semvec/pypi-packages huggingface dataset:
singer-summarize 0.0.1a6
Singer target that summarizes a tap's output
License: MIT
Requires Python: >=3.7
Keywords: singer.io,target

# singer-summarize

A POC Singer target that summarizes a tap's output.

## Installation

### From PyPI

I recommend using [pipx](https://pypa.github.io/pipx/) to install this package:

```shell
pipx install singer-summarize
```

## Build

### Binary

```shell
cargo build -p singer_summarize --release
```

This will create a binary at `target/release/singer-summarize`.

### Python

```shell
maturin build --release
```

This will create a Python wheel at `target/wheels/`.

## Usage

Copy the binary to your `PATH`:

```shell
cp target/release/singer-summarize ~/.local/bin
```

Test it with a Singer tap:

```console
$ tap-exchangeratesapi -c config.json | singer-summarize
{
  "streams": {
    "exchange_rate": {
      "schema": 1,
      "record": 100,
      "activate_version": 0,
      "batch": 0
    }
  },
  "state": {
    "count": 1,
    "last_seen": {
        "start_date": "2020-01-01",
    }
  }
}
```
model-serializer 1.0.3
A simple Python package for serializing and deserializing Python objects to and from JSON.
License: MIT
Requires Python: >=3.9

# Model Serializer and Directory Tree Builder

This is a Python package that includes: ModelSerializer and DirectoryTreeBuilder. The package is designed to provide serialization and deserialization capabilities for Python objects, as well as the ability to create a tree structure representing the directory and file hierarchy of a specified directory.

## ModelSerializer

The ModelSerializer class is used to serialize Python objects into JSON format and deserialize JSON strings back into Python objects. It provides the following methods:

```python
__init__(self, model=None)
```
where `model`: The model object to serialize.

**[1.A]** Initialize the ModelSerializer with a model object.

```python
to_json(self, model=None)
```

**[1.B]** Serialize the model object to JSON.

where `model`: (optional) If provided, **[2.A]** serialize the specified model object, otherwise, **[2.B]** use the object provided during initialization.

```python
serialize_model(self, obj)
```
where `obj`: The object to be serialized.

**[3]** Recursively serialize a Python object into a JSON-serializable format.

```python
from_json(json_str)
```
where `json_str`: The JSON string to deserialize.

**[4]** Deserialize a JSON string into a Python object.

## DirectoryTreeBuilder

The DirectoryTreeBuilder class is used to create a tree structure that represents the directory and file hierarchy of a specified directory. It provides the following methods:

```python
__init__(self, root_path)
```
where `root_path`: The path to the root directory to build the tree from.

**[1]** Initialize the DirectoryTreeBuilder with a root directory path.

```python
build_tree(self)
```
_Returns:_ A dictionary representing the directory and file hierarchy.

**[2]** Recursively construct a tree structure for the specified directory.

```python
to_json(self)
```
_Returns:_ JSON representation of the directory tree.

**[3]** Serialize the directory tree to JSON format.

## Example Usage

Here's an example of how to use these classes:

```python
from model_serializer import ModelSerializer
from directory_tree_builder import DirectoryTreeBuilder

# Example for ModelSerializer
data = {"name": "John", "age": 30, "city": "New York"}
serializer = ModelSerializer(data)
json_data = serializer.to_json()

# Example for DirectoryTreeBuilder
root_directory = '/path/to/root/directory'
tree_builder = DirectoryTreeBuilder(root_directory)
directory_tree_json = tree_builder.to_json()
```

To install this package from PyPI, you can use pip:

```python
pip install model-serializer
```


# License

This package is distributed under the MIT License. Feel free to use it in your projects and contribute to its development on GitHub.

# Author

Made with ❤️ by Olger Chotza in Thessaloniki, Greece.

If you encounter any issues, have questions, or want to contribute to the development of this package, please visit the GitHub repository and create an issue or pull request.

Thank you for using the Model Serializer and Directory Tree Builder package!
pypi-github-helper 0.1.5
a template for build python package
License: MIT
Requires Python: >=3.8,<4.0

# pypi-template
a template for build python package to upload pypi repository


```bash

ppoetry install
poetry run dev

```

## git
```bash
change pyproject.toml file   --    version = "0.1.5"

git add .
git commit -m "change readme"
git tag v0.1.5 -m "release v0.1.5"
git push origin v0.1.5

```
aprendepython 1.0.1
Librería interactiva para aprender los fundamentos de Python
License: MIT
Requires Python: >=3.7
Keywords: python,curso,fundamentos

# aprendepython

Librería de código abierto diseñada para enseñar los fundamentos del lenguaje
Python.

## Contenido

El curso se centra en temas básicos de Python, insipirado en el contenido de la
sección _Learn the Basics_ de [learnpython.org](https://learnpython.org/)

Los temas incluyen:

- Variables y tipos de datos
- Operadores aritméticos, relacionales y lógicos
- Condicionales
- Ciclos
- Funciones
- Clases y objetos

## Instalación

Para utilizar aprendepython es necesario contar con Python 3.7 o superior
instalado en el sistema. Después, instala la librería utilizando pip con el
siguiente comando:

```sh
pip install aprendepython
```

> Nota: Se puede utilizar entornos virtuales en caso de haber problemas con la
> instalación global. Para más información sobre entornos virtuales visita
> [Creación de entornos virtuales](https://docs.python.org/3/library/venv.html).

## Uso

Para comenzar a usar el curso interactivo, solo necesitas importar la librería
en un entorno de Python y llamar la función `comenzar()`:

```python
import aprendepython

aprendepython.comenzar()
```

Al iniciar el curso por primera vez se mostrará una introducción que indica la
forma de interactuar con las lecciones y navegar por el menú.

## Contribuciones

Las contribuciones de la comunidad son valoradas y bienvenidas, ya sea para
mejorar el contenido del curso o integrar mejoras al código. Si deseas colaborar
en el desarrollo, puedes seguir estos pasos:

1. Realiza un fork del proyecto.
2. Realiza cambios en el código o las lecciones.
3. Haz un pull request a este proyecto para revisar los cambios e integrar tus
   contribuciones.

## Licencia

Este proyecto se distribuye bajo la licencia MIT, indicando que es de código
abierto y que puede utilizarse libremente en otros proyectos. Para más detalles,
consulta el archivo [LICENSE](LICENSE).
MoNeT-MGDrivE 0.9.1.1
MoNeT python package for MGDrivE data analysis
License: MIT


This module was created to accompany the [MGDrivE](https://marshalllab.github.io/MGDrivE/) and [MoNeT](https://chipdelmal.github.io/MoNeT/) projects to make the analysis of the spatiotemporal simulations of gene-drive spreads as seamless as possible.

It is also meant to serve as a platform to ensure the reproducibility of results of the publications from our [research group at UC, Berkeley](https://www.marshalllab.com/), as part of [DARPA's: Safe Genes program](https://www.darpa.mil/program/safe-genes) and [UCI Malaria  Initiative](http://malaria.bio.uci.edu/).

<hr>

##  Project Status

Our code has been used and tested in several [MGDrivE](https://marshalllab.github.io/MGDrivE/) publications. For some examples of how this package is being currently used, please follow this [link](https://chipdelmal.github.io/MoNeT/Berkeley.html).

<hr>

##  Installation

To install from pypi with pip:

```bash
pip install MoNeT-MGDrivE
```

<hr>

##  Authors

* __Lead__: [Héctor M. Sánchez C](https://chipdelmal.github.io/)
* __Former Dev__: Chris De León, Priscilla Zhang, Sabrina Wong, Sarafina Smith, Víctor Ferman, Biyonka Liang, Gillian Chu, Maya Shen
* __PI__: [John M. Marshall](https://www.marshalllab.com/)
lrclibapi 0.3.1
python wrapper for the lrclib.net api
License: MIT
Requires Python: >=3.8.10,<4.0.0
Keywords: lrclib,lrclib.net,lrclib.net api,lrclib.net python,lrclib.net python api,lrclib.net python wrapper,synced lyrics,synced lyrics api,synced lyrics python

# LRCLibAPI

Python Wrapper for [lrclib.net](https://lrclib.net/) api to get synced lyrics.

<p>
  <a href="https://pypi.org/project/lrclibapi/">
    <img src="https://img.shields.io/pypi/v/lrclibapi?color=darkblue" alt="Stable Version">
  </a>
  <a href="https://pypistats.org/packages/lrclibapi">
    <img src="https://img.shields.io/pypi/dm/lrclibapi?color=teal" alt="Downloads">
  </a>
  <a href="https://github.com/Dr-Blank/lrclibapi/actions">
    <img src="https://github.com/Dr-Blank/lrclibapi/actions/workflows/tests.yaml/badge.svg" alt="Test">
  </a>
  <a href="https://codecov.io/gh/Dr-Blank/lrclibapi" > 
    <img src="https://codecov.io/gh/Dr-Blank/lrclibapi/graph/badge.svg"/> 
  </a>
  <a href='https://lrclibapi.readthedocs.io/en/latest/?badge=latest'>
    <img src='https://readthedocs.org/projects/lrclibapi/badge/?version=latest' alt='Documentation Status' />
  </a>
  <a href="https://github.com/psf/black">
    <img src="https://img.shields.io/badge/code%20style-black-000000.svg" alt="Code style: black">
  </a>
  <a href="https://mypy-lang.org/">
    <img src="https://www.mypy-lang.org/static/mypy_badge.svg" alt="Checked with mypy">
  </a>
</p>

## Installation

```bash
pip install lrclibapi
```

## Usage

See [Documentation](https://lrclibapi.readthedocs.io/en/latest/) for more details.
python-docx-ml6 1.0.2
Create, read, and update Microsoft Word .docx files. This is a fork from the original library that includes feature requests that have been provided by the open source community but have not yet been merged in the original package.
License: MIT
Requires Python: >=3.7
Keywords: docx,office,openxml,word

# python-docx

This package is a fork from the original `python-docx`. It includes feature requests that are yet to be merged in the original one.
*python-docx* is a Python library for reading, creating, and updating Microsoft Word 2007+ (.docx) files.

## Installation

```
pip install python-docx-ml6
```

## Example

```python
>>> from docx import Document

>>> document = Document()
>>> document.add_paragraph("It was a dark and stormy night.")
<docx.text.paragraph.Paragraph object at 0x10f19e760>
>>> document.save("dark-and-stormy.docx")

>>> document = Document("dark-and-stormy.docx")
>>> document.paragraphs[0].text
'It was a dark and stormy night.'
```

More information is available in the [python-docx documentation](https://python-docx.readthedocs.org/en/latest/)
dolomite-schemas 0.0.8
JSON schemas for bioconductor objects.
License: MIT

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# Bioconductor object schemas for Python

## Overview

This package vendors the [Bioconductor object schemas](https://github.com/ArtifactDB/BiocObjectSchemas) for the **dolomite-** Python packages.
The idea is to ensure that downstream packages have consistent access to schemas without the need for a remote look-up.
We put this in a separate package so that schema updates are kept separate from actual programming changes.

## Installation

Developers can install the package through `pip`.

```sh
pip install dolomite-schemas
```

## Usage

Schemas are vendored into the `schemas/` subdirectory in the installation directory.
This directory can be easily found by working back from the **dolomite-schemas** module location:

```python
import dolomite_schemas
os.path.join(os.path.dirname(dolomite_schemas.__file__), "schemas")
```

Application-specific schema-vendoring modules should use the same relative location for their schema subdirectory in the installation directory.

## Developer notes

The schemas are not actually committed to this repository, but are instead obtained by running:

```shell
cd extern && ./fetch.sh
```

This can be modified to point to any relevant version of the schemas.