Brief Summary
This lecture introduces lists in Python, a versatile data structure that can hold a sequence of values of different types. It covers how to access elements and sub-lists (slices), the concept of nested lists, and the crucial distinction between mutable and immutable values. The lecture also explains how assignment works differently for mutable types like lists, the implications for copying lists, and the use of "equality" vs. "is" operators to check for value equality and object identity. Finally, it touches on list concatenation using the plus operator and its effect on creating new lists.
- Lists are sequences of values that can be of mixed types.
- Lists are mutable, meaning they can be updated in place.
- Assignment of mutable values does not create a fresh copy; both names point to the same value.
- Use full slice to create a true copy of a list.
- "==" checks for value equality, while "is" checks for object identity.
Introduction to Lists
The lecture begins by recapping basic data types in Python: integers (int), floating-point numbers (float), booleans (bool), and strings (str). It reviews arithmetic operations, logical operations, and string manipulation techniques like indexing and slicing. The focus then shifts to introducing lists as another type of sequence, highlighting that lists can contain a mix of different data types, unlike strings which are sequences of characters.
List Basics: Definition, Indexing and Slicing
A list is a sequence of values, which can be of different types. Lists are defined using square brackets [] and elements are separated by commas. Like strings, lists are indexed starting from 0. Individual elements can be accessed using square bracket notation (e.g., factors[3] to get the element at the third position). Slices can be extracted using the colon notation (e.g., mixed[0:2] to get a sub-list from the 0th position up to, but not including, the 2nd position). The len() function returns the length of a list.
Distinction Between Lists and Strings
A key difference between lists and strings is how single elements and slices of length one are treated. In strings, extracting a single character at a position is indistinguishable from extracting a substring of length one. However, in lists, extracting an element at a position yields a single value, while extracting a slice of length one yields a list containing that value. Therefore, a single value and a slice of length one are not the same for lists.
Nested Lists
Lists can be nested, meaning a list can contain other lists as elements. This creates a multi-dimensional structure where elements can be accessed using multiple indices. For example, nested[0][1] accesses the element at position 1 of the list located at position 0 of the nested list. Slices can also be used with nested lists to extract sub-lists at different levels of nesting.
Lists Are Mutable
Lists are mutable, meaning their elements can be changed after the list is created. Individual elements can be updated by assigning a new value to a specific index (e.g., nested[1] = 7 changes the value at position 1 to 7). This mutability extends to nested lists, where elements within inner lists can also be modified directly. This is a fundamental difference from strings, which are immutable and cannot be changed in place.
Assignment and Mutable Values
The mutability of lists has important implications for assignment. When assigning an immutable value (int, float, bool, string) to a new variable, a fresh copy of the value is created. However, when assigning a mutable value (like a list), a new copy is not created; instead, both variables point to the same list in memory. This means that modifying the list through one variable will affect the other variable as well.
Copying Lists
To create a true copy of a list, a full slice can be used. A full slice (e.g., list1[:]) creates a new list with the same elements as the original list. Assigning this full slice to a new variable (e.g., list2 = list1[:]) ensures that list2 is a separate list from list1, so modifications to one will not affect the other.
Equality vs. Identity
Python provides two ways to check for equality: == and is. The == operator checks if two variables have the same value, while the is operator checks if two variables refer to the same object in memory. Two lists can have the same value (i.e., be equal according to ==) but still be different objects (i.e., not be the same according to is). If two variables is equal, modifying the object through one variable will affect the other.
List Concatenation
Lists can be combined using the + operator, which concatenates them to create a new list. This operation always produces a new list, even if one of the operands is the original list. If a list is concatenated with another list and assigned back to the original list's variable, the variable will now point to the new list, and any other variables that were previously pointing to the original list will remain unchanged.
Summary
The lecture concludes by summarizing the key concepts related to lists: their definition as sequences of values, the possibility of mixed data types and nested structures, the use of indexing and slicing, and the crucial concept of mutability. It reiterates the implications of mutability for assignment and copying, emphasizing the use of full slices to create true copies. Finally, it reinforces the distinction between value equality (==) and object identity (is).
