>)
member_names    = [a.name for a in <enum>]
member_values   = [a.value for a in <enum>]
random_member   = random.choice(list(<enum>))

Inline

Cutlery = Enum('Cutlery', ['fork', 'knife', 'spoon'])
Cutlery = Enum('Cutlery', 'fork knife spoon')
Cutlery = Enum('Cutlery', {'fork': 1, 'knife': 2, 'spoon': 3})

Functions can not be values, so they must be wrapped:

from functools import partial
LogicOp = Enum('LogicOp', {'AND': partial(lambda l, r: l and r),
                           'OR' : partial(lambda l, r: l or r)})

Exceptions

while True:
    try:
        x = int(input('Please enter a number: '))
    except ValueError:
        print('Oops!  That was no valid number.  Try again...')
    else:
        print('Thank you.')
        break

Raising exception:

raise ValueError('A very specific message!')

Finally

>>> try:
...     raise KeyboardInterrupt
... finally:
...     print('Goodbye, world!')
Goodbye, world!
Traceback (most recent call last):
  File "<stdin>", line 2, in <module>
KeyboardInterrupt

System

Command Line Arguments

import sys
script_name = sys.argv[0]
arguments   = sys.argv[1:]

Print Function

print(<el_1>, ..., sep=' ', end='\n', file=sys.stdout, flush=False)

• Use 'file=sys.stderr' for errors.

Pretty print:

>>> from pprint import pprint
>>> pprint(dir())
['__annotations__',
 '__builtins__',
 '__doc__', ...]

Input Function

• Reads a line from user input or pipe if present.
• The trailing newline gets stripped.
• The prompt string is printed to standard output before reading input.

<str> = input(prompt=None)

Prints lines until EOF:

while True:
    try:
        print(input())
    except EOFError:
        break

Open Function

Opens file and returns a corresponding file object.

<file> = open(<path>, mode='r', encoding=None)

Modes:

• 'r' - Read (default).
• 'w' - Write (truncate).
• 'x' - Write or fail if the file already exists.
• 'a' - Append.
• 'w+' - Read and write (truncate).
• 'r+' - Read and write from the beginning.
• 'a+' - Read and write from the end.
• 'b' - Binary mode.
• 't' - Text mode (default).

Read Text from File:

def read_file(filename):
    with open(filename, encoding='utf-8') as file:
        return file.readlines()

Write Text to File:

def write_to_file(filename, text):
    with open(filename, 'w', encoding='utf-8') as file:
        file.write(text)

Command Execution

import os
<str> = os.popen(<command>).read()

或:

>>> import subprocess
>>> a = subprocess.run(['ls', '-a'], stdout=subprocess.PIPE)
>>> a.stdout
b'.\n..\nfile1.txt\nfile2.txt\n'
>>> a.returncode
0

Recursion Limit

>>> import sys
>>> sys.getrecursionlimit()
1000
>>> sys.setrecursionlimit(5000)

Path

from os import path, listdir
<bool> = path.exists(<path>)
<bool> = path.isfile(<path>)
<bool> = path.isdir(<path>)
<list> = listdir(<path>)

>>> from glob import glob
>>> glob('../*.gif')
['1.gif', 'card.gif']

Pathlib

This module offers classes representing filesystem paths with semantics appropriate for different operating systems.

from pathlib import Path
pwd    = Path()
<Path> = Path('<path>' [, '<path>', <Path>, ...])
<Path> = <Path> / '<dir>' / '<file>'

<iter>  = <Path>.iterdir()          # Returns all files in a dir.
<iter>  = <Path>.glob('<pattern>')  # Returns all matches.
<Path>  = <Path>.resolve()          # Makes path absolute.
<bool>  = <Path>.exists()
<bool>  = <Path>.is_dir()
<file>  = <Path>.open()

<str>   = str(<Path>)               # Returns path as string.
<str>   = <Path>.name               # Final component.
<str>   = <Path>.stem               # Final component without extension.
<str>   = <Path>.suffix             # Final component's extension.
<Path>  = <Path>.parent             # Path without final component.
<tuple> = <Path>.parts              # All components as strings.

JSON

import json
<str>    = json.dumps(<object>, ensure_ascii=True, indent=None)
<object> = json.loads(<str>)

To preserve order:

from collections import 或deredDict
<object> = json.loads(<str>, object_pairs_hook=或deredDict)

Read File

def read_json_file(filename):
    with open(filename, encoding='utf-8') as file:
        return json.load(file)

Write to File

def write_to_json_file(filename, an_object):
    with open(filename, 'w', encoding='utf-8') as file:
        json.dump(an_object, file, ensure_ascii=False, indent=2)

Pickle

import pickle
<bytes>  = pickle.dumps(<object>)
<object> = pickle.loads(<bytes>)

Read Object from File

def read_pickle_file(filename):
    with open(filename, 'rb') as file:
        return pickle.load(file)

Write Object to File

def write_to_pickle_file(filename, an_object):
    with open(filename, 'wb') as file:
        pickle.dump(an_object, file)

SQLite

import sqlite3
db = sqlite3.connect(<filename>)
...
db.close()

Read

cursor = db.execute(<query>)
if cursor:
    <tuple> = cursor.fetchone()  # First row.
    <list>  = cursor.fetchall()  # Remaining rows.

Write

db.execute(<query>)
db.commit()

Bytes

Bytes object is immutable sequence of single bytes. Mutable version is called bytearray.

<bytes> = b'<str>'
<int>   = <bytes>[<index>]
<bytes> = <bytes>[<slice>]
<bytes> = b''.join(<coll_of_bytes>)

Encode

<bytes> = <str>.encode(encoding='utf-8')
<bytes> = <int>.to_bytes(length, byteorder='big|little', signed=False)
<bytes> = bytes.fromhex(<hex>)

Decode

<str>   = <bytes>.decode('utf-8')
<int>   = int.from_bytes(<bytes>, byteorder='big|little', signed=False)
<hex>   = <bytes>.hex()

Read Bytes from File

def read_bytes(filename):
    with open(filename, 'rb') as file:
        return file.read()

Write Bytes to File

def write_bytes(filename, bytes_obj):
    with open(filename, 'wb') as file:
        file.write(bytes_obj)

Struct

• Module that performs conversions between Python values and a C struct, represented as a Python bytes object.
• Machine’s native type sizes and byte order are used by default.

from struct import pack, unpack, calcsize
<bytes> = pack('<format>', <value_1> [, <value_2>, ...])
<tuple> = unpack('<format>', <bytes>)

Example

>>> pack('>hhl', 1, 2, 3)
b'\x00\x01\x00\x02\x00\x00\x00\x03'
>>> unpack('>hhl', b'\x00\x01\x00\x02\x00\x00\x00\x03')
(1, 2, 3)
>>> calcsize('>hhl')
8

Format

For standard sizes start format string with:

• '=' - native byte order
• '<' - little-endian
• '>' - big-endian

Use capital letter for unsigned type. Standard size in brackets:

• 'x' - pad byte
• 'c' - char (1)
• 'h' - short (2)
• 'i' - int (4)
• 'l' - long (4)
• 'q' - long long (8)
• 'f' - float (4)
• 'd' - double (8)

Array

List that can only hold elements of predefined type. Available types are listed above.

from array import array
<array> = array(<typecode> [, <collection>])

Memory View

Used for accessing the internal data of an object that supports the buffer protocol.

<memoryview> = memoryview(<bytes> / <bytearray> / <array>)
<memoryview>.release()

Deque

A thread-safe list with efficient appends and pops from either side. Pronounced “deck”.

from collections import deque
<deque> = deque(<collection>, maxlen=None)

<deque>.appendleft(<el>)
<deque>.extendleft(<collection>)  # Collection gets reversed.
<el> = <deque>.popleft()
<deque>.rotate(n=1)               # Rotates elements to the right.

Threading

from threading import Thread, RLock

Thread

thread = Thread(target=<function>, args=(<first_arg>, ))
thread.start()
...
thread.join()

Lock

lock = RLock()
lock.acquire()
...
lock.release()

Hashlib

>>> import hashlib
>>> hashlib.md5(<str>.encode()).hexdigest()
'33d0eba106da4d3ebca17fcd3f4c3d77'

Itertools

• Every function returns an iterator and can accept any collection and/or iterator.
• If you want to print the iterator, you need to pass it to the list() function!

from itertools import *

Combinatoric iterators

>>> combinations('abc', 2)
[('a', 'b'), ('a', 'c'), ('b', 'c')]

>>> combinations_with_replacement('abc', 2)
[('a', 'a'), ('a', 'b'), ('a', 'c'),
 ('b', 'b'), ('b', 'c'),
 ('c', 'c')]

>>> permutations('abc', 2)
[('a', 'b'), ('a', 'c'),
 ('b', 'a'), ('b', 'c'),
 ('c', 'a'), ('c', 'b')]

>>> product('ab', [1, 2])
[('a', 1), ('a', 2),
 ('b', 1), ('b', 2)]

>>> product([0, 1], repeat=3)
[(0, 0, 0), (0, 0, 1), (0, 1, 0), (0, 1, 1),
 (1, 0, 0), (1, 0, 1), (1, 1, 0), (1, 1, 1)]

Infinite iterators

>>> i = count(5, 2)
>>> next(i), next(i), next(i)
(5, 7, 9)

>>> a = cycle('abc')
>>> [next(a) for _ in range(10)]
['a', 'b', 'c', 'a', 'b', 'c', 'a', 'b', 'c', 'a']

>>> repeat(10, 3)
[10, 10, 10]

Iterators

>>> chain([1, 2], range(3, 5))
[1, 2, 3, 4]

>>> compress('abc', [True, 0, 1])
['a', 'c']

>>> # islice(<collection>, from_inclusive, to_exclusive)
>>> islice([1, 2, 3], 1, None)
[2, 3]

>>> people = [{'id': 1, 'name': 'Bob'},
              {'id': 2, 'name': 'Bob'},
              {'id': 3, 'name': 'Peter'}]
>>> groups = groupby(people, key=lambda a: a['name'])
>>> {name: list(group) for name, group in groups}
{'Bob':   [{'id': 1, 'name': 'Bob'},
           {'id': 2, 'name': 'Bob'}],
 'Peter': [{'id': 3, 'name': 'Peter'}]}

Introspection and Metaprograming

Inspecting code at runtime and code that generates code. You can:

• Look at the attributes
• Set new attributes
• Create functions dynamically
• Traverse the parent classes
• Change values in the class

Variables

<list> = dir()      # Names of in-scope variables.
<dict> = locals()   # Dict of local variables. Also vars().
<dict> = globals()  # Dict of global variables.

Attributes

class Z:
    def __init__(self):
        self.a = 'abcde'
        self.b = 12345

>>> z = Z()

>>> vars(z)
{'a': 'abcde', 'b': 12345}

>>> getattr(z, 'a')
'abcde'

>>> hasattr(z, 'c')
False

>>> setattr(z, 'c', 10)

Parameters

from inspect import signature
sig          = signature(<function>)
no_of_params = len(sig.parameters)
param_names  = list(sig.parameters.keys())

Type

Type is the root class. If only passed the object it returns it's type. Otherwise it creates a new class (and not the instance!).

type(<class_name>, <parents_tuple>, <attributes_dict>)

>>> Z = type('Z', (), {'a': 'abcde', 'b': 12345})
>>> z = Z()

Meta Class

Class that creates class.

def my_meta_class(name, parents, attrs):
    attrs['a'] = 'abcde'
    return type(name, parents, attrs)

或:

class MyMetaClass(type):
    def __new__(cls, name, parents, attrs):
        attrs['a'] = 'abcde'
        return type.__new__(cls, name, parents, attrs)

Metaclass Attribute

When class is created it checks if it has metaclass defined. If not, it recursively checks if any of his parents has it defined and eventually comes to type.

class MyClass(metaclass=MyMetaClass):
    def __init__(self):
        self.b = 12345

Operator

from operator import add, sub, mul, truediv, floordiv, mod, pow, neg, abs, \
                     eq, ne, lt, le, gt, ge, \
                     not_, and_, or_, \
                     itemgetter, attrgetter, methodcaller

import operator as op
product_of_elems = functools.reduce(op.mul, <list>)
sorted_by_second = sorted(<list>, key=op.itemgetter(1))
sorted_by_both   = sorted(<list>, key=op.itemgetter(1, 0))
LogicOp          = enum.Enum('LogicOp', {'AND': op.and_, 'OR' : op.or_})
last_el          = op.methodcaller('pop')(<list>)

Eval

Basic

>>> from ast import literal_eval
>>> literal_eval('1 + 2')
3
>>> literal_eval('[1, 2, 3]')
[1, 2, 3]
>>> ast.literal_eval('abs(1)')
ValueError: malformed node or string

Using Abstract Syntax Trees

import ast
from ast import Num, BinOp, UnaryOp
import operator as op

LEGAL_OPERATORS = {ast.Add:    op.add,
                   ast.Sub:    op.sub,
                   ast.Mult:   op.mul,
                   ast.Div:    op.truediv,
                   ast.Pow:    op.pow,
                   ast.BitXor: op.xor,
                   ast.USub:   op.neg}

def evaluate(expression):
    root = ast.parse(expression, mode='eval')
    return eval_node(root.body)

def eval_node(node):
    node_type = type(node)
    if node_type == Num:
        return node.n
    if node_type not in [BinOp, UnaryOp]:
        raise TypeError(node)
    operator_type = type(node.op)
    if operator_type not in LEGAL_OPERATORS:
        raise TypeError(f'Illegal operator {node.op}')
    operator = LEGAL_OPERATORS[operator_type]
    if node_type == BinOp:
        left, right = eval_node(node.left), eval_node(node.right)
        return operator(left, right)
    elif node_type == UnaryOp:
        operand = eval_node(node.operand)
        return operator(operand)

>>> evaluate('2 ^ 6')
4
>>> evaluate('2 ** 6')
64
>>> evaluate('1 + 2 * 3 ** (4 ^ 5) / (6 + -7)')
-5.0

Coroutine

• Similar to Generator, but Generator pulls data through the pipe with iteration, while Coroutine pushes data into the pipeline with send().
• Coroutines provide more powerful data routing possibilities than iterators.
• If you built a collection of simple data processing components, you can glue them together into complex arrangements of pipes, branches, merging, etc.

Helper Decorator

• All coroutines must be "primed" by first calling next().
• Remembering to call next() is easy to forget.
• Solved by wrapping coroutines with a decorator:

def coroutine(func):
    def out(*args, **kwargs):
        cr = func(*args, **kwargs)
        next(cr)
        return cr
    return out

Pipeline Example

def reader(target):
    for i in range(10):
        target.send(i)
    target.close()

@coroutine
def adder(target):
    while True:
        item = (yield)
        target.send(item + 100)

@coroutine
def printer():
    while True:
        item = (yield)
        print(item)

reader(adder(printer()))  # 100, 101, ..., 109

Libraries

Progress Bar

# $ pip3 install tqdm
from tqdm import tqdm
from time import sleep
for i in tqdm([1, 2, 3]):
    sleep(0.2)
for i in tqdm(range(100)):
    sleep(0.02)

Plot

# $ pip3 install matplotlib
from matplotlib import pyplot
pyplot.plot(<data_1> [, <data_2>, ...])
pyplot.savefig(<filename>, transparent=True)
pyplot.show()

Argparse

from argparse import ArgumentParser
desc   = 'calculate X to the power of Y'
parser = ArgumentParser(description=desc)
group  = parser.add_mutually_exclusive_group()
group.add_argument('-v', '--verbose', action='store_true')
group.add_argument('-q', '--quiet',   action='store_true')
parser.add_argument('x', type=int, help='the base')
parser.add_argument('y', type=int, help='the exponent')
args   = parser.parse_args()
answer = args.x ** args.y

if args.quiet:
    print(answer)
elif args.verbose:
    print(f'{args.x} to the power {args.y} equals {answer}')
else:
    print(f'{args.x}^{args.y} == {answer}')

Table

Prints CSV file as ASCII table:

# $ pip3 install tabulate
import csv
from tabulate import tabulate
with open(<filename>, encoding='utf-8') as file:
    lines   = csv.reader(file, delimiter=';')
    headers = [header.title() for header in next(lines)]
    table   = tabulate(lines, headers)
    print(table)

Curses

# $ pip3 install curses
from curses import wrapper

def main():
    wrapper(draw)

def draw(screen):
    screen.clear()
    screen.addstr(0, 0, 'Press ESC to quit.')
    while screen.getch() != 27:
        pass

def get_border(screen):
    from collections import namedtuple
    P = namedtuple('P', 'x y')
    height, width = screen.getmaxyx()
    return P(width - 1, height - 1)

Image

Creates PNG image of greyscale gradient:

# $ pip3 install pillow
from PIL import Image
width  = 100
height = 100
size   = width * height
pixels = [255 * i/size for i in range(size)]

img = Image.new('L', (width, height), 'white')
img.putdata(pixels)
img.save('test.png')

Modes

• '1' - 1-bit pixels, black and white, stored with one pixel per byte.
• 'L' - 8-bit pixels, greyscale.
• 'RGB' - 3x8-bit pixels, true color.
• 'RGBA' - 4x8-bit pixels, true color with transparency mask.
• 'HSV' - 3x8-bit pixels, Hue, Saturation, Value color space.

Audio

Saves a list of floats with values between -1 and 1 to a WAV file:

import wave, struct
samples = [struct.pack('<h', int(a * 30000)) for a in <list>]
wf = wave.open('test.wav', 'wb')
wf.setnchannels(1)
wf.setsampwidth(2)
wf.setframerate(44100)
wf.writeframes(b''.join(samples))
wf.close()

Plays Popcorn

# pip3 install simpleaudio
import simpleaudio, math, struct
from itertools import chain, repeat
F  = 44100
S1 = '71♪,69,,71♪,66,,62♪,66,,59♪,,,'
S2 = '71♪,73,,74♪,73,,74,,71,,73♪,71,,73,,69,,71♪,69,,71,,67,,71♪,,,'
get_pause = lambda seconds: repeat(0, int(seconds * F))
sin_f     = lambda i, hz: math.sin(i * 2 * math.pi * hz / F)
get_wave  = lambda hz, seconds: (sin_f(i, hz) for i in range(int(seconds * F)))
get_hz    = lambda n: 8.176 * 2 ** (int(n) / 12)
parse_n   = lambda note: (get_hz(note[:2]), 0.25 if len(note) > 2 else 0.125)
get_note  = lambda note: get_wave(*parse_n(note)) if note else get_pause(0.125)
samples_f = chain.from_iterable(get_note(n) for n in f'{S1}{S1}{S2}'.split(','))
samples_b = b''.join(struct.pack('<h', int(a * 30000)) for a in samples_f)
simpleaudio.play_buffer(samples_b, 1, 2, F)

Url

from urllib.parse import quote, quote_plus, unquote, unquote_plus

Encode

>>> quote("Can't be in URL!")
'Can%27t%20be%20in%20URL%21'
>>> quote_plus("Can't be in URL!")
'Can%27t+be+in+URL%21'

Decode

>>> unquote('Can%27t+be+in+URL%21')
"Can't+be+in+URL!"
>>> unquote_plus('Can%27t+be+in+URL%21')
"Can't be in URL!"

Scraping

# $ pip3 install requests beautifulsoup4
>>> import requests
>>> from bs4 import BeautifulSoup
>>> url   = 'https://en.wikipedia.org/wiki/Python_(programming_language)'
>>> page  = requests.get(url)
>>> doc   = BeautifulSoup(page.text, 'html.parser')
>>> table = doc.find('table', class_='infobox vevent')
>>> rows  = table.find_all('tr')
>>> link  = rows[11].find('a')['href']
>>> ver   = rows[6].find('div').text.split()[0]
>>> link, ver
('https://www.python.org/', '3.7.2')

Web

# $ pip3 install bottle
from bottle import run, route, post, template, request, response
import json

Run

run(host='localhost', port=8080)
run(host='0.0.0.0', port=80, server='cherrypy')

Static Request

@route('/img/<image>')
def send_image(image):
    return static_file(image, 'images/', mimetype='image/png')

Dynamic Request

@route('/<sport>')
def send_page(sport):
    return template('<h1>{{title}}</h1>', title=sport)

REST Request

@post('/odds/<sport>')
def odds_handler(sport):
    team = request.forms.get('team')
    home_odds, away_odds = 2.44, 3.29
    response.headers['Content-Type'] = 'application/json'
    response.headers['Cache-Control'] = 'no-cache'
    return json.dumps([team, home_odds, away_odds])

Test:

# $ pip3 install requests
>>> import requests
>>> url = 'http://localhost:8080/odds/football'
>>> data = {'team': 'arsenal f.c.'}
>>> response = requests.post(url, data=data)
>>> response.json()
['arsenal f.c.', 2.44, 3.29]

Profile

Basic

from time import time
start_time = time()  # Seconds since Epoch.
...
duration = time() - start_time

High Performance

from time import perf_counter as pc
start_time = pc()    # Seconds since restart.
...
duration = pc() - start_time

Timing a Snippet

from timeit import timeit
timeit('"-".join(str(a) for a in range(100))',
       number=10000, globals=globals(), setup='pass')

Line Profiler

# $ pip3 install line_profiler
@profile
def main():
    a = [*range(10000)]
    b = {*range(10000)}
main()

Usage:

$ kernprof -lv test.py
Line #      Hits         Time  Per Hit   % Time  Line Contents
==============================================================
     1                                           @profile
     2                                           def main():
     3         1       1128.0   1128.0     27.4      a = [*range(10000)]
     4         1       2994.0   2994.0     72.6      b = {*range(10000)}

Call Graph

Generates a PNG image of call graph with highlighted bottlenecks:

# $ pip3 install pycallgraph
from pycallgraph import output, PyCallGraph
from datetime import datetime
time_str = datetime.now().strftime('%Y%m%d%H%M%S')
filename = f'profile-{time_str}.png'
drawer = output.GraphvizOutput(output_file=filename)
with PyCallGraph(output=drawer):
    <code_to_be_profiled>

NumPy

Array manipulation mini language. Can run up to 100 times faster than equivalent Python code.

# $ pip3 install numpy
import numpy as np

<array> = np.array(<list>)
<array> = np.arange(from_inclusive, to_exclusive, step_size)
<array> = np.ones(<shape>)
<array> = np.random.randint(from_inclusive, to_exclusive, <shape>)

<array>.shape = <shape>
<view>  = <array>.reshape(<shape>)
<view>  = np.broadcast_to(<array>, <shape>)

<array> = <array>.sum(<axis>)
indexes = <array>.argmin(<axis>)

• Shape is a tuple of dimension sizes.
• Axis is an index of dimension that gets collapsed.

Indexing

<el>       = <2d_array>[0, 0]        # First element.
<1d_view>  = <2d_array>[0]           # First row.
<1d_view>  = <2d_array>[:, 0]        # First column. Also [..., 0].
<3d_view>  = <2d_array>[None, :, :]  # Expanded by dimension of size 1.

<1d_array> = <2d_array>[<1d_row_indexes>, <1d_column_indexes>]
<2d_array> = <2d_array>[<2d_row_indexes>, <2d_column_indexes>]

<2d_bools> = <2d_array> > 0
<1d_array> = <2d_array>[<2d_bools>]

• If row and column indexes differ in shape, they are combined with broadcasting.

Broadcasting

Broadcasting is a set of rules by which NumPy functions operate on arrays of different sizes and/or dimensions.

left  = [[0.1], [0.6], [0.8]]  # Shape: (3, 1)
right = [ 0.1 ,  0.6 ,  0.8 ]  # Shape: (3)

1. If array shapes differ, left-pad the smaller shape with ones:

left  = [[0.1], [0.6], [0.8]]  # Shape: (3, 1)
right = [[0.1 ,  0.6 ,  0.8]]  # Shape: (1, 3) <- !

2. If any dimensions differ in size, expand the ones that have size 1 by duplicating their elements:

left  = [[0.1, 0.1, 0.1], [0.6, 0.6, 0.6], [0.8, 0.8, 0.8]]  # Shape: (3, 3) <- !
right = [[0.1, 0.6, 0.8], [0.1, 0.6, 0.8], [0.1, 0.6, 0.8]]  # Shape: (3, 3) <- !

3. If neither non-matching dimension has size 1, rise an error.

例子

For each point returns index of its nearest point ([0.1, 0.6, 0.8] => [1, 2, 1]):

>>> points = np.array([0.1, 0.6, 0.8])
[ 0.1,  0.6,  0.8]
>>> wrapped_points = points.reshape(3, 1)
[[ 0.1],
 [ 0.6],
 [ 0.8]]
>>> distances = wrapped_points - points
[[ 0. , -0.5, -0.7],
 [ 0.5,  0. , -0.2],
 [ 0.7,  0.2,  0. ]]
>>> distances = np.abs(distances)
[[ 0. ,  0.5,  0.7],
 [ 0.5,  0. ,  0.2],
 [ 0.7,  0.2,  0. ]]
>>> i = np.arange(3)
[0, 1, 2]
>>> distances[i, i] = np.inf
[[ inf,  0.5,  0.7],
 [ 0.5,  inf,  0.2],
 [ 0.7,  0.2,  inf]]
>>> distances.argmin(1)
[1, 2, 1]

Basic Script Template

#!/usr/bin/env python3
#
# Usage: .py
#

from collections import namedtuple
from enum import Enum
import re
import sys


def main():
    pass


###
##  UTIL
#

def read_file(filename):
    with open(filename, encoding='utf-8') as file:
        return file.readlines()


if __name__ == '__main__':
    main()