Related to #94, which is about classifying generated values and showing stats about those classes.
It might be nice to show stats unrelated to classifications too: for example, here's a doc on how Hypothesis does things: there, if you run with cmdline argument --hypothesis-show-statistics, you'll see:
- during generate phase (0.06 seconds):
- Typical runtimes: < 1ms, ~ 47% in data generation
- 100 passing examples, 0 failing examples, 0 invalid examples
- Stopped because settings.max_examples=100
or, if you use something that throws out a value with invalid (eg. filter, andThen, ...),
test_even_integers:
- during generate phase (0.08 seconds):
- Typical runtimes: < 1ms, ~ 57% in data generation
- 100 passing examples, 0 failing examples, 12 invalid examples
- Events:
* 51.79%, Retried draw from integers().filter(lambda x: x % 2 == 0) to satisfy filter
* 10.71%, Aborted test because unable to satisfy integers().filter(lambda x: x % 2 == 0)
- Stopped because settings.max_examples=100
or, if you use an event function to classify a generated value,
test_even_integers:
- during generate phase (0.09 seconds):
- Typical runtimes: < 1ms, ~ 59% in data generation
- 100 passing examples, 0 failing examples, 32 invalid examples
- Events:
* 54.55%, Retried draw from integers().filter(lambda x: x % 2 == 0) to satisfy filter
* 31.06%, i mod 3 = 2
* 28.79%, i mod 3 = 0
* 24.24%, Aborted test because unable to satisfy integers().filter(lambda x: x % 2 == 0)
* 15.91%, i mod 3 = 1
- Stopped because settings.max_examples=100
Related to #94, which is about classifying generated values and showing stats about those classes.
It might be nice to show stats unrelated to classifications too: for example, here's a doc on how Hypothesis does things: there, if you run with cmdline argument
--hypothesis-show-statistics
, you'll see:or, if you use something that throws out a value with
invalid
(eg.filter
,andThen
, ...),or, if you use an
event
function to classify a generated value,