Added initial interface for fetching inferred section modes #937
Conversation
- Reused implementation done by TTAlex and incorporated into section_queries.py. - Developed the test cases under TestSectionQueries.py by first generating the required sections-users list data.
|
@MukuFlash03 for the record:
This is not correct. It may seem that way when you focus on the server, but in the end to end system, the UUID is created when the user registers (aka signs up) using the app. All data in the system is then associated with the UUID. |
| # Fetching the timeseries entries containing both raw data and analysis data after running intake pipeline | ||
| ts_agg = esta.TimeSeries.get_aggregate_time_series() |
There was a problem hiding this comment.
for clarification: this doesn't actually fetch the user entries - it just fetches the appropriate access layer.
| edb.get_analysis_timeseries_db().delete_many({"user_id": self.testUUID1}) | ||
| edb.get_analysis_timeseries_db().delete_many({"user_id": self.testUUID}) |
There was a problem hiding this comment.
Good job cleaning this up. I am not going to insist on it this time, but in the future, you should really put these unrelated changes into a separate commit to keep the commit history clean. You can have multiple commits in a PR, and having separate commits will keep the "git blame" more relevant.
The task is to add interface for the functionality to fetch inferred modes data given the cleaned sections and the user ids.
This is done to support this PR for the op-admin-dashboard repository for a new feature.
Reused implementation done by TTAlex and incorporated into
section_queries.py.The function is a part of
emissions/storage/decorations/section_queries.pyand can be accessed viaesdsinterface.The function takes in the
cleaned section idsand theuser idsas a list of dictionaries to the function as a parameter.This input format seems relevant as each section_id will be tied to a user_id which is generated during the intake pipeline process by storing these entries into the analysis timeseries db.
If we pass a separate list of section ids and then another list of user ids, we can zip them into a combined list but may have to check whether each section ids has a user id or vice versa.
Additionally, the initial implementation by TTAlex, used the same input format too by extracting data from the returned dataframe object.
TestSectionQueries.pyby first generating the required sections-users list by fetching the running the intake pipeline for multiple users.