A list comprehension ni njia nyingi, inayosomeka vizuri ya kujenga orodha kwa kubadilisha na/au kufilter iterable katika usemi mmoja — Pythoni's njia idiomatiki badala ya for loop inayoongeza kwa orodha.
squares = []
n ():
squares.append(n ** )
squares = [n ** n ()]
Soma kama "mraba wa n, kwa kila n katika range(5)." Ni nyingi zaidi na mara nyingi haraka kuliko loop ya manual.
# keep only even numbers
evens = [n for n in range(10) if n % 2 == 0] # [0, 2, 4, 6, 8]
# transform AND filter together
result = [n * 2 for n in range(10) if n % 2 == 0] # [0, 4, 8, 12, 16]
# if/else goes BEFORE the for (it's part of the expression, not a filter)
labels = ["even" if n % 2 == 0 else "odd" for n in range(4)]
# ["even", "odd", "even", "odd"]
{x ** 2 for x in range(5)} # set comprehension → {0, 1, 4, 9, 16}
{k: v for k, v in pairs} # dict comprehension
(x ** 2 for x in range(5)) # generator expression — LAZY, memory-efficient
Syntax sawa inajenga seti na dicts; na mabano inakuwa generator expression inayozalisha maadili kwa mail (hakuna orodha kamili katika kumbukumbu — nzuri sana kwa data kubwa).
# ❌ deeply nested / complex logic → a regular loop is more readable
matrix = [[row[i] for row in data] for i in range(cols)] # OK, but don't over-nest
Punguza comprehensions rahisi; ikiwa zinahitaji loops nyingi zilizosomekana au masharti magumu, loop ya kawaida ni wazi zaidi.
List comprehensions ni "Pythonic" — nyingi, inayosomeka vizuri, na mara nyingi haraka kuliko loops zinazolingana, inayotumiwa kila wakati kwa mabadiliko na kuchuja data.
Kufahamu zao (pamoja na seti/dict/generator variants, na lazy generator expression kwa data kubwa) ni muhimu kwa kuandika Python idiomatiki.
Kujua wakati wa kuzitumia (transformations/filters rahisi) dhidi ya loop ya kawaida (logic magumu) ni dalili ya kod safi, inayosomeka vizuri.