A commanding view of your test-coverage.
“A commanding view of your test-coverage”
The command-line tool cuv provided by this package gives some useful tools to visualize your project’s coverage data. This means you must first run coverage against your project’s test-suite.
Once you have a .coverage file, you can use the commands documented below (or just type cuv to explore the help).
We utilize several quality open-source packages to achieve this:
Background + Terminology
This started out as some experiments in “whole-project coverage visualization”, and then also grew some console tools that I find useful when working with Python code. There are a few hack-job proof-of-concept visualizations in the works as well.
Modern MacBooks have resolution up to 2880x1800, and 4k displays can be something like 3840x2160 – I thought it might be interesting to try and view the coverage of a “whole project at once”. Some of these experiments can be seen with cuv pixel.
Whenever I say “line”, I mean a “statement” as defined by coverage.py – this just means we ignore all comments and other non-code lines in the visualizations. So, each file will usually appear to have far fewer total lines than if you ran wc or ohcount against it.
Although I’ve done some code-cleanups and rudimentary testing, this “works for me” but might not “work for your setup” ;)
As far as my setup, I am using Debian with a 256-color and unicode capable shell using Solarized Dark color schemes. There are probably bugs with other setups, and to a reasonable extent I’m happy to accept pull-reqeusts fixing these. That said, a unicode-capable shell is a must.
Notes on Tox
If you’re using tox to run tests (and you should, it’s great!) your coverage files will – depending upon setup – end up in .tox/envname/.coverage or similar. So, you will either need to use --coverage to point cuv’ner at the right file, or simply move it to the top-level of your project for ease-of-use.
The two main tools usable directly in the console are cuv graph and cuv lessopen. cuv spark can provide some amusement as well.
This displays all the files in your project and a histogram-like graph of their coverage. Each character represents 8 lines of code, and uses a group of unicode characters (0x2580 through 0x2587) to draw a little graph. So, if those 8 lines are not covered at all, the graph will be all red; if they’re all covered, it will be all green. If 2 out of the 8 lines are covered, there will be about 25% green and the rest red.
The total size of each file can thus be easily seen (by the length of the histogram part, which wraps to subsequent lines if needed) and an idea of which parts are covered is given.
- testing on more terminal types
- how does it look when using something besides Solarized Dark?
- useful, beyond eye-candy?
This command is intended to be used via the LESSOPEN environment variable, which lets you pre-process files that are opened with less. So, once set up (see the help via cuv lessopen --help) you can simply run less on any file in your project, and it will get syntax-highlighted and show you the line-by-line coverage with a leading green or red mini-verical bar and red background (for uncovered lines).
A header appears at the top showing the total coverage for this particular file.
You can pipe a git diff to this and see a colorized version of the diff in your console. I am using a library called unidiff to read the actual diff, which so far works quite nicely. That said, I’ve only tried against the output of Git, like so:
git diff | cuv diff | less
- colors are unsatisfying, since for added lines they’re pretty much the same as Git’s colored output
- maybe make it look more like the “real” underlying diff? (e.g. re-create the @@ and so forth things)
- does it work with merge commits?
This shows a “spark-line” sort of thing in the console. It’s not very useful for big projects (e.g. Twisted), but gives a very quick overview of the coverage in a small amount of space. Using the same unicode characters as cuv graph, this represents each file as a single character, and its percentage coverage is graphed (so you only get granularity down to about 12.5%).
cuv hist produces an SVG-based “histogram” type of display, showing every line in all your files. Each little vertical bar represents a single line of course code, and is red if it was not covered or yellow if it was partially covered (only when you enable --branch coverage).
You may view this in Firefox, for example.
- figure out how to display the text better
- options for the size or aspect ratio desired
- file size is huge; can we do better?
- is an image really the better way to go (size-wise)?
(Very much in-progress, just proof-of-concept at the moment). Produces a very-tiny representation of every line of your code, organized into 80-character wide columns with each pixel (or 2x2, 1x1, or 2x1 square) representing a single character of source code, syntax-highlighted and coloured by coverage data. So, this shows the overall “shape” of your code along with coverage information.
For a small project (e.g. txtorcon) this works fairly well – in fact, ever “unreadably small” fonts can be used per-glyph and still fit on a single screen. For a larger project (e.g. Twisted, over 350k lines of code) this is a bit more problemmatic – however, with 1 pixel per glyph and 80-character width you can still get the entire project visualized on two screenfulls of a 3840x2160 display, albeit with a nearly 10MB png image…
In between those two, Crossbar.io – which weighs in at ~112k lines of code – can easily fit on a single macbook display.
Still, I’m not sure if it’s really useful but does look kind of neat. What would be useful is to have more interactivity – e.g. a single-screen “overview” that had mouse-over effects to zoom in on particular bits of code, shown in a “real” font…
Now, this would almost certainly work way better and faster for local developers as a GTK+/Qt “native” application – but a Web-based thing was fairly fast to prototype, and has the advantage that you can publish it easily as part of your project for visitors who probably don’t want to try and install a Python GUI application…
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