J-Quants API Clientにサンプルが追加されたので、使ってみる

5つの例が、J-Quantas API クライアントの使用サンプルに追加された。

github.com

これが先日 main にマージされたので、早速使ってみる。スコープを狭めるために、財務情報関連を1つのclassに押し込めることにした。

from datetime import datetime
from dateutil import tz
import jquantsapi
import pandas as pd
import os
import numpy as np


class Statements:
    def __init__(self, storage_dir_path: str, jqapi: jquantsapi.Client):
        self.storage_dir_path = storage_dir_path
        self._jqapi = jqapi

    def fetch_from_api_with_cache(self):
        '''
        Original: J-Quants/jquants-api-client-python
        https://github.com/J-Quants/jquants-api-client-python/blob/da16a23d85c80a0106673f0a0deaec3437016418/examples/20220825-003-dividend.ipynb
    
        Arguments
        -------------------
        storage_dir_path: str
            DataFrameをpickle化したものを保存先の親ディレクトリへのパス
        '''
        # 過去3ヶ月に発表された財務情報を取得します
        now = pd.Timestamp.now(tz="Asia/Tokyo")
        start_dt = now - pd.Timedelta(90, unit="D")
        end_dt = now
        if end_dt.hour < 1:
            # データ更新時間前の場合は日付を1日ずらします。
            end_dt -= pd.Timedelta(1, unit="D")
        statements_file = f"{self.storage_dir_path}/statements.pkl"
        if not os.path.isfile(statements_file):
            cache_dir = f"{self.storage_dir_path}/raw_statements"
            os.makedirs(cache_dir, exist_ok=True)
            df_s = self._jqapi.get_statements_range(
                start_dt=start_dt, end_dt=end_dt, cache_dir=cache_dir
            )
            df_s.to_pickle(self.statements_file)
            print(f"save file: {self.statements_file}")
        else:
            df_s = self.load_df(statements_file)
        df = self._format_dt(df_s)
        return df
    
    def _format_dt(self, df_s: pd.DataFrame):
        '''
        Original: J-Quants/jquants-api-client-python
        https://github.com/J-Quants/jquants-api-client-python/blob/da16a23d85c80a0106673f0a0deaec3437016418/examples/20220825-003-dividend.ipynb
        '''
        # float64にするために"-"をnp.nanに置き換えます
        df_s.replace({"－": np.nan}, inplace=True)
        df_s["ResultDividendPerShareFiscalYearEnd"] = df_s["ResultDividendPerShareFiscalYearEnd"].astype(np.float64)
        df_s["EarningsPerShare"] = df_s["EarningsPerShare"].astype(np.float64)
        df_s["ForecastDividendPerShareAnnual"] = df_s["ForecastDividendPerShareAnnual"].astype(np.float64)
        df_s["ForecastEarningsPerShare"] = df_s["ForecastEarningsPerShare"].astype(np.float64)
        # 日付型に変換します
        df_s.loc[:, "DisclosedDate"] = pd.to_datetime(
            df_s["DisclosedDate"], format="%Y-%m-%d"
        )
        df_s.loc[:, "CurrentPeriodEndDate"] = pd.to_datetime(
            df_s["CurrentPeriodEndDate"], format="%Y-%m-%d"
        )
        df_s.loc[:, "CurrentFiscalYearStartDate"] = pd.to_datetime(
            df_s["CurrentFiscalYearStartDate"], format="%Y-%m-%d"
        )
        df_s.loc[:, "CurrentFiscalYearEndDate"] = pd.to_datetime(
            df_s["CurrentFiscalYearEndDate"], format="%Y-%m-%d"
        )
        df_s.sort_values("DisclosedUnixTime", inplace=True)
        return df_s
    
    def load_df(self, statements_file: str):
        '''
        Original: J-Quants/jquants-api-client-python
        https://github.com/J-Quants/jquants-api-client-python/blob/da16a23d85c80a0106673f0a0deaec3437016418/examples/20220825-003-dividend.ipynb
        '''
        print(f"file exists: {statements_file}, loading")
        df_s = pd.read_pickle(statements_file)
        return df_s


my_refresh_token: str = '(token)'
cli = jquantsapi.Client(refresh_token=my_refresh_token)
parent_path = '/content/drive/MyDrive/drive_ws/marketdata'

statements = Statements(parent_path, cli)
df = statements.fetch_from_api_with_cache()

df[df.LocalCode == 79740]

これを実行すると、下記のような表を得られる。

index	DisclosureNumber	DisclosedDate	ApplyingOfSpecificAccountingOfTheQuarterlyFinancialStatements	AverageNumberOfShares	BookValuePerShare	ChangesBasedOnRevisionsOfAccountingStandard	ChangesInAccountingEstimates	ChangesOtherThanOnesBasedOnRevisionsOfAccountingStandard	CurrentFiscalYearEndDate	CurrentFiscalYearStartDate	CurrentPeriodEndDate	DisclosedTime	DisclosedUnixTime	EarningsPerShare	Equity	EquityToAssetRatio	ForecastDividendPerShare1stQuarter	ForecastDividendPerShare2ndQuarter	ForecastDividendPerShare3rdQuarter	ForecastDividendPerShareAnnual
92	20220726504912	2022-08-03 00:00:00	NaN	116817xxx.0	NaN	false	false	false	2023-03-31 00:00:00	2022-04-01 00:00:00	2022-06-30 00:00:00	15:30:00	1xxx540600.0	xxxx.55	203xxxx000000.0	0.xxx	NaN	NaN	NaN	NaN

これで次は過去5年間の配当性向がどのようになっているかを見られるようにしたい。