What does a python development engineer do?

Python development engineer refers to the position of an engineer who uses Python to develop software.

Python is a high-level scripting language that combines interpretation, compilation, interactivity and object-oriented. Python is designed to be highly readable. It often uses English keywords and some punctuation marks in other languages, and it has a more distinctive grammatical structure than other languages.

The Python development engineer is the collective name for those who are engaged in software development related to the Python language. The technical requirements for Python development engineers are relatively comprehensive.

So what are the roles of Python engineers in the enterprise? Mainly covering the following four major business modules:

1. Verification algorithm:

Mainstream research directions include but are not limited to video algorithm engineers, image processing algorithm engineers, audio algorithm engineers, and communication baseband Algorithm engineer, signal algorithm engineer, etc. Able to obtain the required output within a limited time for certain standardized inputs. If an algorithm is flawed or inappropriate for a problem, executing the algorithm will not solve the problem. Different algorithms may use different time, space, or efficiency to complete the same task. The quality of an algorithm can be measured by its space complexity and time complexity.

2. Rapid development:

You should be familiar with this rapid development, which is to use a relatively mature framework and relatively less code to develop a website. Python has many advantages in the front and backend of the website. Less mature frameworks, such as flask, bottle, tornado, etc., are commonly used. At present, many well-known websites at home and abroad are developed using Python, such as domestic Zhihu, Douban and other websites.

3. Test operation and maintenance:

refers to the testing tools and processes implemented in python, including automated testing processes such as server-side, client-side, web, etc., the execution of automated performance tests, For monitoring and analysis, commonly used frameworks include selenium, appium, etc. Python can write a lot of scripts, and the daily operations in operation and maintenance work cover monitoring, deployment, network configuration, log analysis, security detection and other "operations" to the extreme. Moreover, Python is also rich in server management tools, such as configuration management (saltstack), batch execution (fabric, saltstack), virtualization management (python-libvirt), cloud computing (openstack), etc.

4. Data analysis:

NmPy, SciPy and Matplotlib are recognized as the most outstanding libraries in the Python field. NumPy is a general-purpose library that not only supports commonly used numerical arrays, but also provides functions for efficient processing of these arrays. SciPy is Python's scientific computing library. It has greatly expanded the functions of NumPy, and some of its functions overlap. Matplotlib is a 2D plotting library that provides good support for drawing graphics and images. Currently, Matplotlib has been integrated into SciPy and supports NumPy.

For more Python related technical articles, please visit the Python Tutorial column to learn!

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