semvec/pypi-packages huggingface dataset:
sqlalchemy-data-model-visualizer 0.1.3
A tool to visualize SQLAlchemy data models with Graphviz.
License: MIT
Keywords: sqlalchemy visualization graphviz data-model

# SQLAlchemy Data Model Visualizer

## Overview

This Python-based utility generates high-quality, readable visualizations of your SQLAlchemy ORM models with almost no effort. With a focus on clarity and detail, it uses Graphviz to render each model as a directed graph, making it easier to understand the relationships between tables in your database schema.

![Example Data Model Diagram](https://raw.githubusercontent.com/Dicklesworthstone/sqlalchemy_data_model_visualizer/main/my_interactive_data_model_diagram.svg)

## Try it Out Easily in Colab:

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1np5kPvDtdhq138eLHOGINYuTUMJo_wrj?usp=sharing)

## Features

- Automatically maps SQLAlchemy ORM models to a directed graph.
- Table-like representation of each model with fields, types, and constraints.
- Export diagrams to SVG format for high-quality viewing and printing using Roboto font. 

## Installation with pip and Usage:

```bash
pip install sqlalchemy-data-model-visualizer

# Suppose these are your SQLAlchemy data models defined above in the usual way, or imported from another file:
models = [GenericUser, Customer, ContentCreator, UserSession, FileStorage, ServiceRequest, GenericAuditLog, GenericFeedback, GenericAPIKey, GenericNotification, GenericAPICreditLog, GenericSubscriptionType, GenericSubscription, GenericSubscriptionUsage, GenericBillingInfo]
output_file_name = 'my_data_model_diagram'
generate_data_model_diagram(models, output_file_name)
add_web_font_and_interactivity('my_data_model_diagram.svg', 'my_interactive_data_model_diagram.svg')
```

## Installation from Source

To get started, clone the repository and install the required packages.

```bash
git clone https://github.com/Dicklesworthstone/sqlalchemy_data_model_visualizer.git
cd sqlalchemy_data_model_visualizer
python3 -m venv venv
source venv/bin/activate
python3 -m pip install --upgrade pip
python3 -m pip install wheel
pip install -r requirements.txt
```

## Requirements

- Python 3.x
- SQLAlchemy
- Graphviz
- lxml

## Usage

### Generate Data Model Diagram

First, paste in your SQLAlchemy models. A set of fairly complex data models are provided in the code directly as an example-- just replace these with your own from your application.

Then, simply call the `generate_data_model_diagram` function. This will generate an SVG file with the name `my_data_model_diagram.svg`.

## API Documentation

### `generate_data_model_diagram(models, output_file='my_data_model_diagram', add_labels=True)`

- `models`: List of SQLAlchemy models you want to visualize.
- `output_file`: Name of the output SVG file.
- `add_labels`: Set to False to hide labels on the edges between tables

## Contributing

Contributions are welcome! Please open an issue or submit a pull request.

## License

This project is licensed under the MIT License.
protecto-libraries 0.0.1
Tokenisation Package
License: MIT

# README #

This README would normally document whatever steps are necessary to get your application up and running.

### What is this repository for? ###

* Quick summary
* Version
* [Learn Markdown](https://bitbucket.org/tutorials/markdowndemo)

### How do I get set up? ###

* Summary of set up
* Configuration
* Dependencies
* Database configuration
* How to run tests
* Deployment instructions

### Contribution guidelines ###

* Writing tests
* Code review
* Other guidelines

### Who do I talk to? ###

* Repo owner or admin
* Other community or team contact
FlaskAuth2FA 1.7.5
A Flask extension for handling user authentication.
License: MIT
Requires Python: >=3.6

# FlaskAuth2FA Package

This package provides a Flask extension for handling user authentication.

## Installation

To install FlaskAuth2FA, run:

```
pip install FlaskAuth2FA
```

## Usage

To use FlaskAuth2FA in your Flask application, register the authentication Blueprint:

```python
from flask_auth import auth

app.register_blueprint(auth, url_prefix='/auth')

```
### Next, specify where to redirect the user after successful logins:
```
# Set a default or specific success URL for each project
app.config['LOGIN_SUCCESS_URL'] = 'dashboard'  # Use the endpoint name here
- !!Note!! This should be a route that actually routes to something in your project. Otherwise, you will get a 500 or 404. 
```
See the documentation for more details.
colourtime 0.4.0
Represent time with colours
License: MIT

```sh
pip install colourtime
```

Colourtime converts an Event Stream file (.es) into a PNG image, where time is represented with colour gradients.

The pip package installs a Python library (`import colourtime`) and command-line executable (`colourtime`).

The following command converts an Event Stream file.

```sh
colourtime /path/to/input.es
```

Run `colourtime --help` to list available options.

Check **python/**init**.py** for details on the Python API.

## Build from source

```sh
python3 -m venv .
source ./bin/activate
pip3 install -U pip event_stream matplotlib maturin numpy pillow
maturin develop -r
```

## Format

```
isort .; black .; pyright .
```