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https://issues.apache.org/jira/browse/AIRFLOW-6481?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Jarek Potiuk resolved AIRFLOW-6481.
-----------------------------------
Fix Version/s: 2.0.0
Resolution: Fixed
> SalesforceHook attempts to use .str accessor on object dtype
> ------------------------------------------------------------
>
> Key: AIRFLOW-6481
> URL: https://issues.apache.org/jira/browse/AIRFLOW-6481
> Project: Apache Airflow
> Issue Type: Bug
> Components: hooks
> Affects Versions: 1.10.7
> Reporter: Teddy Hartanto
> Assignee: Teddy Hartanto
> Priority: Minor
> Fix For: 2.0.0
>
> Original Estimate: 1h
> Remaining Estimate: 1h
>
> I've searched through Airflow's issues and couldn't find any report regarding
> this. I wonder if I'm the only one who's facing this?
> {noformat}
> Panda version: 0.24.2{noformat}
> *Bug description*
> I'm using the SalesforceHook to fetch data from SalesForce and I encountered
> this exception:
> {code:java}
> AttributeError: ('Can only use .str accessor with string values, which use
> np.object_ dtype in pandas', ...)
> {code}
> The root of the problem is that some of the object in Salesforce has a column
> with compound data type. Eg: User's address is a Python dict:
> {code:java}
> <class 'dict'>: {'city': None, 'country': 'my', 'geocodeAccuracy': None,
> 'latitude': None, 'longitude': None, 'postalCode': None, 'state': None,
> 'street': None}{code}
> The problematic code is here:
> {code:java}
> if fmt == "csv":
> # there are also a ton of newline objects
> # that mess up our ability to write to csv
> # we remove these newlines so that the output is a valid CSV format
> self.log.info("Cleaning data and writing to CSV")
> possible_strings = df.columns[df.dtypes == "object"]
> df[possible_strings] = df[possible_strings].apply(
> lambda x: x.str.replace("\r\n", "")
> )
> df[possible_strings] = df[possible_strings].apply(
> lambda x: x.str.replace("\n", "")
> )
> # write the dataframe
> df.to_csv(filename, index=False)
> {code}
> Because a Series containing Python dicts are also considered of dtype object,
> they're assumed to be "possible_strings". And then, when .str is called on
> that Series, the exception is thrown.
> To fix it, we could explicitly cast the object type to string as such:
> {code:java}
> if fmt == "csv":
> ...
> df[possible_strings] = df[possible_strings].astype(str).apply(
> lambda x: x.str.replace("\r\n", "")
> )
> df[possible_strings] = df[possible_strings].astype(str).apply(
> lambda x: x.str.replace("\n", "")
> )
> {code}
> I've tested this and it works for me. Could somebody help me verify that the
> type conversion is indeed needed? If yes, I'm keen to submit a PR to fix this
> with the unit test included.
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