Package: cel-python
Pure Python implementation of Google Common Expression Language,https://opensource.google/projects/cel.The Common Expression Language (CEL) implements common semantics for expression evaluation,
enabling different applications to more easily interoperate.Key ApplicationsSecurity policy: organization have complex infrastructure and need common tooling to reason about the system as a wholeProtocols: expressions are a useful data type and require interoperability across programming languages and platforms.This implementation has minimal dependencies, runs quickly, and can be embedded into Python-based applications.
Specifically, the intent is to be part of Cloud Custodian, C7N, as part of the security policy filter.Installationpip install cel-pythonYou now have the CEL run-time available to Python-based applications.Command LineWe can read JSON directly from stdin, making this a bit likejq.% python -m celpy '.this.from.json * 3 + 3' <<EOF
heredoc> {"this": {"from": {"json": 13}}}
heredoc> EOF
42It’s also a desk calculator, likeexpr, but with float values:% python -m celpy -n '355.0 / 113.0'
3.1415929203539825It’s not as sophistcated asbc.
But, yes, this has a tiny advantage overpython-c'355/113'. Most notably, the ability
to embed Google CEL into other contexts where you don’treallywant Python’s power.It’s also capable of decision-making, liketest:% echo '{"status": 3}' | python -m celpy -sb '.status == 0'
false
% echo $?
1We can provide a-aoption to define objects with specific data types.
This is particularly helpful for providing protobuf message definitions.python -m celpy -n --arg x:int=6 --arg y:int=7 'x*y'
42If you want to see details of evaluation, use-v.python -m celpy -v -n '[2, 4, 6].map(n, n/2)'
... a lot of output
[1, 2, 3]LibraryTo follow the pattern defined in the Go implementation, there’s a multi-step
process for compiling a CEL expression to create a runnable “program”. This program
can then be applied to argument values.>>> import celpy
>>> cel_source = """
... account.balance >= transaction.withdrawal
... || (account.overdraftProtection
... && account.overdraftLimit >= transaction.withdrawal - account.balance)
... """

>>> env = celpy.Environment()
>>> ast = env.compile(cel_source)
>>> prgm = env.program(ast)

>>> activation = {
...     "account": celpy.json_to_cel({"balance": 500, "overdraftProtection": False}),
...     "transaction": celpy.json_to_cel({"withdrawal": 600})
... }
>>> result = prgm.evaluate(activation)
>>> result
BoolType(False)The Python classes are generally based on the object model inhttps://github.com/google/cel-goThese types semantics are slightly different from Python’s native semantics.
Type coercion is not generally done.
Python//truncates toward negative infinity. Go (and CEL)/truncates toward zero.DevelopmentThe parser is based on the grammars used by Go and C++, but processed through Python Lark.Seehttps://github.com/google/cel-spec/blob/master/doc/langdef.mdhttps://github.com/google/cel-cpp/blob/master/parser/Cel.g4https://github.com/google/cel-go/blob/master/parser/gen/CEL.g4NotesCEL provides a number of runtime errors that are mapped to Python exceptions.no_matching_overload: this function has no overload for the types of the arguments.no_such_field: a map or message does not contain the desired field.return error for overflow: integer arithmetic overflowsThere are mapped to Pythoncelpy.evaluation.EvalErrorexception. The args will have
a message similar to the CEL error message, as well as an underlying Python exception.In principle CEL can pre-check types.
However, seehttps://github.com/google/cel-spec/blob/master/doc/langdef.md#gradual-type-checking.
Rather than try to pre-check types, we’ll rely on Python’s implementation.ContributingSeehttps://cloudcustodian.io/docs/contribute.htmlCode of ConductThis project adheres to theOpen Code of Conduct. By
participating, you are expected to honor this code.