A library based on `PyYAML` that promises to parse YAML documents and produce Python objects, for executing Python code within YAML documents and instantiating Python objects based on YAML arguments.
Project description
InYAML
Overview
The library based on PyYAML
promises to parse YAML documents and produce Python objects, for executing Python code within YAML documents and instantiating Python objects based on YAML arguments.
Features
- Executable YAML: This introduces Python code defined within YAML documents when the code is not wrapped in the
""
or''
. It supports importing modules, executing arbitrary Python expressions directly from YAML. - Instantiable YAML: It is ot only
Executable
but also supports instantiating Python objects as defined by class or function tags in YAML. This allows the YAML to not just carry data but also semantic information about how the data should be instantiated into Python objects. - Dynamic Import and Execution: Functionality to dynamically import Python modules and execute functions as specified in the YAML, providing flexibility and powerful integration capabilities.
Key Components
ExecutableConstructor
:
- Executes Python codes or expressions within YAML.
- Manages import (
__import__
as the default key) and run (__run__
as the default key) executions through special YAML keys. - Ensures that only designated code is executed to maintain safety.
InstantiableConstructor
: - Inherits from
ExecutableConstructor
. - Adds the capability to instantiate objects using type specifications provided in YAML tags.
- Supports advanced features like namespace and argument passing for constructors.
load
Function: - Parses YAML documents and uses either
ExecutableConstructor
orInstantiableConstructor
based on whetheris_instantiable
isTrue
. - All imported modules or classes will be stores in the imported targets attribute (
__import__
as the default identifier) of the outermostNamespace
.
Installation
pip install inyaml
Usage Example
import inyaml
class TestClass:
def __init__(self, *args, **kwargs):
print(args)
print(kwargs)
print('TestClass')
def test_run_function(arg=0):
print(arg)
input_data = """
add: 1+2
string: "string"
number: 3
outer_namespace: &ref
inner_namespace:
first: [9+ 8,{'any_number':99}]
second: {"any_number":333}
list: [{'any_float':99.1}, 1, 2, 3+4, *ref]
__import__ (np): numpy
dict: {"any_number_in_a_dict":444}
__run__: test_run_function()
instance: !TestClass
string: "from"
__args__: [1,2,3]
__kwargs__:
first: 1
second: 2
number: 12345
np_array: !np.array ~([1, 20, 300])
np_array_2: !np.array [[1, 20, 300]]
__run__: test_run_function(25)
"""
print(inyaml.load(input_data))
Safety Notice
While this library allows execution of Python code specified in YAML, it should be used with caution to avoid executing untrusted code, especially in applications where YAML documents could come from untrusted sources.
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