add github actions

.github/workflows/python-test.yml

@@ -0,0 +1,26 @@
+name: Python Prepro
+
+on: [push]
+
+jobs:
+    build:
+
+        runs-on: ubuntu-latest
+
+        steps:
+            - uses: actions/checkout@v4
+            - name: set up python
+              uses: actions/setup-python@v4
+              with:
+                python-version: '3.12'
+            - name: Install dependencies
+              run: |
+                python -m pip install -U pip
+                pip install -r dev_requirements.txt
+            - name: Test with pytest
+              run: |
+                python -m pytest tests/test_unit_citycode_class.py tests/test_unit_proptransactions_class.py
+            - name: code formatter
+              run: |
+                python -m isort .
+                python -m black *

CHANGELOG.md

@@ -1,5 +1,11 @@
 ## 開発メモ
 
+
+### add-new-feature
+
+- お値段の通貨選択機能の追加を検討中。
+
+
 ### 20231020
 
 - released version_0.1

dev_requirements.txt

@@ -4,4 +4,4 @@ flake8
 mypy
 pytest
 build
-wheel
+wheel

j_realty_api/__init__.py

@@ -1,2 +1 @@
-from . import j_realty_en
-from . import j_realty_jp
+from . import j_realty_en, j_realty_jp

j_realty_api/j_realty_en.py

@@ -1,8 +1,8 @@
 import json
 import math
 from dataclasses import dataclass
-from typing import Union
 from datetime import datetime
+from typing import Union
 
 import numpy as np
 import pandas as pd
@@ -23,9 +23,9 @@
 class CityCode:
 
     """
-    A class that, when given a prefecture name, returns data containing 
-    the names and codes of the municipalities in that prefecture. When a 
-    municipality name is specified, it returns the municipality code. 
+    A class that, when given a prefecture name, returns data containing
+    the names and codes of the municipalities in that prefecture. When a
+    municipality name is specified, it returns the municipality code.
 
     """
 
@@ -48,31 +48,31 @@ def pref_code(self) -> str:
 
     @property
     def city_json(self) -> dict[str]:
-        '''
+        """
         api returns each pref's city_codes json.
         Returns:
             Dict[str]: JSON with {'cityname' : 'citycode'}
-        '''
+        """
         r = requests.get(self.base_path, params={"area": self.pref_code})
         city_json = r.json()
         new_list = list()
-        for d in city_json['data']:
-            d['name'] = d['name'].lower()
+        for d in city_json["data"]:
+            d["name"] = d["name"].lower()
             new_list.append(d)
-        city_json['data'] = new_list
+        city_json["data"] = new_list
         return city_json
 
     def city_code(self, city_name: str) -> str:
-        '''
+        """
         Searches for the city code corresponding to the provided
         city name from the city_json.
-        
+
         Args:
             city_name str: City name for which to find the city code.
         Returns:
             str: city code
 
-        '''
+        """
         for d in self.city_json.get("data", []):
             if d["name"].startswith(city_name.lower()):
                 return d["id"]
@@ -82,28 +82,28 @@ def city_code(self, city_name: str) -> str:
 @dataclass
 class PropTransactions:
 
-    '''
+    """
     A class that retrieves property transaction data based on the specified parameters
     such as prefecture code, city code, and date range from a given API endpoint.
-    '''
-    
+    """
+
     pref_code: str
     city_code: str
     from_dt: int = 20222
     to_dt: int = 20223
     base_url: str = TRADESEARCH_EN_URL
 
     def get_data(self) -> pd.DataFrame:
-        '''
-        Sends a GET request to the API with the specified parameters and retrieves 
+        """
+        Sends a GET request to the API with the specified parameters and retrieves
         property transaction data.
-        
+
         The method constructs a DataFrame from the received JSON data and returns it.
-        
+
         Returns:
             pd.DataFrame: A DataFrame containing the property transaction data.
 
-        '''
+        """
         params = {
             "from": self.from_dt,
             "to": self.to_dt,
@@ -114,49 +114,49 @@ def get_data(self) -> pd.DataFrame:
         if r.status_code == 200:
             try:
                 df = pd.DataFrame(r.json()["data"])
-                df['Period'] = df['Period'].map(self.custom_to_datetime)
+                df["Period"] = df["Period"].map(self.custom_to_datetime)
                 # for col in ['TradePrice']: # 'Area'は文字列のものが入っているので、対応を考えて追加する
                 #     df[col] = df[col].astype(int)
                 return df
             except KeyError:
-                print(f'''KeyError: The received JSON does not contain the expected "data" key.
+                print(
+                    f"""KeyError: The received JSON does not contain the expected "data" key.
                       pref_code: {self.pref_code}, city_code: {self.city_code}, 
                       from_dt: {self.from_dt}, to_dt: {self.to_dt}
-                      ''')
+                      """
+                )
         else:
             raise Exception(f"Status_code: {r.status_code}")
-
 
     def custom_to_datetime(self, p_str):
-        split_str = p_str.split(' ')
+        split_str = p_str.split(" ")
         year = int(split_str[2])
         q = split_str[0]
-        if q == '1st':
+        if q == "1st":
             qt = self.dt_to_qt(year, 2)
             return qt
-        elif q == '2nd':
+        elif q == "2nd":
             qt = self.dt_to_qt(year, 5)
             return qt
-        elif q == '3rd':
+        elif q == "3rd":
             qt = self.dt_to_qt(year, 8)
             return qt
-        elif q == '4th':
+        elif q == "4th":
             qt = self.dt_to_qt(year, 11)
             return qt
         else:
-            raise ValueError(f'invalid quater: {p_str}')
-
+            raise ValueError(f"invalid quater: {p_str}")
 
     def dt_to_qt(self, year, month):
         dt = datetime(year, month, 1)
         ts = pd.Timestamp(dt)
-        qt = ts.to_period('Q')
+        qt = ts.to_period("Q")
         return qt
 
 
 if __name__ == "__main__":
     k = CityCode("Kyoto")
     pref_code = k.pref_code
-    city_code = k.city_code('Kyoto')
+    city_code = k.city_code("Kyoto")
     print(pref_code)
-    print(city_code)
+    print(city_code)

j_realty_api/j_realty_jp.py

@@ -44,16 +44,16 @@ def pref_code(self) -> str:
 
     @property
     def city_json(self) -> dict[str]:
-        '''
+        """
         指定した都道府県の市町村コードのJSON
-        '''
+        """
         r = requests.get(self.base_path, params={"area": self.pref_code})
         return r.json()
 
     def city_code(self, city_name: str) -> str:
-        '''
+        """
         city_nameに対応したcitycodeが返される
-        '''
+        """
         for d in self.city_json.get("data", []):
             if d["name"].startswith(city_name):
                 return d["id"]
@@ -86,13 +86,13 @@ class PropTransactions:
     base_url: str = TRADESEARCH_URL
 
     def get_data(self) -> pd.DataFrame:
-        '''
+        """
         指定された都道府県コード、市町村コード、期間の
         不動産取引価格情報を取得する。
         データはJSONをDataFrameにして返す。
         Returns:
             pd.DataFrame
-        '''
+        """
         params = {
             "from": self.from_dt,
             "to": self.to_dt,

requirements.txt

@@ -1,2 +1,2 @@
 pandas
-requests
+requests

samples/test.py

@@ -1,4 +1,4 @@
 from j_realty_api import j_realty_en
 
-d = j_realty_en.CityCode('Kyoto')
-print(d.pref_code)
+d = j_realty_en.CityCode("Kyoto")
+print(d.pref_code)

setup.py

@@ -1,13 +1,9 @@
-from setuptools import setup, find_packages
-
+from setuptools import find_packages, setup
 
 setup(
-    name='j_realty_api',
+    name="j_realty_api",
     version=0.1,
     packages=find_packages(),
-    install_requires=[
-        'pandas',
-        'requests'
-    ],
-    include_package_data=True
-)
+    install_requires=["pandas", "requests"],
+    include_package_data=True,
+)

tests/api_test.py

@@ -2,19 +2,14 @@
 
 TRADESEARCH_EN_URL = "https://www.land.mlit.go.jp/webland_english/api/TradeListSearch"
 
-pref_code: str = '26'
-city_code: str = '26100'
+pref_code: str = "26"
+city_code: str = "26100"
 from_dt: int = 20222
 to_dt: int = 20223
 base_url: str = TRADESEARCH_EN_URL
 
 
-params = {
-    'from': from_dt,
-    'to': to_dt,
-    'area': pref_code,
-    'city': city_code
-}
+params = {"from": from_dt, "to": to_dt, "area": pref_code, "city": city_code}
 r = requests.get(base_url, params)
 if r.status_code:
-    print(r.json())
+    print(r.json())

tests/test.py

@@ -1,13 +1,13 @@
 from j_realty_api import j_realty_en as je
 
-cc = je.CityCode('kyoto')
+cc = je.CityCode("kyoto")
 pref_code = cc.pref_code
-city_code = cc.city_code('kyoto')
+city_code = cc.city_code("kyoto")
 pt = je.PropTransactions(
     pref_code,
     city_code,
 )
 
 df = pt.get_data()
-df.to_csv('./tests/data/test.csv')
+df.to_csv("./tests/data/test.csv")
 print(df.info())