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nizar-m a40bf10b9f run graphql tests on both http and websocket; add parallelism (close #1868 ) (#1921 )

Examples 
1)  `
pytest --hge-urls "http://127.0.0.1:8080" --pg-urls "postgresql://admin@127.0.0.1:5432/hge_tests" -vv
`
2)  `pytest --hge-urls "http://127.0.0.1:8080"   "http://127.0.0.1:8081" --pg-urls "postgresql://admin@127.0.0.1:5432/hge_tests"  "postgresql://admin@127.0.0.1:5432/hge_tests2" -vv
`
### Solution and Design
<!-- How is this issue solved/fixed? What is the design? -->
<!-- It's better if we elaborate -->
#### Reducing execution time of tests
- The Schema setup and teardown, which were earlier done per test method, usually takes around 1 sec. 
- For mutations, the model has now been changed to only do schema setup and teardown once per test class.
-  A data setup and teardown will be done once per test instead (usually takes ~10ms).
- For the test class to get this behaviour, one can can extend the class `DefaultTestMutations`. 
    - The function  `dir()` should be define which returns the location of the configuration folder.
    - Inside the configuration folder, there should be 
        - Files `<conf_dir>/schema_setup.yaml` and `<conf_dir>/schema_teardown.yaml`, which has the metadata query executed during schema setup and teardown respectively
        - Files named `<conf_dir>/values_setup.yaml` and `<conf_dir>/values_teardown.yaml`. These files are executed to setup and remove data from the tables respectively. 

#### Running Graphql queries on both http and websockets
- Each GraphQL query/mutation is run on the both HTTP and websocket protocols
- Pytests test parameterisation is used to achieve this
- The errors over websockets are slightly different from that on HTTP
   - The code takes care of converting the errors in HTTP to errors in websockets

#### Parallel executation of tests.
- The plugin pytest-xdist helps in running tests on parallel workers.
- We are using this plugin to group tests by file and run on different workers.
- Parallel test worker processes operate on separate postgres databases(and separate graphql-engines connected to these databases). Thus tests on one worker will not affect the tests on the other worker.
- With two workers, this decreases execution times by half, as the tests on event triggers usually takes a long time, but does not consume much CPU.

2019-04-08 12:52:38 +05:30

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Contributing

This guide explains how to set up the graphql-engine server for development on your own machine and how to contribute.

Pre-requisites

stack
A Postgres server (Recommended: Use docker to run a local postgres instance)
GNU Make (optional)
Node.js (v8.9+)
libpq-dev
psql
python >= 3.7 with pip3

Upgrading npm

If your npm is too old (< 5.7),

npm install -g npm@latest

sudo npm install -g npm@latest

or update your nodejs

Getting pip3

sudo apt install python3-pip

Development workflow

Fork and clone

Fork the repo on GitHub
Clone your forked repo: git clone https://github.com/<your-username>/graphql-engine
cd graphql-engine

Compile

compile console assets
```
cd console
npm ci
cd ..
```

compile the server

cd server
stack build --fast --flag graphql-engine:local-console

Run

Make sure postgres is running (Postgres >= 9.5)
Create a database on postgres
Run the binary: stack exec graphql-engine -- --database-url=<database-url> serve

database url looks like: postgres://<username>:<password>@<host>:<port>/<dbname>

Running Postgres

The easiest way is to run docker in a container

docker run -p 5432:5432 -d postgres:11.1

Test if it's running by

telnet localhost 5432

psql

You will need psql or another client

sudo apt install postgresql-client

Work

Work on the feature/fix
Add test cases if relevant

Test

Install the py-test dependencies:

pip3 install -r tests-py/requirements.txt

Make sure postgres is running
Run the graphql-engine:

stack exec graphql-engine -- --database-url=<database-url> serve --enable-console

Set the environmental variables for event-trigger tests

export EVENT_WEBHOOK_HEADER="MyEnvValue"
export WEBHOOK_FROM_ENV="http://127.0.0.1:5592"

Run tests:

cd tests-py
pytest --hge-urls http://127.0.0.1:8080 --pg-urls <database_url> -vv

Create Pull Request

Make sure your commit messages meet the guidelines.
Create a pull request from your forked repo to the main repo.
Every pull request will automatically build and run the tests.

Code conventions

This helps enforce a uniform style for all committers.

Compiler warnings are turned on, make sure your code has no warnings.
Use hlint to make sure your code has no warnings.
Use stylish-haskell to format your code.

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