Resources for Unit-Testing

We implement our own command in Python and distribute it via pip with pip install sheet2graph.

The command takes spreadsheets files (csv, xlsx) as input, and generates images (png, jpg, svg) based on the data contained.

We will setup testing in our project to check the features we implemented.

• The unittest module in Python
• Add a test target to the Makefile
• Test loaders
• Assertions in testing
• Adding tests cache to .gitignore

Once we have the infrastructure for testing, we will write a few helpers to make the tests more concise and easier to write.

• Setup and teardown in a test suite
• Using Shutil to deal with filesystem operations
• Checking that a file is created in a specific path
• Checking the size of an image with PIL
• Running a command line application from a test

After the testing infrastructure and helpers are ready, we are writing the tests for our commandline application.

• Testing input files
• Testing location of output files
• Testing generated image sizes
• Testing graph types

We will be making our command a bit friendlier, improving the default behaviour with informative messages for the user.

• New option to print help of command
• Print version of the command
• Default behaviour. No flags prints the version and exits
• Testing the output of our command with os.system and subprocess

For each axis, we will allow the user to use expressions like 'b4,b5,b6,b7' or 'B4:B7' to select cells or ranges to graph.

• Add options '-x' and '-y' to select the data to be graphed
• Making the expressions case-insensitive
• Implementing a comma separated selection option
• Implementing a range selection option
• Adding tests first and making them pass after implementation, as in Test-Driven-Development (TDD)
• Better and more informative user messages in case of error
• Verifying and fixing problems in our Pandas implementation

We will check everything is working so far and add extra options to set the axis labels to a custom user-defined value.

• Debugging broken tests and making all tests pass after all our changes
• Adding an x label and y label options to our command, to specify the labels in the horizontal and vertical axis
• Debugging column types in pandas
• Using exceptions to deal with unreliable cases