Books & Videos

Table of Contents

Chapter: Basics of Classes and Objects

The Course Overview

03m 39s

Using a Class to Encapsulate Data and Processing

15m 43s

Designing Classes with Lots of Processing

09m 55s

Designing Classes with Little Unique Processing

08m 10s

Optimizing Small Objects with _slots_

05m 13s

Using More Sophisticated Collections

07m 31s

Extending a Collection

05m 38s

Using Properties for Lazy Attributes

05m 54s

Using Settable Properties to Update Eager Attributes

08m 6s

Chapter: More Advanced Class Design

Choosing Between Inheritance and Extension

12m 51s

Separating Concerns via Multiple Inheritance

07m 10s

Leveraging Python's Duck Typing

05m 10s

Managing Global and Singleton Objects

09m 3s

Using more Complex Structures

04m 6s

Creating a Class that Has Orderable Object

07m 55s

Defining an Ordered Collection

06m 48s

Deleting from a List of Mappings

08m 53s

Chapter: Functional and Reactive Programming Features

Writing Generator Functions with the Yield Statement

11m 23s

Using Stacked Generator Expression

11m 50s

Applying Transformations to a Collection

04m 54s

Picking a Subset

06m 22s

Summarizing a Collection

05m 2s

Combining Map and Reduce Transformations

08m 50s

Implementing “There Exists” Processing

06m 44s

Creating a Partial Function

06m 34s

Simplifying Complex Algorithms with Immutable Data Structures

09m 45s

Writing Recursive Generator Functions with the Yield from Statement

06m 7s

Chapter: Input/Output, Physical Format, Logical Layout

Using pathlib to Work with Filenames

13m 2s

Reading and Writing Files with Context Managers

07m 45s

Replacing a File While Preserving the Previous Version

06m 8s

Reading Delimited Files with the CSV Module

05m 56s

Reading Complex Formats Using Regular Expressions

03m 4s

Reading JSON Documents

13m 55s

Reading XML Documents

06m 45s

Reading HTML Documents

06m 49s

Upgrading CSV from DictReader to the namedtuple Reader

05m 54s

Upgrading CSV from a DictReader to a Namespace Reader

05m 0s

Using Multiple Contexts for Reading and Writing Files

05m 41s

Chapter: Statistical Programming and Linear Regression

Using the Built-in Statistic Library

09m 57s

Average of Values in a Counter

07m 20s

Computing the Coefficient of a Correlation

04m 22s

Computing Regression Parameters

06m 17s

Computing an Autocorrelation

08m 29s

Confirming that the Data is Random – the Null Hypothesis

10m 31s

Locating Outliers

10m 1s

Analyzing Many Variables in One Pass

09m 6s