pyfuncol 1.3.1

Functional collections extension functions for Python

pyfuncol

• pyfuncol
  • Installation
  • Usage
    • Usage without forbiddenfruit
    • API
  • Documentation
  • Compatibility
  • Contributing
  • License

A Python functional collections library. It extends collections built-in types with useful methods to write functional Python code. It uses Forbidden Fruit under the hood.

pyfuncol provides:

• Standard "eager" methods, such as map, flat_map, group_by, etc.
• Parallel methods, such as par_map, par_flat_map, etc.
• Pure methods that leverage memoization to improve performance, such as pure_map, pure_flat_map, etc.
• Lazy methods that return iterators and never materialize results, such as lazy_map, lazy_flat_map, etc.

pyfuncol can also be used without forbiddenfruit.

Installation

pip install pyfuncol

Usage

Note: If you are not using forbiddenfruit, the functions will not extend the builtins. Please see here for usage without forbiddenfruit.

To use the methods, you just need to import pyfuncol. Some examples:

import pyfuncol

[1, 2, 3, 4].map(lambda x: x * 2).filter(lambda x: x > 4)
# [6, 8]

[1, 2, 3, 4].fold_left(0, lambda acc, n: acc + n)
# 10

{1, 2, 3, 4}.map(lambda x: x * 2).filter_not(lambda x: x <= 4)
# {6, 8}

["abc", "def", "e"].group_by(lambda s: len(s))
# {3: ["abc", "def"], 1: ["e"]}

{"a": 1, "b": 2, "c": 3}.flat_map(lambda kv: {kv[0]: kv[1] ** 2})
# {"a": 1, "b": 4, "c": 9}

pyfuncol provides parallel operations (for now par_map, par_flat_map, par_filter and par_filter_not):

[1, 2, 3, 4].par_map(lambda x: x * 2).par_filter(lambda x: x > 4)
# [6, 8]

{1, 2, 3, 4}.par_map(lambda x: x * 2).par_filter_not(lambda x: x <= 4)
# {6, 8}

{"a": 1, "b": 2, "c": 3}.par_flat_map(lambda kv: {kv[0]: kv[1] ** 2})
# {"a": 1, "b": 4, "c": 9}

pyfuncol provides operations leveraging memoization to improve performance (for now pure_map, pure_flat_map, pure_filter and pure_filter_not). These versions work only for pure functions (i.e., all calls to the same args return the same value) on hashable inputs:

[1, 2, 3, 4].pure_map(lambda x: x * 2).pure_filter(lambda x: x > 4)
# [6, 8]

{1, 2, 3, 4}.pure_map(lambda x: x * 2).pure_filter_not(lambda x: x <= 4)
# {6, 8}

{"a": 1, "b": 2, "c": 3}.pure_flat_map(lambda kv: {kv[0]: kv[1] ** 2})
# {"a": 1, "b": 4, "c": 9}

pyfuncol provides lazy operations that never materialize results:

list([1, 2, 3, 4].lazy_map(lambda x: x * 2).lazy_filter(lambda x: x > 4))
# [6, 8]

list({1, 2, 3, 4}.lazy_map(lambda x: x * 2).lazy_filter_not(lambda x: x <= 4))
# [6, 8]

list({"a": 1, "b": 2, "c": 3}.lazy_flat_map(lambda kv: {kv[0]: kv[1] ** 2}))
# [("a", 1), ("b", 4), ("c", 9)]

set([1, 2, 3, 4].lazy_map(lambda x: x * 2).lazy_filter(lambda x: x > 4))
# {6, 8}

Usage without forbiddenfruit

If you are using a Python interpreter other than CPython, forbiddenfruit will not work.

Fortunately, if forbiddenfruit does not work on your installation or if you do not want to use it, pyfuncol also supports direct function calls without extending builtins.

from pyfuncol import list as pfclist

pfclist.map([1, 2, 3], lambda x: x * 2)
# [2, 4, 6]

API

For lists, please refer to the docs.

For dictionaries, please refer to the docs.

For sets and frozensets, please refer to the docs.

For more details, please have a look at the API reference.

We support all subclasses with default constructors (OrderedDict, for example).

Documentation

See https://pyfuncol.readthedocs.io/.

Compatibility

For functions to extend built-ins, Forbidden Fruit is necessary (CPython only).

Contributing

See the contributing guide for detailed instructions on how to get started with the project.

License

pyfuncol is licensed under the MIT license.