Python SDK - Upstash Documentation

upstash-blob is the Python SDK. It has a sync Bucket and an async AsyncBucket, and an upload handler for each that serves the browser client, so a React app can upload straight to storage through a Python backend. This section is the Python reference: names, types, and framework wiring. What each call does, its defaults and its limits are on the concept pages it links to.

Install

pip install upstash-blob

uv add upstash-blob

poetry add upstash-blob

It needs Python 3.10 or later, and its one dependency is httpx. FastAPI, Django, Flask, pydantic and boto3 are not pulled in; the modules that use them import them only when you do.

Modules

Import	Exports
`upstash_blob`	`Bucket`, `AsyncBucket`, `UploadHandler`, `AsyncUploadHandler`, `UploadRoute`, `BeforeUploadResult`, `unique_path`, `BlobError`, `format_bytes`, and the types
`upstash_blob.fastapi`	`upload_view`, for an `AsyncUploadHandler` on FastAPI or Starlette
`upstash_blob.django`	`upload_view`, for either handler
`upstash_blob.flask`	`upload_view`, for an `UploadHandler`

There is no Python browser client. The browser runs @upstash/blob/react or @upstash/blob/browser, which speak the same protocol to a Python handler as to a TypeScript one; see With a server in another language.

Bucket and AsyncBucket

from upstash_blob import Bucket

bucket = Bucket.from_env()  # reads UPSTASH_BLOB_TOKEN
blob = bucket.put("notes/1.md", "# Hello")

from upstash_blob import AsyncBucket

bucket = AsyncBucket.from_env()  # reads UPSTASH_BLOB_TOKEN
blob = await bucket.put("notes/1.md", "# Hello")

The two have the same methods, options and records. Every AsyncBucket method is awaited, including public_url() and s3(), except stream(), which is async with and yields an AsyncBlobStream. Its put also takes async iterables as a body. Use AsyncBucket under FastAPI, Starlette or any other asyncio code, and Bucket everywhere else. Each bucket holds an httpx client with its own connection pool. A bucket built once at import lives as long as the process and needs no closing. One you build for a single job closes with a context manager:

with Bucket.from_env() as bucket:
    bucket.put("exports/today.csv", rows)

async with AsyncBucket.from_env() as bucket:
    await bucket.put("exports/today.csv", rows)

close() and await aclose() do the same by hand.

The Bucket client

app/blob.py

import os

from upstash_blob import Bucket

bucket = Bucket(
    os.environ["UPSTASH_BLOB_TOKEN"],
    cache="immutable",
    enable_telemetry=False,
)

Bucket.from_env() is the same constructor with the token read from UPSTASH_BLOB_TOKEN. It takes the same keyword options, and a variable name when the token lives somewhere else:

Bucket.from_env(cache="immutable")
Bucket.from_env("REPORTS_BUCKET_TOKEN", cache="immutable")

An unset or empty variable raises a TypeError when the bucket is built, not on the first request.

Option	Type	Description
`token`	`str`	Required, and the only positional argument. See Connecting.
`cache`	`CacheOption`	The default `Cache-Control` for every object this client stores. A per-call `cache` overrides it. See Caching.
`enable_telemetry`	`bool`	`False` turns telemetry off for this client. See Telemetry.
`retry`	`RetryConfig \| Literal[False]`	`False`, or `{"retries": ..., "backoff": ...}`. See Retries.
`http_client`	`httpx.Client` / `httpx.AsyncClient`	Sends every request, for a proxy or custom timeouts. A client you pass is never closed by the bucket.

AsyncBucket takes an httpx.AsyncClient; Bucket takes an httpx.Client. There is no visibility option. Whether the bucket is public or private is a console setting; see Connecting.

Retries

Bucket(token, retry=False)  # every request once
Bucket(token, retry={"retries": 5, "backoff": lambda n: n * 500})

Field	Type	Description
`retries`	`int`	Retries after the first attempt, for every request this client makes.
`backoff`	`Callable[[int], float]`	Milliseconds before retry `n`, counted from 0. A `Retry-After` from the service wins over it.

RetryConfig is the TypedDict for this shape. An unknown key, a negative count or a backoff that is not callable raises a TypeError when the bucket is built. Which requests are retried, and the default budget and backoff, are on Retries.

Using an S3 client

import boto3

from app.blob import bucket

cfg = bucket.s3()
s3 = boto3.client("s3", **cfg.client_kwargs())

s3.get_object(Bucket=cfg.bucket, Key="reports/q3.pdf", Range="bytes=0-1023")

bucket.s3() returns an S3Config with the endpoint, region, bucket name and a short-lived credential. client_kwargs() is what boto3.client("s3", ...) takes. On AsyncBucket, s3() is awaited. Unlike the TypeScript config, the credential is a fixed value, not a provider: boto3 cannot refresh it. It stops working at cfg.expires_at, so build a new client from a fresh bucket.s3() before then. What an S3 client is for, and why it must not presign, is on Using an S3 client.

Option types

Type	Python	Grammar
`Size`	`int \| str`	Size
`Duration`	`int \| float \| str \| timedelta`	Duration. A `timedelta` counts as its total seconds.
`CacheOption`	`Duration \| Literal["immutable", "revalidate", "no-store"]`	CacheOption. A raw header is a `str`.
`MultipartOption`	`bool \| Size`	Changing the threshold

All four are exported from upstash_blob.

from datetime import timedelta

bucket.signed_read_url("reports/q3.pdf", expires_in=timedelta(minutes=2))
bucket.put("avatars/7.png", data, cache=timedelta(days=7))  # public, max-age=604800
bucket.put("export.csv", chunks, max_size="10MiB")

A value of the wrong type, such as a bool size, raises a TypeError. A string that does not parse, such as "5mbit", raises a ValueError naming the option. Both are raised by the call that takes the option, except a cache on the client, which is checked on each call that stores an object. See Bad options. Every size the SDK returns is an int of bytes. format_bytes(2_400_000) is '2.4 MB', the same text the browser client shows.

Next steps

Bucket API

Every Bucket method, its options and the records it returns.

Upload handler

UploadHandler options, callbacks, and mounting it in FastAPI, Django and Flask.

Errors

BlobError, the fields it carries, and what raises something else.

FastAPI + React

A Python backend serving useUpload, end to end.

​Install

​Modules

​Bucket and AsyncBucket

​The Bucket client

​Retries

​Using an S3 client

​Option types

​Next steps