semvec/pypi-packages huggingface dataset:
ictasks 0.2.4
A utility to run multiple small tasks in a single HPC job submission.
Requires Python: >=3.10
Keywords: Slurm, HPC, tasks, MPI

# ictasks

`ictasks` is a library to support running collections of small tasks in parallel, from a laptop through to a HPC cluster.

It is being developed to support projects and workflow standarisation at the Irish Centre for High End Computing (ICHEC).

There are many libraries like this, this one focuses on:

* being small and simple - easy for ICHEC researchers to understand all elements of it
* having low dependencies - can be installed with `pip`
* having an easy to use configuration format with `yaml`
* having verbose and structured reporting of task related metadata for analysis

# Features #

The library allows a few different ways to specify tasks.

1) As a Python package

You can create a collection of `Task` instances and launch them with the `session.run()` function. 

2) Using a `tasklist.dat` file and the command line interface (CLI):

``` shell
ictasks taskfarm --tasklist $PATH_TO_TASKLIST
```

See the `test/data/tasklist.dat` file for an example input with two small tasks.

3) Using a `yaml` config file, giving task and environment info.

``` yaml
job_id: my_job
task_distribution:
    cores_per_node: 1

tasks:
    items:
    - id: 0
      launch_cmd: "echo 'hello from task 0'"
    - id: 1
      launch_cmd: "echo 'hello from task 1'"
```

we can run this with:

``` shell
ictasks taskfarm --config my_config.yaml
```

Launching the run will launch the task in that directory and output a status file `task.json`. By default all processors on the machine (or compute node) will be assigned tasks.


## task_distribution ##

There are 5 variables available in `task_distribution`

 - `cores_per_node=0`
 - `threads_per_core=0`
 - `cores_per_task=1`
 - `gpus_per_node=0`
 - `gpus_per_task=0`

If left unspecified, both `cores_per_task` and `gpus_per_task` will be automatically detected and set.

The number of active `worker`s will be set depending on these resource limitations, with gpu limits being hit first if needed. These workers can then execute tasks in parallel.

### gpus in your tasks ##

When taskfarming with gpus, there will be a `gpu_ids.txt` file in each task directory which contains a gpu_id per line, the user's program must then use this file to specify which gpu(s) to use. The function `ictasks.task.get_gpu_ids` can be used to retrieve the ids in this file as a Python list. See [an example here](./test/mocks/gpu_script.py).


# Installing #

The package can be installed from PyPI:

``` shell
pip install ictasks
```

# Contact #

Our Gitlab hosting arrangement doesn't allow us to easily accept external contributions or feedback, however they are still welcome.

In future if there is interest 


If you have any feedback on this library 

# License #

This package is Coypright of the Irish Centre for High End Computing. It can be used under the terms of the GNU Public License (GPL v3+). See the included `LICENSE.txt` file for details.

If you are an ICHEC collaborator or user of the National Service different licensing terms can be offered - please get in touch to discuss.
searchallpdf 0.2.0
Search for terms in all pdf in current and sub folders.
Requires Python: >=3.0

[![PyPI Version](https://img.shields.io/pypi/v/searchallpdf)](https://pypi.org/project/searchallpdf/)
[![License](https://img.shields.io/github/license/casiez/searchallpdf)](LICENSE)

# searchallpdf

Command line to search in pdf files
## Install
```pip install searchallpdf --upgrade```

## Features

Run ```searchallpdf -h``` to show all the options available.

### Search in all pdf files in current and sub folders

```searchallpdf termTofind1 termTofind2```

### Search in one pdf file

```searchallpdf -f file.pdf termTofind1 termTofind2```
ghstats-cli 0.1.0
A CLI to display your GitHub contributions heatmap, streaks, and activity over the past year.
Requires Python: >=3.8
Keywords: GitHub, CLI, contributions, streaks, heatmap

# ghstats-cli 

A simple command-line tool to display your GitHub contribution heatmap right in your terminal.

## Installation

### Recommended (via pipx)

The best way to install `ghstats-cli` is using `pipx`, which installs the tool in an isolated environment to avoid dependency conflicts.

1.  **Install pipx (if you don't have it):**

    ```bash
    pip install pipx
    ```

2.  **Install the tool:**

    ```bash
    pipx install ghstats-cli
    ```

### Alternative (via pip)

You can also use standard `pip`. It's recommended to install it in a virtual environment to avoid cluttering your global packages.

```bash
pip install ghstats-cli
````

## Getting Started

### 1\. One-Time Setup

Before you begin, run the interactive setup to configure your default GitHub username and create a Personal Access Token (PAT). The tool will guide you through the process.

```bash
ghstats setup
```

This will securely store your credentials for all future requests.

### 2\. Usage

Once configured, viewing your heatmap is as simple as running the main command.

#### Show Your Own Heatmap

```bash
ghstats
```

#### Show a Specific User's Heatmap

Use the `--user` flag to view the contribution graph of any GitHub user.

```bash
ghstats --user torvalds
```

## All Commands

Here is the full list of available commands and options.

```
Usage: ghstats [OPTIONS] COMMAND [ARGS]...

  ghstats — A sleek tool to show GitHub contribution heatmaps in your
  terminal.

Options:
  --user TEXT  Show heatmap for a specific GitHub user.
  -h, --help   Show this message and exit.

Commands:
  setup        Interactively configure your default username and GitHub token.
  config       Open the configuration file in your default editor.
  show-config  Show current configuration with a masked token.
```

## License

This project is licensed under the MIT License - see the [LICENSE](https://raw.githubusercontent.com/d1rshan/ghstats-cli/refs/heads/main/LICENSE) file for details.
fast-gaussian-initialization 0.0.2
A library for fast CPU-based initialization of 3D Gaussian Splatting models from point clouds.
Requires Python: >=3.9

# Fast Gaussian Initialization (FGI)

This is FastGI library, designed for rapid CPU-based
initialization of 3D Gaussian Splatting models.

Key features include:
- Flexible PLY file loading (PlyFile)
- Greedy clustering of point clouds (Fit class)
- Gaussian fitting with GMM or fast PCA fallback
- Export to standard 3DGS PLY format
- Basic test renderer (test_render)
- Open3D viewer integration (view_ply)

Adds pyproject.toml for packaging and dependency management.

I'll add way more information later :)
Version 0.0.2, btw!
mt5-grpc-server 0.2.1
MetaTrader 5 gRPC Server for remote trading operations
Requires Python: >=3.8
Keywords: metatrader, mt5, trading, grpc, server, api

# MT5 gRPC Server

A high-performance gRPC server implementation for MetaTrader 5, enabling remote trading operations and market data access.

## Overview
This module provides a gRPC server that interfaces with MetaTrader 5 terminal, allowing remote access to trading operations, market data, and account management through a standardized gRPC API.

## Installation

```bash
pip install mt5-grpc-server
```

## Features

- **Account Operations**
  - Account info retrieval
  - Balance and equity monitoring
  - Trading history access

- **Trading Operations**
  - Order placement and modification
  - Position management
  - Order validation and calculations

- **Market Data**
  - Real-time price data
  - Symbol information
  - Market depth (DOM)


## Usage

### Starting the Server

Example with secure connection:
```bash
mt5-grpc-server --host 127.0.0.1 --port 50052 --secure --cert-file server.crt --private-key-file server.key
```

Or without secure connection:
```bash
# Default port is 50051 and host is 0.0.0.0
mt5-grpc-server 
```


### Command-line Options

The server supports the following command-line options:

- `--host HOST`: Host address to bind the server to (default: "0.0.0.0")
- `--port PORT`: Port number to listen on (default: 50051)
- `--secure`: Enable secure connection with SSL/TLS
- `--cert-file FILE`: Path to the SSL certificate file (required if --secure is used)
- `--private-key-file FILE`: Path to the private key file (required if --secure is used)
mt5-grpc-proto 0.2.1
Protocol Buffers and gRPC service definitions for MetaTrader 5 RPC Server
Requires Python: >=3.8
Keywords: metatrader, mt5, trading, grpc, protobuf, api

# MT5 gRPC Proto

Protocol Buffers and gRPC service definitions for MetaTrader 5 RPC Server.

## Overview
This module contains the Protocol Buffer definitions and generated gRPC service code for interacting with MetaTrader 5 through a gRPC interface. It provides the contract between the MT5 gRPC server and its clients.

## Installation

```bash
pip install mt5-grpc-proto
```

## Features

The proto definitions cover the following MetaTrader 5 functionalities:
- Account operations
- Trading operations
- Market data retrieval
- Order management
- Position tracking
- Historical data access
- Terminal information
streamsnatcher 0.1.2
StreamSnatcher — rip encode and capture streams with style
Requires Python: >=3.9

[![Chat-GPT-Image-Sep-13-2025-05-31-00-AM.png](https://i.postimg.cc/65Fg3xzg/Chat-GPT-Image-Sep-13-2025-05-31-00-AM.png)](https://postimg.cc/xcytx7w3)



# StreamSnatcher 🎧⚡

**StreamSnatcher** is a lightweight Python tool for ripping, capturing, and saving streams with style.  
Fast, simple, and designed to just work — no bloat, no fuss.

---

## 🚀 Features
- 🔥 Quick and reliable stream capture
- 🐍 Pure Python (no heavy dependencies)
- 🛠 Easy CLI interface (`streamsnatcher`)
- ✅ Tested on Linux, macOS, and Windows

---

## 📦 Installation
Install directly from PyPI:

```bash
pip install streamsnatcher
````

Or install from source:

```bash
git clone https://github.com/youruser/streamsnatcher.git
cd streamsnatcher
pip install .
```

---

## 🖥 Usage

Run via CLI after installation:

```bash
streamsnatcher <url_or_stream>
```

Example:

```bash
streamsnatcher https://example.com/live/stream.m3u8
```

Output will be saved in the current directory.

---

## 🧪 Development

Clone the repo and install dependencies:

```bash
git clone https://github.com/youruser/streamsnatcher.git
cd streamsnatcher
pip install -r requirements.txt
```

Run tests:

```bash
pytest
```

---

## 📜 License

StreamSnatcher is released under the **Private License**.
See [LICENSE.md](LICENSE.md) for details.

---

## 🤝 Contributing

Pull requests are welcome! Open an issue for bugs, features, or discussion.

---

## 🌐 Links

* **PyPI:** [StreamSnatcher on PyPI](https://pypi.org/project/streamsnatcher/)
* **GitHub:** [StreamSnatcher Repository](https://github.com/74Thirsty/streamsnatcher)