fastavro¶
The current Python avro package is packed with features but dog slow.
On a test case of about 10K records, it takes about 14sec to iterate over all of them. In comparison the JAVA avro SDK does it in about 1.9sec.
fastavro is less feature complete than avro, however it’s much faster. It iterates over the same 10K records in 2.9sec, and if you use it with PyPy it’ll do it in 1.5sec (to be fair, the JAVA benchmark is doing some extra JSON encoding/decoding).
If the optional C extension (generated by Cython) is available, then fastavro will be even faster. For the same 10K records it’ll run in about 1.7sec.
Example¶
# Writing
from fastavro import writer
schema = {
'doc': 'A weather reading.',
'name': 'Weather',
'namespace': 'test',
'type': 'record',
'fields': [
{'name': 'station', 'type': 'string'},
{'name': 'time', 'type': 'long'},
{'name': 'temp', 'type': 'int'},
],
}
# 'records' can be an iterable (including generator)
records = [
{u'station': u'011990-99999', u'temp': 0, u'time': 1433269388},
{u'station': u'011990-99999', u'temp': 22, u'time': 1433270389},
{u'station': u'011990-99999', u'temp': -11, u'time': 1433273379},
{u'station': u'012650-99999', u'temp': 111, u'time': 1433275478},
]
with open('weather.avro', 'wb') as out:
writer(out, schema, records)
# Reading
import fastavro
with open('weather.avro', 'rb') as fo:
reader = fastavro.reader(fo)
schema = reader.schema
for record in reader:
print(record)