A better CSV module
Project description
A better CSV library
Features
Lets you program in both Python 2 and Python 3 as if you had the Python 3 CSV module.
Under Python 2, provides a Python 3 compatible csv module.
Under Python 3, passes through transparently.
Lets your CSV files be encoded any way you want.
Python 3 compatibility
import cordwainer.csv as csv ought to be equivalent to importing the Python 3 csv module, whether running with Python 2 or 3. See the Python 3 csv module documentation
CSV file encoding
The Python 2 csv module expects file handles passed to it to return data encoded in ASCII or UTF-8, and writes it to files the same way.
The Python 3 csv module expects handles passed to it to return text data, already decoded, and writes un-encoded text data to them. It’s your responsiblity to arrange for conversion when you open the file, or pipe your stream through some kind of conversion.
Using Cordwainer, you can just pass an extra encoding parameter to say that your stream is providing or expecting binary data with the specified encoding, and Cordwainer will take care of all necessary conversions.
If encoding is omitted or None, Cordwainer assumes the provided stream will provide or expect un-encoded text data, just like Python 3’s csv module.
Misc. Usage Notes
The encoding parameter is only applied for reading from and writing to streams.
String arguments should always be passed to the API as characters, and results are always characters.
E.g.:
Pass fieldnames to DictWriter as characters
Pass data in rows to writerow() as characters
next() returns rows in characters
Intended (eventually) features
Optional header row
Validate expected fields, types (probably specify a Django form to do the validation)
Verbose error handling - say what the problem was on what line, for every line that has an error
Optionally stop processing after N errors
Optionally import the lines that are valid while skipping invalid ones
Optionally do the whole thing in one transaction
Optionally ignore any extra columns
Optionally save uploaded file and then process it in a background task (to not delay the HTTP request)
For Excel, be flexible in deciding what sheet to import - or even import from multiple sheets from one upload
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