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envparse-0.2.0
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Simple environment variable parsing
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | envparse-0.2.0 |
| نام | envparse |
| نسخه کتابخانه | 0.2.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Rick Harris |
| ایمیل نویسنده | rconradharris@gmail.com |
| آدرس صفحه اصلی | https://github.com/rconradharris/envparse |
| آدرس اینترنتی | https://pypi.org/project/envparse/ |
| مجوز | MIT |
envparse
========
``envparse`` is a simple utility to parse environment variables.
If you use Heroku and/or subscribe to the tenets of the
`12 Factor App <http://www.12factor.net/>`_
you'll be using a lot of environment variable-based configuration in your app.
``os.environ`` is a great choice to start off with but over time you'll find
yourself duplicating quite a bit of code around handling raw environment
variables.
``envparse`` aims to eliminate this duplicated, often inconsistent parsing
code and instead provide a single, easy-to-use wrapper.
Ideas, and code portions, have been taken from `django-environ
<https://github.com/joke2k/django-environ>`_ project but made framework
agnostic.
Installing
----------
Through PyPI::
$ pip install envparse
Manually::
$ pip install git+https://github.com/rconradharris/envparse.git
OR
$ git clone https://github.com/rconradharris/envparse && cd envparse
$ python setup.py install
Usage
-----
In your settings or configuration module, first either import the standard
parser or one with a schema::
# Standard
from envparse import env
# Schema
from envparse import Env
env = Env(BOOLEAN_VAR=bool, LIST_VAR=dict(type=list, subtype=int))
``env`` can then be called in two ways:
* Type explicit: ``env('ENV_VAR_NAME', type=TYPE, ...)``
* Type implicit (for Python builtin types only): ``env.TYPE('ENV_VAR_NAME', ...)``
If type is not specified, explicitly or implicitly, then the default
type is ``str``.
Casting to a specified type::
# Environment variable: MAIL_ENABLED=1
mail_enabled = env('MAIL_ENABLED', type=bool)
# OR mail_enabled = env.bool('MAIL_ENABLED')
assert mail_enabled is True
Casting nested types::
# Environment variable: FOO=1,2,3
foo = env('FOO'), subtype=int)
# OR: foo = env('FOO', type=list, subtype=int)
# Note that there is no way to implicitly call subtypes.
assert foo == [1, 2, 3]
Specifying defaults::
# Environment variable MAX_ROWS has not been defined
max_rows = env.int('MAX_ROWS', default=100)
assert max_rows == 100
Proxying values, useful in Heroku for wiring up the environment variables they
provide to the ones that your app actually uses::
# Environment variables: MAILGUN_SMTP_LOGIN=foo,
# SMTP_LOGIN='{{MAILGUN_SMTP_LOGIN}}'
smtp_login = env('SMTP_LOGIN')
assert smtp_login == 'foo'
Now if you switch to using Mandrill as an email provider, instead of having to
modify your app, you can simply make a configuration change::
SMTP_LOGIN='{{MANDRILL_UESRNAME}}'
There are also a few convenience methods:
* ``env.json``: parses JSON and returns a dict.
* ``env.url``: parses a url and returns a ``urlparse.ParseResult`` object.
Type specific notes:
* list: the expected environment variable format is ``FOO=1,2,3`` and may
contain spaces between the commas as well as preceding or trailing whitespace.
* dict: the expected environment variable format is ``FOO='key1=val1,
key2=val2``. Spaces are also allowed.
* json: a regular JSON string such as ``FOO='{"foo": "bar"}'`` is expected.
Schemas
~~~~~~~
Define a schema so you can only need to provide the type, subtype, and defaults
once::
# Environment variables: MAIL_ENABLED=0, LIST_INT='1,2,3'
# Bind schema to Env object to get schema-based lookups
env = Env(MAIL_ENABLED=bool, SMTP_LOGIN=dict(type=str, default='foo'),
LIST_INT=dict(type=list, subtype=int))
assert env('MAIL_ENABLED') is False
assert env('SMTP_LOGIN') == 'foo' # Not defined so uses default
assert env('LIST_INT') == [1, 2, 3]
The ``Env`` constructor takes values in the form of either: ``VAR_NAME=type``
or ``VAR_NAME=dict`` where ``dict`` is a dictionary with either one or more of
the following keys specified: ``type``, ``subtype``, ``default``.
Pre- and Postprocessors
~~~~~~~~~~~~~~~~~~~~~~~
Preprocessors are callables that are run on the environment variable string
before any type casting takes place::
# Environment variables: FOO=bar
# Preprocessor to change variable to uppercase
to_upper = lambda v: v.upper()
foo = env('FOO', preprocessor=to_upper)
assert foo == 'BAR'
Postprocessors are callables that are run after the type casting takes place.
An example of one might be returning a datastructure expected by a framework::
# Environment variable: REDIS_URL='redis://:redispass@127.0.0.1:6379/0'
def django_redis(url):
return {'BACKEND': 'django_redis.cache.RedisCache',
'LOCATION': '{}:{}:{}'.format(url.hostname, url.port, url.path.strip('/')),
'OPTIONS': {'PASSWORD': url.password}}
redis_config = env('REDIS_URL', postprocessor=django_redis)
assert redis_config == {'BACKEND': 'django_redis.cache.RedisCache',
'LOCATION': '127.0.0.1:6379:0', 'OPTIONS': {'PASSWORD': 'redispass'}}
Environment File
~~~~~~~~~~~~~~~~
Read from a .env file (line delimited KEY=VALUE)::
# This recurses up the directory tree until a file called '.env' is found.
env.read_env()
# Manually specifying a path
env.read_env('/config/.myenv')
# Values can be read as normal
env.int('FOO')
Tests
-----
.. image:: https://secure.travis-ci.org/rconradharris/envparse.png?branch=master
To run the tests install tox::
pip install tox
Then run them with::
make test
نحوه نصب
نصب پکیج whl envparse-0.2.0:
pip install envparse-0.2.0.whl
نصب پکیج tar.gz envparse-0.2.0:
pip install envparse-0.2.0.tar.gz