semvec/pypi-packages huggingface dataset:
auteurismz 2.1
auteurismz
License: MIT
Keywords: SOME, MEANINGFULL, KEYWORDS

# Python library quick start
This is a minimal template for uploading your python packages to pypi.org.

## To Use
* First clone this project.
```bash
# Clone this repository
git clone https://github.com/defartsa23/python-library-quick-start.git
# Go into the repository
cd python-library-quick-start
```
* Rename the folder `your-package` to the package name you want. then place all your files into a folder. Open the `__init__.py` file with a text editor of your choice. In this file, you write nothing but the import statement which has the following schema:
```python
from .Filename import Classname
```
* Replace the information in the `setup.py` file with the matching content.
* Upload your package to PyPi
```sh
python setup.py sdist
twine upload dist/*
```
cheatsheetify 0.1.2
cheatsheetify is a command-line tool that generates PDF versions of cheatsheets for popular command-line tools
License: MIT
Requires Python: <4.0,>=3.10

<h1 align="center">Cheatsheetify</h1>

<p align="center">
<img alt="PyPI - Version" src="https://img.shields.io/pypi/v/cheatsheetify?style=for-the-badge&labelColor=%23363a4f&color=%23f5a97f&link=https%3A%2F%2Fpypi.org%2Fproject%2Fcheatsheetify%2F">
<img alt="GitHub Actions Workflow Status" src="https://img.shields.io/github/actions/workflow/status/HYP3R00T/Cheatsheetify/pypi_publish.yml?style=for-the-badge&labelColor=%23363a4f&color=%238aadf4">
</p>

cheatsheetify is a command-line tool that generates PDF versions of cheatsheets for popular command-line tools.

Documentation: [cheatsheetify.hyperoot.dev](https://cheatsheetify.hyperoot.dev/)

## Features

- Generates PDF cheatsheets for popular command-line tools.
- Easy to use with a simple command-line interface.
- Customizable output options.
- Custom themes for the PDFs

## Installation

To install cheatsheetify, you can use pip:

```sh
pip install cheatsheetify
```

## Usage

```sh
python cheatsheetify <list of commands>
```

For example, to generate a cheatsheet for `ls cp rm`, you would run:

```sh
python cheatsheetify ls cp rm
```

The generated PDF cheatsheet will be saved in the current directory. Read the [documentation](https://cheatsheetify.hyperoot.dev/) to learn more about the avialable customizations.

## Credits

This project would not have been possible without the awesome [tldr](https://tldr.sh/) project.

## Contributing

Contributions are welcome! If you'd like to add support for a new command-line tool or improve an existing cheatsheet, feel free to open a pull request.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
causalimpact-return 0.0.0
Python Package for causal inference using Bayesian structural time-series models with data returned..
License: MIT
Requires Python: >=2.6

## CausalImpact

[![Python package](https://github.com/jamalsenouci/causalimpact/actions/workflows/main.yml/badge.svg)](https://github.com/jamalsenouci/causalimpact/actions/workflows/main.yml)
[![codecov](https://codecov.io/gh/jamalsenouci/causalimpact/branch/master/graph/badge.svg?token=EIPC36VQHS)](https://codecov.io/gh/jamalsenouci/causalimpact)
![monthly downloads](https://pepy.tech/badge/causalimpact/month)
[![DeepSource](https://deepsource.io/gh/jamalsenouci/causalimpact.svg/?label=active+issues&show_trend=true&token=R5aIDSkIId_5THWTAPKccjcH)](https://deepsource.io/gh/jamalsenouci/causalimpact/?ref=repository-badge)

#### A Python package for causal inference using Bayesian structural time-series models

This is a port of the R package CausalImpact, see: https://github.com/google/CausalImpact.

This package implements an approach to estimating the causal effect of a designed intervention on a time series. For example, how many additional daily clicks were generated by an advertising campaign? Answering a question like this can be difficult when a randomized experiment is not available. The package aims to address this difficulty using a structural Bayesian time-series model to estimate how the response metric might have evolved after the intervention if the intervention had not occurred.

As with all approaches to causal inference on non-experimental data, valid conclusions require strong assumptions. The CausalImpact package, in particular, assumes that the outcome time series can be explained in terms of a set of control time series that were themselves not affected by the intervention. Furthermore, the relation between treated series and control series is assumed to be stable during the post-intervention period. Understanding and checking these assumptions for any given application is critical for obtaining valid conclusions.

#### Try it out in the browser

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/jamalsenouci/causalimpact/HEAD?labpath=GettingStarted.ipynb)

#### Installation

install the latest release via pip

```bash
pip install causalimpact
```

#### Getting started

[Documentation and examples](https://nbviewer.org/github/jamalsenouci/causalimpact/blob/master/GettingStarted.ipynb)

#### Further resources

- Manuscript: [Brodersen et al., Annals of Applied Statistics (2015)](http://research.google.com/pubs/pub41854.html)

#### Bugs

The issue tracker is at https://github.com/jamalsenouci/causalimpact/issues. Please report any bugs that you find. Or, even better, fork the repository on GitHub and create a pull request.
oxeyesz 1.1
oxeyesz
License: MIT
Keywords: SOME, MEANINGFULL, KEYWORDS

# Python library quick start
This is a minimal template for uploading your python packages to pypi.org.

## To Use
* First clone this project.
```bash
# Clone this repository
git clone https://github.com/defartsa23/python-library-quick-start.git
# Go into the repository
cd python-library-quick-start
```
* Rename the folder `your-package` to the package name you want. then place all your files into a folder. Open the `__init__.py` file with a text editor of your choice. In this file, you write nothing but the import statement which has the following schema:
```python
from .Filename import Classname
```
* Replace the information in the `setup.py` file with the matching content.
* Upload your package to PyPi
```sh
python setup.py sdist
twine upload dist/*
```
ascianz 2.1
ascianz
License: MIT
Keywords: SOME, MEANINGFULL, KEYWORDS

# Python library quick start
This is a minimal template for uploading your python packages to pypi.org.

## To Use
* First clone this project.
```bash
# Clone this repository
git clone https://github.com/defartsa23/python-library-quick-start.git
# Go into the repository
cd python-library-quick-start
```
* Rename the folder `your-package` to the package name you want. then place all your files into a folder. Open the `__init__.py` file with a text editor of your choice. In this file, you write nothing but the import statement which has the following schema:
```python
from .Filename import Classname
```
* Replace the information in the `setup.py` file with the matching content.
* Upload your package to PyPi
```sh
python setup.py sdist
twine upload dist/*
```
create-flask-package 0.1.6
A CLI tool for generating Flask web application scaffolding.
License: MIT

Package Description:

create-flask-package is a Python package that provides a command line interface (CLI) tool for generating a scaffold for a Flask web application. With this package, developers can quickly create the basic structure of a Flask project including directories, files, and boilerplate code, allowing them to focus on building their web application logic.

Required Libraries:

The create-flask-package package requires the following Python libraries:

Flask: Flask is a lightweight WSGI web application framework for Python. It provides tools and libraries for building web applications in Python, making it easy to create web APIs, web services, and dynamic web pages.
Flask-SQLAlchemy: Flask-SQLAlchemy is an extension for Flask that adds support for SQLAlchemy, a powerful SQL toolkit and Object-Relational Mapping (ORM) library for Python. Flask-SQLAlchemy simplifies database operations in Flask applications, allowing developers to work with relational databases using high-level Python constructs.
Flask-CORS: Flask-CORS is a Flask extension that adds Cross-Origin Resource Sharing (CORS) support to Flask applications. CORS is a security feature implemented by web browsers to prevent cross-origin requests, and Flask-CORS provides middleware for handling CORS requests in Flask applications.
Flask-Login: Flask-Login is an extension for Flask that provides user session management and authentication support. It simplifies the process of managing user sessions and authenticating users in Flask applications, making it easy to implement user authentication and access control.
Flask-Session: Flask-Session is an extension for Flask that adds support for server-side session management in Flask applications. It provides tools for storing and accessing session data in Flask applications, allowing developers to manage user sessions securely.
These libraries are essential for building Flask web applications and are included as dependencies of the create-flask-package package to ensure compatibility and ease of use for developers.

USE:


After Installation, just write "create-flask-package" in the CMD and write the package name you want to, and thats it
nutils-poly 1.0.1
Low-level functions for evaluating and manipulating polynomials (Python bindings)
License: MIT
Requires Python: >=3.8

Low-level functions for evaluating and manipulating polynomials.

# Examples

The vector of coefficients for the polynomial `f(x, y) = 3 x y + x^2` is
`[0, 3, 0, 1, 0, 0]`.

With `eval()` we can evaluate this polynomial:

```python
import nutils_poly
import numpy

coeffs = numpy.array([0, 3, 0, 1, 0, 0], dtype=float)
# array of three `x` and `y` pairs (last axis)
values = numpy.array([[1, 0], [1, 1], [2, 3]], dtype=float)
numpy.testing.assert_allclose(nutils_poly.eval(coeffs, values), [1, 4, 22])
```

`PartialDerivPlan::apply()` computes the coefficients for the partial
derivative of a polynomial to one of the variables. The partial derivative
of `f` to `x`, the first variable, is `∂_x f(x, y) = 3 y + 2 x`
(coefficients: `[3, 2, 0]`):

```python
import nutils_poly
import numpy

coeffs = numpy.array([0, 3, 0, 1, 0, 0], dtype=float)
pd = nutils_poly.PartialDerivPlan(
    2, # number of variables
    2, # degree
    0, # variable to compute the partial derivative to
)
numpy.testing.assert_allclose(pd(coeffs), [3, 2, 0])
```

# Further reading

This package is a Python interface for the Rust crate
[`nutils-poly`][crate:nutils-poly] using [PyO3].

This package is part of the [Nutils project].

[crate:nutils-poly]: https://crates.io/crates/nutils-poly
[PyO3]: https://pyo3.rs
[Nutils project]: https://nutils.org
somersetsz 1.1
somersetsz
License: MIT
Keywords: SOME, MEANINGFULL, KEYWORDS

# Python library quick start
This is a minimal template for uploading your python packages to pypi.org.

## To Use
* First clone this project.
```bash
# Clone this repository
git clone https://github.com/defartsa23/python-library-quick-start.git
# Go into the repository
cd python-library-quick-start
```
* Rename the folder `your-package` to the package name you want. then place all your files into a folder. Open the `__init__.py` file with a text editor of your choice. In this file, you write nothing but the import statement which has the following schema:
```python
from .Filename import Classname
```
* Replace the information in the `setup.py` file with the matching content.
* Upload your package to PyPi
```sh
python setup.py sdist
twine upload dist/*
```
arylz 2.1
arylz
License: MIT
Keywords: SOME, MEANINGFULL, KEYWORDS

# Python library quick start
This is a minimal template for uploading your python packages to pypi.org.

## To Use
* First clone this project.
```bash
# Clone this repository
git clone https://github.com/defartsa23/python-library-quick-start.git
# Go into the repository
cd python-library-quick-start
```
* Rename the folder `your-package` to the package name you want. then place all your files into a folder. Open the `__init__.py` file with a text editor of your choice. In this file, you write nothing but the import statement which has the following schema:
```python
from .Filename import Classname
```
* Replace the information in the `setup.py` file with the matching content.
* Upload your package to PyPi
```sh
python setup.py sdist
twine upload dist/*
```
nonfugitivelyz 1.1
nonfugitivelyz
License: MIT
Keywords: SOME, MEANINGFULL, KEYWORDS

# Python library quick start
This is a minimal template for uploading your python packages to pypi.org.

## To Use
* First clone this project.
```bash
# Clone this repository
git clone https://github.com/defartsa23/python-library-quick-start.git
# Go into the repository
cd python-library-quick-start
```
* Rename the folder `your-package` to the package name you want. then place all your files into a folder. Open the `__init__.py` file with a text editor of your choice. In this file, you write nothing but the import statement which has the following schema:
```python
from .Filename import Classname
```
* Replace the information in the `setup.py` file with the matching content.
* Upload your package to PyPi
```sh
python setup.py sdist
twine upload dist/*
```
armhoopz 2.1
armhoopz
License: MIT
Keywords: SOME, MEANINGFULL, KEYWORDS

# Python library quick start
This is a minimal template for uploading your python packages to pypi.org.

## To Use
* First clone this project.
```bash
# Clone this repository
git clone https://github.com/defartsa23/python-library-quick-start.git
# Go into the repository
cd python-library-quick-start
```
* Rename the folder `your-package` to the package name you want. then place all your files into a folder. Open the `__init__.py` file with a text editor of your choice. In this file, you write nothing but the import statement which has the following schema:
```python
from .Filename import Classname
```
* Replace the information in the `setup.py` file with the matching content.
* Upload your package to PyPi
```sh
python setup.py sdist
twine upload dist/*
```
latinicz 1.1
latinicz
License: MIT
Keywords: SOME, MEANINGFULL, KEYWORDS

# Python library quick start
This is a minimal template for uploading your python packages to pypi.org.

## To Use
* First clone this project.
```bash
# Clone this repository
git clone https://github.com/defartsa23/python-library-quick-start.git
# Go into the repository
cd python-library-quick-start
```
* Rename the folder `your-package` to the package name you want. then place all your files into a folder. Open the `__init__.py` file with a text editor of your choice. In this file, you write nothing but the import statement which has the following schema:
```python
from .Filename import Classname
```
* Replace the information in the `setup.py` file with the matching content.
* Upload your package to PyPi
```sh
python setup.py sdist
twine upload dist/*
```
araucanianz 2.1
araucanianz
License: MIT
Keywords: SOME, MEANINGFULL, KEYWORDS

# Python library quick start
This is a minimal template for uploading your python packages to pypi.org.

## To Use
* First clone this project.
```bash
# Clone this repository
git clone https://github.com/defartsa23/python-library-quick-start.git
# Go into the repository
cd python-library-quick-start
```
* Rename the folder `your-package` to the package name you want. then place all your files into a folder. Open the `__init__.py` file with a text editor of your choice. In this file, you write nothing but the import statement which has the following schema:
```python
from .Filename import Classname
```
* Replace the information in the `setup.py` file with the matching content.
* Upload your package to PyPi
```sh
python setup.py sdist
twine upload dist/*
```