simpleml.save_patterns package

Package for the different save patterns available Patterns are loaded into global registry on import and more can be added externally by decorating

Nomenclature -> Save Location : Save Format

• Database Storage

  • database_table: Dataframe saving (as tables in dedicated schema)
  • database_pickled: In database as a binary blob
  • database_hdf5: In database as a binary blob

• Local Filesystem Storage

  • disk_pickled: Pickled file on local disk
  • disk_hdf5: HDF5 file on local disk
  • disk_keras_hdf5: Keras formatted HDF5 file on local disk

• Cloud Storage

  • cloud_pickled: Pickled file on cloud backend
  • cloud_hdf5: HDF5 file on cloud backend
  • cloud_keras_hdf5: Keras formatted HDF5 file on cloud backend

  Supported Backends:

  • Amazon S3
  • Google Cloud Platform
  • Microsoft Azure
  • Microsoft Onedrive
  • Aurora
  • Backblaze B2
  • DigitalOcean Spaces
  • OpenStack Swift

  Backend is determined by cloud_section in the configuration file

• Remote filestore saving

  • SCP to remote server

Submodules

• simpleml.save_patterns.base module
• simpleml.save_patterns.database module
• simpleml.save_patterns.decorators module
• simpleml.save_patterns.libcloud module
• simpleml.save_patterns.local module
• simpleml.save_patterns.onedrive module