Details

• Talktorial ID: T011
• Title: Querying online API webservices
• Original authors: Jaime Rodríguez-Guerra
• Reviewer(s): David Schaller
• Date of review:

Content review

• Potential labels or categories (e.g. machine learning, small molecules, online APIs): XXXXXX
• One line summary: XXXXXXXXXX
• The table of contents reflects the talktorial story-line; order of #, ##, ### headers is correct
• URLs are linked with meaningful words, instead of pasting the URL directly or linking words like here.
• I have spell-checked the notebook
• Images have enough resolution to be rendered with quality, without being too heavy.
• All figures have a description
• Markdown cell content is still in-line with code cell output (whenever results are discussed)
• I have checked that cell outputs are not incredibly long (this applies also to DataFrames)
• Formatting looks correctly on the Sphinx render (bold, italics, figure placing)

Code review

• Time it took to execute (approx.):
• Variable and function names follow snake case rules (e.g. a_variable_name vs aVariableName)
• Spacing follows PEP8 (run Black on the code cells if needed)
• Code line are under 99 characters each (run black -l 99)
• Comments are useful and well placed
• There are no unpythonic idioms like for i in range(len(list)) (see slides)
• All 3rd party dependencies are listed at the top of the notebook
• I have marked all code cell with output referenced in markdown cells with the label # TODO: CI
• I have identified potential candidates for a code refactor / useful functions
• All import ... lines are at the top (practice part) cell, ordered by standard library / 3rd party packages / our own (teachopencadd.*)
• I have update the relative paths to absolute paths.
• List here unfamiliar libraries you find in the imports and their intended use: