Python  Library

Python Library


Collaborate | Web-based Collaboration tool Written in Python


This is a web application for managing and building stories based on tips solicited from the public. This project is meant to be easy to setup for non-programmer, intuitive to use and highly extendable.

Here are a few use cases:

  • Collection of data from various sources (Google Form via Google Sheets, Screendoor, Private Google Spreadsheets)
  • An easy to setup data entry system
  • Organizing data from multiple sources and allowing many users to view and annotate it

The project is broken up into several components:

  • A system for transforming CSV files into managed database records
  • A default and automatic Django admin panel built for rapid and easy editing, managing and browsing of data
  • Customizable fields for tagging, querying, annotating and tracking tips

This is a project of ProPublica, supported by the Google News Initiative.


We have a GitBook with a full user guide that covers running Collaborate, importing and refining data, and setting up Google services. You can read the documentation here.

Getting Started (Local Testing/Development)

Getting the system set up and running locally begins with cloning this repository and installing the Python dependencies. Python 3.6 or 3.7 and Django 2.2 are assumed here.

# virtual environment is recommended
mkvirtualenv -p /path/to/python3.7 collaborative
# install python dependencies
pip install -r requirements.txt

Assuming everything worked, let's bootstrap and then start the local server:

# get the database ready
python migrate

# create a default admin account
python createsuperuser

# gather up django and collaborate assets
python collectstatic --noinput

# start the local application
python runserver

You can then access the application http://localhost:8000 and log in with the credentials you selected in the createsuperuser step (above). Logging in will bring you to a configuration wizard where you will import your first Google Sheet and import its contents.

Production Deploy (Nginx/Docker)

If you want to deploy this to a production environment, we've included configuration templates and scripts for Docker and Nginx.

A Collaborate Dockerfile (the same one used by the Google Cloud Run deploy) can be found here:


This creates a basic production environment with nginx and gunicorn. By default, it uses SQLite3, but you can configure the database by adding a DATABASE_URL environment variable. You can read more about the format for this variable here.

We also included a configuration script for plain Nginx deploys here:


This can be copied to your main Nginx sites configuration directory (e.g., /etc/nginx/sites-available/).

In order to get auto-updating data sources, make sure to add a cron job that runs the following command: refresh_data_sources

There's an example cron file that, when added to your /etc/crontab, will update data every 15 minutes:


Note that if you use the above example, you probably want to add logrotate for the logfile the above cron config adds. You can find the logrotate script here (add it to /etc/logrotate.d/refresh_data_sources):


Deploy it

Collaborate has builtin support for one-click installs in both Google Cloud and Heroku. During the setup process for both deployments, make sure to fill in the email, username and password fields so you can log in.



The Heroku deploy button will create a small, "free-tier" Collaborate system. This consists of a small web server, a database which supports between 10k-10M records (depending on data size) and automatically configures scheduled data re-importing.

Google Cloud

Run on Google Cloud

The Google Cloud Run button launches Collaborate into the Google Cloud environment. This deploy requires you to setup a Google Project, enable Google Cloud billing and enable the Cloud Run API. Full set up instructions are here.

This deploy does not automatically configure scheduled re-importing, but you can add it via Cloud Scheduler by following these instructions.

Once you've deployed your Cloud Run instance, you can manage your running instance from the Google Developer's Console.

Download Details:
Author: propublica
Source Code:
License: MIT license


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Collaborate | Web-based Collaboration tool Written in Python
Ray  Patel

Ray Patel


Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

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Ray  Patel

Ray Patel


Advance Web Penetration Testing Tool For Python

Features 🎭

Admin Panel Finder

Admin Scanner

Dork Generator

Advance Dork Finder

Extract Links

No Redirect

Hash Crack (Online-Database)

Hash Crack (Wordlist)

Whois Lookup

Tcp Port Scan

Geo IP Lookup

Reserve Analysts Search

Csrf Vernavility Checker


WordPress Username Finder

#testing #advance web penetration testing tool for python #python #advance web penetration #testing tool for python #web

Shardul Bhatt

Shardul Bhatt


Why use Python for Software Development

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas. 

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities. 

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly. 

5 Reasons to Utilize Python for Programming Web Apps 

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

Robust frameworks 

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions. 

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events. 

Simple to read and compose 

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building. 

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties. 

Utilized by the best 

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player. 

Massive community support 

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions. 

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking. 

Progressive applications 

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.


Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential. 

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

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Arvel  Parker

Arvel Parker


Basic Data Types in Python | Python Web Development For Beginners

At the end of 2019, Python is one of the fastest-growing programming languages. More than 10% of developers have opted for Python development.

In the programming world, Data types play an important role. Each Variable is stored in different data types and responsible for various functions. Python had two different objects, and They are mutable and immutable objects.

Table of Contents  hide

I Mutable objects

II Immutable objects

III Built-in data types in Python

Mutable objects

The Size and declared value and its sequence of the object can able to be modified called mutable objects.

Mutable Data Types are list, dict, set, byte array

Immutable objects

The Size and declared value and its sequence of the object can able to be modified.

Immutable data types are int, float, complex, String, tuples, bytes, and frozen sets.

id() and type() is used to know the Identity and data type of the object







Built-in data types in Python

a**=str(“Hello python world”)****#str**














Numbers (int,Float,Complex)

Numbers are stored in numeric Types. when a number is assigned to a variable, Python creates Number objects.

#signed interger




Python supports 3 types of numeric data.

int (signed integers like 20, 2, 225, etc.)

float (float is used to store floating-point numbers like 9.8, 3.1444, 89.52, etc.)

complex (complex numbers like 8.94j, 4.0 + 7.3j, etc.)

A complex number contains an ordered pair, i.e., a + ib where a and b denote the real and imaginary parts respectively).


The string can be represented as the sequence of characters in the quotation marks. In python, to define strings we can use single, double, or triple quotes.

# String Handling

‘Hello Python’

#single (') Quoted String

“Hello Python”

# Double (") Quoted String

“”“Hello Python”“”

‘’‘Hello Python’‘’

# triple (‘’') (“”") Quoted String

In python, string handling is a straightforward task, and python provides various built-in functions and operators for representing strings.

The operator “+” is used to concatenate strings and “*” is used to repeat the string.


output**:****‘Hello python’**

"python "*****2

'Output : Python python ’

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sophia tondon

sophia tondon


Hire Python Developer | Python web development company india

Are you looking to hire Python developers online? ValueCoders provide dedicated and certified Python engineers who are proficient in building robust, secure & scalable web applications utilizing the best Python development strategies.

Visit Website -

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