根据另一个字典列表更新字典值

Question

I have a list of dictionaries called x in the form of

x = [{id:3, name:’abc’, order:’’} , {id:7, name:’cde’, order:’’},  {id:10, name:’zz’, order:’’}  ] 

I have a second list of dictionaries y in the form of

y = [{id:3, order:4}, {id:10, order:6} ]

What I want to do is update the 'order' values in the first dictionary (x) based on the order value for the matching id in the second dictionary (y)

So in the example above x would look like the following after doing so:

 x = [{id:3, name:’abc’, order:4} , {id:7, name:’cde’, order:’’},  {id:10, name:’zz’, order:6} ]

I keep running into errors. Any help would be appreciated. I'm on python 3.8

Answer 1

Reconstruct list of dictionaries using comprehension

# create a map id => order
map_order = {dict_y["id"]: dict_y["order"] for dict_y in y}

# reconstruct x using a dict comprehension whereby order is the y value with default ""
x_update = [{"id": dict_x["id"], 
             "name": dict_x["name"], 
             "order": map_order.get(dict_x["id"], "")}
            for dict_x in x]

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Update values without creating a new x list

It might be more efficient to update the values in x without reconstructing everything. Details likely depend on the size. For small size, go for the comprehension for the sake of style.

# create a map id => order
map_order = {dict_y["id"]: dict_y["order"] for dict_y in y}

for dict_x in x:
    if dict_x["id"] in map_order:
        dict_x["order"] = map_order[dict_x["id"]]

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Pandas-based approach

Also, since what you are describing is essentially an outer join, you could also use Pandas, which might be a more appropriate data structure when considering the big picture. Note that this assumes that "order" in x never contains useful information (hence the drop ).

import pandas as pd
pd.merge(pd.DataFrame(x).drop("order", axis=1), 
         pd.DataFrame(y), 
         how="outer"
        ).fillna("").to_dict("records"))

---

Pandas with update

... in case the order in x do contain useful information, which merely need to be updated, but which are supposed to be unchanged, in case the id is not present in y :

df = pd.DataFrame(x).set_index("id")
df.update(pd.DataFrame(y).set_index("id"))
df.reset_index().to_dict("records")