Modern Python Solutions – Part 2

Modern Python Solutions – Part 2

English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 5h 55m | 1.47 GB

The latest in modern Python recipes for the busy programmer

Python is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great scripting language that can power your applications and provide great speed, safety, and scalability. By exposing Python as a series of simple recipes, you can gain insight into specific language features in a particular context. Having a tangible context helps make the language or standard library features easier to understand. This video comes with over 100 recipes on the latest version of Python.

The videos will touch on all the necessary Python concepts related to data structures, OOP, functional programming, as well as statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively use the advantages that it offers.

You will be armed with the knowledge of creating applications with flexible logging, powerful configuration, and command-line options, automated unit tests, and good documentation.You will end the book equipped with the knowledge of testing, web services, and configuration and application integration tips and tricks.

What You Will Learn

  • Explore the basic and advanced class design in Python
  • Perform input/output operations and get to know the logical layouts
  • Get acquainted with advanced programming techniques in Python
  • Equip yourself with functional and statistical programming features
Table of Contents

Basics of Classes and Objects
01 The Course Overview
02 Using a Class to Encapsulate Data and Processing
03 Designing Classes with Lots of Processing
04 Designing Classes with Little Unique Processing
05 Optimizing Small Objects with _slots_
06 Using More Sophisticated Collections
07 Extending a Collection
08 Using Properties for Lazy Attributes
09 Using Settable Properties to Update Eager Attributes

More Advanced Class Design
10 Choosing Between Inheritance and Extension
11 Separating Concerns via Multiple Inheritance
12 Leveraging Python’s Duck Typing
13 Managing Global and Singleton Objects
14 Using More Complex Structures
15 Creating a Class that Has Orderable Object
16 Defining an Ordered Collection
17 Deleting from a List of Mappings

Functional and Reactive Programming Features
18 Writing Generator Functions with the Yield Statement
19 Using Stacked Generator Expression
20 Applying Transformations to a Collection
21 Picking a Subset
22 Summarizing a Collection
23 Combining Map and Reduce Transformations
24 Implementing “There Exists” Processing
25 Creating a Partial Function
26 Simplifying Complex Algorithms with Immutable Data Structures
27 Writing Recursive Generator Functions with the Yield from Statement

Input/Output, Physical Format, Logical Layout
28 Using pathlib to Work with Filenames
29 Reading and Writing Files with Context Managers
30 Replacing a File While Preserving the Previous Version
31 Reading Delimited Files with the CSV Module
32 Reading Complex Formats Using Regular Expressions
33 Reading JSON Documents
34 Reading XML Documents
35 Reading HTML Documents
36 Upgrading CSV from DictReader to the namedtuple Reader
37 Upgrading CSV from a DictReader to a Namespace Reader
38 Using Multiple Contexts for Reading and Writing Files

Statistical Programming and Linear Regression
39 Using the Built-in Statistic Library
40 Average of Values in a Counter
41 Computing the Coefficient of a Correlation
42 Computing Regression Parameters
43 Computing an Autocorrelation
44 Confirming that the Data is Random – the Null Hypothesis
45 Locating Outliers
46 Analyzing Many Variables in One Pass