Book Image

Getting Productive with Modern Python [Video]

By : Rahul Tiwari
Book Image

Getting Productive with Modern Python [Video]

By: Rahul Tiwari

Overview of this book

<p><span id="description" class="sugar_field">Python is simple, but it isn't easy. Python emphasizes code readability, using indentation and whitespaces to create code blocks. This makes it simpler than C++ or Java, where curly braces and keywords are scattered across the code. Python is high-level, which allows programmers like you to create logic with fewer lines of code.<br /></span></p> <p><span id="description" class="sugar_field">This course follows a problem-solution format to tackle common roadblocks in Python programming. How can we handle large datasets and files, processing them in Python efficiently? How can we address performance issues for long-running tasks? <br /></span></p> <p><span id="description" class="sugar_field">There is no other course that can transform every corner of your Python code. After going through the course, you will be confident enough to use Python for your large-scale applications and will perform tasks faster and more effective.<br /></span></p> <p><span id="description" class="sugar_field">All the code and supporting files are available on GitHub at - <a href="https://github.com/PacktPublishing/Getting-Tricky-with-Modern-Python" target="_new">https://github.com/PacktPublishing/Getting-Tricky-with-Modern-Python</a></span></p> <h1><span class="sugar_field">Style and Approach</span></h1> <p><span class="sugar_field"><span id="trade_selling_points_c" class="sugar_field">A friendly course packed with step-by-step instructions, working examples, and helpful advice. This extensive course is divided into small bits so you can learn at your own pace and focus on the areas of most interest to you.</span></span></p>
Table of Contents (6 chapters)
Chapter 3
Figuring Out Why Your Program Is Slow with Timeit and Profile
Content Locked
Section 2
Figuring Out Where Time Is Spent with the Profile Module
In this video, we will identify how Python source consumes time and how parts of your code take the longest with profiler module. - Logic behind built-in profiler, cProfiler - Use run() to calculate time spent executing code - Create program using cProfile