parsel vs. Scrapy vs. h5py vs. python-sql Comparison Chart

Parsel is a BSD-licensed Python library to extract and remove data from HTML and XML using XPath and CSS selectors, optionally combined with regular expressions. Create a selector object for the HTML or XML text that you want to parse. Then use CSS or XPath expressions to select elements. CSS is a language for applying styles to HTML documents. It defines selectors to associate those styles with specific HTML elements. XPath is a language for selecting nodes in XML documents, which can also be used with HTML. You can use either CSS or XPath. CSS is usually more readable, but some things can only be done with XPath. Being built atop lxml, parsel selectors support some EXSLT extensions and come with pre-registered namespaces to use in XPath expressions. Parsel selectors allow you to chain selectors, so most of the time you can just select by class using CSS and then switch to XPath when needed.

The h5py package is a Pythonic interface to the HDF5 binary data format. It lets you store huge amounts of numerical data, and easily manipulate that data from NumPy. For example, you can slice into multi-terabyte datasets stored on disk, as if they were real NumPy arrays. Thousands of datasets can be stored in a single file, categorized and tagged however you want. H5py uses straightforward NumPy and Python metaphors, like dictionary and NumPy array syntax. For example, you can iterate over datasets in a file, or check out the .shape or .dtype attributes of datasets. You don't need to know anything special about HDF5 to get started. In addition to the easy-to-use high level interface, h5py rests on a object-oriented Cython wrapping of the HDF5 C API. Almost anything you can do from C in HDF5, you can do from h5py.