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python: process result files after metadata type inference.
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@ -101,9 +101,6 @@ def load(_dir, _process=None, _format=None, _stream='stdout',
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# Create a DataFrame from the matches.
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df = pd.DataFrame(matches)
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if _process and not df.empty:
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df['res'] = df.resfile.apply(_process)
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df = df.drop('resfile', axis=1)
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# Optionally try to convert string argument values to numeric types.
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if _infer_types:
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@ -111,6 +108,13 @@ def load(_dir, _process=None, _format=None, _stream='stdout',
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df.to_csv(buf)
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df = pd.read_csv(StringIO(buf.getvalue()), index_col=0)
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# Open and process the results. This needs to happen after the type
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# infererence phase since the processed results can be arbitrary
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# Python objects and might not survive the round-trip.
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if _process and not df.empty:
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df['res'] = df.resfile.apply(_process)
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df = df.drop('resfile', axis=1)
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return df
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def _parse_name(file, sep='\t'):
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