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A library for simplifying the configuration of Python applications at all stages of deployment.

Opset is a config manager that let you manage your configuration via yaml file or environment variables. The general principle of Opset is that you want to hold your secrets and manage your configurations via configuration files when doing local development and via environment variables when your app is deployed. It is however possible to also handle local development through environment variables if the developer see fit.

With Opset you define everything that can be tweaked with your application in one specific file (default.yml). This way the developers and integrators working with your code will know exactly what setting they can change on your code base. You can then overwrite the default config with a local config stored in a file called local.yml, this file is aimed to be used for local development by your developers and let them easily manage a configuration file that fits their development need. Finally, you can also have environment variables that have a matching name to your config that will overwrite your config, letting you use your config in a deployed environment without having your secret written down in a config file. Opset aims to reconcile the ease of use of a config file with the added security of environment variables.

This library is available on PyPI under the name Opset. You can install with pip by running pip install opset.

Table of Contents

  1. Lexicon
  2. Architecture Overview
    1. Loading the config for unit tests
    2. Safeguards
      1. Settings not declared in default.yml are not loaded
      2. Forcing all default settings to have values
  3. Usage Guide
    1. Making the difference between null and empty
  4. Example of Usage
    1. Opset + Environment Variables
    2. Naming your config sections
    3. Controlling your entry points
  5. Example Configuration file
    1. default.yml
    2. local.yml
    3. unit_test.yml
    4. Example Logging Configuration values
    5. Log Processors
  6. Support for unit tests
    1. setup_unit_test_config
      1. Usage example of setup_unit_test_config
    2. mock_config
      1. Usage example of mock_config
  7. Contributing and getting set up for local development


Term Definition
config A configuration file (format: YAML).
section A section within a configuration file, a section tend to group different settings together under a logical block. For example a section named redis would encompass all settings related specifically to redis. Section name should not contain underscore.
setting A key within a section in a configuration file. A value is associated with a key and querying the config for a setting within a section will return the value associated with it.


Architecture Overview

There are three possible config files

Config Name Purpose
default.yml This is the base config, default.yml needs to have the declaration of all sections and settings.
local.yml This is a local config that overwrites the default config, this file is not committed to the repository and is meant to be used in a local development environment.
unit_test.yml This is a local config that overwrites the default config during unit tests, this file is not committed to the repository and is meant to be used in a local development environment. When the config is initialized for unit tests, if a unit_test.yml file is present it will be loaded, otherwise the environment variables will be loaded on top of the default config.

The content of the default config is loaded first, and if any settings are redefined in local.yml, the values from default.yml are overwritten by local.yml.

Environment variables will apply after the local.yml overwrite of the config settings if they have a matching name. To do so, the environment variable must be named in the following way:


So for the application my-small-project if we wanted to overwrite the setting port from the section app, your environment variable would need to be named like this:



Loading the config for unit tests

Opset provides a specific function to load the config when performing unit testing that provides the developer with some additional tool to better handle the reality of unit testing. When initializing the config for unit tests, the content of the default config is loaded first, and if the unit_test.yml file is present and have values, the values from default.yml are overwritten by unit_test.yml. Then the values from the environment variables apply and if you need some config values to be specific to your unit tests you have the option to pass config values when loading the unit tests that will overwrite all other sources.



There are two safeguards in the code to try to prevent developer mistakes.

Settings not declared in default.yml are not loaded

Your default.yml is what defines what can be tweaked in your application, it is made to be the one place to look at if you are wondering what can be changed in the configuration of your application.

When loading the configuration a warning will be raised if a setting is detected from the local config, environment variables or unit tests values that is not present in default.yml. This means that if your local.yml config looks like this:

  port: 7777
  ham_level: 7
  api_key: 332d5c3e-a7a3-41db-aa5c-c0dfbac8f3d2

And your default config looks like this:

  port: 7777
  debug: False
  api_key: null

A warning will be issued when the config is loaded because the setting ham_level from the section app is not known to the default config. The setting and value of ham_level will not be loaded in the config and will not be usable in the application if it's not present in default.yml. As per the example above, you are not forced to set a value for settings in the default config (see api_key), but the setting needs to be there.

Forcing all default settings to have values

There is a special flag called critical_settings that is passed to the function setup_config from the module. This flag is set to True by default and will make Opset raises an error if there is no value defined for a setting in default.yml after having applied all possible configuration files and environment variables.

Usage Guide

You interact with the library through the function opset.setup_config to set up the config and with the singleton object opset.config to read config values. Optionally Opset can also manage your application logging via the function opset.load_logging_config or the argument setup_logging from the function opset.setup_config. The opset.config object is a singleton which means that no matter where it is accessed in the code and the loading order, as long as it has been initiated with opset.setup_config it will hold the same configuration values in all of your application.

The library expects that your project will contain yaml files named default.yml and (optionally) local.yml and unit_test.yml. You will be able to point to the location of those config files when invoking opset.setup_config as the second positional argument. The file default.yml should be committed and follow your project and should not contain any secrets. The files local.yml and unit_test.yml should be added to your .gitignore to avoid having them committed by accident as those files can contain secrets.

The opset.setup_config function will handle everything from reading the yaml file containing your project's config values, to loading them into your environment being mindful not to overwrite ENV variables already present. It needs to be passed the name of your application along with the python style path (eg. module.submodule) to where the default.yml, local.yml or unit_test.yml files are located in the project.

To initialize the configuration, use the function opset.setup_config and that's it. After that you can import the variable opset.config from the module to use the config. You can safely import the config variable before initializing it because access to the config object attributes is dynamic. It is important to note that the config is built to be read-only, it gets populated when opset.setup_config and from then on you just read the values from the config as needed in your implementation.

The function setup_config takes the following arguments:

Parameter Description Default value Example
app_name The name of the application, usually the name of the repo. Ex: myproject-example. This will be used
for finding the prefix to the environment variables. The name of the app will be uppercased and dashes
will be replaced by underscores. myproject-example
config_path A python path to where the configuration files are. Relative to the application.
Ex: tasks.config would mean that the config files are located in the directory config of the directory tasks
from the root of the repo. tasks.config
critical_settings A boolean to specify how null settings in default.yml should be handled. If set to True, the function
will raise an exception when a key in default.yml is not defined in local.yml or in an environment variable. True True
setup_logging Whether the logging config should be loaded immediately after the config has been loaded.
Default to True. True True

Making the difference between null and empty

The configuration is stored in yaml and follows the yaml standard. As such, it makes a distinction between null keys and empty keys.

  # this setting's value is declared but not defined
  # it will be set to None when accessed unless it is overwritten in local.yml or in an environment variable
  api_key: null
  # this setting's value is set to an empty string

Naming your config sections

Due to certain limitations when loading environment variables, your config sections should not contain underscores to avoid issues when loading environment variables.

Controlling your entry points

The config object is initiated once you call the function opset.setup_config, before that, trying to get read a value from the config will throw an exception. It is very important to have a good idea of what the entry points are in your application and to call opset.setup_config as early as possible in your application to avoid issues.

To avoid duplicating calls to opset.setup_config we recommend you add the call to opset.setup_config in a function that is called whenever you need to start your application, you can then safely call this function whenever you create a new entry points in your application.

Be mindful about reading values from the config object at module level. If you need to import modules before you can call opset.setup_config and one of those modules has a module-level call to read the config, Opset will raise an error when importing because the code will be read at import time and the config will not have been initiated.

For a more concrete example, avoid doing something like this:

from opset import config

FULL_DB_URI = f"{config.db.scheme}{config.db.user}:{config.db.password}@{}:{config.db.port}"

And do something like this instead:

from opset import config

def get_full_db_uri():
    return f"{config.db.scheme}{config.db.user}:{config.db.password}@{}:{config.db.port}"

Last thing, remember that it is safe to import the config object before the config has been initiated. The config object is a singleton and will be populated after opset.setup_config has been called, even if it was imported first.

Example Of Usage

Here is a little example of how to use the opset features in a simple Flask app.

from flask import Flask, jsonify
from opset import config, setup_config

setup_config("myproject-example", "myproject-example.config")
app = Flask(

def hello():
    return jsonify({"Hello and welcome to":})

This example will leverage the config values stored under the myproject-example/config folder, with the following content:

  welcome_message: Hi lads

Opset + Environment Variables

One of the features of Opset is how it handles the interaction between the config values in your projects' yaml files and the values that might already be set in your environment. Values already in your environment have higher priority and will overwrite any values in your config files. In order to compare against the environment variables, Opset builds the names for config values using <APP_NAME>_<SECTION_NAME>_<SETTING_NAME> as a template. This means that if your environment contains the value MYPROJECT_EXAMPLE_DATABASE_HOST, and your application is named myproject-example it will overwrite the value of the database host from the following config file:


The conversion to python types from the yaml config file is handled by pyyaml but for environment variables Opset do its own conversion depending on the value:

  • true, t, yes, y (case-insensitive) will be converted to a True bool
  • false, f, no, n (case-insensitive) will be converted to a False bool
  • Any number-only string will be converted to an int if they have no decimals and float if they do
  • A JSON-valid array will be converted to a list
  • A JSON-valid object will be converted to a dict
  • Any other value will remain a str

NOTE: Be sure to respect JSON conventions when defining arrays and objects, use lower-case booleans, double quotes, etc.

Example Configuration file


Declare in the default.yml file all the settings that the app will require. For each of the keys, you can define a default value. If there is no sensible defaults for a setting, leave it blank (which is equivalent to setting it to null).

As a rule of thumb, a default value should be equally good and safe for local, staging or prod environments. For example, setting app.debug above to True would be an error as it may cause prod to run with debug messages enabled if prod is not overriding it. The opposite is also true. A default value pointing to a production system can easily wipe or overload it during testing if tests do not overwrite the defaults properly. When in doubt, prefer a null value.

Also, secrets should NEVER be added to this file.


This file is typically defined by developers for their own development and local usage of the app. This file may contain secrets and as such it must be added to the .gitignore file.


This file is used to handle configuration values when running unit tests locally by developers. The content of this file is only used when initiating the config through opset.setup_unit_test_config and is discussed in more details in the section of the documentation dedicated to unit testing. This file may contain secrets and as such it must be added to the .gitignore file.

Example Logging Configuration values

Opset also provides functionality for configuring the logging handlers for your project, this uses structlog in the background. This is provided through the aforementioned load_logging_config function. If you choose to use this functionality, you will need to add some more values to your configuration files, and you can find an example of such values here:

  date_format: "iso"  # strftime-valid date format, e.g.: "%Y-%M-%d", or "iso" to use the standard ISO format
  use_utc: True  # Use UTC timezone if true, or local otherwise
  min_level: DEBUG  # Minimum level to display log for
  disable_processors: False  # Disables log processors (additional info at the end of the log record)
  logger_overrides:  # overwrite min log level of third party loggers
    googleapiclient: ERROR

Log Processors

Since we are using structlog you can use the Processor feature to add additional info to your log records, this can be useful to add a request ID, or the hostname of the machine to all your log records without having to pass anything to your logging calls.

To use this simply define any processors you want by inheriting from the BaseProcessor class of opset and pass an instance to the load_logging_config call:

import logging

from flask import Flask
from opset import BaseProcessor, load_logging_config, setup_config

from my_app.request_context import get_request_id

class RequestContextProcessor(BaseProcessor):
    def __call__(self, logger, name, event_dict):
        event_dict["request_id"] = get_request_id()
        return event_dict

setup_config("my_app", "my_app.config", setup_logging=False)  # Defer the logging setup
load_logging_config(custom_processors=[RequestContextProcessor()])  # Pass your custom processors

app = Flask(__name__)

def root():"This will include the request ID!")
    return "OK"

A processor receives the logger object, the logger name and most importantly the event_dict which contains all the info of the log record. So simply add to the event_dict in your processor and return it.

In local development processors can add some unnecessary noise to the log output, so they can be disabled by setting logging.disable_processors to True in your local.yml.

By default, Opset enables the built-in HostNameProcessor, which adds the machine hostname to log records. It can be disabled by passing use_hostname_processor=False in the load_logging_config call.

Support for unit tests

Opset support unit testing to make sure you can handle the special cases that may come up in your application configuration during unit testing.


The function opset.setup_unit_test_config is made to replace opset.setup_config when running unit tests. Remember to control your entry points and call this function as early as possible when running the unit tests. If you are using pytest it is recommended to add it to a module set at the root of your unit tests package.

opset.setup_unit_test_config works in the same way as opset.setup_config but will load the yaml config file unit_test.yml if present instead of local.yml. It also accepts an additional parameter called config_values that is a dictionary representation of a config file that will have the highest priority when doing overwrites.

Parameter Description Default value Example
app_name The name of the application, usually the name of the repo. Ex: myproject-example. This will be used
for finding the prefix to the environment variables. The name of the app will be uppercased and dashes
will be replaced by underscores. myproject-example
config_path A python path to where the configuration files are. Relative to the application.
Ex: tasks.config would mean that the config files are located in the directory config of the directory tasks
from the root of the repo. tasks.config
config_values A dictionary mimicking the structure of the config files, to be applied as an overwrite on top of
default + unit_test config (if available) and env variables. {"app": {"debug": False}}

Usage example of setup_unit_test_config

In default.yml:

    name: staging

In unit_test.yml:

    user: serge
    password: mystrongpassword

In the module a the root of your unit tests package:

from opset import config, setup_unit_test_config

setup_unit_test_config("myproject-example", "myproject-example.config", config_values={"db": {"name": "test"}})

After running opset.setup_unit_test_config the config will hold the following values:

>>> config.db.user

>>> config.db.password



The function opset.mock_config is a context manager that lets you overwrite config values from the config object for the time of a unit tests. If your unit test requires for the time of a test to have your config hold a special temporary value, opset.mock_config is there for you. It takes the parameter config_values which is identical to what opset.setup_unit_test_config uses.

Your config object will be duplicated for the duration of your context manager and overwritten by the values you send to the parameter config_values. Once you exit the context manager the copy of the config disappears and your application resumes with the config object being in the same state as it was before entering the context manager.

Usage example of mock_config

In your module to be tested:

from opset import config

def is_admin(user_name: str) -> bool:
    return user_name in

In your default.yml:


In your unit_test.yml:

      - "jotaro kujo"

In your unit test module:

from opset import mock_config

from my_package.my_module import is_admin

def test_is_admin():
    # Test true
    assert is_admin("jotaro kujo")
    # Test false
    with mock_config(config_values={"app": {"admin_list": []}}):
        assert not is_admin("jotaro kujo")

Contributing and getting set up for local development

To set yourself up for development on Opset, make sure you are using poetry and simply run the following commands from the root directory:

make bootstrap
make install

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