semvec/pypi-packages huggingface dataset:
notigram 2.2.3
A dev tool to enhance productivity
Requires Python: >=3.7

Notigram-CLI 🛎
===============

Notigram is a small project, aimed as a productivity-aid tool.

The functionality provided is basically sending notifications from a script or command line, to a Telegram client, so you can be notified about any kind of event through it.

The tool is composed by 3 parts: 
  * A CLI interface, which can be used from command line, python module, or http request. 
  * A Telegram Bot, which will provide a personal token for the user and will deliver the notifications. 
  * And finally the API, which manages the message requests and the bot.

The API code can be found `here on my other repo <https://github.com/Rinngell-Rezs/notigram-bot-API>`_, in case you want to check out how it works ^^.

The Telegram bot can be found as @notigram_apibot or at https://t.me/notigram_apibot.

Installing 👨‍💻
================

.. code-block:: bash

    pip install notigram

Usage 👓
=========

.. code-block:: bash

    >>> from notigram import ping
    >>> ping('<TOKEN>',"You've got a message from python!")
    {'response':'result'}

or 🤷‍♂️

.. code-block:: bash

    [user@linux ~]$ python -m notigram <TOKEN> Hello from command line! :D
    {'response':'result'}

If you aren't using a python program or a command line, you can always send an http post request to the server (https://notigram.blahaj-bay.gay/sendMessage) as well with the following format: 

.. code-block:: bash

    {
        "token": "TOKEN",
        "message": "The Postman says Hello!"
    }
neuralinit 0.1.0
Automation tool to scaffold deep learning project directory structure
Requires Python: >=3.6

# NeuralInit

`neuralinit` is a Python automation tool that creates a clean, modular deep learning project folder structure for researchers and students.

## Features

- GUI-based project initialization
- Creates well-organized directories and Jupyter notebooks
- Ideal for long-term DL and ML projects

## ðŸ“¦ Installation

```bash
pip install neuralinit
potatotime 0.0.6
Synchronize events between Google, Outlook, and iCal.
Requires Python: >=3.8

# PotatoTime

Synchronize events between Google, Outlook, and iCal.

```bash
pip install potatotime
```

## Quickstart

To get started, setup OAuth credentials for each service.

- To obtain the Google client file, create an OAuth Desktop Application in
the Google Cloud Console and download the JSON credentials. Save this as
`potatotime_client_google.json`.

- For Microsoft, register an app in the Azure Portal and note the
Application (client) ID and secret. Set these values in the environment
variables `POTATOTIME_MSFT_CLIENT_ID` and
`POTATOTIME_MSFT_CLIENT_SECRET` before authorizing.

Then, run the following script.

```python
from potatotime.services.gcal import GoogleService
from potatotime.services.outlook import MicrosoftService
from potatotime.synchronize import synchronize

google = GoogleService(); google.authorize("user")
microsoft = MicrosoftService(); microsoft.authorize("user")

synchronize([google.get_calendar(), microsoft.get_calendar()])
```

This will prompt you login to each service via the browser. The credentials will be stored in the current directory as `potatotime_user_{SERVICE}.json`
by default.

## Storage

The library stores credentials with a simple `FileStorage` by default.
User tokens are written to `potatotime_user_<USER_ID>.json` and OAuth
client details are read from `potatotime_client_<SERVICE>.json` in the
current directory.

You can also read credentials from environment variables using
`EnvStorage`:

```python
from potatotime.storage import EnvStorage

google = GoogleService(); google.authorize("user", storage=EnvStorage())
microsoft = MicrosoftService(); microsoft.authorize("user", storage=EnvStorage())
```

By default, this expects user tokens to be stored in environment variables
as `POTATOTIME_USER_{USER_ID}` and OAuth client details to be stored in
environment variables as `POTATOTIME_CLIENT_{SERVICE}`.

### Apple Calendar

Apple Calendar access requires a username and an app password:

```bash
export POTATOTIME_APPLE_USERNAME="your_apple_id@example.com"
export POTATOTIME_APPLE_PASSWORD="app-specific-password"
```

Generate the password from your Apple ID account page and supply your
Apple ID email address for the username.

## Development

Run all tests using the following.

```bash
pip install -e .[test]
py.test --cov -x
```
tldx 1.0.1
TLD Expansion Tool for Bug Bounty Reconnaissance
Requires Python: >=3.6
Keywords: bugbounty recon tld security

<div align="center">
<img src="logo.png" style="width: 200px; hight: 200px;"/>
<h2>TLDX</h2>
<p>Top Level Domain(TLD) Expansion Tool for Bug Bounty</p>
</div>

---
Expand keywords across all TLDs to discover hidden assets during reconnaissance.

### Features
- Generate domain permutations (keyword + TLD)
- Supports single keywords or keyword files
- Uses official IANA TLD list
- Custom TLD lists support
- Output to console or file

### Installation
```bash
pip install tldx
```
### Usage
```yaml
# Single keyword
tldx -k google

# Keyword file
tldx -kf keywords.txt

# Save output
tldx -k admin -o targets.txt

# Custom TLD list
tldx -k test -t custom_tlds.txt

# Verbose mode
tldx -k dev -v
```
### Example

```yaml
# Generate government domains
tldx -k google | head -5
google.aaa
google.aarp
google.abb
google.abbott
google.abbvie

# Pipe to DNS resolver
tldx -k "api.google" | dnsx -silent

# Full recon workflow
tldx -kf keywords.txt | httpx -silent | nuclei -t vulnerabilities/
```

```yaml
tldx/
├── setup.py
├── requirements.txt
├── README.md
├── tldx/
│   ├── __init__.py
│   ├── cli.py
│   └── core.py
└── tests/
    └── test_tldx.py
```