How to combine the result of one HTTP call to update several cells?-CodePudding

I have a CSV file that has a column id. I create a new one (m0), which contents come from an HTTP call with id as a parameter:

d['m0'] = d['id'].apply(lambda id: pd.read_json(f"http://localhost:3000/{id}").get('H', {}).get('M0', "X"))

I need to also create columns m1 and m2 in a similar way. I could do

d['m0'] = d['id'].apply(lambda id: pd.read_json(f"http://localhost:3000/{id}").get('H', {}).get('M0', "X"))
d['m1'] = d['id'].apply(lambda id: pd.read_json(f"http://localhost:3000/{id}").get('H', {}).get('M1', "X"))
d['m2'] = d['id'].apply(lambda id: pd.read_json(f"http://localhost:3000/{id}").get('H', {}).get('M2', "X"))

but the HTTP call is very expensive and slow (I have quite a lot of data).

Is there a way to combine all three calls in one?, knowing that this structure of the JSON I get, for a given id, is

"H": {
  "M0": "sjkdhfjkshd",
  "M1": "isudfyfsdif",
  "M2": "azednbzaebe"
}

CodePudding user response：

You can write a common function, make an HTTP call, extract all required fields and return result as a pandas Series:

def get_all_fields(row):
  h_json = pd.read_json(f"http://localhost:3000/{row['id']}").get('H', {})
  return pd.Series([
      h_json.get('M0', "X"),
      h_json.get('M1', "X"),
      h_json.get('M2', "X"),
  ])

d[['m0', 'm1', 'm2']] = d.apply(lambda row: get_all_fields(row), axis=1)