https://github.com/coady/placeholder

Operator overloading for fast anonymous functions.
https://github.com/coady/placeholder

functional lambda partial underscore

Last synced: 10 months ago
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Operator overloading for fast anonymous functions.

• Host: GitHub
• URL: https://github.com/coady/placeholder
• Owner: coady
• License: other
• Created: 2015-09-19T22:56:35.000Z (over 10 years ago)
• Default Branch: main
• Last Pushed: 2024-09-28T05:49:03.000Z (over 1 year ago)
• Last Synced: 2024-10-14T09:41:34.139Z (over 1 year ago)
• Topics: functional, lambda, partial, underscore
• Language: Python
• Homepage: https://coady.github.io/placeholder
• Size: 775 KB
• Stars: 50
• Watchers: 2
• Forks: 5
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE.txt

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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]

```