"""Amazon S3 Excel Read Module (PRIVATE).""" import logging from typing import Any, Dict, Optional, Union import boto3 import awswrangler.pandas as pd from awswrangler import _utils, exceptions from awswrangler.s3._fs import open_s3_object openpyxl = _utils.import_optional_dependency("openpyxl") _logger: logging.Logger = logging.getLogger(__name__) @_utils.check_optional_dependency(openpyxl, "openpyxl") def read_excel( path: str, version_id: Optional[str] = None, use_threads: Union[bool, int] = True, boto3_session: Optional[boto3.Session] = None, s3_additional_kwargs: Optional[Dict[str, Any]] = None, **pandas_kwargs: Any, ) -> pd.DataFrame: """Read EXCEL file(s) from a received S3 path. Note ---- This function accepts any Pandas's read_excel() argument. https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_excel.html Note ---- Depending on the file extension ('xlsx', 'xls', 'odf'...), an additional library might have to be installed first. Note ---- In case of `use_threads=True` the number of threads that will be spawned will be gotten from os.cpu_count(). Parameters ---------- path : str S3 path (e.g. ``s3://bucket/key.xlsx``). version_id : Optional[str] Version id of the object. use_threads : Union[bool, int] True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. If given an int will use the given amount of threads. If integer is provided, specified number is used. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] Forward to botocore requests, only "SSECustomerAlgorithm" and "SSECustomerKey" arguments will be considered. pandas_kwargs: KEYWORD arguments forwarded to pandas.read_excel(). You can NOT pass `pandas_kwargs` explicit, just add valid Pandas arguments in the function call and awswrangler will accept it. e.g. wr.s3.read_excel("s3://bucket/key.xlsx", na_rep="", verbose=True) https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_excel.html Returns ------- pandas.DataFrame Pandas DataFrame. Examples -------- Reading an EXCEL file >>> import awswrangler as wr >>> df = wr.s3.read_excel('s3://bucket/key.xlsx') """ if "pandas_kwargs" in pandas_kwargs: raise exceptions.InvalidArgument( "You can NOT pass `pandas_kwargs` explicit, just add valid " "Pandas arguments in the function call and awswrangler will accept it." "e.g. wr.s3.read_excel('s3://bucket/key.xlsx', na_rep='', verbose=True)" ) with open_s3_object( path=path, mode="rb", version_id=version_id, use_threads=use_threads, s3_block_size=-1, # One shot download s3_additional_kwargs=s3_additional_kwargs, boto3_session=boto3_session, ) as f: _logger.debug("pandas_kwargs: %s", pandas_kwargs) return pd.read_excel(f, **pandas_kwargs)