Env to skip aqi data download in development

[smannist]

Add this line to local backend .env file to skip aqi data download in development:

ENVIRONMENT = "development"

(or anything that's not "production" really)

[codecov]

Codecov Report

Merging #299 (cec8ce2) into main (3a5931e) will decrease coverage by 1.59%.
Report is 1 commits behind head on main.
The diff coverage is 45.45%.

❗ Current head cec8ce2 differs from pull request most recent head b1015c6. Consider uploading reports for the commit b1015c6 to get more accurate results

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #299      +/-   ##
==========================================
- Coverage   80.55%   78.97%   -1.59%     
==========================================
  Files          55       55              
  Lines        1445     1460      +15     
  Branches      169      175       +6     
==========================================
- Hits         1164     1153      -11     
- Misses        257      280      +23     
- Partials       24       27       +3     

Files Changed	Coverage Δ
recommender-back/src/apis/manager.py	47.56% <33.33%> (+0.72%)	⬆️
recommender-back/src/apis/current.py	70.37% <40.00%> (-23.22%)	⬇️
...mmender-back/src/services/scoring/indoor_scorer.py	91.42% <50.00%> (-2.52%)	⬇️
...mender-back/src/services/scoring/outdoor_scorer.py	91.42% <50.00%> (-2.52%)	⬇️
recommender-back/src/apis/poi.py	93.75% <57.14%> (-6.25%)	⬇️

... and 1 file with indirect coverage changes

[JoJoensuu]

Maybe write a test to see that scoring works if air_quality is not fetched (eg. air quality is 0)?

Some nitpicking about redundant code.

Otherwise looks good and logical.

[JoJoensuu]

There's some duplicate code here that could be refactored.
For example:
`temperature = weather_data.get('temperature')
wind_speed = weather_data.get('wind_speed')
humidity = weather_data.get('humidity')
precipitation = weather_data.get('precipitation')
clouds = weather_data.get('clouds')
air_quality = weather_data.get('air_quality', 0)

data['Score'] = scorer.score(
temperature, wind_speed, humidity, precipitation, clouds, air_quality,
sunrise_time, sunset_time, current_time
)`