Confuse: Painless Configuration
===============================

`Confuse`_ is a straightforward, full-featured configuration system
for Python.

.. _Confuse: https://github.com/beetbox/confuse


Basic Usage
-----------

Set up your Configuration object, which provides unified access to
all of your application’s config settings:

.. code-block:: python

    config = confuse.Configuration('MyGreatApp', __name__)

The first parameter is required; it’s the name of your application, which
will be used to search the system for a config file named ``config.yaml``.
See :ref:`Search Paths` for the specific locations searched.

The second parameter is optional: it’s the name of a module that will
guide the search for a *defaults* file. Use this if you want to include a
``config_default.yaml`` file inside your package. (The included
``example`` package does exactly this.)

Now, you can access your configuration data as if it were a simple
structure consisting of nested dicts and lists—except that you need to
call the method ``.get()`` on the leaf of this tree to get the result as
a value:

.. code-block:: python

    value = config['foo'][2]['bar'].get()

Under the hood, accessing items in your configuration tree builds up a
*view* into your app’s configuration. Then, ``get()`` flattens this view
into a value, performing a search through each configuration data source
to find an answer. (More on views later.)

If you know that a configuration value should have a specific type, just
pass that type to ``get()``:

.. code-block:: python

    int_value = config['number_of_goats'].get(int)

This way, Confuse will either give you an integer or raise a
``ConfigTypeError`` if the user has messed up the configuration. You’re
safe to assume after this call that ``int_value`` has the right type. If
the key doesn’t exist in any configuration file, Confuse will raise a
``NotFoundError``. Together, catching these exceptions (both subclasses
of ``confuse.ConfigError``) lets you painlessly validate the user’s
configuration as you go.


View Theory
-----------

The Confuse API is based on the concept of *views*. You can think of a
view as a *place to look* in a config file: for example, one view might
say “get the value for key ``number_of_goats``”. Another might say “get
the value at index 8 inside the sequence for key ``animal_counts``”. To
get the value for a given view, you *resolve* it by calling the
``get()`` method.

This concept separates the specification of a location from the
mechanism for retrieving data from a location. (In this sense, it’s a
little like `XPath`_: you specify a path to data you want and *then* you
retrieve it.)

Using views, you can write ``config['animal_counts'][8]`` and know that
no exceptions will be raised until you call ``get()``, even if the
``animal_counts`` key does not exist. More importantly, it lets you
write a single expression to search many different data sources without
preemptively merging all sources together into a single data structure.

Views also solve an important problem with overriding collections.
Imagine, for example, that you have a dictionary called
``deliciousness`` in your config file that maps food names to tastiness
ratings. If the default configuration gives carrots a rating of 8 and
the user’s config rates them a 10, then clearly
``config['deliciousness']['carrots'].get()`` should return 10. But what
if the two data sources have different sets of vegetables? If the user
provides a value for broccoli and zucchini but not carrots, should
carrots have a default deliciousness value of 8 or should Confuse just
throw an exception? With Confuse’s views, the application gets to decide.

The above expression, ``config['deliciousness']['carrots'].get()``,
returns 8 (falling back on the default). However, you can also write
``config['deliciousness'].get()``. This expression will cause the
*entire* user-specified mapping to override the default one, providing a
dict object like ``{'broccoli': 7, 'zucchini': 9}``. As a rule, then,
resolve a view at the same granularity you want config files to override
each other.

.. warning::
    It may appear that calling ``config.get()`` would retrieve the entire
    configuration at once. However, this will return only the
    *highest-priority* configuration source, masking any lower-priority
    values for keys that are not present in the top source. This pitfall is
    especially likely when using :ref:`Command-Line Options` or
    :ref:`Environment Variables`, which may place an empty configuration
    at the top of the stack. A subsequent call to ``config.get()`` might
    then return no configuration at all.

.. _XPath: http://www.w3.org/TR/xpath/


Validation
----------

We saw above that you can easily assert that a configuration value has a
certain type by passing that type to ``get()``. But sometimes you need
to do more than just type checking. For this reason, Confuse provides a
few methods on views that perform fancier validation or even
conversion:

* ``as_filename()``: Normalize a filename, substituting tildes and
  absolute-ifying relative paths. For filenames defined in a config file,
  by default the filename is relative to the application's config directory
  (``Configuration.config_dir()``, as described below). However, if the config
  file was loaded with the ``base_for_paths`` parameter set to ``True``
  (see :ref:`Manually Specifying Config Files`), then a relative path refers
  to the directory containing the config file. A relative path from any other
  source (e.g., command-line options) is relative to the working directory. For
  full control over relative path resolution, use the ``Filename`` template
  directly (see :ref:`Filename`).
* ``as_choice(choices)``: Check that a value is one of the provided
  choices. The argument should be a sequence of possible values. If the
  sequence is a ``dict``, then this method returns the associated value
  instead of the key.
* ``as_number()``: Raise an exception unless the value is of a numeric
  type.
* ``as_pairs()``: Get a collection as a list of pairs. The collection
  should be a list of elements that are either pairs (i.e., two-element
  lists) already or single-entry dicts. This can be helpful because, in
  YAML, lists of single-element mappings have a simple syntax (``- key:
  value``) and, unlike real mappings, preserve order.
* ``as_str_seq()``: Given either a string or a list of strings, return a list
  of strings. A single string is split on whitespace.
* ``as_str_expanded()``: Expand any environment variables contained in
  a string using `os.path.expandvars()`_.

.. _os.path.expandvars(): https://docs.python.org/library/os.path.html#os.path.expandvars

For example, ``config['path'].as_filename()`` ensures that you get a
reasonable filename string from the configuration. And calling
``config['direction'].as_choice(['up', 'down'])`` will raise a
``ConfigValueError`` unless the ``direction`` value is either "up" or
"down".


Command-Line Options
--------------------

Arguments to command-line programs can be seen as just another *source*
for configuration options. Just as options in a user-specific
configuration file should override those from a system-wide config,
command-line options should take priority over all configuration files.

You can use the `argparse`_ and `optparse`_ modules from the standard
library with Confuse to accomplish this. Just call the ``set_args``
method on any view and pass in the object returned by the command-line
parsing library. Values from the command-line option namespace object
will be added to the overlay for the view in question. For example, with
argparse:

.. code-block:: python

    args = parser.parse_args()
    config.set_args(args)

Correspondingly, with optparse:

.. code-block:: python

    options, args = parser.parse_args()
    config.set_args(options)

This call will turn all of the command-line options into a top-level
source in your configuration. The key associated with each option in the
parser will become a key available in your configuration. For example,
consider this argparse script:

.. code-block:: python

    config = confuse.Configuration('myapp')
    parser = argparse.ArgumentParser()
    parser.add_argument('--foo', help='a parameter')
    args = parser.parse_args()
    config.set_args(args)
    print(config['foo'].get())

This will allow the user to override the configured value for key
``foo`` by passing ``--foo <something>`` on the command line.

Overriding nested values can be accomplished by passing `dots=True` and
have dot-delimited properties on the incoming object.

.. code-block:: python

    parser.add_argument('--bar', help='nested parameter', dest='foo.bar')
    args = parser.parse_args()  # args looks like: {'foo.bar': 'value'}
    config.set_args(args, dots=True)
    print(config['foo']['bar'].get())

`set_args` works with generic dictionaries too.

.. code-block:: python

    args = {
      'foo': {
        'bar': 1
      }
    }
    config.set_args(args, dots=True)
    print(config['foo']['bar'].get())

.. _argparse: http://docs.python.org/dev/library/argparse.html
.. _parse_args: http://docs.python.org/library/argparse.html#the-parse-args-method
.. _optparse: http://docs.python.org/library/optparse.html

Note that, while you can use the full power of your favorite
command-line parsing library, you'll probably want to avoid specifying
defaults in your argparse or optparse setup. This way, Confuse can use
other configuration sources---possibly your
``config_default.yaml``---to fill in values for unspecified
command-line switches. Otherwise, the argparse/optparse default value
will hide options configured elsewhere.


Environment Variables
---------------------

Confuse supports using environment variables as another source to provide an
additional layer of configuration. The environment variables to include are
identified by a prefix, which defaults to the uppercased name of your
application followed by an underscore. Matching environment variable names
are first stripped of this prefix and then lowercased to determine the
corresponding configuration option. To load the environment variables for
your application using the default prefix, just call ``set_env`` on your
``Configuration`` object. Config values from the environment will then be
added as an overlay at the highest precedence. For example:

.. code-block:: sh

    export MYAPP_FOO=something

.. code-block:: python

    import confuse
    config = confuse.Configuration('myapp', __name__)
    config.set_env()
    print(config['foo'].get())

Nested config values can be overridden by using a separator string in the
environment variable name. By default, double underscores are used as the
separator for nesting, to avoid clashes with config options that contain
single underscores. Note that most shells restrict environment variable names
to alphanumeric and underscore characters, so dots are not a valid separator.

.. code-block:: sh

    export MYAPP_FOO__BAR=something

.. code-block:: python

    import confuse
    config = confuse.Configuration('myapp', __name__)
    config.set_env()
    print(config['foo']['bar'].get())

Both the prefix and the separator can be customized when using ``set_env``.
Note that prefix matching is done to the environment variables *prior* to
lowercasing, while the separator is matched *after* lowercasing.

.. code-block:: sh

    export APPFOO_NESTED_BAR=something

.. code-block:: python

    import confuse
    config = confuse.Configuration('myapp', __name__)
    config.set_env(prefix='APP', sep='_nested_')
    print(config['foo']['bar'].get())

For configurations that include lists, use integers starting from 0 as nested
keys to invoke "list conversion." If any of the sibling nested keys are not
integers or the integers are not sequential starting from 0, then conversion
will not be performed. Nested lists and combinations of nested dicts and lists
are supported.

.. code-block:: sh

    export MYAPP_FOO__0=first
    export MYAPP_FOO__1=second
    export MYAPP_FOO__2__BAR__0=nested
    
.. code-block:: python

    import confuse
    config = confuse.Configuration('myapp', __name__)
    config.set_env()
    print(config['foo'].get())  # ['first', 'second', {'bar': ['nested']}]

For consistency with YAML config files, the values of environment variables
are type converted using the same YAML parser used for file-based configs.
This means that numeric strings will be converted to integers or floats, "true"
and "false" will be converted to booleans, and the empty string or "null" will
be converted to ``None``. Setting an environment variable to the empty string
or "null" allows unsetting a config value from a lower-precedence source.

To change the lowercasing and list handling behaviors when loading environment
variables or to enable full YAML parsing of environment variables, you can
initialize an ``EnvSource`` configuration source directly.

If you use config overlays from both command-line args and environment
variables, the order of calls to ``set_args`` and ``set_env`` will
determine the precedence, with the last call having the highest precedence.


Search Paths
------------

Confuse looks in a number of locations for your application's
configurations. The locations are determined by the platform. For each
platform, Confuse has a list of directories in which it looks for a
directory named after the application. For example, the first search
location on Unix-y systems is ``$XDG_CONFIG_HOME/AppName`` for an
application called ``AppName``.

Here are the default search paths for each platform:

* macOS: ``~/.config/app`` and ``~/Library/Application Support/app``
* Other Unix: ``~/.config/app`` and ``/etc/app``
* Windows: ``%APPDATA%\app`` where the `APPDATA` environment variable falls
  back to ``%HOME%\AppData\Roaming`` if undefined

Both macOS and other Unix operating sytems also try to use the
``XDG_CONFIG_HOME`` and ``XDG_CONFIG_DIRS`` environment variables if set
then search those directories as well.

Users can also add an override configuration directory with an
environment variable. The variable name is the application name in
capitals with "DIR" appended: for an application named ``AppName``, the
environment variable is ``APPNAMEDIR``.


Manually Specifying Config Files
--------------------------------

You may want to leverage Confuse's features without :ref:`Search Paths`.
This can be done by manually specifying the YAML files you want to include,
which also allows changing how relative paths in the file will be resolved:

.. code-block:: python

    import confuse
    # Instantiates config. Confuse searches for a config_default.yaml
    config = confuse.Configuration('MyGreatApp', __name__)
    # Add config items from specified file. Relative path values within the
    # file are resolved relative to the application's configuration directory.
    config.set_file('subdirectory/default_config.yaml')
    # Add config items from a second file. If some items were already defined,
    # they will be overwritten (new file precedes the previous ones). With
    # `base_for_paths` set to True, relative path values in this file will be
    # resolved relative to the config file's directory (i.e., 'subdirectory').
    config.set_file('subdirectory/local_config.yaml', base_for_paths=True)

    val = config['foo']['bar'].get(int)


Your Application Directory
--------------------------

Confuse provides a simple helper, ``Configuration.config_dir()``, that
gives you a directory used to store your application's configuration. If
a configuration file exists in any of the searched locations, then the
highest-priority directory containing a config file is used. Otherwise,
a directory is created for you and returned. So you can always expect
this method to give you a directory that actually exists.

As an example, you may want to migrate a user's settings to Confuse from
an older configuration system such as `ConfigParser`_. Just do something
like this:

.. code-block:: python

    config_filename = os.path.join(config.config_dir(),
                                   confuse.CONFIG_FILENAME)
    with open(config_filename, 'w') as f:
        yaml.dump(migrated_config, f)

.. _ConfigParser: http://docs.python.org/library/configparser.html


Dynamic Updates
---------------

Occasionally, a program will need to modify its configuration while it's
running. For example, an interactive prompt from the user might cause
the program to change a setting for the current execution only. Or the
program might need to add a *derived* configuration value that the user
doesn't specify.

To facilitate this, Confuse lets you *assign* to view objects using
ordinary Python assignment. Assignment will add an overlay source that
precedes all other configuration sources in priority. Here's an example
of programmatically setting a configuration value based on a ``DEBUG``
constant:

.. code-block:: python

    if DEBUG:
        config['verbosity'] = 100
    ...
    my_logger.setLevel(config['verbosity'].get(int))

This example allows the constant to override the default verbosity
level, which would otherwise come from a configuration file.

Assignment works by creating a new "source" for configuration data at
the top of the stack. This new source takes priority over all other,
previously-loaded sources. You can cause this explicitly by calling the
``set()`` method on any view. A related method, ``add()``, works
similarly but instead adds a new *lowest-priority* source to the bottom
of the stack. This can be used to provide defaults for options that may
be overridden by previously-loaded configuration files.


YAML Tweaks
-----------

Confuse uses the `PyYAML`_ module to parse YAML configuration files. However, it
deviates very slightly from the official YAML specification to provide a few
niceties suited to human-written configuration files. Those tweaks are:

.. _pyyaml: http://pyyaml.org/

- All strings are returned as Python Unicode objects.
- YAML maps are parsed as Python `OrderedDict`_ objects. This means that you
  can recover the order that the user wrote down a dictionary.
- Bare strings can begin with the % character. In stock PyYAML, this will throw
  a parse error.

.. _OrderedDict: http://docs.python.org/2/library/collections.html#collections.OrderedDict

To produce a YAML string reflecting a configuration, just call
``config.dump()``. This does not cleanly round-trip YAML,
but it does play some tricks to preserve comments and spacing in the original
file.

Custom YAML Loaders
'''''''''''''''''''

You can also specify your own `PyYAML`_ `Loader` object to parse YAML
files. Supply the `loader` parameter to a `Configuration` constructor,
like this:

.. code-block:: python

    config = confuse.Configuration("name", loader=yaml.Loaded)

To imbue a loader with Confuse's special parser overrides, use its
`add_constructors` method:

.. code-block:: python

    class MyLoader(yaml.Loader):
        ...
    confuse.Loader.add_constructors(MyLoader)
    config = confuse.Configuration("name", loader=MyLoader)


Configuring Large Programs
--------------------------

One problem that must be solved by a configuration system is the issue
of global configuration for complex applications. In a large program
with many components and many config options, it can be unwieldy to
explicitly pass configuration values from component to component. You
quickly end up with monstrous function signatures with dozens of keyword
arguments, decreasing code legibility and testability.

In such systems, one option is to pass a single `Configuration` object
through to each component. To avoid even this, however, it's sometimes
appropriate to use a little bit of shared global state. As evil as
shared global state usually is, configuration is (in my opinion) one
valid use: since configuration is mostly read-only, it's relatively
unlikely to cause the sorts of problems that global values sometimes
can. And having a global repository for configuration option can vastly
reduce the amount of boilerplate threading-through needed to explicitly
pass configuration from call to call.

To use global configuration, consider creating a configuration object in
a well-known module (say, the root of a package). But since this object
will be initialized at module load time, Confuse provides a `LazyConfig`
object that loads your configuration files on demand instead of when the
object is constructed. (Doing complicated stuff like parsing YAML at
module load time is generally considered a Bad Idea.)

Global state can cause problems for unit testing. To alleviate this,
consider adding code to your test fixtures (e.g., `setUp`_ in the
`unittest`_ module) that clears out the global configuration before each
test is run. Something like this:

.. code-block:: python

    config.clear()
    config.read(user=False)

These lines will empty out the current configuration and then re-load
the defaults (but not the user's configuration files). Your tests can
then modify the global configuration values without affecting other
tests since these modifications will be cleared out before the next test
runs.

.. _unittest: http://docs.python.org/2/library/unittest.html
.. _setUp: http://docs.python.org/2/library/unittest.html#unittest.TestCase.setUp


Redaction
---------

You can also mark certain configuration values as "sensitive" and avoid
including them in output. Just set the `redact` flag:

.. code-block:: python

    config['key'].redact = True

Then flatten or dump the configuration like so:

.. code-block:: python

    config.dump(redact=True)

The resulting YAML will contain "key: REDACTED" instead of the original data.
