mirror of
https://github.com/hwchase17/langchain
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256 lines
8.0 KiB
Python
256 lines
8.0 KiB
Python
"""Test for Serializable base class"""
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import json
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import os
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from typing import Any, Dict, List
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from unittest.mock import patch
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import pytest
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from langchain.chains.llm import LLMChain
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from langchain_core.load.dump import dumps
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from langchain_core.load.serializable import Serializable
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from langchain_core.prompts.chat import ChatPromptTemplate, HumanMessagePromptTemplate
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from langchain_core.prompts.prompt import PromptTemplate
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from langchain_core.pydantic_v1 import Field, root_validator
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from langchain_core.tracers.langchain import LangChainTracer
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class Person(Serializable):
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secret: str
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you_can_see_me: str = "hello"
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@classmethod
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def is_lc_serializable(cls) -> bool:
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return True
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@property
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def lc_secrets(self) -> Dict[str, str]:
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return {"secret": "SECRET"}
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@property
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def lc_attributes(self) -> Dict[str, str]:
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return {"you_can_see_me": self.you_can_see_me}
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class SpecialPerson(Person):
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another_secret: str
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another_visible: str = "bye"
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@classmethod
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def get_lc_namespace(cls) -> List[str]:
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return ["my", "special", "namespace"]
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# Gets merged with parent class's secrets
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@property
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def lc_secrets(self) -> Dict[str, str]:
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return {"another_secret": "ANOTHER_SECRET"}
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# Gets merged with parent class's attributes
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@property
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def lc_attributes(self) -> Dict[str, str]:
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return {"another_visible": self.another_visible}
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class NotSerializable:
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pass
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def test_person(snapshot: Any) -> None:
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p = Person(secret="hello")
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assert dumps(p, pretty=True) == snapshot
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sp = SpecialPerson(another_secret="Wooo", secret="Hmm")
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assert dumps(sp, pretty=True) == snapshot
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assert Person.lc_id() == ["tests", "unit_tests", "load", "test_dump", "Person"]
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assert SpecialPerson.lc_id() == ["my", "special", "namespace", "SpecialPerson"]
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def test_typeerror() -> None:
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assert (
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dumps({(1, 2): 3})
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== """{"lc": 1, "type": "not_implemented", "id": ["builtins", "dict"], "repr": "{(1, 2): 3}"}""" # noqa: E501
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)
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@pytest.mark.requires("openai")
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def test_serialize_openai_llm(snapshot: Any) -> None:
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from langchain_community.llms.openai import OpenAI
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with patch.dict(os.environ, {"LANGCHAIN_API_KEY": "test-api-key"}):
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llm = OpenAI( # type: ignore[call-arg]
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model="davinci",
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temperature=0.5,
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openai_api_key="hello",
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# This is excluded from serialization
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callbacks=[LangChainTracer()],
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)
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llm.temperature = 0.7 # this is reflected in serialization
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assert dumps(llm, pretty=True) == snapshot
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@pytest.mark.requires("openai")
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def test_serialize_llmchain(snapshot: Any) -> None:
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from langchain_community.llms.openai import OpenAI
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llm = OpenAI(model="davinci", temperature=0.5, openai_api_key="hello") # type: ignore[call-arg]
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prompt = PromptTemplate.from_template("hello {name}!")
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chain = LLMChain(llm=llm, prompt=prompt)
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assert dumps(chain, pretty=True) == snapshot
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@pytest.mark.requires("openai")
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def test_serialize_llmchain_env() -> None:
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from langchain_community.llms.openai import OpenAI
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llm = OpenAI(model="davinci", temperature=0.5, openai_api_key="hello") # type: ignore[call-arg]
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prompt = PromptTemplate.from_template("hello {name}!")
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chain = LLMChain(llm=llm, prompt=prompt)
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import os
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has_env = "OPENAI_API_KEY" in os.environ
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if not has_env:
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os.environ["OPENAI_API_KEY"] = "env_variable"
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llm_2 = OpenAI(model="davinci", temperature=0.5) # type: ignore[call-arg]
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prompt_2 = PromptTemplate.from_template("hello {name}!")
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chain_2 = LLMChain(llm=llm_2, prompt=prompt_2)
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assert dumps(chain_2, pretty=True) == dumps(chain, pretty=True)
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if not has_env:
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del os.environ["OPENAI_API_KEY"]
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@pytest.mark.requires("openai")
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def test_serialize_llmchain_chat(snapshot: Any) -> None:
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from langchain_community.chat_models.openai import ChatOpenAI
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llm = ChatOpenAI(model="davinci", temperature=0.5, openai_api_key="hello") # type: ignore[call-arg]
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prompt = ChatPromptTemplate.from_messages(
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[HumanMessagePromptTemplate.from_template("hello {name}!")]
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)
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chain = LLMChain(llm=llm, prompt=prompt)
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assert dumps(chain, pretty=True) == snapshot
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import os
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has_env = "OPENAI_API_KEY" in os.environ
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if not has_env:
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os.environ["OPENAI_API_KEY"] = "env_variable"
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llm_2 = ChatOpenAI(model="davinci", temperature=0.5) # type: ignore[call-arg]
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prompt_2 = ChatPromptTemplate.from_messages(
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[HumanMessagePromptTemplate.from_template("hello {name}!")]
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)
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chain_2 = LLMChain(llm=llm_2, prompt=prompt_2)
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assert dumps(chain_2, pretty=True) == dumps(chain, pretty=True)
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if not has_env:
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del os.environ["OPENAI_API_KEY"]
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@pytest.mark.requires("openai")
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def test_serialize_llmchain_with_non_serializable_arg(snapshot: Any) -> None:
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from langchain_community.llms.openai import OpenAI
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llm = OpenAI( # type: ignore[call-arg]
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model="davinci",
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temperature=0.5,
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openai_api_key="hello",
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client=NotSerializable,
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)
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prompt = PromptTemplate.from_template("hello {name}!")
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chain = LLMChain(llm=llm, prompt=prompt)
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assert dumps(chain, pretty=True) == snapshot
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def test_person_with_kwargs(snapshot: Any) -> None:
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person = Person(secret="hello")
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assert dumps(person, separators=(",", ":")) == snapshot
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def test_person_with_invalid_kwargs() -> None:
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person = Person(secret="hello")
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with pytest.raises(TypeError):
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dumps(person, invalid_kwarg="hello")
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class TestClass(Serializable):
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my_favorite_secret: str = Field(alias="my_favorite_secret_alias")
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my_other_secret: str = Field()
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class Config:
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"""Configuration for this pydantic object."""
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allow_population_by_field_name = True
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@root_validator(pre=True)
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def get_from_env(cls, values: Dict) -> Dict:
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"""Get the values from the environment."""
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if "my_favorite_secret" not in values:
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values["my_favorite_secret"] = os.getenv("MY_FAVORITE_SECRET")
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if "my_other_secret" not in values:
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values["my_other_secret"] = os.getenv("MY_OTHER_SECRET")
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return values
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@classmethod
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def is_lc_serializable(cls) -> bool:
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return True
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@classmethod
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def get_lc_namespace(cls) -> List[str]:
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return ["my", "special", "namespace"]
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@property
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def lc_secrets(self) -> Dict[str, str]:
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return {
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"my_favorite_secret": "MY_FAVORITE_SECRET",
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"my_other_secret": "MY_OTHER_SECRET",
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}
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def test_aliases_hidden() -> None:
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test_class = TestClass(my_favorite_secret="hello", my_other_secret="world") # type: ignore[call-arg]
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dumped = json.loads(dumps(test_class, pretty=True))
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expected_dump = {
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"lc": 1,
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"type": "constructor",
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"id": ["my", "special", "namespace", "TestClass"],
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"kwargs": {
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"my_favorite_secret": {
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"lc": 1,
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"type": "secret",
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"id": ["MY_FAVORITE_SECRET"],
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},
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"my_other_secret": {"lc": 1, "type": "secret", "id": ["MY_OTHER_SECRET"]},
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},
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}
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assert dumped == expected_dump
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# Check while patching the os environment
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with patch.dict(
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os.environ, {"MY_FAVORITE_SECRET": "hello", "MY_OTHER_SECRET": "world"}
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):
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test_class = TestClass() # type: ignore[call-arg]
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dumped = json.loads(dumps(test_class, pretty=True))
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# Check by alias
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test_class = TestClass(my_favorite_secret_alias="hello", my_other_secret="world") # type: ignore[call-arg]
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dumped = json.loads(dumps(test_class, pretty=True))
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expected_dump = {
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"lc": 1,
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"type": "constructor",
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"id": ["my", "special", "namespace", "TestClass"],
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"kwargs": {
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"my_favorite_secret": {
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"lc": 1,
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"type": "secret",
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"id": ["MY_FAVORITE_SECRET"],
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},
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"my_other_secret": {"lc": 1, "type": "secret", "id": ["MY_OTHER_SECRET"]},
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},
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}
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assert dumped == expected_dump
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