Blog_Banner_Asset
    Homebreadcumb forward arrow iconBlogbreadcumb forward arrow iconData Sciencebreadcumb forward arrow iconTop 21 Python Developer Skills You Must Need To Become a Successful Python Developer

Top 21 Python Developer Skills You Must Need To Become a Successful Python Developer

Last updated:
19th Feb, 2024
Views
Read Time
16 Mins
share image icon
In this article
Chevron in toc
View All
Top 21 Python Developer Skills You Must Need To Become a Successful Python Developer

Its intuitive syntax, extensive libraries and versatile integration capabilities have fueled incredible growth across web development and scientific computing sectors. Python’s “batteries included” ecosystem allows python developers skills to enhance to achieve in hours what takes days in other languages, boosting productivity tremendously with python skills. Yet more than raw efficiency, Python promotes cleaner code organisation by emphasising modular design, object-oriented principles and exception-based error handling.

These best practices scale resiliently to support complex applications involving hundreds of modules and millions of lines without becoming tangled chaos behind the scenes. The resulting code proves straightforward to write and, crucially, to maintain amid changing product requirements for python backend developer skills. There are many skills one needs to learn to become a good Python Developer. Here, we are going to discuss top Python developer skills that one will require to be a Better Python developer.

Its intuitive syntax, extensive libraries and versatile integration capabilities have fueled incredible growth across web development and scientific computing sectors. Python’s “batteries included” ecosystem allows developers to achieve in hours what takes days in other languages, boosting productivity tremendously.

Yet more than raw efficiency, Python promotes cleaner code organisation by emphasising modular design, object-oriented principles and exception-based error handling. These best practices scale resiliently to support complex applications involving hundreds of modules and millions of lines without becoming tangled chaos behind the scenes.

The resulting code proves straightforward to write and, crucially, to maintain amid changing product requirements. There are many skills one needs to learn to become a good Python Developer. Here, we are going to discuss top Python developer skills that one will require to be a Better Python developer.

What are the benefits of learning Python?

Python has been the most popular coding language for several years, which means that career advancement opportunities for Python developers are excellent.

Many giant firms, including Pinterest, Instagram, Yahoo!, and Nokia, use Python. Python is preferred by more than 68% of Data Scientists. Python has numerous advantages, which are discussed further below.

  1.    Easy to learn and understand

Despite the fact that Python is a high-level language that allows you to perform complex tasks, it is simple to learn and understand. It has a simple syntax and is appropriate for both novice and experienced programmers. Python can appear difficult at first if you are a complete beginner. This language is used by large development teams with inexperienced members to improve output.

  1.     Python is Adaptable

It is used in Web Development, Data Mining, Data Science, Artificial Intelligence, Machine Learning, Gaming, Product Development, Rapid Application Development, Testing, Automation, and other areas. Python is becoming increasingly popular as the primary language for many applications.

  1.     Python is popular and offers a high salary

Python is a popular programming language that is constantly growing in popularity. As Python gains popularity, so does the number of skilled Python developers. Python training can help you break into a world of hugely profitable career opportunities.

Python developers are among the highest-paid in the market, especially in data science, machine learning, and web development.

  1.     Open-Source Language

Python is a community-developed open-source language with a large support base. Having Python source code freely available enables global collaboration within the dev community. Anyone can contribute improvements and new features or find issues transparently. There are also no licensing fees, reducing barriers to usage. The open ecosystem allows Python capabilities to advance rapidly through decentralised enhancement, with questions like what are the skills required for python developer.

  1.     Has regular updates

Python, like any other programming language, regularly receives additions and updates to improve its functionality and keep up with evolving development standards. Leveraging contributions from its widespread community, Python sees regular updates that continue fortifying it as an optimal programming language. Each new release provides access to the latest productivity features, security fixes, and compatibility improvements are some skills for python developer.

The frequent refresh cycle ensures Python remains cutting-edge.

Leveraging contributions from its widespread community, Python sees regular updates that continue fortifying it as an optimal programming language. Each new release provides access to the latest productivity features, security fixes, and compatibility improvements. The frequent refresh cycle ensures Python remains cutting-edge.

  1.     Minimal Program Management

Python’s excellent readability and simple syntax make it easy for beginners to learn and use the programming language. It also has a large user base, which results in a diverse set of internet resources. This improves language development and allows for minimal program management.

Because Python has a gentle learning curve, developers can focus more on solving programming problems versus wrestling with stubborn, complicated syntax rules especially when skills required for python developer. Moreover, Python has some complex features under the hood. But most of those are abstracted away when you’re first starting out. So newbies,with  python developer required skills can build up a good foundation in core programming concepts quickly is role of backend python developer skills.

  1.     Massive support libraries

Python has a vast standard library that includes a wide range of topics. Since there are numerous libraries of already scripted commonly used tasks, it greatly reduces the time to write and the length of the code. Some basic python interview questions are about how it works. To this, answer, reinventing the wheel is an inefficient use of development time and resources. Thankfully, Python’s expansive set of curated modules covers a remarkable range of domains to incorporate directly, from web frameworks to mathematical computations with various python developer skills required. These libraries also possess thoughtful documentation, enabling relatively smooth usage and customization which is often considered python programming for network engineers, role by python full stack developer skill.

  1.     Increase in Productivity

Because Python does not require compilation, the test-debug cycle is extremely fast. A segmentation fault is never caused by a bad input or a bug; rather, it raises the exception.

Python’s beginner-friendly syntax, dynamic typing and lightweight code reduce complexity substantially over other languages. Developers can implement rich functionality in far fewer lines of straightforward Python versus convoluted equivalents. Removing that excess coding friction enables the delivery of projects to be faster.

  1.     Third-Party Modules

The Python Package Index contains a large number of third-party modules, allowing it to converse with the majority of other platforms and programming languages.

Thanks to Python’s versatility, over 150,000 third-party libraries and counting are available to incorporate. Instead of reinventing existing functionality, developers can install battle-tested modules for needs like data science, web frameworks and machine learning. Standing on the shoulders of open-source Giants saves immense development time.

  1.   Enhancing your resume

Being familiar with Python and being a certified Python programmer is not the same thing. As a Python-certified programmer, you will be able to add more value to your resume and make a stronger impression on recruiters.

Formal Python certification demonstrates deeper hands-on mastery versus just claiming “knowledge” of the language. Backing skills with verified credentials builds trust and confidence during the hiring process. Additionally, the journey to gaining reputable Python certification itself further solidifies the breadth of expertise.

  1.   Change your career path

Python developer skills and a  Python certification, you will find it easier to transition because it demonstrates that you have the necessary knowledge to handle a variety of projects.

With Python usage continuing to surge in fields ranging from backend services to data analysis, Python skills present growing career opportunities. Organisations urgently seek Python expertise, given its balance of human-friendliness and scalability. Learning Python unlocks income potential and flexibility to shift across high-demand industries.

Check out all trending Python tutorial concepts in 2024

Top Python Developer Skills

1. Expertise in Core Python

The developer should have an excellent knowledge of Core Python. One should know the concepts of core python and its aspects are:

  • Iterators
  • Generators
  • Exception Handling
  • File handling concepts
  • Data types and variables
  • OOPs Concepts
  • Data Structures

Mastering this core foundation establishes a solid technical aptitude to then expand into specialised domains. Web developers might explore GUI programming next or DevOps roles could target multi-threading. Data scientists may focus on speed optimisations. However, everyone benefits from excellence first with fundamentals like control flow, modularity, classes, and typing. There is no substitute for dedication to perfecting the basics through hands-on projects before layering on more advanced capabilities and knowing python programming skill, of python programming datacamp.

2. Sound Knowledge of Web Frameworks

Flask and Django are the most popular Python web framework, and a developer should have an excellent grasp of either of these web frameworks. Flask is a Python micro web framework which is very widely used. Django encourages a practical, clean and functional design and also a high-level Python Web Framework. Knowledge of JavaScript, CSS, and HTML is also beneficial to become a Good Python Developer.

Both eliminate mundane HTTP handling, templating and routing tasks so developers focus on an application’s unique logic. They support vital needs like user authentication, database integrations, and out-of-the-box session management. Unit testing and deploying applications comes smoothly as well.

Strong backend skills naturally pair with sufficient font-end mastery, too – JavaScript, CSS and HTML fundamentals for responsive, dynamic UIs. Modern JavaScript frameworks like React may incorporate advanced features like real-time updated.

3. Object Relational Mappers

An object-oriented Programming language is used for the conversion of data between two systems that are incompatible, and that technique is called Object Relational Mapper (ORM). From any programming language, a virtual object database is created by Object Relational Mappers. Programmers also use many customizable ORM tools.

In Python, SQLAlchemy is the most comprehensive ORM option. It supports PostgreSQL, MySQL, Oracle and MSSQL through a unified interface while retaining vast SQL control if needed. But Django and other frameworks have lightweight ORM modules as well.

Good Python developers are adept both utilising ORMs for cleaner data access and understanding how they simplify SQL use cases like joins, aggregations and connection management behind the scenes. ORMs promote code reuse since common record operations get implemented only once. They also enable switching database systems more easily by abstracting storage details with issues of programming and problem solving with python.

Eager to put your Python skills to the test or build something amazing? Dive into our collection of Python project ideas to inspire your next coding adventure.

4. Skills of Data Scientists

A Python developer can grow very much in the field of Data Science by having a good grasp in the popular aspect of Data Science such as:

  • Good Knowledge of SQL
  • Knowledge to use Python packages such as Scikit learn, MatPlotib, NumPy, etc. for Data Science
  • Cleaning up of Data
  • Data Wrangling
  • Analysis of Data
  • Visualization of Data
  • Mathematical Knowledge
  • Knowledge of Probability
  • Knowledge of Statistics

Finding a best data science course will help you learn all the important topics and make you ready for your dream job.

Explore our Popular Data Science Courses

upGrad’s Exclusive Data Science Webinar for you –

Transformation & Opportunities in Analytics & Insights

Beyond foundational skills, one must stay atop bleeding edge data science advancements to excel. Continued learning in domains like NLP augments abilities, as do adjacencies like cloud infrastructure management. Soft skills even emerge for collaborating cross-functionally conveying metrics or models to non-technical stakeholders. Moreover, mastering full spectrum data capabilities – from scratch preprocessing to bleeding-edge ML algorithm customisation – establishes expertise beyond the transient popularity of singular techniques. There will always be new nuances to incorporate. It comes with the intrinsically fast-moving territory of data science.

5. Artificial Intelligence and Machine Learning Skill

A developer in Data Science should have good knowledge about Artificial Intelligence and Machine Learning as it comes under Data Science. One should have good proficiency in Machine Learning algorithms. He should have a good understanding of Neural Networks, Produce insight from data, visualization of data, Data analysis, and collection of data from various sources.

Must read: Excel online course free!

From initially exploring popular ML packages like TensorFlow, PyTorch and Keras, professionals gradually cement fluency in applying ML-powered decision-making to products. APis democratise access to advanced ML models. Adding skills in data visualization, pipeline automation, and metrics-driven fine-tuning establishes full-stack ML abilities. Moreover, having baseline ML-powered feature knowledge despite focusing on particular domains allows more open collaboration as the practice permeates industries. One day, AI transformation may sneak into initially unrelated roles.

6. Deep Learning

Deep Learning is also a field that comes under Data Science. One is expected to have a good understanding of the concepts in deep learning and Neural network architecture. This is after covering all the aspects of Artificial Intelligence, Machine Learning, and the Basics of Data Science. There are many aspects of Deep Learning, such as:

  • Audio Processing
  • Video Processing
  • NLP ( Natural Language Processing)

Our learners also read – python online course free!

Read our popular Data Science Articles

7. Good Understanding of Multi-Process Architecture

A developer should know the codes that are used in the working of release and deployment. The design engineer usually does this, but a developer too must have a basic understanding. If one wants to become a good Python Developer, then they should learn about MVT (Model View Template) and MVC (Model View Controller) Architecture. A developer will be able to solve the problem in the core framework after understanding the multi-process architecture.

8. Analytical Skills

One must have excellent analytical skills in the field of Data Science to be a good python developer in the future. The required analytical skills may need a good understanding of building useful websites for web development, visualizing datasets for Data Science in a better way, optimization of algorithms while coding, writing clean code which is not redundant, etc.

Top Data Science Skills to Learn

9. Design Skills

A good developer should also have a good understanding of designs which will be helpful while designing scalable products. Servers should be implemented to make them highly available. A python developer can use any python framework like Flask or Django to create a website. In this way, Python will be able to work at both server-side and client-side programming.

Must read: Data structures and algorithm free!

10. Communication Skills

Communication skill is one of the essential skills which one should have in any profession. Successful communication can bring success to the professional and the organization. One must be able to avoid any communication gap or confusion in understanding or any kind of misunderstanding. Half of the job is already done when one communicates do peer code review and make a contribution within the team in an efficient manner. Communication is also needed to solve any problem and to communicate with teammates.

11. Version Control

Changes in the source code are multiple times, and one should be able to keep track of every change. It is one of the vital job requirements expected by any company. If a developer has correctly set up their GitHub, and they are already familiar with the words like “commit, pull, fork, push”, then they will be efficiently handling different versions of codings and track the changes in the codes.

12. Front-End Technologies Knowledge

A Python developer will need to work and coordinate with the front-end team to match the client-side with the server-side. There should be a good understanding of front-end technologies to a developer so that they can know about the appearance of the application, working of front-end, possibilities, and limitations of the front-end. For a Python Developer, the experience and knowledge of front-end will be helpful in some of the main projects.

13. The Ability of Integration

To enhance your Python Developer skills, you must be able to integrate multiple databases and data sources into a single system. This integration will help in the smooth running of the system, and there will be fewer discrepancies.

For example, Python might populate analytical models by aggregating social media metrics, real-time server logs and historical records in a lake. Clean pipelines simplify gleaning insights across silos. Or a CRUD backend centralises multiple specialty databases under a common OData interface for mobile sync. Even on frontend systems, Python plays integration glue – whether rendering React server views or embedding MATLAB visualisations into dashboards. At scale, teams require hybrid technology blending.

14. Knowledge of Server-Side Templating Language

A python developer also needs a good understanding of modelling language at the server-side such as Make, Jinja 2, etc.

Both render templates filled with backend values into final documents sent to browsers. Additional engines add niche functionality like internationalization or async rendering as needed.

Master templaters design with separation of concerns in mind – HTML/CSS static assets focus purely on structure/presentation while Python views handle model preparation. Template inheritance reduces duplication through reuse while template logic improves responsiveness by skipping unnecessary processing. Configuration not code prevails.

15. Knowledge of User Authorization and Authentication

A developer in Python should also know about the user authorization and authentication that happens between multiple environments, servers, and systems.

Developers leverage industry-standard protocols like OAuth and cryptographic best practices to fulfil these needs reliably. For example, JSON Web Tokens allow stateless user validation by embedding identity claims directly into tamper-proof tokens carried in requests. Hashing and salting techniques now prevent exposing passwords, even in breaches. Role-based access systems grant precise access cryptographic configurations that balance security with overhead through digest algorithms like BCrypt tailored for passwords. Together, these techniques assemble comprehensive identity frameworks managing users from initial access through ongoing session validation checks.

16. Python Event-Driven programming

A developer in Python should be familiar with programming in Python that is event-driven.

Rather than traditional synchronous code executing sequentially, event-driven systems react dynamically to notifications from external sources. These triggers invoke event handler callbacks to process notifications as needed.

For example, a web server may spawn a thread per incoming request while queueing a backend event for each. Separate database logic processes data asynchronously while serving pages and API responses fully. By decoupling event handling from primary logic, overall throughput improves dramatically.

Python frameworks like asyncio (standard) and Twisted (third party) encourage this non-blocking I/O approach for network programming especially.

17. Good Debugging and Unit Test Skills

A developer should have strong skills in debugging and unit testing.

Debugging involves systematically isolating, diagnosing and addressing unexpected faults or unintended behaviour in applications. Strategies here run the gamut from inserting print statements to monitoring metrics dashboards.

Unit testing establishes repeatable validation suites protecting against regressions as code evolves. Tests confirm components operate correctly in isolation and help clarify assumptions early. Frameworks like PyTest encourage test-driven designs validated incrementally as complexity increases. Together, debugging prowess and unit testing expertise afford resilience no tutorial or documentation can replace.

18. Code Versioning Tool Understanding

A developer can also have a good understanding of the code versioning tools like SVN, Mercurial, and Git.

Git simplifies creating experimental branches, merging contributions from peers, resolving conflicts intelligently and rolling back problematic updates. Workflow automation around testing, validation checks and deployments further increases productivity by setting policy safeguards. Built-in facilitation guides non-technical stakeholders, also contributing through intuitive interfaces, expanding engagement. Understanding Git dynamics builds awareness into often opaque software lifecycles.

19. Database Schemas Creation Ability

If a developer can create schemas in the database, then he can support business processes and represent it.

Developers should grasp relationships, normalization rules, indexing strategies and other model optimization considerations. Schemas provide the backbone connecting object code to persistent storage. Careful column type selection preserves data integrity, while foreign keys and joins handle complex interconnections. Schema migration allows graceful evolutionary enhancements as well. Excellent Python developers possess mental maps from common access patterns to ideal table layouts, index choices and even database engine strengths or weaknesses based on unique workloads.

20. Multiple Delivery Platforms Understanding

There are many platforms to deliver an output such as desktop or mobile, and a python developer should have good knowledge of the difference between different platforms. He should also be able to optimize the output according to the target platform to match the requirements.

21. Logical Thinking Ability

In any case, the Python developer is required to think logically and the ability of good logical thinking should be the second nature of a developer to become a good developer in the python programming language.

Conclusion

If you are reading this article, most likely you have ambitions towards becoming a Python developer. Here we have discussed the top skills required by a Python developer and we hope this article has been informative to you.

If you’re interested to learn python & want to get your hands dirty on various tools and libraries, check out Executive PG Programme in Data Science.

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)

1What are the most common applications of Python?

Python is a programming language that is extensively used for online and software development, task automation, data analysis, and data visualization. Python is used in a variety of fields, such as web and game development, machine learning, artificial intelligence, scientific computing, and academic research. Due to its relative simplicity of learning, Python has been welcomed by many non-programmers, such as accountants and scientists, for a variety of routine operations, such as money management.

2Is Python a backend programming language?

Python is an appropriate backend language in this field of technology because of its emphasis on code readability and its extensive libraries and frameworks. Furthermore, Python includes a large number of machine learning libraries, such as Keras, TensorFlow, and Scikit-learn. Python is a key programming language for back-end development because of its accessible syntax and extensive server-side use.

3What are the limitations of event-driven programming?

Event-driven programming is generally more difficult and time-consuming than batch programming for basic systems. The program's flow is typically less logical and clear. In most cases, Event Driven Development is only effective in GUI programming. Commercial applications do not benefit from event-driven programming because they require data processing, which event-driven programming does not provide.

Explore Free Courses

Suggested Blogs

Most Common PySpark Interview Questions & Answers [For Freshers & Experienced]
20780
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
5056
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)
5145
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
5071
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]
17538
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
10738
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
80468
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]
138836
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

Data Science Vs Data Analytics: Difference Between Data Science and Data Analytics
68880
Summary: In this article, you will learn, Difference between Data Science and Data Analytics Job roles Skills Career perspectives Which one is right
Read More

by Rohit Sharma

19 Feb 2024

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