Python Weekly Issue 427

Python Weekly

Welcome to issue 427 of Python Weekly. Let's get straight to the links this week. From Our Sponsor  Python developers are in demand on Vettery Vettery is an online hiring marketplace that's changing the way people hire and get hired. Ready for a bold career move? Make a free profile, name your salary, and connect with hiring managers from top employers today. News OpenMined and PyTorch partner to launch fellowship funding for privacy-preserving ML community The PyTorch team has invested $250,000 to support OpenMined in furthering the development and proliferation of privacy-preserving ML and there are three different opportunities for you to participate in the project’s development. Each of these fellowships furthers our shared mission to lower the barrier-to-entry for privacy-preserving ML and to create a more privacy-preserving world. Articles, Tutorials and Talks Bootstrapping Understanding: An Introduction to Reverse Engineering Reverse engineering an unfamiliar data file could be described as the bootstrapping of understanding. In many ways the process resembles the scientific method, only applied to human-made, abstract objects instead of the natural world. You begin by gathering data, and then you use that information to put forth one or more hypotheses. You test the hypotheses, and use the outcome of those tests to refine them. Repeat as needed. Developing skills in reverse engineering is largely a matter of practice. Through an accumulation of experiences, you build up an intuition of where to investigate first, what patterns to look for, and what tools to keep handy. This post walks through the process of reverse-engineering some data files from an old computer game, in order to show you a little bit of how it's done. Python Tips and Trick, You Haven't Already Seen There are plenty of articles written about lots of cool features in Python such as variable unpacking, partial functions, enumerating iterables, but there is much more to talk about when it comes to Python, so here I will try to show some of the features I know and use, that I haven't yet seen mentioned elsewhere. Part 2 - Here comes another round of Python features that you hopefully haven't seen yet. How a Data Scientist Buys Extended Warranties A Deep-Dive look at the Math of “Extended Warranties” Controlling Text Generation with Plug and Play Language Models Uber AI's Plug and Play Language Model gives NLP practitioners the flexibility to plug simple attribute models into a large, unconditional language model. A comprehensive guide to OCR with Tesseract, OpenCV and Python A comprehensive tutorial on getting started with Tesseract and OpenCV for OCR in Python: preprocessing, deep learning OCR, text extraction and limitations. 15 Insights for Managing Data Science Teams A collection of insights and recommendations to help data and analytics leaders overcome the challenges of hiring and managing data science teams. This Gartner report is provided by Domino Data Lab. SPONSOR Plotnine: Grammar of Graphics for Python A translation of the visualisation chapters from “R for Data Science” to Python using Plotnine and Pandas. Writing a Python ORM for Redis An elegant way to store instances in Redis. Django 3.0 Full Course For Beginners  Doing Python Configuration Right North Bay Python 2019 Videos  shrynk - Using Machine Learning to learn how to Compress Monads aren't as hard as you think Interesting Projects, Tools and Libraries AI Dungeon 2 AI Dungeon 2 is a completely AI generated text adventure built with OpenAI's largest GPT-2 model. It's a first of it's kind game that allows you to enter and will react to any action you can imagine. Mario: Shell pipes in Python Have you ever wanted to use Python functions directly in your Unix shell? Mario can read and write csv, json, and yaml; traverse trees, and even do xpath queries. Plus, it supports async commands right out of the box. Build your own commands with a simple configuration file, and install plugins for even more! Informer A Telegram Mass Surveillance Bot in Python. awspx A graph-based tool for visualizing effective access and resource relationships in AWS environments. Pixcryption Pixcryption's goal is to offer a new form of steganography/encryption through imagery. It uses a random seeded UUID to generate a user_key which matches RGB perfect values to match to unicode characters. These are stored in a user_key.png file which is used to encrypt and decrypt messages. PyFlow Visual scripting framework for Python. pydeps Python module dependency visualization. video-to-pose3D Convert video to 3D pose in one-key. omnibot A Slack proxy, and Slack bot framework. GoCheese A Python private package repository and caching proxy. Horology Conveniently measures time of your for-loops, contexts and functions. Maze-Generator A script that generates randomized mazes/labrynths. Invented by accident. SparkTorch Train and run Pytorch models on Apache Spark. django_vue_generator Generates vue frontend structure for django rest framework projects. Generates forms(validated with vuelidate) for your serializers and viewsets and methods to call api via vue-resource. PyTorch Elastic PyTorch Elastic (torchelastic) is a framework that enables distributed training jobs to be executed in a fault tolerant and elastic manner. blender-tools A Blender add-on containing workflow tools for game development. New Releases Python 3.8.1rc1 Upcoming Events and Webinars Presentation Night @ Boston Python Meetup - Cambridge, MA There will be following talks  Python Optimization Options Extending Python with Rust Optimized human learning - London, UK Spaced repetition, the testing of knowledge over a period of time, is one of the most important tools we know of in the science of learning. Modern technology, in the form of spaced repetition software like Anki, promise to take this to the next level by offering personalized learning schedules for each individual learner — but often underdeliver. In this talk, Jacob Puthipiroj walks through an implementation of spaced repetition scheduling via machine learning, the first of its kind in a commercially available software. Lightning Talks @ NYC PyLadies - New York, NY PyHou Meetup December 2019 - Houston, TX San Diego Python Meetup December 2019 - San Diego, CA LjPyMeetup December 2019 - Ljubljana, Slovenia Source : https://mailchi.mp/pythonweekly/python-weekly-issue-427?e=a27cb03609 Python Weekly <rahul@pythonweekly.com>

Guide to Encoding Categorical Values in Python - Practical Business Python

https://pbpython.com/categorical-encoding.html

Questions for Assignment Test

1.What is socket ? Explain how socket connection can be established to the internet using Python code over the TCP/IP connection and the http protocol to get the web document.

2.Explain the significance of XML over the web development. Illustrate with an example.

3.Write a note on Google Geocoding web service . Using Python supported libraries , demonstrate with a snippet code.

4.What is embedded SQL? Explain the importance of SQLite database . Write a Python code to establish a database connection to ‘EmpDb’ and display the total gross salary paid to the employees working in the “Quality Control department. Assume the employee table has been already created and exist in the “EmpDb”.The fields of Employee table are : ( EmpID, DepName, GrossSalary)

PYTHON SEMINAR TOPICS

PYTHON ASSIGNMENT : LAST DATE 25th APRIL 2019

ASSIGNMENT  2

Subject: Python Application Program

Subject Code: 15CS664

SEM: VI DIV: B

Type: Open book Written Assignment   

Dead Line:  Before April 25^th 2019

Assignment Questions:

1. Define and Compare List, Dictionary and Tuples. Write the answer in the following format:

	List	Dictionary	Tuple
Definition
Empty
Single element
Five Elements
Example for Accessing

2

   Explain with examples the different ways to create a list. Why lists are called Mutable. Discuss the following List operations and functions with examples: Traversing , Slicing , + (concatenation) ,   * (Repetition) , append , extend , sort , remove , delete , len , sum, min , max , split and join .

3 Differentiate between Key and value of the Dictionary element. Mention the properties of Key .  Discuss the following Dictionary operations and functions with examples: Accessing , Traversing using loop , Updating and  Deleting

4 Compare Tuple with list. Discuss the following tuple operations and functions with examples:  Accessing ,  Updating , Deleting , Traversing (Iteration) , Comparing , len ,(in) membership ,  + (concatenation) ,   * (Repetition) and DSU (Decorate , Sort and Undecorate ) pattern

5 Discuss the Tuple Assignment with example . Write a Python program to input two integers a  and  b , and swap those numbers . Print both input and swapped numbers

6 With example program illustrate how the Dictionary can be used to count the occurrence of words in a file.

Faculty In charge                                                                                            

Python Question Paper June/July 2018

Why Should you learn Programming ( to write Programs) ?

1. It is Creative and Rewarding Activity. (Programming Skills + Power of Imagination = Creativity )
2. It teaches how to think 
3. It is used to solve Realtime Problems 
4. To create Website , Mobile Apps and Desktop Apps
5. To digitize our Ideas ( To express our ideas digitally)
6. It can scale its problem solving capabilities .
7. No shortage of Jobs in Programming 
8. To create user interface to interact with machines.
9. To design  Games
10. To earn Money 
11. To perform Data Analysis 
12. A programmer will subconsciously pick up problem Solving skills 
    

Python Features

• Python is Interpreted 
• Python is Interactive 
• Python is Object-Oriented 
• Python is a Beginner's Language 
• Easy-to-learn
• Easy-to-read 
• Easy-to-maintain 
• A broad standard library 
• Interactive Mode 
• Portable 
• Extendable 
• Databases 
• GUI Programming 
• Scalable 
• Supports functional and structured programming methods as well as OOP.
• Can be  used as a scripting language 
• Provides very high-level dynamic data types and supports dynamic type checking.
• Supports automatic garbage collection.
• Can be easily integrated with C, C++, COM, ActiveX, CORBA, and Java.