Skip to content

Instantly share code, notes, and snippets.

View moandcompany's full-sized avatar
💭
Meow

Andrew Mo moandcompany

💭
Meow
  • Mo and Company
  • Internet
View GitHub Profile
@veekaybee
veekaybee / normcore-llm.md
Last active September 3, 2025 21:15
Normcore LLM Reads

Anti-hype LLM reading list

Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.

Foundational Concepts

Screenshot 2023-12-18 at 10 40 27 PM

Pre-Transformer Models

@bearfrieze
bearfrieze / comprehensions.md
Last active June 11, 2025 03:12
Comprehensions in Python the Jedi way

Comprehensions in Python the Jedi way

by Bjørn Friese

Beautiful is better than ugly. Explicit is better than implicit.

-- The Zen of Python

I frequently deal with collections of things in the programs I write. Collections of droids, jedis, planets, lightsabers, starfighters, etc. When programming in Python, these collections of things are usually represented as lists, sets and dictionaries. Oftentimes, what I want to do with collections is to transform them in various ways. Comprehensions is a powerful syntax for doing just that. I use them extensively, and it's one of the things that keep me coming back to Python. Let me show you a few examples of the incredible usefulness of comprehensions.

@vasanthk
vasanthk / System Design.md
Last active September 3, 2025 23:11
System Design Cheatsheet

System Design Cheatsheet

Picking the right architecture = Picking the right battles + Managing trade-offs

Basic Steps

  1. Clarify and agree on the scope of the system
  • User cases (description of sequences of events that, taken together, lead to a system doing something useful)
    • Who is going to use it?
    • How are they going to use it?
@why-not
why-not / gist:4582705
Last active June 21, 2025 06:24
Pandas recipe. I find pandas indexing counter intuitive, perhaps my intuitions were shaped by many years in the imperative world. I am collecting some recipes to do things quickly in pandas & to jog my memory.
"""making a dataframe"""
df = pd.DataFrame([[1, 2], [3, 4]], columns=list('AB'))
"""quick way to create an interesting data frame to try things out"""
df = pd.DataFrame(np.random.randn(5, 4), columns=['a', 'b', 'c', 'd'])
"""convert a dictionary into a DataFrame"""
"""make the keys into columns"""
df = pd.DataFrame(dic, index=[0])
@ibeex
ibeex / foo.log
Created August 4, 2012 13:46
Flask logging example
A warning occurred (42 apples)
An error occurred