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Yet Another Python Configuration. A simple way to manage configurations for python applications.
Yapconf allows you to easily manage your python application's configuration. It handles everything involving your application's configuration. Often times exposing your configuration in sensible ways can be difficult. You have to consider loading order, and lots of boilerplate code to update your configuration correctly. Now what about CLI support? Migrating old configs to the new config? Yapconf can help you.
Yapconf helps manage your python application's configuration
To install Yapconf, run this command in your terminal:
.. code-block:: console
$ pip install yapconf
Then you can use Yapconf yourself!
Load your first config
.. code-block:: python
from yapconf import YapconfSpec
# First define a specification
spec_def = {
"foo": {"type": "str", "default": "bar"},
}
my_spec = YapconfSpec(spec_def)
# Now add your source
my_spec.add_source('my yaml config', 'yaml', filename='./config.yaml')
# Then load the configuration!
config = my_spec.load_config('config.yaml')
print(config.foo)
print(config['foo'])
In this example load_config will look for the 'foo' value in the file
./config.yaml and will fall back to the default from the specification
definition ("bar") if it's not found there.
Try running with an empty file at ./config.yaml, and then try running with
.. code-block:: yaml
foo: baz
Load from Environment Variables
.. code-block:: python
from yapconf import YapconfSpec
# First define a specification
spec_def = {
"foo-dash": {"type": "str", "default": "bar"},
}
my_spec = YapconfSpec(spec_def, env_prefix='MY_APP_')
# Now add your source
my_spec.add_source('env', 'environment')
# Then load the configuration!
config = my_spec.load_config('env')
print(config.foo)
print(config['foo'])
In this example load_config will look for the 'foo' value in the
environment and will fall back to the default from the specification
definition ("bar") if it's not found there.
Try running once, and then run export MY_APP_FOO_DASH=BAZ in the shell
and run again.
Note that the name yapconf is searching the environment for has been modified.
The env_prefix MY_APP_ as been applied to the name, and the name itself has
been capitalized and converted to snake-case.
Load from CLI arguments
.. code-block:: python
import argparse
from yapconf import YapconfSpec
# First define a specification
spec_def = {
"foo": {"type": "str", "default": "bar"},
}
my_spec = YapconfSpec(spec_def)
# This will add --foo as an argument to your python program
parser = argparse.ArgumentParser()
my_spec.add_arguments(parser)
# Now you can load these via load_config:
cli_args = vars(parser.parse_args(sys.argv[1:]))
config = my_spec.load_config(cli_args)
print(config.foo)
print(config['foo'])
Load from multiple sources
.. code-block:: python
from yapconf import YapconfSpec
# First define a specification
spec_def = {
"foo": {"type": "str", "default": "bar"},
}
my_spec = YapconfSpec(spec_def, env_prefix='MY_APP_')
# Now add your sources (order does not matter)
my_spec.add_source('env', 'environment')
my_spec.add_source('my yaml file', 'yaml', filename='./config.yaml')
# Now load your configuration using the sources in the order you want!
config = my_spec.load_config('my yaml file', 'env')
print(config.foo)
print(config['foo'])
In this case load_config will look for 'foo' in ./config.yaml. If not
found it will look for MY_APP_FOO in the environment, and if stil not
found it will fall back to the default.
Since the 'my yaml file' label comes first in the load_config arguments
yapconf will look there for values first, even though add_source was
called with 'env' first.
Watch your config for changes
.. code-block:: python
def my_handler(old_config, new_config):
print("TODO: Something interesting goes here.")
my_spec.spawn_watcher('config.yaml', target=my_handler)
Generate documentation for your config
.. code-block:: python
# Show me some sweet Markdown documentation
my_spec(spec.generate_documentation())
# Or write it to a file
spec.generate_documentation(output_file_name='configuration_docs.md')
For more detailed information and better walkthroughs, checkout the documentation!
Documentation is available at https://yapconf.readthedocs.io
This package was created with Cookiecutter_ and the audreyr/cookiecutter-pypackage_ project template.
.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _audreyr/cookiecutter-pypackage: https://github.com/audreyr/cookiecutter-pypackage
dump_data to __all__fq_name was not correctly set for complex objectsdump_kwargs to migrate_config (#53)long_description on config items (#44)validator on config items (#43)choices to item specification (#14)alt_env_names to item specification (#13)None was a respected value.FAQs
Yet Another Python Configuration
We found that yapconf demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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