semvec/pypi-packages huggingface dataset:
llm-fragments-reddit 0.1.1
A plugin for llm to load Reddit threads as fragments
Requires Python: >=3.12

# llm-fragments-reddit

A plugin for [llm](https://github.com/simonw/llm) that loads Reddit threads as fragments, making it easy to analyze and summarize Reddit discussions with large language models.

## Features

- Load entire Reddit threads (submission + comments) as LLM fragments
- Support for both Reddit URLs and submission IDs
- Preserves comment hierarchy with proper indentation
- Converts threads to clean Markdown format
- Handles deleted comments and "load more" placeholders gracefully

## Installation

Install using pip:

```bash
llm install llm-fragments-reddit
```

Or for development:

```bash
git clone https://github.com/banteg/llm-fragments-reddit
cd llm-fragments-reddit
pip install -e .
```

## Usage

The plugin adds a `reddit` fragment loader to the `llm` command. You can use it in two ways:

### Using Reddit URLs

```bash
llm -f reddit:https://www.reddit.com/r/Python/comments/abc123/my_thread/ "summarize the key ideas"
```

### Using Submission IDs

```bash
llm -f reddit:abc123 "extract the main arguments from this discussion"
```

## How it works

The plugin:

1. Fetches the Reddit thread using Reddit's JSON API
2. Converts the submission title, self-text, and comment tree into Markdown
3. Preserves comment hierarchy with indentation (2 spaces per nesting level)
4. Each comment is formatted as: `- **u/username**: comment body`
5. Returns the entire thread as a single fragment for LLM processing

## Output Format

The generated fragment includes:

- Thread title as H1 header
- Original post content (if any)
- Nested comment tree with proper indentation
- Author attribution for each comment

Example output structure:
```markdown
# DAE think Reddit is becoming too mainstream?

I've been on Reddit for 7 years (this is my alt account) and I swear the quality of discourse has really declined. Back in my day we had actual discussions instead of just memes and karma farming.

---

- **u/NostalgicRedditor2016**: This. So much this. I remember when you could have nuanced discussions without getting downvoted to oblivion.
  - **u/ActuallyIm14**: OK boomer. Reddit was always trash, you just got older and realized it.
    - **u/NostalgicRedditor2016**: I'm 23 but go off I guess
      - **u/GrammarNaziPatrol**: *you're
        - **u/NostalgicRedditor2016**: No, "you" is correct there. Maybe learn grammar before correcting others?
          - **u/GrammarNaziPatrol**: Edit: Thanks for the gold, kind stranger!
- **u/RedditExpert2024**: Unpopular opinion but Reddit has always been a circlejerk. The real issue is people thinking upvotes = truth
  - **u/PhilosophyUndergrad**: This is a profound observation. As Nietzsche once said... [3000 word comment about nihilism]
    - **u/SkippedTheReading**: TL;DR?
- **u/PowerModerator**: Locked. Y'all can't behave.
```

## Requirements

- Python ≥ 3.12
- [llm](https://github.com/simonw/llm) ≥ 0.26
- requests ≥ 2.32.3

## License

MIT License - see the source code for details.

## Author

Created by [banteg](https://github.com/banteg)
aPowerConverter 1.2.0
A tool to convert DOCX files to AsciiDoc format with special table handling
Requires Python: >=3.6

# aPowerConverter

A powerful tool to convert DOCX files to AsciiDoc format with special handling for tables and formatting.

## Features

- Converts DOCX files to AsciiDoc format using Pandoc
- Special handling for tables with `|a|` format, converting them to INFO blocks
- Preserves document structure and formatting
- Supports batch processing of multiple files
- Handles images and media extraction
- Normalizes punctuation and heading levels
- Supports document ID generation

## Installation

Make sure you have Python 3.6+ and Pandoc installed on your system.

```bash
pip install aPowerConverter
```

## Usage

Basic usage:
```bash
aPowerConverter input.docx
```

Convert multiple files:
```bash
aPowerConverter file1.docx file2.docx file3.docx
```

Options:
- `-o, --output-dir`: Output directory for converted files
- `-i, --image-dir`: Base directory for extracted images
- `-k, --keep-numbers`: Keep section numbers from the original document
- `-d, --dry-run`: Show what would be done without making changes
- `-q, --quiet`: Suppress progress messages
- `-g, --generalize`: Generalize headings after conversion
- `-v, --version`: Show version information

## Table to INFO Block Conversion

The converter automatically detects tables with `|a|` format and converts them to INFO blocks:

Input table:
```
|===
| a|
* First bullet point
* Second bullet point
|===
```

Gets converted to:
```
[INFO]
====
* First bullet point
* Second bullet point
====
```

## Requirements

- Python 3.6+
- Pandoc (https://pandoc.org/installing.html)

## License

MIT License
Flask-RQ 0.3.3
RQ (Redis Queue) integration for Flask and Quart applications.
Requires Python: >=3.9

# Flask-RQ

Flask-RQ is a [Flask]/[Quart] extension that background job execution using
[RQ]. RQ allows queueing functions to be run in separate worker processes,
allowing long-running jobs to run in the background without blocking the web app
from returning a response quickly. Flask-RQ allows configuring RQ using Flask's
config, and handles executing jobs in the application context, so other services
like database connections are available.

[Flask]: https://flask.palletsprojects.com
[Quart]: https://quart.palletsprojects.com
[RQ]: https://python-rq.org

## Pallets Community Ecosystem

> [!IMPORTANT]\
> This project is part of the Pallets Community Ecosystem. Pallets is the open
> source organization that maintains Flask; Pallets-Eco enables community
> maintenance of related projects. If you are interested in helping maintain
> this project, please reach out on [the Pallets Discord server][discord].

[discord]: https://discord.gg/pallets

## Installation

Install from [PyPI]:

```
$ pip install flask-rq
```

[PyPI]: https://pypi.org/project/Flask-RQ/

## Example

```python
from flask import Flask, g
from flask_rq import RQ

app = Flask(__name__)
rq = RQ(app)

@rq.job
def send_password_reset_job(user_id:  int) -> None:
    ...

@app.route("/auth/send-password-reset")
def send_password_reset():
    send_password_reset_job.enqueue(user_id=g.user.id)
    return "Check your email!"
```

```
$ flask rq worker
```
cloud-ds-api 1.2.11
cloud-ds-api


This Python package provides an interface for interacting with typical cloud storage systems. 
It allows users to create, retrieve, update, and delete data objects, each with associated 
metadata and content. The library includes support for session management, access control, 
transfer tracking, and metadata serialization, making it suitable for prototyping 
storage workflows or testing data processing pipelines. It offers a lightweight and 
dependency-free environment for modeling storage behavior in local or embedded applications.
linuxmd 0.1
Linux command-line utilities for Windows
Requires Python: >=3.6


# Linuxmd

This CLI (command line interface) is designed to let linux commands be used on non-linux machines 


## Documentation

This lets you use linux commands

Here are the commands:

```rm
cat
touch
mkdir
cp
mv
pwd
echo
clear
whoami
```

I will not tell you what these commands do, as I do not know.
## Deployment

To deploy this project run

```pip install linuxmd```