It's mad that it ever wasn't this way. Mapping-with-ordered-keys is such a useful and pervasive data structure (all database query result rows, for one) that an ordered dictionary should be a fundamental part of a language.
It has been so much more pleasant to write python since ordering was maintained by default.
Here's one real-life use case of that: Avro records. One of the formats Avro uses is a text format that's basically ordered JSON. One company I worked for years ago used Avro as its wire protocol, and some Avro data was stored as JSON files on disk. Of course, Python's JSON implementation by default loads/unloads JSON to/from a dict. So just calling json.load() and json.dump() means I can't just load an Avro record from disk, change some data, and save it (which is something that came up when I was writing an upgrade script at a company I was working at years ago).
Thankfully, I had an out: the JSON library lets you override what container you load JSON into with object_pairs_hook, so I could just snarf it into an OrderedDict. But if I ever have to do this again after 3.7 comes out, I'm glad I won't have to worry about making sure I have the right container class. It makes my code simpler, and I won't have to leave a comment explaining why the code will break unless I specify an OrderedDict.
I hate to think of all the developer hours wasted because JSON doesn't maintain key ordering.
What? No. SQL does not return results in any consistent ordering unless specifically instructed to.
> Not the result set, the rows of the result set.
Each row is a mapping with ordered keys.
A result set has rows, which are not in a deterministic order unless an "order by" is provided. Each row has columns. The columns are in order, obviously.
I said that database query result rows are made up of ordered dictionaries. I didn't mention ordering of the result set.
Happy to keep repeating this as many times as necessary.
That said, you disagreed with my question then went on to show my question was on point.
The “rows themself” being an ordered map means you are referring to the columns, the order being set by the SELECT clause or table definition order (in case of wildcard).
That said, I personally feel iterating over table columns in that way to be a “bad code smell”. Not saying it’s bad in all cases, but generally it’s an anti-pattern to me.
"An array which represents an n-ary relation R has the following properties:
1. Each row represents an n-tuple of R.
2. The ordering of rows is immaterial.
3. All rows are distinct.
4. The ordering of columns is significant -- it corresponds to the ordering S1, S2, ..., Sn of the domains on which R is defined (see, however, remarks below on domain-ordered and domain-unordered relations).
5. The significance of each column is partially conveyed by labeling it with the name of the corresponding domain."
-- A relational model of data for large shared data banks[1]
[1]: https://cs.uwaterloo.ca/~david/cs848s14/codd-relational.pdf
I didn't mention the collection of rows, I mentioned the rows themselves.
> The “rows themself” being an ordered map means you are referring to the columns
No, it means I'm referring to the rows themselves.
The rows themselves are each ordered mappings.
Hope this helps to clarify things. Happy to keep repeating this as many times as necessary.
but hey, its Guido, I still can't fathom that he moved reduce into functools.
https://mail.python.org/pipermail/python-dev/2016-September/...
OrderedDict is fundamentally different because it is designed to allow inserting/removing keys in the middle of the ordering in O(1) time. It does not use the new dict under the hood, or vice-versa.