Henosis

Added
- Added a check that resets `models.preload_pickles` to False if the AWS S3 bucket is empty for consistency ([issue 23](https://github.com/vc1492a/henosis/issues/23)).
- Added `load_model` and `load_generators` functions, which allow users to
load a Models().SKModel() object from a running system and the generator functions
associated with that object, respectively ([issue 1](https://github.com/vc1492a/henosis/issues/1)).
- Added `delete` function, which allows users to delete a Models.SKModel()
object from a running system and the generator functions
associated with that object (if not shared with other models),
respectively ([issue 1](https://github.com/vc1492a/henosis/issues/1)).

Changed
- Migrated to Flask v1.0.2 from 0.12.2 ([issue 17](https://github.com/vc1492a/henosis/issues/17)).
- Changed the manner in which a connection object is referenced when calling
`Server()` to match the behavior when modeling ([issue 15](https://github.com/vc1492a/henosis/issues/15)).
- The manner in which API and Elasticsearch auth is specified in `config.yaml` to
correspond with the fix related to [issue 22](https://github.com/vc1492a/henosis/issues/22).

Fixed
- A behavior whereby an error in retrieving models from AWS S3 caused the application / API
server to crash. Added a while loop to check for success and continue attempting to
retrieve models from S3 until successful ([issue 19](https://github.com/vc1492a/henosis/issues/19)).
- An issue where an AWS S3 connection was being instantiated twice on server instantiation.
- An issue that was causing a timer start even if `models.refresh_pickles` is set to None or False.
- A security vulnerability that was opened by using `yaml.load` as opposed to `yaml.safe_load` ([issue 22](https://github.com/vc1492a/henosis/issues/22)).

Fixed
- A small unintended KeyError introduced when logging requests after the 0.0.9 update.

Added
- A check that creates a temporary directory needed when storing models or
tagging functions.
- Additional fields for the response from the /requestlog API endpoint,
providing a "modelsUsed" field and a "modelsWithheld" field. When *predict_probabilities*
is set to True in your configuration file, these fields provide context behind how
frequently models meet their minimum recommendation (confidence) threshold.
- Additional checks for errors in making predictions.

Changed
- The default model field return when requesting the API for recommendations. Changed
from *modelsQueried* to *modelsUsed*.

Fixed
- A deprecation warning related to the WSGI import from gevent.

Fixed
- An issue with relative imports across Henosis files, changed to absolute imports.

Added
- Added the ability to set a minimum confidence threshold that dictates when
individual models will provide recommendations, which can be useful in certain
use cases.
- Added in a timer that periodically reloads models in memory if *preload_pickles* is
set to **True** and a float or integer value (in minutes) is specified in the
instance's configuration file.
- Added a check to ensure that only models in the *pickle_jar* are checked for use
if *preload_pickles* is set to True. This ensures no error is encountered if a model
has been deployed but isn't yet in the *pickle_jar*.
- Included additional logging for improved system monitoring and debugging.

Changed
- Restructured Henosis such that server deployment and modeling classes are separated
and can be imported into a Python script or application with different imports. This
allows for easier use of Henosis by users and for better code maintainability.
*Breaks previous functionality.*

Fixed
- An issue that was causing an error when using scikit-learn's TfidfVectorizer.

Removed
- Removed pymssql requirement and functionality.

Fixed
- An issue where all X and y data (not only X_train and y_train) were resampled when upsampling or downsampling, causing
the test or validation set information to bleed into the training data.