A Framework for Deploying Python in Finance 3 Steps | Ep.064

The Adam Shilton Podcast

This video talks through a 3-step framework for deploying Python in finance. ------CHAPTERS------ 1. Python Libraries https://spectacled-redcurrant-dae.notion.site/e28a304c1f034deda720dcdf42ba9ab5?v=4c851e78252c4f5e9f6b625e693f69e3 2. Library prompt https://chat.openai.com/share/c819bec9-3c65-437e-b24c-3a2b78a9210b 3. Application prompt https://chat.openai.com/share/451553fc-bb60-446e-b73b-8dfc11219217

4. Google Colab Code https://chat.openai.com/share/84f85da3-1068-4c70-b3b5-611ace9d5f15 ------SHOW NOTES------ 1. [L] Python Library **Key takeaway** - If there’s not a library for your use case, Python may not be the best option. At least not without a developer. **Pro Tip** - Use this prompt with an AI of your choice: “List some Python libraries that can be used for [Use Case] (that don't relate to the finance industry or algorithmic trading) and describe what they do.” 1. [A] Application **Key Takeaways** - It’s important to match your application to your specific use case. Online environments like Jupyter notebooks have a much lower barrier to entry that installing developer tools like Visual Studio Code. **Pro Tip** - Use this prompt with an AI of your choice: “I’m thinking of performing [use case] using a library like [library]. Is this the library you’d suggest? If so, which platform (e.g Google Colab or Visual Studio Code) would you use to deploy it?” 1. [W] Workflow **Key Takeaway -** Python become infinitely more powerful when added to day to day workflows. Have a think about where it can slot into yours. ## Putting it into practise The best way to get concepts to stick is to put them into practise. Try this: 1. Login to an AI of your choice (ChatGPT Pro or [Copilot](https://copilot.microsoft.com/) preferred as they’re better with coding) 2. Enter this prompt: “Using the Matplotlib library, generate some Python code that someone in corporate finance could use in Google Colab to get an immediate impression of the power of Python - Use dummy data within the code to avoid the need for data upload or data connection - Exclude anything to do with the finance industry or algorithmic trading.” 3. Copy the code 4. Create a new Notebook in Google Colab (login using [this link](https://colab.research.google.com/)) 5. Copy the code and hit play (top left) P.S - Don’t forget to head over to www.techforfinance.com and sign up to Framework Friday for 1 actionable tech framework you can use to stay ahead of the game.