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add option to put docstrings on model attributes (#1190)
Adds a `docstrings_on_attributes` option that causes property descriptions to appear in docstrings on the attributes, instead of in the class docstring. This is a desirable behavior when using documentation generators like Sphinx. This is a non-breaking change; if the option is not set, code generation is exactly the same as before (evidence: the existing golden-record directories have no changes). ## Clarification about how docstrings on attributes work Python does not treat all docstrings the same, in terms of availability at runtime. A docstring on a class or method is available as a `__doc__` attribute— but a docstring on an attribute is not; such a string is just thrown away by the interpreter. If class `A` has attribute `b`, then `A.b.__doc__` will never be a thing— you would have to define `b` as a property getter method instead. However, docstrings on attributes are still valid as per [PEP 257](https://peps.python.org/pep-0257/) as a thing that can be surfaced by other tools. Sphinx _will_ use them when generating documentation, and VS Code _will_ show them as a description in the popup if you hover over an attribute.
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.changeset/config-in-templates.md

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---
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default: minor
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---
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# Make `config` available in custom templates
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The configuration options object is now exposed as a variable called `config` in Jinja2 templates.
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---
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default: minor
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---
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# Add `docstrings_on_attributes` config setting
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Setting this option to `true` changes the docstring behavior in model classes: for any attribute that have a non-empty `description`, instead of describing the attribute as part of the class's docstring, the description will appear in an individual docstring for that attribute.

README.md

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The easiest way to find what needs to be overridden is probably to generate your client and go look at everything in the `models` folder.
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### docstrings_on_attributes
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By default, when `openapi-python-client` generates a model class, it includes a list of attributes and their
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descriptions in the docstring for the class. If you set this option to `true`, then the attribute descriptions
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will be put in docstrings for the attributes themselves, and will not be in the class docstring.
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```yaml
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docstrings_on_attributes: true
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```
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### literal_enums
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By default, `openapi-python-client` generates classes inheriting for `Enum` for enums. It can instead use `Literal`
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__pycache__/
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build/
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dist/
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*.egg-info/
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.pytest_cache/
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# pyenv
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.python-version
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# Environments
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.env
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.venv
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# mypy
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.mypy_cache/
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.dmypy.json
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dmypy.json
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# JetBrains
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.idea/
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/coverage.xml
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/.coverage
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# my-test-api-client
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A client library for accessing My Test API
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## Usage
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First, create a client:
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```python
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from my_test_api_client import Client
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client = Client(base_url="https://api.example.com")
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```
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If the endpoints you're going to hit require authentication, use `AuthenticatedClient` instead:
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```python
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from my_test_api_client import AuthenticatedClient
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client = AuthenticatedClient(base_url="https://api.example.com", token="SuperSecretToken")
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```
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Now call your endpoint and use your models:
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```python
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from my_test_api_client.models import MyDataModel
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from my_test_api_client.api.my_tag import get_my_data_model
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from my_test_api_client.types import Response
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with client as client:
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my_data: MyDataModel = get_my_data_model.sync(client=client)
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# or if you need more info (e.g. status_code)
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response: Response[MyDataModel] = get_my_data_model.sync_detailed(client=client)
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```
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Or do the same thing with an async version:
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```python
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from my_test_api_client.models import MyDataModel
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from my_test_api_client.api.my_tag import get_my_data_model
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from my_test_api_client.types import Response
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async with client as client:
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my_data: MyDataModel = await get_my_data_model.asyncio(client=client)
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response: Response[MyDataModel] = await get_my_data_model.asyncio_detailed(client=client)
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```
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By default, when you're calling an HTTPS API it will attempt to verify that SSL is working correctly. Using certificate verification is highly recommended most of the time, but sometimes you may need to authenticate to a server (especially an internal server) using a custom certificate bundle.
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```python
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client = AuthenticatedClient(
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base_url="https://internal_api.example.com",
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token="SuperSecretToken",
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verify_ssl="/path/to/certificate_bundle.pem",
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)
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```
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You can also disable certificate validation altogether, but beware that **this is a security risk**.
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```python
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client = AuthenticatedClient(
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base_url="https://internal_api.example.com",
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token="SuperSecretToken",
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verify_ssl=False
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)
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```
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Things to know:
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1. Every path/method combo becomes a Python module with four functions:
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1. `sync`: Blocking request that returns parsed data (if successful) or `None`
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1. `sync_detailed`: Blocking request that always returns a `Request`, optionally with `parsed` set if the request was successful.
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1. `asyncio`: Like `sync` but async instead of blocking
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1. `asyncio_detailed`: Like `sync_detailed` but async instead of blocking
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1. All path/query params, and bodies become method arguments.
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1. If your endpoint had any tags on it, the first tag will be used as a module name for the function (my_tag above)
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1. Any endpoint which did not have a tag will be in `my_test_api_client.api.default`
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## Advanced customizations
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There are more settings on the generated `Client` class which let you control more runtime behavior, check out the docstring on that class for more info. You can also customize the underlying `httpx.Client` or `httpx.AsyncClient` (depending on your use-case):
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```python
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from my_test_api_client import Client
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def log_request(request):
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print(f"Request event hook: {request.method} {request.url} - Waiting for response")
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def log_response(response):
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request = response.request
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print(f"Response event hook: {request.method} {request.url} - Status {response.status_code}")
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client = Client(
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base_url="https://api.example.com",
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httpx_args={"event_hooks": {"request": [log_request], "response": [log_response]}},
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)
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# Or get the underlying httpx client to modify directly with client.get_httpx_client() or client.get_async_httpx_client()
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```
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You can even set the httpx client directly, but beware that this will override any existing settings (e.g., base_url):
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```python
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import httpx
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from my_test_api_client import Client
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client = Client(
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base_url="https://api.example.com",
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)
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# Note that base_url needs to be re-set, as would any shared cookies, headers, etc.
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client.set_httpx_client(httpx.Client(base_url="https://api.example.com", proxies="http://localhost:8030"))
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```
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## Building / publishing this package
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This project uses [Poetry](https://python-poetry.org/) to manage dependencies and packaging. Here are the basics:
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1. Update the metadata in pyproject.toml (e.g. authors, version)
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1. If you're using a private repository, configure it with Poetry
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1. `poetry config repositories.<your-repository-name> <url-to-your-repository>`
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1. `poetry config http-basic.<your-repository-name> <username> <password>`
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1. Publish the client with `poetry publish --build -r <your-repository-name>` or, if for public PyPI, just `poetry publish --build`
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If you want to install this client into another project without publishing it (e.g. for development) then:
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1. If that project **is using Poetry**, you can simply do `poetry add <path-to-this-client>` from that project
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1. If that project is not using Poetry:
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1. Build a wheel with `poetry build -f wheel`
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1. Install that wheel from the other project `pip install <path-to-wheel>`
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"""A client library for accessing My Test API"""
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from .client import AuthenticatedClient, Client
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__all__ = (
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"AuthenticatedClient",
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"Client",
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)
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"""Contains methods for accessing the API"""

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