apifetch (Python)
apifetch is a small, dependency-light toolkit for talking to
token-authenticated REST APIs. It handles three recurring chores:
- Token management — store/get/remove/list tokens in process environment variables (never written to disk), namespaced per service.
- Request building — pluggable authentication and pagination
strategies, bundled into a reusable
Apiprofile. - Data retrieval — fetch one page, or fetch everything in chunks.
This is the Python sibling of the R package
apifetch. Both were extracted
from the BigDataPE package,
which is now one use case (see examples/bigdatape.py).
Installation
pip install apifetch
Usage
import apifetch as af
# 1. Describe the API once: where, how to authenticate, how to paginate.
api = af.Api(
endpoint="https://api.example.com/v1/search",
service="Example",
auth=af.AuthBearer(), # "Authorization: Bearer <token>"
pagination=af.PaginateOffset(where="query"),
)
# 2. Store a token (kept only in this process's environment).
af.store_token("reports", "my-secret-token", service="Example")
# 3. Fetch.
one_page = af.fetch(api, "reports", limit=50)
everything = af.fetch_all(api, "reports", chunk_size=1000)
# Optional: turn it into a DataFrame.
# import pandas as pd; df = pd.DataFrame(everything)
Strategies
Authentication: AuthBearer, AuthRaw, AuthHeader, AuthQuery.
Pagination: PaginateOffset(where="header" | "query"), PaginateNone.
License
MIT © André Leite
1 maintainer
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