list of useful methods of itertools module.

permutations
combinations
combinations_with_replacement
zip_longest
count
repeat
cycle
accumulate
product
groupby
tee
isslice
chain
chain.from_iterable
filterfalse
dropwhile

https://realpython.com/python-itertools/

program creek seems to be a good site for handy references of python modules. For e.g. when I wanted to know how to use Stratified Shuffle module, the examples shown on this page were very useful.

https://www.programcreek.com/python/example/91149/sklearn.model_selection.StratifiedShuffleSplit

This code will change the standard out to a file so that jupyter notebook cell's responses are saved to a file.

import sys
oldStdout = sys.stdout
file = open('logFile', 'w')
sys.stdout = file

First start ipython in cluster mode

ipcluster start -n 4

from IPython.parallel import Client
rc = Client()
v=rc.load_balanced_view()
@v.parallel(block=True)
def f(x): return 2*x
result = f.map(range(10))
print("Using a parallel function: ", result)

You may see this message if you have DEBUG = True in your Django settings file and you haven't configured any URLs.

django-admin.py startproject todo

python manage.py runserver localhost:8000

$$   If you plan to use a database, edit the DATABASES setting in todo/settings.py.
python manage.py startapp todoapp

$$ syncdb and flush are other 2 parameters accepted by manage.py

This is the python way of calculating the date that is 14 days ago.

import datetime
(datetime.datetime.now() - datetime.timedelta(days = 14)).date()

And this is pandas way of getting the same results:

import pandas as pd
(pd.datetime.today() - pd.offsets.Day(14)).floor('D')

apt-get update && apt-get upgrade
mkdir -p /usr/share/man/man1
apt-get install default-jdk
apt install openjdk-11-jdk

from itertools import groupby
s = 'abcccccbba'

for w, v in groupby(s):
print (''.join(w), ''.join(v))

a a
b b
c ccccc
b bb
a a

module for google search

!pip install google

from googlesearch import search
for url in search('"Breaking Code" WordPress blog', stop=10):
print(url)

1) Download the polyglot pickled marathi model
wget http://bit.ly/12FI1xV
mv 12FI1xV polyglot-mt.pkl

2) Extract all the words from the embedding

from polyglot.mapping import Embedding
embeddings=Embedding.load("polyglot-mt.pkl")
with open('myfile.txt', 'w') as fx:
for i in embeddings.vocabulary:
fx.write(i.encode('utf-8')+'\n')

3) Download the wordlist:
https://s3.amazonaws.com/gamabhana/wiki_wordlist.txt