在 Python 中读取镶木地板字节对象 [英] Read a parquet bytes object in Python

问题描述

我有一个 python 对象，我知道这是一个加载到对象的镶木地板文件.(我无法从文件中实际读取它).

I have a python object which I know this is a parquet file loaded to the object. (I do not have the possibility to actually read it from a file).

对象 var_1 包含 b'PAR1\x15\x....1\x00PAR1

当我检查类型时:

type(var_1)

我得到的结果是bytes.

有没有办法阅读这个?说成熊猫数据框?

Is there a way to read this ? say into a pandas data-frame ?

我试过:1)

from fastparquet import ParquetFile
pf = ParquetFile(var_1)

得到:

TypeError: a bytes-like object is required, not 'str'

2

import pyarrow.parquet as pq
dataset = pq.ParquetDataset(var_1)

并得到:

TypeError: not a path-like object

注意，如何读取Parquet文件的解决方案进入 Pandas DataFrame?.即 pd.read_parquet(var_1, engine='fastparquet') 导致 TypeError: a bytes-like object is required, not 'str'

推荐答案

已使用 Pandas 1.2.3 进行测试

This was tested with Pandas 1.2.3

要将镶木地板 bytes 对象读取作为 Pandas 数据帧:

To read a parquet bytes object as a Pandas dataframe:

import io

import pandas as pd

pq_bytes = b'PAR1\x15\x02\x19\x1c5\x00\x18\x06schema\x15\x00\x00\x16\x00\x19\x1c\x19\x0c\x16\x00\x16\x00&\x00\x16\x00\x14\x00\x00\x19,\x18\x06pandas\x18\x8c\x01{"index_columns": [], "column_indexes": [], "columns": [], "creator": {"library": "pyarrow", "version": "1.0.1"}, "pandas_version": "1.1.3"}\x00\x18\x0cARROW:schema\x18\xd8\x02//////gAAAAQAAAAAAAKAA4ABgAFAAgACgAAAAABBAAQAAAAAAAKAAwAAAAEAAgACgAAAMQAAAAEAAAAAQAAAAwAAAAIAAwABAAIAAgAAACcAAAABAAAAIwAAAB7ImluZGV4X2NvbHVtbnMiOiBbXSwgImNvbHVtbl9pbmRleGVzIjogW10sICJjb2x1bW5zIjogW10sICJjcmVhdG9yIjogeyJsaWJyYXJ5IjogInB5YXJyb3ciLCAidmVyc2lvbiI6ICIxLjAuMSJ9LCAicGFuZGFzX3ZlcnNpb24iOiAiMS4xLjMifQAAAAAGAAAAcGFuZGFzAAAAAAAAAAAAAA==\x00\x18"parquet-cpp version 1.5.1-SNAPSHOT\x19\x0c\x00M\x02\x00\x00PAR1'
pq_file = io.BytesIO(pq_bytes)
df = pd.read_parquet(pq_file)

要将 Pandas 数据帧写入到 bytes 对象:

To write a Pandas dataframe to a bytes object:

import pandas as pd

df = pd.DataFrame()
df.to_parquet()
b'PAR1\x15\x04\x15\x00\x15\x02L\x15\x00\x15\x04\x12\x00\x00\x00&&\x1c\x15\x02\x195\x04\x00\x06\x19\x18\x11__index_level_0__\x15\x02\x16\x00\x16\x1c\x16\x1e&\x00&\x08)\x1c\x15\x04\x15\x04\x15\x02\x00\x00\x00\x15\x02\x19,5\x00\x18\x06schema\x15\x02\x00\x15\x02%\x02\x18\x11__index_level_0__l\xbc\x00\x00\x00\x16\x00\x19\x1c\x19\x1c&&\x1c\x15\x02\x195\x04\x00\x06\x19\x18\x11__index_level_0__\x15\x02\x16\x00\x16\x1c\x16\x1e&\x00&\x08)\x1c\x15\x04\x15\x04\x15\x02\x00\x00\x00\x16\x1e\x16\x00&&\x16\x1e\x14\x00\x00\x19,\x18\x06pandas\x18\xf6\x02{"index_columns": ["__index_level_0__"], "column_indexes": [{"name": null, "field_name": null, "pandas_type": "empty", "numpy_type": "object", "metadata": null}], "columns": [{"name": null, "field_name": "__index_level_0__", "pandas_type": "empty", "numpy_type": "object", "metadata": null}], "creator": {"library": "pyarrow", "version": "3.0.0"}, "pandas_version": "1.2.3"}\x00\x18\x0cARROW:schema\x18\xec\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\x00\x18"parquet-cpp version 1.5.1-SNAPSHOT\x19\x1c\x1c\x00\x00\x00\x1f\x05\x00\x00PAR1'

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