Metadata-Version: 2.1
Name: HackDuck
Version: 0.1.0
Summary: Machine learning data flow for reproducible data science
Home-page: https://github.com/AlexandreKempf/HackDuck
Author: Alexandre Kempf
Author-email: alexandre.kempf@cri-paris.org
License: UNKNOWN
Description: # IDEAL HACKDUCK PROJECT
        
        
        Several pipelines for dataflow (Prefect):
          - nothing -> data_generation -> save to disk
          - preprocessing
          - augmentation
          - postprocessing
        
        Model handle (Pytorch & Ignite):
          - fit -> give X and Y and learn
          - evaluate -> give X and Y, predict and return metrics
          - predict -> give X, return Y
        
        Save logs and artifacts (MLflow):
          - save metrics during training (ignite)
          - save a bunch of data before and after each pipeline
        
        Run model from with a REST app (MLflow):
          - save a github folder for each project
          - can easely have predition on a bunch of data
        
        
        
        # FEATURES:
         - seed for reproducibility
         - map arguments to loop over a list
         - mlflow integration (automatic logs parameters, can log metrics or artifacts)
         - all prefect avantages
         - handle subflows
         - task bank to do basic operations
         - unit test handle by ward
        
        
        # TODO:
        [ ] map over subflows ?
        [ ] pip package for TaskBank and save commit (needed to rerun the flow)
        [ ] save python files inside mlruns/... and git them and save git commit
        [ ] being able to rerun a previous flow (save args and kwargs and output ref)
        [ ] run it in a docker
        [ ] put to prod thanks to travis CI that create the MLflow git repo
        [ ] do deep learning with it
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
