Release notes

v1.0.0

New features

Add new end-user devices from Base Empreinte
Add PEF impacts criteria
Add IoT device impacts
Add min/max values depending on user input completeness
Add warnings
Improvement of the completion process from CPU name
Adding around 2000 CPUs for completion
Adding utils routers (list available data for string fields, archetypes routers, etc.)
Users can now choose the impact factors to compute
Users can now add a special message to the home page of the API
Refactor and normalize routes names
CPU die is now express in mm2 instead of cm2
Refactor the allocation process based on duration

Internal changes

Facilitating the completion process
Facilitating the process of adding new devices
Facilitating the archetype process
Externalize the impact factors in a separate file
Create a config file
CPU die completion now use cpu spec file
CPU uses die_size instead of die_size_per_core

Breaking changes

Cloud routers

Before

We add one rout per cloud provider (e.g. /v1/cloud/aws)

Now

We have only one route for all cloud providers (e.g. /v1/cloud/instance)
Each route has a parameter called provider (in the url for GET requests, in the body for POST requests).

Duration & allocation

Before

Duration was a field in the usage object called hours_use_time.

{
  "usage": {
    "hours_use_time": 2,
  }
}

Allocation was a route parameter.

Now

Duration is now a route parameter. Allocation is no longer used
If not provided, we use the lifetime of the device as duration.
We compute usage impacts hover the duration and allocate embedded impacts on the duration hover the lifetime of the device.
We introduce the notion of use_time_ratio which is the proportion of time the device is used during the given duration. When a device is always used, the usage ratio is 1. When a device is never used, the usage ratio is 0.

{
  "usage": {
    "use_time_ratio": 0.5,
  }
}

Impacts format

Before

or



href="#__codelineno-2-1">"gwp": { "manufacture": 1900, "use": 260, "unit": "kgCO2eq" }, href="#__codelineno-3-1">"manufacture_impacts": { "gwp": { "value": 23.8, "unit": "kgCO2eq" }, "pe": { "value": 353, "unit": "MJ" }, "adp": { "value": 0.02, "unit": "kgSbeq" } } class="p">}
Now

Impact formats are now unified.
"manufacture" is now called "embedded"

"impacts": {
   "gwp": {
     "embedded": {
       "value": 6.68,
       "min": 6.68,
       "max": 6.68,
       "warnings": [
         "End of life is not included in the calculation"
       ]
     },
     "use": "not implemented",
     "unit": "kgCO2eq",
     "description": "Total climate change"
   },

Verbose format
Before
"USAGE": {
  ...
  "usage_impacts": {
       ...
  }
  "avg_power": {
    "value": 94.62364134445255,
    "unit": "W",
    "status": "COMPLETED",
    "source": null
  },
...
}

Now

For each component, all attributes are now at the same level in the dictionary. 
Usage impacts are now in the "impacts" dictionary
Usage attributes are now at the same level as the other attributes
Attributes may have a "min", a "max" and a "warnings" field.

  "CPU-1": {
      "impacts": {
        "gwp": {
          "embedded": {
            "value": 64.7,
            "significant_figures": 3,
            "min": 24.6,
            "max": 149,
            "warnings": [
              "End of life is not included in the calculation"
            ]
          },
          "use": {
            "value": 160,
            "significant_figures": 2,
            "min": 160,
            "max": 160
          },
          "unit": "kgCO2eq",
          "description": "Total climate change"
        }
      },
      "die_size_per_core": {
        "value": 0.47078947368421054,
        "status": "COMPLETED",
        "unit": "mm2",
        "source": "Average for Skylake",
        "min": 0.07,
        "max": 1.02
      }
      ... 
}

Contributors
@airloren
@csauge
@da-ekchajzer
@samuelrince
@dorev
@demeringo
@PierreRust
Known future requirements

Mobile and fix network impacts
Generalize the AWS process to other cloud providers
GPU impacts
Add multiple impact factors for depending on the engraving process size
Screen impacts from characteristics
Take into account the uncertainty of the impact factors
Adding a system layer

v0.2.2
What's Changed

Change CPU manufacturing impact formula by @samuelrince in https://github.com/Boavizta/boaviztapi/pull/142
reduce docker image size using distroless by @AirLoren in https://github.com/Boavizta/boaviztapi/pull/141
Modify cloud route to allow multiple cloud providers by @AirLoren in https://github.com/Boavizta/boaviztapi/pull/139

New Contributors

@AirLoren made his first contribution in https://github.com/Boavizta/boaviztapi/pull/141

Full Changelog: https://github.com/Boavizta/boaviztapi/compare/v0.2.1...v0.2.2
v0.2
Goal
v0.2 contains significant changes to the code to facilitate the addition of new features. The main additional functionality is the ability to model the power consumption of certain components, servers and cloud instances from their configuration.
Improvements

Implementing linear allocation for manufacturing impacts
Implementing fuzzy matching for string fields 
Model electrical consumption from technical characteristics and usage context for CPU, RAM, Server and Cloud instance 
Complete CPU info from CPU name
Adding source, units and status for each attributes in verbose mode
Adding utils routers (list available data for string fields)
Storing all data in CSV format
Ease the deployment of API as a serverless application
Documentation improvements
Improving CORS settings
Adding new AWS EC2 instances

Known future requirements

Mobile and fix network impacts
Screen impacts
Workplace impacts
IoT impacts
Generalize AWS process to other cloud providers
GPU impacts
Add multiple impact factors for semiconductors
Add multiple impacts factors for impacts related to electricity

v0.1.2
Bug
missing W to kW conversion
hour_electical_consumption should be given in Watt.
When avg_power was directly given (in watt) the value was used in Wh. The electrical impacts factor requires kWh.
Correction
Adding conversion from W to kW ( / 1000) when hour_electical_consumption is used with an electrical impact factor.
PR
https://github.com/Boavizta/boaviztapi/pull/93
V0.1.1
Goal
The V0.1.1 adds new CPU data and electrical impact factors.
Improvements

Adding new CPUs
Implement PE and ADP impact for use phase
Improvement of gwp impacts factor quality

Known future requirements

Mobile and fix network impacts
Screen impacts
Workplace impacts
IoT impacts
Generalize AWS process to other cloud providers

v0.1
Goal
The V0.1.0 introduces the notions of archetypes, verbose and units. An implementation of AWS instances impacts have been implemented. Impact of usage have also been developed.
Functionalities

Retrieve the impacts of AWS instances
Retrieve the impacts of server archtypes
Retrieve usage imapcts (GWP only) of usage
Verbose option
Bug fix
Work on documentation

Known future requirements

Mobile and fix network impacts
Screen impacts
Workplace impacts
IoT impacts
Generalize AWS process to other cloud providers

V0
Goal
The V0 is the MVP of Boavizta tools api.
It aims at giving access to the server bottom-up methodology measuring the scope 3 of servers explain in this article :
https://boavizta.cmakers.io/blog/numerique-et-environnement-comment-evaluer-l-empreinte-de-la-fabrication-d-un-serveur-au-dela-des-emissions-de-gaz-a-effet-de-se?token=2112aecb183b1b5d27e137abc61e0f0d39fabf99
Project setup

Setup python project (fastAPI)
Setup project test (pytest)
Setup project documentation (mkdocs)
Setup CI/CD (gitworkflow - git repository)
Creation of the theoretical architecture

Functionalities

Retrieve the manufacture impact of components from its characteristics
Retrieve the manufacture impact of servers from its characteristics with the bottom-up methodology
Complete the server or component characteristic if incomplete data are sent by the user

Known future requirements

Bug fix
Returns a verbose object (hypothesis, modify datas, calculation steps)
Integrate Boavizta database
Implement new devices
Support use case implementations
Implement scope 1 & 2