rename replace_none -> replace_none_str

custom_components/adaptive_lighting/__init__.py

@@ -15,10 +15,10 @@ hues. Hormone production, brainwave activity, mood and wakefulness are
 just some of the cognitive functions tied to cyclical natural light.
 http://en.wikipedia.org/wiki/Zeitgeber
 
-Here's some further reading:
+Further reading:
 
-http://www.cambridgeincolour.com/tutorials/sunrise-sunset-calculator.htm
-http://en.wikipedia.org/wiki/Color_temperature
+- http://www.cambridgeincolour.com/tutorials/sunrise-sunset-calculator.htm
+- http://en.wikipedia.org/wiki/Color_temperature
 
 Technical notes: I had to make a lot of assumptions when writing this app
 *   There are no considerations for weather or altitude, but does use your

custom_components/adaptive_lighting/const.py

@@ -100,7 +100,7 @@ def maybe_coerce(key, validation):
     return validation
 
 
-def replace_none(value, replace_with=None):
+def replace_none_str(value, replace_with=None):
     """Replaces "None" -> replace_with."""
     return value if value != NONE_STR else replace_with
 
@@ -112,7 +112,7 @@ validation_tuples = [
 
 _DOMAIN_SCHEMA = vol.Schema(
     {
-        vol.Optional(key, default=replace_none(default, vol.UNDEFINED)): validation
+        vol.Optional(key, default=replace_none_str(default, vol.UNDEFINED)): validation
         for key, default, validation in validation_tuples
     }
 )

custom_components/adaptive_lighting/switch.py

@@ -79,7 +79,7 @@ from .const import (
     SUN_EVENT_MIDNIGHT,
     SUN_EVENT_NOON,
     VALIDATION_TUPLES,
-    replace_none,
+    replace_none_str,
 )
 
 _SUPPORT_OPTS = {
@@ -146,7 +146,7 @@ def validate(config_entry):
     data = deepcopy(defaults)
     data.update(config_entry.options)  # come from options flow
     data.update(config_entry.data)  # all yaml settings come from data
-    data = {key: replace_none(value) for key, value in data.items()}
+    data = {key: replace_none_str(value) for key, value in data.items()}
     for key, (validate, _) in EXTRA_VALIDATION.items():
         value = data.get(key)
         if value is not None: