Hacktoberfest 2026: die Issues, die Maintainer für den Oktober markiert haben – offen und einsteigerfreundlich. Hacktoberfest-Issues durchsuchen

DAPR_* environment variables are snapshotted at import time, so loading config after import silently dials localhost

Offen
#1,259 0 Kommentare 0 Reaktionen 1 zugewiesene Person Auf GitHub ansehen

Maintainer antworten meist innerhalb von 4 Tagen

@CasperGN arbeitet bereits daran.

Seit 09.10.2026.

  • #1262 von @CasperGN — offen

Bewertung

Schwierigkeit
3/5
Geschätzter Aufwand
1-2 Tage
Anfängerfreundlichkeit
45/100
Issue-Typ
Bug
Klarheit
Größtenteils klar
Aktivitätsstatus
Aktiv
Tech-Stack
python
Bereich
backend

Rechercherichtung

Start with the dapr.conf settings module, which reads the DAPR_* variables at import, and with dapr.conf.helpers.GrpcEndpoint, which builds the endpoint from them. Run the reproduction in the issue to confirm the value stays None after os.environ changes. Done means either the settings are read when a client is constructed, or a clear error or warning is raised when os.environ and the snapshot disagree. The issue leaves the choice between these options to the maintainers, so confirm the approach before writing code.

Vom Indexierungsmodell aus dem Issue-Text verfasst.

Beschreibung

What happens

dapr.conf.settings reads the DAPR_* environment variables when the module is
first imported. Setting them afterwards has no effect, and the SDK silently
falls back to dns:localhost:50001 instead of the configured endpoint. There is
no warning and no error — the first symptom is a connection failure that looks
like a network or platform problem.

This is easy to hit with any of the common config patterns: python-dotenv in a
config.py, a settings module, a CLI that parses args before wiring the client,
or a framework that imports your package before your .env loader runs.

Reproduction

import os
assert "DAPR_GRPC_ENDPOINT" not in os.environ

import dapr.conf as conf
print(conf.settings.DAPR_GRPC_ENDPOINT)    # None

os.environ["DAPR_GRPC_ENDPOINT"] = "https://grpc-example.example.com:443"
print(os.environ["DAPR_GRPC_ENDPOINT"])    # the value we just set
print(conf.settings.DAPR_GRPC_ENDPOINT)    # None  <-- still

from dapr.conf.helpers import GrpcEndpoint
ep = GrpcEndpoint(conf.settings.DAPR_GRPC_ENDPOINT
                  or f"localhost:{conf.settings.DAPR_GRPC_PORT}")
print(ep.endpoint)                         # dns:localhost:50001

Observed output:

1. imported dapr.conf with no DAPR_GRPC_ENDPOINT set
   settings.DAPR_GRPC_ENDPOINT = None
   settings.DAPR_GRPC_PORT     = 50001

2. set DAPR_GRPC_ENDPOINT AFTER import
   os.environ value            = https://grpc-example.example.com:443
   settings.DAPR_GRPC_ENDPOINT = None

3. endpoint the SDK would dial: dns:localhost:50001

Expected

Any of the following would have saved the debugging time:

  1. Read the setting lazily, at client construction, rather than at import.
  2. Keep the import-time read, but re-check os.environ when a client is built
    and raise or warn on a mismatch between os.environ["DAPR_GRPC_ENDPOINT"]
    and settings.DAPR_GRPC_ENDPOINT.
  3. Document it prominently in the client docs — "set DAPR_* before importing
    dapr" — since the current failure mode is silent.

(1) seems best; (2) is the cheapest thing that makes the failure loud.

Environment

  • dapr 1.18.3, dapr-ext-workflow 1.18.3
  • Python 3.12.12, macOS 15 (darwin 24.3.0)
  • Talking to a managed Dapr control plane over a remote gRPC endpoint, so the
    localhost fallback can never succeed

Why it matters

Against a local sidecar the fallback is often correct, which is why this is
rarely noticed. Against any remote or managed endpoint it is always wrong, and
the error surfaces far from its cause — the one I chased presented as "every
connection fails", with correct-looking values in .env and in os.environ.

Vorherrschende Sprache
Python
Sterne
273
Forks
156
Ø Merge
6 T. 6 Std.
Gemergte PRs (30 T.)
16

Entwicklungsumgebung

In Codespaces öffnen

Startet den Dev-Container des Projekts im Browser, mit Ihrem eigenen GitHub-Konto.

Erste Schritte

  1. Lesen Sie das ganze Issue und danach den Beitragsleitfaden des Projekts.
  2. Schreiben Sie ins Issue, dass Sie es übernehmen — das erspart doppelte Arbeit.
  3. Forken Sie das Repository und arbeiten Sie in einem Branch.
  4. Öffnen Sie einen Pull Request, der die Issue-Nummer nennt.

Mehr aus dapr/python-sdk

Alle Issues in dapr/python-sdk

Ähnliche Issues

Weitere Issues zu Python

Neue Issues direkt in Ihr Postfach

Eine kurze Übersicht über anfängerfreundliche GitHub-Issues.