How to update records in MySQL using SqlAlchemy python

Question

so Im attempting to updated records in database by id's.

• The problem is it overwrites all rows ```id and Cost`` with the last row of the list
• I dont get any errors, but it should match the id's then replace only Cost

database:

table =

id             Cost
000074800795   157.05974458228403
000074801136   80.637745302714
000074801299    7
000074800300   13
000074800955   10

my code:

df = pd.DataFrame({ "id": [000074800795 , 000074801136, 000074801299,000074800300, 000074800955] ,
                    "Cost" : [157.05974458228403 ,80.637745302714, 7, 13, 10] }) 

# replacing Null
df = df.where((pd.notnull(df)), None)

# reset index for For loop
df = df.reset_index()

df.id = df.id.astype(str)
#df.Cost = df.Cost.astype(str)

df.dtypes
out[101]: 
index  int64
id    object
Cost  object
dtype: object

values_list = []

for i in range(len(df)):
    values_list.append({ "id": df["id"][i] , 
                         "Cost": df["Cost"][i] ,
                       })

print(values_list[0:2])
[{'id': '000074800795', 'Cost': 157.05974458228403}, {'id': '000074801136', 'Cost': 80.637745302714}]

Loading at db.

• The problem is it overwrite ```id and Cost`` with the last row of the list

• I dont get any errors, but it should match the id's then replace only Cost

engine = db.create_engine("my connection")

connection = engine.connect()
metadata = db.MetaData()

# Creating Table
data = db.Table('table', metadata, 
              db.Column('id', db.String(100), nullable=True),    
              db.Column('Cost', db.String(100), nullable=True),  
              extend_existing=True 
              )

metadata.create_all(engine)

query = db.update(data)
ResultProxy = connection.execute(query, values_list)

engine.dispose()

Output:

table =

id             Cost
000074800955   10
000074800955   10
000074800955   10
000074800955   10
000074800955   10

Answer 1

Are you doing import sqlalchemy as db? It seems you think the dictionary can work as a primary key update dictionary, but I don't think that's how it works. One standard way of doing it is in the docs, and looks like this:

table.update().where(table.c.id==7).values(name='foo')

To do it this way, you need to filter your table down to one row, then run update on that row using the data in your dataframe. Otherwise, without a query, it seems db.update will update everything in your table.

Try something like this:

import pandas as pd
import sqlalchemy as db

metadata = db.MetaData()

table = db.Table('table', metadata,
                db.Column('id', db.String(100), nullable=True),
                db.Column('Cost', db.String(100), nullable=True),
                extend_existing=True
                )

df = pd.DataFrame({
    'id': ['000074800795', '000074801136', '000074801299', '000074800300', '000074800955'],
    'Cost': ['157.05974458228403', '80.637745302714', '7', '13', '10']
})

for index, row in df.iterrows():
    id_value = row['id']
    cost_value = row['Cost']
    table.update().where(table.c.id == id_value).values(Cost=cost_value)

There are certainly changes we could make to the style here, but hopefully this directs you in the right direction.