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Python

Table of Contents​

Hello World​

python 2​

print "Hello World"

python 3​

print("Hello World")  # "Hello World\n"
print("Hello", "World", sep="/")  # "Hello/World"
print("Hello World", end="")  # "Hello World"

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Comments​

# Single line comment

"""
multi-line comments
"""

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Program Entry Point​

if __name__ === "__main__":
    # do something

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Collections​

List​

import itertools
import functools

list = list[from_inclusive : to_exclusive : ±step_size]

list.append(el)  # Or: list += [el]
list.extend(collection)  # Or: 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]))

# Flatten list
list_example = [[1, 2, 3], [4, 5, 6], [7], [8, 9]]
flatter_list = list(itertools.chain.from_iterable(list_example))  # [1, 2, 3, 4, 5, 6, 7, 8, 9]

product_of_elems = functools.reduce(lambda out, el: out * el, collection)

list_of_chars    = list(str)

int = list.count(el)  # Returns number of occurrences, also works on strings

index = list.index(el)  # Returns index of first occurrence or raises ValueError

list.insert(index, el)  # Inserts item at index and moves the rest to the right

el = list.pop([index])  # Removes and returns item at index or from the end

list.remove(el)  # Removes first occurrence of item or raises ValueError

list.clear()  # Removes all items, also works on dictionary and set

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Dictionary​

view = dict.keys()  # Coll. of keys that reflects changes
view = dict.values()  # Coll. of values that reflects changes
view = dict.items()  # Coll. of key-value tuples that reflects chgs

value  = dict.get(key, default=None)  # Returns default if key is missing
value  = dict.setdefault(key, default=None)  # Returns and writes default if key is missing
dict = collections.defaultdict(type)  # Creates a dict with default value of type
dict = collections.defaultdict(lambda: 1)  # Creates a dict with default value 1

dict = dict(collection)  # Creates a dict from coll. of key-value pairs
dict = dict(zip(keys, values))  # Creates a dict from two collections
dict = dict.fromkeys(keys [, value])  # Creates a dict from collection of keys

dict.update(dict)  # Adds items. Replaces ones with matching keys
value = dict.pop(key)  # Removes item or raises KeyError
{k for k, v in dict.items() if v == value}  # Returns set of keys that point to the value
{k: v for k, v in dict.items() if k in keys}  # Returns a dictionary, filtered by keys
  • Counter
from collections import Counter

colors = ['blue', 'blue', 'blue', 'red', 'red']
counter = Counter(colors)
counter['yellow'] += 1  # Counter({'blue': 3, 'red': 2, 'yellow': 1})

counter.most_common()[0]  # ('blue', 3)

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Set​

set = set()

set.add(el)  # Or: set |= {el}
set.update(collection)  # Or: set |= set

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

el = set.pop()  # Raises KeyError if empty
set.remove(el)  # Raises KeyError if missing
set.discard(el)  # Doesn't raise an error
  • Frozen Set
    • Is immutable and hashable
    • That means it can be used as a key in a dictionary or as an element in a set
frozenset = frozenset(collection)

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Tuple​

  • Tuple is an immutable and hashable list
tuple = ()
tuple = (el, )
tuple = (el_1, el_2 [, ...])
  • Named Tuple
    • Tuple's subclass with named elements
from collections import namedtuple

Point = 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  # ('x', 'y')
Point._fields  # ('x', 'y')

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Range​

range = range(to_exclusive)
range = range(from_inclusive, to_exclusive)
range = range(from_inclusive, to_exclusive, ±step_size)

from_inclusive = range.start
to_exclusive   = range.stop

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Enumerate​

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

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Iterator​

iter = iter(collection)  # `iter(iter)` returns unmodified iterator
iter = iter(function, to_exclusive)  # A sequence of return values until 'to_exclusive'
el   = next(iter [, default])  # Raises StopIteration or returns 'default' on end
list = list(iter)  # Returns a list of iterator's remaining elements
  • Itertools
from itertools import count, repeat, cycle, chain, islice

iter = count(start=0, step=1)  # Returns updated value endlessly. Accepts floats
iter = repeat(el [, times])  # Returns element endlessly or 'times' times
iter = cycle(collection)  # Repeats the sequence endlessly

iter = chain(coll_1, coll_2 [, ...])  # Empties collections in order
iter = chain.from_iterable(collection)  # Empties collections inside a collection in order

iter = islice(collection, to_exclusive)
iter = islice(collection, from_inclusive, to_exclusive [, +step_size])

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Generator​

  • Any function that contains a yield statement returns a generator
  • Generators and iterators are interchangeable
def count(start, step):
    while True:
        yield start
        start += step


counter = count(10, 2)
next(counter), next(counter), next(counter)  # (10, 12, 14)

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Types​

Type​

  • Everything is an object
  • Every object has a type
  • Type and class are synonymous
type = type(el)  # Or: el.__class__
bool = isinstance(el, type)  # Or: issubclass(type(el), type)

type('a'), 'a'.__class__, str  # (class 'str', class 'str', class 'str')
  • Some types do not have built-in names, so they must be imported
from types import FunctionType, MethodType, LambdaType, GeneratorType
  • Abstract Base Classes
    • Each abstract base class specifies a set of virtual subclasses
    • These classes are then recognized by isinstance() and issubclass() as subclasses of the ABC, although they are really not
from collections.abc import Sequence, Collection, Iterable

isinstance([1, 2, 3], Iterable)  # True
SequenceCollectionIterable
list, range, str☑☑☑
dict, set☑☑
iter☑
from numbers import Integral, Rational, Real, Complex, Number

isinstance(123, Number)  # True
IntegralRationalRealComplexNumber
int☑☑☑☑☑
fractions.Fraction☑☑☑☑
float☑☑☑
complex☑☑
decimal.Decimal☑

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String​

str1 = "test string"
str1.capitalize()  # "Test string"
str1.upper()  # "TEST STRING"
str1.lower()  # "test string"
str1.title()  # "Test String"


str = str.strip()  # Strips all whitespace characters from both ends
str = str.strip('chars')  # Strips all passed characters from both ends
str = str.lstrip()  # Strips all whitespace characters from left end
str = str.rstrip()  # Strips all whitespace characters from right end

list = str.split()  # Splits on one or more whitespace characters
list = str.split(sep=None, maxsplit=-1)  # Splits on 'sep' str at most 'maxsplit' times.
list = str.splitlines(keepends=False)  # Splits on \n,\r,\r\n. Keeps them if 'keepends'
str  = str.join(coll_of_strings)  # Joins elements using string as separator

bool = sub_str in str  # Checks if string contains a substring
bool = str.startswith(sub_str)  # Pass tuple of strings for multiple options
bool = str.endswith(sub_str)  # Pass tuple of strings for multiple options
int = str.find(sub_str)  # Returns start index of first match or -1
int = str.index(sub_str)  # Same but raises ValueError if missing

str = str.replace(old, new [, count])   # Replaces 'old' with 'new' at most 'count' times

txt = "Hello Sam!"
mytable = txt.maketrans("S", "P")  # Create a mapping table
# use mapping table in the translate() method to replace any "S" characters with a "P" character
txt.translate(mytable)  # "Hello Pam!"

str = chr(int)  # Converts int to Unicode char
int = ord(str)  # Converts Unicode char to int
  • Property Methods
!#$%...a-zA-Z1/4 1/2 3/4sup2/supsup3/supsup1/sup0-9
isprintable()☑☑☑☑☑
isalnum()☑☑☑☑
isnumeric()☑☑☑
isdigit()☑☑
isdecimal()☑
str1 = ""
str1.isspace()  # False

str2 = " t "
str2.isspace()  # False

str3 = " "
str3.isspace()  # True

# checks for \t\n\r\f\v...
str4 = " \n"
str4.isspace()  # True

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Regular Expression​

  • Argument flags=re.IGNORECASE can be used with all functions
  • Argument flags=re.MULTILINE makes ^ and $ match the start/end of each line
  • Argument flags=re.DOTALL makes dot also accept the \n
  • Use r\1 or \\1 for backreference
  • Add ? after an operator to make it non-greedy
import re

str = re.sub(regex, new, text, count=0)  # Substitutes all occurrences with 'new'
list = re.findall(regex, text)  # Returns all occurrences as strings
list = re.split(regex, text, maxsplit=0)  # Use brackets in regex to include the matches

# Search() and match() return None if they can't find a match
Match = re.search(regex, text)  # Searches for first occurrence of the pattern
Match = re.match(regex, text)  # Searches only at the beginning of the text

iter = re.finditer(regex, text)  # Returns all occurrences as match objects
  • Match Object
str = Match.group()  # Returns the whole match, also group(0)
str = Match.group(1)  # Returns part in the first bracket
tuple = Match.groups()  # Returns all bracketed parts
int = Match.start()  # Returns start index of the match
int = Match.end()  # Returns exclusive end index of the match
  • Special Sequences
    • By default digits, alphanumerics and whitespaces from all alphabets are matched, unless flags=re.ASCII argument is used
    • Use a capital letter for negation
'\d' == '[0-9]'  # Matches any digit
'\w' == '[a-zA-Z0-9_]'  # Matches any alphanumeric
'\s' == '[\t\n\r\f\v]'  # Matches any whitespace

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Format​

str = f'{el_1}, {el_2}'
str = '{}, {}'.format(el_1, el_2)
  • Attributes
from collections import namedtuple

Person = namedtuple('Person', 'name height')
person = Person('Jean-Luc', 187)
f'{person.height}'  # '187'
'{p.height}'.format(p=person)  # '187'
  • General Options
str = "test
f"{str:10}"  # 'test      '
f"{str:^10}"  # '   test   '
f"{str:10}"  # '      test'
f"{str:.10}"  # 'test......'
f"{str:0}"  # 'test'
  • Strings
    • !r calls object's repr() method, instead of str(), to get a string
f"{'abcde'!r:10}"  # "'abcde'   "
f"{'abcde':10.3}"  # 'abc       '
f"{'abcde':.3}"  # 'abc'
  • Numbers
f"{123456:10,}"  # '   123,456'
f"{123456:10_}"  # '   123_456'
f"{123456:+10}"  # '   +123456'
f"{-123456:=10}"  # '-   123456'
f"{123456:}"  # '123456'
f"{-123456:}"  # '-123456'
  • Floats
f"{1.23456:10.3}"  # '      1.23'
f"{1.23456:10.3f}"  # '     1.235'
f"{1.23456:10.3e}"  # ' 1.235e+00'
f"{1.23456:10.3%}"  # '  123.456%'
f"{float}"f"{float:f}"f"{float:e}"f"{float:%}"
0.000056789'5.6789e-05''0.000057''5.678900e-05''0.005679%'
0.00056789'0.00056789''0.000568''5.678900e-04''0.056789%'
0.0056789'0.0056789''0.005679''5.678900e-03''0.567890%'
0.056789'0.056789''0.056789''5.678900e-02''5.678900%'
0.56789'0.56789''0.567890''5.678900e-01''56.789000%'
5.6789'5.6789''5.678900''5.678900e+00''567.890000%'
56.789'56.789''56.789000''5.678900e+01''5678.900000%'
567.89'567.89''567.890000''5.678900e+02''56789.000000%'
f"{float:.2}"f"{float:.2f}"f"{float:.2e}"f"{float:.2%"
0.000056789'5.7e-05''0.00''5.68e-05''0.01%'
0.00056789'0.00057''0.00''5.68e-04''0.06%'
0.0056789'0.0057''0.01''5.68e-03''0.57%'
0.056789'0.057''0.06''5.68e-02''5.68%'
0.56789'0.57''0.57''5.68e-01''56.79%'
5.6789'5.7''5.68''5.68e+00''567.89%'
56.789'5.7e+01''56.79''5.68e+01''5678.90%'
567.89'5.7e+02''567.89''5.68e+02''56789.00%'
  • Ints
f"{90:c}"  # 'Z'
f"{90:b}"  # '1011010'
f"{90:X}"  # '5A'

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Numbers​

  • Types
    • int(str) and float(str) raise ValueError on malformed strings
    • Decimal numbers can be represented exactly, unlike foats where 1.1 + 2.2 != 3.3
    • Precision of decimal operations is set with: decimal.getcontext().prec = int
int = int(float/str/bool)  # Or: math.floor(float)
float = float(int/str/bool)  # Or: reale±int
complex = complex(real=0, imag=0)  # Or: real ± realj
Fraction = fractions.Fraction(0, 1)  # Or: Fraction(numerator=0, denominator=1)
Decimal = decimal.Decimal(str/int)  # Or: Decimal((sign, digits, exponent))
  • Basic Functions
num = pow(num, num)  # Or: num ** num
num = abs(num)  # float = abs(complex)
num = round(num [, ±ndigits])  # `round(126, -1) == 130`
  • Math
from math import e, pi, inf, nan, isinf, isnan
from math import cos, acos, sin, asin, tan, atan, degrees, radians
from math import log, log10, log2
  • Statistics
from statistics import mean, median, variance, stdev, pvariance, pstdev
  • Random
from random import random, randint, choice, shuffle

float = random()
int = randint(from_inclusive, to_inclusive)
el = choice(list)
shuffle(list)
  • Bin, Hex
int = ±0bbin  # Or: ±0xhex
int = int('±bin', 2)  # Or: int('±hex', 16)
int = int('±0bbin', 0)  # Or: int('±0xhex', 0)
'[-]0bbin' = bin(int)  # Or: hex(int)
  • Bitwise Operators
int = int & int  # And
int = int | int  # Or
int = int ^ int  # Xor (0 if both bits equal)
int = int  n_bits  # Shift left ( for right)
int = ~int  # Not (also: -int - 1)

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Combinatorics​

  • Every function returns an iterator
  • If you want to print the iterator, you need to pass it to the list() function first!
from itertools import product, combinations, combinations_with_replacement, permutations

product([0, 1], repeat=3)  # itertools.product object at 0x10b08ffc0
list(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)]

list(product('ab', '12'))  # [('a', '1'), ('a', '2'), ('b', '1'), ('b', '2')]

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

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

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

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Datetime​

  • Module 'datetime' provides 'date', 'time', 'datetime' and 'timedelta' classes
    • All are immutable and hashable
  • Time and datetime objects can be 'aware' (have defined timezone), or 'naive' (don't have defined timezone)
  • If object is naive, it is presumed to be in the system's timezone

python 2​

from datetime import date, time, datetime, timedelta
from dateutil.tz import UTC, tzlocal, gettz, resolve_imaginary  # included in python 2

python 3​

  • pip install python-dateutil
from datetime import date, time, datetime, timedelta
from dateutil.tz import UTC, tzlocal, gettz, resolve_imaginary  # needs to install 3rd party library
  • Constructors
    • Use date/datetime.weekday() to get the day of the week (Mon == 0)
    • 'fold=1' means the second pass in case of time jumping back for one hour
    • datetime aware = resolve_imaginary(datetime aware) fixes datetimes that fall into the missing hour
date  = date(year, month, day)
time  = time(hour=0, minute=0, second=0, microsecond=0, tzinfo=None, fold=0)
datetime = datetime(year, month, day, hour=0, minute=0, second=0, ...)
timedelta = timedelta(days=0, seconds=0, microseconds=0, milliseconds=0,
                        minutes=0, hours=0, weeks=0)
  • Now
    • To extract time use datetime naive.time(), datetime aware.time() or datetime aware.timetz()
date/datetime naive  = date/datetime.today()  # Current local date or naive datetime
datetime naive = datetime.utcnow()  # Naive datetime from current UTC time
datetime aware = datetime.now(tzinfo)  # Aware datetime from current tz time
  • Timezone
tzinfo = UTC  # UTC timezone. London without DST
tzinfo = tzlocal()  # Local timezone, also gettz()
tzinfo = gettz('Continent/City')  # 'Continent/City_Name' timezone or None
datetime aware    = datetime.astimezone(tzinfo)  # Datetime, converted to passed timezone
time aware/datetime aware = time/datetime.replace(tzinfo=tzinfo)  # Unconverted object with new timezone
  • Encode
    • ISO strings come in following forms: 'YYYY-MM-DD', 'HH:MM:SS.ffffff[±offset]', or both separated by an arbitrary character
      • Offset is formatted as: HH:MM
    • Epoch on Unix systems is: '1970-01-01 00:00 UTC', '1970-01-01 01:00 CET', ...
date/time/datetime = date/time/datetime.fromisoformat('iso')  # Object from ISO string. Raises ValueError
datetime = datetime.strptime(str, 'format')  # Datetime from str, according to format
date/datetime naive = date/datetime.fromordinal(int)  # date/datetime naive from days since Christ, at midnight
datetime naive = datetime.fromtimestamp(real)  # Local time datetime naive from seconds since Epoch
datetime aware = datetime.fromtimestamp(real, tz.)  # Aware datetime from seconds since Epoch
  • Decode
str = date/time/datetime.isoformat(sep='T')  # Also timespec='auto/hours/minutes/seconds'
str = date/time/datetime.strftime('format')  # Custom string representation
int = date/datetime.toordinal()  # Days since Christ, ignoring time and tz
float = datetime naive.timestamp()  # Seconds since Epoch, from datetime naive in local tz
float = datetime aware.timestamp()  # Seconds since Epoch, from datetime aware
  • Format
    • When parsing, %z also accepts ±HH:MM
    • For abbreviated weekday and month use %a and %b
from datetime import datetime

dt = datetime.strptime('2015-05-14 23:39:00.00 +0200', '%Y-%m-%d %H:%M:%S.%f %z')
dt.strftime("%A, %dth of %B '%y, %I:%M%p %Z")  # "Thursday, 14th of May '15, 11:39PM UTC+02:00"
  • Arithmetics
date/datetime = date/datetime ± timedelta  # Returned datetime can fall into missing hour
timedelta = date/datetime naive - date/datetime naive  # Returns the difference, ignoring time jumps
timedelta = datetime aware - datetime aware  # Ignores time jumps if they share tzinfo object
timedelta = datetime_UTC - datetime_UTC  # Convert datetimes to UTC to get the actual delta

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Syntax​

Arguments​

  • Inside Function Call
function(positional_args)  # f(0, 0)
function(keyword_args)  # f(x=0, y=0)
function(positional_args, keyword_args)  # f(0, y=0)
  • Inside Function Definition
def f(nondefault_args):  # def f(x, y):
    ...

def f(default_args):  # def f(x=0, y=0):
    ...


def f(nondefault_args, default_args):  # def f(x, y=0):
    ...

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Splat Operator​

  • Inside Function Call
    • Splat expands a collection into positional arguments, while splatty-splat expands a dictionary into keyword arguments
# method 1
args = (1, 2)
kwargs = {'x': 3, 'y': 4, 'z': 5}
functionName(*args, **kwargs)

# method 2
functionName(1, 2, x=3, y=4, z=5)
  • Inside Function Definition
    • Splat combines zero or more positional arguments into a tuple, while splatty-splat combines zero or more keyword arguments into a dictionary
def add(*a):
    return sum(a)


add(1, 2, 3)  # 6
  • Legal argument combinations
def f(x, y, z):  # f(x=1, y=2, z=3) | f(1, y=2, z=3) | f(1, 2, z=3) | f(1, 2, 3)
def f(*, x, y, z):  # f(x=1, y=2, z=3)
def f(x, *, y, z):  # f(x=1, y=2, z=3) | f(1, y=2, z=3)
def f(x, y, *, z):  # f(x=1, y=2, z=3) | f(1, y=2, z=3) | f(1, 2, z=3)

def f(*args):  # f(1, 2, 3)
def f(x, *args):  # f(1, 2, 3)
def f(*args, z):  # f(1, 2, z=3)
def f(x, *args, z):  # f(1, 2, z=3)


def f(**kwargs):  # f(x=1, y=2, z=3)
def f(x, **kwargs):  # f(x=1, y=2, z=3) | f(1, y=2, z=3)
def f(*, x, **kwargs):  # f(x=1, y=2, z=3)

def f(*args, **kwargs):  # f(x=1, y=2, z=3) | f(1, y=2, z=3) | f(1, 2, z=3) | f(1, 2, 3)
def f(x, *args, **kwargs):  # f(x=1, y=2, z=3) | f(1, y=2, z=3) | f(1, 2, z=3) | f(1, 2, 3)
def f(*args, y, **kwargs):  # f(x=1, y=2, z=3) | f(1, y=2, z=3)
def f(x, *args, z, **kwargs):  # f(x=1, y=2, z=3) | f(1, y=2, z=3) | f(1, 2, z=3)
  • Other Uses
list  = [*collection [, ...]]
set   = {*collection [, ...]}
tuple = (*collection, [...])
dict  = {**dict [, ...]}

head, *body, tail = collection

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Inline​

  • Lambda
function = lambda: return_value
function = lambda argument_1, argument_2: return_value
  • Comprehensions
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}
iter = (i+5 for i in range(10))  # (5, 6, ..., 14)
dict = {i: i*2 for i in range(10)}  # {0: 0, 1: 2, ..., 9: 18}

# method 1
out = [i+j for i in range(10) for j in range(10)]

# method 2
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}
obj  = 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
obj = expression_if_true if condition else expression_if_false

[a if a else 'zero' for a in (0, 1, 2, 3)]  # ['zero', 1, 2, 3]
  • Namedtuple, Enum, Dataclass
from collections import namedtuple
from enum import Enum
from dataclasses import make_dataclass


Point = namedtuple('Point', 'x y')
point = Point(0, 0)

Direction = Enum('Direction', 'n e s w')
direction = Direction.n

Creature = make_dataclass('Creature', ['location', 'direction'])
creature = Creature(Point(0, 0), Direction.n)

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Closure​

  • have a closure in Python when:
    • A nested function references a value of its enclosing function
    • and the enclosing function returns the nested function
    • If multiple nested functions within enclosing function reference the same value, that value gets shared
    • To dynamically access function's first free variable use function.__closure__[0].cell_contents
def get_multiplier(a):
    def out(b):
        return a * b
    return out


multiply_by_3 = get_multiplier(3)
multiply_by_3(10)  # 30
  • Partial
    • Partial is also useful in cases when function needs to be passed as an argument
      • because it enables us to set its arguments beforehand
    • e.g.: defaultdict(function), iter(function, to_exclusive) and dataclass's field(default_factory=function)
from functools import partial
import operator as op


function = partial(function [, arg_1, arg_2, ...])

multiply_by_3 = partial(op.mul, 3)
multiply_by_3(10)  # 30
  • Non-Local
    • If variable is being assigned to anywhere in the scope, it is regarded as a local variable
    • unless it is declared as a global or a nonlocal
def get_counter(): i= 0
    def out():
        nonlocal i
        i += 1
        return i
    return out


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

back to top

Decorator​

  • A decorator takes a function, adds some functionality and returns it
@decorator_name
def function_that_gets_passed_to_decorator():
    ...
  • Debugger Example
    • Wraps is a helper decorator that copies the metadata of the passed function (func) to the function it is wrapping (out)
    • Without it add.__name__ would return 'out'
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
  • LRU Cache
    • Decorator that caches function's return values
    • All function's arguments must be hashable
    • CPython interpreter limits recursion depth to 1000 by default
      • To increase it use sys.setrecursionlimit(depth)
from functools import lru_cache


@lru_cache(maxsize=None)
def fib(n):
    return n if n  2 else fib(n-2) + fib(n-1)
  • Parametrized Decorator
    • A decorator that accepts arguments and returns a normal decorator that accepts a function
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

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Class​

  • Return value of repr() should be unambiguous and of str() readable

  • If only repr() is defined, it will also be used for str()

    class Test:
        def __init__(self, a):
            self.a = a
        def __repr__(self):
            class_name = self.__class__.__name__
            return f'{class_name}({self.a!r})'
        def __str__(self):
            return str(self.a)

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

    • Str() use cases

      test = Test("sample")
      print(test)  # sample
      print(f"{test}")  # sample
      raise Exception(test)
      """
      Traceback (most recent call last):
        File "/path/to/file.py", line 27, in module
          raise Exception(test)
      Exception: sample

      shell returned 1
      """
import loguru  # pip install loguru

loguru.logger.debug(test)  # 2022-04-04 02:43:02.509 | DEBUG    | __main__:module:28 - sample


import csv

# open the file in the write mode
file = open('path/to/csv_file', 'w')
csv.writer(file).writerow([test])
```

  • Repr() use cases

    test = Test("sample")
    print([test])  # [Test('sample')]
    print(f'{test!r}')  # Test('sample')
import loguru  # pip install loguru

loguru.logger.exception(test)
"""
2022-04-04 02:51:52.414 | ERROR    | __main__:module:25 - sample
NoneType: None
"""


import dataclasses

Z = dataclasses.make_dataclass('Z', ['a'])
print(Z(test))  # Z(a=Test('sample'))
```

  • 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
```

  • Multiple Inheritance

    class A: pass
    class B: pass
    class C(A, B): pass

    # MRO determines the order in which parent classes are traversed when searching for a method
    C.mro()  # [class 'C', class 'A', class 'B', class 'object']

  • Property

    • Pythonic way of implementing getters and setters
    class MyClass:
        @property
        def a(self):
            return self._a

        @a.setter
        def a(self, value):
            self._a = value

el = MyClass() el.a = 123 el.a # 123


- Dataclass

- Decorator that automatically generates init(), repr() and eq() special methods
- Objects can be made sortable with 'order=True' and/or immutable and hashable with 'frozen=True'
- Function field() is needed because `attr_name: list = []` would make a list that is shared among all instances
- Default_factory can be any callable

```python
from dataclasses import dataclass, field


@dataclass(order=False, frozen=False)
class class_name:
    attr_name_1: type
    attr_name_2: type = default_value
    attr_name_3: list/dict/set = field(default_factory=list/dict/set)

  • Inline

    from dataclasses import make_dataclass
class = make_dataclass('class_name', coll_of_attribute_names)
class = make_dataclass('class_name', coll_of_tuples)
tuple = ('attr_name', type [, default_value])
```

  • Slots

    • Mechanism that restricts objects to attributes listed in 'slots' and significantly reduces their memory footprint

      class MyClassWithSlots:
          __slots__ = ['a']
          def __init__(self):
              self.a = 1

  • Copy

    from copy import copy, deepcopy

object = copy(object) object = deepcopy(object)


[back to top](#table-of-contents)

### Duck Type

- A duck type is an implicit type that prescribes a set of special methods
- Any object that has those methods defined is considered a member of that duck type
- 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
- Only the left side object has eq() method called, unless it returns NotImplemented, in which case the right object is consulted

```python
class MyComparable:
    def __init__(self, a):
        self.a = a

    def __eq__(self, other):
        if isinstance(other, type(self)):
            return self.a == other.a
        return NotImplemented

  • Hashable

    • Hashable object needs both hash() and eq() methods and its 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 = a

          @property
          def a(self):
              return self._a

          def __eq__(self, other):
              if isinstance(other, type(self)):
                  return self.a == other.a
              return NotImplemented

          def __hash__(self):
              return hash(self.a)

  • Sortable

    • With total_ordering decorator, you only need to provide eq() and one of lt(), gt(), le() or ge() special methods
    from functools import total_ordering

    @total_ordering
    class MySortable:
        def __init__(self, a):
            self.a = a

        def __eq__(self, other):
            if isinstance(other, type(self)):
                return self.a == other.a
            return NotImplemented

        def __lt__(self, other):
            if isinstance(other, type(self)):
                return self.a  other.a
            return NotImplemented

  • Iterator

    • Any object that has methods next() and iter() is an iterator
    • Next() should return next item or raise StopIteration
    • Iter() should return 'self'
    • Python has many different iterator objects
      • Iterators returned by the iter() function, such as list_iterator and set_iterator
      • Objects returned by the itertools module, such as count, repeat and cycle
      • Generators returned by the generator functions and generator expressions
      • File objects returned by the open() function, etc
    class Counter:
        def __init__(self):
            self.i = 0

        def __next__(self):
            self.i += 1
            return self.i

        def __iter__(self):
            return self

counter = Counter() next(counter), next(counter), next(counter) # (1, 2, 3)


- Callable

- All functions and classes have a call() method, hence are callable
- When this cheatsheet uses `function` as an argument, it actually means `callable`

```python
class Counter:
    def __init__(self):
        self.i = 0

    def __call__(self):
        self.i += 1
        return self.i


counter = Counter()
counter(), counter(), counter()  # (1, 2, 3)

  • Context Manager

    • Enter() should lock the resources and optionally return an object
    • Exit() should release the resources
    • Any exception that happens inside the with block is passed to the exit() method
    • If it wishes to suppress the exception it must return a true value
    class MyOpen:
        def __init__(self, filename):
            self.filename = filename

        def __enter__(self):
            self.file = open(self.filename)
            return self.file

        def __exit__(self, exc_type, exception, traceback):
            self.file.close()

with open('test.txt', 'w') as file: file.write('Hello World!')

with MyOpen('test.txt') as file: print(file.read())

Hello World!


- Iterable

- Only required method is iter()
  - It should return an iterator of object's items
- Contains() automatically works on any object that has iter() defined

```python
class MyIterable:
  def __init__(self, a):
      self.a = a

  def __iter__(self):
      return iter(self.a)

  def __contains__(self, el):
      return el in self.a


obj = MyIterable([1, 2, 3])
[el for el in obj]  # [1, 2, 3]
1 in obj  # True

  • Collection

    • Only required methods are iter() and len()
    class MyCollection:
        def __init__(self, a):
            self.a = a

        def __iter__(self):
            return iter(self.a)

        def __contains__(self, el):
            return el in self.a

        def __len__(self):
            return len(self.a)

  • Sequence

    • Only required methods are len() and getitem()
    • Getitem() should return an item at index or raise IndexError
    • Iter() and contains() automatically work on any object that has getitem() defined
    • Reversed() automatically works on any object that has getitem() and len() defined
    class MySequence:
        def __init__(self, a):
            self.a = a

        def __iter__(self):
            return iter(self.a)

        def __contains__(self, el):
            return el in self.a

        def __len__(self):
            return len(self.a)

        def __getitem__(self, i):
            return self.a[i]

        def __reversed__(self):
            return reversed(self.a)

  • ABC Sequence

    • It's a richer interface than the basic sequence
    • Extending it generates iter(), contains(), reversed(), index() and count()
    • Unlike 'abc.Iterable' and 'abc.Collection', it is not a duck type
      • That is why 'issubclass(MySequence, abc.Sequence)' would return False even if MySequence had all the methods defined
    from collections import abc

class MyAbcSequence(abc.Sequence): def init(self, a): self.a = a

  def __len__(self):
      return len(self.a)

  def __getitem__(self, i):
      return self.a[i]

- available special methods
  - iter(), contains(), len(), getitem(), reversed(), index(), count()
- Other ABCs that generate missing methods are: MutableSequence, Set, MutableSet, Mapping and MutableMapping
- Names of their required methods are stored in `abc.__abstractmethods__`

[back to top](#table-of-contents)

### Enum

- If there are no numeric values before auto(), it returns 1
- Otherwise it returns an increment of the last numeric value

```python
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()


member = enum.member_name  # Returns a member
member = enum['member_name']  # Returns a member or raises KeyError
member = enum(value)  # Returns a member or raises ValueError
str = member.name  # Returns member's name
obj = member.value  # Returns member's 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))
def get_next_member(member):
    members = list(member.__class__)
    index = (members.index(member) + 1) % len(members)
    return members[index]

  • Inline

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

    • User-defined functions cannot be values, so they must be wrapped

      • Another solution in this particular case is to use built-in functions and() and or() from the module operator
      from functools import partial
LogicOp = Enum('LogicOp', {'AND': partial(lambda l, r: l and r),
                           'OR' : partial(lambda l, r: l or r)})
```

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Exception​

  • Basic Example

    try:
        code
    except exception:
        code

  • Complex Example

    • Code inside the 'else' block will only be executed if 'try' block had no exception
    • Code inside the 'finally' block will always be executed.
    try:
        code_1
    except exception_a:
        code_2_a
    except exception_b:
        code_2_b
    else:
        code_2_c
    finally:
        code_3

  • Catching Exceptions

    • Also catches subclasses of the exception
    • Use traceback.print_exc() to print the error message to stderr
    except exception:
    except exception as name:
    except (exception, ...):
    except (exception, ...) as name:

  • Raising Exceptions

    raise exception
    raise exception()
    raise exception(el [, ...])
    • Re-raising caught exception
      except exception as name:
          ...
          raise

  • Exception Object

    arguments = name.args
    exc_type = name.__class__
    filename = name.__traceback__.tb_frame.f_code.co_filename
    func_name = name.__traceback__.tb_frame.f_code.co_name
    line = linecache.getline(filename, name.__traceback__.tb_lineno)
    error_msg = traceback.format_exception(exc_type, name, name.__traceback__)

  • Built-in Exceptions

    BaseException
     ├── SystemExit                   # Raised by the sys.exit() function
     ├── KeyboardInterrupt            # Raised when the user hits the interrupt key (ctrl-c)
     └── Exception                    # User-defined exceptions should be derived from this class
          ├── ArithmeticError         # Base class for arithmetic errors
          │    └── ZeroDivisionError  # Raised when dividing by zero
          ├── AttributeError          # Raised when an attribute is missing
          ├── EOFError                # Raised by input() when it hits end-of-file condition
          ├── LookupError             # Raised when a look-up on a collection fails
          │    ├── IndexError         # Raised when a sequence index is out of range
          │    └── KeyError           # Raised when a dictionary key or set element is not found
          ├── NameError               # Raised when a variable name is not found
          ├── OSError                 # Failures such as “file not found” or “disk full”
          │    └── FileNotFoundError  # When a file or directory is requested but doesn't exist
          ├── RuntimeError            # Raised by errors that don't fall in other categories
          │    └── RecursionError     # Raised when the maximum recursion depth is exceeded
          ├── StopIteration           # Raised by next() when run on an empty iterator
          ├── TypeError               # Raised when an argument is of wrong type
          └── ValueError              # When an argument is of right type but inappropriate value
               └── UnicodeError       # Raised when encoding/decoding strings to/from bytes fails

  • Collections and their exceptions

    listdictset
    getitem()IndexErrorKeyError
    pop()IndexErrorKeyErrorKeyError
    remove()ValueErrorKeyError
    index()ValueError

  • Useful built-in exceptions:

    raise TypeError('Argument is of wrong type!')
    raise ValueError('Argument is of right type but inappropriate value!')
    raise RuntimeError('None of above!')

  • User-defined Exceptions

    class MyError(Exception):
        pass

class MyInputError(MyError): pass


[back to top](#table-of-contents)

## System

### Exit

- Exits the interpreter by raising SystemExit exception

```python
import sys


sys.exit()  # Exits with exit code 0 (success)
sys.exit(el)  # Prints to stderr and exits with 1
sys.exit(int)  # Exits with passed exit code

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Print​

  • Use file=sys.stderr for messages about errors

  • Use `flush=True“ to forcibly flush the stream

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

  • Pretty Print

    • Levels deeper than 'depth' get replaced by '...'.

      from pprint import pprint
pprint(collection, width=80, depth=None, compact=False, sort_dicts=True)
```

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Input​

  • Reads a line from user input or pipe if present
    • Trailing newline gets stripped
    • Prompt string is printed to the standard output before reading input
    • Raises EOFError when user hits EOF (ctrl-d/z) or input stream gets exhausted
    str = input(prompt=None)

back to top

Command Line Arguments​

import sys


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

  • Argument Parser

    • Use help=str to set argument description

    • Use default=el to set the default value

    • Use type=FileType(mode) for files

      from argparse import ArgumentParser, FileType
p = ArgumentParser(description=str)
p.add_argument('-short_name', '--name', action='store_true')  # Flag
p.add_argument('-short_name', '--name', type=type)  # Option
p.add_argument('name', type=type, nargs=1)  # First argument
p.add_argument('name', type=type, nargs='+')  # Remaining arguments
p.add_argument('name', type=type, nargs='*')  # Optional arguments
args = p.parse_args()  # Exits on error
value = args.name
```

back to top

Open​

  • Opens the file and returns a corresponding file object

    • encoding=None means that the default encoding is used, which is platform dependent
      • Best practice is to use encoding="utf-8" whenever possible
    • newline=None means all different end of line combinations are converted to '\n' on read
      • while on write all \n characters are converted to system's default line separator
    • newline="" means no conversions take place
      • but input is still broken into chunks by readline() and readlines() on either \n, \r or \r\n
    file = open('path', mode='r', encoding=None, newline=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 start
    • a+ - Read and write from the end
    • t - Text mode (default)
    • b - Binary mode

  • Exceptions

    • FileNotFoundError can be raised when reading with r or r+
    • FileExistsError can be raised when writing with x
    • IsADirectoryError and PermissionError can be raised by any
    • OSError is the parent class of all listed exceptions

  • File Object

    • Methods do not add or strip trailing newlines, even writelines()
    file.seek(0)  # Moves to the start of the file
    file.seek(offset)  # Moves "offset" chars/bytes from the start
    file.seek(0, 2)  # Moves to the end of the file
    bin_file.seek(±offset, anchor)  # Anchor: 0 start, 1 current position, 2 end

    str/bytes = file.read(size=-1)  # Reads 'size' chars/bytes or until EOF
    str/bytes = file.readline()  # Returns a line or empty string/bytes on EOF
    list = file.readlines()  # Returns a list of remaining lines
    str/bytes = next(file)  # Returns a line using buffer, do not mix

    file.write(str/bytes)  # Writes a string or bytes object
    file.writelines(collection)  # Writes a collection of strings or bytes objects
    file.flush()  # Flushes write buffer

  • 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)

back to top

Path​

from os import getcwd, path, listdir
from glob import glob


str = getcwd()  # Returns the current working directory
str = path.join(path, ...)  # Joins two or more pathname components
str = path.abspath(path)  # Returns absolute path

str = path.basename(path)  # Returns final component of the path
str = path.dirname(path)  # Returns path without the final component
tup = path.splitext(path)  # Splits on last period of the final component

list = listdir(path='.')  # Returns filenames located at path
list = glob('pattern')  # Returns paths matching the wildcard pattern

bool = path.exists(path)  # Or: Path.exists()
bool = path.isfile(path)  # Or: DirEntry/Path.is_file()
bool = path.isdir(path)  # Or: DirEntry/Path.is_dir()

  • DirEntry

    • Using scandir() instead of listdir() can significantly increase the performance of code that also needs file type information
    from os import scandir

iter = scandir(path='.') # Returns DirEntry objects located at path str = DirEntry.path # Returns path as a string str = DirEntry.name # Returns final component as a string file = open(DirEntry) # Opens the file and returns file object


- Path Object

```python
from pathlib import Path


Path = Path(path [, ...])  # Accepts strings, Paths and DirEntry objects
Path = path / path [/ ...]  # One of the paths must be a Path object

Path = Path()  # Returns relative cwd, also Path('.')
Path = Path.cwd()  # Returns absolute cwd, also Path().resolve()
Path = Path.resolve()  # Returns absolute Path without symlinks

Path = Path.parent  # Returns Path without final component
str = Path.name  # Returns final component as a string
str = Path.stem  # Returns final component without extension
str = Path.suffix  # Returns final component's extension
tup = Path.parts  # Returns all components as strings

iter = Path.iterdir()  # Returns dir contents as Path objects
iter = Path.glob('pattern')  # Returns Paths matching the wildcard pattern

str = str(Path)  # Returns path as a string
file = open(Path)  # Opens the file and returns file object

back to top

OS Commands​

  • Files and Directories

    • Paths can be either strings, Paths or DirEntry objects

    • Functions report OS related errors by raising either OSError or one of its subclasses

      import os, shutil
os.chdir(path)  # Changes the current working directory
os.mkdir(path, mode=0o777)  # Creates a directory. Mode is in octal

shutil.copy(from, to)  # Copies the file, 'to' can exist or be a dir
shutil.copytree(from, to)  # Copies the directory, 'to' must not exist

os.rename(from, to)  # Renames/moves the file or directory
os.replace(from, to)  # Same, but overwrites 'to' if it exists

os.remove(path)  # Deletes the file
os.rmdir(path)  # Deletes the empty directory
shutil.rmtree(path)  # Deletes the directory
```

  • Shell Commands

    import os

str = os.popen('shell_command').read()


- Sends '1 + 1' to the basic calculator and captures its output:

```python
from subprocess import run


run('bc', input='1 + 1\n', capture_output=True, encoding='utf-8')  # CompletedProcess(args='bc', returncode=0, stdout='2\n', stderr='')

  • Sends test.in to the basic calculator running in standard mode and saves its output to test.out

    from shlex import split

os.popen('echo 1 + 1 test.in') run(split('bc -s'), stdin=open('test.in'), stdout=open('test.out', 'w')) # CompletedProcess(args=['bc', '-s'], returncode=0) open('test.out').read() # '2\n'


[back to top](#table-of-contents)

## Data

### JSON

- Text file format for storing collections of strings and numbers

```python
import json


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

  • Read Object from JSON File

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

  • Write Object to JSON 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)

back to top

Pickle​

  • Binary file format for storing objects
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)

back to top

CSV​

  • Text file format for storing spreadsheets
import csv

  • Read

    • File must be opened with newline="" argument, or newlines embedded inside quoted fields will not be interpreted correctly!
    reader = csv.reader(file)  # Also: `dialect='excel', delimiter=','`
    list = next(reader)  # Returns next row as a list of strings
    list = list(reader)  # Returns list of remaining rows

  • Write

    • File must be opened with newline="" argument, or \r will be added in front of every \n on platforms that use \r\n line endings!
    writer = csv.writer(file)   # Also: `dialect='excel', delimiter=','`
    writer.writerow(collection)  # Encodes objects using `str(el)`
    writer.writerows(coll_of_coll)  # Appends multiple rows

  • Parameters

    • dialect - Master parameter that sets the default values
    • delimiter - A one-character string used to separate fields
    • quotechar - Character for quoting fields that contain special characters
    • doublequote - Whether quotechars inside fields get doubled or escaped
    • skipinitialspace - Whether whitespace after delimiter gets stripped
    • lineterminator - Specifies how writer terminates rows
    • quoting - Controls the amount of quoting: 0 - as necessary, 1 - all
    • escapechar - Character for escaping 'quotechar' if doublequote is False

  • Dialets

    excelexcel-tabunix
    delimiter,\t,
    quotechar"""
    doublequoteTrueTrueTrue
    skipinitialspaceFalseFalseFalse
    lineterminator\r\n\r\n\n
    quoting001
    escapecharNoneNoneNone

  • Read Rows from CSV File

    def read_csv_file(filename):
        with open(filename, encoding='utf-8', newline='') as file:
            return list(csv.reader(file))

  • Write Rows to CSV File

    def write_to_csv_file(filename, rows):
        with open(filename, 'w', encoding='utf-8', newline='') as file:
            writer = csv.writer(file)
            writer.writerows(rows)

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SQLite​

  • Server-less database engine that stores each database into a separate file

  • Connect

    • Opens a connection to the database file
    • Creates a new file if path doesn't exist
    import sqlite3

con = sqlite3.connect('path') # Also ':memory:' con.close()


- Read

- Returned values can be of type str, int, float, bytes or None

```python
cursor = con.execute('query')  # Can raise a subclass of sqlite3.Error
tuple = cursor.fetchone()  # Returns next row. Also next(cursor)
list = cursor.fetchall()  # Returns remaining rows. Also list(cursor)

  • Write

    con.execute('query')
    con.commit()

    # or
    with con:
        con.execute('query')

  • Placeholders

    • Passed values can be of type str, int, float, bytes, None, bool, datetime.date or datetime.datetme
    • Bools will be stored and returned as ints and dates as ISO formatted strings
    con.execute('query', list/tuple)  # Replaces '?'s in query with values
    con.execute('query', dict/namedtuple)  # Replaces ':key's with values
    con.executemany('query', coll_of_above)  # Runs execute() many times

  • In this example values are not actually saved because con.commit() is omitted!

    import sqlite3

con = sqlite3.connect('test.db')

con.execute('create table person (person_id integer primary key, name, height)') con.execute('insert into person values (null, ?, ?)', ('Jean-Luc', 187)).lastrowid # 1 con.execute('select * from person').fetchall() #[(1, 'Jean-Luc', 187)]


[back to top](#table-of-contents)

### MySQL

- Has a very similar interface with SQLite, but with differences listed below

- `pip3 install mysql-connector`

```python
from mysql import connector


con = connector.connect(host=str, ...)  # `user=str, password=str, database=str
cursor = con.cursor()  # Only cursor has execute method

cursor.execute('query')  # Can raise a subclass of connector.Error
cursor.execute('query', list/tuple)  # Replaces '%s's in query with values
cursor.execute('query', dict/namedtuple)  # Replaces '%(key)s's with values

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Bytes​

  • Bytes object is an immutable sequence of single bytes
  • Mutable version is called bytearray
bytes = b'str'  # Only accepts ASCII characters and \x00 - \xff
int = bytes[index]  # Returns int in range from 0 to 255
bytes = bytes[slice]  # Returns bytes even if it has only one element
bytes = bytes.join(coll_of_bytes)  # Joins elements using bytes object as separator

  • Encode

    bytes = bytes(coll_of_ints)  # Ints must be in range from 0 to 255
    bytes = bytes(str, 'utf-8')  # Or: str.encode('utf-8')
    bytes = int.to_bytes(n_bytes, ...)  # `byteorder='big/little', signed=False`
    bytes = bytes.fromhex('hex')  # Hex numbers can be separated by spaces

  • Decode

    list = list(bytes)  # Returns ints in range from 0 to 255
    str = str(bytes, 'utf-8')  # Or: bytes.decode('utf-8')
    int = int.from_bytes(bytes, ...)  # `byteorder='big/little', signed=False`
    'hex' = bytes.hex()  # Returns a string of hexadecimal numbers

  • 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)

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Struct​

  • Module that performs conversions between a sequence of numbers and a bytes object
  • Machine’s native type sizes and byte order are used by default
from struct import pack, unpack, iter_unpack


bytes = pack('format', num_1 [, num_2, ...])
tuple = unpack('format', bytes)
tuples = iter_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)
  • Format
    • For standard type sizes start format string with:
      • = - native byte order
      • `` - little-endian
      • `` - big-endian (also '!')
    • Integer types. Use a capital letter for unsigned type. Standard sizes are in brackets:
      • x - pad byte 'b' - char (1)
      • h - short (2) 'i' - int (4)
      • l - long (4)
      • q - long long (8)
    • Floating point types:
      • f - float (4)
      • d - double (8)

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Array​

  • List that can only hold numbers of a predefined type
  • Available types and their sizes in bytes are listed above
from array import array


array = array('typecode', collection)  # Array from collection of numbers
array = array('typecode', bytes)  # Array from bytes object
array = array('typecode', array)  # Treats array as a sequence of numbers
bytes = bytes(array)  # Or: array.tobytes()

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Memory View​

  • A sequence object that points to the memory of another object
  • Each element can reference a single or multiple consecutive bytes, depending on format
  • Order and number of elements can be changed with slicing.
mview = memoryview(bytes/bytearray/array)  # Immutable if bytes, else mutable
real = mview[index]  # Returns an int or a float
mview = mview[slice]  # Mview with rearranged elements
mview = mview.cast('typecode')  # Casts memoryview to the new format
mview.release()  # Releases the object's memory buffer

bin_file.write(mview)  # Writes mview to the binary file
bytes = bytes(mview)  # Creates a new bytes object
bytes = bytes.join(coll_of_mviews)  # Joins mviews using bytes object as sep
array = array('typecode', mview)  # Treats mview as a sequence of numbers

list  = list(mview)  # Returns list of ints or floats
str = str(mview, 'utf-8')  # Treats mview as a bytes object
int = int.from_bytes(mview, ...)  # `byteorder='big/little', signed=False`
'hex' = mview.hex()  # Treats mview as a bytes object

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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)  # Opposite element is dropped if full
deque.extendleft(collection)  # Collection gets reversed
el = deque.popleft()  # Raises IndexError if empty
deque.rotate(n=1)  # Rotates elements to the right

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Advanced​

Threading​

  • CPython interpreter can only run a single thread at a time
  • That is why using multiple threads won't result in a faster execution, unless at least one of the threads contains an I/O operation
from threading import Thread, RLock, Semaphore, Event, Barrier

  • Thread

    • Use kwargs=dict to pass keyword arguments to the function
    • Use daemon=True, or the program will not be able to exit while the thread is alive
    Thread = Thread(target=function)  # Use `args=collection` to set arguments
    Thread.start()  # Starts the thread
    bool = Thread.is_alive()  # Checks if thread has finished executing
    Thread.join()  # Waits for thread to finish

  • Lock

    lock = RLock()
    lock.acquire()  # Waits for lock to be available
    lock.release()  # Makes the lock available again

    # Or
    lock = RLock()
    with lock:
        ...

  • Semaphore, Event, Barrier

    Semaphore = Semaphore(value=1)  # Lock that can be acquired 'value' times
    Event = Event()  # Method wait() blocks until set() is called
    Barrier = Barrier(n_times)  # Method wait() blocks until it's called 'n_times'

  • Thread Pool Executor

    from concurrent.futures import ThreadPoolExecutor

with ThreadPoolExecutor(max_workers=None) as executor: # Does not exit until done iter = executor.map(lambda x: x + 1, range(3)) # (1, 2, 3) iter = executor.map(lambda x, y: x + y, 'abc', '123') # ('a1', 'b2', 'c3') Future = executor.submit(function [, arg_1, ...]) # Also visible outside block

Future

bool = Future.done() # Checks if thread has finished executing obj = Future.result() # Waits for thread to finish and returns result


- Queue
- A thread-safe FIFO queue
- For LIFO queue use LifoQueue

```python
from queue import Queue


Queue = Queue(maxsize=0)

Queue.put(el)  # Blocks until queue stops being full
Queue.put_nowait(el)  # Raises queue.Full exception if full
el = Queue.get()  # Blocks until queue stops being empty
el = Queue.get_nowait()  # Raises queue. Empty exception if empty

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Operator​

  • Module of functions that provide the functionality of operators
from operator import add, sub, mul, truediv, floordiv, mod, pow, neg, abs
from operator import eq, ne, lt, le, gt, ge
from operator import and_, or_, not_
from operator import itemgetter, attrgetter, methodcaller
import operator as op


elementwise_sum  = map(op.add, list_a, list_b)
sorted_by_second = sorted(collection, key=op.itemgetter(1))
sorted_by_both = sorted(collection, key=op.itemgetter(1, 0))
product_of_elems = functools.reduce(op.mul, collection)
LogicOp = enum.Enum('LogicOp', {'AND': op.and_, 'OR' : op.or_})
last_el = op.methodcaller('pop')(list)

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Introspection​

  • Inspecting code at runtime

  • Variables

    list = dir()  # Names of local variables (incl. functions)
    dict = vars()  # Dict of local variables. Also locals()
    dict = globals()  # Dict of global variables

  • Attributes

    list = dir(object)  # Names of object's attributes (incl. methods)
    dict = vars(object)  # Dict of object's fields. Also obj.__dict__
    bool = hasattr(object, 'attr_name')  # Checks if getattr() raises an error
    value  = getattr(object, 'attr_name')  # Raises AttributeError if attribute is missing
    setattr(object, 'attr_name', value)    # Only works on objects with __dict__ attribute
    delattr(object, 'attr_name')           # Equivalent to `del object.attr_name`

  • Parameters

    from inspect import signature

sig = signature(function) no_of_params = len(sig.parameters) param_names = list(sig.parameters.keys()) param_kinds = [a.kind for a in sig.parameters.values()]


[back to top](#table-of-contents)

### Metaprogramming

- Code that generates code
- Type

- Type is the root class
- If only passed an object it returns its type (class)
  - Otherwise it creates a new class

```python
class = type('class_name', parents_tuple, attributes_dict)

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

  • Meta Class

    • A class that creates classes
    • New() is a class method that gets called before init()
      • If it returns an instance of its class, then that instance gets passed to init() as a 'self' argument
      • It receives the same arguments as init(), except for the first one that specifies the desired type of the returned instance (MyMetaClass in our case)
      • new() can also be called directly, usually from a new() method of a child class (def __new__(cls): return super().__new__(cls))
      • The only difference between the examples above is that my_meta_class() returns a class of type type, while MyMetaClass() returns a class of type MyMetaClass
    def my_meta_class(name, parents, attrs):
          attrs['a'] = 'abcde'
          return type(name, parents, attrs)

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

  • Metaclass Attribute

    • Right before a class is created it checks if it has the 'metaclass' attribute defined
    • If not, it recursively checks if any of his parents has it defined and eventually comes to type()
    class MyClass(metaclass=MyMetaClass):
        b = 12345

MyClass.a, MyClass.b # ('abcde', 12345)


- Type Diagram

```python
type(MyClass) == MyMetaClass  # MyClass is an instance of MyMetaClass
type(MyMetaClass) == type  # MyMetaClass is an instance of type
  • Inheritance Diagram
MyClass.__base__ == object  # MyClass is a subclass of object
MyMetaClass.__base__ == type  # MyMetaClass is a subclass of type

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Eval​

from ast import literal_eval


literal_eval('1 + 2')  # 3
literal_eval('[1, 2, 3]')  # [1, 2, 3]
literal_eval('abs(1)')  # ValueError: malformed node or string

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Coroutine​

  • Coroutines have a lot in common with threads, but unlike threads, they only give up control when they call another coroutine and they don’t use as much memory
  • Coroutine definition starts with async and its call with await
  • asyncio.run(coroutine) is the main entry point for asynchronous programs
  • Functions wait(), gather() and as_completed() can be used when multiple coroutines need to be started at the same time
  • Asyncio module also provides its own Queue, Event, Lock and Semaphore classes
  • Example
    • Runs a terminal game where you control an asterisk that must avoid numbers:
import asyncio, collections, curses, enum, random


P = collections.namedtuple('P', 'x y')  # Position
D = enum.Enum('D', 'n e s w')  # Direction

def main(screen):
    curses.curs_set(0)  # Makes cursor invisible
    screen.nodelay(True)  # Makes getch() non-blocking
    asyncio.run(main_coroutine(screen))  # Starts running asyncio code


async def main_coroutine(screen):
    state = {'*': P(0, 0), **{id_: P(30, 10) for id_ in range(10)}}
    moves = asyncio.Queue()
    coros = (*(random_controller(id_, moves) for id_ in range(10)),
             human_controller(screen, moves),
             model(moves, state, *screen.getmaxyx()),
             view(state, screen))
    await asyncio.wait(coros, return_when=asyncio.FIRST_COMPLETED)


async def random_controller(id_, moves):
    while True:
        moves.put_nowait((id_, random.choice(list(D))))
        await asyncio.sleep(random.random() / 2)


async def human_controller(screen, moves):
    while True:
        ch = screen.getch()
        key_mappings = {259: D.n, 261: D.e, 258: D.s, 260: D.w}
        if ch in key_mappings:
            moves.put_nowait(('*', key_mappings[ch]))
        await asyncio.sleep(0.01)


async def model(moves, state, height, width):
    while state['*'] not in {p for id_, p in state.items() if id_ != '*'}:
        id_, d = await moves.get()
        p      = state[id_]
        deltas = {D.n: P(0, -1), D.e: P(1, 0), D.s: P(0, 1), D.w: P(-1, 0)}
        new_p  = P(*[sum(a) for a in zip(p, deltas[d])])
        if 0 = new_p.x  width-1 and 0 = new_p.y  height:
            state[id_] = new_p


async def view(state, screen):
    while True:
        screen.clear()
        for id_, p in state.items():
            screen.addstr(p.y, p.x, str(id_))
        await asyncio.sleep(0.01)


curses.wrapper(main)

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Libraries​

Progress Bar​

  • pip3 install tqdm
from tqdm import tqdm
from time import sleep


for el in tqdm([1, 2, 3]):
    sleep(0.2)

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Plot​

  • pip3 install matplotlib
from matplotlib import pyplot


pyplot.plot(y_data [, label=str])
pyplot.plot(x_data, y_data)
pyplot.legend()  # Adds a legend
pyplot.savefig('path')  # Saves the figure
pyplot.show()  # Displays the figure
pyplot.clf()  # Clears the figure

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Table​

  • Prints a CSV file as an ASCII table:
  • pip3 install tabulate
import csv, tabulate


with open('test.csv', encoding='utf-8', newline='') as file:
    rows = csv.reader(file)
    header = [a.title() for a in next(rows)]
    table = tabulate.tabulate(rows, header)
    print(table)

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Curses​

  • Clears the terminal, prints a message and waits for the ESC key press:
from curses import wrapper, curs_set, ascii
from curses import KEY_UP, KEY_RIGHT, KEY_DOWN, KEY_LEFT


def main():
    wrapper(draw)


def draw(screen):
    curs_set(0)  # Makes cursor invisible
    screen.nodelay(True)  # Makes getch() non-blocking
    screen.clear()
    screen.addstr(0, 0, 'Press ESC to quit.')  # Coordinates are y, x
    while screen.getch() != ascii.ESC:
      pass


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


if __name__ == '__main__':
    main()

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Logging​

  • pip3 install loguru
  • Levels: debug, info, success, warning, error, critical
from loguru import logger


logger.add('debug_{time}.log', colorize=True)  # Connects a log file
logger.add('error_{time}.log', level='ERROR')  # Another file for errors or higher
logger.level('A logging message.')

  • Exceptions

    • Exception description, stack trace and values of variables are appended automatically
    try:
        ...
    except exception:
        logger.exception('An error happened.')

  • Rotation

    • Argument that sets a condition when a new log file is created
    • int - Max file size in bytes
    • timedelta - Max age of a file
    • time - Time of day
    • str - Any of above as a string: '100 MB', '1 month', 'monday at 12:00', ...
    rotation = int|datetime.timedelta|datetime.time|str

  • Retention

    • Sets a condition which old log files get deleted
    • int - Max number of files
    • timedelta - Max age of a file
    • str - Max age as a string: '1 week, 3 days', '2 months', ...
    retention = int|datetime.timedelta|str

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Scraping​

  • Scrapes Python's URL, version number and logo from Wikipedia page:
  • pip3 install requests beautifulsoup4
import requests, sys
from bs4 import BeautifulSoup


URL = 'https://en.wikipedia.org/wiki/Python_(programming_language)'

try:
    html  = requests.get(URL).text
    doc   = BeautifulSoup(html, '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]
    url_i = rows[0].find('img')['src']
    image = requests.get(f'https:{url_i}').content
    with open('test.png', 'wb') as file:
        file.write(image)
    print(link, ver)
except requests.exceptions.ConnectionError:
    print("You've got problems with connection.", file=sys.stderr)

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Web​

  • pip3 install bottle
from bottle import run, route, static_file, template, post, request, response
import json

  • Run

    run(host='localhost', port=8080)  # Runs locally
    run(host='0.0.0.0', port=80)  # Runs globally

  • Static Request

    @route('/img/image')
    def send_image(image):
        return static_file(image, 'img_dir/', 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]

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Profile​

  • Stopwatch

    from time import time

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


- High performance

```python
from time import perf_counter


start_time = perf_counter()  # Seconds since restart
...
duration = perf_counter() - start_time
  • Timing a Snippet
from timeit import timeit


timeit('"-".join(str(a) for a in range(100))', ... , number=10000, globals=globals(), setup='pass')  # 0.34986

  • Profiling by Line

    • pip3 install line_profiler memory_profiler
    @profile
    def main():
        a = [*range(10000)]
        b = {*range(10000)}
    main()
    • kernprof -lv test.py
    • python3 -m memory_profiler test.py

  • Call Graph

    • Generates a PNG image of a 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(drawer): code_to_be_profiled


[back to top](#table-of-contents)

### NumPy

- `pip3 install numpy`
- Array manipulation mini-language
- It can run up to one hundred times faster than the equivalent Python code
- Shape is a tuple of dimension sizes
- Axis is the index of a dimension that gets collapsed
- The leftmost dimension has index 0

```python
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)

  • Indexing

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

  • 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 in length, left-pad the shorter 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, raise an error

      • Example: 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]

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Image​

  • pip3 install pillow
from PIL import Image


Image = Image.new('mode', (width, height))
Image = Image.open('path')
Image = Image.convert('mode')
Image.save('path')
Image.show()

tuple/int = Image.getpixel((x, y))  # Returns a pixel
Image.putpixel((x, y), tuple/int)  # Writes a pixel to the image
ImagingCore = Image.getdata()  # Returns a sequence of pixels
Image.putdata(list/ImagingCore)  # Writes a sequence of pixels
Image.paste(Image, (x, y))  # Writes an image to the image

2d_array = np.array(Image)  # Creates NumPy array from greyscale image
3d_array = np.array(Image)  # Creates NumPy array from color image
Image = Image.fromarray(array)  # Creates image from NumPy array of floats

  • 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

  • Examples

    • Creates a PNG image of a rainbow gradient

      WIDTH, HEIGHT = 100, 100
      size = WIDTH * HEIGHT
      hues = [255 * i/size for i in range(size)]
      img = Image.new('HSV', (WIDTH, HEIGHT))
      img.putdata([(int(h), 255, 255) for h in hues])
      img.convert('RGB').save('test.png')

    • Adds noise to a PNG image

      from random import randint
add_noise = lambda value: max(0, min(255, value + randint(-20, 20)))
img = Image.open('test.png').convert('HSV')
img.putdata([(add_noise(h), s, v) for h, s, v in img.getdata()])
img.convert('RGB').save('test.png')
```

  • Drawing

    • Use fill=color to set the primary color
    • Use outline=color to set the secondary color
    • Color can be specified as a tuple, int, #rrggbb string or a color name
    from PIL import ImageDraw

ImageDraw = ImageDraw.Draw(Image) ImageDraw.point((x, y), fill=None) ImageDraw.line((x1, y1, x2, y2 [, ...]), fill=None, width=0, joint=None) ImageDraw.arc((x1, y1, x2, y2), from_deg, to_deg, fill=None, width=0) ImageDraw.rectangle((x1, y1, x2, y2), fill=None, outline=None, width=0) ImageDraw.polygon((x1, y1, x2, y2 [, ...]), fill=None, outline=None) ImageDraw.ellipse((x1, y1, x2, y2), fill=None, outline=None, width=0)


[back to top](#table-of-contents)

### Animation

- `pip3 install pillow imageio`
- Creates a GIF of a bouncing ball

```python
from PIL import Image, ImageDraw
import imageio


WIDTH, R = 126, 10
frames = []

for velocity in range(15):
    y = sum(range(velocity+1))
    frame = Image.new('L', (WIDTH, WIDTH))
    draw  = ImageDraw.Draw(frame)
    draw.ellipse((WIDTH/2-R, y, WIDTH/2+R, y+R*2), fill='white')
    frames.append(frame)

frames += reversed(frames[1:-1])
imageio.mimsave('test.gif', frames, duration=0.03)

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Audio​

  • Bytes object contains a sequence of frames, each consisting of one or more samples
  • In a stereo signal, the first sample of a frame belongs to the left channel
  • Each sample consists of one or more bytes that, when converted to an integer, indicate the displacement of a speaker membrane at a given moment
  • If sample width is one, then the integer should be encoded unsigned
  • For all other sizes, the integer should be encoded signed with little-endian byte order
import wave


Wave_read = wave.open('path', 'rb')  # Opens the WAV file
framerate = Wave_read.getframerate()  # Number of frames per second
nchannels = Wave_read.getnchannels()  # Number of samples per frame
sampwidth = Wave_read.getsampwidth()  # Sample size in bytes
nframes = Wave_read.getnframes()  # Number of frames
params = Wave_read.getparams()  # Immutable collection of above
bytes = Wave_read.readframes(nframes)  # Returns next 'nframes' frames

Wave_write = wave.open('path', 'wb')  # Truncates existing file
Wave_write.setframerate(int)  # 44100 for CD, 48000 for video
Wave_write.setnchannels(int)  # 1 for mono, 2 for stereo
Wave_write.setsampwidth(int)  # 2 for CD quality sound
Wave_write.setparams(params)  # Sets all parameters
Wave_write.writeframes(bytes)  # Appends frames to the file

  • Sample Values

    sampwidthminzeromax
    10128255
    2-32768032767
    3-838860808388607
    4-214748364802147483647

  • Read Float Samples from WAV File

    def read_wav_file(filename):
        def get_int(a_bytes):
            an_int = int.from_bytes(a_bytes, 'little', signed=width!=1)
            return an_int - 128 * (width == 1)
        with wave.open(filename, 'rb') as file:
            width  = file.getsampwidth()
            frames = file.readframes(-1)
        byte_samples = (frames[i: i + width] for i in range(0, len(frames), width))
        return [get_int(b) / pow(2, width * 8 - 1) for b in byte_samples]

  • Write Float Samples to WAV File

def write_to_wav_file(filename, float_samples, nchannels=1, sampwidth=2, framerate=44100):
    def get_bytes(a_float):
        a_float = max(-1, min(1 - 2e-16, a_float))
        a_float += sampwidth == 1
        a_float *= pow(2, sampwidth * 8 - 1)
        return int(a_float).to_bytes(sampwidth, 'little', signed=sampwidth!=1)
    with wave.open(filename, 'wb') as file:
        file.setnchannels(nchannels)
        file.setsampwidth(sampwidth)
        file.setframerate(framerate)
        file.writeframes(b''.join(get_bytes(f) for f in float_samples))

  • Examples

    • Saves a sine wave to a mono WAV file

      from math import pi, sin
samples_f = (sin(i * 2 * pi * 440 / 44100) for i in range(100000))
write_to_wav_file('test.wav', samples_f)
```

  • Adds noise to a mono WAV file

    from random import random
add_noise = lambda value: value + (random() - 0.5) * 0.03
samples_f = (add_noise(f) for f in read_wav_file('test.wav'))
write_to_wav_file('test.wav', samples_f)
```

  • Plays a WAV file

    • pip3 install simpleaudio
    from simpleaudio import play_buffer
with wave.open('test.wav', 'rb') as file:
    p = file.getparams()
    frames = file.readframes(-1)
    play_buffer(frames, p.nchannels, p.sampwidth, p.framerate)
```

  • Text to Speech

    • pip3 install pyttsx3
    import pyttsx3

engine = pyttsx3.init() engine.say('Sally sells seashells by the seashore.') engine.runAndWait()


[back to top](#table-of-contents)

### Synthesizer

- Plays Popcorn by Gershon Kingsley

- `pip3 install simpleaudio`

```python
import simpleaudio, math, struct
from itertools import chain, repeat


F = 44100
P1 = '71♪,69,,71♪,66,,62♪,66,,59♪,,,'
P2 = '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 key: 8.176 * 2 ** (int(key) / 12)

parse_note = lambda note: (get_hz(note[:2]), 0.25 if '♪' in note else 0.125)

get_samples = lambda note: get_wave(*parse_note(note)) if note else get_pause(0.125)

samples_f = chain.from_iterable(get_samples(n) for n in f'{P1}{P1}{P2}'.split(','))

samples_b = b''.join(struct.pack('h', int(f * 30000)) for f in samples_f)

simpleaudio.play_buffer(samples_b, 1, 2, F)

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Games​

  • Basic Example

    • pip3 install pygame
    import pygame as pg
    pg.init()
    screen = pg.display.set_mode((500, 500))
    rect = pg.Rect(240, 240, 20, 20)
    while all(event.type != pg.QUIT for event in pg.event.get()):
        deltas = {pg.K_UP: (0, -3), pg.K_RIGHT: (3, 0), pg.K_DOWN: (0, 3), pg.K_LEFT: (-3, 0)}
        for delta in (deltas.get(i) for i, on in enumerate(pg.key.get_pressed()) if on):
            rect = rect.move(delta) if delta else rect
        screen.fill((0, 0, 0))
        pg.draw.rect(screen, (255, 255, 255), rect)
        pg.display.flip()

    • Rectangle

      • Object for storing rectangular coordinates
      Rect = pg.Rect(x, y, width, height)  # X and y are coordinates of topleft corner
      int = Rect.x/y/centerx/centery/...  # Top, right, bottom, left
      tup = Rect.topleft/center/...  # Topright, bottomright, bottomleft
      Rect = Rect.move((x, y))  # Use move_ip() to move in place

      bool = Rect.collidepoint((x, y))  # Tests if a point is inside a rectangle
      bool = Rect.colliderect(Rect)  # Tests if two rectangles overlap
      int = Rect.collidelist(list_of_Rect)  # Returns index of first colliding Rect or -1
      list = Rect.collidelistall(list_of_Rect)  # Returns indexes of all colliding Rects

    • Surface

      • Object for representing images
      Surf = pg.display.set_mode((width, height))  # Returns the display surface
      Surf = pg.Surface((width, height))  # Creates a new surface.
      Surf = pg.image.load('path')  # Loads the image
      Surf = Surf.subsurface(Rect)  # Returns a subsurface

      Surf.fill(color)  # Fills the whole surface
      Surf.set_at((x, y), color)  # Updates pixel
      Surf.blit(Surface, (x, y))  # Draws passed surface to the surface

      Surf = pg.transform.flip(Surf, xbool, ybool)
      Surf = pg.transform.rotate(Surf, degrees)
      Surf = pg.transform.scale(Surf, (width, height))

      pg.draw.line(Surf, color, (x1, y1), (x2, y2), width)
      pg.draw.arc(Surf, color, Rect, from_radians, to_radians)
      pg.draw.rect(Surf, color, Rect)
      pg.draw.polygon(Surf, color, points)
      pg.draw.ellipse(Surf, color, Rect)

    • Font

      Font = pg.font.SysFont('name', size, bold=False, italic=False)
      Font = pg.font.Font('path', size)
      Surf = Font.render(text, antialias, color [, background])

    • Sound

      Sound = pg.mixer.Sound('path')  # Loads the WAV file
      Sound.play()  # Starts playing the sound

  • Basic Mario Brothers Example

    import collections, dataclasses, enum, io, pygame, urllib.request, itertools as it
    from random import randint

P = collections.namedtuple('P', 'x y') # Position D = enum.Enum('D', 'n e s w') # Direction SIZE, MAX_SPEED = 50, P(5, 10) # Screen size, Speed limit

def main(): def get_screen(): pygame.init() return pygame.display.set_mode(2 [SIZE16])

  def get_images():
      url = 'https://gto76.github.io/python-cheatsheet/web/mario_bros.png'
      img = pygame.image.load(io.BytesIO(urllib.request.urlopen(url).read()))
      return [img.subsurface(get_rect(x, 0)) for x in range(img.get_width() // 16)]

  def get_mario():
      Mario = dataclasses.make_dataclass('Mario', 'rect spd facing_left frame_cycle'.split())
      return Mario(get_rect(1, 1), P(0, 0), False, it.cycle(range(3)))

  def get_tiles():
      positions = [p for p in it.product(range(SIZE), repeat=2) if {*p} & {0, SIZE-1}] + \
          [(randint(1, SIZE-2), randint(2, SIZE-2)) for _ in range(SIZE**2 // 10)]
      return [get_rect(*p) for p in positions]

  def get_rect(x, y):
      return pygame.Rect(x*16, y*16, 16, 16)

  run(get_screen(), get_images(), get_mario(), get_tiles())

def run(screen, images, mario, tiles): clock = pygame.time.Clock() while all(event.type != pygame.QUIT for event in pygame.event.get()): keys = {pygame.K_UP: D.n, pygame.K_RIGHT: D.e, pygame.K_DOWN: D.s, pygame.K_LEFT: D.w} pressed = {keys.get(i) for i, on in enumerate(pygame.key.get_pressed()) if on} update_speed(mario, tiles, pressed) update_position(mario, tiles) draw(screen, images, mario, tiles, pressed) clock.tick(28)

def update_speed(mario, tiles, pressed): x, y = mario.spd x += 2 ((D.e in pressed) - (D.w in pressed)) x -= x // abs(x) if x else 0 y += 1 if D.s not in get_boundaries(mario.rect, tiles) else (-10 if D.n in pressed else 0) mario.spd = P([max(-limit, min(limit, s)) for limit, s in zip(MAX_SPEED, P(x, y))])

def updateposition(mario, tiles): new_p = mario.rect.topleft larger_speed = max(abs(s) for s in mario.spd) for in range(larger_speed): mario.spd = stop_on_collision(mario.spd, get_boundaries(mario.rect, tiles)) new_p = P(*[a + s/larger_speed for a, s in zip(new_p, mario.spd)]) mario.rect.topleft = new_p

def get_boundaries(rect, tiles): deltas = {D.n: P(0, -1), D.e: P(1, 0), D.s: P(0, 1), D.w: P(-1, 0)} return {d for d, delta in deltas.items() if rect.move(delta).collidelist(tiles) != -1}

def stop_on_collision(spd, bounds): return P(x=0 if (D.w in bounds and spd.x 0) or (D.e in bounds and spd.x 0) else spd.x, y=0 if (D.n in bounds and spd.y 0) or (D.s in bounds and spd.y 0) else spd.y)

def draw(screen, images, mario, tiles, pressed): def get_frame_index(): if D.s not in get_boundaries(mario.rect, tiles): return 4 return next(mario.frame_cycle) if {D.w, D.e} & pressed else 6

  screen.fill((85, 168, 255))
  mario.facing_left = (D.w in pressed) if {D.w, D.e} & pressed else mario.facing_left
  screen.blit(images[get_frame_index() + mario.facing_left * 9], mario.rect)

  for rect in tiles:
      screen.blit(images[18 if {*rect.topleft} & {0, (SIZE-1)*16} else 19], rect)

  pygame.display.flip()

if name == 'main': main()


[back to top](#table-of-contents)

### Pandas

- `pip3 install pandas`

```python
import pandas as pd
from pandas import Series, DataFrame

  • Series

    • Ordered dictionary with a name
    Series([1, 2], index=['x', 'y'], name='a')
    """
    x  1
    y  2
    Name: a, dtype: int64
    """

    Sr = Series(list)  # Assigns RangeIndex starting at 0
    Sr = Series(dict)  # Takes dictionary's keys for index
    Sr = Series(dict/Series, index=list)  # Only keeps items with keys specified in index

    el = Sr.loc[key]  # Or: Sr.iloc[index]
    Sr = Sr.loc[keys]  # Or: Sr.iloc[indexes]
    Sr = Sr.loc[from_key : to_key_inclusive]  # Or: Sr.iloc[from_i : to_i_exclusive]

    el = Sr[key/index]  # Or: Sr.key
    Sr = Sr[keys/indexes]  # Or: Sr[key_range/range]
    Sr = Sr[bools]  # Or: Sr.i/loc[bools]

    Sr = Sr == el/Sr  # Returns a Series of bools
    Sr = Sr +-*/ el/Sr  # Non-matching keys get value NaN

    Sr = Sr.append(Sr)  # Or: pd.concat(coll_of_Sr)
    Sr = Sr.combine_first(Sr)  # Adds items that are not yet present
    Sr.update(Sr)  # Updates items that are already present

    • Aggregate, Transform, Map

      • The way aggregate() and transform() find out whether a function accepts an element or the whole Series is by passing it a single value at first and if it raises an error, then they pass it the whole Series
      • Last result has a hierarchical index. Use Sr[key_1, key_2] to get its values
      el = Sr.sum/max/mean/idxmax/all()  # Or: Sr.aggregate(agg_func)
      Sr = Sr.rank/diff/cumsum/ffill/interpl()  # Or: Sr.agg/transform(trans_func)
      Sr = Sr.fillna(el)  # Or: Sr.apply/agg/transform/map(map_func)
sr = Series([1, 2], index=['x', 'y'])
"""
x  1
y  2
"""
```

|               | 'sum' | ['sum'] | {'s': 'sum'} |
| ------------- | ----- | ------- | ------------ |
| sr.apply(...) | 3     | sum 3   | s 3          |
| sr.agg(...)   |       |         |              |

|               | 'rank' | ['rank'] | {'r': 'rank'} |
| ------------- | ------ | -------- | ------------- |
| sr.apply(...) |        | rank     |               |
| sr.agg(...)   | x 1    | x1       | rx1           |
| sr.trans(...) | y 2    | y 2      | y 2           |

  • DataFrame

    • Table with labeled rows and columns
    DataFrame([[1, 2], [3, 4]], index=['a', 'b'], columns=['x', 'y'])
    """
      x y
    a 1 2
    b 3 4
    """

    DF = DataFrame(list_of_rows)  # Rows can be either lists, dicts or series
    DF = DataFrame(dict_of_columns)  # Columns can be either lists, dicts or series

    el = DF.loc[row_key, column_key]  # Or: DF.iloc[row_index, column_index]
    Sr/DF = DF.loc[row_key/s]  # Or: DF.iloc[row_index/es]
    Sr/DF = DF.loc[:, column_key/s]  # Or: DF.iloc[:, column_index/es]
    DF = DF.loc[row_bools, column_bools]  # Or: DF.iloc[row_bools, column_bools]

    Sr/DF = DF[column_key/s]  # Or: DF.column_key
    DF = DF[row_bools]  # Keeps rows as specified by bools
    DF = DF[DF_of_bools]  # Assigns NaN to False values

    DF = DF == el/Sr/DF  # Returns DataFrame of bools
    DF = DF +-*/ el/Sr/DF  # Non-matching keys get value NaN

    DF = DF.set_index(column_key)  # Replaces row keys with values from a column
    DF = DF.reset_index()  # Moves row keys to their own column
    DF = DF.filter('regex', axis=1)  # Only keeps columns whose key matches the regex
    DF = DF.melt(id_vars=column_key/s)  # Converts DF from wide to long format

    • Merge, Join, Concat

      • l.merge(r, on="y", how=...)

        • outer

            x y z
          0 1 2 .
          1 3 4 5
          2 . 6 7

        • inner

          x y z
          3 4 5

        • left

          x y z
          1 2 .
          3 4 5

        • Joins / Merges on column

        • also accepts left_on and right_on parameters

        • uses inner by default

      • l.join(r, lsuffix="l", rsuffix="r", how=...)

        • outer

            x yl yr z
          a 1 2  .  .
          b 3 4  4  5
          c . .  6  7

        • inner

          x yl yr z
          3 4  4  5

        • left

          x yl yr z
          1 2  .  .
          3 4  4  5

        • Joins / Merges on row keys

        • uses left by default

      • pd.concat([l, r], axis=0, join=...)

        • outer

            x y z
          a 1 2 .
          b 3 4 .
          b . 4 5
          c . 6 7

        • inner

          y
          2
          4
          4
          6

        • Adds rows at the bottom

        • uses outer by default

        • by default works the same as l.append(r)

      • pd.concat([l, r], axis=1, join=...)

        • outer

            x y y z
          a 1 2 . .
          b 3 4 4 5
          c . . 6 7

        • inner

          x y y z
          3 4 4 5

        • Adds columns at the right end

        • uses outer by default

      • l.combine_first(r)

        • outer

            x y z
          a 1 2 .
          b 3 4 5
          c . 6 7

        • Adds missing rows and columns

      l = DataFrame([[1, 2], [3, 4]], index=['a', 'b'], columns=['x', 'y'])
      """
        x y
      a 1 2
      b 3 4
      """

      r = DataFrame([[4, 5], [6, 7]], index=['b', 'c'], columns=['y', 'z'])
      """
        y z
      b 4 5
      c 6 7
      """

    • Aggregate, Transform, Map

      • All operations operate on columns by default
      • Use axis=1 parameter to process the rows instead
      • Use DF[col_key_1, col_key_2][row_key] to get the fifth result's values.
      Sr = DF.sum/max/mean/idxmax/all()  # Or: DF.apply/agg/transform(agg_func)
      DF = DF.rank/diff/cumsum/ffill/interpl()  # Or: DF.apply/agg/transform(trans_func)
      DF = DF.fillna(el)  # Or: DF.applymap(map_func)

      # example
      df = DataFrame([[1, 2], [3, 4]], index=['a', 'b'], columns=['x', 'y'])
        x y
      a 1 2
      b 3 4

    • Encode, Decode

      DF = pd.read_json/html('str/path/url')
      DF = pd.read_csv/pickle/excel('path/url')
      DF = pd.read_sql('query', connection)
      DF = pd.read_clipboard()

      dict = DF.to_dict(['d/l/s/sp/r/i'])
      str  = DF.to_json/html/csv/markdown/latex([path])
      DF.to_pickle/excel(path)
      DF.to_sql('table_name', connection)

  • GroupBy

    • Object that groups together rows of a dataframe based on the value of the passed column

      df = DataFrame([[1, 2, 3], [4, 5, 6], [7, 8, 6]], index=list('abc'), columns=list('xyz'))
      df.groupby('z').get_group(3)
      """
        x y
      a 1 2
      """

      df.groupby('z').get_group(6)
      """
        x y
      b 4 5
      c 7 8
      """

      GB = DF.groupby(column_key/s)  # DF is split into groups based on passed column
      DF = GB.get_group(group_key)  # Selects a group by value of grouping column

    • Aggregate, Transform, Map

      DF = GB.sum/max/mean/idxmax/all()  # Or: GB.apply/agg(agg_func)
      DF = GB.rank/diff/cumsum/ffill()  # Or: GB.aggregate(trans_func)
      DF = GB.fillna(el)  # Or: GB.transform(map_func)

      gb = df.groupby('z')
           x y z
      3: a 1 2 3
      6: b 4 5 6
         c 7 8 6

  • Rolling

    • Object for rolling window calculations

      R_Sr/R_DF/R_GB = Sr/DF/GB.rolling(window_size)  # Also: `min_periods=None, center=False`.
      R_Sr/R_DF = R_DF/R_GB[column_key/s]  # Or: R.column_key
      Sr/DF/DF = R_Sr/R_DF/R_GB.sum/max/mean()  # Or: R.apply/agg(agg_func/str)

back to top

Plotly​

  • pip3 install pandas plotly

  • Covid Deaths by Continent example

    import pandas as pd
    import plotly.express

covid = pd.read_csv('https://covid.ourworldindata.org/data/owid-covid-data.csv', usecols=['iso_code', 'date', 'total_deaths', 'population']) continents = pd.read_csv('https://datahub.io/JohnSnowLabs/country-and-continent-codes-' + \ 'list/r/country-and-continent-codes-list-csv.csv', usecols=['Three_Letter_Country_Code', 'Continent_Name']) df = pd.merge(covid, continents, left_on='iso_code', right_on='Three_Letter_Country_Code') df = df.groupby(['Continent_Name', 'date']).sum().reset_index() df['Total Deaths per Million'] = df.total_deaths * 1e6 / df.population df = df[('2020-03-14' df.date) & (df.date '2020-06-25')] df = df.rename({'date': 'Date', 'Continent_Name': 'Continent'}, axis='columns') plotly.express.line(df, x='Date', y='Total Deaths per Million', color='Continent').show()


- Confirmed Covid Cases, Dow Jones, Gold, and Bitcoin Price

```python
import pandas, datetime
import plotly.graph_objects as go


def main():
    display_data(wrangle_data(*scrape_data()))


def scrape_data():
    def scrape_yahoo(id_):
          BASE_URL = 'https://query1.finance.yahoo.com/v7/finance/download/'
        now  = int(datetime.datetime.now().timestamp())
        url  = f'{BASE_URL}{id_}?period1=1579651200&period2={now}&interval=1d&events=history'
        return pandas.read_csv(url, usecols=['Date', 'Close']).set_index('Date').Close

    covid = pd.read_csv('https://covid.ourworldindata.org/data/owid-covid-data.csv',
                        usecols=['date', 'total_cases'])
    covid = covid.groupby('date').sum()
    dow, gold, bitcoin = [scrape_yahoo(id_) for id_ in ('^DJI', 'GC=F', 'BTC-USD')]
    dow.name, gold.name, bitcoin.name = 'Dow Jones', 'Gold', 'Bitcoin'
    return covid, dow, gold, bitcoin


def wrangle_data(covid, dow, gold, bitcoin):
    df = pandas.concat([covid, dow, gold, bitcoin], axis=1)
    df = df.loc['2020-02-23':].iloc[:-2]
    df = df.interpolate()
    df.iloc[:, 1:] = df.rolling(10, min_periods=1, center=True).mean().iloc[:, 1:]
    df.iloc[:, 1:] = df.iloc[:, 1:] / df.iloc[0, 1:] * 100
    return df


def display_data(df):
    def get_trace(col_name):
        return go.Scatter(x=df.index, y=df[col_name], name=col_name, yaxis='y2')
    traces = [get_trace(col_name) for col_name in df.columns[1:]]
    traces.append(go.Scatter(x=df.index, y=df.total_cases, name='Total Cases', yaxis='y1'))
    figure = go.Figure()
    figure.add_traces(traces)
    figure.update_layout(
        yaxis1=dict(title='Total Cases', rangemode='tozero'),
        yaxis2=dict(title='%', rangemode='tozero', overlaying='y', side='right'),
        legend=dict(x=1.1)
    ).show()


if __name__ == '__main__':
    main()

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Cython​

  • Library that compiles Python code into C
  • pip3 install cython
import pyximport; pyximport.install()
import cython_script


cython_script.main()

  • Definitions

    • All cdef definitions are optional, but they contribute to the speed-up
    • Script needs to be saved with a pyx extension
    cdef type var_name = el
    cdef type[n_elements] var_name = [el_1, el_2, ...]
    cdef type/void func_name(type arg_name_1, ...):

    cdef class class_name:
        cdef public type attr_name

        def __init__(self, type arg_name):
            self.attr_name = arg_name

cdef enum enum_name: member_name_1, member_name_2, ...


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