history: | 20090524T134300, brand new docs. |
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history: | 20090613T164000, final touches for 3.0 |
history: | 20090913T084400, new command line syntax |
When you install coverage, a command-line script called coverage is placed in your Python scripts directory. Coverage has a number of commands which determine the action performed:
You collect execution data by running your Python program with the run coverage command:
$ coverage run my_program.py arg1 arg2
blah blah ..your program's output.. blah blah
Your program runs just as if it had been invoked with the Python command line. Arguments after your file name are passed to your program in sys.argv.
By default, coverage does not measure code installed with the Python interpreter. If you want to measure that code as well as your own, add the -L flag.
If your coverage results seems to be overlooking code that you know has been executed, try running coverage again with the --timid flag. This uses a simpler but slower trace method. Projects that use DecoratorTools, including TurboGears, will need to use --timid to get correct results. This option can also be set with the environment variable COVERAGE_OPTIONS set to --timid.
Coverage collects execution data in a file called “.coverage”. If need be, you can set a new file name with the COVERAGE_FILE environment variable. By default, each run of your program starts with an empty data set. If you need to run your program multiple times to get complete data (for example, because you need to supply disjoint options), you can accumulate data across runs with the -a flag on the run command.
To erase the collected data, use the erase command:
$ coverage erase
If you need to collect coverage data from different machines, coverage can combine multiple files into one for reporting. Use the -p flag during execution to append a machine name and process id to the .coverage data file name.
Once you have created a number of these files, you can copy them all to a single directory, and use the combine command to combine them into one .coverage data file.
Coverage provides a few styles of reporting. The simplest is a textual summary produced with report:
$ coverage report
Name Stmts Exec Cover
---------------------------------------------
my_program 20 16 80%
my_module 15 13 86%
my_other_module 56 50 89%
---------------------------------------------
TOTAL 91 79 87%
For each module executed, the report shows the count of executable statements, the number of those statements executed, and the resulting coverage, expressed as a percentage.
The -m flag also shows the line numbers of missing statements:
$ coverage report -m
Name Stmts Exec Cover Missing
-------------------------------------------------------
my_program 20 16 80% 33-35, 39
my_module 15 13 86% 8, 12
my_other_module 56 50 89% 17-23
-------------------------------------------------------
TOTAL 91 79 87%
You can restrict the report to only certain files by naming them on the command line:
$ coverage report -m my_program.py my_other_module.py
Name Stmts Exec Cover Missing
-------------------------------------------------------
my_program 20 16 80% 33-35, 39
my_other_module 56 50 89% 17-23
-------------------------------------------------------
TOTAL 76 66 87%
The -o flag omits files that begin with specified prefixes. For example, this will omit any modules in the django directory:
$ coverage report -m -o django
Coverage can annotate your source code for which lines were executed and which were not. The html command creates an HTML report similar to the report summary, but as an HTML file. Each module name links to the source file decorated to show the status of each line.
Here’s a sample report.
Lines are highlighted green for executed, red for missing, and gray for excluded. The counts at the top of the file are buttons to turn on and off the highlighting.
The -d argument to specify an output directory is required:
$ coverage html -d covhtml
The annotate command produces a text annotation of your source code. With a -d argument specifying an output directory, each Python file becomes a text file in that directory. Without -d, the files are written into the same directories as the original Python files.
Coverage status for each line of source is indicated with a character prefix:
> executed
! missing (not executed)
- excluded
For example:
# A simple function, never called with x==1
> def h(x):
"""Silly function."""
- if 0: #pragma: no cover
- pass
> if x == 1:
! a = 1
> else:
> a = 2