fnc#
Functional programming in Python with generators and other utilities.
Links#
Project: https://github.com/dgilland/fnc
Documentation: https://fnc.readthedocs.io
Github Actions: https://github.com/dgilland/fnc/actions
Features#
Functional-style methods that work with and return generators.
Shorthand-style iteratees (callbacks) to easily filter and map data.
String object-path support for references nested data structures.
100% test coverage.
Python 3.6+
Quickstart#
Install using pip:
pip3 install fnc
Import the main module:
import fnc
Start working with data:
users = [
{'id': 1, 'name': 'Jack', 'email': 'jack@example.org', 'active': True},
{'id': 2, 'name': 'Max', 'email': 'max@example.com', 'active': True},
{'id': 3, 'name': 'Allison', 'email': 'allison@example.org', 'active': False},
{'id': 4, 'name': 'David', 'email': 'david@example.net', 'active': False}
]
Filter active users:
# Uses "matches" shorthand iteratee: dictionary
active_users = fnc.filter({'active': True}, users)
# <filter object at 0x7fa85940ec88>
active_uesrs = list(active_users)
# [{'name': 'Jack', 'email': 'jack@example.org', 'active': True},
# {'name': 'Max', 'email': 'max@example.com', 'active': True}]
Get a list of email addresses:
# Uses "pathgetter" shorthand iteratee: string
emails = fnc.map('email', users)
# <map object at 0x7fa8577d52e8>
emails = list(emails)
# ['jack@example.org', 'max@example.com', 'allison@example.org', 'david@example.net']
Create a dict
of users keyed by 'id'
:
# Uses "pathgetter" shorthand iteratee: string
users_by_id = fnc.keyby('id', users)
# {1: {'id': 1, 'name': 'Jack', 'email': 'jack@example.org', 'active': True},
# 2: {'id': 2, 'name': 'Max', 'email': 'max@example.com', 'active': True},
# 3: {'id': 3, 'name': 'Allison', 'email': 'allison@example.org', 'active': False},
# 4: {'id': 4, 'name': 'David', 'email': 'david@example.net', 'active': False}}
Select only 'id'
and 'email'
fields and return as dictionaries:
# Uses "pickgetter" shorthand iteratee: set
user_emails = list(fnc.map({'id', 'email'}, users))
# [{'email': 'jack@example.org', 'id': 1},
# {'email': 'max@example.com', 'id': 2},
# {'email': 'allison@example.org', 'id': 3},
# {'email': 'david@example.net', 'id': 4}]
Select only 'id'
and 'email'
fields and return as tuples:
# Uses "atgetter" shorthand iteratee: tuple
user_emails = list(fnc.map(('id', 'email'), users))
# [(1, 'jack@example.org'),
# (2, 'max@example.com'),
# (3, 'allison@example.org'),
# (4, 'david@example.net')]
Access nested data structures using object-path notation:
fnc.get('a.b.c[1][0].d', {'a': {'b': {'c': [None, [{'d': 100}]]}}})
# 100
# Same result but using a path list instead of a string.
fnc.get(['a', 'b', 'c', 1, 0, 'd'], {'a': {'b': {'c': [None, [{'d': 100}]]}}})
# 100
Compose multiple functions into a generator pipeline:
from functools import partial
filter_active = partial(fnc.filter, {'active': True})
get_emails = partial(fnc.map, 'email')
get_email_domains = partial(fnc.map, lambda email: email.split('@')[1])
get_active_email_domains = fnc.compose(
filter_active,
get_emails,
get_email_domains,
set,
)
email_domains = get_active_email_domains(users)
# {'example.com', 'example.org'}
Or do the same thing except using a terser “partial” shorthand:
get_active_email_domains = fnc.compose(
(fnc.filter, {'active': True}),
(fnc.map, 'email'),
(fnc.map, lambda email: email.split('@')[1]),
set,
)
email_domains = get_active_email_domains(users)
# {'example.com', 'example.org'}
For more details and examples, please see the full documentation at https://fnc.readthedocs.io.
Guide#
- Installation
- API Reference
- Generators
- Iteratees
- Function Composition
- Sequences
chunk()
compact()
concat()
countby()
difference()
differenceby()
duplicates()
duplicatesby()
filter()
find()
findindex()
findlast()
findlastindex()
flatten()
flattendeep()
groupall()
groupby()
intercalate()
interleave()
intersection()
intersectionby()
intersperse()
keyby()
map()
mapcat()
mapflat()
mapflatdeep()
partition()
reject()
union()
unionby()
unzip()
without()
xor()
- Mappings
- Utilities
- Developer Guide