Pythonic way to flatten a dictionary into a list using list comprehension

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I have the following function:

def create_list_from_dict1(mydict):
    output = []
    for k, v in openint_dict.items():
        output.append( (k, v['field1'], v['field2'], v['field3']) )

    return output

Essentially, it flattens the dictionary, so that I can perform sorting on one of the fields of the tuple in the returned list.

I don't like the fact that I am having to 'hard code' the field names of the value dictionary ('field1', ..., 'fieldN'), and I want a more pythonic and elegant way of doing this so that this function works for all dictionaries that contain a fixed structure (non-nested) dictionary as its values.

I imagine that I will have to use **kwargs and/or a lambda function, as well as list comprehension. What would be the most pythonic way to write this function?

You can do it like this:

fields = ("field1", "field2", "field3")

output = [[k] + [mydict[k].get(x) for x in fields] for k in mydict]

In that code we iterate dict keys and add them with selected subset of second-level dictionaries values.

Python, Given a list of the dictionaries, the task is to convert it into single Python code to demonstrate Method #2: Using dict comprehension. This is probably the worst part in the code, yet this is pretty much the whole code. Variable names are terrible and the intent is a bit hidden. I understand that unpack returns lists so your list-comprehension generates a list of lists. So this expression is flattening a list of list of tuples and turning it into a dictionary.

Python, Conversion from one data type to other is essential in various facets of programming. Method #1 : Using list comprehension. We can use list comprehension as the one-liner alternative to perform various naive tasks providing list of tuples to dictionary value lists � Python - Convert Flat dictionaries to Nested dictionary� While this works, it's clutter you can do without. This tip show how you can take a list of lists and flatten it in one line using list comprehension. The loop way #The list of lists list_of_lists = [range(4), range(7)] flattened_list = [] #flatten the lis for x in list_of_lists: for y in x: flattened_list.append(y) List comprehension way

If order doesn't matter...

def create_list_from_dict1(mydict):
    output = []
    for k, v in openint_dict.items():
        fields = [value for key, value in v.items()]
        output.append( tuple([k] + fields )

    return output

If order matters you either need to do as you did and call out the fields specifically...or you need to used an OrderedDict for the sub-dicts.

7 Handy Use Cases Of Dictionary Comprehensions In Python, Comprehensions in Python are syntactic constructs that are used to build sequences Flattening, inverting, merging, filtering, and more By invoking the items() method on a dictionary, you can convert it into a list of tuples of� List comprehensions provide a concise way to create lists. It consists of brackets containing an expression followed by a for clause, then zero or more for or if clauses. The expressions can be anything, meaning you can put in all kinds of objects in lists. The result will be a new list resulting from evaluating […]

Python dicts have keys() and values() methods to get a list of the keys and values. If order of the fields is not important:

[(k,) + tuple(v.values()) for k, v in mydict]

If the ordering of the values does matter:

[(k,) + tuple([v[i] for i in sorted(v.keys())]) for k, v in mydict]

Note that the second option would be identical to the first without the call to sorted(). The order depends on how things were added to the subdict, so you should use the second option as much as possible.

Pythonic way to flatten nested dictionarys, dictionary_ = dict( ii for i in [unpack(key, value) for key, value in So this expression is flattening a list of list of tuples and turning it into a dictionary. instead of full list-comprehension to play it nicer with the memory. This only� Dictionary comprehension is a method for transforming one dictionary into another dictionary. During this transformation, items within the original dictionary can be conditionally included in the new dictionary and each item can be transformed as needed. A good list comprehension can make your code more expressive and thus, easier to read.

def create_list_from_dict1(mydict):
    return [tuple([k]+list(v.values())) for k,v in openint_dict.items()]

doesn't use the fields' names and produces the same result.

In Python 3.5, you can just type (because starred expressions are allowed everywhere):

def create_list_from_dict1(mydict):
    return [(k,*v.values()) for k,v in openint_dict.items()]

5. Data Structures — Python 3.8.5 documentation, If no index is specified, a.pop() removes and returns the last item in the list. List comprehensions provide a concise way to create lists. in <module> [x, x**2 for x in range(6)] ^ SyntaxError: invalid syntax >>> # flatten a list using a Another useful data type built into Python is the dictionary (see Mapping Types — dict). List comprehension is an elegant way to define and create lists based on existing lists. List comprehension is generally more compact and faster than normal functions and loops for creating list. However, we should avoid writing very long list comprehensions in one line to ensure that code is user-friendly.

When to Use a List Comprehension in Python – Real Python, Using Conditional Logic; Using Set and Dictionary Comprehensions; Using the There are a few different ways you can create lists in Python. Take this example, which uses a nested list comprehension to flatten a matrix:. List Comprehensions are one of the most amazing features of Python. It is a smart and concise way of creating lists by iterating over an iterable object. Nested List Comprehensions are nothing but a list comprehension within another list comprehension which is quite similar to nested for loops.

20+ examples for flattening lists in Python, In this tutorial, you will learn flattening lists with different shapes & levels in 13 Flatten & remove duplicates; 14 Flatten a dictionary into a list; 15 Using reduce List comprehension is a way to create lists in one line of code. Performing list(d) on a dictionary returns a list of all the keys used in the dictionary, in insertion order (if you want it sorted, just use sorted(d) instead). To check whether a single key is in the dictionary, use the in keyword. Here is a small example using a dictionary:

Chapter 6, In this chapter we will learn how to use each type of comprehension. You will find that the List comprehensions in Python are very handy. They can also be a comprehension. One reason to do that is to flatten multiple lists into one. too can use them. Now we're ready to move on to Python's dictionary comprehensions! Now, let’s see different ways of creating a dictionary of list. Note that the restriction with keys in Python dictionary is only immutable data types can be used as keys, which means we cannot use a dictionary of list as a key.

Comments
  • So you start with a dictionary of dictionaries? Does the order within the tuple matter? Do they need to be consistent between the tuples, even? Are the keys you're extracting values for a subset of the keys in the v dictionaries, or all of them? Could you give an example input and acceptable output? (Sorry for long comment!)
  • @jonrsharpe: Answers given in same order as questions: Yes, Yes, Yes, No - the keys are ticker codes, and the tuples consist of market data
  • Could you edit the question accordingly, and add an example?
  • I would replace the hard coded fields with a call to mydict.keys(). Otherwise, it seems very elegant, and just what I'm looking to do. Will try it out first though ... to make sure it works, before accepting your answer.
  • Take a note that dictionary in python is not ordered, so using mydict.keys you mix your data.
  • @HomunculusReticulli that will give you the keys to the outer dictionary, too, which may not be the same as the inner dictionaries (still no example?)
  • Yes, I thought we talking about inner dictionaries, because fields hardcoded for them.
  • Can you explain this: tuple(v for _, ? I have never come across this syntax before ... it looks like you're invoking a magic method.. what does the underscore mean?
  • @HomunculusReticulli per the answer, _ means "we aren't using this" (the inner dict's key, in this case). It's like ... for k, v in ... but makes it clearer that k is being ignored on purpose.
  • Thanks for the explanation. I think I will go with your answer, as its the most pythonic. However, I may have to sub class the dict class, with my own class which will have a fields attribute to use in the function, instead of calling sorted(val.items()). The tuples are records from a database, so the order of the columns must not be changed.
  • @HomunculusReticulli then are you sure you have the right data structure to begin with?
  • Absolutely, the data is coming from a database.
  • The problem with this is that there's no guarantee that values from each inner dictionary will be in the same order, which the OP commented as a requirement.
  • Not sure, but it seems to work on a 'fixed structure'. I don't know if is garanteed.
  • It isn't guaranteed, that's what I'm telling you.