Here is the list of some of the modules used for audio-visual processing using deep learning.

chroma: Feature Learning for Chord Recognition: The Deep Chroma Extractor
MFCC: Mel-frequency cepstral coefficients (MFCCs) are coefficients that collectively make up an MFC
TCD-TIMIT: An Audio-Visual Corpus of Continuous Speech
librosa
RBF: Radial Basis Function
HMM: Hidden Markov Model
VGG: Resnet 50
voxceleb-luigi: Luigi pipeline to download VoxCeleb audio from YouTube and extract speaker segments
deepfakes
obamanet
yolo

module for google search

!pip install google

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

from datetime import datetime
date_string = "21 June, 2018"
date_object = datetime.strptime(date_string, "%d %B, %Y")

This will return the mixed datatypes but this can be slow.

df.applymap(type).nunique() > 1

Better approach pythonic approach would be...

from pandas.api.types import infer_dtype

infer_dtype(df.A)
'mixed-integer'

df.apply(lambda x: 'mixed' in infer_dtype(x))

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

Google suddenly stopped download of Input Tools package without giving any reason. And here is official response by Google:
We have been in touch with the Google Input Tools team and have confirmed that the Windows application is no longer available for download or installation. Instead, the team recommends you install the Google Input Tools Chrome extension as an alternative.

This is not expected from a company like google.

Here are important python objects and their methods
int __mul__, __add__, __eq__, __ge__, __mod__, __pow__
float .is_integer()
string .upper(), .endswith(), .split()
bool .numerator .__abs__()
list .append, .pop, __len__() / slicing
tuple
dict .items(), .keys(), .values() / slicing
pd.Series .sum(), .stack(), .groupby(), .resample(), .sort_values(), .sort_index(), .iloc
pd.DataFrame

Here is how to read a JSON file into pandas dataframe.

import json
import pandas as pd

with open('/tmp/aclImdb/movie_data/gv.json', 'r') as f:
data = json.load(f)

df=pd.DataFrame(data['data'])
df.to_excel('gov.xlsx')

Fabric is a high level Python library designed to execute shell commands remotely over SSH, yielding useful Python objects in return:
"""
a#!/usr/bin/env python
from fabric.api import hosts, run, task
from fabric.tasks import execute

@task
@hosts(['shantanu@1.2.3.4:1224'])
def test():
run('hostname -f')

if __name__ == '__main__':
execute(test)
"""

It is easy to backup mysql users -

wget percona.com/get/pt-show-grants;
perl pt-show-grants