[joshvm]

> assert(isinstance(arg, type))

The most irritating thing I've found is trying to write a function that accepts either a path or the raw contents of a file.

Python 3 makes this easy, you can check against string. Python 2 of course treats everything as a byte string.

In the end I just check the length of the input if the interpret identifies as python 2. If it's a short byte string, I assume it's a file name. Otherwise the minimum expected file size is almost certainly larger than the maximum path length.

[newen]

Why would you ever do that? Why would you even want a function that accepts either a file name or file contents when both are strings? What's so hard about defining a new function?

[mjw1007]

One common case where this is attractive is where you have a bunch of "public" functions built on top of each other, with the higher ones passing that parameter on and not otherwise caring what it is:

  high_level_function(src, ...)
      ...
      mid_level_function(src, ...)
      ...

  mid_level_function(src, ...)
      low_level_function(src, ...)
      ...

  low_level_function(src, ...)
      ...

If you can make the low-level function generic one way or another, you avoid having to duplicate the higher-level functions.

Another case is where there are two or more parameters that you want to be generic in this sense: if your only option is duplicating the function you can end up having to define inconveniently many variants.

[newen]

Yeah, that is convenient and I do that often. But I try to wrap the variables in different types depending on their source (e.g. whether it's a filename or file content) so that functions further down can disambiguate between variables explicitly.

[guidopallemans]

An example: pandas.read_csv

https://pandas.pydata.org/pandas-docs/stable/reference/api/p...

[makapuf]

Why not have clearer file, filename or data keyword arguments ? Or just file and call open or stringio if you have the file name or data ? Plenty of more explicit solutions.

[joshvm]

Lots of public APIs support this behaviour, it's convenient for users. For example numpy.fromfile will accept a file object or a string.