Ebonite

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* Minor bugfixes

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* Deleted accidental debug 'print' call :/

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* Prebuilt flask server images for faster image build
* More and better methods in Ebonite client
* Pipelines - chain Models methods into one Model-like objects
* Refactioring of image and instance API
* Rework of pandas DatasetType: now with column types, even non-primitive (e.g. datetimes)
* Helper functions for stanalone docker build/run
* Minor bugfixes and features

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* Fixed dependency inspection to include wrapper dependencies
* Fixed s3 repo to fail with subdirectories
* More flexible way to add parameters for instance running (e.g. docker run arguments)
* Added new type of Requirement to represent unix packages - for example, libgomp for xgboost
* Minor tweaks

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* Minor fixes and examples update

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* Built Docker images and running Docker containers along with their metadata are now persisted in metadata repository
* Added possibility to track running status of Docker container via Ebonite client
* Implemented support for pushing built images to remote Docker registry
* Improved testing of metadata repositories and Ebonite client and fixed discovered bugs in them
* Fixed bug with failed transactions not being rolled back
* Fixed bug with serialization of complex models some component of which could not be pickled
* Decomposed model IO from model wrappers
* bytes are now used for binary datasets instead of file-like objects
* Eliminated build_model_flask_docker in favor of Server-driven abstraction
* Sped up PickleModelIO by avoiding ModelAnalyzer calls for non-model objects
* Sped up Model.create by calling model methods with given input data just once
* Dataset types and model wrappers expose their runtime requirements