Sarath Gadde
2020-11-30 17:19:23
你可以使用engine = xlsxwriter实例化ExcelWriter（）并使用fs-gcsfs将bytes数组写入GCS存储桶中的excel文件。
根据你的情况，你可以执行以下操作：
import io
import pandas as pd
from fs_gcsfs import GCSFS
gcsfs = GCSFS(bucket_name='name_of_your_bucket',
root_path='path/to/excel',
#set a different root path if you wish to upload multiple files in different locations
strict=False)
gcsfs.fix_storage()
output = io.BytesIO()
writer = pd.ExcelWriter(output, engine='xlsxwriter')
dataframe1.to_excel(writer, sheet_name='sheet1', index=False)
dataframe2.to_excel(writer, sheet_name='sheet2', index=False)
writer.save()
xlsx_data = output.getvalue()
with gcsfs.open('./excel_file.xlsx', 'wb') as f:
f.write(xlsx_data)
PS：我必须使用strict = False，因为fs-gcsfs无法找到根路径（请检查文档中fs-gcsfs的限制部分）
来源：https : //xlsxwriter.readthedocs.io/working_with_pandas.html#saving-the-dataframe-output-to-a-string
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Mamba is a new state space model architecture showing promising performance on information-dense data such as language modeling, where previous subquadratic models fall short of Transformers. It is based on the line of progress on structured state space models, with an efficient hardware-aware design and implementation in the spirit of FlashAttention.
(翻译：Mamba 是一种新的状态空间模型架构，在信息密集型数据（例如语言建模）上显示出良好的性能，而之前的二次模型在 Transformers 方面存在不足。它基于结构化状态空间模型的进展，并本着FlashAttention的精神进行高效的硬件感知设计和实现。)