Jacob Johns

Relational Operators

• true/false bool type
• true/false bool type
• == value equality / equivalence
• != value inequality / inequivalence
• < less-than
• > greater-than
• <= less-than or equal
• >= greater=than or equal

Control Flow

Conditional statement: Branch execution based on the value of an expression

Else-clause

While-loops

Relational Operators

break

• Python requires the use of while True and break
• break jumps out of the inner-most executing loop to the line immediately after it

Summary

• int, float, None, and bool
• Relational operators for equivalence and ordering
• Conditional code with if-elif-else
• While-loops
• While-loops expressions converted to bool
• Interrupt loops with Control-C
• Control-C generates a KeyboardInterrupt exception
• Break out of loops with break
• Exits the innter-most executing loop
• Takes execution to the first statement following the loop
• Augmented assignment operators like +=
• Request text input from the user with input()

Overview

• str, bytes, list, and dict
• for-loop
• Put it all together

Collections

• str
• Data type for strings in Python
• Sequence of Unicode code points
• Immutable
• String Literals - "" / ''
• Escape Sequences - \n \' \"
• String Features
• Unicode Strings
• bytes
• Data type for sequences of bytes
• Raw binary data
• Fixed-width single-byte encodings
• Convert Between Strings and Bytes
• list
• Sequences of objects
• Mutable
• Workhorse in Python
• dict
• Fundamental data structure in Python
• Map keys to values
• Also known as maps or associative arrays
• for-loops
• Visit each item for an iterable sequence

Put it all together

Summary

• Single- and multi-line literals
• Concatenation of adjacent literals
• Universal newlines
• Escape sequences
• Raw strings
• Use str constructor to convert other types
• Access individual characters with square bracket indexing
• Rich API
• String literals can contain Unicode
• Bytes
• Sequence of bytes rather than codepoints
• Literals prefixed with lowercase "b"
• Use str.encode() and bytes.decode() for conversion
• Lists
• Mutable, heterogeneous sequences
• Literals delimited by square brackets
• Literal items separated by commas
• Access elements with square brackets
• Elements can be replaced by assigning to an index
• Grow lists with append()
• Use list constructor to create lists from other sequences
• Dicts
• Associate keys with values
• Literals are delimited by curly braces
• Key-value pairs are separated by commas
• Keys are separated from values by colons
• For-loops
• Bind each item from an iterable one at a time to a name
• Called for-each loops in other languages

Overview

• Reusable functions
• Source code files called modules
• Modules can be used from other modules
• Importing modules
• Programs or scripts
• Python execution model
• Make programs executable

Modularity

• Module code is only executed once on first import

Functions

• Functions are defined with the def keyname followed by the function name, and argument list in ()
• functions are called via the function name with arguments: my_function(my_argument)
• Many language features are implemented or controlled using specially named objects & functions. Such as, __feature__, known as a dunder.
• Dunder is a portmanteau of "double underscore"

__name__

• Specially named variable allowing to detect whether a module is run as a script or imported into another module

Python Execution Model

• def is a statement
• Top-level functions are defined when a module is imported or run

Docstrings

• Literal strings which document functions, modules, & classes
• They must be the first statement in the blocks for these constructs:"""Documentation strings"""
• Module docstrings must be at the start of the module before any statments
• PEP 257: Official Python convention for docstrings
• Sphinx: Tool to create HTML documentation from Python docstrings
• Google Style Guide
• help(function_name) can access the help from the REPL

Comments

• Code is ideally clear enough without ancillary explanation
• Sometimes you need to explain why your code is written as it is
• Comments in Python start with # & extend to the end of the line

Summary

• Python code is generally place in *.py files
• Execute modules by passing them as the first argument to Python
• All top-level statements are executed when a module is imported
• Define functions with the def keyword
• Return objects from functions with the return keyword
• return without an argument returns None, as does the implicit return
• Use __name__ to determine how a module is being used
• if __name__ == '__main__' lets the module be executable & importable
• A module is executed once, on first import
• def is a statement which binds code to a name
• sys.argv contains command line arguments
• Dynamic typing supports generic programming
• Functions can have docstrings
• help() can retrieve docstrings
• Modules can have docstrings
• Python comments start with #
• Program loaders can use #! (Shebang) to determine which Python to run

Overview

• Python object model
• Named references to objects
• Value vs. identity equality
• Value-equality & identity equality are fundamentally different concepts
• Comparison by value can be controlled programatically
• Identity comparison is unalterably defined by the language
• Passing arguments & returning values
• Python's type system
• Scopts to limit name access
• "Everything is an object"

Passing Arguments & Returning Values

• Function arguments are transferred using pass-by-object-reference
• References to objects are copied, not the objects themselves

Function Arguments

• Arguments with default values must come after those without default values
• Default Value Evaluation
• def is a statement executed at runtime
• Default arguments are evaluated when def is executed
• Immutable default values don't cause problems
• Mutable default values can cause confusing effects
• Always use immutable objects for default values

Python's Type System

• Python will not generally perform implicit conversions between types
• The exception to this rule is the conversion of if statement & while loop predicates to bool
• Type declarations are unnecessary in Python
• Names can be rebound as necessary to objects of any type

Scopes

• Name resolution to objects is managed by scopes & scoping rules
• Four types of scope in Python arranged in the hierarchy (from narrowest to broadest
• Local: Inside the current function
• Enclosing: Inside enclosing functions
• Global: At the top level of the module
• Built-in: In the special builtins module
• Scopes in Python do not correspond to source code blocks as demarcated by indentation
• global: Rebind global names into a local namespace

"Everything is an Object"

• Determine the type of any object by using the type built in function
• Attributes of an object can be viewed with the dir built in function in a Python interactive session

Summary

• Python uses named references to objects
• Assignment attaches a name to an object
• Assigning one name to another makes them both point at the same object
• The garbage collector removes objects with no references
• id() returns a unique integer ID for an object
• is determines if two names refer to the same object
• We can test for equivalence with ==
• Function arguments are passed by object reference
• Rebinding function arguments loses the original object reference
• return passes back an object reference to the caller
• Function arguments may have a default value
• Default argument values are evaluated once, when the function is defined
• Python uses dynamic typing
• Python has strong typing
• Python names are looked up using the LEGB rule
• Global references can be read from local scopes
• Use global to assign to global references from a local scope
• Everything in Pyton is an object
• import & def bind names to objects
• type() reports the type of an object
• dir() introspects the attributes of an object
• You can access the name of a function or module with __name__
• Docstrings can be accessed though __doc__
• You can use len() to measure the length of a string
• The repetition operator, *, repeats a string an integral number of times

Overview

• Deeper look at str, list, & dict
• New collection types:
• tuple
• range
• set
• Protocols that unite collections

tuples

• immutable sequences of arbitrary objects
• Once created, the objects within them cannot be replaced or removed, and new elements cannot be added.
• Similar syntax to lists, except they are delimited by parentheses rather than square brackets

Tuple unpacking

• Destructuring operation that unpacks data structures into named references