Python: get a dict from a list based on something inside the dict

my_item = next((item for item in my_list if item['id'] == my_unique_id), None)

This iterates through the list until it finds the first item matching my_unique_id, then stops. It doesn't store any intermediate lists in memory (by using a generator expression) or require an explicit loop. It sets my_item to None of no object is found. It's approximately the same as

for item in my_list:
    if item['id'] == my_unique_id:
        my_item = item
        break
else:
    my_item = None

else clauses on for loops are used when the loop is not ended by a break statement.

If you have to do this multiple times, you should recreate a dictionnary indexed by id with your list :

keys = [item['id'] for item in initial_list]
new_dict = dict(zip(keys, initial_list)) 

>>>{
    'yet another id': {'id': 'yet another id', 'value': 901.20000000000005, 'title': 'last title'}, 
    'an id': {'id': 'an id', 'value': 123.40000000000001, 'title': 'some value'}, 
    'another id': {'id': 'another id', 'value': 567.79999999999995, 'title': 'another title'}
}

or in a one-liner way as suggested by agf :

new_dict = dict((item['id'], item) for item in initial_list)

Worked only with iter() for me:

my_item = next(iter(item for item in my_list if item['id'] == my_unique_id), None)

I used this, since my colleagues are probably more able to understand what's going on when I do this compared to some other solutions provided here:

[item for item in item_list if item['id'] == my_unique_id][0]

And since it's used in a test, I think the extra memory usage isn't too big of a deal (but please correct me if I am wrong). There's only 8 items in the list in my case.

You can create a simple function for this purpose:

lVals = [{'title': 'some value', 'value': 123.4,'id': 'an id'},
 {'title': 'another title', 'value': 567.8,'id': 'another id'},
 {'title': 'last title', 'value': 901.2, 'id': 'yet another id'}]

def get_by_id(vals, expId): return next(x for x in vals if x['id'] == expId)

get_by_id(lVals, 'an id')
>>> {'value': 123.4, 'title': 'some value', 'id': 'an id'}