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Python scripts to export the VerA PostgreSQL database in Parquet format

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VerA DB Parquet Export Script

Python scripts and Docker container to export the Verifier Alliance PostgreSQL database in Parquet format and upload it to an S3 bucket.

Warning: The script likely has some memory leak issues and needs some refinement. Still, does the job.

The latest export is available on Cloudflare R2. The database with the new v1 schema is still in the making. We'll announce when these new exports are publicly available. Bear in mind the data is not production-ready and contains many mistakes. We've laid out some of the problems in this document

Requirements

  • Python 3

Installation

Create a virtual environment:

python -m venv venv

Activate the virtual environment:

source venv/bin/activate

Install dependencies:

pip install -r requirements.txt

Usage

Run the script with:

python main.py

The script takes some additional env vars for debugging purposes:

  • DEBUG_TABLE: The name of the table to dump solely. Skips other tables.
  • DEBUG_OFFSET: Will add an offset to the SELECT queries "SELECT * FROM {table_name} OFFSET {os.getenv('DEBUG_OFFSET')}"

The rest of the env vars can be found in the .env-template file. Copy the .env-template file to .env and fill in the values.

The config.py file contains the configuration for each database table about the chunk sizes and number of chunks per file, and the datatypes for each column in the table.

Example:

  {
    'name': 'verified_contracts',
    'datatypes': {
        'id': 'Int64',
        'created_at': 'datetime64[ns]',
        'updated_at': 'datetime64[ns]',
        'created_by': 'string',
        'updated_by': 'string',
        'deployment_id': 'string',
        'compilation_id': 'string',
        'creation_match': 'bool',
        'creation_values': 'string',
        'creation_transformations': 'string',
        'runtime_match': 'bool',
        'runtime_values': 'string',
        'runtime_transformations': 'string'
    },
    'chunk_size': 10000,
    'num_chunks_per_file': 10
  }

This config gives 10,000 * 10 = 100,000 rows per file.

The files will be named verified_contracts_0_100000_zstd.parquet and verified_contracts_100000_200000_zstd.parquet etc. (zstd is the compression algorithm).

The script also generates a manifest.json that contains a timestamp when the dump is created, and the list of files to access them in the S3 bucket.

{
  "timestamp": 1718042395518,
  "dateStr": "2024-06-10T17:59:55.518972Z",
  "files": {
    "code": [
      "code/code_0_100000_zstd.parquet",
      "code/code_100000_200000_zstd.parquet",
      "code/code_200000_300000_zstd.parquet",
      "code/code_300000_400000_zstd.parquet",
      "code/code_400000_500000_zstd.parquet",
      "code/code_500000_600000_zstd.parquet",
      "code/code_600000_700000_zstd.parquet",
      "code/code_700000_800000_zstd.parquet"
    ],
    "contract_deployments": [...],
    "compiled_contracts": [...],
    "verified_contracts": [...]
  }
}

Docker

Build the image:

docker build --tag=kuzdogan/test-parquet-linux --platform=linux/amd64 .

Publish:

docker push kuzdogan/test-parquet-linux

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