Convex
The official Python client for Convex.
Write and read data from a Convex backend with queries, mutations, and actions.
Get up and running at docs.convex.dev.
Installation:
pip install convex
Basic usage:
>>> from convex import ConvexClient
>>> client = ConvexClient('https://example-lion-123.convex.cloud')
>>> messages = client.query("messages:list")
>>> from pprint import pprint
>>> pprint(messages)
[{'_creationTime': 1668107495676.2854,
'_id': '2sh2c7pn6nyvkexbdsfj66vd9h5q3hg',
'author': 'Tom',
'body': 'Have you tried Convex?'},
{'_creationTime': 1668107497732.2295,
'_id': '1f053fgh2tt2fc93mw3sn2x09h5bj08',
'author': 'Sarah',
'body': "Yeah, it's working pretty well for me."}]
>>> client.mutation("sendMessage", dict(author="Me", body="Hello!"))
To find the url of your convex backend, open the deployment you want to work
with in the appropriate project in the
Convex dashboard and click "Settings" where the
Deployment URL should be visible. To find out which queries, mutations, and
actions are available check the Functions pane in the dashboard.
To see logs emitted from Convex functions, set the debug mode to True.
>>> client.set_debug(True)
To provide authentication for function execution, call set_auth()
.
>>> client.set_auth("token-from-authetication-flow")
Join us on Discord to get your questions
answered or share what you're doing with Convex. If you're just getting started,
see https://docs.convex.dev to see how to quickly spin up a backend that does
everything you need in the Convex cloud.
Convex types
Convex backend functions are written in JavaScript, so arguments passed to
Convex RPC functions in Python are serialized, sent over the network, and
deserialized into JavaScript objects. To learn about Convex's supported types
see https://docs.convex.dev/using/types.
In order to call a function that expects a JavaScript type, use the
corresponding Python type or any other type that coerces to it. Values returned
from Convex will be of the corresponding Python type.
Ints and Floats
While
Convex supports storing Int64s and Float64s,
idiomatic JavaScript pervasively uses the (floating point) Number
type. In
Python float
s are often understood to contain the int
s: the float
type
annotation is
generally understood as Union[int, float]
.
Therefore, the Python Convex client converts Python's float
s and int
s to a
Float64
in Convex.
To specify a JavaScript BigInt, use the ConvexInt64 class. Functions which
return JavaScript BigInts will return ConvexInt64 instances.
Convex Errors
The Python client supports the ConvexError
type to hold application errors
that are propagated from your Convex functions. To learn about how to throw
ConvexError
s see
https://docs.convex.dev/functions/error-handling/application-errors.
On the Python client, ConvexError
s are Exceptions with a data
field that
contains some ConvexValue
. Handling application errors from the Python client
might look something like this:
import convex
client = convex.ConvexClient('https://happy-animal-123.convex.cloud')
try:
client.mutation("messages:sendMessage", {body: "hi", author: "anjan"})
except convex.ConvexError as err:
if isinstance(err.data, dict):
if "code" in err.data and err.data["code"] == 1:
else:
elif isinstance(err.data, str):
print(err.data)
except Exception as err:
Paginated queries are queries
that accept pagination options as an argument and can be called repeatedly to
produce additional "pages" of results.
For a paginated query like this:
import { query } from "./_generated/server";
export default query(async ({ db }, { paginationOpts }) => {
return await db.query("messages").order("desc").paginate(paginationOpts);
});
and returning all results 5 at a time in Python looks like this:
import convex
client = convex.ConvexClient('https://happy-animal-123.convex.cloud')
done = False
cursor = None
data = []
while not done:
result = client.query('listMessages', {"paginationOpts": {"numItems": 5, "cursor": cursor}})
cursor = result['continueCursor']
done = result["isDone"]
data.extend(result['page'])
print('got', len(result['page']), 'results')
print('collected', len(data), 'results')
Versioning
While we are pre-1.0.0, we'll update the minor version for large changes, and
the patch version for small bugfixes. We may make backwards incompatible changes
to the python client's API, but we will limit those to minor version bumps.