Hypothesis strategies for generating Python programs, something like CSmith.
This is definitely pre-alpha, but if you want to play with it feel free! You can even keep the shiny pieces when - not if - it breaks.
You can run the tests, such as they are, with
tox on Python 3.6 or later. Use
tox -va to see what environments are available.
This package provides two Hypothesis strategies for generating Python source code.
The generated code will always be syntatically valid, and is useful for testing parsers, linters, auto-formatters, and other tools that operate on source code.
DO NOT EXECUTE CODE GENERATED BY THESE STRATEGIES.
It could do literally anything that running Python code is able to do, including changing, deleting, or uploading important data. Arbitrary code can be useful, but "arbitrary code execution" can be very, very bad.
hypothesmith.from_grammar(start="file_input", *, auto_target=True)
Generates syntactically-valid Python source code based on the grammar.
Valid values for
"eval_input"; respectively a single interactive statement, a module or sequence of commands read from a file, and input for the eval() function.
True, this strategy uses
hypothesis.target() internally to drive towards larger and more complex examples. We recommend leaving this enabled, as the grammar is quite complex and only simple examples tend to be generated otherwise.
hypothesmith.from_node(node=libcst.Module, *, auto_target=True)
Generates syntactically-valid Python source code based on the node types defined by the
You can pass any subtype of
libcst.CSTNode. Alternatively, you can use Hypothesis' built-in
from_type(node_type).map(lambda n: libcst.Module([n]).code, after Hypothesmith has registered the required strategies. However, this does not include automatic targeting and limitations of LibCST may lead to invalid code being generated.