您可以简单地使用schema_to_json() 方法将您的表模式转换为json。它需要两个属性,分别是 schema_list 和 destination。
我使用带有嵌套数据的公共数据集来举例说明您的情况,并使用StringIO() 来展示架构的样子。
from google.cloud import bigquery
import io
client = bigquery.Client()
project = 'bigquery-public-data'
dataset_id = 'samples'
table_id = 'shakespeare'
dataset_ref = client.dataset(dataset_id, project=project)
table_ref = dataset_ref.table(table_id)
table = client.get_table(table_ref)
f = io.StringIO("")
client.schema_to_json(table.schema, f)
print(f.getvalue())
还有输出:
[
{
"description": "A single unique word (where whitespace is the delimiter) extracted from a corpus.",
"mode": "REQUIRED",
"name": "word",
"type": "STRING"
},
{
"description": "The number of times this word appears in this corpus.",
"mode": "REQUIRED",
"name": "word_count",
"type": "INTEGER"
},
{
"description": "The work from which this word was extracted.",
"mode": "REQUIRED",
"name": "corpus",
"type": "STRING"
},
{
"description": "The year in which this corpus was published.",
"mode": "REQUIRED",
"name": "corpus_date",
"type": "INTEGER"
}
]
与使用命令!bq show --format=prettyjson bigquery-public-data:samples.wikipedia | jq '.schema.fields'时显示的输出相同