ORCA / web API / python / 情報の取り出し

目的
- ORCA web API経由で情報の取り出し
環境
- python (jupyter Notebook 6.3.0), macbook air (M1)
参照サイト
- ORCA Project：日医標準レセプトソフト API 患者基本情報
- ここの解説は私には難しすぎて理解できず　サンプルソースはRuby, C#でpythonなし
- 代わりに下記を参照 (楽天トラベルからホテルリストを作成する）
- Pythonで楽天トラベルAPIを使用した宿泊先リスト作成方法をわかりやすく解説！ - YouTube
- 上記のほかに、pd.json_normalizeの知識が必要だった
- 渉猟した限りORCA+APIの情報はあまり見つからず
以下にsource

# libraryのimport

import requests
from requests.auth import HTTPBasicAuth
import pandas as pd

# # BASIC認証　webAPIにrequest

res = requests.get('http://ip-address:8000/api01rv2/patientgetv2?id=36817&format=json', auth=HTTPBasicAuth('id', 'pw'))

res.json()

{'patientinfores': {'Information_Date': '2021-10-11',
  'Information_Time': '16:58:35',
  'Api_Result': '00',
  'Api_Result_Message': '処理終了',
  'Reskey': 'Patient Info',
  'Patient_Information': {'Patient_ID': '0036817',
   'WholeName': '日医\u3000太郎',
   'WholeName_inKana': 'ニチイ\u3000タロウ',
   'BirthDate': '1948-03-27',
   'Sex': '1',
   'HouseHolder_WholeName': 'ニチイ',
   'Home_Address_Information': {'Address_ZipCode': '9493333',
    'WholeAddress1': '上越市〇〇区××',
    'WholeAddress2': '２８３−２',
    'PhoneNumber1': '025-555-9999',
    'PhoneNumber2': '090-4444-1111'},
   'Comment1': 'Ｈ２７．０１．１３来院',
   'TestPatient_Flag': '0',
   'Reduction_Reason': '00',
   'Reduction_Reason_Name': '該当なし',
   'Discount': '00',
   'Discount_Name': '該当なし',
   'Condition1': '00',
   'Condition1_Name': '該当なし',
   'Condition2': '00',
   'Condition2_Name': '該当なし',
   'Condition3': '00',
   'Condition3_Name': '該当なし',
   'Ic_Code': '01',
   'Ic_Code_Name': '現金',
   'Community_Cid_Agree': 'False',
   'FirstVisit_Date': '2015-03-10',
   'LastVisit_Date': '2021-10-05',
   'HealthInsurance_Information': [{'Insurance_Combination_Number': '0003',
     'InsuranceCombination_Rate_Admission': '0.20',
     'InsuranceCombination_Rate_Outpatient': '0.20',
     'Insurance_Nondisplay': 'N',
     'InsuranceProvider_Class': '060',
     'InsuranceProvider_Number': '150037',
     'InsuranceProvider_WholeName': '国保',
     'HealthInsuredPerson_Symbol': '〇〇',
     'HealthInsuredPerson_Number': '３５００００００',
     'HealthInsuredPerson_Branch_Number': '06',
     'HealthInsuredPerson_Assistance': '2',
     'HealthInsuredPerson_Assistance_Name': '２割',
     'RelationToInsuredPerson': '2',
     'HealthInsuredPerson_WholeName': '日医\u3000太郎',
     'Certificate_StartDate': '2021-08-10',
     'Certificate_ExpiredDate': '2022-07-31',
     'Certificate_GetDate': '2021-08-01',
     'Insurance_CheckDate': '2021-08-10'},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {},
    {}]}}}

result = res.json()

# IDを取り出したい

result['patientinfores']['Patient_Information']['Patient_ID']

'0036817'

patient_info = result['patientinfores']['Patient_Information']

pd.json_normalize(patient_info)

	Patient_ID	WholeName	WholeName_inKana	BirthDate	Sex	HouseHolder_WholeName	Comment1	TestPatient_Flag	Reduction_Reason	Reduction_Reason_Name	...	Ic_Code_Name	Community_Cid_Agree	FirstVisit_Date	LastVisit_Date	HealthInsurance_Information	Home_Address_Information.Address_ZipCode	Home_Address_Information.WholeAddress1	Home_Address_Information.WholeAddress2	Home_Address_Information.PhoneNumber1	Home_Address_Information.PhoneNumber2
0	0036817	日医　太郎	ニチイ　タロウ	1945-01-01	1	日医	Ｈ２７．０１．１３来院	0	00	該当なし	...	現金	False	2015-03-10	2021-10-05	[{'Insurance_Combination_Number': '0003', 'Ins...	9493333	上越市〇〇区××	２８３−２	025-555-9999	090-4444-1111

1 rows × 29 columns

df = pd.json_normalize(patient_info)

df.columns

Index(['Patient_ID', 'WholeName', 'WholeName_inKana', 'BirthDate', 'Sex',
       'HouseHolder_WholeName', 'Comment1', 'TestPatient_Flag',
       'Reduction_Reason', 'Reduction_Reason_Name', 'Discount',
       'Discount_Name', 'Condition1', 'Condition1_Name', 'Condition2',
       'Condition2_Name', 'Condition3', 'Condition3_Name', 'Ic_Code',
       'Ic_Code_Name', 'Community_Cid_Agree', 'FirstVisit_Date',
       'LastVisit_Date', 'HealthInsurance_Information',
       'Home_Address_Information.Address_ZipCode',
       'Home_Address_Information.WholeAddress1',
       'Home_Address_Information.WholeAddress2',
       'Home_Address_Information.PhoneNumber1',
       'Home_Address_Information.PhoneNumber2'],
      dtype='object')

# 必要なcolumnを指定する

df[['Patient_ID', 'WholeName', 'WholeName_inKana', 'BirthDate', 'Sex','Home_Address_Information.Address_ZipCode',
       'Home_Address_Information.WholeAddress1',
       'Home_Address_Information.WholeAddress2']]

	Patient_ID	WholeName	WholeName_inKana	BirthDate	Sex	Home_Address_Information.Address_ZipCode	Home_Address_Information.WholeAddress1	Home_Address_Information.WholeAddress2
0	0036817	日医　太郎	ニチイ　タロウ	1945-01-01	1	9493333	上越市〇〇区××/td>	２８３−２

# .csvで書き出す

df[['Patient_ID', 'WholeName', 'WholeName_inKana', 'BirthDate', 'Sex','Home_Address_Information.Address_ZipCode',
       'Home_Address_Information.WholeAddress1',
       'Home_Address_Information.WholeAddress2']].to_csv('patient-info.csv',index=False)

# patient-info.csvというファイルが書き出された