This accurate and comprehensive dataset encapsulates the main information published on the BOAMP website (the official journal for public procurement notices in France) from 2015 to 2023, enriched with the individual characteristics of contracting authorities and holders of public contracts. After converting the notices into a processed table, we use a machine learning algorithm to estimate the SIRETs (i.e. national identifiers) of the contracting parties, so that we can merge the open data on public procurement with individual information on public and private agents (size, legal status, main activity, geolocation...). Finally, we estimate the geolocation of foreign firms. The dataset contains about 300,000 public contracts and describes more than 1,000,000 interactions between approximately 16,000 public entities and 130,000 companies. It covers over 100 variables on the contract features, the outcome of the award procedure, the characteristics of contracting authorities and the characteristics of awarded firms.