Modern Python Solutions - Part 2

  • Section 1: Basics of Classes and Objects

    This section will show youthe different kinds of numbers, workwith strings, use tuples, and use the essential built-in types in Python. We will also exploit the full power of the Unicode character set.

    • 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

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  • Section 2: More Advanced Class Design

    This section will let you dive a little more deeply into Python classes. We will combine some features we have previously learned about to create more sophisticated objects

    • 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

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  • Section 3: Functional and Reactive Programming Features

    This section provides us with methods to write small, expressive functions that perform the required data transformations. Moving ahead, you will learn about the idea of reactive programming, that is, having processing rules that are evaluated when the inputs become available or change.

    • 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 ďThere ExistsĒ Processing
    • Creating a Partial Function
    • Simplifying Complex Algorithms with Immutable Data Structures
    • Writing Recursive Generator Functions with the Yield from Statement

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  • Section 4: : Input/Output, Physical Format, Logical Layout

    This section will let you work with different file formats such as JSON, XML, and HTML. You will explore the input/output operations and connect Python with different file formats.

    • 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

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  • Section 5: Statistical Programming and Linear Regression

    This section will let you explore some basic statistical calculations that we can do with Pythonís built-in libraries and data structures. We will look at the questions of correlation, randomness, and the null hypothesis.

    • 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 Ė the Null Hypothesis
    • Locating Outliers
    • Analyzing Many Variables in One Pass

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