Magnus167

[alias]
	pr = "!f() { BRANCH=$(git branch --show-current); REPOURL=$(git config --get remote.origin.url); python ~/Code/work_HK/getpr.py $REPOURL $BRANCH; }; f"

Magnus167

import json
import urllib.request
import sys
import os

# get repo and branch from sys.argv
if len(sys.argv) < 3:
    print("Usage: python getpr.py <repo> <branch>")
    sys.exit(1)

Magnus167

# Usage:
# git checkout featureX
# git pmerge main

# When merging branch `main` into `featureX`, 
# one often has to pull from `main` to ensure 
# merging into the correct head.
# Assume you're on branch featureX
# >> git pmerge main
# executes:

Magnus167

# load commit_data.csv
from typing import List, Optional

import pandas as pd

df = pd.read_csv("commit_data.csv")

# filter where username is Palash Tyagi or Spalash

df = df[(df["username"] == "Palash Tyagi") | (df["username"] == "Spalash")]

Magnus167

In a nutshell, what is a Monte Carlo simulation anyway?

Monte Carlo simulations are typically used to get estimates of results, when the actual problem is too vast to be solved in entirety (or in a reasonable amount of time).

There are 3 examples, each closer to the real world version than the last. Example 1 is the best 😄

Example 1: Estimating the number of potholes in London

Magnus167

# adapted from https://matplotlib.org/stable/gallery/animation/double_pendulum.html#sphx-glr-gallery-animation-double-pendulum-py
from numpy import sin, cos
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from collections import deque

G = 9.8  # acceleration due to gravity, in m/s^2
L1 = 1.0  # length of pendulum 1 in m
L2 = 1.0  # length of pendulum 2 in m

Magnus167

#include <stdio.h>
#include <string.h>

#define MAX 256
#define INT_BITS 32

void countingSort(int arr[], int n, int exp) {
    int output[n]; // output array
    int i, count[MAX] = {0};

Magnus167

"""
Scans Jupyter Notebooks for functions used from a given package.
The return 
"""
from typing import List, Dict, Set, Tuple, Type, Callable
import ast

# import functools
import glob
import nbformat

Magnus167

NOTICE:

TLDR : Not my original work, I copied it over as I needed it to be in markdown formatting.

This is not my own content, and is merely curated here for accessibilty and sharing. The below article has been copied from https://www.joelsleppy.com/blog/gunicorn-application-preloading/, with all rights to intellectual property reserved by the authors/domain-owners.

Gunicorn Application Preloading

Magnus167

import copy

original_list = [[1, 1, 1], [2, 2, 2], [3, 3, 3]]

list_a = original_list
original_list[0][0] = "a"
assert list_a[0][0] == "a"

list_b = copy.deepcopy(original_list)
original_list[0][0] = "b"