henrik

tmux cheatsheet

As configured in my dotfiles.

start new:

tmux

start new with session name:

MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

Atem18

Set up Django, Nginx and Gunicorn in a Virtualenv controled by Supervisor

Steps with explanations to set up a server using:

• Virtualenv
• Virtualenvwrapper
• Django
• Gunicorn

JustinTArthur

from django.views.decorators.csrf import csrf_exempt

@csrf_exempt
def reverse_proxy(request):
    """
    Reverse proxy for a remote service.
    """
    path = request.get_full_path()
    #Optionally, rewrite the path to fit whatever service we're proxying to.
    

nlothian

Taken from https://web.archive.org/web/20130517134339/http://bulba.sdsu.edu/jeanette/thesis/PennTags.html (since the source document now appears to be offline)

Penn Treebank II Tags

Note: This information comes from "Bracketing Guidelines for Treebank II Style Penn Treebank Project" - part of the documentation that comes with the Penn Treebank.

Contents:

Bracket Labels
Clause Level

alvations

NLTK API to Stanford NLP Tools compiled on 2015-12-09

Stanford NER

With NLTK version 3.1 and Stanford NER tool 2015-12-09, it is possible to hack the StanfordNERTagger._stanford_jar to include other .jar files that are necessary for the new tagger.

First set up the environment variables as per instructed at https://github.com/nltk/nltk/wiki/Installing-Third-Party-Software

dannguyen

Using Python 3 + Google Cloud Vision API's OCR to extract text from photos and scanned documents

Just a quickie test in Python 3 (using Requests) to see if Google Cloud Vision can be used to effectively OCR a scanned data table and preserve its structure, in the way that products such as ABBYY FineReader can OCR an image and provide Excel-ready output.

The short answer: No. While Cloud Vision provides bounding polygon coordinates in its output, it doesn't provide it at the word or region level, which would be needed to then calculate the data delimiters.

On the other hand, the OCR quality is pretty good, if you just need to identify text anywhere in an image, without regards to its physical coordinates. I've included two examples:

####### 1. A low-resolution photo of road signs

miguelgrinberg

import asyncio
loop = asyncio.get_event_loop()

async def hello():
    await asyncio.sleep(3)
    print('Hello!')
    
if __name__ == '__main__':
    loop.run_until_complete(hello())
    

rafaelhdr

# Reason for choosing cherrypy
# https://blog.appdynamics.com/engineering/a-performance-analysis-of-python-wsgi-servers-part-2/
#
# Flask application based on Quickstart
# http://flask.pocoo.org/docs/0.12/quickstart/
#
# CherryPy documentation for this
# http://docs.cherrypy.org/en/latest/deploy.html#wsgi-servers
# http://docs.cherrypy.org/en/latest/advanced.html#host-a-foreign-wsgi-application-in-cherrypy
# Install: pip install cherrypy

meain

# post_loc.txt contains the json you want to post
# -p means to POST it
# -H adds an Auth header (could be Basic or Token)
# -T sets the Content-Type
# -c is concurrent clients
# -n is the number of requests to run in the test

ab -p post_loc.txt -T application/json -H 'Authorization: Token abcd1234' -c 10 -n 2000 http://example.com/api/v1/locations/