improving df.to_csv performance #7147
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…rows_fast into lib.pyx that manages file open/close on its own with self.path_or_buf from CSVFormmatter.
| @@ -1165,6 +1165,20 @@ def save(self): | |||
| if self.encoding is not None: | |||
| writer_kwargs['encoding'] = self.encoding | |||
| self.writer = com.UnicodeWriter(f, **writer_kwargs) | |||
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| elif self.engine == 'fast': | |||
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pls add a loop around some of the tests, so that each are tested with each engine e.g. [None,fast'] (I think the default is None), we should remove the 'python' engine (separate issue). Of course later need to add logic / tests to deal with certain data that maybe can't be written via fast engine
…ce. Taking care of float, int and string dtypes.
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closing for now. pls reopen if you want to update. |
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This is a WIP and discuss PR 🚧 for #3186
Adding small Writer class to have short-lived self.writer in CSVFomatter just for the header line. It is closed after the header was written.
Adding new lib.pyx function write_csv_rows_fast that manages file open/close on its own with self.path_or_buf from CSVFormmatter.
Current speed-up is factor 2.5 compared to before. Possibly the fprintf for each item is inefficient, but I thought as fprintf is buffered (in contrast to write) it can't be too bad. Any suggestions what I'm doing horribly wrong?