jerry-git/learn-python3

Features

• Interactive Notebook Tutorials - Delivers an interactive Python tutorial as Jupyter notebooks with embedded exercises.
• Jupyter Notebook Curricula - The entire repository is a structured Jupyter notebook curriculum for learning Python.
• If-Elif Chains - Evaluates a series of boolean expressions in sequence and runs the block for the first true condition.
• Range Generators - Teaches generating numeric ranges with range for use in loops.
• Standard Library Curricula - Teaches Python using only built-in modules, avoiding external dependencies for all examples.
• Key-Value Pair Managers - Teaches using dictionaries as key-value collections for storing and manipulating data.
• Dictionary Construction - Teaches creating dictionaries with curly braces or the dict() constructor.
• Web-Based REPLs - Provides a browser-based REPL for executing Python code cells with immediate feedback.
• Standard Library Sandboxes - Runs all notebooks using only the Python standard library, eliminating setup friction.
• Python Development Guides - Provides notebooks covering virtual environments, packaging, and professional Python workflows.
• Function Definitions - Teaches defining reusable blocks of code that accept inputs and return results.
• Embedded Notebook Exercises - Embeds practice tasks within explanatory notebook cells requiring active code writing.
• Notebook-Based Lessons - Delivers each lesson as a self-contained Jupyter notebook combining text, code, and exercises.
• Code Examples - Demonstrates every concept with minimal runnable code snippets before abstract explanations.
• Parallel Collection Iterations - Teaches iterating over multiple collections in parallel using zip.
• Conditional Branching - Teaches if-statement conditional branching as a fundamental Python control flow construct.
• Dictionary Comprehensions - Teaches concise dictionary construction using comprehension syntax in interactive notebooks.
• List and Set Comprehensions - Teaches list and set comprehensions as idiomatic Python constructs for concise collection building.
• Dictionary Iteration - Teaches iterating over dictionary key-value pairs using .items() in interactive notebooks.
• Function Argument Passing - Teaches passing values to functions as positional or keyword arguments.
• Default Arguments - Teaches assigning fallback values to function parameters for optional arguments.
• Indexed Iteration - Teaches using enumerate to pair each element with its index during iteration.
• Progressive Concept Sequences - Orders topics so each new concept builds directly on previously introduced syntax and patterns.
• Keyword Argument Usage - Teaches specifying arguments by name when calling functions.
• Standard Library Exploration - Demonstrates built-in Python modules and tools without external dependencies.
• Truthiness Evaluators - Converts any Python value to its truthy or falsy boolean equivalent for use in conditions.
• Loop Iteration Skipping Mechanisms - Teaches loop break statements as a fundamental Python control flow mechanism.
• Integer Arithmetic - Teaches integer arithmetic operations including floor division, modulus, and exponentiation.
• List Iteration - Teaches walking through each element of a list in sequence using a for loop.
• Named Tuples - Teaches creating named tuples for readable, self-documenting immutable data records.
• Test Driven Development - Teaches writing tests before implementation to ensure code matches requirements.
• pytest Tutorials - Teaches pytest fixtures, parametrization, and testing practices through interactive notebooks.
• Local File Writing - Teaches creating or overwriting files with text content using context managers.
• Date and Time Libraries - Teaches Python's datetime module for creating, inspecting, and formatting dates and times.
• Dictionary Copying - Teaches creating independent dictionary copies using the dict() constructor.
• Existence Verifiers - Teaches checking whether a path points to an existing file or directory.
• Boolean Aggregation Checks - Teaches built-in any() and all() functions for boolean aggregation checks.
• Entry Removals - Teaches removing dictionary entries with del, pop, and popitem methods.
• Safe Key Accessors - Teaches safe key access with get to return a default instead of raising an error.
• Default Value Assignments - Teaches setdefault to assign a default value only when a key is absent.
• Truthy Fallback Selections - Teaches the or-operator pattern for selecting the first truthy value from options.
• Maximum Value Calculators - Teaches built-in max() and min() functions for finding extreme values.
• Path Construction Utilities - Teaches constructing and resolving file-system paths with an object-oriented API.
• Module Organization - Teaches structuring Python source files into modules and packages for maintainability.
• Expression Embedding - Teaches f-string syntax for embedding variables and expressions directly in string literals.
• Temporary Directory Managers - Teaches creating and automatically cleaning up disposable file-system resources during tests.
• pytest Fixtures - Teaches writing automated tests with pytest fixtures, parametrization, and mocking.
• Random Number Generation - Teaches Python's random module for generating random numbers with optional seeding.
• JSON Serialization - Teaches Python's json module for encoding objects to JSON and decoding JSON strings.
• Conditional Logic - Teaches joining boolean expressions with and, or, and not operators.
• Context Managers - Teaches the with statement for resource management as a core Python language construct.
• Custom Exception Definitions - Teaches creating application-specific exception classes by inheriting from Exception.
• Dictionary Construction From Sequences - Teaches constructing dictionaries by pairing two sequences using zip.
• Default Value Initializers - Teaches using defaultdict to supply default values for missing dictionary keys.
• Dictionary Merging - Teaches merging dictionaries with update, overwriting existing keys with incoming values.
• Entry Additions and Updates - Teaches inserting and updating dictionary entries using assignment syntax.
• Starred Sequence Unpackings - Teaches starred expression unpacking for assigning first, last, and middle elements.
• Loop Else Clauses - Teaches the for-else loop construct, a distinctive Python language feature.
• Specific Symbol Imports - Teaches importing individual classes or functions from a module for direct use.
• Hierarchical Imports - Teaches loading modules from package hierarchies using dot-separated import paths.
• Namespace Imports - Teaches importing entire modules and accessing contents through the module name.
• Relational Value Comparisons - Teaches checking equality, inequality, and ordering between values using standard operators.
• Exception Suppression - Teaches catching specific exception types with multiple except clauses.
• Try-Except-Else Blocks - Teaches the try-except-else construct for separating success logic from error handling.
• Finally Blocks - Teaches the finally block for unconditional cleanup after exception handling.
• Sequence Reversals - Teaches reversing sequences with reversed to iterate from last to first element.
• Tuple Unpacking Swaps - Teaches tuple unpacking for swapping variable values without a temporary variable.
• Floating Point Arithmetic - Teaches floating-point number representation and its precision limitations.
• Decimal Arithmetic Types - Teaches Python's Decimal type for precise decimal arithmetic without rounding errors.
• Comparison Operator Chaining Rules - Teaches combining multiple relational operators into one expression to test ranges.
• Operator Precedence Management - Teaches operator precedence rules and bracket usage for controlling evaluation order.
• Package-Based Code Organization - Teaches organizing related modules into packages to keep projects maintainable.
• Collection Element Counters - Teaches Python's collections.Counter for tallying element occurrences in collections.
• Monkeypatching Utilities - Teaches overriding environment variables and object attributes during tests for isolation.
• Pytest Fixtures - Teaches creating reusable test fixtures to avoid duplicating setup code across test cases.
• Dependency Mocking - Teaches replacing module dependencies with controlled substitutes during testing.
• Manual Test Code Writing - Teaches writing test cases manually to verify behavior and catch regressions.
• Parametrized Test Cases - Teaches parametrization of test cases with multiple input-output pairs using pytest decorators.
• File Reading - Teaches opening and reading files line by line using context managers.
• Ternary Expression Evaluators - Teaches ternary conditional expressions for concise value selection in Python.
• Python Development Resources - Case-based learning for Python 3 using Jupyter Notebooks.

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