If a company tries Python 3 and discovers basic things like CSV produce utter gibberish, they would do well to opt out. And they do--in droves.
My data is not misencoded, you see. It's just misunderstood.
So I won't be able to use NumPy with either of my two native languages. That sounds like a bit of a shortcoming for the majority of the world.
It could be argued that the csv module's behaviour is reasonable, and NumPy's isn't. (I'm not 100% sure about all the details of this issue) Hopefully, NumPy will change it's behaviour to match Python 3, but if not you could still use the NumPy CSV routines like `loadtxt` or `genfromtxt` [0]. So then this becomes a documentation change to add some warnings to both modules.
> they would do well to opt out. And they do--in droves.
This is simply not true. They would do well to handle strings properly and so avoid bugs in future - something Python 3 actively encourages, and Python 2 obscures. And while I can't speak for every company, our metrics show that our Python 3 code has far less customer issues than Python 2, Perl, or Ruby. Now that's business value. (Edit: I mean it's hard to make the comparison - the Perl code is e.g. older - but we're writing code now, and when the interns add new stuff to the Python 3 codebase, it breaks less. All of them are still actively developed, and the Ruby one is about as old as the Python 3 one).
[0] https://docs.scipy.org/doc/numpy/reference/generated/numpy.l...
Text encoding issues are absolute garbage in Python 3.x
I fucking hate the way that csv module works with text encodings.
As soon as I can figure out a reliable way to take latin-1 and save it as UTF-8 without breaking everything, I will try to shoehorn in a PR.
Right now, it's fucking awful. My ETL pipeline hates it, I hate it, my boss hates it, and my internal constituents hate it. Because it sucks.
A file I can read in one encoding and write as another should be readable with the encoding I wrote it in. That is not currently the case with the latest version of Python.
And it makes me hate the world.
with open('some latin-1 file', 'rb) as f:
text = f.read().decode('latin-1')
with open('some utf8 file', 'wb') as f:
f.write(text.encode('utf-8'))
If you use bytes as a string you are Doing It Wrong.
If you use bytes as a string you are Doing It Wrong.
I do that operation on a file I get from an API. I know for a fact that the encoding I'm receiving is latin-1.
I run exactly that operation on the file that you wrote out in code.
When I try to read that file back in as UTF-8, I get encoding errors. That does not make for "super good." That makes me want to scream.
I do not have this problem when I use Python 2.7.x
To be perfectly clear: bytes (b'') is not a string. Again: bytes is NOT a string. It is an array of octets, aka bytes, aka unsigned 8 bit integers. NOT characters. NOT a string.
If you are dealing with bytes that are encoded representations of a string, then you have to know what encoding they use to decode them and treat them as strings.
in_file = open("in.csv", 'r', encoding='latin-1')
in_csv = csv.reader(in_file)
out_file = open("out.csv", 'w', encoding='utf-8')
out_csv = csv.writer(out_file)
out_csv.writerows(row for row in in_csv)The resulting file is not readable, and it makes me want to kick puppies and punch kittens.
I don't see how silently printing a binary literal, if that is indeed what it does, is reasonable. Simply put, b"foo" is not meaningful CSV.
What it should do is 1) raise an exception by default, informing the user that they need to be supplying strings and not bytes, and 2) provide an explicit switch to treat binary data as pass-thru, which would be useful in scenarios where you're just reading a file and dumping it elsewhere, and don't want to spend time decoding and then encoding everything.
+ if (PyBytes_Check(field)) {
+ append_ok = FALSE;
+ Py_DECREF(field);
+ PyErr_SetString(PyExc_TypeError, "Field is bytes");
+ }
else {
I don't think this is the right solution. It seems weird to have a special case because people aren't watching what they're putting in. Garbage in, garbage out, consenting adults and all that.
But "practicality beats purity".
And "errors should never pass silently"!
It's the same kind of thing that leads to safety warning stickers put on products. You may read it and think that it's something so obvious that consenting adults should know better. But then you look at the statistics about how many people did not, and realize that, yeah, a sticker along the lines of "don't stick your finger into a food processor" is actually a good idea. Especially given how cheap it is, and how expensive reattaching fingers is...
Basically, products should be designed around known human weaknesses, and that includes entrenched modes of thinking by past products. It doesn't mean that new products should accommodate those entrenched modes, especially when they lead to other problems. But they should try to detect them, and issue clear and explicit warnings, to guide the person to the proper way of doing things.
In fact, the reason I chose Python was because I was able to dive so quickly into real problems like this with no problems whatsoever.
This is a minor issue for someone porting from 2 to 3, it is not a problem with 3