Welcome to SivNorm’s documentation!¶
API pour nettoyer les champs marque/modèle d’une carte grise en leur affectant une référence.
Clean car make and model using a reference table.
Structure¶
├── docker-compose.yml
├── docs <- Sphinx documentation folder
│ ├── build
│ ├── make.bat
│ ├── Makefile
│ └── source
├── dss
│ ├── caradisiac_marque_modele.csv
│ ├── esiv_caradisiac_marque_modele_genre.csv
│ └── esiv_marque_modele_genre.csv
├── artifacts <- Env variables definition file
├── Makefile <- Orchestring commands
├── README.md <- Top-level README for developers using this project
├── setup.py
├── sivnorm <- Python application folder
│ ├── app.py
│ ├── __init__.py
│ ├── process.py
│ └── __pycache__
└── tests <- Unit test scripts
├── check.csv
├── check.py
├── README.md
└── test_small.csv
Installation¶
This module can be installed locally using docker compose
Install docker¶
sudo apt-get remove docker docker-engine docker.io
sudo apt-get update
sudo apt-get install \
apt-transport-https \
ca-certificates \
curl \
software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo add-apt-repository \
"deb [arch=amd64] https://download.docker.com/linux/ubuntu \
$(lsb_release -cs) \
stable"
sudo apt-get update
sudo apt-get install docker-ce docker-ce-cli containerd.io
sudo usermod -aG docker $USER
Install docker-compose¶
sudo curl -L "https://github.com/docker/compose/releases/download/1.23.0/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
sudo chmod +x /usr/local/bin/docker-compose
sudo ln -s /usr/local/bin/docker-compose /usr/bin/docker-compose
Deploy aws lambda function¶
AWS SAM is used to deploy lambda application. These functions have been compiled in the Makefile
make sam_build
make sam_package
make sam_deploy
API¶
-
GET/clean¶ Clean brand and model field
- Query Parameters
marque (string) – Vehicle brand (eg: Renault)
modele (string) – Vehicle model (eg: Clio)
- Status Codes
200 OK – Success
- Response JSON Object
marque (string) – Cleaned brand
modele (string) – Cleaned model
-
GET/norm/{table_ref_name}¶ Normalize a single brand and model using a defined referential table
- Parameters
table_ref_name (string) – Reference table [siv,cardisiac,siv_caradisiac]
- Query Parameters
marque (string) – Vehicle brand (eg: Renault)
modele (string) – Vehicle model (eg: Clio)
- Status Codes
200 OK – Success
- Response JSON Object
marque (string) – Matched brand
modele (string) – Matched model
score (number) – Global matching score. Combination of score_marque and score_modele
score_marque (integer) – Matching score for brand
score_modele (integer) – Matching score for model
-
POST/norm/{table_ref_name}¶ Normalize a table of brand and model using a defined referential table
- Parameters
table_ref_name (string) – Reference table [siv,cardisiac,siv_caradisiac]
- Status Codes
200 OK –
CSV file containing matching brand model and score like:
RENAULT,CLIO,1.0 RENAULT,CLIO,0.945 AUDI, TTS,1.0 RENAULT,CLIO,0.945 RENAULT,CLIO,0.95 RENAULT,CLIO,1.0
Functions Documentation¶
Application modules
Flask application¶
-
class
app.Clean(api=None, *args, **kwargs)¶ Docstring for MyClass.
-
get()¶ Clean brand and model field
-
-
class
app.Custom_API(app=None, version='1.0', title=None, description=None, terms_url=None, license=None, license_url=None, contact=None, contact_url=None, contact_email=None, authorizations=None, security=None, doc='/', default_id=<function default_id>, default='default', default_label='Default namespace', validate=None, tags=None, prefix='', ordered=False, default_mediatype='application/json', decorators=None, catch_all_404s=False, serve_challenge_on_401=False, format_checker=None, **kwargs)¶ -
property
specs_url¶ The Swagger specifications absolute url (ie. swagger.json)
- Return type
str
-
property