Reference: https://www.jetbrains.com/research/python-developers-survey-2018/
- JavaScript
- Data Analysis
- Web Development
- DevOps/SysAdmin/Automation Scrits
- Testing: 93% Professionally / 7 % Hobby
- DevOps: 90% Professionally / 10 % Hobby
- Web Dev: 87% Professionally / 13 % Hobby
- Web Development
- Data Analysis
- ML
- DevOps
- 38% OS-provided Python (via apt-get, yum, homebrew, etc.)
- 33% Python.org
- 22% Anaconda
- 15% I use Docker containers
- 15% pyenv
- 64% Virtualenv / pipenv
- 31% Docker
- 22% Conda
- 9% Vagrant
- 3% Other
- 21% None
- 47% Flask
- 45% Django
- 62% Numpy
- 51% Pandas
- 46% Matplotlib
- 53% REquests
- 29% Pillow
- 19% Scrapy
- 18% Asyncio
- 18% Tkinter
- 16% PyQT
- 36% AWS
- 29% Google App Engine
- 26% Heroku
- 23% Digital Ocean
- 47% In Virtual Machines
- 40% Within Containers
- 28% On a Platform-as-a-Service
- 21% Serverless
- 56% Locally with virtualenv (or similar)
- 35% In Docker containers
- 24% In virtual machines
- 17% With local system interpreter
- 17% In remote development environments
- 9% Directly in the production environment
- 69% Linux
- 47% Windows
- 32% MacOS
- 46% pytest
- 32% unittest
- 15% mock
- 44% PostgreSQL
- 41% MySQL
- 41% SQLite
- 20% MongoDB
- 19% Redis
- 11% MS SQL Server
- 8% Oracle DB
- 3% Amazon Redshift
- 3% Cassandra
- 1% DB2
- 1% Couchbase
- 34% SQLAlchemy
- 33% Django ORM
- 4% SQLObject
- 12% Apache SPark
- 76% None
- 25% Jenkins/Hudson
- 18% Gitlab CI
- 18% Travis CI
- 7% Circl CI
- 46% None
- 20% Ansible
- 9% Custom Solution
- 6% Puppet
- 4% Salt
- 4% Chef
- 65% None
- 20% PyCharm Professional Edition
- 16% VSCode
- 15% PyCharm Community Edition
We’ve identified the relative popularity of the tools and features used to develop in Python: version control, code autocompletion, code refactorings, writing unit tests, and using virtual environments for Python projects all occupy the top spots.
- 62% Fully Employed by a company/organization
- 19% Student
- 6% Freelancer
- 73% Developer/programmer
- 19% Architect
- 19% Data analyst
- 42% Yes, I work on many different projects
- 48% Work in a team
- 48% Work on your own projects individually
- 4% work as an external consultant or trainer
-74% (2-7 ppl)
....
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Python 3 adoption rate is growing fast and is already at 84%, while Python 2 is used as the main interpreter by only 16% of Python users. That’s a huge jump in popularity for Python 3, from 75% in 2017.
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Data analysis has become more popular than web development among Python users, growing from 50% in 2017 to 58% in 2018.
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Half of all developers using Python as their main language also use JavaScript. Python is also frequently used together with HTML/CSS, Bash/Shell, SQL, C/C++, and Java.
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Flask and Django are the most popular frameworks among web developers. Having equal shares (around 45% each), they leave other Python web frameworks far behind.
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NumPy, Pandas, Matplotlib, and SciPy are the most popular data science frameworks and libraries. Machine learning-specific libraries such as SciKit-Learn, TensorFlow, Keras, and others are also quite popular.
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AWS is the most popular cloud platform for Python developers, followed by Google Cloud Platform, Heroku, DigitalOcean, and Microsoft Azure.
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In 2018, we had significantly more respondents who are involved in DevOps (an increase of 8 percentage points compared to 2017). In terms of Python users using Python as their secondary language, DevOps has overtaken web development.
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PyCharm with its two editions is the most popular tool for Python development. Interestingly enough, VS Code has expanded from 7% in 2017 to 16% in 2018, making it the second most popular editor for Python development. Other popular editors for Python include Vim, Sublime, and Jupyter Notebook.
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Surprisingly, almost two-thirds of Python developers choose Linux as their development environment OS.
nice