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Python Programming Language Profile

Quick Summary - Even if you’re not super tech-savvy, you’ve probably been hearing more and more about how companies of all sizes are using Python for web applications - and data science.

Python Programming Language Profile

We provide an overview of where Python can be put to best use and where it may not be the best option. Even then, with the right developers on your team, you can mix and match the technologies you need to go with Python as the core of your backend.

7 mins read

What is Python?

Python is one of the most popular programming languages and demand is steadily increasing for it globally. It’s regarded as a general-purpose programming language suitable for projects of any size. Python was designed to be easy to read and uses an object-oriented approach to assist developers in writing clear, logical (ostensibly) high-quality code.

This is especially significant as software has an average lifespan of 7 years, up to twice that for large, complex systems. Developers will spend much more time reading code than writing it. The easier it is to read, the faster it is to understand, debug, and upgrade.

Python was initially released in 1991, but it has undergone three major versions since then. Python 3 was released in 2008, it’s most recent update was in October 2020 with Python 3.8. Early versions of Python are not entirely compatible with Python 3. Presently, there are no plans for Python 4.

Strengths and advantages of Python

Python is a strong contender as a programming language for many functions like prototyping, data analysis, web development and applications, machine learning, and as a DevOps tool for writing automated scripts and tests. Reasons to use Python for your project include:

  • Python is OSI-approved open-source, free to use, modify, and distribute, so you can use it to add your own functionality or behavior.
  • Python is a cross-platform language – it will run on Windows, Mac OS, Linux, but has significant constraints with iOS and Android devices (see weaknesses below).
  • Python’s easy to read because it uses an English-based syntax.
  • Compared to many other programming languages, most tasks in Python can be performed with fewer lines of code which reduces code complexity and potential for defects.
  • Python developers are inclined to be more productive as they’ll spend less time reading and gaining an understanding of the code.
  • As an interpreted language, Python executes code one line at a time. If it encounters an error, it stops and generates an error report. This makes debugging a methodical process. This may also count as a weakness.
  • Python has a vast standard library capable of supporting most tasks, plus developers can use the Python package manager to import additional packages from an index of over 200k.
  • There is a very large and active community of Python developers. Many are happy to lend their support and insight if asked.

Applications where Python really shines

Python is used for an extremely wide range of software development projects spanning every industry imaginable. However, there are three major areas where Python really shines.

AI, Data Analytics, and Machine Learning – Nearly half of data scientists with less than five years of experience use Python. Data scientists are in extremely short supply for requiring a combination of high-end skills. Python enables them to set up and test new ideas and algorithms quickly (again fast prototyping).

Web and Web App Development – Python is supported by an extensive range of “batteries included” type tools with extensive libraries and modules for web development and advanced content management systems, like Django and Pyramid. Python is highly regarded for its security, scalability, and flexibility.

Prototyping and MVPs – As Python developers can accomplish more with fewer lines of code, apps can be created faster. The ability to create and test ideas fast is very helpful for generating user data and feedback for fast iteration. Startups engaged with incubator and accelerator programs usually don’t need fully functional apps on “Pitch Day” – so working with Python developers may be the best option for when your “funding runway” is its shortest.

Weaknesses and disadvantages of Python

As they say in sales, “Fast, Good, Cheap – Pick Two,” Python is no different. In this case, we can single out issues of speed and efficiency in terms of app performance. Speed and efficiency of development, however, are actually stellar. A lot of software is developed using two or more programming languages, so a lot of the limitations can be overcome. The idea is to use Python in the areas where it works best, and use another language in areas where it doesn’t.

The main weaknesses and disadvantages of Python are:

  • Python takes up a lot of memory, is not memory-efficient, and can present issues when running alongside other programs competing for RAM.
  • As an interpreted language, Python is slower than many other programming languages – because it does only execute one line of code at a time.
  • Python is not well-suited to a mobile environment, as it’s not supported by Android or iOS. However, frameworks like Kivy can make it comparatively easy to overcome this limitation.
  • Most browsers don’t support Python, so it typically is not used for client-side tasks. This is not much of a limitation as Python is frequently used and works well with JavaScript.
  • Though Python’s native database is weak, this disadvantage can be fairly easily offset with PostgreSQL and MySQL.
  • Python’s prone to runtime errors for a small variety of reasons and so requires extensive testing, but that holds true for all software development projects.

While Python definitely has a few weaknesses, there are plenty of ways to work around them.

Who else uses Python?

Millions of companies use Python for a wide spectrum of software development. Python also happens to be very popular with the US Government. You’ll probably recognize most of the following names – they all use Python in some significant way:

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Help for your Python tech stack

In all software development projects, it is important to create a software specification detailing which technologies it will use. Defining the tech stack is one important element of this. A tech stack encompasses programming languages, frameworks, servers, and databases. If you don’t feel you have the technical acumen to define the tech stack for your project, it’s highly recommended that you talk with a software engineer. If you wish to investigate yourself, we can recommend this site for covering a wide range of options for your Python project.

  • Popular Python frameworks: Django, Flask, Pyramid, Bottle, TurboGears, Web2py – to name a few.
  • Game development frameworks for Python: Kivy, Pygame, PyKyra, Pyglet, PyOpenGL
  • Data science frameworks and libraries – NumPy, Pandas, Matplotlib, SciPy, SciKit-Learn, TensorFlow
  • Template engines: Jinja2, Mako, Django Templates
  • Databases: PostgreSQL, SQLite, MySQL, MongoDB, Redis, MS SQL Server
  • Object-relational mappers: Django ORM, SQLAlchemy, Peewee
  • NoSQL databases: MongoDB, Redis, Apache Cassandra, Neo4j
  • Cloud platforms:  AWS, Google Cloud, Heroku, MS Azure, Digital Ocean, Python Anywhere
  • DevOps – for monitoring: Datadog, Rollbar, Sentry, Prometheus

In terms of Python tools for working with Big Data, developers indicate a preference for using Apache Spark or Dask in conjunction with JupiterLab. Apache Kafka, Apache Hadoop, and Apache Hive are also popular.

Additional Python developer statistics

Four out of five Python developers use Python as their primary programming language.
According to a JetBrains 2020 Survey of Python developers, JavaScript is the most popular language to combine with Python according to 42% of participants. It’s followed by HTML/CSS (39%), Bash/Shell (36%), SQL (34%) and C/C++ (27%). Other languages with which it sees significant use are Jave C#, PHP, Go, and TypeScript.

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The typical team size for Python developers is between 2 and 7 people (75%). Only 4% of Python developers work in teams of larger than 21 people. More interestingly, however, is that nearly 20% of Python developers work in companies with more than 5,000 employees indicating its growing popularity with enterprises. The distribution in company size is otherwise relatively even indicating its suitability for start-ups and SMBs, alike.

While used across the full spectrum of industries, as one might suspect, it is most used by companies involved in software development and Information Technology.

Python developers for your team

Demand for Python developers is steadily growing. Python’s ease of learning is catching on fast, with nearly a third of Python developers being new to professional software development. However, one out of six Python developers has eleven or more years of professional experience, while another two of six have 3-10 years.

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Source: JetBrains 2020 Python Developer Survey

When it comes to finding the right Python developers for your project, it’s highly desirable that they also have experience with the other components of your tech stack. With our large pool of software developers, we can help you find Python developers with the specific skills and experience needed for your project.

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