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Questions and Answers
When was Python developed?
When was Python developed?
Python 2 is currently the recommended version for usage.
Python 2 is currently the recommended version for usage.
False
What is meant by 'significant whitespace' in Python?
What is meant by 'significant whitespace' in Python?
Whitespace in Python is used for denoting code blocks instead of curly braces or parentheses.
Python uses __________ for single-line comments.
Python uses __________ for single-line comments.
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What is an object in Python?
What is an object in Python?
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Are objects in Python strongly typed?
Are objects in Python strongly typed?
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A list is an ordered sequence of Python objects. Objects can be of any type. If you need to keep track of unique values and do not care about order, use _____.
A list is an ordered sequence of Python objects. Objects can be of any type. If you need to keep track of unique values and do not care about order, use _____.
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How can you extract a single value from a list in Python?
How can you extract a single value from a list in Python?
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Match the following data structures with their descriptions:
Match the following data structures with their descriptions:
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What is an object in Python?
What is an object in Python?
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Which of the following data types are mutable in Python? (Select all that apply)
Which of the following data types are mutable in Python? (Select all that apply)
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Tuples in Python are immutable.
Tuples in Python are immutable.
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To extract a single value from a list in Python, we can specify its __________.
To extract a single value from a list in Python, we can specify its __________.
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Match the following data structures with their mutability in Python:
Match the following data structures with their mutability in Python:
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Study Notes
Python Programming Language
- Developed in the early 1990s by Guido van Rossum
- Python 3 is the future, and we will be using it in this course
- General-purpose, high-level language that is readable
- Important resource: Python documentation at https://docs.python.org/3/
- Fun fact: The name "Python" comes from Guido van Rossum's favorite TV show "Monty Python's Flying Circus"
Getting Started
- Download and install Python from https://www.python.org/downloads/
- We will be using IDLE as the integrated development environment in this course
- First task: download, install, and write your first Python program (refer to TK2053_Python_Lab0)
Python Interpreter
- Python is an interpreted language
- Two ways to run a Python program:
- Interactive interpreter: execute one line of code at a time
- Python file (.py file): store Python programs in text files and run them
Some Fundamentals
- Whitespace is significant in Python
- Python uses indentation to denote code blocks (unlike other languages that use {} or ())
- Comments:
- Single-line comments denoted by #
- Multi-line comments begin and end with three "
- Typically used for documentation
Objects
- An object is an entity with a type (e.g., string or integer)
- The object's type determines what can be done with the data and whether it's mutable (can be changed) or immutable (constant)
- Objects are dynamically typed, meaning Python keeps track of types automatically without requiring declaration code
- Objects are strongly typed, meaning the type of an object doesn't change, even if its value is mutable
Mutable vs Immutable
- Mutable objects are like open boxes, where the value can be changed
- Immutable objects are like closed boxes, where the value can't be changed, but a new object is created when the value changes
- Examples of mutable objects: lists
- Examples of immutable objects: integers, strings, tuples
Lists
- A list is an ordered sequence of Python objects
- Lists can contain objects of any type, including mixed types
- Lists are mutable, meaning they can be modified
- Lists can be created with zero or more elements, separated by commas, and can be converted from other data types
- Lists can be modified by accessing and changing individual items using offsets
- Lists can be sliced to extract a subsequence
- Lists can be nested to contain other lists
Tuples
- Tuples are sequences of arbitrary items, similar to lists
- Tuples are immutable, meaning they can't be added, deleted, or changed after creation
- Tuples can be created with or without parentheses, using commas to separate elements
- Tuples can be used in place of lists, but have fewer functions and use less space
- Tuples can be used as dictionary keys
Dictionaries
- Dictionaries are mutable collections of key-value pairs
- Dictionaries are unordered, meaning the order of items doesn't matter
- Dictionary keys must be unique and immutable (e.g., strings, integers, tuples)
- Dictionary values can be any type
- Dictionaries can be created using curly brackets and key-value pairs
- Dictionaries can be modified by adding, changing, or deleting key-value pairs
- Dictionaries can be used to get values by specifying a key
- Dictionaries have functions to get all keys, values, or key-value pairs
Sets
- Sets are collections of unique values, similar to dictionaries without values
- Sets are mutable, but the keys must be unique and immutable
- Sets can be created using the set() function or curly brackets with comma-separated values
- Sets can be used to test for values, and have operators for union, intersection, and difference
- Sets can be used to discard duplicates from lists, strings, tuples, or dictionaries
Comparing Data Structures
- Lists, tuples, and dictionaries are compared in terms of creating and accessing elements
- Each data structure has its own use cases and advantages
Bigger Data Structures
- Lists, tuples, and dictionaries can be combined to create more complex data structures
- Examples include lists or tuples of lists, or dictionaries of lists
- These data structures can be used to store and manipulate larger amounts of data
Objects
- An object is an entity with a type (e.g., string or integer)
- The object's type determines what can be done with the data and whether it's mutable (can be changed) or immutable (constant)
- Objects are dynamically typed, meaning Python keeps track of types automatically without requiring declaration code
- Objects are strongly typed, meaning the type of an object doesn't change, even if its value is mutable
Mutable vs Immutable
- Mutable objects are like open boxes, where the value can be changed
- Immutable objects are like closed boxes, where the value can't be changed, but a new object is created when the value changes
- Examples of mutable objects: lists
- Examples of immutable objects: integers, strings, tuples
Lists
- A list is an ordered sequence of Python objects
- Lists can contain objects of any type, including mixed types
- Lists are mutable, meaning they can be modified
- Lists can be created with zero or more elements, separated by commas, and can be converted from other data types
- Lists can be modified by accessing and changing individual items using offsets
- Lists can be sliced to extract a subsequence
- Lists can be nested to contain other lists
Tuples
- Tuples are sequences of arbitrary items, similar to lists
- Tuples are immutable, meaning they can't be added, deleted, or changed after creation
- Tuples can be created with or without parentheses, using commas to separate elements
- Tuples can be used in place of lists, but have fewer functions and use less space
- Tuples can be used as dictionary keys
Dictionaries
- Dictionaries are mutable collections of key-value pairs
- Dictionaries are unordered, meaning the order of items doesn't matter
- Dictionary keys must be unique and immutable (e.g., strings, integers, tuples)
- Dictionary values can be any type
- Dictionaries can be created using curly brackets and key-value pairs
- Dictionaries can be modified by adding, changing, or deleting key-value pairs
- Dictionaries can be used to get values by specifying a key
- Dictionaries have functions to get all keys, values, or key-value pairs
Sets
- Sets are collections of unique values, similar to dictionaries without values
- Sets are mutable, but the keys must be unique and immutable
- Sets can be created using the set() function or curly brackets with comma-separated values
- Sets can be used to test for values, and have operators for union, intersection, and difference
- Sets can be used to discard duplicates from lists, strings, tuples, or dictionaries
Comparing Data Structures
- Lists, tuples, and dictionaries are compared in terms of creating and accessing elements
- Each data structure has its own use cases and advantages
Bigger Data Structures
- Lists, tuples, and dictionaries can be combined to create more complex data structures
- Examples include lists or tuples of lists, or dictionaries of lists
- These data structures can be used to store and manipulate larger amounts of data
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Description
Learn the basics of Python programming language, its history, and features. This quiz also covers the differences between Python 2 and Python 3.
