Blockchain RPC Exporter

The exporter is used to scrape metrics from blockchain RPC endpoints. The purpose of this exporter is to perform black-box testing on RPC endpoints.

Metrics

Exporter currently supports all EVM-compatible chains. In addition, there is limited support for the following chains:

• Cardano (wss)
• Conflux (wss)
• Solana (https & wss)
• Bitcoin (https)
• Dogecoin (https)
• Filecoin (https)
• Starknet (https)

Available Metrics

Disclaimer

Please note that this tool is in the early development stage and should not be used to influence critical business decisions. The project in its current form suits our short-term needs and will receive limited support. We encourage you to fork the project and extend it with additional functionality you might need.

Development

You should install pre-commit so that automated linting and formatting checks are performed before each commit.

Run:

pip install pre-commit
pre-commit install

Running locally

1. Make sure you have python3 installed (>3.11)
2. Set up your python environment

pip3 install virtualenv
virtualenv venv
source venv/bin/activate
pip install -r requirements.txt
pip install -r requirements-dev.txt

1. Generate valid exporter config and validation file. For example see config example and validation example.
2. Export paths of generated configuration files relative to src/exporter.py:

export VALIDATION_FILE_PATH="validation.yml" # For example if we saved validation config file in src/validation.yml
export CONFIG_FILE_PATH="config.yml"  # For example if we saved config file in src/config.yml

3. Finally you can run the exporter

python exporter.py

Run with docker-compose

1. Generate valid exporter config and validation file. For example see config example and validation example.
2. Export paths of generated configuration files relative to docker-compose.yml:

export VALIDATION_FILE_PATH="src/validation.yml" # For example if we saved validation config file in src/validation.yml
export CONFIG_FILE_PATH="src/config.yml"  # For example if we saved config file in src/config.yml

3. Execute

docker-compose build
docker-compose up
curl localhost:8000/metrics # Exporter
curl localhost:3000         # Grafana
curl localhost:9090         # Prometheus

Testing

Testing is performed using pytest run by coverage.py to generate test coverage reporting. pylint is used to lint the pyhton code. These dependencies can be found in the requirements-dev.txt file. Unit testing and linting is performed on every commit push to the repository. 90% test coverage and no linter errors/warnings are a requirement for the tests to pass.

Testing Locally (venv)

Tests can be run locally in the virtual environment.

1. Run the unit tests with coverage.py from within the src directory.

coverage run --branch -m pytest

2. Generate the coverage report. To view the report open the generated index.html file in a browser.

coverage html

3. Run the linter to find any errors/warnings.

pylint src/*py

Testing Locally (docker)

The tests and linter can be run using docker by building the test docker stage.

1. Build the test stage in the Dockerfile.

docker build --target test .