Details
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Type:
Story
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Status: Done
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Resolution: Done
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Fix Version/s: None
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Component/s: None
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Labels:None
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Story Points:7
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Epic Link:
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Team:SQuaRE
Description
As part of the migration of the SQuaSH API to Flask we need an mvp project with the packages and extensions defined in DM-12191 including a test client to exercise the API.
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Activity
| Field | Original Value | New Value |
|---|---|---|
| Epic Link |
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| Assignee | Angelo Fausti [ afausti ] |
| Summary | API acceptance test suite | Implement unit tests and improve test coverage for the squash-api |
| Summary | Implement unit tests and improve test coverage for the squash-api | Implement unit tests and improve test coverage for the SQuaSH REST API |
| Description | We need a squash API acceptance test suite that can be run against a live squash instance that exercises the the entire REST API. It should use "real world" fixture data include the large (>50MiB) HSC measurement data set. |
We need a squash API acceptance test suite that can be run against a live squash instance that exercises the the entire REST API. It should use for example "real world" fixture data include the large (>50MiB) HSC measurement data set.
There are interesting options like {{django-nose}} package see |
| Story Points | 4.2 | |
| Description |
We need a squash API acceptance test suite that can be run against a live squash instance that exercises the the entire REST API. It should use for example "real world" fixture data include the large (>50MiB) HSC measurement data set.
There are interesting options like {{django-nose}} package see |
We need a squash API acceptance test suite that can be run against a live squash instance that exercises the the entire REST API. It should use for example "real world" fixture data include the large (>50MiB) HSC measurement data set.
There are interesting options like {{django-nose}} package see for instance: https://www.safaribooksonline.com/library/view/building-restful-python/9781788620154/video8_1.html |
| Summary | Implement unit tests and improve test coverage for the SQuaSH REST API | Implement tests for the SQuaSH REST API |
| Description |
We need a squash API acceptance test suite that can be run against a live squash instance that exercises the the entire REST API. It should use for example "real world" fixture data include the large (>50MiB) HSC measurement data set.
There are interesting options like {{django-nose}} package see for instance: https://www.safaribooksonline.com/library/view/building-restful-python/9781788620154/video8_1.html |
We need a squash API acceptance test suite that can be run against a live squash instance that exercises the the entire REST API. It should use for example "real world" fixture data include the large (>50MiB) HSC measurement data set.
Since we are migrating the SQuaSH API to Flask I am looking at other options like Postman and Newman to implement and execute tests. |
| Status | To Do [ 10001 ] | In Progress [ 3 ] |
| Description |
We need a squash API acceptance test suite that can be run against a live squash instance that exercises the the entire REST API. It should use for example "real world" fixture data include the large (>50MiB) HSC measurement data set.
Since we are migrating the SQuaSH API to Flask I am looking at other options like Postman and Newman to implement and execute tests. |
Since we are migrating the SQuaSH API to Flask I am looking at other options like Postman and Newman to implement and execute tests. |
| Summary | Implement tests for the SQuaSH REST API | Implement a minimal viable REST API in Flask with a test client |
| Description | Since we are migrating the SQuaSH API to Flask I am looking at other options like Postman and Newman to implement and execute tests. |
As part of the migration of the SQuaSH API to Flask we need an mvp project with the packages and extensions defined in |
| Story Points | 4.2 | 7 |
- Implemented a very simple model with user, metrics and measurements tables unsing flask-sqlalchemy
- Implemented the corresponding API resources using flask-restful with get, post, update and delete methods when applicable
- Implemented token authentication using flask-jwt
- Implemented a test client that instantiate the app with the testing configuration, create an empty database, add a test user, get the authentication token, execute the tests and tear down the testing setup
- Testing the JSON data type on MySQL 5.7 by adding a data field in the measurements model
Test client output example:
$ coverage run --source=app test.py
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test_measurement (tests.tests.TestAPI) ... ok
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test_metric (tests.tests.TestAPI) ... ok
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test_user (tests.tests.TestAPI) ... ok
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----------------------------------------------------------------------
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Ran 3 tests in 1.025s
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OK
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Name Stmts Miss Branch BrPart Cover
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----------------------------------------------------------------
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app/__init__.py 22 0 0 0 100%
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app/auth.py 8 0 2 1 90%
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app/config.py 19 0 0 0 100%
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app/db.py 2 0 0 0 100%
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app/models.py 68 1 4 1 97%
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app/resources/__init__.py 0 0 0 0 100%
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app/resources/measurement.py 37 4 8 2 82%
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app/resources/metric.py 26 5 8 3 76%
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app/resources/user.py 29 5 8 1 78%
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----------------------------------------------------------------
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TOTAL 211 15 30 8 89%
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Coverage.py warning: No data was collected. (no-data-collected)
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Merged this initial implementation https://github.com/lsst-sqre/squash-rest-api/pull/1
| Resolution | Done [ 10000 ] | |
| Status | In Progress [ 3 ] | Done [ 10002 ] |
These are the main resources I'm using for implementing the REST API in Flask:
REST APIs with Flask and Python:
Developing RESTful APIs with Python and Flask:
Building RESTful Python Web Services: