Goals
- Allow for scale-ability in analytics framework for SENSSOFT
- Allow for user generated python content within Distill
- Allow for processed user log data portability to different environments (e.g., visualization, other analytic environments, i.e., anaconda)
Background and strategic fit
Assumptions
- Distill will always operate as a RESTful API
Requirements
# | Title | User Story | Importance | Notes |
---|---|---|---|---|
1 | Must be able to use custom analytics with Distill | MUST HAVE | ||
2 | Must be able to call Distill from server side (for automation) and IDE | MUST HAVE | ||
3 | Must be able to accomodate different data streams (beside UserALE), either by design or through instructions for how to build custom schemas | MUST HAVE | ||
4 | Libraries must supported through pip (limited or no support for other distros in 0.2.0) | |||
5 | Support wheels, eggs for build support on Windows x64 (NO x32) | |||
6 | Requires Python 3.6 | MUST HAVE |
Questions
Below is a list of questions to be addressed as a result of this requirements document:
Question | Outcome |
---|---|
| |
2. Does Distill require a specific backend (Elastic) or can it go to Solr/Lucene | Underlying data store needs to support key value pairs |
3. How do we support Windows Users? |
|
4. How do we provide the "average" data scientist enough out of the box packages, modules to be minimally viable out of the box? | |
5. Roadmap for supporting packages and Anaconda distribution | |
6. Migrate to Django from Flask? |