Ayoub Hamidi

Creation of an API with the Python web framework FLASK that reads several .fits files sent by the Svom satellite (Franco-Chinese mission), and converts them to .json and .csv. Library used to read .fits: astropy. The second application created with the Js Angular framework consumes the .csv data sent by the API and displays them as curves according to the file type. The curves are displayed differently. The library I used is D3.js. Scientists interpret the curves representing the brightness of stars and return the star's location for a second, more precise observation if necessary. Additionally, integration of the Aladin Lite library to display star coordinates. Mission accomplished successfully!

Subject 1: Creation of an Xml2Csv converter for public procurement files. Via an XML file or a URL pointing to a public procurement XML file, the tool allows checking the order of fields, counting the number of missing fields, traversed fields, and the number of procurements. When the file conforms to a standard, the tool returns the CSV file download link; otherwise, it returns an error message. Subject 2: OpenStreetMaps Data Rapid Selection and Extraction Tool. The tool allows extracting OSM datasets through the OverPass Turbo API. The backend allows the administrator to create keys, values, themes, and queries. The Frontend allows the user to choose a dataset (Fire hydrants, defibrillators, schools, etc.), enter the commune's Insee code, a search radius, and choose whether to enrich or not enrich the dataset (add complementary fields: street, address, city, postal code, etc.). The user receives a download link and a link to retrieve the OverPass Turbo API response.

• Main objective: develop a web environment for data synchronization (DataSud Mapping).

o Sub-objective 1: Set up a back office with the Laravel framework.

o Sub-objective 2: Investigate the functioning of access to the APIDAE API.

o Sub-objective 3: Develop a POC (Proof Of Concept) for APIDAE export (transform into CSV via the DataSud Mapping back office).

o Sub-objective 4: Identify a production deployment solution.

o Sub-objective 5: Deploy DataSud Mapping into production.

o Sub-objective 6: Optional, Develop a POC (Proof Of Concept) for Musambule export.

o Sub-objective 7: Clean, document, and deploy DataSud Mapping into production.