Envresolver is a Python library for parsing environment variables to common Python datatypes. Environment variables are only accessible as pure text (string) typed variables and thus need some manipulation to transform into any other types. EnvResolver class provides a nifty way of parsing the current environment according to given specifications.

Install with pip: pip install envresolver

• str
• bool
• int
• float
• list holding any of the supported types
• Json
• XML
• datetime

Envresolver is a lightweight alternative to other environment parsers and customizable by-design. Adding support for new types is ultra-simplified and does not need any source modifications of the library itself.

All variables to-be-resolved must be specified with a supported type when using EnvResolver. EnvResolver then inspects all the specified variables and tries to parse an environment variable with the same name to the given type format. For example, to parse simple string values:

from envresolver import EnvResolver

r = EnvResolver()
r.add_variable("var")
r.resolve()

If an environment variable var was present in the current environment, it can be accessed after resolving by a special namespace member ns or by an explicit method getr.

r.ns.var
# Or
r.getr("var")

Additionally, variables can also be fetched from the current environment without pre-calculated resolving. This is suitable for simple variables and values that can change constantly:

from envresolver import EnvResolver

r = EnvResolver()
r.get("var")

User can also supply default values to all requests:

r.add_variable("var2", default="default_value")
# Or
r.get("var2", default="default_value")

As stated before, EnvResolver also supports automated type conversions for environment variables. Variable types can be specified as shown:

r.add_variable("var", t=int, default=-1)
# Or
r.get("var", t=int, default=-1)

Let's imagine the current environment would hold the variable var with a value of "5". By running EnvResolver.resolve, it would be automatically parsed. However, if the environment variable var would hold an incompatible value, "_" as an example, the parsing would fail and r.var would hold the default value, if one was given:

from envresolver import EnvResolver

# export var=5
r = EnvResolver()
r.add_variable("var", t=int, default=-1)
r.resolve()
r.ns.var  # 5

# export var=_
r = EnvResolver()
r.add_variable("var", t=int, default=-1)
r.resolve()
r.ns.var  # -1

EnvResolver currently supports also some more advanced types of variables, such as lists, Json and XML. Lists have full support of type hinting and will try to convert all elements accordingly:

from typing import List
from envresolver import EnvResolver

# export my_list="1,2,3,4"
r = EnvResolver()
r.add_variable("my_list", t=List[int])
r.resolve()
r.ns.my_list  # [1, 2, 3, 4]

Json and XML are supported via custom type notations stored in envresolver.Types. Json and XML will be parsed using Pythons built-in json and xml modules. Json parsing will output native python lists/dicts and XML results will be of type xml.etree.ElementTree.Element. Here is an example on Json parsing:

from envresolver import EnvResolver, Types

# export json='{"key": "val"}'
r = EnvResolver()
r.add_variable("json", t=Types.Json)
r.resolve()
r.ns.json  # {"key": "val"}

Date objects are supported via Pythons built-in datetime module. User can specify in which format the date strings are expected, with the default being %Y-%m-%d %H:%M:%S. Here is an example:

import datetime
from envresolver import EnvResolver

# export mydate="2021-01-01 12:34:56"
r = EnvResolver()
r.add_variable("mydate", datetime.datetime)
r.resolve()
r.ns.mydate # datetime.datetime -object with the correct time

Parsing certain advaced types, such as datetime objects or lists, relies on additional information regarding the data format. List parsing needs to know the list separator character and datetime conversions rely on certain date formats. These can be configured either at EnvResolver initialization or afterwards using the methods set_list_separator and set_datetime_format.

Users can supply EnvResolver with custom parsers as well as override existing ones. Below is an example of using a custom parser for reading data into a user-defined class:

from envresolver import EnvResolver


class MyData:
    def __init__(self, a, b):
        self.a = a
        self.b = b


def my_data_converter(e: str):
    s = e.split(".")

    # Raise ValueError if the given 
    # environment variable is in 
    # wrong format
    if len(s) != 2:
        raise ValueError

    # Return parsed data
    return MyData(a=s[0], b=s[1])


# export data="john.smith"
r = EnvResolver()
r.add_converter(MyData, my_data_converter)
r.add_variable("data", t=MyData)
r.resolve()
r.ns.data  # MyData(a = "john", b = "smith")