Skip to main content

No project description provided

Project description

speckenv because a speck is a synonym for a dot and because Speck is awesome.



Read the settings contained in ./.env into os.environ:

from speckenv import read_speckenv


Note that read_speckenv uses os.environ.setdefault to set new values, which means that if a particular key exists more than once in the file the first value is retained, not the last.

If the file is named differently or resides in a different path, pass the full path as first argument to read_speckenv.

Read individual values:

from speckenv import env

# Standard usage:

# Fallback if SETTING2 does not exist:
SETTING2 = env("SETTING2", default="bla")

# Fail hard if missing:
SETTING3 = env("SETTING3", required=True)

# Coerce the value before returning it (coercion is also applied to
# default values):
SETTING4 = env(
    coerce=lambda value: date(*(int(part) for part in value.split("-"))),

The following values are evaluated as Python literals, therefore coercing values may be useful less often than you might think:

BOOL=True  # And False, None etc.
SWEET_HOME=["localhost", ""]

Additional whitespace around the equals sign is supported. Empty lines and lines starting with a # are ignored:


You shouldn’t use comments in lines though. They sometimes work by accident but it’s a bad idea.

If a value looks like a Python type but you want to load it as a string you have to use coercion, e.g.

NUMBER_AS_STRING = env("NUMBER", coerce=str)

# Alternatively, read the value directly from os.environ:

Custom mapping instead of os.environ

It may be useful to use a mapping separate from os.environ. This is easily possible by overriding the default mapping argument:

from speckenv import env, read_speckenv

mapping = {}
read_speckenv("file_with_variables.env", mapping=mapping)
setting1 = env("SETTING1", mapping=mapping)

Django support

speckenv comes with a few utilities for configuring Django using environment variables. These are all pure functions without any side effects and no dependency on their environment. They are only bundled with speckenv because they are useful and because it’s convenient to do so.

Many other projects exist which already do this but speckenv_django is different in that it only covers interesting settings. Also, the implementation doesn’t add monkey patches to urllib.parse.

speckenv doesn’t depend on Django, if you don’t want to use Django or the speckenv_django module you’re not paying anything besides a few KiB on the harddisk.


Covers configuring a Redis, locmem or dummy cache backend with optional authentication credentials. The Redis configuration only supports Django 4 or better. redis:// and hiredis:// are equivalent since recent enough versions of redis-py automatically select the hiredis parser if it is available.

from speckenv import env
from speckenv_django import django_cache_url

# CACHE_URL=hiredis://localhost:6379/1/?key_prefix=example_com"
CACHES = {"default": django_cache_url(env("CACHE_URL", default="locmem://"))}
# NOTE! locmem:// may be a bad default, but that's up to you really.


Covers configuring a PostgreSQL, PostGIS or sqlite database engine with authentication credentials.

from speckenv import env
from speckenv_django import django_database_url

# DATABASE_URL=postgres://localhost:5432/example_com
DATABASES = {"default": django_database_url(env("DATABASE_URL", required=True))}


Covers configuring an email backend. Known backends are smtp://, submission:// (same as smtp:// but with TLS and a default port of 587), locmem://, console:// and dummy:.

The utility also supports explicitly requesting SSL (?ssl=true), TLS (?tls=true), SMTP timeouts (?timeout=10) and setting a DEFAULT_FROM_EMAIL address (?

from speckenv import env
from speckenv_django import django_email_url

# DATABASE_URL=smtp://
    globals().update(django_email_url(env("EMAIL_URL", default="console://")))
    globals().update(django_email_url(env("EMAIL_URL", default="smtp://")))

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

speckenv-4.0.tar.gz (6.6 kB view hashes)

Uploaded source

Built Distribution

speckenv-4.0-py3-none-any.whl (7.2 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page