functools: partial and reduce
Create specialized functions with partial and fold sequences with reduce.
functools: partial and reduce is a free Python Academy lesson on CoddyKit. This is lesson 3 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Python Academy learning path, and your progress syncs across the web and the CoddyKit app. The Python Academy course includes 4 lessons in total.
functools Overview
functools is a standard-library module of higher-order functions that operate on or return other functions.
import functools
# partial, reduce, lru_cache, wraps, cached_property ...
print(dir(functools))partial()
functools.partial(func, *args, **kw) creates a new callable with some arguments pre-filled.
import functools
def power(base, exp):
return base ** exp
square = functools.partial(power, exp=2)
cube = functools.partial(power, exp=3)
print(square(4)) # 16
print(cube(3)) # 27partial with Methods
Use partial to adapt methods with fixed parameters for use as callbacks or event handlers.
import functools, logging
logger = logging.getLogger("app")
log_error = functools.partial(logger.log, logging.ERROR)
log_error("Something went wrong")partial vs lambda
partial is preferred over lambda for pre-filling arguments because it is picklable, has a good repr, and preserves the docstring.
import functools
mul = lambda x, y: x * y
double_lambda = lambda x: mul(x, 2) # lambda approach
double_partial = functools.partial(mul, y=2) # partial approach
print(double_partial(5)) # 10reduce()
functools.reduce(func, iterable, initial) folds the iterable left-to-right using a binary function.
import functools, operator
total = functools.reduce(operator.add, [1,2,3,4,5])
print(total) # 15
product = functools.reduce(operator.mul, [1,2,3,4,5], 1)
print(product) # 120Building max() with reduce
Illustrate reduce by reimplementing max():
import functools
def my_max(seq):
return functools.reduce(lambda a, b: a if a > b else b, seq)
print(my_max([3, 1, 4, 1, 5, 9])) # 9Flattening Nested Lists
Use reduce with operator.iconcat to flatten one level of nesting.
import functools, operator
nested = [[1,2],[3,4],[5]]
flat = functools.reduce(operator.iconcat, nested, [])
print(flat) # [1, 2, 3, 4, 5]partial for URL Building
A practical partial pattern: fix a base URL and create specialised request helpers.
import functools, urllib.request
def fetch(base, path):
url = base.rstrip("/") + "/" + path.lstrip("/")
with urllib.request.urlopen(url) as r:
return r.read()
github = functools.partial(fetch, "https://api.github.com")
# github("/users/octocat")wraps(): Preserving Metadata
When writing decorators, use @functools.wraps(wrapped) so the wrapper preserves the original function's name and docstring.
import functools
def decorator(func):
@functools.wraps(func)
def wrapper(*args, **kw):
return func(*args, **kw)
return wrapper
@decorator
def greet(name):
"""Say hello."""
return f"Hello, {name}"
print(greet.__name__) # greet
print(greet.__doc__) # Say hello.total_ordering
@functools.total_ordering fills in missing comparison methods when you define __eq__ and one of __lt__/__le__/__gt__/__ge__.
import functools
@functools.total_ordering
class Version:
def __init__(self, major, minor):
self.v = (major, minor)
def __eq__(self, o): return self.v == o.v
def __lt__(self, o): return self.v < o.v
print(Version(1,2) >= Version(1,1)) # Truesingledispatch
@functools.singledispatch creates a function that dispatches to different implementations based on the type of the first argument.
import functools
@functools.singledispatch
def process(arg):
raise NotImplementedError(type(arg))
@process.register(int)
def _(n): return n * 2
@process.register(str)
def _(s): return s.upper()
print(process(5)) # 10
print(process("hi")) # HIQuick Check
What does functools.partial(pow, 2) create?
Recap
partial pre-fills function arguments; reduce folds a sequence with a binary function; wraps preserves decorator metadata; total_ordering fills comparison methods; singledispatch dispatches by type.
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Yes — the full text of “functools: partial and reduce” is free to read here on the web. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Python Academy course, upgrade to CoddyKit PRO. The Python Academy course includes 4 lessons in total.
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Create specialized functions with partial and fold sequences with reduce. You practise Python Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
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No prior experience is required. Python Academy on CoddyKit is structured for beginners through advanced learners, so you can start here or from the beginning and move at your own pace. This is lesson 3 of 4.
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All lessons in this course
- itertools: Infinite and Finite Iterators
- itertools: Combinatorics
- functools: partial and reduce
- functools: lru_cache and cached_property