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compressed-spreadsheets-1.0.1


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توضیحات

Read & write to gzip compressed CSV files.
ویژگی مقدار
سیستم عامل -
نام فایل compressed-spreadsheets-1.0.1
نام compressed-spreadsheets
نسخه کتابخانه 1.0.1
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Max Bond
ایمیل نویسنده -
آدرس صفحه اصلی https://github.com/MaxBondABE/compressed_spreadsheets
آدرس اینترنتی https://pypi.org/project/compressed-spreadsheets/
مجوز -
Compressed Spreadsheets ----------------------- Compressed Spreadsheets is a simple Python library for reading & writing to `gzip` compressed CSV files using a similar API as the builtin `csv.DictReader` and `csv.DictWriter`. # Priorities * Simplicity * Speed * Ergonomics * Compatibility with the API of `DictReader` and `DictWriter` (though not the file format) # Caveats This code assumes that each row has to correct number of elements, in order to avoid imposing checks on each row. The goal of the implementation is to be reasonably fast with a simple implementation. The CSVs it generates won't be compatible with any other library, because of the (simple, easy) way special characters are escaped. If we were to use `StringIO` to create a buffer that a real `DictWriter` instance would write to, and then shuffle this into the compressed file, then we'd have compatiblity without sacrificing simplicity; however, speed was more important than compatiblity for my purposes, so I opted for this implementation. The library does not behave well on sheets with 0 columns. # Installation ## From GitHub Simply download the project and place `compressed_spreadsheets.py` into your project directory; it has no external requirements. ## From PyPI `pip install compressed-spreadsheets` # Examples These examples enumerate common use cases. See the docstrings for full documentation. ## Writing to a spreadsheet ``` sheet = CompressedDictWriter.open("my_sheet.csv.gz", ("Column A", "Column B")) sheet.writeheader() sheet.writerow({"Column A": "Value 1", "Column B": "Value 2"}) sheet.writerows(( {"Column A": "foo", "Column B": "bar"}, {"Column A": "baz", "Column B": "snafu"} )) sheet.close() ``` ## Reading from a spreadsheet Calling `CompressedDictReader.open(filename)` returns an object we can iterate over to retrieve our rows. ``` sheet = CompressedDictReader.open("my_sheet.csv.gz") # If the optional fieldnames argument is omitted, it is assumed the first line is a header row next(sheet) # {"Column A": "Value 1", "Column B": "Value 2"} for row in sheet: process(row) ``` ## Specifying types for fields The `fieldtypes` argument allows you to automatically convert values into their proper types. ``` write_sheet = CompressedDictWriter.open("my_numbers_sheet.csv.gz", fieldnames=("Column A", "Column B")) write_sheet.writeheader() write_sheet.writerow({"Column A": 10, "Column B": 5.1}) write_sheet.close() read_sheet = CompressedDictReader.open("my_numbers_sheet.csv.gz", fieldtypes={"Column A": int, "Column B": float}) next(read_sheet) # {"Column A": 10, "Column B": 5.1}) ``` ## Context managers Both `CompressedDictReader` and `CompressedDictWriter` can be used as context managers. This will ensure the file is closed properly. ``` with CompressedDictWriter.open("my_sheet.csv.gz") as sheet: for row in data: sheet.writerow(row) ``` # Contributing I'm open to contributions, and especially open to bug reports. Please open an issue for any bugs, and please include unit tests & docstrings for any pull requests. Use `pip -r development.txt` to install the testing dependencies. Run tests with `pytest`. If you've made a very significant change or you'd like to hear for computer fan, you can use `pytest --hypothesis-profile hammer` to generate 1000 testcases for each test. # License Compressed Spreadsheets is distributed under the MIT license. See LICENSE.txt for the full terms of the license.


زبان مورد نیاز

مقدار نام
>=3.5, <4 Python


نحوه نصب


نصب پکیج whl compressed-spreadsheets-1.0.1:

    pip install compressed-spreadsheets-1.0.1.whl


نصب پکیج tar.gz compressed-spreadsheets-1.0.1:

    pip install compressed-spreadsheets-1.0.1.tar.gz