There are few programming languages out there that are as favored and revered as Python. Python is a very popular programming language that was both created and founded by renowned Dutch programmer called Guido van Rossum and was initially released in 1991.
In recent years, Python has become one of the greatest and most widely used general-purpose programming languages around the world thanks to its easy-to-use syntax and its beginner-friendly operation.
Plus, it’s much faster than other available programming languages.
Not only is Python a highly accessible language that is popular among non-developers and developers alike, but you can usually find this type of programming in a variety of processes such as software testing, system scripting, or building websites, for example.
But what important things do you need to know before you begin using this coding language? And is it truly beginner-friendly?
Whether you’re completely new to programming or are simply looking for more information about how to get your start using Python, this guide will provide you with all of the essential tools and knowledge that you could need!
Let’s jump right in.
Python coding is a general-purpose language that can be used to create various programs rather than being specialized for a single problem.
Its beginner-friendly application and this sort of versatility have made Python one of the stand-out and most widely used programming languages in the world today.
Interpreted: Python coding can execute at runtime with any program changes being easy to spot. In technical terms, Python coding has a compiler that translates code written from one programming language into another.
When compared to Java or C++, the differences between the software are quite prominent. For example, Python coding is far more transparent and automatic than these other types of software.
However, with Python, there is no need to worry about the compilation step as this occurs in real-time.
Unfortunately, interpreted languages are usually much slower than any compiled ones as they take a single line of instruction or code at a time as their input.
Semantically Dynamic: Python uses dynamic semantics which means its variables are dynamic objects. These are instances of values that exist at the run-time level and are set as constructs in the code.
Object-Oriented: everything in Python coding is an object. This means you have the means to structure the programs to guarantee that properties and behaviors are bundled into different objects.
Yet you have the choice to write code in a procedural, object-oriented, or functional way. We’ll talk more about this below.
High Level: Python is a high-level programming language because it so closely resembles English. This means that Python doesn’t require you to have the knowledge to contend with any low-level machine details.
Python Works On Different Platforms
One of the greatest things about Python is that it is a cross-platform language. It’s versatile enough to work across various systems which speeds up the process of building applications while making it more convenient, too.
This means that any programs written on a Macintosh (Mac) computer will also work on a Linux system and vice versa. Python programs also run on Windows computers provided the machine has the correct Python interpreter installed.
Other operating systems such as Raspberry Pi also provide different options for writing Python coding. However, the platform or operating platform that is chosen is mostly a matter of personal preference.
Allows Developers To Write Short Programs Than Other Languages
Python has a syntax that enables developers to write programs with far fewer lines than other programming languages. The word “syntax” is used to describe the set of rules that actively defines how Python will be both written and interpreted.
As Python runs on an interpreter system, it allows code to be quickly executed as soon as it is written, which means prototyping is typically done quite quickly.
Turning an idea or a concept into code for any type of working short software prototype can be carried out in a matter of days or weeks instead of months.
Can Be Used As A Functional, Object-Oriented, And Procedural Way
Though the consensus is that Python is an object-oriented programming language instead of procedural programming, this isn’t necessarily the case. Python coding can support both object-oriented and procedural programming.
However, it is important to write Python in a functional style — especially if you are trying to program something that requires quite a lot of mathematical computations.
Python Language Is Similar To English
Python is a high-level language that was designed to act almost as a second language that programmers must learn. Thanks to its syntax, this coding language closely resembles the English language which means it has lots of readability for humans yet is far less readable for a computer.
It’s relatively easy to learn and has a low learning curve. Provided programmers are willing to put the effort and dedication into developing their understanding of the Python language, it theoretically shouldn’t be too difficult.
As we have established, syntax refers to the structure of the programming language. These are set rules that are used to define how a Python program will be both written and interpreted by the human reader and the computer.
Like we must learn grammar to understand English, you must do the same to learn the Python language. Python coding and programming is supposed to be an easily readable language once you have gotten to grips with its elegant syntax structure.
Understanding what syntax is and what it does remains one of the simplest requirements that programmers must know to code in any programming language.
When you develop a program, you’re responsible for managing a lot of different values. To effectively store all of your values, you must use variables.
Python supports various types of variables including floating point numbers, text, and whole numbers. Anything can be labeled as a variable provided you can assign a value to it.
No, these aren’t like the strings on a guitar. Instead, a string is a series of characters. In Python, anything inside of either single or double quotes is considered a string.
One thing to note is that strings are immutable meaning they cannot be changed. You can access the string elements using an index, with the first character having an index of zero.
Python numbers introduce you to number types like floating-point numbers, complex numbers, and integers. These are also immutable, meaning if you change the value of the data then you will end up with a new object entirely.
These number objects are created once a value has been assigned to them.
In any programming, you will need to frequently check whether a condition is True or not and then take the most suitable course of action. To represent the true value of different types of data, Python provides you with booleans.
When you compare two numbers or two strings, Python will return the results in the form of a boolean value.
As the name suggests, these are constant variables that have a value that cannot be changed. It may be helpful to think of these as containers that hold a lot of unchangeable information.
Constants are rarely used in Python as there are no equivalents. Programmers are usually knowledgable enough to leave values they want to stay constant alone.
You also need to learn how to make notes in your code to keep track of where you are, or to simply document the type of code you are writing.
Adding comments including inline comments, block comments, and even documentation strings will become second nature once you have grasped the general rules of the Python coding language.
Type conversion is the direct conversion of an object from one type of data to another which is useful in competitive and day-to-day programming.
There are two types of type conversions in Python: implicit type conversion which converts data types without user involvement, and explicit type conversion which requires manual input to convert data types.
These operators will introduce you to the comparison operators and how they can be used to compare two different values. Essentially, they do what the name suggests: compare.
However, they are also known by the name relational operators as they can be used to find the relation between operands and then generate a boolean value.
There are six comparison operators:
- Less than (<)
- Less than or equal to (<=)
- Greater than (>)
- Greater than or equal to (>=)
- Equal to (==)
- Not equal to (!=)
If you’re looking to check multiple conditions at any given time, you must use logical operators. There are three logical operators in Python coding:
- And operator – simultaneously checks whether two conditions are True.
- Or operator – this checks multiple conditions but returns “True” when either or both of the individual conditions are True.
- Not operator – this applies only to one condition and then reverses it. For example, if the condition is True, this operator will return false.
If… Else Statements
The “if-else” statement is generally used to execute the True and False parts of a condition. If the condition is deemed to be true then the block code is executed.
If the condition is false, the else block code will be executed (this will be a different block of code).
The ternary operator is a great way of writing conditional statements in Python programming, allowing you to control the flow of the program.
It can be thought of as a simple single-line version of the “if…else” statement to test out a condition and determine whether it is True or False.
As its name suggests, the Python operator consists of three separate operands:
- True Value – this can be assigned if the expression is evaluated to be True.
- False Value – this can be assigned if the expression is false.
- Condition – a boolean expression that evaluates to either True or false.
For Loop With Range ()
In any type of programming, you will often need to execute a single block of code multiple times. This is when you will need to use a for loop with a range() function.
For loops work to reduce the risk of repetition in your code as you can repeat the same operation as many times as you’d need.
The ‘while’ loop statement in Python helps you to execute a code block repeatedly – provided a given condition is True.
This while loop falls under the category of an indefinite iteration which means that it is generally used when the number of times to iterate beforehand is unknown or is not explicitly stated in advance.
A break in Python is a control statement that is used to maintain control of a total loop sequence. The break statement in Python programming terminates a current loop and then resumes its execution at the very next available statement.
A common use of the break function is when you need to completely exit a loop when an external condition is triggered, or you want to skip a part of a loop.
Another keyword you need to know when dealing with Python coding is ‘continue’. This function is used to end the current loop iteration that contains it.
Total control of the program then flows straight to the statement after the body of the loop. The ‘continue’ statement can be used in for and while loops.
When dealing with Python coding, the ‘pass’ statement acts as a great placeholder for future code. Nothing happens when this statement is executed yet you can avoid receiving an error when an empty code isn’t permitted.
Empty code is not allowed in function definitions, loops, statements, or as part of class definitions.
A Python function has two main parts: a function body and definition. The function body is made up of indented lines while the definition starts with the ‘def’ keyword and the name of the function ‘greet’.
Functions are used to divide larger programs into manageable parts, making it much easier to begin developing, reading, testing, and maintaining your program.
Keyword arguments are one of those Python features that seem a little odd compared to other programming languages. Also known as named arguments, these are values that can be identified by specific parameter names when being passed into a function.
When you call a function and then pass an argument to a parameter with a default value, the function will use that instead of the default value.
To use default parameters you must place parameters in the default values after other parameters, otherwise, you’ll end up with a syntax error.
Recursive functions can be defined as a routine that either calls themselves directly or indirectly. Some main examples include the factorial where an integer is multiplied by itself while being lowered.
Lambda expressions are advanced constructs of Python. They are short blocks of code that take in parameters and return a value. By learning more about these, you can learn how to define some anonymous functions.
A docstring is a literal string used to document a Python class, module, method, or function to allow programmers to understand what it does without needing implementation details. It helps programmers to identify and document specific segments of code.
As its name suggests, a list has its items in order so you can add the same item as many times as you would like to. Lists are also mutable which means you can change the list after being created by adding or removing items or simply changing the values.
Similar to a list, a tuple helps programmers to keep things in order and also allows the repetition of items. Yet there is one key difference: a tuple is immutable which means that it cannot be changed after being created. If you do try to make changes then a Python interpreter will show that there is an error.
Sort In A List Place
The sort() method sorts the original list in place and modifies the order of the elements in the list. It arranges these in ascending or descending order using the default < comparison operator between the items.
Sort A List
Any Python coding programmer must learn how to use the sorted() function to restore a new sorted list from its original list. It doesn’t modify the original list but instead sorts the elements from the lowest to the highest using the less-than operator (<).
Slice A List
In addition to sorting a list, it’s also important to learn how to slice a list. It is one of the most widely used techniques for programmers everywhere to resolve problems.
- The start is the index of a list where the slicing begins.
- The stop is the index where slicing ends.
- The step helps you to select the nth item in the start to-stop range.
Unpack A List
This basic function helps you to assign list elements and values to different variables via list unpacking. It’s common to use * to officially unpack the list so every element can be passed as a different parameter.
Iterate Over A List
Lists are used to store sequences of data in programming as we often want to perform the same operations on each element in a list. This could include manipulating each element mathematically or displaying said element. A loop must be used to iterate over each element in a list, repeating the same code for each.
Index Of An Element
In Python and other programming languages, indices begin at 0 instead of 1. If you want to find the index of a list in Python, you must use the inbuilt index() function which searches for a given element at the beginning of the list and returns the lowest index figure where the element appears.
An iterable in Python is an object that includes zero, one, or several elements. It can return these elements one at a time. Due to this feature, you can use a for loop to iterate over an iterable.
Transform List Elements With Map ()
The built-in Python map() function iterates over all elements in an iterable and later returns map objects. The iterable includes a tuple, list, dictionary, and set. It then applies a specific function to each and returns a new iterator of the elements.
Filter List Elements With Filter ()
Python features an in-built function called filter() which iterates over elements in a list and applies the fn() function to each one.
This returns an iterator for elements where items are filtered through a function to test whether the item is accepted or not.
Reduce List Elements Into A Value With Reduce ()
The reduce() function works differently than map() and filter(). It doesn’t return a new list based on the function and the iterable that has been passed but instead returns a single value. Simply, it reduces all values of an iterable into a single value.
This is a single tool that can be used in many situations. In Python, list comprehension offers shorter syntax if you want to create a new list based on the values of an already existing list.
A dictionary in Python is mutable yet does not guarantee the order of elements in a program. Python dictionaries allow you to set your access keys for each of the elements.
A dictionary comprehension with Python coding helps you to accurately run a for loop on a dictionary. From here, you can transform or filter each item. Overall, dictionary comprehensions offer more concise and expressive syntax if used correctly.
A set is an unordered, unindexed, and unchangeable data type that has no duplicate elements. It is used to store multiple items in a single variable and has a highly optimized way of checking whether a specific element is contained within the set. Items cannot be accessed using indexes.
Set comprehension in Python is a tool that is hardly ever spoken about. It works by returning a set, meaning elements inside will be returned unordered and duplicate-free. The rest follows a similar operation to a list comprehension.
Union Of Sets
The union of two or more sets works to return distinct values from both sets. Simply, the union() method returns a set that contains all items from the original set and the specified set.
Intersection Of Sets
The built-in intersection() method finds the intersection of at least two or more sets and then returns the set containing the similarity between two or more sets.
Difference Of Sets
In Python, this difference between the sets is equal to the total difference between the number of elements in two sets. The difference() function returns a set that marks this difference between the two sets.
Symmetric Difference Of Sets
Symmetric differences in sets are elements that belong to any one of the available sets but are not present in the intersection. To get the symmetric difference between two or more sets in Python, you can use the symmetric_difference() function.
The subset() function works to return the subset that is represented by the current instance. Let’s say you have two sets: A and B.
Set A is said to be the superset of set B if all elements of A are also the same for B. If the two sets are not of equal value, A is an official subset of B.
You can use built-in Python comparison operators to look for supersets in the program. For example, you can use the less than or equal to function (<=) or the issuperset() method. This will return True only if set A is a superset of B.
Sets are deemed as disjoint when they share no elements in common and have an empty intersection. Python has a built-in isdisjoint() feature that identifies whether two sets are disjoint or not.
This will return True if no element from one set is a member of another specified set.
If you want to handle exceptions in Python (the errors that may crash the code) then you must use the ‘try/except’ statement.
Place the block of code that may cause the exception in ‘try.’ If everything goes well, you won’t need to worry about invoking the ‘except’ block.
If the exception is raised the block of code inside will be executed, meaning the program will not crash.
The ‘finally’ block is usually executed independently of the exceptions being raised or not. They usually serve the purpose of allowing the program to clear up resources including memory, files, and even network connections.
It is entirely possible to add an ‘else’ command at the end. However, this will only run if there are no exceptions in the program.
A script in Python is a file that contains commands that are also structured to execute like a program. In Python, scripting is an excellent high-level language tool that can be used to automate those everyday practical tasks that can quickly feel repetitive.
However, it can also be carried out in apps, websites, games, and other command line applications.
Python has become extremely important in data science. The language continues to be used in experiments to conduct complex calculations, build machine learning algorithms, authorize tasks relating to data, and create data visualizations.
Python can create various data visualizations including 3D plots, line and bar graphs, and even pie charts.
Python is often used to develop the back end of an application or website or the side that a user does not usually interact with or see.
Python’s general role in web development may include processing data and communicating with relevant databases, sending and receiving data from servers, guaranteeing security, and URL routing.
Machine learning is a field of computer science that utilizes statistical methods to provide computer programs with the ability to learn from their past experiences and then work out how to improve their performance for specific tasks. Simply, it is a type of artificial intelligence (AI) that gives computers the ability to learn without being programs.
Python comes with a set of built-in mathematical functions that allow you to perform mathematical tasks on multiple types of operations.
The math module performs functions that are quite useful in number theory and representation theory. It helps you to perform common mathematical calculations in your application.
Python has wide-reaching capabilities that make it suitable for many types of software development, with a capacity to scale as the needs of business evolve.
It is typically used for audio or video applications, game development, scientific computing, and even data analysis and visualization, for example.
A workflow module in Python defines many functions that can be used to complete a specific task. Creating, developing, and executing Python code typically follows two different workflow patterns:
- Create new code in a text file and execute it using Python.
- Create code in a text file and import it into Python REPL.
Python coding may initially seem like an impossible language to learn with new things at every corner.
Yet if you take the time to dedicate yourself to understanding all of its syntax and the way that different functions work, you will be on your way to programming in no time.
In reality, it’s one of the greatest beginner-friendly programming languages out there. This is thanks to easy-to-digest syntax and digestible code.
Aside from this, Python can also be used on multiple platforms without changes. This makes it universally accessible — something many other similar programming languages do not offer.
It is also undoubtedly considered to be a top programming language by enterprises and businesses around the world, despite being almost 30 years old.
Even now, it remains extremely relevant thanks to such a wide array of applications, its vibrant user community, and its general ease of use. It truly is no wonder why so many people continue to value and use Python coding!
Python is one of the most popular languages in the United States of America. I have been working with Python for a long time and I have expertise in working with various libraries on Tkinter, Pandas, NumPy, Turtle, Django, Matplotlib, Tensorflow, Scipy, Scikit-Learn, etc… I have experience in working with various clients in countries like United States, Canada, United Kingdom, Australia, New Zealand, etc. Check out my profile.