PRAKTIKOS is an open-source Robotic Process Automation (RPA) tool that allows you to automate repetitive tasks using Python. With PRAKTIKOS, you can build complex RPA bots using configurable, conditional, and custom actions, and execute them with ease.

• Configurable, conditional, and custom actions
• Lightweight and efficient execution
• Terminal-based flow designer
• Easy-to-use API for creating and executing flows
• Extensible and customizable architecture
• Support for Windows and Linux

To install PRAKTIKOS, run the following command:

pip install praktikos

To get started with PRAKTIKOS, check out the documentation for information on how to use the terminal-based flow designer and the Python API.

If you would like to contribute to PRAKTIKOS, please read the contributing guidelines for instructions on how to get started.

1. Minimum Viable Product (MVP):

   • Basic flow designer with built-in actions and conditional actions
   • Basic error handling and logging
   • Basic third-party integrations (e.g. HTTP requests, OCR, email)
   • Basic CLI for running and managing workflows

2. Enhanced and sophisticated error handling and logging: Improving error handling and logging should be a priority, as it will make it easier to identify and fix issues in automation workflows. This could include features such as more detailed error messages, log aggregation and analysis, and the ability to generate alerts or notifications when errors occur.

   • Python logging module for logging messages and exceptions
   • Sentry for error tracking and aggregation
   • Airflow for scheduling and monitoring workflows
   • Grafana for visualizing and analyzing log data

3. Third-party integrations: Adding support for more third-party libraries and APIs could be the next priority, as it will expand the range of applications and platforms that Praktikos can support. This could include libraries for web automation, database integration, or machine learning, depending on the specific use case.

   • Requests library for making HTTP requests
   • Selenium for web automation
   • PyTesseract for OCR
   • PyAudio for audio recording and playback
   • Twilio for SMS and voice notifications
   • Slack for chat integration
   • AWS SDK for cloud services integration

4. Advanced flow designer features: Adding more advanced flow designer features, such as drag-and-drop actions, external resource linking, and collaboration tools, could help streamline the process of creating and managing automation workflows.

   • PyQt or PySide for building graphical user interfaces
   • PyGraphviz or NetworkX for generating visual representations of workflows
   • Django or Flask for building web-based workflow editors
   • RabbitMQ or Apache Kafka for message queuing and event-based workflows

5. Machine learning and AI: Integrating machine learning and AI capabilities into Praktikos could potentially make it more powerful and flexible. This could include features such as improved OCR accuracy, natural language processing, image recognition, or AI-powered decision making.

   • TensorFlow, PyTorch, or Keras for building and training machine learning models
   • OpenCV for computer vision and image processing
   • spaCy or NLTK for natural language processing
   • Apache Spark for distributed computing and machine learning
   • Scikit-learn for machine learning algorithms

PRAKTIKOS is licensed under the MIT License.

This README.md file was generated with the help of ChatGPT, an AI language model trained by OpenAI. If you have any questions or feedback about this README or the PRAKTIKOS project, please feel free to contact me!