elyasha

sudo apt update && sudo apt upgrade

sudo apt install build-essential default-jdk libssl-dev exuberant-ctags ncurses-term ack-grep silversearcher-ag fontconfig imagemagick libmagickwand-dev software-properties-common git vim-gtk3 curl lib32readline-dev sqlite3 libsqlite3-dev

sudo apt install postgresql postgresql-contrib redis-server libhiredis-dev memcached libmemcached-dev

sudo apt install zlib1g-dev libffi-dev libbz2-dev libreadline-dev libpq-dev bzip2

elyasha

Software Name as Headline
======
**Software Name** is a software for things. Short description here.

#### Screenshot
![Screenshot software](http://url/screenshot-software.png "screenshot software")

## Download
* [Version X.Y](https://github.com/username/sw-name/archive/master.zip)
* Other Versions

elyasha

Script Name as Headline
======
**Script Name** is a script for things. The usage is explained like this:

```
$ ./script parameter1 .. parameterN
 Output
$ 
```
## Version 

elyasha

# Microsoft apps 
- OneDrive
- Office 365 (+ Grammarly for Office)
- To do
- Edge Chromium
- Project
- Teams
- Lync
- Other

elyasha

sudo apt update && sudo apt upgrade

sudo apt install build-essential default-jdk libssl-dev exuberant-ctags ncurses-term fontconfig software-properties-common git curl lib32readline-dev sqlite3 libsqlite3-dev

sudo apt install postgresql postgresql-contrib memcached libmemcached-dev

sudo apt install zlib1g-dev libffi-dev libbz2-dev libreadline-dev

elyasha

celery -A proj worker -l INFO -P gevent -E

elyasha

os.environ.setdefault('FORKED_BY_MULTIPROCESSING', '1')

elyasha

# Define your functions
def print_message():
  print("I'm sorry, I did not understand your selection. Please enter the corresponding letter for your response.")

def get_drink_type():
  res = input('What type of drink would you like? \n[a] Brewed Coffee \n[b] Mocha \n[c] Latte \n> ')
  if res == "a":
    return "brewed coffee"
  elif res == "b":
    return "mocha"

elyasha

# regex for removing punctuation!
import re
# nltk preprocessing magic
import nltk
from nltk.tokenize import word_tokenize
from nltk.stem import PorterStemmer
from nltk.stem import WordNetLemmatizer
# grabbing a part of speech function:
from part_of_speech import get_part_of_speech

elyasha

import spacy
from nltk import Tree
from squids import squids_text

dependency_parser = spacy.load('en')

parsed_squids = dependency_parser(squids_text)

# Assign my_sentence a new value:
my_sentence = "I am learning Parsing Text"