Put the carbon-txt-preview route behind a flag

[mrchrisadams]

This pull request introduces the use of feature flags to control access to the CarbonTxt preview functionality. It adds the WaffleFlagMixin to the CarbonTxtCheckView class and includes tests to ensure the feature flag works as expected.

Feature flag implementation:

• apps/accounts/admin_site.py: Added WaffleFlagMixin to CarbonTxtCheckView and set waffle_flag to "carbon-txt-preview". [1] [2]

Testing enhancements:

• apps/greencheck/tests/views/test_api_carbon_txt.py: Added override_flag import and a new test method test_carbon_txt_preview_behind_flag to verify the behavior of the CarbonTxt preview behind the feature flag. [1] [2]

Minor cleanup:

• apps/accounts/admin_site.py: Removed unnecessary whitespace in get_app_list method.

[github-actions]

Old Energy Estimation

Eco-CI Output:

Label	🖥 avg. CPU utilization [%]	🔋 Total Energy [Joules]	🔌 avg. Power [Watts]	Duration [Seconds]
Total Run (incl. overhead)	14.8396	697.994	3.07	227
checkout	7.44	3.54273	1.77	2
pip install uv wheel	7.54	3.54348	3.54	1
pip install requirements	64.332	31.4507	5.24	6
pytest	13.5638	659.457	3.07	215

🌳 CO2 Data:
City: San Jose, Lat: 37.1835, Lon: -121.7714
IP: 52.157.3.100
CO₂ from energy is: 0.231036014 g
CO₂ from manufacturing (embodied carbon) is: 0.064766234 g
Carbon Intensity for this location: 331 gCO₂eq/kWh
SCI: 0.295802 gCO₂eq / pipeline run emitted

[github-actions]

Old Energy Estimation

Eco-CI Output:

Label	🖥 avg. CPU utilization [%]	🔋 Total Energy [Joules]	🔌 avg. Power [Watts]	Duration [Seconds]
Total Run (incl. overhead)	14.0944	757.796	3.04	249
checkout	6.59	3.5169	3.52	1
pip install uv wheel	20.015	7.88134	3.94	2
pip install requirements	64.462	31.8832	5.31	6
pytest	12.9197	714.514	3.01	237

🌳 CO2 Data:
City: Chicago, Lat: 41.8874, Lon: -87.6318
IP: 172.183.122.97
CO₂ from energy is: 0.261439620 g
CO₂ from manufacturing (embodied carbon) is: 0.071043138 g
Carbon Intensity for this location: 345 gCO₂eq/kWh
SCI: 0.332483 gCO₂eq / pipeline run emitted

[github-actions]

Old Energy Estimation

Eco-CI Output:

Label	🖥 avg. CPU utilization [%]	🔋 Total Energy [Joules]	🔌 avg. Power [Watts]	Duration [Seconds]
Total Run (incl. overhead)	15.9558	712.799	3.17	225
checkout	12.37	3.71462	1.86	2
pip install uv wheel	23.7333	12.1664	4.06	3
pip install requirements	66.442	32.1486	5.36	6
pytest	14.5074	664.77	3.15	211

🌳 CO2 Data:
City: Boydton, Lat: 36.6676, Lon: -78.3875
IP: 20.55.214.246
CO₂ from energy is: 0.248766851 g
CO₂ from manufacturing (embodied carbon) is: 0.064195607 g
Carbon Intensity for this location: 349 gCO₂eq/kWh
SCI: 0.312962 gCO₂eq / pipeline run emitted

[github-actions]

Eco-CI Output:

Label	🖥 avg. CPU utilization [%]	🔋 Total Energy [Joules]	🔌 avg. Power [Watts]	Duration [Seconds]
Total Run (incl. overhead)	15.9014	698.158	3.14	222
checkout	14.64	7.58254	3.79	2
pip install uv wheel	14.62	3.79157	1.90	2
pip install requirements	63.0567	36.8203	5.26	7
pytest	14.2199	649.964	3.12	208

🌳 CO2 Data:
City: Phoenix, Lat: 33.4475, Lon: -112.0866
IP: 20.172.5.210
CO₂ from energy is: 0.237373720 g
CO₂ from manufacturing (embodied carbon) is: 0.063339665 g
Carbon Intensity for this location: 340 gCO₂eq/kWh
SCI: 0.300713 gCO₂eq / pipeline run emitted