# jellyfin-api-client
A client library for accessing Jellyfin API
Generated API bindings for python from the Jellyfin OpenAPI specification with the help of [openapi-python-client](https://github.com/openapi-generators/openapi-python-client).
## Installation
`pip install jellyfin-api-client`
## Usage
First, create a client:
```python
from jellyfin_api_client import Client
client = Client(base_url="https://api.example.com")
```
If the endpoints you're going to hit require authentication, use `AuthenticatedClient` instead:
```python
from jellyfin_api_client import AuthenticatedClient
client = AuthenticatedClient(base_url="https://api.example.com", token="SuperSecretToken")
```
Now call your endpoint and use your models:
```python
from jellyfin_api_client.models import MyDataModel
from jellyfin_api_client.api.my_tag import get_my_data_model
from jellyfin_api_client.types import Response
with client as client:
my_data: MyDataModel = get_my_data_model.sync(client=client)
# or if you need more info (e.g. status_code)
response: Response[MyDataModel] = get_my_data_model.sync_detailed(client=client)
```
Or do the same thing with an async version:
```python
from jellyfin_api_client.models import MyDataModel
from jellyfin_api_client.api.my_tag import get_my_data_model
from jellyfin_api_client.types import Response
async with client as client:
my_data: MyDataModel = await get_my_data_model.asyncio(client=client)
response: Response[MyDataModel] = await get_my_data_model.asyncio_detailed(client=client)
```
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.
```python
client = AuthenticatedClient(
base_url="https://internal_api.example.com",
token="SuperSecretToken",
verify_ssl="/path/to/certificate_bundle.pem",
)
```
You can also disable certificate validation altogether, but beware that **this is a security risk**.
```python
client = AuthenticatedClient(
base_url="https://internal_api.example.com",
token="SuperSecretToken",
verify_ssl=False
)
```
Things to know:
1. Every path/method combo becomes a Python module with four functions:
1. `sync`: Blocking request that returns parsed data (if successful) or `None`
1. `sync_detailed`: Blocking request that always returns a `Request`, optionally with `parsed` set if the request was successful.
1. `asyncio`: Like `sync` but async instead of blocking
1. `asyncio_detailed`: Like `sync_detailed` but async instead of blocking
1. All path/query params, and bodies become method arguments.
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)
1. Any endpoint which did not have a tag will be in `jellyfin_api_client.api.default`
## Advanced customizations
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):
```python
from jellyfin_api_client import Client
def log_request(request):
print(f"Request event hook: {request.method} {request.url} - Waiting for response")
def log_response(response):
request = response.request
print(f"Response event hook: {request.method} {request.url} - Status {response.status_code}")
client = Client(
base_url="https://api.example.com",
httpx_args={"event_hooks": {"request": [log_request], "response": [log_response]}},
)
# Or get the underlying httpx client to modify directly with client.get_httpx_client() or client.get_async_httpx_client()
```
You can even set the httpx client directly, but beware that this will override any existing settings (e.g., base_url):
```python
import httpx
from jellyfin_api_client import Client
client = Client(
base_url="https://api.example.com",
)
# Note that base_url needs to be re-set, as would any shared cookies, headers, etc.
client.set_httpx_client(httpx.Client(base_url="https://api.example.com", proxies="http://localhost:8030"))
```
## Building / publishing this package
This project uses [Poetry](https://python-poetry.org/) to manage dependencies and packaging. Here are the basics:
1. Update the metadata in pyproject.toml (e.g. authors, version)
1. If you're using a private repository, configure it with Poetry
1. `poetry config repositories.<your-repository-name> <url-to-your-repository>`
1. `poetry config http-basic.<your-repository-name> <username> <password>`
1. Publish the client with `poetry publish --build -r <your-repository-name>` or, if for public PyPI, just `poetry publish --build`
If you want to install this client into another project without publishing it (e.g. for development) then:
1. If that project **is using Poetry**, you can simply do `poetry add <path-to-this-client>` from that project
1. If that project is not using Poetry:
1. Build a wheel with `poetry build -f wheel`
1. Install that wheel from the other project `pip install <path-to-wheel>`
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"description": "# jellyfin-api-client\nA client library for accessing Jellyfin API\n\nGenerated API bindings for python from the Jellyfin OpenAPI specification with the help of [openapi-python-client](https://github.com/openapi-generators/openapi-python-client).\n\n## Installation\n\n`pip install jellyfin-api-client`\n\n## Usage\nFirst, create a client:\n\n```python\nfrom jellyfin_api_client import Client\n\nclient = Client(base_url=\"https://api.example.com\")\n```\n\nIf the endpoints you're going to hit require authentication, use `AuthenticatedClient` instead:\n\n```python\nfrom jellyfin_api_client import AuthenticatedClient\n\nclient = AuthenticatedClient(base_url=\"https://api.example.com\", token=\"SuperSecretToken\")\n```\n\nNow call your endpoint and use your models:\n\n```python\nfrom jellyfin_api_client.models import MyDataModel\nfrom jellyfin_api_client.api.my_tag import get_my_data_model\nfrom jellyfin_api_client.types import Response\n\nwith client as client:\n my_data: MyDataModel = get_my_data_model.sync(client=client)\n # or if you need more info (e.g. status_code)\n response: Response[MyDataModel] = get_my_data_model.sync_detailed(client=client)\n```\n\nOr do the same thing with an async version:\n\n```python\nfrom jellyfin_api_client.models import MyDataModel\nfrom jellyfin_api_client.api.my_tag import get_my_data_model\nfrom jellyfin_api_client.types import Response\n\nasync with client as client:\n my_data: MyDataModel = await get_my_data_model.asyncio(client=client)\n response: Response[MyDataModel] = await get_my_data_model.asyncio_detailed(client=client)\n```\n\nBy 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.\n\n```python\nclient = AuthenticatedClient(\n base_url=\"https://internal_api.example.com\", \n token=\"SuperSecretToken\",\n verify_ssl=\"/path/to/certificate_bundle.pem\",\n)\n```\n\nYou can also disable certificate validation altogether, but beware that **this is a security risk**.\n\n```python\nclient = AuthenticatedClient(\n base_url=\"https://internal_api.example.com\", \n token=\"SuperSecretToken\", \n verify_ssl=False\n)\n```\n\nThings to know:\n1. Every path/method combo becomes a Python module with four functions:\n 1. `sync`: Blocking request that returns parsed data (if successful) or `None`\n 1. `sync_detailed`: Blocking request that always returns a `Request`, optionally with `parsed` set if the request was successful.\n 1. `asyncio`: Like `sync` but async instead of blocking\n 1. `asyncio_detailed`: Like `sync_detailed` but async instead of blocking\n\n1. All path/query params, and bodies become method arguments.\n1. If your endpoint had any tags on it, the first tag will be used as a module name for the function (my_tag above)\n1. Any endpoint which did not have a tag will be in `jellyfin_api_client.api.default`\n\n## Advanced customizations\n\nThere 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):\n\n```python\nfrom jellyfin_api_client import Client\n\ndef log_request(request):\n print(f\"Request event hook: {request.method} {request.url} - Waiting for response\")\n\ndef log_response(response):\n request = response.request\n print(f\"Response event hook: {request.method} {request.url} - Status {response.status_code}\")\n\nclient = Client(\n base_url=\"https://api.example.com\",\n httpx_args={\"event_hooks\": {\"request\": [log_request], \"response\": [log_response]}},\n)\n\n# Or get the underlying httpx client to modify directly with client.get_httpx_client() or client.get_async_httpx_client()\n```\n\nYou can even set the httpx client directly, but beware that this will override any existing settings (e.g., base_url):\n\n```python\nimport httpx\nfrom jellyfin_api_client import Client\n\nclient = Client(\n base_url=\"https://api.example.com\",\n)\n# Note that base_url needs to be re-set, as would any shared cookies, headers, etc.\nclient.set_httpx_client(httpx.Client(base_url=\"https://api.example.com\", proxies=\"http://localhost:8030\"))\n```\n\n## Building / publishing this package\nThis project uses [Poetry](https://python-poetry.org/) to manage dependencies and packaging. Here are the basics:\n1. Update the metadata in pyproject.toml (e.g. authors, version)\n1. If you're using a private repository, configure it with Poetry\n 1. `poetry config repositories.<your-repository-name> <url-to-your-repository>`\n 1. `poetry config http-basic.<your-repository-name> <username> <password>`\n1. Publish the client with `poetry publish --build -r <your-repository-name>` or, if for public PyPI, just `poetry publish --build`\n\nIf you want to install this client into another project without publishing it (e.g. for development) then:\n1. If that project **is using Poetry**, you can simply do `poetry add <path-to-this-client>` from that project\n1. If that project is not using Poetry:\n 1. Build a wheel with `poetry build -f wheel`\n 1. Install that wheel from the other project `pip install <path-to-wheel>`\n\n",
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