Metadata-Version: 2.1
Name: placeholder
Version: 1.5
Summary: Operator overloading for fast anonymous functions.
Author-email: Aric Coady <aric.coady@gmail.com>
License: Copyright 2022 Aric Coady
        
           Licensed under the Apache License, Version 2.0 (the "License");
           you may not use this file except in compliance with the License.
           You may obtain a copy of the License at
        
             http://www.apache.org/licenses/LICENSE-2.0
        
           Unless required by applicable law or agreed to in writing, software
           distributed under the License is distributed on an "AS IS" BASIS,
           WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
           See the License for the specific language governing permissions and
           limitations under the License.
        
Project-URL: Homepage, https://github.com/coady/placeholder
Project-URL: Documentation, https://coady.github.io/placeholder
Project-URL: Changelog, https://github.com/coady/placeholder/blob/main/CHANGELOG.md
Project-URL: Issues, https://github.com/coady/placeholder/issues
Keywords: functional,lambda,scala,underscore
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Typing :: Typed
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE.txt

[![image](https://img.shields.io/pypi/v/placeholder.svg)](https://pypi.org/project/placeholder/)
![image](https://img.shields.io/pypi/pyversions/placeholder.svg)
[![image](https://pepy.tech/badge/placeholder)](https://pepy.tech/project/placeholder)
![image](https://img.shields.io/pypi/status/placeholder.svg)
[![image](https://github.com/coady/placeholder/workflows/build/badge.svg)](https://github.com/coady/placeholder/actions)
[![image](https://codecov.io/gh/coady/placeholder/branch/main/graph/badge.svg)](https://codecov.io/gh/coady/placeholder/)
 [![image](https://github.com/coady/placeholder/workflows/codeql/badge.svg)](https://github.com/coady/placeholder/security/code-scanning)
[![image](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
[![image](https://mypy-lang.org/static/mypy_badge.svg)](https://mypy-lang.org/)

A `placeholder` uses operator overloading to create partially bound functions on-the-fly. When used in a binary expression, it will return a callable object with the other argument bound. It's useful for replacing `lambda` in functional programming, and resembles Scala's placeholders.

## Usage
```python
from placeholder import _     # single underscore

_.age < 18     # lambda obj: obj.age < 18
_[key] ** 2    # lambda obj: obj[key] ** 2
```

Note `_` has special meaning in other contexts, such as the previous output in interactive shells. Assign to a different name as needed. Kotlin uses `it`, but in Python `it` is a common short name for an iterator.

`_` is a singleton of an `F` class, and `F` expressions can also be used with functions.

```python
from placeholder import F

-F(len)        # lambda obj: -len(obj)
```

All applicable double underscore methods are supported.

## Performance
Every effort is made to optimize the placeholder instance. It's 20-40x faster than similar libraries on PyPI.

Placeholders are also iterable, allowing direct access to the underlying functions.

```python
(func,) = _.age  # operator.attrgetter('age')
```

Performance should generally be comparable to inlined expressions, and faster than lambda. Below are some example benchmarks.

```python
min(data, key=operator.itemgetter(-1))    # 1x
min(data, key=_[-1])                      # 1.3x
min(data, key=lambda x: x[-1])            # 1.6x
```

## Installation
```console
% pip install placeholder
```

## Tests
100% branch coverage.

```console
% pytest [--cov]
```
