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https://github.com/d1618033/listful

Efficient filtering of lists of objects
https://github.com/d1618033/listful

database dict filter list pandas python python3 query search

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Efficient filtering of lists of objects

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# listful

[![pypi](https://badge.fury.io/py/listful.svg)](https://pypi.org/project/listful)
[![Python: 3.7+](https://img.shields.io/badge/Python-3.8+-blue.svg)](https://pypi.org/project/listful)
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[![Build Status](https://travis-ci.org/d1618033/listful.svg?branch=master)](https://travis-ci.org/d1618033/listful)
[![Code coverage](https://codecov.io/gh/d1618033/listful/branch/master/graph/badge.svg)](https://codecov.io/gh/d1618033/listful)
[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://en.wikipedia.org/wiki/MIT_License)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/ambv/black)

## Description

Efficient filtering of lists of objects

## Installation

pip install listful

## Usage

Initialize with the fields you want to filter by:

>>> from listful import Listful
>>> data = Listful(
... [{'x': 1, 'y': 10}, {'x': 2, 'y': 20}, {'x': 2, 'y': 30}],
... fields=['x', 'y']
... )

(If you don't specify the fields, all the fields whose corresponding values are hashable will be chosen)

### Filtering:

* By one field:

>>> data.filter(x=1).one_or_none()
{'x': 1, 'y': 10}
>>> data.filter(y=20).one_or_none()
{'x': 2, 'y': 20}

* By one field, with more than one result:

>>> data.filter(x=2).to_list()
[{'x': 2, 'y': 20}, {'x': 2, 'y': 30}]

* By two fields:

>>> data.filter(x=2, y=30).one_or_none()
{'x': 2, 'y': 30}

* Raise exception if more than one found

>>> data.filter(x=2).one_or_raise()
Traceback (most recent call last):
<...>
listful.exceptions.MoreThanOneResultException: Found more than one result for filter {'x': 2}: [{'x': 2, 'y': 20}, {'x': 2, 'y': 30}]

* Get all values for a specific field

>>> data.get_all_for_field('x')
[1, 2, 2]

### Updating indexes:

`Listful` has the same api as `list`, so you can get/set/delete items the same way
and the indices will be updated automatically

>>> data[0] = {'x': 17, 'y': 17}
>>> data.filter(x=17).one_or_none()
{'x': 17, 'y': 17}
>>> data[0]
{'x': 17, 'y': 17}
>>> del data[0]
>>> data.filter(x=17).one_or_none()

If you want to modify an element and update the indices you can do so explicitly:

>>> data[0]['x'] = 1
>>> data.rebuild_indexes_for_item(data[0])
>>> data.filter(x=1).one_or_none()
{'x': 1, 'y': 20}

### Objects:

Listful supports also lists of objects:

>>> class Item:
... def __init__(self, x, y):
... self.x = x
... self.y = y
...
... def __repr__(self):
... return f"Item(x={self.x}, y={self.y})"

>>> items = Listful(
... [Item(x=1, y=10), Item(x=2, y=20), Item(x=2, y=30)],
... fields=['x', 'y']
... )
>>> items.filter(x=1).one_or_none()
Item(x=1, y=10)

Here too, if you don't specify the fields, all fields with hashable values will be chosen:

>>> items = Listful(
... [Item(x=1, y=10), Item(x=2, y=20), Item(x=2, y=30)],
... )
>>> items.fields
['x', 'y']

## Performance

See `scripts/timing.py`.

A comparison of filtering with listful vs filtering with pandas (with/without index)

| | listful | pandas | pandas_with_index |
| --- | --- | --- | --- |
| init | 7.63e-02 | 3.03e-01 | 5.24e-02 |
| filter:1 | 2.07e-05 | 1.46e-03 | 1.79e-03 |
| filter:n | 2.02e-01 | 7.40e+01 | 1.54e+01 |

70x faster than pandas with indexing, 360x faster than pandas without indexing.

## For developers

### Create venv and install deps

make init

### Install git precommit hook

make precommit_install

### Run linters, autoformat, tests etc.

make pretty lint test

### Bump new version

make bump_major
make bump_minor
make bump_patch

## License

MIT

## Change Log

Unreleased
-----

* ...

0.3.0 - 2021-01-17
-----

* ...

0.2.1 - 2020-04-08
-----

* ...

0.2.0 - 2020-04-08
-----

* Add support for default fields

0.1.3 - 2020-02-14
-----

* ...

0.1.1 - 2020-02-12
-----

* ...

0.1.0 - 2020-02-12
-----

* initial