pymaskinporten
This is a python package to request a token from Maskinporten - the Norwegian national access control solution for businesses that exchange data.
graph LR
Consumer["Application"] -- request token ---> Maskinporten
Maskinporten -- issue new token ---> Consumer
Consumer -- use token ---> Service["External Service"]
Installation
pip install pymaskinporten
Optional extras add the secret-store SDKs and the demo app:
| Extra | Adds |
|---|---|
azure |
Azure Key Vault loader |
databricks |
Databricks secrets loader |
aws |
AWS Secrets Manager loader |
gcp |
Google Secret Manager loader |
web |
The pymaskinporten-web demo app |
For example: pip install "pymaskinporten[azure,web]".
Example usage
This assumes you have created the integration at Digdir and have its private key (PEM), key ID, client ID and scope.
By default the credentials are read from the environment variables PRIVATE_KEY,
MASKINPORTEN_CLIENT_ID, KID and SCOPE:
from pymaskinporten import request_maskinporten_token
access_token, expires_in = request_maskinporten_token("test") # or "prod"
api_env must be "test" or "prod"; anything else raises ValueError. A failed token request
raises MaskinportenTokenError.
Secret stores
load_config() can also read the credentials from a secret store. Pass the result with config=:
from pymaskinporten import load_config, request_maskinporten_token
config = load_config("azure", key_vault_uri="https://my-vault.vault.azure.net/")
access_token, expires_in = request_maskinporten_token("prod", config=config)
| Store | Call | Install |
|---|---|---|
| Azure Key Vault | load_config("azure", key_vault_uri="https://...") |
pip install "pymaskinporten[azure]" |
| Databricks secrets | load_config("databricks", secret_scope="maskinporten") |
pip install "pymaskinporten[databricks]" |
| AWS Secrets Manager | load_config("aws", region="eu-north-1") |
pip install "pymaskinporten[aws]" |
| Google Secret Manager | load_config("gcp", project_id="my-project") |
pip install "pymaskinporten[gcp]" |
Each store signs in with its SDK's default credentials: DefaultAzureCredential for Azure,
the Databricks runtime for Databricks, boto3's credential chain for AWS (region falls back to
boto3's configured region), and Application Default Credentials for Google (the latest secret
version is read).
Secret stores use dashes in the names, because Key Vault doesn't allow underscores:
| Credential | Environment variable | Secret name |
|---|---|---|
| Private key (PEM) | PRIVATE_KEY |
PRIVATE-KEY |
| Client ID | MASKINPORTEN_CLIENT_ID |
MASKINPORTEN-CLIENT-ID |
| Key ID | KID |
KID |
| Scope | SCOPE |
SCOPE |
Name prefixes
prefix is put in front of every environment variable or secret name, so test and prod
credentials can live side by side:
# Reads PROD_PRIVATE_KEY, PROD_KID, ...
load_config(prefix="PROD_")
# Reads maskinporten/prod/PRIVATE-KEY, ...
load_config("aws", prefix="maskinporten/prod/")
The prefix is used as-is, so use only characters the source allows (besides letters and digits):
- Environment variables:
_ - Azure Key Vault:
- - Google Secret Manager:
-_ - Databricks:
-_. - AWS Secrets Manager:
-_/+=.@
Passing credentials directly
To use credentials from anywhere else, build them yourself and pass them with config=:
from pymaskinporten import MaskinportenSecrets, request_maskinporten_token
secrets = MaskinportenSecrets(
PRIVATE_KEY=open("private_key.pem").read(),
MASKINPORTEN_CLIENT_ID="your-client-id",
KID="your-kid",
SCOPE="your-scope",
)
access_token, expires_in = request_maskinporten_token("prod", config=secrets)
Using a .env file
By default, load_config() reads environment variables only. To keep the credentials in a .env
file, install python-dotenv (pip install python-dotenv) and load it before requesting a
token:
from dotenv import load_dotenv
load_dotenv()
The demo app below does this for you.
Testing against Maskinporten
To check a change against the real test environment, create a Maskinporten integration for a synthetic organisation (syntetisk organisasjon) in Digdir's test self-service, then from the repo root:
uv run --extra web python scripts/make_test_key.py # writes a new .env with a key pair
# paste PUBLIC_KEY from .env into the integration, fill in KID, MASKINPORTEN_CLIENT_ID, SCOPE
uv run --extra web python scripts/real_token_test.py
Docker container
To test the library in a web browser, use the pymaskinporten-web demo app (a flask app).
Run it locally with pip install "pymaskinporten[web]" and pymaskinporten-web, or use the
Docker image:
cat > .env <<EOF
MASKINPORTEN_CLIENT_ID=your-client-id
KID=your-kid
SCOPE=your-scope
EOF
docker run -p 127.0.0.1:5000:5000 --env-file .env \
-e PRIVATE_KEY="$(cat private_key.pem)" \
ghcr.io/norwegianveterinaryinstitute/pymaskinporten:main
--env-file keeps quotes as part of the value and doesn't support multi-line values, so leave
the values unquoted and pass the PEM key with -e. In PowerShell, use
-e PRIVATE_KEY="$(Get-Content -Raw private_key.pem)".
Then open http://127.0.0.1:5000.
Metadata
Release files for pymaskinporten 2.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pymaskinporten-2.0.1.tar.gz | 10.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pymaskinporten-2.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 23.1 kB
Release files / pymaskinporten-2.0.1.tar.gz
| Download URL | pymaskinporten-2.0.1.tar.gz |
|---|---|
| Size | 10.7 kB |
| Tags | Source |
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