Python Built-in Functions
Since Python is a "time-effective" or "time-efficient" language. That is why Python provides a lot of built-in functions that are pre-defined and can be used in the program to save a lot of time doing the task.
In other words, Python is a well-liked programming language renowned for its brevity, usability, and flexibility. Due to its extensive libraries and potent tools, it has become a preferred option for developers, data analysts, and scientists. Python's built-in functions are among its most alluring features. By using these functions, developers can complete a variety of tasks without having to write voluminous and intricate code.
Mathematical calculations, string manipulation, file handling, and other tasks can all be accomplished using the extensive library of built-in functions that Python has to offer. Developers can easily access these functions because they are pre-defined and readily available in the Python interpreter. They give users a quick and effective way to complete common tasks, boosting output and lowering the time and effort needed to write code.
Note: Each and every one of the built-in functions listed in this post is described in its own separate post with at least one example program. Programs provided as examples are well-tested and executed.
List of built-in functions in Python
The following is a list of Python's built-in functions. If you want to learn a specific built-in function, click on it; otherwise, proceed by clicking the "Next Function" button available at the end of this post for each built-in function article to learn these built-in functions one by one.
- abs()
- all()
- any()
- append()
- ascii()
- bin()
- bool()
- breakpoint()
- bytearray()
- bytes()
- callable()
- chr()
- classmethod()
- clear()
- close()
- compile()
- complex()
- copy()
- count()
- delattr()
- dict()
- dir()
- divmod()
- enumerate()
- eval()
- exec()
- extend()
- fileno()
- filter()
- float()
- flush()
- format()
- fromkeys()
- frozenset()
- getattr()
- get()
- globals()
- hasattr()
- hash()
- help()
- hex()
- id()
- index()
- input()
- insert()
- int()
- isatty()
- isinstance()
- issubclass()
- items()
- iter()
- join()
- keys()
- len()
- list()
- locals()
- map()
- max()
- memoryview()
- min()
- next()
- object()
- oct()
- open()
- ord()
- pop()
- popitem()
- pow()
- print()
- property()
- range()
- readable()
- read()
- readline()
- readlines()
- remove()
- replace()
- repr()
- reversed()
- reverse()
- round()
- seek()
- setattr()
- setdefault()
- set()
- slice()
- sorted()
- sort()
- split()
- staticmethod()
- str()
- sum()
- super()
- tell()
- truncate()
- tuple()
- type()
- update()
- vars()
- writeable()
- write()
- writelines()
- zip()
How do Python's built-in functions save time?
For example, let's suppose we need a code in Python to convert decimal to binary. Therefore, to save our time in writing an unnecessary number of statements, just use the bin() function to do the job, as shown in the example given below:
x = 2454 b = bin(x) print(b)
The output is:
As you can see, the decimal number stored in x is directly converted into its equivalent binary value using, of course, the function bin(). Imagine how much of your time is saved by writing self-defined code to do the same task.
One of my friends uses built-in functions most of the time because of his slow typing speed. I mean seriously. 😀
One More Thing: Some built-in functions are necessary to learn, such as print(), input(), read(), close(), etc., to achieve their respective functions. Because we cannot create self-defined code for the task that these functions are used for.
Advantages of built-in functions in Python
- Time is saved by built-in functions because they are ready to use and don't need to be defined.
- Built-in features offer users a predictable experience because of their consistency in usage and behavior.
- Built-in functions typically perform better than user-defined functions because they are well-optimized and written in highly efficient code.
- There are many built-in functions in Python that offer a variety of functionality, from straightforward tasks like printing to more difficult ones like handling dates and times.
Disadvantages of built-in functions in Python
- Built-in functions are not always adaptable to specific use cases.
- Overuse of built-in functions can lead to a misunderstanding of the underlying code and principles.
- Some built-in functions may not be the best fit for the specific use case, and a custom function may be required instead.
- The built-in functions available in one version of Python may not be available in another, causing compatibility issues when working with code across environments.
« Python Tutorial Next Function »
Liked this post? Share it!