piny 1.1.0

Description:

piny 1.1.0

Piny is YAML config loader with environment variables interpolation for Python.
Keep your app’s configuration in a YAML file.
Mark up sensitive data in the config as environment variables.
Set environment variables on application deployment.
Now let the piny load your config and substitute environment variables
in it with their values.
Piny is developed with Docker and Kubernetes in mind,
though it’s not limited to any deployment system.

Rationale
Piny combines readability and versioning you get when using config files,
and security that environment variables provide. Read more about this approach
in the blog post.


Help
See documentation for more details.


Installation
Just run:
pip install -U piny


Usage
Set your environment variables, add them to your YAML configuration file:
db:
login: user
password: ${DB_PASSWORD}
mail:
login: user
password: ${MAIL_PASSWORD:-my_default_password}
sentry:
dsn: ${VAR_NOT_SET}
Then load your config:
from piny import YamlLoader

config = YamlLoader(path="config.yaml").load()
print(config)
# {'db': {'login': 'user', 'password': 'my_db_password'},
# 'mail': {'login': 'user', 'password': 'my_default_password'},
# 'sentry': {'dsn': None}}
You may want to discourage Bash-style envs with defaults in your configs.
In such case, use a StrictMatcher:
from piny import YamlLoader, StrictMatcher

config = YamlLoader(path="config.yaml", matcher=StrictMatcher).load()
Both strict and default matchers produce None value if environment variable
matched is not set in the system (and no default syntax used in the case of
default matcher).
Piny also comes with command line utility that works both with files and standard
input and output:
$ export PASSWORD=mySecretPassword
$ echo "db: \${PASSWORD}" | piny
db: mySecretPassword


Validation
Piny supports optional data validation using third-party libraries:
Marshmallow, Pydantic, Trafaret.
import marshmallow as ma
from piny import MarshmallowValidator, StrictMatcher, YamlLoader

class DBSchema(ma.Schema):
login = ma.fields.String(required=True)
password = ma.fields.String()

class ConfigSchema(ma.Schema):
db = ma.fields.Nested(DBSchema)

config = YamlLoader(
path="database.yaml",
matcher=StrictMatcher,
validator=MarshmallowValidator,
schema=ConfigSchema,
).load(many=False)


Exceptions
LoadingError is thrown when something goes wrong with reading or parsing YAML-file.
ValidationError is a wrapper for exceptions raised by the libraries for optional data validation.
Original exception can be accessed by origin attribute. It comes in handy when you need more than
just an original exception message (e.g. a dictionary of validation errors).
Both exceptions inherit from the ConfigError.


Best practices

Maintain a healthy security/convenience balance for your config
Mark up entity as an environment variable in your YAML if and only if
it really is a secret (login/passwords, private API keys, crypto keys,
certificates, or maybe DB hostname too? You decide)
When loading config file, validate your data.
Piny supports a few popular data validation tools.
Store your config files in the version control system along with your app’s code.
Environment variables are set by whoever is responsible for the deployment.
Modern orchestration systems like Kubernetes make it easier to keep envs secure
(see Kubernetes Secrets).



Fun facts
Piny is a recursive acronym for Piny Is Not YAML.
Not only it’s a library name, but also a name for YAML marked up
with environment variables.


Changelog
See CHANGELOG.rst.


Contributing
See CONTRIBUTING.rst.