Usage¶
In order to use Yapconf in a project, you will first need to create your specification object. There are lots of options for this object, so we’ll just start with the basics. Check out the Item Arguments section for all the options available to you. For now, let’s just assume we have the following specification defined
from yapconf import YapconfSpec
my_spec = YapconfSpec({
'db_name': {'type': 'str'},
'db_port': {'type': 'int'},
'db_host': {'type': 'str'},
'verbose': {'type': 'bool', 'default': True},
'filename': {'type': 'str'},
})
Now that you have a specification for your configuration, you should add some sources for where these config values can be found from. You can find a list of all available sources in the Sources section.
# Let's say you loaded this dict from the command-line (more on that later)
cli_args = {'filename': '/path/to/config', 'db_name': 'db_from_cli'}
# Also assume you have /some/config.yml that has the following:
# db_name: db_from_config_file
# db_port: 1234
config_file = '/some/config.yml' # JSON is also supported!
# Finally, let's assume you have the following set in your environment
# DB_NAME="db_from_environment"
# FILENAME="/some/default/config.yml"
# DB_HOST="localhost"
# You can, just call load_config directly, but it is helpful to add these as sources
# to your specification:
my_spec.add_source('cli_args', 'dict', data=cli_args)
my_spec.add_source('environment', 'environment')
my_spec.add_source('config.yaml', 'yaml', filename=config_file)
Then you can load your configuration by calling load_config
. When using this method, it is
significant the order in which you pass yoru arguments as it sets precedence for load order. Let’s
see this in practice.
# You can load your config:
config = my_spec.load_config('cli_args', 'config.yaml', 'environment')
# You now have a config object which can be accessed via attributes or keys:
config.db_name # > db_from_cli
config['db_port'] # > 1234
config.db_host # > localhost
config['verbose'] # > True
config.filename # > /path/to/config
# If you loaded in a different order, you'll get a different result
config = my_spec.load_config('environment', 'config.yaml', 'cli_args')
config.db_name # > db_from_environment
This config object is powered by python-box which is a handy utility for handling your config object. It behaves just like a dictionary and you can treat it as such!
Loading config without adding sources¶
If all you want to do is load your configuration, you can do that without sources. The point of the sources is to allow yapconf to eventually support watching those configs. See the yapconf watcher issue for more details.
# You can load your config without the add_source calls:
config = my_spec.load_config(cli_args, '/path/to/config.yaml', 'ENVIRONMENT')
Nested Items¶
In a lot of cases, it makes sense to nest your configuration, for example, if we wanted to take all of our database configuration and put it into a single dictionary, that would make a lot of sense. You would specify this to yapconf as follows:
nested_spec = YapconfSpec({
'db': {
'type': 'dict',
'items': {
'name': { 'type': 'str' },
'port': { 'type': 'int' }
}
}
})
config = nested_spec.load_config({'db': {'name': 'db_name', 'port': 1234}})
config.db.name # returns 'name'
config.db.port # returns 1234
config.db # returns the db dictionary
List Items¶
List items are a special class of nested items which is only allowed to have a single item listed. It can be specified as follows:
list_spec = YapconfSpec({
'names': {
'type': 'list',
'items': {
'name': {'type': 'str'}
}
}
})
config = list_spec.load_config({'names': ['a', 'b', 'c']})
config.names # returns ['a', 'b', 'c']
Environment Loading¶
If no env_name
is specified for each item, then by default, Yapconf will automatically format
the item’s name to be all upper-case and snake case. So the name foo_bar
will become
FOO_BAR
and fooBar
will become FOO_BAR
. If you do not want to apply this formatting,
set format_env
to False
. Loading list
items and dict
items from the environment is
not supported and as such env_name
s that are set for these items will be ignored.
Often times, you will want to prefix environment variables with your application name or something
else. You can set an environment prefix on the YapconfSpec
item via the env_prefix
:
import os
env_spec = Specification({'foo': {'type': 'str'}}, 'MY_APP_')
os.environ['FOO'] = 'not_namespaced'
os.environ['MY_APP_FOO'] = 'namespaced_value'
config = env_spec.load_config('ENVIRONMENT')
config.foo # returns 'namespaced_value'
Note
When using an env_name
with env_prefix
the env_prefix
will still be applied
to the name you provided. If you want to avoid this behavior, set the apply_env_prefix
to
False
.
As of version 0.1.2, you can specify additional environment names via: alt_env_names
. The
apply_env_prefix
flag will also apply to each of these. If your environment names collide with
other names, then an error will get raised when the specification is created.
CLI Support¶
Yapconf has some great support for adding your configuration items as command-line arguments by
utilizing argparse. Let’s assume the my_spec
object from the original example
import argparse
my_spec = YapconfSpec({
'db_name': {'type': 'str'},
'db_port': {'type': 'int'},
'db_host': {'type': 'str'},
'verbose': {'type': 'bool', 'default': True},
'filename': {'type': 'str'},
})
parser = argparser.ArgumentParser()
my_spec.add_arguments(parser)
args = [
'--db-name', 'db_name',
'--db-port', '1234',
'--db-host', 'localhost',
'--no-verbose',
'--filename', '/path/to/file'
]
cli_values = vars(parser.parse_args(args))
config = my_spec.load_config(cli_values)
config.db_name # 'db_name'
config.db_port # 1234
config.db_host # 'localhost'
config.verbose # False
config.filename # '/path/to/file'
Yapconf makes adding CLI arguments very easy! If you don’t want to expose something over the
command line you can set the cli_expose
flag to False
.
Boolean Items and the CLI¶
Boolean items will add special flags to the command-line based on their defaults. If you have a
default set to True
then a --no-{item_name}
flag will get added. If the default is
False
then a --{{item_name}}
will get added as an argument. If no default is specified,
then both will be added as mutually exclusive arguments.
Nested Items and the CLI¶
Yapconf even supports list
and dict
type items from the command-line:
import argparse
spec = YapconfSpec({
'names': {
'type': 'list',
'items': {
'name': {'type': 'str'}
}
},
'db': {
'type': 'dict',
'items': {
'host': {'type': 'str'},
'port': {'type': 'int'}
},
}
})
parser = argparse.ArgumentParser()
cli_args = [
'--name', 'foo',
'--name', 'bar',
'--db-host', 'localhost',
'--db-port', '1234',
'--name', 'baz'
]
cli_values = vars(parser.parse_args(args))
config = my_spec.load_config(cli_values)
config.names # ['foo', 'bar', 'baz']
config.db.host # 'localhost'
config.db.port # 1234
Limitations¶
There are a few limitations to how far down the rabbit-hole Yapconf is willing to go. Yapconf does
not support list
type items with either dict
or list
children. The reason is that it
would be very cumbersome to start specifying which items belong to which dictionaries and in which
index in the list.
CLI/Environment Name Formatting¶
A quick note on formatting and yapconf
. Yapconf tries to create sensible ways to convert your
config items into “normal” environment variables and command-line arguments. In order to do this,
we have to make some assumptions about what “normal” environment variables and command-line
arguments are.
By default, environment variables are assumed to be all upper-case, snake-case names. The item
name foO_BaR
would become FOO_BAR
in the environment.
By default, command-line argument are assumed to be kebab-case. The item name foo_bar
would
become --foo-bar
If you do not like this formatting, then you can turn it off by setting the format_env
and
format_cli
flags.
Watching¶
Yapconf supports watching your configuration. There are two main ways that yapconf can help you with configuration changes. You can receive them at the global level (i.e. anytime the config appears to change in the environment), or on an item-by-item basis.
Note
You can only watch sources. So if you want to use the watching functionality, you _must_
use add_source
before these calls.
The simplest way to know your configuration changed is to just use the global level:
def my_handler(old_config, new_config):
print("TODO: Something with the new/old config")
print(old_config)
print(new_config)
my_spec.add_source('label', 'json', '/path/to/file.json')
thread = my_spec.spawn_watcher('label', target=my_handler)
print(thread.isAlive())
The spawn_watcher
command returns a thread. Now, any time /path/to/file.json
changes the
my_handler
event will get called. One thing of note is that if /path/to/file.json
is
deleted, then the thread will die with an exception.
If you want, you can also specify an eternal
flag to the spawn_watcher
call:
thread = my_spec.spawn_watcher('label', eternal=True)
With this flag, if the watcher dies (for example, the /path/to/file.json
is deleted) then a
new watcher will be spawned in its place.
Often times, there are only certain items in a specification that you would like to watch. Parsing
the configuration can be a pain just to figure out what changed. To solve this problem, yapconf
allows you to specify a watch_target
on individual items.
def my_handler(old_foo, new_foo):
print("Foo value changed")
print(old_foo)
print(new_foo)
spec = YapconfSpec({'foo': {'watch_target': my_handler}})
Config Documentation¶
So you have this great app that can be configured easily. Now you need to pass it off to your
operations team. They want to know all the knobs they can tweak and adjust for individual
deployments. Yapconf has you covered. Simply run the generate_documentation
command for your
specification, and behold beautiful documentation for your application!
my_spec.generate_documentation(output_file_name='config_docs.md')
The configuration documentation takes into account all of your sources. So it’s best if you
can add all of your sources before the call to generate_documentation
my_spec.add_source('Source 1 Label', 'etcd', etcd_client)
my_spec.add_source('Source 2 Label', 'yaml', '/path/to/config.yaml')
my_spec.add_source('environment', 'environment')
my_spec.generate_documentation(output_file_name='config_docs.md')
This will give you some basic information about how your application can be configured! If you want to see an example of the documentation that can be generated by yapconf you should check out the example configuration documentation in our repo.
Config Migration¶
Throughout the lifetime of an application it is common to want to move configuration around,
changing both the names of configuration items and the default values for each. Yapconf also makes
this migration a breeze! Each item has a previous_defaults
and previous_names
values that
can be specified. These values help you migrate previous versions of config files to newer
versions. Let’s see a basic example where we might want to update a config file with a new default:
# Assume we have a JSON config file ('/path/to/config.json') like the following:
# {"db_name": "test_db_name", "db_host": "1.2.3.4"}
spec = YapconfSpec({
'db_name': {'type': 'str', 'default': 'new_default', 'previous_defaults': ['test_db_name']},
'db_host': {'type': 'str', 'previous_defaults': ['localhost']}
})
# We can migrate that file quite easily with the spec object:
spec.migrate_config_file('/path/to/config.json')
# Will result in /path/to/config.json being overwritten:
# {"db_name": "new_default", "db_host": "1.2.3.4"}
You can specify different output config files also:
spec.migrate_config_file('/path/to/config.json',
output_file_name='/new/path/to/config.json')
There are many values you can pass to migrate_config_file
, by default it looks like this:
spec.migrate_config_file('/path/to/config',
always_update=False, # Always update values (even if you set them to None)
current_file_type=None, # Used for transitioning between json and yaml config files
output_file_name=None, # Will default to current file name
output_file_type=None, # Used for transitioning between json and yaml config files
create=True, # Create the file if it doesn't exist
update_defaults=True # Update the defaults
)
YAML Support¶
Yapconf knows how to output and read both json
and yaml
files. However, to keep the
dependencies to a minimum it does not come with yaml
. You will have to manually install
either pyyaml
or ruamel.yaml
if you want to use yaml
.
Item Arguments¶
For each item in a specification, you can set any of these keys:
Name | Default | Description |
---|---|---|
name | N/A | The name of the config item |
item_type | 'str' |
The python type of the item ('str', 'int', 'long', 'float', 'bool', 'complex', 'dict', 'list' ) |
default | None |
The default value for this item |
env_name | name.upper() |
The name to search in the environment |
description | None |
Description of the item |
long_description | None |
Long description of the item, will support Markdown in the future |
required | True |
Specifies if the item is required to exist |
cli_short_name | None |
One-character command-line shortcut |
cli_name | None |
An alternate name to use on the command-line |
cli_choices | None |
List of possible values for the item from the command-line |
previous_names | None |
List of previous names an item had |
previous_defaults | None |
List of previous defaults an item had |
items | None |
Nested item definition for use by list or dict type items |
cli_expose | True |
Specifies if this item should be added to arguments on the command-line (nested list are always False ) |
separator | . |
The separator to use for dict type items (useful for previous_names ) |
bootstrap | False |
A flag that indicates this item needs to be loaded before others can be loaded |
format_env | True |
A flag to determine if environment variables will be all upper-case SNAKE_CASE. |
format_cli | True |
A flag to determine if we should format the command-line arguments to be kebab-case. |
apply_env_prefix | True |
Apply the env_prefix even if the environment name was set manually. Ignored if format_env is False |
choices | None |
A list of valid choices for the item. Cannot be set for dict items. |
alt_env_names | [] |
A list of alternate environment names. |
validator | None |
A custom validator function. Must take exactly one value and return True/False. |
fallback | None |
A fully qualified backup name to fallback to if no value could be found |
watch_target | None |
A function to call if the config item changes (you must call spawn_watch for this to take effect. |