O'Reilly Live Trainining - Automate Tasks with Python + AI

Setup

• This repo was tested on a Mac with python=3.11.
• If you are a complete beginner check the installation guides for mac and windows to setup homebrew, git and download python:
  • ./installation-guide-mac.md
  • ./installation-guide-windows.md

Environment Setup

Conda

• Install anaconda or miniconda
• Create an environment: conda create -n oreilly-automate-tasks python=3.11
• Activate your environment with: conda activate oreilly-automate-tasks
• Install requirements with: pip install -r requirements/requirements.txt
• Setup your Openai API key
• Setup your Anthropic API key
• Download Ollama

Pip

1. Create a Virtual Environment: Navigate to your project directory. Make sure you have python3.11 installed! If using Python 3's built-in venv: python -m venv oreilly-automate-tasks If you're using virtualenv: virtualenv oreilly-automate-tasks

2. Activate the Virtual Environment:

   • On Windows:: .\oreilly-automate-tasks\Scripts\activate
   • On macOS and Linux:: source oreilly-automate-tasks/bin/activate

3. Install Dependencies from requirements.txt:

   pip install python-dotenv
   pip install -r ./requirements/requirements.txt

4. Setup your openai API key

Remember to deactivate the virtual environment afterwards: deactivate

Setup your .env file

• Change the .env.example file to .env and add your OpenAI API key.

OPENAI_API_KEY=<your openai api key>
ANTHROPIC_API_KEY=<your claude api key>
....

To use this Environment with Jupyter Notebooks:

• conda install jupyter -y
• python -m ipykernel install --user --name=oreilly-automate-tasks

Notebooks

Here are the notebooks available in the notebooks/ folder:

1. Python Basics: Data Types, Strings, Operators (Updated)
   

2. Python Basics: Variables (Updated)
   

3. Python Basics: Functions (Updated)
   

4. Python Basics: Lists, For Loops (Updated)
   

5. Python Basics: Dictionaries
   

6. Python Basics: Comparators (Updated)
   

7. Python Basics: Conditionals, Branching Decisions
   

8. Python Basics: Working with Files
   

9. Python Basics: Working with Tabular Data (CSVs)
   

10. Python Basics: Packages and APIs
    

11. Building AI Scheduler Agent
    

12. Extracting Data from Receipts, Storing CSV
    

13. Building Your Own Automation Scripts
    

14. Automatic Downloads: Examples
    

15. AI Tools: LLM APIs
    

16. File Management Automations
    

17. Automation Frameworks and Recipes
    

18. Automating Data Extraction with LLMs
    

19. Automating Data Extraction from Websites
    

20. Automating Data Extraction for Product Information
    

21. Introduction to APIs: Using AI APIs (OpenAI, Claude, Llama3)
    

22. Building Automation Workflows with AI
    

23. Building Email Assistant