Modern Python Solutions - Part 2 [Video]

Modern Python Solutions - Part 2 [Video]

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Steven F. Lott

The latest in modern Python recipes for the busy programmer
$10.00
RRP $124.99
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Video Details

ISBN 139781787280274
Course Length5 hours and 55 minutes

Video Description

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.

Style and Approach

The course is broken down into 5 sections that build from simple language concepts to more complex applications of the language. The videos take a problem-solution approach to resolve issues commonly faced by Python programmers across the globe.

Table of Contents

Basics of Classes and Objects
The Course Overview
Using a Class to Encapsulate Data and Processing
Designing Classes with Lots of Processing
Designing Classes with Little Unique Processing
Optimizing Small Objects with _slots_
Using More Sophisticated Collections
Extending a Collection
Using Properties for Lazy Attributes
Using Settable Properties to Update Eager Attributes
More Advanced Class Design
Choosing Between Inheritance and Extension
Separating Concerns via Multiple Inheritance
Leveraging Python's Duck Typing
Managing Global and Singleton Objects
Using More Complex Structures
Creating a Class that Has Orderable Object
Defining an Ordered Collection
Deleting from a List of Mappings
Functional and Reactive Programming Features
Writing Generator Functions with the Yield Statement
Using Stacked Generator Expression
Applying Transformations to a Collection
Picking a Subset
Summarizing a Collection
Combining Map and Reduce Transformations
Implementing “There Exists” Processing
Creating a Partial Function
Simplifying Complex Algorithms with Immutable Data Structures
Writing Recursive Generator Functions with the Yield from Statement
Input/Output, Physical Format, Logical Layout
Using pathlib to Work with Filenames
Reading and Writing Files with Context Managers
Replacing a File While Preserving the Previous Version
Reading Delimited Files with the CSV Module
Reading Complex Formats Using Regular Expressions
Reading JSON Documents
Reading XML Documents
Reading HTML Documents
Upgrading CSV from DictReader to the namedtuple Reader
Upgrading CSV from a DictReader to a Namespace Reader
Using Multiple Contexts for Reading and Writing Files
Statistical Programming and Linear Regression
Using the Built-in Statistic Library
Average of Values in a Counter
Computing the Coefficient of a Correlation
Computing Regression Parameters
Computing an Autocorrelation
Confirming that the Data is Random – the Null Hypothesis
Locating Outliers
Analyzing Many Variables in One Pass

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

Authors

Table of Contents

Basics of Classes and Objects
The Course Overview
Using a Class to Encapsulate Data and Processing
Designing Classes with Lots of Processing
Designing Classes with Little Unique Processing
Optimizing Small Objects with _slots_
Using More Sophisticated Collections
Extending a Collection
Using Properties for Lazy Attributes
Using Settable Properties to Update Eager Attributes
More Advanced Class Design
Choosing Between Inheritance and Extension
Separating Concerns via Multiple Inheritance
Leveraging Python's Duck Typing
Managing Global and Singleton Objects
Using More Complex Structures
Creating a Class that Has Orderable Object
Defining an Ordered Collection
Deleting from a List of Mappings
Functional and Reactive Programming Features
Writing Generator Functions with the Yield Statement
Using Stacked Generator Expression
Applying Transformations to a Collection
Picking a Subset
Summarizing a Collection
Combining Map and Reduce Transformations
Implementing “There Exists” Processing
Creating a Partial Function
Simplifying Complex Algorithms with Immutable Data Structures
Writing Recursive Generator Functions with the Yield from Statement
Input/Output, Physical Format, Logical Layout
Using pathlib to Work with Filenames
Reading and Writing Files with Context Managers
Replacing a File While Preserving the Previous Version
Reading Delimited Files with the CSV Module
Reading Complex Formats Using Regular Expressions
Reading JSON Documents
Reading XML Documents
Reading HTML Documents
Upgrading CSV from DictReader to the namedtuple Reader
Upgrading CSV from a DictReader to a Namespace Reader
Using Multiple Contexts for Reading and Writing Files
Statistical Programming and Linear Regression
Using the Built-in Statistic Library
Average of Values in a Counter
Computing the Coefficient of a Correlation
Computing Regression Parameters
Computing an Autocorrelation
Confirming that the Data is Random – the Null Hypothesis
Locating Outliers
Analyzing Many Variables in One Pass

Video Details

ISBN 139781787280274
Course Length5 hours and 55 minutes
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