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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 3/42310-9
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: <real>e±<int>
<complex> = complex(real=0, imag=0)  # Or: <real> ± <real>j
<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> = ±0b<bin>  # Or: ±0x<hex>
<int> = int('±<bin>', 2)  # Or: int('±<hex>', 16)
<int> = int('±0b<bin>', 0)  # Or: int('±0x<hex>', 0)
'[-]0b<bin>' = 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)

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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
    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>)

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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
    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>
    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
    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__

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Enum​

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

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System​

Exit​

  • Exits the interpreter by raising SystemExit exception
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)

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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>

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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)

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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

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

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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:

    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'

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Data​

JSON​

  • Text file format for storing collections of strings and numbers
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)

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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)

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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
    <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)]

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MySQL​

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

    • pip3 install mysql-connector
    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
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()]

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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
    <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

    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

    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>

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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
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)

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Animation​

  • pip3 install pillow imageio

  • Creates a GIF of a bouncing ball

    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()

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Synthesizer​

  • Plays Popcorn by Gershon Kingsley

    • pip3 install simpleaudio
    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 * [SIZE*16])

        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 update_position(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()

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Pandas​

  • pip3 install pandas
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(...)3sum 3s 3
      sr.agg(...)
      'rank'['rank']{'r': 'rank'}
      sr.apply(...)rank
      sr.agg(...)x 1x1rx1
      sr.trans(...)y 2y 2y 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>)

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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

    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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