How to use integer_dtypes method in hypothesis

Best Python code snippet using hypothesis

datatypes.py

Source:datatypes.py Github

copy

Full Screen

1from numpy import obj2sctype, ndarray2from numpy import bool_3from numpy import byte, short, intc, int_, longlong, intp4from numpy import ubyte, ushort, uintc, uint, ulonglong, uintp5from numpy import single, float_, longfloat6from numpy import csingle, complex_, clongfloat7# These are only used for membership tests, but things break if they are sets8# rather than lists. TK, Jan 2012.9integer_dtypes = [10 int,11 uint,12 byte,13 short,14 intc,15 int_,16 longlong,17 intp,18 ubyte,19 ushort,20 uintc,21 uint,22 ulonglong,23 uintp]24try:25 integer_dtypes.append(long)26except NameError:27 pass # long is just int for Python 328float_dtypes = [float, single, float_, longfloat]29complex_dtypes = [complex, csingle, complex_, clongfloat]30bool_dtypes = [bool, bool_]31def check_type(stochastic):32 """33 type, shape = check_type(stochastic)34 Checks the type of a stochastic's value. Output value 'type' may be35 bool, int, float, or complex. Nonnative numpy dtypes are lumped into36 these categories. Output value 'shape' is () if the stochastic's value37 is scalar, or a nontrivial tuple otherwise.38 """39 val = stochastic.value40 if val.__class__ in bool_dtypes:41 return bool, ()42 elif val.__class__ in integer_dtypes:43 return int, ()44 elif val.__class__ in float_dtypes:45 return float, ()46 elif val.__class__ in complex_dtypes:47 return complex, ()48 elif isinstance(val, ndarray):49 if obj2sctype(val) in bool_dtypes:50 return bool, val.shape51 elif obj2sctype(val) in integer_dtypes:52 return int, val.shape53 elif obj2sctype(val) in float_dtypes:54 return float, val.shape55 elif obj2sctype(val) in complex_dtypes:56 return complex, val.shape57 else:58 return 'object', val.shape59 else:60 return 'object', ()61continuous_types = [float, complex]62def is_continuous(stochastic):63 dtype, shape = check_type(stochastic)64 if dtype in continuous_types:65 return True66 else:...

Full Screen

Full Screen

common.py

Source:common.py Github

copy

Full Screen

2from hypothesis.extra.numpy import arrays as hy_arrays3from hypothesis.extra.numpy import floating_dtypes, integer_dtypes4from hypothesis.strategies import one_of5hy_array_gen = hy_arrays(6 dtype=one_of(integer_dtypes(sizes=(32, 64)), floating_dtypes(sizes=(32, 64))),7 shape=array_shapes(),8)9hy_int_array_gen = hy_arrays(10 dtype=integer_dtypes(sizes=(32, 64)),11 shape=array_shapes(),...

Full Screen

Full Screen

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.

LambdaTest Learning Hubs:

YouTube

You could also refer to video tutorials over LambdaTest YouTube channel to get step by step demonstration from industry experts.

Run hypothesis automation tests on LambdaTest cloud grid

Perform automation testing on 3000+ real desktop and mobile devices online.

Try LambdaTest Now !!

Get 100 minutes of automation test minutes FREE!!

Next-Gen App & Browser Testing Cloud

Was this article helpful?

Helpful

NotHelpful