semvec/pypi-packages huggingface dataset:
stochastipy 0.1.0
Interactive learning through stochastic simulations and modeling.
Requires Python: >=3.11

# StochastiPy

StochastiPy is a Python package designed to explore and learn about statistical models, 
probability distributions, and random processes. With features like simulation, model 
evaluation, and interactive visualizations, it serves as a hands-on educational tool 
for students, professionals, and enthusiasts aiming to deepen their understanding of 
statistical methods.
weekdatemac 1.0.1
A macOS script to display the current week number in the menu bar.

# What Week Is It?

What week is it? This is a simple Python script that tells you what week of the year it is.

This is the MacOS implementation of the script.

## Setup
First, clone and navigate to the repository:
```bash
git clone https://github.com/Silicon27/weekdatemac
cd weekdatemac
```

Make it executable:
```bash
chmod +x run_week_menu_bar.sh
```

Move it to `~/Library/LaunchAgents/`
```bash
mv com.weekmenubar.plist ~/Library/LaunchAgents/
```

Then you can add it to your Launch Agent with `launchctl` and run it:
```bash
launchctl unload ~/Library/LaunchAgents/com.weekmenubar.plist && \
launchctl load ~/Library/LaunchAgents/com.weekmenubar.plist
```

And that's it! You should see the week number in your menu bar.

An example would look like this: 
![Week Date Mac](/demo.png)
konvertek 0.1.3
Convert media.
Requires Python: >=3.7

# konvertek

konvertek konvert all video files from one folder to another with certain video encoder, bitrate, resolution and fps. 
The file hierarchy will be preserved exactly as in the original directory.


# Installation and usage

Install by typing:

```bash
pip3 install konvertek
```

Run:

```bash
konvertek convert /path/to/source/dir /path/to/destenation/dir /path/to/progress.json \
                  --v_codec libx265 --bitrate 3M \ 
                  --resolution 720p --fps 24

         # progress.json is file, which contains transcode progress. 
         # If failed or power outages, this file will store progress.
         # Just retype command again with same progress.json
```

If needed hardware acceleration, use video encoder (`--v_codec`) `hevc_nvenc` (H.265) or `h264_nvenc` (H.264) for nvidia 
and  `h265_vaapi` (H.265) or `h264_vaapi` (H.264) for amd. Use `--help` for more parameters.
up-bank-api 1.2.0
💎 Typed python client for Up's banking API
Requires Python: >=3.8

# Up Bank API

[![Project version](https://img.shields.io/pypi/v/up-bank-api?style=flat-square)](https://pypi.python.org/pypi/up-bank-api)
[![Supported python versions](https://img.shields.io/pypi/pyversions/up-bank-api?style=flat-square)](https://pypi.python.org/pypi/up-bank-api)
[![License](https://img.shields.io/github/license/jcwillox/up-bank-api?style=flat-square)](https://github.com/jcwillox/up-bank-api/blob/main/LICENSE)
[![CodeFactor Grade](https://img.shields.io/codefactor/grade/github/jcwillox/up-bank-api?style=flat-square)](https://www.codefactor.io/repository/github/jcwillox/up-bank-api)
[![Monthly Downloads](https://img.shields.io/pypi/dm/up-bank-api?style=flat-square)](https://pypistats.org/packages/up-bank-api)
[![Total Downloads](https://img.shields.io/pepy/dt/up-bank-api?style=flat-square)](https://pepy.tech/project/up-bank-api)
[![Code style](https://img.shields.io/badge/code%20style-black-000000.svg?style=flat-square)](https://github.com/psf/black)

This is an unofficial Python API wrapper for the Australian Bank [Up's](https://up.com.au/) API.

This package is fully typed, documented, and it has an intuitive structure, so I'd recommend just having quick look at the [docs](https://jcwillox.github.io/up-bank-api), and letting syntax completion take the wheel.

- 📚 [Package Documentation](https://jcwillox.github.io/up-bank-api)
- 🕶️ [The Up Website](https://up.com.au)
- 📖 [Up API Documentation](https://developer.up.com.au)
- 🔗 [Up API on GitHub](https://github.com/up-banking/api)

## Installation

```shell
pip install up-bank-api
```

To include async support

```shell
pip install up-bank-api[async]
```

## Usage

To use this library you will need a personal access token which can be retrieved from https://developer.up.com.au. When using this library you can either provide the token directly or use the environment variable `UP_TOKEN`.

**Synchronous Client**

```python
from upbankapi import Client, NotAuthorizedException

# implicitly use the environment variable UP_TOKEN
client = Client()

# or directly provide token
client = Client(token="MY_TOKEN")

# check the token is valid
try:
    user_id = client.ping()
    print(f"Authorized: {user_id}")
except NotAuthorizedException:
    print("The token is invalid")
```

**Asynchronous Client**

```python
import asyncio
from upbankapi import AsyncClient, NotAuthorizedException

async def main():
    # implicitly use the environment variable UP_TOKEN
    client = AsyncClient()

    # or directly provide token
    client = AsyncClient(token="MY_TOKEN")

    # use a context manager to automatically close the aiohttp session
    async with AsyncClient() as client:
        try:
            user_id = await client.ping()
            print(f"Authorized: {user_id}")
        except NotAuthorizedException:
            print("The token is invalid")

if __name__ == "__main__":
    asyncio.run(main())
```

See the [docs](https://jcwillox.github.io/up-bank-api) for more information, examples and code reference.
medchemfilters 0.0.1
Utility for reaction modeling using graph grammar
Requires Python: >=3.11

# medchemfilters

## Overview
`medchemfilters` is a Python-based utility designed to streamline virtual screening in drug discovery. It features `MCFilter`, a comprehensive module for calculating molecular properties and filtering compounds according to well-established pharmaceutical guidelines such as Ro5, Pfizer, and GSK rules.

## Installation

To install and set up `medchemfilters`, follow these steps:

1. Clone the repository:
   ```bash
   git clone https://github.com/your-username/medchemfilters.git
   cd medchemfilters


2. Install required Python packages:
   ```bash
   pip install -r requirements.txt
   ```

## Usage

### In a Jupyter Notebook
For interactive use, such as in a Jupyter notebook, follow this example to utilize the `MCFilter`:

```python
from medchemfilters.ADMET.filters import MCFilter

# Initialize MCFilter with default settings
filter = MCFilter()

# Calculate molecular descriptors for a SMILES string
smiles = "CCO"
results = filter.calculate_des(smiles)
print(results)
```

### Command-Line Interface
`MCFilter` can also be executed from the command line to process either individual SMILES strings or batches from a CSV file:

- **Processing a Single SMILES String:**
  ```bash
  python main.py "CCO"
  ```

- **Processing SMILES from a CSV File:**
  ```bash
  python main.py path/to/input.csv --smiles_column column_name --output path/to/output.csv
  ```

#### Command-Line Options
- `input`: A single SMILES string or the path to a CSV file containing SMILES strings.
- `-c, --smiles_column`: Specifies the column name in the CSV that contains SMILES strings (default: smiles).
- `-o, --output`: Specifies the output file path for processed results. If not provided, results will be displayed in the terminal.
- `-j, --jobs`: The number of parallel jobs for processing (default: 1).
- `-v, --verbose`: Sets the verbosity level of the output (default: 0, silent).

## Requirements
Python 3.9 or higher is required.
All dependencies are listed in the requirements.txt file.

## License
`medchemfilters` is open-source software licensed under the MIT License. See the LICENSE file for more details.
gregor 0.0.2
A library for spatial aggregation and disaggregation
Requires Python: <4,>=3.8
Keywords: gis

# Gregor: Aggregation and disaggregation of spatial data

Gregor is a tool that makes your life easier when aggregating and dis-aggregating spatial data. It has been developed in the context of preparing data for energy system modeling, but can be applied in any situation involving spatial data.

<img src="https://raw.githubusercontent.com/jnnr/gregor/refs/heads/main/docs/img/polygons-to-raster-and-back.png" width=850>

## Installation

Install the latest release from pypi using pip.

    pip install gregor

Alternatively, install an editable local version in an environment by cloning the repository and running:

    pip install -e <path-to-repo>

## Usage

Please have a look at the examples presented in the [documentation](https://gregor.readthedocs.io/en/latest/). 

## Development

If you encounter a bug, consider opening an issue on [GitHub](https://github.com/jnnr/gregor/issues).