path: root/packages/pipeline/README.md

## @0xproject/pipeline

This repository contains scripts used for scraping data from the Ethereum blockchain into SQL tables for analysis by the 0x team.

## Contributing

We strongly recommend that the community help us make improvements and determine the future direction of the protocol. To report bugs within this package, please create an issue in this repository.

Please read our [contribution guidelines](../../CONTRIBUTING.md) before getting started.

### Install dependencies:

```bash
yarn install
```

### Build

```bash
yarn build
```

### Clean

```bash
yarn clean
```

### Lint

```bash
yarn lint
```

### Migrations

Create a new migration: `yarn migrate:create --name MigrationNameInCamelCase`
Run migrations: `yarn migrate:run`
Revert the most recent migration (CAUTION: may result in data loss!): `yarn migrate:revert`

## Testing

There are several test scripts in **package.json**. You can run all the tests
with `yarn test:all` or run certain tests seprately by following the
instructions below. Some tests may not work out of the box on certain platforms
or operating systems (see the "Database tests" section below).

### Unit tests

The unit tests can be run with `yarn test`. These tests don't depend on any
services or databases and will run in any environment that can run Node.

### Database tests

Database integration tests can be run with `yarn test:db`. These tests will
attempt to automatically spin up a Postgres database via Docker. If this doesn't
work you have two other options:

1.  Set the `DOCKER_SOCKET` environment variable to a valid socket path to use
    for communicating with Docker.
2.  Start Postgres manually and set the `ZEROEX_DATA_PIPELINE_TEST_DB_URL`
    environment variable. If this is set, the tests will use your existing
    Postgres database instead of trying to create one with Docker.

## Running locally

`pipeline` requires access to a PostgreSQL database. The easiest way to start
Postgres is via Docker. Depending on your platform, you may need to prepend
`sudo` to the following command:

```
docker run --rm -d -p 5432:5432 --name pipeline_postgres postgres:11-alpine
```

This will start a Postgres server with the default username and database name
(`postgres` and `postgres`). You should set the environment variable as follows:

```
export ZEROEX_DATA_PIPELINE_DB_URL=postgresql://postgres@localhost/postgres
```

First thing you will need to do is run the migrations:

```
yarn migrate:run
```

Now you can run scripts locally:

```
node packages/pipeline/lib/src/scripts/pull_radar_relay_orders.js
```

To stop the Postgres server (you may need to add `sudo`):

```
docker stop pipeline_postgres
```

This will remove all data from the database.

If you prefer, you can also install Postgres with e.g.,
[Homebrew](https://wiki.postgresql.org/wiki/Homebrew) or
[Postgress.app](https://postgresapp.com/). Keep in mind that you will need to
set the`ZEROEX_DATA_PIPELINE_DB_URL` environment variable to a valid
[PostgreSQL connection url](https://stackoverflow.com/questions/3582552/postgresql-connection-url)

## Directory structure

```
.
├── lib: Code generated by the TypeScript compiler. Don't edit this directly.
├── migrations: Code for creating and updating database schemas.
├── node_modules:
├── src: All TypeScript source code.
│   ├── data_sources: Code responsible for getting raw data, typically from a third-party source.
│   ├── entities: TypeORM entities which closely mirror our database schemas. Some other ORMs call these "models".
│   ├── parsers: Code for converting raw data into entities.
│   ├── scripts: Executable scripts which put all the pieces together.
│   └── utils: Various utils used across packages/files.
├── test: All tests go here and are organized in the same way as the folder/file that they test.
```

## Adding new data to the pipeline

1.  Create an entity in the _entities_ directory. Entities directly mirror our
    database schemas. We follow the practice of having "dumb" entities, so
    entity classes should typically not have any methods.
2.  Create a migration using the `yarn migrate:create` command. Create/update
    tables as needed. Remember to fill in both the `up` and `down` methods. Try
    to avoid data loss as much as possible in your migrations.
3.  Add basic tests for your entity and migrations to the **test/entities/**
    directory.
4.  Create a class or function in the **data_sources/** directory for getting
    raw data. This code should abstract away pagination and rate-limiting as
    much as possible.
5.  Create a class or function in the **parsers/** directory for converting the
    raw data into an entity. Also add tests in the **tests/** directory to test
    the parser.
6.  Create an executable script in the **scripts/** directory for putting
    everything together. Your script can accept environment variables for things
    like API keys. It should pull the data, parse it, and save it to the
    database. Scripts should be idempotent and atomic (when possible). What this
    means is that your script may be responsible for determining _which_ data
    needs to be updated. For example, you may need to query the database to find
    the most recent block number that we have already pulled, then pull new data
    starting from that block number.
7.  Run the migrations and then run your new script locally and verify it works
    as expected.
8.  After all tests pass and you can run the script locally, open a new PR to
    the monorepo. Don't merge this yet!
9.  If you added any new scripts or dependencies between scripts, you will need
    to make changes to https://github.com/0xProject/0x-pipeline-orchestration
    and make a separate PR there. Don't merge this yet!
10. After your PR passes code review, ask @feuGeneA or @xianny to deploy your
    changes to the QA environment. Check the [QA Airflow dashboard](http://airflow-qa.0x.org:8080)
    to make sure everything works correctly in the QA environment.
11. Merge your PR to 0x-monorepo (and
    https://github.com/0xProject/0x-pipeline-orchestration if needed). Then ask
    @feuGeneA or @xianny to deploy to production.
12. Monitor the [production Airflow dashboard](http://airflow.0x.org:8080) to
    make sure everything still works.
13. Celebrate! :tada:

#### Additional guidelines and tips:

*   Table names should be plural and separated by underscores (e.g.,
    `exchange_fill_events`).
*   Any table which contains data which comes directly from a third-party source
    should be namespaced in the `raw` PostgreSQL schema.
*   Column names in the database should be separated by underscores (e.g.,
    `maker_asset_type`).
*   Field names in entity classes (like any other fields in TypeScript) should
    be camel-cased (e.g., `makerAssetType`).
*   All timestamps should be stored as milliseconds since the Unix Epoch.
*   Use the `BigNumber` type for TypeScript code which deals with 256-bit
    numbers from smart contracts or for any case where we are dealing with large
    floating point numbers.
*   [TypeORM documentation](http://typeorm.io/#/) is pretty robust and can be a
    helpful resource.
*   Scripts/parsers should perform minimum data transformation/normalization.
    The idea here is to have a raw data feed that will be cleaned up and
    synthesized in a separate step.