Advanced Python Topics

• The course is aimed at an intermediate skill level, requiring some basic Python knowledge, and covers advanced topics to bring Python skills to the next level.

• The course is divided into 21 sections, covering essential topics every experienced Python programmer should know.

• A list is a collection data type that is ordered, mutable, and allows duplicate elements.

• Lists are created with square brackets, and elements are separated by commas.

• Lists can contain different data types, such as integers, Booleans, and strings.

• Lists allow duplicate elements, and elements can be accessed by referring to their index, which starts at zero.

• Negative indices can be used, with -1 referring to the last item, -2 referring to the second last item, and so on.

• Lists can be iterated over using a for loop.

• The 'in' keyword can be used to check if an item is in a list.

• The 'len' method returns the number of elements in a list.

• The 'append' method is used to add items to a list.

• The 'insert' method is used to insert items at a specific position in a list.

• The 'remove' method is used to remove the first occurrence of an item in a list.

• The 'clear' method is used to remove all elements from a list.

• Lists can be reversed using the 'reverse' method.

• Lists can be sorted using the 'sort' method, which sorts in place.

• The 'sorted' function can be used to create a new sorted list without changing the original list.

• Lists can be multiplied to create a new list with the same elements repeated multiple times.

• Lists can be concatenated using the '+' operator.

• Slicing is a way to access sub-parts of a list using the colon operator, allowing for specification of start and stop indices, and an optional step index.

• Slicing can be used to create a new list with a subset of elements from an original list.

• Lists can be copied using the 'copy' method, the 'list' function, or slicing with a colon operator.

• List comprehension is a way to create a new list from an existing list using a single line of code, with an expression and a for loop.

• Tuples are a collection data type that is ordered and immutable.

• Tuples are created with parentheses, and elements are separated by commas.

• Tuples are often used for objects that belong together.

• Parentheses are optional when creating a tuple, and tuples can contain different data types.

• A tuple with one element requires a comma after the element to distinguish it from an expression.• A tuple is a collection of data that is ordered and immutable, and it is created with parentheses.

• To create a tuple with a single element, a comma must be included after the element, otherwise, it is recognized as a string.

• Tuples can be created using the built-in tuple function, which can take an iterable as an argument.

• Elements in a tuple can be accessed using indexing, with the index starting at 0.

• Negative indexing can be used to access elements from the end of the tuple, with -1 referring to the last element.

• Tuples are immutable, which means elements cannot be changed or assigned after creation.

• The len() method can be used to get the number of elements in a tuple.

• The count() method can be used to count the occurrences of a specific element in a tuple.

• The index() method can be used to find the first occurrence of a specific element in a tuple.

• Tuples can be converted to lists and vice versa using the list() and tuple() functions.

• Slicing can be used to access sub-parts of a tuple, with the syntax tuple[start:stop:step].

• The step argument can be omitted, and it defaults to 1.

• A negative step can be used to reverse the tuple.

• Unpacking can be used to assign elements of a tuple to separate variables.

• The number of variables must match the number of elements in the tuple, otherwise, a ValueError will be raised.

• A dictionary is a collection of data that is unordered and mutable, and it is created with braces.

• Dictionaries consist of key-value pairs, where each key is mapped to a specific value.

• The dict() function can be used to create a dictionary from an iterable of key-value pairs.

• Elements in a dictionary can be accessed using their keys, with the syntax dictionary[key].

• If a key is not found in the dictionary, a KeyError will be raised.

• Dictionaries are mutable, which means elements can be added or changed after creation.

• The del statement or the pop() method can be used to delete items from a dictionary.

• The popitem() method can be used to remove an arbitrary item from a dictionary.

• The update() method can be used to merge two dictionaries, overwriting existing keys.

• The keys() method can be used to get a list of all keys in a dictionary.

• The values() method can be used to get a list of all values in a dictionary.

• The items() method can be used to get a list of all key-value pairs in a dictionary.

• A set is a collection of data that is unordered and mutable, and it does not allow duplicate elements.

• A set is created with braces, just like a dictionary, but without key-value pairs.

• The set() function can be used to create a set from an iterable.

• Elements in a set can be accessed using an for-in loop.

• The add() method can be used to add elements to a set.

• The remove() method can be used to remove elements from a set, or the discard() method can be used to avoid raising a KeyError if the element is not found.

• The pop() method can be used to remove an arbitrary element from a set.

• The clear() method can be used to empty a set.

• The union(), intersection(), and difference() methods can be used to perform set operations.

• The symmetric_difference() method can be used to get a set with all elements from both sets, but not the elements that are in both sets.

• The update() method can be used to modify a set in place, adding elements from another set.

• The intersection_update() method can be used to modify a set in place, keeping only the elements found in both sets.

• The difference_update() method can be used to modify a set in place, removing elements found in another set.

• The symmetric_difference_update() method can be used to modify a set in place, keeping only the elements found in both sets, but not the elements that are in both sets.Here are the summarized bullet points:

• In sets, is subset and is superset methods are used to check if all elements of one set are in another set or vice versa.

• is subset returns True if all elements of the first set are in the second set, and False otherwise.

• is superset returns True if the first set contains all elements of the second set, and False otherwise.

• Two sets are disjoint if they have no elements in common, and the is disjoint method returns True if they are disjoint and False otherwise.

• When copying a set, a simple assignment only copies the reference, so modifying the copy also modifies the original.

• To make an actual copy of a set, use the copy method or the set method with the original set as an argument.

• A frozen set is an immutable collection data type, and it cannot be changed after creation.

• A string is an ordered and immutable collection data type used for text representation.

• Strings can be created with single or double quotes, and triple quotes are used for multi-line strings.

• To access characters or sub-strings in a string, use indexing or slicing with square brackets.

• A string is immutable, so it cannot be changed in place.

• The strip method removes whitespace from a string, but does not change the original string.

• The upper and lower methods convert a string to upper or lower case, respectively.

• The startswith and endswith methods check if a string starts or ends with a specific character or sub-string.

• The find method returns the index of the first occurrence of a character or sub-string in a string, or -1 if not found.

• The count method returns the number of occurrences of a character or sub-string in a string.

• The replace method replaces a character or sub-string in a string with a new value.

• The split method splits a string into a list of words, and the join method concatenates a list of words into a string.

• The join method is more efficient and cleaner than using a loop to concatenate a list of strings.

• There are three ways to format strings: the old style with the % operator, the new style with the format method, and the newest style with f-strings.

• The old style uses placeholders like %s or %d and is less readable and less efficient.

• The new style uses placeholders like {} and is more readable and efficient.

• The newest style with f-strings uses placeholders like {var} and is the most readable and efficient.

• The collections module provides special container data types, including the counter, named tuple, ordered dict, default dict, and deque.

• The counter is a container that stores elements as dictionary keys and their counts as dictionary values.

• The counter can be used with any iterable, and provides methods like most_common to get the most common elements.

Test your knowledge of advanced Python concepts, including lists, tuples, dictionaries, sets, and strings. Learn how to create, manipulate, and iterate over these data structures, as well as how to perform set operations and string formatting.