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Python Tips, Tricks & Techniques[Video], published by Packt

Python Tips, Tricks and Techniques [Video]

This is the code repository for Python Tips, Tricks and Techniques [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.

About the Video Course

You have been programming in Python and you know that Python is easy to get started with, but hard to get right. You want to write Python code to make an impact in both the open source arena and your career. No other course can transform every corner of your Python code. Take this course NOW and become an overnight Python rockstar developer.

The course is full of hands-on instructions, interesting and illustrative visualizations, and clear explanations. It is packed full of useful tips and relevant advice which can be applied to real, commercial products. Throughout the course, we maintain a focus on practicality and getting things done, not fancy programming concepts and theory.

What You Will Learn

  • Master lists and list comprehension to write less clunky for loops.
  • Learn to use dictionaries in a smarter way to keep track of your application's state.
  • Save time writing custom subclasses by learning new data structures built right into Python.
  • Use functional programming concepts in Python to make your code more compact
  • Smartly organize your code and make it more readable with OOP
  • Evolve into a seasoned Python developer with top Pythonic tips

Instructions and Navigation

Assumed Knowledge

To fully benefit from the coverage included in this course, you will need:
This course is aimed at Python developers who want to make their code clean and Pythonic to steal a march on the average coder. Developers who have moved to Python from a different language will also benefit from this course. Some prior Python programming experience is assumed.

Technical Requirements

This course has the following software requirements:
SETUP AND INSTALLATION Minimum Hardware Requirements For successful completion of this course, students will require the computer systems with at least the following:

OS: Windows 7 SP1 64-bit, Windows 8.1 64-bit or Windows 10 64-bit

Processor: Intel Core i5 or equivalent

Memory: 8 GB RAM

Storage: 35 GB available space

Recommended Hardware Requirements For an optimal experience with hands-on labs and other practical activities, we recommend the following configuration:

OS: Windows 7 SP1 64-bit, Windows 8.1 64-bit or Windows 10 64-bit

Processor: Intel Core i7 or equivalent

Memory: 8GB RAM

Storage: 35 GB available space

Software Requirements

OS: Windows 7 or Windows 10

Browser: Google Chrome, Latest Version

Code Editor: Atom IDE, Latest Version

Others: Python3 installed using the Anaconda package or equivalent, Tensorflow r1.4

Exercise Files

Exercise files should have a start and an end state for each video that contains a demonstration of code.

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