semvec/pypi-packages huggingface dataset:
ansaittua 2022.7.30
Earned Value Management (Finnish: ansaittua arvonhallintaa) when coding swiftly.
Requires Python: >=3.8
Keywords: code-generation,developer-tools,validation,verification

# ansaittua

Earned Value Management (Finnish: ansaittua arvonhallintaa) when coding swiftly.

[License: MIT](https://git.sr.ht/~sthagen/ansaittua/tree/default/item/LICENSE)

[![version](https://img.shields.io/pypi/v/ansaittua.svg?style=flat)](https://pypi.python.org/pypi/ansaittua/)
[![downloads](https://img.shields.io/pypi/dm/ansaittua.svg?style=flat)](https://pypi.python.org/pypi/ansaittua/)
[![wheel](https://img.shields.io/pypi/wheel/ansaittua.svg?style=flat)](https://pypi.python.org/pypi/ansaittua/)
[![supported-versions](https://img.shields.io/pypi/pyversions/ansaittua.svg?style=flat)](https://pypi.python.org/pypi/ansaittua/)
[![supported-implementations](https://img.shields.io/pypi/implementation/ansaittua.svg?style=flat)](https://pypi.python.org/pypi/ansaittua/)

## Documentation

User and developer [documentation of ansaittua](https://codes.dilettant.life/docs/ansaittua).

## Bug Tracker

Feature requests and bug reports are bested entered in the [todos of ansaittua](https://todo.sr.ht/~sthagen/ansaittua).

## Primary Source repository

The primary source repository of [ansaittua is at sourcehut](https://git.sr.ht/~sthagen/ansaittua)
a collection of tools useful for software development.

## Status

Experimental.

**Note**: The default branch is `default`.
breakable-list 0.1
Build a list from a iterable, breakable by KeyboardInterrupt (SIGINT), and monitorable by SIGUSR1 and SIGUSR2.
Requires Python: >=3.6

A breakable list
================

Build a list from a iterable, breakable by KeyboardInterrupt (SIGINT), and
monitorable by SIGUSR1 and SIGUSR2.

The function `breakable_list` act as list() constructor, and build a list from
an iterable, except:
  - When a SIGINT (CTRL-C, KeyboardInterrupt) is received, the construction
    is stopped, and the current list is returned.
  - When a SIGUSR1 is received, the last item is pickled in a file, and the
    construction of the list continues.
  - When a SIGUSR2 is received, the current list is pickled in an file, and
    the construction of the list continues.
pyeditdistance 1.0.1
A pure, minimalist, no-dependency Python library of various edit distances.
Requires Python: >=3.7

# pyeditdistance

<p>
<img alt="PyPI" src="https://img.shields.io/pypi/v/pyeditdistance">
<img alt="PyPI - Downloads" src="https://img.shields.io/pypi/dm/pyeditdistance">
<img alt="PyPI - License" src="https://img.shields.io/pypi/l/pyeditdistance?label=license">
</p>

A pure, minimalist Python library of various edit distance metrics. MIT-licensed, zero dependencies.

Implemented methods:
  - [Levenshtein](https://en.wikipedia.org/wiki/Levenshtein_distance) (iterative and recursive implementations)
  - Normalized Levenshtein (using [Yujian-Bo](https://ieeexplore.ieee.org/document/4160958) [1])
  - [Damerau-Levenshtein](https://en.wikipedia.org/wiki/Damerau%E2%80%93Levenshtein_distance)
  - [Hamming distance](https://en.wikipedia.org/wiki/Hamming_distance)
  - [Longest common subsequence (LCS)](https://en.wikipedia.org/wiki/Longest_common_subsequence_problem)

Levenshtein and Damerau-Levenshtein distances use the Wagner-Fischer dynamic programming algorithm [2].

Some basic unit tests can be executed using `pytest`

## Installation

```pip install pyeditdistance```

Optional (user-specific):
```pip install --user pyeditdistance```

## Usage

```python
from pyeditdistance import distance as d

s1 = "I am Joe Bloggs"
s2 = "I am John Galt"

# Levenshtein distance
res = d.levenshtein(s1, s2) # => 8

# Normalized Levenshtein
res = d.normalized_levenshtein(s1, s2) # => 0.4324...

# Damerau-Levenshtein
s3 = "abc"
s4 = "cb"
res = d.damerau_levenshtein(s3, s4) # => 2

# Hamming distance
s5 = "abcccdeeffghh zz"
s6 = "bacccdeeffhghz z"
res = d.hamming(s5, s6) # => 6

# Longest common subsequence (LCS)
s7 = "AAGGQQERqer"
s8 = "AaQERqer"
res = d.longest_common_subsequence(s7, s8) # => 7
```

## References
1.  L. Yujian and L. Bo, "A normalized Levenshtein distance metric," 
    IEEE Transactions on Pattern Analysis and Machine Intelligence (2007).
    https://ieeexplore.ieee.org/document/4160958
2.  R. Wagner and M. Fisher, "The string to string correction problem," 
    Journal of the ACM, 21:168-178, 1974.
scraper-api 0.1.1b0
CI/CD pipelines for scraper library
Requires Python: >=3.10,<4.0

# ci-cd-example

ci-cd-example

CI/CD pipelines for scraper library


## Get started


#### Install requirements & pre-commit hooks

```bash
$ make setup
```

#### Testing
```bash
$ make test
```

#### Documentation

##### Locally

Serve docs locally

```bash
$ make docs-dev
```

##### Build site

```bash
$ make docs-build
```


#### Linters requirements & pre-commit hooks

##### Run flake8

```bash
$ make lint
```

##### Run black & isort

```bash
$ make black
```