Edits history of script submission #6017 for ' ETL / Data pipeline on tabular data (duckdb)'

• python3

  Ap­pro­ved version

  Edit in Windmill

  Embed

  #requirements:
  wmill>=1.229.0
  #duckdb==0.9.1
  
  # Windmill embedded integration with Polars and DuckDB for data pipelines: https://www.windmill.dev/docs/core_concepts/persistent_storage/large_data_files#windmill-embedded-integration-with-polars-and-duckdb-for-data-pipelines
  
  import wmill
  from wmill import S3Object
  import duckdb
  
  
  def main(input_file: S3Object):
      bucket = wmill.get_resource("u/admin/windmill-cloud-demo")["bucket"]
  
      # create a DuckDB database in memory
      # see https://duckdb.org/docs/api/python/dbapi
      conn = duckdb.connect()
  
      # this will default to the workspace s3 resource
      args = wmill.duckdb_connection_settings().connection_settings_str
      # this will use the designated resource
      # args = wmill.duckdb_connection_settings("<PATH_TO_S3_RESOURCE>").connection_settings_str
  
      # connect duck db to the S3 bucket - this will default to the workspace s3 resource
      conn.execute(args)
  
      input_uri = "s3://{}/{}".format(bucket, input_file["s3"])
      output_file = "output/result.parquet"
      output_uri = "s3://{}/{}".format(bucket, output_file)
  
      # Run queries directly on the parquet file
      query_result = conn.sql(
          """
          SELECT * FROM read_parquet('{}')
      """.format(
              input_uri
          )
      )
      query_result.show()
  
      # Write the result of a query to a different parquet file on S3
      conn.execute(
          """
          COPY (
              SELECT COUNT(*) FROM read_parquet('{input_uri}')
          ) TO '{output_uri}' (FORMAT 'parquet');
      """.format(
              input_uri=input_uri, output_uri=output_uri
          )
      )
  
      conn.close()
      return S3Object(s3=output_file)

  Submitted by hugo697 398 days ago

• python3

  Edit in Windmill

  Embed

  #requirements:
  wmill>=1.229.0
  #duckdb==0.9.1
  
  # Windmill embedded integration with Polars and DuckDB for data pipelines: https://www.windmill.dev/docs/core_concepts/persistent_storage/large_data_files#windmill-embedded-integration-with-polars-and-duckdb-for-data-pipelines
  
  import wmill
  from wmill import S3Object
  import duckdb
  
  
  def main(input_file: S3Object):
      bucket = wmill.get_resource("u/admin/windmill-cloud-demo")["bucket"]
  
      # create a DuckDB database in memory
      # see https://duckdb.org/docs/api/python/dbapi
      conn = duckdb.connect()
  
      # this will default to the workspace s3 resource
      args = wmill.duckdb_connection_settings().connection_settings_str
      # this will use the designated resource
      # args = wmill.duckdb_connection_settings("<PATH_TO_S3_RESOURCE>").connection_settings_str
  
      # connect duck db to the S3 bucket - this will default to the workspace s3 resource
      conn.execute(args)
  
      input_uri = "s3://{}/{}".format(bucket, input_file["s3"])
      output_file = "output/result.parquet"
      output_uri = "s3://{}/{}".format(bucket, output_file)
  
      # Run queries directly on the parquet file
      query_result = conn.sql(
          """
          SELECT * FROM read_parquet('{}')
      """.format(
              input_uri
          )
      )
      query_result.show()
  
      # Write the result of a query to a different parquet file on S3
      conn.execute(
          """
          COPY (
              SELECT COUNT(*) FROM read_parquet('{input_uri}')
          ) TO '{output_uri}' (FORMAT 'parquet');
      """.format(
              input_uri=input_uri, output_uri=output_uri
          )
      )
  
      conn.close()
      return S3Object(s3=output_file)

  Submitted by henri186 819 days ago