pip install scrapy cat > myspider.py <<EOF import scrapy class BlogSpider(scrapy.Spider): name = 'blogspider' start_urls = ['https://www.zyte.com/blog/'] def parse(self, response): for title in response.css('.oxy-post-title'): yield {'title': title.css('::text').get()} for next_page in response.css('a.next'): yield response.follow(next_page, self.parse)EOF scrapy runspider myspider.py

Welcome to PyGreSQL¶ About PyGreSQL Copyright notice Download information Current PyGreSQL versions Older PyGreSQL versions Changes and Future Development Installation Distribution files Project home sites The PyGreSQL documentation Contents Indices and tables PyGreSQL Development and Support Mailing list Access to the source repository Issue Tracker Support Project home sites PyGreSQL Navigation

Generating Excel 97+ files with Python 2.4+ (need decorators), importing Excel 95+ files, support for UNICODE in Excel files, using variety of formatting features and printing options, Excel files and OLE2 compound files dumper. No need in Windows/COM

py2exe py2exe is a Python Distutils extension which converts Python scripts into executable Windows programs, able to run without requiring a Python installation. Development is hosted on GitHub. You can find the mailing list, svn, and downloads for Python 2 there. Downloads for Python 3 are on PyPI. py2exe was originally developed by Thomas Heller who still makes contributions. Jimmy Retzlaff, Ma

You didn't write that awful page. You're just trying to get some data out of it. Beautiful Soup is here to help. Since 2004, it's been saving programmers hours or days of work on quick-turnaround screen scraping projects. Beautiful Soup is a Python library designed for quick turnaround projects like screen-scraping. Three features make it powerful: Beautiful Soup provides a few simple methods and

Matplotlib: Visualization with Python Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. Create publication quality plots. Make interactive figures that can zoom, pan, update. Customize visual style and layout. Export to many file formats. Embed in JupyterLab and Graphical User I

NumPy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object sophisticated (broadcasting) functions tools for integrating C/C++ and Fortran code useful linear algebra, Fourier transform, and random number capabilities Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional containe

News 09.03.2016 MDP 3.5 released! This is a bug-fix release Note that from this release MDP is in maintenance mode. 13 years after its first public release, MDP has reached full maturity and no new features are planned in the future. If you plan to do serious machine learning in Python, use sklearn. Note though that some algorithms, notably SFA and Growing Neural Gas, are only available in MDP. We