Argonne National Laboratory
government · United StatesScores
1 product on the map — 1 open.
Openness
5 high confidence- license
- MIT(OSI
- source
- public(the whole framework)
- core features withheld
- no — a DOE-funded national-laboratory project with no paid edition
APPFL is MIT-licensed and developed at Argonne with Department of Energy funding. There is no commercial party positioned to hold features back, and no paid edition is named.
- https://raw.githubusercontent.com/APPFL/APPFL/HEAD/LICENSE recorded 2026-09-27
The LICENSE body: verbatim MIT text, "Copyright (c) 2023 Argonne National Laboratory".
- https://raw.githubusercontent.com/APPFL/APPFL/HEAD/README.md recorded 2026-09-27
README: "This material is based upon work supported by the U.S. Department of Energy, Office of Science, under contract number DE-AC02-06CH11357." No paid tier is named.
- https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/APPFL%2FAPPFL recorded 2026-09-27
Repository record for APPFL/APPFL: license mit, not archived, not a fork, pushed 2026-09-21, 184 stars.
- https://ungh.cc/repos/APPFL/APPFL/files/main recorded 2026-09-27
The 900-file tree of APPFL/APPFL at `main`: one root LICENSE, and no ee/, enterprise/, commercial/, proprietary/ or premium/ path anywhere in it. Path absence only, paired with the statement cited beside it.
Adoption
1 medium confidencePyPI downloads of `appfl`, which carries both the server and the client.
- https://pypistats.org/api/packages/appfl/recent recorded 2026-09-27
last_month = 438 downloads for the package `appfl`.
Capability
4 medium confidenceClients authenticate over gRPC or through Globus, and training can apply differential privacy, so APPFL runs real cross-institution federations as Flower does. Its HPC support is MPI simulation rather than a launcher for production sites, which keeps it below NVIDIA FLARE.
- https://raw.githubusercontent.com/APPFL/APPFL/HEAD/README.md recorded 2026-09-27
README: "APPFL supports MPI for single-machine/cluster simulation, and gRPC and Globus Compute with authenticator for secure distributed training"; "APPFL supports several global/local differential privacy schemes".
- https://ungh.cc/repos/APPFL/APPFL/files/main recorded 2026-09-27
The tree ships launch_server_auth and launch_client_auth notebooks, a gRPC authentication guide and an SSL example.