How to categorize list of dictionaries based on the value of a key in python efficiently?
categorization, list, python
Solution
Your code can be rewritten using `itertools.groupby`
for _, category in itertools.groupby(dictList, key=lambda item:item['type']):
processingMethod(list(category))
Or if processingMethod can process `iterable`,
for _, category in itertools.groupby(dictList, key=lambda item:item['type']):
processingMethod(category)
Problem
I have a list of dictionaries in python which I want to categorized them based on the value of a key which exists in all dictionaries and process each category separately. I don't know what are the values, I just know that there exists a special key. Here's the list: ``` dictList = [ {'name': 'name1', 'type': 'type1', 'id': '14464'}, {'name': 'name2', 'type': 'type1', 'id': '26464'}, {'name': 'name3', 'type': 'type3', 'id': '36464'}, {'name': 'name4', 'type': 'type5', 'id': '43464'}, {'name': 'name5', 'type': 'type2', 'id': '68885'} ] ``` This is the code I currently use: ``` while len(dictList): category = [l for l in dictList if l['type'] == dictList[0]['type']] processingMethod(category) for item in category: dictList.remove(item) ``` This iteration on the above list will give me following result: ``` Iteration 1: category = [ {'name': 'name1', 'type': 'type1', 'id': '14464'}, {'name': 'name2', 'type': 'type1', 'id': '26464'}, ] Iteration 2: category = [ {'name': 'name3', 'type': 'type3', 'id': '36464'} ] Iteration 3: category = [ {'name': 'name4', 'type': 'type5', 'id': '43464'} ] Iteration 4: category = [ {'name': 'name5', 'type': 'type2', 'id': '68885'} ] ``` Each time, I get a category, process it and finally remove processed items to iterate over remaining items, until there is no remaining item. Any idea to make it better?