semvec/pypi-packages huggingface dataset:
bifrost 19.2.1
Deployment of physical machines using OpenStack Ironic and Ansible
Requires Python: >=3.9

Bifrost
-------

.. image:: https://governance.openstack.org/tc/badges/bifrost.svg
    :target: https://governance.openstack.org/tc/reference/tags/index.html
    :alt: Team and repository tags

Bifrost (pronounced bye-frost) is a set of Ansible playbooks that
automates the task of deploying a base image onto a set of known hardware using
ironic_. It provides modular utility for one-off operating system deployment
with as few operational requirements as reasonably possible.

The mission of bifrost is to provide an easy path to deploy ironic in
a stand-alone fashion, in order to help facilitate the deployment of
infrastructure, while also being a configurable project that can consume
other OpenStack components to allow users to easily customize the
environment to fit their needs, and drive forward the stand-alone
perspective.

Use cases include:

* Installation of ironic in standalone/noauth mode without other OpenStack
  components.
* Deployment of an operating system to a known pool of hardware as
  a batch operation.
* Testing and development of ironic in the standalone mode.

.. _ironic: https://docs.openstack.org/ironic/latest/

Useful Links
~~~~~~~~~~~~

Bifrost's documentation can be found at:
  https://docs.openstack.org/bifrost/latest

Release notes are at:
  https://docs.openstack.org/releasenotes/bifrost/

The project source code repository is located at:
  https://opendev.org/openstack/bifrost/

Bugs can be filed in launchpad:
  https://launchpad.net/bifrost
outputdecorator 0.1.0
Library for decorating strings in CLI apps.
Requires Python: >=3.6

# Output Decorator <sup>v0.1.0</sup>

[![GitHub release (latest by date)](https://img.shields.io/github/v/release/saneksking/outputdecorator)](https://github.com/saneksking/outputdecorator/)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/outputdecorator?label=pypi%20downloads)](https://pypi.org/project/outputdecorator/)
![GitHub top language](https://img.shields.io/github/languages/top/saneksking/outputdecorator)
[![PyPI](https://img.shields.io/pypi/v/outputdecorator)](https://pypi.org/project/outputdecorator)
[![GitHub](https://img.shields.io/github/license/saneksking/outputdecorator)](https://github.com/saneksking/outputdecorator/blob/master/LICENSE)
[![PyPI - Format](https://img.shields.io/pypi/format/outputdecorator)](https://pypi.org/project/outputdecorator)
***
### Output Decorator - Library for decorating strings in CLI apps 
***

## Help:

`pip install outputdecorator`

```python
from output_decorator import StringDecorator

text = StringDecorator.string_decorate(text='Python', symbol='*', print_flag=False)
print(text) # ************************************ Python ***********************************

StringDecorator.string_decorate(text='Python', symbol='*', print_flag=True) 

StringDecorator.framed_decorate(text='Python', top_symbol='*', bottom_symbol='-')
"""
******
Python
------
"""
# Output: ************************************ Python ***********************************

```

***

## Disclaimer of liability:
    THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
    AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
    IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
    DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
    FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
    DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
    SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
    CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
    OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
    OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
get-external-data2 1.0.2
Downloads and imports shapefiles into OSM database.
Requires Python: >=3.12

# get-external-data2

A drop-in replacement for the original [`get-external-data.py`](https://github.com/gravitystorm/openstreetmap-carto/blob/master/scripts/get-external-data.py) script from OpenStreetMap Carto, rewritten with safety, validation, and better user experience in mind.

## Overview

`get-external-data2` is a full rewrite of the OSM Carto data import utility that downloads and imports shapefiles into a PostGIS database.

It behaves identically to the original script — but is:
- **More reliable** (honors HTTP `Last-Modified`, **skips unnecessary re-downloads**)
- **Safer** (SQL-safe with `psycopg3` and type-checked logic)
- **More transparent** (shows download progress via [`tqdm`](https://pypi.org/project/tqdm/))
- **Configurable and validated** (using [`pydantic`](https://pypi.org/project/pydantic/) with JSON schema generation)

## Installation

```bash
pip install get-external-data2
```

Or from source:

```
git clone https://github.com/insan3d/get-external-data2.git
cd get-external-data2
pip install .
```

## Features

- Fully backwards-compatible YAML configuration format and CLI interface
- Built-in `--dump-config-schema` to generate a JSON Schema for your config
- `--delete-cache` flag now actually works
- Honors HTTP caching (`If-Modified-Since` / `Last-Modified`)
- Clean interruption handling (`SIGTERM`, `KeyboardInterrupt`)
- Progress bars for file downloads
- Strict validation for schema and table names
- Safer database logic with transactional DDL via `psycopg3`

## Removed / Changed Behavior

- `file://` protocol is no longer supported for local files — only `http(s)://`
- Archive handling is limited to `.zip` (as in original script, for now)
- Modern PostgreSQL and GDAL versions are expected (tested with Debian 13 __Trixie__).

## Usage Example

```bash
get-external-data2 -c external-data.yml -v
```

Typical configuration file (`external-data.yml`):

```yaml
settings:
  schema: public
  temp_schema: loading
  database: gis
  host: /var/run/postgresql
  username: gis
  metadata_table: external_data

sources:
  simplified_water_polygons:
    url: https://osmdata.openstreetmap.de/download/simplified-water-polygons-complete-3857.zip
    file: simplified-water-polygons-complete-3857/simplified_water_polygons.shp
    archive:
      format: zip
      files:
        - simplified-water-polygons-complete-3857/simplified_water_polygons.shp
        - simplified-water-polygons-complete-3857/simplified_water_polygons.dbf
        - simplified-water-polygons-complete-3857/simplified_water_polygons.prj
        - simplified-water-polygons-complete-3857/simplified_water_polygons.shx
```

## License

MIT License — as the original OSM Carto tools.
diglife 0.2.28
Add your description here
Requires Python: >=3.12

# 考虑是否要安装卡夫卡


scp dist/* zhaoxuefeng@192.168.1.165:/Users/zhaoxuefeng/pypi-simple-server/packages


scp dist/*  root@39.96.146.47:/root/workspace

Aihuashen2025
fumadocs-autodoc 0.0.2
Extract API documentation from source code and docstrings. For the python API extension for FumaDocs.
Requires Python: >=3.10

# Fumadocs-autodoc

Generate serialized documentation for your Python projects for use with Fumadocs.

## Usage

Install `fumadocs-autodoc`:

```bash
pip install fumadocs-autodoc
```

Then run the `fumadocs-autodoc` command with the path to your Python project:

```bash
fumadocs-autodoc name-of-package --dir path/to/output/dir
```

## Dependencies
- `griffe`
kafe2 2.11.0
Karlsruhe Fit Environment 2: a package for fitting and elementary data analysis
Requires Python: >=3.6
Keywords: kafe2, kit, karlsruhe, data, analysis, lab, laboratory, practical courses, education, university, students, physics, fitting, minimization, minimisation, regression, parametric, parameter, estimation, optimization, optimisation

.. -*- mode: rst -*-

*************************************
kafe2 - Karlsruhe Fit Environment 2
*************************************
.. image:: https://badge.fury.io/py/kafe2.svg
    :target: https://badge.fury.io/py/kafe2

.. image:: https://readthedocs.org/projects/kafe2/badge/?version=latest
    :target: https://kafe2.readthedocs.io/en/latest/?badge=latest
    :alt: Documentation Status


*kafe2* is an open-source Python package for the likelihood-based estimation of model parameters
from measured data.
As the spiritual successor to the original *kafe* package it aims to provide
state-of-the-art statistical methods in a way that is still easy to use.
More information `here <https://philfitters.github.io/kafe2/>`__.

If you have installed pip just run

.. code-block:: bash

    pip install kafe2

to install the latest stable version and you're (mostly) ready to go.
The Python package *iminuit* which *kafe2* uses internally for numerical optimization
`may fail to be installed automatically if no C++ compiler is available on your system
<https://iminuit.readthedocs.io/en/stable/install.html>`__ .
While *iminuit* is strictly speaking not required its use is heavily recommended.
**Make sure to read the pip installation log.**
As of *kafe2* v2.4.0 only Python 3 is supported.
*kafe2* works with matplotlib version 3.4 and newer.

The documentation under `kafe2.readthedocs.io <https://kafe2.readthedocs.io/>`__
has more detailed installation instructions.
It also explains *kafe2* usage as well as the mathematical foundations upon which *kafe2* is built.

If you prefer a more practical approach you can instead look at the various
`examples <https://github.com/PhiLFitters/kafe2/tree/master/examples>`__.
In addition to the regular Python/kafe2go files there are also Jupyter notebook
tutorials (in English and in German) that mostly cover the same topics.

If you encounter any bugs or have an improvement proposal, please let us
know by opening an issue `here <https://github.com/PhiLFitters/kafe2/issues>`__.
python-usernames 1.1.0
Python library to validate usernames suitable for use in public facing applications.
Requires Python: >=3.8
Keywords: regex, safe, security, signup, user registration, username, validation

# python-usernames

[![Build
Status](https://travis-ci.org/theskumar/python-usernames.svg?branch=v0.1.0)](https://travis-ci.org/theskumar/python-usernames)
[![Coverage
Status](https://coveralls.io/repos/theskumar/python-usernames/badge.svg?branch=master&service=github)](https://coveralls.io/github/theskumar/python-usernames?branch=master)
[![PyPI
version](https://badge.fury.io/py/python-usernames.svg)](http://badge.fury.io/py/python-usernames)

Python library to validate usernames suitable for use in public facing
applications where use can choose login names and sub-domains.

## Features

-   Provides a default regex validator
-   Validates against list of [banned
    words](https://github.com/theskumar/python-usernames/blob/master/usernames/reserved_words.py)
    that should not be used as username.
-   Python 3.8+

## Installation

    pip install python-usernames

## Usages

```python
from python_usernames import is_safe_username

>>> is_safe_username("jerk")
False  # contains one of the banned words

>>> is_safe_username("handsome!")
False  # contains non-url friendly `!`
```

**is\_safe\_username** takes the following optional arguments:

-   `whitelist`: a case insensitive list of words that should be
    considered as always safe. Default: `[]`
-   `blacklist`: a case insensitive list of words that should be
    considered as unsafe. Default: `[]`
-   `max_length`: specify the maximun character a username can have.
    Default: `None`

- `regex`: regular expression string that must pass before the banned
:   words is checked.

The default regular expression is as follows:

    ^                       # beginning of string
    (?!_$)                  # no only _
    (?![-.])                # no - or . at the beginning
    (?!.*[_.-]{2})          # no __ or _. or ._ or .. or -- inside
    [a-zA-Z0-9_.-]+         # allowed characters, atleast one must be present
    (?<![.-])               # no - or . at the end
    $                       # end of string

## Credits

- [The-Big-Username-Blocklist](https://github.com/marteinn/The-Big-Username-Blocklist)

## Further Reading

-   [Let’s talk about
    usernames](https://www.b-list.org/weblog/2018/feb/11/usernames/)

## Gotchas

Words like `bigcock12` will validated just fine, only equality against
the [banned word
lists](https://github.com/theskumar/python-usernames/blob/master/usernames/reserved_words.py)
is checked. We don't try to be smart to avoid [Scunthorpe
problem](https://en.wikipedia.org/wiki/Scunthorpe_problem). If you can
come up with a algorithm/solution, please create an issue/pr :).

## License

MIT
matplotlib-inline 0.2.1
Inline Matplotlib backend for Jupyter
Requires Python: >=3.9
Keywords: ipython, jupyter, matplotlib, python

# Matplotlib Inline Back-end for IPython and Jupyter

This package provides support for matplotlib to display figures directly inline in the Jupyter notebook and related clients, as shown below.

## Installation

With conda:

```bash
conda install -c conda-forge matplotlib-inline
```

With pip:

```bash
pip install matplotlib-inline
```

## Usage

Note that in current versions of JupyterLab and Jupyter Notebook, the explicit use of the `%matplotlib inline` directive is not needed anymore, though other third-party clients may still require it.

This will produce a figure immediately below:

```python
%matplotlib inline

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 3*np.pi, 500)
plt.plot(x, np.sin(x**2))
plt.title('A simple chirp');
```

## License

Licensed under the terms of the BSD 3-Clause License, by the IPython Development Team (see `LICENSE` file).
PixMClass 0.1.5
Multiclass pixel classification
Requires Python: >=3
Keywords: Segmentation, Classification, Microscopy, Cell

# Multiclass pixel classifier
Deep learning segmentation method with very low annotation requirement.

Similar to [Ilastik pixel classification](https://www.ilastik.org/documentation/pixelclassification/pixelclassification) procedure, but based on a deep neural network.

Described and used in the work [Near-infrared co-illumination of fluorescent proteins reduces photobleaching and phototoxicity](https://doi.org/10.1038/s41587-023-01893-7). Please cite this work when using this method. 

Docuementation: see this [tutorial](https://github.com/jeanollion/bacmman/wiki/Train-and-use-PixMClass)