semvec/pypi-packages huggingface dataset:
sphinxcontrib-d2lang 0.0.5
an extension for sphinx to render d2lang diagrams in sphinx documents
Requires Python: >=3.8

# sphinxcontrib-d2lang

This is a Sphinx extension for [d2lang](https://d2lang.com/). 

## Usage

### Install

```bash
$ pip install sphinxcontrib-d2lang
```

### Adding the extension

`conf.py`

```python
extensions = [
    "sphinxcontrib.d2lang",
]
```

### Adding a diagram (inline)

You can use d2lang in sphinx directive

`source/index.rst`

```
Hello World
===========

.. d2lang::

    hello -> world
```


### Adding a diagram (external file)

You can use an external file like this

```
Hello World
===========

.. d2lang:: helloworld.d2

```

### Options

There is two options you can use

- layout
- filename

#### Layout engine

You can specify layout engine to use

```rest
Hello World
===========

.. d2lang::
   :layout: elk

    hello -> world
```

#### Output filename

```rest
Hello World
===========

.. d2lang::
   :filename: d2lang_files/helloworld.svg

    hello -> world
```
code-complexity-checker 0.1.10
A simple Python tool to calculate code complexity.
Requires Python: >=3.7

# Code Complexity Checker

[![PyPI](https://img.shields.io/pypi/v/code-complexity-checker.svg)](https://pypi.org/project/code-complexity-checker/)
[![Python](https://img.shields.io/badge/python-3.7%2B-blue)](https://www.python.org/)
[![License](https://img.shields.io/badge/license-MIT-green)](LICENSE)

A lightweight Python tool that **analyzes the complexity** of your code using [Radon](https://radon.readthedocs.io/) . Quickly check function complexity, detect high-complexity areas, and improve your code quality! 

## Features
- **Analyze Cyclomatic Complexity** of Python functions & classes  
- **Generate JSON Reports** with detailed complexity insights  
- **Command-Line Interface (CLI)** for quick execution  
- **Lightweight & Easy to Use**  
- **Supports Python 3.7+**

## Installation
Install the package using `pip`:
```bash
pip install code-complexity-checker
```

## Usage
Analyze a Python file:
```bash
!code-checker --file example.py
```
This will output something like:
```bash
[
    {"function": "calculate_factorial", "complexity": 3, "lineno": 5},
    {"function": "fibonacci", "complexity": 4, "lineno": 12}
]
```

## How It Works

1. Reads the Python file
2. Uses **Radon's `ComplexityVisitor`** to analyze function/class complexity
3. Outputs a structured JSON report with function names & their complexity scores


## Why Use This?

- Helps you **identify complex functions** early  
- Makes code **easier to maintain & optimize**  
- Great for **code reviews & refactoring** 

## Contributing
Contributions are welcome! Follow these steps to contribute:

1. Fork the repository on [GitHub](https://github.com/sneha30404/code-complexity-checker).
2. Clone your fork:
   ```bash
   git clone https://github.com/sneha30404/code-complexity-checker.git
    ```
3. Create a new branch for your feature
    ```bash
    git checkout -b feature-name
    ```
4. Make your changes and commit them:
    ```bash
    git commit -m "Add feature-name"
    ```
5. Push to your branch:
    ```bash
    git push origin feature-name
    ```
6. Submit a Pull Request.


## Links

- **PyPI:** [Code Complexity Checker](https://pypi.org/project/code-complexity-checker/)  
- **GitHub:** [Source Code](https://github.com/sneha30404/code-complexity-checker/)  
- **Radon Docs:** [Radon Library](https://radon.readthedocs.io/)  

---

## License

This project is licensed under the **MIT License**.

---

**Happy Coding!**
cassyy 0.0.9
Simple Apereo Central Authentication Service (CAS) client
Requires Python: >=3.11
Keywords: Authentication, SSO, CAS

# cassyy

A simple Apereo Central Authentication Service (CAS) client that provides basic
support for validating service tickets using CAS Protocols 2/3. It uses the
Python standard library `urllib.request` module and has no external
dependencies.

# Usage

Below provides just an example of how it might be used in a web
application. The example is generic and does not represent any specific web
framework. It is up to the application to decide what `service_url` it will
use with the `build_login_url` method. It is common to use the current request
url or a fixed url that CAS will redirect the user to after the login is
successful along with a `ticket` that can be validated to retrieve information
about the user.

```python
import cassyy

cas_client = cassyy.CASClient.from_base_url('https://cas.example.org')

def login_route(request, response):
    redirect_url = ...
    target_url = cas_client.build_login_url(redirect_url)
    response.redirect(target_url)

# This could be a route or some authentication middleware that intercepts
# unauthenticated requests and redirects to CAS and/or validates a CAS ticket
# if one is included in the request.
def validate_route(request, response):
    ticket = ...  # pull from request
    service_url = ...
    cas_user = cas_client.validate(service_url, ticket)
    request.session['user'] = cas_user.asdict()

def logout_route(request, response):
    # where to have CAS redirect back to the app after the CAS logout occurs,
    # or None to use the CAS logout page
    service_url = ...
    target_url = cas_client.build_logout_url(service_url)
    response.redirect(target_url)
```
TCPYLib 0.3.0
A collection of utilities and functions for various tasks.
Requires Python: >=3.6

# TCPYLib

The `TCPYLib` module is a collection of utilities and functions designed to support various tasks in the project. Below is an overview of the submodules and their functionalities.

## Submodules

### `lib.cli`

- **arguments.py**
  - `add_arg(parser: ArgumentParser, name: str, help_text: str, default: str | None = None, action: str | None = None, required: bool = False) -> None`
  - `parse_args(parser: ArgumentParser) -> dict[str, str]`
- **shell.py**
  - `clear_console()`
  - `run_command(cmd)`

### `lib.config`

- **config.json**
  - Configuration file containing logging settings and paths.
- **loader.py**
  - `load_config() -> dict`
  - `CONFIG: dict`

### `lib.core`

- **parser.py**
  - `parse_custom_time(time_str: str)`
- **time.py**
  - `get_timestamp()`
  - `format_date(date: datetime, fmt: str = "%Y-%m-%d %H:%M:%S")`

### `lib.logger`

- **logger.py**
  - `Logger`
    - `debug(self, msg: str) -> None`
    - `info(self, msg: str) -> None`
    - `warn(self, msg: str) -> None`
    - `error(self, msg: str) -> None`
    - `critical(self, msg: str, exit: bool = False, exit_code: int = 0) -> None`

### `lib.math`

- **advanced.py**
  - `clamp(value, min_value, max_value)`
- **random.py**
  - `random_string(length=10)`

### `lib.network`

- **ip.py**
  - `get_ip()`
  - `ping(host: str)`

### `lib.screens`

- **download.py**
  - `run_download_screen(...)`
- **error.py**
  - `run_error_screen(...)`
- **info.py**
  - `run_info_screen(...)`
- **warn.py**
  - `run_warn_screen(...)`

### `lib.startup`

- **functions.py**
  - `clean_pycaches(root_dir, show: bool = False)`
  - `check_environment()`
  - `backup_config()`
  - `pre_tasks()`
  - `log_performance(execution_time)`
  - `cleanup_resources()`
  - `post_tasks(execution_time)`

### `lib.utils`

- **file_ops.py**
  - `create_folder(path)`
  - `delete_folder(path)`
  - `read_file(file_path)`
  - `write_file(file_path, content)`
  - `append_file(file_path, content)`
  - `delete_file(file_path)`
- **passwords.py**
  - `input_pwsd(prompt: str, mask: str = "*") -> str`
  - `hash_password(password: str, salt: str = "") -> str`
  - `generate_password(length: int = 12, use_digits: bool = True, use_special: bool = True) -> str`
  - `strong_password_check(password: str, min_length: int = 8) -> bool`
- **decorators.py**
  - `deactive(reason="Diese Funktion ist deaktiviert.")`

## License

This project is licensed under the MIT License - see the [LICENSE](data/LICENSE) file for details.
qtl-power 0.5.0b0
"Power calculations for GWAS study design."
Requires Python: >=3.9
Keywords: genetics, GWAS


[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/aabiddanda/qtl-power/HEAD) [![Read the Docs](https://img.shields.io/readthedocs/qtl-power)](https://aabiddanda.github.io/qtl-power/)

# Power Calculation Routines for GWAS Study Design

This is a library to quickly calculate power curves for the expected detected effect in Genome-Wide Association Studies.

## Installation

If you are interested in installing this package for direct use within scripts or notebooks, please run:

```
pip install qtl-power
```

## Interactive Exploration via Notebooks

If you are primarily interested in a more interactive experience, you can immediately use several of our pre-built notebooks via the [`mybinder`](https://mybinder.org/v2/gl/data-analysis5%2Fqtl-power/default?labpath=notebooks%2F) link above. This will allow you to use the library to generate commonly used plots for comparing power for genetic association based on mutliple input parameters.

## Documentation

Currently the documentaton is held in the `/docs` directory and is built using [`Sphinx`](https://www.sphinx-doc.org/en/master/). To rebuild the documentation:

```
cd docsrc
make clean html copy
cd ..
git add docs/
```

then create a commit that will create an updated set of documentation.

## References

* Matti Pirinen [(GWAS Course Notes)](https://www.mv.helsinki.fi/home/mjxpirin/GWAS_course/material/GWAS3.html)
* Andriy Derkach, Haoyu Zhang, Nilanjan Chatterjee, Power Analysis for Genetic Association Test (PAGEANT) provides insights to challenges for rare variant association studies, Bioinformatics, Volume 34, Issue 9, 01 May 2018, Pages 1506–1513, [https://doi.org/10.1093/bioinformatics/btx770](https://doi.org/10.1093/bioinformatics/btx770)
* Jennifer Li Johnson, Goncalo Abecasis [GAS Calculator](https://github.com/jenlij/GAS-power-calculator/blob/master/equations_gas_power_calc.pdf)
bluesky-navdata 1.0.0
Navigation data files for the BlueSky Open ATM Simulator
Requires Python: >=3.10
Keywords: ATM, aircraft, aviation, simulation, transport

# BlueSky Navdata - Navigation data for the Open Air Traffic Simulator
BlueSky is meant as a tool to perform research on Air Traffic Management and Air Traffic Flows, and is distributed under the GNU General Public License v3.

The goal of BlueSky is to provide everybody who wants to visualize, analyze or simulate air
traffic with a tool to do so without any restrictions, licenses or limitations. It can be copied,
modified, cited, etc. without any limitations.

**Citation info:** J. M. Hoekstra and J. Ellerbroek, "[BlueSky ATC Simulator Project: an Open Data and Open Source Approach](https://www.researchgate.net/publication/304490055_BlueSky_ATC_Simulator_Project_an_Open_Data_and_Open_Source_Approach)", Proceedings of the seventh International Conference for Research on Air Transport (ICRAT), 2016.

## BlueSky Releases
BlueSky is also available as a pip package, for which periodically version releases are made. You can find the latest release here:
https://github.com/TUDelft-CNS-ATM/bluesky/releases
The BlueSky pip package is installed with the following command:

    pip install bluesky-simulator[full]

Using ZSH? Add quotes around the package name: `"bluesky-simulator[full]"`. For more installation instructions go to the Wiki.

## BlueSky Wiki
Installation and user guides are accessible at:
https://github.com/TUDelft-CNS-ATM/bluesky/wiki
bluesky-guidata 1.0.1
Resources for the BlueSky Open ATM Simulator GUI
Requires Python: >=3.10
Keywords: ATM, aircraft, aviation, simulation, transport

# BlueSky GUIData - Graphics data for the Open Air Traffic Simulator
BlueSky is meant as a tool to perform research on Air Traffic Management and Air Traffic Flows, and is distributed under the GNU General Public License v3.

The goal of BlueSky is to provide everybody who wants to visualize, analyze or simulate air
traffic with a tool to do so without any restrictions, licenses or limitations. It can be copied,
modified, cited, etc. without any limitations.

**Citation info:** J. M. Hoekstra and J. Ellerbroek, "[BlueSky ATC Simulator Project: an Open Data and Open Source Approach](https://www.researchgate.net/publication/304490055_BlueSky_ATC_Simulator_Project_an_Open_Data_and_Open_Source_Approach)", Proceedings of the seventh International Conference for Research on Air Transport (ICRAT), 2016.

## BlueSky Releases
BlueSky is also available as a pip package, for which periodically version releases are made. You can find the latest release here:
https://github.com/TUDelft-CNS-ATM/bluesky/releases
The BlueSky pip package is installed with the following command:

    pip install bluesky-simulator[full]

Using ZSH? Add quotes around the package name: `"bluesky-simulator[full]"`. For more installation instructions go to the Wiki.

## BlueSky Wiki
Installation and user guides are accessible at:
https://github.com/TUDelft-CNS-ATM/bluesky/wiki
letterboxd-stats 0.2.18
Get information about your Letterboxd activity.
Requires Python: >=3.8

# Letterboxd Stats

![](./example.gif)

Get information about your Letterboxd activity.

Search for actors/directors, analyze your diary/watchlist/rating, check which film you have seen for a particular person. All in your terminal.

## Requirements

-   Python >= 3.8
-   A [TMDb API key](https://www.themoviedb.org/documentation/api): to retrieve all the general information for movies/people
-   A Letterboxd account: to export your Letterboxd activity through web-scraping.

## Installation

Just run:

```shell
pip3 install letterboxd_stats
```

## Configuration

It is required to create a `config.toml`. You can create it in the default config folder (for example, `.config/letterboxd_stats` in Linux) or specify your custom folder with the `-c` command. For each platform, default config folder follows the structure of the [platformdirs](https://github.com/platformdirs/platformdirs) package.

```toml
# Where you want the .csv file of your Letterboxd activity to be saved.
root_folder = "~/Documents/letterboxd_stats/"

[CLI]
# The size of the ASCII art poster printed in your terminal when you check the details of a movie.
# Set to 0 to disable
poster_columns = 180
# Set ascending order for sorting of tables
ascending = false

[TMDB]
api_key = "YOUR_TMDB_API_KEY"
# When you get your lists (-L options), also get all the runtimes from TMDB
# and compute the mean of the ratings weighted on the durations. This slows the process.
get_list_runtimes = false


[Letterboxd]
username = "your-username"
password = "your-password"
```

## Options

```shell
options:
  -h, --help            show this help message and exit
  -s SEARCH, --search SEARCH
                        Search for a director
  -S SEARCH_FILM, --search-film SEARCH_FILM
                        Search for a film.
  -d, --download        Download letterboxd data from your account
  -W, --watchlist       show watchlist
  -D, --diary           show diary
  -R, --ratings         show ratings
  -L, --lists           show lists
  -l LIMIT, --limit LIMIT
                        limit the number of items of your wishlist/diary
  -c CONFIG_FOLDER, --config_folder CONFIG_FOLDER
                        Specify the folder of your config.toml file

```

## To do

_Note: this is something I do during my free time. Therefore, I can't promise consistent support for this project._

-   [x] Use web-scraping to add film to diary/wishlist

-   [ ] Check followers' activity.