semvec/pypi-packages huggingface dataset:
daedal-emailaddressextractor 0.1.4
Extracts email addresses from MBOX files
Requires Python: >=3.7

# Email Address extractor by Daedal Systems

This is a program that allows you to read all email addresses from your mailbox and creates the following output files for you.
1. It will create a list of all distinct email senders and give a count of how many emails each one of them have sent you in the past
2. It will also generate a list of distinct email senders without the count. 

The package has two modules:
1. mboxwriter - It writes all the email senders from the mailbox and writes them into a file. It takes in two parameters namely mbox and output. The mbox parameter is for the path where the mailbox is present. The output parameter is providing the path where output file will be stored.
2. createmailerlist - It cleans the output file (or any file that has only email addresses) and creates two further output files storing email addresses and number of emails coming from them followed by a second file with just a list of distinct emails. This module needs 5 parameters to run but only one of them is mandatory. Below mentioned are the parameter details.
input - mandatory parameter. User enters the path of the input file. This will be the path for file with email addresses
emailsonly = Optional parameters. If you leave blank, it'll default to 'uniquemails.txt'
emailswithcnt = Optional parameter. If you leave it blank, it will not generate the file where you get email senders alond with the number of emails sent by them.
dir = optional parameter. Will save the files to current working directory if not filled in.
invalid = optional parameter. This will allocate the selected value to the invalid emails. If left blank, it'll default to 'invalid email'
kgrag-store 2.0.3
A Python library for knowledge graph management and retrieval with advanced memory capabilities.
Requires Python: >=3.9
Keywords: agent, knowledge, memory, retrieval, vector-store, kgrag

[![View on GitHub](https://img.shields.io/badge/View%20on-GitHub-181717?style=for-the-badge&logo=github)](https://github.com/gzileni/kgrag-store)
[![GitHub stars](https://img.shields.io/github/stars/gzileni/kgrag-store?style=social)](https://github.com/gzileni/kgrag-store/stargazers)
[![GitHub forks](https://img.shields.io/github/forks/gzileni/kgrag-store?style=social)](https://github.com/gzileni/kgrag-store/network)

## 📦 Installation

Install the `krag-store` library via pip:

```bash
pip install krag-store
```                

## Ingestion Data

### 📥 Usage Examples

#### 1️⃣ Ingestion from Local Filesystem

#### 2️⃣ Ingestion from AWS S3

Just set in your `.env`:

```env
AWS_ACCESS_KEY_ID=your_access_key
AWS_SECRET_ACCESS_KEY=your_secret
AWS_BUCKET_NAME=my-bucket
AWS_REGION=eu-west-1
```

## 🧠 Query

## [Docker](./docker/README.md)
textual-pdf 0.1.7
Display PDF files in textual widgets!
Requires Python: >=3.13
Keywords: pdf, python, textual, tui

# Textual PDF

A Textual widget for viewing PDF files.

## Installation

Install the package using your package manager:

```sh
pip install textual-pdf
uv add textual-pdf
poetry add textual-pdf
```

## Usage

Here is a simple example of how to use the `PDFViewer` widget in your Textual application:

```python
from textual.app import App, ComposeResult
from textual_pdf.pdf_viewer import PDFViewer

class PDFApp(App):
    def compose(self) -> ComposeResult:
        yield PDFViewer("path/to/your/document.pdf")

app = PDFApp()
app.run()
```

The `PDFViewer` class also comes with an option to switch protocols

`PDFViewer` supports whatever image protocols `textual-image` supports, which are `TGP`, `Sixel`, and `Halfcell` and `Unicode`

`TGP` and `Sixel` are the most recommended to use as they allow the clearest image to be produced. `Halfcell` and `Unicode` are not readable at all, and simply exists for the fun of it.

```py
# use tgp
PDFViewer("path/to/your/document.pdf", protocol="TGP")
# autodetect (default)
PDFViewer("path/to/your/document.pdf", protocol="Auto")
```

## CLI

`textual-pdf` is available as a CLI tool via `ptf`
```
uv tool install git+https://github.com/NSPC911/ptf
```

## License

This project is licensed under the MIT License.