JSON Hyper Schema client
Project description
A JSON Hyper Schema client that allows hypermedia navigation and resource validation.
Basic Usage
import pluct
# Load a resource
item = pluct.resource('http://myapi.com/api/item', timeout=2) # Works with connect timeout
# Verifying if the resource is valid for the current schema
item.is_valid()
# Use the resource as a dictionary
first_title = item['subitems'][0]['title']
# Accessing the item schema
item.schema['properties']['title']
# Loading a related resource
category = item.rel('category')
# With additional parameters
category = item.rel('category', timeout=(1, 2)) # You can choose from request parameters: http://docs.python-requests.org/en/latest/api/#requests.Session.request
Authentication / Custom HTTP Client
Pluct uses the Session object from the requests package as a HTTP client.
Any other client with the same interface can be used.
Here is an example using alf, an OAuth 2 client:
from pluct import Pluct
from alf.client import Client
alf = Client(
token_endpoint='http://myapi.com/token',
client_id='client-id',
client_secret='secret')
# Create a pluct session using the client
pluct = Pluct(client=alf)
item = pluct.resource('http://myapi.com/api/item')
All subsequent requests for schemas or resources in this session will use the same client.
Parameters and URI expansion
URI Templates are supported when following resource links.
The context for URL expansion will be a merge of the resource data attribute and the params parameter passed to the resource’s rel method.
Any variable not consumed by the URL Template will be used on the query string for the request.
Better explained in an example. Consider the following resource and schema snippets:
{
"type": "article"
}
{
"...": "...",
"links": [
{
"rel": "search",
"href": "/api/search/{type}"
}
]
}
The next example will resolve the href from the search link to /api/search/article?q=foo and will load articles containing the text “foo”:
import pluct
# Load a resource
item = pluct.resource('http://myapi.com/api/item')
articles = item.rel('search', params={'q': 'foo'})
To search for galleries is just a matter of passing a different type in the params argument, as follows:
galleries = item.rel('search', params={'type': 'gallery', 'q': 'foo'})
To send your own body data you can send the object as data. This will follow your method (PUT, POST, GET or DELETE) with all data from object:
galleries = item.rel('create', data=item)
Schema loading
When a resource is loaded, a lazy-schema schema will be created and its data will only be loaded when accessed.
Pluct looks for a schema URL on the profile parameter of the Content-type header:
Content-Type: application/json; profile="http://myapi.com/api/schema"
References ($ref)
JSON Pointers on schemas are also supported.
Pointers are identified by a dictionary with a $ref key pointing to an external URL or a local pointer.
Considering the following definitions on the /api/definitions url:
{
"address": {
"type": "object",
"properties": {
"line1": {"type": "string"},
"line2": {"type": "string"},
"zipcode": {"type": "integer"},
}
}
}
And this schema on /api/schema that uses the above definitions:
{
"properties": {
"shippingAddress": {"$ref": "http://myapi.com/api/definitions#/address"},
"billingAddress": {"$ref": "http://myapi.com/api/definitions#/address"},
}
}
The billingAddress can be accessed as follows:
import pluct
schema = pluct.schema('http://myapi.com/api/schema')
schema['properties']['billingAddress']['zipcode'] == {"type": "integer"}
Contributing
Fork the repository on Github: https://github.com/globocom/pluct
Create a virtualenv and install the dependencies:
make setup
Tests are on the pluct/tests directory, run the test suite with:
make test
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