Santiago Profile picture
Sep 26, 2020 12 tweets 7 min read Read on X
I do a lot of Python 🐍, but you knew that already, right?

However, there's something new: the libraries and tools that I use on every single project. Every. Single. One.

Here are 10 of them. The best ones.

🧵👇
1⃣bpython — A lightweight interpreter

I constantly use the interpreter to test ideas or review the syntax of what I want to do.

bpython is a great alternative to the standard REPL. It offers syntax highlighting, expected parameter list, auto-indentation, and autocompletion.

👇
2⃣rope — A refactoring library

A free utility for refactoring Python code. I personally use it integrated with @code, but you can also use it directly by writing scripts.

This @realpython article discusses rope and refactoring in general: realpython.com/python-refacto…

👇
3⃣flake8 — Enforcing style consistency

This is the first library I install on every project. It's a linter that ensures that my code follows good conventions.

This library is a must, especially for teams.

And it supports third-part extensions!

flake8.pycqa.org/en/latest/

👇
4⃣black — Formatting my code

If flake8 is the first library I install, black is number two.

It's a tool to automatically format my code. It does so keeping compatibility with a standard style guide. I also use it integrated with @code.

github.com/psf/black

👇
5⃣venv — Virtual environments

Every Python developer should master virtual environments and use them for every project.

There are several ways to create virtual environments but since Python 3.3, I mostly use the standard venv module.

docs.python.org/3/library/venv…

👇
6⃣logging — The standard logging facility

It might be time to stop cluttering your code with print statements and start using logging like a grown-up 😋

logging is a standard Python module.

You can find more information in this @realpython article: realpython.com/python-logging/

👇
7⃣sphinx — Generating documentation

Whenever I need to package all my docstrings as a nice HTML documentation site, I go to sphinx.

There are a ton of things about sphinx! It took me some time to get the hang of it, but now I constantly use it.

sphinx-doc.org/en/master/

👇
8⃣pytest — For testing my code

I do a lot of TDD, so pytest is always there with me.

It's very simple to get started with it. At the same time, it's very robust, extensible, and so far, I've found everything I ever needed right there.

Site: docs.pytest.org/en/stable/

👇
9⃣coverage — Understanding your test coverage

The library determines which lines of your code are executable, and which have been executed by the tests.

It gives me an idea of how much code is currently not exercised by my pytest suite.

github.com/nedbat/coverag…

👇
🔟faker — Generating fake data

I discover faker very recently, and it's great! You can use it to generate all sorts of fake data that you can use as part of your tests or for whatever you need.

There's even a pytest plugging which is a bonus!

github.com/joke2k/faker

👇
Let me know what are the libraries and tools that you always use in your projects. I'm always looking for ways to improve this setup!

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More from @svpino

Aug 4
AI is changing everything. Full stop.

If you still don't get it, watch this.

Look at the attached video. A company using this tool will execute 100x faster than everyone else. There's simply no match for how fast AI can transform what you do.
I'm working here with @PromptQL. They will help you build a reasoning AI that is specialized to your business.

This makes an ocean of difference:

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You can teach the system how to interpret your data and how you prefer things to be done.

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Jul 7
Here is how you can test your applications using an LLM:

We call this "LLM as a Judge", and it's much easier to implement than most people think.

Here is how to do it:

1/11 Image
(LLM-as-a-judge is one of the topics I teach in my cohort. The next iteration starts in August. You can join at .)

2/11ml.school
We want to use an LLM to test the quality of responses from an application.

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Jun 6
Bye-bye, virtual assistants! Here is the most useful agent of 2025.

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I asked it to read my emails and reply to every cold outreach message.

My mind is blown!
AI Secretary and the folks @genspark_ai will start printing money!

You can try this out here:

Check their announcement video and you'll see some of the crazy things it can do for you. genspark.ai
The first obvious way I've been using AI Secretary:

100x better email search.

For example, I just asked it to "show me the last 3 emails asking for an invoice for the Machine Learning School cohort."

I also asked it to label every "email containing feedback about the cohort."
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You can now have a literal army of coding interns working for you while you sleep!

Remote Agent is now generally available. This is how we all get to experience what AI is really about.

Here is what you need to know:
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Remote Agent:

• Runs in the cloud
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Here is a link to try it out: fnf.dev/4jobOrw
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Jun 4
Knowledge graphs are infinitely better than vector search for building the memory of AI agents.

With five lines of code, you can build a knowledge graph with your data.

When you see the results, you'll never go back to vector-mediocrity-land.

Here is a quick video:
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• Easy to use
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Here is a link to the repository: github.com/topoteretes/co…Image
Here is the paper explaining how Cognee works and achieves these results:

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May 26
Cursor, WindSurf, and Copilot suck with Jupyter notebooks. They are great when you are writing regular code, but notebooks are a different monster.

Vincent is an extension fine-tuned to work with notebooks.

10x better than the other tools!

Here is a quick video:
You can try Vincent for free. Here is a link to the extension:



It works with any of the VSCode forks, including Cursor and Windsurf. The free plan will give you enough to test it out.marketplace.visualstudio.com/items?itemName…
The extension will feel familiar to you:

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