Mikhail Korobov
Head Of Development at Zyte (formerly Scrapinghub)
Yekaterinburg, Sverdlovsk Oblast, Russia
Summary
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Top expert inPython Development Ecosystem
Mikhail Korobov is a seasoned software leader with 17 years of experience, currently serving as Head of Development at Zyte (formerly Scrapinghub) in Yekaterinburg. He blends hands-on backend and full-stack engineering with technical leadership, having progressed from developer to Head of Data Science before his current role. Mikhail is an active open-source contributor across prominent Python projects—Scrapy, IPython, scikit-learn, Pillow and Theano—where he has fixed critical compatibility bugs, improved docs, and optimized core algorithms. His work shows a strong focus on reliability, testing and performance (e.g., vectorizing Viterbi in seqlearn, fixing memory leaks in bindings, and hardening sandbox limits in Splash). Comfortable across ML, NLP and web scraping ecosystems, he also has deep experience in Cython/C extensions and productionizing complex Python tooling. Colleagues would note his pragmatic approach to refactoring and documentation that makes hard internals accessible and maintainable.
17 years of coding experience
7 years of employment as a software developer
УГТУ УПИ
Stackoverflow
22,088reputation
5.1mreached
253answers
0questions
django-models
top-5%
scrapy
top-1%
pandas
top-5%
javascript
top-5%
django
top-1%
django-forms
top-1%
Github Skills (104)
python10
image-processing10
testing10
proxy10
ipython10
lua10
scrapy10
django-forms10
cython10
command-line-tool10
backend10
integration-testing10
javascript10
develop10
django10
Programming languages (19)
Github contributions (5)
scrapy/parsel
Dec 2013 - Nov 2022
Parsel lets you extract data from XML/HTML documents using XPath or CSS selectors
Role in this project:
Technical Writer
Technical WriterContributions:1 release, 53 reviews, 111 commits in 9 years
Contributions summary:Mikhail primarily contributed to the documentation of the `parsel` library, focusing on improving clarity and consistency. Their commits involved correcting typos, refining examples, and promoting the use of updated API methods like `.get()` and `.getall()` over older ones. They also incorporated the `.attrib` property into the documentation, which was a new feature. Additionally, the user made adjustments to the documentation build process, ensuring a smooth and accurate presentation of the library's functionality.
css-selectorshtml-documentparselxmlxpath
scrapinghub/python-crfsuite
Apr 2014 - Jan 2022
A python binding for crfsuite
Role in this project:Backend Developer
Backend DeveloperContributions:205 commits, 38 PRs, 85 pushes in 7 years 10 months
Contributions summary:Mikhail primarily focused on improving and refactoring the Python-based CRFsuite library, particularly its Python bindings. Their contributions included modifying the Cython wrapper to support additional data formats for training and prediction, enhancing the training process through logging and parameter customization, and fixing existing issues related to memory leaks and file handling. These changes reflect a focus on improving the library's functionality, usability, and stability.
crfsuitepythondata-sciencecrf
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