ma7dev

#!/bin/bash

# TODO: you will need to have conda installed

# create a python environment
conda create -n env_tmp python=3.8.13 -y

# activate environment
conda activate env_tmp

ptmcg

import rich.progress
import rich.spinner
import time
import random


class RandomChars(rich.progress.ProgressColumn):
    """Simulation of computer 'thinking' by displaying random characters
    Args:
        chars (str): characters from which to choose for display. Defaults to 0-9A-F.

parente

Summary

The %run magic provided by IPython not only supports the execution of regular Python scripts, it also runs Jupyter Notebook files (.ipynb).

Example

The run_demo.ipynb notebook below uses %run to execute all of the cells in reusable_stuff.ipynb. Once it does, both globals defined in reusable_stuff are available in run_demo for use.

fomightez

import time

def executeSomething():
    #code here
    print ('.')
    time.sleep(480) #60 seconds times 8 minutes

while True:
    executeSomething()

thomasp85

library(magick)
library(reshape2)
library(dplyr)
library(tidygraph)
library(particles)
library(animation)

plot_fun <- function(sim) {
  df <- as_tibble(sim)
  plot(df$x, df$y, col = df$color, pch = '.', axes = FALSE, xlim = c(-100, 317), ylim = c(-268, 100), xlab = NA, ylab = NA)

fomightez

# These are meant to work in both Python 2 and 3, except where noted.

# See my useful_pandas_snippets.py for those related to dataframes (such as pickling/`df.to_pickle(save_as)`)
# https://gist.github.com/fomightez/ef57387b5d23106fabd4e02dab6819b4
# also see https://gist.github.com/fomightez/324b7446dc08e56c83fa2d7af2b89a33 for examples of my 
# frequently used Python functions and slight variations for more expanded, modular structures.


#argparse
# good snippet collection at https://mkaz.tech/code/python-argparse-cookbook/

astrojuanlu

download_kegg.sh

# Get a list of all organisms
curl -s  "http://rest.kegg.jp/list/organism"  > organisms-all.txt

# Get just a few of interest
cat organisms-all.txt | awk '$2~/^(hsa|mmu|rno|cfa|bta|gga|xla|xtr|dre|dme|cel|ath|ehi|tgo|eco|sau|mtu|mav|cje|ccol)$/' > organisms-of-interest.txt

# Get the accession codes for each
cut -f1 organisms-of-interest.txt > organisms-of-interest-codes.txt

# Make a directory to put all the kgml files downloaded

evanmiltenburg

import matplotlib.pyplot as plt
import seaborn as sns

from matplotlib.lines import Line2D

my_palette = sns.color_palette("cubehelix", 3)
sns.set_palette(my_palette)

def legend_circles(labels, palette, loc=1, markersize=10, marker='o', padding=0):
    "Make a legend where the color is indicated by a circle."

fomightez

# List unique values in a DataFrame column
df['Column Name'].unique()

# To extract a specific column (subset the dataframe), you can use [ ] (brackets) or attribute notation.
df.height
df['height']
# are same thing!!! (from http://www.stephaniehicks.com/learnPython/pages/pandas.html 
# -or-
# http://www.datacarpentry.org/python-ecology-lesson/02-index-slice-subset/)