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[FreeCoursesOnline.Me] [Packt] Getting Productive With Modern Python [FCO]
TORRENT SUMMARY
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Bring your Python skills into the real world. Solve production issues around databases, parallelism, and deployment
Video Details
ISBN 9781788474375
Course Length 1 hour 7 minutes
Table of Contents
• Save Your Work Over Time with Simple Databases
• Writing Cleaner Code with Advanced Comprehensions and Containers
• Figuring Out Why Your Program Is Slow with Timeit and Profile
• Do Not Wait Around for IO with Concurrent Programming
• Do Multiple Things at Once with Parallel Programming
• Creating Reusable Applications from Your Python Scripts
Learn
• Persist your work and data across time with Python databases
• Create faster and more compact applications with advanced comprehensions and containers
• Understand your program's speed and bottlenecks with profiling
• Improve the speed at which you interface with input-output channels via concurrency
• Leverage modern multithreaded CPUs with parallelism to enhance performance
• Package your Python code so you can distribute it and share it with other developers
About
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.
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?
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.
All the code and supporting files are available on GitHub at - https://github.com/PacktPublishing/Getting-Tricky-with-Modern-Python
Style and Approach
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.
Features:
• Take your skills to the next level in crucial areas of programming such as performance optimization and concurrent-processing large datasets
• Go from a Python user to Python expert by learning tips and tricks gathered from Stack Overflow, developer forums, and Python source code
• Following a problem-solution format, each video makes it easy to understand tried-and-tested solutions to solve common problems
Author
Rahul Tiwari
Colibri Digital is a technology consultancy company founded in 2015 by James Cross and Ingrid Funie. The company works to help its clients navigate the rapidly changing and complex world of emerging technologies, with deep expertise in areas such as Big Data, Data Science, Machine Learning, and Cloud Computing. Over the past few years, they have worked with some of the world's largest and most prestigious companies, including a tier 1 investment bank, a leading management consultancy group, and one of the World's most popular soft drinks companies, helping each of them to better make sense of its data, and process it in more intelligent ways. The company lives by its motto: Data -> Intelligence -> Action.
Rahul Tiwari trains and consults organizations and individuals on Business Analytics, Data Science, and Machine Learning (Using R and Python). For 12 years, he has been helping students and organizations in various domains (such as retail, telecom, life sciences, finance, and more) solve their business problems using Data Science, Business Analytics, and Machine Learning. He has implemented machine learning algorithms in R extensively. He worked on various classification and regression models for his clients using R and Python. He has a sound knowledge of statistics as well, which is very much necessary for Data Science projects.
After starting his career 12 years back in data warehousing, he moved on to the Data Science domain and held various roles. Mostly working with CTOs, key IT decision makers, and students, he has always focused on building capacity, knowledge, and solutions in Data Science, Business Analytics, and Machine Learning.
He is a certified Tableau and Teradata associate. His core expertise is in R, Python, Tableau, Power BI, and SQL.
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FILE LIST
Filename
Size
0. Websites you may like/How you can help Team-FTU.txt
237 B
01.Save Your Work Over Time with Simple Databases/0101.The Course Overview.mp4
49.8 MB
01.Save Your Work Over Time with Simple Databases/0102.Creating In-Memory and Flat File Databases with SQLite.mp4
38.2 MB
01.Save Your Work Over Time with Simple Databases/0103.Parse Unstructured Data from www with Requests and Feedparser.mp4
9.6 MB
01.Save Your Work Over Time with Simple Databases/0104.Persist Data and State with JSON Files and Pickling.mp4
6.8 MB
02.Writing Cleaner Code with Advanced Comprehensions and Containers/0201.Creating Complex Lists in One Line with Comprehensions.mp4
7 MB
02.Writing Cleaner Code with Advanced Comprehensions and Containers/0202.Quick Summary Statistics with collections.counter.mp4
8.2 MB
02.Writing Cleaner Code with Advanced Comprehensions and Containers/0203.Power Up Your Dictionaries with One Line Merges and Defaultdicts.mp4
6.5 MB
03.Figuring Out Why Your Program Is Slow with Timeit and Profile/0301.Measuring Time Between Two Lines of Code with Timeit.mp4
8.5 MB
03.Figuring Out Why Your Program Is Slow with Timeit and Profile/0302.Figuring Out Where Time Is Spent with the Profile Module.mp4
9.2 MB
03.Figuring Out Why Your Program Is Slow with Timeit and Profile/0303.Looking at Memory Consumption with Memory_profiler.mp4
5.7 MB
04.Do Not Wait Around for IO with Concurrent Programming/0401.Simple Concurrent Programming with gevent.mp4
7.6 MB
04.Do Not Wait Around for IO with Concurrent Programming/0402.IOLoop Driven Concurrency with Tornado.mp4
3.8 MB
04.Do Not Wait Around for IO with Concurrent Programming/0403.Native Python Concurrency with Asyncio.mp4
11.5 MB
05.Do Multiple Things at Once with Parallel Programming/0501.Easily Speed Up a Group of Processes with Pool.mp4
5.3 MB
05.Do Multiple Things at Once with Parallel Programming/0502.Stop Processes from Interfering with Each Other with Locks.mp4
8.5 MB
05.Do Multiple Things at Once with Parallel Programming/0503.Logging What Happens When You Have Many Processes.mp4
4.6 MB
06.Creating Reusable Applications from Your Python Scripts/0601.Create Command Line Interfaces (CLIs) with plac.mp4
13.7 MB
06.Creating Reusable Applications from Your Python Scripts/0602.Manage Dependencies and Packages with Pipenv.mp4
23.7 MB
06.Creating Reusable Applications from Your Python Scripts/0603.Refactor and Tidy Up Code with PyCharm and Black.mp4
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