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# Trading Market-Sim End-To-End Tests
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.
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.
## Prerequisites
- [Poetry](https://python-poetry.org/docs/#installing-with-the-official-installer)
- [Docker](https://www.docker.com/)
- [Python versions ">=3.9,<3.11"](https://www.python.org/)
Ensure you have the following installed:
## Getting Started
- [Poetry](https://python-poetry.org/docs/#installing-with-the-official-installer) for dependency management.
- [Docker](https://www.docker.com/) for running isolated application containers.
- Python, versions ">=3.9,<3.11". Install from the [official Python website](https://www.python.org/).
1. **Install Poetry**: Follow the instructions on the [official Poetry website](https://python-poetry.org/docs/#installing-with-the-official-installer).
2. **Install Docker**: Follow the instructions on the [official Docker website](https://docs.docker.com/desktop/).
3. **Install Python**: Follow the instructions on the [official Python website](https://www.python.org/)
**ensure you install a version between 3.9 and 3.11.**
4. **Start up a Poetry environment**: Execute the commands below to configure the Poetry environment.
## Setup
### Ensure you are in the tests folder before running commands
### 1. Install Dependencies
- **Poetry**: Follow the installation guide on the [official Poetry website](https://python-poetry.org/docs/#installing-with-the-official-installer).
- **Docker**: Installation instructions are available on the [official Docker website](https://docs.docker.com/desktop/).
- **Python**: Install a version between 3.9 and 3.11, as detailed on the [official Python website](https://www.python.org/).
### 2. Configure Your Environment
Ensure you're in the tests folder before executing commands.
```bash
poetry shell
```
5. **Install python dependencies**
To make sure you are on the latest version of our market-sim branch.
```bash
poetry update vega-sim
```
```bash
poetry update vega-sim # Updates to the latest version of the market-sim branch
poetry install
playwright install chromium # Installs necessary browsers for Playwright
```
6. **Install Playwright Browsers**: Execute the command below to browsers for Playwright.
### 3. Prepare Binaries and Docker Images
```bash
playwright install chromium
```
7. **Download necessary binaries**:
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`
Download necessary binaries for the desired Vega version:
```bash
python -m vega_sim.tools.load_binaries --force --version $VEGA_VERSION
```
8. **Pull the desired Docker image**
```bash
docker pull vegaprotocol/trading:develop
```
9. **Run tests**: Poetry/Python will serve the app from docker
### Update the .env file with the correct trading image.
```bash
poetry run pytest
```
### Docker images
Pull the desired image:
**Testnet**
```bash
docker pull vegaprotocol/trading:develop
```
**Mainnet**
```bash
docker pull vegaprotocol/trading:main
```
Find all available images on [Docker Hub](https://hub.docker.com/r/vegaprotocol/trading/tags).
#### Create a Docker Image of Your Locally Built Trading App
To build your Docker image, use the following commands:
```bash
yarn nx build trading ./docker/prepare-dist.sh
```
Pull Docker images for your environment:
- **Development**: `docker pull vegaprotocol/trading:develop`
- **Production**: `docker pull vegaprotocol/trading:main`
### 4. Build a Docker Image of Your Locally Built Trading App
```bash
./docker/prepare-dist.sh
docker build -f docker/node-outside-docker.Dockerfile --build-arg APP=trading --build-arg ENV_NAME=stagnet1 -t vegaprotocol/trading:latest .
```
## Running Tests 🧪
## Running Tests
Before running make sure the docker daemon is running.
Ensure the Docker daemon is running. Update the `.env` file with the correct trading image before proceeding.
To run a specific test, use the `-k` option followed by the name of the test.
Run all tests:
- **Run all tests**: `poetry run pytest`
- **Run a specific test**: `poetry run pytest -k "test_name" -s --headed`
- **Run tests using your locally served console**:
```bash
poetry run pytest
In one terminal window, build and serve the trading console:
```bash
yarn nx build trading
yarn nx serve trading
```
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.
NOTE: Parallel running of tests will not work against locally served console.
## Test Strategy and Container Cleanup
### Strategy
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.
### Cleanup Procedure
To ensure proper cleanup of containers after each test, use the following fixture pattern:
```python
@pytest.fixture
def vega(request):
with init_vega(request) as vega_instance:
request.addfinalizer(lambda: cleanup_container(vega_instance))
yield vega_instance
```
Run a targeted test:
## Running Tests in Parallel
```bash
poetry run pytest -k "test_name" -s --headed
```
For running tests in parallel:
Run from anywhere:
- **Within the e2e folder**: `poetry run pytest -s --numprocesses auto --dist loadfile`
- **From anywhere**: `yarn trading:test:all`
```bash
yarn trading:test -- "test_name" -s --headed
```
## Troubleshooting
Run using your locally served console:
If IntelliSense is not working in VSCode, follow these steps:
Within one terminal
```bash
yarn nx build trading
```
```bash
yarn nx serve trading
```
Once console is served you can update the .env file to have local_server to true.
## Running Tests in Parallel 🔢
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.
### From within the e2e folder:
```bash
poetry run pytest -s --numprocesses auto --dist loadfile
```
### From anywhere:
```bash
yarn trading:test:all
```
# Things to know
If you "intellisense" isn't working follow these steps:
1. ```bash
poetry run which python
```
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
1. Find the Poetry environment's Python binary: `poetry run which python`
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.