Vyper

Python configuration with (more) fangs! Python port of the very awesome Viper for Go.

PyPI name change

The package changed name on pypi from vyper to vyper-config on August 20th 2018. The vyper name is now used by the following project. The vyper-config package is available on PyPI.

What is Vyper?

Vyper is a complete configuration solution for Python applications including 12 factor apps. It is designed to work within an application, and can handle all types of configuration needs and formats. It supports:

• setting defaults
• reading from JSON, TOML, and YAML config files
• live watching and re-reading of config files (optional)
• reading from environment variables
• reading from remote config systems (etcd, Consul or ZooKeeper)
• live watching and re-reading of remote config files (optional)
• reading from command line arguments
• reading from buffer
• setting explicit values

Vyper can be thought of as a registry for all of your applications configuration needs.

Why Vyper?

When building a modern application, you don’t want to worry about configuration file formats; you want to focus on building awesome software. Vyper is here to help with that.

Vyper does the following for you:

1. Find, load, and unmarshall a configuration file in JSON, TOML, or YAML format.
2. Provide a mechanism to set default values for your different configuration options.
3. Provide a mechanism to set override values for options specified through command line arguments.
4. Provide an alias system to easily rename parameters without breaking existing code.
5. Make it easy to tell the difference between when a user has provided a command line or config file which is the same as the default.

Vyper uses the following precedence order. Each item takes precedence over the item below it:

• explicit call to set
• argument
• environment variable
• config
• key/value store
• default

Vyper configuration keys are case insensitive.

Putting Values into Vyper

Establishing Defaults

A good configuration system will support default values. A default value is not required for a key, but it's useful in the event that a key hasn't been set via config file, environment variable, remote configuration or argument.

Examples:

v.set_default('ContentDir', 'content')
v.set_default('LayoutDir', 'layouts')
v.set_default('Taxonomies', {'tag': 'tags', 'category': 'categories'})

Reading Config Files

Vyper requires minimal configuration so it knows where to look for config files. Vyper supports JSON, TOML and YAML files. Vyper can search multiple paths, but currently a single Vyper instance only supports a single configuration file. Vyper does not default to any configuration search paths leaving defaults decision to an application.

Here is an example of how to use Vyper to search for and read a configuration file. None of the specific paths are required, but at least one path should be provided where a configuration file is expected.

v.set_config_name('config')  # name of config file (without extension)
v.add_config_path('/etc/appname/')  # path to look for the config file in
v.add_config_path('$HOME/.appname')  # call multiple times to add many search paths
v.add_config_path('.')  # optionally look for config in the working directory
v.read_in_config()  # Find and read the config file

Watching and re-reading config files

Vyper supports the ability to have your application live read a config file while running.

Gone are the days of needing to restart a server to have a config take effect, vyper powered applications can read an update to a config file while running and not miss a beat.

Simply tell the Vyper instance to watch_config(). Optionally you can provide a function for Vyper to run each time a change occurs.

Make sure you add all of the config_paths prior to calling watch_config()

v.watch_config()
def f():
    print('Config file changed')
v.on_config_change(f)

Reading Config from buffer

Vyper pre-defines many configuration sources such as files, environment variables, arguments, and remote K/V store, but you are not bound to them. You can also implement your own required configuration source and feed it to Vyper.

v.set_config_type('yaml')  # or v.set_config_type('YAML')

# any approach to require this configuration into your program.
yaml_example = '''
Hacker: true
name: steve
hobbies:
- skateboarding
- snowboarding
- go
clothing:
  jacket: leather
  trousers: denim
age: 35
eyes : brown
beard: true
'''

v.read_config(yaml_example)

v.get('name')  # this would be 'steve'

Setting Overrides

These could be from a command line argument, or from your own application logic.

v.set('Verbose', True)
v.set('LogFile', log_file)

Registering and Using Aliases

Aliases permit a single value to be referenced by multiple keys

v.register_alias('loud', 'Verbose')

v.set('verbose', True)  # same result as next line
v.set('loud', True)  # same result as prior line

v.get_bool('loud')  # True
v.get_bool('verbose')  # True

Working with Environment Variables

Vyper has full support for environment variables. This enables 12 factor applications out of the box. There are four methods that exist to aid working with ENV:

• automatic_env()
• bind_env(string)
• set_env_prefix(string)
• set_env_replacer(string)

When working with ENV variables, it’s important to recognize that Vyper treats ENV variables as case sensitive.

Vyper provides a mechanism to try to ensure that ENV variables are unique. By using set_env_prefix(), you can tell Vyper to use add a prefix while reading from the environment variables. Both bind_env() and automatic_env() will use this prefix.

bind_env() takes one or two parameters. The first parameter is the key name, the second is the name of the environment variable. The name of the environment variable is case sensitive. If the ENV variable name is not provided, then Vyper will automatically assume that the key name matches the ENV variable name, but the ENV variable is IN ALL CAPS. When you explicitly provide the ENV variable name, it does not automatically add the prefix.

One important thing to recognize when working with ENV variables is that the value will be read each time it is accessed. Vyper does not fix the value when the bind_env() is called.

automatic_env() is a powerful helper especially when combined with set_env_prefix(). When called, Vyper will check for an environment variable any time a v.get() request is made. It will apply the following rules. It will check for a environment variable with a name matching the key uppercased and prefixed with the env_prefix() if set.

set_env_replacer() allows you to use a str object to rewrite Env keys to an extent. This is useful if you want to use - or something in your get() calls, but want your environmental variables to use _ delimiters. An example of using it can be found in tests/test_vyper.py.

Env example

v.set_env_prefix('spf')  # will be uppercased automatically
v.bind_env('id')

os.environ['SPF_ID'] = '13'  # typically done outside of the app

id = v.get('id')  # 13

Working with command line arguments

Vyper has the ability to bind to command line arguments. Specifically, Vyper supports argparse. See doc for more details.

The values are set when the binding method is called.

As it deals with command line arguments, the bind_args() method needs to be called passing an instance of argparse.ArgumentParser(). The method also sets defaults based on what you pass via add_argument() default parameter.

Note: If you don't specify a default, the values will be set to None.

p = argparse.ArgumentParser(description="Application settings")
p.add_argument('--app-name', type=str, help='Application and process name')
p.add_argument('--env', type=str, choices=['dev', 'pre-prod', 'prod'], help='Application env')
p.add_argument('--port', type=int, default=5000, help='Application port')
p.add_argument('--password', type=str, help='Application password')
v.bind_args(p)

# "your_app.py", "--app-name=cmd-app", "--env=prod"

app_name = v.get('app_name')  # 'cmd-app'
env = v.get('env')            # 'prod'
port = v.get('port')          # 5000
password = v.get('password')  # `None`

Getting Values From Vyper

In Vyper, there are a few ways to get a value depending on the value's type. The following functions and methods exist:

• get(key)
• get_bool(key) : bool
• get_float(key) : float
• get_int(key) : int
• get_string(key) : str
• is_set(key) : bool

One important thing to recognize is that each get function will return a zero value if it’s not found. To check if a given key exists, the is_set() method has been provided.

Example:

v.get_string('logfile')  # case-insensitive Setting & Getting
if v.get_bool('verbose'):
    print('verbose enabled')

Accessing nested keys

The accessor methods also accept formatted paths to deeply nested keys. For example, if the following JSON file is loaded:

{
    "host": {
        "address": "localhost",
        "port": 5799
    },
    "datastore": {
        "metric": {
            "host": "127.0.0.1",
            "port": 3099
        },
        "warehouse": {
            "host": "198.0.0.1",
            "port": 2112
        }
    }
}

Vyper can access a nested field by passing a . delimited path of keys:

v.get_string('datastore.metric.host')  # returns '127.0.0.1'

This obeys the precedence rules established above; the search for the root key (in this example, datastore) will cascade through the remaining configuration registries until found. The search for the sub-keys (metric and host), however, will not.

For example, if the metric key was not defined in the configuration loaded from file, but was defined in the defaults, Vyper would return the zero value.

On the other hand, if the primary key was not defined, Vyper would go through the remaining registries looking for it.

Lastly, if there exists a key that matches the delimited key path, its value will be returned instead. E.g.

{
    "datastore.metric.host": "0.0.0.0",
    "host": {
        "address": "localhost",
        "port": 5799
    },
    "datastore": {
        "metric": {
            "host": "127.0.0.1",
            "port": 3099
        },
        "warehouse": {
            "host": "198.0.0.1",
            "port": 2112
        }
    }
}

v.get_string('datastore.metric.host')  # returns '0.0.0.0'

Vyper or Vypers?

Vyper comes ready to use out of the box. There is no configuration or initialization needed to begin using Vyper. Since most applications will want to use a single central repository for their configuration, the vyper package provides this. It is similar to a singleton.

In all of the examples above, they demonstrate using vyper in it's singleton style approach.