A Python dictionary is a data structure that stores key-value pairs. Unlike lists, which use integer indices to access values, dictionaries use keys that can assume other types, such as strings. This makes dictionaries a powerful tool for organizing and retrieving data efficiently. Dictionaries are implemented using hash tables, which provide a method for fast access to values based on associated keys.
A Python tuple is a collection of ordered items, much like a list. However, tuples differ from lists in a fundamental way: they are immutable, meaning their elements cannot be changed after creation. This immutability makes tuples simpler and more efficient data structures. They are useful for situations where you need to store a fixed set of values that should not be modified during program execution.
A Python iterator is an object that enables the elements inside a collection object, such as a lists, tuples, dictionaries, and strings, to be looped over and accessed one at a time. Such collections are called iterables and their common characteristic is that they can provide an iterator.
Python inner functions, also known as nested functions, are functions defined within the scope of another function. Inner functions are particularly useful as helper functions, which encapsulate logic only useful within the context of another function, and as factory functions, which create and return other more specialized functions.
Variable arguments, which are commonly known as args and kwargs in Python, enable you to create functions that can handle a dynamic number of inputs.
While functions typically return a single value or no value at all, there are cases in which having multiple return values in Python functions is desirable. It is a general programming best-practice to have each function be responsible for doing one thing only, and therefore those multiple returned values should be closely related to a single concept.
A Python docstring is a string that appears at the beginning of a function and serves as a human-readable explanation of a function’s purpose, behavior, and usage.
Lambda functions in Python is a feature that allows you to create small, inline functions without the need for a definition using the def keyword. Lambda functions, are particularly useful when you need to create simple functions on the fly, for one-time use for tasks such as filtering, mapping, and sorting data. Because lambda functions are not defined with a name, they are also known as anonymous functions.
Sometimes, you may encounter situations where you want a function to work a certain way most of the time, but also have the option of changing its behavior occasionally. This is where Python optional parameters come in. Optional parameters allow you to define functions with parameters that have default values. These default values are used when an argument is not provided during the function call.
In Python, keyword arguments allow you to pass arguments to a function by specifying the names of the parameters. This approach matches the values passed to the function and its parameters according to the parameter names rather than the order in which they appear. This makes function calls more explicit and self-documenting, as you provide the values along with their corresponding parameter names.
