- TransparentPath : A pathlib-like way to handle paths on Google Cloud Storage. Developed by our former Lead Python Engineer Philippe Cotte.
- MailUtility : Package containing a tool to send mail and a tool to monitor a mailbox easily. Supports remote directories with TransparentPath.
- TableWriter : Class used to produce a ready-to-compile .tex file containing a table from a pandas or dask DataFrame object. Can also compile the .tex to produce a .pdf.
- PDFFactory : Class to update and/or create a PDF object, and add pages to it. Supports matplotlib.figure and tablewriter.TableWriter objects.
- HtmlMerger : Package allowing to merge all HTML files in a directory in a single file.
- Color and Style Cycler : Cycler for matplotlib. Can cycle through combination of colors and line or marker styles
- AdRubix : RubixHeatmap class for plotting complex, highly customizable heatmaps with metadata as HTML and PNG
- AdParallelEngine : A package wrapped around Dask, mpi4py and basic Python's multiprocessing libraries providing an easy way to make parallel maps
- complex : Simple package illustrating good code practices by implementing the notion of complex number. Also used as a template for creating a public Python package.
- AdTypingDecorators : Python decorators allowing to check and/or enforce types in functions' arguments based on typing hints
- mail_watcher_example : An example of mail watcher cronjob for Kubernetes
- AdAdjust : Package allowing to fit any mathematical function to (for now 1D only) data
- AdAnnealing : Package doing simulated annealing
- IFRA : Interpretable Federated Rule Algorithm
- RIPE (forked from thibaulthans/RIPE) : Implementation of a rule based prediction algorithm called RIPE
- RICE : Implementation of a rule-based prediction algorithm called RICE (Rule Induction Covering Estimator). RICE is a deterministic and interpretable algorithm, for regression problem.
- ruleskit : Package implementing all useful tools for rule-based machine learning algorithms
- AdNMTF : Non-Negative Matrix and Tensor Factorizations co-developped with our biostatistician Paul Fogel
- AdClean : A package that allows one to clean features prior to a learning process
- Elsevier Energy and AI 2022 : Repository for the Elsevier Energy and AI 2022 paper "Stress Testing Electrical Grids: Generative Adversarial Networks For Load Scenario Generation"