A fancy and practical functional tools
A collection of fancy functional tools focused on practicality.
Inspired by clojure, underscore and my own abstractions. Keep reading to get an overview
or read the docs <http://funcy.readthedocs.org/>
.
Or jump directly to cheatsheet <http://funcy.readthedocs.io/en/stable/cheatsheet.html>
.
Works with Python 3.4+ and pypy3.
::
pip install funcy
Import stuff from funcy to make things happen:
.. code:: python
from funcy import whatever, you, need
Merge collections of same type (works for dicts, sets, lists, tuples, iterators and even strings):
.. code:: python
merge(coll1, coll2, coll3, ...)
join(colls)
merge_with(sum, dict1, dict2, ...)
Walk through collection, creating its transform (like map but preserves type):
.. code:: python
walk(str.upper, {'a', 'b'}) # {'A', 'B'}
walk(reversed, {'a': 1, 'b': 2}) # {1: 'a', 2: 'b'}
walk_keys(double, {'a': 1, 'b': 2}) # {'aa': 1, 'bb': 2}
walk_values(inc, {'a': 1, 'b': 2}) # {'a': 2, 'b': 3}
Select a part of collection:
.. code:: python
select(even, {1,2,3,10,20}) # {2,10,20}
select(r'^a', ('a','b','ab','ba')) # ('a','ab')
select_keys(callable, {str: '', None: None}) # {str: ''}
compact({2, None, 1, 0}) # {1,2}
Manipulate sequences:
.. code:: python
take(4, iterate(double, 1)) # [1, 2, 4, 8]
first(drop(3, count(10))) # 13
lremove(even, [1, 2, 3]) # [1, 3]
lconcat([1, 2], [5, 6]) # [1, 2, 5, 6]
lcat(map(range, range(4))) # [0, 0, 1, 0, 1, 2]
lmapcat(range, range(4)) # same
flatten(nested_structure) # flat iter
distinct('abacbdd') # iter('abcd')
lsplit(odd, range(5)) # ([1, 3], [0, 2, 4])
lsplit_at(2, range(5)) # ([0, 1], [2, 3, 4])
group_by(mod3, range(5)) # {0: [0, 3], 1: [1, 4], 2: [2]}
lpartition(2, range(5)) # [[0, 1], [2, 3]]
chunks(2, range(5)) # iter: [0, 1], [2, 3], [4]
pairwise(range(5)) # iter: [0, 1], [1, 2], ...
And functions:
.. code:: python
partial(add, 1) # inc
curry(add)(1)(2) # 3
compose(inc, double)(10) # 21
complement(even) # odd
all_fn(isa(int), even) # is_even_int
one_third = rpartial(operator.div, 3.0)
has_suffix = rcurry(str.endswith, 2)
Create decorators easily:
.. code:: python
@decorator
def log(call):
print call._func.__name__, call._args
return call()
Abstract control flow:
.. code:: python
walk_values(silent(int), {'a': '1', 'b': 'no'})
# => {'a': 1, 'b': None}
@once
def initialize():
"..."
with suppress(OSError):
os.remove('some.file')
@ignore(ErrorRateExceeded)
@limit_error_rate(fails=5, timeout=60)
@retry(tries=2, errors=(HttpError, ServiceDown))
def some_unreliable_action(...):
"..."
class MyUser(AbstractBaseUser):
@cached_property
def public_phones(self):
return self.phones.filter(public=True)
Ease debugging:
.. code:: python
squares = {tap(x, 'x'): tap(x * x, 'x^2') for x in [3, 4]}
# x: 3
# x^2: 9
# ...
@print_exits
def some_func(...):
"..."
@log_calls(log.info, errors=False)
@log_errors(log.exception)
def some_suspicious_function(...):
"..."
with print_durations('Creating models'):
Model.objects.create(...)
# ...
# 10.2 ms in Creating models
And much more <http://funcy.readthedocs.org/>
_.
Funcy is an embodiment of ideas I explain in several essays:
Why Every Language Needs Its Underscore <https://suor.github.io/blog/2014/06/22/why-every-language-needs-its-underscore/>
_Functional Python Made Easy <https://suor.github.io/blog/2013/10/13/functional-python-made-easy/>
_Abstracting Control Flow <https://suor.github.io/blog/2013/10/08/abstracting-control-flow/>
_Painless Decorators <https://suor.github.io/blog/2013/11/03/painless-decorators/>
_To run the tests using your default python:
::
pip install -r test_requirements.txt
py.test
To fully run tox
you need all the supported pythons to be installed. These are
3.4+ and PyPy3. You can run it for particular environment even in absense
of all of the above::
tox -e py310
tox -e pypy3
tox -e lint
.. |Build Status| image:: https://github.com/Suor/funcy/actions/workflows/test.yml/badge.svg :target: https://github.com/Suor/funcy/actions/workflows/test.yml?query=branch%3Amaster