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https://issues.apache.org/jira/browse/THRIFT-4089?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15865568#comment-15865568
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Aki Sukegawa commented on THRIFT-4089:
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Sounds like version mismatch between compiler and library: 0.10.0 compiler
against older python lib.
> Several issues with generated Python code: TFrozenDict, _fast_encode
> --------------------------------------------------------------------
>
> Key: THRIFT-4089
> URL: https://issues.apache.org/jira/browse/THRIFT-4089
> Project: Thrift
> Issue Type: Bug
> Affects Versions: 0.10.0
> Environment: Python 2.7. OS-X
> Reporter: Manasi Vartak
>
> When you generate Python sources for a simple thrift file (e.g. Thrift
> tutorial from https://thrift.apache.org/tutorial/py will also repro erros),
> errors are thrown while running the PythonServer and PythonClient.
> 1. When running the vanilla PythonServer, I get the following error:
> File "gen-py/shared/SharedService.py", line 9, in <module>
> from thrift.Thrift import TType, TMessageType, TFrozenDict, TException,
> TApplicationException
> ImportError: cannot import name TFrozenDict
> I see this error consistently for all generated thrift files. The error
> disappears on removing TFrozenDict from the generated files (it is not used
> anywhere in the file).
> 2. When running the vanilla PythonClient (the server is now running after the
> above fix), I get the following error:
> File "PythonClient.py", line 51, in main
> client.ping()
> File "gen-py/tutorial/Calculator.py", line 73, in ping
> self.send_ping()
> File "gen-py/tutorial/Calculator.py", line 79, in send_ping
> args.write(self._oprot)
> File "gen-py/tutorial/Calculator.py", line 297, in write
> if oprot._fast_encode is not None and self.thrift_spec is not None:
> AttributeError: TBinaryProtocol instance has no attribute '_fast_encode'
> I am not sure why this error is being thrown/what can be done to fix it.
> These two errors, and mainly the latter one, are rendering the Server/Client
> un-usable. Is this a known issue? And how do you recommend working around it?
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