semvec/pypi-packages huggingface dataset:
hdf 2023.9.1
Easy Framework
License: MIT
Requires Python: >=3.8,<4.0

# Easy

## Installation

1. Create a virtual environment and activate it.

       ❯ python3 -m venv venv
       ❯ . ./venv/bin/activate

2. Create the initial env files to run Easy.

       ❯ flask core init -d

3. Check and modify the three new files `dev_easy.conf`, `.env`, and `.flaskenv`.

   The most important one is `dev_easy.conf` where you should check the following keys:
  - `SECRET_KEY`
  - `ALCHEMICAL_DATABASE_URL`
  - `EASY_ADMINS` before you go to the next step!.
  - `MAIL_*` you will need this to safely create the user accounts and communicate with the users.
  - `EASY_*` in general.

4. Create the DB Migrations infrastructure, the first migration, and apply it.
   
       ❯ flask db init
       ❯ flask db migrate
       ❯ flask db upgrade

5. Create the Admin Accounts according to the `EASY_ADMIN` key in the conf file (see step 3).
   
       ❯ flask auth create-admins

6. Now you can run the development server and conform that you can log in + change the password from the default value of `Easy` to a more secure one.

   Each admin account will be forced to change the password on the first successful login.
FFEMcv 0.3.0
Easy and Fast Facial Emotion Monitoring
License: MIT

# Fast Facial Emotion Monitoring (FFEM)

This package provides a simple and efficient way to perform Facial Emotion Recognition (FER). It leverages advanced techniques and algorithms to detect and classify emotions from facial expressions.

## Main Function

* `MonitorEmotion_From_Video(video_path: str | int, output_path:str) -> None`
  This function takes a video file or a webcam feed as input and performs FER. The results are saved to the specified output path.

## Main Class

* `FaceEmotion_Detection()`
  This class is the backbone of the FER process. It performs face detection and emotion recognition using DeepFace and MediaPipe. The `MonitorEmotion_From_Video` function utilizes this class to carry out its operations.

This package is designed with user-friendliness in mind, making the complex task of FER accessible and straightforward for users. Whether youâ€™re a researcher, a developer, or someone interested in FER, this package can be a valuable tool for your projects.
pg-streamline 1.2.0
pg-streamline is a Python library designed to simplify and streamline the process of logical replication
License: MIT
Keywords: netsuite,api,python,sdk

# pg-streamline-py

## Streamlining PostgreSQL Logical Replication and Event Processing

pg-streamline is a Python library designed to simplify and streamline the process of logical replication and event processing with PostgreSQL. It provides modular components for producers, consumers, parsers, and plugins, making it highly extensible and customizable.

---

### Table of Contents

1. [Installation](#installation)
2. [Features](#features)
3. [Usage](#usage)
   - [Producer](#producer)
   - [Consumer](#consumer)
   - [Parser](#parser)
   - [Plugins](#plugins)
4. [Contributing](#contributing)
5. [License](#license)

---

### Installation

```bash
pip install pg-streamline
```

## Features

### Producer

- Handles PostgreSQL logical replication.
- Supports multiple output plugins like 'pgoutput' and 'wal2json'.
- Pooling support for better performance.

For more details, see the [Producer README](./pg_streamline/producer/README.md).

### Consumer

- Consumes and processes the events replicated by the producer.
- Extensible: Can be extended to perform custom actions when specific database changes occur.

For more details, see the [Consumer README](./pg_streamline/consumer/README.md).

### Parser

- Parses different types of logical events from PostgreSQL.
- Supports parsing of INSERT, UPDATE, and DELETE events.
- Makes it easier to understand and act upon the changes in the database.

For more details, see the [Parser README](./pg_streamline/parser/README.md).

### Plugins

- Extend the functionality of pgStreamline with various plugins.
- Currently supports RabbitMQ for message queuing.
- More plugins are in development.

For more details, see the [Plugins README](./pg_streamline/plugins/README.md).

## Usage

Please refer to the README files in each module's directory for specific usage instructions:

- [Producer Usage](./pg_streamline/producer/README.md)
- [Consumer Usage](./pg_streamline/consumer/README.md)
- [Parser Usage](./pg_streamline/parser/README.md)
- [Plugins Usage](./pg_streamline/plugins/README.md)

## Contributing

We welcome contributions! Please see the [Contributing Guidelines](CONTRIBUTING.md) for more details.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.