CSV 到 AVRO 使用 python

Question

我有以下 csv：

field1;field2;field3;field4;field5;field6;field7;field8;field9;field10;field11;field12;
eu;4523;35353;01/09/1999; 741 ; 386 ; 412 ; 86 ; 1.624 ; 1.038 ; 469 ; 117 ;

我想把它转换成 avro。 我创建了以下 avro 架构：

{"namespace": "forecast.avro",
 "type": "record",
 "name": "forecast",
 "fields": [
     {"name": "field1", "type": "string"},
     {"name": "field2", "type": "string"},
     {"name": "field3", "type": "string"},
     {"name": "field4", "type": "string"},
     {"name": "field5", "type": "string"},
     {"name": "field6", "type": "string"},
     {"name": "field7", "type": "string"},
     {"name": "field8", "type": "string"},
     {"name": "field9", "type": "string"},
     {"name": "field10", "type": "string"},
     {"name": "field11", "type": "string"},
     {"name": "field12", "type": "null"}
 ]
}

我的代码是下一个：

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


FORECAST = "forecast.csv"
fields = ("field1", "field2", "field3", "field4", "field5", "field6", "field7", "field8", "field9", "field10", "field11", "field12")
forecastRecord = namedtuple('forecastRecord', fields)

def read_forecast_data(path):
    with open(path, 'rU') as data:
        data.readline()
        reader = csv.reader(data, delimiter = ";")
        for row in map(forecastRecord._make, reader):
            print(row)
            yield row

if __name__=="__main__":
    for row in read_forecast_data(FORECAST):
        print (row)
        break

def parse_schema(path="forecast.avsc"):
    with open(path, 'r') as data:
        return avro.schema.parse(data.read())
def serialize_records(records, outpath="forecast.avro"):
    schema = parse_schema()
    with open(outpath, 'w') as out:
        writer = DataFileWriter(out, DatumWriter(), schema)
        for record in records:
            record = dict((f, getattr(record, f)) for f in record._fields)
            writer.append(record)
if __name__ == "__main__":
    serialize_records(read_forecast_data(FORECAST))

当我运行代码时，我收到错误消息，指出数据不是当前模式的示例。 我一次又一次地检查我的架构以发现任何不一致之处，但直到现在我还没有找到任何不一致之处。 有人可以帮我吗？

Answer 1

当我按照编写的方式运行你的代码时，我得到一个错误TypeError: Expected 12 arguments, got 13 for row in map(forecastRecord._make, reader):中for row in map(forecastRecord._make, reader): TypeError: Expected 12 arguments, got 13 for row in map(forecastRecord._make, reader):因为你的CSV以a结尾; 因此有13个领域。

一旦我删除了那些尾随; s，我可以运行该示例并获得有关模式不匹配的相同错误。 原因是模式中的field12被定义为null类型，但在数据中它是一个string类型（值为"117" ）。

如果您将avsc文件更改为{"name": "field12", "type": "string"}那么它可以正常工作。

Answer 2

示例中的另一种方式：

    import csv
    from collections import namedtuple
    from fastavro import parse_schema, writer


    schema = {
              "namespace": "test.avro",
              "type": "record",
              "name": "test",
              "fields": [
                         {"name": "region", "type": "string"},
                         {"name": "anzsic_descriptor", "type": "string"},
                         {"name": "gas", "type": "string"},
                         {"name": "units", "type": "string"},
                         {"name": "magnitude", "type": "string"},
                         {"name": "year", "type": "string"},
                         {"name": "data_val", "type": "string"}
                         ]
                      }
fields = 
  ("region","anzsic_descriptor","gas","units","magnitude","year","data_val")
forecastRecord = namedtuple('forecastRecord', fields)
parsed_schema = parse_schema(schema)

lst = []
with open('test.csv', 'r') as data:
    data.readline()
    reader = csv.reader(data, delimiter=",")
    for records in map(forecastRecord._make, reader):
        record = dict((f, getattr(records, f)) for f in records._fields)
        l.append(record)

with open("users.avro", "wb") as fp:
    writer(fp, schema, l)