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fnc
|version| |build| |coveralls| |license|
Functional programming in Python with generators and other utilities.
Install using pip:
::
pip3 install fnc
Import the main module:
.. code-block:: python
import fnc
Start working with data:
.. code-block:: python
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:
.. code-block:: python
# 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:
.. code-block:: python
# 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'
:
.. code-block:: python
# 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:
.. code-block:: python
# 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:
.. code-block:: python
# 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:
.. code-block:: python
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:
.. code-block:: python
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:
.. code-block:: python
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.
.. |version| image:: https://img.shields.io/pypi/v/fnc.svg?style=flat-square :target: https://pypi.python.org/pypi/fnc/
.. |build| image:: https://img.shields.io/github/workflow/status/dgilland/fnc/Main/master?style=flat-square :target: https://github.com/dgilland/fnc/actions
.. |coveralls| image:: https://img.shields.io/coveralls/dgilland/fnc/master.svg?style=flat-square :target: https://coveralls.io/r/dgilland/fnc
.. |license| image:: https://img.shields.io/pypi/l/fnc.svg?style=flat-square :target: https://pypi.python.org/pypi/fnc/
pick
.v0.5.1
that broke get/has
for dictionaries and dot-delimited keys that reference integer dict-keys.get/has
that caused defaultdict
objects to get populated on key access.intersection/intersectionby
and difference/differenceby
where incorrect results could be returned when generators passed in as the sequences to compare with.Add functions:
differenceby
duplicatesby
intersectionby
unionby
tuple
can be given which will then be converted to a callable using functools.partial
. For example, instead of fnc.compose(partial(fnc.filter, {'active': True}), partial(fnc.map, 'email'))
, one can do fnc.compose((fnc.filter, {'active': True}), (fnc.map, 'email'))
.Add functions:
negate
over
overall
overany
Rename functions: (breaking change)
ismatch -> conforms
matches -> conformance
Make conforms/conformance
(formerly ismatch/matches
) accept callable dictionary values that act as predicates against comparison target. (breaking change)
None
for keys that don't exist in source object. Instead of fnc.pick(['a'], {}) == {'a': None}
, it's now fnc.pick(['a'], {}) == {}
.MIT License
Copyright (c) 2020 Derrick Gilland
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
FAQs
Functional programming in Python with generators and other utilities.
We found that fnc demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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