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Python 速查表
Contents
1. Collections: List
, Dictionary
, Set
, Tuple
, Range
, Enumerate
, Iterator
, Generator
.
2. Types: Type
,String
, Regular_Exp
, Format
, Numbers
, Combinatorics
, Datetime
.
3. Syntax: Args
, Inline
, Import
, Decorator
, Class
, Duck_Types
, Enum
, Exception
.
4. System: Exit
, Print
, Input
, Command_Line_Arguments
, Open
, Path
, OS_Commands
.
5. Data: JSON
, Pickle
, CSV
, SQLite
, Bytes
, Struct
, Array
, Memory_View
, Deque
.
6. Advanced: Operator
, Match_Stmt
, Logging
, Introspection
, Threading
, Coroutines
.
Main
python
if __name__ == '__main__': # Skips next line if file was imported.
main() # Runs `def main(): ...` function.
List
python
<list> = [<el_1>, <el_2>, ...] # Creates new list. Also list(<collection>).
python
<el> = <list>[index] # First index is 0. Last -1. Allows assignments.
<list> = <list>[<slice>] # Also <list>[from_inclusive : to_exclusive : ±step].
python
<list>.append(<el>) # Appends element to the end. Also <list> += [<el>].
<list>.extend(<collection>) # Appends elements to the end. Also <list> += <coll>.
python
<list>.sort() # Sorts elements in ascending order.
<list>.reverse() # Reverses the list in-place.
<list> = sorted(<collection>) # Returns new list with sorted elements.
<iter> = reversed(<list>) # Returns reversed iterator of elements.
python
<el> = max(<collection>) # Returns largest element. Also min(<el_1>, ...).
<num> = sum(<collection>) # Returns sum of elements. Also math.prod(<coll>).
python
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]))
flatter_list = list(itertools.chain.from_iterable(<list>))
- For details about sort(), sorted(), min() and max() see Sortable.
- Module operator has function itemgetter() that can replace listed lambdas.
- This text uses the term collection instead of iterable. For rationale see Collection.
python
<int> = len(<list>) # Returns number of items. Also works on dict, set and string.
<int> = <list>.count(<el>) # Returns number of occurrences. Also `if <el> in <coll>: ...`.
<int> = <list>.index(<el>) # Returns index of the first occurrence or raises ValueError.
<el> = <list>.pop() # Removes and returns item from the end or at index if passed.
<list>.insert(<int>, <el>) # Inserts item at index and moves the rest to the right.
<list>.remove(<el>) # Removes first occurrence of the item or raises ValueError.
<list>.clear() # Removes all items. Also works on dictionary and set.
Dictionary
python
<dict> = {key_1: val_1, key_2: val_2, ...} # Use `<dict>[key]` to get or set the value.
python
<view> = <dict>.keys() # Collection of keys that reflects changes.
<view> = <dict>.values() # Collection of values that reflects changes.
<view> = <dict>.items() # Coll. of key-value tuples that reflects chgs.
python
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>) # Returns a dict with default value `<type>()`.
<dict> = collections.defaultdict(lambda: 1) # Returns a dict with default value 1.
python
<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.
python
<dict>.update(<dict>) # Adds items. Replaces ones with matching keys.
value = <dict>.pop(key) # Removes item or raises KeyError if missing.
{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} # Filters the dictionary by keys.
Counter
python
>>> from collections import Counter
>>> counter = Counter(['blue', 'blue', 'blue', 'red', 'red'])
>>> counter['yellow'] += 1
>>> print(counter.most_common())
[('blue', 3), ('red', 2), ('yellow', 1)]
Set
python
<set> = {<el_1>, <el_2>, ...} # Use `set()` for empty set.
python
<set>.add(<el>) # Or: <set> |= {<el>}
<set>.update(<collection> [, ...]) # Or: <set> |= <set>
python
<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>
python
<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.
python
<frozenset> = frozenset(<collection>)
Tuple
Tuple is an immutable and hashable list.
python
<tuple> = () # Empty tuple.
<tuple> = (<el>,) # Or: <el>,
<tuple> = (<el_1>, <el_2> [, ...]) # Or: <el_1>, <el_2> [, ...]
Named Tuple
Tuple's subclass with named elements.
python
>>> from collections import namedtuple
>>> Point = namedtuple('Point', 'x y')
>>> p = Point(1, y=2); p
Point(x=1, y=2)
>>> p[0]
1
>>> p.x
1
>>> getattr(p, 'y')
2
Range
Immutable and hashable sequence of integers.
python
<range> = range(stop) # range(to_exclusive)
<range> = range(start, stop) # range(from_inclusive, to_exclusive)
<range> = range(start, stop, ±step) # range(from_inclusive, to_exclusive, ±step_size)
python
>>> [i for i in range(3)]
[0, 1, 2]
Enumerate
python
for i, el in enumerate(<coll>, start=0): # Returns next element and its index on each pass.
...
Iterator
python
<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
python
import itertools as it
python
<iter> = it.count(start=0, step=1) # Returns updated value endlessly. Accepts floats.
<iter> = it.repeat(<el> [, times]) # Returns element endlessly or 'times' times.
<iter> = it.cycle(<collection>) # Repeats the sequence endlessly.
python
<iter> = it.chain(<coll>, <coll> [, ...]) # Empties collections in order (figuratively).
<iter> = it.chain.from_iterable(<coll>) # Empties collections inside a collection in order.
python
<iter> = it.islice(<coll>, to_exclusive) # Only returns first 'to_exclusive' elements.
<iter> = it.islice(<coll>, from_inc, …) # `to_exclusive, +step_size`. Indices can be None.
Generator
- Any function that contains a yield statement returns a generator.
- Generators and iterators are interchangeable.
python
def count(start, step):
while True:
yield start
start += step
python
>>> counter = count(10, 2)
>>> next(counter), next(counter), next(counter)
(10, 12, 14)
Type
- Everything is an object.
- Every object has a type.
- Type and class are synonymous.
python
<type> = type(<el>) # Or: <el>.__class__
<bool> = isinstance(<el>, <type>) # Or: issubclass(type(<el>), <type>)
python
>>> type('a'), 'a'.__class__, str
(<class 'str'>, <class 'str'>, <class 'str'>)
Some types do not have built-in names, so they must be imported:
python
from types import FunctionType, MethodType, LambdaType, GeneratorType, ModuleType
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. ABC can also manually decide whether or not a specific class is its virtual subclass, usually based on which methods the class has implemented. For instance, Iterable ABC looks for method iter(), while Collection ABC looks for iter(), contains() and len().
python
>>> from collections.abc import Iterable, Collection, Sequence
>>> isinstance([1, 2, 3], Iterable)
True
text
+------------------+------------+------------+------------+
| | Iterable | Collection | Sequence |
+------------------+------------+------------+------------+
| list, range, str | yes | yes | yes |
| dict, set | yes | yes | |
| iter | yes | | |
+------------------+------------+------------+------------+
python
>>> from numbers import Number, Complex, Real, Rational, Integral
>>> isinstance(123, Number)
True
text
+--------------------+----------+----------+----------+----------+----------+
| | Number | Complex | Real | Rational | Integral |
+--------------------+----------+----------+----------+----------+----------+
| int | yes | yes | yes | yes | yes |
| fractions.Fraction | yes | yes | yes | yes | |
| float | yes | yes | yes | | |
| complex | yes | yes | | | |
| decimal.Decimal | yes | | | | |
+--------------------+----------+----------+----------+----------+----------+
String
Immutable sequence of characters.
python
<str> = <str>.strip() # Strips all whitespace characters from both ends.
<str> = <str>.strip('<chars>') # Strips passed characters. Also lstrip/rstrip().
python
<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) # On [\n\r\f\v\x1c-\x1e\x85\u2028\u2029] and \r\n.
<str> = <str>.join(<coll_of_strings>) # Joins elements using string as a separator.
python
<bool> = <sub_str> in <str> # Checks if string contains the substring.
<bool> = <str>.startswith(<sub_str>) # Pass tuple of strings for multiple options.
<int> = <str>.find(<sub_str>) # Returns start index of the first match or -1.
<int> = <str>.index(<sub_str>) # Same, but raises ValueError if there's no match.
python
<str> = <str>.lower() # Changes the case. Also upper/capitalize/title().
<str> = <str>.replace(old, new [, count]) # Replaces 'old' with 'new' at most 'count' times.
<str> = <str>.translate(<table>) # Use `str.maketrans(<dict>)` to generate table.
python
<str> = chr(<int>) # Converts int to Unicode character.
<int> = ord(<str>) # Converts Unicode character to int.
- Use
'unicodedata.normalize("NFC", <str>)'
on strings like'Motörhead'
before comparing them to other strings, because'ö'
can be stored as one or two characters. 'NFC'
converts such characters to a single character, while'NFD'
converts them to two.
Property Methods
python
<bool> = <str>.isdecimal() # Checks for [0-9]. Also [०-९] and [٠-٩].
<bool> = <str>.isdigit() # Checks for [²³¹…] and isdecimal().
<bool> = <str>.isnumeric() # Checks for [¼½¾…], [零〇一…] and isdigit().
<bool> = <str>.isalnum() # Checks for [a-zA-Z…] and isnumeric().
<bool> = <str>.isprintable() # Checks for [ !#$%…] and isalnum().
<bool> = <str>.isspace() # Checks for [ \t\n\r\f\v\x1c-\x1f\x85\xa0…].
Regex
Functions for regular expression matching.
python
import re
<str> = re.sub(r'<regex>', new, text, count=0) # Substitutes all occurrences with 'new'.
<list> = re.findall(r'<regex>', text) # Returns all occurrences as strings.
<list> = re.split(r'<regex>', text, maxsplit=0) # Add brackets around regex to keep matches.
<Match> = re.search(r'<regex>', text) # First occurrence of the pattern or None.
<Match> = re.match(r'<regex>', text) # Searches only at the beginning of the text.
<iter> = re.finditer(r'<regex>', text) # Returns all occurrences as Match objects.
- Raw string literals do not interpret escape sequences, thus enabling us to use regex-specific escape sequences that cause SyntaxWarning in normal string literals (since 3.12).
- Argument 'new' of re.sub() can be a function that accepts Match object and returns a str.
- Argument
'flags=re.IGNORECASE'
can be used with all functions. - Argument
'flags=re.MULTILINE'
makes'^'
and'$'
match the start/end of each line. - Argument
'flags=re.DOTALL'
makes'.'
also accept the'\n'
. 're.compile(<regex>)'
returns a Pattern object with methods sub(), findall(), …
Match Object
python
<str> = <Match>.group() # Returns the whole match. Also group(0).
<str> = <Match>.group(1) # Returns part inside the first brackets.
<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
python
'\d' == '[0-9]' # Also [०-९…]. Matches a decimal character.
'\w' == '[a-zA-Z0-9_]' # Also [ª²³…]. Matches an alphanumeric or _.
'\s' == '[ \t\n\r\f\v]' # Also [\x1c-\x1f…]. Matches a whitespace.
- By default, decimal characters and alphanumerics from all alphabets are matched unless
'flags=re.ASCII'
is used. It restricts special sequence matches to the first 128 Unicode characters and also prevents'\s'
from accepting'\x1c'
,'\x1d'
,'\x1e'
and'\x1f'
(non-printable characters that divide text into files, tables, rows and fields, respectively). - Use a capital letter for negation (all non-ASCII characters will be matched when used in combination with ASCII flag).
Format
perl
<str> = f'{<el_1>}, {<el_2>}' # Curly brackets can also contain expressions.
<str> = '{}, {}'.format(<el_1>, <el_2>) # Or: '{0}, {a}'.format(<el_1>, a=<el_2>)
<str> = '%s, %s' % (<el_1>, <el_2>) # Redundant and inferior C-style formatting.
Example
python
>>> Person = collections.namedtuple('Person', 'name height')
>>> person = Person('Jean-Luc', 187)
>>> f'{person.name} is {person.height / 100} meters tall.'
'Jean-Luc is 1.87 meters tall.'
General Options
python
{<el>:<10} # '<el> '
{<el>:^10} # ' <el> '
{<el>:>10} # ' <el>'
{<el>:.<10} # '<el>......'
{<el>:0} # '<el>'
- Objects are rendered using
'format(<el>, "<options>")'
. - Options can be generated dynamically:
f'{<el>:{<str/int>}[…]}'
. - Adding
'='
to the expression prepends it to the output:f'{1+1=}'
returns'1+1=2'
. - Adding
'!r'
to the expression converts object to string by calling its repr() method.
Strings
python
{'abcde':10} # 'abcde '
{'abcde':10.3} # 'abc '
{'abcde':.3} # 'abc'
{'abcde'!r:10} # "'abcde' "
Numbers
python
{123456:10} # ' 123456'
{123456:10,} # ' 123,456'
{123456:10_} # ' 123_456'
{123456:+10} # ' +123456'
{123456:=+10} # '+ 123456'
{123456: } # ' 123456'
{-123456: } # '-123456'
Floats
python
{1.23456:10.3} # ' 1.23'
{1.23456:10.3f} # ' 1.235'
{1.23456:10.3e} # ' 1.235e+00'
{1.23456:10.3%} # ' 123.456%'
Comparison of presentation types:
text
+--------------+----------------+----------------+----------------+----------------+
| | {<float>} | {<float>:f} | {<float>:e} | {<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%' |
+--------------+----------------+----------------+----------------+----------------+
text
+--------------+----------------+----------------+----------------+----------------+
| | {<float>:.2} | {<float>:.2f} | {<float>:.2e} | {<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%' |
+--------------+----------------+----------------+----------------+----------------+
'{<float>:g}'
is'{<float>:.6}'
with stripped zeros, exponent starting at'1e+06'
.- When both rounding up and rounding down are possible, the one that returns result with even last digit is chosen. That makes
'{6.5:.0f}'
a'6'
and'{7.5:.0f}'
an'8'
. - This rule only effects numbers that can be represented exactly by a float (
.5
,.25
, …).
Ints
python
{90:c} # 'Z'. Unicode character with value 90.
{90:b} # '1011010'. Number 90 in binary.
{90:X} # '5A'. Number 90 in uppercase hexadecimal.
Numbers
python
<int> = int(<float/str/bool>) # Or: math.trunc(<float>)
<float> = float(<int/str/bool>) # Or: <int/float>e±<int>
<complex> = complex(real=0, imag=0) # Or: <int/float> ± <int/float>j
<Fraction> = fractions.Fraction(0, 1) # Or: Fraction(numerator=0, denominator=1)
<Decimal> = decimal.Decimal(<str/int>) # Or: Decimal((sign, digits, exponent))
'int(<str>)'
and'float(<str>)'
raise ValueError on malformed strings.- Decimal numbers are stored exactly, unlike most floats where
'1.1 + 2.2 != 3.3'
. - Floats can be compared with:
'math.isclose(<float>, <float>)'
. - Precision of decimal operations is set with:
'decimal.getcontext().prec = <int>'
.
Basic Functions
python
<num> = pow(<num>, <num>) # Or: <number> ** <number>
<num> = abs(<num>) # <float> = abs(<complex>)
<num> = round(<num> [, ±ndigits]) # `round(126, -1) == 130`
Math
python
from math import e, pi, inf, nan, isinf, isnan # `<el> == nan` is always False.
from math import sin, cos, tan, asin, acos, atan # Also: degrees, radians.
from math import log, log10, log2 # Log can accept base as second arg.
Statistics
python
from statistics import mean, median, variance # Also: stdev, quantiles, groupby.
Random
python
from random import random, randint, choice # Also: shuffle, gauss, triangular, seed.
<float> = random() # A float inside [0, 1).
<int> = randint(from_inc, to_inc) # An int inside [from_inc, to_inc].
<el> = choice(<sequence>) # Keeps the sequence intact.
Bin, Hex
python
<int> = ±0b<bin> # Or: ±0x<hex>
<int> = int('±<bin>', 2) # Or: int('±<hex>', 16)
<int> = int('±0b<bin>', 0) # Or: int('±0x<hex>', 0)
<str> = bin(<int>) # Returns '[-]0b<bin>'. Also hex().
Bitwise Operators
python
<int> = <int> & <int> # And (0b1100 & 0b1010 == 0b1000).
<int> = <int> | <int> # Or (0b1100 | 0b1010 == 0b1110).
<int> = <int> ^ <int> # Xor (0b1100 ^ 0b1010 == 0b0110).
<int> = <int> << n_bits # Left shift. Use >> for right.
<int> = ~<int> # Not. Also -<int> - 1.
Combinatorics
python
import itertools as it
python
>>> list(it.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)]
python
>>> list(it.product('abc', 'abc')) # a b c
[('a', 'a'), ('a', 'b'), ('a', 'c'), # a x x x
('b', 'a'), ('b', 'b'), ('b', 'c'), # b x x x
('c', 'a'), ('c', 'b'), ('c', 'c')] # c x x x
python
>>> list(it.combinations('abc', 2)) # a b c
[('a', 'b'), ('a', 'c'), # a . x x
('b', 'c')] # b . . x
python
>>> list(it.combinations_with_replacement('abc', 2)) # a b c
[('a', 'a'), ('a', 'b'), ('a', 'c'), # a x x x
('b', 'b'), ('b', 'c'), # b . x x
('c', 'c')] # c . . x
python
>>> list(it.permutations('abc', 2)) # a b c
[('a', 'b'), ('a', 'c'), # a . x x
('b', 'a'), ('b', 'c'), # b x . x
('c', 'a'), ('c', 'b')] # c x x .
Datetime
Provides 'date', 'time', 'datetime' and 'timedelta' classes. All are immutable and hashable.
python
# $ pip3 install python-dateutil
from datetime import date, time, datetime, timedelta, timezone
import zoneinfo, dateutil.tz
python
<D> = date(year, month, day) # Only accepts valid dates from 1 to 9999 AD.
<T> = time(hour=0, minute=0, second=0) # Also: `microsecond=0, tzinfo=None, fold=0`.
<DT> = datetime(year, month, day, hour=0) # Also: `minute=0, second=0, microsecond=0, …`.
<TD> = timedelta(weeks=0, days=0, hours=0) # Also: `minutes=0, seconds=0, microseconds=0`.
- Aware times and datetimes have defined timezone, while naive don't. If object is naive, it is presumed to be in the system's timezone!
'fold=1'
means the second pass in case of time jumping back for one hour.- Timedelta normalizes arguments to ±days, seconds (< 86 400) and microseconds (< 1M). Its str() method returns
'[±D, ]H:MM:SS[.…]'
and total_seconds() a float of all seconds. - Use
'<D/DT>.weekday()'
to get the day of the week as an int, with Monday being 0.
Now
python
<D/DTn> = D/DT.today() # Current local date or naive DT. Also DT.now().
<DTa> = DT.now(<tzinfo>) # Aware DT from current time in passed timezone.
- To extract time use
'<DTn>.time()'
,'<DTa>.time()'
or'<DTa>.timetz()'
.
Timezone
python
<tzinfo> = timezone.utc # London without daylight saving time (DST).
<tzinfo> = timezone(<timedelta>) # Timezone with fixed offset from UTC.
<tzinfo> = dateutil.tz.tzlocal() # Local timezone with dynamic offset from UTC.
<tzinfo> = zoneinfo.ZoneInfo('<iana_key>') # 'Continent/City_Name' zone with dynamic offset.
<DTa> = <DT>.astimezone([<tzinfo>]) # Converts DT to the passed or local fixed zone.
<Ta/DTa> = <T/DT>.replace(tzinfo=<tzinfo>) # Changes object's timezone without conversion.
- Timezones returned by tzlocal(), ZoneInfo() and implicit local timezone of naive objects have offsets that vary through time due to DST and historical changes of the base offset.
- To get ZoneInfo() to work on Windows run
'> pip3 install tzdata'
.
Encode
python
<D/T/DT> = D/T/DT.fromisoformat(<str>) # Object from ISO string. Raises ValueError.
<DT> = DT.strptime(<str>, '<format>') # Datetime from str, according to format.
<D/DTn> = D/DT.fromordinal(<int>) # D/DT from days since the Gregorian NYE 1.
<DTn> = DT.fromtimestamp(<float>) # Local naive DT from seconds since the Epoch.
<DTa> = DT.fromtimestamp(<float>, <tz>) # Aware datetime from seconds since the Epoch.
- ISO strings come in following forms:
'YYYY-MM-DD'
,'HH:MM:SS.mmmuuu[±HH:MM]'
, or both separated by an arbitrary character. All parts following the hours are optional. - Python uses the Unix Epoch:
'1970-01-01 00:00 UTC'
,'1970-01-01 01:00 CET'
, ...
Decode
python
<str> = <D/T/DT>.isoformat(sep='T') # Also `timespec='auto/hours/minutes/seconds/…'`.
<str> = <D/T/DT>.strftime('<format>') # Custom string representation of the object.
<int> = <D/DT>.toordinal() # Days since Gregorian NYE 1, ignoring time and tz.
<float> = <DTn>.timestamp() # Seconds since the Epoch, from local naive DT.
<float> = <DTa>.timestamp() # Seconds since the Epoch, from aware datetime.
Format
python
>>> dt = datetime.strptime('2025-08-14 23:39:00.00 +0200', '%Y-%m-%d %H:%M:%S.%f %z')
>>> dt.strftime("%dth of %B '%y (%a), %I:%M %p %Z")
"14th of August '25 (Thu), 11:39 PM UTC+02:00"
'%z'
accepts'±HH[:]MM'
and returns'±HHMM'
or empty string if datetime is naive.'%Z'
accepts'UTC/GMT'
and local timezone's code and returns timezone's name,'UTC[±HH:MM]'
if timezone is nameless, or an empty string if datetime is naive.
Arithmetics
python
<bool> = <D/T/DTn> > <D/T/DTn> # Ignores time jumps (fold attribute). Also ==.
<bool> = <DTa> > <DTa> # Ignores jumps if they share tz object. Broken ==.
<TD> = <D/DTn> - <D/DTn> # Ignores jumps. Convert to UTC for actual delta.
<TD> = <DTa> - <DTa> # Ignores jumps if they share tzinfo object.
<D/DT> = <D/DT> ± <TD> # Returned datetime can fall into missing hour.
<TD> = <TD> * <float> # Also: <TD> = abs(<TD>) and <TD> = <TD> ±% <TD>.
<float> = <TD> / <TD> # E.g. how many hours are in TD. Also //, divmod().
Arguments
Inside Function Call
python
func(<positional_args>) # func(0, 0)
func(<keyword_args>) # func(x=0, y=0)
func(<positional_args>, <keyword_args>) # func(0, y=0)
Inside Function Definition
python
def func(<nondefault_args>): ... # def func(x, y): ...
def func(<default_args>): ... # def func(x=0, y=0): ...
def func(<nondefault_args>, <default_args>): ... # def func(x, y=0): ...
- Default values are evaluated when function is first encountered in the scope.
- Any mutation of a mutable default value will persist between invocations!
Splat Operator
Inside Function Call
Splat expands a collection into positional arguments, while splatty-splat expands a dictionary into keyword arguments.
python
args = (1, 2)
kwargs = {'x': 3, 'y': 4, 'z': 5}
func(*args, **kwargs)
Is the same as:
python
func(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.
python
def add(*a):
return sum(a)
python
>>> add(1, 2, 3)
6
Legal argument combinations:
python
def f(*args): ... # f(1, 2, 3)
def f(x, *args): ... # f(1, 2, 3)
def f(*args, z): ... # f(1, 2, z=3)
python
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)
python
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)
python
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)
Other Uses
python
<list> = [*<coll.> [, ...]] # Or: list(<collection>) [+ ...]
<tuple> = (*<coll.>, [...]) # Or: tuple(<collection>) [+ ...]
<set> = {*<coll.> [, ...]} # Or: set(<collection>) [| ...]
<dict> = {**<dict> [, ...]} # Or: <dict> | ...
python
head, *body, tail = <coll.> # Head or tail can be omitted.
Inline
Lambda
python
<func> = lambda: <return_value> # A single statement function.
<func> = lambda <arg_1>, <arg_2>: <return_value> # Also allows default arguments.
Comprehensions
python
<list> = [i+1 for i in range(10)] # Or: [1, 2, ..., 10]
<iter> = (i for i in range(10) if i > 5) # Or: iter([6, 7, 8, 9])
<set> = {i+5 for i in range(10)} # Or: {5, 6, ..., 14}
<dict> = {i: i*2 for i in range(10)} # Or: {0: 0, 1: 2, ..., 9: 18}
python
>>> [l+r for l in 'abc' for r in 'abc'] # Inner loop is on the right side.
['aa', 'ab', 'ac', ..., 'cc']
Map, Filter, Reduce
python
from functools import reduce
python
<iter> = map(lambda x: x + 1, range(10)) # Or: iter([1, 2, ..., 10])
<iter> = filter(lambda x: x > 5, range(10)) # Or: iter([6, 7, 8, 9])
<obj> = reduce(lambda out, x: out + x, range(10)) # Or: 45
Any, All
python
<bool> = any(<collection>) # Is `bool(<el>)` True for any el?
<bool> = all(<collection>) # True for all? Also True if empty.
Conditional Expression
python
<obj> = <exp> if <condition> else <exp> # Only one expression is evaluated.
python
>>> [a if a else 'zero' for a in (0, 1, 2, 3)] # `any([0, '', [], None]) == False`
['zero', 1, 2, 3]
Named Tuple, Enum, Dataclass
python
from collections import namedtuple
Point = namedtuple('Point', 'x y') # Creates a tuple's subclass.
point = Point(0, 0) # Returns its instance.
python
from enum import Enum
Direction = Enum('Direction', 'N E S W') # Creates an enum.
direction = Direction.N # Returns its member.
python
from dataclasses import make_dataclass
Player = make_dataclass('Player', ['loc', 'dir']) # Creates a class.
player = Player(point, direction) # Returns its instance.
Imports
Mechanism that makes code in one file available to another file.
python
import <module> # Imports a built-in or '<module>.py'.
import <package> # Imports a built-in or '<package>/__init__.py'.
import <package>.<module> # Imports a built-in or '<package>/<module>.py'.
- Package is a collection of modules, but it can also define its own objects.
- On a filesystem this corresponds to a directory of Python files with an optional init script.
- Running
'import <package>'
does not automatically provide access to the package's modules unless they are explicitly imported in its init script. - Directory of the file that is passed to python command serves as a root of local imports.
- For relative imports use
'from .[…][<pkg/module>[.…]] import <obj>'
.
Closure
We have/get a closure in Python when a nested function references a value of its enclosing function and then the enclosing function returns its nested function.
python
def get_multiplier(a):
def out(b):
return a * b
return out
python
>>> multiply_by_3 = get_multiplier(3)
>>> multiply_by_3(10)
30
- Any value that is referenced from within multiple nested functions gets shared.
Partial
python
from functools import partial
<function> = partial(<function> [, <arg_1> [, ...]])
python
>>> def multiply(a, b):
... return a * b
>>> multiply_by_3 = partial(multiply, 3)
>>> multiply_by_3(10)
30
- Partial is also useful in cases when a function needs to be passed as an argument because it enables us to set its arguments beforehand.
- A few examples being:
'defaultdict(<func>)'
,'iter(<func>, to_exc)'
and dataclass's'field(default_factory=<func>)'
.
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'.
python
def get_counter():
i = 0
def out():
nonlocal i
i += 1
return i
return out
python
>>> counter = get_counter()
>>> counter(), counter(), counter()
(1, 2, 3)
Decorator
- A decorator takes a function, adds some functionality and returns it.
- It can be any callable, but is usually implemented as a function that returns a closure.
python
@decorator_name
def function_that_gets_passed_to_decorator():
...
Debugger Example
Decorator that prints function's name every time the function is called.
python
from functools import wraps
def debug(func):
@wraps(func)
def out(*args, **kwargs):
print(func.__name__)
return func(*args, **kwargs)
return out
@debug
def add(x, y):
return x + y
- Wraps is a helper decorator that copies the metadata of the passed function (func) to the function it is wrapping (out). Without it,
'add.__name__'
would return'out'
.
Cache
Decorator that caches function's return values. All function's arguments must be hashable.
python
from functools import cache
@cache
def fib(n):
return n if n < 2 else fib(n-2) + fib(n-1)
- Potential problem with cache is that it can grow indefinitely. To clear stored values run
'fib.cache_clear()'
, or use'@lru_cache(maxsize=<int>)'
decorator instead. - CPython interpreter limits recursion depth to 3000 by default. To increase it run
'sys.setrecursionlimit(<int>)'
.
Parametrized Decorator
A decorator that accepts arguments and returns a normal decorator that accepts a function.
python
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
- Using only
'@debug'
to decorate the add() function would not work here, because debug would then receive the add() function as a 'print_result' argument. Decorators can however manually check if the argument they received is a function and act accordingly.
Class
A template for creating user-defined objects.
python
class MyClass:
def __init__(self, a):
self.a = a
def __str__(self):
return str(self.a)
def __repr__(self):
class_name = self.__class__.__name__
return f'{class_name}({self.a!r})'
@classmethod
def get_class_name(cls):
return cls.__name__
python
>>> obj = MyClass(1)
>>> obj.a, str(obj), repr(obj)
(1, '1', 'MyClass(1)')
- Return value of str() should be readable and of repr() unambiguous.
- If only repr() is defined, it will also be used for str().
- Methods decorated with
'@staticmethod'
do not receive 'self' nor 'cls' as their first argument.
Expressions that call the str() method:
python
print(<obj>)
f'{<obj>}'
logging.warning(<obj>)
csv.writer(<file>).writerow([<obj>])
raise Exception(<obj>)
Expressions that call the repr() method:
python
print/str/repr([<obj>])
print/str/repr({<obj>: <obj>})
f'{<obj>!r}'
Z = dataclasses.make_dataclass('Z', ['a']); print/str/repr(Z(<obj>))
>>> <obj>
Inheritance
python
class Person:
def __init__(self, name):
self.name = name
class Employee(Person):
def __init__(self, name, staff_num):
super().__init__(name)
self.staff_num = staff_num
Multiple inheritance:
python
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 or an attribute:
python
>>> C.mro()
[<class 'C'>, <class 'A'>, <class 'B'>, <class 'object'>]
Type Annotations
- They add type hints to variables, arguments and functions (
'def f() -> <type>:'
). - Hints are used by type checkers like mypy, data validation libraries such as Pydantic and lately also by Cython compiler. However, they are not enforced by CPython interpreter.
python
from collections import abc
<name>: <type> [| ...] [= <obj>] # `|` since 3.10.
<name>: list/set/abc.Iterable/abc.Sequence[<type>] [= <obj>] # Since 3.9.
<name>: dict/tuple[<type>, ...] [= <obj>] # Since 3.9.
Dataclass
Decorator that uses class variables to generate init(), repr() and eq() special methods.
python
from dataclasses import dataclass, field, make_dataclass
@dataclass(order=False, frozen=False)
class <class_name>:
<attr_name>: <type>
<attr_name>: <type> = <default_value>
<attr_name>: list/dict/set = field(default_factory=list/dict/set)
- Objects can be made sortable with
'order=True'
and immutable with'frozen=True'
. - For object to be hashable, all attributes must be hashable and 'frozen' must be True.
- Function field() is needed because
'<attr_name>: list = []'
would make a list that is shared among all instances. Its 'default_factory' argument can be any callable. - For attributes of arbitrary type use
'typing.Any'
.
python
Point = make_dataclass('Point', ['x', 'y'])
Point = make_dataclass('Point', [('x', float), ('y', float)])
Point = make_dataclass('Point', [('x', float, 0), ('y', float, 0)])
Property
Pythonic way of implementing getters and setters.
python
class Person:
@property
def name(self):
return ' '.join(self._name)
@name.setter
def name(self, value):
self._name = value.split()
python
>>> person = Person()
>>> person.name = '\t Guido van Rossum \n'
>>> person.name
'Guido van Rossum'
Slots
Mechanism that restricts objects to attributes listed in 'slots', reduces their memory footprint.
python
class MyClassWithSlots:
__slots__ = ['a']
def __init__(self):
self.a = 1
Copy
python
from copy import copy, deepcopy
<object> = copy/deepcopy(<object>)
Duck Types
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. False is returned if both return NotImplemented.
- Ne() automatically works on any object that has eq() defined.
python
class MyComparable:
def __init__(self, a):
self.a = a
def __eq__(self, other):
if isinstance(other, type(self)):
return self.a == other.a
return NotImplemented
Hashable
- Hashable object needs both hash() and eq() methods and its hash value should never change.
- Hashable objects that compare equal must have the same hash value, meaning default hash() that returns
'id(self)'
will not do. - That is why Python automatically makes classes unhashable if you only implement eq().
python
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 and the rest will be automatically generated.
- Functions sorted() and min() only require lt() method, while max() only requires gt(). However, it is best to define them all so that confusion doesn't arise in other contexts.
- When two lists, strings or dataclasses are compared, their values get compared in order until a pair of unequal values is found. The comparison of this two values is then returned. The shorter sequence is considered smaller in case of all values being equal.
- To sort collection of strings in proper alphabetical order pass
'key=locale.strxfrm'
to sorted() after running'locale.setlocale(locale.LC_COLLATE, "en_US.UTF-8")'
.
python
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 exception.
- Iter() should return 'self'.
python
class Counter:
def __init__(self):
self.i = 0
def __next__(self):
self.i += 1
return self.i
def __iter__(self):
return self
python
>>> counter = Counter()
>>> next(counter), next(counter), next(counter)
(1, 2, 3)
Python has many different iterator objects:
- Sequence 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.
Callable
- All functions and classes have a call() method, hence are callable.
- Use
'callable(<obj>)'
or'isinstance(<obj>, collections.abc.Callable)'
to check if object is callable. - When this cheatsheet uses
'<function>'
as an argument, it means'<callable>'
.
python
class Counter:
def __init__(self):
self.i = 0
def __call__(self):
self.i += 1
return self.i
python
>>> counter = Counter()
>>> counter(), counter(), counter()
(1, 2, 3)
Context Manager
- With statements only work on objects that have enter() and exit() special methods.
- 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.
- The exit() method can suppress the exception by returning a true value.
python
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()
python
>>> with open('test.txt', 'w') as file:
... file.write('Hello World!')
>>> with MyOpen('test.txt') as file:
... print(file.read())
Hello World!
Iterable Duck Types
Iterable
- Only required method is iter(). It should return an iterator of object's items.
- Contains() automatically works on any object that has iter() defined.
python
class MyIterable:
def __init__(self, a):
self.a = a
def __iter__(self):
return iter(self.a)
def __contains__(self, el):
return el in self.a
python
>>> 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(). Len() should return the number of items.
- This cheatsheet actually means
'<iterable>'
when it uses'<collection>'
. - I chose not to use the name 'iterable' because it sounds scarier and more vague than 'collection'. The main drawback of this decision is that the reader could think a certain function doesn't accept iterators when it does, since iterators are the only built-in objects that are iterable but are not collections.
python
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 getitem() and len().
- Getitem() should return an item at the passed 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. It returns reversed iterator of object's items.
python
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)
Discrepancies between glossary definitions and abstract base classes:
- Python's glossary defines iterable as any object with special methods iter() and/or getitem() and sequence as any object with getitem() and len(). It doesn't define collection.
- Passing ABC Iterable to isinstance() or issubclass() only checks whether object/class has special method iter(), while ABC Collection checks for iter(), contains() and len().
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. It however recognizes list, tuple, range, str, bytes, bytearray, array, memoryview and deque, since they are registered as Sequence's virtual subclasses.
python
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]
Table of required and automatically available special methods:
text
+------------+------------+------------+------------+--------------+
| | Iterable | Collection | Sequence | abc.Sequence |
+------------+------------+------------+------------+--------------+
| iter() | REQ | REQ | Yes | Yes |
| contains() | Yes | Yes | Yes | Yes |
| len() | | REQ | REQ | REQ |
| getitem() | | | REQ | REQ |
| reversed() | | | Yes | Yes |
| index() | | | | Yes |
| count() | | | | Yes |
+------------+------------+------------+------------+--------------+
- Method iter() is required for
'isinstance(<obj>, abc.Iterable)'
to return True, however any object with getitem() will work with any code expecting an iterable. - MutableSequence, Set, MutableSet, Mapping and MutableMapping ABCs are also extendable. Use
'<abc>.__abstractmethods__'
to get names of required methods.
Enum
Class of named constants called members.
python
from enum import Enum, auto
python
class <enum_name>(Enum):
<member_name> = auto() # Increment of the last numeric value or 1.
<member_name> = <value> # Values don't have to be hashable.
<member_name> = <el_1>, <el_2> # Values can be collections (this is a tuple).
- Methods receive the member they were called on as the 'self' argument.
- Accessing a member named after a reserved keyword causes SyntaxError.
python
<member> = <enum>.<member_name> # Returns a member. Raises AttributeError.
<member> = <enum>['<member_name>'] # Returns a member. Raises KeyError.
<member> = <enum>(<value>) # Returns a member. Raises ValueError.
<str> = <member>.name # Returns member's name.
<obj> = <member>.value # Returns member's value.
python
<list> = list(<enum>) # Returns enum's members.
<list> = [a.name for a in <enum>] # Returns enum's member names.
<list> = [a.value for a in <enum>] # Returns enum's member values.
python
<enum> = type(<member>) # Returns member's enum.
<iter> = itertools.cycle(<enum>) # Returns endless iterator of members.
<member> = random.choice(list(<enum>)) # Returns a random member.
Inline
python
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:
python
from functools import partial
LogicOp = Enum('LogicOp', {'AND': partial(lambda l, r: l and r),
'OR': partial(lambda l, r: l or r)})
Exceptions
python
try:
<code>
except <exception>:
<code>
Complex Example
python
try:
<code_1>
except <exception_a>:
<code_2_a>
except <exception_b>:
<code_2_b>
else:
<code_2_c>
finally:
<code_3>
- Code inside the
'else'
block will only be executed if'try'
block had no exceptions. - Code inside the
'finally'
block will always be executed (unless a signal is received). - All variables that are initialized in executed blocks are also visible in all subsequent blocks, as well as outside the try statement (only function block delimits scope).
- To catch signals use
'signal.signal(signal_number, <func>)'
.
Catching Exceptions
python
except <exception>: ...
except <exception> as <name>: ...
except (<exception>, [...]): ...
except (<exception>, [...]) as <name>: ...
- Also catches subclasses of the exception.
- Use
'traceback.print_exc()'
to print the full error message to stderr. - Use
'print(<name>)'
to print just the cause of the exception (its arguments). - Use
'logging.exception(<str>)'
to log the passed message, followed by the full error message of the caught exception. For details see Logging. - Use
'sys.exc_info()'
to get exception type, object, and traceback of caught exception.
Raising Exceptions
python
raise <exception>
raise <exception>()
raise <exception>(<obj> [, ...])
Re-raising caught exception:
python
except <exception> [as <name>]:
...
raise
Exception Object
python
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)
trace_str = ''.join(traceback.format_tb(<name>.__traceback__))
error_msg = ''.join(traceback.format_exception(type(<name>), <name>, <name>.__traceback__))
Built-in Exceptions
text
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 such as ZeroDivisionError.
+-- AssertionError # Raised by `assert <exp>` if expression returns false value.
+-- AttributeError # Raised when object doesn't have requested attribute/method.
+-- EOFError # Raised by input() when it hits an end-of-file condition.
+-- LookupError # Base class for errors when a collection can't find an item.
| +-- IndexError # Raised when a sequence index is out of range.
| +-- KeyError # Raised when a dictionary key or set element is missing.
+-- MemoryError # Out of memory. May be too late to start deleting variables.
+-- NameError # Raised when nonexistent name (variable/func/class) is used.
| +-- UnboundLocalError # Raised when local name is used before it's being defined.
+-- OSError # Errors such as FileExistsError/TimeoutError (see #Open).
| +-- ConnectionError # Errors such as BrokenPipeError/ConnectionAbortedError.
+-- RuntimeError # Raised by errors that don't fall into other categories.
| +-- NotImplementedEr… # Can be raised by abstract methods or by unfinished code.
| +-- RecursionError # Raised when the maximum recursion depth is exceeded.
+-- StopIteration # Raised when an empty iterator is passed to next().
+-- TypeError # When an argument of the wrong type is passed to function.
+-- ValueError # When argument has the right type but inappropriate value.
Collections and their exceptions:
text
+-----------+------------+------------+------------+
| | List | Set | Dict |
+-----------+------------+------------+------------+
| getitem() | IndexError | | KeyError |
| pop() | IndexError | KeyError | KeyError |
| remove() | ValueError | KeyError | |
| index() | ValueError | | |
+-----------+------------+------------+------------+
Useful built-in exceptions:
python
raise TypeError('Argument is of the wrong type!')
raise ValueError('Argument has the right type but an inappropriate value!')
raise RuntimeError('I am too lazy to define my own exception!')
User-defined Exceptions
python
class MyError(Exception): pass
class MyInputError(MyError): pass
Exit
Exits the interpreter by raising SystemExit exception.
python
import sys
sys.exit() # Exits with exit code 0 (success).
sys.exit(<int>) # Exits with the passed exit code.
sys.exit(<obj>) # Prints to stderr and exits with 1.
Print
python
print(<el_1>, ..., sep=' ', end='\n', file=sys.stdout, flush=False)
- Use
'file=sys.stderr'
for messages about errors. - Stdout and stderr streams hold output in a buffer until they receive a string containing '\n' or '\r', buffer reaches 4096 characters,
'flush=True'
is used, or program exits.
Pretty Print
python
from pprint import pprint
pprint(<collection>, width=80, depth=None, compact=False, sort_dicts=True)
- Each item is printed on its own line if collection exceeds 'width' characters.
- Nested collections that are 'depth' levels deep get printed as '...'.
Input
python
<str> = input()
- Reads a line from the user input or pipe if present (trailing newline gets stripped).
- If argument is passed, it gets printed to the standard output before input is read.
- EOFError is raised if user hits EOF (ctrl-d/ctrl-z⏎) or input stream gets exhausted.
Command Line Arguments
python
import sys
scripts_path = sys.argv[0]
arguments = sys.argv[1:]
Argument Parser
python
from argparse import ArgumentParser, FileType
p = ArgumentParser(description=<str>) # Returns a parser.
p.add_argument('-<short_name>', '--<name>', action='store_true') # Flag (defaults to False).
p.add_argument('-<short_name>', '--<name>', type=<type>) # Option (defaults to None).
p.add_argument('<name>', type=<type>, nargs=1) # Mandatory first argument.
p.add_argument('<name>', type=<type>, nargs='+') # Mandatory remaining args.
p.add_argument('<name>', type=<type>, nargs='?/*') # Optional argument/s.
args = p.parse_args() # Exits on parsing error.
<obj> = args.<name> # Returns `<type>(<arg>)`.
- Use
'help=<str>'
to set argument description that will be displayed in help message. - Use
'default=<obj>'
to set option's or optional argument's default value. - Use
'type=FileType(<mode>)'
for files. Accepts 'encoding', but 'newline' is None.
Open
Opens a file and returns the corresponding file object.
python
<file> = open(<path>, mode='r', encoding=None, newline=None)
'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 every '\n', '\r' and '\r\n'.
Modes
'r'
- Read. Used by default.'w'
- Write. Deletes existing contents.'x'
- Write or fail if the file already exists.'a'
- Append. Creates new file if it doesn't exist.'w+'
- Read and write. Deletes existing contents.'r+'
- Read and write from the start.'a+'
- Read and write from the end.'b'
- Binary mode ('rb'
,'wb'
,'xb'
, …).
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
python
<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, origin) # Origin: 0 start, 1 current position, 2 end.
python
<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.
python
<file>.write(<str/bytes>) # Writes a string or bytes object.
<file>.writelines(<collection>) # Writes a coll. of strings or bytes objects.
<file>.flush() # Flushes write buffer. Runs every 4096/8192 B.
<file>.close() # Closes the file after flushing write buffer.
- Methods do not add or strip trailing newlines, not even writelines().
Read Text from File
python
def read_file(filename):
with open(filename, encoding='utf-8') as file:
return file.readlines()
Write Text to File
python
def write_to_file(filename, text):
with open(filename, 'w', encoding='utf-8') as file:
file.write(text)
Paths
python
import os, glob
from pathlib import Path
python
<str> = os.getcwd() # Returns working dir. Starts as shell's $PWD.
<str> = os.path.join(<path>, ...) # Joins two or more pathname components.
<str> = os.path.realpath(<path>) # Resolves symlinks and calls path.abspath().
python
<str> = os.path.basename(<path>) # Returns final component of the path.
<str> = os.path.dirname(<path>) # Returns path without the final component.
<tup.> = os.path.splitext(<path>) # Splits on last period of the final component.
python
<list> = os.listdir(path='.') # Returns filenames located at the path.
<list> = glob.glob('<pattern>') # Returns paths matching the wildcard pattern.
python
<bool> = os.path.exists(<path>) # Or: <Path>.exists()
<bool> = os.path.isfile(<path>) # Or: <DirEntry/Path>.is_file()
<bool> = os.path.isdir(<path>) # Or: <DirEntry/Path>.is_dir()
python
<stat> = os.stat(<path>) # Or: <DirEntry/Path>.stat()
<num> = <stat>.st_mtime/st_size/… # Modification time, size in bytes, etc.
DirEntry
Unlike listdir(), scandir() returns DirEntry objects that cache isfile, isdir, and on Windows also stat information, thus significantly increasing the performance of code that requires it.
python
<iter> = os.scandir(path='.') # Returns DirEntry objects located at the path.
<str> = <DirEntry>.path # Returns the whole path as a string.
<str> = <DirEntry>.name # Returns final component as a string.
<file> = open(<DirEntry>) # Opens the file and returns a file object.
Path Object
python
<Path> = Path(<path> [, ...]) # Accepts strings, Paths, and DirEntry objects.
<Path> = <path> / <path> [/ ...] # First or second path must be a Path object.
<Path> = <Path>.resolve() # Returns absolute path with resolved symlinks.
python
<Path> = Path() # Returns relative CWD. Also Path('.').
<Path> = Path.cwd() # Returns absolute CWD. Also Path().resolve().
<Path> = Path.home() # Returns user's home directory (absolute).
<Path> = Path(__file__).resolve() # Returns script's path if CWD wasn't changed.
python
<Path> = <Path>.parent # Returns Path without the 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.
python
<iter> = <Path>.iterdir() # Returns directory contents as Path objects.
<iter> = <Path>.glob('<pattern>') # Returns Paths matching the wildcard pattern.
python
<str> = str(<Path>) # Returns path as a string.
<file> = open(<Path>) # Also <Path>.read/write_text/bytes(<args>).
OS Commands
python
import os, shutil, subprocess
python
os.chdir(<path>) # Changes the current working directory.
os.mkdir(<path>, mode=0o777) # Creates a directory. Permissions are in octal.
os.makedirs(<path>, mode=0o777) # Creates all path's dirs. Also `exist_ok=False`.
python
shutil.copy(from, to) # Copies the file. 'to' can exist or be a dir.
shutil.copy2(from, to) # Also copies creation and modification time.
shutil.copytree(from, to) # Copies the directory. 'to' must not exist.
python
os.rename(from, to) # Renames/moves the file or directory.
os.replace(from, to) # Same, but overwrites file 'to' even on Windows.
shutil.move(from, to) # Rename() that moves into 'to' if it's a dir.
python
os.remove(<path>) # Deletes the file.
os.rmdir(<path>) # Deletes the empty directory.
shutil.rmtree(<path>) # Deletes the directory.
- Paths can be either strings, Paths, or DirEntry objects.
- Functions report OS related errors by raising either OSError or one of its subclasses.
Shell Commands
python
<pipe> = os.popen('<commands>') # Executes commands in sh/cmd. Returns combined stdout.
<str> = <pipe>.read(size=-1) # Reads 'size' chars or until EOF. Also readline/s().
<int> = <pipe>.close() # Returns None if last command exited with returncode 0.
Sends '1 + 1' to the basic calculator and captures its output:
python
>>> subprocess.run('bc', input='1 + 1\n', capture_output=True, text=True)
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:
python
>>> from shlex import split
>>> os.popen('echo 1 + 1 > test.in')
>>> subprocess.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'
JSON
Text file format for storing collections of strings and numbers.
python
import json
<str> = json.dumps(<list/dict>) # Converts collection to JSON string.
<coll> = json.loads(<str>) # Converts JSON string to collection.
Read Collection from JSON File
python
def read_json_file(filename):
with open(filename, encoding='utf-8') as file:
return json.load(file)
Write Collection to JSON File
python
def write_to_json_file(filename, list_or_dict):
with open(filename, 'w', encoding='utf-8') as file:
json.dump(list_or_dict, file, ensure_ascii=False, indent=2)
Pickle
Binary file format for storing Python objects.
python
import pickle
<bytes> = pickle.dumps(<object>) # Converts object to bytes object.
<object> = pickle.loads(<bytes>) # Converts bytes object to object.
Read Object from File
python
def read_pickle_file(filename):
with open(filename, 'rb') as file:
return pickle.load(file)
Write Object to File
python
def write_to_pickle_file(filename, an_object):
with open(filename, 'wb') as file:
pickle.dump(an_object, file)
CSV
Text file format for storing spreadsheets.
python
import csv
Read
python
<reader> = csv.reader(<file>) # Also: `dialect='excel', delimiter=','`.
<list> = next(<reader>) # Returns next row as a list of strings.
<list> = list(<reader>) # Returns a list of remaining rows.
- File must be opened with a
'newline=""'
argument, or newlines embedded inside quoted fields will not be interpreted correctly! - To print the spreadsheet to the console use Tabulate library.
- For XML and binary Excel files (xlsx, xlsm and xlsb) use Pandas library.
- Reader accepts any iterator of strings, not just files.
Write
python
<writer> = csv.writer(<file>) # Also: `dialect='excel', delimiter=','`.
<writer>.writerow(<collection>) # Encodes objects using `str(<el>)`.
<writer>.writerows(<coll_of_coll>) # Appends multiple rows.
- File must be opened with a
'newline=""'
argument, or '\r' will be added in front of every '\n' on platforms that use '\r\n' line endings! - Open existing file with
'mode="a"'
to append to it or'mode="w"'
to overwrite it.
Parameters
'dialect'
- Master parameter that sets the default values. String or a 'csv.Dialect' object.'delimiter'
- A one-character string used to separate fields.'lineterminator'
- How writer terminates rows. Reader is hardcoded to '\n', '\r', '\r\n'.'quotechar'
- Character for quoting fields that contain special characters.'escapechar'
- Character for escaping quotechars.'doublequote'
- Whether quotechars inside fields are/get doubled or escaped.'quoting'
- 0: As necessary, 1: All, 2: All but numbers which are read as floats, 3: None.'skipinitialspace'
- Is space character at the start of the field stripped by the reader.
Dialects
text
+------------------+--------------+--------------+--------------+
| | excel | excel-tab | unix |
+------------------+--------------+--------------+--------------+
| delimiter | ',' | '\t' | ',' |
| lineterminator | '\r\n' | '\r\n' | '\n' |
| quotechar | '"' | '"' | '"' |
| escapechar | None | None | None |
| doublequote | True | True | True |
| quoting | 0 | 0 | 1 |
| skipinitialspace | False | False | False |
+------------------+--------------+--------------+--------------+
Read Rows from CSV File
python
def read_csv_file(filename, **csv_params):
with open(filename, encoding='utf-8', newline='') as file:
return list(csv.reader(file, **csv_params))
Write Rows to CSV File
python
def write_to_csv_file(filename, rows, mode='w', **csv_params):
with open(filename, mode, encoding='utf-8', newline='') as file:
writer = csv.writer(file, **csv_params)
writer.writerows(rows)
SQLite
A server-less database engine that stores each database into its own file.
python
import sqlite3
<conn> = sqlite3.connect(<path>) # Opens existing or new file. Also ':memory:'.
<conn>.close() # Closes connection. Discards uncommitted data.
Read
python
<cursor> = <conn>.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
python
<conn>.execute('<query>') # Can raise a subclass of sqlite3.Error.
<conn>.commit() # Saves all changes since the last commit.
<conn>.rollback() # Discards all changes since the last commit.
Or:
python
with <conn>: # Exits the block with commit() or rollback(),
<conn>.execute('<query>') # depending on whether any exception occurred.
Placeholders
python
<conn>.execute('<query>', <list/tuple>) # Replaces '?'s in query with values.
<conn>.execute('<query>', <dict/namedtuple>) # Replaces ':<key>'s with values.
<conn>.executemany('<query>', <coll_of_coll>) # Runs execute() multiple times.
- Passed values can be of type str, int, float, bytes, None, or bool (stored as 1 or 0).
Example
Values are not actually saved in this example because 'conn.commit()'
is omitted!
python
>>> conn = sqlite3.connect('test.db')
>>> conn.execute('CREATE TABLE person (person_id INTEGER PRIMARY KEY, name, height)')
>>> conn.execute('INSERT INTO person VALUES (NULL, ?, ?)', ('Jean-Luc', 187)).lastrowid
1
>>> conn.execute('SELECT * FROM person').fetchall()
[(1, 'Jean-Luc', 187)]
SQLAlchemy
Library for interacting with various DB systems via SQL, method chaining, or ORM.
python
# $ pip3 install sqlalchemy
from sqlalchemy import create_engine, text
<engine> = create_engine('<url>') # Url: 'dialect://user:password@host/dbname'.
<conn> = <engine>.connect() # Creates a connection. Also <conn>.close().
<cursor> = <conn>.execute(text('<query>'), …) # `<dict>`. Replaces ':<key>'s with values.
with <conn>.begin(): ... # Exits the block with commit or rollback.
text
+-----------------+--------------+----------------------------------+
| Dialect | pip3 install | Dependencies |
+-----------------+--------------+----------------------------------+
| mysql | mysqlclient | www.pypi.org/project/mysqlclient |
| postgresql | psycopg2 | www.pypi.org/project/psycopg2 |
| mssql | pyodbc | www.pypi.org/project/pyodbc |
| oracle+oracledb | oracledb | www.pypi.org/project/oracledb |
+-----------------+--------------+----------------------------------+
Bytes
A bytes object is an immutable sequence of single bytes. Mutable version is called bytearray.
python
<bytes> = b'<str>' # Only accepts ASCII characters and \x00-\xff.
<int> = <bytes>[index] # Returns an 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 as a separator.
Encode
python
<bytes> = bytes(<coll_of_ints>) # Ints must be in range from 0 to 255.
<bytes> = bytes(<str>, 'utf-8') # Encodes the string. Also <str>.encode().
<bytes> = bytes.fromhex('<hex>') # Hex pairs can be separated by whitespaces.
<bytes> = <int>.to_bytes(n_bytes, …) # `byteorder='big/little', signed=False`.
Decode
python
<list> = list(<bytes>) # Returns ints in range from 0 to 255.
<str> = str(<bytes>, 'utf-8') # Returns a string. Also <bytes>.decode().
<str> = <bytes>.hex() # Returns hex pairs. Accepts `sep=<str>`.
<int> = int.from_bytes(<bytes>, …) # `byteorder='big/little', signed=False`.
Read Bytes from File
python
def read_bytes(filename):
with open(filename, 'rb') as file:
return file.read()
Write Bytes to File
python
def write_bytes(filename, bytes_obj):
with open(filename, 'wb') as file:
file.write(bytes_obj)
Struct
- Module that performs conversions between a sequence of numbers and a bytes object.
- System’s type sizes, byte order, and alignment rules are used by default.
python
from struct import pack, unpack
<bytes> = pack('<format>', <el_1> [, ...]) # Packs objects according to format string.
<tuple> = unpack('<format>', <bytes>) # Use iter_unpack() to get iterator of tuples.
python
>>> 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 and manual alignment (padding) start format string with:
'='
- System's byte order (usually little-endian).'<'
- Little-endian (i.e. least significant byte first).'>'
- Big-endian (also'!'
).
Besides numbers, pack() and unpack() also support bytes objects as a part of the sequence:
'c'
- A bytes object with a single element. For pad byte use'x'
.'<n>s'
- A bytes object with n elements (not effected by byte order).
Integer types. Use a capital letter for unsigned type. Minimum and standard sizes are in brackets:
'b'
- char (1/1)'h'
- short (2/2)'i'
- int (2/4)'l'
- long (4/4)'q'
- long long (8/8)
Floating point types (struct always uses standard sizes):
'f'
- float (4/4)'d'
- double (8/8)
Array
List that can only hold numbers of a predefined type. Available types and their minimum sizes in bytes are listed above. Type sizes and byte order are always determined by the system, however bytes of each element can be reversed with byteswap() method.
python
from array import array
python
<array> = array('<typecode>', <coll_of_nums>) # Creates array from collection of numbers.
<array> = array('<typecode>', <bytes>) # Writes passed bytes to array's memory.
<array> = array('<typecode>', <array>) # Treats passed array as a sequence of numbers.
<array>.fromfile(<file>, n_items) # Appends file's contents to array's memory.
python
<bytes> = bytes(<array>) # Returns a copy of array's memory.
<file>.write(<array>) # Writes array's memory to the binary file.
Memory View
A sequence object that points to the memory of another bytes-like object. Each element can reference a single or multiple consecutive bytes, depending on format. Order and number of elements can be changed with slicing.
python
<mview> = memoryview(<bytes/bytearray/array>) # Immutable if bytes is passed, else mutable.
<obj> = <mview>[index] # Returns int or float. Bytes if format is 'c'.
<mview> = <mview>[<slice>] # Returns memoryview with rearranged elements.
<mview> = <mview>.cast('<typecode>') # Only works between B/b/c and other types.
<mview>.release() # Releases memory buffer of the base object.
python
<bytes> = bytes(<mview>) # Returns a new bytes object. Also bytearray().
<bytes> = <bytes>.join(<coll_of_mviews>) # Joins memoryviews using bytes as a separator.
<array> = array('<typecode>', <mview>) # Treats memoryview as a sequence of numbers.
<file>.write(<mview>) # Writes `bytes(<mview>)` to the binary file.
python
<list> = list(<mview>) # Returns a list of ints, floats, or bytes.
<str> = str(<mview>, 'utf-8') # Treats memoryview as a bytes object.
<str> = <mview>.hex() # Returns hex pairs. Accepts `sep=<str>`.
Deque
List with efficient appends and pops from either side.
python
from collections import deque
python
<deque> = deque(<collection>) # Use `maxlen=<int>` to set size limit.
<deque>.appendleft(<el>) # Opposite element is dropped if full.
<deque>.extendleft(<collection>) # Passed collection gets reversed.
<deque>.rotate(n=1) # Last element becomes first.
<el> = <deque>.popleft() # Raises IndexError if deque is empty.
Operator
Module of functions that provide the functionality of operators. Functions are ordered and grouped by operator precedence, from least to most binding. Logical and arithmetic operators in lines 1, 3 and 5 are also ordered by precedence within their own group.
python
import operator as op
python
<bool> = op.not_(<obj>) # or, and, not (or/and missing)
<bool> = op.eq/ne/lt/ge/is_/is_not/contains(<obj>, <obj>) # ==, !=, <, >=, is, is not, in
<obj> = op.or_/xor/and_(<int/set>, <int/set>) # |, ^, &
<int> = op.lshift/rshift(<int>, <int>) # <<, >>
<obj> = op.add/sub/mul/truediv/floordiv/mod(<obj>, <obj>) # +, -, *, /, //, %
<num> = op.neg/invert(<num>) # -, ~
<num> = op.pow(<num>, <num>) # **
<func> = op.itemgetter/attrgetter/methodcaller(<obj> [, ...]) # [index/key], .name, .name([…])
python
elementwise_sum = map(op.add, list_a, list_b)
sorted_by_second = sorted(<coll>, key=op.itemgetter(1))
sorted_by_both = sorted(<coll>, key=op.itemgetter(1, 0))
first_element = op.methodcaller('pop', 0)(<list>)
- Most operators call the object's special method that is named after them (second object is passed as an argument), while logical operators call their own code that relies on bool().
- Comparisons can be chained:
'x < y < z'
gets converted to'(x < y) and (y < z)
'.
Match Statement
Executes the first block with matching pattern. Added in Python 3.10.
python
match <object/expression>:
case <pattern> [if <condition>]:
<code>
...
Patterns
python
<value_pattern> = 1/'abc'/True/None/math.pi # Matches the literal or a dotted name.
<class_pattern> = <type>() # Matches any object of that type (or ABC).
<wildcard_patt> = _ # Matches any object. Useful in last case.
<capture_patt> = <name> # Matches any object and binds it to name.
<as_pattern> = <pattern> as <name> # Binds match to name. Also <type>(<name>).
<or_pattern> = <pattern> | <pattern> [| ...] # Matches any of the patterns.
<sequence_patt> = [<pattern>, ...] # Matches sequence with matching items.
<mapping_patt> = {<value_pattern>: <patt>, ...} # Matches dictionary with matching items.
<class_pattern> = <type>(<attr_name>=<patt>, ...) # Matches object with matching attributes.
- Sequence pattern can also be written as a tuple.
- Use
'*<name>'
and'**<name>'
in sequence/mapping patterns to bind remaining items. - Sequence pattern must match all items of the collection, while mapping pattern does not.
- Patterns can be surrounded with brackets to override precedence (
'|'
>'as'
>','
). - Built-in types allow a single positional pattern that is matched against the entire object.
- All names that are bound in the matching case, as well as variables initialized in its block, are visible after the match statement.
Example
python
>>> from pathlib import Path
>>> match Path('/home/gto/python-cheatsheet/README.md'):
... case Path(
... parts=['/', 'home', user, *_]
... ) as p if p.name.lower().startswith('readme') and p.is_file():
... print(f'{p.name} is a readme file that belongs to user {user}.')
README.md is a readme file that belongs to user gto.
Logging
python
import logging as log
python
log.basicConfig(filename=<path>, level='DEBUG') # Configures the root logger (see Setup).
log.debug/info/warning/error/critical(<str>) # Sends message to the root logger.
<Logger> = log.getLogger(__name__) # Returns logger named after the module.
<Logger>.<level>(<str>) # Sends message to the logger.
<Logger>.exception(<str>) # Error() that appends caught exception.
Setup
python
log.basicConfig(
filename=None, # Logs to stderr or appends to file.
format='%(levelname)s:%(name)s:%(message)s', # Add '%(asctime)s' for local datetime.
level=log.WARNING, # Drops messages with lower priority.
handlers=[log.StreamHandler(sys.stderr)] # Uses FileHandler if filename is set.
)
python
<Formatter> = log.Formatter('<format>') # Creates a Formatter.
<Handler> = log.FileHandler(<path>, mode='a') # Creates a Handler. Also `encoding=None`.
<Handler>.setFormatter(<Formatter>) # Adds Formatter to the Handler.
<Handler>.setLevel(<int/str>) # Processes all messages by default.
<Logger>.addHandler(<Handler>) # Adds Handler to the Logger.
<Logger>.setLevel(<int/str>) # What is sent to its/ancestors' handlers.
<Logger>.propagate = <bool> # Cuts off ancestors' handlers if False.
- Parent logger can be specified by naming the child logger
'<parent>.<name>'
. - If logger doesn't have a set level, it inherits it from the first ancestor that does.
- Formatter also accepts: pathname, filename, funcName, lineno, thread and process.
- RotatingFileHandler creates and deletes files based on 'maxBytes', 'backupCount' args.
- An object with
'filter(<LogRecord>)'
method (or the method itself) can be added to loggers and handlers via addFilter(). Message is dropped if filter() returns a false value.
Creates a logger that writes all messages to a file and sends them to the root's handler that prints warnings or higher:
python
>>> logger = log.getLogger('my_module')
>>> handler = log.FileHandler('test.log', encoding='utf-8')
>>> handler.setFormatter(log.Formatter('%(asctime)s %(levelname)s:%(name)s:%(message)s'))
>>> logger.addHandler(handler)
>>> logger.setLevel('DEBUG')
>>> log.basicConfig()
>>> log.root.handlers[0].setLevel('WARNING')
>>> logger.critical('Running out of disk space.')
CRITICAL:my_module:Running out of disk space.
>>> print(open('test.log').read())
2023-02-07 23:21:01,430 CRITICAL:my_module:Running out of disk space.
Introspection
python
<list> = dir() # Local names of variables, functions, classes and modules.
<dict> = vars() # Dict of local names and their objects. Also locals().
<dict> = globals() # Dict of global names and their objects, e.g. __builtin__.
python
<list> = dir(<obj>) # Returns names of object's attributes (including methods).
<dict> = vars(<obj>) # Returns dict of writable attributes. Also <obj>.__dict__.
<bool> = hasattr(<obj>, '<name>') # Checks if object possesses attribute with passed name.
value = getattr(<obj>, '<name>') # Returns object's attribute or raises AttributeError.
setattr(<obj>, '<name>', value) # Sets attribute. Only works on objects with __dict__ attr.
delattr(<obj>, '<name>') # Deletes attribute from __dict__. Also `del <obj>.<name>`.
python
<Sig> = inspect.signature(<func>) # Returns a Signature object of the passed function.
<dict> = <Sig>.parameters # Returns dict of Parameters. Also <Sig>.return_annotation.
<memb> = <Param>.kind # Returns ParameterKind member (Parameter.KEYWORD_ONLY, …).
<type> = <Param>.annotation # Returns Parameter.empty if missing. Also <Param>.default.
Threading
CPython interpreter can only run a single thread at a time. Using multiple threads won't result in a faster execution, unless at least one of the threads contains an I/O operation.
python
from threading import Thread, Lock, RLock, Semaphore, Event, Barrier
from concurrent.futures import ThreadPoolExecutor, as_completed
Thread
python
<Thread> = Thread(target=<function>) # Use `args=<collection>` to set the arguments.
<Thread>.start() # Starts the thread. Also <Thread>.is_alive().
<Thread>.join() # Waits for the thread to finish.
- 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.
Lock
python
<lock> = Lock/RLock() # RLock can only be released by acquirer.
<lock>.acquire() # Waits for the lock to be available.
<lock>.release() # Makes the lock available again.
Or:
python
with <lock>: # Enters the block by calling acquire() and
... # exits it with release(), even on error.
Semaphore, Event, Barrier
python
<Semaphore> = Semaphore(value=1) # Lock that can be acquired by 'value' threads.
<Event> = Event() # Method wait() blocks until set() is called.
<Barrier> = Barrier(n_times) # Wait() blocks until it's called n times.
Queue
python
<Queue> = queue.Queue(maxsize=0) # A thread-safe first-in-first-out queue.
<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.
Thread Pool Executor
python
<Exec> = ThreadPoolExecutor(max_workers=None) # Or: `with ThreadPoolExecutor() as <name>: ...`
<iter> = <Exec>.map(<func>, <args_1>, ...) # Multithreaded and non-lazy map(). Keeps order.
<Futr> = <Exec>.submit(<func>, <arg_1>, ...) # Creates a thread and returns its Future obj.
<Exec>.shutdown() # Blocks until all threads finish executing.
python
<bool> = <Future>.done() # Checks if the thread has finished executing.
<obj> = <Future>.result(timeout=None) # Waits for thread to finish and returns result.
<bool> = <Future>.cancel() # Cancels or returns False if running/finished.
<iter> = as_completed(<coll_of_Futures>) # `next(<iter>)` returns next completed Future.
- Map() and as_completed() also accept 'timeout'. It causes futures.TimeoutError when next() is called/blocking. Map() times from original call and as_completed() from first call to next(). As_completed() fails if next() is called too late, even if all threads are done.
- Exceptions that happen inside threads are raised when map iterator's next() or Future's result() are called. Future's exception() method returns exception object or None.
- ProcessPoolExecutor provides true parallelism but: everything sent to/from workers must be pickable, queues must be sent using executor's 'initargs' and 'initializer' parameters, and executor should only be reachable via
'if __name__ == "__main__": ...'
.
Coroutines
- 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'
. - Use
'asyncio.run(<coroutine>)'
to start the first/main coroutine.
python
import asyncio as aio
python
<coro> = <async_function>(<args>) # Creates a coroutine by calling async def function.
<obj> = await <coroutine> # Starts the coroutine and returns its result.
<task> = aio.create_task(<coroutine>) # Schedules the coroutine for execution.
<obj> = await <task> # Returns coroutine's result. Also <task>.cancel().
python
<coro> = aio.gather(<coro/task>, ...) # Schedules coros. Returns list of results on await.
<coro> = aio.wait(<tasks>, …) # `aio.ALL/FIRST_COMPLETED`. Returns (done, pending).
<iter> = aio.as_completed(<coros/tasks>) # Iterator of coros. All return next result on await.
Runs a terminal game where you control an asterisk that must avoid numbers:
python
import asyncio, collections, curses, curses.textpad, enum, random
P = collections.namedtuple('P', 'x y') # Position
D = enum.Enum('D', 'n e s w') # Direction
W, H = 15, 7 # Width, Height
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):
moves = asyncio.Queue()
state = {'*': P(0, 0)} | {id_: P(W//2, H//2) for id_ in range(10)}
ai = [random_controller(id_, moves) for id_ in range(10)]
mvc = [human_controller(screen, moves), model(moves, state), view(state, screen)]
tasks = [asyncio.create_task(coro) for coro in ai + mvc]
await asyncio.wait(tasks, return_when=asyncio.FIRST_COMPLETED)
async def random_controller(id_, moves):
while True:
d = random.choice(list(D))
moves.put_nowait((id_, d))
await asyncio.sleep(random.triangular(0.01, 0.65))
async def human_controller(screen, moves):
while True:
key_mappings = {258: D.s, 259: D.n, 260: D.w, 261: D.e}
if d := key_mappings.get(screen.getch()):
moves.put_nowait(('*', d))
await asyncio.sleep(0.005)
async def model(moves, state):
while state['*'] not in (state[id_] for id_ in range(10)):
id_, d = await moves.get()
deltas = {D.n: P(0, -1), D.e: P(1, 0), D.s: P(0, 1), D.w: P(-1, 0)}
state[id_] = P((state[id_].x + deltas[d].x) % W, (state[id_].y + deltas[d].y) % H)
async def view(state, screen):
offset = P(curses.COLS//2 - W//2, curses.LINES//2 - H//2)
while True:
screen.erase()
curses.textpad.rectangle(screen, offset.y-1, offset.x-1, offset.y+H, offset.x+W)
for id_, p in state.items():
screen.addstr(offset.y + (p.y - state['*'].y + H//2) % H,
offset.x + (p.x - state['*'].x + W//2) % W, str(id_))
screen.refresh()
await asyncio.sleep(0.005)
if __name__ == '__main__':
curses.wrapper(main)