通过 REST API 获取数据以及如何将其存储在 mysql 数据库中？

Question

I just got the data through REST API and wanted to save it in mysql database. As I'm a beginner, just looking a way to save the data into my sql database. Could you guys please suggest me some tutorial/library/example. That would be great help. Thanks. And if I'm against the stackoverflow terms and condition, I'm really sorry that. But I need really help on this topic.

**from entsoe import EntsoePandasClient
import pandas as pd

client = EntsoePandasClient(api_key='api-key')

start = pd.Timestamp('20171201', tz='Europe/Brussels')
end = pd.Timestamp('20180101', tz='Europe/Brussels')
country_code = 'BE'  # Belgium

# methods that return Pandas Series
client.query_day_ahead_prices(country_code, start=start,end=end)
client.query_load(country_code, start=start,end=end)
client.query_load_forecast(country_code, start=start,end=end)
client.query_generation_forecast(country_code, start=start,end=end)

# methods that return Pandas DataFrames
client.query_wind_and_solar_forecast(country_code, start=start,end=end, psr_type=None)
client.query_generation(country_code, start=start,end=end, psr_type=None)
client.query_installed_generation_capacity(country_code, start=start,end=end, psr_type=None)
client.query_crossborder_flows('DE', 'DK', start=start,end=end)
client.query_imbalance_prices(country_code, start=start,end=end, psr_type=None)
client.query_unavailability_of_generation_units(country_code, start=start,end=end, docstatus=None)
#client.query_withdrawn_unavailability_of_generation_units('DE', start=start,end=end)

ts = client.query_day_ahead_prices(country_code, start=start, end=end)
print(ts)**

Answer 1

Using to_sql function provided by pandas all u need is to pass a connection object created with the SQLAlchemy library :

from sqlalchemy import create_engine
engine = create_engine("mysql+pymysql://root:pass@localhost/mydb")

df.to_sql('table_name_for_df', con=engine, if_exists='append', flavor='mysql')
# check if the data has been sent
engine.execute("SELECT * FROM table_name_for_df").fetchall()