使用Python3处理AVRO的嵌套模式

时间:2019-03-03 03:45:47

标签: python-3.x avro

我正在使用avro1.8.2 + python3.7(pip install avro-python3)进行AVRO格式处理。

这是AVRO website

中的示例代码
import avro.schema
from avro.datafile import DataFileReader, DataFileWriter
from avro.io import DatumReader, DatumWriter

schema = avro.schema.parse(open("user.avsc", "rb").read())

writer = DataFileWriter(open("users.avro", "wb"), DatumWriter(), schema)
writer.append({"name": "Alyssa", "favorite_number": 256})
writer.append({"name": "Ben", "favorite_number": 7, "favorite_color": "red"})
writer.close()

reader = DataFileReader(open("users.avro", "rb"), DatumReader())
for user in reader:
    print user
reader.close()

此代码无效,因为parse方法已重命名为Parse,并且第二个参数(支持嵌套模式)已删除。

所以问题是如何在python3中使用嵌套模式读取/写入AVRO?

1 个答案:

答案 0 :(得分:1)

阅读Avro库的源代码后,我想出了一种方法来实现。这是代码

import json

import avro.schema
from avro.datafile import DataFileReader, DataFileWriter
from avro.io import DatumReader, DatumWriter

def create_schema():
    names = avro.schema.Names()
    load = lambda dict_value: avro.schema.SchemaFromJSONData(dict_value, names=names)

    transaction_schema_dict = {
        "namespace": "myavro",
        "type": "record",
        "name": "Transaction",
        "fields": [
            {"name": "name", "type": "string"},
        ]
    }
    account_schema_dict = {
        "namespace": "myavro",
        "type": "record",
        "name": "Account",
        "fields": [
            {"name": "name", "type": "string"},
            {"name": "transaction",  "type": ["null", {'type': 'array', 'items': 'Transaction'}], 'default': "null"},
        ]
    }

    load(transaction_schema_dict)
    return load(account_schema_dict)

def write_avro_file(file_path, schema, data):
    with open(file_path, 'wb') as f, DataFileWriter(f, DatumWriter(), schema) as writer:
        writer.append(data)

def print_avro_file(file_path):
    with open(file_path, 'rb') as f, DataFileReader(f, DatumReader()) as reader:
        for account in reader:
            print(account)

def run():
    schema = create_schema()
    file_path = 'account.avro'
    data = {
        'name': 'my account',
        'transaction': [
            { 'name': 'my transaction 1' },
            { 'name': 'my transaction 2' },
        ]
    }
    write_avro_file(file_path, schema, data)
    print_avro_file(file_path)

run()

关键是使用SchemaFromJSONData函数而不是Parse,并分配相同的Names对象以允许架构相互引用。请注意,加载架构调用的顺序很重要。