- #PYTHON MERGE DICTIONARIES WITH OVERLAPPING KEYS HOW TO#
- #PYTHON MERGE DICTIONARIES WITH OVERLAPPING KEYS UPDATE#
The item in result1 is the “natural” iteration order, and that corresponds to rightmost priority in the nary operation. > a = ub.SetDict(ĭepending on the order in which you iterate through data, “reduced” (better term?) calls to symmetric difference will result in a different order.
#PYTHON MERGE DICTIONARIES WITH OVERLAPPING KEYS HOW TO#
implement merge callables so the user can specify how to resolve A heavier extension would be needed for that. Item-wise operations are in general not hashable and therefore not
The SetDict class only defines key-wise set operations. The rights are lists/sets, whereas difference / intersection does. Unpaired union might have been a better name for this, but takeĪlso, union / symmetric_difference does not make sense if arguments on I'm don't have a greatĪrgument for it, but it seemed easier to implement this way and itĭoes seem closer to a union than it is to a difference. symmetric_difference is somewhat strange. it is basically just an aliasįor dict.update, so the new (rightmost) keys clobber the old.ģ. Other dictionary (or set or list of keys), whereasĢ. To find values in the first (main) dictionary that are also in some intersection / difference is for removing keys - i.e. Symmetric_difference and left-most values take priority in intersectionġ. The reason righmost values take priority in union / Takes the itemsįrom all dictionaries where the key appears an odd number of times. * symmetric_difference (or the ``^`` operator). Takes only items from the firstĭictionary that do not share keys with following dictionaries. Takes the items from theįirst dictionary that share keys with the following dictionaries
#PYTHON MERGE DICTIONARIES WITH OVERLAPPING KEYS UPDATE#
This is nearly identical to the update operation. * union (or the ``|`` operator) combines multiple dicttionaries into Or via a custom ``merge`` callable similar to _. Right-most priority (default for ``union`` and ``symmetric_difference``), With left-most priority (default for ``intersection`` and ``difference``), Like performing the operation on sets of keys. I spent a lot of time writing the docs, so I’ll just paste that description: """Ī dictionary subclass where all set operations are defined.Īll of the set operations are defined in a key-wise fashion, that is it is I have a baseline implementation in my ubelt library call SetDict - ubelt.util_dict module - UBelt 1.3.2 documentation I have a strong opinion that dictionaries in Python should have key-based set operations. This post is about my thoughts on extending Python’s dictionary. Literal syntax is a bit cleaner, but there are situations where dict() is useful.In another thread ( Scientific Utilities - Contributor & Development Discussion - Scientific Python) I was encouraged to submit some of my ideas to the Python discussion forum. This is essential for dictionary keys where hashes are used to store and look up values: if the hash changed each time we hashed the key, we'd never find anything! Creatingĭictionaries can be defined using both literal or constructor syntax. Reproducible means that hashing the same input will always produce the same output. This means list or dict objects cannot be used for dictionary keys, however a tuple is fine.Ī hash is a reproducible, compact, representation of an original value. In contrast keys must be hashable and immutable - the object hash must not change once calculated.
That includes mutable types including list and even dict - meaning you can nest dictionaries inside on another. This usually only has consequences for iterating (see later).Īnything which can be stored in a Python variable can be stored in a dictionary value.
Unlike a language dictionary however, keys in Python dictionaries are not alphabetically sorted.įrom Python 3.6 onwards dictionaries are ordered in that elements are stored and retrieved in the order in which they are added. This is analogous with a real dictionary where you look up definitions (data) using a given key - the word. Dictionaries are key-value stores, meaning they store, and allow retrieval of data (or values) through a unique key.
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