Blog_Banner_Asset
    Homebreadcumb forward arrow iconBlogbreadcumb forward arrow iconData Sciencebreadcumb forward arrow iconHow to Run a Python Project? Installation & Setup, Execution [2024]

How to Run a Python Project? Installation & Setup, Execution [2024]

Last updated:
6th Oct, 2022
Views
Read Time
9 Mins
share image icon
In this article
Chevron in toc
View All
How to Run a Python Project? Installation & Setup, Execution [2024]

In today’s software industry, it is impossible to not know about the Python programming language. It has risen to an extreme standard, due to its simplicity of coding and human-readable code. Python is widely adapted in the scientific computing field, but it has also seen a tremendous amount of growth in the general software development industry. 

Python had first introduced nearly three decades ago, but its widespread usage has been pretty recent. The article will help you understand the basic syntactic procedures and steps necessary for you to run a Python project successfully. 

File Structure of Python Projects

Now let us first understand the file structure of a Python project. While working on industry level code, you would most probably come across code that is written in a hierarchy or form of various packages. So, it is necessary to understand what they are. While coding packages, it is crucial to remember that every hierarchy is decided and accessed by a dot (.), with the parent preceding the child package. 

The second thing is the procedure in which Python gets executed. The subtle difference that most people fail to understand is that Python does get compiled. Yes, we do agree that Python is an interpreter language, but internally, Python does get compiled. It is one of the essential details to understand how to run a python project fully.

Python code is internally compiled into bytecode. But the CPU does not understand the Byte code generated. So, we need the interpreter. The interpreter is also called a Python virtual machine or PVM. So here are the internal steps executed, while trying to run a python project:

1. Syntax checker runs on the Python code

2. Internal compilation of the Python code

3. Conversion of Python code to Bytecode

4. Interpret the byte code via Python Virtual machine

5. Generate the output

If any error occurs at any step, the execution is interrupted on that line itself, and the error is printed. Due to this, some people find it difficult and tedious to solve errors in Python. In Python, the code may contain a hundred errors, but at a time, only one error is shown, as the execution gets halted at the line itself and prints the stack trace with the error message. 

Read: Python Projects on Github

Installation and Setup of Python

Now before we start the implementation of our code, let us install and set up Python in our machine. The installation of Python is much simpler than most of the programming languages. To download Python on your PC, you may visit this site

After downloading the Python executable file, just run it and it will install Python on your PC. If you use a Mac OS or Ubuntu-based operating system, then Python comes pre-installed. You can still verify by using the command Python in the terminal or command prompt. 

Now let us write the first program in Python. Here is the starter code:

class firstPy: #class definition

    def __init__(self, name): #internal function definition

        self.name = name

    def add(self,a,b): #function definition

        print(“The sum is: “+str(a+b))

k = firstPy(“This”) #object creation

k.add(9,8) #calling function of the class firstPy

A lot of things are going on here. Let us discuss things one at a time. 

Class Definition

The first thing to notice is the class definition. Most of the time, while you try to run a python project, it will contain a class, especially working with industry code. In python, the class is defined by keyword class followed by class name. In python, the blocks are defined by indentations. 

While you try to run a python project, it is important to take care of that. Every internal block is indented. For example, the starting of the function inside the class needs to indent. Mostly, a tab works, but the standard definition also calls for four spaces. It is usually a personal preference. 

Check out The Trending Python Tutorial Concepts in 2024

Internal Function Definition

The second thing to note is the internal function definition. In python, the class initializer can be coded by __init__ function definition. Inside the class, functions are compulsory to have the ‘self’ argument. It is like the ‘this’ keyword that you may have noticed in other programming languages like C/C++. 

Here we add a name parameter, to give our object a name at the time of creation. Whatever parameters are specified in the init keyword needs to be entered while the creation of the object of that particular class. Second is the add function. 

Notice that this function also has a ‘self’ keyword parameter. The other two parameters are the numbers that will need adding up. The line of code following that does four things in total. First, computing the sum of a and b, which is done by the code snippet (a+b). The second is the str keyword. It converts the integer into the string. 

Then the string concatenation takes place. And finally, the string is taken as an argument in the print statement, and the output is printed through that. 

Now once the definitions are over, the time is to use those. The first thing is to create an instance of class firstPy. It can be done using the class name as a function call and initialize using the name attribute we added to its definition. It is crucial to assign the object to some variable, or else there is no way of accessing the functionality of it. 

The next step is to use the add function inside the class firstPy. To access any internal function or variable, you can use the dot(.) functionality. So here we use k.add(9,8). Note that we are only supplying two arguments. The keyword self directly takes the object name as the argument. So, no need to explicitly pass the object to the ‘self’ parameter. 

Check out: Python AI & ML Open Source Projects

Executing the Program

It is necessary to tell that the code is for Python3. It can be easily established, looking at the print statement. The print statement in Python2 does not have parenthesis. 

Now, moving on to the execution of the program. You can type this up in any text editor of your choice and save the file with .py extension. For example, firstprogram.py. Once done, open the terminal in the file location and type the following command. 

· python firstprogram.py

It will execute the program and should give the following output:

· The sum is: 17

Well, that is it. You successfully executed a program in Python. But how to run a python project? Specifically, a project.

Explore our Popular Data Science Courses

Run a Python Project

Well, for this, first, you need to understand the structure of the project. If it is a minor project, you should be fine as it may not contain many files. But if it is a big project, there can be many .py files and, you may be confused as to which one to run. 

Well, there is no clear choice in selecting a file. It depends on the documentation and how the project is coded. But mostly, the main file would be named accordingly. You only need to run that file with the same python command followed by the name of the file, and the code will execute itself if no errors occur. 

While working on different projects and solving the errors or maybe adding new functionality, it is necessary to know and identify the structure of the project. For example, assume there is a project of a music classifier. It may contain many files, and some files may be arranged in the hierarchy of packages. It is critical to know which file is under which package or module. It can be seen and verified by looking at the folder structure as well as the first line of code in the file that is using that particular package. 

It always contains the import keyword followed by the entire path hierarchy of the particular package in usage. Mostly, the packages are written, stored, and maintained in the hierarchy of folders itself, so it will not be much confusing to understand the modules. It is necessary to know this while trying to run a python project.

It is crucial to maintain the hierarchy in the same way it is written, or else you would need to use the functionality of a pre-built package “os”. The “os” package gives the function of joining the system path, which can help in importing packages out of the folder hierarchies.  

Well, that is it about folder structure while running or coding a python project. We only have touched the surface of a python program, but it should help in understanding the structure of any python project that you try to run. 

Also Read: Top 4 Python Challenges for Beginners

upGrad’s Exclusive Data Science Webinar for you –

How upGrad helps for your Data Science Career?

Read our popular Data Science Articles

The Bottom Line

So, this is everything on how to run a python project. Python is a dynamic language. It has a huge community and a lot of pre-built functionalities that make the overall process of development smoother and way easier than other programming languages. It is important to note that sometimes Python may feel slow, especially on heavy computations but, the overall development speed makes up for it. 

Top Data Science Skills to Learn

The development is easier also because of the ease of use of language and quick adaptability. Python is also reader-friendly. It is a bit easier to comb through a code written in Python than in other programming languages like C/C++. 

To know more about the language and to learn more about it, do visit upGrad’s courses. upGrad also offers courses on scientific computation using Python, that is, data science and machine learning algorithms. The knowledge you gained in the article will not only help in the general software development goals but also in courses and projects based on Data Science and ML or almost any other field in which Python is used.

Profile

Rohit Sharma

Blog Author
Rohit Sharma is the Program Director for the UpGrad-IIIT Bangalore, PG Diploma Data Analytics Program.

Frequently Asked Questions (FAQs)

1Why is Python popular for project development?

Python has a wide range of rich libraries and modules that makes it one of the best and most versatile languages for development purposes. The following are some of the most popular Python libraries: TensorFlow is a boon to Machine Learning engineers. This library is developed by Google and can be considered a computational library. If you are working with complex data then you must have Scikit-Learn in your arsenal. This library provides the cross-validation feature which allows various methods to check the accuracy of your model. Numpy is again a machine learning library used by other Python libraries like TensorFlow to perform internal operations. Keras is another popular Python library that provides a convenient mechanism for neural networks.

2Explain the file structure of a Python project.

Understanding the hierarchy of all the packages in a Python project is crucial as most of the time you will be working on an industry-level code where packages are ordered in a conventional manner.
The first thing to remember is that every package is accessed by a dot (.) with the parent preceding the child package. Next is understanding the execution of the Python code. Although Python is an interpreter code, it is compiled internally. Python is compiled into Bytecode but since the CPU does not understand it, we need an interpreter to decode it.

3Is Python becoming outdated or is it still worth learning Python in 2024?

Python is in high demand due to its versatility and flexibility. Its vast range of libraries and modules makes it compatible with various technical fields. The following are some of the popular tech domains that use Python and make it worth learning. You can be a Python developer right after acquiring the Python knowledge. Python developers are responsible for building websites, optimize data algorithms, or writing clean and efficient Python codes. Python is considered the most suitable language for data science and data analysis, which are the hottest technical sectors of 2024. Project management is in high demand, as a project manager is highly responsible for the business and marketing of the companies. A machine learning engineer trains the machines or models for making predictions based on the data provided to them.

Explore Free Courses

Suggested Blogs

Top 13 Highest Paying Data Science Jobs in India [A Complete Report]
905092
In this article, you will learn about Top 13 Highest Paying Data Science Jobs in India. Take a glimpse below. Data Analyst Data Scientist Machine
Read More

by Rohit Sharma

12 Apr 2024

Most Common PySpark Interview Questions & Answers [For Freshers & Experienced]
20854
Attending a PySpark interview and wondering what are all the questions and discussions you will go through? Before attending a PySpark interview, it’s
Read More

by Rohit Sharma

05 Mar 2024

Data Science for Beginners: A Comprehensive Guide
5064
Data science is an important part of many industries today. Having worked as a data scientist for several years, I have witnessed the massive amounts
Read More

by Harish K

28 Feb 2024

6 Best Data Science Institutes in 2024 (Detailed Guide)
5150
Data science training is one of the most hyped skills in today’s world. Based on my experience as a data scientist, it’s evident that we are in
Read More

by Harish K

28 Feb 2024

Data Science Course Fees: The Roadmap to Your Analytics Career
5075
A data science course syllabus covers several basic and advanced concepts of statistics, data analytics, machine learning, and programming languages.
Read More

by Harish K

28 Feb 2024

Inheritance in Python | Python Inheritance [With Example]
17595
Python is one of the most popular programming languages. Despite a transition full of ups and downs from the Python 2 version to Python 3, the Object-
Read More

by Rohan Vats

27 Feb 2024

Data Mining Architecture: Components, Types & Techniques
10774
Introduction Data mining is the process in which information that was previously unknown, which could be potentially very useful, is extracted from a
Read More

by Rohit Sharma

27 Feb 2024

6 Phases of Data Analytics Lifecycle Every Data Analyst Should Know About
80604
What is a Data Analytics Lifecycle? Data is crucial in today’s digital world. As it gets created, consumed, tested, processed, and reused, data goes
Read More

by Rohit Sharma

19 Feb 2024

Sorting in Data Structure: Categories & Types [With Examples]
138991
The arrangement of data in a preferred order is called sorting in the data structure. By sorting data, it is easier to search through it quickly and e
Read More

by Rohit Sharma

19 Feb 2024

Schedule 1:1 free counsellingTalk to Career Expert
icon
footer sticky close icon