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from __future__ import annotations

from typing import Any

[docs]def bq_cast(string_field: str, bq_type: str) -> None | int | float | bool | str: """ Cast a BigQuery row to the appropriate data types. This is useful because BigQuery returns all fields as strings. """ if string_field is None: return None elif bq_type == "INTEGER": return int(string_field) elif bq_type in ("FLOAT", "TIMESTAMP"): return float(string_field) elif bq_type == "BOOLEAN": if string_field not in ["true", "false"]: raise ValueError(f"{string_field} must have value 'true' or 'false'") return string_field == "true" else: return string_field
[docs]def convert_job_id(job_id: str | list[str], project_id: str, location: str | None) -> Any: """ Convert job_id to path: project_id:location:job_id. :param project_id: Required. The ID of the Google Cloud project where workspace located. :param location: Optional. The ID of the Google Cloud region where workspace located. :param job_id: Required. The ID of the job. :return: str or list[str] of project_id:location:job_id. """ location = location or "US" if isinstance(job_id, list): return [f"{project_id}:{location}:{i}" for i in job_id] else: return f"{project_id}:{location}:{job_id}"

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