Skip to main content

Schul-Cloud Search API

Project description

Build Status Python Package Index Dockerhub Automated Build Status First Timers

These are the tests for the Schul-Cloud search API. You can read motivation blog post about

  • common tests for all search engines

  • testing during live deployment

Installation

You can install the tests by installing Python version 3 and pip. Then, you run the installation from the command line:

pip install --user schul-cloud-search-tests

Installation for Development

If you would like to contribute code to this repository, you can clone it first.

git clone https://github.com/schul-cloud/schul_cloud_search_tests.git
cd schul_cloud_search_tests

Install the required packages for Python:

pip3 install --user -r requirements.txt pip-tools==1.6.5

Note that if you would like to change the requirements, please edit the requirements.in file and run this command to update the dependencies:

pip-compile --output-file requirements.txt requirements.in

Specification

The idea is that these tests run in between your search client and your search engine or search adapter. You use the test interface instead of your search engine interface to run checks on every request the client makes:

  • Is the client request formulated correctly?

  • Is the server response folmulated correctly?

These cases can be defined and are defined:

  • When the client issues a successful request and the server responds correctly, the request is forwarded, optionally including a note that the tests passed.

  • When the client issues a malformed request, HTTP error 400 is returned including the information which tests did not pass. The request is forwarded to the server and the response is expected to be 400, too.

  • When the client issues a correct request, and the server response is malformed, then HTTP error 409 is returned including a list of error descriptions of the mistakes made by the server.

To make the decisions transparent, the client request and the server response are included in the error reponses.

Usage as Proxy

Suppose you have a server running on http://localhost:1234/v1/search/. You can tun the search engine tests as a proxy on port 8080 like this:

python3 -m schul_cloud_search_tests.proxy http://localhost:1234/v1/search 8080 /endpoint/

Now, all your requests to http://localhost:8080/endpoint/ will be forwarded to http://localhost:1234/v1/search.

When you are done, you can visit http://localhost:8080/stop to stop the server or run this command:

python3 -m schul_cloud_search_tests.stop 8080

The return code is zero (success) if all tests of all requests passed. If one test fails, it is a number greater than zero.

Note that the defaults are as follows. The command in each line is the same.

python3 -m schul_cloud_search_tests.proxy http://localhost:8080/v1/search 8081 /v1/search
python3 -m schul_cloud_search_tests.proxy http://localhost:8080/v1/search 8081
python3 -m schul_cloud_search_tests.proxy http://localhost:8080/v1/search
python3 -m schul_cloud_search_tests.proxy

Usage as Tests

In case you have a search engine which should be tested at the URL, you can run tests against it with the following command

python3 -m schul_cloud_search_tests.search http://localhost:8080/v1/search \
           --query "Q=einstein" --query "Q=test&page[offset]=20"

The tests test the following:

  • There is a search engine running at http://localhost:8080/v1/search

  • These queries Q=einstein and Q=test&page[offset]=20 are handled correctly.

  • Additional tests are run wich test correct and malformed queries, see Issue 6.

The return status of the tests is zero if all tests passed, otherwise a positive number.

Development Process

The idea is stated in the motivation blog post. We can use the tests to test the search engines. However, the tests can become complex and must be tested themselves. Therefore, the following development process is proposed.

  1. Have a look at the specification:

    The specification is the most important document. It determines what needs to be tested.

  2. Implement tests according to examples of the specification. These tests are located in the schul_cloud_search_tests/tests folder. They test how you would like to have the search proxy respond to the different valid and invalid requests.

  3. Make the tests run.

Further Reading


You can edit this document on Github and check it with this editor.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

schul_cloud_search_tests-1.0.96.tar.gz (24.3 kB view details)

Uploaded Source

Built Distribution

schul_cloud_search_tests-1.0.96-py3-none-any.whl (36.9 kB view details)

Uploaded Python 3

File details

Details for the file schul_cloud_search_tests-1.0.96.tar.gz.

File metadata

File hashes

Hashes for schul_cloud_search_tests-1.0.96.tar.gz
Algorithm Hash digest
SHA256 9ca136e6b90a43a37d921b129bc2c8fa0cd1da446fa25a47fde1bbd27d658ce3
MD5 a0ac20d21ee7a267dd7ed33155a350e4
BLAKE2b-256 f7adbef60ab335b7e3f9c1481c507d92ac204bd45e3de045f13d46886cdffff3

See more details on using hashes here.

File details

Details for the file schul_cloud_search_tests-1.0.96-py3-none-any.whl.

File metadata

File hashes

Hashes for schul_cloud_search_tests-1.0.96-py3-none-any.whl
Algorithm Hash digest
SHA256 d008445d216074478b0121436ae51a31d602be8c43cbf89de13e54f9fd4d1f95
MD5 586b2f300ddc14805fc26d335c7127ac
BLAKE2b-256 9ec0e2a475bf109c25cb69cc32765216023e39804183cffb7afc43211478102c

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page