python cheatsheet
1.0.0
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1. Collectes : List , Dictionary , Set , Tuple , Range , Enumerate , Iterator , Generator .
2. Types : Type , String , Regular_Exp , Format , Numbers , Combinatorics , Datetime .
3. Syntaxe : Args , Inline , Import , Decorator , Class , Duck_Types , Enum , Exception .
4. Système : Exit , Print , Input , Command_Line_Arguments , Open , Path , OS_Commands .
5. Données : JSON , Pickle , CSV , SQLite , Bytes , Struct , Array , Memory_View , Deque .
6. Avancé : Operator , Match_Stmt , Logging , Introspection , Threading , Coroutines .
7. Bibliothèques : Progress_Bar , Plot , Table , Console_App , GUI , Scraping , Web , Profile .
8. Multimédia : NumPy , Image , Animation , Audio , Synthesizer , Pygame , Pandas , Plotly .
if __name__ == '__main__' : # Skips next line if file was imported.
main () # Runs `def main(): ...` function. < list > = [ < el_1 > , < el_2 > , ...] # Creates new list. Also list(<collection>). < el > = < list > [ index ] # First index is 0. Last -1. Allows assignments.
< list > = < list > [ < slice > ] # Also <list>[from_inclusive : to_exclusive : ±step]. < list > . append ( < el > ) # Appends element to the end. Also <list> += [<el>].
< list > . extend ( < collection > ) # Appends elements to the end. Also <list> += <coll>. < 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. < el > = max ( < collection > ) # Returns largest element. Also min(<el_1>, ...).
< num > = sum ( < collection > ) # Returns sum of elements. Also math.prod(<coll>). 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 > )) < 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. < dict > = { key_1 : val_1 , key_2 : val_2 , ...} # Use `<dict>[key]` to get or set the value. < 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. 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. < 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 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. > >> 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 > = { < el_1 > , < el_2 > , ...} # Use `set()` for empty 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. < frozenset > = frozenset ( < collection > )Tuple est une liste immuable et hachable.
< tuple > = () # Empty tuple.
< tuple > = ( < el > ,) # Or: <el>,
< tuple > = ( < el_1 > , < el_2 > [, ...]) # Or: <el_1>, <el_2> [, ...]Sous-classe de Tuple avec des éléments nommés.
> >> 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 Séquence d'entiers immuable et hachable.
< 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) > >> [ i for i in range ( 3 )]
[ 0 , 1 , 2 ] for i , el in enumerate ( < coll > , start = 0 ): # Returns next element and its index on each pass.
... < 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. import itertools as it < 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. < iter > = it . chain ( < coll > , < coll > [, ...]) # Empties collections in order (figuratively).
< iter > = it . chain . from_iterable ( < coll > ) # Empties collections inside a collection in order. < 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. def count ( start , step ):
while True :
yield start
start += step > >> counter = count ( 10 , 2 )
> >> next ( counter ), next ( counter ), next ( counter )
( 10 , 12 , 14 ) < 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' > ) from types import FunctionType , MethodType , LambdaType , GeneratorType , ModuleTypeChaque classe de base abstraite spécifie un ensemble de sous-classes virtuelles. Ces classes sont ensuite reconnues par isinstance() et issubclass() comme des sous-classes de l'ABC, bien qu'elles ne le soient pas vraiment. ABC peut également décider manuellement si une classe spécifique est ou non sa sous-classe virtuelle, généralement en fonction des méthodes implémentées par la classe. Par exemple, Iterable ABC recherche la méthode iter(), tandis que Collection ABC recherche iter(), contain() et len().
> >> from collections . abc import Iterable , Collection , Sequence
> >> isinstance ([ 1 , 2 , 3 ], Iterable )
True +------------------+------------+------------+------------+
| | Iterable | Collection | Sequence |
+------------------+------------+------------+------------+
| list, range, str | yes | yes | yes |
| dict, set | yes | yes | |
| iter | yes | | |
+------------------+------------+------------+------------+
> >> from numbers import Number , Complex , Real , Rational , Integral
> >> isinstance ( 123 , Number )
True +--------------------+----------+----------+----------+----------+----------+
| | 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 | | | | |
+--------------------+----------+----------+----------+----------+----------+
Séquence de caractères immuable.
< str > = < str > . strip () # Strips all whitespace characters from both ends.
< str > = < str > . strip ( '<chars>' ) # Strips passed characters. Also lstrip/rstrip(). < 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 [nrfvx1c-x1ex85u2028u2029] and rn.
< str > = < str > . join ( < coll_of_strings > ) # Joins elements using string as a separator. < 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. < 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. < str > = chr ( < int > ) # Converts int to Unicode character.
< int > = ord ( < str > ) # Converts Unicode character to int.'unicodedata.normalize("NFC", <str>)' sur des chaînes comme 'Motörhead' avant de les comparer à d'autres chaînes, car 'ö' peut être stocké sous la forme d'un ou deux caractères.'NFC' convertit ces caractères en un seul caractère, tandis que 'NFD' les convertit en deux. < 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 [ !#$%…] and isalnum().
< bool > = < str > . isspace () # Checks for [ tnrfvx1c-x1fx85xa0…]. Fonctions de correspondance d'expressions régulières.
import re
< str > = re . sub ( r'<regex>' , new , text , count = 0 ) # Substitutes all occurrences with 'new'.
< list > = re . findall ( r'<regex>' , text ) # Returns all occurrences as strings.
< list > = re . split ( r'<regex>' , text , maxsplit = 0 ) # Add brackets around regex to keep matches.
< Match > = re . search ( r'<regex>' , text ) # First occurrence of the pattern or None.
< Match > = re . match ( r'<regex>' , text ) # Searches only at the beginning of the text.
< iter > = re . finditer ( r'<regex>' , text ) # Returns all occurrences as Match objects.'flags=re.IGNORECASE' peut être utilisé avec toutes les fonctions.'flags=re.MULTILINE' fait que '^' et '$' correspondent au début/fin de chaque ligne.'flags=re.DOTALL' donne '.' acceptez également le 'n' .'re.compile(<regex>)' renvoie un objet Pattern avec les méthodes sub(), findall(),… < 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. '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.'flags=re.ASCII' est utilisé. Il restreint les correspondances de séquences spéciales aux 128 premiers caractères Unicode et empêche également 's' d'accepter 'x1c' , 'x1d' , 'x1e' et 'x1f' (caractères non imprimables qui divisent le texte en fichiers, tables, lignes et champs, respectivement).<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. > >> 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.'{ < el > : < 10 } # '<el> '
{ < el > : ^ 10 } # ' <el> '
{ < el > : > 10 } # ' <el>'
{ < el > :. < 10 } # '<el>......'
{ < el > : 0 } # '<el>''format(<el>, "<options>")' .f'{<el>:{<str/int>}[…]}' .'=' à l'expression l'ajoute au début de la sortie : f'{1+1=}' renvoie '1+1=2' .'!r' à l'expression convertit l'objet en chaîne en appelant sa méthode repr().{ 'abcde' : 10 } # 'abcde '
{ 'abcde' : 10.3 } # 'abc '
{ 'abcde' : .3 } # 'abc'
{ 'abcde' !r: 10 } # "'abcde' "{ 123456 : 10 } # ' 123456'
{ 123456 : 10 ,} # ' 123,456'
{ 123456 : 10_ } # ' 123_456'
{ 123456 : + 10 } # ' +123456'
{ 123456 : = + 10 } # '+ 123456'
{ 123456 : } # ' 123456'
{ - 123456 : } # '-123456'{ 1.23456 : 10.3 } # ' 1.23'
{ 1.23456 : 10.3 f } # ' 1.235'
{ 1.23456 : 10.3 e } # ' 1.235e+00'
{ 1.23456 : 10.3 % } # ' 123.456%' +--------------+----------------+----------------+----------------+----------------+
| | {<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%' |
+--------------+----------------+----------------+----------------+----------------+
+--------------+----------------+----------------+----------------+----------------+
| | {<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}' est '{<float>:.6}' avec des zéros supprimés, l'exposant commençant à '1e+06' .'{6.5:.0f}' un '6' et '{7.5:.0f}' un '8' ..5 , .25 , …).{ 90 : c } # 'Z'. Unicode character with value 90.
{ 90 : b } # '1011010'. Number 90 in binary.
{ 90 : X } # '5A'. Number 90 in uppercase hexadecimal. < 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>)' et 'float(<str>)' déclenchent ValueError sur les chaînes mal formées.'1.1 + 2.2 != 3.3' .'math.isclose(<float>, <float>)' .'decimal.getcontext().prec = <int>' . < num > = pow ( < num > , < num > ) # Or: <number> ** <number>
< num > = abs ( < num > ) # <float> = abs(<complex>)
< num > = round ( < num > [, ± ndigits ]) # `round(126, -1) == 130` 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. from statistics import mean , median , variance # Also: stdev, quantiles, groupby. 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. < int > = ± 0 b < 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(). < 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. import itertools as it > >> 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 )] > >> 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 > >> list ( it . combinations ( 'abc' , 2 )) # a b c
[( 'a' , 'b' ), ( 'a' , 'c' ), # a . x x
( 'b' , 'c' )] # b . . x > >> 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 > >> 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 . Fournit les classes « date », « time », « datetime » et « timedelta ». Tous sont immuables et hachables.
# $ pip3 install python-dateutil
from datetime import date , time , datetime , timedelta , timezone
import zoneinfo , dateutil . tz < 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`.'fold=1' signifie le deuxième passage en cas de recul d'une heure.'[±D, ]H:MM:SS[.…]' et total_seconds() un float de toutes les secondes.'<D/DT>.weekday()' pour obtenir le jour de la semaine sous forme d'int, lundi étant 0. < 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.'<DTn>.time()' , '<DTa>.time()' ou '<DTa>.timetz()' . < 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.'> pip3 install tzdata' . < 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.'YYYY-MM-DD' , 'HH:MM:SS.mmmuuu[±HH:MM]' , ou les deux séparées par un caractère arbitraire. Toutes les parties suivant les heures sont facultatives.'1970-01-01 00:00 UTC' , '1970-01-01 01:00 CET' , ... < 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. > >> 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' accepte '±HH[:]MM' et renvoie '±HHMM' ou une chaîne vide si datetime est naïf.'%Z' accepte 'UTC/GMT' et le code du fuseau horaire local et renvoie le nom du fuseau horaire, 'UTC[±HH:MM]' si le fuseau horaire est sans nom, ou une chaîne vide si datetime est naïf. < 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(). func ( < positional_args > ) # func(0, 0)
func ( < keyword_args > ) # func(x=0, y=0)
func ( < positional_args > , < keyword_args > ) # func(0, y=0) 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): ...Splat étend une collection en arguments de position, tandis que splatty-splat étend un dictionnaire en arguments de mots-clés.
args = ( 1 , 2 )
kwargs = { 'x' : 3 , 'y' : 4 , 'z' : 5 }
func ( * args , ** kwargs ) func ( 1 , 2 , x = 3 , y = 4 , z = 5 )Splat combine zéro ou plusieurs arguments de position dans un tuple, tandis que splatty-splat combine zéro ou plusieurs arguments de mots-clés dans un dictionnaire.
def add ( * a ):
return sum ( a ) > >> add ( 1 , 2 , 3 )
6 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 ( ** 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 ( * 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 , 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) < list > = [ * < coll . > [, ...]] # Or: list(<collection>) [+ ...]
< tuple > = ( * < coll . > , [...]) # Or: tuple(<collection>) [+ ...]
< set > = { * < coll . > [, ...]} # Or: set(<collection>) [| ...]
< dict > = { ** < dict > [, ...]} # Or: <dict> | ... head , * body , tail = < coll . > # Head or tail can be omitted. < func > = lambda : < return_value > # A single statement function.
< func > = lambda < arg_1 > , < arg_2 > : < return_value > # Also allows default arguments. < 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} > >> [ l + r for l in 'abc' for r in 'abc' ] # Inner loop is on the right side.
[ 'aa' , 'ab' , 'ac' , ..., 'cc' ] from functools import reduce < 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 < bool > = any ( < collection > ) # Is `bool(<el>)` True for any el?
< bool > = all ( < collection > ) # True for all? Also True if empty. < obj > = < exp > if < condition > else < exp > # Only one expression is evaluated. > >> [ a if a else 'zero' for a in ( 0 , 1 , 2 , 3 )] # `any([0, '', [], None]) == False`
[ 'zero' , 1 , 2 , 3 ] from collections import namedtuple
Point = namedtuple ( 'Point' , 'x y' ) # Creates a tuple's subclass.
point = Point ( 0 , 0 ) # Returns its instance. from enum import Enum
Direction = Enum ( 'Direction' , 'N E S W' ) # Creates an enum.
direction = Direction . N # Returns its member. from dataclasses import make_dataclass
Player = make_dataclass ( 'Player' , [ 'loc' , 'dir' ]) # Creates a class.
player = Player ( point , direction ) # Returns its instance. Mécanisme qui rend le code d'un fichier disponible dans un autre fichier.
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'.'import <package>' ne donne pas automatiquement accès aux modules du package à moins qu'ils ne soient explicitement importés dans son script d'initialisation.'from .[…][<pkg/module>[.…]] import <obj>' . Nous avons/obtenons une fermeture en Python lorsqu'une fonction imbriquée fait référence à une valeur de sa fonction englobante, puis la fonction englobante renvoie la fonction imbriquée.
def get_multiplier ( a ):
def out ( b ):
return a * b
return out > >> multiply_by_3 = get_multiplier ( 3 )
> >> multiply_by_3 ( 10 )
30 from functools import partial
< function > = partial ( < function > [, < arg_1 > [, ...]]) > >> def multiply ( a , b ):
... return a * b
> >> multiply_by_3 = partial ( multiply , 3 )
> >> multiply_by_3 ( 10 )
30'defaultdict(<func>)' , 'iter(<func>, to_exc)' et 'field(default_factory=<func>)' de dataclass.Si une variable est affectée à n'importe quel endroit de la portée, elle est considérée comme une variable locale, à moins qu'elle ne soit déclarée comme « globale » ou « non locale ».
def get_counter ():
i = 0
def out ():
nonlocal i
i += 1
return i
return out > >> counter = get_counter ()
> >> counter (), counter (), counter ()
( 1 , 2 , 3 ) @ decorator_name
def function_that_gets_passed_to_decorator ():
...Décorateur qui imprime le nom de la fonction à chaque fois que la fonction est appelée.
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'add.__name__' renverrait 'out' .Décorateur qui met en cache les valeurs de retour de la fonction. Tous les arguments de la fonction doivent être hachables.
from functools import cache
@ cache
def fib ( n ):
return n if n < 2 else fib ( n - 2 ) + fib ( n - 1 )'fib.cache_clear()' ou utilisez plutôt le décorateur '@lru_cache(maxsize=<int>)' .'sys.setrecursionlimit(<int>)' .Un décorateur qui accepte les arguments et renvoie un décorateur normal qui accepte une fonction.
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'@debug' pour décorer la fonction add() ne fonctionnerait pas ici, car debug recevrait alors la fonction add() comme argument 'print_result'. Les décorateurs peuvent cependant vérifier manuellement si l'argument qu'ils ont reçu est une fonction et agir en conséquence. Un modèle pour créer des objets définis par l'utilisateur.
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__ > >> obj = MyClass ( 1 )
> >> obj . a , str ( obj ), repr ( obj )
( 1 , '1' , 'MyClass(1)' )'@staticmethod' ne reçoivent pas 'self' ni 'cls' comme premier argument. print ( < obj > )
f' { < obj > } '
logging . warning ( < obj > )
csv . writer ( < file > ). writerow ([ < obj > ])
raise Exception ( < obj > ) print / str / repr ([ < obj > ])
print / str / repr ({ < obj > : < obj > })
f' { < obj > !r } '
Z = dataclasses . make_dataclass ( 'Z' , [ 'a' ]); print / str / repr ( Z ( < obj > ))
> >> < obj > 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 class A : pass
class B : pass
class C ( A , B ): passMRO détermine l'ordre dans lequel les classes parentes sont parcourues lors de la recherche d'une méthode ou d'un attribut :
> >> C . mro ()
[ < class 'C' > , < class 'A' > , < class 'B' > , < class 'object' > ]'def f() -> <type>:' ). 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.Décorateur qui utilise des variables de classe pour générer des méthodes spéciales init(), repr() et eq().
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 )'order=True' et immuables avec 'frozen=True' .'<attr_name>: list = []' créerait une liste partagée entre toutes les instances. Son argument 'default_factory' peut être n'importe quel appelable.'typing.Any' . Point = make_dataclass ( 'Point' , [ 'x' , 'y' ])
Point = make_dataclass ( 'Point' , [( 'x' , float ), ( 'y' , float )])
Point = make_dataclass ( 'Point' , [( 'x' , float , 0 ), ( 'y' , float , 0 )])Manière pythonique d'implémenter les getters et les setters.
class Person :
@ property
def name ( self ):
return ' ' . join ( self . _name )
@ name . setter
def name ( self , value ):
self . _name = value . split () > >> person = Person ()
> >> person . name = ' t Guido van Rossum n '
> >> person . name
'Guido van Rossum'Le mécanisme qui restreint les objets aux attributs répertoriés dans les « emplacements » réduit leur empreinte mémoire.
class MyClassWithSlots :
__slots__ = [ 'a' ]
def __init__ ( self ):
self . a = 1 from copy import copy , deepcopy
< object > = copy / deepcopy ( < object > )Un type duck est un type implicite qui prescrit un ensemble de méthodes spéciales. Tout objet pour lequel ces méthodes sont définies est considéré comme un membre de ce type de canard.
'id(self) == id(other)' , ce qui équivaut à 'self is other' . 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'id(self)' ne fera pas l'affaire. 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 )'key=locale.strxfrm' à sorted() après avoir exécuté 'locale.setlocale(locale.LC_COLLATE, "en_US.UTF-8")' . 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 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(<obj>)' ou 'isinstance(<obj>, collections.abc.Callable)' pour vérifier si l'objet est appelable.'<function>' comme argument, cela signifie '<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 ) 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 ! 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'<iterable>' lorsqu'elle utilise '<collection>' . 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 ) 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.Iterable' et 'abc.Collection' , ce n'est pas un type canard. C'est pourquoi 'issubclass(MySequence, abc.Sequence)' renverrait False même si MySequence avait toutes les méthodes définies. Il reconnaît cependant list, tuple, range, str, bytes, bytearray, array, memoryview et deque, car ils sont enregistrés en tant que sous-classes virtuelles de Sequence. 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 ] +------------+------------+------------+------------+--------------+
| | 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 |
+------------+------------+------------+------------+--------------+
'isinstance(<obj>, abc.Iterable)' renvoie True, mais tout objet avec getitem() fonctionnera avec n'importe quel code attendant un itérable.'<abc>.__abstractmethods__' pour obtenir les noms des méthodes requises. Classe de constantes nommées appelées membres.
from enum import Enum , auto 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). < 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. < 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. < 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. Cutlery = Enum ( 'Cutlery' , 'FORK KNIFE SPOON' )
Cutlery = Enum ( 'Cutlery' , [ 'FORK' , 'KNIFE' , 'SPOON' ])
Cutlery = Enum ( 'Cutlery' , { 'FORK' : 1 , 'KNIFE' : 2 , 'SPOON' : 3 }) from functools import partial
LogicOp = Enum ( 'LogicOp' , { 'AND' : partial ( lambda l , r : l and r ),
'OR' : partial ( lambda l , r : l or r )}) try :
< code >
except < exception > :
< code > try :
< code_1 >
except < exception_a > :
< code_2_a >
except < exception_b > :
< code_2_b >
else :
< code_2_c >
finally :
< code_3 >'else' ne sera exécuté que si le bloc 'try' n’a eu aucune exception.'finally' sera toujours exécuté (sauf si un signal est reçu).'signal.signal(signal_number, <func>)' . except < exception > : ...
except < exception > as < name > : ...
except ( < exception > , [...]): ...
except ( < exception > , [...]) as < name > : ...'traceback.print_exc()' pour imprimer le message d'erreur complet sur stderr.'print(<name>)' pour imprimer uniquement la cause de l'exception (ses arguments).'logging.exception(<str>)' pour enregistrer le message transmis, suivi du message d'erreur complet de l'exception interceptée. Pour plus de détails, voir journalisation.'sys.exc_info()' pour obtenir le type d'exception, l'objet et le traçage de l'exception interceptée. raise < exception >
raise < exception > ()
raise < exception > ( < obj > [, ...]) except < exception > [ as < name > ]:
...
raise 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__ )) 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.
+-----------+------------+------------+------------+
| | List | Set | Dict |
+-----------+------------+------------+------------+
| getitem() | IndexError | | KeyError |
| pop() | IndexError | KeyError | KeyError |
| remove() | ValueError | KeyError | |
| index() | ValueError | | |
+-----------+------------+------------+------------+
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!' ) class MyError ( Exception ): pass
class MyInputError ( MyError ): pass Quitte l’interpréteur en déclenchant l’exception SystemExit.
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 ( < el_1 > , ..., sep = ' ' , end = ' n ' , file = sys . stdout , flush = False )'file=sys.stderr' pour les messages concernant les erreurs.'flush=True' soit utilisé ou que le programme se termine. from pprint import pprint
pprint ( < collection > , width = 80 , depth = None , compact = False , sort_dicts = True ) < str > = input ( prompt = None ) import sys
scripts_path = sys . argv [ 0 ]
arguments = sys . argv [ 1 :] 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>)`.'help=<str>' pour définir la description de l'argument qui sera affichée dans le message d'aide.'default=<obj>' pour définir la valeur par défaut de l'option ou de l'argument facultatif.'type=FileType(<mode>)' pour les fichiers. Accepte « encodage », mais « nouvelle ligne » vaut Aucun. Ouvre le fichier et renvoie un objet fichier correspondant.
< file > = open ( < path > , mode = 'r' , encoding = None , newline = None )'encoding=None' signifie que l'encodage par défaut est utilisé, qui dépend de la plate-forme. La meilleure pratique consiste à utiliser 'encoding="utf-8"' autant que possible.'newline=None' signifie que toutes les différentes combinaisons de fin de ligne sont converties en 'n' lors de la lecture, tandis qu'à l'écriture, tous les caractères 'n' sont convertis en séparateur de ligne par défaut du système.'newline=""' signifie qu'aucune conversion n'a lieu, mais l'entrée est toujours divisée en morceaux par readline() et readlines() sur chaque 'n', 'r' et 'rn'.'r' - Lire. Utilisé par défaut.'w' - Écrivez. Supprime le contenu existant.'x' - Écrit ou échoue si le fichier existe déjà.'a' - Ajouter. Crée un nouveau fichier s'il n'existe pas.'w+' - Lecture et écriture. Supprime le contenu existant.'r+' - Lire et écrire depuis le début.'a+' - Lire et écrire à partir de la fin.'b' - Mode binaire ( 'rb' , 'wb' , 'xb' , …).'FileNotFoundError' peut être déclenché lors de la lecture avec 'r' ou 'r+' .'FileExistsError' peut être déclenché lors de l'écriture avec 'x' .'IsADirectoryError' et 'PermissionError' peuvent être déclenchés par n'importe qui.'OSError' est la classe parent de toutes les exceptions répertoriées. < 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. < 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 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. def read_file ( filename ):
with open ( filename , encoding = 'utf-8' ) as file :
return file . readlines () def write_to_file ( filename , text ):
with open ( filename , 'w' , encoding = 'utf-8' ) as file :
file . write ( text ) import os , glob
from pathlib import Path < 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(). < 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. < list > = os . listdir ( path = '.' ) # Returns filenames located at the path.
< list > = glob . glob ( '<pattern>' ) # Returns paths matching the wildcard pattern. < 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() < stat > = os . stat ( < path > ) # Or: <DirEntry/Path>.stat()
< num > = < stat > . st_mtime / st_size / … # Modification time, size in bytes, etc.Contrairement à listdir(), scandir() renvoie les objets DirEntry qui mettent en cache isfile, isdir et, sous Windows, également des informations statistiques, augmentant ainsi considérablement les performances du code qui le nécessite.
< 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 > = 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. < 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. < 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. < iter > = < Path > . iterdir () # Returns directory 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 > ) # Also <Path>.read/write_text/bytes(<args>). import os , shutil , subprocess 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`. 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. 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. os . remove ( < path > ) # Deletes the file.
os . rmdir ( < path > ) # Deletes the empty directory.
shutil . rmtree ( < path > ) # Deletes the directory. < 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. > >> subprocess . run ( 'bc' , input = '1 + 1 n ' , capture_output = True , text = True )
CompletedProcess ( args = 'bc' , returncode = 0 , stdout = '2 n ' , stderr = '' ) > >> 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 ' Format de fichier texte pour stocker des collections de chaînes et de nombres.
import json
< str > = json . dumps ( < list / dict > ) # Converts collection to JSON string.
< coll > = json . loads ( < str > ) # Converts JSON string to collection. def read_json_file ( filename ):
with open ( filename , encoding = 'utf-8' ) as file :
return json . load ( file ) 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 )Format de fichier binaire pour stocker les objets Python.
import pickle
< bytes > = pickle . dumps ( < object > ) # Converts object to bytes object.
< object > = pickle . loads ( < bytes > ) # Converts bytes object to object. def read_pickle_file ( filename ):
with open ( filename , 'rb' ) as file :
return pickle . load ( file ) def write_to_pickle_file ( filename , an_object ):
with open ( filename , 'wb' ) as file :
pickle . dump ( an_object , file )Format de fichier texte pour stocker des feuilles de calcul.
import csv < 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.'newline=""' , sinon les nouvelles lignes intégrées dans les champs entre guillemets ne seront pas interprétées correctement ! < writer > = csv . writer ( < file > ) # Also: `dialect='excel', delimiter=','`.
< writer > . writerow ( < collection > ) # Encodes objects using `str(<el>)`.
< writer > . writerows ( < coll_of_coll > ) # Appends multiple rows.'newline=""' , sinon 'r' sera ajouté devant chaque 'n' sur les plates-formes qui utilisent des fins de ligne 'rn' !'mode="a"' pour l'ajouter ou 'mode="w"' pour l'écraser.'dialect' - Paramètre principal qui définit les valeurs par défaut. Chaîne ou un objet 'csv.Dialect'.'delimiter' - Une chaîne d'un caractère utilisée pour séparer les champs.'lineterminator' - Comment le rédacteur termine les lignes. Le lecteur est codé en dur sur 'n', 'r', 'rn'.'quotechar' - Caractère permettant de citer les champs contenant des caractères spéciaux.'escapechar' - Caractère permettant d'échapper aux guillemets.'doublequote' - Indique si les guillemets à l'intérieur des champs sont/sont doublés ou échappés.'quoting' - 0 : Si nécessaire, 1 : Tous, 2 : Tous sauf les nombres lus comme des flottants, 3 : Aucun.'skipinitialspace' - Le caractère espace au début du champ est supprimé par le lecteur. +------------------+--------------+--------------+--------------+
| | excel | excel-tab | unix |
+------------------+--------------+--------------+--------------+
| delimiter | ',' | 't' | ',' |
| lineterminator | 'rn' | 'rn' | 'n' |
| quotechar | '"' | '"' | '"' |
| escapechar | None | None | None |
| doublequote | True | True | True |
| quoting | 0 | 0 | 1 |
| skipinitialspace | False | False | False |
+------------------+--------------+--------------+--------------+
def read_csv_file ( filename , ** csv_params ):
with open ( filename , encoding = 'utf-8' , newline = '' ) as file :
return list ( csv . reader ( file , ** csv_params )) 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 )Un moteur de base de données sans serveur qui stocke chaque base de données dans son propre fichier.
import sqlite3
< conn > = sqlite3 . connect ( < path > ) # Opens existing or new file. Also ':memory:'.
< conn > . close () # Closes connection. Discards uncommitted data. < 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>). < 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. with < conn > : # Exits the block with commit() or rollback(),
< conn > . execute ( '<query>' ) # depending on whether any exception occurred. < 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. Les valeurs ne sont pas réellement enregistrées dans cet exemple car 'conn.commit()' est omis !
> >> 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 )]Bibliothèque pour interagir avec divers systèmes de base de données via SQL, le chaînage de méthodes ou ORM.
# $ 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. +-----------------+--------------+----------------------------------+
| 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 |
+-----------------+--------------+----------------------------------+
Un objet bytes est une séquence immuable d’octets simples. La version mutable est appelée bytearray.
< 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. < 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`. < 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`. def read_bytes ( filename ):
with open ( filename , 'rb' ) as file :
return file . read () def write_bytes ( filename , bytes_obj ):
with open ( filename , 'wb' ) as file :
file . write ( bytes_obj ) 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. > >> 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 )'=' - Ordre des octets du système (généralement petit-boutiste).'<' - Little-endian (c'est-à-dire l'octet de poids faible en premier).'>' - Big-endian (également '!' ). 'c' - Un objet bytes avec un seul élément. Pour l'octet de remplissage, utilisez 'x' .'<n>s' - Un objet octets avec n éléments (non affecté par l'ordre des octets). 'b' - caractère (1/1)'h' - court (2/2)'i' - int (2/4)'l' - long (4/4)'q' - long long (8/8) 'f' - flotter (4/4)'d' - double (8/8) Liste ne pouvant contenir que des nombres d'un type prédéfini. Les types disponibles et leurs tailles minimales en octets sont répertoriés ci-dessus. La taille des types et l'ordre des octets sont toujours déterminés par le système, mais les octets de chaque élément peuvent être inversés avec la méthode byteswap().
from array import array < 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. < bytes > = bytes ( < array > ) # Returns a copy of array's memory.
< file > . write ( < array > ) # Writes array's memory to the binary file. Un objet séquence qui pointe vers la mémoire d’un autre objet de type octet. Chaque élément peut référencer un ou plusieurs octets consécutifs, selon le format. L'ordre et le nombre d'éléments peuvent être modifiés avec le découpage.
< 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. < 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. < 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>`. Liste avec des ajouts et des pops efficaces de chaque côté. Prononcé « pont ».
from collections import deque < 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. Module de fonctions qui fournissent les fonctionnalités des opérateurs. Les fonctions sont classées et regroupées par priorité des opérateurs, du moins au plus contraignant. Les opérateurs logiques et arithmétiques des lignes 1, 3 et 5 sont également classés par priorité au sein d'un groupe.
import operator as op < 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([…]) 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 > )'x < y < z' est converti en '(x < y) and (y < z) '. Exécute le premier bloc avec le motif correspondant. Ajouté dans Python 3.10.
match < object / expression > :
case < pattern > [ if < condition > ]:
< code >
... < 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.'*<name>' et '**<name>' dans les modèles de séquence/mappage pour lier les éléments restants.'|' > 'as' > ',' ). > >> 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.' import logging as log 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. 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.
) < 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>.<name>' .'filter(<LogRecord>)' (ou la méthode elle-même) peut être ajouté aux enregistreurs et aux gestionnaires via addFilter(). Le message est supprimé si filter() renvoie une valeur fausse. > >> 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 . < list > = dir () # List of local names (variables, funcs, classes, modules).
< dict > = vars () # Dict of local names and their objects. Also locals().
< dict > = globals () # Dict of global names and their objects, e.g. __builtin__. < 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>`. < 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. L'interpréteur CPython ne peut exécuter qu'un seul thread à la fois. L'utilisation de plusieurs threads n'entraînera pas une exécution plus rapide, à moins qu'au moins l'un des threads contienne une opération d'E/S.
from threading import Thread , Lock , RLock , Semaphore , Event , Barrier
from concurrent . futures import ThreadPoolExecutor , as_completed < 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.'kwargs=<dict>' pour transmettre des arguments de mot-clé à la fonction.'daemon=True' , sinon le programme ne pourra pas se terminer tant que le thread est en vie. < 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. with < lock > : # Enters the block by calling acquire() and
... # exits it with release(), even on error. < 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 > = 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. < 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. < 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.'if __name__ == "__main__": ...' . 'async' et son appel par 'await' .'asyncio.run(<coroutine>)' pour démarrer la première/coroutine principale. import asyncio as aio < 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(). < 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. 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 ) # $ pip3 install tqdm
> >> import tqdm , time
> >> for el in tqdm . tqdm ([ 1 , 2 , 3 ], desc = 'Processing' ):
... time . sleep ( 1 )
Processing : 100 % | ████████████████████ | 3 / 3 [ 00 : 03 < 00 : 00 , 1.00 s / it ] # $ pip3 install matplotlib
import matplotlib . pyplot as plt
plt . plot / bar / scatter ( x_data , y_data [, label = < str > ]) # Also plt.plot(y_data).
plt . legend () # Adds a legend.
plt . title / xlabel / ylabel ( < str > ) # Adds a title or label.
plt . savefig ( < path > ) # Saves the plot.
plt . show () # Displays the plot.
plt . clf () # Clears the plot. # $ pip3 install tabulate
import csv , tabulate
with open ( 'test.csv' , encoding = 'utf-8' , newline = '' ) as file :
rows = list ( csv . reader ( file ))
print ( tabulate . tabulate ( rows , headers = 'firstrow' )) # $ pip3 install windows-curses
import curses , os
from curses import A_REVERSE , KEY_DOWN , KEY_UP , KEY_LEFT , KEY_RIGHT , KEY_ENTER
def main ( screen ):
ch , first , selected , paths = 0 , 0 , 0 , os . listdir ()
while ch != ord ( 'q' ):
height , width = screen . getmaxyx ()
screen . erase ()
for y , filename in enumerate ( paths [ first : first + height ]):
color = A_REVERSE if filename == paths [ selected ] else 0
screen . addnstr ( y , 0 , filename , width - 1 , color )
ch = screen . getch ()
selected += ( ch == KEY_DOWN ) - ( ch == KEY_UP )
selected = max ( 0 , min ( len ( paths ) - 1 , selected ))
first += ( selected >= first + height ) - ( selected < first )
if ch in [ KEY_LEFT , KEY_RIGHT , KEY_ENTER , ord ( ' n ' ), ord ( ' r ' )]:
new_dir = '..' if ch == KEY_LEFT else paths [ selected ]
if os . path . isdir ( new_dir ):
os . chdir ( new_dir )
first , selected , paths = 0 , 0 , os . listdir ()
if __name__ == '__main__' :
curses . wrapper ( main ) # $ pip3 install PySimpleGUI
import PySimpleGUI as sg
text_box = sg . Input ( default_text = '100' , enable_events = True , key = '-QUANTITY-' )
dropdown = sg . InputCombo ([ 'g' , 'kg' , 't' ], 'kg' , readonly = True , enable_events = True , k = '-UNIT-' )
label = sg . Text ( '100 kg is 220.462 lbs.' , key = '-OUTPUT-' )
button = sg . Button ( 'Close' )
window = sg . Window ( 'Weight Converter' , [[ text_box , dropdown ], [ label ], [ button ]])
while True :
event , values = window . read ()
if event in [ sg . WIN_CLOSED , 'Close' ]:
break
try :
quantity = float ( values [ '-QUANTITY-' ])
except ValueError :
continue
unit = values [ '-UNIT-' ]
factors = { 'g' : 0.001 , 'kg' : 1 , 't' : 1000 }
lbs = quantity * factors [ unit ] / 0.45359237
window [ '-OUTPUT-' ]. update ( value = f' { quantity } { unit } is { lbs :g } lbs.' )
window . close () # $ pip3 install requests beautifulsoup4
import requests , bs4 , os
response = requests . get ( 'https://en.wikipedia.org/wiki/Python_(programming_language)' )
document = bs4 . BeautifulSoup ( response . text , 'html.parser' )
table = document . find ( 'table' , class_ = 'infobox vevent' )
python_url = table . find ( 'th' , text = 'Website' ). next_sibling . a [ 'href' ]
logo_url = table . find ( 'img' )[ 'src' ]
logo = requests . get ( f'https: { logo_url } ' ). content
filename = os . path . basename ( logo_url )
with open ( filename , 'wb' ) as file :
file . write ( logo )
print ( f' { python_url } , file:// { os . path . abspath ( filename ) } ' )Bibliothèque pour scraper des sites Web avec du contenu dynamique.
# $ pip3 install selenium
from selenium import webdriver
< WebDrv > = webdriver . Chrome / Firefox / Safari / Edge () # Opens a browser. Also <WebDrv>.quit().
< WebDrv > . get ( '<url>' ) # Also <WebDrv>.implicitly_wait(seconds).
< El > = < WebDrv / El > . find_element ( 'css selector' , …) # '<tag>#<id>.<class>[<attr>="<val>"]…'.
< list > = < WebDrv / El > . find_elements ( 'xpath' , …) # '//<tag>[@<attr>="<val>"]…'. See XPath.
< str > = < El > . get_attribute ( < str > ) # Property if exists. Also <El>.text.
< El > . click / clear () # Also <El>.send_keys(<str>). '$x("<xpath>")' : < xpath > = // < element > [ / or // < element > ] # /<child>, //<descendant>, /../<sibling>
< xpath > = // < element > / following :: < element > # Next element. Also preceding/parent/…
< element > = < tag > < conditions > < index > # `<tag> = */a/…`, `<index> = [1/2/…]`.
< condition > = [ < sub_cond > [ and / or < sub_cond > ]] # For negation use `not(<sub_cond>)`.
< sub_cond > = @ < attr > [ = "<val>" ] # `text()=`, `.=` match (complete) text.
< sub_cond > = contains (@ < attr > , "<val>" ) # Is <val> a substring of attr's value?
< sub_cond > = [ // ] < element > # Has matching child? Descendant if //. Flask est un framework/serveur micro web. Si vous souhaitez simplement ouvrir un fichier HTML dans un navigateur Web, utilisez plutôt 'webbrowser.open(<path>)' .
# $ pip3 install flask
import flask as fl app = fl . Flask ( __name__ ) # Returns the app object. Put at the top.
app . run ( host = None , port = None , debug = None ) # Or: $ flask --app FILE run [--ARG[=VAL]]…'http://localhost:5000' . Utilisez 'host="0.0.0.0"' pour exécuter en externe. @ app . route ( '/img/<path:filename>' )
def serve_file ( filename ):
return fl . send_from_directory ( 'dirname/' , filename ) @ app . route ( '/<sport>' )
def serve_html ( sport ):
return fl . render_template_string ( '<h1>{{title}}</h1>' , title = sport )'fl.render_template(filename, <kwargs>)' restitue un fichier situé dans le répertoire 'templates'.'fl.abort(<int>)' renvoie le code d'erreur et 'return fl.redirect(<url>)' redirige.'fl.request.args[<str>]' renvoie le paramètre de la chaîne de requête (URL à droite de '?').'fl.session[<str>] = <obj>' stocke les données de session. Cela nécessite que la clé secrète soit définie au démarrage avec 'app.secret_key = <str>' . @ app . post ( '/<sport>/odds' )
def serve_json ( sport ):
team = fl . request . form [ 'team' ]
return { 'team' : team , 'odds' : [ 2.09 , 3.74 , 3.68 ]} # $ pip3 install requests
> >> import threading , requests
> >> threading . Thread ( target = app . run , daemon = True ). start ()
> >> url = 'http://localhost:5000/football/odds'
> >> response = requests . post ( url , data = { 'team' : 'arsenal f.c.' })
> >> response . json ()
{ 'team' : 'arsenal f.c.' , 'odds' : [ 2.09 , 3.74 , 3.68 ]} from time import perf_counter
start_time = perf_counter ()
...
duration_in_seconds = perf_counter () - start_time > >> from timeit import timeit
> >> timeit ( 'list(range(10000))' , number = 1000 , globals = globals (), setup = 'pass' )
0.19373 $ pip3 install line_profiler
$ echo '@profile
def main():
a = list(range(10000))
b = set(range(10000))
main()' > test.py
$ kernprof -lv test.py
Line # Hits Time Per Hit % Time Line Contents
==============================================================
1 @profile
2 def main():
3 1 253.4 253.4 32.2 a = list(range(10000))
4 1 534.1 534.1 67.8 b = set(range(10000))
$ apt/brew install graphviz && pip3 install gprof2dot snakeviz # Or download installer.
$ tail --lines=+2 test.py > test.py # Removes first line.
$ python3 -m cProfile -o test.prof test.py # Runs built-in profiler.
$ gprof2dot --format=pstats test.prof | dot -T png -o test.png # Generates call graph.
$ xdg-open/open test.png # Displays call graph.
$ snakeviz test.prof # Displays flame graph. +--------------+------------+-------------------------------+-------+------+
| pip3 install | Target | How to run | Lines | Live |
+--------------+------------+-------------------------------+-------+------+
| pyinstrument | CPU | pyinstrument test.py | No | No |
| py-spy | CPU | py-spy top -- python3 test.py | No | Yes |
| scalene | CPU+Memory | scalene test.py | Yes | No |
| memray | Memory | memray run --live test.py | Yes | Yes |
+--------------+------------+-------------------------------+-------+------+
Mini-langage de manipulation de tableaux. Il peut s’exécuter jusqu’à cent fois plus vite que le code Python équivalent. Une alternative encore plus rapide qui s'exécute sur un GPU s'appelle CuPy.
# $ pip3 install numpy
import numpy as np < array > = np . array ( < list / list_of_lists / … > ) # Returns a 1d/2d/… NumPy array.
< array > = np . zeros / ones / empty ( < shape > ) # Also np.full(<shape>, <el>).
< array > = np . arange ( from_inc , to_exc , ± step ) # Also np.linspace(start, stop, len).
< array > = np . random . randint ( from_inc , to_exc , < shape > ) # Also np.random.random(<shape>). < view > = < array > . reshape ( < shape > ) # Also `<array>.shape = <shape>`.
< array > = < array > . flatten () # Also `<view> = <array>.ravel()`.
< view > = < array > . transpose () # Or: <array>.T < array > = np . copy / abs / sqrt / log / int64 ( < array > ) # Returns new array of the same shape.
< array > = < array > . sum / max / mean / argmax / all ( axis ) # Aggregates specified dimension.
< array > = np . apply_along_axis ( < func > , axis , < array > ) # Func can return a scalar or array. < array > = np . concatenate ( < list_of_arrays > , axis = 0 ) # Links arrays along first axis (rows).
< array > = np . vstack / column_stack ( < list_of_arrays > ) # Treats 1d arrays as rows or columns.
< array > = np . tile / repeat ( < array > , < int / list > [, axis ]) # Tiles array or repeats its elements.<el> = <2d>[row_index, col_index] # Or: <3d>[<int>, <int>, <int>]
<1d_view> = <2d>[row_index] # Or: <3d>[<int>, <int>, <slice>]
<1d_view> = <2d>[:, col_index] # Or: <3d>[<int>, <slice>, <int>]
<2d_view> = <2d>[from:to_row_i, from:to_col_i] # Or: <3d>[<int>, <slice>, <slice>] <1d_array> = <2d>[row_indices, col_indices] # Or: <3d>[<int/1d>, <1d>, <1d>]
<2d_array> = <2d>[row_indices] # Or: <3d>[<int/1d>, <1d>, <slice>]
<2d_array> = <2d>[:, col_indices] # Or: <3d>[<int/1d>, <slice>, <1d>]
<2d_array> = <2d>[np.ix_(row_indices, col_indices)] # Or: <3d>[<int/1d/2d>, <2d>, <2d>] <2d_bools> = <2d> > <el/1d/2d> # 1d object must have size of a row.
<1/2d_arr> = <2d>[<2d/1d_bools>] # 1d_bools must have size of a column.':' renvoie une tranche de tous les indices de dimension. Les dimensions omises sont par défaut ':' .'obj[i, j]' en 'obj[(i, j)]' !'ix_([1, 2], [3, 4])' renvoie '[[1], [2]]' et '[[3, 4]]' . En raison des règles de diffusion, cela revient à utiliser '[[1, 1], [2, 2]]' et '[[3, 4], [3, 4]]' .Un ensemble de règles selon lesquelles les fonctions NumPy opèrent sur des tableaux de formes différentes.
left = [ 0.1 , 0.6 , 0.8 ] # Shape: (3,)
right = [[ 0.1 ], [ 0.6 ], [ 0.8 ]] # Shape: (3, 1) left = [[ 0.1 , 0.6 , 0.8 ]] # Shape: (1, 3) <- !
right = [[ 0.1 ], [ 0.6 ], [ 0.8 ]] # Shape: (3, 1) left = [[ 0.1 , 0.6 , 0.8 ], # Shape: (3, 3) <- !
[ 0.1 , 0.6 , 0.8 ],
[ 0.1 , 0.6 , 0.8 ]]
right = [[ 0.1 , 0.1 , 0.1 ], # Shape: (3, 3) <- !
[ 0.6 , 0.6 , 0.6 ],
[ 0.8 , 0.8 , 0.8 ]][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 = points - wrapped_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. ]]
> >> distances [ range ( 3 ), range ( 3 )] = np . inf
[[ inf , 0.5 , 0.7 ],
[ 0.5 , inf , 0.2 ],
[ 0.7 , 0.2 , inf ]]
> >> distances . argmin ( 1 )
[ 1 , 2 , 1 ] # $ pip3 install pillow
from PIL import Image < Image > = Image . new ( '<mode>' , ( width , height )) # Creates new image. Also `color=<int/tuple>`.
< Image > = Image . open ( < path > ) # Identifies format based on file's contents.
< Image > = < Image > . convert ( '<mode>' ) # Converts image to the new mode (see Modes).
< Image > . save ( < path > ) # Selects format based on extension (PNG/JPG…).
< Image > . show () # Displays image in default preview app. < int / tup > = < Image > . getpixel (( x , y )) # Returns pixel's value (its color).
< ImgCore > = < Image > . getdata () # Returns a flattened view of pixel values.
< Image > . putpixel (( x , y ), < int / tuple > ) # Updates pixel's value. Clips passed int/s.
< Image > . putdata ( < list / ImgCore > ) # Updates pixels with a copy of the sequence.
< Image > . paste ( < Image > , ( x , y )) # Draws passed image at the specified location. < Image > = < Image > . filter ( < Filter > ) # Use ImageFilter.<name>(<args>) for Filter.
< Image > = < Enhance > . enhance ( < float > ) # Use ImageEnhance.<name>(<Image>) for Enhance. < array > = np . array ( < Image > ) # Creates a 2d/3d NumPy array from the image.
< Image > = Image . fromarray ( np . uint8 ( < array > )) # Use <array>.clip(0, 255) to clip the values.'L' - Légèreté (image en niveaux de gris). Chaque pixel est un entier compris entre 0 et 255.'RGB' - Rouge, vert, bleu (image en vraies couleurs). Chaque pixel est un tuple de trois entiers.'RGBA' - RVB avec alpha. Un alpha faible (c'est-à-dire le quatrième int) rend les pixels plus transparents.'HSV' - Teinte, saturation, valeur. Trois entiers représentant la couleur dans l'espace colorimétrique HSV. WIDTH , HEIGHT = 100 , 100
n_pixels = WIDTH * HEIGHT
hues = ( 255 * i / n_pixels for i in range ( n_pixels ))
img = Image . new ( 'HSV' , ( WIDTH , HEIGHT ))
img . putdata ([( int ( h ), 255 , 255 ) for h in hues ])
img . convert ( 'RGB' ). save ( 'test.png' ) 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 . show () from PIL import ImageDraw
< Draw > = ImageDraw . Draw ( < Image > ) # Object for adding 2D graphics to the image.
< Draw > . point (( x , y )) # Draws a point. Truncates floats into ints.
< Draw > . line (( x1 , y1 , x2 , y2 [, ...])) # To get anti-aliasing use Image's resize().
< Draw > . arc (( x1 , y1 , x2 , y2 ), deg1 , deg2 ) # Draws in clockwise dir. Also pieslice().
< Draw > . rectangle (( x1 , y1 , x2 , y2 )) # Also rounded_rectangle(), regular_polygon().
< Draw > . polygon (( x1 , y1 , x2 , y2 , ...)) # Last point gets connected to the first.
< Draw > . ellipse (( x1 , y1 , x2 , y2 )) # To rotate use Image's rotate() and paste().
< Draw > . text (( x , y ), < str > , font = < Font > ) # `<Font> = ImageFont.truetype(<path>, size)`.'fill=<color>' pour définir la couleur primaire.'width=<int>' pour définir la largeur des lignes ou des contours.'outline=<color>' pour définir la couleur des contours.'#rrggbb[aa]' ou un nom de couleur. # $ pip3 install imageio
from PIL import Image , ImageDraw
import imageio
WIDTH , HEIGHT , R = 126 , 126 , 10
frames = []
for velocity in range ( 1 , 16 ):
y = sum ( range ( velocity ))
frame = Image . new ( 'L' , ( WIDTH , HEIGHT ))
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 ) import wave < Wave > = wave . open ( '<path>' ) # Opens the WAV file for reading.
< int > = < Wave > . getframerate () # Returns number of frames per second.
< int > = < Wave > . getnchannels () # Returns number of samples per frame.
< int > = < Wave > . getsampwidth () # Returns number of bytes per sample.
< tuple > = < Wave > . getparams () # Returns namedtuple of all parameters.
< bytes > = < Wave > . readframes ( nframes ) # Returns next n frames (-1 returns all). < Wave > = wave . open ( '<path>' , 'wb' ) # Creates/truncates a file for writing.
< Wave > . setframerate ( < int > ) # Pass 44100 for CD, 48000 for video.
< Wave > . setnchannels ( < int > ) # Pass 1 for mono, 2 for stereo.
< Wave > . setsampwidth ( < int > ) # Pass 2 for CD, 3 for hi-res sound.
< Wave > . setparams ( < tuple > ) # Tuple must contain all parameters.
< Wave > . writeframes ( < bytes > ) # Appends frames to the file. +-----------+-----------+------+-----------+
| sampwidth | min | zero | max |
+-----------+-----------+------+-----------+
| 1 | 0 | 128 | 255 |
| 2 | -32768 | 0 | 32767 |
| 3 | -8388608 | 0 | 8388607 |
+-----------+-----------+------+-----------+
def read_wav_file ( filename ):
def get_int ( bytes_obj ):
an_int = int . from_bytes ( bytes_obj , 'little' , signed = ( p . sampwidth != 1 ))
return an_int - 128 * ( p . sampwidth == 1 )
with wave . open ( filename ) as file :
p = file . getparams ()
frames = file . readframes ( - 1 )
bytes_samples = ( frames [ i : i + p . sampwidth ] for i in range ( 0 , len ( frames ), p . sampwidth ))
return [ get_int ( b ) / pow ( 2 , ( p . sampwidth * 8 ) - 1 ) for b in bytes_samples ], p def write_to_wav_file ( filename , samples_f , p = None , nchannels = 1 , sampwidth = 2 , framerate = 44100 ):
def get_bytes ( a_float ):
a_float = max ( - 1 , min ( 1 - 2e-16 , a_float ))
a_float += p . sampwidth == 1
a_float *= pow ( 2 , ( p . sampwidth * 8 ) - 1 )
return int ( a_float ). to_bytes ( p . sampwidth , 'little' , signed = ( p . sampwidth != 1 ))
if p is None :
p = wave . _wave_params ( nchannels , sampwidth , framerate , 0 , 'NONE' , 'not compressed' )
with wave . open ( filename , 'wb' ) as file :
file . setparams ( p )
file . writeframes ( b'' . join ( get_bytes ( f ) for f in samples_f )) from math import pi , sin
samples_f = ( sin ( i * 2 * pi * 440 / 44100 ) for i in range ( 100_000 ))
write_to_wav_file ( 'test.wav' , samples_f ) from random import uniform
samples_f , params = read_wav_file ( 'test.wav' )
samples_f = ( f + uniform ( - 0.05 , 0.05 ) for f in samples_f )
write_to_wav_file ( 'test.wav' , samples_f , params ) # $ pip3 install simpleaudio
from simpleaudio import play_buffer
with wave . open ( 'test.wav' ) as file :
p = file . getparams ()
frames = file . readframes ( - 1 )
play_buffer ( frames , p . nchannels , p . sampwidth , p . framerate ). wait_done () # $ pip3 install pyttsx3
import pyttsx3
engine = pyttsx3 . init ()
engine . say ( 'Sally sells seashells by the seashore.' )
engine . runAndWait () # $ pip3 install simpleaudio
import array , itertools as it , math , simpleaudio
F = 44100
P1 = '71♩,69♪,,71♩,66♪,,62♩,66♪,,59♩,,,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 : it . 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 note : 440 * 2 ** (( int ( note [: 2 ]) - 69 ) / 12 )
get_sec = lambda note : 1 / 4 if '♩' in note else 1 / 8
get_samples = lambda note : get_wave ( get_hz ( note ), get_sec ( note )) if note else get_pause ( 1 / 8 )
samples_f = it . chain . from_iterable ( get_samples ( n ) for n in ( P1 + P2 ). split ( ',' ))
samples_i = array . array ( 'h' , ( int ( f * 30000 ) for f in samples_f ))
simpleaudio . play_buffer ( samples_i , 1 , 2 , F ). wait_done () # $ pip3 install pygame
import pygame as pg
pg . init ()
screen = pg . display . set_mode (( 500 , 500 ))
rect = pg . Rect ( 240 , 240 , 20 , 20 )
while not pg . event . get ( pg . QUIT ):
deltas = { pg . K_UP : ( 0 , - 20 ), pg . K_RIGHT : ( 20 , 0 ), pg . K_DOWN : ( 0 , 20 ), pg . K_LEFT : ( - 20 , 0 )}
for event in pg . event . get ( pg . KEYDOWN ):
dx , dy = deltas . get ( event . key , ( 0 , 0 ))
rect = rect . move (( dx , dy ))
screen . fill ( pg . Color ( 'black' ))
pg . draw . rect ( screen , pg . Color ( 'white' ), rect )
pg . display . flip ()Objet pour stocker les coordonnées rectangulaires.
< Rect > = pg . Rect ( x , y , width , height ) # Creates Rect object. Truncates passed floats.
< int > = < Rect > . x / y / centerx / centery / … # Top, right, bottom, left. Allows assignments.
< tup . > = < Rect > . topleft / center / … # Topright, bottomright, bottomleft. Same.
< Rect > = < Rect > . move (( delta_x , delta_y )) # Use move_ip() to move in-place. < bool > = < Rect > . collidepoint (( x , y )) # Checks if rectangle contains the point.
< bool > = < Rect > . colliderect ( < Rect > ) # Checks if the two rectangles overlap.
< int > = < Rect > . collidelist ( < list_of_Rect > ) # Returns index of first colliding Rect or -1.
< list > = < Rect > . collidelistall ( < list_of_Rect > ) # Returns indices of all colliding rectangles.Objet pour représenter des images.
< Surf > = pg . display . set_mode (( width , height )) # Opens new window and returns its surface.
< Surf > = pg . Surface (( width , height )) # New RGB surface. RGBA if `flags=pg.SRCALPHA`.
< Surf > = pg . image . load ( < path / file > ) # Loads the image. Format depends on source.
< Surf > = pg . surfarray . make_surface ( < np_array > ) # Also `<np_arr> = surfarray.pixels3d(<Surf>)`.
< Surf > = < Surf > . subsurface ( < Rect > ) # Creates a new surface from the cutout. < Surf > . fill ( color ) # Tuple, Color('#rrggbb[aa]') or Color(<name>).
< Surf > . set_at (( x , y ), color ) # Updates pixel. Also <Surf>.get_at((x, y)).
< Surf > . blit ( < Surf > , ( x , y )) # Draws passed surface at specified location. from pygame . transform import scale , ...
< Surf > = scale ( < Surf > , ( width , height )) # Returns scaled surface.
< Surf > = rotate ( < Surf > , anticlock_degrees ) # Returns rotated and scaled surface.
< Surf > = flip ( < Surf > , x_bool , y_bool ) # Returns flipped surface. from pygame . draw import line , ...
line ( < Surf > , color , ( x1 , y1 ), ( x2 , y2 ), width ) # Draws a line to the surface.
arc ( < Surf > , color , < Rect > , from_rad , to_rad ) # Also ellipse(<Surf>, color, <Rect>, width=0).
rect ( < Surf > , color , < Rect > , width = 0 ) # Also polygon(<Surf>, color, points, width=0). < Font > = pg . font . Font ( < path / file > , size ) # Loads TTF file. Pass None for default font.
< Surf > = < Font > . render ( text , antialias , color ) # Background color can be specified at the end. < Sound > = pg . mixer . Sound ( < path / file / bytes > ) # WAV file or bytes/array of signed shorts.
< Sound > . play / stop () # Also set_volume(<float>), fadeout(msec). import collections , dataclasses , enum , io , itertools as it , pygame as pg , urllib . request
from random import randint
P = collections . namedtuple ( 'P' , 'x y' ) # Position
D = enum . Enum ( 'D' , 'n e s w' ) # Direction
W , H , MAX_S = 50 , 50 , P ( 5 , 10 ) # Width, Height, Max speed
def main ():
def get_screen ():
pg . init ()
return pg . display . set_mode (( W * 16 , H * 16 ))
def get_images ():
url = 'https://gto76.github.io/python-cheatsheet/web/mario_bros.png'
img = pg . 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 ():
border = [( x , y ) for x in range ( W ) for y in range ( H ) if x in [ 0 , W - 1 ] or y in [ 0 , H - 1 ]]
platforms = [( randint ( 1 , W - 2 ), randint ( 2 , H - 2 )) for _ in range ( W * H // 10 )]
return [ get_rect ( x , y ) for x , y in border + platforms ]
def get_rect ( x , y ):
return pg . Rect ( x * 16 , y * 16 , 16 , 16 )
run ( get_screen (), get_images (), get_mario (), get_tiles ())
def run ( screen , images , mario , tiles ):
clock = pg . time . Clock ()
pressed = set ()
while not pg . event . get ( pg . QUIT ) and clock . tick ( 28 ):
keys = { pg . K_UP : D . n , pg . K_RIGHT : D . e , pg . K_DOWN : D . s , pg . K_LEFT : D . w }
pressed |= { keys . get ( e . key ) for e in pg . event . get ( pg . KEYDOWN )}
pressed -= { keys . get ( e . key ) for e in pg . event . get ( pg . KEYUP )}
update_speed ( mario , tiles , pressed )
update_position ( mario , tiles )
draw ( screen , images , mario , tiles )
def update_speed ( mario , tiles , pressed ):
x , y = mario . spd
x += 2 * (( D . e in pressed ) - ( D . w in pressed ))
x += ( x < 0 ) - ( x > 0 )
y += 1 if D . s not in get_boundaries ( mario . rect , tiles ) else ( D . n in pressed ) * - 10
mario . spd = P ( x = max ( - MAX_S . x , min ( MAX_S . x , x )), y = max ( - MAX_S . y , min ( MAX_S . y , y )))
def update_position ( mario , tiles ):
x , y = mario . rect . topleft
n_steps = max ( abs ( s ) for s in mario . spd )
for _ in range ( n_steps ):
mario . spd = stop_on_collision ( mario . spd , get_boundaries ( mario . rect , tiles ))
x , y = x + ( mario . spd . x / n_steps ), y + ( mario . spd . y / n_steps )
mario . rect . topleft = x , y
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 ):
screen . fill (( 85 , 168 , 255 ))
mario . facing_left = mario . spd . x < 0 if mario . spd . x else mario . facing_left
is_airborne = D . s not in get_boundaries ( mario . rect , tiles )
image_index = 4 if is_airborne else ( next ( mario . frame_cycle ) if mario . spd . x else 6 )
screen . blit ( images [ image_index + ( mario . facing_left * 9 )], mario . rect )
for t in tiles :
is_border = t . x in [ 0 , ( W - 1 ) * 16 ] or t . y in [ 0 , ( H - 1 ) * 16 ]
screen . blit ( images [ 18 if is_border else 19 ], t )
pg . display . flip ()
if __name__ == '__main__' :
main ()Bibliothèque d'analyse de données. Pour des exemples, voir Plotly.
# $ pip3 install pandas matplotlib
import pandas as pd , matplotlib . pyplot as pltDictionnaire commandé avec un nom.
> >> s = pd . Series ([ 1 , 2 ], index = [ 'x' , 'y' ], name = 'a' ); s
x 1
y 2
Name : a , dtype : int64 < S > = pd . Series ( < list > ) # Uses list's indices for 'index'.
< S > = pd . Series ( < dict > ) # Uses dictionary's keys for 'index'. < el > = < S > . loc [ key ] # Or: <S>.iloc[i]
< S > = < S > . loc [ coll_of_keys ] # Or: <S>.iloc[coll_of_i]
< S > = < S > . loc [ from_key : to_key_inc ] # Or: <S>.iloc[from_i : to_i_exc] < el > = < S > [ key / i ] # Or: <S>.<key>
< S > = < S > [ coll_of_keys / coll_of_i ] # Or: <S>[key/i : key/i]
< S > = < S > [ bools ] # Or: <S>.loc/iloc[bools] < S > = < S > > < el / S > # Returns S of bools. Pairs items by keys.
< S > = < S > + < el / S > # Items with non-matching keys get value NaN. < S > = pd . concat ( < coll_of_S > ) # Concats multiple series into one long Series.
< S > = < S > . combine_first ( < S > ) # Adds items that are not yet present.
< S > . update ( < S > ) # Updates items that are already present. < S > . plot . line / area / bar / pie / hist () # Generates a plot. `plt.show()` displays it.'obj[x, y]' est converti en 'obj[(x, y)]' !'np.int64' . La série est convertie en 'float64' si nous attribuons np.nan à n'importe quel élément. Utilisez '<S>.astype(<str/type>)' pour obtenir une série convertie.'pd.Series([100], dtype="int8") + 100' . < el > = < S > . sum / max / mean / idxmax / all () # Or: <S>.agg(lambda <S>: <el>)
< S > = < S > . rank / diff / cumsum / ffill / interpol …() # Or: <S>.agg/transform(lambda <S>: <S>)
< S > = < S > . isna / fillna / isin ([ < el / coll > ]) # Or: <S>.agg/transform/map(lambda <el>: <el>) +--------------+-------------+-------------+---------------+
| | 'sum' | ['sum'] | {'s': 'sum'} |
+--------------+-------------+-------------+---------------+
| s.apply(…) | 3 | sum 3 | s 3 |
| s.agg(…) | | | |
+--------------+-------------+-------------+---------------+
+--------------+-------------+-------------+---------------+
| | 'rank' | ['rank'] | {'r': 'rank'} |
+--------------+-------------+-------------+---------------+
| s.apply(…) | | rank | |
| s.agg(…) | x 1.0 | x 1.0 | r x 1.0 |
| | y 2.0 | y 2.0 | y 2.0 |
+--------------+-------------+-------------+---------------+
'inplace=True' .'<S>[key_1, key_2]' pour obtenir ses valeurs.Tableau avec des lignes et des colonnes étiquetées.
> >> df = pd . DataFrame ([[ 1 , 2 ], [ 3 , 4 ]], index = [ 'a' , 'b' ], columns = [ 'x' , 'y' ]); df
x y
a 1 2
b 3 4 < DF > = pd . DataFrame ( < list_of_rows > ) # Rows can be either lists, dicts or series.
< DF > = pd . DataFrame ( < dict_of_columns > ) # Columns can be either lists, dicts or series. < el > = < DF > . loc [ row_key , col_key ] # Or: <DF>.iloc[row_i, col_i]
< S / DF > = < DF > . loc [ row_key / s ] # Or: <DF>.iloc[row_i/s]
< S / DF > = < DF > . loc [:, col_key / s ] # Or: <DF>.iloc[:, col_i/s]
< DF > = < DF > . loc [ row_bools , col_bools ] # Or: <DF>.iloc[row_bools, col_bools] < S / DF > = < DF > [ col_key / s ] # Or: <DF>.<col_key>
< DF > = < DF > [ < S_of_bools > ] # Filters rows. For example `df[df.x > 1]`.
< DF > = < DF > [ < DF_of_bools > ] # Assigns NaN to items that are False in bools. < DF > = < DF > > < el / S / DF > # Returns DF of bools. S is treated as a row.
< DF > = < DF > + < el / S / DF > # Items with non-matching keys get value NaN. < DF > = < DF > . set_index ( col_key ) # Replaces row keys with column's values.
< DF > = < DF > . reset_index ( drop = False ) # Drops or moves row keys to column named index.
< DF > = < DF > . sort_index ( ascending = True ) # Sorts rows by row keys. Use `axis=1` for cols.
< DF > = < DF > . sort_values ( col_key / s ) # Sorts rows by passed column/s. Also `axis=1`. < DF > = < DF > . head / tail / sample ( < int > ) # Returns first, last, or random n rows.
< DF > = < DF > . describe () # Describes columns. Also info(), corr(), shape.
< DF > = < DF > . query ( '<query>' ) # Filters rows. For example `df.query('x > 1')`. < DF > . plot . line / area / bar / scatter ( x = col_key , …) # `y=col_key/s`. Also hist/box(by=col_key).
plt . show () # Displays the plot. Also plt.savefig(<path>). > >> df_2 = pd . DataFrame ([[ 4 , 5 ], [ 6 , 7 ]], index = [ 'b' , 'c' ], columns = [ 'y' , 'z' ]); df_2
y z
b 4 5
c 6 7 +-----------------------+---------------+------------+------------+---------------------------+
| | 'outer' | 'inner' | 'left' | Description |
+-----------------------+---------------+------------+------------+---------------------------+
| df.merge(df_2, | x y z | x y z | x y z | Merges on column if 'on' |
| on='y', | 0 1 2 . | 3 4 5 | 1 2 . | or 'left_on/right_on' are |
| how=…) | 1 3 4 5 | | 3 4 5 | set, else on shared cols. |
| | 2 . 6 7 | | | Uses 'inner' by default. |
+-----------------------+---------------+------------+------------+---------------------------+
| df.join(df_2, | x yl yr z | | x yl yr z | Merges on row keys. |
| lsuffix='l', | a 1 2 . . | x yl yr z | 1 2 . . | Uses 'left' by default. |
| rsuffix='r', | b 3 4 4 5 | 3 4 4 5 | 3 4 4 5 | If Series is passed, it |
| how=…) | c . . 6 7 | | | is treated as a column. |
+-----------------------+---------------+------------+------------+---------------------------+
| pd.concat([df, df_2], | x y z | y | | Adds rows at the bottom. |
| axis=0, | a 1 2 . | 2 | | Uses 'outer' by default. |
| join=…) | b 3 4 . | 4 | | A Series is treated as a |
| | b . 4 5 | 4 | | column. To add a row use |
| | c . 6 7 | 6 | | pd.concat([df, DF([s])]). |
+-----------------------+---------------+------------+------------+---------------------------+
| pd.concat([df, df_2], | x y y z | | | Adds columns at the |
| axis=1, | a 1 2 . . | x y y z | | right end. Uses 'outer' |
| join=…) | b 3 4 4 5 | 3 4 4 5 | | by default. A Series is |
| | c . . 6 7 | | | treated as a column. |
+-----------------------+---------------+------------+------------+---------------------------+
< S > = < DF > . sum / max / mean / idxmax / all () # Or: <DF>.apply/agg(lambda <S>: <el>)
< DF > = < DF > . rank / diff / cumsum / ffill / interpo …() # Or: <DF>.apply/agg/transform(lambda <S>: <S>)
< DF > = < DF > . isna / fillna / isin ([ < el / coll > ]) # Or: <DF>.applymap(lambda <el>: <el>) +-----------------+---------------+---------------+---------------+
| | 'sum' | ['sum'] | {'x': 'sum'} |
+-----------------+---------------+---------------+---------------+
| df.apply(…) | x 4 | x y | x 4 |
| df.agg(…) | y 6 | sum 4 6 | |
+-----------------+---------------+---------------+---------------+
+-----------------+---------------+---------------+---------------+
| | 'rank' | ['rank'] | {'x': 'rank'} |
+-----------------+---------------+---------------+---------------+
| df.apply(…) | | x y | |
| df.agg(…) | x y | rank rank | x |
| df.transform(…) | a 1.0 1.0 | a 1.0 1.0 | a 1.0 |
| | b 2.0 2.0 | b 2.0 2.0 | b 2.0 |
+-----------------+---------------+---------------+---------------+
'axis=1' pour traiter les lignes à la place.'<DF>.loc[row_key, (col_key_1, col_key_2)]' . < DF > = < DF > . xs ( row_key , level = < int > ) # Rows with key on passed level of multi-index.
< DF > = < DF > . xs ( row_keys , level = < ints > ) # Rows that have first key on first level, etc.
< DF > = < DF > . set_index ( col_keys ) # Combines multiple columns into a multi-index.
< S / DF > = < DF > . stack / unstack ( level = - 1 ) # Combines col keys with row keys or vice versa.
< DF > = < DF > . pivot_table ( index = col_key / s ) # `columns=key/s, values=key/s, aggfunc='mean'`. < DF > = pd . read_json / html ( '<str/path/url>' ) # Run `$ pip3 install beautifulsoup4 lxml`.
< DF > = pd . read_csv ( '<path/url>' ) # `header/index_col/dtype/usecols/…=<obj>`.
< DF > = pd . read_pickle / excel ( '<path/url>' ) # Use `sheet_name=None` to get all Excel sheets.
< DF > = pd . read_sql ( '<table/query>' , < conn . > ) # SQLite3/SQLAlchemy connection (see #SQLite). < dict > = < DF > . to_dict ( 'd/l/s/…' ) # Returns columns as dicts, lists or series.
< str > = < DF > . to_json / html / csv / latex () # Saves output to a file if path is passed.
< DF > . to_pickle / excel ( < path > ) # Run `$ pip3 install "pandas[excel]" odfpy`.
< DF > . to_sql ( '<table_name>' , < connection > ) # Also `if_exists='fail/replace/append'`.'<S> = pd.to_datetime(<S>, errors="coerce")' , qui utilise pd.nat.'<S>.dt.year/date/…' .Objet qui regroupe les lignes d'une dataframe basée sur la valeur de la colonne passée.
< GB > = < DF > . groupby ( col_key / s ) # Splits DF into groups based on passed column.
< DF > = < GB > . apply ( < func > ) # Maps each group. Func can return DF, S or el.
< DF > = < GB > . filter ( < func > ) # Drops a group if function returns False.
< DF > = < GB > . get_group ( < el > ) # Selects a group by grouping column's value.
< S > = < GB > . size () # S of group sizes. Same keys as get_group().
< GB > = < GB > [ col_key ] # Single column GB. All operations return S. < DF > = < GB > . sum / max / mean / idxmax / all () # Or: <GB>.agg(lambda <S>: <el>)
< DF > = < GB > . rank / diff / cumsum / ffill () # Or: <GB>.transform(lambda <S>: <S>)
< DF > = < GB > . fillna ( < el > ) # Or: <GB>.transform(lambda <S>: <S>) 'z' sur reset_index (): > >> df = pd . DataFrame ([[ 1 , 2 , 3 ], [ 4 , 5 , 6 ], [ 7 , 8 , 6 ]], list ( 'abc' ), list ( 'xyz' ))
> >> gb = df . groupby ( 'z' ); gb . apply ( print )
x y z
a 1 2 3
x y z
b 4 5 6
c 7 8 6
>> > gb . sum ()
x y
z
3 1 2
6 11 13Objet pour les calculs de fenêtres en roulage.
< RS / RDF / RGB > = < S / DF / GB > . rolling ( win_size ) # Also: `min_periods=None, center=False`.
< RS / RDF / RGB > = < RDF / RGB > [ col_key / s ] # Or: <RDF/RGB>.col_key
< S / DF > = < R > . mean / sum / max () # Or: <R>.apply/agg(<agg_func/str>) # $ pip3 install plotly kaleido pandas
import plotly . express as px , pandas as pd < Fig > = px . line ( < DF > , x = col_key , y = col_key ) # Or: px.line(x=<list>, y=<list>)
< Fig > . update_layout ( margin = dict ( t = 0 , r = 0 , b = 0 , l = 0 )) # Also `paper_bgcolor='rgb(0, 0, 0)'`.
< Fig > . write_html / json / image ( '<path>' ) # <Fig>.show() displays the plot. < Fig > = px . area / bar / box ( < DF > , x = col_key , y = col_key ) # Also `color=col_key`.
< Fig > = px . scatter ( < DF > , x = col_key , y = col_key ) # Also `color/size/symbol=col_key`.
< Fig > = px . scatter_3d ( < DF > , x = col_key , y = col_key , …) # `z=col_key`. Also color/size/symbol.
< Fig > = px . histogram ( < DF > , x = col_key [, nbins = < int > ]) # Number of bins depends on DF size. 
covid = pd . read_csv ( 'https://raw.githubusercontent.com/owid/covid-19-data/8dde8ca49b'
'6e648c17dd420b2726ca0779402651/public/data/owid-covid-data.csv' ,
usecols = [ 'iso_code' , 'date' , 'total_deaths' , 'population' ])
continents = pd . read_csv ( 'https://gto76.github.io/python-cheatsheet/web/continents.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 [ df . date > '2020-03-14' ]
df = df . rename ({ 'date' : 'Date' , 'Continent_Name' : 'Continent' }, axis = 'columns' )
px . line ( df , x = 'Date' , y = 'Total Deaths per Million' , color = 'Continent' ). show ()
import pandas as pd , plotly . graph_objects as go
def main ():
covid , bitcoin , gold , dow = scrape_data ()
df = wrangle_data ( covid , bitcoin , gold , dow )
display_data ( df )
def scrape_data ():
def get_covid_cases ():
url = 'https://covid.ourworldindata.org/data/owid-covid-data.csv'
df = pd . read_csv ( url , usecols = [ 'location' , 'date' , 'total_cases' ])
df = df [ df . location == 'World' ]
return df . set_index ( 'date' ). total_cases
def get_ticker ( symbol ):
url = ( f'https://query1.finance.yahoo.com/v7/finance/download/ { symbol } ?'
'period1=1579651200&period2=9999999999&interval=1d&events=history' )
df = pd . read_csv ( url , usecols = [ 'Date' , 'Close' ])
return df . set_index ( 'Date' ). Close
out = get_covid_cases (), get_ticker ( 'BTC-USD' ), get_ticker ( 'GC=F' ), get_ticker ( '^DJI' )
names = [ 'Total Cases' , 'Bitcoin' , 'Gold' , 'Dow Jones' ]
return map ( pd . Series . rename , out , names )
def wrangle_data ( covid , bitcoin , gold , dow ):
df = pd . concat ([ bitcoin , gold , dow ], axis = 1 ) # Creates table by joining columns on dates.
df = df . sort_index (). interpolate () # Sorts rows by date and interpolates NaN-s.
df = df . loc [ '2020-02-23' :] # Discards rows before '2020-02-23'.
df = ( df / df . iloc [ 0 ]) * 100 # Calculates percentages relative to day 1.
df = df . join ( covid ) # Adds column with covid cases.
return df . sort_values ( df . index [ - 1 ], axis = 1 ) # Sorts columns by last day's value.
def display_data ( df ):
figure = go . Figure ()
for col_name in reversed ( df . columns ):
yaxis = 'y1' if col_name == 'Total Cases' else 'y2'
trace = go . Scatter ( x = df . index , y = df [ col_name ], name = col_name , yaxis = yaxis )
figure . add_trace ( trace )
figure . update_layout (
yaxis1 = dict ( title = 'Total Cases' , rangemode = 'tozero' ),
yaxis2 = dict ( title = '%' , rangemode = 'tozero' , overlaying = 'y' , side = 'right' ),
legend = dict ( x = 1.08 ),
width = 944 ,
height = 423
)
figure . show ()
if __name__ == '__main__' :
main ()Bibliothèque qui compile le code de type python dans C.
# $ pip3 install cython
import pyximport ; pyximport . install () # Module that runs imported Cython scripts.
import < cython_script > # Script needs a '.pyx' extension.
< cython_script > . main () # Main() isn't automatically executed. 'cdef' sont facultatives, mais elles contribuent à l'accélération.'*' et '&' , les structures, les syndicats et les énumériques. cdef < ctype / type > < var_name > [ = < obj > ]
cdef < ctype > [ n_elements ] < var_name > [ = < coll_of_nums > ]
cdef < ctype / type / void > < func_name > ( < ctype / type > < arg_name > ): ... cdef class < class_name > :
cdef public < ctype / type > < attr_name >
def __init__ ( self , < ctype / type > < arg_name > ):
self . < attr_name > = < arg_name >Système d'installation des bibliothèques directement dans le répertoire du projet.
$ python3 -m venv NAME # Creates virtual environment in current directory.
$ source NAME/bin/activate # Activates env. On Windows run `NAMEScriptsactivate`.
$ pip3 install LIBRARY # Installs the library into active environment.
$ python3 FILE # Runs the script in active environment. Also `./FILE`.
$ deactivate # Deactivates the active virtual environment. Exécutez le script avec '$ python3 FILE' ou '$ chmod u+x FILE; ./FILE' . Pour démarrer automatiquement le débogueur lorsque une exception non capturée se produit '$ python3 -m pdb -cc FILE' .
#!/usr/bin/env python3
#
# Usage: .py
#
from sys import argv , exit
from collections import defaultdict , namedtuple
from dataclasses import make_dataclass
from enum import Enum
import functools as ft , itertools as it , operator as op , re
def main ():
pass
###
## UTIL
#
def read_file ( filename ):
with open ( filename , encoding = 'utf-8' ) as file :
return file . readlines ()
if __name__ == '__main__' :
main ()'#<title>' sur la page Web limitera la recherche aux titres.'?' Pour obtenir un lien vers sa section.
