在插入pandas df的同时从另一个表插入外键

Question

I have trying to update a player table by inserting a pandas Dataframe into MySQL (community edition). The query works for the standard data/information (int and str) that I am inserting, but I am struggling to find the a solution to add a foreign key in a 'team' column whilst referencing a team table (multiple players can play for one team).

team_id is the foreign key in the player table referencing a team table

#connection to database
conn = mysql.connector.connect(host='localhost', user='root', passwd='passed')
cur = conn.cursor() #create cursor

#query statement to insert a list of teams to table
query_list_to_column = "INSERT IGNORE INTO team (team_name) VALUES (%s)"
#execute statements
cur.executemany(query_list_to_column, [(r,) for r in team_list]) #team lists to team table

#SQL statement to insert df into player table
sql_df_insert = """INSERT INTO player (`full_name`, `first_name`, `last_name`,
                                    `name_FIBA_format`, `dob`, `age`, `height`,
                                    `real_gm_profile`, `team_id`, `game_log_url`)
         VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s)"""

final_df = final_df.reindex(['full_name', 'first_name', 'last_name', 'name_FIBA_format',
                             'dob', 'age', 'height', 'real_gm_profile', (SELECT id from team WHERE team_name = 'team'), 'game_log_url'],
                            axis='columns')

cur.executemany(sql_df_insert, final_df.to_numpy().tolist())
conn.commit()

I am not sure if I am putting 2 and 2 together and getting 8 with how I have approached this, but any direction on how I would achieve this would be greatly appreciated.

Answer 1

As you noticed you have to get the last inserted id first.bwfore the second insert

Django has some possibilityies to get it Like https://stackoverflow.com/questions/14832115/get-the-last-inserted-id-in-djang

Another option can be using the select max(id) statement instead of the %s if the where clause doesn't have user input , it still is secure