Previously: https://news.ycombinator.com/item?id=46557542

> _canonicalize_table = str.maketrans( "ABCDEFGHIJKLMNOPQRSTUVWXYZ_.", "abcdefghijklmnopqrstuvwxyz--", )

> ...

> value = name.translate(_canonicalize_table)

> while "--" in value:

> value = value.replace("--", "-")

translate can be wildly fast compared to some commonly used regexes or replacements.

Misleading title, they didn't make the packaging library 3x faster, they made reading one attribute of a package 3x faster. The whole library is still very, very slow compared to alternatives.

Unrelated, but I personally am not satisfied with the performance of Panda's XLSX export. As you can see here [0], the code does really strange things. It takes cell.style and throws it into json.dumps() to generate a key for a dictionary so that they can cache the XlsxStyler.convert(cell.style) result. Except, the vast majority of cells do not have any styling whatsoever, so json.dumps is producing the string "null", which is then used to lookup None. The low hanging fruit are jaw dropping. You can easily speed up the code 10%+ by adding a simple check "if cell.style is not None or fmt is not None:" and switching from json.dumps(cell.style) to str(cell.style). If I wanted an easy weekend project that positively impacts many people this is what I'd work on.

[0] https://github.com/pandas-dev/pandas/blob/main/pandas/io/exc...