chore(trading): update e2e test readme (#5844)
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# Trading Market-Sim End-To-End Tests
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# Trading Market-Sim End-To-End Tests
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This direcotry contains end-to-end tests for the trading application using vega-market-sim. This README will guide you through setting up your environment and running the tests.
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This directory contains end-to-end tests for the Trading application using Vega-market-sim. This guide will help you set up your environment and run the tests efficiently.
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## Prerequisites
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## Prerequisites
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- [Poetry](https://python-poetry.org/docs/#installing-with-the-official-installer)
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Ensure you have the following installed:
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- [Docker](https://www.docker.com/)
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- [Python versions ">=3.9,<3.11"](https://www.python.org/)
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## Getting Started
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- [Poetry](https://python-poetry.org/docs/#installing-with-the-official-installer) for dependency management.
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- [Docker](https://www.docker.com/) for running isolated application containers.
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- Python, versions ">=3.9,<3.11". Install from the [official Python website](https://www.python.org/).
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1. **Install Poetry**: Follow the instructions on the [official Poetry website](https://python-poetry.org/docs/#installing-with-the-official-installer).
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## Setup
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2. **Install Docker**: Follow the instructions on the [official Docker website](https://docs.docker.com/desktop/).
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3. **Install Python**: Follow the instructions on the [official Python website](https://www.python.org/)
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**ensure you install a version between 3.9 and 3.11.**
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4. **Start up a Poetry environment**: Execute the commands below to configure the Poetry environment.
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### Ensure you are in the tests folder before running commands
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### 1. Install Dependencies
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- **Poetry**: Follow the installation guide on the [official Poetry website](https://python-poetry.org/docs/#installing-with-the-official-installer).
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- **Docker**: Installation instructions are available on the [official Docker website](https://docs.docker.com/desktop/).
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- **Python**: Install a version between 3.9 and 3.11, as detailed on the [official Python website](https://www.python.org/).
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### 2. Configure Your Environment
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Ensure you're in the tests folder before executing commands.
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```bash
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```bash
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poetry shell
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poetry shell
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```
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poetry update vega-sim # Updates to the latest version of the market-sim branch
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5. **Install python dependencies**
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To make sure you are on the latest version of our market-sim branch.
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```bash
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poetry update vega-sim
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```
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```bash
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poetry install
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poetry install
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playwright install chromium # Installs necessary browsers for Playwright
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```
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```
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6. **Install Playwright Browsers**: Execute the command below to browsers for Playwright.
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### 3. Prepare Binaries and Docker Images
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```bash
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Download necessary binaries for the desired Vega version:
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playwright install chromium
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```
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7. **Download necessary binaries**:
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Use the following command within your Python environment. The `--force` flag ensures the binaries are overwritten, and the `--version` specifies the desired version. e.g. `v0.73.4`
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```bash
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```bash
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python -m vega_sim.tools.load_binaries --force --version $VEGA_VERSION
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python -m vega_sim.tools.load_binaries --force --version $VEGA_VERSION
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```
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```
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8. **Pull the desired Docker image**
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Pull Docker images for your environment:
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```bash
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- **Development**: `docker pull vegaprotocol/trading:develop`
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docker pull vegaprotocol/trading:develop
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- **Production**: `docker pull vegaprotocol/trading:main`
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```
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### 4. Build a Docker Image of Your Locally Built Trading App
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9. **Run tests**: Poetry/Python will serve the app from docker
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### Update the .env file with the correct trading image.
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```bash
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poetry run pytest
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```
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### Docker images
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Pull the desired image:
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**Testnet**
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```bash
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docker pull vegaprotocol/trading:develop
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```
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**Mainnet**
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```bash
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docker pull vegaprotocol/trading:main
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```
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Find all available images on [Docker Hub](https://hub.docker.com/r/vegaprotocol/trading/tags).
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#### Create a Docker Image of Your Locally Built Trading App
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To build your Docker image, use the following commands:
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```bash
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yarn nx build trading ./docker/prepare-dist.sh
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```
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```bash
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```bash
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./docker/prepare-dist.sh
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docker build -f docker/node-outside-docker.Dockerfile --build-arg APP=trading --build-arg ENV_NAME=stagnet1 -t vegaprotocol/trading:latest .
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docker build -f docker/node-outside-docker.Dockerfile --build-arg APP=trading --build-arg ENV_NAME=stagnet1 -t vegaprotocol/trading:latest .
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```
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```
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## Running Tests 🧪
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## Running Tests
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Before running make sure the docker daemon is running.
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Ensure the Docker daemon is running. Update the `.env` file with the correct trading image before proceeding.
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To run a specific test, use the `-k` option followed by the name of the test.
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- **Run all tests**: `poetry run pytest`
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Run all tests:
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- **Run a specific test**: `poetry run pytest -k "test_name" -s --headed`
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- **Run tests using your locally served console**:
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```bash
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In one terminal window, build and serve the trading console:
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poetry run pytest
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```bash
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yarn nx build trading
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yarn nx serve trading
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```
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Once the console is served, update the `.env` file to set `local_server=true`. You can then run your tests using the same commands as above.
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NOTE: Parallel running of tests will not work against locally served console.
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## Test Strategy and Container Cleanup
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### Strategy
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We aim for each test file to use a single Vega instance to ensure test isolation and manage resources efficiently. This approach helps in maintaining test performance and reliability.
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### Cleanup Procedure
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To ensure proper cleanup of containers after each test, use the following fixture pattern:
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```python
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@pytest.fixture
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def vega(request):
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with init_vega(request) as vega_instance:
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request.addfinalizer(lambda: cleanup_container(vega_instance))
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yield vega_instance
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```
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```
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Run a targeted test:
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## Running Tests in Parallel
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```bash
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For running tests in parallel:
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poetry run pytest -k "test_name" -s --headed
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```
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Run from anywhere:
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- **Within the e2e folder**: `poetry run pytest -s --numprocesses auto --dist loadfile`
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- **From anywhere**: `yarn trading:test:all`
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```bash
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## Troubleshooting
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yarn trading:test -- "test_name" -s --headed
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```
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Run using your locally served console:
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If IntelliSense is not working in VSCode, follow these steps:
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Within one terminal
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1. Find the Poetry environment's Python binary: `poetry run which python`
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2. In VSCode, open the command menu (`cmd + shift + p`), search for `Python: Select Interpreter`, select `Enter interpreter path`, and paste the path from step 1.
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```bash
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yarn nx build trading
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```
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```bash
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yarn nx serve trading
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```
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Once console is served you can update the .env file to have local_server to true.
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## Running Tests in Parallel 🔢
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To run tests in parallel, use the `--numprocesses auto` option. The `--dist loadfile` setting ensures that multiple runners are not assigned to a single test file.
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### From within the e2e folder:
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```bash
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poetry run pytest -s --numprocesses auto --dist loadfile
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```
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### From anywhere:
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```bash
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yarn trading:test:all
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```
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# Things to know
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If you "intellisense" isn't working follow these steps:
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1. ```bash
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poetry run which python
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```
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2. Then open the command menu in vscode (cmd + shift + p) and type `select interpreter` , press enter, select enter interpreter path press enter then paste in the output from that above command you should get the right python again
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